← 論文一覧に戻る

Beef and animal protein consumption as major sources of urban food related carbon emissions

牛肉と動物性タンパク質消費:都市の食関連炭素排出の主要因 (AI 翻訳)

Fatmah, Irene S. Fitrinitia, Liang Gao

Frontiers in Sustainable Food Systems📚 査読済 / ジャーナル2026-07-02#その他対象セクター: food
DOI: 10.3389/fsufs.2026.1842044
原典: https://doi.org/10.3389/fsufs.2026.1842044

🤖 gxceed AI 要約

日本語

インドネシアの都市部における食事関連炭素排出を分析。牛肉を含む動物性タンパク質が排出の主要因で、牛肉の排出原単位は他のタンパク質源の約45倍。低炭素な食習慣への転換が重要。

English

This study analyzes urban food-related carbon emissions in Indonesia, finding animal protein (especially beef) is the largest contributor, with beef having 45 times higher emission intensity than alternatives. It advocates for low-carbon dietary interventions.

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

日本の食料システムでも牛肉消費の排出削減は重要だが、本研究はインドネシア都市部の実証データを提供。日本の食料政策やフードテックへの示唆は限定的。

In the global GX context

While focused on Indonesia, this paper contributes to the global literature on food-related emissions, supporting dietary shift recommendations. It provides emission factors for beef vs alternatives that can inform LCA databases.

👥 読者別の含意

🔬研究者:Provides empirical data on dietary emission patterns in an urban developing-country setting.

🏢実務担当者:Food companies can use the emission intensity comparison to prioritize low-carbon protein sourcing.

🏛政策担当者:Supports integrating dietary change into climate mitigation strategies, especially for urban populations.

📄 Abstract(原文)

Introduction The diet related emissions constitute a significant source of global carbon emissions, with animal protein representing a major contributing component, especially high-emission products such as beef. This study aimed to analyze the key determinants significantly associated with carbon emissions arising from animal protein consumption and daily activities. Methods A cross-sectional study was conducted among 210 respondents aged 18–70 years from middle-to-upper socioeconomic groups in South Jakarta and Depok. Data were collected through a structured questionnaire assessing sociodemographic characteristics, knowledge of climate change and carbon emissions, animal protein consumption practices, carbon emissions from transportation, household appliances, food, and waste activities. Carbon emissions were estimated and analyzed using univariate, bivariate, and multivariate statistical methods. Results Food consumption was the primary driver of carbon emissions, accounting for 46.6% of the total, with animal protein contributing the largest share (59.6%). A substantial proportion was also observed in household appliances, whereas the lowest proportion was found in waste. Among animal protein sources, beef consumption emerged as the primary contributor, responsible for 45.6% of emissions. Significant differences in carbon emissions from both the food system and animal protein were observed across sociodemographic and knowledge-related variables, including age, family structure, income level, knowledge of climate change and greenhouse gases, awareness of the link between animal protein consumption and emissions, and dietary practices particularly beef consumption ( p  < 0.05). Marital status was also significantly associated with emissions from the food system ( p  < 0.05) due to the dietary pattern. Beef consumption exhibited a substantially higher emission intensity compared to other animal protein sources, with an impact approximately 45 times greater. Furthermore, urban respondents who consumed beef generated approximately 45-fold higher carbon emissions than those consuming alternative animal protein sources. Conclusion Animal protein consumption, particularly beef, is a major driver of carbon emissions, underscoring the need for low-carbon dietary interventions to promote sustainable consumption. Integrating such strategies into pre-climate related disaster nutrition planning such as floods, droughts, heatwaves, and landslides may enhance nutritional resilience while mitigating environmental impacts in the context of climate-related disasters.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。