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Characteristics and source apportionment of VOCs measured in Shanghai, China
AbstractVolatile organic compounds (VOCs) were measured from 2007 to 2010 at the center of Shanghai, China. Because VOCs are important precursors for ozone photochemical formation, detailed information of VOC sources needs to be investigated. The results show that the measured VOC concentrations in Shanghai are dominated by alkanes (43%) and aromatics (30%), following by halo-hydrocarbons (14%) and alkenes (6%). Based on the measured VOC concentrations, a receptor model (PMF; positive matrix factorization) coupled with the information related to VOC sources (the distribution of major industrial complex, meteorological conditions, etc.) is applied to identify the major VOC sources in Shanghai. The result shows that seven major VOC sources are identified by the PMF method, including (1) vehicle related source which contributes to 25% of the measured VOC concentrations, (2) solvent based industrial source to 17%, (3) fuel evaporation to 15%, (4) paint solvent usage to 15%, (5) steel related industrial production to 12%, (6) biomass/biofuel burning to 9%, and (7) coal burning to 7%. Furthermore, ozone formation potential related to VOC sources is calculated by the MIR (maximum incremental reactivity) technique. The most significant VOC source for ozone formation potential is solvent based industrial sources (27%), paint solvent usage (24%), vehicle related emissions (17%), steel related industrial productions (14%), fuel evaporations (9%), coal burning (6%), and biomass/biofuel burning (3%). The weekend effect on the VOC concentrations shows that VOC concentrations are generally higher in the weekdays than in the weekends at the sampling site, suggesting that traffic conditions and human activities have important impacts on the VOC emissions in Shanghai.
Characteristics and source apportionment of VOCs measured in Shanghai, China
AbstractVolatile organic compounds (VOCs) were measured from 2007 to 2010 at the center of Shanghai, China. Because VOCs are important precursors for ozone photochemical formation, detailed information of VOC sources needs to be investigated. The results show that the measured VOC concentrations in Shanghai are dominated by alkanes (43%) and aromatics (30%), following by halo-hydrocarbons (14%) and alkenes (6%). Based on the measured VOC concentrations, a receptor model (PMF; positive matrix factorization) coupled with the information related to VOC sources (the distribution of major industrial complex, meteorological conditions, etc.) is applied to identify the major VOC sources in Shanghai. The result shows that seven major VOC sources are identified by the PMF method, including (1) vehicle related source which contributes to 25% of the measured VOC concentrations, (2) solvent based industrial source to 17%, (3) fuel evaporation to 15%, (4) paint solvent usage to 15%, (5) steel related industrial production to 12%, (6) biomass/biofuel burning to 9%, and (7) coal burning to 7%. Furthermore, ozone formation potential related to VOC sources is calculated by the MIR (maximum incremental reactivity) technique. The most significant VOC source for ozone formation potential is solvent based industrial sources (27%), paint solvent usage (24%), vehicle related emissions (17%), steel related industrial productions (14%), fuel evaporations (9%), coal burning (6%), and biomass/biofuel burning (3%). The weekend effect on the VOC concentrations shows that VOC concentrations are generally higher in the weekdays than in the weekends at the sampling site, suggesting that traffic conditions and human activities have important impacts on the VOC emissions in Shanghai.
Characteristics and source apportionment of VOCs measured in Shanghai, China
Cai, Changjie (Autor:in) / Geng, Fuhai (Autor:in) / Tie, Xuexi (Autor:in) / Yu, Qiong (Autor:in) / An, Junlin (Autor:in)
Atmospheric Environment ; 44 ; 5005-5014
27.07.2010
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Characterizations of ozone, NOx, and VOCs measured in Shanghai, China
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