Enhanced Deep-Learning Model for Carbon Footprints of Chemicals.

Millions of chemicals have been designed; however, their product carbon footprints (PCFs) are largely unknown, leaving questions about their sustainability. This general lack of PCF data is because the data needed for comprehensive environmental analyses are typically not available in the early molecular design stages. Several predictive tools have been developed to estimate the PCF of chemicals, which are applicable to only a narrow range of common chemicals and have limited predictive ability. Here, we propose FineChem 2, which is based on a novel transformer framework and first-hand industry data, for accurately predicting the PCF of chemicals. Compared to previous tools, FineChem 2 demonstrates significantly better predictive power, and its applicability domains are improved by ∼75% on a diverse set of chemicals on the global market, including the high-production-volume chemicals identified by regulators, daily chemicals, and chemical additives in food and plastics. In addition, through better interpretability from the attention mechanism, FineChem 2 may successfully identify PCF-intensive substructures and critical raw materials of chemicals, providing insights into the design of more sustainable molecules and processes. Therefore, we highlight FineChem 2 for estimating the PCF of chemicals, contributing to advancements in the sustainable transition of the global chemical industry.

Global site-specific health impacts of fossil energy, steel mills, oil refineries and cement plants.

Climate change and particulate matter air pollution present major threats to human well-being by causing impacts on human health. Both are connected to key air pollutants such as carbon dioxide (CO[Formula: see text]), primary fine particulate matter (PM[Formula: see text]), sulfur dioxide (SO[Formula: see text]), nitrogen oxides (NO[Formula: see text]) and ammonia (NH[Formula: see text]), which are primarily emitted from energy-intensive industrial sectors. We present the first study to consistently link a broad range of emission measurements for these substances with site-specific technical data, emission models, and atmospheric fate and effect models to quantify health impacts caused by nearly all global fossil power plants, steel mills, oil refineries and cement plants. The resulting health impact patterns differ substantially from far less detailed earlier studies due to the high resolution of included data, highlighting in particular the key role of emission abatement at individual coal-consuming industrial sites in densely populated areas of Asia (Northern and North-Eastern India, Java in Indonesia, Eastern China), Western Europe (Germany, Belgium, Netherlands) as well as in the US. Of greatest health concern are the high SO[Formula: see text] emissions in India, which stand out due to missing flue gas treatment and cause a particularly high share of local health impacts despite a limited number of emission sites. At the same time, the massive infrastructure and export capacity build-up in China in recent years is taking a substantial toll on regional and global health and requires more stringent regulation than in the rest of the world due to unfavorable environmental conditions and high population densities. The current phase-out of highly emitting industries in Europe is found not to have started with sites having the greatest health impacts. Our detailed site-specific emission and impact inventory is able to highlight more effective alternatives and to track future progress.

Net-zero transition of the global chemical industry with CO2-feedstock by 2050: feasible yet challenging.

Carbon capture, utilization and storage (CCUS) have been projected by the power and industrial sectors to play a vital role towards net-zero greenhouse gas emissions. In this study, we aim to explore the feasibility of a global chemical industry that fully relies on CO2 as its carbon source in 2050. We project the global annual CO2 demand as chemical feedstock to be 2.2-3.1 gigatonnes (Gt), well within the possible range of supply (5.2-13.9 Gt) from the power, cement, steel, and kraft pulp sectors. Hence, feedstock availability is not a constraint factor for the transition towards a fully CO2-based chemical industry on the global basis, with the exception of few regions that could face local supply shortages, such as the Middle East. We further conduct life cycle assessment to examine the environmental benefits on climate change and the trade-offs of particulate matter-related health impacts induced by carbon capture. We conclude that CO2 captured from solid biomass-fired power plants and kraft pulp mills in Europe would have the least environmental and health impacts, and that India and China should prioritize low-impact regional electricity supply before a large-scale deployment of CCUS. Finally, two bottom-up case studies of China and the Middle East illustrate how the total regional environmental and health impacts from carbon capture can be minimized by optimizing its supply sources and transport, requiring cross-sectoral cooperation and early planning of infrastructure. Overall, capture and utilization of unabatable industrial waste CO2 as chemical feedstock can be a feasible way for the net-zero transition of the industry, while concerted efforts are yet needed to build up the carbon-capture-and-utilization value chain around the world.

Globally Regionalized Monthly Life Cycle Impact Assessment of Particulate Matter.

This work provides a globally regionalized approach for quantifying particulate matter (PM2.5) health impacts. Atmospheric transport and pollutant chemistry of primary particulate matter, sulfur dioxide (SO2), nitrogen oxide (NOx), and ammonia (NH3) from stack emissions were modeled and used to calculate monthly high-resolution maps of global characterization factors that can be used for life cycle impact assessment (LCIA) and risk assessment. These characterization factors are applied to a global data set of coal power emissions. The results show large regional and temporal differences in health impacts per kg of emission and per amount of coal power generation (5-1300 DALY TWh-1). While small emission reductions of PM2.5 and SO2 from coal power lead to similar health benefits across densely populated areas of Asia and Europe, we find that larger emission reductions result in up to three times higher health benefits in parts of Asia because of the nonlinear health responses to pollution exposure changes. Hence, many regions in Asia benefit disproportionately much from large coal power PM2.5 and SO2 emission reductions. NOx emission reductions can lead to equally high health benefits, where unfavorable atmospheric conditions coincide with elevated NH3 background pollution and large population (e.g., in Central Europe, Indonesia, or Japan but also numerous other places).