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Small and medium-scale enterprises increasingly show greater interest in managing their environmental footprints in response to shifting customer preferences. Beyond the mixed results in the literature exploring environmental concerns from an organisational perspective, questions related to firm strategy and energy efficiency have yet to be definitively determined. This study investigated the mediating role of business associations in the relationship between firm strategy and energy efficiency among small and medium-scale enterprises. Using binary logit regression, data from over 20,000 firms across 39 countries were analysed. Our analysis demonstrates that business strategy positively impacts climate-friendly energy generation, energy management, and energy consumption improvements. Furthermore, business associations were found to significantly mediate these relationships. A comparative analysis revealed some differences across economic regions, with the impact of business strategy being more pronounced in the Middle East and Africa compared to other regions of the world. The present findings suggest that improving small and medium-scale enterprises' affiliations to business associations is a promising approach to increasing their adoption of sustainable energy practices. The study findings further advance the understanding of the firm strategy-energy efficiency nexus, and have implications for policymaking in environmental performance enhancement. [ABSTRACT FROM AUTHOR]

Batch plants boast operational flexibility in manufacturing process and resource sharing, making batch processes suitable to fluctuating-demand or small-scale production. However, given time dependence of operational behavior, batch processes are more demanding in energy integration than continuous processes, a task which is especially important amid the global net zero-emission current. It is, therefore, imperative to develop sustainable design strategies for intermittent processes. The study introduced a targeting method and developed an innovative over-time heat integration technique to optimize energy utilization in batch processes, involving use of heat transfer media for heat recovery over various time intervals and a heat makeup strategy to heat the media over different periods, in order to enhance heat-energy utilization efficiency. The technique is applicable to both fixed and unspecified batch schedules, the latter of which involves simultaneous design of production schedule and heat recovery systems, increasing flexibility and improving heat energy utilization. Case studies are conducted to demonstrate the proposed method. With the heat makeup technique, energy efficiency can be significantly enhanced, achieving energy savings of 51% and 93.1% in hot and cold utility, respectively. Meanwhile, the simultaneous design of production schedule and heat integration can boost savings up to 53% and 99%. Results have proven the benefits of the technique, including significant reduction of energy consumption and carbon emission, contributing to clean production, environmental protection, and sustainable development. • Innovative batch heat integration overcomes time constraints. • Heat transfer media and heat makeup strategy improve energy efficiency. • Simultaneous scheduling and heat recovery enhance heat integration flexibility. • Significant energy reduction promotes clean, green, sustainable production. [ABSTRACT FROM AUTHOR]

Energy-saving construction has promoted the sustainable development of cities and is an important measure to achieve carbon neutrality and peak carbon. This paper uses the synthetic control method(SCM), propensity score matching difference-in-difference model(PSM-DID), spatial Durbin difference-in-difference model (SDM-DID) and other methods to explore the policy effect of energy-saving policy on the green innovation efficiency of Chinese cities based on the New Energy Demonstration City(NEDC) policy as a quasi-natural experiment. The paper has found that establishing NEDC can significantly improve the green innovation efficiency of pilot cities, and its positive impact continues to increase over time. The effect of energy-saving policy has regional heterogeneity, and NEDC can promote the improvement of urban green innovation efficiency more in eastern and central China. The results of PSM-DID further verify the robustness of the previous conclusion. The results of SDM-DID show that NEDC has a positive spatial spillover effect on the improvement of urban green innovation efficiency. NEDC policy can effectively promote the improvement of green innovation efficiency in neighboring cities of pilot cities. Mechanism analysis shows that NEDC affects urban green innovation efficiency by optimizing industrial structure, reducing resource dependence and gathering innovative elements. This paper enriches the research on the effect of urban energy-saving policies and provides policy references for improving urban green innovation capabilities. [Display omitted] [ABSTRACT FROM AUTHOR]

Global businesses are facing increasingly significant climate risks. Firms with ESG controversies will likely suffer from higher financing costs and inadequate investment capability, leading to investment inefficiency. We use a newly introduced ESG Controversy Score database to investigate the relationship between ESG controversies and corporate investment efficiency. The results show that ESG controversies significantly reduces firms' overall investment efficiency, and such adverse impact is manifest in underinvestment inefficiency. Further analysis indicates that such a negative effect is more pronounced in firms with larger size and higher analyst coverage. Our findings highlight the significant role of ESG misbehaviour in corporate sustainable development. [ABSTRACT FROM AUTHOR]

Industry 4.0 (I4.0) technologies and energy efficiency measures (EEMs) could enhance the performance of manufacturing industries, but research on the role of I4.0 on EEMs adoption with respect to production resources and operational performance is lacking. The academic contribution of this research in terms of novelty is twofold: first, this study has represented an innovative attempt to explicitly consider EEMs impact on production resources operational performances. Second, the study qualitatively highlights the contribution of specific I4.0 technologies to boost performance of industrial EEMs. To achieve the research objectives, a framework is developed to assess EEMs based on the impact over various production resources and operational performance, further integrating how Industry 4.0 technologies may affect such impacts. The application of the framework in selected companies allowed several interesting insights compared to extant literature. The synergic use and management of machine data and hardware allows to reap unexploited benefits beyond energy efficiency, such as Overall Equipment Effectiveness (OEE), labour effectiveness, reliability, reduced operational costs. The study reveals the contribution of specific I4.0 technologies with respect to specific EEMs: whilst implementing Artificial Intelligence is deemed important for boosting the benefits of heating, ventilation, and air conditioning and closed cycle process in water management (improving OEE, productivity and reducing operational costs), Internet of Things seems to beneficially affect the adoption of motor systems by improving OEE and reliability. The study concludes with limitations, major recommendations for industrial decision-makers and future research avenues. [ABSTRACT FROM AUTHOR]

This study develops an integrated analytical framework, based on LMDI method, to identify the driving factors of energy and water (EW) nexus in Beijing from both economy- and sector-wide perspectives. The notable findings are: (1) The service and urban household sectors contributed most to the increase of energy use while the agriculture sector played a dominated role in the large decline of water use in Beijing from 2002 to 2017. Service and urban household were the key sectors of EW nexus. (2) Both economy- and sector-wide factors exerted synergistic effects on EW use, although their contributions to water-saving were much higher than energy-saving. Regarding economy-wide factors, production expansion considerably increased both EW use in Beijing, with the contribution degrees of 129.9% and 276.2%, respectively, and population expansion also played an important role in increasing EW use, with the contribution degree of 10.3% and 32.9%; while efficiency improvement and industrial structure adjustment led to much more water-saving of 261.7% and 145.1% than energy-saving of 56.6% and 5.6%, respectively. As to sector-wide factors, production expansion of industry and service sectors, and income improvement of urban household contributed to a considerable increase in both energy and water use, and the contribution degree are 58.3%, 65.7% and 28.5% for energy use as well as 61.0%, 79.8% and 22.8% for water use, respectively, whereas efficiency improvement of industry sector effectively curbed the increase of energy and water use, with the contribution degree of −50.5% and −76.7%, respectively. (3) The only trade-off between energy- and water-saving occurred in the efficiency improvement of the agriculture sector. (4) More attention should be paid to reducing EW use in the service and urban household sectors through efficiency improvement and behavior guidance for EW saving. • Service and urban household were the key EW nexus sectors. • Production and population expansion considerably increased both EW use. • There existed synergic effects of various factors on the reduction of EW use. • Modern agricultural technologies caused trade-off between energy- and water-saving. [ABSTRACT FROM AUTHOR]

This study aims to assess the utilization efficiency of industrial land in China's rapid urbanization. Land productivity is calculated to analyze spatial characteristics using the data of 275 prefecture-level cities from 2006 to 2016. Findings suggest that urban industrial land productivity has steadily increased over time. The points and belt shape is the spatial feature, in which high-level productivity cities located in the coastal regions are connected into an S curve. The gap of land productivity among the four regions in China had been widening from 2006 to 2016. The empirical results show that capital density, labor density, urban developed area, urban population, economic growth, and industrial structure are significant factors of land productivity. [ABSTRACT FROM AUTHOR]

Geographic Information Systems (GIS) are commonly employed to solve problems related to landfill siting and optimization of waste collection. This research aims to develop an easily implementable tool to optimize the topology of waste management regions in various Canadian jurisdictions using ArcGIS ModelBuilder. Landfill count, populated places, and road length are minimized using standard deviation to determine optimized tessellations. In Nova Scotia, reductions in standard deviation of 9.6–30.4% are observed between original and optimized tessellations. The results suggest that an optimized tessellation of Nova Scotia's Federal subdivisions may perform better than that of their waste management regions. In Saskatchewan, reductions in standard deviation of 4.9–46.1% were observed between original and optimized tessellations. Considering all Saskatchewan Federal Subdivisions, no optimization occurred. However, partitions of Saskatchewan Federal Subdivisions yielded better results, with vertical partitions yielding a 30% decrease in standard deviation of roads, while landfills and population were reduced in the horizontal subdivision by 20.0% and 38.0%, respectively. This suggests that a different approach may be required for waste management regions in Northern Saskatchewan. Saskatchewan transportation planning committees regions had the highest standard deviation across all parameters, and optimized at the fourth iteration (landfills and populated places), and first iterations (roads), despite the fact that this tessellation was developed in direct relation to roads in the province. The proposed tool, however, showed a limited application in the City of Regina given that land use planning within City limits. This work will improve the data driven aspect of regional waste management system design. Image 1 • A novel method for delineating waste management regions is proposed and implemented. • One municipal and two provincial tessellations were evaluated via subdivisions. • Landfills, populated places, and road length are applied as geospatial indicators. • Significant reductions in standard deviation (4.9–46.1%) are observed. [ABSTRACT FROM AUTHOR]

Reusing waste materials of other industries, a practice known as industrial symbiosis, attracts growing attention by industry. However, the waste materials are often of lower quality than the virgin materials they substitute. When production processes are intolerant for lower quality materials, production issues may occur. This paper sets out to explore how firms can manage the waste quality through supplier integration with the waste supplier. As suppliers have to learn new knowledge, the construct of absorptive capacity is used as an interpretive lens. An in-depth longitudinal exploratory case study approach is used to examine the involvement of different individuals and departments in the supplier integration activities in the context of the waste-based fuel supply chain of a global cement producer. Qualitative and quantitative data was gathered at both the buyer and the supplier. The data show that buyers can increase the absorptive capacity of the suppliers by aligning their own knowledge bases with the scope of the supplier integration. The increased absorptive capacity enables the suppliers to align waste quality with production requirements. Managing waste quality is an important capability of industrial symbiosis, especially when firms want to go beyond the low-hanging fruits and increase the effectiveness of their industrial symbiosis activities. The research concludes with theoretical and managerial insights into how firms can organize the supplier integration to manage waste quality in the context of industrial symbiosis. • Using poor waste quality lowers production efficiency in industrial symbiosis. • Waste quality parameters can be ambiguous and therefore hard to manage. • Buyers can help suppliers to manage waste quality through supplier integration. • Absorptive capacity explains the effectiveness of supplier integration. • Aligning waste quality with production requirements improves production efficiency. [ABSTRACT FROM AUTHOR]

Investments in energy efficiency often remain undecided upon and there is a large potential for enhancing energy efficiency in the industrial and commercial sectors. Within this context, the aim of the research project M_Key "Management as a key driver of energy performance" is to better understand how large-scale energy consumer (LSEC) companies make energy-efficiency investment decisions. With about 35% of the total Swiss electricity consumption, LSECs are an important target group for energy-efficiency programmes in Switzerland. The goal of this paper is to present and describe the main findings of M_Key (Management as Key for Energy Performance) research project. For the first time, these findings extensively depict large-scale energy consumers in Switzerland. They highlight the low level of energy management in Swiss LSECs and of the resources allocated to tackle energy issues. Due to a lack of monitoring and control tools, companies have difficulty assessing their energy-efficiency investments. Energy issues are not generally a priority for companies, with a few exceptions, mainly in large firms. Requirements from national or cantonal energy policies have a significant role (and in the case of SMEs a key role) in inciting companies to action. When energy efficiency is perceived as strategic, companies tend to have a high level of energy management. The better the energy management system is, the more likely the chances are for a positive decision on energy-efficiency investment. Another important conclusion is that the more strategic a project or investment is considered to be, the less restrictive are the financial criteria applied. [ABSTRACT FROM AUTHOR]

Research has revealed the existence of an energy-efficiency gap – the difference between optimal and actual energy end-use, suggesting that energy efficiency can be improved. Energy management (EnM) is a means for improving industrial energy efficiency. However, due to various barriers, the full potential of EnM is not realised. Several studies have addressed drivers and barriers to energy efficiency but few to EnM. This study aims to identify EnM practices, the most important perceived drivers and barriers for EnM, and relations among them in the energy-intensive Swedish pulp and paper industry (PPI), which has the longest experience internationally of practising EnM systems, and has worked according to the standards since 2004. Our results show that, altogether, the PPI works regularly and continuously with EnM, with a clear division of responsibilities. The highest maturity for EnM practices was for energy policy, followed by organization, investments, and performance measurement. The study also shows that communication between middle management and operations personnel has potential for improvement. The most important categories of drivers were economic, whereas for barriers they were organizational. Nevertheless, knowledge-related barriers and drivers were amongst the most important, suggesting that the absorptive capacity for energy issues could be improved. Image 1029 • Energy is managed continuously, with clear policies and responsibilities. • The main drivers are economical while main barriers are organizational. • Knowledge related barriers and drivers are amongst the next most important. • Employees' absorptive capacity for energy issues could be improved. • Link between energy policy and performance measurement could be improved. [ABSTRACT FROM AUTHOR]

Abstract Mechanization of agriculture drastically increases labour productivity in crop production, playing a major role in industrialization by freeing up workforce for industry and services. These historical processes are well studied, but there is much less knowledge on their environmental implications, particularly the carbon footprint. In this work, we aimed to reconstruct the complete historical process of mechanization in Spanish agriculture at the national scale, estimating the carbon footprint of traction through a life cycle assessment approach. The assessment includes greenhouse gas emissions from working animals and feed production, and accounts for the historical changes in the energy efficiency of the industrial production of machinery and fuels. The results reveal an increase in the carbon footprint of traction from 3.1 Pg CO 2 e yr−1 in 1900 to 11–12 Pg CO 2 e yr−1 in the 1970s and 1980s, decreasing to 7–8 Pg CO 2 e yr−1 in 2010–2014. Area-based emissions ranged 185–242 kg CO 2 e ha−1 yr−1 in 1900–1933, when the practical totality of traction was animal, and 503–540 kg CO 2 e ha−1 yr−1 in the 21st century, when animal traction had almost completely disappeared. Product-based emissions were similar at the beginning and at the end of the study period, as the productivity growth offset the area-based emissions growth. The results show a large peak in emissions during the main decades of the mechanization process. Thus, the large savings observed in the last three decades start from a very high emission level. The carbon footprint of traction could be reduced by mimicking the logic of traditional organic systems but still benefiting from modern technological efficiency, through the self-production of the fuel. Our analysis, however, shows that a simple shift to biofuels may actually increase greenhouse gas emissions and consume a large share of the current agricultural output. Therefore, its combination with significant reductions in fuel and feed demand would be necessary to achieve its mitigation potential. Highlights • Detailed reconstruction of inventory data on animal and mechanical traction. • Animal traction emissions depend on species mix and feed emission factor. • Higher greenhouse gas emissions in mechanized systems. • Highest emissions during the transition from animal to mechanical traction. • Self-produced biofuels could contribute to mitigation but also increase emissions. [ABSTRACT FROM AUTHOR]

Abstract Improving energy efficiency of industrial sectors is essential to achieve energy conservation in the Pearl River Delta urban agglomeration (PRDUA) in China. This study adopted stochastic frontier analysis (SFA) to evaluate the industrial total factor energy efficiency (TFEE) of nine cities in PRDUA during 2004–2016, and then to decompose the growth of TFEE into technical change (TC), technical efficiency change (TEC), and economies of scale (SC) effects. Results show that the TFEE of industrial sectors of PRDUA had an overall downward trend during the study period, and that technical change was the major driving force behind the growth of TFEE. The Tobit model was then adopted to further investigate the determinants of energy efficiency improvement and test the robustness of empirical results. The main contributions of this study to the existing literature lie in showing that (1) the degree of openness, local government spending, foreign direct investment, factor input structure, environmental regulation strength, and GDP per capita have positive impacts on the industrial TFEE; (2) enterprise scale and energy consumption structure have a negative impact on industrial energy efficiency. Finally, we address policy implications for energy management regarding their economic and environmental aspects in industrial sectors of the PRDUA. [ABSTRACT FROM AUTHOR]

Abstract This study reports a novel method using microwave vacuum pyrolysis combined with sodium-potassium hydroxide mixture (NaOH-KOH) activation to produce highly porous activated carbon (AC) from palm residue (i.e. palm kernel shell, PKS) – a solid residue constantly produced in large volume by palm industry. The yield and properties of AC produced were found significantly influenced by two key process parameters - type of activating agent and chemical impregnation ratio. The pyrolysis provided fast heating rate (60 °C/min), high temperature (607 °C), and short process time (35 min) to convert PKS into biochar, and the subsequent activation by NaOH-KOH mixture at 1.0 of chemical impregnation ratio resulted in 84 wt% yield of AC. The AC possessed high BET surface area (1320 m2/g) and highly porous structure formed by micro- and meso-pores, thus showing high adsorption capacity. The adsorption capacity of AC was examined via impregnation with nickel and aluminium atoms (termed "Ni/AC" and "Al/AC") followed by application in treating industrial effluent abundantly released from palm oil mill (termed 'palm oil mill effluent, POME). Both Ni/AC and Al/AC showed high removal efficiency in reducing the total suspended solid (TSS), oil and grease (O&G), biochemical (BOD) and chemical oxygen demand (COD) in POME. Higher removal efficiency on BOD and COD was observed for Ni/AC and Al/AC than normal AC (non-metallic AC). The production cost of AC using this pyrolysis method was estimated to be ranged from 4 to 10 USD/kg. The results show the exceptional promise of this pyrolysis method as an approach to transform PKS into highly porous AC for utilize as an adsorbent to treat POME. Graphical abstract Image Highlights • Microwave vacuum pyrolysis combined with NaOH-KOH activation was reported. • Two process parameters were examined for the yield and properties of AC produced. • AC was upgraded into metallic AC (Al/AC and Ni/AC) to treat palm oil mill effluent. • Metallic AC removed 85% of BOD and 89% of COD concentrations. • Normal AC (non-metallic) showed higher removal rate of TSS (80%) and O&G (88%). [ABSTRACT FROM AUTHOR]

Abstract In this study, the industrial eco-efficiency measures of 30 Chinese provinces (municipalities and autonomous regions) from 2001 to 2015 were estimated based on a proposed data envelopment analysis (DEA) model and the non-convex metafrontier-undesirable outputs-super efficiency-slacks-based measure (NCMeta-US-SBM) which simultaneously incorporates non-convex metafrontier technology, undesirable outputs, and super efficiency into slacks-based measure. Subsequently, dynamic spatial econometric models were employed to test the spatial convergence of industrial eco-efficiency. The empirical results show that: 1) the average value of industrial eco-efficiency was the highest in the eastern region (0.67), followed by the western region (0.30) and central region (0.27), indicating the existence of a significant regional disparity. 2) Strong evidence for global and club spatial convergence of industrial eco-efficiency was found. With regard to regional heterogeneity, provinces in the eastern region converged faster than those in the central and western regions; while the convergence speed of industrial eco-efficiency increased after 2008 with respect to temporal heterogeneity. 3) The ownership structure appeared to have a higher impact on industrial eco-efficiency than other controls in the presence of spatial conditional β -convergence. These findings are robust with regard to both spatial econometric model and spatial weighting matrix specifications. Based on the empirical analysis, the following policies promote industrial eco-efficiency in China have been recommended. First, relevant authorities must take effective measures to encourage the central/western regions to adopt clean energy technologies. The energy subsidy policies should strive to break through the technological lock-in and turn to regional green development. Second, full advantage of the spatial effects must be taken and technological exchanges and cooperation among neighboring areas must be strengthened to ensure that the industrial eco-efficiency of the central and western regions converge with those of the eastern coastal areas. Policy implications of multidimensional heterogeneity and adjustment of industrial structure should be highlighted while promoting industrial eco-efficiency. Finally, it is crucial to emphasize factors, such as foreign direct investment (FDI), ownership and industrial structures to attract FDI and optimize the current industrial structure. Graphical abstract Image 1 Highlights • Industrial eco-efficiency measures of 30 Chinese provinces (municipalities, autonomous regions) are estimated based on the proposed DEA model. • Eastern region performs the best, followed by the western and central regions. • Both global and club spatial convergence of industrial eco-efficiency is supported. • Empirical results are robust to different spatial weighting matrix specifications. [ABSTRACT FROM AUTHOR]

Renewable energies are attracting considerable interest as an appropriate alternative for the fossil fuel-based sources of energy due to increasing concerns about global warming and environmental issues. In this regard, this paper takes a new look at designing a sustainable Switchgrass-based bioenergy supply chain network (BSCN) incorporating conflicting economic, environmental and social objectives. We propose a novel, multi-objective, mixed integer linear programming model as a decision-making (DM) tool. To deal with sustainability factors, the proposed model is solved using two-stage algorithms consisting of augmented ε-constraint and TOPSIS. This approach paves the way to determine the suitable strategical and tactical decisions and manage bioenergy supply chain performance with respect to the preference of decision makers for appropriate trade-off among of the sustainability factors. Computational analysis is carried out to indicate the validity of the proposed model by using a real case study in Iran. The results demonstrate that achieving a desirable level of social and environmental preservation conducted a circa 15% increase in economic objective function at the end of planning horizon. The results also show that high investment cost is a precondition to improving BSCN. It behooves the government to prioritize their plans and compartmentalize their budgets and spending in more constructive and effective ways related to bioenergy supply chain planning. [ABSTRACT FROM AUTHOR]

Microgrids (MGs) that contain a reversible solid oxide cell (rSOC) system and battery energy storage system (BESS) are gaining prominence in terminal load supply and renewable energy consumption. However, the economy and durability are highly dependent on the reliability of its energy management system (EMS). Herein, a model-based online optimal control strategy is proposed to obtain optimal schedule decisions for EMS. Firstly, the aging of BESS and the efficiency of the rSOC system are considered simultaneously, and are modeled in detail. Subsequently, the optimal energy management (OEM) is formulated as a multi-objective optimization problem based on the constructed model. On this basis, to improve the efficiency and accuracy of the optimization search, a novel multi-objective evolutionary algorithm is proposed and verified, which hybridizes the non-dominated sorting genetic algorithm-II and tabu search, and incorporates improved crossover and mutation operations. Afterwards, data from a commercial user in Ningxia, China was used for the case study. The results show that the proposed control strategy can effectively slow down the aging of BESS and improve the efficiency of the rSOC system compared to the rule-based control strategy. Furthermore, compare with the rule-based control and economic dispatching strategy, the MG obtained a higher self-sufficiency rate (93.28%) and a shorter payback period (14.57 years) under the proposed OEM strategy. [ABSTRACT FROM AUTHOR]

Improving urban energy efficiency on the basis of cost-effectiveness is an important topic of universal concern across the world. The input cost has great influence on energy efficiency. Thus, as one of the important factors in the production progress, land price may exert an energy effect via affecting the urban industries. With a focus on land price levels and the variability, our study investigates the impact of land market on urban energy efficiency, based on the panel data of China's prefecture-level cities. Further, by exploring effects of the segment land markets, our study reveals the exact price features in land market that have driven the changes in energy efficiency of cities. The main results are: (a) Either of the price level and the price variability in urban land market has a positive net effect on energy efficiency. When price level and variability increase by 1%, urban energy efficiency respectively increases by 0.06% and 0.04%, and the effects vary with city's population size and geographic location; (b) An increase of land price level improves energy efficiency by optimizing industrial structure and reduces energy efficiency by weakening industrial production efficiency, while an increase in land price variability exerts a positive impact on energy efficiency by adjusting industrial structure; (c) The price level factor affecting urban energy efficiency is mainly the commercial-residential land prices, while the difference between commercial-residential and industrial land prices is the variability factor that affects energy efficiency. [Display omitted] • The energy effect of land market is explored. • Land price level and variability both positively impact energy efficiency via industrial structure and TFP. • The higher level of commercial-residential land price, the higher energy efficiency. • The larger difference in land prices of different categories, the higher energy efficiency. • Advising on land policy, energy policy and housing policy. [ABSTRACT FROM AUTHOR]

This literature review puts forward a comparison between the traditional seller, usually represented by classic Industrial Organization (IO) models, and system providers, which are illustrated by Product Service System (PSS) models. A multidisciplinary systematic literature review, that compares PSS and IO models, is conducted, and ends up in to define PSS as a technology highlights the differences and similarities between classic IO and classic PSS and evaluate the weakness and strengths of different models. In total, 148 articles from different disciplines have been investigated, and a different understanding of PSS is provided. A new IO framework, that considers classic sellers and PSSs providers, is established to preserve PSS specificities and stress the role of policy maker and competition for PSSs expansion. [ABSTRACT FROM AUTHOR]

The concept of circularity has been widely discussed in the literature, but the implementation of the circular economy at the micro-level remains unexplored. It is still not clear what are the antecedents for circular economy implementation at the industry level, instead of cleaner production principles and practices have been discussed as essential for circular economy adoption from the bottom up, but more empirical studies are still necessary to better understand the adoption and effects of cleaner production in promoting circular economy. Thus, this paper aims to explore the cleaner production principles and practices adopted by a manufacturing company located in an emerging economy in order to understand how these were valuable in foster circular economy implementation. A case-based research approach was adopted in this investigation. The circular economy practices introduced by the company were analyzed by considering their connections with the requirements when transitioning to a circular economy paradigm, within company-related processes in addition to circular economy areas at the micro-level. An inductive approach was adopted for data analysis to develop some propositions regarding circular economy interactions. The main findings revealed that cleaner production practices for product optimization are valuable to circular economy implementation regarding circular product design strategies. The cleaner production principle of input substitution is valuable for reducing input and use of natural resources as well as increasing the share of renewable and recyclable resources. Technological optimization can contribute to reducing emissions levels. In addition, field data showed that cleaner production practices at the production area enable circular economy practices to be implemented at the micro-level, as well as there is a connection with other circular economy areas (i.e. waste management, consumption, and support). Moreover, the findings confirmed that all cleaner production practices and principles implemented by the organization are connected to each other and across the processes. Further studies may focus on testing the propositions developed in this study in other manufacturing contexts, as well as on the investigation of possible cause-effect relationships that may exist between cleaner production and circular economy transition pathways. [ABSTRACT FROM AUTHOR]

The activities of the most enterprises are related to the difficulties while adapting to the current market demand, therefore, it is vitally important to define and solve the arising problems. Today consumers require non-expensive, personalized, ecological products just on time to their doorstep. Most government policies in this area are focused on the customer rights, demand in sustainable products and on stemming the environmental impacts of unsustainable production practices. However, the authors' of the current scientific publications are discussing the limited possibilities to achieve the cost effective performance and sustainability. The conducted literature analysis indicates that there is a lack of industry 4.0 practices for supply chain management. The presented publication considers the competitiveness strategy, which contributes to sustainable and optimal costs management. The supply chain must evolve and shift from the traditional to more sustainable solutions. The Internet of Things, big data analytics, cloud computing, cyber-physical systems along with autonomous vehicles and logistic clusters can help to maintain the competitiveness advantage in the long-run. The proposed approach also provides flexibility, redundancy and adaptive abilities to manage the logistic cluster, which allows limit the trade-offs between sustainability and cost effective performance. The simulation of the logistic network was done using the real data from the specialists' interviews within the food industry. The obtained results showed that by implementing the autonomous vehicles strategy along with the consolidation warehouses CO 2 emission level can be decreased by 22%. Moreover, the rest stops are not required during the trip because of the autonomous vehicles implementation in the supply chain. The proposed strategy also decreased costs of the whole logistic network. Currently the practical implementation of the developed distribution strategy is limited by the legislation and infrastructure issues, which should be solved aiming to reach sustainable supply chain and cost effective performance. [ABSTRACT FROM AUTHOR]

The improvement of regional eco-efficiency is a significant approach to achieve coordinated development of China's economic development and environmental protection, and an effective environmental regulation system is a crucial driver to the improvement of regional eco-efficiency. Based on the panel data of China's 30 provinces during 2000–2013, this paper divides environmental regulation into three types: command-and-control regulation, market-based regulation and voluntary regulation. STIRPAT model is employed to test the effects of these three environmental regulations on eco-efficiency in the eastern, central and western regions of China. Research results turn out that: (1) in the eastern region, market-based and voluntary environmental regulation have a positive impact on eco-efficiency improvement while command-and-control environmental regulation has no significant impact, and (2) in the central region, command-and-control and market-based environmental regulation can promote eco-efficiency more significantly compared with voluntary environmental regulation, and (3) in the western region, command-and-control environmental regulation plays a positive role in eco-efficiency improvement whilst market-based and voluntary environmental regulation have no significant impacts. These findings indicate that the effects of different types of environmental regulation on eco-efficiency apparently differ in regions. Finally, to optimize and adjust the environmental regulation tools, policy recommendations targeting different regions are concluded. [ABSTRACT FROM AUTHOR]

Many industrial companies use material and energy flow analysis as a tool to improve the resource efficiency and in particular the climate impact of their production plants. As material flow models of industrial production systems are typically large and complex, optimal operating conditions or designs are hard to find without computational support. To overcome this shortcoming an integrated approach that combines material and energy flow analysis with mathematical optimization has recently been proposed. This paper presents a prototypic optimization tool for material flow based optimization via mathematical programming. A particularly interesting area of application arises from using the optimization tool already during the model building process. Such an optimization-aided material and energy flow analysis facilitates the systematic exploration of the decision-makers action space and thus supports the construction of valid optimization models. It furthermore helps to find adequate compromises, when there are conflicts between objectives like costs and greenhouse gas emissions. The optimization tool as well as these conceptual aspects are illustrated by applying it to a production plant from the technology metals sector. [ABSTRACT FROM AUTHOR]

The study proposes an optimization approach for design of “green” products' portfolio of a supply chain for curd production. It includes three interconnected models for describing curd production, supply chain and its environmental impact. The latter is assessed in terms of wastewater and CO 2 emissions associated with the curd production and the transportation of raw material and products. The models are included in a broader optimization framework whereby the environmental criteria are defined in terms of costs such as the best trade-off between total profit and environmental impact to be achieved. The proposed approach is applied to a Bulgarian case study for production of two types of curd in dairy supply chain involving suppliers, dairies and markets. Two optimization problems for “green” products portfolio and profit products' portfolio design are formulated and solved. The obtained results show that the “green” products portfolio is limited by the environmental impact consideration and the optimal profit products' portfolio is limited by the plants' capacities. The successful implementation of the proposed approach opens the prospect of expanding not only to the whole range of dairy products but also the entire supply chain that includes players which are in a competition with each other. [ABSTRACT FROM AUTHOR]

A general rolling horizon optimization framework for the integrated condition-based operational and maintenance planning of production and utility systems in process industries is presented. In brief, the proposed optimization framework considers for the production and utility units: (i) improved unit performance degradation and recovery models that depend on both the cumulative time of operation and the unit operating levels deviation of units; (ii) modified operating capacities under online cleaning periods; (iii) different types of cleaning tasks (flexible time-window and online or offline condition-based); (iv) alternative options for offline cleaning tasks; (v) limited availability of cleaning resources; (vi) the initial state of the overall system at the beginning of each planning horizon; and (vii) terminal constraints for the rolling horizon problem. Total cost constitutes the objective function of the resulting problem and includes unit operating costs, cleaning costs, energy consumption costs and resource purchases costs. The case studies solved show that when compared to solutions obtained by sequential approaches the proposed integrated approach provides significantly better solutions in terms of total costs (reduction from 5% to 32%), and especially in cost terms related to utility units operation, energy consumption, cleaning and startup/shutdown operations. Unnecessary cleanings and purchases of resources can be avoided by the proposed integrated approach. Overall, the significant reduction in total costs is a direct result of the enhanced energy efficiency of the overall system through the efficient generation and use of energy, the improved utilization of energy and material resources resulting in a more sustainable and cleaner production practices. [ABSTRACT FROM AUTHOR]

This paper deconstructs industrial green transformation into two aspects, industrial efficiency green transformation and industrial structure green transformation. We examine the impact of digital finance development on industrial green transformation using data from Chinese cities and listed companies. The results showed that: (1) digital finance can contribute to the green transformation of industrial structure distinctly but has an inhibiting effect on the green transformation of industrial efficiency. (2) Digital finance can promote capital-using technological progress and support industrial green transformation with its price effect and scale effect. (3) Higher government environmental preferences and governance capacity can strengthen the green transformation effect of digital finance. Strengthening financial supervision and narrowing the digital divide will help digital finance better support industrial green transformation. Digital finance development can more effectively promote the industrial green transformation of non-SOEs and enterprises with high financing constraints and high financial dependence. (4) Considering the financial attributes and highly polluting characteristics of real estate, digital finance exacerbates the pollution of the real estate industry. This study helps clarify the mechanism of digital finance supporting green development and provides some ideas for China's digital finance development and green economy transformation. • Deconstructing the industry green transformation (IGT) into EFFI and STRU. • Analyzing the synergistic effects of digital finance on the EFFI and STRU of the industry green transformation. • The positive impact of digital finance on the industry green transformation is statistically significant and robust. • The green transformation incentive effect of digital finance has significant heterogeneity. [ABSTRACT FROM AUTHOR]

The present research work focuses on simultaneous optimization of prime energy consumption responses, surface roughness and material removal rate for sustainable machining operations. The experiments were conducted on rough turning of EN 353 alloy steel with multi-layer coated tungsten carbide insert. The effect of input parameters: nose radius, cutting speed, feed rate and depth of cut along with their interactions were studied on the response parameters viz. power factor (PF), active power consumed by the machine (APCM), active energy consumed by the machine (AECM), energy efficiency (EE), surface roughness (Ra) and material removal rate (MRR). The Taguchi’s L 27 orthogonal array had been used for design of experiments by using Minitab 16 software. The weights of importance to the responses were assigned by Equal, Analytical Hierarchy Process (AHP) and Entropy weights method. The multi performance composite index (MPCI) was obtained by Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method and was optimized with Taguchi method. The results showed that the MPCI with these three different weight criteria had different optimum control factor levels. At optimal turning parameters of MPCI using AHP weights, Equal weights and Entropy weights, there was an improvement in MPCI of 319.72%, 45.38% and 9.02% respectively compared to turning parameters in common use. The depth of cut was found to be a vital parameter for MPCI with AHP weights and nose radius for MPCI with Equal and Entropy weights. Hence the choice of method of assigning weights of importance to the responses and even the optimization method plays important role in decision making in multi objective optimization. [ABSTRACT FROM AUTHOR]

Data Envelopment Analysis (DEA) is a well-known tool used to assess the efficiency of homogenous units. In a DEA study, outputs are generally considered as the benefits gained and inputs are defined as the resources or the factors that may affect the performance of decision making units. However, if there is a necessity to deal with undesired factors, they are either defined as inputs or as undesired outputs in the DEA model. This study focuses on cement manufacturing facilities and aims to assess the effect of undesired outputs such as the amount of emissions that requires to be minimized and location of the facilities that needs to be maximized to avoid side effects of polluted air. This study considers eleven cement manufacturing facilities that are member of Cement Manufacturers’ Association of Turkey. DEA models are defined for common input and outputs available in the literature and for the proposed input, output, and undesired outputs. It is concluded that there is a significant difference in terms of consistency for the performances of cement manufacturing facilities when undesired factors are included and weights are assigned. [ABSTRACT FROM AUTHOR]

More environmentally-benign processes are required for the production of important chemicals such as ammonia. Techno-enviro-economic studies that utilize process modeling and optimization play a decisive role in predicting the viability of these processes, but they tend to focus on a single geographical location. This limits the usefulness of the results from such studies, because it is hard to compare results for different feedstock and location factors. Thus, the present study compares the economics and environmental potential of several variations of a novel biomass-based ammonia production process in different locations. The process is simulated for three biomass feedstocks grown in Australia, Brazil, and India. A comprehensive economic analysis and life cycle assessment is performed for the different process variants. A Multi-Objective Optimization (MOO) approach is used to minimize the manufacturing costs and the environmental impacts of the biomass-to-ammonia process specific to each feedstock and country. The Indian scenario was found to be the most favorable economically, whereas the Brazilian scenario had the lowest greenhouse gas potential. The results demonstrate that each type of biomass is specific to its location and both the economic and environmental profiles are strongly related to the location. The results of the individual studies are superimposed to provide a Global Pareto Front for the cost and environmental impact of the production of ammonia from biomass. This provides a very useful resource for future researchers who can compare results for alternative biomass, locations and processes. [ABSTRACT FROM AUTHOR]

The world is moving towards renewable energies as an alternative to fossil fuels. The photovoltaic technologies have the highest capacity increase rate among all the renewable energy systems throughout the last decade. Therefore, the huge amounts of photovoltaic wastes from such significant global installations are inevitable and needs to be dealt with sooner than later to increase the potential of PVs being an affordable and clean energy source. This work is split into two parts with different models. The first one mathematically models the PV waste projection using the Weibull distribution and socio-environmental decision-making factors while connecting them to the power purchase agreements (PPAs). This model uses data from both c-Si and CdTe PV projects in the United Arab Emirates (UAE). This model's results showed the possibility of increasing the PV projects operational age in UAE to 30 years for both technologies with 2030 being the best and latest year to start PV waste management procedures with the profitable reusability of PVs after projects' decommissioning. The second part is an optimization model for the PV waste and installations management by controlling the total future PV installations and possible PV replacements, while considering budget limitations and dismantling capacities. With a planning horizon until the year of 2100, this model's results suggest annually installing 670 MW of new PVs to achieve 50% of the country's consumption by 2030 and 100% by 2040 without any power shortage or outage. Finally, the models are flexible and extremely beneficial for future works for improvements, results comparison, and to design PV waste management centers or dismantling facilities. • Projected PV wastes through socio-environmental factors and Weibull distribution. • Built an optimization model to balance PV installations with waste replacements. • Unprecedently improved both c-Si and CdTe PV waste management plans in the UAE. • Install 670 MW of PVs annually to achieve 50% of the country's consumption by 2030. • Required annual replacements will start exceeding 100 MW by 2040. [ABSTRACT FROM AUTHOR]

This study intends to provide an insight into China's nonferrous metals industry production based on the analysis of the environmental efficiency, the Malmquist productivity index (MPI), and the Malmquist–Luenberger productivity index (MLPI). The empirical experiment based on the annual data of 27 regions (including provinces, autonomous regions and municipalities) of China during 2003–2009 shows the following results. First, the industry's environmental efficiency in the east area is mostly higher than that of the other area. Second, the industry's average annual change of MPI and MLPI in China were 4.4% and 0.9%, respectively. This indicated that the total factor productivity growth of the industry was overestimated if undesirable outputs were ignored. Third, the industry's productivity was mainly affected through technological advances rather than endogenous factors such as improvements in managerial practices. Finally, during the worldwide financial crisis occurred in 2008, the industry's MLPIs exceeded the MPIs in most regions through measures such as adjustment of the product structure and elimination of backward production capacity. [ABSTRACT FROM AUTHOR]

Biodiesel is a clean renewable fuel which is an alternative source of diesel fuel in compression ignition engines without any modification. According to previous research, the importance of biodiesel production through heterogeneous transesterification of waste cooking palm oil (WCPO) over Sr/ZrO 2 catalyst has led to developing a new mathematical algorithm called Modified Data Envelopment Analysis (MDEA). MDEA, a hybrid of Data Envelopment Analysis (DEA) with Neural Network (NN), was proposed for experiment design of multi-response problems. It was validated with Response Surface Methodology (RSM), which is a statistical method. This method was developed to maximise Fatty Acid Methyl Ester (FAME) yield and five decision variables were considered. The optimum amount of methanol to oil molar ratio, catalyst loading, reaction temperature, reaction time on Ester yield, and free fatty acid (FFA) conversion were calculated via MDEA method. The obtained results showed that the derived optimal parameter-setting of the proposed method, MDEA, is more reliable and accurate than RSM. The errors of predicted Ester yields are 5% and 14% in MDEA and RSM. The calculated errors of conversions are 3% and 19% in MDEA and RSM. [ABSTRACT FROM AUTHOR]

This paper presents a new Total Site Heat Integration (TSHI) method for the design of integrated evaporation systems including vapour recompression that minimises energy use and/or cost objective functions. The design of integrated evaporation systems is a common industrial chemical and process engineering problem. The method defines a new hybrid Total Site Profile (TSP) as a key element of the new design method. This profile is a composite of nearby streams that may directly integrate with the evaporation system as well as stream segments from processes that require indirect integration via the utility system. The hybrid TSP plays an important role in the iterative optimisation of evaporation system design parameters including vapour recompression and evaporation load distribution to optimise objective functions such as total cost, total operating cost, and heat recovery. The new TSHI design method for evaporation systems is demonstrated using an industrial milk processing case study. [ABSTRACT FROM AUTHOR]

In process industries, a steam system is usually constructed to satisfy the demands of steam and electricity in a plant, in which steam turbines and electric motors are commonly used to drive rotating equipment, such as pumps and compressors. In this paper, a multi-objective optimization model for the design of a steam system with drivers option for rotating equipment is proposed to simultaneously minimize the economic and environmental objectives. It features that the energy performances of steam turbines and electric motors are embedded in the model, and the environmental impacts caused by both the material of equipment and the utilities consumption in the system are evaluated by life cycle assessment method. A steam system of the hydrotreating units in a refinery is taken as a case study to demonstrate the application of the proposed method. The Pareto front of the economic and environmental objectives is obtained, and three scenarios on the Pareto front are analyzed and discussed. Results show that appropriate drivers option can effectively reduce both the economic and environmental impacts of the steam system. In addition, the preference of steam turbines and electric motors in the system is intensively dependent on the two objectives. Consequently, the drivers option for the power demand in a plant should be determined before the entire steam system is designed and optimized. [ABSTRACT FROM AUTHOR]

It is crucial for the industrial sector to achieve the multifaceted or composite efficiency of energy savings and the minimization of environmental wastes in the present circumstances of worsening global warming and resource depletion. Furthermore, the positive effects of composite energy efficiency on sustainable growth could lead to practical questions for the industrial sector, to ensure that it consistently uses its energy and resources effectively. The present research examines the positive contribution of this composite efficiency to the growth of final outputs in this sector, using the two-stage method of Malmquist efficiency analysis (MEA) and the linear regression of panel data from about 154 Korean industries from 2010 to 2012. The results found that composite efficiency and changes in the production factors have positive impacts on industrial productivity. In particular, relative efficiency has a positive influence on productivity, but technical efficiency does not have a significant impact. Our findings suggest that industries may voluntarily make efforts to improve their use of energy resources, but they also need to invest in energy technologies and develop efficient production structures, with the help of public policies. [ABSTRACT FROM AUTHOR]

To enable the consideration of life cycle environmental impacts in the early stages of vehicle design, a methodology using the proxy of life cycle energy is proposed in this paper. The trade-offs in energy between vehicle production, operational performance and end-of-life are formulated as a mathematical problem, and simultaneously balanced with other transport-related functionalities, and may be optimised. The methodology is illustrated through an example design study, which is deliberately kept simple in order to emphasise the conceptual idea. The obtained optimisation results demonstrate that there is a unique driving-scenario-specific design solution, which meets functional requirements with a minimum life cycle energy cost. The results also suggest that a use-phase focussed design may result in a solution, which is sub-optimal from a life cycle point-of-view. [ABSTRACT FROM AUTHOR]

The sustainable development of port operation management is strongly related to the energy consumption of production at automated container terminals (ACTs). This paper focuses on the production activities at a container yard, which is the primary facility of ACTs. A digital twin-based approach is proposed to optimize the operation of an automatic stacking crane (ASC) handling containers in terms of energy consumption. A virtual container yard that syncs with a physical container yard in the ACT digital twin system for observation and validation is developed. A mathematical model is established to minimize the total energy consumption of completing all tasks. Then, the Q-learning algorithm is adapted to optimize a solution based on the operating data from the ACT digital twin system. Numerical experiments are conducted to demonstrate the effectiveness of the proposed approach by comparing it with two other solution algorithms, viz., genetic algorithm (GA) and particle swarm optimization (PSO). The total energy consumption of two operation strategies (i.e., centralized and decentralized) are also compared using the proposed digital twin-based approach. With digital twin, the operational environment and energy consumption are visualized to support optimization and management of ASCs. Managers and operators can choose an appropriate strategy according to the designated sustainable goal. [Display omitted] • A digital twin-based approach is proposed to study the port operations. • Digital twin and Q-learning are used to observe operation and optimize production. • The total energy consumption of handling containers is minimized. • The proposed approach is superior to 2 well established methods based on case studies. • The centralized and decentralized strategies are analyzed for the sustainability. [ABSTRACT FROM AUTHOR]

Carbon emissions from industrial production affect agricultural production, and forests have the benefit of being carbon neutral. Therefore, this study adopts the dynamic network data envelopment analysis (DEA) model, takes carbon emissions as the link between industry and agriculture, and explores the production efficiency of industry and agriculture. It further incorporates forest area as a carry-over for evaluation and discusses 27 EU members' dynamic overall efficiency and productivity changes in 2014–2018. The empirical results are as follows. 1) The EU countries' industrial stage efficiency is better than their agriculture efficiency, with Germany, Luxembourg, Malta, and the Netherlands exhibiting the best efficiency performance. 2) The overall efficiencies of the Czech Republic, Portugal, and Croatia are the worst, because their misallocation of resources and excessive energy input cannot improve their output value. 3) The agricultural productivity of EU countries is better than that of industry productivity. 4) The EU has made great efforts at planting forests. 5) As energy consumption and carbon emissions are still rising, the EU still needs to do more to achieve the carbon reduction goals of the Paris Agreement and the Eu's 2030 zero carbon emissions. • A dynamic network model assesses industrial and agricultural efficiencies in the EU. • Forests in the EU have grown slightly over time. • It is difficult for high-income economies to cut and reduce carbon emissions. • The EU members still need to do more to achieve their carbon reduction goals. [ABSTRACT FROM AUTHOR]

As an important part of China's chemical industry, chlor-alkali enterprises were featured by heavy consumption of natural resource and large amount of pollutants. Circular economy in chlor-alkali industry should be developed in China to achieve a balance between economic growth and resource consumption. This study took three chlor-alkali enterprises in Shanghai Chemical Industry Park as a case, and three scenarios were established for chlorine metabolism: Scenario 1 (Chlorine flows independently), Scenario 2 (Chlorine flows from Enterprise A to Enterprise B and C), Scenario 3 (Closed loop of Chlorine Gas). An integrated methodology based upon Substance Flow Analysis (SFA), Life Cycle Assessment (LCA), Life Cycle Cost (LCC), and Data Envelopment Analysis (DEA) was set up and used to evaluate the Chlor-Alkali Industrial Symbiosis. The results showed that the resource efficiency, production and conversion rate of chlorine was significantly improved with the establishment and optimization of symbiosis scenarios, which also showed very positive environmental and economic benefits according to LCA-LCC analysis. DEA was performed to analyze the Chlorine's resource efficiency in its metabolism, and the results showed that the efficiency of Scenario 1, Scenario 2 and Scenario 3 were 0.8548, 0.9490 and 1, respectively. Especially, in Scenario 3, a new chemical technology, catalytic oxidation of hydrogen chloride, can convert the by-product hydrogen chloride into chlorine, which can be reused and finally made a closed-loop in this industrial symbiosis. The results of this study can provide a new way to optimize the resource recycle, pollutants discharge and carbon emissions of chlor-alkali industry. [ABSTRACT FROM AUTHOR]

As an important part of China's chemical industry, chlor-alkali enterprises were featured by heavy consumption of natural resource and large amount of pollutants. Circular economy in chlor-alkali industry should be developed in China to achieve a balance between economic growth and resource consumption. This study took three chlor-alkali enterprises in Shanghai Chemical Industry Park as a case, and three scenarios were established for chlorine metabolism: Scenario 1 (Chlorine flows independently), Scenario 2 (Chlorine flows from Enterprise A to Enterprise B and C), Scenario 3 (Closed loop of Chlorine Gas). An integrated methodology based upon Substance Flow Analysis (SFA), Life Cycle Assessment (LCA), Life Cycle Cost (LCC), and Data Envelopment Analysis (DEA) was set up and used to evaluate the Chlor-Alkali Industrial Symbiosis. The results showed that the resource efficiency, production and conversion rate of chlorine was significantly improved with the establishment and optimization of symbiosis scenarios, which also showed very positive environmental and economic benefits according to LCA-LCC analysis. DEA was performed to analyze the Chlorine's resource efficiency in its metabolism, and the results showed that the efficiency of Scenario 1, Scenario 2 and Scenario 3 were 0.8548, 0.9490 and 1, respectively. Especially, in Scenario 3, a new chemical technology, catalytic oxidation of hydrogen chloride, can convert the by-product hydrogen chloride into chlorine, which can be reused and finally made a closed-loop in this industrial symbiosis. The results of this study can provide a new way to optimize the resource recycle, pollutants discharge and carbon emissions of chlor-alkali industry. [ABSTRACT FROM AUTHOR]

Considering the environmental governance dilemma caused by environmental decentralization, this study aims to explore whether the strategic synergy between local and neighborhood environmental regulations can be an essential tool to improve green innovation efficiency and achieve sustainable development. Using the data of industrial firms from 2005 to 2019, and employing network slack-based measure and Tobit regression, this study provides empirical evidence that (1) the green innovation efficiency shows an upward trend in fluctuations but still has great room for improvement; (2) the direct impact of local environmental regulation on green innovation is positive, but the indirect impact through forcing firms to transfer into the neighborhood with loose regulation is negative, that is, the industrial transfer plays a suppression effect; (3) the strategic synergy of environmental regulations has U-shaped and direct effect on green innovation and also has a positive indirect effect through inhibiting the firm's behavior transferring into the neighborhood. This study reveals the influence mechanism of the strategic synergy of local-neighborhood environmental regulations and offers empirical evidence to explain the reason why synergistic environmental governance can effectively promote green innovation, which provides the theoretical guidance for government to formulate environmental policies and construct an environmental governance system. • The innovation efficiency shows an upward trend in fluctuations but has great improvement room. • The local environmental regulation significantly improves innovation efficiency. • The industrial transfer suppresses the effect of local regulation on innovation efficiency. • The strategic synergy of local-neighborhood regulations has U-shaped on innovation efficiency. • This strategic synergy also inhibits the firms' behavior transferring to neighborhood. [ABSTRACT FROM AUTHOR]

Facing water scarcity and water pollution, improving recycling water efficiency has become a crucial task, especially in urban areas. This research proposes a dynamic two-stage recycling model within the directional distance function (DDF) which takes reused water in the wastewater treatment (WT) as a recycled product for clean water use (WU) stage's input in the next period. To comprehensively evaluate the efficiency of industrial recycling water from the perspective of quality and quantity, greywater footprint and wastewater discharge are treated as unexpected outputs. Moran' I and Spatial Error Model (SEM) are applied to analyzing the spatial correlation and screening out the key influencing factors of industrial recycling water efficiency in China, furthermore, geographically weighted regression (GWR) model being built to measure spatial heterogeneity of the key influencing factors. The results reveal that: The overall efficiency of industrial recycling water efficiency in China is 0.75, which has not reached the effective utilization status. The integrated system is efficient if and only if both subsystems are efficient, especially wastewater treatment subsystems. China's industrial recycling water efficiency does not show obvious spatial autocorrelation, and its local differences have experienced the transformation from spatial agglomeration dominated by wastewater treatment subsystems to spatial heterogeneity dominated by clean water use subsystems. Besides, water resource endowment and water structure are conducive to improving the efficiency, while industrial water intensity inhibits its improvement. There still existed spatial heterogeneity of influencing factors where regional industrial structure and industrial water intensity effect acted as a stimulus to industrial recycling water efficiency in the central and western regions, in contrast, water resources endowment and water structure mainly boosting in the eastern region, and environmental negative effect mainly inhibiting in the southeast coast and central region of clean water use efficiency. Some policy implications from provincial and national perspectives are suggested. [ABSTRACT FROM AUTHOR]

The stability requirement for node enterprises within Ecological Industrial Chain ( EIC ) has a high degree of functional similarity with the reliability of engineering components. Thus, a methodology for EIC design optimization is established in this study based on the reliability theory. Results showed that series structure had weaker stability than parallel structure. The stability of entire system is reduced with the increase of the number of series, and node enterprises with smaller reliability showed greater contribution to the system stability. On contrary, for the parallel structure, node enterprises with higher reliability had greater contribution to the system stability. To improve the system stability, it is crucial to maintain the weak parts of system or to introduce an appropriate number of “spare parts”, i.e. to adopt parallel structure and reduce the number of enterprises series. For the parallel structure, priority must be given to those enterprises with higher reliability. Similarly, other constraints (e.g. economic costs and resource constraints) should also be taken into consideration. The redundant design of EIC becomes nonlinear planning decision problems. Novel nonlinear programming model for redundant EIC design is proposed in this study based on the reliability theory, and is effectively verified by means of MATLAB software programming and empirical analysis. Results provide a theoretical basis and practical reference for decision making process of optimizing the design and management of EIC . [ABSTRACT FROM AUTHOR]

When municipal waste scenarios are compared by using Life Cycle Assessment, the comparison is usually carried out among a limited number of alternative scenarios identified in advance. Therefore, however accurate and broad the scenario definition may be, the scenario actually generating the lowest environmental impacts might just not be included among the alternatives proposed and analysed. To overcome this limitation, this paper proposes linear programming models developed to identify, among all the potential scenarios, the waste management scenario that minimises one particular environmental impact or a set of impacts at the same time, using environmental data from Life Cycle Assessment. Besides describing the proposed models, a concise overview of solution methods for multi-objective linear programming is provided. These models were tested in a case study and the results obtained are here presented and analysed. As a case-study, a suitable waste management system in the Abruzzo Region, Italy, was identified. In addition, a further hypothetical waste management context, also including an incinerator plant, was considered. Moreover, a sensitivity analysis was carried out to identify how changing distances to plants may affect optimal scenarios. As a result, different best-performing scenarios for the analysed waste management system were obtained, one for each single impact category considered, and one for each solution method adopted. Furthermore, the analysis of the hypothetical context shows how the introduction of an additional treatment plant could affect the system. Both distances and the solution methods used affect the results. The models developed could be used in decision-making processes to identify the best-performing scenario of a waste management system from the environmental point of view. The models are easy to apply and flexible, since they can be modelled according to the context to be analysed by introducing new factors. [ABSTRACT FROM AUTHOR]

Collaborative governance is increasingly advocated to address the ecological risk management issues that occur during urban agglomeration developing. However, how to form strong and effective collaboration is still a great challenge among multiple cities in urban agglomeration. By analysing the multiple ecological risk transmission pathways of the case of Pearl River Delta Urban Agglomeration (PRD) in China, this paper aims at deconstructing the complex structure and connection types in urban agglomeration, as well as exploring the inherent mechanism of ecological risk governance to achieve collaboration. Thus, a new Bayesian network model of ecological risk transmission is developed to visualize the key connection notes of risk transmission process. Testing the impacts of (1) number of collaborative cities, (2) spatial distance factor and (3) risk transmission links, we can find the optimal cooperative risk management strategy by reducing the probability of occurrence of key nodes and intervening on the critical path of the risk transmission process. The results show that (1) The current collaborative governance plan in the PRD is mainly formulated by large cities driving small surrounding cities, which is not an optimal strategy. (2) The management effect of ecological risks in urban agglomerations is not necessarily positively correlated with the number of collaborative cities. There are multiple combinations methods under a certain number of collaborative cities and the effects of ecological risk collaborative governance are different. (3) Collaboration governance of urban agglomeration should be based on the overall planning of urban development, and comprehensively consider collaboration number, spatial distance and association between cities. [Display omitted] [ABSTRACT FROM AUTHOR]

The coagglomeration of manufacturing and producer service industries and technological innovation plays an essential role in China's booming economy. Considering the coordinated development goal of the environment and the economy, from the life-cycle perspective of industrial coagglomeration, this study empirically examines whether industrial coagglomeration has dynamic influences on environmental pollution and verifies the direct and indirect impact mechanisms based on the panel threshold model and mediation model. Panel data for China's 30 provinces from 2008 to 2019 are employed. The results suggest that the impact of industrial coagglomeration on environmental pollution is positive and has significant threshold effects. As industrial coagglomeration deepens, its aggravating effect on environmental pollution presents an inverted S-shaped trend. The impact of industrial coagglomeration on technological innovation is negative. With the deepening of coagglomeration, the adverse effect gradually decreases. Additionally, technological innovation is conducive to the reduction of environmental pollution. It acts as a vital mediator between industrial coagglomeration and environmental pollution, and its mediating effect varies with the dynamic evolution of industrial coagglomeration. These conclusions show the importance of increasing industrial coagglomeration efficiency and stimulating the effective play of positive environmental and innovative externalities to realize the sustainable pursuit of economic and ecological benefits. 1 •Industrial coagglomeration (Coagg) intensifies environmental pollution (Ep). • The impact of Coagg on Ep is inverted S-shaped and has threshold effects. • The influence mechanisms of Coagg on Ep are divided into direct and indirect ones. • Technological innovation (Tec) acts as a vital mediator between Coagg and Ep. • The negative effect of Coagg on Tec decreases with the dynamic evolution of Coagg. [ABSTRACT FROM AUTHOR]

Material and energy flow analysis (MEFA) is used by many companies for sustainability assessments of their production systems. MEFA generally leads to large and complex system models for which optimal operating conditions are hard to find manually. This article therefore presents an extension of MEFA towards mathematical programming that provides powerful methods for system optimization. A theoretic concept for this methodological integration is developed, illustrated by means of a simplified example and finally applied to a case study of an industrial waste treatment scenario. Technical feasibility is thus demonstrated. Moreover, the algebraic transformation of material flow models into mathematical programs reveals, on a conceptual level, the basic principles of an optimization-oriented MEFA. [ABSTRACT FROM AUTHOR]

The presented study investigates the application of a Model Predictive Controller, equipped with linear-programming based optimizer, with application to energy management in production environments. The study focuses on an automotive OEM assembly plant that consumes fossil fuel (natural and landfill gas) in addition to electricity drawn from the grid. This manuscript details the optimization structure under two different cost functions; specifically, cost-savings and energy efficiency. The predicted results are in agreement with the current plant consumption and demonstrate the conflicting nature of the two cost models proposed; thusly, highlighting the importance of objective decision making tools, driven by specific performance criteria, in managing the energy and the overall sustainability of production environments. Additionally, the study discusses the role of the co-generation process efficiency on the overall plant energy consumption. [ABSTRACT FROM AUTHOR]

Circular economy plays an essential and useful role in China in considering economic and ecological sustainability. Individual firms, as the primary implements of a circular economy, are facing many obstacles at present in aspects of resource and ecological efficiency. Therefore, this study presents a set of tools to help decision makers better solve these problems and to guide resource-based chemical industries in sustainable development. First, this study describes resource efficiency based on the SFA of a selected P-chemistry firm and identifies the key potential opportunities for improvement using analysis tools and assessment tools. Furthermore, by applying eco-design and decision tools, a firm-level, P-chemical, circular economic system is designed and constructed. A phosphorus chemical optimization model is established, and relevant successive scenarios are generated. Finally, the corresponding feasible solutions and policy recommendations are proposed to improve economic benefit, resource efficiency, waste recycling rate, and eco-efficiency. After industry design, planning, and technological progress, the total economic benefit increases dramatically, and the recycling efficiencies of accompanying resources (F, Si, I, and S) improve by different degrees. The results demonstrate that the economic benefit of phosphorus products increases by 28.5%, and P utilization efficiency correspondingly increases from 81.1% to 94.7%. The comprehensive utilization efficiency of phosphor gypsum increases to 100%, and the eco-efficiency could be improved significantly by eliminating the phosphor gypsum stack. This study demonstrates that technological progress in mineral processing and the production of associated products is the endogenic motivation to increase economic benefit and improve resource efficiency. The method proposed in this paper can be applied, duplicated, and spread not only within the P-chemical industry but also in other resource-based chemical industries. [ABSTRACT FROM AUTHOR]

The process of a regional industrial system in China can be separated into two internal stages: production stage and pollutant abatement stage. This paper aims to examine the efficiency of Chinese regional industrial systems by taking the operational performance of its two internal stages into consideration. Unlike traditional data envelopment analysis models that treat decision making units as “black box” when measuring their efficiencies with undesirable factors, this paper proposes a two-stage model based on slacks-based measure to evaluate the efficiency of Chinese regional industrial systems. By decomposing the efficiency into production efficiency and abatement efficiency, the proposed model can estimate the efficiencies of the whole regional industrial system, its production stage and abatement stage simultaneously. The model provides a way of improving performance of a regional industrial system through identifying its inefficient internal stages. This can help to find out the main sources of the inefficiency that arise from the internal stages within the system, which cannot be done by using conventional environmental data envelopment analysis models. Findings resulting from the model application show that there are great disparities in regional industrial systems' efficiencies, and the inefficiency of Chinese industrial system is largely driven by the abatement stage. [ABSTRACT FROM AUTHOR]