An approach to stimulate the sustainability of an eco-industrial park using coupled emergy and system dynamics

Using an emergy and system dynamics model, this paper proposes a dynamic evaluation method for the sustainable development of eco-industrial parks and conducts an empirical analysis of the Shenyang Economic and Technological Development Zone (SETDZ). Four SETDZ’s development scenarios were designed, including inertia, economic, environmental protection, and science and technology scenarios, and the sustainable development status of each scenario was simulated and dynamically evaluated. In this paper, emergy analysis and SD method are used to simulate the changes of system functional elements and emergy evaluation indexes of SETDZ. The results show that under the coordinated development of the economy and environment, the science and technology scenario based on high-tech investment is the best development strategy for SETDZ. The sustainability of the SETDZ greatly improved on the implementation of the circular economic model, and the sustainable development indicator of the science and technology scenario increased from 3.59E-02 (2014) to 8.16E-02 (2024). Furthermore, SETDZ could achieve the coordinated development of the economy and environment owing to the reasonable layout of industrial enterprises, integration of public resources, effective utilization and disposal of waste, establishment of an enterprise symbiosis system, development of cleaner production, and other measures.


Introduction
Since the 1980s, academia and governments have paid substantial attention to major issues such as population, resources, energy, and environment. Driven by the increasing pressure on the environment, there is an upsurge in industrial zone planning and construction, with a focus on eco-industrial parks (EIPs). An EIP not only improves economic quality but is also important for improving the regional environmental quality. The concept of EIP is a major research field in industrial ecology. This concept concentrates on the production of goods and services from the perspective of ecology and works to imitate a natural system through the conservation and recycling of resources (Zhao et al., 2017a(Zhao et al., , 2017b). An EIP is based on a circular economy (Li, 2011), industrial ecology principles (Roberts, 2004), and cleaner production. In that regard, waste could be reduced if industrial systems were operated more like natural ecosystems (Carr, 1998). EIPs are composed of companies, nature/ ecology, and residential areas, which establish a "producers-consumers-decomposers" cycle for industrial systems by simulating a natural system. By food chains for material and energy flows, EIPs can form mutually beneficial networks and efficiently share resources (Gibbs & Deutz, 2005). EIPs collaborate with each other and local communities to efficiently share resources (information, materials, water, energy, infrastructure, and natural habitats). This can lead to economic, environmental, and quality-of-life improvements for industries and local communities. Zhao et al. (2017a) built an evaluation index system of EIPs by using gray Delphi method and put forward that paying attention to the relevance of upstream and downstream enterprises is helpful to construct industrial chain. Through the extension and development of public infrastructure and supporting service industries, a comprehensive system can eventually form to achieve the coordinated development of an EIP and its associated cities (Geng et al., 2014). Accordingly, it is possible to add value to the overall resources of a region and to achieve mutual benefits for the environment and economy.
In 2015, China's Ministry of Environmental Protection, Ministry of Commerce, and Ministry of Science and Technology promulgated the "Administrative Measures for the National Eco-industrial Demonstration Park" and "National Ecological Industrial Demonstration Park Standard." The measures indicated that China would focus on the promotion of national-level economic and technological development zones, national high-tech industrial development zones, or other characteristic parks. Moreover, China would actively launch the establishment of eco-industrial demonstration zones. The efforts to promoting Chinese pilot EIP practices mainly concentrated on clearer and coordinated division of the competent authorities more scientific and standardized procedures and standards, more investment on relevant researches, and that the capacity for the government agency can be improved. By the end of January 2017, the National Ecological Industry Demonstration Park Construction Leading Group Office demonstrated the adoption of 48 national eco-industrial demonstration parks (Ministry of environmental protection of China, 2017). This paper evaluates the development model by analyzing the industrial chain of SETDZ and explores a new way for the sustainable development of EIPs. As a national demonstration eco-industrial park, SETDZ forms various material metabolism relationships of the industrial ecosystem, maximizes material utilization and output, and minimizes waste generation.
To assess the sustainability of EIPs, it is necessary to measure relevant factors in a unified manner. The ability to evaluate energy, materials, and currency in equivalent terms allows researchers to perform sustainability assessments for all types of systems. For quantitative comparison, emergy analysis can be used to measure the value of natural resources, goods and services, so that different types of energy have been unified (Zhang & Ma, 2021). Given the vigorous industrial park construction in China, many studies have focused on emergy evaluations of industrial parks (Liu et al., 2016). As an environmental auditing technique, emergy analysis is a systematic approach that balances the development of the natural environment and social economy, and emergy indicator systems have been established for some EIPs (Zhe et al., 2016). A specific emergy index of industrial symbiosis has been previously formulated for a comprehensive measurement of industrial symbiosis (Geng et al., 2014), in contrast to measuring the effect of the industrial symbiosis system. Through emergy analysis, the ecosystem and socioeconomic system are unified to objectively reflect the interaction and contribution of each subsystem (Cheng et al. 2017;Wan et al., 2021).
Most current research on the sustainability of EIPs focuses on the static evaluation of these systems, describes the historical sustainable development of the systems, and makes predictions according to historical development (Geng et al., 2010;Leong et al., 2016). Based on the analysis of system structure and planning, there are few research results on the system dynamics (SD) of the sustainability of such systems. SD is used to conduct analysis using different dimensions and different types of data, and is widely used for the comprehensive research of complex social, economic, and ecological systems. With the combination of qualitative and quantitative analyses, the application of SD models can be extended to the field of sustainability. In this study, emergy analysis and the SD method were adopted to evaluate the sustainable development of an EIP. The combination of static emergy analysis and dynamic SD avoids the deficiencies of using a single research method. Emergy analysis can evaluate the sustainable development of a system through historical data analysis, and the relationship between different functions in the eco-economic system can be evaluated using the SD model, allowing a more comprehensive analysis. The changes in various functions were simulated to grasp the sustainability.
In this paper, the traditional emergy index is first combined with SD to establish a model, and the simulation is carried out under different scenarios, so as to provide a new method for exploring the path of sustainable development of EIPs. This method breaks through the bottleneck in static analysis of traditional emergy index and expands the application field of emergy analysis. The rest of this paper is organized as follows. We review the relevant literature of the evaluation methods of EIPs in Sect. 2; we propose the methodology and the source of data acquisition-including the establishment of evaluation index system and SD model of SETDZ in Sect. 3; then, we design such four scenarios as inertia, economic development, environmental protection, and science and technology, analyze the industrial ecological networking of the park, and combine emergy index system and SD model to evaluate SETDZ's sustainability in Sect. 4; and we provide concluding remarks in Sect. 5.

Literature review
An EIP can improve the efficiency of material and energy use, reduce the generation of waste, and balance the inputs and outputs of natural ecosystems (Geng et al., 2010). The essence of eco-economic efficiency is to measure the impact of economic activities on the ecological environment, which is usually expressed as the ratio of value of a product or service to the environmental impact. Currently, the most widely used methods include life cycle assessment (Zhang et al., 2017), analytic hierarchy process (Leong et al., 2016), data envelopment analysis (Hu et al., 2019), and game theory (Chew et al., 2009). However, problems exist in their application, such as strong subjectivity, large amounts of data, and complex applications. Emergy analysis can avoid these drawbacks and increases the objectivity of the efficiency measurement. Emergy analysis allows the unified quantification of material flows, energy flows, currency, population, and information. The construction of an emergy evaluation index system builds "a bridge between environment and economy." The theory of emergy accounting was established in the 1980s by Odum (1996). Emergy refers to the amount of another type of energy contained in a certain flow or stored energy; that is, the sum of one type of energy put into application during the formation of product or service. Since the energy of various resources, products, or labor services directly or indirectly originate from solar energy, emergy is used to measure the certain energy. A quantitative analysis is to assess the utilization of natural resources in the ecosystem. A unit emergy value (UEV), refers to the amount of solar energy contained per unit of material or energy (Odum, 1996). By means of a UEV, different types of energy and substances flowing and stored in the ecosystem can be converted into the same standard emergy. In natural ecosystems and social economic systems, the UEV of products and services such as complex life, human labor, and high-tech is relatively high. Some major kinds of UEVs include the transformity (Sej/j), specific emergy (Sej/g), emergy per unit money (Sej/$), and emergy per unit labor (Sej/y, Sej/h, or Sej/$) (Zhao et al., 2019). The geobiosphere emergy baseline (GEB) is the emergy of the geobiosphere that primarily drives the emergy flow, and it has reference value for emergy flows in emergy evaluation process using UEVs. The total emergy of the geobiosphere, as calculated by Brown et al. (2016), is 12.0E + 24 Sej/y, which is used as the emergy baseline for this paper. With emergy accounting developed, some studies have combined additional technical methods with emergy accounting. Giannetti et al. (2006) introduced the ternary diagrams commonly used in materials science into emergy calculation and environmental accounting and created graphical tools for the ternary graphs. Subsequently, the emergy ternary diagrams were used to compare environmental and energy diagnoses between Brazil, Russia, India, China, South Africa, and the USA (Giannetti et al., 2013). Zhao et al. (2020) analyzed the product supply chain with the aid of the auxiliary line of the emergy ternary diagram. Vega-Azamar et al. (2013) assessed urban environmental sustainability by using the resource flow lines of an emergy ternary diagram and compared the Island of Montreal with nine other urban centers in Canada.
The combination of SD and other research methods can allow the establishment of a simulation model for use in the field of sustainability. The combination of the SD model and emergy accounting can clearly describe the coupling effect and feedback of various influencing factors, and can simulate the trend prediction of sustainable development systems. Fang et al. (2017) established an SD model of emergy flow for an eco-economic system and considered different scenarios to study the impact of economic growth and investment in environmental protection on the sustainability of cities. Franco (2019) used the SD model to simulate the effect of slowing down and closing the resource cycle in the product supply chain design under a circular economy system. The design and evaluation of the circular economy development model depend on the interrelation of variables and the dynamic changes in a sustainable ecosystem. SD can specifically facilitate the understanding of such complex systems and construction of models (Honti et al., 2019). Inês et al. (2019) established an SD model for information transparency based on fuzzy cognitive mapping to analyze the impact of energy change on sustainability.

Data acquisition
Take Shenyang Economic and Technological Development Zone (SETDZ) as an example, this paper comprehensively analyzes an evaluation method of sustainability for EIPs. SETDZ was built in June 1988, approved as a National Eco-industrial Demonstration in January 2014. SETDZ is located in the southwestern part of Shenyang. There are 2021 types of industrial enterprises in SETDZ, including 83 transnational corporations and 231,000 employees. SETDZ employs a circular economic model by fostering cleaner production companies and thereby realizes a reduction of waste emissions. SETDZ has six major industrial clusters, which are equipment manufacturing, automobile and parts manufacturing, pharmaceutical and chemical, food processing, building materials, and textile industries.
Since 2010, SETDZ's industrial eco-chains have been constructed. Companies in EIPs are guided by high-value-added, low-pollution, high-tech industries, and gradually accomplish the adjustment, reconstruction, transformation, and upgrading of the industrial structures of their EIPs. This paper uses the pharmaceutical and chemical industry as an example, to illustrate the symbiosis in industrial network integration. The symbiotic relationship among the pharmaceutical, chemical industries and their surrounding industries is shown in Fig. 1. SETDZ establishes and improves comprehensive utilization management systems for resources, extends industrial chains, increases resource utilization, and builds demonstration bases for the sustainable development. The data were drawn from "Shenyang Statistical Yearbooks (2008-2018)," "Tiexi Statistical Yearbook (2008-2018)," "Environmental quality report of SETDZ (2009-2019)," and "Construction planning of Shenyang Tiexi ecological industry." Based on the analysis of SETDZ system structure and its influencing factors, this paper analyzes the emergy of the system and constructs the system emergy evaluation index system, then builds the SETDZ system dynamics model and carries out simulation under different scenarios, so as to explore the optimal model for the sustainable development of SETDZ.

Emergy index system
For a quantitative comparison, emergy analysis can be used to measure the true value of natural resources, goods, and services, through unifying different kinds of emerge. The steps of emergy analysis: (1) Collect data on the natural environment, resources and economic activities.
(2) Draw a detailed emergy flow diagram, and summarize the relationship among each emergy flows. (3) According to the corresponding UEV of each resource, compile an emergy analysis table. (4) Establish an emergy index system to analyze the ecoeconomy based on the emergy analysis table. (5) Dynamically simulate the main factors that play a decisive role in development, and estimate and predict the development path. The flowchart of emergy analysis steps is shown in Fig. 2.
By emergy accounting, the ecosystem and socioeconomic system are unified in order to reflect the mutual influence and contributions of each subsystem. Song et al. (2012) divided the sustainable development of EIPs into three dimensions: social, economic, and environment. According to the three-dimensional positioning of the EIP,

Fig. 1
Eco-industrial network of pharmaceutical and chemical industries and their surrounding industries in SETDZ this measure is taken to assess the ecological efficiency and sustainability of the compound system. When an EIP's sustainability is evaluated, it is necessary to distinguish the utilization of resources in the socioeconomic and environmental subsystems. Each subobjective set includes indicators which address different terms; consequently, they constitute a comprehensive framework for EIP evaluation.
There are multiple emergy flows in EIPs. The emergy of renewable natural resources (waves, tide, earth cycle) is denoted by R. The emergy of a nonrenewable resource in the system is denoted by N. Purchased emergy is denoted by F, indicating inputs imported from outside of the system. Yield emergy is denoted by Y, indicating the emergy of the outputs. The emergy of wastes is denoted by W, indicating wastes that are ultimately excluded. The total emergy in the system is denoted by U and is the sum of R, N, and F.
Based on emergy accounting and the characteristics of material, energy, and information flow in the EIP, an emergy analysis system is established. The emergy analysis system comprehensively reflects the structure, function, and efficiency in eco-economic systems in EIPs. This provides a scientific basis for the development of circular economies in EIPs. First, comprehensive indicators describe the sustainable development capabilities of EIPs. Second, the system-level indicators include three subsystems, which are economic development, social acceptability, and environmental compatibility, to assess the performance of the complex eco-economies in an EIP. Third, a specific variable layer is introduced. The various emergy indicators and their meanings are shown in Table 1.
The evaluation indicators of economic development include EDR and EYR. EDR is the ratio of total emergy use and industrial added value of the park in one year (Ascione, et al., 2009;Tao et al., 2013).
The indicator synthetically evaluates the degree of development of the EIP. The more the industrial park develops, the lower the EDR is, since the base of industrial added value is bigger and the utilization efficiency of various resources is higher.
EYR is the ratio of the total emergy output to the emergy purchased from the society (including fuels, goods and services), and it is an evaluation index that measures the contribution of the industrial park to the social economy (Ulgiati S. et al. 1998;Mu et al., 2011). The indicator reflects the utilization efficiency of resources. The higher the EYR, the higher the production efficiency of the system. A high value indicates that industrial production is competitive and that the economic benefits are great.
The evaluation indicator for environmental compatibility includes EWR and ELR. EWR is the ratio of the sum of emergy, with "three wastes" (waste gas, wastewater, and solid wastes), to the total emergy, which is used to measure the pressure of wastes on the ecosystem.
ELR is the ratio of purchased and nonrenewable local emergy to the free/renewable resource emergy (Ulgiati S. et al. 1998;Mu et al., 2011).
EIPs only provide a small amount of natural resources, and most renewable resources need to be purchased from the outside world. EIPs with a high degree of industrialization have high energy utilization in the system. The higher the ELR, the greater the utilization ratio of the nonrenewable resources, and the greater the load-bearing pressure of the entire ecological environment.
The evaluation indicators for social acceptability include ED and CP. The ED is the ratio of the emergy created by production processes to the area of the EIP (Ascione, et al., 2009;Tao et al., 2013).

Indicators of economic development
Ratio of emergy to GDP (EDR) A measure of emergy inputs for generating per unit of money Emergy yield ratio (EYR) A measure of outputs a process will contribute to the economy Indicators of environmental compatibility Environmental load ratio (ELR) A measure of ecosystem stress resulting from production Ratio of wastes to the total emergy (EWR) A measure of pressure of waste to the system environment Indicators of social acceptability Emergy density (ED) A measure of intensity of the emergy inputs per unit area Carrying population (CP) A measure of capacity of the population under the current environment Indicator of sustainable development Sustainable development indicator (ESI) A measure of the contribution of a resource or process to the economy per unit of environmental load In the formula, A is the land area. This index reflects the degree of intensive land use in the park. The higher the ED, the higher the output of the land per unit of the EIP.
The CP is the ratio of available and per capita emergy usage (Ulgiati et al., 1994, Nakajima et al. 2016).
In the formula, P is the population. This indicator calculates the population carrying capacity by using the available emergy. The available energy in the park does not include purchased emergy. The higher the indicator, the more population the park can carry.
The evaluation indicator for sustainable development is ESI. The ESI is the ratio of the emergy output rate to the ecological environmental load rate and is used to evaluate the sustainable development ability of the system (Ulgiati S. et al. 1998;Mu et al., 2011).
The EYR is used to evaluate the output efficiency of the system, and the ELR is used to evaluate the environmental pressure on the system. The higher the ESI, the greater the sustainable development ability of the EIP (Zhao et al., 2019).
The emergy analysis method is used to draw an actual emergy flow system diagram for the SETDZ through actual investigation. A detailed emergy diagram of the SETDZ is drawn to characterize the flows of various streams in the park. The industrial metabolism involves all processes, i.e., physical, chemical, biological, and information transfer, which tend to achieve a given aim, i.e., a product (material or energy) or service. The emergy flow diagram includes the main components and interrelationships of the system and the directions of material flows, emergy flows, and currency, as shown in Fig. 3.
An emergy analysis table is compiled to determine the number of emergy flows, such as energy (J), material (g), and currency ($) flows. According to the corresponding UEVs from various resources, different energy units are transformed to a unified emergy unit. The main emergy flows of the SETDZ before and after implementation of the circular economy program are shown in Table 2.
According to the emergy flow table, the emergy evaluation indicators of the SETDZ are calculated, and the results are shown in Table 3.
The data in Tables 2 and 3 are related to the production methods of basic industries such as the equipment manufacturing, metallurgy, pharmaceutical, and chemical industries in the SETDZ. The development of such industries consumes a large amount of natural resources, and the demand for natural resources also increases with the expansion of the scale.

System dynamics model
The steps of the EIP's system dynamic model are as follows: (1) Determine the system boundary of the EIP's industrial scope, endogenous, and exogenous variables of the system.
(2) Find out the feedback loop in the EIP system, and explain the causal relationship and changes of variables. The "Check" function in Vensim can be used to analyze the structure of the model to determine whether the system model effectively presents the characteristics of the eco-economic system. The research base year is 2008, the time step is one year, and the operation cycle is 2008-2028. Taking region of SETDZ as the system boundary, the EIP is regarded as an emergy system, and the relationship among the social, economic, and ecological subsystems is analyzed. According to the quantitative relationship and emergy flows of SETDZ ecosystem, the system dynamics equations are established. Combined with the comprehensive index of emergy analysis, the development status and sustainability were simulated, and the SD flow diagram is shown in Fig. 4.  In the SD model of SETDZ, the average method is used to calculate some parameters of GDP and the capital flow of new fixed asset investment, and the exponential smoothing method is used to process the time series data. Population is the consumer of various resources, and outputs products and services, and it is simulated by birth rate and mortality, immigration rate, and emigration rate. The key of industrial ecological chain is the material emergy in the system, which can be calculated through UEV, as shown in Table 2 and Table 3 for details.
In this paper, the reliability of the simulation model is evaluated by comparing the difference between the simulation value and the existing statistical data. Table 4 shows the test results of model authenticity, and these results are basically consistent with the development of industrial ecosystem in the new area, with a relative error between-8% and 10%. This model can accurately describe the current situation of SETDZ's References in Table 2 are as follows. a: Odum (1996)

Results and discussion
Combined with the planning of the SETDZ, four typical scenarios were designed, namely inertia, economic, environmental protection, and science and technology scenarios. The purpose of the scenarios was to comprehensively analyze the sustainability of the SETDZ and explore the best scenario for SETDZ sustainability. The adjustment schemes for the four scenarios are shown in Table 5. Based on the current science and technology investment, industrial layout, and waste treatment level, Scenario 1, i.e., the inertia scenario, simulates the evolution of the ecosystem and demonstrates the sustainable development of the industrial park.
Under Scenario 2 which denotes the economic scenario, the industrial park reduces the proportion of investment in other industries, while increasing the investment in secondary industries and nonrenewable resources that contribute the most to gross domestic product (GDP), to maximize economic benefits.
Under Scenario 3 which denotes the environmental protection, the industrial park reduces the proportion of investment in primary and secondary industries that have a greater negative impact on the environment, increase investment in tertiary industries, and purchases energy with less negative impact on the environment, thereby maximizing environmental benefits.   By introducing new technologies and equipment under Scenario 4 which denotes the science and technology scenario, the industrial park improves the technological factors of the industry, maintains the investment and labor ratios of various industries, and increases the impact of different waste energy utilization rates and purchased energy on sustainability.

Analysis of economic development
In recent years, the economy of SETDZ has developed rapidly. Figure 5 shows that the EDR is dropping after the implementation of circular economic model. The lower the EDR is, the higher the economic benefits. The production efficiency and emergy application efficiency of SETDZ have been continuously improved, mainly owing to the measures taken by the park, in addition to constantly adjusted reform measures. Scenario 2, which focuses on economic development, has the fastest GDP growth. GDP growth rates in Scenario 3 and Scenario 4 decreases in turn. Scenario 1 with the slowest GDP growth cannot meet the economic expectations. It can be seen that the economic benefit in SETDZ increasingly depends on less natural resources, and SETDZ requires less emergy inputs than before implementing the circular economic model to produce the same GDP. Future development in Scenario 1 is obviously the highest, but this model ignores environmental and social development. In Scenario 4, GDP has been effectively improved while taking into account the three aspects of economy, environment, and society; this indicates that the sustainable development system is more dynamic.
The EYR indicates locally available renewable or nonrenewable emergy flows that are exploited by emergy investments from outside of the system. In Fig. 6, the EYR of Scenario 2 has been stably increased due to the circular economic model, and the value in 2028 of EYR is nearly twice than the value in 2008 (from 8.68E-01 to 1.79E + 00). Meanwhile, the scale of the economy is expanding, and SETDZ reliance on local resources remains basically unchanged. Although the single pursuit of economic development can meet the economic expectations, the coordinated development could make SETDZ be full of vitality. The development of SETDZ depends on domestic resources, and the emergy purchased abroad from Scenario 2 and Scenario 3 is small. The EYR in Scenario 2 and Scenario 3 is higher than the current development model, while Scenario 4 has less output due to the huge investment in the early stage. Therefore, by improving the scientific and technological level and increasing the added value of output products, the steady improvement for production efficiency of resources can be realized so that the sustainable development could be implemented.

Analysis of environmental compatibility
The ELR indicates the environmental load of nonrenewable flow dominated by human beings. The lower the ELR is, the less the pressure on the environment is (Jiang et al., 2007). In Fig. 7, the ELR of Scenario 4 has dropped from 3.96E + 01 to 2.27 + 01 in 2010-2028, ELR also decreases in the other three scenarios. With SETDZ industries continuing to expand the scale of the industrial economy, the pressure on the environment is declining. However, it is very difficult to completely reduce the pressure on the system environment for economic development. ELR represents the environment pressure caused Fig. 6 Simulation results of EYR by system economic activities, the results in the values of Scenario 3 and Scenario 4 become slightly different and the result of Scenario 4 is better than that of Scenario 3.
In Fig. 8, the waste emission tends to be stable, and the EWR of Scenario 1 decreases from 4.74E-02 (2010) to 3.63E-02 (2020). The SETDZ has high utilization rate of renewable resources, strong system circulation capacity, and healthy development. However, EWR continues to rise and the circulation capacity tends to weaken. After 2020, with environmental protection being put great emphasis in Scenario 3, the output value increases while the utilization rate of waste is also higher. Scenario 2 and Scenario 4 both increase the input of production factors, and the utilization rate of waste is lower; this results in greater pressure on the environment. The growth rate of the final waste discharge in SETDZ lags behind the growth rate of the total emergy consumption, and the resource utilization efficiency needs to be effectively controlled.

Analysis of social acceptability
In Fig. 9, the ED of Scenario 4 drops from 3.48E + 15 sej/m 2 (2014) to 3.21E + 15 sej/m 2 (2024), a decline of 7.76%. The results indicate that the intensity of the emergy inputs per unit area is gradually declining, and the available emergy in the park is decreasing. The economy growth of the SETDZ has brought serious challenges to the local ecosystem, and some practical difficulties and obstacles still presently exist in promoting the development of the circular economy. All issues mainly include the imperfect laws and regulations, the ineffective implementation of policies and guidelines, and the weak awareness of national economy of residents, which result in the waste of resources.
The CP represents the population of emergy support in the system. The CP of Scenario 4 is 3.36E + 05 in 2018, respectively, and the actual population is 3.91E + 05, i.e., much higher than the population load. In Fig. 10, CP is the highest in Scenario 2 and the lowest in Scenario 4. The data show that economic development and social progress have led to urban agglomeration, along with increasing population and environmental problems in the region. The general problem with some contemporary industrial practices is that they are wasteful in ways that are environmentally and economically costly. The problems in the social subsystem of the SETDZ mainly include imperfect laws and regulations, an inability to effectively implement principles and policies, a lack of awareness of saving, and irrational consumption methods. The achievement of a successful EIP requires tight social interconnections based on individuals, organizations, culture, values, and institutions. Due to the abundant emergy of renewable resources, the emergy per capita shows an upward trend; this indicates that the quality of people's life is constantly being improved.

Analysis of the comprehensive indicator
In Fig. 11, the ESI of SETDZ increases in all four scenarios. After implementation of the circular economic model, the ESI of Scenario 4 increases from 3.59E-02 (2014) to 8. 16E-02 (2024), and sustainability improved considerably. When ESI < 1, the sustainability of the system is low; when 5 > ESI > 1, the system is well sustainable; and when ESI > 5, the system is able to self-satisfy the conditions of sustainable development (Giannetti et al., 2013). In particular, ESI is less than 1 in the four scenarios, SETDZ is a typical resource consumption ecosystem. In Scenario 4, science and technology develops rapidly, and the sustainable development capacity of the system is also improving. In Scenario 1 and Scenario 2, the emergy of the import resources and labor services in the total emergy usage has gradually increased, and the dependence on local nonrenewable resources remains high.
The sustainability of SETDZ is gradually improved, with the main resources depending on external purchase, relatively more residents and high resource consumption industries, less renewable resource use and waste discharge. In the long run, ESI shows a trend of recovery and the proportion of nonrenewable emergy decreases; this facilitates the capacity development of EIP continuously.

Comparison of eco-economic system evaluation methods
Compared with previous studies, this paper combines the traditional emergy analysis index with SD to expand the application scope of emergy analysis. Geng et al. (2014) developed an integrated material flow analysis and emergy evaluation model to investigate the environmental and ecological benefits of industrial symbiosis implementation of SETDZ. Fang et al. (2017) established an emergy flow SD model of an urban eco-economic system, including economic, population, waste and emergy submodels. Based on their index system and system construction, we embed the emergy index into the construction of SD model, simulate the development of SETDZ, and forecast its future sustainable development trend. Specifically, in Table 6, the methods are compared from three aspects: subsystem composition, scenario setting, and index system. In contrast, we classify sustainable development into three levels: economic development, environmental compatibility and social acceptability. This is the first time that the traditional emergy analysis index is combined with SD to expand the application of emergy analysis.

Conclusion
By analyzing the ecological and economic efficiency of EIPs, the emergy method herein can solve the problem of comparability of objective, unify the dimensions, and determine the scope of the calculation. Based on the actual research results for the SETDZ, the ecoindustrial network and integration method for the EIP are analyzed. Using the emergy analysis, an evaluation index system is established and the SETDZ is assessed from the aspects of resource utilization, economic development, environmental compatibility, social acceptability, and sustainable development. By combining the emergy analysis and SD method, the SETDZ dynamic eco-economic model is established, and the deficiency of a single research method can be avoided. Based on the historical development of the system, the emergy analysis and SD method can be used to simulate the changes in the system's functional elements and emergy evaluation index, to evaluate the sustainability of the system.
We provide four scenarios and implementable strategies for the development of the SETDZ. The results show that the ESI of Scenario 4 is higher than that of other scenarios in the same period, and it has the least pressure on the environment and the best sustainability. Owing to the continuous expansion of the scope of SETDZ, it is difficult to reduce the environmental pressure on the system when focusing only on economic development (Scenario 2). The urban agglomeration effect has led to increasing population, environmental problems, and faster economic growth in the SETDZ, whereas sustainability has not increased consistently. Scenario 4 is the best development strategy considering the economy, environment, and society.
During the later development of the SETDZ, policies should focus on improving science and technology factors. (1) Policies should improve the industrial innovation support system and increase investment in the research and development of environmental protection technologies. Then, the integration of industrial chains can lead to cluster innovation, promote the sharing of resources, and form a closed loop for raw material reuse and recycling processes.
(2) With intelligence and capital as the driving force, policies should promote industrial technological innovation and upgrade industrial technological elements. SETDZ should increase investment in the development of new technologies for waste recycling, introduce core environmental protection technologies and equipment, and attract relevant talent.
This paper combines static and dynamic methods, embeds emergy index into the construction of system dynamics model, stimulates the development of SETDZ, and forecasts the future sustainable development trend. From the perspective of function flow, the subsystem of EIP system is classified; this provides a new idea for the research of SD in the field of EIP's sustainable development. In the future, the application scope can be expanded. Macroscopically, it is used to simulate the sustainable development of regions, such as urban regions or countries. Microscopically, it is used to simulate the recycling of waste, such as recycled concrete and other construction waste.