(354c) Climate Policies Can Substantially Reduce the Environmental Footprint of Green Chemicals

The chemical industry poses a formidable challenge towards decarbonization, primarily due to its heavy reliance on fossil fuels as carbon and energy sources, leading to 5.6 Gt CO₂‑eq y^–1, accounting for 10% of global GHG emissions [1]. Specifically, traditional routes of platform chemicals like ammonia and methanol are catalytic processes, currently heavily relying on natural gas for their production and resulting in significant CO₂ emissions (560 Mt y^–1) [2]. About one‑third of these emissions are direct, while the remaining are attributed to energy acquisition and the upstream value chain [1]. This challenging dependence on global energy systems and supply chains also presents an opportunity to reduce environmental impacts in platform chemical production through other key sector decarbonization strategies.

In recent years, emerging catalytic technologies have played a crucial role in advancing low‑carbon production routes for these chemicals. Greener production routes for ammonia and methanol, based on green hydrogen, have been put forward more recently, with their environmental performance evaluated through life cycle assessments (LCAs) [3–5]. In these LCA studies, a process model is developed utilizing mass and energy balances of the main plant (i.e., foreground system), which is combined with life cycle emissions data based on various technologies across the chemical supply chains (i.e., background system). It is common in LCA studies to assume a fixed background system, i.e., a set of technologies providing inputs to the chemical production plant, reflecting the current state of the technosphere [6–8].

However, the targets set by climate policies will necessitate substantial changes in the economy, including the decarbonization of energy production and transportation. Neglecting these future technological changes when evaluating the environmental impacts of chemicals can result in spurious conclusions. Hence, in this work, we perform a prospective LCA to evaluate the environmental impacts of fossil and green ammonia and methanol pathways until 2050 by considering potential or predicted changes in the power, materials, and transportation sectors.

Therefore, our study investigates the extent to which future economic trends affect the environmental impacts of fossil and green ammonia and methanol production pathways. To enable the assessment of current and future environmental impacts based on expected socioeconomic and technological trends, we utilize future projections of the economy derived with an Integrated Assessment Model (IAM). IAMs like IMAGE comprehensively capture interactions among society, the biosphere, and the climate system [9]. Specifically, in this work, we adopt the ‘middle‑of‑the‑road’ shared socioeconomic pathway (SSP2) to perform our assessments. In parallel, IMAGE also projects different representative concentration pathways (RCPs), specifically RCP6, RCP2.6, and RCP1.9, presenting a range of radiative forcing values in 2100. RCP6 is a pathway that limits global mean surface temperature to below 3.5 °C, while RCP2.6 and RCP1.9 aim to restrict temperature to 2 °C and 1.5 °C, respectively [10]. Combining these SSPs with RCPs, a range of scenarios is generated entailing specific changes in the economy to perform more accurate environmental assessments.

In terms of climate change impacts, we found that the solar and wind‑based ammonia or methanol production routes show a promising trend, with significant reductions anticipated by 2050 (in the range 55–110%), in contrast to fossil‑based pathways, which will reduce impacts only marginally (4–11%). Under more ambitious climate policies, such as the 1.5 °C scenario, these impacts are expected to decrease substantially. Specifically, by 2050, both the solar‑ and wind‑based routes are projected to achieve almost a 70% reduction in impacts. Furthermore, a regional analysis reveals that for solar‑ and wind‑based ammonia and methanol production, impact reductions vary significantly by region, emphasizing the importance of location‑based dynamics for strategic planning. We believe these results equip policymakers and technology investors with tools to navigate the evolving landscape of the chemical industry, ensuring informed decisions.

References

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