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Assessment of NO2 population exposure from 2005 to 2020 in China.

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Title: Assessment of NO2 population exposure from 2005 to 2020 in China.
Authors: Huang, Zhongyu1,2 (AUTHOR), Xu, Xiankang1,2 (AUTHOR), Ma, Mingguo1,2 (AUTHOR), Shen, Jingwei1,2 (AUTHOR) sjwgis@swu.edu.cn
Source: Environmental Science & Pollution Research. Nov2022, Vol. 29 Issue 53, p80257-80271. 15p.
Subject Terms: *Random forest algorithms, *Pollutants, *Environmental health, *Spatial variation, *Tropospheric aerosols, *Air pollutants, Population of China
Geographic Terms: China
Abstract: Nitrogen dioxide (NO2) is a major air pollutant with serious environmental and human health impacts. A random forest model was developed to estimate ground-level NO2 concentrations in China at a monthly time scale based on ground-level observed NO2 concentrations, tropospheric NO2 column concentration data from the Ozone Monitoring Instrument (OMI), and meteorological covariates (the MAE, RMSE, and R2 of the model were 4.16 µg/m3, 5.79 µg/m3, and 0.79, respectively, and the MAE, RMSE, and R2 of the cross-validation were 4.3 µg/m3, 5.82 µg/m3, and 0.77, respectively). On this basis, this article analyzed the spatial and temporal variation in NO2 population exposure in China from 2005 to 2020, which effectively filled the gap in the long-term NO2 population exposure assessment in China. NO2 population exposure over China has significant spatial aggregation, with high values mainly distributed in large urban clusters in the north, east, south, and provincial capitals in the west. The NO2 population exposure in China shows a continuous increasing trend before 2012 and a continuous decreasing trend after 2012. The change in NO2 population exposure in western and southern cities is more influenced by population density compared to northern cities. NO2 pollution in China has substantially improved from 2013 to 2020, but Urumqi, Lanzhou, and Chengdu still maintain high NO2 population exposure. In these cities, the Environmental Protection Agency (EPA) could reduce NO2 population exposure through more monitoring instruments and limiting factory emissions. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 159838185
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PubType: Academic Journal
PubTypeId: academicJournal
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  Label: Title
  Group: Ti
  Data: Assessment of NO<subscript>2</subscript> population exposure from 2005 to 2020 in China.
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  Data: <searchLink fieldCode="AR" term="%22Huang%2C+Zhongyu%22">Huang, Zhongyu</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xu%2C+Xiankang%22">Xu, Xiankang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ma%2C+Mingguo%22">Ma, Mingguo</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shen%2C+Jingwei%22">Shen, Jingwei</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> sjwgis@swu.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Science+%26+Pollution+Research%22">Environmental Science & Pollution Research</searchLink>. Nov2022, Vol. 29 Issue 53, p80257-80271. 15p.
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  Data: *<searchLink fieldCode="DE" term="%22Random+forest+algorithms%22">Random forest algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Pollutants%22">Pollutants</searchLink><br />*<searchLink fieldCode="DE" term="%22Environmental+health%22">Environmental health</searchLink><br />*<searchLink fieldCode="DE" term="%22Spatial+variation%22">Spatial variation</searchLink><br />*<searchLink fieldCode="DE" term="%22Tropospheric+aerosols%22">Tropospheric aerosols</searchLink><br />*<searchLink fieldCode="DE" term="%22Air+pollutants%22">Air pollutants</searchLink><br /><searchLink fieldCode="DE" term="%22Population+of+China%22">Population of China</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Nitrogen dioxide (NO2) is a major air pollutant with serious environmental and human health impacts. A random forest model was developed to estimate ground-level NO2 concentrations in China at a monthly time scale based on ground-level observed NO2 concentrations, tropospheric NO2 column concentration data from the Ozone Monitoring Instrument (OMI), and meteorological covariates (the MAE, RMSE, and R2 of the model were 4.16 µg/m3, 5.79 µg/m3, and 0.79, respectively, and the MAE, RMSE, and R2 of the cross-validation were 4.3 µg/m3, 5.82 µg/m3, and 0.77, respectively). On this basis, this article analyzed the spatial and temporal variation in NO2 population exposure in China from 2005 to 2020, which effectively filled the gap in the long-term NO2 population exposure assessment in China. NO2 population exposure over China has significant spatial aggregation, with high values mainly distributed in large urban clusters in the north, east, south, and provincial capitals in the west. The NO2 population exposure in China shows a continuous increasing trend before 2012 and a continuous decreasing trend after 2012. The change in NO2 population exposure in western and southern cities is more influenced by population density compared to northern cities. NO2 pollution in China has substantially improved from 2013 to 2020, but Urumqi, Lanzhou, and Chengdu still maintain high NO2 population exposure. In these cities, the Environmental Protection Agency (EPA) could reduce NO2 population exposure through more monitoring instruments and limiting factory emissions. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1007/s11356-022-21420-6
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 15
        StartPage: 80257
    Subjects:
      – SubjectFull: Random forest algorithms
        Type: general
      – SubjectFull: Pollutants
        Type: general
      – SubjectFull: Environmental health
        Type: general
      – SubjectFull: Spatial variation
        Type: general
      – SubjectFull: Tropospheric aerosols
        Type: general
      – SubjectFull: Air pollutants
        Type: general
      – SubjectFull: Population of China
        Type: general
      – SubjectFull: China
        Type: general
    Titles:
      – TitleFull: Assessment of NO2 population exposure from 2005 to 2020 in China.
        Type: main
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            NameFull: Huang, Zhongyu
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            NameFull: Xu, Xiankang
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            NameFull: Ma, Mingguo
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            NameFull: Shen, Jingwei
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            – D: 22
              M: 11
              Text: Nov2022
              Type: published
              Y: 2022
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            – TitleFull: Environmental Science & Pollution Research
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