青海高原西宁城镇社区家庭能耗直接碳排放研究

选取青海高原城市西宁为研究对象，开展家庭能源消费问卷入户调查，建立高原城市家庭能源消费数据库(N=500)，采用探索性空间数据分析方法，总结分析家庭能耗碳排放的空间特征与驱动因素，得出以下结论：(1)西宁市家庭人均能源消费量与人均能耗碳排放平均值分别为10.57 kgce/d和6.11 kg/d，取暖、厨房设备及热水器设备是家庭能耗及碳排放的主要来源；(2)西宁市人均家庭能源消费碳排放总体呈现出高值区(HH)、低值区(LL)相对集聚，而局部地区也存在高低值区(HL)和低高值区(LH)集聚现象，其空间规律呈现明显的异质性；(3)家庭收入、地理环境以及建筑特征等因素是人均家庭能源消费碳排放空间异质性形成的主要因素。

Household energy consumption and carbon emissions in Xining on Qinghai Plateau

Chinese cities need to advance sustainable energy consumption and ensure carbon emission peak and carbon neutrality. The research topic of this paper is the relationship between urban growth in a Chinese plateau city and the factors driving households to consume different kinds of household energy and their carbon emissions. We select Xining, a plateau city in Qinghai, as the research object, conduct household energy consumption questionnaire household surveys, establish a plateau city household energy consumption database (N=500), and use spatial data analysis methods to analyze household energy consumption and carbon emissions. We found that: 1) The per capita energy consumption and per capita carbon emissions of households in Xining, a plateau city, are 10.57 kgce/d and 6.11 kg/d, respectively, heating, kitchen equipment, and water heater equipment are the main sources. What is more, the per capita energy consumption of Xining is 18 times that of Guangzhou (0.58 kgce/d), a global super city economy. However, the proportion of energy consumption of large household appliances in Xining is lower than that in Guangzhou, because Guangzhou households pay more attention to energy efficiency when purchasing household appliances and are more willing to buy energy-efficient products; 2) The carbon emission per capita household energy consumption in Xining City generally shows a relative concentration of high-value areas (HH) and low-value areas (LL), and there are also high and low-value areas in some areas. high and low-value areas (HL) and low- and high-value areas (LH) agglomeration phenomenon and its spatial law present obvious heterogeneity; 3) Factors such as household income, geographical environment, and building characteristics are the formation of spatial heterogeneity of per capita household energy consumption carbon emissions. We observe the diversity of energy transition by comparing the patterns of carbon emission from household energy consumption within the city. Then, a comprehensive picture of the diversity underlying the energy transition applied across cases can be distilled.