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在新冠疫情初期感知城市局部能源消耗模式的全球变化。

Sensing global changes in local patterns of energy consumption in cities during the early stages of the COVID-19 pandemic.

作者信息

Rowe Francisco, Robinson Caitlin, Patias Nikos

机构信息

Geographic Data Science Lab, Department of Geography and Planning, University of Liverpool, Liverpool, United Kingdom.

School of Geographical Sciences, University of Bristol, Bristol, United Kingdom.

出版信息

Cities. 2022 Oct;129:103808. doi: 10.1016/j.cities.2022.103808. Epub 2022 Jun 16.

Abstract

COVID-19, and the wider social and economic impacts that a global pandemic entails, led to unprecedented reductions in energy consumption globally. Whilst estimates of changes in energy consumption have emerged at the national scale, detailed sub-regional estimates to allow for global comparisons are less developed. Using night-time light satellite imagery from December 2019-June 2020 across 50 of the world's largest urban conurbations, we provide high resolution estimates (450 m) of spatio-temporal changes in urban energy consumption in response to COVID-19. Contextualising this imagery with modelling based on indicators of mobility, stringency of government response, and COVID-19 rates, we provide novel insights into the potential drivers of changes in urban energy consumption during a global pandemic. Our results highlight the diversity of changes in energy consumption between and within cities in response to COVID-19, moderating dominant narratives of a shift in energy demand away from dense urban areas. Further modelling highlights how the stringency of the government's response to COVID-19 is likely a defining factor in shaping resultant reductions in urban energy consumption.

摘要

新冠疫情以及全球大流行所带来的更广泛的社会和经济影响,导致全球能源消耗出现了前所未有的下降。虽然在国家层面已经出现了能源消耗变化的估计,但用于全球比较的详细次区域估计则较少。利用2019年12月至2020年6月期间全球50个最大城市集聚区的夜间灯光卫星图像,我们提供了城市能源消耗时空变化的高分辨率估计(450米),以反映新冠疫情的影响。通过基于流动性指标、政府应对措施的严格程度和新冠疫情感染率的模型对这些图像进行背景分析,我们对全球大流行期间城市能源消耗变化的潜在驱动因素提供了新的见解。我们的结果突出了城市之间和城市内部能源消耗变化的多样性,以应对新冠疫情,缓和了能源需求从密集城市地区转移的主流观点。进一步的模型分析突出了政府对新冠疫情应对措施的严格程度可能是塑造城市能源消耗最终下降的一个决定性因素。

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