Carbon emissions' spatial-temporal heterogeneity and identification from rural energy consumption in China. (15th February 2022) - Zhang, Hengshuo; Li, Shaoping
Abstract: Carbon emissions from industry and cities have been the focus of global carbon emissions control, but the need to reduce carbon emissions from large agricultural countries cannot be ignored. This study measured rural carbon emissions based on the energy consumption of rural residents and agricultural production from 2000 to 2018 in China, and the spatial-temporal evolution and variation of rural carbon emissions were analyzed using the quadrant diagram method and Theil index, which also further identified the contribution elements of rural carbon emissions. The gradual growth of rural carbon emissions in China's provinces has been accompanied by a spatial clustering of high emissions, and the carbon emissions among the country's eight regions are characterized by large inter-regional and small intra-regional differences. By identifying the carbon emissions contributions of regions and the carbon sources, we found that the provinces in the central region produce the most emissions, with the top 3 of 11 provinces contributing up to 61.56% of the total national production. Furthermore, emissions from the dominant carbon source in rural China, raw coal, has decreased to 49.22%, and the low use of electricity and natural gas results in the structure of rural carbon sources being weakly decarbonized. The decomposition of carbon emissions indicated that rural economic development plays a prominent contributory role in carbon emissions, whereas energy consumption per unit output value has a significant inhibitory effect on carbon emissions. This study contributes to current carbon emission-related research by identifying the main contributors of rural carbon emissions from multiple perspectives. Highlights: Rural carbon emission types present a low-speed - steady - high-speed evolution in China. Carbon emissions in rural China show large inter-area variance and small intra-area variance. Rural economic development factors have a promotional effect on rural carbon emissions. Rural energy consumption per unit of output has an obvious carbon suppression effect. Contribution identification provides governance orientation for rural carbon emissions.