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Author(s):Li, Jiangong
Director of Research:Wang, Xinlei
Doctoral Committee Chair(s):Wang, Xinlei
Doctoral Committee Member(s):Akdeniz, Neslihan; Gates, Richard S; Kim, Harrison Hyung Min; Wang, Kaiying
Department / Program:Engineering Administration
Discipline:Agricultural & Biological Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Optimal design
Nutrient cycling
Manure management.
Abstract:There is no doubt that animal feeding operations (AFO) significantly improve meat production at a lower cost. However, accumulative manure produced in AFOs cannot be efficiently utilized in a sustainable and economical way. How to develop the animal manure management strategy is a challenge for both the local agricultural production industry and the ecological system. The overall goal of this dissertation research is to develop decision support models that enhance AFO manure management in the pursuit of sustainability and profitability. A systematic approach is proposed to assist in informatics management, analysis, and decision-making through the graphical user interface, cyber map service, operation research, geographic information systems (GIS), and techno-economic analysis. To bridge existing information gaps between AFO productions, local conditions, and technologies, a cyber-map enabled decision support platform was developed. This platform integrates data for manure production, treatments, application regulations, agronomist recommendations, and local electronic maps with user interactions to examine potential alternative manure management plans. To address the manure management problem of a single farm in a region that lacks adequate crop land for manure spreading, we present a modeling approach (Analytic target cascading, ATC) to optimize the design and operation of a swine manure management system by formulating economic, engineering, and environmental objectives into individual tasks. The conceptual design of a manure management plan was conducted by the decision support platform. Then, the ATC-based model identifies optimal capacities of main components, and operations of manure and crop management sequentially through updating the targets and responses in each iteration. A case study in Hangzhou, China (a swine farm with Anaerobic Digestion process + Ectopic Fermentation) is presented to illustrate the decision process and the sensitivity of the economic parameters i.e., a configuration of mass flows in the system and the size of each process in different seasons under different economic scenarios. Additionally, the scenario analyses are discussed to provide further insights of opportunities and risks. Manure is generated, processed, transported, and utilized in various ways. Manure management requires the coordination of animal feeding operations (AFOs), centralized processing facilities (CPF), and crop farms. Such a manure utilization chain is more than an individual farm scale, and it is a complex nexus between different production systems. To minimize annual manure utilization costs and identify the optimal manure flow patterns, a mixed-mode manure utilization chain (RMUC model) was proposed to ensure sustainable manure utilization for distributed animal farms. The model was implemented to evaluate the manure utilization chain in Hangzhou, China. The scenario analyses are discussed to estimate that the average solid and slurry manure utilization costs under existed and optimal logistics configurations. The decision-making of management practices needs intensive knowledge and a scientific basis while accommodating unique local conditions. The RMUC model can be used to inspect potential configurations (numbers and capacities of facilities, transportation routes, crop farms), quantify performance (economic returns, available manure application lands, nutrient utilization efficiency), and analyze the synergies and trade-offs among different objectives. The scenario analysis suggests setbacks for manure land application and determines the availability of manure applicable lands. The slurry-manure RMUC model was modified to analyze the operational cost and operational greenhouse gas emission of the slurry manure utilization chain in Hangzhou, China. The Pareto-optimal results of baseline scenario demonstrated how the GHG emission constraints affect the optimal configuration of the manure utilization chain, and how the improvement of those practices could change manure utilization cost, increase nutrient utilization, and reduce overall cost and GHG emission. A scenario analysis was conducted to allow the manure nutrient contents to vary within specific ranges. The results conceptually approved the benefits of accurate measurement of nutrient composition in manure management. Finally, we compared four different transportation modes and the results showed that adding a secondary storage station in each village will improve animal manure utilization. This study is an example of dealing with systematic agricultural problems with social, environmental, and economic constraints. It assists in overcoming the barrier to implement high-quality analysis tools in optimization models for establishing an ideal approach to use the information and computational science.
Issue Date:2020-12-02
Rights Information:Copyright 2020 Jiangong Li
Date Available in IDEALS:2021-03-05
Date Deposited:2020-12

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