Baseline Investigation on Residential PM&lt;sub&gt;2.5&lt;/sub&gt; Pollution of General Living Scenarios — 12 Cities, China, 2018

Lin, Fan; Wang, Jiao; Yang, Yuyan; Li, Li; Li, Xu; Hang, Liu; Yang, Wenjing; Ge, Tanxi; Wang, Lin; Yao, Xiaoyuan; Wang, Xianliang

doi:10.46234/ccdcw2020.165

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…The study did not exclude the factor of ventilation. Fan et al 24 reported the average concentration to be 79 μg/m 3 in 12 cities in 2018. It was a baseline investigation with limitations on the detecting environment.…”

Section: Introductionmentioning

confidence: 99%

Characterization and exposure assessment of household fine particulate matter pollution in China

et al. 2021

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Household fine particulate matter (PM2.5) pollution greatly impacts residents' health. To explore the current national situation of household PM2.5 pollution in China, a study was conducted based on literature published from 1998 to 2018. After extracting data from the literature in conformity with the requirements, the nationwide household‐weighted mean concentration of household PM2.5 (HPL) was calculated. Subgroup analyses of spatial, geographic, and temporal differences were also done. The estimated overall HPL in China was 132.2 ± 117.7 μg/m3. HPL in the rural area (164.3 ± 104.5 μg/m3) was higher than that in the urban area (123.9 ± 122.3 μg/m3). For HPLs of indoor sampling sites, the kitchen was the highest, followed by the bedroom and living room. There were significant differences of geographic distributions. The HPLs in the South were higher than the North in four seasons. The inhaled dose of household PM2.5 among school‐age children differed from provinces with the highest dose up to 5.9 μg/(kg·d). Countermeasures should be carried out to reduce indoor pollution and safeguard health urgently.

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Section: Introductionmentioning

confidence: 99%

Characterization and exposure assessment of household fine particulate matter pollution in China

et al. 2021

Self Cite

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“…The anthropogenic emission of PM2.5 can be analyzed by the concentration value after eliminating the influence of meteorological factors. The contamination baseline (CB) is characterized as the lowest limit of long-term anthropogenic impact on soil and atmospheric contamination [13][14][15]. The cumulative frequency curve method is the most commonly used approach for determining CB.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Estimation of Urban PM2.5 Pollution Baseline and Meteorological Resource Endowment Using Machine Learning in Chinese Yangtze River Economic Belt

Ou,

Li,

Zhang

et al. 2023

IETI Trans. Data Anal. Forecast.

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Considering the influence of baseline values, meteorological conditions, and human activities on PM2.5, quantifying them will facilitate the classification, control, and management of pollution. The machine learning model explained the PM2.5-meteorological nonlinear relationship between PM2.5 and meteorological factors in each city across the Yangtze River Economic Belt, China. Meteorological resource endowments (MRE) are used to quantify the variation on PM2.5 concentration caused by meteorological conditions. Contamination baseline (CB) is used to characterize the lowest limit of anthropogenic impact in PM2.5 contamination without meteorological interference. According to the values of MRE and CB, cities in the Yangtze River economic belt can be divided into four categories (Q1-4). The average value of MRE is −0.41 μg/m3. The average value of CB is 34.05 μg/m3, which is lower than the Chinese Grade II standard (GB 3095-2012). The additional emissions by humans resulted in an increase of 7 μg/m3 in concentration, while the meteorological factors led to a decrease of −0.41 μg/m3. In terms of city classification, Q1 is concentrated in the midstream, and PM2.5 is the most challenging pollutant to control. Q2 is concentrated downstream, with relatively high PM2.5 emissions but favorable meteorological conditions. Q3 is concentrated upstream, and there is surplus environmental capacity even with limited meteorological conditions. Cites in Q4 have the most suitable development potential and exhibit a discrete spatial distribution. The research distinguished various categories of pollution and provided insights into the different characteristics of pollution around the Yangtze River Economic Belt. This information has helped the government classify cities and implement specific policies based on their individual situations.

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Spatiotemporal variation in residential PM2.5 and PM10 concentrations in China: National on-site survey

Zhu

Lin

Wang

et al. 2021

Environmental Research

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Baseline Investigation on Residential PM<sub>2.5</sub> Pollution of General Living Scenarios — 12 Cities, China, 2018

Cited by 3 publications

References 7 publications

Characterization and exposure assessment of household fine particulate matter pollution in China

Characterization and exposure assessment of household fine particulate matter pollution in China

Quantitative Estimation of Urban PM2.5 Pollution Baseline and Meteorological Resource Endowment Using Machine Learning in Chinese Yangtze River Economic Belt

Spatiotemporal variation in residential PM2.5 and PM10 concentrations in China: National on-site survey

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