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Gas-particle partitioning process contributes more to nitrate dominated air pollution than oxidation process in northern China.

Authors :
Tian, Xiao
Yu, Haofei
Wei, Yuting
Shi, Zongbo
Feng, Yinchang
Zhang, Linlin
Shi, Guoliang
Source :
Aerosol Science & Technology. Feb2024, Vol. 58 Issue 2, p181-194. 14p.
Publication Year :
2024

Abstract

Nitrate has been recognized as a key aerosol component in regional haze formation in China. However, reducing nitrate aerosol concentration remains a major challenge. Generally, the formation of particulate nitrate (NO3-) is mainly affected by two processes: oxidation (to generate gaseous HNO3 or particulate NO3-) and gas-particle partitioning (HNO3-NO3- partition). Here, we proposed a new method to explore the contributions of above two processes ( C Oxi obs (%) and C G / P obs (%)) to nitrate formation based on field observation, and combined theoretical calculation and modeling to verify it. Quantitative results showed that gas-particle partitioning process (average C G / P obs (%) was 64.90%) always contributed more than oxidation process (average C Oxi obs (%) was 35.10%) for particulate nitrate formation under different pollution scenarios in the ambient environment. We argued that this phenomenon was mainly caused by high aerosol pH (>4.5). Nevertheless, as pollution level rose, the C Oxi obs (%) will also increase (contributing to 32%, 38%, 40% and 41% under clean, light, medium and heavy pollution levels) which may be attributed to the increased HNO3 production rate and relatively enhanced heterogeneous reaction pathway. The results indicate future strategies for prevention and control of nitrate pollution should both consider reducing precursors emission and regulating aerosol acidity, in order to increase the effectiveness of reducing nitrate dominated pollution. Copyright © 2023 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02786826
Volume :
58
Issue :
2
Database :
Academic Search Index
Journal :
Aerosol Science & Technology
Publication Type :
Academic Journal
Accession number :
175034731
Full Text :
https://doi.org/10.1080/02786826.2023.2294944