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Targeted Fecal Sludge and Sawdust Data Collection Informed Design at Innovative Waste to Value FSTP

2 Service Delivery for Low-Income Communities » 2 Knowledge-based decision-making

Speaker: David Zweig


Summary – for publication in conference brochure:


Too often, Fecal Sludge treatment facilities are designed based on what has been done in the past. Waste characteristics are estimated from data collected elsewhere and processes and technologies are chosen simply because they’ve been implemented at other sites, rather than because they are the best fit for the facility at hand.  By contrast, new sampling data, research, and vendor discussions on every project are vital to design a facility capable of producing high-quality effluent.

 

This presentation will discuss how data collection and early vendor engagement informed technology selection and reduced risks at Sanivation’s innovative resource-recovery fecal sludge treatment facility.


Introduction, methods, results and discussion:


 

Too often, Fecal Sludge treatment facilities are designed based on what has been done in the past. Designers rely on average waste characteristics from data collected elsewhere; use formulas written for wastewater instead of fecal sludge (FS); and choose processes and technologies are simply because they’ve been implemented at other sites, rather than because they are the best fit for the facility at hand. By contrast, new sampling data, research, and vendor discussions on every project are vital to design a facility capable of producing high-quality effluent.

Sanivation, a social enterprise specializing in waste-to-value solutions, knew that they would need comprehensive data to effectively design their innovative combined FS treatment and biomass briquetting facility. To get it, they constructed a pilot facility to gather operational data and validate their financial model. Sanivation then hired Stantec, a global engineering consulting firm, to complete the design of the full-scale facility. 

This presentation will focus on four tests carried out by the owner with direction from the design team:

11. FS Sampling – The team tested over 150 of samples to determine the average and peak waste strength characteristics: BOD, Total Solids, total Suspended Solids, Ammonia, Total Nitrogen, and Total Phosphorus.

22.  Woody Biomass Drying Experiments – 3 month-long experiments using 12 samples to determine storage and drying requirements.  Uniform biomass was stacked at different heights and the team measured Percent Dry Solids daily to develop a drying curve.

43.  Piloted Biosolids (Dewatered FS) drying - For one year, Sanivation collected data to optimize the Percent Dry Solids and ratio of biomass to biosolids for the briquette machine.  The pilot iteratively pressed briquettes at varying ratios and % dry solids and tested the finished products. 

44. Polymer Jar Tests  - Jar tests helped determine the amount of polymer required for coagulation.

The data from these tests was combined with biosolid and effluent treatment goals to generate the design criteria.   The team then contacted over 30 local and international suppliers to discuss the project and design criteria, learn about their products and determine if their equipment was suitable.  As equipment was selected, the design criteria was adjusted to reflect its performance and the downstream equipment/processes were reassessed to confirm they could still meet project requirements.

This process led to sourcing major equipment packages from four different countries. Waste strength characteristics were used to procure a packaged liquid treatment system designed in Kenya and dewatering equipment from South Africa.  The drying curves and piloting data allowed for design of a smaller storage area for the biomass and biosolids.  The optimized waste ratios and vendors outreach led to the selection of a dryer from China and briquette press from Denmark. And the jar tests revealed a need for a higher polymer dosing rate than initially believed.

The collected data and the information gained through vendor discussions led to significant changes to the original design, bolstering the facility’s ability to maintain smooth operations and supporting Sanivation’s goal of creating a sustainable business from value-added fecal sludge treatment.

 

 


Conclusions and implications:


The design of Fecal Sludge Treatment Plants involves making decisions while faced with many uncertainties.  When faced with time and budget pressures, it can be tempting to skip rigorous data collection and extended preliminary design discussions. However, when data is unavailable, engineers must make the tradeoff between designing facilities that might not achieve their treatment goals, or build in extra factors of safety that translate to increased costs.

Sanivation’s experience demonstrates how data sampling, research, and vendor engagement can facilitate an economical and robust design. Downsizing the drying area reduced capital costs without impairing facility performance, which enabled a viable financial model even in the face of higher OpEx from items like increased polymer dosing costs. Taken all together, the data collection and preliminary design efforts created much stronger certainty around the design, which removed risk from Sanivation’s cost model.

FSM practitioners are encouraged to consider how data collection from tests and experiments, combined with research and vendor selection, can be targeted and deployed as early as possible in their own project designs. Without doing so, they run the risk of designing treatment plants that are over-engineered and costly, or may simply not work as intended.


Relevant references:


IUWASH Influent Sludge Sampling Data Review Memo
IPLT Technology Options Selection Guide Appendices


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