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GIS-based emission inventories of urban scale: A case study of Hangzhou, China
AbstractThis research established GIS-based urban-scale emission inventories of SO2, NOX, and PM10 from both fossil energy consumption and industrial production process. Hangzhou, a typical Yangtse Delta city in south China, was selected to be the case study city. It is found that PM10 emission from industrial production process is the third highest, about 17.1% of total PM10 emission. The total emissions of SO2, NOX, and PM10 were 41385.9, 54780.4, and 24239.2ta−1 in 2004. AERMOD model was used to simulate pollutants concentration in the urban area of Hangzhou. The simulated concentrations were compared with the observed data collected at seven air quality-monitoring stations. The results show that simulated data of SO2 and NOX annual average concentrations agreed reasonably with observation data in five monitoring stations, but had obvious differences with observation data in the other two monitoring stations because of boundary and geographical data limitation in the simulation. The simulated data of PM10 annual average concentrations were much lower than observation data of all monitoring stations because secondary PM10 data were not included in the simulation.
GIS-based emission inventories of urban scale: A case study of Hangzhou, China
AbstractThis research established GIS-based urban-scale emission inventories of SO2, NOX, and PM10 from both fossil energy consumption and industrial production process. Hangzhou, a typical Yangtse Delta city in south China, was selected to be the case study city. It is found that PM10 emission from industrial production process is the third highest, about 17.1% of total PM10 emission. The total emissions of SO2, NOX, and PM10 were 41385.9, 54780.4, and 24239.2ta−1 in 2004. AERMOD model was used to simulate pollutants concentration in the urban area of Hangzhou. The simulated concentrations were compared with the observed data collected at seven air quality-monitoring stations. The results show that simulated data of SO2 and NOX annual average concentrations agreed reasonably with observation data in five monitoring stations, but had obvious differences with observation data in the other two monitoring stations because of boundary and geographical data limitation in the simulation. The simulated data of PM10 annual average concentrations were much lower than observation data of all monitoring stations because secondary PM10 data were not included in the simulation.
GIS-based emission inventories of urban scale: A case study of Hangzhou, China
Zhang, Qingyu (author) / Wei, Yumei (author) / Tian, Weili (author) / Yang, Kemin (author)
Atmospheric Environment ; 42 ; 5150-5165
2008-02-04
16 pages
Article (Journal)
Electronic Resource
English
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