System dynamics prediction and development path optimization of regional carbon emissions: A case study of Tianjin

Abstract

The prediction of regional carbon emissions and the optimization of development paths are particularly important. Regional heterogeneity leads to different links between carbon emissions and population, economy, industry, energy, environment, and other factors. However, most of the previous studies carried out the accounting, factor decomposition, prediction, and decision-making of regional carbon emissions alone, which failed to form the sustainable assessment of regional carbon emissions. Therefore, the carbon emissions coefficient, Logarithmic Mean Divisia Index, system dynamics model and Interlink Decision Making Index were selected in this study to establish the regional carbon emissions systems framework. In this study, a mega-city such as Tianjin was taken as an example, the comprehensive assessment and prediction of regional carbon emissions system was carried out. The results show the change in energy intensity had the strongest mitigation effect, reducing carbon emissions by 106.17 million tons in total, and the per capita GDP effect had the strongest promotion effect, with a cumulative contribution of 265.19 million tons of carbon emissions. Among all 13 scenarios in Tianjin, Scenario-12 is identified as the optimal development path and provides policy suggestions. The results of this study not only verify the effectiveness and necessity of the framework, but also provide guidance tools for regional carbon emissions development. The results of this study validate the effectiveness and necessity of the framework to provide guidance for the regional carbon emissions development path. The results of the case also provide help for the optimization of Tianjin's carbon emissions development path.