Search

The pulp and paper industry accounts for approximately 5% of total industrial energy consumption and contributes 2% of direct carbon dioxide (CO 2 ) emissions from industries. World paper and paperboard demand and production are increasing significantly, leading to an increase in this sector's energy use and CO 2 emissions. Although current studies identify a wide range of energy-efficiency technologies that have already been commercialized for the pulp and paper industry, information is limited or scattered regarding new energy-efficiency technologies that are not yet fully commercialized. Development of emerging or advanced energy-efficiency technologies and their deployment in the market will be crucial for this industry's mid- and long-term energy saving and climate change mitigation strategies. This paper compiles available information on energy savings, environmental and other benefits, costs, and commercialization status for 25 emerging technologies to reduce the energy use and CO 2 emissions. The purpose is to provide a well-structured comprehensive review on these emerging energy-efficiency technologies for engineers, researchers, investors, policy makers, pulp and/or paper companies, and other interested parties. [ABSTRACT FROM AUTHOR]

Cities have emerged as critical and challenging places for promoting the green and low-carbon transformation of the economy and society in the context of the "dual carbon" targets. Meanwhile, fiscal policy is also an indispensable component of the public policy framework supporting the green and low-carbon transformation. This paper uses the pilot project of "Comprehensive Demonstration Cities for Energy Conservation and Emission Reduction Fiscal Policies" ("ECER-CD" policy) implemented in China since 2011 as a quasi-natural experiment. This research theoretically analyzes and empirically tests the energy conservation and emission reduction effects of fiscal policies supporting green and low-carbon transformation utilizing methodologies such as time-varying DID and multiple periods and multiple groups of DID. The study finds that the pilot cities effectively reverse the behavioural bias of local governments and promote energy conservation and emission reduction efforts. This conclusion holds after undergoing robustness tests such as parallel trend analysis and heterogeneity treatment effects. The effectiveness of the pilot policy is attributed to the upgrade of industrial structure, improvement of energy efficiency, and the effects of green technology innovation. However, cities' geographic location and resource dependency can interfere with the effective implementation of policies. This paper also further explores the environmental dividends and economic consequences of the policy and finds that the pilot cities have certain environmental dividends and do not significantly restrain economic and social development. This study broadens the research perspective on fiscal policies in energy conservation and emission reduction and clarifies the pathways through which fiscal policies promoting green, low-carbon transformation drive energy conservation and emission reduction in cities. Moreover, it also improves the use of the Difference-in-Differences method in evaluating policy effects in scenarios such as the overlapping implementation of pilot policies and policy withdrawal. Finally, this paper proposes policy recommendations to provide more empirical evidence for China to accelerate the green and low-carbon transformation of the economy and society. [ABSTRACT FROM AUTHOR]

Energy quota trading is critical to both energy conservation and the achievement of dual-carbon goals. However, little remains to be done on total factor productivity and economic potential for Chinese industry. The purpose of this paper is to counterfactually model and explore the effects of energy quota trading on total factor productivity and economic potential in industrial sector. We propose a command-controlled DEA model and an energy quota trading DEA model through non-parametric linear programming based on two policy strategies of energy consumption control. We then assess total factor productivity and its growth sources for 35 two-digit industrial sector in China, as well as examine economic potential and optimal path forecasts for carbon peaking. The results show that total factor productivity and economic potential for energy quota trading are higher than those for command-controlled energy policy. Energy-saving effect can be achieved for energy quota trading because the total energy input is lower. Additionally, the sources of productivity growth differ in timing. The average economic potential and total factor productivity of different industries differ due to the heterogeneity of the production conditions and scale of development of individual market players. Moreover, the catch-up emission reduction path with an increase of 8% in output and 4.76% in energy consumption is the optimal carbon peaking path under energy quota trading. Our findings shed valuable light on China's efforts to expand energy quota trading for high-quality development in the context of carbon peaking. • Propose a command-controlled DEA model and an energy quota trading DEA model. • Assess TFP and its growth sources for industrial sector in China. • Compare the impact of different energy policies on economic potential and TFP. • Estimate the energy saving and emission reduction potential of energy quota trading. • Examine the optimal energy-saving and emission-reduction path forecasts for carbon peaking.. [ABSTRACT FROM AUTHOR]

Abstract Water pumping systems are widely used in industrial and civil applications. During their operational life, they consume energy and materials (mainly for installation and replacement of components). The aim of this paper is to optimize the pump operations in order to save energy and enlarge the operational life of the pumps and their components. This paper addresses the multi-period (e.g. 24-hours time horizon) optimization of pumping systems. To this end, we have developed a simulation-based optimization approach including novel relevant technical features of a generic but realistic pumping system, namely cavitation and overflow. The proposed multi-period optimization differs further from the classic static optimization (i.e. at the design stage), proposing a new dynamic approach in which pump activation is steered dynamically for an optimal management of the variability of water inflow. Furthermore, the problem includes constraints on the number of pump activations allowed to reduce material strain. The performances of different meta-heuristic optimization algorithms (e.g. genetic algorithm, simulated annealing and particle swarm optimization) for solving the problem are compared. The numerical results show that energy savings are possible with the dynamic approach and that particle swarm optimization and simulated annealing algorithms provide the most suitable solutions for this problem. Highlights • Three algorithms are compared to minimize energy pump consumption. • The pump model includes energy, cavitation, overow and activation frequency. • Static and dynamic optimizations are investigated. • The dynamic optimization can reduce the energy consumption by 6.5%. [ABSTRACT FROM AUTHOR]

Abstract The extensive use of energy-saving appliances can promote household energy conservation, which, to a certain extent, can help to alleviate haze pollution. Based on the Theory of Planned Behavior and Normative Activation Model, a research framework is developed in this paper to explore residents' intention to purchase energy-saving appliances under the influence of severe haze pollution. This paper takes the residents in Xuzhou as the object of survey. Then, the structural equation model and Bootstrap method are used to analyze the valid measurement questionnaires. The results demonstrate that residents had a very strong intention to purchase energy-saving appliances under the influence of haze pollution from the perspective of self-interest and altruism, respectively. Attitude, subjective norm, perceived behavior control and personal norm are the key factors influencing residents' purchasing intention of energy-saving appliances under frequent haze pollution, of which attitude is the most powerful influence. In addition, ascription of responsibility is a partial mediator between the relationship of awareness of consequences and personal norm, and together with awareness of consequences can positively influence personal norm. Finally, based on the empirical results, this paper proposes measures to guide consumers to buy energy-saving appliances. [ABSTRACT FROM AUTHOR]

Continuous growth of energy consumption for metro systems has raised the public's concern. Meanwhile, both operators and passengers pursue for efficient metro services, especially during peak hours. This paper aims at designing a bi-objective optimization model and a new solution approach so that the energy conservation of metro trains and less passenger waiting time can be achieved. Firstly, considering complex routes, a multi-particle train operation model with the objectives of punctuality, parking accuracy, energy efficiency and safety provided is established for the minimization of traction energy consumption through investigating the optimal force coefficients and coast positions, while suitable dwell times and headway times of metro trains are found trough building a timetable model, which balances the regenerative energy, transfer and non-transfer passenger waiting time. Secondly, a deep reinforcement learning (DRL) and non-dominated sorting genetic algorithm II (NSGA-II) based two-layer solution approach is introduced for model calculation. Finally, comparison shows that the proposed model can achieve the energy conservation of metro trains by 9.16% with passenger waiting time decreased by 15.88%. More experiments further demonstrate the superiority of the developed model and solution approach. [Display omitted] [ABSTRACT FROM AUTHOR]

The food industry is one of the world's largest contributors to carbon emissions, due to energy consumption throughout the food life cycle. This paper is focused on the residential consumption phase of the food life cycle assessment (LCA), i.e., energy consumption during home cooking. Specifically, while much effort has been placed on improving appliance energy efficiency, appliance models used in various applications, including the food LCA, are not updated regularly. This process is hindered by the fact that the cooking appliance models are either very cumbersome, requiring knowledge of parameters which are difficult to obtain or dependent on manufacturers' data which do not always reflect variable cooking behaviour of the general public. This paper proposes a methodology for generating accurate appliance models from energy consumption data, obtained by smart meters that are becoming widely available worldwide, without detailed knowledge of additional parameters such as food being prepared, mass of food, etc. Furthermore, the proposed models, due to the nature of smart meter data, are built incorporating actual usage patterns reflecting specific cooking practice. We validate our results from large, geographically spread energy datasets and demonstrate, as a case study, the impact of up-to-date models in the consumption phase of food LCA. [ABSTRACT FROM AUTHOR]

Under the policy of energy saving and emission reduction, technological innovation has become the key power-driver to improve energy utilization efficiency. By using the panel data of 21 industrial segments between 2000 and 2015, this paper investigates the driving effect of technological innovation on energy-utilization efficiency in strategic emerging industries and analyzes the critical factors influencing the driving effect of technological innovation by the stochastic frontier analysis method. The empirical result shows that technological innovation between 2000 and 2015 has had a significant positive driving effect on the energy utilization efficiency of strategic emerging industries and exhibits a development trend of year-by-year steady-state growth on the whole. The greater the value of the development expenditure of new green products and the investment in environmental pollution treatment, the greater the technological efficiency; the greater the value of the transformation expenditure of energy-saving technology, the greater the technological inefficiency. Finally, the paper proposes the countermeasures and suggestions for the driving effect of technological innovation on energy utilization efficiency in strategic emerging industries. An empirical study is made to analyze the driving effect of technological innovation on energy utilization efficiency, the positive and negative factors of technological innovation are forgotten. Strategic emerging industries can select optimal innovation behavior to improve quality and efficiency of energy utilization based on the results. [ABSTRACT FROM AUTHOR]

Coal mining activities have caused serious environmental problems; however, almost 30% of global primary energy demand is met using coal, making it difficult to replace in the near future. Under these circumstances, as it is not possible to completely cease coal mining activities, coal mines need to invest in cleaner production techniques to reduce environmental damage. To achieve pollution emissions and energy reductions, this paper proposes a dynamic multi-objective mixed 0–1 model based on ecological coal mining, in which environmental technological investment and production adjustments are integrated into a dynamic system to seek ecological and economic equilibrium, and emissions reductions and energy conservation are controlled using double dynamic transfer equations. Different from previous papers, this model considers the effect of production adjustments and energy conservation on the environment and the economy with the aim of achieving global optimization through integrated planning. To solve the proposed model, a hybrid algorithm with a standard and an antithetic method-based Particle Swarm Optimization (PSOs) is developed. A case study from Chaohua Colliery is presented to demonstrate the practicality and efficiency of the optimization model. The results and comparison analyses showed that as the dynamic adjustments strengthened the production and investment coordination for global optimization, integrated production and environmental investment planning provided coal mines with a superior method to solve conflicts between the ecology and the economy. [ABSTRACT FROM AUTHOR]

Existing studies pay little attention to when or under which conditions foreign direct investment (FDI) can spill energy-saving technologies. From a perspective of energy-biased technical change and using a two-layer nested constant elasticity of substitution (CES) production function, this paper investigates the energy-saving spillover effect of FDI on technical change (i.e., energy-saving spillovers) in China between 2002 and 2015. In particular, we consider the conditions of marketization, industry, technology, and labor mobility to examine whether and when FDI has energy-saving spillovers. The results indicate no income inequality effect, i.e., there is no evidence supporting that FDI flowing into low- and middle-income regions increases energy consumption, while FDI flowing into high-income regions conserves energy. However, there is a condition effect: FDI can improve (support the halo effect) or deteriorate (contradict the halo effect) the environmental performance under different conditions. Moreover, there is a threshold effect: the direction of FDI spillovers varies with the different levels of the threshold variables. An increasing marketization motivates enterprises to select energy-biased technologies. It is more likely to generate energy-saving spillovers in the regions with a lower specialized agglomeration level. FDI will have energy-biased spillovers when domestic technological level is relatively high with an evident energy-biased technology. In addition, a moderate labor mobility is beneficial to the energy-saving spillovers of FDI. [ABSTRACT FROM AUTHOR]

Hydraulic press machines (HPMs) are often preferred in metal processing for their high power-to-mass ratio, stiffness, and load capacity. Unfortunately, they are also known for their high energy consumption and low energy efficiency. The mismatch between installed and demanded power is the primary cause of low energy efficiency among HPMs. This paper proposes an energy-saving hydraulic drive system based on the flywheel energy storage system (FESS) to reduce the installed power and improve the energy efficiency. The FESS is used to store redundant energy when the demanded power is less than the installed power. During pressing with slow falling, the stored energy is recycled in combination with an AC motor to work against the heavy load. Furthermore, unlike traditional FESS's, the variable frequency drive (VFD) and specific control algorithm are adopted to improve the energy storage capacity of the FESS, as well as the operation and lifetime of the hydraulic drive system. The proposed method presents the first integration of both VFD and FESS into a hydraulic drive system. Using this method, the low energy efficiency caused by high installed power can be significantly improved, and the negative effects caused by mismatches between the installed and demanded power can be largely mitigated. Finally, a test platform is set up to verify the effectiveness of the proposed hydraulic drive system. The results show that the installed power and energy consumption are reduced by approximately 30% and 40%, respectively, based on the working characteristics of a traditional drive system. • An energy-saving hydraulic drive system based on the flywheel energy storage system and variable frequency control is developed. • The installed power and average energy consumption of the traditional hydraulic press machines can be reduced by 30% and 40%, respectively. • The proposed hydraulic drive system has the same working characteristics and processing properties as the traditional drive system. [ABSTRACT FROM AUTHOR]

Research on energy-saving retrofits of the existing industrial systems can effectively improve the systems' energy-saving level and increase company revenue. The energy-saving bottleneck diagnosis for systems is the foundation of the energy-saving retrofit design. The diagnosis also aims to yield a more targeted energy-saving retrofit, thus ensuring the energy-saving effect and investment income of the transformation project. Therefore, this paper proposes a new method to diagnose the energy-saving bottleneck of the existing industrial systems. First, the energy-saving bottleneck diagnosis is decomposed into two parts: the diagnosis of energy-saving bottleneck units and the diagnosis of energy-saving bottleneck factors. Then, the energy density decomposition method is improved and a multi-mode energy efficiency density decomposition method is proposed. Next, an energy-saving bottleneck diagnosis method for industrial systems based on multi-mode energy efficiency density decomposition and an orthogonal test method is proposed. The proposed method can analyze the energy-saving potential of existing systems, accurately locate energy-saving bottlenecks, and avoid the dependence on a large amount of expert experience or complete production data in the existing methods. Finally, the proposed method is applied to an actual circulating cooling water system and the system energy-saving bottleneck diagnosis is realized, thus verifying the practicability of the method. • Energy-saving bottlenecks in industrial systems are analyzed and decomposed. • A method for energy-saving bottleneck diagnosis from two directions is proposed. • An improved energy efficiency density decomposition method is proposed. • The diagnosis of energy-saving bottlenecks in industrial systems is achieved. • The verification is performed for an industrial circulating cooling water system. [ABSTRACT FROM AUTHOR]

For many years, China has invested effort into achieving resource conservation and environmentally friendly economic development. The measures implemented include promoting technological innovation, market-oriented reform and industrial structure adjustment. But there are open questions: What have the effects of these measures been? Have they helped China achieve win-win development in terms of its resources, environment, and economy? This paper aims to answer these questions by using a newly proposed global three-hierarchy meta-frontier Luenberger index that can quantify the effects of promoting technological innovation, industrial restructuring, etc., on economic growth, energy conservation and emissions reduction. The results show that (1) during 2001–2016, China's energy efficiency, economic efficiency, and emissions efficiency improved, indicating that China's efforts have brought about the win-win development of resources, the environment, and the economy; (2) the implemented measures have heterogeneous effects on economic growth, energy conservation, and emissions reduction. The implemented measures are generally beneficial to energy conservation and emissions reduction but potentially harmful to the economy; (3) the effects of these measures on economic growth, energy conservation and emissions reduction across China's regions and provinces are also quite different, indicating that local provincial governments should have a clear understanding of their own characteristics before implementing the relevant policies and measures. • A global three-hierarchy meta-frontier Luenberger index was proposed for the study. • It can quantify the effects of China's efforts on economy, energy, and emissions. • Results show that China's efforts have brought about a win-win development. • There are the heterogeneities of China's pathways to economic growth, energy conservations and emissions reductions. • The future strategies for China's win-win development should take the heterogeneities into account. [ABSTRACT FROM AUTHOR]

The annual consumption of petroleum products in India was about 221 million metric tons in 2015. Of this, 84% was imported. The Indian industrial sector accounts for about 16%-20% of the total fuel consumption for thermal energy for different heating applications in the temperature range of 50°C--250 °C. Solar collectors can meet these temperature requirements and offer the possibility to mitigate the consumption of oil. This study highlights the fact that conversion efficiency from solar energy is much higher for process heating than for electricity generation and that process heating applications constitute a significant share of industrial energy consumption. In this paper, a methodology has been developed to estimate the potential for integration of solar collectors for process heating. The methodology employs process operating temperatures to select the type of solar collectors. The size of the solar field is estimated taking into account the thermal heat loads, working fluid and temperatures of these processes, the efficiency of the chosen solar collectors, location-based solar irradiance and capacity utilization of the solar collectors. The proposed methodology has been validated with a software tool called System Advisor Model (SAM). The techno-economic analysis will indicate the viability of solar systems for integration in industries. Therefore, the consociated parameters on economic (capital cost, fuel oil savings, monetary benefits), financial (Payback periods, Rates of Returns) and environmental (Carbon savings) are estimated. Further, the methodology has been applied to select Indian industries to verify its potential quantitatively. The industries selected include Textile, Pulp & Paper, Dairy, Leather and Automobile. Process-wise energy demands are considered while estimating the potential as the fuel requirement offset by solar energy in terms of absolute fuel oil savings, monetary benefits and carbon savings. The other economic and financial parameters mentioned above were estimated to verify the capability and present the market position of solar systems. Further, sensitivity analyses have been performed with respect to solar energy penetration and fuel oil prices to address the viability of integration of solar energy for process heating. [ABSTRACT FROM AUTHOR]

This paper investigates CO 2 emissions produced by two different container terminal operating models (tire transtainers and rail transtainers) at the port of Kaohsiung, and seeks to determine energy saving and CO 2 reduction strategies for shipping companies and terminal operators in order to comply with green port requirements. This paper's research methodology involves carbon footprint analysis and gray relational analysis. Carbon footprint analysis is employed to calculate the CO 2 emissions per container of two different container terminal operating models employing data for various areas (such as the berthing area, container yard, and gate area), where the raw data is collected from shipping companies or terminal operating companies at the port of Kaohsiung. Gray relational analysis is then used to determine the ranking order of different container terminal operating models based on the green port assessment criteria of working time efficiency, energy consumption, and CO 2 emissions. The chief findings of this paper are that the ranking order of container terminal types based on carbon footprint is tire transtainer ahead of rail transtainer; optimal green port assessment criteria constituted working time efficiency, energy cost, and CO 2 emissions; and use of container handling equipment with high operating efficiency can not only accomplish work rapidly, lessening the berthing time of ships in port, but also reduce energy costs and CO 2 emissions. [ABSTRACT FROM AUTHOR]

Abstract This paper is a multi-case study of three oil and gas projects in Brazil that investigates the tacit knowledge on how to best manage energy use during the construction phase. Twenty-two in-depth interviews form the primary evidence of the case studies. The methodology incorporates network analysis of concepts that influence energy use to formalize the case studies and collect additional knowledge. The framework comprises thirteen construction activities and twenty-one systems and factors related to design, resources and site characteristics, specific to the construction domain. This set of concepts can influence the energy consumption during the construction phase. Although these concepts are present in nearly every project, their dynamics and their inter-relations with project-specific systems change, depending on the context of the project. The proposed method, which employs network analysis, help identify their interrelationships and relative importance of these concepts. In addition to the opportunities and lessons learned that can guide future energy assessments and improve energy use in construction projects, the results show how promising network analytics is to obtain knowledge usually difficult to perceive in traditional knowledge processes. Besides, this work highlights the importance of supporting collaboration between project team members to study and decide on the plans to manage/reduce energy consumption during the construction phase in oil and gas facilities. While the energy savings are smaller than the upstream and operation phases, it has received much less attention. It is also a phase with much more subjective and contextualized knowledge – making the use of case-based analyses more suitable. Highlights • Supports collaboration in studying and planning energy use during the construction phase of O&G projects. • Three case studies are conducted supported by in-depth interviews. • Network analysis is used to represent construction activities, factors and systems. • The approach represents a meaningful way to formalize the knowledge in the cases. • Can help formalize the knowledge contained in a text case. [ABSTRACT FROM AUTHOR]

Abstract Energy conservation and emissions reduction have been the focus of the road transport sector due to its energy-intensive and air pollution-intensive nature. It also embodies the imprints of human technological progress. This paper compares the energy consumption of the road transport sector in China and OECD countries. We used time series and panel data, co-integration analysis, error correction model and dynamic model to study the impacts of the major influencing factors such as income, income structure, urbanization, price, and technological advancement on gasoline and diesel consumption in road transport. Overall, China's fuel consumption is influenced mainly by investment, government expenditure and demographic changes such as urbanization, while the fuel consumption of OECD countries is mainly driven by household final consumption expenditure. In the short run and from a dynamic perspective, China's fuel consumption is less influenced by its historical consumption than current influencing factors, while that of OECD countries is more affected by historical fuel consumption. Based on the analysis and findings of this study, some policy implications are proposed. [ABSTRACT FROM AUTHOR]

Abstract Large amount of energy is consumed to meet user satisfaction in public buildings, which causes carbon emission and results in environmental problem. A direct method to reduce this carbon emission is restricting opening area in public buildings. However, restricting opening area causes occupant satisfaction reduction. Trade-off carbon emission and occupant satisfaction needs to be concerned in building operation strategy design. In this paper, we developed a new integrated modelling method to trade-off between the carbon emission and occupant satisfaction of restriction strategies. We designed a case study in the sixth teaching building (STB) in Tsinghua University. Survey and field investigation were conducted to obtain data and build model. Integrated model result showed that satisfaction increases with the increase of carbon emission, while there exists cluster division and marginal diminishing patterns. By analyzing the performance of strategies with different calculation methods, we found that most optimal strategies open section B and C in STB. Meanwhile, when occupant number is 1,000, 2000 and 4,000, corresponding average satisfaction is 71.4%, 58.8% and 40.4%. It indicates that optimal operation strategy performance changes with the increase of occupant number, but the fluctuation is relatively mild. This integrated model has prospect in guiding energy conservation operation strategy design. It also supports real time monitoring and has potential in interactive platform application. Highlights • We developed a tradeoff model with carbon emission and occupant satisfaction in public building. • Our model found out optimal restriction strategies and strategy performance patterns. • Strategy performance slightly changes with the increase of occupant number. [ABSTRACT FROM AUTHOR]

Abstract The construction industry is one of the largest energy consumers and CO 2 emitters in China. This paper primarily aimed to explore the driving forces of energy-related CO 2 emissions (ECE) from the construction industry. Adopting a comprehensive decomposition approach, this study decomposes the changes in ECE into eight factors. The main results provide the following findings. (1) Industrial activity was the largest factor pushing the growth of CO 2 emissions, driving up CO 2 emissions in all years and contributing to a 174.65 Mt CO 2 emissions increase in total. (2) In contrast, advances in industrial output technology represented the dominant factor inhibiting CO 2 emissions, cumulatively reducing CO 2 emissions by 99 Mt. (3) The effects of potential energy intensity changes and industrial output technical efficiency fluctuated in different years but exerted positive effects on CO 2 emissions over the entire period. (4) Additionally, changes in spatial structure, energy-saving technology, and energy consumption structure as well as energy usage efficiency all contributed to emissions reductions to varying degrees. The CO 2 emissions of the construction industry increased in all provinces, while emissions changes and their factor effects varied distinctly across provinces. Highlights • Direct and indirect CO 2 emissions in China's construction industry are calculated. • Impacts of driving factors are quantified by combining the PDA and IDA methods. • Industrial activity is mainly responsible for CO 2 emissions increase. • Industrial output technology change is the dominant curbing factor. • Factor effects of China's construction industry vary distinctly across provinces. [ABSTRACT FROM AUTHOR]

A fundamental problem in the management of energy usage is the inability to clearly predict any possible energy saving opportunities. The cost of both under or overestimating potential returns on investment can be prohibitive to a decision maker. In recent years the simulation of energy usage using existing manufacturing simulation tools has increased in popularity among researchers, but it is decision makers who need to see the benefits of this discipline. This paper proposes an interactive manufacturing energy management toolkit which makes use of existing productivity simulation models for the prediction of energy usage. An interactive Microsoft ® Excel ® based toolkit is developed to control Lanner's WITNESS ® discrete-event simulation software using Microsoft ® Visual Basic ® for Applications. The toolkit has the ability to predict potential areas where energy saving opportunities can be made within a complex manufacturing line, and is accessible from management presentations and proposals. The interactivity of the toolkit provides an environment which facilitates efficient hypothesis testing. The paper includes an industrial case study where the approach was used to quantify theoretical savings from certain energy usage reduction scenarios within a complex automotive engine manufacturing line. [ABSTRACT FROM AUTHOR]

Significant increases in industry energy efficiency are crucial for the transformation of the world's energy systems. Many production sites offer high energy savings capabilities, and if these are accompanied by short periods of economic amortization, companies should be willing to act. This case study provides a novel and extended energy assessment for plastics processing plants including primary energy, greenhouse gas emissions, and energy costs. The research distinguishes between the standard form of separate individual energy assessments and provides a more innovative holistic approach taking all relevant energy flows within the production system into account. Dynamic simulation offers a quick and effective way to predict the results of the possible energy saving measures highlighted in this analysis. The paper presents validated energy consumption simulations based on realistic processing conditions for two injection molding factories in different climatic zones. The results show that combining a number of separate energy saving measures can reduce the primary energy demand by around 26% for a German plant under temperate climate conditions and 20% for a Western Australian plant under Mediterranean conditions. However, when the separate energy saving measures are holistically combined the reduction in energy use significantly increases to 41% and 43% respectively. This holistic energy strategy involves incorporating better cogeneration and waste heat recovery options. For small and medium sized companies in particular major energy infrastructure investments may often be considered too expensive without examining the extended benefits from a holistic energy assessment perspective. In contrast, a holistic framework, like the one suggested in this paper could provide a number of new options for increasing energy efficiency that individually might normally not be accepted under conventional economic rate of return analysis. [ABSTRACT FROM AUTHOR]

Changing people's behaviour in relation to energy consumption will be one of the most important challenges in the near future. We analyzed the determinants behind individuals' decisions to adopt curtailment behaviour or to purchase energy saving products. Using data from 213 university students, we explored the influence of personal capabilities and moral norms, along with trust in information on energy saving actions provided by different entities on two energy saving behaviours. The results of the statistical model emphasise how personal norms and trust in information provided by private companies, on the one hand, and family and friends, on the other, strongly influence the adoption of energy saving actions and curtailment behaviours. The paper reveals the pivotal role of private companies in developing the market demand for energy-saving products by providing credible and scientifically-based information on environmental performance. The paper also contributes to strengthening the reliability of value-belief-norm theory and emphasizes the role of trust in information as a contextual factor that influences the adoption of a pro-environmental behaviour. [ABSTRACT FROM AUTHOR]

Legislation targeting business carbon emissions typically excludes the significant portion of the economy comprised of small- and medium-sized enterprises (SMEs). As an alternative many governments have developed voluntary programs to assist SMEs to reduce emissions and increase their energy efficiency. To maximise benefits associated with such programs, this paper seeks to provide insights into key factors contributing to the design of successful voluntary energy efficiency programs for SMEs. This is achieved by comprehensively analysing the factors that impacted the uptake of energy savings measures by 202 SMEs which participated in the ClimateSmart Business Cluster Program (commencing in 2009). Expanding on previous research that has mostly focus on identifying inhibiting factors (barriers) to the uptake of energy savings measures, this paper offers a comprehensive assessment of barriers and motivating factors (motivators). A unique finding of this research is that SMEs experienced many different barriers and motivators while participating in the program, inferring great complexity to achieving the critical aim of reducing carbon emissions. Based on these findings, this paper argues that voluntary government energy efficiency programs should be flexibly designed and implemented to accommodate the many and various barriers. Motivating factors should be emphasised and barriers identified upfront so that the program can be tailored to the often idiosyncratic needs of SMEs. [ABSTRACT FROM AUTHOR]

Dry ice blasting is a highly efficient and environmentally-friendly method for cleaning of contaminated surfaces. The method is widely used in many industries, such as automotive, machinery and food industry. Dry ice blasting is a technology that requires large amounts of compressed air which is among the most expensive forms of energy currently employed in industries. Compressed air (air of high pressure and volume) accelerates particles of dry ice during the blasting. Our paper presents a comprehensive overview of saving measures which can greatly help decrease energy intensity of the blasting. Technology of dry ice blasting comprises four key elements: a compressor (generator of compressed air), a blasting machine, transport of pellets, and a blasting nozzle. Our team successively analysed these four key aspects of the technology and designed relevant savings measures, which results in identification of minimum, theoretically attainable energy consumption. Experiments and operational tests proved that application of all available savings measures may decrease energy consumption by 87% compared to current industry standards. It is possible to evaluate current technologies for dry ice blasting in terms of performance of the blasting machine and its functional properties. So far, there has been no method for evaluation of energy parameters of the technology. This paper presents a novel quantity which helps quantify and evaluate energy consumption of dry ice blasting. Main benefit of the quantity called “specific energy consumption of dry ice blasting” is the fact that it allows to compare energy consumptions of various blasting systems. For the purposes of this paper, the novel quantity is especially used to quantify the impact of recommended savings measures. [ABSTRACT FROM AUTHOR]

When new energy efficient products are struggling with their commercialisation and diffusion into widespread applications you would typically expect policy-makers and green lead-users to guide the way. This paper examines the case of the hot water circulator pump industry in Europe, where parts of the industry envisioned and worked for a voluntary energy label, bringing technological innovation, new business and energy savings of approx. 85% for each new circulator pump. The case study explores the complexities of innovation processes where technology, market, actors and policy co-evolve over time to transform an existing socio-technical regime. The paper highlights the importance of policies to reduce barriers towards innovation and energy efficiency and shows that it is not always policy-makers that establish the crucial policies that change the innovation dynamics for the benefit of the environment and the industry. [ABSTRACT FROM AUTHOR]

Energy management systems are considered as appropriate instruments to identify and realize energy efficiency potentials in industrial plants. Studies point out a largely untapped potential for energy efficiency in industry through the adoption of systematic energy management. We suggest introducing qualitative and quantitative modelling tools into energy management to facilitate a focused process to set priorities and identify effective measures. This paper describes the case of voestalpine Austria Draht GmbH, an Austrian wire rolling mill. voestalpine Austria Draht GmbH at present is implementing a knowledge based energy management system. Within the work described in this paper, first an overview of energy flows using Sankey diagrams was elaborated. Then a qualitative systems analysis was developed for the plant and a gap analysis done for priority areas. Subsequently physical input–output models for several energy intensive units were prepared. The paper describes the models for the cooling water system and product cooling. This study revealed a significant potential to save electricity by optimizing the control of cooling water pumps along the milling train and to recover heat from the final products. 2 GWh of electricity can be saved annually. The biggest single energy loss in the mill is the heat from air cooling the products on hook conveyors. These heat flows contain about 30–50 % of the energy input for heating up the billets. Following a theoretical analysis of the potential, a demonstration plant was developed and pilot tests were run to characterize the realistic potential of heat recovery on the hook conveyor. Based on the test results, feasibility studies for large scale plants were carried out. As a result, 0.8 GWh of heat can be recovered annually. The method was found useful because it helped to structure the existing information with a reasonable effort mostly by the operators themselves in their work and to build a conceptual model of energy flows and energy efficiency of the total plant. [ABSTRACT FROM AUTHOR]

Reducing energy demand in manufacture is an urgent challenge. This challenge is driven by higher consumer demand for manufactured products, increasing electricity and energy prices, volatility and uncertainty in energy supply and national policy. These factors, together with a need to reduce energy consumption derived carbon dioxide emissions, strategically call for energy efficient manufacturing. In manufacturing processes, especially mechanical machining, more than 90% of environmental impact arises from direct electrical energy demand in machine tools. At the machine tool level, the biggest share of the electrical energy associated with mechanical machining is required to bring the machine to a ready state and support non-cutting operations such as spindle torque requirements, auxiliary units and movements. These activities are controlled and related to machine commands such as NC codes. In this paper comprehensive information on energy intensity in machining process, including the influence of tool wear, was studied. Key energy states were identified to build up an energy demand for machining components. The paper defines the essential power constants for a database that can assist energy prediction for any available machines and workpiece materials. The assessment of alternative toolpaths identified major opportunities for energy demand reduction. [ABSTRACT FROM AUTHOR]

Scheduling can have significant impacts on energy saving in manufacturing systems. The complex process constraints and dynamic manufacturing tasks in flexible manufacturing system make the scheduling a complicated nonlinear programming problem. To this end, this paper proposes a two-stage energy-saving optimization method for Flexible Job-Shop Scheduling Problems (FJSP). In this method, an operation-based integrated chart is firstly proposed to reveal the dynamic characteristics of the operations, enabling the energy-saving scheduling optimization. Then the optimization is conducted at two stages: the machine tool stage and the operation sequence stage. A Modified Genetic Algorithm (MGA) is applied at the first stage and a hybrid method that integrates Genetic Algorithm (GA) with Particle Swarm Optimization (PSO) is adopted at the second stage. Finally, a case study is employed to illustrate the applicability and validity of the proposed method. The results revealed that the proposed method can effectively optimize FJSP. This may provide a basis for decision makers to utilize a manufacturing scheduling that is optimized regarding its energy saving. [ABSTRACT FROM AUTHOR]

The regional energy management body has a large amount of regional industrial companies’ energy consumption data. It can evaluate the energy utilization of listed regional industrial companies based on the total data and, then, find the key points for understanding the resources usage patterns, identifying the problematic companies, and establishing good energy consumption practices. This paper reviews the research progress on big data analysis and industrial energy efficiency evaluation and focuses on the energy efficiency evaluation methods based on energy consumption process analysis and big data mining approach. Based on K-means and multi-dimensional association rules algorithm, to analyze the characteristics of regional energy consumption in different industries and companies, we cluster single industry in K-means and finding their levels of water and energy consumption. This classification provided us a reference point to identify the industries and companies to focus on and locate the bad consumption practices and environmental performance. Then, multi-dimensional association rules are used to find the correlation of processes, companies and energy efficiency to guide the energy conservation in regional energy monitor. The output of our research is a working Big Data analytics platform and the results generated from advance analytics techniques applied specifically to solve regional energy efficiency problems. [ABSTRACT FROM AUTHOR]

Fuel poverty is a recognized and increasing problem in several European countries. A growing body of literature covers this topic, but dedicated analysis for Portugal are scarce despite the high perception of this condition. This paper contributes to fill this knowledge gap focusing on a European southern city while bringing new datasets and analysis to the assessment of this topic; consumer groups identification and to policy discussion. Daily electricity smart meters' registries were combined with socio-economic data, collected from door-to-door surveys, to understand the extent and the determinants of energy consumption for two contrasting consumer groups (herein called fuel poverty and fuel obesity groups). The analysis is based on the amount and annual profile of electricity consumption and was complemented with building energy simulations for relevant building typologies in those groups, to identify heating and cooling thermal performance gaps. The existence of these gaps allowed confirming and/or discarding the initial hypothesis of the poverty or obesity conditions. Results disclose socio-economic variables, as income, and consumers' behavior as key determinants of electricity consumption. It was identified a severe lack of thermal comfort levels inside households of both groups, either in cooling (98% for fuel poverty and 87% for fuel obesity) and heating seasons (98% for fuel poverty and 94% for fuel obesity). Major conclusion refers that electricity consumption cannot be used alone to segment consumer groups. This assessment may serve to support energy policy measures and instruments targeted to different consumers' groups. For example, distinct campaigns and differentiated incentives may apply to achieve energy efficiency and reduction while keep or improve indoor comfort levels. [ABSTRACT FROM AUTHOR]

China's energy conservation has received extensive attention. As the most important sector of the economy, the manufacturing industry plays a vital role in China's energy issues. Conserving energy in China's manufacturing industry (CMI) is of great significance for both China and the world. In this paper, the co-integration method is applied to test the long-term equilibrium relationship among energy consumption and three explanatory variables during the period 1980–2013. Furthermore, we use scenarios analysis method to forecast the energy demand of CMI. The results show that if the government does not properly manage the economy, the energy demand of CMI will reach 2558.97 Mtce in 2020 and 2594.18 Mtce in 2030. On the contrary, if the government attaches importance to energy conservation and takes necessary actions, energy demand in the industry will reduce to 1113.79 Mtce by 2030, which implies a large energy conservation potential for CMI. [ABSTRACT FROM AUTHOR]

Understanding the driving factors behind energy consumption changes provides insights about consumption patterns and can inform targeted energy saving polices. This paper applies a joint decomposition approach, introducing an index decomposition analysis (IDA) method into a production theoretical decomposition analysis (PDA). This integrated approach decomposed energy consumption changes into eight drivers. A subsequent empirical study of China resulted in three key findings. First, regardless of the geographic area considered, potential economic development was the largest factor driving energy consumption growth. Second, the technological change effects associated with economic development and energy savings both played significant roles in reducing energy consumption. Third, the efficiency change effects of energy use and economic development were generally unable to relieve the pressure of increases in energy consumption, especially in the eastern regions. [ABSTRACT FROM AUTHOR]

Abstract: A key factor deciding the capacity to increase the sustainability of final products is the energy efficiency. The energy embodied in a product is an aggregation of all of the energy embodied in the products' components and subsystems, expended through its manufacturing processes and logistical activities. Currently, accurate estimation of this energy metric is hindered due to the unavailability of energy use data traceable to individual processes and equipment associated with the product's assembly. In this paper, we propose using minimally-required energy to compute energy efficiency of a product assembly process. Based on the proposed approach, efficiency metrics established on the process, product, material and equipment characteristics have been presented at the assembly activity and equipment level. A case study has been presented for a hybrid laser welding process to demonstrate the computational methods used to arrive at these efficiency metrics. Major contributions of this paper are the metrics development and exemplifying the metrics through an actual assembly process (hybrid laser welding) case study. We will explain how these metrics can provide industries with a capability to identify opportunities to improve their sustainability performance across their assembly processes. [Copyright &y& Elsevier]

Following the impressive economic achievements in the past decades, China is faced with energy and environmental challenges. To carry out more effective and targeted energy policies, the heterogeneities of different industrial sectors are of great importance. The energy consumption of China’s light industry in 2012 was 316 million tons of coal equivalents, which is about the energy consumption of South Korea. The paper explored the substitution relationships between various input factors and fuel sources, and showed that electricity price reform is crucial for energy conservation in China’s light industry. Then, the dynamics of energy intensity change is examined by decomposing energy intensity into budget effect, substitution effect, output effect and technology advance effect. The result revealed that the substitution effect between input factors is a key driving force. However, technology progress seems to contribute very little. For future energy policy alternatives, promoting the implementation of new conservation technology and electricity price reform may be effective measures. [ABSTRACT FROM AUTHOR]

The European Energy Efficiency Directive requests the application of high quality and cost effective energy audits across Europe. The potential of up to 20% of energy savings shall be realized to follow the strategy of smart, sustainable, and inclusive growth. A number of barriers must be tackled to implement the Directive, especially among small and medium sized enterprises (SMEs). A large number of cost effective energy efficiency measures remains unimplemented because of financial reasons, a lack of information, and limited in-house skills. Information measures, audits, capacity buildings are suggested as potentially effective measures to support implementation of energy efficiency measures. Within the work described in this paper, an auditing approach was developed, focusing on modelling the energy consumption of an SME. The model of the energy consumption is built using simple MS Excel tools, dividing the process into unit operations and attributing annual consumption to these units, from measurements or by calculation. Consumption is linked to drivers of consumption and corresponding losses, thus developing an understanding of the origin of energy consumption, priorities, and the potential for reduction. The approach simultaneously addresses the needs for the identification of measures, capacity building, information and awareness raising. The auditing approach was tested with 280 companies in Austria, Bulgaria, Cyprus, Italy, Romania, Slovakia and Spain. A wide range of energy efficiency measures was identified and implemented, partly consisting of no-cost options, but partly also innovative technical solutions. Over EUR 10 million investments with a simple payback time of less than three years were triggered. 6500 toe per year of primary energy savings were realized, as well as greenhouse gas emission reductions of 13,500 tonnes per year. [ABSTRACT FROM AUTHOR]

Strengthening the implementation of environmental regulation is one of the key measures to prevent further energy depletion and environmental deterioration. This paper focuses on complicated relation between environmental regulation and fossil energy consumption. We theoretically identified the direct and indirect paths of environmental regulation that affect fossil energy consumption and analyzed the relationship between the two. To identify the indirect impact of environmental regulation on fossil energy consumption, we incorporated three types of technology (e.g., production technology, pollution abatement technology, and backstop technology) into our model. On the theoretical basis, we then evaluated the impact of environmental regulation on fossil energy consumption in China by applying both non-spatial models and spatial econometric models. In the direct path, energy-saving effect of environmental regulation in China is dynamic and yields complex results from the “Green Paradox” and “compliance cost”. As for indirect effects, we find that current environmental regulations have promoted technological progress in production to induce energy savings but failed to drive technological advancements in pollution abatement and backstop to guarantee a sustainable energy development. Based on the findings, some corresponding policy implications are provided. [ABSTRACT FROM AUTHOR]

Energy conservation is a major strategy for China to shift to a low-carbon economy and achieve sustainable development. The heating industry uses coal as its main fuel source in China. Energy consumption of China's heating industry grew at an average annual growth rate of 7.75% over 1980–2011. We use the co-integration method to explore the long-run relationship between energy consumption of the heating industry and the factors including GDP, urban population density, central heating supply areas and fuel price. The results indicate that 1% GDP growth yields 2.24% increase in energy consumption of the heating industry. 1% urban population density growth and 1% central heating areas growth result in 0.56% and 0.36% decline in energy consumption of the heating industry, respectively. Under the BAU scenario, energy consumption of the heating industry will be 157.11 Mtce in 2020. Energy conservation potential is estimated to be 22.16 Mtce under the moderate scenario and 43.6 Mtce under the advanced scenario. Moreover, this paper holds the view that the central heating system can be considered as an effective heating method for cities with dense population, both in the south and north. At last, policy recommendations for energy conservation in the heating industry are provided. [ABSTRACT FROM AUTHOR]

Smart metering and various consumption-feedback systems can be used as applicable technology to encourage end-use energy efficiency in the residential sector. Many studies have demonstrated the positive influence of socially contextualized feedback on the energy consumption of households, but not many such studies dealt with the specifics of low-income households. This paper evaluates the effect of customized consumption feedback and other information interactions on energy-behaviour patterns and energy savings in low-income households. The experimentation process was accompanied by an interactive awareness campaign, with the emphasis being on a proper understanding of the consumption feedback and other complementary energy services provided to low-income households. The feedback actions were customized to tackle the recognised needs of each specific target household, considering both the social aspects and the typology of the dwelling. The results clearly confirmed the importance of customized information and efficiency indicators for specific household groups, with a potential to increase knowledge and develop awareness with respect to established habits and their relevance to energy behaviour. [ABSTRACT FROM AUTHOR]

This paper explores the environmental impacts of a refrigerator recycling system in Brazil and quantifies its ecological advantages over primary resource production through a Life Cycle Assessment based on ISO 14040. The Life Cycle Assessment (LCA) accounts for savings of 720 kg CO 2 -eq per recycled refrigerator on average, thus demonstrating that an environmentally sound recycling process holds substantial emission reduction potential. In addition, the application of the recycling process in conjunction with collection and reverse logistics of refrigerators in a recycling system can reduce energy demand in Brazil by an average of 1.5 GJ per recycled unit. As a result, refrigerator recycling systems qualify as a valid and scalable energy efficiency measure in accordance with the Brazilian national framework for the evaluation of energy efficiency projects (PROPEE). The energy economics for projects based on recycling systems are shown for the 30 largest energy distributors in Brazil. Available budgets, calculated with diagnostics undertaken in conformity with the International Performance Measurement and Verification Protocol (IPMVP) for a threshold value (cost-benefit ratio = 0.8), clearly indicate the viability and competitiveness of these recycling systems as project opportunities for energy conservation under the national energy regulation agency ANEEL's energy efficiency program (PEE). [ABSTRACT FROM AUTHOR]

Renewable energy consumption has a strong driving force for promoting energy conservation and emission reduction, and is a new way to achieve clean and low-carbon development. Based on this, this paper uses the data of renewable energy consumption, carbon productivity, GDP, population, energy efficiency and technological innovation of 30 provinces in China from 2011 to 2020, and empirically analyzes the impact of renewable energy consumption on carbon productivity in 30 provinces in China, using STIRPAT model, comprehensively considers spatial horizontally and temporal vertically dimension. The empirical results show that: (1) China's carbon productivity shows a significant spatial spillover effect, its impact can spill over to adjacent areas within 1000 km; (2) China's renewable energy power consumption plays a significant role in promoting the improvement of carbon productivity. (3) Renewable energy consumption in the western region plays the most important role in driving carbon productivity. Finally, according to the temporal and spatial relationship between renewable energy consumption and carbon productivity in different regions, we provide specific regional policy suggestions. • The STIRPAT model is employed to explore temporal and spatial impact, while it considers sub regions. • Spatialy, the impact can spill over to adjacent areas within 1000km. Temporally, the impact fluctuates and rises. • The positive role of renewable energy consumption is found in China's western region. [ABSTRACT FROM AUTHOR]

The rapid development of the magnesia refractory industry has caused serious problems of resource and energy waste and environmental pollution. Cleaner Production and Cleaner Production Audit are considered effective tools for energy conservation and emission reduction in the industry. This study presents an application of cleaner production and cleaner production audit in a typical large-scale magnesia raw material production plant in Liaoning, China and the results of their implementation. Through the 7 steps of a cleaner production audit (planning and organization, pre-assessment, assessment, option generation and screening, feasibility analysis, implementation, and maintenance of cleaner production), the resource and energy consumption and environmental emissions of the enterprise are investigated, the key auditing procedures are identified, and the cleaner production opportunities are analyzed. 28 cleaner production options, including raw material and energy substitution, technology improvement, facility maintenance and updates, process optimization and control, waste reutilization, management, and staff training and motivation, have been developed and implemented in a feasible way. After complete implementation of these options, great environmental and economic benefits are expected to be achieved: increased utilization of magnesite tailing powder by 281,000 t per year; annual savings of 25,000 t of magnesite ore; savings of 384,000 kW h of electricity; a 21.7% reduction in magnesite consumption per ton of FM product; improvement of the wastewater utilization rate from 70% to 100%; the removal of dust, SO 2 and NO x emissions produced by burning coal or producer gas; savings of 1.066 million USD per year. The results demonstrate that implementing cleaner production can not only bring huge environmental benefits, but also significant economic gains. Moreover, factory staff have recognized the benefits that cleaner production can bring to the plant, and plan to continue the process. Since there are few studies on the application of cleaner production in the magnesia refractory industry, this paper provides scientific guidelines for its implementation in other similar enterprises, and a theoretical and practical basis for promoting the sustainable development of the industry. [ABSTRACT FROM AUTHOR]

Environmental protection is one of the main concerns of the international community. Countries show meticulous attention to environmental issues by considering eco-efficiency. The eco-efficiency evaluation of countries is a complex and multidisciplinary topic. Data envelopment analysis has widely been applied to measure the eco-efficiency of organization for economic co-operation and development countries. In previous studies, energy inputs have not been contemplated. The subject becomes more important when there are non-discretionary factors. In this paper, the eco-efficiency of countries in the organization for economic co-operation and development is assessed given energy inputs, undesirable outputs, and non-discretionary factors. To this end, slack-based and range-adjusted measures are extended. Also, new environmental indices are introduced. The relationship between consumption of energy inputs and production of undesirable outputs can be addressed by two new environmental indices. Spearman correlation test indicates a direct and positive relationship between potential of energy saving and potential of undesirable output abatement. France, Germany, Luxemburg, Norway, Sweden, and the United Kingdom are recognized as eco-efficient countries. South Korea and Italy have the highest and lowest potential for energy saving, respectively. Poland and Iceland are countries with the highest and lowest potential for undesirable output abatement, respectively. It can be concluded that countries producing high undesirable outputs may not operate eco-efficiently and thus have an extreme potential to save the optimum energy. Moreover, countries consuming low energy may operate eco-efficiently and have a low potential to reduce undesirable outputs. [ABSTRACT FROM AUTHOR]

China is currently experiencing rapid economic growth as a result of industrialization and urbanization. In the next 20 years, China's energy demand will increase substantially, and energy conservation will become imperative for the country's low carbon economic transformation. Since 1998, China's chemical fiber production has ranked first in the world. In 2011, China's chemical fiber production accounted for about 70% of the world's total output. Therefore, energy saving is important for China's chemical fiber industry, and can provide immense benefits, and hence the need for thorough and intense research. In this paper, the co-integration method is used to test the relationship between energy consumption and its influencing factors such as GDP, energy prices, population and R&D expenditures. The results show that there is a long-term relationship between the variables. Based on this, we estimate energy demand and predict the energy-saving potential for the industry under different scenarios. We apply the Monte Carlo simulation method to verify the reliability of the prediction. Scenario analysis is adopted to predict energy demand and energy saving in the industry under different scenarios. Finally, we propose some policy suggestions on energy saving based on the research. [ABSTRACT FROM AUTHOR]

Starting with the 11th Five-Year Plan (FYP) and continuing in the 12th FYP, quantitative and binding targets have been set for energy-efficiency improvement in China. Drawing on international experience in burden-sharing on climate change, this paper presents a framework for provincial-level disaggregation of energy-saving targets in China. Based on principles of equity and efficiency, four scenarios have been established by weighting different choice preferences of responsibility, capacity, and potential. In addition, nonlinear and linear allocation models have been developed by considering or ignoring marginal energy-saving cost. When this framework was applied to the disaggregation of the national energy saving target of 16% during the 12th FYP, the results show that the final allocation schemes are largely determined by the policy maker's choice preferences. The extreme reduction target of 37.26% fell to Shanghai under responsibility preferring (RP) using the linear allocation method, while the capability preferring (CP) scenario considering marginal energy-saving cost is the closest to the actual scheme accepted by the 30 provinces. Development of such a framework may serve as a feasible policy instrument to help China achieve its conservation targets in a cost-effective way and in accordance with its regional development strategies. [ABSTRACT FROM AUTHOR]

The embodied and operating energy consumption of the civil building sector accounts for more than 30% of the national consumption. It is of great significance to probe the energy saving potential of the building sector and to explore the critical factors responsible for its energy saving practice, which may greatly benefit carbon emission reduction in the process of urbanization. In this paper, we develop a series of formulations to calculate both embodied and operating energy based on hybrid energy input–output model. Taking 2011–2050 as the study period, we combined the embodied and operating energy and designed six scenarios to comprehensively quantify the impacts of three factors: new building floor areas, energy efficiency standards and its implementation rate on the energy saving potential. Furthermore, sensitivity analysis was conducted to dissect the influence of the corresponding factors. The results show that improved standards and less new building floor areas will be the most effective ways to reduce energy consumption and that the best energy saving practice can save up to 20 billion tons of coal equivalent (tce) during the study period. The focus of policy reforms may be varied according to the times and regions. Energy saving technology development and more emphasis on key areas will reduce building energy consumption significantly in the short term, while household lifestyle changes, as well as improved building energy efficiency, should be given a higher priority in the long run. [ABSTRACT FROM AUTHOR]

Better digging the sustainable development path of the top five energy consumers (China, the United States, India, Japan and Russia) can serve both domestic economy and global economy to achieve coordinated development with the ever-increasing energy demand. This work has made the following efforts: (1) the Tapio decoupling model was employed to determine the decoupling states between energy consumption and economy; (2) based on the extended Kaya formula and the LMDI method, this work focused on measuring the impact of technological factors and urbanization factor on energy consumption; (3) the LMDI method and the Tapio decoupling model were combined to measure the impact degree of influencing factors on decoupling indicators. The main findings show that from 2001 to 2018: (1) Japan was the country with the most year of strong decoupling, followed by the United States, which indicates that the decoupling status of developed countries was better than that of developing countries. (2) The driving forces behind the energy consumption growth are mainly the effects of R&D scale and urbanization, while the main factors that hinder energy consumption growth were technological factors, including energy intensity effect and R&D efficiency effect. (3) Energy intensity effect was the main driving force for the decoupling process, and the R&D efficiency effect was the biggest obstacle to decoupling energy consumption from economic growth. Finally, this paper proposes that the government can give priority to relying on technological innovation to accelerate the development and promotion of energy-saving and emission-reduction technologies. • Exploring the coordinated development path of energy consumption and economic growth in top five energy consumers. • Extending the traditional LMDI method to measure the impact of technological progress and urbanization on energy consumption. • R&D scale and urbanization promote energy consumption growth, while technological progress inhibits energy consumption growth. • Governments can prioritize technological innovation to speed up energy conservation and emissions reduction. [ABSTRACT FROM AUTHOR]

Although China has made a lot of achievements in Energy Conservation and Emission Reduction (ECER) initiatives currently, the continued reduction in the ECER space has gradually become one of the bottlenecks hindering the construction of ecological civilization. It is thus imperative that all levels of government develop and introduce more effective policies and measures to further drive the potentiality exploitation of ECER. The purpose of this paper is to examine which policies are more conducive to improving regional ECER levels. By taking Fujian Province as an example, the paper builds an ECER dynamic model and provides integrated incentives from six dimensions including fiscal, tax, emissions trading, finance, industry and technology, and examines their policy effectiveness. The results show that: (1) In the single policy scheme, the tax policy is the most effective, though such effect is less than that of the policy combination; (2) With the increase of the category and quantity of policy combinations, the synergy among policies is so significant that ECER effect is expected to be remarkable; (3) Within the scenarios of policy combination, the technical policy has not contributed to obvious performance improvement, because it requires a longer lag phase to truly experience a prominent innovation spillover of clean technology. This paper elucidates theoretical implications by enriching the social-economic system and underscoring the critical importance of public incentive for the ECER initiative. Also, the findings carry managerial implications by guiding companies to carry out more targeted green and cleaner production activities and providing a valuable reference for the government to make ECER policy. • We develop a dynamic model for ECER of which government subsystem is the operation hub. • We create an ECER policy framework including fiscal, tax, emissions trading, finance, industry and technology. • By the model, we simulate energy consumption and main pollutant emissions variables and examine the ECER policy effect. • We find that the ECER effect of single tax policy is the most significant, compared with other policies. • We find that the effect of ECER policy combination is more salient than the single policy scheme and we suggest an optimal ECER policy portfolio eventually. [ABSTRACT FROM AUTHOR]

Abstract: Covering a building envelope with green walls is considered a sustainable construction practice. Green walls can be classified as green facades or living walls based on their purpose and characteristics. Living walls are built with different layers and variable planting styles depending on the geographic location, function, and weather conditions. This paper discusses a comparative lifecycle assessment (LCA) of three living wall systems: trellis system, planter box system, and felt layer system. Chemical emissions and energy consumption of the living wall materials are evaluated in the whole lifecycle, and compared with the chemical absorption and energy savings of operational living walls. The results demonstrated that the felt layer system is not environmentally sustainable in air cleaning and energy saving compared to the trellis system and modular panel system. The environmental performance of living walls is influenced by the types of materials and plants chosen for the systems, as well as the external factors, such as climate and building type. The LCA indicates the need of environmental friendly materials for sustainable living walls. [Copyright &y& Elsevier]

Abstract: Energy consumption keeps increasing in China's building sector with the constant growth of urban population and people's living standard. In order to achieve co-benefits of reducing energy use, greenhouse gas (GHG) emissions and energy costs effectively, all respects related to the energy performance in the building sector need to be addressed. Considering the fact that over 80% of total energy use in a building's lifecycle is contributed by the operation stage, the study's focus is put on this stage for well understanding the energy consumption and carbon emissions and exploring the approach to achieve the effectiveness of co-benefits. The energy use in large commercial buildings is 4–6 times higher than residential buildings in China, thus IKEA Xuhui Store as one of large shopping malls in Shanghai is selected as the case study by using the method formed in the study. The outcomes of research show that the benefit of annual 170 MWh of energy use and 150 tons of CO2e reduction as well as the significant economic benefit have been achieved by implementing different measures in IKEA Xuhui Store between 2008 and 2011. Existing investment, technology and capacity barriers to co-benefits approach in a wider consideration of China's building sector are described. The assessment for evaluating co-benefits of cutting energy use and CO2 emissions in the production and demolition stages in a building's lifecycle are also addressed by the paper. However, it is very complicated to make a lifecycle assessment on the overall co-benefits in the building sector because of the complexity and the lack of available data for the research. [Copyright &y& Elsevier]

Abstract: The first objective of this paper is to map the adoption of technologies for the reduction of energy and resource consumption in production and the second is to test the relationship between the implementation of those technologies and the performance of manufacturing firms. The aim is to contribute to the identification of the characteristics of the manufacturing firms that use this kind of innovative technology in order to help policy makers promote energy and resource efficiency in a suitable manner. Our research is based on the Spanish and Slovenian subsamples of a wider European Manufacturing Survey. Our suggested models explain how significant energy efficiency is, and how much of the variability in economic performance and environmental performance it can explain. The results show that the use of energy and material saving technologies does not have a clear and significant relationship with economic performance. On the other hand a significant positive relationship is found between energy and material saving technologies and environmental performance. [Copyright &y& Elsevier]