Identification of VOC emission hotspots in industrial parks by high-spatiotemporal-resolution sensor networks
Industrial emissions are a significant contributor to volatile organic compound (VOC) pollution. However, timely and accurate tracking of high-emitting plants within industrial parks remains a challenge. Here, we deployed three high-density VOC sensor networks across a package printing industrial pa...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-08-01
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| Series: | Environment International |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0160412025003794 |
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| author | Xiaocan Bai Yuhan Huang Yanhui Wang Ziyi Wang Xue Li Ruixue Du Manyun Long Huawei Zhang Yan Tan Ting Liu Chun Chen Xianhui Fan Yanru Xu Jinping Cheng Shengao Jing Zizhen Ma Zehui Li Jingkun Jiang |
| author_facet | Xiaocan Bai Yuhan Huang Yanhui Wang Ziyi Wang Xue Li Ruixue Du Manyun Long Huawei Zhang Yan Tan Ting Liu Chun Chen Xianhui Fan Yanru Xu Jinping Cheng Shengao Jing Zizhen Ma Zehui Li Jingkun Jiang |
| author_sort | Xiaocan Bai |
| collection | DOAJ |
| description | Industrial emissions are a significant contributor to volatile organic compound (VOC) pollution. However, timely and accurate tracking of high-emitting plants within industrial parks remains a challenge. Here, we deployed three high-density VOC sensor networks across a package printing industrial park (103 sites/km2), a fine chemical industrial park (8.57 sites/km2), and an urban area in central China. These networks enabled the identification of VOC pollution characteristics and sources in regions. The hourly average VOC concentrations in the package printing industrial park (320 ± 262 ppb) and the fine chemical industrial park (155 ± 62 ppb) were 1.62 to 2.75 times and 1.27 to 1.70 times higher compared to the urban area. Pollution levels in these two industrial parks were more severe than other reported industrial parks, primarily due to the higher VOC emission factors or higher VOC emission fluxes associated with these industries. Importantly, by integrating VOC concentration contour maps with meteorological data, major polluting plants in the package printing industrial park and the fine chemical industrial park were identified. These were further validated through downwind tracing of VOC species using gas chromatography-mass spectrometry. The results highlight that a VOC sensor network is an effective tool for real-time monitoring of VOC variations and the precise identification of high-pollution plants across various industrial parks, which can provide valuable insights for the refined control and management of VOC pollution emissions. |
| format | Article |
| id | doaj-art-adf8860edb5e45c5a79e2db2af3d6a0e |
| institution | Kabale University |
| issn | 0160-4120 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Environment International |
| spelling | doaj-art-adf8860edb5e45c5a79e2db2af3d6a0e2025-08-20T03:32:47ZengElsevierEnvironment International0160-41202025-08-0120210962810.1016/j.envint.2025.109628Identification of VOC emission hotspots in industrial parks by high-spatiotemporal-resolution sensor networksXiaocan Bai0Yuhan Huang1Yanhui Wang2Ziyi Wang3Xue Li4Ruixue Du5Manyun Long6Huawei Zhang7Yan Tan8Ting Liu9Chun Chen10Xianhui Fan11Yanru Xu12Jinping Cheng13Shengao Jing14Zizhen Ma15Zehui Li16Jingkun Jiang17School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, PR ChinaSchool of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, PR ChinaSchool of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, PR ChinaState Key Laboratory of Green Papermaking and Resource Recycling, School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR ChinaSchool of Environment, Henan Normal University, Xinxiang 453007, PR ChinaSchool of Environment, Henan Normal University, Xinxiang 453007, PR ChinaState Key Laboratory of Green Papermaking and Resource Recycling, School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR ChinaSchool of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, PR ChinaSchool of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, PR ChinaSchool of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, PR ChinaCenter of Ecological Environment Monitoring and Safety of Henan Province, Zhengzhou 450046, PR ChinaTC Air Technology Limited Company, Beijing 100084, PR ChinaTC Air Technology Limited Company, Beijing 100084, PR ChinaState Key Laboratory of Green Papermaking and Resource Recycling, School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR ChinaState Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, PR ChinaSchool of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, PR China; Corresponding authors at: School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, PR China (Z. Ma); State Key Laboratory of Green Papermaking and Resource Recycling, School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China (Z. Li).State Key Laboratory of Green Papermaking and Resource Recycling, School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China; State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, PR China; Corresponding authors at: School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, PR China (Z. Ma); State Key Laboratory of Green Papermaking and Resource Recycling, School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China (Z. Li).State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, PR ChinaIndustrial emissions are a significant contributor to volatile organic compound (VOC) pollution. However, timely and accurate tracking of high-emitting plants within industrial parks remains a challenge. Here, we deployed three high-density VOC sensor networks across a package printing industrial park (103 sites/km2), a fine chemical industrial park (8.57 sites/km2), and an urban area in central China. These networks enabled the identification of VOC pollution characteristics and sources in regions. The hourly average VOC concentrations in the package printing industrial park (320 ± 262 ppb) and the fine chemical industrial park (155 ± 62 ppb) were 1.62 to 2.75 times and 1.27 to 1.70 times higher compared to the urban area. Pollution levels in these two industrial parks were more severe than other reported industrial parks, primarily due to the higher VOC emission factors or higher VOC emission fluxes associated with these industries. Importantly, by integrating VOC concentration contour maps with meteorological data, major polluting plants in the package printing industrial park and the fine chemical industrial park were identified. These were further validated through downwind tracing of VOC species using gas chromatography-mass spectrometry. The results highlight that a VOC sensor network is an effective tool for real-time monitoring of VOC variations and the precise identification of high-pollution plants across various industrial parks, which can provide valuable insights for the refined control and management of VOC pollution emissions.http://www.sciencedirect.com/science/article/pii/S0160412025003794VOCsSensor networkHigh spatiotemporal resolutionIndustrial parkSource identification |
| spellingShingle | Xiaocan Bai Yuhan Huang Yanhui Wang Ziyi Wang Xue Li Ruixue Du Manyun Long Huawei Zhang Yan Tan Ting Liu Chun Chen Xianhui Fan Yanru Xu Jinping Cheng Shengao Jing Zizhen Ma Zehui Li Jingkun Jiang Identification of VOC emission hotspots in industrial parks by high-spatiotemporal-resolution sensor networks Environment International VOCs Sensor network High spatiotemporal resolution Industrial park Source identification |
| title | Identification of VOC emission hotspots in industrial parks by high-spatiotemporal-resolution sensor networks |
| title_full | Identification of VOC emission hotspots in industrial parks by high-spatiotemporal-resolution sensor networks |
| title_fullStr | Identification of VOC emission hotspots in industrial parks by high-spatiotemporal-resolution sensor networks |
| title_full_unstemmed | Identification of VOC emission hotspots in industrial parks by high-spatiotemporal-resolution sensor networks |
| title_short | Identification of VOC emission hotspots in industrial parks by high-spatiotemporal-resolution sensor networks |
| title_sort | identification of voc emission hotspots in industrial parks by high spatiotemporal resolution sensor networks |
| topic | VOCs Sensor network High spatiotemporal resolution Industrial park Source identification |
| url | http://www.sciencedirect.com/science/article/pii/S0160412025003794 |
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