Quorn, Beef and Chicken footprints

Contents 1 Introduction ...... 3 2 Summary ...... 3 2.1 Main findings ...... 3 3 Beef – Carbon ...... 4 3.1 Methodology ...... 4 3.2 Data Sources ...... 4 3.2.1 EBLEX report (generated by E-CO2) and Bord Bia ...... 5 3.2.2 FAO reports ...... 5 4 Chicken – Carbon ...... 6 4.1 Methodology ...... 6 4.2 Data Sources ...... 6 5 Quorn – Carbon ...... 6 5.1 Methodology ...... 6 5.2 Data Sources ...... 6 6 Beef – Land ...... 6 6.1 Methodology ...... 6 6.2 Data Sources ...... 7 7 Chicken - Land ...... 8 7.1 Methodology ...... 8 7.2 Data Sources ...... 9 8 Quorn – Land ...... 9 8.1 Methodology ...... 9 8.2 Data sources ...... 9 9 Beef - Water ...... 9 9.1 Methodology ...... 9 9.2 Data Sources ...... 10 10 Chicken - Water ...... 10 10.1 Methodology ...... 10 10.2 Data Sources ...... 10 11 Quorn – Water ...... 10 11.1 Methodology ...... 10 11.2 Data Sources ...... 10 12 Comparisons ...... 11 12.1 Quorn Mince comparisons ...... 11 12.2 Quorn Pieces comparisons ...... 11 13 Diet and Sustainability ...... 11 14 References ...... 12

1 Introduction

The objective of this project is to help Quorn identify credible carbon, water and land use footprinting information for beef and chicken and to calculate the water and land use footprints for mince and pieces products. By identifying reliable footprint data it will enable Quorn to compare the carbon, water and land use impacts of its products against meat (specifically beef and chicken).

This report summarises the results of our research, documenting the comparable footprinting data sources for (carbon, water and land use) for beef, chicken and Quorn.

We analyse these data within the context of nutrition and sustainability, showing how each source of protein differs due to current production methods. Our main focus is upon typical UK production, but data from important beef exporting regions is also considered.

The methodologies used, data sources and results are discussed. We briefly discuss the relationship between our methodologies and alternative assessment methods but an in depth analysis is beyond the scope of this report.

Our analysis of the footprints of each food shows for the first time how the impact of our dietary choices upon climate change, water and land availability may be compared.

2 Summary 2.1 Main findings

GHG Land Green Water Blue Water Grey Water (KgCO2e/Kg) (ha/Kg) (Lt/Kg) (Lt/Kg) (Lt/Kg)

Beef – Mixed 30 (16 – 69) 0.0035 15,500 250 4,000 Beef – Grazed 121 (114 – 0.0049 16,500 300 5,000 130) Chicken 9.0 (7 – 11) 0.0007 3,500 70 400 Quorn – Mince 3.4 0.0004 1,500 60 400

Quorn - Pieces 3.4 0.0003 1,300 60 350

Comparison summary.

 There is a consistent boundary between the footprint assessments. All footprints are measured from cradle to processing gate.  Grazing beef is has a higher footprint than mixed beef due to the lower nutrition value of grass-based systems compared to supplementary feeds.  There is less difference between chicken and Quorn on all footprint metrics.

 There is difference in the land use footprint between Mince and Pieces is due to the malted barley used in the mince.

An important feature of beef production (much less so for chicken) is the range of environmental efficiencies found between farms. This range tends to be reasonably independent of the specific system, at least as practiced within a given country. For example, in the UK the range of per Kg beef GHG footprints has been shown to vary by as much as 8 fold and it is likely that a similar range will be found in Brazil. It will be important in future to compare Quorn the better performing farms as the livestock industry is clearly interested in moving the average performance in this direction.

In addition, the Brazilian data from the past 10 years indicates that the rate of deforestation is falling quickly. The role of initiatives such as the Roundtable for Sustainable Soya may also help to drive improvements in knowledge about soya sourcing.

Each of section of this report introduces the footprinting methodology used to generate the footprint results and references each of the main data sources.

3 Beef – Carbon 3.1 Methodology We have used data from studies using or consistent with the methodology developed by the Carbon Trust and based upon the Dairy guidelines from DairyUK/DairyCo/Carbon Trust (DairyUK and DairyCo, 2010). This methodology is fully compatible with IDF dairy guidelines (IDF, 2010) and FAO beef studies (Gerber, 2013), (Opio, 2013). It has been used over 100,000 times on nearly 40,000 farms in the UK and Ireland (Bord Bia, 2014), (EBLEX, 2012).

The boundary thus includes all feed production, manure storage and spreading and enteric methane. In terms of herd structure, the supporting suckler herd and replacements are wholly allocated to resulting beef produced and sold regardless of whether they are maintained on the final (finishing) farm or not.

A crucial point of continuing debate is how to manage the interaction between dairy and beef herds, where surplus dairy calves are transferred to beef production. Economic allocation is used to estimate the environmental (carbon, water and land) impact associated with dairy calves fattened for beef, which we assumed here to be a 95:5 split between milk/cull cows and calves to beef (E-CO2 pers. comm.). Other methods (feed energy requirements etc.) may result in slightly different ratios but the overall result in this context is not significantly different.

Other key data includes the type of feed and efficiency of the suckler herd. Emissions are high when a large numbers of animals are maintained for longer in order to produce finished animals. The main causes we consider are health, husbandry, feed quality and deforestation. Health and husbandry determine the size of the suckler herd and number of required replacements, whilst feed quality determines the rate of finisher maturity. More extensive systems in tropical/sub-tropical regions tend to be responsible for more deforestation. The more animals and the longer then are on farm, the higher emissions per Kg of meat tend to be – poorer health and feed also tend to mean higher emissions. 3.2 Data Sources The following data sources have been identified as the most recent, relevant and comparable basis to evaluate the impact of beef versus Quorn:

The data we researched allowed us to evaluate the differences between mixed and grazed beef systems.

FAO – information on mixed vs. grassland. (mixed = if more than 10% of feed is imported to farm and/or is grain co-products). We are also able to differentiate the mixed system between pure suckler bred beef and dairy bred beef.

Four generic beef production systems were analysed, although the two main ones of interest (intensive mixed and extensive grazing) have more coverage.

Intensive-Mixed: Typical system in the UK, based upon specialist beef breeds

Extensive Grazed: Typical system in South America

Dairy-bred: Common alternative system in the UK

The following sections introduce the key data sources that have been used to define the carbon footprint values for mixed and grazed beef systems. 3.2.1 EBLEX report (generated by E-CO2) and Bord Bia The EBLEX report just focuses on the UK (not grassland - only mixed - according to FAO classification).

The following table summarised their data, in terms of Kg CO2e per Kg meat produced (converted to edible portion1).

System Low High Average Finisher/rearer-Finisher 16 69 30 Dairy-bred Beef 7 35 20

Bord Bia do not publish their results, as the focus is upon farmer engagement and increasing efficiency. However, results for comparable farms are consistent with EBLEX (Padraig Brennan, pers. comm.). The methodology has been assessed by the Carbon Trust and certified as fully compliant with their livestock guidelines, PAS 2050 and consistent with other existing systems (such as E-CO2’s used for EBLEX). 3.2.2 FAO reports Carbon footprint for both mixed and grazed systems worldwide has been modelled by the FAO (Opio, 2013) Figure 12, (Gerber, 2013) Table 5.

Boundary assumptions and herd structure modelled by FAO are sufficiently similar to E-CO2/EBLEX for meaningful analysis.

System FAO Kg CO2e per Kg edible weight EBLEX for comparison Mixed 38 – Western Europe, 71 global average Ave 30 Dairy Calves, Mixed 22 – mostly EU but presented as global ave Ave 20 Grazed 121 – global ave, 25% - 33% from deforestation N/A

1 A kill-out ratio of 55% and deboning impact (further waste and processing energy) of 27% was assumed by CT when converting to edible portion

The FAO data for dairy-bred and mixed farming in Western Europe is highly consistent with that from EBLEX. We therefore use the farm-based EBLEX dairy-bred and mixed data plus the modelled FAO grazed data for comparison purposes. A point of caution is that the FAO grazed footprint may be at the high end of estimates, as the global average mixed footprint is at the high end of the UK mixed beef range. It should also be stated that much of the deforestation impact occurred 10 or more years ago and evidence strongly suggests that this issue is improving quickly.

4 Chicken – Carbon 4.1 Methodology Data from FAO analysis of 10 other reports (adjusted to same method/boundary) (MacLeod, 2013). Is comparable to UK and Ireland industry figures. 4.2 Data Sources Industry data from the UK and Ireland certified by the Carbon Trust against PAS 2050 (confidential results) and using a method fully consistent with the FAO (MacLeod, 2013) provides equivalent footprints.

LUC from import soya is a big factor as shown by the following table summarising results from 10 previous studies at farm gate, from table 30 in (MacLeod, 2013).

Feed Assumption Low High Average Kg CO2e per Kg edible portion weight2 With land use change (soya) 4 8 6.4 Without LUC 2.5 5.5 3.7

The chicken carbon footprint is between 25% and 33% that of intensively produced beef.

5 Quorn – Carbon To be completed – When Quorn’s latest figures are available. 5.1 Methodology PAS 2050. FPX Framework. 5.2 Data Sources To be completed by Quorn with details of their suppliers when recertification data collection is completed.

6 Beef – Land 6.1 Methodology To assess the land use requirements for beef, we built a model with the same structure and core herd assumptions as per the carbon footprint assessments (see section 3.1) to quantify the land utilised by different production systems. The land footprint is a factor of herd management and feeding regime.

The dry matter requirements of a typical beef animal were sourced from (EBLEX, 2011). Beef cattle require approximately 2% of dry matter per body weight per day. Therefore a 600kg cow eats about

2 We have assumed an additional burden and conversion factor due to waste (e.g. bones) of 55% compared to published carcase weight data, when generating the edible portion footprint

12kg of dry matter per day, young stock less according to age. Digestibility and the nutritional value of the feed will change up/down the productivity of the animal. If you have a highly nutritious diet – then you rear the animals very quickly because the nutritional value per Kg dry matter will be higher. So in Australia and US feedlots can only take up to 18 months from birth to slaughter (Pelletier N, 2010). Alternatively if it is a wholly grass-based diet (lots of exercise and variable digestibility), such as Brazil, it can take up to 3 years to raise to slaughter weight due to poorer grass quality (Cohn A, 2011). So the UK falls part way between US and South America at about 2 years (based upon a mixture and quality of grass and grain feed.

By quantifying the amount of dry matter required to feed livestock it is possible to calculate their land use requirements and how much dry matter is sourced from grass (and whole-crop forage) vs supplementary feeds. An important land-sparing effect is generated by using supplementary feeds e.g. brewers grains (waste barley from brewing). These typically have a footprint ~10% of the emissions of the original crop due to economic allocation between beer (for example) and these by- products – therefore reducing the land use requirements by 90%.

With a mixed beef system, there is a split between grass and concentrate. We have assumed a standard makeup of 20% concentrate for UK diets (Williams & Audsley, 2006) Tables 40 and 41. Yield data for the UK comes from DEFRA’s annual farm statistics (DEFRA, 2014). We can make an assumption for yield of grass per hectare (various assumptions exist) depending on variety/fertiliser… etc. We have used a mid-value of 10 tonnes/ha. This has quite a big impact on land footprint. The nutritional value will also have a big impact but this is largely reflected in the time taken to finish the cattle. In the summer cattle will be grazing from fields directly, but also require fields used to produce silage.

The main modelling criteria used to evaluate the land footprint of beef are listed below with specific details provided in the data source section:

 The herd structure and herd management is a variable (e.g. birthing rate and replacement rate).  The final weight of the animal and the kill out ratio is also a variable (reflects amount of meat produced in the allotted time).  The total amount of meat produced is based upon typical finished weights, kill out ratio and a contribution from culled suckler cows.  The time to finish varies, according to relative digestibility of the diets.  To validate the findings we looked at diet make up. We also looked at farms from existing industry studies.  Intensive Mixed – mostly grassed with 20% supplement  Extensive farm (100% grass-based)  Dairy calves – The footprint figure is low as the number of mothers you need to maintain to produce the beef animal is low due to 5% allocation (also assume lower quality meat with lower KO ratio and finish weight compared to Intensive Mixed). 6.2 Data Sources Concentrate feed mix (minerals and other additives make up the final 5%), Table 34, DEFRA 2013 UK yield statistics and assuming a 10% economic allocation to crop and industrial co-products (e.g. brewer’s grain). Use of co-products has a significant impact upon the land footprint.

Ingredient Proportion Dry Mass Yield / hectare Wheat 36% 6.4 tonnes Brewer’s Grain etc. 26% 64

Soya Bean 14% 2.1 Rape Seed 14% 2.9 Maize (grain) 5% 8.5

We have used typical industry averages for the main breeds (Pocketbook, 2013) alongside DEFRA data (DEFRA, 2014) and key international studies (Gerber, 2013), (Pelletier N, 2010) to determine the model’s parameters for each farm system.

Intensive Extensive Dairy-bred Mixed Grazed Concentrate diet % 20% 0% 20% Grazing, forage, silage diet % 80% 100% 80% DM grain yield t/ha 20 20 20 DM grass yield t/ha 10 10 10 Suckler herd replacement rate 20% 20% 30% Suckler herd fertility rate 90% 90% 90% Years to finish 2 3 2 Kill-out ratio 55% 55% 50% Mother's weight (Kg) 600 600 600 Average 2nd year weight (Kg) 500 500 450 Average 1st year weight (Kg) 300 300 250 Finished weight (Kg) 800 800 700 Result: ha/Kg meat 0.0035 0.0049 0.0015

As a validation check, (Meier, et al., 2014) calculated the land required for food production (table 1), including beef = 0.00254 ha/Kg (carcase weight)

We also compared the actual mixed farm data from an Irish farm (primary data regarding herd structure and diet) and achieved comparable results (0.00275 ha/Kg, carcase weight).

7 Chicken - Land 7.1 Methodology The grain for broilers and grain for the layers, is based upon typical UK diet (Williams & Audsley, 2006). We have discounted the parent birds as non-material to the footprint based upon our previous experience.

We determined the main feed ingredients, the yield (Kg per hectare) and typical UK feed amounts required to produce a Kg of meat (Williams & Audsley, 2006), (confidential Carbon Trust industry data). This data allows a straightforward calculation to estimate ha/Kg of chicken meat.

7.2 Data Sources Concentrate feed mix and typical UK dry yield (DEFRA, 2014). Many minor ingredients and additives are not included as they are immaterial to the footprint results:

Ingredient Proportion Dry Mass Yield / hectare Wheat 40% 6,400 Kg Maize (grain) 24% 8,500 Kg Soya 25% 2,100 Kg

The typical amount of meat per chicken is 2.3Kg

(1/SumProduct(%age:yield))/Kg meat per chicken at farm gate = 0.0005 ha/Kg

As a validation check, (Meier, et al., 2014) calculated the land required for US food production (table 1), including chicken 0.00062 ha/Kg (carcase weight). Allowing for typically lower per ha yields in the US compared to the UK this is a good agreement.

The land footprint for poultry comes out at 15% that of the beef, which is a larger difference than the carbon footprint.

8 Quorn – Land 8.1 Methodology As per the chicken calculations, the typical UK dry yield (DEFRA, 2014) was used to calculate the ha/kg for the raw ingredients used to make mycoprotein. The grain requirements and feed content between broilers and egg-laying hens is also similar. 8.2 Data sources Defra, British Sugar.

To be completed by Quorn with details of their suppliers when recertification data collection is completed.

9 Beef - Water 9.1 Methodology Same calculations that were used in section 0 are performed for beef water, substituting land use for water utilisation. That is, we calculated the water content of feed, rather than hectares per feed, adding drinking water.

Note that although we use WFN data for the feed and grazing water use (Mekonnen, Value of Water Research Report Series No.47, 2010), our herd modelling results in higher water footprints per Kg of meat compared to WFN data (Mekonnen, A Global Assessment of the Water Footprint of Farm Animal Products, 2012). This is due to our more comprehensive “bottom-up” methodology that properly models herd structure rather than relying upon top-down assumptions based on national statistics. The key difference between our results and those of Mekonnen and Hoekstra is that they estimate 16 Kg feed (dry mass) is required per Kg meat (Appendix 1, whilst we estimate 27 Kg (UK intensive beef). The reason for this difference is that the bottom-up approach includes the support herd necessary for

specialist beef. It is interesting to note that using a 2 year raising and finishing period and data from EBLEX, we calculate that based purely on the finished animal 15.7 Kg DM feed/Kg meat is required.

On the other hand, our results are somewhat lower than those reported by EBLEX (Chatterton & Hess, 2010) at 17,700 Lt/Kg meat (carcase weight, green, blue and grey water combined). Interestingly, if we don’t account for beef produced by culling suckler cows, our UK intensive beef water footprint is almost exactly the same as that reported by EBLEX. 9.2 Data Sources Water requirements are calculated using the same model as per land, simply replacing hectares with water use data.

Raw data for feed water use from WFN (Mekonnen, Value of Water Research Report Series No.47, 2010). To follow ISO 14046 in part, we recommend not including grey water in the assessment of water amounts as this should arguably be considered a separate impact category (e.g. eutrophication), parallel with water scarcity. The inclusion of Green Water also remains contentious and we present results separately for each “colour”.

Blue water also includes animal drinking water, estimated to be on average 5Lt/Kg dry matter eaten (EBLEX, 2013).

Intensive Extensive Dairy-bred Mixed Grazed Green Water (Lt/Kg) 15,500 16,500 6,500 Blue 250 300 100 Grey 4,000 5,000 1,700 Total 19,750 21,800 8,300

10 Chicken - Water 10.1 Methodology Water footprint for poultry was calculated in the same way as for chicken land – that is, the water footprint of each feed (WFN) was used in conjunction with the feed required per Kg meat. The result is about the same as reported by the water footprint network. 10.2 Data Sources Same assumptions about feed yield and proportions as per the land calculations.

11 Quorn – Water 11.1 Methodology Water requirements are calculated using the same model as per land, simply replacing hectares with water use data. 11.2 Data Sources Quorn FPX Product Footprinting model and data from Quorn’s suppliers.

(Mekonnen, Value of Water Research Report Series No.47, 2010),

12 Comparisons The raw data:

GHG Land (ha/Kg) Green Water Blue Water Grey Water (KgCO2e/Kg) (Lt/Kg) (Lt/Kg) (Lt/Kg) Beef – Mixed 30 0.0035 15,500 250 4,000 Beef – Grazed 121 0.0049 16,500 300 5,000 Beef – Dairy-bred 20 0.0012 6,500 100 1,700 Chicken 9.0 0.0007 3,500 70 400 Quorn – Mince 3.4 0.0004 1,500 60 400 Quorn - Pieces 3.4 0.0003 1,300 60 350

12.1 Quorn Mince comparisons The following table shows the ratio of Quorn Mince footprints to those of the respective meat alternatives.

GHG Land Green Water Blue Water Grey Water Beef – Mixed 11% 10% 10% 24% 10% Beef – Grazed 3% 7% 9% 20% 8% Beef – Dairy-bred 17% 30% 23% 60% 24% Chicken 38% 49% 43% 86% 100%

On a per Kg basis, Quorn is much more efficient that beef across all measures. The picture in comparison to chicken is more mixed. 12.2 Quorn Pieces comparisons The following table shows the ratio of Quorn Pieces footprints to those of the respective meat alternatives.

GHG Land Green Water Blue Water Grey Water Beef – Mixed 11% 9% 8% 24% 9% Beef – Grazed 3% 6% 8% 20% 7% Beef – Dairy-bred 17% 25% 20% 60% 21% Chicken 38% 42% 37% 86% 88%

The results for Pieces are very similar to Mince, other than for land where the lower ha/Kg footprint is reflected in an improved performance against the meat alternatives.

However:

 Is a Kg of Quorn nutritionally equivalent to a Kg of beef or chicken?  In our diet, which relative performance is the most important - GHG, land or water?

An initial attempt to understand how we can understand the significance of Quorn’s performance in regard to the GHGs, land and water impact of our diet can be found in section 13 below.

13 Diet and Sustainability Footprints and LCA demonstrate the physical relationship between human activity (e.g. producing food) and environmental impacts. The actions that may be taken to mitigate this impact or to promote

changes on farm or in the home are not the focus of this report. However, we hope to provide a unique perspective on the three most important environmental issues (climate change, water and land use) and how they may be better understood in relation to our diet.

We make decisions about purchasing food based on a number of criteria. Price and health are two crucial factors, both of which may be constrained by budgets, or limits - that is, our finances and responses to the Guideline Daily Amount (GDA) of crucial nutrients. Each purchase takes up a part of our financial and GDA "budget", which becomes our main decision making criteria. It may help, therefore, to be able to understand the environmental impact of our food in a similar manner.

The carbon, water and land footprints of our food can be highly complicated issues. However, in terms of decision making the crucial factor is knowing how much of each we are "allowed" to use (our budgets) and what contribution each food item contributes. To this end, we can estimate nutritionally equivalent carbon, water and land GDAs for Quorn, beef and chicken. The relative impacts of each may therefore be properly compared against or each other.

For the first time, we show how the environmental budgets available to us may be understood across multiple impacts. It becomes very straightforward to compare choices across GHG, water and land without taking the risk that a reduction in one area leads to an increase elsewhere or a loss of nutritional value. In terms of Quorn’s decision-making, we anticipate that this framework will help understanding of the relative importance of carbon, water and land impacts. For example, in understanding which area is *really* the most significant and helping to manage interactions. We can help Quorn to understand their impacts in relation to global water availability, a safe GHG emission target and land availability. In addition, the environmental impact of Quorn used as a protein replacement for beef and chicken can also be compared to their impacts.

An interesting aside is that a much larger proportion of the land and water impact of beef and chicken occurs outside the UK (in feed production) compared to Quorn (some potential overseas impact from egg and sugar).

14 References Bord Bia. (2014, April 14). Retrieved from Bord Bia - Origin Green: http://origingreen.fusio.net/

Chatterton, J., & Hess, T. a. (2010). The Water Footprint of English Beef and Lamb Production. EBLEX.

Cohn A, B. M. (2011). The viability of cattle ranching intensification in Brazil as a strategy to spare land and mitigate greenhouse gas emissions. CGIAR.

DairyUK and DairyCo. (2010). Guidelines for the carbon footprinting of dairy products in the UK. DairyUK, DairyCo. Retrieved from Dairy Guidelines.

DEFRA. (2014, March 19). Structure of the agriculture industry. Retrieved from GOV.UK: https://www.gov.uk/government/collections/structure-of-the-agricultural-industry

EBLEX. (2011). Making grass silage for better returns.

EBLEX. (2012). Down to Earth - The beef and sheep roadmap, phase 3. EBLEX.

EBLEX. (2013). Water use, reduction and rainwater harvesting on beef and sheep farms. EBLEX. Retrieved from http://www.eblex.org.uk/wp/wp-content/uploads/2013/11/BRPplus- rainwater-factsheet141113.pdf

Gerber, P. S. (2013). Tackling climate change through livestock – A global assessment of emissions and mitigation. Rome.

IDF. (2010). A common carbon footprint approach for dairy - The IDF guide to standard lifecycle assessment methodology for the dairy sector. Brussels: International Dairy Federation.

MacLeod, M. G. (2013). Greenhouse gas emissions from pig and chicken supply chains – A global life cycle. Rome: FAO.

Meier, T., Christen, O., Semler, E., Jahreis, G., Voget-Kleshin, L., & Schrode, A. a. (2014). Balancing virtual land imports by a shift in the diet. Using a land balance approach to assess the sustainability of food consumption. Food Policy, 20-34.

Mekonnen, M. a. (2010). The green, blue and grey water footprint of crops and derived crop products. UNESCO-IHE. Retrieved from Water Footprint Network.

Mekonnen, M. a. (2012). A Global Assessment of the Water Footprint of Farm Animal Products. Ecosystems.

Opio, C. G. (2013). Greenhouse gas emissions from ruminant supply chains – A global life cycle. Rome.

Pelletier N, P. R. (2010). Comparative life cycle environmental impacts of three beef production strategies in the Upper Midwestern United States. Agricultural Systems, 103, 380-389.

Pocketbook. (2013). John Nix Farm Management Pocketbook 2013. Pocketbook.

Williams, A., & Audsley, E. a. (2006). Determining the environmental burdens and resource use in the production of agricultural and horticultural commodities. DEFRA.