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Source Journal of Chinese Scientific and Technical Papers
Included as T2 Level in the High-Quality Science and Technology Journals in the Field of Environmental Science
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Volume 42 Issue 11
Nov.  2024
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Article Contents
LI Cheng, LU Binbin, YI Xinyuan, SHAO Xuehong, XU Bin, TANG Yulin. CARBON EMISSION CHARACTERISTICS AND INFLUENCING FACTORS OF TYPICAL WATER SUPPLY PLANTS IN SHANGHAI BASED ON MONTHLY DATA[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(11): 131-139. doi: 10.13205/j.hjgc.202411014
Citation: LI Cheng, LU Binbin, YI Xinyuan, SHAO Xuehong, XU Bin, TANG Yulin. CARBON EMISSION CHARACTERISTICS AND INFLUENCING FACTORS OF TYPICAL WATER SUPPLY PLANTS IN SHANGHAI BASED ON MONTHLY DATA[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(11): 131-139. doi: 10.13205/j.hjgc.202411014

CARBON EMISSION CHARACTERISTICS AND INFLUENCING FACTORS OF TYPICAL WATER SUPPLY PLANTS IN SHANGHAI BASED ON MONTHLY DATA

doi: 10.13205/j.hjgc.202411014
  • Received Date: 2024-07-15
    Available Online: 2025-01-16
  • This study conducted a systematic carbon accounting for a typical deep treatment waterworks in Shanghai based on monthly monitoring and operational data from 2020 to 2023, using the emission factor method, to reveal the composition and trend of carbon emissions in the waterworks. The results showed that the water intake and supply volume increased year by year from 2020 to 2023, and the total carbon emissions increased year by year, with an average annual total carbon emissions of 14,972.84 t CO2-eq, and a carbon emission intensity of 0.2240 kg CO2-eq/m3. From the perspective of compositions, the pumping stations, conventional treatment, and chemical use were the main sources of carbon emissions, accounting for 29.02%, 36.69%, and 17.40%, respectively. From the perspective of seasonal changing trend, the carbon emission intensity of electricity was relatively stable throughout the year, while the carbon emission intensity of chemicals showed significant seasonal fluctuations, with peak emission intensity mainly appearing in the first and third quarters. By conducting regression analysis and relative importance analysis on carbon emission intensity based on climate and water quality indicators, the regression model was found good in explaining the changes in electricity and coagulant carbon emission intensity, with the water intake being a significant factor of electricity carbon emission intensity, and coagulant carbon emission intensity being significantly affected by water intake and water temperature. Waterworks can formulate corresponding energy-saving and carbon reduction schemes based on the composition and monthly variation characteristics of key carbon emission nodes.
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