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Please go to the CIRCA environmental meetings and download the documents in the MFA workshop folder

2. Introduction to MFA Workshop
Eurostat MFA Workshop
2-3 September 2009
Ampere, Bech, Luxembourg
Julie L. Hass and Cristina Popescu
Eurostat

3. Who we are… Eurostat: Julie L. Hass (END Norway)
Cristina Popescu (END Romania)
For 2009
Wuppertal Institute: Helmut Schultz
IFF – Austria: (1) Fridolin Krausmann (2) Anke Schaffartzik

4. Agenda Day 2 Day 1 Table A: Domestic Extraction – Petroleum resources
Concluding remarks regarding Domestic Extraction
Tables B, C, D, and E: Imports and exports
Reporting via eDAMIS
Indicators using DE, import and export data and the SDI indicators
EW-MFA output side: Table F and G
Day 1
Introduction to EW-MFA
“Tour de Table”
Table A: Domestic Extraction – Biomass
Evaluating country data vs. data compiled from international data sources
Check your own data!
Table A: Domestic Extraction – Metal ores and Non-metallic minerals

5. Dinner this evening at Namaste Restaurant
Please indicate if you will be attending! Don’t use the coupon – you tear off the portion of the map on the back that you need! You will not be able to find the restaurant…
Sign up on sheet being passed around!
When are participants needing to leave tomorrow to catch planes/trains? 15:00? 16:00?

6. Economy-Wide Material Flow Accounts Input side: Domestic Extraction (Table A), Imports and Exports (Tables B, C, D, E)

7. Improving data…where to focus our attention?
Mouse / Elephant (focus should be on the elephant!)

8. SDI: Domestic Material Consumption: Mouse? Elephant? (2004 data)
1000 tonnes

9. Domestic Extraction: Mouse? Elephant?
(2004 data)

10. Biomass: Mouse? Elephant?
(2004 data)

11. Non-metallic Minerals: Mouse? Elephant?
(2004 data)

12. Eurostat concluded that countries needed help on certain materials… Developed the pink calculation tools!
Get the best data for the big pieces of the picture!
Problem with the big pieces of the picture: Many are ESTIMATES and NOT statistics that can be easily identified.
Estimation methodology makes a BIG difference.
Calculation tools help you to know what information to find and what to do with it! – but do NOT change the formulas in the green shaded areas!

13. Why were there changes to the Questionnaire from 2007 to 2009?
Tried to keep changes to minimum
Try to get system boundaries to be closer to national accounts
Grouped materials typically found in “statistics” into categories Grouped materials that need to be estimated into other categories. Why?
Estimation methodology needed to have different aggregation of categories – introduced a 4-digit level
Anticipating the required “quality reports” in potential legal base
Allows for more detailed publication of data – currently only 3 materials – want more! Plan publication at 2-digit level.
Look at Annex 0 of questionnaire for closer explanation

15. Mistake in Table A – Brown coal and Hard coal labelled incorrectly
Adjusting for residence principle for fuel purchased by resident units outside of the national territory – add to imports
Adjusting for residence principle for fuel purchased by non-resident units inside of the national territory – add to exports

16. Questions? …before we move on to the “Tour de Table”

17. “Tour de Table”
A) Tell about MFA in your country - is this something new or established? Priority or not? Etc.
B) If you have tried to fill out the tables - where do you have the most trouble? Which tables/materials do you spend the most time working on?
C) What are your expectations/wishes/goals for these 2 days?

18. We will now go through each section of the questionnaire together as a large group. Then we will break up into 3 smaller groups with our MFA experts leading each group – here you can ask direct questions about your country’s data, methodology, etc.

19. EW-MFA Table A: Domestic Extraction Biomass

20. Biomass: Mouse? Elephant? Data sources: statistics and estimates

21. A.1 Biomass – based mostly on statistics
A.1.1 Primary Crops
These are statistics! Simply go to your agriculture statistics and fill this in. Questions regarding where certain crops should go… check the Imports/exports annex and use this as a guide. Example: Flowers?
A.1.4 Fish catch and other aquatic plants/animals
These are statistics!
Fish farming is NOT included – only “fishing” Technically only the fish captured by resident units should be included – also that from resident vessels operating abroad. Spanish fishing vessels landing fish in Norway – should be Spanish flows but this is not easy.

22. A.1 Biomass – typically based on statistics and some calculations
Number and type of animal =
Mass
(tonnes)
Weight (mass) per type of animal
A.1.5 Hunting and gathering
These are statistics! But typically they are given in number of animals. Biggest challenge is the conversion from number to tonnes. Need to obtain conversion tables based on average weights.

23. Relationship between mass, density and volume: Needed to convert timber statistics to mass units
(tonnes) =
Density
(tonnes/m3)
Volume
(m3)
A.1.3 Wood
These are statistics! But typically they are given in cubic meters – a measure of volume NOT mass.
Need to convert from cubic meters (volume) to mass (tonnes)… Need density: tonnes per volume
Need to also identify what the timber statistics include… excludes branches and bark
Volume
(m3) =
Mass
(tonnes)
Density
(tonnes/m3)

24. M.1.3 Memorandum item: Net increment of timber stock
To bring the system boundaries of EW-MFA closer to the system boundaries of the national accounts…
Cultivated forests are inside the national accounts production boundary – therefore the growth of these trees is also to be included in the EW-MFA.
So far we do not have an estimation methodology for this – but some countries do have these estimates so they should be included here if data exist.

25. These are reasonably straight forward data collection exercises from existing statistics. Any questions so far?
Next are the biomass materials that need to be estimated: A.1.2 Crop residues (used), fodder crops and grazed biomass

26. A.1.2 Crop residues (used), fodder crops and grazed biomass
A Straw
A Other crop residues (sugar and fodder beet leaves, other)
A Fodder crops and grazed biomass
A Fodder crops (including biomass harvest from grassland)
A Grazed biomass
Typically Crop residues (used) is found in agriculture statistics. Fodder crops and grazed biomass need to be estimated. If no data are available and a “demand side” estimate needs to be made then the estimate is for the whole aggregate A What about adjusting for moisture content (mc)?

27. Please go to the pink calculation tool: “Crop residues” A. 1. 2
Please go to the pink calculation tool: “Crop residues” A Crop residues (used)
A Straw
A Other crop residues (sugar and fodder beet leaves, other)
A Fodder crops (including biomass harvest from grassland)
A Grazed biomass
Please go to the pink calculation tool: “Grazed biomass” - supply and demand A Fodder crops and grazed biomass

28. Let’s stop here and break into 3 smaller groups with 5 countries in each group – with our consultants leading each group – and have some additional time to ask questions about your own biomass data. Eurostat will “float” joining each of the groups in turn.

29. Checking if the figures are “right”

30. How do you know if you are “right”?
Compare with other countries that are similar to yours – are the patterns (mouse/elephant) similar? But do NOT assume that they are right – use own judgement and discuss with other countries/Eurostat/our consultants how they develop their figures.
Compare with the estimates in reports by MFA experts that have created figures for your country from international databases
Compare your data with data reported or estimated for your country last time (2007 data collection exercise)

31. Evaluating country data vs
Evaluating country data vs. data compiled from international data sources
IFF / Wuppertal will give an overview of how they edited the data reported by countries in the 2007 data collection exercise and plans for 2009.

32. Table A: Domestic Extraction – Metal ores and Non-metallic minerals
IFF / Wuppertal
Eurostat: Cristina Popescu – calculation tools

33. Table A: Domestic extraction – Petroleum resources
Eurostat: Julie L. Hass

34. Petroleum resources – extraction statistics
A.4 Petroleum resources (Fossil energy carriers)
A Coal and other solid energy resources
A Brown coal NOTE ORDER! v1 was wrong!
A Hard coal NOTE ORDER!
A Oil sands and oil shale
A Peat Not “petroleum” but listed here
A Liquid and gaseous petroleum resources
A Crude oil and natural gas liquids
A Crude Oil
A Natural gas liquids
A Natural gas

35. UNITS! Oil Gas Condensate NGL (Natural Gas Liquids)
Sm3 oil equivalents
[mill Sm3]
[bill Sm3]
[mill]
2008
99.231
4.18
16.021
2007
89.662
3.474
16.577
2006
87.613
7.989
16.672
2005
84.963
8.422
15.735
2004
78.333
9.142
13.581
2003
73.124
11.06
12.878
2002
65.501
8.02
11.798
2001
53.895
6.561
10.924
2000
49.748
6.277
7.225
NGL = butane + ethane + isobutane + propane + LPG + gasoline + NGL mix. Condensate = Condensate

36. Biggest challenge for oil and natural gas is conversion from units used in extraction statistics to mass units needed in EW-MFA
Oil is different from different parts of the world – so different density / conversion factors are needed.
“condensate” and “natural gas liquids” are sometimes added to “oil” and sometimes not – so to be clear a new category was added.
Typically extraction statistics for petroleum products are provided in energy units, “Sm3 oil equivalents”
Challenge is to covert to mass! At this time the instructions are rather sketchy on this point – needs improvement – need to consider the methodology and the categories (relative to changes in energy statistics).

37. Questions about “Petroleum Resources”?

38. Before reporting… check your data!

39. “Tool” to check 2007 reporting/estimates vs. 2009
We have made an Excel file where you can cut and paste the data from the previous reporting and from the new reporting and check to see if you have some major differences….
Let’s look at the 2009 data from Ireland… - Excel file…

40. Major mistakes can be identified this way…
Sub-totals are not filled in
Should report in 1000 tonnes – but data reported in tonnes = decimal error
Have corrected year 2000 and then we see some major differences – in the yellow areas. These we would tend to question – and would like to have explanations.

41. Exercise: Take the “revision” file, cut and paste your 2007 reported data (sent to you last week) into the sheet for 2007, cut and paste the data you have developed so far from 2009 data… what do you find??

42. Economy-Wide Material Flow Accounts Input side: Imports and Exports (Tables B, C, D, E)

43. SDI: Domestic Material Consumption: Mouse? Elephant? (2004 data)
1000 tonnes

44. What has changed for the 2009 reporting?
All years EU-27
Total imports and exports (Tables B and D)
Extra EU-27 trade (Tables C and E)
In 2007 data collection requested intra and extra EU trade and this was seldom reported. Definition of “EU” changed over the years so not a consistent time series for evaluating changes – since it was mostly due to membership of the EU and not changes in material use.

45. Converting trade statistics into EW-MFA
Need a conversion table… SITC-HS-CN: Correspondence of items in Questionnaire Tables B to E with SITC rev 4, HS 2007, CN 2007 Codes
How do I get from one system to the other?

46. Conversion table…
In 2007 and 2009v1 a conversion table for 4-digits was provided with the questionnaire – Problem: not detailed enough, some codes missing, some codes listed twice, no codes for waste.
In many countries this is not detailed enough resulting in each country making their own detailed conversion tables. Consequences: lots of time used by each country, different grouping of products.
Eurostat solution: One table showing 8-digit CN 2007, 6-digit HS 2007, 3-5-digit SITC rev4 conversion table

47. Trade statistics to EW-MFA categories
See new annex sent with Rev2 of the questionnaire: “2009 MFA Annex: SITC-HS-CN: Correspondence of items in Questionnaire Tables B to E with SITC rev 4, HS 2007, CN 2007 Codes”
Almost 10,000 codes! Thank you Cristina!
Let’s look at the table!

48. But how do I use this? What do I do now? Work smarter, not harder!
Mark Davis from Statistics Ireland is going to show what he has done to go from trade statistics database to filling in the tables.
SAS programs as an example…
EW-MFA Tables B, C, D, E
Trade data
Conversion Table (Eurostat)

49. Assumptions about the trade statistics…
Physical trade statistics are good
Complete picture is given – Nothing is left out
Are these valid assumptions about the trade statistics?
Perhaps not…
“Cut off” – more and more is being left out
Monetary trade statistics have higher quality than physical
Products with low value have low quality – such as “waste”
Not according to “residence principle”

50. What is not in the trade statistics that we need to include?
To adjust the system boundaries of EW-MFA to the residence principle… need (especially) the fuel purchases of international transport.
Need to add fuel purchases of resident units operating outside of the national territory, subtract the fuel purchases of non-resident units purchasing fuel on the national territory.
Have requested this information according to: Land, water, air transport

51. Questions about the trade statistics…

52. Reporting data to Eurostat via eDAMIS
Cristina Popescu – Eurostat

53. Please provide information regarding the person who will be submitting data using eDAMIS – we need to give them access to the domain: ENVPFLAC (Domain name ENVPFLAC = ENVironmental Physical FLow Accounts) This domain will also be used for reporting Air emissions accounts next year.

54. Indicators using the input side of economy-wide material flow accounts
How are these data going to be used?

55. From 2007 SDI report

57. DMC: Level 1 and 2 Level 3 SDIs for Sustainable Consumption and Production
Used in monitoring resource productivity: GDP per DMC (Euro per kilo) The construction of this indicator assumes the same system boundaries for the numerator and the denominator… one major reason for getting these to correspond better!
Components of domestic material consumption (DE, Imports, Exports)  
Domestic material consumption by material (Biomass, Minerals, Fossil fuels)

58. Impact indicator?
“Rucksack” concept – that imports have “embedded” material flows. Imports shift the environmental consequences outside of the national borders.
EMC – using life cycle assessment information to bring the “embedded” emissions into the picture. Not feasible for the statistical system.
RME – Raw Material Equivalents – currently being evaluated. Need RME factors for each type of import – obtained from I-O, LCA.

59. Next steps to be evaluated by Task Force
How to go from materials to distribute the materials by industry… Domestic Extraction is fairly easy – agriculture, fishing, forestry, mining and extraction.
Challenge is how to distribute imports and exports… What is the starting point for doing this? What information and methodology is needed to distribute the data? Does it make sense that the statistical system do this?
Are import and export data by material needed for anything besides calculating “DMC”?
Should Eurostat only collect Table A or should we also require tables B-D since we have Comext. Who does the trade data work – countries or Eurostat/consultants?

60. EW-MFA: Output side Table F and G
IFF/Wuppertal