Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Assessment of the impacts of aromatic VOC emissions and yields of SOA on SOA concentrations with the air quality model RAMS-CMAQ
AbstractThe secondary organic aerosol (SOA) concentration is generally underestimated by models. Recent studies suggest that the underprediction is related to underestimations of aromatic volatile organic compound (VOC) emissions and SOA yields in current models. Here, the impacts of these two factors in China were investigated with the regional air quality modeling system RAMS-CMAQ, referring to field observations during the episode from October 14 to November 14, 2014. Comparisons between the observed and modeled SOA of four sensitivity simulation cases indicated the significant impacts of the two underestimated factors on the SOA output. By considering these two aspects, the simulated mean SOA concentrations significantly increased by nearly 4 times with a good representation of the intensively temporal variations of concentrations, which were largely controlled by photochemical processes rather than meteorological conditions. The improvement in SOA compensated for the underestimations by approximately 23.5% and contributed to the mean fraction of SOA to organic aerosol (OA) by increasing the fraction from less than 7% to more than 25%, which was closer to the observed result. These results suggested a more reasonable and more realistic representation of SOA formation in the model after allowing for the two factors. Due to the better simulation of SOA, predictions of OA were correspondingly improved when the correlation coefficient increased from 0.57 to 0.73 and other bias parameters were reduced, which indicated the improved ability of our model to trace the temporal variations of OA. Based on the improved simulation throughout the episode, the mean SOA concentration was obviously higher in eastern China than in the west. The highest concentration appeared in the Sichuan Basin and Pearl River Delta (PRD) areas, with values of 6–11 μg/m3 and 8–17 μg/m3, respectively. Over the wide regions of central and eastern China, the dominant component in SOA was formed from anthropogenic sources (ASOA), generally accounting for more than 60%.
HighlightsAromatic-derived SOA formations under different NOx concentrations are incorporated in the model.The impacts of underestimated aromatic emissions and SOA yields on SOA production are evaluated.By the considerations of two underestimated factors, modeled SOA concentrations increased by nearly 4 times.Over 60% of SOA were formed from anthropogenic precursors in central and eastern China.
Assessment of the impacts of aromatic VOC emissions and yields of SOA on SOA concentrations with the air quality model RAMS-CMAQ
AbstractThe secondary organic aerosol (SOA) concentration is generally underestimated by models. Recent studies suggest that the underprediction is related to underestimations of aromatic volatile organic compound (VOC) emissions and SOA yields in current models. Here, the impacts of these two factors in China were investigated with the regional air quality modeling system RAMS-CMAQ, referring to field observations during the episode from October 14 to November 14, 2014. Comparisons between the observed and modeled SOA of four sensitivity simulation cases indicated the significant impacts of the two underestimated factors on the SOA output. By considering these two aspects, the simulated mean SOA concentrations significantly increased by nearly 4 times with a good representation of the intensively temporal variations of concentrations, which were largely controlled by photochemical processes rather than meteorological conditions. The improvement in SOA compensated for the underestimations by approximately 23.5% and contributed to the mean fraction of SOA to organic aerosol (OA) by increasing the fraction from less than 7% to more than 25%, which was closer to the observed result. These results suggested a more reasonable and more realistic representation of SOA formation in the model after allowing for the two factors. Due to the better simulation of SOA, predictions of OA were correspondingly improved when the correlation coefficient increased from 0.57 to 0.73 and other bias parameters were reduced, which indicated the improved ability of our model to trace the temporal variations of OA. Based on the improved simulation throughout the episode, the mean SOA concentration was obviously higher in eastern China than in the west. The highest concentration appeared in the Sichuan Basin and Pearl River Delta (PRD) areas, with values of 6–11 μg/m3 and 8–17 μg/m3, respectively. Over the wide regions of central and eastern China, the dominant component in SOA was formed from anthropogenic sources (ASOA), generally accounting for more than 60%.
HighlightsAromatic-derived SOA formations under different NOx concentrations are incorporated in the model.The impacts of underestimated aromatic emissions and SOA yields on SOA production are evaluated.By the considerations of two underestimated factors, modeled SOA concentrations increased by nearly 4 times.Over 60% of SOA were formed from anthropogenic precursors in central and eastern China.
Assessment of the impacts of aromatic VOC emissions and yields of SOA on SOA concentrations with the air quality model RAMS-CMAQ
Li, Jialin (Autor:in) / Zhang, Meigen (Autor:in) / Wu, Fangkun (Autor:in) / Sun, Yele (Autor:in) / Tang, Guiqian (Autor:in)
Atmospheric Environment ; 158 ; 105-115
21.03.2017
11 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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