工业园区VOCs光离子化气体检测技术适用性研究

蔡云飞; 段玉森; 党亚婷; 陈斐; 伏晴艳; 徐薇; 林长青; 高松

doi:10.13198/j.issn.1001-6929.2023.07.15

工业园区VOCs光离子化气体检测技术适用性研究

doi: 10.13198/j.issn.1001-6929.2023.07.15

蔡云飞^1,,
段玉森¹,
党亚婷²,
陈斐³,
伏晴艳¹,
徐薇⁴,
林长青¹,
高松^5, ,

1.
上海市环境监测中心，上海　200235
2.
北京雪迪龙科技股份有限公司，北京　102206
3.
东方国际集团上海环境科技有限公司，上海　200082
4.
上海建科环境技术有限公司，上海　201108
5.
上海大学环境与化学工程学院，上海　200444

基金项目: 上海市科技创新行动计划项目(No.20dz1204000)

详细信息

作者简介:
蔡云飞（1980-），男，上海人，高级工程师，主要从事环境监测与传感器研究，caiyf@sheemc.cn

通讯作者:
高松（1978-），男，江苏启东人，高级工程师，博士，主要从事环境监测与人工智能研究，njulegao@163.com

中图分类号: X815
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- 被引次数: 0
出版历程
- 收稿日期: 2023-05-11
- 修回日期: 2023-06-18
- 网络出版日期: 2023-07-14

Study on the Applicability of Photoionization Detection Technology for VOCs Monitoring in Industrial Areas

1.
Shanghai Environmental Monitoring Center, Shanghai 200235, China
2.
Beijing SDL Technology Co., Ltd., Beijing 102206, China
3.
Orient International Holding Shanghai Environmental Technology Co., Ltd., Shanghai 200082, China
4.
Shanghai Jianke Environmental Technology Co., Ltd., Shanghai 201108, China
5.
Shanghai University School of Environmental and Chemical Engineering, Shanghai 200444, China

Funds: Shanghai Science and Technology Innovation Action Plan, China (No.20dz1204000)

摘要

摘要: 目前在使用光离子化气体检测器(PID)设备对工业园区挥发性有机物(VOCs)进行监测过程中，设备间监测数据普遍存在偏差大、准确度和稳定性不足等问题，影响了园区VOCs的监测评价与管控. 为探究偏差产生的原因，本文选取了市售4个品牌的8套PID监测设备，在工业园区进行实地测试，对其适用性进行研究. 结果表明：① 在安装了除湿装置后，PID设备在高湿阶段监测正常，同时通过在现场对不同湿度标准气体的测试可知，除湿装置对测试数据的准确性无影响. 因此，在高湿度地区采用除湿装置，可提高PID设备监测数据的准确性. ② 环境空气实测时，虽然与气相色谱仪/氢火焰离子化检测器(GC-FID)设备原理不同，但经过一系列改进措施后，8台PID设备测得总VOCs体积分数变化趋势与GC-FID设备基本一致；同时，同品牌设备间平行性较好，各PID设备与GC-FID设备所测结果的相关系数均在0.82以上，最高可达0.96，但在GC-FID设备监测的VOCs体积分数<50×10⁻⁹时，二者相关性不理想. ③ 针对工业园区VOCs监测，本研究提出了将PID设备和GC-FID设备监测数据的比对计算方法，与将PID设备和GC-FID设备的监测数据经过简单求和后进行比对的方法相比，前者的相关性优于后者. 研究显示，可通过规定PID设备在工业园区进行报警的浓度，明确与常用设备比对的内容以及增加冷凝装置等方式来提高PID设备的监测准确性，从而提升工业园区O₃前体物的管控效果.
- PID /
- 监测 /
- 挥发性有机物(VOCs)
Abstract: During the grid monitoring of volatile organic compounds (VOCs) in industrial parks using low-cost PID equipment, the monitoring data deviation between equipment is large, resulting in insufficient accuracy and stability. This is a common problem affecting the evaluation and control of VOCs in the parks. To investigate the cause of this deviation, eight sets of PID monitoring equipment of four different brands were selected for field testing in an industrial park to study their applicability. The results showed that: (1) After installing a dehumidifier, the PID monitoring equipment worked normally in high humidity stages. Moreover, the field test of standard gases with different humidity showed that the dehumidifier had no effect on the accuracy of the test data. Therefore, using a dehumidifier can improve the accuracy of PID monitoring data in high-humidity areas. (2) During environmental air testing, the total VOC concentration measured by the eight PID equipment showed a similar trend to that measured by GC-FID equipment. The correlation coefficients between each PID equipment and the FID equipment were all above 0.82, with the highest correlation coefficient reaching 0.96. However, the correlation between the two pieces of equipment was not ideal in the low-concentration stage (50×10⁻⁹) of GC-FID equipment, indicating that PID equipment is suitable for rapid alarm detection with concentrations above 50×10⁻⁹. (3) For the monitoring of VOCs in industrial parks, this study proposes the method of comparing the monitoring data from PID equipment and GC-FID equipment after corresponding calculation, and the correlation of the former method is better than that of the latter method, compared with the method of comparing the monitoring data from PID equipment and GC-FID equipment after simple summation. (4) The research shows that the accuracy of PID monitoring can be improved by specifying the concentration of PID devices to trigger alarms in industrial parks, clarifying the comparison with commonly used devices, and adding condensation devices. This helps to determine the application positioning of PID devices in the industrial park and lay the foundation for managing O₃ precursor substances in industrial parks.
- PID /
- monitoring /
- volatile organic compounds (VOCs)

HTML全文

图 1 PID设备干湿标准气体测试结果

Figure 1. Dry and wet standard gas test results of PID equipment

下载: 全尺寸图片幻灯片

图 2 设备A与设备S数据之间平行性分析

Figure 2. Parallelism between equipment A and equipment S

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图 3 GC-FID设备与PID设备结果的玫瑰风向图

Figure 3. Rose wind diagram for GC-FID equipment and PID equipment

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图 4 报警时段PID设备和GC-FID设备所测结果的分布趋势

Figure 4. Trend of PID equipment and GC-FID equipment concentrations during alarms

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表 1 设备测试期间的性能评估结果

Table 1. Performance evaluation results of the equipment during the comparison period

设备名称	有效数据量	体积分数平均值/10⁻⁹	相关系数(与GC-FID设备所测数据)	斜率	截距	均方根误差/10⁻⁹	标准偏差/10⁻⁹
GC-FID	915	23.4±36.4
Y-2	858	50.4±34.7	0.87	0.94	−22.9	30.9	38.0
Z-1	915	74.3±5.7	0.96	6.07	−427.8	59.6	36.4
A-1	915	28.2±38.5	0.90	0.82	−3.3	19.4	38.5
A-2	915	28.2±38.5	0.89	0.84	−0.2	18.7	37.5
A-3	915	33.5±40.2	0.92	0.83	−4.5	18.7	38.7
S-1	915	22.5±19.0	0.82	1.58	−12.1	23.3	29.0
S-2	915	24.4±19.2	0.83	1.58	−15.2	22.9	29.1
S-3	915	20.7±18.8	0.84	1.63	−10.3	23.1	29.0

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表 2 设备比对期间GC-FID所测体积分数小于50×10⁻⁹时的性能评价结果

Table 2. Performance evaluation results of the equipments when GC-FID monitoring data smaller than 50×10⁻⁹ during the comparison period

设备名称	有效数据量	体积分数平均值/10⁻⁹	相关系数(与GC-FID设备数据)	斜率	截距	均方根误差/10⁻⁹	标准偏差/10⁻⁹
GC-FID	811	13.5±11.6
Y-2	754	41.1±17.5	0.72	0.48	−6.0	28.8	20.2
Z-1	811	72.8±1.9	0.83	4.93	−345.2	60.2	30.8
A-1	811	18.6±15.3	0.78	0.54	1.5	13.8	15.1
A-2	811	18.6±15.3	0.68	0.51	3.9	12.4	13.8
A-3	811	23.0±17.4	0.79	0.53	1.3	14.3	15.5
S-1	811	18.0±11.1	0.44	0.46	5.2	12.8	11.6
S-2	811	19.8±11.2	0.46	0.48	3.9	13.4	11.8
S-3	811	16.2±10.7	0.46	0.50	5.3	11.9	11.2

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表 3 报警时段内PID设备与GC-FID设备数据比较

Table 3. Comparison of PID equipment and GC-FID equipment during the alarm period

时段	GC-FID设备所测体积分数/10⁻⁹	A-3设备所测体积分数/10⁻⁹	A-3设备整小时体积分数/10⁻⁹	A-3设备体积分数最大值出现时刻	A-3设备体积分数最大值/10⁻⁹
12月15日03:00—03:59	69.2	71.2	70.8	03:00	105.0
12月15日04:00—04:59	74.3	110.8	103.9	04:21	132.0
12月15日05:00—05:59	162.2	142.2	136.6	05:33	169.5
12月15日06:00—06:59	139.6	152.2	162.9	06:10	227.0
12月15日07:00—07:59	201.0	242.6	226.8	07:55	303.5
12月15日08:00—08:59	72.5	77.6	122.4	08:00	275.0
12月15日09:00—09:59	36.3	37.4	59.7	09:00	337.0

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