Sustainable aviation fuel (SAF) is a drop-in fossil fuel alternative made from various biological feedstocks, including those that can be naturally cultivated like corn, soybean, and algae. SAF has the potential to greatly reduce emissions generated by the aviation industry, which accounts for 2.5% of global emissions and is projected to grow. However, the economics of decarbonizing the aviation sector through SAF are not well understood at a local resolution, and precise models estimating domestic SAF production are lacking.

To foster success in the deployment of new infrastructure and land-use changes to meet the demands for domestic SAF, this study uses process modeling and techno-economic analysis (TEA) to study the economic feasibility of SAF production compared to standard jet fuel. A discounted cash flow rate of return method was used to evaluate the internal rate of return (IRR) of the SAF systems when the net present value of cash flows becomes zero. The TEA model integrates the mass, energy, and financial inputs required for SAF production systems and outputs accurate operational and capital expenditures (OPEX, CAPEX) over the system’s life cycle. A corn-to-SAF pathway was studied and an engineering process model including corn cultivation, starch fermentation, and fuel upgrading was developed. A second pathway that uses miscanthus as a SAF feedstock was also modeled. In this pathway, miscanthus undergoes a Fischer-Tropsch gasification process that produces a biocrude, which is then processed into various liquid fuels and upgraded into SAF.

Historical data was utilized to inform the process model, enabling geo-specific inputs of the South-Central region of the U.S. A comparative analysis was then conducted between the corn-to-SAF and miscanthus-to-SAF pathways to identify key contributors to the Minimum Fuel Selling Price (MFSP) of SAF from either feedstock. Results show that the corn-to-SAF process consistently portrayed greater values in terms of OPEX, CAPEX, and MFSP over miscanthus-to-SAF. For instance, the average MFSP for the corn-derived SAF in the studied agricultural districts in Kansas was found to be $5.62 per gallon of gasoline equivalent (GGE) compared to $3.06 for miscanthus-based SAF.

Future work will include the modeling of multiple feedstock pathways in the same agricultural districts and counties to further compare MFSP and economic feasibility of SAF production in the South-Central U.S. region. Additionally, Monte Carlo methods will be utilized to portray variability in the model, as depicted by historical and projective data sources of biomass availability.

Food waste (FW) management is a significant environmental issue in the United States, with 38% of ~ 96.8 million metric tons annually ending up in landfills, causing substantial greenhouse gas emissions and resource loss. This study fills knowledge gaps by conducting an environmental impact assessment of FW valorization in Wastewater Resource Recovery Facilities (WRRFs), using static Material Flow Analysis (MFA) and Life Cycle Impact Assessment (LCIA) at the county level in the U.S. The evaluated scenarios include (1) traditional landfilling, (2) co-digestion of FW in a conventional activated sludge (CAS) WRRF with anaerobic digestion + struvite fertilizer production, and (3) co-digestion in an anaerobic membrane bioreactor (AnMBR) WRRF + struvite fertilizer production. For Gwinnett County, Georgia, MFA showed that 104,870 tons of FW are landfilled annually, with only 17,240 tons per year processed in WRRFs. LCIA results indicated that landfilling FW has the highest Global Warming Potential (GWP) at 68.55 Kg CO₂ eq per ton of FW due to uncontrolled methane emissions. Conversely, CAS and AnMBR WRRF scenarios reduced GWP to 2.8 E-4Kg CO₂ eq per ton of FW+ wastewater (WW) and 1.12 E-3 Kg CO₂ eq per ton of FW + WW, respectively. Valorization of FW only at CAS and AnMBR WRRFs contributed only 1.05 E-08 and 1.68 E-08 CO₂ eq per ton of FW, respectively. Sensitivity and uncertainty analyses confirmed these findings, showing that co-digestion of FW does not affect effluent quality or regulatory compliance. This study is innovative in its integrated approach, using real-scale WRRF process modeling with MFA and LCIA, providing actionable insights for policymakers and industry stakeholders. The results support a sustainable transition in FW management practices, demonstrating that WRRFs can convert FW into valuable resources, reduce emissions by over 99% compared to landfilling, and contribute to a circular economy while protecting watershed health.

The production and consumption of eggs have grown rapidly in the United States and across the world due to its popularity as a versatile cooking ingredient for many types of cuisine, as well as being one of the more affordable sources of high-quality animal protein. While eggs are also considered to be environmentally friendlier compared to many livestock products, the rapid and sustained growth of egg demand has prompted interest in reducing its environmental footprint to prepare the industry for a net zero future. One of the promising ways to potentially improve the sustainability of the egg industry is to utilize grocery wastes destined for the landfills as a feed ingredient for layer hens. Food waste in the landfill generates potent greenhouse gases such as methane and is widely recognized as a serious climate change concern. Therefore, the food waste to feed valorization approach offers a multifaceted solution that can reduce the large climate change burden of landfilling food wastes, improves circularity of nutrients, and reduces the environmental burden of egg production all at the same time. Despite its potential, there currently exists a lack of studies in the literature that investigate food waste to feed valorization, particularly at a commercial scale in western countries. Therefore, to contribute towards filling the knowledge gap, this study investigates the environmental footprint of a commercial scale grocery waste to poultry feed manufacturer based in Pennsylvania through Life Cycle Assessment (LCA). This study also investigates the environmental impacts and benefits of incorporating this feed input for conventional egg production in the US. It was found that a climate burden reduction of at least 8.5% could be achieved compared to conventional egg production when the layer feed ingredients were substituted at a rate of only 5% by weight with the valorized product. Improvements in equipment energy use efficiency, efficient transportation, and incorporating renewable energy sources can maximize the environmental benefits.

The steel sector contributes 11% of industrial emissions in the U.S., primarily driven by automotive demand and carbon-intensive upstream metal production. Decarbonizing the U.S. automotive steel sector is critical for meeting the IPCC's 2050 emission reduction targets. Most automotive demand goes into light-duty vehicle (LDV) manufacturing, in which alloyed steel sheet accounts for over 70% of steel-based semi-components. Manufacturing these sheet alloys is challenging with secondary steelmaking processes due to the target alloys' intolerance to copper contamination in scrap streams, leading to a reliance on primary steelmaking in the U.S., which predominantly follows the blast furnace route.

This presentation aims to propose a decarbonization roadmap for the U.S. Automotive steel consumption by examining material efficiency pathways (lightweighting, yield improvements, and recycling), advanced steelmaking and low-carbon technologies (CCUS, hydrogen-based methods, and electrolysis), and adopting cleaner electrical grids (supported by institutional efforts such as the Inflation Reduction Act and national goal of 100% carbon-free electricity by 2035). This presentation will highlight a dynamic vehicle fleet model for estimating future sales and end-of-life vehicle volumes, which we used to project the annual steel consumption for light-duty vehicles from 2023 to 2050. These time-varying trajectories were combined with vehicle weights for 10 powertrains across 3 light-duty vehicle classes (Cars, SUVs, and Light-duty trucks) to predict the annual demand of steel for LDVs and the mass of end-of-life scrap generated. Then, using a steel sheet model developed in collaboration with Ford Motor Company, Nucor, and U.S. Steel, along with trade statistics from UN Comtrade and USGS, we calculated the energy consumption and global warming potential under business-as-usual (BAU) conditions. Subsequently, we evaluated 4,455 decarbonization pathways under varying consumption, trade, and technological scenarios through techno-economics and life-cycle assessments. Results have revealed significant emission reduction potential via direct reduction technologies and electrolysis while highlighting the substantial carbon abatement from hydrogen-based pathways, albeit at higher costs. Government incentives such as hydrogen production tax credits were shown to dramatically reduce the economic burden of transitioning to hydrogen technologies. Based on these findings, this presentation will explore decision-making insights and provide actionable guidance to stakeholders and policymakers on decarbonizing the automotive industry through the production of low-carbon steel.

Over the past half-century, the manufacturing and extraction sectors in the United States have experienced a steady decline. However, bipartisan investments and private contributions signal a potential reversal of this trend. Spurred by geopolitical tensions, supply chain vulnerabilities exposed during the pandemic, and the economic potential of clean and emerging technologies, Biden-era policies directed approximately $2 billion toward the development of domestic production, supplemented by $614 billion in private investments.

While this shift promises extensive economic opportunities, the potential social implications vested in this transition require consideration, many of which may be disproportionate to certain US populations. Racial and economic-based environmental inequality has been tied to exposure to industrial pollution since the 1980s, propagating negative health outcomes throughout marginalized US communities (Salazar et al., 2019). As the US ushers in a new era of industrial advancement, an opportunity exists to harness development to address long-standing inequities, using production growth as a catalyst for reducing racial and economic disparities. Equitable development — where individuals or groups receive tailored resources or experiences to achieve true fairness and accessibility — is essential to realizing key United Nations Development Goals, including Gender Equality; Reduced Inequalities; Peace, Justice, and Strong Institutions; and Partnerships for the Goals (Romero-Lenko & Nobler, 2018).

The type 1 Social Life Cycle Assessment (SLCA) framework offers a comprehensive tool to evaluate the social performance and equitable achievements of industrial operations. However, its application in the US is limited by a lack standardized methods and procedures accounting for regionally variabilities, such as the US. This critical review aims to enhance SLCA methodologies by developing a data decision tree addressing data availability, interdisciplinary data collection methods, US specific performance reference points (PRPs) to assess inventory data and interpretation through the lens of systemic equity. We aim to demonstrate this methodology using a case study on the US manufacturing sector.

Using the data decision tree in future SLCA studies will help identify indicators for which unavailable data inhibits the generation of performance reference points. Unavailable data highlighted through this matriculation can then be populated through stakeholder interviews, focus groups, or questionnaires, where guiding questions are informed by case study analysis and literature review. Subsequently, inventory data will then be scored according to the most geographically specific available data, which can then be compared with relevant performance reference points. Finally, this study recommends interpretation according to the Systemic Equity Framework proposed by Bozeman et al. (2022) (i.e., distributive, procedural, and recognitional equity).

This integrated and standardized approach enhances the replicability of SLCA studies while increasing the relevance of their findings in the US and other similarly heterogenous regions, such as the European Union. Broader adoption of these methods can expand data availability, significantly elevate corporate social responsibility (CSR) performance, and contribute to advancing all 17 Sustainable Development Goals (SDGs).

Article 6 was established under the Paris Agreement to facilitate the goal of holding “the increase in global average temperature to well below 2°C”. It allows countries to engage cooperatively to achieve their climate pledges either directly or through carbon markets. Article 6 enables cooperating parties to have greater ambition while diverting fewer resources than would have been required had the parties acted independently. The intent is to enhance mitigation ambition by utilizing efficiency gains from trading. Such international emissions trading forms the bedrock to mobilize public and private sector investment flows to meet ambitious climate and sustainable development goals (SDGs). However, a significant body of research concludes that there are important links between mitigation and other societal objectives, such as the SDGs. The aggregate success of such global cooperation and emissions trading mechanisms will then depend on the critical co-benefits and tradeoffs on some of the SDGs. This raises an important and unexplored question of how global emissions trading may enable or hinder energy justice and how different countries might evaluate their participation in such markets.

In this paper, using a global integrated assessment model (GCAM: Global Change Analysis Model,), we demonstrate that spatial and temporal distributions of the influence of Article 6 emissions markets on a subset of the broader SDGs may differ. We use a subset of sustainability metrics related to the energy equity and justice issues. Our analysis of these metrics tracks the interconnected nature of human and earth systems under different emission market designs for 20 key geographical regions (including USA, EU, China, India, Japan, Brazil, Russia, Australia, Sub-Saharan Africa, South Asia, Indonesia & Latin America) from 2030 to 2050, under a consistent integrated framework. This allows us to assess the local implications of emissions market design on different dimensions of energy justice such: energy access, residential energy prices (affordability), clean energy shares (sustainability), & energy imports (security). We show the effects of redistribution and international financial transfers and demonstrate these effects between the Global North & South for different national and global mitigation scenarios and alternative market designs and pricing mechanisms: the Glasgow Pledges, a net zero 2050 and an equity-oriented net zero pathway.

Our results imply that global cooperation in markets can be altered if interactions between mitigation and local effects on the energy justice dimensions were accounted for. Furthermore, we demonstrate that the extent to which these distributions differ depends on market design and pricing of nature-based mitigation options. Our analysis provides a foundation for assessing how global emission market schemes under Article 6 could be better understood in the local developmental contexts of energy justice & equity.

Since countries view their own climate mitigation efforts through a more comprehensive lens than mere emissions reduction, and the links with societal outcomes would influence their consideration of comparability and participation in emissions trading markets, the success of such global cooperation mechanisms would depend on perceptions of the relationships of mitigation with local and regional societal goals. The degree of congruence between these relationships demonstrated in this paper could influence future climate negotiations and carbon market design.

A future powered by clean energy and a circular economy could transform how industry and society approach resources and waste. However, there are few resources for analyzing the community impacts of emerging technologies in these fields. This talk will introduce an environmental justice framework that uses a series of metrics, questions, and actionable guidelines to empower experts and nonexperts to evaluate the broader implications of their solutions. Through a series of case studies related to plastic circularity and chemical decarbonization, we will showcase how early consideration of community impacts can inspire innovative research that minimizes and mitigates harm to the environment and humanity.