海贼王

杭州织密城市绿网打造“百姓园林”_我的网站

A |     

    Illustration: Liu Xiangya/GT
Recent media reports have questioned whether a natural gas plant built to power an Amazon data center project in Texas could become the largest climate polluter in the US. The controversy, whatever the eventual outcome, offers a reality check for America's artificial intelligence (AI) drive. 
It exposes a growing contradiction: The US is racing to expand its AI capabilities, yet its protectionist trade policies are making it harder and more costly to access some of the clean-energy technologies needed to sustain that expansion. This raises a broader question: Can an energy-intensive AI race afford the costs of renewable energy protectionism?
The US is entering a new era of rising electricity demand. Data centers, the backbone of the AI economy, are emerging as one of the fastest-growing sources of power consumption. Much of that demand is still being met by fossil fuels: The International Energy Agency reports that natural gas supplies more than 40 percent of the electricity used by data centers in the US, making it their largest source of power. 
So, it's not surprising that the expansion of data centers has raised concerns over their environmental impact and the pressure they could place on local power systems and electricity bills. A Gallup survey conducted in March found that seven in 10 Americans opposed the construction of AI data centers in their local area, including 48 percent who strongly opposed such projects.
The findings point to a broader challenge for the US: The race to develop AI is increasingly becoming a race to meet growing energy needs. Addressing this challenge will require more than advances in computing technology; it will also depend on an energy system capable of delivering large amounts of reliable, affordable and cleaner power. That, in turn, will require faster development and broader deployment of clean-energy technologies, from solar power to energy storage.
Yet in the clean-energy sector, the US has increasingly relied on protectionist trade measures that limit access to cost-competitive products from global markets. The country has placed greater emphasis on expanding domestic manufacturing capacity, but rebuilding entire clean-energy supply chains at home is a costly and time-consuming process. Even if expanded domestic production is achieved, it is likely to come at a higher cost, making the deployment of renewable technologies more expensive and potentially slower.
The solar industry offers a clear illustration of this policy direction. The US has continued to expand trade barriers in the sector. Reuters reported that the US government announced on Thursday a series of price floors and a 15 percent tariff on products made from polysilicon, a raw material used in solar panels.
The challenge lies in the limited scale of the US polysilicon industry. Reuters reported that the country has two polysilicon factories. Against this backdrop, relying on domestic polysilicon production while restricting access to imports runs counter to the goal of expanding solar power in the US. The country risks creating barriers that ultimately constrain its own access to the global supply chains needed for growth.
The pressing issue for the US is the speed at which new power demand is emerging. The expansion of data centers is creating electricity needs that cannot wait for domestic clean-energy capacity to develop gradually. Global supply chains can provide the scale and speed required in the near term. By narrowing access to these sources, the US risks turning clean-energy policy into a drag on the infrastructure needed for its AI race.
The US has placed AI high on its economic and technological agenda. The outcome of this race will matter greatly, as financial markets are also watching whether America can turn its AI efforts into commercial success.
This leaves the US with a difficult choice: Can it afford the cost of clean-energy protectionism while racing to build AI infrastructure? The answer may be no. Trade barriers that limit access to competitive renewable technologies could ultimately become a constraint on the AI expansion that Washington is seeking to accelerate.
The author is a reporter with the Global Times. [email protected]

。    达标成型的林荫道可让体感温度下降明显杭州日报讯 盛夏酷暑，连片交错的行道树冠撑起巨型遮阳穹顶，层层绿荫隔绝燥热，让城市道路化身解暑降温的“天然空调”。“林荫道的降温效果十分直观。”市园文局专家实地监测，盛夏晴日，南山路无遮挡路面温度可达55摄氏度，而浓密树荫下温度仅33摄氏度，温差十分显著。数据测算显示，达标成型的林荫道，可让行人体感温度下降明显；城市慢行道绿荫覆盖率超八成时，市民日常出行基本无需遮阳。目前，杭州行道树总量突破61万株。

B | 不同于公园集中式绿化，杭州林荫道沿城市街巷全域延展，覆盖市民日常出行全场景。从北山街、灵隐路等经典景区林荫廊道，到拱墅运河沿岸、滨江滨盛路、富阳桂花路等社区街巷绿廊，上千条林荫道路串联起公园、河道、滨水空间，打通城市蓝绿生态脉络。这些紧邻小区、学校、农贸市场的便民绿廊，成为市民触手可及的“百姓园林”，大幅提升了市民出行的舒适度与幸福感，也是杭州深耕公园城市建设、践行民生绿化理念的生动缩影。满城浓荫的背后，是系统化、标准化的制度体系提供的坚实支撑。为稳步推进林荫道建设、规范建设管理标准，杭州持续优化顶层设计，构建全流程建设管理体系。

C | 2021年，《杭州市林荫道系统专项规划》正式印发，确立“联绿通蓝，织路成网”的建设布局，远景规划打造约500条、总长近1900公里的林荫道，搭建贯通城乡的慢行绿荫骨架。在此基础上，杭州持续细化规范标准，补齐管理细则。

D | 2023年落地的《杭州市林荫道设计导则》，统一树种挑选、种植密度、树池打造等全流程建设标准；2024年实施的《杭州市林荫道评选标准和管理导则（试行）》，建立量化打分体系，划分一、二级林荫道，并增设风貌特色加分项。依托完善的制度规范，杭州完成首轮精品林荫道征集评选工作，经区县自荐、市民线上举荐、卫星遥感勘测、专家现场核验多轮筛选，最终选出首批100条精品林荫道，实现各区、县（市）全域覆盖，涵盖知名景观道路与社区小众便民绿道。三分栽种，七分养护。稳定的林荫景观成效，离不开精细化、常态化的管护保障。目前，杭州正为全市林荫道建立“一路一档”数字化台账，对行道树的长势动态跟踪、全程建档，结合季节特点制定闭环式精细化管护清单。

E | 春季集中开展整形修枝、缺株补植，拓宽树冠遮阴范围；夏季聚焦高温管护，错峰采用滴灌、水袋补水方式养护，加密日常巡查频次，及时清理枯枝、消除安全隐患；秋冬季有序疏枝、树干刷白防寒、科学追肥，为树木越冬积蓄养分。

F | 同时，常态化开展路面巡查，快速处置树木病害、枝干倒伏、管线冲突等问题，针对高温、台风等极端天气提前制定应急预案，对弱势树木精准施救，全方位筑牢林荫覆盖成效。林荫惠民建设久久为功，城市生态提质步履不停。下一步，市园文局将在扩容、提质上双向发力，持续升级城市林荫体系——结合城市更新、老旧街巷改造工作，打通林荫断点、补齐绿化空白区域，不断扩充林荫道存量规模；优选香樟、悬铃木、枫香等冠大荫浓的本土乔木，打造“一路一品”的特色林荫风貌。同时，持续完善林荫道动态评估、名录更新机制，畅通市民推荐反馈通道、民意诉求渠道，构建全民共建共治共享的城市绿化治理新格局，持续擦亮杭州公园城市名片，提升市民的生态获得感与幸福感。

Current article:http://p936rz.yaoyaotoutuanmieshaideizun.buzz/ywkq/20260826/61125.html

Published on:15:33:50