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This paper explores the impacts of industrial collaborative agglomeration on industrial sulfur dioxide intensity from a spatiotemporal perspective based on panel data on the 284 prefecture-level cities from 2003 to 2019, with systematic consideration of the underlying mechanism of channels and actions. The empirical results show that industrial co-agglomeration significantly intensifies industrial SO2 intensity, especially with increasing agglomeration. In addition, its positive spatial spillover effects are established in geographical proximity to the city. Furthermore, the channel analysis shows that the industrial structure path, industrial efficiency path, and industrial scale path account for a sharp increase in industrial SO2 intensity. The market forces reverse and moderate this exacerbating process more significantly than the government does, which provides evidence for the importance of pursuing a dynamic equilibrium between them. Finally, there exist heterogeneous effects across cities with different administrative levels, innovation capacities, and macropolicies of special emission limits for air pollutant policy. While arguing for the environmental pollution effects of industrial co-agglomeration, this paper also provides solid support and a new perspective for promoting sustainable economic development and achieving win–win economic and environmental benefits. [ABSTRACT FROM AUTHOR]

In urban areas, primary and secondary organic aerosols are typically considered to originate from vehicular traffic emissions. However, industrial emissions within or in the vicinity of urban areas may also be significant contributors to carbonaceous aerosol concentrations. This hypothesis was tested and validated in two urban areas in Spain. The observed unusual dominance of organic carbon (OC) over elemental carbon (EC), the analysis of the variability of OC, EC and OC/EC and their correlation with transport patterns suggested the presence of OC sources associated with industrial activities. A methodology based on chemical speciation of particulate matter (PM) followed by the application of receptor modelling techniques allowed for the identification of the specific industrial sources of OC, which were linked to primary OC emissions from a grain drying plant (cereal) and to secondary OC formation from paper production activities (paper mills), as well as from urban sources and biogenic emissions. This work presents an integrated approach to identifying and characterizing of industrial sources of carbonaceous aerosols in urban areas, aiming to improve the scarce body of literature currently available on this topic. [ABSTRACT FROM AUTHOR]

China has long exercised environmental control through the imposition of sewage charges. The start of the environmental protection tax on January 1, 2018, means that China has entered a new phase of environmental control. Unlike many previous studies on the role of environmental taxes at the firm level, this paper examines whether environmental taxes affect pollution emissions by influencing the behavioral choices of micro-actors. This paper first reviews the Pyrrhic tax, the Porter hypothesis, and the "double dividend effect." We then construct provincial panel data for 30 provinces in China from 2012 to 2019 as a sample, use the environmental protection tax as a natural experiment to evaluate the policy of this environmental protection tax using propensity score matching and difference-in-differences model, investigate the intermediate transmission mechanism of the policy implementation, and then analyze the differences in policy effects between provinces with different levels of economic development. The increased tax burden in 2018 led to a general reduction in provincial pollution emissions in which technological innovation by various groups, including firms and universities, had a mediating role. [ABSTRACT FROM AUTHOR]

The paper reviews the existing applications of sensing technologies for measuring construction off-road vehicle emissions (COVE) such as earthmoving equipment. The current literature presented different measurement methods and reported the results of utilisation of new technologies for measuring COVE. However, previous papers used different technology applications covering only a part of the monitoring process with its own limitations. Since technologies are advancing and offering novel solutions, there is an urgent need to identify the gaps, re-evaluate the current methods, and develop a critical agenda for automating the entire process of collecting emissions data from construction sites, and monitoring the emission contributors across cities. This paper systematically identifies relevant papers through a search of three key databases—Web of Science, Engineering Valley and Scopus—covering the publications in the last decade from 2008 to 2017. An innovative robust research method was designed to select and analyse the relevant papers. The identified papers were stored in a data set, and a thematic algorithm employed to find the clusters of papers which might be potentially relevant. The selected papers were used for further micro-thematic analysis to find key relevant papers on COVE, and the gap in the literature. A sample of relevant papers was found relevant to COVE and critically reviewed by coding and content analysis. This paper critically reviews the selected papers and also shows that there is a considerable gap in the applications of new technologies for measuring in-use COVE in real time based on real activities toward automated methods. This review enables practitioners and scholars to gain a concrete understanding of the gap in measuring COVE and to provide a significant agenda for future technology applications. [ABSTRACT FROM AUTHOR]

Industrial symbiotic agglomeration is important for promoting the circular economy and reducing pollution emissions. This paper examines the effects of industrial symbiotic agglomeration on pollution emissions using the staggered difference-in-difference model. The findings suggest the following: (1) industrial symbiotic agglomeration reduces total urban pollution emissions, with significant reductions in SO2 and wastewater, although not in solid waste and PM2.5 emissions. (2) The emission reduction effect is achieved mainly through green innovation, the recycling effect, and structural optimization, whereas the cost reduction effect of symbiotic agglomeration is not obvious. (3) Industrial symbiotic agglomeration promotes emission reduction in neighboring cities within a 300-km range, and this reduction decays with geographical distance. In addition, the pollution emission reduction effect of industrial symbiotic agglomeration is only realized when its size reaches 187.17 km2, with the effect becoming stronger as the size increases. At present, industrial symbiotic agglomeration mainly plays an emission reduction effect in non-resource cities. This paper provides a new way to promote the green development of industry and region. [ABSTRACT FROM AUTHOR]

The global warming caused by greenhouse gas emissions has received widespread attention from all around the world. In this regard, how to calculate the carbon footprint (CF) scientifically and accurately produced by human activities to achieve emission reduction goals has been widely discussed by scholars. In recent years, related research on this issue has increased, leading to a significant expand in the number of publications. It is necessary to excavate and summarize the current development status and possible future trends of this field based on quantitative methods. To achieve this goal, this paper develops a main path analysis (MPA) of the entire field and three research sub-topics (agriculture, energy fuels, and business economic) based on the 4973 papers extracted from Web of Science (WoS) database. The results show that the CF domain mainly focuses on optimizing the CF calculation methods from a theoretical perspective to improve the accuracy of estimation. Furthermore, scholars engaged in the agricultural research mainly focus on adjusting the life cycle assessment (LCA) model, which has advantage on microlevel CF accounting, according to actual needs to achieve more accurate predictions, while researchers who pay attention to the topic of business economic are committed to improving the input–output model, which is suitable for meso and macro analysis, to enhance accounting accuracy. In general, this article is beneficial for presenting the intellectual structure and knowledge diffusion trajectories of the CF domain from horizontal and vertical perspectives. [ABSTRACT FROM AUTHOR]

Many alternative fuel technologies have been studied for the transport sector to increase its sustainability while reducing costs, greenhouse gases (GHG), and air pollution emissions. Nevertheless, conventional diesel is still the predominant fuel for heavy-duty trucks. Road freight transport consumes 25% of the world's energy and is responsible for emissions with local health impacts and the global greenhouse effect. In this context, this paper reviewed items from 2015 to 2020 to analyze the technologies available for the road freight transport regarding pollutant and GHG emissions. Results are presented in two parts: first quantitatively, quantitative data was extracted from reviewed papers and statistically treated and, second, qualitatively through a comparative chart, which shows the impact on air pollutants from the use of a different type of fuels. In general, papers are mostly concerned with particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), and hydrocarbons (HC) emissions due to its impact on public health, with a low number of papers covering GHG emissions. The trade-off between different fuels and how this process can impact emissions, sometimes increasing or decreasing specific pollutants, is discussed. According to the analyzed papers, the main characteristics that affect the pollutant emissions are, in general, the fuel oxygen content and the combustion chamber temperature. [ABSTRACT FROM AUTHOR]

The goals of this paper are to examine whether the environmental Kuznets curve (EKC) holds and to investigate whether renewable energy consumption can decrease CO2 emissions in the USA using monthly data spanning the period 2000:M01–2018:M07. For these purposes, the paper employs a cointegration test with a regime shift and observes the long-run coefficients before and after the regime shift. The findings support the presence of the EKC. The findings also indicate that renewable energy consumption has negative effects on CO2 emissions, while these effects are greater when the share of renewable energy consumption in total energy consumption is higher in the USA. Theoretical and practical implications for these findings are discussed. [ABSTRACT FROM AUTHOR]

Given the global ecological environment deteriorating, the ESG (environmental, social, and governance) concept advocates that economic growth and environmental protection must go hand in hand. Green taxations, in particular, are critical to economic development as they serve as a key lever for the government in regulating the national economy and improving environmental quality. This paper aims to examine the pollution reduction effect of green taxation in China. We constructed fixed effect model using provincial panel data from 2012 to 2017 to empirically examine the effect of green taxation—including environment protection tax, consumption tax, resource tax, and vehicle purchase tax—on pollution emissions. The findings show that environmental protection tax has a significant inhibitory effect on exhaust gas emissions but a poor inhibitory effect on wastewater and industrial solid waste emissions. Other green taxations—consumption tax, resource tax, and vehicle purchase tax—do not have an ideal inhibitory effect on pollution emissions. The paper concludes with policy recommendations organized around improving the environmental protection tax, actively promoting the ESG concept, and optimizing the top-level design of the green taxation system. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to quantify the level of new-type urbanization and unravel the spatial and nonlinear effects of new-type urbanization and technological innovation on industrial carbon emissions. Although the impact of traditional urbanization levels on carbon emissions has been widely studied, there is still a huge room for optimization, and the impact of new-type urbanization on carbon emissions has not yet been clarified. Selecting 37 cities in the Yangtze River Delta as a research sample, this paper measures the new-type urbanization based on an evaluation system we build. Consequently, we assess the spatial and nonlinear effects of new-type urbanization and technological innovation on carbon emissions by the spatial Durbin model and non-parameter addictive model, respectively. The results indicate that the new-type urbanization and low-carbon city pilot policy have significant spatial spillover effects on reducing carbon dioxide emissions, while the economic growth plays a positive role in increasing carbon emission. As for nonlinear effects, there is a significant inverted "N"-shaped relationship between the level of new-type urbanization and carbon dioxide emissions, while the nexus between technological innovation and carbon emissions is an inverted "U"-shaped relationship. This paper provides a new perspective for confirming the mechanism of the new-type urbanization on carbon emissions. Meanwhile, these findings are of significance for the relevant authorities in China to develop appropriate policy in carbon dioxide emission reduction. [ABSTRACT FROM AUTHOR]

This paper analyzes the impacts of the per capita income, the per capita energy consumption, and the trade openness on the level of per capita carbon emissions in the panel dataset of 35 Organization for Economic Cooperation and Development (OECD) countries over the period 1960-2013. Along with the nominal trade openness, the paper uses a different trade openness measure, so called as the 'trade potential index' (TPI). To the best of our knowledge, this is the first paper that uses the TPI in the empirical environmental Kuznets curve (EKC) hypothesis literature. The paper finds that the EKC hypothesis is valid and there is an 'inverted-U' relationship between the income and the carbon emissions. In addition, the paper observes that there is a positive effect of the energy consumption on the carbon emissions. Furthermore, the results indicate that both trade openness measures are negatively associated with the carbon emissions in the OECD countries in the long run. [ABSTRACT FROM AUTHOR]

With the rapid growth rate of China's economy, the extensive pattern of economic growth of "high energy consumption and low output" has magnified the constraints of energy issues on China's economic development and environmental protection, which highlights the importance of improving energy efficiency. As one of the three major economic zones in China, the Pearl River Delta region also faces high energy consumption and pollution emissions while developing at a high speed. Hence, improving the energy efficiency of the Pearl River Delta region is needed, as it not only is conducive to driving its development of the surrounding green economy, but also promotes the subsequent sustainable economic development. However, there are few literatures on the calculation and analysis of energy efficiency in the Pearl River Delta, and lacking a systematic analysis of input–output index system of energy efficiency measurement. Therefore, this paper calculates the energy efficiencies and the Malmquist indexes based on the panel data of the nine cities in the Pearl River Delta from 2005 to 2019 through super-efficiency SBM model and Malmquist index method by using MAXDEA and MATLAB software. The result illustrates that all regions in the Pearl River Delta except Guangzhou and Shenzhen show obvious energy inefficiency, which is mainly caused by the imbalance between technical efficiency and scale efficiency. Based on the calculation results, this paper gives some relevant suggestions for the further approach of energy reform in the Pearl River Delta according to the calculation results. [ABSTRACT FROM AUTHOR]

One essential component that reflects the development of society and the economy of most countries is life expectancy (LEXP). Nevertheless, LEXP can be influenced by varying factors, including socioeconomic and medical factors. Therefore, this analysis's focal point and motivation is to explore how socioeconomic factors such as economic growth, technological innovation, carbon emission, human capital, and renewable energy affect LEXP. The study utilized panel data from 1990 to 2020 from the North American Free Trade Agreement (NAFTA), which consists of the USA, Mexico, and Canada. The initial test confirmed that the research series were stationary and cointegrated. Therefore, the research applied the cross-sectional autoregressive distributed lag (CS-ARDL) model to predict the paper's short- and long-term estimates. The empirical estimated model concluded that human capital, renewable energy, technological innovation, and economic growth boost life expectancy. Contrarily, the outcome espoused that carbon emission has an inverse association with LEXP. The causality test confirmed a unidirectional interaction between human capital, economic growth, technological innovation, and life expectancy. On the other hand, there is a bidirectional connection between carbon emission, renewable energy, and life expectancy. The research suggests that stakeholders and policy-makers strengthen and enforce air quality standards to reduce pollution from industrial emissions and vehicle exhaust and encourage using cleaner technologies to promote LEXP. The research outcome is empirically and theoretically consistent, providing an essential breakthrough for environment-health-energy and economic development policies. [ABSTRACT FROM AUTHOR]

At present, the life and production of our society are still accompanied by high pollution emissions. The proposal of the "double carbon" goal puts forward clearer requirements for China's energy conservation and emission reduction process. To cope with stricter green development requirements, green finance came into being, contributing a new path to the realization of the "double carbon" goal. This paper is based on the panel data of 30 provinces and cities in China (except Tibet, Hong Kong, Macao, and Taiwan) from 2011 to 2020, using the fixed effect model, threshold model, mediator model, and SDM model to study the impact of green finance on carbon neutralization capacity and its impact path based on reasonable measurement of regional green finance development level and carbon neutralization capacity. The study found that due to the existence of the "green paradox" and "forced emission reduction", China's green finance has a significant positive U-shaped impact path on carbon neutralization capacity; at the same time, informal regulation has a significant single-threshold effect in this path. When informal regulation crosses 0.47, the impact of green finance on carbon neutralization capacity will change from negative to positive, overcoming the impact of the "green paradox"; there is a nonlinear mediating effect of marketization level and technological innovation in the path of green finance affecting carbon neutralization capacity. In addition, green finance not only affects local carbon neutralization capacity but also has a positive spillover effect on neighboring regions. [ABSTRACT FROM AUTHOR]

The present article evaluates establishment of development zones and its association with carbon emissions. In the process of industrialization, carbon emissions in underdeveloped regions of the world increase with economic growth. In order to promote economic growth in the western region and strengthen the management of enterprise pollution emissions, the Chinese government has set up hundreds of development zones. Existing research shows that development zone establishment can promote economic growth; however, literature is scarce when the relationship is tested across region. Based on the panel data of five provinces with relatively backward economy in western China from 2001 to 2017, this paper constructs a "multi-period difference-in-difference" (DID) model with the establishment of development zones as a "quasi-natural experiment" to test the relationship. Findings reveal that development zone establishment increases carbon emissions in the region, and has a significant inhibitory effect on carbon emissions at national level. The conclusions of this paper provide empirical evidence and policy implications for reducing carbon emissions in economically underdeveloped areas. [ABSTRACT FROM AUTHOR]

This paper aims to revisit the interdependency between business conditions, climate policy change, and the environmental pollution of the USA. Interestingly, our paper represents a completion to the existing literature on three levels at least. First, we propose to analyze this issue during normal periods and periods of turmoil, particularly the COVID-19 outbreak. To do so, contrary to previous studies that used economic growth, we employ the ADS index as a real-time business conditions measurement. Second, we employ a frequency approach, based on the continuous wavelet transform, allowing us to understand the nature of the relationship. Understanding whether the relationship holds in the short- or long-term is useful for policymakers in monitoring public policies to achieve CO2 emission reduction as well as to investors interested in high value-added projects. Our analysis shows that, during the last two decades, the relationship between business conditions as well as climate uncertainty index and CO2 emissions is observed during the long- and short-term, and driven through economic conditions. However, during the crisis periods, the effect is detected across various scales and the relationship is bi-directional. Our results have several practical implications for the US policymakers to consider when setting policies for fighting pollution emissions and environmental protection. [ABSTRACT FROM AUTHOR]

Urban carbon emissions are one of the most important areas contributing to the growth of carbon emissions, and resource-dependent cities with natural resource extraction and processing as their leading industries tend to have higher carbon emissions. Ordos is the city with the highest coal production in China, and its economic development is dominated by coal, oil and gas, and other resource extraction and processing industries, with industrial activities making a large contribution to carbon emissions. At the same time, Ordos has undergone rapid industrialization in recent years, but still faces the problem of environmental pollution, epitomizing a typical resource-dependent city in China. Therefore, this paper takes Ordos as an example and uses the Generalized Divisa Index Method (GDIM) to study the drivers of industrial carbon emissions in Ordos from 2005–2020, a typical resource-dependent city in China, and further analyzes are conducted in relation to the three phases of development. Based on the key drivers, the Monte Carlo method is used to forecast industrial carbon emissions from 2021 to 2030. The results show that the most important factors driving the growth of industrial carbon emissions are the scale of industrial output and industrial energy consumption, while the intensity of industrial energy investment is the most important factor mitigating industrial carbon emissions, and that energy efficiency and carbon intensity of energy consumption can also mitigate carbon emissions after economic transformation. At the same time, investment is the factor with the greatest potential for optimization on the path to emissions reduction. [ABSTRACT FROM AUTHOR]

The topic of grain production and quality has always been a fundamental issue for the country's livelihood. With the purpose of contributing to high-quality grain development and ensuring national food security, this paper explores the spatial and temporal evolution, regional differences and convergence of grain green total factor productivity (GTFP) in the main grain-producing regions of China from the dual perspectives of carbon emissions and surface pollution with the help of EBM-GML model, kernel density function estimation and convergence methods. The results show that (1) Grain GTFP has generally shown a positive growth trend, although there exists obvious spatial differences. (2) In terms of decomposition indices, technological progress is the source of the increase in grain GTFP. (3) There are σ convergence, absolute β convergence and conditional β convergence in the main producing region as well as in the Yellow River basin and the Yangtze River basin; there are only absolute β convergence and conditional β convergence in the Songhua River basin. Grain GTFP has a single high-efficiency convergence point, and the grain GTFP is enhancing year by year in each province, and the inter-provincial gap is shrinking. [ABSTRACT FROM AUTHOR]

Industry is a core area to achieve the carbon neutrality target for most developing countries including China. Hence, it is of great practical significance to study the spatio-temporal characteristics of China's industrial carbon intensity and its evolution. The exploratory spatial data analysis methods were adopted to conduct global and local spatial correlation analysis in this paper. The result shows that (1) the industrial carbon emission intensity decreases year by year, with high industrial carbon emission intensity in the West and low in the East. (2) There is a correlation in the spatial distribution of industrial carbon intensity, with the Moran index experiencing the stage of descending first and then ascending. (3) The local spatial clustering of industrial carbon intensity is obvious. (4) Half of the provinces have experienced a leap, with the majority located in the western part of China. Based on these findings, it is concluded that industrial emission reduction policy synergy between provinces is particularly important, such as low-carbon industrial production policy and green industry development policy. [ABSTRACT FROM AUTHOR]

Under the policy background of "joint prevention and control" of global greenhouse gas emission reduction and regional air pollutants, the power industry, as an important target industry of energy conservation and emission reduction policies, has become an effective choice to release dual pressures. In this paper, the "bottom-up" emission factor method was used to measure the emission of CO2 and NOX from 2011 to 2019. Then, the contributions of six factors to NOX emission reduction in China's power industry were identified using the Kaya identity and logarithmic mean divisia index (LMDI) decomposition methods. The research results show that (1) there is a significant synergistic emission reduction effect between CO2 emission reduction and NOX emission reduction; (2) the factor that inhibits the growth of NOX emissions reduction in the power industry is economic development factor; and (3) the main factors that promote the reduction of NOX emission from the power industry are synergy effect, energy intensity, power generation intensity, and power production structure factors. Several suggestions are proposed, which are the power industry should adjust its structure, improve energy intensity, focus on applying low-nitrogen combustion technology, and improve the air pollutant emission information disclosure system to reduce NOX emissions. [ABSTRACT FROM AUTHOR]

Carbon emissions are a critical concern in the realm of energy consumption, with many nations committed to curbing them and striving for carbon neutrality. This research addresses a specific gap in the literature by focusing on carbon emission reduction in the industrial sector through the application of supply chain management (SCM) principles under a monopolistic competition context and by utilizing carbon neutral indicators. Specifically, we develop a mathematical model integrated into an agent-based simulation framework and employ experimental design methods to determine the most optimal decision-making processes for incorporating supply chain carbon neutral indicators. Our findings highlight the effectiveness of two specific carbon neutral indicators within SCM: green-credit policies and the promotion of green products. These measures contribute significantly toward reducing global carbon emissions. This paper offers insights for government decision-makers regarding ideal implementation levels and strategies for green credit policies and the promotion of green products within supply chain environments. It also provides guidance to manufacturers on how to achieve profit maximization while progressing towards carbon neutrality. [ABSTRACT FROM AUTHOR]

The surge of carbon dioxide emission plays a dominant role in global warming and climate change, posing an enormous threat to the development of human being and a profound impact on the global ecosystem. Thus, it is essential to analyze the carbon dioxide emission change trend through an accurate prediction to inform reasonable energy-saving emission reduction measures and effectively control the carbon dioxide emission from the source. This paper proposed a hybrid model by combining the random forest and extreme learning machine together for the carbon dioxide emission forecasting in this paper; the random forest is applied for influential factors analysis and the extreme learning machine for the prediction. To improve the performance of the prediction model, moth-flame optimization is adopted to optimize initial weight and bias in extreme learning machine. A case study whose data is derived from Hebei Province, China, during the period 1995-2015 is conducted to verify the effectiveness of the proposed model. Results show that the novel model outperforms the compared parallel models in carbon dioxide emission prediction and has the potential to improve the accuracy of CO2 emission forecasting. [ABSTRACT FROM AUTHOR]

The calculation of marginal abatement costs of CO2 plays a vital role in meeting China’s 2020 emission reduction targets by providing reference for determining carbon tax and carbon trading pricing. However, most existing researches only used one method to discuss regional and industrial marginal abatement costs, and almost no studies predicted future marginal abatement costs from the perspective of CO2 emission efficiency. To make up for the gaps, this paper first estimates marginal abatement costs of CO2 in three major industries of 30 provinces in China from 2005 to 2015 based on three assumptions. Second, based on the principle of fairness and efficiency, China’s 2020 emission reduction targets are decomposed by province. Based on the ZSG-C-DDF model, the marginal abatement costs of CO2 in all provinces in China in 2020 are estimated and compared with the marginal abatement costs of 2005 to 2015. The results show that (1) from 2005 to 2015, marginal abatement costs of CO2 in all provinces show a fluctuating upward trend; (2) compared with the marginal abatement costs of primary industry or tertiary industry, most provinces have lower marginal abatement costs for secondary industry; and (3) the average marginal abatement costs of CO2 for China in 2020 are 2766.882 Yuan/tonne for the 40% carbon intensity reduction target and 3334.836 Yuan/tonne for the 45% target, showing that the higher the emission reduction target, the higher the marginal abatement costs of CO2. (4) Overall, the average marginal abatement costs of CO2 in China by 2020 are higher than those in 2005-2015. The empirical analysis in this paper can provide multiple references for environmental policy makers. [ABSTRACT FROM AUTHOR]

Cobalt recycling is important for solving environmental problems such as resource shortage and pollution emissions. This paper quantifies the positive significance of cobalt recycling on resource replenishment and pollution emission by using the substance flow analysis and life cycle analysis. The results show that the proportion of recycled cobalt supplied as cobalt raw material is 7.1%, which improves the supply structure of the resource. Meanwhile, the environmental impact of recycling cobalt using the combined treatment process is low. The environmental impact of mining cobalt from mines is about 4.03–41.53 times that of recycling cobalt from cobaltiferous waste materials. However, the overall cobalt recycling is not ideal. First, the cobalt recycling rate is growing slowly. From 1994 to 2020, 245,132 t of cobalt-containing final products entered waste management in China. However, only 79,593 t of cobalt have been recycled, with a recycling rate of 32.47%. Secondly, many recycling enterprises only carry out recycling for a certain type of cobaltiferous waste materials due to the non-uniform cobalt recycling process. Finally, China's cobalt recycling policy does not divide the recycling channels for cobalt waste and does not regulate the specific process. In the future, China should set up separate recycling systems for cobaltiferous waste materials according to different categories and consider adopting combined treatment processes. China can only promote the sustainable use of cobalt if it ensures stable and orderly cobalt recycling in terms of policy and technology. [ABSTRACT FROM AUTHOR]

To solve coordination between economic development and pollutant emissions, it is necessary to face the innovation problem of energy saving and emission reduction. Promoting the effective integration of tech and the financial system is an effective way to solve this problem. According to panel data for prefecture-level cities in China, this paper is based on the pilot policy of combining science and technology with finance implemented in 2011 as a quasi-natural experiment and uses the difference-in-differences (DID) method to evaluate the impact of Science and Technology Financial Policies (STFP) on the air pollutant emission, meanwhile, considering the spatial overflow effect of policy implementation. The research results show that: (1) The STFP has certain inhibitions on pollutant emissions, and this finding holds after a series of robustness tests. (2) The policy has different effects on cities that have different scale, different regions, and different government efficiency. (3) From the results of mechanism analysis, the policy mainly enhances regional pollutant emission reduction capacity through ways such as increasing regional green total factor productivity, enhancing regional science and technology levels, and promoting regional industrial structure optimization. (4) The policy shows a negative spatial spillover effect in reducing pollutant emissions. [ABSTRACT FROM AUTHOR]

This paper discusses the effect of network infrastructure on environmental pollution reduction and the realization mechanism behind it. Based on the panel data of 285 cities in China from 2005 to 2019, this study regards the "Broadband China" pilot policy as a quasi-natural experiment to clarify the pollution emission reduction effect of network infrastructure construction through differences-in-differences method and other methods. The research results show the following: (1) The Broadband China pilot policy has reduced environmental pollution, that is, the construction of network infrastructure has the effect of environmental pollution reduction. The conclusion is still established after a series of robustness tests such as parallel trend test, placebo test, and instrumental variable method. Through the heterogeneity test, it is found that the pollution reduction effect of network infrastructure construction is more obvious in non-resource-based cities, first and second tier cities, and cities in the eastern region (2). The construction of network infrastructure plays a restraining role on local environmental pollution. Due to the insufficient level of regional linkage and the siphon effect of pilot cities, the spatial spillover characteristics of the pollution reduction effect are not obvious (3). The mechanism of action shows that green innovation is an important mediating effect mechanism for network infrastructure construction to reduce environmental pollution. Cities in regions with high degree of marketization and environmental regulation can strengthen the effect of network infrastructure construction on environmental pollution reduction. The research conclusions are conducive to accelerating the development of the digital economy represented by the construction of network infrastructure and provide a useful reference for promoting the level of environmental pollution reduction and achieving high-quality development. [ABSTRACT FROM AUTHOR]

The thermal power industry takes the important social responsibility of energy conservation and environmental protection. The carbon emissions made by the thermal power industry are affected by the industrial structure. In this paper, the carbon emission of thermal power generation is divided into three links: energy combustion, desulfurization process, and power transportation. The total carbon emission of thermal power in 11 provinces in western China from 2000 to 2017 is calculated. Combined with industrial reform, this paper constructs a panel data fixed effect model to systematically analyze the interactive response relationship between thermal power carbon emission and industrial structure in the western region. The research shows that due to the continuous expansion of hydropower, wind power, and other new energy power generation scale and the improvement of energy efficiency in the western region, the growth trend of thermal power carbon emission has slowed down since 2010. The industrial development pattern is the main driving force of regional economic development, and the secondary industry in the western region is the main driving factor of thermal power carbon emission. High quality economic development in the western region can be promoted through technological upgrading, new energy development, and industrial multi-mode operation. [ABSTRACT FROM AUTHOR]

Combined thermal power (CHP) production mode plays a more important role in energy production, but the impact of its pollutant emission on the natural environment is still difficult to eradicate. Traditional pollutant control adopts post-treatment process to degrade the generated pollutants, but there is little research on controlling the generation of pollutants from the source. Therefore, starting from the source, this paper predicts the pollutants through the prediction model, so as to provide countermeasures for production regulation and avoiding excessive emission. In this paper, a pollution emission prediction method of CHP systems based on feature engineering and a hybrid deep learning model is proposed. Feature engineering performs multi-step preprocessing on the original data, refines the correlation factors, and removes redundant variables. The hybrid deep learning model has a multi-variable input and is established by combining the convolutional neural network, long short-term memory network with the attention mechanism. The case study is conducted on the collected actual dataset. The influence of the prediction target periodicity on the prediction results is analyzed seasonally to verify the effectiveness of the hybrid model. The results show that the root mean square error of the proposed method is less than one, and the error is reduced compared to the other basic methods, which proves the superiority of the proposed pollution emission prediction method over the existing methods. [ABSTRACT FROM AUTHOR]

To promote sustainable water resource management, the Chinese government has enacted restrictive policies and targets in terms of total water usage, water intensity, and pollution emissions. While data envelopment analysis (DEA) has been extensively adopted in assessing industrial water resource systems, previous studies have not integrated the realistic constraints on total water consumption and total pollution emissions into a unified framework. This paper examines the system as a two-stage process of water use (WU) and water pollution abatement (WPA), where fixed-sum constraints are imposed on both water consumption and pollution emissions. To address such two-stage DMUs with fixed-sum inputs and fixed-sum outputs, we propose a novel two-stage fixed-sum DEA approach and apply it to evaluate the performance of industrial WU-WPA systems for 29 provinces in China from 2014 to 2018. The results are as follows. From the overall efficiency perspective, the industrial WU-WPA system in China is overall efficient, but provincial overall efficiency polarizes with 19 provinces evaluated as overall inefficient. From a time perspective, overall efficiency shows an increasing then decreasing or descending trend nationally and across the 16 provinces; on the national average, WPA efficiency shows an increasing and then decreasing trend, while WU efficiency demonstrates consistent improvement over time and surpasses WPA efficiency after 2016. In terms of the four areas, regional disparities in the overall efficiencies are converging; for both the whole system and the sub-stage, the eastern area performs the best, followed by the western, northeastern, and central areas. Based on the empirical results, suggestions for improving industrial water resource management are given at the national, regional, and provincial perspectives respectively. [ABSTRACT FROM AUTHOR]

Whether logistics agglomeration and pollution reduction can form a perfect combination in space is one of the important breakthroughs for the successful green transformation of the logistics industry in the future. This paper attempts to clarify the nonlinear change law of logistics agglomeration evolution on environmental quality in China and further clarify the interpretation of informatization and legalization factors on macro-regulatory functions. Based on the panel data of 31 provincial-level administrative regions in China from 2010 to 2020, the empirical verification is carried out by means of two-way fixed effects, quantile regression, instrumental variables, and spatial econometrics. The research finds that (1) there is an inverted U-shaped change trend between logistics agglomeration and environmental quality and the low-level logistics agglomeration period has a blocking effect on pollution emission reduction. However, from the starting point of the sample interval, representative regions such as Beijing and Shanghai gradually break through the bottleneck of logistics agglomeration in the form of a pyramid, which has an incentive effect on pollution emission reduction. The above conclusions are supported by robustness tests in six ways, including eliminating extreme data disturbance, eliminating the impact of the COVID-19, controlling the impact of other factors, pollutant sensitivity testing, avoiding the interference of pollution prevention and control, and correcting the endogenous bias of the model. (2) Further analysis of superimposed spatial effects and regulatory effects shows that regional spillover pollution has spatial dependence in both geographical and economic distribution. The effect of logistics agglomeration also produces an inverted U-shaped spatial spillover effect on the environmental quality of adjacent areas. Both informatization and legalization factors help alleviate the pollution increasing effect in the low-level logistics agglomeration stage. Under the regulatory effect of informatization, the arrival of the critical point for logistics agglomeration and emission reduction will be relatively delayed. Under the regulatory effect of legalization, the arrival of the critical point for logistics agglomeration and emission reduction will be relatively accelerated. (3) There is significant regional heterogeneity in the environmental effects of logistics agglomeration. Each region needs to "suit the remedy to the case" in combination with its own situation to break through the threshold of pollution reduction as soon as possible. [ABSTRACT FROM AUTHOR]

Fertilizers play an essential role in increasing crop yield, maintaining soil fertility, and provide a steady supply of nutrients for plant requirements. The excessive use of conventional fertilizers can cause environmental problems associated with nutrient loss through volatilization in the atmosphere, leaching to groundwater, surface run-off, and denitrification. To mitigate environmental issues and improve the longevity of fertilizer in soil, controlled release fertilizers (CRFs) have been developed. The application of CRFs can reduce the loss of nutrients, provide higher nutrient use efficiency, and improve soil health simultaneously to achieve the goals of climate-smart agricultural (CSA) practices. The major findings of this review paper are (1) CRFs can prevent direct exposure of fertilizer granule to soil and prevent loss of nutrients such as nitrate and nitrous oxide emissions; (2) CRFs are less affected by the change in environmental parameters, and that can increase longevity in soil compared to conventional fertilizers; and (3) CRFs can maintain required soil nitrogen levels, increase water retention, reduce GHG emissions, lead to optimum pH for plant growth, and increase soil organic matter content. This paper could give good insights into the ongoing development and future perspectives of CRFs for CSA practices. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, high energy consumption and high pollution emission have become serious problems. To solve these problems, many studies have been done to evaluate energy and environmental efficiency, as the results can provide valuable information to improve performance. However, the previous research mainly evaluates China's regional energy and environmental efficiency by considering each region's industry as a whole system, ignoring the internal structure. In reality, each region mainly includes three parallel types of industry: primary, secondary, and tertiary. Therefore, this paper provides a parallel data envelopment analysis (DEA) approach to evaluate China's regional energy and environment efficiency by considering these parallel industrial systems. The following findings can be obtained based on the empirical results: (1) the overall energy efficiency of China is low, and the inefficiency of the economic system is mainly sourced from the lower energy and environmental performance of the primary industry and the tertiary industry. (2) the introduction of the environmental variable (CO2) leads to the increase of some backward areas' efficiencies. (3) the energy efficiency of each provincial region is different, and most of them have their own inefficient industries. (4) the total factor productivity of China is declining, mainly because of the decline of technical efficiency. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In China, industrial pollution is a prominent source of environmental pollution, and the important goal of sustainable development is to reduce industrial pollutant emissions, while ensuring economic stability. Special fiscal revenue (SFR) is the direct channel of government environmental regulation and the main source of environmental protection investment; it is of great significance to analyze the influence of special revenue on industrial pollution for industrial sustainable development. Therefore, this paper uses panel data from 30 provinces in China from 2005 to 2018 to empirically analyze the impact of SFR on the comprehensive industrial pollution index (CIP) and the spatial spillover effect by combining traditional regression and spatial econometric model. The empirical results show that: (1) The increase in SFR will significantly reduce the level of regional CIP emissions, and it verifies the role of SFR as a channel of government environmental regulation and a major source of special funds for environmental protection. (2) SFR exists a significant negative spatial spillover effect. For every 1% increase in SFR in surrounding provinces, the local CIP will decrease by about 0.448%, reflecting SFR has a stronger inhibition effect on CIP for surrounding areas. (3) According to the analysis of different periods, the main impact of SFR on CIP is after the new round of reforms in 2012. The sources and expenditure channels of SFR are more transparent, indicating that the institutional policies have a significant effect on emission reduction. (4) The analysis of individual heterogeneity finds that the increase of SFR in economically underdeveloped areas has a stronger inhibitory effect on CIP, and the space for technological progress in economically developed areas is small, so it is difficult to inhibit CIP in a short period of time. In addition, the instrumental variable model and robustness test support the above conclusions. [ABSTRACT FROM AUTHOR]

Over the past couple of decades, the world has witnessed a rise in greenhouse gas (GHG) emissions and rising income inequality that threatens human well-being. Addressing these challenges and ensuring sustainable development become a pressing issue for policymakers. This paper investigates the impact of GHG emissions on income inequality in Africa. The study uses a panel data set from 49 countries from 1981 to 2015 and shows that GHG emission widens income inequality. The result is robust for alternative emission indicators. A direct implication is that climate change policy should be designed to narrow income inequality. It is emphasized that mitigation actions should focus on the agriculture sector. Hence, intervention towards energy-smart agriculture, land conservation practices, exploiting the job creation potential, and strengthening value addition in the agricultural sector is decisive. Reforming agriculture reduces emission, narrows income inequality, and realizes sustainable development on the continent. [ABSTRACT FROM AUTHOR]

China has a vast territory and abundant resources, and there are significant differences in the development of pig breeding in different regions. Chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) produced in the process of pig breeding will affect China's environmental quality. In view of this, based on the Minimum Distance to Weak efficient frontier model, this paper constructs Metafrontier-Malmquist-Luenberger (MML) index considering negative output under the common frontier to comprehensively evaluate the green total factor productivity of Chinese pig breeding (GTCP). This has guiding significance for improving China's pork production and reducing pollution emissions. The results manifest that (1) no matter under the common frontier or the group frontier, GTCP presents large temporal and spatial differentiation characteristics. Compared with the central region and the western region, the eastern region has obvious advantages in GTCP. (2) GTCP has shown an upward trend as a whole, which is mainly due to the technical progress. (3) Compared with small-scale and medium-sized GTCP, large-scale GTCP has apparent superiorities. Based on the above outcomes, this paper finally raises policy recommendations for improving GTCP: (1) give full play to the advantages of pig breeding in different regions, (2) increase the research and introduction of pig breeding clean technology and improve the application efficiency, and (3) give full play to the scale effect and vigorously develop large-scale pig breeding. [ABSTRACT FROM AUTHOR]

Studying the comprehensive performance of industrial carbon emission has profound significance for improving carbon allowance allocation scheme and achieving the carbon neutrality target. The paper selects 181 enterprises in Zhengzhou as the case, a comprehensive carbon emission performance indicator system and a carbon allowance allocation model were established, and compared with other allocation schemes (historical/baseline method). The results showed that the overall differences in the comprehensive performance evaluation indicator of carbon emissions in typical industries in Zhengzhou were obvious, and there was a correlation with the characteristics of industrial production activities. The overall emission reduction of Zhengzhou was 244.33×103t, and the emission reduction ratio was 7.94% by simulating carbon allowance allocation under the comprehensive performance. The carbon allowance allocation method based on the comprehensive performance has the strongest restraint on the "high emission, low performance" industry, which is more equitable and more conducive to carbon emission reduction. In the future, it will be recommended to give full play to the leading role of the government, implement industrial carbon allowance allocation based on the comprehensive performance evaluation of carbon emissions, to achieve multi–objectives of resource conservation, environmental pollution abatement, and carbon reduction. [ABSTRACT FROM AUTHOR]

Under the guidance of carbon peak and carbon neutral targets, the industrial structure transformation is vital for carbon emissions reduction in China. However, there is a rebound effect of carbon emissions during the industrial structure transformation. Resource dependence and technological progress have significant impacts on industrial structure transformation and its carbon reduction effect. This paper explores how industrial structure transformation under resource dependence causes the rebound effect from a technological progress perspective. The key results indicate that (1) resource dependence distorts the carbon emissions reduction effect of industrial structure transformation; (2) with the development of technology, the industrial structure upgrading under resource dependence could cause an increase on carbon emissions at the beginning, but the increase would be weakened subsequently, displaying a two-stage feature; (3) the industrial structure rationalization under resource dependence reduces carbon emissions at first, but the reduction would be weakened as the technology develops, then industrial structure's rationalization shows an insignificant impact on carbon emissions, and finally reduces carbon emissions again, presenting a four-stage characteristic; (4) environmental protection technology can correct the distortion effect of resource dependence on the industrial structure rationalization and amplify the industrial structure rationalization's reduction effects on carbon emissions; (5) with the development of energy-saving technology, industrial structure rationalization has a paradoxical impact on carbon emissions, the industrial structure rationalization first reduces, then increases, and finally reduces carbon emissions, indicating an inverted "N" relationship. Finally, policy recommendations for carbon emissions reduction are proposed from the perspective of industrial structure transformation and technological progress. [ABSTRACT FROM AUTHOR]

The cities are the consumption concentration of energy, resources, and the concentration of CO emissions. The cities' area only accounted for 2% in the world's surface; however, their population accounted for about 50% of the total population, and CO emissions accounted for about 80% of the total emissions. The cities lie in a key position in solving the global climate change. China's urbanization level was just exceeding by 50%, which was in the intermediate stage of urbanization. The rapid development of the urbanization process and the expansion of city scale have brought economic growth and all kinds of environmental issues. Therefore, is there an optimal city scale which can make cities maintain economic growth and can also reduce or even avoid the environmental problems in the meantime? The question deserves deep research. Based on the background, the data from 1998 to 2014, and the goals of the cities' economic and environmental benefits, this paper builds the optimal scale model for the cities, and obtain two conclusions: (1) in a certain period and range, the cities have the optimal scale; (2) for the cities in China, the optimal scale is about 1.78 million people. [ABSTRACT FROM AUTHOR]

This paper re-estimates the environmental Kuznets curve (EKC) in China. To this end, it uses the unit root tests with structural breaks and the autoregressive-distributed lag (ARDL) estimations over the period 1971-2010. The special role is given to the impact of export product quality on CO emissions in the empirical models. The paper finds that the EKC hypothesis is applicable in China. It also observes the positive effect from energy consumption to CO emissions. In addition, it finds that the export product quality is negatively associated with CO emissions. The paper also argues potential implications. [ABSTRACT FROM AUTHOR]

This study interprets enterprise pollution reduction from the perspective of the financial market. Using data on Chinese industrial enterprises, this paper tests the impacts of bank competition on enterprise pollution emissions. The findings show that bank competition has a significant total effect and technique effect on pollutant reduction. Bank competition reduces pollutant emissions by easing financing constraints, increasing the implementation of internal pollution control, and improving the efficiency of bank credit resource allocation. Further research shows that both bank type and bank branch level could moderate the pollution reduction effects and such effects vary a lot under different environmental regulation intensities. We expand the relevant literature on the economic consequences of banking competition and have certain theoretical and practical reference significance for the future reform of the banking industry. [ABSTRACT FROM AUTHOR]

This paper aims to capture the effect of an environmental tax on environmental degradation in the Netherlands while controlling economic growth, primary energy consumption, and trade in the Netherlands. As part of its climate change plan, the Netherlands government aims to reduce greenhouse gas emissions to industrial levels by 2030 and reach net-zero emissions by 2050. The present study used novel Fourier ADL cointegration, Fourier ARDL, and Fourier TY causality approaches. The outcomes of this study reveal that environmentally related taxes cause the mitigation of environmental degradation in the Netherlands, while primary energy consumption affects environmental sustainability negatively. This study provides policy implications based on the empirical results of this study, which support the Sustainable Development Goals (SDG) of 2030 through (SDG 7) affordable and sustainable energy, (SDG 9) innovation, and (SDG 13) environmental sustainability. [ABSTRACT FROM AUTHOR]

Continuous and rapid economic development has brought about excessive resource consumption and environmental pollution. Therefore, it is particularly essential to coordinate economic, resource, and environmental factors to achieve sustainable development. This paper develops a new data envelopment analysis (DEA) method that can be used for multi-level complex system evaluation (MCSE-DEA) to reveal the inter-provincial green development efficiency (GDE) in China from 2010 to 2018. Moreover, the Tobit model is applied to explore the influencing factors of GDE. We found that (i) the MCSE-DEA model tends to have lower efficiency scores than the traditional P-DEA (panel data envelopment analysis) model, and the top three provinces are Shanghai, Tianjin, and Fujian; (ii) the efficiency shows an increasing trend during the whole study period. The southeast region and the Middle Yangtze River region have the highest efficiency values, reaching 1.09, while the northwest region ranks last with an average efficiency value of 0.66. Shanghai performs the best, while Ningxia performs the worst, with efficiency values of 1.43 and 0.58, respectively; (iii) the provinces with lower efficiency values mainly come from economically underdeveloped remote regions, which can be attributed to issues of water consumption (WC) and energy consumption (EC). Moreover, there are much room for improvement in solid waste emissions (SW) and soot and industrial dust emissions (SD); (iv) the environmental investment, R&D investment, and economic development level can significantly improve GDE, while industrial structure, urbanization level, and energy consumption have inhibiting effects. [ABSTRACT FROM AUTHOR]

Industrial digital transformation is a key engine to help developing countries reduce pollution and carbon emissions. We used the composite system synergy model (CSSM) and modified entropy weight method to measure the degree of synergy between pollution and carbon emissions control (SPCEC) and the level of industrial digitization in each province and city based on the Chinese inter-provincial panel data from 2011 to 2020. We then used the two-way fixed effects and panel quantile regression models to test the heterogeneous influence of industrial digitization on the SPCEC. We found that: (1) industrial digitization had a positive contribution to the SPCEC. (2) Digitization of industry contributes more to the SPCEC level than the digitization of agriculture and services. (3) The promotion of SPCEC by industrial digitization is significant in the western region, but not in the eastern, central and northeastern regions. (4) In provinces and municipalities with lower level of SPCEC, the contribution of industrial digitization to the SPCEC is higher. This paper reveals the impact of industrial digitization on the SPCEC and can provide a policy reference for the realization of the SPCEC from the perspective of the integration of industry and digitization. [ABSTRACT FROM AUTHOR]

Sustainable Development Goal 9 targets (SDG 9 targets) are mainly tracked through the indicators of penetration of internet and mobile broadband subscription, logistic performance index, quality and ranking of the universities, investment in research and development initiatives, industrial reforms and emission control, and connectivity to rural areas. The attainment of many of these targets and tracking of indicators is confronted by challenges of poor awareness, funding issues, distorted policies, and implementation failures. This systematic review on achievements, challenges, and future scope in attaining SDG 9 consolidates the literature from the Web of Science, related to SDG 9 and indicators, since 2017; develops bibliometric patterns; conducts thematic analysis by focusing the leading indicators of SDG 9; and develops agenda for future research. The major limitations of this study include focusing on selected indicators and limited literature availability. This review recommends policymakers, researchers, and administrators to focus on promising themes such as tackling the digital divide and ensuring digital justice and digital equality; clean fuel and technology adoption; enhancing internet and mobile broadband subscription with reduced negative impacts, logistic sector reforms; industrial policy reforms and technology integration; improving the quality and sustainability of universities; and increasing funding and support for research and development initiatives and improving the rural connectivity. [ABSTRACT FROM AUTHOR]

To effectively combat global warming, an enormous reduction in CO2 emissions is required. Cameroon, which is currently the largest emitter of CO2 in the CEMAC subregion, has committed to reducing its greenhouse gas emissions by 32% by 2035. However, previous studies in Cameroon have only addressed the relationship between economic growth, energy consumption, and CO2 emissions without estimating all causal relationships at the same time. Moreover, no study has yet decomposed this country's CO2 emissions to date. To fill these research gaps and further assess the determinants of these CO2 emissions, an extended Kaya identity and the Logarithm Mean Divisia Index (LMDI I) have been applied in this paper to identify, quantify, and explain the main drivers of Cameroon's CO2 emissions from 2007 to 2014. Seven effects were measured and the main findings show that carbon intensity and the emission factor increased by 0.57% and 107.50% respectively. Regarding contributions to the increase of CO2 emissions, the population effect was the most positive followed by the activity effect, whereas the energy intensity, the substitution of fossil fuels and the penetration of renewable energies have contributed to reduce the CO2 emission. To enable Cameroon to not only achieve the goals of its vision but also develop a low-carbon economy, this paper provides some proposed avenues that should be considered by policymakers. [ABSTRACT FROM AUTHOR]

The disposal of food waste has attracted worldwide attention. Each year, the amount of wasted food accounts for an estimated one third of annual food production globally. This large amount of food waste has caused serious land, water, and air pollution. In the past, most research on food waste was focused solely on food waste disposal processing. Only a few studies analysed the flow of materials in food waste treatment processes. Therefore, this paper focused on the process of food waste anaerobic treatment in Beijing and investigated the treatment. According to a life cycle theory, the food waste treatment process is divided into three processes: "collection and transportation, disposal, and resource utilization." This paper analysed the input and output of food waste treatment in different processes and evaluated the economic and environmental costs and benefits of food waste treatment. The study found that 200 t of food waste anaerobic treatment can obtain benefits 66,888 Chinese yuan, generate electricity energy 43,350 kW⋅h, and reduce carbon dioxide emissions 16,087 kg. Generally, the economic and environmental benefits of the food waste anaerobic treatment project are considerable. However, the economic benefits are mainly from government subsidies. There are many impurities in food waste, which indicates some problems in food waste treatment. Thus, the proposals to strengthen waste classification, optimize the layout of garbage collection and transportation, and accelerate the development of waste treatment plants have been put forward. [ABSTRACT FROM AUTHOR]

Financial development is often expressed as a private sector initiative earmarked towards motivating economic growth and mitigating poverty. Nonetheless, the need for economic development accompanied by high industrialisation and commercialisation strategies has generated natural environmental effects which have raised enormous concern to green interest groups about whether all the seventeen sustainable development goals will be achieved. This paper investigated the environmental effects of financial development in OECD countries from 2001 to 2012 by employing static models and system GMM analysis. The study utilised foreign direct investments, domestic credit to private sector by banks and domestic credit to private sector as the three proxies of financial development. The effects of these measures of financial development were examined on carbon emissions and greenhouse gases (indicators of environmental quality) and environmental sustainability. In this setting, the findings of the research spotlight that domestic credit to private sector by banks shows a negative and significant relationship with carbon emissions, greenhouse gases and sustainability. Conversely, domestic credit to private sector and economic growth indicates a positive and statistically significant relationship with carbon emissions, greenhouse gases and sustainability. Foreign direct investment is positive and significantly connected with carbon emissions and sustainability but only shows a positive and not significant link with greenhouse gases. The evidence suggested by this analysis adds that the financial system should continue to add more initiatives which consider natural environmental perspectives in their current operations. This present study also confirms the existence of the environmental Kuznets curve (EKC) in carbon emissions (turning point, $109,820), total greenhouse gases (turning point, $74,280) and sustainability (turning point, $112,505). The finding that the turning point of carbon emissions is higher than that of total greenhouse gases indicates why introducing initiatives designed to curb growth of carbon emissions in the respective OECD economies is important. [ABSTRACT FROM AUTHOR]

The aim of this paper is to augment the existing literature on convergence of CO2 emissions, by adding carbon footprint per capita and ecological footprint per capita to the convergence debate. We use the residual augmented least squares regression to examine the stochastic convergence of the environmental indices in 27 OECD countries. Furthermore, in contrast to the previous studies which mainly used the conventional beta-convergence approach to examine conditional convergence, we use a beta-convergence method that is capable of identifying the actual number of countries that contribute to conditional convergence. The sigma-convergence of the environmental indices is also examined. The results suggest that conditional convergence exists in 12 countries for CO2 emissions per capita, 15 countries for carbon footprint per capita and also 13 countries for ecological footprint per capita. There is evidence for sigma-convergence for all the three indicators. The policy implications of the results are discussed in the body of the paper. [ABSTRACT FROM AUTHOR]

The proliferation of carbon dioxide (CO2) emissions has resulted in significant environmental challenges worldwide, particularly within industrialized nations. The present paper tries to investigate the role of food, beverages, and tobacco in mitigating CO2 emissions in the top industrial countries. Economic growth and renewable and non-renewable energy consumption are integrated as control variable in the empirical model. The study applied the pooled mean group-autoregressive distributed lag (PMG-ARDL) model proposed by (J Appl Econ, 16:289-326, 2001) and Granger causality test for causalities directions. The empirical outcomes suggest the presence of cross-sectional dependence, and variables are integrated of order one and cointegrated. Long-run estimates revealed the presence of inversed U curve proving the validity of the environmental Kuznets curve. Also, the results show that renewable energy (RE) consumption contribute in reducing emissions, while non-renewable energy (NRE) and food, beverages, and tobacco (FBT) led to increase emissions level in the long run. Granger shows bidirectional long-run relationship between CO2 emissions, non-renewable energy, and economic growth. Moreover, Granger recorded no causality between food, beverages, and tobacco and any other variable. We recommend that firms engaged in the production of food, beverages, and tobacco products are increasingly urged to make investments in clean technologies powered by renewable energy sources for their manufacturing processes. This is considered a necessary step to achieve a significant reduction in CO2 emissions over an extended period. [ABSTRACT FROM AUTHOR]