Associations between Source-Specific Fine Particulate Matter and Emergency Department Visits for Respiratory Disease in Four U.S. Cities

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.

High spatial-resolved source-specific exposure and risk in the city scale: Influence of spatial interrelationship between PM2.5 sources and population on exposure

Research on High Spatial-Resolved Source-Specific Exposure and Risk (HSRSSER) was conducted based on multiple-year, multiple-site synchronous measurement of PM2.5-bound (particulate matter with aerodynamic diameter<2.5 μm) toxic components in a Chinese megacity. The developed HSRSSER model combined the Positive Matrix Factorization (PMF) and Land Use Regression (LUR) to predict high spatial-resolved source contributions, and estimated the source-specific exposure and risk by personal activity time- and population-weighting. A total of 287 PM2.5 samples were collected at ten sites in 2018-2020, and toxic species including heavy metals (HMs), polycyclic aromatic hydrocarbons (PAHs) and organophosphate esters (OPEs) were analyzed. The percentage non-cancer risk were in the order of traffic emission (48 %) > industrial emission (22 %) > coal combustion (12 %) > waste incineration (11 %) > resuspend dust (7 %) > OPE-related products (0 %) ≈ secondary particles (0 %). Similar orders were observed in cancer risk. For traffic emission, due to its higher source contributions and large population in central area, non-cancer and cancer risk fraction increased from 23 % to 48 % and 20 % to 46 % after exposure estimation; while for industrial emission, higher source contributions but small population in suburb area decreased the percentage non-cancer and cancer risk from 38 % to 22 % and 39 % to 24 %, respectively.

A review of common statistical methods for dealing with multiple pollutant mixtures and multiple exposures

Traditional environmental epidemiology has consistently focused on studying the impact of single exposures on specific health outcomes, considering concurrent exposures as variables to be controlled. However, with the continuous changes in environment, humans are increasingly facing more complex exposures to multi-pollutant mixtures. In this context, accurately assessing the impact of multi-pollutant mixtures on health has become a central concern in current environmental research. Simultaneously, the continuous development and optimization of statistical methods offer robust support for handling large datasets, strengthening the capability to conduct in-depth research on the effects of multiple exposures on health. In order to examine complicated exposure mixtures, we introduce commonly used statistical methods and their developments, such as weighted quantile sum, bayesian kernel machine regression, toxic equivalency analysis, and others. Delineating their applications, advantages, weaknesses, and interpretability of results. It also provides guidance for researchers involved in studying multi-pollutant mixtures, aiding them in selecting appropriate statistical methods and utilizing R software for more accurate and comprehensive assessments of the impact of multi-pollutant mixtures on human health.

A spatial approach to assessing PM2.5 exposure level of a brickmaking community in South Africa

Globally, particulate matter with an aerodynamic diameter of 2.5 µm or less poses a significant threat to human health. The first step in quantifying human health impacts caused by exposure to PM2.5 pollution is exposure assessment. Population-weighted exposure level (PWEL) estimation is one of the methods that provides a more precise exposure assessment since it incorporates the spatiotemporal distribution of population with the pollution concentration estimate. In this study, PM2.5 exposure levels in the local communities around brickmaking industries were investigated, using the population census data of the study area and 1-year data from nine PM2.5 monitoring stations installed in and around the brickmaking industries. The observed PM2.5 data was spatially interpolated using inverse distance weight (IDW). Data on PM2.5 levels across the study area were classified based on the World Health Organization interim target (IT) guidelines and the South African National ambient air quality standard (NAAQS). An annual PM2.5 population weighted exposure level of 27.6 µg/m3 was estimated for the study area. However, seasonal exposure levels of 28.9, 37.6, 26.5, and 20.7 µg/m3 were estimated for the autumn, winter, spring, and summer seasons, respectively. This implies that local communities around the brick kiln in the Vhembe District are exposed to high levels of PM2.5, especially in winter. The PM2.5 levels in the brickmaking industries as well as its other sources in the Vhembe District, therefore, need to be lowered. Findings from population exposure level to pollutants can provide valuable data for formulating policies and recommendations on exposure reduction and public health protection.Implications: PM2.5 concentration in any given environment has high spatial and temporal variability due to the presence of diffused sources in the environment. Using ambient air concentrations to directly estimate population exposure without taking into consideration the disproportionate spatial and temporal distribution of the pollutant and the population may not yield accurate results on human exposure levels. It is, therefore, important to assess the aggregated PM2.5 exposure of a populace within a given area. This study therefore examines the PM2.5 population-weighted-exposure level of the host communities of the brickmaking industry in Vhembe District, South Africa.

Elemental Characterization of Ambient Particulate Matter for a Globally Distributed Monitoring Network: Methodology and Implications

Global ground-level measurements of elements in ambient particulate matter (PM) can provide valuable information to understand the distribution of dust and trace elements, assess health impacts, and investigate emission sources. We use X-ray fluorescence spectroscopy to characterize the elemental composition of PM samples collected from 27 globally distributed sites in the Surface PARTiculate mAtter Network (SPARTAN) over 2019-2023. Consistent protocols are applied to collect all samples and analyze them at one central laboratory, which facilitates comparison across different sites. Multiple quality assurance measures are performed, including applying reference materials that resemble typical PM samples, acceptance testing, and routine quality control. Method detection limits and uncertainties are estimated. Concentrations of dust and trace element oxides (TEO) are determined from the elemental dataset. In addition to sites in arid regions, a moderately high mean dust concentration (6 μg/m3) in PM2.5 is also found in Dhaka (Bangladesh) along with a high average TEO level (6 μg/m3). High carcinogenic risk (>1 cancer case per 100000 adults) from airborne arsenic is observed in Dhaka (Bangladesh), Kanpur (India), and Hanoi (Vietnam). Industries of informal lead-acid battery and e-waste recycling as well as coal-fired brick kilns likely contribute to the elevated trace element concentrations found in Dhaka.

Haze weather and mortality in China from 2014 to 2020: Definitions, vulnerability, and effect modification by haze characteristics

Haze weather, characterized by low visibility due to severe air pollution, has aroused great public concern. However, haze definitions are inconclusive, and multicentre studies on the health impacts of haze are scarce. We collected data on the daily number of deaths and environmental factors in 190 Chinese cities from 2014 to 2020. The city-specific association was estimated using quasi-Poisson regression and then pooled using meta-analysis. We found a negative association between daily visibility and non-accidental deaths, and mortality risk sharply increased when visibility was < 10 km. Haze weather, defined as a daily average visibility of < 10 km without a limit for humidity, produced the best model fitness and greatest effect on mortality. A haze day was associated with an increase of 2.53% (95% confidence interval [CI]:1.96, 3.10), 2.84 (95% CI: 2.13, 3.56), and 2.99% (95% CI: 1.94, 4.04) in all non-accident, cardiovascular and respiratory mortality, respectively. Haze had the greatest effect on lung cancer mortality. The haze-associated risk of mortality increased with age. Severe haze (visibility <2 km) and damp haze (haze with relative humidity >90%) had greater health impacts. Our findings can help in the development of early warning systems and effective public health interventions for haze.

Ambient atmospheric PM worsens mouse lung injury induced by influenza A virus through lysosomal dysfunction

BACKGROUND

Particulate matter (PM) air pollution poses a significant risk to respiratory health and is especially linked with various infectious respiratory diseases such as influenza. Our previous studies have shown that H5N1 virus infection could induce alveolar epithelial A549 cell death by enhancing lysosomal dysfunction. This study aims to investigate the mechanisms underlying the effects of PM on influenza virus infections, with a particular focus on lysosomal dysfunction.

RESULTS

Here, we showed that PM nanoparticles such as silica and alumina could induce A549 cell death and lysosomal dysfunction, and degradation of lysosomal-associated membrane proteins (LAMPs), which are the most abundant lysosomal membrane proteins. The knockdown of LAMPs with siRNA facilitated cellular entry of both H1N1 and H5N1 influenza viruses. Furthermore, we demonstrated that silica and alumina synergistically increased alveolar epithelial cell death induced by H1N1 and H5N1 influenza viruses by enhancing lysosomal dysfunction via LAMP degradation and promoting viral entry. In vivo, lung injury in the H5N1 virus infection-induced model was exacerbated by pre-exposure to silica, resulting in an increase in the wet/dry ratio and histopathological score.

CONCLUSIONS

Our findings reveal the mechanism underlying the synergistic effect of nanoparticles in the early stage of the influenza virus life cycle and may explain the increased number of respiratory patients during periods of air pollution.

The impact of air pollution on outpatient medical service utilization and expenditure in a clean air city

BACKGROUND

Although there's increasing research on the health effects of air pollution in China, its direct influence on health-related expenditures, particularly during less severe pollution episodes, is still not well-understood. This study aims to quantify impact of three air pollutants (sulfur dioxide, nitrogen dioxide, and particulate matter) on individual healthcare spending in a city with relatively clean air.

METHODS

Using transaction-level medical social insurance data and temperature inversion as the instrumental variable, we estimate the current and cumulative effects of air pollutants on outpatient visits and medical expenses in an eastern city in China.

RESULTS

We find a significantly positive effect on outpatient visits for 15-day moving average, and a significantly positive effect on outpatient expenditure for 25-day moving average. Therefore, the cumulative effect of pollutants on medical expenditure should not be ignored. The effects on total outpatient expenditure are larger for the elderly and men. The cumulative pollution exposure increases the visits to respiratory department but also increases the expenditure on non-respiratory diseases in the long term.

CONCLUSION

Our findings provide empirical evidence that even for cities with good air quality, further improvements can improve patients' quality of life and lessen the expenditure burden on medical insurance.

Agricultural burning in Imperial Valley, California and respiratory symptoms in children: A cross-sectional, repeated measures analysis

Burning of agricultural fields is an understudied source of air pollution in rural communities in the United States. Smoke from agricultural burning contains air toxics that adversely impact respiratory health. Imperial County in southeastern California is a highly productive agricultural valley that heavily employs agricultural burning to clear post-harvest crop remnants. We related individual-level exposure to agricultural burns to parent-reported respiratory symptoms in children. We leveraged the Children's Assessing Imperial Valley Respiratory Health and the Environment (AIRE) cohort of 735 predominantly Hispanic low-income elementary school students in Imperial County. Parents reported children's respiratory health symptoms and family demographic characteristics in questionnaires collected at enrollment and in annual follow-up assessments from 2017 to 2019. Permitted agricultural burns in Imperial County from 2016 to 2019 were spatially linked to children's geocoded residential addresses. We used generalized estimating equations to evaluate prevalence differences (PDs) in respiratory symptoms with increasing exposure to agricultural burning within 3 km in the 12 months prior to each assessment. Nearly half of children (346, 49 %) lived within 3 km of at least one agricultural burn in the year prior to study enrollment. In adjusted models, each additional day of agricultural burning in the prior year was associated with a one percentage point higher prevalence of wheezing (PD 1.1 %; 95 % CI 0.2 %, 2.0 %) and higher bronchitic symptoms (PD 1.0 %; 95 % CI -0.2 %, 2.1 %). Children exposed to four or more days of burning had an absolute increased prevalence of wheezing and bronchitic symptoms of 5.9 % (95 % CI -0.3 %, 12 %) and 5.6 % (95 % CI -1.8 %, 13 %), respectively, compared to no burn exposure. Associations with wheezing were stronger among children with asthma (PD 14 %; 95 % CI -1.4 %, 29 %). To our knowledge, this is the first U.S. study of agricultural burning and children's respiratory health. This work suggests that reducing agricultural burning could improve children's respiratory health.

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.

Particulate Matter Pollution Remains a Threat for Cardiovascular Health: Findings From the Global Burden of Disease 2019

Background Particulate matter (PM) pollution is a significant risk factor for cardiovascular diseases, causing substantial disease burden and deaths worldwide. This study aimed to investigate the global burden of cardiovascular diseases attributed to PM from 1990 to 2019. Methods and Results We used the GBD (Global Burden of Disease) study 2019 to investigate disability-adjusted life-years (DALYs), years of life lost (YLLs), years lived with disability (YLDs), and deaths attributed to PM as well as its subgroups. It was shown that all burden measures' age-standardized rates for PM were in the same decreasing trend, with the highest decline recorded for deaths (-36.7%). However, the all-age DALYs increased by 31%, reaching 8.9 million in 2019, to which YLLs contributed the most (8.2 million [95% uncertainty interval, 7.3 million-9.2 million]). Men had higher deaths, DALYs, and YLLs despite lower years lived with disability in 2019 compared with women. There was an 8.1% increase in the age-standardized rate of DALYs for ambient PM; however, household air pollution from solid fuels decreased by 65.4% in the assessed period. Although higher in men, the low and high sociodemographic index regions had the highest and lowest attributed YLLs/YLDs ratio for PM pollution in 2019, respectively. Conclusions Although the total age-standardized rate of DALYs for PM-attributed cardiovascular diseases diminished from 1990 to 2019, the global burden of PM on cardiovascular diseases has increased. The differences between men and women and between regions have clinical and policy implications in global health planning toward more exact funding and resource allocation, in addition to addressing inequity in health care access.

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.

Impaired PPARγ activation by cadmium exacerbates infection-induced lung injury

Emerging data indicate an association between environmental heavy metal exposure and lung disease, including lower respiratory tract infections (LRTIs). Here, we show by single-cell RNA sequencing an increase in Pparg gene expression in lung macrophages from mice exposed to cadmium and/or infected with Streptococcus pneumoniae. However, the heavy metal cadmium or infection mediated an inhibitory posttranslational modification of peroxisome proliferator-activated receptor γ (PPARγ) to exacerbate LRTIs. Cadmium and infection increased ERK activation to regulate PPARγ degradation in monocyte-derived macrophages. Mice harboring a conditional deletion of Pparg in monocyte-derived macrophages had more severe S. pneumoniae infection after cadmium exposure, showed greater lung injury, and had increased mortality. Inhibition of ERK activation with BVD-523 protected mice from lung injury after cadmium exposure or infection. Moreover, individuals residing in areas of high air cadmium levels had increased cadmium concentration in their bronchoalveolar lavage (BAL) fluid, increased barrier dysfunction, and showed PPARγ inhibition that was mediated, at least in part, by ERK activation in isolated BAL cells. These observations suggest that impaired activation of PPARγ in monocyte-derived macrophages exacerbates lung injury and the severity of LRTIs.

Personal exposure to PM2.5 in different microenvironments and activities for retired adults in two megacities, China

Microenvironmental concentrations and time-activity patterns influence personal exposure to fine particulate matter (PM_2.5). However, the variations and contributions of PM_2.5 exposures from various microenvironments (MEs) and activities remain unclear. In this study, gravimetrically corrected real-time personal PM_2.5 measurements were collected during routine activities in different MEs from 66 non-smoking retired adults. Exposure data were collected for five consecutive days over two seasons in Nanjing (NJ) and Beijing (BJ), China. Measured PM_2.5 concentrations varied substantially both between and within different MEs and activities. The highest average concentrations were observed in restaurants (NJ: mean 192 μg/m³, SD 242 μg/m³; BJ: mean 91 μg/m³, SD 79 μg/m³) and were associated with sources such as passive smoking and cooking emissions. Overall, PM_2.5 concentrations in different MEs and activities were moderately to highly correlated with outdoor PM_2.5 concentrations (Spearman's r = 0.51-0.97) except in restaurants and during passive smoking. The at-home ME contributed approximately 85 % of the total PM_2.5 exposure, corresponding to the participants spending about 87 % of their time there. The majority of household exposures occurred during sleeping, cooking, and other home-based activities. Transportation accounted for <5 % of total exposure. Our results indicate that improving indoor air quality, especially residential indoors, is important to reduce personal exposure to PM_2.5.

Pollution source and chemicals structure of the water-soluble fractions in PM2.5 that induce apoptosis in China

Identify risk drivers is the key condition in air pollution control, and biological effect-directed analysis is the most commented method for combing chemical identify and human health. The water-soluble organic matter contained in PM_2.5 plays an important role in human health, while it is also the most difficult to identify its chemical information. Exploring the structural characteristics and pollution sources of its key toxic components is the optimized strategy to meet this question. In this study, the induction of apoptosis by the water-soluble fractions (WSF) of PM_2.5 samples collected in 10 major cities in China over a period of 1 year was observed in vitro in Beas-2b cells. Organic carbon structures were examined using nuclear magnetic resonance; air potential sources were identified using δ¹³C and ¹⁴C isotopic markers. Apoptosis induction by WSF in PM_2.5 was generally stronger in northern cities than in southern cities, and in winter than in summer. Organic compounds with aromatic and double-bond carbon structures from secondary products of motor vehicle exhausts, coal-derived emissions, and emissions derived from the burning of core residues may be primarily responsible for apoptosis induction by PM_2.5. Our results will contribute to understanding the toxic substances contained in WSF and provide basic data for accurate pollution control.

Is the oxidative potential of components of fine particulate matter surface-mediated?

Redox-active substances in fine particulate matter (PM) contribute to inhalation health risks through their potential to generate reactive oxygen species in epithelial lung lining fluid (ELF). The ELF's air-liquid interface (ALI) can play an important role in the phase transfer and multi-phase reactions of redox-active PM constituents. We investigated the influence of interfacial processes and properties by scrubbing of coated nano-particles with simulated ELF in a nebulizing mist chamber. Weakly water-soluble redox-active organics abundant in ambient fine PM were reproducibly loaded into ELF via ALI mixing. The resulting oxidative potential (OP) of selected quinones and other PAH derivatives were found to exceed the OP resulting from bulk mixing of the same amounts of redox-active substances and ELF. Our results indicate that the OP of PM components depends not only on the PM substance properties but also on the ELF interface properties and uptake mechanisms. OP measurements based on bulk mixing of phases may not represent the effective OP in the human lung.

Evaluation of the efficiency of a Venturi scrubber in particulate matter collection smaller than 2.5 µm emitted by biomass burning

Energy demand has increased worldwide, and biomass burning is one of the solutions most used by industries, especially in countries that have a great potential in agriculture, such as Brazil. However, these energy sources generate pollutants, consisting of particulate matter (PM) with a complex chemical composition, such as sugarcane bagasse (SB) burning. Controlling these emissions is necessary; therefore, the aim was to evaluate PM collection using a rectangular Venturi scrubber (RVS), and its effects on the composition of the PM emitted. Considering the appropriate use of biomass as an industrial fuel and the emerging need for a technique capable of efficiently removing pollutants from biomass burning, this study shows the control of emissions as an innovation in a situation such as the industrial one with the use of a Venturi scrubber in fine particle collection, in addition to using portable and representative isokinetic sampling equipment of these particles. The pilot-scale simulation of the biomass burning process, the representative sampling of fine particles and obtaining parameters to control pollutant emissions for a Venturi scrubber, meets the current situation of concern about air quality. The average collection efficiency values were 96.6% for PM_{> 2.5}, 85.5% for PM_1.0-2.5, and 66.9% for PM_{< 1.0}. The ionic analysis for PM_{< 1.0} filters showed potassium, chloride, nitrate, and nitrite at concentrations ranging from 20.12 to 36.5 μg/m³. As the ethanol and sugar plants will continue to generate electricity with sugarcane bagasse burning, emission control technologies and cost-effective and efficient portable samplers are needed to monitor particulate materials and improve current gas cleaning equipment projects.

Fine particulate matter and cardiorespiratory health in China: A systematic review and meta-analysis of epidemiological studies

This review aimed to systematically summarize the epidemiological literature on the cardiorespiratory effects of PM_2.5 published during the 13^th Five-Year Plan period (2016-2020) in China. Original articles published between January 1, 2016 and June 30, 2021 were searched in PubMed, Web of Science, the China National Knowledge Internet Database and Wanfang Database. Random- or fixed-effects models were used to pool effect estimates where appropriate. Of 8558 records identified, 145 met the full eligibility criteria. A 10 µg/m³ increase in short-term PM_2.5 exposure was significantly associated with increases of 0.70%, 0.86%, 0.38% and 0.96% in cardiovascular mortality, respiratory mortality, cardiovascular morbidity, and respiratory morbidity, respectively. The specific diseases with significant associations included stroke, ischemic heart disease, heart failure, arrhythmia, chronic obstructive pulmonary disease, pneumonia and allergic rhinitis. The pooled estimates per 10 µg/m³ increase in long-term PM_2.5 exposure were 15.1%, 11.9% and 21.0% increases in cardiovascular, stroke and lung cancer mortality, and 17.4%, 11.0% and 4.88% increases in cardiovascular, hypertension and lung cancer incidence respectively. Adverse changes in blood pressure, heart rate variability, systemic inflammation, blood lipids, lung function and airway inflammation were observed for either short-term or long-term PM_2.5 exposure, or both. Collectively, we summarized representative exposure-response relationships between short- and long-term PM_2.5 exposure and a wide range of cardiorespiratory outcomes applicable to China. The magnitudes of estimates were generally smaller in short-term associations and comparable in long-term associations compared with those in developed countries. Our findings are helpful for future standard revisions and policy formulation. There are still some notable gaps that merit further investigation in China.

A comprehensive understanding of ambient particulate matter and its components on the adverse health effects based from epidemiological and laboratory evidence

The impacts of air pollution on public health have become a great concern worldwide. Ambient particulate matter (PM) is a major air pollution that comprises a heterogeneous mixture of different particle sizes and chemical components. The chemical composition and physicochemical properties of PM change with space and time, which may cause different impairments. However, the mechanisms of the adverse effects of PM on various systems have not been fully elucidated and systematically integrated. The Adverse Outcome Pathway (AOP) framework was used to comprehensively illustrate the molecular mechanism of adverse effects of PM and its components, so as to clarify the causal mechanistic relationships of PM-triggered toxicity on various systems. The main conclusions and new insights of the correlation between public health and PM were discussed, especially at low concentrations, which points out the direction for further research in the future. With the deepening of the study on its toxicity mechanism, it was found that PM can still induce adverse health effects with low-dose exposure. And the recommended Air Quality Guideline level of PM_2.5 was adjusted to 5 μg/m³ by World Health Organization, which meant that deeper and more complex mechanisms needed to be explored. Traditionally, oxidative stress, inflammation, autophagy and apoptosis were considered the main mechanisms of harmful effects of PM. However, recent studies have identified several emerging mechanisms involved in the toxicity of PM, including pyroptosis, ferroptosis and epigenetic modifications. This review summarized the comprehensive evidence on the health effects of PM and the chemical components of it, as well as the combined toxicity of PM with other air pollutants. Based on the AOP Wiki and the mechanisms of PM-induced toxicity at different levels, we first constructed the PM-related AOP frameworks on various systems.

Chemical explosion, COVID-19, and environmental justice: Insights from low-cost air quality sensors

OBJECTIVES

To examine the impact of the Intercontinental Terminals Company (ITC) fire and COVID-19 on airborne particulate matter (PM) concentrations and the PM disproportionally affecting communities in Houston using low-cost sensors.

METHODS

We compared measurements from a network of low-cost sensors with a separate network of monitors from the Environmental Protection Agency (EPA) in the Houston metropolitan area from Mar 18, 2019, to Dec 31, 2020. Further, we examined the associations between neighborhood-level sociodemographic status and air pollution patterns by linking the low-cost sensor data to EPA environmental justice screening and mapping systems.

FINDINGS

We found increased PM levels during ITC fire and pre-COVID-19, and lower PM levels after the COVID-19 lockdown, comparable to observations from the regulatory monitors, with higher variations and a greater number of locations with high PM levels detected. In addition, the environmental justice analysis showed positive associations between higher PM levels and the percentage of minority, low-income population, and demographic index.

IMPLICATION

Our study indicates that low-cost sensors provide pollutant measures with higher spatial variations and a better ability to identify hot spots and high peak concentrations. These advantages provide critical information for disaster response and environmental justice studies.

SYNOPSIS

We used measurements from a low-cost sensor network for air pollution monitoring and environmental justice analysis to examine the impact of anthropogenic and natural disasters.

Tracking Daily Concentrations of PM2.5 Chemical Composition in China since 2000

PM_2.5 chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely updated information on China's PM_2.5 chemical composition is the basis for research and environmental management. Here, we developed a full-coverage near-real-time PM_2.5 chemical composition data set at 10 km spatial resolution since 2000, combining the Weather Research and Forecasting-Community Multiscale Air Quality modeling system, ground observations, a machine learning algorithm, and multisource-fusion PM_2.5 data. PM_2.5 chemical components in our data set are in good agreement with the available observations (correlation coefficients range from 0.64 to 0.75 at a monthly scale from 2000 to 2020 and from 0.67 to 0.80 at a daily scale from 2013 to 2020; most normalized mean biases within ±20%). Our data set reveals the long-term trends in PM_2.5 chemical composition in China, especially the rapid decreases after 2013 for sulfate, nitrate, ammonium, organic matter, and black carbon, at the rate of -9.0, -7.2, -8.1, -8.4, and -9.2% per year, respectively. The day-to-day variability is also well captured, including evolutions in spatial distribution and shares of PM_2.5 components. As part of Tracking Air Pollution in China (http://tapdata.org.cn), this daily-updated data set provides large opportunities for health and climate research as well as policy-making in China.

Effect of PM2.5 Levels on ED Visits for Respiratory Causes in a Greek Semi-Urban Area

Fine particulate matter that have a diameter of <2.5 μm (PM2.5) are an important factor of anthropogenic pollution since they are associated with the development of acute respiratory illnesses. The aim of this prospective study is to examine the correlation between PM2.5 levels in the semi-urban city of Volos and Emergency Department (ED) visits for respiratory causes. ED visits from patients with asthma, pneumonia and upper respiratory infection (URI) were recorded during a one-year period. The 24 h PM2.5 pollution data were collected in a prospective manner by using twelve fully automated air quality monitoring stations. PM2.5 levels exceeded the daily limit during 48.6% of the study period, with the mean PM2.5 concentration being 30.03 ± 17.47 μg/m3. PM2.5 levels were significantly higher during winter. When PM2.5 levels were beyond the daily limit, there was a statistically significant increase in respiratory-related ED visits (1.77 vs. 2.22 visits per day; p: 0.018). PM2.5 levels were also statistically significantly related to the number of URI-related ED visits (0.71 vs. 0.99 visits/day; p = 0.01). The temperature was negatively correlated with ED visits (r: −0.21; p < 0.001) and age was found to be positively correlated with ED visits (r: 0.69; p < 0.001), while no statistically significant correlation was found concerning humidity (r: 0.03; p = 0.58). In conclusion, PM2.5 levels had a significant effect on ED visits for respiratory causes in the city of Volos.

Particulate matter exposure at urban traffic intersection during haze episodes: A case study in Changsha

Urban intersection has been identified as a major contributor to the total personal exposure and short-term high exposure of particulate matter (PM) in modern cities. The main aim of this study was to get a better understanding of the determinants of traffic-related PM temporal variations and personal exposure to PMs at a viaduct-covered intersection controlled by traffic signals during the winter haze episodes. A two-day field sampling campaign was conducted with a portable device during evening rush hour and measured the PMs in the 0.3-10 μm size range both on the surface crosswalk and underground passage. PM variations and related cumulative respiratory deposition dose (RDD) along two routes with six road crossing scenarios were estimated on a severe pollution day and a typical day for both adults and children, respectively. The PM concentration on the severe pollution day ranged 59.2-67.9 μg/m³ for PM₁, 163.8-257.0 μg/m³ for PM₂, and 258.2-469.1 μg/m³ for PM₁₀, respectively, as compared to 47.9-57.9 μg/m³for PM₁, 112.7-199.8 μg/m³ for PM₂, and 151.0-301.0 μg/m³ for PM₁₀ on the typical day, respectively. The variability could be explained largely by the built-up environment, traffic component, signal setting, and ventilation condition. Our data suggest that an appropriate setting of the traffic signal would help reduce the personal exposure dose on the surface crosswalk at urban intersections and the ventilation condition had a significant influence on local PM distributions inside the underground passage. Results here provide possible suggestions for the future design of a walkable city.

The global burden of disease attributable to ambient fine particulate matter in 204 countries and territories, 1990-2019: A systematic analysis of the Global Burden of Disease Study 2019

Understanding the spatio-temporal patterns of the disease burden attributable to ambient PM2.5 across the world is essential for the prevention of related diseases, as well as ambient PM2.5 control. Following the framework and methodology of the Global Burden of Disease Study (GBD) in 2019, the global, regional, and national data on ambient PM2.5-attributable death and disability-adjusted life years (DALYs), and the age-standardized rates of mortality (ASMR) and disability-adjusted life years (ASDR) were summarized based on age, gender, year, location and specific diseases. We calculated the average annual percentage change (AAPC) to depict the secular trends of ASMR and ASDR from 1990 to 2019. In 2019, the global ambient PM2.5-related deaths and DALYs were 4,140,970 and 118.2 million, respectively, with 1,702,150 deaths and 47.5 million DALYs for females and 2,438,820 deaths and 70.7 million DALYs for male. In the 13 level-three causes, ischemic heart disease, stroke, chronic obstructive and pulmonary disease (COPD) were the leading three causes of deaths and DALYs attributable to ambient PM2.5. The number of global deaths and DALYs attributable to ambient PM2.5 has increased by 102.3% and 67.7% from 1990 to 2019, respectively. However, ASMR and ASDR showed little change. In the 13 level-three diseases, ischemic heart disease, stroke, COPD, diabetes mellitus, and lung cancer were the top five contributors to the increase of global deaths or DALYs, among which diabetes mellitus had the fastest increase of ASMR and ASDR, with AAPC of 1.5 (95% CI: 1.43, 1.58) and 2.21 (95% CI: 2.15, 2.27), respectively. The population attributable fractions (PAF) of causes in ASMR or ASDR varied significantly across regions, of which PAF of COPD, stroke and lung cancer were the top three. Regarding the GBD region, high PAF mainly occurred in North Africa and Middle East, South Asia, and East Asia. The age-specific PAFs of ischemic heart disease and stroke deaths and DALYs due to ambient PM2.5 were negatively correlated with age. ASMR and ASDR of overall PM2.5 related-burden showed an inverted "V/U" relationship with the socio-demographic index (SDI). The AAPC of ASMR and ASDR of the overall causes showed a strong negative correlation with SDI in 2019, especially at the SDI larger than 0.5. The deaths and DALYs attributable to ambient PM2.5 continued to increase under the context of population growth and aging. Decision-makers should consider controlling the PM2.5 emission when developing the economy.

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.

Application of an Improved Gas-constrained Source Apportionment Method Using Data Fused Fields: a Case Study in North Carolina, USA

A number of studies have found differing associations of disease outcomes with PM_2.5 components (or species) and sources (e.g., biomass burning, diesel vehicles and gasoline vehicles). Here, a unique method of fusing daily chemical transport model (Community Multiscale Air Quality Modeling) results with observations has been utilized to generate spatiotemporal fields of the concentrations of major gaseous pollutants (CO, NO₂, NO_x, O₃, and SO₂), total PM_2.5 mass, and speciated PM_2.5 (including crustal elements) over North Carolina for 2002-2010. The fused results are then used in chemical mass balance source apportionment model, CMBGC-Iteration, which uses both gas constraint and particulate matter concentrations to quantify source impacts. The method, as applied to North Carolina, quantifies the impacts of ten source categories and provides estimates of source contributions to PM_2.5 concentrations. The ten source categories include both primary sources (diesel vehicles, gasoline vehicles, dust, biomass burning, coal-fired power plants and sea salt) and secondary components (ammonium sulfate, ammonium bisulfate, ammonium nitrate and secondary organic carbon). The results show a steady decrease in anthropogenic source impacts, especially from diesel vehicles and coal-fired power plants. Secondary pollutant components accounted for approximately 70% of PM_2.5 mass. This study demonstrates an ability to provide spatiotemporal fields of both PM components and source impacts using a chemical transport model fused with observation data, linked to a receptor-based source apportionment method, to develop spatiotemporal fields of multiple pollutants.

Sources of cellular oxidative potential of water-soluble fine ambient particulate matter in the Midwestern United States

We investigated the spatiotemporal distribution and sources of cellular oxidative potential (OP) in the Midwest US. Weekly samples were collected from three urban [Chicago (IL), Indianapolis (IN), and St. Louis (MO)], one rural [Bondville (IL], and one roadside site [Champaign (IL)] for a year (May 2018 to May 2019), and analyzed for water-soluble cellular OP using a macrophage reactive oxygen species (ROS) assay. Chemical composition of the samples including several carbonaceous components, inorganic ions, and water-soluble elementals, were also analyzed. The emission sources contributing to water-soluble cellular OP and PM_2.5 mass were analyzed using positive matrix factorization. The secondary organic aerosols contributed substantially (≥54%) to PM_2.5 cellular OP at urban sites, while the roadside and rural OP were dominated by road dust (54%) and agricultural activities (62%), respectively. However, none of these sources contributed substantially to the PM_2.5 mass (≤21%). Other sources contributing significantly to the PM_2.5 mass, i.e., secondary sulfate and nitrate, biomass burning and coal combustion (14-26%) contributed minimally to the cellular OP (≤13%). Such divergent profiles of the emission sources contributing to cellular OP vs. PM_2.5 mass demonstrate the need of considering more health-relevant metrics such as OP in the design of air pollution control strategies.

Black Carbon Emissions and Associated Health Impacts of Gas Flaring in the United States

Gas flaring from oil and gas fields is a significant source of black carbon (BC) emissions, a component of particulate matter that damages health and warms the climate. Observations from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite instrument indicate that approximately 17.2 billion cubic meters (bcm) of gas was flared from upstream oil and gas operations in the United States in 2019. Based on an emissions factor equation that accounts for the higher heating value of the gas, that corresponded to nearly 16,000 tons of BC emitted, though estimates vary widely across published emissions factors. In this study, we used three reduced-form air quality and health effect models to estimate the health impacts from the flaring-emitted BC particulate matter in the United States. The three models—EASIUR, AP3, and InMAP—predict 26, 48, and 53 premature deaths, respectively, in 2019. The mortality range expands from 5 to 360 deaths annually if alternative emission factors are used. This study shows that reduced-form models can be useful to estimate the impacts of numerous dispersed emissions sources such as flares, and that further research is needed to better quantify BC emissions factors from flares.

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.

Mechanisms and Pathways for Coordinated Control of Fine Particulate Matter and Ozone

PURPOSE OF REVIEW

Fine particulate matter (PM_2.5) and ground-level ozone (O₃) pose a significant risk to human health. The World Health Organization (WHO) has recently revised healthy thresholds for both pollutants. The formation and evolution of PM_2.5 and O₃ are however governed by complex physical and multiphase chemical processes, and therefore, it is extremely challenging to mitigate both pollutants simultaneously. Here, we review mechanisms and discuss the science-informed pathways for effective and simultaneous mitigation of PM_2.5 and O₃.

RECENT FINDINGS

Global warming has led to a general increase in biogenic emissions, which can enhance the formation of O₃ and secondary organic aerosols. Reductions in anthropogenic emissions during the COVID-19 lockdown reduced PM_2.5; however, O₃ was enhanced in several polluted regions. This was attributed to more intense sunlight due to low aerosol loading and non-linear response of O₃ to NO _x . Such contrasting physical and chemical interactions hinder the formulation of a clear roadmap for clean air over such regions.

SUMMARY

Atmospheric chemistry including the role of biogenic emissions, aerosol-radiation interactions, boundary layer, and regional-scale transport are the key aspects that need to be carefully considered in the formulation of mitigation pathways. Therefore, a thorough understanding of the chemical effects of the emission reductions, changes in photolytic rates and boundary layer due to perturbation of solar radiation, and the effect of meteorological/seasonal changes are needed on a regional basis. Statistical emulators and machine learning approaches can aid the cumbersome process of multi-sector multi-species source attribution.

Exposure to combustion derived particulate matter exacerbates influenza infection in neonatal mice by inhibiting IL22 production

Background

Particulate matter (PM) containing environmentally persistent free radicals (EPFRs) are formed during various combustion processes, including the thermal remediation of hazardous wastes. Exposure to PM adversely affects respiratory health in infants and is associated with increased morbidity and mortality due to acute lower respiratory tract infections. We previously reported that early-life exposure to PM damages the lung epithelium and suppresses immune responses to influenza virus (Flu) infection, thereby enhancing Flu severity. Interleukin 22 (IL22) is important in resolving lung injury following Flu infection. In the current study, we determined the effects of PM exposure on pulmonary IL22 responses using our neonatal mouse model of Flu infection.

Results

Exposure to PM resulted in an immediate (0.5–1-day post-exposure; dpe) increase in IL22 expression in the lungs of C57BL/6 neonatal mice; however, this IL22 expression was not maintained and failed to increase with either continued exposure to PM or subsequent Flu infection of PM-exposed mice. This contrasts with increased IL22 expression in age-matched mice exposed to vehicle and Flu infected. Activation of the aryl hydrocarbon receptor (AhR), which mediates the induction and release of IL22 from immune cells, was also transiently increased with PM exposure. The microbiome plays a major role in maintaining epithelial integrity and immune responses by producing various metabolites that act as ligands for AhR. Exposure to PM induced lung microbiota dysbiosis and altered the levels of indole, a microbial metabolite. Treatment with recombinant IL22 or indole-3-carboxaldehyde (I3A) prevented PM associated lung injury. In addition, I3A treatment also protected against increased mortality in Flu-infected mice exposed to PMs.

Conclusions

Together, these data suggest that exposure to PMs results in failure to sustain IL22 levels and an inability to induce IL22 upon Flu infection. Insufficient levels of IL22 may be responsible for aberrant epithelial repair and immune responses, leading to increased Flu severity in areas of high PM.

Associations between ambient fine particulate matter and child respiratory infection: The role of particulate matter source composition in Dhaka, Bangladesh

Air pollution in the form of fine particulate matter (PM_2.5) has been linked to adverse respiratory outcomes in children. However, the magnitude of this association in South Asia and sources of PM_2.5 that drive adverse health effects are largely unknown. This study evaluates associations between short-term variation in ambient PM_2.5 and incidence of pneumonia and upper respiratory infections among children in Dhaka, Bangladesh. We also perform an exploratory analysis of the PM_2.5 source composition that is most strongly associated with health endpoints. We leveraged data from health surveillance of children less than five years of age between 2005 and 2014 in Kamalapur, Bangladesh, including daily physician-confirmed diagnoses of pneumonia and upper respiratory infection. Twice-weekly source-apportioned ambient PM_2.5 measurements were obtained for the same period, and Poisson regression adjusted for time-varying covariates was used to estimate lagged associations between ambient PM_2.5 and respiratory infection. We use complementary matching and stratification approaches to evaluate whether these associations vary across PM_2.5 source composition. Total PM_2.5 mass was associated with a modest increase in incidence of pneumonia, with a peak effect size two days after exposure (rate ratio = 1.032; 95% confidence interval = 1.008-1.056). We did not identify a significant association between PM_2.5 and upper respiratory infection. Stratified and matching analyses suggested this association was stronger among days when ambient PM_2.5 had a higher mass percent associated with brick kiln and fugitive lead emissions.: This study suggests that elevated ambient PM_2.5 contributes to increased incidence of child pneumonia in urban Dhaka, and that this relationship varies among days with different source composition of PM_2.5.

Potential impacts of prescribed fire smoke on public health and socially vulnerable populations in a Southeastern U.S. state

Prescribed fire is an essential tool for wildfire risk mitigation and ecosystem restoration in the Southeastern United States. It is also one of the region's largest sources of atmospheric emissions. The public health impacts of prescribed fire smoke, however, remain uncertain. Here, we use digital burn permit records, reduced-complexity air quality modeling, and epidemiological associations between fine particulate matter concentrations and multiple health endpoints to assess the impacts of prescribed burning on public health across Georgia. Additionally, we examine the social vulnerability of populations near high prescribed burning activity using a demographic- and socioeconomic-based index. The analysis identifies spatial clusters of burning activity in the state and finds that areas with intense prescribed fire have levels of social vulnerability that are over 25% higher than the state average. The results also suggest that the impacts of burning in Georgia can potentially include hundreds of annual morbidity and mortality cases associated with smoke pollution. These health impacts are concentrated in areas with higher fractions of low socioeconomic status, elderly, and disabled residents, particularly vulnerable to air pollution. Estimated smoke-related health incidence rates are over 3 times larger than the state average in spatial clusters of intense burning activity, and over 40% larger in spatial clusters of high social vulnerability. Spatial clusters of low social vulnerability experience substantially lower negative health effects from prescribed burning relative to the rest of the state. The health burden of smoke from prescribed burns in the state is comparable to that estimated for other major emission sectors, such as vehicles and industrial combustion. Within spatial clusters of socially-vulnerable populations, the impacts of prescribed fire considerably outweigh those of other emission sectors. These findings call for greater attention to the air quality impacts of prescribed burning in the Southeastern U.S. and the communities most exposed to fire-related smoke.

Hydroxyl Radical Production by Air Pollutants in Epithelial Lining Fluid Governed by Interconversion and Scavenging of Reactive Oxygen Species

Air pollution is a major risk factor for human health. Chemical reactions in the epithelial lining fluid (ELF) of the human respiratory tract result in the formation of reactive oxygen species (ROS), which can lead to oxidative stress and adverse health effects. We use kinetic modeling to quantify the effects of fine particulate matter (PM2.5), ozone (O₃), and nitrogen dioxide (NO₂) on ROS formation, interconversion, and reactivity, and discuss different chemical metrics for oxidative stress, such as cumulative production of ROS and hydrogen peroxide (H₂O₂) to hydroxyl radical (OH) conversion. All three air pollutants produce ROS that accumulate in the ELF as H₂O₂, which serves as reservoir for radical species. At low PM2.5 concentrations (<10 μg m^-3), we find that less than 4% of all produced H₂O₂ is converted into highly reactive OH, while the rest is intercepted by antioxidants and enzymes that serve as ROS buffering agents. At elevated PM2.5 concentrations (>10 μg m^-3), however, Fenton chemistry overwhelms the ROS buffering effect and leads to a tipping point in H₂O₂ fate, causing a strong nonlinear increase in OH production. This shift in ROS chemistry and the enhanced OH production provide a tentative mechanistic explanation for how the inhalation of PM2.5 induces oxidative stress and adverse health effects.

A review on the role of dispersion and receptor models in asthma research

There is substantial evidence that air pollution exposure is associated with asthma prevalence that affects millions of people worldwide. Air pollutant exposure can be determined using dispersion models and refined with receptor models. Dispersion models offer the advantage of giving spatially distributed outdoor pollutants concentration while the receptor models offer the source apportionment of specific chemical species. However, the use of dispersion and/or receptor models in asthma research requires a multidisciplinary approach, involving experts on air quality and respiratory diseases. Here, we provide a literature review on the role of dispersion and receptor models in air pollution and asthma research, their limitations, gaps and the way forward. We found that the methodologies used to incorporate atmospheric dispersion and receptor models in human health studies may vary considerably, and several of the studies overlook features such as indoor air pollution, model validation and subject pathway between indoor spaces. Studies also show contrasting results of relative risk or odds ratio for a health outcome, even using similar methodologies. Dispersion models are mostly used to estimate air pollution levels outside the subject's home, school or workplace; however, very few studies addressed the subject's routines or indoor/outdoor relationships. Conversely, receptor models are employed in regions where asthma incidence/prevalence is high or where a dispersion model has been previously used for this assessment. Road traffic (vehicle exhaust) and NOx are found to be the most targeted source and pollutant, respectively. Other key findings were the absence of a standard indicator, shortage of studies addressing VOC and UFP, and the shift toward chemical speciation of exposure.

The effect of air pollution on the transcriptomics of the immune response to respiratory infection

Combustion related particulate matter air pollution (PM) is associated with an increased risk of respiratory infections in adults. The exact mechanism underlying this association has not been determined. We hypothesized that increased concentrations of combustion related PM would result in dysregulation of the innate immune system. This epidemiological study includes 111 adult patients hospitalized with respiratory infections who underwent transcriptional analysis of their peripheral blood. We examined the association between gene expression at the time of hospitalization and ambient measurements of particulate air pollutants in the 28 days prior to hospitalization. For each pollutant and time lag, gene-specific linear models adjusting for infection type were fit using LIMMA (Linear Models For Microarray Data), and pathway/gene set analyses were performed using the CAMERA (Correlation Adjusted Mean Rank) program. Comparing patients with viral and/or bacterial infection, the expression patterns associated with air pollution exposure differed. Adjusting for the type of infection, increased concentrations of Delta-C (a marker of biomass smoke) and other PM were associated with upregulation of iron homeostasis and protein folding. Increased concentrations of black carbon (BC) were associated with upregulation of viral related gene pathways and downregulation of pathways related to antigen presentation. The pollutant/pathway associations differed by lag time and by type of infection. This study suggests that the effect of air pollution on the pathogenesis of respiratory infection may be pollutant, timing, and infection specific.

Examining fine particulate matter and cause-specific morbidity during the 2017 North San Francisco Bay wildfires

BACKGROUND

Recent increases in wildfire frequency and severity necessitate better understanding of health effects of wildfire smoke to protect affected populations.

OBJECTIVES

We examined relationships between fine particulate matter (PM_2.5) and morbidity during wildfires in California, and whether those relationships differed during the fire compared to a similar non-fire period.

METHODS

For nine San Francisco Bay Area counties, daily county-level diagnosis-specific counts of emergency department visits (EDVs) and hospitalizations were linked with county-level estimates of daily mean PM_2.5 during the October 2017 Northern California wildfires and similar October days in 2015, 2016, and 2017. Associations were estimated using Poisson regression.

RESULTS

The median difference between county PM_2.5 during the fire versus the non-fire period was 23.4 μg/m³, with days exceeding 80 μg/m³ in some counties. Over the entire study period, PM_2.5 was most consistently linked to EDVs for respiratory disease (RR_EDV(lag0) per 23.4 μg/m³ increase: 1.25, 95% CI: 1.21, 1.30), asthma, chronic lower respiratory disease (CLRD; RR_EDV(lag0): 1.18, 95% CI: 1.10, 1.27), and acute myocardial infarction (RR_EDV(lag0): 1.14, 95% CI: 1.03, 1.25). Increases in acute upper respiratory infections and decreases in mental/behavioral EDVs were observed but were sensitive to model specification, specifically the inclusion of time-related covariates. Comparing fire and non-fire period EDV associations, we observed indications that PM_2.5 during the fire was more strongly associated with asthma (RR_lag0: 1.46, 95% CI: 1.38, 1.55) compared to non-fire period PM_2.5 (RR_lag0: 0.77, 95% CI: 0.55, 1.08)_, and the opposite observed for dysrhythmia, with the asthma difference being particularly robust to model choice. For hospitalizations, the most robust PM_2.5 relationships were positive associations with respiratory, CLRD, and diabetes, and inverse associations with pneumonia. Respiratory and CLRD effect estimates were generally similar or smaller than for EDVs.

CONCLUSIONS

Elevated short-term PM_2.5 levels from wildfire smoke appears to impact respiratory and other health domains.

Short-term health effects from outdoor exposure to biomass burning emissions: A review

Biomass burning (BB) including forest, bush, prescribed fires, agricultural fires, residential wood combustion, and power generation has long been known to affect climate, air quality and human health. With this work we supply a systematic review on the health effects of BB emissions in the framework of the WHO activities on air pollution. We performed a literature search of online databases (PubMed, ISI, and Scopus) from year 1980 up to 2020. A total of 81 papers were considered as relevant for mortality and morbidity effects. High risk of bias was related with poor estimation of BB exposure and lack of adjustment for important confounders. PM10 and PM2.5 concentrations originating from BB were associated with all-cause mortality: the meta-analytical estimate was equal to 1.31% (95% CI 0.71, 1.71) and 1.92% (95% CI -1.19, 5.03) increased mortality per each 10 μg m^-3 increase of PM10 and PM2.5, respectively. Regarding cardiovascular mortality 8 studies reported quantitative estimates. For smoky days and for each 10 μg m^-3 increase in PM2.5 concentrations, the risk of cardiovascular mortality increased by 4.45% (95% CI 0.96, 7.95) and by 3.30% (95% CI -1.97, 8.57), respectively. Fourteen studies evaluated whether respiratory morbidity was adversely related to PM2.5 (9 studies) or PM10 (5 studies) originating from BB. All found positive associations. The pooled effect estimates were 4.10% (95% CI 2.86, 5.34) and 4.83% (95% CI 0.06, 9.60) increased risk of total respiratory admissions/emergency visits, per 10 μg m^-3 increases in PM2.5 and PM10, respectively. Regarding cardiovascular morbidity, sixteen studies evaluated whether this was adversely related to PM2.5 (10 studies) or PM10 (6 studies) originating from BB. They found both positive and negative results, with summary estimates equal to 3.68% (95% CI -1.73, 9.09) and 0.93% (95% CI -0.18, 2.05) increased risk of total cardiovascular admissions/emergency visits, per 10 μg m^-3 increases in PM2.5 and PM10, respectively. To conclude, a significant number of studies indicate that BB exposure is associated with all-cause and cardiovascular mortality and respiratory morbidity.

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.

Comparisons of simple and complex methods for quantifying exposure to individual point source air pollution emissions

Expanded use of reduced complexity approaches in epidemiology and environmental justice investigations motivates detailed evaluation of these modeling approaches. Chemical transport models (CTMs) remain the most complete representation of atmospheric processes but are limited in applications that require large numbers of runs, such as those that evaluate individual impacts from large numbers of sources. This limitation motivates comparisons between modern CTM-derived techniques and intentionally simpler alternatives. We model population-weighted PM_2.5 source impacts from each of greater than 1100 coal power plants operating in the United States in 2006 and 2011 using three approaches: (1) adjoint PM_2.5 sensitivities calculated by the GEOS-Chem CTM; (2) a wind field-based Lagrangian model called HyADS; and (3) a simple calculation based on emissions and inverse source-receptor distance. Annual individual power plants' nationwide population-weighted PM_2.5 source impacts calculated by HyADS and the inverse distance approach have normalized mean errors between 20 and 28% and root mean square error ranges between 0.0003 and 0.0005 µg m^-3 compared with adjoint sensitivities. Reduced complexity approaches are most similar to the GEOS-Chem adjoint sensitivities nearby and downwind of sources, with degrading performance farther from and upwind of sources particularly when wind fields are not accounted for.

Impact of a Large Fire and Subsequent Pollution Control Failure at a Coke Works on Acute Asthma Exacerbations in Nearby Adult Residents

Clairton, Pennsylvania, is home to the largest coke works facility in the United States (US). On 24 December 2018, a large fire occurred at this facility and damaged pollution control equipment. Although repairs were not completed for several months, production continued at pre-fire capacity and daily emissions increased by 24 to 35 times, with multiple exceedances of monitored levels of outdoor air pollution (OAP). The aim of this study was to objectively evaluate the impact of this industrial incident and resultant OAP exceedances on asthma morbidity. We assessed pre-fire and post-fire rate ratios (RR) of outpatient and emergency department (ED) visits for asthma exacerbations among nearby adult residents. Pre-fire versus post-fire RRs increased for both visit types: RR = 1.82 (95% CI: 1.30, 2.53; p < 0.001) and 1.84 (95% CI: 1.05, 3.22; p = 0.032) for outpatient and ED visits, respectively. Additionally, total visit rates increased on days with OAP exceedances: RR = 2.47 (95% CI: 1.52, 4.01; p < 0.0001), 1.58 (95% CI: 1.00, 2.48; p = 0.048) and 1.79 (95% CI: 1.27, 2.54; p = 0.001) for PM_2.5, SO₂, and H₂S exceedance days, respectively. These results show a near doubling of acute visits for asthma exacerbations in nearby adult residents during this industrial incident and underscore the need for prompt remediation and public notification of OAP exceedances to prevent adverse health impacts.

Associations of fine particulate matter and its constituents with airway inflammation, lung function, and buccal mucosa microbiota in children

BACKGROUND

Previous studies have suggested acute effects of ambient fine particulate matter (PM_2.5) air pollution on respiratory health among children, but evidence for PM_2.5 constituents and respiratory health were still limited.

OBJECTIVES

To investigate associations of short-term exposure to PM_2.5 and its constituents with airway inflammation, lung function, and airway microbiota in children.

METHODS

We conducted a longitudinal panel study with 3 repeated health measurements among 62 children in Shanghai, China from November 2018 to June 2019. Respiratory health was measured by fractional exhaled nitric oxide (FeNO), saliva tumor necrosis factor-α (TNF-α), lung function (forced vital capacity and forced exhaled volume in 1 s), and microbiota diversity in buccal mucosa samples. Based on the linear mixed-effect models, we applied the single-constituent models and the constituent-PM_2.5 adjustment models to examine the associations between PM_2.5 constituents and health outcomes.

RESULT

Short-term exposure to PM_2.5 was associated with higher TNF-α, FeNO levels and reduced lung function. Among all constituents, organic carbon, elemental carbon, NO₃^- and NH₄⁺ had the consistent and strongest associations with airway inflammation biomarkers and lung function parameters, followed by metallic elements. We also found short-term PM_2.5 exposure was associated with decreased diversity in buccal mucosa bacterial community and two bacterial phyla, Fusobacteria and Proteobacteria, were identified as differential microbes with PM_2.5 exposure.

CONCLUSION

Short-term exposure to PM_2.5 may impair children's respiratory health represented by higher airway inflammation, lower lung function and altered buccal mucosa microbial colonization. Organic carbon, elemental carbon, NO₃^- and NH₄⁺ may dominate these effects.

Effect of PM2.5 Levels on Respiratory Pediatric ED Visits in a Semi-Urban Greek Peninsula

Ambient air pollution accounts for an estimated 4.2 million deaths worldwide. Particulate matter (PM)_2.5 particles are believed to be the most harmful, as when inhaled they can penetrate deep into the lungs. The aim of this study was to examine the relationship between PM_2.5 daily air concentrations and pediatric emergency department (ED) visits for respiratory diseases in a Greek suburban area. All pediatric ED visits for asthma-, pneumonia- and upper respiratory infection (URI)-related complaints were recorded during the one-year period. The 24-h PM_2.5 air pollution data were prospectively collected from twelve fully automated air quality monitoring stations. The mean annual concentration of PM_2.5 was 30.03 μg/m³ (World Health Organization (WHO) Air Quality Guidelines (AQG) Annual mean concentration: 10 μg/m³). PM_2.5 levels rose above the WHO Air Quality Guidelines (AQG) 24-h concentrations (25 μg/m³)), 178 times (48.6% of the study period). When PM_2.5 levels were above the daily limit, an increase of 32.44% (p < 0.001) was observed in daily pediatric ED visits for respiratory diseases and the increase was much higher during spring (21.19%, p = 0.018). A 32% (p < 0.001) increase was observed in URI-related visits, when PM_2.5 levels were ≥25 μg/m³, compared to the mean daily visits when PM_2.5 levels were <25 μg/m³. Air pollution levels were associated with increased pediatric ED visits for respiratory-related diseases.

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.

Pollutants from primary sources dominate the oxidative potential of water-soluble PM2.5 in Hong Kong in terms of dithiothreitol (DTT) consumption and hydroxyl radical production

Increasing scientific findings show that the adverse health effects of PM_2.5 are related not only to its mass but also PM_2.5 sources and chemical compositions. Here, we conducted a comprehensive characterization and source apportionment of oxidative potential (OP) of water-soluble PM_2.5 collected in Hong Kong for one year. Two OP indicators, namely dithiothreitol (DTT) consumption and ∙OH formation, were quantified. Six PM_2.5 sources, i.e. secondary sulfate, biomass burning, secondary organic aerosol (SOA), vehicle emissions, marine vessels, and a metal-related factor, were apportioned and identified to be DTT active. The four primary sources accounted for 83.5% of DTT activity of water-soluble PM_2.5, with the metal-related factor and marine vessels as the leading contributors. However, only three sources, i.e. metal-related factor, vehicle emissions, and SOA, showed ∙OH generation ability, with a predominant contribution of 96.2% from the two primary sources, especially the metal-related factor (84.5%). Based on the source apportionment results, we further evaluate the intrinsic OP of water-soluble PM_2.5 from each source. Marine vessels exhibited the highest intrinsic DTT activity; while metal-related factor was most effective in ∙OH generation.

Exposure to different fractions of diesel exhaust PM2.5 induces different levels of pulmonary inflammation and acute phase response

AIM

Ambient fine particulate matter (PM2.5) consists of various components, and their respective contributions to the toxicity of PM2.5 remains to be determined. To provide specific recommendations for preventing adverse effects due to PM2.5 pollution, we determined whether the induction of pulmonary inflammation, the putative pathogenesis for the morbidity and mortality due to PM2.5 exposure, was fractioned through solubility-dependent fractioning.

METHODS

In the present study, the water and heptane solubilities-dependent serial fractioning of diesel exhaust particulate matter (DEP), a prominent source of urban PM2.5 pollution, was performed. The pro-inflammatory actions of these resultant fractions were then determined using both an intratracheal instillation mouse model and cultured BEAS-2B cells, a human bronchial epithelial cell line.

RESULTS

Instillation of the water-insoluble, but not -soluble fraction elicited significant pulmonary inflammatory and acute phase responses, comparable to those induced by instillation of DEP. The water-insoluble fraction was further fractioned using heptane, a polar organic solvent, and instillation of heptane-insoluble, but not -soluble fraction elicited significant pulmonary inflammation and acute phase responses. Furthermore, we showed that DEP and water-insoluble DEP, but not water-soluble DEP, activated pro-inflammatory signaling in cultured BEAS-2B cells, ruling out the possibility that the solubility impacts the in vivo distribution and thus the pulmonary inflammatory response.

Mass dose rates of particle-bound organic pollutants in the human respiratory tract: Implications for inhalation exposure and risk estimations

To date, little is known about the effective doses of airborne particulate matter (PM) and PM-bound hazardous organic components to the human respiratory tract (HRT). In the light of this, here we provide particle mass dose rates (dose per hour of exposure) of PM and a suite of PM-bound hazardous organic compounds in the HRT for two population age groups (adults & children). More specifically, the mass dose rates of PM and PM-bound polycyclic aromatic hydrocarbons (PAHs), nitrated-PAH (NPAHs), polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs) and polybrominated diphenyl ethers (PBDEs) were estimated at two urban sites using a multiple path particle dosimetry model. We find that, in most cases, the total mass doses are following similar variations across sites and seasons as their ambient total concentrations, however their distribution in the HRT is a function of the particle size distributions and the physiological parameters of each age group. More specifically, the majority of the deposited mass of PM and all the chemical components investigated was accumulated in the upper airways instead of the lungs. We further show that children, due to their different physiology, are more susceptible and receive larger fraction of the total mass doses in the deepest parts of the lungs compared to the adults' group. Comparing the traditional method for estimating the inhalation risk, which is based on the ambient concentration of pollutants, and a modified version using the mass dose in the HRT, we find that the former may overestimate the reported risks. The results presented here provide a novel dataset composed by previously undetermined doses of hazardous airborne particulate organic components in the HRT and demonstrate that alternative health risk estimation approaches may capture some variabilities that are traditionally overlooked.

Four Decades of United States Mobile Source Pollutants: Spatial-Temporal Trends Assessed by Ground-Based Monitors, Air Quality Models, and Satellites

On-road emissions sources degrade air quality, and these sources have been highly regulated. Epidemiological and environmental justice studies often use road proximity as a proxy for traffic-related air pollution (TRAP) exposure, and other studies employ air quality models or satellite observations. To assess these metrics' abilities to reproduce observed near-road concentration gradients and changes over time, we apply a hierarchical linear regression to ground-based observations, long-term air quality model simulations using Community Multiscale Air Quality (CMAQ), and satellite products. Across 1980-2019, observed TRAP concentrations decreased, and road proximity was positively correlated with TRAP. For all pollutants, concentrations decreased fastest at locations with higher road proximity, resulting in "flatter" concentration fields in recent years. This flattening unfolded at a relatively constant rate for NO_x, whereas the flattening of CO concentration fields has slowed. CMAQ largely captures observed spatial-temporal NO₂ trends across 2002-2010 but overstates the relationships between CO and elemental carbon fine particulate matter (EC) road proximity. Satellite NO_x measures overstate concentration reductions near roads. We show how this perspective provides evidence that California's on-road vehicle regulations led to substantial decreases in NO₂, NO_x, and EC in California, with other states that adopted California's light-duty automobile standards showing mixed benefits over states that did not adopt these standards.

The short-term effect of PM2.5/O3 on daily mortality from 2013 to 2018 in Hefei, China

This research intends to explore the short-term impacts of PM_2.5/O₃ on daily death in Hefei from 2013 to 2018. Data on daily death of Hefei residents, meteorological factors, and air pollutants were collected from Jan 1, 2013, to Dec 31, 2018. The correlation between PM_2.5/O₃ and daily death in Hefei during the research period was studied by time series analysis. From 2013 to 2018, there were 61,683 non-accidental deaths, including 27,431 cardiovascular deaths, 5587 respiratory deaths, 20,921 malignant tumor deaths, and 1674 diabetes deaths, in Hefei. Annual mean concentrations of PM_2.5, PM₁₀, NO₂, SO₂, CO, and O₃ in Hefei were 66.18, 92.37, 39.75, 15.39, 930, and 79.08 μg m^-3, respectively. An increase of 10 μg m^-3 in PM_2.5 was related with 0.53% (95% CI 0.31-0.75%), 0.93% (95% CI 0.60-1.26%), 0.90% and (95% CI 0.23-1.57%) increase in non-accidental, cardiovascular and respiratory diseases mortality, respectively. The association between ozone and mortality was not significant. In cold seasons, PM_2.5 had a stronger effect on the deaths resulting from non-accidental, cardiovascular, and respiratory diseases. The effect of O₃ on deaths was not significantly different between the cold season and the warm season. Women and the elders (over 65 years) were at high risk of being affected by PM_2.5/O₃. Short-term exposure to PM_2.5 was positively correlated with increased deaths due to non-accidental, cardiovascular and respiratory diseases in Hefei. Females and elders were more vulnerable to PM_2.5/O₃ exposure. No significant associations were observed between ozone and deaths from non-accidental, cardiovascular, respiratory, malignant tumors, and diabetes diseases.

Prolonged Life Expectancy for Those Dying of Stroke by Achieving the Daily PM2.5 Targets

This time-series study collects data on stroke-related mortality, years of life lost (YLL), air pollution, and meteorological conditions in 96 Chinese cities from 2013 to 2016 and proposes a three-stage strategy to generate the national and regional estimations of avoidable YLL, gains in life expectancy and stroke-related population attributable fraction by postulating that the daily fine particulate matter (PM2.5) has been kept under certain standards. A total of 1 318 911 stroke deaths are analyzed. Each 10 µg m-3 increment in PM2.5 at lag03 is associated with a city-mean increase of 0.31 (95% CI: 0.19, 0.44) years of life lost from stroke. A number of 914.11 (95% CI: 538.28, 1288.94) years of city-mean life lost from stoke could be avoided by attaining the WHO's Air Quality Guidelines (AQG) (25 µg m-3). Moreover, by applying the AQG standard, 0.11 (0.08, 0.15) years of life lost might be prevented for each death, and about 0.91% (95% CI: 0.62%, 1.19%) of the total years of life lost from stroke might be explained by the daily excess PM2.5 exposure. This study indicates that stroke patients can have a longer life expectancy if stricter PM2.5 standards are put in place, especially ischemic stroke patients.