| Abstrakt: |
The simulation deviation of Gf(RH) parameterization scheme with RH as the univariate variable was analyzed on the basis of hourly observational data of Chengdu City by means of nephelometer, aethalometer and GRIMM180 ambient particles monitor during the period of October-December, 2017, and the simultaneous data of atmospheric visibility (V), relative humidity (RH) and nitrogen dioxide (NO2), aerosol particle size hygroscopic growth factor (Gf) retrieved by an immune evolutionary algorithm; moreover, the response of Gf to multifactor variation was systematically explored by the generalized additive model (GAM). Accordingly, the results suggested the Gf(RH) parameterization scheme could well simulate the variation feature of Gf in case of low RH (when RH<85%), while under the high relative humidity condition (RH>85%), the fitted values would considerably deviate from observed ones. The explanatory variables of RH, CBC, CBC / CPM1, CPM1/CPM2.5 and CPM2.5/CPM10 were proposed by using the combination of multivariate recursion and VIF method, among them RH and CBC exerted considerable effects on Gf, the adjusted coefficients of determination (R2) in the corresponding univariate GAM model being 0.78 and 0.17, respectively; while CBC/CPM1, CPM1/CPM2.5 and CPM2.5/CPM10 had relatively small effects on Gf, the adjusted coefficients of determination (R2) in the corresponding univariate GAM model were 0.08, 0.12 and 0.03, respectively; and the GAM model with RH, CBC, CBC/CPM1, CPM1/CPM2.5 and CPM2.5/CPM10 as independent variables was constructed for the multi-factorial effects of Gf, and correspondingly, the adjustment determination coefficient (R2) and the determination coefficient of reduced major axis regression were respectively 0.868 and 0.872, thus cutting down the fitting deviation under high relative humidity conditions (RH>85%), and significantly enhancing the simulation effect of aerosol particle size hygroscopic growth factor under smog weather condition. [ABSTRACT FROM AUTHOR] |
