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Huan Jing Ke Xue ; 37(3): 825-33, 2016 Mar 15.
Artículo en Zh | MEDLINE | ID: mdl-27337872

RESUMEN

To analyze the characteristics and formation mechanism of a heavy air pollution episode in Shanghai City from January 23th to January 24th, 2013, the observed data of PM2.5 concentration and ground meteorological data and the WRF-Chem model were collected. The analysis revealed that the synoptic necessary mechanism of the heavy air pollution episode could be characterized by the following patterns: Accompanied with weak cold front activities, the city experienced weak winds (i. e. stable atmosphere) at first and then northerly winds (i. e. pollutant transport process ), causing the continuous increase and maintaining of pollutant concentration. The detailed results are shown as follows: Firstly, the stable atmosphere circulation pattern which lasted for 10 hours was not good for air pollution dispersion, as a result, local PM2.5 concentrations continued to increase and reached severe pollution level and the high concentrations maintained for 7 hours caused by the stable boundary layer (e. g. static surface winds and low level temperature inversion) during nighttime, and the average PM2.5 concentrations during the stable weather process was 172.4 µg · m⁻³. Secondly, the dispersion condition was slightly improved later on with the arrival of a weak cold front, the upstream pollution transportation occurred at the same time, leading to further increase of PM2.5 concentration (up to 280 µg · m⁻³), and the average PM2.5 concentration during the upstream transportation process was 213.6 µg · m⁻³. Numerical simulation with the WRF-Chem model showed that, average contribution of upstream transportation to local PM2.5 concentrations during the episode was 23% . Among them, the contribution during the stable weather and upstream transportation stage was 17.2% and 32.2% . Our results suggested that there were significant differences in the contribution of upstream transportation to the local PM2.5 concentration of Shanghai due to variation of weather conditions. Therefore, the government can design effective emission control strategy in advance taking pollution weather forecasting into account.


Asunto(s)
Contaminantes Atmosféricos/análisis , Monitoreo del Ambiente , Atmósfera , China , Ciudades , Modelos Teóricos , Tamaño de la Partícula , Material Particulado/análisis , Tiempo (Meteorología) , Viento
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