Atmospheric conditions and composition that influence PM 2.5 oxidative potential in Beijing, China.

Autor:	Campbell SJ; Department of Environmental Sciences, University of Basel, Basel, Switzerland.; Department of Chemistry, University of Cambridge, Cambridge, UK., Wolfer K; Department of Environmental Sciences, University of Basel, Basel, Switzerland., Utinger B; Department of Environmental Sciences, University of Basel, Basel, Switzerland., Westwood J; Department of Chemistry, University of Cambridge, Cambridge, UK., Zhang ZH; Department of Environmental Sciences, University of Basel, Basel, Switzerland.; Department of Chemistry, University of Cambridge, Cambridge, UK., Bukowiecki N; Department of Environmental Sciences, University of Basel, Basel, Switzerland., Steimer SS; Department of Chemistry, University of Cambridge, Cambridge, UK., Vu TV; School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK., Xu J; School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK., Straw N; Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK., Thomson S; School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK., Elzein A; Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, UK., Sun Y; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China., Liu D; School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK.; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China., Li L; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China., Fu P; Institute of Surface Earth System Science, Tianjin University, Tianjin, China., Lewis AC; Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, UK.; National Centre for Atmospheric Science, University of York, York, UK., Harrison RM; School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK., Bloss WJ; School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK., Loh M; Institute of Occupational Medicine, Edinburgh, UK., Miller MR; Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK., Shi Z; School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK., Kalberer M; Department of Environmental Sciences, University of Basel, Basel, Switzerland.; Department of Chemistry, University of Cambridge, Cambridge, UK.
Jazyk:	angličtina
Zdroj:	Atmospheric chemistry and physics [Atmos Chem Phys] 2021 Apr 12; Vol. 21 (7), pp. 5549-5573.
DOI:	10.5194/acp-21-5549-2021
Abstrakt:	Epidemiological studies have consistently linked exposure to PM 2.5 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 PM 2.5 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 PM 2.5 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 PM 2.5 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 PM 2.5 , 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 PM 2.5 at a central site in Beijing. Positive correlations of OP (normalised per volume of air) of all four assays with overall PM 2.5 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 PM 2.5 mass concentrations (μgm -3 ) were found to have lower mass-normalised OP values as measured by AA and DTT. This finding supports that total PM 2.5 mass concentrations alone may not always be the best indicator for particle toxicity. Univariate analysis of OP values and an extensive range of additional measurements, 107 in total, including PM 2.5 composition, gas-phase composition and meteorological data, provided detailed insight into the chemical components and atmospheric processes that determine PM 2.5 OP variability. Multivariate statistical analyses highlighted associations of OP assay responses with varying chemical components in PM 2.5 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 PM 2.5 and how they affect both PM 2.5 OP and the concentrations of particle-bound reactive oxygen species. Competing Interests: Competing interests. The authors declare that they have no conflict of interest.
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu