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Updated: Sep 20, 2025
Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions
Published on: January 7, 2019
[Analysis on the Characteristics of Oxidation Potential and Influence Sources of PM2.5 in Baoding City in Winter]
Ji-Yan Wu1,2, Chi Yang1,2, Chun-Yan Zahng1,2
1International Joint Laboratory on Climate and Environment Change (ILCEC), Yale-NUIST Center on Atmospheric Environment, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China.
Abstract:
In order to explore the characteristics of PM2.5 oxidation potential and its impact sources in the suburbs of Baoding City in the winter of 2018, the dithiothreitol (DTT) method was used to determine the reactive oxygen species in PM2.5. Pearson correlation was used to analyze the relationship between the chemical components in PM2.5 and the oxidation potential. PMF was used to analyze the pollution source of DTTv. Firstly, the results showed that the average value of ρ(PM2.5) in Baoding in winter was (140.96±70.67) μg·m-3 higher than the concentration of PM2.5 in Beijing during the same period. Secondly, both the DTTv and DTTm values of the oxidation potential were higher during the day than those at night[DTTv was (2.37±0.76) nmol·(min·m3)-1 during the day and (2.14±1.17) nmol·(min·m3)-1 at night; DTTm was (0.96±0.60) pmol·(min·μg)-1 during the day and (0.76±0.41) pmol·(min·μg)-1 at night]. This showed that the atmospheric environment during the day was more conducive to the generation and survival of active oxygen. In addition, through the analysis of the correlation between DTTv and carbohydrates, inorganic salt ions, OC, EC, and water-soluble metals, it was found that metal Fe, oxalate, and NH4+ had a high correlation with DTTv both day and night (during the day:r=0.790, P<0.01, at night:r=0.960, P<0.01; during the day:r=0.609, P<0.01, at night:r=0.577, P<0.01; during the day:r=0.627, P<0.01, at night:r=0.586, P<0.01), and OC, levoglucan, mannan, and galactan were only highly correlated with DTTv in the daytime (r=0.675, P<0.01; r=0.701, P<0.01; r=0.662, P<0.01; r=0.671, P<0.01). Finally, according to the PMF source analysis, there were five main pollution sources that affected DTTv:secondary sources (29.9%), biomass combustion (29.2%), dust (11.2%), mineral dust and industrial sources (8.6%), and traffic sources (21.1%). The influence of secondary sources and biomass combustion on DTTv was dominant.
