Modeling carbon emission trend in China's building sector to year 2060
Introduction
As the world's largest carbon emission country, the carbon emission mitigation actions of China play an important role in mitigating the global climate change (Liu et al., 2015). Therefore, the Chinese government has announced its aggressive carbon emission goals of achieving carbon peak in 2030 (UNFCCC, 2015) and carbon neutrality in 2060 (Zhao et al., 2022). As one of the three major final energy consumption and carbon emission sectors in China (Ma et al., 2020), the building sector produced 2.11 billion tons of CO2 (BtCO2) in 2018, accounting for 21.90% of China's energy-related carbon emission (CABEE, 2020). Compared with the developed countries, the per capita building area and building end-use service demand are still low in China. According to the data of International Energy Agency (IEA, 2021b), the per capita building energy intensity in China is only 21%, 72%, and 23% of that in the US, Japan, and the UK, respectively. Therefore, in future, with an increase in residents’ income and development of tertiary industry, the energy consumption of China's building sector will continuously face a strong increasing trend in its carbon emissions (Ramaswami et al., 2016), which will severely hinder the realization of China's carbon peak and neutrality goals (Ma et al., 2019; Zhang et al., 2022a).
It is worth noting that, compared with the industry and transportation sectors, the building sector has more obvious carbon emission mitigation potential, and it may achieve cost savings and economic benefits through existing technologies and policies (IEA, 2020a; LNBL, 2016; McKinsey, 2013). The study of Lawrence Berkely National Laboratory (LNBL, 2016) reported that the building sector can achieve 74% carbon emissions by 2050. In practice, to limit the direct and indirect carbon emissions of the building sector of China, its multi government departments have published a series of severe policies such as the standard of building energy conservation and renewable energy utilization published by the Ministry of Housing and Urban-Rural Development (MOHURD, 2021), the plan of winter clean heating in northern area (2017–2021) published by the National Energy Administration (NEA, 2017), and the plan of carbon peak and carbon neutrality of electricity published by the State Grid (Grid, 2021). Considering the huge carbon emissions and obvious emission mitigation potential of China's building sector, it is necessary to formulate rational carbon emission trends and determine key emission mitigation strategies for achieving its carbon peak and carbon neutrality goals (Guo et al., 2021; Ma et al., 2020). Therefore, in this study, we aimed to address the following three key issues.
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What is the future carbon emission trend of China's building sector?
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What are the main driving factors of the future carbon emission trend of China's building sector?
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What would be the main emission mitigation strategies for China's building sector?
To solve the above issues, based on the characteristics of China's building sector, we first developed a multi-layer (climate areas, building types, and end-use services) dynamic carbon emission quantization model that covers most of the emission mitigation strategies derived from the present practical policies. Subsequently, to respond to issue 1, four combined scenarios (base scenario, single building sector scenario, collective effort of multi sectors scenario, collective of over society scenario) were developed to forecast the future carbon emissions. Finally, the logarithmic mean Divisia index (LMDI) decomposition method was adopted to identify the main driving factors for the future carbon emission trend and to quantify the emission mitigation contribution of each strategy at the national and building type levels, as responses to issues 2 and 3, respectively.
The most significant contribution of this study is the multi-layer dynamic emission quantization model. To investigate energy consumption emission trends, existing studies have established different models. Xu and Wang (2020) employed the a “stochastic impacts by regression on population, affluence, and technology” (STIRPAT) model to established the energy consumption outlook of China's building sector in 2100. However, this model doesn't integrate the building characteristics. To address this gap, Tan et al. (2018) and Guo et al. (2021) developed models that consider the four building types: urban residential buildings, rural residential buildings, public and commercial buildings and central heating. The model developed by Delmastro et al. (2015) considered the impact of climate and merged five of China's climate zones into three: northern (cold and severe cold region), transition (hot summer and cold winter region), and southern areas (hot summer and warm winter as well as moderate regions). The model developed by Yang et al. (2017) followed a bottom-up framework and integrated six end-services demands (heating, cooling, lighting, cooking, hot water, and other appliances). Furthermore, the model developed by Ma et al. (2020) considered the uncertainty of parameters and established the distribution of carbon peak time and value of China’ commercial and public buildings. However, these models have some limitations. 1) Generally, the models directly set the future building area target and technique-related parameters separately, ignoring the relationship between techniques renovation and metabolism (Yang et al., 2022); for example, the renovation of building envelop technique occurs during building energy renovation or constructing the new buildings. Owing to such limitations, these models do not match with practical policies and provide limited guidance on the formulation of policies. For example, carbon peak action in the building sector required the new building to adopt a building energy efficiency standard, rather than implement a certain percentage reduction in average energy consumption unit area of overall building sector. To solve this problem, this study employed a building stock turnover model was employed to represent the techniques renovation. 2) To formulate reasonable decarbonization pathway, existing studies have attempted to set scenarios based on single or a combination of policies (Huo et al., 2021; Li et al., 2021; Tan et al., 2018). However, most policies are concentrated in building sector, such as optimizing building design, building energy renovation, and improving end-use service equipment energy efficiency (Huo et al., 2021; Li et al., 2021; Tan et al., 2018). In practice, the building sector is one of top three final energy consumption sectors, its indirect carbon emissions derived from electricity and heating generation account for a larger proportion than direct carbon emissions. Therefore, emission mitigation action of other sectors has an obvious impact on formulating emission mitigation strategies for the building sector, such as building electrification and decarbonization of electricity generation. In the study, the model parameters covered the emission mitigation strategies within the building sector as well as in other sectors (heating and electricity generation sector). As the proposed model addressed the abovementioned gaps, it can be used as a valuable policy simulation tool to test policy effectiveness and provides better guidance on formulation of policy-making of building sector's decarbonization.
This paper is structured as follows. Section 2 introduces the quantization model for carbon emissions of China's building sector, the emission mitigation strategies, and four combined scenarios. Additionally, the LDMI model is presented in this section. The simulation results of the models are analyzed in Section 3. The key driving factors for future emission trends are discussed in Section 4. The main emission strategies for building sector at the national and building type levels are discussed in Section 5. Section 6 compares this study with existing studies. Finally, Section 7 describes the main findings and implications of this study, along with recommendations for future research.
Section snippets
Model framework
We first developed a multi-layers Chinese building carbon emissions model to quantify the future carbon emission and energy consumption of China's building sector. The framework is shown in Fig. 1.
The first advantage of the model is that it fully considers the energy utilization characteristics of Chinese buildings. Specifically, the framework included three layers: 1) L1, Climate area. The climatic conditions have a significant impact on the heating and cooling energy consumption of buildings.
Carbon emissions of China's building sector at the national level
Combining with the parameters of four combined scenarios, the model simulates the future carbon emissions of China's building sector. Fig. 2 shows the carbon emissions, energy consumption, and emission structure of China's building sector for each scenario until 2060. For the base scenario, China's building sector will achieve the carbon peak, with carbon emissions of 2.52 BtCO2 and energy consumption of 0.77 billion tons of standard coal equivalent (Btce), in 2033, which is three years later
Driving factors of future carbon emissions in China's building sector
Based on the Kaya identity, the carbon emissions of China's building sector are divided into six driving factors: demand in end-use services, technique in end-use services, energy-related emission factor, per capita floor area, urbanization, and population. The future carbon emissions in the base scenario were decomposed to identify the key driving factor of their major driving factors, and the period of base scenario was divided into two stages: from the base year to the carbon peak year
Emission mitigation strategies at national level
In this study, we decomposed the gap of carbon emissions between the base scenario and the best scenario (CS3) in 2060 to quantify the emission mitigation and final energy saving potential of 10 stronger strategies. Fig. 6 represents the emission mitigation contribution of strategies in 2060. The top three emission mitigation strategies are decarbonization of electricity generation (M6: 47.85%, 0.46 BtCO2), building stock regulation (M9: 14.24%, 0.14 BtCO2), and residential green behavior
Comparing with existing studies
To ensure the accuracy and robustness of the historical data and simulation results, we compared the results of this study and those of existing literature. For historic data, we selected the building stock and carbon emission of China's building sector to build the comparison. Fig. 9a presents the carbon emission of China's building sector in 2019. The carbon emission in this study was 2.17 BtCO2, which was slightly higher than the results of Hu et al. (2022): 2.16 BtCO2; IEA (2021a): 2.09 BtCO
Conclusions and future research directions
In this study, we proposed a multi-layer dynamic carbon emission quantification model to forecast the potential future emission trend of China’ building sector up to 2060. Furthermore, the detailed future carbon emission trend in four buildings types and three climate zones were explored. In addition, the LDMI decomposition method was used to identify to the main driving factors for future carbon emission trend and key emission mitigation strategies for each building type. The main conclusions
CRediT authorship contribution statement
Kairui You: Conceptualization, Validation, Methodology, Visualization, Formal analysis, Writing – original draft. Hong Ren: Conceptualization, Formal analysis, Writing – review & editing. Weiguang Cai: Conceptualization, Data curation, Validation, Writing – review & editing. Ruopeng Huang: Formal analysis, Visualization, Writing – review & editing. Yuanli Li: Formal analysis, Visualization, Writing – review & editing.
Declaration of Competing Interest
The author(s) declare no potential conflicts of interest for the research, authorship, and/or publication of this article.
Acknowledgements
The authors would like to acknowledge financial support provided by the National Social Science Fund of China (19BJY065). The authors are grateful to the editors and the anonymous reviewers for their insightful comments and suggestions.
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