Carbon pricing is a policy tool adopted by many governments worldwide for mitigating climate change. This approach can make emitters either adjust their operations to lower GHG emissions or pay for their GHG emissions, which can be used for renewable energy investment or rebates to low-income households. There are a couple of primary carbon pricing systems, carbon tax and cap-and-trade system. For the carbon tax system, a set tax rate is applied to all GHG emissions and has been adopted in areas including British Columbia in Canada, Finland, and Sweden. For the cap-and-trade system, emitters will be allocated with initial emissions allowances. If an emitter generates more greenhouse gas than they are allowed, they will need to purchase additional allowances through government auction or the open carbon market. In contrast, if an emitter emits less than they are allowed, they can profit by selling excess allowances in the open carbon market. The carbon permit price in the carbon market is fluctuating and determined based on supply and demand. In the European Union Emissions Trading System, the carbon permit price can range from around $5 EUR per tonne of CO 2 -equivalent (CO 2 eq) in 2017 to around $100 EUR per tonne of CO 2 eq in 2023. The cap-and-trade system has been implemented in several regions, including the European Union, California in the United States, and China. From an optimization stand-point, carbon taxes and cap-and-trade are equivalent (because the inherent dual values of carbon quotas can be seen as penalties). It is also important to highlight that production companies can internalize carbon prices within their jurisdiction (without government intervention); specifically, companies can have an "internal" perceived value of carbon, which can be estimated based on negative inherent impacts (e.g., negative public perception and loss of market/brand value). The idea of incorporating carbon pricing schemes into technology pathway selection for decarbonization has been adopted in literature. For example, Lopez et al. presented an optimization framework to determine technology pathways to decarbonize university campuses. In this work, we adapt the optimization-based framework of Lopez et al. for analyzing production pathways of mainstream plastics from fossil and biomass feedstocks. The modeling framework captures the complex interdependencies in the production pathways of individual plastics at a systemswide level. As such, the framework allows us to quantify system-wide feedstock needs, total production costs, and total carbon footprints. The framework can be seen as an integrative platform of techno-economic and life-cycle data and can be used to: i) identify plastics and technologies that should be prioritized to achieve different levels of decarbonization and ii) navigate complex tradeoffs and limiting behavior of production costs and carbon footprints. We also evaluate the hidden impacts of biomass-based plastic production that arise from increased land and fertilizer use (which can lead to significant eutrophication). Our case study uses basic data and a limited subset of possible technologies to demonstrate the benefits of the proposed modeling framework; as such, our results should not be interpreted as recommendations on carbon pricing or on feedstock/technology use.