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This paper developed internationally compatible methods for delineating boundaries of urban areas in China. By integrating emission source data with existing official statistics as well as using rescaling methodology of data mapping for 1 km grid, the authors constructed high resolution emission gridded data in Beijing-Tianjin-Hebei (Jing-Jin-Ji) region in China for 2012. Comparisons between urban and non-urban areas of carbon emissions from industry, agriculture, household and transport exhibited regional disparities as well as sectoral differences. Except for the Hebei province, per capita total direct carbon emissions from urban extents in Beijing and Tianjin were both lower than provincial averages, indicating the climate benefit of urbanization, comparable to results from developed countries. Urban extents in the Hebei province were mainly industrial centers while those in Beijing and Tianjin were more service oriented. Further decomposition analysis revealed population to be a common major driver for increased carbon emissions but climate implications of urban design, economic productivity of land use, and carbon intensity of GDP were both cluster- and sector-specific. This study disapproves the one-size-fits-all solution for carbon mitigation but calls for down-scaled analysis of carbon emissions and formulation of localized carbon reduction strategies in the Jing-Jin-Ji as well as other regions in China. [ABSTRACT FROM AUTHOR]

The green growth of Beijing-Tianjin-Hebei (BTH) urban agglomeration plays a leading and exemplary role in overcoming internal resource restrictions, addressing climate change, and supporting China's high-quality growth. From the standpoint of pollution reduction and carbon reduction, this paper first conducts a comprehensive evaluation of the environmental impact based on combined weighting technique. The Logarithmic Mean Divisia Index (LMDI) model is used to decompose the environmental impact drivers in distinct areas. A decoupling effort index is further constructed to measure the effect of various efforts on the decoupling of economic growth and environmental impact, the improved grey Markov model is applied to predict the future trend of regional decoupling efforts. The results of empirical analysis based on data of the BTH region during 2011–2018 show that: 1) the environmental impact index of Beijing is the lowest followed by Tianjin and Hebei; 2) environmental regulation exerts the most significant impact on reducing environmental pressure in Beijing while technology progress and energy intensity have the most significant effect on easing environmental pressure in Tianjin; 3) strong decoupling efforts have been found in Beijing, Tianjin and Hebei, however, such effect is more significant in Beijing; 4) Beijing's decoupling state is mostly driven by regulatory effect, intensity effect, and scale effect, while Tianjin and Hebei's decoupling states are primarily driven by improvements in environmental regulation and energy intensity; 5) according to the forecast outcome of the improved grey Markov technique, a state of strong decoupling effort will be maintained in the BTH area by 2025, and the decoupling effort index in Beijing will remain the highest while the index in Hebei will remain the lowest. • A comprehensive evaluation of the environmental impact of BTH based on combined weighting method is estimated. • Determinants of environmental impact is decomposed as regulatory, technological, intensity, growth and scale effects. • LMDI model is constructed to estimate the five determinants of regional environmental impact. • Decoupling effort approach and improved grey Markov model are used to analyze and predict the status of various decoupling efforts. • Various suggestions are proposed from the perspective of regional heterogeneity. [ABSTRACT FROM AUTHOR]