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• Direct and indirect effects of sectors on net energy consumption are analysed. • Level effect is identified as the major driver for increasing energy consumption. • Manufacturing has the largest energy consumption reduction potential. • How to decrease net energy consumption has been offered to policy-makers. This paper provides a comprehensive analysis of Australian net energy consumption between 2004–05 and 2014–15. Results from environmentally-extended input-output (EEIO) analysis show that the Transport sector has the largest direct effect on net energy consumption in industrial sectors, which decreased by about 35% for net energy consumption per million $AUD in the period. The Export sector has the largest direct net energy consumption while Households consumption results in the largest net energy consumption embodied in different categories of Final demand. The structural decomposition analysis (SDA) decomposes the change of net energy consumption into five drivers, in which net energy intensity mainly reduces Australian net energy consumption by about 8000 Petajoules, while the level effect of Final demand increases it by about 10,000 Petajoules. Analysis of forward and backward linkages highlights the Manufacturing sector as the key industrial sector with the largest energy consumption reduction potential via minor changes in its input and Final demand. This indicates that more attention should be given to the reduction of energy demand from the consumption patterns of Households consumption, the improvement of energy intensity, and the application of cleaner technologies in the Transport and Manufacturing sectors. The Australian Environmental-Economic Accounts is combined with Australian input-output tables to construct the EEIO tables for net energy consumption. The combination of economic and environmental data sets provides a depth of understanding their potential to inform environmental policy decisions. The novelty of the research is the combination of economic and energy data sets, the application of EEIO model, the implementation of the additive SDA method, and the use of forward and backward linkages for the Australian energy system. [ABSTRACT FROM AUTHOR]

Energy system optimization models (ESOMs) are widely used to generate insight that informs energy and environmental policy. Using ESOMs to produce policy-relevant insight requires significant modeler judgement, yet little formal guidance exists on how to conduct analysis with ESOMs. To address this shortcoming, we draw on our collective modelling experience and conduct an extensive literature review to formalize best practice for energy system optimization modelling. We begin by articulating a set of overarching principles that can be used to guide ESOM-based analysis. To help operationalize the guiding principles, we outline and explain critical steps in the modelling process, including how to formulate research questions, set spatio-temporal boundaries, consider appropriate model features, conduct and refine the analysis, quantify uncertainty, and communicate insights. We highlight the need to develop and refine formal guidance on ESOM application, which comes at a critical time as ESOMs are being used to inform national climate targets. [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]

Over the last few years concerns have increased about the energy mix in many countries. These concerns have been of greater magnitude for countries with a common energy regulation such as European Union (EU) member states. An important aspect to take into account when choosing a given energy mix is the efficiency involved in its generation. In this context, the present study analyzes the efficiency with which electricity and derived heat was produced in 25 EU member states over the last decade. This analysis considers not only the inputs and outputs involved but, more importantly, which undesirable by-products were generated during the production process, a relevant issue for EU climate policy. To this end, two nonparametric frontier models are applied: first, a Directional Distance Function (DDF), based on Briec’s (1997) [16] proposal and, second, a modified version of Tone’s (2001) [51] Slacks-Based Measure (SBM) model, both of which are especially appropriate in this particular context due to their treatment of undesirable outputs. Results are partly innovative since, with few exceptions, applications on this issue are relatively scarce. From a policy implications’ point of view, our achievements are also interesting because they reveal remarkable efficiency differences among EU countries: those countries from the latest EU enlargements account for the lowest efficiencies, with large opportunities for improvement in CO 2 abatement and primary energy saving. Results also show stable efficiencies along the evaluated period and, therefore, highlighting the need to further intensify the initiatives designed to harmonize environmental policies and identifying drivers for efficiency improvement turn out to be still key objectives. [ABSTRACT FROM AUTHOR]

• A practical multi-agent problem in the automobile industry is defined. • A comprehensive approach including System Dynamics and game theory is provided. • Energy efficiency, environmental awareness, and social welfare are considered. • A function for the average of vehicle kilometers traveled in a unit of time is suggested. • Several managerial insights for both manufacturers and governments are presented. This paper looks at the effects that environmental policies have on car manufacturers. A standing problem for car manufacturers is determining both a car's price and its level of energy efficiency. The South Korean government has sustainable goals that encompass saving energy, seeking revenue, and advancing social welfare. This study highlights four decision variables in two groups for the government. The government determines the optimal value of each goal, while maintaining a threshold for the two other goals as constraints. The four decision variables are determining the car sales tax, determining the fuel tax, determining the cost of educating the public about environmental awareness, and determining the percentage of government's cooperation in the manufacturer's research and development expenditure. For the purpose of this study, a new function, average of vehicle kilometer traveled in a unit of time (AVKT), is suggested for calculating the average distance driven by a car over a given period of time, based on the cost of fuel, the car's energy efficiency, the driver's environmental awareness quotient, and the rebound effect. This newly defined multi-agent problem is solved by looking at the structure of the Stackelberg game, and equilibrium solutions are offered by implementing the backward induction procedure. By considering demand and profit for fuel, this study offers the most efficient goals and strategies for both car manufacturers and fuel producers alike. Finally, this study offers several results and insights. [ABSTRACT FROM AUTHOR]