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Techno economic assessment of abattoir waste treatment using microalgae

Kossen, James (2016) Techno economic assessment of abattoir waste treatment using microalgae. Honours thesis, Murdoch University.

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Wastewater from Abattoir systems is highly concentrated with nutrients from the processes that occur in the day to day operation of the facilities. The current systems in place to treat this wastewater are usually lacklustre in regards to Nitrogen and Phosphorous reduction. The following thesis investigates the Techno Economics of installing a microalgae treatment system in order to reduce the overall Nitrogen and Phosphorous levels effectively. Microalgae growth has been shown to lower the levels of these nutrients as they are key growth components of biomass.

In order to find the Techno Economics a treatment system must first be designed for the abattoir waste. There is an extensive literature published in regards to abattoir waste loading including case studies from real abattoir systems. This literature data as well as the data from a local abattoir was used to find the total potential biomass that can be generated from the Nitrogen and Phosphorous loadings. With the total potential biomass calculated the land area required to generate the biomass was calculated using a specific microalgae growth rate in unit (g/m2/day). Once the land size was calculated the total pond system design began.

Using the literature data supplied by Meat and Livestock Australia (MLA) and the Australian Meat Processor Corporation (AMPC) unique systems were designed for three different size abattoirs. The data supplied was analysed on Pre AD data as well as simulated Post AD data as it was not recorded by the abattoirs. The total scale of these abattoirs ranged from a large scale (>2000 kL/day) to a small scale family run abattoir (<200 kL/day). The potential of these systems to generate biomass vary greatly from case to case. Biomass generation is important, as this will account for a large portion of the revenue needed for the profits generation.

The techno economics for these systems increase as the systems get larger however the initial Capital Investment and annual Operational Expenditure do not rise greatly as the systems get larger. Several break even schemes were solved, by altering the price/kg of biomass, for each system in order to find the minimum biomass sale price. This value greatly increases as the size of the abattoir goes down, as expected due to the lower biomass generation as well as the similar system CAPEX and OPEX. For the largest abattoir the minimum sale price was $0.82/kg and for the smallest system it was $5.85/kg. The largest abattoir case is an achievable sale price requiring only a small margin commodity as opposed to the smallest scale which would require more expensive biomass to grow.

The second case study supplied only the Post AD data which required no manipulation. The supplied data was taken over a 5 year period so the minimum, average and maximum waste loading cases, over this period, were analysed. The variation from the minimum case to the maximum case is ~830 kg potential biomass daily generated. This equates to a substantial difference in system design ranging from a 2 ha minimum system to a 9 ha pond system. As in Case Study one three break even schemes were solved for each individual case, the range of the sale data was $0.94/kg biomass for the minimum case and $0.89/kg biomass for the maximum case. These are achievable values depending on which microalgae strain will grow.
From the analysis performed microalgae growth in Raceway ponds using feed from the abattoir wastewater is an economically viable project. The more biomass generated the lower minimum biomass sale price for break even as well as raise the NPV of the project. The market demand and specific microalgae strain that will grow in the effluent will determine the economic viability of raceway pond installation; however with the required $/kg being low, the system should be viable for most large scale abattoirs.

Item Type: Thesis (Honours)
Murdoch Affiliation(s): School of Engineering and Information Technology
Supervisor(s): Bahri, Parisa and Moheimani, Navid
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