Elsevier

Energy and Buildings

Volume 253, 15 December 2021, 111485
Energy and Buildings

Spatiotemporal decomposition analysis of carbon emissions on Chinese residential central heating

https://doi.org/10.1016/j.enbuild.2021.111485Get rights and content

Abstract

Residential central heating (RCH) is an important part of residents’ well-being policy. However, it is accompanied by extensive energy consumption and carbon emissions. To identify and design efficient future clean heating strategies, we quantified the carbon emissions from RCH in China from 2000 to 2017. Notably, our study is the first to analyze the driving factors of RCH carbon emissions using decomposition analysis and introduce the climate parameter into the Kaya identity. The following results were obtained. 1) The RCH carbon emissions reached the flection point in 2016 (321.75 MtCO2). 2) Area-related energy intensity is the key driving factor to mitigate carbon emissions of RCH; the area-related carbon intensity in 2017 was one-third less than that in 2000. Conversely, per capita residential heating area and urban population increased carbon emissions from RCH. 3) At the provincial level, the recommended emission mitigation strategies were different. For example, Heilongjiang and Jilin should focus on decreasing the emission factors, whereas Shandong and Xinjiang need to focus on decreasing the area-related energy intensity. The results of this study can help governments to formulate more rational and feasible policies for the emission road map, and the targeted advice also offers a reference for future studies.

Introduction

China has the highest carbon emissions globally, and therefore, the country’s emission mitigation actions are significant to mitigate climate change and maintain the sustainable development of human society [1]. As a responsible country, China acknowledged that its carbon emissions will peak in 2030 and carbon emissions per unit of gross domestic product (GDP) in 2030 will decrease by 60–65% compared to 2015 [2]. Furthermore, during the 75th session of the United Nations General Assembly (UNGA), China announced an ambitious emission target: to be carbon neutral by 2060. Notably, one of the major challenges for China, a developing country, is to achieve the carbon emission mitigation while meeting the growing demands of its residents [3].

There is a substantial demand for heating in northern China due to the extremely cold and long winter duration [4]. Therefore, China has adopted a central heating policy in the area north of the Qinling Mountains and Huaihe River; this is one of the most important policies for people's livelihood in China [5]. Central heating is considered to be one of the dominant causes of emissions and energy consumption in China [6], and carbon emission mitigation in central heating is important for achieving the carbon neutral target. In the past decades, China's energy consumption and emissions from residential central heating (RCH) have increased significantly due to rapid urbanization and population growth [4]. According to the China Association of Building Energy Efficiency (CABEE) [7], the carbon emission of RCH accounts for approximately 28% of a residential building's carbon emissions. Additionally, the high area-related energy intensity of RCH in China, which is 2–3 times that of developed countries, is often criticized.

RCH in China is generated by burning fossil fuels, especially coal, which, in 2015, accounted for more than 90% of total energy structure [3]. Thus, RCH results in high carbon emissions, and generates a variety of toxic and harmful substances [8], such as sulfur dioxide [9] and PM2.5. Central heating poses a serious threat to China's environment and the health of its residents [5]. Studies have confirmed that current central heating policies have increased the death rate from heart and lung diseases and reduced life expectancy of residents living in northern China [8], [10], [11], [12]. Therefore, the Chinese government proposed a series of strict policies and pollution control plans to limit the negative impacts of RCH. For example, in 2017, China Ministry of Environmental Protection (CMEE) proposed the “2 + 26” Cities Interim Policy on Urban Air Pollution Control [13], which mandates rigorous standards on boilers in China's Beijing–Tianjin–Hebei region. And this policy implementing the “coal to electricity” and “coal to gas” boiler renewal policies and prohibiting the use of medium and small boilers [13]. In the same year, the National Development and Reform Commission (NDRC) and nine other departments released the “Clean Heating Plan for Northern Regions in Winter” (2017–2021), the plan mandated clean heating rates of 60% and 89% in Chinese cities to be in 2019 and 2021, respectively [14]. The country has a heating mode dominated by coal-fired and cogeneration boilers; however, the use of gas-fired boilers is increasing continuously [3].

Currently, China is in a critical period of heating reform and development. To formulate rational policies and realize the emission mitigation goals of the heating industry in the future, it is important for China to clarify its historical emission trends and major driving factors of RCH carbon emissions and understand the main issues regarding heating emission mitigation in different regions. Therefore, in this study, we addressed the following three questions:

  • What was the RCH trend in China in recent decades?

  • What are the main driving factors of RCH at the national and provincial levels?

  • How to develop a rational RCH policy of different provinces and accelerate RCH emission mitigation?

To answer these questions, our study first quantified the provincial-level CO2 emissions from RCH for the period 2000–2017. Second, the effects of driving factors on central heating emissions were analyzed by combining the logarithmic mean Divisia index (LMDI) with an extended Kaya identity. Finally, using a spatial LMDI decomposition method, the main interprovincial differences of RCH were analyzed and corresponding emission mitigation strategies were proposed.

This paper is structured as follows: Section 2 conducts a literature review on central heating and decomposition methods. Section 3 introduces the method used to quantify carbon emissions from RCH, develops the RCH emission model using the Kaya identity, and introduces the main calculation flow of the spatiotemporal LMDI model. Section 4 presents and analyzes the results of the models. Section 5 discusses and recommends the main emission mitigation strategies for each province. Finally, Section 6 describes the main findings and implications of our study, along with recommendations for directions of future research.

Section snippets

Studies on central heating

Considering the associated high energy consumption and serious pollution, extensive studies have been conducted on heating. With respect to the quantification of carbon emissions from central heating [15], using data from Yearbook, Du et al. [3] quantified the CO2 emission in China from the central heating supply system for the period 2006–2015, along with quantifying the proportion distribution of coal-fired, cogeneration, and gas-fired boilers at the provincial level. Zhang et al. [4] and Cui

Quantification of Carbon Emissions from Central Heating

The carbon emissions from residential central heating were calculated using the following formula:C=EFheating×Eheatingwhere Eheating represents the heating power (data obtained from the China Urban and Rural Construction Statistical Yearbook, CURCSY) and EFheating represents the emission factor of heating power. EFheating was calculated using the following equation:EFheating=Ei'×EFiEheating'where Ei represents the consumption of fuel i used to product heating power, ′ represents the data from

National level carbon emissions residential central heating (RCH)

In Fig. 1a, we can observe that during the study period, although the area-related carbon intensity (CI) continuously decreased from 124.97 kgCO2/m2 to 49.61 kg CO2/m2, the carbon emissions from RCH increased to 321.75 MtCO2 and reached the inflection point in 2016. Furthermore, the emission factor of RCH (represented by a converse-U shape) peaked in 2007 (3.6 kgCO2/kgce) and was 3.40 kgCO2/kgce in 2017.

These results were mainly attributed to three reasons: 1) Improvement in boiler efficiency

Impact of climate parameter on residential central heating (RCH)

The most important hypothesis of this study is that climate parameter has a significant impact on the inter-province EI differences in RCH. To confirm this hypothesis, we selected the coefficient of variation (CV, standard deviation/mean), which can eliminate dimensional effects, to test the inter-province EI differences in RCH. As shown in Table 1, in the past years, the CV of EI has obviously decreased from 0.599 in 2005 to 0.332 in 2015, indicating the inter-province EI differences in RCH

Main conclusions

We quantified the historic carbon emission trend of RCH and analyzed the driving factors of RCH carbon emissions and interprovincial EI differences using spatiotemporal decomposition. Furthermore, by combining the study results with the performance of different parameters in each province, we have suggested a few future clean heating strategies to mitigate future RCH emissions. The main results are as follows:

RCH carbon emissions reached an inflection point of 321.75 MtCO2 in 2016. Although the

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The authors would like to acknowledge financial support provided by Fundamental Research Funds for the Central Universities (No. 2020CDJSK03XK15), the National Social Science Fund of China (19BJY065), and Graduate research and innovation foundation of Chongqing, China (CYS18052). The authors are grateful to the editors and the anonymous reviewers for their insightful comments and suggestions.

References (53)

  • B. Lin et al.

    Evaluating energy conservation in China's heating industry

    J. Clean. Prod.

    (2017)
  • X. Zhao et al.

    Residential energy consumption in urban China: A decomposition analysis

    Energy Policy

    (2012)
  • L. Zhang et al.

    The increasing district heating energy consumption of the building sector in China: Decomposition and decoupling analysis

    J. Clean. Prod.

    (2020)
  • S. Hu et al.

    Urban residential heating in hot summer and cold winter zones of China—Status, modeling, and scenarios to 2030

    Energy Policy

    (2016)
  • H. Zhang et al.

    Decarbonizing a large City's heating system using heat pumps: A case study of Beijing

    Energy

    (2019)
  • R. Zhang et al.

    Is geothermal heating environmentally superior than coal fired heating in China?

    Renew. Sustain. Energy Rev.

    (2020)
  • Q. Zhang et al.

    Techno-economic analysis of air source heat pump applied for space heating in northern China

    Appl. Energy

    (2017)
  • W. Wang et al.

    Study on substitutable value of electric heating instead of coal heating in northern China under carbon constraints

    J. Clean. Prod.

    (2020)
  • M. Carlsson et al.

    Investigating the potential impact of a compartmentalization and ventilation system retrofit strategy on energy use in high-rise residential buildings

    Energy Build.

    (2019)
  • J. Lee et al.

    Exploring the localization process of low energy residential buildings: A case study of Korean passive houses

    J. Build. Eng.

    (2020)
  • L. Garcia-Ceballos et al.

    Life cycle study of different constructive solutions for building enclosures

    Sci. Total Environ.

    (2018)
  • S. Saboor et al.

    Strategic design of wall envelopes for the enhancement of building thermal performance at reduced air-conditioning costs

    Environ. Res.

    (2021)
  • C. Piccardo et al.

    Retrofitting a building to passive house level: A life cycle carbon balance

    Energy Build.

    (2020)
  • A. Stephan et al.

    A comprehensive assessment of the life cycle energy demand of passive houses

    Appl. Energy

    (2013)
  • B. Ang et al.

    Factorizing changes in energy and environmental indicators through decomposition

    Energy

    (1998)
  • C. Zheng et al.

    Characteristics of CO2 and atmospheric pollutant emissions from China’s cement industry: A life-cycle perspective

    J. Clean. Prod.

    (2021)
  • Cited by (25)

    View all citing articles on Scopus
    View full text