AI 中文总结
本研究评估美国AI数据中心的环境与经济影响，发现其影响由电力等系统决定，需综合政策协调数据中心运营与资源规划以改善绩效。
AI 中文摘要
本研究利用电力需求增长、冷却需求及备用系统运行情况，评估美国人工智能数据中心的环境与经济影响。研究结果表明，影响并非仅由设施设计决定，还取决于这些设施运营所处的更广泛的电力、水及土地利用系统。排放主要由电力消耗驱动，因此取决于边际发电结构、输电约束以及需求的时空分布。分析进一步显示，局部影响包括水资源压力、噪声暴露增加和土地利用变化，且结果因地区和基础设施条件而异。对技术和运营措施的评估表明，能源效率、冷却配置和运营策略的改进可降低这些影响，尽管其有效性取决于系统层面条件。对监管和市场结构的评估表明，现有框架可能未充分考虑特定地点和时间的外部性。这些发现支持采用综合政策方法的必要性，该方法需使数据中心的部署和运营与电力系统特征、水资源可用性及土地利用规划相协调，以提升整体环境与经济绩效。
英文摘要
In this study, we use electricity demand growth, cooling requirements, and backup system operation to evaluate the environmental and economic implications of artificial intelligence data centers in the United States. Our results indicate that impacts are not determined solely by facility design, but by the broader electricity, water, and land-use systems in which these facilities operate. Emissions are primarily driven by electricity consumption and therefore depend on marginal generation mixes, transmission constraints, and the spatial and temporal distribution of demand. Analysis further shows that local effects include pressures on water resources, increased noise exposure, and land-use changes, with outcomes varying across regions and infrastructure conditions. The assessment of technological and operational measures shows that improvements in energy efficiency, cooling configurations, and operational strategies can reduce these impacts, although their effectiveness depends on system-level conditions. Evaluation of regulatory and market structures suggests that existing frameworks may not fully account for location- and time-specific externalities. These findings support the need for integrated policy approaches that align data center deployment and operation with electricity system characteristics, water availability, and land-use planning to improve overall environmental and economic performance.
