Methods development and data curation for industrial pollution generation and discharge accounting

ZHANG Yue; SUN Yuanyuan; QIAO Qi; ZHOU Xiaoyun; XU Wen; BAI Lu

doi:10.13205/j.hjgc.202508016

Volume 43 Issue 8

Aug. 2025

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Article Navigation > ENVIRONMENTAL ENGINEERING > 2025 > 43(8): 177-186

ZHANG Yue, SUN Yuanyuan, QIAO Qi, ZHOU Xiaoyun, XU Wen, BAI Lu. Methods development and data curation for industrial pollution generation and discharge accounting[J]. ENVIRONMENTAL ENGINEERING , 2025, 43(8): 177-186. doi: 10.13205/j.hjgc.202508016

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ZHANG Yue, SUN Yuanyuan, QIAO Qi, ZHOU Xiaoyun, XU Wen, BAI Lu. Methods development and data curation for industrial pollution generation and discharge accounting[J]. ENVIRONMENTAL ENGINEERING , 2025, 43(8): 177-186. doi: 10.13205/j.hjgc.202508016

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Methods development and data curation for industrial pollution generation and discharge accounting

doi: 10.13205/j.hjgc.202508016

Key Laboratory of Eco-Industry of Ministry of Ecology and Environment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China

Received Date: 2025-04-16
Accepted Date: 2025-08-19
Rev Recd Date: 2025-07-25

Abstract

Abstract

Data on the generation and discharge of industrial pollution serves as a critical foundation for industrial pollution prevention and control， environmental management， and scientific research. This study systematically analyzed industrial production and discharge patterns， classified industrial sectors into process-oriented industries （including petroleum refining， chemical production， and steel manufacturing， etc） and discrete industries （including encompassing automotive assembly， electronics manufacturing， and machinery production， etc）. An innovative concept， the minimum pollution-generating benchmark unit （MPGBU）， was proposed. A scientific classification methodology was established by dividing independent units according to process links in process-oriented industries， and by eliminating redundancy through extraction of common characteristic units in discrete industries. By deconstructing each MPGBU， six key influencing factors were identified： raw materials， products， production processes， production scale， types of pollutants， and treatment technologies. Based on these factors， an accounting model for pollutant emissions was developed. To facilitate the application of pollution generation and emission coefficients， a coding system was designed， and a digital management platform was created， enabling the digital management of over 100000 coefficients. In response to emerging needs in precise pollution control， the Dual Carbon Strategy， and the integration of big data and artificial intelligence， further research should be conducted on methods for precise pollution control with MPGBUs as the basic units. We should also explore pollution-carbon synergistic accounting techniques based on MPGBUs， and adopt new information technologies such as big data and artificial intelligence to support new approaches for updating pollution generation and emission coefficients.
- industrial pollution sources,
- pollutant generation and discharge coefficient,
- minimum pollution-generating benchmark unit,
- data curation

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References(35)

References

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