Abstract: A models-3 community multi-scale air quality(CMAQ) modeling system is widely applied to air quality issues in recent years.Emission inventory is an important input data for the CMAQ model.A nonlinear optimizing system based on genetic algorithms(GAs),which includes four modules: emission inventory adjusting,population initializing,GAs,and CMAQ result analyzing,is developed under the Linux system for optimizing the emission inventory of the CMAQ model.The system is used to optimize the emission inventory of Beijing in typical days.The improved emission inventory is applied to simulate Beijing's PM₁₀ concentrations of January,April,July,and October in 2002.The mean relative errors between the monitoring and the simulation values are reduced by 2.6%,7.02%,14.07% and 2.17% separately.This indicates that the nonlinear optimizing system based on genetic algorithms is an effective method to improve the emission inventory for the CMAQ modeling system.