5.2. Indicator of Description
After averaging the statistics of the actual data of 30 province-level regions in China (Beijing, Tianjin, HeBei, LiaoNing, ShangHai, JiangSu, Zhejiang, Fujian, Shandong, Guangdong, Hainan, Shanxi, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, Hunan, Neimenggu, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Shanxi, Gansu, Qinghai, Ningxia, Xinjiang), the descriptive statistical analysis results of all variables are obtained, as shown in
Table 4. Variables with less dispersion include VANWD, TVNPWD, SDXE%IGDP, NOXE%IGDP, SDE%IGDP, and IEGIEGI, of which standard deviations are all less than 10. The variable with the largest degree of dispersion is IIWT, which reaches 245,996.40. However, in order to reasonably evaluate the magnitude of the fluctuations of variables, it is necessary to resort to the coefficient of variation, which incorporates the level of the variable into the measurement of variable variation. As shown in
Table 4, the variables with the highest fluctuations are SVHW, GHW, and DVGISW, and their fluctuations between variable values are the greater. The least fluctuating variable is RUST, and its fluctuation is relatively stable. At the same time, from the perspective of the change of the overall average, most of the pressure indicators of environmentally sustainable development in 2016–2018 are gradually declining, and the state indicators of environmentally sustainable development are getting better, but the response indicators of environmentally sustainable development are uncertain.
5.3. Analysis of the Results
We separately extract the principal components of the pressure indicators of Environmentally Sustainable Development, the state indicators of Environmentally Sustainable Development, and the response indicators of Environmentally Sustainable Development. The original data are standardized and the correlation coefficient matrix is obtained. Bartlett’s test and Kaiser–Meyer–Olkin (KMO) were used for the validity of the scale [
25,
26]. The sphericity values of Bartlett’s test are 1180.496, 349.502, 273.735, and all significance are 0.000, so it can be considered that the correlation coefficient matrix is not the identity matrix [
27]. The value of KMO statistics is between (0–1). 0 indicates that there is no relationship between the original variables, and 1 indicates that there is an important relationship [
24]. The KMO test values in this paper are all greater than 0.6, so the data are suitable for factor analysis, as shown in
Table 5.
Subsequently, this paper will find the characteristic root and factor loading matrix. Rotating the data to maximize variance, in terms of the principle that the eigenvalue is greater than 1, the principal component analysis of environmental pressure, environmental state and environmental governance extracts three principal components F1, F2, and F3 respectively. If the cumulative contribution rate of the extracted factors reaches more than 80%, it is believed that the newly extracted principal component can basically reflect most of the information of the original indicator data, that is, the analysis obtained from the extracted principal component of the original variable is effective, and it is enough to describe the environmental pressure, state, and response. See
Figure 1.
It can be seen from the rotated factor loading matrix that the component 1 of the pressure of Environmentally Sustainable Development is mainly determined by the four indicators of TVWD, DVCODWD, VANWD, and TVNPWD, which represents the pressure of wastewater discharge on the environment and can be summarized as the factors of the water environment pressure. Component 2 is mainly determined by the three indicators of GGISW, GHW, and TGW, which represent the pressure of solid waste on the environment and can be summarized as the factors of solid waste pressure. Component 3 is mainly determined by three indicators: SDE%IGDP, NOXE%IGDP, and SDXE%IGDP, which means the pressure produced by each GDP on atmospheric environment can be summarized as the factors of atmospheric environmental pressure. In component 1 of the state of environmentally sustainable development, the three indicators of WRPC, VSWR, and VGR account for a large proportion, which can be summarized as factors of water environment state. Component 2 is mainly determined by two indicators: GGISW and GHW, which can be summarized as factors of solid waste state. Component 3 is mainly determined by two indicators: RNAAPLC and AACIPM
10, which can be summarized as the factors of atmospheric environmental state. Component 1 of the response of environmentally sustainable development is mainly determined by four indicators: TVSD, IIWT, RUST and NSWQSP, which represent the treatment of sewage and wastewater and can be summarized as factors of water environment treatment. Component 2 is mainly composed of IWGI%IGDP and IEGIEGI, which represent the government’s emphasis on atmospheric environmental governance and can be summarized as atmospheric environmental governance factor. Component 3 is mainly determined by the CUVGISW and DVGISW, which represent the utilization and disposal capacity of solid waste and can be summarized as factors of solid waste response. As shown in
Table 6.
5.4. Discussions
According to the state variable weight vector calculation Formulas (3), (4), and (6), and the variable weight vector calculation Formulas (4) and (7), as well as the environmental data of the 30 provinces and cities in China from 2016 to 2018, the principal components were extracted. The average variable weight vectors are obtained respectively, as shown in
Table 7 below.
In
Table 7, the maximum weight of the pressure of environmental sustainability criterion layer is 0.232 in Shanghai, and the lowest is 0.053 in Shandong. The difference between the variable weights of the two is relatively large. A certain item at the criterion level, such as the environmental sustainability discovery status project, is more important, so the variable weight is more important than other provinces and cities. In terms of State of environmental sustainability, Guangdong’s power to change rights is greater than that of other provinces and cities, which means that Guangzhou has invested more energy in this aspect and has given more attention. In terms of response to environmental sustainability, Guangdong’s variable weight is significantly lower than Shandong, and there is a large difference between the two. This phenomenon shows that, to some extent, Shandong pays more attention to response to environmental sustainability.
Similarly, Shandong has a large difference in the weights of the three criterion levels. Shandong’s weight in response to environmental sustainability is eight times that of the other two criterion levels and is more active in response. Except for several provinces and cities such as Qinghai and Guizhou, most provinces and cities place variable weights on Response to environmental sustainability. Regions such as the Yunnan-Guizhou Plateau have given the State of environmental sustainability a greater proportion due to factors such as fragile environment and unstable ecological development. Among the 30 provinces and cities in China, Shanghai has a more even distribution of variable weights. The three variable weights are 0.232, 0.379, and 0.389, which are inseparable from its geographic location and economic development. Shanghai’s economic development is fast, and the pressure for sustainable environmental development is not small. After a series of measures such as environmental remediation, Shanghai’s environmental sustainability has been improved. Therefore, the Shanghai government aims to better maintain the environment.
5.5. Sustainable Capacity and Balanced Distribution
According to the above formulas and steps, we average and analyze the results of three years’ constant contingency weights of 30 province-level regions in China.
After averaging the results, comparing to the scores of constant weight results, the scores of variable weight results reduced with different degrees, which shows that some values of state factors are “unbalanced” in both index layer and criterion layer. Environmental assessment includes the pressure of atmospheric environmental, the pressure of water environmental, the state of water environmental and environmental response, of which various internal sub-responsibilities are “disharmonious”. Therefore, they have received a certain degree of “penalty”, which leads to the comprehensive evaluation value of variable weight being low. If being “penalized”, it means some matters in a certain area are not handled well, which makes the composite scores drop China’s provinces of Shandong, Yunnan, and Fujian rank first, third, and fourth, respectively, in both the scores of constant weight and variable weight, which indicates that these provinces are not changed after varied weight processing, probably because the better natural environment is, the relatively higher score is, especially for Yunnan province. Yunnan Province is rich in natural resources. It is known as the “vegetable kingdom”, “animal kingdom”, “non-ferrous metal kingdom”, and “hometown of medicinal materials”, and has gained the reputation of “the south of colorful clouds”. Because the weather in Yunnan province is mild, the utilization rate of coal is lower than that of cold northern cities, so the air is fresh and the environment is good. However, Dianchi Lake in Yunnan province is slightly polluted, and the main pollution indicators are demand volume of chemical oxygen and total phosphorus. Among the 10 monitored water quality points, Grade IV accounts for 60.0% (China divides water quality into five categories. Grade I: good water quality. Groundwa-ter only needs to be disinfected, and surface water can be used for drinking after simple purification (such as filtration) and disinfection. Grade II: the water quality is slightly polluted. After conventional purification treatment (such as flocculation, sedimentation, filtration, disinfection, etc.), the water quality can reach to daily drinking. Grade III: suita-ble for the secondary protection area of the centralized drinking water source, general fish protection area and swimming area. Grade V: suitable for general industrial protection areas and recreational water areas that are not in direct contact with the human body. Grade IV: suitable for agricultural water areas and general landscape requirements. Water bodies that exceed the five types of water quality standards basically have no use function.), Grade V accounts for 40.0%, and there are no Grade I, II, III, or inferior Grade V. Through the treatment, comparing to those indicators of 2017, the proportion of water quality points of Grade IV increased by 60.0%, and the percentage of water quality points of inferior Grade V decreased by 60.0%. The water quality of Shandong province has continued to improve for 16 consecutive years, with a water quality ratio of 46.3%, and the air has continued to improve for six years (data source: Shandong Province 2018 Environmental Bulletin). A good natural ecological environment and favorable governance have laid the foundation for the above provinces.
The rankings of Henan province, Guangxi province, and Anhui province are in a below average level in the constant weight results, but the results of variable weight integrated assessment method rank second, fifth, and seventh respectively, of which the scores are higher than other provinces and cities. The advantages of these provinces’ natural environment are not prominent. The Henan Provincial Environmental Bulletin in 2019 showed that the national ecological environment index (EI, environment index.) (China divides water quality into five categories. Grade I: good water quality. Groundwater only needs to be disinfected, and surface water can be used for drinking after simple purification (such as filtration) and disinfection. Grade II: the water quality is slightly polluted. After conventional purification treatment (such as flocculation, sedimentation, filtration, disinfection, etc.), the water quality can reach to daily drinking. Grade III: suitable for the secondary protection area of the centralized drinking water source, general fish protection area and swimming area. Grade V: suitable for general industrial protection areas and recreational water areas that are not in direct contact with the human body. Grade IV: suitable for agricultural water areas and general landscape requirements. Water bodies that exceed the five types of water quality standards basically have no use function.) value was 51.3, and the ecological quality was not good. The count area with excellent and good ecological quality accounted for 44.7% of the total land area, average -quality area accounted for 22.7%, and fair and poor accounted for 32.6%. However, Henan province payed attention to environmental response, and served the overall situation. In accordance with the provincial deployment of environmental pollution prevention and control, it completed 428 sets of the emergency control and the automatic monitoring facilities of exhaust gas of peak-shift production enterprises, and 714 sets of construction and networking of total nitrogen automatic monitoring facilities in 2018. At the same time, it guided and urged relevant cities and counties to complete the installation pilot tasks of VOCS online monitoring facilities and video monitoring facilities. Combining the needs of the accomplishment of tough tasks and the management and control of weather in the day of heavy pollution, Henan province actively monitored pollutant emissions and exceeding standards of enterprises, regularly prepared various special monitoring reports, and put forward relevant countermeasures and suggestions, which provided effective data support for the implementation of the whole province’s tough task.
Table 8 shows the ranking of score of constant weight and variable weight of 30 provincial-level regions in China in 2016–2018. In the first column of
Table 8, the following notations are defined. ASCWA: average score of constant weight; RCW: ranking of constant weight; ASVW: average score of variable weight; RVW: ranking of variable weight. It can be seen from the table that, compared with the ranking of constant weight, the ranking of variable weight of each province has been changed, indicating that the contingent analytic hierarchy process uses real data to correct the permanent power score and obtains a more realistic variable ranking. This ranking of variable weight shows that Beijing (RCW is 4, RVW is 15), Fujian (RCW is 3, RVW is 4), Guangdong (RCW is 2, RVW is 6), and Jiangsu (RCW is 4, RVW is 15) are all lower than the Ranking of constant weight, especially Tianjin, whose score of constant weight ranked first, but the variable weight score ranked around 20th. Economic development may be achieved at the cost of the ecological environment, but economic development cannot be at the expense of the ecological environment, and environmentally sustainable development is limited by the environmental carrying capacity.