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  The Contribution of Black Carbon-Containing Particles to PM2.5: Variability, Drivers, and Impacts

Zhang, Y., Wang, J., Wu, N., Ouyang, X., Li, G., Cheng, Y., et al. (2025). The Contribution of Black Carbon-Containing Particles to PM2.5: Variability, Drivers, and Impacts. Environmental Science & Technology, 59. doi:10.1021/acs.est.5c00675.

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 Creators:
Zhang, Yuxuan, Author
Wang, Jinbo, Author
Wu, Nana, Author
Ouyang, Xiaoran, Author
Li, Guo, Author
Cheng, Yafang1, Author           
Zhang, Qiang, Author
Ding, Aijun, Author
Su, Hang, Author
Affiliations:
1Aerosol Chemistry, Max Planck Institute for Chemistry, Max Planck Society, ou_3618664              

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 Abstract: Atmospheric black carbon (BC) particles play an important role in air pollution, climate change, and human health. Evaluating BC’s impacts by model simulation requires an understanding of the distribution of other aerosol species between those containing BC and those free of BC particles during the atmospheric aging process. Previous studies observed a large variability in the mass fraction of BC-containing particles in PM2.5 (FBC-containing), complicating the determination of their impacts. In this work, we conducted field observations in various polluted environments across China for process-level understanding of FBC-containing. We find that the variability in FBC-containing, ranging from 10 to 90%, can be elucidated by the concept of atmospheric oxidation capacity (AOC). The contrast between observations of FBC-containing during haze events is determined by whether the initial aging of freshly emitted BC is limited by daytime AOC levels. We quantify and parametrize FBC-containing by resolving BC aging under different AOC conditions, indicating efficient formation of secondary aerosol on BC-containing particles when daytime-average concentrations of Ox (i.e., O3 + NO2) exceed 80 μg m–3. Our study provides valuable insights into BC mixing state representations under different environments, facilitating accurate evaluation of BC’s impacts in atmospheric models.

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Language(s): eng - English
 Dates: 2025-03-07
 Publication Status: Published online
 Pages: 9
 Publishing info: -
 Table of Contents: The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.5c00675.
 Rev. Type: -
 Identifiers: DOI: 10.1021/acs.est.5c00675
 Degree: -

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Title: Environmental Science & Technology
  Other : Environmental Science and Technology
  Other : ES&T
  Abbreviation : Environ. Sci. Technol.
Source Genre: Journal
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Publ. Info: Easton, PA : American Chemical Society
Pages: - Volume / Issue: 59 Sequence Number: - Start / End Page: - Identifier: ISSN: 1520-5851
ISSN: 0013-936X
CoNE: https://pure.mpg.de/cone/journals/resource/954921342157