A meta-analysis and multisite time-series analysis of the differential toxicity of major fine particulate matter constituents

Air Quality and Health Impacts of Onshore Oil and Gas Flaring and Venting Activities Estimated Using Refined Satellite-Based Emissions

Emissions from flaring and venting (FV) in oil and gas (O&G) production are difficult to quantify due to their intermittent activities and lack of adequate monitoring and reporting. Given their potentially significant contribution to total emissions from the O&G sector in the United States, we estimate emissions from FV using Visible Infrared Imaging Radiometer Suite satellite observations and state/local reported data on flared gas volume. These refined estimates are higher than those reported in the National Emission Inventory: by up to 15 times for fine particulate matter (PM2.5), two times for sulfur dioxides, and 22% higher for nitrogen oxides (NOx). Annual average contributions of FV to ozone (O3), NO2, and PM2.5 in the conterminous U.S. (CONUS) are less than 0.15%, but significant contributions of up to 60% are found in O&G fields with FV. FV contributions are higher in winter than in summer months for O3 and PM2.5; an inverse behavior is found for NO2. Nitrate aerosol contributions to PM2.5 are highest in the Denver basin whereas in the Permian and Bakken basins, sulfate and elemental carbon aerosols are the major contributors. Over four simulated months in 2016 for the entire CONUS, FV contributes 210 additional instances of exceedances to the daily maximum 8-hr average O3 and has negligible contributions to exceedance of NO2 and PM2.5, given the current form of the national ambient air quality standards. FV emissions are found to cause over $7.4 billion in health damages, 710 premature deaths, and 73,000 asthma exacerbations among children annually.

Acute exposure to total and source-specific ambient fine particulate matter and risk of respiratory disease hospitalization in Kuwait

Many epidemiologic studies concerned with acute exposure to ambient PM2.5 have reported positive associations for respiratory disease hospitalization. However, few studies have investigated this relationship in Kuwait and extrapolating results from other regions may involve considerable uncertainty due to variations in concentration levels, particle sources and composition, and population characteristics. Local studies can provide evidence for strategies to reduce risks from episodic exposures to high levels of ambient PM2.5 and generating hypotheses for evaluating health risks from chronic exposures. Therefore, using speciated PM2.5 data from local samplers, we analyzed the impact of daily total and source-specific PM2.5 exposure on respiratory hospitalizations in Kuwait using a case-crossover design with conditional quasi-Poisson regression. Total and source-specific ambient PM2.5 were modeled using 0-5-day cumulative distributed lags. For total PM2.5, we observed a 0.16% (95% confidence interval [CI] = 0.05, 0.27%) increase in risk for respiratory hospitalization per 1 μg/m3 increase in concentration. Of the source factors assessed, dust demonstrated a statistically significant increase in risk (0.16%, 95% CI = 0.04, 0.29%), and the central estimate for regional PM2.5 was positive (0.11%) but not statistically significant (95% CI = -0.11, 0.33%). No effect was observed from traffic emissions and 'other' source factors. When hospitalizations were stratified by sex, nationality, and age, we found that female, Kuwaiti national, and adult groups had higher effect estimates. These results suggest that exposure to ambient PM2.5 is harmful in Kuwait and provide some evidence of differential toxicity and effect modification depending on the PM2.5 source and population affected.

Association between long-term exposure to PM2.5 constituents and electrocardiographic abnormality: A nationwide longitudinal study in China

BACKGROUND

Electrocardiogram (ECG) abnormalities are known to have prognostic value for heart conditions, while evidence on the relationship between long-term exposure to PM2.5 constituents and electrocardiographic (ECG) abnormalities is limited. This study aimed to quantify the association between long-term exposure to PM2.5 constituents and changes in ECG diagnoses.

METHODS

We designed a longitudinal study among participants with repeated records of ECG examination based on the China National Stroke Screening Survey 2013-2018. Logistic regressions with multiple adjustment, estimated by the generalized estimating equation to incorporate repeated measurements, were used to assess the associations between the occurrence of any physician-diagnosed ECG abnormalities and long-term exposure to PM2.5 constituents.

RESULTS

We included 61,094 participants with 132,249 visits. All five constituents (sulfate, nitrate, ammonium, organic matter, and black carbon) were significantly associated with an increased risk of ECG abnormalities. The excess risk of ECG abnormalities per interquartile-range increase in exposure was the highest for sulfate (26%, 95% confidence interval [CI] 23-29%), followed by ammonium (22%, 19-26%), nitrate (21%, 17-24%), black carbon (16%, 13-10%) and organic matter (9%,6%-11%). We also found that atrial fibrillation patients might be susceptible to the adverse effects of PM2.5 constituents on ECG.

CONCLUSION

Differential associations between various constituents of PM2.5 and ECG abnormalities were found. The unequal toxicities for different chemical constituents of ambient particles on cardiovascular electrophysiological endpoints should be taken into consideration when considering the biological pathways linking PM2.5 and cardiovascular conditions.

Ecological Study on Global Health Effects due to Source-Specific Ambient Fine Particulate Matter Exposure

Ambient air pollution of fine particulate matter with diameters less than 2.5 μm (PM2.5) is associated with millions of premature deaths per year, recognized as a leading global health concern. The dose-response relation between ambient PM2.5 exposure and mortality risk is the most fundamental information for assessments of the health effects of PM2.5. The existing dose-response relations were generally developed based on the assumption of equal contribution to toxicity from various sources. However, the sources of PM2.5 may significantly influence health effects. In this study, we conducted an ecological study to investigate the global long-term correlation between source-specific PM2.5 exposure and cause-specific mortality risk (SPECM) based on the regional aggregate data of the publically available official health databases from 528 regions worldwide with a total registered population of 3.2 billion. The results provided preliminary epidemiological evidence for differing chronic health effects across various sources. The relative mortality risks of lung cancer and circulatory diseases were closely correlated with the primary emissions from industrial and residential combustion sources. Chronic lower respiratory diseases were mostly associated with the mass concentration of particulate matter.

Environmental Health, Racial/Ethnic Health Disparity, and Climate Impacts of Inter-Regional Freight Transport in the United States

We quantify and compare three environmental impacts from inter-regional freight transportation in the contiguous United States: total mortality attributable to PM2.5 air pollution, racial-ethnic disparities in PM2.5-attributable mortality, and CO2 emissions. We compare all major freight modes (truck, rail, barge, aircraft) and routes (∼30,000 routes). Our study is the first to comprehensively compare each route separately and the first to explore racial-ethnic exposure disparities by route and mode, nationally. Impacts (health, health disparity, climate) per tonne of freight are the largest for aircraft. Among nonaircraft modes, per tonne, rail has the largest health and health-disparity impacts and the lowest climate impacts, whereas truck transport has the lowest health impacts and greatest climate impacts─an important reminder that health and climate impacts are often but not always aligned. For aircraft and truck, average monetized damages per tonne are larger for climate impacts than those for PM2.5 air pollution; for rail and barge, the reverse holds. We find that average exposures from inter-regional truck and rail are the highest for White non-Hispanic people, those from barge are the highest for Black people, and those from aircraft are the highest for people who are mixed/other race. Level of exposure and disparity among racial-ethnic groups vary in urban versus rural areas.

Short-term exposure to fine particulate matter constituents and mortality: case-crossover evidence from 32 counties in China

A growing number of studies associated increased mortality with exposures to specific fine particulate (PM_2.5) constituents, while great heterogeneity exists between locations. In China, evidence linking PM_2.5 constituents and mortality was extensively sparse. This study primarily aimed to quantify short-term associations between PM_2.5 constituents and non-accidental mortality among the Chinese population. We collected daily mortality records from 32 counties in China between January 1, 2011, and December 31, 2013. Daily concentrations of main PM_2.5 constituents (organic carbon (OC), elemental carbon (EC), nitrate (NO₃^-), sulfate (SO₄^2-), and ammonium (NH₄⁺)) were estimated using the modified Community Multiscale Air Quality model. Time-stratified case-crossover design with conditional logistic regression models was adopted to estimate mortality risks associated with short-term exposures to PM_2.5 mass and its constituents. Stratification analyses were done by sex, age, and season. A total of 116,959 non-accidental deaths were investigated. PM_2.5 concentrations on the day of death were averaged at 75.7 µg m^-3 (control day: 75.6 µg m^-3), with an interquartile range (IQR) of 65.2 µg m^-3. Per IQR rise in PM_2.5, EC, OC, NO₃^-, SO₄^2-, and NH₄⁺ at lag-04 day was associated with an increase in non-accidental mortality of 2.4% (95% confidence interval, (1.0-3.7), 1.7% (0.8-2.7), 2.9% (1.6-4.3), 2.1% (0.4-3.9), 1.0% (0.2-1.9), and 1.6% (0.3-2.9), respectively. Both PM_2.5 mass and its constituents were strongly associated with elevated cardiovascular mortality risks, but only PM_2.5, EC, and OC were positively associated with respiratory mortality at lag-3 day. PM_2.5 mass and its constituents associated effects on mortality varied among sex- and age-specific subpopulations. Differences in the seasonal pattern of associations exist among PM_2.5 constituents, with stronger effects related to EC and NO₃^- in warm months but SO₄^2- and NH₄⁺ in cold months. Short-term exposures to PM_2.5 compositions were positively associated with increased risks of mortality, particularly those constituents from combustion-related sources.

Acute effects of black carbon on mortality in nine megacities of China, 2008-2016: a time-stratified case-crossover study

Black carbon (BC) may have more adverse effects on human health than other constituents of PM_2.5. The daily mean concentrations of BC in China are much higher than those in developed countries and are estimated to account for more than a quarter of global anthropogenic BC emissions. However, reports on the health effects of BC in China have been limited. Thus, a time-stratified case-crossover study was conducted to evaluate the impacts of BC on daily mortality risk in nine Chinese megacities from 2008-2016. Our results show that for all-cause mortality, when compared to the interquartile range (IQR) of BC concentration increased, odds ratios (ORs) were in the range of 1.01-1.06 (95% CIs: 0.99-1.10). For cardiovascular mortality, ORs were in the range of 1.02-1.07 (95% CIs: 1.003-1.12), and for respiratory mortality, ORs were in the range of 1.01-1.15 (95% CIs: 1.00-1.18). The effects of BC in the nine cities were robust after adjusting for PM_2.5, or even became more prominent. Furthermore, BC had stronger effects in spring and winter in northern cities, whereas in mid-latitude cities, BC had stronger effects in the warm seasons. In southern cities, BC had stronger effects in the cool and dry seasons. Our findings support an association between residential exposure to BC and mortality and thus provide further evidence that BC negatively impacts human health and is helpful for decision-making.

Accumulation of trace element content in the lungs of Sao Paulo city residents and its correlation to lifetime exposure to air pollution

Heavy metals are natural and essential elements of the environment and living beings, produced from natural (e.g. volcanic activity and cosmic ray-induced spallation) and anthropogenic processes (e.g. industrial and fossil fuel combustion). High-concentrations of heavy metals and radionuclides are also originated from anthropogenic activities in urban and industrial areas. In this preliminary study, we analyzed the levels of heavy metals and Polonium-210 (²¹⁰Po) in lung tissues in autopsies from residents of the city of Sao Paulo, SP, Brazil. In order to identify the link among sources of the heavy metals in lungs, factor analysis was performed. Of the first four factors, which explain 66% of the total variability, three were associated with vehicular sources. The fitting of a regression model with ²¹⁰Po as the response variable and with the four factors as explanatory variables, controlling for age, sex and tobacco, showed a significant association between the concentration of polonium and the first factor that is generated by catalysts and brakes (coefficient = 0.90, standard error = 0.33, p = 0.016). Our findings suggest an association between traffic-related trace metals and ²¹⁰Po in lung autopsies.

Is short-term and long-term exposure to black carbon associated with cardiovascular and respiratory diseases? A systematic review and meta-analysis based on evidence reliability

OBJECTIVE

Adverse health effects of fine particles (particulate matter_2.5) have been well documented by a series of studies. However, evidences on the impacts of black carbon (BC) or elemental carbon (EC) on health are limited. The objectives were (1) to explored the effects of BC and EC on cardiovascular and respiratory morbidity and mortality, and (2) to verified the reliability of the meta-analysis by drawing p value plots.

DESIGN

The systematic review and meta-analysis using adapted Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach and p value plots approach.

DATA SOURCES

PubMed, Embase and Web of Science were searched from inception to 19 July 2021.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Time series, case cross-over and cohort studies that evaluated the associations between BC/EC on cardiovascular or respiratory morbidity or mortality were included.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently selected studies, extracted data and assessed risk of bias. Outcomes were analysed via a random effects model and reported as relative risk (RR) with 95% CI. The certainty of evidences was assessed by adapted GRADE. The reliabilities of meta-analyses were analysed by p value plots.

RESULTS

Seventy studies met our inclusion criteria. (1) Short-term exposure to BC/EC was associated with 1.6% (95% CI 0.4% to 2.8%) increase in cardiovascular diseases per 1 µg/m³ in the elderly; (2) Long-term exposure to BC/EC was associated with 6.8% (95% CI 0.4% to 13.5%) increase in cardiovascular diseases and (3) The p value plot indicated that the association between BC/EC and respiratory diseases was consistent with randomness.

CONCLUSIONS

Both short-term and long-term exposures to BC/EC were related with cardiovascular diseases. However, the impact of BC/EC on respiratory diseases did not present consistent evidence and further investigations are required.

PROSPERO REGISTRATION NUMBER

CRD42020186244.

Do temporal trends of associations between short-term exposure to fine particulate matter (PM2.5) and risk of hospitalizations differ by sub-populations and urbanicity-a study of 968 U.S. counties and the Medicare population

While associations between short-term exposure to fine particulate matter (PM_2.5) and risk of hospitalization are well documented and evidence suggests that such associations change over time, it is unclear whether these temporal changes exist in understudied less-urban areas or differ by sub-population. We analyzed daily time-series data of 968 continental U.S. counties for 2000-2016, with cause-specific hospitalization from Medicare claims and population-weighted PM_2.5 concentrations originally estimated at 1km × 1 km from a hybrid model. Circulatory and respiratory hospitalizations were categorized based on primary diagnosis codes at discharge. Using modified Bayesian hierarchical modelling, we evaluated the temporal trend in association between PM_2.5 and hospitalizations and whether disparities in this trend exist across individual-level characteristics (e.g., sex, age, race, and Medicaid eligibility as a proxy for socio-economic status) and urbanicity. Urbanicity was categorized into three levels by county-specific percentage of urban population based on urban rural delineation from the U.S. Census. In this cohort with understudied less-urban areas without regulatory monitors, we still found positive association between circulatory and respiratory hospitalization and short-term exposure to PM_2.5, with higher effect estimates towards the end of study period. Consistent with current literature, we identified significant disparity in associations by race, socioeconomic status and urbanicity. We found that the percentage change in circulatory hospitalization rate per 10 μg/m³ increase in PM_2.5 was higher in the 2008-2016 time period compared to the 2000-2007 period by 0.33% (95% posterior credible interval 0.22, 0.44%), 0.52% (0.33, 0.69%), and 0.67% (0.53, 0.83%) for low, medium and high tertiles of urban areas, respectively. We also observed significant differences in temporal trends of associations across socioeconomic status, sex, and age, indicating a possible widening in disparity of PM_2.5-related health burden. This study raises the importance of considering environmental justice issues in PM_2.5-related health impacts with respect to how associations may change over time.

Drivers of air pollution variability during second wave of COVID-19 in Delhi, India

To curb the 2nd wave of COVID-19 disease in April-May 2021, a night curfew followed by full lockdown was imposed over the National Capital Territory, Delhi. We have analyzed the observed variation in pollutants and meteorology, and role of local and transboundary emission sources during night-curfew and lockdown, as compared to pre-lockdown period and identical periods of 2020 lockdown as well as of 2018 and 2019. In 2021, concentration of pollutants (except O₃, SO₂, and toluene) declined by 4-16% during night-curfew as compared to the pre-lockdown period but these changes are not statistically significant. During lockdown in 2021, various pollutants decreased by 1-28% as compared to the night-curfew (except O₃ and PM₂.₅), but increased by 31-129% compared to the identical period of 2020 lockdown except O₃. Advection of pollutants from the region of moderate lockdown restrictions and an abrupt increase in crop-residue burning activity (120-587%) over Haryana and Punjab increased the air pollution levels over NCT during the lockdown period of 2021 as compared to 2020 in addition to a significant contribution of long-range transport. The increase in PM₂.₅ during the lockdown period of 2021 compared to 2020 might led to 5-29 additional premature mortalities.

Air quality and health-related impacts of traditional and alternate jet fuels from airport aircraft operations in the U.S

Aviation emissions from landing and takeoff operations (LTO) can degrade local and regional air quality leading to adverse health outcomes in populations near airports and downwind. In this study we aim to quantify the air quality and health-related impacts from commercial LTO emissions in the continental U.S. for two recent years' inventories, 2011 and 2016. We quantify the LTO-attributable PM_2.5, O₃, and NO₂ concentrations and health outcomes for mortality and multiple morbidity health endpoints. We also quantify the impacts from two scenarios representing a nation-wide implementation of 5% or 50% blends of sustainable alternative jet fuels. We estimate 80 (68-93) and 88 (75-100) PM_2.5-attributable and 610 (310-920) and 1,100 (570-1,700) NO₂-attributable premature mortalities in 2011 and 2016, respectively. We estimate a net decrease of 28 (14-56) and 54 (27-110) in O₃-attributable premature mortalities across the U.S. in 2011 and 2016, respectively due to the large O₃ titration effects near the airports. We also find that the asthma exacerbations due to NO₂ exposures from LTO emissions increase from 100,000 (2,500-200,000) in 2011 to 170,000 (4,400-340,000) in 2016. Implementing a 5% or 50% blend of sustainable alternative jet fuel in 2016 results in a 1% or 18% reduction, respectively in PM_2.5-attributable premature mortalities. Monetizing the value of avoided total premature mortalities, we find that a 50%-blended sustainable alternative jet fuel results in a 19% decrease in PM_2.5 damages per ton of fuel burned and a 2% decrease in total damages per ton of fuel burned as compared to damages from traditional jet fuel. We also quantify health impacts by state and find California to be the most impacted by LTO emissions. We find that LTO-attributable PM_2.5 and NO₂ premature mortalities increase by 10% and 80%, respectively from 2011 to 2016 and that NO₂-attributable premature mortalities are responsible for 91% of total LTO-attributable premature mortalities in both 2011 and 2016. And since we find LTO-attributable NO₂ to be unaffected by the implementation of sustainable alternative jet fuels, additional approaches focused on NO_X reductions in the combustor are needed to mitigate the air quality-related health impacts from LTO emissions.

Assessing short-term impacts of PM2.5 constituents on cardiorespiratory hospitalizations: Multi-city evidence from China

Apart from concentrations of particulate mass, PM_2.5-associated effects on health may largely depend on its chemical components. However, little is known regarding the underlying effects of specific PM_2.5 constituents. The study included nearly 1 million hospital admissions from five Chinese cities during 2015-2017. Based on the modified Community Multiscale Air Quality model, our study simulated daily concentrations of PM_2.5 and five main components. We used a time-stratified case-crossover design with conditional logistic regression models to estimate short-term effects of PM_2.5 constituents on cause-specific hospital admissions. Per interquartile range increase in exposure to PM_2.5, elemental carbon, organic carbon, nitrate, sulfate and ammonium at lag 04-day was related to an excess risk (ER%) for non-accidental admissions of 1.6% [95% confidence interval: 1.1-2.0], 1.9% [1.3-2.4], 1.0% [0.5-1.6], 1.2% [0.4-2.0], 1.2% [0.9-1.5] and 1.4% [0.9-1.9], respectively. Great heterogeneities of constituents-admission associations existed in diverse causes and constituents. This study provided multi-center high-quality evidence that hospital admissions, particularly those for ischemic heart disease (ER% ranging from 2.3 to 5.4% at lag 04-day) and pneumonia (1.9-5.1% at lag 4-day), could be triggered by short-term exposures to ambient PM_2.5 constituents. Relatively stronger constituents-admission associations were found among females for respiratory causes and the elderly for cardiovascular causes.

Spatio-temporal variation in fine particulate matter and effect on air quality during the COVID-19 in New Delhi, India

Novel Coronavirus disease has affected almost all the countries; which leads to the pandemic, impacting adversely on environment. The impact on environment during pre-and during lockdowns needs an attention to correlate the pollutants from industrial emissions and other factors. Therefore, the current study demonstrates the changes in fine particulate matter PM_2.5, PM₁₀ and effect on air quality during lockdown. The highest reduction was observed in lockdown I (25 March - 14 April) as compared to others lockdowns (between 15 April and 31st May 2020) due to the complete shutdown of industrial, transport, and construction activities. A significant reduction in PM_2.5 and PM₁₀ from 114.27 μg/m³ and 194.48 μg/m³ for pre-lockdown period to 41.41 μg/m³ and 86.81 μg/m³ for lockdown I was observed. The levels of air quality index fall under satisfactory category for lockdown I whereas satisfactory to moderate category for other lockdowns. The present study revealed a strong correlation between PM_2.5 and PM₁₀ levels during the pre-lockdown period (0.71) and through lockdown IV (0.76), which indicate that change in the PM₁₀ level influences the PM_2.5 level greatly. The findings of the present study could be scaled up nationwide and might be useful in formulating air pollution reduction policies in the future.

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 (PM_2.5) provide evidence of substantial spatial heterogeneity in city-specific mortality risk estimates across the United States. Because PM_2.5 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 PM_2.5 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 PM_2.5-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, PM_2.5 ammonium, PM_2.5 nitrate, and PM_2.5 sulfate. In multivariable models, only daily correlation of PM_2.5 with PM₁₀ and long-term average PM_2.5 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 PM_2.5-mortality effect estimates, continuing to demonstrate that this heterogeneity is multifactorial and not attributable to a single aspect of PM.

Temporal variation in association between short-term exposure to fine particulate matter and hospitalisations in older adults in the USA: a long-term time-series analysis of the US Medicare dataset

BACKGROUND

Short-term exposure to fine particulate matter (PM_2·5) is associated with increased risk of hospital admissions and mortality, and health risks differ by the chemical composition of PM_2·5. Policies to control PM_2·5 could change its chemical composition and total mass concentration, leading to change in the subsequent health impact. However, there is little ence on whether associations between PM_2·5 and health exhibit temporal variation. We investigated whether risks of hospitalisations from short-term exposure to PM_2·5 varied over time in the USA.

METHODS

We did a time-series analysis using a national dataset comprising daily circulatory and respiratory hospitalisation rates of Medicare beneficiaries (age ≥65 years) and PM_2·5 in 173 US counties from 1999 to 2016. We fitted modified quasi-Poisson models to estimate temporal trends of associations within a county, and pooled county-level estimates using Bayesian hierarchical modelling to generate an overall estimate.

FINDINGS

The study included 10 559 654 circulatory and 3 027 281 respiratory hospitalisations. We identified changes in the national average association between previous-day PM_2·5 and respiratory hospitalisation over time, with a U-shape that is robust under stratification, linear, and non-linear models. The change in risk of respiratory hospitalisation per 10 μg/m³ increase in previous-day PM_2·5 decreased from 0·75% (95% posterior credible interval 0·05 to 1·46) in 1999 to -0·28% (-0·79 to 0·23) in 2008, and then increased to 1·44% (0·00 to 2·91) in 2016. No statistically significant temporal change was observed for associations between same-day PM_2·5 and circulatory hospitalisation.

INTERPRETATION

Hospitalisation risk from PM_2·5 changes over time and has increased over the past 7 years in study, especially in northeastern USA. The temporal trend differs by cause of hospitalisation. This study emphasises the necessity of evaluating temporal heterogeneity in health impacts of PM_2·5 and suggests caution in applying association estimates to a different time period.

FUNDING

US Environmental Protection Agency and Yale Institute for Biospheric Studies.

A community-based study on associations between PM2.5 and PM1 exposure and heart rate variability using wearable low-cost sensing devices

Few studies have investigated the effect of personal PM_2.5 and PM₁ exposures on heart rate variability (HRV) for a community-based population, especially in Asia. This study evaluates the effects of personal PM_2.5 and PM₁ exposure on HRV during two seasons for 35 healthy adults living in an urban community in Taiwan. The low-cost sensing (LCS) devices were used to monitor the PM levels and HRV, respectively, for two consecutive days. The mean PM_2.5 and PM₁ concentrations were 13.7 ± 11.4 and 12.7 ± 10.5 μg/m³ (mean ± standard deviation), respectively. Incense burning was the source that contributed most to the PM_2.5 and PM₁ concentrations, around 9.2 μg/m³, while environmental tobacco smoke exposure had the greatest impacts on HRV indices, being associated with the highest decrease of 20.2% for high-frequency power (HF). The results indicate that an increase in PM_2.5 concentrations of one interquartile range (8.7 μg/m³) was associated with a change of -1.92% in HF and 1.60% in ratio of LF to HF power (LF/HF). Impacts on HRV for PM₁ were similar to those for PM_2.5. An increase in PM₁ concentrations of one interquartile range (8.7 μg/m³) was associated with a change of -0.645% in SDNN, -1.82% in HF and 1.54% in LF/HF. Stronger immediate and lag effects of PM_2.5 exposure on HRV were observed in overweight/obese subjects (body mass index (BMI) ≥24 kg/m²) compared to the normal-weight group (BMI <24 kg/m²). These results indicate that even low-level PM concentrations can still cause changes in HRV, especially for the overweight/obese population.

Atmospheric conditions and composition that influence PM2.5 oxidative potential in Beijing, China

Epidemiological studies have consistently linked exposure to PM_2.5 with adverse health effects. The oxidative potential (OP) of aerosol particles has been widely suggested as a measure of their potential toxicity. Several acellular chemical assays are now readily employed to measure OP; however, uncertainty remains regarding the atmospheric conditions and specific chemical components of PM_2.5 that drive OP. A limited number of studies have simultaneously utilised multiple OP assays with a wide range of concurrent measurements and investigated the seasonality of PM_2.5 OP. In this work, filter samples were collected in winter 2016 and summer 2017 during the atmospheric pollution and human health in a Chinese megacity campaign (APHH-Beijing), and PM_2.5 OP was analysed using four acellular methods: ascorbic acid (AA), dithiothreitol (DTT), 2,7-dichlorofluorescin/hydrogen peroxidase (DCFH) and electron paramagnetic resonance spectroscopy (EPR). Each assay reflects different oxidising properties of PM_2.5, including particle-bound reactive oxygen species (DCFH), superoxide radical production (EPR) and catalytic redox chemistry (DTT/AA), and a combination of these four assays provided a detailed overall picture of the oxidising properties of PM_2.5 at a central site in Beijing. Positive correlations of OP (normalised per volume of air) of all four assays with overall PM_2.5 mass were observed, with stronger correlations in winter compared to summer. In contrast, when OP assay values were normalised for particle mass, days with higher PM_2.5 mass concentrations (μgm^-3) were found to have lower mass-normalised OP values as measured by AA and DTT. This finding supports that total PM_2.5 mass concentrations alone may not always be the best indicator for particle toxicity. Univariate analysis of OP values and an extensive range of additional measurements, 107 in total, including PM_2.5 composition, gas-phase composition and meteorological data, provided detailed insight into the chemical components and atmospheric processes that determine PM_2.5 OP variability. Multivariate statistical analyses highlighted associations of OP assay responses with varying chemical components in PM_2.5 for both mass- and volume-normalised data. AA and DTT assays were well predicted by a small set of measurements in multiple linear regression (MLR) models and indicated fossil fuel combustion, vehicle emissions and biogenic secondary organic aerosol (SOA) as influential particle sources in the assay response. Mass MLR models of OP associated with compositional source profiles predicted OP almost as well as volume MLR models, illustrating the influence of mass composition on both particle-level OP and total volume OP. Univariate and multivariate analysis showed that different assays cover different chemical spaces, and through comparison of mass- and volume-normalised data we demonstrate that mass-normalised OP provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis. This study constitutes one of the most extensive and comprehensive composition datasets currently available and provides a unique opportunity to explore chemical variations in PM_2.5 and how they affect both PM_2.5 OP and the concentrations of particle-bound reactive oxygen species.

A Spatiotemporal Prediction Model for Black Carbon in the Denver Metropolitan Area, 2009-2020

Studies on health effects of air pollution from local sources require exposure assessments that capture spatial and temporal trends. To facilitate intraurban studies in Denver, Colorado, we developed a spatiotemporal prediction model for black carbon (BC). To inform our model, we collected more than 700 weekly BC samples using personal air samplers from 2018 to 2020. The model incorporated spatial and spatiotemporal predictors and smoothed time trends to generate point-level weekly predictions of BC concentrations for the years 2009-2020. Our results indicate that our model reliably predicted weekly BC concentrations across the region during the year in which we collected data. We achieved a 10-fold cross-validation R² of 0.83 and a root-mean-square error of 0.15 μg/m³ for weekly BC concentrations predicted at our sampling locations. Predicted concentrations displayed expected temporal trends, with the highest concentrations predicted during winter months. Thus, our prediction model improves on typical land use regression models that generally only capture spatial gradients. However, our model is limited by a lack of long-term BC monitoring data for full validation of historical predictions. BC predictions from the weekly spatiotemporal model will be used in traffic-related air pollution exposure-disease associations more precisely than previous models for the region have allowed.

Airborne Aerosols and Human Health: Leapfrogging from Mass Concentration to Oxidative Potential

The mass concentration of atmospheric particulate matter (PM) has been systematically used in epidemiological studies as an indicator of exposure to air pollutants, connecting PM concentrations with a wide variety of human health effects. However, these effects can be hardly explained by using one single parameter, especially because PM is formed by a complex mixture of chemicals. Current research has shown that many of these adverse health effects can be derived from the oxidative stress caused by the deposition of PM in the lungs. The oxidative potential (OP) of the PM, related to the presence of transition metals and organic compounds that can induce the production of reactive oxygen and nitrogen species (ROS/RNS), could be a parameter to evaluate these effects. Therefore, estimating the OP of atmospheric PM would allow us to evaluate and integrate the toxic potential of PM into a unique parameter, which is related to emission sources, size distribution and/or chemical composition. However, the association between PM and particle-induced toxicity is still largely unknown. In this commentary article, we analyze how this new paradigm could help to deal with some unanswered questions related to the impact of atmospheric PM over human health.

Mitigating the air pollution effect? The remarkable decline in the pollution-mortality relationship in Hong Kong

Using transboundary pollution from mainland China as an instrument, we show that air pollution leads to higher cardio-respiratory mortality in Hong Kong. However, the air pollution effect has dramatically decreased over the past two decades: before 2003, a 10-unit increase in the Air Pollution Index could lead to a 3.1% increase in monthly cardio-respiratory mortality, but this effect has declined to 0.5% using recent data and is no longer statistically significant. Exploratory analyses suggest that a well-functioning medical system and immediate access to emergency services can help mitigate the contemporaneous effects of pollution on mortality.

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.

Associations of daily mortality with short-term exposure to PM2.5 and its constituents in Shanghai, China

Epidemiological studies have shown that fine particulate matter (PM_2.5) has adverse impacts on human health. However, limited studies have investigated the effects of short-term exposure to PM_2.5 and its constituents on mortality in China. This study used the generalized linear model (GLM) to investigate the effects of PM_2.5 and its constituents, including organic carbon (OC), element carbon (EC), ammonium (NH₄⁺), nitrate (NO₃^-), sulfate (SO₄^2-), on different causes of mortality in Shanghai from January 1, 2013 to December 31, 2015. The single-day lagged model and the moving average lagged model were used to examine the lagging effects of pollutants on mortality. At lag0 day, PM_2.5 had a significant effect on all-cause mortality, and a 10 μg/m³ increase leads to 0.68% increase in all-cause mortality (RR 1.0068, 95%CI 1.0013-1.0123). Among the five constituents, EC had the greatest impact on all-cause mortality in Shanghai, with 10.48% increase of mortality (RR 1.1048, 95%CI 1.0266-1.1891) per 10 μg/m³ increase of concentrations, followed by OC (RR 1.0577, 95%CI 1.0277-1.0886), NH₄⁺ (RR 1.0272, 95%CI 1.0028-1.0522) and SO₄^2- (RR 1.0104, 95%CI 1.0003-1.0206). For respiratory diseases mortality, EC, OC, NO₃^- and NH₄⁺ had significant impacts and caused an increase of mortality by 44.99% (RR 1.4499, 95%CI 1.1813-1.7794), 10.40% (RR 1.1040, 95%CI 1.0260-1.1880), 5.338% (RR 1.0533, 95%CI 1.0097-1.0989) and 7.34% (RR 1.0734, 95%CI 1.0015-1.1505) per 10 μg/m³ increase of concentrations, respectively. The cumulative effect of PM_2.5 on mortality was significant in Shanghai. Except for SO₄^2-, the RR value of the single-day lagged model was smaller than the moving average lagged model.

Associations of ambient fine particulate matter and its constituents with serum complement C3 in a panel study of older adults in China

Epidemiological studies have demonstrated association between the total mass of fine particulate matter (PM_2.5) exposures and inflammation. There are few studies exploring the associations between PM_2.5 constituents and the biomarkers of inflammation in older adults and the underlying biological mechanisms are not exact. In this study, we examined the associations between PM_2.5 and its constituents (organic carbon (OC), elemental carbon (EC), total carbon (TC), polycyclic aromatic hydrocarbons (PAHs) and complement three factor (C3), an important biomarker of inflammation in a repeated panel of 175 older adults in Beijing, China. We have constructed three different linear mixed effect models (single-pollutant model, constituent-PM_2.5 joint model, and constituent-residual model) to evaluate the association of PM_2.5 and its constituents and complement C3, controlling for concentration of high sensitive C-reactive protein (hs-CRP), day of week, mean temperature, relative humidity, location and potential individual confounders. We found robust positive associations of OC, EC, TC, PAHs and PM_2.5 mass concentration with complement C3 at different lag patterns. The cumulative effects of pollutants increased across average of 2-5 days. Individuals aged 65 and above, or with diabetes, or BMI ≥30, or with no-cardiopathy, or with hypertension also exhibited positive associations between PM_2.5 and complement C3. The results revealed that short-term exposure to PM_2.5 and its constituents could result in a significant increase in serum level of complement C3. These findings suggested a possible involvement of complement C3 in the effect of PM_2.5 on inflammatory reaction.

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.

Acute Effects of Air Pollution and Noise from Road Traffic in a Panel of Young Healthy Adults

Panel studies are an efficient means to assess short-term effects of air pollution and other time-varying environmental exposures. Repeated examinations of volunteers allow for an in-depth analysis of physiological responses supporting the biological interpretation of environmental impacts. Twenty-four healthy students walked for 1 h at a minimum of four separate occasions under each of the following four settings: along a busy road, along a busy road wearing ear plugs, in a park, and in a park but exposed to traffic noise (65 dB) through headphones. Particle mass (PM_2.5, PM₁), particle number, and noise levels were measured throughout each walk. Lung function and exhaled nitrogen oxide (NO) were measured before, immediately after, 1 h after, and approximately 24 h after each walk. Blood pressure and heart rate variability were measured every 15 min during each walk. Recorded air pollution levels were found to correlate with reduced lung function. The effects were clearly significant for end-expiratory flows and remained visible up to 24 h after exposure. While immediate increases in airway resistance could be interpreted as protective (muscular) responses to particulate air pollution, the persisting effects indicate an induced inflammatory reaction. Noise levels reduced systolic blood pressure and heart rate variability. Maybe due to the small sample size, no effects were visible per specific setting (road vs. park).

Current State of Research on the Risk of Morbidity and Mortality Associated with Air Pollution in Korea

PURPOSE

The effects of air pollution on health can vary regionally. Our goal was to comprehensively review previous epidemiological studies on air pollution and health conducted in Korea to identify future areas of potential study.

MATERIALS AND METHODS

We systematically searched all published epidemiologic studies examining the association between air pollution and occurrence of death, diseases, or symptoms in Korea. After classifying health outcomes into mortality, morbidity, and health impact, we summarized the relationship between individual air pollutants and health outcomes.

RESULTS

We analyzed a total of 27 studies that provided 104 estimates of the quantitative association between risk of mortality and exposure to air pollutants, including particulate matter with aerodynamic diameter less than 10 μm, particulate matter with aerodynamic diameter less than 2.5 μm, sulfur dioxide, nitrogen dioxide, ozone, and carbon monoxide in Korea between January 1999 and July 2018. Regarding the association with morbidity, there were 38 studies, with 98 estimates, conducted during the same period. Most studies examined the short-term effects of air pollution using a time series or case-crossover study design; only three cohort studies that examined long-term effects were found. There were four health impact studies that calculated the attributable number of deaths or disability-adjusted life years due to air pollution.

CONCLUSION

There have been many epidemiologic studies in Korea regarding air pollution and health. However, the present review shows that additional studies, especially cohort and experimental studies, are needed to provide more robust and accurate evidence that can be used to promote evidence-based policymaking.

Fine Particle Constituents and Mortality: A Time-Series Study in Beijing, China

There is a rising concern that fine particle (PM_2.5) compositions may play an important role in explaining PM_2.5-related mortality risks. However, PM_2.5 constituents responsible for these risks have not yet been determined. To date, there are few PM_2.5 constituent health studies in developing countries. We adopted a time-series approach, using generalized linear regression models to examine associations between short-term exposure to PM_2.5 constituents and mortality. We analyzed data stratified by sex and by age groups (<65, 65-74, and >74) from 2013 to 2015 in Beijing, China. We also investigated seasonal patterns of such associations. For a 0 day lag, interquartile range increases in potassium, calcium, magnesium, and organic carbon were associated with 0.51% (95% CI: 0.17-0.85), 2.07% (95% CI: 0.71-3.44), 0.26% (95% CI: 0.08-0.44), and 2.65% (95% CI: 0.18-5.18) increases in respiratory mortality, and sulfate with a 1.57% (95% CI: 0.04-3.12) increase in cardiovascular mortality. In the season-stratified analysis, the association of some constituents (potassium, calcium, magnesium, nitrate, sulfate, and organic carbon) with respiratory mortality appeared to be stronger in cold seasons than in warm seasons. Older adults (65-74) may be susceptible to certain compositions. Our findings provide evidence that link PM_2.5 constituents with mortality and suggest that adverse effects vary among constituents in different seasons.

A National Multicity Analysis of the Causal Effect of Local Pollution, [Formula: see text], and [Formula: see text] on Mortality

BACKGROUND

Studies have long associated [Formula: see text] with daily mortality, but few applied causal-modeling methods, or at low exposures. Short-term exposure to [Formula: see text], a marker of local traffic, has also been associated with mortality but is less studied. We previously found a causal effect between local air pollution and mortality in Boston.

OBJECTIVES

We aimed to estimate the causal effects of local pollution, [Formula: see text], and [Formula: see text] on mortality in 135 U.S. cities.

METHODS

We used three methods which, under different assumptions, provide causal marginal estimates of effect: a marginal structural model, an instrumental variable analysis, and a negative exposure control. The instrumental approach used planetary boundary layer, wind speed, and air pressure as instruments for concentrations of local pollutants; the marginal structural model separated the effects of [Formula: see text] from the effects of [Formula: see text], and the negative exposure control provided protection against unmeasured confounders.

RESULTS

In 7.3 million deaths, the instrumental approach estimated that mortality increased 1.5% [95% confidence interval (CI): 1.1%, 2.0%] per [Formula: see text] increase in local pollution indexed as [Formula: see text]. The negative control exposure was not associated with mortality. Restricting our analysis to days with [Formula: see text] below [Formula: see text], we found a 1.70% (95% CI 1.11%, 2.29%) increase. With marginal structural models, we found positive significant increases in deaths with both [Formula: see text] and [Formula: see text]. On days with [Formula: see text] below [Formula: see text], we found a 0.83% (95% CI 0.39%, 1.27%) increase. Including negative exposure controls changed estimates minimally.

CONCLUSIONS

Causal-modeling techniques, each subject to different assumptions, demonstrated causal effects of locally generated pollutants on daily deaths with effects at concentrations below the current EPA daily [Formula: see text] standard. https://doi.org/10.1289/EHP2732.

What Are the Net Benefits of Reducing the Ozone Standard to 65 ppb? An Alternative Analysis

In October 2015, the United States Environmental Protection Agency (EPA) lowered the level of the ozone National Ambient Air Quality Standard (NAAQS) from 0.075 ppm to 0.070 ppm (annual 4th highest daily maximum 8-h concentration, averaged over three years). The EPA estimated a 2025 annual national non-California net benefit of $1.5 to $4.5 billion (2011$, 7% discount rate) for a 0.070 ppm standard, and a −$1.0 to $14 billion net benefit for an alternative 0.065 ppm standard. The purpose of this work is to present a combined toxicological and economic assessment of the EPA’s benefit-cost analysis of the 2015 ozone NAAQS. Assessing the quality of the epidemiology studies based on considerations of bias, confounding, chance, integration of evidence, and application of the studies for future population risk estimates, we derived several alternative benefits estimates. We also considered the strengths and weaknesses of the EPA’s cost estimates (e.g., marginal abatement costs), as well as estimates completed by other authors, and provided our own alternative cost estimate. Based on our alternative benefits and cost calculations, we estimated an alternative net benefit of between −$0.3 and $1.8 billion for a 0.070 ppm standard (2011 $, 7% discount rate) and between −$23 and −$17 billion for a 0.065 ppm standard. This work demonstrates that alternative reasonable assumptions can generate very difference cost and benefits estimates that may impact how policy makers view the outcomes of a major rule.

A Comparison of the Health Effects of Ambient Particulate Matter Air Pollution from Five Emission Sources

This article briefly reviews evidence of health effects associated with exposure to particulate matter (PM) air pollution from five common outdoor emission sources: traffic, coal-fired power stations, diesel exhaust, domestic wood combustion heaters, and crustal dust. The principal purpose of this review is to compare the evidence of health effects associated with these different sources with a view to answering the question: Is exposure to PM from some emission sources associated with worse health outcomes than exposure to PM from other sources? Answering this question will help inform development of air pollution regulations and environmental policy that maximises health benefits. Understanding the health effects of exposure to components of PM and source-specific PM are active fields of investigation. However, the different methods that have been used in epidemiological studies, along with the differences in populations, emission sources, and ambient air pollution mixtures between studies, make the comparison of results between studies problematic. While there is some evidence that PM from traffic and coal-fired power station emissions may elicit greater health effects compared to PM from other sources, overall the evidence to date does not indicate a clear ‘hierarchy’ of harmfulness for PM from different emission sources. Further investigations of the health effects of source-specific PM with more advanced approaches to exposure modeling, measurement, and statistics, are required before changing the current public health protection approach of minimising exposure to total PM mass.

Ultrafine and Fine Particle Number and Surface Area Concentrations and Daily Cause-Specific Mortality in the Ruhr Area, Germany, 2009-2014

BACKGROUND

Although epidemiologic studies have shown associations between particle mass and daily mortality, evidence on other particle metrics is weak.

OBJECTIVES

We investigated associations of size-specific particle number concentration (PNC) and lung-deposited particle surface area concentration (PSC) with cause-specific daily mortality in contrast to PM₁₀.

METHODS

We used time-series data (March 2009-December 2014) on daily natural, cardiovascular, and respiratory mortality (NM, CVM, RM) of three adjacent cities in the Ruhr Area, Germany. Size-specific PNC (electric mobility diameter of 13.3-750 nm), PSC, and PM₁₀ were measured at an urban background monitoring site. In single- and multipollutant Poisson regression models, we estimated percentage change (95% confidence interval) [% (95% CI)] in mortality per interquartile range (IQR) in exposure at single-day (0-7) and aggregated lags (0-1, 2-3, 4-7), accounting for time trend, temperature, humidity, day of week, holidays, period of seasonal population decrease, and influenza.

RESULTS

PNC_100-750 and PSC were highly correlated and had similar immediate (lag0-1) and delayed (lag4-7) associations with NM and CVM, for example, 1.12% (95% CI: 0.09, 2.33) and 1.56% (95% CI: 0.22, 2.92) higher NM with IQR increases in PNC_100-750 at lag0-1 and lag4-7, respectfully, which were slightly stronger then associations with IQR increases in PM₁₀. Positive associations between PNC and NM were strongest for accumulation mode particles (PNC 100-500 nm), and for larger UFPs (PNC 50-100 nm). Associations between NM and PNC_<100 changed little after adjustment for O₃ or PM₁₀, but were more sensitive to adjustment for NO₂.

CONCLUSION

Size-specific PNC (50-500 nm) and lung-deposited PSC were associated with natural and cardiovascular mortality in the Ruhr Area. Although associations were similar to those estimated for an IQR increase in PM₁₀, particle number size distributions can be linked to emission sources, and thus may be more informative for potential public health interventions. Moreover, PSC could be used as an alternative metric that integrates particle size distribution as well as deposition efficiency. https://doi.org/10.1289/EHP2054.

Estimating Acute Cardiovascular Effects of Ambient PM2.5 Metals

BACKGROUND

Few epidemiologic studies have investigated health effects of water-soluble fractions of PM_2.5 metals, the more biologically accessible fractions of metals, in their attempt to identify health-relevant components of ambient PM_2.5.

OBJECTIVES

In this study, we estimated acute cardiovascular effects of PM_2.5 components in an urban population, including a suite of water-soluble metals that are not routinely measured at the ambient level.

METHODS

Ambient concentrations of criteria gases, PM_2.5, and PM_2.5 components were measured at a central monitor in Atlanta, Georgia, during 1998-2013, with some PM_2.5 components only measured during 2008-2013. In a time-series framework using Poisson regression, we estimated associations between these pollutants and daily counts of emergency department (ED) visits for cardiovascular diseases in the five-county Atlanta area.

RESULTS

Among the PM_2.5 components we examined during 1998-2013, water-soluble iron had the strongest estimated effect on cardiovascular outcomes [R͡R=1.012 (95% CI: 1.005, 1.019), per interquartile range increase (20.46ng/m³)]. The associations for PM_2.5 and other PM_2.5 components were consistent with the null when controlling for water-soluble iron. Among PM_2.5 components that were only measured during 2008-2013, water-soluble vanadium was associated with cardiovascular ED visits [R͡R=1.012 (95% CI: 1.000, 1.025), per interquartile range increase (0.19ng/m³)].

CONCLUSIONS

Our study suggests cardiovascular effects of certain water-soluble metals, particularly water-soluble iron. The observed associations with water-soluble iron may also point to certain aspects of traffic pollution, when processed by acidifying sulfate, as a mixture harmful for cardiovascular health. https://doi.org/10.1289/EHP2182.

Finely Resolved On-Road PM2.5 and Estimated Premature Mortality in Central North Carolina

To quantify the on-road PM_2.5 -related premature mortality at a national scale, previous approaches to estimate concentrations at a 12-km × 12-km or larger grid cell resolution may not fully characterize concentration hotspots that occur near roadways and thus the areas of highest risk. Spatially resolved concentration estimates from on-road emissions to capture these hotspots may improve characterization of the associated risk, but are rarely used for estimating premature mortality. In this study, we compared the on-road PM_2.5 -related premature mortality in central North Carolina with two different concentration estimation approaches-(i) using the Community Multiscale Air Quality (CMAQ) model to model concentration at a coarser resolution of a 36-km × 36-km grid resolution, and (ii) using a hybrid of a Gaussian dispersion model, CMAQ, and a space-time interpolation technique to provide annual average PM_2.5 concentrations at a Census-block level (∼105,000 Census blocks). The hybrid modeling approach estimated 24% more on-road PM_2.5 -related premature mortality than CMAQ. The major difference is from the primary on-road PM_2.5 where the hybrid approach estimated 2.5 times more primary on-road PM_2.5 -related premature mortality than CMAQ due to predicted exposure hotspots near roadways that coincide with high population areas. The results show that 72% of primary on-road PM_2.5 premature mortality occurs within 1,000 m from roadways where 50% of the total population resides, highlighting the importance to characterize near-road primary PM_2.5 and suggesting that previous studies may have underestimated premature mortality due to PM_2.5 from traffic-related emissions.

A cost-benefit analysis of a pellet boiler with electrostatic precipitator versus conventional biomass technology: A case study of an institutional boiler in Syracuse, New York

BACKGROUND

Biomass facilities have received increasing attention as a strategy to increase the use of renewable fuels and decrease greenhouse gas emissions from the electric generation and heating sectors, but these facilities can potentially increase local air pollution and associated health effects. Comparing the economic costs and public health benefits of alternative biomass fuel, heating technology, and pollution control technology options provides decision-makers with the necessary information to make optimal choices in a given location.

METHODS

For a case study of a combined heat and power biomass facility in Syracuse, New York, we used stack testing to estimate emissions of fine particulate matter (PM_2.5) for both the deployed technology (staged combustion pellet boiler with an electrostatic precipitator) and a conventional alternative (wood chip stoker boiler with a multicyclone). We used the atmospheric dispersion model AERMOD to calculate the contribution of either fuel-technology configuration to ambient primary PM_2.5 in a 10km×10km region surrounding the facility, and we quantified the incremental contribution to population mortality and morbidity. We assigned economic values to health outcomes and compared the health benefits of the lower-emitting technology with the incremental costs.

RESULTS

In total, the incremental annualized cost of the lower-emitting pellet boiler was $190,000 greater, driven by a greater cost of the pellet fuel and pollution control technology, offset in part by reduced fuel storage costs. PM_2.5 emissions were a factor of 23 lower with the pellet boiler with electrostatic precipitator, with corresponding differences in contributions to ambient primary PM_2.5 concentrations. The monetary value of the public health benefits of selecting the pellet-fired boiler technology with electrostatic precipitator was $1.7 million annually, greatly exceeding the differential costs even when accounting for uncertainties. Our analyses also showed complex spatial patterns of health benefits given non-uniform age distributions and air pollution levels.

CONCLUSIONS

The incremental investment in a lower-emitting staged combustion pellet boiler with an electrostatic precipitator was well justified by the population health improvements over the conventional wood chip technology with a multicyclone, even given the focus on only primary PM_2.5 within a small spatial domain. Our analytical framework could be generalized to other settings to inform optimal strategies for proposed new facilities or populations.

Air pollution and cardiovascular events at labor and delivery: a case-crossover analysis

PURPOSE

In this case-crossover study, we investigated the odds of having a labor/delivery with cardiovascular event (i.e., ischemic heart disease, stroke, heart failure, cardiac arrest/failure, and other or unspecified cardiovascular events) associated with acute exposure to common air pollutants.

METHODS

We selected 680 women with singleton pregnancy and cardiovascular events at labor/delivery from 12 U.S. clinical sites (2002-2008). Exposures to six criteria air pollutants, six particulate constituents, and 26 air toxics were obtained using modified Community Multiscale Air Quality models. Conditional logistic regression models calculated the odds ratio (OR) and 95% confidence intervals (CI) comparing exposures during the day of delivery, the week before delivery, and each of the days of the week before delivery to two control periods before and after.

RESULTS

An interquartile range increase in particulate matter (PM) ≤2.5 microns and nitric oxide exposures during the week before delivery was associated with an 11% (OR 1.11, 95% CI: 1.01-1.23) and 21% (OR 1.21, 95% CI: 1.04-1.42) increased cardiovascular events odds, respectively. These pollutants, sulfur dioxide, carbon monoxide, PM ≤ 10 microns, and some PM constituents showed associations with event odds for days 0, 1, 5, and 6 before delivery. Inverse associations were observed for O₃ and some PM constituents as well as air toxics.

CONCLUSIONS

Cardiovascular events at labor/delivery merit more attention in relation to air pollution.

Ozone and childhood respiratory disease in three US cities: evaluation of effect measure modification by neighborhood socioeconomic status using a Bayesian hierarchical approach

BACKGROUND

Ground-level ozone is a potent airway irritant and a determinant of respiratory morbidity. Susceptibility to the health effects of ambient ozone may be influenced by both intrinsic and extrinsic factors, such as neighborhood socioeconomic status (SES). Questions remain regarding the manner and extent that factors such as SES influence ozone-related health effects, particularly across different study areas.

METHODS

Using a 2-stage modeling approach we evaluated neighborhood SES as a modifier of ozone-related pediatric respiratory morbidity in Atlanta, Dallas, & St. Louis. We acquired multi-year data on emergency department (ED) visits among 5-18 year olds with a primary diagnosis of respiratory disease in each city. Daily concentrations of 8-h maximum ambient ozone were estimated for all ZIP Code Tabulation Areas (ZCTA) in each city by fusing observed concentration data from available network monitors with simulations from an emissions-based chemical transport model. In the first stage, we used conditional logistic regression to estimate ZCTA-specific odds ratios (OR) between ozone and respiratory ED visits, controlling for temporal trends and meteorology. In the second stage, we combined ZCTA-level estimates in a Bayesian hierarchical model to assess overall associations and effect modification by neighborhood SES considering categorical and continuous SES indicators (e.g., ZCTA-specific levels of poverty). We estimated ORs and 95% posterior intervals (PI) for a 25 ppb increase in ozone.

RESULTS

The hierarchical model combined effect estimates from 179 ZCTAs in Atlanta, 205 ZCTAs in Dallas, and 151 ZCTAs in St. Louis. The strongest overall association of ozone and pediatric respiratory disease was in Atlanta (OR = 1.08, 95% PI: 1.06, 1.11), followed by Dallas (OR = 1.04, 95% PI: 1.01, 1.07) and St. Louis (OR = 1.03, 95% PI: 0.99, 1.07). Patterns of association across levels of neighborhood SES in each city suggested stronger ORs in low compared to high SES areas, with some evidence of non-linear effect modification.

CONCLUSIONS

Results suggest that ozone is associated with pediatric respiratory morbidity in multiple US cities; neighborhood SES may modify this association in a non-linear manner. In each city, children living in low SES environments appear to be especially vulnerable given positive ORs and high underlying rates of respiratory morbidity.

A review of biomass burning: Emissions and impacts on air quality, health and climate in China

Biomass burning (BB) is a significant air pollution source, with global, regional and local impacts on air quality, public health and climate. Worldwide an extensive range of studies has been conducted on almost all the aspects of BB, including its specific types, on quantification of emissions and on assessing its various impacts. China is one of the countries where the significance of BB has been recognized, and a lot of research efforts devoted to investigate it, however, so far no systematic reviews were conducted to synthesize the information which has been emerging. Therefore the aim of this work was to comprehensively review most of the studies published on this topic in China, including literature concerning field measurements, laboratory studies and the impacts of BB indoors and outdoors in China. In addition, this review provides insights into the role of wildfire and anthropogenic BB on air quality and health globally. Further, we attempted to provide a basis for formulation of policies and regulations by policy makers in China.

Comparison of Health Impact of Air Pollution Between China and Other Countries

Air pollution is the world's largest single environmental risk according to the World Health Organization (WHO), which caused around seven million deaths in 2012. Extensive epidemiological studies have been carried out worldwide to examine the health impacts of ambient air pollution, consistently demonstrating significant health impacts of ambient air pollution. Air pollution problem in China is especially serious; it has become the fourth biggest threat to the health of the Chinese people. In this review, we summarized existing literature, compared health impact of air pollution between China and other countries, and found substantial heterogeneity in the risk estimates of air pollution. The effect heterogeneities may be due to the differences in the characteristics of populations (e.g., the proportion of the elder population and people with preexisting diseases), exposure profile (e.g., air pollution concentrations and composition), and regional climate. Although the magnitude of relative risk estimates of air pollution is generally similar with that in other parts of the world, air pollution is one of China's most serious environmental health problems given the huge number of people exposed to high concentration levels of air pollution in China.

Chemical composition and source apportionment of size fractionated particulate matter in Cleveland, Ohio, USA

The Cleveland airshed comprises a complex mixture of industrial source emissions that contribute to periods of non-attainment for fine particulate matter (PM_2.5) and are associated with increased adverse health outcomes in the exposed population. Specific PM sources responsible for health effects however are not fully understood. Size-fractionated PM (coarse, fine, and ultrafine) samples were collected using a ChemVol sampler at an urban site (G.T. Craig (GTC)) and rural site (Chippewa Lake (CLM)) from July 2009 to June 2010, and then chemically analyzed. The resulting speciated PM data were apportioned by EPA positive matrix factorization to identify emission sources for each size fraction and location. For comparisons with the ChemVol results, PM samples were also collected with sequential dichotomous and passive samplers, and evaluated for source contributions to each sampling site. The ChemVol results showed that annual average concentrations of PM, elemental carbon, and inorganic elements in the coarse fraction at GTC were ∼2, ∼7, and ∼3 times higher than those at CLM, respectively, while the smaller size fractions at both sites showed similar annual average concentrations. Seasonal variations of secondary aerosols (e.g., high NO₃^- level in winter and high SO₄^2- level in summer) were observed at both sites. Source apportionment results demonstrated that the PM samples at GTC and CLM were enriched with local industrial sources (e.g., steel plant and coal-fired power plant) but their contributions were influenced by meteorological conditions and the emission source's operation conditions. Taken together the year-long PM collection and data analysis provides valuable insights into the characteristics and sources of PM impacting the Cleveland airshed in both the urban center and the rural upwind background locations. These data will be used to classify the PM samples for toxicology studies to determine which PM sources, species, and size fractions are of greatest health concern.

Association between fine particulate matter chemical constituents and airway inflammation: A panel study among healthy adults in China

BACKGROUND

Ambient fine particulate matter (PM2.5) air pollution has been associated with increased airway inflammation, but the roles of various PM2.5 constituents remain to be determined.

OBJECTIVES

To investigate the acute effects of PM2.5 constituents on fractional exhaled nitric oxide (FeNO), a well-established biomarker of respiratory inflammation.

METHODS

A longitudinal panel study was performed among 32 healthy young adults in Shanghai, China from January 12th to February 6th, 2015. FeNO was repeatedly measured, 6-8 times per subject. Real-time mass concentration of ambient PM2.5 and chemical constituents were obtained from a nearby monitoring station. Linear mixed-effect models were applied to evaluate the association between FeNO and PM2.5 constituents, with the adjustment of age, gender, body mass index, temperature, relative humidity and day of week. The robustness of constituents' effects was also evaluated.

RESULTS

A total of 234 effective measurements of FeNO were obtained with a geometric mean of 13.1 ppb. The PM2.5-FeNO associations were strongest at lags of 0-6h and diminished at lags longer than 12h. An interquartile range increase in PM2.5 constituents (NH4(+), NO3(-), K(+), SO4(2-) and elemental carbon) at lags of 0-6h were significantly associated with increments in FeNO by 12.3%, 11.3%, 11.1%, 9.6% and 10.7%, respectively. After controlling for PM2.5 total mass and the colinearity, only elemental carbon remained significant.

CONCLUSION

Several chemical constituents of PM2.5 may impact FeNO following acute exposure. Elemental carbon in particular may be the primary component responsible for increased airway inflammation.

Short-term exposure to ambient particulate matter and emergency ambulance dispatch for acute illness in Japan

Short-term exposure to air pollution may be linked to negative health outcomes that require an emergency medical response. However, few studies have been undertaken on this phenomenon to date. The aim of this study therefore was to examine the association between short-term exposure to ambient suspended particulate matter (SPM) and emergency ambulance dispatches (EADs) for acute illness in Japan. Daily EAD data, daily mean SPM and meteorological data were obtained for four prefectures in the Kanto region of Japan for the period from 2007 to 2011. The area-specific association between daily EAD for acute illness and SPM was explored using generalized linear models while controlling for ambient temperature, relative humidity, seasonality, long-term trends, day of the week and public holidays. Stratified analyses were conducted to evaluate the modifying effects of age, sex and medical conditions. Area-specific estimates were combined using meta-analyses. For the total study period the mean level of SPM was 23.7μg/m(3). In general, higher SPM was associated with a significant increase in EAD for acute illness [estimated pooled relative risk (RR): 1.008, 95% CI: 1.007 to 1.010 per 10μg/m(3) increase in SPM at lag 0-1]. The effects of SPM on EAD for acute illness were significantly greater for moderate/mild medical conditions (e.g. cases that resulted in <3weeks hospitalization or no hospitalization) when compared to severe medical conditions (e.g. critical cases, and cases that led to >3weeks hospitalization or which resulted in death). Using EAD data, this study has shown the adverse health effects of ambient air pollution. This highlights the importance of reducing the level of air pollution in order to maintain population health and well-being.

Associations of Source-Specific Fine Particulate Matter With Emergency Department Visits in California

While many studies have investigated the health effects associated with acute exposure to fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5)), very few have considered the risks of specific sources of PM2.5 We used city-specific source apportionment in 8 major metropolitan areas in California from 2005-2009 to examine the associations of source-specific PM2.5 exposures from vehicular emissions, biomass burning, soil, and secondary nitrate and sulfate sources with emergency department visits (EDVs) for cardiovascular and respiratory diseases, including 7 subclasses. Using a case-crossover analysis, we observed associations of vehicular emissions with all cardiovascular EDVs (excess risk = 1.6%, 95% confidence interval: 0.9, 2.4 for an interquartile-range increment of 2.8 µg/m(3)) and with several subclasses of disease. In addition, vehicular emissions, biomass burning, and soil sources were associated with all respiratory EDVs and with EDVs for asthma. The soil source, which includes resuspended road dust, generated the highest risk estimate for asthma (excess risk = 4.5%, 95% confidence interval: 1.1, 8.0). Overall, our results provide additional evidence of the public health consequences of exposure to specific sources of PM2.5 and indicate that some sources of PM2.5 may pose higher risks than the overall PM2.5 mass.

An Analysis of Costs and Health Co-Benefits for a U.S. Power Plant Carbon Standard

Reducing carbon dioxide (CO2) emissions from power plants can have important "co-benefits" for public health by reducing emissions of air pollutants. Here, we examine the costs and health co-benefits, in monetary terms, for a policy that resembles the U.S. Environmental Protection Agency's Clean Power Plan. We then examine the spatial distribution of the co-benefits and costs, and the implications of a range of cost assumptions in the implementation year of 2020. Nationwide, the total health co-benefits were $29 billion 2010 USD (95% CI: $2.3 to $68 billion), and net co-benefits under our central cost case were $12 billion (95% CI: -$15 billion to $51 billion). Net co-benefits for this case in the implementation year were positive in 10 of the 14 regions studied. The results for our central case suggest that all but one region should experience positive net benefits within 5 years after implementation.

Current Methods and Challenges for Epidemiological Studies of the Associations Between Chemical Constituents of Particulate Matter and Health

Epidemiological studies have been critical for estimating associations between exposure to ambient particulate matter (PM) air pollution and adverse health outcomes. Because total PM mass is a temporally and spatially varying mixture of constituents with different physical and chemical properties, recent epidemiological studies have focused on PM constituents. Most studies have estimated associations between PM constituents and health using the same statistical methods as in studies of PM mass. However, these approaches may not be sufficient to address challenges specific to studies of PM constituents, namely assigning exposure, disentangling health effects, and handling measurement error. We reviewed large, population-based epidemiological studies of PM constituents and health and describe the statistical methods typically applied to address these challenges. Development of statistical methods that simultaneously address multiple challenges, for example, both disentangling health effects and handling measurement error, could improve estimation of associations between PM constituents and adverse health outcomes.

Short-term exposure to traffic-related air pollution and daily mortality in London, UK

Epidemiological studies have linked daily concentrations of urban air pollution to mortality, but few have investigated specific traffic sources that can inform abatement policies. We assembled a database of >100 daily, measured and modelled pollutant concentrations characterizing air pollution in London between 2011 and 2012. Based on the analyses of temporal patterns and correlations between the metrics, knowledge of local emission sources and reference to the existing literature, we selected, a priori, markers of traffic pollution: oxides of nitrogen (general traffic); elemental and black carbon (EC/BC) (diesel exhaust); carbon monoxide (petrol exhaust); copper (tyre), zinc (brake) and aluminium (mineral dust). Poisson regression accounting for seasonality and meteorology was used to estimate the percentage change in risk of death associated with an interquartile increment of each pollutant. Associations were generally small with confidence intervals that spanned 0% and tended to be negative for cardiovascular mortality and positive for respiratory mortality. The strongest positive associations were for EC and BC adjusted for particle mass and respiratory mortality, 2.66% (95% confidence interval: 0.11, 5.28) and 2.72% (0.09, 5.42) per 0.8 and 1.0 μg/m(3), respectively. These associations were robust to adjustment for other traffic metrics and regional pollutants, suggesting a degree of specificity with respiratory mortality and diesel exhaust containing EC/BC.

Short-term exposure to traffic-related air pollution and daily mortality in London, UK

Epidemiological studies have linked daily concentrations of urban air pollution to mortality, but few have investigated specific traffic sources that can inform abatement policies. We assembled a database of >100 daily, measured and modelled pollutant concentrations characterizing air pollution in London between 2011 and 2012. Based on the analyses of temporal patterns and correlations between the metrics, knowledge of local emission sources and reference to the existing literature, we selected, a priori, markers of traffic pollution: oxides of nitrogen (general traffic); elemental and black carbon (EC/BC) (diesel exhaust); carbon monoxide (petrol exhaust); copper (tyre), zinc (brake) and aluminium (mineral dust). Poisson regression accounting for seasonality and meteorology was used to estimate the percentage change in risk of death associated with an interquartile increment of each pollutant. Associations were generally small with confidence intervals that spanned 0% and tended to be negative for cardiovascular mortality and positive for respiratory mortality. The strongest positive associations were for EC and BC adjusted for particle mass and respiratory mortality, 2.66% (95% confidence interval: 0.11, 5.28) and 2.72% (0.09, 5.42) per 0.8 and 1.0 μg/m(3), respectively. These associations were robust to adjustment for other traffic metrics and regional pollutants, suggesting a degree of specificity with respiratory mortality and diesel exhaust containing EC/BC.

Assessing public health burden associated with exposure to ambient black carbon in the United States

Black carbon (BC) is a significant component of fine particulate matter (PM2.5) air pollution, which has been linked to a series of adverse health effects, in particular premature mortality. Recent scientific research indicates that BC also plays an important role in climate change. Therefore, controlling black carbon emissions provides an opportunity for a double dividend. This study quantifies the national burden of mortality and morbidity attributable to exposure to ambient BC in the United States (US). We use GEOS-Chem, a global 3-D model of atmospheric composition to estimate the 2010 annual average BC levels at 0.5×0.667° resolution, and then re-grid to 12-km grid resolution across the continental US. Using PM2.5 mortality risk coefficient drawn from the American Cancer Society cohort study, the numbers of deaths due to BC exposure were estimated for each 12-km grid, and then aggregated to the county, state and national level. Given evidence that BC particles may pose a greater risk on human health than other components of PM2.5, we also conducted sensitivity analysis using BC-specific risk coefficients drawn from recent literature. We estimated approximately 14,000 deaths to result from the 2010 BC levels, and hundreds of thousands of illness cases, ranging from hospitalizations and emergency department visits to minor respiratory symptoms. Sensitivity analysis indicates that the total BC-related mortality could be even significantly larger than the above mortality estimate. Our findings indicate that controlling BC emissions would have substantial benefits for public health in the US.