Tag: beef

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Particulate matter from open lot dairies and cattle feeding: recent developments

The research community is making good progress in understanding the mechanical, biochemical, and atmospheric processes that are responsible for airborne emissions of particulate matter (PM, or dust) from open-lot livestock production, especially dairies and cattle feedyards.  Recent studies in Texas, Kansas, Nebraska, Colorado, California, and Australia have expanded the available data on both emission rates and abatement measures. Although the uncertainties associated with our estimates of fugitive emissions are still unacceptably high, we have learned from our recent experience with ammonia that using a wide variety of credible measurement techniques, rather than focusing on one so-called “standard” technique, may be the better way to improve confidence in our estimates.  Whereas the most promising control measures for gaseous emissions continue to be dietary strategies  with management of corral-surface moisture a close second for particulate matter, corral-surface management and moisture management play comparable roles, depending on the mechanical strength of soils and the availability of water, respectively.  The cost per unit reduction of emitted mass attributable to these abatement measures varies as widely as the emissions estimates themselves, so we need to intensify our emphasis on process-based emissions research to (a) reduce the variances in our emissions estimates and (b) mitigate the contingency of prior, empirically based estimates.  As a general rule, although cattle feedyard emission factors may be thought a reasonable starting point for estimating emissions from open-lot dairies, such estimates should be viewed with suspicion.

Purpose          

Document the state of the art of particulate-matter (PM) emissions from open-lot livestock facilities, including emission fluxes and abatement measures.

What did we do?

We conducted (a) field research at commercial, open-lot livestock facilities in the southern High Plains and (b) an up-to-date review of the latest literature concerning primary particulate matter emission fluxes and the abatement measures appropriate to the source type. Field research included time-resolved concentration measurements upwind and downwind of the livestock facilities during the hottest, driest times of the year (in the case of dairy emissions) and throughout the year (in the case of beef feedyards); and a 5-month evaluation of stocking density manipulation using electric cross-fences that preserve optimum bunk space for beef cattle on feed. The literature review surveyed research findings from anywhere in the world that were published in refereed journals as recently as March 2015 concerning the same topics.

What have we learned?

Increasing the stocking density of fed beef cattle as compared to the industry-wide average during hot, dry weather suppresses dust emissions to a measurable and reasonably consistent degree. Concentrations of PM measured downwind of open-lot dairies vary throughout the day, though to a lesser degree and at lower overall concentrations than those measured downwind of nearby beef cattle feedyards, likely reflecting (a) the comparatively lower intensity of the dairy animal’s physical activity and (b) the greater diurnal uniformity of animal-activity patterns in dairies as compared to those in cattle feedyards. Stocking density manipulation does not appear likely to influence dairy dust emissions to the same degree as it influences feedyard dust emissions. Our confidence in emission-flux estimates from these open-lot systems suffers from a lack of methodological diversity; that confidence would be greatly bolstered by the deployment of measurement techniques that differ from the standard inverse-dispersion-modeling paradigm. The integrated horizontal flux (IHF) approach to emissions estimation, which we are now testing at a cattle feedyard in the Texas Panhandle, will provide some corroborating evidence that will allow us to narrow the range of PM flux estimates in the research literature, a range that now spans more than an order of magnitude when expressed on a per-animal-unit basis.

Future Plans

We will continue long-term, ground-level monitoring of time-resolved PM concentrations at a commercial cattle feedyard in the Texas Panhandle; continue our ongoing tests of the IHF flux-estimation technique; and evaluate eye-safe lidar as a path-averaging monitoring technology for the intermediate path lengths (50-300m) that will permit experimental discrimination of concentration data downwind of adjacent pen areas featuring different dust-abatement measures.

Authors    

Brent Auvermann, Professor, Texas A&M AgriLife Extension Service b-auvermann@tamu.edu

K. Jack Bush and Kevin R. Heflin, Research Associates, Texas A&M AgriLife Research

Additional information              

6500 Amarillo Blvd. West, Amarillo, TX 79106-1796, (806)670-8081 (cell)

Acknowledgements      

USDA-NIFA Contract Nos. 2010-34466-20739 and 2009-55112-05235; Texas A&M AgriLife Research; JBS Five Rivers Cattle Feeding; Texas Air Research Center; Texas Cattle Feeders Association

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2015. Title of presentation. Waste to Worth: Spreading Science and Solutions. Seattle, WA. March 31-April 3, 2015. URL of this page. Accessed on: today’s date.

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Adaptation and Risk Management

Food production is dependent on weather and climate. Agriculture must always be planning and preparing for weather or responding to weather as it happens. Adaptation to weather and climate has occurred since farming started and will continue to occur as we move forward in the future. The rate of adaptation is the key to keep up with the rate that the climate changes.

Factsheet: Adapting to a changing climate: A planning guide (PDF; 44 pp)

Climate Change Adaptation is the most common terminology used to discuss how organisms and ecosystems adjust to changing extremes or patterns in weather over time. Most cities and states are drafting plans to help prepare for weather events such as flooding, extreme heat events, disease outbreaks, and others.

Risk Management is a term more commonly used in business and refers to the process of identifying, assisting, and prioritizing of risk followed by some application of resources (usually time or money) to prevent or minimize the negative consequences.

A report from Iowa Beef Center in 1995 discussed a survey of beef producers who lost cattle in a 13 county area over a 2 day period. For those farmers loosing animals, the impact was significant but a quote from the paper sums up the cost benefit decision that must be made when planning for a changing climate.

“How much can a feedlot operator spend to protect against a weather event that has occurred only six times in the last 101 years?”

This is a real and critical question that must be asked. What if this similar type of heat event started occurring every 10 years, or every 5 years? This changes the equation when looking at risk and reward or cost benefit to the implementation of practices or systems to deal with extreme heat.

Adaptation Strategies

Adaptation strategies lay on a continuum with the least drastic listed first (increasing resilience) and most drastic last (transformation).

  • Increasing resilience is a level of adaptation that is similar to what has occurred in the past. As climate changes, technologies or management improves or adjusts to those changes. Resilience has resulted in animal housing, irrigation, diet, genetics, management and other factors that allow farms to be profitable with standard weather variability.
  • Reducing vulnerability is adaptation at the next level with larger and longer term changes in an existing operation to reduce the risk of current or future climate trends. Things such as bringing in heat tolerant genetics, additional cooling capacity in the buildings, or farm diversification. These strategies require a higher investment and are focused on operational changes that allow for profitability into the future.
  • Adaptation through transformation are those changes where the current farming system is nearly abandoned due to climate changes. Complete changes are made in cropping or animals or a new business venture replaces the one on the current site. Transformation might also include the general migration of an industry to a new climate region.

cattle loafing on a bed pack in their barn

Any adaption strategy must be chosen as a function of the site specific features of the farm. Geographic location, current management, current finances, long term and short term farm goals and other considerations need to be made when evaluating farm management and business changes. In addition, the strategy must be based on the current or predicted trends in weather and the impacts this might bring to the farm. A farm prone to flooding in a region where flooding trends are increasing may be interested in a transformational adaptation strategies like relocation than a farm that never experiences flooding.

Cost benefits of these adaptation strategies are not simple. If we were only comparing damage cost to the cost to prevent the damage, the calculation would be simple. Unfortunately, the damage cost is a function of the probability of the weather event and its intensity. For now we must rely on recent weather trends and future climate predictions. Therefore, it is important to be informed about climate change, the impacts of climate change on a local and global level and the economics of adaptation options. Site assessment and planning are key to making good long term adaptation decisions.

Educator Materials

If you would like a copy of the original slides or downloadable copy of the video, please fill out this form. If you use these materials for educational purposes, please send an email to e.whitefield@wsu.edu with how you used the video and how many people watched, to help us improve our resources and document our impact.

Recommended Reading/Viewing

Agricultural Adaptation to Climate Change: Economic and Environmental Implications Vary by Region More… (USDA Economic Research Service, 2012)

Dairy Cattle – Heat Stress

Beef Feedlot Cattle – Heat Stress

Rangeland/Pasture – Drought

Swine Heat Stress

Poultry Heat Stress

Drought: Water Quality and Quantity

Disaster Preparedness Resources

Acknowledgements

Author: David Schmidt, University of Minnesota schmi071@umn.edu

This material was developed through support from the USDA National Institute for Food and Agriculture (NIFA) under award #2011-67003-30206.

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Particulate Matter Adjacent to Cattle Deep-Bedded Monoslope Facilities

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Why Study Monoslope Barns and Air Quality?

Confined cattle facilities are an increasingly common housing system in the Northern Great Plains region.  Many of these facilities add organic bedding material to the pens once or twice per week.  Particulate matter concentrations and emissions from these facilities have not been evaluated.  The objective of this study was to quantify particulate matter concentration adjacent to a deep-bedded mono-slope facility housing cattle and to compare the concentrations during normal operation and a bedding event.
Average 24-hr total particulate matter concentration of ambient air collected from a beef deep-bedded monoslope barn.

What Did We Do?

Three Lo-Vol Particulate Samplers were placed 4.6 m from the north side of the building, and three were placed 4.6 m from the south side of the building with 36.6 m between the samplers on each side.  Average sampler flow rate was 16.7 L/min.  Samples were collected over two five-day periods (April and June 2011).  Each sample period included three 24-hr collections during normal operation and two 3-hr collections during a bedding event.  Filters were collected, conditioned for 48 hr at 21.1 °C and 35% humidity, then weighed in micrograms and analyzed on a Beckman Coulter LS 230 to determine total suspended particulate matter (TSP).

What Have We Learned?
Average 3-hr total particulate matter concentration of air collected during a bedding event of beef deep-bedded monoslope barn.

During the April sampling period, average 24-hr TSP concentration ranged from 40.1 to 91.4 µg/m3 during days of normal operation. Average 3-hr particulate matter concentration during bedding events ranged from 281.8 to 540.5 µg/m3.  During the June sampling period, 24-hr TSP concentration on days of normal operation ranged from 52.7 to 64.6 µg/m3, while 3-hr particulate matter concentration during bedding events averaged 302.4 to 1684.2 µg/m3. Sweeten et al. (1998) reported average TSP concentrations of 410 µg/m3 measures for 24 hr periods on open feedlots in Texas. In general, particulate matter concentrations adjacent to the deep-bedded monoslope facility were lower than previously reported for open lot feedlots.  Concentrations of TSP were higher during the 3-hr bedding event than during normal operation.

Future Plans

To compliment this research, data has been collected from two monoslope beef barns over the past two years as part of an AFRI-funded research grant.  MiniVol particulate samplers were used to determine PM-10 and PM-2.5 concentrations over 24-hr periods.  Data collected from this project will further define the particle size of dust being emitted from these facilities.

Authors

Mindy J. Spiehs, Research Animal Scientist, USDA – ARS Meat Animal Research Center, Clay  Center, NE, mindy.spiehs@ars.usda.gov

Greg A. Holt, Research Leader, USDA- ARS Cotton Production and Processing Research Unit, Lubbock, TX

Kris D. Kohl, Extension Agricultural Engineer, Iowa State University Extension and Outreach, Storm Lake, IA

Beth E. Doran, Extension Beef Specialist, Iowa State University Extension and Outreach, Orange City, IA

David B. Parker, Professor and Director, Commerical Core Laboratory, Palo Duro Research Center, West Texas A & M University, Canyon, TX

Erin Cortus, Assistant Professor, South Dakota State University, Brookings, SD

Additional Information

Acknowledgements

The authors wish to acknowledge James (Bud) Welch and Alan Kruger for assembly and disassembly of  the particulate matter sampling equipment and Ron and Clayton Christensen for the use of their cattle facility.  Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.  USDA is an equal opportunity provider and employer.

 

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2013. Title of presentation. Waste to Worth: Spreading Science and Solutions. Denver, CO. April 1-5, 2013. URL of this page. Accessed on: today’s date.

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Staying Ahead of the Curve: How Farmers and Industry Are Responding to the Issue of Climate Change

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Why Is This Topic Important?

Several farmers, ranchers, and industry groups are leading the way on the issue of climate change. 

What Will Be Learned In This Presentation?

These panelists will share how their farm or industry is responding to climate change, what factors are driving their decision to make changes, and the impact of climate change on long-term planning. This moderated session will encourage audience questions and facilitate exchange of ideas on how the agriculture industry can meet this challenge.

Presenters

David Smith, Southwest Region Coordinator Animal Agriculture and Climate Change Project, Texas A&M University dwsmith@ag.tamu.edu and Liz Whitefield, Western Region Coordinator, Washington State University

  • Jamie Burr –  Tyson Foods, Chair National Pork Board Environment Committee
  • Abe Collins – cattle grazier, Cimarron Farm, Regenerative Farmscaping consultant, Board Member Soil Carbon Coalition
  • Paul Helgeson – Sustainability Director with Gold’n Plump Chicken
  • Bryan Weech, Director Livestock & MTI Commodity Lead, World Wildlife Fund
  • Andy Werkoven – dairyman and anaerobic digester co-owner, Werkhoven Dairy Inc., 2012 winner of US Dairy Sustainability Award

 

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Photometric measurement of ground-level fugitive dust emissions from open-lot animal feeding operations.

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Abstract

Fugitive dust from confined livestock operations is a primary air quality issue associated with impaired visibility, nuisance odor, and other quality-of-life factors.  Particulate matter has conventionally been measured using costly scientific instruments such as transmissometers, nephelometers, or tapered-element, oscillating microbalances (TEOMs).  The use of digital imaging and automated data-acquisition systems has become a standard practice in some locations to track visibility conditions on roadways; however, the concept of using photometry to measure fugitive dust concentrations near confined livestock operations is relatively new.  We have developed a photometric method to estimate path-averaged particulate matter (PM10) concentrations using digital SLR cameras and high-contrast visibility targets.  Digital imaging, followed by automated image processing and interpretation, would be a plausible, cost-effective alternative for operators of confined livestock facilities to monitor on-site dust concentrations.  We report on the development and ongoing evaluation of such a method for use by cattle feeders and open-lot dairy producers.

Purpose

To develop a low-cost practical alternative for measurement of path-averaged particulate matter (PM10) concentrations downwind of open-lot animal feeding operations.

What Did We Do?

Working downwind of a cattle feedyard under a variety of dust conditions, we photographed an array of high contrast visibility targets with dSLR cameras and compared contrast data extracted from the photographs with path-averaged particulate matter (PM10) concentration data collected from several TEOMs codeployed alonside the visibility targets.

What Have We Learned?

We have developed a photometric method to estimate path-averaged particulate matter (PM10) concentrations using digital SLR cameras and high-contrast visibility targets.  Using contrast data from digital images we expect to predict PM10 concentrations within 20% of TEOM values under the dustiest conditions.  Digital imaging, followed by automated image processing and interpretation, may be a plausible, cost-effective alternative for operators of open-lot livestock facilities to monitor on-site dust concentrations and evaluate the abatement measures and management practices they put in place.

Future Plans

We intend to improve the prediction accuracy of the photometric method and automate it such that it can be easily adapted for use as a cost-effective alternative for measuring path-averaged particulate matter (PM10) concentrations at cattle feedyards and open-lot dairies.

Authors

Brent Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research.  b-auvermann@tamu.edu

Sharon Preece, Senior Research Associate, Texas A&M AgriLife Research; Brent W. Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research; Taek M. Kwon, Professor of Electrical and Computer Engineering, University of Minnesota-Duluth; Gary W. Marek, Postdoctoral Research Associate, Texas A&M AgriLife Research; Kevin Heflin, Extension Associate, Texas A&M AgriLife Research; K. Jack Bush, Research Associate, Texas A&M AgriLife Research.

Additional Information

Please contact Brent W. Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research, 6500 Amarillo Boulevard West, Amarillo TX, 79106, Phone: 806-677-5600, Email: b-auvermann@tamu.edu.

Acknowledgements

This research was underwritten by grants from the USDA National Institute on Food and Agriculture (contract nos. 2010-34466-20739 and 2009-55112-05235).

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2013. Title of presentation. Waste to Worth: Spreading Science and Solutions. Denver, CO. April 1-5, 2013. URL of this page. Accessed on: today’s date.

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Developing a Modeling Framework to Characterize Manure Flows in Texas

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Abstract

In recent years, sharply rising costs of inorganic fertilizers have contributed to an increased demand for manure and compost in crop production acreage, transforming cattle manure from a valueless waste to a viable alternative to commercial fertilizer. If additional demand for manure as a bio-fuel were to arise manure could take on two distinct values, a fertilizer value and a fuel value. This potential “dual” value of manure begs several questions. What would the fertilizer and fuel markets of manure look like? Is there enough manure supply for the markets to operate independently? If not, which market would prevail? In essence, how, if at all, would manure’s potential value as a bio-fuel distort the traditional Panhandle manure market? A modeling framework was developed to assess the potential impacts of a manure-fired ethanol plant on the existing Texas Panhandle manure fertilizer market.  Two manure-allocation runs were performed using a spreadsheet model. Run #1 allocated all available manure from dairies and feedlots to cropland as manure fertilizer; run #2 first allocated fuel manure to the ethanol plant and then allocated the remaining manure to cropland. Both model runs assumed a time horizon of one year and no antecedent nutrients in cropland soils. Other constraints included only irrigated acreages received manure and no supplemental fertilizer was used. The model revealed a 6.4% increase in cost per acre of fertilizing with manure for fields whose nutrient requirements were fully satisfied in both runs. The increase in cost per acre was likely due to an increase in hauling distances attributed to fewer CAFOs available for fertilizer manure. The model is not presented as a dynamic, systems model, but rather a static model with the potential to be incorporated into a more dynamic systems-based modeling environment. Suggestions for further model development and expansion including GAMS integration are presented.

Why Model Manure Transport and Use?

To demonstrate the potential for systems modeling to characterize manure flows in response to fertilizer prices,  biofuel demand, and other externalities in the Texas Panhandle

Conceptual model diagram.

What Did We Do?

We develeloped a spreadsheet based modeling framework to evaluate how both manure use and transport might be affected by regional changes in fertilizer prices, crop composition, and biofuel demand.  Specifically, we evaluated how traditional fertilizer valued manure flows might be affected by potential biofuel based flows stemming from a proposed manure-fired ethanol plant.  Two model simulations representing manure flows with and without biofuel manure demand from the proposed plant were performed.

Explicit model boundary shown with TNRIS satellite imagery used to locate and identify center pivot irrigated fields.

What Have We Learned?

Although the cattle industry in Texas Panhandle generates a substantial volume of manure, almost all of it is land applied as fertilizer.  However, the introduction of manure-fired facilities such as the proposed ethanol plant would undoubtedly change the dynamics of the existing manure market by introducing at least additional demand, if not a second value-based market.  Assuming only transportation costs of acquiring manure for biofuel, our model simulations suggested a 6.4% increase in cost per acre for lands whose manure requirements were fully satisfied in both simulations.  Assuming that manure for biofuel received an allocation preference for proximity to the plant, we propose that costs associated with having to transport manure over longer distances significantly contributes the the increased cost per acre for fertilized lands.

In terms of what we learned about systems modeling, we have experienced (although anticipated) that translating broad, systems based conceptual modeling ideas into an explicit, user friendly, and robust modeling interface can be extremely challenging. Although systems-based modeling efforts occur largely at a macro level, they often require extensive supplemental datasets.  We have experienced difficulty in identifying software packages that are equipped to adequately handle both aspects of systems modeling.

Future Plans

We plan to continue to develop and expand the current modeling framework by incorporating  a GIS-based water availability aquifer component, expanding the current crop-composition database, and providing logic algorithms for producer-based management decisions using GAMS (General Algebraic Modeling System) optimization modeling.

Manure allocation map for model run #1 (232 LMU cells allocated).

Authors

Brent Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research, b-auvermann@tamu.edu

Gary Marek, Postdoctoral Research Associate, Texas A&M AgriLife Research; Brent W. Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research; Kevin Heflin, Extension Associate, Texas A&M AgriLife Extension

Additional Information

Please contact Gary Marek, Postdoctoral Research Associate, Texas A&M AgriLife Research, 6500 Amarillo Boulevard West, Amarillo TX, 79106, Phone: 806-677-5600, Email: gwmarek@ag.tamu.edu or  Brent W. Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research, 6500 Amarillo Boulevard West, Amarillo TX, 79106, Phone: 806-677-5600, Email: b-auvermann@tamu.edu.

Acknowledgements

Special thanks to Dr. Raghavan Srinivasan and David Shoemate of the Texas A&M University Department of Ecosystem Science and Management Spacial Sciences Laboratory for their help in GIS processing scripts.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2013. Title of presentation. Waste to Worth: Spreading Science and Solutions. Denver, CO. April 1-5, 2013. URL of this page. Accessed on: today’s date.

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Greenhouse Gas Emissions from Livestock & Poultry

Agriculture is both a source and sink for greenhouse gases (GHG). A source is a net contribution to the atmosphere, while a sink is a net withdrawal of greenhouse gases.  In the United States, agriculture is a relatively small contributor, with approximately 8% of the total greenhouse gas emissions, as seen below.  Most agricultural emissions originate from soil management, enteric fermentation (the ruminant digestion process that produces methane), energy use, and manure management.  The primary greenhouse gases related to agriculture are carbon dioxide, methane, and nitrous oxide. Within animal production, the largest emissions are from beef followed by dairy, and largely dominated by the methane produced in during cattle digestion.

U.S. GHG Inventory

U.S. greenhouse gas inventory with electricity distributed to economic sectors (EPA, 2013) 

Ag Sources of GHGs

U.S. agricultural greenhouse gas sources (Adapted from Archibeque, S. et al., 2012)

Greenhouse gas emissions from livestock in 2008 (USDA, 2011)

Soil Management

Excess nitrogen in agriculture systems can be converted to nitrous oxide through the nitrification-denitrification process. Nitrous oxide is a very potent greenhouse gas, with 310 times greater global warming potential than carbon dioxide.  Nitrous oxide can be produced in soils following fertilizer application (both synthetic and organic).

As crops grow, photosynthesis removes carbon dioxide from the atmosphere and stores it in the plants and soil life. Soil and plant respiration adds carbon dioxide back to the atmosphere when microbes or plants breakdown molecules to produce energy.  Respiration is an essential part of growth and maintenance for most life on earth. This repeats with each growth, harvest, and decay cycle, therefore, feedstuffs and foods are generally considered to be carbon “neutral.”

Some carbon dioxide is stored in soils for long periods of time.  The processes that result in carbon accumulation are called carbon sinks or carbon sequestration.  Crop production and grazing management practices influence the soil’s ability to be a net source or sink for greenhouse gases.  Managing soils in ways that increase organic matter levels can increase the accumulation (sink) of soil carbon for many years.

Animals

The next largest portion of livestock greenhouse gas emissions is from methane produced during enteric fermentation in ruminants – a natural part of ruminant digestion where microbes in the first of four stomachs, the rumen, break down feed and produce methane as a by-product. The methane is released  primarily through belching.

As with plants, animals respire carbon dioxide, but also store some in their bodies, so they too are considered a neutral source of atmospheric carbon dioxide.

Manure Management

A similar microbial process to enteric fermentation leads to methane production from stored manure.  Anytime the manure sits for more than a couple days in an anaerobic (without oxygen) environment, methane will likely be produced.  Methane can be generated in the animal housing, manure storage, and during manure application. Additionally, small amounts of methane is produced from manure deposited on grazing lands.

Nitrous oxide is also produced from manure storage surfaces, during land application, and from manure in bedded packs & lots.

Other sources

There are many smaller sources of greenhouse gases on farms. Combustion engines exaust carbon dioxide from fossil fuel (previously stored carbon) powered vehicles and equipment.  Manufacturing of farm inputs, including fuel, electricity, machinery, fertilizer, pesticides, seeds, plastics, and building materials, also results in emissions.

To learn more about how farm emissions are determined and see species specific examples, see the Carbon Footprint resources.

To learn about how to reduce on-farm emissions through mitigation technology and management options, see the Reducing Emissions resources.

 Additional Resources

Additional Animal Agriculture and Climate Change Resources

Author: Crystal A. Powers, UNL
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