Stored dairy manure is a source of aerial emissions like greenhouse gases (carbon dioxide, methane, and nitrous oxide), ammonia, hydrogen sulfide, particulate matter, and volatile organic compounds. These emissions have been linked to negative impacts on human health, degradation of terrestrial and aquatic ecosystems, and air quality degradation. Aerial emissions from dairy manure are not only a challenge to environment degradation but also result in both economic loss and fertilizer value of the manure (nitrogen in particular). Therefore it is important to understand and accurately quantify the production and loss or emissions from manure storages to design adequate management practices to implement better mitigation strategies to abate the air pollution. Quantifying emissions by direct measurement is site-specific and typically difficult and expensive because of the equipment and skill level required. Because aerial emission from dairy manure storage results from a series of biogeochemical processes, process-based modeling is a practical approach to predict the formation and emission of manure gases. Existing process-based models include Integrated Farm System Model (IFSM) and Manure Denitrification Decomposition Model (Manure-DNDC). These models have general modules to estimate gaseous emissions from manure storage tanks as a single unit. However environmental factors (temperature, moisture, redox potential, microbial activity, pH, and substrate concentration gradient) governing biogeochemical processes vary with space and time and are driven by factors such as weather, storage geometry, and management practices. These existing models do not adequately consider these spatial and temporal variations and therefore need improvement. The broad objective of this study is to develop a heterogeneous compartmented process-based model to increase the accuracy of estimating greenhouse gases and ammonia emissions from stored liquid diary manure.To accomplish the objective, a comprehensive review of biogeochemical reactions used in IFSM and Manure-DNDC models and current literature will be conducted to identify processes that should be updated and any other critical information needed since the models were developed. The information will be used to improve the accuracy of quantifying gases formed and released, the manure storage tank. Our approach will consider and use as compartmentalization as a basis for improvement based on our understanding that manure mixing is never complete or homogenous during storage. Our model will use the finite elements principles to define and characterize the system (nodes). Simulations will be conducted on MATLAB platform. The model will be developed for a 100 milking herd dairy in Virginia. Weather data from the past 20 years for Blacksburg will be used. Further, we will seek data from studies that have reported gas emissions in the literature and those from other scientists to validate our model.Once completed, this project will provide a tool that improves the accuracy of estimating gaseous emissions from manure storage tanks thereby leading to a better understanding of quantities or information to base the design of mitigation technologies.
|Effective start/end date||1/10/10 → 30/09/18|
- National Science Foundation: $373,618.00