环境空气PM_1自动监测与手工采样比对分析
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摘要
选取3种原理(β射线法,β射线+光散射融合法和振荡天平法)9种型号国产和进口PM_1自动监测仪器和4台手工监测设备开展PM_1自动监测和手工监测比对实验,并利用线性回归曲线和相对偏差方法分析和评价比对测试结果。结果表明:4台手工采样器的平行性满足参考标准要求;参与比对的9款自动监测仪器监测结果与手工采样监测结果的回归曲线的相关系数、斜率、截距均满足参考标准要求;国产和进口仪器以及不同原理自动监测仪器监测结果与手工监测结果回归曲线的相关系数、斜率和截距无明显差异。低PM_1质量浓度下自动监测结果和手工监测结果的相对偏差最大,实际应用中需重点关注低PM_1质量浓度时的监测数据质量。
Nine types of typical domestic and imported PM_1 automatic monitoring system with three different principles(β-ray method, β-ray+light scattering fusion method, oscillation balance method) and four manual monitoring equipments were selected to carry out the comparison experiment between PM_1 automatic monitoring method and manual monitoring method. Linear regression and relative deviation methods were used to analyze and evaluate the results. The results indicate that parallelism of four manual samplers meets reference standard requirements. The correlation coefficient, slope and intercept of the regression curves of the monitoring results of the nine automatic monitoring instruments and the monitoring results of manual sampling monitoring all meet the requirements of the reference standard. The correlation coefficient, slope and intercept of regression curves between the results of domestic and imported instruments and automatic monitoring instruments of different principles and the results of manual monitoring showed no significant difference. The relative deviation between the automatic monitoring results and the manual monitoring results at the low PM_1 mass concentration is largest. In practical applications, it is necessary to focus on the quality of monitoring data at low PM_1 mass concentrations.
Nine types of typical domestic and imported PM_1 automatic monitoring system with three different principles(β-ray method, β-ray+light scattering fusion method, oscillation balance method) and four manual monitoring equipments were selected to carry out the comparison experiment between PM_1 automatic monitoring method and manual monitoring method. Linear regression and relative deviation methods were used to analyze and evaluate the results. The results indicate that parallelism of four manual samplers meets reference standard requirements. The correlation coefficient, slope and intercept of the regression curves of the monitoring results of the nine automatic monitoring instruments and the monitoring results of manual sampling monitoring all meet the requirements of the reference standard. The correlation coefficient, slope and intercept of regression curves between the results of domestic and imported instruments and automatic monitoring instruments of different principles and the results of manual monitoring showed no significant difference. The relative deviation between the automatic monitoring results and the manual monitoring results at the low PM_1 mass concentration is largest. In practical applications, it is necessary to focus on the quality of monitoring data at low PM_1 mass concentrations.
引文
[1] 江琪,孙业乐,王自发,等.应用颗粒物化学组分监测仪(ACSM)实时在线测定致霾细粒子无机和有机组分[J].科学通报,2013,58(36):3818-3828.
[2] 江琪,王飞,孙业乐.河北香河亚微米气溶胶组分特性、来源及其演变规律分析[J].环境科学,2018,39(7):3022-3032.
[3] 刘瑜存,朱雯斐,王毓旻,等.基于高质量分辨率质谱仪研究上海城区秋季大气亚微米级颗粒物化学特性[J].环境科学学报,2018,38(7):2746-2756.
[4] 黄丽坤,王薇,王琨,等.哈尔滨市采暖期PM1中金属元素的污染特征[J].黑龙江大学自然科学学报,2016,33(6):808-812.
[5] Zanobeiti A,Franklin M,Koutrais P,et al.Fine particulate air pollution and its components in association with cause-specific emergency admissions[J].Environ Health,2008,19(6):315-316.
[6] Seinfeld,J H,Pandis S N.Atmospheric chemistry and physics:from air pollution to climate change.John Wiley&Sons:2012.Chapter 15:Interaction of Aerosols with Radiation.
[7] 赵辰航.上海地区光化学烟雾特征及分级标准研究[D].上海:东华大学.
[8] 王强,钟琪,迟颖,等.环境空气PM2.5连续监测系统手工采样比对测试[J].环境科学,2015,36(5):1538-1543.
[9] 滕曼,姚雅伟,付强.京津冀地区环境空气PM2.5自动监测现场比对研究[J].环境工程学报,2015,9(1):331-334.
[10] 秦玮,周晓辉,陈正勇,等.国产PM2.5颗粒物自动在线监测仪性能比对研究[J].四川环境,2016,35(4):78-82.
[11] 潘本锋,郑皓皓,李莉娜,等.空气自动监测中 PM2.5 与 PM10“倒挂” 现象特征及原因[J].中国环境监测,2014,30(5):90-95.
[12] 郑翔翔,洪正昉,陈浩,等.PM2.5手工标准方法与自动监测法比对分析[J].环境污染与防治,2015,37(7):77-81.
[2] 江琪,王飞,孙业乐.河北香河亚微米气溶胶组分特性、来源及其演变规律分析[J].环境科学,2018,39(7):3022-3032.
[3] 刘瑜存,朱雯斐,王毓旻,等.基于高质量分辨率质谱仪研究上海城区秋季大气亚微米级颗粒物化学特性[J].环境科学学报,2018,38(7):2746-2756.
[4] 黄丽坤,王薇,王琨,等.哈尔滨市采暖期PM1中金属元素的污染特征[J].黑龙江大学自然科学学报,2016,33(6):808-812.
[5] Zanobeiti A,Franklin M,Koutrais P,et al.Fine particulate air pollution and its components in association with cause-specific emergency admissions[J].Environ Health,2008,19(6):315-316.
[6] Seinfeld,J H,Pandis S N.Atmospheric chemistry and physics:from air pollution to climate change.John Wiley&Sons:2012.Chapter 15:Interaction of Aerosols with Radiation.
[7] 赵辰航.上海地区光化学烟雾特征及分级标准研究[D].上海:东华大学.
[8] 王强,钟琪,迟颖,等.环境空气PM2.5连续监测系统手工采样比对测试[J].环境科学,2015,36(5):1538-1543.
[9] 滕曼,姚雅伟,付强.京津冀地区环境空气PM2.5自动监测现场比对研究[J].环境工程学报,2015,9(1):331-334.
[10] 秦玮,周晓辉,陈正勇,等.国产PM2.5颗粒物自动在线监测仪性能比对研究[J].四川环境,2016,35(4):78-82.
[11] 潘本锋,郑皓皓,李莉娜,等.空气自动监测中 PM2.5 与 PM10“倒挂” 现象特征及原因[J].中国环境监测,2014,30(5):90-95.
[12] 郑翔翔,洪正昉,陈浩,等.PM2.5手工标准方法与自动监测法比对分析[J].环境污染与防治,2015,37(7):77-81.