Spatial and temporal trends in the mortality burden of air pollution in China: 2004-2012

Spatiotemporal Patterns and Equity Analysis of Premature Mortality Due to Ischemic Heart Disease Attributable to PM2.5 Exposure in China: 2007-2022

Long-term exposure to PM2.5 pollution increases the risk of cardiovascular diseases, particularly ischemic heart disease (IHD). Current assessments of the health effects related to PM2.5 exposure are limited by sparse ground monitoring stations and applicable disease research cohorts, making accurate health effect evaluations challenging. Using satellite-observed aerosol optical depth (AOD) data and the XGBoost-PM25 model, we obtained 1 km scale PM2.5 exposure levels across China. We quantified the premature mortality caused by PM2.5-exposure-induced IHD using the Global Exposure Mortality Model (GEMM) and baseline mortality data. Furthermore, we employed the Gini coefficient, a measure from economics to quantify inequality, to evaluate the distribution differences in health impacts due to PM2.5 exposure under varying socioeconomic conditions. The results indicate that PM2.5 concentrations in China are higher in the central and eastern regions. From 2007 to 2022, the national overall level showed a decreasing trend, dropping from 47.41 μg/m3 to 25.16 μg/m3. The number of premature deaths attributable to PM2.5 exposure increased from 819 thousand in 2007 to 870 thousand in 2022, with fluctuations in certain regions. This increase is linked to population growth and aging because PM2.5 levels have decreased. The results also indicate disparities in premature mortality from IHD among different economic groups in China from 2007 to 2022, with middle-income groups having a higher cumulative proportion of IHD-related premature deaths compared with high- and low-income groups. Despite narrowing GDP gaps across regions from 2007 to 2022, IHD consistently "favored" the middle-income groups. The highest Gini coefficient was observed in the Northwest (0.035), and the lowest was in the South (0.019). Targeted policy interventions are essential to establish a more equitable atmospheric environment.

Long-term exposure to ambient ozone and cardiovascular diseases: Evidence from two national cohort studies in China

INTRODUCTION

The health effects of ambient ozone have been investigated in many previous studies. However, the effects of long-term exposure to ambient ozone on the incidence of cardiovascular disease (CVD) remain inconclusive.

OBJECTIVES

To estimate the associations of long-term exposure to maximum daily 8-hours average ozone (MDA8 O3) with the incidence of total CVD, heart disease, hypertension, and stroke.

METHODS

This was a prospective cohort study, and the data was obtained from the China Health and Retirement Longitudinal Survey (CHARLS) implemented during 2011-2018 and the China Family Panel Studies (CFPS) implemented during 2010-2018. We applied a Cox proportional hazards regression model to evaluate the associations of MDA8 O3 with total CVD, heart disease, hypertension, and stroke risks, and the corresponding population-attributable fractions (PAF) attributable to MDA8 O3 were also calculated. All analyses were conducted by R software.

RESULTS

The mean MDA8 O3 concertation of all included participants in the CHARLS and CFPS were 51.03 part per billion (ppb) and 51.15 ppb, respectively. In the CHARLS including 18,177 participants, each 10 ppb increment in MDA8 O3 concentration was associated with a 31% increase [hazard ratio (HR) = 1.31, 95% confidence interval (CI): 1.22-1.42] in the risk of incident heart disease, and the corresponding population-attributable fractions (PAF) was 13.79% [10.12%-17.32%]. In the CFPS including 30,226 participants, each 10 ppb increment in MDA8 O3 concentration was associated with an increase in the risk of incident total CVD (1.07 [1.02-1.13]), and hypertension (1.10 [1.03-1.18]). The PAFs of total CVD, and hypertension attributable to MDA8 O3 were 3.53% [0.82%-6.16%], and 5.11% [1.73%-8.38%], respectively. Stratified analyses showed greater associations in males, urban areas, and Southern China.

CONCLUSIONS

Long-term exposure to MDA8 O3 may increase the incidence of CVD. Therefore, the policies that control O3 and related precursors are persistently needed.

High-resolution spatial and spatiotemporal modelling of air pollution using fixed site and mobile monitoring in a Canadian city

The development of high-resolution spatial and spatiotemporal models of air pollutants is essential for exposure science and epidemiological applications. While fixed-site sampling has conventionally provided input data for statistical predictive models, the evolving mobile monitoring method offers improved spatial resolution, ideal for measuring pollutants with high spatial variability such as ultrafine particles (UFP). The Quebec Air Pollution Exposure and Epidemiology (QAPEE) study measured and modelled the spatial and spatiotemporal distributions of understudied pollutants, such as UFPs, black carbon (BC), and brown carbon (BrC), along with fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) in Quebec City, Canada. We conducted a combined fixed-site (NO2 and O3) and mobile monitoring (PM2.5, BC, BrC, and UFPs) campaign over 10-months. Mobile monitoring routes were monitored on a weekly basis between 8am-10am and designed using location/allocation modelling. Seasonal fixed-site sampling campaigns captured continuous 24-h measurements over two-week periods. Generalized Additive Models (GAMs), which combined data on pollution concentrations with spatial, temporal, and spatiotemporal predictor variables were used to model and predict concentration surfaces. Annual models for PM2.5, NO2, O3 as well as seven of the smallest size fractions in the UFP range, had high out of sample predictive accuracy (range r2: 0.54-0.86). Varying spatial patterns were observed across UFP size ranges measured as Particle Number Counts (PNC). The monthly spatiotemporal models for PM2.5 (r2 = 0.49), BC (r2 = 0.27), BrC (r2 = 0.29), and PNC (r2 = 0.49) had moderate or moderate-low out of sample predictive accuracy. We conducted a sensitivity analysis and found that the minimum number of 'n visits' (mobile monitoring sessions) required to model annually representative air pollution concentrations was between 24 and 32 visits dependent on the pollutant. This study provides a single source of exposure models for a comprehensive set of air pollutants in Quebec City, Canada. These exposure models will feed into epidemiological research on the health impacts of ambient UFPs and other pollutants.

Long- and short-term health benefits attributable to PM2.5 constituents reductions from 2013 to 2021: A spatiotemporal analysis in China

Long- and short-term exposure to constituents of fine particulate matter (PM2.5) substantially affects human health. However, assessments of the health and economic benefits of reducing PM2.5 constituents are scarce. This study estimates the number of premature deaths from all-cause, cardiovascular (CVD), and respiratory diseases avoided due to reductions in daily and annual average concentrations of PM2.5 constituents. The Environmental Benefits Mapping and Analysis Program was used for two scenarios: we used yearly concentrations of PM2.5 constituents from 2013 to 2020 as the baseline concentration surface (Scenario I), and 2021 as the baseline year (Scenario II). With reductions in daily and annual average concentrations of PM2.5 constituents, 309,099 (95 % confidence interval [CI]: 37,265-571,485) and 195,297 (95 % CI: 178,192-211,914) premature deaths were avoided in Scenario I, respectively; meanwhile, 347,296 (95 % CI: 79,258-604,758) and 201,567 (95 % CI: 185,038-217,530) premature deaths were avoided in Scenario II, respectively. Moreover, economic benefits associated with the prevention of premature deaths were estimated using the willingness to pay (WTP) and modified human capital (AHC) methods. The total estimated economic benefits amounted to 563.32 billion RMB (WTP) and 322.03 billion RMB (AHC) in Scenario I. In Scenario II, the associated economic benefits were 751.48 billion RMB (WTP) and 427.56 billion RMB (AHC), accounting for 0.657 and 0.374 % of China's gross domestic product in 2021, respectively. Additionally, we analyzed the sensitivity of CVD-related premature deaths to the concentrations of PM2.5 constituents, and found that CVD-related premature deaths were more sensitive to black carbon.

Trade-offs between cold protection and air pollution-induced mortality of China's heating policy

The winter heating policy in northern China was designed to safeguard households from the harsh subfreezing temperatures. However, it has inadvertently resulted in seasonal spikes in air pollution levels because of the reliance on coal as an energy source. While the loss of life years attributable to mortality from air pollution caused by winter heating has been estimated, the beneficial effect of protection from cold temperatures has not been assessed, primarily due to a lack of individual-level data linking these variables. Our study aims to address this research gap. We provide individual-level empirical evidence that quantifies the impact of protection from cold temperatures and air pollution on mortality, studying 5,334 older adults living around the Huai River during the period between 2000 and 2018. Our adjusted Cox-proportional hazard models show that winter heating was associated with a 22% lower mortality rate (95% CI: 16-28%). Individuals residing in areas without access to winter heating are subjected to heightened mortality risks during periods of cold temperatures. The protective effect is offset by a 27.8% rise attributed to elevated PM2.5 levels. Our results imply that the equilibrium between the effects of these two factors is achieved when PM2.5 concentration exceeds 24.3 µg/m3 (95% CI: 18.4-30.2). Our research suggests that while the existing winter heating policy significantly mitigates winter mortality by lessening the detrimental effects of cold temperatures, future air pollution reduction could provide further health benefits.

Trends in all causes and cause specific mortality attributable to ambient particulate matter pollution in China from 1990 to 2019: A secondary data analysis study

BACKGROUND

Particularly fine particulate matter (PM2.5) has become a significant public health concern in China due to its harmful effects on human health. This study aimed to examine the trends in all causes and cause specific morality burden attributable to PM2.5 pollution in China.

METHODS

We extracted data on all causes and cause specific mortality data attributable to PM2.5 exposure for the period 1990-2019 in China from the Global Burden of Disease 2019. The average annual percent change (AAPC) in age-standardized mortality rates (ASMR) and years of life lost (YLLs) due to PM2.5 exposure were calculated using the Joinpoint Regression Program. Using Pearson's correlation, we estimated association between burden trends, urban green space area, and higher education proportions.

RESULTS

During the period 1990-1999, there were increases in mortality rates for All causes (1.6%, 95% CI: 1.5% to 1.8%), Diabetes mellitus (5.2%, 95% CI: 4.9% to 5.5%), Encephalitis (3.1%, 95% CI: 2.6% to 3.5%), Ischemic heart disease (3.3%, 95% CI: 3% to 3.6%), and Tracheal, bronchus and lung cancer (5%, 95% CI: 4.7% to 5.2%). In the period 2010-2019, Diabetes mellitus still showed an increase in mortality rates, but at a lower rate with an AAPC of 1.2% (95% CI: 1% to 1.4%). Tracheal bronchus and lung cancer showed a smaller increase in this period, with an AAPC of 0.5% (95% CI: 0.3% to 0.6%). In terms of YLLs, the trends appear to be similar.

CONCLUSION

Our findings highlight increasing trends in disease burden attributable to PM2.5 in China, particularly for diabetes mellitus, tracheal, bronchus, and lung cancer.

The mortality trends analysis of ischemic heart disease attributed to (PM) 2.5 exposure in China from 1990 to 2019 in APC model

OBJECTIVE

To analyze the mortality trend of ischemic heart disease (IHD) attributed to particulate matter (PM) 2.5 exposure among Chinese populations from 1990 to 2019. To evaluate the influences of cohort, period, and age on long-term of IHD mortality trends.

METHODS

Global burden of disease (GBD) data in 2019 regarding IHD death rate attributed to exposure to (PM) 2.5 in China from 1990 to 2019 were adopted. The age-period-cohort (APC) model based on the R language produced by the National Cancer Institute of the United States was used for statistical analysis to investigate the influences of different ages, periods, and cohorts on IHD death rate attributed to exposure to (PM) 2.5.

RESULTS

The age-standardized death rate of IHD attributed to exposure to ambient (PM) 2.5 in China revealed an uptrend from 1990 to 2019. This increased from 8.63/100,000 in 1990 to 21.31/100,000 in 2019. This was an increase of 1.47%. The age-standardized IHD death rate attributed to exposure to household (PM) 2.5 showed a decreasing trend. This decreased from 19.61/100,000 in 1990 to 8.72/100,000 in 2019. This was a decrease of 0.74%. The results of the APC model indicated that the annual net drift of IHD mortality attributed to exposure to (PM) 2.5 was -0.10%. The annual net drifts of exposure to household and ambient (PM) 2.5 were -4.54% and 3.44%, respectively. The IHD death rate attributed to ambient and household (PM) 2.5 exposure in the same birth cohort enhanced with age. With time, the rate ration (RR) of period effects of IHD mortality attributed to ambient (PM) 2.5 exposure for both male and female showed an upward trend. The RR of period effects of IHD death rate attributed to household (PM) 2.5 exposure suggested a downtrend. In the consecutive birth cohorts, the population in China with a later birth cohort presented a higher risk of IHD death attributed to exposure to ambient (PM) 2.5 and a lower risk of IHD death attributed to household (PM) 2.5 exposure.

CONCLUSIONS

In China for the burden of IHD attributed to exposure to (PM) 2.5, the primary environmental risk was ambient (PM) 2.5 exposure compared to exposure to household PM2.5. IHD exposure to environmental air pollution posed a greater risk to young people.

Air pollution and associated health impact and economic loss embodied in inter-provincial electricity transfer in China

As the largest producer and consumer of coal in the world, China heavily relies on coal resources for thermal power generation. Owing to the unbalanced distribution of energy resources, electricity transfer among regions in China plays a key role in promoting economic growth and ensuring energy safety. However, little is known about air pollution and the related health impacts resulting from electricity transfer. This study assessed PM_2.5 pollution and related health and economic losses attributable to the inter-provincial electricity transfer in mainland China in 2016. The results show that a large amount of virtual air pollutant emissions were transferred from energy-abundant northern, western and central China to well-developed and populated eastern coastal regions. Correspondingly, the inter-provincial electricity transfer dramatically reduced the atmospheric levels of PM_2.5 and related health and economic losses in eastern and southern China, while increasing those in northern, western and central China. The health benefits attributable to inter-provincial electricity transfer were mainly found in Guangdong, Liaoning, Jiangsu and Shandong, whereas the extra health loss is concentrated in Hebei, Shanxi, Inner Mongolia, and Heilongjiang. Overall, the inter-provincial electricity transfer led to an extra increase of 3600 (95 % CI: 3200-4100) PM_2.5-related deaths and 345 (95 % CI: 294-389) million USD of economic loss in China in 2016. The results could assist air pollution mitigation strategies for the thermal power sector in China by strengthening the cooperation between suppliers and consumers of electricity.

Impact analysis of meteorological variables on PM2.5 pollution in the most polluted cities in China

With the continuous promotion of urbanization in China, air pollution problems have become increasingly prominent in recent years. Various factors, such as emissions, meteorology, and physical and chemical reactions, jointly affect the severity of PM_2.5 pollution to a large extent. This study selected five meteorological variables (planetary boundary layer height (PBLH), wind speed (WS), temperature(T), water vapor mixing ratio(Q), and precipitation (PCP)) for perturbation, and 21 different scenarios were set up. In this study, the effects of changes in a single meteorological variable on the pollutants produced in the area were represented by subtracting the baseline scenario (i.e., without perturbation of meteorological variables) simulated in January 2017 separately from each post-disturbance scenario. The results showed that Handan (HD) has the highest annual mean PM_2.5 concentration of 85.75 μg/m³ in 2017, while all cities in study area exceeded the secondary concentration limit of urban atmospheric particulate matter. The correlation coefficient (R) between the simulation values of models and the actual monitoring values ranges from 0.41 to 0.74, indicating good model performance and acceptable simulation errors. PBLH (±10%-±20%), WS(±10%-±20%), and PCP(±10%-±20%) all showed a single adverse effect among the five meteorological variables, meaning that a reduction in these three factors led to an increase in PM_2.5 concentrations. However, T (±1 K-±1.5 K) and Q (±10%-±20%) could indicate a positive impact under certain conditions. From the sensitivity calculations of single meteorological variables, it is clear that WS, PBLH, and PCP show a highly linear trend in all cities at the 0.01 level of significance. The hypothesis that T changes linearly in 10 cities in the study area is valid, while for Q, the hypothesis that Q changes linearly only occurs in Shijiazhuang and Baoding. When different meteorological variables are disturbed, there are significant spatial differences in the main affected areas of PM_2.5 concentrations. By discussing the impact of meteorological variable disturbance on air quality in critically polluted cities in China, this study identified the meteorological variables that can substantially affect PM_2.5 concentration. The more complex T and Q should be considered when formulating relevant emission measures.

Identifying the Environmental Determinants of Lung Cancer: A Case Study of Henan, China

Lung cancer has become one of the most prevalent cancers in the last several decades. Studies have documented that most cases of lung cancer are caused by inhaling environmental carcinogens while how external environmental factors lead to individual lung cancer is still an open issue as the pathogenesis may come from the combined action of multiple environmental factors, and such pathogenic mechanism may vary from region to region. Based on the data of lung cancer cases from hospitals at the county level in Henan from 2016 to 2020, we analyzed the response relationship between lung cancer incidence and physical ambient factors (air quality, meteorological conditions, soil vegetation) and socioeconomic factors (occupational environment, medical level, heating mode, smoking behavior). We used a Bayesian spatio-temporal interaction model to evaluate the relative risk of disease in different regions. The results showed that smoking was still the primary determinant of lung cancer, but the influence of air quality was increasing year by year, with meteorological conditions and occupational environment playing a synergistic role in this process. The high-risk areas were concentrated in the plains of East and Central Henan and the basin of South Henan, while the low-risk areas were concentrated in the hilly areas of North and West Henan, which were related to the topography of Henan. Our study provides a better understanding of the environmental determinants of lung cancer which will help refine existing prevention strategies and recognize the areas where actions are required to prevent environment and occupation related lung cancer.

Substantial short- and long-term health effect due to PM2.5 and the constituents even under future emission reductions in China

Heavy pollution events of fine particulate matter (PM_2.5) frequently occur in China, seriously affecting the human health. However, how meteorological factors and anthropogenic emissions affect PM_2.5 and the major constituents, as well as the subsequent health effect, remains unclear. Here, based on regional climate and air quality models Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ), the PM_2.5 and major constituents in China at present and mid-century under the carbon neutral scenario Shared Socioeconomic Pathways (SSP)1-2.6 are simulated. Due to anthropogenic emission reduction, concentrations of PM_2.5 and the constituents decrease substantially in SSP1-2.6. The long-term exposure premature deaths at present are 2.23 million per year in mainland China, which is projected to increase by 76 % under SSP1-2.6 despite emission reduction, primarily attributable to aging which strikingly offsets the effect of air quality improvement. The number of annual premature deaths resulting from short-term exposure is 228,104 in mainland China at present, which is projected to decrease in the future. Using North China Plain as an example, we identify that among the major constituents of PM_2.5, organic carbon leads to the most short-term exposure deaths considering the largest exposure-response coefficient. Regarding the abnormally meteorological conditions, we find, relative to low relative humidity (RH) and non-stagnation, the compound events, defined as concurrence of high RH and atmospheric stagnation, exhibit an amplified role inducing larger premature deaths compared to the additive effect of the individual event of high RH and atmospheric stagnation. This nonlinear effect occurs at both present and future, but diminished in future due to emission reductions. Our study highlights the importance of considering both the long- and short-term premature deaths associated with PM_2.5 and the constituents, as well as the critical effect of extreme weather events.

Source Contributions to PM2.5-Related Mortality and Costs: Evidence for Emission Allocation and Compensation Strategies in China

The emissions from various pollution sources were not proportional to their contributions to ambient PM_2.5 concentrations and associated health burdens. That means even with the same total abatement targets, different abatement allocation strategies across emission sources can have distinct health benefits. Insufficient knowledge of various sources' contributions to health burdens in China, the country suffering substantial PM_2.5-related deaths, hindered the government from seeking optimized abatement allocation strategies. In this context, we separated the contributions of 155 emission sources (31 provinces × 5 sectors) to PM_2.5-related mortality across China in 2017 by coupling the Comprehensive Air Quality Model with Extensions (CAMx), Weather Research and Forecasting model (WRF), and health impact assessment model. We further identified the priority-control emission sources and quantified interprovincial ecological compensation volumes to alleviate inequality induced by emission allocation strategies. Results showed that PM_2.5 pollution caused 899,443 excess deaths and around 127 billion USD costs in 2017. Approximately half of the deaths and costs were attributable to emissions from sources outside the boundary of the regions where the deaths occurred. Twenty-five out of 155 emission sources that contributed to the top 60% mortality burdens and had high marginal abatement efficiencies in China shall be the priority-control emission sources. A 1 μg/m³ decrease of PM_2.5 concentration in regions where these key emission sources occur shall be compensated by 76-153 million USD in their receptor regions. Our study sheds light on the sources' contributions to mortality burdens and costs and provides scientific evidence for optimizing the emission allocation and compensation strategies in China. It also has wide implications for other countries suffering similar problems.

Air quality improvement through vehicle electrification in Hainan province, China

To improve the ecological environment, provinces in China have set ambitious goals for the electrification of fossil-fuel-powered vehicles (FVs) and the promotion of electric vehicles (EVs). Hainan is the first province to propose a clean energy target that schedules the banning of new FVs sales from 2030. Therefore, Hainan is a good case study to illustrate how this policy might improve regional air quality over the coming years. This study first developed an anthropogenic emission inventory of seven major air pollutants in 2017 in Hainan. The total emissions of CO, NOx, NH3, volatile organic compounds (VOCs), PM10 and PM2.5 and SO2 in 2017 were estimated as 247.56, 69.61, 61.87, 41.38, 37.02, 19.82, and 8.55 kt, respectively. Using the developed emission inventory, multiple scenarios of economic development were considered to assess the benefits to air quality from Hainan's goal of electrification. In comparison with 2017, the reductions in emissions of SO2, NOx, CO, PM10, PM2.5, VOCs, and NH3 by 2045 were projected to be 5.45 (11.11%), 275.07 (57.32%), 675.51 (34.07%), 8.39 (5.73%), 7.73 (8.24%), 81.15 (9.76%), and 4.89 (0.91%) kt, respectively, under the all-electric vehicle scenarios. These results indicate that this policy will not only reduce the emission of air pollutants but also avoid complex O3 pollution in the future. The findings of this work elucidate the effects of vehicle electrification policies on regional air quality and provide scientific support for policymakers in developing pollution control strategies.

Trends in the Burden of COPD Attributable to Ambient PM2.5 Exposure in China 1990-2019: An Age-Period-Cohort Analysis

Objective

Exposure to ambient particulate matter (PM_2.5) is the leading risk factor for developing chronic obstructive pulmonary disease (COPD) in China. The present study aimed to investigate the trends in COPD mortality attributable to ambient PM_2.5 exposure in China from 1990 to 2019.

Methods

Data on COPD burden attributable to ambient PM_2.5 exposure in China were extracted from the Global Burden of Disease (GBD) study 2019. The estimated annual percentage change (EAPC) was used to assess COPD mortality from 1990 to 2019. The APC model was used to analyze the temporal trends in the rate of COPD mortality attributable to ambient PM_2.5 exposure according to age, period, and cohort.

Results

Exposure to ambient PM_2.5 contributed to 192.4 thousand deaths in 1990 and 263.6 thousand deaths in 2019. The age-standardized mortality rate (ASMR) and the age-standardized disability-adjusted life year rate (ASDR) due to ambient PM_2.5 exposure showed a gradual downward trend, the ASMR and ASDR in 2019 decreased to 16.6 per 100,000 with an EAPC of -2.82 (95% CI: -8.61 to 3.34) and 278.6 per 100,000 with an EAPC of -2.02 (95% CI: -7.85 to 4.19), compared to those in 1990, respectively. The relative risk (RR) of COPD increased with age in females, while in males, mortality significantly increased from the levels among those in the 60-64 age group to that among those in the 90-94 age group. In the period group, the RR of COPD in males remained above 1.0 from the 2000 to 2004 period, but it gradually decreased in females. The cohort effect showed an overall downward trend.

Conclusion

Although the ASMR and ASDR are decreasing in Chinese patients with COPD, the number of deaths due to COPD is increasing. Ambient PM_2.5 exposure is more harmful in males and older people above 60 years of age.

Tracking long-term population exposure risks to PM2.5 and ozone in urban agglomerations of China 2015-2021

China has experienced severe air pollution in the past decade, especially PM2.5 and emerging ozone pollution recently. In this study, we comprehensively analyzed long-term population exposure risks to PM2.5 and ozone in urban agglomerations of China during 2015-2021 regarding two-stage clean-air actions based on the Ministry of Ecology and the Environment (MEE) air monitoring network. Overall, the ratio of the population living in the regions exceeding the Chinese National Ambient Air Quality Standard (35 μg/m3) decreases by 29.9 % for PM2.5 from 2015 to 2021, driven by high proportions in the Middle Plain (MP, 42.3 %) and Lan-Xi (35.0 %) regions. However, this ratio almost remains unchanged for ozone and even increases by 1.5 % in the MP region. As expected, the improved air quality leads to 234.7 × 103 avoided premature mortality (ΔMort), mainly ascribed to the reduction in PM2.5 concentration. COVID-19 pandemic may influence the annual variation of PM2.5-related ΔMort as it affects the shape of the population exposure curve to become much steeper. Although all eleven urban agglomerations share stroke (43.6 %) and ischaemic heart disease (IHD, 30.1 %) as the two largest contributors to total ΔMort, cause-specific ΔMort is highly regional heterogeneous, in which ozone-related ΔMort is significantly higher (21 %) in the Tibet region than other urban agglomeration. Despite ozone-related ΔMort being one order of magnitude lower than PM2.5-related ΔMort from 2015 to 2021, ozone-related ΔMort is predicted to increase in major urban agglomerations initially along with a continuous decline for PM2.5-related ΔMort from 2020 to 2060, highlighting the importance of ozone control. Coordinated controls of PM2.5 and O3 are warranted for reducing health burdens in China during achieving carbon neutrality.

The efforts of China to combat air pollution during the period of 2015-2018: A case study assessing the environmental, health and economic benefits in the Beijing-Tianjin-Hebei and surrounding "2 + 26" regions

During the period of 2015-2018, Chinese government had made great efforts to mitigate air pollutants, such as air quality monitoring, energy structure adjustment, and pollutant emission reduction from industry, transportation and household sectors. With the special investment of 152 billion Chinese Yuan (CNY) in the Beijing-Tianjin-Hebei (BTH) and surrounding "2 + 26" regions, the annual local concentrations of PM_2.5, PM₁₀, SO₂ and NO₂ decreased from 77, 132, 38 and 46 μg/m³ to 60, 109, 20 and 43 μg/m³. It was estimated that the improvement in air quality avoided 27,021 (95 % CIs 12,548-39,738) premature deaths attributed to air pollution exposure based on an exposure-response function, including 45 %, 17 % and 15 % of cardiopulmonary, lung cancer and respiratory morality cases. Air pollution reduction was also effective in reducing work time loss, which reduced the total working time loss by 3.8 × 10⁷ (95 % CIs 1.8 × 10⁷-5.6 × 10⁷) h, and the per capita working time loss by 0.28 (95 % CIs 0.13-0.41) h/capita by 2018. From the economic aspect, air pollution control actions in those regions saved 95.6 (95 % CIs 44.2-141) billion CNY economic loss by using the value of statistical life (VSL). The total benefit-cost ratio was 63.7 % (95 % CIs 29.4 %-93.7 %). The cost-effectiveness in Beijing and Tianjin were relatively low due to the regional contribution from other cities of the air pollution transmission channel. Despite the uncertainties, the results clearly show the significance of the environmental, health and economic benefits of actions in the BTH and surrounding "2 + 26" regions for combating air pollution.

Air Pollutants in Metropolises of Eastern Coastal China

Recently released hourly particular matter (PM:PM_2.5 and PM₁₀) and gaseous pollutants (SO₂, NO₂, CO, and O₃) data observed in Qingdao, Hangzhou, and Xiamen from 2015 to 2019 were utilized to reveal the current situation of air pollution over eastern coastal China. The PM pollution situation over the three metropolises ameliorated during studied period with the concentrations decreasing about 20-30%. Gas pollutants, excepting SO₂, generally exhibit no evident reduction tendencies, and a more rigorous control standard on gaseous pollutants is neededEven for the year 2018 with low pollution levels among the study period, these levels (<10% of PM_2.5, <6% of PM₁₀, and <15% of O₃) surpass the Grade II of the Chinese Ambient Air Quality Standard (CAAQS) over these metropolises of eastern coast China. No matter in which year, both SO₂ and CO concentrations are always below the Grade-II standards. According to the comparative analysis of PM_2.5/PM₁₀ and PM_2.5/CO during episode days and non-episode days, the formation of secondary aerosols associated with stagnant weather systems play an important role in the pollutant accumulation as haze episodes occurred. The stronger seasonal variations and higher magnitude occur in Qingdao and Hangzhou, while weaker seasonal variations and lower magnitudes occur in Xiamen. In Qingdao and Hangzhou, PM, NO₂, SO₂, and CO show relatively high levels in the cold wintertime and low levels in summer, whereas O₃ shows a completely opposite pattern. Xiamen exhibits high levels of all air pollutants except O₃ in spring due to its subtropical marine monsoon climate with mild winters. According to the back trajectory hierarchical clustering and concentration weighted trajectory (CWT) analysis, the regional transmission from adjacent cities has a significant impact on the atmospheric pollutant concentrations under the control of the prejudiced winds. Thus, besides local emission reduction, strengthening regional environmental cooperation and implementing joint prevention are effective measures to mitigate air pollution in the eastern coastal areas of China.

Spatial Effect of Digital Economy on Particulate Matter 2.5 in the Process of Smart Cities: Evidence from Prefecture-Level Cities in China

During the COVID-19 pandemic, the digital economy has developed rapidly. The airborne nature of COVID-19 viruses has attracted worldwide attention. Therefore, it is of great significance to analyze the impact of the digital economy on particulate matter 2.5 (PM2.5) emissions. The research sample of this paper include 283 prefecture-level cities in China from 2011 to 2019 in China. Spatial Durbin model was adopted to explore the spatial spillover effect of digital economy on PM2.5 emissions. In addition, considering the impact of smart city pilot (SCP) policy, a spatial difference-in-differences (SDID) model was used to analyze policy effects. The estimation results indicated that (1) the development of the digital economy significantly reduces PM2.5 emissions. (2) The spatial spillover effect of the digital economy significantly reduces PM2.5 emissions in neighboring cities. (3) Smart city construction increases PM2.5 emissions in neighboring cities. (4) The reduction effect of the digital economy on PM2.5 is more pronounced in the sample of eastern cities and urban agglomerations.

Assessment of NO2 population exposure from 2005 to 2020 in China

Nitrogen dioxide (NO2) is a major air pollutant with serious environmental and human health impacts. A random forest model was developed to estimate ground-level NO2 concentrations in China at a monthly time scale based on ground-level observed NO2 concentrations, tropospheric NO2 column concentration data from the Ozone Monitoring Instrument (OMI), and meteorological covariates (the MAE, RMSE, and R2 of the model were 4.16 µg/m3, 5.79 µg/m3, and 0.79, respectively, and the MAE, RMSE, and R2 of the cross-validation were 4.3 µg/m3, 5.82 µg/m3, and 0.77, respectively). On this basis, this article analyzed the spatial and temporal variation in NO2 population exposure in China from 2005 to 2020, which effectively filled the gap in the long-term NO2 population exposure assessment in China. NO2 population exposure over China has significant spatial aggregation, with high values mainly distributed in large urban clusters in the north, east, south, and provincial capitals in the west. The NO2 population exposure in China shows a continuous increasing trend before 2012 and a continuous decreasing trend after 2012. The change in NO2 population exposure in western and southern cities is more influenced by population density compared to northern cities. NO2 pollution in China has substantially improved from 2013 to 2020, but Urumqi, Lanzhou, and Chengdu still maintain high NO2 population exposure. In these cities, the Environmental Protection Agency (EPA) could reduce NO2 population exposure through more monitoring instruments and limiting factory emissions.

How the Air Clean Plan and carbon mitigation measures co-benefited China in PM2.5 reduction and health from 2014 to 2020

China implemented a stringent Air Clean Plan (ACP) since 2013 to address environmental and health risks caused by ambient fine particulate matter (PM_2.5). However, the policy effectiveness of ACP and co-benefits of carbon mitigation measures to environment and health are still largely unknown. Using satellite-based PM_2.5 products produced in our previous study, concentration-response functions, and the logarithmic mean Divisia index (LMDI) method, we analyzed the spatiotemporal dynamics of premature deaths attributable to PM_2.5 exposure, and quantitatively estimated the policy benefits of ACP and carbon mitigation measures. We found the annual PM_2.5 concentrations in China decreased by 33.65 % (13.41 μg m^-3) from 2014 to 2020, accompanied by a decrease in PM_2.5-attributable premature deaths of 0.23 million (95 % confidence interval (CI): 0.22-0.27), indicating the huge benefits of China ACP for human health and environment. However, there were still 1.12 million (95 % CI: 0.79-1.56) premature deaths caused by the exposure of PM_2.5 in mainland China in 2020. Among all ACP measures, clean production (contributed 55.98 % and 51.14 % to decrease in PM_2.5 and premature deaths attributable to PM_2.5) and energy consumption control (contributed 32.58 % and 29.54 % to decrease in PM_2.5 and premature deaths attributable to PM_2.5) made the largest contribution during the past seven years. Nevertheless, the environmental and health benefits of ACP are not fully synergistic in different regions, and the effectiveness of ACP measures reduced from 2018 to 2020. The co-effects of CO₂ and PM_2.5 has become one of the major drivers for PM_2.5 and premature deaths reduction since 2018, confirming the clear environment and health co-benefits of carbon mitigation measures. Our study suggests, with the saturation of clean production and source control, more targeted region-specific strategies and synergistic air pollution-carbon mitigation measures are critical to achieving the WHO's Air Quality Guideline target and the UN's Sustainable Development Goal Target in China.

Assessing the effects of ultraviolet radiation, residential greenness and air pollution on vitamin D levels: A longitudinal cohort study in China

Vitamin D metabolism is essential in aging and can be affected by multiple environmental factors. However, most studies conducted single exposure analyses. We aim to assess the individual and combined effects of ultraviolet (UV) radiation, residential greenness, fine particulate matter (PM_2.5), and ozone (O₃) on vitamin D levels in a national cohort study of older adults in China. We used the 2012 and 2014 Chinese Longitudinal Healthy Longevity Survey data, and measured the environmental exposure in the same year. We interpolated the UV radiation from monitoring stations, measured residential greenness through satellite-derived Normalized Difference Vegetation Index (NDVI), modeled PM_2.5 with satellite data, and estimated O₃ using machine learning. We dichotomized serum 25-hydroxy vitamin D (25(OH)D), the primary circulating form of vitamin D, into non-deficiency (≥50 nmol/L) and deficiency (<50 nmol/L) categories. We used the generalized estimating equation for analysis, adjusted for sociodemographic information, lifestyle, physical condition, and season of blood draw, and calculated joint odds ratios based on the Cumulative Risk Index. We also explored the interaction between interested exposures, modification of participants' characteristics, and potential mediation. We included 1,336 participants, with a mean age of 83 at baseline. In single exposure models, the odds ratios of vitamin D deficiency (VDD) for per interquartile range increase in UV radiation, NDVI, PM_2.5, and O₃ and decrease were 0.39 (95 % CI:0.33,0.46), 0.90 (0.81,1.00), 1.65 (1.53,1.78), 1.67 (1.46,1.92), respectively. UV radiation mediated nearly 48 % and 78 % of the relationship between VDD and PM_2.5 and O₃, respectively. The association between UV radiation and VDD was stronger in females than men (OR: 2.25 vs 1.22). UV radiation, residential greenness can protect against VDD, while, PM_2.5 and O₃ increase the risk of VDD. UV radiation partly mediated the association between air pollution and VDD.

Relationship between air pollution and childhood atopic dermatitis in Chongqing, China: A time-series analysis

Background

The prevalence of atopic dermatitis (AD) in children has increased substantially in China over past decades. The ongoing rise in the prevalence stresses the important role of the environmental factors in the pathogenesis of AD. However, studies evaluating the effects of air pollution on AD in children are scarce.

Objective

To quantitatively assess the association between air pollution and outpatient visits for AD in children.

Methods

In this time-series study, we collected 214,747 children of AD from January 1, 2015 to December 31, 2019 through the electronic data base in the Children's Hospital of Chongqing Medical University. The number of daily visits was treated as the dependent variable, and generalized additive models with a Poisson like distribution were constructed, controlling for relevant potential confounders and performing subgroup analyses.

Results

Each 10 μg/m³ increase in PM_2.5, PM₁₀, SO₂, NO₂ and each 1 mg/m³ increase in CO concentrations was significantly associated with a 0.7% (95% CI: 0.2, 1.3%), 0.9% (95% CI: 0.5, 1.4%), 11% (95% CI: 7.5, 14.7%), 5.5% (95% CI: 4.3, 6.7%) and 10.1% (95% CI: 2.7, 18.2%) increase of AD outpatient visits on the current day, respectively. The lag effect was found in SO₂, PM₁₀, and NO_2. The effects were stronger in cool season and age 0-3 group.

Conclusions

Our study suggests that short-term exposure to ambient air pollution contributes to more childhood AD outpatient visits in Chongqing, China.

Assessment of long-term particulate nitrate air pollution and its health risk in China

Air pollution is a major environmental and public health challenge in China and the Chinese government has implemented a series of strict air quality policies. However, particulate nitrate (NO₃⁻) concentration remains high or even increases at monitoring sites despite the total PM_2.5 concentration has decreased. Unfortunately, it has been difficult to estimate NO₃⁻ concentration across China due to the lack of a PM_2.5 speciation monitoring network. Here, we use a machine learning model incorporating ground measurements and satellite data to characterize the spatiotemporal patterns of NO₃⁻, thereby understanding the disease burden associated with long-term NO₃⁻ exposure in China. Our results show that existing air pollution control policies are effective, but increased NO₃⁻ of traffic emissions offset reduced NO₃⁻ of industrial emissions. In 2018, the national mean mortality burden attributable to NO₃⁻ was as high as 0.68 million, indicating that targeted regulations are needed to control NO₃⁻ pollution in China.

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We build a NO₃⁻ model using machine learning techniques incorporating satellite data

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We estimate spatiotemporal variations of NO₃⁻ concentration in China from 2005–2018

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In 2018, the national mean mortality burden attributable to NO₃⁻ was about 0.68 million

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Targeted regulations on vehicle emissions are needed to control NO₃⁻ pollution in China

The influence of socioeconomic and environmental determinants on acute myocardial infarction (AMI) mortality from the spatial epidemiological perspective

Plenty of epidemiological approaches have been explored to detect the effects of environmental and socioeconomic factors on acute myocardial infarction (AMI) mortality. Whereas, identifying the influence of potential affecting factors on AMI mortality based on a spatial epidemiological perspective was strongly desired. Moreover, the interaction effects of two potential factors on the diseases were always neglected previously. Here, the Geodetector and geographically & temporally weighted regression model (GTWR) combined with multi-source spatiotemporal datasets were introduced to quantitatively determine the relationship between AMI mortality and potential influencing factors across Xi'an during 2014-2016. Besides, Moran's I was adopted to diagnose the spatial autocorrelation of AMI mortality. Some findings were achieved. The number of AMI mortality cases increased from 5075 in 2014 to 6774 in 2016. Air pollutants, meteorological factors, economic status, and topography factors exhibited a significant effect on AMI mortality. The AMI mortality demonstrated an obvious spatial autocorrelation feature during 2014-2016. POP and PE represented the most obvious impact on AMI mortality, respectively. Moreover, the interaction of any two factors was larger than that of the single factor on AMI mortality, and the factors with the strongest interaction vary according to lag groups and ages. The effects of factors on AMI mortality were POP (- 628.925) > PE (140.102) > RD (79.145) > O₃ (- 58.438) > E_NH₃ (42.370) for male, and POP (- 751.206) > RD (132.935) > E_NH₃ (58.758) > PE (- 45.434) > O₃ (- 21.256) for female, respectively. This work reminds the local government to continuously control air pollution, strengthen urban planning, and improve the health care of the rural areas for alleviating AMI mortality. Meanwhile, the scheme of the current study supplies a scientific reference for examining the effects of potential impact factors on related diseases using the spatial epidemiological perspective.

Air Pollution and Human Health: Investigating the Moderating Effect of the Built Environment

Air pollution seriously threatens human health and even causes mortality. It is necessary to explore effective prevention methods to mitigate the adverse effect of air pollution. Shaping a reasonable built environment has the potential to benefit human health. In this context, this study quantified the built environment, air pollution, and mortality at 1 km × 1 km grid cells. The moderating effect model was used to explore how built environment factors affect the impact of air pollution on cause-specific mortality and the heterogeneity in different areas classified by building density and height. Consequently, we found that greenness played an important role in mitigating the effect of ozone (O3) and nitrogen dioxide (NO2) on mortality. Water area and diversity of land cover can reduce the effect of fine particulate matter (PM2.5) and NO2 on mortality. Additionally, gas stations, edge density (ED), perimeter-area fractal dimension (PAFRAC), and patch density (PD) can reduce the effect of NO2 on mortality. There is heterogeneity in the moderating effect of the built environment for different cause-specific mortality and areas classified by building density and height. This study can provide support for urban planners to mitigate the adverse effect of air pollution from the perspective of the built environment.

Mortality burden due to long-term exposure to ambient PM2.5 above the new WHO air quality guideline based on 296 cities in China

OBJECTIVE

Quantifying the spatial and socioeconomic variation of mortality burden attributable to particulate matters with aerodynamic diameter ≤ 2.5 µm (PM2.5) has important implications for pollution control policy. This study aims to examine the regional and socioeconomic disparities in the mortality burden attributable to long-term exposure to ambient PM2.5 in China.

METHODS

Using data of 296 cities across China from 2015 to 2019, we estimated all-cause mortality (people aged ≥ 16 years) attributable to the long-term exposure to ambient PM2.5 above the new WHO air quality guideline (5 µg/m3). Attributed fraction (AF), attributed deaths (AD), attributed mortality rate (AMR) and total value of statistical life lost (VSL) by regional and socioeconomic levels were reported.

RESULTS

Over the period of 2015-2019, 17.0% [95% confidence interval (CI): 7.4-25.2] of all-cause mortality were attributable to long-term exposure to ambient PM2.5, corresponding to 1,425.2 thousand deaths (95% CI: 622.4-2,099.6), 103.5/105 (95% CI: 44.9-153.3) AMR, and 1006.9 billion USD (95% CI: 439.8-1483.4) total VSL per year. The AMR decreased from 120.5/105 (95% CI: 52.9-176.6) to 92.7/105 (95% CI:39.9-138.5) from 2015 to 2019. The highest mortality burden was observed in the north region (annual average AF = 24.2%, 95% CI: 10.8-35.1; annual average AMR = 137.0/105, 95% CI: 60.9-198.5). The highest AD and economic loss were observed in the east region (annual average AD = 390.0 thousand persons, 95% CI: 170.3-574.6; annual total VSL = 275.6 billion USD, 95% CI: 120.3-406.0). Highest AMR was in the cities with middle level of GDP per capita (PGDP)/urbanization. The majority of the top ten cities of AF, AMR and VSL were in high and middle PGDP/urbanization regions.

CONCLUSION

There were significant regional and socioeconomic disparities in PM2.5 attributed mortality burden among Chinese cities, suggesting differential mitigation policies are required for different regions in China.

Assessment of PM2.5-related health effects: A comparative study using multiple methods and multi-source data in China

In China, PM_2.5 pollution has caused extensive death and economic loss. Thus, an accurate assessment of the spatial distribution of these losses is crucial for delineating priority areas for air pollution control in China. In this study, we assessed the PM_2.5 exposure-related health effects according to the integrated exposure risk function and non-linear power law (NLP) function in 338 prefecture-level cities in China by utilizing online monitoring data and the PM_2.5 Hindcast Database (PHD). Our results revealed no significant difference between the monitoring data and PHD (p value = 0.66 > 0.05). The number of deaths caused by PM_2.5-related Stroke (cerebrovascular disease), ischemic heart disease, chronic obstructive pulmonary disease, and lung cancer at the national level estimated through the NLP function was 0.27 million (95% CI: 0.06-0.50), 0.23 million (95% CI: 0.08-0.38), 0.31 million (95% CI: 0.04-0.57), and 0.31 million (95% CI: 0.16-0.40), respectively. The total economic cost at the national level in 2016 was approximately US$80.25 billion (95% CI: 24.46-132.25). Based on a comparison of Z statistics, we propose that the evaluation results obtained using the NLP function and monitoring data are accurate. Additionally, according to scenario simulations, Beijing, Chongqing, Tianjin, and other cities should be priority areas for PM_2.5 pollution control to achieve considerable health benefits. Our statistics can help improve the accuracy of PM_2.5-related health effect assessments in China.

Short-term effects of indoor and outdoor air pollution on the lung cancer morbidity in Henan Province, Central China

Lung cancer is one of the most common cancer types and a major cause of death. The relationship between lung cancer morbidity and exposure to air pollutants is of particular concern. However, the relationship and difference in lung cancer morbidity between indoor and outdoor air pollution effects remain unclear. In this paper, the aim was to comprehensively investigate the spatial relationships between the lung cancer morbidity and indoor-outdoor air pollution in Henan based on the standard deviation ellipse, spatial autocorrelation analysis and GeoDetector. The results indicated that (1) the spatial distribution of lung cancer morbidity was related to the geomorphology, while high-morbidity areas were concentrated in the plains and basins of Central, Eastern and Southern Henan. (2) Among the selected outdoor air pollutants, PM_2.5, NO₂, SO₂, O₃ and CO were significantly correlated with the lung cancer morbidity. The degree of indoor air pollution was measured by the use of heating energy, and the proportions of coal-heating households, households with coal/biomass stoves and households with heated kangs were highly decisive in regard to the lung cancer morbidity. (3) The interaction between two factors was more notable than a single factor in explaining the lung cancer morbidity. Moreover, the interaction type was mainly nonlinear enhancement, and the proportion of households with coal/biomass stoves imposed the strongest interaction effect on the other factors.

Unencapsulated and washable two-dimensional material electronic-textile for NO2 sensing in ambient air

Materials adopted in electronic gas sensors, such as chemiresistive-based NO₂ sensors, for integration in clothing fail to survive standard wash cycles due to the combined effect of aggressive chemicals in washing liquids and mechanical abrasion. Device failure can be mitigated by using encapsulation materials, which, however, reduces the sensor performance in terms of sensitivity, selectivity, and therefore utility. A highly sensitive NO₂ electronic textile (e-textile) sensor was fabricated on Nylon fabric, which is resistant to standard washing cycles, by coating Graphene Oxide (GO), and GO/Molybdenum disulfide (GO/MoS₂) and carrying out in situ reduction of the GO to Reduced Graphene Oxide (RGO). The GO/MoS₂ e-textile was selective to NO₂ and showed sensitivity to 20 ppb NO₂ in dry air (0.05%/ppb) and 100 ppb NO₂ in humid air (60% RH) with a limit of detection (LOD) of ~ 7.3 ppb. The selectivity and low LOD is achieved with the sensor operating at ambient temperatures (~ 20 °C). The sensor maintained its functionality after undergoing 100 cycles of standardised washing with no encapsulation. The relationship between temperature, humidity and sensor response was investigated. The e-textile sensor was embedded with a microcontroller system, enabling wireless transmission of the measurement data to a mobile phone. These results show the potential for integrating air quality sensors on washable clothing for high spatial resolution (< 25 cm²)—on-body personal exposure monitoring.

Tracking PM2.5 and O3 Pollution and the Related Health Burden in China 2013-2020

Based on the exposure data sets from the Tracking Air Pollution in China (TAP, http://tapdata.org.cn/), we characterized the spatiotemporal variations in PM_2.5 and O₃ exposures and quantified the long- and short-term exposure related premature deaths during 2013-2020 with respect to the two-stage clean air actions (2013-2017 and 2018-2020). We find a 48% decrease in national PM_2.5 exposure during 2013-2020, although the decrease rate has slowed after 2017. At the same time, O₃ pollution worsened, with the average April-September O₃ exposure increased by 17%. The improved air quality led to 308 thousand and 16 thousand avoided long- and short-term exposure related deaths, respectively, in 2020 compared to the 2013 level, which was majorly attributed to the reduction in ambient PM_2.5 concentration. It is also noticed that with smaller PM_2.5 reduction, the avoided long-term exposure associated deaths in 2017-2020 (13%) was greater than that in 2013-2017 (9%), because the exposure-response curve is nonlinear. As a result of the efforts in reducing PM_2.5-polluted days with the daily average PM_2.5 higher than 75 μg/m³ and the considerable increase in O₃-polluted days with the daily maximum 8 h average O₃ higher than 160 μg/m³, deaths attributable to the short-term O₃ exposure were greater than those due to PM_2.5 exposure since 2018. Future air quality improvement strategies for the coordinated control of PM_2.5 and O₃ are urgently needed.

A stochastic exposure model integrating random forest and agent-based approaches: Evaluation for PM2.5 in Jiangsu, China

This research proposes an Activity Pattern embedded Air Pollution Exposure Model (AP2EM), based on survey data of when, where, and how people spend their time and indoor/outdoor ratios for microenvironments. AP2EM integrates random forest and agent-based approaches to simulate the stochastic exposure to outdoor fine particulate matter (PM_2.5) along with indoor and in-vehicle PM_2.5 of outdoor origin. The R² of the linear regression between the model's calculations and personal measurement was 0.65, which was more accurate than the commonly-used aggregated exposure (AE) model and the outdoor exposure (OE) model. The population-weighted PM_2.5 exposure estimated by the AP2EM was 36.7 μg/m³ in Jiangsu, China, during 2014-2017. The OE model overestimated exposure by 54.0%, and the AE model underestimated exposure by 6.5%. These misestimate reflect ignorance of traditional studies on effects posed from time spent indoors (~85%) and doing low respiratory rate activities (~93%), problems of biased sampling, and neglecting low probability events. The proposed AP2EM treats activity patterns of individuals as chains and uses stochastic estimates to model activity choices, providing a more comprehensive understanding of human activity and exposure characteristics. Overall, the AP2EM is applicable for other air pollutants in different regions and benefits China's air pollution control policy designs.

Effects of the INDC and GGRMA Regulations on the Impact of PM2.5 Particle Emissions on Maritime Ports: A Study of Human Health and Environmental Costs

This study employs an activity-based model to estimate the PM2.5 particle emissions from ships, cargo-handling equipment, and heavy-duty vehicles in the Port of Kaohsiung, Taiwan. External health costs, the index of health impact (IHI), and external environmental costs are assessed to quantify the impact of PM2.5 particle emissions. The mitigation regulations applied in this study are the Intended Nationally Determined Contribution Act (INDC) and the Greenhouse Gas Reduction and Management Act (GGRMA). The provisions in these acts are incorporated into Scenario-INDC and Scenario-GGRMA. The results are as follows: from 2005 to 2017, PM2.5 particle emissions caused an external health cost of 3238.30 DALY (disability-adjusted life year), an IHI value of 8.53%, and environmental cost of USD 2176.04 million annually. For Scenario-INDC and Scenario-GGRMA, it is predicted that PM2.5-related external health costs, IHI value, and external environmental cost will decrease by 927.64 DALY, 2.45%, and USD 608.86 million and by 1736.28 DALY, 4.58%, and USD 1139.84 million, respectively, as compared to BAU-2030 and BAU-2050. The results indicate that compliance with INDC and GGRMA regulations will lead to a significant mitigation of PM2.5 particle emissions, resulting in a significant improvements in air quality and human health in addition to a reduction in environmental costs.

What drives long-term PM2.5-attributable premature mortality change? A case study in central China using high-resolution satellite data from 2003 to 2018

Ambient PM_2.5 was reported to be related to numerous negative health outcomes, leading to adverse public health impacts in many countries such as China. Despite the apparent reduction in PM_2.5 levels over China due to its emission control policies in recent years, the health burdens were not reduced as much as expected. This calls for a comprehensive analysis to explain the reasons behind to provide a useful reference for formulating effective emission control strategies. Taking central China as an example due to its large population and high levels of PM_2.5, this study quantified the spatiotemporal dynamics of premature mortality associated with PM_2.5 pollution in central China for each year during 2003-2018 and applied a decomposition analysis to dissect the contribution of various driving factors including ambient PM_2.5 level, demographic distribution and baseline incidence rate of four diseases related to air pollution. Results show significant spatiotemporal variations in PM_2.5-attributed health impact in central China, including Henan, Hubei, and Hunan provinces. Five Henan cities had the largest PM_2.5-attributable premature mortality (∼8-12 K premature mortalities), while three Hubei cities and one Hebei city had the least chronic PM_2.5-related all-cause mortality numbers (<1 K mortalities). Throughout the study period, the PM_2.5-caused premature mortality decreased by 54 K, in which changes in PM_2.5 levels and baseline incidence rates of stroke and chronic obstructive pulmonary disease contributed to the positive effect, whereas demographic changes and baseline incidence rate change of ischemic heart disease and lung cancer brought a countervailing effect. Our findings suggest more dynamic and comprehensive policies and measures that take into account spatiotemporal variations of health burden for effective alleviation of the health impact of PM_2.5 pollution in the country.

Exposure to concentrated ambient PM2.5 (CAPM) induces intestinal disturbance via inflammation and alternation of gut microbiome

Air pollution causes a great disease burden worldwide. Recent evidences suggested that PM_2.5 contributes to intestinal disease. The objective of present study was to investigate the influence of ambient PM_2.5 on intestinal tissue and microbiome via whole-body inhalation exposure. The results showed that high levels and prolonged periods exposure to concentrated ambient PM_2.5 (CAPM) could destroy the mucous layer of the colon, and significantly alter the mRNA expression of tight junction (Occludin and ZO-1) and inflammation-related (IL-6, IL-10 and IL-1β) genes in the colon, comparing with exposure to the filtered air (FA). The composition of intestinal microbiome at the phylum and genus levels also varied along with the exposure time and PM_2.5 levels. At the phylum level, Bacteroidetes was greatly decreased, while Proteobacteria was increased after exposure to CAPM, comparing with exposure to FA. At the genus level, Clostridium XlVa, Akkermansia and Acetatifactor, were significantly elevated exposure to CAPM, comparing with exposure to FA. Our results also indicated that high levels and prolonged periods exposure to CAPM altered metabolic functional pathways. The correlation analysis showed that the intestinal inflammation was related to the alteration of gut microbiome induced by CAPM exposure, which may be a potential mechanism that elucidates PM_2.5-induced intestinal diseases. These results extend our knowledge on the toxicology and health effects of ambient PM_2.5.

A Health Impact and Economic Loss Assessment of O3 and PM2.5 Exposure in China From 2015 to 2020

China is in a critical air quality management stage. Rapid industrial development and urbanization has resulted in non-ignorable air pollution, which seriously endangers human health. Assessment of the health impacts and economic losses of air pollution is essential for the prevention and control policy formulation. Based on ozone (O3) and fine particulate matter concentration (PM2.5) monitoring data in 331 Chinese cities from 2015 to 2020, this study evaluated the health effects and the corresponding economic losses of O3 and PM2.5 pollution on three health endpoints. The ratio of population exposed to O3 levels that exceeded the Chinese Ambient Air Quality Standards (CAAQS) increased from 13.35% in 2015 to 14.15% in 2020, which resulted in 133,415 (2015) - 156,173 (2020) all-cause deaths, 88,941 (2015) - 104,051 (2020) cardiovascular deaths, and 28,614 (2015) - 33,456 (2020) respiratory deaths. The ratio of population exposed to PM2.5 levels that exceeded the CAAQS decreased, but in many regions, especially in North China and the Yangtze River Delta, the PM2.5 concentration remained high. By 2020, nearly half of the population in China was still exposed to PM2.5 levels that exceeded the CAAQS, and the corresponding economic losses reached CNY 3.46 and 3.05 billion, respectively. These results improved the understanding of the spatial-temporal variation trends of major air pollutants at city scale in China, and emphasize the continued coordination urgently needed for controlling O3 and PM2.5 following the implementation of the 2013 policy to mitigate air pollution to protect human health.

Observed causative impact of fine particulate matter on acute upper respiratory disease: a comparative study in two typical cities in China

Association between fine particulate matter (PM_2.5) and respiratory health has attracted great concern in China. Substantial epidemiological evidences confirm the correlational relationship between PM_2.5 and respiratory disease in many Chinese cities. However, the causative impact of PM_2.5 on respiratory disease remains uncertain and comparative analysis is limited. This study aims to explore and compare the correlational relationship as well as the causal connection between PM_2.5 and upper respiratory tract infection (URTI) in two typical cities (Beijing, Shenzhen) with rather different ambient air environment conditions. The distributed lag nonlinear model (DLNM) was used to detect the correlational relationship between PM_2.5 and URTI by revealing the lag effect pattern of PM_2.5 on URTI. The convergent cross mapping (CCM) method was applied to explore the causal connection between PM_2.5 and URTI. The results from DLNM indicate that an increase of 10 μg/m³ in PM_2.5 concentration is associated with an increase of 1.86% (95% confidence interval: 0.74%-2.99%) in URTI at a lag of 13 days in Beijing, compared with 2.68% (95% confidence interval: 0.99-4.39%) at a lag of 1 day in Shenzhen. The causality detection with CCM quantitatively demonstrates the significant causative influence of PM_2.5 on URTI in both two cities. Findings from the two methods consistently show that people living in low-concentration areas (Shenzhen) are less tolerant to PM_2.5 exposure than those in high-concentration areas (Beijing). In general, our study highlights the adverse health effects of PM_2.5 pollution on the general public in cities with various PM_2.5 levels and emphasizes the needs for the government to provide appropriate solutions to control PM_2.5 pollution, even in cities with low PM_2.5 concentration.

Contributions of Traffic and Industrial Emission Reductions to the Air Quality Improvement after the Lockdown of Wuhan and Neighboring Cities Due to COVID-19

Wuhan was locked down from 23 January to 8 April 2020 to prevent the spread of the novel coronavirus disease 2019 (COVID-19). Both public and private transportation in Wuhan and its neighboring cities in Hubei Province were suspended or restricted, and the manufacturing industry was partially shut down. This study collected and investigated ground monitoring data to prove that the lockdowns of the cities had significant influences on the air quality in Wuhan. The WRF-CMAQ (Weather Research and Forecasting-Community Multiscale Air Quality) model was used to evaluate the emission reduction from transportation and industry sectors and associated air quality impact. The results indicate that the reduction in traffic emission was nearly 100% immediately after the lockdown between 23 January and 8 February and that the industrial emission tended to decrease by about 50% during the same period. The industrial emission further deceased after 9 February. Emission reduction from transportation and that from industry was not simultaneous. The results imply that the shutdown of industry contributed significantly more to the pollutant reduction than the restricted transportation.

Role of ammonia in secondary inorganic aerosols formation at an ammonia-rich city in winter in north China: A comparative study among industry, urban, and rural sites

Ammonia is essential for the generation of secondary inorganic aerosols (SIA) in particulate matter, which affects severely the air quality in north China. In this study, PM_2.5 sampling was conducted as well as gaseous pollutant concentration and meteorological parameters were measured from November 2017 to January 2018. PM_2.5 concentration was highest in the industrial site (94.8 ± 41.7 μg m^-3), followed by urban (40.9 ± 24.1 μg m^-3) and rural (35.6 ± 20.3 μg m^-3) sites. The mass ratio of NO₃^-/SO₄^2- exhibited clear site variations, with the highest average value of 1.2 was found at the urban site, likely due to the dense traffic volume resulting in higher emissions of NO₂, and the lowest value of 0.9 at the industry site. The presence of Excess-NHx (E-NHx), raising the pH 24 by 1.4, 1.3, and 1.4 units in industry, urban, and rural sites, respectively, might be vital for raising the aerosol pH. Correlation coefficients of Nitrogen oxidation rate (NOR, NOR = [NO₃^-]/[NO₃^-] + [NO₂]) vs. Photochemical oxidants (O_x, NO₂ +O₃ in our study) and NOR vs. aerosol water content (AWC) at three sites were implied that both homogeneous and heterogeneous reactions occurred for nitrate formation in industry site, while heterogeneous reactions were dominant in urban and rural sites. Oxidation rates were most sensitive to the variation of E-NHx concentration at rural site, followed by the urban and industry sites, which was shown by the fact that the increase in E-NHx concentration by 1.0 μg m^-3 increased the SIA concentration by 1.21, 1.02, and 0.37 μg m^-3 at rural, urban, and industry sites, respectively. With the increase in NH_x emissions at present, the role of NH_x in SIA formation at ammonia-rich atmosphere requires more attention, especially in the less-noticed rural areas.

Spatial Distribution of PM2.5-Related Premature Mortality in China

PM2.5 is a major component of air pollution in China and has a serious threat to public health. It is very important to quantify spatial characteristics of the health effects caused by outdoor PM2.5 exposure. This study analyzed the spatial distribution of PM2.5 concentration (45.9 μg/m3 national average in 2016) and premature mortality attributed to PM2.5 in cities at the prefectural level and above in China in 2016. Using the Global Exposure Mortality Model (GEMM), the total premature mortality in China was estimated to be 1.55 million persons, and the per capita mortality was 11.2 per 10,000 persons in the year 2016, resulting in higher estimates compared to the integrated exposure-response model. We assessed the premature mortality attributed to PM2.5 through common diseases, including ischemic heart disease (IHD), cerebrovascular disease (CEV), chronic obstructive pulmonary disease (COPD), lung cancer (LC), and lower respiratory infections (LRI). The premature mortality due to IHD and CEV accounted for 68.5% of the total mortality, and the per capita mortality (per 10,000 persons) for all ages due to IHD was 3.86, the highest among diseases. For the spatial distribution of disease-specific premature mortality, the top two highest absolute numbers of premature mortality associated with IHD, CEV, LC, and LRI, respectively, were found in Chongqing and Beijing. In 338 cities of China, we have found a significant positive spatial autocorrelation of per capita premature mortality, indicating the necessity of coordinated regional governance for an efficient control of PM2.5.

Urban-rural disparity of the short-term association of PM2.5 with mortality and its attributable burden

Although studies have investigated the associations between PM_2.5 and mortality risk, evidence from rural areas is scarce. We aimed to compare the PM_2.5-mortality associations between urban cities and rural areas in China. Daily mortality and air pollution data were collected from 215 locations during 2014–2017 in China. A two-stage approach was employed to estimate the location-specific and combined cumulative associations between short-term exposure to PM_2.5 (lag 0–3 days) and mortality risks. The excess risks (ER) of all-cause, respiratory disease (RESP), cardiovascular disease (CVD), and cerebrovascular disease (CED) mortality for each 10 μg/m³ increment in PM_2.5 across all locations were 0.54% (95% confidence interval [CI]: 0.38%, 0.70%), 0.51% (0.10%, 0.93%), 0.74% (0.50%, 0.97%), and 0.52% (0.20%, 0.83%), respectively. Slightly stronger associations for CVD (0.80% versus 0.60%) and CED (0.61% versus 0.26%) mortality were observed in urban cities than in rural areas, and slightly greater associations for RESP mortality (0.51% versus 0.43%) were found in rural areas than in urban cities. A mean of 2.11% (attributable fraction [AF], 95% CI: 1.48%, 2.76%) of all-cause mortality was attributable to PM_2.5 exposure in China, with a larger AF in urban cities (2.89% [2.12%, 3.67%]) than in rural areas (0.61% [−0.60%, 1.84%]). Disparities in PM_2.5-mortality associations between urban cities and rural areas were also found in some subgroups classified by sex and age. This study provided robust evidence on the associations of PM_2.5 with mortality risks in China and demonstrated urban-rural disparities of PM_2.5-mortality associations for various causes of death.

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PM_2.5 had greater effects on CVD/CED mortality in urban cities than in rural areas

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PM_2.5 had stronger effects on RESP mortality in rural areas than in urban cities

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An annual mean of 16.5/100,000 deaths was attributable to PM_2.5 in urban cities

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An annual mean of 3.4//100,000 deaths was attributable to PM_2.5 in rural areas

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Spatially targeted measures are needed to reduce PM_2.5-related mortality in China

The impacts of pollution and its associated spatial spillover effects on ill-health in China

While the adverse health effects of air pollution and its associated spatial spillovers have been extensively explored, there are a paucity of studies examining and comparing the effects of air pollution, water pollution, and their associated spatial spillover consequences for health. This study aims to evaluate and compare the impacts of water pollution, air pollution, and their associated spillover effects on ill-health. This study combined individual-level health data acquired from three waves of the China Health and Retirement Longitudinal Study (CHARLS) for 25,504 residents from 28 Chinese provinces with provincial-level pollution data for 2011, 2013 and 2015. We used Moran's I statistic to examine the existence and direction of the spatial spillover effects of pollution. The Spatial Durbin Model was then employed to assess the impacts of pollution and its associated spatial spillover effects on ill-health. A province's ill-health score increased by 6.649 for every 1 ton per capita per annum increase in the average amount of soot/dust discharged by its adjacent provinces. For every 1 ton per capita per annum increase in wastewater discharged, a province's ill-health score increased by 0.004. Targeted actions through the construction of cooperative action with adjacent provinces are suggested by our study to improve the efficiency of policy interventions.

Anthropogenic emission inventory of multiple air pollutants and their spatiotemporal variations in 2017 for the Shandong Province, China

Shandong is the most populous and highly industrialized province in eastern China, and the resultant poor air quality is a cause for widespread concern. This study combines bottom-up and top-down approaches to develop a high-resolution anthropogenic emission inventory of air pollutants for 2017. The inventory was developed based on updated emission factors and detailed activity data. The emissions of sulfur dioxide (SO₂), nitrogen oxides (NO_x), particulate matter with aerodynamic diameters smaller than 2.5 and 10 μm (PM_2.5 and PM₁₀, respectively), carbon monoxide (CO), volatile organic compounds (VOCs), and ammonia (NH₃) were estimated to be 1387.8, 2488.6, 5281.7, 3193.0, 9250.7, 2254.7, and 1210.6 kt, respectively. Power plants were the largest contributors of SO₂ and NO_x emissions accounting for 43.7% and 41.9% of the total emissions, respectively. CO emissions mainly originated from industrial processes (40.1%), mobile sources (24.8%), and fossil fuel burning (21.2%). The major sources of PM₁₀ and PM_2.5 emissions were industrial processes and fugitive dust, contributing 83.0% and 86.9% of their total emissions, respectively. Industrial processes (60.0%) contributed the largest VOC emissions, followed by mobile sources (16.8%) and solvent use (14.5%). Livestock and N-fertilizers were major emitters of NH₃, accounting for 69.9% and 21.2% of the total emissions, respectively. Emissions were spatially allocated to grid cells with a resolution of 0.05 ° × 0.05 ° based on spatial surrogates, using Geographic Information System (GIS). Heavy pollutant emissions were mainly concentrated in the central and eastern areas of Shandong, while high NH₃-emissions occurred in the western region. Most pollutant emissions from industrial sectors occurred in June and July, while low emissions were recorded between January and February. Range uncertainties in emission inventory were quantified using Monte Carlo simulations. Our inventory provides effective information to understand local pollutant emission characteristics, perform air quality simulations, and formulate pollution control measures.

Effects of air pollutant emission on the prevalence of respiratory and circulatory system diseases in Linyi, China

As a typical industrial city, Linyi has suffered severe atmospheric pollution in recent years. Meanwhile, a high incidence of respiratory and circulatory diseases has been observed in Linyi. The relationship between air pollutants and the prevalence of respiratory and circulatory system diseases in Linyi is still unclear, and therefore, there is an urgent need to assess the human health risks associated with air pollutants. In this study, the number of outpatient visits and spatial distribution of respiratory and circulatory diseases were first investigated. To clarify the correlation between diseases and air pollutant emissions, the residential intake fraction (IF) of air pollutants was calculated. The results showed that circulatory and respiratory diseases accounted for 62.32% of the total causes of death in 2015. The incidence of respiratory diseases was high in the winter, and outpatient visits were observed for more males (60.9%) than females (39.1%). The spatial distribution suggested that outpatient visits for respiratory and circulatory diseases were concentrated in the main urban area of Linyi, including the Hedong District, Lanshan District, and Luozhuang District, and especially at the junction of these three areas. After calculating the IF combined with the characteristics of pollution sources, meteorological conditions, and population data, a high IF value was concentrated in urban and suburban areas, which was consistent with the high incidence of diseases. Moreover, high R values and a significant correlation (R > 0.6, p < 0.05) between outpatient visits and residential IF of air pollutants imply similar spatial distributions of outpatient visits and IF value of residents. The spatial similarity of air pollution and outpatient visits suggested that future air pollution control policies should better reflect the health risks of spatial hotspots. This study can provide a potentially important reference for environmental management and air pollution-related health interventions.

Decrease in the chronic health effects from PM2.5 during the 13th Five-Year Plan in China: Impacts of air pollution control policies

The Chinese government implemented a series of policies to improve air quality during the Thirteenth Five-Year Plan (13^th FYP). However, the long-term health effects of the 13^th FYP air pollution control policies have not been evaluated, and the outbreak of coronavirus disease 2019 (COVID-19) has brought great uncertainty regarding the evaluation of the effects. In this study, we selected 329 cities in mainland China to study the chronic health effects due to the decrease in fine particulate matter (PM_2.5) during the 13^th FYP. The relative risk (RR) of PM_2.5 exposure was obtained from a previous study, and the total premature deaths were calculated. We also applied the grey prediction model to predict the PM_2.5 concentration in each city in 2020 to evaluate the impacts of COVID-19. The results showed that the annual PM_2.5 concentration was reduced from 49.7 μg/m³ in 2015 to 33.2 μg/m³ in 2020, and premature deaths were reduced from 1,186,201 (95% CI: 910,339-1,451,102) and 446,415 (in key regions, 95% CI: 343,426-544,813) in 2015 to 997,955 (95% CI: 762,167-1,226,652) and 368,786 (in key regions, 95% CI: 282,114-452,567) in 2020, respectively. A total of 188,246 (95% CI: 148,172-224,450) people avoided premature deaths due to the reduction in PM_2.5 concentrations from 2015 to 2020. Although the impacts of COVID-19 in 2020 brought a significant reduction of 35.3% in February (14.2 μg/m³, p < 0.0001) and in March by 17.6% (5.8 μg/m³, p = 0.001), we found that COVID-19 showed few obvious influences on China's long-term air pollution control plans. The observed data and predicted data are very close in annual mean values and showed no statistical significance both in all cities (p = 0.98) and in key regions (p = 0.56) in 2020.

Non-optimum temperature-related mortality burden in China: Addressing the dual influences of climate change and urban heat islands

Under the dual effects of climate change and urban heat islands (UHI), non-optimum temperature-related mortality burdens are complex and uncertain, and are rarely discussed in China. In this study, by applying city-specific exposure-response functions to multiple temperature and population projections under different climate and urbanization scenarios, we comprehensively assessed the non-optimum temperature-related mortality burdens in China from 2000 to 2050. Our results showed that temperature-related deaths will decrease from 1.19 million in 2010 to 1.08-1.17 million in 2050, with the exception of the most populous scenario. Excess deaths attributable to non-optimal temperatures under representative concentration pathway 8.5 (RCP8.5) were 2.35% greater than those under RCP4.5. This indicates that the surge in heat-related deaths caused by climate change will be offset by the reduction in cold-related deaths. As the climate changes, high-risk areas will be confronted with more severe health challenges, which requires health protection resource relocation strategies. Simultaneously, the net effects of UHIs are beneficial in the historical periods, preventing 3493 (95% CI: 22-6964) deaths in 2000. But UHIs will cause an additional 6951 (95% CI: -17,637-31,539, SSP4-RCP4.5) to 17,041 (95% CI: -10,516-44,598, SSP5-RCP8.5) deaths in 2050. The heavier health burden in RCP8.5 than RCP4.5 indicates that a warmer climate aggravates the negative effects of UHIs. Considering the synergistic behavior of climate change and UHIs, UHI mitigation strategies should not be developed without considering climate change. Moreover, the mortality burden exhibited strong spatial variations, with heavy burdens concentrated in the hotspots including Beijing-Tianjin Metropolitan Region, Yangtze River Delta, Chengdu-Chongqing City Group, Guangzhou, Wuhan, Xi'an, Shandong, and Henan. These hotspots should be priority areas for the allocation of the national medical resources to provide effective public health interventions.

Recent trends in premature mortality and health disparities attributable to ambient PM2.5 exposure in China: 2005-2017

In the past decade, particulate matter with aerodynamic diameter less than 2.5 μm (PM_2.5) has reached unprecedented levels in China and posed a significant threat to public health. Exploring the long-term trajectory of the PM_2.5 attributable health burden and corresponding disparities across populations in China yields insights for policymakers regarding the effectiveness of efforts to reduce air pollution exposure. Therefore, we examine how the magnitude and equity of the PM_2.5-related public health burden has changed nationally, and between provinces, as economic growth and pollution levels varied during 2005-2017. We derive long-term PM_2.5 exposures in China from satellite-based observations and chemical transport models, and estimate attributable premature mortality using the Global Exposure Mortality Model (GEMM). We characterize national and interprovincial inequality in health outcomes using environmental Lorenz curves and Gini coefficients over the study period. PM_2.5 exposure is linked to 1.8 (95% CI: 1.6, 2.0) million premature deaths over China in 2017, increasing by 31% from 2005. Approximately 70% of PM_2.5 attributable deaths were caused by stroke and IHD (ischemic heart disease), though COPD (chronic obstructive pulmonary disease) and LRI (lower respiratory infection) disproportionately affected poorer provinces. While most economic gains and PM_2.5-related deaths were concentrated in a few provinces, both gains and deaths became more equitably distributed across provinces over time. As a nation, however, trends toward equality were more recent and less clear cut across causes of death. The rise in premature mortality is due primarily to population growth and baseline risks of stroke and IHD. This rising health burden could be alleviated through policies to prevent pollution, exposure, and disease. More targeted programs may be warranted for poorer provinces with a disproportionate share of PM_2.5-related premature deaths due to COPD and LRI.

Impact of Air Pollution (PM2.5) on Child Mortality: Evidence from Sixteen Asian Countries

Air pollution in Asian countries represents one of the biggest health threats given the varied levels of economic and population growth in the recent past. The quantification of air pollution (PM_2.5) vis à vis health problems has important policy implications in tackling its health effects. This paper investigates the relationship between air pollution (PM_2.5) and child mortality in sixteen Asian countries using panel data from 2000 to 2017. We adopt a two-stage least squares approach that exploits variations in PM_2.5 attributable to economic growth in estimating the effect on child mortality. We find that a one-unit annual increase in PM_2.5 leads to a nearly 14.5% increase in the number of children dying before the age of five, suggesting the severity of the effects of particulate matter (PM_2.5) on health outcomes in sixteen Asian countries considered in this study. The results of this study suggest the need for strict policy interventions by governments in Asian countries to reduce PM_2.5 concentration alongside environment-friendly policies for economic growth.

Assessment of Air Pollution before, during and after the COVID-19 Pandemic Lockdown in Nanjing, China

A unique illness, the coronavirus disease 2019 (COVID-19), emerged in Wuhan, People’s Republic of China, in December 2019. To reduce the spread of the virus, strict lockdown policies and control measures were put in place all over the world. Due to these enforced limitations, a drastic drop in air pollution and an improvement in air quality were observed. The present study used six air pollutants (PM10, PM2.5, SO2, NO2, CO and O3) to observe trends before, during and after the COVID-19 lockdown period in Nanjing, China. The data were divided into six phases: P1–P3, pre-lockdown (1 October–31 December 2019), lockdown (1 January–31 March 2020), after lockdown (1 April–30 June 2020), P4–P6: the same dates as the lockdown but during 2017, 2018 and 2019. The results indicate that compared with the pre-lockdown phase, the PM10 and PM2.5 average concentrations decreased by –27.71% and –5.09%. Compared with the previous three years, 2017–2019, the reductions in PM10 and PM2.5 were –37.99% and –33.56%, respectively. Among other pollutants, concentrations of SO2 (–32.90%), NO2 (–34.66%) and CO (–16.85%) also decreased during the lockdown, while the concentration of O3 increased by approximately 25.45%. Moreover, compared with the pre- and during lockdown phases, PM10, PM2.5 and NO2 showed decreasing trends while SO2, CO and O3 concentrations increased. These findings present a road map for upcoming studies and provide a new path for policymakers to create policies to improve air quality.