Performance and Evaluation of Swine House Heating with a Solar Energy Intensifier-thermal Energy Storage System

The urgency for energy independence in the United States is unprecedented in its history. The demand for energy is reflected in rising fuel costs which affects every segment of the economy. Among the most severely affected sectors is the agriculture industry, whose fossil fuel consumption is crucial to its efficient production of food and fiber. Solar, one of several alternative energy sources being developed nationwide has unique possibilities in the U.S. agriculture system. Large areas are available for locating collector units, and the energy requirements in the farm are low compared with the available radiation falling on the area. Drying of harvested crops and space heating of farm buildings can efficiently utilize low quality heat which can be generated with simple, inexpensive, solar equipment. Consequently, the agriculture industry has excellent opportunities to develop widespread application of solar energy systems. At least three serious problems exist in the development of a successful agricultural solar system. First, the seasonal variability of solar radiation, in the Great Plains region, is such that when the demand for energy on the farm peaks during the fall and winter, the amount of available radiation is at its lowest level. Second, thermal energy collection ceases during nighttime hours when the coldest temperatures occur. The third problem is the design and construction of an economical and reliable system that can be used for more than one application to increase its annual utilization. A contractor system can be used to intensify low level solar radiation onto a small collector and thereby achieve the required temperature range for agricultural applications. A thermal energy storage unit can be used to allow nighttime delivery of energy collected during the day. Finally, by producing air temperatures that are compatible with both grain drying and preheating of ventilation air, a single system can be utilized for a greater number of days during the year. A solar energy intensifier-thermal energy storage (SEI-TES) system was designed to incorporate all three of the aspects and to enhance the feasibility of solar energy for agriculture use. A unique location for the thermal energy storage unit in the system was included in the design to reduce heat losses and improve performance. To investigate the feasibility of the multiple-use SEI-TES system, research was conducted with the following objectives: 1. Test the SEI-TES for preheating swine house ventilation air under actual operating conditions. 2. Evaluate the performance and operating characteristics of the SEI-TES system

Dust, odor and gas control in swine finishing barns through oil sprinkling

AGRICULTURALMU GuidePUBLISHED BY MU EXTENSION, UNIVERSITY OF MISSOURI-COLUMBIASwine ManagementThe odors and gases produced by pigs raised in confinement buildings are a concern for producers working inside the buildings and for their neighbors living nearby. Poor air quality inside the building is a health and wellness issue for workers as well as the animals living in the buildings, while emissions of odors and gases can lead to complaints and nuisance lawsuits by neighbors. Research has shown that sprinkling vegetable oils on the floor and other pen surfaces in swine barns can significantly reduce airborne particulate matter (dust) concentrations. In a study recently conducted in northern Missouri, sprinkling soybean oil once a day in a swine finishing barn significantly reduced total suspended particulates (TSP) and particulate matter less than 10 microns in diameter (PM10). At an overall operational cost of about $1.00 per pig space (about$0.40 per finishing pig) for the basic oil sprinkling system, this technology appears to be cost-effective for swine producers.Amy M. Schmidt (Extension Agricultural Engineer, Food Science and Engineering Unit and Commercial Agriculture Program), Albert J. Heber (Extension Agricultural Engineer, Agricultural and Biosystems Engineering Department, Purdue University)New November 2018 -- websit

Improving Data Quality for a Dairy Pollutant Emissions Study

The National Air Emissions Monitoring Study (NAEMS) was sanctioned by the EPA to determine the characteristics of airborne pollutant emissions from confined broiler, egg, pork, and dairy housing. Fifteen representative monitoring sites were selected around the U.S., at which influent and effluent pollutant concentrations were measured in conjunction with airflow and climatic data. Due to the monumental nature of this study and the potential ramifications of its findings, it is of vital importance that the data collected by the researchers and utilized by the EPA be as complete and accurate as possible. To improve the validity of the data collected at a dairy facility in New York, it was necessary to review the work of previous data analysts while studying the field notes that were logged by scientists onsite during data collection. This allowed for the correction of perceived errors in the handling of the data. When sensor data were deemed invalid or missing, redundant data were substituted. Any unnecessarily flagged out data were restored. The use of these strategies led to a significant improvement in data quality. For example, data completeness for ambient temperature and relative humidity were increased by over 6%, while atmospheric pressure data saw an improvement of more than 18% after substituting data from the nearest NWS weather station. These and other improvements to this data set will allow EPA to develop more accurate dairy facility emissions models that will have substantial, wide-ranging effects for both producers and consumers in the U.S. dairy industry

Improving Ammonia Emission Modeling and Inventories by Data Mining and Intelligent Interpretation of the National Air Emission Monitoring Study Database

Ammonia emission is one of the greatest environmental concerns in sustainable agriculture development. Several limitations and fundamental problems associated with the current agricultural ammonia emission modeling and emission inventories have been identified. They were associated with a significant disconnection between field monitoring data and knowledge about the data. Comprehensive field measurement datasets have not been fully exploited for scientific research and emission regulations. This situation can be considerably improved if the currently available data are better interpreted and the new knowledge is applied to update ammonia emission modeling techniques. The world’s largest agricultural air quality monitoring database with more than 2.4 billion data points has recently been created by the United States’ National Air Emission Monitoring Study. New approaches of data mining and intelligent interpretation of the database are planned to uncover new knowledge and to answer a series of questions that have been raised. The expected results of this new research idea include enhanced fundamental understanding of ammonia emissions from animal agriculture and improved accuracy and scope in regional and national ammonia emission inventories

Improving Ammonia Emission Modeling and Inventories by Data Mining and Intelligent Interpretation of the National Air Emission Monitoring Study Database

Ammonia emission is one of the greatest environmental concerns in sustainable agriculture development. Several limitations and fundamental problems associated with the current agricultural ammonia emission modeling and emission inventories have been identified. They were associated with a significant disconnection between field monitoring data and knowledge about the data. Comprehensive field measurement datasets have not been fully exploited for scientific research and emission regulations. This situation can be considerably improved if the currently available data are better interpreted and the new knowledge is applied to update ammonia emission modeling techniques. The world\u27s largest agricultural air quality monitoring database with more than 2.4 billion data points has recently been created by the United States\u27 National Air Emission Monitoring Study. New approaches of data mining and intelligent interpretation of the database are planned to uncover new knowledge and to answer a series of questions that have been raised. The expected results of this new research idea include enhanced fundamental understanding of ammonia emissions from animal agriculture and improved accuracy and scope in regional and national ammonia emission inventories

On the Effects of Modeling As-Manufactured Geometry: Toward Digital Twin

Asimple, nonstandardized material test specimen,which fails along one of two different likely crack paths, is considered herein.The result of deviations in geometry on the order of tenths of amillimeter, this ambiguity in crack pathmotivates the consideration of asmanufactured component geometry in the design, assessment, and certification of structural systems.Herein, finite elementmodels of as-manufactured specimens are generated and subsequently analyzed to resolve the crack-path ambiguity. The consequence and benefit of such a "personalized" methodology is the prediction of a crack path for each specimen based on its as-manufactured geometry, rather than a distribution of possible specimen geometries or nominal geometry.The consideration of as-manufactured characteristics is central to the Digital Twin concept. Therefore, this work is also intended to motivate its development

Air Quality Measurements at a Laying Hen House: Particulate Matter Concentrations and Emissions

Particulate matter (PM) was measured in the ventilation exhaust air of a caged layer house using three tapered element oscillating microbalances (TEOMs). Diurnal patterns of PM concentration and emission were observed during 6 days in June 2002. The average daily mean (±95% c.i.) concentrations and emissions were 39±8.0, 518±74, and 1887±563 .g/m3 and 1.1±0.3, 16±3.4, and 63±15 g/d-AU for PM2.5, PM10, and total suspended particulates (TSP), respectively. Daytime (lights on) PM2.5, PM10, and TSP concentrations were 151, 108, and 136% higher (P\u3c0.05) than at night. Emissions peaked during the day when birds were most active and ventilation rates were the highest. Wide diurnal variations in PM concentration and ventilation were observed. PM emission was correlated to ventilation, ambient and exhaust temperatures, and relative humidity (P\u3c0.05)

Air Quality Monitoring and Data Acquisition for Livestock and Poultry Environment Studies

The development of analytical instruments and computer technologies in recent decades has facilitated significant changes in the methodologies used in scientific studies of agricultural air quality. A variety of instruments and sensors have been used for long-term and continuous measurements at commercial animal facilities and laboratories for determining baseline pollutant emissions and testing mitigation technologies. New measurement strategies were developed for real-time measurement and multi-location sampling. Optimization of this technology change necessitates an up-to-date system to acquire high-frequency data, control instruments and sampling locations, and monitor system operation. While various air quality research projects involve similar objectives and instrumentation to meet those objectives, they are usually conducted with monitoring plans that differ among sites and among projects. Special data acquisition and control (DAC) hardware and software have to be adapted for each monitoring plan. This paper summarizes various measurement and control devices used for comprehensive air quality studies of livestock and poultry environments. The paper further presents methods for real-time data transformation and processing. It introduces an air quality DAC system, which provided novel, flexible, and user-friendly features. The methodology and technology used in the new DAC system reduces system development and operational cost, increase reliability and work efficiency, and enhances data quality

Ammonia Emissions from a Commercial Poultry Manure Composting Facility

Composting is an effective waste management technology for converting animal wastes into valuable organic fertilizer. However, air emissions from composting, especially ammonia (NH3) emission, reduces the nitrogen fertilizer value of the compost and greatly impacts the environment. Ammonia emission from commercial composting facilities is not well understood and is limiting mitigation or recovery of NH3 emission from these facilities. The goal of this study was to determine the NH3 emission from a poultry manure compost facility and its temporal variations for development of mitigation strategies. A commercial composting facility was chosen for this study. Manure was supplied from four adjacent manure-belt layer barns. The composting building was tunnel ventilated by four 122-cm exhaust fans. Ammonia concentration at the building inlet and the fan exhausts was monitored quasi-continuously for one month in each of the four seasons using a MSA photoacoustic NH3 analyzer. Air temperature and humidity at the exhausts were monitored using a HOBO temperature and RH sensor and data logger. The exhaust fans were calibrated using FANS units to quantify the ventilation rate of the building. Ammonia emission rate was calculated according to the NH3 concentrations and building ventilation rate. The daily average NH3 concentrations at the exhaust of the compost house varied from 123 ppm in spring to 167 ppm in summer. The daily average NH3 emission rates of the compost facility varied from 231 kg/d in spring to 315 kg/d in summer. Strong diurnal variations exist in spring and summer seasons. Daytime NH3 emission is significantly higher than that of nighttime. The annual NH3 emission rate of the composting facility was estimated as 96,143 kg. The emission factors were calculated as 13±1.3 kg/ton · d and 0.32 ±0.14 g/d · hen. The results of this study will contribute to the development of NH3 emission mitigation technologies and management practices

Air Quality Monitoring and On-Site Computer System for Livestock and Poultry Environment Studies

This article reviews the development of agricultural air quality (AAQ) research on livestock and poultry environments, summarizes various measurement and control devices and the requirements of data acquisition and control (DAC) for comprehensive AAQ studies, and introduces a new system to meet DAC and other requirements. The first experimental AAQ study was reported in 1953. Remarkable progress has been achieved in this research field during the past decades. Studies on livestock and poultry environment expanded from indoor air quality to include pollutant emissions and the subsequent health, environmental, and ecological impacts beyond the farm boundaries. The pollutants of interest included gases, particulate matter (PM), odor, volatile organic compounds (VOC), endotoxins, and microorganisms. During this period the research projects, scales, and boundaries continued to expand significantly. Studies ranged from surveys and short-term measurements to national and international collaborative projects. While much research is still conducted in laboratories and experimental facilities, a growing number of investigations have been carried out in commercial livestock and poultry farms. The development of analytical instruments and computer technologies has facilitated significant changes in the methodologies used in this field. The quantity of data obtained in a single project during AAQ research has increased exponentially, from several gas concentration samples to 2.4 billion data points. The number of measurement variables has also increased from a few to more than 300 at a single monitoring site. A variety of instruments and sensors have been used for on-line, real-time, continuous, and year-round measurements to determine baseline pollutant emissions and test mitigation technologies. New measurement strategies have been developed for multi-point sampling. These advancements in AAQ research have necessitated up-to-date systems to not only acquire data and control sampling locations, but also monitor experimental operation, communicate with researchers, and process post-acquisition signals and post-measurement data. An on-site computer system (OSCS), consisting of DAC hardware, a personal computer, and on-site AAQ research software, is needed to meet these requirements. While various AAQ studies involved similar objectives, implementation of OSCS was often quite variable among projects. Individually developed OSCSs were usually project-specific, and their development was expensive and time-consuming. A new OSCS, with custom-developed software AirDAC, written in LabVIEW, was developed with novel and user-friendly features for wide ranging AAQ research projects. It reduced system development and operational cost, increased measurement reliability and work efficiency, and enhanced quality assurance and quality control in AAQ studies