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07/15/2026 | Press release | Distributed by Public on 07/15/2026 10:21

The Environmental Footprint of Emerging Technology and Artificial Intelligence

The Environmental Footprint of Emerging Technology and Artificial Intelligence

Data Centers, Community Health and Policy Responses

4 Min Read

Jul 15, 2026

By

Emma Uridge, M.P.H.,

Jasmin Kamruddin, M.D., M.P.H.

Executive Summary

The rapid growth and use of artificial intelligence (AI) is transforming many sectors, but it also has environmental implications that are complex and multifaceted. AI infrastructure drives increased demand for significant water use, greater energy consumption and expanded grid infrastructure, all of which require careful management to avoid environmental and community harm.

Energy and Emissions

U.S. data centers consumed 183 terawatt-hours (TWh) of electricity in 2024, more than 4 percent of the country's total energy usage, and that figure is projected to grow by 133 percent to 426 TWh by 2030.

Virginia, Texas and Oregon had the highest emissions attributable to data centers.

Typical AI research pipelines involve training thousands of models, resulting in cumulative emissions of tens of thousands of pounds of carbon dioxide (CO2) equivalent over several months. Training a single AI model can emit more than 626,000 pounds of CO₂ equivalent, nearly five times the lifetime emissions, including manufacturing, of an average American car.

Water

Data centers consumed an estimated 17 billion gallons of water directly in 2023, with projections suggesting that use could double or quadruple by 2028. In 2021, 1 in 5 U.S. data centers was already located in an area experiencing water stress.

Data center water use occurs both directly through cooling and indirectly through electricity consumption. Cooling alone can account for as much as 40 percent of a data center's total electricity consumption. Some facilities draw more than half of their water from potable sources and increasing data center capacity means water demand is likely to rise as computing infrastructure expands.

Grid Impact

In the United States, fossil fuel dominated all electricity generated for data centers (56 percent), followed by renewable energy (22 percent) and nuclear power (21 percent).

The growth of data centers is delaying coal plant closures, slowing or preventing national, state and local priorities to transition to clean energy, as renewable sources are insufficient to meet both hyperscale data centers and existing users' needs.

AI Task Intensity

Emerging technologies, like AI, often require larger, more energy-intensive data centers to meet computational demand. Searches driven by generative AI use four to five times the energy of a conventional web search.

Generative AI tasks such as text generation, summarization, image captioning and image generation tend to be more energy- and carbon-intensive than discriminative (predictive) use cases, such as using existing data in machine learning models to identify patterns, anticipate user behaviors and forecast upcoming events.

Policy Landscape

Policy responses vary and often reflect a tension between furthering state-level economic development interests and balancing local community health and environmental concerns. States are primarily addressing energy reporting, ratepayer protection and environmental assessment. Local governments have tended to act more directly on land use, zoning and permitting, driven by community opposition and the immediacy of local resource impacts.

Select local actions include:

  • Loudoun County, Virginia, ended by-right zoning for data centers, requiring all new applications to undergo public hearings (2025).
  • Kansas City, Missouri, classified data centers as industrial, requiring council approval and mandatory impact studies on water and electricity rates (2026).
  • Marana, Arizona, prohibited potable water use for cooling and required water source disclosure (2024).

Path Forward for Public Health

Public health practitioners are well-positioned to help navigate the tension between economic development and community health. The three core functions of public health, policy development, assessment and assurance, provide a concrete structure for that work:

  • Policy development: Advocate for health impact assessments in permitting, transparency requirements and community notification standards; contribute public health expertise to state and local rulemaking.
  • Assessment: Track and analyze cumulative environmental exposures, air quality near diesel generators, water availability in stressed regions and electricity cost burdens on low-income households; push for systematic, mandatory data collection from operators.
  • Assurance: Monitor health outcomes in affected communities over time, hold operators and regulators accountable to environmental standards and ensure vulnerable populations have meaningful access to decision-making processes.

The most consequential recommendation is also the most foundational, communities need the information, access and standing to participate in decisions about AI infrastructure that will affect their health for decades to come. Public health can serve as a valuable partner in shaping the ethical rollout of AI and emerging technologies in our increasingly digital society.

Learn more

Download the full report to explore the findings in greater detail.

Acknowledgments

This report builds upon a growing body of research dedicated to responsible artificial intelligence (AI) integration in public health. Particular recognition is given to the foundational work produced through a collaboration between the Kansas Health Institute, Health Resources in Action and the Wichita State University Community Engagement Institute, whose publication: Developing Artificial Intelligence (AI) Policies for Public Health Organizations: A Template and Guidance helped catalyze critical thinking around the emergence and rapid expansion of AI infrastructure in public health contexts and policy. Jasmin Kamruddin completed work on this project while an intern at the Kansas Health Institute.

About Kansas Health Institute

The Kansas Health Institute supports effective policymaking through nonpartisan research, education and engagement. KHI believes evidence-based information, objective analysis and civil dialogue enable policy leaders to be champions for a healthier Kansas. Established in 1995 with a multiyear grant from the Kansas Health Foundation, KHI is a nonprofit, nonpartisan educational organization based in Topeka.

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KHI - Kansas Health Institute Inc. published this content on July 15, 2026, and is solely responsible for the information contained herein. Distributed via Public Technologies (PUBT), unedited and unaltered, on July 15, 2026 at 16:22 UTC. If you believe the information included in the content is inaccurate or outdated and requires editing or removal, please contact us at [email protected]