# document

id: 88a12ada64a10282598ce2c2ec01aafe
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 21199
content:
"[...] to GWP100 being used throughout the 21st century, in very high \r overshoot scenarios that reach the long-term temperature goal \r of 1.5degC or 2degC only in the 22nd century. For such scenarios, the \r most cost-effective weighting of SLCF emissions is generally less \r than GWP100 in the next few decades, but two to three times \r higher than GWP100 once temperature has peaked. These findings \r strengthen the conclusions by Fuglestvedt et al. (2018) and Tanaka \r and O'Neill (2018) that the choice of GHG metric is particularly \r important for the rate of temperature decline once net zero GHG \r emissions have been reached."


id: c48b80e1f8d4f7494087c6e4ee14e856
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 31887
content:
"The United Nations Environment Programme Society of \r Environmental Toxicology and Chemistry (UNEP-SETAC) task force \r on lifecycle assessment (LCA) recommended that at least two, but \r potentially even three, metrics with divergent weightings for SLCFs \r (GWP100 and GTP100 and potentially also GWP20) be used to better \r understand the extent to which GHG metric choices may implicitly \r or inadvertently affect reported carbon footprints (Cherubini \r et al. 2016; Levasseur et al. 2016; Jolliet et al. 2018). This matches \r recommendations by other researchers for the use of multiple \r metrics (Grewe and Dahlmann 2015; Ocko et  al. 2017; Balcombe \r et al. 2018; Cooper et al. 2020; Allen et al. 2021) especially where \r there is no unambiguous policy goal for a sectoral or entity-level \r LCA. While there is a strong agreement in the literature that using \r multiple metrics provides a more nuanced understanding of the \r climate effects of emissions, there is no strong consensus specific \r [...]"


id: 2866981735a1ca1010e5a986c91967ac
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 4314
content:
"[...] pairs or sets of metrics to use (e.g., GWP20 and GWP100, or GWP100 \r and GTP100). GWP* has only had limited use in LCA so far, mainly \r to understand the impact of sustained changes in CH4 emissions \r resulting from system changes or lifetime dietary choices, consistent \r with its focus on the effect of sustained emission changes (Clark et al. \r 2020; Barnsley et al. 2021)."


id: 4f71cf5b339ad9742d2a2afa59b4cfd1
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 11261
content:
"Various studies evaluated the extent to which cost-effective sectoral \r abatement strategies might change under different climate metrics. \r In some instances (e.g., for transport and fuel choices), the choice of \r metric can change abatement preferences and timing (Edwards and \r Trancik 2014; Edwards et al. 2016; Edwards et al. 2017). Similarly, the \r magnitude of the climate impact from aviation when expressed in \r CO2-equivalents depends strongly on the choice of emission metric \r and time horizon, as SLCF emissions and contrails enhance warming \r significantly over days to decades, in addition to the warming from \r CO2 that occurs over centuries to millennia (Fuglestvedt et al. 2010; \r Azar and Johansson 2012; Deuber et  al. 2013; Lund et  al. 2017; \r Lee et  al. 2021). For the energy sector, Tanaka et  al. (2019) show \r that switching from coal to gas (which has lower CO2 but higher \r CH4 emissions) for energy supply offers consistent climate benefits \r [...]"


id: 9a63e49e40978b62dafbc132d04d82f9
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 24404
content:
"[...] regardless of metric and time horizon unless CH4 leakage rates are \r very high and a short-term metric (GWP20) is selected. Lynch and \r Pierrehumbert (2019) show that the climate impact of cultured meat \r (which they assume to have higher CO2 but lower CH4 emissions than \r cattle meat and a lower GHG footprint based on GWP100) increases \r over time, given the cumulative warming from CO2 emissions. \r Substituting cattle meat with cultured meat would result in lower \r warming for at least the next several decades but could eventually \r result in higher warming than cattle meat, if this substitution is \r sustained over centuries and if the carbon intensity of energy supply \r for the manufacture of cultured meat does not decline."


id: f26aaf47595ec3d68da9385ffd2a655b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 40044
content:
"For some sectors, mitigation strategies and the relative merit of \r specific technologies or practices compared to others (such as \r intensive vs extensive agricultural production and mitigation options, \r or choices to reduce air pollutants with a climate forcing effect) \r have been shown to be relatively robust against the choice of metric \r (Reisinger and Ledgard 2013; Ledgard and Reisinger 2014; Reisinger \r et al. 2017; Astrom and Johansson 2019). Clark et al. (2020) show that \r current emissions trends in the global food system alone would be \r sufficient to exceed a 1.5degC temperature limit and associated global \r emission targets even if GWP* is used to calculate CO2-equivalent \r emissions. This indicates that the importance of limiting food system \r emissions is not an artefact of using GWP100 as GHG emission \r metric, though it can change the quantification of CO2-eq emissions \r over time. Even if the most effective mitigation option does not \r [...]"


id: 5b2a5ec5c31c29a9252c9349a2cc61fe
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 13291
content:
"[...] depend strongly on the choice of GHG emission metric, the cost to \r emitters (if emissions were priced based on their CO2-equivalent \r values as part of national policies) can depend strongly on the GHG \r metric (Dorner and Kerr 2017)."


id: 87294852f468566d29254f5296b90e7b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 20943
content:
"Warming relative to a given reference point provides a different \r perspective: the contribution from CH4 emissions to global warming \r declines with declining emissions, whereas the contribution from \r CO2 emissions to global warming continues to rise even when its \r emissions decline, and this contribution keeps rising until CO2\r emissions are reduced to net zero. CO2 therefore remains and \r becomes the increasingly dominant driver of anthropogenic warming \r in virtually all emission scenarios (see also WGI Summary for \r Policymakers, Figure SPM.4). This information is relevant for policies \r and perspectives that are concerned with the changing contribution \r of individual gases and sectors to global warming over multiple \r decades, including their historical emissions (e.g., Lynch et al. 2021). \r Figure  2.SM.9 shows that, for CO2, the marginal and additional \r warming from future emissions is virtually identical, whereas the \r [...]"


id: f804f06a8355ab9f8b35310dd53adb4b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 41006
content:
"[...] marginal and additional warming from future CH4 emissions point in \r opposite directions in a mitigation pathway. Marginal metrics such \r as GWP and GTP, and step/pulse metrics such as GWP* (as applied \r in the literature so far) can differ substantially in the CO2 emissions \r they calculate as 'equivalent' to CH4 emissions, because they focus \r on different aspects of climate change. The specific policy objective \r (e.g., a focus on cost-effective abatement, a cost-benefit approach, \r or a focus on additional warming compared to a reference level) is \r therefore crucial for choosing and applying a metric that matches \r a given objective."


id: 32eab75dcf8febcf5cb1db4037daf403
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 6222
content:
"Figure 2.SM.9 illustrates these different perspectives: in an Illustrative \r Mitigation Pathway that limits warming to 1.5degC with no or limited \r overshoot (IMP-Ren15) (Chapter  3 and Annex III), the marginal\r warming from future CH4 emissions is always positive and can be \r comparable to the marginal warming from future CO2 emissions. That \r is, emissions of CH4 and CO2 from 2020 onwards (or any other specified \r reference year) both result in future global temperature being higher \r than it would be without those future emissions. Marginal warming is \r relevant for choices about the effort and costs that might be justified \r (from a damages, cost-benefit or cost-effectiveness perspective) to \r mitigate future emissions of either gas. The specific policy objective \r can then help determine what specific metric and time horizon would \r be optimal to use, provided that metrics are applied in a way that \r captures this marginal warming from future emissions. Information \r [...]"


id: 4b6d167bfb5a3d2a34c2afaa14cbcaf3
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 10523
content:
"[...] about marginal warming by definition does not include warming \r from past emissions that may continue into the future."


id: 43f81dcc57a0a9a4046760e565d4b7d5
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 9191
content:
"In contrast, one study suggests that international trade avoided \r 15  GtCO2 emissions globally between 1995 and 2009, when \r compared to a hypothetical situation without trade (Lopez et  al. \r 2018). Zhu and Jiang (2019) found that the recent slowdown in \r globalisation from 2012 to 2016 did not lower but instead increased \r global CO2 emissions by 202 Mt. This is because the consumption \r of domestic intermediate and final products increased in many \r countries, in particular in China and India, leading to increased \r domestic and therefore global CO2 emissions (Mi et al. 2017; Guan \r et al. 2018; Khochiani and Nademi 2019; Liu et al. 2019; Wang and \r Jiang 2019; Zheng et al. 2019; Wang et al. 2020c). Partly, this is due \r to the fact that non-OECD countries have a higher emissions intensity \r than OECD economies at the aggregate level (Zhu and Jiang 2019; \r Gonzalez-Torres et al. 2021). Scenario modelling of the USA-China \r [...]"


id: bb734db0de8b108bc139dc05c9bc9715
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 30200
content:
"[...] trade war in 2018-2019 showed an increase in global CO2 emissions, \r despite a decrease in global economic output (Lu et al. 2020). This was \r because the modelled change in trade patterns as a consequence of \r the trade war meant that increased emissions from land-use changes \r and higher production in some countries far exceeded the reductions \r through structural effects in other countries (Lu et al. 2020)."


id: ec32f4680d12da94a71e18f21340bfdf
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 38926
content:
"Figure 2.SM.13 | Change in regional GHGs from multiple perspectives and their underlying drivers. Panel (a): Regional GHG emissions trends (in GtCO2-eq yr-1) \r for 1990-2019. GHG emissions from international aviation and shipping are not assigned to individual countries and shown separately. Panels (b) and (c): Changes in GHG \r emissions for the 20 largest emitters (as of 2019) for 1990-2019 in relative (% annual change) and absolute terms (GtCO2-eq). Panels (d) and (e): GHG emissions per capita \r and per unit of GDP in 2019 for the 20 largest emitters (as of 2019). GDP estimated using constant international purchasing power parity (USD2017). Emissions are converted \r into CO2-equivalents based on global warming potential with a 100-year time horizon (GWP100) from IPCC's AR6 (Forster et al. 2021). The yellow dots represent the emissions \r [...]"


id: 6e3bc972ea4e8736417fb43470048719
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 16660
content:
"[...] data from UNFCCC-CRFs (2021) that were accessed through Gutschow et al. (2021a). Net LULUCF CO2 emissions are included in panel (a), based on the average of three \r bookkeeping models (Chapter 2, Section 2.2), but are excluded in panels (b) to (e) due to a lack of country resolution."


id: 611ea38a1d3d3b6ce9791af363294d2f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 14380
content:
"Alaa Al Khourdajie (United Kingdom/Syria), Christoph Bertram (Germany), Valentina Bosetti (Italy), \r Elina Brutschin (Austria), Edward Byers (Austria/Ireland), Tamma Carleton (the United States of \r America), Leon Clarke (the United States of America), Annette Cowie (Australia), Delavane Diaz \r (the United States of America), Laurent Drouet (Italy/France), Navroz  K.  Dubash  (India), \r James Edmonds (the United States of America) Jan S. Fuglestvedt (Norway), Shinichiro Fujimori \r (Japan), Oliver Geden (Germany), Giacomo Grassi (Italy/European Union), Michael Grubb \r (United Kingdom), Anders Hammer Stromman (Norway), Frank Jotzo (Australia), Jarmo Kikstra \r (Austria/the Netherlands), Zbigniew Klimont (Austria/Poland), Alexandre Koberle (Brazil/United \r Kingdom), Robin Lamboll (United Kingdom/the United States of America), Franck Lecocq \r (France), Jared Lewis (Australia/New Zealand), Yun Seng Lim (Malaysia), Giacomo Marangoni \r [...]"


id: e6e77917c8344ddce0bdb95e77a7821d
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 37913
content:
"[...] (Italy), Eric Masanet (the United States of America), Toshihiko Masui (Japan), David McCollum \r (the United States of America), Malte Meinshausen (Australia/Germany), Aurelie Mejean (France), \r Joel Millward-Hopkins (United Kingdom), Catherine Mitchell (United Kingdom), Gert-Jan Nabuurs \r (the Netherlands), Zebedee  Nicholls (Australia), Brian  O'Neill (the United States of America), \r Anthony  Patt (Switzerland), Franziska Piontek (Germany), Andy  Reisinger (New Zealand), \r Joeri Rogelj (Belgium/United Kingdom), Steven Rose (the United States of America), Bastiaan \r van Ruijven (the Netherlands), Yamina Saheb (France/Algeria), Marit Sandstad (Norway), Jim Skea \r (United Kingdom), Chris Smith (Austria/United Kingdom), Bjorn Soergel (Germany), Florian Tirana \r (France), Kaj-Ivar van der Wijst (the Netherlands), Harald Winkler (South Africa)"


id: c6d0831f8b7ffc27d6274e69ea5a5b98
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 32287
content:
"Chapter 3 assesses the emissions pathways literature in order \r to identify their key characteristics (both in commonalities and \r differences) and to understand how societal choices may steer \r the system into a particular direction (high confidence). More \r than 2000 quantitative emissions pathways were submitted to the \r IPCC's Sixth Assessment Report AR6 scenarios database, out of which \r 1202 scenarios included sufficient information for assessing the \r associated warming consistent with WGI. Five Illustrative Mitigation \r Pathways (IMPs) were selected, each emphasising a different scenario \r element as its defining feature: heavy reliance on renewables (IMP\u0002Ren), strong emphasis on energy demand reductions (IMP-LD), \r extensive use of carbon dioxide removal (CDR) in the energy and \r the industry sectors to achieve net negative emissions (IMP-Neg), \r [...]"


id: b14e576e9fe372cd6469d09bd1c562af
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 28426
content:
"[...] mitigation in the context of broader sustainable development (IMP\u0002SP), and the implications of a less rapid and gradual strengthening of \r near-term mitigation actions (IMP-GS). {3.2, 3.3}"


id: a46f1859672d090651ac956a4de96de0
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 26133
content:
"Pathways following Nationally Determined Contributions \r (NDCs) announced prior to COP262 until 2030 reach annual \r emissions of 47-57 GtCO2-eq by 2030, thereby making it \r impossible to limit warming to  1.5degC with no or limited \r overshoot and strongly increasing the challenge to limit \r warming to 2degC (>67%) (high confidence). A  high overshoot \r of  1.5degC increases the risks from climate impacts and increases \r the dependence on large-scale carbon dioxide removal from the \r atmosphere. A  future consistent with NDCs announced prior to \r COP26 implies higher fossil fuel deployment and lower reliance on \r low-carbon alternatives until 2030, compared to mitigation pathways \r with immediate action to limit warming to 2degC (>67%) or lower. To \r limit warming to 2degC (>67%) after following the NDCs to 2030, the \r pace of global GHG emission reductions would need to accelerate \r rapidly from 2030 onward: to an average of 1.4-2.0 GtCO2-eq yr-1\r [...]"


id: 89c1be1c2bef9aa47085f31088876eab
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 21407
content:
"[...] between 2030 and 2050, which is around two-thirds of the global \r CO2 emission reductions in 2020 due to the COVID-19 pandemic, \r and around 70% faster than in immediate action pathways that \r limit warming to 2degC (>67%). Accelerating emission reductions after \r following an NDC pathway to 2030 would be particularly challenging \r because of the continued buildup of fossil fuel infrastructure that \r would be expected to take place between now and 2030. {3.5, 4.2}"


id: 92c091e1422b67f1a811f49232eff590
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 23034
content:
"Pathways consistent with the implementation and \r extrapolation of countries' implemented policies until the end \r of 2020 see greenhouse gas (GHG) emissions reaching 54-\r 61 GtCO2-eq yr-1 by 2030 and to 47-67 GtCO2-eq yr-1 by 2050, \r leading to a median global warming of 2.2degC to 3.5degC by 2100\r (medium confidence). These pathways consider policies at the time \r that they were developed. The Shared Socio-economic Pathways \r (SSPs) permit a more systematic assessment of future GHG emissions \r and their uncertainties than was possible in AR5. The main emissions \r drivers include growth in population, reaching  8.5-9.7 billion by \r 2050, and an increase in global GDP of 2.7-4.1% per year between \r 2015 and 2050. Final energy demand in the absence of any new \r climate policies is projected to grow to around 480-750 EJ yr-1 in \r 2050 (compared to around 390 EJ in 2015) (medium confidence). The \r highest emissions scenarios in the literature result in global warming \r [...]"


id: ce67c912bfec48d7675fd054c7c73d96
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 33655
content:
"[...] of >5degC by 2100, based on assumptions of rapid economic growth \r and pervasive climate policy failures (high confidence). {3.3} "


id: de20c09c8b00ad1284f6477efc3ad0bd
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 36340
content:
"Rapid reductions in non-CO2 GHGs, particularly methane, \r would lower the level of peak warming (high confidence).\r Residual non-CO2 emissions at the time of reaching net zero \r CO2 range between 5 and 11 GtCO2-eq yr-1 in pathways limiting \r warming to 2degC  (>67%) or lower. Methane (CH4) is reduced by \r around 19% (4-46%) in 2030 and 45% (29-64%) in 2050, relative \r to 2019. Methane emission reductions in pathways limiting warming \r to  1.5degC (>50%) with no or limited overshoot are substantially \r higher by 2030, 34% (21-57%), but only moderately so by 2050, \r 51% (35-70%). Methane emissions reductions are thus attainable \r at relatively lower GHG prices but are at the same time limited in \r scope in most  1.5degC-2degC pathways. Deeper methane emissions \r reductions by 2050 could further constrain the peak warming. N2O \r emissions are reduced too, but similar to CH4, emission reductions \r saturate for more stringent climate goals. In the mitigation pathways, \r [...]"


id: ca5b10f5bd7b5f4cf0b5efbc9df161df
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 32943
content:
"[...] the emissions of cooling aerosols are reduced due to reduced use of \r fossil fuels. The overall impact on non-CO2-related warming combines \r these factors. {3.3}"


id: d21daa90420b3035ac4b4aa299815c0c
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 34319
content:
"The global benefits of pathways limiting warming to 2degC \r (>67%) outweigh global mitigation costs over the 21st century, \r if aggregated economic impacts of climate change are at the \r moderate to high end of the assessed range, and a  weight \r consistent with economic theory is given to economic impacts \r over the long term. This holds true even without accounting for \r benefits in other sustainable development dimensions or non\u0002market damages from climate change (medium confidence).\r The aggregate global economic repercussions of mitigation \r pathways include the macroeconomic impacts of investments in \r low-carbon solutions and structural changes away from emitting \r activities, co-benefits and adverse side effects of mitigation, \r (avoided) climate change impacts, and (reduced) adaptation costs. \r Existing quantifications of global aggregate economic impacts show \r a strong dependence on socio-economic development conditions, as \r [...]"


id: dd4a786f3be0ab5d70c83826731663ba
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 36195
content:
"[...] these shape exposure and vulnerability and adaptation opportunities \r and responses. (Avoided) impacts for poorer households and \r poorer countries represent a  smaller share in aggregate economic \r quantifications expressed in GDP or monetary terms, whereas their \r well-being and welfare effects are comparatively larger. When \r aggregate economic benefits from avoided climate change impacts \r are accounted for, mitigation is a welfare-enhancing strategy (high \r confidence). {3.6.2}"


id: 35e895023849334c02f7d171281c0c37
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 6728
content:
"The economic repercussions of mitigation vary widely across \r regions and households, depending on policy design and level \r of international cooperation (high confidence). Delayed global \r cooperation increases policy costs across regions, especially in those \r that are relatively carbon intensive at present (high confidence). \r Pathways with uniform carbon values show higher mitigation costs \r in more carbon-intensive regions, in fossil fuel exporting regions \r and in poorer regions (high confidence). Aggregate quantifications \r expressed in GDP or monetary terms undervalue the economic effects \r on households in poorer countries; the actual effects on welfare and \r well-being are comparatively larger (high confidence). Mitigation \r at the speed and scale required to limit warming to 2degC (>67%) or \r lower implies deep economic and structural changes, thereby raising \r multiple types of distributional concerns across regions, income \r [...]"


id: 410d2c329bd3a29c2903362f60a743d1
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 8628
content:
"Stabilising global average-temperature change requires reducing \r CO2 emissions to net zero. Thus, a central cross-cutting topic within \r the chapter is the timing of reaching net zero CO2 emissions and \r how a  'balance between anthropogenic emissions by sources \r and removals by sinks' could be achieved across time and space. This \r includes particularly the increasing body of literature since the IPCC \r Special Report on Global Warming of 1.5degC (SR1.5) which focuses on \r net zero CO2 emissions pathways that avoid temperature overshoot \r and hence do not rely on net negative CO2 emissions. The chapter \r conducts a systematic assessment of the associated economic costs \r as well as the benefits of mitigation for other societal objectives, \r such as the Sustainable Development Goals (SDGs). In addition, the \r chapter builds on SR1.5 and introduces a new conceptual framing for \r the assessment of possible social, economic, technical, political, and \r [...]"


id: 911f758d1e726d998c862822f71d93c7
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 22735
content:
"[...] geophysical 'feasibility' concerns of alternative pathways, including \r the enabling conditions that would need to fall into place so that \r stringent climate goals become attainable."


id: ada8157e23e66e2414ec5a7838bb59b1
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 27792
content:
"The structure of the chapter is as follows: Section  3.2 introduces \r different types of mitigation pathways as well as the available \r modelling. Section 3.3 explores different emissions trajectories given \r socio-economic uncertainties and consistent with different long-term \r climate outcomes. A central element in this section is the systematic \r categorisation of the scenario space according to key characteristics of \r the mitigation pathways (including e.g., global average-temperature \r change, socio-economic development, technology assumptions, etc.). \r In addition, the section introduces selected Illustrative Mitigation \r Pathways (IMPs) that are used across the whole report. Section 3.4 \r conducts a sectoral analysis of the mitigation pathways, assessing \r the pace and direction of systems changes across sectors. Among \r others, this section aims at the integration of the sectoral information \r across AR6 WGIII chapters through a comparative assessment of the \r [...]"


id: aafb9b5758d0fdee004df6bb6d487f1
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 27307
content:
"[...] sectoral dynamics in economy-wide systems models compared to \r the insights from bottom-up sectoral models (from Chapters 6 to 11). \r Section 3.5 focuses on the required timing of mitigation actions, and \r the implication of near-term choices for the attainability of a range \r of long-term climate goals. After having explored the underlying \r systems transitions and the required timing of the mitigation actions, \r Section 3.6 assesses the economic implications, mitigation costs and \r benefits; and Section  3.7 assesses related co-benefits, synergies, \r and possible trade-offs for sustainable development and other \r societal (non-climate) objectives. Section 3.8 assumes a central role \r in the chapter and introduces a multidimensional feasibility metric "


id: cdfd2918ceff05e2d1475bed14f08ccc
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content:
"The literature shows a wide range of possible emissions trajectories, depicting developments in the absence of new climate policies or \r showing pathways consistent with the Paris Agreement. From the literature, a set of five Illustrative Mitigation Pathways (IMPs) was \r selected to denote implications of choices on socio-economic development and climate policies, and the associated transformations of \r the main GHG-emitting sectors (Figure 3.5b). The IMPs include a set of transformative pathways that illustrate how choices may lead \r to distinctly different transformations that may keep temperature increase to below 2degC (>67%) or 1.5degC. These pathways illustrate \r the implications of a focus on renewable energy such as solar and wind; reduced energy demand; extensive use of CDR in the energy \r and the industry sectors to achieve net negative emissions and reliance on other supply-side measures; strategies that avoid net \r [...]"


id: 3cc3f0a51f51ce344560f99da6d11c71
created_at: 2023-04-19 13:23:08
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"[...] negative carbon emissions, and gradual strengthening. In addition, one IMP explores how climate policies consistent with keeping \r limit warming to 1.5C (>50%) can be combined with a broader shift towards sustainable development. These IMPs are used in various \r chapters, exploring for instance their implications for different sectors, regions, and innovation characteristics (Figure 3.5b)."


id: 76642ac0b6d1e1a3c2d2265cd318988a
created_at: 2023-04-19 13:23:08
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"Mitigation scenarios explore different strategies to meet climate goals \r and are typically derived from reference scenarios by adding climate \r or other policies. Mitigation pathways are often developed to meet \r a predefined level of climate change, often referred to as a backcast. \r There are relatively few IAMs that include an endogenous climate \r model or emulator due to the added computational complexity, \r though exceptions do exist. In practice, models implement climate \r constraints by either iterating carbon-price assumptions (Strefler \r et al. 2021b) or by adopting an associated carbon budget (Riahi \r et al. 2021). In both cases, other GHGs are typically controlled by \r CO2-equivalent pricing. A large part of the AR5 literature has focused \r on forcing pathways towards a target at the end of the century (van \r Vuuren et al. 2007, 2011; Clarke et al. 2009; Blanford et al. 2014; Riahi \r et al. 2017), featuring a  temporary overshoot of the warming and \r [...]"


id: c1c21e91917fc8cc239f89e43f92d67c
created_at: 2023-04-19 13:23:08
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"[...] forcing levels (Geden and Loschel 2017). In comparison, many recent \r studies explore mitigation strategies that limit overshoot (Johansson \r et al. 2020; Riahi et al. 2021). An increasing number of IAM studies \r also explore climate pathways that limit adverse side effects with \r respect to other societal objectives, such as food security (van Vuuren \r et al. 2019; Riahi et al. 2021) or larger sets of sustainability objectives \r (Soergel et al. 2021a)."


id: 633cb96b7ea489fdeebed34f5d9cd9e3
created_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
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content:
"IAMs have a  long history in addressing environmental \r problems, particularly in the IPCC assessment process (van Beek \r et al. 2020). Many policy discussions have been guided by IAM-based \r quantifications, such as the required emission reduction rates, net \r zero years, or technology deployment rates required to meet certain \r climate outcomes. This has led to the discussion about whether IAM \r scenarios have become performative, meaning that they act upon, \r transform or bring into being the scenarios they describe (Beck and \r Mahony 2017, 2018). Transparency of underlying data and methods \r is critical for scenario users to understand what drives different \r scenario results (Robertson 2020). A number of community activities \r have thus focused on the provision of transparent and publicly \r accessible databases of both input and output data (Riahi et al. 2012; \r Huppmann et al. 2018; Krey et al. 2019; Daioglou et al. 2020), as well \r [...]"


id: 7427af6a63b82796715d2eaf95c42ae2
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content:
"[...] as the provision of open-source code, and increased documentation \r (Annex III.I.9). Transparency is needed to reveal conditionality of results \r on specific choices in terms of assumptions (e.g., discount rates) and \r model architecture. More detailed explanations of underlying model \r dynamics would be critical to increase the understanding of what \r drives results (Bistline et al. 2020; Butnar et al. 2020; Robertson 2020)."


id: 8559d423319b2176635fdec6d25b348f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
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content:
"Integrated Assessment Models (IAMs) are critical for understanding \r the implications of long-term climate objectives for the required \r near-term transition. For doing so, an integrated systems perspective \r including the representation of all sectors and GHGs is necessary. \r IAMs are used to explore the response of complex systems in a formal \r and consistent framework. They cover a broad range of modelling \r frameworks (Keppo et al. 2021). Given the complexity of the systems \r under investigation, IAMs necessarily make simplifying assumptions \r and therefore results need to be interpreted in the context of these \r assumptions. IAMs can range from economic models that consider \r only carbon dioxide emissions through to detailed process-based \r representations of the global energy system, covering separate \r regions and sectors (such as energy, transport, and land use), all GHG \r emissions and air pollutants, interactions with land and water, and \r [...]"


id: 23a902701185c24207ca61dfbc3cf96d
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updated_at: 2023-04-19 13:23:08
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vector_id: 3472
content:
"[...] a reduced representation of the climate system. IAMs are generally \r driven by economics and can have a variety of characteristics such as \r partial-, general- or non-equilibrium; myopic or perfect foresight; be "


id: 63997710d643976db0718a748a59481e
created_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 14814
content:
"cost-effectiveness approach, they do not make any additional equity \r assumptions. Notable exceptions include Tavoni et al. (2015), Pan et al. \r (2017), van den Berg et al. (2020), and Bauer et al. (2020). Regional \r IAM results therefore need to be assessed with care, considering that \r emissions reductions are happening where it is most cost-effective, \r which needs to be separated from who is ultimately paying for \r the mitigation costs. Cost-effective pathways can provide a  useful \r benchmark, but may not reflect real-world developments (Calvin \r et al. 2014a; Trutnevyte 2016). Different modelling frameworks may \r lead to different outcomes (Mercure et al. 2019). Recent studies have \r shown that other desirable outcomes can evolve with only minor \r deviations from cost-effective pathways (Bauer et al. 2020; Neumann \r and Brown 2021). IAM and sectoral models represent social, political, \r and institutional factors only in a rudimentary way. This assessment is \r [...]"


id: 5399ee33022bfd9949583dc7d5d762d3
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vector_id: 11982
content:
"[...] thus relying on new methods for the ex post assessment of feasibility \r concerns (Jewell and Cherp 2020; Brutschin et al. 2021). A literature is \r emerging that recognises and reflects on the diversity and strengths/\r weaknesses of model-based scenario analysis (Keppo et al. 2021)."


id: 74d5b236eb4f75240107d7783d9cdf07
created_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 17793
content:
"IPCC reports have often used voluntary submissions to a  scenario \r database in its assessments. The database is an ensemble of opportunity, \r as there is not a well-designed statistical sampling of the hypothetical \r model or scenario space: the literature is unlikely to cover all possible \r models and scenarios, and not all scenarios in the literature are \r submitted to the database. Model intercomparisons are often the core \r of scenario databases assessed by the IPCC (Cointe et al. 2019; Nikas \r et al. 2021). Single-model studies may allow more detailed sensitivity \r analyses or address specific research questions. The scenarios that are \r organised within the scientific community are more likely to enter the \r assessment process via the scenario database (Cointe et al. 2019), \r while scenarios from different communities, in the emerging literature, \r or not structurally consistent with the database may be overlooked. \r [...]"


id: 42bf3dcc1dc75ed357c976c4111680d
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index: climate_gpt_v2
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content:
"[...] Scenarios in the grey literature may not be assessed even though they \r may have greater weight in a policy context."


id: 3b1f973febb23f3169196175c785ed73
created_at: 2023-04-19 13:23:08
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content:
"One notable development since AR5 is the Shared Socio-economic \r Pathways (SSPs), conceptually outlined in Moss et al. (2010) and \r subsequently developed to support integrated climate research across \r the IPCC Working Groups (O'Neill et al. 2014). Initially, a set of SSP \r narratives were developed, describing worlds with different challenges \r to mitigation and adaptation (O'Neill et al. 2017a): SSP1 (sustainability), \r SSP2 (middle of the road), SSP3 (regional rivalry), SSP4 (inequality) \r and SSP5 (rapid growth). The SSPs have now been quantified in terms \r of energy, land-use, and emission pathways (Riahi et al. 2017), for \r both no-climate-policy reference scenarios and mitigation scenarios \r that follow similar radiative-forcing pathways as the Representative \r Concentration Pathways (RCPs) assessed in AR5 WGI. Since then the \r SSPs have been successfully applied in thousands of studies (O'Neill \r et al. 2020b) including some critiques on the use and application of \r [...]"


id: 45c2d6a09ebc9893fa848383974b169b
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content:
"[...] the SSP framework (Pielke and Ritchie 2021; Rosen 2021). A selection \r of the quantified SSPs are used prominently in AR6 WGI as they were \r the basis for most climate modelling since AR5 (O'Neill et al. 2016). \r Since 2014, when the first set of SSP data was made available, there \r has been a divergence between scenario and historic trends (Burgess \r et al. 2020). As a result, the SSPs require updating (O'Neill et al. 2020b). \r Most of the scenarios in the AR6 database are SSP-based and consider \r various updates compared to the first release (Riahi et al. 2017)."


id: 454ec2bc345d19fa91b4f8cc5010e094
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content:
"Many factors influence the deployment of technologies in the \r IAMs. Since AR5, there has been fervent debate on the large-scale \r deployment of bioenergy with carbon capture and storage (BECCS) in \r scenarios (Fuss et al. 2014; Geden 2015; Anderson and Peters 2016; \r Smith et al. 2016; van Vuuren et al. 2017; Galik 2020; Koberle 2019). \r Hence, many recent studies explore mitigation pathways with limited \r BECCS deployment (Grubler et al. 2018; van Vuuren et al. 2019; \r Riahi et al. 2021; Soergel et al. 2021a). While some have argued that \r technology diffusion in IAMs occurs too rapidly (Gambhir et al. 2019), \r others argued that most models prefer large-scale solutions resulting \r in a  relatively slow phase-out of fossil fuels (Carton 2019). While \r IAMs are particularly strong on supply-side representation, demand\u0002side measures still lag in detail of representation despite progress \r since AR5 (Grubler et al. 2018; Lovins et al. 2019; van den Berg et al. \r [...]"


id: af12bdb12a3f01faf13e8020b8a7aae7
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content:
"[...] 2019;  O'Neill et al. 2020b; Hickel et al. 2021; Keysser and Lenzen \r 2021). The discount rate has a  significant impact on the balance \r between near-term and long-term mitigation. Lower discount rates \r <4% (than used in IAMs) may lead to more near-term emissions \r reductions - depending on the stringency of the target (Emmerling \r et al. 2019; Riahi et al. 2021). Models often use simplified policy \r assumptions (O'Neill et al. 2020b) which can affect the deployment \r of technologies (Sognnaes et al. 2021). Uncertainty in technologies \r can lead to more or less short-term mitigation (Grant et al. 2021; \r Bednar et al. 2021). There is also a recognition to put more emphasis \r on what drives the results of different IAMs (Gambhir et al. 2019) \r and suggestions to focus more on what is driving differences in result \r across IAMs (Nikas et al. 2021). As noted by Weyant (2017, p. 131), "


id: 75a4c7def76777a0af26e443e05249c6
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vector_id: 17927
content:
"action (634) and (P2a) without any transfer of emission permits - 435, \r (P2b) with transfers - 70; or (P2c) with additional policy assumptions - \r 55; (P3) globally coordinated climate policies with delayed (i.e., from \r 2030 onwards or after 2030) action (451), preceded by (P3a) no \r mitigation commitment or current national policies - 7, (P3b) NDCs - \r 426, (P3c) NDCs and additional policies - 18; (P4) cost-benefit analysis \r (CBA)  -  2. The policy categories were identified using text pattern \r matching on the scenario metadata and calibrated on the best-known \r scenarios from model intercomparisons, with further validation against \r the related literature, reported emission and carbon price trajectories, \r and exchanges with modellers. If the information available is enough \r to qualify a policy category number but not sufficient for a subcategory, \r then only the number is retained (e.g., P2 instead of P2a/b/c). A suffix \r [...]"


id: f7453e22689969d6b93418db09dada3d
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content:
"[...] added after P0 further qualifies a diagnostic scenario as one of the other \r policy categories. To demonstrate the diversity of the scenarios, the vetted \r scenarios were classified into different categories along the dimensions \r of population, GDP, energy, and cumulative emissions (Figure 3.4). The \r number of scenarios in each category provides some insight into the \r current literature, but this does not indicate a higher probability of that \r category occurring in reality. For population, the majority of scenarios \r are consistent with the SSP2 'middle of the road' category, with very \r few scenarios exploring the outer extremes. GDP has a slightly larger \r variation, but overall most scenarios are around the SSP2 socio\u0002economic assumptions. The level of CCS and CDR is expected to change \r depending on the extent of mitigation, but there remains extensive use \r of both CDR and CCS in scenarios. CDR is dominated by bioenergy with \r [...]"


id: 8d29eed62a7f1adf0d9e430fac2f65d0
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content:
"[...] CCS (BECCS) and sequestration on land, with relatively few scenarios \r using direct air capture with carbon storage (DACCS) and even less \r with enhanced weathering (EW) and other technologies (not shown). \r In terms of energy consumption, final energy has a much smaller range \r than primary energy as conversion losses are not included in final \r energy. Both mitigation and reference scenarios are shown, so there is \r a broad spread in different energy carriers represented in the database. \r Bioenergy has a number of scenarios at around 100 EJ, representing \r a constraint used in many model intercomparisons."


id: d62188d2d5d5b4b422ae093e7bba874c
created_at: 2023-04-19 13:23:08
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content:
"The selected scenarios (IPs) are divided into two sets (Figures  3.5 \r and 3.6): two reference pathways illustrative of high emissions and five \r Illustrative Mitigation Pathways (IMPs). The narratives are explained \r in full in Annex III.II.2.4. The two reference pathways explore the \r consequences of current policies and pledges: Current Policies (CurPol) \r and Moderate Action (ModAct). The CurPol pathway explores the \r consequences of continuing along the path of implemented climate \r policies in 2020 and only a  gradual strengthening after that. The \r scenario illustrates the outcomes of many scenarios in the literature \r that project the trend from implemented policies until the end of \r 2020. The ModAct pathway explores the impact of implementing \r the Nationally Determined Contributions (NDCs) as formulated in \r 2020 and some further strengthening after that. In line with current \r literature, these two reference pathways lead to an increase in global \r [...]"


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content:
"The Illustrative Mitigation Pathways (IMPs) properly explore different \r pathways consistent with meeting the long-term temperature goals \r of the Paris Agreement. They represent five different pathways that \r emerge from the overall assessment. The IMPs differ in terms of their \r focus, for example, placing greater emphasis on renewables (IMP-Ren), \r deployment of carbon dioxide removal that results in net negative \r global GHG emissions (IMP-Neg), and efficient resource use and \r shifts in consumption patterns, leading to low demand for resources, \r while ensuring a high level of services (IMP-LD). Other IMPs illustrate \r the implications of a less rapid introduction of mitigation measures \r followed by a subsequent gradual strengthening (IMP-GS), and how \r shifting global pathways towards sustainable development, including \r by reducing inequality, can lead to mitigation (IMP-SP) In the IMP \r framework, IMP-GS is consistent with limiting warming to 2degC (>67%) \r [...]"


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content:
"[...] (C3), IMP-Neg shows a strategy that also limits warming to 2degC (>67%) \r but returns to nearly 1.5degC (>50%) by the end of the century (hence \r indicated as C2*). The other variants that can limit warming to 1.5degC \r (>50%) (C1) were selected. In addition to these IMPs, sensitivity cases \r that explore alternative warming levels (C3) for IMP-Neg and IMP-Ren\r are assessed (IMP-Neg-2.0 and IMP-Ren-2.0)."


id: fcad22100d1bde62f08bd4cc5d0e1797
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content:
"Economic growth is even more uncertain than the population projections \r (Figure  3.9c). The average growth rate of GDP was about  2.8% per \r year (constant USD) in the 1990-2019 period (The World Bank 2021). \r In 2020, the COVID-19 crisis resulted in a considerable drop in GDP \r (estimated around  4-5%) (IMF 2021). After a  recovery period, most \r economic projections assume growth rates to converge back to previous \r projections, although at a lower level (IMF 2021; OECD 2021) (see also \r Box  3.2). In the long term, assumptions on future growth relate to \r political stability, the role of the progress of the technology frontier and \r the degree to which countries can catch up (Johansson et al. 2013). The \r SSP scenarios cover an extensive range, with low per-capita growth in \r SSP3 and SSP4 (mostly in developing countries) and rapid growth in \r SSP1 and SSP5. At the same, however, also scenarios outside the range \r [...]"


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content:
"[...] have some plausibility - including the option of economic decline (Kallis \r et al. 2012) or much faster economic development (Christensen et al. \r 2018). The OECD long-term projection is at the global level reasonably \r consistent with SSP2. Equally important economic parameters include \r income distribution (inequity) and the type of growth (structural \r change,  i.e.,  services vs manufacturing industries). Some projections \r (like SSP1) show a considerable convergence of income levels within \r and across countries, while in other projections, this does not occur \r (e.g., SSP3). Most scenarios reflect the suggested inverse relationship \r between the assumed growth rate for income and population growth \r (Figure  3.9e). SSP1 and SSP5 represent examples of scenarios with \r relatively low population increase and relatively high-income increase \r over the century. SSP3 represents an example of the opposite - while \r [...]"


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content:
"[...] SSP2 and SSP4 are placed more in the middle. Nearly all scenarios \r assessed here do not account for climate impacts on growth (mostly \r for methodological reasons). As discussed in Section 3.5 these impacts \r can be considerable. An emerging area of literature emphasises the \r possibility of stabilisation (or even decline) of income levels in developed \r countries, arguing that such a trend would be preferred or even needed \r for environmental reasons (Anderson and Larkin 2013; Hickel and Kallis \r 2020; Kallis et al. 2020; Hickel et al. 2021; Keysser and Lenzen 2021) (see \r also Chapter 5). Such scenarios are not common among IAM outcomes, \r that are more commonly based on the idea that decarbonisation can \r be combined with economic growth by a combination of technology, \r lifestyle and structural economic changes. Still, such scenarios could \r result in a dramatic reduction of energy and resource consumption."


id: 21749c01151630f8e268e3c5ff75f46e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 3094
content:
"Greenhouse gas (GHG) emissions mainly originate from the use and \r transformation of energy, agriculture, land use (change) and industrial \r activities. The future development of these sources is  influenced \r by trends in socio-economic development, including  population, \r economic activity, technology, politics, lifestyles, and climate policy. \r Trends for these factors are not independent, and scenarios provide \r a consistent outlook for these factors together (Section 3.2). Marangoni \r et al. (2017) show that in projections, assumptions influencing \r energy intensity (e.g., structural change, lifestyle and efficiency) and \r economic growth are the most important determinants of future \r CO2 emissions from energy combustion. Other critical factors include \r technology assumptions, preferences, resource assumptions and \r policy (van Vuuren et al. 2008). As many of the factors are represented \r differently in specific models, the model itself is also an important \r [...]"


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index: climate_gpt_v2
vector_id: 25001
content:
"[...] factor  - providing a  reason for the importance of model diversity \r (Sognnaes et al. 2021). For land use, Stehfest et al. (2019) show that \r assumptions on population growth are more dominant given that \r variations in per capita consumption of food are smaller than for \r energy. Here, we only provide a brief overview of some key drivers. We \r focus first on so-called reference scenarios (without stringent climate \r policy) and look at mitigation scenarios in detail later. We use the SSPs \r to discuss trends in more detail. The SSPs were published in 2017, and \r by now, some elements will have to be updated (O'Neill et al. 2020b). \r Still, the ranges represent the full literature relatively well."


id: a9ab6388540eebf022b14f4a9671bce0
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updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 27067
content:
"Historically, population and GDP have been growing over time. \r Scenario studies agree that further global population growth \r is likely up to 2050, leading to a  range of possible outcomes of \r around 8.5-11 billion people (Figure 3.9a). After 2050, projections \r show a much wider range. If fertility drops below replacement levels, \r a decline in the global population is possible (as illustrated by SSP1 \r and SSP5). This typically includes scenarios with rapid development \r and investment in education. However, median projections mostly \r show a  stabilisation of the world population (e.g.,  SSP2), while \r high-end projections show a continued growth (e.g., SSP3). The UN \r Population Prospects include considerably higher values for both \r the medium projection and the high end of the range than the SSP \r scenarios (KC and Lutz 2017; UN 2019). The most recent median \r UN projection reaches almost 11 billion people in 2100. The key \r [...]"


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updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 40961
content:
"[...] differences are in Africa and China: here, the population projections \r are strongly influenced by the rate of fertility change (faster drop in \r SSPs). Underlying these differences, the UN approach is more based \r on current demographic trends while the SSPs assume a  broader \r range of factors (including education) driving future fertility."


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vector_id: 959
content:
"Scenarios show a range of possible energy projections. In the absence \r of climate policy, most scenarios project the final energy demand \r to continue to grow to around 650-800 EJ yr-1 in 2100 (based on \r the AR6 Scenarios Database, Figure  3.9b). Some projections show \r a very high energy demand up to 1000 EJ yr-1 (comparable to SSP5). \r The scenario of the IEA lies within the SSP range but near the SSP1 \r projection. However, it should be noted that the IEA scenario includes \r current policies (most reference scenarios do not) and many scenarios \r published before 2021 did not account for the COVID-19 crisis. Several \r researchers discuss the possibility of decoupling material and energy \r demand from economic growth in the literature, mainly in developed \r countries (Kemp-Benedict 2018) (decoupling here refers to either \r a much slower increase in demand or even a decrease). In the scenario \r literature, this is reflected by scenarios with very low demand for final \r [...]"


id: f714c35e7d32d39a40d5f13353550e54
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 40841
content:
"[...] energy based on increased energy efficiency and less energy-intensive \r lifestyles (e.g., SSP1 and the LED scenario) (Grubler et al. 2018; van \r Vuuren et al. 2018). While these studies show the feasibility of such "


id: 98374036115a4aec82f9a103dbe45ca6
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 23989
content:
"pathways, their energy efficiency improvement rates are considerably \r above the historic range of around 2% (Gutschow et al. 2018; Jeffery et \r al. 2018; Vrontisi et al. 2018; Haberl et al. 2020; Roelfsema et al. 2020; \r Giarola et al. 2021; Hohne et al. 2021; IEA 2021a; Hohne et al. 2021; \r Sognnaes et al. 2021). These scenarios also show clear differences in \r food consumption and the amount of land used for agriculture. Food \r demand in terms of per-capita caloric intake is projected to increase in \r most scenarios (Figure 3.9d). However, it should be noted that there \r are large differences in dietary composition across the scenarios (from \r more meat-intensive in scenarios such as SSP5 to a decrease in meat \r consumptions in other scenarios such as SSP1). Land-use projections \r also depend on assumed changes in yield and the population scenarios \r (Figure 3.9f). Typically, changes in land use are less drastic than some \r [...]"


id: e49a80e574a180d6ea45267b45dfd09b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 37506
content:
"[...] other parameters (in fact, the  5-95th percentile database range \r is almost stable). Agriculture land is projected to increase in SSP3, "


id: 129c6da4fb5ff2e062908535621b0dd
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 477
content:
"The reduction in CO2 emissions of the COVID-19 pandemic in 2020 was estimated to be about 6% (Section 4.2.2.4 and Table 4.SM.2) \r lower than 2019 levels (Forster et al. 2020; Friedlingstein et al. 2020; Liu et al. 2020c; BP 2021; Crippa et al. 2021; IEA 2021; Le Quere \r et al. 2021). Near-real-time monitoring estimates show a rebound in emissions levels, meaning 2021 emissions levels are expected \r to be higher than 2020 (Le Quere et al. 2021). The longer-term effects are uncertain but so far do not indicate a clear structural \r change for climate policy related to the pandemic. The increase in renewable shares in 2020 could stimulate a further transition, \r but slow economic growth can also slow down (renewable) energy investments. Also, lifestyle changes during the crisis can still \r develop in different directions (working from home, but maybe also living further away from work). Without a major intervention, \r [...]"


id: e2fb626e3ee63b58fd7e4f2f0972304b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 37230
content:
"[...] most long-term scenarios project that emissions will start to follow a similar pathway as earlier projections (although at a reduced \r level) (IEA 2020b; Kikstra et al. 2021a; Rochedo et al. 2021). If emissions reductions are limited to only a short time, the adjustment \r of pathways will lead to negligible outcomes in the order of 0.01K (Forster et al. 2020; Jones et al. 2021). At the same time, however, \r the large amount of investments pledged in the recovery packages could provide a  unique opportunity to determine the long\u0002term development of infrastructure, energy systems and land use (Andrijevic et al. 2020b; Hepburn et al. 2020; Pianta et al. 2021). \r Near-term alternative recovery pathways have been shown to have the potential to influence carbon-price pathways, and energy \r investments and electrification requirements under stringent mitigation targets (Bertram et al. 2021; Kikstra et al. 2021a; Pollitt et al. \r [...]"


id: 1c19a19d4c24ed3f456ef63cd32c1570
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 2123
content:
"[...] 2021; Rochedo et al. 2021; Shan et al. 202). Most studies suggest a noticeable reduction in 2030 emissions. However, much further \r reductions would be needed to reach the emission levels consistent with mitigation scenarios that limit warming to 2degC (>67%) \r or lower (see Chapter 4). At the moment, the share of investments in greenhouse gas reduction is relatively small in most recovery \r packages, and no structural shifts for climate policies are observed linked to the pandemic. Finally, most of the scenarios analysed \r in this Chapter do not include the 2020 emissions reduction related to the COVID-19 pandemic. The effect of the pandemic on the \r pathways will likely be very small. The assessment of climate mitigation pathways in this chapter should be interpreted as being \r almost exclusively based on the assumption of a fast recovery with limited persistent effects on emissions or structural changes."


id: 3f94e560ed9ff2f82ee3b02b1cb7bc4c
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 8375
content:
"The higher categories (C6 and C7) mostly included scenarios with \r no or modest climate policy. Because of the progression of climate \r policy, it is becoming more common that reference scenarios \r incorporate implemented climate policies. Modelling studies typically \r implement current or pledged policies up until 2030 (Vrontisi et al. \r 2018; Roelfsema et al. 2020; Sognnaes et al. 2021) with some studies \r focusing also on the policy development in the long term (Hohne \r et al. 2021; IEA  2021a; Jeffery et al. 2018; Gutschow et al. 2018). \r Based on the assessment in Chapter 4, reference pathways consistent \r with the implementation and trend from implemented policies until \r the  end of 2020 are associated with increased GHG emissions \r from 59 (53-65) GtCO2-eq yr-1 in 2019 to 54-60 GtCO2-eq yr-1 by \r 2030 and to 47-67 GtCO2-eq yr-1 by 2050 (Figure  3.6). Pathways \r with these near-term emissions characteristics lead to a  median \r [...]"


id: 9b1242d08fe688d140f82042f71a85c1
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 24535
content:
"[...] global warming of 2.2degC to 3.5degC by 2100 (see also further in this \r section). These pathways consider policies at the time that they \r were developed. A recent model comparison that harmonised socio\u0002economic, technological, and policy assumptions (Giarola et al. 2021) \r found a  2.2degC-2.9degC median temperature rise in 2100 for current \r and stated policies, with the results sensitive to the model used and \r the method of implementing policies (Sognnaes et al. 2021). Scenario \r inference and construction methods using similar policy assumptions \r lead to a median range of 2.9degC-3.2degC in 2100 for current policies \r and 2.4degC-2.9degC in 2100 for 2030 pledges (Hohne et al. 2021). The \r median spread of 1degC across these studies (2.2degC-3.2degC) indicates \r the deep uncertainties involved with modelling temperature \r outcomes of 2030 policies through to 2100 (Hohne et al. 2021)."


id: 56ab4c05e8e205a02b3be6c87e8881fc
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 12502
content:
"Figure 3.11 shows the possible consequences of the different scenario \r categories for global mean temperature calculated using a reduced \r complexity model (RCM) calibrated to the IPCC AR6 WGI assessment \r (see Annex III.II.2.5 of this report and Cross-Chapter Box 7.1 in \r AR6 WGI report). For the C5-C7 categories (containing most of the \r reference and current policy scenarios), the global mean temperature \r is expected to increase throughout the century (and further increase \r will happen after 2100 for C6 and C7). While warming would more \r likely than not be in the range from 2.2degC to 3.5degC, warming up to 5degC \r cannot be excluded. The highest emissions scenarios in the literature \r combine assumptions about rapid long-term economic growth \r and pervasive climate policy failures, leading to a reversal of some \r recent trends (Box 3.3). For the categories C1-C4, a peak in global \r mean temperature is reached mid-century for most scenarios in the \r [...]"


id: 6c0a72d296da88726a293644ae600c80
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 16311
content:
"[...] database, followed by a small (C3/C4) or more considerable decline \r (C1/C2). There is a clear distinction between the scenarios with no or "


id: 4b386321a46ed3dfa83ad6ce432e1cda
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 10481
content:
"At the time the Representative Concentration Pathways (RCPs) were published, they included three scenarios that could represent \r emission developments in the absence of climate policy: RCP4.5, RCP6 and RCP8.5, described as, respectively, low, medium and high\u0002end scenarios in the absence of strong climate policy (van Vuuren et al. 2011). RCP8.5 was described as representative of the top 5% \r scenarios in the literature. The SSPs-based set of scenarios covered the RCP forcing levels, adding a new low scenario (at 1.9 W m-2). \r Hausfather and Peters (2020) pointed out that since 2011, the rapid development of renewable energy technologies and emerging \r climate policy have made it considerably less likely that emissions could end up as high as RCP8.5. Still, emission trends in developing \r countries track RCP8.5 Pedersen et al. (2020), and high land-use emissions could imply that emissions would continue to do so in the \r [...]"


id: 9539b7e4126ff2f94bf391a41aefac0e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 23453
content:
"[...] future, even at the global scale (Schwalm et al. 2020). Other factors resulting in high emissions include higher population or economic \r growth as included in the SSPs (Section 3.3.1) or rapid development of new energy services. Climate projections of RCP8.5 can also \r result from strong feedbacks of climate change on (natural) emission sources and high climate sensitivity (AR6 WGI Chapter 7), and \r therefore their median climate impacts might also materialise while following a lower emission path (e.g., Hausfather and Betts 2020). \r The discussion also relates to a more fundamental discussion on assigning likelihoods to scenarios, which is extremely difficult given \r the deep uncertainty and direct relationship with human choice. However, it would help to appreciate certain projections (e.g., Ho \r et al. 2019). All in all, this means that high-end scenarios have become considerably less likely since AR5 but cannot be ruled out. It \r [...]"


id: ab7631ccb3be530aec1dd351307288fe
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 27396
content:
"[...] is important to realise that RCP8.5 and SSP5-8.5 do not represent a typical 'business-as-usual' projection but are only useful as high\u0002end, high-risk scenarios. Reference emission scenarios (without additional climate policy) typically end up in the C5-C7 categories \r included in this assessment."


id: 1492c62793a2c466f7f4d11be1c59a5d
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 844
content:
"For accounting of emissions and the substitution of different gases as \r part of a  mitigation strategy, typically, emission metrics are used to \r compare the climate impact of different gases. Most policies currently \r use Global Warming Potentials (GWPs) with a 100-year time horizon \r as this is also mandated for emissions reporting in the Paris Rulebook \r (for a  wider discussion of GHG metrics, see Box 2.1 in Chapter  2 of \r this report, and AR6 WGI, Chapter 7, Section 7.6). Alternative metrics \r have also been proposed, such as those using a shorter or longer time \r horizon, or those that focus directly on the consequences of reaching \r a certain temperature target (Global Temperature Change Potential - \r GTP), allowing a more direct comparison with cumulative CO2 emissions \r (Allen et al. 2016; Lynch et al. 2020) or focusing on damages (Global \r Damage Potential) (an overview is given in Chapter 2, and Cross-Chapter \r [...]"


id: 1fa74a6879c93caaca5f747f2950e7b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 2782
content:
"[...] Box 3 in Chapter 3). Depending on the metric, the value attributed to \r reducing short-lived forcers such as methane can be lower in the near \r term (e.g., in the case of GTP) or higher (GWP with a short reference \r period). For most metrics, however, the impact on mitigation strategies is \r relatively small, among others, due to the marginal abatement cost curve \r of methane (low costs for low-to-medium mitigation levels; expensive \r for high levels). The timing of reductions across different gases impacts \r warming and the co-benefits (Harmsen et al. 2016; Cain et al. 2019). \r Nearly all scenarios in the literature use GWP-100 in cost-optimisation, \r reflecting the existing policy approach; the use of GWP-100 deviates \r from cost-optimal mitigation pathways by at most a few percent for \r temperature goals that limit warming to 2degC (>67%) or lower (Box 2.1)."


id: b25ede09aa562768d8f8076158fa5763
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 28618
content:
"The trajectory of future CO2 emissions plays a critical role in mitigation, \r given CO2 long-term impact and dominance in total greenhouse gas \r forcing. As shown in Figure 3.12, CO2 dominates total greenhouse \r gas emissions in the high-emissions scenarios but is also reduced \r most, going from scenarios in the highest to lower categories. In C4 \r and below, most scenarios exhibit net negative CO2 emissions in the \r second half of the century compensating for some of the residual \r emissions of non-CO2 gases as well as reducing overall warming \r from an intermediate peak. Still, early emission reductions and further \r reductions in non-CO2 emissions can also lead to scenarios without \r net negative emissions in 2100, even in C1 and C3 (shown for the \r 85-95th percentile). In C1, avoidance of significant overshoot implies \r that immediate gross reductions are more relevant than long-term \r net negative emissions (explaining the lower number than in C2) but \r [...]"


id: dbbfec7c74e787871b0e9fcbde36cd65
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 35949
content:
"[...] carbon dioxide removal (CDR) is still playing a role in compensating \r for remaining positive emissions in hard-to-abate sectors."


id: 1a8aef826113dfa7472f21de05659f18
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 1873
content:
"CH4 and N2O emissions are also reduced from C7 to C1, but this mostly \r occurs between C7 and C5. The main reason is the characteristics \r of abatement potential: technical measures can significantly reduce \r CH4 and N2O emissions at relatively low costs to about 50% of the \r current levels (e.g., by reducing CH4 leaks from fossil fuel production \r and transport, reducing landfill emissions gazing, land management \r and introducing measures related to manure management, see also \r Chapter 7 and 11). However, technical potential estimates become \r exhausted even if the stringency of mitigation is increased (Harmsen \r et al. 2019a,b; Hoglund-Isaksson et al. 2020). Therefore, further \r reduction may come from changes in activity levels, such as switching \r to a less meat-intensive diet, therefore reducing livestock (Stehfest \r et al. 2009; Willett et al. 2019; Ivanova et al. 2020) (Chapter 7). Other \r non-CO2 GHG emissions (halogenated gases) are reduced to low \r [...]"


id: 1459c4f393557561319f51e8fb7e9225
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 798
content:
"The dominating role of CO2 and its long lifetime in the atmosphere \r and some critical characteristics of the Earth System implies that \r there is a  strong relationship between cumulative CO2 emissions \r and temperature outcomes (Allen et al. 2009; Matthews et al. 2009; \r Meinshausen et al. 2009; MacDougall and Friedlingstein 2015). This \r is illustrated in Figure 3.13, which plots the cumulative CO2 emissions \r against the projected outcome for global mean temperature, both until \r peak temperature and through to end of century (or 2100). The deviations \r from a linear relationship in Figure 3.13 are mostly caused by different \r non-CO2 emission and forcing levels (see also Rogelj et al. 2015b). This \r means that reducing non-CO2 emissions can play an important role \r in limiting peak warming: the smaller the residual non-CO2 warming, \r the larger the carbon budget. This impact on carbon budgets can be \r substantial for stringent warming limits. For 1.5degC pathways, variations \r [...]"


id: 4d9d014eb13e443afebc6499cca2f316
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 10932
content:
"[...] in non-CO2 warming across different emission scenarios have been \r found to vary the remaining carbon budget by approximately 220 GtCO2 \r (AR6 WGI Chapter 5, Section 5.5.2.2). In addition to reaching net zero \r CO2 emissions, a strong reduction in methane emissions is the most \r critical component in non-CO2 mitigation to keep the Paris climate goals \r in reach (Collins et al. 2018; van Vuuren et al. 2018) (see also AR6 WGI, \r Chapters 5, 6 and 7). It should be noted that the temperature categories \r (C1-C7) generally aligned with the horizontal axis, except for the end\u0002of-century values for C1 and C2 that coincide."


id: eb79a2594e85fe7ca07072d5186ce28e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 38786
content:
"Short-lived climate forcers (SLCFs) also play an important role in climate \r change, certainly for short-term changes (AR6 WGI, Figure  SPM.2) \r (Shindell et al. 2012). These forcers consist of (i) substances contributing \r to warming, such as methane, black carbon and tropospheric ozone, \r and (ii) substances contributing to cooling (other aerosols, such as \r related to sulphur emissions). Most SLCFs are also air pollutants, and \r reducing their emissions provides additional co-benefits (Shindell et al. \r 2017a,b; Hanaoka and Masui 2020). In the case of the first group, \r emission reduction thus leads to both air pollution and climate benefits. \r For the second, group there is a possible trade-off (Shindell and Smith \r 2019; Lund et al. 2020). As aerosol emissions are mostly associated \r with fossil fuel combustion, the benefits of reducing CO2 could, in \r the short term, be reduced as a result of lower aerosol cooling. There \r [...]"


id: 5345af9c833f02f2bbafd6cb1a4b7dd0
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 11921
content:
"[...] has been an active discussion on the exact climate contribution of \r SLCF-focused policies in the literature. This discussion partly emerged \r from different assumptions on possible reductions in the absence of \r ambitious climate policy and the uncertain global climate benefit from \r aerosol (black carbon) (Rogelj et al. 2014). The latter is now assessed to \r be smaller than originally thought (Takemura and Suzuki 2019; Smith \r et al. 2020b) (see also AR6 WGI Section 6.4). Reducing SLCF emissions \r is critical to meet long-term climate goals and might help reduce \r the rate of climate change in the short term. Deep SLCF emission \r reductions also increase the remaining carbon budget for a specific \r temperature goal (Rogelj et al. 2015a; Reisinger et al. 2021) (Box 3.4). \r A more detailed discussion can be found in AR6 WGI Chapters 5 and 6."


id: facf11bdf15bb5e2a1abc3c0ae01132a
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 41502
content:
"The AR6 WGI estimated the remaining carbon budgets from their assessment of (i) the transient climate response to cumulative \r emissions of carbon dioxide (TCRE), and estimates of (ii) the historical human-induced warming, (iii) the temperature change after \r reaching net zero CO2 emissions, (iv) the contribution of future non-CO2 warming (derived from the emissions scenarios assessed in \r the Special Report on 1.5degC Warming using WGI-calibrated emulators), and (v) the Earth System feedbacks (AR6 WGI Chapter 5.5, \r Box 5.2). For a given warming level, AR6 WGI assessed the remaining carbon budget from the beginning of 2020 onwards. These are \r 650/500/400 GtCO2 for limiting warming to 1.5degC with 33%/50%/ 67% chance and 1350/1150 GtCO2 for limiting warming to 2degC \r with 50%/67% chance. The estimates are subject to considerable uncertainty related to historical warming, future non-CO2 forcing, \r [...]"


id: 6ec2ea82667e836ad7194507e5e14686
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 16755
content:
"[...] and poorly quantified climate feedbacks. For instance, variation in non-CO2 emissions across scenarios are estimated to either increase \r or decrease the remaining carbon budget estimates by 220 GtCO2. The estimates of the remaining carbon budget assume that non\u0002CO2 emissions are reduced consistently with the tight temperature targets for which the budgets are estimated."


id: fc2dc08122b5466fc839833c56446adb
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 41731
content:
"Estimates of the remaining carbon budgets thus vary with the assumed level of non-CO2 emissions, which are a function of policies \r and technology development. The linear relationship used in the AR6 WGI assessment between peak temperature and the warming \r as a result of non-CO2 emissions (based on the SR1.5 data) is shown in the right panel of Figure 2 (dashed line). In the AR6 WGIII \r approach, the non-CO2 warming for each single scenario is based on the individual scenario characteristics. This is shown in the same \r figure by plotting the outcomes of scenario outcomes of a range of models (dots). The lines show the fitted data for individual models, \r emphasising the clear differences across models and the relationship with peak warming (policy level). In some scenarios, stringent \r non-CO2 emission reductions provide an option to reach more stringent climate goals with the same carbon budget. This is especially \r [...]"


id: 76df08b30e2066b93658ba720f429009
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 18124
content:
"[...] the case for scenarios with a very low non-CO2 warming, for instance, as a result of methane reductions through diet change. The \r left panel shows how these differences impact estimates of the remaining carbon budget. While the AR6 scenarios database includes \r a broad range of non-CO2 emission projections the overall range is still very consistent with the WGI relationship and the estimated \r uncertainty with a +-220 GtCO2 range (see also Figure 5 in Annex III.II.2.5.1)."


id: 377c39640e8d29dce2d2b30070d15b9e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 6973
content:
"Overall, the slight differences between the cumulative emissions in AR6 WGIII and the carbon budget in AR6 WGI are because the \r non-CO2 warming in the WGIII scenarios is slightly lower than in the SR1.5 scenarios that are used for the budget estimates in WGI \r (Annex III.2.5.1). In addition, improved consistency with Cross-Chapter Box 7.1 in Chapter 7, AR6 WGI results in a non-CO2-induced \r temperature difference of about about 0.05K between the assessments. Recalculating the remaining carbon budget using the WGI \r methodology combined with the full AR6 WGIII scenario database results in a reduction of the estimated remaining 1.5degC carbon \r budget by about 100 GtCO2 (-20%), and a reduction of about 40 GtCO2 (-3%) for 2degC. Accounting also for the categorisation effect, \r the difference between the WGI and WGIII estimates is found to be small and well within the uncertainty range (Figure 1). This means \r [...]"


id: a7fa39c575af047d3385718ce81cb7dc
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 26763
content:
"[...] that the cumulative CO2 emissions presented in WGIII and the WGI carbon budgets are highly consistent."


id: 8c497238f10c27c6523a74cffa1880ac
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 21858
content:
"Box 3.4, Figure 2 | (a) Differences in regressions of the relationship between peak surface temperature and associated cumulative CO2 emissions \r from 2020 derived from scenarios of eight integrated assessment model frameworks. The coloured lines show the regression at median for scenarios of \r the eight modelling frameworks, each with more than 20 scenarios in the database and a detailed land-use representation. The red dotted lines indicate the non-CO2\r uncertainty range of AR6 WGI Chapter 5 (+-220 GtCO2), here visualised around the median of the eight model framework lines. Carbon budgets from 2020 until 1.5degC \r (0.43K above 2010-2019 levels) and 2.0degC (0.93K above 2010-2019 levels) are shown for minimum and maximum model estimates at the median, rounded to the \r nearest 10 GtCO2. Panel (b) shows the relationship between the estimated non-CO2 warming in mitigation scenarios that reach net zero and the associated peak \r [...]"


id: 4bbc10d1f781f66a822abc4da24b2ca9
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 10581
content:
"[...] surface temperature outcomes. The coloured lines show the regression at median for scenarios of the eight modelling frameworks with more than 20 scenarios in the \r database and a detailed land-use representation. The black dashed line indicates the non-CO2 relationship based on the scenarios and climate emulator setup as was \r assessed in AR6 WGI Chapter 5."


id: 8c6d3fa515296e945c660c800a6707ec
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 21891
content:
"systems. For the energy systems, these negative emissions originate \r from bioenergy with carbon capture and storage (BECCS), while \r for AFOLU, they originate from reforestation and afforestation. For \r C3-C5, reforestation has a  larger CDR contribution than BECCS, \r mostly due to considerably lower costs (Rochedo et al. 2018). For C1 \r and C2, the tight carbon budgets imply in many scenarios more CDR \r use (Riahi et al. 2021). Please note that net negative emissions are not \r so relevant for peak-temperature targets, and thus the C1 category, \r but CDR can still be used to offset the remaining positive emissions \r (Riahi et al. 2021). While positive CO2 emissions from fossil fuels are \r significantly reduced, inertia and hard-to-abate sectors imply that \r in many C1-C3 scenarios, around 800-1000 GtCO2 of net positive \r cumulative CO2 emissions remain. This is consistent with literature \r estimates that current infrastructure is associated with 650 GtCO2\r [...]"


id: 6b21bf6b1b54b91e0fab6d1bb52978ff
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 16144
content:
"[...] (best estimate) if operated until the end of its lifetime (Tong et al. \r 2019). These numbers are considerably above the estimated carbon \r budgets for  1.5degC estimated in AR6 WGI, hence explaining CDR \r reliance (either to offset emissions immediately or later in time)."


id: f3ad763ab2cb72484af82dcbe9018b10
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 40245
content:
"Creating net negative emissions can thus be an important part of \r a mitigation strategy to offset remaining emissions or compensate \r for emissions earlier in time. As indicated above, there are different \r ways to potentially achieve this, including reforestation and \r afforestation and BECCS (as often covered in IAMs) but also soil \r carbon enhancement, direct air carbon capture and storage (DACCS) \r and ocean alkalinisation (Chapter 12). Except for reforestation, these \r options have not been tested at large scale and often require more R&D. \r Moreover, the reliance on CDR in scenarios has been discussed given \r possible consequences of land use related to biodiversity loss and \r food security (BECCS and afforestation), the reliance on uncertain \r storage potentials (BECCS and DACCS), water use (BECCS), energy \r use (DACCS), the risks of possible temperature overshoot and the \r consequences for meeting Sustainable Development Goals (SDGs) \r [...]"


id: 8ee3e9c872718742f81f90d5f9962aa9
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 22325
content:
"[...] (Anderson and Peters 2016; Smith et al. 2016; Venton 2016; Peters \r and Geden 2017; van Vuuren et al. 2017; Honegger et al. 2021). In \r the case of BECCS, it should be noted that bioenergy typically is \r associated with early-on positive CO2 emissions and net negative \r effects are only achieved in time (carbon debt), and its potential is \r limited (Cherubini et al. 2013; Hanssen et al. 2020); most IAMs have \r only a very limited representation of these time dynamics. Several \r scenarios have therefore explored how reliance on net negative CO2 \r emissions can be reduced or even avoided by alternative emission \r strategies (Grubler et al. 2018; van Vuuren et al. 2018) or early \r reductions by more stringent emission reduction in the short term \r (Rogelj et al. 2019b; Riahi et al. 2021). A more in-depth discussion \r of land-based mitigation options can be found in Chapter 7. It needs \r to be emphasised that even in strategies with net negative CO2 \r [...]"


id: 1bea1e64110c3282690c52a987329aae
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 2094
content:
"[...] emissions, the emission reduction via more conventional mitigation \r measures (efficiency improvement, decarbonisation of energy supply) \r is much larger than the CDR contribution (Tsutsui et al. 2020)."


id: e0d50334c2efaf834bd7606a6a05b1fe
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 36816
content:
"Figure  3.14 shows that there is a  relationship between the \r temperature target, the cumulative CO2 emissions budget, and the net \r zero year for CO2 emissions (panel a) and the sum of greenhouse \r gases (panel b) for the scenarios published in the literature. In other \r words, the temperature targets from the Paris Agreement can, to \r some degree, be translated into a  net-zero emission year (Tanaka \r and  O'Neill 2018). There is, however, a  considerable spread. In \r addition to the factors influencing the emission budget (AR6 WGI \r and Section  3.3.2.2), this is influenced by the emission trajectory \r until net zero is reached, decisions related to temperature overshoot \r and non-CO2 emissions (especially for the moment CO2 reaches net \r zero emissions). Scenarios with limited or no net negative emissions \r and rapid near-term emission reductions can allow small positive \r emissions (e.g., in hard-to-abate-sectors). They may therefore have \r [...]"


id: 35e9539e34c2f9d483861334907012f7
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 6729
content:
"[...] a later year that net zero CO2 emissions are achieved. High emissions \r in the short term, in contrast, require an early net zero year."


id: 89d057d278c2bb1a6cf74eb908e00c1a
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 21414
content:
"For the scenarios in the C1 category (limit warming to 1.5degC (>50% \r with no or limited overshoot, the net zero year for CO2 emissions \r is typically around 2035-2070. For scenarios in C3 (limiting \r warming to 2degC (>67%)), CO2 emissions reach net zero around \r after 2050. Similarly, also the years for net zero GHG emissions \r can be calculated (see Fig 3.14b. The GHG net zero emissions year \r is typically around 10-40 years later than the carbon neutrality. \r Residual non-CO2 emissions at the time of reaching net zero CO2\r range between 5-11 GtCO2-eq in pathways that limit warming to \r 2degC (>67%) or lower. In pathways limiting warming to 2degC (>67%), \r methane is reduced by around 19% (3-46%) in 2030 and 46% (29-\r 64%) in 2050, and in pathways limiting warming to 1.5degC (>50%) \r with no or limited overshoot by around 34% (21-57%) in 2030 and \r a  similar 51% (35-70%) in 2050. Emissions-reduction potentials \r assumed in the pathways become largely exhausted when limiting \r [...]"


id: 832ec1097bd5150f7d6be40737c1011f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 20205
content:
"[...] warming to 2degC (>50%). N2O emissions are reduced too, but similar \r to CH4, emission reductions saturate for stringent climate goals. \r In the mitigation pathways, the emissions of cooling aerosols are \r reduced due to reduced use of fossil fuels. The overall impact on non\u0002CO2-related warming combines these factors."


id: dde04e5fdde0fc196ef7b6f996bc3a23
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 36296
content:
"In addition to the constraints on change in global mean temperature, \r the Paris Agreement also calls for reaching a  balance of sources \r and sinks of GHG emissions (Art. 4). Different interpretations of the \r concept related to balance have been published (Rogelj et al. 2015c; \r Fuglestvedt et al. 2018). Key concepts include that of net zero CO2\r emissions (anthropogenic CO2 sources and sinks equal zero) and net \r zero greenhouse gas emissions (see Annex I: Glossary, and Box 3.3). \r The same notion can be used for all GHG emissions, but here \r ranges also depend on the use of equivalence metrics (Box  2.1). \r Moreover, it should be noted that while reaching net zero CO2\r emissions typically coincides with the peak in temperature increase; \r net zero GHG emissions (based on GWP-100) imply a  decrease in \r global temperature (Riahi et al. 2021) and net zero GHG emissions \r typically require negative CO2 emissions to compensate for the \r [...]"


id: a2a2b1bf5e456bdcc022c18b5a0a1bf8
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 25831
content:
"[...] remaining emissions from other GHGs. Many countries have started \r to formulate climate policy in the year that net zero emissions (either \r CO2 or all greenhouse gases) are reached - although, at the moment, \r formulations are often still vague (Rogelj et al. 2021). There has \r been increased attention on the timing of net zero emissions in the \r scientific literature and ways to achieve it."


id: 286c181fa503bf79efbbcf5732981868
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 4317
content:
"In cost-optimal scenarios, regions will mostly achieve net zero \r emissions as a function of options for emission reduction, CDR, and \r expected baseline emission growth (van Soest et al. 2021b). This \r typically implies relatively early net zero emission years in scenarios \r for the Latin America region and relatively late net zero years for \r Asia and Africa (and average values for OECD countries). However, an \r allocation based on equity principles (such as responsibility, capability \r and equality) might result in different net zero years, based on the \r principles applied - with often earlier net zero years for the OECD \r (Fyson et al. 2020; van Soest et al. 2021b). Therefore, the emission \r trajectory until net zero emissions is a critical determinant of future \r warming (Section 3.5). The more CO2 is emitted until 2030, the less \r CO2 can be emitted after that to stay below a warming limit (Riahi \r et al. 2015). As discussed before, also non-CO2 forcing plays a key \r [...]"


id: b48bfb72295a971f8d9a21ffdc55266b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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vector_id: 29009
content:
"Authors: Elmar Kriegler (Germany), Alaa Al Khourdajie (United Kingdom/Syria), Edward Byers (Austria/Ireland), Katherine Calvin (the \r United States of America), Leon Clarke (the United States of America), Annette Cowie (Australia), Navroz Dubash (India), Jae Edmonds \r (the United States of America), Jan  S. Fuglestvedt (Norway), Oliver Geden (Germany), Giacomo Grassi (Italy/European Union), \r Anders Hammer Stromman (Norway), Frank Jotzo (Australia), Alexandre Koberle (Brazil/United Kingdom), Franck Lecocq (France), \r Yun Seng Lim (Malaysia), Eric Masanet (the United States of America), Toshihiko Masui (Japan), Catherine Mitchell (United Kingdom), \r Gert-Jan Nabuurs (the Netherlands), Anthony Patt (the United States of America/Switzerland), Glen  P. Peters (Norway/Australia), \r Andy  Reisinger (New Zealand), Keywan Riahi (Austria), Joeri Rogelj (United Kingdom/Belgium), Yamina Saheb (France/Algeria), \r [...]"


id: 41e8f0b6081aeec619613f63ab729245
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 8789
content:
"[...] Jim Skea (United Kingdom), Detlef P. van Vuuren (the Netherlands), Harald Winkler (Republic of South Africa)"


id: a0a4398acb1c309b9c6827f75a6881da
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 25471
content:
"Net zero CO2 emissions are reached between 2050-2055 (2035-2070) in global emissions pathways limiting warming \r to 1.5degC (>50%) with no or limited overshoot, and between 2070-2075 (2055-...) in pathways limiting warming to 2degC \r (>67%) as reported in the AR6 scenarios database (median five-year interval and 5-95th percentile ranges).5\r  The variation of \r non-CO2 emissions in 1.5degC-2degC pathways varies the available remaining carbon budget which can move the time of reaching net \r zero CO2 in these pathways forward or backward.6\r  The shape of the CO2 emissions reduction profile also affects the time of reaching \r net zero CO2 (Figure 1c in this Cross-Chapter Box). Global emission pathways that more than halve CO2 emissions from 2020 to 2030 \r can follow this rapid reduction by a more gradual decline towards net zero CO2 and still limit warming to 1.5degC with no or limited \r [...]"


id: cb781039fbb63f0a92dfa0b8cc8269e7
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 33124
content:
"[...] overshoot, reaching the point of net zero after 2050. The literature since SR1.5 included a larger fraction of such pathways than were \r available at the time of SR1.5. This is the primary reason for the small backward shift in the median estimate of reaching global net \r zero CO2 emissions in 1.5degC pathways collected in the AR6 scenario database compared to SR1.5. This does not mean that the world \r is assessed to have more time to rapidly reduce current emissions levels compared to SR1.5. The assessment of emissions reductions \r by 2030 and 2040 in pathways limiting warming to 1.5degC (>50%) with no or limited overshoot has not changed substantially. It only \r means that the exact timing of reaching net zero CO2 after a steep decline of CO2 emissions until 2030 and 2040 can show some \r variation, and the SR1.5 median value of 2050 is still close to the middle of the current range (Figure 1c in this Cross-Chapter Box)."


id: 3abe349352f372a9e2ce6800b793325a
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 7536
content:
"Global net zero GHG emissions measured in terms of GWP-100 are reached between 2095 and 2100 (2050-...)10 in \r emission pathways limiting warming to 1.5degC (>50%) with no or limited overshoot (median and 5-95th percentile).\r Around 50% of pathways limiting warming to 1.5degC (>50%) with no or limited overshoot and 70% of pathways limiting warming \r to 2degC (>67%) do not reach net zero GHG emissions in terms of GWP-100 before 2100. These pathways tend to show less reduction \r in warming after the peak than pathways that reach net zero GHG emissions. For the subset of pathways that reach net zero GHG \r emissions before 2100, including around 90% of pathways that return warming to 1.5degC after a high overshoot (>0.1degC) by 2100, \r the time lag between reaching net zero CO2 and net zero GHG is 12-14 (7-39) years and the amount of net negative CO2 emissions \r deployed to balance non-CO2 emissions at the time of net zero GHG is around -7 (-10 to -4) GtCO2 (range of medians and lowest \r [...]"


id: 677e5b62f441afd1875e8bf748c986d2
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 15478
content:
"[...] 5th to highest 95 percentile across the four scenario classes that limit median warming to 2degC or lower) (Section 3.3 and Table 3.2)."


id: 2451cb00e8390dee5c6ca0e42e7c2e2f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 3581
content:
"The timing of net zero CO2 or GHG emissions may differ across regions and sectors. Achieving net zero emissions globally \r implies that some sectors and regions must reach net zero CO2 or GHG ahead of the time of global net zero CO2 or GHG if \r others reach it later. Similarly, some sectors and regions would need to achieve net negative CO2 or GHG emissions to compensate \r for continued emissions by other sectors and regions after the global net zero year. Differences in the timing to reach net zero \r emissions between sectors and regions depend on multiple factors, including the potential of countries and sectors to reduce GHG \r emissions and undertake carbon dioxide removal (CDR), the associated costs, and the availability of policy mechanisms to balance \r emissions and removals between sectors and countries (Fyson et al. 2020; Strefler et al. 2021a; van Soest et al. 2021b). A lack of such \r [...]"


id: 37044a1302e6bc2341372e04d9dc2ff1
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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vector_id: 6906
content:
"[...] mechanisms could lead to higher global costs to reach net zero emissions globally, but less interdependencies and institutional needs \r (Fajardy and Mac Dowell 2020). Sectors will reach net zero CO2 and GHG emissions at different times if they are aiming for such \r targets with sector-specific policies or as part of an economy-wide net zero emissions strategy integrating emissions reductions and \r removals across sectors. In the latter case, sectors with large potential for achieving net negative emissions would go beyond net zero \r to balance residual emissions from sectors with low potential, which in turn would take more time compared to the case of sector\u0002specific action. Global pathways project global AFOLU emissions to reach global net zero CO2 the earliest, around 2030 to 2035 in \r pathways to limit warming to 2degC (>67%) or lower, by rapid reduction of deforestation and enhancing carbon sinks on land, although \r [...]"


id: e6e22b03e21d69fce0f592a6ee0fd263
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 37911
content:
"[...] net zero GHG emissions from global AFOLU are typically reached 30 years later, if at all. The ability of global AFOLU CO2 emissions to \r reach net zero as early as in the 2030s in modelled pathways hinges on optimistic assumptions about the ability to establish global \r cost-effective mechanisms to balance emissions reductions and removals across regions and sectors. These assumptions have been \r challenged in the literature and the Special Report on Climate Change and Land (IPCC SRCCL)."


id: a9c05c83c3f638820ba5927fd6f30b5d
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 27089
content:
"The accounting of anthropogenic carbon dioxide removal on land matters for the evaluation of net zero CO2 and net zero \r GHG strategies. Due to the use of different approaches between national inventories and global models, the current net CO2 emissions \r are lower by 5.5 GtCO2, and cumulative net CO2 emissions in modelled 1.5degC-2degC pathways would be lower by 104-170 GtCO2, if carbon \r dioxide removals on land are accounted based on national GHG inventories. National GHG inventories typically consider a much larger \r area of managed forest than global models, and on this area additionally consider the fluxes due to human-induced global environmental \r change (indirect effects) to be anthropogenic, while global models consider these fluxes to be natural. Both approaches capture the same \r land fluxes, only the accounting of anthropogenic vs natural emissions is different. Methods to convert estimates from global models \r [...]"


id: 7be390c7b1572facca0d813f922e2ef0
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 19007
content:
"[...] to the accounting scheme of national GHG inventories will improve the use of emission pathways from global models as benchmarks \r against which collective progress is assessed. (Section 7.2.2.5)."


id: a435afd465b8cc59cdf09049939a8677
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 26081
content:
"Table  3.2 summarises the key characteristics for all temperature \r categories in terms of cumulative CO2 emissions, near-term \r emission reductions, and the years of peak emission and net \r zero CO2 and GHG emissions. The table shows again that many \r pathways in the literature limit global warming to 2degC (>67%) \r or limit warming to  1.5degC (>50%) with no or limited overshoot \r compared to pre-industrial levels. Cumulative net CO2 emissions \r from the year 2020 until the time of net zero CO2 in pathways \r that limit warming to 1.5degC (>50%) with no or limited overshoot \r are 510 (330-710) GtCO2 and in pathways that limit warming \r to 2degC (>67%), 890 (640-1160) GtCO2 (see also Cross-Chapter \r Box 3 in this chapter). Mitigation pathways that limit warming to \r 2degC (>67%) compared to pre-industrial levels are associated with \r net global GHG emissions of 44 (32-55) GtCO2-eq yr-1 by 2030 \r and 20 (13-26) GtCO2-eq yr-1 in 2050. These correspond to GHG \r [...]"


id: d1eb918fc287866dbe093d573b9346be
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updated_at: 2023-04-19 13:23:08
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vector_id: 34280
content:
"[...] emissions reductions of 21% (1-42%) by 2030, and 64% (53-77%) \r by 2050 relative to 2019 emission levels. Pathways that limit \r global warming to  1.5degC (>50%) with no or limited overshoot \r require a  further acceleration in the pace of the transformation, \r with GHG emissions reductions of 43% (34-60%) by 2030 and \r 84% (73-98%) in 2050 relative to modelled 2019 emission levels. \r The likelihood of limiting warming to below  1.5degC (>50%) with \r no or limited overshoot of the most stringent mitigation pathways \r in the literature (C1) has declined since SR1.5. This is because \r emissions have risen since 2010 by about 9 GtCO2 yr-1, resulting \r in relatively higher near-term emissions of the AR6 pathways by \r 2030 and slightly later dates for reaching net zero CO2 emissions \r compared to SR1.5."


id: 42f80d4560b63c50b3a3765a6e8973c3
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vector_id: 8981
content:
"[...] ranges, the median warming for every pathway in that category is calculated for each of the two climate model emulators (MAGICC and FaIR). Subsequently, the 5th and \r 95th percentile values across all pathways for each emulator are calculated. The coolest and warmest outcomes (i.e., the lowest p5 of two emulators, and the highest p95, \r respectively) are shown in square brackets. These ranges therefore cover both the uncertainty of the emissions pathways as well as the climate emulators' uncertainty."


id: e5ff5ad862f8af8cc5283ee4578811
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 37758
content:
"i\r  Emissions milestones are provided for five-year intervals in order to be consistent with the underlying five-year time-step data of the modelled pathways. Peak emissions \r (CO2 and GHGs) are assessed for five-year reporting intervals starting in 2020. The interval 2020-2025 signifies that projected emissions peak as soon as possible between \r 2020 and at latest before 2025. The upper five-year interval refers to the median interval within which the emissions peak or reach net zero. Ranges in square brackets \r underneath refer to the range across the pathways, comprising the lower bound of the 5th percentile five-year interval and the upper bound of the 95th percentile five-year \r interval. Numbers in round brackets signify the fraction of pathways that reach specific milestones.\r j\r  Percentiles reported across all pathways in that category include those that do not reach net zero before 2100 (fraction of pathways reaching net zero is given in round \r [...]"


id: 575953ab0ce10b66f361e07a6c69f13d
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updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 12629
content:
"The share of renewables is around 30-70% in the scenarios that \r limit warming to 2degC (>67%) and clearly above 40% for scenarios \r that limit warming   1.5degC (>50%) (panel  c). Scenarios have been \r published with 100% renewable energy systems even at a  global \r scale, partly reflecting the rapid progress made for these technologies \r in the last decade (Creutzig et al. 2017; Jacobson et al. 2018; Breyer \r and Jefferson 2020). These scenarios do not show in the graph due to \r a lack of information from non-energy sources. There is a debate in \r the literature on whether it is possible to achieve a 100% renewable \r energy system by 2050 (Brook et al. 2018). This critically depends on \r assumptions made on future system integration, system flexibility, \r storage options, consequences for material demand and the ability \r to supply high-temperature functions and specific mobility functions \r with renewable energy. The range of studies published showing \r [...]"


id: 56274b290ba40d61bb7698b5aa04aa77
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updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 12433
content:
"[...] 100% renewable energy systems show that it is possible to design \r such systems in the context of energy system models (Hong et al. "


id: 8d42a811afa6cb3dfa603fdc1025ed98
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 22033
content:
"At the moment, climate change impact on mitigation potential is hardly \r considered in model-based scenarios. While a detailed overview of \r climate impacts is provided in IPCC AR6 WGII and Section 3.6 discusses \r the economic consequences, here we concentrate on the implications \r for mitigation potential. Climate change directly impacts the carbon \r budget via all kinds of feedbacks - which is included in the ranges \r provided for the carbon budget (e.g., 300-900 GtCO2 for 17th-83rd \r percentile for not exceeding 1.5degC; see AR6 WGI Chapter 5, 2021). \r Climate change, however, alters the production and consumption \r of energy (Section 6.5). An overview of the literature is provided by \r Yalew et al. (2020). In terms of supply, impacts could influence the \r cooling capacity of thermal plants, the potential and predictability of \r renewable energy, and energy infrastructure (van Vliet et al. 2016; \r Turner et al. 2017; Cronin et al. 2018a; Lucena et al. 2018; Yalew \r [...]"


id: b6ae42076bc6e368d9495a21ca3ef82d
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vector_id: 29341
content:
"[...] et al. 2020; Gernaat et al. 2021). Although the outcomes of these \r studies differ, they seem to suggest that although impacts might be \r relatively small at the global scale, they could be substantial at the \r regional scale (increasing or decreasing potential). Climate change \r can also impact energy demand, with rising temperatures resulting \r in decreases in heating demand and increases in cooling demand \r (Isaac and van Vuuren 2009; Zhou et al. 2014; Labriet et al. 2015; \r McFarland et al. 2015; Auffhammer et al. 2017; Clarke et al. 2018; \r van Ruijven et al. 2019; Yalew et al. 2020). As expected, the increase \r in cooling demand dominates the impact in warm regions and \r decreases in heating demand in cold regions (Isaac and van Vuuren \r 2009; Zhou et al. 2014; Clarke et al. 2018). Globally, most studies \r show a net increase in energy demand at the end of the century due \r to climate impacts (Isaac and van Vuuren 2009; Clarke et al. 2018; \r [...]"


id: 7fbad0f641f137180f31e76d3db98861
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 19606
content:
"[...] van Ruijven et al. 2019); however, one study shows a net decrease \r (Labriet et al. 2015). Only a  few studies quantify the combined \r impacts of climate change on energy supply and energy demand \r (McFarland et al. 2015; Mima and Criqui 2015; Emodi et al. 2019; "


id: 49092f229ea001edd3df4401429d5ece
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 10072
content:
"Climate change can impact the potential for AFOLU mitigation \r action by altering terrestrial carbon uptake, crop yields and \r bioenergy potential (Chapter  7). Carbon sequestration in forests \r may be positively or adversely affected by climate change \r and  CO2 fertilisation. On the one hand, elevated CO2 levels and \r higher temperatures could enhance tree growth rates, carbon \r sequestration, and timber and biomass production (Beach et al. \r 2015; Kim et al. 2017; Anderegg et al. 2020). On the other hand, \r climate change could lead to greater frequency and intensity of \r disturbance events in forests, such as fires, prolonged droughts, \r storms, pests and diseases (Kim et al. 2017; Anderegg et al. 2020). \r The impact of climate change on crop yields could also indirectly \r impact the availability of land for mitigation and AFOLU emissions \r (Calvin et al. 2013; Bajzelj and Richards 2014; Kyle et al. 2014; Beach \r [...]"


id: 36744c0319b2eb6bbd79fe74d06dad7e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 6817
content:
"[...] et al. 2015; Meijl et al. 2018). The impact is, however, uncertain, as \r discussed in AR6 WGII Chapter 5. A few studies estimate the effect \r of climate impacts on AFOLU on mitigation, finding increases in \r carbon prices or mitigation costs by 1-6% in most scenarios (Calvin \r et al. 2013; Kyle et al. 2014)."


id: e7244938beddb67c5154891c2ffe6517
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 37964
content:
"This section describes the role of sectors in long-term emissions \r pathways (Table  3.3). We discuss both sectoral aspects of IAM \r pathways and some insights from sectoral studies. Sectoral studies \r typically include more detail and additional mitigation options \r compared to IAMs. However, sectoral studies miss potential \r feedbacks and cross-sectoral linkages that are captured by IAMs. \r Additionally, since IAMs include all emissions sources, these models \r can be used to identify pathways to particular climate goals. In such \r pathways, emissions are balanced across sectors typically based \r on relative marginal abatement costs; as a result, some sectors are \r sources and some are sinks at the time of net zero CO2 emissions. \r For these reasons, the mitigation observed in each sector in an IAM \r may differ from the potential in sectoral studies. Given the strengths \r and limitations of each type of model, IAMs and sectoral models are \r [...]"


id: 1bab666db20dc62352ead251c2cedc8e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 2053
content:
"A small number of mitigation pathways include stringent demand\u0002side mitigation, including changes in thermostat set points \r (van Sluisveld et al. 2016; van Vuuren et al. 2018), more efficient or \r smarter  appliances (van Sluisveld et al. 2016; Grubler et al. 2018; \r Napp  et al. 2019), increased recycling or reduced industrial goods \r (Liu  et al. 2018; van  Sluisveld et al. 2016; Grubler et al. 2018; \r van  de  Ven et al. 2018; Napp et al. 2019), telework and travel \r avoidance (Grubler et al. 2018; van de Ven et al. 2018), shifts to public \r transit (van  Sluisveld et al. 2016; Grubler et al. 2018; van Vuuren \r et al. 2018), reductions in food waste (van de Ven et al. 2018) and \r less meat-intensive diets (Liu et al. 2018; van de Ven et al. 2018; \r van Vuuren et al. 2018). These pathways show reduced dependence \r on CDR and reduced pressure on land (Grubler et al. 2018; Rogelj et al. \r 2018a; van de Ven et al. 2018; van Vuuren et al. 2018) (Section 5.3.3). \r [...]"


id: 5652c088f5145de50cd52b2ba90e92ba
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 12453
content:
"[...] However, the representation of these demand-side mitigation \r options in IAMs is limited, with most models excluding the costs of \r such changes (van Sluisveld et al. 2016), using stylised assumptions \r to represent them (van den Berg et al. 2019), and excluding rebound \r effects (Krey et al. 2019; Brockway et al. 2021). Furthermore, there \r are questions about the achievability of such pathways, including \r whether the behavioural changes included are feasible (Azevedo \r et al. 2021) and the extent to which development and demand can \r be decoupled (Steckel et al. 2013; Brockway et al. 2021; Keysser and \r Lenzen 2021; Semieniuk et al. 2021)."


id: 2edf23ade5f9405ac0ebf8c6bf19143d
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 5523
content:
"So, while pathways indicate some flexibility in emissions \r reductions across sectors, all pathways involve substantial CO2\r emissions reductions in all sectors and regions (high confidence) \r (Luderer et al. 2018; Rogelj et al. 2018a,b; Mejean et al. 2019; \r Azevedo et al. 2021). Projected CO2 emissions reductions between \r 2019 and 2050 in  1.5degC (>50%) pathways with no or limited \r overshoot are around 77% for energy demand, with a  5-95% \r range of 31-96%,12 115% for energy supply (90-167%), and \r 148% for AFOLU (94-387%). In pathways that limit warming to \r 2degC (>67%), projected CO2 emissions are reduced between 2019 \r and 2050 by around 49% for energy demand, 97% for energy \r supply, and 136% for AFOLU (Sections 3.4.2-3.4.6). Almost 75% \r of GHG reductions at the time of net zero GHG are from the \r energy system, 13% are from AFOLU CO2, and 13% from non-CO2\r (Figure 3.21). These reductions are achieved through a variety of \r [...]"


id: 148af5ed8b637783aaa6194017b9c00a
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 839
content:
"[...] sectoral strategies, illustrated in Figure  3.21 (Figure  3.21b), and \r described in Sections 3.4.2 to 3.4.7; the primary strategies include \r declines in fossil energy, increases in low-carbon energy use, and \r CDR to address residual emissions."


id: 1164199896a5a126e37af76ac64f77cc
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 253
content:
"In the context of mitigation pathways, only a  few studies have \r examined solar radiation modification (SRM), typically focusing on \r Stratospheric Aerosol Injection (Arinoa et al. 2016; Emmerling and \r Tavoni 2018a,b; Heutel et al. 2018; Helwegen et al. 2019; Rickels \r et al. 2020; Belaia et al. 2021). These studies find that substantial \r mitigation is required to limit warming to a given level, even if SRM \r is available (Moreno-Cruz and Smulders 2017; Emmerling and Tavoni \r 2018b; Belaia et al. 2021). SRM may reduce some climate impacts, \r reduce peak temperatures, lower mitigation costs, and extend the \r time available to achieve mitigation; however, SRM does not address \r ocean acidification and may involve risks to crop yields, economies, \r human health, or ecosystems (AR6 WGII Chapter 16; AR6 WGI TS and \r Chapter 5; SR1.5 SPM; and Cross-Working Group Box 4 in Chapter 14 \r of this report). There are also significant uncertainties surrounding \r [...]"


id: 4366cd92ee11f62ae108551af63c1d7d
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 9077
content:
"[...] SRM, including uncertainties on the costs and risks, which can \r substantially alter the amount of SRM used in modelled pathways \r (Tavoni et al. 2017; Heutel et al. 2018; IPCC 2018; Helwegen \r et al. 2019; NASEM 2021). Furthermore, the degree of international \r cooperation can influence the amount of SRM deployed in scenarios, \r with uncoordinated action resulting in larger SRM deployment and \r consequently larger risks/impacts from SRM (Emmerling and Tavoni \r 2018a). Bridging research and governance involves consideration \r of the full range of societal choices and ramifications (Sugiyama \r et al. 2018). More information on SRM, including the caveats, risks, \r uncertainties, and governance issues is found in AR6 WGI Chapter 4; \r AR6 WGIII Chapter 14; and Cross-Working Group Box 4 in Chapter 14 \r of this report."


id: 9f21a756fced78121a1fc616c3cc011e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 25216
content:
"The inclusion of CDR options, like BECCS, can affect the timing of \r emissions mitigation in IAM scenarios, that is, delays in mitigations \r actions are compensated by net negative emissions in the second half \r of the century. However, studies with limited net negative emissions \r in the long term require very rapid declines in emissions in the near \r term (van Vuuren et al. 2017). Especially in forest-based systems, \r increased harvesting of forests can perturb the carbon balance of \r forestry systems, increasing emissions for some period; the duration \r of this period of increased emissions, preceding net emissions \r reductions, can be very variable (Mitchell et al. 2012; Lamers and \r Junginger 2013; Roder et al. 2019; Hanssen et al. 2020; Cowie et al. \r 2021). However, the factors contributing to differences in recovery \r time are known (Mitchell et al. 2012; Zanchi et al. 2012; Lamers and \r Junginger 2013; Laganiere et al. 2017; Roder et al. 2019). Some studies \r [...]"


id: 2abf5e48435ddb90f2518dbf11b7f7b6
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 4749
content:
"[...] that consider market-mediated effects find that an increased demand \r for biomass from forests can provide incentives to maintain existing \r forests and potentially to expand forest areas, providing additional \r carbon sequestration as well as additional biomass (Dwivedi et al. \r 2014; Kim et al. 2018; Baker et al. 2019; Favero et al. 2020). However, \r these responses are uncertain and likely to vary geographically."


id: b212f66f4ce5f87dff64462c650a62f8
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 28556
content:
"Pathways with very high biomass production for energy use typically \r include very high carbon prices in the energy system (Popp et al. \r 2017; Rogelj et al. 2018b), little or no land policy (Calvin et al. 2014b), \r a high discount rate (Emmerling et al. 2019), and limited non-BECCS \r CDR options (e.g.,  afforestation, DACCS) (Chen and Tavoni 2013; \r Calvin et al. 2014b; Marcucci et al. 2017; Realmonte et al. 2019; \r Fuhrman et al. 2020). Higher levels of bioenergy consumption are \r likely to involve trade-offs with mitigation in other sectors, notably \r in construction (i.e., wood for material and structural products) and \r AFOLU (carbon stocks and future carbon sequestration), as well as \r trade-offs with sustainability (Section  3.7) and feasibility concerns \r (Section 3.8). Not all of these trade-offs are fully represented in all \r IAMs. Based on sectoral studies, the technical potential for bioenergy, \r when constraints for food security and environmental considerations \r [...]"


id: 1ce97a382c43c3b163664b6e954c928a
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 2267
content:
"[...] are included, are 5-50 EJ yr-1 and 50-250 EJ yr-1 in 2050 for residues \r and dedicated biomass production systems, respectively (Chapter 7). \r Bioenergy deployment in IAMs is within the range of these potentials, "


id: 923b089d86687a02c8e2eed02bb3297b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 22948
content:
"Without mitigation, energy consumption and supply emissions \r continue to rise (high confidence) (Kriegler et al. 2016; Bauer et al. \r 2017; Riahi et al. 2017; Mcjeon et al. 2021) (Section 6.7). While the \r share of renewable energy continues to grow in reference scenarios, \r fossil fuel accounts for the largest share of primary energy (Bauer \r et al. 2017; Price and Keppo 2017; Riahi et al. 2017). In scenarios \r that limit warming to 2degC or lower, transition of the energy-supply \r sector to a  low- or no-carbon system is rapid (Rogelj et al. 2016, \r 2018b; Grubler et al. 2018; Luderer et al. 2018; van Vuuren et al. \r 2018). CO2 emissions from energy supply reach net zero around \r 2041 (2033-2057) in pathways limiting warming to 1.5degC (>50%) \r with no or limited overshoot and around 2053 (2040-2066) in \r pathways that limit warming to 2degC (>67%). Emissions reductions \r continue, with emissions reaching -7.1 GtCO2 yr-1  (-15 to \r [...]"


id: 1f0e8394495036d7ddffb9efdf2cdbd9
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 2667
content:
"2020; Urge-Vorsatz et al. 2020). For example, energy demand is \r driven by economic development that fulfills basic needs (Mastrucci \r et al. 2019; Rao et al. 2019a), but also drives up floor space in \r general (Daioglou et al. 2012; Levesque et al. 2018; Mastrucci et al. \r 2021) and ownership of energy-intensive appliances such as air \r conditioners (Isaac and van Vuuren 2009; Colelli and Cian 2020; \r Poblete-Cazenave et al. 2021). These dynamics are heterogeneous \r and lead to differences in energy demand and emission mitigation \r potential across urban/rural buildings and income levels (Krey et al. \r 2012; Poblete-Cazenave et al. 2021). Mitigation scenarios rely on \r fuel switching and technology (Knobloch et al. 2017; Dagnachew \r et al. 2020), efficiency improvement in building envelopes \r (Levesque et al. 2018; Edelenbosch et al. 2021) and behavioural \r changes (van  Sluisveld et al. 2016; Niamir et al. 2018, 2020). \r [...]"


id: ead6ca31772c544ae19a83d391389d09
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 38681
content:
"The relative contribution of demand-side reduction, energy- efficiency \r improvements, fuel switching, and decarbonisation of fuels, varyies \r by model, level of mitigation, mitigation options available, and \r underlying socio-economic pathway (Longden 2014; Wise et al. 2017; \r Yeh et al. 2017; Luderer et al. 2018; Yeh et al. 2017; Edelenbosch \r et al. 2020; Muller-Casseres et al. 2021a,b). IAMs typically rely on \r technology-focused measures like energy- efficiency improvements \r and fuel switching to reduce carbon emissions (Pietzcker et al. 2014; \r Edelenbosch et al. 2017a; Yeh et al. 2017; Zhang et al. 2018a,b; Rogelj \r et al. 2018b; Zhang et al. 2018a,b; Sharmina et al. 2020). Many \r mitigation pathways show electrification of the transport system \r (Luderer et al. 2018; Pietzcker et al. 2014; Longden 2014; Luderer \r et al. 2018; Zhang et al. 2018a); however, without decarboniszation \r of the electricity system, transport electrification can increase \r [...]"


id: f0b5b6aaccbcedb074575aa2d0a16443
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 39719
content:
"[...] total energy system emissions (Zhang and Fujimori 2020). A small \r number of pathways include demand-side mitigation measures in \r the transport sector; these studies show reduced carbon prices and \r reduced dependence on CDR (Grubler et al. 2018; Mejean et al. \r 2019; van de Ven et al. 2018; Zhang et al. 2018c; Mejean et al. 2019) \r (Section 3.4.1)."


id: 60af1759de250f29ee6ae4a92f14dd3
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 14308
content:
"As a result of these missing options and differences in how mitigation \r is implemented, IAMs tend to show less mitigation than the potential \r from national transport/energy models (Wachsmuth and Duscha \r 2019; Gota et al. 2019; Yeh et al. 2017; Gota et al. 2019; Wachsmuth \r and Duscha 2019; Edelenbosch et al. 2020). For the transport sector \r as a whole, studies suggest a mitigation potential of 4--5 GtCO2 per \r year in 2030 (Edelenbosch et al. 2020) with complete decarbonization \r decarbonisation possible by 2050 (Gota et al. 2019; Wachsmuth and \r Duscha 2019). However, in the scenarios assessed in this chapter that \r limit warming to below 1.5degC (>50%) with no or limited overshoot, \r transport sector CO2 emissions are reduced by only 59% (28-% \r to 81%) in 2050 compared to 2015. IAM pathways also show less \r electrification than the potential from other studies; pathways that \r limit warming to 1.5degC with no or limited overshoot show a median \r [...]"


id: 7c92da7ea8e81ab8d6f8f77892b83e02
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 19112
content:
"[...] of 25% (7- to 43%) of final energy from electricity in 2050, while the \r IEA NZE scenario includes 45% (IEA 2021a)."


id: a53cb9e54a645721f3026b3dcf382d9d
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 26300
content:
"Limiting warming to likely 2degC (>67%) or lower can result in \r large-scale transformation of the land surface (high confidence) \r (Popp et al. 2017; Rogelj et al. 2018a,b; Brown et al. 2019; Roe \r et al. 2019). The scale of land transformation depends, inter alia, \r on the temperature goal and the mitigation options included (Popp \r et al. 2017; Rogelj et al. 2018a; IPCC 2019a). Pathways with more \r demand-side mitigation options show less land transformation \r than those with more limited options (Grubler et al. 2018; van \r Vuuren et al. 2018; IPCC 2019a). Most of these pathways show \r increases in forest cover, with an increase of 322 million ha \r (-67 to 890 million ha) in 2050 in pathways that limit warming \r to  1.5degC (>50%) with no or limited overshoot, whereas bottom\u0002up models portray an economic potential of 300-500 million ha of \r additional forest (Chapter 7). Many IAM pathways also include large \r amounts of energy cropland area, to supply biomass for bioenergy and \r [...]"


id: 67babbaecfc355561c51afd6b5e09014
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 15518
content:
"[...] BECCS, with 199 (56-482) million ha in 2050 in pathways that limit \r warming to 1.5degC (>50%) with no or limited overshoot. Large land \r transformations, such as afforestation/reforestation and widespread \r planting of energy crops, can have implications for biodiversity and \r sustainable development (Sections 3.7, 7.7.4 and 12.5)."


id: 725dbcac45c5e278d255cf8d521ca25f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 17365
content:
"Some AFOLU mitigation options can enhance vegetation and \r soil carbon stocks such as reforestation, restoration of degraded \r ecosystems, protection of ecosystems with high carbon stocks and \r changes to agricultural land management to increase soil carbon \r (high confidence) (Griscom et al. 2017; de Coninck et al. 2018; Fuss \r et al. 2018; Smith et al. 2019) (AR6 WGIII Chapter 7). The time scales \r associated with these options indicate that carbon sinks in terrestrial \r vegetation and soil systems can be maintained or enhanced so as to \r contribute towards long-term mitigation (high confidence); however, \r many AFOLU mitigation options do not continue to sequester \r carbon indefinitely (Fuss et al. 2018; de Coninck et al. 2018; IPCC \r 2019a) (AR6 WGIII Chapter  7). In the very long term (the latter \r part of the century and beyond), it will become more challenging \r to continue to enhance vegetation and soil carbon stocks, so that \r [...]"


id: b374ef427c89fb755a8d85fbbf9f213e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 28815
content:
"[...] the associated carbon sinks could diminish or even become sources \r (high confidence) (de  Coninck et al. 2018; IPCC 2019a) (AR6 WGI \r Chapter 5). Sustainable forest management, including harvest and "


id: 72d883d583942b84e5272c516822c884
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 17455
content:
"Very few studies and pathways include other CDR options (Table 3.5). \r Pathways with DACCS include potentially large removal from DACCS \r (up to 37 GtCO2 yr-1 in 2100) in the second half of the century \r (Chen and Tavoni 2013; Marcucci et al. 2017; Realmonte et al. 2019; \r Fuhrman et al. 2020, 2021; Shayegh et al. 2021; Akimoto et al. 2021) \r and reduced cost of mitigation (Bistline and Blanford 2021; Strefler \r et al. 2021a). At large scales, the use of DACCS has substantial \r implications for energy use, emissions, land, and water; substituting \r DACCS for BECCS results in increased energy usage, but reduced \r land-use change and water withdrawals (Fuhrman et al., 2020, \r 2021) (Chapter 12.3.2; AR6 WGI Chapter 5). The level of deployment \r of DACCS is sensitive to the rate at which it can be scaled up, the \r climate goal or carbon budget, the underlying socio-economic \r scenario, the availability of other decarbonisation options, the cost \r [...]"


id: 5ab2f3fb42df198677c2eb6a2c962ba9
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 13209
content:
"[...] of DACCS and other mitigation options, and the strength of carbon\u0002cycle feedbacks (Chen and Tavoni 2013; Fuss et al. 2013; Honegger \r and Reiner 2018; Realmonte et al. 2019; Fuhrman et al. 2020; Bistline \r and Blanford 2021; Fuhrman et al. 2021; Strefler et al. 2021a) (AR6 \r WGI Chapter  5). Since DACCS consumes energy, its effectiveness \r depends on the type of energy used; the use of fossil fuels would \r reduce its sequestration efficiency (Creutzig et al. 2019; NASEM 2019; \r Babacan et al. 2020). Studies with additional CDR options in addition \r to DACCS (e.g., enhanced weathering, BECCS, afforestation, biochar, \r and soil carbon sequestration) find that CO2 removal is spread across "


id: bf010f31c8670332ea4be8cb7f1c24c8
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 30872
content:
"Anthropogenic land CO2 emissions and removals in IAM pathways \r cannot be directly compared with those reported in national \r GHG inventories (high confidence)  (Grassi et al. 2018, 2021) \r (Section  7.2).   Due to differences in  definitions  for the area  of \r managed forests and which emissions and removals are considered \r anthropogenic, the reported anthropogenic land CO2  emissions \r and removals differ by about  5.5 GtCO2  yr-1 between IAMs, \r which rely on bookkeeping approaches  (e.g.,  Houghton and \r Nassikas 2017), and national GHG inventories (Grassi et al. \r 2021). Such  differences  in  definitions  can alter the  reported  time \r at which  anthropogenic  net zero  CO2 emissions  are  reached  for \r a  given emission scenario. Using national inventories would lead \r to an earlier reported time of net zero (van Soest et al. 2021b) or \r to lower calculated cumulative emissions until the time of net zero \r (Grassi et al. 2021) as compared to IAM pathways. The numerical \r [...]"


id: 8df1f627198dd3aebec2c73db86a2a50
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 22164
content:
"[...] differences are purely due to differences in the conventions applied \r for reporting  the  anthropogenic  emissions and do not have any \r implications for the underlying land-use changes or mitigation \r measures in the pathways. Grassi et al. (Grassi et al. 2021) \r offer a  methodology for adjusting to reconcile these differences \r and enable a more accurate assessment of the collective progress \r achieved under the Paris Agreement (Chapter 7 and Cross-Chapter \r Box 6 in Chapter 7)."


id: d1b5dbe2324f372689bb176592a4ca8b
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vector_id: 34248
content:
"The assessment in this section shows that if mitigation ambitions \r in NDCs announced prior to COP262,18 are followed until 2030, \r leading to estimated emissions of 47-57 GtCO2-eq in 203019\r (Section  4.2.2), it is no longer possible to limit warming to  1.5degC \r (>50%) with no or limited overshoot (high confidence). Instead, it \r would entail high overshoot (typically >0.1degC) and reliance on net \r negative CO2 emissions with uncertain potential to return warming \r to 1.5degC (>50%) by the end of the century. It would also strongly \r increase mitigation challenges to limit warming to 2degC (>67%) \r (high confidence). GHG emissions reductions would need to abruptly \r increase after 2030 to an annual average rate of  1.4-2.0 GtCO2-\r eq during the period 2030-2050, around 70% higher than in \r mitigation pathways assuming immediate action1\r  to limit warming \r to 2degC (>67%). The higher post-2030 reduction rates would have \r [...]"


id: 9b49dac87e4e15d655117c07431d9738
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 24568
content:
"[...] to be obtained in an environment of continued buildup of fossil fuel \r infrastructure and less development of low-carbon alternatives until \r 2030. A  lock-in to fossil fuel-intensive production systems (carbon \r lock-in) will increase the societal, economic and political strain of \r a rapid low-carbon transition after 2030 (high confidence)."


id: a526172f464a85c4f4a65422ecb1af5b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 26284
content:
"The relationship between warming limits and near-term action is \r illustrated in Figure 3.29, using a set of 1.5degC-2degC scenarios with \r different levels of near-term action, overshoot and non-CO2 warming \r contribution from a recent study (Riahi et al. 2021). In general, the \r more CO2 is emitted until 2030, the less CO2 can be emitted thereafter \r to stay within a remaining carbon budget and below a warming limit. \r Scenarios with immediate action to observe the warming limit give \r the longest time to exhaust the associated remaining carbon budget \r and reach net zero CO2 emissions (see light blue lines in Figure 3.29 \r and Cross-Chapter Box 3 in this chapter). In comparison, following \r projected NDC emissions until 2030 would imply a more pronounced \r drop in emissions from 2030 levels to net zero to make up for the \r additional near-term emissions (see orange lines in Figure  3.29). \r If  such a  drop does not occur, the remaining carbon budget is \r [...]"


id: 605565ddda1b1a99fd50faba9009136a
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 14252
content:
"[...] exceeded and net negative CO2 emissions are required to return \r global mean temperature below the warming limit (see black lines in \r Figure 3.29) (Clarke et al. 2014; Fuss et al. 2014; Rogelj et al. 2018a)."


id: 95d29e6ef0c07c8830148230853b8b0f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 23557
content:
"The section builds on previous assessments in the IPCC's Fifth \r Assessment Report (Clarke et al. 2014) and the IPCC Special Report \r on 1.5degC Warming (Rogelj et al. 2018a). The literature assessed in these \r two reports has focused on delayed action until 2030 in the context of \r limiting warming to 2degC (den Elzen et al. 2010; van Vuuren and Riahi \r 2011; Luderer et al. 2013, 2016; Rogelj et al. 2013a; Kriegler et al. 2015; \r Riahi et al. 2015) and 1.5degC (Rogelj et al. 2013b; Luderer et al. 2018; \r Strefler et al. 2018). Here we provide an update of these assessments \r drawing on the most recent literature on global mitigation pathways. \r New studies have focused, inter alia, on  constraining near-term \r developments by peak warming limits (Rogelj et al. 2019b; Riahi et al. \r 2021; Strefler et al. 2021b) and updating assumptions about near- and\r medium-term emissions developments based on national plans \r and long-term strategies (Roelfsema et al. 2020) (Section 4.2). Several \r [...]"


id: ca5859ec3fb3a0c82126eb1309480105
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 32941
content:
"[...] studies have explored new types of pathways with accelerated action \r bridging between current policy plans and the goal of limiting warming \r below 2degC (Kriegler et al. 2018a; van Soest et al. 2021a) and looked at \r hybrid international policy regimes to phase in global collective action \r (Bauer et al. 2020)."


id: df13b0d51f28af6636d8f180b8d0795f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 36497
content:
"The relationship between warming limits and near-term action is \r also affected by the warming contribution of non-CO2 greenhouse \r gases and other short-lived climate forcers (Section  3.3; AR6 WGI \r Section  6.7). The estimated budget values for limiting warming \r to  1.5degC-2degC already assume stringent reductions in non-CO2\r greenhouse gases and non-CO2 climate forcing as found in 1.5degC-2degC \r pathways (Section 3.3 and Cross-Working Group Box 1 in this chapter; \r AR6 WGI Section  5.5 and Box  5.2 in Chapter  5). Further variations \r in non-CO2 warming observed across 1.5degC-2degC pathways can vary \r the median estimate for the remaining carbon budget by 220 GtCO2\r (AR6 WGI Section 5.5). In 1.5degC-2degC pathways, the non-CO2 warming \r contribution differs strongly between the near, medium and long term. \r Changes to the atmospheric composition of short-lived climate forcers \r (SLCFs) dominate the warming response in the near term (AR6 WGI \r [...]"


id: 7d51be236da3ffdc536ad821e024015e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 19225
content:
"[...] Section 6.7). CO2 reductions are combined with strong reductions in air \r pollutant emissions due to rapid reduction in fossil fuel combustion and \r in some cases the assumption of stringent air quality policies (Rao et al. \r 2017b; Smith et al. 2020c). As air pollutants exert a net-cooling effect, "


id: 11f4907df1738c38be58a90e802e1b3a
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 348
content:
"Figure 3.29 | Illustration of emissions and climate response in four mitigation pathways with different assumptions about near-term policy developments, \r global warming limit and non-CO2 warming contribution drawn from Riahi et al. (2021). Shown are (a) CO2 emissions trajectories, (b) cumulative CO2 emissions, \r (c) effective non-CO2 radiative forcing, and (d) the resulting estimate of the 67th percentile of global mean temperature response relative to 1850-1900. Light blue lines \r show a scenario that acts immediately on a remaining carbon budget of 900 GtCO2 from 2020 without allowing net negative CO2 emissions (i.e., temporary budget overshoot) \r (COFFEE 1.1, Scenario EN_NPi2020_900). Orange and black lines show scenarios drawn from the same model that follow the NDCs until 2030 and thereafter introduce action \r to stay within the same budget - in one case excluding net negative CO2 emissions like before (orange lines; COFFEE 1.1., Scenario EN-INDCi2030_900) and in the other \r [...]"


id: e1be3cd5d02a01e456019088e0e2886d
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 36993
content:
"[...] allowing for a temporary overshoot of the carbon budget until 2100 (black lines; COFFEE 1.1., Scenario EN-INDCi2030_900f). Light blue lines describe a scenario following the \r NDCs until 2030, and then aiming for a higher budget of 2300 GtCO2 without overshoot (AIM/CGE 2.2, Scenario EN-INDCi2030_1200). It is drawn from another model which \r projects a lower anthropogenic non-CO2 forcing contribution and therefore achieves about the same temperature outcome as the other two non-overshoot scenarios despite \r the higher CO2 budget. Grey funnels include the trajectories from all scenarios that limit warming to 2degC (>67%) (category C3). Historical CO2 emissions until 2019 are from \r Chapter SM.2.1 EDGAR v6.0."


id: ab0df91204e44b6161eba6c41e0dc744
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 27320
content:
"integrated assessment modelling of global mitigation pathways \r accounts for technology inertia (Bertram et al. 2015a; Mercure et al. \r 2018) and technology innovation and diffusion (Wilson et al. 2013; \r van Sluisveld et al. 2018a; Luderer et al. 2021), there are limitations \r in capturing socio-technical and political drivers of innovation, \r diffusion and transition processes (Gambhir et al. 2019; Kohler et al. \r 2019; Hirt et al. 2020; Keppo et al. 2021). Mitigation pathways show \r a  wide range of transition speeds that have been interrogated in \r the context of socio-technical inertia (Gambhir et al. 2017; Kefford \r et al. 2018; Kriegler et al. 2018a; Brutschin et al. 2021) vs accelerating \r technological change and self-enforcing socio-economic developments \r (Creutzig et al. 2017; Zenghelis 2019) (Section 3.8). Diagnostic analysis \r of detailed IAMs found a lag of 8-20 years between the convergence \r of emissions pricing and the convergence of emissions response after \r [...]"


id: 40f7c093e627fa27fdcab5930cd4b504
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 8616
content:
"[...] a period of differentiated emission prices (Harmsen et al. 2021). This \r provides a  measure of the inertia to changing policy signals in the \r model response. It is about half the time scale of 20-40 years observed \r for major energy transitions (Grubb et al. 2021). Hence, the mitigation \r pathways assessed here capture socio-technical inertia in reducing \r emissions, but the limited modelling of socio-political factors may alter \r the extent and persistence of this inertia."


id: b11efbc1071ca2ce5f26fae1e312c2b2
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 28388
content:
"The assessed emission ranges from implementing the unconditional \r (unconditional and conditional) elements of NDCs announced prior to \r COP26 implies an emissions gap to cost-effective mitigation pathways \r of 19-26 (16-23) GtCO2-eq in 2030 for limiting warming to 1.5degC \r (>50%) with no or limited overshoot and 10-16 (6-14) GtCO2-eq in \r 2030 for limiting warming to 2degC (>67%) (Cross-Chapter Box 4 in \r Chapter 4). The emissions gap gives rise to a number of mitigation \r challenges (Kriegler et al. 2013a, 2018a,b; Luderer et al. 2013, 2018; \r Rogelj et al. 2013a; Fawcett et al. 2015; Riahi et al. 2015; Fujimori \r et al. 2016b; Strefler et al. 2018; Winning et al. 2019; SEI et al. 2020; \r UNEP 2020): (i) larger transitional challenges post-2030 to still \r remain under the warming limit, in particular higher CO2 emissions \r reduction rates and technology transition rates required during \r 2030-2050; (ii)  larger lock-in into carbon-intensive infrastructure \r [...]"


id: a5aad01540f25bf4d88458f53b33e69b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 26377
content:
"[...] and increased risk of stranded fossil fuel assets (Section  3.5.2.2); \r and (iii) larger reliance on CDR to reach net zero CO2 more rapidly \r and compensate excess emissions in the second half of the century \r (Section  3.5.2.1). All these factors exacerbate the socio-economic \r strain of implementing the transition, leading to an increased risk \r of overshooting the warming and a  higher risk of climate change \r impacts (Drouet et al. 2021)."


id: 7c1dbfae29b9bb892e611f3d4bc866e6
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 19045
content:
"The implications of near-term climate action for long-term climate \r outcomes can be explored by comparing mitigation pathways with \r different near-term emissions developments aiming for the same \r climate target (Riahi et al. 2015; Vrontisi et al. 2018; Roelfsema \r et al. 2020). A particular example is the comparison of cost-effective \r pathways with immediate action to limit warming to 1.5degC-2degC with \r mitigation pathways pursuing more moderate mitigation action \r until 2030. After the adoption of the Paris Agreement, near-term \r action was often modelled to reflect conditional and unconditional \r elements of originally submitted NDCs (2015-2019) (Fawcett et al. \r 2015; Fujimori et al. 2016a; Kriegler et al. 2018a; Vrontisi et al. \r 2018; Roelfsema et al. 2020). The most recent modelling studies \r also include submission of updated NDCs or announcements of \r planned updates in the first half of 2021 (Network for Greening \r [...]"


id: fec971482c0411c5a0058ba6009f4aff
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 42217
content:
"[...] the Financial System 2021; Riahi et al. 2021). Emissions levels \r under NDCs announced prior to COP26 are assessed to range \r between 47-57 GtCO2-eq in 2030 (Section  4.2.2). This assessed \r range corresponds well to 2030 emissions levels in 2degC mitigation \r pathways in the literature that are designed to follow the original \r or updated NDCs until 2030.20 For the 139 scenarios of this kind \r that are collected in the AR6 scenario database and that still \r limit warming to 2degC (>67%), the 2030 emissions range is 53 \r (45-58) GtCO2-eq (based on native model reporting) and 52.5 \r (47-56.5) GtCO2-eq, respectively (based on harmonised emissions \r data for climate assessment (Annex III.2.5.1); median and 5-95th \r percentile). This close match allows a  robust assessment of the \r implications of implementing NDCs announced prior to COP26 for "


id: 5615c9a8e13f7848268832221f2ab412
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 12418
content:
"The challenges are illustrated in Table 3.6 and Figure 3.30, surveying \r global mitigation pathways in the literature that were collected in \r the AR6 scenarios database. There is a clear trend of increasing peak \r warming with increasing 2030 GHG emission levels (Figure 3.30a,b). \r In particular, there is no mitigation pathway designed to follow the \r NDCs until 2030 that can limit warming to 1.5degC (>50%) with no or \r limited overshoot. Our assessment confirms the finding of the IPCC\r Special Report on Global Warming of  1.5degC (Rogelj et al. 2018) for \r the case of NDCs announced prior to COP26 that pathways following \r the NDCs until 2030 'would not limit global warming to 1.5degC, even if \r supplemented by very challenging increases in the scale and ambition \r of emissions reductions after 2030' (SR1.5 SPM). This assessment is now \r more robust than in SR1.5 as it is based on a larger set of 1.5degC-2degC \r pathways with better representation of current trends and plans \r [...]"


id: 8e1f5bdbfe3027d27dadfb1ce04ee808
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 22201
content:
"[...] covering a  wider range of post-2030 emissions developments. In \r particular, a  recent multi-model study limiting peak cumulative CO2\r emissions for a wide range of carbon budgets and immediate vs NDC\u0002type action until 2030 established a feasibility frontier for the existence \r of such pathways across participating models (Riahi et al. 2021)."


id: f457806ebedfdf04f768c9efd6e1fbee
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 40364
content:
"Figure 3.30 | Relationship between level of global GHG emissions in 2030 and selected indicators as listed in the panel titles for scenarios collected \r in the AR6 scenario database. Emissions data based on harmonised emissions used for the climate assessment. All scenarios that limit warming to 2degC (>67%) or lower \r are coloured blue or red (see p67 peak warming in panel (b)). The large majority of blue-coloured scenarios act immediately on the temperature target, while red-coloured \r scenarios depict all those that were designed to follow the NDCs or lesser action until 2030 and orange-coloured scenarios comprise a small set of pathways with additional \r regulatory action beyond NDCs (Section 3.5.3). Grey-coloured scenarios do not limit warming to 2degC (>67%) due to temporary overshoot or towards the end of the century. \r [...]"


id: b9f21ef2192422cd5166b2c9d654fcce
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 29937
content:
"[...] Large markers denote the five Illustrative Mitigation Pathways (IMPs) (legend in Panel (h); Section 3.2). Shaded yellow areas depict the estimated range of 2030 emissions from \r NDCs announced prior to COP26 (Section 4.2.2). Dotted lines are inserted in some panels to highlight trends in the dependency of selected output variables on 2030 GHG \r emissions levels (Section 3.5.2)."


id: ff3fce04c93fa65eeaca40a1cd7a82f7
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 42309
content:
"Table 3.6 | Comparison of key scenario characteristics for five scenario classes (see Table 3.2): (i) immediate action to limit warming to 1.5degC (>50%) with \r no or limited overshoot, (ii) near team action following the NDCs until 2030 and returning warming to below 1.5degC (>50%) by 2100 after a high overshoot, \r (iii) immediate action to limit warming to 2degC (>67%), (iv) near term action following the NDCs until 2030 followed by post-2030 action to limit warming to \r 2degC (>67%). Also shown are the characteristics for (v) the combined class of all scenarios that limit warming to 2degC (>67%). The classes (ii) and (iv) comprise the large majority of \r scenarios indicated by red dots, and the classes (i) and (iii) comprise the scenarios depicted by blue dots in Figure 3.30. Shown are median and interquartile ranges (in brackets) for \r [...]"


id: 6ebab22f9ed51716cef0f3119e15b5c1
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 16746
content:
"[...] selected global indicators. Emissions ranges are based on harmonized emissions data for the climate assessment with the exception of land use CO2 emissions for which uncertainty \r in historic estimates is large. Numbers are rounded to the nearest 5, with the exception of cumulative CCS, BECCS, and net negative CO2 emissions rounded to the nearest 10."


id: f01533f29a7c2e24cfc682b404f9d617
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 39620
content:
"The 2030 emissions levels in the NDCS announced prior to COP26 \r also tighten the remaining space to limit warming to 2degC (>67%). As \r shown in Figure 3.30b, the 67th percentile of peak warming reaches \r values above 1.7degC in pathways with 2030 emissions levels in this \r range. To still limit warming to 2degC (>67%), the global post-2030 GHG \r emission reduction rates would need to be abruptly raised in 2030 \r from 0-0.7 GtCO2-eq yr-1 to an average of 1.4-2.0 GtCO2-eq yr-1\r during the period 2030-2050 (Figure  3.30c), around 70% higher \r than in immediate mitigation pathways confirming findings in \r the literature (Winning et al. 2019). Their average reduction rate \r of 0.6-1.4 GtCO2 yr-1 would already be unprecedented at the global \r scale and, with a  few exceptions, national scale for an extended \r period of time (Riahi et al. 2015). For comparison, the impact of \r COVID-19 on the global economy is projected to have lead to \r [...]"


id: b90c434b1e9c73ff8b5d450672219c2f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 29760
content:
"[...] a decline of around 2.5-3 GtCO2 of global CO2 emissions from fossil \r fuels and industry in 2020 (Friedlingstein et al. 2020) (Section 2.2)."


id: e6a66d74b54a68a0d407e6f76456cdc0
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 37875
content:
"If near- to medium-term emissions developments deplete the \r remaining carbon budget, the associated warming limit will be \r overshot. Some pathways that return warming to 1.5degC (>50%) by \r the end of the century show mid-century overshoots of up to 1.8degC \r median warming. The overshoot tends to be higher, the higher the \r 2030 emissions. Mitigation pathways with 2030 emissions levels in \r the NDCS announced prior to COP26 consistently overshoot 1.5degC \r by  0.15degC-0.3degC. This leads to higher risks from climate change \r impacts during the time of overshoot compared to pathways that limit \r warming to 1.5degC (>50%) with no or limited overshoot (Schleussner \r et al. 2016a; Mengel et al. 2018; Hofmann et al. 2019; Lenton et al. \r 2019; Tachiiri et al. 2019; Drouet et al. 2021). Furthermore, even if \r warming is reversed by net negative emissions, other climate changes \r such as sea level rise would continue in their current direction for \r [...]"


id: 2d4629212fefa8117cee11b07ba08b4e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 5251
content:
"The increased post-2030 transition challenge in mitigation pathways \r with moderate near-term action is also reflected in the timing of \r reaching net zero CO2 emissions (Figure  3.30d and Cross-Chapter \r Box 3 in this chapter). As 2030 emission levels and the cumulated \r CO2 emissions until 2030 increase, the remaining time for dropping \r to net zero CO2 and staying within the remaining carbon budget \r shortens (Figure  3.29). This gives rise to an inverted  v-shape of \r the lower bound on the year of reaching net zero as a function of \r 2030 emissions levels. Reaching low emissions in 2030 facilitates \r reaching net zero early (left leg of the inverted v), but staying high \r until 2030 also requires reaching net zero CO2 faster to compensate \r for higher emissions early on (right leg of the inverted v). Overall, \r there is a considerable spread of the timing of net zero CO2 for any \r 2030 emissions level due to variation in the timing of spending the \r [...]"


id: 93dd4d37d8a3ddc3d4d86f47890b4e75
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 23222
content:
"[...] remaining carbon budget and the non-CO2 warming contribution \r (Cross-Chapter Box 3 in this chapter)."


id: da898542f9cdf5dfeea55accca6be078
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 35749
content:
"Returning warming to lower levels requires net negative CO2\r emissions in the second half of the century (Clarke et al. 2014; \r Fuss et al. 2014; Rogelj et al. 2018a). The amount of net negative \r CO2 emissions in pathways limiting warming to 1.5degC-2degC climate \r goals varies widely, with some pathways not deploying net negative \r CO2 emissions at all and others deploying up to -600 to -800 GtCO2. \r The amount of net negative CO2 emissions tends to increase with \r 2030 emissions levels (Figure 3.30e and Table 3.6). Studies confirmed \r the ability of net negative CO2 emissions to reduce warming, but \r pointed to path dependencies in the storage of carbon and heat \r in the Earth System and the need for further research particularly \r for cases of high overshoot (Zickfeld et al. 2016, 2021; Keller et al. \r 2018a,b; Tokarska et al. 2019). The AR6 WGI assessed the reduction \r in global surface temperature to be approximately linearly related to \r [...]"


id: b6fb5e1d56314fa693773f0c66e66f82
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 29405
content:
"[...] cumulative CO2 removal and, with lower confidence, that the amount \r of cooling per unit CO2 removed is approximately independent of the \r rate and amount of removal (AR6 WGI TS.3.3.2). Still there remains \r large uncertainty about a potential asymmetry between the warming \r response to CO2 emissions and the cooling response to net negative \r CO2 emissions (Zickfeld et al. 2021). It was also shown that warming \r can adversely affect the efficacy of carbon dioxide removal measures \r and hence the ability to achieve net negative CO2 emissions \r (Boysen et al. 2016)."


id: c92887d0788a7372fd34695723cca93f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 32716
content:
"There is also a  profound impact on the underlying transition of \r energy and land use (Figure  3.30f-h and Table  3.6). Scenarios \r following NDCs until 2030 show a much smaller reduction in fossil \r fuel use, a slower growth in renewable energy use, and a  smaller \r reduction in CO2 and CH4 land-use emissions in 2030 compared to \r immediate action scenarios. This is then followed by a much faster \r reduction of land-use emissions and fossil fuels, and a larger increase \r of nuclear energy, bioenergy and non-biomass renewable energy \r during the medium term in order to get close to the levels of the \r immediate action pathways in 2050. This is combined with a larger \r amount of net negative CO2 emissions that are used to compensate \r the additional emissions before 2030. The faster transition during \r 2030-2050 is taking place from a greater investment in fossil fuel \r infrastructure and lower deployment of low-carbon alternatives in \r [...]"


id: 73d7d9515474f8dfc67a1f8ebeaa6a25
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updated_at: 2023-04-19 13:23:08
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vector_id: 17634
content:
"[...] 2030, adding to the socio-economic challenges to realise the higher \r transition rates (Section 3.5.2.2). Therefore, these pathways also show \r higher mitigation costs, particularly during the period 2030-2050, \r than immediate action scenarios (Section  3.6.1 and Figure  3.34d) \r (Liu et al. 2016; Kriegler et al. 2018a; Vrontisi et al. 2018). Given \r these circumstances and the fact the modelling of socio-political and \r institutional constraints is limited in Integrated Assessment Models \r (IAMs) (Gambhir et al. 2019; Kohler et al. 2019; Hirt et al. 2020; Keppo \r et al. 2021), the feasibility of realising these scenarios is assessed to "


id: 1257fc71587b58a52af99df10c77587b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 435
content:
"et al. 2018; Hilaire et al. 2019; Jia et al. 2019) (Section 12.3). CDR \r therefore cannot be deployed arbitrarily to compensate any degree \r of overshoot. A fraction of models was not able to compute pathways \r that would follow the mitigation ambition in unconditional and \r conditional NDCs until 2030 and return warming to below 1.5degC by \r 2100 (Luderer et al. 2018; Roelfsema et al. 2020; Riahi et al. 2021). \r There exists a  three-way trade-off between near-term emissions \r developments until 2030, transitional challenges during 2030-50, \r and long-term CDR deployment post-2050 (Sanderson et al. 2016; \r Holz et al. 2018; Strefler et al. 2018). For example, Strefler et al. (2018) \r find that if CO2 emission levels stay at around 40 GtCO2 until 2030, \r within the range of what is projected for NDCs announced prior \r to COP26, rather than being halved to 20 GtCO2 until 2030, CDR \r deployment in the second half of the century would have to increase \r [...]"


id: 71a8aa0e445ad2c627bbcb7e2337ee87
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 17243
content:
"[...] by 50-100%, depending on whether the 2030-2050 CO2 emissions \r reduction rate is doubled from 6% to 12% or kept at 6% yr-1. This \r three-way trade-off has also been identified at the national level \r (Pan et al. 2020)."


id: 14cabef15897a68f8286abb884e12176
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 884
content:
"A systematic map of the literature on carbon lock-in has synthesized \r quantification of stranded assets in the mitigation pathways \r literature, and showed that (i) coal power plants are the most \r exposed to risk of  becoming stranded, (ii) delayed mitigation \r action increases stranded assets, and (iii) sectoral distribution and \r the amount of  stranded assets differ between countries (Fisch\u0002Romito et al. 2021). There is high agreement that existing fossil fuel \r infrastructure would need to be retired earlier than historically, used \r less, or retrofitted with CCS, to stay within the remaining carbon \r budgets of limiting warming to 1.5degC or 2degC (Johnson et al. 2016; \r Kefford et al. 2018; Pfeiffer et al. 2018; Cui et al. 2019; Fofrich et al. \r 2020; Rogelj et al. 2018a). Studies estimate that cumulative early \r retired power plant capacities by 2060 can be up to 600 GW for gas \r and 1700 GW for coal (Iyer et al. 2015a; Kefford et al. 2018), that \r [...]"


id: 6f2101b5d1e192d7ea3fb75a70062d34
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 16820
content:
"[...] only 42% of the total capital stock of both operating and planned \r coal-fired powers plants can be utilised to be compatible with the \r 2degC target (Pfeiffer et al. 2018), and that coal-fired power plants in \r scenarios consistent with keeping global warming below 2degC or 1.5degC \r retire one to three decades earlier than historically has been the case \r (Cui et al. 2019; Fofrich et al. 2020). After coal, electricity production \r based on gas is also projected to be phased out, with some capacity \r remaining as back-up (van Soest et al. 2017a). Kefford et al. (2018) \r find USD541 billion worth of stranded fossil fuel power plants could \r be created by 2060, with China and India the most exposed."


id: fda29246f9759eefe1210854378f1c8c
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 41974
content:
"In addition to enabling a  temporary budget overshoot by net \r negative CO2 emissions in the second half of the century, CDR can \r also be used to compensate  - on an annual basis  - residual CO2\r emissions from sources that are difficult to eliminate and to reach \r net zero CO2 emissions more rapidly if deployed before this point \r (Kriegler et al. 2013b; Rogelj et al. 2018a). This explains its continued \r deployment in pathways that exclude overshoot and net negative \r CO2 emissions (Riahi et al. 2021). However, given the time scales that \r would likely be needed to ramp-up CDR to gigatonne scale (Nemet \r et al. 2018), it can be expected to only make a limited contribution to \r reaching net zero CO2 as fast as possible. In the vast majority (95%) \r of 1.5degC-2degC mitigation pathways assessed in this report, cumulative \r CDR deployment did not exceed 100 GtCO2 until mid-century. This \r adds to the risk of excessively relying on CDR to compensate for \r [...]"


id: 4871c6fcb3bc44f3f404874c364e202b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 9955
content:
"[...] weak mitigation action until 2030 by either facilitating massive \r net CO2 emissions reduction rates during 2030-2050 or allowing \r a high temporary overshoot of 1.5degC until the end of the century. If \r international burden-sharing considerations are taken into account, \r the CDR penalty for weak action could increase further, in particular \r for developed countries (Fyson et al. 2020). Further assessment \r of CDR deployment in  1.5degC-2degC mitigation pathways is found \r in Section 3.4.7."


id: 89bfc4f98372744f4d524466f4808128
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 21404
content:
"Some publications have suggested that stranded long-lived assets \r may be even more important outside of the power sector. While \r stranded power sector assets by 2050 could reach up to USD1.8 trillion \r in scenarios consistent with a 2degC target, Saygin et al. (2019) found \r a range of USD5-11 trillion in the buildings sector. Muldoon-Smith \r and Greenhalgh (2019) have even estimated a potential value at risk \r for global real estate assets up to USD21 trillion. More broadly, the set \r of economic activities that are potentially affected by a low-carbon \r transition is wide and includes also energy-intensive industries, \r transport and housing, as reflected in the concept of climate policy \r relevant sectors introduced in Battiston et al. (2017). The sectoral \r distribution and amount of stranded assets differ across countries \r (Fisch-Romito et al. 2021). Capital for fossil fuel production and \r distribution represents a larger share of potentially stranded assets in \r [...]"


id: 2c424054c5eea4b18d8afa7590f49073
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 5052
content:
"[...] fossil fuel-producing countries such as the United States and Russia. \r Electricity generation would be a larger share of total stranded assets \r in emerging countries because this capital is relatively new compared \r to its operational lifetime. Conversely, buildings could represent \r a  larger part of stranded capital in more developed countries and \r regions such as the USA, EU or even Russia because of high market \r value and low turnover rate."


id: 7391950bd6030e47d2fa1409be0f2ddf
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 17589
content:
"2019; SEI et al. 2020). Pathways following NDCs announced prior \r to COP26 until 2030 do not show a significant reduction of coal, oil \r and gas use (Figure 3.30f-h and Table 3.6) compared to immediate \r action pathways. Stranded coal power assets are evaluated to be \r higher by a factor of two to three if action is strengthened after 2030 \r rather than now (Iyer et al. 2015b; Cui et al. 2019). There is high \r agreement that the later climate policies are implemented, the higher \r the expected stranded assets and the societal, economic and political \r strain of strengthening action. Associated price increases for carbon\u0002intensive goods and transitional macro-economic costs have been \r found to scale with the emissions gap in 2030 (Kriegler et al. 2013a). \r At the aggregate level of the whole global economy, Rozenberg et al. \r (2015) showed that each year of delaying the start of mitigation \r decreases the required CO2 intensity of new production by 20-50 \r [...]"


id: 3f3c75eaf3021c7b0c9ec712f0f1655d
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 8316
content:
"[...] gCO2 per USD. Carbon lock-in can have a long-lasting effect on future \r emissions trajectories after 2030. Luderer et al. (2018) compared \r cost-effective pathways with immediate action to limit warming \r to  1.5degC-2degC with pathways following the NDCs until 2030 and \r adopting the pricing policy of the cost-effective pathways thereafter, \r and found that the majority of additional CO2 emissions from carbon \r lock-in occur after 2030, reaching a cumulative amount of 290 (160-\r 330) GtCO2 by 2100 (Section 2.7.2). Early action and avoidance of \r investments in new carbon-intensive assets can minimise these risks."


id: 683e08ea345cf06ef8de6857a7eb07ab
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 15611
content:
"The large literature on accelerating climate action was assessed in \r the IPCC Special Report on Global Warming of  1.5degC (de Coninck \r et al. 2018) and is taken up in this report primarily in Chapters 4, 13, \r and 14. Accelerating climate action and facilitating transformational \r change requires a perspective on socio-technical transitions (Geels \r et al. 2016a; Geels et al. 2016b; Geels 2020), a portfolio of policy \r instruments to manage technological and environmental change \r (Fischer and Newell 2008; Goulder and Parry 2008; Acemoglu et al. \r 2012, 2016), a  notion of path dependency and policy sequencing \r (Pierson 2000; Meckling et al. 2017; Pahle et al. 2018) and the \r evolvement of polycentric governance layers of institutions and \r norms in support of the transformation (Dietz et al. 2003; Leach et al. \r 2007; Messner 2015). This subsection is focused on an assessment \r of the emerging quantitative literature on global accelerated action \r [...]"


id: 438a4bd359887c82300f34ea114acb84
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 9107
content:
"[...] pathways towards 1.5degC-2degC, which to a large extent abstracts from \r the underlying processes and uses a number of stylised approaches \r to generate these pathways. A representative of accelerated action \r pathways has been identified as one of the Illustrative Mitigation \r Pathways (IMPs) in this assessment (IMP-GS, Figure 3.31)."


id: 69d0c360ba9cd1954d4b992a32fb2de
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 15888
content:
"Figure 3.31 | Comparison of (i) pathways with immediate action to limit warming to 2degC (>67%) (Immediate, light blue), (ii) pathways following the \r NDCs until 2030 and limiting warming to 2degC (>67%) thereafter (NDC; orange), and (iii) pathways accelerating near-term action until 2030 beyond NDC \r ambition levels and limiting warming to 2degC (>67%) thereafter (accelerated) for selected indicators as listed in the panel titles, based on pathways from \r van Soest et al. (2021a). Low-carbon electricity comprises renewable and nuclear power. Indicator ranges are shown as box plots (full range, interquartile range, and median) \r for the years 2030, 2050 and 2100 (absolute values) and for the periods 2020-2030, 2030-2050 (change indicators). Ranges are based on nine models participating in van \r Soest et al. (2021a) with only seven models reporting emissions and climate results and eight models reporting carbon prices. The purple dot denotes the Illustrative Mitigation \r [...]"


id: 87d61ba2b07127ad07de01b4f10c4b4e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 21053
content:
"about 20% compared to a  current policy scenario. These findings \r were found in good agreement with a  recent model comparison \r study based on results from nine integrated assessment models \r (IAMs) (van Soest et al. 2021a). Based on these three studies, \r implementing accelerated action in terms of a  global roll out of \r regulatory and moderate pricing policies is assessed to lead to \r global GHG emissions of 48 (38-52) GtCO2-eq in 2030 (median \r and 5-95th percentile based on 10 distinct modelled pathways). This \r closes the implementation gap for the NDCs, and in addition falls \r below the emissions range implied by implementing unconditional \r and conditional elements of NDCs by  2-9 GtCO2-eq. However, it \r does not close the emissions gap to immediate action pathways \r that limit warming to 2degC (>67%), and, based on our assessment in \r Section 3.5.2, emission levels above 40 GtCO2-eq in 2030 still have \r a very low prospect for limiting warming to 1.5degC (>50%) with no \r [...]"


id: a2784d14d020a796c26da1ca3c24674a
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 25804
content:
"The most common approach relies on strengthening regulatory policies \r beyond current policy trends, also motivated by the finding that such \r policies have so far been employed more often than comprehensive \r carbon pricing (Kriegler et al. 2018a; Roelfsema et al. 2018; Fekete et al. \r 2021; IEA 2021a; van Soest et al. 2021a). Some studies have focused \r on generic regulatory policies such as low-carbon support policies, \r fossil fuel-sunset policies, and resource-efficiency policies (Bertram \r et al. 2015b; Hatfield-Dodds et al. 2017). Bertram et al. (2015b) found \r that a moderate carbon price combined with a coal moratorium and \r ambitious low-carbon support policies can limit efficiency losses until \r 2030 if emissions pricing is raised thereafter to limit warming to 2degC. \r They also showed that all three components are needed to achieve this \r outcome. Hatfield-Dodds et al. (2017) found that resource efficiency \r can lower 2050 emissions by an additional 15-20% while boosting \r [...]"


id: be01a1b0c775a2e7f0b6dc6c04672811
created_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 30692
content:
"[...] near-term economic growth. The International Energy Agency (IEA \r 2021a) developed a detailed net zero scenario for the global energy \r sector characterised by a  rapid phase-out of fossil fuels, a  massive \r clean energy and electrification push, and the stabilisation of energy \r demand, leading to 10 GtCO2 lower emissions from energy use in 2030 \r than in a scenario following the announced pledges."


id: 86ac49ce60c6181a7ebee507b3ed2fd1
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 20861
content:
"Figure  3.31 shows the intermediate position of accelerated action \r pathways derived by van Soest et al. (2021a) between pathways \r that follow the NDCs until 2030 and immediate action pathways \r limiting warming to 2degC (>67%). Accelerated action is able to reduce \r the abrupt shifts in emissions, fossil fuel use and low-carbon power \r generation in 2030 and also limits peak warming more effectively \r than NDC pathways. But primarily due to the moderate carbon price \r assumptions (Figure 3.31b), the reductions in emissions and particular \r fossil fuel use are markedly smaller than what would be obtained in \r the case of immediate action. The assessment shows that accelerated \r action until 2030 can have significant benefits in terms of reducing the \r mitigation challenges from following the NDCs until 2030. But putting \r a significant value on GHG emissions reductions globally remains a key \r element of moving onto  1.5degC-2degC pathways. The vast majority of \r [...]"


id: baaccc7b0a7ba2fb52f3404e70fc518a
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 30060
content:
"[...] pathways that limit warming to 2degC (>67%) or lower, independently \r of their differences in near-term emission developments, converge to \r a global mitigation regime putting a significant value on GHG emission \r reductions in all regions and sectors."


id: 6f67434f4e1920eb07a79d5d4129f526
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 16863
content:
"The Paris Agreement has spurred the formulation of NDCs for 2030 \r and mid-century strategies around the world (cf. Chapter 4). This is \r giving researchers a  rich empirical basis to formulate accelerated \r policy packages taking national decarbonisation pathways as \r a starting point (Graichen et al. 2017; Jiang et al. 2017; van Soest \r et al. 2017b; Waisman et al. 2019). The concept is to identify good \r practice policies that had demonstrable impact on pushing low\u0002carbon options or reducing emissions in a  country or region and \r then consider a wider roll out of these policies taking into account \r regional specificities (den Elzen et al. 2015; Fekete et al. 2015, 2021; \r Kriegler et al. 2018a; Kuramochi et al. 2018; Roelfsema et al. 2018). \r A challenge for this approach is to account for the fact that policy \r effectiveness varies with different political environments in different \r geographies. As a result, a global roll out of good practice policies to \r [...]"


id: 8301218dccdb96c66fefd3149e9f7024
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 20175
content:
"[...] close the emissions gap will still be an idealised benchmark, but it is \r useful to understand how much could be gained from it."


id: 9462fe050aee2710bd9221a8e1119f45
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 23313
content:
"The marginal abatement cost of carbon, also called carbon price, is determined by the mitigation target under consideration: it \r describes the cost of reducing the last unit of emissions to reach the target at a given point in time. Total macroeconomic mitigation \r costs (or gains) aggregate the economy-wide impacts of investments in low-carbon solutions and structural changes away from \r emitting activities. The total macroeconomic effects of mitigation pathways are reported in terms of variations in economic output \r or consumption levels, measured against a  reference scenario, also called baseline, at various points in time or discounted over \r a given time period. Depending on the study, the reference scenario reflects specific assumptions about patterns of socio-economic \r development and assumes either no-climate policies or the climate policies in place or planned at the time the study was carried \r [...]"


id: 544c06025a9b22ce14c1b262121ca972
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 12107
content:
"[...] out. When available in the AR6 scenarios database, this second type of reference scenario, with trends from implemented policies \r until the end of 2020, has been chosen for computation of mitigation costs. In the vast majority of studies that have produced the \r body of work on the cost of mitigation assessed here, and in particular in all studies that have submitted global scenarios to the AR6 \r scenarios database except (Schultes et al. 2021), the feedbacks of climate change impacts on the economic development pathways \r are not accounted for. This omission of climate impacts leads to overly optimistic economic projections in the reference scenarios, in \r particular in reference scenarios with no or limited mitigation action where the extent of global warming is the greatest. Mitigation \r cost estimates computed against no or limited policy reference scenarios therefore omit economic benefits brought by avoided climate \r [...]"


id: 2c5f56ee64a0020d56305c97e9557a71
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 5074
content:
"[...] change impact along mitigation pathways, and should be interpreted with care (Grant et al. 2020). When aggregate economic benefits \r from avoided climate change impacts are accounted for, mitigation is a welfare-enhancing strategy (Section 3.6.2)."


id: 4c33bd3199d926e226e7849c8d0dac7
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 10665
content:
"If GDP or consumption in mitigation pathways are below the reference scenario levels, they are reported as losses or macroeconomic \r costs. Such cost estimates give an indication of how economic activity slows relative to the reference scenario; they do not necessarily \r describe, in absolute terms, a reduction of economic output or consumption levels relative to previous years along the pathway. Aggregate \r mitigation costs depend strongly on the modelling framework used and the assumptions about the reference scenario against which \r mitigation costs are measured, in particular whether the reference scenario is, or not, on the efficiency frontier of the economy. If the \r economy is assumed to be at the efficiency frontier in the reference scenario, mitigation inevitably leads to actual costs, at least in \r the short-run until the production frontier evolves with technical and structural change. Starting from a reference scenario that is not \r [...]"


id: 1256fd7fa7b8635836325f3cb1d38ab1
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 432
content:
"[...] on the efficiency frontier opens the possibility to simultaneously reduce emissions and obtain macroeconomic gains, depending on the \r design and implementation of mitigation policies. A number of factors can result in reference scenarios below the efficiency frontier, for \r instance distorting labour taxes and/or fossil fuel subsidies, misallocation or under-utilisation of production factors such as involuntary \r unemployment, imperfect information or non-rational behaviours. Although these factors are pervasive, the modelling frameworks used \r to construct mitigation pathways are often limited in their ability to represent them (Koberle et al. 2021)."


id: 1f4bddbb5c7ad8160b6baf1f6ac1dc47
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 2711
content:
"Estimates for the marginal abatement cost of carbon in mitigation \r pathways vary widely, depending on the modelling framework used \r and socio-economic, technological and policy assumptions. However, \r it is robust across modelling frameworks that the marginal abatement \r cost of carbon increases for lower temperature categories, with \r a higher increase in the short term than in the longer term (Figure 3.32, \r left panel) (high confidence). The marginal abatement cost of carbon \r increases non-linearly with the decrease of CO2 emissions level, but \r the uncertainty in the range of estimates also increases (Figure 3.33). \r Mitigation pathways with low-energy consumption patterns exhibit \r lower carbon values (Mejean et al. 2019; Meyer et al. 2021). In the \r context of the COVID-19 pandemic recovery, Kikstra et al. (2021a) also \r show that a  low-energy-demand recovery scenario reduces carbon \r prices for a 1.5degC-consistent pathway by 19% compared to a scenario \r [...]"


id: 79f90e73eb05e5578146ed43197472d2
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 18657
content:
"below the efficiency frontier, based on non-equilibrium economic \r theory, and assume that mitigation is undertaken in such a  way \r that green investments do not crowd out investment in other parts \r of the economy - and therefore offers an economic stimulus. In the \r context of the recovery from the COVID-19 crisis, it is estimated that \r a green investment push would initially boost the economy while also \r reducing GHG emissions (IMF 2020; Pollitt et al. 2021). Conversely, \r several studies find that only a  GDP non-growth/degrowth or post\u0002growth approach enable reaching climate stabilisation below 2degC \r (Hardt and O'Neill 2017; D'Alessandro et al. 2020; Hickel and Kallis \r 2020; Nieto et al. 2020), or to minimise the risks of reliance on high \r energy-GDP decoupling, large-scale CDR and large-scale renewable \r energy deployment (Keysser and Lenzen 2021). Similarly, feedbacks of \r financial system risk amplifying shocks induced by mitigation policy \r [...]"


id: 66022f3d89aad6a7d73eb914b82af27e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 15205
content:
"Aggregate economic activity and consumption levels in mitigation \r pathways are primarily determined by socio-economic development \r pathways but are also influenced by the stringency of the mitigation \r goal and the policy choices to reach the goal (high confidence). \r Mitigation pathways in temperature categories C1 and C2 entail \r losses in global consumption with respect to their baselines  - not \r including benefits of avoided climate change impacts nor co-benefits \r or co-harms of mitigation action - that correspond to an annualised \r reduction of consumption growth by 0.04 (median value) (interquartile \r range [0.02-0.06]) percentage points over the century. For pathways in \r temperature categories C3 and C4 this reduction in global consumption \r growth is  0.03 (median value) (interquartile range [0.01-0.05]) \r percentage points over the century. In the majority of studies that \r focus on the economic effects of mitigation without accounting for \r [...]"


id: 1473354b85bbd2bb92edff9296dcb661
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 820
content:
"[...] climate damages, global economic growth and consumption growth \r is reduced compared to baseline scenarios (that omit damages from \r climate change), but mitigation pathways do not represent an absolute \r decrease of economic activity level (Figure 3.34b,c)."


id: 228be0a6aaeedaf5ebb6fc6fb8f9217
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 3294
content:
"Mitigation pathways with early emissions reductions represent higher \r mitigation costs in the short-run but bring long-term gains for the \r economy compared to delayed transition pathways (high confidence). \r Pathways with earlier mitigation action bring higher long-term GDP \r than pathways reaching the same end-of-century temperature with \r weaker early action (Figure 3.34d). Comparing counterfactual history \r scenarios, Sanderson and  O'Neill (2020) also find that delayed \r mitigation action leads to higher peak costs. Rogelj et al. (2019b) \r and Riahi et al. (2021) also show that pathways with earlier timing \r of net zero CO2 lead to higher transition costs but lower long-term \r mitigation costs, due to dynamic effects arising from lock-in avoidance \r and learning effects. For example, Riahi et al.(2021) find that for a 2degC \r target, the GDP losses (compared to a  reference scenario without \r impacts from climate change) in 2100 are 5-70% lower in pathways \r [...]"


id: 35b2ec4c404b047613ec5653b7d8bf66
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"[...] that avoid net negative CO2 emissions and temperature overshoot \r than in pathways with overshoot. Accounting also for climate change \r damage, van der Wijst et al. (2021a) show that avoiding net negative \r emissions leads to a small increase in total discounted mitigation costs \r over 2020-2100, between 5% and 14% in their medium assumptions, \r but does not increase mitigation costs when damages are high and \r when using a low discount rate, and becomes economically attractive \r if damages are not fully reversible. The modelled cost-optimal balance \r of mitigation action over time strongly depends on the discount rate \r used to compute or evaluate mitigation pathways: lower discount \r rates favour earlier mitigation, reducing both temperature overshoot \r and reliance on net negative carbon emissions (Emmerling et al. "


id: 62ad243b80168bd12eeb6d35f37c197f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
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content:
"The economic repercussions of mitigation policies vary across \r countries (Aldy et al. 2016; Hof et al. 2017): regional variations \r exist in institutions, economic and technological development, and \r mitigation opportunities. For a globally uniform carbon price, carbon\u0002intensive and energy-exporting countries bear the highest economic \r costs because of a  deeper transformation of their economies and \r of trade losses in the fossil markets (Stern et al. 2012; Tavoni et al. \r 2015; Bohringer et al. 2021). This finding is confirmed in Figure 3.35. \r Since carbon-intensive countries are often poorer, uniform global \r carbon prices raise equity concerns (Tavoni et al. 2015). On the other \r hand, the climate economic benefits of mitigating climate change \r will be larger in poorer countries (Cross-Working Group Box 1 in this \r chapter). This reduces policy regressivity but does not eliminate it \r (Taconet et al. 2020; Gazzotti et al. 2021). Together with co-benefits, \r [...]"


id: 31cf5e434abf03acfc7eed65160d393c
created_at: 2023-04-19 13:23:08
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content:
"[...] such as health benefits of improved air quality, the economic benefits \r of mitigating climate change are likely to outweigh mitigation costs \r in many regions (Li et al. 2018, 2019; Scovronick et al. 2021)."


id: 245b117331c9a770c46e3dec923d3472
created_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
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content:
"Mitigation reduces the extent of climate change and its impacts on ecosystems, infrastructure, and livelihoods. This box summarises \r elements from the AR6 WGII report on aggregate climate change impacts and risks, putting them into the context of mitigation \r pathways. AR6 WGII provides an assessment of current lines of evidence regarding potential climate risks with future climate change, \r and therefore, the avoided risks from mitigating climate change. Regional and sectoral climate risks to physical and social systems are \r assessed (AR6 WGII Chapters 2-15). Over 100 of these are identified as Key Risks (KRs) and further synthesised by WGII Chapter 16 \r into eight overarching Representative Key Risks (RKRs) relating to low-lying coastal systems; terrestrial and ocean ecosystems; critical \r physical infrastructure, networks and services; living standards; human health; food security; water security; and peace and mobility \r [...]"


id: 2f251ba7b63ea015fb13d19de48afe12
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
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content:
"[...] (AR6 WGII Section  16.5.2). The RKR assessment finds that risks increase with global warming level, and also depend on socio\u0002economic development conditions, which shape exposure and vulnerability, and adaptation opportunities and responses. 'Reasons \r For Concern', another WGII aggregate climate-impacts risk framing, are also assessed to increase with climate change, with increasing \r risk for unique and threatened systems, extreme weather events, distribution of impacts, global aggregate impacts, and large-scale \r singular events (AR6 WGII Chapter  16). For human systems, in general, the poor and disadvantaged are found to have greater \r exposure level and vulnerability for a given hazard. With some increase in global average warming from today expected regardless \r of mitigation efforts, human and natural systems will be exposed to new conditions and additional adaptation will be needed (AR6 \r [...]"


id: b30db41b19c713f0917b8532141c141e
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 28743
content:
"[...] WGII Chapter 18). The range of dates for when a specific warming level could be reached depends on future global emissions, with \r significant overlap of ranges across emissions scenarios due to climate system response uncertainties (AR6 WGI Tables 4.2 and 4.5). \r The speed at which the climate changes is relevant to adaptation timing, possibilities, and net impacts."


id: 66c209a3d6f021260933bc051a3a99cc
created_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
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content:
"The AR6 WGII also assesses the growing literature estimating the global aggregate economic impacts of climate change and the social \r cost of carbon dioxide and other greenhouse gases (AR6 WGII Cross-Working Box ECONOMIC: Estimating Global Economic Impacts \r from Climate Change and the Social Cost of Carbon in AR6 WGII Chapter  16). The former represents aggregate estimates that \r inform assessment of the economic benefits of mitigation. This literature is characterised by significant variation in the estimates, \r including for today's level of global warming, due primarily to fundamental differences in methods, but also differences in impacts \r included, representation of socio-economic exposure, consideration of adaptation, aggregation approach, and assumed persistence \r of damages. The AR6 WGII's assessment identifies different approaches to quantification of aggregated economic impacts of climate \r [...]"


id: 7d8a37c61e8374a47f3431cd148e8616
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
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content:
"[...] change, including: physical modelling of impact processes, such as projected mortality rates from climate risks such as heat, vector- or \r waterborne diseases that are then monetised; structural economic modelling of impacts on production, consumption, and markets for \r economic sectors and regional economies; and statistical estimation of impacts based on observed historical responses to weather \r and climate. The AR6 WGII finds that variation in estimated global economic impacts increases with warming in all methodologies, \r indicating higher risk in terms of economic impacts at higher temperatures (high confidence). Many estimates are non-linear with \r marginal economic impacts increasing with temperature, although some show declining marginal economic impacts with temperature, \r and functional forms cannot be determined for all studies. The AR6 WGII's assessment finds that the lack of comparability between \r [...]"


id: 3306bb999002e6cd39d72e6207d99bb9
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
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content:
"[...] methodologies does not allow for identification of robust ranges of global economic impact estimates (high confidence). Further, AR6 \r WGII identifies evaluating and reconciling differences in methodologies as a research priority for facilitating use of the different lines \r of evidence (high confidence). However, there are estimates that are higher than AR5, indicating that global aggregate economic \r impacts could be higher than previously estimated (low confidence due to the lack of comparability across methodologies and lack of \r robustness of estimates) (AR6 WGII Cross-Working Box ECONOMIC)."


id: 10eee5f2842dc6b4e0dbf5d79ccb6c64
created_at: 2023-04-19 13:23:08
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content:
"Cross-Working Group Box  1, Figure  1 | Global aggregate economic benefits of mitigation from avoided climate change impacts in 2100 \r corresponding to shifting from a higher temperature category (4degC (3.75degC-4.25degC), 3degC (2.75degC-3.25degC), or above 2degC (2degC-2.5degC), to below \r 2degC (1.5degC-2degC), as well as from below 2degC to below 1.5degC (1degC-1.5degC)), from the five studies discussed in the text. Panel (a) is adapted from AR6 \r WGII Cross-Working Group Box ECONOMIC, Figure 1, showing global aggregate economic impact estimates (% global GDP loss relative to GDP without additional \r climate change) by temperature change level. All estimates are shown in grey. Estimates used for the computation of estimated benefits in 2100 in panel (b) are \r coloured for the selected studies, which provide results for different temperature change levels. See the AR6 WGII AR6 WGII Cross-Working Group Box ECONOMIC for \r [...]"


id: 8b85a1850c9d120397c277d6af615654
created_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
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content:
"[...] discussion and assessment of the estimates in panel (a) and the differences in methodologies. For B18 and T19, median estimates in the cluster are considered. Shape \r distinguishes the baseline scenarios. Temperature ranges are highlighted. HS17 estimates are based on their preferred model -50th percentile of non-catastrophic \r damage. Panel (b) shows the implied aggregate economic benefits in 2100 of a lower temperature increase. Economic benefits for point estimates are computed as \r a difference, while economic benefits from the curve HS17 are computed as ranges from the segment differences."


id: d15820ec05d8f9f98eca211942ed34d5
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 34182
content:
"from avoided climate change (Howard and Sterner 2017; Burke et al. 2018; Pretis et al. 2018; Kahn et al. 2019; Takakura et al. 2019). \r Burke et al. (2018), Pretis et al. (2018) and Kahn et al. (2019) are examples of statistical estimations of historical relationships between \r temperature and economic growth, whereas Takakura et al. (2019) is an example of structural modelling, which evaluates selected \r impact channels (impacts on agriculture productivity, undernourishment, heat-related mortality, labour productivity, cooling/heating \r demand, hydro-electric and thermal power generation capacity and fluvial flooding) with a general equilibrium model. Howard and \r Sterner (2017) and Rose et al. (2017b) estimate damage functions that can be used to compute the economic benefits of mitigation \r [...]"


id: b88421bfd52943daecdd5765aa7d8a74
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 29673
content:
"[...] from avoiding a given temperature level for a lower one. Howard and Sterner (2017) estimate a damage function from a meta\u0002analysis of aggregate economic impact studies, while Rose et al. (2017b) derive global functions by temperature and socio-economic \r drivers from stylised aggregate cost-benefit-analysis (CBA) integrated assessment models (IAMs) using diagnostic experiments. Cross\u0002Working Group Box 1, Figure 1 summarises the global aggregate economic benefits in 2100 of avoided climate change impacts from \r individual studies corresponding to shifting from a higher temperature category (above 3degC, below 3degC or below 2.5degC) to below 2degC, \r as well as from below 2degC to below 1.5degC. Benefits are positive and increase with the temperature gap for any given study, and this \r result is robust across socio-economic scenarios. The Figure provides evidence of a wide range of quantifications, and illustrates the \r [...]"


id: 7b80a16b1e638322ddb0349cb552d473
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
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content:
"[...] important differences associated with methods. Panel a puts the studies used to calculate aggregate economic benefits arising from \r avoided impacts into the context of the broader set of studies assessed in WGII (Section 16.6.2 of this report, AR6 WGII Cross-Working \r Group Box ECONOMIC,). However, economic benefits in 2100 arising from avoided impacts cannot be directly computed from damage \r estimates across this broader set of studies, due to inconsistencies - different socio-economic assumptions, scenario designs, and \r counterfactual reference scenarios across studies. Furthermore, these types of estimates cannot be readily compared to mitigation \r cost estimates. The comparison would require a framework that ensures consistency in assumptions and dynamics and allows for \r consideration of benefits and costs along the entire pathway."


id: 99302a15e5d6cbeb886b9268c4c1141f
created_at: 2023-04-19 13:23:08
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content_type: text
index: climate_gpt_v2
vector_id: 24165
content:
"Cost-benefit analyses (CBA) aim to balance all costs and benefits \r in a  unified framework (Nordhaus, 2008). Estimates of economic \r benefits from avoided climate change impacts depend on the types \r of damages accounted for, the assumed exposure and vulnerability \r to these damages as well as the adaptation capacity, which in \r turn are based on the development pathway assumed (Cross\u0002Working Group Box 1 in this chapter). CBA IAMs raised criticism, in \r particular for omitting elements of dynamic realism, such as inertia, \r induced innovation and path dependence, in their representation of \r mitigation (Grubb et al. 2021), and for underestimating damages \r from climate change, missing non-monetary damages, the uncertain \r and heterogeneous nature of damages and the risk of catastrophic \r damages (Stern 2013, 2016; Diaz and Moore 2017; NASEM 2017; \r Pindyck 2017; Stoerk et al. 2018; Stern and Stiglitz 2021). Emerging \r [...]"


id: baec341e42815c60fcd7a8a72594dc77
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content:
"[...] literature has started to address those gaps, and integrated into cost\u0002benefit frameworks the account of heterogeneity of climate damage \r and inequality (Dennig et al. 2015; Budolfson et al. 2017; Fleurbaey \r et al. 2019; Kornek et al. 2021), damages with higher persistence, \r including damages on capital and growth (Moyer et al. 2014; Dietz \r and Stern 2015; Moore and Diaz 2015; Guivarch and Pottier 2018; \r Ricke et al. 2018; Piontek et al. 2019), risks of tipping points (Cai et al. \r 2015, 2016; Lontzek et al. 2015; Lemoine and Traeger 2016; van der \r Ploeg and de Zeeuw 2018; Cai and Lontzek 2019; Nordhaus 2019; \r Yumashev et al. 2019; Taconet et al. 2021) and damages to natural \r capital and non-market goods (Tol 1994; Sterner and Persson 2008; \r Bastien-Olvera and Moore 2020; Drupp and Hansel 2021)."


id: 7915523a250e411fb571d815ca0e4eb4
created_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 18492
content:
"Lontzek 2019), in the consideration of damages to natural capital \r and non-market goods (Bastien-Olvera and Moore 2020) or in the \r combination of updated representations of carbon cycle and climate \r modules, updated damage estimates and/or updated representations \r of economic and mitigation dynamics (Dietz and Stern 2015; Hansel \r et al. 2020; Wei et al. 2020; van der Wijst et al. 2021b). In the studies \r cited above that perform a sensitivity analysis, this result is found to \r be robust to a wide range of assumptions on social preferences (in \r particular, on inequality aversion and pure rate-of-time preference) \r and holds except if assumptions of economic damages from climate \r change are in the lower end of available estimates and the pure rate\u0002of-time preference is in the higher range of values usually considered \r (typically above 1.5%). However, although such pathways bring net \r benefits over time (in terms of aggregate discounted present value), \r [...]"


id: 390bf1c8da2d7498ab4dd4f5532e5083
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content:
"[...] they involve distributional consequences and transition costs (Brown \r et al. 2020; Brown and Saunders 2020) (Sections 3.6.1.2 and 3.6.4)."


id: 551bdbfaf9f9157ab14447c9979b77fa
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 12248
content:
"Each of these factors, when accounted for in a  CBA framework, \r tends to increase the welfare benefit of mitigation, thus leading \r to stabilisation at a  lower temperature in optimal mitigation \r pathways. The limitations in CBA modelling frameworks remain \r significant, their ability to represent all damages incomplete, and \r the uncertainty in estimates remains large. However, emerging \r evidence suggests that, even without accounting for co-benefits \r of mitigation on other sustainable development dimensions (see \r Section 3.6.3 for further details about on co-benefits), global benefits \r of pathways that limit warming to 2degC outweigh global mitigation \r costs over the 21st century: depending on the study, the reason for \r this result lies in assumptions of economic damages from climate \r change in the higher end of available estimates (Moore and Diaz \r 2015; Ueckerdt et al. 2019; Brown and Saunders 2020; Glanemann \r [...]"


id: 1f50370a23341259bd3ea0ce608144a2
created_at: 2023-04-19 13:23:08
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vector_id: 2712
content:
"Systematic reviews of the literature on co-benefits and trade-offs \r from mitigation actions have shown that only a  small portion of \r articles provide economic quantifications (Deng et al. 2017; Karlsson \r et al. 2020). Most economic quantifications use monetary valuation \r approaches. Improved air quality, and associated health effects, \r are the co-benefit category dominating the literature (Markandya \r et al. 2018; Vandyck et al. 2018; Scovronick et al. 2019; Howard et al. \r 2020; Karlsson et al. 2020b; Rauner et al. 2020a,b), but some studies \r cover other categories, including health effects from diet change \r (Springmann et al. 2016b) and biodiversity impacts (Rauner et al. \r 2020a). Regarding health effects from air quality improvement and \r from diet change, co-benefits are shown to be of the same order of \r magnitude as mitigation costs (Thompson et al. 2014; Springmann \r et al. 2016a,b; Markandya et al. 2018; Scovronick et al. 2019b; \r [...]"


id: 4801cc8cac5e012e9ef3669f222e4790
created_at: 2023-04-19 13:23:08
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content:
"[...] Howard et al. 2020; Rauner et al. 2020a,b; Liu et al. 2021; Yang \r et al. 2021). Co-benefits from improved air quality are concentrated \r sooner in time than economic benefits from avoided climate change \r impacts (Karlsson et al. 2020), such that when accounting both \r for positive health impacts from reduced air pollution and for the \r negative climate effect of reduced cooling aerosols, optimal GHG \r mitigation pathways exhibit immediate and continual net economic \r benefits (Scovronick et al. 2019a). However, AR6 WGI Chapter  6 \r (Section 6.7.3) shows a delay in air pollution reduction benefits when \r they come from climate change mitigation policies compared with air \r pollution reduction policies."


id: d38cda070548d0f9435e61f76b780b42
created_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 34557
content:
"Mitigation affects work through multiple channels, which impacts \r geographies, sectors and skill categories differently (Fankhaeser \r et al. 2008; Bowen et al. 2018; Malerba and Wiebe 2021). Aggregate \r employment impacts of mitigation pathways mainly depend on \r the aggregate macroeconomic effect of mitigation (Sections  3.6.1 \r and  3.6.2) and of mitigation policy design and implementation \r (Freire-Gonzalez 2018) (Section 4.2.6.3). Most studies that quantify \r overall employment implications of mitigation policies are conducted \r at the national or regional scales (Section 4.2.6.3), or sectoral scales \r (e.g., see Chapter 6 for energy sector jobs). The evidence is limited \r at the multinational or global scale, but studies generally find \r small differences in aggregate employment in mitigation pathways \r compared to baselines: the sign of the difference depends on the \r assumptions and modelling frameworks used and the policy design \r [...]"


id: b82b066a071f751db0f0b42388577527
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vector_id: 29616
content:
"[...] tested, with some studies or policy design cases leading to small \r increases in employment (Chateau and Saint-Martin 2013; Pollitt \r et al. 2015; Barker et al. 2016; Garcia-Casals et al. 2019; Fujimori \r et al. 2020a; Vrontisi et al. 2020; Malerba and Wiebe 2021) and other \r studies or policy design cases leading to small decreases (Chateau \r and Saint-Martin 2013; Vandyck et al. 2016). The small variations in \r aggregate employment hide substantial reallocation of jobs across \r sectors, with jobs creation in some sectors and jobs destruction in \r others. Mitigation action through thermal renovation of buildings, \r installation and maintenance of low-carbon generation, and the \r expansion of public transit lead to job creation, while jobs are lost \r in fossil fuel extraction, energy supply and energy-intensive sectors \r in mitigation pathways (von Stechow et al. 2015, 2016; Barker et al. \r 2016; Fuso Nerini et al. 2018; Perrier and Quirion 2018; Pollitt and \r [...]"


id: a6c8d2765e6ef9b7e0d46122c4d64f0e
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index: climate_gpt_v2
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content:
"[...] Mercure 2018; Dominish et al. 2019; Garcia-Casals et al. 2019). In \r the energy sector, job losses in the fossil fuel sector are found to \r be compensated by gains in wind and solar jobs, leading to a net \r increase in energy sector jobs in 2050 in a  mitigation pathway \r compatible with stabilisation of the temperature increase below \r 2degC (Pai et al. 2021). Employment effects also differ by geographies, \r with energy-importing regions benefiting from net job creations but \r energy-exporting regions experiencing very small gains or suffering "


id: 45c0d7f314518688453157310614705c
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index: climate_gpt_v2
vector_id: 9485
content:
"A few studies consider both mitigation policies' distributional impacts \r and avoided climate change impacts on inequalities along mitigation \r pathways. Rezai et al. (2018) find that unmitigated climate change \r impacts increase inequality, whereas mitigation has the potential \r to reverse this effect. Considering uncertainty in socio-economic \r assumptions, emission pathways, mitigation costs, temperature \r response, and climate damage, Taconet et al. (2020) show that the \r uncertainties associated with socio-economic assumptions and \r damage estimates are the main drivers of future inequalities between \r countries and that in most cases mitigation policies reduce future \r inequalities between countries. Gazzotti et al. (2021) show that \r inequality persists in 2degC-consistent pathways due to regressivity \r of residual climate damages. However, the evidence on mitigation \r pathways' implications for global inequality and poverty remains \r [...]"


id: 97278b7c54fbfa459263ae6c4416b7a8
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content:
"[...] limited, and the modelling frameworks used have limited ability to \r fully represent the different dimensions of inequality and poverty and \r all the mechanisms by which mitigation affects inequality and poverty \r (Rao et al. 2017a; Emmerling and Tavoni 2021; Jafino et al. 2021)."


id: 24af0832f9ca9c04debbe1fcf765221b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 3649
content:
"Mitigation policies can have important distributive effects between \r and within countries, either reducing or increasing economic \r inequality and poverty, depending on policy instruments' design \r and implementation (see Section  3.6.1.2 for an assessment of \r the distribution of mitigation costs across regions in mitigation \r pathways; Sections 3.7 and 4.2.2.6, and Box 3.6 for an assessment of \r the fairness and ambition of NDCs; and Section 4.5 for an assessment \r of national mitigation pathways along the criteria of equity, including \r Just Transition, as well as Section 17.4.5 for equity in a Just Transition). \r For instance, emissions taxation has important distributive effects, \r both between and within income groups (Cronin et al. 2018b; Klenert \r et al. 2018; Pizer and Sexton 2019; Douenne 2020; Steckel et al. \r 2021). These effects are more significant in some sectors, such as \r transport, and depend on country-specific consumption structures \r [...]"


id: c63c6dc09e0eeef532f88d6559c80528
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index: climate_gpt_v2
vector_id: 32188
content:
"[...] (Dorband et al. 2019; Fullerton and Muehlegger 2019; Ohlendorf \r et al. 2021). However, revenues from emissions taxation can be used \r to lessen their regressive distributional impacts or even turn the \r policy into a  progressive policy reducing inequality and/or leading \r to gains for lower-income households (Cameron et al. 2016; Jakob \r and Steckel 2016; Fremstad and Paul 2019; Fujimori et al. 2020b; \r Bohringer et al. 2021; Budolfson et al. 2021; Soergel et al. 2021b; \r Steckel et al. 2021). Mitigation policies may affect the poorest \r through effects on energy and food prices (Hasegawa et al. 2015; \r Fujimori et al. 2019). Markkanen and Anger-Kraavi (2019) and Lamb \r et al. (2020) synthesize evidence from the existing literature on social \r co-impacts of climate change mitigation policy and their implications \r for inequality. They show that most policies can compound or \r lessen inequalities depending on contextual factors, policy design \r [...]"


id: 41be09b5f91f7745ba32b2a2f7f99c5
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 8762
content:
"[...] and policy implementation, but that negative inequality impacts of \r climate policies can be mitigated (and possibly even prevented), \r when distributive and procedural justice are taken into consideration \r in all stages of policymaking, including policy planning, development \r and implementation, and when focusing on the carbon intensity \r of lifestyles, sufficiency and equity, well-being and decent living \r standards for all (Section 13.6)."


id: f414de4bbe54fa63f61dafad237f44cf
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 40314
content:
"This section covers the long-term interconnection of sustainable \r development and mitigation, taking forward the holistic vision of \r sustainable development described in the SDGs (Brandi 2015; Leal \r Filho et al. 2018). Recent studies have explored the aggregated \r impact of mitigation for multiple sustainable-development \r dimensions (Hasegawa et al. 2014; Bertram et al. 2018; Fuso Nerini \r et al. 2018; Grubler et al. 2018; McCollum et al. 2018b; Soergel et al. \r 2021a; van Vuuren et al. 2019). For instance, Figure  3.38 shows \r selected mitigation co-benefits and trade-offs based on a  subset \r of models and scenarios, since so far many IAMs do not have \r a comprehensive coverage of SDGs (Rao et al. 2017a; van Soest et al. \r 2019). Figure 3.38 shows that mitigation likely leads to increased \r forest cover (SDG 15  - life on land) and reduced mortality from \r ambient PM2.5 pollution (SDG 3  - good health and well-being) \r [...]"


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vector_id: 21773
content:
"[...] compared to reference scenarios. However, mitigation policies \r can also cause higher food prices and an increased population at \r risk of hunger (SDG 2  - zero hunger) and relying on solid fuels \r (SDG 3 - good health and well-being; and SDG 7 - affordable and "


id: f71b9c99979a31801d8cebba7d9a1693
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 40846
content:
"Figure 3.39 | Sustainable development effects of mitigation to 1.5degC. Panel (a): benefits of mitigation from avoided impacts. Panel (b): sustainability co-benefits \r and trade-offs of narrow mitigation policies (averaged over multiple models). Panel (c): sustainability co-benefits and trade-offs of mitigation policies integrating Sustainable \r Development Goals. Scale: 0% means no change compared to 3degC (left) or current policies (middle and right). Blue values correspond to proportional improvements, red values \r to proportional worsening. Note: only the left panel considers climate impacts on sustainable development; the middle and right panels do not. 'Res' C&P' stands for Responsible \r Consumption and Production (SDG 12). Data are from Byers et al. (2018) (left), SP/Soergel et al. (2021a) (right). Methods used in middle panel: for biodiversity, Ohashi et al. \r [...]"


id: e22ef6faaf97c9d6bd3d03f7f672ecb9
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 37073
content:
"[...] (2019); for ecotoxicity and eutrophication, Arvesen et al. (2018) and Pehl et al. (2017); for energy access, Cameron et al. (2016). 'Energy services' on the right is a measure of \r useful energy in buildings and transport. 'Food prices' and 'Risk of hunger' in the middle panel are the same as in Figure 3.38."


id: 6c872956eebae207a2819cb5e3b7dff1
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 16384
content:
"There is high confidence (medium evidence, high agreement) that the eradication of extreme poverty and universal access to energy \r can be achieved without resulting in significant GHG emissions (Tait and Winkler 2012; Chakravarty and Tavoni 2013; Pachauri et al. \r 2013; Pachauri 2014; Rao 2014; Hubacek et al. 2017b; Poblete-Cazenave et al. 2021). There is also high agreement in the literature \r that a focus on well-being and decent living standards for all can reduce disparities in access to basic needs for services concurrently \r with climate mitigation (Section 5.2). Mitigation pathways in which national redistribution of carbon-pricing revenues is combined with \r international climate finance, achieve poverty reduction globally (Fujimori et al. 2020b; Soergel et al. 2021b). Carbon-pricing revenues \r in mitigation pathways consistent with limiting temperature increase to 2degC could also contribute to finance investment needs for \r [...]"


id: d0f5c527142825b5b6556a880306db82
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 34107
content:
"[...] basic infrastructure (Jakob et al. 2016) and the achievement of the SDGs (Franks et al. 2018)."


id: d207e55598dd88adf7b811d7bbab2719
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 34304
content:
"Several studies conclude that reaching higher income levels globally, beyond exiting extreme poverty, and achieving more qualitative \r social objectives and well-being, are associated with higher emissions (Ribas et al. 2017, 2019; Hubacek et al. 2017b; Fischetti 2018; \r Scherer et al. 2018). Studies give divergent results on the effect of economic inequality reduction on emissions, with either an increase \r or a decrease in emissions (Berthe and Elie 2015; Lamb and Rao 2015; Grunewald et al. 2017; Hubacek et al. 2017a,b; Jorgenson et al. \r 2017; Knight et al. 2017; Mader 2018; Rao and Min 2018; Liu et al. 2019; Sager 2019; Balezentis et al. 2020; Liobikiene 2020; Liobikiene \r and Rimkuviene 2020; Liu et al. 2020b; Millward-Hopkins and Oswald 2021). However, the absolute effect of economic inequality \r reduction on emissions remains moderate, under the assumptions tested. For instance, Sager (2019) finds that a full redistribution \r [...]"


id: 4da5f53f7fcb1e522fa8898c037e08b8
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 10939
content:
"[...] of income leading to equality among US households in a counterfactual scenario for 2009 would raise emissions by 2.3%; and Rao \r and Min (2018) limit to 8% the maximum plausible increase in emissions that would accompany the reduction of the global Gini \r coefficient from its current level of 0.55 to a level of 0.3 by 2050. Similarly, reduced income inequality would lead to a global energy\u0002demand increase of 7% (Oswald et al. 2021). Reconciling mitigation and inequality reduction objectives requires policies that take into \r account both objectives at all stages of policymaking (Markkanen and Anger-Kraavi 2019), including focusing on the carbon intensity \r of lifestyles (Scherer et al. 2018), attention to sufficiency and equity (Fischetti 2018), and targeting the consumption of the richest and \r highest-emitting households (Otto et al. 2019)."


id: 6078ebc1343b7ee1253922654326ef74
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 14278
content:
"Mitigating climate change while ensuring that food security is \r not adversely affected requires a range of different strategies and \r interventions (high confidence). Fujimori et al. (2018) explore possible \r economic solutions to these unintended impacts of mitigation \r (e.g.,  agricultural subsidies, food aid, and domestic reallocation of \r income) with an additional small (<0.1%) change in global GDP. \r Targeted food-security support is needed to shield impoverished and \r vulnerable people from the risk of hunger that could be caused by the \r economic effects of policies narrowly focussed on climate objectives. \r Introducing more biofuels and careful selection of bioenergy \r feedstocks could also reduce negative impacts (FAO, IFAD, UNICEF, \r WFP and WHO, 2017). Reconciling bioenergy demands with food and \r biodiversity, as well as competition for land and water, will require \r changes in food systems  - agricultural intensification, open trade, \r [...]"


id: cebdec2f289fe11d19ba8ce9e1f000d
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 33712
content:
"[...] less consumption of animal products and reduced food losses - and \r advanced biotechnologies (Henry et al. 2018; Xu et al. 2019)."


id: e828f2ac998d45a9404ee3fd670970f7
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 38172
content:
"The effects of mitigation on water demand depends on the mitigation \r technologies deployed (high confidence) (Chaturvedi et al. 2013a,b; \r Hanasaki et al. 2013; Kyle et al. 2013; Hejazi et al. 2014; Bonsch et al. \r 2016; Jakob and Steckel 2016; Mouratiadou et al. 2016; Fujimori \r et al. 2017; Maizi et al. 2017; Bijl et al. 2018; Cui et al. 2018; Graham \r et al. 2018; Parkinson et al. 2019). Some mitigation options could \r increase water consumption (volume removed and not returned) \r while decreasing withdrawals (total volume of water removed, \r some of which may be returned) (Kyle et al. 2013; Fricko et al. 2016; \r Mouratiadou et al. 2016; Parkinson et al. 2019). Bioenergy and \r BECCS can increase water withdrawals and water consumption (high \r confidence) (Chaturvedi et al. 2013a; Kyle et al. 2013; Hejazi et al. \r 2014; Bonsch et al. 2016; Jakob and Steckel 2016; Mouratiadou et al. \r 2016; Fujimori et al. 2017; Maizi et al. 2017; Seferian et al. 2018; \r [...]"


id: fad8f221b6ef9eb2510bb613d3af0625
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 41513
content:
"[...] Yamagata et al. 2018; Parkinson et al. 2019) (AR6 WGII Chapter 4). \r DACCS (Fuhrman et al. 2020) and CCS (Kyle et al. 2013; Fujimori "


id: fee01f1ce8eb6a30aa9513c2f6eaa471
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 42238
content:
"The additional energy demand to meet the basic cooling requirement \r in the Global South is estimated to be much larger than the \r electricity needed to provide basic residential energy services \r universally via clean and affordable energy, as defined by SDG 7 (IEA \r 2019; Mastrucci et al. 2019) (high confidence). If conventional air\u0002conditioning systems are widely deployed to provide cooling, energy \r use could rise significantly (van Ruijven et al. 2019; Bezerra et al. \r 2021; Falchetta and Mistry 2021), thus creating a positive feedback \r further increasing cooling demand. However, the overall emissions \r are barely altered by the changing energy demand composition with \r reductions in heating demand occurring simultaneously (Isaac and \r van Vuuren 2009; Labriet et al. 2015; McFarland et al. 2015; Clarke \r et al. 2018). Some mitigation scenarios show price increases of clean \r cooking fuels, slowing the transition to clean cooking fuels (SDG 7.1) \r [...]"


id: 4b95caec613d202d166b15a2c833e025
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 10560
content:
"[...] and leaving a billion people in 2050 still reliant on solid fuels in South \r Asia (Cameron et al. 2016)."


id: 61394b4db8a0fa730554557c2efe3f79
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 14407
content:
"Climate change alters the production of energy through changes \r in temperature (hydropower, fossil fuel, nuclear, solar, bioenergy, \r transmission and pipelines), precipitation (hydropower, fossil fuel, \r nuclear and bioenergy), windiness (wind and wave), and cloudiness \r (solar) (high confidence). Increases in temperature reduce efficiencies \r of thermal power plants (e.g.,  fossil fuel and nuclear plants) with \r air-cooled condensers by  0.4-0.7% per degC increase in ambient \r temperature (Cronin et al. 2018a; Simioni and Schaeffer 2019; \r Yalew, S.G. et al. 2020). Potentials and costs for renewable energy \r technologies are also affected by climate change, though with \r considerable regional variation and uncertainty (Gernaat et al. 2021). \r Biofuel yields could increase or decrease depending on the level of \r warming, changes in precipitation, and the effect of CO2 fertilisation \r (Calvin et al. 2013; Kyle et al. 2014; Gernaat et al. 2021). Coastal \r [...]"


id: a64330d8f89c72a7d36f5905fcf3610d
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 26467
content:
"Cost-benefit analyses for climate mitigation in urban settings that do \r not account for health may underestimate the potential cost savings \r and benefits (Hess et al. 2020). The net health benefits of controlling \r air pollution as part of climate mitigation efforts could reach trillions \r of dollars annually, depending on the air quality policies adopted \r globally (Markandya et al. 2018; Scovronick et al. 2019b). Air pollution \r reductions resulting from meeting the Paris Agreement targets \r were estimated to provide health co-benefits-to-mitigation ratios \r of between 1.4 and 2.5 (Markandya et al. 2018). In Asia, the benefit of \r air pollution reduction through mitigation measures was estimated to \r reduce premature mortality by 0.79 million, with an associated health \r benefit of USD2.8 trillion versus mitigation costs of USD840 billion, \r equating to 6% and 2% of GDP, respectively (Xie et al. 2018). Similarly, \r stabilising radiative forcing to  3.4 W  m-2 in South Korea could \r [...]"


id: 2dd28deb44ee156932e00ad7db43e879
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 5343
content:
"[...] cost USD1.3-8.5 billion in 2050 and could lead to a USD23.5 billion \r cost reduction from the combined benefits of avoided premature \r mortality, health expenditures, and lost work hours (Kim et al. 2020). \r The health co-benefits related to physical exercise and reduced air \r pollution largely offset the costs of implementing low-CO2-emitting \r urban mobility strategies in three Austrian cities (Wolkinger et al. 2018)."


id: fedc1ef6a5a5cdd62532757a0080144c
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 42236
content:
"Climate change mitigation actions to reduce or slow negative impacts \r on ecosystems are likely to support the achievement of SDGs 2, 3, 6, \r 12, 14 and 15. Some studies show that stringent and constant GHG \r mitigation practices bring a net benefit to global biodiversity even \r if land-based mitigation measures are also adopted (Ohashi et al. \r 2019), as opposed to delayed action which would require much more \r widespread use of BECCS. Scenarios based on demand reductions \r of energy and land-based production are expected to avoid many \r such consequences, due to their minimised reliance on BECCS (Conijn \r et al. 2018; Grubler et al. 2018; Bowles et al. 2019; Soergel et al. \r 2021a). Stringent mitigation that includes reductions in demand for \r animal-based foods and food waste could also relieve pressures on \r land use and biodiversity (high confidence), both directly by reducing \r agricultural land requirements (Leclere et al. 2020) and indirectly by \r [...]"


id: 10435ae4b2c9cf00386e24e7251a05e2
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 49
content:
"Effectively responding to climate change and achieving sustainable \r development requires overcoming a series of challenges to transition \r away from fossil-based economies. Feasibility can be defined in many \r ways (Chapter 1). The political science literature (Majone 1975a,b; \r Gilabert and Lawford-Smith 2012) distinguishes the feasibility of \r 'what' (i.e., emission reduction strategies), 'when and where' (i.e., in \r the year 2050, globally) and 'whom' (i.e.,  cities). It distinguishes \r desirability from political feasibility (von Stechow et al. 2015): the \r former represents a normative assessment of the compatibility with \r societal goals (i.e., SDGs), while the latter evaluates the plausibility of \r what can be attained given the prevailing context of transformation \r (Nielsen et al. 2020). Feasibility concerns are context and time \r dependent and malleable: enabling conditions can help overcome \r them. For example, public support for carbon taxes has been hard to \r [...]"


id: 829f1cc2b19d81b102857bb4a79a4c18
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 20107
content:
"[...] secure but appropriate policy design and household rebates can help \r dissipate opposition (Murray and Rivers 2015; Carattini et al. 2019)."


id: 9c7a1150ace12af4aa6c25e850d31fbc
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 24782
content:
"Most of the existing literature has focused on the technological \r dimensions, given the technology focus of models and the ease of \r comparison. The literature points to varied findings. Some suggest that \r scenarios envision technological progress consistent with historical \r benchmarks (Wilson et al. 2013; Loftus  et al. 2015). Others that \r scenarios exceed historically observed rates of low-carbon technology \r deployment and of energy demand transformation globally (van der \r Zwaan et al. 2013; Napp et al. 2017; Cherp et al. 2021; Semieniuk \r et al. 2021), but not for all countries (Cherp et al. 2021). The reason for \r these discrepancies depends on the unit of analysis and the indicators \r used. Comparing different kinds of historical indicators, (van Sluisveld \r et al. 2015) find that indicators that look into the absolute change of \r energy systems remain within the range of historical growth frontiers \r [...]"


id: 22e7cf30d272df6c4a79f9337b4bca06
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 3345
content:
"[...] for the next decade, but increase to unprecedented levels before mid\u0002century. Expert assessments provide another way of benchmarking \r scenarios, though they have shown to be systematically biased \r (Wiser et al. 2021) and to underperform empirical methods (Meng \r et al. 2021). van Sluisveld et al. (2018a) find that scenarios and \r experts align for baseline scenarios but differ for low-carbon ones. \r Scenarios rely more on conventional technologies based on existing \r infrastructure (such as nuclear and CCS) than what is forecasted by \r experts. Overall, the technology assessment of the feasibility space \r highlights that Paris-compliant transformations would have few \r precedents, but not zero (Cherp et al. 2021)."


id: 6529b6fcd9a766fa28bf6218de1d7e47
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 15065
content:
"be comprehensively understood. It is of vital importance that the \r process of technical change must be considered in its institutional \r and social context so as to ascertain potential transition barriers \r which in turn provide an indication of pathway feasibility. In order \r to address the multitudinous challenges associated with low\u0002carbon transition feasibility and governance, it has been opined \r that the robustness of evaluating pathways may be improved by the \r bridging of differing quantitative-qualitative analytical approaches \r (Haxeltine et al. 2008; Foxon et al. 2010; Hughes 2013; Wangel et al. \r 2013; Li et al. 2015; Turnheim et al. 2015; Geels et al. 2016a,b, 2020; \r Moallemi et al. 2017; De Cian et al. 2020; Li and Strachan 2019). The \r rationale for such analytical bridging is to rectify the issue that in \r isolation each disciplinary approach can only generate a fragmented \r comprehension of the transition pathway with the consequence \r [...]"


id: cb8b8e18cbde55f890c761d6bf5d50c
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 33140
content:
"[...] being an incomplete identification of associated challenges in terms \r of feasibility. Concerning low-carbon transition pathways generated \r by IAMs, it has been argued that a comprehensive analysis should \r include social scientific enquiry (Geels et al. 2016a, 2020; van Sluisveld \r et al. 2018b). The normative analysis of IAM pathways assists in the \r generation of a vision or the formulation of a general plan with this \r being complemented by socio-technical transition theory (Geels et al. \r 2016a). Such an approach thereby allowing for the socio-political \r feasibility and the social acceptance and legitimacy of low-carbon \r options to be considered. Combining computer models and the multi\u0002level perspective can help identify 'transition bottlenecks' (Geels \r et al. 2020). Similarly, increased resolution of integrated assessment \r models' actors has led to more realistic narratives of transition in terms \r of granularity and behaviour (McCollum et al. 2017; van  Sluisveld \r [...]"


id: 3298f42c64b6554a4cdf007166101ce6
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 6163
content:
"[...] et al. 2018b). Increased data availability of actual behaviour from \r smart technology lowers the barriers to representing behavioural \r change in computer simulations, and thus better represents crucial \r demand-side transformations (Creutzig et al. 2018). Increasing the \r model resolution is a meaningful way forward. However, integrating \r a much broader combination of real-life aspects and dynamics into \r models could lead to an increased complexity that could restrict them \r to smaller fields of applications (De Cian et al. 2020)."


id: 68fee2a2a21ae8a845f24caca93a4d7f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 15744
content:
"In Figure  3.43, we show the results of applying the methodology \r of Brutschin et al. (2021) to the AR6 scenarios database. The \r charts highlight the dynamic nature of feasibility risks, which are \r mostly concentrated in the decades before mid-century except \r for geophysical risks driven by CO2 removals later in the century. \r Different dimensions pose differentiated challenges: for example, \r institutional feasibility challenges appear to be the most relevant, in \r line with the qualitative literature. Thus, feasibility concerns might be \r particularly relevant in countries with weaker institutional capacity. \r Figure 3.43 also highlights the key roles of policy and technology as \r enabling factors. In particular (panel b), internationally coordinated \r and immediate emission reductions allow to smooth out feasibility \r concerns and reduce long-term challenges compared to delayed \r policy action, as a  result of a  more gradual transition and lower \r [...]"


id: 3ad63b9f4b2c63f091d9761416e6d167
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 7549
content:
"[...] requirements of CO2 removals. For the same climate objective, \r different Illustrative Mitigation Pathways entail somewhat different \r degrees and distributions of implementation challenges (panel c)."


id: 9cb10c7541e2dd93d62faa8fed98ca89
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 24805
content:
"One of the most relevant factors affecting mitigation pathways and \r their feasibility is the rate and kind of socio-economic development. \r For example, certain socio-economic trends and assumptions \r about policy effectiveness preclude achieving stringent mitigation \r futures (Rogelj et al. 2018b). The risk of failure increases markedly \r in high-growth, unequal and/or energy-intensive worlds such as \r those characterised by the shared socio-economic pathways SSP3, \r SSP4 and SSP5. On the other hand, socio-economic development \r conducive to mitigation relieves the energy sector transformation \r from relying on large-scale technology development: for example, \r the amount of biomass with CCS in SSP1 is one third of that in SSP5. \r The reason why socio-economic trends matter so much is that they \r both affect the CO2 emissions in counterfactual scenarios as well \r as the mitigation capacity (Riahi et al. 2017; Rogelj et al. 2018b). \r [...]"


id: 4098ba18f874ff47e9c86aead1f73af5
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 8554
content:
"[...] Economic growth assumptions are the most important determinant \r of scenario emissions (Marangoni et al. 2017). Degrowth and post\u0002growth scenarios have been suggested as valuable alternatives to \r be considered (Hickel et al. 2021; Keysser and Lenzen 2021), though \r substantial challenges remain regarding political feasibility (Keysser \r and Lenzen 2021)."


id: fcd2f3bd1a15631e1c5e07b9f273de31
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 41845
content:
"The AR6 scenarios database contains 3131 scenarios of which \r 2425 with global scope were considered by this chapter, generated \r by almost 100 different model versions, from more than 50 model \r families. Of the 1686 vetted scenarios, 1202 provided sufficient \r information for a climate categorisation. Around 46% of the pathways \r are consistent with an end-of-century temperature of at least likely\r limiting warming to below 2degC (>67%). There are many ways of \r constructing scenarios that limit warming to a particular level and \r the choice of scenario construction has implications for the timing of \r both net zero CO2 and GHG emissions and the deployment of CDR \r (Emmerling et al. 2019; Rogelj et al. 2019b; Johansson et al. 2020). \r The AR6 scenarios database includes scenarios where temperature \r is temporarily exceeded (40% of all scenarios in the database \r have median temperature in 2100 that is 0.1degC lower than median \r [...]"


id: 5e9463925b7a30c1595271170edbff94
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 13929
content:
"[...] peak temperature). Climate stabilisation scenarios are typically \r implemented by assuming a carbon price rising at a particular rate \r per year, though that rate varies across model, scenario, and time \r period. Standard scenarios assume a  global single carbon price to \r minimise policy costs. Cost-minimising pathways can be reconciled \r with equity considerations through posterior international transfers. \r Many scenarios extrapolate current policies and include non-market, \r regulatory instruments such as technology mandates."


id: 1df5b5afc1c0faaafacd4c5618895026
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 2462
content:
"The type of policy instrument assumed to drive the decarbonisation \r process also plays a vital role for determining feasibility. The majority \r of scenarios exploring climate stabilisation pathways in the past have \r focused on uniform carbon pricing as the most efficient instrument \r to regulate emissions. However, carbon taxation raises political \r challenges (Beiser-McGrath and Bernauer 2019) (Chapters  13 and \r 14). Carbon pricing will transfer economic surplus from consumers \r and producers to the government. Losses for producers will be highly \r concentrated in those industries possessing fixed or durable assets \r with 'high asset specificity' (Murphy 2002; Dolphin et al. 2020). These \r sectors have opposed climate jurisdictions (Jenkins 2014). Citizens \r are sensitive to rising energy prices, though revenue recycling can \r be used to increase support (Carattini et al. 2019). A recent model \r comparison project confirms findings from the extant literature: \r [...]"


id: e4e55759f6d4be87951000b1f3ab25eb
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 37556
content:
"[...] using revenues to reduce pre-existing capital or, to a lesser extent, \r labour taxes, reduces policy costs and eases distributional concerns \r (Barron et al. 2018; Mcfarland et al. 2018)."


id: 46ed22f815791d9163d57870bc995d08
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 9681
content:
"The models assessed in this chapter differ in their sectoral coverage \r and the level of complexity in each sector. Models tend to have more \r detail in their representation of energy supply and transportation, \r than they do for industry (Section 3.4 and Annex III.I). Some models \r include detailed land-use models, while others exclude land models \r entirely and use supply curves to represent bioenergy potential \r (Bauer et al. 2018a). IAMs do not include all mitigation options \r available in the literature (Rogelj et al. 2018b; Smith et al. 2019). \r For example, most IAM pathways exclude many granular demand\u0002side mitigation options and land-based mitigation options found in \r more detailed sectoral models; additionally, only a  few pathways \r include CDR options beyond afforestation/reforestation and BECCS. \r Section 3.4 and Chapter 12 include some results and comparisons \r to non-IAM models (e.g.,  bottom-up studies and detailed sectoral \r [...]"


id: 9f7426bb9e22e4b2b0c40f0d16431162
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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content:
"[...] models). These sectoral studies often include a  more complete set \r of mitigation options but exclude feedbacks and linkages across \r sectors which may alter the mitigation potential of a given sector. \r There is an increasing focus in IAM studies on SDGs (Section 3.7), \r with some studies reporting the implications of mitigation pathways \r on SDGs (e.g.,  Bennich et al. 2020) and others using achieving \r SDGs as a constraint on the scenario itself (van Vuuren et al. 2015; \r Soergel et al. 2021a). However, IAMs are still limited in the SDGs they \r represent, often focusing on energy, water, air pollution and land. \r On the economic side, the majority of the models report information \r on marginal costs (i.e.,  carbon price). Only a  subset provides full \r economic implications measured by either economic activity or \r welfare. Also often missing, is detail about economic inequality \r within countries or large aggregate regions."


id: 4b52daee88bb95c2bd3a1ee032039029
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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content:
"Yes. Achieving net zero CO2 emissions and sustaining them into the future is sufficient to stabilise the CO2-induced warming signal \r which scales with the cumulative net amount of CO2 emissions. At the same time, the warming signal of non-CO2 GHGs can be \r stabilised or reduced by declining emissions that lead to stable or slightly declining concentrations in the atmosphere. For short-lived \r GHGs with atmospheric lifetimes of less than 20 years, this is achieved when residual emissions are reduced to levels that are lower \r than the natural removal of these gases in the atmosphere. Taken together, mitigation pathways that bring CO2 emissions to net \r zero and sustain it, while strongly reducing non-CO2 GHGs to levels that stabilise or decline their aggregate warming contribution, \r will stabilise warming without using net negative CO2 emissions and with positive overall GHG emissions when aggregated using \r [...]"


id: bd3cf601753cc9080581418914a49f3d
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
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content:
"[...] GWP-100. A considerable fraction of pathways that limit warming to 1.5degC (>50%) with no or limited overshoot and limit warming \r to 2degC (>67%), respectively, do not or only marginally (<10 GtCO2 cumulative until 2100) deploy net negative CO2 emissions (26% \r and 46%, respectively) and do not reach net zero GHG emissions by the end of the century (48% and 70%, respectively). This is no \r longer the case in pathways that return warming to 1.5degC (>50%) after a high overshoot (typically >0.1degC). All of these pathways \r deploy net negative emissions on the order of 360 (60-680) GtCO2 (median and 5-95th percentile) and 87% achieve net negative \r GHGs emissions in AR6 GWP-100 before the end of the century. Hence, global net negative CO2 emissions, and net zero or net \r negative GHG emissions, are only needed to decline, not to stabilise global warming. The deployment of carbon dioxide removal \r [...]"


id: 8773a132daedfe04e55e6fc71e529e1b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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content:
"[...] (CDR) is distinct from the deployment of net negative CO2 emissions, because it is also used to neutralise residual CO2 emissions to \r achieve and sustain net zero CO2 emissions. CDR deployment can be considerable in pathways without net negative emissions and \r all pathways limiting warming to 1.5degC use it to some extent."


id: a1dfcc905559eee716f6395ca84eeead
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 25706
content:
"Not all regions and sectors must reach net zero CO2 or GHG emissions individually to achieve global net zero CO2 or GHG emissions, \r respectively; instead, positive emissions in one sector or region can be compensated by net negative emissions from another sector \r or region. The time each sector or region reaches net zero CO2 or GHG emissions depends on the mitigation options available, the \r cost of those options, and the policies implemented (including any consideration of equity or fairness). Most modelled pathways \r that likely limit warming to 2degC (>67%) above pre-industrial levels and below use land-based CO2 removal such as afforestation/\r reforestation and BECCS to achieve net zero CO2 and net zero GHG emissions even while some CO2 and non-CO2 emissions continue \r to occur. Pathways with more demand-side interventions that limit the amount of energy we use, or where the diet that we consume \r [...]"


id: c41567af165ee472f998a001603f861c
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 31783
content:
"[...] is changed, can achieve net zero CO2, or net zero GHG emissions with less carbon dioxide removal (CDR). All available studies \r require at least some kind of carbon dioxide removal to reach net zero; that is, there are no studies where absolute zero GHG or \r even CO2 emissions are reached by deep emissions reductions alone."


id: d27893d7008247afe72f54e70282d6b
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 34384
content:
"IAMs are used to develop a wide range of scenarios describing future trajectories for greenhouse gas emissions based on a wide set \r of assumptions regarding socio-economic development, technological changes, political development and climate policy. Typically, \r the IAM-based scenarios can be divided into (i) reference scenarios (describing possible trajectories in the absence of new stringent \r climate policies) and (ii) mitigation scenarios (describing the impact of various climate policy assumptions). Reference scenarios \r typically result in high emissions and, subsequently, high levels of climate change (in the order of 2.5degC-4degC during the 21st century). \r The purpose of such reference scenarios is to explore the consequences of climate change and act as a reference for mitigation \r scenarios. The possible emission levels for reference scenarios diverge from stabilising and even slowly declining emissions (e.g., for \r [...]"


id: 9f1c6f368462bd3d2f78887dea5d7ed7
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 25214
content:
"[...] current policy scenarios or SSP1) to very high emission levels (e.g., SSP5 and RCP8.5). The latter leads to nearly 5degC of warming \r by the end of the century for medium climate sensitivity. Hausfather and Peters (2020) pointed out that since 2011, the rapid \r development of renewable energy technologies and emerging climate policy have made it considerably less likely that emissions \r could end up as high as RCP8.5. This means that reaching emissions levels as high as RCP8.5 has become less likely. Still, high \r emissions cannot be ruled out for many reasons, including political factors and, for instance, higher than anticipated population \r and economic growth. Climate projections of RCP8.5 can also result from strong feedbacks of climate change on (natural) emission \r sources and high climate sensitivity (AR6 WGI Chapter 7). Therefore, their median climate impacts might also materialise while \r [...]"


id: be24b44896a7511531741dbbb345a3c2
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 30721
content:
"[...] following a lower emission path (e.g., Hausfather and Betts 2020). All in all, this means that high-end scenarios have become \r considerably less likely since AR5 but cannot be ruled out. High-end scenarios (like RCP8.5) can be very useful to explore high-end \r risks of climate change but are not typical 'business-as-usual' projections and should therefore not be presented as such."


id: e86df770a813a0359cc0af11983d982d
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 38230
content:
"Given the gaps, there is a  need to explore accelerated \r mitigation (relative to NDCs and current policies). There is \r increasing understanding of the technical content of accelerated \r mitigation pathways, differentiated by national circumstances, with \r considerable though uneven literature at country-level (medium \r evidence, high agreement). Transformative technological and \r institutional changes for the near term include demand reductions \r through efficiency and reduced activity, rapid decarbonisation of the \r electricity sector and low-carbon electrification of buildings, industry \r and transport (robust evidence, medium agreement). A  focus on \r energy use and supply is essential, but not sufficient on its own - \r the land sector and food systems deserve attention. The literature \r does not adequately include demand-side options and systems \r analysis, and captures the impact from non-CO2 GHGs with medium \r [...]"


id: c19868487186473372b0f007b1be1c39
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 31362
content:
"[...] confidence. Countries and regions will have different starting points \r for transition pathways. Some factors include climate conditions \r resulting in different heating and cooling needs, endowments with \r different energy resources, patterns of spatial development, and \r political and economic conditions. {4.2.5}"


id: 3f175efaf83cc1a9ccef0e48ed39e223
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 8289
content:
"An emissions gap persists, exacerbated by an implementation \r gap, despite mitigation efforts including those in near-universal \r nationally determined contributions (NDCs). The 'emissions gap' \r is understood as the difference between the emissions with NDCs in \r 2030, and mitigation pathways consistent with the temperature goals. \r In general, the term 'implementation gap' refers to the difference \r between goals on paper and how they are achieved in practice. In \r this report, the term refers to the gap between mitigation pledges \r contained in national determined contributions, and the expected \r outcome of existing policies. There is considerable literature on \r country-level mitigation pathways, including but not limited to NDCs. \r Country distribution of this literature is very unequal (robust evidence,\r high agreement). Current policies lead to median global greenhouse \r gas (GHG) emissions of 57 GtCO2-eq with a full range of 52-60 by \r [...]"


id: df14c4968509888fb95d92d9ead2c3e3
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 36500
content:
"[...] 2030. NDCs with unconditional and conditional elements1\r  lead to \r 53 (50-57) and 50 (47-55) GtCO2-eq, respectively (medium evidence,\r medium agreement) (Table 4.3). This leaves estimated emissions gaps \r in 2030 between projected outcomes of unconditional elements of \r NDCs and emissions in scenarios that limit warming to 1.5degC (>50%) \r with no or limited overshoot of 19-26 GtCO2-eq, and 10-16 GtCO2-eq \r for scenarios that limit warming to 2degC (>67%) with immediate action. \r When conditional elements of NDCs are included, these gaps narrow \r to 16-23 GtCO2-eq and 6-14 GtCO2-eq, respectively. {Cross-Chapter \r Box 4, Figure 1}"


id: 6115215ddc9ab1d5e06aa1285575e2d7
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 14371
content:
"Accelerated mitigation alone may run into obstacles. If such \r obstacles are rooted in underlying structural features of society, then \r transforming such structures helps remove obstacles, which amounts \r to shifting development pathways. Various actors have developed an \r increasing number of mitigation strategies up to 2050 (mid-term). \r A growing number of such strategies aim at net zero GHG or CO2\r emissions, but it is not yet possible to draw global implications due \r to the limited size of sample (medium evidence, low agreement). \r Non-state actors are also engaging in a  wide range of mitigation \r initiatives. When adding up emission reduction potentials, sub\u0002national and non-state international cooperative initiatives could \r reduce up to about 20 GtCO2-eq in 2030 (limited evidence, medium \r agreement). Yet perceived or real conflicts between mitigation and \r other Sustainable Development Goals (SDGs) can impede such \r [...]"


id: 32986e95b65c0a61644d015205b00f9c
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 6162
content:
"[...] action. If undertaken without precaution, accelerated mitigation is \r found to have significant implications for development objectives and \r macroeconomic costs at country level. For example, most country\u0002level mitigation modelling studies in which GDP is an endogenous \r variable report negative impacts of mitigation on GDP in 2030 and \r 2050, relative to the reference. In all reviewed studies, however, \r GDP continues to grow even with mitigation (robust evidence, high \r agreement). The literature finds that employment effect of mitigation \r policies tends to be limited on aggregate, but can be significant \r at sectoral level (limited evidence, medium agreement). Detailed \r design of mitigation policies is critical for distributional impacts and \r avoiding lock-in (robust evidence, high agreement), though further \r research is needed in that direction. {4.2.3, 4.2.4, 4.2.6}"


id: a1ee5204f1346241086525dfb3d7c3c2
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 25722
content:
"Studies evaluating up to 105 updated NDCs submitted by \r October 2021 indicate that emissions in conditional NDCs \r have been reduced by 4.5 (2.7-6.3) GtCO2-eq, but only closes \r the emission gaps by about one-third to 2degC and about 20% \r to 1.5degC compared to the original NDCs submitted in 2015/16 \r (medium evidence, medium agreement). The magnitude of these \r emission gaps calls into question whether current development \r pathways and efforts to accelerate mitigation are adequate to achieve \r the Paris mitigation objectives. In addition, an implementation gap \r exists between the projected emissions of 'current policies' and \r the projected emissions resulting from the implementation of the \r unconditional and conditional elements of NDCs, and is estimated to \r be around and 7 GtCO2-eq in 2030, respectively (medium evidence,\r medium agreement), with many countries requiring additional \r policies and associated climate action to meet their autonomously \r [...]"


id: 4eefedff4006e87d5ede98b761d320ae
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 11171
content:
"[...] determined mitigation targets as specified under the first NDCs \r (limited evidence). There is, furthermore, a  potential difference \r between mitigation targets set in NDCs ex ante and what is achieved \r ex post. A  limited number of studies assess the implementation \r gaps of conditional NDCs in terms of finance, technology and "


id: d571f24694d04ffe24fb1f4f17488662
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 34868
content:
"Shifting development pathways towards sustainability \r offers ways to (i) broaden the range of levers and enablers \r that a  society can use to provide enabling conditions and \r accelerate mitigation; and (ii) increase the chances of \r advancing at the same time towards mitigation and towards \r other development goals. The way countries develop determines \r their capacity to accelerate mitigation and achieve other sustainable \r development objectives simultaneously (medium-robust evidence,\r medium agreement). Yet meeting ambitious mitigation and \r development goals cannot be achieved through incremental change, \r hence the focus on shifting development pathways (robust evidence,\r medium agreement). Though development pathways result from the \r actions of a wide range of actors, it is possible to shift development \r pathways through policies and enhancing enabling conditions (limited \r evidence, medium agreement). For example, policies such as those \r [...]"


id: 54ea3933b533b8f35d49c38f1c4a1fde
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 12211
content:
"[...] listed in Table 4.12 are typically associated with broader objectives \r than greenhouse gas mitigation. They are generally conceived and \r implemented in the pursuit of overall societal development objectives, \r such as job creation, macroeconomic stability, economic growth, and \r public health and welfare. In some countries, such policies are framed \r as part of a just transition. However, they can have major influence \r on mitigative capacity, and hence can be seen as tools to broaden \r mitigation options, as illustrated by the Illustrative Mitigation \r Pathway 'Shifting Pathways' (medium evidence, medium agreement). \r There are practical options to shift development pathways in ways \r that advance mitigation and other sustainable development \r objectives, supporting political feasibility, increase resources to \r meet multiple goals, and reduce emissions (limited evidence, high \r agreement). Concrete examples assessed in this chapter include high \r [...]"


id: 8f224374e641e10969408247c5b382fa
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 22382
content:
"[...] employment and low emissions structural change, fiscal reforms for \r mitigation and social contract, combining housing policies to deliver \r both housing and transport mitigation, and change economic, social \r and spatial patterns of development of the agriculture sector provide \r the basis for sustained reductions in emissions from deforestation. \r These examples differ by context. Examples in other chapters include \r transformations in energy, urban, building, industrial, transport, and \r land-based systems, changes in behaviour and social practices, as well \r as transformational changes across whole economies and societies. \r Coordinated policy mixes would need to coordinate multiple actors - \r individuals, groups and collectives, corporate actors, institutions and \r infrastructure actors - to deepen decarbonisation and shift pathways \r towards sustainability. Shifts in one country may spill over to other \r countries. Shifting development pathways can jointly support \r [...]"


id: 9dcc9585d7d969d250dc9a31cf3682f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
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index: climate_gpt_v2
vector_id: 24998
content:
"[...] mitigation and adaptation. Some studies explore the risks of high \r complexity and potential delay attached to shifting development \r pathways. {4.3, 4.3.1, 4.3.2, 4.4.2, 4.4.3, 4.4.1.7-4.4.1.10, Figure 4.7, \r Cross-Chapter Box 5, 5.8, Box 6.2, 8.2, 8.3.1, 8.4, 9.8.1, 9.8.2, 10.4.1, \r Cross-Chapter Box 5, Cross-Chapter Box 7, Cross-Chapter Box 12}\r The literature identifies a broad set of enabling conditions that \r can both foster shifting development pathways and accelerated \r mitigation, along five categories (medium evidence, high \r agreement). Policy integration is a necessary component of shifting \r development pathways, addressing multiple objectives. To this aim, \r mobilising a range of policies is preferable to single policy instruments \r (robust evidence, high agreement). Governance for climate mitigation \r and shifting development pathways is enhanced when tailored to "


id: 6f455e5476e418f3ce4e63b0d03c8b00
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 16838
content:
"national and local contexts. Improved institutions and governance \r enable ambitious climate action and help bridge implementation \r gaps (medium evidence, high agreement). Given that strengthening \r institutions may be a  long term endeavour, it needs attention in \r the near ter  m. Accelerated mitigation and shifting development \r pathways necessitates both redirecting existing financial flows from \r high- to low-emissions technologies and systems and to provide \r additional resources to overcome current financial barriers (robust \r evidence, high agreement). Opportunities exist in the near term to \r close the finance gap. At the national level, public finance for actions \r promoting the SDG agenda helps broaden the scope of mitigation \r (medium evidence, medium agreement). Changes in behaviour and \r lifestyles are important to move beyond mitigation as incremental \r change, and when supporting shifts to more sustainable development \r [...]"


id: 305235ab02b915be13492fc2e73e3198
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 5753
content:
"[...] pathways will broadening the scope of mitigation (medium evidence,\r medium agreement). The direction of innovation matters (robust \r evidence, high agreement). The necessary transformational changes \r are likely to be more acceptable if rooted in the development \r aspirations of the economy and society within which they take place. \r {4.4.1, 4.4.1.2, 4.4.1.3, 4.4.1.4, 4.4.1.5, 4.4.1.6, Figure 4.8, 15.2.2}"


id: afc384437703494a35540358a4506812
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 28158
content:
"Equity can be an important enabler of deeper ambition for \r accelerated mitigation, dealing with the distribution of costs and \r benefits and how these are shared as per social contracts, national \r policy and international agreements. Transition pathways have \r distributional consequences such as large changes in employment \r and economic structure (robust evidence, high agreement). In that \r regard, the just transition concept has become an international focal \r point tying together social movements, trade unions, and other key \r stakeholders to ensure equity is better accounted for in low-carbon \r transitions. Effectiveness of cooperative action and the perception of \r fairness of such arrangements are closely related, in that pathways \r that prioritise equity and allow broad stakeholders participation can \r enable broader consensus for the transformational change implied \r by deeper mitigation efforts (robust evidence, medium agreement). \r [...]"


id: 78a69733c2c3c6433ed0b136c3d8f853
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 18421
content:
"How can one shift development pathway and accelerate \r mitigation? The literature does not provide a  complete handbook \r for shifting development pathways and accelerating mitigation. \r The literature does, however, shed light on some of the underlying \r dynamics. Shifting development pathways can be necessitated by the \r existence of pervasive obstacles that prove prohibitive to reaching \r mitigation and other development objectives (Section 4.2.7). Deliberate \r measures taken to facilitate the shifting of development pathways \r and accelerated mitigation involve putting in place key enabling \r conditions that help overcome those obstacles (Figure 4.6) - improving \r governance and institutional capacity, fostering behavioural change \r and technological innovation, designing and implementing adequate \r policy, and finance. Just transitions, while they will differ by context, \r are critical to identifying and avoiding or addressing inequitable \r [...]"


id: 21481b000f207324a11c41d79ededc8f
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 3071
content:
"The chapter builds on past IPCC reports. In AR5, all mitigation \r pathways were assessed in a  single chapter (Clarke et al. 2014), \r which focused mostly on the long term. IPCC Special Report on \r Global Warming of 1.5degC (SR1.5) included a chapter on mitigation \r pathways compatible with the temperature goal in the Paris \r Agreement (Rogelj et al. 2018a), mostly at the global level. It also \r considered strengthening mitigation (de Coninck et al. 2018) in the \r context of poverty, inequality and sustainable development (Roy et al. \r 2018). Development pathways have also been explored, albeit less \r frequently, in past IPCC reports starting with the Special Report on \r Emissions Scenarios (Nakicenovic et al. 2000). Some early framing of \r development pathways was included in the Third Assessment Report \r (Banuri et al. 2001), further developed in the Fourth Assessment \r Report (Sathaye et al. 2007). An extended discussion of climate \r [...]"


id: 2b2f138878f8cec010c97285fda7f674
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 4843
content:
"Prior to COP21, in 2015, most countries submitted their Intended \r Nationally Determined Contributions (INDCs), which included \r mitigation targets for 2025 or 2030. INDCs become first NDCs on \r ratification and/or after national governments' revision, and by \r 11 October 2021, the official NDC registry contained 194 first NDCs \r with 105 new and updated NDCs from 132 Parties to the Paris \r Agreement, covering 53% of the total global emissions in 2019 \r of 52.4  GtCO2-eq without land use, land-use change and forestry \r (LULUCF), and 13 second NDCs. Most of the Parties that submitted \r new or updated NDCs have demonstrated increased ambition in \r addressing climate change. Moreover, though some countries have \r not submitted their updated NDCs yet, they have already announced \r their updated NDC goals somewhere. Countries will take the first \r stock in 2023 based on their progression towards achieving the \r objectives of Paris Agreement (UNFCCC 2015a, 2018a; SB Chairs \r [...]"


id: 37524ae99f8ba5950a3081ea5d0e58ef
created_at: 2023-04-19 13:23:08
updated_at: 2023-04-19 13:23:08
content_type: text
index: climate_gpt_v2
vector_id: 6948
content:
"Near-term mitigation targets submitted as part of NDCs to the \r UNFCCC, as well as currently implemented policies, provide a basis \r for assessing potential emissions levels up to 2030 at the national, \r regional and global level. The following sections present an evaluation \r of the methods used for assessing projected emissions under NDCs \r and current policies (Section  4.2.2.2), and the results of these \r assessments at global, regional and national level assessing a broad \r available literature based on first NDC submissions from 2015/16 \r and pre-COVID economic projections (Section 4.2.2.3). The impacts \r of the COVID-19 pandemic and related government responses on \r emissions projections are then discussed in Section 4.2.2.4 and the \r implications of updated NDCs submitted in 2020/21 on emissions \r follow in Section  4.2.2.5. Section  4.2.2.6 presents an assessment \r of the so-called 'implementation gap' between what currently \r [...]"


id: bdb1c859f8cf73ad97be3b0029cf7c86
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 30635
content:
"[...] implemented policies are expected to deliver and what the ambitions \r laid out under the full implementation of the NDCs are projected to \r achieve. Finally, a comparison of ambitions across different countries \r or regions (Section  4.2.2.7) is presented and the uncertainties of \r projected emissions associated with NDCs and current policies are \r estimated, including a discussion of measures to reduce uncertainties \r in the specification of NDCs (Section 4.2.2.8)."


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"Most first NDCs cover all specific sectors, including LULUCF, and \r communicate specific targets for individual sub-sectors to support \r their overall mitigation targets. Concrete actions and priority areas \r are more detailed in the energy sector, with increased share of \r renewable energies and energy efficiency being highlighted in the \r majority of NDCs. Given the uncertainty behind LULUCF emission \r and removal accounting (Grassi et al. 2017; Jian et al. 2019), several \r countries state that their accounting framework will only be defined \r in later NDCs. The GHG included and the global warming potentials \r (GWPs) used to aggregate emissions also vary across NDCs. Most \r countries only refer to carbon dioxide, methane and nitrous oxide \r emissions aggregated based on IPCC AR2 or AR4 metrics, while few \r NDCs also include fluorinated gases and use IPCC AR5 GWPs. The \r shares of Parties that indicate possible use of at least one type of \r [...]"


id: bdbd0b78fbf17e5728f435ad327508aa
created_at: 2023-04-19 13:23:09
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"[...] voluntary cooperation and set qualitative limits on their use have \r both nearly doubled in new or updated NDCs."


id: c4ad84d2eabc5d1173c792a8bc7d4be0
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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vector_id: 31909
content:
"The number of studies estimating the emissions implications of new \r and updated NDCs and announced mitigation pledges that can be used \r for the quantitative assessment is limited to four (Table 4.3) (Climate \r Action Tracker 2021; den Elzen et al. 2021; Meinshausen et al. 2021; \r JRC 2021). One other study includes a limited number of NDC updates \r (Riahi et al. 2021) and another (UNFCCC 2021) excludes LULUCF \r emissions. They are therefore not directly comparable to the other two. \r In addition, the UNEP Emissions Gap Report 2021 (UNEP 2021) in itself \r is assessment of almost the same studies included here. The evidence \r base for the updated NDC assessment is thus considerably smaller \r compared to that of the assessment of emissions implications of original \r NDCs presented in Section 4.2.2.3. However, it is worthwhile to note \r that the earlier versions of the studies summarised in Table 4.2 and \r Table 4.3 are broadly representative for the emissions range implied by \r [...]"


id: 987e50d63d07558f3a0f35b981a658b
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 24038
content:
"[...] the pre-COVID-19 current policies and original NDCs of the full set of \r studies shown in Table 4.1, therefore building confidence in estimates."


id: 44be8d9c5a4737bb37d7d2149decec48
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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vector_id: 9321
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"Notes: a GHG emissions expressed in CO2-eq emission using AR6 100-year GWPs. GHG emissions from studies that provide aggregate GHG emissions using other GWPs are \r rescaled using 2019 GHG emissions from Chapter 2 (Minx et al. 2021; Crippa et al. 2021). Note that due to slightly different system boundaries across historical emission \r datasets as well as data uncertainties (Chapter 2, SM2.2) relative change compared to historical emissions should be calculated vis-a-vis the historical emissions data used by \r a particular study. b If a range is available from a study, a median is provided in addition to the range. c Announced mitigation pledges on global 2030 emissions of China and \r Japan included. d\r  Announced mitigation pledges of China, Japan, Republic of Korea included. e Announced mitigation pledge of Korea not included. f Announced mitigation \r pledges of China and Republic of Korea not included, emissions from international aviation and shipping not included. g\r [...]"


id: 51a3676d17743a5bafd34400332dbf74
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 11644
content:
"[...]  Ranges across four studies are calculated using the \r median and the full range including the minimum and maximum of studies if available. h\r  UNEP EGR 2021 estimate listed for comparison, but since largely relying on the same \r studies not included in range estimate. i\r  NDCs submitted until 30 July included, announcements not included, excluding LULUCF emissions. j NDC updates of Brazil, EU and \r announcement of China included as a sensitivity analysis compared to original NDCs."


id: f9840a99f35752a2dea68471d8227c05
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 41268
content:
"Comparing the emission levels implied by the new and updated \r NDCs as shown in Table  4.3 with those estimated by the original \r NDCs from the same studies (as included in Table 4.1), a downward \r revision of 3.8 (3.0-5.3) GtCO2-eq of the central unconditional NDC \r estimates and of 4.5 (2.7-6.3) GtCO2-eq of the central conditional \r NDC estimate emerges (medium evidence, medium agreement). The \r emissions gaps between temperature limits and new and updated \r NDCs are assessed in Cross-Chapter Box 4 below. New and updated \r unconditional NDCs reduce the median gap with emissions pathways \r that limit warming to 2degC (>67%) in 2030 by slightly more than 20%, \r from a median gap of 17 GtCO2-eq (9-23) to 13 (10-16). New and \r updated conditional NDCs reduce the median gap with emissions \r pathways that limt warming to 2degC (>67%) in 2030 by about one \r third, from 14  GtCO2-eq (10-20) to 9  (6-14). New and updated \r unconditional NDCs reduce the median gap with emissions pathways \r [...]"


id: 87ac19ab999634b018a0ec477ccb192a
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 21028
content:
"[...] that limit warming to 1.5degC (>50%) with no or limited overshoot in \r 2030 by about 15%, from a median gap of 27 GtCO2-eq (19-32) to "


id: d35ee0df7443f21cd5709111b59d77fd
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 34530
content:
"has assessed equity, analysing how fairness is expressed in NDCs \r in a  bottom-up manner (Mbeva and Pauw 2016; Cunliffe et al. \r 2019; Winkler et al. 2018). Some studies compare NDC ambition \r level with different effort sharing regimes and which principles are \r applied to various countries and regions (Peters et al. 2015; Pan \r et al. 2017; Robiou Du Pont et al. 2017; Holz et al. 2018; Robiou \r du Pont and Meinshausen 2018; van den Berg et al. 2019). Others \r propose multi-dimensional evaluation schemes for NDCs that \r combine a  range of indicators, including the NDC targets, cost\u0002effectiveness compared to global models, recent trends and policy \r implementation into consideration (Aldy et al. 2017; Hohne et al. \r 2018). Yet other literature evaluates NDC ambition against factors \r such as technological progress of energy efficiency and low-carbon \r technologies (Jiang et al. 2017; Kuramochi et al. 2017; Wakiyama \r and Kuramochi 2017), synergies with adaptation plans (Fridahl \r [...]"


id: 1eb8f76a75731491f8f8885d994833d4
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
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content:
"[...] and Johansson 2017), the obligations to deploy carbon dioxide \r removal technologies like bioenergy with carbon capture and \r storage (BECCS) in the future implied by their near-term emission \r reductions where they are not reflected on in the first NDCs (Peters \r and Geden 2017; Fyson et al. 2020; Pozo et al. 2020; Mace et al. \r 2021). Others identify possible risks of unfairness when applying \r GWP* as emissions metric at national scale (Rogelj and Schleussner \r 2019). A recent study on national fair shares draws on principles of \r international environmental law, excludes approaches based on cost \r and grandfathering, thus narrowing the range of national fair shares \r previously assessed, and apply this to the quantification of national \r fair share emissions targets (Rajamani et al. 2021)."


id: ca60335eb21fa5d2a5321a4dbb73c188
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 32946
content:
"towards implementing their NDCs and to which degree the NDCs \r collectively are sufficient to reach the temperature targets of the \r Paris agreement (Rogelj et al. 2016; Quere et al. 2018; Hohne et al. \r 2018; Roelfsema et al. 2020; den Elzen et al. 2019; Hohne et al. 2020). \r Most of these studies focus on major emitters such as G20 countries \r and with the aim to inform countries to strengthen their ambition \r regularly, for example, through progress of NDCs and as part of the \r global stocktake (Hohne et al. 2018; Peters et al. 2017). However, \r a  limited number of studies assess the implementation gaps of \r conditional NDCs in terms of finance, technology and capacity \r building support. Some authors conclude that finance needed to \r fulfil conditional NDCs exceeds available resources or the current \r long-term goal for finance (USD100 billion yr-1) (Pauw et al. 2019); \r others assess financial resources needed for forest-related activities \r [...]"


id: eb8982d6adaf9751bf0d49d5e32ad4f2
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 38802
content:
"[...] (Kissinger et al. 2019) (Section 15.4.2). The literature suggests that \r consistent and harmonised approach to track progress of countries \r towards their NDCs would be helpful (Peters et al. 2017; Hohne et al. \r 2018; den Elzen et al. 2019), and negotiations on a common tabular \r format are expected to conclude during COP26 in November 2021."


id: 4338ea7131843f5db9ab3d8874efdd37
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 9036
content:
"A comparison between the projected emission outcomes of current policies, the NDCs (which include unconditional and conditional \r elements, Section 4.2.1) and mitigation pathways acting immediately, i.e. from 2020 onwards, on reaching different temperature \r goals in the long-term (Section  3.3.3) allows identifying different 'emission gaps' in 2030 (Cross-Chapter Box  4, Figure  1). First, \r the  implementation gap between 'current policies' and unconditional and conditional NDCs is estimated to be around 4  and \r 7  GtCO2-eq in 2030, respectively (Section  4.2.2 and Tables  4.2 and  4.3). Second, the comparison of unconditional (conditional) \r NDCs and long-term mitigation pathways that limit warming to 2degC (>67%) or lower gives rise to a 2030 median emissions gap \r of 19-26  GtCO2-eq (16-23  GtCO2-eq) for limiting end-of-century warming to  1.5degC (>50%) with no or limited overshoot and \r 10-16 GtCO2-eq (6-14 GtCO2-eq) for limiting warming to 2degC (>67%).5\r [...]"


id: afda34ee172c6fd2529ee4ed7e08ba29
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 28176
content:
"[...]  GHG emissions of NDCs are broadly consistent with 2030 \r emission levels of cost-effective long-term pathways staying below 2.5degC (scenarios category C5, Table 3.2, Chapter 3)."


id: 4bba1df02c5697ec10b00f64aafb1a79
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 10577
content:
"Working Group II contribution to this Assessment finds that the overall extent of adaptation-related responses in human systems is \r low (high confidence) and that there is limited evidence on the extent to which adaptation-related responses in human systems are \r reducing climate risk (O'Neill et al. 2020). Thus there is an adaptation gap (UNEP 2018a), and bridging that gap requires enablers \r including institutional capacity, planning and investment (UNEP 2016). Estimates of adaptation costs vary greatly across studies. Recent \r studies based on climate change under RCP8.5 report adaptation costs for developing countries of up to 400 billion (300 billion in \r RCP2.6) USD2005 in 2030 (New et al. 2020). Of the NDCs submitted in 2015, 50 countries estimated adaptation costs of USD39 billion \r annually. Both public and private finance for adaptation is increasing, but remains insufficient and constitutes a small fraction (4-8%) \r [...]"


id: 534ef5cb97621b5bf14ede4983f41558
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
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content:
"[...] of total climate finance which is mostly aimed at mitigation. The pledge of developed countries of mobilising finance for developing \r countries to address adaptation needs globally as part of the Paris Agreement are insufficient. By 2030 the adaptation needs are \r expected to be three to six times larger than what is pledged, further increasing towards 2050 (UNEP 2016; New et al. 2020)."


id: 9a52772a2a49bed6b56db533a0b8a5f7
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
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content:
"The decision adopting the Paris Agreement stresses the importance \r of 'stronger and more ambitious climate action' by non-government \r and sub-national stakeholders, 'including civil society, the private \r sector, financial institutions, cities and other sub-national authorities, \r local communities and indigenous peoples' (UNFCCC 2015a). The \r Marrakech Partnership for Global Action, launched in the 2016 \r UNFCCC Conference of Parties by two 'high-level champions,' further \r formalised the contributions of non-government and sub-national \r actors taking action through seven thematic areas (e.g.,  energy, \r human settlements, industry, land-use, etc.) and one cross-cutting \r area (resilience). Since then, non-state actors, for example, companies \r and civil society, and sub-national actors, such as cities and regions, \r have emerged to undertake a  range of largely voluntary carbon \r mitigation actions (Hsu et al. 2018, 2019) both as individual non-state \r [...]"


id: 837f2a85cf77817ccd72fabaee20c031
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 20274
content:
"[...] actors (NSAs in the following) and through national and international \r cooperative initiatives, or ICIs (Hsu et al. 2018). ICIs take a variety of \r forms, ranging from those that focus solely on non-state actors to \r those that engage national and even local governments. They can \r also range in commitment level, from primarily membership-based \r initiatives that do not require specific actions to those that require "


id: ab3506a4f9d9bfe4e7d912d18db47283
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 27349
content:
"initiatives reporting high potential. In Table 4.4 and Figure 4.1, we \r report estimates of the emissions reductions from 19 distinct sub\u0002national and non-state initiatives to mitigate climate change. The \r table shows wide ranges of potential mitigation based on current, \r target or potential membership, as well as a  wide diversity of \r actors and membership assumptions. Current membership reflects \r the number of non-state or sub-national actors that are presently \r committed to a  particular initiative; while targeted or potential \r membership represents a  membership goal (e.g.,  increasing from \r 100 to 200 members) that an initiative may seek to achieve (Kuramochi \r et al. 2020). When adding up emission reduction potentials, sub\u0002national and non-state international cooperative initiatives could \r reduce up to about 20 Gt of CO2-eq in 2030 (limited evidence, medium \r agreement). Chapter 8 also presents data on the savings potential of \r [...]"


id: de67000cf70fe94d45ee120d23ed35d5
created_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 36395
content:
"[...] cities and it suggests that these could reach 2.3 GtCO2-eq annually \r by 2030 and 4.2 GtCO2-eq annually for 2050."


id: 4bec6e05ec44ffe82ccd69723bea5b6
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 10619
content:
"Equally important to note here is that none of the studies reviewed \r in Figure  4.1 quantified the potential impact of financial sector \r actions, for example, divestment from emission intensive activities \r (Section 15.3 has a more detailed discussion of how financial actors \r and instruments are addressing climate change). Moreover, only \r a limited number of studies on the impact of actions by diverse actors \r go beyond 2050 (Table 4.4), which may reflect analysts' recognition \r of the increasing uncertainties of longer time horizons. Accurate \r accounting methods can help to avoiding counting finance multiple \r times, and methods across mitigation and finance would consider \r counting carbon market flows and the tons reduced. As Table  4.4 \r and Figure  4.1 indicate, activities by businesses have potential to \r significantly contribute to global mitigation efforts. For example, \r the SBTi (Science Based Targets initiative) encourages companies to \r [...]"


id: 80822630ddde60d4cfb0f97c79378505
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
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content:
"[...] pledge to reduce their emissions at rates which according to SBTi \r would be compatible with global pathways to well below 2degC or 1.5degC, \r with various methodologies being proposed (Andersen et al. 2021; \r Faria and Labutong 2019). Readers may note, however, that the link \r between emissions by individual actors and long-term temperature \r goals cannot be inferred without additional assumptions (Box 4.2). In \r the energy sector, some voluntary initiatives are also emerging to stop \r methane emissions associated with oil and gas supply chains. The Oil \r and Gas Methane Partnership (OGMP) is a voluntary initiative lead \r by the Climate and Clean Air Coalition, which has recently published \r a  comprehensive framework for methane detection, measurement \r and reporting (UNEP 2020b)."


id: be84e65bf78fef566c822125e20c6ba6
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 30781
content:
"Initiatives made up of cities and sub-national regions have an \r especially large potential to reduce emissions, due to their inclusion \r of many actors, across a range of different geographic regions, with \r ambitious emissions reduction targets, and these actors' coverage of \r a large share of emissions (Kuramochi et al. 2020). Hsu et al. (2019) \r find largest potential in that area. Several sub-national regions like \r California and Scotland have set zero emission targets (Hohne et al. \r 2019), supported by short- and medium-term interim goals (Scottish \r Government 2020b; State of California 2018). Sharing of effort across \r global and sub-global scales has not been quantified, though one \r study suggests that non-state actors have increasingly adopted \r more diverse framings, including vulnerability, human rights and \r transformational framings of justice (Shawoo and McDermott 2020). \r Initiatives focused on forestry have high emissions reduction potential \r [...]"


id: 5dfa79f574b048047e0852e04808322
created_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 13833
content:
"[...] due to the current high deforestation rates, and due to the ambitious \r targets of many of these forestry initiatives, such as the New York \r Declaration on Forests' goal to end deforestation by 2030 (Hohne \r et al. 2019; Lui et al. 2021), although the Initiative acknowledges "


id: f725b7cf3e069f03739ddeaed5db6ec5
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 40854
content:
"The literature frequently refers to national mitigation pathways up to 2030 or 2050 using long-term temperature limits in the Paris \r Agreement (i.e., '2degC' or '1.5degC scenario'). Without additional information, such denomination is incorrect. Working Group I reaffirmed \r 'with high confidence the AR5 finding that there is a near-linear relationship between cumulative anthropogenic CO2 emissions and \r the global warming they cause' (WGI SPM AR6). It is not the function of any single country's mitigation efforts, nor any individual \r actor's. Emission pathways of individual countries or sectors in the near to mid-term can only be linked to a long-term temperature \r with additional assumptions specifying (i) the GHG emissions and removals of other countries up the mid-term; and (ii) the GHG \r emissions and removals of all countries beyond the near and mid-term. For example, a national mitigation pathway can be labelled \r [...]"


id: d26a9accf4b8511553f2e45e5efeef89
created_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 34377
content:
"[...] '2degC compatible' if it derives from a global mitigation pathway consistent with 2degC via an explicit effort sharing scheme across \r countries (Sections 4.2.2.6 and 4.5)."


id: b943a9b61468c04fd165af42a2ff4379
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 29803
content:
"At the 2019 Climate Action Summit, 77 countries indicated their \r aim to reach net zero CO2 emissions by 2050, more the number \r of countries having submitted LEDS to the UNFCCC. Table 4.6 lists \r the countries that have a national net zero by 2050 target in laws, \r strategies or other documents (The Energy and Climate Intelligence \r Unit 2019). Bhutan and Suriname already have achieved net negative \r emissions. France second 'low-carbon national strategy' adopted in \r 2020 has an objective of GHG neutrality by 2050. Net zero is also the \r basis of the recent revision of the official notional price of carbon for \r public investment in France (Quinet et al. 2019). The Committee on \r Climate Change of the UK analyses sectoral options and concludes \r that delivering net zero GHG by 2050 is technically feasible but \r highly challenging (Committee on Climate Change 2019). For \r Germany, three steps to climate neutrality by 2050 are introduced: \r [...]"


id: a8e18c016f8d1c83533cccb9a498858d
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 26922
content:
"[...] first, a  65% reduction of emissions by 2030; second, a  complete \r switch to climate-neutral technologies, leading to a  95% cut in \r emissions, all relative to 1990 levels by 2050; and third balancing \r of residual emissions through carbon capture and storage (Prognos \r et al. 2020). In addition to the countries in Table 4.6, EU reported \r the net zero GHG emission pathways by 2050 under Green Deal \r (European Commission 2019). China and South Korea, have made \r announcements of carbon neutrality before 2060 and net zero GHG \r emission by 2050, respectively (UN 2020a,b). In the case of Japan, \r the new target to net zero GHG emission by 2050 was announced \r in 2020 (UN 2020c). As of August 25, 2021, a total 121 countries \r participate in the 'Climate Ambition Alliance: Net Zero 2050', \r together with businesses, cities and regions."


id: 7753f16840163f8418d3425e8b53b99b
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 18201
content:
"Figure 4.2 provides a snapshot of this literature. For a selected set of \r countries, it shows the mid-century emission pathways at national \r scale that have been registered in the International Institute for \r Applied Systems Analysis (IIASA) national mitigation scenario \r database built for the purpose of this Report (Annex III.3.3). Overall, \r the database contains scenarios for 50 countries. Total GHG emission \r are the most comprehensive information to assess the pathways on \r climate mitigation actions, but energy-related CO2 emissions are the \r most widely populated data in the scenarios. As a result, Figure 4.2 \r shows energy-related CO2 emission trajectories. Scenarios for EU \r countries show reduction trends even in the reference scenario, \r whereas developing countries and non-European developed \r countries such as Japan and USA show emissions increase in the \r reference. In most countries plotted on Figure  4.2, studies have \r [...]"


id: c6c359fc54a94ab13941a99399bd17ba
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updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 32276
content:
"[...] found that reaching net zero energy related CO2 emissions by 2050 is \r feasible, although the number of such pathways is limited."


id: 2a11d6c660737679efd764b3323b351f
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 4614
content:
"Accelerated mitigation pathways differ by countries, depending inter \r alia on sources of emissions, mitigation opportunities and economic \r context. In China, India, Japan and other Southeast Asian countries, \r more aggressive action related to climate change is also motivated \r by regional concerns over health and air quality related to air \r pollutants and SLCFs (Ashina et al. 2012; Aggarwal 2017; Kuramochi \r et al. 2017; Xunzhang et al. 2017; Dhar et al. 2018; Jiang et al. 2018; \r Oshiro et al. 2018; China National Renewable Energy Centre 2019; \r Energy Transitions Commission and Rocky Mountain Institute 2019; \r Khanna et al. 2019). Studies of accelerated mitigation pathways \r in North America tend to focus on power sector and imported fuel \r decarbonisation in the US , and on electrification and demand-side \r reductions in Canada (Vaillancourt et al. 2017; Hodson et al. 2018; \r Victor et al. 2018; Bahn and Vaillancourt 2020; Hammond et al. 2020; \r [...]"


id: 8f3e38a56322d7285c4b098a2057ec0c
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 22407
content:
"[...] Jayadev et al. 2020). In Latin America, many pathways emphasise \r supply-side mitigation measures, finding that replacing thermal \r power generation and developing bioenergy (where resources are \r available) utilisation offers the greatest mitigation opportunities \r (Herreras Martinez et al. 2015; Nogueira de Oliveira et al. 2016; \r Arango-Aramburo et al. 2019; Delgado et al. 2020; Lap et al. 2020). \r The European Union member states (EU-28) recently announced \r 2050 climate neutrality goal is explored by pathways that emphasise \r complete substitution of fossil fuels with electricity generated by \r low-carbon sources, particularly renewables; demand reductions \r through efficiency and conservation, and novel fuels and end-use \r technologies (Prognos et al. 2020). The limited literature so far on \r Africa's future pathways suggest those could be shaped by increasing \r energy access and mitigating the air pollution and health effects \r [...]"


id: ad1b1f3500df8b258995eb4d2ca650b1
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 27693
content:
"[...] of relying on traditional biomass use, as well as cleaner expansion of \r power supply alongside end-use efficiency improvements (Hamilton \r and Kelly 2017; Oyewo et al. 2019, 2020; Ven et al. 2019; Wright et al. \r 2019; Forouli et al. 2020)."


id: 3ebb24d79a6d06b75de09b4f4d6c8976
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 8225
content:
"Many accelerated mitigation pathways include high shares of renewable energy, with national variations. In Europe, some argue \r that the EU 2050 net zero GHG emissions goal can be met with 100% renewable power generation, including use of renewable \r electricity to produce hydrogen, biofuels (including imports), and synthetic hydrocarbons, but will require significant increases in \r transmission capacity (Duscha et al. 2019; Zappa et al. 2019). Capros et al. (2019) explore a 1.5degC compatible pathway that includes \r 85% renewable generation, with battery, pumped hydro, and chemical storage for variable renewables. High-renewable scenarios \r also exist for individual Member States. In France, for example, Krakowski et al. (2016) propose a 100% renewable power generation \r scenario that relies primarily on wind (62%), solar PV (26%) and oceans (12%). To reach this aim, integration into the European grid is \r [...]"


id: 9ef3633c577f6d7a7cf24bde06db1584
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 25193
content:
"[...] of vital importance (Brown et al. 2018). While debated, incremental costs could be limited regardless of specific assumptions of future \r costs of individual technologies (Shirizadeh et al. 2020). In Germany, similarly, 100% renewable electricity systems are found feasible \r by numerous studies (Oei et al. 2020; Thomas Klaus et al. 2010; Wuppertal-Institut 2021; Hansen et al. 2019)."


id: 7cc49ec4c7c3e6714573d820994258b2
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 19149
content:
"Accelerated mitigation scenarios offer contrasting views on the \r share of nuclear in power generation. In the USA, (Victor et al. 2018) \r build a scenario in which nuclear contributes 23% of CO2 emission \r reductions needed to reduce GHG emissions by 80% from 2005 levels \r by 2050. Deep power sector decarbonisation pathways could require \r a two-folded increase in nuclear capacity according to (Jayadev et al. \r 2020) for the USA, and nearly a ten-fold increase for Canada, but \r may be difficult to implement (Vaillancourt et al. 2017). For China to \r meet a 1.5degC pathway or achieve carbon neutrality by 2050, nuclear \r may represent 14-28% of power generation in 2050 according to \r (Jiang et al. 2018; China National Renewable Energy Centre 2019; \r Energy Transitions Commission and Rocky Mountain Institute 2019). \r For South Korea, Hong et al. (2014) and Hong and Brook (2018) find \r that increasing nuclear power can help complement renewables in \r [...]"


id: 55b8153aeb8c2be81069f78efa1437c
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 12351
content:
"[...] decarbonising the grid. Similarly, India has put in place a three-stage \r nuclear programme which aims to enhance nuclear power capacity \r from the current level of 6  GW to 63 GW by 2032, if fuel supply \r is ensured (GoI 2015). Nuclear energy is also considered necessary \r as part of accelerated mitigation pathways in Brazil, although it is \r not expected to increase significantly by 2050 even under stringent \r low-carbon scenarios (Lucena et al. 2016). France developed its \r nuclear strategy in response to energy security concerns after the \r 1970s oil crisis, but has committed to reducing nuclear's share of \r power generation to 50% by 2035 (Millot et al. 2020). Conversely, \r some analysis find deep mitigation pathways, including net zero GHG \r emissions and 80-90% reduction from 2013 levels, feasible without \r additional nuclear power in EU-28 and Japan respectively, but \r assuming a combination of bio- and novel fuels and CCS or land-use \r [...]"


id: a8faffa72ea75e4aa0d9ec9105bff4a2
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 26936
content:
"One possible synergy between SLCF and climate change mitigation \r is the simultaneous improvement in energy efficiency in refrigeration \r and air-conditioning equipment during the hydrofluorocarbon (HFC) \r phase-down, as recognised in the Kigali Amendment to the Montreal \r Protocol. The Kigali Amendment and related national and regional \r regulations are projected to reduce future radiative forcing from \r HFCs by about half in 2050 compared to a scenario without any HFC \r controls, and to reduce future global average warming in 2100 from \r a baseline of 0.3degC-0.5degC to less than 0.1degC, according to a recent \r scientific assessment of a  wide literature (World Meteorological \r Organization 2018). If ratified by signatories, the rapid phase-down \r of HFCs under the Kigali Amendment is possible because of extensive \r replacement of high-global warming potential (GWP) HFCs with \r commercially available low-GWP alternatives in refrigeration and \r [...]"


id: d2008b2650c050b9db0f760e5e120cc8
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 34298
content:
"[...] air-conditioning equipment. Each country's choices of alternative \r refrigerants will likely be determined by energy efficiency, costs, \r and refrigerant toxicity and flammability. National and regional \r regulations will be needed to drive technological innovation and \r development (Polonara et al. 2017)."


id: dc403ab821ba085c6cfd0179d70662b4
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 36021
content:
"For example, scenarios for Japan project continued electrification of \r residential and commercial buildings to 65% and 79% respectively \r by 2050 to reach 70-90% CO2 reduction from 2013 levels (Kato \r and Kurosawa 2019). Similarly, a  mitigation pathway for China \r compatible with 1.5degC would require 58% to 70% electrification of \r buildings according to (Jiang et al. 2018; China National Renewable \r Energy Centre 2019E; nergy Transitions Commission and Rocky \r Mountain Institute 2019). For the EU-28 to reach net carbon \r neutrality, complete substitution of fossil fuels with electricity (up \r to 65% share), district heating, and direct use of solar and ambient \r heat are projected to be needed for buildings, along with increased \r use of solar thermal and heat pumps for heating (Duscha et al. \r 2019). In the UK and Canada, improved insulation to reduce energy \r demand and efficient building appliances and heating systems are \r [...]"


id: 7ad6ce8aa2eb07ad757e25352ded2387
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 18813
content:
"[...] important building strategies needed to reduce emissions to zero \r by 2050 (Vaillancourt et al. 2017; Chilvers et al. 2017; Roberts \r et al. 2018a). In Ireland, achieving 80-95% emissions reduction \r below 1990 levels by 2050 also requires changes in building energy "


id: a4afff215eb6047366cdaa2f9918688d
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 26190
content:
"In addition, an increasing number of countries have set up net zero \r energy building targets (Table 4.8) (Hohne et al. 2020). Twenty-seven \r countries have developed roadmap documents for NZEBs, mostly \r in developed countries in Europe, North America, and Asia-Pacific, \r focusing on energy efficiency and improved insulation and design, \r renewable and smart technologies (Mata et al. 2020). The EU, Japan \r and the USA (the latter for public buildings only) have set targets \r for shifting new buildings to 100% near-zero energy buildings by \r 2030, with earlier targets for public buildings. Scotland has a similar \r target for 2050 (Hohne et al. 2020). Technologies identified as \r needed for achieving near-zero energy buildings vary by region, but \r include energy-efficient envelope components, natural ventilation, \r passive cooling and heating, high performance building systems, \r air heat recovery, smart and information and communication \r [...]"


id: eab382d954d74b11ada2e2720760bfb1
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 38651
content:
"[...] technologies, and changing future heating and cooling supply fuel \r mixes towards solar, geothermal, and biomass (Mata et al. 2020). \r Sub-national regions in Spain, USA, Germany, and Mexico have set \r local commitments to achieving net zero carbon new buildings by \r 2050, with California having the most ambitious aspirational target \r of zero net energy buildings for all new buildings by 2030 (Hohne \r et al. 2020). The EU is also targeting the retrofitting of 3% of existing \r public buildings to zero-energy, with emphasis on greater thermal \r insulation of building envelopes (Hohne et al. 2020; Mata et al. \r 2020). China's roadmaps have emphasised insulation of building \r envelope, heat recovery systems in combination with renewable \r energy, including solar, shallow geothermal, and air source heat \r pumps (Mata et al. 2020)."


id: 22394f2b0cb67b5db8135056b608e4cd
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 3242
content:
"Beyond technological measures, some densely populated countries \r including Germany, Japan, and India are exploring using information \r technology/internet of things (IOT) to support mode-shifting and \r reduce mobility demand through broader behaviour and lifestyle \r changes (Ashina et al. 2012; Canzler and Wittowsky 2016; Aggarwal \r 2017; Dhar et al. 2018; Vishwanathan et al. 2018b). In Japan, \r accelerated mitigation pathways consider the use of information \r technology and internet of things (IoT) to transform human \r behaviour and transition to a sharing economy (Ashina et al. 2012; \r Oshiro et al. 2017a, 2018). In Germany, one study points to including \r electromobility information and communication technologies in \r the transport sector as key (Canzler and Wittowsky 2016) while \r another emphasise shifting from road to rail transport, and reduced \r distances travelled as other possible transport strategies (Schmid and \r [...]"


id: 24a3aada4536b95434890facb51366de
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 3636
content:
"[...] Knopf 2012). India's transport sector strategies also include use of \r information technology and the internet, a  transition to a  sharing \r economy, and increasing infrastructure investment (Dhar et al. 2018; \r Vishwanathan et al. 2018b). Behaviour and lifestyle change along \r with stakeholder integration in decision-making are considered \r key to implementing new transport policies (Aggarwal 2017; \r Dhar et al. 2018)."


id: c44bf90140afcab6c81bd2cd3a8837ca
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 31824
content:
"In China, for example, non-conventional electrical and renewable \r technologies, including low-grade renewable heat, biomass use for \r high-temperature heat in steel and cement sectors, and additional \r electrification in glass, food and beverage, and paper and pulp \r industries, are part of scenarios that achieve 60% reduction in \r national CO2 emission by 2050 (Khanna et al. 2019; Zhou et al. \r 2019), in addition to increased recycled steel for electric arc furnaces \r and direct electrolysis or hydrogen-based direct reduction of iron \r and CCS utilisation in clinker and steel-making (Jiang et al. 2018; \r China National Renewable Energy Centre 2019). Similarly, in India, \r (Vishwanathan and Garg 2020) point to the need for renewable \r energy and CCS to decarbonise the industrial sector. In EU-28, net \r CO2 neutrality can only be reached with 92% reduction in industrial \r emissions relative to 1990, through electrification, efficiency \r [...]"


id: 67b18b8e0a3b2083f7e704aa69de8703
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 15510
content:
"[...] improvement and new technologies such as hydrogen-based direct \r reduction of steel, low-carbon cement and recycling (Duscha et al. \r 2019). Both China and EU see 50% of industry electrification by 2050 \r as needed to meet 1.5degC and net carbon neutrality pathways (Jiang \r et al. 2018; Capros et al. 2019)."


id: c54418f4d9a048db3a29849258cf76f2
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 32013
content:
"household air pollution and reversing health- and crop-damaging \r tropospheric ozone (Jacobson 2002, 2010). SLCF mitigation measures \r can have regional impacts, including avoiding premature deaths in \r Asia and Africa and warming in central and northern Asia, southern \r Africa, and the Mediterranean (Shindell et al. 2012). Reducing \r outdoor air pollution could avoid 2.4 million premature deaths and \r 52 million tonnes of crop losses for four major staples (Haines et al. \r 2017). Existing research emphasises climate and agriculture benefits \r of methane mitigation measures with relatively small human health \r benefits (Shindell et al. 2012). Research also predicts that black \r carbon mitigation could substantially benefit global climate and \r human health, but there is more uncertainty about these outcomes \r than about some other predictions (Shindell et al. 2012). Other \r benefits to SLCF reduction include reducing warming in the critical \r [...]"


id: 31c1104ffd99cc26280c1bb89bbb9e88
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 5998
content:
"[...] near term, which will slow amplifying feedbacks, reduce the risk \r of non-linear changes, and reduce long-term cumulative climate \r impacts - like sea-level rise - and mitigation costs (Hu et al. 2017; \r UNEP and WMO 2011; Rogelj et al. 2018a; Xu and Ramanathan \r 2017; Shindell et al. 2012)."


id: b1863fe241f73f25873b062b4322629f
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 28456
content:
"Systemic solutions are also not being sufficiently discussed, such \r as low-carbon materials; light-weighting of buildings, transport, \r and industrial equipment; promoting circular economy, recyclability \r and reusability, and addressing the food-energy-water nexus. \r These solutions reduce demand in multiple sectors, improve overall \r supply chain efficiency, and require cross-sector policies. Using \r fewer building materials could reduce the need for cement, steel, \r and other materials and thus the need for production and freight \r transport. Concrete can also be produced from low-carbon cement, \r or designed to absorb CO2 from the atmosphere. Few regions \r have developed comprehensive policies or strategies for a  circular \r economy, with the exception of the EU and China, and policies in \r the EU have only emerged within the last decade. While China's \r circular economy policies emphasises industrial production, water, \r [...]"


id: 4d4e8dc14c6e44b3720adcb6e7334502
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 10883
content:
"[...] pollution and scaling-up in response to rapid economic growth and \r industrialisation, EU's strategy is focused more narrowly on waste \r and resources and overall resource efficiency to increase economic \r competitiveness (McDowall et al. 2017)."


id: 7bc2bd744f3dc356c8ee9d32c0a98b28
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 18983
content:
"A significant part of the literature assesses the impacts of mitigation \r on GDP, consistent with policymakers' interest in this variable. \r It must be noted upfront that computable equilibrium models, on \r which our assessments are mostly based, capture the impact of \r mitigation on GDP and other core economic variables while typically \r overlooking other effects that may matter (like improvements in air \r quality). Second, even though GDP (or better, GDP per capita) is not \r an indicator of welfare (Fleurbaey and Blanchet 2013), changes in \r GDP per capita across countries and over time are highly correlated \r with changes in welfare indicators in the areas of poverty, health, \r and education (Gable et al. 2015). The mechanisms linking mitigation \r to GDP outlined below would remain valid even with alternative \r indicators of well-being (Section  5.2.1). Third, another stream of \r literature criticises the pursuit of economic growth as a goal, instead \r [...]"


id: bf701262fbe7630d1801281a73659b9a
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 30944
content:
"[...] advocating a range of alternatives and suggesting modelling of post\u0002growth approaches to achieve rapid mitigation while improving social \r outcomes (Hickel et al. 2021). In the language of the present chapter, \r these alternatives constitute alternative development pathways."


id: 8df21051ce922a8c7485ade50ca7e6fa
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 22165
content:
"use of a production factor (fossil energy), thus reducing GDP. In the \r simulations, the mechanism at work is that firms and households \r reduce their use of GHG-intensive goods and services in response \r to higher prices due to reduced fossil energy use. Second, additional \r investment required for mitigation partially crowds out productive \r investment elsewhere (Fujimori et al. 2019), except in Keynesian \r models in which increased public investment actually boosts GDP \r (Pollitt et al. 2015; Landa Rivera et al. 2016; Bulavskaya and Reynes \r 2018). Magnitude and duration of GDP loss depend on the stringency \r of the carbon constraint, the degree of substitutability with less-GHG\u0002intensive goods and services, assumptions about costs of low-carbon \r technologies and their evolution over time (e.g., Duan et al. 2018; van \r Meijl et al. 2018; Cui et al. 2019) and decisions by trading partners, \r which influence competitiveness impacts for firms (Alton et al. 2014; \r [...]"


id: 3a58f6d29199ae5b7595a79f531cceaa
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 7470
content:
"Numerous studies have analysed the potential impact of carbon \r pricing on labour markets. Chateau et al. (2018) and OECD (2017a) find \r that the implementation of green policies globally (defined broadly as \r policies that internalise environmental externalities through taxes and \r other tools, shifting profitability from polluting to green sectors) need \r not harm total employment, and that the broad skill composition (low, \r high- and medium-skilled jobs) of emerging and contracting sectors \r is very similar, with the largest shares of job creation and destruction \r at the lowest skill level. To smoothen the labour market transition, \r they conclude that it may be important to reduce labour taxes, to \r compensate vulnerable households, and to provide education and \r training programs, the latter making it easier for labour to move to \r new jobs. Consistent with this, other studies that simulate the impact \r of scenarios with more or less ambitious mitigation policies (including \r [...]"


id: a5904feb71f316c2b7822eb9f1c7f831
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 26367
content:
"[...] 100% reliance on renewable energy by 2050) find relatively small \r (positive or negative) impacts on aggregate global employment that \r are more positive if labour taxes are reduced but encompass substantial \r losses for sectors and regions that today are heavily dependent on \r fossil fuels (Arndt et al. 2013; Huang et al. 2019; Vandyck et al. 2016; \r Jacobson et al. 2019). Among worker categories, low-skilled workers \r tend to suffer wage losses as they are more likely to have to reallocate, \r something that can come at a cost in the form of a wage cut (assuming \r that workers who relocate are initially less productive than those who \r already work in the sector). The results for alternative carbon revenue \r recycling schemes point to trade-offs: a reduction in labour taxes often \r leads to the most positive employment outcomes while lump-sum \r (uniform per-capita) transfers to households irrespective of income \r yield a more egalitarian outcome."


id: c1c4e80b5ae41c43bf96de1a19bc838b
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 31393
content:
"The literature finds that the detailed design of mitigation policies \r is critical for their distributional impacts (robust evidence, high \r agreement). For example, Vogt-Schilb et al. (2019) suggest to turn \r to cash transfer programs, established as some of the most efficient \r tools for poverty reduction in developing countries. In an analysis \r of Latin America and the Caribbean, they find that allocation of \r 30% of carbon revenues would suffice to compensate poor and \r vulnerable households on average, leaving the rest for other uses. \r This policy tool is not only available in countries with relatively high \r per-capita incomes: in Sub-Saharan Africa, where per-capita incomes \r are relatively low, cash transfer programs have been implemented in \r almost all countries (Beegle et al. 2018, p. 57), and are found central \r to the success of energy subsidy reforms (Rentschler and Bazilian \r 2017). In the same vein, Bohringer et al. (2021) finds that recycling \r [...]"


id: c79ea1cffe5efa94fe8ee71fd14ecf88
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 32431
content:
"[...] of revenues from emissions pricing in equal amounts to every \r household appeals as an attractive strategy to mitigate regressive \r effects and thereby make stringent climate policy more acceptable \r on societal fairness grounds. However, distributional gains from such \r recycling may come at the opportunity cost of not reaping efficiency "


id: 8b9555f9bd63a65d7fb120fe0f7f8151
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 21728
content:
"Distributional concerns related to climate mitigation are also prevalent \r in developed countries, as demonstrated, for instance, by France's \r recent yellow-vest movement, which was ignited by an increase \r in carbon taxes. It exemplifies the fact that, when analysing the \r distributional effects of carbon pricing, it is not sufficient to consider \r vertical redistribution (i.e., redistribution between households at \r different incomes levels but also horizontal redistribution (i.e., \r redistribution between households at similar incomes which is due \r to differences in terms of spending shares and elasticities for fuel \r consumption). Compared to vertical redistribution, it is more difficult \r to devise policies that effectively address horizontal redistribution \r (Cronin et al. 2019; Pizer and Sexton 2019; Douenne 2020). However, \r it has been shown ex post that transfer schemes considering income \r levels and location could have protected or even improved the \r [...]"


id: 9297c41d6fee687032bb52a999643180
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 23013
content:
"[...] purchasing power of the bottom half of the population (Bureau et al. \r 2019). Investments in public transportation may reduce  horizontal \r redistribution if it makes it easier for households to reduce fossil \r fuel consumption when prices increase (see Sections  4.4.1.5 \r and 4.4.1.9). Similarly, in relation to energy use in housing, policies \r that encourage investments that raise energy efficiency for low\u0002income households may complement or be an alternative to taxes \r and subsidies as a means of simultaneously mitigating and reducing \r fuel poverty (Charlier et al. 2019). From a  different angle, public \r acceptance of the French increase in the carbon tax could also have \r been enhanced via a public information campaign could have raised \r public acceptance of the carbon tax increase (Douenne and Fabre \r 2020). (See Section 4.4.1.8 for a discussion of this and other factors \r that influence public support for carbon taxation.)"


id: c7f06d212891459836c545af6902fdf2
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 32483
content:
"Obstacles to the implementation of accelerated mitigation pathways \r can be grouped in four main categories (Table  4.10). The first set \r of arguments can be understood through the lens of cost-benefit \r analysis of decision-makers, as they revolve around the following \r question: Are costs too high relative to benefits? More precisely, are \r the opportunity costs - in economics terms, what is being forfeited by \r allocating scarce resources to mitigation - justified by the benefits for \r the decision-maker (whether individual, firm, or nation)? This first set \r of obstacles is particularly relevant because accelerated mitigation \r pathways imply significant effort in the short-run, while benefits in \r terms of limited warming accrue later and almost wholly to other \r actors. However, as discussed in Sections 3.6 and 4.2.6, mitigation \r costs for a  given mitigation target are not carved in stone. They \r strongly depend on numerous factors, including the way mitigation \r [...]"


id: 954b660c286999c44b4eee290c6e34b3
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 23466
content:
"[...] policies have been designed, selected, and implemented, the \r processes through which markets have been shaped by market actors \r and institutions, and nature of socially- and culturally-determined \r influences on consumer preferences. Hence, mitigation choices that \r might be expressed straightforwardly as techno-economic decisions \r are, at a deeper level, strongly conditioned by underlying structures \r of society."


id: b6e46e5e9e93926b222c3bfb441e9e8d
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 29382
content:
"A common thread in the discussion above is that the obstacles to \r accelerated mitigation are to a large degree rooted in the underlying \r structural features of societies. As a  result, transforming those \r underlying structures can help to remove those obstacles, and \r thus facilitate the acceleration of mitigation. This remark is all the \r more important that accelerated mitigation pathways, while very \r different across countries, all share three characteristics: speed of \r implementation, breadth of action across all sectors of the economy, \r and depth of emission reduction achieving more ambitious targets. \r Transforming those underlying structures amounts to shifting \r a  society's development pathway (Figure  4.6). In the following \r Sections  3 and  4, we argue that it is thus necessary to recast \r accelerated mitigation in the broader context of shifting development \r pathways, and that doing so opens up additional opportunities to \r [...]"


id: 3661e7cbd96ca659bd76bbf4745a5e20
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 6802
content:
"[...] (i)  overcome the obstacles outlined above, and also (ii) combine \r climate mitigation with other development objectives."


id: 8b09033d0b6f2091865f289359157bb
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updated_at: 2023-04-19 13:23:09
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"The term development pathway is defined in various ways in the \r literature, and these definitions invariably refer to the evolution \r over time of a society's defining features. A society's development \r pathway can be described, analysed, and explained from a variety \r of perspectives, capturing a  range of possible features, trends, \r processes, and mechanisms. It can be examined in terms of specific \r quantitative indicators, such as population, urbanisation level, \r life expectancy, literacy rate, GDP, carbon dioxide emission rate, \r average surface temperature, etc. Alternately, it can be described \r with reference to trends and shifts in broad socio-political or cultural \r features, such as democratisation, liberalisation, colonisation, \r globalisation, consumerism, etc. Or, it can be described in a way that \r highlights and details a particular domain of interest; for example, \r as an 'economic pathway', 'technological pathway', 'demographic \r [...]"


id: 75b6840bf7fff1db1db2ae41b53d6056
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"[...] pathway', or others. Any such focused description of a pathway is \r more limited, by definition, than the general and encompassing \r notion of a development pathway."


id: 51c01c820ee6a96dac2daab68ba570c0
created_at: 2023-04-19 13:23:09
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"Systematic studies of the 17 SDGs have found the interactions \r among them to be manifold and complex (Nilsson et al. 2016; \r Pradhan et al. 2017; Weitz et al. 2018; Fuso Nerini et al. 2019). \r Addressing them calls for interventions affecting fundamental, \r interconnected, structural features of global society (International \r Panel on Social Progress 2018; TWI2050 - The World in 2050 2018), \r such as to our physical infrastructure (e.g., energy, water, industrial, \r urban infrastructure) (Waage et al. 2015; Adshead et al. 2019; \r Chester 2019; Mansell et al. 2019; Thacker et al. 2019; ), our societal \r institutions (e.g.,  educational, public health, economic, innovation, \r and political institutions) (Ostrom 2010; Klay et al. 2015; Messner \r 2015; Sachs et al. 2019), and behavioural and cultural tendencies \r (e.g.,  consumption patterns, conventional biases, discriminatory \r interpersonal and intergroup dynamics, and inequitable power \r [...]"


id: e2927e3303b654614485d79ef6828e4
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"[...] structures) (Esquivel 2016; Sachs et al. 2019). These observations \r imply that attempt to address each SDG in isolation, or as \r independent technical challenges, would be insufficient, as would \r incremental, marginal changes. In contrast, effectively addressing \r the SDGs is likely to mean significant disruption of long-standing \r trends and transformative progress to shift development pathways \r to meet al. the SDGs, including climate action, beyond incremental \r changes targeted at addressing mitigation objectives in isolation. \r In other words, mitigation conceived as incremental change is not \r enough. Transformational change has implications for equity in its \r multiple dimensions ( Steffen and Stafford Smith 2013; Klinsky et al. \r 2017a; Leach et al. 2018) including just transitions (Section 4.5)."


id: 684b62fe431052e8c09f0786094f9fe6
created_at: 2023-04-19 13:23:09
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"Development priorities are reflected in the decisions that actors \r within societies make, such as policy choices by governments and \r parliaments at all levels, votes over competing policy platforms by \r citizens, or selection of issues that non-state actors push for. Multiple \r objectives range from poverty eradication to providing energy access, \r addressing concerns of inequality, providing education, improving \r health, cleaning air and water, improving connectivity, sustaining \r growth and providing jobs, among others. For example, eradicating \r poverty and reducing inequality is a key development priority across \r many countries, such as Brazil (Grottera et al. 2017), Indonesia \r (Irfany and Klasen 2017), India (GoI 2015), South Africa (Winkler \r 2018) and other low- and middle-income countries (Dorband et al. \r 2019). Reducing inequality relates not only to income, but also to \r other dimensions such as in access to energy services (Tait 2017), \r [...]"


id: 13745f3521c0551acb7e0f71937f4bac
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"[...] gender, education, racial and ethnic profiles (Andrijevic et al. 2020), \r and thereby assumes relevance in both developing and developed \r countries. The development priorities of many poor countries and \r communities with low capacities to adapt, has been focused more \r on reducing poverty, providing basic infrastructure, education and \r improving health, rather than on mitigation (Chimhowu et al. 2019)."


id: 71aa8818aa146ea36909338cc79303a1
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"China's development plans have evolved over time from being \r largely growth oriented, and geared largely towards the objectives \r of addressing poverty, improving health, education and public \r well-being to also including modernisation of agriculture, industry \r and infrastructure, new forms of urbanisation and a clear intent of \r focusing on innovation and new drivers of development (Central \r Compilation & Translation Press 2016). China's 14th Five Year Plan \r not only seeks to promote high quality development in all aspects \r and focus on strengthening the economy in the global industrial \r chain, but also includes a vision of an 'ecological civilisation', which \r had been developed (CPC-CC 2015) and analysed earlier (He 2016; \r Xiao and Zhao 2017). It seeks to enhance China's climate pledge to \r peak CO2 emissions by 2030 and achieve carbon neutrality by 2060 \r through more vigorous policies and measures. Development plans \r [...]"


id: 5efdae8e787b9f35e2051bb0d7676b57
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"[...] tie in multiple development priorities that evolve and broaden over \r time as societies develop, as exemplified inter alia by the history of \r development plans in India (Box 4.4)."


id: e59c0d8a3a4a5570b505381281512b13
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"India's initial national development plans focused on improving the living standards of its people, increasing national income and \r food self-sufficiency. Accordingly, there was a thrust towards enhancing productivity of the agricultural and industrial sectors. While \r the main focus was on maintaining high economic growth and industrial productivity, poverty eradication, employment and inclusive \r growth remained important priorities. The National Action Plan on Climate Change with eight National Missions focusing on mitigation \r as well as adaptation was launched in 2008 integrating climate change considerations in planning and decision-making (MoEF 2008). \r The 12th Five-Year Plan (2012-2017) also brought in a focus on sustainability and mentioned the need for faster, sustainable and \r inclusive growth. The National Institution for Transforming India (NITI Aayog) was set up in 2017 replacing the erstwhile Planning \r [...]"


id: 4022b63cd4c9bdac72050227384e23bc
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"[...] Commission, with a renewed focus towards bringing innovation, technology, enterprise and efficient management together at the \r core of policy formulation and implementation. However, while India has moved away from its Five-Year Plans, decision-making is \r more dynamic, with a  number of sector-specific initiatives and targets focused on integrating sustainability dimensions through \r a series of policies and measures supporting resource efficiency, improved energy access, infrastructure development, low-carbon \r options and building resilient communities, among other objectives (MoEFCC 2018, 2021). India's overall development pathway \r currently has a strong focus on achieving robust and inclusive growth to ensure balanced development across all regions and states \r and across sectors. There is a thrust on embracing new technologies while fostering innovation and upskilling, modernisation of \r [...]"


id: 13a6ca386e0c1aff1863df4219264d24
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"[...] agriculture, improving regional and interpersonal equity, bridging the gap between public and private sector performance, by focusing \r on efficient delivery of public services, rooting out corruption and black economy, formalising the economy and expanding the tax \r base, improving the ease of doing business, nursing the stressed commercial banking sector back to a healthy state, and stopping \r leakages through direct benefit transfers, among other measures (GoI 2015, 2018; MoEFCC 2021)."


id: 85c06aedcd536779559dc155237809f6
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"The Illustrative Mitigation Pathways (IMP) developed for this \r Report (Box 3.1 and Section 3.2.5) provide another example of how \r development pathways influence mitigative capacity. Precisely, \r IMP1.5-SP (Shifting Pathways) and 1.5-Ren (Renewables) lead to the \r same long-term temperature, but differ in underlying socio-economic \r conditions. The former is based on Shared Socio-economic Pathway \r (SSP) 1  (sustainable development), whereas the latter is based on \r SSP2 (middle of the road). Comparing 1.5-Ren to 1.5-SP can thus be \r interpreted as a numerical translation of trying the reach the same \r long-term temperature goal without and with shifting development \r pathways towards sustainability. Data shows that the global price of \r carbon necessary to remain on target is 40-50% lower in the latter \r relative to the former, thus indicating that mitigation is cheaper with \r a  shift in development pathway towards sustainability. Other cost \r [...]"


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"[...] indicators (e.g. consumption loss or GDP loss) tell the same story. \r Since both IMPs were computed using the same underlying model, \r the comparison is even more robust."


id: 51714b12f2a352419259694967d846da
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"Degree of inequality: Chapter  2  notes that while eradicating \r extreme poverty and providing universal access to modern energy \r services to poor populations across the globe has negligible \r implications for emissions growth, existing studies on the role of \r poverty and inequality as drivers of GHG emissions provide limited \r evidence that under certain contexts greater inequality can lead \r to a deterioration in environmental quality and may be associated \r with higher GHG emissions (Section 2.4). In fact, factors affecting \r household consumption-based emissions include household size, \r age, education attainment, employment status, urban vs rural \r location and housing stock (Druckman and Jackson 2015). There \r is evidence to indicate that at the household level, the increase \r in emissions from additional consumption of the lower income \r households could be larger than the reduction in emissions from \r the drop in consumption from the high income households (Sager \r [...]"


id: 63715fedc94be073453a591de5af42ef
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"[...] 2019). Accordingly, as countries seek to fulfil the objective of \r reducing inequality, there are possibilities of higher increase in \r emissions (Sager 2019)."


id: c0f228cd7f4b15b5995a6c490281211f
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"Concerns about mitigation are already being introduced in national \r development plans, as there is evidence that development strategies \r and pathways can be carefully designed so as to align towards multiple \r priorities and achieve greater synergistic benefits. For example, India's \r solar programme is a key element in its NDC that can in the long run, \r not only provide energy security and contribute to mitigation, but \r can simultaneously contribute to economic growth, improved energy \r access and additional employment opportunities, if appropriate \r policies and measures are carefully planned and implemented. \r However, the environmental implications of the transition need to be \r carefully examined with regard to the socio-economic implications \r in light of the potential of other alternatives like green hydrogen, \r nuclear or carbon capture, use and storage (CCUS). Similarly, South \r Africa National Development Plan (2011) also integrates transition to \r [...]"


id: 3583e156769d0963291efce35e15f5af
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"Doing so requires new ways of thinking with interdisciplinary \r research and use of alternative frameworks and methods suited to \r deeper understanding of change agents, determinants of change \r and adaptive management among other issues (Winkler 2018). \r This includes, inter alia, being able to examine enabling conditions \r for shifting development pathways (Section  4.4.1); re-evaluating \r the neo-classical assumptions within most models, both on the \r functioning of markets and on the behaviour of agents, to better \r address obstacles on the demand side, obstacles on the supply \r side and market distortions (Ekholm et al. 2013; Staub-Kaminski \r et al. 2014; Grubb et al. 2015) improving representation of issues \r related with uncertainty, innovation, inertia and irreversibility \r within the larger development contexts, including energy access \r and security; improving the representation of social and human \r capital, and of social, technological and governance innovations \r [...]"


id: a2024b8a0341a7e6b7af0c541cf49f31
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"Tools have been developed in that direction, for example in the \r Mitigation Action Plans and Scenarios (MAPS) community (La \r Rovere et al. 2014b), but need to be further mainstreamed in the \r analysis. Back-casting is often a  preferred modelling approach for \r assessment aiming to align national development goals with global \r climate goals like CO2 stabilisation. Back-casting is a  normative \r approach where modellers construct desirable futures and specify \r upfront targets and then find out possible pathways to attain these \r targets (IPCC et al. 2001). Use of approaches like back-casting are \r useful not only in incorporating the long term national development \r objectives in the models, but also evaluating conflicts and synergies \r more effectively (van der Voorn et al. 2020). In back casting, the long\u0002term national development objectives remain the key benchmarks \r guiding the model dynamics and the global climate goal is interfaced \r [...]"


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"[...] to realise the co-benefits. The models then delineate the roadmap \r of national actions such that the national goals are achieved with "


id: 7b4932492b5c9a667cb5b78d3d7be18e
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content:
"Policies such as those listed in Table 4.12 are typically associated with \r broader objectives than GHG mitigation. They are generally conceived \r and implemented in the pursuit of overall societal development \r objectives, such as job creation, macroeconomic stability, economic \r growth, and public health and welfare. However, they can have major \r influence on mitigative capacity, and hence can be seen as necessary \r tools if mitigation options are to be significantly broadened and \r accelerated (medium evidence, medium agreement). The example of \r the UK shows how accelerated mitigation through dietary changes \r require a wide set of efforts to shift underlying drivers of behaviour. \r In this case, multiple forces have interacted to lead to reduced meat \r consumption, including health attitudes, animal welfare concerns, \r and an increasing focus on climate and other environmental \r impacts of livestock production, along with corporate investment \r [...]"


id: 4dbb67767d6f9440f80680923c2321a2
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"Other historic cases that are unrelated to recent mitigation efforts \r might be more appropriate examples of major socio-technical shifts \r that were largely driven by intentional, coherent intentional policy \r initiatives across numerous domains to meet multiple objectives. The \r modernisation of agriculture in various national contexts fits such \r a  mold. In the USA, for example, major government investments \r in agricultural innovation through the creation of agricultural \r universities and support for research provided advances in the \r technological basis for modernisation. A  network of agricultural \r extension services accelerated the popularization and uptake of \r modern methods. Infrastructure investments in irrigation and drainage \r made production more viable, and investment in roadways and rail \r for transport supported market formation. Agricultural development \r banks made credit available, and government subsidies improved \r [...]"


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content:
"[...] the profitability for farmers and agricultural corporations. Public \r campaigns were launched to modify food habits (Ferleger 2000)."


id: eac996a12fbbbbee4b3834f4829c807d
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"Further examples of SDPS across many different systems and sectors \r are elaborated across this report. Concrete examples assessed in \r this chapter include high employment and low emissions structural \r change, fiscal reforms for mitigation and social contract, combining \r housing policies to deliver both housing and transport mitigation, \r and change economic, social and spatial patterns of development \r of the agriculture sector provide the basis for sustained reductions \r in emissions from deforestation (Sections  4.4.1.7-4.4.1.10). These \r examples differ by context. Examples in other chapters include \r transformations in energy, urban, building, industrial, transport, \r and land-based systems, changes in behaviour and social practices, \r as well as transformational changes across whole economies and \r societies (Cross-Chapter Box 5 in this chapter, Section 5.8, Box 6.2, \r Sections 8.2, 8.3.1, 8.4, 9.8.1, 9.8.2 and 10.4.1, and Cross-Chapter \r [...]"


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"[...] Box 12 in Chapter 16). These examples and others can be understood \r in the context of an explanation of the concept of SDPS, and how to \r shifting development pathways (Cross-Chapter Box 5 in this chapter)."


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"Policy design can also manage trade-offs, for example through policy measures as part of just transitions (Section 17.4). However, \r even with good policy design, decisions about mitigation actions, and the timing and scale thereof, may entail trade-offs with the \r achievement of other national development objectives in the near-, mid- and long term. In the near term, for example, regulations may \r ban vehicles from city centres to reduce congestion and local air pollution, but reduce mobility and choice. Increasing green spaces \r within cities without caps on housing prices may involve trade-offs with affordable housing and push low income residents outside \r the city (Section 8.2.2). In the mid- and long-term, large-scale deployment of biomass energy raises concerns about food security and \r biodiversity conservation (Sections 3.7.1, 3.7.5, 7.4.4, 9.8.1, 12.5.2 and 12.5.3). Conflicts between mitigation and other development \r [...]"


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"[...] objectives can act as an impediment to climate action (Section 13.8). Climate change is the result of decades of unsustainable energy \r production, land-use, production and consumption patterns, as well as governance arrangements and political economic institutions \r that lock in resource-intensive development patterns (robust evidence, high agreement). Reframing development objectives and \r shifting development pathways towards sustainability can help transform these patterns and practices, allowing space for transitions \r transforming unsustainable systems (medium evidence, high agreement) (Chapter 17, Executive Summary)."


id: 2e6c2a34f19adbc100a2d120069df21e
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"There is no one-size-fits-all recipe for shifting development pathways. However, the following insights can be drawn from past \r experience and scenarios of possible future development pathways (Section  4.4.1). For example, policies making inner-urban \r neighbourhoods more accessible and affordable reduce transport costs for low- and middle-income households, and also reduce \r transport emissions (Section 4.4.1.9). Shifts in development pathways result from both sustained political interventions and bottom\u0002up changes in public opinion. No single sector or policy action is enough to achieve this. Coordinated policy mixes would need to \r coordinate multiple actors - in other words, individuals, groups and collectives, corporate actors, institutions and infrastructure actors - \r to deepen decarbonisation and shift pathways towards sustainability (Pettifor 2020). One example was the liquefied petroleum gas \r [...]"


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"[...] (LPG) Subsidy ('Zero Kero') Program in Indonesia which harnessed creative policy design to shift to cleaner energy by overcoming \r existing private interests. The objective of decreasing fiscal expenditures on domestic kerosene subsidies by replacing it with LPG was \r achieved by harnessing distribution networks of existing providers supported by government subsidised provision of equipment and \r subsidised pricing (Cross-Chapter Box 9 in Chapter 13)."


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"In some developed countries and communities, affluence leads to high levels of consumption and emissions across sectors (Mazur \r and Rosa 1974; Wiedmann et al. 2020). For some countries, reducing consumption can reduce emissions without compromising on \r wellbeing. However, some developing countries still face the challenge of escaping 'middle-income traps' (Agenor and Canuto 2015), \r as labour-saving technological change and globalisation have limited options to develop via the manufacturing sector (Altenburg \r and Rodrik 2017). In least developed countries, infrastructure, industry, and public services are still being established, posing both \r a challenge to financial support to deploy technologies, and large opportunities to support accelerating low-to-zero carbon options - \r especially in terms of efficient and sufficient provision (Millward-Hopkins et al. 2020). Availability of capital, or lack thereof, is a critical \r [...]"


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"The literature does not provide a handbook on how to accomplish the \r above. However, analysis of past experience as well as understanding \r of how societies function yield insights that the present section aims \r at presenting. Human history has seen multiple transformation of \r economies due to path-breaking innovations (Michaelowa et al. \r 2018), like the transformation of the energy system from traditional \r biomass to fossil fuels or from steam to electricity (Fouquet 2010, \r 2016a; Sovacool 2016). Fouquet (2016b) and Smil (2016) argue \r that even the most rapid global transformations have taken several \r decades. Enabling transformational change implies to create now \r the conditions that lead to that transformation (Diaz et al. 2019). \r The starting point is that there is no single factor determining such \r a transformation. Rather a range of enabling conditions can combine \r in a co-evolutionary process. Amongst the conditions that have been \r [...]"


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content:
"[...] cited in the literature are higher levels of innovation, multilevel \r governance, transformative policy regimes or profound behavioural \r transformation (Rockstrom et al. 2017; IPCC 2018a; Geels et al. 2018; \r Kriegler et al. 2018). It might be possible to put in place some of \r the above conditions rapidly, while others may take longer, thereby \r requiring an early start."


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content:
"Long experience of political management of change demonstrates \r that managing such risks is not easy, and requires sufficiently strong \r and competent institutions (Stiglitz 1998). For example, shift away \r from fossil fuel-based energy economy could significantly disrupt the \r status quo, leading to a stranding of financial and capital assets and \r shifting of political-economic power. Ensuring the decision-making \r process is not unduly influenced by actors with much to lose is key \r to managing a  transformation. Effective governance, as noted in \r Chapter 13, requires establishing strategic direction, coordination of \r policy responses, and mediation among divergent interests. Among \r varieties of climate governance, which institutions emerge is path\u0002dependent, based on the interplay of national political institutions, \r international drivers, and bureaucratic structures (Dubash 2021). \r Focused national climate institutions to address these challenges \r [...]"


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content:
"[...] are more likely to emerge, persist and be effective when they \r are consistent with a  framing of climate change that has broad \r national political support (medium evidence, medium agreement) \r (Sections 4.5, 13.2 and 13.5)."


id: 33439b50c7c1967ec7bc39e12c483115
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content:
"Because low-carbon transitions are political processes, analyses \r are needed of policy as well as for policy (Section  13.6). Political \r scientists have developed a number of theoretical models that both \r explain policy-making processes and provide useful insights for \r influencing those processes. Case studies of successes and failures \r in sustainable development and mitigation offer equally important \r insights. Both theoretical and empirical analysis reinforce the \r argument that single policy instruments are not sufficient (robust \r evidence, high agreement). Policymakers might rather mobilise \r a range of policies, such as financial instruments (taxes, subsidies, \r grants, loans), regulatory instruments (standards, laws, performance \r targets) and processual instruments (demonstration projects, network \r management, public debates, consultations, foresight exercises, \r roadmaps) (Voss et al. 2007). Policies can be designed to focus on \r [...]"


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"[...] limiting or phasing out high-carbon technology. The appropriate mix is \r likely to vary between countries and domains, depending on political \r cultures and stakeholder configurations (Rogge and Reichardt 2016), \r but is likely to include a combination of: (i) standards, nudges and \r information to encourage low-carbon technology adoption and \r behavioural change; (ii) economic incentives to reward low-carbon \r investments; (iii) supply-side policy instruments including for fossil "


id: e211adf362f1a423e2c73b8c276e679d
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
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content:
"Different approaches have been explored to improve such alignment \r (Section  15.6), from national credit policies to directly green \r mainstream financial regulations (e.g., through modifications in the \r Basel rules for banks). For all approaches, an essential precondition \r is to assess and monitor the contribution of financial flows to climate \r and sustainability goals, with better metrics that clearly link with \r financial activity (Chenet et al. 2019). Enabling the alignment of \r investment decision-making with achieving climate and broader \r sustainability goals includes acknowledgment and disclosure of \r climate-change related risk and of risks associated with mitigation \r in financial portfolios. Current disclosures remain far from the \r scale the markets need to channel investment to sustainable and \r resilient solutions (UNEP - Finance Initiative 2020; Clark et al. 2018; \r Task Force on Climate-Related Financial Disclosures 2019; IPCC \r [...]"


id: b80b758e7176decc087c2ee4867d42cc
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 29599
content:
"[...] 2018b). Disclosure, however, is not enough (Ameli et al. 2020). \r In addition, climate targets can be translated into investment \r roadmaps and financing needs for financial institutions, both at \r national and international level. Financing needs are usable for \r financial institutions, to inform portfolio allocation decisions and \r financing priorities (Chenet et al. 2019). At the international level, \r for example, technology roadmaps for key sectors can be translated \r into investment roadmaps and financing needs, as shown by existing \r experiences in energy and industrial sectors (IEA 2015; IEA and \r WBSCD 2018; Chenet et al. 2019)."


id: e1039dd583f93efd4f79121e81bd2416
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 36852
content:
"Meeting these challenges also requires enhanced institutional \r capacity and enhanced institutional mechanisms to strengthen the \r coordination between multiple actors, improve complementarities \r and synergies between multiple objectives (Rasul 2016; Ringel 2017; \r Liu et al. 2018) and pursue climate action and other development \r objectives in an integrated and coherent way (Von Stechow et al. \r 2016; McCollum et al. 2018; Rogelj et al. 2018b; Roy et al. 2018; Fuso \r Nerini et al. 2019), particularly in developing countries (Adenle et al. \r 2017; Rosenbloom 2017). Institutional capacities to be strengthened \r include vertical collaboration and interaction within nation states \r and horizontal collaboration (e.g.,  transnational city networks) for \r the development and implementation of plans, regulations and \r policies. More specifically capacities include: capacity for knowledge \r harnessing and integration (from multiple perspectives); for \r [...]"


id: c4f2cbcbd43fd15b946eb328d54c09a7
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 31957
content:
"[...] integrated policy design and implementation (Scott 2017); for long\u0002term planning (Lecocq et al. 2021) for monitoring and review process; \r for coordinating multi-actor processes to create synergies and avoid \r trade-offs. As a result, institutions that enable and improve human \r capacities and capabilities are a major driver of transformation. To \r this extent, promoting education, health care and social safety, also \r are instrumental to undertake climate change mitigation and cope \r with environmental problems (Winkler et al. 2007; Sachs et al. 2019). \r Given that strengthening institutions may be a long-term endeavour, \r it needs attention in the near term."


id: 3f9738eb723407408dc6475e05b721ae
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
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content:
"Individual motivation and capacity are impacted by different factors \r that go beyond traditional social, demographic and economic \r predictors. However, it is unclear to what extent behavioural factors \r (i.e., cognitive, motivational and contextual aspects) are taken into \r account in policy design (Dubois et al. 2019; Mundaca et al. 2019). \r In fact, while economic policies play a significant role in influencing \r people's decisions and behaviour, many drivers of human behaviour \r and values work largely outside the market system (Winkler et al. \r 2015; Diaz et al. 2019) as actors in society, particularly individuals, do \r not respond in an economically 'rational' manner based on perfect\u0002information cost-benefit analyses (Runge 1984; Shiller 2019). Rather, \r compelling narratives can drive individuals to adopt new norms and \r policies. And norms can be more quickly and more robustly shifted \r by proposing and framing policies designed with awareness of how \r [...]"


id: af829d3f7866e47aaae7e3b738aee54
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 28110
content:
"[...] framings interact with individual cognitive tendencies (van der Linden \r et al. 2015). Transformative policies are thus much more likely to be \r successfully adopted and lead to long-term behavioural change if \r designed in accordance with principles of cognitive psychology (van \r der Linden et al. 2015), and with the deep understanding of decision\u0002making offered by behavioural science (UNEP 2017b). Similarly, given \r that present bias - being motivated by costs and benefits that take \r effect immediately than those delivered later  - significantly shapes \r behaviour, schemes that bring forward distant costs into the present or \r that upfront incentives have proved to be more effective (Zauberman \r et al. 2009; van den Broek et al. 2017; Safarzynska 2018). Overall, \r transformational strategies that align mitigation with subjective life \r satisfaction, and build societal support by positive discourses about \r economic, social, and cultural benefits of low-carbon innovations, \r [...]"


id: 2ce55e54f1060c33d53660a08930c045
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 5170
content:
"[...] promises far more success than targeting mitigation alone (WBGU \r 2011; Asensio and Delmas 2016; Geels et al. 2017)."


id: 6963bf0ae8173eb6ba2fdec1ba119d1c
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 15810
content:
"At the national level, it is also essential to create public fiscal space \r for actions promoting the SDG agenda and thereby broadening the \r scope of mitigation (medium evidence, medium agreement). To do \r so, pricing carbon - either through tax payments based on the level \r of emissions or cap-and-trade systems that limit total allowable \r emissions - is an efficient means of discouraging carbon emissions \r throughout an economy (both in consumption and production) while \r simultaneously encouraging a switch to non-carbon energy sources \r and generating revenues for prioritised actions (Section  13.6.3). \r Regarding to levels, the High-Level Commission on Carbon Prices \r concluded that 'carbon-price level consistent with achieving the Paris \r temperature target is at least USD40-80 tCO2\r -1 by 2020 and USD50-\r 100 tCO2\r -1 by 2030, provided a supportive policy environment is in \r place' (CPLC 2017; Wall Street Journal 2019). National level models \r [...]"


id: e2689cabfbfacc2c3792976c8ba1794a
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 37125
content:
"[...] yield median carbon values of carbon values of USD733 tCO2\r -1 in \r 2050 along accelerated mitigation pathways (Section 4.2.6), while \r global models find a median value of USD578 tCO2\r -1 for pathways \r that reach net zero CO2 between 2045 and 2055 [interquartile range \r USD405-708] (Section 3.6.1)."


id: f56afe72f98f1077bfd02a91e789b3a
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 40544
content:
"Carbon pricing, however, is designed to reduce its fiscal base. \r Fiscal space may therefore also need to stem from other sources, \r although fiscal reforms are complex endeavours (Section 4.4.1.8). For \r countries at lower income levels, foreign aid can make an important \r contribution to the same agenda (Kharas and McArthur 2019). It may \r also be noted that, according to estimates at the global level, military \r spending amounted to USD1.748 trillion in 2012 (the last year with \r data), a figure that corresponded to 2.3% of GDP, 55% of government \r spending in education, and was 13 times the level of net ODA (World \r Bank 2020; SIPRI 2020). Given this, moderate reductions in military \r spending (which may involve conflict resolution and cross-country \r agreements on arms limitations) could free up considerable resources \r for the SDG agenda, both in the countries that reduce spending and \r in the form of ODA. The resolution of conflicts within and between \r [...]"


id: 9cea821a9f521f15923b00b619a321c0
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 24843
content:
"[...] countries before they become violent would also reduce the need for \r public and private spending repairing human and physical damage. \r The fact that civil wars are common in the countries that face the \r severest SDG challenges underscores the importance of this issue \r (Collier 2007, pp.17-37)."


id: 78b29833a4f1e1c04ce3525e9105f812
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 18426
content:
"Several studies have pointed at the important possible contributions \r of grassroots innovators for the start-up of sustainability transitions \r (Seyfang and Smith 2007; Seyfang et al. 2014; Smith et al. 2016). In \r particular, a range of studies have shown that users can play a variety \r of roles in promoting system innovation: shielding, nurturing (including \r learning, networking and visioning) and empowering the niches \r in relation to the dominant system and regime (Schot et al. 2016; \r Randelli and Rocchi 2017; Meelen et al. 2019). More fundamentally, \r innovation regimes can be led and guided by markets driven by \r monetisable profits (as much of private sector led technological \r innovation of patentable  intellectual property), or prioritise social \r returns (e.g.,  innovation structures such as innovation prizes, public \r sector innovation, investments in human capital, and socially-beneficial \r intellectual property regimes). In both cases, public policies can play \r [...]"


id: 971579226f2d5282d7e7d532d42b7fd7
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 23775
content:
"[...] a key role by providing resources and favourable incentives (IEA 2020). \r Chapter 16 provides more details on ways to foster innovation."


id: 1598178133fa711c635ae61e96b55b6a
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 1014
content:
"As outlined in Section 4.2.5, rapid, large-scale deployment of improved \r low-carbon technology is a  critical component of accelerated \r mitigation pathways. As part of its key role in technological \r change, R&D can make a crucial contribution to accelerated mitigation \r up to 2030 and beyond, among other things by focusing on closing \r technology gaps that stand in the way of decarbonising today's high \r emitting sectors. Such sectors include shipping, trucking, aviation \r and heavy industries like steel, cement and chemicals. More broadly, \r it is increasingly clear that digital changes are becoming a key driving \r force in societal transformation (Tegmark 2017). Digitalisation is not \r only an 'instrument' for resolving sustainability challenges, it is also \r a fundamental driver of disruptive, multiscalar change (Sachs et al. \r 2019) that amounts to a shift in development pathway. Information \r and communication technologies, artificial intelligence, the internet \r [...]"


id: c175a80c3750066d84eaf4ff18f59250
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 31343
content:
"[...] of things, nanotechnologies, biotechnologies, robotics, are not usually \r categorised as climate technologies, but have a potential impact on \r GHG emissions (OECD 2017b) (Cross-Chapter Box 11 in Chapter 16)."


id: 340df8b92e508c0f8982573235250b33
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 6401
content:
"climate mitigation component of the fiscal reform varies strongly \r with the context, and may not be sufficient to address the other \r objectives pursued. Even if the carbon price is high, the revenue \r it generates may be moderate as a share of GDP and eventually it \r will be zero if emissions are eliminated. For example, Jakob et al. \r (2016) find that the carbon pricing revenues that most countries \r in Sub-Saharan Africa could expect to generate only would meet \r a  small part of their infrastructure spending needs. In Sweden, \r the country with the highest carbon tax rate in the world, the tax \r has not been a  significant part of total tax revenues. Moreover, \r emissions from sectors covered by the tax have shrunk and, \r as a  result, the revenues from the tax, as a  share of GDP, have \r also declined, from a peak of 0.93% in 2004, when the rate was \r USD109 per metric tonne of CO2, to 0.48% in 2018, when the rate \r [...]"


id: 779bd1faf558e648be848df1775a3134
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 18247
content:
"[...] had reached USD132 (Jonsson et al. 2020; Statistics Sweden 2020). \r This means that governments that want to avoid a decline in the \r GDP share for total tax revenues over time would have to raise \r the intake from other taxes. However, it is here important to note \r that domestic tax hikes are likely to involve trade-offs since, at the \r same time as the spending they fund may provide various benefits, \r they may also reduce the capacity of households and the private \r sector to consume and invest, something that may reduce growth \r over time and reduced resources for spending in support of human \r development (Lofgren et al. 2013). It is also worth emphasising that \r restructuring of the fiscal system amount to changes in the social \r contract of the society (Combet and Hourcade 2017 and 2014), and \r thus represents a major economic and social decision."


id: 56b0f03162076e483d27dbcf1db65681
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 12506
content:
"The timing of carbon pricing reforms is also important: they are more \r likely to succeed if they exploit windows of opportunity provided \r by events that raise awareness of the costs of carbon emissions \r (like bouts of elevated local air pollution or reports about the role \r of emissions in causing global warming), as well as momentum \r from climate actions by other countries and international climate \r agreements (Karapin 2016; Jakob et al.2019). It is also important \r to consider the level of international prices of carbon energy: when \r they are low, consumer resistance would be smaller since prices \r will remain relatively low, though the tax may become more visible \r when energy prices increase again. As part of ongoing efforts \r to accelerate mitigation, such tax hikes may be crucial to avoid \r a  slow down in the shift to renewable energy sources (Withana \r 2016; Rentschler and Bazilian 2017). In countries that export \r [...]"


id: c363427f7ff3120a0c7e8d0459746438
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 31647
content:
"There is also considerable literature providing insights on the political \r and social acceptability of carbon taxes, suggesting for example \r that political support may be boosted if the revenue is recycled to \r the tax payers or earmarked for areas with positive environmental \r effects (e.g., Bachus et al. (2019) for Belgium, and Beiser-McGrath \r and Bernauer (2019) for Germany and the USA), as well as on \r the difficulties associated with political vagaries (and economic \r consequences thereof) associated with the introduction of such \r instruments (Pereira et al. 2016). Similarly, 'best practices' have been \r drawn from past experience on fossil-fuel subsidy reforms (Rentschler \r and Bazilian 2017; Sovacool 2017). Specific policies, however, \r depend on societal objectives, endowments, structure of production, \r employment, and trade, and institutional structure (including the \r functioning of markets and government capacity) (Kettner et al. \r [...]"


id: 3aacd9c0754018f9bcdf1ae5d167661c
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updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 7527
content:
"[...] 2019). As noted in Section 4.2.6, macroeconomic analysis finds that \r the overall economic implications of carbon pricing differ markedly \r depending on the way the proceeds from carbon pricing are used, \r and thus on the way the fiscal system is reformed, with potential for \r double dividend if the proceeds from the tax are used to repeal the \r most distortive taxes in the economy."


id: 9048097465e9cd6781aab6cba02e539e
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 22584
content:
"A growing literature assesses co-benefits of sectoral policies that \r lead to decarbonisation and simultaneously promote economic \r development, improve living standards, reduce inequality, and create \r job opportunities (Maroun and Schaeffer 2012; Bataille et al. 2016b; \r Pye et al. 2016; Bataille et al. 2018; La Rovere et al. 2018; Richter \r et al. 2018; Waisman et al. 2019). While this may be particularly \r challenging in developing countries, given large populations still \r lacking basic needs, previous development paths show that finding \r synergies in development and climate objectives in the AFOLU \r sector is possible. One example is Brazil, which has arguably shifted \r its development pathway to reduce emissions and make progress \r towards several SDGs, though progress is not linear. Over the past \r two decades, Brazil had made remarkable progress in implementing \r a sequence of policies across multiple sectors. This policy package \r [...]"


id: 1c545ff627857d7514f5d316c2b14fbf
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 2172
content:
"[...] simultaneously increased minimum wages of low income families, \r achieved universal energy access, and raised the quality of life and \r well-being for the large majority of the population (Da Silveira \r Bezerra et al. 2017; Grottera et al. 2017, 2018; La Rovere et al. 2018). \r This led to significant social benefits, reduction of income inequality \r and poverty eradication (Da Silveira Bezerra et al. 2017; Grottera \r et al. 2017), reflected in a decrease of the Gini coefficient and a rise \r in the human development index (La Rovere 2017)."


id: b5e0533af9b8f4dd1cfd50f9a10bc5f1
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 29221
content:
"Making inner-cities neighbourhoods more accessible and more \r affordable is a complex endeavour (Benner and Karner 2016). At the \r same time, it is already a policy objective in its own right in many \r countries, independent of the climate mitigation motivation, for \r a  range of social, health and economic reasons. Revenues derived \r from climate policies could provide additional resources to support \r such programs, as some climate policy already have provisions to use \r their revenues towards low-income groups (Karner and Marcantonio \r 2018). The mitigation benefits of keeping inner-cities more accessible \r and affordable for low- and middle-income households often remains \r out of, or is only emerging in the debates surrounding the planning \r of fast-developing cities in many developing countries (IADB 2012; \r Grant 2015; Khosla and Bhardwaj 2019). Finally, from a  political \r economy perspective, it is also interesting to note that (Bergquist et \r [...]"


id: 146dd3a2dca184a0a4748189e796df04
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index: climate_gpt_v2
vector_id: 815
content:
"[...] al. 2020) find higher support for climate policy packages in the USA \r when affordable housing programs are included."


id: 10c6c3acb4ad7a2c7ad5c38f2791505f
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 134
content:
"In addition, investment in infrastructure is critical to the development \r of decarbonised economic structures that generate growth, \r employment, and universal access to a wide range of services that \r are central to the SDG agenda: transportation, water, sanitation, \r electricity, flood protection, and irrigation. For low- and middle\u0002income countries, annual costs of reaching these goals by 2030 and \r putting their economies on a path toward decarbonisation may range \r between 2% and 8% of GDP, with the level depending on spending \r efficiency. Notably, these costs need not exceed those of more \r polluting alternatives (Rozenberg and Fay 2019). For transportation, \r this involves a shift toward more public transportation (rail and bus), \r and decarbonised electricity for vehicles, combined with land-use \r policies that densify cities and reduce distances between homes and \r jobs. By influencing the spatial distribution of households and firms \r [...]"


id: af5c0a092538b3d65a9ae4186b025aa0
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updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 28085
content:
"[...] and the organisation of transportation, infrastructure has a strong \r bearing on GHG emissions and the costs of providing services to \r different populations. Depending on country context, the private \r sector may play a  particularly important role in the financing of \r infrastructure (World Bank 2009; Klein 2015)."


id: 9fbd236ad4fdd9bbcabe2af3a0245a0a
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 25308
content:
"Regulatory instruments were used to limit deforestation rates, \r together with implemented economic instruments that provided \r benefits to those protecting local ecosystems and enhancing land\u0002based carbon sinks (Nunes et al. 2017; Bustamante et al. 2018; \r Soterroni et al. 2018, 2019). In parallel, public policies reinforced \r environmental regulation and command-and-control instruments \r to limit deforestation rates and implemented market-based \r mechanisms to provide benefits to those protecting local ecosystems \r and enhancing land-based carbon sinks (Sunderlin et al. 2014; \r Nunes et al. 2017; Hein et al. 2018; Simonet et al. 2019). The private \r sector, aligned with public policies and civil society, implemented the \r Amazon Soy Moratorium, a voluntary agreement that bans trading of \r soybeans from cropland associated with cleared Amazon rainforest \r and blacklists farmers using slave labour. This was achieved without \r [...]"


id: ff6c775efd001a9ad5b6532ee8989075
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
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index: climate_gpt_v2
vector_id: 42339
content:
"[...] undermining production of soybean commodities (Soterroni et al. \r 2019). As a result, between 2005 and 2012, the country halved its \r GHG emissions and reduced the rate of deforestation by 78% (INPE \r 2019a,b). This example shows that development delivering well\u0002being can be accompanied by significant mitigation. A  long-term \r and strategic vision was important in guiding enabling policies \r and mechanisms."


id: ff08d90b92e56639ff2d81d8151995b
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 42270
content:
"A substantial literature detailing trade-offs and synergies between \r mitigation and adaptation exists and is summarised in the IPCC SR1.5 \r including energy system transitions; land and ecosystem transitions \r (including addressing food system efficiency, sustainable agricultural \r intensification, ecosystem restoration); urban and infrastructure \r system transitions (including land use planning, transport systems, \r and improved infrastructure for delivering and using power); \r industrial system transitions (including energy efficiency, bio-based \r and circularity, electrification and hydrogen, and industrial carbon \r capture, utilisation and storage (CCUS); and carbon dioxide removal \r (including bioenergy with CCS, afforestation and reforestation, \r soil carbon sequestration, and enhanced weathering) (IPCC 2018: \r Table  4.SM.5.1). Careful design of policies to shift development \r pathways towards sustainability can increase synergies and manage \r [...]"


id: 990e2175954324d71cfdf6ec2edc8fc8
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 24144
content:
"In more recent years, some of these shifts in Brazil's development \r pathways were undone. Political changes have redefined \r development priorities, with higher priority being given to \r agricultural development than climate change mitigation. The current \r administration has reduced the power of environmental agencies and \r forestry protection laws (including the forest code), while allowing \r the expansion of cropland to protected Amazon rainforest areas \r (Ferrante and Fearnside 2019; Rochedo et al. 2018). As a result, in \r 2020, deforestation exceeded 11,000 km2\r , and reached the highest \r rate in the last 12 years (INPE 2020). The literature cautions that, \r if current policies and trends continue, the Amazon may reach an \r irreversible tipping point beyond which it will be impossible to \r remediate lost ecosystems and restore carbon sinks and indigenous \r people knowledge (Lovejoy and Nobre 2018; INPE 2019a; Nobre \r [...]"


id: dd03414748f821f5ffa044595833f1f2
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 36145
content:
"[...] 2019). In addition, fossil fuel subsidies and other fiscal support of \r increased exploitation of oil resources may create carbon lock-ins \r that further inhibit low-carbon investments (Lefevre et al. 2018)."


id: d17afeabfd1bc42d33e160183b9cf637
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 34207
content:
"Previous IPCC assessments have reflected on making development \r more sustainable (IPCC et al. 2001; Sathaye et al. 2007; Fleurbaey \r et al. 2014). Other assessments have highlighted how ecosystem \r functions can support sustainable development and are critical to \r meeting the goals of the Paris Agreement (IPBES 2019b). IPCC SR1.5 \r found that sustainable development pathways to  1.5degC broadly \r support and often enable transformations and that 'sustainable \r development has the potential to significantly reduce systemic \r vulnerability, enhance adaptive capacity, and promote livelihood \r security for poor and disadvantaged populations (high confidence)' \r (IPCC 2018b: Section  5.3.1). With careful management, shifting \r development pathways can build greater adaptive and mitigative \r capacity, as further confirmed in recent literature (Schramski et al. \r 2018; Harvey et al. 2014; Ebi et al. 2014; Rosenbloom et al. 2018; \r [...]"


id: a1d49f0f0ff41f8a5c697a4669e999ee
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updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 25690
content:
"[...] Antwi-Agyei et al. 2015; Singh 2018; IPBES 2019b). The literature \r points to the challenge of design of specific policies and shifts \r in development pathways to achieve both mitigation and \r adaptation goals."


id: 3d8ab2d6a29b4c014399849917edd507
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 8001
content:
"Mitigation actions can be adaptive and vice-versa. In particular, \r many nature-based solutions (NBS) for climate mitigation \r are  adaptive (medium evidence, medium agreement). Multiple \r NBS are being pursued under current development pathways \r (Chapter  7), but shifting to sustainable development pathways \r may enable a wider set of nature-based mitigation solutions with \r adaptation benefits. An example of this would be a shift to more \r sustainable diets through guidelines, carbon taxes, or investment \r in  R&D of animal product substitutes (Figure  13.2) which could \r reduce pressure on land and allow for implementation of multiple \r NBS. Many of these solutions are consistent with meeting other \r societal goals, including biodiversity conservation and other \r sustainable development goals (Griscom et al. 2017; Fargione \r et al. 2018; Tallis et al. 2018). However, there can be synergies \r and trade-offs in meeting a  complex set of sustainability goals \r [...]"


id: cd800e02d3b59fa8c10e268f78ab043c
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 33486
content:
"Systems transitions that address both adaptation and mitigation \r include the widespread adoption of new and possibly disruptive \r technologies and practices and enhanced climate-driven innovation \r (IPCC 2018a). See Chapter  16 for an in-depth discussion of \r innovation and technology transfer. The literature points to trade\u0002offs that developing countries face in investing limited resources \r in research and development, though finding synergies in relation \r to agriculture (Adenle et al. 2015). Other studies point to difference \r in technology transfers for adaptation and mitigation (Biagini \r et al. 2014). Adaptation projects tend to use existing technologies \r whereas mitigation climate actions are more likely to rely on novel \r technologies. Innovations for mitigation are typically technology \r transfers from developed to less-developed countries (Biagini \r et al. 2014), however this so-called North-South technology transfer \r [...]"


id: 644cd86d1a448fce403dba96e2da3d3c
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 14930
content:
"[...] pathway is not exclusive (Biagini et al. 2014), and is increasingly \r challenged by China's global role in implementing mitigation actions \r (Chen 2018; Urban 2018). Indigenous knowledge can be a unique \r source for techniques for adaptation (Nyong et al. 2007) and may be \r favoured over externally generated knowledge (Tume et al. 2019)."


id: 956f61b276585f5ecb61b7f98574a134
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 23495
content:
"Restoration or protection of coastal ecosystems is an important \r adaptation action with multiple benefits, with bounded global \r mitigation benefits (Gattuso et al. 2018; Bindoff et al. 2019). Such \r restoration/preservation reduces coastal erosion and protects from \r storm surges, and otherwise mitigates impacts of sea level rise and \r extreme weather along the coast line (Siikamaki et al. 2012; Romanach \r et al. 2018; Alongi 2008). Restoration of tidal flow to coastal wetlands \r inhibits methane emissions which occur in fresh and brackish water \r (Kroeger et al. 2017) (Section 7.4.2.8 describes a more inclusive set \r of ecosystem services provided by coastal wetlands). Coastal habitat \r restoration projects can also provide significant social benefits in the \r form of job creation (through tourism and recreation opportunities), \r as well as ecological benefits through habitat preservation (Edwards \r et al. 2013; Sutton-Grier et al. 2015; Sutton-Grier and Moore 2016; \r [...]"


id: 769984a3c03c1a903554e47966026772
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 18086
content:
"Remedies include first devising policy packages that are, to the \r extent possible, robust to uncertainty regarding external decisions. \r For example, mitigation in the building sector is considered less \r problematic for competitiveness since the construction sector is \r less exposed to international competition. Remedies also include \r securing international cooperation to reduce the uncertainty \r that domestic decision-makers face about the international \r context. Shifting investments towards low-GHG solutions requires \r a  combination of conducive public policies, attractive investment \r opportunities and financing of transitions (Section 15.6), which can \r enable shifting development pathways. Cooperation can generate \r positive spill overs through technology diffusion (Section  13.6.6). \r Third, cooperation is not limited to governments. As discussed in \r Section 4.2.3, international cooperative initiatives among non-state \r [...]"


id: dd64c4f5b4c78661116958da028c7a6
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 36219
content:
"[...] actors (cities, economic branches, etc.) can also provide know-how, \r resources and stable cooperative frameworks that reduce uncertainty \r for individual actors (Section 14.5.5)."


id: 305e2dbd98138bd55af1e9f9c4ed3f56
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 5764
content:
"As outlined in the examples in Section  4.4.1 above, shifting \r development pathways and accelerating mitigation are complex \r endeavours, on which there is limited experience and know-how \r from the past. An uncertainty is that parts of these policy packages \r may fail, in other words, under-deliver relative to the amount of \r mitigation and of transformations initially expected. For example, \r France has failed to meet its 2015-2018 carbon budget as housing \r retrofitting programs, in particular, have failed to deliver the expected \r amount of emission reductions (Haut Conseil pour le Climat 2019). \r There are two main options to tackle this risk. The first is to build \r in redundancy. The second is to anticipate that some parts of the \r policies will inevitably fail, and build-in monitoring and corrective \r mechanisms in a sequential decision-making process. To this regard, \r building institutions that can properly monitor, learn from and \r [...]"


id: e89483a76f892f2bba101b694592473c
created_at: 2023-04-19 13:23:09
updated_at: 2023-04-19 13:23:09
content_type: text
index: climate_gpt_v2
vector_id: 38259
content:
"As noted above, shifting development pathways and accelerating \r mitigation involve a  broad range of stakeholders and decision\u0002makers, at multiple geographical and temporal scales. They \r require a  credible and trusted process for reconciling perspectives \r and balancing potential side-effects, managing winners and losers \r and implementing compensatory measures to ensure an inclusive \r just transition (Newell and Mulvaney 2013; Miller and Richter 2014; \r Gambhir et al. 2018; Diffenbaugh and Burke 2019). Such processes \r are designed to manage the risk of inequitable or non-representative \r power dynamics (Helsinki Design Lab 2011; Boulle et al. 2015; \r Kahane 2012). More generally, stakeholder processes can be subject \r to regulatory capture by special interests, or outright opposition \r from a  variety of stakeholders. Information asymmetry between \r government and business may shape the results of consultative \r processes. Long experience of political management of change \r [...]"


