Quantitative Modeling of AI Data Center Emissions Under Alternative Energy Policies
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| Natura: | Recurso digital |
| Lingua: | inglese |
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Zenodo
2026
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| _version_ | 1866901905009016832 |
|---|---|
| author | Case, Finn |
| author_facet | Case, Finn |
| contents | <p>This paper develops a quantitative framework for evaluating the environmental impact of AI-related data center electricity demand under alternative energy policy regimes. Using projected AI infrastructure electricity consumption, carbon intensity estimates, and Monte Carlo simulation methods, the analysis compares carbon taxes, renewable energy subsidies, dynamic energy pricing, and clean energy mandates. Results suggest that dynamic energy pricing combined with clean energy mandates achieves substantial emissions reductions while minimizing economic distortion and public cost. The paper contributes to emerging research on AI infrastructure economics, carbon-aware compute allocation, and energy systems optimization.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20320804 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Quantitative Modeling of AI Data Center Emissions Under Alternative Energy Policies Case, Finn AI Infrastructure Energy Economics Carbon Emissions Data Centers Monte Carlo Simulation Environmental Economics Compute Optimization AI Policy <p>This paper develops a quantitative framework for evaluating the environmental impact of AI-related data center electricity demand under alternative energy policy regimes. Using projected AI infrastructure electricity consumption, carbon intensity estimates, and Monte Carlo simulation methods, the analysis compares carbon taxes, renewable energy subsidies, dynamic energy pricing, and clean energy mandates. Results suggest that dynamic energy pricing combined with clean energy mandates achieves substantial emissions reductions while minimizing economic distortion and public cost. The paper contributes to emerging research on AI infrastructure economics, carbon-aware compute allocation, and energy systems optimization.</p> |
| title | Quantitative Modeling of AI Data Center Emissions Under Alternative Energy Policies |
| topic | AI Infrastructure Energy Economics Carbon Emissions Data Centers Monte Carlo Simulation Environmental Economics Compute Optimization AI Policy |
| url | https://doi.org/10.5281/zenodo.20320804 |