Data Mining in 27 European Countries Austria, Denmark, France, Germany (WP 3) Copenhagen, 25 November 2009

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1 Data Mining in 27 European Countries Austria, Denmark, France, Germany (WP 3) Copenhagen, 25 November 2009

2 WP 3 > Objectives > Main Working Steps > Deliverables > Data Sources > Data Processing > Problems and Results

3 WP 3: Objectives Validated data for specific countries: Austria Denmark France Germany

4 WP 3: Context in FORWAST Input from WP1 WP2, esp.: - Definition of the System (D2-2) - Data Collection Guidelines (D2-4) WP3 - Data Collection for A, DK, F, D - Data Processing - Data Validation -etc. WP4 Parallel Work for EU27 WP6 - Future Waste Streams - Scenarios from WP5

(D2-4) WP3 - Data Collection for A, DK, F, D - Data Processing -

5 WP 3: Main Working Steps > Definition of operational data structure in relation with WP1 and WP2 > Collection of statistics and additional data > Review and verification of acquired data > Identification of missing data > Processing / substitution of missing data > Plausibility and Data Reconciliation > Identification of potentials and difficulties for completing data collection

Identification of missing data > Processing / substitution of missing data > Plausibility and

6 WP 3: Main Working Steps >Balancing the Matrices

7 WP 3: Deliverables > D3-1: report chapter: data processing and validation > D3-2: Databases of material flows and stocks for the four countries > D3-3: Report chapter: indirect procedures for estimation of transfer coefficients > D3-4: Report chapter: potentials and difficulties for completing data collection

Report chapter: indirect procedures for estimation of transfer coefficients >

8 WP 3: Data Sources European Level > EUROSTAT, 2008a (Monetary Supply and Use Matrix) 59 x 59 categories (NACE 01 95) Available for Austria, Denmark, France, Germany Primary source of monetary supply and use tables (MSUT) Reference year: 2003

95) Available for Austria, Denmark, France, Germany Primary

9 WP 3: Data Sources European Level > EUROSTAT, 2008a Monetary Values (Mio. EUR) Supply-tables in basic prices => Transformation in purchasers prices Use-tables in purchasers prices => transformation into basic prices Imports/Exports implemented Disaggregation from 59 to 117 activities (manually)

Use-tables in purchasers prices => transformation into basic prices

10 WP 3: Data Sources European Level > PRODCOM (PRODuction COMmunautaire) - EUROSTAT, 2008b Detailed data of supplied commodities NACE based mining, quarrying and manufacturing

11 WP 3: Data Sources European Level > Physical Environmental Accounts e.g. NAMEA Air survey Material Use Physical Input-Output Tables others

12 WP 3: other Global data Sources (excerpt) UNDATA UNFCCC UNCTAD British Geological Survey (BGS) Euromines EPER EIONET FAOSTAT

13 additional data sources Sectoral data (e.g. iron industry, paper industry, energy economics etc.) => European + national level National data (e.g. macroeconomic accounting, environmental accounting, air pollution registers, national statistics etc.) Detailed description of data sources for each country in D3-1.

14 Data Processing Matrix Expander Disaggregation: 57 x 57 => 117 x 117

15 Data Processing Matrix Master MSUT

16 Data Processing Matrix Master Price-Matrix Material Composition

17 Data Processing Emissions Machine

18 Data Processing Emissions Machine

19 Data Processing Matrix Master Resources Emissions

20 Data Processing Matrix Master PSUT Residuals

21 Data Processing Matrix Master «yellow cells» e.g. negative waste «supply of residuals»

22 Data Processing Eliminating «yellow cells» 1. Physical balance adjustments/verifications: - Use - Supply - Import / export - resources and emissions - Disaggregations - D1-table (transfer coefficients) e.g. negative waste (supply of residuals) 2. Price adjustments 3. Verification of monetary data 4. Crosschecks 5. Estimations

23 Data Processing Examples D1, iron basic > 1 Mg iron ores => 0,7 Mg iron basics => imbalances > adjustment D1-Matrix concrete and water > incorporated water in cement => imbalance in Tdry > Solution: adjustment Water in Resource-Table (R)

24 Data Processing (main steps) Matrix Master > Check for plausibility > Elimination of «yellow cells» > Make tables consistent to the model > Procedures for eliminating errors and inconsistencies => Adjustment of data, mined from statistics

25 Problems > Conversion of monetary into physical values is sometimes problematic (insufficient level of price information) > Combination of data obtained from several sources and different statistics leads to inconsistencies > Differences in system boundaries, aggregation of activities and systematic methodologies influences statistical data. > Large number of manual adjustments necessary in order to fit to the FORWAST-model > How many adjustments can be tolerated?

26 Results > Balanced monetary + physical tables for Austria, Denmark, France and Germany > Not all SUT s are consistent to the model until now > Consistency can be reached by further adjustment of data > Problem: too much data manipulation? > Additional external data for verification of manipulation > Verifiing significance of statistical data

27 conclusions > Monetary balancing differs significant from physical balancing > Monetary balances follow rules of economic accounting > Mass balances follows chemical mass action law Harmonization of MSUT and PSUT need for investigation enough data for reconciliation time requirement

28 thank you

Data Mining in the EU-27 - Methodology

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