| VOCs在线监测设备数据识别能力的评估方法及应用 |
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| 引用本文： | 张涛, 王新明, 周炎, 裴成磊, 陈多宏, 区宇波, 陈春贻. VOCs在线监测设备数据识别能力的评估方法及应用[J]. 环境工程学报, 2021, 15(1): 298-306. doi: 10.12030/j.cjee.202003023 |
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| 作者姓名： | 张涛 王新明 周炎 裴成磊 陈多宏 区宇波 陈春贻 |
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| 作者单位： | 1.中国科学院广州地球化学研究所，有机地球化学国家重点实验室，广州 510640; 2.中国科学院大学，北京 100049; 3.广东省环境监测中心，国家环境保护区域空气质量监测重点实验室，广州 510308; 4.广州市环境监测中心站，广州 510006 |
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| 基金项目： | 国家重点研发计划;国家自然科学基金;广州市珠江科技新星项目 |
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| 摘 要： | 为评估VOCs在线监测设备原始监测数据的准确性，建立了一种VOCs在线监测设备数据识别能力的评估方法。结果表明：8种VOCs在线监测设备在数据识别方面的表现存在一定的差异，原始数据与人工审核数据的平均相对偏差为−100%~56 652%；相较于高碳物种，低碳物种的原始数据与人工审核数据平均相对偏差更大；根据应用案例分析提出“数据识别指数”，对不同VOCs在线监测设备的数据识别能力进行定量区分。该方法可为今后VOCs在线监测设备评估工作提供一种全新的考核指标，还可以科学评判其他在线监测设备的快速分析应用能力。
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| 关 键 词： | 挥发性有机物 在线监测 评估方法 数据识别能力 指数 |
| 收稿时间： | 2020-03-04 |
Evaluation method and application of data recognition capability of VOCs online monitoring equipment |
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| ZHANG Tao, WANG Xinming, ZHOU Yan, PEI Chenglei, CHEN Duohong, OU Yubo, CHEN Chunyi. Evaluation method and application of data recognition capability of VOCs online monitoring equipment[J]. Chinese Journal of Environmental Engineering, 2021, 15(1): 298-306. doi: 10.12030/j.cjee.202003023 |
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| Authors: | ZHANG Tao WANG Xinming ZHOU Yan PEI Chenglei CHEN Duohong OU Yubo CHEN Chunyi |
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| Affiliation: | 1.State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; 2.University of Chinese Academy of Sciences, Beijing 100049, China; 3.State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Monitoring Center, Guangzhou 510308, China; 4.Guangzhou Environmental Monitoring Center, Guangzhou 510006, China |
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| Abstract: | In order to evaluate the accuracy of the original data of VOCs online monitoring equipments, an evaluation method for data recognition capability of VOCs online monitoring equipments was established. The results showed that there were some differences in the performance of the eight VOCs online monitoring equipments in data recognition capability, and the average relative deviation between original data and manual audit data ranged from −100% to 56 652%. Compared with high-carbon species, a greater mean relative deviation between the original data and the manual audit data occurred for low-carbon species. According to the application case analysis, the data recognition index (DRI) proposed in this study could quantitatively distinguish the data recognition capability of different VOCs online monitoring equipments. This method not only provided a new assessment index for the evaluation of VOCs online monitoring equipments in the future, but also could make a scientific evaluation for the rapid analysis and application capability of other online monitoring equipments. |
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| Keywords: | volatile organic compounds online monitoring evaluation method data recognition capability index |
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