optimisation of household scale biosand filters

Individual Environmental Systems Project

Optimisation of Household scale Biosand Filters

Richard Outhwaite

Project Supervisor: Dr. Luiza Campos

Date: 08.09.2010

Optimisation of household Biosand filters Richard Outhaite

Acknowledgements

I would like to thank all those who have helped me carry out this project, in

particular to Dr Luiza Campos as the project supervisor and to Ian Sturtevant and

Judith Zhou for their assistance in the laboratory.

I would also like to thank Engineers without Borders for the funding provided they

have provided for the materials for this project, without which it would not have

been possible. Thanks also to WBB minerals for providing the sand used in the

project and Andy Skinstad for his transportation services.


Abstract

The household Biosand filter is a well-established example of ʻappropriateʼ technology used throughout the developing world to improve the quality of drinking water. This project studied two methods to optimize its performance and mitigate some of the risks that can arise from incorrect operating conditions and procedures. It also investigated the filters ability to remove pesticides from raw water. The first method to optimise the filter was by ʻseedingʼ one filter using sand from an existing Biosand filter to speed up the maturation of the filter. The second method used to improve the performance of the filter was the addition of a tap to

the outflow pipe, which would prevent the need for users to store water that had been filtered, thus removing the possibility of recontamination through storage. The ability of the filter to remove pesticides was studied to allow us to establish whether the filter could be used on waters contaminated by other pollutants. Total coliform counts were used as the indicator to quantify bacteriological removal and Gas Chromatography-Mass spectrometry was used to detect the residual pesticide, Metaldehyde, in the filtrate. Headlosses, pH, turbidity and Dissolved Oxygen were also measured and studied. The seeded filter reached 99% coliform removal after 16 days, 10 days before the unseeded filter. It showed significantly higher coliform removal rates than the unseeded filter throughout the study across the 3 samples taken during each test (p < 0.01). The filter with the tap showed that it could still maintain significantly high coliform removal rates (99.2%, p <0.01) even after pausing the flow of water. These two modifications to the installation and operating system indicate that they can both improve filter performance and reduce the risk of operational misuse. The filter did not show consistent removal of the Metaldehyde, as a wide spectrum of removal rates were recorded (0.00% - 73.5%). Whist the results were not conclusive to show that the filter could consistently remove the pesticide; it does however show some potential, which could be investigated in further studies.


Table of Contents

1. Introduction....................................................................................................1

2. Literature Review...........................................................................................3

2.1. Slow sand filtration....................................................................................4

2.2. Biosand filter .............................................................................................9

2.3. Pesticide removal....................................................................................12

3. Methodology ................................................................................................14

3.1. Experiment Design..................................................................................14

3.1.1. Filter maturation study ......................................................................15

3.1.2. Tap study..........................................................................................15

3.1.3. Pesticide removal study....................................................................20

3.2. Filter Construction...................................................................................22

3.2.1. Sand media ......................................................................................23

3.3. Dye tests .................................................................................................25

3.3.1. Tracer tests ......................................................................................25

3.3.2. Solution tests....................................................................................26

3.4. Raw water ...............................................................................................26

3.5. Bacteriological analysis & coliform counting ...........................................27

3.6. Culture Media..........................................................................................28

3.7. Metaldehyde sampling & analysis...........................................................28

3.8. pH meter .................................................................................................29

3.9. DO meter ................................................................................................29

3.10. Sterilization..............................................................................................29

4. Results and Discussion ..............................................................................30

4.1. Dye Testing.............................................................................................30

4.2. Filter maturation study.............................................................................33

4.2.1. Coliform removal efficiency...............................................................33

4.2.2. DO Consumption ..............................................................................37

4.2.3. Headloss development .....................................................................39

4.2.4. Turbidity reduction ............................................................................41

4.3. Tap study ................................................................................................45

4.3.1. Coliform removal efficiency...............................................................45


4.3.2. DO consumption...............................................................................48

4.3.3. Turbidity Reduction...........................................................................50

4.3.4. pH reduction .....................................................................................52

5. Pesticide removal ........................................................................................53

6. Conclusions and Recommendations.........................................................57

6.1. Maturation Study.....................................................................................57

6.2. Tap study ................................................................................................58

6.3. Pesticide Study .......................................................................................59

7. References ...................................................................................................60

8. Appendices ..................................................................................................64


List of Figures

Figure 2-1 – Relationship between grain diameter and pore size (Huisman &

Wood, 1974) ...................................................................................................6

Figure 2-2 - Structural formula of Metaldehyde (WHO, 1996) ..............................12

Figure 3-1 Schematic of test procedure and sampling frequency.........................17

Figure 3-2 - Schematic of test procedure and sampling frequency for tap study..19

Figure 3-3 - Schematic diagram of experiment variables & sampling frequency..21

Figure 3-4 - Plan and section views of constructed Biosand filters ......................22

Figure 3-5 - Particle size distribution - Unseeded sand........................................24

Figure 3-6 - Particle size distribution - Seeded sand............................................24

Figure 3-7 - Raw water sampling location – Regents Park...................................27

Figure 4-1 - Graph of Light absorption against Time – Unseeded filter ................30

Figure 4-2 - Light absorption against Time - Seeded filter....................................31

Figure 4-3 - Light absorption against Time - Unseeded & seeded solution tests .32

Figure 4-4 - Dye Tracer tests in Unseeded filter at (a) 5 mins & (b) 70 mins........33

Figure 4-5 - Graph of Coliform removal rate against time - Unseeded filter .........34

Figure 4-6 - Graph of Coliform removal rate against time - Seeded filter .............35

Figure 4-7 - Dissolved oxygen consumption against time (Unseeded filter).........38

Figure 4-8 - Dissolved oxygen consumption against time (Seeded filter).............39

Figure 4-9 - Headloss development for seeded and unseeded filters ..................40

Figure 4-10 - Turbidity of raw water .....................................................................42

Figure 4-11 - Turbidity of Filtrate - Unseeded filter ...............................................43

Figure 4-12 - Turbidity of Filtrate - Seeded Filter..................................................43

Figure 4-13 – Possible positions of seeded sand within a filter............................44


Figure 4-14 - Coliform removal rate against time – Filter without Tap..................47

Figure 4-15 - Coliform removal rate against time – Filter with Tap.......................48

Figure 4-16 - Coliform removal rate against DO consumption – No Tap..............49

Figure 4-17 - Coliform removal rate against DO consumption - Tap ....................49

Figure 4-18 - Turbidity of filtrate - Filter without tap..............................................51

Figure 4-19 - Turbidity of filtrate - Filter with tap...................................................52

Figure 5-1 – Concentration of Metaldehyde in filtrate at 180µg/L – Filter without

Tap................................................................................................................54

Figure 5-2 Concentration of Metaldehyde in filtrate at 1000µg/L – Filter without

Tap................................................................................................................54

Figure 5-3 Concentration of Metaldehyde in filtrate at 180µg/L – Filter with Tap .55

Figure 5-4 Concentration of Metaldehyde in filtrate at 1000µg/L – Filter with Tap55

Figure 7-1 - Gas Chromatography parameters ....................................................70

Figure 7-2 - Chromatogram for Metaldehyde sample with internal standard........71

Figure 7-3 - Integral of chromatogram to determine quantity of Metaldehyde ......72


List of Tables

Table 2.1 - Health effects of Metaldehyde exposure (INCHEM, 1996).................13

Table 4.1 – Effect of seeding on coliform removal rates for samples collected at

different residence time.................................................................................36

Table 4.2 – Effect of residence time on coliform removal rates for seeded and

unseeded filters.............................................................................................37

Table 4.3 - Coliform removal rates and significance factors for filters with and

without Tap ...................................................................................................45

Table 4.4 – Coliform removal rates on filters with tap and without tap .................46

Table 4.5 - Mean turbidity for filtrate from filters with & without tap ......................51

Table 4.6 - Mean filtrate pH for filter with & without tap........................................52

Table 5.1 - Reduction in Metaldehyde concentration at 180µg/L & 1000µg/L ......53


List of Equations Equation 1 - Uniformity Co-efficient......................................................................23

Equation 2 - Porosity of sand bed ........................................................................25


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1. Introduction

In 1804, John Gibb of Paisley, Scotland established the first recorded example of

filtration as a means of water treatment. This was mainly for private use in his

bleachery, but some of the excess filtered water was sold off to the public. This

method was modified and adopted by others until James Simpson constructed the

first plant supplying water to the public in 1829 at the Chelsea Water works. Whilst

the processes involved in the prevention of disease by slow sand filtration were not

identified until John Snowʼs discovery of materes morbi, the benefits of slow sand

filtration were readily apparent. By 1885 the work of Pasteur and other leading

scientists of that era had led to regular bacteriological testing of the drinking water

supplies.

Due to advances in the technology of water treatment and vast improvements in the

knowledge of the process involved in water treatment, public health has gone from

strength to strength in the developed world. Water-borne disease has become a

thing of the past. However, many parts of the world are still desperately lacking in the

infrastructure and knowledge on how to provide themselves with clean and safe

drinking water. Children are the most vulnerable to a lack of access to clean water. It

is estimated that every 15 seconds a child dies from water related disease (UNDP,

2006) and that a total of 1.4 million children die from diarrhoea each year (Pruss-

Ustin et al., 2008). Out of all the people killed by diarrhoea each year, 90% are

children under 5 years old living in developing countries (UN Water, 2008).


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Developments have been made in the appropriate household water treatment

technology in recent years. Developments such as the Biosand filter (Manz, 1997;

Buzunis 1995) and the Filtron ceramic water purifier (Potters for Peace, 2008) have

begun to address this problem, but there still remain a number of challenges.

As new technology develops and becomes available, new technical and socio-

technical challenges arise when these technologies are implemented. How people

use, and often more importantly misuse, these technologies create new challenges

to be solved. Incorrect or unanticipated use of the technology in the field can

increase the risk of exposure to contaminants (Baumgartner et al, 2007).

This study aimed to investigate whether modifications to the Biosand filter can

increase its performance in removing water-borne pathogens and avoid possible

pathways to misuse that can reduce its efficiency, as well as speeding up the time

for the filter to reach its optimum performance. It will also look at whether the filter is

able to remove other chemical compounds, such as pesticides, as the filter is often

used in rural, agricultural areas without protected water sources.


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2. Literature Review

Diseases from poor sanitation and low quality drinking water currently affect more

than 2.2 billion people worldwide. It is estimated of those people over 1 billion people

still do not have access to an improved water source within one kilometre (WHO,

2000; Sphere, 2004).

Well known diseases such as diarrhoea and cholera; as well as trachoma,

schistosomiasis, amebiasis and giardiasis are prevalent in areas without access to

proper sanitation and drinking water (UNICEF, 2006). This greatly impacts on

mortality rates of populations, especially children. Not only are the health and

wellbeing of communities being impacted upon by the lack of critical infrastructure

but also the economic output of developing countries. People who are suffering from

any of those diseases cannot work and become a burden for their community.

The international community has recognized the issue, which as long ago as 1980

has been the subject of numerous international conventions. The most recent

international effort, The Millennium Declaration by the UN, created the Millennium

Development Goals (MDG). These outline major targets for improving sanitation and

water supply for people in developing countries. These aim to halve the number of

people unable to reach or afford safe drinking water and basic sanitation by 2015

(UN, 2000).


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Achieving these goals is a monumental task. To be effective in developing countries

that do often have access to trained personal or specialized equipment, the

application of appropriate technology is essential. One of the most simple and

successful ways to treat water over the past 200 years has been filtration of water

through a sand bed.

2.1. Slow sand filtration

The basic operation of a slow sand filter is very simple. The raw water enters the

filter and remains above the sand bed for a few hours due to the slow flow rate of

water through the bed. During this time some separation and sedimentation occurs.

The water then passes through the sand bed, usually for 2 hours or more, where it is

exposed to a number of different processes that purify it. These will be covered in

more detail later.

In comparison to a rapid sand filter, in which the water only spends a few minutes in

the filter, the amount of bacterial removal and chemical improvement is very low.

However, rapid sand filters are usually used in conjunction with chemical

coagulation-flocculation followed by sedimentation or flotation. This removes a large

number of the contaminants before the water arrives at the rapid sand filter. To

maintain flow rates through the rapid sand filters, regular cleaning through

backwashing is required. The high flow rates in a rapid sand filter, between 100-200

m3/m2/day (Tebbut, 1998) and the frequent backwashing prevents the development

of a biofilm and schmutzdecke on the surface of the rapid filter, one the main

components of bacterial removal in slow sand filtration.


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Typical flow rates of slow sand filters range from 1-4 m3/m2/day (Tebbut, 1998)

depending on their position in the treatment process. Slow sand filters in Amsterdam

have been run at rates of up to 6 m3/m2/day, as they were the final step of a multi-

treatment process (Visscher, 1990). It is this combination of slow flow rates and long

filter runs through a fine sand media that allow a host biological community to

establish in the filter and form a biofilm.

The schmutzdecke develops on the surface of the filter as the raw water is filtered

through it to create a layer of purifying bacteria and microorganisms. It is made up of

filamentous algae that host plankton, diatoms, rotifers, protozoa and bacteria

(Huisman & Wood, 1974). It is here that the purification process begins. After

passing through the schmutzdecke the water passes through the voids between the

sand grains where the water is subjected to further biological activity and other

removal mechanisms.

The processes that occur in slow sand filtration that removes pathogenic bacteria

and other microorganisms can be broadly placed into three categories: physical

straining, physico-chemical attachment and biological predation.

Physical straining occurs through the fine sand media used within the filter. Small,

suspended particles and other matter to which bacteria can often be attached are

filtered out at or near the surface of the sand bed. A sand bed can filter particles up

to approximately 15% of its grain diameter (Haarhoff & Cleasby, 1991, & Huisman &


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Wood, 1974). This means that for a typical slow sand filter with an effective grain

size of 0.15mm, only particles larger than 20μm will be removed in theory. This is

shown in Figure 2-1. Colloidal particles, with diameters of 1μm or less, and bacteria

and viruses with lengths up to 15μm are much smaller than the pore sizes (Tebbut,

1998). Therefore the removal of viruses and bacteria within the filter must occur

through other processes.

Figure 2-1 – Relationship between grain diameter and pore size (Huisman & Wood, 1974)

The main processes of virus and bacteria removal from raw water are biological

predation, adsorption to the biofilm and to non-biological surfaces. (Wheeler et al.,

1988). Predatory bacteria and microorganisms that inhabit the biofilm and

schmutzdecke consume the pathogens as they pass through (Weber-Shirk & Dick,

1997). Whilst most of the biological action occurs within the uppermost areas of the

sand bed where the micro fauna and flora are most abundant (Wheeler et al., 1988),

biological action that occurs within the sand bed can occur up to 40cm deep into the

bed (ASCE, 1991).


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Attachment to the biofilm and sand media takes place through of a series of physical

and chemical reactions between the sand grains, the biofilm and the bacterial cells.

Specific electrostatic charges cause an attraction between the organic matter and

the negative charged sand particles, which cause the bacteria or virus to bond to it

(Huisman & Wood, 1974). The same effect can occur through Van der Waals forces

once the particles have been brought into close proximity to each other.

Once the filter begins to ripen the biofilm, or zooglea (Brock & Madigan, 1991), is

formed by bacteria, organic matter and waste produced by the bacteria. This creates

a sticky surface that forms on the surface of the sand grains to which further organic

matter sticks. Here it is either broken down by the bacteria to be assimilated into the

biofilm or is retained on the surface until it is removed when the filter bed is cleaned.

Smaller, colloidal-sized particles are generally not removed through slow sand

filtration, as they are smaller than the void spaces in the sand bed. Such fine silt and

clay requires pre-treatment such as chemical coagulation-flocculation to form flocs

that are large enough to be filtered out by the slow sand filter. This can result in low

flow rates due to increases in headloss as the filter becomes blocked with sediment.

It is therefore recommended to remove such flocs by sedimentation or flotation if

possible prior to filtration.

A mature slow sand filter will produce filtrate of high quality. The raw water should

generally not have a turbidity of over 20 NTU to avoid over frequent bed cleaning,


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unless other processes in the treatment train are used (Tebbut, 1998). Provided

these criteria are met is met the filter will provide a filtrate with:

• Turbidity less than 1 NTU

• Coliform removal rates up to 99%

• Virus and Microorganisms removal, e.g. Cryptosporidium and Giardia cysts,

up to 99%

• 75% removal of colour.

• 10% removal of TOC.

As slow sand filtration was one of the first techniques to be adopted, it has become

seen to be obsolete in the face of more technological and chemical treatment

processes. Currently, few authorities consider it to be appropriate technology,

especially as it requires larger land area in comparison to other treatment processes.

However as recent legislation limit the amount of Trihalomethanes in water, caused

by chlorination of water still containing organic matter, biological treatment methods

such as slow sand filtration are becoming more popular again.

One area where slow sand filtration is still seen as an appropriate technique is in

developing countries. As a standalone process, it has been ranked as the second

most effective technique in improving the physical, chemical and biological quality of

water after desalinisation and evaporation (House & Reed, 1997). The simple

installation, operation and maintenance make it a key technology in improving the

quality of drinking water in the developing world.


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2.2. Biosand filter

The household Biosand filter was first conceptualized in the 1990s as a solution to

the widespread problems of poor water quality and public health in developing

countries. The household scale filter was developed to try and combat the fact that

with a community scale slow sand filtration, a small drop in participation of the

stakeholders would results in complete failure of the system for the entire

community. Conversely, a household scale scheme gives proportional benefits to the

amount of participation. It is often found that 98% of households in a community will

adopt the household Biosand filter (Manz, 2007).

It has been widely adopted throughout parts of the developing world in over 70

countries. Over 200,000 filters have been installed and more are being implemented

every day (Manz, 2007). The health benefits from using the filter have been

documented in two pilot schemes in the Dominican Republic and Kenya. During a six

month trial in the Dominican Republic, households benefited from a 47% reduction in

diarrhoeal disease, representing a significant improvement in health conditions

(Stauber et al, 2006.) Similar improvements were experienced by rural communities

in Kenya, where households recorded a 54% reduction in child diarrhoea cases

(Tiwari et al, 2009).

The main difference between a traditional slow sand filter and the Biosand filter

pioneered by Manz is that it is operated intermittently. Water is loaded into the filter

through a diffuser to avoid damaging the biofilm and schmutzdecke below where it is

allowed to drain freely through the sand bed until the water has reached its standing


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level. The water standing level is recommended to be 50mm above the sand bed.

This is to allow oxygen to diffuse through the water to the biofilm on the surface and

keep the host bacteria alive (Buzunis, 1995). The most efficient depth of standing

water for biofilm development was identified to be 20-30mm (Palmateer et al., 1999),

however to prevent disturbing the biofilm and prevent drying of the filter bed in hot,

dry climates 50mm is generally adopted (Manz, 2007). Thus the entire volume of

water put into the reservoir is filtered and requires storage afterwards. However, this

introduces a new pathway for contamination.

Water has been regularly been recorded to have been re-contaminated after filtering

(CAWST, 2009). This could be avoided if the filter was fitted with a tap, so the user

did not to store filtered water and the filter could be used as a true on-demand based

supply. It has been recommended that the flow of water should not be paused during

its flow (Manz, 2009), however recent studies have shown that residence time plays

a key factor in improving the quality of the filtrate (Baumgartner et al, 2007, Elliot et

al, 2008 & Jenkins et al, 2009).

Previous studies looked at the effect of filtering smaller volumes, therefore keeping

the filtrate within the pore space of the sand bed for as long as possible. If a tap were

provided, the same effect could be achieved, but this would result in depths of raw

water greater than 50mm being retained above sand bed. Whilst it would be higher

than the optimum recommended 20mm-30mm depths, this was not developed

through laboratory tests. Buzunis (1995) recorded good filter performance with a


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standing water level of 12.5cm; therefore there is the possibility of achieving good

filter performance with a flow control device.

As a biological process, the filter requires a certain time for the host bacteria to

develop. During this time it is recommended that the filtrate still requires chlorination

(CAWST, 2009). Many communities in the developing world have a low acceptance

to putting chlorine into their water; therefore this step may be omitted altogether

(Manz, 2007). There is also no clear indicator as to when the filter has achieved

satisfactory either. This is a major disadvantage compared to other household water

filtration systems developed by NGO ʻPotters for Peaceʼ such as the Filtron, which

provides immediate treatment, though at much slower flow rates (Latange &

Ambiental, 2002).

The maturation process can take up to 21 days before acceptable performance is

required. The performance can continue to improve until 53 days into operation

(Elliot et al, 2008). Thus methods to improve and speed up the maturation process

are one area where significant improvements can be made to the filter process. This

could be achieved by increasing the amount of nutrients in the form of additional

bacteria in the water, however in practice this is not feasible. In conventional slow

sand filtration, when filter beds are re-sanded after a period of use, the bed is

comprised of sand from the existing filter, with new, clean sand added on top of that.

This enables some of the bacteria and microorganisms to be retained and thus they

are able to populate the bed much more rapidly (Tebbut, 1998). This process could


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be achieved in Biosand filters using sand from existing filters already established

within a community.

2.3. Pesticide removal

The bacterial and pathogen removal capabilities of the filter are well developed and

documented. However, the filters ability to remove other pollutants such as

pesticides and herbicides are not well known. To assess the filters ability to remove

such chemical compounds, Metaldehyde was used in the test series.

Metaldehyde is a molluscicide commonly used to attract and kill snails and slugs

around the world. It is used in household gardens as well agricultural crops. It takes

the form of pellets, sprays foams and others and is applied to the soil around crops

(WHO, 1996).

Metaldehyde is a cyclic polymer of acetaldehyde, and forms a white powder in its

pure forms. The molecular formula is C8H16O4. The structural formula of the molecule

is shown in Figure 2-2.

Figure 2-2 - Structural formula of Metaldehyde (WHO, 1996)

Metaldehyde is soluble in water up to 190 mg/L and has been classified as having

groundwater contamination potential by the EPA and the EA (Kegley et al, 2010). It


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has been shown that existing removal techniques may not remove the pesticide from

water, often failing to reduce background levels, around 8μg/L, down to the required

limit of 0.1 μg/L required by the Environment Agency (EA, 2010).

The WHO classifies Metaldehyde as a class 2 toxin, which means it can be

moderately hazardous to acute health impacts (Kegley et al, 2010). The effects of

ingesting Metaldehyde are wide ranging depending on the dosage received. A small

dosage of up to 50mg/kg of body mass can cause vomiting, dizziness and nausea.

Larger doses can lead to organ failure and death (Extoxnet, 1993). The differing

health impacts and their corresponding dosages of Metaldehyde are shown in Table

2-1.

Table 2.1 - Health effects of Metaldehyde exposure (INCHEM, 1996)

Dosage Health Impacts Toxicity

Up to ≈ 5 mg/kg

• Salivation

• Facial flushing

• Fever

• Abdominal cramps

• Nausea and vomiting

LOW

Up to ≈ 50 mg/kg

• Drowsiness

• Tachycardia

• Spasms

• Irritability

MEDIUM

Up to ≈ 100-200

mg/kg

• Convulsions

• Tremor

• Hyperreflexia

HIGH

Up to ≈ 400mg/kg • Coma

• Death VERY HIGH


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Whilst the short-term health effects have been identified, the long-term effects of low-

level dosage have not been identified. It is not currently listed as a carcinogenic,

mutagenic or endocrine disrupting substance by a number of authorities, however

the EPA has characterized it of being suggestive of such effects (EPA, 2006; Kegley

et al, 2010).

3. Methodology

This chapter describes the experimental design, and methods and techniques used

throughout each of the tests.

3.1. Experiment Design

Three experiments were designed to study how the filter functioned under different

operating conditions with an aim to improve or assess the filters performance. The

experiments were designed as follows:

• Dye Tests – Operating the filters using organic dye to establish the hydraulic

performance of the filter and the residence time the raw water spends in the

filter.

• Filter maturation study – Seeding of new filter bed using sand from existing

Biosand filter to speed up the maturation process.

• Filter flow control study – Filter paused twice during filter runs using a tap for 1

hour, 2 hours and 3 hours to establish and drop in bacteria removal

performance.

• Pesticide removal study - Filter paused twice for 2 hours during each run

using tap, concentration levels at 180μg/L & 1000 μg/L.


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The raw water volume was derived from a minimum basic water requirement of 20L

per capita per day (WHO, 2000) and the reservoir volume of the filter, 12L. This

represents a basic required amount for drinking, hygiene and cooking, however this

may differ depending on the users, physiological, social and cultural norms (Sphere,

2004). A total volume of 24L ensures that the filtrate being sampled can be

compared directly with the raw water, as verified by dye testing and porosity

calculations. The filtrate was sampled 3 times during the filter run, to establish the

effect of different residence times within the filter on water quality.

The test procedure is shown in Figure 3-1.

3.1.1. Filter maturation study

To establish the effect of adding sand from an existing Biosand filter on the rate at

which a new filter matures, one filter (unseeded) was composed of new sand, whilst

the other (seeded) was composed of 50% new sand and 50% sand from an existing

Biosand filter. The top 20cm of sand within the existing Biosand filter was scraped off

and discarded, and 20cm of new, clean sand was added on top to create the seeded

filter. Following the test procedure shown in Figure 3-1, the effects of residence time

and the effect of seeding the filter to speed up its bacterial removal can be studied.

3.1.2. Tap study

To determine the effect of using a Biosand filter with a tap on the quality of the

filtrate, one filter was operated as per the current practice by allowing the entire

reservoir to freely pass through the filter (Figure 3-1), while the other had a tap. The

volume of raw water used for the tap study was 24L. The tap was added to the filter

that had been seeded in the previous study.


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The flow of raw water was paused twice on the filter with the tap, to simulate water

being used at different intervals throughout a day when it was required, rather than

filtering the entire volume of water in the reservoir each time.


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Figure 3-1 Schematic of test procedure and sampling frequency

T = 0 minutes

Add 1st 12L of raw water to filter

T = 45 minutes

Add 2nd 12L of raw water to filter

T = 90 minutes

Take sample after 24L filtered = sample S1

T = 10 minutes

Take sample after 4L filtered = Sample S2

Step 3 – Day 1

T = 0 minutes

Add 1st 12L of new raw water to filter

T = 45 minutes

Add 2nd 12L of new raw water to filter – Take sample S3

T = 90 minutes

Take sample after 24L filtered = sample S1

Step 2 – Day 1

Step 1 – Day 1 Step 5 – Day 2

Step 6 – Day 2

Step 7 – Day 2

Step 4 – Day 2


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The flow on the filter with a tap was paused each time after eight litres of raw water

had flowed i.e. after 8L and 16L, then the water was allowed to flowed until all 24L

had flowed through and the water reached the 50mm standing water level. The

pause period was varied between one, two and three hours. Thus the effects of

pausing the flow of water through the filter on the bacteria removal capacity of the

filter could be determined. The test procedure for the tap study is shown in Figure 3-

2. For clarity, the steps for one day of testing are shown due to the increased

number of steps within the test.


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Figure 3-2 - Schematic of test procedure and sampling frequency for tap study

T = 20 minutes + P1

Open tap and restart flow from filter

T = 90 minutes + P1 + P2

Take sample after 24L filtered = S1

Take sample after 4L filtered = Sample S2

T = 20 minutes

After 8L filtered, close tap & begin Pause 1 (P1)

T = 45 minutes + P1

Step 3 – Day 1

T = 60 minutes + P1

After 8L filtered, close tap & begin Pause 2 (P2)

Step 5 – Day 1

Step 6 – Day 1

Step 8 – Day 1 Step 4 – Day 1

T = 0 minutes

Add 1st 12L of raw water to filter

T = 10 minutes

Step 2 – Day 1

Step 1 – Day 1

Add 2nd 12L of new raw water to filter – Take sample S3

T = 60 minutes + P1 + P2

Step 7 – Day 1

Open tap and restart flow from filter


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3.1.3. Pesticide removal study

As well as establishing whether the Biosand filter was able to remove the organic

contaminant, the effect of the tap on the filter was also studied. This will help to

establish whether one of the removal processes discussed earlier is more effective.

Thus one of the filters was run without pausing the flow as per Figure 3-1, whilst the

filter with the tap was paused twice during the test for 2 hours at a time, following the

Tap study test procedure (Figure 3-2).

The amount of pesticide was increased from normal background levels to be able to

better detect the amount removed by the filter. Therefore concentrations of 180μg/L

& 1000 μg/L were used. Samples were analyzed to determine the residual

Metaldehyde content in the filtrate. The effect of the pesticide on the filterʼs ability to

remove bacteria was also studied carrying out bacteriological analysis of samples

during the pesticide test.

A schematic of the experiments carried out is shown in Figure 3-3.


- 21 -

Figure 3-3 - Schematic diagram of experiment variables & sampling frequency

Pesticide study

No Tap,

C=1 mg/L

No Tap, C=180μg/L

No pause

Tap,

C=180μg/L 2-hour pause

Tap,

C=1mg/L

2-hour pause

Filter with

Tap

No Tap

1-hour pause

Filter with

Tap 2-hour pause

Filter with

Tap 3-hour pause

Variable Samples & Approximate residence Time Pause in test

Maturation study

Unseeded Filter

S1 S2 S3 90mins 24hrs 24hrs

Seeded Filter

No pause

No pause

Tap study

No pause

No pause







S1 S2 S3

90mins 24hrs 24hrs




- 22 -

3.2. Filter Construction

Two Biosand filters were constructed in accordance to the Biosand Filter Manual

(CAWST, 2009). To enable monitoring of the filter during its use, the front of the

filters was constructed from Perspex to allow better inspection of the biofilm and

schmutzdecke development. Coarse and fine gravel were washed and deposited

into the base of the each filter as the under-drain in 50mm layers, before the sand

layer was installed. The 400mm fine sand layer was installed wet into a shallow layer

of water to prevent air bubbles becoming trapped in the filter. The dimensions of

each filter as installed are shown in Figure 3-4.

Figure 3-4 - Plan and section views of constructed Biosand filters

50mm deep fine gravel

300mm

300m

m

PLAN

1100

m

m

50mm deep coarse gravel

400mm deep fine sand

50mm deep standing water

Section


- 23 -

3.2.1. Sand media

A sieve analysis was conducted to establish the effective size of the sand grains and

their uniformity coefficients. The test was carried out in accordance to British

Standard 1377-2:1990 – Methods of test for soils. The sand used in the study was

RH45 sand from WBB Mineralsʼ quarry in Redhill, Surrey.

As 50% of the sand to be used in the maturation study was from the existing Biosand

filter and therefore from a different batch of RH45 sand, a sieve analysis was carried

on a sample of that sand as well to determine any differences between the samples.

The sand was washed to remove fines, then oven-dried at 105°C. The sand was

sieved in a mechanical shaker for 15 minutes through the specified sieve sizes.

Based on the results of this test the effective diameter for the unseeded filter was

calculated to be 0.182mm, with a uniformity coefficient of 1.65. The effective

diameter for the seeded sand was calculated to be 0.202mm, with a uniformity

coefficient of 1.80. This is within typical values of grain size between 0.15mm and

0.30mm and uniformity coefficient of less than 4 for use in slow sand filtration

(Huisman & Wood, 1974). The particle size distribution is shown for both the sand

used for the unseeded and seeded filter respectively are shown in Figures 3-5 and 3-

6. Data for the sieve analysis can be found in Appendix A.

Uniformity Co-efficient = D60

D10

Equation 1 - Uniformity Co-efficient


- 24 -

Figure 3-5 - Particle size distribution - Unseeded sand

Figure 3-6 - Particle size distribution - Seeded sand

D10

D10

D60

D60


- 25 -

3.2.1.1. Sand bed porosity

The porosity of the sand bed was calculated by weighing a known volume of

saturated and unsaturated samples of the RH45 sand and calculating the weight of

water in the void space, therefore the percentage of voids or porosity. This is

expressed in the equation 2.

Equation 2 - Porosity of sand bed

The sand bed was calculated to have a porosity of 41.5%. Therefore the sand bed

could contain a maximum of 14.5L of water. Including the 50mm of standing water on

top of the sand bed, the total volume of water within the filter was 19.5L.

3.3. Dye tests

Dye tests were carried out to establish the residence time of the raw water in the

filter during test conditions following the test procedure in Figure 3-1 to confirm the

time to take samples during the filter test run. It was also used to establish the

possible presence of any wall effects in the columns (Mehta & Hawley, 1969).

3.3.1. Tracer tests

A volume of 2.5mL of organic green food colouring was simultaneously injected at

three locations along the Perspex face of the filter through a syringe. The plug of dye

was photographed at one-minute intervals throughout the test and the filtrate was

sampled every minute for two hours or until all the dye had run through the filter. The

filtrate samples were analyzed with a Spectrophotometer to determine the amount of

light absorbed, thus the concentration of dye.

Porosity = (Mass saturated sand – Mass dry sand)

(Volume of sand x ρwater)


- 26 -

The dye was subsequently injected into the middle of the sand bed and the process

repeated. This will determine whether the flow down the edges of the filter is quicker

than through the sand media. This was repeated twice times for each filter.

3.3.2. Solution tests

To further establish the time to concentration of the sample water flowing through the

Biosand filters, dye tests using 12L raw water dyed with 35mL of organic food

colouring were carried out. The dyed water was put into the filter as per the

experimental procedures (Figure 3-1) using two volumes of 12L dyed solutions. The

samples were taken every minute for two hours or until all the influent had run

through the filter, then analyzed with a Spectrophotometer to establish the

concentration of dye within each sample. From this data the time of peak

concentration can be established. This process was repeated twice for each filter.

3.4. Raw water

To simulate the conditions that the Biosand filter will be used in the field as closely

as possible, water from an unprotected source was required. This was preferred to

rainwater or tap water as both could contain chemicals e.g. Chlorine or other

compounds, which may hinder the development of the biofilm. The water was

collected from the lake in Regents Park in two 25L containers. The exact location is

shown in Figure 3-7.


- 27 -

Figure 3-7 - Raw water sampling location – Regents Park

3.5. Bacteriological analysis & coliform counting

Total coliform bacteria counts were used as the indicator for bacterial improvement

of the filtrate. The membrane filter technique was used to determine the number of

bacteria present in the influent and filtrate. A Nalgene filter and 0.45μm cellulose

membrane filters were used for all bacteriological tests. It is a direct plating method,

therefore as effective as the multiple-tube fermentation method for detecting

coliforms (APHA, 2005). Coliforms were counted using a Stuart SC6 colony counter

and reported as Colony Forming Units (CFU) per 100mL. Raw water was taken in

10mL samples and diluted to make it up to 100mL, as per regulatory requirements

for lake water (APHA, 2005). Filtrate samples were filtered in 100mL quantities. To

Location of sampling from Regents Park

Lake


- 28 -

allow for clear counting of coliforms, this was separated into four 25mL samples as

the filter was ripening and reduced accordingly as the coliform counts became lower.

3.6. Culture Media

Agar plates were produced using a dehydrated culture media. Fluka Modified-Endo

medium was used for total coliform growth. Culture media were prepared in batches

that were refrigerated and used within one week. The M-Endo media has been noted

to produce uncertain results, due to the non-appearance of metallic sheen on

colonies that form on the membrane due to the presence of non-coliforms

(Burlingame et al., 1983). E-Coli detection could have been included to supplement

the data and improve the robustness of the data by providing another indicator of

bacterial quality.

3.7. Metaldehyde sampling & analysis

Samples containing Metaldehyde were collected in PET bottles and stored below

5°C for up to 21 days prior to analysis. The 50mL samples were extracted using the

J.T Baker Solid Phase Extraction process. The samples were then analysed using

Parkin-Elmer Gas Chromatography-Mass Spectrometer to determine the amount of

Metaldehyde in each sample. The analysis process followed the Environment

Agency guidelines for the determination of Metaldehyde in water using GC-MS.

Detailed information on the extraction and analysis process can be found in

Appendix B.


- 29 -

3.8. pH meter

A Jenway 4330 conductivity and pH meter was used to measure the pH of the

samples. The pH meter used was calibrated daily using three standard buffer

solutions (pH 4.0, 7.0 and 10.0). Buffers solutions were dated when opened and

changed every week.

3.9. DO meter

A Jenway DO meter was calibrated every two weeks using standard solutions of

0mg/L and 100mg/L. The membrane was kept wet at all times to ensure no air

bubbles become trapped on the surface of the selective membrane.

3.10. Sterilization

All sample collection bottles, membrane filter assembly and pads, dilution and rinse

water used in microbial analysis were autoclaved at 121°C for 15 minutes. All

equipment was washed and rinsed thoroughly before use and stored in foil prior to

autoclaving. Heat indicating tape was applied to equipment to ensure it had reached

the required temperature. Safety cabinets and hoods were cleaned weekly before

and after use and wiped with surgical spirit.


- 30 -

4. Results and Discussion

4.1. Dye Testing

The tracer dye tests showed that the unseeded filter had a mean time to flow of 66

minutes when the dye was injected in the middle of the filter. When the filter was

injected against the wall of the unseeded filter the mean time to flow was 65 minutes.

This is shown in Figure 4-1. Tests Centre-2 and Centre-4 showed a time to flow of

71 minutes, slower than the other times. This coincided with a significant drop in the

temperature of the influent water, which was 7°C colder than the mean temperature

of 22°C. This would increase the viscosity of the water and reduce the rate of flow

through the filter, thus explaining the resulting longer time to flow.

Figure 4-1 - Graph of Light absorption against Time – Unseeded filter


- 31 -

The tracer dye tests for the seeded filter showed a mean time to flow of 60 minutes

when the dye was injected in the middle of the filter. The time to flow when injected

against the wall of the filter was 62 minutes. Using an independent t-test analysis to

compare the time to concentration for when dye was injected in the centre and at the

wall, the significance factor, p, of the injection point is 0.117. Therefore it can be said

that the injection point of the dye within the filter is not significant. This can be seen

in Figure 4-2.

Figure 4-2 - Light absorption against Time - Seeded filter

The unseeded filter would also have had a longer time to flow due to the increased

resistance to the flow from the slightly smaller grain size used in that bed. The

solution dye tests in both filters showed that under test conditions, the time to

concentration of the dye tests occurred at 80 minutes. This was determined when


- 32 -

the rate of change of light absorbed by the samples showed no further increase. The

total volume of 24L was filtered in 90 minutes. Therefore the samples taken at 90

minutes into the test after 24L is definitely the filtrate of the raw water put in that day.

The time to peak concentration is shown in Figure 4-3 for both filters.

Figure 4-3 - Light absorption against Time - Unseeded & seeded solution tests

Photographs showing the dye tracer tests in progress at time intervals of 5 minutes

and 70 minutes are shown in Figure 4-4.


- 33 -

(a) Dye Tracer test – Unseeded filter – T = 5 minutes

(b) Dye Tracer test – Unseeded filter – T = 70 minutes

Figure 4-4 - Dye Tracer tests in Unseeded filter at (a) 5 mins & (b) 70 mins

4.2. Filter maturation study

4.2.1. Coliform removal efficiency

The unseeded filter initially produced low coliform removal rates. Over the first five

days to of operation the filter achieved a maximum of 53% coliform bacteria removal.

As the filter and schmutzdecke were still maturing and developing, respectively, in

this period, the main removal mechanisms acting are physico-chemical attachment

of bacteria to the sand and physical straining of bacteria in the sand bed. The filter

matures as the microbiology is established, and the schmutzdecke begins to develop

and the biofilm grows on sand grains.


- 34 -

The unseeded filter achieved 90% removal after 15 days operation when S2 and S3

were collected with residence time of 24 hours. It took a further 11 days operation to

achieve 99% removal rates at 26 days. This rate of bacteria removal is considered to

be a mature filter (Manz, 2007). The coliform removal rates are shown in Figure 4-5.

Figure 4-5 - Graph of Coliform removal rate against time - Unseeded filter

The seeded filter reached higher coliform removal rates much more rapidly. After 7

days of operation it had achieved 90% coliform removal when samples S2 and S3

were collected. (Figure 4-6). This improved to 99% coliform removal after 16 days of

operation.


- 35 -

The samples S1 taken at the same day they have been filtered (i.e. residence time

equal 45min) had consistently lower coliform removal rates in both filters and did not

achieve consistently high coliform removal rates. Whilst the removal rate reached

80% removal after 10 days of operation in the seeded filter compared to 18 days in

the unseeded filter, after this it showed no further improvement, fluctuating around

this mark throughout the remainder of the tests. This can be seen in Figure X. It can

also be seen that the seeded filter started with much higher coliform removal rates

(<50%) while the unseeded filter started with lower coliform removal rates (>30%).

Figure 4-6 - Graph of Coliform removal rate against time - Seeded filter

A one-way analysis of variance was carried out to test the null hypotheses that

bacterial removal across with seeded and unseeded filters at each residence time


- 36 -

was equal. A p value of < 0.05 is considered to be significant. For sample S1,

seeding did not have a significant effect on the bacteria removal of filtrate (p =

0.393). This indicates that after 12L of water have been filtered, there is a decrease

in biological activity as the microorganisms within the filter have consumed as much

of the pathogens as possible, regardless of whether the filter has been seeded or

not. For samples S2 and S3, the seeding had a significant effect on the bacterial

quality of the filtrate, with significance factor p = 0.001 and 0.026 respectively.

Therefore it can be said that when the filter is used as per the standard procedure

i.e. using 12L raw water volumes, seeding has a significant effect on the bacterial

quality of the filtrate. It does not appear to have significant benefits when volumes of

water greater than 12L are filtered.

Table 4.1 – Effect of seeding on coliform removal rates for samples collected at different residence time.

Samples Seeded / Unseeded N Mean Coliform removal

(95% CI) Min–Max removal

Significance, p-value

S1 Unseeded 15 56.8% (41.5%, 72.2%) 0.00% - 83.2% Seeded 15 65.6% (49.9%, 81.6%) 0.00% - 87.3%

0.393


0.001


0.026

Note: N = number of samples

The significance of the sampling point within each filter was compared using

independent variable t-tests. For the seeded filter, samples S2 and S3 had

significantly higher removal rates than samples S1 (p = 0.004 and 0.036

respectively). There was no significant difference between samples S2 and S3 (p =

0.280). The unseeded filter showed no significant difference between samples S1,


- 37 -

S2 or S3 (p = 0.420, 0.869 and 0.576 respectively). This shows that the effect of

increased residence time does not affect performance until the filter is more mature.

As a more mature filter will have higher populations of microorganisms, this suggests

that it is the process of biological predation that is most prevalent during increased

contact time with the filter.

Table 4.2 – Effect of residence time on coliform removal rates for seeded and unseeded filters

Seeded/Unseeded Sample point N Mean Coliform

removal (95% CI) Significance, p-

value Seeded S1 15 65.6% (49.9%, 81.6%)

S2 15 91.7% (86.0%, 92.3%) 0.004

Seeded S1 15 65.6% (49.9%, 81.6%) S3 15 84.1% (80.4%, 97.8%)

0.036

Seeded S2 15 91.7% (86.0%, 92.3%) S3 15 84.1% (80.4%, 97.8%) 0.280

Unseeded U1 15 56.8% (41.5%, 72.2%) U2 15 65.2% (49.9%, 80.3%) 0.420

Unseeded U1 15 56.8% (41.5%, 72.2%) U3 15 58.7% (40.0%, 77.4%) 0.869

Unseeded U2 15 65.2% (49.9%, 80.3%) U3 15 58.7% (40.0%, 77.4%) 0.576

4.2.2. DO Consumption

During the filter maturation, increasing DO consumption levels were observed during

throughout. The consumption rates peaked when the filter reached maturation at 7

days and 15 days for the seeded filter (Figure 4-8) and unseeded filters (Figure 4-7)

respectively. The DO consumption was on average 68.1% for the seeded filter for

samples S2 when mature, while the unseeded filter consumed on average 66%.

Raw water was taken from a source with relatively high DO levels where flora and

fauna are abundant. DO levels in the raw water were always above 6mg/L, the


- 38 -

lowest levels required to sustain fish and other aquatic life. There was some variation

of DO level depending on the temperature and time of day the water was taken, as

both affect the amount of DO present due to the rate of photosynthesis of plants. If

lower DO levels were present in raw water, which may be found in groundwater from

wells, similar performance may not occur during the maturation process.

Figure 4-7 - Dissolved oxygen consumption against time (Unseeded filter)


- 39 -

Figure 4-8 - Dissolved oxygen consumption against time (Seeded filter)

The rate of consumption of DO seems to change as the filter is maturing, as the

unseeded filter shows higher consumption in the early stages of the maturation, then

plateaus. This can be seen in the seeded filter, as the DO consumption is almost

constant.

4.2.3. Headloss development

Headloss was monitored through the experiment and increased for both filters

throughout the maturation period and through the other tests. The unseeded filter

experienced much higher headlosses throughout the maturation period. The

headloss increased from an initial value of 6cm to 8.5cm after 19 days of filtration.

This continued to increase until the final test 54 days later, reaching a maximum of

12.4cm, an increase of 31%. This can be seen in Figure 4-9.


- 40 -

The seeded filter experienced lower headlosses through the tests. Initial losses were

4.3cm, increasing to 5.9cm after the maturation period. This is an increase of 28%, a

similar increase to the unseeded filter. However, by the final test headlosses had

increased to only 6.8cm, a further 14% increase, as shown in Figure 4-9.

Figure 4-9 - Headloss development for seeded and unseeded filters

This suggests that microbial dynamics therefore play an important role in headloss

development in slow sand filtration and the consumption of organic material reduces

filter clogging.

It can be seen that the headloss increases as the filters are operated and

schmutzdecke is developed. As the seeded filter experienced significantly less

headloss after maturity has been reached, this suggests that the biofilm and bacterial


- 41 -

population had fully developed by this stage. Headloss increase was observed in the

unseeded filter throughout the tests after the filter was considered mature, even

though the turbidity of the raw water was the same for both filters. This suggests that

deeper biological activity was still being established and takes much longer to

develop than the initial biofilm. This seems to be in contrast to typical headloss

profiles of uncovered filters, where the entire headloss occurs in the schmutzdecke

layer and the sand layers make no significant contribution (Barrett & Silverstein,

1988).

4.2.4. Turbidity reduction

The ability of the filter to reduce the turbidity of the filtrate was present from the initial

test in both the unseeded and seeded filter. Even when the biofilm wasnʼt considered

to be mature, the turbidity was reduced from a mean value of 8.85 NTU in the raw

water to below 1 NTU at sample points 2 and 3 for both filters. At sample point 1, the

recorded turbidity was generally higher than 1 NTU, as shown in Figure 4-11 and

Figure 4-12 for the unseeded and seeded filter respectively. This indicates that as

well as the physical straining of the sand bed; the increased residence time of

samples taken at 4L and 12L enabled greater physico-chemical removal of

suspended particles from the raw water. As the biofilm matured further, greater

turbidity reduction was observed. The biofilm and schmutzdecke thus increases

physical removal of particles as they adhere to the sticky surface or zooglea it

creates or are trapped within the porous mat of the schmutzdecke.


- 42 -

The unseeded filter showed higher reduction in turbidity levels (Figure 4-12). This

could be attributed to the lower effective diameter (0.182mm) of the grains used in

that filter, as the grains from the existing Biosand filter were 10% larger in their

effective diameter (0.202mm). This indicates that the effective size of the filter may

be more important in the reduction of turbidity levels than the maturity of the biofilm.

Figure 4-10 - Turbidity of raw water


- 43 -

Figure 4-11 - Turbidity of Filtrate - Unseeded filter

Figure 4-12 - Turbidity of Filtrate - Seeded Filter


- 44 -

The seeded filter clearly displays improved performance and speeds up filter

maturation i.e. 99% bacteria removal, 16 days before the unseeded filter (Figure 4-

8). However in the field it may not be possible to obtain sand 50% of the volume of

sand required from existing filters. Further studies should be carried out with varying

depths of seeded sand to measure the impact. The position of the seeded sand

within the filer should also be studied. As the biological activity within the filter

occurs) and the biofilm at the surface develops first near the surface, where food and

oxygen are more abundant for bacteria, it may be that putting the seeded sand at the

bottom of the sand bed enables the deeper bacteria community, up to depths of

0.4m within the filter (ASCE, 1991), to develop more quickly as they move towards

the food and oxygen source above.

Figure 4-13 – Possible positions of seeded sand within a filter

1. Bacteria in seeded sand move up through the bed closer to oxygen and food source.

2. Bacteria in seeded sand remain near surface to oxygen and food source

Scenario 1 Scenario 2


- 45 -

In addition to increasing the amount of bacteria within the filter by using sand from an

existing Biosand filter, it may be possible to add nutrients to the raw water to allow

the biofilm and host microorganisms to multiply more quickly if the raw water is low in

nutrients and bacteria. A simple packet of glucose could be added to the raw water

prior to being filtered. This can be a cheap, organic way to increase the nutrients for

the bacteria within the filter.

4.3. Tap study

4.3.1. Coliform removal efficiency

The mean coliform removal rate for the filter with tap was above 99% for samples S2

and S3 collected with residence time of 24h. Even at overflow conditions, samples

S1 achieved 97% mean coliform removal rates. This is contrary to recommendations

that the flow should not be stopped during the filtration (Manz, 2007). The mean

coliform removal rates for filters with and without tap are shown in Table 4-3.

Table 4.3 - Coliform removal rates and significance factors for filters with and without Tap

Sampling Point

Tap / No Tap N Mean Coliform removal

(95% CI) Min–Max removal


1 No Tap 15 84.2% (82.5%, 85.9%) 80.0% - 88.0% Tap 15 97.1% (94.2%, 99.0%) 91.7% - 99.9% <0.001

2 No Tap 15 98.9% (97.8%, 99.9%) 95.4% - 99.9% Tap 15 99.9% (99.7%, 100%) 99.1% - 100% 0.042

3 No Tap 15 98.3% (97.3%, 99.4%) 95.0% - 99.8% Tap 15 99.6% (99.2%, 99.9%) 98.1% - 100% 0.023

A one-way analysis of variance (ANOVA) was carried out to assess the effect of the

tap on the coliform removal rate at different sampling points. The tap had the most

significant effect on sample point 1. The filtrate from the filter with the tap was

significantly higher (p < 0.001%) than the filter without. At sample points 2 and 3, the


- 46 -

tap still provided significantly higher removal rates (p = 0.042 and 0.023

respectively).

This shows that at the filter with tap consistently provided higher coliform removal

rates. The tap increases the residence time and allows smaller volumes of water to

be filtered without storage. This follows work by Baumgartner et al. (2007), which

identified that smaller dosing volumes of water filtered had lower coliform counts.

Table 4.4 – Coliform removal rates on filters with tap and without tap

Tap / No Tap Sampling Point N Mean Coliform removal

(95% CI) Significance,

p-value Tap 1 15 97.1% (94.2%, 99.0%)

2 15 99.9% (99.7%, 100%) 0.004

Tap 1 15 97.1% (94.2%, 99.0%) 3 15 99.6% (99.2%, 99.9%) 0.036

Tap 2 15 99.9% (99.7%, 100%) 3 15 99.6% (99.2%, 99.9%) 0.280

No Tap 1 15 84.2% (82.5%, 85.9%) 2 15 98.9% (97.8%, 99.9%) 0.005

No Tap 1 15 84.2% (82.5%, 85.9%) 3 15 98.3% (97.3%, 99.4%) 0.012

No Tap 2 15 98.9% (97.8%, 99.9%) 3 15 98.3% (97.3%, 99.4%) 0.088

There were also significantly higher removal rates between samples at different

residence time for filters with and without the tap. Independent t-tests showed that

samples S1 had statistically significantly lower coliform removal rates over both

samples S2 and S3 for both filters, p = .0.004 and 0.036 for the filter with tap and

0.005 and 0.012 for the filter without tap. This shows that even with the improved

performance of the tap, the effect of residence time within the filter is significant.


- 47 -

Figure 4-14 - Coliform removal rate against time – Filter without Tap

This is in contradiction to current recommendations that pauses in filter flow are

detrimental to the filterʼs performance (Manz, 2007). Clear improvement can be seen

in the filtrate of the filter, which was paused using the tap. Even a 1-hour pause

increases the performance of the filter. Thus using tap for on-demand supply may be

a possible solution to increase performance of the filter and avoid one of the

pathways to recontamination.

However, the filter was always run down to 50mm pause level after 24-litres had

been filtered during the experiment. The effect of different pause levels on filter

performance should be investigated to assess any unfavourable combinations of

standing water level and pause time on filter performance.


- 48 -

Figure 4-15 - Coliform removal rate against time – Filter with Tap

4.3.2. DO consumption

The higher bacteria removal rates correlated with higher DO consumption when

using the tap. During the pause introduced by the tap, it is proposed that during the

increased residence time more of the organic matter begins to be broken down in the

raw water into more assimilable elements while still at the supernatant stage

(Huisman & Wood, 1974) and the bacteria consume more of the pathogens through

predation. Therefore as both of these processes require the consumption of more

oxygen, a reduction in DO of the filtrate occurs and the water quality is improved.

The DO consumption of each filter over the course of the Tap study is shown in

Figure 4-17. It can be seen from the graph that higher bacteria removal rates

occurred when using the tap.

1hr pause 2hr pause 3hr pause


- 49 -

Figure 4-16 - Coliform removal rate against DO consumption – No Tap

Figure 4-17 - Coliform removal rate against DO consumption - Tap


- 50 -

From the above graphs it can be seen that the amount of DO concentrations in the

raw water is critical. The raw water collected for this study was sufficient to sustain

fish and other wildlife, i.e. it contained a minimum DO concentration of 6 mg/l, in its

natural environment. These high concentrations of DO may have sustained the

bacteria within the biofilm and sand bed for longer during pause times. In addition to

this, the water inside the filter is not exposed to sunlight, as a normal slow sand filter

would be. As such it is not subject to the diurnal variations in DO levels caused by

the photosynthesis of algae (Tebbut, 1998). In this situation, water with higher

amounts of algae present will consume more DO during the paused periods when

using the tap. Despite this, it is recommended that the use of a tap be considered in

the design of the Biosand filter.

There are no current recommendations for the minimum DO levels for raw water to

be used with Biosand filters, as in developing countries it is difficult to be continually

monitored. However, it could be assessed during the pilot scheme or prior to

implementation of the filters in a community.

4.3.3. Turbidity Reduction

The effect of the tap on turbidity reduction was minimal, with no improvement gained

from increasing the residence time within the filter. The mean turbidity values for the

filter with and without a tap are shown in Table 4-5.


- 51 -

Table 4.5 - Mean turbidity for filtrate from filters with & without tap Mean Turbidity (NTU)

No pause No pause No pause No Tap-S1 1.44 1.51 1.44 No Tap-S2 0.82 0.62 0.90 No Tap-S3 0.82 0.80 0.99 1hr pause 2hr pause 3hr pause Tap-S1 1.44 1.56 1.23 Tap-S2 1.03 1.26 1.01 Tap-S3 1.19 1.33 1.32

The main factor affecting turbidity was again the sampling point. Samples S2 and S3

had lower turbidity than the sample S1. This can be seen in Figure 4-18 and Figure

4-19, as the samples S1 clearly shows the lowest turbidity. This suggests that the

processes involved in reducing turbidity during residence time in the filter require

more than 3 hours (the longest pause period using the tap) to be effective.

Figure 4-18 - Turbidity of filtrate - Filter without tap


- 52 -

Figure 4-19 - Turbidity of filtrate - Filter with tap

4.3.4. pH reduction

The filtrate of both filters showed a reduction in pH. This reduction in pH shows that

the filter is degrading the DOC within the raw water, thus producing organic acids

(Zheng et al, 2007). The mean pH values for the filtrate are shown in Table 4-6.

From this it can be seen that the tap does not increase the removal of DOC, however

similar improvement is seen in S2 and S3 that have had longer residence time, S2

showing greatest reduction in pH.

Table 4.6 - Mean filtrate pH for filter with & without tap Mean pH

No pause No pause No pause No Tap-S1 8.44 8.64 8.44 No Tap-S2 8.30 8.51 8.33 No Tap-S3 8.33 8.57 8.36 1hr pause 2hr pause 3hr pause Tap-S1 8.39 8.46 8.37 Tap-S2 8.30 8.59 8.32 Tap-S3 8.33 8.50 8.34

1hr pause 2hr pause 3hr pause


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5. Pesticide removal

The first tests used lower concentrations of Metaldehyde within the raw water. The

filter did not consistently or effectively remove the Metaldehyde from the water. A

paired t-test showed that the mean amount of Metaldehyde removed was not

significant, compared to the influent concentration (p = 0.78). A large variation was

recorded in the maximum and minimum amount of Metaldehyde removed (Table 5-

1).

Table 5.1 - Reduction in Metaldehyde concentration at 180µg/L & 1000µg/L

Concentration Tap / No Tap N

Mean reduction in Metaldehyde

concentration (95% CI)

Min–Max removal


180µg/L No Tap 12 6.1% (1.0%, 10.9%) 0.00% - 70.5% Tap 12 2.9% (0.5%, 6.3%) 0.00% - 93.3% 0.893

1000µg/L No Tap 12 11.7% (18.7%, 4.9%) 0.00% - 70.1% Tap 12 10.2% (16.6%, 3.8%) 0.00% - 73.4% 0.731

There was no significant reduction in the amount of Metaldehyde removed when

using the filter with a tap at the high and low concentrations, (p = 0.731 and 0.893

respectively). Some of the results even showed higher concentrations than those in

the influent. This suggests that the concentration of the pesticides added to the filter

did not remain evenly distributed throughout the process, giving rise to large

variations in concentration. This variation is shown for the filter with tap in Figures 5-

1 and 5-2 and for the filter without tap in Figures 5-3 and 5-4.


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Figure 5-1 – Concentration of Metaldehyde in filtrate at 180µg/L – Filter without Tap

Figure 5-2 Concentration of Metaldehyde in filtrate at 1000µg/L – Filter without Tap


- 55 -

Figure 5-3 Concentration of Metaldehyde in filtrate at 180µg/L – Filter with Tap

Figure 5-4 Concentration of Metaldehyde in filtrate at 1000µg/L – Filter with Tap


- 56 -

Despite the filter being mature when the tests were carried out, the biofilm and

schmutzdecke do not seem able to breakdown the Metaldehyde. During this period,

the filters still recorded high levels of bacteria removal (mean coliform removal of

95.2% for the unseeded filter, 99.3% for the seeded filter). This shows that the

presence of pesticides within the water does not affect the activity of the bacteria

within the filter, as coliform removal rates are still high.

There was also no significant difference between the samples 1,2 and 3, which was

previously identified during the bacteriological testing. This indicates that increase in

residence time does not affect the processes involved in breaking down the

pesticide, or that the residence time of 24hrs is not sufficient for the process to have

an effect.

The failure of the filter to significantly reduce the concentration of Metaldehyde could

be because the concentration was too great for the filter, and the removal rates were

not noticeable. The high concentrations that were higher than the influent

concentration could also have been due to errors during the extraction and analysis

process. The solvent used to dissolve the Metaldehyde (Dichloromethane) into the

vials used for analysis is extremely reactive. As such any exposure to air will reduce

the volume of solvent very quickly. Any reduction in volume of solvent will

concentrate the sample further giving rise to errors within the sample. However the

distribution in concentration is too large to be attributed to this, therefore there may

be another mechanism, which concentrates the Metaldehyde into certain parts of the

filtrate.


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6. Conclusions and Recommendations

6.1. Maturation Study

The filter seeded with sand from an existing filter showed greatly improved

performance, and identified that the process is greatly speeded up by adding 50% of

the sand from another existing filter. The effect of putting smaller volumes of seeded

sand should be studied, as this would increase the number of filters that could be

seeded using the same volume of sand. The position of where the seeded sand was

installed in the new filter could be important an important consideration, as it could

affect how the biofilm develops. The effect of adding nutrients to the water was

identified as being another possible route to speeding the rate of maturation.

To confirm the performance of the filter on removing pathogens more specifically, the

samples should be assessed for E-Coli bacteria as well, rather than the effect on

broad indicator bacteria that total coliform counts give.

The characteristics of the raw water being filtered will also have an impact on how

the biofilm develops. DO was shown to be consumed much more quickly in the initial

stages of maturation, therefore variations in DO and nutrients in the water can have

an effect on the maturation process, possibly making the effect of seeding even

more prevalent.

As the filters were not required to be cleaned during the process due to low turbidity

of raw water, the performance of how the filter performs after it is cleaned should


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also be studied, as the biofilm and schmutzdecke will be disturbed during this

process.

6.2. Tap study

The tests conducted on the filters with the tap proved that the tap did not adversely

affect the performance of the filter to which it was fitted, and the pause in the flow

that it introduced did not reduce the bacterial quality of the filtrate. The filter that was

seeded in the previous study was the one fitted with a tap; therefore the filter may

have been performing better than the other one before the study. It is therefore not

possible to definitively say that the performance of the filter with a tap was better

than the one without a tap. However, it can be shown that the tap did not have a

detrimental effect on the filter it was fitted to. This therefore should help to eliminate a

pathway to recontamination of the filtrate, as storage of the water after it has been

filtered is no longer required.

The provision of the tap may also have an impact on the maturation of the filter, so

should be incorporated into a further study of how the filter mature when provided

with a tap.

Again, incorporating the removal of E-coli to confirm the removal rate of pathogenic

bacteria as well as total coliforms would help to confirm the performance of the filter.


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6.3. Pesticide Study

The study into pesticide removal did not confirm whether the filter could significantly

remove Metaldehyde from the raw water due to very wide ranging concentration of

Metaldehyde in the filtrate. Despite this, certain results from the test did show

marked reductions in the concentration of the pesticide.

It is therefore possible that at lower concentrations, different levels of performance

may be noticed and a better understanding of the filter to remove such contaminants

can be gained.

Different methods to analyse the samples should also be tested. There are currently

five approved methods for use by the environment agency. Further research into

other procedures using GC-MS should be carried, as well as analysis by High

performance Liquid Chromatography (HPLC).


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7. References

APHA (2005). Standard Methods for the Examination of Water & Wastewater: Contennial Edition 21st ed., American Technical Publishers, New York, USA. ASCE (1991) Slow sand filtration. Logsdon, G.S. (Ed). American Society of Civil Engineers, New York, USA. Barrett, J.M., and Silverstein, J. (1988) The effects of high carbon and high coliform feed waters on the performance of slow sand filters under tropical conditions, in Slow sand filtration: recent developments in water treatment technology. Edited by N.J.D. Graham, Ellis Horwood Ltd., Chichester, UK pp 231–252. Baumgartner, J., Murcott, S. & Ezzati, M. (2007) Reconsidering ʻappropriate technologyʼ: the effects of operating conditions on the bacterial removal performance of two household drinking-water filter systems. Environmental Research Letters, 2 (2), pp 24-33. Brock, T.D. & Madigan, M.T. (1991) Biology of Microorganisms. 6th Edition. Prentice Hall, New Jersey.

Burlingame, G. A., Mcelhaney, J., Bennett, M. & Pipes, W. (1983) Bacterial Interference with Coliform Colony Sheen Production on Membrane Filters, Applied And Environmental Microbiology, Vol 47(1), pp 56-60. Buzunis, B.J. (1995) Intermittently Operated Slow Sand Filtration: A New Water Treatment Process. University of Calgary, Canada. Centre for Alternative Water and Sanitation (2009) Biosand Filter Manual Design, Construction, Installation, Operation And Maintenance, Calgary, Canada.


- 61 -

Elliott, M.A., Stauber, M.A., Koksal, F., Ortiz, G.M., Digiano, F.A., Sobsey, M.D. (2008) Reductions of E. coli, echovirus type 12 and bacteriophages in an intermittently operated household-scale slow sand filter, Water Research, 42(10-11), pp 2662-2670. Environment Agency (2010) The Environment Agencyʼs position on Metaldehyde, Accessed at: http://www.environmentagency.gov.uk/static/documents/Business/Metaldehyde_position_statement.doc-27.1.10.pdf on 7 April 2010.

Extension Toxicology Network (1996) Pesticide Information Profiles: Metaldehyde. Accessed at http://extoxnet.orst.edu/pips/metaldeh.htm on 4 April 2010. Haarhoff, J. & Cleasby, J. (1991) Biological and Physical Mechanisms in Slow Sand Filtration. In Slow Sand Filtration. American Society of Civil Engineers, New York, USA, pp. 19-68. House, S. & Reed, R. (1997) Emergency Water Sources. WEDC, Loughborough, UK, p.171. Huisman, L. & Wood, W.E., (1974) Slow Sand Filtration, WHO, Geneva, Switzerland. International Program on Chemical Safety, (1990) Metaldehyde. Accessed at http://www.inchem.org/documents/pims/chemical/pim332.htm#SectionTitle:3.3%20%20Physical%20properties on 5 April 2010. Kegley, S.E., Hill, B.R., Orme S., & Choi A.H., PAN (2010) Pesticide Database, Pesticide Action Network, San Francisco, North America, http://www.pesticideinfo.org.

Latagne, S.D. & Ambiental, A., Research on clay filters impregnated with colloidal silver promoted by Potters for Peace, USAID, New York.


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Manz, D. (2007) BioSand Water Filter Technology: Household Concrete Design, University of Calgary, Canada. Mehta, D. & Hawley, M.C. (1969) Wall Effect in Packed Columns, Industrial & Engineering Chemistry Process Design and Development, Vol 8(2), pp 280-282. Palmateer, G., Manz, D., Jurkovic, A., McInnis, R., Unger, S., Kwan, K.K. & Dutka, B.J. (1999) Toxicant and Parasite Challenge of Manz Intermittent Slow Sand Filter. Environmental Toxicology, Vol. 14, pp 217- 225.

Potters for Peace (2008) www.pottersforpeace.org, accessed 19 March 2010 Prüss-Üstün A, Bos R, Gore F, Bartram J. (2008) Safer water, better health: costs, benefits and sustainability of interventions to protect and promote health, World Health Organization, Geneva. Stauber, C.E., Elliot, M.A., Koksal, F., Ortiz, G.M., Digiano, F.A., Sobsey, M.D. (2009) A randomized controlled trial of the concrete biosand filter and its impact on diarrheal disease in Bonao, Dominican Republic. The American Journal of Tropical Medicine and Hygiene, 80(2), pp 286-293. Tebbutt, T.H.Y., (1997). Principles of Water Quality control, 5th edition., Butterworth-Heinemann, Oxford, UK. Tiwari, S.K., Schmidt, W.P., Darby, J., Kariuki, Z.G & Jenkins, M.W. (2009) Intermittent slow sand filtration for preventing diarrhoea among children in Kenyan households using unimproved water sources: randomized controlled trial, Tropical Medicine & International Health: TM & IH, 14(11), pp 374-1382.

The Sphere Project (2004) Humanitarian Charter and Minimum Standards in Disaster Response, The Sphere Project: Geneva, Switzerland.


- 63 -

United Nations Children's Fund (2006) Annual Report, New York, US. Accessed at http://www.unicef.org.uk/publications/pdf/ar2006.pdf 4 February 2010.

United Nations Development Program (2006) Beyond scarcity: Power, poverty and the global water crisis, Palgrave Macmillan, Hampshire UK.

United Nations Water (2008) UN Water Annual report 2008. Accessed at http://www.unwater.org/downloads/annualreport2008.pdf, 17 March 2010.

Visscher, J.T. (1990) Slow Sand Filtration: Design, Operation and Maintenance,

Journal of American Water works Association, Vol. 82 (6), pp 67-71.

Weber-Shirk, M. & Dick, R. (1997) Biological mechanisms in slow sand filters. Journal American Water Works Association, Vol 89 (1), pp 87-100.

Wheeler, D., Bartman, J. & Loyd, B.J. (1988) The removal of viruses by filtration through slow sand filtration : recent developments in water treatment technology. Graham, N.J.D. (Ed.) John Wiley & Sons, New York, USA.

World Health Organisation (2009) How much water is needed in emergencies: Technical Note for Emergencies 9, Geneva, Switzerland.

World Health Organisation (1996) Data sheets on pesticides No. 93: Metaldehyde, Accessed at http://www.inchem.org/documents/pds/pds/pest93_e.htm#1.4 on 3 April 2010.

Zheng, X., Liang., Z. & Jekel, M. (2009) Effect of slow sand filtration of treated wastewater as pre-treatment to UF, Desalination, Vol. 249 (2), pp 591-595.


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8. Appendices


- 65 -

Appendix A

Sieve Analysis Data


- 66 -

Sieve Analysis to BS 1377-2:1990 - Methods of test for soils for civil engineering purposes

Sand type RH 45 - Unseeded

Sand source Redhill quarry, Surrey

Mechaical shaking time 15 minutes > 10 minutes = OK

Weight of sample 200g > 150g = OK

Sieve Size (micron)

Weight in sieve (g)

Weight retained (g)

% Retained % Retained (cumulative)

% Passing sieve

1000 0 0 0.00% 0.00% 100%

710 0.2 0.2 0.10% 0.10% 99.90%

500 0.12 0.32 0.06% 0.16% 99.84%

355 50 50.32 25.00% 25.16% 74.84%

250 73.8 124.12 36.90% 62.06% 37.94%

180 55.28 179.4 27.64% 89.70% 10.30%

125 17.8 197.2 8.90% 98.60% 1.40%

106 1.2 198.4 0.60% 99.20% 0.80%

63 1.46 199.86 0.73% 99.93% 0.07%

<63 (Pan) 0.12 199.98 0.06% 99.99% 0.01%

Red denotes amount in sieve more than 50g. Sieve in two parts

Total Sieved weight within 0.1% of Total = OK


- 67 -

Sieve Analysis to BS 1377-2:1990 - Methods of test for soils for civil engineering purposes

Sand type RH 45 - Seeded

Sand source Redhill quarry, Surrey

Mechaical shaking time 15 minutes > 10 minutes = OK (Clause 9.3.4.5)

Weight of sample 200g > 150g = OK (Clause 9.33 & Table 3)

Sieve Size (micron)

Weight in sieve (g)

Weight retained (g)

% Retained % Retained (cumulative)

% Passing sieve

1000 0 0 0.00% 0.00% 100%

710 0.36 0.36 0.18% 0.18% 99.82%

500 4.1 4.46 2.05% 2.23% 97.77%

355 74.8 79.26 37.40% 39.63% 60.37%

250 77.9 157.16 38.95% 78.58% 21.42%

180 28.48 185.64 14.24% 92.82% 7.18%

125 12.2 197.84 6.10% 98.92% 1.08%

106 0.9 198.74 0.45% 99.37% 0.63%

63 1.16 199.9 0.58% 99.95% 0.05%

<63 (Pan) 0.1 200 0.05% 100.00% 0.00%

Red denotes amount in sieve more than 50g. Sieve in two parts

Total Sieved weight within 0.1% of Total = OK


- 68 -

APPENDIX B

Determination of Metaldehyde in water using gas

chromatography and mass spectrometry.

Detailed Methodology


- 69 -

Introduction

To detect and analyse the amount of Metaldehyde remaining in the filtrate from the

Biosand filters, the Environment Agency - Method A (EA, 2009) was followed. Prior

to analysis, the samples were processed using J.T baker solid phase extraction. This

section will detail the methods used throughout.

Methodology

Solid Phase Extraction

1. Condition the solid phase cartridge using 10mL of Ethanol. Elute the cartridge

with the Ethanol and discard the Eluate. Do not allow the meniscus to drop

below the level of the cartridge.

2. Elute the cartridge with 2mL of de-ionised water. Discard the eluate. The

meniscus of the water should still remain above the level of the cartridge.

3. Elute the cartridge with the sample to be analyzed. Typically the sample size

is 250mL, depending on the concentration of Metaldehyde in the water. As the

concentration in this experiment is higher than typical background levels,

50mL was used. Discard the Eluate.

4. Dry the sample thoroughly by passing air through the cartridge. This takes up

to 45 minutes.

5. Elute the cartridge with 2mL of Dichloromethane. Collect the eluate.

6. Evaporate the combined Dichloromethane sample. Nitrogen gas was used in

the blow-down process, as it is the most inert gas. The sample should be


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evaporated to the required volume, typically 0.5mL. To enable proper

sampling by the GC-MS auto-sampler 1mL was used.

7. Add 5.0μL of working internal standard for every 0.5mL of sample volume. As

the sample prepared was 1.0mL, 10μL of or working internal standard was

added. The sample is now ready for GC-MS determination.

GC-MS Determination & Analysis

1. Set up the GC-MS with the following parameters

• Injection temperature – 260°C.

• Oven Temperature – Initial temp at 50°C, increase at a rate of 20°C per

minute to 260°C. Hold at 260°C for 1 minute.

The other parameters used in the GC method are shown below in Figure X.

Figure 8-1 - Gas Chromatography parameters


- 71 -

• The Mass spectrometer was run in Selective Ion Monitoring mode to give

clean peaks during analysis. The monitoring was carried out for 12 minutes

(Target time for Metaldehyde is around 7 minutes) and the monitoring was

subject to a three minute delay to avoid detecting the solvent peak from the

Dichloromethane and allow clearer analysis of the Metaldehyde peak.

• Once the chromatogram has been drawn, confirm the presence of

Metaldehyde. Target ions no 45 and qualifier 89 confirm the presence of

Metaldehyde in the sample.

A sample of the chromatogram containing Metaldehyde is shown below in

Figure X.

Figure 8-2 - Chromatogram for Metaldehyde sample with internal standard


- 72 -

2. The area under the peak of the chromatogram for each sample is then

compared to a chromatogram of a standard solution containing 100µg/mL of

Metaldehyde. An example of the integrated areas, with the corresponding

parameters, is shown in Figure X. The ratio of the two areas can then be used

to calculate the amount of Metaldehyde in the sample, therefore the

concentration in the filtrate.

Figure 8-3 - Integral of chromatogram to determine quantity of Metaldehyde

optimisation of household scale biosand filters

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