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

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 ($C_{\mathit{Oxi}}^{\mathit{obs}}$ (%) and $C_{G/P}^{\mathit{obs}}$ (%)) 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 $C_{G/P}^{\mathit{obs}}$ (%) was 64.90%) always contributed more than oxidation process (average $C_{\mathit{Oxi}}^{\mathit{obs}}$ (%) 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 $C_{\mathit{Oxi}}^{\mathit{obs}}$ (%) 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

Graphical Abstract

Editor:

• Jingkun Jiang

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability statement

All data necessary for replication are openly available at Zenodo repositories (https://doi.org/10.5281/zenodo.6420029). Additional information about these data is available from the corresponding author upon reasonable request.

Additional information

Funding

This study was supported by National Key Research and Development Program of China (2022YFC3703400), National Natural Science Foundation of China (42077191), Fundamental Research Funds for the Central Universities (63233054), Blue Sky Foundation, Special Innovation and Development Project of China Meteorological Administration (CXFZ2022P063). This work is a contribution from State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control.