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Cited by 926Atmospheric chemistry and aerosolsAir Quality and Health ImpactsAtmospheric aerosols and clouds

The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.

Fine particulate matter (PM2.5) in China at a city level

Open access
Zhang, Yan-Lin, Cao, Fang·2015·Scientific Reports
DOI 10.1038/srep14884PMC PMC4606739
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Abstract

This study presents one of the first long term datasets including a statistical summary of PM 2.5 concentrations obtained from one-year monitoring in 190 cities in China. We found only 25 out of 190 cities could meet the National Ambient Air Quality Standards of China and the population-weighted mean of PM 2.5 in Chinese cities are 61 μg/m 3, ~3 times as high as global population-weighted mean, highlighting a high health risk. PM 2.5 concentrations are generally higher in north than in south regions due to relative large PM emissions and unfavorable meteorological conditions for pollution dispersion. A remarkable seasonal variability of PM 2.5 is observed with the highest during the winter and the lowest during the summer. Due to the enhanced contributions from dust particles and open biomass burning, high PM 2.5 abundances are also found in the spring (in Northwest and West Central China) and autumn (in East China), respectively. In addition, we found the lowest and highest PM 2.5 often occurs in the afternoon and evening hours, respectively, associated with daily variation of the boundary layer depth and anthropogenic emissions. The diurnal distribution of the PM 2.5-to-CO ratio consistently displays a pronounced peak during the afternoon periods, reflecting a significant contribution of secondary PM formation.

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Crossref · 10.1038/srep14884

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Figure 1 The averaged PM2.5 concentrations (μg/m3) of the 190 cities of China, during the year of 2014/2015 (a) and during the spring (b), summer (c), autumn (d), and winter (e). The maps were drawn by the software of Igor Pro, http://www.wavemetrics.com/.
Figure 1 The averaged PM2.5 concentrations (μg/m3) of the 190 cities of China, during the year of 2014/2015 (a) and during the spring (b), summer (c), autumn (d), and winter (e). The maps were drawn by the software of Igor Pro, http://www.wavemetrics.com/.CC BY · PubMed Central
Figure 2 The averaged PM2.5/PM10 ratio of the 190 cities of China, during the year of 2014/2015 (a) and during the spring (b), summer (c), autumn (d), and winter (e). The maps were drawn by the software of Igor Pro, http://www.wavemetrics.com/.
Figure 2 The averaged PM2.5/PM10 ratio of the 190 cities of China, during the year of 2014/2015 (a) and during the spring (b), summer (c), autumn (d), and winter (e). The maps were drawn by the software of Igor Pro, http://www.wavemetrics.com/.CC BY · PubMed Central
Figure 3 Diurnal variations of hourly PM2.5 concentrations in Beijing (a), Shanghai (b) and Guangzhou (c).
Figure 3 Diurnal variations of hourly PM2.5 concentrations in Beijing (a), Shanghai (b) and Guangzhou (c).CC BY · PubMed Central
Figure 4 Daily evolution of average planetary boundary layer height in Beijing (a), Shanghai (b) and Guangzhou (c).
Figure 4 Daily evolution of average planetary boundary layer height in Beijing (a), Shanghai (b) and Guangzhou (c).CC BY · PubMed Central
Figure 5 Diurnal variations of hourly NO2 concentrations in Beijing (a), Shanghai (b) and Guangzhou (c).
Figure 5 Diurnal variations of hourly NO2 concentrations in Beijing (a), Shanghai (b) and Guangzhou (c).CC BY · PubMed Central
Figure 6 Diurnal variations of hourly SO2 concentrations in Beijing (a), Shanghai (b) and Guangzhou (c).
Figure 6 Diurnal variations of hourly SO2 concentrations in Beijing (a), Shanghai (b) and Guangzhou (c).CC BY · PubMed Central
Figure 7 Diurnal variations of hourly PM2.5 to CO ratios (PM2.5/CO) concentrations in Beijing (a), Shanghai (b) and Guangzhou (c).
Figure 7 Diurnal variations of hourly PM2.5 to CO ratios (PM2.5/CO) concentrations in Beijing (a), Shanghai (b) and Guangzhou (c).CC BY · PubMed Central
Figure 8 Cumulative distribution of annual mean PM2.5 estimated from ground measurements in 190 Chinese cities. The results from the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions are also displayed.
Figure 8 Cumulative distribution of annual mean PM2.5 estimated from ground measurements in 190 Chinese cities. The results from the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions are also displayed.CC BY · PubMed Central

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Metadata

Authors
Zhang, Y.-L., & Cao, F.
Affiliations
Nanjing University of Information Science and Technology (CN)
ORCID
Cao, Fang
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2015-10-15
Volume
5
Issue
1
Pages
14884-14884
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/srep14884
PMC
PMC4606739
OpenAlex
W2402894798
Cited by
921
References
36
Citations by year
2026: 15 · 2025: 38 · 2024: 50 · 2023: 82 · 2022: 107 · 2021: 105 · 2020: 119 · 2019: 136 · 2018: 128 · 2017: 95 · 2016: 46
FWCI
62.30
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • National Aeronautics and Space Administration
  • Government of Jiangsu Province
  • Natural Science Foundation of Jiangsu Province
  • Nanjing University of Information Science and Technology (2015r023, 2015r019)
  • Goddard Space Flight Center
  • Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology (2015r019, 2015r023)
Topics
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Atmospheric chemistry and aerosols
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Air Quality and Health Impacts
  • Physical Sciences › Environmental Science › Global and Planetary Change › Atmospheric aerosols and clouds
Keywords
PM2.5, urban air pollution, China, long-term air quality monitoring, seasonal variation, diurnal variation, boundary layer depth, dust, biomass burning, anthropogenic emissions, health risks, air quality standards
MeSH terms
Air Pollutants, China, Cities, Environmental Monitoring, Seasons, Particulate Matter

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