arXiv Machine Learning July 7, 2026 By Qingwen Zeng, Hanlin Xu, Nanjun Xu, Zhenghao Zhao, Joakim Westerholm, Flora Salim, Junbin Gao, Huaming Chen

Engineering Carbon Credits Towards A Responsible FinTech Era: The Practices, Implications, and Future

Read the original on arXiv Machine Learning →

arXiv:2501. 14750v3 Announce Type: replace-cross Abstract: Carbon emissions significantly contribute to climate change, and carbon credits have emerged as a key tool for mitigating environmental damage and helping organizations manage their carbon footprint.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI

Jun 10

Accounting for AI Inference in Corporate GHG Inventories: A Four-Tier Methodology for Scope 3 Category 1 Reporting

arXiv:2606. 10660v1 Announce Type: cross Abstract: AI inference services -- API subscriptions, enterprise chat tools, and SaaS products with embedded AI features -- fall unambiguously within Scope 3 Category 1 under the Corporate Sustainability Reporting Directive (CSRD), which requires disclosure for fiscal years starting January 2024.

By Guillermo Llopis (SOMA AI, Barcelona)

benchmarks

arXiv AI

Jun 16

Green AI Carbon Optimizer: Carbon-Efficient Training Location Recommendation and Global AI Energy Demand Forecasting

arXiv:2606. 14707v1 Announce Type: cross Abstract: AI training and deployment consume substantial electricity, but carbon outcomes remain weakly integrated into routine model development decisions.

By Yuxin Chen (University of Helsinki, Finland), Hao Gao (Independent Researcher), Chujie Zou (University of Helsinki, Finland)

benchmarks

arXiv AI

2d ago

Designing Sustainable Federated Learning as a Service using Neural Architecture Search

arXiv:2608. 14359v1 Announce Type: new Abstract: The sustainability constraints of FLaaS consumers pose significant challenges to maintaining carbon-feasible federated training in FLaaS environments.

By Keya Patel, Sajib Mistry, Sheik Fattah, Deepak Kanneganti, Aneesh Krishna, Mufti Mahmud, Monowar Bhuyan

arXiv AI

Jun 11

Carbon-Aware Governance Gates: An Architecture for Sustainable GenAI Development

arXiv:2602. 19718v2 Announce Type: replace-cross Abstract: The rapid adoption of Generative AI (GenAI) in the software development life cycle (SDLC) increases computational demand, which can raise the carbon footprint of development activities.

By Mateen A. Abbasi, Tommi J. Mikkonen, Petri J. Ihantola, Muhammad Waseem, Pekka Abrahamsson, Niko K. M\"akitalo

rag agents

arXiv AI

Aug 12

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint

arXiv:2608. 09998v1 Announce Type: new Abstract: Artificial Intelligence (AI) and Machine Learning (ML) have become powerful tools for supporting and automating complex human tasks.

By Samar Garrab, Sarra Boughriou, Manel BenSassi

arXiv Machine Learning

Jun 8

Heterogeneous Effects of Green Finance on Urban Decarbonization: Evidence from 285 Cities in China

arXiv:2606. 06986v1 Announce Type: new Abstract: While green finance has become a key instrument for low-carbon city transitions, its actual decarbonization effects and transmission mechanisms remain unclear.

By Xueyang Li, Jinlei Ma

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Accounting for AI Inference in Corporate GHG Inventories: A Four-Tier Methodology for Scope 3 Category 1 Reporting

Green AI Carbon Optimizer: Carbon-Efficient Training Location Recommendation and Global AI Energy Demand Forecasting

Designing Sustainable Federated Learning as a Service using Neural Architecture Search

Carbon-Aware Governance Gates: An Architecture for Sustainable GenAI Development

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Heterogeneous Effects of Green Finance on Urban Decarbonization: Evidence from 285 Cities in China