Search

Background: Both genetic factors and environmental air pollution contribute to the risk of stroke. However, it is unknown whether the association between air pollution and stroke risk is influenced by the genetic susceptibilities of stroke and its risk factors., Methods: This prospective cohort study included 40 827 Chinese adults without stroke history. Satellite-based monthly fine particulate matter (PM 2.5 ) estimation at 1-km resolution was used for exposure assessment. Based on 534 identified genetic variants from genome-wide association studies in East Asians, we constructed 6 polygenic risk scores for stroke and its risk factors, including atrial fibrillation, blood pressure, type 2 diabetes, body mass index, and triglyceride. The Cox proportional hazards model was applied to evaluate the hazard ratios and 95% CIs for the associations of PM 2.5 and polygenic risk score with incident stroke and the potential effect modifications., Results: Over a median follow-up of 12.06 years, 3147 incident stroke cases were documented. Compared with the lowest quartile of PM 2.5 exposure, the hazard ratio (95% CI) for stroke in the highest quartile group was 2.72 (2.42-3.06). Among individuals at high genetic risk, the relative risk of stroke was 57% (1.57; 1.40-1.76) higher than those at low genetic risk. Although no statistically significant interaction was found, participants with both the highest PM 2.5 and high genetic risk showed the highest risk of stroke, with ≈4× that of the lowest PM 2.5 and low genetic risk group (hazard ratio, 3.55 [95% CI, 2.84-4.44]). Similar upward gradients were observed in the risk of stroke when assessing the joint effects of PM 2.5 and genetic risks of blood pressure, type 2 diabetes, body mass index, atrial fibrillation, and triglyceride., Conclusions: Long-term exposure to PM 2.5 was associated with a higher risk of incident stroke across different genetic susceptibilities. Our findings highlighted the great importance of comprehensive assessment of air pollution and genetic risk in the prevention of stroke., Competing Interests: Disclosures None.

Previous studies have established a significant link between ambient fine particulate matter (PM 2.5 ) exposure and atherosclerotic cardiovascular disease (ASCVD) incidence, but whether this association varies across populations with different predicted ASCVD risks was uncertain previously. We included 109,374 Chinese adults without ASCVD at baseline from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) project. We obtained PM 2.5 data of participants' residential address from 2000 to 2015 using a satellite-based spatiotemporal model. Participants were classified into low-to-medium and high-risk groups according to the ASCVD 10-year and lifetime risk prediction scores. Hazard ratios (HRs) and 95% confidence intervals (CIs) for PM 2.5 exposure-related incident ASCVD, as well as the multiplication and additive interaction, were calculated using stratified Cox proportional hazard models. The additive interaction between risk stratification and PM 2.5 exposure was estimated by the synergy index (SI), the attributable proportion due to the interaction (API), and the relative excess risk due to interaction (RERI). Over the follow-up of 833,067 person-years, a total of 4230 incident ASCVD cases were identified. Each 10 μg/m 3 increment of PM 2.5 concentration was associated with 18% (HR: 1.18; 95% CI: 1.14-1.23) increased risk of ASCVD in the total population, and the association was more pronounced among individuals having a high predicted ASCVD risk than those having a low-to-medium risk, with the HR (95% CI) of 1.24 (1.19-1.30) and 1.11 (1.02-1.20) per 10 μg/m 3 increment in PM 2.5 concentration, respectively. The RERI, API, and SI were 1.22 (95% CI: 0.62-1.81), 0.22 (95% CI: 0.12-0.32), and 1.37 (95% CI: 1.16-1.63), respectively. Our findings demonstrate a significant synergistic effect on ASCVD between ASCVD risk stratification and PM 2.5 exposure and highlight the potential health benefits of reducing PM 2.5 exposure in Chinese, especially among those with high ASCVD risk.

The association between long-term joint exposure to all kinds of ambient air pollutants and the risk of mortality is not known. Our study prospectively assessed the joint associations of various air pollutants with cause-specific and all-cause mortality risk and identified potential modifying factors affecting these associations. A total of 400,259 individuals aged 40-70 years were included in this study. Information on PM 10 , PM 2.5-10 , PM 2.5 , NO 2 , and NO x was collected. A weighted air pollution score was calculated to assess joint exposure to the above air pollutants. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models. During a median of 12.0 years (4,733,495 person-years) of follow-up, 21,612 deaths were recorded, including 7097 deaths from cardiovascular disease and 11,557 deaths from cancer. The adjusted HRs of all-cause mortality were 1.39 (95% CI: 1.29-1.50), 1.86 (95% CI: 1.63-2.13), 1.12 (95% CI: 1.10-1.14), and 1.04 (95% CI: 1.03-1.05) for every 10-ug/m 3 increase in PM 10 , PM 2.5 , NO 2 , and NO x , respectively. The adjusted HRs associated with the air pollution score (the highest quintile versus the lowest quintile) were 1.24 (95% CI: 1.19-1.30) for all-cause mortality, 1.33 (95% CI: 1.23-1.43) for cardiovascular mortality, and 1.16 (95% CI: 1.09-1.23) for cancer mortality. Furthermore, we found that the air pollution score was associated with a linear dose-response increase in mortality risk (all P for linearity < 0.001). The findings highlight the importance of a comprehensive assessment of various air pollutants., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Vascular endothelial dysfunction is an early stage to cardiovascular diseases (CVDs), but whether air pollution exposure has an effect on it remains unknown. We conducted a systematic review and meta-analysis to summarize epidemiological evidence between air pollution and endothelial dysfunction. We searched the database of PubMed, EMBASE, the Cochrane Library, and Web of Science up to November 10, 2022. Fixed and random effect models were used to pool the effect change or percent change (% change) and 95% confidence interval (95% CI) of vascular function associated with particulate matter (PM) and gaseous pollutants. I 2 statistics, funnel plot, and Egger's test were used to evaluate heterogeneity and publication bias. There were 34 articles included in systematic review, and 25 studies included in meta-analysis. For each 10 µg/m 3 increment in short-term PM 2.5 exposure, augmentation index (AIx) and pulse wave velocity (PWV) increased by 2.73% (95% CI: 1.89%, 3.57%) and 0.56% (95% CI: 0.22%, 0.89%), and flow-mediated dilation (FMD) decreased by 0.17% (95% CI: - 0.33%, - 0.00%). For each 10 µg/m 3 increment in long-term PM 2.5 exposure, FMD decreased by 0.99% (95% CI: - 1.41%, - 0.57%). The associations between remaining pollutants and outcomes were not statistically significant. The effect of short-term PM 2.5 exposure on FMD change was stronger in population with younger age, lower female proportion, higher mean body mass index and higher PM 2.5 exposure. Cardiac or vasoactive medication might attenuate this effect. Our study provides evidence that PM 2.5 exposure had adverse impact on vascular endothelial function, indicating the importance of air quality improvement for early CVD prevention., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Evidence remains limited about the association of maternal exposure to ambient fine particulate matter (airborne particles with an aerodynamic diameter ≤2.5 µm [PM 2.5 ]) with fetal congenital heart defects (CHDs) in highly polluted regions, and few studies have focused on preconception exposure., Methods: Using a nationwide surveillance-based case-control design in China, we examined the association between maternal exposure to PM 2.5 during periconception (defined as 3 months before conception until 3 months into pregnancy) and risk of CHD in offspring. The study included 1 434 998 births involving 7335 CHDs from 2014 through 2017 on the basis of the National Population-Based Birth Defects Surveillance System, covering 30 provinces, municipalities, or municipal districts in China. We assigned maternal PM 2.5 exposure during the periconception period to each participant using satellite-based PM 2.5 concentrations at 1-km spatial resolution. Multilevel logistic regression models were used to calculate the multivariable-adjusted odds ratio and 95% CI for CHDs in offspring associated with maternal PM 2.5 exposure, and the exposure-response association was investigated using restricted cubic spline analysis. Subgroup or sensitivity analyses were conducted to identify factors that may modify the association., Results: The average maternal exposure to PM 2.5 levels across all participants was 56.51 μg/m 3 (range, 10.95 to 182.13 μg/m 3 ). For each 10 μg/m³ increase in maternal PM 2.5 exposure, the risk of CHDs in offspring was increased by 2% (odds ratio, 1.02 [95% CI, 1.00 to 1.05]), and septal defect was the most influenced subtype (odds ratio, 1.04 [95% CI, 1.01 to 1.08]). The effect of PM 2.5 on CHD risk was more pronounced during the preconception period. Mothers <35 years of age, those living in northern China, and those living in low-income areas were more susceptible to PM 2.5 exposure than their counterparts (all P <0.05). PM 2.5 exposure showed a linear association with total CHDs or specific CHD types., Conclusions: High maternal PM 2.5 exposure, especially during the preconception period, increases risk of certain types of CHD in offspring. These findings are useful for CHD prevention and highlight the public health benefits of improving air quality in China and other highly polluted regions.

Background and Aims: Epidemiological evidence regarding the association of air pollution with the risk of non-alcoholic fatty liver disease (NAFLD) is limited. This study was to examine the associations of long-term exposure to various air pollutants and overall air pollution with risk of incident NAFLD as well as cirrhosis, a major liver-related morbidity for NAFLD., Methods: Included were 456 687 UK residents. Air pollution data included PM 2.5 , PM 2.5-10 , PM 10 , NO 2 and NO x . A weighted air pollution score was also generated from PM 10 and NO x . Cox proportional hazard models were employed to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs)., Results: We identified 4978 cases of NAFLD and 1575 cases of incident cirrhosis, over a median follow-up of 11.9 years. PM 2.5 , PM 10 , NO 2 and NO x exposures contributed to the excess risk of NAFLD associated with air pollution score; and the corresponding adjusted HRs (95% CI) were 1.10 (1.05, 1.14), 1.14 (1.09, 1.20), 1.19 (1.13, 1.24) and 1.11 (1.07, 1.15), respectively, for each interquartile range increase in the above specific air pollutants. Similar patterns were also indicated for cirrhosis risk. Alcohol consumption was an effect modifier for the association between air pollution score and NAFLD risk, whereas body mass index modified the association for cirrhosis risk., Conclusion: Long-term exposure to air pollution was associated with risks of NAFLD and cirrhosis among the UK population., (© 2022 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Previous studies indicated that long-term exposure to high level of fine particulate matter (PM 2.5 ) was associated with elevated blood pressure (BP) and hypertension, but most of them were conducted in high-income countries with low PM 2.5 level. Therefore, we aimed to evaluate the adverse impacts of long-term exposure to PM 2.5 on BP and hypertension in China with high concentration. A total of 99,084 adults aged ≥18 years old were included from three cohorts among the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China. PM 2.5 concentrations during 2000-2015 at 1 × 1 km spatial resolution were evaluated using satellite-based spatiotemporal models. Generalized estimating equation was applied to assess the impact of three-year average PM 2.5 concentrations on BP level and hypertension. We also examined whether health status and lifestyles modified the effects of PM 2.5 on BP and hypertension. Generally, high concentration of PM 2.5 was associated with increased BP level and higher risk of hypertension. With each 10 μg/m 3 increment in PM 2.5 concentration, systolic BP (SBP) and diastolic BP (DBP) increased by 1.67 [95% confidence interval (CI): 1.48, 1.86] mmHg and 0.45 (95% CI: 0.35, 0.56) mmHg, and the prevalence of hypertension increased by 29% [odds ratio (OR): 1.29, 95% CI: 1.26, 1.32]. In comparison with the first quartile of PM 2.5 concentration, SBP, DBP and prevalence of hypertension in the fourth quartile were increased by 8.26 (95% CI: 7.73, 8.80) mmHg, 2.85 (95% CI: 2.55, 3.15) mmHg, and 133% (OR: 2.33, 95% CI: 2.21, 2.47), respectively, in the fully adjusted model. However, the relationships of PM 2.5 with BP might be non-linear, as BP level started to decline when PM 2.5 exceeded 75 μg/m 3 . In conclusion, long-term PM 2.5 exposure could elevate BP level and prevalence of hypertension. People living in high-polluted areas should strengthen their awareness of prevention., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Ambient fine particulate matter (PM 2.5 ) pollution is a major environmental and public health challenge in China. In the recent decade, the PM 2.5 level has decreased mainly driven by reductions in particulate sulfate as a result of large-scale desulfurization efforts in coal-fired power plants and industrial facilities. Emerging evidence also points to the differential toxicity of particulate sulfate affecting human health. However, estimating the long-term spatiotemporal trend of sulfate is difficult because a ground monitoring network of PM 2.5 constituents has not been established in China. Spaceborne sensors such as the Multi-angle Imaging SpectroRadiometer (MISR) instrument can provide complementary information on aerosol size and type. With the help of state-of-the-art machine learning techniques, we developed a sulfate prediction model under support from available ground measurements, MISR-retrieved aerosol microphysical properties, and atmospheric reanalysis data at a spatial resolution of 0.1°. Our sulfate model performed well with an out-of-bag cross-validationR 2 of 0.68 at the daily level and 0.93 at the monthly level. We found that the national mean population-weighted sulfate concentration was relatively stable before the Air Pollution Prevention and Control Action Plan was enforced in 2013, ranging from 10.4 to 11.5 µg m -3 . But the sulfate level dramatically decreased to 7.7 µg m -3 in 2018, with a change rate of -28.7 % from 2013 to 2018. Correspondingly, the annual mean total non-accidental and cardiopulmonary deaths attributed to sulfate decreased by 40.7 % and 42.3 %, respectively. The long-term, full-coverage sulfate level estimates will support future studies on evaluating air quality policies and understanding the adverse health effect of particulate sulfate., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Aims: To explore the association between decreased levels of particulate matter (≤2.5 µm; PM 2.5 ) due to the implementation of environmental protection policies and the incidence of obesity in adolescents in Chongqing, China through a prospective cohort study., Methods: A total of 2105 children (52.02% male; aged 7.33 ± 0.60 years at baseline) were enrolled from the Chongqing Children's Health Cohort. A mixed linear regression model was used to analyse the relationships of PM 2.5 levels with obesity indicators after adjusting for covariates. Additionally, a Poisson regression model was used to determine the relationship between PM 2.5 exposure and the incidence of overweight/obesity., Results: The average PM 2.5 exposure levels from participant conception to 2014, from 2015 to 2017, and from 2018 to 2019 were 66.64 ± 5.33 μg/m 3 , 55.49 ± 3.78 μg/m 3 , and 42.50 ± 1.87 μg/m 3 , respectively; these levels significantly decreased over time (P < 0.001). Throughout the entire follow-up period, the incidence of overweight/obesity after a ≥ 25 μg/m 3 decrease in the PM 2.5 level was 4.57% among females; this incidence was the lowest among females who experienced remarkable decreases in PM 2.5 exposure. A 1-µg/m 3 decrease in the PM 2.5 level significantly decreased the body mass index (BMI), BMI z score (BMI z ), and weight of adolescents (all P < 0.001). Compared with a < 20-μg/m 3 decrease in the PM 2.5 level, a ≥ 25-μg/m 3 decrease protected against increased BMI (net difference= -0.93; 95% confidence interval [CI]: (-1.23,-0.63) kg/m 2 ), BMI z (-0.28 (-0.39, -0.17)), weight (-1.59 (-2.44, -0.74) kg), and incidence of overweight/obesity (0.48 (0.37, 0.62), P < 0.001). Moreover, compared with a < 20-μg/m 3 decrease in the PM 2.5 level, a ≥ 25-μg/m 3 decrease resulted in significant absolute differences in BMI (-1.26 (-1.56, -0.96) kg/m 2 ), BMI z (-0.53 (-0.65, -0.40)) and weight (-3.01 (-3.8, -2.19) kg) (all P < 0.001)., Conclusions: This study showed the etiological relevance of declining PM 2.5 concentrations for the incidence of obesity in children and adolescents, suggesting that controlling ambient air pollutants may prevent the development of obesity in this age group. Continuous implementation of environmental protection policies in China has led to substantial health benefits., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Several literatures have examined the risk of chronic respiratory diseases in association with short-term ambient PM 2.5 exposure in China. However, little evidence has examined the chronic impacts of PM 2.5 exposure on morbidity of chronic respiratory diseases in cohorts from high pollution countries. Our study aims to investigate the associations. Based on a retrospective cohort among adults in northern China, a Cox regression model with time-varying PM 2.5 exposure and a concentration-response (C-R) curve model were performed to access the relationships between incidence of chronic respiratory diseases and long-term PM 2.5 exposure during a mean follow-up time of 9.8 years. Individual annual average PM 2.5 estimates were obtained from a satellite-based model with high resolution. The incident date of a chronic respiratory disease was identified according to self-reported physician diagnosis time and/or intake of medication for treatment. Among 38,047 urban subjects analyzed in all-cause chronic respiratory disease cohort, 482 developed new cases. In CB (38,369), asthma (38,783), and COPD (38,921) cohorts, the onsets were 276, 89, and 14, respectively. After multivariable adjustment, hazard ratio and 95% confidence interval for morbidity of all-cause chronic respiratory disease, CB, asthma, and COPD were 1.15 (1.01, 1.31), 1.20 (1.00, 1.42), 0.76 (0.55, 1.04), and 0.66 (0.29, 1.47) with each 10 μg/m 3 increment in PM 2.5 , respectively. Stronger effect estimates were suggested in alcohol drinkers across stratified analyses. Additionally, the shape of C-R curve showed an increasing linear relationship before 75.00 μg/m 3 concentrations of PM 2.5 for new-onset all-cause chronic respiratory disease, and leveled off at higher levels. These findings indicated that long-term exposure to high-level PM 2.5 increased the risks of incident chronic respiratory diseases in China. Further evidence of C-R curves is warranted to clarify the associations of adverse chronic respiratory outcomes involving air pollution., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Little is known about the links between long-term exposure to air pollution and risk of incident microvascular disease (retinopathy, peripheral neuropathy, and chronic kidney disease). This study included 396 014 UK residents free of microvascular disease and macrovascular disease at baseline. Annual means of PM 2.5 , PM 2.5-10 , PM 10 , NO 2 , and NO x were assessed by land use regression models for each participant. A weighted air pollution score was generated from PM 10 and NO x . Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). During a median follow-up of 11.7 years, 14 327 composite microvascular disease occurred. While none of the air pollutants showed any statistically significant association with the risk of retinopathy, all the air pollutants were linked to the risk of peripheral neuropathy and chronic kidney disease. The adjusted-HRs (95% CIs) for each interquartile range increase in air pollution score were 1.07 (1.05, 1.09), 1.01 (0.94, 1.07), 1.13 (1.08, 1.19), and 1.07 (1.05, 1.10) for overall microvascular disease, retinopathy, peripheral neuropathy, and chronic kidney disease, respectively. In conclusion, long-term exposure to overall air pollution was associated with higher risks of peripheral neuropathy and chronic kidney disease among the general UK population.

Objective: The aim of this study was to explore the association between exposure to particulate matter with an aerodynamic diameter of 2.5 mm or less (PM2.5) and blood pressure (BP) levels in children and adolescents and to illustrate the impact of PM2.5 levels on BP growth curves in a cohort study., Methods: A longitudinal study was designed and included 4303 children (7617 BP measurements) living in the selected areas, and evaluations were conducted in 2014-2015 (visit 1) and followed up in 2019 (visit 2). Two-stage stratified cluster sampling was used to include urban-rural areas. A mixed linear regression model and mixed logistic regression model were used to analyze the effect of PM2.5 exposure on BP and the incidence of prehypertension and hypertension in children., Results: After adjusting for covariates, systolic blood pressure (SBP) (2.21 (95% CIs: 0. 81, 3.62), mmHg), diastolic blood pressure (DBP) (1.92 (95% CIs: 0.74, 3.11), mmHg), mean arterial pressure (MAP) (2.03 (95% CIs: 0.89, 3.17), mmHg) and heart rate (HR) (2.24 (95% CIs: 0.11, 4.37), beats/min) increased significantly in the fourth quartile of PM2.5 exposure levels compared with the first quartile (all P < 0.01). In addition, long-term exposure to PM2.5 was significantly positively correlated with SBP, DBP and MAP, and the effect was more notable in urban areas than that in rural areas. Moreover, the risk of prehypertension and hypertension incidence increased by 1.17 (95% CIs: 1.03, 1.33) fold with a one-quartile increase in PM2.5 exposure. The long-term effects of annual mean PM2.5 exposure on SBP, DBP and MAP were significant from pregnancy to 7, 3 and 4 years of age, respectively., Conclusion: Long-term exposure to PM2.5 was positively associated with growth curves of hemodynamics indexed from pregnancy to childhood and adolescence, and the effect was more significant in urban areas than in rural areas., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: While the relationship between ambient air pollution and diabetes mellitus has recently been reported, data on the association between fine particulate matter (PM 2.5 ) and diabetic complications are limited, especially in microvascular diseases such as diabetic retinopathy., Objectives: To investigate the associations between long-term exposure to PM 2.5 and the prevalence of diabetic retinopathy in adult diabetic patients in rural China., Methods: The study population was based on the Rural Epidemiology for Glaucoma in China (REG-China), a national cross-sectional survey conducted in rural China. This analysis selected diabetic patients with or without diabetic retinopathy. A satellite-based spatiotemporal model was used to estimate personal PM 2.5 exposure. Logistic regression models were used to investigate the effect of long-term PM 2.5 exposure on diabetic retinopathy., Results: The analysis included 3111 diabetic participants, 329 of whom were diagnosed with diabetic retinopathy. The median level of exposure to PM 2.5 from 2000 to2016 was 59.9 μg/m 3 . For each 10 μg/m 3 increase in PM 2.5 , the adjusted odds ratio (95% confidence interval) for diabetic retinopathy was 1.41 (1.27, 1.57). In subgroup analyses, the effect of PM 2.5 on diabetic retinopathy was significantly stronger in participants who self-reported alcohol consumption., Conclusion: These findings suggest that long-term exposure to high PM 2.5 was associated with the risk of diabetic retinopathy among diabetic patients in rural China., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: A growing body of evidence has confirmed the association between fine particulate matter (PM 2.5 ) and ocular diseases, but little is known on the effect of long-term PM 2.5 exposure on glaucoma., Methods: A national cross-sectional study of the Rural Epidemiology for Glaucoma was conducted in 10 provinces of China, and 33,701 adults aged 40 years or more were included. A satellite-based model at 1-km resolution level was used to estimate PM 2.5 concentrations which were assigned to each participant according to geocoded home addresses. Logistic regression model was performed to investigate associations of long-term PM 2.5 exposure with glaucoma and its subtypes., Results: Estimated PM 2.5 concentrations ranged from 28.0 to 96.4 μg/m 3 . For each 10 μg/m 3 increment in PM 2.5 , the adjusted odds ratios (ORs) were 1.07 (95% CI: 1.00-1.15) and 1.14 (95% CI: 1.02-1.26) for glaucoma and primary angle-closure glaucoma (PACG), respectively. A positive but non-significant association (OR = 1.05, 95% CI: 0.92-1.18) was detected between long-term exposure to PM 2.5 and odds of primary open-angle glaucoma. The middle aged residents and non-smokers were more sensitive to the adverse effects of PM 2.5 ., Conclusions: Long-term PM 2.5 exposure was associated with glaucoma and PACG in Chinese adults, which provided new insights on adverse ophthalmic effect of PM 2.5 ., (Copyright © 2021 Elsevier GmbH. All rights reserved.)

Evidence is still limited for the role of long-term PM 2.5 exposure in cerebrovascular diseases among residents in high pollution regions. The study is aimed to investigate the long-term effects of PM 2.5 exposure on stroke mortality, and further explore the effect modification of temperature variation on the PM 2.5 -mortality association in northern China. Based on a cohort data with an average follow-up of 9.8 years among 38,435 urban adults, high-resolution estimates of PM 2.5 derived from a satellite-based model were assigned to each participant. A Cox regression model with time-varying exposures and strata of geographic regions was employed to assess the risks of stroke mortality associated with PM 2.5 , after adjusting for individual risk factors. The cross-product term of PM 2.5 exposure and annual temperature range was further added into the regression model to test whether the long-term temperature variation would modify the association of PM 2.5 with stroke mortality. Among the study participants, the annual mean level of PM 2.5 concentration was 66.3 μg/m 3 ranging from 39.0 μg/m 3 to 100.6 μg/m 3 . For each 10 μg/m 3 increment in PM 2.5 , the hazard ratio (HR) was 1.31 (95% CI: 1.04-1.65) for stroke mortality after multivariable adjustment. In addition, the HRs of PM 2.5 decreased gradually as the increase of annual temperature range with the HRs of 1.95 (95% CI: 1.36-2.81), 1.53 (95% CI: 1.06-2.22), and 1.11 (95% CI: 0.75-1.63) in the low, middle, and high group of annual temperature range, respectively. The findings provided further evidence of long-term PM 2.5 exposure on stroke mortality in high-exposure settings such as northern China, and also highlighted the view that assessing the adverse health effects of air pollution might not ignore the role of temperature variations in the context of climate change., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Quantification of PM 2.5 exposure and associated mortality is critical to inform policy making. Previous studies estimated varying PM 2.5 -related mortality in China due to the usage of different source data, but rarely justify the data selection. To quantify the sensitivity of mortality assessment to source data, we first constructed state-of-the-art PM 2.5 predictions during 2000-2018 at a 1-km resolution with an ensemble machine learning model that filled missing data explicitly. We also calibrated and fused various gridded population data with a geostatistical method. Then we assessed the PM 2.5 -related mortality with various PM 2.5 predictions, population distributions, exposure-response functions, and baseline mortalities. We found that in addition to the well documented uncertainties in the exposure-response functions, missingness in PM 2.5 prediction, PM 2.5 prediction error, and prediction error in population distribution resulted to a 40.5%, 25.2% and 15.9% lower mortality assessment compared to the mortality assessed with the best-performed source data, respectively. With the best-performed source data, we estimated a total of approximately 25 million PM 2.5 -related mortality during 2001-2017 in China. From 2001 to 2017, The PM 2.5 variations, growth and aging of population, decrease in baseline mortality led to a 7.8% increase, a 42.0% increase and a 24.6% decrease in PM 2.5 -related mortality, separately. We showed that with the strict clean air policies implemented in 2013, the population-weighted PM 2.5 concentration decreased remarkably at an annual rate of 4.5 μg/m 3 , leading to a decrease of 179 thousand PM 2.5 -related deaths nationwide during 2013-2017. The mortality decrease due to PM 2.5 reduction was offset by the population growth and aging population., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Investigations on the chronic health effects of fine particulate matter (PM 2.5 ) exposure in China are limited due to the lack of long-term exposure data. Using satellite-driven models to generate spatiotemporally resolved PM 2.5 levels, we aimed to estimate high-resolution, long-term PM 2.5 and associated mortality burden in China. The multiangle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD) at 1-km resolution was employed as a primary predictor to estimate PM 2.5 concentrations. Imputation techniques were adopted to fill in the missing AOD retrievals and provide accurate long-term AOD aggregations. Monthly PM 2.5 concentrations in China from 2000 to 2016 were estimated using machine-learning approaches and used to analyze spatiotemporal trends of adult mortality attributable to PM 2.5 exposure. Mean coverage of AOD increased from 56 to 100% over the 17-y period, with the accuracy of long-term averages enhanced after gap filling. Machine-learning models performed well with a random cross-validation R 2 of 0.93 at the monthly level. For the time period outside the model training window, prediction R 2 values were estimated to be 0.67 and 0.80 at the monthly and annual levels. Across the adult population in China, long-term PM 2.5 exposures accounted for a total number of 30.8 (95% confidence interval [CI]: 28.6, 33.2) million premature deaths over the 17-y period, with an annual burden ranging from 1.5 (95% CI: 1.3, 1.6) to 2.2 (95% CI: 2.1, 2.4) million. Our satellite-based techniques provide reliable long-term PM 2.5 estimates at a high spatial resolution, enhancing the assessment of adverse health effects and disease burden in China., Competing Interests: The authors declare no competing interest.

To improve air quality, China has been implementing strict clean air policies since 2013. These policies not only substantially improved air quality but may also modify the spatial distribution of air pollution, since urban emission sources were under stricter control and some were moved to rural regions with lower air quality improvement targets and lacking of monitoring. Here, we predicted satellite-based monthly PM 2.5 concentrations during 2000-2018 at a 1-km resolution with complete spatial-temporal coverage to analyze changes in the spatial pattern of PM 2.5 pollution in China. We found that the PM 2.5 concentration in urban regions was higher than that in rural regions of the same city by an average of 3.3 μg/m 3 during 2000-2018. This urban-rural disparity in PM 2.5 concentration significantly increased from 2.5 μg/m 3 in 2000 and peaked in 2007 of 3.8 μg/m 3 , then it sharply declined by 49% during 2013-2018 with the implementation of clean air policies. This shrinkage in the urban-rural PM 2.5 gap was partly due to the 1.3 μg/m 3 greater average decrease in the PM 2.5 level in the urban region than in the rural region of the same town during 2013-2018 on average. We also observed that cities that started monitoring earlier experienced greater decreases in the urban-rural PM 2.5 difference, and regions surrounding monitor showed significantly greater PM 2.5 decrease than regions far away from monitor during 2013-2018. Additionally, clean air policies modified the relationship between PM 2.5 concentrations and per capita gross domestic product (GDP), leading to a lower PM 2.5 level with the same per capita GDP after 2013. Emissions in rural and suburban regions should be considered to further improve air quality in China., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Ground-level ozone is the primary source of air pollution in China, particularly during the warmer months. In this study, we investigated the exposure status of ozone pollution and the temperature distribution in an air-conditioned bus in Jinan during the evening peak period based on field measurements obtained with a handheld portable particle counter and indigo disulfonate spectrophotometry. Statistical analysis showed that the passengers experienced poor air quality within the confines of the bus due to the poor air quality outside. Furthermore, the level of passenger comfort was dissatisfactory because of the high temperature, thereby highlighting the urgent need to improve the current situation. Numerical simulations were conducted using FLUENT software to explore the impacts of the air supply angle, the opening and closing of the bus door, and the chemical reaction between ozone and its precursors on the diffusion and distribution of ozone, the temperature, and the airflow field. The results indicated that high concentrations of ozone were present in the middle and front regions of the bus. Pollution can be reduced by keeping the bus door open for no longer than 20 s when waiting for other passengers, and the best optimization effect in relation to the temperature and passenger comfort was determined as an air supply angle of 30°. In addition, the average individual daily intake of ozone was combined with other relevant parameters to assess the exposure level. It is recommended that the elderly and children should avoid peak time travel to reduce their exposure to ozone (inhalation dose values > 60 μg/m 3 and > 56 μg/m 3 according to simulations, respectively). These findings are expected to effectively improve the air quality and passenger comfort levels in busses, thereby protecting the health of passengers and reducing carbon usage.

Evidence of long-term effects of high exposure to ambient fine particulate matter (PM 2.5 ) on coronary heart disease (CHD) remains limited. We incorporated the high-resolution satellite-based PM 2.5 estimates with a large-scale, population-based Chinese cohort comprising 118 229 individuals, to assess the CHD risk of long-term exposure to high PM 2.5 . During the follow-up of 908 376 person-years, 1586 incident CHD cases were identified. The long-term average PM 2.5 concentration for study population was 64.96 μg/m 3 , ranging from 31.17 to 96.96 μg/m 3 . For an increment of 10 μg/m 3 in PM 2.5 , the multivariate-adjusted hazard ratios (HRs) were 1.43 (95% confidence interval [CI]: 1.35-1.51) for total CHD, 1.45 (95% CI: 1.36-1.56) for nonfatal CHD, and 1.38 (95% CI: 1.25-1.53) for fatal CHD, respectively. The effects were different across specific CHD outcomes, with greater effects for unstable angina (HR, 1.71 [95% CI, 1.56-1.88]), and weaker effects for acute myocardial infarction (HR, 1.28 [95% CI, 1.19-1.39]) and other CHD (HR, 1.27 [95% CI, 1.10-1.48]). The exposure-response curve suggested that HRs increased with elevated PM 2.5 concentration over the entire exposure range. Elderly and hypertensive individuals were more susceptible to PM 2.5 -induced CHD. Our findings demonstrate the adverse health effects of severe air pollution and highlight the potential health benefits of air quality improvement.

Background: The concentration-response relationship between mortality and long-term exposure to fine particulate matter (PM 2.5 ) has not been fully elucidated, especially at high levels of PM 2.5 concentrations., Objective: We aimed to evaluate chronic effects of ambient PM 2.5 exposure on deaths among Chinese adults in high-exposure settings., Methods: Participants of the Prediction for Atherosclerotic cardiovascular disease Risk in China (China-PAR) project were included from four prospective cohorts among Chinese adults aged ≥18 years old. The overall follow-up rate of the four cohorts was 93.4% until the recent follow-up survey that ended in 2015. The average of satellite-based PM 2.5 concentrations during 2000-2015 at 1-km spatial resolution was assigned to each participant according to individual residence addresses. Based on the pooled analysis of individual data from the four cohorts, a Cox proportional hazards model was used to estimate the hazard ratio (HR) and corresponding 95% confidence intervals (95% CIs) for the association of PM 2.5 exposure with mortality after multivariate adjustment., Results: A total of 116,821 participants were eligible in the final analysis. During a mean of 7.7 years of follow-up, 6,395 non-accidental deaths and 2,507 cardio-metabolic deaths occurred. The mean of PM 2.5 concentration was 64.9 μg/m 3 ranging from 31.2 μg/m 3 to 97.0 μg/m 3 . For each 10 μg/m 3 increment in PM 2.5 , the HR was 1.11 (95% CI: 1.08-1.14) for non-accidental mortality and 1.22 (95% CI: 1.16-1.27) for cardio-metabolic mortality. In addition, a weak exponential curve for the concentration-response association between mortality and PM 2.5 was observed among Chinese adults., Conclusions: Our study provided important evidence of the long-term effects of PM 2.5 exposure on deaths among Chinese adults. The findings expand our knowledge on concentration-response relationship in high-exposure environments, which is essential to address the urgent challenge of reducing the disease burden attributable to PM 2.5 exposure in rapidly industrializing countries such as China., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020. Published by Elsevier Ltd.)

Background: The prevalence of atopic dermatitis (AD) dramatically increased over these years and environmental factors were considered as potential contributors towards these trends., Objective: This study aimed to explore several major environmental exposures, including air pollution, temperature and relative humidity, in order to identify potential modifiable risk factors and their interactive effects on AD., Methods: We applied a bivariate response surface model and stratification model based on time-series Poisson generalized additive models to examine the interactive effects of air pollution and meteorological factors on AD., Results: A total of 64 987 outpatient visits for AD were recorded from 1 January 2013 to 31 December 2017. Interactive effects were found between air pollutants and meteorological factors. Enhanced positive associations between pollutants and outpatient visits for AD were found at the highest quartile temperature level. A 10 μg/m 3 increase in PM 2.5 , PM 10 , NO 2 and SO 2 were associated with 0.42% (95% CI: 0.16-0.67%), 0.34% (95% CI: 0.15-0.54%), 1.11% (95% CI: 0.38-1.84%) and 1.06% (0.21-1.93%) increase in outpatient visits for AD at the highest quartile temperature level., Conclusion: That effects of air pollutants on AD can be modified by meteorological factors, with enhanced effects on hot days., (© 2019 European Academy of Dermatology and Venereology.)

Background: Eczema and dermatitis are a group of common skin conditions with multiple risk factors. Evidence of the effects of air pollutants on eczema and dermatitis remains limited. This study aimed to investigate the effects of short-term exposure to air pollution on eczema and dermatitis in Beijing., Methods: A time-stratified case-crossover design was used to assess the associations between short-term changes in air pollution and the hospital outpatient visits for eczema and dermatitis in Beijing., Results: A total of 157 595 outpatient visits for eczema and dermatitis were recorded from April 1, 2012 to April 30, 2014. All pollutants showed significant positive associations with the number of outpatient visits for eczema and dermatitis on lag 0 (the current day). Per IQR increase in PM2.5, PM10, NO2 and SO2 was associated with 3.81% (95% CI: 2.92-4.7%), 3.18% (95% CI: 2.39-3.97%), 5.43% (95% CI: 4.43-6.43%) and 5.57% (95% CI: 4.55-6.58%) increases in outpatient visits for eczema and dermatitis on lag 0. Associations of air pollutants with eczema and dermatitis outpatient visits varied with the seasons and were stronger among older people and females. Also, an association of consecutive days' high concentration pollution with increased outpatient visits was observed., Conclusions: Exposure to air pollution increases the exacerbation of eczema and dermatitis and stronger positive associations between air pollutants and outpatient visits for eczema and dermatitis were found among the aged, females and when high concentration air pollution occurs continuously.

Severe and persistent haze accompanied by high concentrations of fine particulate matter (PM 2.5 ) has become a great public health concern in urban China. However, research on the health effects of PM 2.5 in China has been hindered by the lack of high-quality exposure estimates. In this study, we assessed the excess mortality associated with both short- and long-term exposure to ambient PM 2.5 simultaneously using satellite-derived exposure data at a high spatiotemporal resolution. Adult registries of non-accidental, respiratory and cardiovascular deaths in urban Beijing in 2013 were collected. Exposure levels were estimated from daily satellite-based PM 2.5 concentrations at 1 km spatial resolution from 2004 to 2013. Mixed Poisson regression models were fitted to estimate the cause-specific mortality in association with PM 2.5 exposures. With the mutual adjustment of short- and long-term exposure of PM 2.5 , the percent increases associated with every 10 μg/m 3 increase in short-term PM 2.5 exposure were 0.09% (95% CI: -0.14%, 0.33%; lag 01), 1.02% (95% CI: 0.08%, 1.97%; lag 04) and 0.09% (95% CI: -0.23%, 0.42%; lag 01) for non-accidental, respiratory and cardiovascular mortality, respectively; those attributable to every 10 μg/m 3 increase in long-term PM 2.5 exposure (9-year moving average) were 16.78% (95% CI: 10.58%, 23.33%), 44.14% (95% CI: 20.73%, 72.10%) and 3.72% (95% CI: -3.75%, 11.77%), respectively. Both associations of short- and long-term exposure with the cause-specific mortality decreased after they were mutually adjusted. Associations between short-term exposure to satellite-based PM 2.5 and cause-specific mortality were larger than those estimated using fixed measurements. Satellite-based PM 2.5 predictions help to improve the spatiotemporal resolution of exposure assessments and the mutual adjustment model provide better estimation of PM 2.5 associated health effects. Effects attributable to long-term exposure of PM 2.5 were larger than those of short-term exposure, which should be more concerned for public health., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Satellite-driven statistical models have been proven to be able to provide spatially resolved PM 2.5 estimates worldwide. The North China Plain has been suffering from severe PM 2.5 pollution in recent years. An accurate assessment of the spatiotemporal characteristics of PM 2.5 levels in this region is crucial to design effective air pollution control policy. Our objective is to estimate daily PM 2.5 concentrations at 1km spatial resolution from 2004 to 2014 in Beijing and its surrounding areas using the Multi-angle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD). A high-performance three-stage model was developed with AOD, meteorological, demographic and land use variables as predictors, which includes a custom-designed PM 2.5 gap-filling method. The 11-year average annual coverage increased from 177days to 279days and annual PM 2.5 prediction error decreased from 14.1μg/m 3 to 8.3μg/m 3 after gap-filling techniques were applied. Results show that the 11-year overall mean of predicted PM 2.5 was 67.1μg/m 3 in our study domain. The cross-validation R 2 value of our model is 0.82 in 2013 and 0.79 in 2014. In addition, the models predicted historical PM 2.5 concentrations with relatively high accuracy at the seasonal and annual levels (R 2 ranged from 0.78 to 0.86). Our long-term PM 2.5 prediction filled the gaps left by ground monitors, which would be beneficial to PM 2.5 related epidemiological studies in Beijing., (Copyright © 2017 Elsevier B.V. All rights reserved.)

PM 2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM 2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM 2.5 in grid cells with a resolution of 10km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM 2.5 concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R 2 of 0.95 and 0.94, respectively and PM 2.5 was overestimated by WRF-Chem (R 2 =0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM 2.5 . Current monitoring network in North China was dense enough to provide a reliable PM 2.5 prediction by interpolation technique., (Copyright © 2017. Published by Elsevier Inc.)

In January 2013, severe haze events over northeastern China sparked substantial health concerns. This study explores the associations of fine particulate matter less than 2.5 μm (PM 2.5 ) and black carbon (BC) with hospital emergency room visits (ERVs) during a haze season in Beijing. During that period, daily counts of ERVs for respiratory, cardiovascular and ocular diseases were obtained from a Level-3A hospital in Beijing from 1 December 2012 to 28 February 2013, and associations of which with PM 2.5 and BC were estimated by time-stratified case-crossover analysis in single- and two-pollutant models. We found a 27.5% (95% confidence interval (CI): 13.0, 43.9%) increase in respiratory ERV (lag02), a 19.4% (95% CI: 2.5, 39.0%) increase in cardiovascular ERV (lag0), and a 12.6% (95% CI: 0.0, 26.7%) increase in ocular ERV (lag0) along with an interquartile range (IQR) increase in the PM 2.5 . An IQR increase of BC was associated with 27.6% (95% CI: 9.6, 48.6%) (lag02), 18.8% (95% CI: 1.4, 39.2%) (lag0) and 11.8% (95% CI: -1.4, 26.8%) (lag0) increases for changes in these same health outcomes respectively. Estimated associations were consistent after adjusting SO₂ or NO₂ in two-pollutant models. This study provides evidence that improving air quality and reducing haze days would greatly benefit the population health., Competing Interests: The authors declare no conflict of interest.

Objective: To use vertical and humidity correcting method to calibrate aerosol optical depth (AOD), and to explore the feasibility of calibrated-AOD as exposure index to measure the level of air pollutants from the ground and to establish the exposure-response relationship between calibrated-AOD and people's health outcomes., Methods: First of all, we interpolated AOD, PM 2.5 , relative humidity and planetary boundary layer height using Kriging method to obtain data at different locations and matched different data with respiratory death in Beijing by geographical coordinates. Then, the planetary boundary layer height and aerosol hygroscopic growth factor calculated based on relative humidity was used to calbrate the AOD. To compare the effects of calibrated-AOD and PM 2.5 , we used standardization method to get non dimensionless calibrated-AOD and PM 2.5 . At last, we used the generalized additive mixed model (GAMM) to estimate the acute effects of calibrated-AOD and PM 2.5 on respiratory death and chronic obstructive pulmonary disease (COPD) death, after controlling the time trend, temperature and humidity effects, days of the week effect and holiday effects., Results: The correlation coefficient between calibrated-AOD and PM 2.5 was 0.72. The effects of calibrated-AOD on respiratory death and COPD death was the strongest at lag 0-3, one unit of calibrated-AOD increases was associated with 3.64% (95%CI: 0.58%-6.78%) increase of respiratory death and 4.92% (95%CI: 1.81%-8.14%) increase of COPD death. As for PM 2.5 , the strongest effects appeared at lag 0-1, one unit of PM 2.5 (about 155 μg/m 3 ) increases was associated with excess risks of 3.96% (95%CI: 0.82%-7.19%) and 6.12% (95%CI: 1.44%-11.02%) for respiratory death and COPD death respectively. Compared with PM 2.5 , the effects of calibrated-AOD on respiratory death and COPD death had narrower confidence intervals. The calibrated-AOD was sensitive to capture the lag effects, and the cumulative lag effects of calibrated-AOD were all significant on multiple lag days which indicated that the calibrated-AOD was sensitive to capture cumulative lag effects of air pollutants on respiratory death and COPD death as well., Conclusion: We believe that calibrated-AOD can be used as an index to reflect the effects of air pollutants on respiratory death in Beijing. In the absence of ground monitoring, calibrated-AOD can be used to mea-sure the relationship between air pollutants and some health outcomes.

Background: Few studies have used spatially resolved ambient particulate matter with an aerodynamic diameter of <10 μm (PM10) to examine the impact of PM10 on ischemic heart disease (IHD) mortality in China. The aim of our study is to evaluate the short-term effects of PM10 concentrations on IHD mortality by means of spatiotemporal analysis approach., Methods: We collected daily data on air pollution, weather conditions and IHD mortality in Beijing, China during 2008 and 2009. Ordinary kriging (OK) was used to interpolate daily PM10 concentrations at the centroid of 287 township-level areas based on 27 monitoring sites covering the whole city. A generalized additive mixed model was used to estimate quantitatively the impact of spatially resolved PM10 on the IHD mortality. The co-effects of the seasons, gender and age were studied in a stratified analysis. Generalized additive model was used to evaluate the effects of averaged PM10 concentration as well., Results: The averaged spatially resolved PM10 concentration at 287 township-level areas was 120.3 ± 78.1 μg/m3. Ambient PM10 concentration was associated with IHD mortality in spatiotemporal analysis and the strongest effects were identified for the 2-day average. A 10 μg/m3 increase in PM10 was associated with an increase of 0.33% (95% confidence intervals: 0.13%, 0.52%) in daily IHD mortality. The effect estimates using spatially resolved PM10 were larger than that using averaged PM10. The seasonal stratification analysis showed that PM10 had the statistically stronger effects on IHD mortality in summer than that in the other seasons. Males and older people demonstrated the larger response to PM10 exposure., Conclusions: Our results suggest that short-term exposure to particulate air pollution is associated with increased IHD mortality. Spatial variation should be considered for assessing the impacts of particulate air pollution on mortality.

In this study, experiments were performed with a bench-scale tube-type wet electrostatic precipitator (wESPs) to investigate its effectiveness for the removal of mass- and number-based diesel particulate matter (DPM), hydrocarbons (HCs), carbon monoxide (CO), and oxides of nitrogen (NOx) from diesel exhaust emissions. The concentration of ozone (O3) present in the exhaust that underwent a nonthermal plasma treatment process inside the wESP was also measured. A nonroad diesel generator operating at varying load conditions was used as a stationary diesel emission source. The DPM mass analysis was conducted by means of isokinetic sampling and the DPM mass concentration was determined by a gravimetric method. An electrical low-pressure impactor (ELPI) was used to quantify the DPM number concentration. The HC compounds, n-alkanes, and polycyclic aromatic hydrocarbons (PAHs) were collected on a moisture-free quartz filter together with a PUF/XAD/PUF cartridge and extracted in dichloromethane with sonication. Gas chromatography (GC)/mass spectroscopy (MS) was used to determine HC concentrations in the extracted solution. A calibrated gas combustion analyzer (Testo 350) and an O3 analyzer were used for quantifying the inlet and outlet concentrations of CO and NOx (nitric oxide [NO] + nitrogen dioxide [NO2]), and O3 in the diesel exhaust stream. The wESP was capable of removing approximately 67-86% of mass- and number-based DPM at a 100% exhaust volumetric flow rate generated from 0- to 75-kW engine loads. At 75-kW engine load, increasing gas residence time from approximately 0.1 to 0.4 sec led to a significant increase of DPM removal efficiency from approximately 67 to more than 90%. The removal of n-alkanes, 16 PAHs, and CO in the wESP ranged from 31 to 57% and 5 to 38%, respectively. The use of the wESP did not significantly affect NOx concentration in diesel exhaust. The O3 concentration in diesel exhaust was measured to be less than 1 ppm. The main mechanisms responsible for the removal of these pollutants from diesel exhaust are discussed.