Long-term trends in the ambient PM2.5- and O3-related mortality burdens in the United States under emission reductions from 1990 to 2010

Health benefits from the rapid reduction in ambient exposure to air pollutants after China's clean air actions: progress in efficacy and geographic equality

Clean air actions (CAAs) in China have been linked to considerable benefits in public health. However, whether the beneficial effects of CAAs are equally distributed geographically is unknown. Using high-resolution maps of the distributions of major air pollutants (fine particulate matter [PM2.5] and ozone [O3]) and population, we aimed to track spatiotemporal changes in health impacts from, and geographic inequality embedded in, the reduced exposures to PM2.5 and O3 from 2013 to 2020. We used a method established by the Global Burden of Diseases Study. By analyzing the changes in loss of life expectancy (LLE) attributable to PM2.5 and O3, we calculated the gain of life expectancy (GLE) to quantify the health benefits of the air-quality improvement. Finally, we assessed the geographic inequality embedded in the GLE using the Gini index (GI). Based on risk assessments of PM2.5 and O3, during the first stage of CAAs (2013 to 2017), the mean GLE was 1.87 months. Half of the sum of the GLE was disproportionally distributed in about one quarter of the population exposed (GI 0.44). During the second stage of CAAs (2017 to 2020), the mean GLE increased to 3.94 months and geographic inequality decreased (GI 0.18). According to our assessments, CAAs were enhanced, from the first to second stages, in terms of not only preventing premature mortality but also ameliorating health inequalities. The enhancements were related to increased sensitivity to the health effects of air pollution and synergic control of PM2.5 and O3 levels. Our findings will contribute to optimizing future CAAs.

Decoding the effect of demographic factors on environmental health based on city-level PM2.5 pollution in China

Although considerable health effects are gained from air quality improvement action plans implemented in China recently, they may have been amplified or offset due to the complexity and uncertainty of the changing demographic factors. In this study, we developed a framework for analyzing the effects of demographic factors on environmental health effects, focusing on three aspects: population scale, age structure, and spatial distribution. We quantified the above three effects by investigating how the health endpoint changed by the three demographic factors, based on a strategy of counterfactual and step-by-step relaxing hypothesis. We found that the increasing population scale and population aging caused 44,279 to 292,442 premature deaths, which offset the health effect of air quality improvement efforts for China. The change in population spatial distribution, in general, has little impact on the health effects of air quality improvement. Furthermore, the three effects are distributed unevenly across regions, especially the spatial distribution effect. Considering the widespread effect of demographic factors, PM2.5 concentration should be further reduced, and the aged population and mega-cities should be targeted for managing air quality in a cost-effective manner.

Long-term mortality burden trends attributed to black carbon and PM2·5 from wildfire emissions across the continental USA from 2000 to 2020: a deep learning modelling study

BACKGROUND

Long-term improvements in air quality and public health in the continental USA were disrupted over the past decade by increased fire emissions that potentially offset the decrease in anthropogenic emissions. This study aims to estimate trends in black carbon and PM2·5 concentrations and their attributable mortality burden across the USA.

METHODS

In this study, we derived daily concentrations of PM2·5 and its highly toxic black carbon component at a 1-km resolution in the USA from 2000 to 2020 via deep learning that integrated big data from satellites, models, and surface observations. We estimated the annual PM2·5-attributable and black carbon-attributable mortality burden at each 1-km2 grid using concentration-response functions collected from a national cohort study and a meta-analysis study, respectively. We investigated the spatiotemporal linear-regressed trends in PM2·5 and black carbon pollution and their associated premature deaths from 2000 to 2020, and the impact of wildfires on air quality and public health.

FINDINGS

Our results showed that PM2·5 and black carbon estimates are reliable, with sample-based cross-validated coefficients of determination of 0·82 and 0·80, respectively, for daily estimates (0·97 and 0·95 for monthly estimates). Both PM2·5 and black carbon in the USA showed significantly decreasing trends overall during 2000 to 2020 (22% decrease for PM2·5 and 11% decrease for black carbon), leading to a reduction of around 4200 premature deaths per year (95% CI 2960-5050). However, since 2010, the decreasing trends of fine particles and premature deaths have reversed to increase in the western USA (55% increase in PM2·5, 86% increase in black carbon, and increase of 670 premature deaths [460-810]), while remaining mostly unchanged in the eastern USA. The western USA showed large interannual fluctuations that were attributable to the increasing incidence of wildfires. Furthermore, the black carbon-to-PM2·5 mass ratio increased annually by 2·4% across the USA, mainly due to increasing wildfire emissions in the western USA and more rapid reductions of other components in the eastern USA, suggesting a potential increase in the relative toxicity of PM2·5. 100% of populated areas in the USA have experienced at least one day of PM2·5 pollution exceeding the daily air quality guideline level of 15 μg/m3 during 2000-2020, with 99% experiencing at least 7 days and 85% experiencing at least 30 days. The recent widespread wildfires have greatly increased the daily exposure risks in the western USA, and have also impacted the midwestern USA due to the long-range transport of smoke.

INTERPRETATION

Wildfires have become increasingly intensive and frequent in the western USA, resulting in a significant increase in smoke-related emissions in populated areas. This increase is likely to have contributed to a decline in air quality and an increase in attributable mortality. Reducing fire risk via effective policies besides mitigation of climate warming, such as wildfire prevention and management, forest restoration, and new revenue generation, could substantially improve air quality and public health in the coming decades.

FUNDING

National Aeronautics and Space Administration (NASA) Applied Science programme, NASA MODIS maintenance programme, NASA MAIA satellite mission programme, NASA GMAO core fund, National Oceanic and Atmospheric Administration (NOAA) GEO-XO project, NOAA Atmospheric Chemistry, Carbon Cycle, and Climate (AC4) programme, and NOAA Educational Partnership Program with Minority Serving Institutions.

Drivers of ozone-related premature mortality in China: Implications for historical and future scenarios

Long-term exposure to ambient ozone (O3) poses a severe public health threat in China. However, the drivers of premature mortality caused by O3 pollution are still poorly constrained, despite being prerequisites for addressing the threat. Here, we demonstrate the contributions of historical and future changes in peak-season O3, population size, age structure, and baseline mortality to China's O3-related mortality using decomposition analysis. From 2013 to 2021, O3-related mortality decreased dramatically from 78.8 (40.8-124.6) to 68.7 (36.0-107.2) thousand, especially in densely populated areas with high pollution. Variations in peak-season O3, population size, age structure, and baseline mortality led to changes in O3-related mortality of +27.3 (14.8-41.3), +2.6 (1.4-4.1), +22.3 (11.5-35.2), and -40.3 (20.9-63.7) thousand, respectively. The influence of peak-season O3 on O3-related mortality shifted from positive during 2013-2019 (+8.4% per year) to negative during 2019-2021 (-8.8% per year), which highly regulated the interannual trend of mortality. From 2021 to 2035, O3-related mortality is expected to increase by 31% in the current context of peak-season O3 levels, primarily caused by increased aging. Even reducing peak-season O3 to the WHO interim target 1 (IT-1) would only reduce O3-related mortality by 3.9%, while a more rigorous standard (IT-2) would prevent 83.7% of mortality. These findings suggest that improving ambient O3 can lead to significant health benefits, but substantial mitigation strategies are merited given the future trend of population aging.

Assessing the health impacts of PM2.5 and ozone pollution and their comprehensive correlation in Chinese cities based on extended correlation coefficient

The coordinated control of PM_2.5 and ozone pollution is becoming more and more important in the current and next stage of Chinese environmental pollution control. Existing studies are unable to provide sufficient quantitative assessments of the correlation of PM_2.5 and ozone pollution to support the coordinated control of the two air pollutants. This study develops a systematic method to comprehensively assess the correlation between PM_2.5 and ozone pollution, including the evaluation of the impact of two air pollutants on human health and the extended correlation coefficient (ECC) for assessing the bivariate correlation index of PM_2.5-ozone pollution in Chinese cities. According to the latest studies on epidemiology conducted in China, we take cardiovascular and cerebrovascular diseases and respiratory diseases as the ozone pollution's health burden when evaluating the health impact of ozone pollution. The results show that the health impact of PM_2.5 in China decreases by 25.9 % from 2015 to 2021, while the health impact of ozone increases by 11.8 %. The ECC of 335 cities in China shows an increasing-decreasing trend but has generally increased from 2015 to 2021. The study provides important support for an in-depth understanding of the correlation and development trend of Chinese PM_2.5 and ozone pollution by classifying the comprehensive PM_2.5-ozone correlation performances of Chinese cities into four types. China or other countries will get better environmental benefits by implementing different coordinated management approaches for different correlative types of regions based on the assessment method in this study.

Organic Semiconducting Nanoparticles for Biosensor: A Review

Highly bio-compatible organic semiconductors are widely used as biosensors, but their long-term stability can be compromised due to photo-degradation and structural instability. To address this issue, scientists have developed organic semiconductor nanoparticles (OSNs) by incorporating organic semiconductors into a stable framework or self-assembled structure. OSNs have shown excellent performance and can be used as high-resolution biosensors in modern medical and biological research. They have been used for a wide range of applications, such as detecting small biological molecules, nucleic acids, and enzyme levels, as well as vascular imaging, tumor localization, and more. In particular, OSNs can simulate fine particulate matters (PM_2.5, indicating particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) and can be used to study the biodistribution, clearance pathways, and health effects of such particles. However, there are still some problems that need to be solved, such as toxicity, metabolic mechanism, and fluorescence intensity. In this review, based on the structure and design strategies of OSNs, we introduce various types of OSNs-based biosensors with functional groups used as biosensors and discuss their applications in both in vitro and in vivo tracking. Finally, we also discuss the design strategies and potential future trends of OSNs-based biosensors. This review provides a theoretical scaffold for the design of high-performance OSNs-based biosensors and highlights important trends and future directions for their development and application.

Impacts of Environmental Pollution on Brain Tumorigenesis

Pollutants consist of several components, known as direct or indirect mutagens, that can be associated with the risk of tumorigenesis. The increased incidence of brain tumors, observed more frequently in industrialized countries, has generated a deeper interest in examining different pollutants that could be found in food, air, or water supply. These compounds, due to their chemical nature, alter the activity of biological molecules naturally found in the body. The bioaccumulation leads to harmful effects for humans, increasing the risk of the onset of several pathologies, including cancer. Environmental components often combine with other risk factors, such as the individual genetic component, which increases the chance of developing cancer. The objective of this review is to discuss the impact of environmental carcinogens on modulating the risk of brain tumorigenesis, focusing our attention on certain categories of pollutants and their sources.

Particulate Matters Affecting lncRNA Dysregulation and Glioblastoma Invasiveness: In Silico Applications and Current Insights

With a reported rise in global air pollution, more than 50% of the population remains exposed to toxic air pollutants in the form of particulate matters (PMs). PMs, from various sources and of varying sizes, have a significant impact on health as long-time exposure to them has seen a correlation with various health hazards and have also been determined to be carcinogenic. In addition to disrupting known cellular pathways, PMs have also been associated with lncRNA dysregulation-a factor that increases predisposition towards the onset or progression of cancer. lncRNA dysregulation is further seen to mediate glioblastoma multiforme (GBM) progression. The vast array of information regarding cancer types including GBM and its various precursors can easily be obtained via innovative in silico approaches in the form of databases such as GEO and TCGA; however, a need to obtain selective and specific information correlating anthropogenic factors and disease progression-in the case of GBM-can serve as a critical tool to filter down and target specific PMs and lncRNAs responsible for regulating key cancer hallmarks in glioblastoma. The current review article proposes an in silico approach in the form of a database that reviews current updates on correlation of PMs with lncRNA dysregulation leading to GBM progression.

Burden of chronic obstructive pulmonary disease and its attributable risk factors in 204 countries and territories, 1990-2019: results from the Global Burden of Disease Study 2019

OBJECTIVE

To report the global, regional, and national burden of chronic obstructive pulmonary disease (COPD) and its attributable risk factors between 1990 and 2019, by age, sex, and sociodemographic index.

DESIGN

Systematic analysis.

DATA SOURCE

Global Burden of Disease Study 2019.

MAIN OUTCOME MEASURES

Data on the prevalence, deaths, and disability adjusted life years (DALYs) of COPD, and its attributable risk factors, were retrieved from the Global Burden of Disease 2019 project for 204 countries and territories, between 1990 and 2019. The counts and rates per 100 000 population, along with 95% uncertainty intervals, were presented for each estimate.

RESULTS

In 2019, 212.3 million prevalent cases of COPD were reported globally, with COPD accounting for 3.3 million deaths and 74.4 million DALYs. The global age standardised point prevalence, death, and DALY rates for COPD were 2638.2 (95% uncertainty intervals 2492.2 to 2796.1), 42.5 (37.6 to 46.3), and 926.1 (848.8 to 997.7) per 100 000 population, which were 8.7%, 41.7%, and 39.8% lower than in 1990, respectively. In 2019, Denmark (4299.5), Myanmar (3963.7), and Belgium (3927.7) had the highest age standardised point prevalence of COPD. Egypt (62.0%), Georgia (54.9%), and Nicaragua (51.6%) showed the largest increases in age standardised point prevalence across the study period. In 2019, Nepal (182.5) and Japan (7.4) had the highest and lowest age standardised death rates per 100 000, respectively, and Nepal (3318.4) and Barbados (177.7) had the highest and lowest age standardised DALY rates per 100 000, respectively. In men, the global DALY rate of COPD increased up to age 85-89 years and then decreased with advancing age, whereas for women the rate increased up to the oldest age group (≥95 years). Regionally, an overall reversed V shaped association was found between sociodemographic index and the age standardised DALY rate of COPD. Factors contributing most to the DALYs rates for COPD were smoking (46.0%), pollution from ambient particulate matter (20.7%), and occupational exposure to particulate matter, gases, and fumes (15.6%).

CONCLUSIONS

Despite the decreasing burden of COPD, this disease remains a major public health problem, especially in countries with a low sociodemographic index. Preventive programmes should focus on smoking cessation, improving air quality, and reducing occupational exposures to further reduce the burden of COPD.

Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16

A new dynamical core, known as the Finite-Volume Cubed-Sphere (FV3) and developed at both NASA and NOAA, is used in NOAA's Global Forecast System (GFS) and in limited-area models for regional weather and air quality applications. NOAA has also upgraded the operational FV3GFS to version 16 (GFSv16), which includes a number of significant developmental advances to the model configuration, data assimilation, and underlying model physics, particularly for atmospheric composition to weather feedback. Concurrent with the GFSv16 upgrade, we couple the GFSv16 with the Community Multiscale Air Quality (CMAQ) model to form an advanced version of the National Air Quality Forecasting Capability (NAQFC) that will continue to protect human and ecosystem health in the US. Here we describe the development of the FV3GFSv16 coupling with a "state-of-the-science" CMAQ model version 5.3.1. The GFS-CMAQ coupling is made possible by the seminal version of the NOAA-EPA Atmosphere-Chemistry Coupler (NACC), which became a major piece of the next operational NAQFC system (i.e., NACC-CMAQ) on 20 July 2021. NACC-CMAQ has a number of scientific advancements that include satellite-based data acquisition technology to improve land cover and soil characteristics and inline wildfire smoke and dust predictions that are vital to predictions of fine particulate matter (PM_2.5) concentrations during hazardous events affecting society, ecosystems, and human health. The GFS-driven NACC-CMAQ model has significantly different meteorological and chemical predictions compared to the previous operational NAQFC, where evaluation of NACC-CMAQ shows generally improved near-surface ozone and PM_2.5 predictions and diurnal patterns, both of which are extended to a 72 h (3 d) forecast with this system.

Inequality in historical transboundary anthropogenic PM2.5 health impacts

Atmospheric transport of fine particulate matter (PM_2.5), the leading environmental risk factor for public health, is estimated to exert substantial transboundary effects at present. During the past several decades, human-produced pollutant emissions have undergone drastic and regionally distinctive changes, yet it remains unclear about the resulting global transboundary health impacts. Here we show that between 1950 and 2014, global anthropogenic PM_2.5 has led to 185.7 million premature deaths cumulatively, including about 14% from transboundary pollution. Among four country groups at different affluence levels, on a basis of per capita contribution to transboundary mortality, a richer region tends to exert severer cumulative health externality, with the poorest bearing the worst net externality after contrasting import and export of pollution mortality. The temporal changes in transboundary mortality and cross-regional inequality are substantial. Effort to reduce PM_2.5-related transboundary mortality should seek international collaborative strategies that account for historical responsibility and inequality.

Long-term ozone exposure and cognitive impairment among Chinese older adults: A cohort study

Ambient particulate matter pollution has been linked to impaired cognitive performance, but the effect of ambient ozone exposure on cognitive function remains largely unknown. We examined the association of long-term ozone exposure with the risk of cognitive impairment among a national representative cohort of 9,544 Chinese older adults (aged 65 years and over) with baseline normal cognition from the Chinese Longitudinal Healthy Longevity Survey (2005-2018). The ozone exposure of each participant was measured by annual mean ozone concentrations for the county of residence. Cognitive function was assessed by the Chinese version of the Mini-Mental State Examination (MMSE). We defined cognitive impairment as an MMSE score below 18 points accompanied by an MMSE score that declined ≥ 4 points from baseline. Cox proportional hazards models were applied to explore the association of ozone exposure with cognitive impairment. During the mean follow-up time of 6.5 years, 2,601 older adults developed cognitive impairment. Each 10-μg/m³ increase in annual mean ozone exposure was associated with a 10.4% increased risk of cognitive impairment. The exposure-response relationship between ozone exposure and risk of cognitive impairment showed a linear trend. Sensitivity analyses revealed the association to be robust. We found that older adults from Eastern, Central, and Southern China were particularly susceptible. Our results show that ozone is a risk factor for late-life cognitive decline. Reducing ambient ozone pollution may help delay the onset of cognitive impairment among older adults.

Secondary organic aerosol association with cardiorespiratory disease mortality in the United States

Fine particle pollution, PM2.5, is associated with increased risk of death from cardiorespiratory diseases. A multidecadal shift in the United States (U.S.) PM2.5 composition towards organic aerosol as well as advances in predictive algorithms for secondary organic aerosol (SOA) allows for novel examinations of the role of PM2.5 components on mortality. Here we show SOA is strongly associated with county-level cardiorespiratory death rates in the U.S. independent of the total PM2.5 mass association with the largest associations located in the southeastern U.S. Compared to PM2.5, county-level variability in SOA across the U.S. is associated with 3.5× greater per capita county-level cardiorespiratory mortality. On a per mass basis, SOA is associated with a 6.5× higher rate of mortality than PM2.5, and biogenic and anthropogenic carbon sources both play a role in the overall SOA association with mortality. Our results suggest reducing the health impacts of PM2.5 requires consideration of SOA.

Prenatal PM2.5 exposure in the second and third trimesters predicts neurocognitive performance at age 9-10 years: A cohort study of Mexico City children

INTRODUCTION

Prenatal exposure to fine particulate matter air pollution (PM2.5) is an important, under-studied risk factor for neurodevelopmental dysfunction. We describe the relationships between prenatal PM2.5 exposure and vigilance and inhibitory control, executive functions related to multiple health outcomes in Mexico City children.

METHODS

We studied 320 children enrolled in Programming Research in Obesity, GRowth, Environment and Social Stressors, a longitudinal birth cohort study in Mexico City. We used a spatio-temporal model to estimate daily prenatal PM2.5 exposure at each participant's residential address. At age 9-10 years, children performed three Go/No-Go tasks, which measure vigilance and inhibitory control ability. We used Latent class analysis (LCA) to classify performance into subgroups that reflected neurocognitive performance and applied multivariate regression and distributed lag regression modeling (DLM) to test overall and time-dependent associations between prenatal PM2.5 exposure and Go/No-Go performance.

RESULTS

LCA detected two Go/No-Go phenotypes: high performers (Class 1) and low performers (Class 2). Predicting odds of Class 1 vs Class 2 membership based on prenatal PM2.5 exposure timing, logistic regression modeling showed that average prenatal PM2.5 exposure in the second and third trimesters correlated with increased odds of membership in low-performance Class 2 (OR = 1.59 (1.16, 2.17), p = 0.004). Additionally, DLM analysis identified a critical window consisting of gestational days 103-268 (second and third trimesters) in which prenatal PM2.5 exposure predicted poorer Go/No-Go performance.

DISCUSSION

Increased prenatal PM2.5 exposure predicted decreased vigilance and inhibitory control at age 9-10 years. These findings highlight the second and third trimesters of gestation as critical windows of PM2.5 exposure for the development of vigilance and inhibitory control in preadolescent children. Because childhood development of vigilance and inhibitory control informs behavior, academic performance, and self-regulation into adulthood, these results may help to describe the relationship of prenatal PM2.5 exposure to long-term health and psychosocial outcomes. The integrative methodology of this study also contributes to a shift towards more holistic analysis.

Real-time characterization of aerosol particle composition, sources and influences of increased ventilation and humidity in an office

Most of human exposure to atmospheric pollutants occurs indoors, and the components of outdoor aerosols may have been changed in the way before reaching indoor spaces. Here we conducted real-time online measurements of mass concentrations and chemical composition of black carbon and the non-refractory species in PM_2.5 in an occupied office for approximately one month. The open-close windows and controlled dampness experiments were also performed. Our results show that indoor aerosol species primarily originate from outdoors with indoor/outdoor ratio of these species typically less than unity except for certain organic aerosol (OA) factors. All aerosol species went through filtration upon transport indoors. Ammonium nitrate and fossil fuel OA underwent evaporation or particle-to-gas partitioning, while less oxidized secondary OA (SOA) underwent secondary formation and cooking OA might have indoor sources. With higher particulate matter (PM) mass concentration outdoors than in the office, elevated natural ventilation increased PM exposure indoors and this increased exposure was prolonged when outdoor PM was scavenged. We found that increasing humidity in the office led to higher indoor PM mass concentration particularly more oxidized SOA. Overall, our results highlight that indoor exposure of occupants is substantially different from outdoor in terms of mass concentrations and chemical species.

Insight into ozone profile climatology over northeast China from aircraft measurement and numerical simulation

Tropospheric ozone is a major pollutant that can harm human health, animals and plants. With a rapid development in Northeast China, ozone pollution has become an increasingly serious environmental challenge. To study the ozone distribution and the potential sources of ozone precursors in Northeast China, we analyzed vertical ozone profiles from the In-service Aircraft for a Global Observing System (IAGOS) in 2012-2014 and provided the climatological vertical structure of tropospheric ozone over Shenyang. The tropospheric ozone generally presents high in hot months, mainly due to the combined effects of the strong solar radiation and high volatile organic compounds emission in summer. While in cold months, the ozone is low because of weak solar radiation and high nitrogen oxides emission. Besides, a low-ozone center exists within lower troposphere in August, which is mainly caused by the East Asian summer monsoon prevailing in summer. To analyze the sources of ozone, typical ozone pollution episodes were studied and the results revealed the different pathways for the enhancement of ozone pollution in Shenyang: regional transport of anthropogenic emissions from North China Plain (NCP), long-range transport from Siberian biomass burning and local photochemical production. Modeling results show that the largest contribution to the surface ozone in Northeast China is local anthropogenic emissions (exceed 90%); the regional transport of NCP anthropogenic emissions contribute more to the pollutants around 2 km, and account for more than 50% pollutants during highly ozone polluted days; through long-range transport, Siberian biomass burning in the spring also have a nonnegligible effect on the near-ground ozone in Northeast China. Overall, this study provides tropospheric ozone climatology and its source attribution in Northeast China, and highlight the great importance of regional transport of anthropogenic and biomass burning emissions in ozone pollution.

Predicting intraurban PM2.5 concentrations using enhanced machine learning approaches and incorporating human activity patterns

Urban areas contribute substantially to human exposure to ambient air pollution. Numerous statistical prediction models have been used to estimate ambient concentrations of fine particulate matter (PM_2.5) and other pollutants in urban environments, with some incorporating machine learning (ML) algorithms to improve predictive power. However, many ML approaches for predicting ambient pollutant concentrations to date have used principal component analysis (PCA) with traditional regression algorithms to explore linear correlations between variables and to reduce the dimensionality of the data. Moreover, while most urban air quality prediction models have traditionally incorporated explanatory variables such as meteorological, land use, transportation/mobility, and/or co-pollutant factors, recent research has shown that local emissions from building infrastructure may also be useful factors to consider in estimating urban pollutant concentrations. Here we propose an enhanced ML approach for predicting urban ambient PM_2.5 concentrations that hybridizes cascade and PCA methods to reduce the dimensionality of the data-space and explore nonlinear effects between variables. We test the approach using different durations of time series air quality datasets of hourly PM_2.5 concentrations from three air quality monitoring sites in different urban neighborhoods in Chicago, IL to explore the influence of dynamic human-related factors, including mobility (i.e., traffic) and building occupancy patterns, on model performance. We test 9 state-of-the-art ML algorithms to find the most effective algorithm for modeling intraurban PM_2.5 variations and we explore the relative importance of all sets of factors on intraurban air quality model performance. Results demonstrate that Gaussian-kernel support vector regression (SVR) was the most effective ML algorithm tested, improving accuracy by 118% compared to a traditional multiple linear regression (MLR) approach. Incorporating the enhanced approach with SVR algorithm increased model performance up to 18.4% for yearlong and 98.7% for month-long hourly datasets, respectively. Incorporating assumptions for human occupancy patterns in dominant building typologies resulted in improvements in model performance by between 4% and 37%. Combined, these innovations can be used to improve the performance and accuracy of urban air quality prediction models compared to conventional approaches.

Estimation of excess mortality due to long-term exposure to PM2.5 in continental United States using a high-spatiotemporal resolution model

BACKGROUND

Exposure to fine particulate matter (<2.5 mm in aerodynamic diameter, PM_2.5) pollution, even at low concentrations is associated with increased mortality. Estimates of the magnitude of the effect of particulate air pollution on mortality are generally done on a coarse spatial scale, such as 0.5°, and may fail to capture small spatial differences in exposure and baseline rates, which can bias results and impede the ability to consider environmental justice. We estimated the burden of mortality attributable to long-term exposure to ambient PM_2.5 among adults in the Continental United States on a 1 km scale, in order to provide information for decision makers setting health priorities.

METHODS

We conducted a health impact assessment for 2015 using a model predicting U.S. PM_2.5 concentrations at a spatial resolution of 1 km cells. We applied a concentration-response curve from a recently published meta-analysis of long-term PM_2.5 mortality association which incorporates new findings at high and low PM_2.5 concentrations. We computed the change in deaths in each grid cell, based on its grid cell population, Zip code level baseline mortality rates, and exposure under two scenarios; a decrease of PM_2.5 exposure levels by 40% and a decrease of PM_2.5 exposure levels to the county minimum PM_2.5 concentrations.

RESULTS

We estimated the deaths would fall by 104,786 (95% CI 57,016-135,726) and 112,040 (95% CI 63,261-159,116) attributable to 40% reduction and reduction to the county minimum PM_2.5 concentrations_, respectively. The greatest mortality impact due to 40% reduction in PM_2.5 was observed in California with; 11,621 (95% CI; 7156-15,989) and Texas with; 9616 (95% CI; 5798-13,352) excess deaths attributable to annual mean PM_2.5 concentrations of 9.54 and 9.12 μg m^-3, respectively. Within city analyses showed substantial heterogeneity in risk. The estimated Attributable fraction (AF %) in locations with high PM_2.5 levels was 8.6% (95% CI 5.4-11.7) compared to the overall AF% of 4.9% (95% CI; 2.9-6.8). In comparison, results using county average PM_2.5 were smaller than the estimates from the 1 km PM_2.5 datasets. Similarly, estimates using county-level mortality rates were smaller than estimates based on Zip-code level mortality rates.

CONCLUSIONS

Our study provides evidence of major health benefits expected from reducing PM_2.5 exposure, even in regions with relatively low PM_2.5 concentrations. Spatial characteristics of exposure and baseline mortality (e.g., accuracy, scales, and variations) in disease burden studies can significantly impact the results.

Ozone pollution in China: Background and transboundary contributions to ozone concentration & related health effects across the country

China experiences high ozone concentrations with highest annual 8-hour maximum concentration in eastern China of 78 μg/m³ and was followed by southern (73 μg/m³), north-western (69 μg/m³), northern (68 μg/m³), central (67 μg/m³), north eastern (65 μg/m³) and south-western China (59 μg/m³). Ozone concentration peaked in spring season in 4 (eastern, northern, north eastern & central) of 7 regions across China while lowest concentration in most regions across China was experienced in winter season with central and southern China being the only exceptions. Regions outside Asia contributed ozone to all regions across China with highest contributions in 4 (East, Central, North & Northeast) of the 7 regions. South-western China had the largest ozone contribution from outside (23%) and was followed by 16.39% outside ozone contribution in north-western China, 11.64% contribution in north eastern China, 11% contribution in northern China, 7.85% contribution in southern China, 5.28% contribution in central China while 4.56% contribution in eastern China. Policy relevant background (PRB) concentration was above 47 μg/m³ in all regions across China and contributed about 71-94% to total ozone concentration with highest PRB concentration of 65.25 μg/m³ recorded in north-west China. China recorded 93,351 (95%CI: 11001-169,898) ozone related premature mortality in 2015 with 42,673 (95%CI: 11001-69,586) respiratory mortality and 50,678 (95%CI: 0-100,312) cardiovascular mortality. Northern and eastern China recorded high ozone related mortality with 18,230 (95%CI: 4700-29,727) & 12,261 (95%CI: 3161-19,993) respiratory and 21,662 (95%CI: 0-42,877) & 14,528 (95%CI: 0-28,757) cardiovascular deaths respectively. In terms of foreign contributions, premature mortality due to ozone from outside Asia contributed the most to China with 1070 (95%CI: 276-1746) respiratory mortality and 1270 (95%CI: 0-2515) cardiovascular mortality. East Asia contributed to about 419 (95%CI: 109-679) respiratory deaths and 501 (95%CI: 0-989) cardiovascular deaths while North Asia contributed to 220 (95%CI: 56-358) respiratory mortality and 260 (95%CI, 0-515) cardiovascular mortality.

Ozone pollution mitigation in guangxi (south China) driven by meteorology and anthropogenic emissions during the COVID-19 lockdown

With the implementation of COVID-19 restrictions and consequent improvement in air quality due to the nationwide lockdown, ozone (O₃) pollution was generally amplified in China. However, the O₃ levels throughout the Guangxi region of South China showed a clear downward trend during the lockdown. To better understand this unusual phenomenon, we investigated the characteristics of conventional pollutants, the influence of meteorological and anthropogenic factors quantified by a multiple linear regression (MLR) model, and the impact of local sources and long-range transport based on a continuous emission monitoring system (CEMS) and the HYSPLIT model. Results show that in Guangxi, the conventional pollutants generally declined during the COVID-19 lockdown period (January 24 to February 9, 2020) compared with their concentrations during 2016-2019, while O₃ gradually increased during the resumption (10 February to April 2020) and full operation periods (May and June 2020). Focusing on Beihai, a typical Guangxi region city, the correlations between the daily O₃ concentrations and six meteorological parameters (wind speed, visibility, temperature, humidity, precipitation, and atmospheric pressure) and their corresponding regression coefficients indicate that meteorological conditions were generally conducive to O₃ pollution mitigation during the lockdown. A 7.84 μg/m³ drop in O₃ concentration was driven by meteorology, with other decreases (4.11 μg/m³) explained by reduced anthropogenic emissions of O₃ precursors. Taken together, the lower NO₂/SO₂ ratios (1.25-2.33) and consistencies between real-time monitored primary emissions and ambient concentrations suggest that, with the closure of small-scale industries, residual industrial emissions have become dominant contributors to local primary pollutants. Backward trajectory cluster analyses show that the slump of O₃ concentrations in Southern Guangxi could be partly attributed to clean air mass transfer (24-58%) from the South China Sea. Overall, the synergistic effects of the COVID-19 lockdown and meteorological factors intensified O₃ reduction in the Guangxi region of South China.

Assessing the Distribution of Air Pollution Health Risks within Cities: A Neighborhood-Scale Analysis Leveraging High-Resolution Data Sets in the Bay Area, California

BACKGROUND

Air pollution-attributable disease burdens reported at global, country, state, or county levels mask potential smaller-scale geographic heterogeneity driven by variation in pollution levels and disease rates. Capturing within-city variation in air pollution health impacts is now possible with high-resolution pollutant concentrations.

OBJECTIVES

We quantified neighborhood-level variation in air pollution health risks, comparing results from highly spatially resolved pollutant and disease rate data sets available for the Bay Area, California.

METHODS

We estimated mortality and morbidity attributable to nitrogen dioxide (NO2), black carbon (BC), and fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] using epidemiologically derived health impact functions. We compared geographic distributions of pollution-attributable risk estimates using concentrations from a) mobile monitoring of NO2 and BC; and b) models predicting annual NO2, BC and PM2.5 concentrations from land-use variables and satellite observations. We also compared results using county vs. census block group (CBG) disease rates.

RESULTS

Estimated pollution-attributable deaths per 100,000 people at the 100-m grid-cell level ranged across the Bay Area by a factor of 38, 4, and 5 for NO2 [mean=30 (95% CI: 9, 50)], BC [mean=2 (95% CI: 1, 2)], and PM2.5, [mean=49 (95% CI: 33, 64)]. Applying concentrations from mobile monitoring and land-use regression (LUR) models in Oakland neighborhoods yielded similar spatial patterns of estimated grid-cell-level NO2-attributable mortality rates. Mobile monitoring concentrations captured more heterogeneity [mobile monitoring mean=64 (95% CI: 19, 107) deaths per 100,000 people; LUR mean=101 (95% CI: 30, 167)]. Using CBG-level disease rates instead of county-level disease rates resulted in 15% larger attributable mortality rates for both NO2 and PM2.5, with more spatial heterogeneity at the grid-cell-level [NO2 CBG mean=41 deaths per 100,000 people (95% CI: 12, 68); NO2 county mean=38 (95% CI: 11, 64); PM2.5 CBG mean=59 (95% CI: 40, 77); and PM2.5 county mean=55 (95% CI: 37, 71)].

DISCUSSION

Air pollutant-attributable health burdens varied substantially between neighborhoods, driven by spatial variation in pollutant concentrations and disease rates. https://doi.org/10.1289/EHP7679.

Premature mortality attributable to PM2.5 pollution in China during 2008-2016: Underlying causes and responses to emission reductions

Long-term exposure to fine particulate matter (PM_2.5) poses a great threat to public health in China. To this end, the Chinese government promulgated the Air Pollution Prevention and Control Action Plan (the Action Plan) in 2013. However, the health benefits of the Action Plan have not been well explained. In this paper, the underlying causes of changes in premature mortality attributable to PM_2.5 pollution and the response of this mitigation policy in China were explored using sensitivity analysis. The simulated annual average PM_2.5 concentration reduced by 24.9% over mainland China from 2008 to 2016. Subsequently, national premature mortality would decrease by 14.4% from 1.14 million (95% CI: 0.54, 1.55) in 2008 to 0.98 million (95% CI: 0.44, 1.38) in 2016. Specifically, premature mortality reduced by 209,600 cases (-18.3%) owing to PM_2.5 reduction during 2008-2016, of which 188,500 cases were from 2014 to 2016 due to the Action Plan in 2013. Note that the health benefits were limited when compared with air quality improvements, mainly due to that the IER functions have a stable curve at higher concentration intervals. Meanwhile, premature mortality would have increased by 14.2% from 2008 to 2016 owing to demographic changes, substantially weakening the impact of the decrease in PM_2.5 and baseline mortality. The effectiveness of China's new air pollution mitigation policy was proved through the research. However, considering the non-linear response of mortality to PM_2.5 changes and the aggravation of demography trends, stronger emission control steps should be further taken to protect public health in China.

Meteorological influences on PM2.5 and O3 trends and associated health burden since China's clean air actions

Stringent clean air actions have been implemented to improve air quality in China since 2013. In addition to anthropogenic emission abatements, the changes in air quality may be modulated also by meteorology. In this study, we developed multiple linear regression models to quantify meteorological influences on the trends in fine particulate matter (PM_2.5) and ozone (O₃) concentrations and associated health burden over three polluted regions of China, i.e., North China Plain, Yangtze River Delta, and Fen-wei Plain during 2014-2018, with a novel focus on the contributions of the most influential meteorological factors to PM_2.5 and O₃ trends as well as the meteorological contributions to PM_2.5- and O₃-related mortality trends. The meteorology-driven PM_2.5 (O₃) trends for the three regions were -0.5~-2.0 (+0.7~+0.8) μg m^-3 yr^-1, contributing 10- 26% (12- 18%) of the observed five-year decreasing PM_2.5 (increasing O₃) trends. The decreased relative humidity (increased daytime planetary boundary layer height) was identified to be the most influential meteorological factor and explained 55% (42%) of the largest meteorology-driven PM_2.5 (O₃) trend among all regions and seasons. The meteorology-driven decreases in PM_2.5 (increases in O₃) concentrations led to overall decreases in PM_2.5-related (increases in O₃-related) mortalities with trends of -2.2~-7.4 (+0.5~+0.9) thousand yr^-1 for the three regions, accounting for 10- 26% (15- 31%) of the total decreasing (increasing) trends in PM_2.5-related (O₃-related) mortalities. The results emphasize the important role of meteorology in PM_2.5 and O₃ air quality and associated health burden over China, and have important implications for China's air quality planning. In particular, more efforts in emission control should be taken to offset the adverse effects on ozone caused by meteorology.

Air pollution and chronic obstructive pulmonary disease

There is considerable epidemiological evidence indicating that air pollution has adverse effects on human health and is closely related to respiratory diseases, including chronic obstructive pulmonary disease (COPD). These effects, which can be divided into short- and long-term effects, can manifest as an exacerbation of existing symptoms, impaired lung function, and increased hospitalization and mortality rates. Long-term exposure to air with a high concentration of pollutants may also increase the incidence of COPD. The combined effects of different pollutants may become more complex in the future; hence, there is a need for more intensive research on specific at-risk populations, and formulating corresponding protective strategies is crucial. We aimed to review the epidemiological evidence on the effect of air pollution on COPD, the possible pathophysiological mechanisms underlying this effect, as well as protective measures against the effects of air pollutants in patients with COPD.

Indoor Particulate Matter during HOMEChem: Concentrations, Size Distributions, and Exposures

It is important to improve our understanding of exposure to particulate matter (PM) in residences because of associated health risks. The HOMEChem campaign was conducted to investigate indoor chemistry in a manufactured test house during prescribed everyday activities, such as cooking, cleaning, and opening doors and windows. This paper focuses on measured size distributions of PM (0.001-20 μm), along with estimated exposures and respiratory-tract deposition. Number concentrations were highest for sub-10 nm particles during cooking using a propane-fueled stovetop. During some cooking activities, calculated PM_2.5 mass concentrations (assuming a density of 1 g cm^-3) exceeded 250 μg m^-3, and exposure during the postcooking decay phase exceeded that of the cooking period itself. The modeled PM respiratory deposition for an adult residing in the test house kitchen for 12 h varied from 7 μg on a day with no indoor activities to 68 μg during a simulated day (including breakfast, lunch, and dinner preparation interspersed by cleaning activities) and rose to 149 μg during a simulated Thanksgiving day.

Simulation of organic aerosol formation during the CalNex study: updated mobile emissions and secondary organic aerosol parameterization for intermediate-volatility organic compounds

We describe simulations using an updated version of the Community Multiscale Air Quality model version 5.3 (CMAQ v5.3) to investigate the contribution of intermediate-volatility organic compounds (IVOCs) to secondary organic aerosol (SOA) formation in southern California during the CalNex study. We first derive a model-ready parameterization for SOA formation from IVOC emissions from mobile sources. To account for SOA formation from both diesel and gasoline sources, the parameterization has six lumped precursor species that resolve both volatility and molecular structure (aromatic versus aliphatic). We also implement new mobile-source emission profiles that quantify all IVOCs based on direct measurements. The profiles have been released in SPECIATE 5.0. By incorporating both comprehensive mobile-source emission profiles for semivolatile organic compounds (SVOCs) and IVOCs and experimentally constrained SOA yields, this CMAQ configuration best represents the contribution of mobile sources to urban and regional ambient organic aerosol (OA). In the Los Angeles region, gasoline sources emit 4 times more non-methane organic gases (NMOGs) than diesel sources, but diesel emits roughly 3 times more IVOCs on an absolute basis. The revised model predicts all mobile sources (including on- and off-road gasoline, aircraft, and on- and off-road diesel) contribute ~ 1 μgm-3 to the daily peak SOA concentration in Pasadena. This represents a ~ 70% increase in predicted daily peak SOA formation compared to the base version of CMAQ. Therefore, IVOCs in mobile-source emissions contribute almost as much SOA as traditional precursors such as single-ring aromatics. However, accounting for these emissions in CMAQ does not reproduce measurements of either ambient SOA or IVOCs. To investigate the potential contribution of other IVOC sources, we performed two exploratory simulations with varying amounts of IVOC emissions from nonmobile sources. To close the mass balance of primary hydrocarbon IVOCs, IVOCs would need to account for 12% of NMOG emissions from nonmobile sources (or equivalently 30.7 t d-1 in the Los Angeles-Pasadena region), a value that is well within the reported range of IVOC content from volatile chemical products. To close the SOA mass balance and also explain the mildly oxygenated IVOCs in Pasadena, an additional 14.8% of nonmobile-source NMOG emissions would need to be IVOCs (assuming SOA yields from the mobile IVOCs apply to nonmobile IVOCs). However, an IVOC-to-NMOG ratio of 26.8% (or equivalently 68.5 t d-1 in the Los Angeles-Pasadena region) for nonmobile sources is likely unrealistically high. Our results highlight the important contribution of IVOCs to SOA production in the Los Angeles region but underscore that other uncertainties must be addressed (multigenerational aging, aqueous chemistry and vapor wall losses) to close the SOA mass balance. This research also highlights the effectiveness of regulations to reduce mobile-source emissions, which have in turn increased the relative importance of other sources, such as volatile chemical products.

Air pollution control strategies directly limiting national health damages in the US

Exposure to fine particulate matter (PM2.5) from fuel combustion significantly contributes to global and US mortality. Traditional control strategies typically reduce emissions for specific air pollutants and sectors to maintain pollutant concentrations below standards. Here we directly set national PM2.5 mortality cost reduction targets within a global human-earth system model with US state-level energy systems, in scenarios to 2050, to identify endogenously the control actions, sectors, and locations that most cost-effectively reduce PM2.5 mortality. We show that substantial health benefits can be cost-effectively achieved by electrifying sources with high primary PM2.5 emission intensities, including industrial coal, building biomass, and industrial liquids. More stringent PM2.5 reduction targets expedite the phaseout of high emission intensity sources, leading to larger declines in major pollutant emissions, but very limited co-benefits in reducing CO2 emissions. Control strategies limiting health damages achieve the greatest emission reductions in the East North Central and Middle Atlantic states.

Synthetic Chemical Trade as a Potential Driver of Global Health Disparities and Data Gaps on Synthetic Chemicals in Vulnerable Populations

PURPOSE OF REVIEW

Most research on toxic exposures in vulnerable populations focuses on air pollution. Synthetic chemical production, however, is a multi-billion-dollar industry that lacks appropriate international regulation to protect those exposed to toxic chemicals. This paper aims to describe the country-level import and export of key groups of synthetic chemicals using data from the United Nations Comtrade Database and provide a narrative review of the evidence from January 2018 to August 2019 on exposure to, health effects of, and interventions to reduce synthetic chemicals in vulnerable populations around the world.

RECENT FINDINGS

Generally, a small number of high-income countries export the majority of synthetic chemicals, while most low-income countries import more chemicals than they export, which may contribute to higher levels of synthetic chemicals in those settings. However, few studies have quantified exposures to synthetic chemicals in low- and middle-income countries, the health effects of such exposures, or interventions to mitigate exposures. Synthetic chemicals continue to enter markets despite our limited knowledge of their effects on human health, particularly in the most vulnerable populations. We need more research to understand the health impacts of these pervasive exposures.

State-level drivers of future fine particulate matter mortality in the United States

Future fine particulate matter (PM₂.₅) concentrations and resulting health impacts will be largely determined by factors such as energy use, fuel choices, emission controls, state and national policies, and demographcs. In this study, a human-earth system model is used to estimate PM_2.5 mortality costs (PMMC) due to air pollutant emissions from each US state over the period 2015 to 2050, considering current major air quality and energy regulations. Contributions of various socioeconomic and energy factors to PMMC are quantified using the Logarithmic Mean Divisia Index. National PMMC are estimated to decrease 25% from 2015 to 2050, driven by decreases in energy intensity and PMMC per unit consumption of electric sector coal and transportation liquids. These factors together contribute 68% of the decrease, primarily from technology improvements and air quality regulations. States with greater population and economic growth, but with fewer clean energy resources, are more likely to face significant challenges in reducing future PMMC from their emissions. In contrast, states with larger projected decreases in PMMC have smaller increases in population and per capita GDP, and greater decreases in electric sector coal share and PMMC per unit fuel consumption.

Air pollution is not 'the new smoking': comparing the disease burden of air pollution and smoking across the globe, 1990-2017

Air pollution has been labelled the ‘new smoking’, with news articles bearing titles such as ‘If You Live in a Big City You Already Smoke Every Day’ and ‘The Air Is So Bad in These Cities, You May As Well Be Smoking’. Dr Tedros Adhanom Ghebreyesus, WHO Director-General, highlighted this attention-catching comparison, saying, ‘The world has turned the corner on tobacco. Now it must do the same for the ‘new tobacco’ – the toxic air that billions breathe every day’ and ‘Globally, with smoking on the decline, air pollution now causes more deaths annually than tobacco’ at the First Global Conference on Air Pollution and Health in 2018. The suggestion that the world has turned the corner on tobacco control and the reference to air pollution as the ‘new smoking’ raise a number of concerns. We generate outputs from GBD Compare (the online data visualisation tool of the Global Burden of Diseases and Injuries (GBD) Study) to demonstrate historical disease burden trends in terms of disability-adjusted life years and age-standardised mortality attributable to air pollution and tobacco use from 1990 to 2017 across the globe. We find that the disease burden caused by ambient air pollution declined significantly faster than the burden caused by tobacco use. We conclude that the world is still far from turning the corner on the tobacco endemic. Further, the suggestion that air pollution is as bad as actual smoking is not only inaccurate but also potentially dangerous to public health.

Revisiting the estimations of PM2.5-attributable mortality with advancements in PM2.5 mapping and mortality statistics

With the advancements of geospatial technologies, geospatial datasets of fine particulate matter (PM_2.5) and mortality statistics are increasingly used to examine the health effects of PM_2.5. Choices of these datasets with difference geographic characteristics (e.g., accuracy, scales, and variations) in disease burden studies can significantly impact the results. The objective of this study is to revisit the estimations of PM_2.5-attributable mortality by taking advantage of recent advancements in high resolution mapping of PM_2.5concentrations and fine scale of mortality statistics and to explore the impacts of new data sources, geographic scales, and spatial variations of input datasets on mortality estimations. We estimate the PM_2.5-mortality for the years of 2000, 2005, 2010 and 2015 using three PM_2.5 concentration datasets [Chemical Transport Model (CTM), random forests-based regression kriging (RFRK), and geographically weighted regression (GWR)] at two resolutions (i.e., 10 km and 1 km) and mortality rates at two geographic scales (i.e., regional-level and county-level). The results show that the estimated PM_2.5-mortality from the 10 km CTM-derived PM_2.5 dataset tend to be smaller than the estimations from the 1 km RFRK- and GWR-derived PM_2.5 datasets. The estimated PM_2.5-mortalities from regional-level mortality rates are similar to the estimations from those at county level, while large deviations exist when zoomed into small geographic regions (e.g., county). In a scenario analysis to explore the possible benefits of PM_2.5 concentrations reduction, the uses of the two newly developed 1 km resolution PM_2.5 datasets (RFRK and GWR) lead to discrepant results. Furthermore, we found that the change in PM_2.5 concentration is the primary factor that leads to the PM_2.5-attributable mortality decrease from 2000 to 2015. The above results highlight the impact of the adoption of input datasets from new sources with varied geographic characteristics on the PM_2.5-attributable mortality estimations and demonstrate the necessity to account for these impact in future disease burden studies. CAPSULE: We revisited the estimations of PM_2.5-attributable mortality with advancements in PM_2.5 mapping and mortality statistics, and demonstrated the impact of geographic characteristics of geospatial datasets on mortality estimations.

Estimated Long-Term (1981-2016) Concentrations of Ambient Fine Particulate Matter across North America from Chemical Transport Modeling, Satellite Remote Sensing, and Ground-Based Measurements

Accurate data concerning historical fine particulate matter (PM_2.5) concentrations are needed to assess long-term changes in exposure and associated health risks. We estimated historical PM_2.5 concentrations over North America from 1981 to 2016 for the first time by combining chemical transport modeling, satellite remote sensing, and ground-based measurements. We constrained and evaluated our estimates with direct ground-based PM_2.5 measurements when available and otherwise with historical estimates of PM_2.5 from PM₁₀ measurements or total suspended particle (TSP) measurements. The estimated PM_2.5 concentrations were generally consistent with direct ground-based PM_2.5 measurements over their duration from 1988 onward ( R² = 0.6 to 0.85) and to a lesser extent with PM_2.5 inferred from PM₁₀ measurements from 1985 to 1998 ( R² = 0.5 to 0.6). The collocated comparison of the trends of population-weighted annual average PM_2.5 from our estimates and ground-based measurements was highly consistent (RMSD = 0.66 μg m^-3). The population-weighted annual average PM_2.5 over North America decreased from 22 ± 6.4 μg m^-3 in 1981, to 12 ± 3.2 μg m^-3 in 1998, and to 7.9 ± 2.1 μg m^-3 in 2016, with an overall trend of -0.33 μg m^-3 yr^-1 (95% CI: -0.35, -0.31).

Effect of Health-Related Uncertainty and Natural Variability on Health Impacts and Cobenefits of Climate Policy

Climate policy can mitigate health risks attributed to intensifying air pollution under climate change. However, few studies quantify risks of illness and death, examine their contribution to climate policy benefits, or assess their robustness in light of natural climate variability. We employ an integrated modeling framework of the economy, climate, air quality, and human health to quantify the effect of natural variability on U.S. air pollution impacts under future climate and two global policies (2 and 2.5 °C stabilization scenarios) using 150 year ensemble simulations for each scenario in 2050 and 2100. Climate change yields annual premature deaths related to fine particulate matter and ozone (95CI: 25 000-120 000), heart attacks (900-9400), and lost work days (3.6M-4.9M) in 2100. It raises air pollution health risks by 20%, while policies avert these outcomes by 40-50% in 2050 and 70-88% in 2100. Natural variability introduces "climate noise", yielding some annual estimates with negative cobenefits, and others that reach 100% of annual policy costs. This "noise" is three times the magnitude of uncertainty (95CI) in health and economic responses in 2050. Averaging five annual simulations reduces this factor to two, which is still substantially larger than health-related uncertainty. This study quantifies the potential for inaccuracy in climate impacts projected using too few annual simulations.