The coordinated development of society, economy and environment has always been the key issue of regional sustainable development since the concept of sustainable development was put forward by the Commission on World and Environmental Development in 1987 (Zou and Ma,2021; Zhang et al.,2020). With the advancement in worldwide urbanization and industrialization, the contradiction between socio-economic development and population, resources and environment have become increasingly prominent, which restricts the sustainable development of the region (Bao et al.,2020; Bibri et al.,2020). Since the open door reform policy in 1978 in China, much has changed (Lin et al.,2017). One of the major changes is the tremendous improvement of social productivity and rapid economic growth (Yang et al.,2020). Another change is the rapid population growth in large cities (Shi et al.,2018). Meanwhile, many global environmental issues have emerged, such as the excessive exploitation of natural resources, the discharge of pollutants and the deterioration of human settlement environment (Li et al.,2017; Zheng et al.,2018). In order to tackle these problems, we integrate the concept of carrying capacity into the management of urban development. Urban carrying capacity (UCC) or urban comprehensive carrying capacity is an important barometer of urban sustainable development. The research topic is, however, not easy to standardize due to different meanings, principles, and focal points (Rees,1992).
Overall, the development of urban carrying capacity can be divided into three phases. In phase 1, in the twenty years of China’s reform and opening up, insufficient natural resources and environmental destruction phenomenon emerges as the urban economy grows rapidly. While the researches on urban carrying capacity in this period considered urban resources and environment, economic development is still a primary issue for city builders. In phase 2, practitioners and academics began to attach great importance to the resource availability and environmental quality within a city from the late 1990s to the early 2000s. Currently, China, at its third stage of urban carrying capacity, is undergoing comprehensive development which should consider resource, environmental, economic, and social factors. Among these, social factors include not only the direct promotion effect brought by basic public facilities to the city but also the soft condition improvement.
Against this background, the research on urban carrying capacity has gained increasing attention in the scientific community. The term ‘carrying capacity’ was first proposed in studies of physics, demography, and biology (Plumb et al.,2009). With advances in research on UCC, previous published studies are limited to a single content, such as land carrying capacity (Zhao et al.,2019; Tang et al.,2021), water resource carrying capacity (Song et al., 2011; He et al.,2018; Yang et al.,2021), tourist environmental carrying capacity (Pu et al.,2020; Wang et al.,2020) and economy carrying capacity (Di et al.,2016).
From the perspective of the whole research process, although the connotation of carrying capacity is constantly enriched, the relative research about urban carrying capacity is still in its infancy. Generally speaking, recent studies have not formed a unified and robust basic theory and the model method is single. In respect of research methods of urban carrying capacity, those mainly focused on index evaluation method and system dynamics (SD) method (Wang et al.,2017; Zhou et al.,2017; Wang et al.,2020). Index evaluation methods, such as principal component analysis (Xing et al.,2013; Zhang et al.,2019), artificial neural networks (Luo et al.,2019), Expert evaluation method (Li et al.,2021) and fuzzy comprehensive evaluation method have been universally accepted because of its simple operation. Zhang et al.(2019) evaluated the variation trend of water resources carrying capacity on time scale using principal component analysis. However, the interpretation of principal component is fuzzy, which has weak explanatory value for real life. Artificial neural network prediction is based on relatively independent systems, which implies that the coupling between the systems is relatively challenging. The expert evaluation method has a certain level of subjectivity in determining the weight of the index. Due to the systemic, dynamics and feedback of urban carrying capacity, the traditional low-order and linear theories are not conducive to effectively solve this complex system problem. The SD method simulates the causality between factors through positive and negative feedback. It has the ability to deal with high-order, nonlinear and other complex system problems and is gradually used by scholars for the carrying capacity of water resources (Mashaly and Fernald, 2020) and land resources (Zhu et al.,2014). The biggest difference between SD and other methods is its own negative feedback system, that is, a readjustment of constraint conditions (Barati et al.,2019; Wang et al.,2021). Hence, system dynamics model is introduced to solve this problem. As a comprehensive simulation model, system dynamics model can be used to study the behavior of complex systems over time and interact with each other through feedback loops (Zomorodian et al.,2018).
In this study, five scenarios were designed based on the system dynamics model of Shanghai's comprehensive urban carrying capacity, which is composed of social subsystem, economic subsystem, ecological subsystem and resource subsystem. In addition, the population, economic development and green ecological index of each scenario were simulated and predicted. In conclusion, this paper establishes a coupling model composed of a society-economy-ecology-resource(‘SEER’) subsystem to comprehensively evaluate urban carrying capacity, which makes up for the deficiency of single carrying capacity research. Through the green ecological index, the evaluation model of urban carrying capacity is further enriched. Five kinds of urban development scenarios, making it more comprehensive in pattern researches.