Impact of Air Pollutants on Lung Function and Inflammatory Response in Asthma in Shanghai.

Objective: Air pollution is a leading public health issue. This study investigated the effect of air quality and pollutants on pulmonary function and inflammation in patients with asthma in Shanghai. Methods: The study monitored 27 asthma outpatients for a year, collecting data on weather, patient self-management [daily asthma diary, peak expiratory flow (PEF) monitoring, medication usage], spirometry and serum markers. To explore the potential mechanisms of any effects, asthmatic mice induced by ovalbumin (OVA) were exposed to PM 2.5. Results: Statistical and correlational analyses revealed that air pollutants have both acute and chronic effects on asthma. Acute exposure showed a correlation between PEF and levels of ozone (O 3) and nitrogen dioxide (NO 2). Chronic exposure indicated that interleukin-5 (IL-5) and interleukin-13 (IL-13) levels correlated with PM 2.5 and PM 10 concentrations. In asthmatic mouse models, exposure to PM 2.5 increased cytokine levels and worsened lung function. Additionally, PM 2.5 exposure inhibited cell proliferation by blocking the NF-κB and ERK phosphorylation pathways. Conclusion: Ambient air pollutants exacerbate asthma by worsening lung function and enhancing Th2-mediated inflammation. Specifically, PM 2.5 significantly contributes to these adverse effects. Further research is needed to elucidate the mechanisms by which PM 2.5 impacts asthma.

Association between ambient air pollutants and short-term mortality risks during 2015-2019 in Guangzhou, China.

With the development of technology and industry, the problem of global air pollution has become difficult to ignore. We investigated the association between air pollutant concentrations and daily all-cause mortality and stratified the analysis by sex, age, and season. Data for six air pollutants [fine particulate matter (PM2.5), inhalable particles (PM10), nitric dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO)] and daily mortality rates were collected from 2015 to 2019 in Guangzhou, China. A time-series study using a quasi-Poisson generalized additive model was used to examine the relationships between environmental pollutant concentrations and mortality. Mortality data for 296,939 individuals were included in the analysis. The results showed that an increase of 10 µg/m3 in the concentrations of PM2.5, PM10, SO2, O3, NO2, and CO corresponded to 0.84% [95% confidence interval (CI): 0.47, 1.21%], 0.70% (0.44, 0.96%), 3.59% (1.77, 5.43%), 0.21% (0.05, 0.36%), 1.06% (0.70, 1.41%), and 0.05% (0.02, 0.09%), respectively. The effects of the six air pollutants were more significant for male individuals than female individuals, the cool season than the warm season, and people 75 years or older than those younger than 75 years. PM2.5, PM10, SO2, and NO2 were all associated with neoplasms and circulatory and respiratory diseases. The two-pollutant models found that PM2.5, PM10, and NO2 may independently affect the risk of mortality. The results showed that exposure to PM2.5, PM10 and NO2 may increase the risk of daily all-cause excessive mortality in Guangzhou.

A Review of Ambient Air Pollution as a Risk Factor for Posterior Segment Ocular Diseases.

PURPOSE: To review the most recent evidence on the association of ambient air pollution with posterior segment ocular diseases. METHODS: A search of the most recently published medical literature was performed in PubMed and Google Scholar on 10 December 2022. Articles published between 2018 and December 2022 were included in this rapid review. Studies that evaluated the association between ambient air pollutants (nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3), particulate matters (PMs), total hydrocarbons (THC), nonmethane hydrocarbons (NMHC), benzene), and ocular posterior segment diseases (glaucoma, age-related macular degeneration (AMD), and retinal vascular diseases) were included. RESULTS: Nineteen research articles met the inclusion criteria. Significant associations were found between PM2.5 and glaucoma, including primary open angle, primary angle closure, and normal tension glaucoma. An increased risk of AMD was linked to increased exposure to PM2.5, NO2, and CO. Single studies suggested that increased exposure to PM2.5 and PM10 is associated with diabetic retinopathy; THC and NMHC increased the risk of retinal vein occlusion; and CO, NO2, and PM10 are linked to an increased risk of central retinal artery occlusion. CONCLUSIONS: There is increasing evidence that toxic air pollutants have an impact on posterior segment ocular diseases, hence determining it as a potential modifiable risk factor for visual impairment.

Association between ambient air pollutants and upper respiratory tract infection and pneumonia disease burden in Thailand from 2000 to 2022: a high frequency ecological analysis.

BACKGROUND: A pertinent risk factor of upper respiratory tract infections (URTIs) and pneumonia is the exposure to major ambient air pollutants, with short term exposures to different air pollutants being shown to exacerbate several respiratory conditions. METHODS: Here, using disease surveillance data comprising of reported disease case counts at the province level, high frequency ambient air pollutant and climate data in Thailand, we delineated the association between ambient air pollution and URTI/Pneumonia burden in Thailand from 2000 - 2022. We developed mixed-data sampling methods and estimation strategies to account for the high frequency nature of ambient air pollutant concentration data. This was used to evaluate the effects past concentrations of fine particulate matter (PM2.5), sulphur dioxide (SO2), and carbon monoxide (CO) and the number of disease case count, after controlling for the confounding meteorological and disease factors. RESULTS: Across provinces, we found that past increases in CO, SO2, and PM2.5 concentration were associated to changes in URTI and pneumonia case counts, but the direction of their association mixed. The contributive burden of past ambient air pollutants on contemporaneous disease burden was also found to be larger than meteorological factors, and comparable to that of disease related factors. CONCLUSIONS: By developing a novel statistical methodology, we prevented subjective variable selection and discretization bias to detect associations, and provided a robust estimate on the effect of ambient air pollutants on URTI and pneumonia burden over a large spatial scale.

Prenatal ambient air pollutants exposure and the risk of stillbirth in Wuhan, central of China.

BACKGROUND: The existing studies on the relationships of prenatal ambient air pollutants exposure with stillbirth in the Chinese population are very limited and the results are inconsistent, and the susceptible windows and potential modifiers for air pollutants exposure on stillbirth remain unanswered. OBJECTIVE: We aimed to determine the relationships between exposure to ambient air pollutants and stillbirth, and explored the susceptible windows and potential modifiers for air pollutants exposure on stillbirth. METHODS: A population-based cohort was established through the Wuhan Maternal and Child Health Management Information System involving 509,057 mother-infant pairs in Wuhan from January 1, 2011 through September 30, 2017. Personal exposure concentrations of fine particles (PM2.5), inhalable particles (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) for mothers were estimated based on their residential address during pregnancy using the inverse distance weighted (IDW) method. We used the logistic regression models to determine the associations at different stages of pregnancy with adjustment for confounding factors. RESULTS: There were 3218 stillbirths and 505,839 live births among the participants. For each 100 µg/m3 of CO and 10 µg/m3 of O3 increase in the first trimester (conception to 13+6 weeks), the risk of stillbirth increased by 1.0% (OR = 1.01, 95%CI: 1.00-1.03) and 7.0% (OR = 1.07, 95%CI: 1.05-1.09). In the second trimester (14 weeks-27+6 weeks), PM2.5, PM10, CO, and O3 exposure were closely related to the risk of stillbirth (P＜0.05). In the third trimester (28 weeks to delivery), for each 10 µg/m3 increase in exposure concentrations of PM2.5, SO2, and O3, the risk of stillbirth increased by 3.4%, 5.9%, and 4.0%, respectively. O3 exposure was positively relevant to the risk of stillbirth (OR = 1.11, 95%CI: 1.08-1.14) in the whole pregnancy. Exposure to NO2 was not significantly associated with the risk of stillbirth. Stratified analyses also presented a stronger association among mothers with boy infant, living in rural areas, delivering between 2011 and 2013, and those without gestational hypertension and history of stillbirth. CONCLUSION: This study provides evidence that maternal exposure to PM2.5, PM10, SO2, CO, and O3 were related to the increased risk of stillbirth. Both the second and third trimesters might be vital susceptible windows for stillbirth. Our findings expand the evidence base for the important impacts of air pollution on fetal growth.

Long-term exposure to ambient air pollutants and their interaction with physical activity on insomnia: A prospective cohort study.

Exposure to air pollution or lack of physical activity (PA) increases the risk of insomnia. However, evidence on joint exposure to air pollutants is limited, and the interaction of joint air pollutants and PA on insomnia is unknown. This prospective cohort study included 40,315 participants with related data from the UK Biobank, which recruited participants from 2006 to 2010. Insomnia was assessed by self-reported symptoms. The annual average air pollutant concentrations of particulate matter (PM2.5, PM10), nitrogen oxides (NO2, NOX), sulfur dioxide (SO2) and carbon monoxide (CO) were calculated based on participants' addresses. We applied a weighted Cox regression model to evaluate the correlation between air pollutants and insomnia and newly proposed an air pollution score to assess joint air pollutants effect using a weighted concentration summation after obtaining the weights of each pollutant in the Weighted-quantile sum regression. With a median follow-up of 8.7 years, 8511 participants developed insomnia. For each 10 µg/m³ increase in NO2, NOX, PM10, SO2, the average hazard ratios (AHRs) and 95% confidence interval (CI) of insomnia were 1.10 (1.06, 1.14), 1.06 (1.04, 1.08), 1.35 (1.25, 1.45) and 2.58 (2.31, 2.89), respectively; For each 5 µg/m³ increase in PM2.5 and each 1 mg/m³ increase in CO, the corresponding AHRs (95%CI) were 1.27 (1.21, 1.34) and 1.83 (1.10, 3.04), respectively. The AHR (95%CI) for insomnia associated with per interquartile range (IQR) increase in air pollution scores were 1.20 (1.15, 1.23). In addition, potential interactions were examined by setting cross-product terms of air pollution score with PA in the models. We observed an interaction between air pollution scores and PA (P = 0.032). The associations between joint air pollutants and insomnia were attenuated among participants with higher PA. Our study provides evidence on developing strategies for improving healthy sleep by promoting PA and reducing air pollution.

Associations of exposures to air pollution and greenness with mortality in a newly treated tuberculosis cohort.

Some previous studies had linked air pollutants and greenness to the risk of death from tuberculosis (TB). Only a few studies had examined the effect of particulate matter (PM2.5) on the mortality of TB, and few studies had assessed the impact and interaction of multiple air pollutants and greenness on the mortality of newly treated TB patients. The study included 29,519 newly treated TB patients from three cities in Anhui province. We collected meteorological data and five pollutants data from The National Meteorological Science Center and air quality monitoring stations. Greenness data were generated by remote sensing inversion of medium-resolution satellite images. We geocoded each patient based on the residential address to calculate the average exposure to air pollutants and the average greenness exposure for each patient during treatment. The Cox proportional risk regression model was used to evaluate the effects of air pollutants and greenness on mortality in newly treated tuberculosis patients. Our results found that the higher the concentration of air pollutants in the living environment of newly treated TB patients, the greater the risk of death: HR 1.135 (95% CI: 1.123-1.147) and HR 1.333 (95% CI: 1.296-1.370) per 10 µg/m3 of PM2.5 and SO2, respectively. Greenness reduced the mortality among newly treated TB patients: HR for NDVI exposure 0.936 (95% CI: 0.925-0.947), HR for NDVI_250m exposure 0.927 (95% CI: 0.916-0.938), and HR for NDVI_500m exposure 0.919 (95% CI: 0.908-0.931). Stratifying the cohort by median greenness exposure, HRs for air pollutants were lower in the high greenness exposure group. Mortality in newly treated TB patients is influenced by air pollutants and greenness. Higher green exposure can mitigate the effects of air pollution. Improving air quality may help reduce mortality among newly treated TB patients.

Moderate physical activity against effects of short-term PM2.5 exposure on BP via myokines-induced inflammation.

Exposure to PM2.5 increases blood pressure (BP) and cardiovascular morbidity and mortality. We conducted a randomized controlled panel study in Shijiazhuang, China among 55 healthy college students randomly assigned to either the control (CON) or SPORTS group with intervention of 2000 m jogging in 20 min for 3 times in 4 days, and 3-round health examinations from November 15, 2020 to December 6, 2020. We aimed to evaluate whether moderate physical activity (PA) protected BP health against PM2.5 exposure and explore potential mechanisms through myokines and inflammation. Individual PM2.5 exposure was calculated based on outdoor and indoor PM2.5 concentration monitoring data as well as time-activity diary of each subject. In the CON group, the exposure-response curve for SBP was linear with a threshold concentration of approximately 31 µg/m3, while an increment of SBP level was 4.38 mm Hg (95%CI: 0.17 mm Hg, 8.59 mm Hg) at lag03 for each 10-µg/m3 increase in PM2.5, using linear mixed-effect models. For inflammatory indicators, PM2.5 exposure was associated with significant increases in eosinophil counts and proportion in CON group, but decreases in MCP-1 and TNF-α in SPORTS group. Meanwhile, higher myokines including CLU and IL-6 were observed in SPORTS group compared to the CON group. Further mediation analyses revealed that eosinophil counts mediated the elevated BP in CON group, whereas MCP-1 and TNF-α were also crucial mediating cytokines for the SPORTS group, as well as CLU and IL-6 acted as mediators on BP and inflammation indicators in SPORTS group. This study suggests that moderate PA could counteract the elevated BP induced by PM2.5 exposure via myokines-suppressed inflammation pathways.

Ambient air pollutants concentration prediction during the COVID-19: A method based on transfer learning.

Research on the correlation analysis between COVID-19 and air pollution has attracted increasing attention since the COVID-19 pandemic. While many relevant issues have been widely studied, research into ambient air pollutant concentration prediction (APCP) during COVID-19 is still in its infancy. Most of the existing study on APCP is based on machine learning methods, which are not suitable for APCP during COVID-19 due to the different distribution of historical observations before and after the pandemic. Therefore, to fulfill the predictive task based on the historical observations with a different distribution, this paper proposes an improved transfer learning model combined with machine learning for APCP during COVID-19. Specifically, this paper employs the Gaussian mixture method and an optimization algorithm to obtain a new source domain similar to the target domain for further transfer learning. Then, several commonly used machine learning models are trained in the new source domain, and these well-trained models are transferred to the target domain to obtain APCP results. Based on the real-world dataset, the experimental results suggest that, by using the improved machine learning methods based on transfer learning, our method can achieve the prediction with significantly high accuracy. In terms of managerial insights, the effects of influential factors are analyzed according to the relationship between these influential factors and prediction results, while their importance is ranked through their average marginal contribution and partial dependence plots.

Joint association between ambient air pollutant mixture and pediatric asthma exacerbations.

Exposure to air pollutants is known to exacerbate asthma, with prior studies focused on associations between single pollutant exposure and asthma exacerbations. As air pollutants often exist as a complex mixture, there is a gap in understanding the association between complex air pollutant mixtures and asthma exacerbations. We evaluated the association between the air pollutant mixture (52 pollutants) and pediatric asthma exacerbations. Method: This study focused on children (age ≤ 19 years) who lived in Douglas County, Nebraska, during 2016-2019. A seasonal-scale joint association between the outdoor air pollutant mixture adjusting for potential confounders (temperature, precipitation, wind speed, and wind direction) in relation to pediatric asthma exacerbation-related emergency department (ED) visits was evaluated using the generalized weighted quantile sum (qWQS) regression with repeated holdout validation. Results: We observed associations between air pollutant mixture and pediatric asthma exacerbations during spring (lagged by 5 days), summer (lag 0-5 days), and fall (lag 1-3 days) seasons. The estimate of the joint outdoor air pollutant mixture effect was higher during the summer season (adjusted-ßWQS = 1.11, 95% confidence interval [CI]: 0.66, 1.55), followed by spring (adjusted-ßWQS = 0.40, 95% CI: 0.16, 0.62) and fall (adjusted-ßWQS = 0.20, 95% CI: 0.06, 0.33) seasons. Among the air pollutants, PM2.5, pollen, and mold contributed higher weight to the air pollutant mixture. Conclusion: There were associations between outdoor air pollutant mixture and pediatric asthma exacerbations during the spring, summer, and fall seasons. Among the 52 outdoor air pollutant metrics investigated, PM2.5, pollen (sycamore, grass, cedar), and mold (Helminthosporium, Peronospora, and Erysiphe) contributed the highest weight to the air pollutant mixture.

Short-term effect of ambient air pollutant change on the risk of tuberculosis outpatient visits: a time-series study in Fuyang, China.

There is growing evidence that air pollution plays a role in TB, and most studies have been conducted in the core countries with inconsistent results. Few studies have comprehensively included the six common air pollutants, so they cannot consider whether various pollutants interact with each other. Our objectives were to investigate the association between short-term exposure to six common air pollutants and the risk of tuberculosis outpatient visits in Fuyang, China, 2015-2020. We combined the two models to explore the effects of exposure to six air pollutants on the risk of tuberculosis outpatient visits, including the Poisson generalized linear regression model and distributed lag non-linear model (DLNM). We performed stratified analyses for the season, type of cases, gender, and age. We used the lag-specific relative risks and cumulative relative risk obtained by increasing pollutant concentration by per 10 units to evaluate the connection between six air pollutants and TB; PM2.5 (RR = 1.0018, 95% CI: 1.0004-1.0032, delay of 12 days) and SO2 (RR = 1.0169, 95% CI: 1.0007-1.0333, lag 0-16 days) were 0.9549 (95% CI: 0.9389-0.9712, lag 0 day) and 0.8212 (95% CI: 0.7351-0.9173, 0-20-day lag). Stratified analyses showed that seasonal differences had a greater impact on TB, males were more likely to develop TB than females, older people were more likely to develop TB than younger people, and air pollution had a great impact on new cases. Exposure to O3, CO, PM10, PM2.5, and NO2 increases the risk of TB outpatient visits, except SO2 which reduces the risk. The incidence of TB has seasonal fluctuations. It is necessary for the government to establish a sound environmental monitoring and early warning system to strengthen the monitoring and emission management of pollutants in the atmosphere. Management, prevention, and treatment measures should be developed for high-risk groups (males and older people), reducing the risk of TB by reducing their specific behaviors and changing their lifestyle. We need to pay more attention to the impact of seasonal effects on TB to protect TB patients and avoid a shortage of medical resources, and it is necessary for the government to develop some seasonal preventive measures in the future.

Temporal air quality (NO2, O3, and PM10) changes in urban and rural stations in Catalonia during COVID-19 lockdown: an association with human mobility and satellite data.

In this study, changes in air quality by NO2, O3, and PM10 in Barcelona metropolitan area and other parts of Catalonia during the COVID-19 lockdown with respect to pre-lockdown and to previous years (2018 and 2019) were evaluated. Selected air monitoring stations included 3 urban (Gràcia, Vall d'Hebron, and Granollers), 1 control site (Fabra Observatory), 1 semi-urban (Manlleu), and 3 rural (Begur, Bellver de Cerdanya, and Juneda). NO2 lockdown levels showed a diminution, which in relative terms was maximum in two rural stations (Bellver de Cerdanya, - 63% and Begur, - 61%), presumably due to lower emissions from the ceasing hotel and ski resort activities during eastern holidays. In absolute terms and from an epidemiologic perspective, decrease in NO2, also reinforced by the high amount of rainfall registered in April 2020, was more relevant in the urban stations around Barcelona. O3 levels increased in the transited urban stations (Gràcia, + 42%, and Granollers, + 64%) due to the lower titration effect by NOx. PM10 lockdown levels decreased, mostly in Gràcia, Vall d'Hebron, and Granollers (- 35, - 39%, and - 39%, respectively) due to traffic depletion (- 90% in Barcelona's transport). Correlation among mobility index in Barcelona (- 100% in retail and recreation) and contamination was positive for NO2 and PM10 and negative for O3 (P < 0.001). Satellite images evidenced two hotspots of NO2 in Spain (Madrid and Barcelona) in April 2018 and 2019 that disappeared in 2020. Overall, the benefits of lockdown on air quality in Catalonia were evidenced with NO2, O3 and PM10 levels below WHOAQG values in most of stations opposed to the excess registered in previous years.

Association of long-term exposure to ambient air pollution with the number of tuberculosis cases notified: a time-series study in Hong Kong.

To analyze the association of long-term exposure to air pollution and its attributable risks with the number of tuberculosis (TB) cases notified, a quasi-Poisson regression model combined with a distributed lag nonlinear model (DLNM) was constructed using monthly data on air pollution and TB cases notified in Hong Kong from 1999 to 2018. Nonlinear relationships between PM10, PM2.5, and CO and TB cases notified were identified. The concentrations of PM10, PM2.5, and CO corresponding to the minimum numbers of TB cases notified (the minimum TB notification concentrations, MTNCs) were 58.3 µg/m3, 41.7 µg/m3, and 0.1 mg/m3, respectively. Compared with the MTNCs, the overall cumulative numbers of TB cases notified increased by 76.93% (95% CI: 13.08%, 176.83%), 88.81% (95% CI: 26.09%, 182.71%), and 233.43% (95% CI: 13.56%, 879.03%) for the 95th percentiles of PM10 and PM2.5 and for the 97.5th percentiles of CO, respectively. The TB notification rate attributed to concentration ranges above the 97.5th percentile of PM10, PM2.5, and CO was 3.38% (95% empirical confidence intervals [eCI]: 0.93%, 5.61%), 4.73% (95% eCI: 1.87%, 7.15%), and 3.34% (95% eCI: 0.29%, 5.83%), respectively. Long-term exposure to high concentrations of air pollution in Hong Kong may be associated with increases in the number of TB cases notified for this area.

Associations of Ambient Air Pollutants and Meteorological Factors With COVID-19 Transmission in 31 Chinese Provinces: A Time Series Study.

Evidence regarding the effects of environmental factors on COVID-19 transmission is mixed. We aimed to explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases during the outbreak period throughout China. The number of COVID-19 confirmed cases, air pollutant concentrations, and meteorological factors in China from January 25 to February 29, 2020, (36 days) were extracted from authoritative electronic databases. The associations were estimated for a single-day lag as well as moving averages lag using generalized additive mixed models. Region-specific analyses and meta-analysis were conducted in 5 selected regions from the north to south of China with diverse air pollution levels and weather conditions and sufficient sample size. Nonlinear concentration-response analyses were performed. An increase of each interquartile range in PM2.5, PM10, SO2, NO2, O3, and CO at lag4 corresponded to 1.40 (1.37-1.43), 1.35 (1.32-1.37), 1.01 (1.00-1.02), 1.08 (1.07-1.10), 1.28 (1.27-1.29), and 1.26 (1.24-1.28) ORs of daily new cases, respectively. For 1°C, 1%, and 1 m/s increase in temperature, relative humidity, and wind velocity, the ORs were 0.97 (0.97-0.98), 0.96 (0.96-0.97), and 0.94 (0.92-0.95), respectively. The estimates of PM2.5, PM10, NO2, and all meteorological factors remained significantly after meta-analysis for the five selected regions. The concentration-response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily new cases increasing. Higher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. Controlling ambient air pollution, especially for PM2.5, PM10, NO2, may be an important component of reducing risk of COVID-19 infection. In addition, as winter months are arriving in China, the meteorological factors may play a negative role in prevention. Therefore, it is significant to implement the public health control measures persistently in case another possible pandemic.

Association with Ambient Air Pollutants and School Absence Due to Sickness in Schoolchildren: A Case-Crossover Study in a Provincial Town of Japan.

The effect of ambient air pollutants and Asian dust (AD) on absence from school due to sickness has not been well researched. By conducting a case-crossover study, this study investigated the influence of ambient air pollutants and desert sand dust particles from East Asia on absence from school due to sickness. From November 2016 to July 2018, the daily cases of absence due to sickness were recorded in five elementary schools in Matsue, Japan. During the study period, a total of 16,915 absence cases were recorded, which included 4865 fever cases and 2458 cough cases. The relative risk of overall absence in a 10-µg/m3 increment of PM2.5 and a 0.1-km-1 of desert sand dust particles from East Asia were found with 1.28 (95%CI: 1.15-1.42) and 2.15 (1.04-4.45) at lag0, respectively. The significant influence of PM2.5 persisted at lag5 and that of desert sand dust particles at lag2. NO2 had statistically significant effects at lag2, lag3, and lag4. However, there was no evidence of a positive association of Ox and SO2 with absence from school. These results suggested that PM2.5, NO2, and AD increased the risk of absence due to sickness in schoolchildren.

Sperm mtDNA copy number, telomere length, and seminal spermatogenic cells in relation to ambient air pollution: Results of a cross-sectional study in Jing-Jin-Ji region of China.

Evidences on the association of air pollutants and semen quality were limited and mechanism-based biomarkers were sparse. We enrolled 423 men at a fertility clinic in Shijiazhuang, China to evaluate associations between air pollutants and semen quality parameters including the conventional ones, sperm mitochondrial DNA copy number (mtDNAcn), sperm telomere length (STL) and seminal spermatogenic cells. PM2.5, PM10, CO, SO2, NO2 and O3 exposure during lag0-90, lag0-9, lag10-14 and lag70-90 days were evaluated with ordinary Kringing model. The exposure-response correlations were analyzed with multiple linear regression models. CO, PM2.5 and PM10 were adversely associated with conventional semen parameters including sperm count, motility and morphology. Besides, CO was positively associated with seminal primary spermatocyte (lag70-90, 0.49; 0.14, 0.85) and mtDNAcn (lag0-90, 0.37; 0.12, 0.62, lag10-14, 0.31; 0.12, 0.49), negatively associated with STL (lag0-9, -0.30; -0.57, -0.03). PM2.5 was positively associated with mtDNAcn (0.50; 0.24, 0.75 and 0.38; 0.02, 0.75 for lag0-90 and lag70-90) while negatively associated with STL (lag70-90, -0.49; -0.96, -0.01). PM10 and NO2 were positively associated with mtDNAcn. Our findings indicate CO and PM might impair semen quality testicularly and post-testicularly while seminal spermatogenic cell, STL and mtDNAcn change indicate necessity for more attention on these mechanisms.

Personal exposure to ambient PM2.5, PM10, O3, NO2, and SO2 for different populations in 31 Chinese provinces.

Most epidemiological studies usually employ ambient air pollutant concentrations as a proxy of personal exposure to air pollutants originating outdoors, which could lead to a biased estimation of health effects. Herein, we modeled infiltration and exposure factors as the modifications of personal exposure to ambient PM2.5, PM10, O3, NO2, and SO2 for all seasons, genders, and ages in 31 Chinese provinces. The annual average exposure factors of PM10, PM2.5, O3, NO2, and SO2 were 0.42 ± 0.13 (arithmetic mean ± standard deviation), 0.68 ± 0.14, 0.34 ± 0.12, 0.50 ± 0.14, and 0.40 ± 0.13, respectively. We observed significant age, gender, seasonal, and geographical differences in infiltration and exposure factors for all studied ambient air pollutants. These factors were higher in southern China than in the north, and they were the highest in summer and the lowest in winter. The exposure factor of minors (age < 18 years) was significantly lower than that of adults (age ≥ 18 years, P < 0.01). Adult males had higher exposure factors than females (P < 0.01). Epidemiological studies utilizing outdoor concentrations of air pollutants could overestimate personal exposure to these pollutants. The present study could help in reducing the bias in the estimation of the health effects of air pollutants.

Associations of ambient air pollutants with airway and allergic symptoms in 13,335 preschoolers in Shanghai, China.

Findings are inconsistent in studies for impacts of outdoor air pollutants on airway health in childhood. In this paper, we collected data regarding airway and allergic symptoms in the past year before a survey in 13,335 preschoolers from a cross-sectional study. Daily averaged concentrations of ambient sulphur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter with an aerodynamic diameter ≤10 µm (PM10) in the past year before the survey were collected in the kindergarten-located district. We investigated associations of 12-month average concentrations of these pollutants with childhood airway and allergic symptoms. In the two-level (district-child) logistic regression analyses, exposure to higher level of NO2 and of PM10 increased odds of wheeze symptoms (adjusted OR, 95%CI: 1.03, 1.01-1.05 for per 3.0 µg/m3 increase in NO2; 1.22, 1.09-1.39 for per 7.6 µg/m3 increase in PM10), wheeze with a cold (1.03, 1.01-1.06; 1.22, 1.08-1.39), dry cough during night (1.05, 1.03-1.08; 1.23, 1.09-1.40), rhinitis symptoms (1.11, 1.08-1.13; 1.32, 1.07-1.63), rhinitis on pet (1.11, 1.05-1.18; 1.37, 0.95-1.98) and pollen (1.12, 1.03-1.21; 1.23, 0.84-1.82) exposure, eczema symptoms (1.09, 1.05-1.12; 1.22, 0.98-1.52), and lack of sleep due to eczema (1.12, 1.07-1.18; 1.58, 1.25-1.98). Exposures to NO2 and PM10 were also significantly and positively associated with the accumulative score of airway symptoms. Similar positive associations were found of NO2 and of PM10 with the individual symptoms and symptom scores among preschoolers from different kindergarten-located district. These results indicate that ambient NO2 and PM10 likely are risk factors for airway and allergic symptoms in childhood in Shanghai, China.

Spatiotemporal variations and influencing factors of PM2.5 concentrations in Beijing, China.

Fine particulate matter (PM2.5) pollution has become a worldwide environmental concern because of its adverse impacts on human health. This study aimed to explore the spatiotemporal variations and influencing factors of PM2.5 concentrations in Beijing during the 2013-2018 period, and further analyzed the impacts of environmental protection policies implemented in recent years. Notably, this study employed various statistical methods, i.e., ordinary Kriging interpolation, spatial autocorrelation analysis, time-series analysis and the Bonferroni test, to evaluate the regional and seasonal differences of PM2.5 concentrations based on long-term monitoring data. The results illustrated that PM2.5 concentrations decreased on a yearly basis, demonstrating that air pollution control policies have achieved initial success. Furthermore, PM2.5 concentrations were higher in the winter and in the southern regions. Diurnal variation presented a bimodal distribution, which varied slightly with the season. Relative humidity and wind speed were the principal meteorological factors affecting the distribution of PM2.5 concentrations, while precipitation had essentially no effect. A high positive correlation between PM2.5 and gaseous pollutants (SO2, NO2, and CO) indirectly reflected the contribution of automobile exhaust and coal-fired emissions. Generally, PM2.5 concentrations demonstrated strong spatiotemporal variations, and meteorological factors and pollutant emissions played an important role in this.

Spatial homogeneity and heterogeneity of ambient air pollutants in Tehran.

To investigate spatial inequality of ambient air pollutants and comparison of their heterogeneity and homogeneity across Tehran, the following quantitative indicators were utilized: coefficient of divergence (COD), the 90th percentile of the absolute differences between ambient air pollutant concentrations and coefficient of variation (CV). Real-time hourly concentrations of particulate matter (PM) and gaseous air pollutants (GAPs) of twenty-two air quality monitoring stations (AQMSs) were obtained from Tehran Air Quality Control Company (TAQCC) in 2017. Annual mean concentrations of PM2.5, PM10-2.5, and PM10 (PMX) ranged from 21.7 to 40.5, 37.3 to 75.0 and 58.0 to 110.4 µg m-3, respectively. Annual mean PM2.5 and PM10 concentrations were higher than the World Health Organization air quality guideline (WHO AQG) and national standard levels. NO2, O3, SO2 and CO annual mean concentrations ranged from 27.0 to 76.8, 15.5 to 25.1, 4.6 to 12.2 ppb, and 1.9 to 3.8 ppm over AQMSs, respectively. Our generated spatial maps exhibited that ambient PMX concentrations increased from the north into south and south-western areas as the hotspots of ambient PMX in Tehran. O3 hotspots were observed in the north and south-west, while NO2 hotspots were in the west and south. COD values of PMX demonstrated more results lower than the 0.2 cut off compared to GAPs; indicating high to moderate spatial homogeneity for PMX and moderate to high spatial heterogeneity for GAPs. Regarding CV approach, the spatial variabilities of air pollutants followed in the order of O3 (87.3%) > SO2 (65.2%) > CO (61.8%) > PM10-2.5 (52.5%) > PM2.5 (48.9%) > NO2 (48.1%) > PM10 (42.9%), which were mainly in agreement with COD results, except for NO2. COD values observed a statistically (P < 0.05) positive correlation with the values of the 90th percentile across AQMSs. Our study, for the first time, highlights spatial inequality of ambient PMX and GAPs in Tehran in detail to better facilitate establishing new intra-urban control policies.