WIOD conference – Vienna, 26-28 May 2010 Frederik Neuwahl and Aurélien Genty Institute for...

WIOD conference – Vienna, 26-28 May 2010

Frederik Neuwahl and Aurélien Genty Institute for Prospective Technological Studies (IPTS), Seville, Spain

http://ipts.jrc.ec.europa.euKurt Kratena

Austrian Institute of Economic Research (WIFO), Vienna, Austriahttp://www.wifo.ac.at

Energy and Environmental indicatorsin the WIOD System of Satellite Accounts

Dataset version 1: Energy & Emissions to Air

2WIOD conference – Vienna, 26-28 May 2010

Outline

– Scope and definition of satellite accounts covered

– Available information and data reconciliation effort

– Construction of Energy and Air Emission Accounts: methodology

– Completion of vers. 1 dataset: discussion of results

– Modelling: bridging monetary to physical information


Energy-environment satellite accounts in WIOD

– Core indicators Energy use, 25 energy commodities including

• Oil and gas• Electricity and heat• Coal and coal derivatives• Refinery products• Renewables and waste

Air emissions• Global warming potential (CO2, N2O, CH4)• Acidification potential (SO2, NOX, NH3)• Tropospheric ozone formation potential (NOX, NMVOC, CO, CH4)

– Additional indicators Water consumption Land use Resource use


Target: Energy & emissions satellite accounts

– NAMEA concept: framework fully compliant with the accounting conventions of the SUT system. Allows integrated economy-environment analysis/modelling NAMEA-AIR: emissions to air by pollutant and by sector NAMEA-E: energy use by energy commodity and by sector, with a

range of coexisting concepts: net energy use, gross energy use, emission relevant energy use

– Different methodologies: energy first, inventory first

– Additionally: summary energy balances and energy supply


The starting blocks

– Energy information is widely available in two main forms: IEA extended energy balances: ~100 flows, ~60 energy

commodities. In TJ. Complemented by some (less rich) price information.

Use table of the national accounts: ~60 sectors, ~4 energy-related commodities. In $.

– In addition to this basic data situation Some countries already publish energy NAMEA Wider availability of air emission NAMEA (inventory first);

Eurostat provides either official NSI data or estimations for the whole range of EU countries.


The Energy NAMEA01 10 11 15 21 22 23 24 25 40 45 60 61 62

139 175 158 635 23 903 228 000 182 558 48 127 5 993 626 1 385 707 90 325 5 829 714 273 322 361 274 61 302 369 841 1 717 3 956 0 6 236 13 622 0 349 352 32 631 0 1 363 356 539 344 0 0 876 116 760 0 5 057 3 035 0 5 533 9 946 108 1 451 322 275 592 0 0

zusammen 103 335 2 456 740 52 926 8 270 7 353 5 535 389 836 393 11 480 96 791 241 885 298 538 59 622 369 840

Erdöl 0 0 0 0 0 0 4 568 702 0 0 0 0 0 0 0Ottokraft-

stoffe 8 104 45 40 1 592 465 669 147 454 1 278 550 708 18 352 7 156 79 1 135Dieselkraft-

stoffe 68 763 1 309 692 6 930 656 727 1 003 2 002 940 1 614 76 245 281 981 28 953 105 Flugtur- binen-

kraftstoff 0 0 0 0 0 0 158 0 0 0 0 0 0 368 600Heizöl leicht 25 822 811 7 31 420 3 338 5 939 54 980 32 756 9 019 23 560 17 252 35 0 0Heizöl schwer 0 30 0 9 506 2 839 0 147 670 168 665 878 34 209 0 0 26 319 0sonst.

Mineralöl-produkte 647 261 0 3 478 972 18 615 423 631 692 93 36 700 130 035 9 366 4 272 0

12 981 1 193 21 517 95 930 79 668 18 068 64 441 310 545 21 884 647 099 15 613 1 309 1 672 0 360 11 8 89 5 908 10 12 281 24 11 257 695 479 3 102 8 1

19 907 34 258 1 638 67 763 72 055 22 696 26 629 196 168 56 842 2 013 451 14 531 57 388 0 0Elektrischer Strom

Braunkohlen und

Mineralöle

GaseErneuerbare Energien

CPA 1)Insgesamt

Steinkohlen und

DE 2000. Source: DESTAT


Key task in the estimation of NAMEA-E

– Main issue: reconciling the classification mismatch between IEA balances and national accounts

– However, different approaches are possible: Enrich the use table with additional rows containing energy carrier

use in physical unit; uses partial price information, but without allowing an immediate link between the entries of rows 10, 11, 23 and 40 and the physical flows.

Full reconciliation between IEA balances and the monetary information of the use table. Requires the estimation of a full vector of energy prices by energy commodity, de facto is equivalent to the disaggregation of rows 10,11, 23 and 40 in a finer product classification, and to building the equivalent PIOT rows. Also, data inconsistencies would require changes either in the UT or in the EB


From energy balances to NAMEA-E: General issues of concordance to be addressed– Autoproduction of electricity– Assignment of road transport– Territorial vs. Residence principle; affects:

Marine transport Aviation Road transport Tourism statistics

– Military use– Extraterritorial organisations

– Splitting of non energy intensive sectors to target classification information in use table

}Stems from discordantconceptual definition of sector

} International bunkering

}Equivalent problem in National accounts


Alignment with official dataDeviation of results from officially available data: NAMEA-E

(DE, NL, AT, DK) Own estimation fully calibrated to official data at the

available level of sector, energy commodity and time label Extrapolation to target sector, energy commodity and time

series by deriving from own estimation growth indices and split shares

Deviation of results from officially available data: NAMEA-AIR (all EU countries) Emission coefficients scaled to replicate official data of

emissions by sector Or: statistical difference allowed (CO2: small range is

physically possible)


Results for energy :WIOD DESTAT diff % WIOD DESTAT diff %

secAtB 126387 144232 -12.37% sec50 58187 93653 -37.87%secC 156196 204329 -23.56% sec51 138072 132464 4.23%sec15t16 211963 231464 -8.43% sec52 184990 209532 -11.71%sec17t18 40952 49677 -17.56% secH 94677 91327 3.67%sec19 4010 3244 23.63% sec60 343020 361274 -5.05%sec20 33134 48735 -32.01% sec61 61718 61302 0.68%sec21t22 214914 230686 -6.84% sec62 386296 369841 4.45%sec23 5963088 5993626 -0.51% sec63 213580 214863 -0.60%sec24 1583780 1385707 14.29% sec64 90461 51501 75.65%sec25 162189 90325 79.56% secJ 72391 67619 7.06%sec26 307081 324448 -5.35% sec70t74 157942 140722 12.24%sec27t28 997489 1036779 -3.79% secL 298998 219175 36.42%sec29 70072 100395 -30.20% secM 141668 104039 36.17%sec30t33 96568 81487 18.51% secN 223402 153397 45.64%sec34t35 129331 146372 -11.64% secO 147081 238661 -38.37%sec36t37 86295 29162 195.91% tot ind 18451202 18728226 -1.48%secE 5441606 5844870 -6.90% HH 4150413 3827375 8.44%secF 213665 273322 -21.83% TOTAL 22601615 22555602 0.20%

DEU 2000; total energy use by sector, vs. NAMEA-E


Results for energy :– Accuracy tested with NL, DE, AT, DK (countries that publish

a NAMEA-E)– Total values generally match within ~2%– Deviations in energy intensive sectors and households are

typically limited (less than 10%)– Deviations in other sectors can be large in percentage, but

not very influential in absolute value– Deviations by individual energy commodity can be larger in

percentage, especially with small absolute values– In some cases the totals can have larger deviations (20%),

due to energy information used by NSI different from that reported to IEA (vintage problem)


CO2 emissions by country: comparison with official data

0

200

400

600

800

1000

1200

1400

AU

T

BE

L

DN

K

ES

P

FIN

FR

A

DE

U

GR

C

IRL

ITA

NLD

SW

E

GB

R

AU

S

JPN

TU

R

WIOD

Officialsources

Total countryMt


CO2 emissions by sector: comparison with official data

DEU 2000, kt CO2

ESTAT WIOD not calibrated Diff

WIOD calibrated Diff

secAtB 8879 6356 -28,42% 8059 -9,23% secC 4563 11690 156,21% 5592 22,55% sec15t16 10712 8662 -19,14% 10512 -1,87% sec17t18 1616 1334 -17,47% 1646 1,84% sec19 108 144 33,24% 112 3,61% sec20 1436 742 -48,28% 1511 5,22% sec21t22 8042 6950 -13,57% 8231 2,35% sec23 21269 46403 118,18% 24425 14,84% sec24 32223 48151 49,43% 32652 1,33% sec25 2083 1292 -37,99% 2111 1,35% sec26 43425 39856 -8,22% 40777 -6,10% sec27t28 59502 111515 87,41% 66460 11,69% sec29 3795 2122 -44,08% 3511 -7,48% sec30t33 2387 1987 -16,76% 2428 1,68% sec34t35 4356 2628 -39,66% 4200 -3,58% sec36t37 1141 820 -28,13% 1179 3,28% secE 343897 323435 -5,95% 332915 -3,19% secF 9264 1987 -78,55% 8870 -4,25%


(continued)

ESTAT WIOD not calibrated Diff

WIOD calibrated Diff

sec50 3003 1685 -43,90% 3097 3,15% sec51 7769 5273 -32,13% 7838 0,89% sec52 8956 4671 -47,84% 8950 -0,07% secH 3160 2375 -24,84% 3157 -0,06% sec60 21200 1934 -90,88% 21737 2,53% sec61 8045 4568 -43,22% 4332 -46,16% sec62 13581 30889 127,45% 27665 103,71% sec63 14495 4238 -70,76% 14784 1,99% sec64 2669 1928 -27,77% 2292 -14,13% secJ 3074 1684 -45,21% 2914 -5,20% sec70 806 1067 32,36% 976 21,03% sec71t74 6296 4014 -36,25% 6586 4,60% secL 10497 4832 -53,97% 9690 -7,69% secM 4339 4023 -7,29% 4337 -0,03% secN 6840 5873 -14,13% 6064 -11,34% secO 13981 6326 -54,75% 12451 -10,94% secTOT 687408 701453 2,04% 692059 0,68% FC_HH 212854 119544 -43,84% 214094 0,58% TOTAL 900261 820998 -8,80% 906153 0,65%


Results for CO2: – Accuracy can be tested for most EU countries, against

NAMEA-AIR data reported to Eurostat– Total values generally match within few % – Deviations in energy intensive sectors should again be small

(less than 10%)– In some cases the totals can have significant deviations, and

the emissions from energy intensive sectors (power sector) can have large deviations (20%), unexplainable (cannot stem from wrong allocation: no process emissions or classification discordance) unless the energy information used by NSI is different from that reported to IEA. Data vintages issue.


non-CO2 emissions: – The modelling of emission coefficients is complex, combines

parameters such as changes of fuel quality, combustion technology, end of pipe abatement techniques

– Use whenever possible official statistical sources for emissions by industry

– Draw on EXIOPOL experience for the modelling of emissions (explain emissions vs fuel substitution, technology)


SOx vs energy (emitting fuels) inputs in EU countries: whole national economy (EU15 countries), trend

0

0.1

0.2

0.3

0.4

0.5

0.6

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

AUT

BEL

DNK

ESP

FIN

FRA

DEU

GRC

IRL

ITA

NLD

SWE

GBR

SOx emission/energy use

(t SO2-e/TJ)


SOx vs energy (emitting fuels) inputs in EU countries: SOx intensive industries, aggregate EU15, trend

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

sec21

sec23

sec24

sec26

sec27

sec40

sec61

FC_HH


(t SO2-e/TJ)


SOx vs energy (emitting fuels) inputs in EU countries: Basic metals sector, EU15 countries, year 2006

sec27

0

0.05

0.1

0.15

0.2

0.25

AU

T

BLG

DN

K

ES

P

FIN

FR

A

GE

R

GR

C

IRL

ITA

NLD

SW

E

GB

R


(t SO2-e/TJ)


Consistency between monetary (SUT) and physical (NAMEA energy) data

Different data sets with identical or linked variablesThe consistency problem:

1. Energy inputs from NAMEA energy (in TJ, 25 energy carriers) by NACE industry combined with energy prices (OECD/IEA) yield energy inputs aggregating to CPA energy commodities monetary energy inputs CPA*WIOD industry

2. Energy inputs from SUT: monetary energy inputs CPA*WIOD industry


Consistency between monetary (SUT) and physical (NAMEA Energy) data

Consistency of classifications: energy commodities

Energy data for 25 energy carriers in energy units by NACE industry CPA/Energy * WIOD industry

CPA 10: Coal (without coke)CPA 11: Crude Oil & Natural Gas; identification of crude oil by user, only 23 (refineries) uses crude oilCPA 23: Oil products & cokeCPA 40: Electricity & Heat, gas distribution



Comparison of energy inputs in monetary units: long term energy price increase

0

50

100

150

200

250

300

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

mill

. €

10: Coal & lignite inputE: electricity

NAMEA, energy

WIOD, SUT



Comparison of energy inputs in monetary units: ‘no problem’ case

0500

1000150020002500300035004000

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

mill

. €

11: Crude petroleum & nat.gas input23: Coke, refined petroleum

NAMEA, energy

WIOD, SUT



Comparison of energy inputs in monetary units: the post 2004 energy price boom

0

500

1000

1500

2000

2500

3000

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

mill

. €

23: Coke, refined petroleum input60: Land transport

NAMEA, energy

WIOD, SUT



Comparison of energy inputs in monetary units: the post 2004 energy price boom

0100200300400500600700800

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

mill

. €

40: Electricity, gas, heat input27t28: Basic metal

NAMEA, energy

WIOD, SUT



‘Soft link’ between SUT (WP1/WIOD) and Energy satellite accounts (WP4/WIOD)

1. Start with NAMEA energy, apply absolute prices (per energy unit) of 25 energy carriers, from Energy Prices & Taxes (OECD/IEA)

2. Calculate NAMEA energy inputs in monetary units for CPA energy commodities by WIOD-industry (compare to SUT energy inputs in monetary units)

3. Create a ‘soft link’ between - calculated (implicit) deflators of CPA energy commodities from NAMEA energy inputs in monetary units and in energy units- SUT energy deflators of CPA energy commodities


Thank you for your kind attention

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