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Streimikiene D.,Lithuanian Energy Institute | Balezentis T.,Lithuanian Institute of Agrarian Economics
Renewable and Sustainable Energy Reviews | Year: 2016

The Kaya identity relates the greenhouse gas (GHG) emissions to energy use, economic growth and population growth. Therefore, it can be applied to decompose GHG emissions with respect to the latter terms. European Union (EU) has established the main targets of sustainable energy development in Energy and Climate package 20-20-20. EU member states conformed to achieve in 2020 GHG emission reduction by 20% comparing with year 1990 level, to achieve 20% of renewable energy sources (RES) in final energy consumption and to reduce energy intensity by 20% compared to year 2005 level. As all of these targets are interrelated and have to be achieved together, it is very important to track the changes of GHG emissions in EU member states alongside the changes in energy intensity and increase in the share of renewables in final energy consumption. The Kaya identity and decomposition analysis allow the linking of changes in GHG emissions to changes in energy intensity and carbon intensity of energy which directly reflects the increase of the share of renewables in final energy consumption. The impact of GDP growth on GHG emissions is also assessed by Kaya identity. The paper applies a novel approach in tracking progress achieved in implementing 20-20-20 targets by employing Kaya identity and Shapley value for decomposition analysis. The conducted analysis showed that policies to increase energy efficiency are the most important drivers of GHG emission reduction and achieving EU 20-20-20 targets in Baltic States. Though the share of RES has increased significantly in Baltic States its impact on GHG emissions reduction per capita in Baltic States was insignificant therefore more emphasis on energy efficiency policies is necessary as they are the most effective measures for achieving GHG emission reduction targets. © 2016 Elsevier Ltd. All rights reserved.

Balezentiene L.,Lithuanian University of Agriculture | Streimikiene D.,Mykolas Romeris University | Balezentis T.,Lithuanian Institute of Agrarian Economics
Renewable and Sustainable Energy Reviews | Year: 2013

Both strategic and environmental factors make biomass an important energy source and element of sustainable energy policy. The establishment of a reasonable energy crop-mix, indeed, involves various uncertain data. This paper, therefore, offers a multi-criteria decision making framework for prioritization of energy crops based on fuzzy MULTIMOORA method which enables to tackle imprecise information. Given the appropriate energy crop-mix should exhibit both climatic suitability and low environmental pressure, we have defined the indicator set covering respective linguistic and numeric indicators. Accordingly, the set of alternatives were constructed from energy crops suitable for the Lithuanian climate. The fuzzy MULTIMOORA method was employed for data fusion and prioritization. As a result, the prospective species for energy crop-mix were suggested. © 2012 Elsevier Ltd.

Streimikiene D.,Lithuanian Energy Institute | Balezentis T.,Lithuanian Institute of Agrarian Economics
Renewable and Sustainable Energy Reviews | Year: 2013

Lithuania has a strong dependence on foreign energy, mainly Russian oil and gas. The need for replacement of old capacities and closure of Ignalina NPP is an extremely important driving force for transformation, making conventional and new technologies compete for a role in the future energy supply in Lithuania. Lithuania adopted national energy independence strategy in 2012 where construction of new NPP is being considered as the main way to increase energy independence however for Lithuanian population the prices of district heat is the major problem therefore the alternative measures are necessary seeking to solve the problem of energy independence and high district heat prices. One possible development path of energy sector is decentralization of the electricity system. Distributed power generation in small, decentralized units could help to reduce emissions, save grid capacity and provide opportunities for renewable energy. It could be a constituent part of a more sustainable energy future. There are several available technologies for implementation of CHP in buildings. These technologies need to be assessed by taking into account economic, environmental and social criteria. Comparative assessment of these technologies in terms of sustainability and to define the most sustainable one. The multi-criteria decision making (MCDM) methods are the celebrated techniques employed for suchlike assessments and can by applied for this task as provides assessment of technologies based on quantitative, qualitative indicators and also allows to tackle with uncertainties when ranges of values for indicators are available. The aim of the paper is to compare the main small scale CHP technologies for buildings and to rank them according the main criteria of sustainability. © 2013 Elsevier Ltd.

Balezentis T.,Lithuanian Institute of Agrarian Economics | Zeng S.,Zhejiang Wanli University
Expert Systems with Applications | Year: 2013

Multi criteria decision making (MCDM) often involves uncertainty which can be tackled by employing the fuzzy set theory. Type-2 fuzzy sets offer certain additional means for the latter purpose. This paper therefore extends the MULTIMOORA method with type-2 fuzzy sets viz. generalized interval-valued trapezoidal fuzzy numbers. The proposed method thus provides the means for multi-criteria decision making related to uncertain assessments. Utilization of aggregation operators also enables to facilitate group multi-criteria decision making. A numerical example of personnel selection demonstrates the possibilities of application of the proposed method in the field of human resource management and performance management in general. © 2012 Elsevier Ltd. All rights reserved.

Balezentis T.,Lithuanian Institute of Agrarian Economics | Misiunas A.,Vilnius University | Balezentis A.,Mykolas Romeris University
Technological and Economic Development of Economy | Year: 2013

Reasonable strategic management requires the complex assessment of the regulated area. This study, thus, presents a multi-criteria framework for frontier assessment of efficiency and productivity across the Lithuanian economic sectors throughout 2000–2010. The data envelopment analysis was employed to estimate efficiency in terms of an output indicator (value added) and input indicators (intermediate consumption, capital consumption, and remunerations). Furthermore, the decomposition of the Malmquist productivity index enabled to describe the impact of frontier shifts and catch-up effect on the overall change in efficiency. The multi-criteria decision making method MULTIMOORA aggregated different indicators of efficiency and productivity and thus resulted in the ranking of the economic sectors. The analysis suggests that services sector was the most efficient one, whereas manufacturing was second best. Certain branches of manufacturing, namely pharmaceutical, wood, food, and furniture industry, were rather efficient. © 2013 Vilnius Gediminas Technical University (VGTU) Press.

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