| Autor: |
Yao L; China Meteorological Administration-Nankai University Cooperative Laboratory for Atmospheric Environment-Health Research, State Environment Protection Key Laboratory of Urban Particulate Air Pollution Prevention, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China., Luo ZW; China Meteorological Administration-Nankai University Cooperative Laboratory for Atmospheric Environment-Health Research, State Environment Protection Key Laboratory of Urban Particulate Air Pollution Prevention, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China., Hua K; China Meteorological Administration-Nankai University Cooperative Laboratory for Atmospheric Environment-Health Research, State Environment Protection Key Laboratory of Urban Particulate Air Pollution Prevention, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China., Li YF; China Meteorological Administration-Nankai University Cooperative Laboratory for Atmospheric Environment-Health Research, State Environment Protection Key Laboratory of Urban Particulate Air Pollution Prevention, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China., Gu Y; China Meteorological Administration-Nankai University Cooperative Laboratory for Atmospheric Environment-Health Research, State Environment Protection Key Laboratory of Urban Particulate Air Pollution Prevention, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China., Song LL; China Meteorological Administration-Nankai University Cooperative Laboratory for Atmospheric Environment-Health Research, State Environment Protection Key Laboratory of Urban Particulate Air Pollution Prevention, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China., Bi SY; China Meteorological Administration-Nankai University Cooperative Laboratory for Atmospheric Environment-Health Research, State Environment Protection Key Laboratory of Urban Particulate Air Pollution Prevention, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China., Yin SH; China Meteorological Administration-Nankai University Cooperative Laboratory for Atmospheric Environment-Health Research, State Environment Protection Key Laboratory of Urban Particulate Air Pollution Prevention, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China., Kou MQ; Tianjin Jinnan District Ecological Environment Monitoring Center, Tianjin 300350, China., Bi XH; China Meteorological Administration-Nankai University Cooperative Laboratory for Atmospheric Environment-Health Research, State Environment Protection Key Laboratory of Urban Particulate Air Pollution Prevention, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China., Zhang YF; China Meteorological Administration-Nankai University Cooperative Laboratory for Atmospheric Environment-Health Research, State Environment Protection Key Laboratory of Urban Particulate Air Pollution Prevention, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China., Feng YC; China Meteorological Administration-Nankai University Cooperative Laboratory for Atmospheric Environment-Health Research, State Environment Protection Key Laboratory of Urban Particulate Air Pollution Prevention, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China. |
| Abstrakt: |
To elucidate the characteristics of VOCs chemical components during heavy pollution episodes, hourly online VOCs data derived from 11 heavy pollution events in Tianjin from 2019 to 2020 were employed. The positive matrix factorization （PMF） and conditional bivariate probability function （CBPF） were employed to analyze the sources of VOCs during heavy pollution episodes. The results indicated that the average VOCs volume fraction during these episodes was recorded at 35.7×10 -9 . Furthermore, it was observed that during the winter emergency response period, there was a discernible increase in the volume fraction of VOCs when compared to that during the autumn season. Specifically, there was a notable upswing of 48% in the olefins category, whereas alkanes registered a 4% increase. Additionally, the VOCs component structure changed significantly during the heavy pollution episodes. During the orange warning period, the proportion of alkanes increased by 36%, and the proportion of acetylene decreased by 32%. During the yellow warning period, the proportion of alkanes increased by 14%, and the proportion of acetylene decreased by 5%. During the emergency response period, motor vehicle emission sources, natural gas evaporative sources, and solvent use sources were the main contributors of VOCs in environmental receptors, contributing 17.5%, 15.4%, and 15.2%, respectively. Compared with that during the period antecedent to the emergency response, the contribution of vehicle emission sources and diesel volatile sources to VOCs in environmental receptors decreased by 2.0% to 5.5% and 2.1% to 6.6%, respectively, and the contribution of solvent use sources decreased by 0.2% to 2.4% during the yellow warning period. During the orange warning period, the contribution of motor vehicle emission sources was reduced by 0.1% to 8.3%, and the contribution of solvent use sources was reduced by 0.5% to 6.2%. |
