China’s per capita building stock has reached 87% of that of the United States, and the embodied carbon emissions of buildings must be given due attention.
Release Time:
2026-12-09
China’s per capita building stock has reached 87% of that of the United States, and the embodied carbon emissions of buildings must be given due attention.
A research study by Beijing Normal University shows that in 2020, China’s per capita stock of construction materials stood at 123.3 tons per person, roughly 87% of the U.S. level. Between 2001 and 2020, China’s per capita stock of construction materials increased by 58%, while embodied carbon emissions from the built environment accounted for 19% of the country’s total carbon emissions over the same period.
Per capita stock of construction materials in China, disaggregated by region and population density. Source: Chaoqun Zhang et al., "Building material stock drives embodied carbon emissions and risks future climate goals in China", Nature Climate Change (2026)
This study, conducted by Professor Chen Ziyue’s team at Beijing Normal University, aims to clarify the architectural landscape of China. Embodied carbon the spatial distribution and dynamic trends, thereby providing critical data support for achieving carbon neutrality. The relevant paper was published in the latest issue of the internationally renowned journal Nature Climate Change.
The team found that between 2001 and 2020, China’s stock of construction materials increased by approximately 71 billion tonnes, containing an estimated 28.7 billion tonnes of embodied carbon—accounting for roughly 19% of the country’s total carbon emissions during the same period. By material type, the four major sources of embodied carbon are cement, steel, asphalt, and bricks and tiles. Embodied carbon peaked in 2013 at 2.4 ± 0.3 gigatonnes, after which it began to decline, falling to 0.8 ± 0.1 gigatonnes by 2020.
Annual embodied carbon in new buildings, categorized by building material type. Source: Chaoqun Zhang et al., "Building material stock drives embodied carbon emissions and risks future climate goals in China", Nature Climate Change (2026)
The primary challenge of this study lies in achieving high‑precision, dynamic statistical analysis of the built stock. By applying machine learning and spectral–temporal segmentation algorithms to long‑term satellite imagery, the research team quantified the historical dynamics of a total of 200 million individual buildings across China between 2000 and 2020. Building on this, they integrated databases of carbon emission factors for nine major construction materials, including cement, steel, and wood, thereby enabling spatiotemporal analysis of embodied carbon emissions from the built environment.
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