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COW2NUTRIENT: a Python GIS tool for the assessment of nutrient recovery systems in livestock facilities
Citation:
Martin-Hernandez, E., M. Martin, AND Gerardo J. Ruiz-Mercado. COW2NUTRIENT: a Python GIS tool for the assessment of nutrient recovery systems in livestock facilities. PyConES 2020, Virtual, SPAIN, October 03, 2020.
Impact/Purpose:
Water nutrient pollution is one of the major water quality problems worldwide, resulting in environmental issues because of the eutrophication of water bodies, the occurrence of cyanobacteria, and harmful algal blooms (HABs). The implementation of nutrient recovery technologies in livestock facilities to capture phosphorus from cattle manure is a promising approach to recycle and leverage nutrients more efficiently, mitigating water nutrient pollution. Under the inspiring principles of a circular economy for the development of environmentally and economically sustainable production processes, this presentation shows a Python geographic information system (GIS) decision support tool for selecting the most suitable nutrient recovery technologies for cattle concentrated animal feeding operations. The proposed tool determines the geospatial environmental sensitivity to nutrient pollution caused by legacy and new inputs of nutrients at watershed resolution. Also, the tool supplies techno-economic models and assessments to collect diverse input values that define each livestock facility operation and its economic context. This tool has the potential to be a key part of coordinated management efforts by state and regional partners for developing nutrient pollution and ecosystem integrated responses at regional spatial resolution.
Description:
Nutrient pollution is one of the major worldwide water quality problems, resulting in environmental and public health issues. One key source of nutrient releases is the agricultural economic sector that generates substantial amounts of organic waste, representing a challenge in terms of management, treatment, and disposal. In particular, the livestock industry is related to the presence of high concentrations of phosphorus in the soil, which potentially can reach water bodies by runoff. These releases of nutrients, mainly phosphorus, lead to the development of environmental issues, including harmful algal blooms (HABs), which turns into dead zones and hypoxia due to the aerobic degradation of the algal biomass by bacteria; shifting the distribution of aquatic species and releasing toxins in drinking water, even representing treats for human health [1]. In addition, soils can become unavailable for crop activities, and expensive remediation activities have to be implemented to mitigate nutrient pollution, then impacting the economy negatively [2]. Currently, manure is collected and stored as liquid or slurry for further spreading in croplands as nutrient supplementation; or as a solid in dry stacking or composting facilities to be sold as compost [3]. However, these approaches do not allow proper nutrient management since the continued land application of manure in the surroundings of CAFOs can lead to nutrient soil oversaturation and water pollution [4]. Therefore, the development of nutrient recovery systems capable of recovering these nutrients and reintegrating it into the production cycle is not only desirable but also a necessary measure to reach sustainable development. This work describes the development of an open-source tool for the design and assessment of nutrient recovery system based on Python. Two main aspects are under evaluation, a techno-economic study of the available nutrient recovery technology models to aid decision-makers in selecting the optimal process for phosphorus recovery, and a spatial analysis to determine the vulnerability of each watershed to nutrient pollution across the U.S. The goal is to provide a customized solution for each facility by evaluating different nutrient recovery and product valorization alternatives through a multi-criteria analysis framework and reach a satisfactory trade-off between economic and environmental targets. The technologies evaluated by the tool represent the state-of-the-art for nutrient recovery technologies capable of being deployed in livestock facilities. In addition, the proposed tool recommends decision-makers an optimal preliminary process design and cost of the selected technology as a function of the facility operating parameters. This open-source tool provides a decision support tool for the assessment of nutrient recovery systems in livestock facilities, which assists in the decision-making process for cost-effective measures to mitigate nutrient pollution. Also, this tool allows the development of efficient end-of-life alternatives for reuse/recycling of organic waste and the recovery of valuable products.