建筑环境
库存(枪支)
城市化
区域科学
工业化
持续性
业务
地理
环境资源管理
经济地理学
工程类
经济
经济增长
土木工程
市场经济
生态学
考古
生物
作者
Maud Lanau,Gang Liu,Ulrich Kral,Dominik Wiedenhofer,Elisabeth Keijzer,Chang Yu,Christina Ehlert
标识
DOI:10.1021/acs.est.8b06652
摘要
Built environment stocks (buildings and infrastructures) play multiple roles in our socio-economic metabolism: they serve as the backbone of modern societies and human well-being, drive the material cycles throughout the economy, entail temporal and spatial lock-ins on energy use and emissions, and represent an extensive reservoir of secondary materials. This review aims at providing a comprehensive and critical review of the state of the art, progress, and prospects of built environment stocks research which has boomed in the past decades. We included 249 publications published from 1985 to 2018, conducted a bibliometric analysis, and assessed the studies by key characteristics including typology of stocks (status of stock and end-use category), type of measurement (object and unit), spatial boundary and level of resolution, and temporal scope. We also highlighted the strengths and weaknesses of different estimation approaches. A comparability analysis of existing studies shows a clearly higher level of stocks per capita and per area in developed countries and cities, confirming the role of urbanization and industrialization in built environment stock growth. However, more spatially refined case studies (e.g., on developing cities and nonresidential buildings) and standardization and improvement of methodology (e.g., with geographic information system and architectural knowledge) and data (e.g., on material intensity and lifetime) would be urgently needed to reveal more robust conclusions on the patterns, drivers, and implications of built environment stocks. Such advanced knowledge on built environment stocks could foster societal and policy agendas such as urban sustainability, circular economy, climate change, and United Nations 2030 Sustainable Development Goals.
科研通智能强力驱动
Strongly Powered by AbleSci AI