Research on Low-Carbon Building Development and Carbon Emission Control Based on Mathematical Models: A Case Study of Jiangsu Province

Dingjun Chang and Shuling Tang ()
Additional contact information
Dingjun Chang: School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing 100083, China
Shuling Tang: School of Energy Resources, China University of Geosciences (Beijing), Beijing 100083, China

Energies, 2024, vol. 17, issue 18, 1-22

Abstract: This paper investigates the development of low-carbon buildings and carbon emission control in Jiangsu Province, China, utilizing a mathematical model. Through correlation analysis and principal component analysis, the carbon emissions of the entire life cycle of residential buildings are evaluated, and a Grey Prediction Model is established. The study shows that the annual carbon emission from air conditioners is 370.92 kg, given an annual electricity consumption of 1324.71 kW and a carbon emission of 0.28 kg per kWh. It identifies the key carbon emission indicators, including precipitation, temperature, energy consumption, building area, construction materials, water, natural gas, and waste. Principal component analysis ranks building area as the most significant factor. Using the GM (1,1) model, the carbon emissions of Jiangsu Province in 2024 were predicted to be 1.5576 million tons by historical data. Emission reduction suggestions are proposed, such as constructing thicker walls, increasing green spaces, reducing construction waste, and promoting balanced economic development. Moreover, prioritizing insulation materials in building design can reduce winter energy consumption since energy consumption is higher in winter than in summer. This research supports China’s goals of achieving a carbon peak by 2030 and carbon neutrality by 2060 while encouraging low-carbon technological innovation and improving people’s living standards. This study also emphasizes the importance of locally tailored strategies for effective emissions reduction.

Keywords: low-carbon building; carbon emission; heat conduction model; Principal Component Analysis (PCA); Grey Prediction Model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/18/4545/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/18/4545/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:18:p:4545-:d:1475338

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().