[Evolution and Simulation Prediction of Carbon Emissions from Energy Consumption in China].
摘要
The dilemma of energy consumption in the epic engine of economic development has led to relatively uncontrolled growth of carbon emissions. However， scientific estimation and dynamic monitoring of the development of regional energy consumption carbon emissions can provide forward-looking guidance for the implementation of the goal of carbon peak attainment. Based on China's energy consumption data from 2000 to 2020， the IPCC method was used to measure the total energy consumption carbon emissions and characterize their spatial and temporal characteristics， and the geographic probe model was used to reveal the key factors affecting the spatial variation of energy consumption carbon emissions within China. At the same time， it was used as the adjustment parameter of the "economy-energy-public services-carbon emission" SD model， and four development scenarios were established to simulate and forecast China's carbon emissions from 2020 to 2060. The study produced several interesting results： ① China's total carbon emissions from energy consumption show an overall fluctuating increase with time， and the growth curve gradually converges， evolving from a "double M-shape" to a "flat S-shape" curve. They also show the non-equilibrium spatial characteristic of being high in the north and low in the south. ② The main influencing factor changes from industrial structure in 2000 to economic level in 2010 and 2020， and the interaction of different factors shows a significant nonlinear enhancement. Among these， economic level and science and technology innovation are always the dominant combination affecting the spatial distribution of carbon emissions from energy consumption， with an explanatory power of 0.943 6 in 2010. ③ The SD model prediction results show that the peak times of the baseline， structural adjustment priority， energy conservation and emission reduction priority， and comprehensive and coordinated development scenarios are 2037， 2033， 2031， and 2029， respectively，