中文摘要：

硫酸盐和硝酸盐作为大气颗粒物可溶性组成的重要成分,对环境气候和人体健康有重要的影响,因此实现对其快速定量检测具有重要的科研意义。利用衰减全反射傅立叶变换红外光谱（FTIR-ATR）对硫酸盐及硝酸盐单组份水溶液进行了定量分析,线性关系良好,相关系数分别为0.9982、0.9997。利用正交实验设计配制了硫酸盐及硝酸盐的混合溶液,分别利用一元校正和基于偏最小二乘（PLS）模型算法的多元校正对硫酸盐和硝酸盐两组分进行了定量分析。结果表明SO_4~（2-）离子一元校正预测精度优于PLS预测精度,预测值平均相对误差为2.6%,NO_3~-离子基于PLS模型的预测精度优于一元校正,预测值平均相对误差为2.31%。这种方法快速、简便,为同时定量分析气溶胶未知液中硫酸盐和硝酸盐的含量建立了基础。

英文摘要：

Sulfate and nitrate as important components of atmospheric particulates water-soluble components have important effects on climate and human health, thus realization of the fast quantitative detection has important scientific significance. The one-component aqueous solution of sulfate and nitrate were analyzed by attenuated total reflection Fourier transform infrared spectrum （FTIR/ATR）. The result shows that the linear relation is good and the correlation coefficients are 0.9982 and 0.9997, respectively. The mixture of sulfate and nitrate was prepared using the orthogonal experiment design, the quantitative analyses of sulfate and nitrate were carried out by one-dimensional linear regression and multivariate calibration based on partial least squares（PLS） model respectively. The result shows that the prediction accuracy of sulfate by one-dimensional linear regression is better than the prediction accuracy of sulfate by multivariate calibration and the average relative error of predictive value is 2.6%, the prediction accuracy of nitrate by multivariate calibration is better than the prediction accuracy of sulfate by one-dimensional linear regression and the average relative error of predictive value is 2.31%. The method is rapid and simple and it is the foundation of the quantitative analysis of sulfate and nitrate in aerosol aqueous solution at the same time