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Atmospheric conditions and composition that influence PM2.5 oxidative potential in Beijing, China
被引:66
作者:
Campbell, Steven J.
[1
,2
]
Wolfer, Kate
[1
]
Utinger, Battist
[1
]
Westwood, Joe
[2
]
Zhang, Zhi-Hui
[1
,2
]
Bukowiecki, Nicolas
[1
]
Steimer, Sarah S.
[2
,10
]
Vu, Tuan V.
[3
,11
]
Xu, Jingsha
[3
]
Straw, Nicholas
[4
]
Thomson, Steven
[3
]
Elzein, Atallah
[5
]
Sun, Yele
[6
]
Liu, Di
[3
,6
]
Li, Linjie
[6
]
Fu, Pingqing
[8
]
Lewis, Alastair C.
[5
,7
]
Harrison, Roy M.
[3
,12
]
Bloss, William J.
[3
]
Loh, Miranda
[9
]
Miller, Mark R.
[4
]
Shi, Zongbo
[3
]
Kalberer, Markus
[1
,2
]
机构:
[1] Univ Basel, Dept Environm Sci, Basel, Switzerland
[2] Univ Cambridge, Dept Chem, Cambridge, England
[3] Univ Birmingham, Sch Geog Earth & Environm Sci, Birmingham, W Midlands, England
[4] Univ Edinburgh, Ctr Cardiovasc Sci, Queens Med Res Inst, Edinburgh, Midlothian, Scotland
[5] Univ York, Dept Chem, Wolfson Atmospher Chem Labs, York, N Yorkshire, England
[6] Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Atmospher Boundary Layer Phys & Atm, Beijing, Peoples R China
[7] Univ York, Natl Ctr Atmospher Sci, York, N Yorkshire, England
[8] Tianjin Univ, Inst Surface Earth Syst Sci, Tianjin, Peoples R China
[9] Inst Occupat Med, Edinburgh, Midlothian, Scotland
[10] Stockholm Univ, Dept Environm Sci, Stockholm, Sweden
[11] King Abdulaziz Univ, Ctr Excellence Environm Studies, Dept Environm Sci, POB 80203, Jeddah 21589, Saudi Arabia
[12] Imperial Coll London, Sch Publ Hlth, London, England
基金:
瑞士国家科学基金会;
英国自然环境研究理事会;
欧盟地平线“2020”;
欧洲研究理事会;
关键词:
POLYCYCLIC AROMATIC-HYDROCARBONS;
QUASI-ULTRAFINE PARTICLES;
PERSISTENT FREE-RADICALS;
OXYGEN SPECIES ACTIVITY;
WATER-SOLUBLE PM2.5;
PARTICULATE MATTER;
AIR-POLLUTION;
SPATIAL VARIATION;
DITHIOTHREITOL DTT;
GAS-PHASE;
D O I:
10.5194/acp-21-5549-2021
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Epidemiological studies have consistently linked exposure to PM2.5 with adverse health effects. The oxidative potential (OP) of aerosol particles has been widely suggested as a measure of their potential toxicity. Several acellular chemical assays are now readily employed to measure OP; however, uncertainty remains regarding the atmospheric conditions and specific chemical components of PM2.5 that drive OP. A limited number of studies have simultaneously utilised multiple OP assays with a wide range of concurrent measurements and investigated the seasonality of PM2.5 OP. In this work, filter samples were collected in winter 2016 and summer 2017 during the atmospheric pollution and human health in a Chinese megacity campaign (APHH-Beijing), and PM2.5 OP was analysed using four acellular methods: ascorbic acid (AA), dithiothreitol (DTT), 2,7-dichlorofluorescin/hydrogen peroxidase (DCFH) and electron paramagnetic resonance spectroscopy (EPR). Each assay reflects different oxidising properties of PM2.5, including particle-bound reactive oxygen species (DCFH), superoxide radical production (EPR) and catalytic redox chemistry (DTT/AA), and a combination of these four assays provided a detailed overall picture of the oxidising properties of PM2.5 at a central site in Beijing. Positive correlations of OP (normalised per volume of air) of all four assays with overall PM2.5 mass were observed, with stronger correlations in winter compared to summer. In contrast, when OP assay values were normalised for particle mass, days with higher PM2.5 mass concentrations (mu g m(-3)) were found to have lower mass-normalised OP values as measured by AA and DTT. This finding supports that total PM2.5 mass concentrations alone may not always be the best indicator for particle toxicity. Univariate analysis of OP values and an ex-tensive range of additional measurements, 107 in total, including PM2.5 composition, gas-phase composition and meteorological data, provided detailed insight into the chemical components and atmospheric processes that determine PM2.5 OP variability. Multivariate statistical analyses highlighted associations of OP assay responses with varying chemical components in PM2.5 for both mass- and volume-normalised data. AA and DTT assays were well predicted by a small set of measurements in multiple linear regression (MLR) models and indicated fossil fuel combustion, vehicle emissions and biogenic secondary organic aerosol (SOA) as influential particle sources in the assay response. Mass MLR models of OP associated with compositional source profiles predicted OP almost as well as volume MLR models, illustrating the influence of mass composition on both particle-level OP and total volume OP. Univariate and multivariate analysis showed that different assays cover different chemical spaces, and through comparison of mass- and volume-normalised data we demonstrate that mass-normalised OP provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis. This study constitutes one of the most extensive and comprehensive composition datasets currently available and provides a unique opportunity to explore chemical variations in PM2.5 and how they affect both PM2.5 OP and the concentrations of particle-bound reactive oxygen species.
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页码:5549 / 5573
页数:25
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