Abstract

The cities of China, the world’s largest CO2 emitting country, play a crucial role in mitigating global climate change by their pursuit of carbon neutrality. However, assessing their decarbonization levels with internationally recognized metrics such as the OECD cities’ criteria is a major challenge, as the fuzzy definitions of China’s cities – including by city administrative boundary (UB1), city district boundary (UB2), and urban built-up area (UB3) – create misconceptions and ambiguities over the integrity and accuracy of their reported emissions. In this study, we develop a new China high-resolution emission database (CHRED) as a means of quantifying urban emissions based on dynamic city limits defined by population density boundary (UB4). Employing a 1 km grid dataset built from point-emission sources, it is showed that: (1) the reported emissions from the adoption of different urban boundaries can have differences as large as 17.77 %; (2) the spatial structure of China’s urban CO2 emissions has a clustered pattern reflecting the country’s spatial urban agglomeration structure; (3) the CO2 emissions per capita of China mega UB4 cities are similar to OECD C40 cities; and (4) that nonindustrial emissions are influenced by geographical location and population density.We further argue that the boundaries of UB4 cities need to be continuously adjusted to reflect the growth of urban built-up land across China. This is further evidenced by a counterfactual estimation and scenario analysis, which indicates that the differences in per capita nonindustrial emissions under different scenarios of population growth and urban sprawl could be as large as 27.6 % by 2040. The findings show that a bottom-up accounting database based on the UB4 boundary is significant for building high-resolution urban emissions inventories to mitigate nonindustrial carbon emissions in China.

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