内容来源：https://www.wired.com/story/heres-where-to-build-data-centers-to-keep-emissions-down/

内容总结：

近期，科技企业在美国大规模投入数据中心建设，为经济增长注入强劲动力。然而《自然·通讯》最新研究指出，这种爆发式扩张可能使科技公司的"碳中和"承诺面临严峻挑战。

研究表明，数据中心选址将直接决定其生态影响。德克萨斯州、蒙大拿州、内布拉斯加州和南达科他州因兼具清洁能源供应与水资源的平衡优势，被列为理想选址。而亚利桑那等缺水地区，以及弗吉尼亚等清洁能源转型压力较大的传统数据中心枢纽，则面临更大环保压力。

研究负责人、康奈尔大学冯齐有教授指出："AI行业发展速度远超预期，我们必须提前规划可持续发展路径。"数据显示，若按最极端情况推算，全美数据中心每年可能额外产生4400万吨二氧化碳当量，超过匈牙利等国家全年排放总量。

尽管科技巨头仍持续加码传统枢纽地区——如谷歌八月宣布在弗吉尼亚投资90亿美元，但专家警告在资源紧张区域过度集中建设，将导致"自然承载力超限"。与此同时，核能等新能源技术突破、冷却系统效率提升，以及企业自建清洁能源设施等措施，可能成为缓解环境压力的转机。

麻省理工学院气候专家诺曼·巴希尔认为，面对这个快速演进的行业，具体预测数字未必准确，但研究揭示的核心问题值得警惕：在AI竞赛白热化的当下，科技企业的减排承诺正与现实发展产生越来越大的鸿沟。

中文翻译：

近几个月来，科技企业投入巨资建设数据中心，这股热潮正强力驱动美国经济发展——而人工智能竞赛丝毫没有放缓迹象。Meta首席执行官马克·扎克伯格上周向特朗普总统表示，该公司将在2028年前投入6000亿美元用于美国基础设施（包括数据中心）建设，而OpenAI已承诺投入1.4万亿美元。

一项最新全面分析着眼于美国数据中心的环境足迹，试图厘清未来几年持续建设过程中美国可能面临的具体挑战，以及为避免最严重的环境影响应将数据中心布局于何处。这项周一发表于《自然-通讯》期刊的研究，综合运用AI芯片需求、各州电力及水资源短缺等数据，预测到2030年末未来数据中心可能造成的环境影响。研究通过多种情景模拟推演数据中心对美国乃至地球的潜在影响，并警示科技公司的"净零排放"承诺可能难以应对其兴建大型设施所需的能源和水资源消耗。

该研究的合著者、康奈尔大学能源系统工程教授冯琦有表示，三年前启动的这项研究"正值理解人工智能如何影响气候系统及水资源消耗的关键时机"。他补充说，AI产业"发展速度远超预期"，特别是在特朗普政府对该行业高度重视的背景下，"当前整个领域正获得巨大发展动能"。

数据中心的环境影响存在地域差异：其水足迹和碳足迹很大程度上取决于选址位置。某些州可能拥有更高比例的可再生能源电网，或在推进清洁能源并网方面取得重大进展，这能显著降低从这些电网取电的数据中心碳排放。同理，水资源充裕的州更适宜提供数据中心冷却所需的大量用水（冷却能耗也构成数据中心能源消耗的重要部分）。研究发现，未来几年美国数据中心的最佳选址需在两项要素间取得平衡：得克萨斯、蒙大拿、内布拉斯加和南达科他州被列为"AI服务器部署的最优候选地"。

美国数据中心建设历来集中于弗吉尼亚州（美国数据中心枢纽）和北加州等地。毗邻华盛顿特区和硅谷的地理优势、密集的光纤网络及熟练技术工人是吸引数据中心企业的关键因素。弗吉尼亚州多年来持续为数据中心提供大幅税收减免——这也成为其他州争相效仿的招商策略。根据行业监测平台"数据中心地图"统计，在全美4000多座数据中心中，弗吉尼亚州以650余座位居榜首，加州以320余座位列第三。

尽管弗吉尼亚州不缺水，但环保人士指出数据中心巨大的能源需求可能阻碍该州2045年实现100%清洁能源的目标。反观加州，长期存在的水资源问题可能因数据中心持续扩张而加剧（去年10月，州长加文·纽瑟姆否决了要求数据中心运营商披露用水量的法案，声称该州"已为支持数据中心发展做好充分准备"）。

数据中心运营商选址时会综合考量能源与水资源的供需状况，但这并非全部决定因素：拥有160余座数据中心的亚利桑那州在研究中被列为面临"严重水资源短缺"的地区之一。

行业尚无撤离部分热门区域的计划：弗吉尼亚州仍在规划大型项目，包括谷歌八月宣布的90亿美元投资。但冯琦有警告，若持续在资源紧张区域建设，"将突破自然资源承载极限"。他将数据中心运营商扎堆热门区域比作居民同时涌入同一家超市："即使这是全城最好的商店，购物体验也绝不会愉快"。

研究推荐的未来重点发展州中，得克萨斯州已建成健全的数据中心产业，据"数据中心地图"统计现居全美第二（大部分增长源于近期：2023至2024年间该州数据中心建设规模翻了两番）。但蒙大拿、内布拉斯加和南达科他等其他推荐州的数据中心数量仍相对较少。冯琦有指出，随着产业在全国迅猛扩张，这些数字正在攀升：洛杉矶某公司正计划在南达科他州建设首座超大规模数据中心，而内布拉斯加州的39座数据中心已包含Meta和谷歌新近启用的设施。不过这些州要追赶弗吉尼亚仍道阻且长（南达科他州仅5座设施，全美倒数第二）。

如同所有AI相关研究，无论数据中心最终落址何处，预测未来始终充满不确定性。研究指出，模型效率提升、冷却技术进步、电网能源结构变革等多重因素，都可能显著改变未来数年的实际能耗与用水量。AI泡沫破裂也可能导致全国遍布烂尾工程与合同（电力问题已致使部分数据中心闲置多年）。

部分发展前景取决于化石能源替代的政治意愿。例如内布拉斯加州虽拥有巨大风能潜力（研究将其列为理想数据中心选址的原因之一），但至今未实际开发该资源，其公用事业公司今年反而大力投资天然气发电。与此同时，特朗普政府持续数月推行政策倾斜，推动化石能源为AI繁荣供能。

鉴于数据中心在全国的迅猛扩张，电网若未能向可再生能源转型可能引发严重气候危机。分析显示，在最极端情境下，美国数据中心建设每年将额外产生4400万吨二氧化碳当量——超过匈牙利、葡萄牙、新西兰等国家2022年的全国排放总量。

冯琦有表示，最恶劣的环境情境是未来数年AI需求增速超过计算能效提升，同时可再生能源转型进程放缓。"需求正在急速攀升，随着新应用场景、终端设备、代理型AI的涌现，增速可能进一步加快，"他强调，"这将成为严峻挑战"。

但研究同时指出，冷却与供电技术发展结合科学选址，可大幅改善排放与用水状况。业界专家则提醒，对这个仍处快速演进、涉及多重变量的行业进行排放预测需保持审慎。"我尽量避免过度关注具体数值，"未参与研究的麻省理工学院气候与可持续发展联盟计算与气候影响研究员诺曼·巴希尔表示。他指出，数据中心自建发电设施（如天然气电厂或独立于电网的太阳能电池系统）以及核能等关键技术进步，对总体排放的影响可能远超研究测算。

不过巴希尔肯定了该研究的核心结论：在数据中心建设狂潮中，作出净零承诺的科技公司恐难兑现目标。谷歌、微软等科技巨头在近期可持续发展报告中已默认，对AI的专注使其减排承诺的实现难度倍增。

冯琦有希望其研究能推动主导建设的公司提升排放透明度，他将此类比食品营养标签机制。"未来发展将更迅猛、更庞大，"他断言，"就全美AI计算基础设施发展而言，在早期阶段统筹可持续性规划远胜于事后补救。"

英文来源：

Tech companies have invested so much money in building data centers in recent months, it’s actively driving the US economy—and the AI race is showing no signs of slowing down. Meta chief Mark Zuckerberg told President Donald Trump last week that the company would spend $600 billion on US infrastructure—including data centers—by 2028, while OpenAI has committed already to spending $1.4 trillion.
An extensive new analysis looks at the environmental footprint of data centers in the US to get a handle on what, exactly, the country might be facing as this buildout continues over the next few years—and where the US should be building data centers to avoid the most harmful environmental impacts.
The study, published in the journal Nature Communications on Monday, uses a variety of data, including demand for AI chips and information on state electricity and water scarcity, to project the potential environmental impacts of future data centers through the end of the decade. The study models a number of different possible scenarios on how data centers could affect the US and the planet—and cautions that tech companies’ net zero promises aren’t likely to hold up against the energy and water needs of the massive facilities they’re building.
Fengqi You, a professor in energy systems engineering at Cornell and one of the authors of the analysis, says that the study, which began three years ago, comes at “a perfect time to understand how AI is making an impact on climate systems and water usage and consumption.”
The AI industry “is growing much faster than we expected,” he adds—especially with the Trump administration’s laser focus on the industry. “This whole thing is just getting so much momentum right now.”
Not all data centers are created environmentally equal: a lot of their water and carbon footprint depends on where they’re located. Some US states may have grids that run more on renewable energy, or are making big strides in putting more clean energy on the grid; this greatly lessens the carbon emissions from data centers that draw power from those grids. Similarly, states with less water scarcity are better suited to provide the large amounts of water needed for cooling data centers. (Cooling also constitutes a big part of data center energy use.) The best locations for a data center over the next few years in the US are states that strike a balance between these two inputs: Texas, Montana, Nebraska, and South Dakota, the analysis finds, are “optimal candidates for AI server installations.”
Much of the data center buildout in the US has historically focused on places like Virginia, the data center hub of the US, and Northern California. Being close to Washington, DC, and Silicon Valley was important to data center companies, as were the dense fiber connectivity in those regions and their skilled workforces. Virginia has also offered substantial tax breaks for data centers for years—one technique other states are turning to to lure development. According to Data Center Map, an industry tool that tracks data center development, of the 4,000-plus data centers in the US, more than 650 are in Virginia—the most in the country—and California has more than 320, ranking third.
While Virginia doesn’t suffer from water scarcity, advocates have said that massive energy requirements from data centers could derail the state’s goals to source 100 percent clean energy by 2045. Conversely, California’s long-running water issues may cause a problem if data centers keep expanding there. (In October, Governor Gavin Newsom vetoed a bill that would have required data center operators to disclose how much water they use, claiming that the state is “well positioned to support the development” of data centers.)
Data center operators choose locations based on a variety of factors, including energy and water needs. But they’re not the only inputs: Arizona, which has more than 160 data centers, is named in the analysis as one of the states facing “severe water scarcity issues.”
The industry has no plans to move out of some of their favored areas: There are still massive projects planned for Virginia, including a $9 billion investment from Google announced in August. But continue to build in already-stressed areas and “you’re going to exceed the capacity for natural resources,” You says. He compares data center operators flocking to popular areas as analogous to people living in the same area all going to the same grocery store at the same time. “The shopping experience is not going to be pleasant, even if it may be the best shop in town.”
Texas, one of the top states for future development named in the study, has built out a robust data center industry, and is now the second-most-popular state for data centers in the country, according to Data Center Map. (Much of this boom has come very recently: Data center construction in Texas quadrupled between 2023 and 2024.) But other top states named in the analysis—Montana, Nebraska, and South Dakota—still have relatively few data centers. However, their numbers are rising, You says, as the data center industry aggressively expands across the country. An LA-based company is looking to build the first hyperscale data center in South Dakota, while Nebraska’s 39 data centers include recently opened facilities owned by Meta and Google. Still, these states have a long way to go to catch up to places like Virginia. (South Dakota, according to Data Center Map, has just five facilities, the second-lowest in the country.)
As with any studies about AI, making predictions about the future is tricky, no matter where data centers end up getting built. The study acknowledges that a number of factors—from improvements in model efficiency, to advances in cooling technology, to changes in what kinds of energy gets added to the grid—could drastically change the amount of energy and water that ends up being used over the next few years. There’s also a possibility that the AI bubble may burst, leaving a scattered collection of half-built projects and contracts around the country. (Power issues are already leaving some data centers sitting idle for years.)
Part of what could happen depends on the political will for moving off fossil fuels. Nebraska, for instance, has massive potential for wind energy—one of the reasons it’s named in the analysis as a good spot for data centers—but has to date not actually built out that capacity; Nebraska’s utilities have instead invested heavily into more natural gas this year. The Trump administration, meanwhile, has spent months putting its finger on the scale to promote fossil fuels to power the AI boom.
A grid that doesn’t transition to renewable energy could mean serious trouble for the climate, given how aggressively data centers are expanding across the country. In the most extreme scenarios, the analysis finds, the US’s data center buildout could generate up to an extra 44 million tons of carbon dioxide equivalent each year—more than entire countries like Hungary, Portugal, and New Zealand each generated in 2022.
The worst-case scenario for the environment, You says, is if AI demand outstrips efficiency gains in computing in the coming years, while the transition to renewable energy slows down. “We know demand is picking up very quickly, but it could be even faster with all these new applications, more devices, agentic AI, all these things,” says You. “It’s going to be a problem.”
But the study also claims that developments in technology, like those for cooling and powering data centers, in addition to siting data centers correctly, could drastically improve both emissions and water use. Outside experts, meanwhile, caution against trying to predict emissions from what is still a rapidly evolving industry, with lots of different variables involved.
“I try not to put too much value on specific numbers,” says Noman Bashir, the Computing and Climate Impact Fellow at MIT’s Climate and Sustainability Consortium, who was not involved in the study. Bashir points out that data centers installing their own energy onsite—like building their own natural gas plants or installing solar panels and batteries separate from the grid—as well as advancements in some key new technologies, like nuclear, could have a much bigger impact on overall emissions than the study calculates.
But Bashir praises a base conclusion of the paper: that tech companies that made net-zero pledges are unlikely to meet them, given the rush to build data centers. Big Tech players like Google and Microsoft have quietly acknowledged in recent sustainability reports that their focus on AI is making the promises they made on cutting emissions much harder to achieve.
You hopes that his work helps create more transparency on emissions from the companies driving the buildout—something, he says, that could be analogous to the nutrition labels on food.
“The future is going to be much faster, much bigger,” he says. “Keeping sustainability in mind in the early stage is much better than later on, in terms of how AI computing infrastructure will develop and grow in our country.”