Transcript PowerPoint-presentatie

Carbon footprints – reconciling
academic and statistical work
Project: Bram Edens, Rutger Hoekstra, Daan Zult, Harry Wilting
(PBL), Ronghao Wu (intern)
Overview
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–
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Overview work within statistical community
Overview work within academic community
State the problem
Possible solution: SNAC footprint
Conclusions and discussion
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Environmenta
l
Y
2007/ 2008
GHG
1
40
Statistics Canada
MRIO
Y
2002&2006
GHG
4
?
Statistics Denmark
Partial
Y
2005
CO2
13
60
INSEE
Partial
Y
2005
CO2
±15
60
DESTATIS
Partial/ hybrid
Y
2007
Energy, CO2
14
73
Statistics Netherlands
Partial
N
2009
GHG (4)
17
60
Statistics Sweden
SRIO
N
1993-2008
Energy; materials; air
emissions
2
134
GSO Vietnam
SRIO
N
2005, 2007
CO2
1
5
PBL Netherlands
Environmental Assessment
Agency
Partial and MRIO
Y
2001
GHG (3) and land
13
57
DEFRA
MRIO
Y
1990-2009
CO2 and GHG
4
123
MRIO
Y
1995, 2000, 2005, 2008,
2009
CO2 (only emissions from
fuel combustion)
57
18
SRIO
N
2000-2007
8 pressures
2
64
International OECD
institutes
Eurostat
3
Years
SRIO
Country
specific IO
Australian Bureau of
Statistics
Type
Industries
Other
government
agencies
Regions
National
Statistical
Institutes
Institute
NSI/Other
Overview of footprint calculations at
NSI’s and other government agencies
Statistical community
– There is wide range of methods being used
‐ NSIs often use simpler models
– Focus broader than carbon
– Clear interest in additional breakdowns
‐ Household characteristics such as income
– Dissemination practices of the institutes show that the
results are not always presented as “official statistics”
4
Overview of MRIO databases that are currently
publically available
Acronym
GTAP
Global
Project
Institute
Purdue University
Years
1990, 1992, 1995, 1997, 2000
2001, 2004, 2007 (years are
not comparable)
1995-2011
1990-2009
Prices of previous
year
Countries/
Regions
-
-
1995-2009
-
15-129 (depends on year)
57 industries
40
(27 EU and 12 non-EU)
(80% of world GDP in 2006)
35 industries
187
Number of
industries
Environmental
data
43
(27 EU, 16 non-EU)
(95% of the global GDP)
130 industries
Energy use / several energy carriers
Water consumption
Land use
Emissions of greenhouse gases
Air pollutants
Resource use/extraction
Generation and treatment of various
types of waste
Greenhouse gases
Air pollution
Water use
Ecological Footprint
Trade
EXIOBASE
WIOD
Analysis EXIOPOL: Externality data and World Input-Output Database
input-output tools for policy analysis
Eora
-
EXIOBASE: FP6 project (EXIOPOL) FP7 project lead by the University of University of Sydney
led by FEEM Database created by Groningen
NTNU, TNO, SERI, CML
Greenhouse gases (CO2, Emissions (56)
NO2, CH4)
Materials (96)
Energy use
Land use (15)
Land use (split agro- Water use (14)
ecological zone)
5
100-500 industries
Academic work
– Difference between MRIOs:
‐ Aggregation (industries and/or countries)
‐ Construction method: IO based, SUT based, or trade
based
‐ Assumptions RoW or ITMs
‐ Emission data (modeled or not)
– Aim of MRIOs
‐ Information about global developments
‐ No claim to be 100% correct at national level
‐ Focus on consistent method (rather than best country
data)
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Carbon footprints for the Netherlands
from various MRIO databases
350
300
250
Emissions (MtCO2)
PNAS
NCC
200
ESSD
EORA
150
GRAM
WIOD
100
OECD
50
0
1990
1992
1994
Data provided by
Glen Peters and NoriYamano
1996
7
1998
2000
2002
2004
2006
2008
2010
Carbon footprints for the Netherlands:
WIOD and Eora
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Stating the problem
– Growing policy interest in footprints, but no clear answers
– MRIOs have set the standard, but outside NSIs capabilities
• Labour intensive
• Assumptions
– MRIOs vs. official statistics
• Always inconsistent due to integration/balancing
required:
• Trade asymmetries
– Can we reconcile statistical and academic work in area of
footprint analysis?
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A SNAC footprint
– Produce a footprint, based on MRIO, that is consistent
to official statistics of the Netherlands
‐ Single-country National Accounts consistent (SNAC)
– Main approach: “Adjust WIOD to be consistent to Dutch
data”
– Why WIOD?
‐ Transparancy
‐ Time series availibility
– Gain insight why results could be so different
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Method
– Follow WIOD procedure, but overrule with improved Dutch int
SUT:
‐ Improved allocation of imports/exports to countries:
• Trade in goods: Bilateral trade data (re-exports and
domestic trade) from micro data
• Trade in services: Trade in services (confidential)
‐ National Accounts
• Used IO database to isolate re-exports
• Used IO database for valuation layers -> basic prices
‐ Expand from 35 to 72 industries (CO2 only)
– Balancing using the WIOD procedure but keeping the Dutch data
fixed
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Results: SNAC vs. WIOD
2003
Name
Absolute/Percentage
Total Footprint
Domestic indirect emissions
Domestic direct emissions
Total Domestic
Total Foreign
Resident emissions
SNACfootprint
MtCO2
WIOD
MtCO2 %
206
220
81
78
41
40
122
118
85
102
209
2009
SNAC-footprint WIOD
MtCO2
MtCO2 %
-6%
202
210 -4%
4%
80
71 11%
3%
40
39 5%
3%
120
109 9%
-17%
83
101 -22%
205
– Overall difference in footprint: 4-6%
– Mainly due to lower foreign emissions
– NL becomes net exporter of emissions
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Results 2: per capita
Source: CBS 2013
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Results for top 10 countries/regions
Source: CBS 2013
– China at 19%: largest foreign emissions followed by
Germany
– WIOD: 21%
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Why do SNAC and WIOD results differ?
WIOD
use
imports (incl ITM)
Total intermediate inputs
Taxes less subsidies on
products
Intermediate Inputs
adjusted
Value added at basic prices
Output at basic prices
CBS
use
imports
Total intermediate inputs
Taxes less subsidies on
products
Total intermediate inputs
adjusted
Value added at basic prices
Output at basic prices
intermediate
Final
Gross fixed Changes in Gross capital
consumptionconsumption capital
inventories formation
expenditure formation
and
valuables
362
344
78
-3
75
187
59
22
0
22
549
403
100
-3
97
33
21
9
0
9
582
510
1,091
425
109
-4
105
0
0
411
159
570
368
37
405
75
20
95
-1
-2
-3
75
20
95
15
32
14
0
14
585
511
1,096
437
109
-3
109
15
Exports
310
0
Total use at
basic prices
1,091
268
62
244
0
1,096
214
62
Why do SNAC and WIOD results differ? 2
CBS/WIOD
use
imports
Total intermediate
inputs
Taxes less subsidies on
products
Total intermediate
inputs adjusted
Value added at basic
prices
Output at basic prices
Final
Gross fixed
intermediate consumption capital
consumption expenditure formation
Changes in
inventories Gross capital
and valuables formation
Exports
114%
85%
107%
63%
96%
91%
33%
100%
91%
104%
100%
95%
100%
98%
45%
152%
156%
101%
103%
100%
100%
100%
Differences due to:
• Re-exports
• Valuation layers
More detailed information
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156%
75%
104%
Total use at
basic prices
79%
100%
80%
Conclusions and discussion
1. Shift: uncertainty within MRIO to between MRIOs
2. MRIOs are produced for global questions, a SNAC-footprint is
more relevant for national policy makers due to consistency to
country statistics
3. SNAC makes a difference! (at least for the Netherlands)
4. MRIO producers could quite easily make a footprint for
individual countries using “SNAC-philosophy”; key issue is
sharing data
5. Need for enhanced cooperation especially in light of 2008 SNA
‐ Between statistical offices
‐ Between MRIO producers
‐ Statistical and academic community
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