Eco-ITAD: 持続可能なIT資産処分のためのオンプレミス自動ハードウェア診断とScope 3カーボン会計

Eco-ITAD: On-Premise Automated Hardware Diagnostics and Scope 3 Carbon Accounting for Sustainable IT Asset Disposition (原題)

Islam MS, Sarkar J

Research Squareプレプリント2026-09-01#AI×ESGOrigin: Global経営インパクト: 調達リスク対象セクター: it

DOI: 10.21203/rs.3.rs-10500424/v2

原典: https://doi.org/10.21203/rs.3.rs-10500424/v2

🤖 gxceed AI 要約

日本語

Eco-ITADは、オンプレミスでハードウェア診断を行い、S.M.A.R.T.テレメトリから健康スコアを算出し、DEFRA排出係数を用いてScope 3の回避排出量を算定するシステム。揮発メモリ上でコンプライアンス証明書を生成し、ストレージへの永続的書き込みを排除。50回の実行で平均0.322秒の高速処理を実現。

English

Eco-ITAD is an on-premise system that diagnoses hardware health using S.M.A.R.T. telemetry and computes avoided Scope 3 emissions using DEFRA factors. It generates compliance certificates in volatile memory, eliminating persistent writes. Evaluated on 50 runs, it achieves 0.322s mean completion time.

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開示が始まり、Scope 3排出量の算定が企業に求められる中、IT資産処分の実態に即した算定手法は有用。オンプレミス処理によりデータセキュリティを確保しつつ、排出量の精緻化が可能。

In the global GX context

Globally, with ISSB and CSRD requiring Scope 3 disclosure, this paper offers a practical method for ITAD that combines hardware diagnostics with carbon accounting, addressing data security and accuracy gaps in spend-based methods.

👥 読者別の含意

🔬研究者:Provides a novel integration of hardware diagnostics with carbon accounting, offering a replicable model for Scope 3 estimation in ITAD.

🏢実務担当者:Offers a deployable tool for ITAD providers to generate accurate, secure Scope 3 certificates, enhancing compliance and customer trust.

🏛政策担当者:Highlights the need for standardized, condition-based emission factors in e-waste and ITAD regulations.

📄 Abstract（原文）

<title>Abstract</title> <p>Enterprise hardware refresh cycles generate significant volumes of electronic waste and poorly evidenced Scope 3 emissions. Conventional IT Asset Disposition (ITAD) workflows depend on off-site processing centres, introducing multi week turnaround delays and data-exposure risk during transit of unsanitised storage media. Concurrently, commercial ESG accounting platforms predominantly rely on spend-based emission factors that cannot reflect the physical condition of the asset being retired. This paper presents Eco-ITAD, an on-premise diagnostic and carbon accounting engine implemented in Python and Flask. The system derives a deterministic composite health score from NVMe S.M.A.R.T. endurance telemetry, memory subsystem capacity, and normalised compute capability, and maps this score to avoided embodied emissions using a remaining- service-life allocation model parameterised with UK DEFRA conversion factors and published lifecycle inventory data. Com- pliance certificates are generated entirely in volatile memory using buffered I/O streams, incorporating SHA-256 integrity digests while eliminating persistent audit artifacts on host storage. Evaluated across 50 executions on an enterprise desktop system (AMD64 Family 23 Model 113, 31.9 GB RAM, 1 TB Samsung SSD 860 EVO), the diagnostic pipeline achieved mean completion time of 0.322 s (σ = 0.007 s), peak single-core CPU utilization of 103.2%, and zero persistent writes to host storage. We additionally report a sensitivity analysis of the carbon model and an explicit discussion of the limitations of proxy-based health estimation.</p>

🔗 Provenance — このレコードを発見したソース

Research Square https://doi.org/10.21203/rs.3.rs-10500424/v2first seen 2026-09-02 04:33:03 · last seen 2026-09-15 04:21:30

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