scholarly journals Wybrane aspekty oddziaływania rolnictwa na środowisko w państwach Unii Europejskiej

2017 ◽  
Vol 17(32) (1) ◽  
pp. 73-83
Author(s):  
Dorota Janiszewska ◽  
Luiza Ossowska
Keyword(s):  
European Union ◽  
Cluster Analysis ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Ammonia Emissions ◽  
Diagnostic Features ◽  
Gas Emissions ◽  
Eu Countries ◽  
European Union Countries ◽  
Total Ammonia

The main objective of this article is to discuss the diversity of European Union countries based on selected indicators of agriculture's impact on the environment. Figures come from 2013. The analysis was conducted using the cluster analysis. The following diagnostic features were used for the analysis: gross nitrogen balance, share of greenhouse gas emissions from agriculture in the selected country in total greenhouse gas emissions from agriculture in all of EU countries, pesticide sales per hectare UAA, the share of ammonia emissions in the selected country in total ammonia emissions of all EU countries, share of irrigable areas in total UAA and share of organic area in total UAA. As a result of the cluster analysis examined regions were divided into six groups.

scholarly journals Is eco-efficiency in greenhouse gas emissions converging among European Union countries?

2013 ◽  
Vol 47 (1) ◽  
pp. 143-168 ◽  
Author(s):  
Mariam Camarero ◽  
Juana Castillo-Giménez ◽  
Andrés J. Picazo-Tadeo ◽  
Cecilio Tamarit
Keyword(s):  
European Union ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Gas Emissions ◽  
European Union Countries

EMISSION EFFICIENCY OF EUROPEAN UNION COUNTRIES

2018 ◽  
Vol XX (6) ◽  
pp. 55-60
Author(s):  
Edyta Gajos ◽  
Sylwia Małażewska ◽  
Konrad Prandecki
Keyword(s):  
European Union ◽  
United Kingdom ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Value Added ◽  
The European Union ◽  
Gas Emissions ◽  
Emission Efficiency ◽  
European Union Countries ◽  
Emission Volume

The aim of the study was to compare the total greenhouse gas emissions in the European Union countries and their emission efficiency. Emission efficiency was calculated as the ratio of emission volume and value to gross value added generated by the economy of a given country (size of the economy). The necessary statistical data was obtained from Eurostat. It was found that in 2015 most of greenhouse gases were emitted by: Germany, United Kingdom, Poland, France and Italy. At the same time, France and the United Kingdom were characterized by one of the best emission efficiency in the European Union, Germany and Italy obtained average results, while Poland was in the group of countries with the lowest emission efficiency. Therefore, it can be concluded, that the volume of emissions is significantly affected by the size of the economy. Some large emitters have economies based on relatively “clean” technologies and thus their potential to further reduction is not very high. The reverse is true for some low-emission countries, such as Estonia and Bulgaria. This indicates the need for a more comprehensive look at the problem of reducing greenhouse gas emissions.

scholarly journals Environmental Assessment of European Union Countries

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 295 ◽  
Author(s):  
Jin-chi Hsieh ◽  
Ching-cheng Lu ◽  
Ying Li ◽  
Yung-ho Chiu ◽  
Ya-sue Xu
Keyword(s):  
European Union ◽  
Renewable Energy ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Environmental Efficiency ◽  
Gas Emissions ◽  
Dea Model ◽  
Eu Countries ◽  
Carry Over ◽  
The Eu

This study utilizes the dynamic data envelopment analysis (DEA) model by considering time to measure the energy environmental efficiency of 28 countries in the European Union (EU) during the period 2006–2013. There are three kinds of variables: input, output, and carry-over. The inputs are labor, capital, and energy consumption (EC). The undesirable outputs are greenhouse gas emissions (GHE) and sulfur oxide (SOx) emissions, and the desirable output variable is gross domestic product (GDP). The carry-over variable is gross capital formation (GCF). The empirical results show that first the dynamic DEA model can measure environment efficiency and provide optimum improvement for inefficient countries, as more than half of the EU countries should improve their environmental efficiency. Second, the average overall scores of the EU countries point out that the better period of performance is from 2009 to 2012. Third, the output variables of GHE, SOx, and GDP exhibit a significant impact on environmental efficiency. Finally, the average value of others is significantly better than high renewable energy utilization (HRE) with the Wilcoxon test. Thus, the EU’s strategy for environmental energy improvement should be to pay attention to the benefits of renewable energy (RE) utilization, reducing greenhouse gas emissions (GHE), and enhancing the development of RE utilization to help achieve the goal of lower GHE.

scholarly journals Diversification of European Union Member States Due to the Production of Renewable Energy from Agriculture and Forestry

2018 ◽  
Vol 18(33) (2) ◽  
pp. 95-104
Author(s):  
Dorota Janiszewska ◽  
Luiza Ossowska
Keyword(s):  
European Union ◽  
Cluster Analysis ◽  
Renewable Energy ◽  
Union Member ◽  
Energy Change ◽  
Diagnostic Features ◽  
Member States ◽  
Eu Countries ◽  
European Union Countries ◽  
European Union Member States

The main objective of this article is to discuss the diversity of European Union countries in terms of their production of renewable energy from agriculture and forestry. The analysis includes 28 EU countries. Figures come from 2013-2015. Diversification of European Union members was conducted using cluster analysis. The following diagnostic features were used for the analysis: production of renewable energy from agriculture, share of agriculture in production of renewable energy, change in the production of renewable energy from agriculture in 2013-2015, production of renewable energy from forestry, share of forestry in production of renewable energy, change in the production of renewable energy from forestry in 2013-2015. As a result of the cluster analysis examined regions were divided into five groups.

scholarly journals Study of the Percentage of Greenhouse Gas Emissions from Aviation in the EU-27 Countries by Applying Multiple-Criteria Statistical Methods

2020 ◽  
Vol 17 (11) ◽  
pp. 3759 ◽  
Author(s):  
Miriam Andrejiová ◽  
Anna Grincova ◽  
Daniela Marasová
Keyword(s):  
European Union ◽  
Cluster Analysis ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Transport Sector ◽  
Gas Emissions ◽  
Member States ◽  
Average Linkage ◽  
Linkage Method ◽  
The Eu

The transport sector, including air transport, represents an important source of air pollution. The present article deals with the current situation regarding greenhouse gas emissions in the air in 27 European Union (EU-27) member states. Every member state is characterized by selected parameters that determine the unique nature of a particular country (e.g., population, area, life expectancy, gross domestic product (GDP) per capita, etc.). In addition to these parameters, there were also other parameters which were monitored as they characterize the amount of greenhouse gas emissions and the impact of aviation on these emissions. The main purpose of the article is to compare the European Union member states on the basis of 15 examined parameters. The identification of similarities between the EU-27 member states with regard to the selected parameters was carried out by applying principal component analysis (PCA) and hierarchical cluster analysis. The average linkage method was applied to create a dendrogram representing the similarities between the examined member states. The value of the cophenetic correlation coefficient CC = 0.923 confirmed the correct application of the average linkage method. The cluster analysis outputs were five similarity-based homogeneous groups (clusters) into which the 27 member states were divided on the basis of the examined variables.

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