Abstract
Urban energy consumption is mostly concentrated in industrial regions, and carbon emissions from industrial land use have significantly increased as a result of fast urbanization and industrialization. In the battle against climate change, the affluent regions of developing countries are increasingly being used as models for reducing carbon emissions. Therefore, in order to accomplish global sustainable development, it is crucial to understand how industrial land use and carbon emissions are decoupled in wealthy areas of rising nations. This study investigates the decoupling effects and the factors influencing them in six East Chinese provinces and one city between 2005 and 2020 using the Tapio decoupling model and the LMDI decomposition approach. At the same time, the industrial carbon emissions from 2021 to 2035 were predicted using a BP neural network model combined with scenario analysis. The findings indicate that: (1) From 29.921 million tons in 2005 to 40.2843 million tons in 2020, the carbon emissions from industrial land in the East China area have nearly doubled. Of these, Shandong and Jiangsu emit more than half of the region's total emissions around East China. (2) The decoupling effect analysis shows the East China region's decoupling trajectory's phased characteristics, with the degree of decoupling gradually increasing from weak decoupling (2006-2012) to strong decoupling (2013-2018) and finally to negative decoupling (2019-2020). (3) The primary causes of the rise in carbon emissions in the East China region are the scale of per capita economic output and industrial land use. (4) The overall industrial carbon peak time in East China is roughly distributed between 2028 and 2032. It is expected that Shanghai, Shandong, Jiangsu, and Zhejiang will be among the first to achieve carbon emission peak.