AI's growing energy demand worsens air quality, imposing significant public health costs, especially on disadvantaged communities, necessitating better reporting and mitigation strategies.
Source identity and required public metadata were editorially reviewed on 2026-09-15.
Han, Yuelin; Wu, Zhifeng; Li, Pengfei; Wierman, Adam; Ren, Shaolei. 2024-12-09. Health-Informed Computing: Estimating and Addressing the Public Health Impact of Data Centers. https://arxiv.org/abs/2412.06288 (AI & Environment Resource Hub; record paper-024; collection snapshot 2026-09-15).
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.
Selected fields checked: title · 2026-09-06. The arXiv record identifies this exact paper title; the former title was not the source title. Verification source ↗
Source sheet: Scientific Paper · Row 28 · Original ID: paper-024.
A paper listing is not a quality assessment. Peer review and findings require source-level confirmation. Source link reachable · checked 2026-09-15. Source identity and required metadata verified. The import date is not the original date added.
The project explores innovative ways to address Barcelona’s sustainability challenges, such as carbon emissions, air pollution, and energy inefficiency. By leveraging AI, IoT sensors, and Nature-Based Solutions (NBS), the project aims to optimize municipal budgets for interventions that transform underutilized urban spaces into productive assets.
IAAC Blog
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Built environment and infrastructure
Artificial Intelligence (AI) has the potential to transform how water is managed. Yet, these emerging opportunities raise critical considerations around issues such as data governance, energy use, and the environmental footprint of digital infrastructure. To explore these challenges and opportunities, IWRA is launching a new webinar series: "The Promises and Challenges of AI, Data Centres & Freshwater Futures". Bringing together experts from around the world, the series examines the intersection of emerging technologies and water sustainability.
youtube.com
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Built environment and infrastructure
Anne Currie is the co-author of the acclaimed O’Reilly book “Building Green Software”, a pillar of the GSF, a veteran in the Cloud Industry and also a SF novelist with her series of panopticon books. Preparing her forthcoming keynote at Green IO London, she went all the way down into the rabbit hole of AI and energy efficiency. She investigated from OpenAI to DeepSeek and open source models, what a software developer using these models can and cannot do to reduce energy consumption, and so on.
#63.b AI & Energy Efficiency: just follow the money? with Anne Currie
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Built environment and infrastructure
AI and ML optimize optoelectronic systems for sustainability by enhancing energy efficiency, renewable energy harvesting, environmental monitoring, and smart cities while also advancing ocean optics and photonics for marine ecosystem monitoring and climate change mitigation.