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Insights into source-specific PM2.5 mass, light extinction, and health risks in heavily polluted urban and suburban areas, northwestern China

  • Julian Shi
  • , Chongshu Zhu
  • , Suixin Liu
  • , Yao Qu
  • , Wenting Dai
  • , Nan Wang
  • , Luyao Wang
  • , Yue Zhou
  • , Rui Li
  • , Yingqiang Shi
  • , Junji Cao
  • CAS - Institute of Earth Environment
  • Xi'an Institute for Innovative Earth Environment Research
  • Guanzhong Plain Ecological Environment Change and Comprehensive Treatment National Observation and Research Station
  • China Meteorological Administration
  • University of Chinese Academy of Sciences
  • Xi'an Emergency Early Warning Information Release Center

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

To investigate the source apportionments of PM2.5 mass, light extinction, and health risk in a typical polluted Chinese city (Xianyang), urban and suburban PM2.5 samples were collected during the heating season (HS) and the non-heating season (NHS), respectively. Heightened levels of PM2.5 and chemical components were observed during the HS, particularly in urban areas. The urban and suburban PM2.5 concentrations were 132.1 ± 56.8 μg m−3 and 91.8 ± 42.5 μg m−3 during the HS, which were 2.8 and 2.3 times higher than the NHS levels, respectively. High levels of urban nitrogen oxidation ratio (NOR) during the HS and suburban sulfur oxidation ratio (SOR) during the NHS were obtained. Organic matter and secondary inorganic aerosols (SNA: SO42−, NO3−, and NH4+) were the predominant components of PM2.5. Compared to the HS, increased SNA and geological material were observed in the NHS. NH4NO3 was the dominant contributor to the light extinction coefficient (bext). The results indicated that PM2.5 mass, health risks from heavy metals, and bext were primarily attributed to biomass burning, industrial emissions, and secondary aerosols, respectively. Enhanced emission abatement of major primary sources and reducing the precursors of secondary aerosols could effectively improve visibility in the areas.

Original languageEnglish
Article number102205
JournalUrban Climate
Volume58
DOIs
StatePublished - Nov 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Health risk assessment
  • Light extinction
  • PM pollution
  • Source apportionment
  • The Guanzhong plain

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