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Atmospheric Deposition of Particulate Matter and Micropollutants as a Major Mass Transport Route to Surface Water in Winter: Measurement and Modeling in Beijing in 2014 and 2021

Liu, Shuang and Gu, Alan Y. and Zeng, Yuxin and Yin, Lifeng and Dai, Yunrong (2022) Atmospheric Deposition of Particulate Matter and Micropollutants as a Major Mass Transport Route to Surface Water in Winter: Measurement and Modeling in Beijing in 2014 and 2021. ACS Earth and Space Chemistry, 6 (4). pp. 962-973. ISSN 2472-3452. doi:10.1021/acsearthspacechem.1c00361. https://resolver.caltech.edu/CaltechAUTHORS:20220225-724787000

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Abstract

Deposition is a major route for atmospheric pollutants such as heavy metals and polycyclic aromatic hydrocarbons (PAHs) to transport to surface water. Here, we study Beijing, China, during the heavy haze period (2014) and the pandemic period (2021) to investigate the correlation between the atmospheric and surface water concentrations of 12 heavy metals and 16 PAHs. Pearson correlations and a series of back propagation (BP) neural network (NN) models are employed, and local meteorological conditions are included as input variables for the analysis. The surface water concentration of most pollutants analyzed correlate positively with humidity, PM_(2.5), PM₁₀, NO₂, SO₂, and CO, while negatively with the wind speed. The correlation coefficients are bigger in 2014 than in 2021, indicating accelerated gas–aqueous mass transport during haze episodes. The accurate prediction of the BP NN model in 2014 and 2021 presents itself as a promising tool in guiding future modeling efforts and policy changes.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1021/acsearthspacechem.1c00361DOIArticle
ORCID:
AuthorORCID
Gu, Alan Y.0000-0001-8095-3634
Yin, Lifeng0000-0002-5181-195X
Dai, Yunrong0000-0001-6335-4410
Additional Information:© 2022 American Chemical Society. Received: October 26, 2021; Revised: February 6, 2022; Accepted: February 10, 2022; Published: February 25, 2022. This study was financially supported by the National Natural Science Foundation of China (no. 21777009, no. 21407138), the Bill and Melinda Gates Foundation (BMGF RTTC Grants OPP1111246 and OPP1149755), the Beijing Natural Science Foundation (no. 8182031), and the Major Science and Technology Program for Water Pollution Control and Treatment (no. 2018ZX07109). The authors declare no competing financial interest.
Funders:
Funding AgencyGrant Number
National Natural Science Foundation of China21777009
National Natural Science Foundation of China21407138
Bill and Melinda Gates FoundationOPP1111246
Bill and Melinda Gates FoundationOPP1149755
Natural Science Foundation of Beijing Municipality8182031
Ministry of Science and Technology (China)2018ZX07109
Subject Keywords:winter; fine particulate matter; polycyclic aromatic hydrocarbons; heavy metals; correlation; back propagation neural network
Issue or Number:4
DOI:10.1021/acsearthspacechem.1c00361
Record Number:CaltechAUTHORS:20220225-724787000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220225-724787000
Official Citation:Shuang Liu, Alan Y. Gu, Yuxin Zeng, Lifeng Yin, and Yunrong Dai ACS Earth and Space Chemistry 2022 6 (4), 962-973; DOI: 10.1021/acsearthspacechem.1c00361
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:113618
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:25 Feb 2022 22:42
Last Modified:26 Apr 2022 17:09

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