Particulate air pollution as a predictor of mortality in a prospective study of U.S. adults

Predicting Fine Particulate Matter (PM2.5) in the Greater London Area: An Ensemble Approach using Machine Learning Methods

Estimating air pollution exposure has long been a challenge for environmental health researchers. Technological advances and novel machine learning methods have allowed us to increase the geographic range and accuracy of exposure models, making them a valuable tool in conducting health studies and identifying hotspots of pollution. Here, we have created a prediction model for daily PM2.5 levels in the Greater London area from 1st January 2005 to 31st December 2013 using an ensemble machine learning approach incorporating satellite aerosol optical depth (AOD), land use, and meteorological data. The predictions were made on a 1 km × 1 km scale over 3960 grid cells. The ensemble included predictions from three different machine learners: a random forest (RF), a gradient boosting machine (GBM), and a k-nearest neighbor (KNN) approach. Our ensemble model performed very well, with a ten-fold cross-validated R2 of 0.828. Of the three machine learners, the random forest outperformed the GBM and KNN. Our model was particularly adept at predicting day-to-day changes in PM2.5 levels with an out-of-sample temporal R2 of 0.882. However, its ability to predict spatial variability was weaker, with a R2 of 0.396. We believe this to be due to the smaller spatial variation in pollutant levels in this area.

Particulate Matter and Albuminuria, Glomerular Filtration Rate, and Incident CKD

BACKGROUND AND OBJECTIVES

Exposure to particulate matter (PM) <2.5 μm in aerodynamic diameter (PM2.5) has been linked to detrimental health effects. This study aimed to describe the relationship between long-term PM2.5 exposure and kidney disease, including eGFR, level of albuminuria, and incident CKD.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

The study included 10,997 participants from the Atherosclerosis Risk in Communities cohort who were followed from 1996-1998 through 2016. Monthly mean PM2.5 concentrations (μg/m3) were estimated at geocoded participant addresses using geographic information system-based, spatiotemporal generalized additive mixed models-including geospatial covariates such as land use-and then averaged over the 12-month period preceding participant examination. Covariate-adjusted, cross-sectional associations of PM2.5, baseline eGFR, and urinary albumin-creatinine ratio (UACR) were estimated using linear regression. PM2.5 and incident CKD (defined as follow-up eGFR <60 ml/min per 1.73 m2 with ≥25% eGFR decline relative to baseline, CKD-related hospitalization or death based on International Classification of Diseases 9/10 codes, or development of ESKD) associations were estimated using Cox proportional hazards regression. Modeling was stratified by study site, and stratum-specific estimates were combined using random-effects meta-analyses.

RESULTS

Baseline mean participant age was 63 (±6) years and eGFR was 86 (±16) ml/min per 1.73 m2. There was no significant PM2.5-eGFR association at baseline. Each 1-μg/m3 higher annual average PM2.5 was associated with higher UACR after adjusting for demographics, socioeconomic status, and clinical covariates (percentage difference, 6.6%; 95% confidence interval [95% CI], 2.6% to 10.7%). Each 1-μg/m3 higher annual average PM2.5 was associated with a significantly higher risk of incident CKD (hazard ratio, 1.05; 95% CI, 1.01 to 1.10).

CONCLUSIONS

Exposure to higher annual average PM2.5 concentrations was associated with a higher level of albuminuria and higher risk for incident CKD in a community-based cohort.

PM2.5 exposure induces age-dependent hepatic lipid metabolism disorder in female mice

Particulate matter exposure has been described to elevate the risk of lung and cardiovascular diseases. An increasing number of recent studies have indicated positive correlations between PM_2.5 (the fraction of airborne particles with an aerodynamic diameter less than 2.5 μm) exposure and the risk of liver diseases. However, research on the effects of PM_2.5 exposure on liver fat synthesis, secretion, and clearance mechanisms under normal diet conditions is limited, and whether these effects are age-dependent is largely unknown. Female C57BL/6 mice at different ages (4 weeks (4 w), 4 months (4 m), and 10 months (10 m)) were treated with 3 mg/kg body weight of PM_2.5 every other day for 4 weeks. Subsequently, the ultrastructural changes of liver, the expression of genes involved in oxidative damage and lipid metabolism in the liver were examined. Observation of hepatic ultrastructure showed more and larger lipid droplets in the livers of 4-week-old and 10-month-old mice exposed to PM_2.5. Further analysis showed that PM_2.5 exposure increased the expression of genes related to lipid synthesis, but decreased the expression of genes involved in lipid transport and catabolism in the livers of 10-month-old mice. Our findings suggest that exposure to PM_2.5 disrupts the normal metabolism of liver lipids and induces lipid accumulation in the liver of female mice in an age-dependent manner, with older mice being more susceptible to PM_2.5.

Particulate air pollution from different sources and mortality in 7.5 million adults - The Dutch Environmental Longitudinal Study (DUELS)

BACKGROUND

Long-term exposure to particulate air pollution has been associated with mortality in urban cohort studies. Few studies have investigated the association between emission contributions from different particle sources and mortality in large-scale population registries, including non-urban populations.

OBJECTIVES

The aim of the study was to evaluate the associations between long-term exposure to particulate air pollution from different source categories and non-accidental mortality in the Netherlands based on existing national databases.

METHODS

We used existing Dutch national databases on mortality, individual characteristics, residence history, neighbourhood characteristics and modelled air pollution concentrations from different sources and air pollution components: particulate matter PM10, primary particulate matter PM10 (PPM10), particulate matter PM2.5, primary particulate matter PM2.5 (PPM2.5), elemental carbon (EC), nitrogen dioxide (NO₂) and secondary inorganic aerosol (SIA) in PM10 (SIA10) or in PM2.5 (SIA2.5). We established a cohort of 7.5 million individuals 30 years or older. We followed the cohort for eight years (2008-2015). We applied Cox proportional hazard regression models adjusting for potential individual and area-specific confounders.

RESULTS

We found statistically significant associations between total and primary particulate matter (PM10 and PM2.5), elemental carbon and mortality. Adjustment for nitrogen dioxide did not change the associations. Secondary inorganic aerosol showed less consistent associations. All primary PM sources were associated with mortality, except agricultural emissions and, depending on the statistical model, industrial PM emissions.

CONCLUSIONS

We could not identify one or more specific source categories of particulate air pollution as main determinants of the mortality effects found in this and in a previous study. This suggests that present policy measures should be focussed on the wider spectrum of air pollution sources instead of on specific sources.

Atmospheric particulate matters in an Indian urban area: Health implications from potentially hazardous elements, cytotoxicity, and genotoxicity studies

The nature of the atmospheric particulate matters (PMs) varies depending on their sizes and their origin from different activities in the background environment. These PMs are associated with potentially hazardous elements (PHEs) such as organic compounds (e.g. Polyaromatic Hydrocarbons) that can be harmful to health. The main objective of this work is the identification and investigation of the toxicological aspects of PHEs in PMs during pre-monsoon and post-monsoon season in an urban area of Northeast region (NER) of India. In the course of the study, the 24 -hs average concentrations of PMs were detected to be more than two-times higher than the Indian standard limit (NAAQ, category) which indicates poor air quality in both the seasons around the sampling sites. This study demonstrates that the concentrations of PM-bound PAHs are mutagenic and that the Excess Cancer Risks exceed the USEPA standard limits. PMs cause cytotoxicity and can also induce genotoxicity to human health analyzed by cell culture and gel electrophoresis. This study helps to promote research to evaluate the PMs bound PHEs toxicity in diverse human cell lines and also their relationship with climatic factors as well as quantitative source apportionment for mitigation purposes.

Deregulation and the Assault on Science and the Environment

The quality of the environment is a major determinant of the health and well-being of a population. The role of scientific evidence is central in the network of laws addressing environmental pollution in the United States and has been critical in addressing the myriad sources of environmental pollution and the burden of disease attributable to environmental factors. We address the shift away from reasoned action and science to a reliance on belief and document the efforts to separate regulation from science and to remove science-based regulations and policies intended to protect public health. We outline the general steps for moving from research to policy, show how each has been undermined, offer specific examples, and point to resources that document the enormity of the current efforts to set aside scientific evidence.

A new approach combining a simplified FLEXPART model and a Bayesian-RAT method for forecasting PM10 and PM2.5

In this study, we evaluated atmospheric particulate matter (PM) concentration predictions at a regional scale using a simplified Lagrangian particle dispersion modeling system and the Bayesian and multiplicative ratio correction optimization (Bayesian-RAT) method to improve the mixing ratio forecast of PM₁₀ and PM_2.5. We first examined the forecast performance of the LPD (i.e., the simplified FLEXPART model combined with the Bayesian-RAT method) by comparing the model predictions with the PM concentration observations from 95 observation stations in Xingtai city and its surrounding areas. The first 2 months (i.e., Oct. and Nov. 2017) of the study period represented the typical spin-up time period, and the analysis period was December 2017. The LPD forecast system was much better (correlation coefficient: R=0.64 vs. 0.48 and 0.67 vs. 0.50 for PM₁₀ and PM_2.5, respectively; root mean square error: RMSE = 74.98 vs. 105.96 μg/m³ for PM₁₀ and 54.89 vs. 72.81 μg/m³ for PM_2.5) than the pre-calibration results. We also compared the LPD forecasting model with other models (WRF-Chem and Camx) using data from monitoring stations in Xingtai, China, and the LPD forecasting model had higher accuracy than the other models. In particular, the RMSE scores for hourly PM₁₀ concentrations were reduced by 36.51% and 42.21% compared to WRF-Chem and to Camx, respectively. The PM_2.5 forecast results, as in the case of PM₁₀, showed a better performance when applying the LPD model to the data from the monitoring stations. The RMSE was reduced by 26.44% and 18.47% relative to the WRF-Chem and Camx, respectively. The results confirm that there is much advantage of the LPD forecast system for predicting PM and may be for other pollutants.

PM2.5 Pollution: Health and Economic Effect Assessment Based on a Recursive Dynamic Computable General Equilibrium Model

At present particulate matter (PM_2.5) pollution represents a serious threat to the public health and the national economic system in China. This paper optimizes the whitening coefficient in a grey Markov model by a genetic algorithm, predicts the concentration of fine particulate matter (PM_2.5), and then quantifies the health effects of PM_2.5 pollution by utilizing the predicted concentration, computable general equilibrium (CGE), and a carefully designed exposure-response model. Further, the authors establish a social accounting matrix (SAM), calibrate the parameter values in the CGE model, and construct a recursive dynamic CGE model under closed economy conditions to assess the long-term economic losses incurred by PM_2.5 pollution. Subsequently, an empirical analysis was conducted for the Beijing area: Despite the reduced concentration trend, PM_2.5 pollution continued to cause serious damage to human health and the economic system from 2013 to 2020, as illustrated by various facts, including: (1) the estimated premature deaths and individuals suffering haze pollution-related diseases are 156,588 (95% confidence intervals (CI): 43,335-248,914)) and six million, respectively; and (2) the accumulated labor loss and the medical expenditure negatively impact the regional gross domestic product, with an estimated loss of 3062.63 (95% CI: 1,168.77-4671.13) million RMB. These findings can provide useful information for governmental agencies to formulate relevant environmental policies and for communities to promote prevention and rescue strategies.

Fine Particulate Air Pollution from Electricity Generation in the US: Health Impacts by Race, Income, and Geography

Electricity generation is a large contributor to fine particulate matter (PM_2.5) air pollution. However, the demographic distribution of the resulting exposure is largely unknown. We estimate exposures to and health impacts of PM_2.5 from electricity generation in the US, for each of the seven Regional Transmission Organizations (RTOs), for each US state, by income and by race. We find that average exposures are the highest for blacks, followed by non-Latino whites. Exposures for remaining groups (e.g., Asians, Native Americans, Latinos) are somewhat lower. Disparities by race/ethnicity are observed for each income category, indicating that the racial/ethnic differences hold even after accounting for differences in income. Levels of disparity differ by state and RTO. Exposures are higher for lower-income than for higher-income, but disparities are larger by race than by income. Geographically, we observe large differences between where electricity is generated and where people experience the resulting PM_2.5 health consequences; some states are net exporters of health impacts, other are net importers. For 36 US states, most of the health impacts are attributable to emissions in other states. Most of the total impacts are attributable to coal rather than other fuels.

Exposure levels of air pollution (PM2.5) and associated health risk in Kuwait

It is well established that respiratory and cardiovascular mortality and morbidity rates are associated with poor air quality as measured by high concentrations of fine particulate matter such as PM_2.5 parameters. Since such information is lacking for the State of Kuwait, this study examined the exposure levels of PM_2.5 and the associated health risk as evaluated by five mortality measures embodied in ischemic heart disease, stroke, lung cancer, chronic obstructive pulmonary disease and acute lower respiratory infection as well as two morbidity outcomes related to both cardiovascular and respiratory diseases. The measurement models utilized in this investigation followed the WHO guidelines. Over a span of a four-year period (2014-2017), the annual PM_2.5 concentration levels ranged from 38.0 μg/m³ to 75.2 μg/m³. In general, exposure levels tended to fluctuate throughout the day with the higher levels recorded during rush hours (early morning and early evening), weekends (particularly Saturdays), and summer (i.e., August and September). The highest number of excess cases and attributable proportions of premature mortalities were related to ischemic heart disease and stroke at 352 (95% CI 275-426) and 70.8% (95% CI 39.7-85.2), respectively. In general, respiratory diseases showed a higher number of excess cases and attributable proportions than cardiovascular diseases. Relative to other findings on the global stage, the results emanating from Kuwait are emerging on the higher side. The study outcomes suggest that control strategies are in dire need to bend the pollution levels in Kuwait.

Investigating the plausibility of a PMF source apportionment solution derived using a small dataset: A case study from a receptor in a rural site in Apulia - South East Italy

Results of a methodological study on the use of Positive Matrix Factorization (PMF) with smaller datasets are being reported in this work. This study is based on 29 PM₁₀ and 33 PM_2.5 samples from a receptor in a rural setup in Apulia (Southern Italy). Running PMF on the two size fractions separately resulted in the model not functioning correctly. We therefore, augmented the size of the dataset by aggregating the PM₁₀ and PM_2.5 data. The 5-factor solution obtained for the aggregated data was fairly rotationally stable, and was further refined by the rotational tools included in USEPA PMF version 5. These refinements include the imposition of constraints on the solution, based on our knowledge of the chemical composition of the aerosol sources affecting the receptor. Additionally, the uncertainties associated with this solution were fully characterised using the improved error estimation techniques in this version of PMF. Five factors in all, were isolated by PMF: ammonium sulfate, marine aerosol, mixed carbonaceous aerosol, crustal/Saharan dust and total traffic. The results obtained by PMF were further tested inter alia, by comparing them to those obtained by two other receptor modelling techniques: Constrained Weighted Non-negative Matrix Factorization (CW - NMF) and Chemical Mass Balance (CMB). The results of these tests suggest that the solution obtained by PMF, is valid, indicating that for this particular airshed PMF managed to extract most of the information about the aerosol sources affecting the receptor - even from a dataset with a limited number of samples.

Variation of atmospheric emissions within the road transport sector in Italy between 1990 and 2016

The concentration of road transport emissions impacts on air quality, is responsible for climate change and increases the average temperatures. The aim of this study was to analyze the trends of atmospheric emissions within the road transport sector in Italy between 1990 and 2016. A principal component analysis (PCA) was carried out to investigate the pollutants that showed similar trends over time. The Kendall's rank correlation coefficient was studied to establish the statistically dependent variables. Finally, a joinpoint regression analysis was performed to evaluate the time-trends of pollutants' emissions. The Pearson's correlation coefficients were positive for all pollutants except for CO₂, that demonstrated an inverse relationship with CH₄ (-0.07), NOx (-0.089) and NMVOC (-0.128); NO₂ demonstrated inverse relationship with all other pollutants. According to the main component analysis, most pollutants were assimilable in their behavior, except for NO₂, CO2 and N₂O. The joinpoint analysis describes a general decrease of emissions over time with exception of N₂O, NO₂ and CO₂, that showed different trends. This study shows that road traffic-related emissions in Italy, between 1990 and 2016, recorded significant reductions for most of the recorded pollutants. However, CO₂ and N₂O maintained a stable trend while NO₂ showed an increasing trend.

Diesel Exhaust Particle Exposure Compromises Alveolar Macrophage Mitochondrial Bioenergetics

Diesel exhaust particles (DEPs) are known pathogenic pollutants that constitute a significant quantity of air pollution. Given the ubiquitous presence of macrophages throughout the body, including the lungs, as well as their critical role in tissue and organismal metabolic function, we sought to determine the effect of DEP exposure on macrophage mitochondrial function. Following daily DEP exposure in mice, pulmonary macrophages were isolated for mitochondrial analyses, revealing reduced respiration rates and dramatically elevated H₂O₂ levels. Serum ceramides and inflammatory cytokines were increased. To determine the degree to which the changes in mitochondrial function in macrophages were not dependent on any cross-cell communication, primary pulmonary murine macrophages were used to replicate the DEP exposure in a cell culture model. We observed similar changes as seen in pulmonary macrophages, namely diminished mitochondrial respiration, but increased H₂O₂ production. Interestingly, when treated with myriocin to inhibit ceramide biosynthesis, these DEP-induced mitochondrial changes were mitigated. Altogether, these data suggest that DEP exposure may compromise macrophage mitochondrial and whole-body function via pathologic alterations in macrophage ceramide metabolism.

Novel evidence for a greater burden of ambient air pollution on cardiovascular disease

Ambient and household air pollution is a major health problem worldwide, contributing annually to approximately seven million of all-cause avoidable deaths, shorter life expectancy, and significant direct and indirect costs for the community. Air pollution is a complex mixture of gaseous and particulate materials that vary depending on their source and physicochemical features. Each material has detrimental effects on human health, but a number of experimental and clinical studies have shown a strong impact for fine particulate matter (PM_2.5). In particular, there is more and more evidence that PM_2.5 exerts adverse effects particularly on the cardiovascular system, contributing substantially (mainly through mechanisms of atherosclerosis, thrombosis and inflammation) to coronary artery and cerebrovascular disease, but also to heart failure, hypertension, diabetes and cardiac arrhythmias. In this review, we summarize knowledge on the mechanisms and magnitude of the cardiovascular adverse effects of short-and long-term exposure to ambient air pollution, particularly for the PM_2.5 size fraction. We also emphasize that very recent data indicate that the global mortality and morbidity burden of cardiovascular disease associated with this air pollutant is dramatically greater than what has been thought up to now.

Cardiopulmonary Health Effects of Airborne Particulate Matter: Correlating Animal Toxicology to Human Epidemiology

The effects of particulate matter (PM) on cardiopulmonary health have been studied extensively over the past three decades. Particulate matter is the primary criteria air pollutant most commonly associated with adverse health effects on the cardiovascular and respiratory systems. The mechanisms by which PM exerts its effects are thought to be due to a variety of factors which may include, but are not limited to, concentration, duration of exposure, and age of exposed persons. Adverse effects of PM are strongly driven by their physicochemical properties, sites of deposition, and interactions with cells of the respiratory and cardiovascular systems. The direct translocation of particles, as well as neural and local inflammatory events, are primary drivers for the observed cardiopulmonary health effects. In this review, toxicological studies in animals, and clinical and epidemiological studies in humans are examined to demonstrate the importance of using all three approaches to better define potential mechanisms driving health outcomes upon exposure to airborne PM of diverse physicochemical compositions.

Characteristics of cohort studies of long-term exposure to PM2.5: a systematic review

This study systematically reviewed all the cohort studies investigating the relationship between long-term exposure to PM_2.5 and any health outcome until February 2018. We searched ISI Web of Knowledge, Pubmed, and Scopus databases for peer-reviewed journal research articles published in English. We only extracted the results of the single-pollutant main analysis of each study, excluding the effect modifications and sensitivity analyses. Out of the initial 9523 articles, 203 articles were ultimately included for analysis. Based on the different characteristics of studies such as study design, outcome, exposure assessment method, and statistical model, we calculated the number and relative frequency of analyses with statistically significant and insignificant results. Most of the studies were prospective (84.8%), assessed both genders (66.5%), and focused on a specific age range (86.8%). Most of the articles (78.1%) had used modeling techniques for exposure assessment of cohorts' participants. Among the total of 317 health outcomes, the most investigated outcomes include mortality due to cardiovascular disease (6.19%), all causes (5.48%), lung cancer (4.00%), ischemic heart disease (3.50%), and non-accidental causes (3.50%). The percentage of analyses with statistically significant results were higher among studies that used prospective design, mortality as the outcome, fixed stations as exposure assessment method, hazard ratio as risk measure, and no covariate adjustment. We can somehow conclude that the choice of right characteristics for cohort studies can make a difference in their results.

Short-Term Elevation of Fine Particulate Matter Air Pollution and Acute Lower Respiratory Infection

RATIONALE

Nearly 60% of U.S. children live in counties with particulate matter less than or equal to 2.5 μm in aerodynamic diameter (PM_2.5) concentrations above air quality standards. Understanding the relationship between ambient air pollution exposure and health outcomes informs actions to reduce exposure and disease risk.

OBJECTIVES

To evaluate the association between ambient PM_2.5 levels and healthcare encounters for acute lower respiratory infection (ALRI).

METHODS

Using an observational case-crossover design, subjects (n = 146,397) were studied if they had an ALRI diagnosis and resided on Utah's Wasatch Front. PM_2.5 air pollution concentrations were measured using community-based air quality monitors between 1999 and 2016. Odds ratios for ALRI healthcare encounters were calculated after stratification by ages 0-2, 3-17, and 18 or more years.

MEASUREMENTS AND MAIN RESULTS

Approximately 77% (n = 112,467) of subjects were 0-2 years of age. The odds of ALRI encounter for these young children increased within 1 week of elevated PM_2.5 and peaked after 3 weeks with a cumulative 28-day odds ratio of 1.15 per +10 μg/m³ (95% confidence interval, 1.12-1.19). ALRI encounters with diagnosed and laboratory-confirmed respiratory syncytial virus and influenza increased following elevated ambient PM_2.5 levels. Similar elevated odds for ALRI were also observed for older children, although the number of events and precision of estimates were much lower.

CONCLUSIONS

In this large sample of urban/suburban patients, short-term exposure to elevated PM_2.5 air pollution was associated with greater healthcare use for ALRI in young children, older children, and adults. Further exploration is needed of causal interactions between PM_2.5 and ALRI.

A Review of Early Injection Strategy in Premixed Combustion Engines

Due to the increasing awareness of environmental protection, limitations on exhaust emissions of diesel engines have become increasingly stringent. This challenges diesel engine manufacturers to find a new balance between engine performance and emissions. Advanced combustion modes for diesel engines, such as homogeneous charge compression ignition (HCCI) and premixed charge compression ignition (PCCI), which can simultaneously reduce exhaust emissions and substantially improve thermal efficiency, have drawn increasing attention. In order to allow enough time to prepare the homogeneous mixture, the early injection strategy has been utilized widely in HCCI and PCCI diesel engines. This paper is aimed at providing a comprehensive review of the effects of early injection parameters on the performance and emissions of HCCI and PCCI engines fueled by both diesel and alternative fuels. Various early injection parameters, including injection pressure, injection timing, and injection angle, are discussed. In addition, the effect of the blending ratio of alternative fuels is also summarized. Every change in parameters has its own advantages and disadvantages, which are explained in detail in order to help researchers choose the best early injection parameters for HCCI and PCCI engines.

The effects of particle-induced oxidative damage from exposure to airborne fine particulate matter components in the vicinity of landfill sites on Hong Kong

The physical, chemical and bioreactivity characteristics of fine particulate matter (PM_2.5) collected near (<1 km) two landfill sites and downwind urban sites were investigated. The PM_2.5 concentrations were significantly higher in winter than summer. Diurnal variations of PM_2.5 were recorded at both landfill sites. Soot aggregate particles were identified near the landfill sites, which indicated that combustion pollution due to landfill activities was a significant source. High correlation coefficients (r) implied several inorganic elements and water-soluble inorganic ions (vanadium (V), copper (Cu), chloride (Cl^-), nitrate (NO₃^-), sodium (Na) and potassium (K)) were positively associated with wind flow from the landfill sites. Nevertheless, no significant correlations were also identified between these components against DNA damage. Significant associations were observed between DNA damage and some heavy metals such as cadmium (Cd) and lead (Pb), and total Polycyclic Aromatic Hydrocarbons (PAHs) during the summer. The insignificant associations of DNA damage under increased wind frequency from landfills suggested that the PM_2.5 loading from sources such as regional sources was possibly an important contributing factor for DNA damage. This outcome warrants the further development of effective and source-specific landfill management regulations for particulate matter production control to the city.

Long-term exposure to PM2.5 and ozone and hospital admissions of Medicare participants in the Southeast USA

We examined the association between average annual fine particulate matter (PM_2.5) and ozone and first hospital admissions of Medicare participants for stroke, chronic obstructive pulmonary disease (COPD), pneumonia, myocardial infarction (MI), lung cancer, and heart failure (HF). Annual average PM_2.5 and ozone levels were estimated using high-resolution spatio-temporal models. We fit a marginal structural Cox proportional hazards model, using stabilized inverse probability weights (IPWs) to account for the competing risk of death and confounding. Analyses were then repeated after restricting to exposure levels below the current U.S. standards. The results showed that PM_2.5 was significantly associated with an increased hazard of admissions for all studied outcomes; the highest observed being a 6.1% (95% CI: 5.9%-6.2%) increase in the hazard of admissions with pneumonia for each μg/m³ increase in particulate levels. Ozone was also significantly associated with an increase in the risk of first hospital admissions of all outcomes. The hazard of pneumonia increased by 3.0% (95% CI: 2.9%-3.1%) for each ppb increase in the ozone level. Our results reveal a need to regulate long-term ozone exposure, and that associations persist below current PM_2.5 standards.

Long-term exposure to PM2.5 and ozone and hospital admissions of Medicare participants in the Southeast USA

We examined the association between average annual fine particulate matter (PM_2.5) and ozone and first hospital admissions of Medicare participants for stroke, chronic obstructive pulmonary disease (COPD), pneumonia, myocardial infarction (MI), lung cancer, and heart failure (HF). Annual average PM_2.5 and ozone levels were estimated using high-resolution spatio-temporal models. We fit a marginal structural Cox proportional hazards model, using stabilized inverse probability weights (IPWs) to account for the competing risk of death and confounding. Analyses were then repeated after restricting to exposure levels below the current U.S. standards. The results showed that PM_2.5 was significantly associated with an increased hazard of admissions for all studied outcomes; the highest observed being a 6.1% (95% CI: 5.9%-6.2%) increase in the hazard of admissions with pneumonia for each μg/m³ increase in particulate levels. Ozone was also significantly associated with an increase in the risk of first hospital admissions of all outcomes. The hazard of pneumonia increased by 3.0% (95% CI: 2.9%-3.1%) for each ppb increase in the ozone level. Our results reveal a need to regulate long-term ozone exposure, and that associations persist below current PM_2.5 standards.

Relationship between fine particulate air pollution exposure and human adult life expectancy in Taiwan

Among the air pollutants, particulate matter with an aerodynamic diameter less than 2.5 um (PM_2.5) is of particular interest to environmental medicine as epidemiologic studies consistently reported that long-term exposure to PM_2.5 is associated with increased risk of premature death in adults. Life expectancy is a well-documented and important measure of overall public health policy. However, few investigators examined the relationship between PM_2.5 levels and adult life expectancy. In this Taiwan-wide study, county-level annual mean PM_2.5 concentrations data were collected concomitantly with potential confounding variables including demographic and socioeconomic status, as well as smoking prevalence. Subsequently, these PM_2.5 data were analyzed with respect to county-level adult life expectancy data for the period 2010 to 2017. Linear regression was used to determine the relationship between PM_2.5 and life expectancy in adults. Residents residing in the counties characterized as containing higher levels of PM_2.5 exhibited significantly reduced life expectancy after controlling for potential confounders. For each 10 ug/m³ increase in PM_2.5 there was an estimated mean decrease in life expectancy in adults of 0.3 years. The results of this study shed light on the relationship between fine particulate air pollution exposure and risk to human health in Taiwan.

Health Effects of Energy Intensive Sectors and the Potential Health Co-Benefits of a Low Carbon Industrial Transition in China

Background: The issues of environmental pollution and its effects on health have become increasingly serious in China. Energy intensive sectors are not only the main energy consumers, but also the main sources of air pollution. Analyzing the health effects of energy intensive sectors and the potential health co-benefits of a low carbon industrial transition is of great importance for promoting China's air pollution control. Methods: This study used the exposure-response (ER) relationship model and inhalation factor methods to quantitatively analyze the health effects of air pollution and forecast the potential health co-benefits in the power and steel sectors. Results: The results showed that in 2016 SO2 and PM2.5 emissions caused about 850,000 premature deaths, and 10 million cases of respiratory diseases and chest discomfort, resulting in health-related economic losses of 1.2 trillion Yuan, accounting for 1.6% of the GDP. Meanwhile, demand control in consumption could significantly reduce SO2 emissions in the power and steel sectors, thus offering significant health co-benefits. However, there was still some uncertainty regarding the reduction of PM2.5 emissions in the steel sector. Conclusions: There is a need to take advantage of the health co-benefits of emission reduction in energy intensive sectors and to adopt flexible means to stimulate their green transformation.

Change in PM2.5 exposure and mortality among Medicare recipients: Combining a semi-randomized approach and inverse probability weights in a low exposure population

The association between PM_2.5 and mortality is well established; however, confounding by unmeasured factors is always an issue. In addition, prior studies do not tell us what the effect of a sudden change in exposure on mortality is. We consider the sub-population of Medicare enrollees who moved residence from one ZIP Code to another from 2000 to 2012. Because the choice of new ZIP Code is unlikely to be related with any confounders, restricting to the population of movers allows us to have a study design that incorporates randomization of exposure. Over 10 million Medicare participants moved. We calculated change in exposure by subtracting the annual exposure at original ZIP Code from exposure at the new ZIP Code using a validated model. We used Cox proportional hazards models stratified on original ZIP Code with inverse probability weights (IPW) to control for individual and ecological confounders at the new ZIP Code. The distribution of covariates appeared to be randomized by change in exposure at the new locations as standardized differences were mostly near zero. Randomization of measured covariates suggests unmeasured covariates may be randomized also. Using IPW, per 10 µg/m³ increase in PM_2.5, the hazard ratio was 1.21 (95% confidence interval [CI] = 1.20, 1.22] among whites and 1.12 (95% CI = 1.08, 1.15) among blacks. Hazard ratios increased for whites and decreased for blacks when restricting to exposure levels below the current standard of 12 µg/m³. This study provides evidence of likely causal effects at concentrations below current limits of PM_2.5.

Air Pollution and Estimated Health Costs Related to Road Transportations of Goods in Italy: A First Healthcare Burden Assessment

Background: The Italian Society of Environmental Medicine has performed a preliminary assessment of the health impact attributable to road freight traffic in Italy. Methods: We estimated fine particulate matter (PM10, PM2.5) and nitrogen oxides (NOx) generated by road transportation of goods in Italy considering the number of trucks, the emission factors and the average annual distance covered in the year 2016. Simulations on data concerning Years of Life Lost (YLL) attributable to PM2.5 (593,700) and nitrogen oxides NO2 (200,700) provided by the European Environmental Agency (EEA) were used as a proxy of healthcare burden. We set three different healthcare burden scenarios, varying from 1/5 to 1/10 of the proportion of the overall particulate matter attributable to road freight traffic in Italy (about 7% on a total of 2262 tons/year). Results: Road freight traffic in Italy produced about 189 tons of PM10, 147 tons of PM2.5 and 4125 tons of NOx in year 2016, resulting in annual healthcare costs varying from 400 million up to 1.2 billion EUR per year. Conclusion: Road freight traffic has a relevant impact on air pollution and healthcare costs, especially if considered over a 10-year period. Any solution able to significantly reduce the road transportation of goods could decrease avoidable mortality due to air pollution and related costs.

mHealth: Indoor Environmental Quality Measuring System for Enhanced Health and Well-Being Based on Internet of Things

Mobile health research field aims to provide access to healthcare anytime and anywhere through mobile computing technologies while using a cost-effective approach. Mobile health is closely related to ambient assisted living as both research fields address independence in elderly adults. Aging has become a relevant challenge, as it is anticipated that 20% of world population will be aged 60 years and older in 2050. Most people spend more than 90% of their time indoors, therefore the indoor environmental quality has a relevant impact on occupant’s health and well-being. We intended to provide real-time indoor quality monitoring for enhanced living environments and occupational health. This paper presents the AirPlus real-time indoor environmental quality monitoring system, which incorporates several advantages when compared to other systems, such as scalability, flexibility, modularity, easy installation, and configuration, as well as mobile computing software for data consulting and notifications. The results that were obtained are promising and present a significant contribution to the monitoring solutions available in the literature. AirPlus provides a rich dataset to plan interventions for enhanced indoor quality, but also to support clinical diagnostics and correlate occupant’s health problems with their living environment conditions.

Long-term exposure to atmospheric metals assessed by mosses and mortality in France

BACKGROUND

Long-term exposure to air pollution affects health, but little is known about exposure to atmospheric metals. Estimating exposure to atmospheric metals across large spatial areas remains challenging. Metal concentrations in mosses could constitute a useful proxy. Here, we linked moss biomonitoring and epidemiological data to investigate the associations between long-term exposure to metals and mortality.

METHODS

We modelled and mapped 13 atmospheric metals from a 20-year national moss biomonitoring program to derive exposure estimates across France. In the population-based Gazel cohort, we included 11,382 participants from low to intermediate population density areas and assigned modelled metals to their residential addresses. We distinguished between airborne metals that are primarily of natural origin and those primarily of anthropogenic origin. Associations were estimated between exposure to metals and mortality (natural-cause, cardiovascular and respiratory), using Cox models, with confounder adjustment at individual level.

FINDINGS

Between 1996 and 2017, there were 1313 deaths in the cohort (including 181 cardiovascular and 33 respiratory). Exposure to the anthropogenic metals was associated with an increased risk of natural-cause mortality (hazard ratio of 1.16 [1.08-1.24] per interquartile range of exposure), while metals from natural sources were not.

INTERPRETATION

Some atmospheric anthropogenic metals may be associated with excess mortality - even in areas with relatively low levels of exposure to air pollution. Consistent with the previous literature, our findings support the use of moss biomonitoring as a tool to assess health effects of air pollution exposure at individual level.

South Asian Health: Inflammation, Infection, Exposure, and the Human Microbiome

This paper presents the results of the literature review conducted for the working group topic on inflammation, infection, exposure, and the human microbiome. Infection and chronic inflammation can elevate risk for cardiovascular disease and cancer. Environmental exposures common among South Asian (SA) subgroups, such as arsenic exposure among Bangladeshis and particulate matter air pollution among taxi drivers, also pose risks. This review explores the effects of exposure to arsenic and particulate matter, as well as other infections common among SAs, including human papillomavirus (HPV) and hepatitis B/C infection. Emerging research on the human microbiome, and the effect of microbiome changes on obesity and diabetes risk among SAs are also explored.

Air pollution as cause of mental disease: Appraisal of the evidence

A causal association of air pollution with mental diseases is an intriguing possibility raised in a Short Report just published in PLOS Biology. Despite analyses involving large data sets, the available evidence has substantial shortcomings, and a long series of potential biases may invalidate the observed associations. Only bipolar disorder shows consistent results, with similar effects across United States and Denmark data sets, but the effect has modest magnitude, appropriate temporality is not fully secured, and biological gradient, plausibility, coherence, and analogy offer weak support. The signal seems to persist in some robustness analyses, but more analyses by multiple investigators, including contrarians, are necessary. Broader public sharing of data sets would also enhance transparency.

Association of Long-Term Exposure to Fine Particulate Matter and Cardio-Metabolic Diseases in Low- and Middle-Income Countries: A Systematic Review

: Background: Numerous epidemiological studies indicated high levels of particulate matter less than2.5 μm diameter (PM2.5) as a major cardiovascular risk factor. Most of the studies have been conducted in high-income countries (HICs), where average levels of PM2.5 are far less compared to low- and middle- income countries (LMICs), and their socio-economic profile, disease burden, and PM speciation/composition are very different. We systematically reviewed the association of long-term exposure to PM2.5 and cardio-metabolic diseases (CMDs) in LMICs.

METHODS

Multiple databases were searched for English articles with date limits until March 2018. We included studies investigating the association of long-term exposure to PM2.5 (defined as an annual average/average measure for 3 more days of PM2.5 exposure) and CMDs, such as hospital admissions, prevalence, and deaths due to CMDs, conducted in LMICs as defined by World Bank. We excluded studies which employed exposure proxy measures, studies among specific occupational groups, and specific episodes of air pollution.

RESULTS

A total of 5567 unique articles were identified, of which only 17 articles were included for final review, and these studies were from Brazil, Bulgaria, China, India, and Mexico. Outcome assessed were hypertension, type 2 diabetes mellitus and insulin resistance, and cardiovascular disease (CVD)-related emergency room visits/admissions, death, and mortality. Largely a positive association between exposure to PM2.5 and CMDs was found, and CVD mortality with effect estimates ranging from 0.24% to 6.11% increased per 10 μg/m3 in PM2.5. CVD-related hospitalizations and emergency room visits increased by 0.3% to 19.6%. Risk factors like hypertension had an odds ratio of 1.14, and type 2 diabetes mellitus had an odds ratio ranging from 1.14-1.32. Diversity of exposure assessment and health outcomes limited the ability to perform a meta-analysis.

CONCLUSION

Limited evidence on the association of long-term exposure to PM2.5 and CMDs in the LMICs context warrants cohort studies to establish the association.

Human albumin augmented airway inflammation induced by PM2.5 in NC/Nga mice

The synergic allergic inflammatory effects of particulate matter (PM) 2.5 and human albumin were investigated in NC/Nga mice, which are hypersensitive to mite allergens. PM2.5 or PM2.5 plus human albumin with aluminum oxide was injected twice intraperitoneally for sensitization. After 7 days, PM2.5 or PM2.5 plus human albumin was administered five times intranasally to mice for further sensitization. Subsequently, PM2.5 was administered as a challenge on the 11th day. On the 12th day, mice were examined for airway hyperresponsiveness (AHR), bronchoalveolar lavage fluid (BALF) cell count, mRNA expression of Th₁ , Th₂ cytokines, chemokines, and mucus proteins (MUC5AC and MUC5B) in the lung tissue and histopathology. Although PM2.5 or human albumin alone did not induce allergic airway inflammation, simultaneous inoculation of PM2.5 and human albumin-induced airway inflammation showing increase in AHR, total BALF cell numbers, mRNA levels of IL-13, eotaxin 1, eotaxin 2, and MUC5AC, and anti-IG against human serum albumin. Inflammation was observed around the bronchus in PM2.5 plus human albumin-induced lungs. These results demonstrate that PM2.5 can induce allergic airway inflammation through the synergistic action with human albumin in NC/Nga mice.

Vertical monitoring of traffic-related air pollution (TRAP) in urban street canyons of Hong Kong

Rapid urbanization has significantly increased air pollution especially in urban regions with high traffic volumes. Existing methods for estimating traffic-related air pollution (TRAP) and TRAP-related health impacts are based on two-dimensional modelling. This paper describes a point-based methodology to monitor vertical pollutant concentrations in typical street canyons of Hong Kong. It explains the conceptual design, monitoring strategy and selection criteria for a limited number of receptor locations in street canyons to undertake field measurements for both outdoor exposure and indoor infiltration. It also expounds on the limitations and complications associated with field instrumentation and retention of participating home units. The empirical results were applied on the building infiltration efficiencies assessment. It is concluded that the cost-effective field methodology developed in this paper expects to strike a balance between exposure error and limited data locations. These findings will have important implications in future monitoring design of vertical TRAP exposure to support health studies.

Global Effect Factors for Exposure to Fine Particulate Matter

We evaluate fine particulate matter (PM2.5) exposure-response models to propose a consistent set of global effect factors for product and policy assessments across spatial scales and across urban and rural environments. Relationships among exposure concentrations and PM2.5-attributable health effects largely depend on location, population density, and mortality rates. Existing effect factors build mostly on an essentially linear exposure-response function with coefficients from the American Cancer Society study. In contrast, the Global Burden of Disease analysis offers a nonlinear integrated exposure-response (IER) model with coefficients derived from numerous epidemiological studies covering a wide range of exposure concentrations. We explore the IER, additionally provide a simplified regression as a function of PM2.5 level, mortality rates, and severity, and compare results with effect factors derived from the recently published global exposure mortality model (GEMM). Uncertainty in effect factors is dominated by the exposure-response shape, background mortality, and geographic variability. Our central IER-based effect factor estimates for different regions do not differ substantially from previous estimates. However, IER estimates exhibit significant variability between locations as well as between urban and rural environments, driven primarily by variability in PM2.5 concentrations and mortality rates. Using the IER as the basis for effect factors presents a consistent picture of global PM2.5-related effects for use in product and policy assessment frameworks.

Health Effects of Indoor Air Pollution

Exposure to indoor-generated air pollution causes a large number of deaths and cases of disease. These effects are found, largely, in developing countries where people, especially women and young children, are exposed to high concentrations of smoke produced by biomass burning for cooking. Approximately 3 million deaths occur each year. In developed countries, the problem is much less acute: accidental exposure to high concentrations of carbon monoxide is the main cause of death. It should be remembered, however, that much of people's exposure to pollutants generated outdoors occurs in the indoor environment. Indoor exposure to particulate matter has the same effects as outdoor exposure: the cardiovascular system is most affected, with deaths being due to ischaemic heart disease and stroke. Exposure to particulate matter may also contribute to the development of chronic obstructive pulmonary disease (COPD). Exposure to high concentrations of nitrogen dioxide, although perhaps not having a great effect on measures of lung function, may contribute to the development of emphysema and reduce the resistance of the body to bacterial and viral infections. Lung cancer, due to exposure to carcinogens in wood smoke, also occurs. Efforts to reduce levels of indoor air pollution in developing countries, for example by providing flued cooking stoves, have been shown to reduce the prevalence of disease.

Value Assessment of Health Losses Caused by PM2.5 in Changsha City, China

With the advancement of urbanization, the harm caused to human health by PM2.5 pollution has been receiving increasing attention worldwide. In order to increase public awareness and understanding of the damage caused by PM2.5 in the air and gain the attention of relevant management departments, Changsha City is used as the research object, and the environmental quality data and public health data of Changsha City from 2013 to 2017 are used. All-cause death, respiratory death, cardiovascular death, chronic bronchitis, and asthma were selected as the endpoints of PM2.5 pollution health effects, according to an exposure-response coefficient, Poisson regression model, and health-impact-assessment-related methods (the Human Capital Approach, the Willingness to Pay Approach, and the Cost of Illness Approach), assessing the health loss and economic loss associated with PM2.5. The results show that the pollution of PM2.5 in Changsha City is serious, which has resulted in extensive health hazards and economic losses to local residents. From 2013 to 2017, when annual average PM2.5 concentrations fell to 10 μg/m3, the total annual losses from the five health-effect endpoints were $2788.41 million, $2123.18 million, $1657.29 million, $1402.90 million, and $1419.92 million, respectively. The proportion of Gross Domestic Product (GDP) in the current year was 2.69%, 1.87%, 1.34%, 1.04% and 0.93%, respectively. Furthermore, when the concentration of PM2.5 in Changsha City drops to the safety threshold of 10 μg/m3, the number of affected populations and health economic losses can far exceed the situation when it falls to 35 μg/m3, as stipulated by the national secondary standard. From 2013 to 2017, the total loss under the former situation was 1.48 times, 1.54 times, 1.86 times, 2.25 times, and 2.33 times that of the latter, respectively. Among them, all-cause death and cardiovascular death are the main sources of health loss. Taking 2017 as an example, when the annual average concentration dropped to 10 μg/m3, the health loss caused by deaths from all-cause death and cardiovascular disease was 49.16% of the total loss and 35.73%, respectively. Additionally, deaths as a result of respiratory disease, asthma, and chronic bronchitis contributed to 7.31%, 7.29%, and 0.51% of the total loss, respectively. The research results can provide a reference for the formulation of air pollution control policies based on health effects, which is of great significance for controlling air pollution and protecting people's health.

Long-Term PM10 Exposure and Cause-Specific Mortality in the Latium Region (Italy): A Difference-in-Differences Approach

BACKGROUND

The link between particulate matter (PM) exposure and adverse health outcomes has been widely evaluated using large cohort studies. However, the possibility of residual confounding and lack of information about the health effects of PM in rural and suburban areas are unsolved issues.

OBJECTIVE

Our aim was to estimate the effect of annual PM≤10µg (PM₁₀) exposure on cause-specific mortality in the Latium region (central Italy, of which Rome is the main city) during 2006-2012 using a difference-in-differences approach.

METHODS

We estimated daily PM₁₀ concentrations for each 1 km² of the region from 2006 to 2012 by use of satellite data, land-use predictors, and meteorological parameters. For each of the 378 regional municipalities and each year, we averaged daily PM₁₀ values to obtain annual mean PM₁₀ exposures. We applied a variant of the difference-in-differences approach to estimate the association between PM₁₀ and cause-specific mortality by focusing on within-municipality fluctuations of mortality rates and annual PM exposures around municipality means, therefore controlling by design for confounding from all spatial and temporal potential confounders. Analyses were also stratified by population size of the municipalities to obtain effect estimates in rural and suburban areas of the region.

RESULTS

In the period 2006-2012, we observed deaths due to three causes: 347,699 nonaccidental; 92,787 cardiovascular; and 16,509 respiratory causes. The annual average (standard deviation, SD) PM₁₀ concentration was 21.9 (±4.9) µg/km³ in Latium. For each 1-µg/m³ increase in annual PM₁₀ we estimated increases of 0.8% (95% confidence intervals (CIs): 0.2%, 1.3%), 0.9% (0.0%, 1.8%), and 1.4% (-0.4%, 3.3%) in nonaccidental, cardiovascular, and respiratory mortality, respectively. Similar results were found when we excluded the metropolitan area of Rome from the analysis. Higher effects were estimated in the smaller municipalities, e.g., those with population < 5,000 inhabitants.

CONCLUSION

Our study suggests a significant association of annual PM₁₀ exposure with nonaccidental and cardiorespiratory mortality in the Latium region, even outside Rome and in suburban and rural areas. https://doi.org/10.1289/EHP3759.

Time series analysis of ambient air pollution effects on dynamic stroke mortality

This study aims to examine the correlations between air pollution and dynamic stroke mortality, which is defined as the daily real-time number of deaths from stroke. Death data were obtained from daily medical records of 7230 incidents from the Center for Disease Control and Prevention in the Longquanyi District of China from 2016 to 2017. Air pollution data were obtained from environmental monitoring stations in the Longquanyi District. Time series analysis using generalized additive Poisson regression models was applied, and single-pollutant and two-pollutant adjusted models were utilized. Furthermore, categories based on gender, age, and meteorological factors were considered in the analysis. The results indicated that PM2.5, PM10, O₃ , and CO had significant effects on dynamic stroke mortality, which were stronger for older people and during the cold season. This study helps hospital managers, patients, and governments seeking to prevent and control the effects of air pollution on the risks of stroke.

All-cause mortality risk associated with long-term exposure to ambient PM2·5 in China: a cohort study

BACKGROUND

Evidence from cohort studies in North America and Europe indicates that long-term exposure to fine particulate matter (PM_2·5) is associated with an increased mortality risk. However, this association has rarely been quantified at higher ambient concentrations. We estimated the hazard ratio (HR) for all-cause mortality from long-term exposure to PM_2·5 in a well established Chinese cohort of older adults.

METHODS

The Chinese Longitudinal Healthy Longevity Survey (CLHLS) is a prospective cohort study of men and women aged 65 years and older enrolled in 2008 and followed up through 2014 for mortality events. We studied individuals for whom residential locations were available in 2008 for linkage to 1 km grids of PM_2·5 concentrations, derived from satellite remote sensing. Cox proportional hazards models were used to estimate the effect of long-term exposure to PM_2·5 on all-cause mortality, controlling for age, sex, smoking status, drinking status, physical activity, body-mass index, household income, marital status, and education. We then used our results to estimate premature mortality related to PM_2·5 exposure in the population aged 65 years and older in China in 2010.

FINDINGS

13 344 individuals in the CLHLS cohort had data for all timepoints, yielding follow-up data for 49 440 person-years. In a 3-year window, these individuals were exposed to a median PM_2·5 concentration of 50·7 μg/m³ (range 6·7-113·3). The overall HR for a 10 μg/m³ increase in this value was 1·08 (95% CI 1·06-1·09). In stratified analyses, HRs were higher in rural than in urban locations, in southern versus northern regions, and with exposure to lower versus higher PM_2·5 concentrations. Based on the overall HR, we estimated that 1 765 820 people aged 65 years and older in China in 2010 had premature mortality related to PM_2·5 exposure.

INTERPRETATION

Long-term exposure to PM_2·5 is associated with an increased risk of all-cause mortality among adults aged 65 years and older in China, but the magnitude of the risk declines as the concentration of PM_2·5 increases.

FUNDING

National Natural Science Foundation of China, National High-Level Talents Special Support Plan of China for Young Talents, US National Aeronautics and Space Administration, and the Columbia University Global Policy Initiative.

All-cause mortality and long-term exposure to low level air pollution in the '45 and up study' cohort, Sydney, Australia, 2006-2015

BACKGROUND

Epidemiological studies show that long-term exposure to ambient air pollution reduces life expectancy. Most studies have been in environments with relatively high concentrations such as North America, Europe and Asia. Associations at the lower end of the concentration-response function are not well defined.

OBJECTIVES

We assessed associations between all-cause mortality and exposure to annual average particulate matter <2.5 μm (PM_2.5) and nitrogen dioxide (NO₂) in Sydney, Australia, where concentrations are relatively low.

METHODS

The '45 and Up Study' comprises a prospective longitudinal cohort from the state of New South Wales, Australia with 266,969 participants linked to death registry data. We analyzed data for the participants who resided in Sydney at baseline questionnaire (n = 75,268). Exposures to long-term pollution were estimated using annual averages from a chemical transport model (PM_2.5), and a satellite-based land-use regression model (NO₂). Socio-demographic information was extracted from the baseline questionnaire. Cox proportional hazard models were applied to estimate associations, while adjusting for covariates.

RESULTS

In our cohort mean annual PM_2.5 was 4.5 μg/m³ and mean NO₂ was 17.8 μg/m³. The mortality rate was 4.4% over the 7 years of follow up. Models that adjusted for individual-level and area-level risk factors resulted in a detrimental non statistically significant hazard ratio (HR) of 1.05 (95% CI: 0.98-1.12) per 1 μg/m³ increase in PM_2.5, and 1.03 (95% CI: 0.98-1.07) per 5 μg/m³ increase in NO₂.

CONCLUSIONS

We found evidence that low-level air pollution exposure was associated with increased risk of mortality in this cohort of adults aged 45 years and over, even at the relatively low concentrations seen in Sydney. However, a clear determination of the association with mortality is difficult because the results were sensitive to some covariates. Our findings are supportive of emerging evidence that exposure to low levels of air pollution reduces life expectancy.

A Meta-analysis of Traffic-related Air Pollution and Risk of Childhood Leukemia

BACKGROUND

Many studies have analyzed the association between traffic-related air pollution and risk of childhood leukemia, but the results are inconsistent. Therefore, we performed this meta-analysis to investigate the association between traffic-related air pollution and risk of childhood leukemia.

METHODS

PubMed, Cochrane, and Embase databases were searched by the index words to identify eligible case-control studies, and relevant literature sources were also searched. The latest research was performed in September 2017. Odds ratio (OR) along with 95% confidence interval (95% CI) were used to analyzed the main outcomes.

RESULTS

Twenty-one case-control studies were included in the meta-analysis. The results indicated that in the studies of overall traffic density (OR: 1.01, 95% CI: 0.98-1.04), high traffic density (OR: 1.04, 95% CI: 0.91-1.17), moderate exposure to NO2 (OR: 1.02, 95% CI: 0.93-1.10), and benzene (OR: 1.04, 95% CI: 0.71-1.37), the risks of childhood leukemia incidence were higher in the case group than the control group, but no significant difference was found. In other analysis, no significant difference was observed in the risk of childhood leukemia in the 2 groups.

CONCLUSIONS

Current evidence suggests that childhood leukemia is associated with traffic density, and moderate exposure to NO2 and benzene. However, more high-quality studies are required to confirm the conclusions.

Fine-scale damage estimates of particulate matter air pollution reveal opportunities for location-specific mitigation of emissions

Fine particulate matter (PM2.5) air pollution has been recognized as a major source of mortality in the United States for at least 25 years, yet much remains unknown about which sources are the most harmful, let alone how best to target policies to mitigate them. Such efforts can be improved by employing high-resolution geographically explicit methods for quantifying human health impacts of emissions of PM2.5 and its precursors. Here, we provide a detailed examination of the health and economic impacts of PM2.5 pollution in the United States by linking emission sources with resulting pollution concentrations. We estimate that anthropogenic PM2.5 was responsible for 107,000 premature deaths in 2011, at a cost to society of $886 billion. Of these deaths, 57% were associated with pollution caused by energy consumption [e.g., transportation (28%) and electricity generation (14%)]; another 15% with pollution caused by agricultural activities. A small fraction of emissions, concentrated in or near densely populated areas, plays an outsized role in damaging human health with the most damaging 10% of total emissions accounting for 40% of total damages. We find that 33% of damages occur within 8 km of emission sources, but 25% occur more than 256 km away, emphasizing the importance of tracking both local and long-range impacts. Our paper highlights the importance of a fine-scale approach as marginal damages can vary by over an order of magnitude within a single county. Information presented here can assist mitigation efforts by identifying those sources with the greatest health effects.

Regional Inequality and Influencing Factors of Primary PM Emissions in the Yangtze River Delta, China

In recent years, haze pollution has become more and more serious in the Yangtze River Delta (YRD). However, the impact mechanism of socio-economic factors on primary particulate matter (PM) emissions remains unclear. Based on the provincial primary PM emission data in the YRD from 1995 to 2014, this paper used Slope, Theil index, and Stochastic Impacts by Regression on Population, Affluence, and Technology (STIAPAT) models to quantitatively identify the regional differences of primary PM emissions and explore the key influencing factors. The results showed that primary fine particulate matter (PM2.5), inhalable particulate (PM10), and total suspended particulate (TSP) emissions all featured an upward trend of fluctuation over the study period. The regional differences in primary TSP emissions in the YRD region was gradually shrinking and the regional differences of primary PM2.5 and PM10 emissions presented a rising trend of fluctuation. The estimated coefficient of population size, energy structure, and fixed assets investment (FAI) were all significantly positive at the level of 1%. The negative effect of economic growth on energy PM emissions was significant under the level of 1%. The increase of foreign direct investment (FDI) had different effects on primary PM2.5, PM10, and TSP emissions. In addition, the influence of energy intensity on primary PM emission from energy consumption are mainly negative but not significant even under the level of 10%. These conclusions have guiding significance for the formulation of PM emission reduction policy without affecting YRD’s economic development.

Smoking Among Chinese Livery Drivers

We aimed to assess a key risk factor for lung cancer, smoking, in a vulnerable group, Chinese livery drivers in New York City (NYC). This is a nested cohort study conducted in the summer/fall of 2014 within a larger NIMHD-funded R24 program, the Taxi Network. The Taxi Network Needs Assessment (TNNA) survey was administered to a broad demographic of drivers. This study reports on the TNNA survey smoking-related results among NYC Chinese livery drivers. 97 drivers participated. Mean age was 44.7 years, 2.1% were English proficient, and 23.4% were living below the poverty line. Most were insured (82.5%), had a PCP (82.5%), and had had a routine check-up within the past year (79%). 73% were current or former smokers. Culturally and linguistically tailored smoking cessation interventions, strategies to mitigate exposure to air pollution, and programs to facilitate lung cancer screening should be developed and implemented for high-risk Chinese livery drivers.

Mitigation impact of roadside trees on fine particle pollution

Fine particulate matter (PM_2.5) is an important air pollutant due to its adverse health effects. Vehicle emissions make a large contribution to particle concentrations in urban areas. Exposure to particles especially near roadways increases the risk of public health problems. Planting vegetation might be used to capture the fine particles at the roadside, which can lower the health risks for the urban population. Istanbul is the most populous city in Turkey, where the number of non-electric cars is increasing rapidly, resulting in decreasing air quality, especially at the roadsides. Recent studies show that cardiovascular, respiratory and total non-accidental mortality is increasing with short-term exposure to outdoor air pollution in Istanbul. In this study, roadside trees were investigated for the mitigation effect on vehicle-related PM_2.5 and heavy metal (HM). Cupressus sempervirens (Mediterranean Cypress trees) were planted in three different cases (i.e., no trees-C1, trees with gaps-C2 and thick trees with no gaps-C3) at the study site. Location of the site is on a dense-traffic roadside in Istanbul, where thousands of people are living, working and walking through two sides of this road. PM_2.5 samples and tree leaves were examined in the performed experiments. C2 and C3 showed the importance of roadside tree plantation by reducing the exposure to significantly low levels. Roadside PM_2.5 concentrations were reduced by 17% in C3, equivalent to urban background levels in the city. Maximum removal of HMs is observed in nickel from 26.4 ± 7.8 to 7.5 ± 2.4 μg m^-3. Pedestrian exposure is calculated with the measured data in three experiments and exposure is significantly reduced (e.g., >50% for cadmium and lead exposure) in experiment C3. In conclusion, three experiments showed that Mediterranean Cypress trees significantly decreased particle pollution at roadsides in Istanbul.