Defining Best and Worst-

Case Bacterial Removals for

a Home Water Treatment

and Storage Unit

Gail Brion1, Matt King2 and Trish Coakley1

1- University of Kentucky-ERTL; 2- TivaWater

The Problem Every day more than 3,000 children die from diarrhoeal diseases.

Water, sanitation and hygiene has the potential to prevent at least 9.1% of the global disease burden and 6.3% of all deaths.

11% of the world’s population – 783 million people – are still without access to safe drinking water.

In rural areas in least developed countries, 97 out of every 100 people do not have piped water and 14% of the population drinks surface water – for example, from rivers, ponds, or lakes.

Household Water Treatment and Storage is a vital first step for many people. HWTS can provide the health benefits of safe drinking-water while progress is being made in improving water supply infrastructure

Household-based interventions were about twice as effective in preventing diarrhoeal disease (47%) than improved wells, boreholes and communal stand pipes (27%) (Clasen 2006).

The up-front cost of providing low-cost household water treatment is about half that of conventional source-based interventions. Most or all of that cost can be borne directly by the beneficiary, not the public sector.

Sources: Progress on Drinking Water and Sanitation 2012, by the WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation,

UNICEF Promotion of Household Water Treatment and Safe Storage in UNICEF WASH Programmes 2008.

One Solution: Home Water Treatment with

TivaWater Bio-sand Filtration with Integrated

Safe Storage.

Objectives of Research

Determine the removal of a commercial,

biosand type filter under optimal and

worst case operational conditions to

estimate the maximum and minimum

health impacts that could be expected.

Continuous, maximum flow rates, high

head.

Fast continual production when need is

greater than 10-L day, or for

“commercial” uses.

Breakthrough conditions.

Residence time in the filter is reduced to

a few hours from several days.

High fecal inputs.

From waters with large fecal loads, like

sewage contaminated rivers and streams.

Determine the Hydraulic

Characteristics of the Filter.

Maximum flow rate of 5.4 L/hour under constant, high head.

Find Appropriate Source Waters for Feeding

Biofilm and Challenging Filter

Challenge and feed water base

was effluent from the secondary

clarifier of the Town Branch

Sewage Treatment Facility.

Inlet sewage was added to base to

boost the signal of E. coli in the

challenge water.

Target concentration of the

challenge water 20,000 to 70,000

E. coli MPN/100 mL range

(Quantitray).

Each week had 3-4 challenges (10-

36 L), with the other days the

filter was fed (10 L).

Run Worst Case Scenario: High Head, High

Constant Flow, 36-L Breakthrough Challenge.

TIVA Filter Breakthrough Challenge Mode

(36 L/day, grab sample at end of run)

Date Liters Applied Percent

Removal

7/15/2014 72 61.8

7/16/2014 108 45.4

7/17/2014 144 76.3

7/21/2014 210 64.7

7/22/2014* 246 56.0

7/23/2014 282 94.7

7/31/2014 388 76.4

8/7/2014 484 82.4

* sand leak

ave removal 69.7

std dev 15.8

min removal 45.4

max removal 94.7

Note improvement as filter ripened.

After Filter Ripening, Challenge with

Recommended Overnight Filter Scenario: 10-L

Challenge, Declining Head, Declining Flow

Rate, Non-BreakthroughTIVA Filter Normal Use Challenge Mode

(10 L/day, overnight hold, composite sample)

Date Liters Applied Percent

Removal

7/28/2014 332 98.4

7/29/2014 342 94.7

7/30/2014 352 88.6

8/4/2014 428 97.9

8/5/2014 438 88.8

8/6/2014 448 91.6

ave removal 93.3

stdev 4.3

min 88.6

max 98.4

Averaged 1.2 logs of removal

Filter Ripening and Operational Modes Makes

Big Difference

Tiva Filter Microbial Challenge with Ripening

Breakthrough Challenge

36 L Applied

(% Removed)

Normal Usage

Challenge 10 L Applied

Overnight (% Removed)

Pre-Ripened Removal (<282 Liters Applied)

60.8

Post-Ripened Removal (>332 Liters Applied)

84.5 93.3

Expected Health Benefits (DALYs by QMRA)

Using the WHO QMRA Procedure

Assuming pathogenic

Campylobacter jejuni removal

by TIVA biosand filter is well

modeled by E. coli removals

demonstrated in this project.

Assuming the main route for

fecal-oral transport of

Campylobacter jejuni is the

potable water source.

Assuming there is only limited

acquired immunity and 100% of

the population is at risk.

Campylobacter Assumed Concentrations

WHO Risk Assessment (organisms/Liter)

1 10 100

Disability Adjusted Life Year

per person per year*

w/o treatment 10-2.01 10-1.01 10-0.01

with TIVA, 10-L/day 10-3.18 10-2.18 10-1.18

with TIVA, 36-L/day 10-2.53 10-1.53 10-0.53

* WHO intermediate Target 10-4 DALY per person per year

Gains in Number of Productive Days for a

Person or in a Community each YearCampylobacter Assumed Concentrations

WHO Risk Assessment (organisms/Liter)

1 10 100

Days lost/year for a person

w/o treatment 3.6 35.6 355.9

with TIVA, 10-L/day 0.2 2.4 23.8

with TIVA, 36-L/day 1.1 10.8 107.8

Campylobacter Assumed Concentrations

WHO Risk Assessment (organisms/Liter)

1 10 100

Days lost/year population of 100,000

w/o treatment 355,886

3,558,860

35,588,595

with TIVA, 10-L/day 23,844

238,444

2,384,436

with TIVA, 36-L/day 107,833

1,078,334

10,783,344

Almost 25 million

days regained

Summary

Biosand filters can produce more than 1-log of removal after ripening and with extended time in filter.

Testing must include different flow and use regimes to determine best and worst case removals.

Use of these filters, while not meeting the 4-log removal desired, can be expected to have a measurable impact on the health status of households and communities.

Less sickness means more human-power for other enriching activities. (3x less illness even under high head, high flow, overproduction conditions with heavily polluted water)

Source water quality must be considered when using these types of filters w/o disinfection.

Training in the correct use, and potential abuse, of the filters is important.

People are likely to subject filters to overuse flow conditions to maximize production.

We wish to thank TivaWater for allowing us access

to their filter prototype and for their open

collaboration. Not all companies would allow

worst case results to be shared, but they wanted

others to be able to follow the approach we

designed. We wish to acknowledge John May of

the Environmental Training and Education

Laboratories for his assistance with this project.