Qualitative and quantitative analysis of the relationship between water pollution and economic growth: a case study in Nansi Lake catchment, China

Investigating the dynamic decoupling relationship between regional social economy and lake water environment: The application of DPSIR-Extended Tapio decoupling model

The water environmental problems associated with rapid socioeconomic growth have drawn widespread attention from the government and the public. Revealing the decoupling mechanism between the social economy and lake water environment has become an important breakthrough point to seek the pathways of sustainable economic development. To investigate the decoupling process of the social economy‒lake water environmental system, this study proposes a comprehensive evaluation model, which integrates the Driving force-Pressure-State-Impact-Response (DPSIR) model, projection pursuit method, and Tapio decoupling model; and then applies it to the case study of Hefei City and Lake Chaohu in China in 2021-2035. Three typical scenarios of current, social economy, and water environment are designed and simulated using the DPSIR model to evaluate the dynamic decoupling relationships under various development patterns. We found that the DPSIR indexes had a fluctuating upward trend from 2009 to 2020, with a synchronous improvement trend of the social economy and lake water environment. Meanwhile, the Tapio decoupling analysis showed that the decoupling relationships between socioeconomic driver forces, response strategies and the status of lake water environment was mostly strongly decoupled and weakly decoupled during 2009-2020. However, there was still an inconsistency between the improvement rate of the lake water environment and the increase rate of the response strategies. During the 2021-2035 simulation period, the DPSIR indexes of all scenarios depicts an overall increasing trend. The decoupling states of S&I-D&P and S&I-R generally tend to be consistent under three regulation scenarios. Among them, the water environment scenario outperforms other scenarios, and the social economy scenario performs worst. Overall, the decoupling of the social economy and lake water environment can attribute to both the transformation of socioeconomic development patterns and the increase of water environmental protection efforts.

Research on the Evaluation and Spatial Characteristics of China's Provincial Socioeconomic Development and Pollution Control Based on the Lotka-Volterra Model

AIMS

To evaluate the degree of mutualism between socioeconomic development and industrial and domestic pollution in provinces of China and to analyze the differences in spatial characteristics between their regions.

METHODS

This study used the HDI to measure socioeconomic development and the Lotka-Volterra model to group and estimate the force-on and mutualism degree indexes of industrial and domestic pollution and socioeconomic development in 31 provinces of China, which were then used to them. Then, the study calculated the global and local Moran's I under different space weights matrices to analyze their spatial autocorrelation and heterogeneity.

RESULTS

The research showed that in 2016-2020, compared with 2011-2015, the number of provinces where socioeconomic development and industrial pollution control mutually promoted each other was approximately the same, while the number of provinces that promoted each other's effectiveness with domestic pollution control was reduced. There were many provinces with industrial pollution ranked in the S-level, while most provinces placed a different emphasis on industrial and domestic pollution control. The rank in China tended to be spatially balanced in 2016-2020. There was a negative spatial autocorrelation between the ranks of most provinces and neighboring provinces in 2011-2020. The ranks of some eastern provinces showed a phenomenon of a high-high agglomeration, while the ranks of provinces in the western region were dominated by a high-low agglomeration.

Spatiotemporal variations and bioaccumulation of per- and polyfluoroalkyl substances and oxidative conversion of precursors in shallow lake water

Per- and polyfluoroalkyl substances (PFAS) in water and fish from Nansi Lake, Chian and in inflowing tributaries and nearby sewage treatment plants (STPs) were determined to evaluate their distribution and bioaccumulation. The potential precursors of perfluoroalkyl acid (PFAA) present in the water were converted via hydroxyl radical oxidation. Over 3 seasons, the average concentration ranges of the 15 PFAA (∑₁₅PFAA) concentrations in Nansi Lake, inflowing tributaries, and STPs were 22.8-70.3, 19.5-43.5, and 84.1-129 ng L^-1, respectively. Perfluorooctanoic acid, perfluorooctane sulfonate (PFOS), and short-chain PFAA (perfluorocarboxlate acid <8, perfluorosulfonate acids <6) were present in high concentrations in the lake and tributaries. PFAA concentration was the lowest during the wet season and the highest during the dry season. Moreover, PFAA precursors were converted to perfluorocarboxlate acid. The concentration of C8-based precursors was higher than that of the C6-based precursors in the lake and tributaries. The concentration of PFAA in the fish liver was higher than that in fish muscles, and PFOS was the dominant chemical present in fish. Potential risk assessment based on Environment Quality Standard revealed heavy PFOS contamination in the fish. Thus, the water of Nansi Lake was heavily polluted by PFAS.

What are the determinants of wastewater discharge reduction in China? Decomposition analysis by LMDI

Wastewater discharge reduction (WDR) is a key breakthrough point for China's environmental protection. Based on China's 30 provincial data from 2011 to 2017, this paper applied the logarithmic mean Divisia index (LMDI) method to clarify the determinants of WDR at national, regional, and provincial levels. Except for wastewater discharge factor, economic development, and total population, four innovative factors, total water application intensity, water environment cost, water treatment industry development level, and drainage infrastructure investment scale were first proposed in this study. The results indicated that from 2011 to 2017, at the national level, total water application intensity and water treatment industry development level were dominant contributors to WDR, while other factors all inhibited WDR. At the regional level, the results of wastewater discharge factor, economic development, and water environment cost were similar to the national level. The drainage infrastructure investment scale had a positive effect on WDR in Northeast and South China while having a negative effect on other regions. And except for Northeast China, the water treatment industry development level promoted WRD, while the total population inhibited WDR. Finally, the determinants of WDR at the provincial level were investigated. On this basis, targeted corresponding policies were provided in this paper.

Spatiotemporal Heterogeneity and Driving Factors of Water Resource and Environment Carrying Capacity under High-Quality Economic Development in China

Rapid economic growth and social development in China have led to serious water pollution problems and water resource shortages, limiting the sustainable development that could support both the socio-economy and water resources carrying capacity (WRECC). However, the spatial heterogeneity and evolutionary characteristics of the coordination between the WRECC and economic development have not been adequately explored in China. In this study, we developed the support and pressure indicators of China's 30 provinces and then analyzed the spatiotemporal distribution and evolution characteristics of their WRECC by using the geographically and temporally weighted regression (GTWR) model. The main findings are shown in the following: (i) From a temporal perspective, there has been an overall upward trend in the WRECC to support human activities; however, the WRECC level is not high. Approximately 63.7% of provinces remain in an overloaded state, indicating that the support indicator of most provinces is smaller than the pressure indicator imposed by human social activities. (ii) There are significant spatial differences in the WRECC indicators across provinces. Provinces with low-level WRECCs are concentrated in central China but decrease significantly from the country's borders to its center. Eastern regions have a medium-level of WRECC with the greatest degree of regional difference, while western regions have a high-level of WRECC with the smallest degree of regional difference. The variation of WRECC is attributed to within-group differences in the three geographical regions in China. (iii) The factors that significantly impact the WRECC include population density, gross domestic product (GDP), temperature, urbanization, the added value of tertiary industry within the GDP, and R&D expenditures. GDP and R&D expenditures positively impact the WRECC, while the other four factors have different influences on the WRECC. (iv) The spatial distributions of driving factors show significant aggregation characteristics, with decreasing trends from the eastern to western regions and from the southern to northern regions. These findings present a comprehensive understanding of the current WRECC in China's provinces which can be used as a reference for realizing environmentally sustainable water development strategies under high-quality economic development.

Association between Lake Sediment Nutrients and Climate Change, Human Activities: A Time-Series Analysis

Climate change and human activities are closely linked with the nutrient accumulation in sediments, but the role of influence factors and the driving mechanisms are unclear. Here, by using the generalized additive model (GAM), we investigated the contributions and driving mechanisms of climate change and human activities on TON, TN, and TP accumulation in sediments of typical lakes in the Huai River basin (Nansi Lake and Hongze Lake) from 1988 to 2018. The impacts of factors, such as air temperature (AT), real GDP per capita (GDP), population density (PD), crop sown area (CSA), artificial impervious area (AIA), and domestic sewage discharge (DSD) were considered in this study. The results of the multivariate GAM showed that the sediment variables were significantly affected by climate change in Nansi Lake, but not in Hongze Lake. AT and DSD contributed the most to the variation of sediment TOC in Nansi Lake, while the most critical factors affecting TN and TP were AT, PD and DSD. PD and CSA showed strong ability to explain the change of TOC in Hongze Lake, while CSA and DSD showed strong ability to explain the variations of TN and TP. The results show that the selected optimal multivariate GAM can well quantify the effects of climate change and human activities on nutrient enrichment in lake sediments. Effective recommendations are provided for decision-makers in developing water quality management plans to prevent eutrophication outbreaks in lake waters by targeting and controlling key factors.

Assessment of the hydrochemistry, water quality, and human health risk of groundwater in the northwest of Nansi Lake Catchment, north China

In this study, the formation mechanism and water quality of groundwater in the northwest of Nansi Lake Catchment (NNLC) were analyzed through mathematical statistics, hydrochemical analysis and entropy weighted water quality index (EWQI), and the human health risk of nitrate was also evaluated. To this end, 89 wells in the NNLC were sampled, and the groundwater samples were divided into three groups (I, II, and III) according to cluster analysis results and spatial distribution. The main results are as follows: Topographically, Groups I, II, and III correspond to the alluvial plains, apron plain, and low hills and its front margin, respectively. According to the Piper diagram, the hydrochemical types of Groups I and II groundwater are Na-SO₄·Cl and Ca·Mg-HCO₃, respectively, and that of Group III is more concentrated, mostly corresponding to the Ca-HCO₃ type. Hydrochemical analysis indicated that the development of groundwater hydrochemistry is mainly attributable to water-rock interactions, with the primary process being the dissolution of minerals such as calcite, dolomite, gypsum, and albite. Evaporation exhibited an increasing trend from the northeast to the southwest. Groups I and III presented obvious effects of human activities, with Group I showing sulfate pollution and Group III mainly showing nitrate pollution. Analysis of the characteristics and causes of the groundwater hydrochemistry revealed the proposed approach has excellent performance for classification in areas with complex hydrogeological conditions. The results of EWQI showed that the overall water quality was good, following the order Group III > Group II > Group I. The overall human health risk of nitrate in groundwater was low, but the risk was slightly higher for children than for adults. Therefore, the effects of nitrate contamination should be considered when exploiting hilly and peri-urban groundwater for drinking water.

Lake ecosystem health assessment using a novel hybrid decision-making framework in the Nam Co, Qinghai-Tibet Plateau

Lake health assessment (LHA), a powerful tool for lake ecological protection, provides the foundation for sustainable water environment management. However, existing methods have not yet considered the effects of fuzziness and randomness on LHA. In addition, most of the current studies on LHA focus on the plain areas, lack of quantitative studies in mountain areas, such as the Qinghai-Tibet Plateau. The Pythagorean fuzzy cloud (PFC) integration algorithm drawing on the advantages of Pythagorean fuzzy sets (PFS) and cloud model was proposed. A novel hybrid decision-making framework combining PFC integration algorithm and TOPSIS model was developed to determine the lake health levels with fuzziness and randomness. An indicator system incorporating ecosystem integrity (physical habitat, water quantity and quality, aquatic life) and non-ecological performance (social services) was established. To comprehensively investigate the lake health level in the Qinghai-Tibet Plateau, the Nam Co was selected as study area. Our results confirm that the developed framework in this study can overcome the shortcomings of existing methods and provide a more effective approach for LHA with fuzziness and randomness. In Nam Co, the non-ecological performance was significantly better than the ecosystem integrity. Health levels exhibited a remarkable spatial variation influenced by tourism and grazing, with decreasing health status from the northwestern to southeastern Nam Co. Approximately 85% of the sampling sites were at excellent or healthy levels, 15% were subhealthy, and no sampling sites were unhealthy and sick. Our results highlight that tourism has affected health levels at Nam Co, and effective measures are needed to minimize the impact in ecological fragile areas.

Economic and Sustainability Inequalities and Water Consumption of European Union Countries

Water scarcity is becoming a global concern for many reasons as its consumption increases. This research aimed to analyze sustainability inequalities in the water consumption of EU countries. Descriptive statistics using data for four AQUASTAT periods (2002, 2007, 2012, and 2017), and quotients for the AQUASTAT 2017 period, were calculated using a proposed econometric model. The main results were that countries with high GPD and population showed high water stress and total water withdrawal. Countries with lower industry-value-added-to-GDP quotients were among those with higher industrial water use efficiency, while low water-services-use-efficiency quotients were associated with high services value added to GDP. Suggestions for policymakers are provided and formula application guidelines for regional-level comparisons are described.

Urban Pluvial Flood Management Part 1: Implementing an AHP-TOPSIS Multi-Criteria Decision Analysis Method for Stakeholder Integration in Urban Climate and Stormwater Adaptation

Cities are facing increasing pressures to enact adaptation measures due to climate change. While blue-green infrastructure has emerged as a focal adaptation technique for stormwater management, in order to craft adaptation policies cities must consider a multitude of emerging, complex, and competing stakeholder interests around multiple adaptation alternatives. However, accounting for these different interests, analyzing their diverse priorities, and maintaining a transparent decision-making process is not easily achieved within the existing policy frameworks. Here we define and present a combined multi-criteria decision analysis (MCDA) of the analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) methods that easily integrates and quantifies stakeholder priorities while remaining accessible for non-experts engaged in the policy-making process. We demonstrate the method’s effectiveness through analyzing opinions about stormwater adaptation in New York City across several stakeholder groups. The method succeeds in integrating quantitative and qualitative judgements, indicating stakeholder preferential differences and allowing for more inclusive policy to be crafted. It can be extended beyond stormwater to many urban climate adaptation decisions facing multi-criteria considerations.

Using a grey multivariate model to predict impacts on the water quality of the Zhanghe River in China

In order to assess the social factors affecting the water quality of the Zhanghe River and predict the potential impact of growth in primary, secondary, tertiary industries and population on water quality of the Zhanghe River in the next few years, a deformation derivative cumulative grey multiple convolution model (DGMC(1,N)) was applied. In order to improve the accuracy of the model, the accumulation of deformation derivatives is introduced, and the particle swarm optimization algorithm is used to solve the optimal order. The DGMC(1,N) model was compared with GM(1,2) and GM(1,1) models. The results show that the DGMC(1,N) model has the highest prediction accuracy. Finally, DGMC(1,N) model is used to predict the potential impact of growth in primary, secondary, tertiary industries and population on water quality in the Zhanghe River (using chemical oxygen demand (COD) as the water quality indicator).

Managing aquifer recharge with multi-source water to realize sustainable management of groundwater resources in Jinan, China

Managed aquifer recharge (MAR) is an important approach to address water security, water quality decline, ground subsidence, and aquifer degradation. In this study, the large-scale recharge experiments were conducted in a natural river with multiple water sources. The MAR with multi-source water was investigated by developing an improved matter-element model under a limited recharged quantity and period in Jinan, China. Results showed that the background levels (BL) of groundwater quality before recharge was relatively good. However, the use of different water sources would cause a significant increase in the content of some groundwater quality indexes, which might further induce deterioration of regional groundwater quality. And the water quality in porous and karst aquifer displayed deteriorating trends during different water source recharge. Additionally, the adverse effects of recharge water sources on regional groundwater quality in turn was South-to-North Water Diversion Project (SN) > Yellow River (YR) > Wohushan Reservoir (WR). Meanwhile, the high-risk indexes in groundwater quality were presented during different water source recharge. Accordingly, relevant suggestions and measures were then put forward to optimize the MAR with multi-source water and explore the high-efficiency and low-risk recharge mode.

Coupling coordination and spatiotemporal dynamic evolution between urbanization and geological hazards-A case study from China

Investigation of the coupling coordination between urbanization and geological hazards is an important component in fostering environmentally sustainable development. This study constructed the comprehensive index system and developed the improved coupling coordination degree (CCD) model, Moran's I and projection pursuit model based on genetic algorithm to quantitatively investigate the dynamic mechanism and spatiotemporal distribution of coupling coordination between two subsystems within the context of the Five-Year Plan. Results showed that the comprehensive level of urbanization subsystem followed a continuous upward trend, and the geological hazard subsystem changed from a decreasing (2000-2010) to a rising (2011-2017) trend. A U-shaped relationship existed between two subsystems. And the CCD between two subsystems was higher in northeastern than that in southwestern China. Moreover, the significant spatial dependency existed in CCD. Driving by terrain, rainfall, vegetation cover, and human activities, the provinces in southwestern China exhibited low-low (L-L) clustering, while that in northeastern China showed high-high (H-H) clustering. In the past 17 years, the provinces in transitional and balanced development increased by 14.7% and 8.8%, and that in unbalanced development decreased by 23.5%. Overall, the provinces with low CCD were shrinking and the provinces with high CCD were extending from northeastern to southwestern China, meaning that the state of coupling coordination was changing from unbalanced to transitional development.