Ecological Safety Assessment and Convergence of Resource-Based Cities in the Yellow River Basin

Abstract

Promoting the sustainable development of resource-based cities is of great significance for the ecological protection and high-quality development of the Yellow River Basin. In order to solve the dilemma of the sustainable development of resource-based cities in the Yellow River Basin, this paper constructs an ecological security evaluation system. It calculates the ecological security level of 30 resource-based cities in the Yellow River Basin from 2006 to 2020 using the TOPSIS model and carries out a classification convergence analysis. The DID empirical test of ecological security factors by sustainable development planning policies is used to distinguish the development characteristics of different resource-based cities. The results show that (1) the ecological security level of resource cities in the Yellow River Basin is generally well developed, and there are differences between different types of resource cities; (2) the resource cities in the Yellow River Basin mainly rely on industrial transformation to improve the ecological security level; and (3) the local governments pay limited attention to environmental protection.

1. Introduction

The ecological protection and high-quality development of the Yellow River Basin is an important national strategy to which the CPC Central Committee attaches great importance. The Yellow River Basin is an important energy economic belt in China. The Yellow River flows through seventy-four prefecture-level cities in nine provinces, including thirty resource-based cities [1]. Resource-based cities are the national energy strategic guarantee and the important support for the high quality of the national economy. The sustainable development of resource-based cities is not only an important strategic issue in China’s modernization but also a global issue. Of the fourteen coal bases planned by the state, nine are located in the Yellow River Basin, with total coal resources accounting for 40% of the country’s total and output approaching 69.7%. The Yellow River Basin is not only an important area of coal resources and raw coal production and processing in China but it is also a relatively fragile ecological area. Coal mining has a significant impact on the water and sediment environment of the Yellow River [2].

China has always attached great importance to the ecological management of the Yellow River Basin, especially the regulation of water and sand, soil conservation, and the restoration of the ecological functions of the Yellow River. In 2000, the Chinese government formulated the “Western Development Strategy” in order to promote the economic development of the backward western region, promote the coordinated development of the western region and the eastern region, and narrow the regional development gap. Resource-oriented cities in the Yellow River basin are important pillars of western China’s economy, and this period was mainly dominated by investment promotion and opening up to the outside world, attracting a large amount of capital and projects to the west, promoting infrastructure construction, industrial transfer, and ecological protection, and driving economic growth. Duan Hanming and other scholars [3] believe that the ecological environmental protection and reconstruction of the western region is the primary solution to the “Western Development Strategy” and can effectively promote the economic development of the western region and narrow the gap with the eastern part of economic development. In 2010, the Chinese government summarized its experience and further improved its “Western Development Strategy”, proposing ecological construction and environmental protection, realizing ecological improvement and increasing farmers’ income as the goal of economic development, doing a good job of returning farmland to grassland, protecting natural forests and treating the Beijing–Tianjin wind and sand source, building a number of large-scale, high-yield, high-efficiency, low-waste coal production bases, and establishing a reasonable mechanism for pricing electricity sent from the western region to the eastern part of the country. The government sought to strengthen the exploration of mineral resources in the western region, increase the public welfare survey and evaluation of capital investment, implement mandatory protection of important mineral resources, improve the comprehensive utilization rate of resources, and gradually build the western region into the national energy using mineral resources from the main replacement area. Shi Bihua [4] evaluated the economic development achievements after the founding of new China. The “Western Development Strategy” led to historical and environmental reasons for the limitation and was the most difficult task of regional development policy.

Resource cities in the Yellow River Basin have strong resource advantages and have been given the opportunity for rapid development under the “Western Development Strategy”, and the environmental pollution situation has been greatly improved. Wang Chunyan and Wang Gang [5] compared the investment environment of resource cities in the Yellow River Basin, Baiyin, and Jinchang City. Baiyin has fewer types of mineral resources than Jinchang, and the level of infrastructure, human resources, and economic development is not as high as that of Jinchang City, but the environmental pollution situation has been improved and the investment environment has been significantly improved. In 2013, the Chinese government issued the “National Plan for the Sustainable Development of Resource-Based Cities (2013–2020)” (hereinafter referred to as the “PLAN”), the aim of which is that by 2020, the historical problems of resource-based cities will be basically solved, the capacity for sustainable development will be significantly improved, the pattern of harmonization between resource opening and economic and social development and ecological and environmental protection in resource-based areas will be basically formed, and a long-term mechanism for promoting the sustainable development of resource-based cities will be established and improved. A long-term mechanism for promoting the sustainable development of resource cities has been established. The “PLAN” complements the “Western Development Strategy”. It clarifies that resource-rich and ecologically fragile areas in the Yellow River basin, such as western Qinghai and Inner Mongolia, should integrate resource, environmental, social, and economic development.

In 2021, China released the “Outline of the Plan for Ecological Protection and High Quality Development of the Yellow River Basin”, which provides a more systematic and comprehensive development plan for the Yellow River Basin. It mentions the construction of the Yellow River City Cluster and the coordination of regional development, but the policy for the sustainable development of resource-based cities is not clear and needs to be completed. Therefore, this paper takes the resource cities in the Yellow River Basin as the object of research from 2006 to 2020 and includes four steps. First, measure the ecological security level of resource cities; second, analyze the characteristics of changes in ecological security level and factors affecting it; third, evaluate the impact of the “PLAN” on the ecological security level of Yellow River Basin resource cities; and finally, propose a plan for the sustainable development of Yellow River Basin resource cities.

2. Research Objectives

2.1. Ecological Security Evaluation Indices of Resource Cities in the Yellow River Basin

The scientificity and rationality of the ecological security evaluation index system determine the credibility and effectiveness of the quantitative evaluation. This paper constructs a set of ecological security evaluation index elements for resource cities in the Yellow River Basin, taking into account existing studies, China’s ecological environment technical documents, and relevant policy requirements.

Kesler [6] established the evaluation framework of regional ecological safety of coal mining, mainly considering the impact of coal mining on the regional ecological environment. Costanza and others [7] further refined the evaluation index system of the ecological safety of mining areas. Aigbedion and others [8] constructed the index system, including land structure stability, biodiversity, air pollution, water pollution, and other factors, in the study of the regional ecological safety of mineral resources in Nigeria. Maxim and others [9] increased vegetation, air and water pollution, and surface collapse. Ness et al. [10] used the DPSIR model to construct the evaluation index of ecological sustainable development of resource-based cities and analyzed the spatial changes of urban ecology before and after environmental constraints.

In China, scholars construct the ecological safety index system of resource-based cities, focusing on urban land structure, urban ecological function, urban interference, and other aspects to complement the ecological evaluation index system of coal resource-based cities. Yu Jian et al. [11] added a regional development index to study the ecological safety of coal resource-based cities in Anhui. Cao Gang et al. [12] added indicators such as construction land pressure, land use structure, and land production pressure to study the ecological safety evaluation of Linxiang City. Cui Xinyue et al. [13] added regional policy response indicators such as scientific research, education, and energy conservation to study the ecological safety level of the Yangtze River Delta urban agglomeration. They found that the ecological safety of resource-based cities in Anhui Province was slightly worse. Liu Surong and Yang Huimiao [14] relied on big data technology to survey the ecological environment assessment index system of resource-based cities using the PSR analysis framework in CNKI from 2006 to 2016 and summarized thirty-nine ecological environment assessment index systems of resource-based cities with four layers, three dimensions, and eleven elements. Lu Guozhi et al. [15] used the PSR model to analyze the ecological safety of Shizuishan, a coal resource-based city, and added indicators, such as coal resource exploitation and the mining industry investment ratio, and obtained the overall change in ecological safety through obstacle measurement model and gray prediction. Over-exploitation and limited environmental treatment are the main obstacles and factors of ecological safety. There are studies about the causal relationship between natural climate, water resources, land use, and other ecological factors, human health, and living environment. Zhao Xiang and He Guizhen [16] used CiteSpace Ⅲ software to summarize the research on the DPSIR analysis framework at home and abroad from 1998 to 2019. The DPSIR method has matured in small-scale land and water resources research and needs to be improved in large-scale research such as agriculture, marine area, and cities. In the research by Shi Xixi and Yang Li [17], the indicators of resources and science and technology systems were added, and the coordination of sustainable development in the Yellow River Basin from 2008 to 2018 was evaluated. It was considered that attaching importance to ecological protection would not reduce the speed of economic development, while unreasonable economic development mode was the root of conflict, and resource productivity was the key factor to solving the conflict. The nexus of ecology–economy–social development could be explored from the perspectives of ecological pollution control, sustainable development, and technological progress. Du Yong [18] selected twenty-six indicators from four aspects: resource safety, economic development, people’s livelihood and well-being, and environmental protection to evaluate the ecological civilization of resource-based cities in China. Chen Dan and Wang Ran [19] constructed an index evaluation system of three dimensions: environmental carrying capacity, intensive use of resources, and environmental quality, and compared the development level of ecological civilization of mining cities in the Middle East and the West according to the regional characteristics of coal mines.

2.2. The Political Basis for the Evaluation of Indicators for Ecological Security in the Yellow River Basin

The ecological technical evaluation documents issued by the ecological and environmental protection departments are listed in

Table 1. Technical paper on environmental impact assessment in China.

The Technical Specification on the State of the Ecological Environment
Remote Sensing Indicators	Habitat Quality Index	Construction land	Grassland	Cropland	Woodland
Monitoring Indicators	Erosion Level	Pollutant Discharge Compliance Rate	Water Quality Compliance Rate	Air Compliance Rate
Statistical Indicators	Water Resources	Pollutant Gas Emissions	Solid Waste Emissions	Regional Precipitation	Sanded Area Ratio
Measures for Evaluation of Regional Ecological Quality
Ecological Pattern	Habitat Quality Index	Ecological Land Area Ratio Index	Ecological Spatial Connectivity	Ecological Red Line Area
Ecological Function	Soil and Water Conservation Index	Water Conservation Index	Wind and Sand Conservation Index	Greenland Rate Index	Vegetation Cover Rate
Biodiversity Priority	Conservation Biology Index	Biota Vitality Index	Percentage of Species in Native Functional Groups
Ecological Stress	Land Development Disturbance	Maritime Development Intensity	Natural Disaster Index
The Guidelines for Evaluation of Resource and Environmental Carrying Capacity and Suitability for Territorial Spatial Development
The Importance of Ecological Protection	Water Conservation Function	Soil and Water Conservation Function	Biodiversity	Wind and Sand Stabilization
Ecological Vulnerability Assessment	Soil and Water Erosion		Rocky Desertification		Land Desertification
Evaluation of the Suitability of Agricultural Production	Cultivation	Animal husbandry	Fishery
Suitability for Urban Construction	Unsuitable Areas for Urban Construction
Carrying Scale Evaluation	Agricultural Production Carrying Capacity			Urban Construction Carrying Capacity
The Technical Specification for National Ecological Condition Survey and Evaluation—Evaluation of Ecological Problems
Soil Erosion	Calculated using the Soil Loss Equation
Soil Siltation	Vegetation cover
Degree of Rock Desertification	Degree of Slope	Vegetation Cover		Vegetation Cover Rockiness
Degree of Forest Degradation	Ratio of Forest Biomass to Maximum Undisturbed Biomass
Degree of Grassland Degradation	Ratio of Vegetation Cover to Undegraded Grassland Vegetation Cover
Degree of Wetland Degradation	Wetland Shrinkage Area	Eutrophication Index

. “The Technical Specification on the State of the Ecological Environment” is mainly divided into remote sensing data, monitoring data, and statistical data, including land use types, atmospheric and water quality monitoring data, solid waste emissions, and other statistical indicators. The “Measures for Evaluation of Regional Ecological Quality” focuses on the evaluation of ecological quality in terms of regional ecological patterns, functions, and species diversity. “The Guidelines for Evaluation of Resource and Environmental Carrying Capacity and Suitability for Territorial Spatial Development” analyzes carrying capacity from the perspective of territorial use methods. “The Technical Specification for National Ecological Condition Survey and Evaluation—Evaluation of Ecological Problems” analyzes the technical evaluation requirements for various ecological safety events from the perspective of possible ecological safety problems.

2.3. Ecological Security Assessment Index System in the Yellow River Basin

Already, scholars using the ecological evaluation research indicator system are concentrated in the four categories of resources [20,21,22], society [23,24,25,26], economy, and ecology [27,28,29,30]. The indicators in technical documents are concentrated on ecological quality, while the ecological expectation of the national strategy and policy aims to improve the comprehensive development of society and economy through the guidance of scientific and technological innovation and the optimization of industry. This paper summarizes all kinds of technical documents from three perspectives of pressure, threat, and carrying capacity of ecological security and constructs an ecological security evaluation index system of the Yellow River Basin with reference to remote sensing data and statistical data in the technical specification of the ecological environmental condition, as shown in

Table 2. Ecological safety evaluation index system for resource-based cities.

Category	Primary Variable	Secondary Variable	Influence
Ecological Pressure	Social Development	Population density	(−)
		Per capita GDP	(−)
		Urbanization rate	(−)
Ecological Threat	Environmental Pollution	Wastewater	(−)
		SO2	(−)
		Dust	(−)
		PM2.5	(−)
Ecological Carrying Capacity	Comprehensive Control	Solid waste utilization	(+)
		Centralized processing	(+)
		Harmless	(+)
		Greening area	(+)

. The state formulated the “PLAN” in 2013, which is more compatible with the sustainable development goal of resource cities in the Yellow River Basin, and it is proposed that it should be controlled from the population density, optimized industrial structure, strengthened scientific and technological investment, and environmental regulation and control. In this paper, four indicators, namely, population density, the proportion of the tertiary industry, the proportion of green inventions, and the frequency of environmental protection words, are used as control variables to evaluate the “PLAN”. This paper uses the range method to standardize the treatment and adopts the Equation (1) for the positive index and the Equation (2) for the negative index.

$$S_{i,j}=\frac{X_{i,j}-\min X_i}{max X_i-\min X_i}$$

(1)

$$S_{i,j}=\frac{\max X_i-X_{i,j}}{max X_i-\min X_i}$$

(2)

where $X_{i,j}$ is the original data $\max X_i$ is the maximum and $\min X_i$ is the minimum value of the i-th index.

3. Research Methodology

3.1. Calculation Model for the Ecological Safty Level

In this paper, we refer to Yu Jian et al. [11,31], who used the entropy weight fuzzy material element model to evaluate the ecological security of resource cities and compared it with the multi-indicator comprehensive evaluation method, and the multi-indicator comprehensive method obtained consistent analysis results. Based on the comprehensive evaluation of the actual level of ecological safety by the entropy weight method, the ideal point ranking (TOPSIS) model calculates the gap between the actual level and the ideal level by the ideal point ranking method and comprehensively obtains the ecological safety index [32,33], which ranges from 0 to 1. The higher the index, the higher the ecological safety level.

The entropy weighting method is a kind of objective scoring method. The index weight is determined by two factors: one is the degree of index change and the other is the influence of index change on the result. The greater the range of change range of the indicators, the greater the impact on the results and the higher the weight, and vice versa. Specific calculation are shown as follows:

$$F_{i,j}=\frac{S_{i,j}}{{{\displaystyle \sum }}_{i=1}^m{S}_{i,j}}$$

(3)

$$E_j=-\frac{1}{lnm}{{\displaystyle \sum }}_{i=1}^m{F}_{i,j}\ln \left(F_{i,j}\right), 0\le E_j\le 1$$

(4)

$$W_j=\frac{\left(1-E_j\right)}{{{\displaystyle \sum }}_{j=1}^n\left(1-E_j\right)}$$

(5)

They refer to the proportion of the value of the i-th evaluation object under the j index after standardization to the sum of the indices, the information entropy of the item j index, which is obtained by calculation, and the weight of the j-th indicator. $F_{i,j}{E}_j{F}_{i,j}{W}_j$.

Under the multi-objective decision making of limited systems, TOPSIS comprehensively calculates the ecological safety level according to the distance between positive and negative ideal points in different years by measuring the gap between the ecological safety level and the ideal state. Specific calculation formulae are given as follows:

$$V_{i,j}=S_{i,j}\times W_j$$

(6)

$$V^{+}={\left(V_{i,j}\right)}_{max}; V^{-}={\left(V_{i,j}\right)}_{min}$$

(7)

$$D_i^{+}=\sqrt{{{\displaystyle \sum }}_{j=1}^n{\left(V_{i,j}-V^{+}\right)}^2}$$

(8)

$$D_i^{-}=\sqrt{{{\displaystyle \sum }}_{j=1}^n{\left(V_{i,j}-V^{-}\right)}^2}$$

(9)

$$C_i=\frac{D_i^{-}}{\left(D_i^{+}+D_i^{-}\right)}$$

(10)

They refer to the weighted index matrix; the correct the ideal solution; and the negative ideal solution. They refer to the distance between the evaluation of the actual urban ecological safety level and positive and negative ideal solutions, and they refer to the calculated ecological safety index. $V_{i,j}{V}^{+}{V}^{-}{D}_i^{+}, D_i^{-}{C}_i$.

3.2. Regional Differences in Ecological Safety Level: σ Convergence and β Convergence

Regional coordinated development is an important element of ecological protection and high-quality development in the Yellow River Basin. To examine whether the ecological security level of resource-based cities in the Yellow River Basin has regional coordination, σ convergence and β convergence are used to analyze the method. σ convergence refers to the tendency of the ecological security level of different resource cities to gradually reduce the magnitude of deviation from the average value over time and is used to evaluate the convergence analysis of ecological co-security in the Yellow River Basin. It is a common method [34] to calculate σ convergence of the coefficient of variation, and the basic formula is as follows:

$${\sigma }_i=\frac{\sqrt{\frac{1}{N}{{\displaystyle \sum }}_{i=1}^N{\left(C_{i,t}-\overline{C_i}\right)}^2}}{\overline{C_i}}$$

(11)

where N represents the number of resource-based cities in the Yellow River Basin. It is the ecological safety level value of a resource-based city in the Yellow River Basin in a certain year and the average value of ecological safety water in resource-based cities. $C_{i,t}{C}_i$.

Beta convergence examines the changing trend of ecological safety in different resource-based cities from the perspective of the ecological safety growth rate, and beta convergence considers the conditional beta convergence of heterogeneous resource-based cities under the condition of control variables. It uses the classical β convergence influence difference analysis as follows:

$$\ln \left(\frac{C_{i,t+1}}{C_{i,t}}\right)=\alpha +\beta ln{C}_{i,t}+{{\displaystyle \sum }}_{k=1}^n{\theta }_k{X}_{k,i,t}+{\epsilon }_{i,t}$$

(12)

It is the ecological safety level value of a resource-based city in the Yellow River Basin in a certain year. It refers to the growth rate of ecological safety level from t to t + 1 in a resource-based city with the k control variables. It refers to the regression coefficient of the control variables. If it is 0, it is conditional convergence, and 0 is absolute convergence. If it is positive, it means that the ecological safety level tends to converge conditionally; otherwise, it means that the ecological safety level diverges. According to the calculation results, the convergence rate s, T = 15 can be calculated in this paper. At the same time, the half-life cycle t can be calculated, which indicates the time needed for cities with low ecological safety levels to catch up with cities with high ecological safety levels. $C_{i,t}\ln \left(\frac{C_{i,t+1}}{C_{i,t}}\right) X_{k,i,t}{\theta }_k{\theta }_k>{\theta }_k=\beta <0s=-\frac{\ln \left(1+\beta \right)}{T}t=\frac{\ln \left(2\right)}{s}$.

3.3. Analysis of Factors Influencing the Level of Ecological Safety Level under Sustainable Development Policy

In 2013, China issued a sustainable development plan for resource-based cities. This paper takes Tc as the difference variable of ecological safety level to measure the change level of ecological safety of resource-based cities in the Yellow River Basin and introduces the time dummy variable dt, which is set as dt = 0 from 2006 to 2012 before the policy was issued and dt = 1 from 2013 to 2020 after the policy was issued. A double difference model is expressed by Equation (13)

$$T{c}_{i,t}={\beta }_0+{\beta }_{1}d{u}_{i,t}+{\beta }_{2}dt\ast {{\displaystyle \sum }}_{k=1}^n{\beta }_k{X}_{k,i,t}+U_{i,t}+\epsilon$$

(13)

It represents the ecological safety difference in the last two years, dt and du are dummy variables for time and region, and dt* is an interactive item, which represents the difference in ecological safety in the last two years.$T{c}_{i,t} X_{k,i,t}$.

In the development process of growth-type and mature resource-type cities, the contradiction between resource development intensity and ecological environmental protection is prominent [35], and the problems left by resource depletion in recession-type and regeneration-type resource cities are serious and face the urgent need for industrial structure transformation and optimization development. Therefore, this paper selects the proportion of the tertiary industry as the control variable of industrial structure transformation. In the process of transformation and development, the science and technology empowering green mining can effectively alleviate the contradiction between resource development and ecological environmental protection. At the same time, relying on science and technology for transformation and development is conducive to industrial upgrading and the optimization of resource-depleted cities and improving the quality of development. Therefore, this paper chooses the proportion of green inventions in the total number of inventions applied annually as the control variable of science and technology transformation and development in resource-based cities. In the process of resource-based city development, the government’s attention to environmental protection is of great significance for sustainable development. Therefore, this paper chooses the frequency of environmental protection words as the total number of words in the government work report as the control variable for environmental protection policy.

3.4. Overview of Resource-Oriented Cities in the Yellow River Basin

The Yellow River Basin is rich in energy resources. The upper reaches are rich in water resources, which is an important water resource conservation area in China; the middle reaches are rich in coal resources, which are distributed with important coal production bases in China; and the lower reaches are rich in oil and natural gas resources. As shown in Figure 1, the Yellow River flows through nine provinces, namely, Qinghai, Sichuan, Ningxia, Shaanxi, Shanxi, Inner Mongolia, Henan, and Shandong, and there are thirty resource cities in the Yellow River Basin according to the “PLAN” issued by the State Council in 2013.

According to the different stages of resource development, resource-based cities are divided into four types: growth oriented, mature oriented, declining oriented, and regenerative oriented. As shown in

Table 3. Different types of resource-based cities in the Yellow River Basin.

Type	City
Growth	Wuwei, Qingyang, Longnan, Erdos, Xianyang, and Yulin
Mature	Jinchang, Pingliang, Datong, Changzhi, Jincheng, Xinzhou, Jinzhong, Yuncheng, Shuozhou, Sanmenxia, Hebi, Pingdingshan, Dongying, Jining, and Tai’an
Decline	Baiyin, Shizuishan, Wuhai, Tongchuan, Jiaozuo, and Puyang
Regeneration	Zhangye, Baotou, and Zibo

Source: According to the National Sustainable Development Plan of Resource-based Cities (2013–2020).

, there are six growth-oriented resource-based cities with rich resource reserves and long-term development potential that need to pay attention to the coordinated promotion of resource development and ecological safety. There are fifteen mature resource-based cities that face the needs of transformation and development, while the threat to ecological safety from resource development is greater. There are six declining resource-based cities facing the situation of resource depletion. There are three regenerative resource-based cities that have broken out of the mode of relying on resources for development. Taking these 30 resource-based cities as the research objects, the ecological safety assessment model of resource-based cities in the Yellow River Basin was constructed.

The Yellow River originates from the Qinghai–Tibet Plateau, with a total length of 5464 km and a vast drainage area of about 750,000 square kilometers, flowing through the areas of the Qinghai–Tibet Plateau, Loess Plateau, Hetao Plain, and North China Plain, with a great difference in topographic and geomorphic conditions and crossing three major topographic terrains from west to east [36,37,38], making it the largest river in the world in terms of sand content and sand transport.

As shown in Figure 2, the ecological types of cropland, grassland, forest, and wetland are unevenly distributed in the Yellow River Basin. The upper reaches of the Yellow River are the first stage of the Tibetan Plateau and are rich in water, wetland, and grassland ecosystems [39]. The middle reaches of the Yellow River are dominated by desert ecosystems, with landscapes such as the Hetao Plain, the Ordos Plateau, the Loess Plateau, the Fenwei Basin, the Qubuzi Desert, the Mao Wusu Sand, etc [40]. However, this area is often subject to complex meteorology, with frequent hydrological and sedimentary disasters. The lower reaches of the Yellow River, from the Taihang Mountains east to the coastal area are dominated by the North China Plain, with dense settlement ecosystems, concentrated industrial and mining enterprises, and vast areas of farmland. Growing resource cities are mainly distributed in the middle and upper reaches of the Yellow River Basin and are located along the Loess Plateau and the Fenwei Basin [41]; mature resource cities are mainly distributed in the middle and lower reaches of the Yellow River basin and are located in the declining resource cities, and regenerative resource cities are scattered, as shown in Figure 3.

According to the analysis of the principles of holism, non-linearity, and dynamics of complex science theory, the ecosystem and socio-economic development of resource cities in the Yellow River Basin have the following characteristics.

(1) The ecological types of resource-based cities in the Yellow River Basin are very different.

Complex science holds that the system is a whole, but there are imperfections and uncertainties in the whole. When the ecosystem is considered as a whole, there may be internal conflicts or disharmonies, but the carrying capacity of the ecosystem can resolve the external threats and pressures and bring the whole to a safe state. Conversely, if the carrying capacity of the ecosystem cannot withstand the threats and pressures, the whole ecosystem is in a dangerous state. The integrity of the ecosystem is embodied in multi-dimensional coordination, including natural, social, and economic coordination; coordination of different components of the ecosystem; and coordination in the time dimension.

The ecological security of resource-based cities in the Yellow River Basin is different from that of cities [42]. The Yellow River Basin is added to the ecosystem, so it is necessary to assess the impact of resource exploitation and related chemical industry development on the urban ecological carrying capacity of the city and the impact on the ecological carrying capacity of the Yellow River. Ecological protection and high-quality development in the Yellow River basin are important national strategies, and the efficiency of improving the quality of ecological barriers conflicts with resource development. In particular, the middle and upper reaches of the Yellow River are located in the Loess Plateau, with a fragile ecological environment, abundant oil and gas resources, and a unified industrial structure, and there are many contradictions between economic and social development and ecological safety in resource-based cities. Sustainable development of resource-based cities is an important part of China’s modernization, so it is necessary to analyze the ecological safety of resource-based cities in the Yellow River Basin from multiple dimensions.

(2) The process of resource exploitation that affects socio-ecological systems is not linear.

Under the framework of classical economic theory, resource scarcity is the root of promoting price increases and monopolizing economic development, forming the equilibrium theory of selfishness, while the theory of sustainable development pays more attention to social welfare and emphasizes the equilibrium of altruism. The ecological safety of resource-based cities in the Yellow River Basin needs to examine the environmental damage caused by resource exploitation and the impact of the Yellow River [43]. For example, coal mining in the middle and upper reaches of the Yellow River affects the geological structure of the loess plateau, and the development of cracks increase soil erosion, which is not conducive to the stability of plant roots. At the same time, the discharge of coarse sediments into the tributaries of the Yellow River increases, and the increase in heavy metals affects the ecological safety of the Yellow River. It can be seen that the mechanism affecting the ecological safety of resource-based cities in the Yellow River basin is complex. From a linear point of view [44,45,46], it is analyzed that nature provides infinite resources, and through the development of the manufacturing industry, it provides production efficiency and a production scale and transforms resources into various products to meet human needs. This simple causal linear production analysis poses great threats to ecological security. Based on a comprehensive understanding of the state of ecological safety, non-linear thinking puts forward problems from different levels, different angles, and different ways.

(3) Lack of clarity on the benefits of sustainable development policies for socio-ecological systems.

Complexity science holds that the time and space dimensions are superimposed to form a space–time structure that forms a self-organized synergy under the joint action of system function, system organization, and the relationship between the system and the environment. Self-organization can be understood as a functional coupling system that forms a steady state under the action of a feedback mechanism. Coupling includes an information transmission path, maintaining a steady state, and feedback regulation depending on the analysis of the coupling formation process, and the feedback relationship between different levels of ecological subsystems forms ecological behavior. The government ensures smooth feedback between different levels of ecological subsystems and adjusts the steady state by formulating the overall ecological planning of river basins using the overall planning, optimizing the industrial structure, and innovating and promoting green development to improve the self-organization synergy [47,48,49]. The sustainable development plan of resource-based cities issued in 2013 puts forward the principles of classified guidance and characteristic development for different types of resource-based cities and details the planning concepts of the orderly development of resources, the optimization of industrial structure, and people’s livelihood. The synergy between steady state and self-organization is in dynamic change, so the effectiveness of policies should be evaluated in time to ensure the dynamic stability of ecological safety.

4. Empirical Analysis and Results

4.1. Statistical Analysis of the Ecological Safety Level

According to the TOPSIS model [45],

Table 4. TOPSIS test results in 2006, 2013, and 2020.

Year	City	D+	D−	C	Year	City	D+	D−	C
2006	Baiyin	1.547	2.317	0.6	2006	Puyang	1.238	2.618	0.679
2013	Baiyin	1.006	2.631	0.723	2013	Puyang	1.228	2.621	0.681
2020	Baiyin	0.794	2.87	0.783	2020	puyang	0.946	2.756	0.744
2006	Baotou	1.276	2.412	0.654	2006	Qingyang	1.161	2.756	0.704
2013	Baotou	1.442	2.345	0.619	2013	Qingyang	1.096	2.887	0.725
2020	Baotou	1.211	2.631	0.685	2020	Qingyang	0.672	2.96	0.815
2006	Changzhi	1.104	2.424	0.687	2006	Sanmenxia	1.237	2.437	0.663
2013	Changzhi	1.123	2.401	0.681	2013	Sanmenxia	1.034	2.605	0.716
2020	Changzhi	0.935	2.634	0.738	2020	Sanmenxia	1.041	2.656	0.718
2006	Datong	1.363	2.334	0.631	2006	Shizuishan	1.506	2.157	0.589
2013	Datong	1.02	2.523	0.712	2013	Shizuishan	0.992	2.613	0.725
2020	Datong	0.898	2.777	0.756	2020	Shizuishan	1.132	2.623	0.699
2006	Dongying	1.13	2.447	0.684	2006	Shuozhou	1.634	2.227	0.577
2013	Dongying	1.316	2.484	0.654	2013	Shuozhou	0.807	2.68	0.769
2020	Dongying	1.165	2.588	0.69	2020	Shuozhou	0.79	2.863	0.784
2006	Eerduosi	1.494	2.436	0.62	2006	Taian	1.037	2.684	0.721
2013	Eerduosi	1.637	2.351	0.59	2013	Taian	1.153	2.609	0.694
2020	Eerduosi	1.323	2.657	0.668	2020	Taian	1.088	2.649	0.709
2006	Hebi	1.662	2.278	0.578	2006	Tongchuan	1.476	2.368	0.616
2013	Hebi	1.153	2.638	0.696	2013	Tongchuan	0.957	2.711	0.739
2020	Hebi	1.224	2.679	0.687	2020	Tongchuan	0.954	2.772	0.744
2006	Jiaozuo	1.489	2.194	0.596	2006	Wuhai	1.805	2.265	0.557
2013	Jiaozuo	1.457	2.331	0.615	2013	Wuhai	1.629	2.316	0.587
2020	Jiaozuo	1.149	2.564	0.691	2020	Wuhai	1.555	2.534	0.62
2006	Jinchang	1.357	2.387	0.638	2006	Wuwei	0.95	2.795	0.746
2013	Jinchang	1.367	2.295	0.627	2013	Wuwei	0.909	2.761	0.752
2020	Jinchang	1.317	2.628	0.666	2020	Wuwei	0.697	2.946	0.809
2006	Jincheng	1.201	2.36	0.663	2006	Xianyang	1.306	2.441	0.651
2013	Jincheng	1.018	2.554	0.715	2013	Xianyang	0.978	2.629	0.729
2020	Jincheng	0.944	2.687	0.74	2020	Xianyang	0.938	2.683	0.741
2006	Jining	1.178	2.515	0.681	2006	Xinzhou	1.704	2.445	0.589
2013	Jining	1.398	2.481	0.64	2013	Xinzhou	1.037	2.562	0.712
2020	Jining	1.239	2.616	0.679	2020	Xinzhou	0.845	2.787	0.767
2006	Jinzhong	1.176	2.43	0.674	2006	Yulin	1.441	2.438	0.628
2013	Jinzhong	1.416	2.367	0.626	2013	Yulin	1.122	2.557	0.695
2020	Jinzhong	0.83	2.828	0.773	2020	Yulin	1.005	2.676	0.727
2006	Longnan	1.734	2.553	0.596	2006	Yuncheng	1.765	2.137	0.548
2013	Longnan	1.391	2.567	0.649	2013	Yuncheng	1.111	2.568	0.698
2020	Longnan	1.001	2.812	0.737	2020	Yuncheng	1.072	2.599	0.708
2006	Pingdingshan	1.347	2.365	0.637	2006	Zhangye	1.191	2.701	0.694
2013	Pingdingshan	1.235	2.526	0.672	2013	Zhangye	0.969	2.717	0.737
2020	Pingdingshan	0.85	2.797	0.767	2020	Zhangye	0.757	2.875	0.791
2006	Pingliang	1.385	2.656	0.657	2006	Zibo	1.185	2.514	0.68
2013	Pingliang	1.353	2.562	0.654	2013	Zibo	1.313	2.507	0.656
2020	Pingliang	0.685	2.892	0.809	2020	Zibo	1.258	2.515	0.667

shows the results in 2006, 2013, and 2020, including D+ D− and the ecological safety level (C).

Figure 4 shows the ecological safety level of each resource-based city in the Yellow River Basin from 2006 to 2020. Generally speaking, the ecological safety level of resource-based cities in the Yellow River Basin is on a steady upward trend, and the ecological safety level is between 0.5 and 0.8. During the study period, the ecological safety level of some resource cities did not change significantly. The ecological safety level of Wuhai, a declining city, was low, ranging from 0.5 to 0.6, while that of Baotou and Zibo, regenerating cities, was turbulent, ranging from 0.6 to 0.7, with no significant improvement. After the implementation of the plan in 2013, the ecological safety level of most cities shows a clear upward trend.

Figure 5 shows the average changes in the ecological safety level changes of resource-based cities in the Yellow River Basin over different years. Overall, the ecological level of resource-based cities in the Yellow River Basin is improving. It can be summarized into three phases. From 2006 to 2009, it was in a period of rapid improvement, from 2010 to 2013, it was in a period of horizontal adjustment, from 2014 to 2016, it was in a period of rapid recovery, and from 2017 to 2020, it was in a period of slow growth.

Before further discussing the influencing factors of ecological safety of resource-based cities in the Yellow River Basin, the ecological safety level, the proportion of control variables, the proportion of the tertiary industry, the proportion of green inventions, and the proportion of environmental protection word frequency are statistically analyzed, as shown in

Table 5. Statistical table of ecological safety level and control variables.

Variable	Observations	Mean	Max	Min
Ecological safety	450	0.698	0.819	0.548
Ecological safety difference	420	0.0059	0.122	−0.097
Proportion of the tertiary sector of the economy	450	36.19%	81.75%	11.38%
Proportion of green inventions in total inventions	450	0.107	0.375	0
Proportion of environmental protection words in government work reports	450	0.0036	0.0092	0

. The minimum value of the ecological safety level is 0.548, the maximum value is 0.819, and the proportion of the tertiary industry is 81.75% and 36.19%. The share of green inventions is generally low, with a maximum of 0.375. Some resource-based cities pay less attention to green inventions and environmental protection.

4.2. Verifying and Analyzing the Convergence of the Ecological Safety Level

Figure 6 shows the convergence trend of ecological safety σ of resource-based cities in the Yellow River Basin. Overall, the difference is obvious, and the ecological safety level of resource-based cities in the Yellow River Basin changes significantly. However, different types of resource-based cities have different characteristics. The resource development of growth-based resource-based cities is in the initial rising stage, and the σ coefficient is obviously higher than that of other cities. By standardizing the order of resource development and limiting the intensity of resource development, the level of ecological safety can be effectively improved; the resource development of mature resource-based cities is in the stable development stage, the downstream industrial chain of resource development continues to expand, and the industrial structure is optimized and upgraded. As shown by the blue line in the figure, it is in a period of rapid change from 2006 to 2012, first increasing and then decreasing, and after 2013, it is in a period of steady increase; the ecological safety level of declining resource-based cities started low, but the growth rate was higher than that of other cities; the ecological safety level of renewable resource-based cities fluctuates widely, and the ecological safety level is at a low point from 2008 to 2016. The growth range of the σ coefficient of resource-based cities in the Yellow River Basin is about 0.1, indicating that the overall ecological safety is in an upward convergence trend, but the growth rate is limited. The ecological safety level of different resource-based cities was quite different in 2006, and the difference was obviously reduced in 2020. On the whole, growth-based resource-based cities pay more attention to the protection of ecological safety, while the ecological safety level of renewable resource-based cities is not significantly developed.

Table 6. β conditional convergence test results.

Variable	All Cities	Growth	Mature	Decline	Regeneration
lnCi, t	−0.9037 ***	−0.7049 **	−0.0584 ***	−0.4852	−0.5607
	(−20.94)	(−3.63)	(−9.68)	(−1.85)	(−3.75)
Proportion of the tertiary sector of the economy	0.0005	0.0494 *	0.0374 **	0.0693	0.0155
	(2.29)	(2.11)	(2.83)	(1.36)	(1.42)
Proportion of environmental protection words in government work reports	1.7261	−0.027 **	0.0088 *	0.0040	0.0071
	(2.21)	(−3.10)	(1.87)	(0.78)	(2.8)
Proportion of green inventions in total inventions	0.0587	−0.0057	0.0099	−0.0148	−0.0091
	(1.77)	(−0.52)	(1.51)	(−1.31)	(−0.63)
Convergence rate	0.156	0.081	0.004	-	-
Half life cycle	4.44	8.55	173
R2	0.8212	0.6663	0.1834	0.4360	0.7479

* Correlation is significant at the 0.1 level, ** Correlation is significant at the 0.05 level. *** Correlation is significant at the 0.01 level.

shows the convergence test results of the ecological safety β conditions of the resource-based cities in the Yellow River Basin. The overall lnC coefficient of the Yellow River Basin is negative, indicating that the ecological safety level of resource-based cities in the Yellow River Basin has a convergence trend, with a convergence rate of 0.156, a half-life cycle of 4.44, and a fitting degree of 0.8212. Growth resource-based cities with low ecological safety levels need 8 years to catch up with cities with high ecological safety levels. The growth resource-based cities of Wuwei, Qingyang, Longnan, Erdos, Xianyang, and Yulin are all located on the Loess Plateau in the middle and upper reaches of the Yellow River. Under arid and semi-arid natural conditions, the loess texture is loose, the rainfall is concentrated and intense, and the problems of soil erosion, soil aggradation, and siltation of rivers, lakes, and reservoirs are serious. As a result of resource exploitation, industrial water has greatly increased, exceeding the carrying capacity of local water resources, leading to drought and water shortage. From the perspective of control variables, the proportion of the tertiary industry and the word frequency indicators environmental protection have passed the significance test of 10% and 5%, respectively, which has a significant impact on growth-oriented and mature resource-based cities. The proportion of the tertiary industry increased by 1%, the ecological safety level of growth resource-based cities increased by 4.9%, and that of mature resource-based cities increased by 3.74%. The emphasis on environmental protection increased by 1%, the ecological safety level of growing resource-based cities decreased by 2.7%, and the ecological safety level of mature resource-based cities increased by 0.88%.

4.3. Analysis of Factors Influencing the Difference in Ecological Safety Level under Sustainable Development Policy

In 2001, the State Council set up a pilot project for the transformation and development of resource-depleted cities in Fuxin, Liaoning Province. In 2008, 69 pilot projects for the transformation and development of resource-poor cities were reviewed nationwide. In 2013, the National Plan for the Sustainable Development of Resource-exhausted Cities was issued, and 262 resource-exhausted cities were identified. There are four goals: the first is to guide the scientific development of resource-based cities with different classifications; the second is to develop resources in an orderly way; the third is to adjust the industrial structure; and the fourth is to improve people’s livelihood and strengthen environmental management and ecological protection. It is the first national plan for the development of a resource-based city. In this paper, the DID model is used to make a comparative study of the ecological safety level of resource-based cities in the Yellow River Basin before and after planning, and the results are shown in Table 6.

Given the characteristics of resource-based cities in China, the 2013 Plan focuses on improving the classification and guiding the scientific development of various cities, targeting the optimization of the industrial structure, rational development and utilization of resources, and promoting the social development of resource-based cities. The response of various cities to the plan is highlighted in the optimization of industrial structure. Through the empirical results of the DID model,

Table 7. DID test results.

Variable	Growth	Mature	Decline	Regeneration
Proportion of the tertiary sector of the economy	0.0009 ***	0.0008 **	0.0014 ***	0.0005 *
	(5.04)	(3.02)	(4.36)	(2.89)
Proportion of environmental protection words in government work reports	−4.4582 *	2.4797	5.6874	4.9022
	(−2.28)	(1.21)	(1.46)	(1.41)
Proportion of green inventions in total inventions	−0.0691	0.0759	−0.3409 **	−0.1279
	(−0.75)	(1.32)	(−2.73)	(−0.94)
Constant	0.7143 ***	0.6652 ***	0.6512 ***	0.6806 ***
	(44.71)	(90.95)	(31.69)	(35.36)
Observations	90	210	90	45
R2	0.7546	0.3185	0.7034	0.8648

* Correlation is significant at the 0.1 level, ** Correlation is significant at the 0.05 level. *** Correlation is significant at the 0.01 level.

shows that increasing the proportion of the tertiary industry has a significant effect on improving the ecological safety of all resource-based cities after the introduction of the planning. Compared with the analysis of the above β influencing factors above, the proportion of the tertiary industry has no significant impact on the ecological safety of declining and renewable resource-based cities from 2006 to 2020, but it has a significant impact on the ecological safety of declining and renewable resource-based cities from 2013 to 2020.

5. Conclusions and Recommendations

In conclusion, this paper measures the ecological safety level of resource-based cities in the Yellow River Basin by the TOPSIS model. It distinguishes the types of ecological safety by σ convergence and β convergence analysis. It compares the ecological safety differences before and after the “PLAN” by three response characteristics. The main conclusions are as follows.

(1) The ecological safety level of resource-based cities in the Yellow River Basin is generally good, with an increasing trend. The ecological safety level and development trend of various resource-based cities in the Yellow River Basin are significantly different, according to the σ convergence test. The reason is that the resources of declining resource-based cities are developed earlier and the awareness of ecological safety is low, so the overall ecological safety level is low. With the extension of the industrial chain, the degree of coupling of ecological pressure, ecological threat, and ecological carrying capacity is high in mature resource-based cities, and the ability of ecological safety prevention and control is relatively high. However, the growth-oriented resource-based cities have certain ecological safety plans in the early stage of resource development, so the ecological safety level is relatively high.

(2) The sustainable development policy for resource-based cities is beneficial to reduce the gap in the ecological safety level among resource-based cities in the Yellow River Basin, but it has a limited impact on the overall ecological safety level. The optimization of the sustainable development policy can promote the high-quality construction of resource-based cities, but the policy content should be further refined, and a variety of mechanism linkage modes, such as industrial structure optimization and green innovation development, should be constructed.

Through the above research, this paper finds that there are some measures to improve the ecological security level of resource-based cities. 1. Improve the leading mechanism of financial funds for ecological security in the Yellow River Basin. Resource-oriented cities with high GDP levels can play a leading role with regard to financial funds, maintain the strength of financial investment, form institutional arrangements that match the development of ecological security, form the structure of ecological security inputs and the mode of ecological security inputs, release stable and strong signals of investment in sustainable development, and fully mobilize the enthusiasm of the whole society to participate in ecological security. 2. Improve the dynamic monitoring mechanism of ecological safety in the Yellow River basin. Based on the monitoring base of hydrological stations in the tributaries of the Yellow River, the dynamic monitoring mechanism of ecological safety in resource-based cities is established, and the ecological emergency response will be improved. 3. Improve talent introduction policies in resource cities and provide human resource support to enhance the vitality of enterprises in scientific and technological research and development. Through investigation and research in resource-based cities in the Yellow River Basin, such as Ordos, Yulin and Yan’an, the authors found that there are few high-tech enterprises, especially few large-scale high-tech enterprises.

Shortcomings: This paper selects a large number of resource cities, so when determining the evaluation indexes, we need to pay attention to the availability of data. The index system is mainly based on the technical documents of ecological evaluation, and it does not highlight the individual differences between resource cities. We intend to analyze the ecological safety of each resource city in detail in future research and combine remote data, statistical data, and monitoring data to make targeted policy recommendations.