1. Introduction
The sustainable development of the Yangtze River is crucial for the lives of the people and the development of the cities along it [
1,
2]. The Yangtze River has an abundance of natural resources, a superior geographical environment, and a strong shipping capacity. Its navigation mileage exceeds 2800 kilometers, accounting for 80% of Chinese inland river freight volume, and it is known as the Chinese “golden waterway.” The Yangtze River plays a critical role in China’s economic development. Over the years, the economies of the 11 provinces along the Yangtze River have developed rapidly and continuously, forming the Yangtze River Economic Belt. In 2018, the GDP of the Yangtze River Economic Belt was approximately US
$ 5.76 trillion, accounting for 45% of the whole country’s economy [
3]. The Yangtze River Economic Belt is one of the key regions for economic development in China. It has a high degree of urbanization, a large population density, and developed industry and agriculture [
4]. The quality of the water environment directly affects the ecological balance, economic development, and public health in the region [
5]. Therefore, the sustainable development of the Yangtze River’s water quality is particularly crucial.
With the development of the Yangtze River Economic Belt, human disturbance in the Yangtze basin has led to increased soil loss, and, furthermore, increased dam and river navigation has altered the pristine ecosystem and threatened local biodiversity [
6]. In addition, the Yangtze River receives a large amount of industrial waste water [
7], municipal sewage discharge, and sewage discharged from ships. The Yangtze River Valley Water Environment Monitoring Center monitors the water quality of the Yangtze River. It has detected many harmful organic chemicals in the water, and the content of nutrients, heavy metals, and dissolved organic carbon in the wastewater were shown to be increasing [
8]. Water pollution in the Yangtze River will indirectly affect the economic situation of the cities in the basin [
9]. According to relevant studies, the discharge of pollutants into the Yangtze River basin has increased year by year, reaching 35.32 billion tons in 2016. Nearly 20% of the river is inferior to the class III standard for surface water; moreover, the overall compliance rate of important functional areas of water is only 73.8% [
10].
At present, research on the pollution in the Yangtze River water environment is mainly focused on the effects of heavy metal, waste dumping, organic micropollutants, and dam construction [
11,
12,
13,
14,
15]. One study statistically analyzed the influences of runoff, estuarine areas, and adjacent sea areas on heavy metal pollution in the surface water of the Yangtze River estuary using the metal profile fluxes in floods and tides [
12]. In another study, the impact of waste dumping on the water environment of the Yangtze River was determined with statistical data and spatial patterns, and then the subsequent environmental impact on local and water ecosystems was evaluated [
13]. Furthermore, through a water diversion project, the content of organic micropollutants in the Yangtze River water source and their threat to water quality were investigated and analyzed [
14]. Another study discussed the influence of dam construction on the water environment by analyzing the effects of changes in sediment elements and contents on hydrological conditions [
15].
However, the impact of shipping on water pollution in the Yangtze River has rarely been studied. According to statistics, there are more than 80,000 transport vessels in the main stream of the Yangtze River, most of which are not equipped with oil–water separation devices or domestic sewage treatment devices. Millions of tons of oily sewage, tens of billions of tons of wastewater, and 750 million tons of domestic waste are discharged into the Yangtze River every year [
16]. In recent years, domestic garbage, domestic waste water, and oil produced during the transportation of ships have caused pollution to the Yangtze River’s water environment, which cannot be ignored.
The construction and development of the ecological environment monitoring website provided abundant data for environment research. Multivariate statistical analysis methods are considered reliable and effective tools to obtain valuable ecological environment information through a large amount of monitoring data. Various analysis methods of this kind have been used for water quality correlation analysis of rivers in the Yangtze River Basin. Cluster analysis can be used to assess the changes and trends in river water quality [
17]. Principal component analysis can screen out independent comprehensive factors related to water quality [
18]. Factor analysis is often used to identify key information to reflect the distribution of factors affecting water quality [
19]. Canonical correlation analysis (CCA) could establish the correlation between two groups of indicators as a whole and it capable of reflecting the overall correlation between two groups of variables. It has also been applied to a number of environmental quality assessments with agreeable results. CCA has been used in water quality correlation analysis of the Nervion–Ibaizabal estuary in the Basque country of Spain [
20], the Caspian sea in the southwest [
21], and the Kalen river in Iran [
22]. In this article, canonical correlation analysis (CCA) is employed to determine the relationship between shipping and related water environment in the Yangtze river.
In this study, the authors sought to (1) collect, collate, and screen the relevant historical data of shipping and the water environment of the Yangtze River; (2) use Spearman correlation analysis to identify the correlation between shipping and the water environment of the Yangtze River; and (3) use canonical correlation analysis (CCA) to determine the relationship between Yangtze River shipping and the related water environment. This study’s findings provide a reference for developing countermeasures to prevent shipping pollution as well as for the sustainable development of the Yangtze River. Such work will inform public policy and be useful for various stakeholders in discussions on the sustainable development of the Yangtze River.
3. Results and Discussions
3.1. Spearman Correlation Analysis
Spearman correlation analysis was performed to study the relationship between the development of shipping and the water environment of the Yangtze River.
Table 3 presents the results, which show that the freight volume (x
2) of the Yangtze River mainline is significantly correlated with wastewater discharge (y
1) and ammonia nitrogen concentration (y
2). The Pearson correlation coefficients were 0.874 and 0.880, respectively, with a
p-value of <0.001. Spearman correlation analysis was also used to test the inter-group correlation of the X group (x
1 and x
2) and Y group (y
1, y
2, y
3, y
4, and y
5). The correlation coefficient between the Yangtze River Shipping Prosperity Index (x
1) and mainline freight volume (x
2) was −0.661 with a
p-value of 0.027. The inter-group correlation between the Y group results can be found in
Table 4. The correlation coefficients of wastewater discharge (y
1) and ammonia nitrogen concentration (y
2) as well as potassium permanganate index (y
4) and petroleum category (y
5) were −0.775 and 0.804, respectively, with a significance level of 0.05. Although the correlation coefficients between the two variables were very high, Spearman correlation analysis can only reflect the correlation between single variables, and therefore, to reflect the overall correlation between the two groups of variables, performing CCA on the two groups of variables is necessary.
3.2. Canonical Correlation Analysis
In the CCA, two pairs of canonical correlation variables (
U1, V1 and
U2, V2) were extracted from the two groups of data (X and Y groups), as shown in
Table 5. The canonical correlation coefficient of the first pair of canonical correlation variables (
U1 and
V1) was 0.979 at a significance level 0.05, whereas that of the second pair (
U1 and
V1) was 0.55 without a significance level. This meant that the first canonical correlation coefficient was reliable, whereas the second was meaningless. Thus, the first pair of canonical correlation variables (
U1 and
V1) was used in the subsequent analysis.
In addition, the canonical correlation coefficient of the first pair of canonical correlation variables (0.979) was greater than all the correlation coefficients obtained by the Spearman correlation analysis, indicating that the CCA results could better represent the relationship between the river’s shipping and water environment than could the Spearman correlation analysis. This means that the influence of shipping on the water environment is not simply on individual indicators but on the overall water environment. Therefore, the correlation relationship between the shipping and water environment of the Yangtze River could be represented by the first pair of canonical variables
U1 and
V1.
Table 6 lists the standardized canonical correlation coefficients, which are summarized as the canonical correlation model in Equation (8).
According to Equation (8), the canonical variable U1 is dominated by Yangtze River mainline freight volume (x2) with a coefficient of 0.847. The canonical variable V1 is dominated by Yangtze River wastewater discharge quantity (y1) and petroleum (y5), with coefficients of 0.656 and 0.526, respectively. This canonical correlation model indicates that the Yangtze River mainline freight volume has a significant impact on the wastewater discharge quantity and petroleum in the Yangtze River’s water environment.
According to the model’s result, this study determined that the Yangtze River mainline freight volume (x1) has a significant correlation with the wastewater discharge quantity (y1) and petroleum (y5).
For the canonical variable V1, the coefficients of ammonia nitrogen concentration (y2), biochemical oxygen demand (y3), and potassium permanganate index (y4) were 0.382, −0.107, and −0.222, respectively. The negative values of the coefficients indicate that these water pollution indicators in the Yangtze River are gradually decreasing.
3.3. Canonical Structural Analysis
A canonical structural analysis was employed to measure the correlation and direction of the original variables (X and Y) and the canonical variable (
U1 and
V1) using canonical loading and cross loading. Canonical loading is an indicator that reflects the correlation between the original variables and its own canonical variables (e.g.,
U1 with x
1 and x
2). The greater the absolute value of canonical loading, the more the canonical variable interprets its original variable. Cross-loading is the correlation index of the original variable with another canonical variable (e.g.,
U1 with y
1, y
2, y
3, y
4, and y
5).
Table 7 presents the canonical structural analysis results.
According to the results in
Table 7, the canonical loading of the Yangtze River mainline freight volume (x
2) and the canonical variable
U1 were as high as 0.98. This means that mainline freight volume can represent the Yangtze River’s shipping development very well. Furthermore, the cross-loading description of the mainline freight volume (x
2) and the canonical variable
V1 was 0.967, indicating that mainline freight volume greatly affects the Yangtze River’s water environment.
3.4. Discussions
The results of Spearman correlation analysis and CCA revealed that the canonical correlation coefficient derived from the CCA was greater than the correlation coefficients derived from the Spearman correlation analysis. This indicated that the CCA could better reflect the relationship between river shipping and the water environment than could the Spearman correlation analysis. According to the CCA result, mainline freight volume has a significant impact on the wastewater discharge quantity and petroleum in the Yangtze River’s water environment. It also shows that freight rises with the continuous development of Yangtze river shipping. This fact further reflects that Yangtze river shipping quantity, shipping tonnage and the growth of crew numbers have led to an increase in ship sewage wastewater emissions and ship oil spills. Pollution accidents resulting from ships have increased gradually in recent years. This has caused a serious impact on the Yangtze River water environment, which may threaten the sustainable development of the Yangtze River Economic Belt. In addition, in the canonical correlation model, it can also be found that ammonia nitrogen concentration, biochemical oxygen demand and potassium permanganate index show negative correlation coefficients, indicating that these water pollution indicators in the Yangtze River Basin decrease gradually. According to China’s surface water environmental quality standard GB3838-2002, ammonia nitrogen concentration, biochemical oxygen demand, and permanganate index are considered the basic indicators for detecting surface water quality. Therefore, the reduction of the values of these indicators shows that the water quality in the Yangtze River has been improving and further indicates the water quality management in the Yangtze River Basin can be considered successful in recent years. Unfortunately, there are still many pollution problems left in the Yangtze River water environment such as wastewater discharge and petroleum pollution, which require urgent solutions. Additionally, there are still many indicators in the Yangtze River waters that have exceeded standards, such as total phosphorus and chemical oxygen demand, which could not be controlled in the short term. Therefore, the prevention and control of water pollution in the Yangtze River Basin needs a long-term strategy based on continuous data analyses.