Investigation of the marginal impact of electricity generation sources on CO2 emissions in highly emitting countries by daily data and KRLS approach
高排出国における電力源のCO2排出への限界的影響：日次データとKRLSアプローチによる調査 (AI 翻訳)
Mustafa Tevfik Kartal, Galib Gafarli, Özer Depren, Fatih Ayhan
🤖 gxceed AI 要約
日本語
本研究は、中国、米国、インド、ロシア、日本の5か国を対象に、2019年1月から2024年6月までの日次データを用いて、電源タイプ別のCO2排出への平均的・限界的影響をKRLS法で分析した。結果、太陽光発電は全対象国で排出削減に有効であり、石炭火力は全対象国で排出を増加させることが示された。風力や水力は国や排出量のパーセンタイルによって効果が異なる。これらの知見に基づき、政府支援の優先順位や新規設備導入の方向性に関する政策提言を行っている。
English
This study empirically analyzes the average and marginal impacts of electricity generation subtypes on CO2 emissions for five high-emitting countries (China, US, India, Russia, Japan) using daily data from Jan 2019 to Jun 2024 and a kernel regularized least squares (KRLS) approach. Results show solar EG consistently reduces emissions across all countries, while coal EG increases emissions everywhere. Wind and hydro effects vary by country and percentile. The study offers policy implications for prioritizing renewable sources and government support.
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
日本は主要排出国の一つとして、電源構成の転換が急務。本研究の結果は、日本のエネルギー政策における太陽光・水力・原子力の優先順位付けに示唆を与える。また、SSBJ開示やカーボンプライシング導入に向けたエビデンスとしても有用。
In the global GX context
This study provides cross-country empirical evidence on the effectiveness of different electricity sources in reducing CO2 emissions, relevant for global climate policy and transition finance. The findings support prioritizing solar and other renewables, informing ISSB-aligned disclosure and transition planning for utilities and investors.
👥 読者別の含意
🔬研究者:Provides a novel application of KRLS to daily data across major emitters, offering nuanced insights into marginal effects of electricity sources.
🏢実務担当者:Utilities and energy companies can use these findings to guide investment in solar and other low-carbon generation sources.
🏛政策担当者:Highlights which electricity sources yield the greatest CO2 reductions, supporting evidence-based energy policy and subsidy allocation.
📄 Abstract（原文）
Abstract Considering countries’ efforts to combat climate change and the critical role of energy use in carbon dioxide (CO 2 ) emissions, this study empirically analyzes the impact of electricity generation (EG) sub-types on CO 2 emissions. In this vein, the study focuses on the five highly emitting countries (namely, China, the United States, India, Russia, & Japan), uses daily data from 1st January 2019 to 30th June 2024, and implements a kernel regularized least squares (KRLS) approach to consider average and marginal impacts in empirical analyses. The empirical outcomes demonstrate that (i) gas and nuclear EG decreases CO 2 emissions for India; hydro EG is curbs CO 2 emissions in India and Japan; oil EG decreases CO 2 emissions at lower percentiles in the USA; (ii) coal EG cause an increase in CO 2 emissions in the all countries; (iii) wind EG provides a decrease in CO 2 emissions at lower percentiles in the USA and Japan, whereas its effect becomes ineffective across remaining percentiles and countries; (iv) solar EG is the unique source that has a declining impact across countries; (v) the KRLS approach has a high estimation capacity (R 2 : 93.53%). Overall, the study reveals average and marginal impacts of EG subtypes on CO 2 emissions across percentiles and countries. Accordingly, through consideration of empirical outcomes (e.g., solar EG is the most beneficial EG source for all countries) while some other EG sub-types are partially beneficial (e.g., gas EG in China and India; hydro EG in all countries; nuclear EG in all countries except Russia; wind EG in United States, India, and Japan), the study argues various policy implications (e.g., prioritizing the most helpful EG sources in providing further governmental support, focusing on first solar EG and then followed by hydro, nuclear, and wind EG to stimulate new capacity installation).
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1038/s41598-026-64394-yfirst seen 2026-08-14 04:56:18
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