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Life cycle assessment (LCA) of Dairy and beef cattles
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Life cycle assessment (LCA) of Dairy and beef cattles

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Global Greenhouse gas Emissions in animal production: towards an ...

Global Greenhouse gas Emissions in animal production: towards an
Integrated life cycle sustainability assessment from Ruminant Farming Systems

Abstract
The objectives of this review were to evaluate the environmental impacts of the greenhouse gas (GHG) emissions and emissions intensity (Ei) for the small ruminants, Dairy and beef cattle livestock production systems using the life-cycle assessment (LCA) method with a system boundaries from “Cradle-to- farm-gate” and to promote the other capability of this internationally accepted approach nowadays in the agriculture world to determine weaknesses and robustness and/or the performance of the livestock production system adapted in any regions or areas of examination. This aim was illustrated using results from LCAs in the literature and from a pilot study of different production systems. The emissions were estimated using a whole farm GHGs models, based on the Intergovernmental Panel on Climate Change (IPCC) methodology with a yearly time-step. By recognizing different farming systems for ruminant species (i.e. pasture, mixed, and zero grazing). with specific reference to recent published models, outline general conclusions from application of these published models, and describe some limitations and risks associated with these approaches. Certain models were adapted (i.e. an economic optimization model, an environmental assessment model) in which it considers all significant CH4, N2O, and CO2 emissions and removals on the farm and off-farm emissions of N2O derived from nitrogen applied on the farm. This review however, shows that LCAs of different case studies currently cannot be compared directly. Such a comparison requires further international standardization of the LCA method. Nonetheless a recent collective global LCA estimated the GHG intensity of ruminant supply chains to produce 5.7 gigatonnes CO2-eq per annum representing about 80% of the livestock sector emissions. Enteric Methane CH4 was the largest contributing source of GHG accounting for 47%. N2O from soil and deposited manure accounted for a further 24%, while LUC is estimated to contribute 9% of the sector’s overall GHG emissions. However, LCAs should be performed at a large number of practical farms for each production system of interest. Application of LCA on practical farms, however, requires in-depth research to understand underlying processes, and to predict, or measure, variation in emissions realized in practice.

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Life cycle assessment (LCA) of Dairy and beef cattles Life cycle assessment (LCA) of Dairy and beef cattles Document Transcript

  • Student: Mohamed Sarhan Agris Mundus [Academic Year 2013-2014] Supervisor: Prof. MOULIN Charles-Henri Montpellier, SupAgro Table of Contents 1 Introduction…………………………………………….….……..1 2 Whole farm GHGs emissions models…….…….………3 * GHG EMISSIONS FROM BIG AND SMALL RUMINANT DAIRY AND BEEF PRODUCTION SYSTEMS IN A LIFE CYCLE ASSESSMENT (LCA) STUDIES Supervised by: Prof.MOULIN Charles-Henri 2.1 Using models for scientific research………………..3 2.2 Choice of Functional unit…….………………..…….….4 2.3 Standardization of Methodology…….……...........4 2.4 Comparison of LCA Studies…….….………..………...5 2.5 Animal Performance for combined beef and ……….milk production systems…………………….…..….….6 3 The effect of production intensification……………..7 3.1 …...Beef production systems……….…………………...7 3.1.1… Pasture and feedlot based …………….………….7 3.1.1.1 System Performance Assessment..…..…….…7 3.1.1.2 Environmental impact of farming system….9 3.1.2 …Pasture, Mixed and zero-grazing based…….10 3.1.2.1 System Performance Assessment..…..….…..10 3.1.2.2 Environmental Performance Assessment…10 3.1…….Conclusion………………………………..………………11 3.2 .……Milk production systems………….…..………..12 3.2.1.… Organic vs. conventional farming..…..….…..12 3.2.1.1..Environmental impact assessment…………..13 3.2.2.....Intensive vs. extensive farming………………..14 3.2.3.....Mitigation strategies………………………………..15 4 Conclusion…………………………………………..……………..16 5 Appendix …………………………………………..……………..17 5.1. Assembled LCA investigated studies………………17 5.2. Total GHGs CO2-eq of milk results…………….……20 5.3. Total GHGs CO2-eq of meat results…………..……21 5.4. A Whole farm GHGs models…….…………..……….22 6 References …………………………………………..…….…….25 * http://www.econlife.com/climate-change-livestock emissions
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems Global Greenhouse gas Emissions in animal production: towards an Integrated life cycle sustainability assessment from Ruminant Farming Systems Abstract The objectives of this review were to evaluate the environmental impacts of the greenhouse gas (GHG) emissions and emissions intensity (Ei) for the small ruminants, Dairy and beef cattle livestock production systems using the life-cycle assessment (LCA) method with a system boundaries from “Cradle-to- farmgate” and to promote the other capability of this internationally accepted approach nowadays in the agriculture world to determine weaknesses and robustness and/or the performance of the livestock production system adapted in any regions or areas of examination. This aim was illustrated using results from LCAs in the literature and from a pilot study of different production systems. The emissions were estimated using a whole farm GHGs models, based on the Intergovernmental Panel on Climate Change (IPCC) methodology with a yearly time-step. By recognizing different farming systems for ruminant species (i.e. pasture, mixed, and zero grazing). with specific reference to recent published models, outline general conclusions from application of these published models, and describe some limitations and risks associated with these approaches. Certain models were adapted (i.e. an economic optimization model, an environmental assessment model) in which it considers all significant CH4, N2O, and CO2 emissions and removals on the farm and off-farm emissions of N2O derived from nitrogen applied on the farm. This review however, shows that LCAs of different case studies currently cannot be compared directly. Such a comparison requires further international standardization of the LCA method. Nonetheless a recent collective global LCA estimated the GHG intensity of ruminant supply chains to produce 5.7 gigatonnes CO2-eq per annum representing about 80% of the livestock sector emissions. Enteric Methane CH4 was the largest contributing source of GHG accounting for 47%. N2O from soil and deposited manure accounted for a further 24%, while LUC is estimated to contribute 9% of the sector’s overall GHG emissions. However, LCAs should be performed at a large number of practical farms for each production system of interest. Application of LCA on practical farms, however, requires in-depth research to understand underlying processes, and to predict, or measure, variation in emissions realized in practice. Keywords: life cycle assessment, ruminant, greenhouse gases, livestock, climate change, enteric methane, Whole farm modelling, IPCC, Beef production systems, Dairy production systems, Systems analysis 1. Introduction The global livestock industry is charged with providing sufficient animal-source foods while improving the environmental sustainability of animal production (1). The livestock sector represents a significant source of greenhouse gas (GHGs, Fig.1) emissions worldwide, generating carbon dioxide (CO2) which is released from combustion of fossil fuels to power machinery, from burning of biomass, and from microbial decay related to, for example, changes in land use or in crop management and can be sequestered by transforming arable land into permanent grassland (7), methane (CH4; i.e., enteric CH4) is produced when organic matter decomposes in oxygen deprived conditions, for example, during enteric fermentation (especially in ruminants) and storage of manure (8) and nitrous oxide (N2O) is released during microbial transformation of nitrogen in the soil or in manure (i.e. Nitrification of NH4+ into NO3-, and incomplete 1|Page
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems DE nitrification of NO3- into N2) as well as during nitrate fertilizer production (9). The sector faces the difficult challenge of having to reduce its GHG emissions while responding to a significant demand growth for livestock products which will be particularly strong as it appears meat and milk in 2050 is projected to grow by 73 and 58 percent, respectively, from their levels in 2010 to supply the global population which will grow from 7.2 billion today to 9.6 billion in 2050 With emissions estimated at 7.1 gigatonnes CO2-eq per annum, representing 18% of human-induced Figure 1.Main emission pathways of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) GHG emissions (3). Current decisions related to livestock production (Boer et al., 2011) on GHG mitigation in animal production, therefore, are hindered by the complexity and uncertainty of the combined effect of GHG mitigation options on climate change and their relation with other aspects of sustainability (5).Using a life cycle assessment (LCA) approach and accounting for land-use change (LUC), (6) it is estimated that the livestock sector contributes about 18% of the total global anthropogenic GHG emissions in which Feed production and processing, and enteric fermentation from ruminants are the two main sources of emissions, representing 45 and 39 percent of sector emissions, respectively. Manure storage and processing represent 10 percent in which Beef and cattle milk production account for the majority of emissions, respectively contributing 41 and 20 percent of the sector’s emissions (13). Such a LCA enfolds the entire farming system, accounting for all changes in GHG emissions arising from a prospective mitigation practice. Often, reducing, GHG emissions in one part of a farming system can lead to an increase in emissions from another sector; a whole-systems approach avoids potentially illadvised practices based on preoccupation with a single GHG (17). However, LCA also presents significant challenges, particularly when applied to agriculture. First, the data-intensive nature of the method often requires simplification of the inherent complexity of food supply chains (21). A second difficulty lies in the fact that variation in methods and assumptions such as the choice of system boundary, functional units, and allocation techniques can affect results (4). Still The major advantage of conducting a farm-level LCA is the ability to evaluate the impact of changes in farm management in terms of the GHG intensity of meat and milk production and A major disadvantage of conducting an LCA focused only on GHG is that the analysis does not consider other potential benefits of maintaining ruminants on grasslands (15). This paper makes a global comparison of the consequences of different production systems practices adapted while pointing out their environmental footprint. However, it shows that LCAs of these different case studies currently cannot be compared directly as mentioned previously due to different characteristics, assumptions, approaches, functional unit, and algorithms used in calculations. This discrepancy among the different analyses is a major problem because one of the main applications of the LCA is benchmarking and also because one of the main steps of an LCA analysis is a comparison 2|Page
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems with the results obtained by other authors. However, this is only possible if there is a common method or, at least, a common approach to their interpretation. Nonetheless, the comparison we can make is between Beef, meat, and dairy production. In this way, it will determine the comparison of beef production systems (pasture, feedlot) and (pasture, mixed crop-livestock, zero-grazing) for lamb meat. Besides milk production systems (organic, conventional) and (intensive, extensive) farming. Finally it gives some spotlights of the mitigation strategies that could be implemented to reduce Ei and overall GHGs emissions. 2. Whole farm GHGs emissions models Whole farm GHG emissions models (Fig.2) may be categorized as systems analysis models or LCA models not only to facilitate investigation of implications of alternative production strategies on GHG emissions for the farming systems (24) and, developing and assessing mitigation policies to reduce GHG emissions from livestock system (27a). But also it ensures possible interactions with other GHGs are taken into account (34). Whole-farm models are often developed through the combination of existing sub models, which Figure 2.Basic elements of modelling GHGs in a whole-farm approach (Schils et al., 2007) may have different underlying simulation methodologies with respect to GHG, emissions can be calculated with emission factors, comparable to the IPCC1 methodology, or simulated with mechanistic (sub) models (24). While the objective of the IPCC guidelines is to model national level emissions and not to determine emissions or assess strategies to reduce emissions on a lower scale such as at the farm level (35) and, as such, variations that arise due to differences in farming systems and regions are not considered. However, these guidelines developed and published by IPCC will continue to be the primary methodology for reporting national emissions, noted that whole farm modelling approaches should not be seen as a replacement for the IPCC methodology (22). In fact a whole farm GHG emission model provide the most robust and comprehensive approach to developing and implementing effective strategies and to overcome limitations with respect to this national and sectorial approach and enables all emissions associated with production of livestock products to be calculated (27a). And, typically, this involves a cradle-to-farm gate approach (Figure.3). 2.1 Using models for scientific research Studies reviewed confirms that numerous GHGs models have been successfully developed in a way that differs according to the objectives of the raised research question. Anyhow they could be vary from a so-called ” Virtual farm conceptualization” model (e.g. HOLOS) (36) in which its strength lies in linking farm characterization and activities to algorithms (e.g. IPCC Tier 2 emission factors) besides enfolding different animal production systems (e.g. reproduction  initial growth feedlot) . In addition they could be a “whole farm economic simulation” model (e.g. Moorepark Dairy System Model or MDSM) (37) to calculate profitability of dairy farms.in which it mainly operates by selecting GHG emission factors data obtained from the results of experiments of studies completed in relevant temperate grassland dairy systems conducted in Moorepark to be integrated using the GHG model and this approach is hereafter referred to as LCA-refined. Eventually whole-farm GHG models was designed to quantify the internal flows of carbon (C) and nitrogen (N) on dairy farms and provides assessments of emissions from both the production unit and the pre-chains (e.g. Farm GHG) (12). These internal flows are represented as flows 1 The Intergovernmental Panel on Climate Change (IPCC) (33). 3|Page
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems between compartments in the farm system. The model also explicitly includes all C and N losses except for soil respiration and N2 emissions from soils. The energy use is calculated for each compartment and is converted to pre-chain emissions of CO2 and other GHGs. The pre-chain emissions are the emissions associated with imports of production goods to the farm. While the presented framework for a whole farm approach contributes to a transparent evaluation of the effectiveness and efficiency of mitigation strategies (38). Continuous development of models will allow researchers to explore feedbacks within systems that most research cannot investigate due to limitations in measurement equipment, time, and workforce (36). 2.2. Choice of functional unit In most LCAs of agricultural products, the functional unit (FU) has been initially developed to assess environmental impact defined as the mass of the product leaving the farm gate (24). Scientists working on the Carbon footprint (CF) and GHG from livestock production systems studies agree on the importance of choosing a (FU) of GHG emissions evaluations per unit of meat or milk produced for a given period of time rather than per animal unit, regardless of the quantity of product produced or the time required to produce that product (41). Because of its consequences for results interpretation as an essential concept to eliminate contradiction of the results (40). In this review the majority of studies describe emissions on (a /kg live weight or carcass weight) for beef production systems. The two exceptions to this are studies of who expressed output as bone-free meat and protein (28) (39). While for the dairy farms there are many units which can be used for the FU for the emissions (e.g., L of milk, Kg of protein, kg of fat and protein corrected milk (FPCM) and Kg of Energy Corrected Milk (ECM) (20) (24) (42). 2.3. Standardization of Methodology The CF of livestock production is difficult to define; considerable discussion exists as to the ideal methodology and metric for its quantification. Within academia, this is understandable due to the intent to validate models and methodologies to search for improved knowledge (41). However, Decisions need to be based on sound estimates. It is therefore important that the industry supports the development and use of more precise methods to calculate national inventories and the extension of inventories to developing countries not Figure 3. Flowchart of the ‘cradle to farm-gate’ (Boer et al., 2003) currently signatories to emissions reduction obligations. In the same way the industry should press for standardization of life cycle analysis methodology to overcome the confusion that currently exists (40). Comparative studies that provide insight into the relative impact of systems or production practices and thus the possibilities to improve the delta (i.e., the difference between the systems) may be far more valuable. This is especially pertinent to CF quantified via LCA studies (e.g. the beef production in the United States, Canada, Sweden, Australia, and Japan (Table 1), However, variation in methodology, boundaries, and time points for each system render direct comparisons unreliable. Therefore the need for a coordinated international methodology is very vital for LCAs studies. 4|Page
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems 2.4. Comparison of LCAs studies Much of the difference among LCA studies can be partly explained by inherent differences among the production systems investigated [4]. In the contrary [15] emphasizing that the range in GHG intensities reflects not only differences among farming systems, but also different assumptions, approaches, and algorithms in calculating emissions, so direct comparison among studies is not recommended. Nevertheless, it is possible to draw some general conclusions from these analyses.2As though an overview of recently published studies of GHG emissions from beef and dairy production systems is selected in (Tables 2) and, a schematic diagram of the hotspots of all these analysis is presented in (Fig.4). However, not all of these impact categories are considered. Only the impact categories which are typically analyzed in this review are: Global Warming Potential, climate change, Non-renewable Energy, Eutrophication potential, Acidification potential, Carbon footprint, Cumulative Energy Use. With a system performance assessment evaluating the production system by testing different scenarios. Consequently there are 16 studies for beef production systems , which do not include Research question (CF)10 (PEU)9 (CEU) (AP) Economic optimization model FU 12 (SW)8 Results Interpretation 11 of GWP parameters LCIA 7 Scenarios for 1 6 (EP)5 (NRE)4 Verification of model components Sensitivity analysis Land occupation Environmental Performance Co-product Evaluating financial or social costs Model2 Animal, Farm Management Pastoral land, Soil C balance System Performance Evaluating Production system Apportion resource use of multi-output systems Quantifying production Comparison with previous studies Model Validation Soil erosion Carbon Sequestration On/Off- pasture Intensifying production Feedlot, N fertilizer Figure 4. A schematic overview of the Hotspots of the LCA analysis (Sarhan, 2013) studies describing emissions from dairy calf to beef production systems which are generally much lower than those in beef cow systems as a result of cow GHG emissions being mostly allocated to milk production for dairy systems . In many cases, the approach used was to integrate a number of models which were then utilized to complete various components of the analysis required. For example, [13] used a farm simulation model, a feed formulation program and a nutrient budgeting model simultaneously to investigate New Zealand cattle farming systems. Similarly, [1]; [6]; and [8] used a multiple model approach to quantify GHG emissions from beef production systems. While For dairy systems, there were studies coupled two or more models for different aspects of the analysis [37] and [42] applied a whole farm GHG model to investigate European dairy farm systems 1 Research question for either (quantification, comparing between different emissions inventories); 2 Develop certain model independently or integrate sub-models together; 3 Capture, compute data to quantify actual GHGs emissions from national inventories or other literature; 4 Non-renewable Energy; 5 Eutrophication potential; 6 Acidification potential; 7 life cycle impact assessment ; 8 Solid Waste; 9 Primary Energy Use; 10 Carbon footprint; 11 Global Warming Potential; 12 Cumulative Energy Use 5|Page
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems in various regions, while [20] developed a farm level accounting method to model Dutch dairy research farm systems. Most models were single year whole farm system studies with the exception of [1] who adopted a multi-year (8year) approach using the lifespan of a breeding female as the time reference, [14] is more likely to yield a representative national value for GHG emissions from English beef production systems given the industry level farm data used. In contrast, the approach of [1] can facilitate investigation of implications of alternative production strategies on GHG emissions for the farming systems. 2.5 Animal Performance for combined milk and meat production systems Improvements in live weight gain for Irish beef production systems based on use of finishing bulls compared to steers reducing emissions by 6 and 5%/kg beef was founded by [4]; [5] (Fig.5) to be an important mitigation strategy, respectively. [10] compared grain fed feedlot systems, with high levels of animal performance, with grassland pastoral systems and found that grain fed systems had3 higher emissions while [12] found the opposite. However, the studied systems according to [10] were with different regions, breed types and, apparently, different management 1 systems (intensive US feedlot system and a traditional Figure 5. Implications of level of animal performance African pastoral system) and also the technical efficiency making it is difficult to draw definitive conclusions where the methane intensity of the pastoral mode is much larger because of the lower productivity of these systems. In the contrary [1]; [6]; [8] and [9] were conducted in the context of the 3 components of cow calf to beef production systems being, cow calf, stocker (i.e., the period between weaning and start of finishing), and the feedlot. In all cases, the cow calf phase had the highest emissions/kg product largely due to the relatively higher emissions from beef cows compared with younger non-lactating animals. In these studies, the feedlot phase had the lowest emissions with the stocker phase being intermediate. In accordance with these findings (Flysjö et al. 2012) in the study of the link between milk and beef production in LCA and CF studies of milk it is assumed that the meat from both the culled dairy cow and the raised dairy calf replaces beef meat produced in a cow-calf system (Fig.6). However, The production of 5 g meat from a cow-calf system in Europe emits 0.14 kg CO2e, which is more than the difference between the CF of the two production systems (1.13 kg CO2e for the organic system and 1.07 for the high yielding conventional system) this 2 could be explained maybe because dairy farms with Figure 6. Product flows during a lifetime of a dairy cow in Denmark high meat production can deduct a high level of CO2e from avoided beef production in less climate 1 (live weight gain; g/d) on GHG emissions for Irish suckler beef production systems (27a) (number of calves, tonnes of milk (energy corrected milk (ECM)) and meat (carcass weight (CW)) and percent of replacement and surplus calves for organic (O) and high yielding conventional (C) milk production systems) taken from (Flysjö et al., 2012) 2 6|Page
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems friendly cow-calf systems (11). In general variations in animal performance levels on GHG emissions from dairy production systems is somewhat less clear, although improved milk performance/cow can reduce emissions [4], However, if a breeding strategy aimed at improving lactational performance resulted in impaired fertility and, consequently longer calving intervals and higher culling rates, overall emissions may increase (23). This is supported by (12), who found that a reduction of 10% in replacement rate, combined with a strategy to sell surplus heifers at birth, reduced total emissions by 10%. It is apparent that a balanced breeding strategy optimizing milk production capacity while minimizing the number of non-milk producing cattle is important with regard to minimizing emissions from dairy production systems. Nonetheless, [11] recommend combined dairy and beef systems as a means of reducing the impacts of calf production, since dairy cows produce both milk and calves whereas beef cow/calf herds are maintained for calf production only. This may be due to the explanation presented by (29) that the cow–calf phase is the dominant contributor to most impact categories regardless of finishing strategy. This is largely attributable to the low fecundity of cattle compared to other species such as pigs and chickens. Since a cow will produce at most one calf per year, a mature cow is maintained (along with bulls and heifers) for every marketed animal. 3. The effect of production intensification The GHG related to both pastoral and feedlot production systems are compared with other environmental impact indicators both quantitatively and qualitatively with reference to their potential usefulness in assessing livestock systems [10]. And so LCA research has been used to account for multifunctionality of sheep farming systems (SFSs) in the CF of lambs in the Mediterranean in Spain [46], or to examine GHG intensity of conventional and organic milk production in Sweden [11], Ireland [4], and the relative importance of the cow–calf and finishing phases for the farm-gate [10]. And the environmental impacts of Japanese beef production [7].While [9] investigated the influence of management strategies on GHG emissions in conventional beef production in the US. 3.1...... Beef production systems To examine the characteristics of LCA on meat production studies is difficult because of the strong discrepancies between them (Table 3). The main reason is the different methodologies adopted. Which explains the difficulty to explain the variability of results. However, other variables were considered: production system, management practices, mitigation strategies. 3.1.1... Pasture and feedlot based beef production systems 3.1.1.1 System performance assessment 4 [8] from the Upper Midwestern US who tried to evaluate four important measures of environmental performance (CEU, ecological CF, GHG emissions, and EP) for three distinct beef production strategies when weaned calves are either: sent directly to Iowa feedlots; sent to out-of-state small-grain (wheat and other) pastures (back grounded) then finished in Iowa 1 Figure 7. GHG/kg beef live weight for feedlot and grass based 1 Finishing systems in the United States assuming either equilibrium conditions for soil organic C (grey bars) or 0.12 kg C sequestered/ha/yr for cow calf systems and 0.4 t C sequestered/ha/yr for intensive grazing (black bars) (30). 7|Page
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems feedlots; or finished on pasture and hay in Iowa. [8] Reported that GHG emissions per unit of beef were greater in pasture-finished systems (Fig.7) than in feedlot systems. In the contrary [41] explained that this result seems intuitively incorrect for two reasons, the first one because a conventional system that finishes animals on corn-based diets grown with significant fertilizer inputs, transports both feed and animals across the country, and houses animals in confinement seems to have an intrinsically greater environmental impact than a grass-finishing system and the second one [43] demonstrated that the results from a biological viewpoint are easy to explain though growth rates are considerably less in animals finished on grass, and it is difficult to achieve heavier slaughter weights; therefore, grass-finished cattle are usually slaughtered at around 486 kg at 679 days of age, compared with 569 kg at 453 days of age in a conventional system. While the intensification of the beef production of typical (NZ) sheep and beef farming systems in the study of (47) were evaluated by feeding maize silage (MS) or applying nitrogen (N) fertilizer, on two farm types differing in the proportions of cultivatable land to hill land (25% vs. 75% hill) and incorporating a beef feedlot into each of the farm types. [13] Found that Feeding MS or applying N fertilizer substantially increased the amount of beef produced per ha because MS or N helps the farmer to increase the utilization of pasture grown on farm. While intensifying production was also associated with increased total N leaching (from 11 to 14 kg N/ha) due to small annual additions of N fertilizer (<50 kg N/ha/yr) applied in autumn and late winter and GHG emissions (from 3280 to 4000 kg CO2e/ha).although, Feeding MS resulted in lower environmental impact than applying N even after taking into account the land to grow the MS. As a consequence the beef feedlot reduced environmental emissions per kg of beef produced but considerably decreased profitability due to higher capital, depreciation, and labor costs [13]. In Ireland according to this study (27b) estimated the potential effects of changing management to attain reductions in GHG emissions from a simulation of different selection of production options or scenarios by scaling a FU of live weight per year (kg CO2 kg LW yr-1) the suckler-beef system was estimated to produce 11.26 kg CO2 kg LW yr-1 and the cow phase added a significant amount to emissions and had the greatest impact when attenuated. In terms of supplementary management strategies for GHG reduction, the broad range of supplement combinations evaluated yielded no major reduction within a grassdominated system. Besides the potential to reduce GHG emissions allocated to beef production by over 30% if management moves away from using suckler herds and source cows that are essentially redundant except for the production of the beef animal. The difficulty with moving to this more efficient scenario is that the quality of beef produced may be much lower than that achieved by the specialist beef breeds [4]. In the mean while [10] expressed GHG (Table 4). Environmental impacts results (per kg beef) emissions indices in climate change compared with market values per unit of beef costs, by taking the form $/kg CO2 based on the approach of biophysical capital alteration introduced by (45) which means an ecosystem’s ability to use solar energy to maintain the biosphere’s structure and function. (Table 4), summarizes obtained convergent results of comprehensive GHG emissions analysis and the biophysical capital alteration approach, with environmental impacts of the feedlot system 1.8 times greater than that of the pastoral system in both approaches. [10] Concluding that the conventional pollution assessment has tended to find that intensive agriculture is more polluting because of N runoff and 8|Page
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems emissions related to fuel and fertilizer inputs for stock feed. While rangeland and pastoral agriculture tend to involve lower levels of conventional pollution. In contrast, most GHGs emissions analyses completed in recent years assume that the emissions intensity related to traditional agriculture is much higher than the intensive form, because lower productivity translates into higher methane emissions per unit of product. 3.1.1.2 Environmental impact of farming system Based on this research (44) demonstrated that the Japanese black cattle (Wagyu) are fed for a longer period both in the feedlot and/or pasture to obtain a higher quality beef (e.g. higher marbling score). Hence [7] investigated the environmental load of beef-fattening system in japan and found that the major source in the impact category of GWP was (2,851 kg of CO2 e) due to enteric CH4 emissions, AP from cattle wastes and EP due to ammonia emissions from animal management (i.e., cattle Figure 8. Effects of feeding length on each environmental impact category barn, cattle manure in the stage of waste treatment) and treated the matter of production intensification from the point of view of the feeding length because the feed production had the highest impact on the system. Therefore [7] concluded that shortening feeding length had fewer environmental impacts in all categories taken into account in this study (Fig.8). In such a way that shortening feeding length by 1 mo decreased the environmental impacts of AP and EP by 4.5%, and decreased the impacts of GW and CEU by 4.1% reduction. The quantities of this emission and the energy use were mainly due to the feed intake of cattle, which increases until 17 month of age in response to the growth of cattle and declines to 65% of the maximum in the last 6 mo of fattening. However, a longer feeding length makes cattle heavier, causing an increase in beef yield [7]. While the shorter feeding length (by 2 mo) had a smaller environmental impact per unit weight of beef (e.g. feeding cattle until 28 and 26 mo of age were 20.6 and 19.7 kg of CO2e) and so Defining the FU as 1 kg of beef provides an answer for this problem because in this study FU was defined as one animal which proves the necessity of fixing FU (31).5GHG emissions was evaluated through computer (Table 5). Annual GHG emissions in CO2e per product 1 spreadsheets scenarios from U.S. beef and dairy livestock systems from nine locations (48) and the Cattle beef systems of the cow-calf herd emitted the most (Table 5) due to the smaller CH4 coefficient and feedlot cattle the least enteric CH4 and N2O per unit product. However, stocker cattle emitted the most and cow-calf the least total GHG CO2e per head. CO2 emissions per unit product were the least for the cowcalf and greatest for the feedlot scenarios due primarily to the energy expended in the cultivation and processing of grains and transportation of grain and cattle [9]. These final results were obtained also on a Canadian simulation studies simulated over an 8-year production cycle in western Canadian farms (17). Where the cow–calf system accounted for about 80% of total GHG emissions and the feedlot system for only 20% and about 84% of enteric CH4 was from the 1 a: Product is kg live weight gain; b: Product is kg milk; The "stocker" segment was comprised of cattle between weaning and feedlot placement; (Mean±SD) for US livestock systems 9|Page
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems cow–calf herd (Fig.9), mostly from mature cows. The lower CH4 emission from this system is due mainly to its relatively brief duration and, to a lesser extent, to the use of grain-based finishing rations. Despite all these findings, the authors demonstrate how these systems can have many ancillary environmental benefits, by affording wise use of grazing and forage lands. Such lands not only preserve soil C reserves, thereby withholding CO2 from the air, but also have many other ecosystem services including the conservation of biodiversity, water quality, wildlife habitat, and aesthetic value [1]. Figure 9. Source of GHG emission CO2e for a beef farm 3.1.2... Pasture, Mixed, and Zero-grazing beef production systems 3.1.2.1 System performance assessment [9] Studied the adaptation of the production systems required to maximize revenue in response to changes in economic scale (26). For instance Farm D: continued with the same number of calving’s and the same intensive beef production system (17month-old young bulls). However, not all cull cows are fattened, as 57% are sold as store animals and the fattened heifers are all sold at 31 months of age, these herd management adjustments result in a 3% drop in total beef production and free Figure 10.Farm income, NRE consumption, and GHG up 3.6 ha of land for crop farming. Cattle revenue therefore falls emissions for 2012 in comparison to 2006 2% (-1885 euros) while cash crop revenue surges 62% (+7410 euros). Thus there is a 4% increase in overall farm revenue. In the contrary Farm E: mirroring farm D, the economic optimization to the 2012 time horizon cuts back on meat production (-11%) in favor of cash crops. The number of calving’s is kept stable, but only 25% of cull cows are fattened and the males are sold 6 months earlier than in 2006. All the scenarios (Fig.10), run highlighted, system adjustments designed to minimize the drop in income % (except at farm E which enjoys greater flexibility due to its available tillable area), have only a very limited impact on NRE consumption and GHG emissions. Besides Fuels and lubricants were the main factors of NRE consumption, followed by fertilizers and farm equipments. Therefore, farms running mixed crop– livestock systems enjoy greater flexibility to adjust their farming systems than grassland-based farms enabling them to minimize the drop in income over the timeframe to 2012 (-3%) [9]. 3.1.2.2 Environmental performance assessment While the study of (46) which explored the CF in three contrasting sheep farming systems (SFSs) in the north-eastern part of Spain, i.e. a pasture-based system, a mixed sheep–cereal system, and an industrial (zero-grazing) system, accounting both for the production of meat and for the cultural ecosystem services provided (e.g. biodiversity and landscape conservation). GHGs emission per kg of lamb live weight without ES allocation among the SFSs was reversed (Table 6) with lowest values for the pasture-based system (13.9 kg CO2-eq per kg of lamb live weight) and highest for zero-grazing system (19.5 kg CO2eq per kg of lamb live weight) and, with ES allocation GHGs emission per kg of lamb live weight was highest for pasture-based (25.9 kg CO2-eq), intermediate for mixed (24.0 kg CO2-eq) and lowest for zero10 | P a g e
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems grazing system(19.5 kg CO2-eq). While the contribution of each gas to total GHGs emissions differed among SFSs according to the intensification degree, as expected the share of enteric methane emissions was the largest with contribution around 58–62% to the total emissions. Therefore, these results prove that when6CF allocated to lamb meat production only according to the intensification level, the emissions per kg of product decreased, and when accounting for the cultural ecosystem services, GHGs Emissions per kg of product increased according to their degree of intensification [14]. (Table 6). Total GHGs emissions for the three different production systems 1 While the study of (26) investigated the adaptation of the French Charolaise suckler cattle from different farming systems (Table 7) analysis with a model assessing GHGs. In overall terms, French Charolaise suckler cattle farm systems produce 14.3–18.3 tCO2eq/ton of LW produced over 1 year and from 4.77 to 7.00 tCO2eq/ha ”bovine” which are consistent with the results of [4]. Methane emissions specifically and exclusively released during ruminant farming (enteric fermentation and manure management) are the main farm-based driver of GWP at around 61% of total GWP. The least GHG-emitting farms per ton of LW produced were C (0.99 LU/ha) and D (1.38 LU/ha), which fatten all their animals and where cows account, respectively, for 45% and 46% of the livestock units (LU). Farms B (1.08 LU/ha), and E (1.22 LU/ ha), which sell all their animals as store cattle generate, respectively, 17.1 and 18.3 tCO2eq/t LW. Farm B is a grassland-based farm system with few inputs, notably using little N fertilizer, which means it generates lower N2O emissions than farm E. Because of its calf-to-weanling system and its relatively intensive production system. Farm E is the most GHG-emitting farm per ton of LW produced because it uses more inputs than B. Farm A, which produces weaners and fattened females, gives intermediate emission figures (16.6 tCO2eq/t LW). We can conclude from these results obtained from [9] that the stocking rate and therefore the quantity of live weight produced per hectare is the main driver of the GHG emissions per ha for the herd. (Table 7). GHGs for the years 2006 and 2012. tCO2e/ton of LW produced over 1 year 1 GHGs emissions (CO2-eq/kg) with or without ES allocation for lamb live weight or lamb meat and contribution (%) of CO 2, CH4 and N2O to total GHGs; ES: Ecosystem services (46). 11 | P a g e
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems 3.1 Conclusion Based on the study of Environmental consequences of different beef production systems in the EU (25) The environmental costs per kg EU beef leaving the farm gate were 16.0–27.3 kg CO2e for GWP, 101210 g SO2e for AP, 622-1651 g NO3e for EP, 41.3-59.2 MJ for NRE and 16.5-42.9 m2 year for land occupation. Of the two fattening categories, fattening based on suckler herds appeared to be less environmentally friendly than if based on intensively reared dairy calves. In terms of land use, the results (25) suggested that the dairy bull calf system is better than the suckler herd system for Beef production if potential land use change and land opportunity cost are taken into account [3]. Nonetheless red meat production in Australia (32), as well as the comparison with overseas literature, underlines the fact that varying farm operations can significantly influence the environmental performance of red meat production with other identified variables (1) the lifetime of the animals (13-33 months), (2) the regime of manure management, (3) varying IPCC conversion factors for GHGs, (4) effects from the inclusion of LUC, (5) country-specific impacts from energy production, and (6) animal breed. Whether the reduced enteric CH4 emissions from a grain diet can provide greater GHG savings than those caused by the production of the grain feed, and whether other environmental impacts from grain production such as Eco toxicity potentials will become a concern, will eventually and for most depend on the production system practiced [12]. 3.2 Milk production systems To examine the characteristics of LCA on milk production studies is difficult because of the strong discrepancies between them (Table 2). The main reason is the different methodologies adopted. Which explains the difficulty to explain the variability of results. However, other variables were considered: production system, stocking rate, milk productivity, mitigation strategies. 3.2.1 Organic vs. conventional farming Organic farming is considered much more environmentally friendly than conventional farming and several LCA studies aimed to demonstrate this hypothesis. Among those studies in the literature that have been examined there are 3 papers which compared the GHG emitted from a conventional with an organic dairy farming system. In the case of (20); (51) the GHG emission associated with organic milk was higher than that associated with conventional milk [16] and in another (28) in the organic dairy farms, the indirect emissions are lower than in conventional dairy farms, because there is a reduced use of fossil fuel for the production and transport of concentrates and chemical fertilizers [11]. On the contrary, direct emissions are higher: in particular, CH4 emission associated to 1 kg of milk increases in organic farms. Cows in organic farms are widely recognized to be less productive than cows in conventional farms. While results from other studies demonstrated that in the dairy systems approximately one-half of the total GHG CO2e were from CH4 and one-third from N2O (26) which means more CH4 than N2O on a per kg milk basis. Mitigation strategies, such as Intensive grazing according to these study conditions, location and production management system reduced the total number of CO2e per unit production or live weight gain by approximately 10% in both beef and dairy systems [9]. While the study (28) Compared GHG emissions on a whole farm or ‘life cycle’ basis for conventional and organic dairy farms in Sweden. [11] Estimated the conventional Swedish dairy system to produce 0.99 kg CO2e per kg milk similar to the study (48) of [9].without embodied costs, of 1.09 kg CO2e per kg milk. 12 | P a g e
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems 3.2.1.1 Environmental impact assessment An LCA was performed on organic (O) and conventional (C) milk production at the farm level in Sweden (28) with special focus was aimed at substance flows in concentrate feed production and nutrient flows on the farms. And this study shows that O milk production is a way to reduce pesticide use and mineral surplus in agriculture but this production form also requires substantially more farmland than C production. Concerning other environmental impacts, e.g. GWP, AP, and EP, it appears when comparing the environmental performance of C and O food production systems which have such differences in material and energy flows, land use must be assessed in both quantitative and qualitative terms. The results are shown in (Fig.11). It is evident that the use of fossil fuel is only to a minor extent connected to GWP impact category. Emissions of N2O connected to the N cycle on the farms (losses from soil) and N2O-emissions from synthetic fertilizer production play a larger part than CO2emissions from the use of fossil fuel. The most important contributor to GWP in milk production is, however, CH4. Due to the feeding strategy Figure 11. Contribution to GWP, kg CO2-eq per FU. Time horizon is 100 with a larger share of roughage fodder it is years for both (O) and (C) milk production in Swedish environment estimated that methane emissions are 10–15% higher from cows in O production compared with C production. There seems, however, to be considerable variations in the EF for CH4 from cattle. In the study of [11], emission data from the Swedish Environmentally Protection Agency (EPA) were used, estimating methane losses of 155 kg per C dairy cow and year and, because of their larger intake of roughage fodder, 12% higher emissions for the O cows. In the IPCC manual, the methane losses for High yielding cows are estimated to be considerably lower: 118 kg methane per dairy cow and year [17]. Similarly According to this Dutch’03study (20) results showed that environmental performance concerning energy use and EP per kg of milk for O farms than for C farms. Furthermore, higher on-farm acidification potential and GWP per kg O milk implies that higher ammonia (NH3), CH4, and NO2 emissions occur on farm per kg O milk than for C milk. Total AP and GWP per kg milk did not differ between the selected C and O farms. In addition, results showed lower land use per kg C milk (p< 0.001) compared with O milk. Purchased concentrates was found to be the hotspot in the selected C farms in off farm and total impact for all impact categories. Whereas in the selected O farms, concentrates was found to be the hotspot in off farm impact besides roughage. Dutch’03study (20) results were compared with results of two Swedish’01/’02 (52); (51) studies and one German’89 (53) study and only differences and not actual numbers between the different systems in the studies can be compared, because of differences in computational methods [16]. And so the findings were on land use (O higher) and energy use (C higher), product-related AP (in tonnes milk) and product-related EP (in tonnes milk) was lower for O production agree with all three studies (Table 6) The similar climate change of C and O milk production agrees with the (52); (51) ; (53) studies. whereas In the Swedish’01/’02 study O production had the highest emission of NH3 and highest leaching of nitrate (NO3-) per kg milk, which resulted in a 25% higher product-related eutrophication, but this increase was not significant compared with C production. And in the German’89 study, the C production had a higher area-related AP (136 and 119 kg SO2-eq/farm ha) and eutrophication (566 and 326 kg NO3-eq/farm ha) compared with O production (107 kg SO2 -eq/farm ha; 141 kg NO3-eq/farm ha). 13 | P a g e
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems 3.2.2 Intensive vs. extensive farming [16] Found that the reduction in milk production per land unit corresponded to a higher CF. the stocking rate can determine the mass of nutrients (fertilizer and concentrates) and of energy used per unit of animal product. Some LCA studies highlighted this issue; (27a) simulated an increase of approximately 1020% of the stocking rate and estimated a corresponding increase of approximately 5-6% of GWP associated to 1 hectare of land; in contrast, there was no effect on environmental burden of 1 kilogram of milk. [16] Observed that the sample they took of C dairy farms had an average stocking rate of 2.13 LU/ha, whereas O dairy farms averaged 1.7 LU/ha. In this case, the authors observed a significant difference of milk production per cow. If there is no difference in respect to animal productivity, the reduction in the stocking rate does not influence the GWP of 1 kg of milk, but decreases the environmental burden associated to the land unit (35). A point that some authors make is the rational and efficient use of N feed and N fertilizers. Excess nitrogen is often associated to high GHG emission per FU, because it indicates low efficiency of feeding, chemical, and energetic resource utilization (22). (3) analyzed the relationship between milk productivity and GHG per kilogram of FPCM and concluded that the emissions of CO2eq decrease as milk production increases. In their simulation. While (23) did not find any difference in GHG emission per Kg of milk among 3 Holstein-Friesian cattle strains. In this case, the differences in milk production were probably not big enough to be detected with the sensitivity of an LCA analysis. In the simulation of (43) showed that the increase in individual milk production from 1944 to 2007 resulted in a reduction in CF per kilogram of milk from 3.65 to 1.35 kg of CO2-eq, due to dilution of (Table 6). Results of two Swedish’01/’02 (52); (51) and one German’89 (53) LCA studies compared with results of this Dutch’03study (20) results of this Dutch study (Dutch ’03 ) rounded to two digitGHGs for the years 2006 and 2012. tCO2e/ton of LW produced over 1 year maintenance feed requirements. However, (54) showed that the increase in milk productivity determines a reduction in emissions, even when the expansion system is used and an increase in beef cattle population is hypothesized. Finally, the increase in milk production per cow means that, given the quota regimen as in Europe, the number of dairy cattle is reduced. In turn, the population of suckler cows should increase to meet the demand of meat, and an increase in GHG emissions from beef cattle is expected (55). Finally The study of CF of dairy production through partial LCA (42) which it was based on a DairyGHG model to predict all important sources and sinks of CH4, N2O, and CO2 from primary and secondary sources in dairy production estimated that The cradle-to-farm gate C footprint of commonly used production practices was found to vary from 0.37 to 0.69 kg of CO2/kg of ECM produced, depending upon milk production level and the feeding and manure handling strategies used in the production system [15]. 14 | P a g e
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems 3.2.3. Mitigation strategies From the literature results examined, explicitly address mitigation options for beef and dairy. however it appears that they are sensitive to local conditions and/or variations in production practices adapted. For example, [2] showed that elimination of fertilization for forages had a modest impact on emissions for beef farmers in Alberta (Canada) but resulted in large increases in emissions/kg product for farmers in Saskatchewan and Manitoba (Canada) due to differing yield potentials among locations (39). Certainly,(42) found that biogas production from enclosed manure storage systems reduced emissions by 39%/kg milk. The most promising strategy is the anaerobic digestion of the manure (14), thanks to methane recovery. Anaerobic digestion reduces GHG emissions and does not influence the level of NH3 emissions. GHG emissions from manure management can be most effectively abated, if CH4 emissions during storage are reduced. This can be achieved by a reduction in slurry dry matter and easily degradable organic matter content. But probably there is also the need to use more appropriately the soil’s ability to sink the carbon, by adopting forage systems and agronomic techniques which preserve the soil’s organic carbon stocks (24). Therefore there is increasing research effort being focused on calculating the reduction in GHG emissions associated with increased livestock farming efficiency (e.g. in the NZ study of improving production efficiency as a strategy to mitigate GHG emissions) (49). A farm scale mechanistic cow model was used to model a typical pasture based NZ dairy farm as the baseline farm which considers effects of dietary manipulations on CH4 emissions for more accurate assessment of the potential impact of 5 GHG mitigations which were: (1) improved reproductive performance of the herd resulting in lower replacement rates, (2) increased genetic merit of the cows combined with lower stocking rate and longer lactations, (3) keeping lactating cows on a loafing pad for 12 h/day for 2 mo during autumn, (4) growing low protein crops of grains and/or MS, barley and oats on a portion of the farm and feeding this to lactating cows, (5) reducing fertilizer N use and replacing some of this with nitrification inhibitors and the plant growth stimulant gibberellins. [17] found that No single mitigation strategy achieved both targets of increasing production by 10–15% and reducing GHG emissions by 20%, but when all were simultaneously implemented in the baseline farm, milk production increased by 15–20% to 1200 kg milk fat + protein/ha, and absolute GHG emissions decreased by 15–20% to 0.8 kg CO2-eq (CO2-e)/kg (FPCM), which is equivalent to a decrease from 11.7 to 8.2 kg CO2-e/kg fat + protein. Besides The synergies of the mitigations resulted in reduced DM intake and enteric CH4 emissions, a reduction in N input and N dilution in feed, and, therefore, reduced urinary N excretion onto pastures, and an increase in feed conversion efficiency (i.e., more feed was used for production and less for maintenance). As indicated by (56) pursuing a suite of intensive and extensive reproductive management technologies provides a significant opportunity to reduce GHG emissions. Recommended approaches will differ by region and species but should target increasing conception rates in dairy, beef, and increasing fecundity in small ruminants, and reducing embryo mortality in all species. The result will be fewer replacement animals needed, fewer males required where artificial insemination is adopted, longer productive life, and higher breeding production. While Nitrous oxide fluxes can be reduced by using enhanced-efficiency fertilizers. Another option that was tried with positive results on N2O and CH4 emissions is the addition of straw to farmyard manures. Soil N2O emissions can be cut by reduced manure application, corn- 15 | P a g e
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems soybean rotation, and restoration of prairies However, slurry application strategies can have variable results according to crop, soil type and slurry source. Conclusion The IPCC methodologies provide a set of generalized guidelines for compiling and reporting national inventories and, as such, provide a transparent and consistent framework for comparing national GHG emissions at various times. However, limitations with respect to this national and sectorial approach undermine the usefulness of the methodology for modelling at the farm level. In this respect, whole farm modelling is widely employed for farm level GHG emissions modelling. LCA is an effective tool to evaluate the environmental impact of a product, process, or activity throughout its life cycle with the importance of considering the ‘whole farm’ scenario when estimating GHG emissions from agriculture. From the perspective of a CF, extensive livestock systems relate to low production efficiency, which then delivers high GHGs emissions per FU. This highlights the potential conflict between carbon efficiencies and other environmental objectives. From the literature examined, it appears that there is a wide discrepancy among studies, probably because the differences between the methodologies applied are too great. In addition, many mitigation strategies have not been tested in specific contests and so there are no specific EF. CF could be used for benchmarking by comparing GHG emissions from cattle from different countries or different production systems. It could also be used to evaluate the improvements of a farm, a region, or a state after the introduction of technical innovations or political strategies. It could be very effective as a mitigation indicator of results obtained from the enforcement of environmental political decisions. Nowadays, the number of dairy cows in Europe has decreased as a result of an increased milk yield per cow. If this trend keeps up, more and more beef will have to be derived from suckler herds implying an increase in the environmental loads contributed by beef production. It is time to step up efforts to work out improvement measures towards beef production based on suckler herds. Two main things are needed to make CF a practical tool in dairy cattle production. The first is to have a widely accepted standardized methodology, and in this, the IDF’s initiative can be considered very promising. The second is to use EF obtained from direct measurements in the specific environmental conditions they are referred to; only then can LCA be sensitive enough to verify the effectiveness of a mitigation strategy in a specific contest. Emissions from livestock systems that influence climate change are fundamentally different from other pollutants in that they impact to a much greater extent at a global level. Solutions must therefore involve international collective action and in particular allow participation by developing countries where most of the growth in demand, production, and therefore EI will take place. Side by side researchers need to understand what characterizes sustainable dairy and/or beef farming and analyses scenarios for a future sustainable food production and consumption. Finally, few LCA studies consider the role of soil in carbon sequestration, through understanding the factors influencing carbon sequestration and deriving an operational carbon methodology for grassland carbon sequestration as affected by land management and land use while it is generally recognized to be an important factor in the environmental sustainability of livestock systems. 16 | P a g e
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems 5. Appendixes 5.1. Appendix I (Table 1) Assembled LCA investigated studies for each country during the review with a brief description of the approaches, system boundaries, and emission factors utilized for each study Nº [1] [2] [3] [4] [5] [6] Study Beauchemin et al.(2010) Stewart et al. (2009) Country Methodology Canada Multiple-year over the lifespan of a breeding animal. Canada Modelling of four hypothetical farms representing a range of climatic and soil conditions. Single-year, whole Nguyen et al. Denmark farm system model (2010) developed for typical European suckler and dairy-beef production systems. Single year, whole Casey et Ireland system model. Based al.(2006a,b) on typical Irish cowcalf farm finishing all cattle. Single-year, whole Crosson et al. Ireland farm system model of (2010) beef cow systems. Modelled scenarios. Veysset et al. (2010) 17 | P a g e France Coupled a linear programming bio economic model with an environmental assessment model for beef farming systems. System Boundaries Emissions factors EF Direct on farm, IPCC (2006) purchased inputs, and methodology For indirect nitrous oxide Canada. emissions. Excludes Capital and machinery. Direct on farm, IPCC (2006) purchased inputs, methodology For LUC and indirect Canada. nitrous oxide emissions and sinks. Excludes Capital and machinery. Direct on farm, Primarily IPCC purchased inputs, and (2006). indirect nitrous oxide emissions. Direct on farm, purchased inputs emissions. Excludes capital, machinery and chemicals Direct on-farm, purchased inputs, and indirect nitrous oxide emissions. Excludes capital and machinery. Direct on farm, purchased inputs and capital and machinery. Does not include indirect nitrous oxide emissions IPCC (1997) for enteric fermentation and direct nitrous oxide emission. Primarily IPCC (2006). IPCC (2006) methodology for France.
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems [7] Ogino et al. (2004) Japan [8] Pelletier et al. (2010) USA [9] Phetteplace et al.(2001) USA [10] Subak (1999) USA Single year, whole farm system model. Based on Japanese cow-calf to finishing production system. Single year, whole farm system model of cow calf, stocker and feedlot production systems. Systems modelling of cow calf to beef American production systems Environmental analysis of hypothetical pastoral and feedlot beef production systems. Single year, whole [11] Cederberg et Sweden farm system model al.(2000) developed for system expansion allocation of beef from dairy system An LCA model for [12] Peters et al. Australia production emissions (2010) and an input–output analysis for other emissions including purchased chemicals. [13] White et al. (2010) 18 | P a g e New Zealand (NZ) Direct on farm, emissions from energy consumption and imported animal feed. Empirical data from experimental systems (Enteric fermentation). Direct on farm, IPCC (2006). purchased inputs, and indirect nitrous oxide emissions. Excludes capital and machinery. Direct on farm, IPCC (2006). purchased inputs, and indirect nitrous oxide emissions. Excludes capital and machinery. CH4, and CO2 IPCC (2006). emissions from fuel usage. Also includes emissions associated with alternative land uses. Direct on farm, IPCC (1997). purchased inputs, and indirect nitrous oxide emissions. Excludes capital and machinery. Direct on farm, IPCC (1997) purchased inputs, and methodology for Also includes Australia missions at the processing plant. Direct on farm, Farm simulation, feed purchased inputs for IPCC (1997) Formulation, and feed production but methodology for nutrient budgeting not for purchased New Zealand models. feeds, and indirect nitrous oxide emissions. Excludes capital and machinery.
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems [14] R. RipollBosch et al. (2013) Spain [15] Rotz et al. (2010) USA [16] Thomassen et al. (2008) NL [17] Beukes et al. (2011) NZ 19 | P a g e A model was used to capture the most important interactions in complex SFSs, to compute data required to determine for GHGs based on the LCA model used by FAO (2013) Direct on farm, purchased inputs, emissions at the production ,processes of medicines, and also the cultural ecosystem services, machinery and buildings were excluded from the analysis Whole farm system, Direct on farm, Semi-mechanistic purchased inputs, and GHG simulation indirect nitrous Oxide model. Modelled emissions. Excludes pasture-based and buildings. confinement US dairy production systems Cradle to farm gate analysis of ten conventional and 11 Organic Dutch dairy production systems. Integrated three models (a dynamic, mechanistic whole farm simulation model, a mechanistic animal model and nutrient flow model) to investigate mitigation scenarios for typical New Zealand dairy systems IPCC (2006) methodology for Spain Primarily IPCC (2006) and literature-sources emission factors for secondary emission sources Emission factors taken from the literature for most sources (IPCC (1997)) emission factors for nitrous oxide from managed soils) Direct on farm, IPCC purchased inputs and methodology for indirect nitrous oxide New Zealand emissions Direct on farm, purchased inputs, and indirect nitrous oxide emissions. Excludes chemicals and buildings.
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems 5.2. Appendix I (Table 2) Total GHGs CO2-eq contributions of different results from milk production GWP Author Study Total GHG CO2-eq CH4 CO2 N2O 19443.66 17 61.8 2 1 412 3 20071.35 26.8 1 230 Capper et al., (2009) Casey et al., (2006) 6 7 8 9 310 Sweden milk production system Conventional1.09 Organic0.90 25 1 298 Sweden milk production system No allocation1.05 4 Economical 0.92 Biological 0.85 Expansion 0.6 25 1 298 New Zealand and Sweden milk production system NZ 1.0 4 S1.16 63.1 8.13 25.7 50.1 15.9 32.3 Irish milk production system For three Holstein-Friesian strains  0.73-0.81 or 1.116 23 1 Phetteplace et al., (2001) 5 1 O’Brien et al., (2010) 4 21 Flysjö et al., (2012) 3 Conventional1.54 Efficient1.26 Only dairy1.2 Integrated1.05 Cederberg and Stadig, (2004) 2 Irish milk production system Cederberg and Mattsson, (2000) 1 US dairy production Simulated beef and dairy livestock systems in the United States Cow-calf20.6 5 8.65 2 0.94 10.9 Stocker14.4 Feedlot5.66 Cow-calf through feedlot15.5 6.58 1.4 6.41 1.32 2.1 7.84 6.28 1.3 2.22 Includes CO2 emissions from animals, plus CO2equivalents from CH4 and N2O. Includes CH4 emissions from enteric fermentation and manure. Includes N2O emissions from manure (both years) and from inorganic fertilizer application (2007 only). Kg ECM (Estimated Corrected Milk). Kg live weight gain. Product is kgCO2e/kg milk. Kg of fat and protein corrected milk (FPCM). Kg CO2eq Includes CH4 emissions from enteric fermentation and manure. Kg CO2eq Includes CH4 emissions from soil and manure. 20 | P a g e
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems Dairy1.09 6 Thomassen et al., (2008) Dutch dairy production systems. 0.58 0.14 Conventional1.4 7 Organic1.5 23 1 0.37 298 5.3. Appendix I (Table 3) Total GHGs CO2-eq contributions of different results from beef and meat production GWP Author Study Total GHG CO2-eq CH4 Beauchemin et al. (2010) Nguyen et al. (2010) CO2 N2O 276 8 277 208 9 1 Dairy bull calf (12 mo)16.0 Dairy bull calf (16 mo)17.9 Steers (24 mo)19.9 476 2 197 265 376 26 9 10.8 23 1 40% 14.8 20% 16.2 41% 19.2 Beef production 21.731 in western Canada 13.04 5 Different beef production systems in the EU Suckler cow–calf27.3 20.7 Ogino et al. (2004) Japanese beef-fattening system with different feeding lengths 22.6 Pelletier et al. (2010) cow calf, stocker and feedlot production systems in the Upper Midwestern United States Feedlot-finished from Weaning 26.9 Feedlot finished following store period29.5 grass-finished34.9 Intensive US feedlot system and a traditional African pastoral system American feedlot-finished 14.8 African pasture-finished8.4 50108 0.0811 29 0.04 Economic performance assessments in French Charolaise suckler cattle farms Calf-to-weanling and fattened females16.6; calf-to weanling grassland farm17.1; Calf-to-beef. Beef steers production14.9; baby beef production14.6; calf-to-weanling and cereals production19.0 10.1 11.3 8.7 2.3 2.0 2.2 4.1 3.9 4.0 8.5 1.8 4.0 11.5 2.3 5.2 Subak (1999) Veysset et al. (2010) 10 11 In kg CO2e/kg beef carcass Expected social costs of climate change: $6.2–45.2:tonne C or $1.7–9.2 tonne CO2 21 | P a g e 296
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems 5.4. Appendix II: A whole farm GHG models91 Figure 6.Carbon and nitrogen flow diagram of a ruminant livestock system (Schils et al., 2005) (38) Figure 5.Diagram of the pools and flows contained within the model (Stewart et al., 2009) (39) 1 Selected models examples according to the international LCA citation rate and the relevance of the utilized references in this review, which considered the main corner stone for a full accounting holistic LCA based studies by many scientists and researchers on the Carbon footprint (CF) and evaluation of the farming systems management practices and emissions. 22 | P a g e
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems Figure 8 Flows of C and N in and out of the total model farm system FarmGHG (Olesen et al., 2006) (12) Figure 7.HOLOS model (Beauchemin et al., 2012) (15) (16) (17) 23 | P a g e
  • Potential of Life Cycle Assessment for reducing global GHG Intensity from Ruminant Production Systems Figure 9.Operational diagram of greenhouse gas (GHG) model (O’Brien et al. 2011) (37) 24 | P a g e
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