In order to adapt to the rapid development of online automatic monitoring technology, nonlinear least squares algorithm is applied to quantitative analysis of multi-component infrared spectral signals. The quantitative information of measured spectrum is obtained by fitting the standard spectrum and measured spectrum of aerosol inorganic ion composition. Results show that the nonlinear least squares algorithm has some advantages in quantitative analysis of multi-component infrared spectral signals, and the root mean square(RMS) of nitrate is 0.340%. The trend of aerosol inorganic ion concentration in Dongpu Island of Hefei, China is analyzed using the calculation results, and the temporal trends of sulfate and nitrate are obtained. It’s indicated that the nonlinear least squares method can be used for infrared spectroscopy quantitative analysis of the aerosol ion chemical composition concentration without real-time calibration.