Treatment Of Industrial Pollutants Research Articles

Exploring electromembrane extraction and liquid membrane for efficient removal of heavy metals from aqueous solutions: An overview

Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutants and environmental conditions remains uncharted. Future research must expand EME's applicability, assess its environmental impact versus other methods, and boost scalability, cost-effectiveness, and energy efficiency in industry. Advances in novel liquid membrane materials can enhance extraction efficiency and selectivity, aiming to provide efficient, sustainable industrial pollutant treatment. This research provides a review of the existing practices in the field of liquid membranes when coupled with the application of an electric field.

Spatial green growth in China: exploring the positive role of investment in the treatment of industrial pollution.

The industrial sector of China is critical to the country's economic growth. On the other side, industrialisation has resulted in a high rate of emissions, pushing China to spend extensively on industrial pollution remediation. As a result, this study looks at the relationship between investment completed in the treatment of industrial pollution and economic development. Initially, the study used the global Moran's I test (Queen's contiguity matrix) to find spatial autocorrelation for the 'investment completed in the treatment of industrial pollution' factor, where the study found a positive association across Chinese provinces, and suggest the existence of spatial autocorrelation. Thereafter, a time-fixed effect spatial error model was used due to the lowest Akaike information criterion and Bayesian information criterion to analyse regional data of China from 1999 to 2018. The data reveal a positive association between investment completed in the treatment of industrial pollution and regional economic growth, both in the short and long term. Furthermore, the negative consequences of urban wages and foreign investment on investment completed in the treatment of industrial pollution are having the reverse effect on regional green development, necessitating ecologically friendly actions to mitigate the negative environmental effects of both. The results highlight the need for policymakers in other countries to review their plans for economic expansion and create environmentally friendly legislation. By implementing the Chinese green economic growth model, policymakers in industrially polluting nations can reduce industrial pollution and foster green growth in their nation.

A hierarchically porous and hygroscopic carbon-based catalyst from natural wood for efficient catalytic reduction of industrial high-concentration 4-nitrophenol

4-Nitrophenol (4-NP) with high toxicity and non-biodegradability has been causing a great threat to the environment and human health. Catalytic reduction of high-concentrated 4-NP in wastewater to 4-aminophenol (4-AP) and the subsequent recovery and reuse of catalysts are highly demanded for the practical treatment of industrial pollutants, yet are still limited in low mass transfer efficiency and poor stability of catalysts. Herein, we developed a composite catalyst of Pd nanoparticles (NPs) decorated 3D-activated carbon (Pd/3D-AC) to synergistically catalytic reduce high-concentrated industrial 4-NP (14.38 mM) by using natural wood as a 3D scaffold. The hierarchically porous 3D-AC demonstrates abundant surface-active sites (929 m2·g−1) for adequate and unaggregated anchoring Pd NPs (0.61 %), and the interconnected mass transfer channels and hygroscopic behavior of Pd/3D-AC yield an efficient chemical reaction in solution. As a result, the turnover frequency of the Pd/3D-AC is up to 1.68 min−1, and the synergistic interaction occurs to the 3D-AC and Pd NPs. Even after 10 cycles of catalysis, no deactivation was observed to Pd/3D-AC, demonstrating excellent stability and reusability. Moreover, the Pd/3D-AC catalyst contributes to a high conversion rate to 4-NP, with the yield of obtained 4-AP more than 99.9 % within 10 min. This facile strategy of loading metal nano-catalysts on hierarchically porous wood puts forward a flexible and effective approach for promoting the catalytic performance and the practical treatment of industrial wastewater.

Research on the effect of industrial pollution treatment on organizational stability

The industrial firms are the backbone of the national economy and a prominent source of environmental pollution. Industrial pollution contributes more than half of the total annual emissions of sulfur dioxide (SO2), nitrogen oxides (NOx) and smoke (dust) emissions in China. A large amount of energy consumption and pollution emissions force industrial firms to control pollution. This research focus on the effect of industrial pollution treatment on organizational stability. The results showed that ICSR and ECSR are positively related to organizational stability. Compared with industrial pollution treatment, employees are more concern about ICSR. Firms’ industrial pollution treatment should attention the equilibrium between ICSR and ECSR.

Analysis of Water Resources Carrying Capacity of Coastal Cities along the Yangtze River Based on PSR Model

Xu, M.; Chen, M.; Li, Y., and Jiang, Y., 2020. Analysis of water resources carrying capacity of coastal cities along the Yangtze River based on PSR model. In: Wan, Z. (ed.), Coordinated Sustainable Development in Coastal Areas: Environment and Economy. Journal of Coastal Research, Special Issue No. 109, pp. 110–113. Coconut Creek (Florida), ISSN 0749-0208.The coastal cities along the Yangtze River are relatively rich in water resources but the economy is developed, therefore the contradiction between economic society and water resources still exists. According to the characteristics of coastal cities along the Yangtze River, this paper constructs an evaluation index system for water resources carrying capacity based on the Pressure-State-Response(PSR) framework. Based on typical examples of Nantong City's 2010-2018 relevant index data, using the Analytic Hierarchy Process (AHP) model and with the help of YAAHP software, the following conclusions are obtained: 1) There are pressure state response mechanisms in each element of the water resources carrying capacity system of coastal cities along the Yangtze River. The key to the operation of the system is the limit of water resources carrying capacity. 2) Domestic water demand has the greatest impact on water resources carrying capacity. Domestic water demand has the greatest impact on the carrying capacity of water resources, but in the allocation of water resources, it is important to optimize the production water use of the industrial economy and provide sufficient funds to guarantee.3) During the period of 2010-2018 in Nantong City, with the development of industrial economy, the discharge of industrial wastewater was significantly reduced. Moreover, the investment in the treatment of industrial pollution, especially industrial waste water pollution, has been significantly increased, and the carrying capacity of water resources has been constantly optimized.

Industrial environmental efficiency and its influencing factors in China: analysis based on the Super-SBM model and spatial panel data.

The industry sector is not only an important driving force for economic growth but also the largest sector of resource consumption and pollution emission. In this study, we first constructed a super-slack-based measure (Super-SBM) model including the resource consumption and undesirable outputs, and estimated the industrial environmental efficiency (IEE) in China from 2007 to 2016. Afterwards, based on the spatial autocorrelation test and the spatial Durbin model, the spatio-temporal evolution and the influencing factors of IEE were analyzed. The empirical results are obtained as follows: the average IEE from 2007 to 2016 was 0.5176. IEE in the east of China was the highest, whereas it was the lowest in the west. The spatial autocorrelation test showed that the regions with similar levels of IEE in China had significant spatial agglomeration, whereas the local spatial distribution of IEE was unbalanced. The high-high IEE agglomeration areas were located in Liaoning, Jilin, and Inner Mongolia. The low-low IEE agglomeration areas were concentrated in Gansu, Ningxia, and Sichuan. Finally, according to the spatial Durbin panel model and spillover effect decomposition, GDP, FDI, human capital, environmental governance investment, research and development investment, and urbanization have a positive impact on IEE. The industrial and energy consumption structures have a negative impact on IEE. Therefore, the central government should focus on balancing IEE of different provinces and regions, increasing investment in industrial pollution treatment, and encouraging FDI to improve IEE.

Investigating drivers of CO2 emission in China’s heavy industry: A quantile regression analysis

Abstract High energy-consuming heavy industry is one of the main sources of China’s carbon dioxide (CO2) emissions. Based on 2005–2017 panel data of China’s 30 provinces, this paper uses a quantile regression model to investigate CO2 emissions in the heavy industry. The empirical results show that economic growth exerts a stronger influence on the heavy industry’s CO2 emissions in the 25th-50th quantile provinces, due to the difference in the fixed asset investment and heavy industrial output. The impact of urbanization on CO2 emissions in the 10th-25th quantile provinces is lower than that in other quantile provinces because these provinces have the least number of college graduates. Energy efficiency has a smaller impact on CO2 emissions in the upper 90th quantile province, owing to the difference in R&D personnel investment and the number of patents granted. Similarly, environmental regulations have minimal impact on CO2 emissions in the upper 90th quantile province, since the growth rate of industrial pollution treatment investment in these provinces is the lowest. However, the impact of energy consumption structure on CO2 emissions in the 10th-25th and 25th-50th quantile provinces is the highest, because of the provincial differences in coal consumption.

Green development of Yangtze River Delta in China under Population-Resources-Environment-Development-Satisfaction perspective

This paper explores green development of Yangtze River Delta (YRD) under PREDS (Population-Resources-Environment-Development-Satisfaction) perspective. Based on gray relevance analysis, synergy evaluation model and factor analysis model are constructed with improvement of weight determination and relevance degree calculation. Synergy evaluation results show that for the entire YRD the relevance degree of green development increases strictly. As the synergistic effect of the inner system continues to rise, the green development tend toward equilibrium (2003–2017). The provincial level green development ranking is put forward. The results of factor analysis show that four dimensions' impacts on public satisfaction are different. The prediction of “13th Five-Year Plan” suggests that, improving environmental indicators is the most potential solution to promote green development of YRD. Investment completed in industrial pollution treatment is taken as an example to show how the index will affect satisfaction under different growth rates. It turns out that when the growth rate is below or over the critical value (16%), the influence will go out of the trough and continue to increase, forming a “J” curve.

Effects and Choices of Environmental Pollution Liability Insurance in Provinces of China

China began a pilot application for environmental pollution liability insurance in 2008. Although implementation situations vary substantially in different regions in China, it is appropriate to test how much contribution pollution insurance may make to environmental risk mitigation and other factors. Based on an analysis of pollutant emissions and investment completed in the treatment of industrial pollution, we find that pollution liability insurance, both compulsory and voluntary, does not work as expected in reducing environmental pollution. The value of this insurance mainly lies on the concern of the government for victims in environmental disasters. Considering the high administrative costs, it is not proper to push compulsory insurance across the country indiscriminately. Thus, this paper further classifies all 31 provinces in mainland China according to their economy and pollution characteristics and establishes guidelines for adopting pollution insurance for each province. The result shows that compulsory insurance is unnecessary for most provinces, while voluntary insurance can match their needs better.

A Review on Recognition of Various Peroxidases

Peroxidases, widespread in the biological world, are a kind of oxidoreductases important in biological antioxidant defense systems. For great potential value of them in physiology, biochemistry and treatment of industrial pollutants, etc., they receive extraordinary attention, and also a large number of peroxidases have been found and studied on the nature and catalytic properties of them to date. Especially, horseradish peroxidase is first found and given more researches on the protein structure, catalytic mechanism and practical applications, and even modified by gene engineering and protein engineering to improve its catalytic performance. In addition, also there are numerous peroxidases that are derived from various sources or used for catalytic oxidation of different substrates, which have many differences from horseradish peroxidase in amino acid composition, active site structure, catalytic characteristics and corresponding applications. To better study and selectively employ peroxidases as biocatalysts, it is critical to comprehensively recognize various peroxidases, so as to present a reference for the in-depth and accurate studies on them in the future. In this paper, various peroxidases usually focused by enzymologists are reviewed for better mastering the completed research work on them, understanding the main interests in them, and knowing the advantages and disadvantages of them. Moreover, the research aspects that hereafter may be focused on are prospected.

Has the construction of industrial pollution treatment improved the status of environmental pollution in China?

In recent years, China’s economy has developed rapidly and the people’s material living standards have continued to improve, but environmental problems have gradually become apparent, which seriously threatens people’s daily lives and production. Therefore, the state is actively constructing industrial pollution control projects, hoping to improve China’s environmental pollution status and achieve green development. Based on data from 31 provinces in China in 2017, this paper finds that the construction of wastewater treatment projects significantly reduces wastewater discharge and has a significant effect on improving water pollution; while the construction of waste gas treatment projects does not significantly improve the status of air pollution. Further research found that coal Consumption has significantly increased the level of air pollution and weakened the role of waste gas treatment projects. At the same time, investment in technological innovation has significantly improved the state of environmental pollution.

Industrial pollutant treatment efficiency considering environmental factors

Purpose The purpose of this paper is to improve the accuracy of evaluation efficiency by constructing parallel structures considering the main components of industrial pollutants, and then to consider some external influence factors to eliminate random errors. Design/methodology/approach In this paper, data transformation has been used to deal with undesirable output, and a model with a parallel structure based on the three-stage data envelopment analysis model to calculate the efficiency scores of different division in pollution treatment has been composed. Findings The analysis shows that the external environmental factors and random factors of the economy and society greatly affect the efficiency of industrial pollutant treatment; moreover, there is an imbalance between regions in China in the treatment of industrial pollutants. Originality/value Optimal improvement requires each province to take targeted measures to improve its efficiency of pollutant treatment measures, which are tailored to specific situations and determined by efficiency analysis in this paper.

Measuring and Fitting the Relationship between Socioeconomic Development and Environmental Pollution: A Case of Beijing–Tianjin–Hebei Region, China

The Beijing–Tianjin–Hebei (BTH) region is a top urban agglomeration of China but has the problem of severe environmental pollution. Most of the current researches on the sustainable development of this region only concentrate on the environmental pollution itself and ignore its relationship to the socioeconomic development. In this research, an entropy-based coupling model, a polynomial equation with partial least squares algorithm, and socioeconomic and environmental data in 2006–2015 were used to measure and fit the above relationship. Empirical analysis led to the following conclusions. (1) Beijing, Tianjin, and Hebei presented similar socioeconomic development modes but different environmental pollution modes. (2) The social economy of the BTH region has been developing at the expense of environmental pollution, but the environmental cost has been decreasing year by year. (3) At present, the BTH region has huge potential to improve its environment. (4) Increasing the investment in the treatment of industrial pollution in Tianjin and mitigating the soot (dust) emissions in Tianjin and Hebei are the major environmental policy directions. (5) Controlling the development of smelting and pressing of ferrous metals and other building material sectors in Hebei is the major economic policy direction.

A two-stage DEA model for resource allocation in industrial pollution treatment and its application in China

An increasing amount of resources is being utilized to combat the pollution problem in China. Measuring and improving the efficiency of this resource allocation is an effective way to promote pollution treatment at the present technical level. This paper utilizes a two-stage data envelopment analysis (DEA) model to attain allocation results based on the zero-sum gain and fixed-sum gain assumptions. We divide all the inputs into discretionary and non-discretionary inputs and construct two models for allocating resources based on the environmental efficiency scores. The new models are applied to calculate the performance and resource allocation scheme of 30 Chinese provinces from 2011 to 2015. Most provinces are inefficient at controlling pollution emission or treating pollution while using the given level of input resources. Based on the production possibility set of each province in 2015, the processing capacity of wastewater and gas could be increased by 1% and 3%, respectively, by reallocating resources for pollution treatment among different provinces. Environmental efficiency scores and resource allocation plans based on various assumptions are obtained in this paper to enlighten the corresponding decision-makers.

Analysis on the investment efficiency of industrial pollution control based on Markov and DEA model

Taking the investment amount of industrial “three wastes” pollution control in 2000-2016 as an input indicator, the investment amount predicted by the grey residual GM (1, 1) Markov model is compared with the actual value in 2014-2016 to verify the feasibility and accuracy of the model. Sulphur dioxide removal, smoke (powder) dust removal, industrial wastewater discharge standards and solid waste comprehensive utilization are used as output indicators. The DEA-BCC model is used to calculate the input efficiency of industrial pollution control from 2000 to 2016, and the main factors restricting the effect of pollution control are analyzed, and the forecast model is used to provide basis for improving the input efficiency. The results show that the average comprehensive efficiency of industrial pollution control input from 2000 to 2016 was 0.887. Overall, the comprehensive efficiency is relatively low. The fluctuation of input efficiency fluctuated greatly and is not stable enough. There are only 6 years in DEA effective state. The unstable investment scale, the lack of rational allocation of resources, the shortage of talents and governance technologies and the low level of supervision are the key factors affecting the efficiency of industrial pollution treatment.

Sulfur dioxide (SO2) emissions and government spending on environmental protection in China - Evidence from spatial econometric analysis

This study pays attention to a rarely discussed but important issue regarding the influence of the government's environmental protection expenditure on Sulfur Dioxide (SO2) emissions in China under consideration of the potentially spatial dependence of SO2 emissions. A panel dataset of 30 provinces from 2008 to 2013 is utilized to estimate the panel Spatial Durbin models. The main findings of this study are that SO2 emissions can be effectively reduced by government spending on environmental protection and that the relationship between SO2 emissions and gross regional product (GRP) per capita in China is cubic polynomial (N-shaped). In addition, as direct investment from foreign countries toward China increases, SO2 emissions will be reduced. The trade factor also plays an important and negative role in SO2 emissions. Provinces with higher shares of secondary industries to total GRP will have more SO2 emissions. The investment completed in the treatment of industrial pollution in the private sector can effectively reduce SO2 emissions, and a higher population density causes a reduction in SO2 emissions. The coefficient of spatial autocorrelation ρ is statistically positive, confirming a positive spatial correlation (also meaning a spatial competition) of SO2 emissions among provinces in China. All these conclusions are consistent with those in previous works and with our expectations, and remain the same while a two-stage procedure is applied to cope with the potential endogeneity problem of GRP, with the exception of the effect of population density.

Evaluating industrial economy-ecology-coordinated development level by grey target theory

Purpose – This paper aims to construct evaluation index system of industrial economy-ecology-coordinated development based on “driving-force-pressure-state-impact-response” conceptual model. Grey target theory is introduced to evaluate industrial economy-ecology-coordinated development level and identify its key influencing factors. On that basis, the countermeasures are proposed to improve industrial economy-ecology-coordinated development in China. Design/methodology/approach – Bull's-eye degree of grey target theory is introduced to evaluate industrial economy-ecology-coordinated development level of 31 provinces, municipalities and autonomous regions in China. The contribution degree of influence factors is analyzed by contribution degree theory. Findings – The results show that first, the overall level of industrial economy-ecology-coordinated development in China is not high, there is a big gap of coordinated development level between provinces, municipalities and autonomous region, and there is still a large room to improve the status quo. Second, the major factors affecting industrial economy-ecology-coordinated development are gross industrial output value (GIOV) share of investment completed in the treatment of industrial pollution, common industrial solid wastes produced per GIOV, sulphur dioxide emission per GIOV, energy consumption per 10,000 yuan of gross regional product. Originality/value – This paper constructs evaluation index system of industrial economy-ecology-coordinated development and applies grey target theory to evaluate industrial economy-ecology-coordinated development level and identify its key influencing factors.

Ecological total-factor energy efficiency of regions in China

Most existing energy efficiency indices are computed without taking into account undesirable outputs such as CO2 and SO2 emissions. This paper computes the ecological total-factor energy efficiency (ETFEE) of 30 regions in China for the period 2005–2009 through the slack-based model (SBM) with undesirable outputs. We calculate the ETFEE index by comparing the target energy input obtained from SBM with undesirable outputs to the actual energy input. Findings show that China's regional ETFEE still remains a low level of around 0.600 and regional energy efficiency is overestimated by more than 0.100 when not looking at environmental impacts. China's regional energy efficiency is extremely unbalanced: the east area ranks first with the highest ETFEE of above 0.700, the northeast and central areas follow, and the west area has the lowest ETFEE of less than 0.500. A monotone increasing relation exists between the area's ETFEE and China's per capita GDP. The truncated regression model shows that the ratio of R&D expenditure to GDP and the degree of foreign dependence have positive impacts, whereas the ratio of the secondary industry to GDP and the ratio of government subsidies for industrial pollution treatment to GDP have negative effects, on the ETFEE.