Sustainability analysis of reused industrial buildings in China: an assessment method
Abstract
The sustainable development of old industrial buildings is in line with the national construction strategy and has an important impact on current urban renewal. Only by achieving a unified balance among economic, social, and environmental factors can reused industrial buildings be considered sustainable. However, there are no relevant sustainability assessment indicators and methods for reused industrial buildings in China. The purpose of this study was to provide a reasonable and effective method for assessing the sustainability of reused industrial buildings. First, this study analysed the factors influencing reused industrial building sustainability through a project investigation. Second, based on the assessment indicator setting procedure, the sustainability assessment indicator system for reused industrial buildings was optimised. Moreover, a multi-level sustainability assessment model based on extenics was established to identify the correlation functions of indicators with different attributes. Finally, a case was considered to verify this assessment method. The results showed that this assessment method in good agreement with the actual state of the case was validated to be more effective and practical. The assessment method could provide a basis for decision-making to improve sustainability and could be adopted by relevant rating agencies to determine the sustainability level of reused industrial buildings.
Keyword : old industrial buildings, reuse, sustainability assessment, extenics
How to Cite
Tian, W., Zhong, X., Zhang, G., & Goh, Y. M. (2021). Sustainability analysis of reused industrial buildings in China: an assessment method. Journal of Civil Engineering and Management, 27(1), 60-75. https://doi.org/10.3846/jcem.2021.14283
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Mu, E. & Pereyra-Rojas, M. (2017). Practical decision making - An introduction to the Analytic Hierarchy Process (AHP) using Super Decisions. Springer. https://doi.org/10.1007/978-3-319-68369-0_2
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Zhang, X., Wu, Y., Shen, L., & Skitmore, M. (2014). A prototype system dynamic model for assessing the sustainability of construction projects. International Journal of Project Management, 32, 66–76. https://doi.org/10.1016/j.ijproman.2013.01.009
Zhang, L. M., Geng, Y., Dong, H., Zhong, Y., Fujita, T., Xue, B., & Park, H.-s. (2016). Emergy-based assessment on the brownfield redevelopment of one old industrial area: a case of Tiexi in China. Journal of Cleaner Production, 114, 150–159. https://doi.org/10.1016/j.jclepro.2015.05.065
Zhang, H. D., Zhang, T. Y., Li, T., & Zhang, T. H. (2018). Forecast of air quality pollutants’ concentrations based on BP neural network multi-model ensemble method. China Environmental Science, 38(4), 1243–1256.
Zhou, Y., Hao, L., & Liu,W. (2016). Extenics-based study on evaluation of urban community home-care service for the elderly. Procedia Computer Science, 91, 576–580. https://doi.org/10.1016/j.procs.2016.07.146
Almeida, C. P., Ramos, A., & Silva, J. A. (2018). Sustainability assessment of building rehabilitation actions in old urban centres. Sustainable Cities and Society, 36, 378–385. https://doi.org/10.1016/j.scs.2017.10.014
Ameen, R. F. M., & Mourshed, M. (2019). Urban sustainability assessment framework development: The ranking and weighting of sustainability indicators using analytic hierarchy process. Sustainable Cities and Society, 44, 356–366. https://doi.org/10.1016/j.scs.2018.10.020
Atanda, J. O. (2019). Developing a social sustainability assessment framework. Sustainable Cities and Society, 44, 237–252. https://doi.org/10.1016/j.scs.2018.09.023
Banani, R., Vahdati, M. M., Shahrestani, M., & ClementsCroome, D. (2016). The development of building assessment criteria framework for sustainable non-residential buildings in Saudi Arabia. Sustainable Cities and Society, 26, 289–305. https://doi.org/10.1016/j.scs.2016.07.007
Borwein, J. M., & Zhu, Q. J. (2016). A variational approach to Lagrange multipliers. Journal of Optimization Theory and Applications, 171, 727–756. https://doi.org/10.1007/s10957-015-0756-2
Chan, A., Cheung, E., & Wong, I. (2015a). Impacts of the Revitalizing Industrial Buildings (RIB) scheme in Hong Kong. Sustainable Cities and Society, 19, 184–190. https://doi.org/10.1016/j.scs.2015.08.005
Chan, A., Cheung, E., & Wong, I. (2015b). Revitalizing industrial buildings in Hong Kong – A case review. Sustainable Cities and Society, 15, 57–63. https://doi.org/10.1016/j.scs.2014.10.004
Chan, A., Cheung, E., & Wong, I. (2015c). Recommended measures on the revitalizing industrial buildings scheme in Hong Kong. Sustainable Cities and Society, 17, 46–55. https://doi.org/10.1016/j.scs.2015.03.012
Drejeris, R., & Kavolynas, A. (2014). Multi-criteria assessment of building sustainability behavior. Procedia - Social and Behavioral Sciences, 110, 502–511. https://doi.org/10.1016/j.sbspro.2013.12.894
Eom, J. S., & An, D. W. (2018). Regeneration of industrial facilities into cultural facilities in Seoul: Studying location value. Sustainability, 10, 47–78. https://doi.org/10.3390/su10124778
Fan, S. J., Sheng, J. X., Li, H. M., & Yan, R. Q. (2013). Potential assessment of old industrial buildings reuse utilization based on combination weight method. Industrial Construction, 10, 002.
Gu, P. F., Xi, W., Ye, W. P., Shi, J., & Zhao, J. (2019). Extenics matter-element analysis on dilemma problem in HMI design of nuclear power plant. Nuclear Engineering and Design, 350, 176–181. https://doi.org/10.1016/j.nucengdes.2019.05.014
Hannouf, M., & Assefa, G. (2018). A life cycle sustainability assessment-based decision-analysis framework. Sustainability, 10, 3863. https://doi.org/10.3390/su10113863
He, H., Liu, W., Yu, J., & Li, X. (2016). Extenics-based testing method of divergent thinking quotient. Procedia Computer Science, 91, 151–157. https://doi.org/10.1016/j.procs.2016.07.052
Jiang, P., Li, Ch., Li, R. R., & Yang, H. F. (2019). An innovative hybrid air pollution early-warning system based on pollutants forecasting and Extenics evaluation. Knowledge-Based Systems, 164, 174–192. https://doi.org/10.1016/j.knosys.2018.10.036
Lee, J. H., & Lim, S. (2018). An Analytic Hierarchy Process (AHP) approach for sustainable assessment of economybased and community-based urban regeneration: The case of South Korea. Sustainability, 10, 4456. https://doi.org/10.3390/su10124456
Li, H. M., Tian, W., & Yan, R. Q. (2013). Constituting recycling assessment indicator system for old industrial buildings (group). Xi’an University of Architecture & Technology (Natural Science Edition).
Li, W. J., Song, Z. H., Mao, E. & Suh, S. (2018). Using Extenics to describe coupled solutions in Axiomatic design. Journal of Engineering Design, 30, 1–31. https://doi.org/10.1080/09544828.2018.1550633
Liu, Q. Y., Wang, M. W., Zhou, T. L., Shen, F. Q., & Jin, J. L. (2019). A connection cloud model coupled with extenics for water eutrophication evaluation. Earth Science Informatics, 12, 659–669. https://doi.org/10.1007/s12145-019-00403-1
Lou, J. J., Gui, F. Z., Ren, S. D., Xie, Z. W., & Zhao, Y. W. (2018). Improved TRIZ based on extension innovation method. Computer Integrated Manufacturing Systems, 1, 13.
Mahmoud, S., Zayed, T., & Fahmy, M. (2019). Development of sustainability assessment tool for existing buildings. Sustainable Cities and Society, 44, 99–119. https://doi.org/10.1016/j.scs.2018.09.024
Mu, E. & Pereyra-Rojas, M. (2017). Practical decision making - An introduction to the Analytic Hierarchy Process (AHP) using Super Decisions. Springer. https://doi.org/10.1007/978-3-319-68369-0_2
Nilashi, M., Zakaria, R., Ibrahim, O., Majid, M. Z. A., Zin, R. M., Chugtai, M. W., Abidin, N. I. Z., Sahamir, S. R., & Yakubu, D. A. (2015). A knowledge-based expert system for assessing the performance level of green buildings. Knowledge-Based Systems, 86, 194–209. https://doi.org/10.1016/j.knosys.2015.06.009
Peng, D.-g., Wei, T., Zhao, H.-r., Yao, J., & Wang, W.-j. (2019). Cyber security risk assessment of power plant control system based on D-AHP and TOPSIS. Control and Decision, 11, 0240.
Polat, G. (2016). Subcontractor selection using the integration of the AHP and PROMETHEE methods. Journal of Civil Engineering and Management, 22(8), 1042–1054. https://doi.org/10.3846/13923730.2014.948910
Qin, X., Li, H.Q., & Mo, Y. Y. (2017) Study on establishment and evaluation of risk network in green building projects based on SNA. China Civil Engineering Journal, 50(2), 119–131.
Rani, P., Mishra, A. R., Mardani, A., Cavallaro, F., Alrasheedi, M., & Alrashidi, A. (2020). A novel approach to extended fuzzy TOPSIS based on new divergence measures for renewable energy sources selection. Journal of Cleaner Production, 257, 120352. https://doi.org/10.1016/j.jclepro.2020.120352
Saraiva, T. S., De Almeida, M., Bragança, L. & Barbosa, M. T. (2018). Environmental comfort indicators for school buildings in sustainability assessment tools. Sustainability, 10(6), 1849. https://doi.org/10.3390/su10061849
Si, J., Marjanovic-Halburd, L., Nasiri, F., & & Bell, S. (2016). Assessment of building-integrated green technologies: A review and case study on applications of Multi-Criteria Decision Making (MCDM) method. Sustainable Cities and Society, 27, 106–115. https://doi.org/10.1016/j.scs.2016.06.013
Tan, R. R., Avis, K. B., Huelgas, A. P., & Promentilla, M. A. B. (2014). Fuzzy AHP approach to selection problems in process engineering involving quantitative and qualitative aspects Process. Safety and Environmental Protection, 92, 467–475. https://doi.org/10.1016/j.psep.2013.11.005
Tan, Y. T., Shuai, C. Y., & Wang, T. (2018a). Critical success factors (CSFs) for the adaptive reuse of industrial buildings in Hong Kong. International Journal of Environmental Research and Public Health, 15(7), 1546. https://doi.org/10.3390/ijerph15071546
Tan, Y. T., Liu, G., Zhang, Y., Shuai, C. Y., & Shen, Q. P. (2018b). Green retrofit of aged residential buildings in Hong Kong: A preliminary study. Building and Environment, 143, 89–98. https://doi.org/10.1016/j.buildenv.2018.06.058
Tokbolat, S., Karaca, F., Durdyev, S., Nazipov, F., & Aidyngaliyev, I. (2018). Assessment of green practices in residential buildings: A survey-based empirical study of residents in Kazakhstan. Sustainability, 10, 4383. https://doi.org/10.3390/su10124383
Tupenaite, L., Kaklauskas, A., Lill, I., Geipele, I., Naimaviciene, J., Kanapeckiene, L., & Kauskale, L. (2018). Sustainability assessment of the new residential projects in the Baltic States: A multiple criteria approach. Sustainability, 10, 1387. https://doi.org/10.3390/su10051387
Tupenaite, L., Lill, I., Geipele, I., & Naimaviciene, J. (2017). Ranking of sustainability indicators for assessment of the new housing development projects: Case of the Baltic States. Resources, 6, 55. https://doi.org/10.3390/resources6040055
Turcu, C. (2013). Re-thinking sustainability indicators: Local perspectives of urban sustainability. Journal of Environmental Planning Management, 56, 695–719. https://doi.org/10.1080/09640568.2012.698984
Vucicevic, B., Stojiljkovic, M., Afgan, N., Turanjanin, V., Jovanovic, M., & Bakic, V. (2013). Sustainability assessment of residential buildings by non-linear normalization procedure. Energy and Buildings, 58, 348–354. https://doi.org/10.1016/j.enbuild.2012.10.012
Wang, B., Li, H. N., Yuan, X. C., & Sun, Z. M. (2017). Energy poverty in China: a dynamic analysis based on a hybrid panel data decision model. Energy, 10(12), 1942. https://doi.org/10.3390/en10121942
Zhang, X., Wu, Y., Shen, L., & Skitmore, M. (2014). A prototype system dynamic model for assessing the sustainability of construction projects. International Journal of Project Management, 32, 66–76. https://doi.org/10.1016/j.ijproman.2013.01.009
Zhang, L. M., Geng, Y., Dong, H., Zhong, Y., Fujita, T., Xue, B., & Park, H.-s. (2016). Emergy-based assessment on the brownfield redevelopment of one old industrial area: a case of Tiexi in China. Journal of Cleaner Production, 114, 150–159. https://doi.org/10.1016/j.jclepro.2015.05.065
Zhang, H. D., Zhang, T. Y., Li, T., & Zhang, T. H. (2018). Forecast of air quality pollutants’ concentrations based on BP neural network multi-model ensemble method. China Environmental Science, 38(4), 1243–1256.
Zhou, Y., Hao, L., & Liu,W. (2016). Extenics-based study on evaluation of urban community home-care service for the elderly. Procedia Computer Science, 91, 576–580. https://doi.org/10.1016/j.procs.2016.07.146