Dynamic interactive effects of urban land-use efficiency, industrial transformation, and carbon emissions

Clarifying the interactive relationship between urban land-use efficiency (ULUE), industrial transformation, and carbon emissions is of great realistic significance for promoting the coordination of 'resources-economy-environment' and achieving green development. This study used the stochastic frontier analysis (SFA), index method (IM), and remote sensing inversion to calculate the ULUE, the industrial transformation degree (ITD), and the carbon emission intensity (CEI) for 108 cities in the Yangtze River Economic Belt (YREB) from 2005 to 2017, and analyzed their spatiotemporal evolution characteristics. The generalized method of moments (GMM) and impulse response function (IRF) in the panel vector autoregressive (PVAR) model are used to empirically test the dynamic interactive effects of ULUE, ITD, and CEI. The empirical results show that: (i) During the study period, the ULUE and ITD of the YREB increased year-by-year, showing the pattern characteristics of high in the east and low in the west. The CEI decreased by 50.20% cumulatively, and the low-value areas spread from the center of the urban agglomeration towards the periphery. (ii) The GMM shows that there is a significant dynamic dependence between the ULUE, ITD, and CEI. The ULUE has a positive driving effect on the industrial transformation and a negative effects on the CEI in the short term. (iii) The IRF shows that the ULUE and industrial transformation show a synergistic effect of interactive growth. The improvement of the ULUE and industrial restructuring will force the reduction of CEI. The article proposes that the city should take the new urbanization path of resource-conserving, cost-effective, and environment-friendly. (C) 2020 Elsevier Ltd. All rights reserved.