光散射法测定室外空气PM2.5质量浓度校正模型研究
A Study of Calibration Model for Light Scattering Method in Monitoring Outdoor PM2.5 Concentrations
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摘要:目的 比较光散射方法与滤膜称重法测定室外空气细颗粒物(PM2.5)质量浓度的一致性, 探讨影响光散射方法测定结果准确性的因素, 构建校正模型。方法 采用光散射法和滤膜称重法同时测定住宅室外PM2.5浓度, 通过计算相对偏差、相关系数等指标分析两种方法测定结果的一致性; 以重量法和光散散射法测定结果比值(校正系数)为因变量, 分别采用多元线性回归(multiple linear regression, MLR)和随机森林(random forest, RF)算法构建校正模型, 采用十折交叉验证法评价模型的性能。结果 共获得138组有效数据, 其中光散射法测定结果与重量法间存在显著正相关关系(rs=0.932, P < 0.001), 但存在系统偏差, 其测定结果显著高于重量法(P < 0.001);以环境湿度、温度和光散射法响应值为预测变量的两类模型均可以提高光散法的准确性, 且RF模型具有更好的校正效果, 经其校准后两种测定方法结果间相关系数提高至0.957, 均方根误差(root mean square error, RMSE)由13.5 μg/m3下降至7.3 μg/m3, 平均绝对偏差(mean absolute deviation, MAE)由10.8 μg/m3下降至5.4 μg/m3。结论 光散射法与重量法测定结果具有良好的相关性, 但存在系统偏差; 基于MLR或RF模型可以对结果进行有效的校准, 且RF模型的校准效果优于MLR。Abstract:Objective To compare the consistency between light scattering and gravimetric method in the determination of outdoor fine particulate matter (PM2.5), and to develop calibration models with influencing factors.Methods Light scattering and gravimetric methods were used to monitor the outdoor PM2.5 concentrations simultaneously. The consistency of the results from the two methods was analyzed by calculating the relative deviation, correlation coefficient and other indicators. The ratio of the concentrations determined by the gravimetric method and the light scattering method (correction coefficient) was used as the dependent variable, and multiple linear regression (MLR) as well as random forest (RF) were used to develop calibration models for light scattering method. The performance of the models was evaluated by 10-fold cross validation method.Results A total of 138 sets of valid data were obtained. There was a significant positive correlation between the results of light scattering method and gravimetric method (Spearman r = 0.932, P < 0.001), but there was a systematic deviation that the values from scatting light method were significantly higher than that of the gravimetric method (P < 0.001). After calibration by MLR or random RF model with environmental humidity, temperature and light scattering response value as prediction variables, the accuracy of light scattering method was effectively improved, and RF model performed better than MLR model. After calibration using RF model, the correlation coefficient between the results of the two methods increased from 0.932 to 0.957, and the root mean square error (RMSE) decreased from 13.5 μg/m3 to 7.3 μg/m3, while the mean absolute deviation (MAE) decreased from 10.8 μg/m3 to 5.4 μg/m3.Conclusion There was a good correlation between the results of light scattering method and gravimetric method, but systematic deviation existed. The results from light scattering method can be effectively calibrated using MLR or RF model, and the later model performed better.
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