Instruction: create a high quality summary of the given input

Input:
Self-managing artificial pancreas controls glucose levels
 A novel artificial pancreas (AP) system with a smartphone backbone could automatically monitor and adjust patients' glucose levels with little to no hassle, according to a new clinical study published in the journal Diabetes Care.

Unlike previously examined AP systems, the newest iteration — which consists of an insulin pump, continuous glucose monitoring receiver, a Bluetooth-connected smartphone device — uses cloud-based algorithmic calculations to determine weekly adaptations to patients’ insulin delivery without requiring assistance from users or clinicians.

“A limitation of current AP systems is that patients must still input carbohydrate estimations for delivery of meal insulin boluses,” the researchers wrote in the study. “As a result, a number of recent AP studies have included a period of clinician-led optimization of open-loop insulin pump settings or continued clinician adjustments to these settings throughout their use … To help with this process, different degrees of automated adaptation are being developed. Yet how best to optimize adaptation to safely improve glucose control … remains to be determined.”

The researchers’ efforts to develop an adaptive algorithm are based on a previous strategy called “model-predictive control.” By targeting an acceptable glucose level range and building an algorithm that improves with repeated daily cycles, the system can handle basal control and variations due to meals without manual assistance.

To test the automated system, researchers enrolled 30 adult patients with type 1 diabetes in a multi-site clinical trial. Over the course of the 12-week study they observed patients’ hemoglobin A1c (HbA1c) levels, a key indicator of blood sugar for diabetics, along with other secondary data generated by the continuous glucose monitoring device. The results, they wrote, were promising.

“This is the longest test we have conducted of our algorithm in an outpatient setting, hence it is a demonstration of the remarkable robustness of the algorithm,” Frank Doyle, professor and dean at Harvard’s School of Engineering and Applied Sciences, told MobiHealthNews in an email. “It is also the first time we have tested a real-time algorithm with adaptation, showing the power of personalizing the solution to the individual.”

Along with significantly lower levels and a reduction in hypoglycemia, the researchers also noted that less than 10 percent of algorithmic insulin delivery recommendations were overridden through the course of the study. In addition, the greatest changes to delivery were made in the early weeks of the study, with lesser adjustments becoming necessary as the algorithm adapted. Despite some limitations in study design and population, the system “has the potential to deliver enormous benefits” and warrants continued study into adaptive AP systems, they concluded.

Output: Researchers at Harvard’s School of Engineering and Applied Sciences have carried out a 12-week trial on an artificial pancreas (AP) which uses an adaptive algorithm to automatically monitor and adjust glucose levels in patients with type 1 diabetes. In a report published in the journal Diabetes Care, the team's AP system linked an insulin pump, a continuous glucose monitoring receiver and a smartphone. The trial of 30 adult patients saw less than 10% of algorithmic insulin delivery recommendations overridden, and fewer adjustments to the algorithm were needed as the weeks passed.


Instruction: create a high quality summary of the given input

Input:
California marijuana farms suffer from lack of insurance
 As wine growers assess the damage from the Northern California wildfires, marijuana farms are also counting their losses. But unlike other businesses, they have little reprieve.

“We’ve lost millions of dollars of product for sure,” said Ned Fussell, CEO of CannaCraft. “And we have no insurance.”

Even though California will begin issuing licenses for commercial cannabis starting in January, farmers like Fussell do not qualify for crop insurance, because growing marijuana is still against federal law.

Fussell’s company — one of the largest cannabis manufacturers in California — grows marijuana plants and turns them into cannabis oil, which is used to create over 100 different products. Fussell owns about 20 farms in Northern California, but he’s been able to access only a few of them. The others are in fire zones, still burning.

“As bad as this looks, others are a lot worse,” Fussell said Monday morning. “A lot of them are just totally incinerated.”

Hezekiah Allen, executive director of the California Growers Association, said many smaller farmers lost not only their farms, but also their homes.

“This all comes at about the worst timing,” Allen said. “October is harvest season, and many of these farmers have poured their life savings into this business.”

On Fussell’s farm in Santa Rosa, smoke still rises from what once was a 10,000-square-foot curing barn, where CannaCraft stored and dried marijuana before pressing it for oil.

Fussell points into the only thing left standing, a 40,000-square-foot greenhouse with hundreds of marijuana plants inside. There are dozens of heavy industrial fans blowing, and Fussell said there’s a 50-50 chance that even this crop has been ruined by the smoke.

“We’re just concerned about what contaminants might be in the air. We’ll have to test for all those things now,” Fussell said.

Fussell is using a gas generator to pump the wells for water to preserve what little crop is left. He said that while it is devastating, pot farmers are resilient, and they’ve already gone through a lot to get this far.

“We’ve been kicked down many times before, and I’ve always found it’s really important to just kind of keep a level head through it all and just try to, like, see the light at the end of the tunnel,” Fussell said. “And I look all around us, and see so many people have lost so much more. It’s sobering.”

Fussell’s company is now doing what it can to assist other farmers affected by the fires. They’re forming a nonprofit to collect donations for smaller farmers who were wiped out.

“Not everyone will survive this,” he said. “These fires will have profound effect on the industry.”

Output: Northern Californian marijuana farms damaged by recent forest fires in the region are bemoaning a lack of insurance coverage. Many facilities in the region have been unable to find coverage due to marijuana usage being illegal under US federal law. Adult usage of marijuana for recreational purposes is due to become legal in California in January, and the crop is already used medically and to produce products such as oil.


Instruction: create a high quality summary of the given input

Input:
Lifebroker launches insurance quote chatbot on Facebook Messenger
 Life insurance comparison service Lifebroker has announced the launch of Alfred, a Facebook Messenger chatbot that gives consumers 24/7 access to conversational quote comparison services.

Alfred is the Australian life insurance industry's first chatbot that compares life insurance options in real-time.

Built with the support of Jade Software, Alfred was designed to respond to customer questions and provide them with quotes for life insurance cover within five minutes of messaging.

Alex Homer, Lifebroker CEO, says Alfred was developed to deliver customer service improvements by providing them with better access via social media channels and enhanced access to the service out-of-hours that complements Lifebroker's existing channels. “Alfred provides an option for customers who need quick responses and who enjoy using messaging services to connect with companies. Our insights showed that product research is usually done outside of normal working hours, and a chatbot can be available instantly and at any time, giving consumers a convenient way to learn about their insurance options on their own terms.

“Conversations with Alfred can be paused and resumed at will throughout the day and consumers can book an appointment with one of our customer service representatives to discuss more advanced questions.

“Alfred is a very welcome addition to Lifebroker's team of customer service experts, working alongside our existing operations on phone, email and online chat. By integrating our digital and human interactions, we're providing a more engaging and seamless customer experience,” says Homer.

By leveraging artificial intelligence like natural language processing, Alfred has the ability to respond to consumers in context, and with a sense of humour, as opposed to providing stock responses.

Eduard Liebenberger, Jade Software digital head, says Alfred was made using a number of technologies that mirror the intelligence and interaction of human agents.

“User experience is what really makes this chatbot special. It creates the soft skills that make people want to interact with a chatbot and keep them engaged.

“Lifebroker has seen first-hand what people seeking to compare quotes look for online, and we've been able to take those learnings and integrate them into this experience.

“The goal of this project was to challenge the way things are done in insurance. Chatbots offer a new platform for insurers to interact with customers, and when customers can learn more about a business 24 hours a day, that's a good position to be in,” he said.

Alfred is currently live in-market following a three-month development period and customer pilot process.

Output: Australian life insurance comparison provider Lifebroker has teamed up with Jade Software to launch a Facebook Messenger chatbot. Known as Alfred, the bot will be able to answer customer questions and offer quotes on policies within five minutes, the company said. Alfred will use artificial intelligence and is being touted as responding more naturally to consumer questions, rather than simply providing stock responses.


Instruction: create a high quality summary of the given input

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Chinese tourists can now use Alipay in Denmark
 COPENHAGEN — The world's leading mobile payment platform Alipay was launched in Denmark on Monday, enabling its Chinese users to enjoy its fast and convenient payment service when they travel to the Nordic country.

Operated by Ant Financial Services Group, an affiliate company of China's Alibaba Group, Alipay users can hail a taxi, book a hotel, buy movie tickets, pay utility bills, make appointments with doctors, or purchase wealth management products directly from within the app.

"We are happy that Denmark and the Nordics are embracing Alipay for Chinese tourists. The adoption of Alipay services of both payment and marketing will not only enhance the experience of Chinese consumers but also help Danish businesses to reach out to their Chinese customers even before they depart from China," said Wang Li, head of Alipay EMEA (Europe, Middle East and Africa).

Alipay was launched in Denmark by APay Nordic AS, in cooperation with 2paynow, the technology platform provider of Alipay in Europe.

"We are glad to see that APay Nordic is now introducing Alipay into Denmark, which will further strengthen the advantages of Denmark as a Chinese-friendly destination," said Miklos Bengtsen, CFO of ILLUM, a premium department store in Copenhagen, adding that China is a very important market for the Danish retail business.

According to Wang, Alipay's in-store payment service is covering more than 30 countries across the world, and tax reimbursement via Alipay is supported in 24 countries and regions.

Alipay has been launching its services in Europe since mid-2016. Denmark is the fourth Northern European country for Alipay to set foot in after Norway, Finland and Sweden.

Alipay now has over 520 million active users and over 450 financial institution partners globally. Over 10 million merchants accept Alipay across China.

Output: Alipay has launched in Denmark so as to cater to Chinese travellers coming to the country. The Alipay mobile app, which is operated by Ant Financial – an affiliate of Alibaba, allows Chinese visitors to book hotels, hail taxis, pay bills and purchase wealth management products and other goods and services. Chinese tourists are an important market for Danish retailers. Alipay has already launched in Finland, Norway and Sweden.


Instruction: create a high quality summary of the given input

Input:
Conde Nast makes a profit turning magazine articles into films
 On Oct. 20, “Only the Brave,” a film starring Josh Brolin and Jeff Bridges, premiered to rave reviews. The movie, based on a GQ article from 2013 titled “No Exit,” tells the harrowing story of a group of Arizona firefighters who perished battling the Yarnell Hill fire that year. Whereas in the past, film studios would buy the rights to articles in Condé Nast publications from the writers and turn them into hits — the Academy Award-winning “Argo,” adapted from a Wired article, is a famous recent example — Condé Nast is now making money off of such adaptations.

Today, Condé Nast’s 6-year-old entertainment video division has 35 feature film and 30 TV projects in development and production, the company said. This includes upcoming feature films “The Old Man and the Gun,” starring Robert Redford and Casey Affleck; and “King of the Jungle,” starring Johnny Depp; as well as TV series such as “Last Chance U” for Netflix and “Vanity Fair Confidential” for Investigation Discovery.

CNE overall is on track to be profitable this year, said Dawn Ostroff, president of Condé Nast Entertainment. Its digital division, where CNE functions as both a producer and distributor of video, has been profitable since last year. Digital still accounts for a majority of CNE’s revenues, but that’s expected to change in the next five years as the feature film and TV business picks up, Ostroff said.

“You have to remember, there’s a much longer lead time in film and TV — it usually takes three to five years to get a movie made; it takes two years to get a TV show made,” Ostroff said.

At a time when many digital media companies are vying to get on film and TV — and when few have actual deals and projects on air to show off — CNE is further along than most, if not all digital publishers.

“Only the Brave” is CNE’s third feature film and the first film to get a wide release — across more than 2,500 theaters in the U.S. alone. Next year, “The Old Man and the Gun” will premiere next year, and three other projects are expected to go into production.

On TV, CNE has aired five shows, including “Last Chance U,” which Netflix recently picked up for a third season; “Vanity Fair Confidential,” which Investigation Discovery picked up for a fourth season; and “Most Expensivest,” which will premiere on Viceland in November. CNE this year has also sold three scripted pilots, including an untitled project with comedian Bobby Bowman for ABC.

A quartet of executives with extensive backgrounds in film and TV spearheads CNE’s film and TV efforts. Ostroff was the former president of Warner Bros.-owned broadcast network The CW. Jeremy Steckler, former Imagine Entertainment executive, oversees feature films; former ABC executive Jonathan Koa leads on scripted TV; and longtime talent agent Joe LaBracio was hired for unscripted TV programming. Including support staff, CNE counts eight full-time people in its film and TV group.

“It’s a lean group of people, but they have vast and deep experience [in Hollywood]; they speak the language,” Ostroff said. “For us, it’s intuitive because we come from that part of the business.”

CNE’s feature films will focus on adapting stories from Condé Nast publications. That won’t always be the case for TV. Some shows, especially unscripted ones, might be adapted from articles, while others will be based on ideas from writers and filmmakers CNE has relationships with. The project CNE is doing with ABC, for one, was related to a story idea Bobby Bowman had, Ostroff said.

One of the benefits for CNE as it ventures deeper into film is the model it’s set up to finance projects and make money. In film, CNE will finance the early development of a project — scriptwriting, attaching actors and directors — to help make it attractive enough to get financed by a studio or an independent financier. Somewhere between financing and producing the movie, the studio or financing partner will find a distributor.

CNE gets paid as a producer when a film gets funded and then has the potential to make more on the back end if the film is successful enough. This approach mitigates the costs of having to put down millions and millions of dollars to fully produce a movie.

In TV, CNE is a more straightforward production company and sometimes will partner with a TV studio to fund the shows upfront.

“I’m not sure if the traditional business will ever be bigger than the digital video business — which is quite substantial — but we’re just getting going in film and TV,” said Ostroff. “We charted a course, and now, after [six] years, the seeds are finally coming to fruition.”

Output: Six years after its inception, Condé Nast Entertainment (CNE), the video division of the global publisher, is set to turn a profit this year from producing TV shows and making film adaptations of magazine articles. The company, which has 65 film and TV projects in production, will continue to adapt films from its publications, according to CNE president Dawn Ostroff, and will finance development to get projects greenlit, but will also earn revenue as a producer and take a slice of any back-end profits. CNE's digital division started making a profit last year.


Instruction: create a high quality summary of the given input

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Emerson offers update to reservoir management simulation software
 Emerson Automation Solutions has launched the latest version of its reservoir management software suite - Roxar Tempest™ 8.1, designed to provide robust and efficient numerical solutions to support reservoir engineers in maximising field recovery.

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"Emerson expands reservoir simulation software "

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Output: Emerson Automation Solutions' newest iteration of its reservoir management software suite, Roxar Tempest 8.1, has been launched. "Tempest 8.1 brings reservoir engineers more tools to maximise the potential of their fields as well as enhanced field productivity, thanks to greater simulation performance, improved uncertainty analysis, and a truly integrated workflow from geosciences to production," said product development chief Kjetil Fagervik of Roxar. The Roxar software solution also includes a seismic to simulation package and its workflow integration allows for better decision making and reservoir management.


Instruction: create a high quality summary of the given input

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Lyft partners with city of Phoenix to offer rides to bus stops
 Dive Brief:

Phoenix has teamed up with Lyft to offer a 20% discount on 10 rides to customers who use the ride-share service to get to or from bus stops, according to a company blog post.

The 6-month pilot program is called "First Mile Last Mile" and includes trips between the customer's home and 500 bus stops. It could expand to other areas of the city if the pilot is deemed successful.

The measure is the latest in a string of transit-forward actions in Phoenix, which is in line with the city's 35-year "Transportation 2050" plan.

Dive Insight:

Phoenix voters approved moving forward with Transportation 2050 in 2015 and the initiative went into effect in January 2016. It committed Phoenix to investing in light rail construction, bus service improvements and street improvements such as bike lanes and new pavement. The initiative eventually will lead to adding 42 miles of light rail, which will triple the current system's miles.

Under Transportation 2050, bus service hours already have been extended and the frequency of buses has increased. That's credited with creating a 6% bump in bus ridership this year, at a time when most of the country is experiencing a downward trend, according to the American Public Transportation Association's most recent ridership report.

The partnership between Phoenix and Lyft goes against the often-held belief of animosity between public transit providers and ride-share services, which are blamed for stealing customers. The city recognized that the popularity of ride-sharing likely won't diminish anytime soon, so it chose to harness the trend instead of fighting it. Phoenix Mayor Greg Stanton has said that ride-sharing and public transportation both are parts of a modern and complete transit system, and they can complement each other and collaborate in a manner where both benefit.

Customers will benefit from the partnership because of the added convenience, especially those who do not live within walking or biking distance of a bus stop. They also win with cost, not just from the Lyft discount, but also because in many situations it might be cheaper to ride the bus for a portion of their trips instead of using a ride-share the entire time. The partnership adds to residents' multi-modal transportation options during a time when significant demand exists for flexible transportation, plus the exposure from the partnership's marketing campaign reminds residents of the many available forms of transportation that can be used for a single trip.

Output: Ride-hailing service Lyft has partnered with the city of Phoenix to offer its customers a 20% discount on 10 rides to or from bus stops. Named First Mile Last Mile, the six-month pilot programme is part of the city's Transportation 2050 initiative and aims to fuse ride-hailing services with public transport services to encourage those who do not live within walking distance of a bus stop to use the services.


Instruction: create a high quality summary of the given input

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Facebook could struggle to clean up political advertising
 Facebook faces an uphill battle in cleaning up political advertising on its platform.

Facebook is making adjustments to how political advertisers buy ads on its platform. It’ll still be hard for the social media giant to identify all of the political ads running through its system, though.

Facebook can detect a political ad in two main ways. One is by looking at the creative of the ad itself; the other is by looking at who it’s targeted to.

As for the ad creative, Facebook can scan the creative to detect if political content is present, but some political advertisers release hundreds of versions of the same ad within minutes, which allows them to A/B test their creative until they find the right combination of text and imagery that slips by Facebook’s filters.

Those advertisers also use their own data to create nuanced proxy audiences that make it difficult to identify the true intent of their messages. For instance, if fans of a particular TV show are likely to want criminal justice reform, an advertiser advocating against private prisons could target fans of that show to obfuscate the political purpose of the ad. Creating so many permutations of the same ad and using unique data to indirectly target political messages are tactics that ad buyers can use to cloak the partisanship of their data targeting and ad creative.

“Advertising platforms would have to make a considerable investment to catch all political ads,” said Mark Jablonowski, chief technology officer of DSPolitical, an ad-targeting firm used by liberal advertisers. “And they almost certainly won’t catch everything, no matter the spend.”

The pressure Facebook faces for letting a Russian troll farm buy ads on its platform is leading the social giant to change its approach to political advertising. Earlier this month, Facebook announced it would hire 1,000 people to review ads on its platform and require politically targeted ads to be manually reviewed.

U.S. senators also recently introduced a bill called the Honest Ads Act that would require digital platforms to make public information about political ads they host. Facebook declined an interview request for this story.

The other way Facebook can identify a political ad is by looking at who it’s targeted to. Depending on the type of data that political advertisers use to buy ads on Facebook, it can be hard for Facebook to detect that the ad is political, which would trigger a human review by Facebook, said John Randall, vp of digital at ad agency Craft, which specializes in advocacy campaigns for politically conservative groups.

The first type of data is Facebook’s own audience data. This data would be used if someone wanted to target users who, say, self-identified on Facebook as a Democrat or liked Facebook pages related to Hillary Clinton. It is easiest to identify politically targeted ads when this type of data is used, Randall said.

The second type of data is third-party data that an advertiser uploads into Facebook. This data can come from a political database like The Data Trust or a nonpolitical data aggregator like Acxiom that’s used for political targeting.

Spotting when this data is used for political purposes is harder than spotting when Facebook’s own data is used to target political ads. However, the more popular data aggregators are frequently used on Facebook, so the social platform has a lot of experience identifying which data sets belong to which providers and how that information might be used to target users.

The third type of data is first-party data from an advertiser itself that’s uploaded to Facebook, and this data is the hardest to spot political association, Randall said. Advertisers can combine their own surveys with voter file and census data to create unique data sets coded and labeled however the advertiser desires. The various types of data are not mutually exclusive to a campaign. For example, an advertiser using its own first-party data might combine its data with Facebook’s geographic data.

With a unique data set, an advertiser can politically target ads without being obvious about it, said Ken Strasma, CEO of HaystaqDNA, an analytics firm that has worked on campaigns for former President Barack Obama and Sen. Bernie Sanders. Rather than using Facebook’s data to simply target people who liked Hillary Clinton’s Facebook page or using third-party data to target young voters, who are more likely to vote for a Democrat, an advertiser trying to reach liberal voters can mine its proprietary data for patterns of particular policy positions aligning with nonpolitical criteria.

The data firm Deep Root Analytics helped the Trump campaign identity “NCIS” as being popular with anti-Obamacare voters and “The Walking Dead” as being popular with people who favor stricter immigration laws, for example. Political advertisers could theoretically combine their data with Facebook’s data to give the impression they are targeting “NCIS” fans, when in reality, they are subtly using a proxy audience to send a politically charged message.

At some point, the definition of political advertising becomes existential. Aside from using nonpolitical categories to target political messages, advertisers also use political criteria to target nonpolitical products, Strasma said. An example of this is that advertisers selling gold coins will target conservatives since they are more likely to mistrust the government and its currency.

Marketers say that adding human reviewers will indeed help Facebook flag more political ads. But beefing up the review process still won’t catch everything, and it could slow down how quickly marketers get their Facebook ads up and running.

“It’s a question of resources,” Strasma said. “If Facebook or other sites employ enough people and manually review every ad, they can catch most [political ads], but only at tremendous cost both in terms of salary and in terms of inconvenience to the advertisers who value quick turnaround.”

Output: Social media giant Facebook may struggle to identify and verify all political advertising on its site, according to media analysts. Users placing slanted material on the site are employing increasingly sophisticated methods, including aligning content with users' TV preferences by using both Facebook and third party data. Such content is difficult to spot, but introducing human verification into the process will slow down ads' delivery to the site. The US senate recently introduced the Honest Ads Act, which would force digital platforms to publicise information about political ads on their sites.


Instruction: create a high quality summary of the given input

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City of Portland invests in smart lighting
 Dive Brief:

The city council in Portland, ME voted unanimously last week to purchase its street lights from the local power company, according to the Portland Press Herald.

The investment allows the city to install more efficient LED lights. It also opens the door for installing smart technology, such as WiFi, to make the devices connected streetlights.

The $8.5 million purchase is expected to save Portland $10 million over 10 years, due to lower operating costs.

Dive Insight:

The project will roll out in two phases. During the first phase, more than 6,000 street lights will be retrofitted with LED lights, at a cost of $2.9 million. $1.8 million will go toward smart city projects such as installing Wi-Fi at 100 locations. Phase two involves $4 million worth of LED upgrades and Wi-Fi installations at more locations. Another idea being considered as part of the project is to install digital information kiosks in the downtown area.

Several municipalities near Portland have purchased their streetlights following a 2013 law change allowing them to do so. None have moved forward yet with installing Wi-Fi, though. The new LED lights in Portland could boost efficiency not just because of the LED bulbs — which can offer up to 80% savings in operating costs — but also through advanced technology to dim the lights or change their timing. Plus, owning the street lights reduces cities' costs because they no longer have to pay the power company a monthly rental charge. Portland estimates it will save up to $1 million each year once the streetlight project is paid for.

The street light project comes on the heels of Portland's announcement about launching a transportation marketing campaign to promote multimodal transportation. The city also was one of the seven in the running for a $50 million prize in the Smart City Challenge, although Columbus, OH eventually ended up winning. Portland continued forward with numerous plans for advancements, though, proving that being a smart city isn't about size, but rather committing to smart planning and technology.

Are you using smart streetlights? Take our survey»

Output: The city of Portland will spend $8.5m buying its street lighting from the local power company, aiming to save $10m over a decade. In the first part of a two-phase plan, energy-efficient LED bulbs will be installed, along with WiFi at 100 locations around the city. The second phase continues the LED and WiFi installation, but could also include the deployment of digital information kiosks. The scheme is part of Portland's drive to become a smart city, and follows the launch of a campaign to promote multimodal transportation.


Instruction: create a high quality summary of the given input

Input:
Redrow Steve Morgan retains second place in 2017 Wales Rich List
 Wales Business Stephen Farrell

Insider has revealed its 2017 Wales Rich List with a series of new entries cracking the top 50 and a change inside the top five. The total wealth of the richest people in Wales' business community has also grown by 10 per cent on last year to £8.13bn.

The exclusive research for the latest issue of Wales Business Insider has also revealed that a fortune of £42m is now required to make the top 50, up from £35m last year.

Sir Terry Matthews, owner of the Celtic Manor Resort near Newport and chairman of the Swansea Bay City Region, remains in top spot and is still Wales' only billionaire. This is despite his estimated fortune dipping slightly to £1.08bn from £1.17bn last year.

Redrow founder Steve Morgan has also retained his second position, despite handing over an 11.7 per cent stake in the housebuilder to his charitable foundation early in 2017.

The only change in the top five is Bernard Rees-Smith, the founder of medical diagnostics group RSR, who moves into fifth position. Dixondale, RSR's parent company, doubled profits to £25.5m in 2016 and is now valued at more than £300m.

Among the new entries for 2017 is Nigel Broadhurst, managing director of Deeside-headquartered food retailer Iceland. The company's turnover grew by 8.6 per cent in the three months to January 2017, helping it to its highest market share since 2001.

He joins Malcom Walker, Iceland's founder of chief executive, and finance director Tarsem Dhaliwal. Former joint managing director Nicholas Canning, who left the business earlier this month after 15 years, is another new entry.

The highest new entry this year is Andrew Walters in 31st, founder of listed vehicle tracking and fleet management systems provider Quartix. Walters, together with members of his family, owns more than 37 per cent of the business, which has a market value of £168.5m.

The 2017 Wales Rich List top 50 can be found in the November edition of Wales Business Insider, out now.

Output: Steve Morgan, founder of UK housebuilding firm Redrow, has held on to second place in the annual Wales Rich List, behind the country's only billionaire, Sir Terry Matthews. Morgan made headlines earlier this year after he sold an 11.7% stake in the company to his charitable foundation.


Instruction: create a high quality summary of the given input

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TalkTalk Broadband switchers fear losing phone numbers, study reveals
 Tuesday, Oct 24th, 2017 (12:01 am) - Score 632

A new survey of 1,110 ISPreview.co.uk readers, which was conducted between 5th Sept and 19th October 2017, reveals that 31.6% of respondents lost their number while migrating to a new ISP and 49.4% said that the fear of losing their number had discouraged them from future switching.

The loss of a phone number during migration, especially if you’ve had it for many years, is hugely disruptive and can require a large amount of administration in order to correctly update all of your contacts. Suffice to say that most people would prefer to keep their number.

Ofcom’s General Condition 18 (“Number Portability“) rule imposes an obligation upon ISPs to offer number portability to their subscribers and to provide portability to other communications providers. Unfortunately such rules don’t cover every eventuality and problems can still occur.

Sometimes switching ISP means losing your current landline phone number. Does this discourage you from switching?

Yes – 49.4%

No – 47.3%

Unsure – 3.2% Have you ever lost your previous landline phone number while switching broadband ISP?

No – 61.4%

Yes – 31.6%

Unsure – 6.9% Do you think Ofcom is doing enough to improve number portability between providers?

No – 59.3%

Don’t care, I only use Mobile or VoIP! – 28.3%

Yes – 12.2%

Phone numbers are most often lost when moving into a new home (i.e. you have to get a new line and number installed), which typically occurs because you’ve either shifted to a completely different area code, never had a fixed line phone number before or you’re still in the same region but are being covered by a different telephone exchange.

We’ve also seen various examples where people have lost their number while moving between unbundled (e.g. TalkTalk) and / or BT based providers, even though they’re still in the same house and on the same overall Openreach network. This tends to occur due to a combination of poor communication between ISPs and / or the lack of an effective management system for handling such changes between providers.

For example, we’ve seen a few complaints where people have attempted to switch their phone service from TalkTalk (unbundled) to BT and run into problems. In some cases BT would complains that TalkTalk won’t release the number, while TalkTalk will say that they expect a written request from BT and yet BT allegedly claimed not to do this. Similar problems have also occurred when moving between other providers.

The good news is that more people are now viewing their Mobile number as a primary contact or using VoIP in order to maintain greater control, which affords the end use more flexibility due to not being so reliant on a specific fixed line number. Standalone broadband services are also set to become more common over the next few years, which could in theory help to make future switching even easier.

One caveat of using VoIP is that if you intend to switch your fixed line number to a related provider then the process can take awhile to complete (2-4 weeks according to Vonage), which might discourage some people from attempting it. In general, Ofcom could probably still do more to ensure that numbers are not lost unnecessarily.

Meanwhile this month’s new survey asks whether you currently have a “superfast broadband” connection and if the new ultrafast G.fast services will attract you? Vote Here.

NOTE: ISPreview.co.uk surveys are likely to receive a higher proportion of tech-savvy respondents than most, although the majority of our visitors are normal consumers (i.e. they come to this site for help and assistance with basic broadband problems / questions or when hunting for a new ISP).

Output: Almost one-third of respondents feared losing their phone numbers when changing internet service providers (ISPs), according to a survey by ISPreview.co.uk. The survey also found that 49% said the fear of not keeping their number put them off switching. In addition, 59% of 1,110 respondents did not believe Ofcom had done enough to improve number portability between ISPs.


Instruction: create a high quality summary of the given input

Input:
Australian government to ease fintech regulations
 Source: Australian Government

The Turnbull Government has today released exposure draft legislation and regulations to create an enhanced regulatory sandbox to support innovation in financial services.

This proposed legislative package will be a game changer for competition in the financial services sector and continues the Turnbull Government's strong support of Australian FinTech which has helped Australia become the second largest alternative finance market in the Asia-Pacific.

As announced in the 2017-18 Budget, the FinTech regulatory sandbox will allow a broad scope of activities to be tested without the need to meet all the existing licensing requirements of the Australian Securities and Investments Commission. The enhanced regulatory sandbox will help firms overcome the initial regulatory burden and costs of licensing that may otherwise hinder innovative offerings.

This is an exciting opportunity that will further cement Australia's position as a leading FinTech hub in the Asia‑Pacific.

Under the Government's legislative framework, firms can test a wider range of new and innovative FinTech products and services, including:

providing holistic financial advice in relation to superannuation, life insurance and domestic and international securities;

issuing and facilitating consumer credit;

issuing non-cash payment products; and

providing a crowd-funding service.

The 24‑month testing timeframe will improve firms' ability to evaluate the commercial viability of new concepts, promoting greater competition and delivering more choice for Australian consumers.

Firms will need to adhere to robust consumer protections and disclosure requirements including responsible lending obligations, best interests duty, and the need for adequate compensation and dispute resolution arrangements.

The exposure drafts and explanatory material are available on the Treasury website.

Consultation on the draft legislation (and explanatory memorandum) is open until 3 November 2017, and on the draft regulations (and explanatory statement) until 1 December 2017.

Output: The Australian government has released a proposed legislative package enabling the creation of a two-year fintech sandbox, as the country seeks to cement its position as the Asia-Pacific's second-largest alternative finance market. Under the exposure draft legislation and regulations, which are open for consultation until 3 November and 1 December respectively, Australian fintech firms could test a range of innovative solutions. Although they would have to abide by disclosure requirements and consumer protections, participating companies would not face licensing costs or initial regulatory controls.


Instruction: create a high quality summary of the given input

Input:
Global warming could cost the US $35bn per year: GAO
 Climate change is happening now. It is already impacting our daily lives. It is also impacting the United States economy.

Action to address climate change is compatible and essential for economic growth. It also creates jobs.

However, the United States Federal Government under the Trump Administration decided to increase economic growth without climate action. In addition, against the world’s commitment to fight climate change, the United States has begun the process of withdrawing from the Paris Agreement. These decisions were based on the claim that action to tackle climate change is against America’s domestic interests. As a result, energy production in the United States will continue to be primarily generated by burning fossil fuels –the major driver of the observed changes in climate.

The impacts of climate change affect many sectors, including agriculture, water, human health and ecosystems, among others. Although some of these impacts are positive, most are negative and affect lives and livelihoods. Using different indicators and assumptions, numerous studies have assessed the impacts of climate change in the United States. The majority of these assessments use the end of this century as a timeframe for the analysis.

This report specifically focuses on economic losses caused by extreme and frequent weather events influenced by human-induced climate change and on health costs due to air pollution exposure caused by fossil fuel energy production. It is thus a partial assessment of the economic losses and costs of human-induced climate change and fossil fuel use on the United States economy.

Climate is the average weather –temperature, precipitation and wind– over a period of time. Changes in climate are usually measured over a 30 year period, as defined by the World Meteorological Organization. Thus, this report analyzes extreme weather events over three decades: 1980s (1980-1989), 1990s (1990-1999) and the last decade (2007-2016). Based on these past trends, a projection for the next decade is estimated. It also presents the opportunities to boost economic growth and job creation while taking climate action.

Sources used for the analysis presented in this report include the National Oceanic and Atmospheric Administration, the American Meteorological Society, the National Academy of Sciences of the United States of America, the Centers for Disease Control and Prevention, the American Lung Association, the U.S. Department of Commerce, the U.S. Department of Agriculture, the U.S. Energy Information Administration, the U.S. Department of Energy, the U.S. Department of Transportation, the U.S. Census Bureau and the Second Biennial Report of the United States of America under the United Nations Framework Convention on Climate Change. Peer-reviewed research studies published in prestigious journals were used as sources for health costs.

Economic losses, health costs and economic growth figures are presented in 2017 dollars. To harmonize and compare, all figures were adjusted using the latest Consumer Price Index.

September, 2017

Output: The US must develop a plan to combat climate change, or face severe economic consequences, according to a report by the Government Accountability Office. The report discloses that the US government spent over $350bn on natural disasters and flood and crop insurance over the past decade. An additional $300bn will be added to that total by this year’s hurricanes and wildfires. The study warns that costs will rise to $35bn per year by mid-century if global emissions do not fall. Non-profit the Universal Ecological Fund has warned that such costs could be closer to $360bn annually within the decade.


Instruction: create a high quality summary of the given input

Input:
Global warming could cost the US $35bn per year: GAO
 President Trump might think that global warming is a hoax created by the Chinese, but the Government Accountability Office (GAO), Congress’s nonpartisan auditing arm, is urging the administration to craft a plan to confront climate change or else it will have to deal with its massive economic consequences.

According to a new report released by the GAO, the U.S. government has already spent more than $350 billion over the past decade on dealing with natural disasters and losses from flood and crop insurance. The tally does not even include the economic toll from this year’s horrific West Coast fires and successive hurricanes, which is estimated to cost at least $300 billion.

Costs will also soar—as much as $35 billion per year by mid-century—if global emission rates are not reduced, the study warns.

“The federal government has not undertaken strategic government-wide planning to manage climate risks by using information on the potential economic effects of climate change to identify significant risks and craft appropriate federal responses,” the study states. “By using such information, the federal government could take the initial step in establishing government-wide priorities to manage such risks.”

The report, which features interviews with more than two dozen scientific and economic experts and 30 studies, was requested by Senators Maria Cantwell (D-WA) and Susan Collins (R-ME).

“The Government Accountability Office—if you will, the chief bean counter—is basically telling us that this is costing us a lot of money,” Cantwell told the New York Times. “We need to understand that as stewards of the taxpayer that climate is a fiscal issue, and the fact that it’s having this big a fiscal impact on our federal budget needs to be dealt with.”

The Senators hope that the study will prompt Congress and the administration to move towards a bipartisan solution to fight the effects of a warming world.

“My hope is the administration will take a look at this report and realize there is an economic impact here that is significant,” Collins told the Times. “We simply cannot afford the billions of dollars in additional funding that’s going to be needed if we do not take into account the consequences of climate change.”

Trump, however, has notoriously pulled the U.S. out of the Paris climate agreement and rolled back several Obama-era environmental regulations designed to address climate change, including the repeal of the Clean Power Plan. The president’s EPA Administrator Scott Pruitt has close links to the fossil fuel industry and once said that carbon dioxide is not the primary driver of global warming.

Robert N. Stavins, an economist at Harvard University, cast doubt the study would convince the government to act.

“The GAO study is conservative, it’s not alarmist, it’s realistic and balanced and they go out of their way to point out all of the uncertainties involved,” Stavins told the Times. “I don’t see any likelihood it’s going to be taken seriously.”

Indeed, the price tag from the GAO’s study is drastically lower than estimates from other recent reports. The non-profit Universal Ecological Fund found that extreme weather and public health issues related to burning fossil fuels could cost the U.S. up to $360 billion annually—nearly half of annual U.S. economic growth—within the next ten years.

Output: The US must develop a plan to combat climate change, or face severe economic consequences, according to a report by the Government Accountability Office. The report discloses that the US government spent over $350bn on natural disasters and flood and crop insurance over the past decade. An additional $300bn will be added to that total by this year’s hurricanes and wildfires. The study warns that costs will rise to $35bn per year by mid-century if global emissions do not fall. Non-profit the Universal Ecological Fund has warned that such costs could be closer to $360bn annually within the decade.


Instruction: create a high quality summary of the given input

Input:
Major global companies improving environmental record: CDP
 Two years ago, the Paris Agreement fired the gun in the race to a low-carbon economy.

Picking up the pace – the second annual edition in CDP’s Tracking progress on corporate climate action series – reveals how over 1,800 companies are responding to the historic Paris Agreement, signed by nearly 200 nations, and the recommendations of the Task Force for Climate-related Financial Disclosure.

Last year, we started tracking the climate action of a representative sample of 1,829 corporates, chosen for their significance in terms of market capitalization and environmental impact. By doing this we can consistently track progress by the companies of the implementation of the Paris Agreement. We found that many companies had begun the transition to a low-carbon world, but their actions were lacking long-term vision and ambition. This year’s follow-up analysis shows how global business is already starting to pick up the pace.

It confirms the low-carbon transition is happening, now, and it’s being driven by companies around the world that realize climate action represents a huge opportunity not to be missed.

Mapping out the transition

Firstly, this year we are seeing that more companies are setting climate targets. Those targets are extending further in time – showing companies are planning for a low-carbon future. And most importantly, there is a growing understanding that corporate targets and action plans need to be in line with the emissions reductions that are needed to prevent dangerous climate change.

Fourteen per cent of responding companies in our sample have now joined the Science Based Targets initiative, thereby committing to setting emissions reduction targets aligned with the level of decarbonization required to keep global temperature increase below 2 degrees Celsius and deliver on the Paris Agreement. That’s an increase from 94 to 151 companies in the last year, including AkzoNobel, EDP and Unilever. An additional 30% – that’s 317 companies – anticipate setting a science-based target within two years.

This is an important shift for companies, from doing what they think they can easily manage, to stepping up to do what’s needed. This is responsible – and smart – business in the age of climate change.

Take the Portuguese energy company EDP, for example, which joined the initiative earlier this year. EDP has committed to reduce scope 1 and 2 emissions from electricity production by 55% per TWh by 2030, from 2015 levels, and to cut absolute scope 3 emissions by 25% over the same period. The company says that adopting a science-based target gives it a competitive advantage by clarifying its position to investors and key stakeholders, who expect companies – particularly those that are large emitters – to clearly elaborate how they are positioned for the low-carbon transition.

Thanks to this rising ambition, our sample is getting ever closer to being on track for a climate-safe world.

Achieving their current targets would take the companies in our sample 31% of the way to being consistent with a 2 degrees pathway. That’s a notable improvement on the 25% reported in 2016.

We’re not there yet, but these global companies are closing the gap – making significant headway in just one year. That is progress to be celebrated. And it bodes well for the kind of acceleration that’s required to bend the curve.

Innovating the next economy

As companies work to meet their goals, they are turning to innovative ways of doing business. Sweden’s first zero-energy neighbourhood, Solallén, is a perfect example of climate-smart innovation. Developed by multinational construction company Skanska AB, it is designed to generate more energy than it uses, saving both carbon and energy costs.

Since last year, there’s been a 20% increase in companies from our sample offering low-carbon products and services. From Nissan selling electric cars, to San Diego working with GE Current, AT&T and Intel to upgrade 25% of the city’s streetlamps to adaptive LEDs with data-collecting sensors, companies are capitalizing on the opportunities from the transition.

In fact, 75% of companies in the sample now say their products and services help others to reduce emissions – whether it’s from selling greener products or providing low-energy buildings. That’s up from 64% last year.

More and more companies are embracing renewable energy. The number with a renewable energy consumption target has increased by 23% in the last year, with companies like BT and Unilever committed to sourcing 100% renewable energy by 2030 as part of the RE100 initiative.

One of the things driving this shift in energy procurement is carbon pricing. While carbon pricing at the national policy level is on the horizon or already underway in many places, a growing number of corporates are storming ahead and setting their own internal price on carbon.

For example, AkzoNobel has an internal carbon price set at the level needed to drive the global transition to zero-net emissions. At a significant €50/tonne, the price is used to assess the company’s investment decisions. And it’s working: the carbon price has forced a rethink of proposed carbon-intensive investments.

As explored in our recent Putting a price on carbon report, this is a key lever for change. It internalizes the hidden cost of carbon pollution, making it show up on the balance sheet. This corrects a key market failure and naturally drives climate action.

Rising to the top

Underpinning this activity is enhanced accountability. Climate change is now firmly on the boardroom agenda. Nearly all companies in our sample – a huge 98% – have responsibility for climate action at board- or senior management-level. 90% have financial incentives tied to corporate climate progress.

And this board-level engagement is likely being driven by more and more investors asserting that climate risk is now a matter of mainstream fiscal responsibility.

“The burden of proof to explain why climate risk isn’t an issue has shifted to companies” explains Aviva Investors’ chief responsible investment officer, Steve Waygood. “The new norm is that companies should be considering climate risk at the board level”.

All this means we are on the cusp of a tipping point that is beginning to mainstream environmental action.

The transition is picking up pace. Winners and losers are already emerging, with the 112 companies on our 2017 Climate A List leading the charge. CDP’s vision – of a thriving economy that works for people and planet – is well within reach. But while many of the companies in this sample are acting ambitiously on climate, there are many that risk being left behind. To close the emissions gap and peak emissions by 2020, we need to move even faster. Ongoing measurement, transparency and accountability will be vital to tracking progress.

Now, it’s time to accelerate.

Output: The number of companies adopting targets in line with the Paris Climate Accord’s goal of limiting global warming to 2 degrees Celsius is increasing, according to a survey by CDP. The survey, published on Tuesday, analysed 1,073 business representing 12% of global emissions. Of those companies surveyed, almost 90% have set carbon reduction targets. Around 14%, including Unilever and BT, have made reductions in line with the Paris agreement. A further 317 firms, or 30% of respondents, aim to introduce science-based targets within the next two years.


Instruction: create a high quality summary of the given input

Input:
Eradicating poverty could conflict with climate goals
 Relationship to earlier studies

We use the consumption-based approach to carbon accounting. This is a different approach from earlier papers, say for example, by Chakravarty et al.71 and Chakravarty and Tavoni13 as our analysis is based on supply chain carbon emissions that go beyond household direct energy consumption, i.e., accounting for the carbon emitted during the production of consumption items and services, which are then allocated to the final consumer, and are based on very detailed information on income distribution and consumption patterns. This latter point also distinguishes our paper from Chancel and Piketty26 who use GTAP multi-regional IO (MRIO) for data on countries incomes and emissions. But then, in order to move from country average emissions to emissions of different individual (income) groups within countries they allocate CO 2 to different income quantiles using country-year average decile income/consumption data from the World Bank. This is a top-down approach and does not use the detailed consumer expenditure surveys at the household level for different income groups as proposed here. The only paper we are aware of that addresses within country inequality at the global level (Dennig et al.37) uses a modified version of RICE one of the standard integrated assessment models (IAM), which is based on 12 regions and World Bank data on national income, not detailed consumption surveys. Most IAMs are based on very large regional aggregation and do usually not account for income inequality between countries. For example, MESSAGE–MACRO focuses on detailed complex “bottom-up” energy supply sectors but still uses 11 world regions and does not have equivalent micro detailed consumption at different income levels and developing countries and is not set up to address poverty or inequality issues. The same holds for iPETS which has 31 regions, however very aggregated when it comes to poorer countries (for example sub-Saharan Africa is one region). In contrast, we use 90 developing countries provided by the World Bank’s Global Consumption Database and representative developed countries, including the US, 27 EU countries, Australia, and Japan (see below for more detail). That is not to discredit in any way the function and importance of the IAMs but they are built for other purposes and each of these approaches has its own strengths and weaknesses and each provides a different perspective on the policy options available to meet climate change targets. Extreme poverty is typically defined in terms of satisfying immediate basic needs such as food and shelter, needed for long-term physical well-being. Thus, we believe that our approach using detailed household expenditure data, with great detail for a large number of developing countries, contributes a different and useful perspective.

Carbon footprints and consumer expenditure surveys

We use multi-regional input-output (MRIO) analysis to compute household carbon footprints for different income groups for 189 countries. The carbon footprint includes direct emissions associated with a household’s activities such as heating, driving and using electricity as well as indirect emissions associated with the production of goods and services a household consumes24, 25 as well as assumed associated shares of required investments and government expenditure to support increase in production capacity. The consumption patterns of different household groups in 90 developing countries are provided by the World Bank’s Global Consumption Database21 and households in developed countries are based on national consumer expenditure surveys reported by the respective national statistical offices. The global MRIO table is collected from the Eora database38. Eora is a multi-region IO database that provides a time series of high-resolution IO tables with matching environmental and social satellite accounts for 186 countries. This study focuses on 2010 to be consistent with the World Bank’s Global Consumption Database.

In the World Bank’s Global Consumption Database, households in developing countries are categorized in four consumption segments: lowest, low, middle, and higher consumption groups. They are based on global income distribution data, which rank the global population by income per capita, which we use and scale up by actual global population shares for each income category. The lowest consumption segment (below $2.97 per capita a day) corresponds to the bottom half of the global population; the low consumption segment (between $2.97 and $8.44 per capita a day) to the 51th–75th percentiles; the middle consumption segment (between $8.44 and $23.03 per capita a day) to the 76th–90th percentiles; and the higher consumption segment (above $23.03 per capita a day) to the 91st percentile and above (Supplementary Fig. 1). The monetary values are in PPP39. Purchasing power parities tells us how many dollars are needed to buy a dollar’s worth of goods in a country as compared to the United States. In other words, PPP estimates the amount of adjustment needed of the exchange rate between countries in order for the exchange to be equivalent to each currency’s purchasing power.

The first of the UN SDGs, which we are exploring in this study, is to move people out of extreme poverty by 2030, defined as <$1.90 PPP per day. However, the World Bank global consumption database (WBGCD) provides only the consumption patterns for the group with consumption of <$2.97 PPP per day. To estimate the carbon emissions per capita associated with consumption for the people spending <$1.90 PPP per day, we first select the poorest countries with an average expenditure of <$1.90 PPP per day or $456 PPP per year and use their average per capita consumption data as representative of the poorest income category (<$1.90 PPP per day) at the global level.

While the WBGCD represents the consumption patterns of the low income categories it is less representative for consumption patterns of higher income categories which represents consumers from developed countries. Thus in addition to the consumer expenditure surveys for 90 developing countries included in the World Bank’s global consumption database (http://datatopics.worldbank.org/consumption/) we included consumer expenditure surveys from the US22, the EU23, Australia24, and Japan25. Population data for different consumer groups were collected from the World Bank Povcalnet4. According to the PovcalNet database, developed countries only have a share of about 1% of the global population in the <$8.44 consumption groups. In terms of global middle income ($8.44–23.03), developed countries’ share in this group accounts for about 19%, while their share of the global high consumer group (>$23.03) is 89%. Therefore, we use the World Bank’s 90 developing countries’ consumption data (accounting for 89% of total population in developing countries) to estimate per capita carbon footprint for the extreme poor (<$1.9 PPP per day), $1.9–2.97 PPP per day, and $2.97–8.44 PPP per day. To calculate the footprint for the $8.44–23.03 group, we split the countries into two groups. We use the consumption expenditure data of this consumer group of the 90 developing countries in the World Bank’s consumption database (representing 72% of the global total in that category; developing countries account for 81%) and consumer expenditure surveys from the US, Japan, Australia and EU to represent consumption patterns in developed countries (representing 16% of the global total in that category; developed countries account for 19% in this category); their combined share is 87% of the global total in that category. For the highest consumer group (>$23.03) we used the average expenditure for people falling in that consumer category from the 90 developing countries (representing 8% of the global total in that category), the EU, Japan, Australia and the US, which represent about 73% of the global population in that category.

The multi-regional input–output approach

In a MRIO framework, different regions are connected through inter-regional trade. The technical coefficient sub-matrix A rs consists of \(\left\{ {a_{ij}^{rs}} \right\}\) is given by \(a_{ij}^{rs} = t_{ij}^{rs}/x_j^s\), in which \(t_{ij}^{rs}\) represents the inter-sector monetary flows from sector i in region r to sector j in region s; x j s is the total output of sector j in region s. The final demand matrix is \(\left\{ {y_i^{rs}} \right\}\), where \(y_i^{rs}\) is the final demand of region s for goods of sector i from region r. Using matrix notation and dropping the subscripts, we have

$${\bf{A}} = \left[ {\begin{array}{*{20}{c}} {{{\bf{A}}^{{\bf{11}}}}} & {{{\bf{A}}^{{\bf{1}}2}}} & \cdots & {{{\bf{A}}^{{\bf{1n}}}}} \\ {{{\bf{A}}^{{\bf{21}}}}} & {{{\bf{A}}^{{\bf{22}}}}} & \cdots & {{{\bf{A}}^{{\bf{2n}}}}} \\ \vdots & \vdots & \ddots & \vdots \\ {{{\bf{A}}^{{\bf{n1}}}}} & {{{\bf{A}}^{{\bf{n2}}}}} & \cdots & {{{\bf{A}}^{{\bf{nn}}}}} \end{array}} \right];{\bf{Y}}=\left[ {\begin{array}{*{20}{c}} {{\sum{\bf{y}}^{\bf{1r}}}} \\ {{\sum{\bf{y}}^{\bf{2r}}}} \\ \vdots \\ {{\sum{\bf{y}}^{\bf{nr}}}} \end{array}} \right];{\bf{x}} = \left[ {\begin{array}{*{20}{c}} {{{\bf{x}}^{\bf{1}}}} \\ {{{\bf{x}}^{\bf{2}}}} \\ \vdots \\ {{{\bf{x}}^{\bf{n}}}} \end{array}} \right]$$

Consequently, the MRIO framework can be written as:

$${\bf{x}}{\rm{ = }}{\left( {{\rm{I}} - {\bf{A}}} \right)^{ - 1}}{\bf{y}}$$ (1)

where x is a colum vector of sectoral total output for all countries; (I-A)–1 is the Leontief inverse matrix which captures both direct and indirect economic inputs to satisfy one unit of final demand in monetary value; I is the identity matrix with ones on the main diagonal and zeros everywhere else; y is a column vector of sectoral total final demand for all countries.

To calculate the consumption-based CO 2 -e emissions, we extend the MRIO table with a vector of sectoral CO 2 -e emission coefficients for all regions, k:

$${\bf{k}} = \left[ {\begin{array}{*{20}{c}} {{{\bf{k}}_1}} & {\begin{array}{*{20}{c}} {{{\bf{k}}_2}} & \cdots \end{array}} & {{{\bf{k}}_{\bf{n}}}} \end{array}} \right]$$

Thus, the total consumption-based CO 2 -e emissions for all regions can be calculated by:

$${\bf{C}}{{\bf{O}}_{\bf{2}}}{\hbox {-}}{\bf{e}} = {\bf{k}}{\left( {{\bf{I}} - {\bf{A}}} \right)^{ - 1}}{\bf{Y}} + {\bf{H}}{{\bf{H}}_{\bf{C}}}$$ (2)

where CO 2 -e is a row vector of the total CO 2 -e emissions (both supply chain emissions and household direct emissions) associated with total final consumption (Y), sum of household consumption, government expenditure and stock change and investment, in all countries; k is a row vector of CO 2 -e emissions per unit of economic output for all economic sectors in all regions. k (I-A) –1 Y, a row vector, captures supply chain emissions of final demand of goods and services in different countries; HH C is a row vector of household direct emissions of all regions, e.g., driving and house heating;

Household direct emissions for each consumption group in different countries are estimated based on their household fuel consumption from the consumer expenditure survey data.

Matching consumption survey to MRIO household consumption

In the WBGCD21, and the global multi-regional IO database38 have been developed to enable global analyses and are uniform across countries. To match the consumption categories provided by the Global Consumption Database with Eora economic sectors we follow a well-established approach (e.g., refs. 40, 41). We first assign consumption items from the WBGCD to different IO sectors and then scale the consumption survey data for each sector by four income groups to match the total household consumption of each sector from the global MRIO table (see Bridge Matrix in Supplementary Data). This method assumes that national consumption data is more accurate than the consumption survey data in terms of total consumption of each good or service. However, the survey date provides useful information about the distribution of goods and services to different income groups.

In the WBGCD database, all consumption items are categorized according to the International Comparison Program (ICP) classification, equivalent to the international Classification of Individual Consumption According to Purpose (COICOP). To estimate the carbon footprints of different consumption groups, we first map the ICP classification of consumption items to aggregate Eora IO sectors. Three situations can occur:

One ICP category in the WBGCD corresponds to one Eora sector. In some cases there is a perfect match between an ICP category and an Eora sector. The mapping is straightforward.

Multiple ICP categories correspond to one Eora sector. For example, in the ICP category, “Processed fish and seafood”, “Cheese, butter and margarine”, “Other edible oil and fats” can only fit to Eora sector Food & Beverages. Given the more detailed ICP classifications than the Eora sector, this allocation is the most frequent case in the matching process. Mapping is also straightforward in this case.

One ICP category in the WBGCD corresponds to more than one Eora sector. There are some cases that one consumption item category may be produced from multiple economic sectors. For example, some food consumption categories can either be sold directly from the farm and thus would be linked to Eora sector “Agriculture” or have been processed and thus need to be linked to Eora sector “Food & Beverages”. However, there is no good reference to split the aggregate consumption categories, such as “Fresh or Chilled Vegetables Other than Potatoes”, into “Agriculture” and “Food &Beverages’ sectors”. And, the allocation of an aggregate consumption category might vary from country to country. Most studies ignore this problem42 and just equally distribute the aggregate category in consumption (as, e.g., done by the World Bank’s Global Consumption Database) or when linking environmental accounts to IO accounts (e.g., ref. 43), or numerous IO studies linking consumer expenditure survey to IO categories (e.g., refs. 41, 44). We followed this practice for this study but also added an uncertainty analysis using an allocation approach based on different possible “extreme” bridging matrices. We select the possible IO sectors that can be linked to the ICP sectors. For the maximum value, we assign the ICP category to the sector with the highest emissions multiplier, for the lowest possible value, we assign the ICP category to the sector with the lowest emission multiplier. We then take these extreme or maximum possible deviations from the allocation we had chosen and calculate the deviation for each household group and show the range through error bars for each household category (Supplementary Fig. 2). Our uncertainty analysis shows that re-allocation of the consumption categories that may fall into multiple economic sectors has a relatively small impact on per capita footprints of different household groups. The uncertainty range of the per capita CF for all household groups is <2% between the max and the min and even less of an issue for our scenarios only involving the lowest two income categories.

Other final demand sectors by consumer groups

In addition to household consumption we also include other two final demand sectors, government expenditure and capital formation, to accommodate the necessary expansion of production capacity required to produce the increase in household demand. We allocate capital formation and government expenditure column vectors from EORA MRIO database to the four consumer groups based on the share of household consumption by different consumer groups in the total household consumption. Equation (3) was used for disaggregation of capital formation and government expenditure.

$${\bf{Ca}}{{\bf{p}}_{{\bf{Disagg}}}} = {\bf{diag}}\left( {{\bf{Cap}}} \right){\rm{*}}{\bf{H}}{{\bf{H}}_{{\bf{share}}}}$$ (3)

where Cap Disagg is disaggregated capital formation by four consumer groups; Cap is a vector of capital formation by sectors; and diag(Cap) denotes a diagonal matrix with the elements of vector CAP on the main diagonal. HH share is a matrix showing the shares of consumption by different consumer groups in different sectors.

This method assumes that the higher the consumption for a certain product the higher the required capital formation in that sector. Lacking better information, we make the same assumption for government expenditure. For example, we allocate the government expenditure column to different consumer groups based on their consumption of other services from the consumer expenditure survey data.

Scenario analysis

In this study, we set up two scenarios for future additional carbon emissions due to moving poor people out of poverty by 2030 but these emissions are then continued until 2100 to be consistent with IPCC climate change projections. Scenario 1: lifting all people spending <$1.90 PPP per day (i.e., 840 million people45) to a higher consumption group spending between $1.90 and $2.97 PPP per day by 2030, equally spread over the years, with an average of 56 million people moving out of poverty per year. Scenario 2: lifting all people with a per capita income of <$2.97 PPP per day to a higher expenditure group spending between $2.97 per day and $8.44 per day by 2030 with an equal share of people annually moving to the next higher consumption group. We also incorporate population growth into the model. As population growth data for different consumption groups in different countries is not available, we use the UN population growth projection3 for this study. Then, we use population growth rates by different country classifications (low income, lower middle income, upper middle income, and high income) to represent different growth rates in different consumption groups. For instance, we use the average growth rate in low income countries (i.e., <$1045 per capita per year) for the <$1.90 and $1.90–2.97 PPP consumption groups, while we use the average growth rate in lower middle countries (i.e., $1046–4125 per capita per year) to represent the growth rate for the $2.97–8.44 consumption group. In terms of changing fertility rates associated with higher incomes we assume that people moving up to a higher consumption group will have the same fertility rates as their new income peers, otherwise we strictly stick with the UN predictions.

Since long-term climate impacts depend on cumulative carbon emission we add the additional emissions needed to achieve the SDGs of moving people out of extreme poverty to a baseline emission pathway. (By additional emissions, we mean the higher emissions based on the new expenditure group minus previous emissions in the lower expenditure group.) As baseline, we use one of the GHG emission trajectories, known as Representative Concentration Pathways (RCPs), adopted by the IPCC for its fifth Assessment Report (AR5) in 201446. RCPs are concerned with GHG concentration trajectories but the database provides, as a supplement, emission trajectories calculated as inverse emissions, i.e., implied emissions corresponding to the scenario concentrations, using the MAGICC model (see below). These standardized scenarios emphasize not only the long-term emission stabilization level but also the trajectory that leads to that outcome. We use the scenario that is consistent with limiting temperature changes to below 2 °C above pre-industrial level, i.e., RCP2.6. The RCP2.6 (now referred to as RCP3PD in the database, where “PD” stands for Peak and Decline and 3 refer to radiative forcing, in watts per square meter units, predicted by the year 2100) emission scenario assumes that global annual GHG emissions peak sometimes before 2020 and decline substantially afterwards. Other scenarios include RCP4.5, RCP6, and RCP8.5. These are all plausible pathways. We chose RCP2.6 here because the research question we are addressing is whether meeting the SDGs can be achieved without affecting the climate goal47.

RCP scenario data contain reference GHG emissions. However, the database does not report socio-economic variables underlying each scenario. We present un-abated emissions. To convert emissions scenarios into global-mean temperatures we used MAGICC version 648. MAGICC is essentially a reduced-complexity model used in many scientific publications and integrated models. It is also often used by the IPCC, for instance, to facilitate integrated model comparisons. MAGICC integrates a set of simple models linking emissions to concentrations to global radiative forcing and to global changes in temperature and sea-level. For more details see refs. 49, 50. 50 and 66% confidence ranges are obtained in MAGICC by running the model 600 times using a slightly altered set of climatic parameters that are based on historical observations. Details of this approach are available in51.

Limitations

The United Nations52 in a resolution adopted by the Assemble set 17 goals focusing on poverty alleviation, hunger, inequality and inclusion, gender, education, access to water and sanitation. Many of these so-called UN SDGs are related to income but the selected examples already show that poverty goes beyond simply income. This multi-dimensionality of poverty is well reflected in the literature recognizing that income measure alone are a poor representation of poverty9, 10. Albeit true, many of these ailments are linked to income especially at the lowest level of consumption where people spend most of their money on basic consumption items such as food, clothing and shelter (see also Supplementary Fig. 1 based on consumer expenditure patterns of the World Bank (WP)’s poverty database). In this study we focus explicitly on the first SDG and look at the implications of moving people to a higher expenditure group.

The WB database is based on consumer expenditure surveys for 90 developing countries and four expenditure categories and here supplemented by consumer expenditure surveys from developed countries. In our scenarios we move people from one expenditure category to the next (crossing the poverty line) assuming the consumption patterns of the higher expenditure group. The carbon emissions are based on greenhouse gas emissions as represented in the global MRIO database captured through market exchange. We account for carbon emissions associated with burning fuels such as char coal, crop residues and other biomass for cooking and heating when captured through market transactions in the consumer expenditure surveys. These fuel sources can be a substantial part of the livelihoods (e.g., ref. 53). As incomes increase, biomass does not simple get replaced by other fuels but households tend to use a wide mix of fuels in their fuel transitions54, we capture those transitions only when reflected in the consumer surveys. If rural poor replace biomass with paid-for energy than we ignore the potential positive impact on reduced deforestation. Similarly, we do not deal with other land use related carbon emissions associated with subsistence agriculture. At these low levels of income any additional income would not replace these forms of livelihood income but rather would help diversify their livelihoods55.

In this study we do not account for land use related emissions. The literature on how poverty alleviation would change land use at a global level is quite inconclusive and really beyond what we could hope to achieve in this paper. Most of the studies that link land use to consumption patterns are at the regional scale56 or at best at the national level57, and frequently do not explicitly account for differences in income. The few global level studies show that land consumption seem to increase with higher income58.

A somewhat related problem is the different impacts of meat consumption versus other food intake, which have quite different environmental impacts in terms of land use, but are more relevant for our study in terms of methane emissions. While we do account for these differences in terms of emissions, we do not do this in the best possible way as meat consumption is subsumed as part of consumption of agricultural products. Higher income people would pay higher prices for agricultural products and thus cause higher carbon emissions. In this sense we have captured differences in meat versus vegetable consumption. A better way would have been to have a more disaggregated global model to better capture different types of food consumption. Part of the problem is the trade-off of sectoral detail and country coverage of different global multi-regional IO models. For a recent comparison of various global MRIOs see ref. 59.

In this study, we make the assumption that the consumption bundles of each expenditure group remains the same until 2030, in particular for the low expenditure group included in our scenario analysis. While there is a huge amount of literature focusing on consumption patterns within income/expenditure categories this is less so at the global level as discussed in this paper; but the goal of the paper is not to predict carbon emissions for the year 2030 or 2100 but to investigate the implications of two poverty alleviation scenarios (of moving people from a lower category to a higher one) by 2030 using available detailed data on consumption for different expenditure and income categories from the World Bank and other statistical agencies. We want to investigate these counter factual scenarios based on detailed available data and do not want to “dilute” these scenarios by modifying existing consumption bundles in all income categories other than moving people from one category and the associated consumption bundle to the next. Supplementary Table 1 shows that there is considerable stability in terms of expenditure patterns across the poor in that three quarters of the expenditure is for food, shelter and housing, and the remaining expenditure categories only make small contributions to the expenditure.

This is also reflected in the literature. The most important determinant of the carbon footprint is income (see e.g., Minx et al.; Ahmad et al.40, 60), which we consider explicitly in our two poverty alleviation scenarios but other determinants of per capita carbon footprints such as urban characteristics61, population density62, lifestyles (Baiocchi et al 41), and household size63, etc. are not considered in this study as these do not exist at the global level and most of the countries we include in our study, and are only available for specific countries or selected cities. In summary, the “constant consumption assumption” for the poor for the next decade or so is reasonable given that income and associated composition are the most important factors and we change them explicitly based on detailed available information; and that we are only interested in the counter factual poverty alleviation scenario and their carbon implications. Moreover, there is a lack of available studies for most countries considered in this study; and finally, we find a relative stability of consumption patterns of the poorest in poor countries.

Similarly, we use current emissions intensities (from Eora) until 2030, ignoring well-established hypothetical trends of reducing energy intensity and climate policy. This assumption would probably overestimate the poor’s future emissions. Rather than explicitly modeling various technological assumption as is done by Rao64 we calculate the additional carbon emissions of poverty alleviation and the required reduction in carbon emissions. These additional carbon emissions of poverty alleviation are added to the RCP2.6. The RCP are abstracted from possible socio-economic scenarios that can produce them in agreement with (e.g., Moss et al.65). According to the IPCC AR5: “The RCPs ARE NOT [emphasize added] associated with unique socioeconomic assumptions or emissions scenarios but can result from different combinations of economic, technological, demographic, policy, and institutional futures” (Wayne66, p. 8). “RCPs each describe an emission trajectory and concentration by the year 2100, and consequent forcing. Each trajectory represents a specific synthesis drawn from the published literature. From this “baseline”, researchers can then test various permutations of social, technical and economic circumstances.” (Wayne66, p. 9) And this is exactly how we are using the RCP as a reference emission trajectory to assess the carbon consequences of poverty alleviation. We do not make any assumption of whether innovations and technical change will deliver or not. We “just” assume, based on the IEA report, that in the next 12 years that might not be major changes in carbon intensity. We only calculate the additional gains in reduction required to offset the additional carbon emissions from poverty alleviation.

Another important component of the poverty alleviation scenario is the estimation of population growth. Estimation of population growth is ideally based on the population projections for each income group in each country until 2100. However, these data are not available. On the other hand, we understand that different countries may have different population growth rates and using the average growth rate for low income countries for the low consumption group may lead to relatively large uncertainty. Given the predictions available from the UN World Population Prospects3 we have two choices: (1) to use predictions that represent income segments and thus requires averaging across countries (the average population growth rate for countries within an income bracket) based on estimates by the UN, for example, we use the average population growth rate of low income countries to represent the population growth for the extreme poverty group and the consumption group of >$2.97 per day, and use the population growth rate of lower middle income countries for the consumption group of $2.97–8.44 per day; or (2) to use country specific predictions but ignore the changing composition of expenditure groups (population growth rate by country). Both estimates have shortcomings. Applying the national average growth rate to the low income group within a country may lead to an underestimation of population growth for low income groups as their growth rate might be higher than the national average67. However, using the average population growth rate across all low income countries may also lead to uncertainty because countries have different population growth rates even though they all fall into the low income country category. In this study, we use option (1) i.e., using the average growth rate of the respective country group mainly because the country specific predictions are not an option to us anymore after we introduce our poverty alleviation scenarios as these would significantly influence income and thus fertility and mortality rates of these low income countries and the country specific predictions by the UN would not be applicable to these countries anymore. When comparing the two approaches, we find that option 2 provides 13% lower carbon emissions under scenario 1 and 18% lower under scenario 2 than by using option 1.

The scaled investment and government expenditure is likely to have some benefits for the poor but it is hard to estimate which benefits they accrue. For example, one might argue that a lot of the infrastructure investment benefits more the middle class, who can extract greater benefit from such investments. A simple example is road-building which leads to increased vehicular mobility. Those in extreme poverty have little to benefit from this road-building. We thus see these expanded government expenditure and investment as accompanying the expansion in producing those additional goods and services associated with poverty alleviation but they are not the trigger of poverty alleviation. These initial transfer payments are not explicitly included in this study.

There are a number of ways that government expenditure can lead to poverty alleviation such as direct payment transfer (cash transfer) which are being trialed or implemented in Brazil68 and India69, and direct and indirect subsidies (e.g., fuel subsidies, food subsidies, poverty programs)72, 73. However, we did not include any such payment transfer and/or subsidies or similar mechanism to increase the income of the poor as outlined in these scenarios due to the complexity of these wealth distribution mechanism. However, this problem is partially mitigated by the use of expenditures instead of actual income, which is hard to measure in poorer countries. There is evidence that households in poorer countries have negative savings as they appear to spend more than they earn (see, e.g., Fesseau and van de Ven70). The fact that these types of transfer are implicit in the expenditure data is the standard justification for choosing expenditure over income in many studies.

Code availability

Programming code for MRIO analysis is available from the corresponding author on request.

Data availability

All data used in this study is from open access sources, including the World Bank Global Consumption Database, EORA MRIO database, the World Bank Povcalnet and the UN Population Prospects. The websites for data download are provided in the method section.

Output: Eradicating extreme poverty by raising incomes to above $1.9 purchasing power parity (PPP) per day would not compromise climate targets, even in the absence of effective climate policies and without major technological innovation, according to research from the University of Maryland. However, the research found that ensuring that people have a minimum $2.97 PPP would require an increase in climate mitigation efforts of 27%. A commitment to the eradication of extreme poverty by 2030 is the first of the United Nations’ Sustainable Development Goals.


Instruction: create a high quality summary of the given input

Input:
Worker exploitation exposed in Italian tomato industry
 Two of Italy’s biggest food companies have been implicated in labour abuses of migrant workers picking tomatoes bought by thousands of British and European consumers every week, according to court documents.

Italian prosecutor Paola Guglielmi has named food giants Mutti and Conserve Italia as benefiting from “conditions of absolute exploitation” in the country’s hugely lucrative tomato industry, as part of an investigation into the death of a seasonal labourer.

Both Mutti and the Conserve Italia brand Cirio [see footnote] supply major UK supermarkets with premium tinned tomatoes and passata, and are named in court documents signed by Guglielmi.

The case began with the death of Abdullah Muhammed, a 47-year-old legal Sudanese immigrant and father of two, who suffered a heart attack while working in the fields of Nardó, which sits on the heel of southern Italy, in July 2015. The allegation against his employer was that Muhammed’s life could have been saved if he had been allowed to go to hospital.

The Italian investigator used her powers to track the supply chain up to the very top of the country’s €3.2bn (£2.85bn) processed tomato industry. While the companies are not liable for the death, their link is significant.

Like thousands of other workers, Muhammed’s day would start at 4am and he would work until 5pm handpicking tomatoes in the fierce heat of the southern Italian summer. Labour abuses listed in the court documents include working for 12 hours a day, seven days a week, without breaks, with minimal pay and no access to medical staff.

Italian prosecutor Paola Guglielmi. Photograph: Courtesy of Corriere Salentino

“The person responsible for the crime by law was just the gangmaster,” Guglielmi told the Guardian.

“But in this case there was also manslaughter. That guy would not have died if there had been a doctor’s visit. The violation of the safety provisions on the job was flagrant.”

Through a far-reaching investigation, Guglielmi checked telephone records, tapped phone calls and conducted aerial surveillance to painstakingly link the exploitation of seasonal migrant workers to industrial giants.

While workers make an average of €30 a day in the Puglia region, they can expect to lose up to half of that just to pay for food, transport, water and a cut to their gangmaster.

The gangmaster or “caporalato” system is rife across the Italian agricultural sector where migrants – both legal and illegal – are organised into informal labour groups that are hired by Italian landowners to harvest their crops.

The file accuses Italian company owner Giuseppe Mariano and Sudanese gangmaster Mohammed Elsalih of manslaughter. The preliminary investigation has now concluded, and a judge will decide whether the case should go to trial.

The companies named in the file are not liable and stress the extent to which they encourage their suppliers to treat their workers ethically.

A spokesman for Conserve Italia, which produces the Cirio brand of tinned tomatoes that is sold by Tesco, said it requires all its suppliers agree to “respect” their workers and the company’s ethical code, and that the company cut ties with the supplier involved after they were made aware of Muhammed’s death.

“We know in the south of Italy there are some situations that are not in line but we can’t do the work – it’s not our responsibility to verify what happens in the region but we do ask our suppliers to respect human rights,” he said. “We don’t pay less than the normal price.”

Conserve Italia has since said in a statement that it plans to sue the suppliers for damages “to protect its reputation as the most ethical company in this business”.

Mutti also issued a statement. “Mutti has always been committed to fight any exploitation of workers’ systems by all means … ,” it said. “Mutti selects its farmers and agricultural partners with special care and maintains a constant dialogue with them along the entire supply chain. As far as the protection and security of workers is concerned, each contract involves specific requirements on work conditions (salary regularity as well as security in the workplace). Mutti will continue to foster its commitment to work in cooperation with its competitors, farmers associations and the Italian institutions to avoid accidents in fields.”

A member of Médecins Sans Frontières talks to an African worker in a makeshift camp in the countryside near the village of Rignano Garganico, southern Italy. Photograph: Tony Gentile/Reuters

Activists claim that the low production costs drive interests not to tackle the exploitation problem properly. Yvan Sagnet, 32, from Cameroon worked just five days in the fields near to where Mohammed died before leading a mass strike of the workers in 2012. Now he campaigns to end what he brands “slavery”.

“When I arrived in Puglia I discovered the gangmaster system – conditions were inhuman – they were ghettos that were like concentration camps,” he said.

“One day a guy got sick [in the fields], he couldn’t handle it and in those places there is no way to get first aid – there is no address. There is no cellphone signal. The workers don’t speak Italian so the gangmasters take advantage … The gangmaster insisted, ‘If you don’t pay me the 20 euros I will not take you. If you do you can go to the hospital tonight.’”

After years of campaigning and organising a mass strike against the gangmasters, a strengthened law outlawing the caporalato system came into effect last year.

But campaigners say very little has changed in isolated farms where authorities do not do enough to proactively crack down on the practice.

“The interests of these fields are linked with the interests of the politicians and people who own the most important companies in Italy,” said Valeria Sallustio, former president of Finis Terrae, an Italian NGO that worked closely with the workers in Nardó.

Zoe Maddison, spokesperson for the British Retail Consortium (BRC), which represents Tesco and Sainsbury’s among other major UK supermarkets, said: “This is a tragic case and we expect the Italian authorities to carry out a full investigation.

“The welfare of all people who work in our supply chains is of key importance to us, and BRC members will investigate any allegations of malpractice.”

Output: Mutti and Conserve Italia, two of Italy’s largest food companies, have been accused of profiting from “conditions of absolute exploitation” in the country’s €3.2bn (£$3.7bn) tomato sector. The claims, made by prosecutor Paola Guglielmi, come in the wake of the death of a seasonal labourer. Although not arguing that the companies are liable for the death of Sudanese immigrant Abdullah Muhammed, Guglielmi tracked the supply chain from the exploitation of such workers to the very top of the tomato industry. Both Mutti and Conserve Italia supply UK supermarkets, and their products are purchased by thousands of European consumers each week.


Instruction: create a high quality summary of the given input

Input:
Lasers seen to significantly improve ethylene production
 Optimizing ethylene production with laser technology

Ethylene is one of the most valuable organic compound building blocks in the world.

IP: 178.170.195.243

The Authors

Gogates, A. - Emerson Automation Solutions, - Emerson Automation Solutions, Gunnell, J. - Emerson Automation Solutions, - Emerson Automation Solutions,

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Output: Laser technology has long been used in the manufacture of petrochemicals as an analytical tool, but it may be used to improve the production of ethylene. The chemical is a key organic compound used in industry and agriculture that is expected to be produced at a rate of 200 million metric tons per year by 2020. Refining ethylene to its required 99.99% purity could be made more effective by deploying laser absorption spectroscopy in a novel manner called the zero-gap design. The devices can detect impurities more effectively, a critical part of sustaining profitability.