Carbon Aware E Commerce: Real-Time, Region-Specific Measurement and Abatement of Web Emissions
カーボン・アウェアなEコマース：Web排出量のリアルタイム・地域別測定と削減 (AI 翻訳)
Vladyslav Malanin, Vadim Tulchinsky
🤖 gxceed AI 要約
日本語
本論文は、eコマースサイトのWebページ表示に伴う炭素排出量を、リアルユーザーモニタリングとグリーンソフトウェア財団のSCI手法、時間別グリッド炭素強度データを用いて測定・削減するフレームワークを提案。機能単位をセッション・注文・売上高あたりのCO₂eと定義し、画像・スクリプト・フォントなどの影響を評価。次世代画像形式やJavaScript最適化、カーボンアダプティブモードなどの介入効果を示し、商用パフォーマンスを維持しながら排出削減が可能であることを実証した。
English
This paper proposes a carbon-aware measurement and abatement framework for e-commerce websites, combining real user monitoring, the Green Software Foundation's SCI methodology, and hourly grid carbon intensity data. It defines functional units per session, order, and dollar of GMV, evaluates interventions like next-gen images and carbon-adaptive mode, and shows emissions reductions without harming commercial performance.
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
日本では、SSBJ基準や有報でのScope 3開示が進む中、デジタルサービスの間接排出（Scope 3カテゴリ4）の算定手法が注目されている。本論文のリアルタイム・地域別測定アプローチは、日本のeコマース事業者にとって実践的な削減策を提供する。
In the global GX context
Globally, as digital services face pressure to disclose Scope 3 emissions, this paper offers a replicable protocol for measuring and reducing web-related carbon footprints. It aligns with the Green Software Foundation's SCI standard and provides open data, supporting corporate sustainability reporting under frameworks like ISSB and CSRD.
👥 読者別の含意
🔬研究者:Provides a reproducible methodology for web carbon measurement and abatement, with open data for further study.
🏢実務担当者:Offers actionable interventions (e.g., image formats, JS optimization) that reduce emissions while maintaining conversion rates.
🏛政策担当者:Demonstrates feasibility of real-time carbon tracking for digital services, informing potential disclosure guidelines.
📄 Abstract（原文）
E-commerce pages are among the heaviest on the web, with images, video, third-party scripts, fonts, and client-side JavaScript driving network transfer and computation. Prior work often reports a single “average grams CO₂e per page view,” but such figures vary by methodology and have recently been revised downward (e.g., Website Carbon v4 cites ≈approximately 0.36 g CO₂e/page view globally), masking large differences by geography, device, and content mix. To provide decision-useful evidence for online retail, we introduce a carbon-aware measurement and abatement framework that combines real user monitoring (RUM) of page bytes and execution with the Green Software Foundation’s Software Carbon Intensity (SCI) methodology and hourly grid intensity data. We define functional units aligned to business value in terms of CO₂e per session, per order, and per dollar of gross merchandise value, and estimate the contributions of media, scripts, CSS, fonts, and third-party integrations. We then evaluate interventions—next gen image formats, JavaScript consolidation/splitting, critical CSS loading, and font subsetting/WOFF2 alongside a carbon adaptive mode that dynamically downshifts high-impact assets when local grid carbon intensity is high. We report effects on emissions, Cumulative Layout Shift, and conversion. Our results show how e-commerce sites can reduce operational emissions while maintaining commercial performance, and we offer a reproducible protocol and open data to support adoption.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.32628/cseit26121361first seen 2026-05-05 19:12:52
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。