Federal Department of Economic Affairs FDEA
Agroscope Reckenholz-Tänikon Research Station ART
2 March 2010
How to establish life cycle inventories of agricultural products?
Thomas Nemecek
Agroscope Reckenholz-Tänikon Research Station ARTCH-8046 Zurich, Switzerlandhttp://[email protected]
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 2
Overview
Defining system boundaries: temporal and process related How to get the LCI data: data survey vs. modelling ecoinvent database: Version 2.1 Future development to version 3.0 Direct field and farm emissions: how to estimate? Variability and uncertainty: Sources of variability Examples and implications Analysis of variability Assessment of uncertainty How to deal with missing data: generalisation and extrapolation Towards an integrated framework: SALCA Specific aspects of tropical crops Some recommendations
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 3
Defining system boundaries:Temporal system boundariesAnnual crops: Starting after harvest of previous crop (including fallow period
or catch crop, if no product) Ending with harvest of the considered crop
Permanent crops: Annual basis (1st January to 31st December) orMultiannual cropping cycle (distinguishing different phases:
planting, young plantation, main yielding phase, eradication)
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 4
Defining system boundaries:Example of crop production
Products:
Infrastructure:•Buildings•Machinery
Field work processes:•Soil cultivation•Fertilisation•Sowing•Chemical plant protection•Mechanical treatment•Harvest•Transport
Field production
Catch crops
Silage maizeSugar beetsFodder beetsBeetrootCarrotsCabbage
WheatBarleyRyeOatsGrain maizeCCMFaba beansSoya beansProtein peasSunflowersRape seed
Potatoes
Co-Product:Straw
Product treatment:
Grain drying
Potato grading
System boundaryR
esou
rces
Direct and indirect emissions
Manure storage
Animal excrements
Animal production system
Inputs:•Seed•Fertilisers (min. & org.)•Pesticides•Energy carriers•Irrigation water
© T. Nemecek, ART 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 5
Defining system boundaries:Where to draw the line between animal and plant production?
Animal production (incl. feedstuffs, buildings, emissions, etc.)
Manure storageand treatment
Manure application(incl. machinery use and emissions)
Nutrient use in plant production
?
© Gaillard & Nemecek, 2006
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 6
Single crop or cropping system?
YearMonth 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
Year 4 5 6Month 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
Springbarley Grass-clover mixture ...
Fallo
w ..
.
... F
allo
w
1 2 3
... G
rass
-cl
over
mix
ture
PotatoesG
reen
man
ure
Winter wheat Forage catch crop Grain maize
© T. Nemecek, ART 2001
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 7
How to get representative LCI data?Two approaches Structural, general production and economic data are
regularly recorded in most countries (statistics, FADN, FAO, EUROSTAT)
Data on agricultural management are largely missing (fertiliser use, pesticides, use of machinery, timing of interventions, etc.)
Two possible solutions:1. Make a large survey: pilot farm networks one single data source enables to assess the variability preferable, but very expensive!
2. Modelling LCI: based on statistics, FADN, recommendations, expert knowledge, etc. combination of several different data sources difficult to assess the variability most frequently used alternative, much cheaper
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 8
Integrate environmental LCA into FADN Project supported by the Swiss Federal Office for Agriculture Time-frame: 2004 - 2010 with data acquisition from 2006 - 2008 Establish an operating system with 110 farms (during 3 years
with 60 in the first year) Establish an information technology infrastructure Training life cycle management principles in practiceDevelop concepts for evaluation and communication and
practice them with farmers and extension services Sectoral monitoring and environmental management of
farms
How to get representative LCI data? 1. Example of Swiss farm LCA networkProject Life Cycle Assessment – Farm Accountancy Data Network (LCA-FADN)
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 9
How to get representative LCI data? 1. Example of farm network / Project LCA-FADN: workflow
Existing FADN accountancy data
SynergiesFADN LCA-FADN
New FADNLife Cycle Assessment
Export ÖB-Stelle
Trus
t and
ac
coun
ting
offic
e
AccountancyData
FADN database
Accountancy-Software
(AGRO-TWIN)
Plausibility testsSALCAcheck
LCA validation and benchmarking
FAD
N
eval
uatio
n ce
ntre
Farm
LCA
cen
tre
Feedback to farmers
SALCAcalcLCA calculation
Technical data
SALCAprepdata extraction
Farm management software
(AGRO-TECH)
Accountancy data
Accountancy-Software
LCA data
© Agroscope ART 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 10
How to get representative LCI data?2. Example of modelling LCI
Source: Nemecek, Erzinger (2004). Modelling representative life cycle inventories for Swiss arable crops. Int J LCA.
Information provided by seed suppliers and experts (survey)Chemical seed dressing
Pilot farm network (years 1994-96 from BLW et al. 1998)Pesticide applications
Pilot farm network (years 1994-96 from BLW et al. 1998) for farmyard manure
Types of fertilisers in organic systems
Import statistics (years 1996-98 from Rossier 2000) for mineral fertilisersPilot farm network (years 1994-96 from BLW et al. 1998) for farmyard manure
Types of fertilisers in integrated systems
Fertilising recommendations (Walther et al. 2001)Quantity of fertilisers
Work budget (planning tool, Näf 1996)Sowing and harvest dates
Gross-margin catalogue from the extension service (LBL et al. 2000)
Moisture contentQuantity of seedUse of machinery (number of passes)
Fertilising recommendations (Walther et al. 2001)Straw yields and crop residues
FADN ART (weighted means for 1996-2003)Yields for main products
Data source(s)Data category
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 11
Sources of LCI data:ecoinvent database v.2.1
More than 4000 generic LCI process datasets on energy supply, resource extraction, material supply, chemicals, metals, agriculture, waste management services, and transport services
Used by over 1200 members in more than 40 countries
Included in the leading LCA software and eco-design tools
Online access to LCI and LCIA results for all datasets
Based on industry data, compiled by independent experts
Consistent, validated and transparent
Continuously maintained
International in scope, including e.g. data on US agriculture, worldwide sourcing of raw materials and production of electronics in Asia
A joint initiative of the ETH domain and Swiss Federal Offices
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 12
Datasets for the biomassproduction in ecoinvent: Overview
1. Datasets on agricultural means of production: infrastructure (buildings and machinery) and its usage, fertilisers, pesticides, seed and animal feed
2. Datasets on agricultural and biomass products: • Arable crop products• Grass• Wood• Fibres
Swiss Centre For Life CycleInventories
A joint initiative of the ETH domain and Swiss Federal Offices
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 13
Contents of ecoinvent Version 2.1What is covered in agriculture?
Production branches Buil
ding
s
Mac
hine
ry
Wor
k pr
oces
ses
Inpu
ts
Prod
ucts
CH
Pro
duct
s Eu
rope
Prod
ucts
Am
eric
a
Pro
duct
s As
ia
Arable cropsFodder cropsHorticulture (Field)Horticulture (Greenhouse)Fruit growingVineyardsCattle productionPig productionPoultry productionSheep production
relevant datasests availablepartly availablenot available
Swiss Centre For Life CycleInventories
A joint initiative of the ETH domain and Swiss Federal Offices
© ecoinvent centre, 2007
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 14
Contents of ecoinvent version 2.1Datasets for biomass production
Category Subcategory Number of datasetsagricultural means of production buildings 23agricultural means of production machinery 6agricultural means of production work processes 39agricultural means of production mineral fertiliser 24agricultural means of production organic fertiliser 5agricultural means of production pesticides 68agricultural means of production seed 26agricultural means of production feed 10agricultural production plant production 120agricultural production animal production 4biomass production 4wooden materials extraction 123wood energy fuels 13Total 465
Swiss Centre For Life CycleInventories
A joint initiative of the ETH domain and Swiss Federal Offices
© ecoinvent centre, 2007
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 15
Contents of ecoinvent version 2.1Crops and countries
CountriesBrazilCameroonChinaEuropeFranceGermanyGlobalIndiaMalaysiaPhilippinesScandinaviaSpainSwitzerlandThailandUSA
barley potatocotton protein peasfaba beans ramiefodder beets rape seedgrain maize ricegrass ryegrass silage silage maizegreen manure soy beanshay sugar beetshemp sugar canejute sunflowerkenaf sweet sorghumoil palm wheat
CerealsOil cropsProtein cropsFibre cropsGrass
Crops
Swiss Centre For Life CycleInventories
A joint initiative of the ETH domain and Swiss Federal Offices
© ecoinvent centre, 2007
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 16
ecoinvent database: online access
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 17
Example: Unit Process Inventory (extract from V1.0)
ExchangesLocation/Category Unit Value U
ncer
tTy
pe
SD95% Uncert Scores w
heat
gra
ins
IP,
at f
arm
CH
(kg
)
whe
at s
traw
IP,
at f
arm
CH
(kg
)
ammonium nitrate, as N, at regional storehouse RER kg 6.71E+01 1 1.07 (2,1,1,1,1,na) 92% 8%pesticide unspecified, at regional storehouse CH kg 2.60E-01 1 1.13 (2,2,3,1,1,na) 92% 8%wheat seed IP, at regional storehouse CH kg 1.80E+02 1 1.07 (2,1,1,1,1,na) 92% 8%...............................tillage, ploughing CH ha 1.00E+00 1 1.07 (2,1,1,1,1,na) 92% 8%grain drying, low temperature CH kg 7.64E+01 1 1.07 (2,1,1,1,1,na) 100%...............................Occupation, arable, non-irrigated resource/land m2a 7.94E+03 1 1.77 (2,1,1,1,1,na) 92% 8%Transformation, from pasture and meadow, intensive resource/land m2 2.90E+03 1 2.67 (2,1,1,1,1,na) 92% 8%Carbon dioxide, in air resource/in air kg 1.39E+04 1 1.07 (2,2,1,1,1,na) 61% 39%Energy, gross calorific value, in biomass resource/biotic MJ 1.67E+05 1 1.07 (2,2,1,1,1,na) 59% 41%...............................
Ammoniaair/low population density kg 9.06E+00 1 1.30 (2,2,1,1,1,na) 92% 8%
Phosphorus water/river kg 2.58E-01 1 1.77 (2,2,1,1,1,na) 92% 8%Nitrate water/ground- kg 1.25E+02 1 1.77 (2,2,1,1,1,na) 92% 8%Isoproturon soil/agricultural kg 1.27E+00 1 1.32 (2,2,3,1,1,na) 92% 8%Cadmium soil/agricultural kg 3.91E-03 1 1.77 (2,2,1,1,1,na) 42% 58%wheat grains IP, at farm CH kg 6.42E+03 100%wheat straw IP, at farm CH kg 3.91E+03 100%
Unit process inventory for: wheat IP, CH
© ecoinvent centre, 2003
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 18
Plans for the ecoinvent database v.3.0 – release 2011Co-operation with national database initiativesMore detail, more technologies, more completeness: International editorial board and broader supplier base Parameterisation (geography, time, technologies, markets) New data structure based on supply-use framework, allowing easier
production of national versions New indicators Sponsor-funded Open Access to individual datasetsMore frequent updating Improved uncertainty estimation and calculation facilities
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 19
New developments for ecoinvent V3.0:International editorial board and broader supplier base International editorial board Activity editors, for each industry activity and for household
activities Cross-cutting editors, to ensure consistency and monitor
developments across the entire database, both for specific (groups of) emissions, for geographical areas, scenarios, etc., and for the meta-data fields, e.g. uncertainty
Broader supplier base Making it easier for experts and lay users to contribute with new
data or corrections to existing data All such contributions will still be subject to our strict quality
control, review, and validation procedures before entering into the database
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 20
New developments for ecoinvent V3.0: ParameterisationGeographical parameters: Core international datasets + national differences Using GIS coordinates, all other area parameters can be
expressed: Country codes, areas with different population densities, habitat areas, watershed areas, etc. for site-dependent impact assessment
Temporal parameters (years) Scenario parameters (e.g. BaU, optimistic, pessimistic)Dataset-internal parameters Inheritance using parent child-relationships
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 21
New developments for ecoinvent V3.0: Better support for alternative modelling options
Attributional and consequential modelling: Average versus marginal market modelling Allocation versus substitution (system expansion) Several versions of attributional allocation
The unallocated (multi-functional) unit processes are the same for both models
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 22
Estimating direct field and farm emissionsUsually no measurement on site possibleTwo options: 1. Literature values, experiments: take a value for a given
situation Specific for the situation Difficult to find Not flexible Mitigation options usually cannot be considered 2. Modelling More flexible Mitigation options can be considered, depending on the model Level of detail should be consistent across the models No globally usable emission models available
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 23
Estimating direct field and farm emissions
Ideal emission models shouldReflect the underlying environmental mechanisms Be site and time dependentConsider the effect of soil and climateConsider the effect of management Be applicable under a wide range of different situations The different models should have a similar level of detail But also be usable: Parameters are measurable Data can be collected in a reasonable time Calculation is feasible
A compromise is needed!
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 24
SALCA emission modelsAmmonia (NH3)4 Emissions paths are modelled:1. Application of farm manure = f(fertiliser amount, NH3 and
NH4-concentration, covered area, saturation deficit in the air in function of average monthly temperature)
2. Application of mineral fertiliser = emission factors according to fertiliser type (2-15%, Asman 1992)
3. Emission from pasture = 5% of total N in excrements emitted as NH3
4. Emission from stable = emission factors dependent on animal category, housing system, farm manure type (liquid or solid) Source: Menzi et al. (1997)
© Agroscope ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 25
SALCA emission modelsNitrous oxide (N2O)
Fertilisers: Direct emissions: 1% of available N Symbiotic N-fixation in legumes: no emissionsCrop residues: emission factor 1% Storage of farmyard manure: emission factors 0.1% for liquid
manure and 2% for dung Pasture: emission factor 2% Induced Emissions: 1% of NH3-N and 0.75% of NO3-N
N2O in air: adapted method according to IPCC 2006, under consideration of induced N2O-Emissions:
© Agroscope ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 26
SALCA emission modelsSALCA-nitrate
Input of mineral N through fertilisers (NH4, NO3, Amid-N)
N minerali-sation of soil organic matter
N uptakeplants
Leaching Leaching
Non leached N
+
GRUDAF:60 dt yield158 kg N uptake
Example:80 dt yield211 kg N uptake
Temperature dependent
N-Uptake functions(STICS)
Monthly N-uptake
Source: Richner et al. (2006)
© Agroscope ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 27
SALCA emission modelsMethane (CH4) IPCC method 2 (Houghton et al. 1995) currently under revision Animal breading: Emissions from digestion = f(animal category, feeding) Emissions from storage of farm manure = f(animal category,
housing system)
Emission factors:Liquid manure: 10%Dung and pasture: 1%
© Agroscope ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 28
SALCA emission modelsPhosphorus (P)4 kinds of P-emissions in water:
• Surface run-off in rivers (solved PO43-)
• Drainage losses in rivers (solved PO43-)
• Erosion in rivers (P bound to soil particles)• Leaching in ground water (solved PO4
3-)
Emissions are dependent of:• Soil characteristics (granulation, bulk density, soil water
balance) and drainage• Quantity of P-fertiliser• Type of P-fertiliser (manure, compost, mineral)• Field slope and distance to rivers• Quantity of eroded soil• Plant available P in upper soil
Source: Prasuhn (2006)© Agroscope ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 29
SALCA emission modelsHeavy metals
Input-Output-Balance (caused by farmer) per field for:Cd, Cu, Zn, Pb, Ni, Cr, Hg Inputs:
- Fertilisers (mineral and organic)- Seed- Pesticides- Feedstuff and auxiliary materials for animal breeding Outputs:
- Exported primary products (e.g. grains, meat)- Exported co-products (e.g. straw, animal manure)- Leaching to groundwater and drainage to surface water- Erosion to surface water Allocation for inputs caused by the farmer The final balance can be negative! Source: Freiermuth (2006)
© Agroscope ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 30
Variability and uncertainty: Factors influencing environmental impacts
Crop management
Pedo-climatic conditions
Crop yield
Life cycle inventory
Environmental impacts
To understand the variability of
environmental impacts, we need to
look on the variability of the
influencing factors
Socio-economic conditions
© T. Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 31
Global variability of yieldsExample: potato
medianq25%
q2.5%
Source: FAOSTAT
Cumulated potato world production as a function of the yield
05
101520253035404550
0.0 20.0 40.0 60.0 80.0 100.0
Cumulated world production [%]
Yiel
d [t/
ha]
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 32
T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ARTKey factors of crop LCI/LCA variability: example of wheat
Variability of environmental impacts:Wheat datasets in ecoinvent V2.01 (2007)
w heat grains, at farm
0.59
0.67
0.59
0.63
0.76
0.55
0.60
0.00 0.20 0.40 0.60 0.80
CH, IP
CH, ext
CH, org
Barrois, FR
Castilla, ES
Saxony, DE
US
GWP 100a, kg CO2-eq./kg
w heat grains, at farm
3.30
3.45
2.31
3.58
6.42
3.49
4.63
0.00 2.00 4.00 6.00 8.00
CH, IP
CH, ext
CH, org
Barrois, FR
Castilla, ES
Saxony, DE
US
energy demand, MJ-eq./kg
©ec
oinv
ent c
entre
200
7
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 33
Variability of environmental impacts: Energy demand per ha UAA (62 Swiss farms)
Energy demand per ha UAA
020000400006000080000
100000120000140000160000180000200000220000240000260000280000300000
31 22 21 22 23 11 21 21 15 11 11 14 11 22 21 11 11 21 21 51 13 21 53 51 51 21 21 51 55 51 51 11 11 21 14 21 22 16 53 52 53 21 53 21 55 23 21 21 11 51 53 53 56 51 11 53 53 53
MJ-
Eq.
Fa rmty pe D es c ription Fa rm ty pe D es c rip tio n1 1 a rab le fa rm ing 2 3 o th er cat tle1 3 ve ge ta b le cu ltivat io n 3 1 h orse s/g o ats/sh e ep1 4 f ruit cultivat io n 5 1 d airy fa rm / a ra ble fa rm in g com bin ed1 5 viticultu re 5 2 su ckler cow s / a rab le fa rm ing co m b ine d1 6 o th er cu ltu re s 5 3 p ig s a n d po u ltry / a ra ble fa rm in g com bine d2 1 d airy farm 5 5 d airy fa rm s / o th e r co m b in e d2 2 su ckler co ws 5 6 ca ttle / othe r co m b ine d
© Agroscope ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 34
Variability of environmental impacts: Example: Energy demand per ha UAA (dairy farms)
Energy demand of dairy farms
0
10000
20000
30000
40000
50000
60000
70000
80000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
MJ-
Eq./h
a U
AA
other inputs
emissions of animals
purchase of foodstuff
purchase of animals
PPP
fertiliser / nutrients
seeds
energy carriers
machines
buildings / equipment
Eutrophication of dairy farms
0
50
100
150
200
250
300
350
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
kg N
-Eq.
/ha
UA
Aother inputs
emissions of animals
purchase of foodstuff
purchase of animals
PPP
fertiliser / nutrients
seeds
energy carriers
machines
buildings / equipment
© Agroscope ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 35
Variance control as a basis for environmentalmanagement
An balanced use of energy and fertilisers improves eco-efficiency. The best farms (1, 2) had the
lowest pesticide use per area unit.The orchards have high yields (high labour input) and a good physiological and ecological equilibrium.
(i)
y = 3.79x - 0.46r = 0.73, P = 0.007
0.0
2.0
4.0
6.0
0% 20% 40% 60% 80% 100% 120% 140% 160%
Farm No. 1
Farm No. 2
(iii)
y = 0.09x - 0.01r = 0.77, P = 0.003
0.00
0.05
0.10
0.15
0% 20% 40% 60% 80% 100% 120% 140% 160%
Coefficent of Variance
Farm No. 1
Farm No. 2
Energy use (MJ eq./$)
Aq. Eutrophication (PO4 eq./$)
M
M
Source: Mouron et al. (2006)
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 36
Variability and non-linearityAverages may lead to wrong results
Ammonia emission as a function of quantity of slurry applied. TAN = total ammonia N in the slurry (after Menzi et al. 1997)
0
2
4
6
8
10
12
14
16
0 10 20 30 40 50m3 of slurry
kg N
H3/
ha
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
kg N
H3-
N/k
g TA
N
NH3 emission (kg NH3/ha)
Relative emission rate (kg NH3-N/kg TAN)
1x40 m3 slurry 13.5 kg NH3
2x20 m3 slurry 17.4 kg NH3
© T. Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 37
Uncertainty assessment in ecoinvent V2.1: Pedigree matrix
Indicator score 1 2 3 4 5 Remarks
Reliability Verified data based on measurements
Verified data partly based on assumptions OR non-verified data based on measurements
Non-verified data partly based on qualified estimates
Qualified estimate (e.g. by industrial expert); data derived from theoretical information (stoichiometry, enthalpy, etc.)
Non-qualified estimate
verified means: published in public environmental reports of companies, official statistics, etcunverified means: personal information by letter, fax or e-mail
Completeness
Representative data from all sites relevant for the market considered over an adequate period to even out normal fluctuations
Representative data from >50% of the sites relevant for the market considered over an adequate period to even out normal fluctuations
Representative data from only some sites (<<50%) relevant for the market considered OR >50% of sites but from shorter periods
Representative data from only one site relevant for the market considered OR some sites but from shorter periods
Representativeness unknown or data from a small number of sites AND from shorter periods
Length of adequate period depends on process/technology
Temporal correlation
Less than 3 years of difference to our reference year (2000)
Less than 6 years of difference to our reference year (2000)
Less than 10 years of difference to our reference year (2000)
Less than 15 years of difference to our reference year (2000)
Age of data unknown or more than 15 years of difference to our reference year (2000)
less than 3 years means: data measured in 1997 or later;score for processes with investment cycles of <10 years;for other cases, scoring adjustments can be made accordingly
Geographical correlation
Data from area under study
Average data from larger area in which the area under study is included
Data from smaller area than area under study, or from similar area
Data from unknown OR distinctly different area (north america instead of middle east, OECD-Europe instead of Russia)
Similarity expressed in terms of enviornmental legislation. Suggestion for grouping:North America, Australia;European Union, Japan, South Africa; South America, North and Central Africa and Middle East;Russia, China, Far East Asia
Further technological correlation
Data from enterprises, processes and materials under study (i.e. identical technology)
Data on related processes or materials but same technology, OR Data from processes and materials under study but from different technology
Data on related processes or materials but different technology, OR data on laboratory scale processes and same technology
Data on related processes or materials but on laboratory scale of different technology
Examples for different technology:- steam turbine instead of motor propulsion in ships- emission factor B(a)P for diesel train based on lorry motor dataExamples for related processes or materials:- data for tyles instead of bricks production- data of refinery infrastructure for chemical
Sample size>100, continous measurement, balance of purchased products
>20 > 10, aggregated figure in env. report >=3 unknown sample size behind a figure reported in the
information source
© ecoinvent centre, 2007
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 38
Uncertainty assessment for French wheat
95% confidence interval
© T. Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 39
Potential use of multivariate statistics in LCA explain variability
Multivariate statistics (like principal component analysis, PCA) can be used to show similarities between environmental impacts It can be also used to group environmental profiles, e.g.
of cropsAnalysis based on a set of midpoint LCIA indicators In the study applied to crop inventories from SALCA
(Switzerland) and ecoinvent (global)
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 40
Principal component analysis of SALCA inventories
Eigenvalues of correlation matrixActive variables only
52.73%
27.63%
6.18% 5.07% 4.51% 2.24% .94% .70%
-1 0 1 2 3 4 5 6 7 8 9 10
Eigenvalue number
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0E
igen
valu
e
80% of variance explained by first two principal components© T. Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 41
Principal component analysis of SALCA inventories
Relationship between impact indicators and factors 1 and 2
Projection of the variables on the factor-plane ( 1 x 2)
Energy
GWP Ozone
Eutro
Acidi
TET_EDIP
AET_EDIP
HTP_CML
-1.0 -0.5 0.0 0.5 1.0
Factor 1 : 52.73%
-1.0
-0.5
0.0
0.5
1.0
Fact
or 2
: 27
.63%
© T. Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 42
Factor 1: - can group crops- related to the yield
CER LEG MAI OIL ROOT VEG-6 -4 -2 0 2 4 6
Factor 1
-4
-3
-2
-1
0
1
2
3
4
5 Data for Swiss cropsfrom SALCA database: grouping by crop group(CER = cereals, LEG = legumes, MAI = maize, OIL = oil crops, ROOT = root crops, VEG = vegetables).
Fact
or2
© T. Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 43
Factor 2: - related to the farming system and theintensity
Conv Ipint Ipext Org-6 -4 -2 0 2 4 6
Factor 1
-4
-3
-2
-1
0
1
2
3
4
5
Data for Swiss crops from SALCA database: groupingby farming system(Conv=conventional, IPint = integrated intensive, IPext = integrated extensive, Org = organic). Fa
ctor
2
© T. Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 44
Principal component analysis of SALCA inventories
Yield is a key factor
Scatterplot (FALSR58_Res 14v*246c)
Factor 1 = -5.9426-2.1271*x
-3.0 -2.8 -2.6 -2.4 -2.2 -2.0 -1.8 -1.6 -1.4 -1.2 -1.0 -0.8 -0.6 -0.4
LnInvYield
-7
-6
-5
-4
-3
-2
-1
0
1
2Fa
ctor
1
LnInvYield:Factor 1: r2 = 0.4561
© T. Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 45
Principal component analysis of ecoinvent inventories
Effect of the crop group (factor 1)
CER FIB LEG MAI OIL ROOT
-8 -6 -4 -2 0 2 4 6
Factor 1
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
© T. Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 46
Principal component analysis of ecoinvent inventories
Effect of the farming system (factor 2)
Conv IPint IPext Org
-8 -6 -4 -2 0 2 4 6
Factor 1
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
© T. Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 47
Principal component analysis of ecoinvent inventories
Cereals in different countries
w heat barley rye
CH
FRES
DE
CH
CH
US
CH
FRES
DE
CH
CH
CH
RER
CH
CH
-8 -6 -4 -2 0 2 4 6
Factor 1
-2
-1
0
1
2
3
© T. Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 48
Potential use of multivariate statistics in LCA to explain variability
Between 76 and 80% of the variability could be explained by the first two principal components. Factor 1 crop (group) and yield Factor 2 farming system (conventional, integrated, extensive,
organic)More data are needed for more systematic analyses
The analysis helps to show similarities and differences between environmental profiles to find suitable proxies to derive simplified methods for extrapolations and approximations
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 49
How to fill data gaps in agricultural LCI?
The classical approach:1. Establish detailed and specific inventories for each
situationCurrently used alternatives:
2. Use proxies: what you think is the closest LCI (generalisation)
3. Streamlined LCA modelsNew approaches:
4. Extrapolation by yield correction5. Modular extrapolation method geographical extrapolation product extrapolation
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 50
Extrapolation by yield correction
Product extrapolation:
Geographical extrapolation:
c
ca
pc
ca
pcp Y
EeYEeE
'
'
'
)1(
l
la
pl
la
plp Y
Ee
YE
eE'
'
'
)1(
Impacts related to the yield (constant per kg)
Impacts not related to the yield (constant per ha)
pe Fraction of the impacts related to the yieldEstimation of this fraction:
• 0.7 for cereals from the ecoinvent datasets
• 0.5 as default value© Roches & Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 51
Modular EXtrapolation for Agricultural LCA (MEXALCA)
Basic idea: It is possible to split an inventory into different independent
modules. This enables easier adaptation of an existing inventory to a new
situation.
Working procedure:1. Establish a base inventory for one or several typical situations2. Split the inventory into independent modules3. Calculate unit inventories/impacts per module and input unit4. Determine amount of inputs used in each country (using global
estimators derived from FAOSTAT)5. Extrapolate inventory to any producing country6. Estimate global/regional impacts (medians, means, distribution)
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 52
Impacts for extrapolated situation
Input parameters:•yield per area unit•Mechanisation index•% of no-till area•kg N, P2O5, K2O applied•kg pesticide active ingredient•m3 water used•kg water evaporated
Good quality data availablefor some or all inputs
Global estimators(based on FAOSTAT)
Base crop inventory
Impacts per input unitBasic cropping operationsSoil tillageVariable machinery operationsN fertilisation, including N-emissionsP fertilisation, including P-emissionsK fertilisationPesticide applicationIrrigationProduct drying
Splitting
Calculation of unit impacts
Total impactsfor extrapolated
country y
Total impactsfor extrapolated
country z
Total impactsfor extrapolated
country x
0
0.05
0.1
0.15
0.2
0.25
0.3
0% 20% 40% 60% 80% 100%Percentage of the world potato production
GW
P 10
0 a
[kg
CO
2-eq
/kg]
Extrapolation
Extrapolation using MEXALCA
Global distribution of impacts
© T. Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 53
MEXALCA results: impacts per input unit
ModulesImpacts MachFix MachTill MachVar Nfert Pfert Kfert Pestic Irrigat Drying
non-renewable Energy [MJ-eq] 13604.50 1818.25 4621.45 70.91 31.26 10.69 341.5 9.988 0
GWP 100a [kg CO2-eq] 1074.68 118.49 272.66 13.45 2 0.614 15.127 0.247 0
photochemic O3 formation [kg ethylene-eq] 0.65 0.08 0.23 0.001 6E-04 2E-04 0.0092 2E-04 0
Nutrient enrichment [kg N-eq] 12.65 0.34 0.60 0.917 0.126 7E-04 0.023 2E-04 0
Acidification [kg SO2-eq] 9.38 0.95 1.80 0.282 0.039 0.003 0.099 9E-04 0
Aquatic ecotoxicity 100a [kg 1,4-DCB-eq] 56.92 0.13 0.45 0.015 0.404 0.007 114.99 4E-04 0
Terrestrial ecotoxicity 100a [kg 1,4-DCB-eq] 0.99 0.01 0.05 7E-04 0.009 3E-04 80.696 1E-04 0
Human toxicity 100a [kg 1,4-DCB-eq] 460.52 38.32 209.11 1.216 0.97 0.337 337.68 0.181 0
Potatoes
© Roches & Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 54
MEXALCA results: impacts per kg of potato in the world
QUANTILES 2.5% 10.0% 25.0% median 75.0% 90.0% 97.5%Energy [MJ-eq] 9.11E-01 9.77E-01 1.27E+00 1.72E+00 3.00E+00 3.05E+00 4.15E+00GWP [kg CO2-eq] 7.38E-02 8.58E-02 1.11E-01 1.23E-01 1.91E-01 1.92E-01 2.05E-01O3 form. [kg ethylene-eq] 2.84E-05 3.13E-05 4.75E-05 6.59E-05 8.50E-05 8.53E-05 1.07E-04
IMPACTS Nutr. enrich. [kg N-eq] 1.85E-03 1.92E-03 2.41E-03 3.44E-03 5.54E-03 5.61E-03 7.52E-03Acidific. [kg SO2-eq] 9.44E-04 1.14E-03 1.23E-03 1.49E-03 2.27E-03 2.30E-03 2.82E-03Aquat. Ecotox.[kg 1,4-DCB-eq] 1.18E-02 1.65E-02 2.30E-02 3.06E-02 5.24E-02Terr. Ecotox. [kg 1,4-DCB-eq] 5.41E-03 9.15E-03 1.26E-02 1.89E-02 3.50E-02Human tox.[kg 1,4-DCB-eq] 6.91E-02 6.96E-02 7.26E-02 8.34E-02 1.01E-01 1.40E-01 2.00E-01
The modular inventory system enables us to calculate the inputs and impacts in any producing country and to calculate median and quantiles for the inputs and for the impacts for the global production (per kg of product or per cultivated ha).
© Roches & Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 55
Results: estimated distribution of GWP of the potato production
0
0.05
0.1
0.15
0.2
0.25
0.3
0% 20% 40% 60% 80% 100%Percentage of the world potato production
GW
P 1
00 a
[kg
CO
2-eq
/kg]
© Roches & Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 56
First validation: impacts per kg
2 4 6 8 10
24
68
10
Non renewable energy demand [MJ-eq]
ecoinvent
mod
ular
inve
ntor
y
y 1.163x -0.042r2 0.796
0.2 0.4 0.6 0.8 1.0 1.2
0.2
0.6
1.0
Global Warming Potential 100 years [kg CO2-eq]
ecoinvent
mod
ular
inve
ntor
y
Colours
barleywheatry epotatopea
y 0.386x 0.198r 2 0.493
r2 0.493
0.00005 0.00015 0.00025
0.00
005
0.00
020
Photochemical ozone formation [kg ethylene-eq]
mod
ular
inve
ntor
y
Colours
barleywheatry epot atopea
y 0.973x 0r2 0.939
0.01 0.02 0.03 0.04
0.01
0.02
0.03
0.04
Nutrient enrichment [kg N-eq]m
odul
ar in
vent
ory
Colours
barleywheatry epotatopea
y - 0.158x 0.021r 2 0.022
0.002 0.004 0.006 0.008 0.010
0.00
20.
006
0.01
0
Acidification [kg SO2-eq]
ecoinvent
mod
ular
inve
ntor
y
Colours
b arleywhea try ep otat op ea
y 1.103x 0.002r2 0.435
© Roches & Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 57
Sensitivity analysis Performed considering the median (=q50%), q10% and q90% of
each input (estimated variability of the inputs)
POT AT O INPUTSMachVar Nfert Pfert K fert Pestic Irrig at Drying
Quantiles q10% q90% q10% q90% q10% q90% q10% q90% q10% q90% q10% q90% q10% q90%IMPACTSnon-renewable energy [MJ-eq] -1% 7% -11% 22% -2% 3% -1% 4% -2% 7% -27% 62% 0% 0%GWP 100a [kg CO2-eq] -1% 5% -28% 55% -2% 2% -1% 3% -1% 4% -9% 21% 0% 0%photo. ozone formation [kg ethylene-Eq] -1% 11% -5% 11% -1% 1% -1% 3% -2% 6% -15% 34% 0% 0%nutrient enrichm ent [kg N -eq] 0% 0% -64% 125% -4% 5% 0% 0% 0% 0% 0% 1% 0% 0%Acidif icat ion [kg SO2-Eq] 0% 3% -47% 93% -3% 3% 0% 1% -1% 2% -3% 6% 0% 0%Aquatic ecotoxic ity, 100a [kg 1,4-DCB-Eq] 0% 0% 0% 1% -3% 4% 0% 0% -76% 288% 0% 0% 0% 0%Terres trial ecotoxic ity, 100a [kg 1,4-DCB-Eq] 0% 0% 0% 0% 0% 0% 0% 0% -99% 377% 0% 0% 0% 0%Human toxicity, 100a [kg 1,4-DC B-Eq] -1% 7% -4% 8% -1% 2% -1% 3% -43% 165% -11% 25% 0% 0%
Variation: 5 to 10% Variation: 10 to 50% Variation: 50 to 100% Variation: > 100%
© Roches & Nemecek ART, 2010
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 58
Potentials of extrapolation
Extrapolation cannot replace data collection and the establishment of detailed and specific inventories Very important time saving possible Allows to create generic data sets on global and multinational level Assessment of global variability Fairly good estimates possible for energy demand, global warming and
ozone formation, land occupationDifficult for eutrophication and acidification (no site-specific parameters
considered) and toxicity (no detailed information on pesticide active ingredients)Can be used as first approximation and where ingredients is not so
relevant
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 59
SALCA: An integrated concept for agricultural environmental assessment
SALCA = Swiss Agricultural Life Cycle Assessment
SALCA consists of the following elements:Database for life cycle inventories for agriculture (in collaboration
with ecoinvent)Models for the calculation of direct emissions from field and farm A selection of impact assessment methods (midpoints)Methods for the assessment of impacts on biodiversity and soil
qualityCalculation tools for agricultural systems (farm, crop) Interpretation scheme for agricultural LCACommunication concept for the environmental management of
farms
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 60
SALCA calculation tools
Large variability large number of calculations automation requiredGeneric parametrised system modelling for farms and crops: SALCA-farm: generic LCA system for farms SALCA-crop: generic LCA system for arable crops and forage
production systems The templates are designed in order to cover all farms/crops All elements, which occur in at least one system must be
included Variables are defined, which can describe the different
quantities of inputs The variables that are not relevant for a particular system are
set to zeroModular structure
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 61
Data entry
Produktionsinventar.xls
Production inventory:C
omm
on dataentry
of all param
etersforall
tools
Input dataSA
LCA
heavy
metals
Input dataS
ALC
A
(TEA
M/S
imaP
ro)
Input dataS
ALC
A-soilquality
Input dataS
ALC
A-erosion
Input dataS
ALC
A-nitrate
Internal Links in EXCEL-sheet
SALC
A-H
eavym
etalsC
alculations
SALC
A
(TEAM
/SimaPro)
LCI C
alculations
SALC
A-soil
qualityC
alculations
SALC
A-biodiversity
Data entry
Calculations
(separate tool)
SALC
A-N
itrateC
alculations 6 separate tools in EXCEL: dataentry can be donethrough thecommonproduction inventory ordirectly in the tool
LIFE CYCLE INVENTORY (LCI)
LIFE CYCLE IMPACT ASSESSMENT (LCIA)
Transfer LCI data
SALC
A
(TEAM
/SimaPro)
LCIA
Calculation
Modular architecture of the tool SALCA-crop V3.1
© R. Freiermuth, T. Nemecek, ART 2010
SALC
A-Erosion
Calculations
Data transfer by macrosInput dataS
ALC
A-field
SALC
A-Field
(otherdirectem
issions)C
alculations
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 62
Specific aspects of tropical production systems: relevant LCI aspects Less managed production higher variability more dependent on the environment Labour input instead of machinery how to consider manpower?Use of draught animals how to consider?Reconsider the delimitation between plant and animal
production Adaptation of emission models to the conditions of the tropics
and subtropics (soil, climate)
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 63
Recommendations for agricultural LCILarge variability many observations neededCollect detailed farm management dataStandardised methodologyAutomated calculationUse of standard LCI formats (EcoSpold, ILCD)Need for a standardised format for agricultural
management dataRegionalisation, use of GISVariability and uncertainty should be assessed as
standard Infrastructure should be includedDevelopment of globally applicable emission models
How to establish life cycle inventories of agricultural products?T. Nemecek | © Agroscope Reckenholz-Tänikon Research Station ART 64
Thanks toThanks toThanks to
My colleagues: GMy colleagues: GMy colleagues: Gééérard Gaillard, Ruth Freiermuth, rard Gaillard, Ruth Freiermuth, rard Gaillard, Ruth Freiermuth, Martina Martina Martina AligAligAlig, Daniel, Baumgartner, Anne , Daniel, Baumgartner, Anne , Daniel, Baumgartner, Anne RochesRochesRoches, , , Katharina Katharina Katharina PlassmannPlassmannPlassmannEcoinvent centreEcoinvent centreEcoinvent centreUnilever: Unilever: Unilever: LlorenLlorenLlorenççç MilMilMilààà i Canals, Sarah i Canals, Sarah i Canals, Sarah SimSimSim, , , TirmaTirmaTirma
GarciaGarciaGarcia---SuarezSuarezSuarez
You for your kind attention!You for your kind attention!You for your kind attention!