• Energy Research

Over the last 20 years, energy consumption in the residential sector in China has grown rapidly, and the growth is faster than that of any other energy form. To assess the limitations of the spatial characteristics of household energy consumption in urban areas, this paper selected Guangzhou as the research area. Specifically, the old town, core area, central area and peri-urban areas, which best reflect the evolutionary characteristics and spatial differentiation of households, were assessed. Based on the surveyed database of community-scale household energy consumption (N = 1097), the spatial heterogeneity of household energy consumption and carbon emissions at the community scale were assessed through exploratory spatial data analysis and the standard deviation ellipse method. The results report that (1) the main sources of energy consumption in Guangzhou households were water heating equipment, kitchen equipment and refrigeration equipment, which were related to the climatic conditions and cultural traditions of the city. (2) There was significant spatial heterogeneity in the carbon emissions from household domestic energy use in Guangzhou. (3) The economic level, the effects of the Lingnan culture and the characteristics of residents are the main drivers influencing the spatial characteristics of household energy consumption and carbon emissions in Guangzhou. We propose that policy development should actively promote energy-efficient equipment, such as water heating and cooling equipment, in urban households and take full account of the basic household energy needs of residents in old urban and suburban areas while promoting the development of low-carbon buildings.

Although it's well known that the carbon intensity from passenger transport of cities varies widely, few studies assessed the disparities of that in city-level and its underlying factors due to the limited availability of data, and thus developed effective strategies for different types of cities. This study is the first to present a comprehensive inventory of emissions from passenger transport on road for 360 cities in mainland China for 2018, based on the data from 5 transport modes and evaluated by combining distance-based and top-down fuel-based methods. In 2018, passenger transport on road in China emitted 1076 MtC. A large portion of CO2 emissions was identified in the southern and eastern coastal areas and capital cities. GDP, population, and policy were the major factors determining the total CO2 emissions, but not carbon intensity. Clustering analysis of carbon intensity and 9 socio-economic predictors, using a tree-based regression model, clustered the 360 cities into 6 groups and showed that higher carbon intensities occurred in both affluent city groups with a high active population share and less affluent city groups with a low population density but high density of trip destinations. Forward-and-backward stepwise multiple regression analysis indicated that constructing a compact city is more effective for city groups with a high income and high active population share. Enhancing land-use mixed degree is more critical for city groups with a high income and low active population share, while shortening travel distance by intensifying infrastructure construction is more important for the less affluent city groups.

The prevalence of poverty and inequality in megacities often manifests as high levels of energy poverty and disparities in household energy consumption. A comprehensive survey of 2054 households in Beijing was conducted in 2023 to examine the dynamics of energy poverty within such an urban settings. As one of the world's most influential megacities, Beijing offers a distinct and insightful case study for understanding energy poverty in a rapidly urbanizing global context. Utilizing the 10 % and low-cost/high-income (LIHC) methods, we estimated that the energy poverty rate in Beijing ranges between 16.07 % and 17.53 %, with the highest rates observed in suburban areas. In addition, we explored the spatial differences in energy poverty and the root causes. Our research reveals a significant correlation between economic and geographical factors and the spatial distribution of energy poverty. Furthermore, our findings suggest that larger populations tend to be associated with reduced disparities in energy poverty across different areas. Therefore, we suggest promoting the use of energy-efficient installations, implementing time-sensitive heating systems, and providing electricity and hygienic cooking facilities.