Characterization of submicron aerosols influenced by biomass burning at a site in the Sichuan Basin, southwestern China

Severe air pollution in Asia is often the consequence of a combination of large anthropogenic emissions and adverse synoptic conditions. However, limited studies on aerosols have been conducted under high emission intensity and under unique geographical and meteorological conditions. In this stu...

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Main Authors: W. Hu, M. Hu, W.-W. Hu, H. Niu, J. Zheng, Y. Wu, W. Chen, C. Chen, L. Li, M. Shao, S. Xie, Y. Zhang
Format: Article
Language:English
Published: Copernicus Publications 2016-10-01
Series:Atmospheric Chemistry and Physics
Online Access:https://www.atmos-chem-phys.net/16/13213/2016/acp-16-13213-2016.pdf
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author W. Hu
W. Hu
M. Hu
W.-W. Hu
W.-W. Hu
H. Niu
H. Niu
J. Zheng
Y. Wu
W. Chen
C. Chen
L. Li
M. Shao
S. Xie
Y. Zhang
author_facet W. Hu
W. Hu
M. Hu
W.-W. Hu
W.-W. Hu
H. Niu
H. Niu
J. Zheng
Y. Wu
W. Chen
C. Chen
L. Li
M. Shao
S. Xie
Y. Zhang
author_sort W. Hu
collection DOAJ
description Severe air pollution in Asia is often the consequence of a combination of large anthropogenic emissions and adverse synoptic conditions. However, limited studies on aerosols have been conducted under high emission intensity and under unique geographical and meteorological conditions. In this study, an Aerodyne high-resolution time-of-flight aerosol mass spectrometry (HR-ToF-AMS) and other state-of-the-art instruments were utilized at a suburban site, Ziyang, in the Sichuan Basin during December 2012 to January 2013. The chemical compositions of atmospheric submicron aerosols (PM<sub>1</sub>) were determined, the sources of organic aerosols (OA) were apportioned, and the aerosol secondary formation and aging process were explored as well. Due to high humidity and static air, PM<sub>1</sub> maintained a relatively stable level during the whole campaign, with the mean concentration of 59.7 ± 24.1 µg m<sup>−3</sup>. OA was the most abundant component (36 %) in PM<sub>1</sub>, characterized by a relatively high oxidation state. Positive matrix factorization analysis was applied to the high-resolution organic mass spectral matrix, which deconvolved OA mass spectra into four factors: low-volatility (LV-OOA) and semivolatile oxygenated OA (SV-OOA), biomass burning (BBOA) and hydrocarbon-like OA (HOA). OOA (sum of LV-OOA and SV-OOA) dominated OA as high as 71 %. In total, secondary inorganic and organic formation contributed 76 % of PM<sub>1</sub>. Secondary inorganic species correlated well (Pearson <i>r</i> = 0.415–0.555, <i>p</i> &lt; 0.01) with relative humidity (RH), suggesting the humid air can favor the formation of secondary inorganic aerosols. As the photochemical age of OA increased with higher oxidation state, secondary organic aerosol formation contributed more to OA. The slope of OOA against O<sub><i>x</i></sub>( = O<sub>3</sub>+NO<sub>2</sub>) steepened with the increase of RH, implying that, besides the photochemical transformation, the aqueous-phase oxidation was also an important pathway of the OOA formation. Primary emissions, especially biomass burning, resulted in high concentration and proportion of black carbon (BC) in PM<sub>1</sub>. During the episode obviously influenced by primary emissions, the contributions of BBOA to OA (26 %) and PM<sub>1</sub> (11 %) were much higher than those (10–17 %, 4–7 %) in the clean and other polluted episodes, highlighting the significant influence of biomass burning.
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spelling doaj.art-d872e0082036425d8c0182a60c3ce9e32022-12-22T03:17:52ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242016-10-0116132131323010.5194/acp-16-13213-2016Characterization of submicron aerosols influenced by biomass burning at a site in the Sichuan Basin, southwestern ChinaW. Hu0W. Hu1M. Hu2W.-W. Hu3W.-W. Hu4H. Niu5H. Niu6J. Zheng7Y. Wu8W. Chen9C. Chen10L. Li11M. Shao12S. Xie13Y. Zhang14State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, Chinanow at: Graduate School of Environmental and Symbiotic Sciences, Prefectural University of Kumamoto, Kumamoto 862-8502, JapanState Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, ChinaState Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, Chinanow at: Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USAState Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, Chinanow at: Hebei Collaborative Innovation Center of Coal Exploitation, Hebei University of Engineering, Handan 056038, Hebei, ChinaState Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, ChinaState Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, ChinaState Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, ChinaState Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, ChinaState Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, ChinaState Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, ChinaState Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, ChinaState Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, ChinaSevere air pollution in Asia is often the consequence of a combination of large anthropogenic emissions and adverse synoptic conditions. However, limited studies on aerosols have been conducted under high emission intensity and under unique geographical and meteorological conditions. In this study, an Aerodyne high-resolution time-of-flight aerosol mass spectrometry (HR-ToF-AMS) and other state-of-the-art instruments were utilized at a suburban site, Ziyang, in the Sichuan Basin during December 2012 to January 2013. The chemical compositions of atmospheric submicron aerosols (PM<sub>1</sub>) were determined, the sources of organic aerosols (OA) were apportioned, and the aerosol secondary formation and aging process were explored as well. Due to high humidity and static air, PM<sub>1</sub> maintained a relatively stable level during the whole campaign, with the mean concentration of 59.7 ± 24.1 µg m<sup>−3</sup>. OA was the most abundant component (36 %) in PM<sub>1</sub>, characterized by a relatively high oxidation state. Positive matrix factorization analysis was applied to the high-resolution organic mass spectral matrix, which deconvolved OA mass spectra into four factors: low-volatility (LV-OOA) and semivolatile oxygenated OA (SV-OOA), biomass burning (BBOA) and hydrocarbon-like OA (HOA). OOA (sum of LV-OOA and SV-OOA) dominated OA as high as 71 %. In total, secondary inorganic and organic formation contributed 76 % of PM<sub>1</sub>. Secondary inorganic species correlated well (Pearson <i>r</i> = 0.415–0.555, <i>p</i> &lt; 0.01) with relative humidity (RH), suggesting the humid air can favor the formation of secondary inorganic aerosols. As the photochemical age of OA increased with higher oxidation state, secondary organic aerosol formation contributed more to OA. The slope of OOA against O<sub><i>x</i></sub>( = O<sub>3</sub>+NO<sub>2</sub>) steepened with the increase of RH, implying that, besides the photochemical transformation, the aqueous-phase oxidation was also an important pathway of the OOA formation. Primary emissions, especially biomass burning, resulted in high concentration and proportion of black carbon (BC) in PM<sub>1</sub>. During the episode obviously influenced by primary emissions, the contributions of BBOA to OA (26 %) and PM<sub>1</sub> (11 %) were much higher than those (10–17 %, 4–7 %) in the clean and other polluted episodes, highlighting the significant influence of biomass burning.https://www.atmos-chem-phys.net/16/13213/2016/acp-16-13213-2016.pdf
spellingShingle W. Hu
W. Hu
M. Hu
W.-W. Hu
W.-W. Hu
H. Niu
H. Niu
J. Zheng
Y. Wu
W. Chen
C. Chen
L. Li
M. Shao
S. Xie
Y. Zhang
Characterization of submicron aerosols influenced by biomass burning at a site in the Sichuan Basin, southwestern China
Atmospheric Chemistry and Physics
title Characterization of submicron aerosols influenced by biomass burning at a site in the Sichuan Basin, southwestern China
title_full Characterization of submicron aerosols influenced by biomass burning at a site in the Sichuan Basin, southwestern China
title_fullStr Characterization of submicron aerosols influenced by biomass burning at a site in the Sichuan Basin, southwestern China
title_full_unstemmed Characterization of submicron aerosols influenced by biomass burning at a site in the Sichuan Basin, southwestern China
title_short Characterization of submicron aerosols influenced by biomass burning at a site in the Sichuan Basin, southwestern China
title_sort characterization of submicron aerosols influenced by biomass burning at a site in the sichuan basin southwestern china
url https://www.atmos-chem-phys.net/16/13213/2016/acp-16-13213-2016.pdf
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