Ocean Energy in Belgium - 2019

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A Generalisable Bottom-up Methodology for Deriving a Residential Stock Model From Large Empirical Databases.

Average reference dwellings representing a predominant housing typology are defined in this work. Specifying such reference buildings is a prerequisite for (i) calculating cost-optimal energy performance requirements for buildings and building elements and (ii) ensuring valid calculations of national building energy consumption. In the EU, an Energy Performance Certificate (EPC) rating is an assessment of the energy consumption of a dwelling. The use of inappropriate default-values for the building envelope thermal transmittance coefficients (U-values) and standardised thermal bridging transmittance coefficients (Y-values) in the production of EPCs leads to an over-estimation of potential energy savings from interventions in the existing dwelling stock

Rescaling climate justice: sub-national issues and innovations for low carbon futures

Climate justice is emerging as a discourse for mobilising activism around the globe. The language of justice is less explicit as a policy principle despite long standing attention to negotiating responsibilities for causing climate changes and bearing costs related to reducing climate change emissions. Nevertheless there are significant justice issues in terms of how mitigation and adaptation will have differential impacts for people in different places. Even where responsibility and equity negotiations have taken place they have tended to occur at the nation state scale through global institutions and events. However, justice implications of climate change are much more socially and geographically variegated than this would suggest. This paper will examine the arena of beyond-national climate justice issues and actions specifically highlighting the range of beyond-national innovations that seek just transitions to low carbon futures. It will examine the regulatory conditions for supporting such initiatives and relate these findings to the current Irish rhetorical commitment to a green economy.Climate, justice, Ireland, NGOs

A Generalisable Bottom-up Methodology for Deriving a Residential Stock Model From Large Empirical Databases

Specifying representative reference buildings as a prerequisite for calculating cost-optimal energy performance requirements for buildings and building elements. Appropriate characterisation is prerequisite data for an overall national building energy consumption model to produce valid outcomes. Energy Performance Certificates (EPCs) are issued in the EU, for dwellings whenever they are constructed, sold or leased. Where acquiring data for an EPC would be prohibitively costly, nationally applicable default-values are employed for the building envelope thermal transmittance coefficients. Significant levels of retrofits led to the default-values used now being higher than is typical in reality, leading to characterisations of reference dwellings based on these defaults lacking validity. A methodology is presented for the derivation of simplified default-free inputs to a bottom-up residential cost-optimality energy consumption model from an EPC dataset. 35 reference dwellings (RD’s) are employed to appropriately characterise 406,918 dwellings averaging one RD per 11,626 dwellings. The strong association of dwelling age and energy efficiency has been found to be diminishing as retrofits have been carried out. A view that the majority of dwellings in Ireland are thermally sub-standard may no longer be true

Survey of energy audits and energy management systems in the Member States

The present study has been conducted by the Joint Research Centre on behalf of DG ENER with the purpose to understand the status of programmes promoting energy audits and energy management systems in the Member States of the European Union. The objectives of this report are to assess the extent to which the requirements of Article 8 of the Energy Efficiency Directive (EED) are already met and to understand the level of additional effort needed by the Member States to meet their obligations under the named article. Another objective of this report is to identify eventual barriers and make recommendations on how the goals of Article 8 can be fulfilled. This report was put together by sending a survey to different contact points in the Member States, such as members of energy agencies, governmental bodies responsible for the implementation and regulation of energy policy, energy efficiency experts, and members of the academia. There were also performed interviews with national experts and representatives of standardization bodies that gave their input in the matters of the implementation of Article 8 throughout the European Union. It was possible to gather contributions from contact points from the great majority of the Member States except from the cases of Belgium, Ireland and Luxembourg. For the cases of Belgium and Ireland, since these countries have been carrying, for many years now, consolidated programmes on the subject of energy efficiency and energy audits it was still possible to gather sufficient information to perform an evaluation on the status of their general policies. Also, during the workshop organized by the JRC on behalf of DG ENER on the implementation of Article 8 in the month of March of 2014, it was possible to contact with representatives from Member States, from the industry sector and from certification bodies that shared their view on the implementation of this article within their areas of action and expertise.JRC.F.7-Renewables and Energy Efficienc

Introducing the Default Effect: Reducing the Gap Between Theoretical Prediction and Actual Energy Consumed by Dwellings Through Characterising Data More Representative of National Dwellings Stocks

Dwelling stock models that include the renovation status of the dwelling stock enable energy analyses of the stock. Using Ireland’s predominant single‐family housing typology as a case study dwelling, the overarching objective of this research is to define a transparent generalisable methodology to create a stock model from a large empirical Energy Performance Certification (EPC) database, employing reference dwellings (RDs) defined using a ‘bottom‐up’ approach. RDs are to be reported in compliance with Regulation No. (EU) 244/2012. The generalisable methodology defined allows for the development of stock models from EPC datasets. Where obtaining the required data would be prohibitively costly, nationally applicable default‐values are used in EPC assessments. To ensure that dwellings are not assigned wrongly‐higher energy ratings, worst‐case base‐thermal‐default U‐values are used which, in the absence of empirical data, are determined by building type and prevailing building codes at time of construction date. A structural ‘default effect’ error in the EPC data was identified. It was found that 58 % of walls and 67 % of roofs had significant retrofits of insulation, leading to; (i) less association between a dwelling’s age and its energy efficiency, and (ii) currently used default U‐values being outmoded. Outmoded default U‐values; (i) decrease the credibility of both the EPC and its associated advisory report so inhibiting investment in energy efficiency, and (ii) lead to overestimation of potential residential energy savings, estimated at 22 % in post‐thermal regulation dwellings and 70 % in pre‐thermal regulation dwellings. To address this, generalisable methodologies have been developed to derive from an EPC dataset; i) statistically relevant contemporaneous default U‐values, ii) a dwelling stock model derived from largely‐default‐free synthetically averaged RDs, iii) the renovation status of a dwelling stock, iv) a stochastically based energy‐improvement payback calculation methodology, to be used where pessimistic default U‐values are necessarily employed. Use of the statistically‐derived empirical data created will increase the validity and hence credibility of residential stock energy consumption models, the EPC, and its associated advisory report; enabling more valid quantification of the; a) energy saving potential within Ireland’s predominant housing typology, b) effect of default U‐value use on the prebound effect, and c) overall national building energy consumption

Measuring GHG Emissions Across the Agri‐Food Sector Value Chain: The Development of a Bioeconomy Input‐Output Model

Increasing food production to meet rising global demand while minimising negative environmental impacts such as agricultural greenhouse gas (GHG) emissions is one of the greatest challenges facing the agri‐food sector. Sustainable food production relates not only to primary production, but also has wider value chain implications. Aninput‐output (IO) model is a modelling framework which contains information on the flow of goods and services across a value chain at a regional or national economy level. This paper provides a detailed description of the development of a Bioeconomy IO (BIO) model which is disaggregated across the subs‐sectors of the agri‐food valuechain and environmentally extended (EE) to examine environmental outputs, including GHG emissions, We focus on Ireland, where emissions from agriculture comprise 33% of national GHG emissions and where there has been a major expansion and transformation in agriculture supported by national and EU policy. In a substantial Annex to this paper, we describe the modelling assumptions made in developing the BIO model. Breaking up the value chain into components, we find that most value is generated at the processing stage of the value chain, with greaterprocessing value in more sophisticated value chains such as dairy processing. On the other hand, emissions are in general highest in primary production, albeit emissions from purchased animal feed are higher for poultry than for other value chains, given the lower animal based emissions from poultry than from cows or sheep. The level ofdisaggregation also shows that the sub‐sectors are themselves discrete value chains. The analysis highlights that emissions per unit of output are much higher for beef and sheep meat value chains than for pig and poultry. The analysis facilitated by the BIO model also allows for the mapping of emissions along the agri‐food value chain using the adapted IO EE approach. Such analysis is valuable in identifying emissions ‘hot‐spots’ along the value chains and analysing potential avenues for emission efficiencies