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Climate change is driving significant environmental changes with profound implications for human health, including fertility. While the detrimental effects of heat on spermatogenesis are well-documented, the impact of elevated temperatures on ovaries and female fertility remains less explored. This review systematically examines the literature on heat stress (HS) effects on mammalian ovaries, follicles, and oocytes. Evidence from mammalian models indicates that HS significantly impairs ovarian function, disrupting hormone profiles, reducing ovarian size and weight, altering histology, decreasing granulosa cell viability, and compromising oocyte quality. Efforts to develop strategies and substances to mitigate these adverse effects are ongoing, but further research into the underlying mechanisms is urgently needed.

Objective: To synthesize the methodologies of studies that evaluate the impacts of heat exposure on morbidity and mortality., Methods: Embase, MEDLINE, Web of Science, and Scopus were searched from date of inception until 1 March 2023 for English language literature on heat exposure and health outcomes. Records were collated, deduplicated and screened, and full texts were reviewed for inclusion and data abstraction. Eligibility for inclusion was determined as any article with climate-related heat exposure and an associated morbidity/mortality outcome., Results: Of 13,136 records initially identified, 237 articles were selected for analysis. The scope of research represented 43 countries, with most studies conducted in China (62), the USA (44), and Australia (16). Across all studies, there were 141 unique climate data sources, no standard threshold for extreme heat, and 200 unique health outcome data sources. The distributed lag non-linear model (DLNM) was the most common analytic method (48.1% of studies) and had high usage rates in China (68.9%) and the USA (31.8%); Australia frequently used conditional logistic regression (50%). Conditional logistic regression was most prevalent in case-control studies (5 of 8 studies, 62.5%) and in case-crossover studies (29 of 70, 41.4%). DLNMs were most common in time series studies (64 of 111, 57.7%) and ecological studies (13 of 20, 65.0%)., Conclusions: This review underscores the heterogeneity of methods in heat impact studies across diverse settings and provides a resource for future researchers. Underrepresentation of certain countries, health outcomes, and limited data access were identified as potential barriers., Competing Interests: The authors declare no conflicts of interest relevant to this study., (© 2024 The Author(s). GeoHealth published by Wiley Periodicals LLC on behalf of American Geophysical Union.)

Nitrogen dioxide (NO 2 ) is a regulated pollutant that is associated with numerous health impacts. Recent advances in epidemiology indicate high confidence linking NO 2 exposure with increased mortality, an association that recent studies suggest persists even at concentrations below regulatory thresholds. While large disparities in NO 2 exposure among population subgroups have been reported, U.S. NO 2 -attributable mortality rates and their disparities remain unquantified. Here we provide the first estimate of NO 2 -attributable all-cause mortality across the contiguous U.S. (CONUS) at the census tract-level. We leverage fine-scale, satellite-informed, land use regression model NO 2 concentrations and census tract-level baseline mortality data to characterize the associated disparities among different racial/ethnic subgroups. Across CONUS, we estimate that the NO 2 -attributable all-cause mortality is ∼170,850 (95% confidence interval: 43,970, 251,330) premature deaths yr -1 with large variability across census tracts and within individual cities. Additionally, we find that higher NO 2 concentrations and underlying susceptibilities for predominately Black communities lead to NO 2 -attributable mortality rates that are ∼47% higher compared to CONUS-wide average rates. Our results highlight the substantial U.S. NO 2 mortality burden, particularly in marginalized communities, and motivate adoption of more stringent standards to protect public health., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)

Purpose: To describe coronavirus disease 2019 (COVID-19) mortality in Chicago during the spring of 2020 and identify at the census-tract level neighborhood characteristics that were associated with higher COVID-19 mortality rates., Methods: Using Poisson regression and regularized linear regression (elastic net), we evaluated the association between neighborhood characteristics and COVID-19 mortality rates in Chicago through July 22 (2514 deaths across 795 populated census tracts)., Results: Black residents (31% of the population) accounted for 42% of COVID-19 deaths. Deaths among Hispanic/Latino residents occurred at a younger age (63 years, compared with 71 for white residents). Regarding residential setting, 52% of deaths among white residents occurred inside nursing homes, compared with 35% of deaths among black residents and 17% among Hispanic/Latino residents. Higher COVID-19 mortality was seen in neighborhoods with heightened barriers to social distancing and low health insurance coverage. Neighborhoods with a higher percentage of white and Asian residents had lower COVID-19 mortality. The associations differed by race, suggesting that neighborhood context may be most tightly linked to COVID-19 mortality among white residents., Conclusions: We describe communities that may benefit from supportive services and identify traits of communities that may benefit from targeted campaigns for prevention and testing to prevent future deaths from COVID-19., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Electric vehicle (EV) adoption promises potential air pollutant and greenhouse gas (GHG) reduction co-benefits. As such, China has aggressively incentivized EV adoption, however much remains unknown with regard to EVs' mitigation potential, including optimal vehicle type prioritization, power generation contingencies, effects of Clean Air regulations, and the ability of EVs to reduce acute impacts of extreme air quality events. Here, we present a suite of scenarios with a chemistry transport model that assess the potential co-benefits of EVs during an extreme winter air quality event. We find that regardless of power generation source, heavy-duty vehicle (HDV) electrification consistently improves air quality in terms of NO 2 and fine particulate matter (PM 2.5 ), potentially avoiding 562 deaths due to acute pollutant exposure during the infamous January 2013 pollution episode (~1% of total premature mortality). However, HDV electrification does not reduce GHG emissions without enhanced emission-free electricity generation. In contrast, due to differing emission profiles, light-duty vehicle (LDV) electrification in China consistently reduces GHG emissions (~2 Mt CO 2 ), but results in fewer air quality and human health improvements (145 avoided deaths). The calculated economic impacts for human health endpoints and CO 2 reductions for LDV electrification are nearly double those of HDV electrification in present-day (155M vs. 87M US$), but are within ~25% when enhanced emission-free generation is used to power them. Overall, we find only a modest benefit for EVs to ameliorate severe wintertime pollution events, and that continued emission reductions in the power generation sector will have the greatest human health and economic benefits.

Background: Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers., Objective: The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions., Methods: An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies., Results: The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting., Discussion: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice. https://doi.org/10.1289/EHP6745.

Vehicle electrification is a common climate change mitigation strategy, with policymakers invoking co-beneficial reductions in carbon dioxide (CO 2 ) and air pollutant emissions. However, while previous studies of U.S. electric vehicle (EV) adoption consistently predict CO 2 mitigation benefits, air quality outcomes are equivocal and depend on policies assessed and experimental parameters. We analyze climate and health co-benefits and trade-offs of six U.S. EV adoption scenarios: 25% or 75% replacement of conventional internal combustion engine vehicles, each under three different EV-charging energy generation scenarios. We transfer emissions from tailpipe to power generation plant, simulate interactions of atmospheric chemistry and meteorology using the GFDL-AM4 chemistry climate model, and assess health consequences and uncertainties using the U.S. Environmental Protection Agency Benefits Mapping Analysis Program Community Edition (BenMAP-CE). We find that 25% U.S. EV adoption, with added energy demand sourced from the present-day electric grid, annually results in a ~242 M ton reduction in CO 2 emissions, 437 deaths avoided due to PM 2.5 reductions (95% CI: 295, 578), and 98 deaths avoided due to lesser ozone formation (95% CI: 33, 162). Despite some regions experiencing adverse health outcomes, ~$16.8B in damages avoided are predicted. Peak CO 2 reductions and health benefits occur with 75% EV adoption and increased emission-free energy sources (~$70B in damages avoided). When charging-electricity from aggressive EV adoption is combustion-only, adverse health outcomes increase substantially, highlighting the importance of low-to-zero emission power generation for greater realization of health co-benefits. Our results provide a more nuanced understanding of the transportation sector's climate change mitigation-health impact relationship., Competing Interests: The authors declare no conflicts of interest relevant to this study., (©2020. The Authors.)

Shoreline erosion can transition freshwater coastal wetlands from carbon sinks to carbon sources. No studies have explored the impacts of coastal geomorphic processes on freshwater wetland carbon budgets. To do so, we modified a saltmarsh carbon budget model for application in freshwater coastal wetlands. We validated the model with data from a shoreline wetland in the Laurentian Great Lakes. The model generates the carbon budget by differencing carbon export and carbon storage. The inputs for carbon storage are the carbon inventory and maximum wetland age. Inputs for carbon export include erosion rates and overwash extent. The model demonstrates that the wetland examined in this study transitioned to a source of carbon during periods of erosion. In fact, the net carbon export between 2015 and 2018 was 10% of the wetland's original carbon stock. This study indicates that geomorphic change can dictate whether and how freshwater coastal wetlands serve as sources or sinks for terrestrial carbon, and that carbon stocks can fluctuate on a geologically rapid timescale. We recommend that such geomorphic processes be considered when developing carbon budgets for these marginal environments. Furthermore, the carbon budget model refined in this study can be used to prioritize wetlands in land management and conservation efforts.

Human and natural systems have adapted to and evolved within historical climatic conditions. Anthropogenic climate change has the potential to alter these conditions such that onset of unprecedented climatic extremes will outpace evolutionary and adaptive capabilities. To assess whether and when future climate extremes exceed their historical windows of variability within impact-relevant socioeconomic, geopolitical, and ecological domains, we investigate the timing of perceivable changes (time of emergence; TOE) for 18 magnitude-, frequency-, and severity-based extreme temperature (10) and precipitation (8) indices using both multimodel and single-model multirealization ensembles. Under a high-emission scenario, we find that the signal of frequency- and severity-based temperature extremes is projected to rise above historical noise earliest in midlatitudes, whereas magnitude-based temperature extremes emerge first in low and high latitudes. Precipitation extremes demonstrate different emergence patterns, with severity-based indices first emerging over midlatitudes, and magnitude- and frequency-based indices emerging earliest in low and high latitudes. Applied to impact-relevant domains, simulated TOE patterns suggest (a) unprecedented consecutive dry day occurrence in >50% of 14 terrestrial biomes and 12 marine realms prior to 2100, (b) earlier perceivable changes in climate extremes in countries with lower per capita GDP, and (c) emergence of severe and frequent heat extremes well-before 2030 for the 590 most populous urban centers. Elucidating extreme-metric and domain-type TOE heterogeneities highlights the challenges adaptation planners face in confronting the consequences of elevated twenty-first century radiative forcing., (© 2018 John Wiley & Sons Ltd.)

Efforts to understand the influence of historical global warming on individual extreme climate events have increased over the past decade. However, despite substantial progress, events that are unprecedented in the local observational record remain a persistent challenge. Leveraging observations and a large climate model ensemble, we quantify uncertainty in the influence of global warming on the severity and probability of the historically hottest month, hottest day, driest year, and wettest 5-d period for different areas of the globe. We find that historical warming has increased the severity and probability of the hottest month and hottest day of the year at >80% of the available observational area. Our framework also suggests that the historical climate forcing has increased the probability of the driest year and wettest 5-d period at 57% and 41% of the observed area, respectively, although we note important caveats. For the most protracted hot and dry events, the strongest and most widespread contributions of anthropogenic climate forcing occur in the tropics, including increases in probability of at least a factor of 4 for the hottest month and at least a factor of 2 for the driest year. We also demonstrate the ability of our framework to systematically evaluate the role of dynamic and thermodynamic factors such as atmospheric circulation patterns and atmospheric water vapor, and find extremely high statistical confidence that anthropogenic forcing increased the probability of record-low Arctic sea ice extent., Competing Interests: The authors declare no conflict of interest.

The effect of global climate change on infectious disease remains hotly debated because multiple extrinsic and intrinsic drivers interact to influence transmission dynamics in nonlinear ways. The dominant drivers of widespread pathogens, like West Nile virus, can be challenging to identify due to regional variability in vector and host ecology, with past studies producing disparate findings. Here, we used analyses at national and state scales to examine a suite of climatic and intrinsic drivers of continental-scale West Nile virus epidemics, including an empirically derived mechanistic relationship between temperature and transmission potential that accounts for spatial variability in vectors. We found that drought was the primary climatic driver of increased West Nile virus epidemics, rather than within-season or winter temperatures, or precipitation independently. Local-scale data from one region suggested drought increased epidemics via changes in mosquito infection prevalence rather than mosquito abundance. In addition, human acquired immunity following regional epidemics limited subsequent transmission in many states. We show that over the next 30 years, increased drought severity from climate change could triple West Nile virus cases, but only in regions with low human immunity. These results illustrate how changes in drought severity can alter the transmission dynamics of vector-borne diseases., (© 2017 The Author(s).)

During the winters of 2013-2014 and 2014-2015, anomalously warm temperatures in western North America and anomalously cool temperatures in eastern North America resulted in substantial human and environmental impacts. Motivated by the impacts of these concurrent temperature extremes and the intrinsic atmospheric linkage between weather conditions in the western and eastern United States, we investigate the occurrence of concurrent "warm-West/cool-East" surface temperature anomalies, which we call the "North American winter temperature dipole." We find that, historically, warm-West/cool-East dipole conditions have been associated with anomalous mid-tropospheric ridging over western North America and downstream troughing over eastern North America. We also find that the occurrence and severity of warm-West/cool-East events have increased significantly between 1980 and 2015, driven largely by an increase in the frequency with which high-amplitude "ridge-trough" wave patterns result in simultaneous severe temperature conditions in both the West and East. Using a large single-model ensemble of climate simulations, we show that the observed positive trend in the warm-West/cool-East events is attributable to historical anthropogenic emissions including greenhouse gases, but that the co-occurrence of extreme western warmth and eastern cold will likely decrease in the future as winter temperatures warm dramatically across the continent, thereby reducing the occurrence of severely cold conditions in the East. Although our analysis is focused on one particular region, our analysis framework is generally transferable to the physical conditions shaping different types of extreme events around the globe.

Recent evidence suggests that changes in atmospheric circulation have altered the probability of extreme climate events in the Northern Hemisphere. We investigate northeastern Pacific atmospheric circulation patterns that have historically (1949-2015) been associated with cool-season (October-May) precipitation and temperature extremes in California. We identify changes in occurrence of atmospheric circulation patterns by measuring the similarity of the cool-season atmospheric configuration that occurred in each year of the 1949-2015 period with the configuration that occurred during each of the five driest, wettest, warmest, and coolest years. Our analysis detects statistically significant changes in the occurrence of atmospheric patterns associated with seasonal precipitation and temperature extremes. We also find a robust increase in the magnitude and subseasonal persistence of the cool-season West Coast ridge, resulting in an amplification of the background state. Changes in both seasonal mean and extreme event configurations appear to be caused by a combination of spatially nonuniform thermal expansion of the atmosphere and reinforcing trends in the pattern of sea level pressure. In particular, both thermal expansion and sea level pressure trends contribute to a notable increase in anomalous northeastern Pacific ridging patterns similar to that observed during the 2012-2015 California drought. Collectively, our empirical findings suggest that the frequency of atmospheric conditions like those during California's most severely dry and hot years has increased in recent decades, but not necessarily at the expense of patterns associated with extremely wet years.

Surface weather conditions are closely governed by the large-scale circulation of the Earth's atmosphere. Recent increases in the occurrence of some extreme weather phenomena have led to multiple mechanistic hypotheses linking changes in atmospheric circulation to increasing probability of extreme events. However, observed evidence of long-term change in atmospheric circulation remains inconclusive. Here we identify statistically significant trends in the occurrence of atmospheric circulation patterns, which partially explain observed trends in surface temperature extremes over seven mid-latitude regions of the Northern Hemisphere. Using self-organizing map cluster analysis, we detect robust circulation pattern trends in a subset of these regions during both the satellite observation era (1979-2013) and the recent period of rapid Arctic sea-ice decline (1990-2013). Particularly substantial influences include the contribution of increasing trends in anticyclonic circulations to summer and autumn hot extremes over portions of Eurasia and North America, and the contribution of increasing trends in northerly flow to winter cold extremes over central Asia. Our results indicate that although a substantial portion of the observed change in extreme temperature occurrence has resulted from regional- and global-scale thermodynamic changes, the risk of extreme temperatures over some regions has also been altered by recent changes in the frequency, persistence and maximum duration of regional circulation patterns.

Poor air quality causes an estimated 2.6 to 4.4 million premature deaths per year 1-3 . Hazardous conditions form when meteorological components allow the accumulation of pollutants in the near-surface atmosphere 4-8 . Global warming-driven changes to atmospheric circulation and the hydrological cycle 9-13 are expected to alter the meteorological components that control pollutant build-up and dispersal 5-8,14 , but the magnitude, direction, geographic footprint, and public health impact of this alteration remain unclear 7,8 . We utilize an air stagnation index and an ensemble of bias-corrected climate model simulations to quantify the response of stagnation occurrence and persistence to global warming. Our analysis projects increases in stagnation occurrence that cover 55% of the current global population, with areas of increase affecting 10 times more people than areas of decrease. By the late-21 st century, robust increases of up to 40 days per year are projected throughout the majority of the tropics and subtropics, as well as within isolated mid-latitude regions. Potential impacts over India, Mexico, and the western U.S. are particularly acute due to the intersection of large populations and increases in the persistence of stagnation events, including those of extreme duration. These results indicate that anthropogenic climate change is likely to alter the level of pollutant management required to meet future air quality targets.

Stagnant atmospheric conditions can lead to hazardous air quality by allowing ozone and particulate matter to accumulate and persist in the near-surface environment. By changing atmospheric circulation and precipitation patterns, global warming could alter the meteorological factors that regulate air stagnation frequency. We analyze the response of the National Climatic Data Center (NCDC) Air Stagnation Index (ASI) to anthropogenically enhanced radiative forcing using global climate model projections of late-21(st) century climate change (SRES A1B scenario). Our results indicate that the atmospheric conditions over the highly populated, highly industrialized regions of the eastern United States, Mediterranean Europe, and eastern China are particularly sensitive to global warming, with the occurrence of stagnant conditions projected to increase 12-to-25% relative to late-20(th) century stagnation frequencies (3-18+ days/year). Changes in the position/strength of the polar jet, in the occurrence of light surface winds, and in the number of precipitation-free days all contribute to more frequent late-21(st) century air mass stagnation over these high-population regions. In addition, we find substantial inter-model spread in the simulated response of stagnation conditions over some regions using either native or bias corrected global climate model simulations, suggesting that changes in the atmospheric circulation and/or the distribution of precipitation represent important sources of uncertainty in the response of air quality to global warming.

Through use of multivariate statistical and research techniques, the authors analyzed 30 hospital features that contribute to a physician's image of a hospital as being a good or a poor place for patient admission and in which to practice. Use of the data obtained in this study can enable a hospital administrator to monitor changes in physicians' attitudes, plan strategies to encourage quality physicians to admit their patients, improve aspects perceived to be weak or unresponsive, and capitalize on strengths.

It is now apparent that venom and venom components of the Hymenoptera superfamilies of Apida (honeybee) and Vespida (wasps, yellow jackets, and hornets) are becoming increasingly important in the diagnosis and treatment of hypersensitivity reactions. Stings from fire ants (superfamily Formicidae, family Myrmicinae) have also been recognized as causes of systemic reactions in man. Fire ant venom is unique in its composition, consisting mainly of alkaloids in aqueous suspension with only trace amounts of protein. This study compares the skin reactivity of fire ant venom and synthesized alkaloid components with the whole body extract (WBE) of fire ants and other Hymenoptera. The venom as well as the WBE of fire ants was found useful for skin test diagnosis of sensitive individuals. There appear to be cross-reactive or shared antigens between fire ant venom, WBE, and WBE of other Hymenoptera. Successful passive transfer of skin reactivity to nonsensitive individuals was accomplished with sera from sensitive individuals. Loss of this passive transfer by heating sera at 56 degrees C for 4 hr is evidence in favor of IgE mediating the positive skin test to the venom.