Assessment of deaths attributable to air pollution: should we use risk estimates based on time series or on cohort studies?

Choices of morbidity outcomes and concentration-response functions for health risk assessment of long-term exposure to air pollution

Background

Air pollution health risk assessment (HRA) has been typically conducted for all causes and cause-specific mortality based on concentration-response functions (CRFs) from meta-analyses that synthesize the evidence on air pollution health effects. There is a need for a similar systematic approach for HRA for morbidity outcomes, which have often been omitted from HRA of air pollution, thus underestimating the full air pollution burden. We aimed to compile from the existing systematic reviews and meta-analyses CRFs for the incidence of several diseases that could be applied in HRA. To achieve this goal, we have developed a comprehensive strategy for the appraisal of the systematic reviews and meta-analyses that examine the relationship between long-term exposure to particulate matter with an aerodynamic diameter smaller than 2.5 µm (PM2.5), nitrogen dioxide (NO2), or ozone (O3) and incidence of various diseases.

Methods

To establish the basis for our evaluation, we considered the causality determinations provided by the US Environmental Protection Agency Integrated Science Assessment for PM2.5, NO2, and O3. We developed a list of pollutant/outcome pairs based on these assessments and the evidence of a causal relationship between air pollutants and specific health outcomes. We conducted a comprehensive literature search using two databases and identified 75 relevant systematic reviews and meta-analyses for PM2.5 and NO2. We found no relevant reviews for long-term exposure to ozone. We evaluated the reliability of these studies using an adaptation of the AMSTAR 2 tool, which assesses various characteristics of the reviews, such as literature search, data extraction, statistical analysis, and bias evaluation. The tool's adaptation focused on issues relevant to studies on the health effects of air pollution. Based on our assessment, we selected reviews that could be credible sources of CRF for HRA. We also assessed the confidence in the findings of the selected systematic reviews and meta-analyses as the sources of CRF for HRA. We developed specific criteria for the evaluation, considering factors such as the number of included studies, their geographical distribution, heterogeneity of study results, the statistical significance and precision of the pooled risk estimate in the meta-analysis, and consistency with more recent studies. Based on our assessment, we classified the outcomes into three lists: list A (a reliable quantification of health effects is possible in an HRA), list B+ (HRA is possible, but there is greater uncertainty around the reliability of the CRF compared to those included on list A), and list B- (HRA is not recommended because of the substantial uncertainty of the CRF).

Results

In our final evaluation, list A includes six CRFs for PM2.5 (asthma in children, chronic obstructive pulmonary disease, ischemic heart disease events, stroke, hypertension, and lung cancer) and three outcomes for NO2 (asthma in children and in adults, and acute lower respiratory infections in children). Three additional outcomes (diabetes, dementia, and autism spectrum disorders) for PM2.5 were included in list B+. Recommended CRFs are related to the incidence (onset) of the diseases. The International Classification of Diseases, 10th revision codes, age ranges, and suggested concentration ranges are also specified to ensure consistency and applicability in an HRA. No specific suggestions were given for ozone because of the lack of relevant systematic reviews.

Conclusion

The suggestions formulated in this study, including CRFs selected from the available systematic reviews, can assist in conducting reliable HRAs and contribute to evidence-based decision-making in public health and environmental policy. Future research should continue to update and refine these suggestions as new evidence becomes available and methodologies evolve.

Mortality attributable to PM2.5 from wildland fires in California from 2008 to 2018

In California, wildfire risk and severity have grown substantially in the last several decades. Research has characterized extensive adverse health impacts from exposure to wildfire-attributable fine particulate matter (PM2.5), but few studies have quantified long-term outcomes, and none have used a wildfire-specific chronic dose-response mortality coefficient. Here, we quantified the mortality burden for PM2.5 exposure from California fires from 2008 to 2018 using Community Multiscale Air Quality modeling system wildland fire PM2.5 estimates. We used a concentration-response function for PM2.5, applying ZIP code-level mortality data and an estimated wildfire-specific dose-response coefficient accounting for the likely toxicity of wildfire smoke. We estimate a total of 52,480 to 55,710 premature deaths are attributable to wildland fire PM2.5 over the 11-year period with respect to two exposure scenarios, equating to an economic impact of $432 to $456 billion. These findings extend evidence on climate-related health impacts, suggesting that wildfires account for a greater mortality and economic burden than indicated by earlier studies.

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.

Harnessing AI to unmask Copenhagen's invisible air pollutants: A study on three ultrafine particle metrics

Ultrafine particles (UFPs) are airborne particles with a diameter of less than 100 nm. They are emitted from various sources, such as traffic, combustion, and industrial processes, and can have adverse effects on human health. Long-term mean ambient average particle size (APS) in the UFP range varies over space within cities, with locations near UFP sources having typically smaller APS. Spatial models for lung deposited surface area (LDSA) within urban areas are limited and currently there is no model for APS in any European city. We collected particle number concentration (PNC), LDSA, and APS data over one-year monitoring campaign from May 2021 to May 2022 across 27 locations and estimated annual mean in Copenhagen, Denmark, and obtained additionally annual mean PNC data from 6 state-owned continuous monitors. We developed 94 predictor variables, and machine learning models (random forest and bagged tree) were developed for PNC, LDSA, and APS. The annual mean PNC, LDSA, and APS were, respectively, 5523 pt/cm3, 12.0 μm2/cm3, and 46.1 nm. The final R2 values by random forest (RF) model were 0.93 for PNC, 0.88 for LDSA, and 0.85 for APS. The 10-fold, repeated 10-times cross-validation R2 values were 0.65, 0.67, and 0.60 for PNC, LDSA, and APS, respectively. The root mean square error for final RF models were 296 pt/cm3, 0.48 μm2/cm3, and 1.60 nm for PNC, LDSA, and APS, respectively. Traffic-related variables, such as length of major roads within buffers 100-150 m and distance to streets with various speed limits were amongst the highly-ranked predictors for our models. Overall, our ML models achieved high R2 values and low errors, providing insights into UFP exposure in a European city where average PNC is quite low. These hyperlocal predictions can be used to study health effects of UFPs in the Danish Capital.

Evaluating the mortality and health rate caused by the PM2.5 pollutant in the air of several important Iranian cities and evaluating the effect of variables with a linear time series model

All over the world, the level of special air pollutants that have the potential to cause diseases is increasing. Although the relationship between exposure to air pollutants and mortality has been proven, the health risk assessment and prediction of these pollutants have a therapeutic role in protecting public health, and need more research. The purpose of this research is to evaluate the ill-health caused by PM2.5 pollution using AirQ + software and to evaluate the different effects on PM2.5 with time series linear modeling by R software version 4.1.3 in the cities of Arak, Esfahan, Ahvaz, Tabriz, Shiraz, Karaj and Mashhad during 2019-2020. The pollutant hours, meteorology, population and mortality information were calculated by the Environmental Protection Organization, Meteorological Organization, Statistics Organization and Statistics and Information Technology Center of the Ministry of Health, Treatment and Medical Education for 24 h of PM2.5 pollution with Excel software. In addition, having 24 h of PM2.5 pollutants and meteorology is used to the effect of variables on PM2.5 concentration. The results showed that the highest and lowest number of deaths due to natural deaths, ischemic heart disease (IHD), lung cancer (LC), chronic obstructive pulmonary disease (COPD), acute lower respiratory infection (ALRI) and stroke in The effect of disease with PM2.5 pollutant in Ahvaz and Arak cities was 7.39-12.32%, 14.6-17.29%, 16.48-8.39%, 10.43-18.91%, 12.21-22.79% and 14.6-18.54 % respectively. Another result of this research was the high mortality of the disease compared to the mortality of the nose. The analysis of the results showed that by reducing the pollutants in the cities of Karaj and Shiraz, there is a significant reduction in mortality and linear modeling provides a suitable method for air management planning.

Bedeutung der Gesetzgebung zur Luftreinhaltung in der Prävention umweltbedingter Erkrankungen

Die Luftverschmutzung beispielsweise durch Feinstaub (PM, particulate matter), Stickoxide oder Ozon ist schädlich für die Gesundheit. Bestehende Lungenkrankheiten können sich durch kurzfristig erhöhte Luftbelastung verschlimmern. Langfristige Luftbelastung trägt insbesondere zur Entstehung von kardiorespiratorischen Erkrankungen bei. In Deutschland starben im Jahr 2019 53.000 Menschen vorzeitig aufgrund der Feinstaubbelastung. Die Luftreinhaltung ist eine politische Aufgabe mit großem gesundheitlichem Potenzial. Sie hat in den letzten Jahren wesentlich zur Verbesserung der Luftqualität und damit der Gesundheit beigetragen. In Anbetracht der neuen stringenteren Luftqualitätsleitlinien der Weltgesundheitsorganisation (WHO) sind die Behörden und Politiker nun weltweit mit der Frage der Anpassung der Luftreinhalteziele konfrontiert. In Europa prägt die EU-Direktive die Luftreinhalteziele der Mitgliedstaaten. Die Festlegung der Richtwerte obliegt dem EU-Parlament und dem Rat der EU. Das Nichterreichen der gesetzten Ziele ist mit Strafen verbunden. Deshalb besteht die Gefahr, dass erreichbare und weniger ambitionierte Ziele gesetzt werden. Bereits heute liegen die EU-Richtwerte wesentlich höher als jene in den USA oder der Schweiz. Während „nur“ 11 % der Bevölkerung in der EU einer Belastung über dem EU-Grenzwert für Feinstaub PM10 im Jahr 2020 ausgesetzt waren, sind bei Anwendungen der neuen WHO-Leitlinie 71 % der Bevölkerung übermäßigen und gesundheitsgefährdenden Feinstaubwerten ausgesetzt. Zur wichtigsten und erfolgreichsten Maßnahme der Luftreinhaltung zählt die Reduktion der Luftschadstoffe an der Quelle: die Emissionsbegrenzung. Trotz der Energiekrise dürfen Ziele bezüglich Luftreinhaltung und Klimaschutz nicht aus den Augen verloren werden. Wichtig ist, dass der Gesundheitsschutz nicht dem Einzelnen überlassen werden kann. Gesundheitsfachleute haben in der Beratung empfindlicher Patienten im Umgang mit kurzfristig erhöhter Luftschadstoffbelastung eine wichtige klinische Funktion, aber darüber hinaus ist ihre beratende Rolle in der Politik sehr bedeutsam.

Association between temperature and natural mortality in Belgium: Effect modification by individual characteristics and residential environment

BACKGROUND

There is strong evidence of mortality being associated to extreme temperatures but the extent to which individual or residential factors modulate this temperature vulnerability is less clear.

METHODS

We conducted a multi-city study with a time-stratified case-crossover design and used conditional logistic regression to examine the association between extreme temperatures and overall natural and cause-specific mortality. City-specific estimates were pooled using a random-effect meta-analysis to describe the global association. Cold and heat effects were assessed by comparing the mortality risks corresponding to the 2.5th and 97.5th percentiles of the daily temperature, respectively, with the minimum mortality temperature. For cold, we cumulated the risk over lags of 0 to 28 days before death and 0 to 7 days for heat. We carried out stratified analyses and assessed effect modification by individual characteristics, preexisting chronic health conditions and residential environment (population density, built-up area and air pollutants: PM2.5, NO2, O3 and black carbon) to identify more vulnerable population subgroups.

RESULTS

Based on 307,859 deaths from natural causes, we found significant cold effect (OR = 1.42, 95%CI: 1.30-1.57) and heat effect (OR = 1.17, 95%CI: 1.12-1.21) for overall natural mortality and for respiratory causes in particular. There were significant effects modifications for some health conditions: people with asthma were at higher risk for cold, and people with psychoses for heat. In addition, people with long or frequent hospital admissions in the year preceding death were at lower risk. Despite large uncertainties, there was suggestion of effect modification by air pollutants: the effect of heat was higher on more polluted days of O3 and black carbon, and a higher cold effect was observed on more polluted days of PM2.5 and NO2 while for O3, the effect was lower.

CONCLUSIONS

These findings allow for targeted planning of public-health measures aiming to prevent the effects of extreme temperatures.

Short-term health impacts related to ozone in China before and after implementation of policy measures: A systematic review and meta-analysis

This paper presents a meta-analysis of the impacts of short-term exposure to ozone (O₃) on three health endpoints: all-cause, cardiovascular, and respiratory mortality in China. All relevant studies from January 1990 to December 2021 were searched from four databases. After screening, 30 studies were included for the meta-analysis. The results showed that a significant rise of 0.41 % (95 % confidence interval (CI): 0.35 %-0.48 %) in all-cause, 0.60 % (95 % CI: 0.51 %-0.68 %) in cardiovascular and 0.45 % (95 % CI: 0.28 %-0.62 %) in respiratory mortality for each 10 μg m^-3 increase in the maximum daily 8 h average O₃ concentration (MDA8 O₃). Moreover, results stratified by heterogeneous time periods before and after implementing a policy measure in 2013, showed that the pooled effects for all-cause and respiratory mortality before were greater than those after, while the pooled effects for cardiovascular mortality before 2013 were slightly smaller than those after. The finding that short-term exposure to O₃ was positively related to the three health endpoints was validated by means of a sensitivity analysis. Furthermore, we did not observe any publication bias. Our results present an updated and better understanding of the relationship between short-term exposure to O₃ and the three health endpoints, while providing a reference for further assessment of the impact of short-term O₃ exposure on human health.

Methods for assessing the impact of PM2.5 concentration on mortality while controlling for socio-economic factors

Even though industrial development has brought vast improvements to our daily lives, it carries with it negative effects such as adverse health outcomes caused by PM_2.5 and other pollutants. The negative externalities and external costs might occur when property rights are not properly defined, which means that if no one holds a property right on the atmosphere and the quality of air, there is no appropriate mechanism to prevent a further expansion of negative effects. An economic burden of pollution related to premature morbidity and mortality in individual countries can account for 5–14% of GDP (World Bank, 2021). In 2019, the worldwide health cost of mortality and morbidity caused by exposure to PM_2.5 concentration was $8.1 trillion, which is equivalent to 6.1 percent of the global gross domestic product (GDP) (World Bank estimate). Policymakers require evidence-based results that clearly show the impact that air pollution has on the economy and society, in order to be able to establish the proper regulations and ensure their successful implementation. The purpose of this long term study is to provide methods for assessing the negative effects of PM_2.5 concentration on PM_2.5-related mortality using panel data structure and demonstrate how socio-economic factors affect this relation. This study employed advanced econometric techniques to analyse the long-term impact of PM_2.5 on human health, while controlling for socio economic indicators. This study has demonstrated significant effects of socio-economic, health risk and system and governance variables on the relation between PM_2.5 ​concentration and PM_2.5-related mortality.

Methods Matter: A Comparative Review of Health Risk Assessments for Ambient Air Pollution in Switzerland

Objectives: Air pollution health risk assessments (AP-HRAs) provide a method to quantify health effects for entire populations. In Switzerland, AP-HRAs are included in Swiss assessments for Transport Externalities (STEs), ordered by public authorities since the 1990s. This study aimed to describe the differences among national and international AP-HRAs for Switzerland. Methods: We compared input data, approaches and results across AP-HRAs over time. Results and input data for each AP-HRA were expressed as a ratio compared to the most recent STE (in most cases STE-2010). Results: Substantial variation across AP-HRAs was found. For all-cause adult mortality attributed to particulate matter (the most frequent outcome-pollutant pair), the ratio in HRAs oscillated from 0.40 to 2.09 (times the STE-2010 value). Regarding input data, the ratio ranged from 0.69 to 1.26 for population exposure, from 0 to 1.81 for counterfactual scenario, from 0.96 to 1.13 for concentration-response function and from 1.03 to 1.13 for baseline health data. Conclusion: This study demonstrates that methods matter for AP-HRAs. Transparent and possibly standardized reporting of key input data and assumptions should be promoted to facilitate comparison of AP-HRAs.

Environmental Penalties, Investor Attention and Stock Market Reaction: Moderating Roles of Air Pollution and Industry Saliency

Despite the importance of environmental penalties in environmental enforcement, how and under what situations they impact stock market reaction is still unclear. Drawing on the theories of expectancy violation and attention driven, a conceptual model is built to explore how environmental penalty influences stock market reaction through investor attention. Furthermore, it is explored that the air pollution and industry saliency facilitate the indirect relationship between environmental penalty and investor attention. We empirically test this theoretical framework using a sample of 88 listed companies that received the environmental penalty. Up to 31 December 2020, a total of 88 A-share listed companies in Shanghai and Shenzhen stock exchanges were obtained as samples by collecting the announcement of environmental penalties of listed companies on Juchao Network. Furthermore Baidu index is taken as a proxy for investor attention in this study. Our findings reveal that investor attention plays mediating role in the relationship between environmental penalty and abnormal returns, while the direct effect of environmental penalty on stock market reaction has not been verified, thus, investor attention plays a complete mediating role between them. In addition, air pollution moderates the relationship between Environmental penalties and investor attention. The study found that enterprises in heavy pollution industries might suffer safety-in-numbers effect, which would weaken the directly negative impact of environmental penalties, and verified the moderating effect of industry saliency. These findings provide theoretical and practical implications for understanding how environmental penalties influence on stock market reaction.

Estimation of economic costs of air pollution caused by motor vehicles in Iran (Isfahan)

Since mobile sources are one of the most important sources of air pollution, this paper tries to estimate the health effects and economic burden due to fine particulate matter (PM_2.5) concentrations from motor vehicles. In this regard, we calculate the economic costs of air pollution emitted by vehicles in Isfahan over the period from March 2018 to March 2020. The concentration of urban traffic pollution based on the generalized additive model (GAM) as well as spatial distribution of pollution is estimated. Health effects are evaluated using AirQ⁺ updated by the WHO European Centre for Environment and Health. Economic burden of mortality attributable air pollution from traffic is calculated using value of a statistical life (VOSL), and the value of life years (VOLY) approach. The results indicated that the number of deaths attributable to PM_2.5 from motor vehicles in these two consecutive years was 136 (95%CI: 89-179), and 147 cases (95%CI: 96-194), respectively. The number of years of life lost due to premature death from air pollution was 2079 years annually. The economic costs imposed under VOSL approach were on average USD 51.7 (95%CI: 43-75) million per year, and according to VOLY approach USD 11.5 (95%CI: 9-13) million per year. These results help to analyze the cost-benefit and prioritize control measures to reduce air pollution. In addition, combination of these results with other externality cost of road traffic can take account for urban transportation planning.

Exploration of PM mass, source, and component-related factors that might explain heterogeneity in daily PM2.5-mortality associations across the United States

Multi-city epidemiologic studies examining short-term (daily) differences in fine particulate matter (PM2.5) provide evidence of substantial spatial heterogeneity in city-specific mortality risk estimates across the United States. Because PM2.5 is a mixture of particles, both directly emitted from sources or formed through atmospheric reactions, some of this heterogeneity may be due to regional variations in PM2.5 toxicity. Using inverse variance weighted linear regression, we examined change in percent change in mortality in association with 24 "exposure" determinants representing three basic groupings based on potential explanations for differences in PM toxicity - size, source, and composition. Percent changes in mortality for the PM2.5-mortality association for 313 core-based statistical areas and their metropolitan divisions over 1999-2005 were used as the outcome. Several determinants were identified as potential contributors to heterogeneity: all mass fraction determinants, vehicle miles traveled (VMT) for diesel total, VMT gas per capita, PM2.5 ammonium, PM2.5 nitrate, and PM2.5 sulfate. In multivariable models, only daily correlation of PM2.5 with PM10 and long-term average PM2.5 mass concentration were retained, explaining approximately 10% of total variability. The results of this analysis contribute to the growing body of literature specifically focusing on assessing the underlying basis of the observed spatial heterogeneity in PM2.5-mortality effect estimates, continuing to demonstrate that this heterogeneity is multifactorial and not attributable to a single aspect of PM.

Long-term exposure to ambient air pollution is associated with coronary artery calcification among asymptomatic adults

AIMS

We investigated the effects of exposure to very low levels of particulate matter <2.5 µm (PM2.5) and nitrogen dioxide (NO2) on coronary calcium score (CCS) in asymptomatic adults who are free of coronary artery disease (CAD).

METHODS AND RESULTS

This study included 606 asymptomatic adults (49% men, aged 56±7 years) recruited from communities in three states of Australia during 2017-2018. CCS was measured using coronary computed tomography scan at recruitment. Annual PM2.5 and NO2 concentrations were estimated on the year before recruitment using statistical exposure models and assigned to each participant's residential address. Medical history, physical measurements, biochemistry, and sociodemographic and socioeconomic status were also recorded. Median concentrations of PM2.5 and NO2 were 6.9 µg/m3 [interquartile range (IQR) 6.0-7.7)] and 3.1 ppb [IQR 2.2-4.5], respectively. Of the 606 participants, 16% had high CCS (≥100) and 4% had very high CCS (≥400). Exposure to higher PM2.5 (per µg/m3) was significantly associated with greater odds of having high CCS (OR 1.20, 95% CI 1.02-1.43) and very high CCS (OR 1.55, 95% CI 1.05-2.29). Similar associations were observed for NO2 and high CCS (OR 1.14, 95% CI 1.02-1.27) and very high CCS (OR 1.23, 95% CI 1.07-1.51). These findings were robust to adjustment for sociodemographic factors, traditional cardiovascular risk factors, renal function, education, and socio-economic status.

CONCLUSIONS

Ambient air pollution even at low concentration was associated with degree of coronary artery calcification among asymptomatic low cardiovascular risk adults, independent of other risk factors. These findings suggest that air pollution is one of the residual risk factors of CAD.

Inter-mortality displacement hypothesis and short-term effect of ambient air pollution on mortality in seven major cities of South Korea: a time-series analysis

BACKGROUND

Inter-mortality displacement (IMD) between cause-specific mortalities has not been introduced in air pollution epidemiology. Investigation into IMD would provide insights on the actual health burden of air pollution and interpretation of associations. We aimed to investigate IMD regarding short-term effect of air pollution on mortality.

METHODS

We illustrated manifestations and interpretations of lag-mortality associations. If IMD exists, a net increase of one cause-specific death can be offset by a net decrease of other cause-specific deaths. We conducted a time-series analysis to estimate associations of ambient particulate matter smaller than 10 µm (PM10), ozone (O3), sulphur dioxide (SO2), nitrogen dioxide (NO2) and carbon monoxide (CO) with mortality, considering lags up to the previous 45 days, for seven major cities of South Korea from 2006 to 2013. Attributable mortality cases were identified.

RESULTS

For O3, respiratory mortality [11 929 cases, 95% empirical confidence interval (eCI), 5358, 17 688 cases] was counterbalanced by cardiovascular mortality (-11 272 cases, 95% eCI: -22 444, -629 cases). All-cause mortality was 37 148 cases (95% eCI: 4448, 68 782 cases). For PM10, respiratory deaths were 9167 cases (95% eCI: 563, 16 521 cases), and cardiovascular deaths were 6929 cases (95% eCI: -11 793, 24 138 cases). Estimates for SO2 were comparable to those for PM10. All-cause mortality attributable to NO2 was explained by short-term mortality displacement. No associations with mortality were found for CO.

CONCLUSIONS

IMD may exist in the relationship between air pollution and mortality. The actual relationship between air pollution and cause-specific mortality may be masked by IMD.

Continuous increases of surface ozone and associated premature mortality growth in China during 2015-2019

Ambient ozone (O₃) pollution has become a big issue in China. Recent studies have linked long- and short-term O₃ exposure to several public health risks. In this study, we (1) characterize the long-term and short-term O₃-attributed health metric in China from 2015 to 2019; (2) estimate the surface O₃ trends; and (3) quantify the long-term and short-term health impacts (i.e. all-cause, cardiovascular and respiratory mortality) in 350 urban Chinese cities. In these 5-years, the national annual average of daily maximum 8 h average (AVGDMA8) O₃ concentrations and warm-season (April-September) 4th highest daily maximum 8 h average (4DMA8) O₃ concentrations increased from 74.0 ± 15.5 μg/m³ (mean ± standard deviation) to 82.3 ± 12.0 μg/m³ and 167 ± 37.0 μg/m³ to 174 ± 30.0 μg/m³ respectively. During this period, the DMA8 O₃ concentration increased by 1.9 ± 3.3 μg/m³/yr across China, with over 70% of the monitoring sites showing a positive upward trend and 19.4% with trends >5 μg/m³/yr. The estimated long-term all-cause, cardiovascular and respiratory premature mortalities attributable to AVGDMA8 O₃ exposure in 350 Chinese cities were 181,000 (95% CI: 91,500-352,000), 112,000 (95% CI: 38,100-214,000) and 33,800 (95% CI: 0-71,400) in 2019, showing increases of 52.5%, 52.9% and 54.6% respectively compared to 2015 levels. Similarly, short-term all-cause, cardiovascular and respiratory premature mortalities attributed to ambient 4DMA8 O₃ exposure were 156,000 (95% CI: 85,300-227,000), 73,500 (95% CI: 27,500-119,000) and 28,600 (95% CI: 14,500-42,800) in 2019, increases of 19.6%, 19.8% and 21.2% respectively compared to 2015. The results of this study are important in ascertaining the effectiveness of recent emission control measures and to identify the areas that require urgent attention.

Spatial-Temporal Modelling of Disease Risk Accounting for PM2.5 Exposure in the Province of Pavia: An Area of the Po Valley

Spatio-temporal Bayesian disease mapping is the branch of spatial epidemiology interested in providing valuable risk estimates in certain geographical regions using administrative areas as statistical units. The aim of the present paper is to describe spatio-temporal distribution of cardiovascular mortality in the Province of Pavia in 2010 through 2015 and assess its association with environmental pollution exposure. To produce reliable risk estimates, eight different models (hierarchical log-linear model) have been assessed: temporal parametric trend components were included together with some random effects that allowed the accounting of spatial structure of the region. The Bayesian approach allowed the borrowing information effect, including simpler model results in the more complex setting. To compare these models, Watanabe–Akaike Information Criteria (WAIC) and Leave One Out Information Criteria (LOOIC) were applied. In the modelling phase, the relationship between the disease risk and pollutants exposure (PM2.5) accounting for the urbanisation level of each geographical unit showed a strong significant effect of the pollutant exposure (OR = 1.075 and posterior probability, or PP, >0.999, equivalent to p < 0.001). A high-risk cluster of Cardiovascular mortality in the Lomellina subareas in the studied window was identified.

Alternative adjustment for seasonality and long-term time-trend in time-series analysis for long-term environmental exposures and disease counts

Background

Time-series analysis with case-only data is a prominent method for the effect of environmental determinants on disease events in environmental epidemiology. In this analysis, adjustment for seasonality and long-term time-trend is crucial to obtain valid findings. When applying this analysis for long-term exposure (e.g., months, years) of which effects are usually studied via survival analysis with individual-level longitudinal data, unlike its application for short-term exposure (e.g., days, weeks), a standard adjustment method for seasonality and long-term time-trend can extremely inflate standard error of coefficient estimates of the effects. Given that individual-level longitudinal data are difficult to construct and often available to limited populations, if this inflation of standard error can be solved, rich case-only data over regions and countries would be very useful to test a variety of research hypotheses considering unique local contexts.

Methods

We discuss adjustment methods for seasonality and time-trend used in time-series analysis in environmental epidemiology and explain why standard errors can be inflated. We suggest alternative methods to solve this problem. We conduct simulation analyses based on real data for Seoul, South Korea, 2002–2013, and time-series analysis using real data for seven major South Korean cities, 2006–2013 to identify whether the association between long-term exposure and health outcomes can be estimated via time-series analysis with alternative adjustment methods.

Results

Simulation analyses and real-data analysis confirmed that frequently used adjustment methods such as a spline function of a variable representing time extremely inflate standard errors of estimates for associations between long-term exposure and health outcomes. Instead, alternative methods such as a combination of functions of variables representing time can make sufficient adjustment with efficiency.

Conclusions

Our findings suggest that time-series analysis with case-only data can be applied for estimating long-term exposure effects. Rich case-only data such as death certificates and hospitalization records combined with repeated measurements of environmental determinants across countries would have high potentials for investigating the effects of long-term exposure on health outcomes allowing for unique contexts of local populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-020-01199-1.

Short-term exposure to particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), and ozone (O3) and all-cause and cause-specific mortality: Systematic review and meta-analysis

BACKGROUND

Air pollution is a leading cause of mortality and morbidity worldwide. Short-term exposure (from one hour to days) to selected air pollutants has been associated with human mortality. This systematic review was conducted to analyse the evidence on the effects of short-term exposure to particulate matter with aerodynamic diameters less or equal than 10 and 2.5 µm (PM_10, PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃), on all-cause mortality, and PM₁₀ and PM_2.5 on cardiovascular, respiratory, and cerebrovascular mortality.

METHODS

We included studies on human populations exposed to outdoor air pollution from any source, excluding occupational exposures. Relative risks (RRs) per 10 µg/m³ increase in air pollutants concentrations were used as the effect estimates. Heterogeneity between studies was assessed using 80% prediction intervals. Risk of bias (RoB) in individual studies was analysed using a new domain-based assessment tool, developed by a working group convened by the World Health Organization and designed specifically to evaluate RoB within eligible air pollution studies included in systematic reviews. We conducted subgroup and sensitivity analyses by age, sex, continent, study design, single or multicity studies, time lag, and RoB. The certainty of evidence was assessed for each exposure-outcome combination. The protocol for this review was registered with PROSPERO (CRD42018087749).

RESULTS

We included 196 articles in quantitative analysis. All combinations of pollutants and all-cause and cause-specific mortality were positively associated in the main analysis, and in a wide range of sensitivity analyses. The only exception was NO₂, but when considering a 1-hour maximum exposure. We found positive associations between pollutants and all-cause mortality for PM₁₀ (RR: 1.0041; 95% CI: 1.0034-1.0049), PM_2.5 (RR: 1.0065; 95% CI: 1.0044-1.0086), NO₂ (24-hour average) (RR: 1.0072; 95% CI: 1.0059-1.0085), and O₃ (RR: 1.0043; 95% CI: 1.0034-1.0052). PM₁₀ and PM_2.5 were also positively associated with cardiovascular, respiratory, and cerebrovascular mortality. We found some degree of heterogeneity between studies in three exposure-outcome combinations, and this heterogeneity could not be explained after subgroup analysis. RoB was low or moderate in the majority of articles. The certainty of evidence was judged as high in 10 out of 11 combinations, and moderate in one combination.

CONCLUSIONS

This study found evidence of a positive association between short-term exposure to PM₁₀, PM_2.5, NO₂, and O₃ and all-cause mortality, and between PM₁₀ and PM_2.5 and cardiovascular, respiratory and cerebrovascular mortality. These results were robust through several sensitivity analyses. In general, the level of evidence was high, meaning that we can be confident in the associations found in this study.

Global Estimates and Long-Term Trends of Fine Particulate Matter Concentrations (1998-2018)

Exposure to outdoor fine particulate matter (PM_2.5) is a leading risk factor for mortality. We develop global estimates of annual PM_2.5 concentrations and trends for 1998-2018 using advances in satellite observations, chemical transport modeling, and ground-based monitoring. Aerosol optical depths (AODs) from advanced satellite products including finer resolution, increased global coverage, and improved long-term stability are combined and related to surface PM_2.5 concentrations using geophysical relationships between surface PM_2.5 and AOD simulated by the GEOS-Chem chemical transport model with updated algorithms. The resultant annual mean geophysical PM_2.5 estimates are highly consistent with globally distributed ground monitors (R² = 0.81; slope = 0.90). Geographically weighted regression is applied to the geophysical PM_2.5 estimates to predict and account for the residual bias with PM_2.5 monitors, yielding even higher cross validated agreement (R² = 0.90-0.92; slope = 0.90-0.97) with ground monitors and improved agreement compared to all earlier global estimates. The consistent long-term satellite AOD and simulation enable trend assessment over a 21 year period, identifying significant trends for eastern North America (-0.28 ± 0.03 μg/m³/yr), Europe (-0.15 ± 0.03 μg/m³/yr), India (1.13 ± 0.15 μg/m³/yr), and globally (0.04 ± 0.02 μg/m³/yr). The positive trend (2.44 ± 0.44 μg/m³/yr) for India over 2005-2013 and the negative trend (-3.37 ± 0.38 μg/m³/yr) for China over 2011-2018 are remarkable, with implications for the health of billions of people.

Attributable Risk to Assess the Health Impact of Air Pollution: Advances, Controversies, State of the Art and Future Needs

Despite the increased attention given to the health impact assessment of air pollution and to the strategies to control it in both scientific literature and concrete interventions, the results of the implementations, especially those involving traffic, have not always been satisfactory and there is still disagreement about the most appropriate interventions and the methods to assess their effectiveness. This state-of-the-art article reviews the recent interpretation of the concepts that concern the impact assessment, and compares old and new measurements of attributable risk and attributable fraction. It also summarizes the ongoing discussion about the designs and methods for assessing the air pollution impact with particular attention to improvements due to spatio-temporal analysis and other new approaches, such as studying short term effects in cohorts, and the still discussed methods of predicting the values of attributable risk (AR). Finally, the study presents the more recent analytic perspectives and the methods for directly assessing the effects of not yet implemented interventions on air quality and health, in accordance with the suggestion in the strategic plan 2020-2025 from the Health Effect Institute.

Changes in extrapulmonary organs and serum enzyme biomarkers after chronic exposure to Buenos Aires air pollution

Urban air pollution is a serious environmental problem in developing countries worldwide, and health is a pressing issue in the megacities in Latin America. Buenos Aires is a megacity with an estimated moderate Air Quality Index ranging from 42 to 74 μg/m³. Exposure to Urban Air Particles from Buenos Aires (UAP-BA) induces morphological and physiological respiratory alterations; nevertheless, no studies on extrapulmonary organs have been performed. The aim of the present study was to explore the health effects of chronic exposure to UAP-BA (1, 6, 9, and 12 months) on the liver, heart, and serum risk biomarkers. BALB/c mice were exposed to UAP-BA or filtered air (FA) in inhalation chambers, and liver and heart histopathology, oxidative metabolism (superoxide dismutase, SOD; catalase, CAT; lipoperoxidation, TBARS), amino transaminases (AST, ALT) as serum risk biomarkers, alkaline phosphatase (ALP), paraxonase-1 (PON-1), and lipoprotein-associated phospholipase A2 (Lp-PLA2) were evaluated. Chronic exposure to real levels of UAP in Buenos Aires led to alterations in extrapulmonary organs associated with inflammation and oxidative imbalance and to changes in liver and heart risk biomarkers. Our results may reflect the impact of the persistent air pollution in Buenos Aires on individuals living in this Latin American megacity.

Short-term associations between daily mortality and ambient particulate matter, nitrogen dioxide, and the air quality index in a Middle Eastern megacity

There is limited evidence for short-term association between mortality and ambient air pollution in the Middle East and no study has evaluated exposure windows of about a month prior to death. We investigated all-cause non-accidental daily mortality and its association with fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), and the Air Quality Index (AQI) from March 2011 through March 2014 in the megacity of Tehran, Iran. Generalized additive quasi-Poisson models were used within a distributed lag linear modeling framework to estimate the cumulative effects of PM_2.5, NO₂, and the AQI up to a lag of 45 days. We further conducted multi-pollutant models and also stratified the analyses by sex, age group, and season. The relative risk (95% confidence interval (CI)) for all seasons, both sexes and all ages at lag 0 for PM_2.5, NO₂, and AQI were 1.004 (1.001, 1.007), 1.003 (0.999, 1.007), and 1.004 (1.001, 1.007), respectively, per inter-quartile range (IQR) increment (18.8 μg/m³ for PM_2.5, 12.6 ppb for NO₂, and 31.5 for AQI). In multi-pollutant models, the PM_2.5 associations were almost independent from NO₂. However, the RRs for NO₂ were slightly attenuated after adjustment for PM_2.5 but they were still largely independent from PM_2.5. The cumulative relative risks (95% CI) per IQR increment reached maximum during the cooler months, including: 1.13 (1.06, 1.20) for PM_2.5 at lag 0-31 (for females, all ages); 1.17 (1.10, 1.25) for NO₂ at lag 0-45 (for males, all ages); and 1.13 (1.07, 1.20) for the AQI at lag 0-30 (for females, all ages). Generally, the RRs were slightly larger for NO₂ than PM_2.5 and AQI. We found somewhat larger RRs in females, age group >65 years of age, and in cooler months. In summary, positive associations were found in most models. This is the first study to report short-term associations between all-cause non-accidental mortality and ambient PM_2.5 and NO₂ in Iran.

Public health benefits of reducing exposure to ambient fine particulate matter in South Africa

Air pollution is a growing problem in developing countries, and there exists a wide range of evidence documenting the large health and productivity losses associated with high concentrations of pollutants. South Africa is a developing country with high levels of air pollution in some regions, and the costs of air pollution on human health and economic growth in South Africa are still uncertain. The environmental Benefits Mapping and Analysis Program (BenMAP) model was applied to South Africa using local data on population, mortality rates, and concentrations of fine particulate matter (PM_2.5), as well as mortality risk coefficients from the epidemiological literature. BenMAP estimates the number of premature deaths that would likely have been avoided if South African air quality levels met the existing annual National Ambient Air Quality Standard (NAAQS) of 20 μg m^-3, and the more stringent World Health Organization (WHO) guideline for annual average PM_2.5 of 10 μg m^-3. We estimate 14,000 avoided premature mortalities in 2012 if all of South Africa met the existing NAAQS annual average standard for PM_2.5. These avoided cases of mortality have an estimated monetary value of $14.0 billion (US2011$), which is equivalent to 2.2% of South Africa's 2012 GDP (PPP, US2011$). We estimate 28,000 avoided premature mortalities if the more stringent WHO guideline for annual average PM_2.5 is met across South Africa, which when expressed as a national burden is equivalent to 6% of all deaths in South Africa being attributable to PM_2.5 exposure. These avoided cases of mortality have an estimated monetary value of $29.1 billion, which is equivalent to 4.5% of South Africa's 2012 GDP. These results show that there are significant public health benefits to lowering PM_2.5 concentrations across South Africa, with correspondingly high economic benefits.

Impacts of urban form on air quality: Emissions on the road and concentrations in the US metropolitan areas

In the United States (US), one of the effects of urban sprawl is more vehicular travel. The increase in emissions from road traffic renders air quality management unsuccessful, in spite of the efforts of the US Environmental Protection Agency (EPA), operating under the Clean Air Act, which does not regulate land use. As an alternative to urban sprawl, the US-EPA has initiated smart growth strategies based on compact development. In this study, the impacts of metropolitan-level urban form, as a measure of urban compactness/sprawl, was explored with respect to air quality in terms of NO_x and PM_2.5 emissions on the road and NO₂ and PM_2.5 concentrations in US metropolitan areas. Ordinary least squares (OLS) and two-level regression models that control for metropolitan-level socioeconomic and local-level geographic covariates were established. The results showed that high land use mixing is one of the compactness/sprawl factors (i.e., low sprawl) that reduces per-person NO_x and PM_2.5 emissions on the road. While metropolitan-level urban form (i.e. high compactness) had a negative effect on PM_2.5 concentrations, local environmental conditions, such as local ambient roads and emissions facilities, had greater impacts on NO₂ and PM_2.5 concentrations than the urban form. Based on the findings in this study, urban planners and decision makers need to establish policies and practices at two scales when planning urban development: (1) the reduction of emissions from road traffic by managing metropolitan-level urban form and (2) the reduction of emissions concentrations through managing local emissions sources near populated areas.

Chronic exposure to urban air pollution from Buenos Aires: the ocular mucosa as an early biomarker

Air pollution represents a major health problem in megacities, bringing about 8 million deaths every year. The aim of the study was to evaluate in vivo the ocular and respiratory mucosa biological response after chronic exposure to urban air particles from Buenos Aires (UAP-BA). BALB/c mice were exposed to UAP-BA or filtered air for 1, 6, 9, and 12 months. After exposure, histology, histomorphometry, and IL-6 proinflammatory cytokine level were evaluated in the respiratory and ocular mucosa. Total cell number and differential cell count were determined in the brochoalveolar lavage fluid. In the lung, chronic exposure to UAP-BA induced reduction of the alveolar space, polymorhonuclear cell recruitment, and goblet cell hyperplasia. In the ocular surface, UAP-BA induced an initial mucin positive cells rise followed by a decline through time, while IL-6 level increased at the latest point-time assayed. Our results showed that the respiratory and the ocular mucosas respond differently to UAP-BA. Being that lung and ocular mucosa diseases may be triggered and/or exacerbated by chronic exposure to urban air PM, the inhabitants of Buenos Aires whom are chronically exposed to environmental urban air pollution may be considered a subpopulation at risk. Based on our results, we propose the ocular mucosa as a reliable and more accessible surrogate for pulmonary mucosa environmental toxicity that might also serve as an earlier biomarker for air pollution adverse impact on health.

National NO2 exposure models for measuring its impact on vulnerable people in the US metropolitan areas

Epidemiological research requires accurate prediction of the concentrations of air pollutants. In this study, satellite-based estimates (OMI NO₂), distance-weighted models (DWMs), and universal kriging (UK) are applied to land use regression (LUR) to predict annually and monthly averaged NO₂ concentrations in the continental United States. In addition, to assess environmental risk, the relationship between NO₂ concentrations and people potentially exposed to NO₂ within urban areas is explored in 377 metropolitan statistical areas (MSAs). The results of this study show that the application of a combination of OMI NO₂, UK, and DWMs to LUR yielded the highest cross-validated (CV) R² values and the lowest root mean square error of prediction (RMSEP): 82.9% and 0.392 on a square root scale of ppb in the annual model and 70.4-83.5% and 0.408-0.518 on square root scale of ppb in the monthly models, respectively. Moreover, the model presented a spatially unbiased distribution of CV error terms. Models based on LUR provided more accurate NO₂ predictions with lower RMSEP in urban areas than in rural areas. In addition, this study finds that the people living in the urban areas of MSAs, with larger populations and a higher percentage of children under 18 years of age, are likely to be exposed to higher NO₂ concentrations. By contrast, people living in the urban areas of MSAs with a higher percentage of the elderly over 65 years of age are likely to be exposed to lower NO₂ concentrations.

The Shape of the Concentration-Response Association between Fine Particulate Matter Pollution and Human Mortality in Beijing, China, and Its Implications for Health Impact Assessment

BACKGROUND

Studies found approximately linear short-term associations between particulate matter (PM) and mortality in Western communities. However, in China, where the urban PM levels are typically considerably higher than in Western communities, some studies suggest nonlinearity in this association. Health impact assessments (HIA) of PM in China have generally not incorporated nonlinearity in the concentration-response (C-R) association, which could result in large discrepancies in estimates of excess deaths if the true association is nonlinear.

OBJECTIVES

We investigated nonlinearity in the C-R associations between with PM with aerodynamic diameter [Formula: see text] ([Formula: see text]) and mortality in Beijing, China, and the sensitivity of HIA to linearity assumptions.

METHODS

We modeled the C-R association between [Formula: see text] and cause-specific mortality in Beijing, China (2009-2012), using generalized linear models (GLM). [Formula: see text] was included through either linear, piecewise-linear, or spline functions to investigate evidence of nonlinearity. To determine the sensitivity of HIA to linearity assumptions, we estimated [Formula: see text]-attributable deaths using both linear- and nonlinear-based C-R associations between [Formula: see text] and mortality.

RESULTS

We found some evidence that, for nonaccidental and circulatory mortality, the shape of the C-R association was relatively flat at lower concentrations of [Formula: see text], but then had a positive slope at higher concentrations, indicating nonlinearity. Conversely, the shape for respiratory mortality was positive and linear at lower concentrations of [Formula: see text], but then leveled off at the higher concentrations. Estimates of excess deaths attributable to short-term [Formula: see text] exposure were, in some cases, very sensitive to the linearity assumption in the association, but in other cases robust to this assumption.

CONCLUSIONS

Our results demonstrate some evidence of nonlinearity in [Formula: see text]-mortality associations and that an assumption of linearity in this association can influence HIAs, highlighting the importance of understanding potential nonlinearity in the [Formula: see text]-mortality association at the high concentrations of [Formula: see text] in developing megacities like Beijing. https://doi.org/10.1289/EHP4464.

Spatial variation in lag structure in the short-term effects of air pollution on mortality in seven major South Korean cities, 2006-2013

Lag is one of the major uncertainties in the heterogeneity of short-term effects of particulate matter with aerodynamic diameter <10 μm (PM₁₀) on mortality. This study aimed to explore spatial variations in extended lag effects of PM₁₀ on all-cause mortality, cardiovascular mortality and respiratory mortality in seven major South Korean cities over a period spanning 2006-2013. We did time-series analysis using generalized linear models and adjusted for temporal trend, day of the week, holiday, influenza epidemic, and weather. Single lag models and distributed lag models were extensively compared, specifically in terms of lag interval, and adjustment for temporal trend. We also conducted a time-stratified case-crossover analysis. Multivariate meta-regressions with city characteristic variables were conducted in order to assess spatial variation in the lag structure. When considering up to previous 45 days of exposure, we found longer lag associations between PM₁₀ and mortality, particularly in all-cause mortality and respiratory mortality. SO₂, the ratio of SO₂ to PM₁₀ and gross regional domestic product were all found to positively contribute towards the associations between PM₁₀ and all-cause mortality and cardiovascular mortality. Ulsan (Korea's largest industrial city) was found to have the strongest cumulative percentage increases in all-cause mortality and cardiovascular mortality per 10 μg/m³ increase of PM₁₀: 4.9% (95% CI: 2.5, 7.3) and 4.3% (95% CI: -0.9, 9.7) respectively. Busan (Korea's largest seaport city) was found to have the highest cumulative percentage increase in respiratory mortality with an 8.2% increase (95% CI: 2.8, 13.8). In summary, the short-term effects of PM₁₀ on mortality may persist over a period of not just few weeks but longer than a month, and may differ according to regional economy. This study provides public health implication that, in order to minimize the health effects of PM, air quality interventions should focus on not only particulate pollution but also gaseous pollution, such as SO₂.

On inferences about lag effects using lag models in air pollution time-series studies

The choice of lag length is a matter of uncertainty in air pollution time-series studies. Lag models and model selections are widely used for inferences about lag effects, but there is lack of discussion on the integration of the two. We aimed to provide theoretical discussion on the performance of lag models, and the impact of model selections on inferences about lag effects. Bias and model selections based upon information criteria, statistical significance, effect size, and model averaging were discussed in the context of lag analysis. A simulation with eight of PM_2.5-mortality relation scenarios was also conducted in order to explore the performances of lag models and to compare the model selections. The application of lag models with an insufficient lag interval taken into account (i.e. insufficient lag models) provides biased estimates. We provided features of the model selections and showed their pitfalls in lag analysis of air pollution time-series studies. We also discussed limitations of meta-analysis which fails to consider the application of different lag models in individual studies. To foster exploration on air pollution-lag-response relations with relevant tools, we encourage researchers to compare different lag models in terms of effect estimates and variance estimates, and to report their favored models and competing models together based upon scientific knowledge supporting lag-response relations.

The association between high ambient air pollution exposure and respiratory health of young children: A cross sectional study in Jinan, China

There is growing concern about health effects of high air pollution in less-developed countries. Children represent a population at increased risk for air pollution-related respiratory conditions. This study investigated the relationship between high ambient air pollution exposure and respiratory health of young schoolchildren. From 2014 to 2016 in Jinan, China, 2532 primary school children in grades three to five from two different schools with different levels of air pollution were included in the study. Levels of ambient air pollution exposure including PM₁₀, PM_2.5, NO₂, SO₂, CO and O₃ were measured continuously at the two schools. A questionnaire about children's respiratory health was conducted every year. Among them, about 150 randomly selected children also performed lung function tests two times a year at the beginning of November and middle of December. Annual average exposure levels of PM_2.5 (66.8-79.1 vs 90.0-107.7 μg/m³), PM₁₀ (129.5-177.3 vs 198.1-218.6 μg/m³), NO₂ (45.3-53.2 vs 45.0-56.2 μg/m³), SO₂ (29.8-56.5 vs 40.5-80.3 μg/m³), CO (1.3-1.5 vs 1.4-1.7 mg/m³) and O₃ (84.8-120.2 vs 61.1-128.1 μg/m³) in the heavy pollution primary school were significantly higher than the light one. The higher air pollution exposure was related to increased prevalence of respiratory diseases of young children in the last year, especially allergic rhinitis. The increased odds of lung function impairment associated with exposure to higher air pollution, could be up to 171.5% (aOR = 2.715; 95% CI = 1.915-3.849) for PEF < 75% predicted in 2014. However, after short-term exposure for 1.5 month or a week, paired comparison for parameters of the same child showed different results. The association between high ambient air pollution exposure and respiratory health of young children is closely related to exposure time and dose and may be fluctuate and complex.

Disability Adjusted Life Years (DALYs) in Terms of Years of Life Lost (YLL) Due to Premature Adult Mortalities and Postneonatal Infant Mortalities Attributed to PM2.5 and PM10 Exposures in Kuwait

Ambient air pollution in terms of fine and coarse particulate matter (PM_2.5 and PM₁₀) has been shown to increase adult and infant mortalities. Most studies have estimated the risk of mortalities through attributable proportions and number of excess cases with no reference to the time lost due to premature mortalities. Disability adjusted life years (DALYs) are necessary to measure the health impact of Ambient particulate matter (PM) over time. In this study, we used life-tables for three years (2014⁻2016) to estimate the years of life lost (YLL), a main component of DALYs, for adult mortalities (age 30+ years) and postneonatal infant mortalities (age 28+ days⁻1 year) associated with PM_2.5 exposure and PM₁₀ exposure, respectively. The annual average of PM_2.5 and PM₁₀ concentrations were recorded as 87.9 μg/m³ and 167.5 μg/m³, which are 8 times greater than the World Health Organization (WHO) air quality guidelines of 10 μg/m³ and 20 μg/m³, respectively. Results indicated a total of 252.18 (95% CI: 170.69⁻322.92) YLL for all ages with an increase of 27,474.61 (95% CI: 18,483.02⁻35,370.58) YLL over 10 years. The expected life remaining (ELR) calculations showed that 30- and 65-year-old persons would gain 2.34 years and 1.93 years, respectively if the current PM_2.5 exposure levels were reduced to the WHO interim targets (IT-1 = 35 μg/m³). Newborns and 1-year old children may live 79.81 and 78.94 years, respectively with an increase in average life expectancy of 2.65 years if the WHO PM₁₀ interim targets were met (IT-1 = 70 μg/m³). Sensitivity analyses for YLL were carried out for the years 2015, 2025, and 2045 and showed that the years of life would increase significantly for age groups between 30 and 85. Life expectancy, especially for the elderly (≥60 years), would increase at higher rates if PM_2.5 levels were reduced further. This study can be helpful for the assessment of poor air quality represented by PM_2.5 and PM₁₀ exposures in causing premature adult mortalities and postneonatal infant mortalities in developing countries with high ambient air pollution. Information in this article adds insights to the sustainable development goals (SDG 3.9.1 and 11.6.2) related to the reduction of mortality rates attributed to ambient air levels of coarse and fine particulate matter.

Ambient air pollution and daily hospital admissions: A nationwide study in 218 Chinese cities

There have been few large multicity studies to evaluate the acute health effects of ambient air pollution on morbidity risk in developing counties. In this study, we examined the short-term associations of air pollution with daily hospital admissions in China. We conducted a nationwide time-series study in 218 Chinese cities between 2014 and 2016. Data on daily hospital admissions counts were obtained from the National Health Insurance Database for Urban Employees covering 0.28 billion enrollees. We used generalized additive model with Poisson regression to estimate the associations in each city, and we performed random-effects meta-analysis to pool the city-specific estimates. More than 60 million hospital admissions were analyzed in this study. At the national-average level, each 10 μg/m³ increase in PM₁₀, SO₂, and NO₂, and 1 mg/m³ increase in CO at lag 0 day was associated with a 0.29% (95% CI, 0.23%-0.36%), 1.16% (95% CI, 0.92%-1.40%), 1.68% (95% CI, 1.40%-1.95%), and 2.59% (95% CI, 1.69%-3.50%) higher daily hospital admissions, respectively. The associations of air pollution with hospital admissions remained statistically significant at levels below the current Chinese Ambient Air Quality Standards. The effect estimates were larger in cities with lower air pollutants levels or higher air temperatures and relative humidity, as well as in the elderly. In conclusion, our findings provide robust evidence of increased hospital admissions in association with short-term exposure to ambient air pollution in China.

Public health co-benefits of greenhouse gas emissions reduction: A systematic review

BACKGROUND AND OBJECTIVES

Public health co-benefits from curbing climate change can make greenhouse gas (GHG) mitigation strategies more attractive and increase their implementation. The purpose of this systematic review is to summarize the evidence of these health co-benefits to improve our understanding of the mitigation measures involved, potential mechanisms, and relevant uncertainties.

METHODS

A comprehensive search for peer-reviewed studies published in English was conducted using the primary electronic databases. Reference lists from these articles were reviewed and manual searches were performed to supplement relevant studies. The identified records were screened based on inclusion criteria. We extracted data from the final retrieved papers using a pre-designed data extraction form and a quality assessment was conducted. The studies were heterogeneities, so meta-analysis was not possible and instead evidence was synthesized using narrative summaries.

RESULTS

Thirty-six studies were identified. We identified GHG mitigation strategies in five domains - energy generation, transportation, food and agriculture, households, and industry and economy - which usually, although not always, bring co-benefits for public health. These health gains are likely to be multiplied by comprehensive measures that include more than one sectors.

CONCLUSIONS

GHG mitigation strategies can bring about substantial and possibly cost-effective public health co-benefits. These findings are highly relevant to policy makers and other stakeholders since they point to the compounding value of taking concerted action against climate change and air pollution.

Long-term trends and health impact of PM2.5 and O3 in Tehran, Iran, 2006-2015

The main objectives of this study were (1) investigation of the temporal variations of ambient fine particulate matter (PM_2.5) and ground level ozone (O₃) concentrations in Tehran megacity, the capital and most populous city in Iran, over a 10-year period from 2006 to 2015, and (2) estimation of their long-term health effects including all-cause and cause-specific mortality. For the first goal, the data of PM_2.5 and O₃ concentrations, measured at 21 regulatory monitoring network stations in Tehran, were obtained and the temporal trends were investigated. The health impact assessment of PM_2.5 and O₃ was performed using the World Health Organization (WHO) AirQ+ software updated in 2016 by WHO European Centre for Environment and Health. Local baseline incidences in Tehran level were used to better reveal the health effects associated with PM_2.5 and O₃. Our study showed that over 2006-2015, annual mean concentrations of PM_2.5 and O₃ varied from 24.7 to 38.8 μg m^-3 and 35.4 to 76.0 μg m^-3, respectively, and were significantly declining in the recent 6 years (2010-2015) for PM_2.5 and 8 years (2008-2015) for O₃. However, Tehran citizens were exposed to concentrations of annual PM_2.5 exceeding the WHO air quality guideline (WHO AQG) (10 μg m^-3), U.S. EPA and Iranian standard levels (12 μg m^-3) during entire study period. We estimated that long-term exposure to ambient PM_2.5 contributed to between 24.5% and 36.2% of mortality from cerebrovascular disease (stroke), 19.8% and 24.1% from ischemic heart disease (IHD), 13.6% and 19.2% from lung cancer (LC), 10.7% and 15.3% from chronic obstructive pulmonary disease (COPD), 15.0% and 25.2% from acute lower respiratory infection (ALRI), and 7.6% and 11.3% from all-cause annual mortality in the time period. We further estimated that deaths from IHD accounted for most of mortality attributable to long-term exposure to PM_2.5. The years of life lost (YLL) attributable to PM_2.5 was estimated to vary from 67,970 to 106,706 during the study period. In addition, long-term exposure to O₃ was estimated to be responsible for 0.9% to 2.3% of mortality from respiratory diseases. Overall, long-term exposure to ambient PM_2.5 and O₃ contributed substantially to mortality in Tehran megacity. Air pollution is a modifiable risk factor. Appropriate sustainable control policies are recommended to protect public health.

Effects of environment pollution on the ocular surface

The twenty-first century is fraught with dangers like climate change and pollution, which impacts human health and mortality. As levels of pollution increase, respiratory illnesses and cardiovascular ailments become more prevalent. Less understood are the eye-related complaints, which are commonly associated with increasing pollution. Affected people may complain of irritation, redness, foreign body sensation, tearing, and blurring of vision. Sources of pollution are varied, ranging from gases (such as ozone and NO₂) and particulate matter produced from traffic, to some other hazards associated with indoor environments. Mechanisms causing ocular surface disease involve toxicity, oxidative stress, and inflammation. Homeostatic mechanisms of the ocular surface may adapt to certain chronic changes in the environment, so affected people may not always be symptomatic. However there are many challenges associated with assessing effects of air pollution on eyes, as pollution is large scale and difficult to control. Persons with chronic allergic or atopic tendencies may have a pre-existing state of heightened mucosal immune response, hence they may have less tolerance for further environmental antigenic stimulation. It is beneficial to identify vulnerable people whose quality of life will be significantly impaired by environmental changes and provide counter measures in the form of protection or treatment. Better technologies in monitoring of pollutants and assessment of the eye will facilitate progress in this field.

Air Pollution and Successful Aging: Recent Evidence and New Perspectives

PURPOSE OF REVIEW

Worldwide demographic changes occurring in a relatively short period have led to a growing interest in the determinants of aging "successfully" and how to promote a healthier old age. As environmental exposures such as ambient air pollution are believed to play a role in the process of aging, they might represent one of the pathways turning potential successful agers to unsuccessful agers. We aimed to critically review the current epidemiological evidence of the associations between chronic exposure to ambient air pollution and several key determinants of unsuccessful aging and to identify specific populations of unsuccessful agers that are potentially more vulnerable to air pollution's health effects.

RECENT FINDINGS

Epidemiologic evidence supports the association between air pollution and increased risk for several major chronic diseases, cognitive impairment, frailty, and decreased longevity-all important determinants of unsuccessful aging-as well as evidence for higher vulnerability among frail populations. However, several methodological shortcomings, including possible publication bias, lack of use of an adequate indicator of unsuccessful aging, limitations in exposure assessment, and residual confounding particularly due to socioeconomic status, hinder inference of causal relationship at this stage. Future studies should use constructs such as frailty index to estimate successful aging, as well as integrate time activity patterns into the exposure assessment metric. Additionally, studies in low- and middle-income countries are needed.

The association between exposure to air pollutants including PM10, PM2.5, ozone, carbon monoxide, sulfur dioxide, and nitrogen dioxide concentration and the relative risk of developing STEMI: A case-crossover design

BACKGROUND

Unfavorable associations between air pollution and myocardial infarction are broadly investigated in recent studies and some of them revealed considerable associations; however, controversies exists between these investigations with regard to culprit components of air pollution and significance of correlation between myocardial infarction risk and air pollution.

METHODS

The association between exposure to PM₁₀, PM_2.5, ozone, carbon monoxide, sulfur dioxide, and nitrogen dioxide concentration of background air that residents of Tehran, the capital city of Iran, which is ranked as the most air polluted city of Iran and the relative risk of developing ST-elevation myocardial infarction (STEMI) were investigated by a case-crossover design. Our study included 208 patients admitted with a diagnosis of STEMI and undergone primary percutaneous intervention. Air pollutant concentration was averaged in 24-h windows preceding the time of onset of myocardial infarction for the case period. Besides, the mean level of each element of air pollution of the corresponding time in one week, two weeks and three weeks before onset of myocardial infarction, was averaged separately for each day as one control periods. Thus, 624 control periods were included in our investigation such that. Each patient is matched and compared with him/herself.

RESULTS

The mean level of PM₁₀ in case periods (61.47µg/m³) was significantly higher than its level in control periods (57.86µg/m³) (P-value = 0.019, 95% CI: 1.002-1.018, RR = 1.010). Also, the mean level of PM_2.5 in case periods (95.40µg/m³) was significantly higher than that in control days (90.88µg/m³) (P-value = 0.044, 95% CI: 1.001-1.011, RR = 1.006). The level of other components including NO₂, SO₂, CO and O₃ showed no significant differences between case and control periods. A 10µg/m³ increase in PM₁₀ and PM_2.5 would result in 10.10% and 10.06% increase in STEMI event, respectively. Furthermore, the results of sub-group analysis showed that older patients (equal or more than 60 year-old), diabetic patients, non-hypertensive ones and patients with more than one diseased vessel may be more vulnerable to the harmful effect of particular matters including PM₁₀ and PM_2.5 on development of STEMI.

CONCLUSION

Air pollution is a worldwide pandemic with great potential to cause terrible events especially cardiovascular ones. PM_2.5 and PM₁₀ are amongst ambient air pollutant with a high risk of developing STEMI. Thus, more restrictive legislations should be applied to define a safe level of indoor and outdoor air pollutant production.

American Thoracic Society and Marron Institute Report. Estimated Excess Morbidity and Mortality Caused by Air Pollution above American Thoracic Society-Recommended Standards, 2011-2013

Estimates of the health impacts of air pollution are needed to make informed air quality management decisions at both the national and local levels. Using design values of ambient pollution concentrations from 2011-2013 as a baseline, the American Thoracic Society (ATS) and the Marron Institute of Urban Management estimated excess morbidity and mortality in the United States attributable to exposure to ambient ozone (O3) and fine particulate matter (PM2.5) at levels above the American Thoracic Society-recommended standards. Within the subset of counties with valid design values for each pollutant, 14% had PM2.5 concentrations greater than the ATS recommendation, whereas 91% had O3 concentrations greater than the ATS recommendation. Approximately 9,320 excess deaths (69% from O3; 31% from PM2.5), 21,400 excess morbidities (74% from O3; 26% from PM2.5), and 19,300,000 adversely impacted days (88% from O3; 12% from PM2.5) in the United States each year are attributable to pollution exceeding the ATS-recommended standards. California alone is responsible for 37% of the total estimated health impacts, and the next three states (Pennsylvania, Texas, and Ohio) together contributed to 20% of the total estimates. City-specific health estimates are provided in this report and through an accompanying online tool to help inform air quality management decisions made at the local level. Riverside and Los Angeles, California have the most to gain by attaining the ATS recommendations for O3 and PM2.5. This report will be revised and updated regularly to help cities track their progress.

A county-level estimate of PM2.5 related chronic mortality risk in China based on multi-model exposure data

BACKGROUND

Ambient fine particulate matter (PM_2.5) pollution is currently a serious environmental problem in China, but evidence of health effects with higher resolution and spatial coverage is insufficient.

OBJECTIVE

This study aims to provide a better overall understanding of long-term mortality effects of PM_2.5 pollution in China and a county-level spatial map for estimating PM_2.5 related premature deaths of the entire country.

METHOD

Using four sets of satellite-derived PM_2.5 concentration data and the integrated exposure-response model which has been employed by the Global Burden of Disease (GBD) to estimate global mortality of ambient and household air pollution in 2010, we estimated PM_2.5 related premature mortality for five endpoints across China in 2010.

RESULT

Premature deaths attributed to PM_2.5 nationwide amounted to 1.27million in total, and 119,167, 83,976, 390,266, 670,906 for adult chronic obstructive pulmonary disease, lung cancer, ischemic heart disease, and stroke, respectively; 3995 deaths for acute lower respiratory infections were estimated in children under the age of 5. About half of the premature deaths were from counties with annual average PM_2.5 concentrations above 63.61μg/m³, which cover 16.97% of the Chinese territory. These counties were largely located in the Beijing-Tianjin-Hebei region and the North China Plain. High population density and high pollution areas exhibited the highest health risks attributed to air pollution. On a per capita basis, the highest values were mostly located in heavily polluted industrial regions.

CONCLUSION

PM_2.5-attributable health risk is closely associated with high population density and high levels of pollution in China. Further estimates using long-term historical exposure data and concentration-response (C-R) relationships should be completed in the future to investigate longer-term trends in the effects of PM_2.5.

Short-term association between ambient air pollution and pneumonia in children: A systematic review and meta-analysis of time-series and case-crossover studies

Ambient air pollution has been associated with respiratory diseases in children. However, its effects on pediatric pneumonia have not been meta-analyzed. We conducted a systematic review and meta-analysis of the short-term association between ambient air pollution and hospitalization of children due to pneumonia. We searched the Web of Science and PubMed for indexed publications up to January 2017. Pollutant-specific excess risk percentage (ER%) and confidence intervals (CI) were estimated using random effect models for particulate matter (PM) with diameter ≤ 10 (PM₁₀) and ≤2.5 μm (PM_2.5), sulfur dioxide (SO₂), ozone (O₃), nitrogen dioxide (NO₂), and carbon monoxide (CO). Results were further stratified by subgroups (children under five, emergency visits versus hospital admissions, income level of study location, and exposure period). Seventeen studies were included in the meta-analysis. The ER% per 10 μg/m³ increase of pollutants was 1.5% (95% CI: 0.6%-2.4%) for PM₁₀ and 1.8% (95% CI: 0.5%-3.1%) for PM_2.5. The corresponding values per 10 ppb increment of gaseous pollutants were 2.9% (95% CI: 0.4%-5.3%) for SO₂, 1.7% (95% CI: 0.5%-2.8%) for O₃, and 1.4% (95% CI: 0.4%-2.4%) for NO₂. ER% per 1000 ppb increment of CO was 0.9% (95% CI: 0.0%-1.9%). Associations were not substantially different between subgroups. This meta-analysis shows a positive association between daily levels of ambient air pollution markers and hospitalization of children due to pneumonia. However, lack of studies from low-and middle-income countries limits the quantitative generalizability given that susceptibilities to the adverse effects of air pollution may be different in those populations. The meta-regression in our analysis further demonstrated a strong effect of country income level on heterogeneity.

Air Pollution and Hospitalization for Acute Myocardial Infarction in China

There is growing interest in the association between ambient air pollution and acute myocardial infarction (AMI). The objective of this study was to explore the association in 14 Chinese cities using a time-stratified case-crossover design. We identified 80,787 hospital admissions for AMI between January 1, 2014 and December 31, 2015 from electronic hospitalization summary reports. Conditional logistic regression was used to estimate the percent changes with 95% confidence intervals (CIs) in AMI admissions in relation to an interquartile range increase in ambient air pollutant concentrations. All analyzed air pollutants, with the exception of ozone, were positively associated with daily AMI admissions on lag2 and lag3 days. An interquartile range increase in particulate matter <10 µm in aerodynamic diameter, sulfur dioxide, nitrogen dioxide, and carbon monoxide concentrations on lag2 day was significantly associated with a 0.8% (95% CI 0.1%, 1.6%), 2.0% (95% CI 1.2%, 2.9%), 2.2% (95% CI 1.4%, 3.1%), and 1.1% (95% CI 0.4%, 1.8%) increase in AMI admissions, respectively. We also observed a significant association in relation to ozone on lag4 day (percent change: 1.3%; 95% CI 0.2%, 2.4%). Subgroup analyses indicated no effect modification of risk by age (≥65 years and <65 years) or gender. In conclusion, this is the first multicity study in China, or even in other developing countries, to report the short-term effects of air pollution on AMI morbidity. Our findings contribute to the limited scientific data on the effects of ambient air pollution on AMI in developing countries.

Expressing air pollution-induced health-related externalities in physical terms with the help of DALYs

The unintended impacts of industrial activity on human health and the environment have regularly been assessed and monetised (referred to as "external costs"). External costs are, however, a rather abstract aggregate so that decision makers cannot easily relate them to tangible impacts. At the same time, physical health impact indicators have different units that cannot readily be compared and communicated in a joint way. To support better informed decisions at policy or company level, we propose and demonstrate a way to facilitate communication on non-monetized, that is, physical health indicators quantified in studies. The concept Disability-Adjusted Life Year (DALY) is chosen as metric due to its widespread use. We establish a comprehensive and consistent set of six health endpoints caused by particles and ozone, and derive related up-to-date DALYs. Further we apply the DALY values to a French smart grid demonstration project. Owing to its size, the gains in terms of reduced DALYs are however small. In contrast to external cost assessments, in the frame of which morbidity endpoints usually contribute to around 10-15%, they are found to be insubstantial in the overall DALY score (i.e. below 1%). This is because DALYs only consider time losses weighted by severity while external costs also factor in further welfare effects, i.e. combining resource, disutility and opportunity costs of illness. As a result, methodological limitations, mainly existing for the morbidity-related DALY values, appear to be less of concern. Overall, using the DALYs with and without morbidity impacts is justifiable. Either choice in the communication of health-related physical externalities induces the need to explain the limitations in terms of the treatment of morbidity endpoints (notably their definition and the disability weights used) or their complete disregard.

InMAP: A model for air pollution interventions

Mechanistic air pollution modeling is essential in air quality management, yet the extensive expertise and computational resources required to run most models prevent their use in many situations where their results would be useful. Here, we present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations-the air pollution outcome generally causing the largest monetized health damages-attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical information from the output of a state-of-the-science chemical transport model and a variable spatial resolution computational grid to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. In comparisons run here, InMAP recreates comprehensive model predictions of changes in total PM2.5 concentrations with population-weighted mean fractional bias (MFB) of -17% and population-weighted R2 = 0.90. Although InMAP is not specifically designed to reproduce total observed concentrations, it is able to do so within published air quality model performance criteria for total PM2.5. Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. InMAP can be trained to run for any spatial and temporal domain given the availability of appropriate simulation output from a comprehensive model. The InMAP model source code and input data are freely available online under an open-source license.

COVARIATE-ADAPTIVE CLUSTERING OF EXPOSURES FOR AIR POLLUTION EPIDEMIOLOGY COHORTS

Cohort studies in air pollution epidemiology aim to establish associations between health outcomes and air pollution exposures. Statistical analysis of such associations is complicated by the multivariate nature of the pollutant exposure data as well as the spatial misalignment that arises from the fact that exposure data are collected at regulatory monitoring network locations distinct from cohort locations. We present a novel clustering approach for addressing this challenge. Specifically, we present a method that uses geographic covariate information to cluster multi-pollutant observations and predict cluster membership at cohort locations. Our predictive k-means procedure identifies centers using a mixture model and is followed by multi-class spatial prediction. In simulations, we demonstrate that predictive k-means can reduce misclassification error by over 50% compared to ordinary k-means, with minimal loss in cluster representativeness. The improved prediction accuracy results in large gains of 30% or more in power for detecting effect modification by cluster in a simulated health analysis. In an analysis of the NIEHS Sister Study cohort using predictive k-means, we find that the association between systolic blood pressure (SBP) and long-term fine particulate matter (PM2.5) exposure varies significantly between different clusters of PM2.5 component profiles. Our cluster-based analysis shows that for subjects assigned to a cluster located in the Midwestern U.S., a 10 μg/m3 difference in exposure is associated with 4.37 mmHg (95% CI, 2.38, 6.35) higher SBP.

Long-term trend and spatial pattern of PM2.5 induced premature mortality in China

With rapid economic growth, China has witnessed increasingly frequent and severe haze and smog episodes over the past decade, posing serious health impacts to the Chinese population, especially those in densely populated city clusters. Quantification of the spatial and temporal variation of health impacts attributable to ambient fine particulate matter (PM_2.5) has important implications for China's policies on air pollution control. In this study, we evaluated the spatial distribution of premature deaths in China between 2000 and 2010 attributable to ambient PM_2.5 in accord with the Global Burden of Disease based on a high resolution population density map of China, satellite retrieved PM_2.5 concentrations, and provincial health data. Our results suggest that China's anthropogenic ambient PM_2.5 led to 1,255,400 premature deaths in 2010, 42% higher than the level in 2000. Besides increased PM_2.5 concentration, rapid urbanization has attracted large population migration into the more developed eastern coastal urban areas, intensifying the overall health impact. In addition, our analysis implies that health burdens were exacerbated in some developing inner provinces with high population density (e.g. Henan, Anhui, Sichuan) because of the relocation of more polluting and resource-intensive industries into these regions. In order to avoid such national level environmental inequities, China's regulations on PM_2.5 should not be loosened in inner provinces. Furthermore policies should create incentive mechanisms that can promote transfer of advanced production and emissions control technologies from the coastal regions to the interior regions.

Proposed pathophysiologic framework to explain some excess cardiovascular death associated with ambient air particle pollution: Insights for public health translation

The paper proposes a pathophysiologic framework to explain the well-established epidemiological association between exposure to ambient air particle pollution and premature cardiovascular mortality, and offers insights into public health solutions that extend beyond regulatory environmental protections to actions that can be taken by individuals, public health officials, healthcare professionals, city and regional planners, local and state governmental officials and all those who possess the capacity to improve cardiovascular health within the population. The foundation of the framework rests on the contribution of traditional cardiovascular risk factors acting alone and in concert with long-term exposures to air pollutants to create a conditional susceptibility for clinical vascular events, such as myocardial ischemia and infarction; stroke and lethal ventricular arrhythmias. The conceptual framework focuses on the fact that short-term exposures to ambient air particulate matter (PM) are associated with vascular thrombosis (acute coronary syndrome, stroke, deep venous thrombosis, and pulmonary embolism) and electrical dysfunction (ventricular arrhythmia); and that individuals having prevalent heart disease are at greatest risk. Moreover, exposure is concomitant with changes in autonomic nervous system balance, systemic inflammation, and prothrombotic/anti-thrombotic and profibrinolytic-antifibrinolytic balance. Thus, a comprehensive solution to the problem of premature mortality triggered by air pollutant exposure will require compliance with regulations to control ambient air particle pollution levels, minimize exposures to air pollutants, as well as a concerted effort to decrease the number of people at-risk for serious clinical cardiovascular events triggered by air pollutant exposure by improving the overall state of cardiovascular health in the population. This article is part of a Special Issue entitled Air Pollution, edited by Wenjun Ding, Andrew J. Ghio and Weidong Wu.

Exploring the Uncertainty Associated with Satellite-Based Estimates of Premature Mortality due to Exposure to Fine Particulate Matter

The negative impacts of fine particulate matter (PM_2.5) exposure on human health are a primary motivator for air quality research. However, estimates of the air pollution health burden vary considerably and strongly depend on the datasets and methodology. Satellite observations of aerosol optical depth (AOD) have been widely used to overcome limited coverage from surface monitoring and to assess the global population exposure to PM_2.5 and the associated premature mortality. Here we quantify the uncertainty in determining the burden of disease using this approach, discuss different methods and datasets, and explain sources of discrepancies among values in the literature. For this purpose we primarily use the MODIS satellite observations in concert with the GEOS-Chem chemical transport model. We contrast results in the United States and China for the years 2004-2011. Using the Burnett et al. (2014) integrated exposure response function, we estimate that in the United States, exposure to PM_2.5 accounts for approximately 2% of total deaths compared to 14% in China (using satellite-based exposure), which falls within the range of previous estimates. The difference in estimated mortality burden based solely on a global model vs. that derived from satellite is approximately 14% for the U.S. and 2% for China on a nationwide basis, although regionally the differences can be much greater. This difference is overshadowed by the uncertainty in the methodology for deriving PM_2.5 burden from satellite observations, which we quantify to be on the order of 20% due to uncertainties in the AOD-to-surface-PM_2.5 relationship, 10% due to the satellite observational uncertainty, and 30% or greater uncertainty associated with the application of concentration response functions to estimated exposure.