Transcript Slow Sand Filtration

Slow Sand Filtration
 The
Slow Sand Filter Mystery
 Major Events in Slow Sand Filtration
History
 Research at Cornell
 Particle
Removal Mechanisms
 Search for the Mystery Compound
 SSF
research by CEE 453
Slow Sand Filtration
 An
old technology that is poorly understood
 Particle removal improves with time!
 Until recently no one knew how particles
were removed by slow sand filters
 The mystery is not yet solved
 Potential for new useful knowledge
Slow Sand Filter Schematic
A
Filter Cake
B
Sand
Gravel
Underdrains
F
D
C
E
A. Valve for raw water inlet and
regulation of filtration rate
B. Valve for draining unfiltered
water
C. Valve for back-filling the
filter bed with clean water
D. Valve for draining filter bed
and outlet chamber
E. Valve for delivering treated
water to waste
F. Valve for delivering treated
water to the clear-water
reservoir
Slow Sand Filtration:
A Brief History
1790 - SSF used in Lancashire, England to provide clean
water for textile industry
 1829 - SSF used to filter municipal water (London)
 1850: John Snow established the link between drinking
water (from a contaminated well) and Cholera
 1885- SSF shown to remove bacteria
 1892 - Cholera outbreak in Hamburg, Altoona saved by
slow sand filters
 1980s - Giardia shown to be removed by SSF
 1990s - Cryptosporidium not always removed by SSF

Bioengineering in the 1800's
In 1885 Percy F. Frankland used the recently
devised 'gelatin process' of Robert Koch to
enumerate bacteria in raw and filtered water
 Frankland showed that filtration reduced the
average bacteria concentration from Thames water
97.9%

“It is most remarkable, perhaps, that these hygienically
satisfactory results have been obtained without any
knowledge on the part of those who construct these
filters, as to the conditions necessary for the attainment
of such results.” (Percy F. Frankland)
1892 Cholera outbreak in
Hamburg, Germany
Altoona's
water intake
and filter beds
Altoona
Hamburg
Hamburg's sewer
outfalls
Elbe River
Hamburg's
water intake
Large outbreak of Cholera in Hamburg
 17,000 cases; 8,600 deaths
 Very few cases in neighborhoods served by
Altoona's filtered water supply
 Hamburg's sewers were upstream from Altoona's
intake!

The Challenge of the 1990's:
Cryptosporidiosis
Milwaukee (March 1 to April 10 1993): an
estimated 370,000 city residents suffered from
diarrhea, nausea, and stomach cramps caused by
Cryptosporidiosis
 Evidence suggests that a substantial proportion of
non-outbreak-related diarrheal illness may be
associated with consumption of water that meets
all current water quality standards
 Slow sand filters shown to remove less than 50%
of Cryptosporidium oocysts at an operating plant
in British Columbia

In Search of the Secret in the
1990's
How do slow sand filters remove particles
including bacteria, Giardia cysts, and
Cryptosporidium oocysts from water?
 Why don’t SSF always remove Cryptosporidium
oocysts?
 Is it a biological or a physical/chemical
mechanism?
 Would it be possible to improve the performance
of slow sand filters if we understood the
mechanism?

Particle Removal Mechanisms
Straining
(fluid and
gravitational
forces)
Physical-Chemical
Attachment
(electrochemical
forces)
Particle
Removal
Mechanisms
by medium
by
previously
removed
particles
to medium
to previously
removed
particles
Attachment to
biofilms
Biological
Capture by
predators
Suspension
feeders
Grazers
Slow Sand Filtration Research
Apparatus
Manometer/surge tube
Cayuga Lake water
(99% or 99.5% of the flow)
Peristaltic
pumps
Auxiliary feeds
(each 0.5% of the
flow)
Manifold/valve block
Sampling Chamber
Sampling tube
Lower to collect sample
To waste
1 liter
E. coli
feed
1 liter
sodium
azide
Filter cell with
18 cm of medium
Biological and Physical/Chemical
Filter Ripening
Fraction of influent E. coli
remaining in the effluent
Continuously mixed
Cayuga Lake water
Quiescent Cayuga Lake
water
1
1
Sodium azide
(3 mM)
Control
0.1
0.1
0.05
0.05
0
1
2
3
Time (days)
4
5
0
2
4
6
Time (days)
8
10
Biological Poison
1
Fraction of influent E. coli
remaining in the effluent
Control
Sodium azide pulse
Sodium chloride pulse
0.1
0.08
0
1
2
3
Time—h
4
5
6
Effluent particle count
(Dnumber/µl/Dparticle diameter)
Effluent Mystery Particles
9
8
7
6
1.962
3.007
3.986
5
4.965
4
5.958
3
2
1
0
1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2
Particle diameter (µm)
Chrysophyte
long flagellum used for
locomotion and to provide
feeding current
short flagellum
1 µm
stalk used to attach to
substrate (not actually
seen in present study)
Chrysophyte Culture
4000
3500
3000
2500
2000
1500
1000
500
0
1
1.5
2
2.5
Particle diameter (µm)
3
3.5
Chrysophyte Inoculum
1
Control
Chrysophyte
inoculum
0.1
0.01
0.001
0
1
2
Time (days)
3
4
Mechanisms
Particle Removal by Size
1
control
3 mM azide
0.1
0.01
0.001
0.8 1
10
Particle diameter (µm)
Biological Mechanisms
The biological activity of microorganisms being
removed in the filter column was not significant
 The biological activity of the filter biopopulation was
only significant for removal of particles smaller than
2 µm.
 Biofilms were expected to increase removal of
particles larger than 2 µm as well by increasing the
attachment efficiency. The lack of biologically
enhanced removal of particles larger than 2 µm
suggested that “sticky” biofilms did not contribute
significantly to particle removal.

Biological Mechanisms
The immediate and reversible response of slow sand
filters to sodium azide was consistent with
bacterivory and inconsistent with particle removal
by biofilms.
 Biologically mediated mechanisms together with
physical-chemical mechanisms accounted for
removal of particles smaller than about 2 µm in
diameter. In this research bacterivory was the only
significant biologically mediated particle removal
mechanism.

Mechanisms
Filter with Few Particles in
Influent
10
1
0.1
Low particle control
Low particle with azide
0.01
0.8
Day 5
1
10
Particle diameter (µm)
Filters with Many Particles in
Influent
1
High particle control
High particle with azide
0.1
Day 5
0.01
0.001
0.8
1
10
Particle diameter (µm)
Physical-Chemical Particle
Removal Mechanisms
Physical-chemical particle removal mechanisms
are significant in slow sand filters.
 Physical-chemical particle removal efficiency was
greatest when particles previously had been
retained by the filter (within the bed or in the filter
cake) and was considered to be caused by
attachment of particles to retained particles.
 Further work is necessary to determine what types
of particles are most effective for filter ripening.

Mechanisms
fraction remaining
Sludge from Bolton Point
Eureka! CEE 453 1997
1.000
Completely Mixed
2 cm layer
Top Layer
Control
0.100
0.010
0.001
0
20
40
Time (min)
60
?
Sludge from Bolton Point = Alum
(oops) CEE 453 1998
1
0.9
C/Co
slurry
Alum
distilled control
tap water control
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
10
20
30
40
Time (minutes)
50
60
70
Research project 2000
 Successfully
extracted a coagulant from
Cayuga Lake Seston using 1.0 N HCl
 The CLSE fed filters removed up to
99.9999% of the influent coliforms.
 Analysis of the CLSE
 Nonvolatile
solids was 44% of the TSS
 Volatile solids was 56% of the TSS
 Aluminum was dominant metal
CLSE Experiment 2001
 Groups
of 4
 Assemble filter apparatus
 Measure
 Coat
head loss, flow rate, turbidity
filter with CLSE
increased head loss
 Observe _______________
 Challenge
filter with kaolin
head loss
turbidity
 Observe ________and
_______
 Control?
Apparatus
Raw Water