SDU Life Cycle Engineering, Department of Chemical Engineering, Biotechnology, and Environmental Technology, University of Southern Denmark, 5230 Odense, Denmark.
Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing, China.
Environ Sci Technol. 2020 May 5;54(9):5345-5355. doi: 10.1021/acs.est.9b07229. Epub 2020 Apr 24.
Improving our comprehension of the weight and spatial distribution of urban built environment stocks is essential for informing urban resource, waste, and environmental management, but this is often hampered by inaccuracy and inconsistency of the typology and material composition data of buildings and infrastructure. Here, we have integrated big data mining and analytics techniques and compiled a local material composition database to address these gaps, for a detailed characterization of the quantity, quality, and spatial distribution (in 500 m × 500 m grids) of the urban built environment stocks in Beijing in 2018. We found that 3621 megatons (140 ton/cap) of construction materials were accumulated in Beijing's buildings and infrastructure, equaling to 1141 Mt of embodied greenhouse gas emissions. Buildings contribute the most (63% of total, roughly half in residential and half in nonresidential) to the total stock and the subsurface stocks account for almost half. Spatially, the belts between 3 and 7 km from city center (approximately 5 t/m) and commercial grids (approximately 8 t/m) became the densest. Correlation analyses between material stocks and socioeconomic factors at a high resolution reveal an inverse relationship between building and road stock densities and suggest that Beijing is sacrificing skylines for space in urban expansion. Our results demonstrate that harnessing emerging big data and analytics (e.g., point of interest data and web crawling) could help realize more spatially refined characterization of built environment stocks and highlight the role of such information and urban planning in urban resource, waste, and environmental strategies.
提高我们对城市建成环境存量的重量和空间分布的理解对于告知城市资源、废物和环境管理至关重要，但这通常受到建筑物和基础设施的分类和材料组成数据的准确性和一致性的阻碍。在这里，我们整合了大数据挖掘和分析技术，并编制了本地材料组成数据库，以解决这些差距，详细描述 2018 年北京市城市建成环境存量的数量、质量和空间分布（在 500m×500m 网格中）。我们发现，2018 年北京市的建筑物和基础设施中积累了 3621 万吨（140 吨/人）的建筑材料，相当于 1141 兆吨的隐含温室气体排放。建筑物对总存量的贡献最大（占总数的 63%，其中住宅约占一半，非住宅约占一半），地下存量几乎占一半。从空间上看，市中心 3 至 7 公里（约 5 吨/米）和商业网格（约 8 吨/米）之间的地带变得最密集。在高分辨率下，对材料存量和社会经济因素的相关分析表明，建筑物和道路存量密度与社会经济因素呈负相关，这表明北京在城市扩张中为了空间而牺牲了天际线。我们的研究结果表明，利用新兴的大数据和分析技术（例如，兴趣点数据和网络爬虫）可以帮助实现更精细的建成环境存量特征描述，并强调这种信息和城市规划在城市资源、废物和环境战略中的作用。
