Exploring the relationship between urbanization and water environment based on coupling analysis in Nanjing, East China

Coupling coordination analysis and key factors between urbanization and water resources in ecologically fragile areas: a case study of the Yellow River Basin, China

The rapid urbanization (UR) and industrialization in the Yellow River Basin (YRB) have resulted in a significant scarcity of water resources (WRs), highlighting the need to investigate the complex and dynamic relationship between UR and WR for sustainable urban development in ecologically fragile areas. This study utilizes the coupling coordination degree model (CCDM), spatial correlation analysis, and Tobit model to examine the coupling coordination relationship, spatial effects, and key factors between UR and WR in sixty prefecture-level cities within the YRB. The empirical findings reveal that the development of the WR subsystem lags behind the UR subsystem and that there is a significant spatial disequilibrium in the CCD between UR and WR. Specifically, the high-high clusters are located in the northwest and east, while the low-low clusters are spread in the southwest. Furthermore, investment in science and technology and economic development have a positive impact on the CCD, while government capacity, urban construction, and industrial structure have a negative impact. These results can provide valuable guidance for decision-making in urban planning for ecologically fragile areas facing water supply constraints.

Effect of urbanization and urban forests on water quality improvement in the Yangtze River Delta: A case study in Hangzhou, China

In the context of rapid global urbanization, the sustainable development of ecosystems should be considered. Accordingly, the Planetary Boundaries theory posits that reducing the amount of nitrogen and phosphorus pollutants entering bodies of water is necessary as excess levels may harm the aquatic environment and reduce in water quality. Thus, based on the long-term monitoring data of representative urban rivers in the Yangtze River Delta region, we evaluated the nitrogen and phosphorus pollution of water bodies in different urbanization stages and further quantified the effect of urban forests on water quality improvement. The results showed that, with the continuous progression of urbanization, the proportion of impervious surface area increased, along with the levels of nitrogen and phosphorus pollution in water bodies. The critical period of water quality deterioration in urban rivers occurred during the medium urbanization level when the proportion of impervious surface area reached 55-65 %, and the probability of an abrupt increase in total nitrogen (TN) and total phosphorus (TP) concentration exceeded 95 %. However, increasing the area of urban forests during this period reduced TN pollution by 36.64 % and TP pollution by 49.03 %. The results of this study support the expansion of urban forests during the medium urbanization stage to improve water quality. Furthermore, our results provide a reference and theoretical basis for urban forest construction as a key aspect of the sustainable development of the urban ecosystem in the Yangtze River Delta and similar regions around world.

Coupling coordination of new urbanization in Chinese urban agglomeration-characteristics and driving factors

The coordinated development of new urbanization (NU) in urban agglomerations (UAs) is key for promoting sustainable urban development and the way to achieve Chinese-style modernization. Based on the mechanisms of coupling and coordination of NU, the internal subsystem coupling coordination of NU was deconstructed into five dimensions-economic, population, land, social, and ecological. Using 200 cities in 19 Chinese UAs areas, the spatio-temporal evolution characteristics of the coupling coordination degree of NU (CCDNU) were analyzed, and the driving factors were analyzed from both spatial spillover effect and stratification heterogeneity. The results are as follows: (1) CCDNU has increased from moderate disorder to barely coordinated, exhibiting a spatial distribution of a higher CCDNU in the east and lower CCDNU in the west with a positive global spatial autocorrelation feature; (2) economic drive, population concentration, spatial carrying capacity, and environmental quality play facilitating roles in the CCDNU of the study region, while the spatial carrying capacity, quality of life, and environmental quality inhibit the CCDNU of neighboring regions. From the decomposition of long- and short-term effects, both direct and indirect effects of driving factors were found to accumulate significantly over time. In addition, the model results were robust after replacing the geographic distance weight matrix and excluding the extreme values; (3) the spatial carrying capacity, population concentration, and economic drive are the dominant factors affecting the CCDNU in China. The dominant driving factors of are different in different regions. Meanwhile, the interaction detection shows that the interaction of each driver exhibits a two-factor enhancement or non-linear enhancement. Based on these results, corresponding policies are recommended.

Development and application of a multi-centre cloud platform architecture for water environment management

To promote the intelligent and accurate management of river basins, especially large basins which involve many catchments, it is highly required to develop a useful platform to effectively coordinate arithmetic resources and data, and simultaneously help to make decisions based on the real-time calculation. In this study, a multi-centre cloud platform architecture called 3L4C was constructed, which includes a Cloud-edge-terminal Layer (3L), data centre, model centre, control centre, and customer-service centre (4C). Data fusion technology and an air-land-water coupled model were constructed. Based on HTML5, JavaScript, and Java, an integrated water environment management platform was created and applied to the Three Gorges Reservoir Basin, China. The platform was tested and successfully used for automatic water quality prediction, water environment pollution analysis and control, early warning of abnormal water quality, and emergency water pollution incident evaluation. This platform quickly and accurately forecasts and perfectly displays past, present and future state of the water environment, and offers beneficial support for management decisions in various water environment departments.

Regional common prosperity level and its spatial relationship with carbon emission intensity in China

The characteristics of common prosperity include harmonious relationships between humans and the environment, as well as sustainable economic and social growth. The process of achieving common prosperity will necessarily have an impact on carbon emissions. In this article, panel statistics collected from 30 Chinese provinces and cities between the years 2006 and 2020 are utilized to assess the level of common prosperity and the intensity of carbon emissions in China. Then the SDM model is applied to explore the effects of the common prosperity level on the intensity of carbon emissions. The findings reveal that: (i) The common prosperity level in China has shown an increasing tendency. Between 2006 and 2020, the mean level of common prosperity increased from 0.254 to 0.486. From the regional perspective, eastern China has seen greater levels of common prosperity than central China, while central China has experienced greater levels of common prosperity than western China; regional disparities in the degree of common prosperity are substantial among Chinese provinces from 2006 to 2020; the common prosperity level is relatively high in economically developed provinces and relatively low in economically backward provinces. (ii) China's carbon emission intensity shows a continuous downward tendency. The annual average intensity of China's carbon emissions decreased from 4.458 in 2006 to 2.234 in 2020. From the regional perspective, the three main regions' carbon emission intensity likewise exhibits a decline in tendency between 2006 and 2020; still, western China continues to have the greatest carbon emission intensity, following central China, while eastern China has the smallest; however, certain provinces, notably Inner Mongolia and Shanxi, continue to have high carbon emission intensity. (iii) China's common prosperity level and carbon emission intensity both exhibit positive spatial autocorrelation at a 1% significant level under the adjacency matrix. The spatial agglomeration effect is significant, and adjacent provinces can affect each other. (iv) The SDM (Spatial Durbin Model) model test with fixed effects finds that the increase in the level of common prosperity suppresses the intensity of carbon emissions in the local area and neighboring regions. (v) The mediating effects model indicates that the process of common prosperity suppresses carbon emission intensity through high-quality economic development, narrowing the income disparity, and the development of a sharing economy.

Assessing surface water pollution in Hanoi, Vietnam, using remote sensing and machine learning algorithms

Rapid urbanization led to significant land-use changes and posed threats to surface water bodies worldwide, especially in the Global South. Hanoi, the capital city of Vietnam, has been facing chronic surface water pollution for more than a decade. Developing a methodology to better track and analyze pollutants using available technologies to manage the problem has been imperative. Advancement of machine learning and earth observation systems offers opportunities for tracking water quality indicators, especially the increasing pollutants in the surface water bodies. This study introduces machine learning with the cubist model (ML-CB), which combines optical and RADAR data, and a machine learning algorithm to estimate surface water pollutants including total suspended sediments (TSS), chemical oxygen demand (COD), and biological oxygen demand (BOD). The model was trained using optical (Sentinel-2A and Sentinel-1A) and RADAR satellite images. Results were compared with field survey data using regression models. Results show that the predictive estimates of pollutants based on ML-CB provide significant results. The study offers an alternative water quality monitoring method for managers and urban planners, which could be instrumental in protecting and sustaining the use of surface water resources in Hanoi and other cities of the Global South.

Evaluating the relationship between groundwater quality and land use in an urbanized watershed

Understanding the impact of urbanization on groundwater quality is critical. Effective water management requires understanding the relationship between land use and water quality. The study's goals were to compare the effects of land use, identify the types of land that impact hydrochemistry, and define how different land use affects water quality. For this purpose, the comparative relationship between groundwater quality, land use classes and landscape metrics were established for the years 2016 and 2021. Water samples were collected from 42 wells, and different hydro-chemical variables were considered to calculate the water quality index (WQI). The WQI value in 2016 ranged from 26.49 to 151.03 and 29.65 to 155.62 in 2021. The results indicate that the water quality in most parts of the study area is moderate for drinking and domestic purpose use. The google earth engine platform was used and radiometrically corrected and orthorectified Sentinel-2 satellite images were processed to classify land use classes for selected years. Five buffer zones were established within a 2-km watershed along each well site, and the effects of land use types and landscape metrics on water quality in the buffer zones were analyzed. Results revealed that the effects of land use types on water quality were mainly reflected in buffer 1 (B1), buffer 4 (B4), buffer 5 (B5) in 2016 and B1, buffer 3 (B3), and B5 in 2021. The impacts of landscape-level metrics on water quality are mainly reflected in buffer 2 (B2) and B3 in 2021, while at the class-level, they are mainly reflected in B1 and B4 in 2021. The redundancy analysis revealed that different hydro-chemical variables behaved differently with the land use classes and landscape metrics in the various buffer zones.

Assessment of groundwater quality in Ranchi district, Jharkhand, India, using water evaluation indices and multivariate statistics

Groundwater is the most abundant liquid freshwater on earth. Rapid urbanization in developing nations (like India) has led to increased groundwater withdrawal, adversely affecting the physicochemical characteristics. Ranchi district, Jharkhand, is a part of the smart city mission development plan of the government of India. Hence, to ensure safe and clean drinking water, it is necessary to assess groundwater quality and devise development plans. Seventeen physicochemical properties and metal(loid)s contents were analyzed to determine the groundwater quality. Various pollution indices such as water quality index (WQI), metal evaluation index (MI), heavy metal pollution index (HPI), and modified degree of contamination (mC_d) are evaluated using arithmetic weighted value index and presented in a map using Arc GIS inverse distance weighting interpolation method. Chemometric analyses such as correlation, principal component, and cluster analysis were done to identify the source and determine the pollution state. A multiple linear regression model is employed to predict the impact of heavy metal and metalloid concentration on the WQI of the region. WQI shows that groundwater quality in Khelari (100.95) and Bundu (92.52) regions are highly degraded, whereas MI and HPI suggest that Ormanjhi (MI = 53.98) and Rahe (HPI = 109.20) are highly affected by metal contamination. The mC_d suggests that Ormanjhi (97.15) has the highest degree of contamination. The contaminant sources were natural (geogenic processes) and anthropogenic (mining and industrial emissions). The high metal(loid)s concentration may soon result in groundwater quality degradation in the metal-affected regions.

Municipal food waste recycling as an environmental strategy: a game-theoretical approach

With the expansion of urbanization, we are witnessing the growing uncertainty in municipal food demand leading to an increase in urban waste. With the motive of producing organic fertilizers and conserving the environment, expired food can be collected and recycled. This study examines the hypothesis that leasing recycling facilities from peri-urban areas, due to the ban on reproduction operations in the city centers, can manage the recycling system participants' relationship and enhance sustainability in urban communities. The problem has been investigated under two separate sources of uncertainty, namely, quality and capacity. In the first scenario, a recycling system consisting of a commercial food service located in urban areas, a food waste collection agency, and a suburban fertilizer factory is optimized, in which the commercial food service leases the fertilizer factory's facilities for recycling operations. In the second scenario, the two factories' relationship, in which the first factory can rent the second factory's facilities in case of capacity shortage, is managed through hybrid contracts and mathematical programming models. The results show that the whole system optimization and Pareto Improvement results for all members are guaranteed under proposed hybrid contracts. These conclusions can help food recycling system managers have a better relationship with other players in their supply chains and enhance their credibility for caring about the environment, social concerns, and government compliance.

On the coordination in diversity between water environmental capacity and regional development in the Three Gorges Reservoir area

Water environment capacity has drew the attention of policymakers and stakeholders to sustainable development, and its dynamic changes are ultimately impacted by population, capital, and industrial clusters under regional development. Previous research, however, has not been able to completely comprehend it. In this paper, the authors use the Coupling Coordination Degree model and the Geodetector model to study the temporal and spatial evolution of water environment capacity and its driving mechanism based on regional development represented by regional function including urbanization function, ecological function, and agricultural function using the Three Gorges Reservoir area on county scale as a case study from 2000 to 2015. The results showed that (1) compared with 2000, 2005, and 2010, the water environment capacity of the whole reservoir area in 2015 was significantly improved. (2) The urban functions of each district and county are increasing in different years, and the dynamic changes of ecological and agricultural functions are obviously different. (3) The water environment capacity of districts and counties in the head area. There are significant disparities in the relationship between water environment capacity and regional function in various regions. Differences in water environment capacity are largely influenced by ecological function and the interaction driver of the proportion of agricultural function and urban function, which are typically the biggest of all the components. This suggests that regional development is a top priority in order to improve the operability of the water environmental capacity through more regulation, rules, and planning.

New-type urbanization ecologically reshaping China

Addressing critical ecological issues is one of the core objectives of the Chinese National New-type Urbanization Plan (NTU). However, there is not enough research to clearly demonstrate NTU's impact on environmental pollution. There is a need to provide solid empirical evidence from evaluation of the effects of NTU on environmental pollution. This study implements a series of propensity score matching and difference-in-difference analyses based on a comprehensive panel dataset spanning the period 2006-2017. The quantitative results show that NTU is largely conducive to curbing environmental pollution, with PM_2.5 concentrations as a proxy, and its robustness is demonstrated by the parallel trend test and placebo test. Further, the ecological effect of NTU is heterogeneous in terms of city level, location, and former pollution level. Small and medium cities benefit more than larger or central cities from NTU, and eastern cities exhibit better air quality improvement than cities in western regions. In addition, through quantile regression, we find that the positive outcomes of NTU are restricted by level of pollution, i.e., heavier pollution adds greatly to the difficulty of abatement.

Study on the Coupling Coordination between New-Type Urbanization and Water Ecological Environment and Its Driving Factors: Evidence from Jiangxi Province, China

With the rapid development of urbanization, problems such as the degradation of water ecological environment have emerged. How to improve the water ecological environment in the process of urbanization has become one of the urgent problems facing policy makers. This paper studies the coupling coordination relationship between new-type urbanization and water ecological environment, with the purpose of using insights gained from the study to help improve the quality of water ecological environment and promote sustainable development of water ecological environment. We take 11 cities in China's Jiangxi Province as the research object, and construct the coupling coordination evaluation indicator system of new-type urbanization and water ecological environment, then using the coupling coordination degree model to examine the state of coupling coordination between new-type urbanization and water ecological environment from 2009 to 2019. We further explore its driving factors employing random effect panel Tobit model. The results show that: (1) The level of new-type urbanization in Jiangxi Province shows a steady upward trend, and the water ecological environment level tends to rise steadily and slowly, although the comprehensive score of water ecological environment in most cities is lower than 0.1, indicating that the situation of water ecological environment is not optimal yet and there is room for improvement. (2) In 2009, 2014 and 2019, the coupling coordination development level between new-type urbanization and water ecological environment in Jiangxi Province showed an upward trend, from moderate maladjustment recession to mild maladjustment recession, and from low coupling coordination to moderate coupling coordination, although the overall coupling coordination degree was low. (3) The investment in scientific and technological innovation, degree of opening-up and government capacity are positively correlated with the coupling coordination degree, while economic development level, resource agglomeration ability, education level and industrialization level are negatively correlated with the coupling coordination degree. These results can provide insights to support new-type urbanization and water ecological environment in the future, and hold great significance for urban sustainable development.

Government support, talent, coupling of innovation chain and capital chain: empirical analysis in integrated circuit enterprises

Purpose

This study aims to investigate the impact of government support on the coupling coordination degree of innovation chain and capital chain in integrated circuit (IC) enterprises and to explore the mechanism for considering talent in the influence path.

Design/methodology/approach

This paper uses coupling coordination degree model to estimate the coupling of two chains, and applies dynamic panel system generalized method of moments (system-GMM) to analyze the impact of government support on coupling of two chains and conducts dynamic panel threshold regression to explore the threshold effect of talent in the influence of government support on coupling coordination degree.

Findings

Serious imbalance in the coupling of two chains is a major obstacle in IC enterprises. Government support significantly reduces the coupling coordination degree. The talent in IC enterprises has a significant threshold effect. When the number of talent is lower than the threshold value, government support has a negative impact. Once the number of talent reaches a certain level, government support can significantly enhance the coupling of two chains. Compared with state-owned enterprises, government support has a greater negative impact on the coupling of the two chains in non-state-owned enterprises. The former needs more talent to take advantage of government support.

Originality/value

This paper applies the concept of coupling into enterprises and deeply studies the coupling coordination degree of two chains. The influence mechanism of government support and talent on the coupling of two chains is explored, which reveals that government support cannot achieve the expected incentive effect without the support of talent. We also discuss the heterogeneous effect of government support and of talent in enterprises of different ownership types.

Incorporating Ecosystem Service Multifunctionality and Its Response to Urbanization to Identify Coordinated Economic, Societal, and Environmental Relationships in China

Urbanization poses a threat to ecosystems and contributes to the degradation of the environment. It is of great importance to identify coordinated economic, societal, and environmental relationships with key ecological functions and services to achieve regional sustainability. Based on a case study in China, this study seeks to fill this gap by estimating the spatial distribution of ecosystem service multifunctionality (ESM) and its spatially heterogeneous response to urbanization. First, the biophysical values of five typical ecosystem services (ESs) (carbon storage, habitat quality, net primary production, soil conservation, and water yield) were assessed based on several simulation models. The biophysical values of these ESs were then standardized and summed to obtain the spatial distribution of ESM. Afterward, the urbanization level was evaluated, and finally, the spatial interaction between urbanization and ESM was exhibited based on the bivariate Moran’s I and Getis-Ord Gi* statistic. The results showed that: (1) the ESM showed obvious spatial heterogeneity in southeastern and northwestern China, with a gradual decline from the coast to the interior; (2) ESM and urbanization had different spatial distribution patterns and produced significant local aggregation effects; and (3) harmonious relationships between ESM and urbanization were observed in southeastern coastal China and the surrounding areas of the North China Plain, which were related to the capacity of local coastal ecosystems, mangrove forests, and aquatic ecosystems to provide multiple services and goods simultaneously. Our results suggest that multifunctional ecosystems can realize a ‘win–win’ situation for ecological conservation and socioeconomic development. The results of this study can advance our understanding of the ecological effects of urbanization on ecosystems and provide valuable implications for the coordinated development of humans and nature in the rapid urbanization process.