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Spatial character of the gaseous and particulate state compound correlation of urban atmospheric pollution in winter and summer
Authors:XU Xiangde  SHI Xiaohui  XIE Lian  DING Guoan  MIAO Qiuju  MA Jianzhong  ZHENG Xiangdong
Abstract:The spatial/temporal variation information of atmospheric dynamic-chemical processes at observation site points of the "canopy" boundary of Beijing urban building ensemble and over urban area "surface", as well as the seasonal correlation structure of the gaseous and particulate states of urban atmospheric pollution (UAP) and its seasonal conversion feature at observation points are investigated, using the comprehensive observation data of the Beijing City Air Pollution Observation Experiment (BECAPEX) in winter and summer 2003 with a "point-surface" combined research approach. By using "one dimension spatial empirical orthogonal function (EOF)" principal component analysis (PCA) mode, the seasonal change of gaseous and particulate states of atmospheric aerosols and the association feature of pollutant species under the background of the complicated structure of urban boundary layer (UBL) are analyzed. The comprehensive analyses of the principal components of particle concentrations,gaseous pollutant species, and meteorological conditions reveal the seasonal changes of the complex constituent and structure features of the gaseous and particulate states of UAP to further trace the impact feature of urban aerosol pollution surface sources and the seasonal difference of the component structure of UAP. Research results suggest that in the temporal evolution of the gaseous and particulate states of winter/summer UAP, NOx, CO, and SO2 showed an "in-phase" evolution feature, however, O3 showed an "inverse-phase" relation with other species,all possessing distinctive dependent feature. On the whole, summer concentrations of gaseous pollutants CO, SO2, and NOx were obviously lower than winter ones, especially, the reduction in CO concentration was most distinctive, and ones in SO2 and NOx were next. However, the summer O3 concentration was more than twice winter one. Winter/summer differences in PM10and PM2.5 particle concentrations were relatively not obvious, which indicates that responses of PM10 and PM2.5 particle concentrations to the difference of winter/summer heating period emission sources are far less distinctive than those of NOx, SO2, and CO. The correlation feature of winter/summer gaseous and particulate states depicts that both PM10 and PM2.5 particles were significantly correlated with NOx, and their correlations with NOx are more significant than those with other pollutants. Through PCA, it is found that there was a distinctive difference in the principal component combination structure of winter/summer PM10 and PM2.5 particles: SO2 and NOx dominated in the principal component of winter PM10 and PM2.5 particles; while CO and NOx played the major role in the principal component of summer PM10 and PM2.5 particles. For winter/summer PM10 and PM2.5 particles, there might exist the gaseous and particulate states correlation structures of different "combinations" of such dependent pollutant species. Research results also uncover that the interaction processes of gaseous and particulate states were also related with the vertical structure of UBL, that is to say, the low value layer of UBL O3 concentration was associated with the collocation of atmospheric vertical structures of the low level inversion,inverse humidity, and small wind, which depicts summer boundary layer atmospheric character, i.e.the compound impact of the dependent factor "combination" of wind, temperature, and humidity elements and their collocation structure on the variations of different gaseous pollutant concentrations. Such a depth structure of the extremely low value of O3 concentration in the UBL accords with its "inverse-phase" relation with other gaseous pollutant species. The PCA of meteorological factors associated with PM10 and PM2.5 concentrations also reveals the sensitivity of PM10 and PM2.5 concentration to the combinatory feature of local meteorological conditions.
Keywords:aerosol  correlation structure  principal component analysis
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