Welcome to Francis Academic Press

Academic Journal of Computing & Information Science, 2022, 5(10); doi: 10.25236/AJCIS.2022.051011.

Carbon Emission Forecast of Construction Industry Based on Grey Theory

Author(s)

Zhiyuan Guo, Jie Yin

Corresponding Author:
Zhiyuan Guo
Affiliation(s)

Institute of Science and Technology, Agricultural University of Hebei, Cangzhou, Hebei, 061000, China

Abstract

In order to reduce emissions of construction industry in China at an early date, this paper provides a fitting of different influencing factors based on the grey correlation method from the construction industry perspective. The correlation degree of carbon emission and related factors in construction industry was ranked as Rate of technical equipment > Practitioners> GDP > Population size > Gross output value of construction industry. And the future of carbon emissions forecast through the grey forecast, found that the country's construction industry will emit more than 80 million tons of carbon in 2030, facing very great pressure to reduce emissions. Therefore, the construction industry should realize the innovation potential of technology and industry model, accelerate the energy transition and achieve the inter-country emission reduction target at an early date.

Keywords

Carbon emissions; Construction industry; Grey correlation; Grey forecast

Cite This Paper

Zhiyuan Guo, Jie Yin. Carbon Emission Forecast of Construction Industry Based on Grey Theory. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 10: 66-69. https://doi.org/10.25236/AJCIS.2022.051011.

References

[1] Li Junfeng, Li Guang. Carbon Neutralization: Opportunities and Challenges for China's Development and Transformation [J]. Environment and Sustainable Development, 2021, 46 (01): 50-57. DOI: 10.19758/j.cnki.isn 1673-288 x. 202101050.

[2] Li Bo. Research on China's Role in Global Climate Governance [D]. Shandong University, 2020. DOI: 10.27272/d.cnki.gsd.2020.004035.

[3] Wang Ya. Research on sustainable development of construction industry in the Yangtze River Economic Belt from the perspective of technological progress [D]. Shanghai University, 2019. DOI: 10.27300/d.cnki.gshau. 2019.000245.

[4] Tang, C. W. Nguyen. Trends and Characteristics of the Relationship between Higher Education and Employment in the 14th Five-Year Plan Period: Research and Judgment Based on Markov Chain and Grey Prediction Model [J]. Heilongjiang Higher Education Research, 2021,39 (12): 116-122.

[5] Yang K., Yan Y., Yang H. Improvement and Application of GM (1, 1) Grey Prediction Model [J]. Journal of Nanjing University of Technology, 2020, 44 (05): 575-582. DOI: 10.14177/j.cn KI. 32-1397 n. 20.20.44.05.010.

[6] Luan Ziqing. Analysis of Shaanxi Province Transportation Carbon Emission [J] Based on Grey Correlation and Prediction Model, 2019 (03): 121-122 141. DOI: 10.16638/j.cn. 1671-7988. 2019.03.03 8.