Citation: | DENG Yu, WANG Wenxue, WANG Haijun. Regional Divergence and Scenario Simulation of Sustainable Development Patterns in Beijing,China[J]. Geomatics and Information Science of Wuhan University, 2024, 49(5): 844-855. DOI: 10.13203/j.whugis20220546 |
Forecasting trends in sustainable sustainability levels in metropolitan areas serves as the foundation for developing development policies that are tailored to local conditions. Sustainability evaluation studies based on a multidimensional comprehensive index system fall short of highlighting the variability, systemic, and dynamic nature of metropolitan area development. To better understand the role of multidimensional scenarios in guiding the sustainable development of metropolitan areas, a greater emphasis on suburban spatial units and spatial heterogeneity characteristics is required.
We simulate the trends of sustainable development levels of 16 municipal districts in Beijing,China from 2011 to 2030 by combining the system dynamics model and the shared socioeconomic pathways, and thus condense the metropolitan area's sustainable development model and compare the advantages and shortcomings of each development scenario under different models.
The findings show that: (1) Beijing's municipal districts perform differently in economic, social, and environmental subsystems, and there are three types of typical districts: Synergistic development, ecologically biased development, and economic constraint. (2) Shared socioeconomic pathway(SSP)1 is the most desirable urban sustainable development scenario among the four scenarios of SSP1, SSP2 (BAU(business-as-usual)), SSP3, and SSP5. (3) In order to achieve the transition from the historical trajectory to the SSP1 scenario, each district type should pursue a distinct development strategy. To improve the quality of coordinated development, synergistic development type zones should use social security and employment expenditures to compensate for the shortcomings of social development. Ecologically biased zones should reduce energy consumption and increase environmental protection investment to maintain environmental advantages, and economic constraint type zones can maintain high gross domestic product growth rates in the short term to get out of the development dilemma.
The findings of this paper highlight the complex cause-and-effect relationships between urban economic, social, and environmental systems and offer a framework for system evaluation and simulation technology for the sustainable development of metropolitan areas. This framework will serve as a source of regulations and a foundation for management of urban refinement.
[1] |
United Nations Department of Economic and Social Affairs .World Urbanization Prospects: The 2018 Revision[R]. United Nations (Ser. A), Population and Vital Statistics Report, 2019.
|
[2] |
Al-mulali U, Binti Che Sab C N, Fereidouni H G. Exploring the Bi-directional Long Run Relationship Between Urbanization, Energy Consumption, and Carbon Dioxide Emission[J]. Energy, 2012, 46(1): 156-167.
|
[3] |
穆怀中, 范洪敏. 城市化对环境质量的影响: 基于27个国家面板数据的分析[J]. 城市问题, 2016(9): 73-79.
Mu Huaizhong, Fan Hongmin. Influence of Urbanization on the Quality of Environment: An Analysis Based on 27 National Panel Data[J]. Urban Problems, 2016(9): 73-79.
|
[4] |
Huang L, Yan L J, Wu J G. Assessing Urban Sustainability of Chinese Megacities: 35 Years After the Economic Reform and Open-door Policy[J]. Landscape and Urban Planning, 2016, 145: 57-70.
|
[5] |
黄永明, 何凌云. 城市化、环境污染与居民主观幸福感: 来自中国的经验证据[J]. 中国软科学, 2013(12): 82-93.
Huang Yongming, He Lingyun. Urbanization, Environmental Pollution and Subjective Well-being: An Empirical Study on China[J]. China Soft Science, 2013(12): 82-93.
|
[6] |
Huang J, Pan X C, Guo X B, et al. Impacts of Air Pollution Wave on Years of Life Lost: A Crucial Way to Communicate the Health Risks of Air Pollution to the Public[J]. Environment International, 2018, 113: 42-49.
|
[7] |
焦利民, 刘耀林. 可持续城市化与国土空间优化[J]. 武汉大学学报(信息科学版), 2021, 46(1): 1-11.
Jiao Limin, Liu Yaolin. Sustainable Urbanization and Territorial Spatial Optimization[J]. Geomatics and Information Science of Wuhan University, 2021, 46(1): 1-11.
|
[8] |
Zinatizadeh S, Azmi A, Monavari S M, et al. Evaluation and Prediction of Sustainability of Urban Areas: A Case Study for Kermanshah City, Iran[J]. Cities, 2017, 66: 1-9.
|
[9] |
Liu X Q, Pei T, Zhou C H, et al. A Systems Dynamic Model of a Coal-based City with Multiple Adaptive Scenarios: A Case Study of Ordos, China[J]. Science China Earth Sciences, 2018, 61(3): 302-316.
|
[10] |
Gao Q, Fang C L, Liu H M, et al. Conjugate Evaluation of Sustainable Carrying Capacity of Urban Agglomeration and Multi-scenario Policy Regulation[J]. Science of the Total Environment, 2021, 785: 147373.
|
[11] |
Xing L, Xue M G, Hu M S. Dynamic Simulation and Assessment of the Coupling Coordination Degree of the Economy-Resource-Environment System: Case of Wuhan City in China[J]. Journal of Environmental Management, 2019, 230: 474-487.
|
[12] |
Zhang D, Huang Q X, He C Y, et al. Impacts of Urban Expansion on Ecosystem Services in the Beijing-Tianjin-Hebei Urban Agglomeration, China: A Scenario Analysis Based on the Shared Socioeconomic Pathways[J]. Resources, Conservation and Recycling, 2017, 125: 115-130.
|
[13] |
Aguiar A P D, Collste D, Harmáčková Z V, et al. Co-designing Global Target-Seeking Scenarios: A Cross-scale Participatory Process for Capturing Multiple Perspectives on Pathways to Sustainability[J]. Global Environmental Change, 2020, 65: 102198.
|
[14] |
O’Neill B C, Kriegler E, Ebi K L, et al. The Roads Ahead: Narratives for Shared Socioeconomic Pathways Describing World Futures in the 21st Century[J]. Global Environmental Change, 2017, 42: 169-180.
|
[15] |
张帆, 徐宁, 吴锋. 共享社会经济路径下中国2020—2100年碳排放预测研究[J]. 生态学报, 2021, 41(24): 9691-9704.
Zhang Fan, Xu Ning, Wu Feng. Research on China’s CO2 Emissions Projections from 2020 to 2100 Under the Shared Socioeconomic Pathways[J]. Acta Ecologica Sinica, 2021, 41(24): 9691-9704.
|
[16] |
段海燕,肖依静 ,丁哲, 等. 区域人口、经济、能源环境协调发展情景预测研究[J].人口学刊,2017,39(2):47-56.
Duan Haiyan,Xiao Yijing,Ding Zhe, et al.A Study on the Scenario Prediction on Population,Economy and Energy-Environment Coordinated Development of Jilin Province in 2030[J].Population Journal,2017,39(2):47-56.
|
[17] |
Kamei M, Hanaki K, Kurisu K. Tokyo’s Long-term Socioeconomic Pathways: Towards a Sustainable Future[J]. Sustainable Cities and Society, 2016, 27: 73-82.
|
[18] |
He C Y, Li J W, Zhang X L, et al. Will Rapid Urban Expansion in the Drylands of Northern China Continue: A Scenario Analysis Based on the Land Use Scenario Dynamics-Urban Model and the Shared Socioeconomic Pathways[J]. Journal of Cleaner Production, 2017, 165: 57-69.
|
[19] |
Kamei M, Kurisu K, Hanaki K. Evaluation of Long-term Urban Transitions in a Megacity’s Building Sector Based on Alternative Socioeconomic Pathways[J]. Sustainable Cities and Society, 2019, 47: 101366.
|
[20] |
Wu S Y, Li B V. Sustainable Linear Infrastructure Route Planning Model to Balance Conservation and Socioeconomic Development[J]. Biological Conservation, 2022, 266: 109449.
|
[21] |
陈恒, 李文硕. 全球化时代的中心城市转型及其路径[J]. 中国社会科学, 2017(12): 72-93.
Chen Heng, Li Wenshuo. The Transformation of Central Cities in the Era of Globalization and Its Path[J]. Social Sciences in China, 2017(12): 72-93.
|
[22] |
雷诚, 罗震东. 大都市社区公共服务设施供给研究: 基于“三三制” 的体系构建[J]. 城市规划, 2019, 43(8): 41-52.
Lei Cheng, Luo Zhendong. New Supply System and Pattern of Community Public Service Facilities in Metropolitan Area: System Construction Based on 3-3 Pattern[J]. City Planning Review, 2019, 43(8): 41-52.
|
[23] |
Jiang L W, O’Neill B C. Global Urbanization Projections for the Shared Socioeconomic Pathways[J]. Global Environmental Change, 2017, 42: 193-199.
|
[24] |
Jiang X T, Zhai S Y, Liu H, et al. Multi-scenario Simulation of Production-Living-Ecological Space and Ecological Effects Based on Shared Socioeconomic Pathways in Zhengzhou, China[J]. Ecological Indicators, 2022, 137: 108750.
|
[25] |
王火根, 肖丽香, 廖冰. 基于系统动力学的中国碳减排路径模拟[J]. 自然资源学报, 2022, 37(5): 1352-1369.
Wang Huogen, Xiao Lixiang, Liao Bing. Simulation of China’s Carbon Emission Reduction Path Based on System Dynamics[J]. Journal of Natural Resources, 2022, 37(5): 1352-1369.
|
[26] |
Yang H, Huang J L, Liu D F. Linking Climate Change and Socioeconomic Development to Urban Land Use Simulation: Analysis of Their Concurrent Effects on Carbon Storage[J]. Applied Geography, 2020, 115: 102135.
|
[27] |
窦睿音, 张生玲, 刘学敏. 基于系统动力学的资源型城市转型模式实证研究: 以鄂尔多斯为例[J]. 干旱区资源与环境, 2019, 33(8): 18-25.
Dou Ruiyin, Zhang Shengling, Liu Xuemin. Study on Transformation Mode of Resources-based Cities Based on SD: A Case of Ordos[J]. Journal of Arid Land Resources and Environment, 2019, 33(8): 18-25.
|
[28] |
Tan Y T, Jiao L D, Shuai C Y, et al. A System Dynamics Model for Simulating Urban Sustainability Performance: A China Case Study[J]. Journal of Cleaner Production, 2018, 199: 1107-1115.
|
[29] |
Arias-Gaviria J, Valencia V, Olaya Y, et al. Simulating the Effect of Sustainable Buildings and Energy Efficiency Standards on Electricity Consumption in Four Cities in Colombia: A System Dynamics Approach[J]. Journal of Cleaner Production, 2021, 314: 128041.
|
[30] |
Rafew S M, Rafizul I M. Application of System Dynamics Model for Municipal Solid Waste Management in Khulna City of Bangladesh[J]. Waste Management, 2021, 129: 1-19.
|
[31] |
Guan D J, Gao W J, Su W C, et al. Modeling and Dynamic Assessment of Urban Economy-Resource-Environment System with a Coupled System Dynamics-Geographic Information System Model[J]. Ecological Indicators, 2011, 11(5): 1333-1344.
|
[32] |
O’Neill B C, Kriegler E, Riahi K, et al. A New Scenario Framework for Climate Change Research: The Concept of Shared Socioeconomic Pathways[J]. Climatic Change, 2014, 122(3): 387-400.
|
[33] |
曹可心, 邓羽. 可持续城市更新的时空演进路径及驱动机理研究进展与展望[J]. 地理科学进展, 2021, 40(11): 1942-1955.
Cao Kexin, Deng Yu. Spatio-temporal Evolution Path and Driving Mechanisms of Sustainable Urban Renewal: Progress and Perspective[J]. Progress in Geography, 2021, 40(11): 1942-1955.
|
[34] |
程朋根, 岳琛. 多源数据支持下的城市生态环境评价及其与人类活动的关系[J]. 武汉大学学报(信息科学版), 2022, 47(11): 1927-1937.
Cheng Penggen, Yue Chen. Evaluation of Urban Ecological Environment and Its Relationship with Human Activities with Multi-source Data[J]. Geomatics and Information Science of Wuhan University, 2022, 47(11): 1927-1937.
|
[35] |
刘媛媛, 王绍强, 王小博, 等. 基于AHP_熵权法的孟印缅地区洪水灾害风险评估[J]. 地理研究, 2020, 39(8): 1892-1906.
Liu Yuanyuan, Wang Shaoqiang, Wang Xiaobo, et al. Flood Risk Assessment in Bangladesh, India and Myanmar Based on the AHP Weight Method and Entropy Weight Method[J]. Geographical Research, 2020, 39(8): 1892-1906.
|
[36] |
霍叶青, 何跃. 基于离差最大化和Ward系统聚类的四川城镇化水平研究[J]. 软科学, 2010, 24(6): 71-73.
Huo Yeqing, He Yue. Research on the Urbanization Level of Sichuan Based on the Maximizing Deviation and Ward System Analysis[J]. Soft Science, 2010, 24(6): 71-73.
|
[37] |
谷岩岩, 焦利民, 董婷, 等. 基于多源数据的城市功能区识别及相互作用分析[J]. 武汉大学学报(信息科学版), 2018, 43(7): 1113-1121.
Gu Yanyan, Jiao Limin, Dong Ting, et al. Spatial Distribution and Interaction Analysis of Urban Functional Areas Based on Multi-source Data[J]. Geomatics and Information Science of Wuhan University, 2018, 43(7): 1113-1121.
|
[38] |
湛东升, 张文忠, 张娟锋, 等. 北京市公共服务设施集聚中心识别分析[J]. 地理研究, 2020, 39(3): 554-569.
Zhan Dongsheng, Zhang Wenzhong, Zhang Juanfeng, et al. Identifying Urban Public Service Facilities Centers in Beijing[J]. Geographical Research, 2020, 39(3): 554-569.
|
[39] |
Fan Y P,Fang C L,Zhang Q.Coupling Coordinated Development Between Social Economy and Ecological Environment in Chinese Provincial Capital Cities-Assessment and Policy Implications[J].Journal of Cleaner Production,2019,229: 289-298.
|
[1] | ZHANG Xinlong, CHEN Xiuwan, LI Huaiyu, LI Fei. An Improved Cellular Automata Model for Simulating Pedestrian Evacuation[J]. Geomatics and Information Science of Wuhan University, 2017, 42(9): 1330-1336. DOI: 10.13203/j.whugis20150763 |
[2] | WANG Haijun, XIA Chang, ZHANG Anqi, ZHANG Wengting. Calibrating Urban Expansion Cellular Automata Using Biogeography-Based Optimization[J]. Geomatics and Information Science of Wuhan University, 2017, 42(9): 1323-1329. DOI: 10.13203/j.whugis20160438 |
[3] | LI Qingquan. From Geomatics to Urban Informatics[J]. Geomatics and Information Science of Wuhan University, 2017, 42(1): 1-6. DOI: 10.13203/j.whugis20160200 |
[4] | HUI Shan, RUI Xiaoping, LI Yao. An Improved Forest Fire Spread Simulation Algorithm Coupled with Cellular Automata[J]. Geomatics and Information Science of Wuhan University, 2016, 41(10): 1326-1332. DOI: 10.13203/j.whugis20140811 |
[5] | LIU Yilun, LI Xia. Knowledge Transfer and Adaptation for Urban Simulation Cellular AutomataModel Base on Multi-source TrAdaBoost Algorithm[J]. Geomatics and Information Science of Wuhan University, 2014, 39(6): 695-700. DOI: 10.13203/j.whugis20140060 |
[6] | SHU Bangrong, LIU Youzhao, ZHANG Honghui, ZHANG Qingli. Scenario Simulation of Urban Land Expansion Integrate Variable Weight with Constrained Fuzzy Cellular Automata[J]. Geomatics and Information Science of Wuhan University, 2013, 38(4): 498-503. |
[7] | WANG Haijun, HE Sanwei, ZHANG Wenting, DENG Yu. Urban Cellular Automata Model with Considering the Distance of Obstacle Space and Regional Disparity[J]. Geomatics and Information Science of Wuhan University, 2011, 36(8): 999-1002. |
[8] | CAO Liqin, ZHANG Liangpei, LI Pingxiang, HUANG Wei. Simulation Study of Influence of Change of Land Surface Types on Urban Heat Island[J]. Geomatics and Information Science of Wuhan University, 2008, 33(12): 1229-1232. |
[9] | LUO Ping, DU Qingyun, LEI Yuanxin, WANG Tao. Cellular Automata Based on Geographic Feature and Urban Land Use Evolvement[J]. Geomatics and Information Science of Wuhan University, 2004, 29(6): 504-507,512. |
[10] | Sun Shanfang, Tang Zhifeng, Yang Chunhuai. Method of Vision Analysis and Simulation Control of Urban Landscape[J]. Geomatics and Information Science of Wuhan University, 1994, 19(3): 254-258. |
1. |
李成名,武鹏达,印洁. 图数统一表达地理模型及自补偿方法. 测绘学报. 2017(10): 1688-1697 .
![]() |