Association between short-term exposure to particulate matter air pollution and cause-specific mortality in Changzhou, China

Fine particulate matter-sudden death association modified by ventricular hypertrophy and inflammation: a case-crossover study

Background

Sudden death accounts for approximately 10% of deaths among working-age adults and is associated with poor air quality. Objectives: To identify high-risk groups and potential modifiers and mediators of risk, we explored previously established associations between fine particulate matter (PM2.5) and sudden death stratified by potential risk factors.

Methods

Sudden death victims in Wake County, NC, from 1 March 2013 to 28 February 2015 were identified by screening Emergency Medical Systems reports and adjudicated (n = 399). Daily PM2.5 concentrations for Wake County from the Air Quality Data Mart were linked to event and control periods. Potential modifiers included greenspace metrics, clinical conditions, left ventricular hypertrophy (LVH), and neutrophil-to-lymphocyte ratio (NLR). Using a case-crossover design, conditional logistic regression estimated the OR (95%CI) for sudden death for a 5 μg/m3 increase in PM2.5 with a 1-day lag, adjusted for temperature and humidity, across risk factor strata.

Results

Individuals having LVH or an NLR above 2.5 had PM2.5 associations of greater magnitude than those without [with LVH OR: 1.90 (1.04, 3.50); NLR > 2.5: 1.25 (0.89, 1.76)]. PM2.5 was generally less impactful for individuals living in areas with higher levels of greenspace.

Conclusion

LVH and inflammation may be the final step in the causal pathway whereby poor air quality and traditional risk factors trigger arrhythmia or myocardial ischemia and sudden death. The combination of statistical evidence with clinical knowledge can inform medical providers of underlying risks for their patients generally, while our findings here may help guide interventions to mitigate the incidence of sudden death.

Short-term exposure to PM2.5 and 1.5 million deaths: a time-stratified case-crossover analysis in the Mexico City Metropolitan Area

BACKGROUND

Satellite-based PM2.5 predictions are being used to advance exposure science and air-pollution epidemiology in developed countries; including emerging evidence about the impacts of PM2.5 on acute health outcomes beyond the cardiovascular and respiratory systems, and the potential modifying effects from individual-level factors in these associations. Research on these topics is lacking in low and middle income countries. We aimed to explore the association between short-term exposure to PM2.5 with broad-category and cause-specific mortality outcomes in the Mexico City Metropolitan Area (MCMA), and potential effect modification by age, sex, and SES characteristics in such associations.

METHODS

We used a time-stratified case-crossover study design with 1,479,950 non-accidental deaths from the MCMA for the period of 2004-2019. Daily 1 × 1 km PM2.5 (median = 23.4 μg/m3; IQR = 13.6 μg/m3) estimates from our satellite-based regional model were employed for exposure assessment at the sub-municipality level. Associations between PM2.5 with broad-category (organ-system) and cause-specific mortality outcomes were estimated with distributed lag conditional logistic models. We also fit models stratifying by potential individual-level effect modifiers including; age, sex, and individual SES-related characteristics namely: education, health insurance coverage, and job categories. Odds ratios were converted into percent increase for ease of interpretation.

RESULTS

PM2.5 exposure was associated with broad-category mortality outcomes, including all non-accidental, cardiovascular, cerebrovascular, respiratory, and digestive mortality. A 10-μg/m3 PM2.5 higher cumulative exposure over one week (lag06) was associated with higher cause-specific mortality outcomes including hypertensive disease [2.28% (95%CI: 0.26%-4.33%)], acute ischemic heart disease [1.61% (95%CI: 0.59%-2.64%)], other forms of heart disease [2.39% (95%CI: -0.35%-5.20%)], hemorrhagic stroke [3.63% (95%CI: 0.79%-6.55%)], influenza and pneumonia [4.91% (95%CI: 2.84%-7.02%)], chronic respiratory disease [2.49% (95%CI: 0.71%-4.31%)], diseases of the liver [1.85% (95%CI: 0.31%-3.41%)], and renal failure [3.48% (95%CI: 0.79%-6.24%)]. No differences in effect size of associations were observed between age, sex and SES strata.

CONCLUSIONS

Exposure to PM2.5 was associated with non-accidental, broad-category and cause-specific mortality outcomes beyond the cardiovascular and respiratory systems, including specific death-causes from the digestive and genitourinary systems, with no indication of effect modification by individual-level characteristics.

The interactive effects of extreme temperatures and PM2.5 pollution on mortalities in Jiangsu Province, China

Exposure to extreme temperatures or fine particles is associated with adverse health outcomes but their interactive effects remain unclear. We aimed to explore the interactions of extreme temperatures and PM2.5 pollution on mortalities. Based on the daily mortality data collected during 2015-2019 in Jiangsu Province, China, we conducted generalized linear models with distributed lag non-linear model to estimate the regional-level effects of cold/hot extremes and PM2.5 pollution. The relative excess risk due to interaction (RERI) was evaluated to represent the interaction. The relative risks (RRs) and cumulative relative risks (CRRs) of total and cause-specific mortalities associated with hot extremes were significantly stronger (p < 0.05) than those related to cold extremes across Jiangsu. We identified significantly higher interactions between hot extremes and PM2.5 pollution, with the RERI range of 0.00-1.15. The interactions peaked on ischaemic heart disease (RERI = 1.13 [95%CI: 0.85, 1.41]) in middle Jiangsu. For respiratory mortality, RERIs were higher in females and the less educated. The interaction pattern remained consistent when defining the extremes/pollution with different thresholds. This study provides a comprehensive picture of the interactions between extreme temperatures and PM2.5 pollution on total and cause-specific mortalities. The projected interactions call for public health actions to face the twin challenges, especially the co-appearance of hot extremes and PM pollution.

Daily exposure to PM2.5 and 1.5 million deaths: A time-stratified case-crossover analysis in the Mexico City Metropolitan Area

Background

Satellite-based PM2.5 predictions are being used to advance exposure science and air-pollution epidemiology in developed countries; including emerging evidence about the impacts of PM2.5 on acute health outcomes beyond the cardiovascular and respiratory systems, and the potential modifying effects from individual-level factors in these associations. Research on these topics is lacking in Latin America.

Methods

We used a time-stratified case-crossover study design with 1,479,950 non-accidental deaths from Mexico City Metropolitan Area for the period of 2004-2019. Daily 1×1 km PM2.5 (median=23.4 μg/m3; IQR=13.6 μg/m3) estimates from our satellite-based regional model were employed for exposure assessment at the sub-municipality level. Associations between PM2.5 with broad-category (organ-system) and cause-specific mortality outcomes were estimated with distributed lag conditional logistic models. We also fit models stratifying by potential individual-level effect modifiers including; age, sex, and individual SES-related characteristics namely: education, health insurance coverage, and job categories.

Results

PM2.5 exposure was associated with higher total non-accidental, cardiovascular, cerebrovascular, respiratory, and digestive mortality. A 10-μg/m3 PM2.5 higher cumulative exposure over one week (lag06) was associated with higher cause-specific mortality outcomes including hypertensive disease [2.28% (95%CI: 0.26%-4.33%)], acute ischemic heart disease [1.61% (95%CI: 0.59%-2.64%)], other forms of heart disease [2.39% (95%CI: -0.35%-5.20%)], hemorrhagic stroke [3.63% (95%CI: 0.79%-6.55%)], influenza and pneumonia [4.91% (95%CI: 2.84%-7.02%)], chronic respiratory disease [2.49% (95%CI: 0.71%-4.31%)], diseases of the liver [1.85% (95%CI: 0.31%-3.41%)], and renal failure [3.48% (95%CI: 0.79%-6.24%)]. No differences in effect size of associations were observed between SES strata.

Conclusions

Exposure to PM2.5 was associated with mortality outcomes beyond the cardiovascular and respiratory systems, including specific death-causes from the digestive and genitourinary systems, with no indications of effect modification by individual SES-related characteristics.

Urban air pollution and emergency department visits related to central nervous system diseases

Ambient air pollution has been associated with adverse neurological health outcomes. Ambient pollutants are thought to trigger oxidative stress and inflammation to which vulnerable populations, such as elderly may be particularly susceptible. Our study investigated the possible association between concentrations of ambient air pollutants and the number of emergency department (ED) visits for nervous system disorders among people residing in a large Canadian city. A time-stratified case-crossover study design combining data from the National Ambulatory Care Reporting System (NACRS) and the National Air Pollution Surveillance (NAPS) between 2004 and 2015 was used. Two air quality health indices were considered in additional to specific pollutants, including carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃) and fine particulate matter (PM_2.5). Weather condition data were included in the models. ED visits with a discharge diagnosis were identified using ICD-10 codes (G00-G99). The analysis was stratified by sex and age, also by seasons. The associations were investigated in arrays organized as 18 strata and 15 time lags (in days) for each pollutant. Overall, 140,511 ED visits were included for the analysis. Most ED visits were related to episodic and paroxysmal diagnoses (G40-G47, 64%), with a majority of visits for migraines (G43, 39%). Among females, an increase of 0.1ppm ambient CO was associated with an increased risk of paroxysmal diagnoses at day 1 (RR = 1.019 (95%CI 1.004–1.033)), day 6 (1.024 (1.010–1.039)) and day 7 (1.022 (1.007–1.036). PM_2.5 and SO₂, and air quality indices were similarly associated with ED visits for episodic and paroxysmal disorders in days 6 and 7. Findings highlight that ambient air pollution is associated with an increased number of ED visits for nervous system disorders, particularly visits for paroxysmal diagnoses.

Effect modification by sex for associations of fine particulate matter (PM2.5) with cardiovascular mortality, hospitalization, and emergency room visits: systematic review and meta-analysis

Particulate matter with aerodynamic diameter no larger than 2.5 μm (PM2.5) has been linked to cardiovascular diseases (CVDs) but evidence for vulnerability by sex remains unclear. We performed systematic review and meta-analysis to synthesize the state of scientific evidence on whether cardiovascular risks from PM2.5 differ for men compared to women. The databases Pubmed, Scopus, Embase, and GreenFILE were searched for studies published Jan. 1995 to Feb. 2020. Observational studies conducting subgroup analysis by sex for impacts of short-term or long-term exposure to PM2.5 on target CVDs were included. Data were independently extracted in duplicate and pooled with random-effects meta-regression. Risk ratios (RRs) for long-term exposure and percent changes in outcomes for short-term exposure were calculated per 10 μg/m3 PM2.5 increase. Quality of evidence of risk differences by sex was rated following Grading of Recommendations Assessment, Development and Evaluation (GRADE). A total of 12,502 articles were screened, with 61 meeting inclusion criteria. An additional 32 studies were added from citation chaining. RRs of all CVD mortality for long-term PM2.5 for men and women were the same (1.14; 95% CI: 1.09, 1.22) indicating no statistically different risks. Men and women did not have statistically different risks of daily CVD mortality, hospitalizations from all CVD, ischemic heart disease, cardiac arrest, acute myocardial infarction, and heart failure from short-term PM2.5 exposure (difference in % change in risk per 10 μg/m3 PM2.5: 0.04 (95% CI, -0.42 to 0.51); -0.05 (-0.47 to 0.38); 0.17 (-0.90, 1.24); 1.42 (-1.06, 3.97); 1.33 (-0.05, 2.73); and -0.48 (-1.94, 1.01), respectively). Analysis using GRADE found low or very low quality of evidence for sex differences for PM2.5-CVD risks. In conclusion, this meta-analysis and quality of evidence assessment of current observational studies found very limited evidence of the effect modification by sex for effects of PM2.5 on CVD outcomes in adults, which can inform clinical approaches and policies.

Observed causative impact of fine particulate matter on acute upper respiratory disease: a comparative study in two typical cities in China

Association between fine particulate matter (PM_2.5) and respiratory health has attracted great concern in China. Substantial epidemiological evidences confirm the correlational relationship between PM_2.5 and respiratory disease in many Chinese cities. However, the causative impact of PM_2.5 on respiratory disease remains uncertain and comparative analysis is limited. This study aims to explore and compare the correlational relationship as well as the causal connection between PM_2.5 and upper respiratory tract infection (URTI) in two typical cities (Beijing, Shenzhen) with rather different ambient air environment conditions. The distributed lag nonlinear model (DLNM) was used to detect the correlational relationship between PM_2.5 and URTI by revealing the lag effect pattern of PM_2.5 on URTI. The convergent cross mapping (CCM) method was applied to explore the causal connection between PM_2.5 and URTI. The results from DLNM indicate that an increase of 10 μg/m³ in PM_2.5 concentration is associated with an increase of 1.86% (95% confidence interval: 0.74%-2.99%) in URTI at a lag of 13 days in Beijing, compared with 2.68% (95% confidence interval: 0.99-4.39%) at a lag of 1 day in Shenzhen. The causality detection with CCM quantitatively demonstrates the significant causative influence of PM_2.5 on URTI in both two cities. Findings from the two methods consistently show that people living in low-concentration areas (Shenzhen) are less tolerant to PM_2.5 exposure than those in high-concentration areas (Beijing). In general, our study highlights the adverse health effects of PM_2.5 pollution on the general public in cities with various PM_2.5 levels and emphasizes the needs for the government to provide appropriate solutions to control PM_2.5 pollution, even in cities with low PM_2.5 concentration.

Six air pollutants and cause-specific mortality: a multi-area study in nine counties or districts of Anhui Province, China

Air pollution and its negative effects on health of people have been a global concern. Many studies had found a strong association between air pollutants and risk of death, but few had focused on the effects of six pollutants and rural areas. Our study aimed to investigate the effects of six air pollutants (CO, NO₂, O₃, PM_2.5, PM₁₀, and SO₂) on non-accidental and respiratory deaths in rural areas of Anhui Province by adjusting for confounding factors, and to further clarify which populations were susceptible to death associated with air pollution. In the first phase of the analysis, the generalized additive models were combined with the distributed lag non-linear models to evaluate the individual effects of air pollution on death in each area. In the second stage, random-effects models were used to aggregate the associations between air pollutants and mortality risk in nine areas. Overall, six pollutants had the strongest effects on the risk of death on the lag 07 days. The associations between PM_2.5 and NO₂ and daily non-accidental deaths were strongest, with maximum RR (lag 07): 1.63 (1.37-1.88) and 1.67 (1.37-1.96). The maximum pooled effects of association between six air pollutants and RD were PM_2.5, with RR (lag 07): 1.89 (1.45-2.34). PM_2.5 and PM₁₀ had significant differences between the elderly and the non-elderly with respectively, RRR: 1.22 (1.04-1.41) and 1.26 (1.11-1.42). In general, we found that six air pollutants were the important risk factors for deaths (deaths from respiratory disease and non-accidental) in rural areas of Anhui Province. PM₁₀ and PM_2.5 had a considerable impact on the elderly.

Dose-response relationships between polycyclic aromatic hydrocarbon exposure and blood cell counts among coke oven workers: a sex-stratified analysis

OBJECTIVES

To explore sex differences and dose-response relationships between nine urinary polycyclic aromatic hydrocarbon (PAH) metabolites and neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and complete blood counts among coke oven workers.

DESIGN AND SETTING

A cross-sectional study with stratified sex was conducted in Shanxi, China.

PARTICIPANTS

A total of 458 male workers and 226 female workers were selected.

PRIMARY AND SECONDARY OUTCOME MEASURES

General linear models, p values for trend tests and natural cubic spline models were used to explore the dose-response relationships between nine urinary PAH metabolites and NLR, PLR and complete blood counts.

RESULT

Compared with male workers, female workers had lower exposure level of PAH (0.95 ng/mL vs 1.38 ng/mL). Only among female workers did we observe that a 1-unit increase in lg(1-OHPyr) was related to a 0.149 (95% CI: 0.055 to 0.242; p for trend=0.041) and 0.103 (95% CI: 0.025 to 0.181; p for trend=0.007) increase in lg(NLR) and lg(PLR), and a 0.116 (95% CI: -0.179 to -0.054; p for trend=0.007) decrease in lg(lymphocyte counts (LYMs)). A 1-unit increase in lg(2-OHNap) was related to a 0.045 (95% CI: 0.003 to 0.086; p for trend=0.037) increase in lg(PLR) and a 0.029 (95% CI: -0.056 to -0.002; p for trend=0.030) and 0.016 (95% CI: -0.029 to -0.003; p for trend=0.010) decrease in lg(white blood cell counts (WBCs)) and lg(haemoglobin (HGB)).

CONCLUSION

Female workers' NLR, PLR, WBCs, HGB and LYMs may be more susceptible than those of male workers when affected by PAH.

A geodatabase of blood pressure level and the associated factors including lifestyle, nutritional, air pollution, and urban greenspace

Objectives

Hypertension is a prevalent chronic disease globally. A multifaceted combination of risk factors is associated with hypertension. Scientific literature has shown the association among individual and environmental factors with hypertension, however, a comprehensive database including demographic, environmental, individual attributes and nutritional status has been rarely studied. Moreover, an integrated spatial-epidemiological approach has been scarcely researched. Therefore, this study aims to provide and describe a geodatabase including individual-based and socio-environmental data related to people living in the city of Mashhad, Iran in 2018.

Data description

The database has been extracted from the PERSIAN Organizational Cohort study in Mashhad University of Medical Sciences. The data note includes three shapefiles and a help file. The shapefile format is a digital vector storage format for storing geometric location and associated attribute information. The first shapefile includes the data of population, air pollutants and amount of available green space for each census block of the city. The second shapefile consists of aggregated blood pressure data to the census blocks of the city. The third shapefile comprises the individual characteristics data (i.e., demographic, clinical, and lifestyle). Finally, the fourth file is a guide to the previous data files for users.

Impact of ambient fine particulate matter on emergency department admissions for circulatory system disease in a city in Northeast China

The cardiovascular impact of fine particles has caused great concern worldwide. However, evidences on the impact of fine particulate matter (PM_2.5) on emergency department (ED) admissions for circulatory system disease in Northeast China is limited. We assessed the acute, lag, cumulative, and harvesting effects of PM_2.5 on ED admissions for circulatory system diseases and their exposure-response relationship. A total of 26,168 ED admissions, including those for hypertension, ischemic heart disease (IHD), arrhythmia, heart failure (HF), and cerebrovascular events (CVE), were collected from the Shenyang Emergency Center from 1 January 2017 to 31 December 2018. The relationship between PM_2.5 and ED admissions for circulatory system disease was estimated using a distributed lag non-linear model and a generalized additive quasi-Poisson model. We stratified the analyses by temperature. Air pollution was positively correlated with daily ED admissions for circulatory system disease or other cause-specific diseases under different lag structures. For every 10-μg/m³ increase in the PM_2.5 concentration, the relative risk of daily ED admissions for circulatory system disease was 1.007 [95% confidence interval (CI), 1.001-1.013] in lag0, 1.007 (95%CI, 1.000-1.013) in lag1, and 1.011 (95%CI, 1.002-1.021) in lag03. A lag effect was found in IHD, a cumulative effect was found in CVE, and both lag and cumulative effects were found in hypertension and arrhythmia. A harvesting effect was observed in daily ED admissions for circulatory system disease and HF. We found no interaction between pollutants and temperature. We observed a monotonic and almost linear exposure-response relationship between PM_2.5 and circulatory system disease with no threshold effect.PM_2.5 contributes to obvious acute, lag, cumulative, and harvesting effects on circulatory system disease. PM_2.5 was associated with the risk of daily ED admissions for circulatory system disease, hypertension, IHD, arrhythmia, HF, and CVE. Therefore, air quality management must be strengthened.

Years of Life Lost (YLL) Due to Short-Term Exposure to Ambient Air Pollution in China: A Systematic Review and Meta-Analysis

(1) Background: Years of life lost (YLL) as a surrogate of health is important for supporting ambient air pollution related policy decisions. However, there has been little comprehensive evaluation of the short-term impact of air pollution on cause-specific YLL, especially in China. Hence in this study, we selected China as sentinel region in order to conduct a meta-analysis to evaluate disease-specific YLL due to all the main ambient air pollutants. (2) Methods: A meta-analysis was conducted to evaluate disease-specific YLL due to the main ambient air pollutants in China, and 19 studies were included. We conducted methodological quality and risk of bias assessment for each included study as well as for heterogeneity and publication bias. Subgroup analysis and sensitivity analysis were also performed. (3) Results: Meta-analysis indicated that increases in PM_2.5, PM₁₀, SO₂ and NO₂ were associated with 1.99–5.84 years increase in YLL from non-accidental diseases. The increase in YLL to cardiovascular disease (CVD) was associated with PM₁₀ and NO₂, and the increase in YLL to respiratory diseases (RD) was associated with PM₁₀. (4) Conclusions: Ambient air pollution was observed to be associated with several cause-specific YLL, increasing especially for elderly people and females.

Acute effect of particulate matter pollution on hospital admissions for stroke among patients with type 2 diabetes in Beijing, China, from 2014 to 2018

BACKGROUND

The health effect of particulate matter pollution on stroke has been widely examined; however, the effect among patients with comorbid type 2 diabetes (T2D) in developing countries has remained largely unknown.

METHODS

A time-series study was conducted to investigate the short-term effect of fine particulate matter (PM_2.5) and inhalable particulate matter (PM₁₀) on hospital admissions for stroke among patients with T2D in Beijing, China, from 2014 to 2018. An over-dispersed Poisson generalized additive model was employed to adjust for important covariates, such as weather conditions and long-term and seasonal trends.

RESULTS

A total of 159,298 hospital admissions for stroke comorbid with T2D were reported. Approximately linear exposure-response curves were observed for PM_2.5 and PM₁₀ in relation to stroke admissions among T2D patients. A 10 μg/m³ increase in the four-day moving average of PM_2.5 and PM₁₀ was associated with 0.14% (95% confidence interval [CI]: 0.05-0.23%) and 0.14% (95% CI: 0.06-0.22%) incremental increases in stroke admissions among T2D patients, respectively. A 10 μg/m³ increase in PM_2.5 in the two-day moving average corresponded to a 0.72% (95% CI: 0.02-1.42%) incremental increase in hemorrhagic stroke, and a 10 μg/m³ increase in PM₁₀ in the four-day moving average corresponded to a 0.14% (95% CI: 0.06-0.22%) incremental increase in ischemic stroke.

CONCLUSIONS

High particulate matter might be a risk factor for stroke among patients with T2D. PM_2.5 and PM₁₀ have a linear exposure-response relationship with stroke among T2D patients. The study provided evidence of the risk of stroke due to particulate matter pollution among patients with comorbid T2D.

SPATIAL DISTRIBUTED LAG DATA FUSION FOR ESTIMATING AMBIENT AIR POLLUTION

We introduce spatial (DLfuse) and spatiotemporal (DLfuseST) distributed lag data fusion methods for predicting point-level ambient air pollution concentrations, using, as input, gridded average pollution estimates from a deterministic numerical air quality model. The methods incorporate predictive information from grid cells surrounding the prediction location of interest and are shown to collapse to existing downscaling approaches when this information adds no benefit. The spatial lagged parameters are allowed to vary spatially/spatiotemporally to accommodate the setting where surrounding geographic information is useful in one area/time but not in another. We apply the new methods to predict ambient concentrations of eight-hour maximum ozone and 24-hour average PM2.5 at unobserved spatial locations and times, and compare the predictions with those from several state-of-the-art data fusion approaches. Results show that DLfuse and DLfuseST often provide improved model fit and predictive accuracy when the lagged information is shown to be beneficial. Code to apply the methods is available in the R package DLfuse.

Temporal variations and spatial distributions of gaseous and particulate air pollutants and their health risks during 2015-2019 in China

Air quality has been significantly improved in China in recent years; however, our knowledge of the long-term changes in health risks from exposure to air pollutants remain less understood. Here we investigated the temporal variations and spatial distributions of six criteria pollutants (SO₂, NO₂, O₃, CO, PM_2.5 and PM₁₀) in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) during 2015-2019. SO₂ showed 36-60% reductions in three regions, comparatively, NO₂ decreased by 3-17% in BTH and YRD and had a 5% increase in PRD. PM_2.5 and PM₁₀ showed the largest reductions in BTH (30-33%) and the lowest in PRD (7-13%), while O₃ increased by 9% during 2015-2019 particularly in BTH and YRD. Assuming that only air pollutants above given thresholds exert excess risk (ER_total) of mortality, we found that the different variations of pollutants have caused ER_total in BTH decreasing significantly from 4.8% in 2015 to 2.0% in 2019, while from 1.9% to 1.0% in YRD, and a small change in PRD. These results indicate substantially decreased health risks of mortality from exposure to air pollutants as a response to improved air quality. Overall, PM_2.5 dominated ER_total accounting for 42-53% in BTH and 58-64% in YRD with steadily increased contributions, yet ER_total presented strong seasonal dependence on air pollutants with largely increased contribution of O₃ in summer. The ER_total caused by SO₂ was decreased substantially and became negligible except in winter in BTH, while NO₂ only played a role in winter. We also found that ER_PM2.5 was compositional dependent with organics being the major contributor at low ER_PM2.5 while nitrate was more important at high ER_PM2.5. Our results highlight that evaluation of public health risks of air pollution needs to consider chemical differences of PM in different regions in addition to dominant air pollutants in different seasons.

Chemical and Optical Characteristics and Sources of PM2.5 Humic-Like Substances at Industrial and Suburban Sites in Changzhou, China

The chemical and optical properties and sources of atmospheric PM2.5 humic-like substances (HULIS) were investigated from October to December 2016 in both industrial and suburban areas in Changzhou, China, during polluted and fair days. The average PM2.5 concentration in the industrial region was 113.06 (±64.3) μg m−3, higher than 85.27 (±41.56) μg m−3 at the suburban site. The frequency of polluted days was significantly higher in the industrial region. In contrast, the chemical compositions of PM2.5 at the two sampling sites exhibited no statistically significant differences. Rapidly increased secondary inorganic ions (SNA = NH4+ + SO42− + NO3−) concentrations suggested secondary formation played an important role in haze formation. The daily mean concentration of humic-like substance (HULIS) was 1.8–1.9 times that of HULIS-C (the carbon content of HULIS). Our results showed that HULIS accounted for a considerable fraction of PM2.5 (industrial region: 6.3% vs. suburban region: 9.4%). There were no large differences in the mass ratios of HULIS-C/WSOC at the two sites (46% in the industrial region and 52% in the suburban region). On average, suburban HULIS-C constituted 35.1% of organic carbon (OC), higher than that (21.1%) in the industrial region. Based on different MAE (mass absorption efficiency) values under different pollution levels, we can infer that the optical properties of HULIS varied with PM levels. Moreover, our results showed no distinct difference in E2/E3 (the ratio of light absorbance at 250 nm to that at 365 nm) and AAE300–400 (Absorption Angstrom Exponent at 300–400 nm) for HULIS and WSOC. the MAE365 (MAE at 365 nm) value of HULIS-C was different under three PM2.5 levels (low: PM2.5 < 75 μg m−3, moderate: PM2.5 = 75–150 μg m−3, high: PM2.5 > 150 μg m−3), with the highest MAE365 value on polluted days in the industrial region. Strong correlations between HULIS-C and SNA revealed that HULIS might be contributed from secondary formation at both sites. In addition, good correlations between HULIS-C with K+ in the industrial region implied the importance of biomass burning to PM2.5-bound HULIS. Three common sources of HULIS-C (i.e., vehicle emissions, biomass burning, and secondary aerosols) were identified by positive matrix factorization (PMF) for both sites, but the contributions were different, with the largest contribution from biomass burning in the industrial region and secondary sources in the suburban region, respectively. The findings presented here are important in understanding PM2.5 HULIS chemistry and are valuable for future air pollution control measures.

Analysis of incidence of air quality on human health: a case study on the relationship between pollutant concentrations and respiratory diseases in Kennedy, Bogotá

Thousands of deaths associated with air pollution each year could be prevented by forecasting the behavior of factors that pose risks to people's health and their geographical distribution. Proximity to pollution sources, degree of urbanization, and population density are some of the factors whose spatial distribution enables the identification of possible influence on the presence of respiratory diseases (RD). Currently, Bogotá is among the cities with the poorest air quality in Latin America. Specifically, the locality of Kennedy is one of the zones in the city with the highest recorded concentration levels of local pollutants over the last 10 years. From 2009 to 2016, there were 8619 deaths associated with respiratory and cardiovascular diseases in the locality. Given these characteristics, this study set out to identify and analyze the areas in which the primary socioeconomic and environmental conditions contribute to the presence of symptoms associated with RD. To this end, information collected in field by performing georeferenced surveys was analyzed through geostatistical and machine learning tools which carried out cluster and pattern analyses. Random forests and AdaBoost were applied to establish hot spots where RD could occur, given the conjugation of predictor variables in the micro-territory. It was found that random forests outperformed AdaBoost with 0.63 AUC. In particular, this study's approach applies to densely populated municipalities with high levels of air pollution. In using these tools, municipalities can anticipate environmental health situations and reduce the cost of respiratory disease treatments.

The short-term harvesting effects of ambient particulate matter on mortality in Taiyuan elderly residents: A time-series analysis with a generalized additive distributed lag model

The evaluation on mortality displacement and distributed lag effects of airborne particulate matter (PM) on death risks is important to understand the positive association of short-term pollution from both ambient PM₁₀ and PM_2.5 with daily mortality. Herein, short-term influences of urban PM₁₀ and PM_2.5 exposure on the mortality of respiratory diseases (RD) and cardiovascular diseases (CVD) were studied at Taiyuan, China, a typical inland city suffering from heavy ambient PM loading and having high morbidity of RD and CVD. Using a time-series analysis with generalized additive distributed lag model (DLM), the potential mortality displacement was determined and the single-day and cumulative lag-day effects of PM on mortality were estimated after the daily mass concentrations of urban PM_2.5 and PM₁₀ from January 2013 to October 2015 and the daily number of non-accidental death (NAD) and cause-specific mortality in the residents aged more than 65 years old were obtained. Results showed there were significant associations of PM_2.5 and PM₁₀ with daily mortality on the current day and within one week. And a statistically significant increase (P < 0.05) in the cumulative effect estimates of PM_2.5 and PM₁₀ on CVD, ischemic heart disease (IHD), and myocardial infarction (MI) mortality (as well as PM_2.5 on NAD) was observed, while the associations of PM_2.5 with RD and pneumonia mortality, PM₁₀ with NAD and RD mortality were not statistically significant, when the exposure window was extended to lag 0-30 days. It was concluded that there were harvesting effects and cumulative effects of ambient PM_2.5 and PM₁₀ on the elderly residents' mortality due to RD and CVD at Taiyuan and they could be estimated quantitatively when the broader time window was used, suggesting that the underestimation on the association of ambient PM with non-accidental death can be avoided using the present method in our study.

Chemical Composition of PM2.5 and Its Impact on Inhalation Health Risk Evaluation in a City with Light Industry in Central China

A city with light industry in China was selected for the study of the chemical characteristics of PM2.5 and to assess its impact on inhalation health risks. During the period from May 2017 to February 2018, a total of 382 PM2.5 filter samples were collected across four seasons (15–20 days for each season). The results showed that the daily average PM2.5 concentration ranged from 21 to 255 µg/m3, with an annual average of 73 ± 49 µg/m3. SO42−, NO3−, NH4+, and organic matter (OM) were the dominant components, accounting for 13%, 20%, 11%, and 20% of annual PM2.5 mass loading, respectively. Compared with the clean periods, the meteorology of the pollution periods were mostly characterized by high relatively humidity, high temperature, and low wind speeds. Based on positive matrix factorization (PMF), the major source of PM2.5 was identified as secondary aerosols, contributing 28% and 49% on clean days and polluted days, respectively. The health risk assessment of heavy metals showed that non-carcinogenic hazard is not expected to occur, while Cr contributed the highest cancer risk. This study is helpful for the advancement of our scientific understanding of PM2.5 pollution and its impact on health in cities with light industries.

Health disparities attributable to air pollutant exposure in North Carolina: Influence of residential environmental and social factors

Understanding the environmental justice implications of the mortality impacts of air pollution exposure is a public health priority, as some subpopulations may face a disproportionate health burden. We examined which residential environmental and social factors may affect disparities in the air pollution-mortality relationship in North Carolina, US, using a time-stratified case-crossover design. Results indicate that air pollution poses a higher mortality risk for some persons (e.g., elderly) than others. Our findings have implications for environmental justice regarding protection of those who suffer the most from exposure to air pollution and policies to protect their health.

Characteristics, sources and health risks of toxic species (PCDD/Fs, PAHs and heavy metals) in PM2.5 during fall and winter in an industrial area

Particulate toxic species, such as polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs), polycyclic aromatic hydrocarbons (PAHs) and heavy metals may have significant health risks. This study investigated characteristics, sources and health risks of all three classes of toxic species in PM_2.5 (particles with aerodynamic diameter ≤2.5 μm) samples collected at an industrial area in Changzhou, a big city in the Yangtze Delta region of China. Fourteen heavy metals altogether constituted 2.87% of PM_2.5 mass, with Fe, Al and Zn as the major elements. Principal component analysis (PCA) suggested that heavy metals came from four sources: vehicles, industry, crustal dust, mixed coal combustion and industrial process. The daily average concentration of 18 PAHs was 235.29 ng/m³, accounting for 0.21% of PM_2.5 mass. The dominant PAHs were high molecular weight ones, contributing 73.5% to the total PAHs. Diagnostic analyses indicated that sources of PAHs included vehicle/coal combustion and petroleum emissions, wherein diesel emission played a more important role than gasoline emission. PCA showed that the largest contributor of PAHs was vehicle exhaust mixed with coal combustion, followed by three industry-related sources. Total concentration of 17 PCDD/Fs varied between 3.14 and 37.07 pg/m³, with an average of 14.58 pg/m³. The 10 PCDFs accounted for 70.5% of total concentration of 17 PCDD/Fs. Health risk assessments showed that the carcinogenic risk of heavy metals was acceptable, while risks from PAHs and PCDD/Fs cannot be ignored. Back trajectory analysis indicated that local/regional transported air masses from northern China was the major source areas of the toxic species.

Characterization and risk assessment of total suspended particles (TSP) and fine particles (PM2.5) in a rural transformational e-waste recycling region of Southern China

In 2016, total suspended particles (TSP) and fine particles (PM_2.5) were collected near four e-waste recycling parks in a region of Southern China. TSP and PM_2.5 levels and composition around these industrial activities were determined and the potential risks for human health due to the exposure to toxic elements contained on fine particles (PM_2.5) were evaluated. Levels of TSP and PM_2.5 were lower with advanced recycling methods than with small recycling e-waste workshops operating in the sampling region. The main trace elements in particles were Cu, Pb, and Ti, the same as those detected before the transition to advanced dismantling methods in e-waste recycling. Significantly higher levels of Cu, Pb, Sn, Te, Tl and NH₄⁺ in TSP and Cu and Te in PM_2.5 were found in e-waste recycling areas than in BG site. Taking Cu as the indicative element emitted from e-waste recycling activities, significant high positive correlations between Cu and W, and Cu and Te were found. These elements are present and can be released from electrical and electronical components during e-waste recycling processes. Exposure to elements for the population living near these e-waste recycling parks means carcinogenic risks above the acceptable threshold (>10^-5).

Atmospheric nanoparticles affect vascular function using a 3D human vascularized organotypic chip

Inhaled atmospheric nanoparticles (ANPs) can migrate into human blood vessels. However, the exact pathogenesis has not yet been well elucidated. In this study, a perfusable 3D human microvessel network was constructed in a microfluidic device. This functional 3D micro-tissue partly mimicked the physiological response of human vessels. Intravascular nanoparticles tend to adsorb proteins to form a protein corona. Based on this pathological response, vessel permeability and vasoconstriction resulting from ANP stimulation might be related to vascular inflammation. It mediated abnormal expression of nuclear factor-κB (NF-κB) and an influx of intracellular Ca²⁺ ([Ca²⁺]i). This biological behavior disturbed the normal expression of intercellular cell adhesion molecule 1 (ICAM-1) and vascular endothelial growth factor (VEGF). The imbalance of nitric oxide (NO) and endothelin-1 (ET-1) further resulted in endothelial cell contraction. All these bio-events induced the loss of tight junctions (ZO-1) which enhanced vessel permeability. Meanwhile, ANP induced-vascular toxicity was also found in mice. Our observations provide a plausible explanation for how the ANPs affect human vascular function. The vessel-on-chip provides a bridge between in vitro results and human responses. We aimed to use this human 3D functional microvascular model to mimic the physiological responses of human vessels. This model is suitable for the evaluation of vascular toxicity after the human vessel exposure to ANPs.

Particulate Matter Mortality Rates and Their Modification by Spatial Synoptic Classification

Air pollution levels are highly correlated with temperature or humidity, so we investigated the relationship between PM₁₀ and the spatial synoptic classification (SSC) scheme on daily mortality, according to age group and season. Daily death data for 2000-2014 from Seoul, Korea, were acquired, and time-series analysis was applied with respect to season and to each of seven distinct SSC types: dry moderate (DM); dry polar (DP); dry tropical (DT); moist moderate (MM); moist polar (MP); moist tropical (MT); and transition (T). Modification effects were estimated for daily, non-accidental, cardiovascular, and respiratory mortality between PM₁₀ and SSC types. The following SSC-type-specific increased mortalities were observed, by cause of death: non-accidental mortality: DT (1.86%) and MT (1.86%); cardiovascular mortality: DT (2.83%) and MM (3.00%); respiratory mortality: MT (3.78%). Based on simplified weather types, increased PM₁₀ effects in non-accidental mortality rates were observed in dry (1.54%) and moist (2.32%) conditions among those aged 40-59 years and were detected regardless of conditions in other age groups: 60-74 (1.11%), 75-84 (1.55%), and 85+ (1.75%). The effects of particulate air pollution, by SSC, suggest the applicability of SSC to the comparison and understanding of acute effects of daily mortality based on weather type.