The Carbon Footprint of a 5000-Milking-Head Dairy Operation in Central Texas

Abstract

Texas is the third-largest milk-producing state in the U.S., with Central Texas being the second-largest milk-producing region in Texas. The average size of a dairy herd in Texas is 1829 cows. In Central Texas alone, there are 88,000 dairy cows. However, there is a lack of environmental impact research for this region. The overall objective of this case study is to evaluate the net carbon and carbon equivalent balances for a large dairy operation in Central Texas. The dairy selected for this study has a herd size of 5000 milking cows. The data assumptions were made regarding the selected dairy’s performance and production for the 2021 production year. These data include herd size and management, milk production, crop production, feed purchases, and on-farm energy usage. The USDA-Integrated Farm System Model (IFSM) was used to estimate the daily and annual greenhouse gas emissions and environmental footprint of the dairy by quantifying the operation’s carbon footprint based on its 2021 performance and management practices. Research outcomes identify and quantify sources of greenhouse gas (GHG) emissions produced on the dairy farm. Additionally, the carbon footprint (CF) was determined by estimating the CO₂ equivalents (CO₂-eq) emitted or sunk from animal and manure emissions, direct and indirect land emissions, net biogenic and anthropogenic CO₂ emissions, and the production of resource inputs. The results of this case study indicated that the carbon footprint (CF) of the 5000-milking-head dairy in Central Texas was 0.40 lb. of CO₂ per lb. of fat- and protein-corrected milk (FPCM) when considering biogenic CO₂ and 0.83 lb. of CO₂ per lb. of FPCM without biogenic CO₂.

1. Introduction

Climate change can be defined as the long-term shift in temperature and weather patterns due to an increase in heat-trapping gases in the atmosphere. These gases are referred to as greenhouse gases (GHGs). This issue is viewed as a global concern, and efforts are being made to reduce the impact various sectors have on GHG emissions and climate change. Carbon dioxide (CO₂) is one of the most important greenhouse gases because it absorbs and then re-radiates heat, keeping the global surface temperature above freezing. However, there has been an increase in atmospheric CO₂, which has led to an increase in the global surface temperature [1]. According to the Bulletin of the American Meteorological Society’s global climate report, the seven warmest years since the mid to late 1800s occurred from 2015 to 2021 [2]. CO₂ comes from various sources, such as animals, the extraction and burning of fossil fuels, farming, wildfires, manufacturing, deforestation, etc. Most activities impact atmospheric CO₂ by either emitting it into the atmosphere or capturing it on earth [3]. Much like CO₂, there are several other greenhouse gases that impact the atmosphere. These gases include, but are not limited to, methane (CH₄) and nitrous oxide (N₂O). They are often referred to and measured as CO₂ equivalents (CO₂-eq). CO₂-eq is the metric measurement used to estimate or compare the emissions from other GHGs based on their global warming potential (GWP) [4]. For example, at a 100-year GWP, every 1 kilogram (kg) of CH₄ is equivalent to 25 kg of CO₂, and every 1 kg of N₂O is equivalent to 298 kg of CO₂ [5,6].

GHG emissions can be classified into several sectors. Some of these sectors include energy, industry, buildings, transportation, and, lastly, agriculture, forestry, and other land use (AFOLU) [7]. AFOLU was estimated to be responsible for 18.4% of global GHG emissions [8] and 11.2% of total U.S. emissions in 2020 [9]. Figure 1 takes a closer look at GHG emissions for the U.S. in 2019 by quantifying GHG emissions for each of the 11 identified sectors [8]. The GHG emissions were converted into CO₂-eq and measured in millions of tons (Mt). The agriculture sector was ranked 6th, emitting 381.37 Mt of CO₂-eq, respectively. Figure 2 presents the allocation and quantification of CO₂-eq emissions for the agriculture sector. The categories represent groups pertaining to crop and livestock production and management activities [10].

A focus has been placed on the dairy industry, as it is estimated to contribute 1.3 to 1.5% of total U.S. emissions [11,12]. Cattle alone are estimated to produce about 11% of all human-induced GHG emissions globally [13]. In 2020, the Net Zero Initiative was launched within the U.S. dairy community. This initiative encourages dairy operations to adopt technology and practices to achieve an industrywide “net zero” GHG emission status by 2050 [14,15]. Due to initiatives like the Net Zero Initiative, measuring GHG emissions has become more popular at the operational source, industry, state, national, and global scales. Several whole-farm models have been developed to help estimate the GHG emissions, considering that about 72% of emissions occur during production before the milk has left the farm [16]. Listed are some of the modeling systems developed: AgRE Calc, COMET-Farm, Cool Farm Tool, DairyGEM, DairyMod, and several others [17]. The IPCC developed the GWP, or “carbon footprint (CF)”, metric to standardize emissions from multiple gases [18]. CFs are used to evaluate the potential climate impact of products. They can be calculated using life-cycle assessment (LCA) methodology, which quantifies the impact of goods and services over their full life cycle [18].

In 2021, Texas ranked fourth in U.S. milk production. With 335 Grade A dairy farms and an estimated 625,000 cows, 15.6 billion pounds of milk were produced [9]. According to the Texas Association of Dairymen, the Texas dairy industry contributed USD 39.6 billion to the U.S. economy. The direct and indirect economic impact on the economy was USD 50.3 billion, which includes local, state, and federal taxes as well as wages [19]. Dairy farming is the state’s second-largest agricultural commodity behind the cattle industry [20], generating 2.8% of Texas’ GDP in 2021 [21]. A trend throughout the history of the U.S. and Texas dairy industries is consolidation, resulting in fewer and larger farms [22]. The USDA reported that the number of dairy farms decreased from 59,130 to 37,468 between 2007 and 2018, but herd size increased [22].

The Panhandle region of Texas accounts for 80% of the state’s dairy industry [20]. Other top milk-producing counties include Erath and Comanche, located in Central Texas, and Hopkins County, located in Northeast Texas. Northeast Texas was once the leading region for dairy production; however, the amount of rainfall and humidity were not the most ideal conditions for dairy operations [20]. In the 1980s, Central Texas dairy production surpassed Northeast Texas production [23]. By the 1990s, Erath County had become the leading dairy-producing county in the state [24]. Around the 21st century, the dairy industry expanded to the Texas High Plains as several producers from Central Texas and surrounding states moved to that region [25]. By 2010, the Panhandle had become the number one milk-producing region of the state [26]. The drier climate provides a better quality of life for the dairy cattle, and the cheaper land provides a better quality of life for the dairymen. The consolidation of the dairy industry, as discussed by Son, Richard, and Lambert [22], is one of the factors that has influenced Texas dairy producers to re-locate. The availability of land in the Texas Panhandle provides dairy producers with the opportunity to increase herd size and overall profitability as a result of economies of scale [27]. The NASS [28] reported that the costs of production for dairies with 1000–1999 heads were 16% and 30%, respectively, lower than farms with 200–499 heads and 100–199 heads.

In order to demonstrate these trends leading to further analysis, the literature relevant to this paper combines a particular focus on three main parts. The first part is the environmental assessment of the dairy industry. The U.S. dairy industry has set goals to become carbon neutral or better, optimize water use while maximizing recycling, and improve water quality by optimizing the utilization of manure and nutrients by 2050. Studies evaluating the environmental impacts of dairy production have been performed for dairy operations that are general in nature or, at the other extreme, specific to location or production system. Rotz et al. [11] performed a study to build on a regional approach to quantify the important environmental footprints of milk production on dairy farms throughout six regions of the U.S., which include the Northeast, Southeast, Midwest, South Central, Northwest, and Southwest, according to climate, soils, feed production, and animal management practices. For each region, process-level simulations of individual systems provided data on performance and environmental impacts. Regional estimates were used to calculate the national estimate by weighing the footprints of individual production systems by the portion of milk they contributed. A partial LCA was performed using the Integrated Farm System Model (IFSM) to simulate and examine the performance, environmental impacts, and economics of dairy systems.

According to Rotz et al. [11], the total national GHG emissions from dairy farms are 99,000 ± 8480 kg CO₂. The Midwest region accounted for one-third of national emissions. The Southwest region accounted for 27% of national emissions. Enteric emissions contributed 45% [29], and manure emissions contributed 26% of the total carbon footprint. Compared to the 2018 estimated national GHG emissions, the dairy industry accounted for 1.5% of total U.S. GHG emissions. NH₃ is the most concerning emission coming from dairy farms, as it accounts for 24% of all NH₃ emissions in the U.S. Due to the diversity of dairy operations, mitigation strategies need to be tailored to meet the individual needs of the farms. Results indicated that mitigation needs should focus on reducing NH₃ emissions from manure sources, reducing water and energy use within feed production, and reducing CH₄ emissions from enteric and long-term manure storage sources.

Within the context of a full environmental assessment, there is specific literature on the carbon footprint (CF) of milk production, the second major literature focus. Rotz [17] models the GHG emissions from dairy farms and claims that livestock contributes 11% [17] to 14.5% [30] of all GHG emissions and that dairy cattle are responsible for 1.3% of the U.S. total and 20% of the total sector emissions. The study also claims that 72% of emissions happen before the milk has left the farm. The milk CF has been shown to be reduced by increasing milk production per cow rather than by reducing daily emissions of GHGs [31]. Enteric CH₄, manure management, and feed production contribute to approximately 70% of the United States milk CF. The CF of milk production may vary depending on the choice of functional unit, system boundary, LCA methodology, methods of calculations, methods of co-product allocation, and other assumptions. Vida and Tedesco [30] sought to empirically assess the CF of milk production for a dairy farming system that intentionally directs its efforts to reduce environmental impact through mitigation option strategies in order to evaluate the environmental impact of milk production. The case study suggested that enteric CH₄ was the greatest source of GHG emissions. Nutrition and feeding approaches could potentially reduce CH₄ emissions by 2.5 to 15%. N₂O was the second-largest source of GHG emissions due to soil treatments with organic and inorganic fertilizer. The total farm GHG emissions per year were 8592 tons of CO₂ equivalents. The CF of the case farm located in Italy was 1.11 kg CO₂-eq/kg fat- and protein-corrected milk (FPCM) [30].

The third major part of the literature discusses an ever-growing trend in the dairy industry—this inverted relationship noted by Lauer, Hansen, Lamers, and Thrän [32] in their study shows that as the number of Idaho dairy farms decreased, the number of dairy cows increased from 153,000 to 592,000 cows from 2012 to 2017. This is a trend that has been seen in all of U.S. dairy production [33]. As a result of this trend, there is an urgent push to reduce the environmental impact of the dairy industry. A potential solution is the implementation of an anerobic digestion system (ADS), which converts manure waste into biogas or biomethane. Biogas produces electricity and heat. Biomethane is biogas that is converted into renewable natural gas and can be injected into pipelines. Through a non-linear optimization model, the study analyzed the economic viability of on-farm biogas use and the injection of biomethane into the natural gas grid by optimizing the net present value (NPV) of anerobic digestion. The results of the study indicated that farm size has a substantial influence on the choice of manure management practices adopted by farms [34]. For a dairy farm with 3700 or more cows, the conversion of biogas to biomethane becomes more economically feasible. Additionally, for dairy farms with a herd between 3700 and 5900, a complete mix digester achieves a higher NPV than other types of ADSs. However, for dairy farms with a herd size greater than 6000, the covered lagoon digestor achieves the highest NPV [33]. With consideration of the trend discussed previously, it may be inferred that the adoption of a covered lagoon ADS that produces biomethane will reduce a dairy farm’s environmental impact as well as be economically feasible. Results from other studies also indicated that ADSs were viable; however, significant government support is still needed to yield financial returns that are attractive to investors [35].

The existing literature discusses the U.S. dairy industry as a whole, as well as an Italy dairy case study and the Idaho dairy industry in regards to GHG emissions, carbon footprint, and farm management economics. However, through a comprehensive literature review process, it has been determined that there is a lack of environmental research pertaining to the Texas dairy industry. Firstly, this paper discusses the farm structure and management of a large Texas dairy operation. Secondly, the environmental impact of the dairy farm is explained with respect to on-farm activities including crop and milk production, manure management, and housing facilities. Lastly, the research presented in this paper provides a breakdown of a dairy operation’s carbon footprint.

The overall objectives of this study were to evaluate the environmental impact of a 5000-milking-head dairy operation located in Central Texas as well as the environmental impact of a similar dairy system located in the Panhandle region of Texas. More specifically, this study will analyze the annual emission and allocation of GHGs in addition to the CO₂-eq footprints of animal emissions, manure emissions, direct and indirect land emissions, net biogenic CO₂ emissions, anthropogenic CO₂ emissions, and the production of resource inputs. Lastly, this study will discuss the economic analysis resulting from the modeling system.

2. Materials and Methods

2.1. Integrated Farm System Model Version 4.7

The model being used to compute the carbon footprint is the Integrated Farm System Model (IFSM) version 4.7, developed by the Agricultural Research Service (ARS) of the USDA. IFSM 4.7 is a process-based, whole-farm model used to assess and compare the environmental and economic sustainability of farming systems. Initially, the tool was developed for the comprehensive evaluation and comparison of dairy production systems. Now, it can be utilized in crop, dairy, and beef production systems. Due to the complexity of the production systems, the whole farm model is composed of several sub-models with built-in subroutines that organize the farm activities and identify representative inputs for each type of system. The subroutines organize the processes that take place within the sub-models [36].

2.1.1. IFSM 4.7 Model Input

The IFSM 4.7 starts by collecting input information, which includes farm type, machinery, and weather, that is supplied to the user as files. Based on the type of operation chosen, the input files the user chooses will automatically set the parameters. The parameters are presented in the following divided sub models: crop and soil, grazing, machinery, tillage and planting, harvest, feed and grain storage, animal and feeding, manure, and economic information. For example, the machinery file selected will link appropriate machinery parameters into operations for tillage, planting, harvesting, and feeding. However, most of the input parameters can be modified to best represent the specific farming systems being analyzed [36].

With inputs identified, the simulation is performed using a weather data file representative of the general location of the operation being analyzed. The weather data file selected contains many years of daily weather data for the specified location.

2.1.2. IFSM 4.7 Model Output

The model presents the results in four separate files: the summary output, the full report, the optional output, and parameter tables. (1) The summary output file is made up of several tables that show the average performance, costs, and returns over the number of years simulated. The values include the mean and standard deviation over all simulated years of crop yields, feeds produced, feeds purchased and sold, manure produced, a summary of feed production ingredients, manure handling, and other farm costs, and the profitability of the farm. (2) The full report provides the same information; however, values are given for each simulated year. (3) Upon request, the optional output tables provide a closer inspection of how the components of the full simulation are functioning, which includes the daily values of crop growth and development, monthly summaries of suitable days for field work, a daily summary of forage harvest operations, annual summaries of machine, fuel, and labor use, and the ingredients of animal feeding components. (4) The parameter tables may also be requested, which summarize the input parameters specified for a given simulation: crop, soil, tillage, and planting parameters; grazing parameters; machine parameters; and economic parameters.

2.1.3. IFSM 4.7 Model Algorithm

Figure 3 illustrates the algorithm of the IFSM 4.7. The model starts by integrating farm and machinery file input data depending on farm type and the size of the operation. Next, weather input data are incorporated based on farm location. From there, farm-specific inputs are entered regarding production levels and management practices. Once all input data for a given year have been entered, additional operating years may be entered. If no other data are needed, the model simulates farm results and summarizes data based on the information entered into the model.

2.1.4. IFSM 4.7 Carbon Footprint

In addition to the model outputs presented in the model output subsection, the IFSM assesses the environmental footprints of water use, reactive N loss, energy use, and carbon emissions. Several other environmental impacts are also simulated. However, this study will focus on analyzing the carbon emissions, or “carbon footprint”. The carbon footprint comprises the total GHG emissions expressed in CO₂-eq. To measure CO₂-eq the values for CH₄ and N₂O are based on their 100-year global warming potential (GWP) [6]. The 100-year GWP values used for CH₄ and N₂O are 25 and 298 CO₂-eq/kg, respectively [36].

According to the IFSM 4.7, the carbon footprint is the result of dividing the total amount of greenhouse gases produced by the net amount of greenhouse gases assimilated and emitted during production. For dairy operations, the product is fat- and protein-corrected milk. Net emissions are determined through a partial LCA of the production system. A partial LCA is an LCA that focuses on the GHG emissions of a product up to the farm gate, whereas a whole-system LCA focuses on the GHG emissions of a product from the farm level or gate to the consumer [37]. GHG emissions other than CO₂ are converted into their respective CO₂-eq units. Net emissions are calculated by summing the emissions of CO₂, CH₄, and N₂O from primary and secondary sources, then subtracting the net CO₂ assimilated in feed production. Emissions from primary sources are those emitted from the farm or production system during the production process. Secondary emissions include those that occur during the manufacture or production of resources used in the production system (machinery, fuel, fertilizer, etc.). Figure 4 is a representation of the sources and allocation of GHG emissions from a dairy farm operation.

2.2. Data

2.2.1. Dairy Farm Input Parameters

The Central Texas dairy operation consists of Holstein dairy cows. Herd size is composed of 5000 milking cows or heads, 1150 dry cows or heifers older than one year, and 400 heifers younger than one year. Lactating cows are housed in a mechanically ventilated, free-stall confinement barn. Dry cows and heifers are housed in open lots. This assumption was made based on data collected from an anonymous dairy operation located in Central Texas.

Lactating cows are taken to the barn’s rotary parlor, where they are milked twice per day. The cows spend an average of 10 min milking per day. The operation’s total annual milk production is 131,424,000 lbs., which is about 72 lbs. per cow per day and an estimated 26,285 lbs. per cow per year. This assumption was made based on data collected from an anonymous dairy operation located in Central Texas.

A slurry lagoon is used to store manure for 6 months until it is used to spread slurry on cropland and fields. The average diameter and depth of the lagoon are 100 and 15 feet, respectively. This assumption was made based on data collected from an anonymous dairy operation located in Central Texas.

In a production year, the dairy farm harvests two cuts of corn silage and one cut of grass silage. The land allocation for crop production in terms of acreage for corn and grass silage is about 1200 acres for each crop. Each cut produces about 13 tons of corn and grass silage per acre. Additional feed was purchased to meet the dietary needs of the cattle. This assumption was made based on data collected from an anonymous dairy operation located in Central Texas.

Table 1. Data input parameters representing the Central Texas dairy operation.

Data Input Parameter	Value	Units
Herd/facility parameters
Animal type	Holstein
Number of lactating animals	5000
Number of young stock (over 1 year)	1150
Number of young stock (under 1 year)	400
Milk production
Target milk production per cow	26,285	lb/cow/year
Target milk production—TOTAL	131,524,000	lb/year
Animal facilities
Milking center	Double twenty-four parlor
Cow housing	Free stall barn, mechanically ventilated
Heifer housing	Calf hutches
Dry cows/older heifers	Open lot
Feed facility	Commodity shed
Labor for milking and animal handling	10	minutes/cow/day
Feeding
Grain	Loader and mixer wagon
Silage	Loader and mixer wagon
Hay	Tub grinder
Ration constituents
Minimum dry hay in rations	50% of forage
Relative forage to grain ratio	Low
Crude protein supplement	Cotton seed meal
Undegradable protein supplement	Distillers grain
Phosphorus feeding level in rations
Early lactation	0.39%
Mid lactation	0.42%
Late lactation	0.42%
Dry cow	0.30%
Young heifer	0.42%
Older heifer	0.38%
Protein feeding level in rations
Early lactation	16.60%
Mid lactation	17.20%
Late lactation	17.20%
Dry cow	15%
Young heifer	14.20%
Older heifer	13.20%

expresses the input parameters discussed in this section (Section 2.2.1).

2.2.2. Weather and Machinery Data

The IFSM weather data file is specific to location and contains 25 years’ worth of daily historical data. The weather file (TX-ErathCounty) was selected as it contains historical weather data from 1988 to 2012. Daily data include total daily solar radiation, mean temperature (°C), maximum temperature (°C), minimum temperature (°C), total precipitation, and average wind speed. Summary monthly statistics of weather data for the study area are provided in

Table 2. Monthly statistics of weather parameters at the study location.

Statistic	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
Average monthly maximum air temp (°C)	14.74	16.18	20.71	25.36	28.81	32.59	34.95	35.31	31.45	26.26	20.15	14.95
Average monthly min air temp (°C)	0.33	2.42	6.8	10.96	16.04	20.13	21.52	21.35	17.52	11.69	6.15	0.90
Monthly average standard deviation of daily max temp (°C)	6.58	7.24	5.84	4.56	3.60	2.43	2.11	2.53	3.6	4.52	5.65	6.46
Monthly average standard deviation of daily min temp (°C)	4.39	4.82	4.90	4.36	3.55	2.02	1.32	1.58	3.61	4.57	5.21	4.88
Average monthly precipitation (mm)	43.4	53.4	67.9	60.6	114.9	104.4	51.6	61.4	67.8	80	53.8	41.8
Monthly standard deviation of daily precipitation (mm)	4.51	4.93	5.66	5.42	8.30	8.49	4.84	5.34	6.07	7.02	4.62	3.58
Monthly skew coefficient for daily precipitation	3.6	3.3	3.1	3.1	2.8	3.1	3.6	3.2	3.1	3.3	3.3	3.3
Monthly probability of wet day after dry day	0.089	0.109	0.13	0.13	0.129	0.114	0.096	0.106	0.105	0.103	0.085	0.099
Monthly probability of wet day after wet day	0.098	0.108	0.122	0.109	0.182	0.159	0.108	0.119	0.123	0.137	0.125	0.108
Average number days of rain per month (days)	6.0	6.7	8.1	7.3	10.0	8.6	6.6	7.2	7.2	7.4	6.6	6.6

. The machinery component is used to determine the performance and resource rates for all machinery components on the farm.

The machinery parameter file is selected based on farm type and size of equipment. It is composed of predetermined “default” values that are representative of the operation type and size. Machine draft parameters represent machine-specific parameters that are obtained from the American Society of Agricultural Engineers’ (ASAE) Machinery Management Standards [39]. Default values may be modified. For the purpose of this study, the machinery file (LargeFarm.mch) was selected, and no modifications were made. Relationships based upon operation type, size of equipment, and machinery parameters specified to describe each machine are used by the IFSM 4.7 to predict the performance and power requirements of each operation [36].

3. Results

3.1. Annual GHG Emissions

As part of the environmental impact assessment performed by the IFSM 4.7, daily and yearly estimates of GHG emissions were calculated.

Table 3. Annual greenhouse gas emission results determined by the IFSM.

Total Annual GHG Allocation and Emissions
	lb/Cow	lb
Ammonia
Housing facility	99.9	499,699
Manure storage	104.5	522,334
Field application	16.9	84,411
Total farm	221.3	1,106,444
Hydrogen sulfide
Housing facility	0.7	3600
Manure storage	0.1	283
Field application	0.6	2892
Total farm	1.4	6775
Ozone forming VOC
Silo face	5.4	26,911
Silage feeding	12.4	61,967
Housing manure	0.9	4491
Manure storage	0.5	2687
Field application	1	4953
Total farm	20.2	101,009
Methane
Animal	307.2	1,535,836
Housing manure	11.2	56,095
Manure storage	120.4	602,181
Field application	0.1	587
Total farm	438.9	2,194,699
Nitrous oxide
Animal	0.4	1904
Housing manure	2.1	10,579
Manure storage	2.8	14,120
Farmland	0.5	2394
Indirect sources	3	15,243
Total farm	8.8	44,240
Biogenic CO2
Housing facility	13,484.70	67,423,288
Manure storage	132.3	661,682
Net land and feed	−24,476.10	−122,380,680
Total farm	−10,859.10	−54,295,724
Anthropogenic CO2	397.50	1,987,294

identifies and allocates the specific GHGs produced on the dairy farm as well as the total annual emissions based on farm activities. Both total pounds and pounds per animal are available for emission results.

Ammonia (NH₃) is a GHG typically produced from animal manure. The sources of ammonia emissions for the dairy farm include animal housing, manure storage, and manure application to fields. The average daily NH₃ emission from the housing facility is estimated to be 1369 lbs., or 0.274 lbs. per cow per day. Annually, that is equivalent to 499,699 lbs. of NH₃, or 99.9 lbs. per cow per year. According to the model, manure storage is the greatest source of NH₃ emissions for the operation, producing 522,334 lbs. of NH₃ annually, which is about 104.5 lbs. per cow per year produced. The application of manure to fields emits less NH₃ than the other sources; however, it continues to emit an estimated 84,411 lbs. annually. Taking into consideration the listed NH₃ sources, the total annual NH₃ emissions for the dairy farm are estimated to be 1,106,444 lbs., or 221.3 lbs. per cow per year.

Hydrogen sulfide (H₂S) is another GHG produced from manure. Specifically, it is produced during the anaerobic decomposition of organic matter in manure. Sources of H₂S emissions also include animal housing, manure storage, and the application of manure to fields. The housing facility is the largest source of H₂S emissions, with an annual total of 3600 lbs. of H₂S produced. The field application of manure is also a major source of H₂S emissions, producing an estimated 2892 lbs. of H₂S annually. According to the model, manure storage contributes the least to H₂S emissions, with an annual total of 283 lbs. Based on the sources of H₂S emissions, the farm produces 6775 total lbs. of H₂S per year.

Ozone-forming volatile organic compound (VOC) emissions contribute to the formation of ground-level smog. Due to manure and silage being major sources of VOC emissions, emission estimates are provided for the following sources: silo faces, silage feeding, housing manure, manure storage, and field application. Silage-associated sources, silo face and silage feeding, emit the greatest amount of VOCs at an estimated total of 26,911 and 61,967 lbs. per year. Manure-associated sources, including housing manure, manure storage, and field application, contribute an estimated 4491, 2687, and 4953 lbs. of VOCs per year. Annually, the farm emits an estimated total of 101,009 lbs. of VOCs.

Methane (CH₄) is a major contributor to GHG emissions. The digestive processes of livestock, manure production and storage, and the application of manure to fields all produce and emit CH₄. The enteric CH₄ produced during animal digestion emits an estimated annual total of 1,535,836 lbs. That is equal to 307.2 lbs. of CH₄ per animal per year. Manure-associated sources of CH₄ emissions include housing manure, manure storage, and field application. Manure storage is the second major source of CH₄ emissions, with an estimated annual total of 602,181 lbs. produced. Other manure-associated sources, such as housing manure and field application, contribute an estimated total of 56,095 and 587 lbs. of CH₄ annually. Considering the emissions of CH₄ from each identified source, the dairy farm emits an estimated 2,194,699 lbs. of CH₄ per year.

Nitrous oxide (N₂O) is a powerful GHG with a GWP 298 times that of CO₂ [17]. Sources of N₂O emissions for the dairy farm operation estimated in the IFSM include livestock, housing manure, manure storage, farmland, and indirect sources. Livestock produce an estimated 0.4 lbs. of N₂O per year per animal, totaling 1904 lbs. Manure-associated sources of N₂O, such as housing manure and manure storage, produce an estimated 10,579 and 14,120 lbs. of N₂O annually. Additionally, farmland is a source of N₂O emissions, with an estimated annual total contribution of 2394 lbs. This emission is stimulated by the deposit of urine in the soil. Lastly, an estimated annual total of 15,243 lbs. of N₂O comes from indirect sources. Indirect sources may include, but are not limited to, nitrification and denitrification processes in the soil used to produce feed crops and pasture [17]. The dairy farm’s estimated total annual N₂O emissions are 44,240 lbs.

Biogenic CO₂ can be defined as the natural cycle of carbon, also known as the recycling of carbon within the environment [17], which is the process of storing it in biomass and losing it in respiration. The biogenic carbon dioxide section represents and quantifies the activities of the partial life cycle that relate to the natural carbon cycle. The sources that represent the natural carbon cycle for the dairy include the housing facility, manure storage, net land, and feed. The results from the modeling indicate that the housing facility source emits an estimated total of 67,423,288 lbs. of CO₂ annually. Manure storage, like the housing facility, is an emitter of CO₂, with an estimated total annual emission of 661,682 lbs. However, this may not always be the case for a dairy operation, as results depend on manure storage and handling practices. Lastly, land and feed production are part of the natural carbon cycle that sinks CO₂ as it is absorbed by crops and sequestered in soil through the process of photosynthesis. The results indicate land and feed production sink an estimated 122,380,680 lbs. of CO₂ per year. Because of the impact land and feed production have on the biogenic CO₂ emission section, the dairy operation absorbs or sequesters an estimated annual total of 54,295,724 lbs. of CO₂.

The final result presented in Table 3 is the CO₂ emission from anthropogenic sources. A living organism produces biogenic CO₂, whereas human activity produces anthropogenic CO₂ [17]. Examples of these sources include the combustion of fossil fuels or the application of lime to farmlands. Taking human impact into consideration, the estimated annual anthropogenic CO₂ emissions for the dairy operation are 1,987,294 lbs. of CO₂. This value is calculated based on the estimated amount of fuel used in the production system.

3.2. Carbon Footprint

According to the IFSM 4.7, the CF is the result of dividing the total amount of GHGs produced by the net amount of GHGs assimilated and emitted during production. N₂O and CH₄ emissions were converted into CO₂-eq units according to their GWP indexes. The sum of CO₂, N₂O, and CH₄ emissions was subtracted from the CO₂ assimilated in feed production to give the net emissions of the production system. Emissions account for both primary and secondary sources. The primary sources are the GHG emissions produced or emitted from the dairy operation during the production process. Secondary sources are the emissions produced or emitted during the production of fuel, electricity, fertilizer, pesticides, and plastic used in feed production and animal maintenance.

Table 4. Carbon footprint results determined by the IFSM 4.7.

Greenhouse Gas Emissions (CO2-eq)
	Unit	Mean
Animal emissions	lb	43,508,036
Manure emissions	lb	24,993,304
Direct and indirect land emissions	lb	4,673,748
Net biogenic CO2 emissions	lb	−54,295,740
Anthropogenic CO2 emissions	lb	1,987,294
Production of resource inputs	lb	34,022,084
Not allocated to milk production	lb	−8,695,361
Carbon footprint without biogenic CO2	lb/lb FPCM	0.83
Carbon footprint with biogenic CO2	lb/lb FPCM	0.40
Carbon footprint without biogenic CO2	lb/131,524,000 FPCM	43,508,036
Carbon footprint with biogenic CO2	lb/131,524,000 FPCM	24,993,304

presents the carbon footprint results estimated by the IFSM 4.7.

The CF is described by the measurement of CO₂ and CO₂-eq emissions in pounds for the following “big picture” sources: animals, manure, land, biogenic, anthropogenic, resource inputs, and products exported from the farm. The following information describes the contribution each source has to the CF of the dairy operation being studied. The average annual GHG emissions produced from animals and manure are estimated to be 43,508,036 and 24,993,304 lbs. of CO₂-eq. The estimated average direct and indirect land emissions are 4,673,748 lbs. of CO₂-eq. As previously discussed in Section 4.1, CO₂ is either classified as biogenic (the natural cycle of CO₂ through living organisms) or anthropogenic (produced from human activities). The net biogenic CO₂ emission results indicate it to be a GHG sink sinking an estimated average of 54,295,740 lbs. of CO₂-eq. However, due to the man-made nature of anthropogenic CO₂, approximately 1,987,294 lbs. of CO₂-eq are emitted. The GHG emission source production of resource inputs accounts for the inputs used during production, such as fuel, electricity, machinery, fertilizer, pesticides, seeds, and plastic. The production of resource inputs emits an estimated 34,022,084 lbs. of CO₂-eq. Lastly, the GHG source “not allocated to milk production” is estimated to sink 8,695,361 lbs. of CO₂-eq.

The overall CF calculation of the dairy is measured by pounds of CO₂ per pound of fat- and protein-corrected milk (FPCM). Two CFs are calculated: one with biogenic CO₂ and one without biogenic CO₂. The CF without biogenic CO₂ represents solely the GHG emissions produced or emitted by the farm during production. The CF with biogenic CO₂ takes into consideration all possible sources and sinks of the natural carbon cycle and the dairy production system. Due to the dairy CF calculation being based on milk production, the GHG source identified as “not allocated to milk production” was not included in the CF calculation. The calculated CF of the Central Texas dairy operation without and with biogenic CO₂ is 0.83 and 0.40 lbs. of CO₂-eq per lb. of FPCM, respectively. The CF without biogenic CO₂ falls in between two partial life-cycle studies performed by McGeough, Little, and Janzen [40] and Aguirre-Villegas, Passos-Fonseca, and Reinemann [40]. The studies determined the CFs to be 0.92 lb. CO₂ per lb. of FPCM [40] and 0.63 to 0.77 lb. CO₂ per lb. of FPCM [41].

To provide a whole-farm perspective, the per-unit CF data were used to compute total CO₂ emissions for the entire farm. Using recorded milk production data, the whole-farm CO₂ emissions without biogenic CO₂ were computed simply as shown in Table 4.

$${TC}_w=NY{E}_w$$

(1)

where ${TC}_w$ are total CO₂ emissions without biogenic CO₂, $N$ is the number of milking cows on the farm, $Y$ is the milk yield in lbs/milking cow/year, and $E_w$ are the per unit CO₂ emissions per lb. of FPCM without biogenic CO₂. Similarly, total emissions for the case of biogenic CO₂ are calculated using a similar Formula (2), as indicated below:

$${TC}_b=NY{E}_b$$

(2)

where ${TC}_b$ are total CO₂ emissions with biogenic CO₂, and $E_b$ are the per unit CO₂ emissions per lb. of FPCM with biogenic CO₂.

The number of milking cows has already been specified above as 5000. Production records indicate that annual milk production per cow is 26,285 lbs. of FPCM produced per cow per year. Thus, using the data presented in Table 4, the total CO₂ equivalent emissions with and without biogenic CO₂ are, respectively,

$${TC}_w=(5000\mathit{cows}\times \mathrm{26,285}\mathit{lbs}.\mathit{of}\mathit{FPCM}/\mathit{cow})\times 0.83\mathit{lb}.\mathit{of}\mathit{CO}{}_2\mathit{per}\mathit{lb}.\mathit{of}\mathit{FPCM}=\mathrm{109,082,750}lbs.of{CO}_2$$

$${TC}_b=(5000\mathit{cows}\times \mathrm{26,285}\mathit{lbs}.\mathit{of}\mathit{FPCM}/\mathit{cow})\times 0.40\mathit{lb}.\mathit{of}\mathit{CO}{}_2\mathit{per}\mathit{lb}.\mathit{of}\mathit{FPCM}=\mathrm{52,570,000}lbs.of{CO}_2$$

The dairy farm’s total CO₂ emissions, “net CF”, without consideration of biogenic CO_2, are 109,082,750 lbs. of CO₂ per year. The total CO₂ emissions, with consideration of biogenic CO₂, are 52,570,000 lbs. of CO₂ per year. This indicates that accounting for biogenic CO₂ reduces the CF of the dairy operation by 48.15%.

3.3. Economic Results

As a result of the model, an economic analysis of the dairy farm was conducted. In order to forecast the farm’s potential net return or profit, the IFSM 4.7 performs an economic analysis of the whole farm budget. The model is simulated for each weather year, and the values are then averaged to determine the mean over all simulated years. The results of the analysis are displayed as the average annual production costs and return over 25 years. The results of the economic analysis are presented in

Table 5. Simulated average annual economic output from the IFSM 4.7.

Annual Production Costs and Return to Management for a 25-Year Analysis
	Unit	Mean	Standard Deviation
Equipment cost	USD	1,199,412	43,405
Facilities cost	USD	1,067,856	1843
Energy cost	USD	717,094	5282
Labor cost	USD	3,826,504	5073
Seed, fertilizer, and chemical cost	USD	342,622	-
Net purchased feed and bedding cost	USD	7,599,146	142,711
Animal purchase and livestock expense	USD	2,433,500	-
Milk hauling and marketing fees	USD	1,313,446	3506
Property tax	USD	106,746	-
Total Cost	USD	18,606,326
Income from milk sales	USD	24,037,520	64,162
Income from animal sales	USD	1,787,436	-
Return to management and unpaid factors	USD	7,218,630	157,819

.

To simulate the economic analysis, the IFSM 4.7 used a partial budget analysis to determine the cost of production for corn and grass silage, the total cost of feed production and use, and the cost of manure handling. Sources of these costs include equipment, facilities, energy, labor, seed and crop inputs, livestock, milk transportation and marketing, and property tax. Taking into consideration the listed production costs, the dairy farm has an annual total cost of USD 18,606,326.

The results of the economic analysis indicated that the annual income from milk and animal sales is USD 24,037,520 and USD 1,787,436, respectively. Indicating the dairy farms’ total income to be USD 25,824,956. The return, or profit, is found by subtracting the difference between total income and total cost. A net return is determined as the sum of all revenues minus the sum of all production costs, which represents the potential profitability of the farm. Therefore, the annual return to management, or potential profit, is estimated at USD 7,218,626. When interpreting the economic analysis results determined by the IFSM 4.7, it is important to remember that the values presented are assumed by the model and may not accurately represent the Central Texas dairy operation.

4. Conclusions and Recommendations

4.1. Conclusions

This paper analyzes the carbon footprint as well as the movement of GHGs throughout a production year for the dairy farm used to conduct this study. A partial life-cycle assessment was performed using the USDA Integrated Farm System Model (IFSM) 4.7 to determine the results and achieve this study’s objectives. Results indicated that the CF of the 5000-milking-head dairy in Central Texas was 0.40 lb. of CO₂ per lb. of FPCM when considering biogenic CO₂ and 0.83 lb. of CO₂ per lb. of FPCM without biogenic CO₂.

When analyzing the sources of GHG emissions, manure and animal emissions are the leading contributors to the dairy operation’s CF. These emissions contribute about 63% of the total CF. Results show that for the dairy farm being studied, manure and animal-related sources typically produce more GHGs than other farm sources. This conclusion is consistent with the literature that indicates manure and enteric emissions from animals accounted for about 69% of the Southwest region’s total CF. A reduction in these emissions would reduce the CF of both the dairy industry and the agricultural sector as a whole.

4.2. Recommendations

With the Net Zero Initiative in place, technology has been developed to benefit both the environment and producers. Technology such as the anerobic digestor eliminates GHG emissions from manure and, in return, can produce clean energy, renewable natural gas, animal bedding, etc. By adopting an anerobic digestor, producers can achieve net zero status. However, adopting such technology is time-consuming and costly and involves several legal aspects. These factors may prevent a producer from adopting technology because of the short-run implications that come with the high initial investment costs as well as the lengthy start-up process.

The government should establish a cooperative anerobic digester program. Dairy producers within a community would be able to utilize the manure waste service by transporting the waste to the facility. This would benefit dairy producers by alleviating the financial stress of adopting the costly technology, the surrounding community by providing clean energy or renewable natural gas opportunities, and the environment by reducing GHG emissions. With government assistance and financial support, dairy producers would be encouraged to adopt environmentally friendly technology and achieve net zero status.

Additional future research could determine the short- and long-run economic and environmental impacts of utilizing an anerobic digestor as a manure management mitigation strategy. By conducting this research with a focus on short-run issues, producers would be informed of the initial investment risk. A long-run analysis studying the economic return and environmental impact of an ADS would indicate the financial feasibility as well as the possibility for an operation to achieve net zero status.

4.3. Limitations of this Study

A limitation of this study is the fact that an in-depth analysis of Central Texas dairy farms was not performed. According to the Texas Association of Dairymen [18], the two Central Texas milk-producing counties, Comanche and Erath, consist of 51,061 cows and 58 dairies. However, no data were obtained that relate operations to herd size or farm management practices. Due to this limitation, this study is not considered to cover the whole region because of the uncertainty of similar dairy operations. To better represent the area, future research could perform a survey to collect representative data from dairy operations regarding herd size, production, and management practices. By analyzing the survey data, representative values may be assumed regarding the average herd size and management, feed and crop management, and manure management to determine the average CF of a Central Texas dairy operation.