
Jason Hill
· Professor, Distinguished McKnight University ProfessorVerifiedUniversity of Minnesota · Department of Community Development
Active 1943–2025
About
Jason Hill is a Professor in the Department of Bioproducts and Biosystems Engineering at the University of Minnesota. He also serves as a Resident Fellow of the University’s Institute on the Environment. His research focuses on the consequences of food, energy, agriculture, and natural resource use from a life-cycle perspective. Dr. Hill has testified before U.S. House and Senate Committees on the environmental effects of transportation biofuels. His work has been published in prominent journals such as Science and the Proceedings of the National Academy of Sciences. He has served on the National Research Council’s Committee on the Economic and Environmental Impacts of Increasing Biofuels Production and on the United States Environmental Protection Agency Science Advisory Board’s Biogenic Carbon Advisory Panel. Dr. Hill holds an AB in Biology from Harvard College and a PhD in Plant Biological Sciences from the University of Minnesota.
Research topics
- Environmental science
- Geography
- Medicine
- Environmental health
- Biology
- Political Science
- Meteorology
- Ecology
- Waste management
- Business
- Engineering
- Environmental protection
- Agronomy
- Natural resource economics
- Economics
- Physics
- Agricultural economics
- Demography
- Psychology
Selected publications
Air quality-related human health damages of wild capture seafood production in the United States
Environmental Research Food Systems · 2025-01-10
articleOpen accessSenior authorAbstract Exposure to air pollution is the greatest environmental health risk factor for mortality in the United States and globally, to which food production is a major contributor. Recent studies have estimated the human health impacts of air pollution from terrestrial livestock and crop production, but those of seafood production, which is an important component of many diets, are largely unknown. Here, we estimate the air quality-related human health damages of wild capture fisheries production in the United States via the emission and formation of particulate matter (PM 2.5 ). We quantify annual deaths attributable to primary and secondary PM 2.5 from commercial marine vessel emissions using county- and species-specific fishing activity and landings data. We find that, on average, wild caught seafood production is a low air quality-related health impact source of protein, with mortality health impacts 58× less than chicken, 321× less than pork, and 484× less than beef per gram of protein. The air quality-related health impacts of seafood vary widely by species and by fishing activity location. Notably, the highest impact seafood-based sources of protein production tend to be far less damaging than terrestrial animal-based sources of protein and are comparable to plant-based proteins, largely mirroring previously described broader trends for the life cycle greenhouse gas emissions of these various protein sources. Our work suggests that as global protein demand rises, shifting diets towards increased seafood consumption to meet nutritional protein requirements may offer potentially large reductions in environmentally driven harm to human health relative to terrestrial animal-based proteins.
Equity and modeling in sustainability science: Examples and opportunities throughout the process
Proceedings of the National Academy of Sciences · 2024-03-18 · 49 citations
articleOpen accessEquity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.
Air quality, health, and equity impacts of vehicle electrification in India
Environmental Research Letters · 2024-01-09 · 12 citations
articleOpen accessAbstract Ambient air pollution in India accounts for 870 000 deaths per year, including 43 000 from road transportation. Vehicle electrification could posit a sustainable solution. However, 3/4th of India’s electric grid is powered by coal, emitting large amounts of PM 2.5 , SO 2 , and NO x . This leads to uncertainty regarding the health benefits and distributional consequences from vehicle electrification. Our results show that if electric vehicles made up 30% of vehicle kilometers traveled, there would be 1000–2000 additional deaths each year under present day conditions. Higher increases in pollution exposure are seen in scheduled castes/tribes, poor, and rural populations particularly in high coal production states. Switching to net zero-emitting electricity generation for charging would reduce air pollution attributable deaths by 6000–7000 annually and PM 2.5 exposure across all groups of population.
Air pollution mortality from India’s coal power plants: unit-level estimates for targeted policy
Environmental Research Letters · 2024-05-03 · 3 citations
articleOpen accessAbstract Air pollution from coal-fired electricity generation is an important cause of premature mortality in India. Although pollution-related mortality from the sector has been extensively studied, the relative contribution of individual coal-fired units to the fleet-wide mortality burden remains unclear. Here, we find that emissions from a small number of units drive overall mortality. Units producing just 3.5% of total generation and constituting less than 3% of total capacity result in 25% of annual premature mortality from coal-fired generation. This is a direct consequence of the 200-fold variation that we find in the mortality intensity of electricity generation across units. We use a detailed emissions inventory, a reduced complexity air quality model, and non-linear PM 2.5 concentration-response functions to estimate marginal premature mortality for over 500 units operational in 2019. Absolute annual mortality ranges from less than 1 to over 650 deaths/year across units, and the mortality intensity of generation varies from under 0.002 to 0.43 deaths/GWh. Our findings suggest the potential for large social benefits in the form of reduced PM 2.5 -related premature mortality in India if the highest mortality intensity units are prioritized for the implementation of pollution control technologies or accelerated retirement.
2023-03-31
preprintOpen access<p>Direct effect of BIM-355 at different doses on tumor growth in POMC-KO mice model.</p>
2023-03-31
preprintOpen access<p>mRNA expression levels of SST3 in different pituitary neuroendocrine tumors (PitNETs) and NPs.</p>
2023-03-31
preprintOpen accessSupplementary Data from ARQ 197, a Novel and Selective Inhibitor of the Human c-Met Receptor Tyrosine Kinase with Antitumor Activity
Generative adversarial networks for real-time realistic physics simulations
2023-06-12
articleSenior authorLynntech is seeking to develop real-time realistic nondestructive evaluation (NDE) and structural health monitoring (SHM) physics-based simulations, and automated data reduction/analysis methods, for large datasets. Recently, computational efficient Neural Network based simulations have demonstrated the possibility to synthesize data with an orders-of-magnitude increase in speed compared to standard computational techniques [1,2]. In this contribution, we report our initial experimental results for our Generative Adversarial Network for Realistic Physics Simulations, or GAN4RPS.
Proceedings of the National Academy of Sciences · 2023-04-17
letterOpen accessProceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans the biological, physical, and social sciences.
Life Cycle Analysis of Biofuels
Elsevier eBooks · 2023-10-04 · 3 citations
book-chapter1st authorCorresponding
Frequent coauthors
- 56 shared
Christopher W. Tessum
University of Illinois Urbana-Champaign
- 48 shared
Julian Marshall
Seattle University
- 28 shared
Gérald Raverot
- 28 shared
Alexandre Vasiljevic
- 26 shared
Alejandro Ibáñez‐Costa
Centro de Investigación Biomédica en Red
- 26 shared
Mari C. Vázquez‐Borrego
- 26 shared
Raúl M. Luque
- 26 shared
Justo P. Castaño
Instituto Maimónides de Investigación Biomédica de Córdoba
Education
- 2004
PhD, Plant Biological Sciences
University of Minnesota
- 1997
AB, Biology
Harvard College
Awards & honors
- Distinguished McKnight University Professor
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