Effects of Background Database Selection on Carbon Footprint and Mitigation Hotspot Identification in Wastewater Treatment: A Comparative Study of Ecoinvent and CLCD

Life cycle assessment (LCA) is an important tool for carbon footprint accounting in wastewater treatment, and its reliable application is essential for supporting low-carbon operation and environmentally sustainable management. However, LCA results are highly dependent on background database selection, while empirical evidence on its influence remains limited. This study evaluated two full-scale municipal wastewater treatment plants (WWTPs) in Shenzhen, China, using actual operational data, with the system boundary limited to the operational stage. Carbon footprints calculated using Ecoinvent v3.10 and CLCD v0.9 were compared, and sensitivity analysis and metadata comparison were conducted to identify database-related differences. Ecoinvent produced carbon footprints 4.53% and 9.04% higher than CLCD for WWTP A and WWTP B, respectively. Database selection also altered treatment-stage and emission-source contribution profiles, thereby affecting mitigation hotspot identification. Biological treatment remained dominant at both plants, whereas the contributions of sludge and advanced treatment varied substantially between databases. Under CLCD, electricity consumption, direct emissions, and sludge incineration contributed relatively more, while chemical consumption was more prominent under Ecoinvent. Sensitivity analysis identified electricity consumption and direct N2O emissions as robust key factors, whereas sludge incineration and several chemical-related parameters were more database-sensitive. Differences in temporal and geographical representativeness, technological coverage, system boundaries, and data transparency were major drivers of variability. For wastewater treatment LCA in China, locally representative databases should be prioritized, with international databases used for cross-validation, thereby improving the reliability of carbon accounting, mitigation decisions, low-carbon operation, and environmentally sustainable wastewater management.

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Journal
Sustainability
Published
2026-10-08
DOI
https://doi.org/10.3390/su181910219
Primary Topic
Environmental Impact and Sustainability
Type
article
Field-Weighted Citation Impact
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article

Effects of Background Database Selection on Carbon Footprint and Mitigation Hotspot Identification in Wastewater Treatment: A Comparative Study of Ecoinvent and CLCD

Rui Ma, Shichang Sun, Yanxi Liu, Yuan Gao et al.
Sustainability
Environmental Impact and Sustainability
article

Effects of Background Database Selection on Carbon Footprint and Mitigation Hotspot Identification in Wastewater Treatment: A Comparative Study of Ecoinvent and CLCD

Rui Ma, Shichang Sun, Yanxi Liu, Yuan Gao, Yanan You, Chunxue Li, Junhao Lin
article en

Abstract

Life cycle assessment (LCA) is an important tool for carbon footprint accounting in wastewater treatment, and its reliable application is essential for supporting low-carbon operation and environmentally sustainable management. However, LCA results are highly dependent on background database selection, while empirical evidence on its influence remains limited. This study evaluated two full-scale municipal wastewater treatment plants (WWTPs) in Shenzhen, China, using actual operational data, with the system boundary limited to the operational stage. Carbon footprints calculated using Ecoinvent v3.10 and CLCD v0.9 were compared, and sensitivity analysis and metadata comparison were conducted to identify database-related differences. Ecoinvent produced carbon footprints 4.53% and 9.04% higher than CLCD for WWTP A and WWTP B, respectively. Database selection also altered treatment-stage and emission-source contribution profiles, thereby affecting mitigation hotspot identification. Biological treatment remained dominant at both plants, whereas the contributions of sludge and advanced treatment varied substantially between databases. Under CLCD, electricity consumption, direct emissions, and sludge incineration contributed relatively more, while chemical consumption was more prominent under Ecoinvent. Sensitivity analysis identified electricity consumption and direct N2O emissions as robust key factors, whereas sludge incineration and several chemical-related parameters were more database-sensitive. Differences in temporal and geographical representativeness, technological coverage, system boundaries, and data transparency were major drivers of variability. For wastewater treatment LCA in China, locally representative databases should be prioritized, with international databases used for cross-validation, thereby improving the reliability of carbon accounting, mitigation decisions, low-carbon operation, and environmentally sustainable wastewater management.

SustainabilityVol. 18(19)
Shenzhen University (CN), Southeast University (CN)
Openalex Percentile: Top 20%
Environmental Impact and Sustainability
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