1 Introduction
2 Methods
2.1 Chain-OEF approach
2.2 Goal
2.3 Scope
2.3.1 Functional unit
Transported barley grain {GLO} (Colruytketen) |
Oat grain, consumption mix, at feed compound plant/IE economic |
Maize grain, organic {BE} Renaat Moors | at feed compound Aveve (Colruytketen) |
Wheat grain Renaat Moors, at feed compound plant Aveve (Colruytketen) |
Maize germ, dried, from wet milling (germ drying), at plant/FR Economic |
Transported soybean {GLO} (Colruytketen) |
Sunflower seed {GLO}| market for | Alloc Def, U |
Maize bran, from wet milling (drying), at plant/FR Economic |
Sugar beet pulp, dried, consumption mix, at feed compound plant/NL Economic |
Molasses, from sugar beet {GLO}| market for | Alloc Def, U |
Crude palm oil, from crude palm oil production, at plant/ID Economic |
Crude maize germ oil, from wet milling (germ oil production, pressing), at plant/DE Economic |
Monocalciumphosphate |
Sodium chloride, powder {GLO}| market for | Alloc Def, U |
Wheat bran, consumption mix, at feed compound plant/NL Economic |
Rape meal {GLO}| market for | Alloc Def, U |
Crude soybean oil, from crushing (pressing), at plant/NL Economic |
Rye grain {GLO}| market for | Alloc Def, U |
Triticale, consumption mix, at feed compound plant/NL Economic |
Palm kernel meal {GLO}| market for | Alloc Def, U |
Calcium carbonate >63 μm, production, at plant EU-27S |
Distiller’s dried grains with solubles {GLO}| market for | Alloc Def, U |
Soybean hulls, consumption mix, at feed compound plant/NL Economic |
Byproduct (fish oil) |
Coconut oil, crude {GLO}| market for | Alloc Def, U |
Magnesium oxide {GLO}| market for | Alloc Def, U |
Transformation, from industrial area, built up |
Transformation, to industrial area, built up |
Occupation, industrial area, built up |
Electricity, medium voltage {BE}| market for | Alloc Def, U |
Natural gas, burned in gas motor, for storage {NL}| processing | Alloc Def, U |
Tap water, at user {CH}| market for | Alloc Def, U |
Diesel, burned in building machine {GLO}| market for | Alloc Def, U |
Printed paper {GLO}| market for | Alloc Def, U |
Packaging film, low density polyethylene {GLO}| market for | Alloc Def, U |
Emissions to air |
Carbon dioxide |
Municipal solid waste (waste treatment) {BE}| treatment of municipal solid waste, incineration | Alloc Def, U |
Transformation, from industrial area, built up |
Occupation, industrial area, built up |
Transformation, to industrial area, built up |
Electricity, medium voltage {BE}| market for | Alloc Def, U |
Natural gas, burned in gas motor, for storage {NL}| processing | Alloc Def, U |
Tap water, at user {CH}| market for | Alloc Def, U |
Diesel, burned in building machine {GLO}| market for | Alloc Def, U |
Building, hall, steel construction {GLO}| market for | Alloc Def, U |
Water, well, in ground, BE |
Transformation, from agriculture |
Transformation, to agriculture |
Occupation, agriculture |
Electricity, low voltage {BE}| market for | Alloc Def, U |
Diesel, burned in building machine {GLO}| market for | Alloc Def, U |
Sulfuric acid {GLO}| market for | Alloc Def, U |
Transport, freight, lorry 16–32 metric ton, EURO4 {RER}| transport, freight, lorry 16–32 metric ton, EURO4 | Alloc Def, U |
Building, hall, steel construction {GLO}| market for | Alloc Def, U |
Water, well, in ground, BE |
Transformation, from agriculture |
Transformation, to agriculture |
Occupation, agriculture |
Diesel, burned in building machine {GLO}| market for | Alloc Def, U |
Sulfuric acid {GLO}| market for | Alloc Def, U |
Transport, freight, lorry 16–32 metric ton, EURO4 {RER}| transport, freight, lorry 16–32 metric ton, EURO4 | Alloc Def, U |
Electricity, low voltage {BE}| market for | Alloc Def, U |
Building, hall, steel construction {GLO}| market for | Alloc Def, U |
2.3.2 System boundaries and cutoff criteria
Water, well, in ground, BE |
Water, rain |
Transformation, from industrial area, built up |
Occupation, industrial area, built up |
Transformation, to industrial area, built up |
Tap water, at user {Europe without Switzerland}| market for | Alloc Def, U |
Carbon dioxide, liquid {GLO}| market for | Alloc Def, U |
Transport, freight, lorry 16–32 metric ton, EURO4 {RER}| transport, freight, lorry 16–32 metric ton, EURO4 | Alloc Def, U |
Building, hall, steel construction {GLO}| market for | Alloc Def, U |
Electricity, low voltage {BE}| market for | Alloc Def, U |
Heat, central or small-scale, natural gas {Europe without Switzerland}| market for heat, central or small-scale, natural gas | Alloc Def, U |
Diesel, burned in building machine {GLO}| market for | Alloc Def, U |
Municipal solid waste (waste treatment) {BE}| treatment of municipal solid waste, incineration | Alloc Def, U |
Waste paper, unsorted (waste treatment) {Europe without Switzerland}| market for | Alloc Def, U |
Biowaste (waste treatment) {RoW}| treatment of manure and biowaste by anaerobic digestion | Alloc Def, U |
Comeco WWTP (Colruytketen) obv: Wastewater, average (waste treatment) {RoW}| treatment of, capacity 1.6E8l/year | Alloc Def, U |
Transformation, from industrial area, built up |
Transformation, to industrial area, built up |
Occupation, industrial area, built up |
Tap water, at user {Europe without Switzerland}| market for | Alloc Def, U |
Soap {GLO}| market for | Alloc Def, U |
Carbon dioxide, liquid {GLO}| market for | Alloc Def, U |
Oxygen, liquid {GLO}| market for | Alloc Def, U |
Nitrogen, liquid {GLO}| market for | Alloc Def, U |
Argon, liquid {GLO}| market for | Alloc Def, U |
Polypropylene, granulate {GLO}| market for | Alloc Def, U |
Polyethylene, low density, granulate {GLO}| market for | Alloc Def, U |
Corrugated board box {GLO}| market for corrugated board box | Alloc Def, U |
Paper, woodcontaining, lightweight coated {RER}| market for | Alloc Def, U |
Sawnwood, softwood, air dried, planed {RER}| planing, softwood, air dried | Alloc Def, U |
Soap {GLO}| market for | Alloc Def, U |
Sodium chloride, powder {GLO}| market for | Alloc Def, U |
Transport, freight, lorry 16–32 metric ton, EURO4 {RER}| transport, freight, lorry 16–32 metric ton, EURO4 | Alloc Def, U |
Building, hall, steel construction {GLO}| market for | Alloc Def, U |
Electricity from wind power, AC, production mix, at wind turbine, < 1 kV RER S |
Natural gas, burned in gas motor, for storage {GLO}| market for | Alloc Def, U |
Meat and bone meal (waste treatment) {GLO}| market for | Alloc Def, U |
Wastewater, average (waste treatment) {GLO}| market for | Alloc Def, U |
Transformation, from industrial area, built up |
Transformation, to industrial area, built up |
Occupation, industrial area, built up |
Transport, freight, lorry 16–32 metric ton, EURO4 {RER}| transport, freight, lorry 16–32 metric ton, EURO4 | Alloc Def, U |
Building, hall, steel construction {RoW}| building construction, hall, steel construction | Alloc Def, U |
Tap water, at user {Europe without Switzerland}| market for | Alloc Def, U |
Electricity, low voltage {BE}| market for | Alloc Def, U |
Natural gas, burned in gas motor, for storage {NL}| processing | Alloc Def, U |
Ethane, pentafluoro-, HFC-125 |
Ethane, 1,1,1-trifluoro-, HFC-143a |
Ethane, 1,1,1,2-tetrafluoro-, HFC-134a |
Wastewater, average (waste treatment) {GLO}| market for | Alloc Def, U |
Transformation, from industrial area |
Transformation, to industrial area |
Occupation, industrial area |
Transport, freight, lorry 7.5–16 metric ton, EURO4 {RER}| transport, freight, lorry 7.5–16 metric ton, EURO4 | Alloc Def, U |
Vlevico pig meat output (Colruytketen) |
Colruyt Dassenveld pork (Colruytketen) |
Building, hall, steel construction {RoW}| building construction, hall, steel construction | Alloc Def, U |
Tap water, at user {Europe without Switzerland}| market for | Alloc Def, U |
Pine wood, timber, production mix, at saw mill, 40% water content DE S |
Chromium steel pipe {GLO}| market for | Alloc Def, U |
Computer, desktop, without screen {GLO}| market for | Alloc Def, U |
Metal working, average for steel product manufacturing {RER}| processing | Alloc Def, U |
Electricity, low voltage {BE}| market for | Alloc Def, U |
Ethane, pentafluoro-, HFC-125 |
Ethane, 1,1,1-trifluoro-, HFC-143a |
Ethane, 1,1,1,2-tetrafluoro-, HFC-134a |
Wastewater, average (waste treatment) {GLO}| market for | Alloc Def, U |
Data quality criterium | Quality rating | Rationale | |
---|---|---|---|
Technological representativeness | (TeR) | 2 | All technologies included in the foreground system of the study were effectively applied at the analysed unit operations. Background data may deviate somewhat from reality as these are often made up from average production methods. Background data was selected in order to match reality as closely as possible |
Geographical representativeness | (GR) | 2 | Most data was gathered at the specific processing plants in Belgium. Some background data is however more generic and not specific for the considered locations (e.g. using global averages). Background data was selected in order to match reality as closely as possible |
Time-related representativeness | (TiR) | 5 | All gathered foreground data originates from the year 2013. Background datasets and models used are however often more than 5 years older than the foreground data. Background data was selected in order to match reality as closely as possible |
Completeness | (C) | 2 | Completeness is assumed to be good as all but one of the PEF impact categories were considered and all relevant in- and outputs of the foreground processes have been taken into account (only part of the capital goods and commuting were not included and 6 % of the feed ingredients (by mass) were assumed to have similar impacts to the other 94 %). Omitting the commuting data has an impact of max. 10 % and an average of 2 % of the total impacts. For the toxicity related impact categories, detailed data was however limited |
Parameter uncertainty | (P) | 2 | The resource use and emissions data is judged to be of low uncertainty as most data originates from calibrated measurements (e.g. energy use and legally regulated emissions) or recent, published calculation models. Standard deviations from these measurements are unknown but assumed to be limited |
Methodological appropriateness and consistency | (M) | 3 | Multifunctionality was dealt with appropriately. No cutoff was applied. Fossil and biogenic carbon emissions and removals were modelled separately (biogenic carbon emissions are not taken into account in the used ILCD method). GHG emissions from direct land use change were taken into account. No credits were considered for carbon storage or delayed emissions. No emissions off-setting were included. Most of the capital goods were included. All major processes directly linked to the product supply chain were included within the system boundaries. No 50/50 end-of-life modelling was included |
Effect category | Data quality rating |
---|---|
Climate change | 2.54 |
Ozone depletion | 2.67 |
Human toxicity, cancer effects | 2.44 |
Human toxicity, non-cancer effects | 2.00 |
Particulate matter | 2.33 |
Ionizing radiation HH | 2.67 |
Photochemical ozone formation | 2.54 |
Acidification | 2.17 |
Terrestrial eutrophication | 1.78 |
Freshwater eutrophication | 2.57 |
Freshwater ecotoxicity | 2.51 |
Land use | 2.37 |
Water resource depletion | 2.62 |
Mineral, fossil and ren. resource depletion | 2.67 |
Impact category | Quantity | Unit |
---|---|---|
Climate change | 4.6E-01 | kg CO2 eq |
Ozone depletion | 1.7E-08 | kg CFC-11 eq |
Human toxicity, cancer effects | 1.2E-08 | CTUh
|
Human toxicity, non-cancer effects | 6.9E-07 | CTUh
|
Particulate matter | 3.1E-04 | kg PM2.5 eq |
Ionizing radiation HH | 5.5E-02 | kBq U235 eq |
Photochemical ozone formation | 1.3E-03 | kg NMVOC eq |
Acidification | 9.8E-03 | molc H+ eq |
Terrestrial eutrophication | 4.2E-02 | molc N eq |
Freshwater eutrophication | 9.2E-05 | kg P eq |
Freshwater ecotoxicity | 2.6E+00 | CTUe
|
Land use | 8.0E+00 | kg C deficit |
Water resource depletion | 1.4E-01 | m3 water eq |
Mineral, fossil and ren. Resource depletion | 4.6E-05 | kg Sb eq |
Site | Number of employees | Allocation to pork chain (%) | Rationale for allocating |
---|---|---|---|
Feed production | 260 | 1 | Allocation by mass of total production that is destined for farms A and B |
Farms | 1–2 | 100 | Commuting assumed to be negligible |
Slaughterhouse | 80 | 2 | Allocation by mass of pork originating from farms A and B |
Meat processing | 850 | 3 | Allocation by mass of pork originating from farms A and B |
Distribution and retail | 26,150 | 0.1 | Estimate based on turnover |
Transport mode | Amount | unit |
---|---|---|
Employees by car | 70 | % |
Employees by bicycle, foot, bus, tram or train | 30 | % |
Average single distance | 19 | km |
Commuting frequency | 254 | days year−1
|
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The mass balance of the main product flow should fit to 100 %.
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Consumption goods are included for as far as data were readily available at plant level (e.g. utilities, diesel, feed ingredients, packaging, seeds, fertilizer, etc.).
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Major emissions are included (e.g. flue gases, agricultural emissions, hydrofluorocarbons (HFCs), unused gases)
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Waste treatment is included for solid wastes as well as wastewater.
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Capital goods (building infrastructure) and land use are included.
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Transport between plants is included.
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Commuting is excluded for comparability with other studies on the pig production chain, but included in the sensitivity analysis as it is a PEF requirement.
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Only readily available plant data are used and combined with literature models, no additional measurements are performed on-site.
2.3.3 Assumptions
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Electricity use is assumed to be from the Belgian power grid (average mix) unless stated otherwise.
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Feed packaging materials are assumed to be incinerated after use.
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Utility use for packed feeds is assumed to be the same as for bulk feeds.
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Ninety-four percent of feed ingredients (by mass) were assigned specific background datasets in order to calculate their impact. The remaining 6 % was assumed to have the same average impact so that the known feed ingredient impact could be upscaled to 100 % as an estimation of the total impact.
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Derivative maize products such as maize bran are assumed to come from the feed market.
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Sows are assumed to occupy their place in the stables for 1 year.
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Specific for farm A:
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The on-site produced maize and wheat are assumed to be directly used for pig feed for the farm.
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Because the wheat and maize production and consumption numbers are close to each other, it is assumed that all the maize and wheat is from own production (with the mass and impact rescaled to the exact number).
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Specific for farm B:
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The maize consumed at farm B is assumed to have a similar impact to that produced at farm A.
-
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Greenhouse gas emissions:
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Half of the nitrogen taken up by the plant is assumed to stay on the field as corn stover.
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The average weight of a fattening pig assumed to be 70 kg, the average weight of piglets 7 kg and the average weight of sows 200 kg
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Phosphate runoff to surface water:
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The factor P2O5sl is assumed to be 90.3 kg ha−1.
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Wheat production:
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The grain/straw mass ratio is assumed to be similar to that used in the Agri-Footprint database (Blonk 2014), namely 1.82.
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No subcontracting is assumed.
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Electricity from biogas:
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Expert judgement (Velghe F., senior project engineer at OWS, personal communication) is used to quantify the biogas potential and electricity generation: 40 m3 biogas/ton pig manure and 2 kWh electricity/m3 biogas.
-
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For packaging, the PEF guidelines for meat are used: 25 g plastic packaging and 2.5 g paper for the label per kilogram fresh meat (Technical Secretariat for the Fresh Meat Pilot 2014), assuming that the plastic is 50 % PP and 50 % PE.
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Half of the meat is assumed to pass the distribution centre on its way to retail while the other half is transported directly to retail.
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The transport distance from Halle (where both the meat processing and distribution centre are located) to the retail stores and back is assumed to be 160 km as most of the Colruyt retail stores are found within this range.
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Transport in between foreground units is modelled following the OEF Sector Rules Retail (Humbert et al. 2015b): it is assumed to be performed by lorry without taking into account any cooling needs.
2.3.4 Impact assessment method, normalization and weighting
2.3.5 Treatment of multifunctionality
2.4 Process descriptions
2.4.1 Feed production
2.4.2 Animal husbandry
2.4.3 Slaughterhouse
2.4.4 Meat processing
2.4.5 Distribution centre
2.4.6 Retail
2.4.7 Transportation
2.5 Data quality
3 Results and discussion
3.1 Life cycle impact assessment results and hotspot analysis
3.2 Sensitivity
3.3 Uncertainty
3.4 Chain-OEF in practice
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Feed production facility. Utility usage data was relatively easily available at the level of the different production units. Data for feed compositions was also available but required more work due to the large diversity of different feed products with all their specific ingredients. Feed does, however, represent an important impact in the meat supply chain. It is therefore important to gather detailed compositions at the level of specific brands rather than making one average animal feed mix. Including specific brand names allows farmers to link their feed choice directly to their environmental impact.
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Animal husbandries. Whereas data collection for agricultural processes is generally seen as difficult, farmers in Western Europe generally have very detailed bookkeeping and low overhead. Therefore, it is surprisingly easy to gather the required inventory data. However, data on direct elementary flows such as air emissions is more difficult to gather and requires expert knowledge and emission models to calculate.
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Slaughterhouse and meat processing. Data was relatively easily available at plant level. The slaughterhouse is a very linear process and therefore quite straightforward, whereas the meat processing site produces a multitude of outputs. In this study, we have chosen for the group of fresh pig meat, whereas many preparations are made as well, using a large range of utilities such as onion, pepper, port, mayonnaise, etc. This list is very elaborated and therefore time consuming. In that sense it is important to choose a functional unit that fits the goal and scope, which can be the optimisation of the meat supply chain or communication to consumers. In the latter case, it might be advisable to differentiate between specific preparations.
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Distribution centre and retail stores. Data gathering and allocation are rather complicated. In general, the impression is that the larger the company, the more complex the organogram, and consequently, the more distributed the data.
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Bookkeeping data are not directly usable as life cycle inventories. The data needs to be processed, transformed or completed with literature data or calculation models. Currently, this requires the involvement of a sector specialist and an LCA expert, increasing the cost of the study. Therefore, means should be sought to facilitate this step.
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Data is confidential between supply chain actors and often none of the results or only the impact assessment results can be communicated. This can be done by an independent third party, but it would be beneficial to have a data management platform in which supply chain actors can manage their own data, let it be reviewed and let the LCA results be communicated to clients and suppliers, partners, governments, etc.
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Most importantly, the supply chain actors such as SMEs and farmers have relatively fast access to data but the main bottleneck is to convince them to spend effort on an LCA study or at least to spend effort collecting and forwarding the required data to LCA practitioners.
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Pull: eco-branding. Consumers become more conscious about environmental issues and believe that they can play an important role in a transition to a greener society through sustainable consumption. Consumers can therefore induce a positive dynamic in value chains, but whereas they want to make sustainable choices, they do not always know exactly how to do this due to the unavailability of simple and reliable information. Clearly labelling environmentally friendly products can increase their consumption (Vlaeminck et al. 2014).
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Push: legislation. The European PEF/OEF offers a harmonised life cycle assessment methodology that can be used to underpin both recommended and mandatory European and regional policies.
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Push: technology. The consumption of energy and other resources often represents a major part of the product cost. Managing these resources in a more efficient, more sustainable manner by using innovative technologies will not only lead to cost savings across value chains, enhancing the economic benefit and thus the competitiveness of companies, but, more importantly, will also have an ecological benefit, decreasing the overconsumption of natural resources.
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Push: new business models. Innovations can not only be identified for a single production stage, but they can be established by introducing industrial ecology/symbiosis principles within value chains and within industrial clusters. Furthermore, in order to take up a leading role, businesses may require environmental practices from their suppliers that are more demanding than those required by legislation.
4 Conclusions
4.1 Impact of the analysed pork production chain
4.2 Applying chain-OEF
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The installation of a data management platform in which LCA results can be exchanged with respect for confidentiality and
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The link of LCA studies to drivers towards positive change in supply chains.