廃棄物発電からの炭素クレジット創出：UAE向け実践的MRV・政策枠組み
Unlocking Carbon Credits from Waste-To-Energy: A Practical MRV and Policy Framework for the UAE (原題)
Badhria Al Hammadi, Zakaria Awda, Abdulla Al Mansoori
🤖 gxceed AI 要約
日本語
UAEの廃棄物発電（WtE）事業を国家炭素クレジット登録制度（NRCC）に統合するための政策枠組みを提案した研究。実稼働施設の性能評価と全国シナリオ modelling を通じ、埋立回避メタンと化石由来CO2を定量する簡素化MRV手法を提示する。日本・スウェーデン・韓国の事例を参考に、スマートビンや住民還元型インセンティブによる分別促進策をUAE向けに設計している。
English
This study proposes a policy framework to integrate UAE waste-to-energy (WtE) projects into the National Carbon Credit Registry. It assesses an operating WtE facility, models national scenarios for power generation, methane avoidance and credit revenue, and offers a simplified MRV approach for landfill-avoided emissions and fossil CO2, including future CCS. Drawing on Japan, Sweden and South Korea, it designs incentive-based waste segregation (smart bins, household rewards, digital tracking) to improve feedstock quality and MRV accuracy.
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
日本は分別・リサイクル制度とWtEの先進国として明示的に参照されており、国内の廃棄物処理・炭素クレジット（J-クレジット）制度設計や、海外インフラ輸出・二国間クレジット（JCM）案件形成を考える実務家にとって比較材料となる。
In the global GX context
The paper speaks directly to the emerging architecture of domestic carbon-credit registries and Article 6-aligned MRV in emerging markets, and shows how waste-sector crediting can be made interoperable with net-zero strategy and circular-economy policy. Its explicit use of Japanese, Swedish and Korean segregation models makes it a useful comparative reference for global MRV and crediting scholarship.
👥 読者別の含意
🔬研究者:WtEの排出削減量を簡素化MRVで定量する手法と、制度ギャップ分析の枠組みを参考にできる。
🏢実務担当者:廃棄物処理・エネルギー企業が炭素クレジット収益化と分別品質管理を設計する際の実務的雛形になる。
🏛政策担当者:国内炭素クレジット制度に廃棄物部門を組み込む際の規制設計とインセンティブ制度の論点を提供する。
📄 Abstract（原文）
Abstract Municipal solid waste generation in the United Arab Emirates (UAE) continues to increase with rapid urbanization and economic development, placing significant pressure on landfills and contributing to methane emissions. At the same time, the UAE is advancing its Net Zero 2050 Strategy and has introduced the National Carbon Credit Registry (NRCC) to verify and trade domestic emission reductions. Waste-to-Energy (WtE) projects in the UAE already divert significant quantities of waste from landfills and generate renewable electricity, yet their emission-reduction potential is not fully reflected in current waste-management policies or carbon-market regulations. This disconnect prevents WtE projects from registering carbon credits and limits opportunities to monetize their climate benefits. This study develops a policy framework to integrate WtE projects into the NRCC by analysing regulatory gaps, evaluating the technological and environmental performance of an operational WtE facility in the UAE, and modelling national scenarios for energy generation, methane avoidance, and carbon-credit revenue. A simplified MRV (Measurement, Reporting, and Verification) approach is proposed to enable consistent quantification of avoided landfill emissions and fossil CO2 from WtE operations, including future deployment of CCS technologies. Importantly, the study introduces a practical incentive-based waste-segregation system tailored to the UAE context. Drawing on international lessons from Japan, Sweden, and South Korea, the framework recommends smart-bin technologies, household reward schemes, digital tracking systems, and community-level incentives to improve segregation behavior and enhance WtE feedstock quality. These measures strengthen the accuracy of MRV data, increase diversion from landfills, and prepare the waste sector for participation in carbon-crediting mechanisms. The findings demonstrate that aligning waste-management policy, behavioral incentives, and carbon-credit regulations can unlock significant environmental and economic value. Integrating WtE into the NRCC—and improving segregation upstream—positions municipal waste as a measurable climate-action pathway that supports the UAE's Circular Economy and Net Zero objectives.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.2118/236075-msfirst seen 2026-11-03 04:55:03 · last seen 2026-11-06 04:55:03
🔔 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。