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Evaluation and Bias Correction of the Secondary Inorganic Aerosol Modeling over North China Plain in Autumn and Winter.

Authors :
Wu, Qian
Tang, Xiao
Kong, Lei
Dao, Xu
Lu, Miaomiao
Liu, Zirui
Wang, Wei
Wang, Qian
Chen, Duohong
Wu, Lin
Pan, Xiaole
Li, Jie
Zhu, Jiang
Wang, Zifa
Sotiropoulou, Rafaella Eleni P.
Tagaris, Efthimios
Source :
Atmosphere; May2021, Vol. 12 Issue 5, p578, 1p
Publication Year :
2021

Abstract

Secondary inorganic aerosol (SIA) is the key driving factor of fine-particle explosive growth (FPEG) events, which are frequently observed in North China Plain. However, the SIA simulations remain highly uncertain over East Asia. To further investigate this issue, SIA modeling over North China Plain with the 15 km resolution Nested Air Quality Prediction Model System (NAQPMS) was performed from October 2017 to March 2018. Surface observations of SIA at 28 sites were obtained to evaluate the model, which confirmed the biases in the SIA modeling. To identify the source of these biases and reduce them, uncertainty analysis was performed by evaluating the heterogeneous chemical reactions in the model and conducting sensitivity tests on the different reactions. The results suggest that the omission of the SO<subscript>2</subscript> heterogeneous chemical reaction involving anthropogenic aerosols in the model is probably the key reason for the systematic underestimation of sulfate during the winter season. The uptake coefficient of the "renoxification" reaction is a key source of uncertainty in nitrate simulations, and it is likely to be overestimated by the NAQPMS. Consideration of the SO<subscript>2</subscript> heterogeneous reaction involving anthropogenic aerosols and optimization of the uptake coefficient of the "renoxification" reaction in the model suitably reproduced the temporal and spatial variations in sulfate, nitrate and ammonium over North China Plain. The biases in the simulations of sulfate, nitrate, ammonium, and particulate matter smaller than 2.5 μm (PM<subscript>2.5</subscript>) were reduced by 84.2%, 54.8%, 81.8%, and 80.9%, respectively. The results of this study provide a reference for the reduction in the model bias of SIA and PM<subscript>2.5</subscript> and improvement of the simulation of heterogeneous chemical processes. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20734433
Volume :
12
Issue :
5
Database :
Complementary Index
Journal :
Atmosphere
Publication Type :
Academic Journal
Accession number :
150475130
Full Text :
https://doi.org/10.3390/atmos12050578