下水処理における炭素フットプリントと削減ホットスポット特定に対するバックグラウンドデータベース選択の影響：EcoinventとCLCDの比較研究

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

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

Sustainability📚 査読済 / ジャーナル2026-10-08#炭素会計Origin: CN経営インパクト: コスト削減対象セクター: water_utilities

DOI: 10.3390/su181910219

原典: https://doi.org/10.3390/su181910219

🤖 gxceed AI 要約

日本語

中国深セン市の実稼働下水処理場2施設を対象に、運用段階に限定したLCAを実施し、Ecoinvent v3.10とCLCD v0.9の炭素フットプリントを比較した。EcoinventはCLCDより4.53%および9.04%高い値を示し、処理段階・排出源の寄与プロファイルも変化して削減ホットスポット特定に影響を与えた。電力消費と直接N2O排出は頑健な主要因子である一方、汚泥焼却や化学薬品関連はDB感度が高く、中国では地域代表性のあるDBの優先と国際DBによる相互検証が信頼性向上に重要と結論づけた。

English

This study compares Ecoinvent v3.10 and CLCD v0.9 carbon footprints for two full-scale municipal wastewater treatment plants in Shenzhen, China, using operational data. Ecoinvent yielded 4.53% and 9.04% higher footprints than CLCD and altered treatment-stage and emission-source contribution profiles, shifting mitigation hotspot identification. Electricity use and direct N2O emissions were robust key factors, while sludge incineration and chemical parameters were database-sensitive. Locally representative databases should be prioritized for Chinese wastewater LCA, with international databases for cross-validation.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本でも下水処理は自治体・事業者のScope 1/2/3算定対象であり、インベントリDB選択が削減投資判断や開示数値を左右する点はSSBJ・有報の炭素会計精度管理に示唆を与える。地域代表性と透明性の高いDB整備は国内GXインフラの課題でもある。

In the global GX context

As ISSB/CSRD push Scope 3 and product-level carbon accounting into assurance, this paper shows that background database choice materially changes reported footprints and hotspot prioritization. It underscores the need for regionally representative, transparent LCI databases to make disclosure comparable and mitigation decisions defensible.

👥 読者別の含意

🔬研究者:LCAにおけるバックグラウンドDB選択が結果とホットスポット特定に与える影響を定量化した実証例として、炭素会計研究の不確実性評価に有用。

🏢実務担当者:自社の下水・水処理炭素算定でDB選択が削減優先順位を変えうることを理解し、地域DBと国際DBの併用・感度分析を開示に組み込むべき。

🏛政策担当者:地域代表性のあるLCIデータベース整備と、炭素会計のDB選択・透明性に関するガイドライン策定の根拠となりうる。

📄 Abstract（原文）

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.

🔗 Provenance — このレコードを発見したソース

openalex https://doi.org/10.3390/su181910219first seen 2026-10-10 05:15:11

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