2026
|
Jinyu Shiwang; Wei Peng; John Bistline; Jamil Farbes; Xinyuan Huang; Gokul Iyer; Jesse D. Jenkins; Eladio Knipping; Nicholas Mailloux; Erin Mayfield; Aranya Venkatesh; Alicia Zhao; Qianru Zhu: A Multi-Model Assessment of the Air Quality and Health Impacts of U.S. Energy Decarbonization. In: Environmental Science & Technology, vol. 60, iss. 38, pp. 27063–27078, 2026, ISSN: 0013-936X. @article{Shiwang2026,
title = {A Multi-Model Assessment of the Air Quality and Health Impacts of U.S. Energy Decarbonization},
author = {Jinyu Shiwang and Wei Peng and John Bistline and Jamil Farbes and Xinyuan Huang and Gokul Iyer and Jesse D. Jenkins and Eladio Knipping and Nicholas Mailloux and Erin Mayfield and Aranya Venkatesh and Alicia Zhao and Qianru Zhu},
doi = {10.1021/acs.est.6c02914},
issn = {0013-936X},
year = {2026},
date = {2026-09-29},
journal = {Environmental Science & Technology},
volume = {60},
issue = {38},
pages = {27063–27078},
abstract = {Net-zero transitions are expected to reduce ambient fine particulate matter (PM2.5) concentrations and the associated mortality burden. The magnitude and distribution of these health effects are substantially affected by energy technology choices and the resulting precursor emissions that contribute to ambient PM2.5. On the basis of a multi-model analysis using three leading energy system models for the United States (US-REGEN, GCAM-USA, and REPEAT), we demonstrate that a net-zero transition yields robust nationwide reductions in ambient PM2.5 concentrations and associated mortality. Under the net-zero scenarios, national PM2.5-attributable mortality rates in 2050 declined by 28–73% compared to 2017 across the three models. This result confirms substantial health benefits from reducing energy-sector pollution, despite concurrent population growth and aging trends that place upward pressure on mortality. Differences across the models result from how CO2 mitigation efforts are allocated across sectors and associated energy technology choices. For instance, the scale of carbon dioxide removal deployment in 2050 varies by a factor of three across the net-zero scenarios developed by the three models, influencing the amount of fossil fuel use that remains in a deeply decarbonized future and, consequently, the precursor emissions contributing to ambient PM2.5. By exploring sensitivity analyses that vary the projected emissions from non-energy activities such as wildfires, we also find that potential future increases in non-energy emissions can offset energy-sector health benefits.},
keywords = {},
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}
Net-zero transitions are expected to reduce ambient fine particulate matter (PM2.5) concentrations and the associated mortality burden. The magnitude and distribution of these health effects are substantially affected by energy technology choices and the resulting precursor emissions that contribute to ambient PM2.5. On the basis of a multi-model analysis using three leading energy system models for the United States (US-REGEN, GCAM-USA, and REPEAT), we demonstrate that a net-zero transition yields robust nationwide reductions in ambient PM2.5 concentrations and associated mortality. Under the net-zero scenarios, national PM2.5-attributable mortality rates in 2050 declined by 28–73% compared to 2017 across the three models. This result confirms substantial health benefits from reducing energy-sector pollution, despite concurrent population growth and aging trends that place upward pressure on mortality. Differences across the models result from how CO2 mitigation efforts are allocated across sectors and associated energy technology choices. For instance, the scale of carbon dioxide removal deployment in 2050 varies by a factor of three across the net-zero scenarios developed by the three models, influencing the amount of fossil fuel use that remains in a deeply decarbonized future and, consequently, the precursor emissions contributing to ambient PM2.5. By exploring sensitivity analyses that vary the projected emissions from non-energy activities such as wildfires, we also find that potential future increases in non-energy emissions can offset energy-sector health benefits. |
Haein Kim; Tracey Holloway; Peter Rafaj; Zbigniew Klimont; Gregor Kiesewetter; Jonathan A. Patz: Co-benefits of residential heat electrification through interstate grid interconnections in Northeast Asia. 2026. @bachelorthesis{Kim2026,
title = {Co-benefits of residential heat electrification through interstate grid interconnections in Northeast Asia},
author = {Haein Kim and Tracey Holloway and Peter Rafaj and Zbigniew Klimont and Gregor Kiesewetter and Jonathan A. Patz},
url = {https://www.sciencedirect.com/science/article/pii/S277278312600052X#abs0001},
doi = {10.1016/j.cles.2026.100282},
year = {2026},
date = {2026-09-26},
journal = {Cleaner Energy Systems},
volume = {15},
number = {100282},
abstract = {This study examines the potential ambient air quality and associated human health co-benefits of residential heating electrification powered by the Asia Supergrid, which connects the China-North, Korea, and Japan-West regions. By linking a bottom-up power sector optimization model and the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model, we assessed the impacts of the complete removal of fossil fuels from residential heating by 2050, replaced by clean electricity supply through carbon pricing and cross-border electricity transmission. Our results show that the locations of clean energy transitions and health benefits do not necessarily coincide. Power trade redistributes generation and associated emissions between exporting and importing regions, resulting in heterogeneous transboundary air quality and health outcomes that can be obscured by national or regional averages. Combined residential and power sector decarbonization prevents 1600–15,500 premature deaths depending on the electricity generation mix. We found that renewable electricity generation is important in maximizing the co-benefits of end-use electrification, yielding higher health benefits than a carbon-neutral electricity supply based on carbon capture and sequestration and hydrogen. These findings highlight the importance of considering the spatial distribution of health co-benefits in designing regional energy cooperation and coordinated decarbonization strategies.},
keywords = {},
pubstate = {published},
tppubtype = {bachelorthesis}
}
This study examines the potential ambient air quality and associated human health co-benefits of residential heating electrification powered by the Asia Supergrid, which connects the China-North, Korea, and Japan-West regions. By linking a bottom-up power sector optimization model and the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model, we assessed the impacts of the complete removal of fossil fuels from residential heating by 2050, replaced by clean electricity supply through carbon pricing and cross-border electricity transmission. Our results show that the locations of clean energy transitions and health benefits do not necessarily coincide. Power trade redistributes generation and associated emissions between exporting and importing regions, resulting in heterogeneous transboundary air quality and health outcomes that can be obscured by national or regional averages. Combined residential and power sector decarbonization prevents 1600–15,500 premature deaths depending on the electricity generation mix. We found that renewable electricity generation is important in maximizing the co-benefits of end-use electrification, yielding higher health benefits than a carbon-neutral electricity supply based on carbon capture and sequestration and hydrogen. These findings highlight the importance of considering the spatial distribution of health co-benefits in designing regional energy cooperation and coordinated decarbonization strategies. |
Santiago Perea; Tessa A. Rhinehart; Léa Bouffaut; Marcelo Araya-Salas; Isla K. Davidson; Luisa F. Arcila-Pérez; Justin Kitzes; Zuzana Buřivalová: The role of conservation bioacoustics in achieving global biodiversity goals. In: Nature Reviews Biodiversity, vol. 2, pp. 565-581, 2026. @article{Perea2026,
title = {The role of conservation bioacoustics in achieving global biodiversity goals},
author = {Santiago Perea and Tessa A. Rhinehart and Léa Bouffaut and Marcelo Araya-Salas and Isla K. Davidson and Luisa F. Arcila-Pérez and Justin Kitzes and Zuzana Buřivalová},
doi = {10.1038/s44358-026-00189-3},
year = {2026},
date = {2026-08-06},
journal = {Nature Reviews Biodiversity},
volume = {2},
pages = {565-581},
abstract = {Conservation bioacoustics — the science of recording and analysing animal sounds for biodiversity conservation purposes — has become an important part of the conservation toolkit, spurred by the ever-growing need to monitor species on a rapidly changing planet. Innovations in recording hardware, artificial intelligence and ecological understanding of animal sounds and soundscapes have helped to drive forward bioacoustic research. In this Review, we explore the main ways conservation science uses bioacoustics and ecoacoustics, with particular focus on the Kunming–Montreal Global Biodiversity Framework, which requires robust, scalable biodiversity methodologies to achieve its 2030 targets. We review the main considerations for evaluating the evidentiary strength of acoustic data in conservation science, both in the field and during analysis. This Review empowers conservation scientists and practitioners with the knowledge to determine whether conservation bioacoustics is the right approach for a particular need, what kind of results it is going to yield and with what uncertainty. As conservation efforts globalize, involving diverse partners, larger investments and claims of impact, evidence on biodiversity impacts needs to be externally verifiable and comparable across ecosystems and regions. Understanding when and how bioacoustics can provide that evidence is key for a responsible uptake by conservation.},
keywords = {},
pubstate = {published},
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Conservation bioacoustics — the science of recording and analysing animal sounds for biodiversity conservation purposes — has become an important part of the conservation toolkit, spurred by the ever-growing need to monitor species on a rapidly changing planet. Innovations in recording hardware, artificial intelligence and ecological understanding of animal sounds and soundscapes have helped to drive forward bioacoustic research. In this Review, we explore the main ways conservation science uses bioacoustics and ecoacoustics, with particular focus on the Kunming–Montreal Global Biodiversity Framework, which requires robust, scalable biodiversity methodologies to achieve its 2030 targets. We review the main considerations for evaluating the evidentiary strength of acoustic data in conservation science, both in the field and during analysis. This Review empowers conservation scientists and practitioners with the knowledge to determine whether conservation bioacoustics is the right approach for a particular need, what kind of results it is going to yield and with what uncertainty. As conservation efforts globalize, involving diverse partners, larger investments and claims of impact, evidence on biodiversity impacts needs to be externally verifiable and comparable across ecosystems and regions. Understanding when and how bioacoustics can provide that evidence is key for a responsible uptake by conservation. |
Karthik Ramaswamy; Nazli Uludere Aragon; Tyler J. Lark: Opportunities for bioenergy crops to support transitions from irrigated agriculture and conserve the U.S. High Plains Aquifer. In: Agricultural Water Management, vol. 334, no. 110675, 2026. @article{Ramaswamy2026,
title = {Opportunities for bioenergy crops to support transitions from irrigated agriculture and conserve the U.S. High Plains Aquifer},
author = {Karthik Ramaswamy and Nazli Uludere Aragon and Tyler J. Lark},
doi = {10.1016/j.agwat.2026.110675},
year = {2026},
date = {2026-08-05},
journal = {Agricultural Water Management},
volume = {334},
number = {110675},
abstract = {This study investigates potential economic and groundwater driven transitions from irrigated maize production—the dominant irrigated cropping system in the High Plains Aquifer (HPA) region—to alternative crops such as sorghum and switchgrass, two common bioenergy feedstocks. Unsustainable groundwater extraction in the U.S. High Plains presents critical challenges including reduced irrigation capacities, diminished crop yields, lower land values, and escalating energy costs. Using a spatially explicit optimization framework combined with comprehensive economic and hydrogeological data, we evaluate optimal land-use strategies and irrigation system investments over a 30-year planning period. Results indicate significant regional variability in the future economic viability of irrigated agriculture, driven by differences in aquifer recharge rates, groundwater availability, and market conditions. Nebraska and parts of northern Texas can sustain irrigated maize profitability due to relatively favorable groundwater conditions and lower land rents, respectively. In contrast, many portions of Kansas and southern Texas are more likely to transition to dryland agriculture within two decades. Colorado and New Mexico show potential for significant adoption of switchgrass production as an alternative biomass-based energy crop. Overall, over the 30-year horizon, our model implies that approximately 23% of currently irrigated maize area across the HPA region may transition to dryland farming under business-as-usual conditions. This transition is complemented by a threefold increase in non-irrigated sorghum production, from 0.20 to 0.77 Mt yr−1, indicating that groundwater-driven shifts in agricultural production may support a larger regional base for bioenergy feedstocks. The study also reveals opportunities for producers to optimize economic returns and biomass production potential.},
keywords = {},
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This study investigates potential economic and groundwater driven transitions from irrigated maize production—the dominant irrigated cropping system in the High Plains Aquifer (HPA) region—to alternative crops such as sorghum and switchgrass, two common bioenergy feedstocks. Unsustainable groundwater extraction in the U.S. High Plains presents critical challenges including reduced irrigation capacities, diminished crop yields, lower land values, and escalating energy costs. Using a spatially explicit optimization framework combined with comprehensive economic and hydrogeological data, we evaluate optimal land-use strategies and irrigation system investments over a 30-year planning period. Results indicate significant regional variability in the future economic viability of irrigated agriculture, driven by differences in aquifer recharge rates, groundwater availability, and market conditions. Nebraska and parts of northern Texas can sustain irrigated maize profitability due to relatively favorable groundwater conditions and lower land rents, respectively. In contrast, many portions of Kansas and southern Texas are more likely to transition to dryland agriculture within two decades. Colorado and New Mexico show potential for significant adoption of switchgrass production as an alternative biomass-based energy crop. Overall, over the 30-year horizon, our model implies that approximately 23% of currently irrigated maize area across the HPA region may transition to dryland farming under business-as-usual conditions. This transition is complemented by a threefold increase in non-irrigated sorghum production, from 0.20 to 0.77 Mt yr−1, indicating that groundwater-driven shifts in agricultural production may support a larger regional base for bioenergy feedstocks. The study also reveals opportunities for producers to optimize economic returns and biomass production potential. |
Lisa Rausch; Tiago N. P. Reis; Cristiane Mazzetti; Marcos Barrozo; Marin Skidmore; Holly K. Gibbs: The rise and fall of the Amazon Soy Moratorium. In: Science, vol. 393, iss. 6808, pp. 249-251, 2026. @article{Rausch2026,
title = {The rise and fall of the Amazon Soy Moratorium},
author = {Lisa Rausch and Tiago N. P. Reis and Cristiane Mazzetti and Marcos Barrozo and Marin Skidmore and Holly K. Gibbs},
url = {https://www.science.org/doi/10.1126/science.aeg5368},
doi = {10.1126/science.aeg5368},
year = {2026},
date = {2026-07-16},
journal = {Science},
volume = {393},
issue = {6808},
pages = {249-251},
abstract = {The Amazon Soy Moratorium (ASM) is a voluntary multisectoral zero-deforestation pact, in which soy traders agreed to not source or finance soy on Amazon lands deforested after July 2008. Despite successes, most traders terminated their commitments under the ASM in early 2026, amid a series of legislative and administrative challenges. A coalition of Brazilian political parties and civil society organizations (CSOs) mobilized to defend the ASM, including petitioning the Brazilian Federal Supreme Court (STF) to intervene (ADI 7774 and related cases; table S1). Here, we describe how the end of the ASM could impose substantial costs for forests and the soy sector. The pending final STF decision may come too late to preserve the ASM, but broader implications of this case extend beyond the agreement itself to the viability of any voluntary supply-chain standards that include limits on deforestation and ecosystem conversion that are not explicitly specified by Brazilian legislation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Amazon Soy Moratorium (ASM) is a voluntary multisectoral zero-deforestation pact, in which soy traders agreed to not source or finance soy on Amazon lands deforested after July 2008. Despite successes, most traders terminated their commitments under the ASM in early 2026, amid a series of legislative and administrative challenges. A coalition of Brazilian political parties and civil society organizations (CSOs) mobilized to defend the ASM, including petitioning the Brazilian Federal Supreme Court (STF) to intervene (ADI 7774 and related cases; table S1). Here, we describe how the end of the ASM could impose substantial costs for forests and the soy sector. The pending final STF decision may come too late to preserve the ASM, but broader implications of this case extend beyond the agreement itself to the viability of any voluntary supply-chain standards that include limits on deforestation and ecosystem conversion that are not explicitly specified by Brazilian legislation. |
Hannah K. Friedrich; Beth Tellman; Jason R. Jurjevich; Mark Kear; Laura Bakkensen: “Do Battle with Insurance”: Post-Hurricane Insurance Litigation in Southwest Louisiana. In: RSF: The Russell Sage Foundation Journal of the Social Sciences, vol. 12, iss. 4, pp. 178–203, 2026, ISSN: 2377-8253. @article{Friedrich2026,
title = {“Do Battle with Insurance”: Post-Hurricane Insurance Litigation in Southwest Louisiana},
author = {Hannah K. Friedrich and Beth Tellman and Jason R. Jurjevich and Mark Kear and Laura Bakkensen},
doi = {10.7758/RSF.2026.12.4.08},
issn = {2377-8253},
year = {2026},
date = {2026-07-15},
urldate = {2026-07-15},
journal = {RSF: The Russell Sage Foundation Journal of the Social Sciences},
volume = {12},
issue = {4},
pages = {178–203},
abstract = {Property insurance is essential for hurricane recovery, yet timely and fair claims payouts are not guaranteed. Post-disaster litigation over denied or delayed claims is common but understudied in who sues and how this varies sociodemographically. Southwest Louisiana is well situated for such an analysis, where within two years after Hurricane Laura and Hurricane Delta hit the region in 2020, one in five federal civil litigation cases were filed, most regarding insurance. We collate 5,476 court records to geocode implicated properties and assess litigation patterns using property and sociodemographic data. We find litigation is 43 percent more likely in higher percent Black residential areas, with property value amplifying this disparity. Additionally, case duration is longer for residents in these areas, suggesting systemic procedural inequities. Our findings reveal how race, class, and geography relate to insurance litigation, a critical yet overlooked facet of procedural vulnerability that may contribute to inequitable disaster recovery outcomes in the United States.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Property insurance is essential for hurricane recovery, yet timely and fair claims payouts are not guaranteed. Post-disaster litigation over denied or delayed claims is common but understudied in who sues and how this varies sociodemographically. Southwest Louisiana is well situated for such an analysis, where within two years after Hurricane Laura and Hurricane Delta hit the region in 2020, one in five federal civil litigation cases were filed, most regarding insurance. We collate 5,476 court records to geocode implicated properties and assess litigation patterns using property and sociodemographic data. We find litigation is 43 percent more likely in higher percent Black residential areas, with property value amplifying this disparity. Additionally, case duration is longer for residents in these areas, suggesting systemic procedural inequities. Our findings reveal how race, class, and geography relate to insurance litigation, a critical yet overlooked facet of procedural vulnerability that may contribute to inequitable disaster recovery outcomes in the United States. |
Summer Acker; Tracey Holloway; Kevin M. Stewart; Aaron van Donkelaar; Randall V. Martin: Comparison of Policy-Relevant Air Quality Metrics Calculated With Sparse In Situ Monitoring and Contiguous Satellite-Derived Data. In: GeoHealth, vol. 10, iss. 7, 2026. @article{Acker2026,
title = {Comparison of Policy-Relevant Air Quality Metrics Calculated With Sparse In Situ Monitoring and Contiguous Satellite-Derived Data},
author = {Summer Acker and Tracey Holloway and Kevin M. Stewart and Aaron van Donkelaar and Randall V. Martin},
url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025GH001586},
doi = {10.1029/2025GH001586},
year = {2026},
date = {2026-07-07},
journal = {GeoHealth},
volume = {10},
issue = {7},
abstract = {Compliance with the U.S. National Ambient Air Quality Standards (NAAQS) traditionally relies on a sparse network of ground-based monitors. We compare two methods for assessing whether U.S. counties are above or below the annual fine particulate matter (PM2.5) NAAQS of 9.0 μg/m3: the monitor-based methodology used to calculate county design values (CDVs; an EPA metric representing the maximum, in-county PM2.5 monitor value over a 3-year annual average), and a satellite-based methodology that computes county design value equivalents (CDVEs) from Washington University's global satellite-derived PM2.5 data product. The satellite-based approach uses the 90th percentile PM2.5 grid value in a county and shows strong overall agreement with monitor-based CDVs across 536 monitored U.S. counties (r = 0.76; rs = 0.74). Counties were classified as aligned positives (APs), aligned negatives (ANs), non-aligned positives (NPs), or non-aligned negatives (NNs) based on whether CDVEs align or don't align with CDVs on NAAQS status. Risk factors likely contributing to larger differences between CDVEs and CDVs within non-aligned counties include ≤2 monitors, low (<7 μg/m3) or high (>10 μg/m3) CDVs, low (<0.05%) or high (>0.1%) monitor coverage, large county size, wildfires, mountains, deserts, and low urbanization. In non-aligned counties, differences grow with the number of risk factors, with seven-risk-factor counties showing 5x higher median differences than those with one. High error-risk counties cluster in the Western U.S.; low error-risk counties are in the Midwest and East. These findings highlight trade-offs between sparse and contiguous data for regulatory assessments and support integration of satellite-derived data into policy frameworks.},
keywords = {},
pubstate = {published},
tppubtype = {article}
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Compliance with the U.S. National Ambient Air Quality Standards (NAAQS) traditionally relies on a sparse network of ground-based monitors. We compare two methods for assessing whether U.S. counties are above or below the annual fine particulate matter (PM2.5) NAAQS of 9.0 μg/m3: the monitor-based methodology used to calculate county design values (CDVs; an EPA metric representing the maximum, in-county PM2.5 monitor value over a 3-year annual average), and a satellite-based methodology that computes county design value equivalents (CDVEs) from Washington University's global satellite-derived PM2.5 data product. The satellite-based approach uses the 90th percentile PM2.5 grid value in a county and shows strong overall agreement with monitor-based CDVs across 536 monitored U.S. counties (r = 0.76; rs = 0.74). Counties were classified as aligned positives (APs), aligned negatives (ANs), non-aligned positives (NPs), or non-aligned negatives (NNs) based on whether CDVEs align or don't align with CDVs on NAAQS status. Risk factors likely contributing to larger differences between CDVEs and CDVs within non-aligned counties include ≤2 monitors, low (<7 μg/m3) or high (>10 μg/m3) CDVs, low (<0.05%) or high (>0.1%) monitor coverage, large county size, wildfires, mountains, deserts, and low urbanization. In non-aligned counties, differences grow with the number of risk factors, with seven-risk-factor counties showing 5x higher median differences than those with one. High error-risk counties cluster in the Western U.S.; low error-risk counties are in the Midwest and East. These findings highlight trade-offs between sparse and contiguous data for regulatory assessments and support integration of satellite-derived data into policy frameworks. |
Tracey Holloway; Summer Acker; Lizzy Kysela; Colleen Heck; Aaron van Donkelaar; Randall V. Martin; Kevin M. Stewart; Katherine Pruitt: Applying Satellite-Derived PM2.5 Data to Policy-Relevant Air Quality Metrics. In: GeoHealth, vol. 10, iss. 7, 2026. @article{Holloway2026,
title = {Applying Satellite-Derived PM2.5 Data to Policy-Relevant Air Quality Metrics},
author = {Tracey Holloway and Summer Acker and Lizzy Kysela and Colleen Heck and Aaron van Donkelaar and Randall V. Martin and Kevin M. Stewart and Katherine Pruitt},
url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025GH001585},
doi = {10.1029/2025GH001585},
year = {2026},
date = {2026-07-07},
urldate = {2026-07-07},
journal = {GeoHealth},
volume = {10},
issue = {7},
abstract = {Since 2000, the American Lung Association (ALA) has published an annual “State of the Air” report, which assigns grades and ranks United States (U.S.) cities and counties based on data from regulatory monitors reported to the Environmental Protection Agency (EPA). We evaluate satellite-derived gridded data sets for fine particulate matter (PM2.5), as a possible method to support the ALA assessment in counties without regulatory monitors. Our analysis compares two publicly available, annual average, satellite-derived gridded PM2.5 data sets, allocated to U.S. counties using three different methods. Assigning the 90th percentile gridded value of PM2.5 within a county as the county-level indicator yields moderately strong agreement between ground-based monitor PM2.5 results and satellite-derived PM2.5 results, with a spatial correlation coefficient of 0.76 for 8 years of Washington University global (WashU GL) data. This agreement is evaluated with respect to concentration values, rankings, and the definition of counties as “passing” or “failing” the ALA annual PM2.5 benchmark of 9.0 μg/m3 (the 2024 EPA National Ambient Air Quality Standard for annual PM2.5). While most unmonitored counties are “passing” the ALA benchmark, we identify 63 counties that would be classified as “failing” if satellite-based data were used to assign ALA grades. Improving methods to analyze satellite-derived data for comparison with monitor-based metrics can support broader utilization of space-based data in the U.S. and globally.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Since 2000, the American Lung Association (ALA) has published an annual “State of the Air” report, which assigns grades and ranks United States (U.S.) cities and counties based on data from regulatory monitors reported to the Environmental Protection Agency (EPA). We evaluate satellite-derived gridded data sets for fine particulate matter (PM2.5), as a possible method to support the ALA assessment in counties without regulatory monitors. Our analysis compares two publicly available, annual average, satellite-derived gridded PM2.5 data sets, allocated to U.S. counties using three different methods. Assigning the 90th percentile gridded value of PM2.5 within a county as the county-level indicator yields moderately strong agreement between ground-based monitor PM2.5 results and satellite-derived PM2.5 results, with a spatial correlation coefficient of 0.76 for 8 years of Washington University global (WashU GL) data. This agreement is evaluated with respect to concentration values, rankings, and the definition of counties as “passing” or “failing” the ALA annual PM2.5 benchmark of 9.0 μg/m3 (the 2024 EPA National Ambient Air Quality Standard for annual PM2.5). While most unmonitored counties are “passing” the ALA benchmark, we identify 63 counties that would be classified as “failing” if satellite-based data were used to assign ALA grades. Improving methods to analyze satellite-derived data for comparison with monitor-based metrics can support broader utilization of space-based data in the U.S. and globally. |
Hannah K. Friedrich; Ekta Aggarwal; Sophie L. Buijs; Srija Chakraborty; Caitlyn A. Hall; Yang Hu; Beth Tellman: Satellite earth observation for recovery from hydrometeorological hazards. In: Water Security, vol. 28, no. 100205, 2026, ISSN: 2468-3124. @article{Friedrich2026b,
title = {Satellite earth observation for recovery from hydrometeorological hazards},
author = {Hannah K. Friedrich and Ekta Aggarwal and Sophie L. Buijs and Srija Chakraborty and Caitlyn A. Hall and Yang Hu and Beth Tellman},
url = {https://www.sciencedirect.com/science/article/pii/S2468312426000118?via%3Dihub},
doi = {10.1016/j.wasec.2026.100205},
issn = {2468-3124},
year = {2026},
date = {2026-05-30},
urldate = {2026-05-30},
journal = {Water Security},
volume = {28},
number = {100205},
abstract = {Hydrometeorological hazards pose heightened risks to society, whether as standalone events or as multiple hazards that intersect across space and time. A key component of managing these risks is assessing hazard recovery to guide response and mitigate future impacts. Satellite-based Earth Observation (EO) is a valuable data source for mapping physical changes in hazard impacts and recovery, and, in combination with non-EO data, for contextualizing qualitative, functional, resilience, and risk-based components of recovery. We summarize the physical features mapped by EO to monitor recovery from hydrometeorological hazards, and the uses and challenges of integrating non-EO data to achieve contextual measures of recovery. Large-scale measures of land cover and land use classes, and vegetation features, integrate with aggregated non-EO datasets but have limited utility for interrogating fine-scale and temporal changes. Nighttime lights provide high-frequency monitoring of electricity outages and restorations as a proxy for recovery, with a robust empirical linkage to non-EO data, but remain subject to variability in the validity of this relationship across locations. Despite advances in modeling and image resolution for assessing building damage, little attention has been paid to mapping building reconstruction. Inconsistent use of non-EO data to contextualize EO-derived physical changes neglects evaluations of recovery reflecting changes in functional intent, resilience, and risk. We discuss opportunities for achieving more robust assessments while accounting for challenges in monitoring and non-EO integration. Future work is needed to expand integration for monitoring multi-hazard recovery and capture overlapping impacts and asynchronous recovery trajectories in support of reduced disaster risk.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hydrometeorological hazards pose heightened risks to society, whether as standalone events or as multiple hazards that intersect across space and time. A key component of managing these risks is assessing hazard recovery to guide response and mitigate future impacts. Satellite-based Earth Observation (EO) is a valuable data source for mapping physical changes in hazard impacts and recovery, and, in combination with non-EO data, for contextualizing qualitative, functional, resilience, and risk-based components of recovery. We summarize the physical features mapped by EO to monitor recovery from hydrometeorological hazards, and the uses and challenges of integrating non-EO data to achieve contextual measures of recovery. Large-scale measures of land cover and land use classes, and vegetation features, integrate with aggregated non-EO datasets but have limited utility for interrogating fine-scale and temporal changes. Nighttime lights provide high-frequency monitoring of electricity outages and restorations as a proxy for recovery, with a robust empirical linkage to non-EO data, but remain subject to variability in the validity of this relationship across locations. Despite advances in modeling and image resolution for assessing building damage, little attention has been paid to mapping building reconstruction. Inconsistent use of non-EO data to contextualize EO-derived physical changes neglects evaluations of recovery reflecting changes in functional intent, resilience, and risk. We discuss opportunities for achieving more robust assessments while accounting for challenges in monitoring and non-EO integration. Future work is needed to expand integration for monitoring multi-hazard recovery and capture overlapping impacts and asynchronous recovery trajectories in support of reduced disaster risk. |
Laurence S. Kalkstein; Scott Sheridan; José-María Martín-Olalla; Elizabeth Berg; Rebecca Rose; Nicholas Mailloux; Sara Pabich; Gregory A. Wellenius; Kathy Baughman McLeod; Kurt Shickman; Yuval Baharav: Development and evaluation of a health-based heat wave categorization system: a case study of Seville, Spain. In: International Journal of Biometeorology, vol. 70, no. 171 (2026), 2026. @article{Kalkstein2026,
title = {Development and evaluation of a health-based heat wave categorization system: a case study of Seville, Spain},
author = {Laurence S. Kalkstein and Scott Sheridan and José-María Martín-Olalla and Elizabeth Berg and Rebecca Rose and Nicholas Mailloux and Sara Pabich and Gregory A. Wellenius and Kathy Baughman McLeod and Kurt Shickman and Yuval Baharav},
url = {https://link.springer.com/article/10.1007/s00484-026-03206-4},
doi = {10.1007/s00484-026-03206-4},
year = {2026},
date = {2026-05-23},
journal = {International Journal of Biometeorology},
volume = {70},
number = {171 (2026)},
abstract = {In the summer of 2022, our team of climatologists and researchers piloted the first heat warning system that ranks heat events based upon human health outcomes. This system uses local all-cause mortality data in addition to meteorological factors including air mass identification and the Excess Heat Factor to identify heat events that are likely to endanger human health in the region and applies three categories representing increasing severity. In this study, we evaluated this system by comparing the heat events it identified in Seville, Spain between 1995 and 2022 with those identified by the Spanish national meteorology agency (AEMET). We also compared the outputs from both systems against all-cause mortality data over the same time period. We found that our system captured more dangerous heat events than the meteorology-only criteria of AEMET and that the majority of identified heat events occurred during periods of elevated mortality. Additionally, the agreement between systems differed by event severity; roughly half of the high mortality “Category 3” events identified by our system were also identified by AEMET, but AEMET only issued alerts during one of the 24 more minor “Category 1” events that our system identified, even though these events were also correlated with increased mortality. Overall, these results show the potential of health-based warning systems in identifying dangerous events that might be missed by traditional meteorology-based systems.},
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pubstate = {published},
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}
In the summer of 2022, our team of climatologists and researchers piloted the first heat warning system that ranks heat events based upon human health outcomes. This system uses local all-cause mortality data in addition to meteorological factors including air mass identification and the Excess Heat Factor to identify heat events that are likely to endanger human health in the region and applies three categories representing increasing severity. In this study, we evaluated this system by comparing the heat events it identified in Seville, Spain between 1995 and 2022 with those identified by the Spanish national meteorology agency (AEMET). We also compared the outputs from both systems against all-cause mortality data over the same time period. We found that our system captured more dangerous heat events than the meteorology-only criteria of AEMET and that the majority of identified heat events occurred during periods of elevated mortality. Additionally, the agreement between systems differed by event severity; roughly half of the high mortality “Category 3” events identified by our system were also identified by AEMET, but AEMET only issued alerts during one of the 24 more minor “Category 1” events that our system identified, even though these events were also correlated with increased mortality. Overall, these results show the potential of health-based warning systems in identifying dangerous events that might be missed by traditional meteorology-based systems. |
Beth Tellman; Meha Jain; Hallie Eakin; Dylan Connor; Felipe de Alba: Electoral politics influence expansion and titling of informal urban settlements. In: PNAS, vol. 123, iss. 21, 2026. @article{Tellman2026,
title = {Electoral politics influence expansion and titling of informal urban settlements},
author = {Beth Tellman and Meha Jain and Hallie Eakin and Dylan Connor and Felipe de Alba},
url = {https://www.pnas.org/doi/10.1073/pnas.2421303123},
doi = {10.1073/pnas.2421303123},
year = {2026},
date = {2026-05-18},
journal = {PNAS},
volume = {123},
issue = {21},
abstract = {Understanding what and who shapes urban growth and how it unfolds in the Global South is critical to ensure theories and predictive models of urban expansion and, consequently, global environmental change, are salient to contemporary contexts. Much of the urban expansion in the Global South occurs in informal settlements where urbanization is not officially permitted and residents often lack access to basic services and infrastructure. As a result, formalizing settlements becomes an asset for political transactions where politicians provide titles and improve conditions in exchange for residents’ votes. Yet the cumulative effect of these political transactions on land change remains unknown, rendering electoral dynamics absent from land system science models of urbanization. Here we use panel regression to examine the influence of electoral cycles and voting patterns on urban expansion and formalization of property titles from 1997–2015 in Mexico City. We find the distribution of land titles to residents increases in the months leading up to local elections, and more titles are given to core voting neighborhoods of the historically dominant party. Furthermore, urban built-up area increases in districts with higher electoral competition. These results demonstrate that electoral politics influence when and where the legal city boundary expands, who can access secure tenure, and potentially which settlements grow. These results imply sociopolitical dynamics shape urban sustainability. Incorporating quantified links between political dynamics and urban expansion could improve models of future urban growth and identify relevant levers to improve urban sustainability.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Understanding what and who shapes urban growth and how it unfolds in the Global South is critical to ensure theories and predictive models of urban expansion and, consequently, global environmental change, are salient to contemporary contexts. Much of the urban expansion in the Global South occurs in informal settlements where urbanization is not officially permitted and residents often lack access to basic services and infrastructure. As a result, formalizing settlements becomes an asset for political transactions where politicians provide titles and improve conditions in exchange for residents’ votes. Yet the cumulative effect of these political transactions on land change remains unknown, rendering electoral dynamics absent from land system science models of urbanization. Here we use panel regression to examine the influence of electoral cycles and voting patterns on urban expansion and formalization of property titles from 1997–2015 in Mexico City. We find the distribution of land titles to residents increases in the months leading up to local elections, and more titles are given to core voting neighborhoods of the historically dominant party. Furthermore, urban built-up area increases in districts with higher electoral competition. These results demonstrate that electoral politics influence when and where the legal city boundary expands, who can access secure tenure, and potentially which settlements grow. These results imply sociopolitical dynamics shape urban sustainability. Incorporating quantified links between political dynamics and urban expansion could improve models of future urban growth and identify relevant levers to improve urban sustainability. |
Nicholas A. Mailloux; Vijay S. Limaye; Jonathan A. Patz: Improved accounting of the health costs of air pollution in the United States. In: Environmental Research: Health, 2026. @article{Mailloux2026,
title = {Improved accounting of the health costs of air pollution in the United States},
author = {Nicholas A. Mailloux and Vijay S. Limaye and Jonathan A. Patz},
url = {http://iopscience.iop.org/article/10.1088/2752-5309/ae6f43},
doi = {10.1088/2752-5309/ae6f43},
year = {2026},
date = {2026-05-18},
urldate = {2026-05-18},
journal = {Environmental Research: Health},
abstract = {Air pollution exposure poses health and economic burdens, but most assessments of air pollution in the United States do not account for known variation in costs of hospital admissions and emergency department (ED) visits by race/ethnicity or region, nor do they include ambulatory care and other health-related costs. Given that medical cost data are used regularly in policy and regulatory analyses of air pollution, it is important that these data be finely resolved and comprehensive. We estimate hospital admission and ED visit costs by region, race/ethnicity, and payer type for cardiovascular, respiratory, and neurological health outcomes associated with fine particulate matter (PM2.5) exposure that are included in the Environmental Benefits Mapping and Analysis Program–Community Edition. We also determine additional costs associated with outpatient surgeries, home health care, and prescribed medicines. We then apply these cost data to PM2.5 air quality improvement scenarios to assess their effect on monetized benefit totals. Regional hospital admission and ED visit costs differ from the national average by as much as –34% to +65%. Asian Americans incur the highest per-event costs for most outcomes. White and Black Americans generally incur below-average per-event costs for hospital admissions, and Black and Hispanic Americans incur below-average per-event costs for ED visits. Additional costs greatly increase the total cost of medical events for cardiovascular disease outcomes and hospital admissions for Parkinson’s disease and respiratory diseases (ages 18). When stratifying medical costs by race/ethnicity and region and including additional costs, monetized benefits increase by 64% under the revised National Ambient Air Quality Standard for annual PM2.5 exposure. The effect of cost stratification is less pronounced in scenarios in which PM2.5 reductions are more widespread. We recommend that stratified health cost data be considered for use in policy and regulatory analysis, particularly in work considering health equity implications of air pollution exposure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Air pollution exposure poses health and economic burdens, but most assessments of air pollution in the United States do not account for known variation in costs of hospital admissions and emergency department (ED) visits by race/ethnicity or region, nor do they include ambulatory care and other health-related costs. Given that medical cost data are used regularly in policy and regulatory analyses of air pollution, it is important that these data be finely resolved and comprehensive. We estimate hospital admission and ED visit costs by region, race/ethnicity, and payer type for cardiovascular, respiratory, and neurological health outcomes associated with fine particulate matter (PM2.5) exposure that are included in the Environmental Benefits Mapping and Analysis Program–Community Edition. We also determine additional costs associated with outpatient surgeries, home health care, and prescribed medicines. We then apply these cost data to PM2.5 air quality improvement scenarios to assess their effect on monetized benefit totals. Regional hospital admission and ED visit costs differ from the national average by as much as –34% to +65%. Asian Americans incur the highest per-event costs for most outcomes. White and Black Americans generally incur below-average per-event costs for hospital admissions, and Black and Hispanic Americans incur below-average per-event costs for ED visits. Additional costs greatly increase the total cost of medical events for cardiovascular disease outcomes and hospital admissions for Parkinson’s disease and respiratory diseases (ages 18). When stratifying medical costs by race/ethnicity and region and including additional costs, monetized benefits increase by 64% under the revised National Ambient Air Quality Standard for annual PM2.5 exposure. The effect of cost stratification is less pronounced in scenarios in which PM2.5 reductions are more widespread. We recommend that stratified health cost data be considered for use in policy and regulatory analysis, particularly in work considering health equity implications of air pollution exposure. |
L Maurya; S Kaushik; B Tellman: GLACIA: Instance-Aware Positional Reasoning for Glacial Lake Segmentation via Multimodal Large Language Model. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2026. @inproceedings{maurya2026glacia,
title = {GLACIA: Instance-Aware Positional Reasoning for Glacial Lake Segmentation via Multimodal Large Language Model},
author = {L Maurya and S Kaushik and B Tellman},
url = {https://arxiv.org/abs/2512.09251},
year = {2026},
date = {2026-01-01},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
|
S Kaushik; L Maurya; B Tellman: Prithvi-Complimentary Adaptive Fusion Encoder (CAFE): Unlocking Full-Potential for Flood Inundation Mapping. In: arXiv preprint arXiv:2601.02315, 2026. @article{kaushik2026cafe,
title = {Prithvi-Complimentary Adaptive Fusion Encoder (CAFE): Unlocking Full-Potential for Flood Inundation Mapping},
author = {S Kaushik and L Maurya and B Tellman},
url = {https://arxiv.org/abs/2601.02315},
year = {2026},
date = {2026-01-01},
journal = {arXiv preprint arXiv:2601.02315},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
S Kaushik; L Maurya; B Tellman: Cryo-Bench: Benchmarking Foundation Models for Cryosphere Applications. In: arXiv preprint arXiv:2603.01576, 2026. @article{kaushik2026cryobench,
title = {Cryo-Bench: Benchmarking Foundation Models for Cryosphere Applications},
author = {S Kaushik and L Maurya and B Tellman},
url = {https://arxiv.org/abs/2603.01576},
doi = {10.48550/arXiv.2603.01576},
year = {2026},
date = {2026-01-01},
journal = {arXiv preprint arXiv:2603.01576},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
D. Lsoto; R. Sserunjogi; G. Okello; Y. Chen; J. A. Patz; J. J. Schauer: A framework for interpreting air pollution sensor data: Bridging gaps in monitoring, analysis and community action. In: Journal of the Air & Waste Management Association, 2026. @article{Lsoto2026AirPollution,
title = {A framework for interpreting air pollution sensor data: Bridging gaps in monitoring, analysis and community action},
author = {D. Lsoto and R. Sserunjogi and G. Okello and Y. Chen and J. A. Patz and J. J. Schauer},
url = {https://scholar.google.com/citations?view_op=view_citation&citation_for_view=uLr2cnMAAAAJ:PkcyUWeTMh0C},
year = {2026},
date = {2026-01-01},
journal = {Journal of the Air & Waste Management Association},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Aparna R. Phalke; Mutlu Özdoğan; Lachezar H. Filchev: The Peak Value Method (PVM): A Phenology-Guided, Training-Independent Approach for Large-Area Time-Series Winter Wheat Mapping in the Cross-Border Region Between Bulgaria and Türkiye. In: IEEE Transactions on Geoscience and Remote Sensing, vol. 64, pp. 1-17, 2026. @article{11343849,
title = {The Peak Value Method (PVM): A Phenology-Guided, Training-Independent Approach for Large-Area Time-Series Winter Wheat Mapping in the Cross-Border Region Between Bulgaria and Türkiye},
author = {Aparna R. Phalke and Mutlu Özdoğan and Lachezar H. Filchev},
doi = {10.1109/TGRS.2026.3652492},
year = {2026},
date = {2026-01-01},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
volume = {64},
pages = {1-17},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
N. Kimambo; M. Gallop; D. Gu; V. Radeloff; E. Sangalali; L. Naughton-Treves: Obvious and obscure actors are planting trees in rural Africa. In: Environmental Research Letters, vol. 21, no. 1, pp. 014015, 2026. @article{Kimambo2026AfricaTrees,
title = {Obvious and obscure actors are planting trees in rural Africa},
author = {N. Kimambo and M. Gallop and D. Gu and V. Radeloff and E. Sangalali and L. Naughton-Treves},
doi = {10.1088/1748-9326/ad9968},
year = {2026},
date = {2026-01-01},
journal = {Environmental Research Letters},
volume = {21},
number = {1},
pages = {014015},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
J. Buchner; K. E. Lewińska; V. Butsic; Z. Buřivalová; A. Ghoddousi; N. Rogova; V. C. Radeloff: Assessing the effectiveness of strictly protected areas in preventing forest loss and degradation across different forest types in the Caucasus. In: Biological Conservation, vol. 315, pp. 111685, 2026. @article{Buchner2026Caucasus,
title = {Assessing the effectiveness of strictly protected areas in preventing forest loss and degradation across different forest types in the Caucasus},
author = {J. Buchner and K. E. Lewińska and V. Butsic and Z. Buřivalová and A. Ghoddousi and N. Rogova and V. C. Radeloff},
doi = {10.1016/j.biocon.2025.111685},
year = {2026},
date = {2026-01-01},
journal = {Biological Conservation},
volume = {315},
pages = {111685},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
2025
|
Parisa Sarzaeim; Grace Bulltail: Evaluation of FAIR Principles in Indigenous Water-Climate-Environment (WCE) Data Repositories. In: Data Science Journal, vol. 24, no. 31, 2025. @article{Sarzaeim2025Evaluation,
title = {Evaluation of FAIR Principles in Indigenous Water-Climate-Environment (WCE) Data Repositories},
author = {Parisa Sarzaeim and Grace Bulltail},
url = {https://doi.org/10.5334/dsj-2025-031},
year = {2025},
date = {2025-11-01},
journal = {Data Science Journal},
volume = {24},
number = {31},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|