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 2 ) and commercial grids (approximately 8 t/m 2 ) 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.

The rapid urbanization in China since the 1970s has led to an exponential growth of metal stocks (MS) in use in cities. A retrospect on the quantity, quality, and patterns of these MS is a prerequisite for projecting future metal demand, identifying urban mining potentials of metals, and informing sustainable urbanization strategies. Here, we deployed a bottom-up stock accounting method to estimate stocks of iron, copper, and aluminum embodied in 51 categories of products and infrastructure across ten Chinese megacities from 1980 to 2016. We found that the MS in Chinese megacities had reached a level of 2.6-6.3 t/cap (on average 3.7 t/cap for iron, 58 kg/cap for copper, and 151 kg/cap for aluminum) in 2016, which still remained behind the level of western cities or potential saturation level on the country level (e.g., approximately 13 t/cap for iron). Economic development was identified as the most powerful driver for MS growth based on an IPAT decomposition analysis, indicating further increase in MS as China's

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