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Global Impacts: Measuring the Impact of UK Consumption on
Biodiversity Overseas
Chris West, Elena Dawkins, Simon Croft, David Raffaelli, William Sheate
6th December 2012
Outline of Global Impacts SessionTime Activity
11.15 Presentation: An introduction to preliminary work on developing a potential Global Impacts methodology
11.30 Questions related to the presentation
11.45 Discussion: Limitations and Assumptions of the methodology
12.25 Discussion: Moving from prototype to indicator
12.55 Discussion: Targets
13.15? Close, and lunch
Defra Project Background
• Project Duration: Nov 2011 – March 2013
• The Issue– Growing consumption, increasing reliance on imports– Complex supply chains– Indirect and direct impacts of consumption– Overseas biodiversity impacts
• Project Aim – provide a database-driven methodology for linking UK imports to
geographically-defined impacts on biodiversity
Study Products covered Method Applied Biodiversity Indicator(s)
Trends in EU virtual land flows: EU agricultural land use through international trade, Van Sleen (2009)
Wheat case study Material flow analysis with a multi-criteria assessment of impacts
• Genetic diversity• Species diversity• Overall environmental
utility
Dutch Trade and Biodiversity, Kamphuis et al. (2011)
Soya, palm oil and tropical timber products
Trade flow analysis, combined with land area production data.
• Relative species richness
• Relative species richness of original species
Global Biodiversity Database, Scott Wilson (2007)
Soya, lumber palm oil, cotton, shrimps and wine
Trade flow analysis. Identification of ecoregions (WWF) in the country of production, threats to ecoregion.
• Ecoregion land area apportioned by import demand
The global biodiversity footprint of UK biofuel consumption, JNCC (2009)
Biofuels Trade data; source countries and crops, estimate land use requirement and identify the ecosystems under pressure
• Land use matched to region
Existing studies
Existing studiesStudy Products
coveredMethod Applied Biodiversity Indicator
The global land use impact of the United Kingdom’s biomass consumption, JNCC (2011) Part I
Biomass Material flow data (e.g. domestic material consumption) and biomass import data . Land required to supply products, with crop yields and crop water requirements.
• Matched land area requirements of imports to Biogeographical realms, biomes and specific countries
UK National Ecosystem Assessment Technical Report. Chapter 21: UK Dependence on non-UK Ecosystem Services, UNEP-WCMC (2011)
Biomass Import data from converted to land area requirements using crop yields and matched to the Biogeographical Realms . MFA used to track the history of biomass consumption in the UK.
• Matched land area requirements of imports to Biogeographical realms, biomes and specific countries
Lenzen et al. (2012) MRIO and biodiversity threats
Those that ‘threaten’ species
Multi-regional input-output model linked to listed ‘threats’ within the IUCN Red List.
• IUCN Red List Species under threat
• Our approach:
– Understanding consumption: • Measuring trade and supply chains• Linking production abroad with imports to the UK
– Understanding potential biodiversity impacts: • Selecting indicators of biodiversity • Linking indicators to production abroad
Defra Project Background
Trade information:
• Import, export data exists from HMRC, FAO, UN, Eurostat, OECD...– Physical– Financial
• Input-Output (IO) tables map interactions between industry throughout the whole economy. They are necessary to measure indirect/embedded materials within products. They capture the full supply chains of goods.
• We selected GTAP data based on the criteria: – Availability (current and likely future) – Number of regions covered vs no. of sectors covered– Regularly updated– New version just released
Understanding Trade and Consumption
GTAP/MRIO approach:
• Financial flows between 129 countries (multi-regional), across 57 sectors.
• Interactions between economic sectors (all inputs and outputs of whole economy) mapped out in tables (input-output).
• Limitations:– Limited sector resolution– Released every 4 years (latest version has 2004 and 2007 data)– Financial flows not physical quantities
MRIO data
Linking to detailed production data
• FAO: – Agriculture stats: yield, area harvested, production and trade flows for 236
Countries and over 600 products– ForeSTAT: production, import, export for wood product groups– FishSTAT: total capture, aquaculture, commodities, production and trade
• This is more detailed than the financial data, but lacks information about full supply chains.
• We need a method to link detailed product data to the full supply-chain in input-output models…
Diagram of MRIO physical model adapted from: Brad R. Ewing, Troy R. Hawkins, Thomas O. Wiedmann, Alessandro Galli, A. Ertug Ercin, Jan Weinzettel, Kjartan Steen-Olsen, Integrating ecological and water footprint accounting in a multi-regional input–output framework, Ecological Indicators, Volume 23, December 2012, http://www.sciencedirect.com/science/article/pii/S1470160X12000714
Linking production data to MRIO
• Method 1: Allocate physical production of each product and country within FAO to an equivalent producing sector and region within GTAP– Relies solely on financial MRIO data to model trade in commodities
between sectors
• Method 2: Allocate physical production to importing regions in GTAP– Hybrid approach; requires harmonisation of datasets and method for
dealing with re-exports in the physical data
• Method 3: Allocate physical production to regions and sectors in GTAP– Retains product detail to greatest extent but requires seed and feed data
UK Demand for products from:
Product demanded:
Total embedded Brazilian land area used for soybean production
UK Food products nec 184,555UK Trade 34,198
UKBeverages and tobacco products 29,981
UK
Public Administration Defense Education Health 29,697
UKVegetable oils and fats 22,500
China Wearing apparel 10,715
BrazilVegetable oils and fats 10,146
FAO Trade Data
Exports of soybeans to UK
What it tells you:• Exports of raw
materials/commodities to a country.
What it doesn’t tell you:• Where the final/processed
products end up, and whether they are re-exported
• Any ‘hidden’ impacts embedded in products e.g. soya embedded in meat products
DEFRA MODEL
UK Demand for products with ‘embedded’ soybeans
What it tells you:• Impacts (land associated with soybean
production in this case) associated with demand for any products (including ‘hidden’ land embedded in products).
Country TonnesBrazil 619000United States of America 27908Ireland 19539Belgium 14560Ukraine 10418Netherlands 10097Italy 6806Argentina 5063China 4485
• Environmental ‘extensions’ can be added to the production data:– From FAO we have details on yields by country and can therefore
calculate land requirements– We also have data on water consumption and pollution (in the form of
form of green, blue, and grey water– Some fertiliser data is available– IUCN RedList, Important Bird Area databases contain information
about species threats– Other regional information about endemism, habitat types etc.
• These extensions can be viewed in isolation or potentially combined.
Linking production quantity to impact
Sectors linked to physical production and land use data – sector level (e.g. fruit and veg, not mangos)
Physical production linked to environmental drivers of biodiversity loss and indicators
Method Summary• Defra model enables a detailed look at products and land use/ water/
biodiversity impacts etc. of those products.
• Benefits of Defra Model:– Retains product-level detail of FAO. Combines FAO physical data with MRIO financial flow
data.– Calculates all of the ‘hidden’/embedded impacts in products that might be missed in just
direct import/export data of the actual commodity (e.g. captures soya imported via meat products).
– Assesses impacts associated with the final consumption of products, compared to FAO trade data where commodities are likely to go into industry (rather than final consumers) and be processed and either consumed or re-exported elsewhere.
• Defra model:– Still under development, builds on work from OPEN-EU project, adds additional datasets
and indicators for anything associated with production of commodities.– Initial results are starting to become available for UK demand….
• The Hybrid-MRIO model still only contains information to country-level.
• To validate the model, and provide further regionally-specific information we are conducting case studies on Brazilian soybeans and shrimps (probably from Asia).
• It is intended that this approach can be used to drill-down into potential impact ‘hotspots’ inferred in the model.
Case Studies and Knowledge Base
• The following results are (very!) preliminary and therefore only for illustration:– Based on Method 1 (allocating products from FAO to producing
sectors in GTAP).– Available for only a handful of commodities at present.– Some outstanding data issues (e.g. with China data in FAO).– Biodiversity extensions are undergoing further work.
Preliminary results
‘Raw’ data from FAO shows direct imports of soybeans into the UK by exporting country:
Running the data through the hybrid-MRIO model gives us this:
Soybean consumption by the UK (2007)Country TonnesBrazil 619000United States of America 27908Ireland 19539Belgium 14560Ukraine 10418Netherlands 10097Italy 6806Argentina 5063China 4485
Brazil 1424584Argentina 1120954United States of America 535523Paraguay 117199India 44119Canada 39477Ukraine 19371Italy 10307Uruguay 9966Bolivia 5976
We can also look at how demand for different sectors contributes to this production:
Soybean consumption by the UK (2007)Demand from Sector Source Country Tonnes
Food products nec Brazil 688573
Food products nec Argentina 521460
Food products nec United States of America
190930
Vegetable oils and fats Brazil 115469
Beverages and tobacco products
Brazil 106558
Trade Brazil 106072
Vegetable oils and fats Argentina 89162
Public Administration Defense Education Health
Brazil 85703
Trade Argentina 82316
We can also look at how demand for different sectors contributes to this production:
Beyond Production: Top Ten: Seed cotton consumption by the UK (2007)
CountryProduction
(tonnes)Production
RankLand
Use (ha)
Land Use
RankBlue Water
(m3)
Blue Water Rank
Grey Water (m3)
Grey Water Rank
Redlist Species
IBAs (A1)
India 390,124
1
266,967
1
728,122,607
1 376552408 1
121 0
Pakistan 214,580
2
115,439
2
462,589,208
2 152503126 2
17 0
United States of America
164,800
3
68,860
4
148,839,426
5 35181297 3
56 2
Uzbekistan 136,869
4
53,359
5
457,217,578
3 1137 52
11 33
Turkmenistan 34,983
5
23,672
7
166,933,847
4 3861 48
8 26
Brazil 31,314
6
8,578
12
557,141
29 18893396 4 99 19
Greece 16,153
7
5,637
13 19,151,158
11 0 116 12 0
Tajikistan 15,462
8
9,293
10 59,604,994
6 398738 18
9 18
United Republic of Tanzania
13,338
9
29,911
6 5,303,360
15 876390 10 120 15
Australia 12,623
10
2,630
27 23,057,790
9 401987 17
39 64
Beyond Production: Seed cotton consumption by the UK (2007)
Country Land Use (ha) Redlist Species RedList 'Weighting'Old Rank New RankIndia 266,967 121 32,303,044 1 1Pakistan 115,439 17 1,962,457 2 4United States of America 68,860 56 3,856,147 3 2Uzbekistan 53,359 11 586,949 4 6United Republic of Tanzania 29,911 120 3,589,376 5 3Turkmenistan 23,672 8 189,377 6 7Tajikistan 9,293 9 83,635 7 9Brazil 8,578 99 849,232 8 5Greece 5,637 12 67,640 9 10Australia 2,630 39 102,577 10 8
• By SEI:– JNCC/SNH project on material flow analysis for Scottish Biomass and
links to biodiversity impacts– WWF European Policy Office: EU Policy and consumption-related
impacts on WWF Priority Areas for conservation (feasibility study)
• By others: – Manfred Lenzen’s group in Australia– WWF China
Related ongoing and future work
Thank you!