Access to urban natural space, including blue and greenspace, is associated with improved health. In 2021, the C40 Cities Climate Leadership Group set 2030 Urban Nature Declaration (UND) targets: “Quality Total Cover” (30% green area within each city) and “Equitable Spatial Distribution” (70% of the population living close to natural space). We evaluate progress towards these targets in the 96 C40 cities using globally available, high-resolution datasets for landcover and normalized difference vegetation index (NDVI). We use the European Space Agency (ESA)’s WorldCover dataset to define greenspace with discrete landcover categories and ESA’s Sentinel-2A to calculate NDVI, adding the ‘open water’ landcover category to characterize total natural space. We compare 2020 levels of urban green and natural space to the two UND targets and predict the city-specific NDVI level consistent with the UND targets using linear regressions. The 96-city mean NDVI was 0.538 (range: 0.148, 0.739). Most (80%) cities meet the Quality Total Cover target, and nearly half (47%) meet the Equitable Spatial Distribution target. Landcover-measured greenspace and total natural space were strong (mean R2 = 0.826) and moderate (mean R2=0.597) predictors of NDVI and our NDVI-based natural space proximity measure, respectively. The 96-city mean predicted NDVI value of meeting the UND targets was 0.478 (range: 0.352-0.565) for Quality Total Cover and 0.660 (range: 0.498-0.767) for Equitable Spatial Distribution. Our translation of the area- and access-based metrics common in urban natural space targets into the NDVI metric used in epidemiology allows for quantifying the health benefits of achieving such targets.

Air pollution levels are uneven within cities, contributing to persistent health disparities between neighborhoods and population sub-groups. Highly spatially resolved information on pollution levels and disease rates is necessary to characterize inequities in air pollution exposure and related health We leverage recent advances in deriving surface pollution levels from satellite remote sensing and granular data in disease rates for one city, Washington, DC, to assess intra-urban heterogeneity in fine particulate matter (PM5)- attributable mortality and We estimate PM2.5-attributable cases of all-cause mortality, chronic obstructive pulmonary disease, ischaemic heart disease, lung cancer, stroke, and asthma emergency department (ED) visits using epidemiologically-derived health impact Data inputs include satellite-derived annual mean surface PM5 concentrations; age-resolved population estimates; and statistical neighborhood-, zip code- and ward-scale disease counts. We find that PM5 concentrations and associated health burdens have decreased in DC between 2000 and 2018, from approximately 240 to 120 cause-specific deaths and from 40 to 30 asthma ED visits per year (between 2014 and 2018). However, remaining PM5-attributable health risks are unevenly and inequitably distributed across the Higher PM2.5-attributable disease burdens were found in neighborhoods with larger proportions of people of color, lower household income, and lower educational Our study adds to the growing body of literature documenting the inequity in air pollution exposure levels and pollution health risks between population sub-groups, and highlights the need for both high-resolution disease rates and concentration estimates for understanding intra-urban disparities in air pollution-related health risks.

This paper represents the first national-level (United States) estimate of the economic impacts of vibriosis cases as exacerbated by climate change. Vibriosis is an illness contracted through foodborne and waterborne exposures to various Vibrio species (e.g., non-V. cholerae O1 and O139 serotypes) found in estuarine and marine environments, including within aquatic life such as shellfish and finfish. Objectives The objective of this study was to project climate-induced changes in vibriosis related to sea surface temperatures (SSTs) and associated economic impacts in the U.S. Methods Our analysis constructed three logistic regression models by Vibrio species, using vibriosis data sourced from the Cholera and Other Vibrio Illness Surveillance (COVIS) system and using historical SSTs. We relied on previous estimates of the cost-per-case of vibriosis to estimate future total annual medical costs, lost income from productivity loss, and mortality-related indirect costs throughout the U.S. We separately report results for V. parahaemolyticus, V. vulnificus, V. alginolyticus, and “V. spp” given the different associated health burden of each. Results By 2090, increases in SST are estimated to result in a 51 percent increase in cases annually relative to the baseline era (1995) under Representative Concentration Pathway (RCP) 4.5 and a 108 percent increase under RCP8.5. The cost of these illnesses is projected to reach over $5.2 billion annually under RCP4.5 and $7.3 billion annually under RCP8.5, relative to $2.2 billion in the baseline (2018 dollars), equivalent to 140 percent and 234 percent increases respectively. Discussion Vibriosis incidence is likely to increase in the U.S. under moderate and unmitigated climate change scenarios through increases in SST, resulting in a substantial burden of morbidity and mortality, and costing millions of dollars. These costs are mostly attributable to deaths, primarily from exposure to V. vulnificus. Evidence suggests that other factors, including sea surface salinity, may contribute to further increases in vibriosis cases in some regions of the U.S. and should be investigated.

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-climate 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 NO2 and fine particulate matter (PM2.5), 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 CO2), but results in fewer air quality and human health improvements (145 avoided deaths). The calculated economic impacts for human health endpoints and CO2 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.

Increasing wildfire activity across the Western US poses a significant public health threat. While there is evidence that wildfire smoke is detrimental for respiratory health, the impacts on cardiovascular health remain unclear. This study evaluates the association between fine particulate matter (PM2.5) from wildfire smoke and cardiorespiratory hospital visits in California during the 2004-2009 wildfire seasons. We estimate daily mean wildfire-specific PM2.5 with GEOS-Chem, a global three-dimensional model of atmospheric chemistry, with wildfire emissions from the Global Fire Emissions Database (GFED3). We defined a “smoke event day” as cumulative 0-1-day lag wildfire-specific PM2.5>= 98th percentile of cumulative 0-1 lag day wildfire PM2.5. Associations between exposure and outcomes are estimated using negative binomial regression. Results indicate that smoke event days are associated with a 3.3% (95% CI: [0.4%,6.3%]) increase in visits for all respiratory diseases and a 10.3% (95% CI: [2.3%,19.0%]) increase for asthma specifically. Stratifying by age, we found the largest effect for asthma among children ages 0-5y. We observed no significant association between exposure and overall cardiovascular disease, but stratified analyses revealed increases in visits for all cardiovascular, ischemic heart disease, and heart failure among non-Hispanic white individuals and those older than 65y. Further, we found significant interaction between smoke event days and daily temperature for all cardiovascular disease visits, suggesting that days with high wildfire PM2.5 and high temperatures may pose greater disease risk. These results suggest increases in adverse outcomes from wildfire smoke exposure and indicate the need for improved prevention and adaptations to protect vulnerable populations.