Dairy Operations: An Evaluation and Comparison of 

Baseline and Potential Mitigation Practices 

for Emissions Reductions In the San Joaquin Valley 

FINAL REPORT 

Principal Investigator: 

Dr. Charles Krauter 

California State University - Fresno 

Co-Principal Investigator: 

Dr. Donald Blake 

University of California - Irvine 

California Air Resources Board Contract No. 04-343 

Project administered as CSU Fresno Foundation Project #37411 

Submitted May 1, 2009 

Prepared for the California Air Resources Board 

and the California Environmental Protection Agency 
Disclaimer 

 The statements and conclusions in this report are those of the Contractor and not 

necessarily those of the California Air Resources Board. The mention of commercial 

products, their source, or their use in connection with material herein is not to be 

construed as actual or implied endorsement of such products. 

NOTE: This project was proposed in response to a request by the California Air 

Resources Board for a monitoring study to determine the sources and species of ROG 

emissions from dairy operations. A data set was to be collected that would serve to 

validate processes that might reduce emissions and provide a broader base of data for 

facility and regional modeling. After the study was approved and began the initial 

stages of selecting sites and sampling methods; there were requests from other 

agencies and researchers to cooperate and add support to make the project larger in 

scope and extend the time to increase the amount and value of the data collected. One 

of the secondary objectives of the CARB proposal was to solicit just such augmentation 

to the original work. The net result of these additions to the project was positive in all 

respects but one. The additional, related projects are not scheduled to be completed 

until 2009 or 2010. The terms of the CARB research contract require a draft final report 

for review by January, 2009 and a final version of the report by May, 2009. A 

considerable amount of field work remains to be completed and much more data has 

yet to be analyzed from these related projects. Consequently, only data and results 

from the original CARB contract work will be reported here. That data comes from the 

analysis done by Dr. Blake at UC Irvine. The related projects have added air samples 

analyzed at CSU Fresno, analysis of alcohols, N compounds and greenhouse gasses, 

sampling and analysis of feed, silage, manure, soils and other materials to correlate 

with flux rates monitored at the dairy sites. This additional data is not yet complete and 

cannot be reported here. In several instances, UC Irvine data cannot be completely 

evaluated until those related projects are complete. A comprehensive report will be 

prepared by the end of 2009 to include all the data reported here along with the 

additional results from the related projects. 

ii
Acknowledgements: 

The field work portion of this project was conducted by students and staff in the Plant Science 

Department and the Center for Irrigation Technology at CSU Fresno. The following CIT staff 

supervised the sampling and other data collection activities at the dairy locations: 

Shawn Ashkan – Research Scientist and Agricultural Engineer 

Matt Beene – former Research Scientist, now R&D director for Helena Chemical Co. 

Barry Goodrich – former Research Scientist, now a doctoral student at Texas A&M. 

Plant Science Department students: Jon Thornton, Martin Brito, Robbie Massera 

Analytical work for the project was conducted in the Chemistry Department at UC Irvine under 

the direction of Dr. Donald Blake. A doctoral student, Melissa Yang, supervised the sample 

custody, analysis and reporting of data back to CSU Fresno. 

The Principle Investigators gratefully acknowledge the unknown member of the CARB RSC who 

suggested the collaboration with UC Irvine upon review of the original proposal submitted by 

CSU Fresno. 

The Dairy Sub-committee, formed by CARB and CDFA in 2002 and reconstituted by the 

SJVAPCD in 2005 became the advisory group for this project. The original proposal and all 

subsequent revisions described below were suggested and approved by this advisory group. 

The Dairy Sub-committee members directly and actively involved in this project were: 

Public Agency members: 

California Air Resources Board: Patrick Gaffney, Michael FitzGibbon and Dale Shimp 

California Department of Food and Agriculture: Matt Summers and Rolf Frankenbach 

San Joaquin Valley Air Pollution Control District: Dave Mitchell, James Sweet and Sheraz Gill 

USDA-NRCS: John Beyer and Johnnie Siliznoff 

Dairy and Agricultural Industry members: 

Dairy CARES: J. P. Cativiela 

Western United Dairymen: Paul Martin 

California Dairy Campaign: Kevin Abernathy 

Hilmar Cheese Co: Denise Mullinax 

Nisei Farmers League: Manual Cunha 

Dairy Operators: George Longfellow and Simon Vander Woude 

Research members 

UC Davis: Dr. Frank Mitloehner and Dr. Deanne Meyer 

U New Hampshire: Dr. Bill Salas and Dr. Changshen Li 

Texas A&M: Dr. Calvin Parnel, Dr. Bryan Shaw and Barry Goodrich 

The investigators would most like to acknowledge the cooperation of six anonymous dairy 

operators who allowed us frequent access to their dairies, often with little notice, and never 

failed to help us when we needed it. 

This Report was submitted in fulfillment of California Air Resources Board Contract No. 

04-343 for the project titled “Dairy Operations: An Evaluation and Comparison of 

Baseline and Potential Mitigation Practices for Emissions Reductions In the San 

Joaquin Valley” administered as CSU Fresno Foundation Project #37411 under the 

partial sponsorship of the California Air Resources Board. Work on the portion of the 

project reported here was completed as of January, 2009 

iii
Table of Contents Page

Disclaimer ................................................................................................. ii 

Acknowledgements ................................................................................... iii 

List of Tables .............................................................................................. v 

List of Figures ............................................................................................. v 

Glossary of terms, abbreviations and symbols and units .......................... vi 

Abstract .................................................................................................... viii 

Executive Summary .................................................................................. ix 

Introduction ................................................................................................ 1 

Materials and Methods ............................................................................... 2 

 Objectives ............................................................................................ 2 

 Field Sampling Overview ...................................................................... 5 

 Quality Assurance Objectives .............................................................. 5 

 Sample Coordination and Recording .................................................... 6 

 Calibration Procedures ......................................................................... 6 

 Data Reduction, Validation and Reporting ........................................... 6 

 Sampling Sites .................................................................................... 7 

 Dairy Descriptions ................................................................................ 8 

 Regular Sampling Program, Year-2 ..................................................... 9 

Results ..................................................................................................... 18 

 Silage Flux Rates ............................................................................... 19 

 Feed Flux Rates ................................................................................. 21 

 Flush Lane Flux Rates ....................................................................... 24 

 Open Lot Flux Rates .......................................................................... 26 

 Correlations With Ambient Conditions ............................................... 27 

Discussion ................................................................................................ 28 

Summary and Conclusions ...................................................................... 33 

Recommendations ................................................................................... 36 

References ............................................................................................... 37 

Inventions and Publications ...................................................................... 37 

Appendix A. Individual Samples From Dairy Operations ......................... 38 

Appendix B. Year-1 Progress Report ....................................................... 45 

Appendix C. Organics Analysis Description ............................................ 61 

Appendix D. Flux Chamber Methodology and Sample Log Sheets........66 

iv
List of Figures Page 

Figure 1. Flux chamber sampling of an open lot area at Dairy B. 13 

Figure 2. Flux chambers on a flush lane at Dairy B. 14 

Figure 3. Flux chambers sampling Total Mixed Ration at Dairy A. 15 

Figure 4. Flux chamber sampling of silage at Dairy D. 16 

Figure 5. Flux chamber field blank at Dairy F. 17 

Figure 6. Total ROG fluxes related to time after feed placement. 23 

Figure 7. Total Alcohol fluxes related to time after feed placement. 24 

Figure 8. ROG fluxes averaged from each dairy and sampling date. 30 

Figure 9. Fluxes of 6 prominent ROG components in feed and silage. 31 

Figure 10. An example of ROG source magnitudes at a fictitious dairy. 35 

List of Tables Page 

Table 1. Modified Year-2 monitoring program adopted for Fall-07. 11 

Table 2. Special Sampling program proposed for Year-2. 12 

Table 3. Average flux rates for “disturbed silage” material. 20 

Table 4. Average flux rates for “undisturbed silage” material. 21 

Table 5. Average TMR flux rates for all daires. 22 

Table 6. Average TMR flux rates for each dairy sampled. 23 

Table 7. Average flush lane flux rates. 25 

Table 8. Average flush lane flux rates with questionable data deleted. 26 

Table 9. Open lot, exercise pen and corral flux averages. 27 

Table 10. Average flux rates for all dairies, dates and operations. 29 

Table A1. Silage samples from material dislodged from the pile. 39 

Table A2. Silage samples from undisturbed material. 40 

Table A3. Individual samples of feed (TMR) fluxes. 41 

Table A4. Individual flush lane fluxes. 42 

Table A5. Open lot, exercise pen and corral fluxes. 43 

Table A6. Ambient samples taken prior to July, 2007. 44 

 

v
Glossary of terms, abbreviations, symbols and units 

General terms 

CARB – California Air Resources Board 

CDFA – California Department of Food and Agriculture 

CSU Fresno – California State University at Fresno 

Dairy sub-committee – A group formed jointly by CARB and CDFA in 2002 that 

subsequently became the advisory group for this project. 

DPAG – Dairy Permitting Advisory Group formed by the SJVAPCD in 2004. Members 

of the Dairy Sub-committee also participated in this activity. 

SJVAPCD – San Joaquin Valley Air Pollution Control District 

UC Davis – University of California at Davis 

UC Irvine – University of California at Irvine 

UNH – University of New Hampshire 

Dairy terms 

Commodities - Purchased components of the TMR such as cottonseed meal, rolled 

corn, almond hulls, distillers grain, citrus pulp and other materials to add energy 

and nutrition to the feed. 

Flush lanes – long sloping, hard-surfaced lanes upon which the cows stand when 

feeding. The lanes are washed with a large volume of water or scraped several 

times each day to flush manure into various collection and storage areas. 

Lagoons – Ponds containing the water from the flush lanes, generally after separation 

of coarse manure material. Flush water is recycled from the lagoon. 

Manure - The combination of urine and feces eliminated by the dairy cows. 

Open lots – Corrals, exercise pens and other fenced areas available for the cows 

adjacent to the barns. Most dairies restrict access to open lots in wet weather. 

Silage – Chopped and compressed plant material harvested and stored for use in 

making the TMR. Silage is usually the largest component of the TMR. Typically 

made from field corn, it is also made from alfalfa and various small grains and 

referred to as “grass” or “winter” silage. 

TMR - Total mixed ration is the term for the feed mixture made from silage, alfalfa hay 

and various commodities. TMR is usually mixed at the dairy and delivered from a 

truck or wagon into a feed bunker. TMR is fed 2-4 times each day. Most dairies 

employ a nutrition consultant to recommend the specific components of TMR to 

achieve the desired level of energy and nutrition for the cows as it relates to their 

condition, the season and the various commodity prices. 

Research terms and units 

Alcohols – Ethanol, Methanol and Propanol analyzed by UC Irvine and reported as 

components of ROG in this report 

DMS – Di-Methyl Sulfide, a significant component of ROG from some dairy sources. 

DMDS – Di-Methyl Di-Sulfide, a significant component of ROG from some dairy 

sources. 

vi
Emissions – In this report, “emissions” is a term used in a general sense to describe 

the volatile flux of a gas or combination of gasses such as ROG from a surface. 

The term is not intended to imply an emission rate or emission factor when used in 

this report. 

Flux – In this report, “flux” is the term used to describe volatile transfer across the 

interface between a surface and an atmosphere. This interface can be either 

surface to ambient atmosphere or surface to flux chamber atmosphere. 

Flux rate – In this report, “flux rate” refers to the quantitative volume of a flux in units of 

mass per unit area per unit time. 

Flux chamber – In this report, “flux chamber” is the field sampling device described in 

the US-EPA Isolation Flux Chamber Methodology (Appendix D). Flux Chambers 

used in this study covered an area of 0.1924 m2

 and were flushed with zero air at a 

rate of 10 liters/minute. Flux chambers used in this project were manufactured by 

Odotech of Toronto, Canada. 

GC-MS – Gas Chromatography with Mass Spectrometry detection. This is the 

general term for the method of analysis used by UC Irvine to speciate and quantify 

the components of the air samples collected at the dairy sites. 

μg/m2

/minute – The unit of flux rate used in this study. Micro-grams per square meter 

per minute. 

μg/m3 - The unit of mass per unit volume of air. Micro-grams per cubic meter. This is 

the intermediate step in the conversion of proportional volume such as pptV 

reported in the UC Irvine analysis to mass per unit of air before the calculation of 

flux rate. 

ROG – In this report, “Reactive Organic Gas” is the sum of volatile organic 

compounds reported from the UC Irvine analysis that are sufficiently reactive to be 

considered ozone precursors. In this study, 60 of the 64 gasses in the UC Irvine 

analyses were summed and reported as ROG. Methane, CO, CO2 and acetone 

were excluded from the ROG total though they were reported by UC Irvine. The 

gasses included in the total of ROG are not equally reactive. Some may result in 

much more ozone than others. No distinction was made in this study with respect 

to relative reactivity among the ROG gasses but other contemporary studies are 

evaluating reactivity with respect to dairy ROG emissions. A complete evaluation 

of dairy ROG emissions will require the application of the relative reactivity of these 

components of ROG once it has been determined in future research. 

VOC – Volatile Organic Compounds. In this report, “VOC” is used to indicate the total 

of all volatile organic gas from which ROG is the sub-set of gasses that are 

considered precursors of ozone. 

Zero air – Bottled, compressed gas made up of 80% N2 and 20% O2. It is the flush 

gas for the flux chamber method that eliminates contamination of an air sample by 

ambient air above the surface being sampled. 

vii
Abstract 

Dairy operations in California were assumed in 2004 to be major sources of Reactive 

Organic Gas (ROG) and therefore, ozone formation in the Central Valley. In 2005 this 

project was proposed to determine the specific sources and components of ROG in 

emissions from dairies. An advisory group of public agency, industry and academic 

members was formed to develop the initial plan and supervise revisions in accordance 

with initial results. Six dairies were selected to be sampled three times each year to 

evaluate facility and seasonal differences. Ambient air samples were collected initially 

to identify specific ROG components and develop analytical methods for dairy air 

samples. The initial data indicated the predominance of alcohols in feed components 

of dairy ROG emissions and a sampling program was designed to focus on those 

while also monitoring other dairy ROG sources. The sampling program was 

conducted by Dr. Charles Krauter at CSU Fresno. The corresponding analytical 

program was administered by Dr. Donald Blake at UC Irvine. After review of the initial 

data, in 2006, the advisory group revised the sampling program to reflect the 

discovery that alcohols from the feeding operations, rather than manure management 

appeared to be the most significant ROG source. The six dairies were sampled three 

times from June, 2007 through July, 2008. The highest flux rates were for silage and 

feed with an average flux rate of 4,229 μg/m2

/minute from the vertical silage pile face 

and 19,170 μg/m2

/minute for loose, disturbed silage used for mixing feed. Fluxes from 

feed were 15,022 μg/m2/min when first placed in the feed bunker, though the rate 

decreased to 2,929 μg/m2/min as it was consumed. Flux rates for the flush lanes 

were considerably lower with a rate of 353 μg/m2

/min prior to the flushing operation 

that decreased further to 21 μg/m2/min after the flush. Open lots and exercise corrals 

were similar to the flush lanes. Areas of the corrals where the manure pack was 

relatively deep had flux rates of 243 μg/m2/min. while the shallow manure pack in the 

open lots averaged 102 μg/m2

/min. The anticipated seasonal effects appear to be 

less significant than expected. Only emissions from the open lots correlate with 

surface temperatures, increasing in the summer and declining in winter. When the 

areas represented by each of these operations were applied to the flux values, it 

became apparent that feed was the dominant (60%) ROG source, followed by the 

open lots (25%), flush lanes (8%) and silage piles (7%). These proportions were 

calculated as an example of a fictitious dairy that was a composite of the six sampled 

facilities. These percentages would vary when calculated from actual fluxes and 

facility dimensions but feed would probably remain the dominant source of ROG. 

After this California Air Resources Board (CARB) supported project began, several 

related projects were added to the sampling program at the six dairies. Additional 

sampling and analytical systems were added as well as the collection of data related 

to nitrogen compounds, lagoon emissions, land application emissions, silage, feed, 

manure, soil and compost materials. These related projects are still in progress. Only 

data related to the CARB contract is complete and reported here. A comprehensive 

report of all projects related to sampling at these six dairies and other sites will be 

prepared at the end of 2009. 

viii
Executive Summary 

Background 

In 2002, a study group made up of members from state agencies, academic institutions 

and the diary industry was formed by the California Air Resources Board (CARB) and 

the California Department of Food and Agriculture (CDFA). This group was known as 

the Dairy Sub-Committee. Their primary goal was to evaluate existing research to 

estimate the impact of dairy operations on air quality in California. In 2004, the San 

Joaquin Valley Air Pollution Control District (SJVAPCD) began the process of permitting 

dairies in their jurisdiction. Many of the Dairy Sub-Committee members became part of 

the Dairy Permitting Advisory Group (DPAG) of the SJVAPCD. The primary issue 

addressed by the DPAG process was the uncertainty regarding dairy emissions of the 

ozone precursors known as Reactive Organic Gas (ROG). ROG was defined as those 

Volatile Organic Compounds (VOC) that are active in the atmospheric reaction that 

forms ozone. The Dairy Sub-Committee, noting the lack of current research in 

California related to this issue, advocated funding and solicitation of proposals to 

address the problem. This project is one of the responses to that advocacy. The 

project proposal mandated an advisory group of industry, public agency and research 

representatives to oversee the study and suggest changes to increase the relevance of 

the project. The Dairy Sub-committee remained in that role throughout the project. 

Methods 

The original, primary objective of this study was to evaluate the potential emission 

reductions from various methods for handling and managing dairy manure. During the 

initial year, however, research by Dr. Frank Mitloehner at UC Davis suggested ROG 

emissions from feeding operations were more significant than those from the manure 

management processes. This was confirmed by the first flux chamber sampling by 

CSU Fresno and subsequent analysis by Dr. Blake at UC Irvine. The advisory group 

reviewed the initial data and recommended revisions to the sampling program. The 

focus was shifted from ambient samples and dispersion modeling of the whole dairy to 

more site-specific, flux chamber sampling methods that concentrated on feed and the 

feeding operations. Flush-lanes, corrals, lagoons and alternative manure management 

operations continued to be monitored and proved, as suggested by the UCD research, 

to have significantly lower ROG flux rates compared to the feed and feeding operations. 

This CARB funded project was the initial support for what became a much larger study 

with additional objectives beyond the monitoring of ROG emissions from dairy 

operations. The additional funding allowed expansion of the regular sampling program 

from five to six dairies. The focus on ROG by the project advisory group was at the 

expense of the ammonia, methane and other air quality issues that were included as 

possible constituents to be sampled in the original proposal. These added, related 

projects include these other constituents along with more ROG monitoring of additional 

sources. The initial CARB funding is the only part of the study that has reached the end 

of its term. Most of the additional projects will be completed in 2009. Consequently, 

only the data and conclusions from this first ROG study can be reported here. Some 

supporting data from the other projects will be included as it applies to the CARB 

ix
x

project. A comprehensive report will be prepared upon the completion of the related 

projects that will include the data and results from this project compiled with the 

additional data from the other studies. That final report will be completed in 2009. 

Results 

Results from this CARB funded project are primarily from the flux chamber monitoring 

program developed and conducted by CSU Fresno to provide the analytical program 

at UC Irvine with air samples. The results of the UCI analysis were correlated with 

site data to meet the primary objective of characterizing the ROG flux rates from dairy 

operations and evaluating the variability of those fluxes. Total ROG flux rates were 

highest for silage. Undisturbed silage had a flux rate average of 4,229 μg/m2/minute. 

The disturbed silage pulled from the pile had an even higher rate, averaging 

19,170 μg/m2

/min. The composition of these ROG fluxes was about 85% alcohols, 

predominantly ethanol. Feed mixed and delivered to the animals produced similar 

results. Immediately after placement in the feed bunkers, the flux rate averaged 

15,022 μg/m2

/min but decreased to 2,929 μg/m2/min over a period of 6 – 8 hours as it 

was consumed. Disturbing the feed by sweeping partially consumed material closer 

to the animal’s reach appeared to cause a spike in flux rate. ROG flux rates for 

manure management procedures were much lower than for feed. The flush-lane 

rates averaged 353 μg/m2/min, prior to the flushing operation, and 21 μg/m2/min after 

the flush. Open lot areas where manure not left in the flush lanes is deposited had 

flux rates that averaged 102 μg/m2/min where the layer of manure was shallow and 

243 μg/m2/min for the deeper manure pack areas. Variability with respect to season 

was not apparent except for ROG fluxes from the open lots where there appears to be 

some correlation with surface temperature. No seasonal differences in the emissions 

from feed or flush lane operations can be shown with the data from this study. 

Conclusions 

The monitoring procedures used in this project produced calculated flux rates for a 

unit area of the process being sampled. While those values can show the ranking of 

the flux rates for the ROG sources, the calculated flux rate must be multiplied by the 

area at the dairy represented by the particular operation to determine its actual 

proportion of the facility’s ROG emissions. The areas of each source vary among the 

facilities as do the flux rates for each, as measured by this study. However, an 

estimate of the percentages that each of these four sources contributes to the total 

ROG emissions can be calculated from a composite of the six diaries sampled and 

the average flux rates from the study. When these flux rates are applied to the 

dimensions of the composite dairy, the highest flux rate for silage produces the lowest 

proportion (7%) of the dairy’s emissions. Flush lanes are 8%, open lots are 25% and 

feed is the major source at 60% of emissions. Differences in dairies and the variation 

in flux rates monitored in this study will produce different percentages for specific 

facilities but it is likely that the feed material will always be the major component of 

ROG emissions. Additional data from related projects will be evaluated to include 

smaller emission sources such as lagoons and solids separation processes as well as 

better characterization of the variability among different dairies. 
INTRODUCTION 

This project was conceived from the findings of two different study groups formed to 

evaluate air quality problems associated with dairy operations in California. The first of 

these groups was the Dairy Sub-committee organized in 2002 by the California Air 

Resources Board (CARB) and the California Department of Food and Agriculture 

(CDFA) and chaired by Dr. Matt Summers of CDFA. The sub-committee was made up 

of representatives from public agencies (CDFA, CARB, USDA, EPA and SJVAPCD) 

academic researchers from UC Davis and CSU Fresno, and dairy industry 

organizations (Western United Dairymen, Dairy CARES, Hilmar Cheese and California 

Dairy Campaign). The primary goal of the Dairy Sub-committee was to evaluate 

existing air quality research related to diary operations and recommend new projects 

needed by the agencies to develop science based regulations. At the same time the 

Dairy Sub-committee was developing its recommendations, the San Joaquin Valley Air 

Pollution Control District was beginning to develop a permitting process for dairies in 

their jurisdiction. A Dairy Permitting Advisory Group (DPAG) was formed and included 

most of the agency and industry members of the Dairy Sub-committee. The primary 

issue addressed by DPAG was ozone formation and the role of dairy emissions in the 

level of ozone precursors known as Reactive Organic Gas (ROG). ROG was defined 

as volatile organic compounds (VOC) that were reactive in the atmospheric production 

of ozone. In practice, ROG was all measured VOC with the exclusion of methane, 

carbon monoxide, carbon dioxide and acetone. This project proposal was initially 

developed from the findings of the Dairy Sub-committee. As the DPAG process 

indicated the priority of ROG emissions, the original, blanket proposal that also included 

ammonia, hydrogen sulfide and other air quality issues was revised by the Dairy Subcommittee to focus on ROG. The original proposal to CARB for this project mentioned 

those other constituents but the project advisory group mandated the emphasis on ROG 

sampling/analysis with the others relegated to monitoring that could be done without 

interference with the ROG work. Additional funding from other sources became 

available over the course of the project to monitor these other constituents. That data 

will be reported in a later, more comprehensive report. 

This CARB funded project was conducted over the past 36 months though the 

execution of six specific tasks, described below. Six dairies with different manure 

management practices and feeding procedures were evaluated over the course of the 

project. Nearly 600 ROG samples were collected and analyzed at UC Irvine for VOC 

species over the course of the project. CSU Fresno researchers, under the direction of 

Dr. Krauter, were responsible for the field work portion of the project including collecting 

all samples, delivering samples to the IC Irvine laboratory, collecting relevant field data, 

and conducting additional field work to support the related projects. UC Irvine research 

group, under the direction of Dr. Blake, analyzed the samples for organic gases and 

assisted in the analysis and speciation of the collected emissions data. 

The related projects, from the additional funding, will continue through 2009 and, in 

some cases, beyond to collect and analyze additional samples for alcohols, N 

compounds, silage and feed emissions, alternative lagoon emissions, compost 

emissions, and land application emissions. Data related to these additional projects 

1
from UCI analysis as well as interpretation, correlation and conclusions related to those 

issues cannot occur until those projects are completed. 

MATERIALS and METHODS 

Objectives 

There was a primary and three secondary objectives in the original proposal, adopted 

by the Dairy sub-committee. These objectives and their subsequent revisions by the 

sub-committee in their role as the project advisory group are described below. 

Primary Objective: 

The primary objective as stated in the project proposal was to monitor and model 

ROG flux rates at baseline dairies and dairies with alternative manure handling 

systems to evaluate the potential for emissions reduction. While that objective 

remained significant, contemporary research at UC Davis by Dr. Frank 

Mitloehner found higher flux rates from feeding operations than the manure 

handling processes that were to be studied in this project. Dr. Mitloehner and 

other members of the advisory group suggested at the end of the initial year that 

the focus be shifted to feed and feeding operations while continuing to monitor 

manure management practices. The air samples collected by CSU Fresno and 

analyzed by UC Irvine were used to calculate flux rates from sources associated 

with both feeding and manure handling operations. These flux rates are 

summarized in the results section and the individual samples are listed in 

Appendix A. 

Secondary Objectives: 

1. A secondary objective, as stated in the project proposal was to monitor and 

model ammonia emissions from the tested dairies to evaluate the effect of the 

alternative practices on ammonia emissions and to improve baseline 

emission estimates. The GC-MS analytical program at UC Irvine, funded by 

this CARB project, was not the most efficient or cost effective method for 

ammonia monitoring, particularly with the emphasis on the feed sources. The 

advisory group recommended the ammonia sampling and analysis be 

assigned to a related project with the University of New Hampshire (UNH) to 

preserve CARB budget resources for the ROG analysis at UCI. A photoacoustic gas analyzer was suggested by an advisory group member and was 

evaluated against the ammonia denuder method used by the CSU Fresno 

research group in a previous fertilizer emissions study. The INNOVA 

analyzer proved to be equivalent in accuracy to the denuder method for 

ammonia and had the additional advantage of providing real-time results. 

The INNOVA subsequently proved to be a useful secondary method of 

analysis for alcohols and other gases in the related projects. This first 

related study, funded by Dr. William Salas of UNH from his USDA CSREES 

grant, enabled INNOVA monitoring of ammonia and several other N 

compounds from additional sampling at the six regular dairy sites. Results 

2
from that study will be included in the comprehensive report to be completed 

in 2009. 

2. Another secondary objective, as stated in the project proposal was to use the 

CARB project award to obtain matching funding from the California State 

University Agricultural Research Initiative (CSU/ARI). The CSU-ARI funding 

is from a program that requires initial support from an external source which 

can then be matched. No CSU-ARI support would have been available 

without this CARB funding. A CSU/ARI project was proposed in 2006 to 

expand the regular sampling sites from five in the original proposal to six and 

add other sites to be monitored periodically. The addition of the feed sources 

was included in this and a subsequent CSU/ARI proposal that funded most of 

the additional equipment and staff required for those sources. These 

CSU/ARI projects are scheduled to be completed in 2009 and 2010. 

3. The final, secondary objective, as stated in the project proposal was to 

provide additional data from these dairies to cooperating researchers 

conducting projects related to ammonia, methane, N2O, PM, and other factors 

related to dairy operations. The relevant portions of the budgets for these 

cooperating projects shared the common field sampling and other costs with 

the CARB project. In addition to Dr. Salas at UNH, related monitoring 

projects at these dairy sites were funded by UC Riverside, Dr. Mitloehner at 

UC Davis, Sustainable Conservation, Engineered Composting Services, and 

the California Dairy Campaign. This additional funding was also used as 

match for the CSU/ARI projects described in objective 2. A considerable 

body of data is being developed by these related studies and part of each 

agreement is a commitment to share all information from all projects with all 

cooperating agencies. The complete data set will be made available on a 

website and the results included in the comprehensive report at the end of 

2009. 

The objectives of the project were to be met through the specific tasks, listed in the 

proposal and outlined below in their original form. 

Modifications and additions to each of the original tasks, as revised by the project 

advisory group, are shown in italics below each task.

Task 1. Select at least five dairies to monitor in cooperation with ARB and district staff. 

Ensure selected dairies are representative of typical conditions and operations. 

The additional projects and funding enabled a sixth dairy to be added to those to be 

sampled on a regular basis for comparison of their different methods of feeding and 

manure management. The six dairies were chosen with the assistance of several 

members of the advisory group and the approval of the entire group prior to the 

beginning of the sampling program. A list and description of each dairy can be found 

below. 

3
Task 2. Determine and evaluate specific field sampling procedures to accommodate 

the unique features at each dairy. Prepare field test plan including quality 

assurance objectives and data handling protocols and sample custody. 

The initial year of field work was designed to evaluate alternative sampling methods as 

well as determine the initial speciation of the dairy ROG emissions. The discovery of 

the significant alcohol emissions from feeding operations showed the value of this 

strategy. The downwind-upwind ambient samples proved to be unsuitable for 

separating emissions from discrete operations. The substitution of flux chamber 

sampling proved to be a much more viable method. 

Task 3. Conduct initial field sampling at each dairy, analyze collected samples and 

model emissions. Provide summary of results for review by the advisory 

group. 

The regular sampling of six dairies began in early 2006 and continued through summer 

of 2007. Various sampling methods were tested and refined. In the spring of 2007, a 

summary of the Year-1 results was prepared and discussed at a series of advisory 

group meeting. That Year-1 report is attached as Appendix B. 

Task 4. Adjust sampling and analytical procedures based on results from the initial 

sampling periods at each dairy. Revise field test plan. 

After discussion of the Year-1 results, a revised sampling plan was submitted to the 

advisory group. That Year-2 program included not only the CARB sampling but also the 

complete field program for all the related projects that involved monitoring at the six 

regular sites. That field plan is described in the following section and in Appendix B. 

Task 5. Continue sampling and modeling at each dairy in the second year using 

consistent procedures on a regular basis to determine the effect of climate, 

crop season and seasonal dairy practices on emissions. 

The Year-2 program was approved by the advisory group in September, 2007 and was 

implemented in October, 2007. Most of the procedures were included in the spring and 

summer sampling in 2007 as well and are included in the data where appropriate. The 

final sampling period for the six regular dairies was completed in July, 2008. Analysis of 

UC Irvine samples was completed and reported to CSU Fresno in November, 2008. 

Task 6. Compare emissions from each dairy operation in the second year of the project 

to begin to determine differences between potential mitigation practices related 

to dairy operations. Prepare report on results. 

The analysis of the samples taken at the six dairies and analyzed at UCI in Year-2 have 

been converted from concentrations to unit surface fluxes and are reported in the 

results section. A great deal of additional flux chamber data will be added to the body of 

data reported here when the related projects are completed. Correlations between 

calculated fluxes and other data will be more valid at that time and will be included in 

the comprehensive report at the end of 2009. 

Task 7. If, as anticipated, co-funding is available from CSU-Agricultural Research 

Initiative or other sources, select additional sites and waste mitigation 

processes to continue the work started with the initial ARB funding. 

4
Additional funding for related field work and analysis at these six sites and others was 

secured from CSU/ARI, CEC through UC-Riverside, USDA-CSREES through UNH and 

UCD, California Dairy Campaign, Engineered Compost Systems and Sustainable 

Conservation. The data set for all these related projects will be available on a project 

website beginning in April, 2009. The data will be summarized in the comprehensive 

report to be prepared upon completion of most of the related projects in December, 

2009. 

Field Sampling Overview 

The original project field sampling plan, developed by the advisory group, relied on 

collection of ambient upwind and downwind air samples to be analyzed at UCI. Dairy 

ROG emissions were to be quantified through downwind-upwind measurements from 

ambient air sample concentration data collected for the various lagoons, corrals, and 

other dairy emission sources to be evaluated under the project. Samples were 

collected in standard 6-liter evacuated summa canisters outfitted with regulators to allow 

time-integrated samples to be collected. Upwind samples were collected at a height of 

1 to 2 meters, and downwind samples taken at heights of 1, 2, 5, and 10 meters for 

dispersion modeling. Sampling periods were to be selected to ensure a high likelihood 

of consistent wind speed and direction necessary for effective emission flux estimates 

using the Industrial Source Complex Short Term version 3 (ISC-STv3) steady state 

Gaussian plume model. Each dairy sampling event was to include a minimum of two 

sampling periods per day for at least two days. Following sample collection, all 

canisters were to be immediately shipped to Dr. Blake at UC Irvine for sample analysis 

and quantification. 

This original plan proved to be unsuitable for a variety of reasons: 

1. Wind speed and direction parameters for the ISC model were never achieved in 

12 sampling events and several other failed sampling attempts. 

2. Excessive requirements for the limited amount of GC-MS analysis available in 

the budget for UC Irvine precluded more intensive sampling at each facility. 

After the evaluation of the unsatisfactory ambient sampling, a number of alternatives 

were considered and a Year-2 sampling program emphasizing flux chamber 

sampling was developed and approved by the advisory group. 

Quality Assurance Objectives 

Under Task 2 of the project, all field sampling, data collection, analysis, and reporting 

will be designed within a comprehensive Quality Assurance/Quality Control (QA/QC) 

program. The objectives of the QA/QC program will ensure and document the 

precision, accuracy, completeness, representativeness, and comparability of collected 

data. 

The QA/QC procedures for the field sampling are included in the Year-2 plan, (Appendix 

B). The QA/QC program for the UCI analysis was included in the original proposal and 

is attached in Appendix C. 

5
Sample Coordination and Recording 

All samples were to be accounted for from the time of collection until results are verified 

and reported. Sample custody procedures provide a mechanism for clearly 

documenting field records, sample labels, a sample master logbook, sample shipment 

and receipt chain-of-custody, sample handling procedures, and sample preservation 

protocols. 

A series of field log sheets were developed, specific to each sampling operation. 

These sheets were designed to combine data for the ambient conditions, location 

details, sampling parameters and all other sampling related to the specific location and 

date on a single, master sheet. Examples of these log sheets are shown in Appendix D. 

The primary use of these sample logs will be to coordinate the data from the UC Irvine 

analysis reported here with other data for the same locations related to the other 

projects for the comprehensive report. 

Calibration Procedures and Frequency 

All sampling equipment, sampling canister cleaning equipment, laboratory analytical 

equipment, instrumentation, and other analytical devices was to be maintained and 

calibrated according to manufacturer’s specifications. All key equipment was regularly 

calibrated to ensure full and accurate operation. Calibration results will be properly 

documented and retained. Detailed standard operating procedures for key processes 

will be provided as part of project reporting. 

Calibration procedures for this CARB portion of the overall study are all related to the 

UC Irvine analytical procedures found in Appendix C. Calibration of field analytical 

equipment and CSU Fresno procedures for the related projects are detailed in the Year2 program in Appendix D. 

Data Reduction, Validation, and Reporting 

All key project field, laboratory, and analysis data was to be stored in appropriate 

databases or spreadsheets for analysis and documentation. Blank sample analysis, QA 

analysis, out of range data analysis with qualifiers, and all other relevant data 

descriptors and qualifiers will be fully documented. 

Analyses of the canister samples at UC Irvine were reported in proportional volumetric 

units, pptV (parts per trillion by Volume). Calculation of ROG flux from this data was a 

two step operation: 

1. Each constituent in the UC Irvine data had to be converted from a volume proportion 

to a mass in order to accurately sum them for an ROG total. 

 pptV X molecular weight X 0.0000409 = μg/m3

 

This formula gave a mass value for each constituent per unit volume of air so the sum 

of the gasses identified as ROG could be expressed as mass for the calculation of flux. 

6
2. Each constituent and the sum, in μg/m3

 of air, could then be converted to a flux rate 

by a formula described in the US-EPA Isolation Flux Chamber methodology (Appendix 

D). The area covered by the particular flux chamber (0.1924 m2

) and the rate of flow of 

the zero-air flushing gas (10 liters/minute = 0.01 m3/minute) were required for this 

calculation. 

 μg/m3 X (0.1924 m2 / 0.01 m3/minute) = flux rate μg/m2/minute 

All flux rates in tables 3-10 in the results section as well as the individual samples 

shown in Appendix A were calculated in this manner. 

The analytical results from UCI along with conversion steps from the reported 

concentrations to the flux values reported here will be available on a website to be set 

up as part of the comprehensive data set for the entire project. The data for the CARB 

study along with feed, silage, manure, soil and ambient conditions will be available to 

all participating agencies and researchers on this project website by April, 2009. 

Additional data will be added to that website as it is developed. A final report of the 

comprehensive project will be prepared at the end of 2009. 

Sampling Sites 

The original proposal called for five dairies to be selected for a regular sampling 

program over the term of the project. The addition of the related projects enabled the 

regular sampling program to be expanded to six dairies. The sampling periods were 

chosen by the advisory group to reflect three different times during the season when 

both the climate and the operations at the diaries would be different from the other two 

sampling periods of the Year-2 program. 

The regular sampling periods were selected as: 

Winter = January – March 

Early Summer = May – July 

Fall = September – November 

The dairies were originally selected to have different manure handling systems. As 

discussed above, ROG from the feeding operations was shown to be more significant 

and so the focus of the study was altered to emphasize feed and silage while still 

monitoring emissions from the manure management systems. Fortunately, the six 

dairies were sufficiently different with respect to silage, commodities, feeding schedule 

and feed management to be a representative sample of feeding practices across the 

dairy industry. Characterization of the feed and feeding practices involves more 

sampling and records with regard to the materials and ration. Most of this 

characterization is still being done as part of the continuing projects and will be 

documented in detail in the report at the end of 2009. 

One of the first suggestions from the industry representatives in the advisory group was 

to preserve the privacy of the cooperating dairies. Approximately a dozen dairymen 

were contacted and considered for the regular sampling program. Each was reluctant 

until anonymity was promised. Several questioned the ability of the research group to 

7
maintain their privacy. Each cooperating dairy operation was given the following 

assurance: 

1. The name of the dairy would not appear in any reports or published documents 

related to the project. 

2. The address or location of the dairy would not appear in any reports or 

publications beyond identifying all six as being in the San Joaquin Valley. 

3. All records such as feed rations, lab reports and other documents obtained from 

the dairy for the purpose of supporting the project would be redacted to remove 

identifying information. 

4. Each dairy would be identified by a letter (A – F) 

5. The published reports would state that the dairies were located from Tulare 

County north to Stanislaus County. 

6. Each dairy operator would be furnished with all data collected from that particular 

operation and would be given a draft of the final report to review prior to 

publishing. (This will apply to the final, comprehensive report to be published at 

completion of all related projects rather than this CARB report). 

Dairy Descriptions 

The six dairies selected for the regular sampling, designated by letter, and their 

operational characteristics are these: 

A. A free-stall, flush-lane dairy milking 2000 cows with 350 dry cows and 500 

heifers. The manure is flushed into a processing pit, over a sloping screen and 

into one of two treatment lagoons. Effluent flows from the treatment lagoon to a 

large storage lagoon where it is mixed with fresh water and applied to 

surrounding cropland. The separated solids are used for bedding in the freestalls. Lane flushing, corral scraping and other maintenance operations are more 

frequent than at the average dairy. The feed storage and mixing operations are 

carried out on site. 

B. A 3000 cow dairy with 500 dry cows and no heifers. The manure is flushed into 

small pits at the end of the barns, pumped over a sloping screen and into a single 

large lagoon. The barns are a free-stall system with cow mats for bedding 

instead of composted manure. Effluent from the lagoon is pumped into the 

irrigation pipeline system where it mixes with irrigation water and is applied to 

surrounding cropland. Also, lagoon effluent is separated from solids via the 

liquid-solid separator. Corrals are scraped infrequently. Feed storage and 

mixing operations are done at another location approximately 1km from the site. 

C. A free-stall, flush-lane dairy milking 525 cows with 150 dry cows and heifers. 

The manure is flushed into a small processing pit, over a sloping screen and into 

a series of four treatment lagoons. The volume of the lagoons is very large for 

the animal population and the organic loading of the lagoons is very low. Each 

lagoon has several circulators that operate continuously. The lagoon 

environment is such that photosynthetic microbes are prevalent, giving the 

lagoon a purple/red color. The effluent from the final lagoon in the series is used 

as irrigation on 130 acres of pasture for the dry cows and heifers and is also 

8
delivered to a neighboring farm for production of forage and other crops. The 

feed storage and mixing operations are carried out on site. 

D. A free-stall, flush-lane dairy milking 3700 cows with no dry cows or heifers on 

site. The manure is flushed into a large processing pit, over a series of sloping 

screens, through two treatment lagoons and finally into a large storage lagoon. 

The lagoon system is doubled so that half the effluent from the separation 

screens is processed in each of two series of treatment lagoons. Both sets of 

treatment lagoons feed into the large storage lagoon. All treatment lagoons and 

the storage lagoon have several circulators that run continuously. The 

separated solids are used for bedding in the free-stalls. The effluent from the 

storage lagoon is pumped onto cropland when needed for fertilization of the 880 

acres of forage. A nutrient management consultant monitors the soil, crop and 

lagoon effluent to determine the optimum use of effluent for crop nutrition and to 

avoid N leaching problems. The feed storage and mixing operations are carried 

out on site. 

E. A free-stall dairy that utilizes a vacuum truck to collect the undiluted manure 

slurry from lanes twice each day. The dairy milks 1000 cows with 200 dry cows 

and heifers. The manure slurry is pumped from the truck to a plug-flow digester 

with a residence time of approximately 21 days. The gas from the digester is 

used to power a 100 kW generator. Effluent and solids from the digester are 

separated using a screw press with the solids used for bedding and the liquid 

stored in a lagoon for use on surrounding orchards and cropland. In 2007, the 

free-stall beds were converted to cow mats as opposed to composted manure 

beds. The feed storage and mixing operations are carried out on site. 

F. A free-stall dairy with lanes similar to a flush-lane system. The dairy milks 2500 

cows with no dry cows and no heifers on site. The cows are kept in the freestalls with very small open lots. This dairy utilizes water mattresses in the freestall barn as opposed to composted manure bedding. The lanes are not flushed 

as is the usual practice in similar operations. Undiluted manure slurry in the 

lanes is scraped into small pits at the center and end of the free-stall barns. The 

slurry then drains to large holding pits in between the free-stall barns without 

being flushed with a large volume of water. The dairy is surrounded by extensive 

cropland. The manure slurry from the storage pit is pumped into a large tanktrailer, hauled to a field and the slurry is injected 20cm below the surface of the 

soil. The feed storage and mixing operations are carried out on site. 

Regular Sampling Program (Year-2) 

Tasks 2 and 3 of the proposal established the first year’s (Year-1) sampling program 

once the six dairies were selected. That program was primarily to collect initial data for 

speciation of dairy ROG and to evaluate various sampling and analytical methods to be 

validated and used in the final year (Year-2) of the study. A Year-1 report was prepared 

in the spring of 2007 and submitted to CARB in July. That report is attached as 

Appendix B. Prior to submission, a draft was provided to the advisory group for 

discussion of the changes in the sampling program for Year-2 as required for Task 4. 

9
After several meetings, the following modified sampling program was approved by the 

advisory group and implemented for the fall, 2007 sampling period. 

Note: This plan includes all sampling for all related projects. Only samples designated 

“UC Irvine” pertain to this CARB project and the data reported below. Data from the 

other sources listed will be added to the CARB/UC Irvine data in the comprehensive 

report at the end of 2009. 

The Year-2 monitoring plan proposed in the Annual Report submitted to the ARB 

Research Division in May, 2007 was modified after discussions with the ARB staff, the 

local air district staff and the advisory group at the July 12, 2007 meeting. After input 

from the advisory group and further discussions with the ARB staff, several changes to 

the original monitoring plan were adopted. There were three significant areas where the 

plan was modified: 

1. The ambient sampling that requires specific wind conditions and consumes at 

least six canisters and subsequent GC-MS analysis at both UC Irvine and CSU 

Fresno was eliminated from the regular sampling program. It was found to be 

impossible to obtain the required wind conditions at each dairy for each of the 

sampling periods. Under the best conditions, this monitoring/modeling only 

differentiates between emissions from animal housing vs. lagoons. These 

results, from uncertain modeling conditions, consumed nearly half of the 

canisters and analytical activity for results of limited value. The unexpectedly 

significant emissions of alcohols from feed and fresh manure (see item 2 below) 

will require additional canisters and GC-MS analysis for documentation. The 

elimination of the regular ambient sampling will enable the re-direction of those 

resources to the more critical feed and silage monitoring. Ambient downwindupwind sampling will be added, when wind conditions warrant, to the special 

sampling program discussed below in item 3. 

 

2. The most significant new information from the Year-1 data is the documentation 

of significant emissions of alcohols, particularly from feed and silage but also 

from fresh manure. In some instances, the two dominant alcohols, ethanol and 

methanol, comprise well over 90% of the total monitored ROG emissions. The 

original monitoring plan did not include sufficient sampling to adequately 

document the emissions from those sources, particularly with regard to their 

spatial and temporal variability. After discussion in the Dairy Sub-committee and 

consultation with the ARB staff, the focus of the sampling plan has been shifted 

to these sources of alcohols. Additional canisters and analysis at UCI and CSU 

Fresno will be devoted to silage and Total Mixed Ration. 

3. The regular monitoring of the six dairies as described in the original proposal will 

be supplemented by additional sampling between the scheduled sampling 

periods. More intensive sampling of alcohol sources to better characterize 

variability, additional feed components and ambient sampling when wind 

conditions are suitable will be done on two of the six dairies as the opportunities 

10
are presented. Additional monitoring of emissions from lagoons and land 

applications of lagoon effluent will also be done when possible, primarily for N 

compounds but the full suite of ROG’s will also be monitored. 

The modified Year-2 monitoring program for the regular sampling of the six dairies is 

shown in Table 1 and the special sampling program is shown in Table 2. These were 

approved by the CARB staff and the project advisory group for the monitoring period 

scheduled for September/October, 2007, continued through January/February, 2008 

and May/July, 2008. 

Table 1. Modified Year-2 monitoring program adopted for Fall-07. This monitoring 

program, after approval by ARB and the project advisory group was used at the six 

dairies for the regular sampling and analysis from September/October, 2007, through 

January/February, 2008 and May/June, 2008. 

CSUF Dairy Flux Chamber Sampling Sources and Analytical Methods- Year 2 

Proposed Sampling Program at Each Dairy- Routine Sampling (6 Dairies) 

(Number of Samples) 

Source 

Locati

on 

# 

Analytical Method Additional Tests 

Innova

1412 

UCI

Can 

CSUF

Can 

TO-17 

Tube 

Lab 

Samples 

Silage 

Density 

Silage 

Aerobic 

Stability 

Feed Sources 

Total Mixed Ration (0.5 h Post 

Placement- Not Consumed) 1 & 2 2 1 1 1 2 - - 

Total Mixed Ration (~6 h Post 

Placement- Consumed) 3 & 4 2 1 1 1 2 - - 

Total Mixed Ration (~6 h Post 

Placement- Not Consumed) 5 & 6 2 1 1 1 2 - - 

Silage Pile Disturbed Face 7 & 8 2 1 1 1 2 - - 

Silage Pile Vertical Undisturbed Face 9 & 10 2 1 1 1 2 4 2 

Field Blank 11 1 1 1 1 - - - 

Media Blank - 1 1 1 - - - - 

Total Feed Sources (Each Dairy) 12 7 7 6 10 4 2 

TOTAL Feed Sources (6 Dairies) 72 42 42 36 60 24 12 

Manure Sources 

Open Lot/Corral (Deep Manure Pack) 1 & 2 2 1 1 1 2 - - 

Open Lot/Corral (Shallow Manure 

Pack) 3 & 4 2 1 1 1 2 - - 

Flush Lane (Pre-Flush) 5 & 6 2 1 1 1 2 - - 

Flush Lane (Post-Flush) 7 & 8 2 - 1 - 2 - - 

Bedding 9 & 10 2 - 1 - 2 - - 

Field Blank 11 1 1 1 1 - - - 

Media Blank - 1 1 1 - - - - 

Total Manure Sources (Each Dairy) 12 5 7 4 10 0 0 

TOTAL Manure Sources (6 Dairies) 72 30 42 24 60 0 0 

Total Feed & Manure Sources (Each 

Dairy) 24 12 14 10 20 4 2 

TOTAL Feed & Manure Sources (6 

Dairies) 144 72 84 60 120 24 12 

11
Table 2. Special Sampling program proposed for Year-2. This monitoring program was 

conducted at two of the six dairies between the scheduled sampling periods. Most of 

this activity was conducted for the related projects but the UCI data is shown in the 

Results section of this report. 

CSU Fresno Dairy Flux Chamber Sampling Sources and Analytical Methods- Year 2 

Proposed Sampling Program at 2 Dairies- Special Sampling 

(Number of Samples) 

Feed Source 

Analytical Method Additional Tests 

Innova

1412 

UCI

Can 

CSUF

Can 

TO-17 

Tube 

Lab 

Samples 

Silage 

Density 

Silage 

Aerobic 

Stability 

Silage Pile 

Silage Pile Disturbed Face 2 2 2 1 2 - - 

Silage Pile Vertical Undisturbed Face 2 2 2 1 2 4 2 

Main Commodities 

1- 2 1 1 1 1 - - 

2- 2 1 1 1 1 - - 

3- 2 1 1 1 1 - - 

Total Mixed Ration (TMR) 

TMR +0.5 h Post Placement (Not 

Consumed) 2 2 2 1 - - - 

TMR +1.0 h Post Placement (Consumed) 2 2 2 1 - - - 

TMR +2.0 h Post Placement (Consumed) 2 2 2 1 - - - 

TMR +3.0 h Post Placement (Consumed) 2 2 2 1 - - - 

TMR +4.0 h Post Placement (Consumed) 2 2 2 1 - - - 

TMR +5.0 h Post Placement (Consumed) 2 2 2 1 - - - 

TMR +6.0 h Post Placement (Consumed) 2 2 2 1 - - - 

Total (Each Dairy) 24 21 21 12 7 4 2 

TOTAL (2 Dairies) 48 42 42 24 14 8 4 

In addition to comments and suggestions from the advisory group that generated the 

modified programs described above, there were a number of questions related to the 

documentation of the sampling and the dairy operations. A summary of the flux 

chamber procedures as applied to the sampling locations at these dairies follows this 

section. These photos and descriptions illustrate the application of the US-EPA 

Isolation Flux Chamber methodology to these specific monitoring sites. More detailed 

descriptions of the flux chamber methodology as well as examples of the forms used to 

document the sampling locations are attached as Appendix D. 

12
Figure 1. Flux chamber sampling of an open lot area at Dairy B. The canister sampling 

the chamber on the left was analyzed by GC/MS for data reported below. The gas 

analyzer in the cart and the ammonia denuder on the top of the chamber on the right 

are sampling for data to be included later in the comprehensive report. 

The flux chamber is placed on the surface to be monitored with care to disturb the 

surface material as little as possible. A tight seal is not required because of the 

continuous flow (10 L/minute) of sweep air into the chamber, resulting in a positive flow 

out of the chamber through both 1 cm vents in the top and gaps at the bottom of the 

chamber. The sweep air is commercially available “zero-air” (80% N2 plus 20% O2) in 

the cylinder at the center of Figure 1. The chamber is flushed for 30 minutes prior to 

any sampling to eliminate ambient air trapped as the chamber was placed on the 

surface. After the 30 minute conditioning period, various samples can be taken for 

another 30 minutes before significant changes in the surface conditions could occur due 

to the enclosed atmosphere. Initial temperature measurements are recorded for the 

ambient air and surface as well as the air and surface inside the chamber. The ambient 

and chamber temperatures are recorded again at the time of sampling. Flux sampling 

of the open lots was done in this manner; followed by manure/soil samples collected 

where the chambers were placed. 

13
Figure 2. Flux chambers during the conditioning period prior to sampling on a flush 

lane at Dairy B. 

Sampling of the flush lanes began when the cows were feeding and ruminating prior to 

flushing so that the manure/urine slurry was relatively thick in the lane as shown in 

Figure 2. The one-hour monitoring period was timed to occur just prior to a flush so the 

exclusion of the cows from the sampling area would not reduce the amount of manure 

to be sampled below what would normally be found there in the 3 hours prior to the 

flush. Once the Pre-Flush samples were collected, the lane was flushed and the 

chambers were set up at the same location. That often coincided with the cows being 

milked so the barn was empty and no manure was deposited in the lane during the onehour sampling period. The flushing cycles were from 6 to 12 hours apart so it appeared 

this monitoring program was appropriate to determine the beginning and ending 

conditions of the cycle. Deposition of manure was continuous once the cows returned 

from milking so an average of the Pre-flush and Post-flush emissions should give a 

reasonably accurate picture of the flush lane emissions during the cycle. 

14
Figure 3. Flux chambers sampling Total Mixed Ration at Dairy A. This is an 

intermediate sample, a few hours after placement of the feed, as shown by the absence 

of nearly half of the TMR and the disturbed top of the pile of feed. 

Monitoring the TMR with the flux chambers required considerable care and method 

development. The feed is delivered from a large truck or wagon 2 – 4 times each day. 

It was apparent from the initial sampling that the TMR was both a significant and 

variable source. Chambers were placed on the TMR just after it was delivered to the 

bunker. The conditioning period for the chambers precluded any sampling prior to 30 

minutes post-placement so this first sample is considered the initial value. It was 

apparent that the emission rate decreased as the TMR was both consumed and 

exposed to the air over the period of about 6 hours that it was in the bunker. Sampling 

for UCI analysis took place at the beginning and on the residue remaining after 6 hours. 

Sampling was also done on the surface of the bunker after the TMR had been 

consumed or swept up prior to the subsequent feeding operation. Some TMR sampling 

was done between 30 minutes and 6 hours for the special sampling to be reported in 

the comprehensive report. Portions of that intermediate data are shown in Figures 6 

and 7 to illustrate the decrease in emissions over time from the TMR. 

15
Figure 4. Flux chamber sampling of silage at Dairy C. Initial sampling of “disturbed” 

silage pulled down from the pile, shown by the two chambers on the right of the photo, 

indicated very high emissions of alcohols from that source, under these conditions. 

Sampling the relatively larger surface of the “undisturbed” silage of the pile face 

required a frame to hold the chamber against the vertical face shown by the two 

chambers on the left. Canisters for GC/MS analysis are on the ground at the rightcenter, near the Zero-air cylinder and flux chambers on the small pile of disturbed 

silage. 

Silage as described in the results section below needed to be monitored in two forms. 

The compacted, vertical face of the silage pile was very dense and required the 

chambers to be held against the surface by a rack constructed for that purpose. There 

was also an amount of silage pulled loose from the face by the equipment used to mix 

the TMR. That disturbed silage had a lower density and appeared to be more 

biologically active. Chambers could be placed on this loose silage at the base of the 

pile face to determine the differences in emission rates from the two forms of silage. 

Core samples were taken from the face at the location of the undisturbed samples and 

analyzed for composition and density. 

16
Figure 5. Flux chamber field blank at Dairy F. The flux chamber is placed on a clean, 

Teflon sheet on the floor of the equipment trailer; then conditioned and sampled by the 

same procedures used to collect samples from dairy sources. Here the chamber is 

being conditioned to determine a field blank immediately after sampling TMR at Dairy F. 

A field blank was collected at least once each day, following the sampling procedures 

described above. A Teflon sheet was cleaned with distilled water, wiped dry and placed 

on the bed of the truck or equipment trailer while parked in the location of the most 

recent sampling procedure. The chamber was conditioned with sweep air and then 

sampled by a UCI canister as well as the other methods used for that day’s data 

collection. In addition to the field blanks, a media blank was also prepared by filling the 

canister with the zero-air used for sweeping the chamber and sent to the lab for 

analysis. The media blanks were prepared at the same time the field blanks were 

collected. Field blank and media blank data can be found on the project website. Data 

reported in Tables 2 – 10 of this report have been corrected by subtraction of the 

appropriate blank. 

17
RESULTS 

Over the period from June, 2006 through the end of the regular sampling period in July, 

2008, a total of 556 air samples were collected in 2 liter canisters and analyzed by Dr. 

Donald Blake at UC Irvine. The first 57 of these were ambient air samples to be used 

for speciation of dairy ROG emissions and eventually downwind-upwind differences for 

dispersion modeling. These ambient samples were successful in confirming the 

contemporary research at UC Davis showing the predominance of alcohols, particularly 

ethanol, in dairy emissions. Modeling downwind-upwind samples to calculate flux rates 

requires consistent wind direction and a minimum wind speed of 1 m/sec. The 

consistent wind direction could sometimes be obtained with some difficulty but the 

consistent minimum wind speed was never achieved in 12 attempts. 

The advisory group’s recommendation to focus on feeding operations required a 

method of monitoring that was more specific than downwind-upwind sampling could 

provide, even with appropriate wind conditions. The EPA Isolation Flux Chamber 

method (described in Appendix D) proved to be much more suitable in obtaining 

emission fluxes for specific locations and surfaces at the dairies. A number of flux 

chamber samples were collected in Year-1 and summarized for the advisory group in 

April, 2007. After comparing the flux chamber results with the unsatisfactory downwindupwind data, the advisory committee decided to change the major sampling effort to flux 

chamber measurements and increase the emphasis on operations related to feeding 

while still monitoring manure management in Year-2. 

In the Year-2 program, the sampling for the CARB portion of the project is designated 

as the UCI Can samples in Table 1. A more detailed evaluation of feed and silage also 

used UCI Can samples to study silage variability and the feeding operation in more 

detail. The special sampling is described in Table 2 and the data from the UCI Can 

samples is reported below. Comprehensive evaluation will not be possible until the 

completion of related projects later in 2009. 

The regular sampling program, designated as the Year-2 program, began in the fall of 

2007 and was completed in summer of 2008. The UC Irvine/CARB portion of that 

program included 78 samples from silage, 144 samples of feed (TMR), 91 samples from 

flush lanes, 64 samples from open lots or corrals, and 102 samples for field and media 

blanks. Results reported below, with the exception of the ambient samples in Appendix 

A, Table A6 are corrected by the subtraction of an appropriate field blank for that day. 

Some samples taken prior to the beginning of the Year-2 program did not have UC 

Irvine field blanks for corrections and are not reported here. Data from the related 

projects may provide adequate QC for these samples so they can be reported later. 

The average flux rates for each of the four dairy operations that made up the regular 

sampling program during the Year-2 period of summer, 2007 through summer, 2008 are 

shown in Tables 3 through 8 and summarized in Table 10. These are the average flux 

rates for all dairies and dates. Table 10 indicates the relative differences among the 

four dairy sources of feed, the Total Mixed Ration, flush lanes and open lots. The 

18
individual analyses averaged for the tables in this section are shown in Appendix A. 

While each sample taken was analyzed for all identified gasses by UC Irvine, most 

samples included only a few components in significant quantities. The alcohols 

mentioned above made up the major portion of nearly all samples from each operation. 

A few others such as acetaldehyde, di-methyl sulfide, (DMS) and di-methyl-disulfide 

were sometimes as much as 1% - 15% of some samples. Two of the dairies (A and D) 

included cull citrus pulp in their TMR with the result that significant amounts of limonene 

were found in their TMR and manure samples. In order to reduce complexity in the 

tables, only the significant components of the fluxes, the alcohols, acetaldehyde, DMS 

and limonene are shown in the results tables. The remaining ROG components 

analyzed by UC Irvine were nearly always in trace concentrations, at most and 

contributed less than 1% to the total ROG flux. The complete analysis of each UC 

Irvine sample including the trace components will be reported on the project website. 

Silage Flux Rates 

The highest flux rates monitored in the study were from the compressed and fermented 

forage known as silage. Silage is generally the largest component of the Total Mixed 

Ration that is made up at the dairy and fed to the animals. It is 40% - 65% of the TMR 

and provides both energy and nutrition. Silage is most often made from corn grown 

near the dairy. It is harvested in early fall by chopping the entire plant just as it reaches 

maturity. The chopped plant material is piled at the dairy, compacted and covered. The 

material ferments and, if compacted sufficiently, the interior of the pile will be anaerobic 

to the point that lactic acid fermentation will lower the pH until no further microbial 

activity can occur. In this form the silage can be stored for several months to provide 

feed for the cows through the winter and spring when their energy and nutrition 

requirements are highest. 

The silage emissions monitored in this study were from both the compressed, 

undisturbed silage at the “face” of the covered pile, Table 4, and the loose silage pulled 

down from the face to be used for making up the next TMR to be fed. The disturbed 

silage data is shown in Table 3. The flux rates for disturbed material are higher than the 

undisturbed silage piles by a factor of 5. This is most likely due to the rapid 

fermentation and other microbial activity that would be stimulated when the 

compressed, anaerobic material is pulled loose and exposed to air. The very high 

percentage of ethanol from fermentation may be an indication that this is occurring. The 

variability seen in emissions from disturbed material, compared to the more consistent 

emissions from the undisturbed silage in Table 4 is an indication of differences in both 

silage composition and quality. A less compacted silage pile will be less anaerobic and 

may degenerate more rapidly when exposed to air. This variability will occur in both 

disturbed and undisturbed silage but is likely to most prevalent when the material is 

aerated by the feeding equipment. The high levels of DMS are possibly indications of 

spoilage related to high protein silage. Ammonia and other N compound emissions as 

well as silage composition and density were monitored for a related study and those 

results should provide considerably more detailed evaluation of silage quality vs. flux 

rates in the later report. 

19
There is considerable variation among the six dairies with regard to silage flux rates 

shown in Tables 3 and 4. Corn silage is most common but dairies B and F also made 

silage from small grains such as wheat and barley. This “winter silage” has a different 

protein and energy content and would produce different emissions of alcohol and other 

constituents. It is also a more coarse material and more difficult to compress so it may 

degrade more rapidly. Emissions from the different types of silage will be separated in 

more detail when the data from the related projects is complete and reported. 

Potential for emission reductions related to silage management might include 

minimizing the disturbance of the silage by only pulling sufficient material from the pile 

to make up the current feed mix. In spite of the high flux rates from silage, it is a 

relatively small area compared to the rest of the dairy and complicated changes in 

silage management may not have as much potential to contribute to the overall 

emissions of ROG from a dairy. 

Table 3. Average flux rates for “disturbed silage” material pulled loose from the pile 

face for use in the next mixed ration. Individual data averaged for this table can be 

found in Appendix A, Table A1. Values are in μg/m2

/minute and are corrected by the 

subtraction of Field Blank values. Total ROG

Ethanol

Methanol

Total AlcoholsTotal Alcohols

Acetaldehyde

d-Limonene

DMDS

DMS

Dairy Averages Surface Air

A 25.7 22.5 19,018 13,001 1,383 14,407 80% 480 287 1 3,776

B 22.1 15.4 2,961 2,558 325 2,892 98% 32 3 1 34

C 24.6 18.8 36,192 34,828 555 35,401 93% 303 9 1 451

D 27.5 20.5 18,620 8,810 459 9,283 84% 41 4 2 9,266

E 27.1 18.4 13,789 10,440 555 11,004 78% 76 1 1 2,636

F 19.4 19.5 20,252 7,111 513 7,637 75% 321 0 1 12,287

Ambient 

Temperature 

(degrees C)

20
Table 4. Average flux rates for “undisturbed silage” material still compacted in the 

exposed face of the pile. Individual data averaged for this table can be found in 

Appendix A, Table A2. Values are in μg/m2

/minute and are corrected by the subtraction 

of Field Blank values. 

Total ROG

Ethanol

Methanol

Total AlcoholsTotal Alcohols

Acetaldehyde

d-Limonene

DMDS

DMS

Dairy Averages Surface Air

A 27.0 21.4 4,848 3,575 573 4,167 88% 192 11 1 471

B 22.2 17.5 5,577 4,540 282 4,823 86% 16 1 1 738

C 23.8 17.2 5,368 3,605 496 4,107 79% 152 5 1 1,095

D 26.2 16.7 6,124 4,439 697 5,198 85% 665 18 0 239

E 21.5 16.8 2,636 1,798 294 2,094 84% 24 2 0 513

F 19.9 20.7 1,905 1,542 203 1,745 91% 53 0 1 106

Ambient 

Temperature 

(degrees C)

Total Mixed Ration and Feed Materials Flux Rates 

The general term for the material fed to the dairy herd is “Total Mixed Ration” referred to 

here as TMR. The TMR is usually made up from components at the dairy though some 

may truck it in from another facility as is done at Dairy B. The TMR is mixed from silage 

and alfalfa hay with various commodities such as distiller’s grain from ethanol 

production, cotton seed meal, almond hulls and other commodities that can provide 

energy and nutrition. Most dairies employ a consulting nutritionist to recommend the 

most economical components available to provide the energy and nutrition needed for 

the cows. The TMR is mixed and fed generally twice each day in a bunker or trough so 

the cows can eat when they choose. TMR is usually consumed in 6-8 hours. Dairies 

scrape or sweep the remaining feed after about 5 hours so the cows can reach it more 

easily from the flush lane. This practice may affect ROG emissions as seen in the data 

below. 

ROG emissions were monitored by flux chambers on the TMR immediately after it was 

placed in the bunker. The flux chamber procedure requires 30 minutes before sampling 

can take place (see Appendix D) so the flux rates could not be measured until that time. 

As the cows consumed the feed, the amount decreased and the TMR appeared to 

change as it dried. As was observed with silage, disturbing the material appeared to 

stimulate emission of ROG. The mixing and delivery of TMR with its large percentage 

of silage would be expected to produce a spike of emissions. The advisory committee 

anticipated this and included further sampling of the TMR at 6 hours post-placement for 

the Year-2 program. When possible, a sample was taken of the bunker surface after the 

TMR was completely consumed. This was often done 6 hours post placement when 

most of the dairies would sweep the remaining TMR to a small pile nearer the flush 

lane. The 6 hour TMR sample and the “6 hour consumed” sample could be taken 

simultaneously. 

21
The Year-2 TMR flux rates for the post-placement time periods are shown in Table 5 

and the averages for each dairy monitored are in Table 6. The magnitude and 

variability of TMR flux rates are the most significant features of these tables. The rates 

are highest just after feed placement as anticipated and show a significant decrease at 

1.5 hours. The flux rates at 6 hours increase to about twice the level at 1.5 hours 

though the bunker surface when the feed is consumed is decreased. The increase in 

ROG flux rates at 6 hours occurred primarily at Dairies A, B, C, and D while Dairies E 

and F show a continuing reduction in emissions over time (see Table A3 in Appendix A). 

Those first four dairies scrape and sweep the TMR more frequently and it may be that 

disturbing the feed stimulates ROG emissions as it appears to do with silage. 

The special sampling described in the Year-2 program added more frequent monitoring 

of TMR at Dairies A and B in addition to the regular sampling reported here. Flux 

chambers were used to continuously monitor the feed from placement until it was 

consumed. Data from the special sampling of this related project will be included in the 

comprehensive report and should better characterize the relationship between TMR 

management and flux rate. Some UC Irvine samples and analysis was included in this 

special sampling program. While the related project is not yet completed, the UC Irvine 

analysis is finished and the results of five monitoring periods are graphed in Figure 6 for 

total ROG and Figure 7 for alcohols. The comprehensive report will include this data 

along with other sampling and supporting information to better characterized the 

changes in TMR fluxes with time. 

Table 5. Average TMR flux rates for all dairies sampled compared to elapsed time from 

placement in the feed bunker. The 1.5 hour values were only taken in spring, 2007 and 

do not correspond to all of the 0.5 and 6 hour post-placement values. The 6 hour postplacement values may, in many cases include sweeping or scraping of the TMR about 

4-6 hours after placement, the 1.5 hour samples do not. Values labeled “consumed” 

are the feed bunker surface after the TMR was consumed. Individual data averaged for 

this table can be found in Appendix A, Table A3. Values are in μg/m2

/minute and are 

corrected by the subtraction of Field Blank values. Total ROG

Ethanol

Methanol

Total AlcoholsTotal Alcohols

Acetaldehyde

d-Limonene

DMDS

DMS

Total Mixed Ration (0.5 h Post Placement) 15,022 11,668 1,460 13,141 86% 336 584 26 831

Total Mixed Ration (6 h Post Placement) 10,582 7,747 1,591 9,350 87% 469 557 9 152

Total Mixed Ration (6+h Post: consumed) 2,929 2,289 389 2,683 89% 106 102 3 32

Total Mixed Ration (1.5 h Post Placement)* 4,507 3,394 547 3,941 90% 15 459 34 12

 *sampled spring, 2007 only- see comments in text

22
Table 6. Average TMR flux rates for each dairy sampled. Values are averages of all 

samples taken over the feeding period when TMR was present. Individual data 

averaged for this table can be found in Appendix A, Table A3. Values are in 

μg/m2

/minute and are corrected by the subtraction of Field Blank values. Total ROG Ethanol Methanol Total Alcohols Total Alcohols Acetaldehyde d-Limonene

DMDS

DMS

Dairy Surface Air

A 13.9 13.7 9,674 5,356 2,074 7,440 76% 275 1,772 12 85

B 19.9 18.7 7,445 5,127 1,257 6,391 90% 304 2 28 679

C 24.0 17.1 15,549 14,376 602 14,983 95% 314 26 6 187

D 22.9 20.2 10,487 8,165 1,078 9,256 87% 326 641 8 169

E 19.4 20.1 5,781 4,778 432 5,214 90% 142 2 20 368

F 21.1 22.7 3,383 2,591 550 3,150 93% 103 1 27 96

Ambient 

Temperature 

(degrees C)

 

Total ROG Emission Rates from TMR

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

012345678

Hours after TMR Placement

ROG flux (μg/m2/min)

9

A 2/11/08 A 5/28/08 B 11/20/07 B 2/27/08 B 6/30/08

Figure 6. Total ROG fluxes related to time after feed placement from additional TMR 

flux data sampled as part of a related project. 

23
Total Alcohol Emission Rates from TMR

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

012345678

Hours after TMR Placement

ROG flux (μg/m2/min)

9

A 2/11/08 A 5/28/08 B 11/20/07 B 2/27/08 B 6/30/08

Figure 7. Total Alcohol (Methanol, Ethanol and Propanol) fluxes related to time after 

feed placement from additional TMR flux data sampled as part of a related project. 

Flush Lane Flux Rates 

Flush lanes are the concrete surfaced areas between the feed bunkers and the bedding 

stalls in a free stall dairy barn. The cows stand in a flush lane while eating the TMR and 

much of their manure is deposited in the lanes at that time. Most dairies construct the 

lanes with a slope so that a large volume of water can be used to flush the lane and 

remove the manure several times each day. The flush water drains to a collection and 

separation facility where the soil particles and coarse fiber in the manure are separated 

before the water and fine solids are stored in a lagoon. Water from the lagoon recycles 

for subsequent flushing operations. A few dairies remove the manure with a vacuum 

truck (Dairy E) or scrape it into pits (Dairy F) to eliminate the need for the large volume 

of flush water. 

The largest components of ROG identified in the silage and feed monitoring are 

alcohols that are very soluble in water and would, therefore, not be expected to be as 

volatile from an aqueous medium compared to a soil or concrete surface. The 

emissions from the lane after flushing are low as is shown by the Post-flush averages in 

Table 7. The fresh manure also has a significant water content and might also produce 

lower emissions of alcohols and other soluble ROG species. The flux rates for flush 

lanes are generally much lower than those of feed or feed components. The 

24
exceptionally high ROG total for Dairy A on 2/15/08 appears to be an anomaly. The 

total ROG for that sample exceeds the next highest by a factor of 4 and is more than 10 

times the average flux rate. Though the alcohols and DMS are higher than other 

samples, the high rate is due primarily to CFC-12, a refrigerant gas that was not found 

in other samples at more than trace concentrations. It remains to be determined 

whether this is an error or an example of a sporadic phenomenon. Other samples were 

taken on that date that may help explain these anomalous values in the comprehensive 

report. In the event that this one sample is not representative, the flush lane averages 

were recalculated without Dairy A on that date and are shown in Table 8. 

In general, the pre-flush flux rates are about 10% or less compared to those from TMR 

and silage. The post-flush flux rates are about 1% of those from feed. The rates from 

the individual dairies were fairly consistent and the differences between the flush dairies 

(A, B, C, and D) compared to vacuum (E) and scraping (F) were less than expected. 

The two dairies that did not use flush water were lower than the average of the flush 

dairies but only slightly so and the differences may not be statistically significant. 

Additional data from the related projects may result in more definitive evaluation of 

emissions from flush vs. scraped or vacuumed manure management. 

Table 7. Average flush lane flux rates for ROG. Values are averages for each dairy 

from samples taken prior to flushing unless specified as “Post-flush”. The significantly 

higher values for Dairy A are from one sampling event on 2/15/08. See text for further 

explanation. Individual data averaged for this table can be found in Appendix A, Table 

A4. Values are in μg/m2

/minute and are corrected by subtraction of Field Blank values. Total ROG Ethanol Methanol Total Alcohols Total Alcohols Acetaldehyde d-Limonene DMDS DMS

Average of all dairies Surface Air

Flush Lane (Pre-Flush) 17.1 17.9 353 22 9 108 47% 20 7 0 12

Flush Lane (Post-Flush) 12.9 15.8 21 3 1 6 53% 0 0 0 0

A 16.1 14.3 1,402 95 8 374 27% 67 10 0 71

B 16.6 18.0 246 13 9 66 51% 2 4 0 3

C 17.7 18.8 275 9 1 58 38% 38 4 0 5

D 16.1 18.9 116 12 29 83 72% 2 5 0 0

E 15.3 15.8 181 9 5 65 38% 18 17 0 3

F 20.3 20.6 129 12 6 75 58% 4 5 0 2

Ambient 

Temperature 

(degrees C)

25
Table 8. Average flush lane flux rates for ROG. Values are averages for each dairy as 

in Table 7 with the possibly anomalous data from Dairy A on 2/15/08 deleted. Individual 

data averaged for this table can be found in Appendix A, Table A4. Values are in 

μg/m2

/minute and are corrected by subtraction of Field Blank values. Total ROG Ethanol Methanol Total Alcohols Total Alcohols Acetaldehyde

d-Limonene

DMDS

DMS

Average of all dairies Surface Air

Flush Lane (Pre-Flush) 17.1 17.9 241 22 9 108 47% 20 7 0 12

Flush Lane (Post-Flush) 12.9 15.8 21 3 1 6 53% 0 0 0 0

A 16.1 14.3 207 12 9 69 27% 13 7 0 3

B 16.6 18.0 246 13 9 66 51% 2 4 0 3

C 17.7 18.8 275 9 1 58 38% 38 4 0 5

D 16.1 18.9 116 12 29 83 72% 2 5 0 0

E 15.3 15.8 181 9 5 65 38% 18 17 0 3

F 20.3 20.6 129 12 6 75 58% 4 5 0 2

Ambient 

Temperature 

(degrees C)

Open Lot, Exercise Pen and Corral Flux Rates 

Each dairy has some open uncovered areas that the cows can access from the free 

stalls. Some of the dairies (B and D) have very large open lots, others (C and F) have 

much smaller corrals. Except in the winter when access may be restricted, most of the 

manure that is not deposited in the flush lane will fall in the open lot. Animals tend to 

concentrate in parts of the corral where the manure pack will be relatively deeper than 

areas they do not frequent. Flux chamber sampling of fluxes in these open lots included 

both shallow and deep manure pack areas. The flux rates were expected to be different 

across the open lot and the average flux rate for the deep pack areas was higher than 

that of the shallow pack locations. 

Table 9 shows the averages for shallow and deep samples as well as the averages for 

each dairy. The flux rates for deep pack locations averaged about twice that of the 

shallow pack areas. It should be noted that most open lots are harrowed or disked for 

fly and odor control occasionally during dry weather and these practices are very likely 

to affect flux rates from open lots. 

Dairy E had a much higher average flux rate for the deep pack areas. This high 

average was due to the two deep pack samples taken on 6/21/07 in which the alcohols 

were similar to other samples but the acetaldehyde and di-methyl sulfide levels 

exceeded the average flux rates of the other dairies by an order of magnitude. The 

shallow pack sample for that date was also the highest of all sampled locations. Further 

analysis of the data from the related projects may be able to explain the high rates for 

this date. 

26
The average flux rates for open lots are comparable to those of the flush lanes though 

the larger area represented by open lots at most of the dairies makes them, potentially, 

a more significant source. Further analysis with the additional data from the related 

projects should provide more detailed evaluation of the differences between open lot 

conditions and may suggest management practices that might result in reduced 

emissions. 

Table 9. Open lot, exercise pen and corral flux averages. Fluxes are averaged from 

the individual samples found in Appendix A, Table A5. Shallow manure pack indicates 

samples taken from an area where the deposited manure was 0 – 5cm deep. Deep 

manure pack samples were from areas where the manure was 5-15cm deep. Values 

are in μg/m2

/minute and are corrected by the subtraction of Field Blank values. Total ROG Ethanol Methanol Total Alcohols Total Alcohols Acetaldehyde d-Limonene

DMDS

DMS

Average of all dairies Surface Air

Open Lot Shallow Manure Pack 25.2 21.0 102 15 17 45 56% 35 1 0 12

Open Lot Deep Manure Pack 24.4 21.1 243 20 28 60 57% 69 1 0 74

Average of each dairy - shallow manure pack

A 25.9 21.3 109 16 20 55 64% 35 0 0 13

B 23.5 21.0 63 15 12 29 61% 16 0 0 12

C 32.0 26.4 75 11 21 48 60% 17 1 0 5

D 23.9 21.3 150 26 11 75 57% 33 2 0 9

E 25.7 20.6 167 8 30 42 46% 95 1 0 24

F 21.2 15.8 36 8 7 20 44% 4 1 0 7

Average of each dairy - deep manure pack

A 21.7 18.2 92 17 25 44 61% 30 0 0 6

B 21.9 21.0 211 21 25 52 61% 5 1 0 37

C 36.1 24.8 127 15 19 51 43% 53 2 0 11

D 23.1 19.5 174 31 22 72 60% 27 2 0 17

E 26.6 23.6 616 11 49 75 48% 254 1 0 280

F 22.6 20.6 96 27 18 59 60% 8 1 0 20

Ambient 

Temperature 

(degrees C)

Correlations With Ambient Conditions 

The first samples collected in 2005-6 were upwind and downwind air samples described 

in the Year-1 program (Appendix B). This procedure was eliminated for the Year-2 

sampling program for reasons described above. There were two specific objectives for 

the ambient air sampling in Year-1 and the first was achieved while the second was 

unsuccessful. The use of ambient samples to characterize the range of specific 

components of dairy ROG emissions was quite useful. The unexpected predominance 

of alcohols first found in a study at UC Davis was confirmed by these field samples. 

The initial round of air samples also allowed the UC Irvine lab to calibrate their analytical 

systems and develop standards for dairy air emissions work. Dr. Blake’s lab had not 

analyzed samples of this type prior to this project and some calibration was needed 

before quantifiable results could be used with confidence. Table A6 shows the average 

27
of 59 ambient samples analyzed in Year-1. The very high values for alcohols may be 

inflated by some of the first analyses where the lab systems had not yet been properly 

standardized to the appropriate concentrations. The significance of data in Table A6 is 

the identification and relative magnitude of the various ROG components. The 

concentration values were often higher for the upwind or background samples than for 

the dairy downwind samples due to the variable wind speed and direction discussed 

previously. These data should not be used as examples of specific dairy emissions but 

are valuable for the identification of the components of ROG in the ambient atmosphere 

of the dairy areas of the Central Valley. 

DISCUSSION 

The four dairy operations sampled for this study were selected by the project’s advisory 

group after consideration of data from the initial year of the study. Though lagoons 

were originally considered to be a major source of ROG, these four, silage, TMR, flush 

lanes and open lots, proved to be more significant sources and so were emphasized in 

the Year-2 monitoring program. Fluxes for the four sources, averaged for all six dairies 

and each date are shown in Table 10. 

Of these four sources, silage has the highest flux rate, closely followed by TMR with 

flush lanes and open lots at much lower rates. The high flux from silage should be 

considered in light of the difference between the compressed material in the pile and the 

disturbed silage pulled from the pile to be used in the next TMR. Silage piles can be 

hazardous as they are often more than 10m high. The highly compressed material in 

the pile is generally so consolidated that the pile face, where material is pulled for TMR 

is usually vertical and may actually overhang the working area below the face. The 

compaction is never completely uniform and unstable areas of the pile are unavoidable. 

An unexpected fall of material from high on the face is not uncommon and can be 

dangerous. Consequently, the silage is usually pulled down in just a few operations 

each day to minimize the exposure of workers to the danger of a silage avalanche. A 

large amount of compressed silage is therefore often disturbed to be used over a day or 

more of TMR mixing. While it is apparent from this data that silage should be left 

undisturbed as much as possible to minimize ROG emissions, that may be contrary to 

safe working practices. The emissions from disturbed silage are high; however the 

amount of material and the area of the emission is small compared to other sources. 

The average flux rate for undisturbed silage material shown in Table 10 is about 22% of 

the flux rate from disturbed silage. A typical dairy might have a silage pile with an 

exposed face of 250 m2

 with a loose pile of disturbed silage at its base of only about 25 

m2. The total ROG flux from the silage operation would therefore be primarily due to the 

lower flux from the larger area of undisturbed pile face. A considerable amount of 

additional silage data will be available when the related projects are complete, including 

more flux data, silage analysis and density as well as pile dimensions for each of the six 

dairies. More detailed correlations will be possible with that additional data when the 

comprehensive report is completed. 

28
Table 10. Average flux rates for all dairies, all dates and each dairy operation included 

in the regular sampling program for Year-2. The 6 major constituents of ROG are 

reported here with the remaining components grouped as “other”. The UC Irvine 

analysis included ROG components from a list of 64 gasses identified in the analytical 

procedure. Values are in μg/m2

/minute and are corrected by the subtraction of Field 

Blank values. 

Total ROG

Ethanol

Methanol

AlcoholsAlcohols

Acetaldehyde

d-Lim onene

DMDS

DMS

Other

Open Lot Shallow Manure Pack 102 15 17 45 56% 35 1 0 12 23

Open Lot Deep Manure Pack 243 20 28 60 57% 69 1 0 74 50

Lagoons 36 5 2 7 20% 4 0 0 0 25

Flush Lane (Pre-Flush) 353 22 9 108 47% 20 7 0 12 283

Flush Lane (Post-Flush) 21 3 1 6 53% 0 0 0 0 16

TMR (0.5 h Post Placement) 15,022 11,668 1,460 13,141 86% 336 584 26 831 117

TMR (6 h Post Placement) 10,582 7,747 1,591 9,350 87% 469 557 9 152 55

TMR (6+h Post: consumed) 2,929 2,289 389 2,683 89% 106 102 3 32 9

Silage Pile Undisturbed Face 4,229 3,095 416 3,524 86% 164 6 1 532 16

Silage Pile Disturbed Face 19,170 12,814 632 13,461 84% 214 49 1 5,413 47

A few flux chamber samples were collected from lagoon surfaces for a related project 

funded by the California Dairy Campaign. These lagoon fluxes do not correspond to the 

sampling periods reported above but they are shown in Table 10 and Figure 8 to 

illustrate the relative insignificance of lagoon emission rates compared to other dairy 

sources of ROG. These lagoon emission rates were monitored at Dairies A and D in 

May and November, 2007 to compare with lagoons at three other dairies, not included 

in this CARB study. More complete data related to lagoon emission composition and 

rates will be included in the comprehensive report. 

29
0 5,000 10,000 15,000 20,000 25,000

Open Lot Shallow Manure

Pack

Open Lot Deep Manure Pack

Lagoons

Flush Lane (Pre-Flush)

Flush Lane (Post-Flush)

Total Mixed Ration (0.5 h Post

Placement)

Total Mixed Ration (6 h Post

Placement)

Total Mixed Ration (6+h Post:

consumed)

Silage Pile Vertical

Undisturbed Face

Silage Pile Disturbed Face

ROG flux (μg/m2

/minute)

Figure 8. ROG fluxes averaged from each dairy and sampling date. These data are 

from the Total ROG column of Table 10. 

30
0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

Total Mixed Ration

(0.5 h Post

Placement)

Total Mixed Ration

(6 h Post

Placement)

Total Mixed Ration

(6+h Post:

consumed)

Silage Pile Vertical

Undisturbed Face

Silage Pile Disturbed

Face

flux (μg/m2/minute)

Ethanol Methanol Acetaldehyde d-Limonene DMDS DMS Other

Figure 9. Fluxes of the six prominent, specific ROG components of emissions, 

compared to the minor components (other) from feed and silage. This data is from the 

TMR and Silage lines of Table 10. 

The feeding operation has fluxes nearly comparable to those from silage, as would be 

expected from the fact that silage is the major component of the TMR and the mixing 

process thoroughly disturbs all the components. The data for TMR shown in Table 10 

and Figures 8 and 9 reflects the complexity of TMR fluxes of ROG that were not 

completely understood until the Year-2 program was in progress. It was apparent that 

fluxes from TMR were high when the material was initially placed in the feed bunker. 

Consecutive samples in a related project using the real-time INNOVA analyzers showed 

decreasing flux chamber concentrations for alcohols, minute by minute, over the first 

monitoring period, 30-60 minutes post-placement. Project staff noted the distinctive 

odor from the TMR decreased rapidly from the time of placement. Two factors were 

probably responsible for this decrease in flux. The animals consumed feed and the 

volatility appeared to decrease rapidly as the TMR was spread out and exposed to the 

air. 

This apparent decrease in flux with time was monitored prior to Year-2 by following the 

initial, post-placement sample with another at 1.5 hours, post-placement. The flux 

values for these later samples were lower; about 30% of the initial fluxes. The advisory 

group, after consideration of this data, requested a more thorough evaluation of the 

31
TMR. The group considered TMR to be, potentially, the largest ROG source, and, 

perhaps the most complex, variable and manageable. The Year-2 program included 

samples at each diary for the beginning (0.5 hours) and end (6 hours) of the feeding 

period and, if possible a flux from the surface after the TMR was consumed. The 

averages for that portion of the Year-2 program (Table 5) do not appear to match the 

rapid decrease in flux shown by the earlier 1.5 hour post-placement fluxes. A potential 

reason for this involves an additional practice in the feeding operation. The large 

amount of TMR placed initially in the feed bunker is consumed most rapidly in the first 

hour or two. The cows return to the bunker later to eat the remaining feed. It is a 

common practice to scrape or sweep the remnants of the TMR into a more accessible 

pile about 4 – 6 hours after placement. The 1.5 hour samples in Table 5 were taken 

prior to that sweeping and the 6 hour samples were usually following such a practice. 

The sweeping operation disturbed the material and exposed previously buried TMR to 

the air. The odor of the feed was noticeably stronger after sweeping and the fluxes 

were higher. 

This phenomenon became apparent early in the Year-2 program and had, in fact, been 

anticipated by the advisory group. The emphasis on TMR fluxes included a more 

detailed sampling program at Dairies A and B, referred to as the “special sampling” 

described in Appendix B. While that special sampling was done as part of the related 

projects, some UC Irvine samples were included when there were sufficient canisters. 

Though much of the data for the special samples is not yet available, the UC Irvine 

analysis is shown in graphic form in Figures 6 (ROG) and 7 (total alcohols). The 

continuous sampling from placement to complete consumption of the TMR is shown 

over an 8 hour span. The fluxes at 8 hours are for the bunker surface after complete 

consumption. The spike in flux rate at 6 hours seen in the regular sampling is not as 

apparent in these special samples. Further correlation with additional data may explain 

the reasons for this. 

Flush lane fluxes were originally expected to be the major source of ROG from the 

animal housing areas. In fact, flux rates from flush lanes are less than 5% of the 

average TMR flux when the amount of manure is greatest, prior to flushing. When the 

lanes have been flushed, scraped or vacuumed, the flux rate is less than 0.3% of the 

average TMR rate. The composition of the ROG flux is also different for the flush lanes. 

While the alcohols are still the dominant components, they are about half of the ROG 

from the lanes compared to the 80% - 90%+ alcohols in fluxes from silage and TMR. 

Propanol was a much greater component of the fresh manure in the pre-flush lane 

compared to the other sources. The area of flush lanes in the dairy barn is greater than 

that of the feed bunker by a factor of 5 – 10. The relative fluxes from these two sources 

are therefore, less different than their flux rates would indicate but the flush lanes are 

still significantly smaller sources than the TMR. 

Fluxes of ROG from the open lots, shown in Table 9, are lowest of the four sources 

sampled in this project. The open lots are also the most variable in size, composition, 

pattern of use and management practices. The variability in average flux among the 

dairies was actually less than expected and was comparable to that of the flush lanes. 

32
The composition of the ROG emission was also similar to the flush lanes with some 

notable differences. The alcohols made up about half of the ROG emission as with the 

lanes though ethanol and methanol were responsible for nearly all the alcohols in 

relatively equal proportions in the manure pack of the open lots. Though the flux rates 

are comparably low for the open lots, the larger area increases their significance as an 

ROG source. Some dairies have very large lots (10,000 m2 or more) and some are 

quite small (2000 m2

 or less). The differences in size, coupled with different 

management practices and loading will make estimates of emissions from open lots 

more difficult than the other sources. Additional data and management information will 

be included in the comprehensive report. 

SUMMARY and CONCLUSIONS 

There were three basic questions that led to the original proposal to CARB for this 

project and the subsequent revisions by the advisory group. 

1. What are the components of ROG emissions from dairy operations in California? 

2. What are the most significant sources of ROG related to dairy operations? 

3. Are there procedural and seasonal effects on ROG from California dairies? 

The first question was the first priority since the composition of dairy emissions was 

unknown and needed to be characterized in order to select the appropriate methods of 

sampling and analysis for the Year-2 program. The initial downwind-upwind sampling 

and analysis at UC Irvine was successful in that characterization. The data from those 

first year samples is shown in Appendix A, Table A6. Once the major components and 

their relative concentrations were determined, the analytical procedures at UC Irvine 

could be optimized for dairy air samples and analytical standards could be prepared. 

While there are certainly other VOC’s that might have been present in these samples 

that could react as ozone precursors, it was assumed that all significant components of 

ROG were identified and quantified by Dr. Blake at UC Irvine. The identification of 

alcohols as the major component of ROG emissions from each dairy operation was the 

first significant conclusion of this project. That led to several related projects to monitor 

alcohols with additional methods of sampling and analysis. 

Once the composition of dairy ROG emissions had been determined, the second 

question of identifying the relative magnitude of emissions from the various dairy 

operations could be addressed. The initial downwind-upwind samples that were of such 

value in characterizing the ROG components could not discriminate between the 

separate sources within the animal housing areas and so the advisory group directed 

the sampling program’s change to the use of flux chambers. Fluxes measured by this 

chamber method are specific to the surface and the area on which they are placed for a 

particular sample. Multiple measurements over both time and area are required to 

determine the magnitude and variability of the flux from a surface and the limited 

number of UC Irvine analyses that was available in this project budget was not 

adequate to accomplish this for every sampling location and period. The other 

sampling/analysis methods added for the related projects will be important for the 

further characterization of each location. It is possible, as an academic exercise, to 

33
estimate the relative flux magnitudes with the UC Irvine data reported here and that will 

also serve as an example of the conversion procedures that may be possible with 

additional data in the comprehensive report. 

The flux rate averages in Table 10 can be used to illustrate the calculation of emissions 

to the degree that the relative magnitude of each source can be compared. In the 

discussion of the silage source above, an example was given to illustrate the proportion 

of ROG emissions from disturbed and undisturbed silage. That example can be carried 

further and used for the other sources as well at a fictitious 2000 cow dairy that might be 

imagined from a composite of the six facilities sampled in this project. This fictitious 

dairy has four barns, each 400m long, with a feed bunker, two flush lanes and a large 

open lot. The areas of those sources, combined with the ROG flux rates from Table 10 

can be used to illustrate the relative magnitudes of fluxes from a dairy as well as serve 

as an example of how fluxes can be combined with specific dairy dimensions to 

calculate emissions from a specific facility. 

Disturbed Silage 

Average flux (Table 10) = 19,170 μg/m2

/minute 

Estimated area at the fictitious dairy = 25 m2

Estimated emission = 19,170 μg/m2

/minute X 25 m2 X 1440 min/day = 0.7 kg/day 

Undisturbed Silage 

Average flux (Table 10) = 4,229 μg/m2

/minute 

Estimated area at the fictitious dairy = 250 m2

Estimated emission = 4,229 μg/m2

/minute X 250 m2 X 1440 min/day = 1.5 kg/day 

TMR (average of all sample periods) 

Average flux (Table 10) = 8,260 μg/m2

/minute 

Estimated area at the fictitious dairy = 1600 m2

 (1m wide x 400m long x 4 bunkers) 

Estimated emission = 8,260 μg/m2

/minute X 1600 m2 X 1440 min/day = 19.0 kg/day 

Flush lanes (average of pre-flush and post-flush) 

Average flux (Table 10) = 187 μg/m2

/minute 

Estimated area at the fictitious dairy = 9600 m2

 (3m wide x 400m long x 8 lanes) 

Estimated emission = 187 μg/m2

/minute X 9600 m2 X 1440 min/day = 2.6 kg/day 

Open Lots (average of deep and shallow manure pack) 

Average flux (Table 10) = 172 μg/m2

/minute 

Estimated area at the fictitious dairy = 32,000 m2

 (20m wide x 400m long x 4 lots) 

Estimated emission = 172 μg/m2

/minute X 32,000 m2 X 1440 min/day = 7.9 kg/day 

ROG emissions from the fictitious dairy and their relative percentages of the total: 

Disturbed Silage...... 0.7 kg/day (2%) 

Undisturbed Silage... 1.5 kg/day (5%) 

TMR.................... 19.0 kg/day (60%) 

Flush lanes............. 2.6 kg/day (8%) 

Open Lots.............. 7.9 kg/day (25%) 

Total ....................31.8 kg/day (100%) 

34
This estimation does show the fact that the TMR is the largest ROG source at the dairy 

(60%) followed by the open lots (25%), the flush lanes (8%) and the silage (5% for 

undisturbed and 2% for disturbed material). While these percentages will change for 

specific facilities, TMR is likely to remain the dominant source. There is a considerable 

amount of TMR flux data from the related projects that should produce a more accurate 

average as well as a better evaluation of the variability and relationship to feed 

components and other feeding practices. It is clear that reductions in TMR fluxes have 

the most potential to mitigate dairy emissions of ROG. 

TMR

60%

Silage

(undisturbed)

5%

Silage

(disturbed)

2%

Flush Lanes

8%

Open Lots

25%

Figure 10. An example of the relative ROG source magnitudes at a fictitious dairy. 

These proportional values are calculated from the averaged flux rates for all six dairies 

for all sampling periods in Year-2, multiplied by the averaged areas of those sources for 

the six dairies. These are shown to illustrate the relative magnitude of the ROG sources 

Specific source rates and proportions will be different for different dairies and seasons. 

This example calculation is not intended for use as an emission factor for dairies. The 

dimensions do not represent any specific facility and the fluxes are averages of a 

number of sampling events that have considerable variation. Another factor that must 

be considered is the nature of the flux chamber method. Flux chamber data can be 

35
used to calculate ROG emissions from a surface into the artificial, zero-air atmosphere 

of the chamber, immediately above the surface being sampled. Any atmospheric 

reactions that might occur with a flux into an ambient atmosphere or adhesive effects 

between ROG and surfaces at the dairy are not reflected in these results. Atmospheric 

and surface effects on the ROG components would probably reduce the concentrations 

so these reported flux values are most likely an overestimation of the emissions from 

these operations, especially those that take place in the barn areas. Downwind-upwind 

sampling or other similar monitoring methods would be required to determine the 

differences between the flux from these surfaces as measured by the flux chamber 

method and the actual emissions after the post-surface emission reactions have been 

included. That level of monitoring was beyond the scope of this project but is being 

conducted by other research groups in California and elsewhere. 

Correlation of ROG flux rates with ambient conditions was one of the primary objectives 

of the original proposal. The winter, summer and fall sampling periods were selected to 

evaluate an expected seasonal effect on flux rates for the different dairy locations and 

operations. It was assumed that higher temperature surfaces would volatilize higher 

rates of emissions during warm weather. The only example where this is apparent with 

the data reported here is related to the open lots. Both the shallow and deep manure 

pack locations showed a strong, positive correlation with the temperature of the surface. 

Table A5 in Appendix A shows open lot surface temperatures ranging from 39.5 C down 

to 9.3 C. The higher flux rates were consistently found at the higher surface 

temperatures in both shallow and deep pack areas. Additional emissions and manure 

samples were collected for these areas by the related projects and will be statistically 

evaluated in the comprehensive report. Further data analysis may show other 

correlations with surface or air temperature but the open lots are the only areas where 

the correlation is obvious from the CARB data. 

Recommendations 

Recommendations for further research are, for the most part, related to the additional 

projects that were begun during the course of this study with the additional support from 

CSU ARI and the cooperating researchers described above. Completion of these 

related projects in the next year should significantly expand the data set and provide 

much more detailed conclusions with regard to fluxes of ROG and other gasses. The 

more intensive study of emissions from dairy operations recommended in the Summary 

and Conclusions section are necessary to determine the fate of ROG between emission 

from the source surface as measured by the flux in this study and the point at which the 

ROG is emitted from the dairy facility. Some studies of that nature are in progress and 

more should be encouraged to fully evaluate dairy ROG emissions. 

The speciation of ROG emissions from dairies that was the first objective in this project 

is only the first step in characterizing these sources with regard to their potential 

contribution to ozone formation. These ROG species are different, not only by 

composition but also in their ability to participate in the ozone formation reaction. Some 

36
components may be present in significant amounts but have little effect on ozone 

formation because of a low reactivity. Other ROG’s may be present in smaller amounts 

but be more significant precursors of ozone due to a higher reactivity. A complete 

evaluation of dairy emissions as they affect ozone formation will need to include the 

reactivity of these specific ROG’s as well as their relative emission rates. 

References 

This study, as a data collection project, did not include a literature review in the 

proposal. An extensive review of current research was completed by members of the 

project advisory group as part of the contemporary DPAG activity. Though that review 

of literature was important to the planning and execution of this study, it was not done 

as part of this CARB funded activity and is not reported in this document. 

The Dairy Permitting Advisory Group of the San Joaquin Valley Air Pollution Control 

District completed an extensive review of research related to dairy emissions in 2005, 

as this project was beginning. The public agency and industry members of the 

CARB/CDFA Dairy Sub-committee that became the advisory group for this project were 

also DPAG members. The research members of this project’s advisory group 

participated in the DPAG process as well. The review of research and DPAG 

discussions were integral to the development of this project, especially the revisions to 

focus on ROG emissions, recommended by the advisory group as it progressed. A 

review of research and literature beyond that done for the DPAG report would have 

been superfluous. The DPAG report, with an extensive list of references may be found 

at: 

<http://www.valleyair.org/busind/pto/dpag/DPA_%20EF_Report_Final.pdf> 

List of Inventions and publications produced 

No inventions or patentable processes were developed in the course of this project. No 

publications based on this data have yet been submitted by any of the investigators or 

cooperators. Several publications are expected to be submitted by collaborators and 

cooperators when the related projects are completed and the full data set is available.

37
APPENDIX A 

The following tables list the individual samples collected by CSU Fresno and analyzed 

at UC Irvine that were averaged and summarized in the Results section. Only samples 

with corresponding field blanks are reported here. A small number of other samples 

were analyzed at UC Irvine for the special sampling and related projects but do not 

have UC Irvine field blanks and so cannot be evaluated until other QC data is available. 

38
Table A1. Silage samples from material dislodged from the pile for use in the next TMR 

mix. Values are fluxes in μg/m2

/minute and are corrected by the subtraction of Field 

Blank values. The 6 major components of ROG are reported here. The UC Irvine 

analysis included ROG components from a list of 64 gasses identified in the analytical 

procedure. 

Dairy Date Surface Description Surface 

Temp.

Air 

Temp.

Total ROG

Ethanol

Methanol

Total AlcoholsTotal Alcohols

Acetaldehyde

d-Limonene

DMDS

DMS

A 06/11/07 Silage Pile Disturbed Face 35.3 31.5 8,209 6,564 1,438 8,002 97% 76 49 1 0

A 09/25/07 Silage Pile Disturbed Face 25.3 26.2 17,068 13,471 1,694 15,212 89% 739 63 1 1,042

A 02/08/08 Silage Pile Disturbed Face 22.9 12.1 34,875 23,458 1,286 24,779 71% 509 199 1 9,246

A 06/02/08 Silage Pile Disturbed Face 19.3 20.1 15,919 8,510 1,114 9,634 61% 596 837 1 4,818

B 10/02/07 Silage Pile Disturbed Face 18.6 14 2,823 2,369 348 2,743 97% 64 9 1 10

B 02/19/08 Silage Pile Disturbed Face 28.8 12.6 3,546 3,041 442 3,482 98% 11 1 1 59

B 07/02/08 Silage Pile Disturbed Face 18.9 19.6 2,512 2,265 186 2,451 98% 23 0 1 32

C 06/25/07 Silage Pile Disturbed Face 30.8 27.3 56,107 55,797 46 55,843 100% 184 0 1 0

C 10/30/07 Silage Pile Disturbed Face 31.7 16.8 9,859 8,724 671 9,414 95% 440 5 0 1

C 04/09/08 Silage Pile Disturbed Face 15.2 12.1 6,105 4,145 569 4,757 78% 164 1 1 1,169

C 06/17/08 Silage Pile Disturbed Face 20.7 18.8 72,698 70,645 935 71,591 98% 425 31 1 633

D 10/23/07 Silage Pile Disturbed Face 23.7 16 83 82 5 86 104% 4 0 0 0

D 03/14/08 Silage Pile Disturbed Face 14.6 10.1 8,670 7,776 466 8,251 95% 44 20 1 351

D 06/26/08 Silage Pile Disturbed Face 32.5 24.4 60,816 13,189 1,456 14,707 24% 124 0 7 45,922

D 03/22/07 Silage Pile Disturbed Face 27.8 20 5,103 4,722 304 5,026 98% 0 0 1 55

D 07/24/07 Silage Pile Disturbed Face 39 32 18,425 18,283 62 18,346 100% 32 1 1 1

E 06/20/07 Silage Pile Face disturbed 38.8 24.9 28,187 27,829 48 27,877 99% 50 0 1 0

E 10/16/07 Silage Pile Disturbed Face 21.5 14.1 814 228 451 681 84% 134 0 0 1

E 03/10/08 Silage Pile Disturbed Face 15.4 9.2 16,023 5,857 784 6,656 42% 31 1 1 9,316

E 06/09/08 Silage Pile Disturbed Face 32.7 25.5 10,132 7,846 936 8,801 87% 89 1 1 1,227

F 04/17/07 Silage Pile Disturbed Face 18.8 18.4 1,477 1,274 197 1,471 100% 0 0 1 3

F 07/17/07 Silage Pile Disturbed Face 19.4 22 6,104 6,054 40 6,094 100% 4 0 0 0

F 11/06/07 Silage Pile Disturbed Face 18.2 14.8 4,845 3,321 260 3,581 74% 1,259 0 1 6

F 03/28/08 Silage Pile Disturbed Face 11.2 11.7 12,859 9,336 677 10,026 78% 111 1 1 2,719

F 07/09/08 Silage Pile Disturbed Face 29.5 30.8 75,977 15,572 1,393 17,015 22% 232 0 1 58,710

Dairy Averages

A 25.7 22.5 19,018 13,001 1,383 14,407 80% 480 287 1 3,776

B 22.1 15.4 2,961 2,558 325 2,892 98% 32 3 1 34

C 24.6 18.8 36,192 34,828 555 35,401 93% 303 9 1 451

D 27.5 20.5 18,620 8,810 459 9,283 84% 41 4 2 9,266

E 27.1 18.4 13,789 10,440 555 11,004 78% 76 1 1 2,636

F 19.4 19.5 20,252 7,111 513 7,637 75% 321 0 1 12,287

39
Table A2. Silage samples from undisturbed material. Values are fluxes in 

μg/m2

/minute and are corrected by the subtraction of Field Blank values. The 6 major 

components of ROG are reported here. The UC Irvine analysis included ROG 

components from a list of 64 gasses identified in the analytical procedure. 

Dairy Date Surface Description Surface 

Temp.

Air 

Temp.

Total ROG

Ethanol

Methanol

Total AlcoholsTotal Alcohols

Acetaldehyde

d-Limonene

DMDS

DMS

A 09/25/07 Silage Pile Vertical Undisturbed Face 27.3 25 5,426 4,256 858 5,133 95% 265 3 1 22

A 02/08/08 Silage Pile Vertical Undisturbed Face 32.9 15 6,811 4,539 663 5,234 77% 304 13 0 1,248

A 06/02/08 Silage Pile Vertical Undisturbed Face 20.7 24.2 2,305 1,931 198 2,133 93% 8 15 0 143

B 02/19/08 Silage Pile Vertical Undisturbed Face 23.9 13.4 5,442 4,055 337 4,391 81% 9 2 1 1,046

B 07/02/08 Silage Pile Vertical Undisturbed Face 20.4 21.5 5,713 5,026 228 5,255 92% 23 0 1 431

C 10/30/07 Silage Pile Vertical Undisturbed Face 26.8 17.2 2,090 1,591 234 1,832 88% 247 8 0 3

C 04/09/08 Silage Pile Vertical Undisturbed Face 24.6 13.8 9,729 6,271 968 7,249 75% 88 3 1 2,361

C 06/17/08 Silage Pile Vertical Undisturbed Face 20.1 20.6 4,286 2,954 285 3,238 76% 121 5 1 921

D 10/23/07 Silage Pile Vertical Undisturbed Face 40.2 21.4 8,713 6,029 1,194 7,345 84% 1,322 35 0 4

D 03/14/08 Silage Pile Vertical Undisturbed Face 12.2 12 3,536 2,849 201 3,050 86% 9 2 1 474

E 10/16/07 Silage Pile Vertical Undisturbed Face 15.8 14 1,668 1,404 219 1,625 97% 33 0 0 9

E 03/10/08 Silage Pile Vertical Undisturbed Face 19.9 11.5 2,442 1,966 282 2,251 92% 15 3 1 168

E 06/09/08 Silage Pile Vertical Undisturbed Face 28.9 25 3,798 2,022 380 2,406 63% 24 2 0 1,362

F 11/06/07 Silage Pile Vertical Undisturbed Face 17.4 17.3 1,251 953 164 1,118 89% 132 0 1 2

F 03/28/08 Silage Pile Vertical Undisturbed Face 13 13.1 1,971 1,699 159 1,858 94% 2 1 1 108

F 07/09/08 Silage Pile Vertical Undisturbed Face 29.4 31.7 2,492 1,973 285 2,258 91% 25 0 1 207

Dairy Averages

A 27.0 21.4 4,848 3,575 573 4,167 88% 192 11 1 471

B 22.2 17.5 5,577 4,540 282 4,823 86% 16 1 1 738

C 23.8 17.2 5,368 3,605 496 4,107 79% 152 5 1 1,095

D 26.2 16.7 6,124 4,439 697 5,198 85% 665 18 0 239

E 21.5 16.8 2,636 1,798 294 2,094 84% 24 2 0 513

F 19.9 20.7 1,905 1,542 203 1,745 91% 53 0 1 106

40
Table A3. Individual samples of feed (TMR) fluxes. Values are in μg/m2

/minute and 

are corrected by the subtraction of Field Blank values. 

Dairy a

t

e

Surface Description Surface 

Temp.

Air 

Temp.

Total ROG

Ethanol

Metanol

Total AlcoholsTotal Alcohols

Acetaldehyde

d-Limonene

DMDS

DMS

A Total Mixed Ration (0.5 h Post Placement) 10,561 4,634 3,028 7,662 73% 29 2,747 16 0

A Total Mixed Ration (1.5 h Post Placement) 6,994 2,736 1,810 4,547 65% 33 2,288 18 0

A Total Mixed Ration (0.5 h Post Placement) 25.9 18.8 12,148 6,699 2,527 9,257 76% 1,178 1,650 1 4

A Total Mixed Ration (6 h Post Placement) 23.2 26.4 13,269 6,927 3,076 10,030 76% 1,313 1,825 0 4

A Total Mixed Ration (6+h Post: consumed) 22.5 27 2,488 1,338 796 2,140 86% 77 266 0 1

A Total Mixed Ration (0.5 h Post Placement) 19.2 10 10,250 4,293 2,485 6,812 66% 146 2,478 41 543

A Total Mixed Ration (6 h Post Placement) 13.6 15 6,620 2,765 1,919 4,705 71% 69 1,649 12 80

A Total Mixed Ration (6+h Post: consumed) 7.7 5.6 1,200 799 255 1,056 88% 83 45 1 11

A Total Mixed Ration (0.5 h Post Placement) 24.2 19.6 32,477 22,553 5,073 27,637 85% 268 3,722 32 591

A Total Mixed Ration (6 h Post Placement) 22 23.7 16,390 11,648 2,302 13,955 85% 251 2,053 7 55

A Total Mixed Ration (6+h Post: consumed) 18.4 17.5 6,069 3,951 1,281 5,233 86% 190 615 3 18

B Total Mixed Ration (1.5 h Post Placement) 3,114 2,384 646 3,029 97% 0 0 1 63

B Wet Distillers Grain 13.9 12 830 804 17 821 99% 0 0 0 7

B Total Mixed Ration (0.5 h Post Placement) 22 23 8,309 7,875 225 8,100 97% 46 1 101 0

B Total Mixed Ration (1.5 h Post Placement) 23.5 24.4 2,692 2,530 76 2,607 97% 17 0 37 0

B Total Mixed Ration (0.5 h Post Placement) 24.1 20.1 7,532 5,319 1,088 6,440 86% 1,017 0 0 34

B Total Mixed Ration (6 h Post Placement) 26.8 26.3 7,054 3,543 1,347 4,906 70% 2,091 0 1 22

B Total Mixed Ration (6+h Post: consumed) 21 24.2 681 471 142 613 90% 52 14 0 0

B Total Mixed Ration (0.5 h Post Placement) 24.2 13.1 12,770 7,248 2,898 10,171 80% 56 0 44 2,329

B Total Mixed Ration (6 h Post Placement) 10.8 9.8 1,380 856 480 1,338 97% 23 0 1 14

B Total Mixed Ration (6+h Post: consumed) 9.7 8.8 207 137 63 201 97% 4 0 0 0

B Total Mixed Ration (0.5 h Post Placement) 26.5 26.6 20,125 8,515 3,619 12,134 60% 317 3 152 7,336

B Total Mixed Ration (6 h Post Placement) 24.5 29.2 34,254 27,030 6,025 33,067 97% 372 2 57 711

B Total Mixed Ration (6+h Post: consumed) 24.2 29.8 507 399 77 477 94% 0 0 2 27

C Total Mixed Ration (0.5 h Post Placement) 26.2 11.8 14,327 12,956 691 13,656 95% 503 108 1 2

C Total Mixed Ration (6 h Post Placement) 20.1 19 8,512 6,970 862 7,838 92% 630 0 0 1

C Total Mixed Ration (6+h Post: consumed) 17.6 18.4 2,060 1,575 226 1,800 87% 253 0 0 1

C Total Mixed Ration (0.5 h Post Placement) 13.5 8.9 30,432 27,745 1,042 28,798 95% 630 55 29 790

C Total Mixed Ration (6 h Post Placement) 16.3 16.7 5,040 4,210 502 4,714 94% 288 8 3 15

C Total Mixed Ration (6+h Post: consumed) 14.6 16 3,704 3,408 221 3,631 98% 58 7 2 4

C Total Mixed Ration (0.5 h Post Placement) 19.5 16.3 46,515 45,350 666 46,024 99% 199 5 3 259

C Total Mixed Ration (6 h Post Placement) 20.6 23.4 26,376 24,542 967 25,517 97% 238 26 16 562

C Total Mixed Ration (6+h Post: consumed) 21.4 22.5 2,974 2,629 240 2,871 97% 24 28 2 48

D Total Mixed Ration (0.5 h Post Placement) 20.7 28.1 8,598 6,390 1,100 7,551 88% 965 53 0 2

D Total Mixed Ration (6 h Post Placement) 17.9 24.5 16,483 9,964 2,313 12,324 75% 2,183 1,883 0 2

D Total Mixed Ration (6+h Post: consumed) 20.1 25.5 2,893 1,568 517 2,091 72% 386 407 0 1

D Total Mixed Ration (0.5 h Post Placement) 14.9 10.8 14,446 7,495 1,812 9,318 64% 217 3,883 10 423

D Total Mixed Ration (6 h Post Placement) 14.6 14.6 9,022 4,433 1,668 6,107 68% 124 2,564 3 41

D Total Mixed Ration (6+h Post: consumed) 15.1 15.3 1,821 1,061 301 1,363 75% 22 410 1 16

D Total Mixed Ration (0.5 h Post Placement) 28.2 20.4 35,275 31,263 2,340 33,629 95% 140 0 33 1,424

D Total Mixed Ration (6 h Post Placement) 26.7 24.8 20,460 17,922 1,795 19,732 96% 146 0 32 506

D Total Mixed Ration (6+h Post: consumed) 25.3 25.2 22,859 20,289 1,972 22,276 97% 237 32 29 270

D Total Mixed Ration (0.5 h Post Placement) 30.5 10.6 6,380 5,765 471 6,236 98% 0 21 1 40

D Total Mixed Ration (1.5 h Post Placement) 21.4 14.2 3,720 3,333 322 3,655 98% 0 0 0 39

D Total Mixed Ration (1.5 h Post Placement) 21.4 14.2 3,702 3,313 321 3,634 98% 0 0 1 41

D Total Mixed Ration (1.5 h Post Placement) 21.4 14.2 4,415 3,840 520 4,360 99% 0 21 1 4

D Total Mixed Ration (0.5 h Post Placement) 33.3 24.1 3,001 2,738 0 2,738 91% 24 12 1 0

D Total Mixed Ration (1.5 h Post Placement) 28.4 30.9 3,742 3,589 90 3,679 98% 9 4 1 0

E Total Mixed Ration (0.5 h Post Placement) 23.4 16.9 10,716 10,450 28 10,478 98% 38 0 89 0

E Total Mixed Ration (1.5 h Post Placement) 21.6 21 7,282 7,105 50 7,155 98% 26 0 42 0

E Total Mixed Ration (0.5 h Post Placement) 24.1 20.2 16,237 14,264 710 14,987 92% 1,208 0 1 26

E Total Mixed Ration (6 h Post Placement) 17.6 18.5 2,672 2,507 112 2,622 98% 46 0 0 1

E Total Mixed Ration (6+h Post: consumed) 16.8 17.2 1,730 1,286 40 1,326 77% 402 0 0 0

E Total Mixed Ration (6+h Post: consumed) 16.8 17.2 1,416 1,047 122 1,170 83% 244 0 0 2

E Total Mixed Ration (0.5 h Post Placement) 19.5 21 3,287 2,358 617 2,986 91% 52 0 8 111

E Total Mixed Ration (6 h Post Placement) 15.4 15.3 1,683 1,025 494 1,520 90% 30 3 3 116

E Total Mixed Ration (6+h Post: consumed) 15.2 15.3 1,476 967 466 1,436 97% 11 5 2 21

E Total Mixed Ration (0.5 h Post Placement) 20.2 21.3 12,275 6,007 1,373 7,397 60% 50 13 17 4,784

E Total Mixed Ration (6 h Post Placement) 22.2 28.6 7,179 4,829 1,753 6,599 92% 40 7 18 502

E Total Mixed Ration (6+h Post: consumed) 23.5 27.9 851 500 207 708 83% 5 7 8 122

F Total Mixed Ration (0.5 h Post Placement) 20.6 13.9 1,901 1,493 308 1,800 95% 0 0 1 84

F Total Mixed Ration (1.5 h Post Placement) 19.1 16.9 1,533 1,166 347 1,513 99% 0 0 1 12

F Wet Distillers Grain 42.4 22.5 1,191 1,155 22 1,177 99% 0 0 6 2

F Total Mixed Ration (0.5 h Post Placement) 19.8 18.6 6,137 5,956 141 6,096 99% 19 1 3 0

F Total Mixed Ration (1.5 h Post Placement) 21 20.8 1,385 1,145 53 1,198 86% 5 0 174 0

F Total Mixed Ration (0.5 h Post Placement) 27.1 11.9 5,290 3,817 747 4,577 87% 698 0 2 6

F Total Mixed Ration (6 h Post Placement) 17.5 20.4 2,474 1,569 488 2,064 83% 407 0 1 1

F Total Mixed Ration (6+h Post: consumed) 18.7 21.1 309 236 61 298 96% 11 0 0 0

41
Table A4. Individual flush lane fluxes. The high value for Dairy A on 1/15/08 may be a 

sampling or analytical error (see text). The averages for each dairy are calculated both 

with and without that date. Values are in μg/m2

/minute and are corrected by the 

subtraction of Field Blank values. 

Dairy Date Surface Description Surface 

Temp.

Air 

Temp.

Total ROG

Ethanol

Methanol

Total AlcoholsTotal Alcohols

Acetaldehyde

d-Limonene

DMDS

DMS

A 6/14/2007 Flush Lane (Pre-Flush) 22.9 22.9 45 5 6 16 35% 24 0 0 1

A 2/15/2008 Flush Lane (Pre-Flush)? 8.2 4.5 3,722 238 14 1,025 28% 171 28 0 203

A 6/3/2008 Flush Lane (Pre-Flush)? 17.1 15.6 438 41 5 81 19% 7 2 0 8

B 4/10/2007 Flush Lane (Pre-Flush) 14.9 13.9 40 6 0 14 35% 1 0 0 0

B 7/12/2007 Flush Lane (Pre-Flush) 19.9 19.8 54 10 28 52 97% 0 0 0 0

B 10/4/2007 Flush Lane (Pre-Flush)? 14.9 19.3 26 8 3 11 43% 0 12 0 0

B 3/5/2008 Flush Lane (Pre-Flush)? 11.7 9.2 216 16 3 140 65% 6 4 0 5

B 7/3/2008 Flush Lane (Pre-Flush)? 21.6 27.6 893 24 9 110 12% 5 3 0 8

C 7/3/2007 Flush Lane (Pre-Flush) 23 20.9 164 0 0 12 7% 136 0 0 7

C 11/1/2007 Flush Lane (Pre-Flush)? 15 14.7 97 14 3 78 81% 4 13 0 0

C 4/4/2008 Flush Lane (Pre-Flush) 14 19 102 9 0 55 54% 2 1 0

C 6/16/2008 Flush Lane (Pre-Flush)? 18.7 20.5 735 16 0 86 12% 11 2 0 1

D 10/24/2007 Flush Lane (Pre-Flush)? 17.8 25 77 7 17 59 76% 4 13 0 0

D 3/11/2008 Flush Lane (Pre-Flush)? 13.4 14.2 234 23 66 167 71% 3 2 0 0

D 3/20/2007 Flush Lane (Pre-Flush) 17 17.6 36 6 5 25 68% 0 0 0 0

E 6/21/2007 Flush Lane (Post-Flush) 103 0 2 28 27% 69 1 0 4

E 10/18/2007 Flush Lane (Pre-Flush) 14.4 15.3 175 10 1 110 63% 0 64 0 0

E 3/7/2008 Flush Lane (Pre-Flush)? 11.8 9.9 168 12 11 75 45% 1 3 0

E 6/10/2008 Flush Lane (Pre-Flush)? 19.6 22.1 279 14 5 46 16% 3 2 0 7

F 7/19/2007 Flush Lane (Pre-Flush) 21.2 20.2 88 1 2 78 88% 2 0 0 0

F 11/8/2007 Flush Lane (Pre-Flush) 17.3 20 162 20 4 130 80% 9 17 0 0

F 3/24/2008 Flush Lane (Pre-Flush)? 16.5 15.8 175 14 4 66 38% 4 2 0 1

F 7/10/2008 Flush Lane (Pre-Flush)? 26.3 26.2 93 12 13 25 27% 1 0 0 6

D 10/24/2007 Flush Lane (Post-Flush) 14.4 21.1 8 3 3 6 82% 0 1 0

D 3/22/2007 Flush Lane (Post-Flush) 13 13.8 2 1 0 1 56% 0 0 0

F 4/24/2007 Flush Lane (Post-Scrape) 11.3 12.4 53 5 0 10 19% 0 0 0 1

Average of each dairy

Flush Lane (Pre-Flush) 17.1 17.9 353 22 9 108 47% 20 7 0 12

Flush Lane (Post-Flush) 12.9 15.8 21 3 1 6 53% 0 0 0 0

A 16.1 14.3 1,402 95 8 374 27% 67 10 0 71

B 16.6 18.0 246 13 9 66 51% 2 4 0 3

C 17.7 18.8 275 9 1 58 38% 38 4 0 5

D 16.1 18.9 116 12 29 83 72% 2 5 0

E 15.3 15.8 181 9 5 65 38% 18 17 0 3

F 20.3 20.6 129 12 6 75 58% 4 5 0 2

Average of each dairy with Dairy A 2/15/08 deleted

Flush Lane (Pre-Flush) 17.1 17.9 241 22 9 108 47% 20 7 0 12

Flush Lane (Post-Flush) 12.9 15.8 21 3 1 6 53% 0 0 0 0

A 16.1 14.3 207 12 9 69 27% 13 7 0 3

B 16.6 18.0 246 13 9 66 51% 2 4 0 3

C 17.7 18.8 275 9 1 58 38% 38 4 0 5

D 16.1 18.9 116 12 29 83 72% 2 5 0

E 15.3 15.8 181 9 5 65 38% 18 17 0 3

F 20.3 20.6 129 12 6 75 58% 4 5 0 2

1

3

1

0

0

0

0

42
Table A5. Open lot, exercise pen and corral fluxes. Values are in μg/m2

/minute and 

are corrected by the subtraction of Field Blank values. 

Dairy Date Surface Description Surface 

Temp.

Air 

Temp.

Total ROG

Ethanol

Methanol

Total AlcoholsTotal Alcohols

Acetaldehyde

d-Limonene

DMDS

DMS

A 06/14/07 Open Lot/Corral (Shallow Manure Pack) 36.5 30.6 243 24 38 65 27% 134 0 0 3

A 09/27/07 Open Lot Shallow Manure Pack 17.2 17.2 38 16 17 34 89% 0 0 0 0

A 02/15/08 Open Lot Shallow Manure Pack 19.0 14.5 36 5 15 21 59% 1 0 0

A 06/03/08 Open Lot Shallow Manure Pack 30.9 22.8 119 17 9 99 84% 3 2 0 8

B 04/10/07 Open Lot/Corral (Shallow Manure Pack) 20.3 15.3 6 4 0 5 78% 0 0 0

B 07/12/07 Open Lot/Corral (Shallow Manure Pack) 31.5 25.5 131 11 14 27 20% 70 0 0 3

B 10/04/07 Open Lot Deep Manure Pack 13.4 13.4 41 25 10 35 84% 5 1 0 0

B 03/05/08 Open Lot Shallow Manure Pack 12.7 10.6 30 4 10 20 66% 1 0 0

B 07/03/08 Open Lot Shallow Manure Pack 39.5 40.2 105 33 26 60 57% 5 0 0 2

C 07/03/07 Open Lot/Corral (Shallow Manure Pack) 38.2 31.2 58 0 5 14 25% 40 0 0 4

C 04/04/08 Open Lot Shallow Manure Pack 23.9 24.4 60 16 31 47 78% 4 1 0 4

C 06/16/08 Open Lot Shallow Manure Pack 33.9 23.5 107 18 28 81 76% 8 2 0

D 10/24/07 Open Lot Deep Manure Pack 16.2 15.1 72 34 30 65 90% 3 3 0 0

D 03/11/08 Open Lot Shallow Manure Pack 16.1 15.2 25 6 14 20 83% 1 0 0

D 06/25/08 Open Lot Shallow Manure Pack 31.0 24.8 378 64 0 212 56% 13 4 0 33

D 07/26/07 Open Lot/Corral (Shallow Manure Pack) 32.4 30.0 125 1 0 1 1% 115 0 0 0

E 06/21/07 Open Lot/Corral (Shallow Manure Pack) 25.4 20.8 501 1 56 57 11% 363 0 0 80

E 10/18/07 Open Lot Shallow Manure Pack 18.3 14.0 57 10 45 55 96% 1 0 0 0

E 03/07/08 Open Lot Shallow Manure Pack 22.7 20.3 14 3 0 3 20% 1 0 0

E 06/10/08 Open Lot Shallow Manure Pack 36.2 27.2 95 19 19 53 55% 15 4 0 13

F 04/24/07 Open Lot/Corral (Shallow Manure Pack) 24.0 18.0 2 0 0 0 0% 0 0 0 0

F 11/08/07 Open Lot Deep Manure Pack 20.3 14.4 16 6 7 13 81% 0 2 0 0

F 03/24/08 Open Lot Shallow Manure Pack 19.3 15.0 91 18 15 48 52% 11 1 0 21

A 06/14/07 Open Lot/Corral (Deep Manure Pack) 28.9 22.7 180 22 28 52 29% 111 0 0 1

A 09/27/07 Open Lot Deep Manure Pack 16.5 14.4 20 4 14 18 91% 0 0 0

A 02/15/08 Open Lot Deep Manure Pack 17.5 14.2 73 11 31 46 62% 2 0 0 5

A 06/03/08 Open Lot Deep Manure Pack 24.0 21.4 93 31 27 58 63% 6 1 0 6

B 04/10/07 Open Lot/Corral (Deep Manure Pack) 24.5 22.4 22 14 0 14 62% 0 0 0 5

B 07/12/07 Open Lot/Corral (Deep Manure Pack) 24.2 21.8 29 10 15 26 89% 0 0 0 0

B 10/04/07 Open Lot Deep Manure Pack 21.0 22.9 41 19 14 33 81% 4 2 0 0

B 03/05/08 Open Lot Deep Manure Pack 9.3 9.2 22 2 6 12 53% 1 0 0 4

B 07/03/08 Open Lot Deep Manure Pack 30.3 28.5 942 62 90 176 19% 17 2 0 17

C 07/03/07 Open Lot/Corral (Deep Manure Pack) 35.2 26.8 141 0 15 26 18% 93 0 0 17

C 06/16/08 Open Lot Deep Manure Pack 37.0 22.8 113 30 23 76 68% 12 3 0

D 10/24/07 Open Lot Deep Manure Pack 16.2 15.1 86 40 36 76 88% 6 3 0 0

D 03/11/08 Open Lot Deep Manure Pack 14.6 12.2 62 8 10 58 93% 1 1 0

D 06/25/08 Open Lot Deep Manure Pack 35.1 24.2 327 54 0 69 21% 18 4 0 2

D 07/26/07 Open Lot/Corral (Deep Manure Pack) 26.3 26.6 220 21 42 85 39% 84 0 0 4

E 06/21/07 Open Lot/Corral (Deep Manure Pack) 33.8 30.2 1,132 2 74 76 7% 517 0 0 537

E 06/21/07 Open Lot/Corral (Deep Manure Pack) 36.0 30.2 1,657 2 87 89 5% 734 0 0 831

E 10/18/07 Open Lot Deep Manure Pack 11.9 10.6 61 9 50 59 97% 1 0 0

E 03/07/08 Open Lot Deep Manure Pack 21.6 19.9 99 13 11 67 68% 8 2 0 5

E 06/10/08 Open Lot Deep Manure Pack 29.7 27.2 129 27 25 82 63% 8 2 0 2

F 04/24/07 Open Lot/Corral (Deep Manure Pack) 17 6 0 6 35% 0 0 0

F 11/08/07 Open Lot Deep Manure Pack 20.0 20.0 57 23 27 51 90% 3 1 0 0

F 03/24/08 Open Lot Deep Manure Pack 16.3 12.2 112 48 16 68 61% 13 1 0 2

F 07/10/08 Open Lot Deep Manure Pack 31.4 29.5 197 32 31 109 56% 16 4 0 5

8

5

0

3

7

0

6

1

3

3

0

4

5

2

0

6

1

5

5

3

0

43
Table A6. Ambient samples taken prior to July, 2007. Values are concentrations 

(ppmV for Methane, ppbV for CO and pptV for all others). Samples were to be collected 

in canisters over a 5 minute period after 30 minutes of a consistent wind direction. Most 

samples reported did not meet these minimum modeling criteria. The number of 

samples collected for each category is shown in parentheses. 

VOC common name mol.wt. Conc. Upwind (19) Animals (22) Lagoon (14) Digester (4)

Methane (ppmv) Methane 16.04 ppmV 6.7 4.3 6.0 186.6

CO (PPBV) Carbon Monoxide 28.01 ppbV 881.8 180.7 453.0 199.0

Methanol (B) Methanol 32.04 pptV 229,649.3 15,298.0 145,152.9 6,612.8

Ethanol (B) Ethanol 46.07 pptV 2,730,499.5 57,571.5 544,337.1 8,333.3

Acetone (MS) Acetone 58.08 pptV 26,759.8 7,497.5 5,260.6 3,162.0

D-Limonene (B) D-Limonene 136.24 pptV 2,209.7 1,378.2 3,033.8 55.0

OCS (MS) Carbonyl Sulfide 60.07 pptV 887.8 610.0 553.1 594.0

DMS (MS) Dimethylsulfide 62.14 pptV 3,280.2 691.4 887.3 1,142.8

CFC-12 (C/D/MS) Dichlorodifluoromethane 120.91 pptV 530.5 547.5 517.2 569.0

CS2 (MS) Carbon Disulfide 76.14 pptV 18.6 42.8 57.7 71.0

CFC-11 (C/D/MS) Trichlorofluoromethane 137.38 pptV 254.1 285.5 252.9 285.8

CFC-113 (MS) Ethane, 1,1,2-trichloro-1,2,2-trifluoro- 187.37 pptV 76.3 84.1 75.9 83.3

CFC-114 (C/MS) 1,2-Dichloro-1,1,2,2-tetrafluoroethane 170.92 pptV 14.1 15.7 14.3 15.5

H-1211 (C/D/MS) hexadecane 226.45 pptV 4.8 5.1 4.9 5.3

HCFC-141b (MS) 1,1-dichloro-1-fluoroethane 116.95 pptV 21.2 28.0 22.3 26.0

HCFC-142b (MS) 1-Chloro-1,1-difluoroethane 100.50 pptV 21.1 23.2 19.3 27.0

HCFC-22 (MS) chlorodifluoromethane 86.47 pptV 308.7 406.6 266.0 489.0

HFC-134a (MS) hafnium carbide 190.50 pptV 75.8 85.2 85.2 76.5

C2Cl4 (C/D/MS) Tetrachloroethylene 165.83 pptV 61.6 62.5 89.6 22.0

C2HCl3 (D/MS) Trichloroethylene 131.39 pptV 4.2 4.5 5.4 5.0

CCl4 (C/MS) Carbon tetrachloride 153.82 pptV 91.3 101.4 93.7 102.8

CH2Br2 (D) Methane, dibromo- 173.83 pptV 0.4 0.4 0.4 0.3

CH2Cl2 (MS) Methylene chloride 84.93 pptV 50.4 77.0 53.6 68.5

CH3 Br (MS) Methyl bromide 94.94 pptV 28.4 29.0 23.7 23.3

CH3CCl3 (C/MS) Ethane, 1,1,1-trichloro- 133.40 pptV 16.9 19.2 16.9 18.5

CH3Cl (MS) Methyl chloride 50.49 pptV 718.2 942.9 832.7 771.0

CH3I (C/MS) Methyl iodide 141.94 pptV 2.1 1.3 2.5 1.0

CHBr3 (C/MS) Methane, tribromo- 252.73 pptV 0.8 1.1 0.9 0.7

CHCl3 (MS) Chloroform 119.38 pptV 20.9 17.4 15.4 16.0

MeONO2 (C/D) Methyl nitrate 77.04 pptV 20.0 6.4 9.9 5.8

EtONO2 (C/D) 92.00 pptV 16.9 3.7 5.3 4.3

i-PrONO2 (C/D) 104.00 pptV 19.1 11.7 18.8 17.6

n-PrONO2 (D) 104.00 pptV 1.8 1.1 1.5 2.0

2-BuONO2 (C/D) 114.00 pptV 10.1 7.2 9.4 9.4

2-PeONO2 (C/D) 124.00 pptV 3.7 3.0 3.3 3.7

3-PeONO2 (C/D) 124.00 pptV 2.8 2.3 2.3 2.9

Propane (B/E) Propane 44.10 pptV 1,658.7 1,292.1 1,798.4 12,603.8

Propene (B/E) Propene 42.08 pptV 192.1 167.2 1,609.4 813.5

Ethane (E) Ethane 30.07 pptV 2,174.7 1,523.5 2,066.9 3,373.0

Ethene (E) Ethene 28.05 pptV 403.4 719.6 2,539.9 2,722.8

Ethyne (E) Acetylene 26.04 pptV 382.9 401.5 383.7 630.5

n-Butane (B/E) Butane 58.12 pptV 162.9 203.6 417.6 233.8

i-Butane (B/E) Isobutane 58.12 pptV 199.2 171.5 509.6 262.8

1,3-Butadiene (B) Butadiene 54.09 pptV 0.6 0.0 0.0 0.0

1-Butene (E) 1-Butene 56.11 pptV 2.1 6.6 5.6 0.0

trans-2-Butene (B) 2-Butene-trans 56.11 pptV 0.7 0.0 0.0 0.0

n-Pentane (E) Pentane 72.15 pptV 120.2 166.3 129.7 152.8

i-Pentane (E) 72.00 pptV 206.7 390.0 292.1 299.5

n-Hexane (B/E/MS) Hexane 86.18 pptV 100.9 290.5 391.5 81.0

Benzene (MS) Benzene 78.11 pptV 86.3 109.7 110.6 97.0

Isoprene (MS) Isoprene 68.12 pptV 150.5 77.2 73.1 58.0

Toluene (MS) pptV 122.9 220.3 161.2 156.3

o-Ethyltoluene (MS) 2-Ethyltoluene 120.19 pptV 34.8 105.0 59.1 7.3

m-Ethyltoluene (MS) 3-Ethyltoluene 120.19 pptV 47.0 157.1 58.4 11.0

Ethylbenzene (MS) Ethyl Benzene 106.17 pptV 118.4 441.9 131.1 54.0

2-Methylpentane (B) 2-Methylpentane 86.18 pptV 136.6 154.8 171.4 77.3

3-Methylpentane (B) 3-Methylpentane 86.18 pptV 119.4 99.1 103.6 12.5

alpha Pinene (MS) alpha Pinene 136.24 pptV 21.7 103.5 25.4 6.5

beta Pinene (MS) beta Pinene 136.24 pptV 4.1 95.3 13.8 6.3

m-Xylene (MS) m-Xylene 106.17 pptV 46.1 152.7 63.1 25.5

p-Xylene (MS) p-Xylene 106.17 pptV 46.0 152.5 63.4 25.0

o-Xylene (MS) o-Xylene 106.17 pptV 16.6 62.4 22.9 6.3

1,2,4-Trimethylbenzene (M1,2,4-Trimethylbenzene 120.19 pptV 88.2 314.7 124.4 22.8

1,3,5-Trimethylbenzene (M1,3,5-Trimethylbenzene 120.19 pptV 4.2 22.1 9.9 0.0

44
APPENDIX B 

This appendix is the report submitted October 1, 2007 to CARB for the Year-1 progress 

report. In order to comply with Task 4, a draft was prepared in April, 2007 and 

submitted to the project’s advisory group to begin the process of finalizing the Year-2 

sampling and analysis program for not only the CARB project but also the other, related 

monitoring programs for nitrogen compounds, alcohols and feed components. The 

report is included here in its original form as a reference for the development of the 

Year-2 monitoring program to collect the data used for this final project report. 

Data in the figures and tables of appendix B were from the initial year of the project and 

were superseded by Year-2 data reported above. These data were used primarily to 

validate various sampling methods and did not include all the field and media blanks 

collected to correct Year-2 results. While much of the Year-1 results are sufficiently 

similar to the final results to add credibility to the conclusions, no data from Year-1, 

reported below, was referred to in the final report nor should it be used to draw 

conclusions regarding dairy emission rates. 

45
Progress Report: January 1 to March 31, 2007 

(Includes summary of results from Year 1) 

Dairy Operations: An Evaluation and Comparison of Baseline and Potential 

Mitigation Practices 

for Emissions Reductions In the San Joaquin Valley 

Principal Investigator: 

Dr. Charles Krauter 

California State University Fresno 

Co-Principal Investigator: 

Dr. Donald Blake 

University of California Irvine 

California Air Resources Board Contract No. 04-343 

Project to be administered as CSU Fresno Foundation Project #37411 

The statements and conclusions in this report are those of the Contractor and not 

necessarily those of the California Air Resources Board. The mention of commercial 

products, their source, or their use in connection with material herein is not to be construed 

as actual or implied endorsement of such products. 

1. Narrative account of project tasks completed or partially completed during report 

period: 

The activity covered by this contract period was primarily focused on completing the Year-1 

tasks and developing the sampling and analytical program to be used for Year-2 sampling. The 

primary sampling procedure, as described in the proposal, was the collection of upwind and 

simultaneous downwind samples at each dairy for each sampling period. The wind conditions 

required for this canister sampling were not present for some of the fall and most of the winter 

attempts. The problems and proposed changes in the protocol for Year-2 will be discussed in 

detail below. The additional sampling with flux chambers was very successful and, combined 

with additional analytical methods supported by the supplemental funding from CSU-ARI, has 

filled the data gaps in the ambient sampling program very well. In fact, as discussed below, we 

are proposing to shift the emphasis to the flux chamber sampling and continue the ambient 

sample collection only when the wind conditions are suitable for sampling and modeling of the 

results. 

Summaries of the data collected by both ambient and flux chamber sampling and analyzed by 

Dr. Blake’s lab at UCI as well as the real-time monitoring and in-house analysis done at CSU 

Fresno are attached to this report. A revised Year-2 sampling program is also attached for 

review prior to discussion with the advisory group and adoption for the early summer sampling 

period (Task 4). The Year-2 monitoring program (Task 5) is scheduled to start late May, 2007. 

2. Problems encountered during report period and their resolution: 

The primary problem encountered during the initial year of field monitoring was the difficulty in 

collecting upwind and downwind ambient samples under conditions that would allow modeling 

46
of the results to calculate flux rates. Minimum wind conditions were initially determined to be a 

wind speed of at least 1 meter/second and a wind direction within 20 degrees of the mean for a 

period of at least 2 hours. That proved to be nearly impossible to achieve except for a few times 

in April and May. It was particularly difficult to find during the evening hours and for the 

dairies located south of Fresno. A revision of the “minimum wind conditions” was devised to 

reduce the time to 30 minutes at the end of which the canisters would be filled over a 5 minute 

period. It was determined that the upwind sample air would reach the downwind locations in 5 

minutes or less at the minimum wind speed of 1 meter/second so those became the minimal 

sampling conditions. All the data reported for the ambient sampling in the attached summary 

was collected under these revised sampling limits. The expense and effort required to analyze a 

canister made it necessary to limit the sampling to those times when wind conditions would 

enable the results to be considered significant and for modeling to be possible. Less than half of 

the fall sampling and none of the planned winter ambient sampling was accomplished because 

minimal wind conditions were not present. It should be noted that the successful use of the flux 

chambers and the addition of the INNOVA gas analyzer were being developed at the same time 

the problems with ambient sampling was occurring. It became evident that the flux chamber 

method would provide more specific source sampling and was not subject to the wind 

requirements and so was a much better method for the systematic sampling of the different 

dairies for the three seasonal sampling periods. 

3. Discussion of work planned before next report: 

Task 4, the development of a revised Year-2 sampling/analysis program and its review by the 

advisory group will be the next work to be accomplished. A draft of the Year-2 program is 

attached to this report and a meeting or conference call with the advisory group should occur by 

early May. If the proposed program is approved, the first sampling period will begin later in 

May (Task 5). Sampling of the six dairies should be complete by the end of June and the next 

sampling period will start in September. Additional related sampling of land applications, feed 

supplements, and photosynthetic lagoons will be done at these and other dairies during the time 

between sampling periods (Task 7). This additional work will be supported by supplemental 

funding from CSU-ARI, USDA and the California Dairy Campaign. 

4. Allocation of budget items during report period: 

An up-to-date accounting of the expenditures is not currently available. The sub-contract with 

Dr. Blake at UC Irvine is in place. The Year-1 samples have been analyzed. UC Irvine will bill 

CSU Fresno for the work to date and it will be included in a billing to ARB in May. 

5. Percentage of completion for each task: 

Tasks 1, 2 and 3 are completed 

Task 4 is approximately 50% completed 

Task 5 is approximately 0% completed 

Task 6 is approximately 0% completed 

Task 7 is approximately 50% completed 

The original proposal, written in early 2005, emphasized the use of samples collected in Summa 

Canisters taken simultaneously upwind and downwind of significant dairy operations such as the 

animal housing and lagoon areas. This method had been successfully employed in the previous 

47
study done at two of these six dairies and was expected to be an appropriate method if suitable 

analytical procedures were added. Net increases in ROG between the upwind and downwind 

samples were assumed to be emissions from that dairy operation. Modeling of the sampling 

results with a Gaussian Plume model would calculate the emissions from that operation for the 

sampling period. The original plan was to sample for a 2 hour period during the day for two 

consecutive days and also collect a night sample on one of the two days. This was to be done at 

each of the six dairies for each of the three sampling periods (May-June, September-October and 

January-February). This has proven to be impossible. Minimum wind conditions for ambient 

samples (1 meter/second and a deviation of no more than 20 degrees of direction) are rarely 

present except in the spring and for the dairies north of Fresno. The complete set of samples was 

collected twice out of the planned 18. Samples were collected for 5 minutes rather than 2 hours 

for most of the spring and summer sampling periods but no winter ambient samples were 

collected because wind conditions never approached the minimal levels required for modeling. 

Additionally, some of the spring samples were the initial canisters sent down to UCI for analysis. 

Dr. Blake is in the process of developing a standard gas that should increase the precision of the 

quantification of these samples considerably. Until that standard is used, the concentrations 

reported should be considered as relative values rather than absolute concentrations. 

The complete data set of analysis by the UCI lab of all ambient samples taken in Year-1 is 

attached as an Excel file titled “Ambient Data UCI Year1”. A summary of net increase for the 

17 samples from animal housing, 12 samples from lagoons and 3 samples from the digester at 

Dairy E are shown on the next page. The list of species has been sorted to place the largest 

concentrations first. The methane (ppmV), CO (ppbV) and Acetone (pptV) are shown in the 

table but not included in the total ROG calculation. The values shown in the summary table are 

the average of the net difference (downwind – upwind) in concentration for each species. 

Significant results from this data are: 

1. The animal housing areas are a much greater source of ROG than the lagoons. The 

negative net differences seen for the lagoons will have to be evaluated and modeled on a 

case by case basis to determine the actual lagoon emission. 

2. Alcohols are the primary ROG from animal housing. This is confirmed by flux chamber 

samples summarized below. The average total net ROG of 11.6 ppbV for animal housing 

is 70% Methanol plus Ethanol. The low and negative values for alcohols from lagoon 

samples may be from contributions to the upwind value from animal housing or feed 

storage, depending upon the specific dairy. 

48
Table 1. Summary of Net concentrations of Year-1 ambient samples. 

 Animal Housing Lagoon Digester (Dairy E

Total Average Total Average Total Average 

units common name

Methane (ppmv) ppmv Methane 17 -3 12 -3 3 243

CO (PPBV) ppbv Carbon Monoxide 17 -415 12 -273 3 5

Ethanol (B) pptv Ethanol 17 2,966 12 -11,557 3 299

Methanol (B) pptv Methanol 17 5,199 12 -1,858 3 3,062

Acetone (MS) pptv Acetone 17 3,545 12 353 3 325

D-Limonene (B) pptv D-Limonene 17 495 12 -600 3 15

DMS (MS) pptv Dimethylsulfide 17 338 12 50 3 76

alpha Pinene (MS) pptv alpha Pinene 17 91 12 -1 3 1

n-Hexane (B/E/MS) pptv Hexane 17 46 12 -13 3 7

Ethane (E) pptv Ethane 17 -23 12 -136 3 259

OCS (MS) pptv Carbonyl Sulfide 17 141 12 63 3 142

2-Methylpentane (B) pptv 2-Methylpentane 17 52 12 4 3 -54

3-Methylpentane (B) pptv 3-Methylpentane 17 -12 12 -58 3 -8

Ethene (E) pptv Ethene 17 166 12 46 3 567

Propane (B/E) pptv Propane 17 -404 12 -634 3 1,549

Propene (B/E) pptv Propene 17 29 12 -6 3 205

CH3Cl (MS) pptv Methyl chloride 17 305 12 95 3 229

Isoprene (MS) pptv Isoprene 17 38 12 -31 3 51

beta Pinene (MS) pptv beta Pinene 17 117 12 14 3 -10

HCFC-22 (MS) pptv chlorodifluoromethane 17 119 12 10 3 -95

CFC-12 (C/D/MS) (PPTV) pptv Dichlorodifluoromethane 17 -2 12 -9 3 10

Ethylbenzene (MS) pptv Ethyl Benzene 17 422 12 16 3 15

CH2Cl2 (MS) pptv Methylene chloride 17 30 12 2 3 10

1,2,4-Trimethylbenzene (MS) pptv 1,2,4-Trimethylbenzene 17 271 12 39 3 -20

Ethyne (E) pptv Acetylene 17 18 12 25 3 46

i-Pentane (E) pptv ? 17 233 12 46 3 -80

CFC-11 (C/D/MS) pptv Trichlorofluoromethane 17 20 12 11 3 13

n-Butane (B/E) pptv Butane 17 38 12 -11 3 9

i-Butane (B/E) pptv Isobutane 17 -16 12 -24 3 -55

MeONO2 (C/D) pptv Methyl nitrate 17 0 12 -1 3 1

n-Pentane (E) pptv Pentane 17 116 12 3 3 16

EtONO2 (C/D) pptv ? 17 -1 12 -1 3 0

m-Ethyltoluene (MS) pptv 3-Ethyltoluene 17 140 12 11 3 -6

Toluene (B/MS) pptv Toluene 17 137 12 35 3 20

i-PrONO2 (C/D) pptv ? 17 0 12 1 3 3

p-Xylene (MS) pptv p-Xylene 17 145 12 20 3 6

m-Xylene (MS) pptv m-Xylene 17 145 12 19 3 6

HFC-134a (MS) pptv hafnium carbide 17 14 12 6 3 -3

CHCl3 (MS) pptv Chloroform 17 2 12 0 3 1

CCl4 (C/MS) pptv Carbon tetrachloride 17 5 12 4 3 4

o-Ethyltoluene (MS) pptv 2-Ethyltoluene 17 87 12 29 3 -13

CS2 (MS) pptv Carbon Disulfide 17 22 12 50 3 65

Benzene (MS) pptv Benzene 17 21 12 9 3 -6

2-BuONO2 (C/D) pptv ? 17 0 12 0 3 0

CFC-113 (MS) pptv thane, 1,1,2-trichloro-1,2,2-trifluoro 17 3 12 3 3 1

C2Cl4 (C/D/MS) pptv Tetrachloroethylene 17 15 12 13 3 9

o-Xylene (MS) pptv o-Xylene 17 60 12 5 3 -1

HCFC-141b (MS) pptv 1,1-dichloro-1-fluoroethane 17 6 12 1 3 1

HCFC-142b (MS) pptv 1-Chloro-1,1-difluoroethane 17 1 12 1 3 -10

1,3,5-Trimethylbenzene (MS) pptv 1,3,5-Trimethylbenzene 17 23 12 6 3 0

CH3 Br (MS) pptv Methyl bromide 17 -1 12 2 3 2

C2HCl3 (D/MS) pptv Trichloroethylene 17 1 12 1 3 1

CH3CCl3 (C/MS) pptv Ethane, 1,1,1-trichloro- 17 2 12 0 3 0

CH3I (C/MS) pptv Methyl iodide 17 0 12 0 3 0

CFC-114 (C/MS) pptv 2-Dichloro-1,1,2,2-tetrafluoroethan 17 1 12 1 3 0

n-PrONO2 (D) pptv ? 17 0 12 0 3 0

1-Butene (E) pptv 1-Butene 17 4 12 2 3 0

trans-2-Butene (B) pptv 2-Butene-trans 17 1 12 -1 3 0

2-PeONO2 (C/D) pptv ? 17 0 12 0 3 0

H-1211 (C/D/MS) pptv hexadecane 17 0 12 0 3 0

3-PeONO2 (C/D) pptv ? 17 0 12 0 3 0

cis-2-Butene (B) pptv 2-Butene-cis 17 0 12 0 3 0

1,3-Butadiene (B) pptv Butadiene 17 -1 12 0 3 -4

CH2Br2 (D) pptv Methane, dibromo- 17 0 12 0 3 0

CHBr3 (C/MS) pptv Methane, tribromo- 17 0 12 0 3 0

11,630 -14,298 6,333

Ethanol % of ROG 26% 5%

Methanol % of ROG 45% 48%

Total Alcohol % of ROG 70% 53%

49
Flux Chamber Data Summary 

The use of the EPA Isolation Flux Chamber had not been adopted by our research group when 

this project was initially proposed. We had observed its use by Dr. Chuck Schmidt at two of the 

dairies in this study and we expected to develop the method as an additional monitoring 

technique with supplemental funding from CSU-ARI. The difficulties encountered with the 

ambient sampling provided a strong inducement to develop the flux chambers as an alternative 

that would both eliminate the problem of the minimum wind requirement and enable much more 

specific monitoring of different sources within the components of the dairy operation. The 

method has been very successful with respect to both of those goals. There is a US-EPA 

Protocol for the Isolation Flux Chamber that has been published and used by a number of 

researchers. We used the published protocol without modification for the sampling described 

below. 

Unlike the ambient, upwind/downwind sampling where the dairy could only be differentiated 

into major components such as the animal housing and lagoon systems; sampling with the flux 

chambers enables very specific areas to be isolated and sampled without interference or 

contamination from other, nearby sources. We have developed a monitoring program with the 

flux chambers that has proven to be effective in the last two sampling periods and will be 

proposed as the primary method for the Year-2 protocol. The flux chambers have nearly the 

opposite problem compared to the ambient canister samples. The flux chamber is limited to the 

0.5M2

 area that it covers and the sampling period is limited to about 30 minutes following the 30 

minute flush/preparation time. Replication of the flux chamber data is therefore necessary. At 

least 2 chambers are used for each measurement and 4 will sometimes be required when 

variability is expected to be high. We currently have 4 chambers with an additional 4 on order. 

That should be sufficient for the proposed Year-2 monitoring program. 

The ability to sample more discrete locations within the dairy has already shown the flux 

chambers to be an ideal method for work such as this. The initial discovery that alcohols, 

particularly ethanol, are the dominant ROG in many samples led us to suspect the silage and feed 

as possible significant sources. Flux chambers were used to monitor those components as well 

as fresh manure on the flush lanes, the manure pack on the exercise corrals and some monitoring 

of solids and effluent applications to crop land. The emerging importance of ethanol and 

methanol created the need to monitor those ROG’s more frequently and at less cost than the 

canister samples that required GC-MS analysis either at UCI or in-house. A photo-acoustic, 

multi-gas analyzer was purchased to monitor N2O and NH3 from the flux chambers at the six 

dairies for the Denitrification/Decomposition project in collaboration with Bill Salas at New 

Hampshire. This INNOVA has the capability to monitor six gasses in real time at sub-ppb 

concentrations. We had the INNOVA configured for ethanol and methanol along with the CO2, 

water vapor, N2O and NH3 needed for the UNH project. The INNOVA data for the alcohols was 

very consistent when compared to the analysis of a canister taken at the same time and analyzed 

at UCI or in-house. The real-time INNOVA values for silage were consistently 3-4 times greater 

than the UCI analysis of a canister from the same flux chamber (see Table 2). Dr. Blake as well 

as others collaborating on the project have questioned the ability of the GC-MS system to extract 

all of the water soluble gasses such as these alcohols from the canisters when they are analyzed. 

There is the possibility that ethanol and methanol values from canister analysis are reduced by 

this sampling problem and so the higher INNOVA measurements may, in fact be more accurate. 

50
In addition to canisters sampled from the flux chamber for GC-MS analysis and the INNOVA 

monitoring that is done at the same time, NH3 is also monitored with a denuder and we have 

recently been sampling with sorbent tubes for VFA analysis. The VFA data is not yet available 

but the method will be used in the Year-2 program if it proves to be effective. 

The components of the dairy operations for which flux chambers were used are silage, feed 

(Total Mixed Ration or TMR), exercise corrals, and flush lanes on a regular basis beginning with 

the fall-’06 sampling period. Some data is available from summer-’06 for these sources as well 

as others such as feed supplements, solids storage, and land applications. The flux chambers are 

being adapted to float on lagoons but no work other than method development has been done to 

date. A summary of the data from canister sampling in the flux chambers and a comparison 

with INNOVA data taken at the same time is shown below for silage, TMR, exercise corrals and 

flush lanes. This is only a small amount of the INNOVA data since only those measurements 

that coincided with canister samples are reported here. Additional INNOVA data is shown 

where it is needed to support the results for this project. 

Silage 

The most likely source of ethanol at a dairy was expected to be the silage pile where it would be 

produced by yeast fermentation of the plant material as part of the ensiling process. Flux 

chambers were placed at the face of the pile where it is exposed for the feed mixing operation. 

No monitoring of the larger, covered portion of the silage pile has been done to date. Both the 

undisturbed face of the pile and the loose silage disturbed by the feed mixing equipment were 

sampled with the flux chambers. Canisters were used to sample from the flux chamber and 

analyzed at both UCI and CSUF. The INNOVA gas analyzer sampled and reported the alcohols 

in real-time from the chambers. Three INNOVA samples of one minute each were analyzed and 

recorded either just before or just after the canister sample was taken. Both samples were 

completed within the same 10 minute period. The averages of the 8 canisters analyzed at UCI 

are shown in Table 2. The INNOVA unit became available in late June and was matched with 

five of the canister samples, also shown in Table 2. The complete data set can be found in the 

Excel file titled “Year 1 Flux Chamber data”. 

Table 2. Summary of total ROG and alcohol fluxes in silage samples. 

Silage

Emission Rate (μg/m2

/min)

5 INNOVA samples with 8 UCI canisters

Summary and Comparison of UCI Canisters with INNOVA data

UCI Canister Ethanol μg/m2

/min. 14,897

UCI Canister Methanol μg/m2

/min. 695

INNOVA Ethanol μg/m2

/min. 60,598

INNOVA Methanol μg/m2

/min. 12,892

INNOVA/UCI Ethanol ratio 5.14

INNOVA/UCI Methanol ratio 11.53

Total VOC's (UCI) μg/m2

/min. 16,303

Total ROG (UCI) μg/m2

/min.* 15,783

Ethanol % 87.8%

Methanol % 9.2%

Total Alcohol % 97.0%

*Total ROG's = UCI total VOC - (methane+CO+Acetone)

51
The alcohols, ethanol and methanol, were nearly all of the ROG measured from the silage. They 

were 97% of the total measured by the canister analysis. Ethanol concentrations were the 

dominant ROG at about 10 times the methanol levels. The INNOVA measured the alcohols at 

higher concentrations than the UCI canister analysis. There was one anomalous ethanol value 

and one methanol flier from the INNOVA. If those are removed from the average ratios, the 

INNOVA/Canister ratio is consistently between 3 and 4 for both alcohols. The INNOVA was 

returned for recalibration of the alcohol channels late in the summer and the data from the unit 

following that was much more consistent. Further comparisons between canister analysis and 

INNOVA data will be available in Year-2. The development of a standard at UCI to improve the 

quantification of those analyses will increase the validity of the comparison. 

The contribution of silage to Ethanol emissions from dairies was rather variable as shown in the 

data files and summarized in Figure 1 below. The data in Fig. 1 is from the INNOVA and 

includes those values from Table 2 along with others taken when no canister sample was 

collected. 

Figure 1. Ethanol flux rates from silage piles monitored at the six dairies from April to 

November, 2006. Each value is the average of 3 measurements taken within a 4 minute period. 

Ethanol Fluxes from Silage Pile Face

0

20000

40000

60000

80000

100000

120000

F F F F C C B A D D E E

Dairy

ug/m2/min

Ethanol

The considerable variability could be due to a number of factors. Some silage is made from 

corn, including the grain, while other silage is made from grass and winter grown cereals with a 

lower carbohydrate content that should produce less ethanol. A more interesting variable from 

the point of view of potential mitigation is the density of the silage pile as a result of the amount 

of compaction during its construction. Ethanol production from yeast fermentation is a symptom 

of low quality silage. Good silage is made when the plant material is compacted to the point 

where no oxygen is present and lactic acid bacteria are the predominant microbe. Lactic acid 

formation reduces the pH of the silage and preserves it. Incomplete compaction allows sufficient 

oxygen into the silage for yeast to exist and ferment carbohydrates to ethanol. The density of the 

silage piles monitored by the flux chambers was measured by taking a core according to a 

published method and weighing it. The resulting densities are shown in Table 3. 

52
Table 3. Silage density of piles monitored at the six diaries during 2006. 

Dairy Date Avg. DM Denstiy

CSUF 3/24/2006 18.7

CSUF 4/7/2006 11.2

A 4/10/2006 17.9

A 4/13/2006 15.1

A 4/24/2006 16.9

A 9/26/2006 11.1

B 7/10/2006 14.1

B 9/6/2006 9.3

C 1/11/2007 11.3

C 8/8/2006 6.2

D 6/1/2006 14.1

D 11/14/2006 12.2

E 6/23/2006 9.9

F 7/24/2006 8.6

The high ethanol fluxes in Fig. 1 for the silage at dairy C was measured on August 8 and 

corresponds to the lowest density (6.2) of all the measured silage. The high ethanol found at 

dairy F was measured on July 24, matching the next lowest silage density (8.6). It appears that 

high ethanol fluxes from silage are linked to low density silage. The density of silage 

recommended by UC is 12 to 15. The ethanol fluxes from silage in that range were much lower, 

presumably because the yeast fermentation was reduced by the more anaerobic conditions. The 

monitoring of ethanol and comparison with silage density will be continued at each dairy in 

Year-2. 

Total Mixed Ration (Feed) 

The feed is a mixture of various components formulated to provide the proper amount of energy 

and nutrition to the various groups of animals at the dairy. The solid and liquid components are 

loaded into a large bin on a truck or trailer where they are mechanically mixed and delivered to 

the animals through a chute while the feed wagon is driven along the feed lane. This operation 

typically takes place two or three times each day and the Total Mixed Ration (TMR) is 

consumed by the cows in about a 6 hour period. Silage is usually the largest component of the 

TMR so significant ethanol fluxes might also be expected from the feeding operation. Since the 

feed is spread over a much larger area than that of the silage pile face, the potential for emissions 

is greater. 

The fluxes from the TMR were monitored by placing chambers on the feed as soon as it was 

delivered to the animals. The emission of ethanol was expected to change as the feed was 

consumed and as the initial volatile ROG rapidly vaporized. A second set of flux chambers was 

placed on the feed after an hour to monitor any change in emissions with time. The flux 

chambers must be flushed with zero air for 30 minutes before sampling or measurements are 

taken according to the US-EPA published protocol so the values reported are for 30 minutes and 

53
90 minutes after feeding. The average of 18 canisters collected between May and November, 

2006 are shown along with 12 corresponding INNOVA samples in Table 4. 

Table 4. Summary of total ROG and alcohol fluxes in feed (TMR) samples. 

FEED

Emission Rate (μg/m2

/min)

12 INNOVA samples with 18 UCI canisters

Summary and Comparison of UCI Canisters with INNOVA data

UCI Canister Ethanol μg/m2

/min. 5,194

UCI Canister Methanol μg/m2

/min. 764

INNOVA Ethanol μg/m2

/min. 23,697

INNOVA Methanol μg/m2

/min. 2,922

INNOVA/UCI Ethanol ratio 3.98

INNOVA/UCI Methanol ratio 3.73

Total VOC's (UCI) μg/m2

/min. 6,671

Total ROG (UCI) μg/m2

/min.* 6,211

Ethanol % 82.8%

Methanol % 16.2%

Total Alcohol % 99.0%

*Total ROG's = UCI total VOC - (methane+CO+Acetone)

Alcohols are the dominant ROG in the TMR as they were in silage. The flux rates are lower 

since not all the components are subject to fermentation. The higher moisture content of the 

TMR compared to silage may also be a factor if the soluble alcohols are being trapped in water. 

The ethanol:methanol ratio is somewhat lower than in silage as well. The ratio of the INNOVA 

data to the canister samples is even more consistent than it was for silage. 

A comparison of the initial TMR emissions measured at 30 minutes to those measured at 90 

minutes (Fig. 2) shows a considerable decrease in volatile ethanol over time. The flux of ethanol 

appears to decrease by nearly half from the initial hour to the second hour. A few samples have 

been taken over a longer period of time. Those indicate this decrease in alcohol flux continues 

through the several hours that the TMR is in place. 

The third significant ROG found in the TMR samples after ethanol and methanol was limonene. 

It was found at concentrations of about 10% of the methanol flux at dairies A, C and E, at times. 

Dairy A frequently uses citrus pulp as a component of their TMR and the other dairies 

occasionally do the same. The presence of limonene in the TMR was always correlated with the 

use of citrus pulp as a supplement. 

Flush Lanes and Fresh Manure 

Flux chambers were used on the surface of the flush lanes to monitor emissions from both the 

fresh manure as it is deposited when the animals are feeding and the flushed lanes when the 

manure had been removed to the lagoon system. The highest fluxes were expected to be just 

prior to flushing and that appears to be the case. Flux chambers were used 8 times on 5 of the 

dairies to monitor the pre-flush fluxes in the summer and fall of 2006. The dominant ROG is 

ethanol, followed by methanol as it was for the feed and silage. The presence of limonene that 

was correlated with citrus pulp in the TMR also occurred as a flux from the fresh manure at some 

of those same times. The magnitude of the ROG flux from the fresh manure is less than 10% of 

that measured for the feed but the area of the flush lane is considerably larger so they may be 

54
similar with respect to actual emissions. The sampling program in Year-2 will include flux 

chamber monitoring at several intervals to characterize the changes in flux from the clean lanes 

to the heaviest manure load just prior to flushing. 

Table 5. Summary of total ROG and alcohol fluxes in fresh manure samples. 

Flush Lane (Pre Flush)

Emission Rate (μg/m2

/min)

8 UCI canisters

Summary Comparison of UCI Canisters 

UCI Canister Ethanol μg/m2

/min. 265

UCI Canister Methanol μg/m2

/min. 43

Total VOC's (UCI) μg/m2

/minTotal Alcohol % 541

Total ROG's* 317

Ethanol % 76.5%

Methanol % 15.5%

Total Alcohol % 92.1%

Methane % of VOC's 41.4%

*Total ROG's = UCI total VOC - (methane+CO+Acetone)

The range of flux values for these samples runs from a low of 12 mg/M2

/min. to nearly 800. The 

wide variation may be due to amount or age of the manure or some other factor at the dairy. The 

full data set can be found in the Excel file titled “Year 1 Flux Chamber data”. 

Exercise Corrals 

The open areas next to the free stalls are used by the cows in good weather for exercise and 

bovine socializing. After the flush lanes, these exercise pens collect the most manure and are a 

potential emission source. Flux chambers were set up on several of these corrals to monitor 

emissions from the manure pack during the summer and fall of 2006. Data from 3 canisters 

collected from those chambers and analyzed at UCI are summarized below. The full data set 

may be found in the Excel file titled “Year 1 Flux Chamber data”. 

Table 6. Summary of Total ROG and alcohols in exercise corral samples. 

Corrals

Emission Rate (μg/m2

/min)

3 INNOVA samples with 3 UCI canisters

Summary and Comparison of UCI Canisters with INNOVA data

UCI Canister Ethanol μg/m2

/min. 12.4

UCI Canister Methanol μg/m2

/min. 13.6

Total VOC's (UCI) μg/m2

/min. 305

Total ROG (UCI) μg/m2

/min.* 29

Ethanol % 42.6%

Methanol % 47.0%

Total Alcohol % 89.6%

Methane % of VOC 38.8%

*Total ROG's = UCI total VOC - (methane+CO+Acetone)

55
Fluxes of ROG from the surface of the exercise corrals are considerably lower than those from 

TMR, silage or fresh manure but it is still potentially significant because of the large area 

involved. The limited number of samples analyzed to date does not allow conclusions to be 

drawn but it can be pointed out that the alcohols are still the dominant ROG. The ROG is a 

much smaller fraction of the total VOC primarily because the methane and CO were 

proportionally higher in 2 of these 3 samples. The regular sampling of the corrals at each dairy 

in each sampling season proposed for the Year-2 program should provide sufficient data to 

estimate emission fluxes from the corrals. 

Additional sampling and analysis 

These same six diaries are used for related projects to investigate a number of additional air and 

water quality parameters. The sampling periods are generally similar except for the land 

application monitoring and other practices that do not occur on a regular basis. The sampling 

and analysis for those related projects are included in the Year-2 sampling program. 

Year-2 Sampling Program 

Task 4 of the project calls for the development of a sampling and analysis program to monitor 

the six dairies in the second year of the study. This Year-2 program is to be developed from the 

initial monitoring program used in Year-1. The field sampling methods, analytical procedures 

and schedule to be followed in Year-2 will be adopted after a review of the Year-1 results and 

consultation with the designated advisory group and ARB staff. This proposed Year-2 program 

is, therefore subject to revision until it is adopted for the summer-07 sampling period. 

Sampling schedule: 

In order to characterize volatile organic compound emissions from San Joaquin Valley dairies a 

total of six dairies were selected for their differing manure management styles as well as to 

provide a sense of facility variability of emissions. The six dairies are to be sampled three times 

per year to evaluate season emission characteristics. These periods chosen were: 

1. Winter (December to March) 

2. Summer (May to July) 

3. Late Summer/Fall (September to November) 

Field sampling methods: 

Two methods of emissions monitoring are used in the project: 

1. Upwind/Downwind ambient sampling utilized a dispersion model (ISC st3) to derive 

emission fluxes. 

2. USEPA Emission Isolation Flux Chamber used according to the published protocol for 

monitoring fluxes from surfaces. 

1. The upwind/downwind method is not a discrete sampling method and can only break down 

emission sources into two categories on the dairy facility. The method also requires a consistent 

wind speed and direction for proper modeling conditions. The following samples will be taken 

when wind conditions are present to enable modeling of the results: When minimum wind 

conditions are not present, these samples will not be collected. Additional flux chamber samples 

may be taken in place of the ambient samples. 

1. Animal Housing 

a. Free Stalls 

b. Open Lot/Corrals 

56
2. Lagoon Systems 

a. Treatment Lagoons 

b. Storage Ponds 

When minimum wind conditions are not present, these samples will not be collected. Additional 

flux chamber samples may be taken in place of the ambient samples. 

2. Use of the flux chamber method provides the capability to discretely sample individual 

sources within the animal housing area. Four sources were chosen to sample from the animal 

housing: 

1. Total Mixed Ration 

a. 0.5 to 1 hour post feeding 

b. 1.5 to 2 hours post feeding 

2. Flush Lane 

a. Pre-Flush (Pre-Scrape, Pre-Vacuum) 

b. Post-Flush (Post-Scrape, Post-Vacuum) 

3. Bedding 

4. Open Lot/Corral 

a. Deep Manure Pack 

b. Shallow Manure Pack 

c. Harrowed Manure Pack (when available) 

5. Silage Pile Face 

a. Disturbed 

6. Wet Distillers Grain (currently fed at 2 of 6 dairies) or other significant feed components 

Analytical Methods 

1. UC Irvine - Gas Chromatography/MS, ECD, FID Detectors 

a. Sample Media = 2L canisters 

b. Number of Compounds Quantified = 64 

2. CSUF – Gas Chromatography/MS (TO-15 and PAMS) 

a. Sample Media = 6L summa-type 

b. Number of Compounds Quantified 

i. TO-15 =62 

ii. PAMS (Photochemical Assessment Monitoring Stations) = 57 

3. INNOVA 1412 Photoacoustic Field Gas Analyzer (1st unit in use since August, ’06) 

a. Ammonia 

b. Ethanol 

c. Methanol 

d. Carbon Dioxide 

e. Nitrous Oxide 

4. INNOVA 1412 Photoacoustic Field Gas Analyzer (2nd unit ordered April, ’07) 

a. Methane 

b. Trimethylamine 

c. Total Hydrocarbons as Propane 

d. Acetic Acid 

e. Propanol 

5. EAS Lab Inc. TO-17 Volatile Organic Acids from Sorbent Tube 

a. Sample Media - Sorbent Tube 

b. Number of Compounds Quantified = 5 

57
Emission Source Analysis 

Silage and total mixed ration samples are collected from chamber locations immediately 

following emissions monitoring, placed into a plastic bag, and stored in a sample cooler. 

Samples are given specific sample numbers, logged into a log sheet, and prepared for shipment 

to the analytical laboratory. Analysis of feed samples are provided by Dairyland Laboratories 

Inc. (Arcadia, WI) who performs a commercially available analysis called a Fermentation 

Quality Analysis or VFA Profile. This analysis measures the following parameters on a dry 

matter basis. 

1. Moisture (%) 

2. Dry Matter (%) 

3. pH 

4. Lactic Acid (%) 

5. Acetic Acid (%) 

6. Propionic Acid (%) 

7. Butyric Acid (%) 

8. Iso-Butyric Acid (%) 

9. Ethanol (%) 

10. Methanol (%) 

11. Crude Protein (%) 

12. Ammonia-N (% of crude protein) 

13. Total Acids (%) 

Manure samples are collected from chambers locations immediately following emissions 

monitoring, placed into a plastic bag, and stored in a sample cooler. Samples transported to 

CSUF lab facilities and stored until delivery to an analytical laboratory. Manure samples are 

analyzed for the following: 

1. Total Nitrogen 

2. Ammonium (NH4-N) 

3. Nitrate (NO3-N) 

4. Organic Matter (%) 

58
Sampling Program: Year-1 

The sampling program in Year-1 was developed from spring-06 through the winter-07 sampling 

periods. The initial, ambient sampling was supplemented by the flux chambers, CSUF canister 

sampling and INNOVA monitoring as additional funding became available. The sampling 

shown in Table 7 is the final program as it was developed for the winter ’06 period. 

Table 7. 

Source UC Irvine CSUF Innova 1412 Total

Ambient Upwind - 2 day & 1 night 3 3 6

Ambient Downwind Housing - 2 day & 1 night 3 3 6

Ambient Downwind Lagoon - 2 day & 1 night 3 3 6

Total Mixed Ration (0.5 - 1 h post) 1 1 2 4

Total Mixed Ration (1.5 - 2 h post) 1 1 2 4

Silage Pile Face (Disturbed) 1 1 2 4

Flush Lane (Pre-Flush) 1 1 2 4

Flush Lane (Post-Flush) 1 2 3

Bedding 1 2 3

Open Lot/Corral (Deep Manure Pack) 1 1 2 4

Open Lot/Corral (Shallow Manure Pack or Harrowed) 11 2 4

Field Blank 1 1 1 3

Field Replicate 2 2 6 10

Totals 18 20 23 61

Sampling Program - Year 1

Analytical Method

Samples are from flux chambers except for those designated as “Ambient” 

In addition to the dairy sampling program shown in Table 7, land application of liquid effluent 

and solids were also monitored for ROG and various N emissions. Lagoon sampling with the 

flux chambers is under development and will be included for selected sites in the Year-2 

program. 

59
Sampling Program: Year-2 

The sampling and analysis program proposed for Year-2 will begin with the summer-07 

sampling period and will be maintained in this form throughout the year. Additional sampling 

and analysis may be added and a Year-3 program will be developed for the ARI and USDA 

funded portions of the project through 2009. 

Table 8. 

Source UC Irvine CSUF TO-17 Innova 1412 Total

Ambient Upwind - 1 & 1 (when possible) 2 2 4

Ambient Downwind Housing - 1 day & 1 night 2 2 4

Ambient Downwind Lagoon - 1 day & 1 night 2 2 4

Total Mixed Ration (0.5 - 1 h post) 1 1 1 2 5

Total Mixed Ration (1.5 - 2 h post) 1 1 1 2 5

Silage Pile Face (Disturbed) 1 1 1 2 5

Flush Lane (Pre-Flush) 1 1 1 2 5

Flush Lane (Post-Flush) 1 2 3

Bedding 1 2 3

Open Lot/Corral (Deep Manure Pack) 1 1 1 2 5

Open Lot/Corral (Shallow Manure Pack or Harrowed) 11 1 2

Field Blank 1 1 1 1 4

Field Replicate 2 2 1 6 11

Totals 15 17 8 23 63

Proposed Sampling Program - Year 2

Analytical Method

5

Samples are from flux chambers except for those designated as “Ambient” 

 

In addition to the proposed dairy sampling program shown in Table 8, land application of liquid 

effluent and solids will also monitored for ROG and various N emissions when the opportunity 

arises. Solids applications in the winter and spring as well as effluent irrigations in the spring 

and summer will be monitored on at least half of the dairies, if possible. Canisters designated for 

ambient sampling that cannot be used due to insufficient wind will be employed for additional 

flux chamber samples of silage, TMR, flush lanes, lagoons and land applications. Lagoon 

sampling with the flux chambers at selected sites will be added for the CDC project and included 

in the Year-2 program. 

60
APPENDIX C 

Appendix C is a description of the analytical systems and procedures provided by Dr. 

Donald Blake in the Department of Chemistry at UC Irvine. This contract from CARB 

specified the use of Dr. Blake and this laboratory for the analysis of samples collected 

by CSU Fresno field staff for the study. This document was originally part of the 

proposal and is included here for the details of the analytical processes. 

61
Organics Analysis – Detailed Description 

Responsibilities 

Dr. Donald Blake and his UC Irvine team will analyze project test canisters collected at 

dairies for analysis of methane, carbon monoxide, selected C2-C10 nonmethane 

hydrocarbons, selected C1-C2 halocarbons, C1-C5 alkyl nitrates, and selected sulfur 

gases. Canisters will be assayed within 2 weeks of their being received and preliminary 

data will be transmitted to the PI within2 2 weeks after the sample analysis is complete. 

A detailed description of the analytical methods to be used for the project is described 

below. 

Reports, Data and Other Deliverables 

Prepare monthly progress reports to CSU Fresno that will include QA/QC checked and flagged 

data in spreadsheet format. 

Experimental Setup 

A 1215 cm3 sample aliquot (standard temperature and pressure) from an individual 

canister is introduced into the system manifold and passed over glass beads maintained 

at liquid nitrogen temperature. The flow is regulated by a Brooks Instrument mass flow 

controller model 5850E, and is kept below 500 cm3/min to ensure complete trapping of 

the relevant components. This procedure has the effect of pre-concentrating the 

relatively less-volatile components of the sample (such as halocarbons and 

hydrocarbons) while allowing volatile components (such as N2, O2, and Ar) to be 

pumped away. The less volatile compounds are then re-volatilized, by immersing the 

loop containing the beads in hot water (80°C), and subsequently flushed into an helium 

carrier flow (head pressure 48 psi). This sample flow is then split into six streams. Each 

stream is chromatographically separated on an individual column and detected by a 

single detector. Three HP 6890s form the core of the analytical system. Electroncapture detectors (ECD, sensitive to halocarbons and alkyl nitrates), flame-ionization 

detectors (FID, sensitive to hydrocarbons), and a quadrupole mass spectrometer (MS, 

for unambiguous compound identification and selected ion monitoring) will be 

employed. 

The first HP-6890 (GC-1) contains two columns. The first column is a J&W DB-5 (30 m, 

I.D. 0.25 mm, film 1 mm) connected to a Restek 1701 (5 m, I.D. 0.25 mm, film 0.5 mm), 

which is outputted to an ECD detector. The second column is a DB-5ms (60 m, I.D. 

0.25 mm, film 0.5 mm), which is outputted to an MS detector (HP-5973). The DB5/Restek 1701 receives 7.2% of the total carrier flow, and the DB-5ms receives 10.1%. 

The second HP-6890 (GC-2) contains two columns. The first is a J&W DB-1 column 

(60 m, I.D. 0.32 mm, film 1 mm) output to an FID detector. This column receives 14.7% 

of the flow. The second is a J&W Cyclodex (60 m, I.D. 0.32 mm, film 0.5 mm) receives 

10.8% of the flow and is plumbed to an FID. The third HP-6890 (GC-3) contains a J&W 

GS-Alumina PLOT column (30 m, I.D. 0.53 mm) connected to a DB-1 (5 m, I.D. 0.53 

mm, film 1 mm), which is output to an FID detector, and a Restek 1701 (60 m, I.D. 0.25 

62
mm, film 0.50 mm), which is output to an ECD detector. The GS-Alumina PLOT column 

receives 49.9% of the flow, and the Restek 1701 receives the remaining 7.3%. Output 

from each detector is recorded digitally using Chromeleon software (Spectra Physics, 

San Jose, CA). Each resulting chromatogram will be manually modified, and each peak 

shape individually checked. This type of quality control is very important for datasets of 

this size because a slight change in retention time or peak shape can cause We at UC 

Irvine generate our own zero-air and nitrogen for use in our FID and ECD detectors. 

House air is passed through a CUNO Inc. model AP101T aqua pure water filter filled 

with glass wool, then through a Whatman 64-02 Air Dryer equipped with a 100-12 BX 

prefilter. This removes oil, water, and particulates from the air stream, which is then split 

and directed into a Domnick Hunter nitrox-nitrogen generator (NG7-0) and a Praxair 

zero-air generator (model Airlab WHA 76803). The output from these devices are split 

further and directed into gas regulators for head pressure regulation. Before entering 

our system all gases employed are passed through homemade graphite/molecular 

sieve traps to remove any remaining contaminants. These traps are preconditioned 

(and regenerated) by flowing gas through them at a temperature of 350 ̊C for at least 5 

hours. The three FIDs operate at a detector temperature of 250 ̊C with a zero-air flow 

of 450 mL/min, an H2(g) flow of 40 mL/min, and a detector makeup gas flow of 20 mL/min 

N2(g). The ECDs detector temperatures are 250 ̊C with a detector makeup flow of 50 

mL/min N2(g). 

The relative flow passing through an individual column depends primarily on its inner 

diameter. At UC Irvine we split the flow among the channels in such a way as to 

facilitate detection of a variety of halo- and hydrocarbon species. The majority of the 

flow is directed to the PLOT column due in part to the lower per-molecule sensitivity of 

the FID detector, and the low ambient concentrations of many non-methane 

hydrocarbons in remote regions. The split ratios are found to be highly reproducible as 

long as the specific humidity of the injected air is above 2 g-H2O/kg-air. For this reason 

(as well as to increase the stability of certain compounds in the canisters) 20 torr of 

water is added to each (preconditioned, evacuated) canister before being sent into the 

field. 

Multiple standards will be employed during the 8 week period of sample analysis. 

Working standards will be run roughly every two hours, and absolute standards will be 

run at least twice daily. Our lab regularly collects and calibrates pressurized cylinders of 

air from different environments for use as working standards. A primary reference 

standard for halocarbons was previously calibrated from static dilutions of standards 

prepared in this lab. Its absolute accuracy is tied to a manometer measurement and 

how accurately the appropriate volume ratios for the dilution line used are known. At 

UC Irvine we also have primary halocarbon standards provided by other research 

groups involved in halocarbon analysis. 

For hydrocarbons, we use a propane standard purchased from the National Bureau of 

Standards (SRM 1660A) to calculate a Per-Carbon-Response-Factor (PCRF) for the 

FIDs. This is compared to PCRFs calculated from more readily available commercial 

standards to check the absolute accuracy of the commercial standard, as well as the 

appropriateness of using the same PCRF for different compounds. From analysis of the 

commercial standard we assign a different PCRF for each alkane, from ethane to 

63
octane. This PCRF is then used for any compound with an equivalent number of 

carbons. For example, the PCRF determined for butane is employed during 

quantification of the butenes. We have cross-checked our calibration scheme against 

absolute standards from other groups for both hydrocarbons and halocarbons. 

Additionally, we participate in the Non-Methane Hydrocarbon Intercomparison 

Experiment (NOMHICE). The results of this experiment demonstrate that our analytical 

procedures consistently yield accurate identification of a wide range of unknown 

hydrocarbons and produce excellent quantitative results. We estimate our typical 

absolute accuracy as 2-10%, increasing as we approach our detection limits. 

At UC Irvine, our analytical accuracy ranges from 2 to 20%. The precision of the 

measurements varies by compound and by mixing ratio. For example, the measurement 

precision is 1% or 1.5 pptv (whichever is larger) for the alkanes and alkynes, and 3% or 

3 pptv (whichever is larger) for the alkenes. The precision for C2Cl4 at 5 pptv is ±0.05 

pptv. The limit of detection (LOD) is 3 pptv for all NMHCs. 

Typical alkyl nitrate detection limits are 0.03 pptv (0.03 pptv for methyl nitrate) and 

precision ±5% at mixing ratios above 5 pptv and ±10% below 5 pptv. The detection 

limits for methyl iodide (CH3I), bromoform (CHBr3) and DMS are 0.02, 0.02, and 1 pptv, 

respectively. Precision values of 1 and 2%, respectively for CH3I and CHBr3 are typical. 

For DMS, the precision is approximately 3% at mixing ratios >25 pptv, and 1 pptv or 

15%, whichever is higher, at mixing ratios <10 pptv. 

We have been involved in numerous NASA and NSF airborne projects during which 

more than twenty-five thousand samples have been collected and assayed for a wide 

range of hydrocarbons and halocarbons. Once samples are assayed, the stored 

chromatograms are individually inspected the reports from those chromatograms are 

then summarized in spreadsheet format and checked for inconsistencies. Once the 

quality control is complete the data are ready for archive. 

At UC Irvine we will quantify the gases using our 6 column/6 detector analytical system. 

The table on the next page lists the gases that are usually quantified and the associated 

limits of detections (LODs). Additional gases can be added if necessary. 

64
Gases Usually Quantified at UC Irvine by Dr. Donald Blake 

Gas LOD (ppt) Gas LOD (ppt) 

Ethane 3 DMS 1 

Ethene 3 OCS 50 

Ehtylene 3 Methyl Nitrate 0.03 

Propane 3 Ethyl Nitrate 0.03 

Propene 3 n-Propyl Nitrate 0.03 

n-Butane 3 i-Propyl Nitrate 0.03 

i-Butane 3 2-Butyl Nitrate 0.03 

1-Butene 3 2-Pentyl Nitrate 0.03 

cis-2-Butene 3 3-Pentyl Nitrate 0.03 

trans-2-Butene 3 CH2FCF3 (HFC-134a) 1 

1,3-Butadiene 3 CH3CCl2F (HCFC-141b) 1 

n-Pentene 3 CH3CClF2 (HCFC-142b) 1 

i-Pentene 3 CHClF2 (HCFC-22) 1 

Isoprene 3 CBrClF2 (H-1211) 0.05 

n-Hexane 3 Acetone 50 

2-Methylpentane 3 CCl3F (CFC-11) 1 

3-Methylpentane 3 CCl2F2 (CFC-12) 10 

Benzene 3 CCl2FCClF2 (CFC-113) 1 

Toluene 3 CClF2CClF2 (CFC-114) 1 

o-Ethyltoluene 3 CH3Cl 10 

m-Ethyltoluene 3 CCl4 0.1 

1,2,4-Trimethylbenzene 3 CH3CCl3 1 

1,3,5-Trimethylbenzene 3 CHClCCl2 0.05 

o-Xylene 3 CH3Br 1 

m-Xylene 3 CH2Br2 0.02 

p-Xylene 3 CHBr3 0.02 

Ethylbenzene 3 CH3I 0.02 

a-Pinene 3 CH2Cl2 0.2 

b-Pinene 3 CCl2CCl2 0.1 

65
APPENDIX D 

Appendix D is primarily a description of the field procedures used for the US-EPA 

Isolation Flux Chambers. The methodology listed on the EPA website was used as 

closely as possible with some variations to accommodate sampling conditions at the 

specific dairy locations described above. The flux chambers were purchased from 

Odotech of Toronto, Ontario. The specific methodology is detailed below. Some data 

in this report (Fig. 6 & 7) is from a multi-gas analyzer acquired for a project related to 

this one and used along with the sampling canisters for UCI analysis. The calibration 

documents for that analyzer along with the field sheets to show all of the samples and 

field data collected at the same time as the UCI canisters are also included in this 

appendix. 

66
TESTING METHODOLOGY FOR CSUF SURFACE EMISSION FLUX CHAMBER 

MEASUREMENTS 

Testing will be conducted using Surface Isolation Flux Chamber (flux chamber) to 

collect emission data. The main technical reference for flux chamber measurement is a 

study performed under contract with USEPA that provides a recommended protocol 

(Measurement of Gaseous Flux rates from Land Surfaces Using an Emission Isolation 

Flux Chamber, Users Guide, EPA /600/8-86/008, Radian Corporation, February 1986). 

The flux chamber used in this experiment is a clear cylindrical enclosure with a clear 

spherical top and the following technical data: 

 Material of flux chamber: Acrylic resin 

 Material of tubing: Teflon 

 Height of cylinder: 0.24 m 

 Height of half sphere: 0.17 m 

 Total Height: 0.41 m 

 Diameter: 0.495 m 

 Ground surface area: 0.19 m2

 Total volume: 64.5 liters 

The testing methodology is given below: 

1- Measurements of feed and manure sources will be made in two (2) separate days. All 

measurements will be made in the same sequence in all six dairies to provide 

consistency in environmental conditions between dairies, if possible (e.g., total mixed 

ration+0.5 h post placement will be measured first, then silage pile, then total mixed 

ration +6 post placement; or flush lane-pre flush will be measured first, then open lot, 

then flush lane-post flush). At each dairy, field and media blanks will be measured twice 

at the end of each daily measurement. 

2- The sampling plan contains a site map (aerial photo) with location numbers marked. 

Each location will represent an average condition for the designated areas at the time of 

measurements. 

3- Date, time, test site information, and field and equipment data will be documented on 

the CSUF SURFACE FLUX MEASUREMENT DATA FORM. Separate data forms will 

be used for total mixed ration, silage pile, main feed commodities, and manure sources 

for regular sampling in the six dairies. Additional data will be collected in special 

sampling for feed sources in two selected dairies. Data forms are shown on pages 8 

to13. All the pertinent information of the test sites will be collected at the time of 

measurements (e.g., number and time of feeding, number and time of daily disturbance 

of silage pile). Information about silage practices and management will be collected 

separately via survey (see page 14). 

 

67
4- All measurements will be performed in normal test site conditions without any 

physical or environmental modifications (e.g., surface of test sites will not be disturbed; 

total mixed ration and flush lanes will be measured in shade, and normally open lots 

and silage piles will be measured in sunlight). If possible, the rim of the chamber will be 

inserted into the measurement surface 2–3 cm to achieve sealing and minimize ambient 

air intrusion. Additional sealing will be provided around outside perimeter of the flux 

chamber if possible. 

5- All interior surfaces of flux chambers will be fully washed, rinsed with water, and 

wiped before the start of measurements. Flux chambers will be fully dry wiped with a 

clean paper towel between measurements and rinsed with water if necessary. 

6- Multiple flux chambers will be used at each test site. INNOVA will collect samples 

from both flux chambers but only one of the chambers will be used for other sampling 

(one UCI canister, one CSUF canister, and one TO-17 sample will be collected at each 

test site). Based on INNOVA real-time data, the flux chamber with higher ethanol or 

methanol emissions will be selected for other sampling in feed sources, and for manure 

sources, the flux chamber with higher ammonia emissions will be chosen for other 

sampling. 

7- Sweep air flow (ultra zero compressed air) will be initiated immediately after the 

placement of flux chambers using 1/4-inch Teflon tubing with stainless still quickdisconnect fitting. The sweep air will be adjusted and constantly maintained to the 

desired flow rate throughout the measurements using rotameters, metering valves, and 

pressure regulators. The sweep air flow rate will be set at 10 liters per minute. Sample 

collection will be performed at steady-state, assumed to be after four residence 

intervals, or 30 minutes. All 1/4-inch Teflon sample lines will be purged with ultra zero 

air before sampling. 

 

8- High air temperature inside the flux chamber may cause backpressure and hence 

could limit diffusional emissions. Ambient and flux chamber air and surface 

temperatures inside and outside the chambers will be measured immediately when flux 

chamber is placed and right before sampling using a hand-held digital thermocouple. 

Further, air temperature of ambient and flux chamber air will be recorded at all time 

when flux chamber is placed at the test site using HOBO data logger. 

9- Condensation may occur inside the flux chambers in some occasions, which may 

reduce the concentration of water-soluble volatile organic compounds. The occurrence 

and degree of condensation will be noted in the data forms. Further, humidity of ambient 

and flux chamber air will be monitored during the course of measurement using HOBO 

data logger. 

10- Rainfall events could alter surface flux rates. Flux chamber measurements will not 

be taken during and immediately after rainfall in open lots and silage piles. 

68
11- After flux chamber measurements, surface samples will be taken from all chamber 

locations, labeled, and stored in ice chests for laboratory analysis. All feed and manure 

samples should reach the laboratory within 24 hours. 

ANALYSIS SUMMARY 

The flux chambers will be used for the following procedures at each sampling location: 

1. INNOVA unit A 

a. Ethanol 

b. Methanol 

c. Trimethylamine 

d. Isopropanol 

e. THC as n-Hexane 

2. INNOVA unit B 

a. Ammonia 

b. Nitrous Oxide 

c. Carbon Dioxide 

d. Methane 

e. Acetic Acid 

 INNOVA units will be calibrated at the beginning and at the end of annual 

measurements or more frequently if needed. Recent (8-9-07) calibration results 

are shown at the end of this document. 

3. UC Irvine - Gas Chromatography/MS, ECD, FID Detectors 

a. Sample Media= 2L canisters 

b. Number of Compounds Quantified = 64 

4. CSU Fresno – Gas Chromatography/MS (TO-15 and PAMS) 

a. Sample Media= 6L summa-type 

b. Number of Compounds Quantified: 

i. TO-15 =62 

ii. PAMS (Photochemical Assessment Monitoring Stations) = 57 

5. EAS Lab Inc. (commercial lab) TO-17 Volatile Organic Acids from Sorbent Tube 

a. Sample Media- Sorbent Tube 

b. Number of Compounds Quantified = 5 

Documentation of ambient conditions along with material sample documentation and 

information for sample custody was accomplished through the use of field forms to be 

filled out for each sampling event. The following forms used for each type of sample. 

The originals are kept at CSU Fresno as a sample log and the data from the forms will 

be posted to the data website in the near future. 

69
Date: - - 2007 Dairy: Samplers:

Location North □ South □ West □ East □

Current Activity:

Ambient Conditions: Sun □ P. Sun □ Cloudy □ Rain: Yes □ No □

Notes:

Flux Chamber ID: Prior Chamber Cleaning: Full Wash □ Dry Wipe □ Wet Wipe □ None □

Surface Air Surface Air

10 0 Condensation: Yes □ No □

10 1

10 2

10 3

10 4

10 5

Main Feed Sources:

1- 4-

2- 5-

3- 6-

Notes:

INNOVA □ Event # Sample Line Flushed □

UCI □ Canister # Sample Line Flushed □

CSUF □ Canister #

TO-17 □ Tube #

Photo Taken □

Surface Sample Taken □ Lab Number: Lab: Dairyland Laboratories Inc.

Chamber Dome: %

At TMR+0.5 h:

At TMR+3 h:

At TMR+6 h:

Length of Feed Lane (m): 

At TMR+6 h:

At TMR+3 h:

At TMR+0.5 h:

Area of Feed Lane (m2

):

Measurement Number Time Notes

Hours of Feeding:

Number of TMR Push Ups per Day:

Site Diagram

Chamber Base: %

TMR Information

Number of Feeding per Day:

Hours of TMR Push Ups:

Average Width of Feed Lane (cm):

CSUF SURFACE FLUX MEASUREMENT DATA FORM- TOTAL MIXED RATION

Temperature (°C)

Notes

Time Sweep Air 

(L/Min)

Residence 

Number

Chamber Ambient

Flux Chamber Measurements

#

Degree of Condensation:

70
Date: - - 2007 Dairy: Samplers:

Location North □ South □ West □ East □

Type of Measurement: Pile Disturbed Face □ Vertical Undisturbed Face □ Measurement Height: m

Current Activity:

Ambient Conditions: Sun □ P. Sun □ Cloudy □ Rain: Yes □ No □

Notes:

Flux Chamber ID: Prior Chamber Cleaning: Full Wash □ Dry Wipe □ Wet Wipe □ None □

Surface Air Surface Air

10 0 Condensation: Yes □ No □

10 1

10 2

10 3

10 4

10 5

Notes: Silage Density Measurements:

Height=0.9 m Height=1.8 m

Probe Depth: cm

Probe Diameter: 4.826 4.826 cm

INNOVA □ Event # Sample Line Flushed □

UCI □ Canister # Sample Line Flushed □

CSUF □ Canister #

TO-17 □ Tube #

Photo Taken □

Surface Sample Taken □ Lab Number: Lab: Dairyland Laboratories Inc.

CSUF SURFACE FLUX MEASUREMENT DATA FORM- SILAGE PILE

Temperature (°C)

Notes

Time Sweep Air 

(L/Min)

Residence 

Number

Chamber Ambient

#

Silage Information Site Diagram

Chamber Base: %

Chamber Dome: %

Type of Silage:

Dates:

Established:

Vertical Undisturbed Exposed Face:

Finished (est.):

Disturbance:

Number of Daily Disturbance:

Time of Daily Disturbance:

Degree of Condensation:

Flux Chamber Measurements

First Disturbed:

Measurement Number Time Notes

Date and Time of Last Disturbance:

Area of Exposed Surface (m2

)

Pile Disturbed Exposed Face:

71
Date: - - 2007 Dairy: Samplers:

Location North □ South □ West □ East □

Open Lot Deep Manure Pack □ Depth= cm

Open Lot Shallow Manure Pack □ Depth= cm

Bedding □ Depth= cm

Flush Lane (Pre-Flush) □ Depth= cm

Flush Lane (Post-Flush) □

Current Activity:

Ambient Conditions: Sun □ P. Sun □ Cloudy □ Rain: Yes □ No □

Notes:

Flux Chamber ID: Prior Chamber Cleaning: Full Wash □ Dry Wipe □ Wet Wipe □ None □

Surface Air Surface Air

10 0 Condensation: Yes □ No □

10 1

10 2

10 3

10 4

10 5

INNOVA □ Event # Sample Line Flushed □

UCI □ Canister # Sample Line Flushed □

CSUF □ Canister #

TO-17 □ Tube #

Photo Taken □

Surface Sample Taken □ Lab Number: Lab: Dellavalle Laboratory

Chamber Dome: %

CSUF SURFACE FLUX MEASUREMENT DATA FORM- MANURE SOURCES

Temperature (°C)

Notes

Time Sweep Air 

(L/Min)

Residence 

Number

Chamber Ambient

Flux Chamber Measurements

Chamber Base: %

Degree of Condensation:

#

Measurement Number Time Notes

Notes Site Diagram

72
Date: - - 2007 Dairy: Samplers:

Location North □ South □ West □ East □

Current Activity:

Ambient Conditions: Sun □ P. Sun □ Cloudy □ Rain: Yes □ No □

Notes:

Flux Chamber ID: Prior Chamber Cleaning: Full Wash □ Dry Wipe □ Wet Wipe □ None □

Surface Air Surface Air

10 0 Condensation: Yes □ No □

10 1

10 2

10 3

10 4

10 5

Main Feed Sources:

1- 4-

2- 5-

3- 6-

Notes:

INNOVA □ Event # Sample Line Flushed □

UCI □ Canister # Sample Line Flushed □

CSUF □ Canister #

TO-17 □ Tube #

Photo Taken □

Surface Sample Taken □ Lab Number: Lab: Dairyland Laboratories Inc.

At TMR+6 h:

At TMR+4 h:

At TMR+2 h:

At TMR+0.5 h: At TMR+1 h:

At TMR+3 h:

At TMR+5 h:

At TMR+4 h: At TMR+5 h:

At TMR+6 h:

CSUF SURFACE FLUX MEASUREMENT DATA FORM- TOTAL MIXED RATION, SPECIAL SAMPLING (2 DAIRIES)

Temperature (°C)

Notes

Time Sweep Air 

(L/Min)

Residence 

Number

Chamber Ambient

Flux Chamber Measurements

#

Site Diagram

Chamber Base: %

Degree of Condensation:

Chamber Dome: %

Area of Feed Lane (m2

):

Hours of TMR Push Ups:

Length of Feed Lane (m): 

Hours of Feeding:

Number of TMR Push Ups per Day:

At TMR+2 h:

At TMR+0.5 h: At TMR+1 h:

At TMR+3 h:

Measurement Number Time Notes

Average Width of Feed Lane (cm):

TMR Information

Number of Feeding per Day:

73
Date: - - 2007 Dairy: Samplers:

Location North □ South □ West □ East □

Type of Measurement: Pile Disturbed Face □ Vertical Undisturbed Face □ Measurement Height: m

Current Activity:

Ambient Conditions: Sun □ P. Sun □ Cloudy □ Rain: Yes □ No □

Notes:

Flux Chamber ID: Prior Chamber Cleaning: Full Wash □ Dry Wipe □ Wet Wipe □ None □

Surface Air Surface Air

10 0 Condensation: Yes □ No □

10 1

10 2

10 3

10 4

10 5

Notes: Silage Density Measurements:

Height=0.9 m Height=1.8 m

Probe Depth: cm

Probe Diameter: 4.826 4.826 cm

INNOVA □ Event # Sample Line Flushed □

UCI □ Canister # Sample Line Flushed □

CSUF □ Canister #

TO-17 □ Tube #

Photo Taken □

Surface Sample Taken □ Lab Number: Lab: Dairyland Laboratories Inc.

Degree of Condensation:

Flux Chamber Measurements

First Disturbed:

Measurement Number Time Notes

Date and Time of Last Disturbance:

Area of Exposed Surface (m2

)

Pile Disturbed Exposed Face:

Type of Silage:

Dates:

Established:

Vertical Undisturbed Exposed Face:

Finished (est.):

Disturbance:

Number of Daily Disturbance:

Time of Daily Disturbance:

Silage Information Site Diagram

Chamber Base: %

Chamber Dome: %

CSUF SURFACE FLUX MEASUREMENT DATA FORM- SILAGE PILE, SPECIAL SAMPLING (2 DAIRIES)

Temperature (°C)

Notes

Time Sweep Air 

(L/Min)

Residence 

Number

Chamber Ambient

#

74
Date: - - 2007 Dairy: Samplers:

Location North □ South □ West □ East □

Feed Source:

Current Activity:

Ambient Conditions: Sun □ P. Sun □ Cloudy □ Rain: Yes □ No □

Notes:

Flux Chamber ID: Prior Chamber Cleaning: Full Wash □ Dry Wipe □ Wet Wipe □ None □

Surface Air Surface Air

10 0 Condensation: Yes □ No □

10 1

10 2

10 3

10 4

10 5

INNOVA □ Event # Sample Line Flushed □

UCI □ Canister # Sample Line Flushed □

CSUF □ Canister #

TO-17 □ Tube #

Photo Taken □

Surface Sample Taken □ Lab Number: Lab: Dairyland Laboratories Inc.

Notes:

Degree of Condensation:

Flux Chamber Measurements

First Disturbed:

Date and Time of Last Disturbance:

Area of Exposed Surface (m2

)

Pile Disturbed Exposed Face:

Finished (est.):

Disturbance:

Number of Daily Disturbance:

Measurement Number Time Notes

Vertical Undisturbed Exposed Face:

Commodity Information

Time of Daily Disturbance:

Type of Commodity:

Dates:

Hauled:

Site Diagram

Chamber Base: %

Chamber Dome: %

CSUF SURFACE FLUX MEASUREMENT DATA FORM- MAIN COMMODITIES, SPECIAL SAMPLING (2 DAIRIES)

Temperature (°C)

Notes

Time Sweep Air 

(L/Min)

Residence 

Number

Chamber Ambient

#

75
INNOVA Calibration Data (8-9-07) 

76
77

INNOVA Calibration Data (8-9-07)