Identification of VOC emission hotspots in industrial parks by high-spatiotemporal-resolution sensor networks

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

doi:10.1016/j.envint.2025.109628

Identification of VOC emission hotspots in industrial parks by high-spatiotemporal-resolution sensor networks

Environ Int. 2025 Jun 21:202:109628. doi: 10.1016/j.envint.2025.109628. Online ahead of print.

Authors

Xiaocan Bai¹, Yuhan Huang¹, Yanhui Wang¹, Ziyi Wang², Xue Li³, Ruixue Du³, Manyun Long², Huawei Zhang¹, Yan Tan¹, Ting Liu¹, Chun Chen⁴, Xianhui Fan⁵, Yanru Xu⁵, Jinping Cheng², Shengao Jing⁶, Zizhen Ma⁷, Zehui Li⁸, Jingkun Jiang⁹

Affiliations

¹ School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, PR China.
² State Key Laboratory of Green Papermaking and Resource Recycling, School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China.
³ School of Environment, Henan Normal University, Xinxiang 453007, PR China.
⁴ Center of Ecological Environment Monitoring and Safety of Henan Province, Zhengzhou 450046, PR China.
⁵ TC Air Technology Limited Company, Beijing 100084, PR China.
⁶ State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, PR China.
⁷ School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, PR China. Electronic address: mazizhen@qut.edu.cn.
⁸ 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. Electronic address: zehuili@sjtu.edu.cn.
⁹ State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, PR China.

PMID: 40580706
DOI: 10.1016/j.envint.2025.109628

Abstract

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.

Keywords: High spatiotemporal resolution; Industrial park; Sensor network; Source identification; VOCs.