Measuring industrial operational efficiency and factor analysis: A dynamic series-parallel recycling DEA model

In China, industrial pollution has become an urgent problem for policy makers and enterprise managers. To better support industrial development, we need to determine the effectiveness of policies through efficiency evaluation. China’s provincial industrial system consists of two stages: production and emission reduction. The emission reduction stage is composed of three parallel sub stages: solid waste treatment, waste gas treatment and wastewater treatment. In this process, the treatment capacity of industrial wastewater treatment facilities can be used as carry forward variable, which is not only the desirable output of the previous emission reduction stage, but also the input of the current emission reduction stage. Therefore, this paper proposes a dynamic hybrid two-stage data envelopment analysis (DEA) model for eco-efficiency evaluation of industrial systems, and applies it to a case study of Chinese regional industry. Applying the data collected from 2011 to 2015 to the model, the following conclusions can be drawn: (1) During the whole survey period, the average eco-efficiency was 0.9027. The overall eco-inefficiency of China’s provincial industrial system during the study period is mainly due to low efficiency of solid waste treatment and waste gas treatment. (2) The average eco-efficiency of provincial industrial system increased steadily from 2011 (0.6448) to 2014 (0.6777), but decreased slightly in 2015 (0.5908). (3) The carry forward treatment capacity of industrial wastewater treatment facilities has a remarkable impact on provincial industrial system efficiency scores, especially at the wastewater treatment stage (0.6002 vs 0.3691). (4) Provincial industrial system exists distinct geographical characteristics of low efficiency. This study has important guiding significance for policy makers and enterprise managers who are concerned about industrial pollution control.

How to map industrial waste metabolism at a geographical level? A proposal for a composite indicator

Studying economic development in China is a very important topic recently because China's economy is moving toward high-quality development and local governments face the dilemma of environmental governance and economic development. To contribute to the literature in this area further, this paper assesses the impact of tax competition and environmental regulation on high-quality economic development through the spatial Durbin model and instrumental variable and by using the data from 278 prefecture-level and above cities from 2007 to 2017 in China. Our empirical analysis shows that tax competition inhibits high-quality economic development and a positive spatial spillover effect, environmental regulation has a significant direct promoting effect on high-quality economic development and a negative spatial spillover effect, and local government tax competition inhibits the promotion effect of environmental regulation on high-quality economic development. Further heterogeneity analysis conducted in our study shows that both the direct and spatial spillover effects of tax competition and environmental regulation on high-quality economic development in large and medium-sized cities are significantly lower than those in small cities. Our empirical analysis infers that since the 18th National Congress of the Communist Party of China, the promotion effect of environmental regulation on high-quality economic development and the synergistic effect with tax competition has become more and more significant. The findings in our paper are useful for both the central government and the local governments in making better decisions for economic development in China as well as in other countries.

This paper computes efficient three industrial waste abatements (solid, water and gas) for 30 regions in China from 1996–2003. Data envelopment analysis (DEA) with a single output (real GDP) and five inputs (labour, real capital stock, solid wastes, waste water and waste gas) is used to compute the target wastes of each region for each year. The efficient abatement ratios of each region in each year are then obtained by comparing the actual waste to the actual waste of a pollutant. Our major findings are: 1. The east area contains the most efficient regions with respect to the three wastes in every year during the research period. 2. The east, central and west areas have 1996–2003 average target abatement ratios of solid wastes of 24.90%, 64.77% and 62.33%, of waste water 14.27%, 27.45% and 32.01%, and of waste gas 18.42%, 43.21% and 46.66%, respectively. 3. Because the central and west areas have similar critical problems on the three wastes, China is actually divided into two parts considering the three wastes. 4. Compared with the cases of waste water and gas, solid waste reduction is China's most urgent task.

As the land disposal of untreated wastes becomes less acceptable increasing attention is being given by industry and government to alternative hazardous waste treatment and destruction processes. Among these processes are high-temperature incinerators and other thermal process that treat waste streams by exposing the wastes to high temperatures. One of the emerging technologies receiving much attention nowadays is plasma arc technology.

Environmental regulation, land use efficiency and industrial structure upgrading: Test analysis based on spatial durbin model and threshold effect

The DOE Office of Industrial Programs, through the Idaho Operations Office, is sponsoring a program to develop and eventually demonstrate a wet oxidation system for energy production from water borne industrial waste materials and/or low-grade fuels for use in industrial processes. This program is considered a natural extension of previous DOE studies which have evaluated energy production through the wet oxidation of coal and peat. While the results of these studies were favorable for large-scale power generation, the Office of Industrial Programs believes that wet oxidation also has the potential to displace prime fuels on a smaller scale through the treatment of industrial wastes or other low-grade fuels. This report summarizes the feasibility of this program.

How do environmental regulation and environmental decentralization affect green total factor energy efficiency: Evidence from China

Bioelectro Chemical Systems: A Sustainable and Potential Platform for Treating Waste

Strategic interaction in environmental regulation and sulfur dioxide emissions: Evidence from China

Global warming continues to be an intimidating factor for environmental protection, and reducing carbon emissions is an effective way to deal with the phenomenon. However, the energy sector is a significant contributor to greenhouse gas emissions. Therefore, investment in environmental regulations and research and development (R&D), is critical for fostering a low-carbon growth model. This study focuses on 30 provinces in China from 2004 to 2019. We used the spatial Durbin model to investigate how the spatial spillover effect of R&D and environmental regulation impacts carbon emissions. In addition, we applied the dynamic threshold panel model to mitigate potential problems of endogeneity. The results reveal that carbon emissions have a considerable spatial correlation in both temporal and spatial dimensions, exhibiting high and low-value accumulation characteristics. Furthermore, the combined effect of R&D intensity, environmental regulation, and energy consumption were found to contribute to the increase in carbon emissions across China's provinces, and they also suggest different influencing mechanisms. The spillover effects of increased carbon emissions in neighboring regions also contribute to the increase in local carbon emissions. The study also found that R&D and stringent environmental regulations measures strongly moderate the link between energy consumption and carbon emissions. In promoting carbon reduction, by breaking the dynamic equilibrium in China, the provincial investment outflow on R&D intensity could be optimized, and the regional levels should focus more on tightening environmental regulatory measures and promoting the development of energy-conserving technologies.

Using prefecture-level panel data and social media data, this study investigates how industrial agglomeration, environmental regulations, and technology affect the pollutant intensity and spillover channels of pollutant emissions by integrating social and economic networks into a Spatial Durbin Model. The results show that industrial agglomeration, environmental regulations, and technological inputs facilitate the emissions intensity abatement. The outcomes also confirm that these factors affect the intensity of pollutant emissions in neighboring regions through social, economic, and spatial networks. Agglomeration has a negative spillover effect on the intensity of pollutant emissions in surrounding cities via social and spatial networks, while environmental regulations affect pollutant emissions intensity in related cities through social networks. Technology can effectively lower pollutant emissions through economic networks. These findings highlight the network linkages and spillover channels affecting the intensity of pollutant emissions.

The electricity power (EP) industry, a primary source of emissions, significantly affects China's energy conservation and reduction efforts. The Chinese government has introduced various regulatory policies to limit the emissions and waste generated by the EP industry. This paper intends to assess the influence of environmental regulation (ER) on the environmental efficiency (EE) within China's EP sector, particularly concerning spatial spillover effects. The slack-based and the spatial Durbin models are applied to quantify EE and analyze the nonlinear connection between ER and EE. Some findings are summarized below. First, the EE of China's EP industry has significant regional heterogeneity and exhibits a positive spatial agglomeration effect of EE. Second, the influence of ER on EE in local provinces shows a U-shaped relationship, while it exhibits an inverted U-shaped effect in neighboring provinces. Third, ER can indirectly drive EE in the local province by affecting technological innovation. Finally, policy recommendations are offered to enhance the EE in China's EP industry.

Based on machine learning model for prediction of CO2 adsorption of synthetic zeolite in two-step solid waste treatment

At present, the world is committed to the development of environmentally friendly, sustainable and industrial safety. The effective treatment of industrial solid waste can be applied in the field of industrial safety. It is one of the ways to apply industrial solid waste to industrial safety to modify industrial solid waste and combine active powder to prepare industrial solid waste-based composite powder explosion inhibitors and apply it to underground coal dust explosion. This paper introduces the modification and preparation methods of industrial solid waste, and analyzes the good explosion suppression effect and good economic benefit of industrial solid waste-based composite powder explosion inhibitors on coal dust explosion. In this paper, four kinds of industrial solid wastes (red mud, slag, fly ash and sludge) were modified, and the modified solid waste materials with good carrier characteristics were obtained. Combined with a variety of active powders (NaHCO3, KH2PO4 and Al(OH)3), the industrial solid waste-based composite powder explosion inhibitors were obtained by solvent-crystallization (WCSC) and dry coating by ball milling (DCBM). Those kinds of explosion inhibitors can suppress the explosion of pulverized coal in 40–50% of cases. Compared with the powder explosion inhibitor commonly used in industry, it has a lower production cost and better explosion suppression effect. Those kinds of explosion inhibitors have a good industrial application prospect.