Research on Influencing Factors of Residential Building Carbon Emissions and Carbon Peak: A Case of Henan Province in China

Abstract

Buildings are considered to have significant emission reduction potential. Residential building carbon emissions, as the most significant type of building-related carbon emissions, represent a crucial factor in achieving both carbon peak and carbon neutrality targets for China. Based on carbon emission data from Henan Province, a large province located in central China, between 2010 and 2020, this study employed the Kaya-LMDI decomposition method to analyze seven driving factors of carbon emission evolution, encompassing energy, population, and income, and assessed the historical reduction in CO2 emissions from residential buildings. Then, by integrating Kaya identity static analysis with Monte Carlo dynamic simulation, various scenarios were established to infer the future evolution trend, peak time, and potential for carbon emission reduction in residential buildings. The analysis results are as follows: (1) The carbon emissions of residential buildings in Henan exhibited a rising trend from 2010 to 2020, albeit with a decelerating growth rate. (2) Per capita household disposable income is the main driving factor for the increase in carbon emissions, but the household housing purchase index inhibits most of the growth of carbon emissions for the residential buildings in Henan, with the total carbon emission reduction of residential buildings reaches 106.42 million tons of CO2 during the research period. (3) During the period from 2020 to 2050, residential buildings in Henan Province will exhibit an “inverted U-shaped” trend in carbon emissions under the three static scenarios. The base scenario predicts that carbon emissions will reach their peak of 131.66 million tons in 2036, while the low-carbon scenario forecasts a peak of 998.8 million tons in 2030 and the high-carbon scenario projects a peak of 138.65 million tonnes in 2041. (4) Under the dynamic simulation scenario, it is anticipated that residential buildings in Henan Province will reach their carbon peak in 2036 ± 3 years, with a corresponding carbon emission of 155.34 million tons. This study can serve as a valuable reference for the future development of low-carbon pathways within the building sector.

Carbon Emission Projection and Carbon Quota Allocation in the Beijing–Tianjin–Hebei Region of China under Carbon Neutrality Vision

“…In terms of research methods on carbon emission drivers, structural decomposition analysis (SDA) [14,15], index decomposition analysis (IDA) [16][17][18], the STIRPAT model [19][20][21], and system dynamics [22,23] are the mainstream methods, as shown in Table 1. However, each research method has its own applicability and disadvantages.…”

“…The SDA method is often combined with the input-output model, which can analyze the endogenous relationship between departments or variables [14]. Luo et al [15] Influencing factors of carbon emissions in seven sub-sectors of China's power industry IDA Yang et al [16] Driving factors of carbon emissions from residential construction industry in Henan Province, China…”

“…The calculation method of the IDA model is simple and easy to operate, and the decomposition result has no residual value [16].…”

Low-Carbon Optimization Design for Low-Temperature Granary Roof Insulation in Different Ecological Grain Storage Zones in China

“…Andrade et al [10] carried out studies on the carbon reduction potential of ultra-low-energy buildings in severely cold regions of China using an optimization method combining meta-models. Yang et al [11] investigated seven driving factors of carbon emission evolution, encompassing energy, population, and income, and assessed the historical reduction in CO 2 emissions from residential buildings in Henan Province in China using the Kaya-LMDI decomposition method. Yang et al [12] systematically examined the value, potential, challenges, and improvement path of China's green hydrogen industry.…”

Analysis of the Spatial and Temporal Evolution of Energy-Related CO2 Emissions in China’s Coastal Areas and the Drivers of Industrial Enterprises above Designated Size—The Case of 82 Cities

“…A review of the literature showed that there is room for expanding the existing studies: In terms of research regions, most studies have focused on China as a whole [3][4][5], provinces [35], urban agglomerations [36][37][38][39][40][41] and key cities [7,29]. Among these, urban agglomerations are mainly coastal urban agglomerations with high levels of economic development such as Beijing Tianjin Hebei, the Yangtze River Delta, Guangdong, Hong Kong, Macao and Chengdu Chongqing, as well as the Yellow River Basin, Liaoning and the Central South urban agglomerations and other important Chinese areas with high energy usage.…”