Triggering of cardiovascular hospital admissions by source specific fine particle concentrations in urban centers of New York State

Changes in the short-term relationship between air pollution and mortality in New York City, 1990-2019

Background

Few studies have examined how short-term associations between air pollution and mortality have evolved over recent decades when air quality has improved. Public health policy can benefit from timely information.

Methods

We applied time-series models to estimate the mortality impacts of ambient nitrogen dioxide (NO2), ozone (warm season only), and fine particulate matter (PM2.5) in 5-year moving time windows between 1990 and 2019 (2000–2019 for PM2.5) in New York City (NYC). We modeled full-year, warm (May through September) and cold (October through March) season NO2 and PM2.5, adjusting for temperature, temporal trends, day-of-week, and holidays. We also estimated Total Risk Index (TRI) to characterize changes in the combined risk from exposure to two and three pollutants.

Results

All three pollutants showed the strongest association at one lag day. Despite major declines in PM2.5 and NO2 levels over the study period, risk estimates showed no apparent trend, remaining generally positive, but became less precise over time as concentration variability also declined. The estimated overall 1-day lag percent excess risk for PM2.5 was 0.49% (95% confidence interval: 0.12, 0.86) per 10 µg/m3 24-hr average, and for NO2, 0.90% (0.30, 1.50) per 30 ppb daily 1-hr maximum for full year models. Ozone, which slightly increased over the period, had a 1-day lag risk estimate of 1.43% (0.56, 2.30) per 30 ppb daily 8-hr maximum. The TRI followed a similar pattern to individual pollutants’ estimates.

Conclusions

With no clear evidence of risk per unit increase changing over time, the reductions in PM2.5 and NO2 concentrations imply declines in excess deaths. Notably, ozone levels and health burden persist. NO2, which was most robustly associated with mortality and represents two major combustion sources—traffic and fossil fuel combustion in buildings—may be the most relevant indicator of energy transition progress in urban areas like NYC in the coming decade.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12940-025-01171-w.

Source apportionment of PM10 particles in the urban atmosphere using PMF and LPO-XGBoost

Atmospheric particulate matter (PM), as a leading part of air pollution, affects health in many ways. Thus, identifying and quantifying the contribution of atmospheric particulate matter sources of PM is vital for developing effective air quality management strategies. Positive Matrix Factorization (PMF) is one of the most common methods for source apportionment. However, PMF has some limitations, particularly its assumption that each source contributes linearly. In reality, some sources may exhibit nonlinear behaviors, which can compromise the accuracy of source apportionment. This study introduces a Lung Performance Optimization-based XGBoost (LPO-XGBoost) model, which leverages adaptive optimization principles inspired by lung function to enhance classic PM source apportionment. We demonstrate the potential for efficient, real-time application of the LPO-XGBoost model across 21 monitoring sites in 6 European countries. Trained and validated on extensive environmental datasets, the model is capable of predicting major pollution sources, including road traffic, biomass burning, crustal, industrial, nitrate-rich particles, sulfate-rich particles, heavy fuel oil, and sea salt. It outperforms other machine learning models with an overall predictive coefficient of determination (r2 = 0.88). Notably, the model performs exceptionally well in predicting sources such as sea salt (r2 = 0.97) and biomass burning (r2 = 0.89), but shows lower accuracy for the sulfate-rich particles source (r2 = 0.75). Comparative analyses with models including Random Forest (RF), Support Vector Machine (SVM), and their LPO-enhanced variants confirm that LPO-XGBoost provides the most reliable performance in estimating pollution source contributions, offering scalability and robustness ideal for high-time-resolution observational data. This model has significant potential to support targeted air quality management strategies. Future research should focus on expanding key species measurements at monitoring sites, ensuring consistent temporal coverage, and optimizing the model for improved mixed-source predictions to strengthen its applicability in comprehensive urban air quality assessments.

Mapping Source-Specific Air Pollution Exposures Using Positive Matrix Factorization Applied to Multipollutant Mobile Monitoring in Seattle, WA

Mobile monitoring strategies are increasingly used to provide fine spatial estimates of multiple air pollutant concentrations. This study demonstrates a novel approach using positive matrix factorization (PMF) applied to multipollutant mobile monitoring data to assess source-specific air pollution exposures and to estimate associated emission factors. Data were collected from one-year mobile monitoring, with an average of 26 repeated measures of size-resolved particle number counts (PNC), PM2.5, BC, NO2, and CO2 at 309 sites in Seattle from 2019 to 2020. PMF was used to characterize underlying source-related factors. The sources associated with these six factors included emissions from aviation, diesel trucks, gasoline/hybrid vehicles, oil combustion, wood combustion, and accumulation mode aerosols. Fuel-based emission factors for three transportation-related sources were also estimated. This study reveals that PNC of ultrafine particles with size <18, 18-42, and 42-178 nm was dominated by features associated with aircraft, diesel trucks, and both oil and wood combustion. Gasoline and hybrid vehicles contributed the most to CO2 and NO2 concentrations. This approach can also be extended to other metropolitan areas, enhancing the exposure assessment in epidemiology studies.

Source specific fine particles and rates of asthma and COPD healthcare encounters pre- and post-implementation of the Tier 3 vehicle emissions control regulations

We examined associations between seven source-specific PM2.5 concentrations and rates of asthma and COPD hospitalizations and emergency department (ED) visits in New York State and compared the changes in excess rates (ERs) between pre- (2014-2016) and post-implementation (2017-2019) of the Tier 3 automobile emission controls on new vehicles policy. A modified time-stratified case-crossover design and conditional logistic regression were employed to estimate the ERs of asthma and COPD hospitalizations and ED visits associated with interquartile range (IQR) increases in source-specific PM2.5 concentrations. The 7 PM2.5 sources were spark-ignition emissions (GAS), diesel (DIE), biomass burning (BB), road dust (RD), secondary nitrate (SN), secondary sulfate (SS), and pyrolyzed organic rich (OP). Residual PM2.5 (PM2.5 - specific source [e.g., GAS]), daily temperature, relative humidity, weekday, and holidays were included in the model. IQR increases in GAS, SS, RD, BB, and SN were associated with increased ERs of asthma ED visits (highest ERs: 0.5 %-3.1 %), while a negative association was observed with DIE and OP. The rate of asthma hospitalizations was associated with increased RD concentrations (ERs: 1.3 %-1.7 %). Both COPD ED visit and hospitalization rates were associated with increased OP (ERs: 2.1 %-3.4 %), and increased SS was positively associated with COPD ED visits (ER = 3.8 %). In summary, after Tier 3 implementation (2017-2019), we found lower ERs for COPD admissions associated with BB, RD, SN, and SS compared to 2014-2016. However, rates of asthma ED visits associated with source-specific PM2.5 concentrations were generally higher for all sources, except DIE, post- versus pre-implementation, requiring further research for validation.

Heterogeneity in the health effects of PM2.5 sources across the major metropolitan cities, South Korea: Significance of region-specific management

Ambient PM2.5, well-known for its adverse impacts on human health, is a very heterogeneous pollutant. Its chemical composition and attributable sources vary by region, influenced by meteorological and geographical conditions as well as emission sources. However, administrative policies are currently focused on mass concentrations. However, not all PM2.5 sources provide equally toxic particles. Thus, those sources that should be the focus of controls has not been the priority. In the present study, we conducted source apportionment utilizing positive matrix factorization (PMF) and investigated the association of PM2.5 source contributions with emergency department visits (EDVs) in major megacities in South Korea. Overall, an interquartile range (IQR) increment in source contribution increased the number of emergency room visits. Industry and coal combustion sources, marked by heavy metals, were principally associated with the adverse health impacts. However, the sources showing significant associations with EDVs differed across the study area. In addition, we found that region-specific relationships between PM2.5 sources and morbidity were plausible, considering the existence of relevant sources such as industrial complexes and coal-fired power plants. The analysis of source contributions according to wind conditions also supported the source-morbidity relationships. These findings suggest that administrative policies for PM2.5 control should be established and implemented considering region-specific characteristics of the links between PM2.5 sources and health impacts to maximize the control's public health effects. Furthermore, the results of the present study indicate that PMF was an effective method for linking acute exposure to PM2.5 source types with health outcomes to prioritize its sources.

A fingerprint of source-specific health risk of PM2.5-bound components over a coastal industrial city

The influence of specific local land-use activities (continuously redistributing elements across environments) and environmental conditions (altering the chemical composition of airborne particulate matter) on the intrinsic health risk of PM2.5 exposure is sparsely reported. To fill this gap, we employed a novel integrated approach to address the influence of short-term changes in source-specific PM2.5 composition on the exposure-response risk, while controlling for weather conditions. We combine receptor-based source apportionment with conditional logistic regression in a space-time-stratified case-crossover design. This approach is different from previous studies as it: i) controls the impact of spatiotemporal variations in air pollution and human mobility using multilocation-specific fixed and disjointed space-time strata ii) addresses the spatial heterogeneity of personal exposure separating its variable effect from other predictors by allowing different baseline hazards for each space-time stratum; iii) aligns case/control periods with strong/regular episodes of source-specific PM-multipollutant fingerprint contributions rather than health outcomes. This enabled comprehensive examination of the association between source-specific PM2.5-bound species and cardiorespiratory disease hospitalizations. The epidemiological findings were that primary anthropogenic emissions [industrial (ORs 2.5 - 4.8)] were associated with higher 1-day moving average PM-induced risks. Natural-related sources [fresh / aged sea salt aerosol, dust, soil resuspension] and secondary sulfate formation were consistently associated with higher health risks (ORs 1.0 - 1.54) after 1 to 5-days since exposure. The results emphasize the importance of source-specific air quality management in complex areas and our research provides an adaptable universal tool to support targeted place-based policy interventions to mitigate air pollution impacts on health.

PM2.5 and its components and respiratory disease healthcare encounters - Unanticipated increased exposure-response relationships in recent years after environmental policies

Prior studies reported excess rates (ERs) of cardiorespiratory events associated with short-term increases in PM2.5 concentrations, despite implementation of pollution-control policies. In 2017, Federal Tier 3 light-duty vehicle regulations began, and to-date there have been no assessments of population health effects of the policy. Using the NYS Statewide Planning and Research Cooperative System (SPARCS) database, we obtained hospitalizations and ED visits with a principal diagnosis of asthma or chronic obstructive pulmonary disease (COPD) for residents living within 15 miles of six urban PM2.5 monitoring sites in NYS (2014-2019). We used a time-stratified case-crossover design and conditional logistic regression (adjusting for ambient temperature, relative humidity, and weekday) to estimate associations between PM2.5, POC (primary organic carbon), SOC (secondary organic carbon), and rates of respiratory disease hospitalizations and emergency department (ED) visits from 2014 to 2019. We evaluated demographic disparities in these relative rates and compared changes in ERs before (2014-2016) and after Tier 3 implementation (2017-2019). Each interquartile range increase in PM2.5 was associated with increased ERs of asthma or COPD hospitalizations and ED visits in the previous 7 days (ERs ranged from 1.1%-3.1%). Interquartile range increases in POC were associated with increased rates of asthma ED visits (lag days 0-6: ER = 2.1%, 95% CI = 0.7%, 3.6%). Unexpectedly, the ERs of asthma admission and ED visits associated with PM2.5, POC, and SOC were higher during 2017-2019 (after Tier 3) than 2014-2016 (before Tier-3). Chronic obstructive pulmonary disease analyses showed similar patterns. Excess Rates were higher in children (<18 years; asthma) and seniors (≥65 years; COPD), and Black, Hispanic, and NYC residents. In summary, unanticipated increases in asthma and COPD ERs after Tier-3 implementation were observed, and demographic disparities in asthma/COPD and PM2.5, POC, and SOC associations were also observed. Future work should confirm findings and investigate triggering of respiratory events by source-specific PM.

Controlled human exposures: a review and comparison of the health effects of diesel exhaust and wood smoke

One of the most pressing issues in global health is air pollution. Emissions from traffic-related air pollution and biomass burning are two of the most common sources of air pollution. Diesel exhaust (DE) and wood smoke (WS) have been used as models of these pollutant sources in controlled human exposure (CHE) experiments. The aim of this review was to compare the health effects of DE and WS using results obtained from CHE studies. A total of 119 CHE-DE publications and 25 CHE-WS publications were identified for review. CHE studies of DE generally involved shorter exposure durations and lower particulate matter concentrations, and demonstrated more potent dysfunctional outcomes than CHE studies of WS. In the airways, DE induces neutrophilic inflammation and increases airway hyperresponsiveness, but the effects of WS are unclear. There is strong evidence that DE provokes systemic oxidative stress and inflammation, but less evidence exists for WS. Exposure to DE was more prothrombotic than WS. DE generally increased cardiovascular dysfunction, but limited evidence is available for WS. Substantial heterogeneity in experimental methodology limited the comparison between studies. In many areas, outcomes of WS exposures tended to trend in similar directions to those of DE, suggesting that the effects of DE exposure may be useful for inferring possible responses to WS. However, several gaps in the literature were identified, predominantly pertaining to elucidating the effects of WS exposure. Future studies should strongly consider performing head-to-head comparisons between DE and WS using a CHE design to determine the differential effects of these exposures.

A case-crossover study of ST-elevation myocardial infarction and organic carbon and source-specific PM2.5 concentrations in Monroe County, New York

Background

Previous work reported increased rates of cardiovascular hospitalizations associated with increased source-specific PM2.5 concentrations in New York State, despite decreased PM2.5 concentrations. We also found increased rates of ST elevation myocardial infarction (STEMI) associated with short-term increases in concentrations of ultrafine particles and other traffic-related pollutants in the 2014-2016 period, but not during 2017-2019 in Rochester. Changes in PM2.5 composition and sources resulting from air quality policies (e.g., Tier 3 light-duty vehicles) may explain the differences. Thus, this study aimed to estimate whether rates of STEMI were associated with organic carbon and source-specific PM2.5 concentrations.

Methods

Using STEMI patients treated at the University of Rochester Medical Center, compositional and source-apportioned PM2.5 concentrations measured in Rochester, a time-stratified case-crossover design, and conditional logistic regression models, we estimated the rate of STEMI associated with increases in mean primary organic carbon (POC), secondary organic carbon (SOC), and source-specific PM2.5 concentrations on lag days 0, 0-3, and 0-6 during 2014-2019.

Results

The associations of an increased rate of STEMI with interquartile range (IQR) increases in spark-ignition emissions (GAS) and diesel (DIE) concentrations in the previous few days were not found from 2014 to 2019. However, IQR increases in GAS concentrations were associated with an increased rate of STEMI on the same day in the 2014-2016 period (Rate ratio [RR] = 1.69; 95% CI = 0.98, 2.94; 1.73 μg/m3). In addition, each IQR increase in mean SOC concentration in the previous 6 days was associated with an increased rate of STEMI, despite imprecision (RR = 1.14; 95% CI = 0.89, 1.45; 0.42 μg/m3).

Conclusion

Increased SOC concentrations may be associated with increased rates of STEMI, while there seems to be a declining trend in adverse effects of GAS on triggering of STEMI. These changes could be attributed to changes in PM2.5 composition and sources following the Tier 3 vehicle introduction.

Spatial variability of pollution source contributions during two (2012-2013 and 2018-2019) sampling campaigns at ten sites in Los Angeles basin

This study assessed the spatial variability of PM2.5 source contributions across ten sites located in the South Coast Air Basin, California. Eight pollution sources and their contributions were obtained using positive matrix factorization (PMF) from the PM2.5 compositional data collected during the two sampling campaigns (2012/13 and 2018/19) of the Multiple Air Toxics Exposure Study (MATES). The identified sources were "gasoline vehicles", "aged sea salt", "biomass burning", "secondary nitrate", "secondary sulfate", "diesel vehicles", "soil/road dust" and "OP-rich". Among them, "gasoline vehicle" was the largest contributor to the PM2.5 mass. The spatial distributions of source contributions to PM2.5 at the sites were characterized by the Pearson correlation coefficients as well as coefficients of determination and divergence. The highest spatial variability was found for the contributions from the "OP-rich" source in both MATES campaigns suggesting varying influences of the wildfires in the Los Angeles Basin. Alternatively, the smallest spatial variabilities were observed for the contributions of the "secondary sulfate" and "aged sea salt" sources resolved for the MATES campaign in 2012/13. The "soil/road dust" contributions of the sites from the 2018/19 campaign were also highly correlated. Compared to the other sites, the source contribution patterns observed for Inland Valley and Rubidoux were the most diverse from the others likely due to their remote locations from the other sites, the major urban area, and the Pacific Ocean.

The relative contribution of PM2.5 components to the obstructive ventilatory dysfunction-insights from a large ventilatory function examination of 305,022 workers in southern China

BACKGROUND

The new round of WHO/ILO Joint Estimates of the Work-related Burden of Disease assessment requires futher research to provide more evidence, especially on the health impact of ambient air pollution around the workplace. However, the evidence linking obstructive ventilatory dysfunction (OVD) to fine particulate matter (PM2.5) and its chemical components in workers is very limited. Evidence is even more scarce on the interactive effects between occupational factors and particle exposures. We aimed to fill these gaps based on a large ventilatory function examination of workers in southern China.

METHODS

We conducted a cross-sectional study among 363,788 workers in southern China in 2020. The annual average concentration of PM2.5 and its components were evaluated around the workplace through validated spatiotemporal models. We used mixed-effect models to evaluate the risk of OVD related to PM2.5 and its components. Results were further stratified by basic characteristics and occupational factors.

FINDINGS

Among the 305,022 workers, 119,936 were observed with OVD. We found for each interquartile range (IQR) increase in PM2.5 concentration, the risk of OVD increased by 27.8 (95 % confidence interval (CI): 26.5-29.2 %). The estimates were 10.9 % (95 %CI: 9.7-12.1 %), 15.8 % (95 %CI: 14.5-17.2 %), 2.6 % (95 %CI: 1.4-3.8 %), 17.1 % (95 %CI: 15.9-18.4 %), and 11 % (95 %CI: 9.9-12.2 %), respectively, for each IQR increment in sulfate, nitrate, ammonium salt, organic matter and black carbon. We observed greater effect estimates among females, younger workers, workers with a length of service of 24-45 months, and professional skill workers. Furthermore, it is particularly noteworthy that the noise-exposed workers, high-temperature-exposed workers, and less-dust-exposed workers were at a 5.7-68.2 % greater risk than others.

INTERPRETATION

PM2.5 and its components were significantly associated with an increased risk of OVD, with stronger links among certain vulnerable subgroups.

Indoor Air Sources of Outdoor Air Pollution: Health Consequences, Policy, and Recommendations: An Official American Thoracic Society Workshop Report

Indoor sources of air pollution worsen indoor and outdoor air quality. Thus, identifying and reducing indoor pollutant sources would decrease both indoor and outdoor air pollution, benefit public health, and help address the climate crisis. As outdoor sources come under regulatory control, unregulated indoor sources become a rising percentage of the problem. This American Thoracic Society workshop was convened in 2022 to evaluate this increasing proportion of indoor contributions to outdoor air quality. The workshop was conducted by physicians and scientists, including atmospheric and aerosol scientists, environmental engineers, toxicologists, epidemiologists, regulatory policy experts, and pediatric and adult pulmonologists. Presentations and discussion sessions were centered on 1) the generation and migration of pollutants from indoors to outdoors, 2) the sources and circumstances representing the greatest threat, and 3) effective remedies to reduce the health burden of indoor sources of air pollution. The scope of the workshop was residential and commercial sources of indoor air pollution in the United States. Topics included wood burning, natural gas, cooking, evaporative volatile organic compounds, source apportionment, and regulatory policy. The workshop concluded that indoor sources of air pollution are significant contributors to outdoor air quality and that source control and filtration are the most effective measures to reduce indoor contributions to outdoor air. Interventions should prioritize environmental justice: Households of lower socioeconomic status have higher concentrations of indoor air pollutants from both indoor and outdoor sources. We identify research priorities, potential health benefits, and mitigation actions to consider (e.g., switching from natural gas to electric stoves and transitioning to scent-free consumer products). The workshop committee emphasizes the benefits of combustion-free homes and businesses and recommends economic, legislative, and education strategies aimed at achieving this goal.

Analysis of PM2.5 inorganic and organic constituents to resolve contributing sources in Seoul, South Korea and Beijing, China and their possible associations with cytokine IL-8

China and South Korea are the most polluted countries in East Asia due to significant urbanization and extensive industrial activities. As neighboring countries, collaborative management plans to maximize public health in both countries can be helpful in reducing transboundary air pollution. To support such planning, PM2.5 inorganic and organic species were determined in simultaneously collected PM2.5 integrated filters. The resulting data were used as inputs to positive matrix factorization, which identified nine sources at the ambient air monitoring sites in both sites. Secondary nitrate, secondary sulfate/oil combustion, soil, mobile, incinerator, biomass burning, and secondary organic carbon (SOC) were found to be sources at both sampling sites. Industry I and II were only identified in Seoul, whereas combustion and road dust sources were only identified in Beijing. A subset of samples was selected for exposure assessment. The expression levels of IL-8 were significantly higher in Beijing (167.7 pg/mL) than in Seoul (72.7 pg/mL). The associations between the PM2.5 chemical constituents and its contributing sources with PM2.5-induced inflammatory cytokine (interleukin-8, IL-8) levels in human bronchial epithelial cells were investigated. For Seoul, the soil followed by the secondary nitrate and the biomass burning showed increase with IL-8 production. However, for the Beijing, the secondary nitrate exhibited the highest association with IL-8 production and SOC and biomass burning showed modest increase with IL-8. As one of the highest contributing sources in both cities, secondary nitrate showed an association with IL-8 production. The soil source having the strongest association with IL-8 production was found only for Seoul, whereas SOC showed a modest association only for Beijing. This study can provide the scientific basis for identifying the sources to be prioritized for control to provide effective mitigation of particulate air pollution in each city and thereby improve public health.

Unpacking the factors contributing to changes in PM2.5-associated mortality in China from 2013 to 2019

From 2013 to 2019, a series of air pollution control actions significantly reduced PM2.5 pollution in China. Control actions included changes in activity levels, structural adjustment (SA) policy, energy and material saving (EMS) policy, and end-of-pipe (EOP) control in several sources, which have not been systematically studied in previous studies. Here, we integrate an emission inventory, a chemical transport model, a health impact assessment model, and a scenario analysis to quantify the contribution of each control action across a range of major emission sources to the changes in PM2.5 concentrations and associated mortality in China from 2013 to 2019. Assuming equal toxicity of PM2.5 from all the sources, we estimate that PM2.5-related mortality decreased from 2.52 (95 % confidence interval, 2.13-2.88) to 1.94 (1.62-2.24) million deaths. Anthropogenic emission reductions and declining baseline incidence rates significantly contributed to health benefits, but population aging partially offset their impact. Among the major sources, controls on power plants and industrial boilers were responsible for the highest reduction in PM2.5-related mortality (∼80 %), followed by industrial processes (∼40 %), residential combustion (∼40 %), and transportation (∼30 %). However, considering the potentially higher relative risks of power plant PM2.5, the adverse effects avoided by their control could be ∼2.4 times the current estimation. Our power plant sensitivity analyses indicate that future estimates of source-specific PM2.5 health effects should incorporate variations in individual source PM2.5 effect coefficients when available. As for the control actions, while activity levels increased for most sources, SA policy significantly reduced the emissions in residential combustion and industrial boilers, and EOP control dominated the contribution in health benefits in most sources except residential combustion. Considering the emission reduction potential by source and control actions in 2019, our results suggest that promoting clean energy in residential combustion and enforcing more stringent EOP control in the iron and steel industry should be prioritized in the future.

Personal Exposure to Source-Specific Particulate Polycyclic Aromatic Hydrocarbons and Systemic Inflammation: A Cross-Sectional Study of Urban-Dwelling Older Adults in China

Environmental exposure to ambient polycyclic aromatic hydrocarbons (PAHs) can disturb the immune response. However, the evidence on adverse health effects caused by exposure to PAHs emitted from specific sources among different vulnerable subpopulations is limited. In this cross-sectional study, we aimed to evaluate whether exposure to source-specific PAHs could increase systemic inflammation in older adults. The present study included community-dwelling older adults and collected filter samples of personal exposure to PM2.5 during the winter of 2011. Blood samples were collected after the PM2.5 sample collection. We analyzed PM2.5 bound PAHs and serum inflammatory cytokines (interleukin (IL)1β, IL6, and tumor necrosis factor alpha levels. The Positive Matrix Factorization model was used to identify PAH sources. We used a linear regression model to assess the relative effects of source-specific PM2.5 bound PAHs on the levels of measured inflammatory cytokines. After controlling for confounders, exposure to PAHs emitted from biomass burning or diesel vehicle emission was significantly associated with increased serum inflammatory cytokines and systemic inflammation. These findings highlight the importance of considering exposure sources in epidemiological studies and controlling exposures to organic materials from specific sources.

Mortality risk from United States coal electricity generation

Policy-makers seeking to limit the impact of coal electricity-generating units (EGUs, also known as power plants) on air quality and climate justify regulations by quantifying the health burden attributable to exposure from these sources. We defined "coal PM2.5" as fine particulate matter associated with coal EGU sulfur dioxide emissions and estimated annual exposure to coal PM2.5 from 480 EGUs in the US. We estimated the number of deaths attributable to coal PM2.5 from 1999 to 2020 using individual-level Medicare death records representing 650 million person-years. Exposure to coal PM2.5 was associated with 2.1 times greater mortality risk than exposure to PM2.5 from all sources. A total of 460,000 deaths were attributable to coal PM2.5, representing 25% of all PM2.5-related Medicare deaths before 2009 and 7% after 2012. Here, we quantify and visualize the contribution of individual EGUs to mortality.

Research progress of different components of PM2.5 and ischemic stroke

PM2.5 is a nonhomogeneous mixture of complex components produced from multiple sources, and different components of this mixture have different chemical and biological toxicities, which results in the fact that the toxicity and hazards of PM2.5 may vary even for the same mass of PM2.5. Previous studies on PM2.5 and ischemic stroke have reached different or even opposing conclusions, and considering the heterogeneity of PM2.5 has led researchers to focus on the health effects of specific PM2.5 components. However, due to the complexity of PM2.5 constituents, assessing the association between exposure to specific PM2.5 constituents and ischemic stroke presents significant challenges. Therefore, this paper reviews and analyzes studies related to PM2.5 and its different components and ischemic stroke, aiming to understand the composition of PM2.5 and identify its harmful components, elucidate their relationship with ischemic stroke, and thus provide some insights and considerations for studying the biological mechanisms by which they affect ischemic stroke and for the prevention and treatment of ischemic stroke associated with different components of PM2.5.

Associations between source-apportioned PM2.5 and 30-day readmissions in heart failure patients

BACKGROUND

Air pollution exposure is a significant risk factor for morbidity and mortality, especially for those with pre-existing chronic disease. Previous studies highlighted the risks that long-term particulate matter exposure has for readmissions. However, few studies have evaluated source and component specific associations particularly among vulnerable patient populations.

OBJECTIVES

Use electronic health records from 5556 heart failure (HF) patients diagnosed between July 5, 2004 and December 31, 2010 that were part of the EPA CARES resource in conjunction with modeled source-specific fine particulate matter (PM2.5) to estimate the association between exposure to source and component apportioned PM2.5 at the time of HF diagnosis and 30-day readmissions.

METHODS

We used zero-inflated mixed effects Poisson models with a random intercept for zip code to model associations while adjusting for age at diagnosis, year of diagnosis, race, sex, smoking status, and neighborhood socioeconomic status. We undertook several sensitivity analyses to explore the impact of geocoding precision and other factors on associations and expressed associations per interquartile range increase in exposures.

RESULTS

We observed associations between 30-day readmissions and an interquartile range increase in gasoline- (16.9% increase; 95% confidence interval = 4.8%, 30.4%) and diesel-derived PM2.5 (9.9% increase; 95% confidence interval = 1.7%, 18.7%), and the secondary organic carbon component of PM2.5 (SOC; 20.4% increase; 95% confidence interval = 8.3%, 33.9%). Associations were stable in sensitivity analyses, and most consistently observed among Black study participants, those in lower income areas, and those diagnosed with HF at an earlier age. Concentration-response curves indicated a linear association for diesel and SOC. While there was some non-linearity in the gasoline concentration-response curve, only the linear component was associated with 30-day readmissions.

DISCUSSION

There appear to be source specific associations between PM2.5 and 30-day readmissions particularly for traffic-related sources, potentially indicating unique toxicity of some sources for readmission risks that should be further explored.

Overview of PM2.5 and health outcomes: Focusing on components, sources, and pollutant mixture co-exposure

PM_2.5 varies in source and composition over time and space as a complicated mixture. Consequently, the health effects caused by PM_2.5 varies significantly over time and generally exhibit significant regional variations. According to numerous studies, a notable relationship exists between PM_2.5 and the occurrence of many diseases, such as respiratory, cardiovascular, and nervous system diseases, as well as cancer. Therefore, a comprehensive understanding of the effect of PM_2.5 on human health is critical. The toxic effects of various PM_2.5 components, as well as the overall toxicity of PM_2.5 are discussed in this review to provide a foundation for precise PM_2.5 emission control. Furthermore, this review summarizes the synergistic effect of PM_2.5 and other pollutants, which can be used to draft effective policies.

Oxidative Potential Characterization of Different PM2.5 Sources and Components in Beijing and the Surrounding Region

With the implementation of air pollution control measures, the concentration of air pollutants in the North China Plain has exhibited a downward trend, but severe fine particulate matter (PM_2.5) pollution remains. PM_2.5 is harmful to human health, and the exploration of its source characteristics and potential hazards has become the key to mitigating PM_2.5 pollution. In this study, PM_2.5 samples were collected in Beijing and Gucheng during the summer of 2019. PM_2.5 components, its oxidative potential (OP), and health risks were characterized. The average PM_2.5 concentrations in Beijing and Gucheng during the sampling period were 34.0 ± 6.1 μg/m³ and 37.1 ± 6.9 μg/m³, respectively. The principal component analysis (PCA) results indicated that the main sources of PM_2.5 in Beijing were vehicle exhaust and secondary components and that the main sources in Gucheng were industrial emissions, dust and biomass combustion. The OP values were 91.6 ± 42.1 and 82.2 ± 47.1 pmol/(min·m³), respectively, at these two sites. The correlation between the chemical components and the OP values varied with the PM_2.5 sources at these two locations. The health risk assessment results demonstrated that Cr and As were potentially carcinogenic to all populations at both sites, and Cd posed a potential carcinogenic risk for adults in Gucheng. Regional cooperation regarding air pollution control must be strengthened to further reduce PM_2.5 pollution and its adverse health effects.

Ambient Air Pollution and Stroke: An Updated Review

Despite recent advances in treatment and prevention, stroke remains a leading cause of morbidity and mortality. There is a critical need to identify novel modifiable risk factors for disease, including environmental agents. A body of evidence has accumulated suggesting that elevated levels of ambient air pollutants may not only trigger cerebrovascular events in susceptible people (short-term exposures) but also increase the risk of future events (long-term average exposures). This review assesses the updated evidence for both short and long-term exposure to ambient air pollution as a risk factor for stroke incidence and outcomes. It discusses the potential pathophysiologic mechanisms and makes recommendations to mitigate exposure on a personal and community level. The evidence indicates that reduction in air pollutant concentrations represent a significant population-level opportunity to reduce risk of cerebrovascular disease.

Applying principal component pursuit to investigate the association between source-specific fine particulate matter and myocardial infarction hospitalizations in New York City

The association between fine particulate matter (PM_2.5) and cardiovascular outcomes is well established. To evaluate whether source-specific PM_2.5 is differentially associated with cardiovascular disease in New York City (NYC), we identified PM_2.5 sources and examined the association between source-specific PM_2.5 exposure and risk of hospitalization for myocardial infarction (MI).

Methods

We adapted principal component pursuit (PCP), a dimensionality-reduction technique previously used in computer vision, as a novel pattern recognition method for environmental mixtures to apportion speciated PM_2.5 to its sources. We used data from the NY Department of Health Statewide Planning and Research Cooperative System of daily city-wide counts of MI admissions (2007-2015). We examined associations between same-day, lag 1, and lag 2 source-specific PM_2.5 exposure and MI admissions in a time-series analysis, using a quasi-Poisson regression model adjusting for potential confounders.

Results

We identified four sources of PM_2.5 pollution: crustal, salt, traffic, and regional and detected three single-species factors: cadmium, chromium, and barium. In adjusted models, we observed a 0.40% (95% confidence interval [CI]: -0.21, 1.01%) increase in MI admission rates per 1 μg/m³ increase in traffic PM_2.5, a 0.44% (95% CI: -0.04, 0.93%) increase per 1 μg/m³ increase in crustal PM_2.5, and a 1.34% (95% CI: -0.46, 3.17%) increase per 1 μg/m³ increase in chromium-related PM_2.5, on average.

Conclusions

In our NYC study, we identified traffic, crustal dust, and chromium PM_2.5 as potentially relevant sources for cardiovascular disease. We also demonstrated the potential utility of PCP as a pattern recognition method for environmental mixtures.

Triggering of ST-elevation myocardial infarction by ultrafine particles in New York: Changes following Tier 3 vehicle introduction

BACKGROUND

Previously, we found increased rates of ST-elevation myocardial infarction (STEMI) associated with increased ultrafine particle (UFP; <100 nm) concentrations in the previous few hours in Rochester, New York. Relative rates were higher after air quality policies and a recession reduced pollutant concentrations (2014-2016 versus 2005-2013), suggesting PM composition had changed and the same PM mass concentration had become more toxic. Tier 3 light duty vehicles, which should produce less primary organic aerosols and oxidizable gaseous compounds, likely making PM less toxic, were introduced in 2017. Thus, we hypothesized we would observe a lower relative STEMI rate in 2017-2019 than 2014-2016.

METHODS

Using STEMI events treated at the University of Rochester Medical Center (2014-2019), UFP and other pollutants measured in Rochester, a case-crossover design, and conditional logistic regression models, we estimated the rate of STEMI associated with increased UFP and other pollutants in the previous hours and days in the 2014-2016 and 2017-2019 periods.

RESULTS

An increased rate of STEMI was associated with each 3111 particles/cm³ increase in UFP concentration in the previous hour in 2014-2016 (lag hour 0: OR = 1.22; 95% CI = 1.06, 1.39), but not in 2017-2019 (OR = 0.94; 95% CI = 0.80, 1.10). There were similar patterns for black carbon, UFP_11-50nm, and UFP_51-100nm. In contrast, increased rates of STEMI were associated with each 0.6 ppb increase in SO₂ concentration in the previous 120 h in both periods (2014-2016: OR = 1.26, 95% CI = 1.03, 1.55; 2017-2019: OR = 1.21, 95% CI = 0.87, 1.68).

CONCLUSIONS

Greater rates of STEMI were associated with short term increases in concentrations of UFP and other motor vehicle related pollutants before Tier 3 introduction (2014-2016), but not afterwards (2017-2019). This change may be due to changes in PM composition after Tier 3 introduction, as well as to increased exposure misclassification and greater underestimation of effects from 2017 to 2019.

How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state?

Background

Although power outage (PO) is one of the most important consequences of increasing weather extremes and the health impact of POs has been reported previously, studies on the neighborhood environment underlying the population vulnerability in such situations are limited. This study aimed to identify dominant neighborhood environmental predictors which modified the impact of POs on multiple health outcomes in New York State.

Methods

We applied a two-stage approach. In the first stage, we used time series analysis to determine the impact of POs (versus non-PO periods) on multiple health outcomes in each power operating division in New York State, 2001-2013. In the second stage, we classified divisions as risk-elevated and non-elevated, then developed predictive models for the elevation status based on 36 neighborhood environmental factors using random forest and gradient boosted trees.

Results

Consistent across different outcomes, we found predictors representing greater urbanization, particularly, the proportion of residents having access to public transportation (importance ranging from 4.9-15.6%), population density (3.3-16.1%), per capita income (2.3-10.7%), and the density of public infrastructure (0.8-8.5%), were associated with a higher possibility of risk elevation following power outages. Additionally, the percent of minority (-6.3-27.9%) and those with limited English (2.2-8.1%), the percent of sandy soil (6.5-11.8%), and average soil temperature (3.0-15.7%) were also dominant predictors for multiple outcomes. Spatial hotspots of vulnerability generally were located surrounding New York City and in the northwest, the pattern of which was consistent with socioeconomic status.

Conclusion

Population vulnerability during power outages was dominated by neighborhood environmental factors representing greater urbanization.

Associations Between Ambient Extreme Heat Exposure and Emergency Department Visits Related to Kidney Disease

RATIONALE & OBJECTIVE

Extreme heat exposure is associated with multiple diseases. However, our current understanding of the specific impact of extreme heat exposure on kidney disease is limited.

STUDY DESIGN

Case-crossover study.

SETTING & PARTICIPANTS

1,114,322 emergency department (ED) visits with a principal diagnosis of kidney disease were identified in New York state, 2005-2013.

EXPOSURE

Extreme heat exposure was defined as when the daily temperature exceeded the 90th percentile temperature of that month during the study period in the county.

OUTCOME

ED visits with a principal diagnosis of kidney disease and its subtypes (ICD-9 [International Classification of Diseases, Ninth Revision] codes 580-599, 788).

ANALYTICAL APPROACH

Extreme heat exposure on the ED visit days was compared with extreme heat exposure on control days using a conditional logistic regression model, controlling for humidity, air pollutants, and holidays. The excess risk of kidney disease was calculated for a week (lag days 0-6) after extreme heat exposure during the warm season (May through September). We also stratified our estimates by sociodemographic characteristics.

RESULTS

Extreme heat exposure was associated with a 1.7% (lag day 0) to 3.1% (lag day 2) higher risk of ED visits related to kidney disease; this association was stronger with a greater number of extreme heat exposure days in the previous week. The association with extreme heat exposure lasted for an entire week and was stronger in the transitional months (ie, May and September; excess rates ranged from 1.8% to 5.1%) rather than the summer months (June through August; excess rates ranged from 1.5% to 2.7%). The strength of association was greater among those with ED visits related to acute kidney injury, kidney stones, and urinary tract infections. Age and sex may modify the association between extreme heat exposure and ED visits.

LIMITATIONS

Individual exposure to heat-how long people were outside or whether they had access to air conditioning-was unknown.

CONCLUSIONS

Extreme heat exposure was significantly associated with a dose-dependent greater risk of ED visits for kidney disease.

Particle surface area, ultrafine particle number concentration, and cardiovascular hospitalizations

While the health impacts of larger particulate matter, such as PM₁₀ and PM_2.5, have been studied extensively, research regarding ultrafine particles (UFPs or PM_0.1) and particle surface area concentration (PSC) is lacking. This case-crossover study assessed the associations between exposure to PSC and UFP number concentration (UFPnc) and hospital admissions for cardiovascular diseases (CVDs) in New York State (NYS), 2013-2018. We used a time-stratified case-crossover design to compare the PSC and UFPnc levels between hospitalization days and control days (similar days without admissions) for each CVD case. We utilized NYS hospital discharge data to identify all CVD cases who resided in NYS. UFP simulation data from GEOS-Chem-APM, a state-of-the-art chemical transport model, was used to define PSC and UFPnc. Using a multi-pollutant model and conditional logistic regression, we assessed excess risk (ER)% per inter-quartile change of PSC and UFPnc after controlling for meteorological factors, co-pollutants, and time-varying variables. We found immediate and lasting associations between PSC and overall CVDs (lag0-lag0-6: ERs% (95% CI%) ranges: 0.4 (0.1,0.7) - 0.9 (0.7-1.2), and delayed and prolonged ERs%: 0.1-0.3 (95% CIs: 0.1-0.5) between UFPnc and CVDs (lag0-3-lag0-6). Exposure to larger PSC was associated with immediate ER increases in stroke, hypertension, and ischemic heart diseases (1.1%, 0.7%, 0.8%, respectively, all p < 0.05). The adverse effects of PSC on CVDs were highest among children (5-17 years old), in the fall and winter, and during cold temperatures. In conclusion, we found an immediate, lasting effects of PSC on overall CVDs and a delayed, prolonged impact of UFPnc. PSC was a more sensitive indicator than UFPnc. The PSC effects were higher among certain CVD subtypes, in children, in certain seasons, and during cold days. Further studies are needed to validate our findings and evaluate the long-term effects.

A Review of Road Traffic-Derived Non-Exhaust Particles: Emissions, Physicochemical Characteristics, Health Risks, and Mitigation Measures

Implementation of regulatory standards has reduced exhaust emissions of particulate matter from road traffic substantially in the developed world. However, nonexhaust particle emissions arising from the wear of brakes, tires, and the road surface, together with the resuspension of road dust, are unregulated and exceed exhaust emissions in many jurisdictions. While knowledge of the sources of nonexhaust particles is fairly good, source-specific measurements of airborne concentrations are few, and studies of the toxicology and epidemiology do not give a clear picture of the health risk posed. This paper reviews the current state of knowledge, with a strong focus on health-related research, highlighting areas where further research is an essential prerequisite for developing focused policy responses to nonexhaust particles.

Cardiopulmonary Mortality and Fine Particulate Air Pollution by Species and Source in a National U.S. Cohort

The purpose of this study was to estimate cardiopulmonary mortality associations for long-term exposure to PM_2.5 species and sources (i.e., components) within the U.S. National Health Interview Survey cohort. Exposures were estimated through a chemical transport model for six species (i.e., elemental carbon (EC), primary organic aerosols (POA), secondary organic aerosols (SOA), sulfate (SO₄), ammonium (NH₄), nitrate (NO₃)) and five sources of PM_2.5 (i.e., vehicles, electricity-generating units (EGU), non-EGU industrial sources, biogenic sources (bio), "other" sources). In single-pollutant models, we found positive, significant (p < 0.05) mortality associations for all components, except POA. After adjusting for remaining PM_2.5 (total PM_2.5 minus component), we found significant mortality associations for EC (hazard ratio (HR) = 1.36; 95% CI [1.12, 1.64]), SOA (HR = 1.11; 95% CI [1.05, 1.17]), and vehicle sources (HR = 1.06; 95% CI [1.03, 1.10]). HRs for EC, SOA, and vehicle sources were significantly larger in comparison to those for remaining PM_2.5 (per unit μg/m³). Our findings suggest that cardiopulmonary mortality associations vary by species and source, with evidence that EC, SOA, and vehicle sources are important contributors to the PM_2.5 mortality relationship. With further validation, these findings could facilitate targeted pollution regulations that more efficiently reduce air pollution mortality.

Effects of ambient air pollutants on hospital admissions and deaths for cardiovascular diseases: a time series analysis in Tehran

Short-term exposures to air pollution have been associated with various adverse health effects. In this study, we investigated the associations between ambient air pollutants with the number of hospital admissions and mortality from cardiovascular diseases (CVDs). This time series study was conducted in Tehran for the years 2014-2017 (1220 day). We collected the ambient air pollutant concentration data from the regulatory monitoring stations. The health data were obtained from the Ministry of Health and Medical Education. A distributed lag non-linear model (DLNM) was used for the analyses. Total CVDs and ischemic heart disease (IHD) admissions were associated with CO for each 1 mg/m³ increase at lags of 6 and 7 days. Also, there was a positive association between total CVDs (RR 1.01; 1.001 to 1.03), IHD (RR 1.04; 1.006 to 1.07), and cerebrovascular diseases (RR 1.03; 1.005 to 1.07) mortality with SO₂ at a lag of 4 days. PM_2.5 and PM₁₀ were associated with cerebrovascular disease admissions in females aged 16-65 years and 16 years and younger for each 10 µg/m³ increase, respectively. Short-term exposure to SO₂, NO₂, and CO was associated with hospital admissions and mortality for CVDs, IHD, cerebrovascular diseases, and other cardiovascular diseases at different lags. Moreover, females were more affected by ambient air pollutants than males in terms of their burden of CVDs. Therefore, identifying the likely harmful effects of pollutants given their current concentrations requires the planning and implementation of strategies to reduce air pollution.

Changing Emissions Results in Changed PM2.5 Composition and Health Impacts

In the period of 2005 to 2016, multiple air pollution control regulations have entered into effect in the United States at both the Federal and state level. In addition, economic changes have also occurred primarily in the electricity generation sector that substantially changed the emissions from this sector. This combination of policy implementations and economics has led to substantial reductions in PM2.5, its major constituents, and source specific PM2.5 concentrations across the New York State, particularly those of sulfate, nitrate, and primary organic carbon. However, secondary organic carbon and spark-ignition vehicular emission contributions have increased. Related studies of changes in health outcomes, the excess rates of emergency department visits and hospitalizations for a variety of cardiovascular and respiratory diseases and respiratory infections have increased per unit mass of PM2.5. It appears that the increased toxicity per unit mass was due to the reduction in low toxicity constituents such that the remaining mass had greater impacts on public health.

Associations between Source-Specific Fine Particulate Matter and Mortality and Hospital Admissions in Beijing, China

The health effects of PM_2.5 exposure have become a major public concern in developing countries. Identifying major PM_2.5 sources and quantifying the health effects at the population level are essential for controlling PM_2.5 pollution and formulating targeted emissions reduction policies. In the current study, we have obtained PM_2.5 mass data and used positive matrix factorization to identify the major sources of PM_2.5. We evaluated the relationship between short-term exposure to PM_2.5 sources and mortality or hospital admissions in Beijing, China, using 441 742 deaths and 9 420 305 hospital admissions from 2013 to 2018. We found positive associations for coal combustion and road dust sources with mortality. Increased hospital admission risks were significantly associated with sources of vehicle exhaust, coal combustion, secondary sulfates, and secondary nitrates. Compared to the cool season, excess mortality risk estimates of coal combustion source were significantly higher in the warm season. Our findings show that reducing more toxic sources of PM_2.5, especially coal emissions, and developing clean energy alternatives can have critical implications for improving air quality and protecting public health.

Prediction of the oxidation potential of PM2.5 exposures from pollutant composition and sources

The inherent oxidation potential (OP) of atmospheric particulate matter has been shown to be an important metric in assessing the biological activity of inhaled particulate matter and is associated with the composition of PM_2.5. The current study examined the chemical composition of 388 personal PM_2.5 samples collected from students and guards living in urban and suburban areas of Beijing, and assessed the ability to predict OP from the calculated metrics of carcinogenic risk, represented by ELCR (excess lifetime cancer risk), non-carcinogenic risk represented by HI (hazard index), and the composition and sources of the particulate matter using multiple linear regression methods. The correlations between calculated ELCR and HI and the measured OP were 0.37 and 0.7, respectively. HI was a better predictor of OP than ELCR. The prediction models based on pollutants (Model_1) and pollution sources (Model_2) were constructed by multiple linear regression method, and Pearson correlation coefficients between the predicted results of Model_1 and Model_2 with the measured volume normalized OP are 0.81 and 0.80, showing good prediction ability. Previous investigations in Europe and North America have developed location-specific relationships between the chemical composition of particulate matter and OP using regression methods. We also examined the ability of relationships between OP and composition, sources, developed in Europe and North America, to predict the OP of particulate matter in Beijing from the composition and sources determined in Beijing. The relationships developed in Europe and North America provided good predictive ability in Beijing and it suggests that these relationships can be used to predict OP from the chemical composition measured in other regions of the world.

The individual and synergistic impacts of windstorms and power outages on injury ED visits in New York State

BACKGROUND

There is little work in assessing the impact of storm events combined with power outage (PO). In this study, we evaluated the individual and synergistic impacts of wind events and PO on overall and subtypes of injuries in New York State (NYS) and by demographics.

METHODS

The emergency department (ED) visit data were obtained from the NYS Department of Health from November-April 2005-2013 to identify injury cases, length of stay and care costs. Wind event was defined according to high wind, strong wind or thunderstorm wind defined by NOAA. PO occurrence was defined when PO coverage exceeded the 50th percentile of its distribution. By comparing non-event days, we used distributed lag nonlinear models to evaluate the impacts of wind events, PO, and their combined effect on injuries during the cold season over a 0-3-day lag period, while controlling for time-varying confounders. The differences in critical care indicators between event and non-event days were also evaluated.

RESULTS

Overall injuries ED visits (16,628,812) significantly increased during the wind events (highest Risk Ratio (RR): 1.05; 95% CI: 1.02-1.08), and were highest when wind events cooccurred with PO (highest RR: 1.14; 95% CI: 1.10-1.18), but not during PO alone (RR: 1.00; 95%CI: 0.96-1.04). The increase was also observed with all subgroups through Day 2 after the event. Greater risks exist for older adults (≥65 years) and those on Medicaid. After the joint occurrences of wind events and PO, average visits are 0.2 days longer, and cost 13% more, compared to no wind/no PO days.

CONCLUSION

There is a significant increase in ED visits, length of stay and cost of injuries during wind events, especially when they coupled with PO and especially among older cases and Medicaid holders. Our findings may be used for planning disaster preparedness and recovery efforts.

Forecasting PM2.5 concentration using artificial neural network and its health effects in Ahvaz, Iran

The main objective of the present study was to predict the associated health endpoint of PM2.5 using an artificial neural network (ANN). The neural network used in this work contains a hidden layer with 27 neurons, an input layer with 8 parameters, and an output layer. First, the artificial neural network was implemented with 80% of data for training then with 90% of data for training. The value of R for the data validation of these two networks was 0.80 and 0.83 respectively. The World Health Organization AirQ + software was utilized for assessing Health effects of PM2.5 levels. The mean PM2.5 over the 9-year study period was 63.27(μg/m3), about six times higher than the WHO guideline. However, the PM2.5 concentration in the last year decreased by about 25% compared to the first year, which is statistically significant (P-value = 0.0048). This reduced pollutant concentration led to a decrease in the number of deaths from 1785 in 2008 to 1059 in 2016. Moreover, a positive correlation was found between PM2.5 concentration and temperature and wind speed. Considering the importance of predicting PM2.5 concentration for accurate and timely decisions as well as the accuracy of the artificial neural network used in this study, the artificial neural network can be utilized as an effective instrument to reduce health and economic effects.

Power outage mediates the associations between major storms and hospital admission of chronic obstructive pulmonary disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is the third-leading cause of death worldwide with continuous rise. Limited studies indicate that COPD was associated with major storms and related power outages (PO). However, significant gaps remain in understanding what PO's role is on the pathway of major storms-COPD. This study aimed to examine how PO mediates the major storms-COPD associations.

METHODS

In this time-series study, we extracted all hospital admissions with COPD as the principal diagnosis in New York, 2001-2013. Using distributed lag nonlinear models, the hospitalization rate during major storms and PO was compared to non-major storms and non-PO periods to determine the risk ratios (RRs) for COPD at each of 0-6 lag days respectively after controlling for time-varying confounders and concentration of fine particulate matter (PM2.5). We then used Granger mediation analysis for time series to assess the mediation effect of PO on the major storms-COPD associations.

RESULTS

The RRs of COPD hospitalization following major storms, which mainly included flooding, thunder, hurricane, snow, ice, and wind, were 1.23 to 1.49 across lag 0-6 days. The risk was strongest at lag3 and lasted significantly for 4 days. Compared with non-outage periods, the PO period was associated with 1.23 to 1.61 higher risk of COPD admissions across lag 0-6 days. The risk lasted significantly for 2 days and was strongest at lag2. Snow, hurricane and wind were the top three contributors of PO among the major storms. PO mediated as much as 49.6 to 65.0% of the major storms-COPD associations.

CONCLUSIONS

Both major storms and PO were associated with increased hospital admission of COPD. PO mediated almost half of the major storms-COPD hospitalization associations. Preparation of surrogate electric system before major storms is essential to reduce major storms-COPD hospitalization.

Indoor Particulate Matter in Urban Households: Sources, Pathways, Characteristics, Health Effects, and Exposure Mitigation

Particulate matter (PM) is a complex mixture of solid particles and liquid droplets suspended in the air with varying size, shape, and chemical composition which intensifies significant concern due to severe health effects. Based on the well-established human health effects of outdoor PM, health-based standards for outdoor air have been promoted (e.g., the National Ambient Air Quality Standards formulated by the U.S.). Due to the exchange of indoor and outdoor air, the chemical composition of indoor particulate matter is related to the sources and components of outdoor PM. However, PM in the indoor environment has the potential to exceed outdoor PM levels. Indoor PM includes particles of outdoor origin that drift indoors and particles that originate from indoor activities, which include cooking, fireplaces, smoking, fuel combustion for heating, human activities, and burning incense. Indoor PM can be enriched with inorganic and organic contaminants, including toxic heavy metals and carcinogenic volatile organic compounds. As a potential health hazard, indoor exposure to PM has received increased attention in recent years because people spend most of their time indoors. In addition, as the quantity, quality, and scope of the research have expanded, it is necessary to conduct a systematic review of indoor PM. This review discusses the sources, pathways, characteristics, health effects, and exposure mitigation of indoor PM. Practical solutions and steps to reduce exposure to indoor PM are also discussed.

Personal exposure to fine particulate matter and blood pressure: Variations by particulate sources

Fine particulate matter (PM_2.5) is a complex mixture of components which has been associated with various cardiovascular effects, such as elevated blood pressure (BP). However, evidences on specific sources behind these effects remain uncertain. Based on 140 72-h personal measurements among a panel of 36 health college students in Shanghai, China, we assessed associations between source-apportioned PM_2.5 exposure and BP changes. Based on personal filter samples, PM_2.5 source apportionment was conducted using Positive Matrix Factorization (PMF) model. Linear mixed-effects models were applied to evaluate associations of source-specific PM_2.5 exposure with BP changes. Seven sources were identified in PMF analysis. Among them, secondary sulfate (41%) and nitrate (24%) sources contributed most to personal PM_2.5, followed by industrial emissions (15%), traffic-related source (10%), coal combustion (6.2%), dust (2.4%) and aged sea salt (1.1%). We found nitrate, traffic-related source and coal combustion were significantly associated with increased BP. For example, an interquartile range increase in PM_2.5 from traffic-related source was significantly associated with increase in systolic BP [1.5 (95% CI: 0.26, 2.7) mmHg], diastolic BP [1.2 (95% CI: 0.10, 2.2) mmHg] and mean arterial pressure [1.2 (95% CI: 0.15, 2.2) mmHg]. This is the first investigation linking personal PM_2.5 source profile and BP changes. This study provides evidence that several anthropogenic emissions (especially traffic-related emission) may be particularly responsible for BP increases, and highlights that the importance of development of health-oriented PM_2.5 source control strategies.

Cardiovascular morbidity and mortality associations with biomass- and fossil-fuel-combustion fine-particulate-matter exposures in Dhaka, Bangladesh

BACKGROUND

Fine-particulate-matter (i.e. with an aerodynamic diameter of ≤2.5 µm, PM2.5) air pollution is commonly treated as if it had 'equivalent toxicity', irrespective of the source and composition. We investigate the respective roles of fossil-fuel- and biomass-combustion particles in the PM2.5 relationship with cardiovascular morbidity and mortality using tracers of sources in Dhaka, Bangladesh. Results provide insight into the often observed levelling of the PM2.5 exposure-response curve at high-pollution levels.

METHODS

A time-series regression model, adjusted for potentially confounding influences, was applied to 340 758 cardiovascular disease (CVD) emergency-department visits (EDVs) during January 2014 to December 2017, 253 407 hospital admissions during September 2013 to December 2017 and 16 858 CVD deaths during January 2014 to October 2017.

RESULTS

Significant associations were confirmed between PM2.5-mass exposures and increased risk of cardiovascular EDV [0.27%, (0.07% to 0.47%)] at lag-0, hospitalizations [0.32% (0.08% to 0.55%)] at lag-0 and deaths [0.87%, (0.27% to 1.47%)] at lag-1 per 10-μg/m3 increase in PM2.5. However, the relationship of PM2.5 with morbidity and mortality effect slopes was less steep and non-significant at higher PM2.5 concentrations (during crop-burning-dominated exposures) and varied with PM2.5 source. Fossil-fuel-combustion PM2.5 had roughly a four times greater effect on CVD mortality and double the effect on CVD hospital admissions on a per-µg/m3 basis than did biomass-combustion PM2.5.

CONCLUSION

Biomass burning was responsible for most PM2.5 air pollution in Dhaka, but fossil-fuel-combustion PM2.5 dominated the CVD adverse health impacts. Such by-source variations in the health impacts of PM2.5 should be considered in conducting ambient particulate-matter risk assessments, as well as in prioritizing air-pollution-mitigation measures and clinical advice.

Respiratory Emergency Department Visits Associations with Exposures to PM2.5 Mass, Constituents, and Sources in Dhaka, Bangladesh Air Pollution

RATIONALE

To date, there is no published local epidemiological evidence documenting the respiratory health effects of source specific air pollution in South Asia, where PM2.5 composition is different from past studies. Differences include more biomass and residue crop-burning emissions, which may have differing health implications.

OBJECTIVES

We assessed PM2.5 associations with respiratory emergency department (ED) visits in a biomass-burning dominated high pollution region, and evaluated their variability by pollution source and composition.

METHODS

Time-series regression modeling was applied to daily ED visits from January 2014 through December 2017. Air pollutant effect sizes were estimated after addressing long-term trends and seasonality, day-of-week, holidays, relative humidity, ambient temperature, and the effect modification by season, age, and sex.

RESULTS

PM2.5 yielded a significant association with increased respiratory ED visits [0.84% (95% CI: 0.33%, 1.35%)] per 10 μg/m3 increase. The PM2.5 health effect size varied with season, the highest being during monsoon season, when fossil-fuel combustion sources dominated exposures. Results from a source-specific health effect analysis was also consistent with fossil-fuel PM2.5 having a larger effect size per 10 μg/m3 than PM2.5 from other sources [fossil-fuel PM2.5: 2.79% (0.33% to 5.31%), biomass-burning PM2.5: 1.27% (0% to 2.54%), and other-PM2.5: 0.95% (0.06% to 1.85%)]. Age-specific associations varied, with children and older adults being disproportionately affected by the air pollution, especially by the combustion-related particles.

CONCLUSIONS

This study provided novel and important evidence that respiratory health in Dhaka is significantly affected by particle air pollution, with a greater health impact by fossil-fuel combustion derived PM2.5.

Ambient extreme heat exposure in summer and transitional months and emergency department visits and hospital admissions due to pregnancy complications

Although extreme heat exposure (EHE) was reported to be associated with increased risks of multiple diseases, little is known about the effects of EHE on pregnancy complications. We examined the EHE-pregnancy complications associations by lag days, subtypes, sociodemographic characteristics, and areas in New York State (NYS). We conducted a case-crossover analysis to assess the EHE-pregnancy complications associations in summer (June-August) and transitional months (May and September). All emergency department (ED) visits and hospital admissions due to pregnancy complications (ICD 9 codes: 630-649) from 2005 to 2013 in NYS were included. Daily mean temperature > 90th percentile of the monthly mean temperature in each county was defined as an EHE. We used conditional logistic regression while controlling for other weather factors, air pollutants and holidays to assess the EHE-pregnancy complications associations. EHE was significantly associated with increased ED visits for pregnancy complications in summer (ORs ranged: 1.01-1.04 from lag days 0-5). There was also a significant and stronger association in transitional months (ORs ranged: 1.02-1.06, Lag 0). Furthermore, we found EHE affected multiple subtypes of pregnancy complications, including threatened/spontaneous abortion, renal diseases, infectious diseases, diabetes, and hypertension (ORs range: 1.13-1.90) during transitional months. A significant concentration response effect between the number of consecutive days of EHE and ED visits in summer (P for trend <0.001), ED visits in September (P for trend =0.03), and hospital admission in May (P for trend<0.001) due to pregnancy complications was observed, respectively. African Americans and residents in lower socioeconomic position (SEP) counties were more susceptible to the effects of EHE. In conclusion, we found an immediate and prolonged effect of EHE on pregnancy complications in summer and a stronger, immediate effect in transitional months. These effects were stronger in African Americans and counties with lower SEP. Earlier warnings regarding extreme heat are recommended to decrease pregnancy complications.

Airborne particulate matter in Tehran's ambient air

In recent decades, particulate matter (PM) concentrations in Tehran have exceeded the World Health Organization's (WHO) guideline on most days. In this study, a search protocol was defined by identifying the keywords, to carry out a systematic review of the concentrations and composition of PM in Tehran's ambient air. For this purpose, searches were done in Scopus, PubMed, and Web of Science in 2019. Among the founded articles (197 in Scopus, 61 in PubMed, and 153 in Web of Science). The results show that in Tehran, the annual average PM10 exceeded the WHO guidelines and for more than 50.0% of the days, the PM2.5 concentration was more than WHO 24-h guidance value. The PM concentration in Tehran has two seasonal peaks due to poorer dispersion and suspension from dry land, respectively. Tehran has two daily PM peaks due to traffic and changes in boundary-layer heights; one just after midnight and the other during morning rush hour. Indoor concentrations of PM10 and PM2.5 in Tehran were 10.6 and 21.8 times higher than the corresponding values in ambient air. Tehran represents a unique case of problems of controlling PM because of its geographical setting, emission sources, and land use. This review provided a comprehensive assessment for decision makers to assist them in making appropriate policy decisions to improve the air quality. Considering factors such as diversity of resources, temporal and spatial variations, and urban location is essential in developing control plans. Also future studies should focus more on PM reduction plans.

Automating the interpretation of PM2.5 time-resolved measurements using a data-driven approach

The rapid development of automated measurement equipment enables researchers to collect greater quantities of time-resolved data from indoor and outdoor environments. While significant, the interpretation of the resulting data can be a time-consuming effort. This paper introduces an automated process of interpreting PM_2.5 time-resolved data and differentiating PM_2.5 emissions resulting from indoor and outdoor sources. We use Random Forest (RF), a machine learning approach, to study a dataset of 836 indoor emission events that occurred over a 2-week period in 18 apartments in California. In this paper, we show model development and evaluate its performance as the sample size and source vary. We discuss the characteristics of the dataset that tended to help the source identification and why. For example, we show that data from many events and from different apartments are essential for the model to be suitable for analyzing a new separate dataset. We also show that longitudinal data appear to be more helpful than the time frequency of measurements within a given apartment. We use the resulting RF model to analyze PM_2.5 data of an entirely separate dataset collected from 65 new homes in California. The RF model identifies 442 indoor emission events, with only a few misidentifications.

The immediate effects of winter storms and power outages on multiple health outcomes and the time windows of vulnerability

BACKGROUND

While most prior research has focused on extreme heat, few assessed the immediate health effects of winter storms and associated power outages (PO), although severe storms have become more frequent. This study evaluates the joint and independent health effects of winter storms and PO, snow versus ice-storm, effects by time window (peak timing, winter/transitional months) and the impacts on critical care indicators including numbers of comorbidity, procedure, length of stay and cost.

METHODS

We use distributed lag nonlinear models to assess the impacts of winter storm/PO on hospitalizations due to cardiovascular, lower respiratory diseases (LRD), respiratory infections, food/water-borne diseases (FWBD) and injuries in New York State on 0-6 lag days following storm/PO compared with non-storm/non-PO periods (references), while controlling for time-varying factors and PM2.5. The storm-related hospitalizations are described by time window. We also calculate changes in critical care indicators between the storm/PO and control periods.

RESULTS

We found the joint effects of storm/PO are the strongest (risk ratios (RR) range: 1.01-1.90), followed by that of storm alone (1.02-1.39), but not during PO alone. Ice storms have stronger impacts (RRs: 1.04-3.15) than snowstorms (RRs: 1.03-2.21). The storm/PO-health associations, which occur immediately, and some last a whole week, are stronger in FWBD, October/November, and peak between 3:00-8:00 p.m. Comorbidity and medical costs significantly increase after storm/PO.

CONCLUSION

Winter storms increase multiple diseases, comorbidity and medical costs, especially when accompanied by PO or ice storms. Early warnings and prevention may be critical in the transitional months and afternoon rush hours.

Sources, variability and parameterizations of intra-city factors obtained from dispersion-normalized multi-time resolution factor analyses of PM2.5 in an urban environment

Ambient fine particulate matter (PM_2.5) data of similar continuously monitored species at two air monitoring sites with different characteristics within the City of Toronto were used to gauge the intra-city variations in the PM composition over a largely concurrent period spanning two years. One location was <8 m from the side of a major highway while the other was an urban background location. For the first time, multi-time resolution factor analysis was applied to dispersion-normalized concentrations to identify and quantify source contributions while reducing the influence of local meteorology. These factors were particulate sulphate (pSO4), particulate nitrate (pNO3), secondary organic aerosols (SOA), crustal matter (CrM) that were common to both sites, a hydrocarbon-like organic matter (HOM) exclusive to the urban background site, three black carbon related factors (BC, BC-HOM at the highway site, and a brown carbon rich factor (BC-BrC) at the urban background site), biomass burning organic matter (BBOM) and brake dust (BD) factors exclusive to the highway site. The PM_2.5 composition was different between these two locations, over only a 10 km distance. The sum of SOA, pSO4 and pNO3 at the urban background site averaged 57% of the PM_2.5 mass while the same species represented 43% of the average PM_2.5 mass at the highway site. Local or site-specific factors may be of greater interest for control policy design. Thus, regression analyses with potential explanatory, site-specific variables were performed for results from the highway site. Three model approaches were explored: multiple linear regression (MLR), regression with a generalized reduced gradient (GRG) algorithm, and a generalized additive model (GAM). GAM gave the largest fraction of variance for the locally-found factors at the highway site. Heavy-duty vehicles were most important for explaining the black carbon (BC and BC-HOM) factors. Light-duty vehicles were dominant for the brake dust (BD) factor. The auxiliary modelling for the local factors showed that the traffic-related factors likely originated along the main roadways at their respective sites while the more regional factors, - pSO4, pNO3, SOA, - had sources that were both regional and local in origin and with contributions that varied seasonally. These results will be useful in understanding ambient particulate matter sources on a city scale that will support air quality management planning.

Specific differences and responses to reductions for premature mortality attributable to ambient PM2.5 in China

Although recent assessments have quantified the impact of ambient PM_2.5 on public health in China, air quality managers would benefit from assessing specific differences in premature mortality and its responses to air quality improvement. Using PM_2.5 data simulated by an observation-fused air quality model and an integrated exposure-response model for the full range of PM_2.5, we determined the premature mortality attributable to ambient PM_2.5 across mainland China in 2016. Overall, the total number of PM_2.5-related deaths nationwide was 1.31 million, of which lung cancer, chronic obstructive pulmonary disease, ischemic heart disease, and stroke represented 0.13, 0.13, 0.42, and 0.62 million, respectively. Per capita PM_2.5-related mortality in China was 95 per 100,000 person-years, and that of elderly people aged ≥75 years (1166 deaths per 100,000) was much higher than that of young people aged 25-44 years (11 deaths per 100,000). Additionally, there were significant spatial differences in premature deaths, which mainly occurred in regions with high PM_2.5 levels or/and population density. Halving deaths across mainland China required an average of 63% reduction of PM_2.5 nationwide and a decrease by 73% in high concentration regions exceeding 70 μg/m³ and 19% in low concentration locales below 10 μg/m³. Moreover, reducing PM_2.5 to the WHO interim target I (IT-1) of 35 μg/m³ would only result in a 12.6% reduction in premature mortality, while a more exacting standard (reducing PM_2.5 to 10 μg/m³) would avoid 73.0% of mortality. In particular, there is a large potential for reducing the high PM_2.5-related mortality in heavily polluted locales. In conclusion, to further reduce premature mortality across mainland China, targets stricter than the IT-1 and tight policies to improve air quality and protect public health are necessary, especially for vulnerable groups such as the elderly and patients with cardio-cerebrovascular diseases, particularly in areas with high premature mortality.

Temporal changes in short-term associations between cardiorespiratory emergency department visits and PM2.5 in Los Angeles, 2005 to 2016

BACKGROUND

Emissions control programs targeting certain air pollution sources may alter PM_2.5 composition, as well as the risk of adverse health outcomes associated with PM_2.5.

OBJECTIVES

We examined temporal changes in the risk of emergency department (ED) visits for cardiovascular diseases (CVDs) and asthma associated with short-term increases in ambient PM_2.5 concentrations in Los Angeles, California.

METHODS

Poisson log-linear models with unconstrained distributed exposure lags were used to estimate the risk of CVD and asthma ED visits associated with short-term increases in daily PM_2.5 concentrations, controlling for temporal and meteorological confounders. The models were run separately for three predefined time periods, which were selected based on the implementation of multiple emissions control programs (EARLY: 2005-2008; MIDDLE: 2009-2012; LATE: 2013-2016). Two-pollutant models with individual PM_2.5 components and the remaining PM_2.5 mass were also considered to assess the influence of changes in PM_2.5 composition on changes in the risk of CVD and asthma ED visits associated with PM_2.5 over time.

RESULTS

The relative risk of CVD ED visits associated with a 10 μg/m³ increase in 4-day PM_2.5 concentration (lag 0-3) was higher in the LATE period (rate ratio = 1.020, 95% confidence interval = [1.010, 1.030]) compared to the EARLY period (1.003, [0.996, 1.010]). In contrast, for asthma, relative risk estimates were largest in the EARLY period (1.018, [1.006, 1.029]), but smaller in the following periods. Similar temporal differences in relative risk estimates for CVD and asthma were observed among different age and season groups. No single component was identified as an obvious contributor to the changing risk estimates over time, and some components exhibited different temporal patterns in risk estimates from PM_2.5 total mass, such as a decreased risk of CVD ED visits associated with sulfate over time.

CONCLUSIONS

Temporal changes in the risk of CVD and asthma ED visits associated with short-term increases in ambient PM_2.5 concentrations were observed. These changes could be related to changes in PM_2.5 composition (e.g., an increasing fraction of organic carbon and a decreasing fraction of sulfate in PM_2.5). Other factors such as improvements in healthcare and differential exposure misclassification might also contribute to the changes.

Toxicity of airborne particles-established evidence, knowledge gaps and emerging areas of importance

Epidemiological research has taught us a great deal about the health effects of airborne particulate matter (PM), particularly cardiorespiratory effects of combustion-related particles. This has been matched by toxicological research to define underlying mechanistic pathways. To keep abreast of the substantial challenges that air pollution continues to throw at us requires yet more strides to be achieved. For example, being aware of the most toxic components/sources and having a definitive idea of the range of associated disease outcomes. This review discusses approaches designed to close some of these knowledge gaps. These include a focus on particles arising from non-exhaust PM at the roadside and microplastics-both of which are becoming more relevant in the light of a shift in PM composition in response to global pressure to reduce combustion emissions. The application of hypothesis-free approaches in both mechanistic studies and epidemiology in unveiling unexpected relationships and generating novel insights is also discussed. Previous work, strengthening the evidence for both the adverse effects and benefits of intervention tell us that the sooner we act to close knowledge gaps, increase awareness and develop creative solutions, the sooner we can reduce the public health burden attributable to these complex and insidious environmental pollutants. This article is part of a discussion meeting issue 'Air quality, past present and future'.

Global review of recent source apportionments for airborne particulate matter

Source apportionments have become increasingly performed to determine the origins of ambient particulate pollution. The results can be helpful in designing mitigation strategies to improve air quality. Source specific particulate matter (PM) concentrations are also being used in health effects studies to be able to focus attention on those sources most likely to be responsible for the observed adverse health effects. In 2015, the World Health Organization (WHO) released its initial compilation of source apportionment studies published through August 2014. This initial database was described by Karagulian et al. (Atmospheric Environment120 (2015) 475-483). In the present report, a new compilation has been prepared of those apportionments published since 2014 through December 2019. In addition, the database has been expanded to include apportionments of heavy metals, water-soluble components, and carbonaceous components in ambient PM. As a result of this work, we have developed and presented some perspectives on source apportionment going forward. We also have made a series of recommendations for source apportionment studies and reporting them. It is essential for papers to provide a minimum set of information so that the study can be adequately assessed, and the results utilized by others in making policy decisions or as part of other scientific studies.

Neurodegenerative hospital admissions and long-term exposure to ambient fine particle air pollution

PURPOSE

Long-term exposure to ambient fine particle (PM_2.5) concentrations has been associated with an increased rate or risk of neurodegenerative conditions, but individual PM sources have not been previously examined in relation to neurodegenerative diseases.

METHODS

Using the Statewide Planning and Research Cooperative System database, we studied 63,287 hospital admissions with a primary diagnosis of either Alzheimer's disease, dementia, or Parkinson's disease for New York State residents living within 15 miles from six PM_2.5 monitoring sites. In addition to PM_2.5 concentrations, we studied seven specific PM_2.5 sources: secondary sulfate, secondary nitrate, biomass burning, diesel, spark-ignition emissions, pyrolyzed organic rich, and road dust. We estimated the rate of neurodegenerative hospital admissions associated with increased concentration of PM_2.5 and individual PM_2.5 sources average concentrations in the previous 0-29, 0-179, and 0-364 days.

RESULTS

Increases in ambient PM_2.5 concentrations were not consistently associated with increased hospital admissions rates. Increased source-specific PM2.5 concentrations were associated with both increased (e.g., secondary sulfates and diesel emissions) and decreased rates (e.g., secondary nitrate and spark-ignition vehicular emissions) of neurodegenerative admissions.

CONCLUSIONS

We did not observe clear associations between overall ambient PM_2.5 concentrations or source-apportioned ambient PM_2.5 contributions and rates of neurologic disease hospitalizations.