Skip to main content

Advertisement

Log in

Green building performance assessment in China using a cloud model

  • Published:
Environment, Development and Sustainability Aims and scope Submit manuscript

Abstract

With the acceleration of urbanization process in China, the usage of sustainable green buildings is getting a great attention and significance in order to reduce energy consumption. However, there are still challenges for evaluating the performance of green buildings in China due to the lack of unified codes/standards. This paper proposes a method based on cloud model to evaluate the performance of green buildings. This method overcomes the randomness and subjectivity of fuzzy concepts to the maximum extent; on this basis, the system’s indexes including environmental–economic balance, regional social coordination, health, comfort, and green management can be established. The analytic hierarchy process and entropy weight methods are used to calculate the index weight; the cloud model is used to realize the transformation between qualitative and quantitative characteristics; and then, a mathematical evaluation model based on the cloud model is established. Finally, an empirical study is made based on a typical case in Shenzhen city, China. The findings of this research work reveal a performance index for green building created based on expert evaluations and a standard cloud yardstick created in the comprehensive cloud model. Based on the results of this manuscript, the industry can acquire benefits by suggesting effective measures that can be implemented in all stages of green buildings construction where the measurements execution and persuasive components make appraisal models for a green building. This study provides a consistent framework for researchers and other public to evaluate green buildings, and provides a solid foundation for further research and consideration basis on sustainable development and green building operation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Availability of supporting data

All data generated or analysed during this study are included in this published article.

References

  • Alyami, S. H., & Rezgui, Y. (2012). Sustainable building assessment tool development approach. Sustainable Cities and Society, 5, 52–62.

    Article  Google Scholar 

  • Alyami, S. H., Rezgui, Y., & Kwan, A. (2013). Developing sustainable building assessment scheme for Saudi Arabia: Delphi consultation approach. Renewable and Sustainable Energy Reviews, 27, 43–54.

    Article  Google Scholar 

  • Banaitiene, N., Banaitis, A., Kaklauskas, A., & Zavadskas, E. K. (2008). Evaluating the life cycle of a building: A multivariant and multiple criteria approach. Omega, 36(3), 429–441.

  • Barbieri, F., Rajakaruna, S., & Ghosh, A. (2017). Very short-term photovoltaic power forecasting with cloud modeling: A review. Renewable and Sustainable Energy Reviews, 75, 242–263.

    Article  Google Scholar 

  • Borel-Saladin, J. M., & Turok, I. N. (2013). The impact of the green economy on jobs in South Africa. South African Journal of Science, 109(9–10), 1–4.

  • CABEE, 2019. In: Cai, W.G. (Ed.), Chinese Building Energy Consumption Report (2019). Shanghai, PR China. Available at: https://mp.weixin.qq.com/s/I63nbYoEww7oSf-gT7dneA(in Chinese).

  • Di, K. C. (2000). Spatial data mining and knowledge discovery. WuHan University Press.

  • Ding, Z., Fan, Z., Tam, V. W., Bian, Y., Li, S., Illankoon, I. C. S., & Moon, S. (2018). Green building evaluation system implementation. Building and Environment, 133, 32–40.

    Article  Google Scholar 

  • Du, X. Y., Yin, Q. J., Huang, K. D., & Liang, D. N. (2008). Transformation between qualitative variables and quantity based on cloud models and its application. Systems Engineering and Electronics, 30(4), 772–776.

  • Erlandsson, M., & Borg, M. (2003). Generic LCA-methodology applicable for buildings, constructions and operation services—Today practice and development needs. Building and Environment, 38(7), 919–938.

    Article  Google Scholar 

  • Feng, Z., & Zhang, H. W. (2017). “AHP-entropy weight method” based CW-TOPSIS model for predicting rockburst. China Safety Science Journal, 27, 128–133.

    Google Scholar 

  • Kibert, C. J. (2016). Sustainable construction: Green building design and delivery. Wiley.

    Google Scholar 

  • Li, D. Y., Meng, H. J. & Shi, X. M. (1995). Membership of cloud and subordinate cloud generator. Computer Research and Development, 32(6), 15–20.

  • Li, B. Z., He, T. Q., & Z. H. (2007). An introduction to green architecture, 158–159.

  • Li, B. Z., He, T. Q., & Z. H. (2007). An introduction to green architecture, 14.

  • Li, C. Z., Hong, J., Xue, F., Shen, G. Q., Xu, X., & Luo, L. (2016). SWOT analysis and Internet of Things-enabled platform for prefabrication housing production in Hong Kong. Habitat International, 57, 74–87.

    Article  Google Scholar 

  • Li, D. (2000). Uncertainty in knowledge representation. Engineering Science, 2(10), 73–79.

    Google Scholar 

  • Li, X. J., Lai, J. U., Ma, C. Y., & Wang, C. (2021). Using BIM to research carbon footprint during the materialization phase of prefabricated concrete buildings: A China study. Journal of Cleaner Production, 279, 123454.

    Article  CAS  Google Scholar 

  • Li, X., Zhu, Y., & Zhang, Z. (2010). An LCA-based environmental impact assessment model for construction processes. Building and Environment, 45(3), 766–775.

    Article  Google Scholar 

  • Li, Y. Y., Chen, P. H., Chew, D. A. S., Teo, C. C., & Ding, R. G. (2011). Critical project management factors of AEC firms for delivering green building projects in Singapore. Journal of Construction Engineering and Management, 137(12), 1153–1163.

    Article  Google Scholar 

  • Li, Y. P., Liu, M. Q., Wang, F., & Li, R. G. (2017). Safety performance assessment of prefabricated building project based on cloud model. China Safety Science Journal, 27(6), 115–120.

    Google Scholar 

  • Li, Y., Yang, L., He, B., & Zhao, D. (2014). Green building in China: Needs great promotion. Sustainable Cities and Society, 11, 1–6.

    Article  Google Scholar 

  • Liu, J., Gong, E., Wang, D., & Teng, Y. (2018). Cloud model-based safety performance evaluation of prefabricated building project in China. Wireless Personal Communications, 102(4), 3021–3039. https://doi.org/10.1007/s11277-018-5323-3

    Article  Google Scholar 

  • Liu, T. Y., Chen, P. H., & Chou, N. N. (2019). Comparison of assessment systems for green building and green civil infrastructure. Sustainability, 11(7), 2117.

    Article  Google Scholar 

  • Lu, H., Wang, Y., Li, D., & Liu, C. (2003). The application of backward cloud in qualitative evaluation. Chinese Journal of Computers-Chinese Edition, 26(8), 1009–1014.

    Google Scholar 

  • Lu, Z. M., Sun, X. K., & Wang, Y. X. (2019). Green supplier selection in straw biomass industry based on cloud model and possibility degree. Journal of Cleaner Production, 209, 995–1005.

    Article  Google Scholar 

  • Ma, H. T., Du, N. Y., Lu, S. J., Zhang, W. Q., Deng, Z. Y., & Cong, N. L. (2017). Analysis of typical public building energy consumption in northern China. Energy and Buildings, 136(1), 139–150.

    Article  Google Scholar 

  • Qiyue, C. (2010). Structure entropy weight method to confirm the weight of evaluating index. Systems Engineering Theory and Practice, 30(7), 1225–1228.

    Google Scholar 

  • Ren, Y., Zhao, L., Song, Y., & Lin, S. (2019). State assessment method for transformer under DC bias based on gray cloud model. In 2019 IEEE sustainable power and energy conference (iSPEC) (pp. 2282–2286). IEEE.

  • Ren, H., & Zhu, L. B. (2008). Multi-hierarchical grey evaluation on the construction enterprises’ informatization level based on combinational weight. System Engineering Theory and Practice, 02, 82–88.

    Google Scholar 

  • Sharif, S. A., & Hammad, A. (2019). Developing surrogate ANN for selecting near-optimal building energy renovation methods considering energy consumption, LCC and LCA. Journal of Building Engineering, 25, 100790.

    Article  Google Scholar 

  • Vyas, G. S., & Jha, K. N. (2016). Identification of green building attributes for the development of an assessment tool: A case study in India. Civil Engineering and Environmental Systems, 33(4), 313–334.

    Article  Google Scholar 

  • Wang, S. L., Chi, H. H., Yuan, H. N., & Geng, J. (2017). Extraction and representation of common feature from uncertain facial expressions with cloud model. Environmental Science and Pollution Research, 24(36), 27778–27787.

  • Wedding, G. C., & Crawford-Brown, D. (2007). Measuring site-level success in brownfield redevelopments: A focus on sustainability and green building. Journal of Environmental Management, 85(2), 483–495.

    Article  Google Scholar 

  • Wei, G. A., & Wang, J. Z. (2019). Analysis on National Environment of Green Building Assessment Scheme in America and China. In E3S Web of Conferences (Vol. 136, p. 03022). EDP Sciences.

  • Xiong, J. S., Li, J. H., & Yang, Y. H. (2012). Method of determine index weight in security risk evaluation based on information entropy. In 2012 fourth international conference on multimedia information networking and security (pp. 43–48). IEEE.

  • Xu, L. Y. (2006). Green building evaluation method and model research.

  • Zhang, Y., Wang, J., Hu, F., & Wang, Y. (2017). Comparison of evaluation standards for green building in China, Britain, United States. Renewable and Sustainable Energy Reviews, 68, 262–271.

    Article  Google Scholar 

  • Zhao, J. (2000). Mathematical modeling and mathematical experiments. Beijing: Higher Education Press.

  • Zhao, J. (2021). Evaluation of regional environmental economic efficiency based on GIS big data and improved neural network. Arabian Journal of Geosciences, 14, 1866–7511

  • Zhou, J., Zhu, Y. Q., Chai, X. D., & Tang, W. Q. (2012). Approach for analyzing consensus based on cloud model and evidence theory. Systems Engineering-Theory and Practice, 32(12), 2756–2763.

    Google Scholar 

  • Zou, X., & Moon, S. (2014). Hierarchical evaluation of on-site environmental performance to enhance a green construction operation. Civil Engineering and Environmental Systems, 31(1), 5–23.

    Article  Google Scholar 

Download references

Acknowledgements

This research was funded by Huaqiao University, Grant No. 17BS201, and Quanzhou City Government, Grant No. 600005-Z17X0234.

Funding

This research was funded by Huaqiao University, Grant No. 17BS201, and Quanzhou City Government, Grant No. 600005-Z17X0234.

Author information

Authors and Affiliations

Authors

Contributions

Xiao-Juan Li and Wei-bin Chen collected the data, Chen Wang conducted the data analysis, Shilpi Bora drafted the first writing, and Bimenyimana Samuel and Jeffrey Boon Hui Yap were in charge of the methodology.

Corresponding author

Correspondence to Chen Wang.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Consent for publication

All authors have consent for publication.

Ethical approval and consent to participate

The Fujian Agriculture and Forestry University Ethical Review Board approached this study with consent to participate.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, XJ., Wang, C., Chen, Wb. et al. Green building performance assessment in China using a cloud model. Environ Dev Sustain 24, 11626–11650 (2022). https://doi.org/10.1007/s10668-021-01926-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10668-021-01926-8

Keywords

Navigation