CaltechAUTHORS
  A Caltech Library Service

Impacts of condensable particulate matter on atmospheric organic aerosols and fine particulate matter (PM_(2.5)) in China

Li, Mengying and Yu, Shaocai and Chen, Xue and Li, Zhen and Zhang, Yibo and Song, Zhe and Liu, Weiping and Liu, Pengfei and Zhang, Xiaoye and Zhang, Meigen and Sun, Yele and Liu, Zirui and Sun, Caiping and Jiang, Jingkun and Wang, Shuxiao and Murphy, Benjamin N. and Alapaty, Kiran and Mathur, Rohit and Rosenfeld, Daniel and Seinfeld, John H. (2022) Impacts of condensable particulate matter on atmospheric organic aerosols and fine particulate matter (PM_(2.5)) in China. Atmospheric Chemistry and Physics, 22 (17). pp. 11845-11866. ISSN 1680-7324. doi:10.5194/acp-22-11845-2022. https://resolver.caltech.edu/CaltechAUTHORS:20220926-577339400.21

Full text is not posted in this repository. Consult Related URLs below.

Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20220926-577339400.21

Abstract

Condensable particulate matter (CPM) emitted from stationary combustion and mobile sources exhibits high emissions and a large proportion of organic components. However, CPM is not generally measured when conducting emission surveys of PM in most countries, including China. Consequently, previous emission inventories have not included emission rates for CPM. Here, we construct an emission inventory of CPM in China with a focus on organic aerosols (OAs) based on collected CPM emission information. Results show that OA emissions are enhanced twofold after the inclusion of CPM in a new inventory for China for the years 2014 and 2017. Considering organic CPM emissions and model representations of secondary OA (SOA) formation from CPM, a series of sensitivity cases have been simulated here using the three-dimensional Community Multiscale Air Quality (CMAQ) model to estimate the contributions of CPM emissions to atmospheric OA and fine PM (PM_(2.5), particulate matter with aerodynamic diameter not exceeding 2.5 µm) concentrations in China. Compared with observations at a Beijing site during a haze episode from 14 October to 14 November 2014, estimates of the temporal average primary OA (POA) and SOA concentrations were greatly improved after including the CPM effects. These scenarios demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to the POA (51 %–85 %​​​​​​​), SOA (42 %–58 %), and total OA concentrations (45 %–75 %). Furthermore, the contributions of CPM emissions to total OA concentrations were demonstrated over the 2 major cities and 26 other cities of the Beijing–Tianjin–Hebei region (hereafter referred to as the "BTH2 + 26 cities") in December 2018, with average contributions of up to 49 %, 53 %, 54 %, and 50 % for Handan, Shijiazhuang, Xingtai, and Dezhou, respectively. Correspondingly, the inclusion of CPM emissions also narrowed the gap between simulated and observed PM_(2.5) concentrations over the BTH2 + 26 cities. These results improve the simulation performance of atmospheric OA and PM_(2.5) and may also provide important implications for the sources of OA.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.5194/acp-22-11845-2022DOIArticle
ORCID:
AuthorORCID
Yu, Shaocai0000-0001-9718-8246
Liu, Weiping0000-0002-1173-892X
Liu, Pengfei0000-0002-6714-7387
Zhang, Meigen0000-0002-3318-6134
Sun, Yele0000-0003-2354-0221
Liu, Zirui0000-0002-1939-9715
Wang, Shuxiao0000-0001-9727-1963
Murphy, Benjamin N.0000-0003-3542-5378
Mathur, Rohit0000-0001-8927-5876
Rosenfeld, Daniel0000-0002-0784-7656
Seinfeld, John H.0000-0003-1344-4068
Alternate Title:Impacts of condensable particulate matter on atmospheric organic aerosols and fine particulate matter (PM2.5) in China
Additional Information:The authors would like to thank the comprehensive data collection and sharing platform for atmospheric environmental science as well as the CERN Atmospheric Science Branch of the Institute of Atmospheric Physics, Chinese Academy of Sciences, for providing OC measurement data. This research has been supported by the National Natural Science Foundation of China (grant nos. 42175084, 21577126, 41561144004, and 92044302), the Department of Science and Technology of China (grant nos. 2018YFC0213506 and 2018YFC0213503), and the National Research Program for Key Issues in Air Pollution Control in China (grant no. DQGG0107). Pengfei Li is supported by the National Natural Science Foundation of China (grant no. 22006030), the Science and Technology Program of Hebei Province (grant no. 22343702D), the Research Foundation of Education Bureau of Hebei (grant no. BJ2020032), and the Initiation Fund of Hebei Agricultural University (grant no. 412201904).
Funders:
Funding AgencyGrant Number
National Natural Science Foundation of China42175084
National Natural Science Foundation of China21577126
National Natural Science Foundation of China41561144004
National Natural Science Foundation of China92044302
Department of Science and Technology (China)2018YFC0213506
Department of Science and Technology (China)2018YFC0213503
National Research Program for Key Issues in Air Pollution Control in ChinaDQGG0107
National Natural Science Foundation of China22006030
Science and Technology Program of Hebei Province22343702D
Hebei Youth Top FundBJ2020032
Hebei Agricultural University412201904
Issue or Number:17
DOI:10.5194/acp-22-11845-2022
Record Number:CaltechAUTHORS:20220926-577339400.21
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220926-577339400.21
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:117154
Collection:CaltechAUTHORS
Deposited By: Melissa Ray
Deposited On:30 Sep 2022 14:56
Last Modified:30 Sep 2022 14:56

Repository Staff Only: item control page