Temporal and spatial distribution of health, labor, and crop benefits of climate change mitigation in the United States.

Societal benefits from climate change mitigation accrue via multiple pathways. We examine the US impacts of emission changes on several factors that are affected by both climate and air quality responses. Nationwide benefits through midcentury stem primarily from air quality improvements, which are realized rapidly, and include human health, labor productivity, and crop yield benefits. Benefits from reduced heat exposure become large around 2060, thereafter often dominating over those from improved air quality. Monetized benefits are in the tens of trillions of dollars for avoided deaths and tens of billions for labor productivity and crop yield increases and reduced hospital expenditures. Total monetized benefits this century are dominated by health and are much larger than in previous analyses due to improved understanding of the human health impacts of exposure to both heat and air pollution. Benefit-cost ratios are therefore much larger than in prior studies, especially those that neglected clean air benefits. Specifically, benefits from clean air exceed costs in the first decade, whereas benefits from climate alone exceed costs in the latter half of the century. Furthermore, monetized US benefits largely stem from US emissions reductions. Increased emphasis on the localized, near-term air quality-related impacts would better align policies with societal benefits and, by reducing the mismatch between perception of climate as a risk distant in space and time and the need for rapid action to mitigate long-term climate change, might help increase acceptance of mitigation policies.

Societal shifts due to COVID-19 reveal large-scale complexities and feedbacks between atmospheric chemistry and climate change.

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NO x emissions. Second, the response of O3 to decreased NO x emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.

Fuel Use Trends for Boiling Water in Rural China (1992-2012) and Environmental Health Implications: A National Cross-Sectional Study.

Survey data from a comprehensive national survey of ∼34 000 households were analyzed for the mix status and transition trajectory of energy for boiling water in rural Chinese households from 1992 to 2012. In 1992, ∼6% of households reported using electricity, biogas, or liquefied petroleum gas (LPG) to boil drinking water; in 2012, the proportion was ∼60%. Income per capita appeared most strongly associated with this transition toward electricity and other clean fuels. Median annual incomes for households using biomass fuels, electric kettles, and LPG were RMB 15 000, 28 000, and 30 000, respectively. Overall, the transition was most pronounced in eastern China, a region which experienced relatively higher rates of economic growth over the same 20-year period. Energy type preferences appear to be highly dependent on fuel accessibility such that coal and straw usage was higher in provinces with higher coal and grain production. These trends suggest that electric kettle use would likely increase from ∼29% (2012) to ∼60% by 2030, at which point <5% of rural households would be expected to boil with solid fuels. Recent evidence suggests that this transition could contribute to reductions in water-related gastrointestinal illness as well as reductions in air pollutant emissions in rural China.

Direct Energy Consumption Associated Emissions by Rural-to-Urban Migrants in Beijing.

Hundreds of millions of rural residents have migrated to cities in China in recent years. Different lifestyles and living conditions lead to substantial changes in their household energy. Here, we present the result of a survey on direct household energy use of low-skilled rural-to-urban migrants in Beijing. The migrants moved up the energy ladder immediately after arriving in the city by replacing biomass fuels with coal, electricity, and liquefied petroleum gas. After the original shift, pattern of household energy use by the migrants has not changed much over decades, likely due to the long-existing household registration system (Hukou). As a result, the mix of energy types used by the rural-to-urban migrants were different from those by long-term urban residents, although total quantities were similar. Shifting from biomass fuels to coal, the migrants emitted 2.4 times more non-neutral CO2 than rural residents and 14% more than urban residents. The migration also resulted in significant increase in emissions of SO2 and mercury but dramatic decreases in some incomplete combustion products including particulate matter. All these changes have significant implication on air quality, health, and climate considering the scale of urbanization in China.

New concentration-response functions for seven morbidity endpoints associated with short-term PM2.5 exposure and their implications for health impact assessment.

BACKGROUND: Morbidity burdens from ambient air pollution are associated with market and non-market costs and are therefore important for policymaking. The estimation of morbidity burdens is based on concentration-response functions (CRFs). Most existing CRFs for short-term exposures to PM2.5 assume a fixed risk estimate as a log-linear function over an extrapolated exposure range, based on evidence primarily from Europe and North America. OBJECTIVES: We revisit these CRFs by performing a systematic review for seven morbidity endpoints previously assessed by the World Health Organization, including data from all available regions. These endpoints include all cardiovascular hospital admission, all respiratory hospital admission, asthma hospital admission and emergency room visit, along with the outcomes that stem from morbidity, such as lost work days, respiratory restricted activity days, and child bronchitis symptom days. METHODS: We estimate CRFs for each endpoint, using both a log-linear model and a nonlinear model that includes additional parameters to better fit evidence from high-exposure regions. We quantify uncertainties associated with these CRFs through randomization and Monte Carlo simulations. RESULTS: The CRFs in this study show reduced model uncertainty compared with previous CRFs in all endpoints. The nonlinear CRFs produce more than doubled global estimates on average, depending on the endpoint. Overall, we assess that our CRFs can be used to provide policy analysis of air pollution impacts at the global scale. It is however important to note that improvement of CRFs requires observations over a wide range of conditions, and current available literature is still limited. DISCUSSION: The higher estimates produced by the nonlinear CRFs indicates the possibility of a large underestimation in current assessments of the morbidity impacts attributable to air pollution. Further studies should be pursued to better constrain the CRFs studied here, and to better characterize the causal relationship between exposures to PM2.5 and morbidity outcomes.

New seasonal pattern of pollution emerges from changing North American wildfires.

Rising emissions from wildfires over recent decades in the Pacific Northwest are known to counteract the reductions in human-produced aerosol pollution over North America. Since amplified Pacific Northwest wildfires are predicted under accelerating climate change, it is essential to understand both local and transported contributions to air pollution in North America. Here, we find corresponding increases for carbon monoxide emitted from the Pacific Northwest wildfires and observe significant impacts on both local and down-wind air pollution. Between 2002 and 2018, the Pacific Northwest atmospheric carbon monoxide abundance increased in August, while other months showed decreasing carbon monoxide, so modifying the seasonal pattern. These seasonal pattern changes extend over large regions of North America, to the Central USA and Northeast North America regions, indicating that transported wildfire pollution could potentially impact the health of millions of people.

Exploration of the Global Burden of Dementia Attributable to PM2.5: What Do We Know Based on Current Evidence?

Exposure to ambient PM2.5 pollution has been linked to multiple adverse health effects. Additional effects have been identified in the literature and there is a need to understand its potential role in high prevalence diseases. In response to recent indications of PM2.5 as a risk factor for dementia, we examine the evidence by systematically reviewing the epidemiologic literature, in relation to exposure from ambient air pollution, household air pollution, secondhand smoke, and active smoking. We develop preliminary exposure-response functions, estimate the uncertainty, and discuss sensitivities and model selection. We estimate the likely impact to be 2.1 M (1.4 M, 2.5 M; 5%-95% confidence) global incident dementia cases and 0.6 M (0.4 M, 0.8 M) deaths attributable to ambient PM2.5 pollution in 2015. This implies a combined toll from morbidity and mortality of dementia of 7.3 M (5.0 M, 9.1 M) lost disability-adjusted life years. China, Japan, India, and the United States had the highest estimated total burden, and the per capita burden was highest in developed countries with large elderly populations. Compared to 2000, most countries in Europe, the Americas, and Southern Africa reduced the burden in 2015, while other regions had a net increase. Based on a recent systematic review of cost of illness studies for dementia, our estimates imply economic costs of US$ 26 billion worldwide in 2015. Based on this estimation, ambient PM2.5 pollution may be responsible for 15% of premature deaths and 7% of DALYs associated with dementia. Our estimates also indicate substantial uncertainty in this relationship, and future epidemiological studies at high exposure levels are especially needed.

The Effects of Heat Exposure on Human Mortality Throughout the United States.

Exposure to high ambient temperatures is an important cause of avoidable, premature death that may become more prevalent under climate change. Though extensive epidemiological data are available in the United States, they are largely limited to select large cities, and hence, most projections estimate the potential impact of future warming on a subset of the U.S. population. Here we utilize evaluations of the relative risk of premature death associated with temperature in 10 U.S. cities spanning a wide range of climate conditions to develop a generalized risk function. We first evaluate the performance of this generalized function, which introduces substantial biases at the individual city level but performs well at the large scale. We then apply this function to estimate the impacts of projected climate change on heat-related nationwide U.S. deaths under a range of scenarios. During the current decade, there are 12,000 (95% confidence interval 7,400-16,500) premature deaths annually in the contiguous United States, much larger than most estimates based on totals for select individual cities. These values increase by 97,000 (60,000-134,000) under the high-warming Representative Concentration Pathway (RCP) 8.5 scenario and by 36,000 (22,000-50,000) under the moderate RCP4.5 scenario by 2100, whereas they remain statistically unchanged under the aggressive mitigation scenario RCP2.6. These results include estimates of adaptation that reduce impacts by ~40-45% as well as population increases that roughly offset adaptation. The results suggest that the degree of climate change mitigation will have important health impacts on Americans.

Impacts of air pollutants from rural Chinese households under the rapid residential energy transition.

Rural residential energy consumption in China is experiencing a rapid transition towards clean energy, nevertheless, solid fuel combustion remains an important emission source. Here we quantitatively evaluate the contribution of rural residential emissions to PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 µm) and the impacts on health and climate. The clean energy transitions result in remarkable reductions in the contributions to ambient PM2.5, avoiding 130,000 (90,000-160,000) premature deaths associated with PM2.5 exposure. The climate forcing associated with this sector declines from 0.057 ± 0.016 W/m2 in 1992 to 0.031 ± 0.008 W/m2 in 2012. Despite this, the large remaining quantities of solid fuels still contributed 14 ± 10 µg/m3 to population-weighted PM2.5 in 2012, which comprises 21 ± 14% of the overall population-weighted PM2.5 from all sources. Rural residential emissions affect not only rural but urban air quality, and the impacts are highly seasonal and location dependent.

Impacts of rural worker migration on ambient air quality and health in China: From the perspective of upgrading residential energy consumption.

In China, rural migrant workers (RMWs) are employed in urban workplaces but receive minimal resources and welfare. Their residential energy use mix (REM) and pollutant emission profiles are different from those of traditional urban (URs) and rural residents (RRs). Their migration towards urban areas plays an important role in shaping the magnitudes and spatial patterns of pollutant emissions, ambient PM2.5 (fine particulate matter with a diameter smaller than 2.5 µm) concentrations, and associated health impacts in both urban and rural areas. Here we evaluate the impacts of RMW migration on REM pollutant emissions, ambient PM2.5, and subsequent premature deaths across China. At the national scale, RMW migration benefits ambient air quality because RMWs tend to transition to a cleaner REM upon arrival at urban areas-though not as clean as urban residents'. In 2010, RMW migration led to a decrease of 1.5 µg/m3 in ambient PM2.5 exposure concentrations (Cex) averaged across China and a subsequent decrease of 12,200 (5700 to 16,300, as 90% confidence interval) in premature deaths from exposure to ambient PM2.5. Despite the overall health benefit, large-scale cross-province migration increased megacities' PM2.5 levels by as much as 10 µg/m3 due to massive RMW inflows. Model simulations show that upgrading within-city RMWs' REMs can effectively offset the RMW-induced PM2.5 increase in megacities, and that policies that properly navigate migration directions may have potential for balancing the economic growth against ambient air quality deterioration. Our study indicates the urgency of considering air pollution impacts into migration-related policy formation in the context of rapid urbanization in China.

Urbanization-induced population migration has reduced ambient PM2.5 concentrations in China.

Direct residential and transportation energy consumption (RTC) contributes significantly to ambient fine particulate matter with a diameter smaller than 2.5 µm (PM2.5) in China. During massive rural-urban migration, population and pollutant emissions from RTC have evolved in terms of magnitude and geographic distribution, which was thought to worsen PM2.5 levels in cities but has not been quantitatively addressed. We quantify the temporal trends and spatial patterns of migration to cities and evaluate their associated pollutant emissions from RTC and subsequent health impact from 1980 to 2030. We show that, despite increased urban RTC emissions due to migration, the net effect of migration in China has been a reduction of PM2.5 exposure, primarily because of an unequal distribution of RTC energy mixes between urban and rural areas. After migration, people have switched to cleaner fuel types, which considerably lessened regional emissions. Consequently, the national average PM2.5 exposure concentration in 2010 was reduced by 3.9 µg/m3 (90% confidence interval, 3.0 to 5.4 µg/m3) due to migration, corresponding to an annual reduction of 36,000 (19,000 to 47,000) premature deaths. This reduction was the result of an increase in deaths by 142,000 (78,000 to 181,000) due to migrants swarming into cities and decreases in deaths by 148,000 (76,000 to 194,000) and 29,000 (15,000 to 39,000) due to transitions to a cleaner energy mix and lower urban population densities, respectively. Locally, however, megacities such as Beijing and Shanghai experienced increases in PM2.5 exposure associated with migration because these cities received massive immigration, which has driven a large increase in local emissions.