Study on the Evolution of the Spatial-Temporal Pattern and the Influencing Mechanism of the Green Development Level of the Shandong Peninsula Urban Agglomeration

Abstract

Improving the level of green development is an inevitable requirement for promoting the construction of an ecological civilization. In this paper, through a green development level evaluation index system, the CRITIC weight method is used to comprehensively evaluate and analyze the green development level of the Shandong Peninsula Urban Agglomeration from 2007 to 2019. On this basis, a panel data model was constructed to analyze the key influencing factors of the green development level of the Shandong Peninsula Urban Agglomeration. Studies have shown that (1) the level of green development in the Shandong Peninsula Urban Agglomeration from 2007 to 2019 has been steadily improved, but the overall level is still at a low level, with significant differences among the cities. (2) Qingdao and Jinan are the two growth poles of the green development level of Shandong Peninsula Urban Agglomeration. The dual-core leading effect is obvious, forming a spatial pattern in which the green development level of the eastern and central regions is higher than that of other regions’ green development level. (3) Weihai, Dongying, and Qingdao are high-level cities of green development, while Jinan, Yantai, Zibo, Tai’an, and Linyi are medium-level cities of green development. The green development level of other cities is relatively low, and the high-level cities of green development are mostly the Jiaodong economic circle and provincial capital economic circle. (4) Industrial structure, scientific and technological innovation, and government policies are the critical factors in promoting the green development of the Shandong Peninsula Urban Agglomeration.

1. Introduction

In recent years, global issues such as resources, the environment, and climate change have become increasingly exacerbated. Green development has gradually become a new development consensus. Many countries regard green development as essential to promoting economic and social transformation. The concept of green development is further deepened and evolved from the idea of sustainable development, circular development and low-carbon development. Currently, the international community mainly expresses the connotation of green development in terms of the “green economy” and “green growth”. The United Nations Environment Programme (UNEP) points out that a green economy is an economy that can improve human well-being and social equity while significantly reducing environmental risks and ecological scarcity [1]. The Organization for Economic Cooperation and Development (OECD) believes that green growth, as a means of sustainable development, can pressure nature can provide a steady stream of resources and environmental services for the development of human society [2]. The Asia-Pacific Economic Cooperation (APEC) sees green development as a solution to prevent environmental degradation, biodiversity loss, ecological, economic development, and natural resources while pursuing economic growth [3]. The World Bank emphasizes that green growth can recycle natural resources and reduce pollution emissions. An environmentally friendly economic growth method is an inevitable requirement for achieving sustainable development [4]. Since the proposal of the 18th National Congress of the Communist Party of China, China’s green development concept has gradually improved. It has become one of the five significant concepts guiding China’s future development [5]. Wang et al. [6] believed that green development is a development model in which the environment and resources are sustainable, humans and nature coexist in harmony, and the environment is used as intrinsic productivity. In green development, the environment is not only a development of productivity but also a manifestation of international competitiveness. Green development has fundamentally changed the antagonistic relationship between environmental protection and economic development in the traditional development model, pursuing the mutual integration and synergy between ecological conservation and economic and social development. In 2016, the National Development and Reform Commission, the National Bureau of Statistics, and other departments formulated the green development index system and the objective assessment system of ecological civilization construction as the basis for the assessment of ecological civilization construction [7]. Green development has become an essential driving force for China to promote the construction of ecological civilization and achieve the double carbon goal [8].

Presently, research on green development mainly focuses on evaluating green development levels and analyzing the spatiotemporal pattern of green development levels. The evaluation of the green development level mainly focuses on four aspects: green development indicators, green development regional scale, green development evaluation methods, and green development influencing factors.

(1) Green development indicators: Zhang et al. [9] selected 12 indicators from four aspects of ecological space optimization, ecological, economic development, good ecological environment, and ecological life satisfaction and constructed a set of regional green development evaluation indicators system applicable to 11 counties (districts, cities) in Yunnan. The evaluation index system of urban green development in Shandong Province was constructed by Yuan et al. [10] from the two aspects of the urban support system and urban coordination system, and a metropolitan green development evaluation method based on the entropy weight TOPSIS method was proposed.

(2) Regional-scale of green development: Existing studies mainly focus on the national, provincial, and county scales, such as Guo et al. [11] analyzed the regional differences in green development in Ningxia counties; Chang et al. [12] introduced the green development index system and the calculation method of the green development index in Henan Province, which provided a theoretical basis for evaluating green development in Henan Province; Ye et al. [13] conducted a dynamic evaluation of Beijing’s green development effectiveness, measured the development level of China’s green economy, and studied the factors affecting the development level of the green economy, Xu et al. [14] measured the level of green economy development in China and study the factors that affect the level of green economy development.

(3) Green development evaluation methods: Existing studies mainly focus on the analytic hierarchy process, factor analysis, TOPSIS method, and entropy method. Chen et al. [8] used the weighted sum method and the data envelopment analysis method to measure the Beijing-Tianjin-Hebei region’s green development level and efficiency in a decade; Zhang et al. [15] used the factor analysis method to analyze the green development status of 30 provinces in China and conducted an empirical analysis. In terms of the analysis of the spatiotemporal pattern of the green development level, Yan et al. [16] found, through the spatial and temporal analysis of the high-quality green development level of rural villages in the Yellow River Basin, that the high-quality green development level of rural villages in the lower reaches of the Yellow River has improved the fastest, and there are significant temporal and spatial differences in the level of rural high-quality green development in the basin; Chen et al. [17] analyzed and summarized that the overall level of green development in the Yangtze River Economic Belt was stable and improving based on the data of the 11 provinces and cities in the Yangtze River Economic Belt from 2007 to 2017, but there were still differences in the temporal and spatial patterns of temporal and spatial patterns. Zhang et al. [18] and Huang et al. [19] found that the overall green development level of urban agglomerations in China has been continuously improved, with a pattern of high in the east and low in the west.

(4) In terms of influencing factors of green development. Based on the green development indicator system of Anhui Province, Huang et al. [20] determined the weights of green development indicators at all levels through the analytic hierarchy process, and then used cluster analysis and principal component analysis to summarize the main factors that affect the temporal and spatial differences in the green development of counties and districts in Huangshan City. Xu et al. [14] found that the factors affecting the level of green economy development in China had different scopes in different years, and the same local factors in the same year had different significances in other provinces. Liu et al. [21] found that the level of economic development, industrial structure, urbanization rate, and foreign trade development have different degrees of impact on the green development efficiency of Guizhou Province. Cui et al. [22] constructed a green development indicator system in the Yangtze River Economic Belt from green growth, green carrying capacity, and green security capacity and analyzed the factors affecting the differences in the green development levels of cities along the Yangtze River Economic Belt.

Summing up the previous studies, it is found that there is a lack of innovation in green development evaluation methods. Currently, the research scale for green development is more focused on the provincial, municipal, and county levels, and the green development evaluation based on urban agglomeration is less. With the improvement of China’s urbanization level, urban agglomerations continue to play an essential role in China’s economic development. On 21 January 2017, the Shandong Provincial Government approved the implementation of the “Shandong Peninsula Urban Agglomeration Development Plan (2016–2030)”, which included Jinan, Qingdao, Zibo, Zaozhuang, Dongying, Yantai, Weifang, Jining, Taian, Weihai, and Rizhao. The 17 cities Binzhou, Dezhou, Liaocheng, Linyi, Heze, and Laiwu (of which Laiwu was officially revoked and placed under Jinan in 2019) are included in the planning plan [23]. As one of the critical urban agglomerations in China, rapid economic development is accompanied by high energy consumption, high pollution, and low levels. The contradiction between economic construction, resource utilization, and environmental protection is prominent, which is not conducive to future viability—continuous development. Shandong Peninsula Urban Agglomeration is the first comprehensive experimental area for the transformation of old and new kinetic energy in China. At the intersection of several major regional development strategies of the country, we should not only base ourselves on promoting the integrated development of the three economic circles of the provincial capital, Jiaodong and southern Shandong, but also actively integrate into the coordinated development of Beijing, Tianjin and Hebei, connect with the national strategies such as the integration of the Yangtze River economic belt and the Yangtze River Delta, and especially play a leading role in promoting the ecological protection and high-quality development of the Yellow River Basin [24,25]. To promote the green transformation of the Shandong Peninsula Urban Agglomeration, this paper uses the Shandong Peninsula Urban Agglomeration as the research object to study the spatiotemporal pattern of the green development of the Shandong Peninsula Urban Agglomeration through the CRITIC method and the cluster analysis method, analyzes its evolution characteristics and proposes optimization suggestions. Promote the implementation of the conversion between new and old drivers, promote the comprehensive green transformation and high-quality development of the economic and social development of the Shandong Peninsula Urban Agglomeration, and provide theoretical support for the green development of other urban agglomerations.

2. Materials and Methods

2.1. Establishment of an Indicator System

Based on an extensive reading of the relevant literature, we draw on the “Green Development Indicator System” issued by the National Development and Reform Commission and other authoritative departments [7]. The actual situation of the Shandong Peninsula Urban Agglomeration, socioeconomic development, resource consumption and utilization, green growth efficiency, and government policy support was used as the first-level indicators. The evaluation index system for the green development level of the Shandong Peninsula Urban Agglomeration was constructed using 16 indicators, including the proportion of GDP (

Table 1. Evaluation index system of the green development level of Shandong Peninsula Urban Agglomeration.

Indicator System	Indicator Name	Indicator Unit	Indicator Direction	Index Weight
Socioeconomic development (0.35973)	GDP per capita (X1)	ten thousand yuan	+	0.05778
	Gross industrial output value above designated size (X2)	one hundred million yuan	+	0.07678
	Industrial added value as a share of GDP (X3)	%	+	0.09278
	The added value of the tertiary industry accounts for the proportion of GDP (X4)	%	+	0.06725
	R & D expenditure as a percentage of GDP (X5)	%	+	0.06514
Resource consumption (0.18949)	Energy consumption per unit of GDP (X6)	t Standard coal/ten thousand yuan	−	0.05144
	Water consumption per unit of industrial added value (X7)	m3/ten thousand yuan	−	0.04513
	The comprehensive utilization rate of industrial solid waste (X8)	%	+	0.09292
Green Growth efficiency (0.19248)	Sulfur dioxide emissions per unit of GDP (X9)	t/ten thousand yuan	−	0.05341
	Unit GDP smoke and dust emissions (X10)	t/ten thousand yuan	−	0.05341
	Wastewater discharge per unit of GDP (X11)	t/ten thousand yuan	−	0.03952
	Chemical oxygen demand emissions per unit of GDP (X12)	t/ten thousand yuan	−	0.06797
Government policy support (0.25829)	Government spending on energy conservation and environmental protection as a percentage of GDP (X13)	%	+	0.03158
	Municipal waste harmless treatment rate (X14)	%	+	0.05082
	Greening rate of urban built-up area (X15)	%	+	0.05516
	Sewage treatment rate (X16)	%	+	0.06545

). Among them, social and economic development selects per capita GDP, total industrial output value above designated size. The proportion of industrial added value in GDP reflects the city’s overall financial situation and economic scale, and the balance of tertiary industry added a steal to GDP reflects the situation of urban industrial structure and economic structure. The proportion of R & D expenditure in GDP can reflect the intensity of innovation in the city; the energy consumption per unit of GDP, the water consumption per unit of industrial added value, and the total utilization rate of industrial solid waste are selected to reflect the level of resource utilization in the city; the unit of green growth efficiency is selected as the unit. The emissions of sulfur dioxide, soot, wastewater, and chemical oxygen demand in GDP are used to reflect the level of urban environmental pollution emissions; government policies support the selection of the proportion of government energy conservation and environmental protection expenditure in GDP, the harmless treatment rate of urban waste, and the greening of urban built-up areas. The wastewater treatment rate can reflect the government’s efforts in environmental protection and the overall environmental governance level of the city. Environmental emissions and environmental governance are the manifestations of current urban environmental pollution prevention and control and environmental management effectiveness.

2.2. Data Sources

Considering the reliability and availability of the index data, this paper takes the 16 cities in the Shandong Peninsula Urban Agglomeration from 2007 to 2019 (Jinan, including Laiwu from 2019) as the research object. In the Provincial Statistical Yearbook, China Energy Statistical Yearbook, China City Yearbook, and the statistical yearbooks and related bulletins of 16 prefectures and cities, the missing values of very few indicators were supplemented by interpolation. To eliminate the impact of price fluctuations, the data of relevant economic indicators are calculated based on the constant prices in 2005.

2.3. Research Methods

Currently, the commonly used subjective weighting methods include the expert estimation method, analytic hierarchy process, binomial coefficient method, etc., and objective weighting methods include the principal component analysis method, factor analysis method, TOPSIS entropy method, standard deviation method, and CRITIC method. Wang et al. [26] concluded that the CRITIC method could reflect the objective weight of indicators more comprehensively and objectively after thoroughly comparing various objective weighting methods. The CRITIC (criteria importance though intersection correlation) method was proposed by Diakoulaki [27], which can take into account the contrast strength and conflict between the indicators and thus comprehensively determine the objective weight of the indicators. The calculation steps are as follows:

2.3.1. Dimensionless Data

$$\mathrm{Positive} \mathrm{indicators}:x{\prime }_{ij}=\frac{x_j-x_{\min }}{x_{\max }-x_{\min }}$$

(1)

$$\mathrm{Negative} \mathrm{indicators}:x{\prime }_{ij}=\frac{x_{\max }-x_j}{x_{\max }-x_{\min }}$$

(2)

where$x{\prime }_{ij}$ is the first $i$ Region$j$ value of evaluation indicators$i$ = 1, 2, …, $17$; $j$ = 1, 2, …, $16$).

2.3.2. Obtaining Indicator Variability

In the CRITIC weighting method, the standard deviation is used to represent the difference and fluctuation of the internal value of each indicator. The larger the standard deviation is, the more significant the numerical difference of the indicator, the more information it reflects, and the stronger the evaluation intensity of the indicator itself should be assigned. This indicator weights and the formula is:

$$\left\{\begin{array}{c}{\overline{x}}_j=\frac{1}{n}{\displaystyle \sum _{i=1}^n}x{\prime }_{ij},\\ S_j=\sqrt{\frac{{{\displaystyle \sum }}_{i=1}^n{\left(x{\prime }_{ij}-{\overline{x}}_j\right)}^2}{n-1}},\end{array}\right.$$

(3)

where ${\overline{x}}_j$ refers to the average number of samples of $n$ regions to be evaluated for the $j$ th index, $S_j$ represents the standard deviation of the $j$ th index.

2.3.3. Obtaining Indicator Conflict

The correlation coefficient expresses the index conflict. The stronger the correlation is, the smaller the conflict is. The more the same information is reflected, the more repetitive the evaluation content can be reflected. To a certain extent, the evaluation intensity of the index is weakened, and the weight of the index distribution should be reduced. The index conflicts can be obtained by summing the correlation coefficients of each evaluation index.$R_j$ The formula is:

$$R_j={\displaystyle \sum }_{i=1}^p\left(1-r_{ij}\right)$$

(4)

where$r_{ij}$ indicates the evaluation index$i$, $j$ is the correlation coefficient used to represent the correlation between indicators, and$p$ is the number of evaluation indicators.

2.3.4. Calculate the Amount of Indicator Information

Let $C_j$ Represents the first$j$ The amount of information contained in each evaluation index, and the formula is:

$$C_j=S_j{\displaystyle \sum }_{i=1}^p(1-r_{ij})=S_j\times R_j$$

(5)

where$C_j$, the greater the $j$ is, the greater the role of each evaluation index in the entire evaluation index system, the more weight should be assigned to it.

2.3.5. Determining the Objective Weight of the Indicator

For the first $j$, the objective weight of each evaluation indicator $W_j$, the formula is:

The formula of the objective weight $W_j$ of the $j$ th evaluation index is:

$$W_j=\frac{C_j}{{{\displaystyle \sum }}_{j=1}^p{C}_j},$$

(6)

2.3.6. Calculate the Green Development Level Index

First $j$ Item index $V_{ij}$, the formula is:

$$V_{ij}={\displaystyle \sum }_{i=1}^{n}x{\prime }_{ij}{W}_j$$

(7)

The green development level index can be obtained by summing the evaluation indices of each index. $V_i$ The formula is:

$$V_i={\displaystyle \sum }_{j=1}^p{V}_{ij}$$

(8)

3. Results

3.1. Analysis of the Evolution of the Time Pattern of the Green Development Level of the Shandong Peninsula Urban Agglomeration

Based on the above calculation of the green development index of the Shandong Peninsula Urban Agglomeration from 2007 to 2019 (

Table 2. Green development level index of Shandong Peninsula Urban Agglomeration from 2007 to 2019.

City	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	Mean	Coefficient of Variation
Urban agglomeration	0.4343	0.4662	0.5077	0.5229	0.5407	0.5699	0.5979	0.6077	0.6088	0.6115	0.6053	0.6067	0.6169	0.5613	0.1095
Weihai	0.6233	0.5807	0.6092	0.6714	0.6502	0.6903	0.7012	0.7138	0.7187	0.7225	0.6873	0.6717	0.7091	0.6730	0.0670
Qingdao	0.5732	0.6117	0.6329	0.6447	0.6698	0.6714	0.7008	0.6904	0.6877	0.6795	0.6731	0.6959	0.6900	0.6631	0.0568
Dongying	0.5450	0.5563	0.5767	0.6156	0.6373	0.6650	0.7058	0.7234	0.7244	0.7203	0.7093	0.7068	0.6947	0.6600	0.1008
Yantai	0.5567	0.5745	0.5941	0.6213	0.6252	0.6484	0.6573	0.6529	0.6562	0.6673	0.6440	0.6451	0.6752	0.6322	0.0546
Tai’an	0.5065	0.5251	0.5314	0.5792	0.5875	0.6157	0.6259	0.6329	0.6490	0.6620	0.6585	0.6771	0.6742	0.6096	0.0965
Jinan	0.5029	0.5300	0.5398	0.5825	0.5846	0.5956	0.6033	0.6240	0.6424	0.6468	0.6475	0.6823	0.6771	0.6045	0.0929
Zibo	0.4664	0.4972	0.5467	0.5747	0.5948	0.6190	0.6314	0.6351	0.6516	0.6673	0.6748	0.6646	0.6265	0.6039	0.1090
Linyi City	0.5042	0.5248	0.5851	0.5538	0.5776	0.5789	0.5848	0.6001	0.6237	0.6325	0.6260	0.6506	0.6318	0.5903	0.0742
Weifang	0.4900	0.5088	0.5463	0.5289	0.5349	0.5551	0.6246	0.6217	0.6330	0.6488	0.6339	0.6133	0.5903	0.5792	0.0932
Jining	0.4909	0.5041	0.5512	0.5636	0.4902	0.5300	0.5559	0.5683	0.5988	0.6252	0.6475	0.6548	0.6390	0.5707	0.1024
Liaocheng	0.4029	0.4463	0.4923	0.5018	0.5032	0.5879	0.6273	0.6322	0.6554	0.6455	0.6052	0.6189	0.5799	0.5614	0.1469
Dezhou	0.3451	0.4002	0.4221	0.4801	0.5365	0.5644	0.5979	0.6005	0.6242	0.6156	0.6296	0.6586	0.6500	0.5481	0.1890
Rizhao	0.4455	0.4380	0.4545	0.5064	0.5238	0.5476	0.5648	0.5677	0.5905	0.5850	0.5802	0.6392	0.6576	0.5462	0.1282
Zaozhuang	0.3432	0.4160	0.4609	0.4772	0.4890	0.5424	0.5777	0.5992	0.6068	0.6281	0.6389	0.6409	0.6151	0.5412	0.1766
Binzhou	0.3544	0.4489	0.4707	0.5362	0.5661	0.5705	0.5824	0.5850	0.5746	0.4667	0.5929	0.6053	0.6307	0.5373	0.1469
Heze	0.3833	0.4190	0.4572	0.4640	0.4851	0.5172	0.5441	0.5511	0.5640	0.5503	0.5898	0.5996	0.5782	0.5156	0.1324

), it can be seen that in terms of time series evolution, the average green development level index of the Shandong Peninsula Urban Agglomeration from 2007 to 2019 is 0.5613, the minimum is 0.4343, and the maximum is 0.6169. The overall trend is increasing year by year. From 2007 to 2019, the average value of the green development level index of various cities from high to low is Weihai, Qingdao, Dongying, Yantai, Tai’an, Jinan, Zibo, Linyi, Weifang, Jining, Liaocheng, Dezhou, Rizhao, Zaozhuang, Binzhou, Heze, and there are differences among various cities. With the passage of time, the green development level of cities in Shandong Peninsula Urban Agglomeration showed different degrees of improvement from 2007 to 2019. During this period, there was a decline in some cities. The average green development level index of Shandong Peninsula Urban Agglomeration increased from 0.4343 in 2007 to 0.6169 in 2019. In 2007, there were 11 cities whose green development level index was higher than that of Shandong Peninsula Urban Agglomeration as a whole, among which Weihai, Qingdao and Yantai ranked in the top three. Weihai’s green development level index was the highest, 0.6233, and Zaozhuang is the lowest, 0.3432. By 2019, except Zaozhuang, Weifang, Liaocheng and Heze, the other 12 cities are higher than the overall green development level index of Shandong Peninsula Urban Agglomeration, of which Weihai green development level index is the highest, 0.7091, and Heze is the lowest, 0.5782. From 2007 to 2019, the number of cities higher than the overall green development level index of Shandong Peninsula Urban Agglomeration showed an upward trend, the relative difference of green development level among cities gradually narrowed, and the green development level of Shandong Peninsula Urban Agglomeration showed a balanced development trend.

3.2. Analysis of the Evolution of the Spatial Pattern of Green Development in the Shandong Peninsula Urban Agglomeration

The green development level of each prefecture-level city in the Shandong Peninsula Urban Agglomeration was at different stages and degrees in different years. The four-time nodes of 2007, 2011, 2015, and 2019 were selected, and the green development level of the Shandong Peninsula Urban Agglomeration was classified using the natural discontinuity classification method with the help of ArcGIS software. It is divided into three groups low-level, medium-level, and high-level. The color depth indicates the level of green development to more intuitively reflect the spatial pattern evolution characteristics of the green development level of cities in Shandong Peninsula Urban Agglomeration and the regional differences in the development process. The results are shown in Figure 1.

From 2007 to 2011, the level of green development in the northwest and south of Shandong Province was the lowest, the area in the middle of Shandong Province was at a relatively high level, and the high-level areas were mainly distributed in the coastal areas of the Jiaodong Peninsula and the northern coastal areas. The green development level of the northwestern Shandong region has improved, and the southern and central Shandong regions have maintained their original levels compared with other regions. In 2015–2019, the Qingdao metropolitan area and the eastern coastal area with Qingdao as the core area were maintained. The green development level of the provincial capital metropolitan area with Jinan as the core in the western region is significantly higher than that of other areas, forming a high-level area in the west with Jinan as the core and a high-level area in the eastern coastal area with Qingdao as the core. Qingdao, Yantai, and Weihai in the east are located in the Blue Economic Zone of the Shandong Peninsula. Relying on their excellent natural conditions, geographical advantages, and policy support, sea and land transportation is convenient. It is adjacent to Japan and South Korea, which is suitable for introducing capital and advanced talents and technologies and facilitates foreign trade. The high-end manufacturing industry started early, the overall economy is relatively developed, and it has the foundation for green development. As the economic center of Shandong Province, Qingdao is the bridgehead for the entire Shandong Peninsula Urban Agglomeration to achieve comprehensive green transformation and high-quality development. As the capital city of Shandong Province and the central city in the west, Jinan has relatively fast economic growth and apparent advantages in policy support, foreign investment, and attracting talent. Its economic development is rapid, its comprehensive strength is relatively muscular, and its radiation effect is strong. Zibo is an old industrial base and resource-based city in China. Its total GDP is above the medium level in Shandong Province. The heavy industry and deep-processing industries have created tremendous economic benefits for Zibo. Dongying relies on the two national strategies of the Yellow River Delta High-efficiency Ecological Economic Zone and the Shandong Peninsula Blue Economic Zone to drive its economic development through profitable industries such as petrochemicals, nonferrous metals, and new materials. In recent years, the level of green growth in southwestern Shandong has improved under the guidance of the western economic uplift strategy. However, due to the constraints of geographical conditions and development positioning, green development is still relatively low compared to other cities.

Overall, the distribution of green development levels in the Shandong Peninsula Urban Agglomeration from 2007 to 2019 showed significant regional differences. The green development levels of Qingdao, Yantai, and Weihai in the east were relatively good, followed by Weifang and Rizhao, followed by Jinan, Dongying and Zibo, and Tai’an in the central region. The level of green development is relatively good, with a high-low-high-low distribution from east to west, forming a dual-core green development spatial pattern with Qingdao and Jinan as the core. The spatial distribution of the low-level area changed significantly; the low-level and the medium-level regions had a significant mutual transformation trend, and the high-level area was mainly concentrated in the eastern, northern coastal, and central regions. From 2007 to 2019, the number of the three types of development levels changed to varying degrees. The number of the high-level areas increased from four in 2007 to six in 2019, while the number of medium-level areas remained unchanged, while the number of the low-level regions remained unchanged. From 5 in 2007 to 3 in 2019, the evolution of the green development levels of different levels in each city indicates that the green development of the Shandong Peninsula Urban Agglomeration is still at a relatively low level.

3.3. Classification of Urban Types of Green Development in the Shandong Peninsula Urban Agglomeration

To further understand and compare the level of green development in the Shandong Peninsula Urban Agglomeration, a systematic clustering analysis was performed on the green development index of each city in the Shandong Peninsula Urban Agglomeration. In this study, the average value of the green development level index of Shandong Peninsula Urban Agglomeration and each city from 2007 to 2019 was used as the clustering index, and the Euclidean distance was used for the measurement. The sum of squared deviations method was used to classify the samples, and the clustering pedigree diagram is shown in Figure 2.

From Figure 2, the green development level of the Shandong Peninsula Urban Agglomeration can be divided into three basic types (

Table 3. Cluster analysis of the green development level of the Shandong Peninsula Urban Agglomeration.

Type	Score Range	Regional City	Mean	Main Features
I	>0.66	Weihai, Dongying, Qingdao	0.6654	It is a coastal city with a per capita GDP in the forefront of Shandong Province and the coordinated development of economic construction, resource utilization, and environmental protection.
II	0.5903~0.6322	Jinan, Yantai, Zibo, Taian, Linyi	0.6081	It is mainly concentrated in the central Shandong region, where the level of green development is relatively good, and the economic construction, resource utilization, and environmental protection are well coordinated.
III	<0.5412	Weifang, Jining, Liaocheng, Rizhao, Dezhou, Zaozhuang, Binzhou, Heze	0.5499	Most of them are resource-based cities with more traditional industrial zones, and the level of green development is lower than that of other cities. The contradiction between economic construction and resource utilization, and environmental protection is prominent.

). There are specific differences in the level of green development in different types of cities. From the average green development index of the three types of cities, the difference between the type II cities and the type I cities is 0.0573, the difference between the type III cities and the type II cities is 0.0582, and the difference between the type III cities and the type I cities. As high as 0.1155, the development gap is relatively large. Type I cities, represented by Weihai, Dongying, and Qingdao, are mainly located in the eastern coastal area, type II cities are primarily located in the central area, type III cities are mainly located in the western region, and the overall green development level is high in the east and low in the west. The classification results are relatively consistent with the newly issued policy division of the three economic circles of Shandong Peninsula Urban Agglomeration: (1) the provincial capital economic circle includes Jinan, Zibo, Tai’an, Liaocheng, Dezhou, Binzhou and Dongying. It is a demonstration area for ecological protection and high-quality development in the Yellow River Basin, a leading area for regional transmission of national dynamic energy conversion, and a new highland for the exchange and mutual learning of world civilizations. (2) Jiaodong economic circle includes Qingdao, Yantai, Weihai, Weifang, and Rizhao. It is an important shipping and Trade Center, financial center and marine ecological civilization demonstration area in China, a world-class marine science and education core area and a modern marine industry cluster area. (3) The southern Shandong economic circle, including Linyi, Zaozhuang, Jining, and Heze, is a leading area for rural revitalization, a new highland for transformation and development, and an economic uplift belt in the Huaihe River Basin. The order of green development level from high to low is: Jiaodong economic circle, provincial capital economic circle and Lunan Economic Circle.

3.4. Analysis of the Influencing Factors of the Green Development Level of the Shandong Peninsula Urban Agglomeration

The factors affecting the evolution of the green development level of the Shandong Peninsula Urban Agglomeration can be achieved by establishing a regression function that can measure the impact of the green development level of the Shandong Peninsula Urban Agglomeration on industrial structure, government policies, and other control variables. After fully considering the actual situation of the social and economic development stage of the Shandong Peninsula Urban Agglomeration and the regional level difference of each city, this study selects the green development level index of the Shandong Peninsula Urban Agglomeration as the explained variable. It selects the proportion of the added value of the tertiary industry in the GDP and R & D. The proportion of expenditures in GDP, the amount of wastewater discharged per unit of GDP, and the proportion of government energy conservation and environmental protection expenditures in GDP were used as explanatory variables (

Table 4. Influencing factors of green development and interpretation of variables.

Influencing Factors	Variable	Interpretation of Variables
Industrial structure	The proportion of the added value of the tertiary industry in GDP (PVI)	The proportion of the added value of the tertiary sector in the regional GDP reflects the city’s industrial structure.
Technological innovation	R & D expenditure as a proportion of GDP (RD)	The proportion of R & D expenditure in the region’s GDP reflects the innovation level.
Environmental emissions	Wastewater discharge per unit of GDP (WDP)	The smaller the ratio of wastewater discharge to GDP, the lower the wastewater discharge intensity and the higher the level of green development.
Government policy	Proportion of government expenditure on energy conservation and environmental protection in GDP (POG)	The total investment in energy conservation and environmental protection accounts for the proportion of the region’s GDP, reflecting the intensity of the government’s willingness to protect the environment.

). Green Development Level Index of Shandong Peninsula Urban Agglomeration. The functional relationship is expressed by the following equation:

V = f (PVI, RD, WDP, POG)

(9)

where V is the green development level index of the Shandong Peninsula Urban Agglomeration; PVI is the proportion of the added value of the tertiary industry in GDP; RD is the proportion of R & D expenditure in GDP; WDP is the amount of wastewater discharge per unit of GDP; and POG is the proportion of government energy conservation and environmental protection expenditure in GDP.

In this paper, Stata 16.0 (College Station, TX, USA) is used to perform an estimation test on all panel data of Shandong Peninsula Urban Agglomeration from 2007 to 2019, and the multivariate regression model is set as follows:

lnV = β₀ + β₁ lnPVI + β₂ lnRD + β₃ lnWDP + β₄ lnPOG + μ

(10)

Among them, β₀ is the intercept term, β₁, β₂, β₃, and β₄ are the proportion of the added value of the tertiary industry in GDP, the proportion of R & D expenditure in GDP, the amount of wastewater discharge per unit of GDP, and the government expenditure on energy conservation and environmental protection as a percentage of GDP, respectively. Through the regression coefficient, we can see the extent and direction of the influence of each explanatory variable on the explained variable.

To avoid “pseudo regression” the ADF, LLC, and PP methods were used to test the stationarity of each study variable. The results in

Table 5. Stationarity test of panel data.

Variable	ADF		LLC		PP		Conclusion
	Statistics	p-Value	Statistics	p-Value	Statistics	p-Value
lnV	89.1443	0.0006	−7.22018	0.0000	153.185	0.0000	Stable
lnPVI	153.208	0.0000	−5.57331	0.0000	313.628	0.0000	Stable
lnRD	74.6861	0.0001	−4.51224	0.0000	158.306	0.0000	Stable
lnWDP	58.0995	0.0062	−4.19294	0.0000	130.443	0.0000	Stable
lnPOG	75.6278	0.0001	−6.19117	0.0000	185.141	0.0000	Stable

show that each study variable passed the stationarity test. The Hausman test was used further to confirm that the regression model uses the fixed-effects model. The results are shown in

Table 6. Hausman test results.

Test	Chi-Sq. Statistic	p-Value
Hausmann test	20.81	0.0009

. The Hausman test statistic was 0.0009, and the p-value was <0.05, which rejected the null hypothesis. Therefore, the fixed-effects model was used for analysis.

From the regression results of the panel data (

Table 7. Regression results of panel data.

Indicator	Coefficient	Standard Error	t-Statistic	p-Value
lnPVI	0.1397272	0.0450496	3.10	0.002 *
lnRD	0.1331404	0.0122603	10.86	0.000 *
lnWDP	−0.0713295	0.013182	−5.41	0.000 *
lnPOG	0.0351648	0.0108688	3.24	0.001 *
_cons	0.4573482	0.0557473	8.20	0.000 *

Note: * indicates significance at the 1% confidence level.

) and the estimation test of panel data (

Table 8. Estimation test of panel data.

Parameters	Value
R-squared	0.8416
Adjusted R-squared	0.8257
F-statistic	265.66
Prob (F-statistic)	0.0000

), it can be seen that industrial structure, technological innovation, and government policies have a significant positive effect on the green development of the Shandong Peninsula Urban Agglomeration. At the same time, environmental emissions hinder its green development.

(1) The panel model regression coefficient of the added value of the tertiary industry as a proportion of GDP (PVI) is 0.1397272, which shows that the industrial structure can promote the green development of Shandong Peninsula Urban Agglomeration. Compared with the primary industry and the secondary industry, the high-efficiency and low pollution tertiary industry is more conducive to the operation of the economy, and the optimization and adjustment of the industrial structure is imperative. Jinan and Qingdao are the two cities with the highest proportion of tertiary industry in the urban agglomeration, and the “three-two-one” industrial structure model has been formed, while the proportion of secondary industry in other cities is relatively high, and the proportion of the tertiary sector is slightly insufficient.

(2) The regression coefficient of the panel model of R & D expenditure as a proportion of GDP (RD) is 0.1331404, indicating that there is a significant positive correlation between scientific and technological innovation and the green development of Shandong Peninsula Urban Agglomeration. The R & D spending reflects the government’s emphasis on science and technology innovation. From 2007 to 2019, the R & D expenditures of cities in the Shandong Peninsula Urban Agglomeration increased yearly. Upgrade. At the same time, technological innovation can diversify the region’s industrial structure and facilitate the development of high-tech industries. Therefore, the development of science and technology plays a vital role in promoting the green development of the Shandong Peninsula Urban Agglomeration.

(3) The panel model regression coefficient of wastewater discharge per unit GDP (WDP) is −0.0713295, indicating that environmental emissions have a significant negative impact on the green development of Shandong Peninsula Urban Agglomeration The problem of excessive sulfur dioxide emission during the economic development of the Shandong Peninsula Urban Agglomeration is mainly due to the economic production of the heavy chemical industry. Coal and other fossil energy are burned in China, and the energy consumption is enormous. Excessive emission of sulfur dioxide is not in line with the connotation of green development, and it is necessary to continue to vigorously develop technologies to promote energy conservation, emission reduction, and energy consumption and accelerate the transformation and upgrading of traditional industries.

(4) The panel model regression coefficient of the proportion of government energy conservation and environmental protection expenditure in GDP (POG) is 0.0351648, indicating that government policies have a positive impact on the green development level of Shandong Peninsula Urban Agglomeration. During the process, green development should be promoted, and enterprises and the public should be guided to engage in green production and life consciously. By controlling pollutant emissions and introducing and developing environmental protection technologies, green production efficiency should be improved, green consumption can be promoted, and regional green development should be promoted. The cities in the Shandong Peninsula City Group actively responded to the government’s call for developing a green economy. From 2007 to 2019, the energy conservation and environmental protection expenditures of the Shandong provincial government and local cities increased yearly. At the same time, they paid attention to green investment in the development process. Jinan and Qingdao were the first cities to pay attention to environmental protection, and their energy conservation and environmental protection expenditures were much higher than those of other cities. Weihai is the city with the most significant energy conservation and ecological protection expenditure increase. Qingdao has been approved as a national circular economy demonstration pilot city, and Jinan and Yantai have become national low-carbon pilot cities. It can be seen that government policies have effectively improved the level of green development in these cities.

4. Discussion

In this paper, the CRITIC method is used to evaluate the green development level of the Shandong Peninsula Urban Agglomeration by selecting 16 indicators from the four dimensions of social and economic development, resource consumption and utilization, green growth efficiency, and government policy support, including per capita GDP and the proportion of tertiary industry added value in GDP. Indicator system. GIS software was used to spatially express the evaluation results to visualize further the spatiotemporal evolution pattern of green development in the Shandong Peninsula Urban Agglomeration. Although the indicator system and research method for the green development level of Shandong Peninsula Urban Agglomeration are different, the results of this study are relatively consistent with the research results of Liu et al. [28] and Yuan et al. [10]. The main conclusions are as follows:

(1) From 2007 to 2019, the green development level of Shandong Peninsula Urban Agglomeration showed an overall upward trend. The evolution analysis and cluster analysis of the spatial pattern of the green development level of Shandong Peninsula Urban Agglomeration also showed that: in the process of green development, the coastal region was better than the inland region, and the eastern region was ahead of the central and western regions, forming a spatial pattern led by Qingdao and Jinan. In the three major economic circles of Shandong Peninsula Urban Agglomeration, the green development level of Jiaodong economic circle and provincial capital economic circle is higher than that of Lunan Economic Circle.

(2) From the perspective of the influencing factors of green development of Shandong Peninsula Urban Agglomeration, there is a significant positive correlation between industrial structure and green development level index, which shows that promoting the transformation and upgrading of industrial structure and vigorously developing an environmentally friendly economy dominated by the tertiary industry is the best way to promote green development in the region. There is a significant positive correlation between scientific and technological innovation and green development level index. Increasing scientific and technological R & D investment is conducive to improving resource utilization efficiency and transformation efficiency. There is a positive correlation between government policies and the level of green development, but it is not significant, because government policies mainly play a guiding role, and all departments and governments issue relevant policies to guide all kinds of social enterprises and capital elements to tilt towards the tertiary industry. There is a significant negative correlation between environmental emissions and green development level index, indicating that there is still room for progress in resource utilization and environmental protection of Shandong Peninsula Urban Agglomeration.

Based on the above conclusions, this paper puts forward the following suggestions:

(1) Give full play to the distinctive advantages of the provincial capital economic circle, such as strong industrial strength, developed science, innovation, culture and education, rich medical resources, and superior location and transportation. Take Jinan as the center, radiate and drive the integrated development of Zibo, Tai’an, Liaocheng, Dezhou, Binzhou, and Dongying, and build Jinan into a central city in the Yellow River Basin. The local government should continue to give full play to the distinctive advantages of Jiaodong economic circle, such as leading marine economy, developed intelligent manufacturing, concentrated financial services, and high degree of openness. With Qingdao as the leader, the government should promote the development of strong nuclear clusters and clusters with Yantai, Weifang, Weihai, and Rizhao, jointly build a pilot area for China Japan South Korea local economic and trade cooperation and build Qingdao into a global marine center. Give full play to the comparative advantages of the southern Shandong economic circle, such as prominent regional advantages, rich cultural and tourism resources, distinctive industrial characteristics, and huge spatial potential, promote Linyi, Zaozhuang, Jining, and Heze to strengthen urban functions, explore benefit sharing mechanisms that meet the requirements of high-quality development in the fields of industrial development, public services, and ecological environmental protection, promote the transfer of innovative resources and advanced industries, and create a leading area for rural revitalization, a new highland for transformation and development Huaihe River basin economic uplift zone. Promote the synergy and interaction of the “three circles”. Conform to the trend of industrial upgrading, population flow and spatial evolution, promote the transformation of urban development in the economic circle from extension expansion to connotation improvement, and comprehensively optimize and improve the urban carrying capacity and construction quality.

(2) In terms of industrial structure, the government should continue to give play to the demonstration effect of the high-level “dual core” of green development with Qingdao and Jinan as the core, realize the reconstruction and transformation of the industrial structure of various cities in space, break the binding pattern of high in the east and low in the west, and improve the overall green development level of Shandong Peninsula Urban Agglomeration. Expand the “dual core” radiation and driving effect of Qingdao and Jinan, and further accelerate the integrated development of Shandong Peninsula Urban Agglomeration. Actively carry out the construction of “waste free city”, explore the construction of a modern “urban mineral” base [29], and promote the standardized, large-scale and clean utilization of renewable resources. In terms of scientific and technological innovation, the government should transform or ban traditional industries with high energy consumption, high pollution and low output, vigorously develop new green industries such as environmental protection and green services, further adjust the industrial structure and build a green industrial system. Actively promote photovoltaic, wind power, nuclear power and other clean energy projects, improve the layout of relevant infrastructure construction, realize the transformation from the traditional high energy consumption and high pollution energy structure to the green and clean energy structure, and promote the low-carbon development of the city. Strengthen the publicity of the concept of water saving in production and life, speed up the research and development of water-saving technology, reduce the water consumption of industrial and domestic water, and improve the efficiency of water saving and the recycling rate of water resources. In terms of government policies, improve the green fiscal policy, ensure the efficient operation of the carbon emission trading market through a stable and reliable system, help achieve the “double carbon” goal, introduce more policies to attract investment, and promote the comprehensive green transformation of the economic and social development of Shandong Peninsula Urban Agglomeration.