The safety of water resources and the ecological environment in the Asian region is facing severe challenges with the rapid socio-economic development [1
]. There are two main reasons behind this phenomenon. The first is that a large amount of pollutants has been discharged into rivers and lakes, causing the deterioration of regional water quality [3
]. The other point is that regional water use had increased with economic development and population growth, which results in water resources waste and huge water supply pressure [5
]. Shandong province, located in north-central China, has a large population and is one of the regions with serious water shortages in China. The domestic and industrial water use in Shandong has increased rapidly in recent years, but the efficiency of water resources utilization is not high. In addition, water pollution in Shandong is also relatively serious. The eutrophication of rivers and lakes, which is mainly caused by the discharge of industrial and domestic wastewater, is more prominent. At present, the discharge of industrial wastewater in Shandong is ranked third, and the discharge of domestic wastewater is also ranked third in China. However, the number of wastewater treatment facilities in Shandong is ranked 16th in China, far below the ranking of industrial and domestic wastewater emissions. It can be seen that Shandong belongs to a region with serious water pollution in China. Existing research shows that if this trend continues, industrial, domestic water pollution will restrict the water security and sustainable socio-economic development of Shandong in the future. Accordingly, the investigation of industrial, domestic water use and pollution management is becoming increasingly important for promoting water security and sustainable socio-economic development in Shandong.
Over the past few decades, the relationship between environment and economy has concerned relevant researchers, to strengthen pollution emissions control and management [7
]. Some researchers have pointed out that the environmental pollution increased faster than economic growth during the early stages of economic development, and then decreased at higher economic development levels [10
]. This is the famous environmental Kuznets curve (EKC), with an inverted-U-shaped nexus between indicators. The EKC hypothesis was first applied to examine the nexus between environment pollution and economic development in the United States [12
]. Later, many empirical studies about environmental pollution–economic development nexus have been carried out using EKC. Results showed that an inverted-U-shaped relationship has occurred between environment pollution and economic development in most developed countries [13
]. Lee et al. [17
] revisited a water pollution EKC, they found that the existence of an inverted-U-shaped relationship between biological oxygen demand (BOD) emissions and GDP per capita in Europe and America. Fodha and Zaghdoud [18
] found an inverted-U-shaped relationship between SO2
emissions and GDP per capita using time series data.
In China, similar studies have revealed the existence of a relationship between environmental pollution and economic development [19
]. Gao et al. [21
] established the EKC model to study the relationship between industrial wastewater, SO2
emissions and GDP per capita in Jiangsu, China. Peng et al. [22
] used EKC to study the trend of environmental indicators such as industrial wastewater and industrial COD emissions in Shanghai, plotted against economic development. Liu et al. [23
] analyzed the relationship between industrial chemical oxygen demand (COD), NH3
-N, wastewater emissions and per capita GDP in Zaozhuang, Shandong based on the EKC hypothesis. Zhang and Wang [24
] used the EKC model to study the relationship between water pollution (industrial and domestic wastewater discharge) and economic development in Shandong.
Overall, most studies using local pollutants as indicators of environmental degradation have found empirical support for the existence of EKC relationships between income and environment [25
]. The results of the EKC study are highly dependent on the type of contaminant selected, and EKC might work only for some specific air and water pollutants [26
]. Regional pollutants are more suitable for EKC analysis than global pollutants; they are easy to spatially separate and can be controlled at relatively low cost to economic growth [25
]. People need better environmental quality, such as clean water and air, when incomes grow. To meet people’s life needs, the government will take some measures, such as strengthening environmental laws and investing clean technologies. Therefore, as incomes increase, local specific pollutant emissions begin to decrease.
The pressures of regional water use and supply will be intensified with rapid socio-economic development [27
]. Meanwhile, the inefficient utilization and irrational allocation of water resources may generate a series of adverse effects on the regional water security and sustainable socio-economic development [28
]. Accordingly, systematic analysis and quantitative study of the water use and pollution control becomes particularly important for regional sustainable water management.
However, a few researchers who have qualitatively analyzed the link between water use and economic development lacked quantitative research [29
]. In economics, the Lorenz curve is used to investigate the degree of inequality in wealth distribution, which is measured quantitatively using the Gini index [33
]. This theory has been widely used in various fields. Liu et al. [34
] used the Gini coefficient to evaluate the climate of human settlements. Liu et al. [35
] applied the Gini coefficient to study the spatial distribution of grain in China. Delbosc et al. [36
] used the Lorenz curve to assess the fairness of public transportation. Sadras et al. [37
] used the Lorenz curves and Gini coefficients to analyze the magnitude of grain yield variation at the paddock scale. Groves-Kirkby et al. [38
] introduced the Lorenz curve and Gini coefficient to investigate and quantify seasonal variability in environmental radon gas concentration. Jacobson et al. [39
] pointed out that the Lorenz method, which is widely employed by economists to analyze income distribution, is largely unused in energy analysis, so they used this method to analyze the allocation of energy. Later, using the concept of the Gini coefficient and Lorenz curve, some scholars analyzed the allocation and equity of energy consumption in some developing and developed countries [40
The Lorenz curves and Gini coefficients were also introduced gradually into the research on the water resources utilization and socio-economic development nexus [42
]. Gunasekara et al. [46
] examined the relationship between water resource abundance and social development using Lorenz curves, and the results implied that differences existed in the effects of different water resource types on socio-economic development. Hanjra et al. [47
] investigated linkages and complementarities between agricultural water and socioeconomic development using the Gini index. Meanwhile, similar research has also been carried out in China. Wu et al. [48
] applied the Gini coefficient to study the distribution of water resources and secondary industry output, as well as the distribution of water resources and population in Handan, China. Ma et al. [49
] mapped the Lorenz curve of water resources and population, as well as water resources and cultivated land resources, and calculated the Gini coefficient to analyze the degree of spatial matching in water resources. Wei et al. [50
] used the Lorenz curve and the Gini coefficient to analyze the allocation between water resources and population, as well as water resources and secondary industry output, respectively.
In summary, the Lorenz curve and Gini index are well suited to investigate the allocation and equity between water resources utilization and socio-economic development, which provides a valuable approach to qualitatively and quantitatively study the relationship between the two. They can be applied not just to income but to any quantity that can be cumulated across a population [36
]. They can be applied in a range of disciplines, from studies of biodiversity, the allocation of water use and energy consumption to business modeling and even within transport [51
Overall, existing research has either investigated water pollution control or study water use allocation, but few studies have considered combining these methods to conduct integrated research. This paper tries to draw on the advantages of different methods to investigate water pollution control and water use allocation in Shandong. The coordination between industrial water pollution and socio-economic development, as well as the coordination between domestic water pollution and socio-economic development, was investigated based on the optimal EKC model. The allocation and equity of industrial water use and secondary industry output, as well as domestic water use and urban population in different years, were evaluated qualitatively and quantitatively according to the Lorenz curve and the Gini index. In addition, the control of wastewater emissions and the governance of typical pollutants (NH3-N and COD) in wastewater were analyzed quantitatively, relying on the elasticity coefficient method in the context of the Five-Year Plan for Shandong.
Comprehensive analysis of industrial and domestic water use and pollution management will provide theoretical support for the formulation of relevant water environment policies in the future, and further promote water security and sustainable socio-economic development in Shandong. Meanwhile, we hope this study can provide theoretical reference for some regions with similar water resources problems, to optimize water pollution control policies and measures and increase in environmental investment. Additionally, the conjunctive use of the aforementioned three methods provides an approach to investigate the integrated management of water use and water pollution control from multiple angles.
To effectively conduct the integrated planning and management of regional water resources and the social economy, in this paper the optimal EKC models were established based on comparison in the five goodness-of-fit indexes to analyze the water pollution–socio-economic development nexus. The Lorenz curve and the Gini index were applied to quantitatively study the allocation and equity of water use and socio-economic development. Additionally, the control of wastewater emissions and the governance of COD and NH3-N in wastewater were investigated based on the elasticity coefficient model in the context of the Five-Year Plan for Shandong. Accordingly, specific suggestions were proposed according to the current situation between water use and pollutant emissions in Shandong. The conjunctive use of the aforementioned three methods can be valuable for investigating industrial and domestic water use and pollution management from multiple angles.
The EKC of industrial water pollution (wastewater, COD, NH3-N emissions) in the period 2003–2017 showed an inverted-U-shaped, a linear decrease and a binding curve on the left side of the U-shaped curve, respectively. Overall, a coordinated relationship between industrial water pollution and socio-economic development has basically been realized in Shandong. The EKC of domestic water pollution (wastewater, COD, NH3-N emissions) from 2003 to 2017 showed an increasing tendency, a U-shaped curve and a binding curve of the right side of U-shaped curve, respectively. Collectively, the coordinated relationship between domestic water pollution and socio-economic development still has not been achieved. Meanwhile, we found that the type of EKC differed across the type of water pollutant. At present, domestic water pollution in Shandong has become more serious, compared to industrial water pollution. On the one hand, Shandong should pay attention to the treatment of domestic pollutants in the future. On the other hand, Shandong should draw on similar research experiences and lessons from other countries or regions to implement some control and management measures, such as increasing governance for domestic pollutants, investing more funds to build municipal sewage treatment plants, and optimizing wastewater treatment equipment.
The comparison of the Gini indexes in 2003 and 2017 indicated that there was relatively good allocation of water use and socio-economic development in Shandong in 2017. However, some coastal cities (Rizhao, Weihai, Qingdao, Weifang and Yanta) still displayed relatively irrational allocation in industrial and domestic water use. Accordingly, in terms of domestic water use, the supportability of water supply can be increased and the urban population growth rate should be controlled in Jinan, Rizhao, Weihai, Qingdao, Weifang and Yantai. In terms of industrial water use, non-coastal cities of Shandong can draw on experiences in industrial development of coastal cities to improve the production technology and the rate of reclaimed water utilization for industrial enterprises.
The condition of pollution emissions control from 2013 to 2017 was analyzed quantitatively using the elasticity coefficient theory. Relatively good control occurred in industrial wastewater emissions. Although the growth rate of domestic wastewater emissions had decreased, it was still greater than the growth rate of domestic water use. The governance of COD and NH3-N in wastewater has achieved relatively good results over the past few years. In general, the management of domestic wastewater emissions control in Shandong needs to be further improved.
In summary, Shandong should draw on relevant experiences and lessons to change growth patterns and socio-economic behaviors, including institutional design, formulation and implementation of environmental policy, and strengthening of public environmental awareness. These play an important role in achieving water security and sustainable development of the social economy in Shandong.