Regional patterns of energy production and consumption factors in Europe Exploratory Project EREBILAND - European Regional Energy Balance and Innovation Landscape

The Resilient Energy Union with Forward Looking Climate Change Policy is one the ten priorities of the overarching Agenda for Jobs, Growth, Fairness and Democratic Change of the European Commission. The Communication on the Energy Union package and its Annex clearly identify EU-wide targets and policy objectives. The Exploratory Project EREBILAND (European Regional Energy Balance and Innovation Landscape) aims at supporting efficient patterns of regional energy supply and demand in Europe. Integration of spatial scales, from EU-wide to regional or local, and a cross-sector approach, are at the core of the project. The approach is based on territorial disaggregation of information, and the development of optimisation scenarios at regional scale. It is centred around the Land Use-based Integrated Sustainability Assessment (LUISA) modelling platform for the assessment of policies and investments that have spatial impacts, in interaction with the JRC-EU-TIMES model – a bottom-up, technology-rich model representing the EU28+ energy system – and the model RHOMOLO that integrates economic and some social dimensions of regional development. Based on currently operational and up-to-date tools available within the EC, the purpose of the EREBILAND project is to: • provide an overview of the current trends of regional energy production and consumption patterns, and • link these patterns to the structural characteristics of the regions, among which: population density and urbanisation trends, development of different economic sectors, and availability of resources and technological infrastructure. This report presents the outcomes of the EREBILAND Project during its first year. In particular, electricity generation and energy consumed by transport sector are analysed, under the EU Energy Reference Scenario 2013, throughout the period 2015 - 2030. Main results of the analysis dedicated to the electricity generation are: • Electricity generation from biomass increases in the large majority of European regions; a slight decrease can be found only in regions producing electricity already in 2015 above the EU28 average (in Denmark). • Electricity produced from biogas experiences less steep changes then biomass, with almost 50% of NUTS2 decreasing or not changing considerably the amount of electricity produced from this source. • Coal: electricity generated from lignite undergoes a significant reduction in all regions using this fuel already in 2015. Conversely, trends in electricity generated from hard coal are more stable, with some regions experiencing an increase: the average change is higher than 50% (a few regions in Eastern European countries), but steeper increases can be found in Austria, Sweden and the United Kingdom. • The amount of electricity generated from gas generally decreases across Europe from 2015 to 2030, with an average decrease higher than 90%. • Geothermal is the least diffuse source used to generate electricity in Europe and only few regions are represented. • Hydroelectric: the amount of electricity generated from this source is in general forecasted to increase in Europe from 2015 to 2030. Exceptions are a few regions in Bulgaria, Czech Republic, Germany, Spain, Greece, Hungary, Portugal, Romania, Sweden and most NUTS2 in the UK. • Electricity generated from nuclear is forecasted to decrease in the majority of the regions with active nuclear power plants in 2015. • Oil: the majority of the regions generating electricity from this fuel in 2015, experience a decrease in 2030. Notable exceptions are a few regions in Austria, Belgium, Germany, Greece, Hungary, Italy, Poland and Slovenia. • Electricity produced from solar is forecasted to increase in almost three quarters of European regions. The only regions where electricity from solar is forecasted to decrease are located in Greece and Romania. • Wind: electricity generated from wind, both on- and off-shore, is in general forecasted to increase in Europe. The largest increases in electricity generated from on-shore wind (above 5 times the 2015 generation levels) can be found in few regions in Czech Republic, Finland, Lubuskie in Poland, the north-est NUTS2 in Romania, Western Slovakia and Slovenia. Main results of the analysis dedicated to energy consumption of the transport sector are: • In more than two thirds of European regions, the energy supplied to cars (fuel: diesel) decreases from 2015 to 2030, with an average decrease of almost 20%. • The energy supplied to cars (fuels: gas and LPG) is forecasted to decrease throughout all European regions. The decrease is more gradual in few regions in Denmark, Portugal, Greece, Spain and Italy. • Energy supplied to cars (fuel: gasoline) is forecasted to decrease in more than 80% of the European regions, with an average decrease of 27%. • The energy supplied to heavy duty trucks (fuel: diesel) is forecasted to progressively decrease from 2015 to 2030 in 66% of the European regions, with an average decrease of more than 8%. • The energy supplied to light duty trucks (fuel: diesel) is forecasted to steeply decrease throughout European regions. • The energy supplied to light duty trucks (fuel: gasoline) is forecasted to increase in more than 90% of European regions, with an average increase of more than 40% from 2015 to 2030. The highest increases (above 70%) take place in eleven regions in Germany, Walloon Brabant in Belgium, Flevoland in the Netherlands, Lower Austria and Eastern Macedonia and Thrace. • The energy supplied to inter-city buses running on diesel is forecasted to increase from 2015 to 2030 in the large majority of European regions, with an average increase of more than 19%. • The energy supplied to urban buses (fuels: gas, diesel and gasoline) is going to moderately increase from 2015 to 2030 in almost 90% regions throughout EU-28, with an average growth of 15%. • Energy supplied to motorcycles (fuel: gasoline) is forecasted to increase in more than 80% of European NUTS2, with an average growth of 16%. • Energy supplied to cars (fuels: hybrid, electric and hydrogen) is forecasted to increase throughout Europe, in general with sharp increases. • Energy supplied to heavy duty trucks (fuel: gas) and light duty trucks (fuel: LPG) is forecasted to increase in all European regions from 2015 to 2020. In most NUTS2 this trend is kept or even accelerates between 2020 and 2030. The only regions where the trend is reversed (lower energy supplied in 2030 compared to 2020) are located in Poland, Greece, Finland (only Åland) and Croatia (only Jadranska Hrvatska).JRC.H.8-Sustainability Assessmen

Energy demand models for policy formulation : a comparative study of energy demand models

This paper critically reviews existing energy demand forecasting methodologies highlighting the methodological diversities and developments over the past four decades in order to investigate whether the existing energy demand models are appropriate for capturing the specific features of developing countries. The study finds that two types of approaches, econometric and end-use accounting, are used in the existing energy demand models. Although energy demand models have greatly evolved since the early 1970s, key issues such as the poor-rich and urban-rural divides, traditional energy resources, and differentiation between commercial and non-commercial energy commodities are often poorly reflected in these models. While the end-use energy accounting models with detailed sector representations produce more realistic projections compared with the econometric models, they still suffer from huge data deficiencies especially in developing countries. Development and maintenance of more detailed energy databases, further development of models to better reflect developing country context, and institutionalizing the modeling capacity in developing countries are the key requirements for energy demand modeling to deliver richer and more reliable input to policy formulation in developing countries.Energy Production and Transportation,Energy Demand,Environment and Energy Efficiency,Energy and Environment,Economic Theory&Research

CGE-Microsimulation Modelling: A Survey

This paper reviews the recent work on the application of the CGE-microsimulation models. The discussion focuses on the various linking methodologies and how they can impact our results.Computable General Equilibrium (CGE) Model; Microsimulation; Poverty; Inequality;

Urban seismic risk index for Medellín, Colombia, based on probabilistic loss and casualties estimations

The final publication is available at Springer via http://dx.doi.org/10.1007/s11069-015-2056-4Medellín is the second largest city of Colombia with more than 2 million inhabitants according to the latest census and with more than 240,000 public and private buildings. It is located on an intermediate seismic hazard area according to the seismic zonation of Colombia although no destructive earthquakes have occurred having as a consequence low seismic risk awareness among its inhabitants. Using the results of a fully probabilistic risk assessment of the city with a building by building resolution level and considering the dynamic soil response, average annual losses by sectors as well as casualties and other direct effects are obtained and aggregated at county level. Using the holistic evaluation module of the multi-hazard risk assessment CAPRA platform, EvHo, a comprehensive assessment that considered the social fragility and lack or resilience at county level is performed making use of a set of indicators with the objective of capturing the aggravating conditions of the initial physical impact. The urban seismic risk index, USRi, is obtained at county level which is useful to communicate risk to decision-makers and stakeholders besides making easy identifying potential zones that can be problematic in terms of several dimensions of the vulnerability. This case study is an example of how a multidisciplinary research on disaster risk reduction helps to show how risk analysis can be of high relevance for decision-making processes in disaster risk management.Peer ReviewedPostprint (author's final draft

Perspectives on subnational carbon and climate footprints: A case study of Southampton, UK

Sub-national governments are increasingly interested in local-level climate change management. Carbon- (CO2 and CH4) and climate-footprints—(Kyoto Basket GHGs) (effectively single impact category LCA metrics, for global warming potential) provide an opportunity to develop models to facilitate effective mitigation. Three approaches are available for the footprinting of sub-national communities. Territorial-based approaches, which focus on production emissions within the geo-political boundaries, are useful for highlighting local emission sources but do not reflect the transboundary nature of sub-national community infrastructures. Transboundary approaches, which extend territorial footprints through the inclusion of key cross boundary flows of materials and energy, are more representative of community structures and processes but there are concerns regarding comparability between studies. The third option, consumption-based, considers global GHG emissions that result from final consumption (households, governments, and investment). Using a case study of Southampton, UK, this chapter develops the data and methods required for a sub-national territorial, transboundary, and consumption-based carbon and climate footprints. The results and implication of each footprinting perspective are discussed in the context of emerging international standards. The study clearly shows that the carbon footprint (CO2 and CH4 only) offers a low-cost, low-data, universal metric of anthropogenic GHG emission and subsequent management

An Integrated Energy Economic Interaction Model with Application to Egypt

Traditional bottom-up energy models have been widely applied to date to assess the impact of the future energy technologies over a specific time horizon, quantifying the direct economic and environmental implications caused by the evolution of the energy sector. However, such approaches ignore the interactions that the energy sector has with other sectors in the economy, hence failing in quantifying the global impact associated with their technologies: this may produce an unfortunate bias in the definition of future energy and environmental policies. The present study assesses, on a nationwide economy scale, the economic and environmental impacts due to the optimal future power generation mix in Egypt, by soft-linking a bottom-up, technology-rich model (OSeMOSYS) with a top-down Input-Output Analysis model (IOA, based on the EORA 26 dataset). Based on the OSeMOSYS energy modeling framework, the OSeMOSYS-Egypt model is developed. The least cost power generation mix is determined for two different electricity demand forecasts, based on both the New Policies demand forecast scenario developed by International Energy Agency and the market research performed by Business Monitor International. The robustness of the obtained results is assessed through a sensitivity analysis on the main exogenous parameters, including costs, efficiency and production targets of energy technologies, capital discount rate, water and natural gas resources availability. The evolution of the Egyptian power sector in years 2018 to 2040 is analyzed: results of the bottom-up energy model are adopted as exogenous parameters to the top-down multi-sector model, as a way of coupling the two aforementioned models. It is revealed that Combined Cycles, Wind, and Photovoltaic rooftop systems are viable technologies that should be considered in the future Egypt’s power generation mix. In particular, among Egypt’s abundant renewable energy resources, it is shown that wind power technology comes first in achieving the proposed target on renewables penetration in the country’s generation mix, and it might be a feasible alternative to replace part of the natural gas share. To increase the accuracy of the analysis, the original OSeMOSYS framework has been enhanced by imposing the discount rate on capital investments for the energy technologies, as a time dependent exogenous variable; in developing countries in general and in Egypt in particular, discount rates have been known to fluctuate widely. The derived power generation mix, predicted by the bottom-up model, has been applied to the IOA model in the form of a change in energy technology mix and a change in final demand of electricity. To account for the growth in the national GDP during the temporal planning horizon, an econometric function that relates the growth in GDP to increase in the production of electricity is formulated. Besides the results of the energy model, this approach enables the decision maker to assess the expected primary energy requirements, GHG emissions and water use induced by the evolution of the energy mix in a broader perspective. It is worth to note that, the results of the bottom-up energy optimization model indicates that the anticipated increase in the penetration of renewables in the power generation mix, would decrease the primary non-renewable energy consumption and GHG emissions directly caused by the power generation sector over the considered temporal planning horizon (2018-2040). However, the application of the IOA model reveals that decarbonizing the power sector alone is not sufficient in achieving neither, the decoupling of the GDP growth and the total primary energy consumption, nor the GHG emissions within the Egyptian economy

Climate Vulnerability of the Supply-Chain: Literature and Methodological review

The increasing complexity of the present economic system and the strong interdependencies existing between production activities taking place in different world areas make modern societies vulnerable to crisis. The global supply-chain is a paradigmatic example of economic structures on which the impacts of unexpected events propagate rapidly through the system. Climate change, which affects societies all over the world, is one of the most important factors influencing the efficiency of the present economic networks. During the last decades a large set of studies have been oriented to investigate the direct impacts generated on specific geographical areas or productions. However, a smaller number of analyses have been oriented to quantify the cascading economic effects generated all over the world. The great complexity of the global economic system, coupled with methodological and data gaps makes it difficult to estimate the domino effects of unexpected events. A clear understanding of the possible consequences generated all over the world is, however, a fundamental step to build socio-economic resilience and to plan effective adaptation strategies. Within this context, the main objective of the present report is to provide an overview of the main studies, methodologies and databases used to investigate the climate vulnerability of the global supply chain. This information can be useful to i) support further studies, ii) to build consistent quantification methodologies, and iii) to fill the possible data gap.JRC.H.7-Climate Risk Managemen

Projecting socio-economic impacts of bioenergy:Current status and limitations of ex-ante quantification methods

The socio-economic effects of bio-energy are not unequivocally positive, although it is one of the main arguments for supporting its expansion. An ex-ante quantification of the impacts is necessary for transparently presenting the benefits and burdens of bioenergy before they occur, and for minimising unwanted outcomes. In this article, the status, limitations, and possibilities for improvements in ex-ante quantitative research methods for investigating socio-economic impacts of bioenergy are mapped. For this, a literature review to identify relevant indicators, analyse the latest quantitative ex-ante research methods, and to assess their ability and suitability to measure these indicators was performed. The spatial aggregation of existing analyses was specifically considered because quantitative information on different spatial scales shows the geographic distribution of the effects. From the 236 indicators of socio-economic impacts spread over twelve impact categories that were found in this review, it becomes evident that there are clear differences in the ex-ante quantification of these indicators. The review shows that some impact categories receive more attention in ex-ante quantification studies, such as project-level economic feasibility and national-level macroeconomic impacts, while other relevant indicators have not been ex-ante quantified, such as community impacts and public acceptance. Moreover, a key blind spot regarding food security impacts was identified in the aggregation level at which food security impacts are quantified, which does not match the level at which the impacts occur. The review also shows that much more can be done in terms of ex-ante quantification of these impacts. Specifically, spatial disaggregation of models and model collaboration can extend the scope of socio-economic analyses. This is demonstrated for food security impacts, which shows the potential for future household-level analysis of food security impacts on all four pillars of food security

Challenges and opportunities in mapping land use intensity globally

Future increases in land-based production will need to focus more on sustainably intensifying existing production systems. Unfortunately, our understanding of the global patterns of land use intensity is weak, partly because land use intensity is a complex, multidimensional term, and partly because we lack appropriate datasets to assess land use intensity across broad geographic extents. Here, we review the state of the art regarding approaches for mapping land use intensity and provide a comprehensive overview of available global-scale datasets on land use intensity. We also outline major challenges and opportunities for mappinglanduseintensityfor cropland, grazing, and forestry systems, and identify key issues for future research.Peer Reviewe