OXIDATIVE POTENTIAL AND SOURCE APPORTIONMENT OF PM<sub>2.5</sub> DURING SPRING IN CHANGZHOU

WU Yihao; CUI Yaojia; ZANG Xinzhi; WANG Wenqiang; YE Zhaolian

doi:10.13205/j.hjgc.202405007

Volume 42 Issue 5

May 2024

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WU Yihao, CUI Yaojia, ZANG Xinzhi, WANG Wenqiang, YE Zhaolian. OXIDATIVE POTENTIAL AND SOURCE APPORTIONMENT OF PM2.5 DURING SPRING IN CHANGZHOU[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(5): 53-61. doi: 10.13205/j.hjgc.202405007

Citation:

WU Yihao, CUI Yaojia, ZANG Xinzhi, WANG Wenqiang, YE Zhaolian. OXIDATIVE POTENTIAL AND SOURCE APPORTIONMENT OF PM_2.5 DURING SPRING IN CHANGZHOU[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(5): 53-61. doi: 10.13205/j.hjgc.202405007

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OXIDATIVE POTENTIAL AND SOURCE APPORTIONMENT OF PM_2.5 DURING SPRING IN CHANGZHOU

doi: 10.13205/j.hjgc.202405007

School of Resources and Environmental Engineering, Jiangsu University of Technology, Changzhou 213001, China

Received Date: 2023-05-06
Available Online: 2024-07-11

Abstract

Abstract

To explore health risks and sources of fine particles (PM_2.5), we detected the oxidative potential (OP) of PM_2.5 in spring in Changzhou using the dithiothreitol (DTT) method, and characterized it by DTTv (volume-normalized DTT consumption) and DTTm (mass-normalized DTT consumption). Two source apportionment methods including positive matrix factorization (PMF) and principal component analysis (PCA) combined with multiple linear regression (MLR), were used to resolve emission sources of DTTv. The results showed that the average daily DTTv and DTTm in PM_2.5 were (0.83±0.09) nmol/(min·m³) and (12.52±4.22) pmol/(min·μg) during the sampling period, respectively, which were in the relatively lower exposure levels in China. Organic carbon, secondary ions (SO₄^2-, NO₃^-, and NH₄⁺), as well as characteristic elements of the traffic sources (Cu, Zn, etc.), correlated moderately with DTTv, suggesting both the secondary sources and traffic sources had some impact on PM exposure related to health. Source apportionment results from PMF showed that vehicle emission (40.1%) and secondary sources (35.6%) were more important contributors to DTTv in PM_2.5 than dust sources (18.6%) and combustion sources (5.8%), and MLR-PCA source apportionment method further confirmed significant contribution to DTT_v from vehicle emission and secondary sources. The results could provide theoretical and scientific guidance for precise prevention and control of air pollution and health effects.
- PM_2.5,
- oxidative potential,
- multiple linear regression,
- principal component analysis,
- positive matrix factorization

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References(40)

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