Scenario Prediction of Carbon Emission Peak of Urban Residential Buildings in China’s Coastal Region: A Case of Fujian Province

Abstract

With the acceleration of China’s urbanization process, the importance of energy conservation and emission reduction in the building sector has become increasingly prominent. The effective control of carbon emissions in coastal provinces has a decisive impact on achieving the carbon emissions peak target nationwide. Based on the analysis of the influencing factors, this study establishes an urban residential buildings carbon emission prediction model by combining the IPAT model and the ridge regression model. In addition, the prediction model is combined with scenario analysis to simulate the evolution of carbon emission trends of urban residential buildings in Fujian Province from 2018 to 2050 under different scenarios. The results show that total population, urban living area, residents’ consumption expenditure, urbanization rate, per capita GDP, and energy structure are key factors affecting carbon emissions from urban residential buildings in coastal cities. Only under the ultra-low carbon model scenario can Fujian’s urban residential buildings achieve the carbon peak goal in 2027 (13.4748 million tons of CO2), which requires a reduction of 59.67% compared to that under the baseline model scenario. This study can provide an effective reference for energy conservation and emission reduction work of the regional scale and even the national scale.

Prediction of carbon emissions from public buildings in China’s Coastal Provinces under different scenarios ——A case study of Fujian Province

“…Ke et al conducted carbon peak prediction research on residential buildings in coastal provinces, using Fujian Province as an example. They utilized scenario settings to determine the carbon peak situation under different scenarios and proposed feasible suggestions [ 17 ]. Geng et al studied the carbon emissions of urban residential buildings in the Guangdong-Hong Kong-Macao Greater Bay Area from a life cycle perspective, providing data references and recommendations for the low-carbon development path of urban residential buildings [ 18 ].…”

Research on Influencing Factors of Building Carbon Emissions in Extremely Cold Regions of China: A Case Study of Liaoning Province

“…Since a variety of factors impact carbon emissions in every stage of the whole life cycle of buildings, this paper chooses the largest consumption in each stage based on the results of the calculations. At the same time, based on the sorting of relevant references [4][5][6][7][8][9], the author selects cement, electric power, permanent resident population, the added value of the tertiary industry, the level of urbanization, the construction area, the labor productivity of construction enterprises, the total output value of the construction industry and energy intensity as the influencing factors.…”

“…In this study, the dependent variable is the carbon emissions of the construction industry in Liaoning Province, while the nine selected factors are the independent variables. The resulting influencing factor model of building carbon emissions in Liaoning Province is an exponential function, as shown in (7).…”

Flexible Regulation and Synergy Analysis of Multiple Loads of Buildings in a Hybrid Renewable Integrated Energy System

“…Increasing the energy efficiency and consumption ratio of renewable energy in building energy systems is the key path to building carbon reduction [6]. An integrated energy system employs advanced technology and management modes to meet various energy demands of buildings in various forms of energy supply, including electricity, heat, and gas [7].…”