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The overall objective of the proposed project is the comprehensive analysis and synthesis of systems for mitigation of pollutant and pathogen emissions from livestock sources and operations. <P>Specific objectives are to: (1) extensively search and identify additional processes available for the mitigation of pollutant and pathogen emissions from livestock sources and operations; (2) systematically compile and rationally categorize the domain knowledge and data pertaining to the characteristics and behavior of the processes identified in (1) and perform statistical analyses of the data compiled and categorized; (3) quantitatively model the processes on the basis of the domain knowledge and data compiled and categorized in (2) as well as to extensively simulate their performances based on the resultant mechanistic models under a wide range of realistic scenarios; (4) optimally synthesize the systems, under various scenarios in terms of cost by incorporating the processes modeled and simulated in (3) as well as the ancillary processes, which render such systems implementable in practice; and (5) assess the sustainability of the optimal systems determined in (4) in light of different criteria, such as thermal efficiency, environmental compatibility, safety, societal acceptability and regulatory constraints, in addition to cost. <P>The expected outputs of the proposed project will be the optimal systems for mitigation of pollutant and pathogen emissions from livestock sources and operations. Such optimal systems with various configurations and operating modes will be implementable and sustainable in practice under wide-ranging scenarios. <P>The expected outputs can be readily and widely disseminated to the academic, public and industrial sectors in the form of website listings; journal articles; presentations at technical conferences, seminars and short courses; and bulletins and pamphlets.
Non-Technical Summary: The proposed project aims at the comprehensive analysis and optimal synthesis of systems for mitigation of pollutant and pathogen emissions from livestock operations. The expected outcomes of the project will be the framework for the best possible systems synthesized, which will provide the definitive framework for the design, operation, control, and management of sustainable infrastructures and facilities for reducing and/or eliminating pollutants and pathogens in a variety of livestock operations. The project proposed will be performed by carrying out the following. First, additional processes available for mitigation of pollutant and pathogen emissions from livestock sources and operations will be thoroughly searched and identified. Second, the knowledge and data related to the characteristics of the processes identified will be systematically collected and logically categorized. Third, the processes identified will be modeled based on the domain knowledge and data related to them by means of deterministic and stochastic approaches. Moreover, the resultant models will be simulated via conventional and non-conventional numerical techniques under a wide range of realistic conditions. Fourth, the systems' best possible configurations will be determined by incorporating the processes identified and classified at the outset by the graph-theoretic method based on process graphs (P-graphs). Nevertheless, if the system of interest consists of a small number of functioning units, it can be synthesized via a conventional algorithmic method. Fifth, the sustainability of the optimal systems synthesized will be assessed in light of various criteria, such as cost, energy requirement, exergy (available energy) consumption, material requirements, and environmental impacts. An initial estimation of the sustainability will be performed through the method of sustainability potential; if the resultant potential is deemed favorable, it will be further assessed by one or more of the available methods for the evaluation of sustainability. <P> Approach: To achieve the first specific objective, various scientific and technical databases available, e.g., AGRICOLA and SciFinder, will be thoroughly searched to identify abatement methods for mitigating pollutant and pathogen emissions from livestock sources and operations as well as the data pertaining to the characteristics and behavior of these methods. To achieve the second specific objective, the processes and methods identified as well as the domain knowledge and data pertaining to them will be critically reviewed, categorized and cross-referenced in light of a variety of logical criteria; the classified processes and methods will be rendered accessible via a computer database to be established by the project members, which will be continually updated. To achieve the third specific objective, the processes and methods identified and classified will be modeled and simulated. For initial exploration, a series of linear statistical models will be formulated to correlate the various variables characterizing the processes and methods based on the data pertaining to them. Subsequently, non-linear mechanistic models will be formulated and simulated in light of stochastic paradigms in addition to conventional deterministic paradigms. Moreover, the mechanistic models will be simulated via the Monte Carlo method. For validation, the analytical and/or numerical solutions of the models will be compared with the results from Monte Carlo simulation as well as with the available experimental and/or field data and with the solutions of the corresponding deterministic models whenever possible. In validating the mechanistic models, it might be also necessary to carry out a series of statistically designed experiments for generating additional data to corroborate the models' efficacy. The design of such experiments will be performed sequentially to discriminate among the various non-linear mechanistic models derived. To achieve the fourth specific objective, the optimal configurations of the systems will be determined, i.e., the optimal systems will be synthesized, by mainly resorting to the graph-theoretic method based on P-graphs (process graphs), especially when such systems comprise a large number of functioning units (equipment and machinery). It is worth mentioning that if any system of interest comprises a relatively small number of functioning units, it can be readily synthesized by a heuristic or algorithmic method. To achieve the fifth specific objective, the sustainability of the optimal systems synthesized will be assessed in light of different criteria, such as thermal efficiency in terms of exergy consumption; energy and material requirements; costs or profit; safety and health effects; and ecological and environmental impacts. At the outset, the sustainability of the optimal systems synthesized will be estimated by resorting to the method of sustainability potential. If the resultant sustainability potential is deemed favorable, the systems' sustainability will be fully assessed via one or more of available approaches.