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]

Abstract: The pulp and paper industry is one of the most energy-intensive industries worldwide. In 2007, it accounted for 5% of total global industrial energy consumption and 2% of direct industrial carbon dioxide (CO2) emissions. An energy audit is a primary step toward improving energy efficiency at the facility level. This paper describes a plant-wide energy audit aimed at identifying energy conservation and CO2 mitigation opportunities at a paper mill in Guangdong province, China. We describe the energy audit methods, relevant Chinese standards, methods of calculating energy and carbon indicators, baseline energy consumption and CO2 emissions of the audited paper mill, and nine energy-efficiency improvement opportunities identified by the audit. For each of the nine options, we evaluate the energy conservation and associated CO2 mitigation potential. The total technical energy conservation potential for these nine opportunities is 967.8terajoules (TJ), and the total CO2 mitigation potential is equal to 93,453tonnes CO2 annually, representing 14.4% and 14.7%, respectively, of the mill’s total energy consumption and CO2 emissions during the audit period. [Copyright &y& Elsevier]

Abstract: This paper studies allocation of fuel costs and CO2-emissions to heat and power in a CHP plant producing heat to an integrated pulp and paper mill and electricity to the liberalized electricity markets (or to the mill by the market price). The CHP plant and the mill are considered to be two separate economical units and both the mill and the CHP plant perspectives are discussed. Fuel costs and CO2-emissions are allocated using the energy, exergy and market based methods. The CHP plant purchases black liquor and bark from the mill. It also purchases oil from the markets to cover the whole fuel demand of the plant. The results indicate that the marked based method can be recommended as a “neutral” cost allocation method, because with that, the energy producer is not collecting extra margins from selling steam. This means that heat pricing is cost based. The results also indicate that depending on the emission factor and efficiency of alternative energy production form, the marked based method or the exergy method allocate the lowest CO2-emissions to heat. Therefore, the use of market based method for allocating costs and CO2 emissions can be recommended in order to use one single approach in both. [Copyright &y& Elsevier]

Highlights • The majority of carbon emissions derived from indirect fraction of energy consumption in Beijing. • Life expectancy is reduced in areas where a higher amount of coal is burnt for household consumption. • Socio-economic structure changes play a major role in the observed energy and emission trends. • Search of optimal solutions for energy-efficient and low carbon private will continue to be crucial. Abstract Household carbon emissions are major contributors to global emissions that is increasing recognized. In China, approximately 20 million rural populations transfer to the urban areas annually, which results in a lot of new infrastructure construction and consumer requirements. This paper quantifies the numbers and trends of urban and rural resident on energy use and carbon footprint in Beijing from 1996 to 2011 by analysis of Consumer Lifestyle Approach (CLA) and carbon footprint. It provides a better understanding of complete energy consumption and carbon emissions profile in Beijing. The results show that for the Beijing residents, when direct and indirect energy consumption and CO 2 emissions are taken into account, the total household energy consumption proportion compared to the city increases from 22.7% to 59.2%, and the total household CO 2 emissions proportion increases from 32.2% to 68.8% in the research period. In the urbanization process, total energy consumption and carbon emissions of Beijing urban residents are significantly higher than those of rural residents. However, the transformation of a rural Beijing resident into an urban Beijing resident would not create a large difference between urban and rural areas in the per-capita energy consumption and per-capita carbon footprint. Results are assessed with respect to the available scientific literature, as well as potential available technological and policy solutions. Since the implementation that different policy instruments can mitigate carbon emissions, governments are gradually combining policy measures for the same technology. The results in this paper may help promote alternative consumption strategies in household sector which could entail more reasonable resource distribution and effective reduction of both urban and rural environmental influences. [ABSTRACT FROM AUTHOR]

Quantifying the use of resources in food production and its environmental impact is key to identifying distinctive measures which can be used to develop pathways towards low-carbon food systems. In this paper, a first-principle modelling approach is developed, referred to as gThermaR (Glasshouse-Thermal Requirements). gThermaR is a generic tool that focuses on the energy requirements of protected heated production, by integrating holistic energy, carbon, and cost modelling, food production, data analytics and visualization. The gThermaR tool employs historic data from weather stations, growing schedules and requirements specific to grower and product needs (e.g. set-point temperatures, heating periods, etc.) in order to quantify the heating and cooling requirements of glasshouse food production. In the present paper, a case study is reported that employs a database compiled for the UK. Another relevant feature of the tool is that it can quantify the effects that spatial and annual weather trends can have on these heating and cooling requirements. The main contribution of this work, therefore, concerns the development a tool that can provide a simple integrated approach for performing a wide range of analyses relevant to the thermal requirements of heated glasshouses. The tool is validated through collaborations with industrial partners and showcased in a case study of a heated glasshouse in the UK, offering the capacity to benchmark and compare different glasshouse types and food growth processes. Results from the case study indicate that a significant reduction in the heating requirement and, therefore, carbon footprint, of the facility can be achieved by improving key design and operational parameters. Results indicate savings in the peak daily and annual heating requirements of 44–50% and 51–57% respectively, depending on the region where the glasshouse is located. This improvement is also reflected in the carbon emissions and operating costs for the different energy sources considered. Furthermore, the temporal variability/uncertainty of the annual energy requirements and of the peak daily energy requirements are found to be considerably lowered through improvements to the glasshouse attributes. Overall, gThermaR proves its value in quantifying and identifying key factors that have a significant impact on energy requirements of heated glasshouses. Such valuable outputs are invaluable for stakeholders in the food industry that have an interest in mapping the sustainability and mitigating the carbon footprint of their supply chain processes. [ABSTRACT FROM AUTHOR]

The five major power generation corporations dominate the power industry in China, and play vital roles in China's carbon trading scheme. Under this circumstance, this paper studies the allocation of carbon emission quotas to China's five major power generation corporations based on the fairness and efficiency principles, which proves the primary prerequisite for setting up the national carbon market. Specifically, a bi-level programming model is developed to optimally allocate carbon emission quotas to the corporations, and then a zero sum gains data envelopment analysis (ZSG-DEA) model is adopted to evaluate the efficiency of the allocation so as to adjust towards the optimal solution. The results indicate that power generation has significantly positive influence on the allocation of carbon emission quotas. Moreover, the difference between the sum of optimal carbon emissions and the sum of carbon quotas allocated is 1.431 billion tons, which implies that the emission reduction potential of the five major power generation corporations is tremendous. Finally, the bi-level model in this paper can well capture the context of China's power industry and provide effective results for the allocation of carbon quotas. [ABSTRACT FROM AUTHOR]

This paper proposes several novel multi-effect dividing wall column (MEDWC) configurations to retrofit and debottleneck side-stream columns or two-column sequences for multiple objectives such as increasing the column throughput, maximizing energy efficiency, and reducing carbon dioxide (CO 2 ) emissions. This paper also proposes a new practical method that employs a coordinate descent methodology, which is assisted by a random search to avoid local optimal points and box search to overlook more promising solutions for optimal retrofitting. One industrial case was studied and analyzed to demonstrate the proposed configuration. The results show that the proposed modified coordinate descent methodology not only effectively avoided the local optimal points but also overlooked more promising solutions. The proposed method is competitive with the coordinate descent methodology and response surface methodology, which are popular optimization methods used in the chemical process industry. Both the structural and operating variables are effectively and simultaneously optimized. The proposed MEDWC sequence removes the bottleneck problem effectively and achieves substantial energy savings and CO 2 emissions reduction. Notably, a 73.2% and 73.6% reduction in operating costs and CO 2 emissions, respectively, can be achieved in the ethylene dichloride separation processes. The proposed configuration can be applied to both close-boiling and wide-boiling mixtures. [ABSTRACT FROM AUTHOR]

The metallurgy industry plays a very important role in China's economic growth. Due to its energy concentration, the energy consumption of the industry accounts for a large proportion of China's total energy consumption, and thus contributes to carbon emissions. Whether the metallurgy industry can successfully reduce emissions is related to the future of China's carbon emissions targets. In this paper, the logarithmic mean Divisia index model is used to analyze the change in China's carbon dioxide emissions from 1991 to 2014. The empirical results show that there are three main factors affecting the carbon dioxide emissions of China's metallurgy industry. The three factors are labor productivity, energy intensity and industry size. In addition, we further analyzed the deep motivation of carbon dioxide emissions in the industry, and calculated the future emission reduction potentials. Lastly, according to the empirical results, the paper proposes policy recommendations for the future emission reduction of China's metallurgy industry. [ABSTRACT FROM AUTHOR]

Traditional energy planning methods are mostly related to newly-built area. However, in most already-built regions, the existing district energy systems (DESs) need to be ameliorated due to insufficient capacity and low efficiency. This paper investigates the methodology of expansion planning, which can offer planners a viable way to expand existing DESs. The term “expansion” aims to increase the supply capacity of the energy forms, e.g., steam, hot water and electricity, which cannot be accessed from national or urban energy supply network, and meanwhile increase energy utilization efficiency and cut CO 2 emission. Three parts of the methodology, including problem analysis in current DESs, demand side analysis and the existing DES expansion, are introduced in this paper. New concepts of load structure and evaluation system of the whole district are proposed in this methodology. A case analysis of Ningbo Hi-Tech District, China is conducted to shed light on the application of this method. [ABSTRACT FROM AUTHOR]

The allocation of carbon emission quotas is recognized as a fundamental and critical step towards the establishment of an effective nationwide carbon emissions trading (CET) market in China. This paper aims to examine the quota allocation pertaining to China's east coastal areas. These regions are pioneers in reformation and the domestic heavy emitters. In this paper, a multi-criteria decision analysis model is proposed. This model is based on the principles of efficiency and equity. In order to reflect the true efficiency of carbon emissions, a weighted Russell direction distance model is employed. Three criteria, namely capacity, responsibility and potential, are used to evaluate the degrees of equity. Furthermore, different situations are set to evaluate the related indicators. The results indicate the following: (1) Industrial provinces have less carbon emission quota increments. (2) The Yangtze River Delta Economic Zone has notably improved energy efficiency, and future quota increments correspond with the zone's current carbon emissions. (3) Circum-Bohai Sea Economic Zone will be a major buyer of carbon emission quotas, while Pan-Pearl River Delta Economic Zone currently receives surplus quota. (4) The overall allocation of quotas converts from uneven to even as a result of GDP growth. These results provide a reference for collaborative regional reductions in carbon emissions and for the construction of a CET market. [ABSTRACT FROM AUTHOR]

One-third of global energy demand as well as CO 2 emissions is accounted to industrial processes. In particular, over 30% of total industrial energy consumption is attributed to the iron and steel, cement and refining industry. The aim of the present paper is to review crosscutting technologies and measures adopted to improve energy efficiency in the main Italian industrial sectors regulated by the recent EU legislation on integrated pollution prevention and control (IPPC-IED). In fact, 2010/75/EU Directive on industrial emissions, a general improvement on the entire environmental performance of the industrial installations is pursued by taking into account relevant environmental issues, such as emissions into water, air, soil as well as energy efficiency, waste production, recovering and recycling, restoration of the site upon definitive cessation of activities. Moreover, according to 2010/75/EU Directive, IPPC permits should be based on Best Available Techniques (BAT) aimed to reach an adequate level of environmental protection and should establish all the necessary measures including operating conditions, emission limit values for relevant polluting substances as well as monitoring requirements. Thus, in the present paper an assessment of Best Available Techniques (BAT) related to energy efficiency in the main Italian industrial installations is carried out on the base of the analysis on the IPPC permits released by the Italian Ministry for the Environment, Land and Sea, and made available on its web site. As a result a significant improvement in energy efficiency was assessed. In fact, many process units were upgraded, by major revamping or even by replacing the process completely with one showing better performances. Finally, since energy efficiency is at its best at the beginning of the life cycle of the plant, operators, whenever necessary, periodically monitor and measure the actual energy performance of their own installations for process control and maintenance purposes. [ABSTRACT FROM AUTHOR]

As an important part of smart grid optimizations, optimal dispatch of microgrid is of great significance to reduce energy consumption, environmental pollution and user's electricity costs. The development objective of microgrid is not only to meet the basic demand of power supply, but also to improve its economic efficiency and environmental protection. In this regard, this paper proposes a multi-objective optimal dispatch model for microgrid under grid-connected mode, which comprehensively considers the operation cost and the environmental protective cost of the microgrid system. Distribution generators in the microgrid system include photovoltaic array, wind turbine, diesel engine, micro turbine and electric vehicle. The batteries of the accessed electric vehicles are treated as a kind of mobile distributed energy storage device in the model. In order to solve the proposed model effectively, according to the configuration and characteristics of the model, this paper proposes an improved particle swarm optimization algorithm to solve the optimization model. Two different operation scheduling scenarios under grid-connected mode are researched, and the dispatch results of different optimization goals are discussed in this paper. The simulation results show that the effectiveness and superiority of the proposed model, which can effectively reduce the user's electricity costs and environmental pollution, promote the optimal operation of microgrid and achieve the economic management of the batteries of electric vehicles. [ABSTRACT FROM AUTHOR]

Maximizing energy conservation, improving energy efficiency and integration and control of renewable energy sources are critical in order to achieve a low carbon future. An integrated modelling system is needed to evaluate and improve energy performance of urban energy systems’ design and operation, from both financial and environmental perspectives. To this end, this paper presents an urban energy co-simulation framework. It is based on co-simulation standard Functional Mock-up Interface (FMI) and CityGML-based semantic 3D city model and utilized programing packages, like PyFMI, FMILibrary, and mosaik, which is capable of orchestrating the execution of dynamic simulation models supporting the for co-simulation. To demonstrate the proof of concept, two simulation tools are coupled in the first instance: EnergyPlus and No-MASS. Based on the two use cases, the principles and workflow of the framework and results from its application are described. Results from use cases show that synchronization and interaction between our urban energy co-simulation framework and coupled co-simulation components works as intended. The paper concludes by discussing strategies to tackle more complex and multiscale energy systems. [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]

This paper argues that many past studies have only been concerned with efficiency and not with the efficiency achievement ratio, whereas information on Baltic Sea countries' energy or environmental efficiency has always been based on studies that focus on different research objectives, but do not include all the Baltic Sea countries. Hence, the main aim of this paper is to analyze the impact of the achievement ratios for energy consumption and carbon dioxide emissions on both energy consumption and carbon dioxide emissions by including all Baltic Sea countries as a case study and constructing new static and dynamic efficiency indices. The study's results show that the 2008 Global Financial Crisis resulted in low achievement ratios for energy consumption and carbon dioxide emissions, and the conclusion is that since a lot of attention has been paid to staving off an economic downturn, the Global Financial Crisis may in fact have stalled actions to combat carbon dioxide emissions and energy over-consumption. In addition, the Baltic Sea countries should strengthen energy management on the demand side. [ABSTRACT FROM AUTHOR]

Excessive energy consumption and carbon dioxide emissions are long lasting issues and need continuous research to improve efficiency evaluation and performance monitoring of economies. The static and dynamic aspects of efficiency need to be dealt with simultaneously to thoroughly analyze the performance of economies. This paper aims at conducting a static and dynamic analysis of energy and CO 2 emissions efficiency of major economies. In this paper, we applied slacks based model of Tone (2001) with the treatment of undesirable output in objective function and constraint assuming free disposability of undesirable output and built a dashboard. The results can be summarized by saying that the larger economies with intensive production strategy, larger secondary industry, and weaker carbon tax laws are more likely to be inefficient. China, India, and Russia have the greatest potential for improvement in both energy efficiency and carbon dioxide emissions efficiency. The suggested dashboard has the ability to dig out the potential for efficiency improvement of countries like the USA, which mostly appear at the efficient frontier with other techniques. Concluding it can be suggested that economies in lower ranks of dashboard need stricter policy measures to cut energy consumption, carbon dioxide emissions and encourage a shift from fossil fuels to other renewable resources of energy. [ABSTRACT FROM AUTHOR]

Home energy consumption is increasing, and renewable energy sources are being deployed. The use of renewable energy sources as an alternative to fossil fuels and nuclear energy is a significant opportunity for reducing CO 2 emissions. However, carbon emissions from electricity generation are dependent on the type of renewable energy source and the quantity of the electricity that is produced. With the emergence of the smart grid, residents are able to reduce their electricity consumption by shedding the power usage in their homes. The objective of this study is to smooth power peak demand and diminish CO 2 emissions. This paper describes the power shedding benefits of reducing energy consumption and CO 2 emissions. This reduction of CO 2 emissions eliminates the need for auxiliary power plants in the grid in the case of peak demand points and the need to switch to renewable energy sources. In this study, we prove that emerging information and communication technology can reduce energy use and CO 2 emissions. Wireless communication architecture is introduced in this study to increase grid flexibility and rapidity in the data flow among all of the components in the proposed system. Our proposed system with local renewable generation can reduce CO 2 emissions nearly 72% of all CO 2 emissions when all appliances are supplied with the grid. With our load shedding algorithm, the CO 2 emissions decrease nearly 91%. The yearly estimation shows that our system can reduce 62% of CO 2 emissions and 37% of consumed power. In this paper, we introduce an efficient architecture of a smart home energy management system and propose a shedding algorithm for home energy usage. This system is based on wireless communication among home appliances, a home management and control system, a grid management and control system and domestic renewable energy sources. Our proposed system, which employs wireless communication, domestic renewable generation and a power shedding algorithm, can operate in conjunction with future smart grids by applying real-time data, such as peak demand points. Numerous real data sets permitted the development of some of the statistics in the system results. [ABSTRACT FROM AUTHOR]

Climate change mitigation is a key issue in formulating global environmental policies. Energy production and consumption are the main sources of greenhouse gas (GHG) emissions in Europe. Energy consumption and energy-related GHG emissions from agriculture are an important concern for policymakers, as the agricultural activities should meet food security goals along with proper economic, environmental, and social impacts. Carbon dioxide (CO 2 ) emission is the most significant among energy-related GHG emissions. This paper analyses the main drivers behind energy-related CO 2 emission across agricultural sectors of European countries. The analysis is based on aggregate data from the World Input-Output Database. The research explores two main directions. Firstly, Index Decomposition Analysis (IDA), facilitated by the Shapley index, is used to identify the main drivers of CO 2 emission. Secondly, the Slack-based Model (SBM) is applied to gauge the environmental efficiency of European agricultural sectors. By applying frontier techniques, we also derive the measures of environmental efficiency and shadow prices, thereby contributing to a discussion on CO 2 emission mitigation in agriculture. Therefore, the paper devises an integrated approach towards analysis of CO 2 emission based upon advanced decomposition and efficiency analysis models. The research covers eighteen European countries and the applied methodology decomposes contributions to CO 2 emission across of regions and factors. Results of IDA suggest that decreasing energy intensity is the main factor behind declines in CO 2 emission. According to the SBM, the lowest carbon shadow prices are observed in France, Finland, Sweden, Denmark, the Netherlands, Poland, and Belgium. These countries thus have the highest potential for reduction in CO 2 emission. The results imply that measures to increase energy efficiency are a more effective means to reduce CO 2 emissions than are changes in the fuel-mix. [ABSTRACT FROM AUTHOR]

At present, carbon emissions produced by coal consumption have raised concerns around the world, but the carbon emissions associated with coal production should also be considered. As China's second-largest province for coal production, it is of extreme importance around the whole country for small and medium-sized coal enterprises in Inner Mongolia to achieve low-carbon transition. In this paper, we apply the IPAT equation to analyze the relationships among environmental impact, population, affluence and technology. The results of the analysis show that technological innovation can make an environmental impact or can cause pollutant emissions of a unit GDP to decline. Technological innovation is viewed as an avenue for environmental improvement, and corporate entities are key players in the environmental improvement. This equation can also be used indirectly on the micro-scale, for example, to determine the directions of development of enterprises and encourage the enterprises to achieve low-carbon transition as soon as possible. Selecting the example of a surface coal mine in Inner Mongolia (China) under the framework of cleaner production and the theory of inventive problem solving (TRIZ), cleaner production options helping to reduce carbon emissions were proposed and implemented. Through the implementation of the options, carbon emissions of the coal mine were reduced by approximately 4%. Contributing cleaner production options for reducing carbon emissions mainly include increasing the efficiency of energy usage, substitution of environmentally friendly materials, optimization of process controls and changing process technologies. The results obtained in this paper can not only provide a decision-making foundation for the local governments when they invest in carbon reduction projects but also play an exemplary role for other similar enterprises to reduce carbon emissions. [ABSTRACT FROM AUTHOR]

Sensitivity analysis based on Leontief model is applied for identifying the key factors leading to the change of CO 2 emission or energy consumption in the competitive market from demand perspective. On the other hand, this kind of research from supply-side is also valuable for the economy with characteristics of rationing. Based on previous research achievements, this paper developed out sensitivity analysis based on the Ghosh model. In addition, we implemented sensitivity analysis based on the Leontief and Ghosh model respectively to study the most sensitive factors leading to the change of CO 2 emission intensities of the six energy-intensive industries. In terms of 2010 Chinese symmetrical input–output table, the results obtained from the two sensitivity analyses are different. From the demand perspective, the level of production technology in the construction industry plays very important role in the CO 2 emission intensity of energy-intensive industries. While, from the supply side, the adjustment of rationing in extraction of petroleum and nature gas should be paid more attention. At last, comparative analysis was carried out and corresponding policy suggestions were put forward. Emphatically, the method used in this paper could be applied to other industries within supply chains of a country, even in the world wide. [ABSTRACT FROM AUTHOR]

The Chinese government committed to reduce its national CO 2 emissions intensity by 40–45% until 2020 in response to climate change. This paper quantitatively evaluates the performance of CO 2 emissions reduction over the period 2005–2020 from the historical and prospective perspectives by using a combination of decomposition analysis and scenario analysis, aiming to provide suggestions about how to achieve the target in key emissions reduction fields. Unlike traditional index decomposition methods, this paper incorporates the total energy conversion efficiency effect into the model, and further decomposes it into a final energy mix effect and a final energy conversion efficiency effect by a multilevel decomposition procedure, allowing to measure the contributions of primary energy structure low-carbonization, the final energy mix electrification, and the energy conversion efficiency improvement. The results show that the carbon intensity could decline over the period 2005–2020 by 47.8%, 50.9%, 48.0%, 44.5% and 47.5% in the Business as Usual, S1, S2, S3 and S4 scenarios, respectively. This shows that the 40–45% target is very likely to be achieved. The final energy intensity effect is always the most important driving factor, causing carbon intensity to decrease by 24.0% and 22.1%, again respectively, from 2005–2012 to 2012–2020. Moreover, the energy conversion effect was another major driver during 2005–2012. The Chinese government needs to make more efforts to adjust the industrial structure, which could cause carbon intensity to decrease by 3.6% during 2012–2020, and to adjust the primary energy mix, which could cause carbon intensity to decrease by 7.1% during 2012–2020. [ABSTRACT FROM AUTHOR]

Optimal thermal management of modern internal combustion engines (ICE) is one of the key factors for reducing fuel consumption and CO 2 emissions. These are measured by using standardized driving cycles, like the New European Driving Cycle (NEDC), during which the engine does not reach thermal steady state; engine efficiency and emissions are therefore penalized. Several techniques for improving ICE thermal efficiency were proposed, which range from the use of empirical look-up tables to pulsed pump operation. A systematic approach to the problem is however still missing and this paper aims to bridge this gap. The paper proposes a Robust Model Predictive Control of the coolant flow rate, which makes use of a zero-dimensional model of the cooling system of an ICE. The control methodology incorporates explicitly the model uncertainties and achieves the synthesis of a state-feedback control law that minimizes the “worst case” objective function while taking into account the system constraints, as proposed by Kothare et al. (1996). The proposed control strategy is to adjust the coolant flow rate by means of an electric pump, in order to bring the cooling system to operate around the onset of nucleate boiling: across it during warm-up and above it (nucleate or saturated boiling) under fully warmed conditions. The computationally heavy optimization is carried out off-line, while during the operation of the engine the control parameters are simply picked-up on-line from look-up tables. Owing to the little computational effort required, the resulting control strategy is suitable for implementation in the ECU of a modern engine. The control strategy was validated by means of experimental tests under several operating conditions, involving both warm-up and fully warmed engine thermal states. The tests were carried out with a small displacement Spark-Ignition Engine which was equipped with an electric coolant pump, directly driven by the control algorithm. Results show that the controller is robust in terms of disturbance rejections, it respects the defined system constraints and is also very fast in terms of response to the perturbations. The experimental tests proved that the proposed control is effective in decreasing the warm-up time and in reducing the coolant flow rate under fully warmed conditions as compared to a standard configuration with pump speed proportional to engine speed. The adoption of these cooling control strategies will, therefore, result in lower fuel consumption and reduced CO 2 emissions. [ABSTRACT FROM AUTHOR]

Coal mining not only produces, but also consumes a large amount of energy. Coal production has an extremely high energy efficiency potential, and benchmarking is critical to discover this potential. To address problems such as ambiguity of coal production (e.g. underground mining), benchmarking range and absence of both indicators and standards for energy efficiency benchmarking, this paper makes use of product-based and process-based benchmarking. These two techniques are used to construct a benchmarking system for coal production with high energy efficiency, and improve the standards used at the eight coal mines owned by the Yankuang Group. Comparison and analysis of benchmarking in enterprises indicates that energy use during raw coal production could be reduced by 22.77%. Across China energy savings from coal production could reach 15.98–32.98 Mtce, with an equivalent 42–87 Mt of CO 2 emissions saved. Lastly, this paper provides measures to improve coal production energy efficiency. [ABSTRACT FROM AUTHOR]

Emerging economies like China, India, and Mexico are becoming the world's manufacturing leaders through the engagement in offshoring production activities. In achieving this status, however, they have met with difficult environmental issues. This paper features an analysis of industry-level panel data to examine the link between different offshoring tasks in China and carbon dioxide emissions. Through this analysis, the environmental effects of offshored production are addressed. Specifically an input–output model is presented, thereby quantifying offshored production tasks in China. The results show that iron and steel, nonferrous metals (IS) and chemicals (CH) generate the most carbon dioxide during production of processed goods. Additionally, electrical machinery (EM) and general machinery (GM) generate a higher amount of carbon dioxide during production of parts and components. The results also show that those industries characterized by higher energy consumption have higher carbon dioxide (CO 2 ) emissions induced by offshoring. Given these results, it seems that any solutions geared towards reducing the energy consumption of entire manufacturing industries would be useful. Furthermore, the results of the analyses presented here indicate that China would be responsible for working with developed countries to reduce carbon dioxide emissions through cooperative environmental regulation. A globalization perspective is adopted to offer unique insight into the environmental issues faced by China. The results of this paper would provide quantified, actionable information for formulating practical industrial policies geared towards reducing carbon dioxide leakage. [ABSTRACT FROM AUTHOR]

The building sector in the United States is responsible for 41% of energy consumption and 39% of carbon footprint while the majority of energy consumption and carbon footprint are caused by aging buildings which represent 70% of existing buildings in the United States. The energy consumption of aging buildings can be significantly reduced by identifying and implementing green building upgrade measures based on available budgets. Aging buildings are often in urgent need for upgrading to improve their operational, economic, and environmental performance. This paper presents the development of an optimization model that is capable of identifying the optimal selection of building upgrade measures to minimize energy consumption of aging buildings while complying with limited upgrade budgets and building operational performance. This optimization model is designed to estimate building energy consumption using energy simulation software packages such as eQuest and it is integrated with databases of building products. This optimization model performs analysis of replacing existing building fixtures and equipment during the optimization computations to identify the optimal replacement of building products that minimizes building energy consumption and carbon emissions. The model is designed to provide detailed results for building owners and operators, which include specifications for the recommended upgrade measures and their location in the building; upgrade cost; expected energy, operational, and life-cycle cost savings; and expected payback period. This paper illustrates the new and unique capabilities of the developed optimization model. [ABSTRACT FROM AUTHOR]

In this paper a model for choosing the proper modular configuration of a point-focus concentrating thermo-photovoltaic (CPV/T) system according to the domestic user energy demands, is presented. The main aim is to evaluate several modular configuration solutions in terms of energy and economic performances and space occupied. First of all, the main CPV/T system components are chosen: optics, solar cells and tracking system. A point-focus system with parabolic mirrors, triple-junction cells and dual-axis tracking system is considered. The choice of the proper CPV/T system configuration is realized considering an equations system that defines the electric and thermal performances in terms of solar radiation, cells number and concentration factor. The choice model presented in this paper allows to configure, referring to different Italian zones, the CPV/T system under several working conditions minimizing spaces and costs. It is observed that CPV/T modules with a lower cells number allow high flexibility to satisfy the loads. The high concentration level determines interesting solutions related to a domestic application from the energy and economic point of view, above all in southern Italy, during the CPV/T system life cycle. Finally, CPV/T systems allow a significant reduction of CO 2 emissions due to the primary energy savings. [ABSTRACT FROM AUTHOR]

For both energy security and CO 2 emission reduction, synthetic natural gas (SNG) production from coal is an important path to implement clean coal technologies in China. In this paper, an overview of the progress of coal to SNG technologies, including the development of catalysts, reactor designs, synthesis processes, and systems integration, is provided. The coal to SNG system is modeled, the coupling between SNG production and power generation is investigated, the breakthrough points for further energy savings are determined, and the system performance is optimized based on the first and the second laws of thermodynamics. From the viewpoint of the first law of thermodynamics, the energy conversion efficiency of coal to SNG system can reach 59.8%. To reduce the plant auxiliary power, the breakthrough points are the development of low-energy-consumption oxygen production technology and gas purification technology or seeking new oxidants for coal gasification instead of oxygen. From the viewpoint of the second law of thermodynamics, the major exergy destruction in a coal to SNG system occurs in the coal gasification unit, SNG synthesis unit and the raw syngas cooling process. How to reduce the exergy destruction in these units is the key to energy savings and system performance enhancement. The conversion ratio of the first SNG synthesis reactor and the split ratio of the recycle gas are key factors that determine the performance of both the SNG synthesis process and the whole plant. A “turning point” phenomenon is observed: when the split ratio is higher than 0.90, the exergy destruction of the SNG synthesis process will increase sharply, which causes a decrease in overall system efficiency. Keeping the conversion ratio of the first synthesis reaction between 0.78 and 0.90 not only avoids the rapid increase of exergy destruction in the SNG synthesis process but also produces the SNG product with a high CH 4 purity (>94.0%), and the catalyst can be maintained with a high activity. When the split ratio of the recycle gas is approximately 0.85, the best coupling/balance between SNG production and power generation can be attained and thus the highest overall system efficiency of approximately 62% is achieved, much higher than approximately 55% efficiency in a traditional coal to SNG plant. The findings presented in this paper are important steps for future improvements of coal to SNG systems, especially the SNG and power cogeneration systems, integration in the future. [ABSTRACT FROM AUTHOR]

This paper, which aims at the primary gaseous air pollutants (i.e., SO2, NOx, VOCS and CO), is the third paper in the series papers published in Atmospheric Environment to develop new emission estimation models by the regression method. A group of regression models for various industrial and non-industrial sectors were proposed based on an emission investigation case study of Handan region in northern China. The main data requirements of the regression models for industrial sectors were coal consumption, oil consumption, gaseous fuel consumption and annual industrial output. The data requirements for non-industrial sector emission estimations were the population, the number of resident population households, the vehicle population, the area of construction sites, the forestland area, and the orchard area. The models were then applied to Tangshan region in northern China. The results showed that the developed regression models had relatively satisfactory performance. The modeling errors at the regional level for SO2, NOx, VOCS and CO were -16.5%, -10.6%, -11.8% and -22.6%, respectively. The corresponding modeling errors at the county level were 39.9%, 33.9%, 46.3% and 46.9%, respectively. The models were also applied to other regions in northern China. The results revealed that the new models could develop emission inventories with generally lower error than found in previous emission inventory studies. The developed models had the advantages of only using publicly available statistical information for developing high-accuracy and high-resolution emission inventory, without requiring detailed data investigation which is necessary by conventional "bottom-up" emission inventory development approach. [ABSTRACT FROM AUTHOR]

The increasing energy demand in harbour areas, coupled with the need to reduce pollutant emissions, has led to the development of renewable energy-based polygeneration systems to face the carbon footprint of ports and ships at berth. In this way, in the coming years, ports can be converted into modern energy hubs. From this point of view, this paper presents a new dynamic simulation model for assessing and optimizing the energy and economic impact of ports. Here, energy systems and renewable sources can be designed to be connected to national electricity and natural gas grids and can include also alternative fuels (hydrogen, biomethane, etc.) and thermal energy networks, as well as different biomass fluxes (to be exploited for energy aims). Energy availability/demands of near towns and port buildings/infrastructures, as well as on-shore power supply are also included in the dynamic assessments. Hourly weather data and different prices for all the considered energy carriers are taken into account hour by hour. A multi-objective optimization approach is also implemented in the model considering energy and economic indexes to be optimized. The whole model is implemented in a computer tool written in MATLAB. For showing the capability of the developed model, a novel case study referred to the port of Naples (South-Italy) is presented. Here, several renewable energy sources are considered, including an anaerobic biodigester for producing biogas from the organic waste of docked cruise ships. A combined heat and power system (fed by biogas) is implemented in the port energy hub also for supplying absorption chillers. PV panels, and marine power generators are also included. In the conducted analysis, optimization targets are the maximization of system self-consumption and self-sufficiency as well as the minimum simple payback period. The proposed system can effectively contribute to the decarbonization of the port energy demand and reduce harmful pollutant emissions. Results showed that very high rate of renewable energy produced on-site can be exploited (up to 84%) by the considered port facilities, ensuring increasing independency from utility power grid (self-sufficiency index up to 40%). By the obtained results and through the developed simulation/optimization tool, novel design and operating criteria can be achieved for future port energy hubs featured by renewables and bi-directional energy exchange between ships and port. [ABSTRACT FROM AUTHOR]

Abstract: Rapid economic development of industrial cities has led to a significant increase in energy consumption and carbon emissions in China. Through the log-mean Divisia index decomposition method and the cluster analysis method, this paper provides a systematic method to (1) analyze the time series of carbon emissions from the energy consumption of the industrial sector in a city; (2) explore the main factors affecting carbon emissions; and (3) divide industries in a city into different types and analyze combination features of “emissions–efficiency”. Finally, this paper takes Tianjin as an example, and studies the emissions characteristics of Tianjin. Results show that high-emission and low-efficiency industries play important roles in the development and economic growth of industries in Tianjin, improvements in energy utilization efficiency are the most important contributors to effective industrial energy conservation and emission reductions in Tianjin, and that the method developed in this paper is practical in the analysis of carbon emissions characteristics of an industrial city or region. [Copyright &y& Elsevier]

Abstract: Industry uses around one third of the world’s energy, and accounts for about 40% of global carbon dioxide emissions. There is increasing economic and social pressure to improve efficiency and create closed-loop industrial systems, in which energy efficiency plays a key role. This paper describes some of the key concepts involved in modelling the energy flows in manufacturing, both for the building services and the industrial processes. Detailed dynamic energy simulation of buildings is well established and routinely used, working on a time series basis – but current tools are inadequate to model the energy flows of many industrial processes. There are also well-established models of manufacturing flows, used to optimise production efficiency, but typically not modelling energy, and usually representing production and material flows as event-driven processes. The THERM project has developed new software tools to model energy-related and other utility flows in manufacturing, incorporating these into existing thermal models of factory buildings. This makes it possible to map out the whole energy system, and hence to test efficiency measures, to understand the effect of processes on building energy use, to investigate recycling of heat or cooling into other processes or building conditioning, and so on. The paper describes some of the key concepts and modelling approaches involved in developing these models, and gives examples of some real processes modelled in factories. It concludes that such models are entirely feasible and potentially very useful, although to develop a tool which comprehensively models both energy and manufacturing flows would be a major undertaking. [Copyright &y& Elsevier]

Abstract: Index decomposition analysis (IDA) was first extended from energy consumption to energy-related CO2 emission studies in 1991. Since then many studies have been reported covering various countries and emission sectors. However, unlike the case of energy consumption studies, a comprehensive literature survey that focuses specifically on emission studies has so far not been reported. In this paper, we attempt to fill this gap by reviewing 80 papers appearing in peer-reviewed journals from 1991 to 2012 in this application area. The first part of this paper deals with the developments with regard to the IDA approaches used by researchers, and the scope and focus of their studies. In the second part, the empirical results reported in the surveyed studies are analyzed, consolidated, and presented by emission sector. The objective is to reveal the relative contributions of key effects on changes in the aggregate carbon intensity, and this is done by emission sector and by country. The findings of both parts are useful in understanding the development of IDA in the application area of emission study, as well as the key drivers of aggregate carbon intensities in the past and their possible future developments. [Copyright &y& Elsevier]

Abstract: This paper analyses the cost effectiveness of the implementation of some of the Best Available Technologies (BATs) and Innovative Technologies (ITs) in the European industry up to 2030. This is done using a bottom-up model that considers the main processes involved in each facility. The model described in the paper assumes the retrofitting/upgrade of each European facility with a BAT or IT as soon as the criterion for a capital budgeting decision is met. The paper details the effect on the savings in energy and CO2 emissions by European industry, assuming different levels of requirement in the payback period used as main capital-budgeting decision criterion. This approach reveals the full potential that some technologies under research (as the ones considered in the Ultra–Low CO2 Steelmaking project and Carbon Capture and Storage technologies, as well as other technologies that are not widely deployed (Direct Reduced Iron technologies), may have in the European industry. The starting point of the simulation is adjusted so that the CO2 emissions of each facility in the model have a counterpart in the emissions recorded for the benchmarking exercise of the European Union Emissions Trading Scheme. The results show that, by 2030, for a payback period of two years, the margin of improvement in CO2 emissions is around 20%. Whereas, by 2030, for a payback period of six years, the margin of improvement in CO2 emissions is in the range between 50% and 65%. [Copyright &y& Elsevier]

Abstract: The basis for Sustainable PLM is enabling Intelligent Products to communicate between themselves and with other systems in order to reduce CO2 emissions, energy usage, and environmental damage. This type of communication between Intelligent Products and other information systems with the objective of reducing environmental impacts is an example of closed-loop product lifecycle management. The objective of the paper is to outline an architectural information system model for implementing Sustainable PLM based on experiences from a number of real-life applications. The technological challenge for developing Sustainable PLM is the high number and variety of information systems that need to communicate over organizational limits and over time. In the paper we describe how Sustainable PLM has been implemented using Intelligent Products in a number of representative real-life applications. [Copyright &y& Elsevier]

Abstract: In densely populated countries there is a growing and compelling need to use underground for different and possibly coexisting technologies to produce “low carbon” energy. These technologies include (i) clean coal combustion merged with CO2 Capture and Storage (CCS); (ii) last-generation nuclear power or, in any case, safe nuclear wastes disposal, both “temporary” and “geological” somewhere in Europe (at least in one site): Nuclear wastes are not necessarily associated to nuclear power plants; (iii) safe natural gas (CH4) reserves to allow consumption also when the foreign pipelines are less available or not available for geopolitical reasons and (iv) “low-space-consuming” renewables in terms of Energy Density Potential in Land (EDPL measured in [GWh/ha/year]) as geothermics. When geothermics is exploited as low enthalpy technology, the heat/cool production could be associated, where possible, to increased measures of “building efficiency”, low seismic risks building reworking and low-enthalpy heat managing. This is undispensable to build up “smart cities”. In any case the underground geological knowledge is prerequisite. All these technologies have been already proposed and defined by the International Energy Agency (IEA) Road Map 2009 as priorities for worldwide security: all need to use underground in a rational and safe manner. The underground is not renewable in most of case histories [10,11]. IEA recently matched and compared different technologies in a unique “Clean Energy Economy” improved document (Paris, November 16–17, 2011), by the contribution of this vision too (see reference). In concert with “energy efficiency” improvement both for plants and buildings, in the frame of the “smart cities” scenarios, and the upstanding use of “energy savings”, the energetic planning on regional scale where these cities are located, are strategic for the year 2050: this planning is strongly depending by the underground availability and typology. Therefore, if both literature and European Policy are going fast to improve the concept of “smart cities” this paper stresses the concept of “smart regions”, more strategic than “smart cities”, passing throughout a discussion on the synergic and conflicting use of underground to produce energy for the “smart regions” as a whole. The paper highlights the research lines which are urgent to plan the soundest energy mix for each region by considering the underground performances case by case: a worldwide mapping, by GIS tools of this kind of information could be strategic for all the “world energy management” authorities, up to ONU, with its Intergovernmental Panel on Climate Change (IPCC), the G20, the Carbon Sequestration Leadership Forum (CSLF) and the European Platforms such as the “Zero Emissions Fossil Fuel Power Plants” (EU-ZEP Platform), the Steel Platform, the Biomass Platform too. All of these organizations agree on the need for synergistic and coexistent uses of underground for geological storage of CO2, CH4, nuclear waste and geothermic exploitation. The paper is therefore a discussion of the tools, methods and approaches to these underground affecting technologies, after a gross view of the different uses of underground to produce energy for each use, with their main critical issues (i.e. public acceptance in different cases). The paper gives some gross evaluation for the Lazio Region and some hints from the Campania Region, located in Central Italy. Energy Density Potential in Land (EDPL), is calculated for each renewable energy technology (solar, wind, geothermal) highlighting the potentiality of the last. Why the Italian case history among the densely populated countries? on the Italian territory is hard to find suitable areas (mostly if greenfields) to use the own underground, with respect to other European countries, due to the presence of seismotectonic activity and many faulted areas characterized by Diffuse Degassing Structures (DDSs, which are rich in CO2 and CH4). In this cases, public acceptance must be facilitated by the concerted efforts of researchers, universities, NGOs and policy-makers. [Copyright &y& Elsevier]

Abstract: Cement industry is one of the largest carbon emitting industrial sectors. It is responsible for about 5% of anthropogenic CO2 in the world. Therefore, it is a relevant industrial sector for CO2 emission regulation strategies. Bearing in mind the importance of cement industry in Croatia, and because of the fact that Croatia will soon become an EU member state, the present paper analyses the potential to reduce CO2 emission in the Croatian cement industry. There are several measures that can reduce CO2 emissions from the cement manufacturing process: the use of waste heat as an alternative source of energy; CO2 capture and storage technologies; reduction of clinker to cement ratio; the use of alternative and biomass fuels; the use of alternative raw materials; an energy efficient combustion process. The most energy efficient technology for cement manufacturing today is the use of a rotary kiln together with a multi-stage preheater and a calciner. Since the use of cement calciners is a relatively new technology, further improvement of their operating conditions is still needed. This paper also highlights the results of research in the field of computational fluid dynamic (CFD) simulations that are used for the investigation of process and combustion emissions. The above mentioned measures together with numerical investigations can reduce the effect of cement manufacturing in Croatia on the environment and can make it more competitive with cement manufacturers from the EU. [Copyright &y& Elsevier]

Abstract: The paper reports foremost the results of a successful combustion of an innovative lignocellulosic biofuel in a gas turbine. The fuel was processed through liquefaction of lignocellulosic materials with polyhydroxy alcohols in an acid catalyzed reaction. The liquefaction process features: high efficiency, high liquid yields and inexpensive, easily available process equipment. For the purpose of this analysis the following were developed: an experimental gas turbine with internal combustion chamber, a preheated pressurized fuel supply system with swirl-air fuel injector and a heat exchanger to obtain high primary air temperatures. The paper gives results on the emissions of CO, THC, NOx and soot. For the purpose of benchmarking the turbine was also run on diesel fuel. The paper presents analyses of the underlying phenomena with which it aims to provide guidelines for improvements in the fuel processing and in the experimental equipment. It has been shown that direct utilization of this innovative lignocellulosic biofuel gives promising results. Although the CO and THC emissions are higher compared to the benchmark diesel results it has been shown that both emissions decrease with increased turbine inlet temperature and with the increased fuel preheat temperature, due to a very high viscosity of the fuel. It is additionally shown that NOx emissions are low and comparable to those of the diesel fuel, whereas soot emissions are very low for both fuels. [Copyright &y& Elsevier]

Abstract: Due to increasing energy scarcity and pressures from climate change, Chinese iron & steel (IS) companies have struggled to implement practices to reduce their energy consumption and CO2 emissions. However, it is not clear whether these practices can improve the environmental or economic performance of these companies. The determinants that drive or hinder the implementation of these practices are also not known. Therefore, this paper describes an empirical analysis of a total of 85 questionnaires of various IS companies across China. A regression analysis was applied in this paper to verify the relationship among CO2 reduction practices, determinants and performance as reported by the IS companies. The results show that although some CO2 reduction practices can result in significant environmental performance, their impacts on the improvement of economic performance are less clear. The paper discusses some implications regarding strategies for prompting CO2 reduction practices that have been considered during the discussion about the determinants that impact on the practices. [Copyright &y& Elsevier]

Abstract: This paper presents the results of a computational study on the energy consumption and related CO2 emissions for heating and cooling of an office building within the Urban Heat Island of London, currently and in the future. The study developed twenty weather files in an East-West axis through London; the weather files were constructed according to future climate change scenario for 2050 suitable for the UK which have been modified to represent specific locations within the London UHI based on measurements and predictions from a program developed for this purpose (LSSAT). The study simulated an office with typical construction, heat gains and operational patterns with an advanced thermal simulation program (IESVE). The predictions confirm that heating load decreases, cooling load and overheating hours increase as the office location moves from rural to urban sites and from present to future years. It is shown that internal heat gains are an important factor affecting energy performance and that night cooling using natural ventilation will have a beneficial effect at rural and city locations. As overheating will increase in the future, more buildings will use cooling; it is shown that this might lead to a five-fold increase of CO2 emission for city centre offices in London in 2050. The paper presents detailed results of the typical office placed on the East-West axis of the city, arguing the necessity to consider using weather files based on climate projections and urban heat island for the design of current buildings to safeguard their efficiency in the future. [Copyright &y& Elsevier]

Abstract: Combustion in fired heaters, boilers and furnaces often accounts for the major energy consumption on industrial processes. Small improvements in efficiency can result in large reductions in energy consumption, CO2 emissions, and operating costs. This paper will describe some useful low cost modelling techniques based on the zone method to help identify energy saving opportunities on high temperature fuel-fired process plant. The zone method has for many decades, been successfully applied to small batch furnaces through to large steel-reheating furnaces, glass tanks, boilers and fired heaters on petrochemical plant. Zone models can simulate both steady-state furnace operation and more complex transient operation typical of a production environment. These models can be used to predict thermal efficiency and performance, and more importantly, to assist in identifying and predicting energy saving opportunities from such measures as: [•] Improving air/fuel ratio and temperature controls. [•] Improved insulation. [•] Use of oxygen or oxygen enrichment. [•] Air preheating via flue gas heat recovery. [•] Modification to furnace geometry and hearth loading. There is also increasing interest in the application of refractory coatings for increasing surface radiation in fired plant. All of the techniques can yield savings ranging from a few percent upwards and can deliver rapid financial payback, but their evaluation often requires robust and reliable models in order to increase confidence in making financial investment decisions. This paper gives examples of how low cost modelling techniques can be applied to improve confidence in implementing energy efficiency improvements whilst safeguarding manufacturing output and quality. [Copyright &y& Elsevier]

Abstract As a significant basic industry for the national economic development, coal chemical industry is one of the main contributors to energy consumption and CO 2 emission. In this paper, the CO 2 emission in the time series of 2020 and 2030 was calculated and the Logarithmic Mean Divisia Index (LMDI) method was employed to explore the driving forces of CO 2 emission change. According to the industry development, the CO 2 emission in 2020 and 2030 was tentatively predicted. The results show that China's coal chemical industry has experienced a significant increase in CO 2 emission, from 177.87 million ton CO 2 (MtCO 2) to 427.19 MtCO 2 in 2005–2015, with an average annual growth rate of 9.16%. Currently, the coal-to-ammonia industry is the largest contributor. According to the decomposition analysis, the economic growth and energy intensity are the two positive factors and the industry structure is a negative factor to carbon emission change. In 2020, the CO 2 emission will be 617.34 MtCO 2 under slow development scenario and 759.69 MtCO 2 under rapid development scenario. In 2030, the CO 2 emission will reach 1041.90 MtCO 2 and 1440.13 MtCO 2 under slow and fast development scenarios, respectively. The coal-to-olefins industry will take the place of coal-to-ammonia and turn to be the largest one in 2020 and 2030 if no CO 2 capture, utilization and storage (CCUS) technologies are adopted. It is probable that the contribution from coal-to-methanol will also play important role for CO 2 emission due to its rapid development. In addition, by 2030, if coal-to-natural gas industry develops as planned, its CO 2 emission will significantly increase, which has the potential to be equivalent to that of olefins industry. Highlights • The CO 2 emission evolution trend in China's coal chemical industry is analyzed. • The major driving factors of CO 2 emission change are identified and the effect sizes of various factors are evaluated. • The CO 2 emission in 2020 and 2030 is forecasted. • Policy implications to policymakers are provided. [ABSTRACT FROM AUTHOR]

Abstract Improving thermal insulation of buildings envelopes can reduce their energy consumption and related CO 2 emissions considerably. Searching for new and innovative insulation materials is therefore a key challenge. This paper presents an experimental study to show the effect of adding spent coffee grounds (SCGs) on thermal properties of plaster composite. The obtained results using the box method show a significant decrease of thermal conductivity along with an increase of the coffee ground content, indicating the possible usage of the resulting material as efficient insulation in buildings. It is found that the thermal conductivity of the resulting building material can be decreased from 0.5 to 0.31 W/m.K by adding 6 wt% of CGs to the initial material. To illustrate energetically and environmentally the benefit of using the proposed material, annual simulations were carried out for a typical Moroccan house located in Marrakech. The results indicated that up to 20% of the cooling and heating loads of the building can be reduced if the proposed material substitutes the conventional one. From an environmental point of view, the utilization of the proposed material can reduce up to 1500 kg CO 2 , annually for the studied case. [ABSTRACT FROM AUTHOR]

Abstract Theses on China's low-carbon economy focus on the driving forces of carbon emissions, energy–carbon efficiency, and the carbon–economy nexus. Meanwhile, comprehensive frameworks that assess China's green economy and also analyze its driving forces are lacking. This paper constructs a green productivity index based on the Global Malmquist–Luenberger productivity index to evaluate the development of the low-carbon economy in China. A panel vector auto-regression model is adopted to further analyze the endogenous interactions and dynamic relationships among aspects of the green economy and its influencing factors. Empirical results show that China has seen a balanced development of green economic growth in 2000–2016, achieved in a series of clear stages. To maintain the sustainable growth of the low-carbon economy in the future, China must rely more on technological progress. This research also makes some important discoveries that have not been found in previous studies: the impact of China's industrial structure and energy consumption structure on the green economy are short term, having a duration of impact of approximately four years. Finally, we provide an assessment of provincial green economy development and describe the corresponding policy implications. Graphical abstract Image Highlights • A comprehensive analysis of China's green economy. • A slack-based Global Malmquist–Luenberger index is adopted to calculate the Green Productivity Index in China. • The stage characteristics of green economic development are identified. • A panel vector autoregressive model is used to analyze the interactions among aspects of the environmental economic system. • The findings that the impact duration of energy structure, industry structure, and urbanization on the green economy is about four years. [ABSTRACT FROM AUTHOR]

Highlights • Partially premixed combustion was applied on a multi-cylinder engine. • Different injection strategies should be adapted at different engine loads. • During stable operations, a peak gross indicated efficiency of 51% was achieved. • During transient operations, an average net indicated efficiency of 47.5% was demonstrated. Abstract Modern transportation requires advanced powertrain systems to reduce the production of greenhouse gas CO 2. Partially premixed combustion (PPC) is one of the most promising methods to achieve low emission and low fuel consumption of internal combustion engines. The present paper evaluated the effects of the calibration parameters on the efficiency and emissions of a multi-cylinder engine using PPC during stable operations, and the performance of the engine during transient operations. The peak gross indicated efficiency of 51.5% and the peak net indicated efficiency of 48.7% were achieved under stable operating conditions. The transient results also demonstrate an average net indicated efficiency of 47.5%. The nitrogen oxides (NOx), carbon monoxide (CO), and hydrocarbon (HC) conform with the Euro VI emission legislation in the case of most transient operations except some low load points. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we give an overview of the situation of CO2 emissions in both Beijing and Tokyo and discuss and compare the causes for their emission changes according to decomposition based on both social activities and fuel varieties. We find that in order to enjoy a sustainable development, Beijing needs to learn from Tokyo especially in energy consumption area. At the end of the paper, the cooperation between these two metropolises is summarized. [Copyright &y& Elsevier]

Abstract: Reviewing past and current mobility assessments for the Lebanese road transport sector, road mobility demand has experienced a real explosion since 1990, and the trend is strongly upward over the decade to come. This growth is mainly attributed to the raise of daily passenger trips and the increase of car ownership. Moreover, this increase in mobility demand results in severe congestion, mostly in Greater Beirut Area (GBA), which leads to chaotic traffic conditions. As a result, Lebanese citizens are suffering from high budget required for transport, high dependence on fossil fuels, in addition to high pollution level particularly in urban areas. Therefore, reducing the fuel consumption and emissions of Lebanese road transport, particularly for passenger cars, has become a must. Electrification of conventional Internal Combustion Engine Vehicles (ICEV) nowadays appears as an effective solution of paramount importance for car manufacturers, facing the challenge of minimizing the consumption of the road transport. Therefore, the objective of this paper is to present latest technological advancements of hybrid electric vehicles and to assess their impacts in terms of fuel savings in Lebanese urban driving conditions. The logic of vehicle electrification is outlined first by presenting the technological advantages with respect to conventional vehicles. Then the paper addresses a tank-to-wheel energy consumption comparison and an operating costs comparison between several hybrid electric vehicle types and a reference conventional vehicle, on real world driving cycles, representative of GBA driving conditions. Driving cycles are collected during a survey on real route in GBA using onboard GPS devices equipped with data loggers. Finally, an assessment of fuel consumption and CO2 emissions of the Lebanese car fleet is presented, in addition to a methodology for creating mitigation scenarios serving to reduce consumption and emissions by 2020. [Copyright &y& Elsevier]

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]

Abstract There are no commonly agreed ways to assess the total energy consumption of the Internet. Estimating the Internet's energy footprint is challenging because of the interconnectedness associated with even seemingly simple aspects of energy consumption. The first contribution of this paper is a common modular and layered framework, which allows researchers to assess both energy consumption and CO 2 e emissions of any Internet service. The framework allows assessing the energy consumption depending on the research scope and specific system boundaries. Further, the proposed framework allows researchers without domain expertise to make such an assessment by using intermediate results as data sources, while analyzing the related uncertainties. The second contribution is an estimate of the energy consumption and CO 2 e emissions of online advertising by utilizing our proposed framework. The third contribution is an assessment of the energy consumption of invalid traffic associated with online advertising. The second and third contributions are used to validate the first. The online advertising ecosystem resides in the core of the Internet, and it is the sole source of funding for many online services. Therefore, it is an essential factor in the analysis of the Internet's energy footprint. As a result, in 2016, online advertising consumed 20–282 TWh of energy. In the same year, the total infrastructure consumption ranged from 791 to 1334 TWh. With extrapolated 2016 input factor values without uncertainties, online advertising consumed 106 TWh of energy and the infrastructure 1059 TWh. With the emission factor of 0.5656 kg CO 2 e /kWh, we calculated the carbon emissions of online advertising, and found it produces 60 Mt CO 2 e (between 12 and 159 Mt of CO 2 e when considering uncertainty). The share of fraudulent online advertising traffic was 13.87 Mt of CO 2 e emissions (between 2.65 and 36.78 Mt of CO 2 e when considering uncertainty). The global impact of online advertising is multidimensional. Online advertising affects the environment by consuming significant amounts of energy, leading to the production CO 2 e emissions. Hundreds of billions of ad dollars are exchanged yearly, placing online advertising in a significant role economically. It has become an important and acknowledged component of the online-bound society, largely due to its integration with the Internet and the amount of revenue generated through it. Highlights • A practical framework for assessing the environmental impact of any Internet service • Online advertising consumed between 20.38 to 282.75 TWh of energy and 11.53 – 159.93 million tons of CO 2 e was emitted to produce the electricity consumed. • Invalid traffic associated with online advertising resulted in 2.65 – 36.78 million tons of CO 2 e emissions. • The energy burden of online advertising is considerable and urgently requires attention from researchers and industries [ABSTRACT FROM AUTHOR]

Reliable energy statistics serve as the foundation and starting point for understanding the climate policies of any country. As the most comprehensive sources of energy data for China, China Energy Statistics Yearbooks (ESY), published by the National Bureau of Statistics (NBS), underwent three major revisions since 2005. This paper analyzes how these three major revisions correspond to data on China's energy use from 1996 to 2012, and theirs impacts on CO 2 emissions, emission intensity and the share of non-fossil energy in total energy consumption, which are key indicators of China's climate policies. Some notable changes include CO 2 emissions for 2012, which increased by 594 Million tons – a figure equivalent to South Korea's annual emissions, which implies that China's emissions at peak level will be higher than previous estimation. Meanwhile, revised emission intensity data show a higher amount and lower decreasing rate, which means that China's achievements in decreasing emission intensity during 2005–2012 have been overestimated, while future difficulties for achieving the goal of 40–45% reduction will be greater. On the share of non-fossil fuel energy in China's total energy mix, the adjustments increased the indicator by 1.26%, reflecting the fact that China's effort in developing non-fossil energy had been underestimated. Discrepancies in reported scattered coal in different statistics versions are the main contributors to these changes. To further enhance the reliability of its energy statistics, and thereby its climate policies, China should remove incentives for misreporting through legal means, and make the technical system for data collection more comprehensive and accurate, with particular emphasis on scattered coal. [ABSTRACT FROM AUTHOR]

Highlights • The input–output model and ecological network analysis (ENA) are integrated. • The control and dependence conditions of economic sectors in China are analyzed. • The key regions and sectors for carbon mitigation of China are identified. Abstract In this paper, multi-regional input–output analysis (MRIO) and ecological network analysis (ENA) are combined to assess carbon flows within China and identify key regions and sectors in the context of spatial heterogeneity for effective carbon mitigation. An interregional carbon network model is established by articulating the directions and magnitudes of carbon flows based on MRIO. ENA is then used to unveil indirect carbon flows and mutual relationships among regions. The results show that the northwest is the largest controller for most regions in China. Most carbon emissions in the rest of China are induced by the east’s final demand and substantial consumption. In addition, at sectoral level, the control and dependence abilities vary by region in China. This study provides an integrated framework to investigate interregional carbon emission structure, identify efficient pathways for coordinated emission mitigation, and reduce global carbon inequality across regions. [ABSTRACT FROM AUTHOR]