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At least 19 records

Attributing human mortality from fire PM 2.5 to climate change

Climate change intensifies fire smoke, emitting hazardous air pollutants that impact human health. However, the global influence of climate change on fire-induced health impacts remains unquantified. Here, in this study, we used three well-tested fire-vegetation models in combination with a chemical transport model and health risk assessment framework to attribute global human mortality from fire fine particulate matter (PM 2.5 ) emissions to climate change. Of the 46401 (1960s) –to 98748 (2010s) annual fire PM 2.5 mortalities, 669 (1.2%, 1960s) –to 12566 (12.8%, 2010s) were attributed to climate change. The most substantial influence of climate change on fire mortality occurred in South America, Australia, and Europe, coinciding with decreased relative humidity, and in boreal forests with increased air temperature. Increasing relative humidity lowered fire mortality in other regions, like South Asia. Our study highlights the role of climate change in fire mortality, aiding public health authorities in spatial targeting adaptation measures for sensitive fire-prone areas.

54 ENVIRONMENTAL SCIENCES

Assessing the impact of climate change on rainfall-triggered landslides: a case study in California

Landslides are widespread natural hazards which take a heavy toll on lives, property, and infrastructure each year. In January 2023 and 2024, widespread landslides occurred in California as a result of extreme winter precipitation. Estimating the regional evolution of landslide hazard in a changing climate is essential for adaptation planning and risk mitigation efforts. The complex effects of climate change on landslide hazard, however, are poorly understood. Here, we use climate and landslide observations to develop a novel data-driven approach for landslide susceptibility assessment under historical and future climate conditions. We apply this framework to investigate the evolution of landslide susceptibility in California and its impacts on the roadway system based on downscaled climate projections under moderate and high greenhouse gas emission scenarios. On average, the results indicate an increase in landslide susceptibility through 2100 in regions where historical susceptibility is moderate to very high. Although the spatio-temporal variations in landslide susceptibility are sensitive to climate model uncertainties in predicting extreme rainfall, the direst impacts are largely circumvented in lower emission scenarios.

Climate Change

Heterotrophic respiration by soil microbes in a changing climate

Soil microbes strongly influence the soil organic carbon (SOC) pool, which globally stores ~2,000 PgC. Specifically, the balance between microbial heterotrophic respiration (R H ), which degrades SOC, and plant–microbe interactions that stabilize SOC determines whether terrestrial ecosystems are a net source or sink of CO 2 to the atmosphere. Here, in this Review, we evaluate how climate change alters these competing processes. R H is approximately half of total soil respiration, at ~50 PgC yr −1 , with 70% occurring in topsoils. Warming accelerates microbial metabolism, with a 10 °C temperature increase estimated to raise R H by ~50%, an effect that is particularly strong in Arctic soils. Warming also reduces soil moisture, further modulating R H , which responds nonlinearly to soil moisture, being limited by saturation and desiccation and meeting a maximum at intermediate levels. Consequently, R H is highly sensitive to future precipitation changes and drought. However, soil management strategies could enhance SOC stocks and persistence under climate change. Bacterial and fungal inoculants can promote SOC production and stabilization, while deep-rooting plants increase SOC inputs to deeper layers that experience lower R H . Agricultural practices and biochar amendments can also enhance SOC and reduce R H . Expanding field trials across regions, climates and soil types would improve empirical understanding of these responses and support better representation of R H in predictive models, enabling more accurate assessments of climate impacts on SOC storage.

Jansson, Janet K. [Pacific Northwest National Labo

Cooperation in Transmission Expansion Planning: Enhancing Grid Reliability and Efficiency Under a Changing Climate

Electricity grids are challenged to maintain reliability during more intense and frequent extreme weather events due to climate change. This challenge is exacerbated by multi-sector electrification and power sector decarbonization through increased reliance on variable renewable energy, which necessitates the expansion of transmission infrastructure. However, transmission expansion planning is often complicated by intertwined planning authorities and jurisdictions, and allocation of large capital investment needs. These factors cause authorities to manage transmission investments individually (i.e., only/mostly intraregional planning), which can lead to suboptimal transmission networks. This study investigates the potential benefits of cooperative transmission expansion planning (i.e., both intraregional and interregional planning that optimizes transmission investments across the entire physical system). Using sectoral and economic optimization, and machine learning models, it analyzes the impact of different levels of cooperation among transmission planning regions within U.S. Western Interconnection in 2019 and 2059 via an iterative investment process. Furthermore, it examines the effects of future climate change on transmission cooperation by simulating historical heat waves from 2019 under conditions of 2059. The results indicate that cooperative transmission planning leads to lower wholesale electricity prices, decreased energy outages, and reduced greenhouse gas emissions. However, the advantages of collaboration diminish during widespread heat waves, despite remaining beneficial especially for regions like California Independent System Operator with substantial solar installations. The study underscores the importance of transmission cooperation in reducing costs and enhancing reliability, emphasizing the need for strategic investments in storage to address challenges posed by future extreme weather events with varying spatial scales.

Capacity Expansion Model

Building hypotheses to understand the synergistic effects of heat and pollution exposure in a changing climate

The increasing intensity, frequency, and duration of extreme weather events due to climate change poses a broad range of health risks, and the synergistic effects of extreme temperature co-occurring with other hazardous exposures such as air pollution may result in higher risks of all-cause mortality and cardiovascular and respiratory morbidity than exposure to either event alone. There are a number of hypothesized mechanisms for this interaction effect, including increased susceptibility to heat effects on chronic conditions affected by air pollution exposure, exacerbation of pollution effects due to temperature-induced stress, and shared pathophysiological pathways (e.g., systemic inflammation), but specific physiological mechanisms are not well understood. In this editorial, the authors discuss this aspect of a recently published study examining ambient formaldehyde combined with high temperature exposure and respiratory disease admissions among children. Here, the observation that the health effects of pollutants such as formaldehyde are amplified following periods of high temperature can help inform risk warning systems even without knowledge of the underlying physiological mechanisms, but a deeper biological understanding of the interaction effects of heat and ambient air pollution may better inform interventions. This is even more important in view of increases in both extreme temperature and pollution events tied to climate change.

Chambliss, Sarah [University of Texas at Austin, T

Potential Effects of Climate Change and Solar Radiation Modification on Renewable Energy Resources

Solar radiation modification (SRM) is a possible deliberate approach to decrease or reflect incoming solar radiation with the goal of reducing global temperatures, which have increased over the last decades due to high atmospheric greenhouse gas concentrations. Stratospheric aerosol injection, specifically, has shown potential for successfully reducing global temperatures in climate model simulations. Despite the growing literature in the areas of climate change and SRM, their combined effects on renewable energy generation, a climate change mitigation strategy, have not been addressed. In this review paper, we synthesize previous literature on the possible effects of climate change and SRM on renewable energy resources (i.e., wind energy, solar energy, biomass energy, and hydropower), review the status of climate change and SRM research, and explore potential effects of SRM on renewable energy primarily in the Continental United States (CONUS), but with global perspectives as well. We discuss the research challenges and impacts of SRM on renewable energy and conclude by discussing the potential implications of SRM for renewables for SRM governance and policy. This work is not advocating for or against SRM. It is highlighting an important potential impact for future decision makers.

Kumler, Andrew [National Renewable Energy Laborato

HydroForecast Long-term: Improving hydropower’s resilience to climate change through accurate climate-scale

With hydrologic patterns and water availability across the globe shifting due to climate change, advancements in hydrologic prediction systems can help significantly reduce the uncertainties that utilities and water supply entities have in their decision making. Understanding and estimating hydrology at the climate scale is critical for managing water resources under changing climate scenarios. This project focuses on integrating state-of-the-art neural network modeling with downscaled climate projections to deliver the reliable water supply projections decades into the future to meet an urgent need from hydropower operators and water utilities. In this Phase 1 DOE SBIR proposal, we developed and validated a theory-guided neural network model, HydroForecast Long-term, for climate-scale hydrology and implemented the model within existing HydroForecast infrastructure. HydroForecast Long-term combines the most accurate streamflow modeling system with a flexible and scalable data architecture to generate water supply projections out to the year 2100. This report illustrates that we have achieved our four objectives: 1) create a prototype of HydroForecast Long-term, building the neural network prediction model, 2) build an automated data input pipeline that processes large amounts of data from the latest global temperature and precipitation climate models; 3) benchmark the accuracy of the hydrologic model over the recent two decades over a large set of diverse basins, and 4) create a set of output visuals and summary metrics informed by customer feedback that connect the data to critical decision points. This work empowers water users to make data-informed decisions supporting a resilient, renewable-powered grid and water system. The results advance the Department of Energy’s mission by addressing critical gaps in water supply planning under climate change.

13 HYDRO ENERGY

Urban agrivoltaics enhance crop resilience and food-energy synergies in a changing climate

Urban agrivoltaics, the synergistic integration of solar photovoltaics with urban agriculture, offers a transformative solution to food and energy insecurity, which are major barriers to sustainable urban development, especially in low-income urban areas facing intensified heat and water stress due to climate change. With 70% of the global population projected to live in cities by 2050, maximizing underutilized urban spaces is critical. Our study presents the first evaluation of ground-based agrivoltaics in an urban context, demonstrating that, while early-season yields may decline due to light reduction in temperate climates, productivity rebounds during periods of extreme heat, extending harvest windows and enhancing crop resilience. As cities seek climate-adaptive infrastructure, converting just a fraction of vacant land and rooftops to urban agrivoltaics can yield significant co-benefits such as generating renewable energy for thousands of households while supplying fresh produce to help alleviate food deserts.

14 SOLAR ENERGY

Granger causal inference for climate change attribution

Abstract Climate change detection and attribution (D&A) is concerned with determining the extent to which anthropogenic activities have influenced specific aspects of the global climate system. D&A fits within the broader field of causal inference, the collection of statistical methods that identify cause and effect relationships. There are a wide variety of methods for making attribution statements, each of which require different types of input data and focus on different types of weather and climate events and each of which are conditional to varying extents. Some methods are based on Pearl causality (direct experimental interference) while others leverage Granger (predictive) causality, and the causal framing provides important context for how the resulting attribution conclusion should be interpreted. However, while Granger-causal attribution analyses have become more common, there is no clear statement of their strengths and weaknesses relative to Pearl-causal attribution and no clear consensus on where and when Granger-causal perspectives are appropriate. In this prospective paper, we provide a formal definition for Granger-based approaches to trend and event attribution and a clear comparison with more traditional methods for assessing the human influence on extreme weather and climate events. Broadly speaking, Granger-causal attribution statements can be constructed quickly from observations and do not require computationally-intesive dynamical experiments. These analyses also enable rapid attribution, which is useful in the aftermath of a severe weather event, and provide multiple lines of evidence for anthropogenic climate change when paired with Pearl-causal attribution. Confidence in attribution statements is increased when different methodologies arrive at similar conclusions. Moving forward, we encourage the D&A community to embrace hybrid approaches to climate change attribution that leverage the strengths of both Granger and Pearl causality.

Risser, Mark D. (ORCID:0000000319561783)

Artificial Intelligence for Climate Change Mitigation Roadmap (Second Edition)

The first ICEF Artificial Intelligence for Climate Change Mitigation Roadmap was released in December 2023. Since that time, attention to artificial intelligence (AI) has continued to grow at a rapid pace. Tens of billions of dollars have poured into AI projects, policymakers around the world have considered new AI policies, and OpenAI reports that each month more than 200 million people now use ChatGPT. Signs of a changing climate continue to grow as well. Based on global average temperatures, July 22, 2024 was the warmest day ever recorded; 2023 was the warmest year ever recorded; and the 10 warmest years on record are the past 10 years. Yet global emissions of greenhouse gases continue to climb. Can AI help cut emissions of greenhouse gases? This Roadmap explores that question. In this second edition of the Artificial Intelligence for Climate Change Mitigation Roadmap, a team of 25 co-authors builds on last year’s roadmap—comprehensively updating all old chapters, adding six new chapters and offering 5–10 specific, actionable recommendations in each chapter. Our goal is to provide a useful resource for experts and non-experts alike. In Part I of this Roadmap, we provide brief introductions to both AI and climate change. In Part II, we explore eight sectors in which AI is helping respond to climate change and could do much more. In Part III, we explore crosscutting issues. We close with findings and recommendations.

54 ENVIRONMENTAL SCIENCES

Harvest legacies and climate change interact to shape forest structure and biomass through time

Forest structural change driven by climate trends has been observed worldwide and is expected to increase in the future. Management of forest structure has been an important tool for mitigating the impacts of climate change but forest structure may shift independently of management goals as it interacts with climate change. Here, we investigated the long-term impacts of harvest-based management strategies on structure and resistance to climate-induced biomass loss using a process-based ecosystem model for a midwestern USA hardwood forest. We identified aboveground biomass loss events and compared the cumulative number of these events following a five-year period of active management under four management strategies and two climate change scenarios. Management legacy had the clearest impact on climate-driven biomass loss over the mid-term (∼25 years) with the shelterwood scenario experiencing no loss events during this period. However, by the end of the century legacy effects faded and climate change severity became the driver of differences as greater warming scenarios experienced twice the loss events, and end-of-century loss events were 3–10 times more frequent than mid-century events. We found that while structure was distinct among harvest scenarios through the mid-century, differences were negligible by the end-of-century; identical to when management correlated with loss event frequency. Here, we found that loss events were preceded by a drop in precipitation two years prior, while no specific forest structure preceded a loss event. However, the structures preceding a biomass loss event were distinct across different legacies, implying additional influences of past management.

54 ENVIRONMENTAL SCIENCES

Ecological acclimation: A framework to integrate fast and slow responses to climate change

Ecological responses to climate change occur across vastly different time-scales, from minutes for physiological plasticity to decades or centuries for community turnover and evolutionary adaptation. Accurately predicting the range of ecosystem trajectories will require models that incorporate both fast processes that may keep pace with climate change and slower ones likely to lag behind and generate disequilibrium dynamics. However, the knowledge necessary for this integration is currently fragmented across disciplines. We develop ‘ecological acclimation’ as a unifying framework to emphasize the similarity of dynamics driven by processes operating on dramatically different time-scales and levels of biological organization. The framework focuses on ecoclimate sensitivities, measured as the change in an ecological response variable per unit of climate change. Acclimation processes acting at different time-scales cause these sensitivities to shift in magnitude and even direction over time. We highlight shifting ecoclimate sensitivities in case studies from diverse ecosystems, including terrestrial plant communities, coral reefs and soil microbiomes. Models predicting future ecosystem states inevitably make assumptions about acclimation processes; these assumptions must be explicit for users to evaluate whether a model is appropriate for a given forecast horizon. Similarly, decision frameworks that clearly account for multiple acclimation processes and their distinct time-scales will help natural resource managers plan for ecological impacts of climate change from years to many decades into the future. We outline a synthetic research programme focused on the time-scales of ecological acclimation to reduce uncertainty in ecological forecasts.

climate adaptation

Boundary spanning increases knowledge and action on invasive species in a changing climate

Abstract Challenges associated with global change stressors on ecosystems have prompted calls to improve actionable science, including through boundary‐spanning activities, which aim to build connections and communication between researchers and natural resource practitioners. By synthesizing and translating research and practitioner knowledge, boundary‐spanning activities could support proactive, research‐informed conservation practice, but the success of these efforts is rarely evaluated. Using repeat survey data from the Northeast Regional Invasive Species and Climate Change (NE RISCC) Management Network, a boundary‐spanning organization, we evaluate whether participating in NE RISCC affected practitioners' knowledge, actions and priorities related to invasive species management under a changing climate. Our survey results suggest that practitioners who participate in NE RISCC have greater knowledge about invasive species and climate change and are incorporating climate change in more ways into their invasive species management. We also found NE RISCC membership affected the perceived usefulness of informational resources, with NE RISCC members more frequently identifying research syntheses and targeted workshops (both are common products used by NE RISCC to translate science into practice and share manager knowledge) as useful compared to non‐members. Practitioners who participate in NE RISCC also identified somewhat different research priorities, with non‐members and short‐term members more frequently identifying range‐shifting neonative species and their impacts on native communities as higher priorities compared to long‐term NE RISCC members. NE RISCC research activities and outreach materials have consistently framed range‐shifting neonative species as comparatively low risk, suggesting that this information has influenced practitioner's perception of risk. Practical implication : Although real‐world impacts of applied ecology are notoriously difficult to quantify, this analysis illustrates that if research results are actively translated, they can affect the knowledge and actions of natural resource practitioners. These impacts illustrate the potential for boundary‐spanning efforts to address other global change challenges to conservation.

Evans, Annette E.

Human–Earth system interactions under climate change

This special issue, titled ‘Focus on human–Earth system interactions under climate change,’ compiles cutting-edge research that deepens our understanding of the complex feedback mechanisms between anthropogenic activities and Earth system processes in the context of a changing climate (figure 1). The featured articles employ a diverse array of methodologies—including field studies, remote sensing, modeling, and socio-ecological analyses—to explore these interconnections. A unifying theme across these contributions is the imperative to bridge disciplinary divides, integrating physical Earth sciences with social sciences to fully capture the spectrum of human-Earth system interactions. Key topics addressed the impacts of human activities on natural systems, encompassing land-use change and water resource management on biogeochemistry, climate dynamics, and feedback on the climate system and socioeconomics from local to global scales under a changing climate.

Li, Huidong [Vanderbilt Univ., Nashville, TN (Unit

Hydroclimate-coupled framework for assessing power system resilience under summer drought and climate change

Extreme drought, exacerbated by climate change, increasingly threatens power system resilience, and a systematic assessment of such impacts is challenging due to the unpredictability of drought and their associated modeling complexity. Here, to address the challenge, this research develops a hydroclimate-coupled power system resilience assessment framework that enables systematic modeling of drought and climate change impacts on generation, transmission, and demand sectors. Applying the framework to the 2025 Eastern U.S. power grid — comprising 6,055 at-risk generators — under climate-induced summer drought scenarios (including SSP126, SSP245, SSP370, and SSP585) from 2023 to 2100, the study finds that climate-induced droughts could jeopardize the power system’s reliability to a greater extent than historical events, potentially leading to widespread load shedding. More specifically, the study reveals that under the twenty-one representative drought scenarios, the loss of load expectation (LOLE) of the grid could range from 34.77 to 91.48 days per summer. The simulations indicate that implementing resilience enhancement strategies is crucial to ensure reliable system operation, which encompasses initiatives such as demand response, upgrading open cooling systems, and transmission expansion. In all, these findings underscore the urgent need for proactive planning and investment in resilient U.S. power systems to mitigate the impacts of extreme drought events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Climate change drives convergent evolution of root traits on Sky Island climate relicts

Roots are essential to the strategies plants use to survive in variable environments, yet we know little of how they vary within species. Experimental conditions demonstrate that intraspecific plant root traits respond strongly to variation in the environment; however, it is unclear when these responses can be characterized as evolution in response to selective pressures of climate change over many generations. Sky Islands are model, natural climate relict ecosystems to examine climate-change driven evolution. Utilizing a common garden with replicate genotypes of Populus angustifolia (Narrowleaf cottonwood) from six Sky Island (SI) populations and nine adjacent Mountain Chain (MC) populations across three genetic provenances, we hypothesized that SI root traits have diverged due to historical isolation in warmer, drier climates. When grown in common conditions, populations originating on SI’s showed convergent evolution across three distinct genetic provenances, which was characterized by 44.16% decreased total root length, 42.64% decreased average root volume, 43.31% decreased root surface area, and significantly less root trait variation, relative to adjacent mountain chains. Convergent evolution of root traits from trees originating on SI’s is correlated with changes in mean annual precipitation and potential evapotranspiration in the field over the past ~ 125 years. These results demonstrate a consistent pattern in root trait evolution at the landscape scale and the role of climate on the evolution of root traits in a genetic and geographic context relevant to climate change.

Convergent evolution

Climate change and federal aid disbursements after Hurricane Harvey: an extreme event attribution analysis

The role climate change plays in increasing the burden placed on governments and insurers to pay for recovery has not been extensively explored and is the focus of this study. This study examines the impacts of climate change attributed flooding on federal disaster aid disbursement in Harris County, Texas following Hurricane Harvey in 2017. Our approach uses flood models to estimate the amount of flood damages attributable and not attributable to climate change under two climate change attribution scenarios from peer reviewed studies: 20% and 38% increases in rainfall associated with the hurricane due to climate change. These estimates are combined with census tract-level disbursement data for FEMA’s National Flood Insurance Program (NFIP) and the Individual Assistance (IA) part of the Individuals and Households Program. We employ spatial lag regression models with direct and spatial spillover effects to analyze the relationship between a tract’s flood damages—both attributed and not attributed to climate change—and federal disaster aid. We find that both types of flood damage shape federal aid disbursements, but that climate change attributed damages tend to have larger effect sizes (elasticities) especially for IA. Specifically, for a 1% increase in additional climate change attributed damages per household in a census tract (under the 20% scenario), expected NFIP levels in that census tract are 0.26% higher and IA levels are 0.3% higher. Implications center on federal funding in an era of climate change.

FEMA

The impact of climate change on Korea’s agricultural sector under the national self-sufficiency policy

Evolving environmental conditions due to climate change have brought about changes in agriculture, which is required for human life as both a source of food and income. International trade can act as a buffer against potential negative impacts of climate change on crop yields, but recent years have seen breakdowns in global trade, including export bans to improve domestic food security. For countries that rely heavily on imported food, governments may institute policies to protect their agricultural industry from changes in climate-induced crop yield changes and other countries’ potential trade restrictions. This study assesses the individual and combined effects of climate impacts and food self-sufficiency policies in Korea, which is highly dependent on imports. We use the Global Change Analysis Model (GCAM), a global integrated assessment model, to explore (1) the direct impact of climate change on Korea’s agricultural yields, (2) the full impacts of global climate change on agricultural production, including trade-induced changes due to yield changes in other regions, (3) the impacts of food self-sufficiency policy, and (4) the interactive impact of climate change and self-sufficiency policies. We find that, in Korea, the direct impact of climate change on agricultural yields would be overshadowed by the impact of global climate change due to changing trade patterns. Second, global climate change leads to a rise (rice and wheat) or a decline (soybeans) in Korean producer revenues, while simultaneously raising consumer expenditures on both staples and non-staples. Third, implementing self-sufficiency policies for wheat and soybeans in Korea boosts the nation’s producer revenues, in conjunction with the effects of climate change, at the cost of additional increases in consumer expenditures for both staples and non-staples.

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