Comparing the Carbon Footprint of Conventional vs. Organic Milk Production Systems

A photo of milk cartoon on a shelf
Cartons of milk. Photo: M.A. Wattiaux
Note: This webpage is for instructional purposes only and was not actually commissioned by Wisconsin government agencies.

Hypothetical task force Report prepared for the Wisconsin Department of Agriculture, Trade and Consumer Protection (DATCP)

UW-Madison Task Force Members:
   Michel Wattiaux, Department of Dairy Science
   Erin Silva, Department of Plant Pathology
   Alfonso Morales, Urban and Regional Planning
   Kathryn Anderson, Department of Sociology


Scenario | Abstract | Introduction | LCA Methodology | CO2-eq per Kg of Milk  | CO2-eq per Hectare | Climate as a Common Pool Resource | Organic Valley Cooperative | Biodigestion | Conclusions | Citations | Acknowledgements
Scenario 

The Wisconsin state legislators have mandated the Wisconsin Department of Agriculture, Trade and Consumer Protection (DATCP) and the Department of Natural Resources (DNR) to assemble a task force of scientific experts to address the concerns of the dairy industry, advocacy groups and other stakeholders across the state. The task force is expected to summarize the most up-to-date scientific literature in relation to greenhouse gases emission from milk production. The question is whether milk produced following USDA-mandated organic practices results in less, the same, or more GHG emission than milk produced by dairy farms using conventional practices. In addition, the report should highlight any other relevant issues that may have implications for the economy of the state, the protection of its natural resources, and the social welfare of its citizens. The task force is expected to provide it's final report by early March 2018 to the Secretary of Agriculture. The class instructional team is the leadership of the task force. Members of the task force reviewed the literature, discussed scientific findings, and interpreted publications in order to produce the report. An executive summary of the report will be made available as a publicly-available web page (see below).


Abstract

Life cycle analysis (LCA) is a tool that scientists have used to assess carbon footprint of foods. The analysis includes as many parts of the system as possible including the production, transportation, processing, refrigeration, consumption, and disposal of residual waste. There are enormous challenges to account for the full complexity of comparing carbon footprint of milk produced under different feeding and management systems. However recent estimates place milk carbon footprint in the United States at roughly 2.1 kg of CO2eq. per kg of milk. Results of LCAs have clearly indicated that most of the emissions occurrs on-farm (approximately three-forth of total emissions) whereas post-farm emissions (transportation, processing, retail and consumption/disposal) is much less consequential. As a results research has focused on the emissions associated with the crops and livestock components of the dairy systems. The so-called "cradle to farm gate" is approximately 1.0 kg of CO2eq. per kg of milk, but varies considerably. On-farm emissions are from different gases and from different biological processes. First, the single most important source is methane eructed by cows as a result of enteric fermentation of the feed in the digestive system. The second most important source is the methane and nitrous oxide associated with the deposition of manure in pasture and/or the collection, storage and field application of manure as a source of fertilizer. The third most important source is the carbon dioxide and the nitrous oxide emitted with the management of the land as it is cultivated to produced the feed.

Although there are no studies to compare the carbon footprint of organic and conventional milk in the United States (or Wisconsin), Swedish researcher have found only small differences between the two systems in regard to their impact on climate change. These authors, however, pointed that the reduction (elimination) of pesticides and the reduction of importation of nutrients (in particular phosphorus) in the organic system was counterbalanced by a much greater requirement of farmland compared to conventional production system. Other comparative analysis have highlighted two important facts: (a) the high degree of uncertainties associated with estimates of methane and nitrous oxide emissions and (b) the (often time) large variation observed within a system compared to the (small) average difference between two systems.

Eighteen years of data collection from the Wisconsin Integrated Cropping Systems Trials (WICST) indicated that increasing the proportion of the cow’s diet derived from pasture invariably lowers total greenhouse gas emissions associated with feed production on a per hectare basis due to the fact that these practices reduce carbon loss (and even possibly sequester carbon depending on environment and soil characteristics) compared to the conventional cropping practices. Conservation of soil carbon is observed with more diversified rotation and with conservation tillage practices that minimize soil disturbance. The organic system, with yet a more diversified rotation, demonstrated similar overall carbon loss to the conventional conservation tillage system, despite more soil disturbance in the system, due to the increased carbon inputs due to the integration of cereal grains, manure-based inputs, and cover crops into management.

Anaerobic digestion of effluents is another mitigation strategy relevant for large conventional dairy farms. When a farm installs an anaerobic digester, it offsets its energy consumption and may even contribute electricity to the local electrical grid. The projects have a positive effect on the environment by reducing fossil fuel use, substantially eliminating all manure odors and pathogens and better controlling the final waste product. 

Social sustainability is extremely difficult to measure as it relies on world views, perspectives and perceptions of different social groups. The social sustainability of organic producers rely on the "special" connection between the producer and the buyer concerned with a range of issues related to human health and how food is produced and processed. In contrast, the conventional producers rely on producing lots of food for lots of people to buy at the lowest possible price. 


Introduction
Source of emission from different segments of the milk supply chain
Figure 1: Carbon footprint of milk circa 2008 identifying GHG emissions from each segment of the supply chains Source: Thoma et al., 2013.

Dairy farming is one of the pillars of the state of Wisconsin's economy. In 2014, according to the Wisconsin Milk Marketing Board, the state counted more than 10,800 dairy farms, 1.27 million dairy cows producing on average 21,700 lbs per year (9,860 kg per year). Thus total milk production in the state of Wisconsin in 2014 was more than 27.6 billions lbs (12.5 million metric tones), which represented 13.6% of national production. 

Thoma et al. (2013) found that milk production contributed approximately 1.9% of US GHG emission. These authors conducted a Life Cycle Assessment (LCA) also referred to as cradde-to-grave analysis and estimated a milk carbon foot print of 2.05 (90% confidence interval: 1.8-2.4) kg CO2eq per kg milk consumed. The analysis accounted for loss of 12% at retail and an additional 20% loss at consumption. As illustrated in Figure 1, 72% of the emissions takes place within the farm and were associated with: production of the feed (19%), enteric emission (25%), manure management (24%) and farm energy (4%). The single most important source of GHG is methane emitted during fermentation in the digestive system (primarily the rumen) of the feed consumed by the cow. The second most important source of GHG is the combined methane and nitrous oxide emitted during the collection, storage and after field application of the manure. The third most important source of GHG is the combined carbon dioxide and nitrous oxide emitted in the fields in the process of growing the crops that will serve as feed for the cows.  In 2009, the dairy industry committed to a voluntary goal to reduce greenhouse gases (GHG) emissions of fluid milk by 25 percent by 2020. Although each segment of the supply chain has a role to play, research has focused primarily on practices that may be the target of mitigation strategies within farm boundaries. Thus, researchers have conducted 'partial' LCA also referred to as craddle-to-farmgate because they include only factors affecting emissions within the farm.  

There are many ways to feed, manage, and care for dairy cattle on a dairy farm and milk producers are often categorized as conventional, grazers, or organic (Dutreuil et al., 2014). These authors defined organic farms were those that had received USDA certification. Grazing farms were those not certified organic but for which at least 30% of the estimated consumption of feed (measured as dry matter intake, DMI) of lactating cows during the grazing season was from grazed pasture. Conventional farms were defined as nonorganic and nongrazing, which included farms that typically grow crops and harvest forages for indoor feeding and housing for most of the year.

The goal of this research was to gather relevant and most up-to-date scientific evidence to address the question of whether milk produced following USDA-mandated organic practices results in less, the same, or more GHG emission than milk produced by dairy farms using conventional practices.


LCA — Life Cycle Assessment — Methodology

Dairy LCA
Figure 2: Main LCA components and gases associated with milk production Source: Beauchemin and McGeough, 2013.
LCA: A literature review was conducted to identify peer-reviewed articles in which a partial LCA was conducted to estimate and compare GHG emission of milk across production systems.  Estimating GHG emission associated with milk production with LCA include a complex series of tasks. In 2006, the Intergovernmental Panel on Climate Change (IPCC) published guidelines for estimations of national emissions. Volume 4 focused on agriculture, forestry and other land use. Chapters 5, 6, and 10 of volume 4 focus on emissions from cropland, grassland, and livestock and manure management, respectively. In general, the IPCC recognizes three methodologies (three tiers) to estimate emissions from livestock operations: 
  • Tier 1: A simplified method that only takes into account livestock population data by animal species/category and an "emission factor" (emission per animal per day), which varied for different regions of the world. 
  • Tier 2: A refined method that takes into account measurements done under specific local conditions, and scientific findings published in peer-reviewed publications.
  • Tier 3: The most sophisticated method that include the use of highly technical simulation models.   
Most of the research cited in this report is from a combination of tier 2 and tier 3 approaches: data collected on farm provided estimates of inputs, outputs and technical performances ("efficiency" of conversion of inputs into outputs) and other farm management practices that help differentiate one production system from another. It is not until the last few years however that comparative analysis of GHG from milk produced under different farming practices have emerged in the literature.  Most of these efforts have relied on the LCA methodology (although most LCAs will default back to the IPCC equations in absence of accurate locally available data). There are four phases of a LCA: (1) Definition of goal and scope (what elements are to be included and what level of details in needed), (2) Inventory analysis (collection and analysis of relevant input and output data), (3) impact Assessement (use of appropriate indicator to reflect the environmental issue) and (4) Interpretation (conclusions and recommendations).

There are three key components of any LCA:
  • The Functional Unit is the measure of output from the system, which provide a reference point for expressing the environmental impact.  For milk production, the amount of milk output is usually normalized to an equivalent amount of milk with an normalized energy content (energy corrected milk, ECM) or normalized to a constant fat-and-protein content (fat and protein corrected milk, FPCM);
  • The system boundaries define the processes to be included in the LCA (which depends on the goal of the LCA).  Figure 2 identifies the main cycle stages, including inputs, outputs and flows in a theoretical dairy production system and the boundaries for a "cradle-to-farm-gate" LCA. 
  • The co-product allocation refers to the process of allocating the environmental impact to other products that are inevitably associated with the production of the main product of interest. In the case of milk production. Dairy cattle are raised and inevitably enter the meat market after culling. The allocation of the environmental burden to co-products can be done: (a) by system expansion, (b) based on physical relationship between the co-products (biological allocation), or (c) on the basis of economic value. There are still lots of disagreement among experts on the ideal co-product allocation method.        

CO2-eq per Kg of Milk
Greenhouse gas emission from swedish organic and conventional systems
Figure 3: Carbon footprint of milk produced in Swedish organic (Org) and conventional (Conv) dairy farms Source: Cederberg et al., 2000.

LCA of Organic vs. Conventional milk: Although there are no studies to compare the carbon footprint of organic and conventional milk in the United States (or Wisconsin), Swedish researchers (Cederberg et al., 2000) conducted an LCA focusing on the impact of feeding and management strategies. The different feeding strategies in the two forms of production, influence several environmental impact categories. The import of feed by conventional dairy farms often leads to a substantial input of phosphorus and nitrogen. Organic milk production is a way to reduce pesticide use and mineral surplus in agriculture but this production form also requires substantially more farmland than conventional production. Specifically, the land required to produce the feed necessary to obtain 1000 kg of milk was slightly less than 2000 square meters in the conventional system, but almost 3,500 square meters in the organic system. The authors concluded however, that under swedish conditions, a large use of grassland for grazing ruminants is regarded positively since this type of arable land use promotes the domestic environmental goals of biodiversity and aesthetic values. In regard to greenhouse gases emissions, the lower carbon dioxide and nitrous oxide emission, presumably associated with lower (external) inputs to the system, was counterbalanced by higher methane emission, presumably from cows fed diets with a higher proportion of forages (which is the main source of ruminal fermentation, Figure 3).

LCA of Grazing vs. Conventional milk: The literature, however, included a number of recent studies comparing grazing systems to conventional systems. Flysjö et al. (2001) analyzed the farm-gate carbon footprint of milk for an outdoor pasture grazing system in New Zealand and an mainly indoor housing system with heavy reliance on concentrate feed in Sweden. The calculated carbon footprint for 1 kg of energy corrected milk, including related by-products (surplus calves and culled cows), was 1.00 kg CO2eq. for New Zealand and 1.16 kg CO2eq. for Sweden. Methane from enteric fermentation and nitrous oxide emissions from application of nitrogen (as fertilizer and as excreta dropped directly on the field) were the main contributors to the carbon footprint in both countries. The most important parameters to consider when calculating the GHG emissions were the amount of feed consumed by the cow (dry matter intake, DMI), the "assumed" emission factor for methane from enteric fermentation, the amount of nitrogen applied and "assumed" emission factors for direct nitrous oxide emissions from soils, direct manure deposition and from crop residues. However, there was large uncertainties in estimating methane and nitrous oxide emissions. Simulation analysis indicated an uncertainty distribution corresponding to 0.60–1.52 kg CO2eq per kg of milk for NZ and 0.83–1.56 kg CO2eq per kg of milk for Sweden. Thus the variation within the systems is relatively large compared with the difference in carbon footprint between the two systems (countries). Put all together, New Zealand milk production had a lower carbon foot print than Swedish milk production in 89% of cases. Authors recognized the importance to improve our understanding of biological processes that affect emissions of methane and nitrous oxide in order to improve the accuracy of predictions in the future.

Table 1: Emission from a pasture-based system (Irish dairy farm) to conventional intensive dairy system from the United States
Source: O'Brien et al., 2014.

Sources of Emissions
(kg of CO2eq per 1000 kg of milk)
 Location
 Irish
Pasture
 United States
Conventional
 Methane      
 Enteric fermentation   On farm  403.7  373.6
 Manure storage and spreading  On farm  42.1  121.9
 Fertilizer production  Off farm  1.6  0.4
 Concentrate production  Off farm  0.8  1.6
 Electricity and other inputs  Off farm  12.9  15.0
 Nitrous Oxide      
 Fertilizer application  On farm  99.6  16.9
 Manure storage and spreading  On farm  34.5  153.1
 Manure excreted on pasture  On farm  139.9  0.0
 Crop residues  On farm  2.0  3.3
 Fertilizer production   Off farm  30.9  4.7
 Concentrate production  Off farm  7.5  52.2
 Electricity and other inputs  Off farm  6.8  8.7
 Carbon Dioxide      
 Fuel combustion  On farm  13.7  33.3
 Lime application  On farm  1.4  1.2
 Fertilizer application  On farm  6.7  1.6
 Carbon sequestration  On farm  -77.7  0.0
 Fertilizer production  Off farm  43.8  9.4
 Concentrate production  Off farm  21.4  52.7
 Land use change  Off farm  1.8  0.0
 Electricity and other inputs  Off farm  16.0  48.5
Total       
 Carbon footprint (On farm)    693  705
 Carbon footprint (Off farm)    144  193
 Carbon footprint (total)    837  898
 Carbon footprint no C. Seq.    914  898

CO2-eq per Hectare

Wisconsin Integrated Cropping Systems Trial (WICST): The life cycle inventory analysis used to assess GHGs from crops in this study is built on 25 years of WICST data collection at the University of Wisconsin, Arlington Agricultural Research Station. The WICST experiment began in 1990 and consists of six model cropping systems in Wisconsin. Three cash crop (typical of specialized grain farms: CS1, CS2 and CS3 in Figure 4) and three forage crop systems (typical of livestock - crop farms: CS4, CS5 and CS6 in Figure 4) were selected for study based on crop diversity and level of external inputs (Posner et al., 1995; Posner et al., 2008). Specifically:

Crop systems of the Wisconsin Cropping Systems Trial (WISCT)
Figure 4: Short description of the Wisconsin Cropping Systems Trials (WISCT) Courtesy Randy Jackson, Agronomy Department, UW-Madison.

  • CS1: Cash grain, high-external input continuous corn system;
  • CS2: A moderate-external input, corn - soybean system;
  • CS3: An organic corn - soybean - winter wheat with interseeded red clover system;
  • CS4: A high-input corn - alfalfa forage system referred as the g"Green Gold";
  • CS5: An organic oats/alfalfa - corn forage system;
  • CS6: A rotationally heifer grazed pasture forage system seeded to a mixture of red clover, timothy, smooth bromegrass, and orchard grass.

Note that CS3 and CS5 are organic systems. From the information gathered through the years since the inception of this trial 25 years ago, we can estimate the impact of feed production for organic and conventional dairy systems in Wisconsin with respect to greenhouse gas emissions and carbon sequestration. Emissions of N2O, CH4 and CO2 converted to CO2-eq per hectare and per year, were categorized in three major components: embedded emissions associated with field production practices and inputs used; in-field emissions (direct and indirect); and carbon sequestration/loss.

The embedded emissions were calculated with data from the commercially available GaBi databases that have been developed for LCA analyses. The item considered in this analysis included: a) Seeds (and others), b) Diesel, c) Fertilizer, d) Pesticides, e) Grain drying and f) Supplemental feed offered to heifers on pasture in CS6. The direct and indirect in-field emissions were calculated from equations presented in chapter 11 (N2O emissions from managed soils) of volume 4 (Agriculture, Forestry, and Other Land Use of the IPCC (2006). The direct in-field emissions accounted for crop residue and cover crops including: above ground biomass and its nitrogen content, residue remaining post-haverst and nitrogen in crop residue, the ratio of biomass below ground and above ground and the nitrogen content of the biomass below ground. Direct in-field emissions were computed also for cow and poultry manure-based nitrogen fertilizer application and from the nitrogen deposited by heifers as urine and fecal material in CS6.  The in-field indirect emissions accounted for the N2O resulting from nitrogen run-off (lost to surface waters), leaching (through the soil to the ground water), and nitrogen volatilized to the atmosphere (as ammonia) and subsequently deposited to the ground by gravity (dry redeposition) or with rain events (wet deposition). In addition to the kg of CO2-eq produced by hectare per year from N2O emission, the final calculation of the overall emissions for each cropping system accounted for the CO2 gained or lost trough changes in soil organic matter (SOM) concentrations. A positive change indicated sequestration of carbon in the soil whereas a negative change indicated a loss of soil carbon to the atmosphere.

Part-A-Embedde-Emissions.jpg Part-B-In-field-Emissions.jpg Part-C-Total-Emissions.jpg
Figure 5: Greenhouse gases emissions from the six WISCT cropping system: A) embedded emissions, B) in-field emissions, and C) embedded, in-field and soil organic matter change; See text for details (Courtesy Janet Hetccke, Department of Agronomy, UW-Madison).

Results presented in Figure 5 are the averages of 16 years of measurements (between 1993 and 2008). Figures 5a, 5b and 5c showed the embedded emissions, the in-field emissions, and the sum of the embedded, in-field and the carbon lost from SOM, respectively. The embedded emissions and the in-field emissions were in the same order of magnitude and ranged from approximately 500 to 2,000 kg CO2-eq per hectare per year. However total CO2-eq emission range from slightly less than 4,000 to more that 10,000 kg CO2-eq per hectare per year (Figure 5c). Figure 5a showed that the total of the embedded emissions was highest for continuous corn (CS1) due primarily to the production of the large amounts of fertilizer nitrogen (Haber-Bosch process) required by this cropping system. In contrast, the total of the embedded emissions was lowest for the organic corn-soybean-winter wheat (CS3) crop rotation primarily because of the absence of commercial nitrogen fertilizer applications. The total of the embedded emissions was similar among the three dairy forage systems. Figure 5b showed that the in-field emissions was highest for the rotational grazing (CS6) system and the lowest for organic corn-soybean-winter wheat (CS3) crop rotation.  Figure 5c indicated that none of the crop systems sequestered carbon. However the carbon loss from the soil surface was substantially lower for the rotational grazing system (CS6) then the other systems and substantially higher for continuous corn system (CS1) than for the other systems. As a group, it would appear that carbon losses from the soil are greater for the grain systems than the forage systems (Figure 5c). In summary the highlights of this research can be described as follows:

  • Organic production provides several advantages with respect to reducing the overall GHG associated with the production of the crops (corn, soybean, cereal grain, and alfalfa) used to feed the dairy herd;
  • In-field emissions of the conventional (CS4) vs. organic (CS5) forage rotations were similar as the nitrogen needed for corn production was derived from similar sources (nitrogen credit from the nitrogen-fixing alfalfa and manure);
  • Overall the livestock pasture system resulted in the highest in-field emission due to the high biomass produced by the pasture crop;
  • Assessing the total impact of the cropping system strategies on overall changes in GHG concentrations in the atmosphere, the largest contribution impacting this metric is SOM change. The continuous corn system (CS1) and to a lesser extent the other two grain systems are accelerating SOM loss much more so than the forage systems taken as a whole (CS4-6);
  • Moving toward a more diversified rotation with conservation tillage practices that minimize soil disturbance (CS2), conservation of soil carbon is observed, with a lesser footprint of the system. The organic system (CS3), with yet a more diversified rotation, demonstrates similar overall carbon loss to the conventional conservation tillage system, despite more soil disturbance in the system, due to the increased carbon inputs due to the integration of cereal grains, manure-based inputs, and cover crops into management.

Social Dimensions: Climate as a Common Pool Resource

Tragedy of the CommonsTo understand the social constraints and opportunities for reducing agricultural greenhouse gas emissions, we begin with the framework of Common Pool Resources (CPR), as specified by Elinor Ostrom’s team in their 1999 Science article. The bottom line is that as a common pool resource, a stable climate has all the characteristics that make it very difficult to sustainably manage. A stable climate can be thought of as a type of public good.  What kind of public good?  Climate is the type of public that is non-exclusive but rival, which puts it in the category of CRP. It is non-exclusive because you can't prevent people from benefiting from a stable climate.  While it has some non-rival characteristics as well, a stable climate is rival because users who benefit from a stable climate often contribute to the destabilization of climate through emitting greenhouse gases. Common Pool Resources often suffer from free-riding and other dilemmas in which people following their own short-term interests produce outcomes that are not in anyone's long-term interest.

Hardin's famous "Tragedy of the Commons" metaphor describes CPR users as caught in an unavoidable process that causes the collapse of the very resource upon which these users depend.  "Rational" users exploit the resource as long as the expected benefits to them exceed the expected costs from overuse of the resource.  Because each user is doing the same, and ignoring the costs of their actions to other users, the aggregate effect is overuse and, potentially, resource collapse.  

The tragedy of the commons is an appropriate metaphor for climate change because the vast majority of people and firms in the world benefit from a stable climate but also contribute to climate destabilization through their daily activities.  The minute effect that a single user’s greenhouse gas emissions have on the climate is much smaller than their benefit from this activity.  However, the aggregate effects of each user’s actions are catastrophic.

“Tragedy of the Commons” type predictions of resource collapse are based on the idea that individuals are selfish, norm-free, and maximizers of short-run results.  Where public goods are concerned, these predictions are often wrong, and in fact people can and do successfully and sustainably manage common pool resources.

While Garret Hardin wrote very pessimistically about the tragedy of the commons, Elinor Ostrom and others have studied many real cases from around the world in which people are in fact quite successful at managing common pool resources.  This body of research has catalogued those characteristics of (1) the resource, of (2) the people managing it, and of (3) the institutional context, that influence how difficult it is to sustainably manage a resource. A brief discussion of the factors that influence manageability of resources follows:

A. Characteristics of the Resource

  1. Resource size
    • Extremely large resources that cross international boundaries and cannot be managed at the village, watershed, or even country-level are the most difficult to manage sustainably.
    • The larger the resource, the more challenging it is to achieve cooperation of multiple and diverse stakeholders, including different national governments and nested regional and local institutions.
    • International resources require voluntary consensus of national governments.
  2. Measurability
    • The easier it is to assess the health of a resource, the easier it is to manage adaptively.
    • The more that users have reliable and valid indicators of resource conditions, the easier it is to build consensus.
  3. Complexity
    • The more complex a resource is, the harder it is to achieve a shared understanding among diverse stakeholders about how the ecosystem works, the health of the resource, and the likely consequences of different management regimes.
    • The more complex a resource, the more uncertainty there will be about the carrying capacity or resilience of a resource and what are the thresholds over which more exploitation will cause irreversible change or collapse.
  4. Temporal and spatial dimensions of the resource
    • The closer the use of a resource and the consequences of this use are coupled in time and space, the closer the individual costs will be to the social costs, and thus the more likely it will be for users to act in the social interest.
    • When the negative consequences of resource over-use are apparent quickly and are felt locally, the more likely it is to find consensus among stakeholders.

B. Characteristics of The Users

Now let’s consider characteristics of the individuals and organizations that use the CPR.  Here, individual and cultural norms constitute a vital dimension.  Naturally, people are diverse.  You can (arbitrarily) think of people as falling into one of three groups: 
  1. Some people intrinsically have a narrow and self-interested worldview and never cooperate;
  2. Others cooperate when they are assured that they will not be exploited by non-cooperating free-riders; and then there are some users who are
  3. Genuine altruists who always prioritize the group's wellbeing.
The need for extensive rules, monitoring, and enforcement expenses governing institutions depends on the proportion of each of these types of people in the population.  This points to the importance of cultural values and norms in environmental sustainability.  Sustainable management is much more likely if users can learn to overcome their tendency to evaluate their own costs and benefits more intensely than those of the group.  Sustainable management is easiest when:
  1. The proportion of selfish individuals in the population is low.
  2. Individual users (and, even better, the population as a whole) can gain a reputation for reciprocity and cooperation, triggering cooperative behavior from those who only cooperate when they know it will be reciprocated.
  3. Users can identify one another, and thus draw on trust, reciprocity, and reputation to develop and maintain norms that prevent over-use.
Fortunately, new technologies for monitoring, communications, and coordination have allowed management of much larger resources and larger groups of users than was possible in the past.

C. Characteristics of the Institutional Context

Evolved norms and reciprocity are not always enough to protect a resource.  In these cases, participants or external authorities must devise and enforce rules for resource protection.  Governance institutions for sustainably managing common-pool resources are needed to restrict access and create incentives for users to invest and not over-exploit. It is easier for users to see the benefits of devising and following rules when: 1) they understand how the ecosystem functions, 2) they have reliable and valid indicators of resource conditions, and 3) the results of different management regimes have predictable effects on the resource.

The specific shape of these rules has substantial distributional consequences.  For example, when allocating rights to emit greenhouse gasses, if permits are given primarily to those who have developed their economies around high emissions in the past, this may be unfair to developing countries.  It is extremely challenging to find effective rules that match the complex ecological and social dynamics of the system and are also perceived as fair by the users.  The situation is exacerbated when users have unequal political or economic power and use this power to strategically propose policies that disproportionately benefit themselves at a cost to others.

There are many kinds of institutional rules that can be effective in one setting and less so in another. Generally, if users trust others to keep promises, then management institutions can be less expensive. High trust allows low-cost management methods that don't  require expensive monitoring and enforcement. Finally, if rules are imposed by outsiders without including local users in rule development, locals may resist, even if it would be in their interest to comply.

Climate Change as a Common Pool Resource: So how does climate change measure up on these three dimensions of common pool resource management? Unfortunately, a stable climate has all the characteristics that make it incredibly difficult to manage sustainably.  Its extreme size and complexity, the difficulty in measuring and predicting climate change with certainty, and the fact that the causes and consequences of climate change are extremely de-coupled in time and space, add up to an extreme challenge as has never been faced before.  The worst effects of climate change will take place far away from emissions, and the worst costs of climate change will accrue to future generations.  This means the emitters face none of the costs of emitting greenhouse gas, only the benefits, making it extremely difficult to negotiate rules to mitigate climate change.

The more users, the more difficult it is to organize, agree on the rules, and enforce the rules.  The immense size of the resource means that 7 billion people must work together to prevent catastrophic climate change.  In a culturally diverse global world, and in a world where each locality is becoming more culturally diverse, it is becoming more difficult to find shared interests, worldviews, and understandings.  

Because there is not a global government with enforcement authority, the only institutional strategy available is global unanimous consensus and voluntary compliance with negotiated treaties.  As history has shown, negotiating such treaties is enormously challenging and there is no means of enforcement.

Technically, the world is changing faster than ever before; population growth, economic development, capital and labor mobility, and technological change are pushing us past environmental thresholds before we know it. We must rely on various combinations of law, "learning by doing,” and rapid communications about the experiments people are conducting because current problems are so different from those of the past. This means creative solutions people discover must make their way into law and policy where they can be diffused rapidly and incentivized appropriately.
As a common property resource, a stable climate has all the characteristics that make it very difficult to sustainably manage. It seems like a pretty bleak picture.  What can be done? Possibilities include: a) activism, b) cooperative businesses, and c) adding new mitigation activities

Organic Valley: A case study of a market structure that promote a socially desirable (i.e., sustainable) production system

First, we take for granted the existence of cooperatives – but these are social creations, they are a kind of law created by people to create that kind of business organization. What new business organizations might be created by new kinds of law?

Second, the legal entity has implications for social relations and economic impact, which in turn have implications for climate. For instance:

  • high farmgate prices allow farmers to internalize environmental externalities and maintain small and medium sized farms, which in turn can reduce ghg emissions, and
  • the cooperative structure fosters values of cooperation instead of competition between farmers, which can make easier other activities to mitigate climate change, and
  • the business structure can build in investment strategies that use profits to care for the land and labor, which in turn becomes part of a story that consumers can find appealing and thus increase sales.

Case Study of New Mitigation Activities: Social and Regulatory Implications of Biodigestion

First, we take for granted biodigestion as an option for disposing of manure, but this has not always been so, and is in fact made possible by various regulations as well as organizations that see the results of biodigestion as multi-functional.   The 2008 report of the Focus on Energy - Wisconsin Biogas Program provided an overview and case studies of biodigestion in Wisconsin. When a farm installs an anaerobic digester, it offsets its energy consumption and contributes electricity to the local electrical grid. The projects have a positive effect on the environment by reducing fossil fuel use, substantially eliminating all manure odors and pathogens and better controlling the final waste product. As an example, a typical anaerobic digester with a 300 kilowatt (kW) biogas-fueled generator will produce enough electricity to power 224 average Wisconsin homes. In addition, the annual environmental benefits would be equivalent to offsetting 1,117 tons of coal from being burned, the emissions from 361 cars, or nearly 2,460 tons of the greenhouse gas carbon dioxide (CO2-eq) from being released into the atmosphere. Wisconsin is at the forefront of U.S. farm-based digester use. This 2009 edition of the Wisconsin Agricultural Biogas Casebook includes brief case studies of farm-based anaerobic digesters installed in Wisconsin. The report gives a look at the experiences of 21 farms with operating anaerobic digester systems in Wisconsin as of fall 2009. Biodigestion is not, however a size neutral technology. All farms with biodigestors are classified as Concentrated Animal Feeding Operations (CAFO) with herd size ranging from 800 to 4500 dairy cows (Figure 6).

Herdsize of the 21 Wisconsin dairy farms with a biodigestor in 2009
Figure 6: Herdsize of the 21 Wisconsin dairy farms with a biodigestor in 2009 (Source, Focus on Energy, 2009 report).

We present three examples below that differ in details with respect to potential economic, social and environmental outcomes.

Deere Ridge Dairy: Deere Ridge Dairy or Gordondale Farms is an 850 head Holstein dairy operation in Nelsonville, Wisconsin in eastern Portage County. Some 28,000 gallons of manure, bedding and milking parlor wastes are generated per day with an average moisture content of 8.8 percent. Their manure is scrape collected using a skid steer at two hour intervals and they do not add any off-farm wastes. They use digested solids for bedding and their former manure storage system was a pit. The biodigestor has been in operation since 2002. The digester system takes 20 days to run its cycle and produces electricity for the farm as well as heats the main dairy area. The farm owns the digester and sells the excess energy to Alliant Energy. The residual from the digester is used for bedding and applied to the fields. This installation was a result of the farm owner building a new dairy facility and was interested in the benefits anaerobic digestion. Alliant Energy was also interested in a pilot project using biogas. The two parties worked out an agreement for the first digester installed on their farms. To reduce the financial risk for the farm, Alliant Energy agreed to supply, operate and maintain the engine generator set.

Emerald Dairy: The Emerald Dairy biodigester is located on an operating dairy farm in the Town of Emerald, St. Croix County, Wisconsin and is owned by John Vrieze. There are twenty employees working at Emerald Dairy, and presumably, some of them work on operations and maintenance of the biodigester. The anaerobic digester is primarily used for creating power, though 15% of the biogas is used to heat the digester to maintain the required temperature. The heat and power created by the biodigester supplies heat and power for Emerald Dairy. The surplus biogas created by the biodigester is “cleaned up” and converted to “natural” natural gas and the dairy produces enough of this to provide about 875 people with all of their natural gas needs. The “natural” natural gas is currently purchased from the dairy by 3M who does so to contribute to their green energy portfolio.

The primary feedstock of the biodigester is manure from the 1,100 cows on the farm. The manure costs Emerald Dairy $0 because all of the manure is a byproduct of the cows at the dairy. The return on investment (ROI) is not known, but the case study reported that while the per-cow profit decreased slightly during the first two years of operation, the following two years the dairy broke even and it anticipates an increase in per-cow profit the following two years. The projection is that biodigestion will net the dairy a per-cow net profit of $100 annually. There are a few secondary outputs of the system. Most of the dairy’s fertilizer needs (95%) are covered from the byproducts of the biodigester system and this saves the dairy money by not having to purchase fertilizer (the dollar amount varies each year to do fluctuation in commercial fertilizer costs). Bedding for the dairy cows is provided from the solids that remain from the biodigester process. Phosphorous is extracted during the biodigestion process and the dairy is looking into the possibility of selling this in pellet form for additional revenues, which at this point are unknown.

The biodigester cost the dairy over $3 million to purchase and set up and we do not know operations and maintenance costs. The dairy purchased the biodigester through a variety of funding sources. Emerald Dairy received a low interest loan from the Wisconsin Dept. of Commerce through a grant program administered through the West Central Wisconsin Regional Planning Commission. This loan included a 2%, $300,000 loan for a water treatment system and a 4%, $100,000 loan for a lagoon cover. Additional funding came from banks, private investors, self-financing and the University of Minnesota. Some incentives Emerald Dairy receives are carbon credits which they are merchandising through a broker who trades them on the Chicago Climate Exchange (CCX).

Clear Horizon biodigestor at the Crave Brothers' dairy farm
Figure 7: Clear Horizons Digester at Crave Brothers' Farm (Source, Focus on Energy, Wisconsin Agricultural Biogas Casebook, 2008 report).

In addition to the immediate energy and cost savings to the dairy, the biodigester project has many positives in its many potential future projects. One future project involves “tea water” (the liquid left from the process) which can be transformed into a productive by-product (concentrated fertilizer and treated water) that the dairy can use and that will eliminate the need for lagoons. Another future project involves introducing algae to the treated water in an algae bio-reactor which will allow the algae to grow, be pressed into oil, then processed into bio-diesel.

Crave Brothers: Crave Brothers Farmstead cheese operates a 750,000 gallon anerobic digester at their 2,000 acres , 750 dairy cow operation in Waterloo, WI. Built in 2007, this digester received $250,000 financial incentive from Focus on Energy for its construction. It is modeled after units in Germany and today produces enough electricity to power 400 homes. The operation sells $300,000 per year worth of electricity back to the local utility company, WE Energy, in addition to the profits it makes from selling waste digester material for animal bedding and organic potting mix.


Conclusions

LCA of Organic and Conventional Milk: The research reviewed by this task force suggested that the carbon footprint of milk produced in Europe and the United States averages approximately 1.0 kg of CO2-eq per kg of milk and was not substantially different whether the milk was produced following the USDA-mandated organic practices or the "conventional" practices. The variation around the means is likely to be very large. One European study found greater variations in carbon footprint of milk within the organic systems and within the conventional systems than between them. In another study, the one factor that changed the emission ranking and contributed to decreasing the organic milk carbon foot print was the carbon sequestered in the soil when the land is not cultivated but managed as perennial pastures. The reduction in nitrogen fertilizer usage and other external inputs (diesel fuel for example) on organic systems limits GHG emissions, but the reduction in animal productivity associated with these systems translated into greater land area requirement to supply a given amount of milk. In contrast the conventional systems focuses on maximizing productivity as a means to reduce GHG emissions and nutrient losses to the environment per unit of milk. Oftentimes in these systems producers attempt to maximize the efficiency of production of their animals and their crops separately, which have led to unnecessary environmental losses.

Conventional versus Organic Cropping Systems: The integration of pasture and rotational grazing into herd feeding strategies can impact the assessment of overall emissions in both organic versus conventional dairies. However, as compared to conventional production, organic dairy producers are required to integrate pasture within their herd’s diet, as per the regulation outlined by the National Organic Program. Conversely, while some conventional dairies utilize rotational grazing, it is not characteristic of all conventional management, particularly not those milking larger herds. Increasing the proportion of the cow’s diet derived from pasture invariably lowers total greenhouse gas emissions associated with feed production on a per hectare basis, due to the fact that these practices inhibit carbon loss and even sequester carbon depending on environment and soil characteristics. However, it is important to note that this may not be the case when other denominators are used to calculate this metric; for example, the impact of feeding strategies on total GHG of the system will change if the system is evaluated on a per unit of product (milk and meat) produced versus a per land area basis.

Social Dimensions: Our study of the social dimensions of organic milk exemplified by the Organic Valley Cooperative led us to conclude that the organic market serve the desires of the segment of the population concerned with a range of issues related to human health and how food is produced and processed. The "special" connection between the buyer and the producer is an essential component of the social sustainability of the system. In contrast the conventional system is predicated on the idea of producing abundant, safe and economical food, or in other words, to produce "lots" of food for "lots" of people to buy at the lowest possible price.  

Acting only on the physical or biophysical reality will limit our choices and outcomes. We need to understand the social and regulatory situation, the examples of options for social organization and for policy, and we need to experiment and communicate about what we learn, in order to advance our knowledge and practice of sustainability.


Citations

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Bell, M. J., E. Wall, G. Russell, G. Simm and A. W. Stott. 2011. The effect of improving cow productivity, fertility, and longevity on the global warming potential of dairy systems. Journal of Dairy Science 94: 3662-3678.

Beukes, P. C., P. Gregorini, A. J. Romera, G. Levy and G. C. Waghorn. 2010. Improving production efficiency as a strategy to mitigate greenhouse gas emissions on pastoral dairy farms in New Zealand. Agriculture, Ecosystems & Environment 136: 358-365.

Cederberg, C. and B. Mattsson. 2000. Life cycle assessment of milk production — a comparison of conventional and organic farming. Journal of Cleaner Production 8: 49-60.

Cederberg, C., U. M. Persson, K. Neovius, S. Molander and R. Clift. 2011. Including Carbon Emissions from Deforestation in the Carbon Footprint of Brazilian Beef. Environmental Science & Technology 45: 1773-1779.

Chadwick, D., S. Sommer, R. Thorman, D. Fangueiro, L. Cardenas, B. Amon, et al. 2011. Manure management: Implications for greenhouse gas emissions. Animal Feed Science and Technology 166–167: 514-531.

Dutreuil, M., M. A. Wattiaux, C. A. Hardie and V. E. Cabrera. 2014. Feeding strategies and manure management for cost-effective mitigation of greenhouse gas emissions from dairy farms in Wisconsin. Journal of Dairy Science 97: 5904-5917.

Global Research Alliance. 2014. Reducing greenhouse gas emissions from livestock: Best practice and emerging options. Accessed March 24, 2015, here

Flysjö, A., M. Henriksson, C. Cederberg, S. Ledgard and J. E. Englund. 2011. The impact of various parameters on the carbon footprint of milk production in New Zealand and Sweden. Agricultural Systems 104: 459-469.

Haas, G., F. Wetterich and U. Kopke. 2001. Comparing intensive, extensified and organic grassland farming in southern Germany by process life cycle assessment. Agriculture, Ecosystems & Environment 83: 43-53.

O’Brien, D., J. L. Capper, P. C. Garnsworthy, C. Grainger and L. Shalloo. 2014. A case study of the carbon footprint of milk from high-performing confinement and grass-based dairy farms. Journal of Dairy Science 97: 1835-1851.

Osterholz, W. R., C. J. Kucharik, J. L. Hedtcke and J. L. Posner. 2014. Seasonal Nitrous Oxide and Methane Fluxes from Grain- and Forage-Based Production Systems in Wisconsin, USA. J. Environ. Qual. 43: 1833-1843.

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Acknowledgements

This project would not have been successful without the contributions of the outstanding students in our Food Systems, Sustainability, and Climate Change class.  We would particularly like to acknowledge the wonderful and challenging questions, and the specific knowledge that students with different areas of expertise provided.  

About the Authors

To be posted.


KeywordsCase Study: Carbon Footprint of Organic versus Conventional Milk   Doc ID49930
OwnerKate A.GroupFood Production Systems &
Sustainability
Created2015-04-02 13:48:30Updated2019-01-28 10:45:45
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