2015 Quality report. Economy-wide Material Flow Accounts (EW-MFA) Data transmission under Regulation (EU) 691/2011

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1 Economy-wide Material Flow Accounts (EW-MFA) Data transmission under Regulation (EU) 691/ Quality report Country: Ireland. Date: October 20 th 2017 Contact person: name Reamonn McKeever Please fill in this template and return it to Eurostat by 31 December 2017 together with the completed 2017 EW-MFA questionnaire. Both files have to be sent via edamis. Please ensure that the following information is entered in edamis Domain name: ENVPFLAC Data set name: ENVPFLAC_MFA_A End of the (mandatory) reference period: 2015 Please write in English, limit the length of your report and focus on changes compared to last year's quality report. 1

2 Regulation (EU) No 691/2011 in Article 7 requires that Member States shall provide the Commission with a report on the quality of the data transmitted. The quality criteria as referred to in Article 12(1) of Regulation (EC) No 223/2009 shall be applied. Those quality criteria are: relevance, accuracy, timeliness, punctuality, accessibility and clarity, comparability, and coherence. 1 Relevance Relevance refers to the degree to which statistics meet current and potential needs of users. Economy-wide material flow accounts (EW-MFA) provide a rich empirical database for numerous purposes. At international level the European Commission uses EW-MFA and derived indicators for developing and monitoring policies in domains such as circular economy, sustainable development, resource efficiency, sustainable consumption and production, and greening of other policy areas. The derived EW-MFA indicator domestic material consumption (DMC) is a headline indicator for the Europe 2020 resource efficiency initiative. 1.a) Please add references to the use and relevance of EW-MFA at national level (e.g. main users, national indicator sets, quantitative policy targets etc.)? MFA statistics are of relevance to Government, academics and media organisations in policy formulation and evaluation in domains such as the circular economy, sustainable development, resource efficiency and sustainable consumption and production. 2 Accuracy Accuracy' refers to the closeness of estimates to the unknown true values. EW-MFA constitute accounts and as such they are compiled from a variety of data sources. The majority of EW-MFA characteristics are based on statistical data sources (see below section 6 and Annex 1). Some characteristics even need to be estimated because adequate statistical data sources do not exist (see below section 6 and Annex 2). Please assess the accuracy of the reported data. 2.a) Are there general deficiencies in the data? Some data are only available as rough estimates (e.g. crushed Rock in Table A3.6.) Other data, such as Straw in Table , Other Crop Residues in Table , Input Gases in Table G.1 and Output Gases in Table G2 are based on general European conversion factors which may not accurately reflect national circumstances in Ireland. 2

3 2.b) For which characteristic would you assume that data quality is lower? Fodder Crops (Table A ) Grazed Biomass (Table A ) Crushed Rock (Table A.3.6). Sand and Gravel (Table A.3.8) 2.c) If applicable, what steps do you plan to remedy the deficiencies? I apply nation-specific conversion factors rather than European wide ones where possible, impute for missing data, check via the examination of proxy variables and relevant reports, and examine the plausibility of outliers. 3 Timeliness Timeliness refers to the period between the availability of the information and the event or phenomenon it describes. 3.a) By when was the data actually available, nationally? October Punctuality Punctuality refers to the delay between the date of the release of the data and the target date (the date by which the data should have been delivered. According to Regulation (EU) No. 691/2011 economy-wide material flow accounts shall be transmitted within 24 months of the end of the reference year and in each subsequent data transmission to the Commission, Member States shall provide annual data for the years n-4, n-3, n-2, n-1 and n, where n is the reference year. 3

4 4.a) Ireland transmitted the data to Eurostat on 31st October b) Data for the following years are reported in the various tables: Table A: Domestic extraction Table B: Imports Total trade Table C: Imports Extra-EU trade Table D: Exports Total trade Table E: Exports Extra-EU trade Accessibility and clarity Accessibility and clarity refer to the conditions and modalities by which users can obtain, use and interpret data. Data on EW-MFA and derived indicators, including EU totals, will be made available on Eurostat s web site as soon as possible after validation. 5.a) Do you publish this data nationally? Yes, please specify where: Yes. We expect to publish this data nationally on October 25 th 2017 in an electronic release on the Central Statistics Office Website No, please specify why not: Comparability Comparability refers to differences in applied statistical concepts, methods, tools and procedures that may impact comparisons between geographical areas or over time. Here the focus lies on any assessment of the comparability of data across countries and over time. The comparability is mainly affected by the data sources used and by the compilation/estimation methods applied. Switching the data sources and/or estimation methods may cause breaks in time series. 6.a) Please specify the data sources for Table A 'Domestic extraction' by different material categories? 4

5 See Annex 1 6.b) Please explain briefly the estimation approaches for those characteristics in Table A 'Domestic extraction' which cannot be derived directly from statistical sources (e.g. sand and gravel, grazed biomass)? See Annex 2 6.c) Please specify the data sources for trade (Tables B to E)? National foreign trade statistics and/or databases (please specify): National Trade figures are used to compile Tables B to E. Trade figures are compiled using two different sources: Intrastat and Extrastat. Under the Intrastat Survey traders above certain thresholds make detailed monthly returns to the Customs Service concerning imports from and exports to other EU states. In the Extrastat system data for trade with Non-EU states are compiled from the Single Administrative Documents supplied by importers and exporters to the Customs Authorities National accounts and/or balance of payments (please specify): Sectoral statistics, such as e.g. energy, agriculture etc. (please specify): Other (please specify): d) Do you employ Eurostat s correspondence table, provided in Annex 3 of the questionnaire, to assign traded goods to material categories? Yes, we employ Annex 3 to assign traded goods to material categories No, we don't employ Annex 3, please specify why not: Yes, we employ Annex 4 of the EW MFA Questionnaire to assign traded goods to material categories e) Do you use conversion factors to convert traded goods into tonnes (e.g. from pieces, cubic metres etc.)? No, it is not necessary to convert into tonnes. Yes, please specify (e.g. did you use factors from Eurostat's EW-MFA compilation guide?): Yes. Conversion factors from Annex 6 of the EW MFA Questionnaire were used if there are no net mass or usable supplementary units in the Trade data. 5

6 6.f) Fuel trade, residence adjustment: Please describe how do you make adjustments to the trade characteristics B-E for fuel purchases by residents abroad? This relates e.g.to international air and maritime transport as well as to road vehicle journeys abroad. please insert description No, we don't undertake residence adjustments for the following reasons (please specify): not: No. We did not apply an adjustment to fuel trade to reflect the Residence Principle. This was not a high priority as it is a memorandum item only. 6.g) Are there any discontinuities in time series resulting from changes in methodology, data sources etc.? If data was revised compared to a previous data transmission to Eurostat what was the size of the revisions and what principally caused them? The methods used to calculate data for A Fodder Crops have been revised since last year. The crops assigned to this category have been amended based on Eurostat advice. Grass Silage figures have been calculated by assuming two cuts, new yield factors per hectare and an estimation for losses in the harvesting process. Hay figures have also been revised using a new yield factor and an estimate for losses during harvesting. Eurostat recommended a modification of Table G.1.1 Oxygen for Combustion. The figures now include a new Step 3 referring to the Intrinsic Oxygen Content of Energy Carriers. Last year natural gas figures in Table G (water vapour from the oxidised hydrogen content of fuels) incorrectly referred to indigenous production only rather than primary energy supply (indigenous production + imports- exports marine bunkers + stock change). 6.h) Did you encounter significant problems in adapting basic statistics to the concepts of the accounts? Basic statistical data is missing (please specify): Crushed Rock figures (Table A.3.6) and Waste to Landfill figures (Table F.2) are not available before Basic data sources are insufficient, e.g. PRDCOM for A.3.8 Sand and gravel (please specify): Aggregates (Crushed Rock and Sand and Gravel) are one of the most significant contributors to total Domestic Extraction, but these figures are not available as reliable and high quality statistics. In the 2015 MFA results Crushed Rock figures were included under category A.3.6 and Sand and Gravel under A

7 The 2015 figures were based on rough estimates taken from the British Geological Survey s European Mineral Statistics publications; national PRODCOM figures; and supplementary data taken from the Road Freight Transport Survey on the volume of goods transported to road works and building sites. Mapping the classification of basic data source to the EW-MFA classification (please specify): Other problems (please specify): In 2015 we did not include new balancing items in Table G,which were added by Eurostat to its latest Questionnaire, because of methodological concerns. These new items referred to Table G.1.4 (Water Requirements for the Domestic Production of Exported Beverages) and to Table G.2.3 (Excorporated Water from Biomass Products). 7 Coherence Coherence refers to the adequacy of the data to be reliably combined in different ways and for various uses. The accounting framework of EW-MFA is consistent with the System of Environmental-Economic Accounting (SEEA-CF) adopted by the United Nations Statistical Commission as a world-level statistical standard in March EW-MFA are consistent with the European system of accounts (ESA) and hence suited to be combined with ESA aggregates. 7.a) Are there any consistency issues you would like to mention here? The most significant quality problems with data are associated with the category Non-Metallic Minerals, in particular, with A.3.6 Limestone and Gypsum (including Crushed Rock) and A.3.8 Sand and Gravel. There is also a potential consistency problem with the figures for Fodder crops (A ). The methodology used to calculate Fodder Crop statistics was revised this year. New national conversion and yield factors were used to transform the area of fodder crops under harvest into dry weight production volumes. For Grazed Biomass, the data generated by the Supply Side Approach is quite different from the figures produced by the Demand Side Approach. Finally trade figures in Tables B-E are calculated on the basis of cross-border movements of goods, rather than the residence principle applied in National Accounts. 7

8 8 Other assessments and quality reports: 8.a) Do you have national descriptions of the methodology you use? If so please provide them. No 8.b) Do you have national quality reports already available? If so please provide them. No 9 Voluntary MFA in RME data collection: 9.a) In case you have reported data in Table I, have you used Eurostat's country RME tool to compile the MFA in RME? No RME data for Eurostat Table I is available so far for Ireland. Yes. Please specify if you have made country specific alterations: No. If No, please briefly state why you prefer your methodology: If No, do you have a description of the methodology you have used for compiling the MFA in RME? If so please provide it. 8

9 Annex 1: Sources of data for Table A 'Domestic extraction' by material categories Characteristics Table A Code label Please specify the exact data source (add URL or hyperlink if possible) 9 Is it a national data source? Data sources Cereals CSO Agriculture Division Yes No Roots, tuber CSO Agriculture Division Yes No Sugar crops CSO Agriculture Division Yes No Pulses CSO Agriculture Division Yes No Nuts CSO Agriculture Division Yes No Oil-bearing crops CSO Agriculture Division Yes No Vegetables CSO Agriculture Division Yes No Fruits CSO Agriculture Division Yes No Fibres CSO Agriculture Division Yes No Other crops n.e.c. CSO Agriculture Division: Department of Agriculture, Food and Marine and the Irish Christmas Tree Growers Association Yes No Straw CSO Agriculture Division Yes Yes Other crop residues CSO Agriculture Division Yes Yes Fodder crops CSO Agriculture Division Yes No Grazed biomass CSO Agriculture Division Yes No Timber (roundwood) External Consultant Yes No Wood fuel External Consultant Yes No Wild fish catch Sea Fisheries Protection Agency Yes No Other aquatic United Nations Food and Agriculture Organisation No Yes Hunting and gathering Not Applicable 2.1 Iron Not Applicable Copper Not Applicable Nickel Not Applicable Lead The Department of Communications, Climate Action and Environment Yes No Is it an international data source? Please explain which positions in your national data source classification were grouped and assigned to the respective MF category (in particular for biomass and non-metallic minerals)

10 Characteristics Table A Code label Please specify the exact data source (add URL or hyperlink if possible) Is it a national data source? Data sources Zinc The Department of Communications, Climate Action and Environment Yes No Tin Not Applicable Gold, silver, platinum, other precious metals The Department of Communications, Climate Action and Environment Yes No Bauxite, aluminium Not Applicable Uranium, thorium Not Applicable Other non-ferrous n.e.c Not Applicable 3.1 Marble, granite, sandstone, etc. CSO PRODCOM Statistics Yes No 3.2 Chalk and dolomite CSO PRODCOM Statistics Yes No 3.3 Slate CSO PRODCOM Statistics Yes No 3.4 Chemical and fertiliser minerals CSO PRODCOM Statistics Yes No 3.5 Salt CSO PRODCOM Statistics Yes No 3.6 Limestone and gypsum Limestone figures are taken from CSO PRODCOM Statistics. Gypsum figures are taken from the British Geological Survey s European Mineral Statistics publications. Crushed Rock figures are compiled using PRODCOM, the BGS and Road Freight Survey Transport data concerning the delivery of goods to road works and building sites Yes Yes 3.7 Clay and kaolin CSO PRODCOM Statistics Yes Yes 3.8 Sand and gravel CSO PRODCOM Statistics supplemented by the BGS and Road Freight Survey Transportfigures for the volume of goods delivered to road works and building sites. Yes No 3.9 Other non-metallic n.e.c CSO PRODCOM Statistics Yes Yes 3.10 Excavated earth used (optional) Not Applicable Lignite Not Applicable Hard coal Not Applicable Is it an international data source? Please explain which positions in your national data source classification were grouped and assigned to the respective MF category (in particular for biomass and non-metallic minerals) 10

11 Characteristics Table A Code label Please specify the exact data source (add URL or hyperlink if possible) Is it a national data source? Data sources Oil shale, tar sands Not Applicable Peat The Sustainable Energy Authority of Ireland Yes No Crude oil, NGL Not Applicable Natural gas The Sustainable Energy Authority of Ireland Yes No Is it an international data source? Please explain which positions in your national data source classification were grouped and assigned to the respective MF category (in particular for biomass and non-metallic minerals) 11

12 Annex 2: Estimation methods for data of Table A 'Domestic Extraction' for which no statistical data sources exist Characteristics Table A Code Label Cereals Roots, tuber Sugar crops Pulses Nuts Oil-bearing crops Vegetables Fruits Fibres Other crops n.e.c. Do you use the Eurostat estimation approach recommended in the EW-MFA compilation guide? Straw Yes No Other crop residues Yes No Fodder crops No Yes Have you developed your own estimation approach? 12 Estimation methods Please explain briefly the estimation approach including possible data sources for auxiliary data? Cereal production figures are supplied by CSO Agriculture Division. These are then transformed into Straw figures by the application of Eurostat Harvest factors and Recovery Rates Sugar Beet, Roots and Tubers, Fodder Beet and Oilseed Rape figures are supplied by CSO Agriculture Division. These are then transformed into Used Crop Residue figures by the application of Eurostat Harvest factors and Recovery Rates Fodder crop figures are supplied by CSO Agriculture Division and are then transformed using national by conversion factors to convert area size figures into dry weight volumes. Please specify coefficients used (if not Eurostat coefficients)?

13 Characteristics Table A Code Label Do you use the Eurostat estimation approach recommended in the EW-MFA compilation guide? Grazed biomass No Yes Timber (roundwood) Wood fuel Wild fish catch Other aquatic Hunting and gathering 2.1 Iron Copper Nickel Lead Zinc Tin Gold, silver, platinum, other precious metals Bauxite, aluminium Uranium, thorium Other non-ferrous n.e.c 3.1 Marble, granite, sandstone, etc. 3.2 Chalk and dolomite 3.3 Slate 3.4 Chemical and fertiliser minerals 3.5 Salt Have you developed your own estimation approach? 13 Estimation methods Please explain briefly the estimation approach including possible data sources for auxiliary data? Eurostat s Supply Side Approach is used. Silage. Hay, Pasture and Rough Grazing data are supplied by CSO Agriculture Division and then are transformed using national yield factors to produce Grazed Biomass figures. Please specify coefficients used (if not Eurostat coefficients)?

14 Characteristics Table A Code Label 3.6 Limestone and gypsum 3.7 Clay and kaolin 3.8 Sand and gravel 3.9 Other non-metallic n.e.c 3.10 Excavated earth used (optional) Lignite Hard coal Oil shale, tar sands Peat Crude oil, NGL Natural gas Do you use the Eurostat estimation approach recommended in the EW-MFA compilation guide? Have you developed your own estimation approach? Estimation methods Please explain briefly the estimation approach including possible data sources for auxiliary data? Please specify coefficients used (if not Eurostat coefficients)? 14