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Various technologies and strategies have been proposed to decarbonize the chemical industry. Assessing the decarbonization, environmental, and economic implications of these technologies and strategies is critical to identifying pathways to a more sustainable industrial future. This study reviews recent advancements and integration of systems analysis models, including process analysis, material flow analysis, life cycle assessment, techno-economic analysis, and machine learning. These models are categorized based on analytical methods and application scales (i.e., micro-, meso-, and macroscale) for promising decarbonization technologies (e.g., carbon capture, storage, and utilization, biomass feedstock, and electrification) and circular economy strategies. Incorporating forward-looking, data-driven approaches into existing models allows for optimizing complex industrial systems and assessing future impacts. Although advances in industrial ecology–, economic-, and planetary boundary–based modeling support a more holistic systems-level assessment, more effects are needed to consider impacts on ecosystems. Effective applications of these advanced, integrated models require cross-disciplinary collaborations across chemical engineering, industrial ecology, and economics. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering , Volume 15 is June 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

Replacing fossil fuels with biofuels offers a promising path to decarbonizing the transportation sector, a major source of greenhouse gas emissions (GHGs). Utilizing waste biomass such as forest residues is particularly appealing, as it avoids land-use change and associated GHG emissions. Current biofuel life cycle assessment (LCA) adopted by regulatory agencies considers forest residues as carbon-neutral feedstock and typically ignores soil organic carbon (SOC) changes from residue removal. Our study quantifies SOC change caused by removing forest residues in the Southern US and found that they can make a substantial contribution to the carbon footprint of biofuel derived from forest residues. Our results emphasize the need to include soil carbon assessment in future LCAs, biofuel policy, and forest management, even when waste biomass is used and no land-use change is involved. 

A framework integrating life cycle assessment, Green Chemistry, and techno-economic analysis to identify cost-effective, greener pathways for nanomaterial production, demonstrated with cellulose nanomaterials. 

Afforestation and reforestation (AR) on marginal land are nature-based solutions to climate change. There is a gap in understanding the climate mitigation potential of protection and commercial AR with different combinations of forest plantation management and wood utilization pathways. Here, we fill the gap using a dynamic, multiscale life cycle assessment to estimate one-century greenhouse gas (GHG) mitigation delivered by (both traditional and innovative) commercial and protection AR with different planting density and thinning regimes on marginal land in the southeastern United States. We found that innovative commercial AR generally mitigates more GHGs across 100 y (3.73 to 4.15 Giga tonnes of CO 2 equivalent (Gt CO 2 e)) through cross-laminated timber (CLT) and biochar than protection AR (3.35 to 3.69 Gt CO 2 e) and commercial AR with traditional lumber production (3.17 to 3.51 Gt CO 2 e), especially in moderately cooler and dryer regions in this study with higher forest carbon yield, soil clay content, and CLT substitution. In a shorter timeframe (≤50 y), protection AR is likely to deliver higher GHG mitigation. On average, for the same wood product, low-density plantations without thinning and high-density plantations with thinning mitigate more life cycle GHGs and result in higher carbon stock than that of low-density with thinning plantations. Commercial AR increases the carbon stock of standing plantations, wood products, and biochar, but the increases have uneven spatial distributions. Georgia (0.38 Gt C), Alabama (0.28 Gt C), and North Carolina (0.13 Gt C) have the largest carbon stock increases that can be prioritized for innovative commercial AR projects on marginal land.