基于LMDI与Kaya恒等式的上海市碳排放驱动力分析及预测OA

Shanghai,a typical representative of China's rapid economic growth and urbanization,provides critical insight for regional and national low-carbon transitions through its carbon emission drivers and evolutionary pathways.This study developed an integrated forecasting model by combining the logarithmic mean divisia index(LMDI)decomposition method with the Kaya identity to analyze driving factors and project emission trends under three scenarios(baseline,low-carbon,and carbon neutrality)for 2025-2060.Results show that economic expansion and population growth were positive drivers of carbon emissions,with economic scale being the most prominent contributor.Conversely,industrial structure upgrading,energy efficiency improvement,and energy decarbonization effectively suppressed emission growth.Long-term projections reveal distinct evolution paths:the baseline scenario maintains high emissions,hindering carbon neutrality goals;the low-carbon scenario demonstrates substantial reduction potential through enhanced policy and technological advances;and the carbon neutrality scenario outlines an ideal low-carbon path through deep decarbonization and electrification.Future carbon governance in Shanghai should shift from efficiency-focused measures to structural optimization and institutional innovation,providing a practical example for decarbonizing energy,industrial,and urban systems.