An integrated specification for the nexus of water pollution and economic growth in China: Panel cointegration, long-run causality and environmental Kuznets curve

The influence of government ideology on the rate of e-waste recycling in the European Union countries

This study examines the impact of government ideology on e-waste recycling in 30 European countries from 2008 to 2018. This study seeks to enhance the e-waste recycling literature by introducing a novel determinant, examining the unexplored relationship between government ideology and e-waste recycling rates in European countries, thus addressing a substantial research gap. Utilizing panel quantile regression on an unbalanced dataset, the findings revealed that the increased influence of right-wing parties in government was associated with lower e-waste recycling rates. Conversely, greater influence of left-wing or center-wing parties was correlated with higher recycling rates across all quantiles analyzed. The estimation results remain robust when different indicators of government ideology were employed. Overall, the study underscores the importance of political ideology in shaping e-waste recycling policies and environmental sustainability efforts. It emphasizes that effective policies should align with the political commitment of the governing body.

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.

Spatial effects of the agricultural ecosystem services based on environmental kuznets curve in Mengyin county, China

Worldwide most agroecosystems effort to increase production and yields and leads to damages of a series of non-provisioning ecosystem services (ESs). To fill in the knowledge gaps pertaining to the understanding of complex relationship between agricultural harvests and other ESs, therefore this study aims to estimate the existence of Environmental Kuznets Curve (EKC) for agricultural ESs by incorporating the spatial factors. Based on the test of the spatial autocorrelation of agricultural ESs, the estimation results of spatial model are compared with general regression to explain the spatial effect of agricultural ESs. The results show that (1) contrary to expectation, the curve of the nonlinear relationship between agricultural ESs and annual household income is an inverted U-shape, and not an upright U-shape; (2) compared to non-spatial model, the turning point of the inverted U-shaped curve for agricultural ESs under the direct effect would happen earlier and happen later under the indirect effect; (3) years of formal education, vegetation coverage of field margin and cultivated land area have significantly impact on local agricultural ESs, and local perennial crops has significantly impact on agricultural ESs of neighboring villages. Results of this study have a promising application prospect to promote sustainable development of agriculture.

Pollution status of heavy metals and metalloids in Chinese lakes: Distribution, bioaccumulation and risk assessment

Due to intensive human activities, most of Chinese lakes are suffering from the pollution of heavy metals and metalloids. Previous studies on heavy metals and metalloids in Chinese lakes were limited to a few lakes and mainly focused on sediments, to date the knowledge on heavy metals and metalloids in multiple media of Chinese lakes from a national perspective is scarce. We collected the data of nine heavy metals and metalloids including Copper (Cu), Cadmium (Cd), Lead (Pb), Mercury (Hg), Arsenic (As), Chromium (Cr), Nickel (Ni), Zinc (Zn), and Manganese (Mn) in water, surface sediments, and fish of 87 Chinese lakes sampled in the period from 2009 to 2019 from the literature, summarized the distribution of heavy metals and metalloids, evaluated their pollution, and apportioned their sources from a national perspective. Concentration of individual heavy metal and metalloid in water, surface sediments, and fish in Chinese lakes was in the ranges of 0.0080-282 μg/L, 0.020-33858 μg/g, and 0.00030-207 μg/g, respectively. 5.6 % and 33.3 % of lake water were polluted by Cd and As. 88.2 %, 78.6 %, and 66 % of lake sediments were polluted by Cd, Hg, and As. 35.3 %, 11.3 %, 52.4 %, and 12.8 % of Cd, Pb, As, and Cr concentrations in lake fish exceeded the food limits. Concentrations of heavy metals and metalloids in fish viscera were higher than those in other organs. Higher partition coefficient and bioaccumulation factors were found for Pb and Cd, Hg and Zn, respectively. Concentrations of heavy metals and metalloids in both water and sediments of lakes in eastern China were higher than those in western China. Concentrations of heavy metals and metalloids in both lake water and sediments of urban lakes were higher than those of rural lakes. Lakes with extremely high ecological risk of heavy metals and metalloids were mainly located in central China and eastern China. Pollution of heavy metals and metalloids in Chinese lakes was closely correlated with regional economic development. Heavy metals and metalloids in Chinese lakes were mainly derived from industrial, domestic, and mixed discharges. Cd and Hg were selected as the heavy metals for priority control in Chinese lakes.

Relationship between environmental pollution and economic development in late-developing regions shows an inverted V

In late-developing regions, new technologies and previous experiences are applied to reduce the impact of economic development on environmental pollution in the early stages. After economic development has reached a certain level, the application of new environmental remediation technologies and methods can accelerate environmental restoration. Therefore, we hypothesized that the relationship between economic development and environmental pollution would exhibit an inverted V in late-developing regions. We examined water quality changes in 353 monitoring sections of 76 urban rivers in Kunming, southwestern China, over the last 33 years to assess the impact of economic development on river water quality. The results indicate that the relationship between the comprehensive pollution index of urban rivers and the economy shows an inverted V, supporting our hypothesis. The inverted V could be divided into four areas: an environmental self-purification area (<2170 USD); an economic development environmental destruction area (2170-5240 USD); an economic development feedback environment area (5240-11,255 USD); and an economic development promotion environment area (>11,255 USD). On the time axis of economic development, the relationship between economic development and environmental pollution is closer to an inverted U in relatively early developing regions, but the experience with and application of new technologies causes the relationship to change from an inverted U to an inverted V in relatively late-developing regions.

Convergence study of water pollution emission intensity in China: evidence from spatial effects

One of the challenges that China currently faces is how to reduce the emissions of water pollution. However, the study of water pollution convergence has a certain policy significance for controlling the emissions of water pollution. This article firstly uses chemical oxygen demand (COD) and ammonia nitrogen (NH₃-N) as indicators of water pollution. Due to the obvious spillover effect of water in space, this article adds a spatial effect to the convergence model. Based on panel data of 30 provinces and cities from 2006 to 2017, this article uses a dynamic spatial Dubin model to analyze the convergence of water pollution emission intensity to address the endogenous problem in the model. The empirical results of this paper show that there is absolute β-convergence and conditional β-convergence in the intensity of water pollution emissions. The spatial autocorrelation test shows that there is a positive spatial autocorrelation of water pollution emissions, which means that the pollution emissions in neighboring areas will affect the emissions in the local area. The industrial structure has a certain promoting effect on the emission of water pollution, which means that adjusting the industrial structure and alleviating the structure of the secondary industry is the trend of future development. Economic growth can curb the emissions of water pollution. The influences of urbanization and foreign investment on the emissions of the two pollutants are inconsistent, and policies can be formulated according to local conditions in the future.

China industrial environmental database 1998-2015

There has been a rapid-growing trend in studying China's environmental problems in the past decade. However, the existing environmental statistics data are far from meeting researchers' requirements. The biggest problem is that the official environmental statistics data are only provided at either regional level or sectoral level. Considering the huge heterogeneities in different regions and sectors, researchers are unable to conduct comprehensive policy evaluations. In this study, we constructed the time-series industrial environmental database for China (CIED) at both regional and sectoral level. The database includes totally 31 regions and four types of pollutants: chemical oxygen demand (COD), sulphur dioxide (SO₂), ammonia-nitrogen (NH₃-N), and nitrogen oxide (NO_X). This study also clarifies several important concepts for researchers to better understand China's official environmental statistics data.

Does environmental audit help to improve water quality? Evidence from the China National Environmental Monitoring Centre

As an essential re-supervision system of the environmental regulation, the environmental audit can help improve the quality of the ecological environment by correcting the deviation of local governments' environmental regulatory behavior. This study constructed a conceptual model of environmental audit affecting water quality, and empirically examined the effects and mechanism through the difference in difference (DID) regression and the mediating analysis. The panel data were collected from 76 cities covered by the surface water quality monitored by China Environmental Monitoring Station from 2006 to 2017. The results indicated that: (1) the overall effect of the environmental audit on the water quality was positive but not significant; (2) the environmental audit mainly encouraged local governments to strengthen superficial regulations with lower cost, more immediate and perceptible effects, but failed to promote the advanced regulation to reduce the pollution sources and fundamentally improve the water quality. On this basis, the policy implications were proposed that the environmental audit should be strengthened to further promote the advanced regulation and improve water quality constantly.

Testing the heterogeneous effect of air transport intensity on CO2 emissions in G20 countries: An advanced empirical analysis

This study investigates the heterogeneous impact of air transport intensity, air passenger transport, and air freight transport on air transport carbon emissions in G20 countries for the period of 1990-2016. The paper employs a robust and advanced fixed-effect panel quantile regression model that considers unobserved discrete and distributional heterogeneity. Our empirical results show that the impact of the independent variables on air transport carbon emissions is quite heterogeneous across various quantiles. More specifically, the effect of air transport intensity, air passenger transport, and air freight transport on carbon emissions is positive and becomes more assertive with the increasing trend at upper quantiles and is quite heterogeneous across all quantiles. Economic growth, urbanization, and tourism are significant contributing factors in enhancing air transport CO₂ emissions, while crude oil price significantly reduces CO₂ emissions. The Dumitrescu and Hurlin causality test estimates indicate that a bidirectional relationship extends from air transport intensity, air passenger transport, and air freight transport to air transport CO₂ emissions. The findings underline the need for cleaner, renewable, and environmentally sustainable energy sources for air transport operations.

Improving Water Quality in the Citarum River through Economic Policy Approaches

This study examines the upper basin of the Citarum River in West Java, Indonesia, to analyze the optimal environmental policy and issues affecting the balance between economic activities and water environment conservation, for example, controlling water quality while maximizing economic activities in the region. The quantitative results derived using model simulation analysis clarifies the study’s issues. An integrated model linking two sub-models describing socio-economic activities and the dynamics of water pollutants was simulated. The model incorporates government subsidies for sewerage system maintenance and septic tank installation as economic policy variables for water quality control. Further, the optimal amount of these subsidies and changes in local economic activities according to water pollution load constraints are derived in a time-series structure for each region from 2015 to 2030. The gross regional product (GRP) maximization problem is solved under the inflow constraints of total nitrogen, total phosphorus, and chemical oxygen demand into the river. The results showed that the most favorable balance between water environment conservation and local economic activities can be achieved by setting the inflow constraint for 2030 at +3% of the 2015 level and the maximum annual cost of the measures at 10 times the current environmental budget of the West Java Province.

Can campaign-style enforcement facilitate water pollution control? Learning from China's Environmental Protection Interview

The effectiveness of campaign-style enforcement (CSE) on water pollution, especially the long-term effectiveness, is controversial, and little knowledge is known about the channels through which the effectiveness happens. We take advantage of China's Environmental Protection Interview (EPI)- a distinguished form of CSE launched in 2014, as a natural experiment to estimate the short-term and long-term effects of CSE on water pollution. Using a time-varying difference-in-differences model based on city panel data from 2006 to 2018, we find that EPI can lead to an average 14.5% reduction in water pollution, and this effect is still persistent in the long term. Mechanism analysis shows that EPI reduces water pollution mainly through the pressure effect on the government, the penalty effect on the firms, and the mobilization effect on the public. Heterogeneity analysis shows that the effect of EPI on water pollution is more significant in cities with high initial pollution, low public complaints, and low economic levels. Further cost-benefit analysis based on the estimated value of water pollution reduction shows that the upper health benefit of EPI is $520.97 billion, which is 4.87 times higher than its estimated cost of $107.05 billion.

Environmental technology and wastewater treatment: Strategies to achieve environmental sustainability

Water is the vital liquid for human subsistence and is used as a resource in various production processes. However, the degradation of the environment is being reflected in the water resources of the planet. One of the leading causes of water pollution is ineffective wastewater treatment, which results in greywater being returned to the environment without having gone through a decontamination process. Ideally, wastewater should have the lowest concentration of polluting materials to be reused and exploited in other activities, such as agriculture or the generation of renewable energy. However, in its various forms, technological progress plays a vital role in improving wastewater treatment processes, becoming a determining factor in improving greywater quality. This study examines how environmental technology contributes to wastewater improvement in 16 selected OECD countries during 2000-2019. Annualized information is used and collected from various official sources of information, subsequently processed with various econometric approaches. The results obtained show a heterogeneous behaviour in the quantiles of wastewater treatment, environmental technology and renewable energy are positively related to an increase in wastewater treatment between 0.09% - 0.20% and 3.5 e-12% - 5.74 e-12%, respectively. Based on the results obtained, the policy implications suggest promoting environmental technology to improve wastewater treatment.

Vulnerability of groundwater from elevated nitrate pollution across India: Insights from spatio-temporal patterns using large-scale monitoring data

Agriculture-sourced, non-point groundwater contamination (e.g., nitrate) is a serious concern from the drinking water crisis aspect across the agrarian world. India is one of the largest consumers of nitrogen fertilizers in South-Asia as well as in the world but groundwater nitrate lacks critical attention as a wide-scale drinking water pollutant in the country. Our study provides the first documentation of the distribution of groundwater nitrate and the extent of elevated nitrate contamination across India, along with the delineation of the temporal trends and the natural and anthropogenic factors that influence such occurrence of groundwater nitrate. High resolution, annual-scale spatio-temporal variability of groundwater nitrate concentration and consequent contamination was delineated using groundwater nitrate measurements from ~3 million drinking water wells spread across 7038 administrative blocks between 2010 and 2017 in India. An average 8% of the studied blocks were found affected by elevated groundwater nitrate (> 45 mg/L). Depth-dependent trend demonstrated that nitrate concentrations were about 14% higher in shallow water wells (≤ 35 m) than deep wells (>35 m). The overall temporal trend of groundwater nitrate concentration was decreasing slightly nationwide in the study period. The correlation tests and causality test results indicated that the spatial distribution of groundwater nitrate was significantly associated with agricultural N-fertilizer usage, whereas the decreasing temporal trend corresponded with the overall reduced N-fertilizer usage during the study period. Spatial autocorrelation analysis identified the clustering of high nitrate areas in central, north, and southern India, specifically in areas with higher fertilizer usage. We estimate about 71 million Indians possibly exposed to elevated groundwater nitrate concentrations and the majority of them reside in rural areas. Thus, this study provides the previously unrecognized, wide-scale, anthropogenic, diffused groundwater nitrate contamination across India.

The impact of land use and socio-economic factors on ammonia nitrogen pollution in Weihe River watershed, China

Rapid socio-economic development has led to a significant deterioration in the water environment, which has limited sustainable regional development. The soil and water assessment tool (SWAT) and statistical regression method were used to model the ammonia nitrogen (NH₄⁺-N) pollution and explore the impacts of land use and socio-economic factors on NH₄⁺-N pollution within the Weihe River watershed in China from 2015 to 2018. The result of SWAT model revealed that the NH₄⁺-N concentrations were usually relatively high under low runoff conditions and relatively low under high runoff conditions. The average NH₄⁺-N concentration in the upper reaches was 0.77 mg/L, whereas it was 0.87 mg/L in the middle and lower reaches of the watershed. Serious NH₄⁺-N pollution mainly occurred in 2015 and 2016, and the V (2.0 mg/L) and V+ (>2.0 mg/L) water quality classes were associated with approximately 6.67% and 28.94% of the total watershed area, respectively. The multiple linear regression indicated that the building land and secondary industry were the significant controlling factors (P < 0.01). According to the scenario analysis, modelled scenarios for interception measures reduced the NH₄⁺-N load to a greater degree than scenarios for source control measures. To improve the surface water quality in the Weihe River, it is recommended to adjust industrial structure, increase sewage treatment, and strengthen the rural management of the watershed.

Relationship between energy consumption, economic growth and environmental pollution in China

In recent days, many emerging nations facing severe environmental pollution problems. In order to overcome the environmental problems, many new methods and strategies have been built and some advance sources of energies were also utilized in order to overcome such issues but by using such sources, many challenges were faced. In order to find best possible solutions of such issues, this paper was aimed to minimize the gap of research by examining the effect on economic development of energy expenditure and environmental pollution and by means of finding the casual relationship between them because it has been observed that with development of economy, environmental issues always increase. Effects of both traditional and modern energies was analyzed in this research. Several explanatory variables will be used: Renewable energy consumption, CO₂ emission, economic GDP. Environmental pollution will be taken as the mediating factor that influence this association between energy utilization as well as economic development. Present study was based on the economy of China. ARDL regression model was applied in this research to increase the time series econometrics when non-stationary value demonstrated the co-integration and it is also effective for both stationary and non-stationary time series. At the end, some advanced methods of production were discussed that can be used in this era of industry 4.0. By proper implementation of such processes, many economic and environmental benefits can be achieved.

Do spatial spillovers matter? Estimating the impact of tourism development on CO2 emissions

Most of the extant literature on the environmental impact of tourism has ignored the possible spatial interaction effects across countries. This study thus aims to re-investigate the impact of tourism development on CO2 emissions by taking spatial dependence into account. To that end, the spatial econometric techniques, which can address the issue of potential spatial dependence among countries, are adopted. Using a panel data of 95 countries over 2000-2014, the results confirm that there exists a significant spatial dependence among national CO2 emissions. Besides, the results provide confirmation that tourism development exerts a significant enhancing influence on CO2 emissions. Interestingly, we find that the promoting effect of tourism development on CO2 emissions primarily comes from the spillover effect rather than the direct effect, after considering spatial dependence. Finally, in light of the research findings, some policy implications are put forward to improve environmental quality.

The influence of environmental efficiency on PM2.5 pollution: Evidence from 283 Chinese prefecture-level cities

Environmental inefficiency caused by the extensive economic growth pattern is considered a critical driver of the unprecedented PM_2.5 (fine particulate matter) pollution in China. However, the nexus between environmental efficiency and PM_2.5 concentrations has rarely been examined. We used a recently developed data envelopment analysis method to measure environmental efficiency, environmental total factor productivity, and their compositions in China at the prefecture level from 2003 to 2013 and examined the effects of environmental efficiency on PM_2.5 pollution. The results indicated that improvements in environmental efficiency significantly ameliorated PM_2.5 pollution. The effect of technological progress on PM_2.5 reduction is limited, but the pure efficiency and scale efficiency promoted by enhanced management level and optimized production scale strongly contribute to PM_2.5 mitigation. The significant spatial spillover of environmental efficiency and PM_2.5 pollution introduces challenges and opportunities for lowering PM_2.5 emissions. The impact of environmental efficiency on PM_2.5 pollution exhibits significant spatiotemporal heterogeneity, and the strength of influence tends to increase with PM_2.5 concentration and become more pronounced over time. Furthermore, several socioeconomic factors are related to PM_2.5 pollution, which implies that PM_2.5 control is a complex system and requires a comprehensive policy mix.

Analysis of standard accounting method of economic compensation for ecological pollution in watershed

With rapid development of social industry and agriculture, there is an increasing demand for water resources in a watershed, which leads to a series of serious problems in the watershed such as water resource shortage, water environment deterioration, water resource pollution, etc. This paper builds an econometric model of economic loss due to water pollution in a watershed based on the basic process of standard water pollution compensation calculation of economic loss. The econometric model is used to calculate the amount of compensation for economic loss due to water pollution; a mathematic model method of water environment is applied to calculate the degree of effect on the lower reaches; thus the proportion of the impact on the areas in the lower reaches to overall impact is obtained. The amount of compensation that should be borne by all areas is obtained in combination of amount of compensation for water pollution. Empirical analysis is carried out by taking the Taihu Basin for example, and the standard compensation and the amount of compensation for the economic loss caused by water pollution between different areas along the Jiangnan Canal in the Taihu Basin are defined, which provides scientific and theoretical bases for standard calculation of the water pollution compensation. This provides a theoretical basis for solving the problem of water pollution in the watershed and the contradiction in the development of the watershed, and realizing social equity and harmonious development.

Moving to economic growth without water demand growth -- a decomposition analysis of decoupling from economic growth and water use in 31 provinces of China

Increasing water consumption from various economic activities has posed increasing challenges for the sustainability of developing countries. In particular, China is facing a sharp conflict between rapid economic development and water shortage. Evaluating the decoupling state between economic growth and water consumption and exploring the driving factors behind this could serve to develop strategy to moving to economic growth without water use growth. To this end, this work uses the Tapio decoupling and LMDI decomposition methods to evaluate the decoupling performance between China's water consumption and economic growth at the national and provincial levels, and six driving factors are decomposed, namely water consumption intensity, industrial structure, economic development, water resource utilization rate, water resource endowment and population size. Results show that: (1) Only two decoupling states, strong decoupling and weak decoupling, occurred at national level, and the decoupling index shows a decreasing trend. (2) 31 provinces showed only two states of strong decoupling and weak decoupling. More than 60% of the provinces showed strong decoupling after 2011, and the decoupling effect was significantly better than that of 2004-2011. (3) The effects of water consumption intensity and industrial structure drive the occurrence of decoupling. Economic level and population size have a positive incremental effect on water consumption. Finally, we propose policy recommendations such as developing water-saving technologies and optimizing industrial structure to promote water sustainability. The comprehensive methodology in this paper provides a theoretical reference for research in other countries or other environmental issues. Governments in various regions can formulate effective measures to achieve sustainable use of water resources, responding to the 2030 Agenda for Sustainable Development.

Lead distribution in urban street dust and the relationship with mining, gross domestic product GDP and transportation and health risk assessment

Lead (Pb) is an important pollutant and it is of significance to explore the Pb distribution, influencing factors and health risk. Pb concentration and mass load per unit area in 385 street dust samples collected from 19 cities in China were determined during 2011-2013. The results show that the Pb concentration are 68.8, 105.4, 41.7, 49.7, 75.6, 81.7, 131.9, 67.5, 109.3, 164.1, 74.8, 66.4, 99.8, 58.4, 114.0, 59.6, 103.7, 55.4 and 80.4 for Beijing, Chengdu, Daqing, Harbin, Jilin, Jinan, Kunming, Lanzhou, Luoyang, Panzhihua, Qingdao, Yinchuan, Guangzhou, Tangshan, Xi'an, Guangyuan, Nanjing, Taiyuan and Tianjin, respectively. The Pb pollution level of urban street dust varies among cities in the range of 1.72-5.56 times higher than soil background values. The allometric function can fit the change in Pb concentration with particle size well. The medium-sized (38-120 μm) particles contributed 60.2%-80.4% to the Pb load and should be highlighted when selecting street dust management techniques. Influenced by the distribution of Pb ore, the Pb concentration of urban street dust in China shows obvious regional differences, with value in the south 112% higher than that in the north. Among all kinds of mining types, metal-related mining activities discharge a large amount of Pb dust in the process of crushing and smelting, thus contributing most to the Pb load. The Pb load was also affected by transportation. The relationship between Pb load and gross domestic product (GDP) was described with the environmental Kuznets curve (EKC) model, which indicated that the Pb emissions of most cities were still increasing. Finally, the human health risk assessment model with adjusted parameters showed that the Pb risk of all cities was below the threshold. Despite all this, given the EKC law of Pb emission, long-term follow-up assessments are needed.

Environmental Kuznets curve hypothesis: asymmetry analysis and robust estimation under cross-section dependence

In this paper, we revisit the environmental Kuznets curve (EKC) hypothesis by using estimations that account for cross-sectional dependency (CSD) and asymmetry effect in 76 countries for the period 1971-2014. Our results lend moderate support to the EKC hypothesis. The country-specific results unfold that a total of 16 out of 76 countries support the EKC hypothesis using CCEMG estimator. Results from AMG reveal that the EKC hypothesis holds in 24 out of 76 countries. It is worth highlighting that 11 countries (Australia, China, Congo Dem. Rep., Costa Rica, Gabon, Hong Kong, India, Korea, Myanmar, Turkey, and Uruguay) exhibit an inverted U-shaped curve regardless of whether CCEMG or AMG is used. The asymmetry analysis using PMG is also able to support the EKC hypothesis. We conclude that the EKC hypothesis does not fit all countries. Policy implication and recommendation in designing appropriate energy and economic policies are provided.

Analysis on the relationship between fisheries economic growth and marine environmental pollution in China's coastal regions

The rapid development of China's fisheries economy is accompanied by intensified marine environmental pollution over the period covered by this study. Based on data from multiple sources, this paper attempts to measure the relationship between fisheries economic growth and marine environmental pollution among China's coastal regions over the past 17 years. For this purpose, it firstly quantifies changes in fisheries economy and fisheries population. It then goes onto comparing the degree of changes in fisheries economy and marine environment. Finally, it depicts the relationship between fisheries added value (FAV) and polluted marine area (PMA) and between per capita net income of fishermen (PCNIF) and PMA ratio. Results suggest that.

Factory employment exposure and human health: Evidence from rural China

Quantitating the health effects of employment history in factories, especially polluting ones, is essential for understanding the benefits or losses of industrialization in rural areas. Using a traced subset of nationwide panel data from 2005 covering five provinces, 101 villages, and 2026 households (collected recently in 2016) and the econometric models, this study estimated the effect of factory employment history on workers' health. The results showed that: the absolute number of factory workers increased from 1998 to 2015, and the proportion of factory workers was 7.68% in 2015; the absolute number and the proportion of farmers decreased from 63.84% in 1998 to 29.06% in 2015. Given that all the respondents live in rural areas, the HlthPlace (the first place the individual went to for their last illness in 2015) was selected as the main dependent variable of interest, and Hlthexp (Healthcare expenditure per person at last illness in 2015) and self-reported health were used as auxiliary dependent variables. The findings revealed that, after controlling the characteristics of individual, household, hospital and area, a one year increase of factory employment history corresponded to a 0.035 level increase in the probability of people choosing high-level hospital (p < 0.01) and a 237.61 yuan increase in healthcare expenditure (p < 0.1). The results also showed the adverse effect of self-reported health on factory employment history (p < 0.01). In addition, the relationship between the farming history and health was evaluated, and the econometric results showed that compared with factory employment history, farming history had opposite impacts on health (p < 0.01). Finally, the robustness check showed that the empirical results were reliable and that the initial results were robust. Generally, this study revealed the effect of overall factory employment on health, which is a useful research supplement to the studies on the health effects of specific pollution exposure.

Examining the impact factors of the water environment using the extended STIRPAT model: A Case Study in Sichuan

China's rapid social and economic development has led to a significant deterioration in the water environment, which has limited sustainable regional development. Therefore, understanding the specific factors that affect the water environment is vital for future water conservation efforts. From a social economy perspective, this paper used population, the economy, urbanization, technological level, water consumption, and other factors to expand the STIRPAT model, after which partial least squares was applied to solve the model parameters and comprehensively analyze the impact of regional development on the water environment in Sichuan Province from 2007 to 2017. It was found that the main factors affecting the water environment were resident population, urbanization, service industry development, and industrialization, with the industrialization factor being found to have a reverse waste-sewage water discharge inhibition. In addition, it was found that during the study period, there was no environmental Kuznets curve between water resource environmental pollution and economic growth in Sichuan Province. Finally, some policy recommendations for improving the water environment were given based on the results.

Are global cities sustainability champions? A double delinking analysis of environmental performance of urban agglomerations

Urban agglomerations - irrespective of their size or location - may act not only as engines of economic growth, but also as vehicles of environmental and climate sustainability that may stimulate both socio-economic achievements and environmentally-benign outcomes. Clearly, the efficiency of these outcomes may differ for different types of urban agglomeration in the world. This paper aims to present and test an advanced methodology for assessing economic and sustainability-oriented performance strategies for global cities, by developing and applying a super-efficient Data Envelopment Analysis (DEA) model. We compare 40 global cities - included in the Global Power City Index (GPCI) database - in a benchmark study in order to trace the highest-performing urban regions from both an economic and environmental-climatological efficiency perspective, by applying relevant quantitative GPCI indicators to these 40 cities. Our ultimate goal is to test what is termed the 'delinking' hypothesis, from the viewpoint of both economic prosperity and urban size externalities. This approach will be applied empirically by examining the GPCI data set comprised of various multi-dimensional and empirically verified indicators on economic performance and climatological-environmental conditions for the 40 global cities concerned. We regard both the size of these agglomerations and their economic welfare position as critical parameters for assessing their economic and environmental efficiency performance. In the framework of our original DEA approach, these urban areas are categorised according to 2x2 dimensions, viz. in terms of both agglomeration size (big or medium-sized) and the economic development level of the area (highly developed or developing/emerging). Our contribution serves to assess - by means of regression techniques - the highest performing agglomerations among the urban sustainability champions on the basis of the two above-mentioned assessment criteria. This approach provides the opportunity to test the so-called Kuznets sustainability curve under two different conditions, viz. agglomeration size and economic development. The study presents and interprets the empirical findings for these four classes of global cities.

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

Investigation of water pollution-economic growth nexus is an important component for the sustainable development of eco-environment and socio-economy. This study combined the improved Grey relational degree (GRD) model with the environmental Kuznets curve (EKC) to quantitatively and qualitatively investigate the relationships between water pollution and economic growth in Nansi Lake catchment (Jining, Zaozhuang, and Heze) under the context of the Five-Year Plan in Shandong. Results showed that the relational degree of industrial wastewater and economic growth was Heze (0.652) > Zaozhuang (0.581) > Jining (0.538), and of domestic wastewater and economic growth was Jining (0.722) > Heze (0.721) > Zaozhuang (0.650). Meanwhile, the EKC of industrial wastewater rose and then declined, whereas that of domestic wastewater increased upwards. Overall, coordinated development had been gradually obtained between industrial wastewater emissions and economic growth. And, uncoordinated development between domestic wastewater emissions and economic growth still existed, indeed, in recent years it had intensified. Further, domestic wastewater emissions continue to rise, to the point where they now constitute one of the main sources of water pollution in Nansi Lake catchment. Results of this study indicated that combining the improved GRD model with the EKC provides a new approach to comprehensive investigation of the water pollution-economic growth nexus from a qualitative and quantitative perspective.

Forecasting China's wastewater discharge using dynamic factors and mixed-frequency data

Forecasting wastewater discharge is the basis for wastewater treatment and policy formulation. This paper proposes a novel mixed-data sampling regression model, i.e., combination-MIDAS model to forecast quarterly wastewater emissions in China based on dynamic factors at different frequencies. The results show that a significant auto-correlation for wastewater emissions exists and that water consumption per ten thousand gross domestic product is the best predictor of wastewater emissions. The forecast performances of the combination-MIDAS models are robust and better than those of the benchmark models. Therefore, the combination-MIDAS models can better capture the characteristics of wastewater emissions, suggesting that the proposed method is a good method to deal with model misspecification and uncertainty for the control and management of wastewater discharge in China.

Are de jure and de facto globalization undermining the environment? Evidence from high and low globalized EU countries

Globalization as a mechanism to connect people at distance and share knowledge has been flourishing. Simultaneously, environmental degradation has been increasing, as reflected in global warming. Through three dimensions, the economic, the social and political, and two measures, de jure and de facto, this study provides a disaggregated analysis of the effect of globalization on the critical issue of global warming for 25 European Union countries from 1990 to 2016. To emphasize globalization, the countries analysed were evaluated by two measures of globalization, de jure and de facto, resulting in their classification as high or low globalized countries de jure and de facto. Furthermore, energy consumption, economic growth and efficiency were included in an Autoregressive Distributed Lag model performed with the Driscoll-Kraay estimator. Robustness was checked using a Feasible Generalized Least Squares estimator. The results revealed that, overall, globalization increases environmental degradation, with the de jure measure having greater influence on high-globalized countries and the de facto measure having greater influence on low-globalized countries. Bearing in mind the increase in worldwide emissions driven by globalization, practices such as the relocation of polluting industries from high globalized countries should be discouraged. Incentives to harmonize global environmental restrictions could contribute to decarbonization worldwide.

Industrial water use, income, trade, and employment: environmental Kuznets curve evidence from 17 Taiwanese manufacturing industries

This paper investigated the relationships between industrial water use, income, trade, and employment for 17 Taiwanese industries from 1998 to 2015. We explored cross-sectional dependent unit root, panel cointegration, and causality tests to estimate their long-term relationships and causal nexus. There existed long-term equilibrium relationships among the variables. The long-term elasticity estimates of industrial water use with respect to income, squared income, trade, and employment are 4.27, - 0.15, 0.22, and 0.92, respectively. The results do not confirm an inverted U-shaped environmental Kuznets curve. A unidirectional causal relationship is found between water use and income, and a bidirectional causal relationship is identified between water use and employment. Exports cause industrial water use. As expected, both employment and exports lead to income. Hence, policy makers should promote investment into water efficiency and water recycling. Various governments reward firms for water efficiency and lower consumption without negative long-term effects on economic growth.

The Water-Economy Nexus and Sustainable Transition of the Pearl River Delta, China (1999–2015)

As the world’s largest urban area in both size and population, the rapid development of the Pearl River Delta (PRD) during past three decades has been accompanied by worsening water problems. This paper examines the water-economy nexus of the PRD from the perspectives of both water use and water quality between 1999 and 2015, with a Logarithmic Mean Divisia Index decomposition model as well as an Environmental Kuznets Curve model, in order to assess the sustainable transition of the area. The results show that in this period, while the water dependency of economic development went down by a significant extent, the efficiency gains did not prevail over problems caused by economic scale expansion. However, at the city level, the 2008 financial crisis stimulated an economic transformation of the main economies from being scale-dominated to being efficiency-dominated. From 2009 to 2015, the sewage decreases driven by water dependency of Guangzhou, Shenzhen, and Dongguan outweighed the sewage increases driven by economic scale. While sewage discharge increased, the river water quality of the PRD kept improving. We found an inverted “U”-shaped relationship between GDP per capita and water quality of the PRD, with GDP per capita = ¥14,228.27 as the inflection point for river water quality. Once dubbed the “factory floor” of the world, the PRD has moved into a less environmentally impactful phase of development, with more expenditure on environmental protection and policy reform. However, given the huge and ever-increasing economic and population scales, ensuring a sufficient and safe water supply through industrial recycling and public education, along with even further pollution abatement, will be particularly important.

Long-term variations of the riverine input of potentially toxic dissolved elements and the impacts on their distribution in Jiaozhou Bay, China

The concentrations of the potentially toxic dissolved elements (PTEs) As, Hg, Cr, Pb, Cd, and Cu in the main rivers into Jiaozhou Bay (JZB) during 1981-2006 were measured, and the impact of the fluvial PTE fluxes on their distributions in the bay was investigated. The overall average concentration in the rivers into JZB ranged from 8.8 to 39.6 μg L^-1 for As, 10.1 to 632.6 ng L^-1 for Hg, 4.1 to 3003.6 μg L^-1 for Cr, 8.5 to 141.9 μg L^-1 for Pb, 1.1 to 34.2 μg L^-1 for Cd, and 13.2 to 1042.8 μg L^-1 for Cu. The interannual average concentration variations of the PTEs in these rivers were enormous, with maximum differences of 41-21,680 times, while their relative seasonal changes were far smaller with maximum differences of 3-12 times. The total annual fluvial fluxes for As, Hg, and Cr into JZB exhibited the inverse "U" pattern, while those for Pb and Cd showed the "N" pattern. As a whole, the total annual Cu flux presented a growing tendency from 1998 to 2006. In general, the changing trends of the PTE concentrations in JZB were similar to those of their annual fluxes from the rivers, indicating a great impact of their fluvial fluxes on their distributions in JZB. The annual concentration of Cd in the bay almost remained constant and differed from the fluvial flux of Cd. The diversified pattern of the environmental Kuznets curve (EKC) represented China's approach to industrialization as "improving while developing."