Prediction of fine particulate matter chemical components with a spatio-temporal model for the Multi-Ethnic Study of Atherosclerosis cohort

Abstract Background Maternal exposure to fine particulate matter (PM2.5) was associated with pregnancy complications. However, we still lack comprehensive evidence regarding which specific chemical components of PM2.5 are more harmful for maternal and foetal health. Objective We focused on exposure over the first trimester (0–13 weeks of gestation), which includes the early placentation period, and investigated whether PM2.5 and its components were associated with placenta-mediated pregnancy complications (combined outcome of small for gestational age, preeclampsia, placental abruption, and stillbirth). Methods From 2013 to 2015, we obtained information, from the Japan Perinatal Registry Network database, on 83,454 women who delivered singleton infants within 23 Tokyo wards (≈627 km2). Using daily filter sampling of PM2.5 at one monitoring location, we analysed carbon and ion components, and assigned the first trimester average of the respective pollutant concentrations to each woman. Results The ORs of placenta-mediated pregnancy complications were 1.14 (95% CI = 1.08–1.22) per 0.51 μg/m3 (interquartile range) increase of organic carbon and 1.11 (1.03–1.18) per 0.06 μg/m3 increase of sodium. Organic carbon was also associated with four individual complications. There was no association between ozone and outcome. Significance There were specific components of PM2.5 that have adverse effects on maternal and foetal health.

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Source Apportionment of PM2.5 during Haze and Non-Haze Episodes in Wuxi, China

Atmosphere ◽

10.3390/atmos9070267 ◽

2018 ◽

Vol 9 (7) ◽

pp. 267

Author(s):

Pulong Chen ◽

Tijian Wang ◽

Matthew Kasoar ◽

Min Xie ◽

Shu Li ◽

...

Keyword(s):

Particulate Matter ◽

Source Apportionment ◽

Secondary Organic Aerosols ◽

Fine Particulate Matter ◽

Organic Aerosols ◽

Chemical Components ◽

Industrial Sites ◽

Fine Particulate ◽

High Concentrations ◽

Haze Days

Chemical characteristics of fine particulate matter (PM2.5) in Wuxi at urban, industrial, and clean sites on haze and non-haze days were investigated over four seasons in 2016. In this study, high concentrations of fine particulate matter (107.6 ± 25.3 μg/m3) were measured in haze episodes. The most abundant chemical components were organic matter (OM), SO42−, NO3−, elemental carbon (EC), and NH4+, which varied significantly on haze and non-haze days. The concentrations of OM and EC were 38.5 ± 5.4 μg/m3 and 12.3 ± 2.1 μg/m3 on haze days, which were more than four times greater than those on non-haze days. Source apportionment using a chemical mass balance (CMB) model showed that the dominant sources were secondary sulfate (17.7%), secondary organic aerosols (17.1%), and secondary nitrate (14.2%) during the entire sampling period. The source contribution estimates (SCEs) of most sources at clean sites were lower than at urban and industrial sites. Primary industrial emission sources, such as coal combustion and steel smelting, made larger contributions at industrial sites, while vehicle exhausts and cooking smoke showed higher contributions at urban sites. In addition, the SCEs of secondary sulfate, secondary nitrate, and secondary organic aerosols on haze days were much higher than those on non-haze days, indicating that the secondary particulate matter formations process was the dominating reason for high concentrations of particles on haze days.

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Fine Particulate Matter Pollution Characteristics and Source Apportionment of Changchun Atmosphere

10.21203/rs.3.rs-431378/v1 ◽

2021 ◽

Author(s):

Jie Tang ◽

Zhuo Yang ◽

Yue Tui ◽

Ju Wang

Keyword(s):

Particulate Matter ◽

Mass Concentration ◽

Elemental Carbon ◽

Motor Vehicle ◽

Fine Particulate Matter ◽

Water Soluble ◽

Chemical Components ◽

Sample Collection ◽

Pollution Characteristics ◽

Fine Particulate

Abstract In order to study the pollution characteristics and main sources of fine particulate matter in the atmosphere of the city of Changchun, PM2.5 samples were collected during the four seasons in 2014, and representative months for each season are January, April, July, and October. Sample collection was carried out on 10 auto-monitoring stations in Changchun, and PM2.5 mass concentration, and its chemical components (including inorganic elements, organic carbon, elemental carbon, and water-soluble ions) were measured. The results show that the annual average mass concentration of PM2.5 in Changchun in 2014 was about 66.77 µg/m3. Organic matter was the highest component in PM2.5, followed by secondary inorganic ions (SNA), mineral dust (MIN), elemental carbon (EC), and trace elements (TE). Positive Matrix Factorization (PMF) results gave seven factors, namely, industrial, biomass- and coal-burning, industrial and soil dust, motor-vehicle, soil and secondary-ion, light-industrial, and hybrid-automotive and -industrial sources in PM2.5, with contributing values of 18.9%, 24.2%, 5.7%, 23.0%, 11.5%, 13.0%, and 3.6%, respectively.

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Analysis of Spatio-Temporal Heterogeneity and Socioeconomic Driving Factors of PM2.5 in Beijing–Tianjin–Hebei and Its Surrounding Areas

Atmosphere ◽

10.3390/atmos12101324 ◽

2021 ◽

Vol 12 (10) ◽

pp. 1324

Author(s):

Ju Wang ◽

Ran Li ◽

Kexin Xue ◽

Chunsheng Fang

Keyword(s):

Air Pollution ◽

Particulate Matter ◽

Fine Particulate Matter ◽

Shandong Province ◽

Temporal Heterogeneity ◽

Pollution Levels ◽

Fine Particulate ◽

Spatio Temporal ◽

Surrounding Areas ◽

Pm2.5 Concentration

Due to rapid urbanization and socio-economic development, fine particulate matter (PM2.5) pollution has drawn very wide concern, especially in the Beijing–Tianjin–Hebei region, as well as in its surrounding areas. Different socio-economic developments shape the unique characteristics of each city, which may contribute to the spatial heterogeneity of pollution levels. Based on ground fine particulate matter (PM2.5) monitoring data and socioeconomic panel data from 2015 to 2019, the Beijing–Tianjin–Hebei region, and its surrounding provinces, were selected as a case study area to explore the spatio-temporal heterogeneity of PM2.5 pollution, and the driving effect of socioeconomic factors on local air pollution. The spatio-temporal heterogeneity analysis showed that PM2.5 concentration in the study area expressed a downward trend from 2015 to 2019. Specifically, the concentration in Beijing–Tianjin–Hebei and Henan Province had decreased, but in Shanxi Province and Shandong Province, the concentration showed an inverted U-shaped and U-shaped variation trend, respectively. From the perspective of spatial distribution, PM2.5 concentrations in the study area had an obvious spatial positive correlation, with agglomeration characteristics of “high–high” and “low–low”. The high-value area was mainly distributed in the junction area of Henan, Shandong, and Hebei Provinces, which had been gradually moving to the southwest. The low values were mainly concentrated in the northern parts of Shanxi and Hebei Provinces, and the eastern part of Shandong Province. The results of the spatial lag model showed that Total Population (POP), Proportion of Urban Population (UP), Output of Second Industry (SI), and Roads Density (RD) had positive driving effects on PM2.5 concentration, which were opposite of the Gross Domestic Product (GDP). In addition, the spatial spillover effect of the PM2.5 concentrations in surrounding areas has a positive driving effect on local pollution levels. Although the PM2.5 levels in the study area have been decreasing, air pollution is still a serious problem. In the future, studies on the spatial and temporal heterogeneity of PM2.5 caused by unbalanced social development will help to better understand the interaction between urban development and environmental stress. These findings can contribute to the development of effective policies to mitigate and reduce PM2.5 pollutions from a socio-economic perspective.

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Measurements of Indoor and Outdoor Fine Particulate Matter during the Heating Period in Jinan, in North China: Chemical Composition, Health Risk, and Source Apportionment

Atmosphere ◽

10.3390/atmos11090885 ◽

2020 ◽

Vol 11 (9) ◽

pp. 885

Author(s):

Xiaomei Gao ◽

Weidong Gao ◽

Xiaoyan Sun ◽

Wei Jiang ◽

Ziyi Wang ◽

...

Keyword(s):

Particulate Matter ◽

North China ◽

Fine Particulate Matter ◽

Vulnerable Groups ◽

Chemical Components ◽

Fine Particulate ◽

Outdoor Environments ◽

Indoor And Outdoor Environments ◽

Indoor Pm2.5 ◽

Indoor And Outdoor

Fine particulate matter (PM2.5) was simultaneously collected from the indoor and outdoor environments in urban area of Jinan in North China from November to December 2018 to evaluate the characteristics and sources of indoor PM2.5 pollution. The concentrations of indoor and outdoor PM2.5 were 69.0 ± 50.5 µg m−3 and 128.7 ± 67.9 µg m−3, respectively, much higher than the WHO-established 24-h standards for PM2.5, indicating serious PM2.5 pollution of indoor and outdoor environments in urban Jinan. SO42−, NO3−, NH4+, and organic carbon (OC) were the predominant components, which accounted for more than 60% of the PM2.5 concentration. The total elemental risk values in urban Jinan for the three highly vulnerable groups of population (children (aged 2–6 years and 6–12 years) and older adults (≥70 years)) were nearly 1, indicating that exposure to all of the elements in PM2.5 had potential non-carcinogenic risks to human health. Further analyses of the indoor/outdoor concentration ratios, infiltration rates (FINF), and indoor-generated concentration (Cig) indicated that indoor PM2.5 and its major chemical components (SO42−, NO3−, NH4+, OC, and elemental carbon) were primarily determined by outdoor pollution. The lower indoor NO3−/SO42− ratio and FINF of NO3− relative to the outdoor values were due to the volatility of NO3−. Positive matrix factorization (PMF) was performed to estimate the sources of PM2.5 using the combined datasets of indoor and outdoor environments and revealed that secondary aerosols, dust, cement production, and coal combustion/metal smelting were the major sources during the sampling period.

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Air pollution and subclinical interstitial lung disease: the Multi-Ethnic Study of Atherosclerosis (MESA) air–lung study

European Respiratory Journal ◽

10.1183/13993003.00559-2017 ◽

2017 ◽

Vol 50 (6) ◽

pp. 1700559 ◽

Cited By ~ 40

Author(s):

Coralynn Sack ◽

Sverre Vedal ◽

Lianne Sheppard ◽

Ganesh Raghu ◽

R. Graham Barr ◽

...

Keyword(s):

Air Pollution ◽

Particulate Matter ◽

Interstitial Lung Disease ◽

Lung Disease ◽

Fine Particulate Matter ◽

Ambient Air ◽

Ambient Air Pollution ◽

Ethnic Study ◽

Fine Particulate ◽

Temporal Models

We studied whether ambient air pollution is associated with interstitial lung abnormalities (ILAs) and high attenuation areas (HAAs), which are qualitative and quantitative measurements of subclinical interstitial lung disease (ILD) on computed tomography (CT).We performed analyses of community-based dwellers enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA) study. We used cohort-specific spatio-temporal models to estimate ambient pollution (fine particulate matter (PM2.5), nitrogen oxides (NOx), nitrogen dioxide (NO2) and ozone (O3)) at each home. A total of 5495 participants underwent serial assessment of HAAs by cardiac CT; 2671 participants were assessed for ILAs using full lung CT at the 10-year follow-up. We used multivariable logistic regression and linear mixed models adjusted for age, sex, ethnicity, education, tobacco use, scanner technology and study site.The odds of ILAs increased 1.77-fold per 40 ppb increment in NOx (95% CI 1.06 to 2.95, p = 0.03). There was an overall trend towards an association between higher exposure to NOx and greater progression of HAAs (0.45% annual increase in HAAs per 40 ppb increment in NOx; 95% CI −0.02 to 0.92, p = 0.06). Associations of ambient fine particulate matter (PM2.5), NOx and NO2 concentrations with progression of HAAs varied by race/ethnicity (p = 0.002, 0.007, 0.04, respectively, for interaction) and were strongest among non-Hispanic white people.We conclude that ambient air pollution exposures were associated with subclinical ILD.

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