Carbon emission peak forecasting and scenario analysis: A case study of educational buildings in Shanghai city

• Published in: Journal of Building Engineering Vol. 76; p. 107256
• Main Authors: Zhou, Xuan, Xu, Zhixin, Yan, Junwei, Liang, Liequan, Pan, Dongmei
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2023
• Subjects: Carbon emission peak; Electricity carbon emission factors; LEAP model; Pre-primary; Primary and secondary schools; Carbon emission peak; LEAP model; Pre-primary; Primary and secondary schools; Electricity carbon emission factors
• ISSN: 2352-7102; 2352-7102
• DOI: 10.1016/j.jobe.2023.107256

Accurate measurement of carbon emission is the prerequisite for achieving ‘Dual Carbon’ goal in China. In this study, a bottom-up method is proposed to forecast the carbon emissions based on the long-range energy alternatives planning system model which takes pre-primary, primary, and secondary schools in Shanghai city as research subject. The drivers' effects on carbon emission of educational buildings are analyzed with Kaya-LMDI method and three typical scenarios are defined, including normal, energy saving and green scenario. In addition, the electricity carbon emission factor is modified for accurate measure. The results show that these three kinds of schools in Shanghai can achieve carbon peak by 2030 under the above three scenarios. Floor area plays an important role in carbon emission, the peak time would be advanced by two years as the floor area evolves from normal to green scenario. The adoption of dynamically changing electricity carbon emission factor is also essential for accurate measurement. In the end, three policy implications are put forward based on findings. This study enriches the practice of carbon emissions research in building sector from long-term perspective, and provides a new perspective for carbon emission peak forecasting of a segmented industry. •Educational buildings' carbon emission is predicted from long-term perspective.•Electricity carbon emission factor is modified for accurate measurement.•Multiple scenarios are developed for peak forecasting and sensitivity analysis.•Floor area development plays an important role for carbon emissions.