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ORIGINAL RESEARCH
Research on Public Building Carbon Emission
Peak Paths in Mid-Latitude Inland Areas Based
on LEAP Model: Case of Shanxi Province
1
School of Electric Power, Civil Engineering and Architecture, Shanxi University, Taiyuan, 030006, Shanxi, China
Submission date: 2024-08-27
Final revision date: 2024-09-11
Acceptance date: 2024-10-13
Online publication date: 2024-12-04
Publication date: 2025-11-04
Corresponding author
Yingying Xiong
School of Electric Power, Civil Engineering and Architecture, Shanxi University, Taiyuan, 030006, Shanxi, China
School of Electric Power, Civil Engineering and Architecture, Shanxi University, Taiyuan, 030006, Shanxi, China
Pol. J. Environ. Stud. 2025;34(6):7967-7981
KEYWORDS
TOPICS
ABSTRACT
There is an emphasis on urban carbon peaking in the building industry, and public buildings (PB) are
the major source of building industry carbon emissions. This research develops a model for forecasting
PB’s carbon emissions in Shanxi Province by using the LEAP model to analyze the carbon peaking
time and carbon emission level under various scenarios for PB in Shanxi Province in 2021–2050.
The findings indicate that: (1) The baseline scenario and the control area scenario do not reach the peak
during the forecast period; the energy-saving scenario is synchronized with China’s peak carbon target
to peak in 2030; the green scenario is the optimal scenario set in this research and reaches the peak
in 2025. (2) Controlling the public building area moderately can decrease carbon emissions and energy
consumption to a great extent. (3) Carbon emissions can be reduced and peak times brought forward
by reducing energy intensity, adjusting the energy structure, cleaning the heat network, and cleaning
the grid. Finally, according to the prediction results, the carbon peak path of PB in Shanxi Province
provides useful references for public building carbon emission reduction in the mid-latitude inland
areas.
CONFLICT OF 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.
REFERENCES (59)
1.
LI Y., LAN S., RYBERG M., PÉREZ-RAMÍREZ J., WANG X. A quantitative roadmap for China towards carbon neutrality in 2060 using methanol and ammonia as energy carriers. Science. 24 (6), 2021. https://doi.org/10.1016/j.isci... PMid:34142029 PMCid:PMC8188369.
2.
LIU Z., YU C., QIAN Q.K., HUANG R., YOU K., VISSCHER H., ZHANG G. Incentive initiatives on energy-efficient renovation of existing buildings towards carbon-neutral blueprints in China: Advancements, challenges and prospects. Energy and Buildings. 296 (2), 113343, 2023. https://doi.org/10.1016/j.enbu....
3.
LU M., LAI J. Review on carbon emissions of commercial buildings. Renewable and Sustainable Energy Reviews. 119 (1-2), 109545, 2020. https://doi.org/10.1016/j.rser....
4.
ZHANG C., LUO H. Research on carbon emission peak prediction and path of China's public buildings: Scenario analysis based on LEAP model. Energy and Buildings. 289, 113053, 2023. https://doi.org/10.1016/j.enbu....
5.
HUO T., XU L., LIU B., CAI W., FENG W. China's commercial building carbon emissions toward 2060: An integrated dynamic emission assessment model. Applied Energy. 325, 119828, 2022. https://doi.org/10.1016/j.apen....
6.
GAN L., LIU Y., CAI W. Carbon neutral projections of public buildings in China under the shared socioeconomic pathways: A tertiary industry perspective. Environmental Impact Assessment Review. 103 (1), 107246, 2023. https://doi.org/10.1016/j.eiar....
7.
UNIVERSITY B.E.C.R.C.O.T. China Building Energy Efficiency Annual Development Research Report 2023 (Urban Energy Systems Theme). China Architecture & Building Press, Beijing, 2023.
8.
LI R., YOU K., CAI W., WANG J., LIU Y., YU Y. Will the southward center of gravity migration of population, floor area, and building energy consumption facilitate building carbon emission reduction in China? Building and Environment. 242 (7830), 110576, 2023. https://doi.org/10.1016/j.buil....
9.
LIU Q., GAO J., CAI W., HUO T., LI R. A novel allocation method of regional carbon allowance in building sector: Perspective from coupling equity and efficiency. Environmental Impact Assessment Review. 102, 107192, 2023. https://doi.org/10.1016/j.eiar....
10.
YU S., LIU X., YANG J., HAN F., WEI J. The optimization research on the coupled of active and passive energy supplying in public institutions in China. Energy and Built Environment. 5 (2), 288, 2024. https://doi.org/10.1016/j.enbe....
11.
MA M., MA X., CAI W., CAI W. Low carbon roadmap of residential building sector in China: Historical mitigation and prospective peak. Applied Energy. 273 (C), 115247, 2020. https://doi.org/10.1016/j.apen....
12.
TAN X., LAI H., GU B., ZENG Y., LI H. Carbon emission and abatement potential outlook in China's building sector through 2050. Energy Policy. 118, 429, 2018. https://doi.org/10.1016/j.enpo....
13.
LIN C., LI X. Carbon peak prediction and emission reduction pathways exploration for provincial residential buildings: Evidence from Fujian Province. Sustainable Cities and Society. 102, 2024. https://doi.org/10.1016/j.scs.....
14.
MAHMOUDZADEH P., HU W., DAVIS W., DURMUS D. Spatial efficiency: An outset of lighting application efficacy for indoor lighting. Building and Environment. 255, 2024. https://doi.org/10.1016/j.buil....
15.
LI J., WANG M., FANG P., ZHAO Q., ZHENG X., GAO H. Modeling and optimization of a passive building HVAC system based on improved PSO and H-J Algorithm. Energy Reports. 11, 2415, 2024. https://doi.org/10.1016/j.egyr....
16.
ZHAO H., WU Y., SUN H., LIN B., ZHONG M., JIANG G., WU S. A novel building envelope combined with jumping-droplet thermal diode: From theory to practice. Renewable Energy. 218 (C), 2023. https://doi.org/10.1016/j.rene....
17.
WEERATUNGE H., ADITYA G.R., DUNSTALL S., DE HOOG J., NARSILIO G., HALGAMUGE S. Feasibility and performance analysis of hybrid ground source heat pump systems in fourteen cities. Energy. 234 (4), 2021. https://doi.org/10.1016/j.ener....
18.
SADATIFAR S., JOHLIN E. Multi-objective optimization of building integrated photovoltaic solar shades. Solar Energy. 242, 191, 2022. https://doi.org/10.1016/j.sole....
19.
HARTER H., WILLENBORG B., LANG W., KOLBE T.H. Life Cycle Assessment of building energy systems on neighbourhood level based on semantic 3D city models. Journal of Cleaner Production. 407, 137164, 2023. https://doi.org/10.1016/j.jcle....
20.
SHEN Y., PAN Y. BIM-supported automatic energy performance analysis for green building design using explainable machine learning and multi-objective optimization. Applied Energy. 333 (C), 2023. https://doi.org/10.1016/j.apen....
21.
BHATT M.S., RAJKUMAR N., JOTHIBASU S., SUDIRKUMAR R., PANDIAN G.S., NAIR K.R.C. Commercial and residential building energy labeling. Journal of Scientific and Industrial Research. 64, 30, 2005.
22.
MO C., PARK H.-C. Comparison of building energy demand for hotels, hospitals, and offices in Korea. Energy. 92, 383, 2015. https://doi.org/10.1016/j.ener....
23.
FRANCO A., MISEROCCHI L., TESTI D. A method for optimal operation of HVAC with heat pumps for reducing the energy demand of large-scale non residential buildings. Journal of Building Engineering. 43 (1), 103175, 2021. https://doi.org/10.1016/j.jobe....
24.
XUE Z., JIANG Y. Energy consumption and energy saving potential analysis for large-scale public buildings in Beijing. Heating Ventilating & Air Conditioning. 8, 2004.
25.
WU Z., SHI X., FANG F., WEN G., MI Y. Co-optimization of building energy systems with renewable generations combining active and passive energy-saving. Applied Energy. 351 (1), 121514, 2023. https://doi.org/10.1016/j.apen....
26.
QIU G., LI K., CAI W., YU S. Optimization of an integrated system including a photovoltaic/thermal system and a ground source heat pump system for building energy supply in cold areas. Applied Energy. 349 (C), 121698, 2023. https://doi.org/10.1016/j.apen....
27.
EL-SAYED A.H.A., KHALIL A., YEHIA M. Modeling alternative scenarios for Egypt 2050 energy mix based on LEAP analysis. Energy. 266 (4), 126615, 2023. https://doi.org/10.1016/j.ener....
28.
WU W., ZHANG T., XIE X., HUANG Z. Regional low carbon development pathways for the Yangtze River Delta region in China. Energy Policy. 151 (5), 112172, 2021. https://doi.org/10.1016/j.enpo....
29.
HUO T., XU L., FENG W., CAI W., LIU B. Dynamic scenario simulations of carbon emission peak in China's city-scale urban residential building sector through 2050. Energy Policy. 159, 112612, 2021. https://doi.org/10.1016/j.enpo....
30.
CHEN H., CHEN W. Carbon mitigation of China's building sector on city-level: Pathway and policy implications by a low-carbon province case study. Journal of Cleaner Production. 224, 207, 2019. https://doi.org/10.1016/j.jcle....
31.
LI R., LIU Q., CAI W., LIU Y., YU Y., ZHANG Y. Echelon peaking path of China's provincial building carbon emissions: Considering peak and time constraints. Energy. 271 (7830), 127003, 2023. https://doi.org/10.1016/j.ener....
32.
ZHU W., HUANG B., ZHAO J., CHEN X., SUN C. Impacts on the embodied carbon emissions in China's building sector and its related energy-intensive industries from energy-saving technologies perspective: A dynamic CGE analysis. Energy and Buildings. 287 (6), 112926, 2023. https://doi.org/10.1016/j.enbu....
33.
CONG X., ZHAO M., LI L. Analysis of Carbon Dioxide Emissions of Buildings in Different Regions of China Based on STIRPAT Model. Procedia Engineering. 121, 645, 2015. https://doi.org/10.1016/j.proe....
34.
MAVROMATIDIS G., OREHOUNIG K., RICHNER P., CARMELIET J. A strategy for reducing CO2 emissions from buildings with the Kaya identity - A Swiss energy system analysis and a case study. Energy Policy. 88, 343, 2016. https://doi.org/10.1016/j.enpo....
35.
ZHANG J., YAN Z., BI W., NI P., LEI F., YAO S., LANG J. Prediction and scenario simulation of the carbon emissions of public buildings in the operation stage based on an energy audit in Xi'an, China. Energy Policy. 173, 113396, 2023. https://doi.org/10.1016/j.enpo... https://doi.org/10.1016/j.enpo... https://doi.org/10.1016/j.enpo....
36.
PRINA M.G., MANZOLINI G., MOSER D., NASTASI B., SPARBER W. Classification and challenges of bottom-up energy system models-A review. Renewable and Sustainable Energy Reviews. 129, 109917, 2020. https://doi.org/10.1016/j.rser....
37.
LIU Y., CHEN S., JIANG K., KAGHEMBEGA W.S.-H. The gaps and pathways to carbon neutrality for different type cities in China. Energy. 244, 122596, 2022. https://doi.org/10.1016/j.ener....
38.
SUBRAMANYAM V., AHIDUZZAMAN M., KUMAR A. Greenhouse gas emissions mitigation potential in the commercial and institutional sector. Energy and Buildings. 140, 295, 2017. https://doi.org/10.1016/j.enbu....
39.
KUSUMADEWI T.V., LIMMEECHOKCHAI B. CO2 Mitigation in Residential Sector in Indonesia and Thailand: Potential of Renewable Energy and Energy Efficiency. Energy Procedia. 138, 955, 2017. https://doi.org/10.1016/j.egyp....
40.
FANG K., TANG Y., ZHANG Q., SONG J., WEN Q., SUN H., JI C., XU A. Will China peak its energy-related carbon emissions by 2030? Lessons from 30 Chinese provinces. Applied Energy. 255, 2019. https://doi.org/10.1016/j.apen....
41.
LI D., HUANG G., ZHU S., CHEN L., WANG J. How to peak carbon emissions of provincial construction industry? Scenario analysis of Jiangsu Province. Renewable and Sustainable Energy Reviews. 144, 2021. https://doi.org/10.1016/j.rser....
42.
ZHOU N., KHANNA N., FENG W., KE J., LEVINE M. Scenarios of energy efficiency and CO2 emissions reduction potential in the buildings sector in China to year 2050. Nature Energy. 3 (11), 978, 2018. https://doi.org/10.1038/s41560....
43.
WEI C., CHEN J., CONG M., WU Y., HUANG S., ZHOU Z., YANG D., LIU J. Analysis of carbon emissions in urban building sector using multi-influence model. Journal of Cleaner Production. 426 (11), 139130, 2023. https://doi.org/10.1016/j.jcle....
44.
XIE J. Discussion on Peak Carbon Emissions and Energy Saving-Emission Reduction of Public Buildings in Chongqing Based on LEAP Model. Chongqing University, 2021.
45.
JIANG J.-J., YE B., ZENG Z.-Z., LIU J.-G., YANG X. Potential and roadmap of CO2 emission reduction in urban buildings: Case study of Shenzhen. Advances in Climate Change Research. 13 (4), 587, 2022. https://doi.org/10.1016/j.accr....
46.
ZHOU X., XU Z., YAN J., LIANG L., PAN D. Carbon emission peak forecasting and scenario analysis: A case study of educational buildings in Shanghai city. Journal of Building Engineering. 76 (3), 107256, 2023. https://doi.org/10.1016/j.jobe....
47.
LIU Y., ZHANG J., XU J., WANG Y., LI B., ZHANG S. Carbon emission-based life cycle assessment of rural residential buildings constructed with engineering bamboo: A case study in China. Journal of Building Engineering. 76 (4), 107182, 2023. https://doi.org/10.1016/j.jobe....
48.
WANG J., SHEN H., YUAN W., YANG Y., WANG X. Research on Calculation Methods of Civil Building Area and Energy Intensity. Building Science. 36 (S2), 390, 2020.
49.
SUN H. Study on the Prediction of Carbon Peak and Energy Conservation and Emission Reduction Potential Analysis for Public Buildings in Shijiazhuang City (master). Hebei University of Engineering, 2022.
50.
HUO T., REN H., ZHANG X., CAI W., FENG W., ZHOU N., WANG X. China's energy consumption in the building sector: A Statistical Yearbook-Energy Balance Sheet based splitting method. Journal of Cleaner Production. 185, 665, 2018. https://doi.org/10.1016/j.jcle....
51.
YANG D., LIU D., HUANG A., LIN J., XU L. Critical transformation pathways and socio-environmental benefits of energy substitution using a LEAP scenario modeling. Renewable and Sustainable Energy Reviews. 135, 2021. https://doi.org/10.1016/j.rser....
52.
HU G., MA X., JI J. Scenarios and policies for sustainable urban energy development based on LEAP model - A case study of a postindustrial city: Shenzhen China. Applied Energy. 238, 876, 2019. https://doi.org/10.1016/j.apen....
53.
LEI F., YAN Y., YUE Y., BI W., NI P. The pathway of regional carbon peak in building sector: A case study of Central China. Journal of Building Engineering. 80, 2023. https://doi.org/10.1016/j.jobe....
54.
LIU X., GUO W., SONG Z., WU F. The influence of implementation of the Three-child Policy on the Population Growth in Shanxi Province - Based on Leslie Model. Journal of Taiyuan University (Natural Science Edition). 41, 80, 2023.
55.
HUO T., LI X., CAI W., ZUO J., JIA F., WEI H. Exploring the impact of urbanization on urban building carbon emissions in China: Evidence from a provincial panel data model. Sustainable Cities and Society. 56, 2020. https://doi.org/10.1016/j.scs.....
56.
MA M., CAI W. Do commercial building sector-derived carbon emissions decouple from the economic growth in Tertiary Industry? A case study of four municipalities in China. Science of The Total Environment. 650, 822, 2019. https://doi.org/10.1016/j.scit... PMid:30308857.
57.
LI H., ZHENG Y., GONG G., GUO H. A Simulation Study on Peak Carbon Emission of Public Buildings—In the Case of Henan Province, China. Sustainability. 15 (11), 2023. https://doi.org/10.3390/su1511....
58.
UNIVERSITY B.E.C.R.C.O.T. China Building Energy Efficiency Annual Development Research Report 2022 (Public Buildings Theme). China Architecture & Building Press, Beijing, 2022.
59.
YU S., ZHENG S., LI X. The achievement of the carbon emissions peak in China: The role of energy consumption structure optimization. Energy Economics. 74, 693, 2018. https://doi.org/10.1016/j.enec....
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