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Improving Precision of Carbon Emissions Accounting for Sustainability Reporting: Case Study from Latvia

持続可能性報告のための炭素排出会計の精度向上:ラトビアのケーススタディ (AI 翻訳)

Anete Kalniņa, Pauls Sondors, Maksims Feofilovs, Agris Kamenders, Francesco Romagnoli

CONECT. International Scientific Conference of Environmental and Climate Technologies📚 査読済 / ジャーナル2026-05-08#Scope 1/2Origin: EU
DOI: 10.7250/conect.2026.035
原典: https://doi.org/10.7250/conect.2026.035
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🤖 gxceed AI 要約

日本語

本論文は、持続可能性報告におけるスコープ2排出量の算定精度向上を目指し、ラトビアの4社の製造業を対象に、1時間ごとのセンサー測定電力消費データを用いたケーススタディを実施。企業固有の排出係数は、一般的なEcoinventデータベースの国別係数と比較して約56%低いことを示し、高解像度データの重要性を明らかにした。

English

This study improves Scope 2 carbon accounting precision by using hourly sensor data from four Latvian manufacturing companies. Company-specific emission factors were approximately 56% lower than the Ecoinvent country-level factor, highlighting the importance of granular data for accurate sustainability reporting.

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基準や有報でのスコープ2開示が強化される中、本論文の高解像度データ活用は企業の排出係数改善に示唆を与える。特に、再エネ比率の高い地域では立地ベースと市場ベースの差が大きくなる点は、日本の電力市場にも示唆的である。

In the global GX context

Globally, this paper underscores the need for high-resolution data in Scope 2 accounting, directly relevant to ISSB, CSRD, and GHG Protocol debates. It reveals how location-based vs. market-based methods create significant disparities, especially in renewable-rich countries, supporting harmonized data practices.

👥 読者別の含意

🔬研究者:This paper provides empirical evidence on how granular data improves Scope 2 accuracy, useful for comparing accounting methodologies.

🏢実務担当者:Companies can reference this case study when considering sensor-based data to refine their emission factors for sustainability reporting.

📄 Abstract(原文)

Among growing regulatory and investor pressure for high-quality sustainability reporting, accurate carbon accounting has become essential for corporate Environmental, Social, and Governance disclosures. A key challenge exists in calculating consumed electricity-related emissions (Scope 2), where companies often rely on generalized national average emission factors, for which accounting approaches differ in how electricity generation, cross-border exchanges, and energy attributes are interpreted and allocated. Some methods primarily rely on nationally produced electricity as a proxy for consumption, while others incorporate electricity trade and contractual instruments to represent how energy is acquired and reported by companies. Even for two approaches defined by the GHG protocol, known as market-based mix accounting and location-based mix accounting, disparities appear in their interpretation. As concluded from studies on Norway’s and Iceland’s differences between nationally produced, exported and imported energy, the problem with accounting for location-based energy mixes (increasing double counting of renewable energy consumed by companies) has a higher impact on countries with a high share of renewable energy production, which export the produced energy and sell renewable energy certificates, such as Latvia. As a result, the choice of accounting method and data resolution plays a critical role in determining reported electricity-related emissions at the company level. This study aims to explore how an increase in the granularity of company-specific electricity consumption measured data can improve the precision and traceability of related Scope 2 emissions for more qualitative operational decisions in companies. A case study was conducted using hourly sensor-measured electricity consumption data from four manufacturing companies that operate in Latvia over one year. The delivered electricity mix to the company was recorded each hour, and the company-specific average hourly and yearly emission factor was calculated. The results demonstrate that company-specific data typically yield lower calculated emission factors than the commonly used Ecoinvent database country-specific CO2eq emission factor, i.e., company-specific yearly average emission factors were approximately 56 % lower. However, these results must further be contextualized within the methodological tensions between physical location-based and contractual market-based energy mix accounting. This study supports the current need for harmonized, high-resolution energy data practices and integration with digital solutions to support trustworthy carbon emissions disclosures.

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