成都地区气溶胶散射吸湿增长因子双变量模型

基于成都市2017年10～12月逐时的“干”气溶胶散射系数和吸收系数观测数据，结合该时段同时次的能见度（V）、相对湿度（RH）以及二氧化氮（NO₂）监测资料，利用“光学综合法”计算气溶胶散射吸湿增长因子，并探究了气溶胶散射吸湿增长因子单变量f（RH）模型的适用性及其改进方案.结果表明：幂函数、二次多项式、幂指函数形式的f（RH）模型在低RH条件下（RH<85%）均能很好地模拟气溶胶散射吸湿增长因子随RH的变化特征，但在高RH条件下（RH>85%）的模拟值会出现较大的偏差.黑碳质量浓度（C_BC）是影响气溶胶散射吸湿增长因子的另一关键变量，二者之间满足非线性关系.以RH和C_BC为自变量构建了气溶胶散射吸湿增长因子双变量f（RH，C_BC）模型，模型计算值和实测值之间的决定系数R²为0.763，平均相对误差MRE为14.28%.双变量模型f（RH，C_BC）的应用显著改善了气溶胶散射消光系数的模拟效果.

Bivariate model of aerosol scattering hygroscopic growth factor in Chengdu

Based on the hourly observational data of “dry” aerosol scattering coefficient and “dry” aerosol absorption coefficient, as well as the simultaneous data of visibility (V), relative humidity (RH) and nitrogen dioxide (NO₂) from October to December 2017 in Chengdu, aerosol scattering hygroscopic growth factor was calculated by optical synthesis method, and then the applicability of univariate f(RH) model of aerosol scattering hygroscopic growth factor and its improved scheme were further investigated. The results showed that: All three f(RH) models in the form of power function, quadratic polynomial and power index function could well simulate the variation of aerosol scattering hygroscopic growth factor with RH at RH<85%, while for RH>85%, the simulated values would greatly deviate from observed ones. Black carbon mass concentration (C_BC) was another key variable affecting aerosol scattering hygroscopic growth factor, and there existed nonlinear relationship between the two factors. A bivariate f(RH,C_BC) model of aerosol scattering hydroscopic growth factor was proposed, and corresponding determination coefficient(R²) and the average relative error(MRE) were 0.763 and 14.28% respectively. Further application of the bivariate f(RH,C_BC) model indicated that the simulation accuracy of aerosol scattering extinction coefficient was significantly enhanced.