Health and Economic Benefits of Complying With the World Health Organization Air Quality Guidelines for Particulate Matter in Nine Major Latin American Cities.

Objectives: This study aims to estimate the short-term preventable mortality and associated economic costs of complying with the World Health Organization (WHO) air quality guidelines (AQGs) limit values for PM10 and PM2.5 in nine major Latin American cities. Methods: We estimated city-specific PM-mortality associations using time-series regression models and calculated the attributable mortality fraction. Next, we used the value of statistical life to calculate the economic benefits of complying with the WHO AQGs limit values. Results: In most cities, PM concentrations exceeded the WHO AQGs limit values more than 90% of the days. PM10 was found to be associated with an average excess mortality of 1.88% with concentrations above WHO AQGs limit values, while for PM2.5 it was 1.05%. The associated annual economic costs varied widely, between US$ 19.5 million to 3,386.9 million for PM10, and US$ 196.3 million to 2,209.6 million for PM2.5. Conclusion: Our findings suggest that there is an urgent need for policymakers to develop interventions to achieve sustainable air quality improvements in Latin America. Complying with the WHO AQGs limit values for PM10 and PM2.5 in Latin American cities would substantially benefits for urban populations.

Health benefits of decreases in on-road transportation emissions in the United States from 2008 to 2017.

Decades of air pollution regulation have yielded enormous benefits in the United States, but vehicle emissions remain a climate and public health issue. Studies have quantified the vehicle-related fine particulate matter (PM2.5)-attributable mortality but lack the combination of proper counterfactual scenarios, latest epidemiological evidence, and detailed spatial resolution; all needed to assess the benefits of recent emission reductions. We use this combination to assess PM2.5-attributable health benefits and also assess the climate benefits of on-road emission reductions between 2008 and 2017. We estimate total benefits of $270 (190 to 480) billion in 2017. Vehicle-related PM2.5-attributable deaths decreased from 27,700 in 2008 to 19,800 in 2017; however, had per-mile emission factors remained at 2008 levels, 48,200 deaths would have occurred in 2017. The 74% increase from 27,700 to 48,200 PM2.5-attributable deaths with the same emission factors is due to lower baseline PM2.5 concentrations (+26%), more vehicle miles and fleet composition changes (+22%), higher baseline mortality (+13%), and interactions among these (+12%). Climate benefits were small (3 to 19% of the total). The percent reductions in emissions and PM2.5-attributable deaths were similar despite an opportunity to achieve disproportionately large health benefits by reducing high-impact emissions of passenger light-duty vehicles in urban areas. Increasingly large vehicles and an aging population, increasing mortality, suggest large health benefits in urban areas require more stringent policies. Local policies can be effective because high-impact primary PM2.5 and NH3 emissions disperse little outside metropolitan areas. Complementary national-level policies for NOx are merited because of its substantial impacts-with little spatial variability-and dispersion across states and metropolitan areas.

[Economic evaluation on the health hazards of residents caused by PM_(2.5) in Beijing, Tianjin and Hebei from 2013 to 2018].

OBJECTIVE: To learn the health hazards and health economic losses caused by PM_(2.5) pollution in Beijing, Tianjin and Hebei to the resident population. METHODS: Fine particular matter concentration and the basic demographic data of Beijing, Tianjin and Hebei from 2013 to 2018 were collected. Circulatory system disease hospitalization and other indexes were chosen as the end point of health effects, appropriate exposure-response relationship were selected, and the economic loss of health effect caused by PM_(2.5) was assessed by the combination of the cost of illness approach and human capital method. RESULTS: From 2013 to 2018, the economic loss of Beijing, Tianjin and Hebei caused by fine particular matter pollution showed a decreasing trend year by year. The health economic losses of Beijing from 2013 to 2018 were 3.815, 4.177, 4.090, 3.818, 2.567 and 2.031 billion yuan; The health economic losses of Tianjin were 3.046, 2.625, 1.882, 1.914, 1.448 and 1.000 billion yuan; The health economic losses of Hebei were 13.719, 11.850, 7.423, 7.216, 6.499 and 4.124 billion yuan, Hebei Province had the highest economic loss in 2013, accounting for 13.719 billion yuan, accounting for 0.51% of GDP in that year. Tianjin had the lowest economic loss in 2018, accounting for 10.0 billion yuan, accounting for 0.05% of GDP in that year. CONCLUSION: The health loss caused by PM_(2.5) pollution in Beijing, Tianjin and Hebei region shows a decreasing trend year by year, but the number is still very considerable, and the monitoring and control of PM_(2.5) pollution need to be further strengthened.

Annual dementia incidence and monetary burden attributable to fine particulate matter (PM2.5) exposure in Sweden.

BACKGROUND: Alzheimer's disease (AD) and other dementias currently represent the fifth most common cause of death in the world, according to the World Health Organization, with a projected future increase as the proportion of the elderly in the population is growing. Air pollution has emerged as a plausible risk factor for AD, but studies estimating dementia cases attributable to exposure to fine particulate matter (PM2.5) air pollution and resulting monetary estimates are lacking. METHODS: We used data on average population-weighted exposure to ambient PM2.5 for the entire population of Sweden above 30 years of age. To estimate the annual number of dementia cases attributable to air pollution in the Swedish population above 60 years of age, we used the latest concentration response functions (CRF) between PM2.5 exposure and dementia incidence, based on ten longitudinal cohort studies, for the population above 60 years of age. To estimate the monetary burden of attributable cases, we calculated total costs related to dementia, including direct and indirect lifetime costs and intangible costs by including quality-adjusted life years (QALYs) lost. Two different monetary valuations of QALYs in Sweden were used to estimate the monetary value of reduced quality-of-life from two different payer perspectives. RESULTS: The annual number of dementia cases attributable to PM2.5 exposure was estimated to be 820, which represents 5% of the annual dementia cases in Sweden. Direct and indirect lifetime average cost per dementia case was estimated to correspond € 213,000. A reduction of PM2.5 by 1 µg/m3 was estimated to yield 101 fewer cases of dementia incidences annually, resulting in an estimated monetary benefit ranging up to 0.01% of the Swedish GDP in 2019. CONCLUSION: This study estimated that 5% of annual dementia cases could be attributed to PM2.5 exposure, and that the resulting monetary burden is substantial. These findings suggest the need to consider airborne toxic pollutants associated with dementia incidence in public health policy decisions.

Effect of PM2.5 pollution on perinatal mortality in China.

Using ArcGIS to analyze satellite derived PM2.5 estimates, this paper obtains the average concentration and maximum concentration of fine particulate matter (PM2.5) in China's 31 provinces from 2002 to 2015. We adopt fixed effects model and spatial Durbin model to investigate the association between PM2.5 and perinatal mortality rates. The results indicate that PM2.5 has a significantly positive association with perinatal mortality rates. A 1% increase of log-transformed average concentration and maximum concentrations of PM2.5 is associated with 1.76‰ and 2.31‰ increase of perinatal mortality rates, respectively. In spatial econometrics analysis, we find PM2.5 has significant spatial autocorrelation characteristics. The concentrations of log-transformed average and maximum PM2.5 increase 1% is associated with a 2.49% increase in a 2.49‰ and 2.19‰ increase of perinatal mortality rates, respectively. The potential mechanism is that air pollution has an impact on infant weight to impact perinatal mortality rates.

Health and economic impact of air pollution in the states of India: the Global Burden of Disease Study 2019.

BACKGROUND: The association of air pollution with multiple adverse health outcomes is becoming well established, but its negative economic impact is less well appreciated. It is important to elucidate this impact for the states of India. METHODS: We estimated exposure to ambient particulate matter pollution, household air pollution, and ambient ozone pollution, and their attributable deaths and disability-adjusted life-years in every state of India as part of the Global Burden of Disease Study (GBD) 2019. We estimated the economic impact of air pollution as the cost of lost output due to premature deaths and morbidity attributable to air pollution for every state of India, using the cost-of-illness method. FINDINGS: 1·67 million (95% uncertainty interval 1·42-1·92) deaths were attributable to air pollution in India in 2019, accounting for 17·8% (15·8-19·5) of the total deaths in the country. The majority of these deaths were from ambient particulate matter pollution (0·98 million [0·77-1·19]) and household air pollution (0·61 million [0·39-0·86]). The death rate due to household air pollution decreased by 64·2% (52·2-74·2) from 1990 to 2019, while that due to ambient particulate matter pollution increased by 115·3% (28·3-344·4) and that due to ambient ozone pollution increased by 139·2% (96·5-195·8). Lost output from premature deaths and morbidity attributable to air pollution accounted for economic losses of US$28·8 billion (21·4-37·4) and $8·0 billion (5·9-10·3), respectively, in India in 2019. This total loss of $36·8 billion (27·4-47·7) was 1·36% of India's gross domestic product (GDP). The economic loss as a proportion of the state GDP varied 3·2 times between the states, ranging from 0·67% (0·47-0·91) to 2·15% (1·60-2·77), and was highest in the low per-capita GDP states of Uttar Pradesh, Bihar, Rajasthan, Madhya Pradesh, and Chhattisgarh. Delhi had the highest per-capita economic loss due to air pollution, followed by Haryana in 2019, with 5·4 times variation across all states. INTERPRETATION: The high burden of death and disease due to air pollution and its associated substantial adverse economic impact from loss of output could impede India's aspiration to be a $5 trillion economy by 2024. Successful reduction of air pollution in India through state-specific strategies would lead to substantial benefits for both the health of the population and the economy. FUNDING: UN Environment Programme; Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.

The role of burden of disease assessment in tracking progress towards achieving WHO global air quality guidelines.

OBJECTIVES: More than 90% of the global population live in areas exceeding the PM2.5 air quality guidelines (AQGs). We provide an overview of the ambient PM2.5-related burden of disease (BoD) studies along with scenario analysis in the framework of the WHO AQG update on the estimated reduction in the BoD if AQGs were achieved globally. METHODS: We reviewed the literature for large-scale studies for the BoD attributed to ambient PM2.5. Moreover, we used the latest WHO statistics to calculate the BoD at current levels and the scenarios of aligning with interim targets and AQG levels. RESULTS: The most recent BoD studies (2010 onwards) share a similar methodology, but there are differences in the input data which affect the estimates for attributable deaths (2.9-8.9 million deaths annually). Moreover, we found that if AQGs were achieved, the estimated BoD would be reduced by up to 50% in total deaths worldwide. CONCLUSIONS: Understanding the BoD across countries, especially in those that do not align with the AQGs, is essential in order to inform actions to reduce air pollution globally.

Short term exposure to fine particulate matter and hospital admission risks and costs in the Medicare population: time stratified, case crossover study.

OBJECTIVE: To assess risks and costs of hospital admission associated with short term exposure to fine particulate matter with diameter less than 2.5 µm (PM2.5) for 214 mutually exclusive disease groups. DESIGN: Time stratified, case crossover analyses with conditional logistic regressions adjusted for non-linear confounding effects of meteorological variables. SETTING: Medicare inpatient hospital claims in the United States, 2000-12 (n=95 277 169). PARTICIPANTS: All Medicare fee-for-service beneficiaries aged 65 or older admitted to hospital. MAIN OUTCOME MEASURES: Risk of hospital admission, number of admissions, days in hospital, inpatient and post-acute care costs, and value of statistical life (that is, the economic value used to measure the cost of avoiding a death) due to the lives lost at discharge for 214 disease groups. RESULTS: Positive associations between short term exposure to PM2.5 and risk of hospital admission were found for several prevalent but rarely studied diseases, such as septicemia, fluid and electrolyte disorders, and acute and unspecified renal failure. Positive associations were also found between risk of hospital admission and cardiovascular and respiratory diseases, Parkinson's disease, diabetes, phlebitis, thrombophlebitis, and thromboembolism, confirming previously published results. These associations remained consistent when restricted to days with a daily PM2.5 concentration below the WHO air quality guideline for the 24 hour average exposure to PM2.5. For the rarely studied diseases, each 1 µg/m3 increase in short term PM2.5 was associated with an annual increase of 2050 hospital admissions (95% confidence interval 1914 to 2187 admissions), 12 216 days in hospital (11 358 to 13 075), US$31m (£24m, €28m; $29m to $34m) in inpatient and post-acute care costs, and $2.5bn ($2.0bn to $2.9bn) in value of statistical life. For diseases with a previously known association, each 1 µg/m3 increase in short term exposure to PM2.5 was associated with an annual increase of 3642 hospital admissions (3434 to 3851), 20 098 days in hospital (18 950 to 21 247), $69m ($65m to $73m) in inpatient and post-acute care costs, and $4.1bn ($3.5bn to $4.7bn) in value of statistical life. CONCLUSIONS: New causes and previously identified causes of hospital admission associated with short term exposure to PM2.5 were found. These associations remained even at a daily PM2.5 concentration below the WHO 24 hour guideline. Substantial economic costs were linked to a small increase in short term PM2.5.

Spatial-Temporal Effects of PM2.5 on Health Burden: Evidence from China.

By collecting the panel data of 29 regions in China from 2008 to 2017, this study used the spatial Durbin model (SDM) to explore the spatial effect of PM2.5 exposure on the health burden of residents. The most obvious findings to emerge from this study are that: health burden and PM2.5 exposure are not randomly distributed over different regions in China, but have obvious spatial correlation and spatial clustering characteristics. The maximum PM2.5 concentrations have a significant positive effect on outpatient expense and outpatient visits of residents in the current period, and the impact of PM2.5 pollution has a significant temporal lag effect on residents' health burden. PM2.5 exposure has a spatial spillover effect on the health burden of residents, and the PM2.5 concentrations in the surrounding regions or geographically close regions have a positive influence on the health burden in the particular region. The impact of PM2.5 exposure is divided into the direct effect and the indirect effect (the spatial spillover effect), and the spatial spillover effect is greater than that of the direct effect. Therefore, we conclude that PM2.5 exposure has a spatial spillover effect and temporal lag effect on the health burden of residents, and strict regulatory policies are needed to mitigate the health burden caused by air pollution.

Spatiotemporal variation in PM2.5 concentrations and their relationship with socioeconomic factors in China's major cities.

The air quality issues caused by extreme haze episodes in China have become increasingly serious in recent years. In particular, fine particulate matter (PM2.5) has become the major component of haze with many adverse impacts and has therefore become of great concern to scientists, government, and the general public in China. This study investigates the spatiotemporal variation in PM2.5 in 269 Chinese cities from 2015 to 2016 and its associations with socioeconomic factors to identify the possible strategies for PM2.5 pollution mitigation. Specifically, we first quantified the spatial pattern of PM2.5 concentrations in both 2015 and 2016, and then changes between the two years. Next, we examined the relationship between socioeconomic factors and PM2.5 concentrations and changes. The results showed that most cities in eastern China experienced decreases in PM2.5 concentration, although most of these cities already had high PM2.5 pollution level. Cities with low PM2.5 concentrations experienced increases in PM2.5 concentrations and were mostly located in southern and southwestern China. The PM2.5 concentration was the highest in winter, followed by in spring, autumn and summer; for changes in PM2.5 concentrations, the highest magnitude of decrease occurred in summer, followed by the decreases in winter, autumn and spring. Cities with high PM2.5 concentrations tended to be clustered, but the clustered characteristics were not clearly related to the changes in PM2.5 concentrations. The relationship between PM2.5 concentration and urban size was an inverse U-shaped curve, suggesting the existence of the Environmental Kuznets Curve for air quality in China. Population density and secondary industry share are the keys factors relating to air pollution control. In comparison to other cities, most moderately developed cities had a greater magnitude of decrease in PM2.5 concentrations and the key factor for pollution improvement was industrial structure; however, smaller cities tended to have a greater increase in PM2.5 concentrations and population density was the most important influencing factor. As a result, for air pollution control in China, specific regulations should be carried out according to different regions and different developmental stages based on the locations of cities.

Fine particulate matter damages and value added in the US economy.

Emissions of most pollutants that result in fine particulate matter (PM2.5) formation have been decreasing in the United States. However, this trend has not been uniform across all sectors or regions of the economy. We use integrated assessment models (IAMs) to compute marginal damages for PM2.5-related emissions for each county in the contiguous United States and match location-specific emissions with these marginal damages to compute economy-wide gross external damage (GED) due to premature mortality. We note 4 key findings: First, economy-wide, GED has decreased by more than 20% from 2008 to 2014. Second, while much of the air pollution policies have focused to date on the electricity sector, damages from farms are now larger than those from utilities. Indeed, farms have become the largest contributor to air pollution damages from PM2.5-related emissions. Third, 4 sectors, comprising less than 20% of the national gross domestic product (GDP), are responsible for ∼75% of GED attributable to economic activities. Fourth, uncertainty in GED estimates tends to be high for sectors with predominantly ground-level emissions because these emissions are usually estimated and not measured. These findings suggest that policymakers should target further emissions reductions from such sectors, particularly in transportation and agriculture.

Comparison of health and economic impacts of PM2.5 and ozone pollution in China.

Many studies have reported associations between air pollution and health impacts, but few studies have explicitly differentiated the economic effects of PM2.5 and ozone at China's regional level. This study compares the PM2.5 and ozone pollution-related health impacts based on an integrated approach. The research framework combines an air pollutant emission projection model (GAINS), an air quality model (GEOS-Chem), a health model using the latest exposure-response functions, medical prices and value of statistical life (VSL), and a general equilibrium model (CGE). Results show that eastern provinces in China encounter severer loss from PM2.5 and more benefit from mitigation policy, whereas the lower income western provinces encounter severer health impacts and economic burdens due to ozone pollution, and the impact in southern and central provinces is relatively lower. In 2030, without control policies, PM 2.5 pollution could lead to losses of 2.0% in Gross Domestic Production (GDP), 210 billion Chinese Yuan (CNY) in health expenditure and a life loss of around 10,000 billion, while ozone pollution could contribute to GDP loss by 0.09% (equivalent to 78 billion CNY), 310 billion CNY in health expenditure, and a life loss of 2300 billion CNY (equivalent to 2.7% of GDP). By contrast, with control policies, the GDP and VSLs loss in 2030 attributable to ambient air pollution could be reduced significantly. We also find that the health and economic impacts of ozone pollution are significantly lower than PM2.5, but are much more difficult to mitigate. The Chinese government should promote air pollution control policies that could jointly reduce PM2.5 and ozone pollution.

PM2.5 Cooperative Control with Fuzzy Cost and Fuzzy Coalitions.

Haze control cost is hard to value by a crisp number because it is often affected by various factors such as regional uncertain meteorological conditions and topographical features. Furthermore, regions may be involved in different coalitions for haze control with different levels of effort. In this paper, we propose a PM2.5 cooperative control model with fuzzy cost and crisp coalitions or fuzzy coalitions based on the uncertain cross-border transmission factor. We focus on the Beijing­Tianjin­Hebei regions of China and obtain the following major findings. In the case of haze control in the Beijing­Tianjin­Hebei regions of China, local governments in the global crisp coalition can achieve their emission reduction targets with the lowest aggregated cost. However, Hebei fails to satisfy its individual rationality if there is no cost sharing. Therefore, the Hukuhara­Shapley value is used to allocate the aggregated cost among these regions so that the grand coalition is stable. However, the Beijing­Tianjin­Hebei regions cannot achieve their emission reduction targets in the global fuzzy coalition without government subsidies.

What is the health cost of haze pollution? Evidence from China.

INTRODUCTION: Haze pollution has become a serious threat to the health of residents and has brought about considerable economic costs. The objectives of this study are to examine the relationship between haze pollution and residents' health and to estimate the health cost of haze pollution. METHODS: Using macro data on 74 major Chinese cities, this study employs a static panel data model and a dynamic panel generalized method of moments model to investigate the impact of haze pollution on the mortality of residents. On the basis of the estimation results, the value of a statistical life (VOSL) method is used to evaluate the economic cost of haze pollution on residents' health. RESULTS: In 74 major cities of China, an increase in concentration of PM2.5 pollutants by 1 µg/m3 may cause the mortality rate to rise by 25 per million people. The VOSL of haze pollution in China is about 1.53 million yuan. The health cost of residents from haze in 74 major cities of China in 2016 was about 888 billion yuan, equivalent to about 2% of the these cities' GDP. CONCLUSIONS: Haze pollution has serious damage to the health of urban residents and therefore brings about considerable economic losses.

Quantifying health impacts and economic costs of PM2.5 exposure in Mexican cities of the National Urban System.

OBJECTIVES: To estimate avoidable mortality, potential years of life lost and economic costs associated with particulate matter PM2.5 exposure for 2 years (2013 and 2015) in Mexico using two scenarios of reduced concentrations (i.e., mean annual PM2.5 concentration < 12 µg/m3 and mean annual PM2.5 concentration < 10 µg/m3). METHODS: The health impact assessment method was followed. This method consists of: identification of health effects, selection of concentration-response functions, estimation of exposure, quantification of impacts quantification and economic assessment using the willingness to pay and human capital approaches. RESULTS: For 2013, we included data from 62 monitoring sites in ten cities, (113 municipalities) where 36,486,201 live. In 2015, we included 71 monitoring sites from fifteen cities (121 municipalities) and 40,479,629 inhabitants. It was observed that reduction in the annual PM2.5 average to 10 µg/would have prevented 14,666 deaths and 150,771 potential years of life lost in 2015, with estimated costs of 64,164 and 5434 million dollars, respectively. CONCLUSIONS: Reducing PM2.5 concentration in the Mexican cities studied would reduce mortality by all causes by 8.1%, representing important public health benefits.

Health benefits and control costs of tightening particulate matter emissions standards for coal power plants - The case of Northeast Brazil.

Exposure to ambient particulate matter (PM) caused an estimated 4.2 million deaths worldwide in 2015. However, PM emission standards for power plants vary widely. To explore if the current levels of these standards are sufficiently stringent in a simple cost-benefit framework, we compared the health benefits (avoided monetized health costs) with the control costs of tightening PM emission standards for coal-fired power plants in Northeast (NE) Brazil, where ambient PM concentrations are below World Health Organization (WHO) guidelines. We considered three Brazilian PM10 (PMx refers to PM with a diameter under x micrometers) emission standards and a stricter U.S. EPA standard for recent power plants. Our integrated methodology simulates hourly electricity grid dispatch from utility-scale power plants, disperses the resulting PM2.5, and estimates selected human health impacts from PM2.5 exposure using the latest integrated exposure-response model. Since the emissions inventories required to model secondary PM are not available in our study area, we modeled only primary PM so our benefit estimates are conservative. We found that tightening existing PM10 emission standards yields health benefits that are over 60 times greater than emissions control costs in all the scenarios we considered. The monetary value of avoided hospital admissions alone is at least four times as large as the corresponding control costs. These results provide strong arguments for considering tightening PM emission standards for coal-fired power plants worldwide, including in regions that meet WHO guidelines and in developing countries.

Including intangible costs into the cost-of-illness approach: a method refinement illustrated based on the PM2.5 economic burden in China.

The concentrations of particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) and 10 µm (PM10) is a widespread concern and has been demonstrated for 103 countries. During the past few years, the exposure-response function (ERf) has been widely used to estimate the health effects of air pollution. However, past studies are either based on the cost-of-illness or the willingness-to-pay approach, and therefore, either do not cover intangible costs or costs due to the absence of work. To address this limitation, a hybrid health effect and economic loss model is developed in this study. This novel approach is applied to a sample of environmental and cost data in China. First, the ERf is used to link PM2.5 concentrations to health endpoints of chronic mortality, acute mortality, respiratory hospital admission, cardiovascular hospital admission, outpatient visits-internal medicine, outpatient visits-pediatrics, asthma attack, acute bronchitis, and chronic bronchitis. Second, the health effect of PM2.5 is monetized into the economic loss. The mean economic loss due to PM2.5 was much heavier in the North than the South of China. Furthermore, the empirical results from 76 cities in China show that the health effects and economic losses were over 4.98 million cases and 382.30 billion-yuan in 2014 and decreased dramatically compared with those in 2013.

Quantitative Assessment of Relationship between Population Exposure to PM2.5 and Socio-Economic Factors at Multiple Spatial Scales over Mainland China.

Analyzing the association between fine particulate matter (PM2.5) pollution and socio-economic factors has become a major concern in public health. Since traditional analysis methods (such as correlation analysis and geographically weighted regression) cannot provide a full assessment of this relationship, the quantile regression method was applied to overcome such a limitation at different spatial scales in this study. The results indicated that merely 3% of the population and 2% of the Gross Domestic Product (GDP) occurred under an annually mean value of 35 µg/m³ in mainland China, and the highest population exposure to PM2.5 was located in a lesser-known city named Dazhou in 2014. The analysis results at three spatial scales (grid-level, county-level, and city-level) demonstrated that the grid-level was the optimal spatial scale for analysis of socio-economic effects on exposure due to its tiny uncertainty, and the population exposure to PM2.5 was positively related to GDP. An apparent upward trend of population exposure to PM2.5 emerged at the 80th percentile GDP. For a 10 thousand yuan rise in GDP, population exposure to PM2.5 increases by 1.05 person/km² at the 80th percentile, and 1.88 person/km2 at the 95th percentile, respectively.

Air pollution and healthcare expenditure: Implication for the benefit of air pollution control in China.

Quantitating the health effects of air pollution is important for understanding the benefits of environmental regulations. Using the China Urban Household Survey (UHS) Database, this paper estimated the effect of air pollution exposure on household healthcare expenditure. To address potential endogeneity concerns, we performed household healthcare expenditure regressions using an instrumental variables (IV) strategy based on spatial air pollution spillovers. Our research revealed that a 1% increase in yearly exposure to fine particulate matter (PM2.5) corresponds to a 2.942% (95% confidence interval: 1.084%, 4.799%) increase in household healthcare expenditure. The estimates suggest that the 13th Five-Year Plan for Ecological and Environmental Protection (the 13th FYP) would reduce annual national healthcare expenditure by 47.36 Billion Dollar (95% confidence interval: 17.45 Billion Dollar, 77.25 Billion Dollar), which accounts for 0.64% (95% confidence interval: 0.24%, 1.04%) of China's gross domestic product (GDP).

Spatiotemporal Assessment of PM2.5-Related Economic Losses from Health Impacts during 2014⁻2016 in China.

Background: Particulate air pollution, especially PM2.5, is highly correlated with various adverse health impacts and, ultimately, economic losses for society, however, few studies have undertaken a spatiotemporal assessment of PM2.5-related economic losses from health impacts covering all of the main cities in China. Methods: PM2.5 concentration data were retrieved for 190 Chinese cities for the period 2014⁻2016. We used a log-linear exposure⁻response model and monetary valuation methods, such as value of a statistical life (VSL), amended human capital (AHC), and cost of illness to evaluate PM2.5-related economic losses from health impacts at the city level. In addition, Monte Carlo simulation was used to analyze uncertainty. Results: The average economic loss was 0.3% (AHC) to 1% (VSL) of the total gross domestic product (GDP) of 190 Chinese cities from 2014 to 2016. Overall, China experienced a downward trend in total economic losses over the three-year period, but the Beijing⁻Tianjin⁻Hebei, Shandong Peninsula, Yangtze River Delta, and Chengdu-Chongqing regions experienced greater annual economic losses. Conclusions: Exploration of spatiotemporal variations in PM2.5-related economic losses from long-term health impacts could provide new information for policymakers regarding priority areas for PM2.5 pollution prevention and control in China.