Modeling, assessment, and optimization of urban sustainability using probabilistic system dynamics
Maozhi Wu （ Hubei Jianke Technology Group, 430223, Wuhan, China ）
Jiaqi Wang （ School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Hongshan District, Wuhan, Hubei 430074, China ）
Yan Zhang （ School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798 ）
Limao Zhang （ School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Hongshan District, Wuhan, Hubei 430074, China ）
https://doi.org/10.37155/2811-0730-0101-5Abstract
Urban sustainable development of cities could ameliorate many aspects such as population expansion, housing price increase, and ecological environment. For a better understanding of urban sustainability, many scholars have conducted different frameworks to make an accurate evaluation for urban planning. However, a myriad of existing research analyzes sustainable development based on separate and static indicts, which inevitably miss some important information related to interconnects between different indicators and timelines. This study, thus, proposes a comprehensive method that integrates the system dynamic and Monte Carlo sensitivity analysis to examine the interrelationships between different subsystems with a time series, in order to predict the feasibility of new policies for future development. A probabilistic system dynamics approach for policy optimization of sustainable urbanization is proposed with the consideration of dynamic changes and time flows. Several scenarios are simulated to perform and validate the proposed framework, where the comparisons from different results provide optimal strategies for urban sustainability. Some interesting findings can be drawn: (1) the social system is more sensitive to policy change, typically for transport connections and traffic saturation flow respects; (2) policies A1, B1, and B2 are encouraged to implement, as these regulations will boost the urban development; (3) the proposed hybrid method can be used to analyze the variables with a dynamic and long-term urban system.
Keywords
Policy implementation; Urban sustainable development; System dynamic; Monte Carlo simulation; OptimizationFull Text
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[63] Banister, D. and Y. Berechman, Transport investment and the promotion of economic growth. Journal of transport geography, 2001. 9(3): p. 209-218.
[2] Wang, W.-M. and H.-H. Peng, A fuzzy multi-criteria evaluation framework for urban sustainable development. Mathematics, 2020. 8(3): p. 330.
[3] Fan, Y., C. Fang, and Q. Zhang, Coupling coordinated development between social economy and ecological environment in Chinese provincial capital cities-assessment and policy implications. Journal of Cleaner Production, 2019. 229: p. 289-298.
[4] Zhu, J., et al., Efforts for a circular economy in China: A comprehensive review of policies. Journal of Industrial Ecology, 2019. 23(1): p. 110-118.
[5] Hassan, A.M. and H. Lee, Toward the sustainable development of urban areas: An overview of global trends in trials and policies. Land Use Policy, 2015. 48: p. 199-212.
[6] Turcu, C., Re-thinking sustainability indicators: local perspectives of urban sustainability. Journal of Environmental Planning and Management, 2013. 56(5): p. 695-719.
[7] Liu, Y., et al., An Optimization Method Based on Scenario Analysis for Watershed Management Under Uncertainty. Environmental Management, 2007. 39(5): p. 678-690.
[8] Zhou, M., An interval fuzzy chance-constrained programming model for sustainable urban land-use planning and land use policy analysis. Land Use Policy, 2015. 42: p. 479-491.
[9] Peng, Y., et al., An alternative model for measuring the sustainability of urban regeneration: the way forward. Journal of Cleaner Production, 2015. 109: p. 76-83.
[10] Ameen, R.F.M. and M. Mourshed, Urban sustainability assessment framework development: The ranking and weighting of sustainability indicators using analytic hierarchy process. Sustainable Cities and Society, 2019. 44: p. 356-366.
[11] Brandon, P.S. and P. Lombardi, Evaluating sustainable development: in the Built Environment. 2009: John Wiley & Sons.
[12] Shen, L.-Y., et al., The application of urban sustainability indicators – A comparison between various practices. Habitat International, 2011. 35(1): p. 17-29.
[13] Ugwu, O.O. and T.C. Haupt, Key performance indicators and assessment methods for infrastructure sustainability—a South African construction industry perspective. Building and Environment, 2007. 42(2): p. 665-680.
[14] Zhang, K., et al., A Multiple-Indicators Approach to Monitoring Urban Sustainable Development, in Ecology, Planning, and Management of Urban Forests: International Perspectives, M.M. Carreiro, Y.-C. Song, and J. Wu, Editors. 2008, Springer New York: New York, NY. p. 35-52.
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[16] Seabrooke, W., et al., Implementing sustainable urban development at the operational level (with special reference to Hong Kong and Guangzhou). Habitat International, 2004. 28(3): p. 443-466.
[17] Briassoulis, H., Sustainable Development and its Indicators: Through a (Planner's) Glass Darkly. Journal of Environmental Planning and Management, 2001. 44(3): p. 409-427.
[18] Kahn, M.E., Green cities: urban growth and the environment. 2007: Brookings Institution Press.
[19] Michalina, D., et al., Sustainable urban development: A review of urban sustainability indicator frameworks. Sustainability, 2021. 13(16): p. 9348.
[20] Lu, Y. and B. Chen, Urban ecological footprint prediction based on the Markov chain. Journal of cleaner production, 2017. 163: p. 146-153.
[21] Colantonio, A., Social sustainability: linking research to policy and practice. 2009.
[22] Colantonio, A. Urban social sustainability themes and assessment methods. in Proceedings of the Institution of Civil Engineers-Urban Design and Planning. 2010.
[23] Yigitcanlar, T., F. Dur, and D. Dizdaroglu, Towards prosperous sustainable cities: A multiscalar urban sustainability assessment approach. Habitat International, 2015. 45: p. 36-46.
[24] Xu, Z. and V. Coors, Combining system dynamics model, GIS and 3D visualization in sustainability assessment of urban residential development. Building and Environment, 2012. 47: p. 272-287.
[25] Phillis, Y.A., V.S. Kouikoglou, and C. Verdugo, Urban sustainability assessment and ranking of cities. Computers, Environment and Urban Systems, 2017. 64: p. 254-265.
[26] Raven, P.H., Restoring natural capital: science, business, and practice. 2012: Island press.
[27] Fiksel, J., Sustainability and resilience: toward a systems approach. 2006. 2(2): p. 14-21.
[28] Forrester, A.T., Photoelectric Mixing As a Spectroscopic Tool. Journal of the Optical Society of America, 1961. 51(3): p. 253-259.
[29] Sterman, J.D., System Dynamics Modeling: Tools for Learning in a Complex World. California Management Review, 2001. 43(4): p. 8-25.
[30] Kelly, R.A., et al., Selecting among five common modelling approaches for integrated environmental assessment and management. Environmental Modelling & Software, 2013. 47: p. 159-181.
[31] Martinez-Moyano, I.J. and G.P. Richardson, Best practices in system dynamics modeling. System Dynamics Review, 2013. 29(2): p. 102-123.
[32] Wang, J. and H. Yuan, System dynamics approach for investigating the risk effects on schedule delay in infrastructure projects. Journal of Management in Engineering, 2017. 33(1): p. 04016029.
[33] Guo, S., P. Zhang, and J. Yang, System dynamics model based on evolutionary game theory for quality supervision among construction stakeholders. Journal of Civil Engineering and Management, 2018. 24(4): p. 318-330.
[34] Huang, C., et al., Bidding strategy of energy storage in imperfectly competitive flexible ramping market via system dynamics method. International Journal of Electrical Power & Energy Systems, 2022. 136: p. 107722.
[35] Wu, Z., et al., A scientometric review of system dynamics applications in construction management research. Sustainability, 2020. 12(18): p. 7474.
[36] Chen, H., et al., Vulnerability modeling, assessment, and improvement in urban metro systems: A probabilistic system dynamics approach. Sustainable Cities and Society, 2021. 75: p. 103329.
[37] Espinoza, A., et al., Sustainability assessment to support governmental biodiesel policy in Colombia: A system dynamics model. Journal of Cleaner Production, 2017. 141: p. 1145-1163.
[38] Zhang, L., et al., Estimating long-term impacts of tunnel infrastructure development on urban sustainability using granular computing. Applied Soft Computing, 2021. 113: p. 107932.
[39] Abdi-Dehkordi, M., et al., Developing a sustainability assessment framework for integrated management of water resources systems using distributed zoning and system dynamics approaches. Environment, Development and Sustainability, 2021. 23(11): p. 16246-16282.
[40] Assunção, E., et al., Rethinking urban sustainability using fuzzy cognitive mapping and system dynamics. International Journal of Sustainable Development & World Ecology, 2020. 27(3): p. 261-275.
[41] Forrester, J.W. and J.W. Forrester, World dynamics. Vol. 59. 1971: Wright-Allen Press Cambridge, MA.
[42] Kunc, M., M.J. Mortenson, and R. Vidgen, A computational literature review of the field of System Dynamics from 1974 to 2017. Journal of Simulation, 2018. 12(2): p. 115-127.
[43] Hekimoğlu, M. and Y. Barlas, Sensitivity analysis for models with multiple behavior modes: a method based on behavior pattern measures. System Dynamics Review, 2016. 32(3-4): p. 332-362.
[44] Xiang, W., et al., Dynamic response and sensitivity analysis for mechanical systems with clearance joints and parameter uncertainties using Chebyshev polynomials method. Mechanical Systems and Signal Processing, 2020. 138: p. 106596.
[45] Iooss, B. and P. Lemaître, A Review on Global Sensitivity Analysis Methods. Operations Research/ Computer Science Interfaces, 2015. 59: p. 101-122.
[46] Landau, D.P. and K. Binder, A guide to Monte Carlo simulations in statistical physics. 2014: Cambridge university press.
[47] Hewitt, M., J. Ortmann, and W. Rei, Decision-based scenario clustering for decision-making under uncertainty. Annals of Operations Research, 2021: p. 1-25.
[48] Crespo Marquez, A., A. Sánchez Heguedas, and B. Iung, Monte Carlo-based assessment of system availability. A case study for cogeneration plants. Reliability Engineering & System Safety, 2005. 88(3): p. 273-289.
[49] Robert, C. and G. Casella, Monte Carlo statistical methods. 2013: Springer Science & Business Media.
[50] Haroonabadi, H. and M.R. Haghifam, Generation reliability assessment in power markets using Monte Carlo simulation and soft computing. Applied Soft Computing, 2011. 11(8): p. 5292-5298.
[51] Hodbod, J. and W.N. Adger, Integrating social-ecological dynamics and resilience into energy systems research. Energy Research & Social Science, 2014. 1: p. 226-231.
[52] Zhao, J., et al., Does China's increasing coupling of ‘urban population’and ‘urban area’growth indicators reflect a growing social and economic sustainability? Journal of Environmental Management, 2022. 301: p. 113932.
[53] Gołębiowski, P., J. Żak, and I. Jacyna-Gołda, Approach to the proecological distribution of the traffic flow on the transport network from the point of view of carbon dioxide. Sustainability, 2020. 12(17): p. 6936.
[54] Wu, K.-y., et al., Impacts of land use/land cover change and socioeconomic development on regional ecosystem services: The case of fast-growing Hangzhou metropolitan area, China. Cities, 2013. 31: p. 276-284.
[55] Tsai, I.-C., Housing price convergence, transportation infrastructure and dynamic regional population relocation. Habitat International, 2018. 79: p. 61-73.
[56] Ford, A. and H. Flynn, Statistical screening of system dynamics models. System Dynamics Review, 2005. 21(4): p. 273-303.
[57] Kasperska, E., A. Kasperski, and E. Mateja-Losa, Sensitivity analysis and optimization on some models of archetypes using Vensim-experimental issue. Studia Ekonomiczne, 2013(153): p. 53-82.
[58] Hekimoğlu, M. and Y. Barlas, Sensitivity analysis of system dynamics models by behavior pattern measures. Retrieved on March, 2010. 18: p. 2015.
[59] Parra, J.F., P. Jaramillo, and S. Arango-Aramburo, Metaheuristic optimization methods for calibration of system dynamics models. Journal of Simulation, 2018. 12(2): p. 190-209.
[60] Makler-Pick, V., et al., Sensitivity analysis for complex ecological models – A new approach. Environmental Modelling & Software, 2011. 26(2): p. 124-134.
[61] Nabavi, E., Determining criteria and monitoring sustainability of Zayandeh-rud River Basin from water resources management point of view. Civil Engineering, Isfahan University of Technology, Isfahan, 2011.
[62] Fan, P., et al., Urbanization, economic development, environmental and social changes in transitional economies: Vietnam after Doimoi. Landscape and Urban Planning, 2019. 187: p. 145-155.
[63] Banister, D. and Y. Berechman, Transport investment and the promotion of economic growth. Journal of transport geography, 2001. 9(3): p. 209-218.
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