Scientific Paper

Potential of Artificial Intelligence in Reducing Energy and Carbon Emissions of Commercial Buildings at Scale

Ding et al. · 2024-07-14

What it covers

AI can enhance building energy efficiency, potentially reducing carbon emissions by up to 90% by 2050 when combined with policy and low-carbon energy.

Who it helps

Intended audience has not been documented.

Limitations

Source-specific limitations have not been reviewed. Inclusion and topic labels do not establish effectiveness or reliability.

Show citation

Ding et al.. 2024-07-14. Potential of Artificial Intelligence in Reducing Energy and Carbon Emissions of Commercial Buildings at Scale. https://www.nature.com/articles/s41467-024-50088-4 (AI & Environment Resource Hub; record paper-027; collection snapshot 2026-10-04).

Classification and context

Included in the original Scientific Paper collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.

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Available source metadata

Author or creator
Ding et al.
Publisher
Nature Communications
Publication date
2024-07-14
Date precision
day
Geographic scope
Unknown
Language
unknown
Peer review
unknown
Source access
Reachable at last check
Metadata confidence
Metadata unconfirmed
Last verified
Not yet verified
Snapshot import
2026-09-06
Legacy domain
Energy
Legacy subdomain
AI in Energy Efficiency for Buildings
journal
Nature Communications

Provenance and review

Source access
Reachable at last check
Metadata confidence
Metadata unconfirmed
Editorial relevance
Relevance has not been separately reviewed.
Evidence quality
Evidence quality has not been separately assessed.

Source sheet: Scientific Paper · Row 31 · Original ID: paper-027.

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A paper listing is not a quality assessment. Peer review and findings require source-level confirmation. Source link reachable · checked 2026-09-28. Metadata not yet corroborated. The import date is not the original date added.

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Related through shared environmental topics

Ordered by the number of shared provisional topic labels. This indicates a browsing connection, not agreement between sources.

Shared topics: Energy and electricity

Shared topics: Energy and electricity

Shared topics: Energy and electricity

Scientific Paper · 2026-09-15

A Strategic Roadmap for Sustainable Data Center Deployment

This article proposes a five-step state policy roadmap for data center development: conduct environmental and community impact studies, use the findings in siting decisions, reassess incentives, require large facilities to pair with off-grid clean energy and storage, and mandate community-benefit sharing. It focuses on protecting grid reliability, electricity affordability, environmental integrity, and host communities.

Source: SSRNAutomated access restricted · Metadata unconfirmed

Shared topics: Energy and electricity

Scientific Paper · 2025-05-26

A Study on Energy Consumption in AI-Driven Medical Image Segmentation

This study evaluates the energy consumption of AI models used in medical image segmentation and finds that Depthwise Convolution with Mixed Precision offers the most energy-efficient training configuration, highlighting the need for GPU-aware, sustainable AI practices.

Source: MDPIReachable at last check · Metadata unconfirmed