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Impact of meteorology and aerosol sources on PM2.5 and oxidative potential variability and levels in China

  • Jiemei Liu
  • , Jesper H. Christensen
  • , Zhuyun Ye
  • , Shikui Dong
  • , Camilla Geels
  • , Jørgen Brandt
  • , Athanasios Nenes
  • , Yuan Yuan*
  • , Ulas Im*
  • *Corresponding author for this work
  • Harbin Institute of Technology
  • Aarhus University
  • Swiss Federal Institute of Technology Lausanne
  • Foundation for Research and Technology Hellas (FORTH)

Research output: Contribution to journalArticlepeer-review

Abstract

China has long-term high PM2.5 levels, and its oxidative potential (OP) is worth studying as it may unravel the impacts of aerosol pollution on public health better than PM2.5 alone. OP refers to the ability of PM2.5 to induce oxidative stress (OS). OP and PM2.5 are influenced by meteorological factors, anthropogenic emission sources, and atmospheric aging. Although their impact on PM2.5 has been studied, OP measurements only recently became available and on a limited scale, as they require considerable technical expertise and resources. For this, the joint relationship between PM2.5 and OP for a wide range of meteorological conditions and emission profiles remain elusive. Towards this, we estimated PM2.5 and OP over China using the Danish Eulerian Hemispheric Model (DEHM) system with meteorological input from the Weather Research and Forecasting (WRF) model. It was found that higher values of PM2.5 and OP were primarily concentrated in urban agglomerations in the central and eastern regions of China, while lower values were found in the western and northeastern regions. Furthermore, the probability density function revealed that about 40 % of areas in China had annual average PM2.5 concentrations exceeding the Chinese concentration limit. For OP, 36 % of the regions have OP below 1 nmolmin-1 m-3, 41 % have OP between 1 and 2 nmolmin-1 m-3, and 23 % have OP above 2 nmolmin-1 m-3, which are in line with previous measurement studies. Analysis of the simulations indicates that meteorological conditions contributed 46 % and 65 % to PM2.5 concentrations and OP variability, respectively, while anthropogenic emissions contributed 54 % and 35 % to PM2.5 concentrations and OP variability, respectively. The emission sensitivity analysis also highlighted the fact that PM2.5 and OP levels are mostly determined by secondary aerosol formation and biomass burning.

Original languageEnglish
Pages (from-to)10849-10867
Number of pages19
JournalAtmospheric Chemistry and Physics
Volume24
Issue number18
DOIs
StatePublished - 26 Sep 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

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