Research on high-quality economic development in Tianjin

ABSTRACT

This paper selects development indicators of primary industry, secondary industry, and tertiary industry, as well as indicators of public lifestyle, to measure the impact of economic development and general public lifestyle on the environment. A grey relational degree model is used to analyse Tianjin’s evolving characteristics from 2000 to 2020 on the balanced development of the economy and environment. The results suggest that: Firstly, Tianjin’s overall coupling degree between economic growth and environmental change varies from 0.56 to 0.75, which is at a moderate coordination level, and the degree of coordination between tertiary industry and environment is high. Secondly, taking time as the axis, the relational degree is significant between economic growth and environmental change. From 2015 to 2020, the synergy between the development of the secondary industry and the environment declined, indicating that the development of the secondary sector has caused some environmental destruction. On these grounds, Tianjin should give full play to its traditional advantages and comparative advantages, lay emphasis on the optimisation and upgrading of its industrial structure in the process of continuously deepening the integration of Beijing-Tianjin-Hebei, promote the deep integration of manufacturing and service industry, and boost the quality its economic development.

KEYWORDS:

• High-quality economic development
• environmental evolution
• synergy
• empirical
• grey correlation model
• Tianjin

1. Introduction

Since the reform and opening-up, China’s economy has been growing rapidly. At the same time, it caused environmental pollution. Hence, the stability of economic development and the ecological environment has become one of the hot research issues in environmental science, economics, and cross fields, among which the research based on the environmental Kuznets curve hypothesis is the most common. The environmental Kuznets curve (EKC) first defined by Panayotou is the most representative one (Liu and Gao 2019; Wei and Wang 2019; Wang and Ding, 2022). Its application focuses on EKC theory, policy interpretation, and empirical research to decide whether the EKC hypothesis exists between economic growth and environmental quality evolution in different countries or regions (Zhang et al. 2020). In the past 30 years, many studies have shown an inverted U-model, positive U-model, inverted N-model, or linear model relationship between the economy and environment (Zhou and Wang, 2020). The rationalisation level and advanced level of industrial structure, industrial synergy, innovation level, population density, and proportion of scientific and technological expenditure all exert a certain pressure on environmental governance (Gong and Liu 2020; Wang and Sun, 2020; Yan et al. 2019; Hu 2019). In terms of the coordination relationship between economic development and environmental protection (Hao et al. 2019), scholars often measure it by using the input-output model, nonlinear extended production function, and neoclassical economic model (Ruilin et al. 2012), grey correlation degree (Jiqin et al. 2017), coordination degree (Lujun et al. 2015), dynamic coupling (Zhang 2020), fuzzy grading evaluation (Yuan 2001) and other models, etc. ARMA model (Ruiling et al., 2014a; Liu et al. 2022) and grey GM model (Ruiling et al., 2014b) are used to analyse the dynamic evolution of coupling coordination of the 3E system and AEE system. From a regional perspective, existing research objects are mainly focused on the whole nation (Fuzhou and Zhang 2020), economic belt (Jianxin et al. 2020), urban agglomeration (Liu et al. 2019), and province and county. There are a few independent studies on Tianjin, but they are mainly focused on the integration of the Beijing-Tianjin-Hebei region. The strategic positioning of Tianjin’s ‘one base and three districts’ has laid the foundation for Tianjin to form a high-quality development pattern with complementary advantages in integrating Beijing-Tianjin-Hebei. Under the background of entering high-quality economic development in China, although Tianjin’s economy has good foundation conditions for its high-quality product, what is the situation of quality development of Tianjin’s economy? The research results have not given a reasonable explanation. Therefore, it is important to scientifically and reasonably measure the synergy level between Tianjin’s economic development and environmental evolution. We aim to accurately grasp the characteristics of Tianjin’s high-quality economic development and identify the restrictive role of environmental factors in the process of Tianjin’s high-quality economic development as soon as possible.

At present, Zhang and Chenglin, (2021) constructed a coupling coordination degree model of industrial structure, urbanisation, and ecological environment and analysed the dynamic response relationship between them by using impulse response and variance decomposition; the result showed that the coupling degree between industrial development and environmental regulation in Beijing-Tianjin-Hebei was more significant than 0.6; therefore it was considered that the coupling degree between industrial development and environmental regulation is relatively high (Zhang et al. 2021). In addition, the coordinated development degree between industrial structure adjustment and ecological environment in the Beijing-Tianjin-Hebei region was at a medium level and needed to be improved (Rong 2022). Guo, Xue, and Hou (2021) report that was not apparent regarding the synergistic effect of the Beijing-Tianjin-Hebei region. The improvement of the environmental level should be emphatically considered in the future. Hence, previous empirical results are different, resulting in finding out the antecedents. Based on the data on economic development and environmental change in Tianjin from 2010 to 2019, this paper constructed a grey relational model to study the level of high-quality economic development in Tianjin and put forward policy suggestions.

Under the current complex international and domestic background, Tianjin, the largest coastal port and light industry city in the Beijing-Tianjin-Hebei metropolitan area undertakes the critical mission of promoting economic development. To explore the difference of time-space and evolution process in the development progress of Tianjin, according to the country’s sustainable development concept, improving the regional resource allocation, and promoting development trends on an environment-friendly economy, can put forward opinions and suggestions for the coordinated development between the integration of the Beijing-Tianjin-Hebei region and environmental protection, to narrow the gap in Beijing-Tianjin-Hebei metropolitan area development level and environmental quality. It further promotes the coordinated development of Beijing-Tianjin-Hebei integration and provides a reference for the construction of other urban agglomerations in China.

This study provides three paths to high-quality economic development in Tianjin. First, to increase the economic volume by vigorously promoting economic development, and improve the coupling coordination degree between economic development and the environment in Tianjin, paying attention to the scientificity and consistency of formulation of industrial development strategy, and providing strong financial support and administrative capacity guarantee for the steady improvement of Tianjin’s environmental quality (Chuanzhong and Bing 2017). Second, to optimise and upgrade the industrial structure, take advantage of the opportunity of Beijing-Tianjin-Hebei regional integration, adjust pollutant discharge, industrial types, and residents’ lifestyles in the process of relief of non-capital functions, and upgrade technologies. Finally, Tianjin should fully consider the influence of the rise of Xiongan New Area and its changes to the Beijing-Tianjin-Hebei integration pattern, take the initiative to adjust the industrial layout, and gain a head start in the integration of Beijing-Xiongan-Tianjin-Hebei.

2. Literature review

The research on high-quality economic development in academic circles began in October 2017. Until now, the concept of development based on clean water and green mountains is prevalent; the picture of harmonious coexistence between humans and nature has been vividly unfolding across the country. High-level government officials, think tanks, and many scholars have explained the connotation of high-quality economic development, but no unified statement has been formed. The understanding of this connotation is directly related to how to measure the level of high-quality development and what basis to promote the high-quality economic development of various regions in China. The discussion on the deep meaning of high-quality economic development mainly focuses on five aspects: 1) Understanding high-quality economic development from the perspective of five development concepts; 2) From the perspective of the relationship between supply-side structural reform and high-quality development, it is believed that high-quality development is green and sustainable growth, and the extensive growth mode that destroys the ecological environment is not sustainable (Liu et al. 2019); 3) From the perspective of specific discipline research, such as the perspective of economics and sociology; 4) From the macro and micro perspectives, the micro performance of high-quality development is to raise production level, the medium measure performance is the structural upgrade and efficiency change, and the macro performance is the balanced development of the whole economy, which is essentially an advanced stage of economic development. High-quality development has to rely on green development, which requires high tech and innovation. More recently, research achievements on the coupling relationship between economic development and the environment are various. Among the indicators of industrial development and public life that affect environmental quality, industrial wastewater has the most significant spillover effect (Min et al. 2022).

Regarding environmental protection, scholars generally believe that green is an inevitable requirement of high-quality development. Green development emphasises sound and social development between man and nature, the economy, and the ecological environment. Combining economic growth with environmental protection, reducing damage and pollution as much as possible, and paying close attention to the preservation and restoration of the ecological environment can we promote sound and sustained economic and social development. Must adhere to ecological priority, thoroughly understand the essential requirements of ecological civilisation construction, clarify the close relationship between high-quality economic development and green development, adhere to punching pollution, speed up to promoting the economic transformation, release the development space of green growth, to promote high-quality economic development in China. Through constructing an interactive relationship model between environmental quality and economic growth and using the entropy method to estimate the local environmental rate, Liu et al. (2022) report that there is a significant two-way interaction between environmental quality and economic growth. In the stage of high-quality development, economic growth is conducive to improving environmental quality. In the Yangtze River Economic Belt, the growth quality and the value of the eco-environmental optimisation coupling degree have been continuously improved. The corresponding urban ecological environment optimisation score is higher than the growth quality, and the growth quality improvement lags behind the ecological environment optimisation process (Qiang and Wei 2019).To be more specific, the threshold regression effectively resolved the‘heterogeneity’ of the EKC test and got a more accurate conclusion effectively. It is significant to accurately understand the relationship between China’s economic growth and environmental quality. Specifically, effective development measures consist of 1) preparing the natural resources balance sheet; 2) strengthening resources environment audit to promote the reasonable use of natural resources; 3) inhibiting the occurrence and influencing of recessive economic strictly; 4) eliminating the internal resistance of environment and economic growth; 5) encouraging social capital to participate in environmental governance; 6) encouraging insurance industry to play an essential role in environmental pollution liability insurance; 7) promoting the marketisation of environment and economic growth quality (Wen and Wang 2018). Coordinating economic growth and environmental protection was vital because economic growth and environmental quality sometimes were not promoted in a synchronised way. Hence, it is necessary to find out appropriate environmental and economic policy measures (Yingshan 2016). Improving emission reduction technology and increasing investment in pollution control is the key to leapfrogging the turning point of the inverted U-shaped environmental Kuznets curve and realising environment-friendly economic growth (Wang 2015).

Similarly, there is no consensus on what variables should be used to characterise the concept of high-quality economic development. A few scholars believe that the single index can represent high-quality economic development, such as total factor productivity and labour productivity, and many scholars believe that high-quality economic development is a multi-dimensional concept. Consequently, a multi-dimensional variable was constructed. For example, indicators reflecting quality and results involve dimensions of innovation, coordination, green, openness, and sharing). Zhang et al. (2020) respectively based on different understandings, constructed the index system containing multi-dimensional characteristics to characterise high-quality economic development.

Although scholars have constructed different evaluation index systems, there are similarities in selecting fundamental indicators. Among them, the majority of scholars use per capita GDP and economic growth rate to measure economic growth; use industrial structure, demand structure, and supply quality to measure economic structure; use Theil index, tertiary industry proportion, and industrial construction to measure the optimisation of an industrial system; use foreign trade dependence degree and ratio of consumption to measure the optimisation level of demand structure, and use product quality pass rate, product quality superior product rate to measure product supply quality and so on.

In the aspect of the social system, most scholars apply the urbanisation rate to measure the urbanisation level of a region, utilise the income gap ratio of urban and rural residents to measure the optimisation degree of urban and rural structure, and use the number of buses per unit population to represent the development level of public transport. In terms of the environmental system, many researchers use the greening land rate to measure the greening level of a region, apply the energy consumption of a unit product to measure the energy consumption intensity, and use the emission of three wastes to measure the pollution of production. Therefore, scholars study high-quality economic development based on the five systems, which are economy, society, culture, science and technology, and environment. Although many indicators are covered, they are very concentrated in the selection and use, which provides a reference basis and beneficial thought for the construction of the index system for this paper. In addition, the new economic evaluation system of the United States, the national welfare measurement index system of Germany, and the green growth evaluation system of the Netherlands are also of reference significance for the establishment of the measurement index system of high-quality economic development in this paper.

In summary, the existing literature mainly studies the coupling relationship between economic growth and environmental change, discusses the influence mechanism of each other, and proposes governance schemes that lack collaborative analysis of economic development and ecological evolution. The empirical research on the measurement of a high-quality product remains unclear. As a consequence, the policy suggestion would be to find out a necessary practical test. This paper constructed two index systems which include economic growth and people’s lifestyle. It also created a grey correlation model to explore the results of Tianjin’s high-quality economic development. Furthermore, based on these empirical studies and the multi-dimensional characteristics of high-quality economic growth, this paper reveals the essential influencing factors of high-quality economic development in Tianjin and proposes policy implications.

3. Data sources and research methods

3.1. Overview of the study area

Tianjin became one of the world’s megacities in 2011. It is a municipality and a megalopolis in China and the only pilot free trade zone in northern China. By the end of 2019, Tianjin had 15,618,300 permanent residents, an increase of 22,300 over the end of 2018, jurisdiction area of 11,916.85 square kilometres. Regarding the economy, Tianjin’s GDP growth rate was 12.7% in 2002, ranking second in China. The added value of industries increased by 22.8% per year. In 2010, the industrial added value in Tianjin was 23.7%, and the GDP growth rate was 17.4%, ranking first in China until 2013. However, in 2015, Tianjin’s economic growth rate dropped sharply. After that, it kept declining. In 2017 and 2018, the GDP growth rate was only 3.6%. In 2019, The GDP growth rate of Tianjin was 4.8%, although it seemed to be 1.2 percentage points higher than the previous year; the nominal GDP growth rate was −25% after the elimination of the ‘comparable price’ condition. However, in 2019, the proportion of excellent water quality (classI-III) in Tianjin reached 50% for the first time, an increase of 10 percentage points, compared with the base year (2014, The same below), it increased by 25 percentage points; The proportion of inferior water quality dropped to 5%, 20 percentage points lower year-on-year and 60 percentage points less than the base year. The average annual concentrations of major pollutants, permanganate index, chemical oxygen demand, ammonia nitrogen, and total phosphorus, respectively, decreased by 8.7%, 17.2%, 21.5%, and 22.1% year-on-year and reduced by 41.1%, 53.0%, 78.4%, and 68.1% compared with the base year. The environmental water quality reached the best level in recent years (Tianjin Ecological and Environmental Status Bulletin, 2019, June 2020).

3.2. Index system and data sources

On a national scale, from the early 1980s to 2015, environmental pollution caused by economic development showed a trend of aggravation. In turn, environmental pollution also had a significant inhibition effect on economic development through the government’s governance behaviour and the government’s environmental governance that significantly reduced environmental pollution. Therefore, when studying the relationship between economic development and environmental synergy, the three principles of systematism, scientificity and comparability are often followed, and data availability is also taken into consideration (Peng et al. 2020) to select corresponding evaluation indicators to build an evaluation index system. In recent years, there have been fruitful research results in the area of the coupling coordination degree between the economy and the environment. Scholars have constructed different coupling and coordination evaluation index systems for economic development and environmental pollution (Kuang et al. 2020), such as GDP, industrial and domestic COD, SO2 emissions, etc. (Azhong et al., 2020. Or single economic indicators, such as FDI (Cang et al. 2020), industrial structure change, energy efficiency, etc., are used to study the coupling and coordination relationship between economic development and the environment and its stability state. Indicators are selected from the different dimensions of economic growth in describing the state of economic development, mainly including monetary aggregate, economic structure, and the residents’ live level. In the comprehensive measurement environment, the indicators mainly focused on reflecting the ‘three wastes’ and greening degree, such as the forest coverage rate, park area ratio, green coverage, etc.

Based on the existing studies, and considering data availability, following the principles of science, operability, and representativeness, selecting economic development level, financial structure, and environmental quality, etc. 17 indicators from two aspects of economic development and environmental quality, this paper constructed the evaluation index system of coupling coordination degree between economy and environment in Tianjin, as shown in Table 1. $x_1$、$x_2$ are economic aggregate indicators; $x_3$-$x_6$ are structure indicators of the economy; $x_7$-$x_{11}$ are indicators of residents’ living conditions; $y_1$-$y_6$ are indicators of the environment category.

Table 1. Economic and environmental test indicators.

Number	Economic indicators	Serial number	Environmental indicators
$x_1$	Actual GDP	$y_1$	Per capita energy consumption
$x_2$	Industrial added value	$y_2$	Industrial wastewater discharge per capita
$x_3$	The proportion of heavy industry in the industry	$y_3$	Per capita industrial solid waste emissions
$x_4$	The proportion of industry in the GDP	$y_4$	Industrial dust emissions per capita
$x_5$	The proportion of Tertiary Industry	$y_5$	Soot emissions per capita
$x_6$	The actual level of consumption	$y_6$	Sulphur dioxide emissions per capita
$x_7$	The proportion of urban and township population
$x_8$	Per capita living area in cities and towns
$x_9$	Rural per capita living space
$x_{10}$	Per capita road area
$x_{11}$	The number of traffic tools used by per capita

3.3. Research methods

In recent years, the primary analysis methods of system coordination degree are the entropy equation method, coupling coordination degree model, interval value judgement method, and grey relational degree model. The entropy equation method is easy to use. It is objective compared to the higher similarity degree of the graph contour with the grey correlation model and the coupling coordination model. However, only pairwise comparisons can be made to obtain the coordination and short-term coordination trend relative to the comparison object. Calculating the comprehensive development index of the economy and environment is easily influenced by the standardised method. There are two apparent deficiencies in the coupling coordination degree model: one is how to determine the upper and lower limits of factors. Expected value, ideal value, and planning value, which one should be used? People make choices according to subjective criteria. Even if a data set is used, different upper and lower limits may lead to totally different results, and the conclusion tends to be unconvincing. Secondly, the division of coordination levels is too subjective because there could be six levels or more than ten levels. Therefore, the division is non-uniform and lacks test methods. The Interval value judgement method uses the cross-section data of each system to reflect the comprehensive development level. The regression coefficient is calculated to describe the relationship between economic development and environmental change. Its reliability depends on the selection of the type of economic period and region, which requires both the selected economic period and region to be coordinated at the same time. Their simultaneous and coordinated development of them is very rare, so this method is rarely used in empirical research. Grey relational degree model has no special requirements on sample size and regularity. For small computations, it is simple and convenient and can make up for the deficiencies of the mathematical statistics method. There will be no inconsistency between quantitative results and systematic analysis results. It also has a disadvantage: the criteria for the strength of the correlation is artificial and depends on the subjective judgement of researchers.

To conclude, these systems coordination degree analysis methods have their advantages and disadvantages. A grey relational degree model can analyse the main stress factors affecting economic development and environmental change and calculate the degree of correlation between each index in a different system. It is quite suitable to explain the reality of the economic environment with good reliability and slight deviation and has incomparable advantages compared with other methods. This paper chooses the grey relational model to analyse the coordination degree between the economy and environment in Tianjin. Its specific steps are shown as follows:

1. Standardization of raw data

The basic idea of a grey correlation degree model is to describe the contour of the image according to the time sequence of the analysis object and determine the correlation degree by judging its similarity degree. If it is higher than the contour similarity degree of the graph, the corresponding sequence correlation degree is higher, and vice versa.

To eliminate the effects of data dimension and take the principle of stability (Gao and Xingqi 2020) into account, ‘initial value’ is applied to standardise dimensionless processing.

Assume $X_{\mathrm{i}}=(x_i(1),x_i(2),\dots x_i(n))$ is the behavioural sequence of factors$X_{\mathrm{i}}$， $D_1$is the sequence operator, and$=(x_i(1)d_1,x_i(2)d_2,\dots x_i(n)d_n)$， inside，

$x_i(k)d_1=x_i(k)/x_i(1),x_i(1)\ne 0,k=1,2,\dots n$．$D_1$ called initialisation operator， $X_{\mathrm{i}}{D}_1$is the image under the initialisation operator of $X_{\mathrm{i}}$ which refers to the initial image.

2. The grey relational degree model

Assume that the system behaviour sequence is:

$X_1=(x_1(1),x_1(2),\dots x_1(n))$

$X_2=(x_2(1),x_2(2),\dots x_2(n))$

．．．．．．

$X_{\mathrm{i}}=(x_i(1),x_i(2),\dots x_i(n))$

．．．．．．

$X_{\mathrm{n}}=(x_{\mathrm{n}}(1),x_n(2),\dots x_n(n))$

for$\xi \in (0,1)$， to make

(1) $\gamma (x_0(k),x_i(k))=\frac{\underset{i}{min}\underset{k}{min}\left|x_0(k)-x_i(k)\right|+\xi \underset{i}{max}\underset{k}{max}\left|x_0(k)-x_i(k)\right|}{\left|x_0(k)-x_i(k)\right|+\xi \underset{i}{max}\underset{k}{max}\left|x_0(k)-x_i(k)\right|}$(1)

(2) $\gamma (X_0,X_i)=\frac{1}{n}\sum _{k=1}^n\gamma (x_0(k),x_i(k).$(2)

3. The general steps for calculating the correlation degree are shown as follows

①Find the Initial Image.

(3) ${Y_{\mathrm{i}}}^{\mathrm{\prime }}=Y_{\mathrm{i}}/y_i(1).$(3)

②Find the difference between the sequences.

(4) ${\mathrm{\Delta }}_{ij}(k)=\left|{y_i}^{\mathrm{\prime }}(k)-{x_j}^{\mathrm{\prime }}(k)\right|.$(4)

③Find the difference between the poles.

(5) $\underset{i}{\mathrm{M}=max}\underset{k}{max}{\mathrm{\Delta }}_{ij}(k),\mathrm{m}=\underset{i}{min}\underset{k}{min}{\mathrm{\Delta }}_{ij}(k)$(5)

④Find the correlation coefficient.

(6) $\gamma (x_0(k),x_i(k))=\frac{\underset{i}{min}\underset{k}{min}\left|x_0(k)-x_i(k)\right|+\xi \underset{i}{max}\underset{k}{max}\left|x_0(k)-x_i(k)\right|}{\left|x_0(k)-x_i(k)\right|+\xi \underset{i}{max}\underset{k}{max}\left|x_0(k)-x_i(k)\right|}$(6)

⑤ Calculation of grey correlation.

(7) $\gamma (X_0,X_i)=\frac{1}{n}\sum _{k=1}^n\gamma (x_0(k),x_i(k).$(7)

4. Empirical analysis

The mapping quantity of Tianjin’s reaction economy system and environmental system is industrial added value, and the economic indexes such as industrial added value and per capita transportation are expressed by $x_{1\hspace{0.17em}}\hspace{0.17em}to\hspace{0.17em}{x}_{10}$ respectively. The observation data on the serial number k of the Tianjin reaction economy system is $x_i\left(k\right)$. Using $y_1$ to $y_6$ points to represent the per capita industrial dust emissions and other environmental indicators, the observation data on its serial number k is $y_i\left(k\right)$.

4.1. Correlation matrix

The correlation degree, γ, is beneficial to the calculation of the mean value of the correlation coefficient to reflect the complex coupling relationship between economic development and environmental change (Feng et al. 2017). By comparing the correlation degree of each factor, we can analyse the relationship between the determinants of economic growth and the indicators of environmental change. Based on the data from the Tianjin Statistical Yearbook (2000–2015), this paper calculates the correlation coefficient matrix of Tianjin’s economic development and environmental change, as shown in Table 2.

Table 2. Correlation coefficient of economic development and environmental change in Tianjin.

	Energy consumption per capita	Per capita industrial wastewater discharge	Per capita industrial solid waste emissions	Per capita industrial dust emissions	Emissions of soot per capita	Emissions of sulfur dioxide per capita	mean value
Actual GDP	0. 5724	0. 6795	0. 5988	0. 6112	0. 7823	0. 6127	0. 6428
$x_1$	0. 5714	0. 6585	0. 5759	0. 6158	0. 7651	0. 6044	0. 6319
$x_2$	0. 5112	0. 6235	0. 5491	0. 6143	0. 7335	0. 6562	0. 6146
$x_3$	0. 5976	0. 7429	0. 6417	0. 6752	0. 7232	0. 6131	0. 6656
$x_4$	0. 5902	0. 7683	0. 6133	0. 5649	0. 8578	0. 5824	0. 6628
$x_5$	0. 6215	0. 6896	0. 6125	0. 5797	0. 7844	0. 5714	0. 6432
$x_6$	0. 6142	0. 6766	0. 5842	0. 5936	0. 7692	0. 5873	0. 6375
$x_7$	0. 6137	0. 6931	0. 5824	0. 5941	0. 757	0. 5859	0. 6377
$x_8$	0. 5116	0. 7394	0. 6232	0. 5876	0. 6324	0. 6236	0. 6196
$x_9$	0. 5138	0. 6248	0. 5487	0. 6164	0. 7242	0. 5921	0. 6033
$x_{10}$	0. 5394	0. 7573	0. 6748	0. 5436	0. 7754	0. 5867	0. 6462
mean value	0. 5688	0. 6958	0. 6004	0. 5997	0. 7550	0. 6014

From Table 2, the minimum value of the correlation degree between single indicators is 0.5024, and the maximum value is 0.8584. According to theory, the tertiary industry is an environment-friendly industry, and its development has minor damage to the environment. The proportion of the tertiary sector in Tianjin has the strongest correlation with the environment, indicating that tertiary industry development has a more significant impact on the environment and has a strong synergy with the environment. The actual situation of the tertiary industry’s development and environmental changes is consistent with this in Tianjin from 2000～2015. From the above table, the industrial proportion（$x_2$）of heavy industry is poorly correlated with the environment, and the development of heavy industry has a tremendously destructive force on the environment. In the US, heavy industry made unprecedented achievements in the 1950s and 1960s. At the same time, environmental pollution was also the most serious, with the destruction of land, air, rivers, and sea reaching the highest level in history. The development of heavy industry and environmental changes in Tianjin repeated this historical process: in addition to the individual years, heavy industry development in Tianjin has been faster than the national average, the relevant industrial processing equipment level is behind the heavy industry development speed, resource utilisation efficiency is low, producing more waste and pollution, processing efficiency is low, the industrial ‘three wastes’ treatment equipment ability is weak, the environmental pollution of Tianjin is severe.

The correlation degree data in Table 2 also shows that most of the coupling degrees are at a medium or firm level, but the coordination between $x_{3\hspace{0.17em}}$(industry in GDP) and environment is the strongest, indicating that Tianjin is well-coordinated between the development of light industry and environmental protection and has realised sustainable industrial development and environmental protection. As shown in Figure 1.

Figure 1. The correlation between economic development and environmental change.

Among the correlation degree of economic development index and environmental change, the proportion of the tertiary industry is strongly related to the environment.

Based on the correlation degree list, the average value is calculated, and the correlation degree between each economic index and environmental change is obtained. The average weight of each column is calculated to obtain the correlation degree of ecological indicators and economic growth. The correlation degree between economic development indicators and environmental change fluctuates slightly from 0.6033 to 0.6656, and the coupling effect with the environment is moderate. Figure 2 shows the curve of the correlation degree of ecological indicators and economic growth, with the characteristics shown as follows:

Figure 2. Correlation degree.

The correlation degree between environmental change and economic development level shows that the correlation degree coefficient of various indicators of environmental change is in a range from 0.5688 to 0.7550, among which the correlation degree of per capita industrial smoke emissions and economic development is the strongest (0.7550), while the correlation degree of other environmental indexes and economic growth is medium or strong.

4.2. The change of coupling degree between the economy and environment

Taking time as the axis to analyse the coupling relation between economic growth and environmental change in Tianjin, the coordination between them is clearer. Figure 3 shows the curve of the coupling degree of Tianjin’s economy and environment during 2000～2015, with the characteristics shown as follows:

Figure 3. The change curve of economic and environmental coupling degree in Tianjin from 2000 to 2015.

First, the coupling degree of economic development and environmental change is mainly in the range of 0.56 to 0.75, with apparent fluctuation, indicating that the coupling degree of economy and environment is substantial.

Second, at different stages of development, the degree of correlation between Tianjin’s economic growth and environmental change is significantly different. In 2001, the coupling degree decreased to the lowest level and began to increase in 2002, but the increase rate was low, remaining at (0.5, 0.6). In 2007, the coupling degree increased to above 0.7, reaching its highest (close to 0.8) in 2011, which lasted until 2012. Since 2013, the coupling degree began to decline sharply, even dropping to 0.6 in 2015. This trend of change in Tianjin is closely related to major local events: On 12 August 2015, an explosion accident occurred in Binhai New Area, which was the most costly disaster accident in China in recent years, causing a direct economic loss of over 70 billion yuan and an immeasurable indirect cost. The main component of the explosive is cyanide, which causes some pollution to the soil, air, and water environment in the explosion centre and surrounding area.

4.3. Trend analysis of coordinated development of economy and environment

Using the data from Tianjin Statistical Yearbook (2016–2019) and using the same calculation method, the correlation coefficient between the environment and economy in 2016–2019 was calculated, as shown in Table 3.

Table 3. Correlation coefficient matrix of environment and economic development in Tianjin,2016～2019.

	Energy consumption per capita	Per capita industrial wastewater discharge	Per capita industrial solid waste emissions	Per capita industrial dust emissions	Emissions of soot per capita	Emissions of sulfur dioxide per capita	mean value
Actual GDP	0.5349	0.5258	0.7951	0.9849	0.5293	0.5135	0.6473
$x_1$	0.5409	0.5244	0.7954	0.981	0.5158	0.5104	0.6447
$x_2$	0.525	0.5334	0.7964	0.977	0.5215	0.5241	0.6462
$x_3$	0.5282	0.5374	0.794	0.9656	0.5882	0.5219	0.6559
$x_4$	0.8785	0.7275	0.8792	0.8807	0.7128	0.6066	0.7809
$x_5$	0.9659	0.9933	0.4026	0.5318	0.9491	0.9713	0.8023
$x_6$	0.5832	0.5341	0.784	0.9779	0.5056	0.51	0.6491
$x_7$	0.5832	0.533	0.7708	0.9777	0.487	0.5068	0.6431
$x_8$	0.4267	0.5358	0.7703	0.9741	0.3493	0.5183	0.5958
$x_9$	0.4584	0.5052	0.7791	0.982	0.4793	0.5054	0.61828
$x_{10}$	0.4866	0.5155	0.7717	0.9759	0.5065	0.5608	0.6362
mean value	0.5647	0.5696	0.7490	0.9371	0.5404	0.5590

Compared with the correlation degree matrix in the previous section, there are some changes in the correlation degree listed in Table 3 during 2016～2019. The correlation between the economic indicators and the environment has been enhanced, among which the tertiary industry has the most significant correlation coefficient. Meanwhile, environmental indicators and economic correlation degrees changed, as shown in Table 3. During the 13th Five-Year Plan, due to the rising proportion of the tertiary industry in Tianjin and the relatively high correlation between industry and the environment, the environmental quality of Tianjin has improved. The change of coupling degree between them was analysed with time as the axis, as shown in Figure 4.

Figure 4. Change of coupling degree.

The coupling degree of economy and environment in 2016 was slightly different from that in 2015, but it increased in 2017.

This indicates that the coordination ability of the economy and environment system was improved, which was related to the strict environmental control implemented by the government after the ‘8.12’ disaster. In 2018, the coupling degree exceeded 0.8, showing a strong coupling effect on the economy and environment, which is closely related to the in-depth promotion of triple integration. The triple integration is a national strategy, and due to the concentration of heavy industry and ‘three high’ industries in Tianjin, Tangshan, Langfang, Cangzhou, and other cities around Beijing, the environmental pollution in three sides has been serious for more than 15 consecutive years since 2001, which is mainly marked by haze (NASA, 2001–2016). Since the 18th CPC National Congress, the CPC Central Committee, with General Secretary Xi Jinping as the core has paid great attention to the construction of ecological civilisation. Ecological and environmental protection is a cause that will benefit the present and future generations, and environmental protection policies continue to make strong efforts (Bian et al. 2019), and the industrial structure of the Beijing-Tianjin-Hebei region continues to be greatly adjusted. By 2017, the environment of Beijing and Tianjin and its surrounding areas had significantly improved. From 2018 to 2020, the number of days with good air quality increased continuously throughout the year. However, Tianjin’s economy began to squeeze in 2018, with an economic growth rate of 4.8% in 2019, ranking very low in the country. In 2020, affected by the pandemic, the city experienced a negative growth rate of 3.9% in the first half of the year, further reducing the coupling degree between economic development and the environment. However, after three years of GDP ‘squeeze’ and vigorous industrial structure adjustment, Tianjin’s economy has hit bottom and bounced back. Moreover, Tianjin’s industrial foundation is strong and the development momentum is sufficient. The 14th Five-Year Plan should continue to take adequate measures to change the coupling path between economic development and the environmental system so as to realise the coordinated and sustainable development of the economy and environment.

5. Results and discussion

Taking Tianjin as the research object, based on the connotation of high-quality development, constructing the coupling coordination degree evaluation index system between economy and environment, using a grey relational model method to analyse the temporal and spatial variation characteristics of coordination degree between economic development and environmental evolution of Tianjin. The following conclusions are obtained:

1) The correlation degree between economic development indicators and environmental change fluctuates slightly, 0.6033 ~ 0.6656, and the coupling effect with the environment is moderate. This means that the overall coordination degree between Tianjin’s economy and environment is at a medium level, among which the tertiary industry and environment have strong coupling, meaning there is a high degree of coordination.

2) The coupling degree of economy and environment in 2016 was slightly different from that in 2015, but it increased in 2017. This indicates that the coordination ability of the economy and environment system was improved, which was related to the strict environmental control implemented by the government after the ‘8.12’ disaster. From 2015 to the first half of 2020, Tianjin’s synergy between the proportion of industry in GDP and the environment decreased, meaning that Tianjin’s development of secondary industry brought a severe negative impact on environmental protection.

3) At different stages of development, the degree of correlation between Tianjin’s economic growth and environmental change is significantly different. In 2001, the coupling degree decreased to the lowest level and began to increase in 2002, but the increase rate was low, which remained in 0.5,0.6. In 2007, the coupling degree increased to above 0.7 reaching its highest (close to 0.8) in 2011, which lasted until 2012. Since 2013, the coupling degree began to decline sharply, even dropping to 0.6 in 2015. In different periods, the ‘factors’ influence is different in the intensity of the coupling coordination of the economy and environment in Tianjin. Still, the level of economic development and industrial structure has a strong influence in the study period. The effect of the optimisation degree of the industrial system on the coupling coordination of the economy and environment in Tianjin gradually increases.

4) From 2015 to 2020, the synergy degree between industry and the environment decreased. Declining economic growth has optimised the environment. The factors affecting Tianjin’s economy are highly complex, including statistical method changes, brain drain, fake migration, and the bidirectional siphon effect from Beijing and Xiongan New Area.

6. Conclusion

This paper studied the synergy between Tianjin’s economic development and environmental evolution and analyzes the situation of high-quality development based on the data of Tianjin from 2000 to 2020. In terms of selecting environmental indicators, this paper creatively selected two index systems of economic growth and people’s lifestyle, constructed a grey correlation model to explore the results of Tianjin’s high-quality economic development, and for the first time, included Xiongan New Area as an important influencing factor in the study, and drew a conclusion that Tianjin should combine its own advantages to form industrial complementarities and dislocation development with Beijing, Xiongan New Area and Hebei Province. To put it in a nutshell, we fill the literature gaps as follows:

-Leverage traditional strengths and promote high-quality development of the manufacturing industry. The coupling relationship between the light industry and the environment indicates that there is an excellent space for coordination and ‘symbiosis’ between them. The light industry has high added value and high output value, which plays a vital role in the development of a local economy. The 14th Five-Year Plan of Tianjin and the long-term goal of 2035 propose to speed up the construction of a strong manufacturing city, make Tianjin into a national advanced manufacturing research and development base in the coming 5 years, and promote the high-quality development of Tianjin’s economy to a higher level. Tianjin occupies an important position in the history of China’s modern industrial development. It is the birthplace of China’s modern industry, with a solid industrial foundation and complete industrial categories.

-Tianjin is positioned as the development orientation of ‘building a national advanced manufacturing research and development base’ by the central government, should release its comparative advantages and traditional advantages and become a driving force leading China’s transformation from a big manufacturing country to a great manufacturing power.

-Promote the integrated development of advanced manufacturing and modern service industries. The manufacturing industry and manufacturing service industry can promote the level of innovation and development equally, and their coordinated development is the optimal combination of industrial structure upgrading. Therefore, it should not be advocated to simply increase the proportion of the tertiary industry or the single polarisation of manufacturing development.

-According to the ‘14th Five-Year Plan’, Tianjin should vigorously develop the modern manufacturing industry and build a national research and development base for the manufacturing industry. It must adhere to the coordinated development of a modern service industry and advanced manufacturing industry.

-Continue to take innovative modern manufacturing as the leading role and vigorously promote the close follow-up of supporting current manufacturing services, maintain the appropriate proportion of manufacturing and service industries in the national economy, and promote the deeply integrated development of advanced manufacturing and modern service industries.

6.1. Unique contributions

1. The theoretical contribution is that the Xiongan New Era element should be added to the future study of Beijing-Tianjin-Hebei integration, namely, the academic study of Beijing-Tianjin-Hebei-Xiongan integration. Promoting the coordinated integration of the Beijing-Tianjin-Hebei and Xiongan will help high-quality economic development in Tianjin.

2. The practical implication is that Tianjin should fully combine its regional advantages and industrial advantages, rely on the port to focus on developing producer services, cultivate the research and development capacity of producer services, and further increase the proportion of tertiary industry in the economy. It is necessary to complete the upgrading and transformation of traditional industries as soon as possible and reshape them into an environmentally friendly modern industrial system. Taking the Beijing-Tianjin-Hebei integration as an opportunity, policymakers would vigorously enhance Tianjin’s ability to attract high-end manufacturing, build Tianjin into a research and development base, a production base, and a talent highland of advanced manufacturing in the North, and further optimise the industrial structure.

6.2. Future works and limitations

Limitations of this study include the facts are as follows:

1. The research method is simple. Only the grey relational model is used, which lacks the mutual verification between the research results of different methods, and the correctness of the conclusion lacks verification. The evaluation index is incomplete, affecting the accuracy of the results, and is not conducive to in-depth research on the mechanism of the coordinated development of the eco-environment and economy in Tianjin.

2. This paper studies the coordinated development level of the eco-environment and economy from the municipal level of Tianjin but lacks research on the coordinated development level of the eco-economy from the county level. As an important administrative unit, the county is the basic carrier for implementing economic development and environmental protection policies, and the data are more accurate.

3. The siphon effect of Xiongan New Area on talents and industries in Tianjin has not been included, which reduces an intellectual factor affecting the economic development of Tianjin, and may lead to the decline of Tianjin’s economic aggregate and low content of green economy.

In the future, the data on county economic development and environmental evolution should be collected using more than two modelling methods and combined with GIS visualisation and other new technologies so as to better explore the interaction and formation mechanism of complex systems in high-quality economic development.

Acknowledgments

The authors would like to acknowledge the financial support provided by the Tianjin middle and higher vocational education curriculum system (Grant No. KYQD12015), Labor Relations Management: Situational Simulation and Behavior Shaping (Grant NO. SKQD2021B-026), and research on collaborative education Platform construction of deep integration of artificial intelligence and vocational education (Grant NO. 2021WTSCX247), Research on School-enterprise Cooperation Development of Business Administration Teacher Competition Guidance Skills Course in Higher Vocational Colleges(12), Research on the theory and policy of cultural poverty alleviation in the intersection of two centuries (CXGY21-011).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the 广东省教育厅 [2021WTSCX247]; 汕尾职业技术学院 [SKQD2021B-026]; Tianjin University of Technology and Education [KYQD12015].

Notes on contributors

Xujun Zhang

Xujun Zhang is Lecturer in School of Management, Shanwei Institute of Technology , Shanwei.

Di Wang

Di Wang is an Associate Professor in the School of Management, Shanwei Institute of Technology , Shanwei.

Haiwei Peng

Haiwei Peng is the Deputy Director, Department of Organization and Personnel, Shanwei Institute of Technology, Shanwei

Dan Li

Dan li is an Office Clerk, Department of Organization and Personnel, Shanwei Institute of Technology, Shanwei.