Feed

Lactating Cow Ration Dry Matter Make-up

Evaluators are encouraged to select feed ingredient proxies when appropriate. The following table summarizes recommendations based on questions received to-date:

Feed Ingredient FARM ES Proxy
Earlage                       Corn silage
High-moisture corn Corn Grain
Rye hay                       Grass hay
Rye silage                   Grass silage
Snaplage                     Corn silage
Sorghum Sudan        Other
Soybean hulls            Other

The model makes assumptions about the rations for the other animal classes based on the findings from the LCA research. The GHG / energy footprint results include the impacts of feed from all classes (lactating, dry, heifer, etc.).

There are many farms that need to use the ‘all other feed’ category quite heavily. It can be difficult to know the ingredient breakdown for protein mixes. One could consider checking whether the farm can get an ingredient breakdown for the protein mix. That would make the results of FARM ES much more accurate.

If it’s not possible to find out the ingredient breakdown, then enter the data as given into FARM ES. There is a question that will pop up in the evaluation “To help FARM ES improve, please provide a little information about what is included in the ‘All Other Feed’ category for the farm’s lactating cow ration:”. Enter that it is a complete protein mix. The response will go into an anonymized dataset for researchers to inform improvement over time.

Even if you know the primary ingredient of the protein mix, it would be difficult to know what percentage of the protein mix the primary ingredient accounts for. That may not be entirely accurate, so it would be best to include the entire protein mix as “All Other Feed” until you can find out more about the mix itself.

The “Feed Emissions” category uses emissions factors developed following LCA methods (described in this paper). The emissions factors take into account USDA data on typical production practices by region. The amount of each ration ingredient is multiplied by the applicable emissions factor to generate the emissions footprint.

Most byproduct feed ingredients are not separately accounted for in FARM ES. They should be categorized under “all other feed”. The 11 primary feed types included in FARM ES made up 82% of the feed emissions in the original LCA research – so that’s why the model focuses efforts there. The supplementary material in these two papers gives more info about the assumed rations by region in the LCA research (https://www.sciencedirect.com/science/article/pii/S0958694612001999#appsec1 and https://www.sciencedirect.com/science/article/pii/S0958694612002051#appsec1)

Work is underway to include certain byproduct feeds in Version 3 of FARM ES.

Crop Production

Dairies vary widely in the amount of feed they grow on-site versus purchase, which can also vary by year. Approximately 60% of dairy feed is sourced off-farm. Given that variability, FARM ES focuses on the dairy operation itself while using feed emissions factors for feed production. The feed emissions factors take into account USDA data on typical production practices by region. Using feed emissions factors allows FARM ES to provide a holistic, cradle-to-farmgate footprint – whether feed is sourced on-site or off-site. Version 3 of FARM ES, coming in 2024, will offer dairy farms the option to enter information about their unique cropping practices. It will still use feed emissions factors for any feed sourced off-site or for farms that choose not to enter the additional data.

Various forms of cropping methods are all accounted for in the “Feed Emissions” bucket.
The “Feed Production” emissions category uses emissions factors developed following LCA methods (described in this paper). The emissions factors take into account USDA data on typical production practices by region. The amount of each ration ingredient is multiplied by the applicable emissions factor to generate the emissions footprint.

Essentially, the model makes assumption about cropping practices in each region. It does not ask about the producer’s unique practices.

The data is collected for informational purposes only at this point. It does not impact the results. The data will be used to inform future model developments.

Results

Regional and National Benchmarking

The methodology for the enteric emissions footprint is described in Section 2.2.2 of the Thoma (2013) paper. The researchers analyzed a number of estimation methods and landed on one from Ellis (2007).
FARM ES uses DMI to estimate enteric emissions as described in Section 2.5.

The regional and national benchmarks for FARM ES V2 do not include feed production. This is because the feed emissions factors were updated for Version 2, but there was no way to update the benchmarks because the original ones were generated through a national survey of farms.

The regional and national benchmarks are static averages from the LCA research published in 2013. They are not currently dynamic based on data in FARM ES.

General

About FARM ES

As with the rest of the FARM Program, FARM ES is on a 3-year version cycle. Version 2.0 was released in 2020.

FARM collaborates with the Innovation Center for U.S. Dairy on updates to FARM ES. The Innovation Center leads development, maintenance, and updates to the GHG and energy footprint model that powers FARM ES. FARM ES and the Innovation Center regularly review and incorporate new science to (1) ensure robust and reliable results; and, (2) meet expanding interests and needs of farmers and FARM Participants.

Additionally, new metrics are added to FARM ES that are not part of the GHG / energy footprint model, but important for dairy farm sustainability. For example, Version 2.0 added questions about written Nutrient Management Plans.

Unlike other sustainability tools, FARM ES is made by and for the dairy community. The farm’s personal information is private because that is our commitment to our dairy community. The FARM Program and the Innovation Center only use aggregated, anonymous results in public reports. Additionally, anonymized data may be used by the Innovation Center for industry-wide sustainability research.

No. While it is ideal to conduct the FARM ES evaluation on-site, remote evaluations are acceptable when conducted using best practices for data collection and review.

Conducting FARM ES evaluations on all of a Participant’s farms may be impractical or cost prohibitive. Random sampling is a recognized approach by the GHG Protocol for addressing the challenges of Scope 3 data gathering (See the GHG Protocol: Technical Guidance for Scope 3 Reporting for more information: (https://ghgprotocol.org/sites/default/files/standards/Scope3_Calculation_Guidance_0.pdf). The GHG Protocol maintains frameworks for measuring and managing GHG emissions. It is widely used for reporting to CDP.

FARM recommends using stratified random sampling to overcome that barrier while still getting an accurate estimate of Participant-wide GHG emissions intensity. The FARM ES Sampling Protocol stratifies farms based on milk volume and geography.

FARM ES is free for FARM Program Participants and dairy farms. The only cost comes in the form of staff time to conduct the FARM ES evaluation.

Ups and downs in GHG emissions and other sustainability measures are normal because of annual variability in herd productivity, weather, feed availability, economics, and more. Our focus is on long-term trends.

FARM Participants may conduct FARM ES Evaluations at any frequency best suited to their organization and their B2B relationships. FARM recommends that Participants conduct evaluations at least as frequently as the FARM ES Version Cycle (i.e. every 3 years). In practice, if a FARM Participant is using the FARM ES sampling protocol to select a random sample of farms, FARM recommends they complete evaluations on those farms over the course of 3 years.

Yes. FARM ES Evaluators must successfully complete an online training.

FARM ES Evaluations are conducted by second party Evaluators. These individuals are employees or contractors of FARM Participants (dairy cooperatives and processors). Some FARM ES evaluators are 100% focused on FARM ES; others wear multiple hats, such as field technician or FARM Animal Care evaluator.

FARM ES is open to any FARM Program Participant. Email dairyfarm@nmpf.org to request a Participation Form and additional instructions.

Individual dairy farms, whether associated with a FARM Program Participant or not, can conduct self-evaluations using the FARM ES tool. Email dairyfarm@nmpf.org for more information.

No. FARM Program Participants can voluntarily elect to enroll in FARM ES. It is separate from FARM Animal Care.

FARM ES estimates farm-level greenhouse gas (GHG) emissions and energy intensity. It uses a scientific, peer-reviewed model based on IPCC Tier 2 methods and life cycle assessment (LCA) research. Input data includes milk production records, herd data, rations, manure management, and energy use. The results are pounds of carbon dioxide (CO2) equivalent per pound of fat and protein corrected milk (FPCM). FPCM normalizes milk to the same scale, so that farms can track their results consistently even if milk output changes year to year. With each FARM ES evaluation, farmers and cooperatives can assess change over time, identify areas of operational improvement, and report best practices to corporate customers.

The Farmers Assuring Responsible Management (FARM) Environmental Stewardship (ES) program area enables FARM Participants to evaluate and communicate a dairy farm’s environmental achievements in a secure, confidential platform. The online tool combined with the program’s resources assist with setting a path for continuous improvement in ways that make business sense. Today, FARM ES focuses on greenhouse gas (GHG) emissions, energy use, and Nutrient Management Plans.

General

First, make certain that the data input is correct. It is possible there was an error in providing the data.

If you and the farm are sure that the data point is correct and that it falls outside of the boundaries of FARM ES, IT can run the evaluation with the correct data. They have permissions to enter information that falls outside the set range. You can email them directly at farmtechsupport@nmpf.org and let them know that you have a FARM ES evaluation with a data point that falls outside of the allowable range.

You can view your recent evaluations in the Evaluations App. You can select it, edit the data, and resubmit. If it has been more than 90 days since the evaluation was submitted, please email FARM tech support.

FARM ES is not currently designed to collect data for existing carbon markets. As we look toward FARM ES Version 3, we are evaluating how FARM ES data collection could align with the data requirements of private carbon markets. At this time, few private carbon markets offer credits for carbon reductions specific to dairy operations (e.g. enteric emissions reductions).

Yes. FARM Participants can aggregate FARM ES data for Scope 3 reporting, either for their own organization’s Scope 3 reporting purposes or for reporting to dairy buyers. In fact, the Innovation Center for U.S. Dairy has created Scope 3 GHG Inventory Guidance for dairy cooperatives and processors, which recommends the use of FARM ES.

The Scope 3 GHG Inventory Guidance has been reviewed by the GHG Protocol and is in conformance with the requirements set forth in the Corporate Value Chain (Scope 3) Accounting and Reporting Standard. The GHG Protocol maintains frameworks for measuring and managing GHG emissions. It is widely used for reporting to CDP.

A company’s GHG emissions are divided into Scopes 1, 2, and 3. In a nutshell, they are as follows:

Scope 1: Emissions that occur on-site. For example, if you burn natural gas for energy, the GHG emissions are directly released during that process on-site.
Scope 2: Emissions that occur elsewhere, but for which the company has operational control. The best example is electricity. The company has operational control over whether the lights are on or off, but the emissions occur off-site where the electricity is generated.
Scope 3: All other indirect emissions not covered in Scope 2. This includes all of the upstream emissions that occurred before the company had operational control over a process or product (e.g. for a cheese manufacturer, this would include GHG emissions to create the milk that the company purchased). It also includes downstream emissions (e.g., emissions that occur after the cheesemaker’s products leave the plant, like those at the grocery store or when consumers dispose of packaging.)
GHG emissions are categorized into each Scope based on the company’s perspective. So for a cheese manufacturer, on-farm emissions are considered Scope 3. But for the farmer, those emissions are Scope 1 and 2.

You can find out additional details in the Innovation Center for US Dairy’s Scope 1 & 2 GHG Inventory Guidance and Scope 3 GHG Inventory Guidance for dairy cooperatives and processors.

Farm Profile

Facility Information

If the farm’s multiple facilities are co-located or very close to one another, you could do one evaluation for the farm as a whole. Enter the data into one of the facility accounts. In the future, we’ll have the ability to enter the evaluation for the farm as whole rather than only at facility level.

However, if the facilities are in different states, we recommend two separate evaluations.

Production

Production

For the purpose of the FARM ES, it is best practice to include total milk production, even dumped milk.

Herd Profile

Enter the purchased heifers into the field ‘Annual Avg Number of Heifers (2 months to first calf) raised OFF farm’. For the purchased dry cows, we would recommend including them in the ’Annual Avg Herd Size (Lactating and Dry)’. For example, if there are 1,000 head, and they purchase maybe 20 extra dry cows, put the total average herd size as 1,020.

If the facilities are close together geographically, you can do one evaluation for the farm as a whole and enter the information into one of the facility accounts. For the ‘percent’ dry field, enter it assuming the dry cows do not leave the facility.

FARM ES is LCA-based, so it’s trying to get the GHGs associated with the milk. Even though the dry cows leave that facility, the environmental impact associated with caring for the dry cows (feed, etc.) should be ‘associated’ with the milk from the facility that is doing the milking.

The difference between 0-2 months and older than 2 months would be in the ration amount and breakdown assumptions.

The reason FARM ES distinguishes the difference between animals raised off-farm is within the manure emissions section of the evaluation. FARM ES asks about the farm’s manure management, but for animals raised off-site there is no user information on the type of manure management – so the model uses assumptions about regional manure management strategies based on the LCA research findings.

Enter all calves as raised “off-farm” for 0-2 months, then enter that they are all raised as “on-farm” for 2 months and up. FARM ES distinguishes between on-farm and off-farm for the purpose of calculating manure emissions – it uses farm-specific information about the manure management systems for any animals raised on-site; and average, non-user-specific information about manure management systems for animal raised off-site.

Beef Production

The purpose of the ‘beef production’ section of FARM ES is to separate out any of the GHGs from the dairy farm that should be attributed to beef. Cull cows, for example, produce 2 products over their lifetime: milk and beef. FARM ES makes an estimate for how much of the GHG emissions should be attributed to milk versus beef based on the number of cull cows and their approximate weight. Calves that are sold are also incidental to milk production – they’re a necessary part of milk production. Cull cows and calves sold are both incidental to milk production – a necessary part of the process that we want to separate out for GHG accounting purposes.

For operations that are NOT raising animals to finishing and selling the animals as calves, they can be included in the ‘Annual Number sold for Beef’ section. Be sure to not include calves sold as replacement animals to other dairies.

For operations that ARE raising animals to finishing, make a judgment call on when those animals leave the ‘dairy’ side of the business and enter the ‘beef’ side of the business. We have determined that a good arbitrary cutoff is weaning. Include calves being raised for beef on-site until they are weaned. At the point of weaning, consider them ‘sold’ by the dairy and include the number and average weight per cow (lbs) in the evaluation.

Energy

Renewable Energy

On-Site renewable includes digester electricity / heat, solar, or wind. On-site non-renewable is everything else. We recognize that that does not capture grid electricity from renewable sources. Our hope is to reflect the grid electricity renewable mix when we update the electricity factors in the future.

Energy Source

Selling or retaining RECs does not impact the overall energy use measure (in MJs) but does impact whether the energy is categories as “renewable” or “nonrenewable”. If the REC for that renewable energy is sold, then that energy is placed in the “nonrenewable” category. If the REC is retained, then the energy stays in the renewable energy category.

Net metering does not impact the total MJs, but like REC ownership, it affects where it is placed in terms of renewable versus non-renewable.

Here are the energy factors used in FARM ES:

electricity east* 14.07772 MJ primary / kWh electricity
electricity west* 11.10698 MJ primary / kWh electricity
diesel 155.4316 MJ primary / gallon diesel
biodiesel 68.16122 MJ primary / gallon biodiesel
fuel oil 180.5243 MJ primary / gallon fuel oil
propane 104.001 MJ primary / gallon propane
natural gas 139.5043 MJ primary / therm (= ccf) natural gas
gasoline 164.8766 MJ primary / gallon gasoline

* North America is comprised of two different major power grids, east and west. The data source for the electricity factors only offered factors for east and west at the time that the FARM ES model was created.

Diesel use for manure spreading does not need to be entered into the energy use section of FARM ES– the model already makes assumptions about manure spreading energy use within its feed emissions factors in the model.

Diesel to scrape the pens is considered a dairy activity and should be included in the energy use section of FARM ES.

Yes, electricity to run sand separators should be included. For energy use, the model needs anything that is NOT related to cropping activities.

Yes, electricity to run digesters, manure separators and sand separators should be included. For energy use, the model needs anything that is NOT related to cropping activities.

Yes, natural gas to dry manure solids for bedding should be included. For energy use, the model needs anything that is NOT related to cropping activities.

FARM ES does not yet account for benefits of RNG production from digesters. If the digester gas is solely being used for RNG, then the response would be 0% for the questions about electricity and heat generation in the evaluation.

Assuming the main driveway is what’s used to haul milk, etc., plowing is critical for the dairy operation during the winter and energy used for that purpose should be included.

Yes, fuel oil would be the best of the available options. Make a note of it in the “Notes” field in case FARM is ever able to accommodate the specifics of waste oil in the future.

FARM ES cannot provide estimates or industry averages for propane use because it varies tremendously. We would recommend referencing a FARM ES evaluation on a farm of somewhat similar size and style. Use that farm’s propane use as a proxy estimate.
Another option is to find out if the farm has a sense of propane use from a previous year that can be used as an estimate. Or, if the farm knows how much money they spent on propane you could use that to back-estimate the actual usage.

You could also reach out to local extension services for an idea of an estimate.

You should enter 40%. The 60% that is used to power the digester does not count toward the heating potential utilized. When we think about ‘heat potential’ and ‘energy potential’ used we should always think of the digester and its processes as something that can fit in an envelope. Anything we add to the envelope (electricity for example) needs to be included as an input and anything that leaves the digester unit can be included as an output. Therefore, if electricity (or heat) is created by the digester but goes back to running the digester, it should still be considered ‘in the envelope’ and therefore not included as an output. For the question at hand, only the heat used to warm the water for use in the farm can be counted as heat potential used.

FARM ES produces a lifecycle based GHG emissions estimate (cradle to farmgate). The electricity emissions factor is also lifecycle based. It is 0.842 kg CO2e / kg FPCM. This was originally derived from the ecoinvent database. We are exploring updating the electricity and energy emission factors in the future using DOE factors (e.g. those found in the GREET model). We do not recommend replacing the emissions factor with the eGRID factor since it isn’t lifecycle based.

Manure

Manure

Manure hauling, application, and cropping methods are all accounted for in the “Feed Emissions” bucket. The “Feed Production” emissions category uses emissions factors developed following LCA methods and using USDA data. The model makes assumption about average manure hauling / application methods.

The 5% solids cut-off is a good rule of thumb for many situations. However, it is correct that the best distinction of an anaerobic lagoon is one where there is some treatment and deliberate water addition (ie. If we flush the manure out of the barns, if we add water to vacuum it, if we do SLS, etc.). In a case where the only water added is rainwater and maybe wash water (not flush water), the manure pit is likely best described as a slurry.

FARM ES does not currently account for GHG offsets from connecting to a gas pipeline.

If manure solids are used as bedding, they should be categorized as “solid storage” in the FARM ES evaluation, not as “deep bedding”.

We only have the option to specify 2 management strategies for the solid fraction after SLS, so there isn’t a perfect answer to match the farm’s situation. If we could enter more than 2 strategies, we could capture all 4 of the above and weight them by the amount of time (in-vessel composting, windrow composting, sold off-farm, and bedding) – but since we can only do 2, I would focus on those where the manure spends the most ‘time’ of the year, e.g. bedding and sold off farm.

If a farm is using a manure management system not included in FARM ES, the recommendation is to determine the best proxy system that is included in the model.

We would recommend using ‘deep bedding with storage > 1 month’ as a proxy for a compost barn system. The FARM ES model does not list ‘compost barn’ as an option because there is currently insufficient research available on the GHG emissions from compost barn systems.

The Supplementary Data from the Asselin-Balencon paper (https://www.sciencedirect.com/science/article/pii/S0958694612001999) contains a table of manure management emissions factors used in FARM ES (Table S3). The factors are derived from IPCC (2006).

The boundary of the ‘manure’ section of FARM ES is storage and handling. The emissions factor for manure management therefore does not cover emissions after the manure is applied. Because daily spread does not involve manure storage, it has a lower manure emissions factor. Emissions after land application (including daily spread) are incorporated in the feed production emissions category.

The feed production emissions category, which includes an estimate of emissions from land application, is based on LCA research using USDA and other datasets. It is not specific to the farm’s individual field practices.

For additional context, see the following straightforward explanation of the emissions tradeoffs between daily spread and other manure storage. There are many considerations that go into manure management decisions beyond GHGs (e.g. water quality, soil health, etc.). UW Extension has fact sheets on the topic of GHGs and manure.

This situation would not be considered solid storage. Bedded pack has different emissions level than solid storage in part because urine and additional bedding materials are added over time.

If a farm is conducting solid-liquid separation after the anaerobic digester, they can select “solid liquid separation” for the effluent, then indicate the separation efficiency, how the solids are managed, and how the liquid is managed.

Nutrient Management Plan

NMP = nutrient management plan; CNMP = comprehensive nutrient management plan; MMP = manure management plan.

These acronyms are regulatory distinctions of nutrient management plans depending on the size of dairy and the state where it’s located. Generally, a CNMP applies to CAFOs – though some smaller farms need one depending on how they handle manure. NMPs will be the most common; generally applicable to most size dairies above a certain threshold. MMPs vary – some states have them for smaller dairies, though not necessarily required by regulation. For example, this is how it’s broken down in PA: https://extension.psu.edu/programs/nutrient-management/manure/understanding/what-type-of-plan-do-you-need-for-your-farm

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