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Can we estimate what happens after the toilet, and is it worth trying?
Presented by Pete Kolsky, on behalf of teams at UNC and University of Alabama on the Unsafe Return of Human Excreta
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SDG background
Target 6.2: By 2030, achieve access to adequate and equitable sanitation and hygiene for all and end open defecation, paying special attention to the needs of women and girls and those in vulnerable situations
Proposed JMP Target Indicator: Percentage of population using safely managed sanitation services
One approach…Estimate
a) what waste “leaks” out from safe management chainb) how unsafe is it when it leaks?
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Funding from BMGF to look at “unsafe return of human excreta”
Objectives:– Determine feasibility of national estimates of unsafe return– Identify a combination of data and assumptions to make
such estimates by the launch of the SDGs– Document model development and evolution– Learn and share• If feasible, what kinds of useful questions can we
answer? (Why do it at all?)• Why do it this way? (can we find better ways?)
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Activities
• A literature review• Model development• Expert elicitations to populate the models– Public health microbiologists– Sanitation practitioners in at least 5 countries
• Analysis and sharing of results• Planning next steps
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Literature Review
Review of “leakage” from stages of sanitation chain
– Wide range of findings and experience…. “zero” to “high”
Poor documentation of– Latrine/septic tank emptying – Septic tank performance in DCs– Fecal sludge management in DCs
Treatment efficiencies vary by– Technology– Context– Pathogen of interest
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MODEL DEVELOPMENT AND STRUCTURE
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Points of departure
“Safely managed” is a loaded term …but really is what we want to know
More than “just” a mass balance of fecal sludgePathogen die-offLiquid wastes
“Do what you can, with what you have, where you are”
Build on work of JMP &WSP/Leeds Shit Flow Diagrams (SFDs) Why reinvent the wheel? Clarity of exposition and understanding
Estimating on a national basis for SDGs Urban and Rural, whole population
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Mechanics
1. Subdivide all JMP sanitation technologies into: Latrines (onsite, no sullage) “Septic tanks” (onsite solids removal, sullage) Sewers Open defecation
University of Alabama expertise with JMP data made this possible quickly!
2. Explore diverse paths of solid and liquid wastes from above technologies to environment, accounting for hazard reduction en route
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“Hazard” not “mass” balance?
Alternating pit latrines• If pit is sealed and left for two years, most or all pathogens die
off before emptying• The above mass is NOT equivalent to contents of pit latrine
emptied immediately when full• Age matters!
Sewers• If untreated….pathogens released at full strength!• Most treatment is NOT about pathogen destruction
“Safely managed” consideration of these differences
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Simplified Latrine Schematic
Year 1
Year 2
Year 3Year 4Year 5
Feces, urine
“Fresh”
Latrine
Emptying ( or sealing)
Dispose onsite
spillageTransport
Dump community
or wider envt
spillage
Local leakage/ Contam’n via
groundwater, flooding
Treatment and
disposal
Leakage as bypass, or
inadequate treatment
safe unsafe
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Simplified “Septic Tank” schematic
excretawater
Sludge
infiltration bed
Emptying
Safe onsite
disposal
spillage
Sludge transport
Dump community
or wider envt
spillage
effluent surface flow/ Contam’n via groundwater
SludgeTreatment
and disposal
Inadequate ttmt,
dumping
effluent to drain or
sewer
Leak to partial or no treatment
flooding
Unsafe onsite
disposal
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Simplified sewer schematic
Transport
Leakage/discharge
to community
Liquid and solid
treatment and
disposal
excretawater
Combined sewer or open drain
overflow Leakage/ discharge to wider
env’t
Inadequate ttmt,
dumping
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Input to Models
Three types of data:• “yellow cells” from local san experts• “green cells” computed, or derived
from JMP data• “red cells” reflect microbial expert
opinionWe ask experts “unreasonable” questions• “What fraction of septic tanks
contaminate water supplies?”• “What fraction of septic tank sludge
is carried to treatment sites?”We believe their informed opinion is better than nothing!
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Structure of Models
Data used to track “hazard” through “trees” of return of excreta to environment
Separate sheets for– Containment– Emptying – Transport– Treatment/Disposal
for rural and urban technologies
– Latrines– Septic tanks– Sewers
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Elicitation of Microbiologists
Our models to date are very simplistic• For example, an assumed “safe” period of dieoff in sludge
– If sludge undisturbed for safe period x, no significant hazard left– If sludge returned w/o treatment before period x, no threat reduction
Seeking guidance from microbiologists to do betterOnline survey asks “unreasonable” questions– When you mix water and crap together, how much of the
“hazard” goes into the water, how much stays with solids?– What is the rate of “hazard” die-off in
• Latrine sludge?• Septic tank sludge?
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WHAT HAVE WE LEARNED?
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Results to date
Can it be done? Feasibility and the “laugh test”– In-country sanitation experts– Expert public health microbiologists
What can models tell us? What questions do they raise and address?
So what? If we can do this right, how will it help?How can it inform policy and practice?
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CAN IT BE DONE?
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Microbiology “laugh test”: original discussions at Water Micro Conf.
Natural concern for context– What organisms? What temperature? What
moisture content?
Broad agreement that protozoa, worms can be hardy!Some variation in “liquid-solid” hazard attribution
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3 Expert Opinions on Pathogen survival in Pits (11-20o C)
% bacteria surviving % helminths surviving
0 200 400 600
Time (Days)
0 200 400 600
Time (Days)
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Can it be done? Sanitation estimates
Experts in several countries contactedAll face same challenge of “unreasonable questions”Most responsive so far have been in
– Ghana– Mozambique and – the Netherlands (in process)– Working on other contacts in Philippines, Brazil, Egypt
Experts in Ghana and Mozambique have completed spreadsheets, (with suggestions for improvements!!) but have been positive.
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WHAT CAN MODELS TELL US?
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Preliminary results from Ghana
About half of human waste is safely managed
Remaining hazard divided between household and community level
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Ghana Variation by Technology
Approximately 20% of households practice OD, accounting for nearly 40% of unsafe return
Over 60% of unsafe return comes from poorly managed “sanitation” waste
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Preliminary Mozambique Results
Safe Contain-ment6%
Safe Dis-
posal37%
HH Hazard8%
Comm
Hazard42%
Wider Haz-ard7%
About 40% of waste is safely managed
As with Ghana, most hazard at HH and community levels
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Mozambique: Distribution of Unsafe Return by Technology
Rural Open Defecation much more significant fraction of problem than in Ghana
urban lat; 22%
rural lat; 6%
urban ST ; 2%
urban OD; 7%
rural OD; 63%
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Hypothetical Shift from “Shared” to “Improved Pits” in Ghana
• Perhaps not a shock result….better management, less “circulation” among users
0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 1 0 00%10%20%30%40%50%60%70%80%90%100%
Safe Return
Unsafe Return
100% Shared
100% Improved
Pit
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Hypothetical Shift from Improved Pit to Sewer in Ghana
• More surprising….but sewers offer no storage die-off of pathogens, and limited effective anti-pathogen treatment
0 50 1000%
20%
40%
60%
80%
100%
Safe Return
Unsafe Return
Improved Pit Sewer
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Conclusions/Takeaways
• Where data are scarce, expert opinions appear to offer useful insight with surprising consistency
• Models raise useful questions about technological choices– Need to track liquid as well as solid fecal hazards– sewers as “hypodermic needles”
• Strong need to build in country capacity for basic waste monitoring…
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More motivation from the field
In Haiti a year after the outbreak of cholera, chief engineer of Min of Health had no idea where “honey wagons” discharged (outside capital area).
• Need to count more than toilets
• Need to offer tools, develop experience to make easy to do
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Acknowledgments
Bill & Melinda Gates Foundation– JW Rosenboom
University of Alabama – Mark Elliott and Phillip Grammer
UNC– Profs Jamie Bartram & Mark Sobsey– Students/Researchers Kathy Brown, Lisa Fleming, Jackie Wallace,
Ashley Williams– Admin team who make it all work– Others “TNTC”
Leeds/WSP team of Peal/Evans/Hawkins/Blackett et al.Ghana data Lukman Salifu & AssociatesMozambique data Peter Hawkins at Water & Sanitation Program