The effect of methodology on estimates of greenhouse gas emissions from grass-based dairy systems

Agriculture, Ecosystems and Environment 141 (2011) 39–48

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The effect of methodology on estimates of greenhouse gas emissions from grass-based dairy systems D. O’Brien a,b , L. Shalloo a,∗ , F. Buckley a , B. Horan a , C. Grainger a , M. Wallace b a b

Livestock Systems Research Department, Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland School of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland

a r t i c l e

i n f o

Article history: Received 17 May 2010 Received in revised form 21 January 2011 Accepted 6 February 2011 Available online 4 March 2011 Keywords: Greenhouse gas Life cycle analysis Intergovernmental Panel on Climate Change method Holstein-Friesian strain Grass-based

a b s t r a c t The objective of this study was to compare two standard methodologies, Intergovernmental Panel on Climate Change (IPCC) method and life cycle analysis (LCA), for quantifying greenhouse gas (GHG) emissions from dairy farms. Both methods were applied to model the GHG emissions from 9 dairy farm systems differing in strain of Holstein-Friesian cow and type of grass-based feed systems using the physical performance findings of previously published work. The strains of Holstein-Friesian cow used were; high milk production North American (HP), high fertility and survival (durability) North American (HD), and New Zealand (NZ). The alternate grass-based feed systems were; high grass allowance (HG, control); high stocking rate (HS) and high concentrate supplementation (HC). The milk production systems were modelled using a previously developed integrated economic-GHG farm model. The model calculated GHG emissions using the LCA approach and was extended to quantify GHG emissions using the IPCC method. The study found that the method of reporting GHG emissions (per unit of product or per unit area) affected the ranking of emissions of dairy systems investigated. Greenhouse gas emission were greater when calculated using the LCA method rather than the IPCC method. Both methods found reducing inputs or the intensity of dairy production reduced GHG emissions per hectare. When emissions were expressed per unit of product the methodologies did not rank farming systems in the same order. The effect of feed system on emissions per unit of product was inconsistent between methodologies because the IPCC method excludes indirect GHG emissions from farm pre-chains, i.e. concentrate production. Both methodologies agreed that animals selected solely for milk production (HP) had higher GHG emissions per unit of product relative to strains selected on a combination of traits. The results indicate that if dairy systems targeting a net reduction in global GHG for projected increases in meat and milk production are to be developed, a holistic approach such as LCA, should be used to assess emissions on a per unit product basis. © 2011 Elsevier B.V. All rights reserved.

1. Introduction The production of greenhouse gas (GHG) from livestock activities and their impact on climate change are becoming a major concern worldwide. Globally, livestock activities are estimated to be responsible for 18% of total anthropogenic GHG emissions (Steinfeld et al., 2006). Dairy farming is a major contributor to global livestock emissions (FAO, 2010). Thus, reducing emissions from dairy systems will be essential for some nations attempting to meet Kyoto requirements and the targets of any future international treaty. Consequently, a number of mitigation strategies such as the application of nitrification inhibitors (Dobbie and Smith, 2003), anaerobic digestion of stored manure (Amon et al., 2006) or

∗ Corresponding author. Tel.: +353 25 42306; fax: +353 25 42340. E-mail address: [email protected] (L. Shalloo). 0167-8809/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.agee.2011.02.008

supplementation of livestock diets with protein hormones (Capper et al., 2008) have been suggested to reduce GHG emissions from dairy farms. However, many proposed mitigation strategies have only been assessed by considering on-farm emissions. Greenhouse gas mitigation strategies can effect GHG emissions both on and offfarm (Weiske et al., 2006) and this can alter the overall net benefit of any strategy. Consequently, the evaluation of effective mitigation strategies will only be globally beneficial if carried out using a holistic or full accounting approach. Presently, the standard methodology used for accounting of GHG emissions from all activities (including dairy farming) at the local level is the Intergovernmental Panel on Climate Change (IPCC) method (Bastianoni et al., 2004). However, the IPCC method was developed to prepare transparent and simple inventories on a national scale and not to determine emissions or assess strategies to reduce emissions on a lower scale such as at the farm level (Schils et al., 2006). Recognising this issue, some researchers have used

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D. O’Brien et al. / Agriculture, Ecosystems and Environment 141 (2011) 39–48

Table 1 Milk production, BW, and reproductive performance for 3 strains of Holstein-Friesian cows [high production (HP); high durability (HD) and New Zealand (NZ)] within the high grass allowance (HG), high concentrate (HC) and high stocking rate (HS) feed systemsa . Item

HG NZ

No. of lactation records Milk production Milk, kg cow−1 Fat, g kg−1 Protein, g kg−1 Lactose, g kg−1 Average BW, kg Reproductionb Gestation length, d 42-d in-calf rate, % Overall pregnancy rate, % Total services per cow a b

HS HD

HP

HC

NZ

HD

HP

NZ

HD

HP

65

65

65

65

65

65

65

65

65

6335 43.9 36.5 46.7 552

6656 40.9 35.6 46.6 590

6748 40.6 34.5 46.3 558

6255 45.6 36.1 46.6 542

6527 41.1 35.5 46.7 580

6531 41 34.8 46.6 551

6597 44.5 37.2 47.5 541

7588 40.1 35.8 47.1 594

7724 40 35.4 47.7 564

278 74 93 1.61

284 65 86 1.79

284 54 74 2.07

278 74 93 1.61

284 65 86 1.79

284 54 74 2.07

278 74 93 1.61

284 65 86 1.79

284 54 74 2.07

McCarthy et al. (2007). Breeding was initiated at, on average, 60 days in milk.

alternative approaches to quantify GHG emissions and to assess GHG mitigation strategies at the farm level (Casey and Holden, 2005a; Lovett et al., 2006; Olesen et al., 2006). The most popular alternative method used is life cycle analysis (LCA). Unlike the IPCC method, LCA is not obliged to confine the accounting of GHG emissions by sector or geographical boundaries. Instead, the accounting of emissions is restricted by the definition of system boundaries. This allows a holistic analysis of GHG emissions, which is not possible within the framework of the IPCC method. Typically when LCA is employed to assess GHG emissions from dairy farming, the system boundaries are defined to assess GHG emissions from all processes up to the point milk leaves is sold from the farm (Casey and Holden, 2005a; Cederberg and Mattsson, 2000). This is commonly referred to as a cradle to farm gate LCA. As a result of this definition, emissions from processes involved in the production of external inputs such as concentrate feeds and fertilizer are considered part of the dairy farm. This approach may increase emissions from the dairy farm, but ensures the net effect of on-farm mitigation strategies is a reduction in total GHG emissions. The objective of this study was to compare different farming systems using the IPCC and the LCA methodologies and to quantify the effect of farming system and accounting methodology on GHG emissions from pastoral dairy farms. The dairy systems assessed varied in strains of Holstein-Friesian cow (differing in milk production potential) and type of pasture-based feed system (differing in stocking rate and level of concentrate per cow). 2. Materials and methods 2.1. Production study details The GHG emissions of 9 contrasting pastoral dairy production systems, differing in strain of Holstein-Friesian and type of pasturebased feed system were quantified. The design of the study and production and reproduction data used in the analysis (Table 1) was previously reported by Horan et al. (2004, 2005) and McCarthy et al. (2007). In short, 3 strains of Holstein-Friesian cows; highproducing North American (HP), high-durability North American (HD) and New Zealand (NZ) were compared. The HP strain represented animals selected solely for milk production. In contrast, the HD strain represented a breeding program where selection was based on improving a number of traits simultaneously; including milk production, fertility and muscularity. The NZ strain represented the highest possible genetic merit expressed in the New Zealand genetic evaluation system (Breeding Worth). The genetic potential of each strain for each trait of economic importance has been reported (McCarthy et al., 2007).

Cows within strain were blocked and randomised across 3 grassbased feed systems; high grass allowance system (HG, control); high concentrate supplementation system (HC) and a high stocking rate system (HS) (Table 1). The HG system had an overall stocking rate of 2.47 cow’s ha−1 , N fertilizer input of 290 kg of N ha−1 and received 325 kg of dry matter (DM) concentrate per cow in early lactation. The HC system had a similar overall stocking rate and N fertilizer input as the HG system, but 1445 kg of DM concentrate was offered per cow per lactation, with a greater proportion in early spring. The HS system had a similar concentrate and N input as the HG system, but had an overall stocking rate of 2.74 cow’s ha−1 . Both the HG and HC systems were designed to allow each strain to express its potential within each feed system largely unaffected by limitations in feed supply. This did not apply in the HS system where the aim was to reduce the feed allowance by increasing stocking rate, resulting in a lower post grazing sward surface height than either the HG or HC systems. 2.2. Modelling greenhouse gas emissions 2.2.1. LCA methodology The GHG emissions of the dairy production systems described were quantified using LCA. The LCA method was applied using the GHG model (Fig. 1) developed by O’Brien et al. (2010) and this approach is hereafter referred to as LCA-refined. The system boundaries of the GHG model were defined to include all emissions associated with the dairy production system up to the point where milk is sold from the farm. The GHG model operates in combination with the Moorepark Dairy System Model (MDSM) (Shalloo et al., 2004a), which is a whole farm simulation model. The MDSM defines key input parameters (land area, animal inventory, milk production, feed intakes, herbage quality, grazing season length, slurry, fertilizer and lime application) required for the GHG model to quantify emissions. The default parameters of the MDSM (Table 2) were obtained from the results of experiments conducted in Moorepark over recent years (Dillon et al., 1995; Horan et al., 2005; McCarthy Table 2 Default parameters of the modelled farm. Item Farm size, ha Gross milk price, c kg−1 Price ratio of protein to fat Replacement heifer price, D Culled cow price, D Labour costs, D month−1 Concentrate costs, D t−1

38.8 27.0 2.6 1540 270 1905 200

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Fig. 1. Operational diagram of greenhouse gas (GHG) model. Moorepark Dairy System Model (MDSM) provides key parameters for GHG model which are integrated with emission factors to calculate emissions according to the IPCC and LCA methods. Refined emission factors are country specific emission factors.

et al., 2007). The MDSM assumes that the farm area was fixed at 38.8 ha. Therefore, when 38.8 ha is fully utilized any further expansion is achieved using purchased feed. The MDSM assumes that all male calves are sold and replacement heifers are reared on farm from birth. Feed energy requirements are calculated in the MDSM based on the net energy (NE) required for milk production, maintenance and body weight (BW) change (Jarrige, 1989). The GHG model calculates emissions by combining the parameters from the MDSM with specific GHG emission factors (Tables 3 and 4) in Microsoft Excel. Where possible, emission factors for on-farm GHG sources (i.e. enteric fermentation) were obtained from studies completed in relevant temperate grassland systems (Chadwick et al., 2000; Mills et al., 2003). Otherwise, default (tier 1) emission factors were used (IPCC, 2006). The emission factors for

indirect sources (emissions from ammonia, nitrate leaching and farm pre-chains, i.e. fertilizer production) were mainly obtained from European literature (Table 4). Greenhouse gas emissions from concentrate production were calculated using LCA software, Simapro (Pre Consultants, 2008). Greenhouse gas removal from farm sinks; soil carbon sequestration and pastoral photosynthesis were excluded in the GHG model. Carbon sequestration was excluded because most pastures within Ireland are semi or permanent pasture where the long term carbon flux from the soil is most likely to be in equilibrium. Pastoral photosynthesis was not considered because these simulations are based on productive grasslands where carbon fixing through photosynthesis would approximate that of carbon oxidation through senescence and decay.

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Table 3 The emission factors used in the life cycle analysis refined approach (LCA-refineda ) for quantification of on-farm GHG emissions. Gas and source Methane (CH4 ) Enteric fermentation Dairy cows (conserved feed only) Dairy cows (grass only) Heifers Calves Slurry application FYMe spreading FYM storage Slurry storage Silage effluent Nitrous oxide (N2 O) Pastorally deposited dung Pastorally deposited urine Inorganic fertilizer application Slurry spreading FYM spreading FYM storage Slurry storage Carbon dioxide (CO2 ) Diesel combustion Lime a b c d e f

Emission factor

Unit

Reference

(1.06 + 10.27 × (dietary forage proportion) + (0.87 × DMIb )) 0.065 × GEIc 0.065 × GEI 0.065 × GEI (0.00007–0.0123)d × slurry application rate 0.0027 × FYM applied 0.000017 × FYM stored 0.0112 × slurry stored 0.165 × (silage effluent BODf )

MJ d−1 cow−1 MJ d−1 cow−1 MJ d−1 animal−1 MJ d−1 animal−1 kg m−3 g kg−1 kg m−3 d−1 kg m−3 d−1 kg 106 BOD

Mills et al. (2003) Ireland EPA (2009) IPCC (2006) IPCC (2006) Chadwick et al. (2000) Chadwick et al. (2000) Sneath et al. (2006) Sneath et al. (2006) United States EPA (1990)

0.0019 × (N in pasture dung − NH3 loss) 0.0056 × (N in pasture urine − NH3 loss) 0.01 × (N in fertilizer − NH3 loss) (0.0012–0.0097)d × slurry application rate 0.2 × (N of FYM applied − NH3 loss) 0.0004 × FYM stored 0.00001 × slurry stored

kg kg−1 N kg kg−1 N kg kg−1 N kg m−3 kg kg−1 N kg m−3 kg m−3 d−1

Yamulki et al. (1998) Yamulki et al. (1998) Brown et al. (2002) Chadwick et al. (2000) Chadwick et al. (2000) Sneath et al. (2006) Sneath et al. (2006)

2.88 × diesel use 0.44 × lime application

kg l−1 kg kg−1

Reinhardt (1993) Ireland EPA (2009)

LCA-refined = all emissions associated with the dairy production system up to the point milk is sold from the farm. DMI = dry matter intake. GEI = gross energy intake. Depending on month of application. FYM = farmyard Manure dry matter content >20%. BOD = biological oxygen demand.

The model estimates emissions of CO2 , CH4 and N2 O in terms of their 100-year global warming potentials (CO2 equivalents; CO2 equiv.), which on a weight basis relative to CO2 was set to a factor of 25 for 1 kg of CH4 and 298 for 1 kg of N2 O (IPCC, 2006). The main output of the GHG model was a static account of annual GHG emissions. The GHG model uses two LCA functional units to express annual emissions, per unit area (t CO2 -equiv., ha−1 ) and per unit of product [kg CO2 -equiv., kg−1 milk and kg CO2 -equiv., kg−1 milk solids (MS; fat and protein)]. The GHG emissions per unit of product were allocated because dairy production is multi-functional producing both milk and meat (Thomassen et al., 2008; Williams et al., 2006). Similar to previous LCA studies (Basset-Mens et al., 2009; Cederberg and Mattsson, 2000; O’Brien et al., 2010) emissions were allocated

between co-products according to biological causality. Biological causality was based on the relationship of the cow’s two outputs and use of her feed ration. The cow mainly uses feed from birth to first lactation to gain weight instead of producing milk. Thus, GHG emissions associated with the cow from birth to first lactation were attributed to meat. Greenhouse gas emissions associated with cows were attributed to milk from the beginning of her initial lactation as cows are mainly producing milk at this stage. 2.2.2. IPCC methodology The GHG emissions of dairy production systems studied by Horan et al. (2004, 2005) and McCarthy et al. (2007) were also calculated using the IPCC method. In order to calculate GHG emissions

Table 4 The emission factors used in the life cycle analysis refined (LCA-refineda ) approach for quantification of on-farm ammonia emissions and indirect GHG emissions. Gas and source Ammonia (NH3 ) Housing Manure storage Grazing excreta Slurry application FYMe application FYM storage Dirty water and silage effluent Yardf Carbon dioxide equivalent (CO2 -equiv.) Diesel Electricity Lime N fertilizer Concentrate Nitrous oxide (N2 O) Nitrate leaching Ammonia deposition a b c d e f

Emission factor

Unit

Reference

(0.012–0.034)b × luc number 0.0008 × excretion stored 2.27 + (0.0683 × annual N rate ha−1 × lu number) 0.6 × TANd slurry spread 0.76 × TAN FYM spread 0.0025 × FYM stored 0.0004 × dirty water and effluent stored 0.008 × no. of cows

kg lu−1 d−1 kg m−2 d−1 g lu−1 d−1 kg kg kg m−2 d−1 kg m−2 d−1 kg cow−1 d−1

Hyde et al. (2003) Hyde et al. (2003) Misselbrook et al. (2000) Hyde et al. (2003) Hyde et al. (2003) Misselbrook et al. (2000) Misselbrook et al. (2000) Hyde et al. (2003)

1.0062 × diesel use 0.685 × electricity use 0.03573 × lime application 6.487 × N fertilizer use 0.502 × concentrate use

kg l−1 kg kWh−1 kg kg−1 lime kg kg−1 N kg kg−1

Kramer et al. (1999) McGettigan (personal communication) West and Marland (2002) Kramer et al. (1999) Pre Consultants (2008)

0.025 × (N applied per ha × 0.1) 0.01 × (sum of NH3 sources)

kg kg−1 NO3 − kg kg−1 NH3

IPCC (2006) Mosier et al. (1998)

LCA-refined = all emissions associated with the dairy production system up to the point is sold from the farm. Dependent on age of animal. lu = livestock unit equivalent to 500 kg body weight. TAN = total ammoniacal nitrogen content. FYM = farmyard manure dry matter content >20%. Yard = ammonia from collecting yard prior to milking.

D. O’Brien et al. / Agriculture, Ecosystems and Environment 141 (2011) 39–48

43

Table 5 The IPCC-IREa emission factors for quantification of dairy farm GHG emissions. Gas and source Methane (CH4 ) Enteric fermentation Dairy cows (silage) Dairy cows (grass) Heifers Calves Manure storage

Nitrous oxide (N2 O) Manure storage Manure application Inorganic fertilizer application Grazing Ammonia Nitrate leaching a b c d e f g h

Emission factor

Unit

DEIb × (0.096 + 0.035 × (SDMI c /TDMI d )) − (2.298 × (FLe − 1)) 0.065 × GEIf 0.065 × GEI 0.065 × GEI Total manure OMg × 0.24 × 0.67 × ((prop.h at pasture × 0.01) + (prop. in slurry type system × 0.39) + (prop. in solid manure system × 0.01)).

MJ d−1 cow−1 MJ d−1 cow−1 MJ d−1 animal−1 MJ d−1 animal−1 kg yr−1

0.001 × (N stored) 0.0125 × (N in manure − NH3 loss) 0.0125 × (N in fertilizer − NH3 loss) 0.02 × (N in manure − NH3 loss) 0.01 × (sum of NH3 sources) 0.025 × (N applied ha−1 × 0.1)

kg kg−1 N kg kg−1 N kg kg−1 N kg kg−1 N kg kg−1 NH3 -N kg kg−1 NO3 − -N

IPCC = Intergovernmental Panel on Climate Change emission factors as applied in Ireland for quantification of GHG emissions. DEI = digestible energy intake. SDMI = silage dry matter intake. TDMI = total dry matter intake. FL = feeding levels above maintenance energy. GEI = gross energy intake. OM = organic matter. prop. = proportion.

according to the IPCC method the GHG model was modified. The IPCC method was implemented in the GHG model using the emission factors from the agriculture section of the Irish GHG national inventory (Ireland EPA, 2009) (Table 5) and the parameters generated by the MDSM (Table 6). This approach is hereafter referred to as IPCC-IRE. The methodology only reports GHG emissions and removals from the sources and sinks that are considered relevant by the IPCC for dairy farming; enteric fermentation, manure management and agricultural soils (Schils et al., 2005). The emission factors used are approved by the IPCC and vary with level of detail, which the IPCC refer to as tiers. Currently, in Ireland, tier 1 emission factors are used to calculate emissions from agricultural soils and tier 2 emission factors are used for enteric fermentation and manure management (Ireland EPA, 2009). Tier 1 emission factors are global default emission factors and are a simplified approach to calculating emissions and removals when minimal data are available. Tier 2 and 3 emission factors are based on more advanced methods for estimating emissions and removal, and on the use of national or

regional parameters that accommodate the specific national circumstances (IPCC, 2005). The IPCC method reports emissions on a sectoral or national basis. Thus, GHG emissions quantified using the IPCC-IRE method were expressed per unit area. The IPCC-IRE method quantified GHG emissions from cows only as it is not clear whether or not emissions from replacement animals are attributed to dairy producers. Emissions were also quantified per unit of product in order to test the effect of methodology. All emissions were attributed to milk when emissions were calculated per unit of product. In order to complete a full comparison and disentangle the effect of emission factors, sensitivity analysis was conducted for both methods. Sensitivity analysis of the LCA method was completed using IPCC emission factors (Table 5) where appropriate. The approach is referred to as LCA-IRE. Sensitivity analysis of the IPCC-IRE approach was performed in the GHG model using country specific emission factors from Tables 3 and 4 where relevant. This approach is referred to as IPCC-refined.

Table 6 Moorepark Dairy System Modela (MDSM) outputs in a fixed land area scenario (38.8 ha) for 3 strains of Holstein-Friesian cows [high production (HP); high durability (HD) and New Zealand (NZ)] within the high grass allowance (HG), high concentrate (HC) and high stocking rate (HS) feed systems. Item

No. of dairy cowsb No. of calvesb No. of followersb Stocking rate, livestock units ha−1 Pasture intake, kg DM cow−1 yr−1 Silage intake, kg DM cow−1 yr−1 Concentrate intake, kg DM cow−1 yr−1 Total intake cow−1 , kg DM yr−1 Herd pasture intake, t DM yr−1 Herd silage intake, t DM yr−1 Herd concentrate intake, t DM yr−1 Herd total feed intake, t DM yr−1 Milk yield, kg cow−1 yr−1 Milk yield, kg farm−1 yr−1 Milk solids, kg farm−1 yr−1 a b

Shalloo et al. (2004a,b). Average animal numbers.

HG

HS

HC

NZ

HD

HP

NZ

HD

HP

NZ

HD

HP

79.7 22.8 14.6 2.36 3892 1003 320 5215 345 93 35 474 6350 498,132 39,514

75.9 26.1 18.0 2.30 3950 1073 320 5342 343 99 36 477 6678 498,745 37,693

70.6 33.1 24.8 2.27 3891 1155 320 5366 333 107 38 478 6774 469,336 35,355

88.1 25.2 16.2 2.62 3865 991 321 5177 380 102 39 521 6270 543,928 43,665

82.5 28.4 19.6 2.56 3867 1054 320 5240 366 106 39 511 6550 531,786 40,046

76.8 36.1 27.1 2.56 3780 1142 320 5242 354 116 42 511 6555 493,905 36,957

92.0 26.3 16.9 2.75 3277 882 1363 5521 342 97 137 576 6614 599,403 48,724

81.9 28.2 19.4 2.58 3549 979 1367 5895 337 99 125 561 7615 614,935 45,695

77.0 36.1 27.1 2.56 3478 1032 1376 5886 330 108 124 562 7753 587,078 43,781

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D. O’Brien et al. / Agriculture, Ecosystems and Environment 141 (2011) 39–48

Table 7 The IPCC-IRE and LCA-refined GHG emissions (CO2 -equivalents; CO2 -equiv.) calculated using a GHG model in a fixed land scenario (38.8 ha) for 3 strains of Holstein-Friesian cows [high production (HP); high durability (HD) and New Zealand (NZ)] within the high grass allowance (HG), high concentrate (HC) and high stocking rate (HS) feed systems. Methoda

GHG measure

−1

kg CO2 -equiv., kg

−1

kg CO2 -equiv., kg

milk MS

t CO2 -equiv., ha−1

b

IPCC-IRE LCA-refined IPCC-IRE LCA-refined IPCC-IRE LCA-refined

HG

HS

HC

NZ

HD

HP

NZ

HD

HP

NZ

HD

HP

0.901 1.001 11.35 12.62 11.57 14.10

0.886 0.983 11.73 13.01 11.39 14.18

0.899 1.000 11.93 13.28 10.88 14.26

0.897 0.986 11.18 12.28 12.57 15.18

0.883 0.973 11.72 12.92 12.10 14.97

0.907 1.003 12.10 13.41 11.54 15.04

0.874 1.017 10.76 12.51 13.50 17.24

0.813 0.942 10.92 12.67 12.88 16.75

0.814 0.945 10.92 12.68 12.31 16.85

a Method: IPCC-IRE = IPCC method as applied in Irish national inventory for quantification of GHG emissions associated with cows only (Ireland EPA, 2009). LCA-refined = all emissions associated with the dairy production system up to the point milk is sold from the farm quantified using refined emission factors from Tables 3 and 4. Greenhouse gas emissions were biologically allocated between milk and meat using the LCA-refined method. Emissions were not allocated when quantified per unit area. b MS = kilogram of milk fat plus protein.

3. Results

strain in the HS feed system (23%) and lowest for the NZ strain in the HC feed system (17%).

3.1. MDSM outputs for the dairy farming systems 3.2. Dairy systems greenhouse gas emissions The ratio of non-productive animals to dairy cows was 18%, 24% and 35% for the NZ, HD and HP strains, respectively (Table 6). The high ratio of non-productive animals to dairy cows resulted in the HP strain having the lowest farm annual milk yield (kg milk farm−1 yr−1 ) and MS (kg milk solids farm−1 yr−1 ) in all feed systems. This is despite the HP strain having the highest milk yield per cow. The NZ and HD strains had similar farm milk yields but the NZ strain had the highest farm MS yield. The annual farm milk and MS yield for the 3 grass-based feed systems increased in the order HG to HS to HC. The highest farm milk yield occurred when the HD strain was in the HC feed system and highest farm MS yield occurred when the NZ strain was in the HC feed system. Herd total feed intake (kg DM yr−1 ) for the 3 pasture-based systems increased in the order HG to HS to HC (Table 6). Cow strain had little effect on total herd feed intake. The lowest total herd feed intake occurred when the NZ strain was in the HG feed system (474 t DM yr−1 ) while the highest occurred with the NZ strain in the HC feed system (576 t DM yr−1 ). The percentage of the total herd feed intake obtained from concentrate was approximately 8% in the HG and HS feed systems and rose to a maximum of 24% for the NZ strain in the HC feed system. The percentage of the total herd feed intake being provided from silage was highest for the HP

3.2.1. Methodology comparison The GHG emissions of 9 dairy farming systems, calculated by the GHG model, using the IPCC-IRE and LCA-refined methods are shown in Table 7. Using the LCA-refined approach 9%, 11% and 15% of emissions per unit of product were apportioned to meat for the NZ, HD and HP strains, respectively. The LCA-refined approach increased GHG emissions per unit of product by 10–16% compared to the IPCC-IRE method and by 21–37% per unit area .The methodologies ranked dairy farms GHG emissions per kg of milk in the same order two out of nine times (Table 7). When emissions were estimated per kg of MS, the methods ranked GHG emissions in the same order four times. The ranking of GHG emissions per ha was inconsistent between methods (<30%). The ranking of emissions per unit area and per unit of product were inconsistent for both methods (Table 7). 3.2.2. Influence of feed system and strain of cow The IPCC-IRE approach found that when averaged across the 3 strains, GHG emissions per unit of product for the HG and HS feed systems were similar, but the HC feed system had lower emissions (Table 7). The NZ strain produced the highest emissions per kg of

Table 8 The percentage contribution of sources to dairy farm GHG emissions calculated using the LCA-refined and IPCC-IRE approaches in the GHG model for 3 strains of HolsteinFriesian cows [high production (HP); high durability (HD) and New Zealand (NZ)] within the high grass allowance (HG), high concentrate (HC) and high stocking rate (HS) feed systems. Methoda and source

LCA-refined Enteric fermentation Manure storage and spreading Manure deposited on pasture Synthetic fertilizer production Synthetic fertilizer application Concentrate production Energy and lime use Energy and lime production Ammonia deposition and Nitrate leaching IPCC-IRE Enteric fermentation Manure storage Manure spreading Manure deposited on pasture Synthetic fertilizer application Ammonia deposition and nitrate leaching

HG

HS

HC

NZ

HD

HP

NZ

HD

HP

NZ

HD

HP

51.62 11.45 2.07 12.09 8.14 3.25 2.67 2.77 5.95

51.34 11.67 2.08 12.11 8.15 3.29 2.65 2.76 5.96

50.78 12.31 2.06 12.05 8.11 3.49 2.62 2.63 5.94

52.73 11.67 2.13 11.30 7.60 3.34 2.56 2.76 5.91

52.13 11.97 2.09 11.47 7.72 3.39 2.57 2.75 5.91

51.53 12.58 2.06 11.45 7.71 3.61 2.54 2.61 5.90

50.34 10.43 1.99 9.93 6.68 10.32 2.30 2.62 5.39

50.07 10.68 2.00 10.23 6.88 9.70 2.32 2.73 5.41

49.96 11.13 1.95 10.22 6.88 9.55 2.29 2.63 5.39

55.50 10.97 1.90 14.09 11.29 6.26

55.14 11.21 1.95 14.08 11.31 6.31

54.88 11.48 2.02 14.01 11.26 6.35

56.07 11.07 1.93 14.35 10.45 6.14

55.78 11.29 1.97 14.14 10.63 6.19

55.31 11.66 2.05 14.07 10.64 6.26

57.45 10.92 1.88 14.14 9.71 5.91

57.19 11.03 1.89 13.99 9.95 5.95

56.95 11.29 1.95 13.85 9.97 5.99

a Method: LCA-refined = all emissions associated with the dairy production system up to the point milk is sold from the farm quantified using refined emission factors from Tables 3 and 4. IPCC-IRE = IPCC method as applied in Irish national inventory for quantification of GHG emissions (Ireland EPA, 2009).

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Table 9 Sensitivity analysis of GHG emissions (CO2 -equivalents; CO2 -equiv.) calculated according to the IPCC-refined and LCA-IRE approaches in a fixed land scenario (38.8 ha) for 3 strains of Holstein-Friesian cows [high production (HP); high durability (HD) and New Zealand (NZ)] within the high grass allowance (HG), high concentrate (HC) and high stocking rate (HS) feed systems. Methoda

GHG measure

−1

kg CO2 -equiv., kg

−1

kg CO2 -equiv., kg

t CO2 -equiv., ha−1

milk MS

b

IPCC-refined LCA-IRE IPCC-refined LCA-IRE IPCC-refined LCA-IRE

HG

HS

HC

NZ

HD

HP

NZ

HD

HP

NZ

HD

HP

0.792 1.109 9.99 13.97 10.17 15.63

0.778 1.092 10.30 14.44 10.01 15.73

0.792 1.107 10.52 14.70 9.59 15.77

0.790 1.094 9.83 13.63 11.07 16.84

0.776 1.079 10.30 14.33 10.63 16.60

0.801 1.110 10.70 14.81 10.19 16.62

0.762 1.131 9.37 13.91 11.77 19.17

0.707 1.049 9.50 14.10 11.20 18.65

0.710 1.049 9.52 14.05 10.74 18.69

a Method: IPCC-refined = IPCC method applied using refined emission factors from Tables 3 and 4 where relevant to quantify emissions associated with cows only. LCAIRE = all emissions associated with the dairy production system up to the point milk is sold from the farm quantified using refined emission factors from Tables 3 and 4 and IPCC emission factors from Table 5 where relevant. Greenhouse gas emissions were biologically allocated between milk and meat using the LCA-IRE method. Emissions were not allocated when quantified per unit area. b MS = kilogram of milk fat plus protein.

milk on average across the 3 feed systems, while the HD strain produced the lowest emissions. Emissions per kg of MS on average across the 3 feed systems were lowest for the NZ strain and highest for the HP strain. For the HP strain, the least emissions were produced per unit of product in the HC feed system and highest in the HS feed system. For the HD strain, the least emissions per unit of product was in the HC feed system and highest in the HG and HS feed systems. The NZ strain achieved their least emissions per unit of product in the HC feed system and highest emissions in the HG feed system. The LCA-refined method found on average across the 3 strains that the HC feed system produced the lowest emissions per unit of product, with the HG and HS feed systems producing the highest (Table 7). Average emissions per kg of milk across feed systems were lowest for the HD strain and highest for the NZ strain. On average emissions per kg of MS across feed systems were lowest for the NZ strain followed by the HD strain and the HP strain. For the HP strain the least emissions per unit of product were produced in the HC feed system and highest in the HS feed system. For the HD strain the least emissions per unit of product was in the HC feed system and highest in the HG feed system. The NZ strain achieved their least emissions per unit of product in the HS feed system. The NZ strain produced their highest emissions per kg of milk in the HC feed system and highest emissions per kg of MS in the HG system. Both methodologies found that GHG emissions per unit area for the 3 pasture-based feed systems increased in the order HG to HS to HC (Table 7). Strain had a modest effect on emissions when calculated using the LCA-refined method. The IPCC-IRE method found the NZ strain produced the highest emissions per ha on average across the 3 feed systems, while the HD strain had the lowest emissions. Both methods found the highest emissions per ha occurred when the NZ strain was in the HC feed system The LCA approach found the NZ strain in the HG feed system produced the lowest emissions per ha, but the IPCC method disagreed and found it was the HP strain in the HG feed system. 3.2.3. Contribution analysis The largest source of GHG emissions for all dairy farming systems using both methods was enteric fermentation (Table 8). The LCA-refined method found that the next most significant sources of emissions were from fertilizer production and application, and manure storage and spreading (Table 8). The LCA-refined approach found concentrate production was an important source of emissions (10%) in the HC feed system (Table 8). The IPCC-IRE approach found the largest sources of emissions excluding enteric fermentation for all dairy systems were manure deposited on pasture, manure storage and fertilizer use. The LCA-refined approach showed that the proportion of GHG emissions from indirect sources increased by 4% moving from the HG and HS feed system to the HC

feed system and that strain had little effect. The IPCC-IRE approach found neither feed system nor strain had an effect on the proportion of GHG emissions from indirect sources (Table 8). 3.2.4. Sensitivity analysis Sensitivity analysis (Table 9) of the LCA-refined approach resulted in an 11% increase in emission estimates (LCA-IRE). Emissions calculated using the IPCC-IRE approach decreased by 12–13% when country specific emission factors were used (IPCC-refined). Comparing the results of Tables 7 and 9 the LCA-IRE approach increased emissions per unit of product by 22–29% relative to the IPCC-IRE approach and the LCA-refined approach increased emissions per unit of product by 25–33% relative to the IPCCrefined method. The LCA-IRE approach increased emissions per ha by 34–52% relative to the IPCC-IRE approach and the LCA-refined approach increased emissions per ha by 37–57% relative to the IPCC-refined method. 4. Discussion 4.1. Methodology comparison: IPCC versus LCA The method of reporting GHG emissions differs between the IPCC and LCA methods. The IPCC method reports GHG emissions on a national or area basis (Casey and Holden, 2005b) whereas the latter usually reports GHG emissions per unit of product (ISO, 2006). The study found that the method of reporting GHG emissions affected the ranking of dairy systems. Similar to previous studies, our study found that extensive systems produced the lowest GHG emissions per ha relative to intensive systems (Haas et al., 2001; van der Werf et al., 2009). However, when GHG emissions are quantified on a product basis, intensive systems produce less emissions relative to extensive or organic systems (Sevenster and DeJong, 2008; Thomassen et al., 2008; Williams et al., 2006). These findings demonstrate that reducing GHG emissions on a per unit area basis could result in an unnecessary decline in food production. For instance, using the IPCC method our study shows that the HP strain produced their lowest emissions per ha in the HG feed system. Increasing the concentrate level of the HG system increased the HP strain emissions per ha by 13%, but decreased their emissions per kg of MS by 9%. Based on the IPCC method, the feed system with the lowest emissions per ha for the HP strain would be selected, but this would lead to a 9% reduction in production for the same level of emissions. Thus, adopting an area-based approach will not lead to the highest reduction in GHG emissions possible for a given level of product. If dairy production is to decrease emissions and supply sufficient milk to satisfy current and future demand, GHG emissions should be quantified per unit of product that represents the purpose of the farming system (Capper et al., 2009).

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Expressing emissions per unit of product encourages producers to improve their productive efficiency, ensuring GHG emissions would decrease for a given level of food production (Beukes et al., 2010; Lovett et al., 2008). It has been estimated that global production of milk will increase by 1.8 times from 1999–2001 to 2050 (FAO, 2006). Given this projected increase in milk production, national and global targets to reduce GHG emissions from milk should focus on reducing emissions per unit of product instead of per unit area or nationally. This would allow the concentration of milk production within specific regions where it can be produced with the least impact on GHG emissions. The IPCC approach does not quantify all emissions associated with dairy production. Consequently, GHG emissions per unit of product and per unit area were always greater using the LCA method compared to the IPCC method, which is similar to previous findings (Schils et al., 2006). Excluding GHG sources associated with dairy farming would not matter if farming systems always ranked the same when the IPCC or LCA method was used. In the current study, we found that GHG emissions per unit of product and per unit area for the HD and HP strains ranked consistently across the 3 feed systems using either method. However, the rankings were not always consistent. For example, when GHG emissions per unit of product were estimated for the NZ strain, the IPCC method found the NZ strain produced their lowest emissions in the HC system, but the LCA approach found that their lowest emissions were produced in the HS feed system. The ranking of emissions per unit of product was not consistent for the NZ strain because the IPCC method does not account for indirect GHG emissions from farm pre-chains, such as concentrate production, whereas the LCA method does include these emissions. This was also the reason for the inconsistency between methodologies for the ranking of GHG emissions per unit of product for the 9 dairy production systems. In agreement with our work Schils et al. (2006) found, in a study of dairy farms that varied in soil type and management of N fertilizer, that the method (IPCC method versus full accounting approach) used for estimating GHG emissions per kg of milk affected the ranking of dairy farms. Therefore, if the IPCC method is not reformed, the results of our study illustrate that producers could adopt farming systems which comply with policy methodology and reduction targets, but when a holistic analysis is conducted this may not be the case. Regardless of the method used in this study, the largest source of GHG emissions for dairy farms was enteric fermentation (45–65%), which is in agreement with previously reported findings (BassetMens et al., 2009; Lovett et al., 2006; Schils et al., 2005). Therefore, strategies that reduce CH4 from enteric fermentation, and do not increase other GHG emissions could result in large reductions in emissions from dairy systems. Both methods found that the remaining on-farm GHG emissions are predominately from fertilizer use and manure storage. Strategies to reduce emissions from these sources include increased N use efficiency (de Klein and Eckard, 2008; Olesen et al., 2006), increasing the length of the grazing season (Lovett et al., 2008) and anaerobic digestion (Amon et al., 2006). The IPCC method also found that GHG emissions from manure deposited on pasture was an important source of on-farm emissions. The proportion of GHG emissions from excreta deposited during grazing differed between methods because there was a four-fold difference in the emission factors used. The IPCC emission factor used for this source was the tier 1 emission factor (Ireland EPA, 2009) whereas the emission factor adopted in the LCA approach was based on recent studies conducted in the UK, New Zealand and Australia (de Klein et al., 2003; Galbally et al., 2010; Yamulki et al., 1998). The large differences in emissions measured from manure deposited on pasture highlights the potential effect of changing from tier 1 to country specific estimates. Thus, greater research should be

a priority for nations that use tier 1 emission factors for key sources. The main sources of indirect emissions from dairy farms differed between methods. The IPCC method found that NH3 deposition and NO3 − leaching were the main sources of indirect emissions because these were the only indirect emissions quantified. The LCA method found that indirect emissions were predominately from fertilizer production, but in high concentrate supplementation feed systems, concentrate production was also an important source, which is similar to the findings of Casey and Holden (2005a). Thus, both approaches show that implementing on-farm strategies to increase N use efficiency decrease indirect and on-farm GHG emissions, but the magnitude of the reduction is significantly higher using the LCA approach. The LCA approach was the only method that indicates decreasing concentrate use or using concentrate with lower emissions decreases indirect emissions. 4.2. Effect of cow strain and feed system on GHG emissions Both methods found that higher genetic potential animals for milk production caused GHG emissions per unit product to increase through a rise in emissions from non-productive animals and a consequent decrease in farm milk. The methodologies did not agree when emissions were quantified per unit area. The LCA approach found emissions per ha were similar for each strain because the total herd feed intake, the main cause of enteric CH4 emissions (Hegarty et al., 2007), was similar for each strain. The total herd feed intake was similar for the various strains, because as replacement rate increased, the feed intake of non-productive animals increased but decreased for productive animals. The IPCC method only assessed GHG associated with cows. Thus, the approach omitted the change in feed intake of non-productive animals. The increases observed in emissions per unit of product for animals with higher genetic potential for milk are similar to the findings of Lovett et al. (2006). Therefore, based on these findings, continuing to increase the genetic merit of Holstein-Friesian cows for milk yield alone will cause GHG emissions per unit of product to increase. However, if the fertility of Holstein-Friesians cows with high genetic merit for milk yield (HP strain) improved (similar to NZ strain), this could lead to substantial reductions in emissions per unit of product. In 2001 in Ireland, a selection index for dairy cattle breeding combining milk production and fertility traits for pasture-based systems was established (Veerkamp et al., 2002). It is anticipated that the use of this new index will increase farm profitability (Shalloo et al., 2004b), and based on this study, will contribute to reducing GHG emissions per unit of product. The IPCC and LCA methods both found that, reducing inputs in particular feed, reduced GHG emissions per ha. Thus, the lowest emission per ha occurred in the least intensive feed system (HG). These findings are congruous with previous studies, which investigated the effects of intensification of milk production on GHG emissions (Casey and Holden, 2005b; Thomassen et al., 2008; van der Werf et al., 2009). The effect of feed system on emissions per unit of product was not consistent between methods. The IPCC method demonstrated that within strain as concentrate level increased, GHG emissions per unit of product decreased. This agrees with the results of Lovett et al. (2006), but Lovett et al. (2006) did not use the IPCC method to estimate emissions; instead, an approach similar to LCA was used. In our study, the LCA method found increasing concentrate supplementation reduced emissions per unit of product for the HD and HP strains, but increased emissions for the NZ strain. The HC feed system reduced emissions for the HD and HP strains, because increasing concentrate supplementation of these strains resulted in a greater increase in farm milk yield (23–25%) than in emissions per ha (13–18%), regardless of method used. The substantial increase

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in milk production occurred for these strains because they had a large response to increased concentrate supplementation (Horan et al., 2005). The HC feed system increased GHG emissions per unit of product of the NZ strain using the LCA method, because the increase in milk production was less than the increase in emissions per ha. However, the IPCC method found that the opposite was the case. The divergence between methods occurred in part because of differences in system boundaries and because of the poor milk production response of the NZ strain to increased concentrate supplementation (Horan et al., 2005). Both methods agreed that the HS feed system reduced GHG emissions per unit of product for the NZ strain, but had minimal effect on the HD and HP strains. Increasing the stocking rate of the NZ strain resulted in an increase in farm milk yield that was greater than the increase in emissions per ha. The large increase in milk production occurred because this strain had a low replacement rate. In contrast to the NZ strain, the HD and HP strains had a relatively high replacement rate (Horan et al., 2005). This prevented a substantial increase in milk production and caused a similar or greater increase in emissions per ha. 5. Conclusions Our study found that when the IPCC or LCA approach was used to quantify GHG emissions per ha, reducing the intensity of dairy production reduced GHG emissions per ha. However, expressing emissions per ha does not appropriately reflect the effect different dairy systems can have on milk production. Therefore, we conclude that farming systems should be assessed per unit of product as this will result in the lowest GHG emissions for the projected increases in world meat and milk production. The IPCC and LCA methods did not rank dairy systems emissions per unit of product in the same order. This was because the IPCC method excludes indirect GHG emissions from farm pre-chains, i.e. concentrate production. Therefore, we suggest that the LCA approach be integrated into the existing IPCC framework to identify production systems with a net reduction in global GHG emissions. Acknowledgements The authors would like to acknowledge the support of Dan Lovett and John Murphy. Their contribution to an initial development of the GHG model is greatly appreciated. References Amon, B., Kryvoruchko, V., Amon, T., Zechmeister-Boltenstern, S., 2006. Methane, nitrous oxide and ammonia emissions during storage and after application of dairy cattle slurry and influence of slurry treatment. Agric. Ecosyst. Environ. 112, 153–162. Basset-Mens, C., Ledgard, S., Boyes, M., 2009. Eco-efficiency of intensification scenarios for milk production in New Zealand. Ecol. Econ. 68, 1615–1625. Bastianoni, S., Pulselli, F.M., Tiezzi, E., 2004. The problem of assigning responsibility for greenhouse gas emissions. Ecol. Econ. 49, 253–257. Beukes, P.C., Gregorini, P., Romera, A.J., Levy, G., Waghorn, G.C., 2010. Improving production efficiency as a strategy to mitigate greenhouse gas emissions on pastoral dairy farms in New Zealand. Agric. Ecosyst. Environ. 136, 358–365. Brown, L., Syed, B., Jarvis, S.C., Sneath, R.W., Phillips, V.R., Goulding, K.W.T., Li, C., 2002. Development and application of a mechanistic model to estimate emission of nitrous oxide from UK agriculture. Atmos. Environ. 36, 917–928. Capper, J.L., Cady, R.A., Bauman, D.E., 2009. The environmental impact of dairy production: 1944 compared with 2007. J. Anim. Sci. 87, 2160–2167. Capper, J.L., Castaneda-Gutierrez, B., Cady, R.A., Bauman, D.E., 2008. The environmental impact of recombinant bovine somatotropin (rbST) use in dairy production. Proc. Natl. Acad. Sci. U.S.A. 105, 9668–9673. Casey, J.W., Holden, N.M., 2005a. Analysis of greenhouse gas emissions from the average Irish milk production system. Agric. Syst. 86, 97–114. Casey, J.W., Holden, N.M., 2005b. The relationship between greenhouse gas emissions and the intensity of milk production in Ireland. J. Environ. Qual. 34, 429–436. Cederberg, C., Mattsson, B., 2000. Life cycle assessment of milk production – a comparison of conventional and organic farming. J. Cleaner Prod. 8, 49–60.

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