TREATMENT WETLANDS - CHAPTER 12 pot

TABLE 12.2 Indicator Microorganisms and Their Abundance in Feces and Raw Domestic Wastewater Water Concentration CFU/100 mL Fecal Coliform Density #/gram × 10 6 Fecal Coliforms... Howev

Pathogens are present in untreated domestic wastewaters as

well as in runoff waters from animal sources These

organ-isms range from submicroscopic viruses to parasitic worms

visible to the unaided eye and represent important

compo-nents of water quality Table 12.1 lists some of the most

prev-alent human pathogens associated with domestic wastewater

These pathogens are divided into five groups: viruses,

bac-teria, fungi, protozoans, and helminths The density of these

organisms in raw wastewater varies geographically

Viruses are submicroscopic, nonliving particles of

genetic material that are enclosed in a sheath Viruses

can-not divide and reproduce alone, but they can infect host

organisms and reproduce to very large populations at the

expense of the host organism Over 100 virus types are

known to occur in human feces, with minimum infective

doses as low as one organism for some species Bacteria

are universally present in human feces, with normal

pop-ulations of about 1011 organisms per gram (Leclerc et al.,

1977) Although most of these organisms live symbiotically

with their hosts, a number of species are known human

pathogens and occur with great frequency in infected

indi-viduals Human parasites derived from wastewater-related

infections include protozoa and helminths Two common

protozoan parasites are Entamoeba histolytica and Giardia

lamblia, which both cause diarrhea in infected humans The

phylum Aschelminthes (cavity worms) includes all parasitic

worms incapable of adult life without a host organism A

number of helminths, including tapeworms and flukes, are

found in infected humans and can be spread through

waste-water pathways For a summary discussion of

environmen-tally transmitted pathogens, see Maier et al (2000).

The efficiencies of conventional treatment technologies

that reduce pathogens to noninfective levels have been

stud-ied thoroughly, and wastewater treatment plants regularly

add processes to accomplish necessary removals (Metcalf

and Eddy Inc., 1991; Crites and Tchobanoglous, 1998) The

most common add-on disinfection processes are

chlorina-tion, ozonachlorina-tion, and ultraviolet irradiation

Because of its low cost and proven effectiveness,

chlori-nation has been the disinfection method of choice for many

years However, negative side effects of effluent

chlorina-tion have become apparent in the past two decades

Resid-ual free chlorine harms a variety of aquatic organisms and

causes chronic and acute toxicity to microorganisms and fish

Also, when it comes in contact with organic compounds in

wastewater or receiving waters, free chlorine forms

trihalo-methanes and other organochlorine compounds known to be

carcinogenic These findings have resulted in the increased

use of dechlorination techniques and in the development of the ozonation and ultraviolet disinfection technologies.Animals are also a source of pathogenic organisms Farm animals produce feces with high numbers of bacteria Cows, sheep, pigs, and poultry produce 105–107 fecal coli-forms per gram, and 106–108 fecal streptococci per gram Cats, dogs, mice, and chipmunks produce similar concentra-

tions (Maier et al., 2000) Waterfowl and other wetland birds

also contribute coliforms to the wetland environment and may do so in great quantities during migratory concentra-tions Beavers, muskrats, and other warm-blooded wetland animals are also producers of enteric pathogens Beavers

have been implicated in transmission of Giardia About

half the animals in Colorado were found to be infected and shedding 108 cysts per animal per day Ninety-five percent

of muskrats in this study were found to be infected with

Giardia (Erlandsen, 1995).

Natural treatment technologies have the potential to reduce populations of enteric pathogens because of natural die-off rates and hostile environmental conditions Wetlands have been found to reduce pathogen populations with varying but significant degrees of effectiveness This chapter reviews the pathogens typically found in wastewater and describes the effect that treatment wetlands have on the pathogen popu-lations passing through them

12.1 INDICATOR ORGANISMS AND MEASUREMENT

Measurement of human pathogenic organisms in natural and wastewaters is expensive and technically challenging Con-sequently, it has been customary to first look for indicator organisms that are easy to monitor and correlate with popu-lations of pathogenic organisms No perfect indicators have been found, but the coliform bacteria group has long been used as the first choice among indicator organisms Typical indicator organisms are listed in Table 12.2

In the United States, total coliforms were the first approved indicator organisms These coliforms include bac-terial species that are rod-shaped, stain gram-negative, do not form spores, are facultatively anaerobic, and ferment lactose with gas production in 48 hours at a temperature of 35°C Because many members of the group are not limited

to fecal sources, methods have been developed to tiate organisms of fecal origin Fecal coliforms are sepa-rated from total coliforms by their ability to ferment lactose with gas production in 24 hours at a temperature of 44.5°C

differen-An even narrower group, Escherichia coli, is being used

more frequently as an indicator organism, because it can

readily be separated from the rest of the fecal group, and

because several strains are capable of causing severe human health problems However, as these bacteria also originate

in other warm-blooded animals, E coli is not diagnostic

of human fecal contamination alone The coliform groups

in general have an indicator disadvantage in that they may regrow in aquatic environments

The fecal streptococcus group is used to confirm the gins of fecal contamination A high ratio of fecal coliform to fecal streptococcus (FC/FS  4) is regarded as an indication

ori-of human origin, whereas a low ratio (FC/FS  0.7) is

indica-tive of animal pollution (Clausen et al., 1977) However, the

validity of this separation has been subject to question (Gerba, 2000) Fecal streptococcus is found in the feces of humans and other warm-blooded animals including birds and mammals These bacteria are found frequently in waters receiving fecal contamination and are not believed to multiply in natural or polluted waters and soils Because fecal streptococci bacte-ria seem to survive longer than fecal coliforms in receiving waters, they are used as a second indicator of fecal contamina-tion Because bacterial die-off affects the ratio, it is only appli-cable to fecal pollution within 24 hours of discharge

It is generally recognized that fecal coliforms are not suitable indicators of viral contamination in surface water receiving domestic waste because some viruses are more resistant to chlorination and environmental deactivation than

bacteria (Kraus, 1977; Gersberg et al., 1987; Gerba, 2000)

Bacteriophages (viruses that infect bacteria, such as coliphage MS-2) have been used as viral indicators in wetland treat-

ment systems (Gersberg et al., 1987; Schuerman et al., 1989)

TABLE 12.1

Some Human Pathogens Typical of Domestic Wastewater

Viruses Adenovirus (31 types) Respiratory disease

Enteroviruses (67 types) Diarrhea, respiratory disease,

polio Hepatitis A Infectious hepatitis

Norwalk agent Gastroenteritis

Rotavirus Diarrhea

Reovirus Gastroenteritis

Bacteria Campylobacter jejuni Diarrhea

Escherichia coli Diarrhea

Legionella pneumophila Fever, respiratory tract infections

Leptospira (150 spp.) Leptospirosis

Salmonella typhi Typhoid fever

Salmonella (~1,700 spp.) Salmonellosis

Shigella (4 spp.) Diarrhea, dysentery

Vibrio spp. Cholera, diarrhea

Yersinia spp. Yersiniosis

Fungi Aspergillus fumigatus Aspergillosis

Candida albicans Fungal infections

Protozoa Balantidium coli Diarrhea, dysentery

Cryptosporidium parvum Diarrhea

Entamoeba histolytica Diarrhea, dysentery

Giardia lamblia Diarrhea

Helminths Ascaris lumbricoides Roundworm

Clonorchis sinensis Bile duct infection

Diphyllobothrium latum Fish tapeworm

Enterobius vericularis Pinworm

Fasciola hepatica Liver fluke

Fasciolopsis buski Intestinal fluke

Hymenolepis nana Dwarf tapeworm

Necator americanus Hookworm

Opisthorchis spp. Bile duct infection

Schistosoma spp. Schistosomiasis

Taenia spp. Tapeworm

Trichuris trichura Whipworm

Source: Data from Krishnan and Smith (1987) In Aquatic Plants for Water

Treatment and Resource Recovery Reddy and Smith (Eds.), Magnolia

Pub-lishing, Orlando, Florida, pp 855–878; Shiaris (1985) In Ecological

Con-siderations in Wetlands Treatment of Municipal Wastewaters Godfrey et al.

(Eds.), Van Nostrand Reinhold, New York, pp 243–261; Leclerc et al.

(1977) In Bacterial Indicators/Health Hazards Associated with Water.

Hoadley and Dutka (Eds.), American Society for Testing and Materials

(ASTM), Philadelphia, pp 23–36; Cabelli (1977) In Bacterial Indicators/

Health Hazards Associated with Water Hoadley and Dutka (Eds.) American

Society for Testing and Materials (ASTM): Philadelphia, pp 222–238;

Metcalf and Eddy Inc (1991) Wastewater Engineering, Treatment,

Dis-posal, and Reuse Tchobanoglous and Burton (Eds.), Third Edition,

McGraw-Hill, New York; Crites and Tchobanoglous (1998) Small and

Decentralized Wastewater Management Systems McGraw-Hill, New York.

TABLE 12.2 Indicator Microorganisms and Their Abundance in Feces and Raw Domestic Wastewater

Water Concentration (CFU/100 mL)

Fecal Coliform Density (#/gram × 10 6 ) Fecal Coliforms

Pathogens 485

Enumeration of bacteriophages is technically simpler and

more rapid than enumeration of the target pathogenic viruses

Also, MS-2 is nearly the same size as enteroviruses and is

more resistant to ultraviolet (UV) light, heat, and

disinfec-tion than most enteric viruses In a free water surface (FWS)

study at San Jacinto, California, Chendorain et al (1998)

added cultured MS-2 virus to the wetland influent

wastewa-ter to dewastewa-termine die-off rates

12.2 PATHOGEN REMOVAL PROCESSES

The observed net removal of pathogenic organisms in

treat-ment wetlands is the result of a variety of processes, some

that remove pathogens and some that introduce

patho-gens Generally speaking, removal mechanisms are much

more prevalent than reintroduction mechanisms, and most

constructed wetlands demonstrate large net removals of

pathogenic organisms down to a nonzero background

con-centration (C*).

S OLAR D ISINFECTION

UV radiation is a potent agent for killing bacteria in FWS

wetlands An exponential relation is commonly used to

describe the inactivation in disperse batch cultures:

inactivation rate coefficient, m /J

However, most organisms are present in association with

waste-water particulates, rather than in a dispersed phase (Emerick

et al., 2000) Consequently, UV inactivation rates are lowered

from shielding of the organisms by the particle structures

Equation 12.1 is still applied, but rate constants are much lower

than for dispersed-phase populations Emerick et al (2000)

found little variation in rates for fecal coliforms across 11

treat-ment technologies, with 0.022  ki 0.054 m2/J for activated

sludge, trickling filter, aerated, and facultative pond effluents

The UV wavelengths that are absorbed by

microorgan-isms, and hence are effective in disinfection, comprise the

range 240–280 nm (Crites and Tchobanoglous, 1998) Lamps

used for in-line disinfection of wastewaters are designed to

provide radiation in this range The effectiveness of the

radi-ation depends on water quality factors, such as optical

absor-bance and suspended solids content Typical UV dosages are

100–850 J/m2 to provide suitable disinfection of fecal

coli-forms to the range between 1,000 and 23 CFU/100 mL (Crites

and Tchobanoglous, 1998)

In a natural system, such as a pond or an open-water

wet-land, sunlight provides a source of ultraviolet (UV) radiation

However, the fraction of the incoming solar radiation that is

in the UV range is small, typically less than 1% Therefore, solar inactivation rates based on total solar radiation are much smaller than those determined for UV lamp sources,

and these are designated kS For example, Davies-Colley

et al (1999) present pond water data for E coli for which kSy0.7 m2/MJ, which is about 100,000 times lower than for a UV

lamp Salih (2003) determined a similar value for E coli, kSy 1.5 m2/MJ Davies-Colley et al (1999) also demonstrated

that dissolved oxygen and pH had important influences on rates of inactivation These authors inferred that both direct hit radiation damage and photooxidation were caused by incoming radiation

The overall solar inactivation rate for a shallow water body (pond) is further reduced by the lack of penetration of light (Mayo, 1995) The top few centimeters of a stabilization pond get the required radiation, but deeper sections do not Accordingly, the solar inactivation rate constant is approxi-mately inversely proportional to the pond depth:

K h

S S L

where

h k

water depth, moverall solar inactivati

' intrinsic sol

2 S

k  aar inactivation rate coefficient, m /Jl

2 L

K  iight attenuation coefficient, m 1Mayo (1995) reported values of 0.012  hkS 0.016 m3/MJ for five stabilization pond studies Additionally, high-rate ponds (0.2–0.3 m depth and a few days’ detention) have been shown

to have kS 0.0675 m2/MJ (Davies-Colley et al., 2003) and

phages Davies-Colley et al (1999) provide pond data for an F-DNA phage (kSy 0.7 m2/MJ) and for an F-RNA phage (kSy0.6 m2/MJ) The inactivation of phages by sunlight has been found to be a good rate analog for the inactivation of human pathogenic polio, echo, and coxsackie viruses (Fujioka and Yoneyama, 2002)

Solar disinfection depends on the sunlight reaching and penetrating into the water column Dense vegetation inter-cepts sunlight in the wetland environment and diminishes the potential for solar disinfection This negative effect is putatively present for emergent and floating plant commu-nities It may or may not be present in submersed algal or macrophyte communities where subsurface oxygenation may occur The presence of enhanced amounts of dissolved

oxygen (DO) fosters the photooxidation route of disinfection

and may compensate for reduced penetration of UV radiation

(Davies-Colley et al., 1999; Sun et al., 2003).

However, when pond performance is compared to

veg-etated wetland performance for fecal coliform reduction

across large numbers of both types of systems receiving

varying numbers of pathogens, little difference can be seen

in the general level of reduction (Kadlec, 2005e) Other

mechanisms of organism mortality and removal, beyond

just solar disinfection, become operative in the wetland

environment

PREDATION

Most pathogens are food for nematodes, rotifers, and

pro-tozoa (Decamp and Warren, 1998) Among these, rotifers

and flagellated and ciliated protozoa have been implicated as

important contributors to the reduction of bacteria in

treat-ment wetlands (Panswad and Chavalprit, 1997;

Laybourn-Parry et al., 1999; Proakis, 2003; Stott and Tanner, 2005)

as well as in natural aquatic systems (Menon et al., 2003)

While pathogenic organisms span a wide size range (0.2–100

μm), so do the associated predator/grazing communities

(Figure 12.1) They are found in secondary wastewaters

in considerable numbers; for instance, Fox et al (1981)

reported up to about 50 rotifers per liter in such effluents

(Figure 12.2)

Proakis (2003) determined that rotifers consumed

enterococci at the rate of about 600/h when the bacterial

density was approximately 106 per 100 mL From this rate,

it was determined that rotifers, at a density of ten per mL,

could suitably disinfect stormwater in a 1.2-hour detention in

a marsh The next question, then, is about concentrations of

predators that can be expected in the wetland waters

Decamp and Warren (1998) found that the ciliate

Para-mecium consumed more than 100 E coli per hour when the

bacterial density was approximately 108 per 100 mL This

was interpreted to require 20 Paramecium per mL to remove

about 2 × 106E coli per 100 mL in eight hours’ detention

This concentration of Paramecium was comfortably within

the observed concentration range in the SSF wetland from which the protozoa were taken

Heterotrophic nanoflagellates (HNAN) were found to dominate the protozoan community in both lagoons and

grass filters treating sewage (Laybourn-Parry et al., 1999)

Ciliates contributed to only about 10% of the grazer lations The grass filters harbored more numbers (approxi-mately 108 per 100 mL) of these bacterial predators than the lagoons (approximately 107 per 100 mL)

popu-The overall effect of grazing on bacterial numbers in

aquatic systems was quantified by Menon et al (2003) Grazing

by protozooplankton was responsible for more than 90% of the overall mortality rate of both fecal and autochthonous bacteria

in the river Seine For example, whereas in the presence of tozoa the overall first-order volumetric mortality coefficient was

pro-34 × 10−3 h−1, it was 2 × 10−3 h−1 in the absence of protozoa.Grazing is generally higher at higher temperatures

(Laybourn-Parry et al., 1999; Menon et al., 2003), but

temperature coefficients for wetland environments are not available The aforesaid studies indicate a strong poten-tial for pathogen removal through predation in constructed wetlands They do not, unfortunately, allow quantification of this removal mechanism Whereas predation/grazing is an important removal mechanism (especially in FWS wetlands),

it is not the only removal mechanism Settling and filtration also play important roles in pathogen reduction, and these removal mechanisms have a cumulative effect in treatment wetland systems

SETTLING AND FILTRATION

A measurable proportion of wastewater microorganisms are found either associated with particulates or as aggregates of

FIGURE 12.1 Pathogen and predator size chart.

Pathogen size class

Consumer’s preferred food size class

Removal processes*

Larger Organisms

Predation Filtration*

Protozoa

Helminth Ova Protozoa

Pathogens 487

many organisms For the activated sludge process, the

frac-tion of particles with associated coliform ranges from 1%

to 24% (Loge et al., 2002) This fraction declines with the

residence time (mean cell residence time) of organics in the

activated sludge process The loss of coliform organisms

inside the activated sludge process has been speculatively

attributed to predation by protozoans (Loge et al., 2002)

Organisms associated with particles are far less susceptible

to UV or solar disinfection, presumably because of shielding

effects (Emerick et al., 2000).

Bacteria may clump together to form aggregates These

are highly amorphous and porous, but the internal voids are

apparently filled with exopolymeric material (Li and Yuan,

2002) Sedimentation of these particles contributes to their

removal from the water column, with removals of 25–75%

due to gravitational sedimentation in conventional treatment

plants (Metcalf and Eddy Inc., 1991) Tests of algal settling

ponds produced 40% removal of E coli by sedimentation

(Davies-Colley et al., 2003).

In the wetland environment, submersed plant parts and

their associated biofilms form “sticky traps” for particles,

including all sizes of microorganisms (see Chapter 7) These

biofilms are capable of trapping considerable numbers of

organisms (Flood and Ashbolt, 2000; Stott and Tanner, 2005)

Such biofilms are enhanced in quantity by larger quantities of

submersed surfaces and exposure to light There may be an

optimal plant density that allows light and provides the sary surfaces for biofilm growth

neces-M ORTALITY AND R EGROWTH

Bacteria, protozoa, helminths, and viruses typically do not survive longer than about 30 days in freshwater environ-ments and about 50 days in soil environments (Crites and Tchobanoglous, 1998) Similar survivals might therefore

be predicted for wetlands, but there are many site-specific factors and processes which may materially increase or decrease survival

A part of the overall removal of pathogens consists of the death or inactivation of organisms for reasons other than

radiation damage or predation This has been called the dark

death rate (Khatiwada and Polprasert, 1999b) Mortailty has

been found to be approximately 25% of the overall removal

rate in ponds (Craggs et al., 2004), with a similar fraction in a

Typha FWS wetland in Thailand (Khatiwada and Polprasert,

1999b) However, care must be taken to separate tion and filtration from mortality in this dark death rate For instance, Khatiwada and Polprasert (1999b) estimated that only 6.5% of the overall fecal coliform removal rate was due

sedimenta-to temperature-modulated death of organisms

There is no definitive study of the temperature effect on mortality of bacteria in wetlands Estimates of temperature

FIGURE 12.2 (a) Rotifer Keratella spp 200 µm (b) Rotifer Lepadella spp 100 µm (c) Protozoan Discophrya spp 80 µm (d) Protozoan

Vorticella spp 65 µm (From Fox et al (1981) Sewage Organisms: A Color Atlas Lewis Publishers, Boca Raton, Florida Reprinted with

permission.)

coefficients (Q) for ponds range from 1.000 (no effect) to

1.070 (strong effect)

Very low temperatures may result in freezing conditions

Ice formation followed by a thaw drastically reduces the

pop-ulations of pathogens in water For instance, Torrella et al.

(2003) found that only 1.2% of fecal coliforms survived four

days of freezing, but more coliphages survived However, care

must be taken in enumeration, because organisms may be

viable after freezing, but unculturable in routine tests (Parker

and Martel, 2002) Further, many bacteria survive the snow-

making process Less than one log loss was measured for fecal

streptococcus due to snow formation and melting (Parker

et al., 2000).

To complicate matters even more, some indicator

organ-isms are capable of regrowing and multiplying in an aquatic

environment All members of the coliform group have been

observed to regrow in natural surface water (Gerba, 2000)

Such regrowth is fostered by high concentrations of organic

matter and by elevated temperatures This phenomenon is

recognizable when disinfected wastewater is introduced into

treatment wetlands, and bacterial populations increase along

the direction of flow (Figure 12.3)

REINTRODUCTION

Indicator organisms can be produced by sources other than

incoming wastewaters This is particularly true for the

coli-form group, which may originate from many different

warm-blooded animals that frequent wetlands As an example,

consider the performance of the Orlando Easterly FWS

Wet-lands (Figure 12.4) Incoming fecal coliforms are very low,

but animal (bird) populations are high, especially near the

outlet Background geometrical annual averages range from

50 to 142 per 100 mL Monthly values show an exceedance

frequency of 40% of the permit limit of 100 CFU/100 mL

The five-year median fecal coliform was 64 CFU per 100 mL

and FS was 106 CFU per 100 mL The ratio FC/FS was 0.6;

thus, the presumption may be made that the source of

con-tamination is animal rather than human (criterion  FC/FS 

0.7) In this case, the treatment wetland has been measured

to have very large bird populations, which also supports the concept of reintroduction of pathogens from avian popula-tions (U.S EPA, 1993a; U.S EPA, 1993d)

These naturally-caused bacterial populations are erally low, but they may be variable and seasonally high because of wildlife activity patterns Total and coliform bacteria have been measured in natural wetlands that receive

gen-no wastewater For example, Fox et al (1984) measured

between 109 and 456 CFU/100 mL of fecal coliforms in cypress wetlands in Florida that were not receiving any exter-nal water inputs Fecal coliform concentration in lake water passing through a wetland in Montreal, Quebec, increased from 40 to 110 CFU/100 mL (Vincent, 1992) Because nat-ural sources of coliforms and fecal streptococcus bacteria are found in all wetlands open to wildlife, outflow indicator bacteria populations in treatment wetlands cannot be consis-tently reduced to near zero unless disinfection is used.Subsurface flow (SSF) wetlands provide much less wildlife habitat than FWS systems; however, their use by wildlife cannot

FIGURE 12.3 Longitudinal profiles of total residual chlorine (TRC) and E coli through Tres Rios Hayfield, Arizona, wetland H1.

0.00 0.50 1.00 1.50 2.00 2.50 3.00

Inlet Splitter Inlet DZ DZ1 DZ2 DZ3 DZ4 DZ5 H1 EFF

0 200 400 600 800 1,000 1,200 1,400

TRC E coli

FIGURE 12.4 Fecal coliforms entering and leaving the Orlando

Easterly Wetland, in Florida during 1993–1997 The incoming wastewater is disinfected, with only a few detections of the indica- tor organisms The balance of the nondetect samples are plotted as half the detection limit of 1.0 per 100 mL (Unpublished data from city of Orlando.)

0.1 1 10 100 1,000

Months

Inlet Outlet

Pathogens 489

be excluded For instance, a HSSF wetland in Arizona, fed with

disinfected potable water, produced on an average, effluent

con-centrations of 130 total coliforms (CFU/100 mL) and 22.3 fecal

coliforms (CFU/100 mL) This reintroduction of indicator

organ-isms was attributed to wildlife use of the system Because

wild-life use of SSF wetlands has been observed on many occasions

(Wallace et al., 2001), it is to be expected that these treatment

wetlands will also deliver a nonzero background

concentra-tion (C*) for indicator organisms However, wildlife use is so

restricted that backgrounds are likely of little consequence

12.3 FECAL COLIFORM REMOVAL

IN FWS WETLANDS

The most common indicator organism group is the fecal

coli-form group and consequently the wetland database is

larg-est for this group Further, several attempts have been made

to extract quantitative generalities about the removal of this

indicator group in FWS treatment wetlands

FIRST-ORDER REMOVAL MODELS

The complexity of the suite of processes responsible for

reducing indicator bacteria in FWS wetlands is considerable,

with the many interacting processes described previously

Although some attempts have been made to combine these into

a single removal model (Mayo, 1995; Bahlaoui et al., 1998;

Khatiwada and Polprasert, 1999b), data have been

insuffi-cient to provide robust calibrations of combination models

Information on light exposure and penetration, vegetative

cover, and predator density is typically lacking Therefore, at

this point in the evolution of treatment wetland technology,

only very simple global removal models may be considered

Model Structure

First-order models have been used to describe reductions of

indicator bacterial populations in lagoons and wetlands:

First-order (volumetric) C C

k N

N

o i

N

o i

¤

¦

³µ

o i

A

¤

¦

³µ

A V

areal rate coefficient, m/dvolumetric

number of TISnom

1

T

N 

 iinal detention time, d

The first question that arises is whether to use Equation 12.3 or Equation 12.4, the former being volume-specific and the later being area-specific In the situation of unvegetated systems, von Sperling and Mascarenhas (2005) provide an unequivo-cal answer: no difference was found in doubling the depth (80 cm versus 40 cm) and thus doubling the detention time

for E coli removal The implications are that kV is inversely proportional to depth and, hence, the areal rate coefficient

in Equation 12.4 is constant The same inverse proportion

is found for the Arcata, California, pilot data, in which six pairs of emergent FWS wetland cells were run at two depths

and different hydraulic loadings (data from Gearheart et al.,

1983) Thus, for both ponds and wetlands, there is strong

evi-dence that the areal rate coefficient (kA) is constant, whereas

the volumetric rate coefficient (kV) decreases with increasing depth In this book, the areal rate coefficient will be used and presumed constant over some modest depth range, such as 20–80 cm However, FWS volumetric rate coefficients, when they are reported elsewhere, may be easily converted to an areal basis simply by dividing by the free water depth

A far more serious question unique to pathogen removal

is the internal pattern of the flow (number of tanks in series,

N) to be assigned to the system for which k is to be

deter-mined or used For other measures of wetland water quality improvement, such as biochemical oxygen demand (BOD), total suspended solids (TSS), and nutrient removal, reduc-tions are rarely greater than 90–95% (less than one log10removal) For pathogens, reductions often reach 99.99% (two to three log10 removal) or more This is precisely the region of performance in which reductions are extremely

sensitive to the number of tanks-in-series (NTIS) value

(see Chapter 6) Equation 12.4 has been graphed for the

case of a negligibly small C* (C*  Co) in Figure 12.5

FIGURE 12.5 Reductions according to a first-order model in the

high removal range.

The Damköhler number (Da  kAT/h) embodies the

intrin-sic rate of removal together with the detention time and

depth Independent of these factors, the wetland may have

differing degrees of hydraulic efficiency (see Chapter 2),

as indicated by different values of N.Figure 12.5 indicates

that the number of log10 reductions increases steeply with

number of tanks in series (N) at any given detention time

(Damköhler number)

The underlying phenomenon is hydraulic

short-circuit-ing Small elements of flow can carry enough organisms to

the outlet, without treatment, to jeopardize the high levels

of removal that prevail for the remainder (majority) of the

flow Conversely, if a wetland exhibits performance of, say,

two log10 reduction, the rate coefficient is extremely

sensi-tive to whether the NTIS value is 4, 8, or ∞ (plug flow);

the computed areal rate coefficient (kA) changes by

approx-imately 100% if N  4 as opposed to N  ∞ (plug flow)

(Figure 12.5)

Data from waste stabilization ponds provides

confirma-tion of this phenomenon Lloyd et al (2003) studied fecal

coliform removal in a sequence of pond modifications, each

designed to improve the hydraulic efficiency The levels of

contamination were in the range of 104–106 fecal coliforms

per 100 mL, outlet to inlet; thus, in this instance, C* is

negli-gible The results may be summarized as follows:

nelized, aspect 36:1, wind break 98.13% ( 1.7 8 8 log

Batch reduction (plug-flow equival

eent) 99.7% (2.6 log10)Although tracer tests were not performed to determine the

number of tanks in series, it is clear that the increasing aspect

ratio and decreasing wind mixing had very large effects on

the performance of the pond These results correspond nicely

to the theoretical projections of Figure 12.5 for a Damköhler

number of about 6.0 From these considerations, it may be

concluded that the reduction of pathogens in FWS wetlands

is critically dependent on the internal flow patterns

Longitudinal Profiles

Irrespective of the degree of hydraulic efficiency in a

particu-lar wetland, global first-order models forecast a decline in

pathogens through the wetland, provided the incoming

lev-els exceed the regrowth and reintroduction potentials This

theory corresponds to observations for a number of wetlands,

such as the Byron Bay, Australia, FWS system (Figure 12.6)

There is a drop of about two log10 over the first third of that

system, followed by a plateau at levels of 300–2,000 fecal

coliforms per 100 mL, depending upon the year in question

Avian use of the outlet portions of the system may account

for the plateaus For most FWS wetland systems, complete

elimination of fecal coliforms has not been achieved, and

therefore the inclusion of a C* value in the first-order model

is a necessity

Because of residual indicator bacteria populations in all wetlands, bacteria removal efficiency is a function of the inflow bacteria population Removal efficiency is typically high at high-inflow populations but declines to negative effi-

ciencies when inflow populations are lower than the in situ

bacteria production and addition rates For instance, at the Titusville, Florida, wetland treatment system, inflow to the wetland contains essentially no indicator bacteria because

of a high level of pretreatment and disinfection (less than

1 CFU/100 mL); however, the wetland outflow contains small numbers of fecal coliforms (63 CFU/100 mL) and fecal strep-tococci (170 CFU/100 mL), presumably because of wetland bird use (unpublished data from Titusville, Florida)

Implications for Design

There are two important points to be kept in mind when extracting information from the literature for use in design: (1) literature die-off rates are often computed using the plug-flow equivalent of Equations 12.3 and 12.4, and (2) the use

of that plug-flow formulation in design in an extrapolation mode is extremely dangerous, because it creates large over-estimates of reductions

Data from 28 FWS systems, totaling 47 wetland years, was

used to estimate fecal coliform areal rate coefficients (kA) for a

presumed C*  40 CFU/100 mL These systems were selected

for having inlet fecal coliform concentrations of at least 1,000 CFU/100 mL, thus eliminating systems with low influent fecal coliform concentrations, whether due to pretreatment disinfec-

tion or other factors The hydraulic parameter N, representing

the number of tanks in series, was relaxed to the more general

case of P, which accounts not only for the nonideal lics but also treatment effects as well (P  N), as discussed in

hydrau-Chapter 6 Because the critically important PTIS values were

not known, three different assumptions were made:

PTIS (plug flow; known to be wrong, but

i

 cn

n common use)TIS 3 (a modest degree of de

flow and complete miixing)TIS 1 (complete mixing)

S 1  kAo s.e 16,300 9,500 m/yr  o ( median  1,030 m m/yr)

It is seen that the presumed degree of nonideal flow has a very large effect on the calibrated areal rate coefficients, as has been theoretically explained previously This wide dis-parity exists for each individual wetland as well as for the means and medians of the N 28 dataset

Pathogens 491

The danger of extrapolation is seen in an example for which

we assume C*  0 for simplicity Suppose that the given

wet-land is producing 1.0 log10 reduction at a hydraulic loading rate

of 10 cm/d and the wetland hydraulics can be characterized by

PTIS  3 The plug flow kA 84 m/yr (areal die-off coefficient)

(Equation 12.5), and the 3TIS kA 126 m/yr (Equation 12.4)

It is desired to improve performance by lowering the hydraulic

loading rate to 2 cm/d According to the plug flow model

(Equa-tion 12.5), performance should increase to 5.0 log10 reduction

But, according to the 3TIS model (Equation 12.4), performance

would increase to only 2.49 log10 reduction Thus, even though

the plug flow rate coefficient is typically considered to be

“con-servative,” it is in error by more than a factor of 300

It is concluded that first-order modeling is not useful in

design unless the hydraulic characterization of the wetland is

taken into account

Nonetheless, it is appropriate to explore the rates of

reduc-tion of pathogens in FWS systems, and here the indicator

fecal coliforms is used to identify the intersystem

variabil-ity Table 12.3 shows the frequencies of reductions and areal

k-values for a set of FWS wetlands that are in the mode of

removal, i.e., they receive a load of organisms at or above the

expected background, here taken to be 40 CFU/100 mL For

a presumed PTIS  3, the median reduction is 1.54 log10, and

the median k 83 m/yr

Seasonal and Stochastic Effects

There are no pronounced seasonal or temperature effects for

pathogen removal in the FWS treatment wetland datasets

that are currently available Computation of cosine trends

in outlet concentrations typically produces a low amplitude,

about 12% in log10, with the annual maximum in September

(Table 12.4) Ten years’ data from Estevan, Saskatchewan,

showed an increase in fecal coliforms in the wetland (0.26

log10 increase), but a decrease in total coliforms (2.01 log10

reduction) However, the seasonal trend for both displays

higher summer values (Figure 12.7)

Temperature Coefficients

There are conflicting potential effects of temperature on pathogen reduction Cold temperatures are inimical to

TABLE 12.3 Annual Reduction of Fecal Coliforms in FWS Wetlands

Stipulations

1 Annual averages are used in calculations.

2 For k-value calculations, the following P-k-C* parameters are

log 10 FC In (CFU/100 mL)

log 10 FC Out (CFU/100 mL)

Rate Constant (m/yr)

FIGURE 12.6 Average annual longitudinal profiles of fecal coliforms in the Byron Bay, Australia, treatment wetlands (Unpublished data

from Byron Bay operations.)

100 1,000 10,000 100,000 1,000,000

0.0 0.2 0.4 0.6 0.8 1.0

Fractional Distance through Wetland Cell

1990–91 1991–92 1992–93

TABLE 12.4

in the Effluent from FWS Wetlands

log 10 Mean

log 10 Amplitude

Note: The multipliers that represent the frequency of excursions from the trend are also shown For instance, the 99th percentile median log10 of concentration

is 1.36 times higher than the trend If the outlet trend value is 1,000 per 100 mL, then one time out of twenty the outlet may reach 1,000 1.36  12,022 per 100 mL Trend multiplier is (1 + 9); see Equation 6.61.

a Date adjusted 182 days

FIGURE 12.7 Folded time series of log10 fecal and total coliforms at the Estevan, Saskatchewan, FWS wetlands The wetlands operate during the unfrozen season Note a midsummer peak in both Fecal coliforms showed an increase of 0.26 log 10 , whereas total coliforms decreased 2.01 log10 (Unpublished data from city of Estevan.)

0 1 2 3 4 5 6

Pathogens 493

the survival of organisms that originate in warm-blooded

organisms, and thus human pathogens usually do not

sur-vive well outside the body Survival times in waters are

typically 10–30 days (Crites and Tchobanoglous, 1998) On

the other hand, the activity of predatory organisms, such as

protozoa, is lessened at cold temperatures, although direct

lethality is unlikely (Davies-Colley et al., 2005) Removal

by adsorption is expected to be insensitive to temperature

but slightly less effective under cold conditions The very

high temperature coefficients suggested for ponds and FWS

wetlands (Q  1.19) (U.S EPA, 2000a; Shilton and Mara, 2005) are unlikely to prevail in the subsurface environment and do not apply A number of FWS wetlands have a median

of Q  0.963 (Table 12.5)

For example, the reductions in fecal coliforms for Listowel Systems 4 and 5 show slight but opposite trends with tem-perature, with a low degree of variability explained (low R2)(Figure 12.8) System 4 shows Q  0.985, whereas System 5 shows Q  1.021, where Q is the modified Arrhenius tempera-ture coefficient Part of these trends are due to flow changes

TABLE 12.5

Temperature Coefficients for First-Order Plug Flow k-values for FWS Wetlands

HLR (cm/d)

T Range (nC)

log 10 Inlet (CFU/100mL)

log 10 Outlet (CFU/100 mL)

Annual Areal

k (m/yr) Theta Fecal Coliforms

Total Coliforms

E coli

FIGURE 12.8 Dependence of log10 reduction of fecal coliform for Listowel, Ontario, Systems 4 and 5 Three years of monthly data are

rep-resented (Data from Herskowitz (1986) Listowel Artificial Marsh Project Report Ontario Ministry of the Environment, Water Resources

Branch: Toronto, Ontario.)

from summer to winter, and thus the rate constants exhibit

lesser temperature dependence (Q  0.997 and 1.002,

respec-tively, Table 12.5)

Stochastic variability in the bacterial indicator organisms

leaving FWS wetlands is very large Fecal coliform counts are

due to internal loading within the wetland as well as declines

in populations entering with wastewater For example, at the

Imperial, California, wetland, the four-year time series of

monthly incoming fecal coliforms varied over three orders

of magnitude (factor of 1,000) and the wetland effluent fecal

coliforms varied over two orders of magnitude (factor of 100)

(Figure 12.9) Such time series may be expressed as probability

density plots, such as those for Listowel Systems 4 and 5

(Fig-ure 12.10) For these side-by-side wetlands, the variability of

fecal coliform in the lagoon source water was much less than in

the wetland effluents, which display a spread of more than three

orders of magnitude It is also noteworthy that the wetland of

greater aspect ratio (System 4) shows a greater reduction

Excursions around mean performance should be edged in design and regulation Trends in outlet pathogens can form the basis, or predictions from a first order or other model Table 12.4 shows example trend fits for several FWS wetlands, together with the multipliers necessary to contain excursions of a given frequency of occurrence For instance, the 95th percentile median log10 of concentration is 1.31 times higher than the trend If the outlet trend value is 1,000 CFU/100 mL, then 1 out of 20 times, the outlet may reach 1,0001.31 8,511 CFU/100 mL

acknowl-INPUT–OUTPUT RELATION FOR FECAL COLIFORMS

FWS treatment wetlands reduce high numbers of incoming fecal coliforms Wetland data has been acquired for a num-ber of systems, with examples listed in Table 12.6

Input–output annual data for 256 wetland years is played in Figure 12.11 The scatter in these data is quite high

dis-1 10 100 1,000 10,000 100,000 1,000,000

Months

In Out

FIGURE 12.9 Time series of monthly fecal coliforms entering and leaving the Imperial, California, treatment wetlands (From unpublished

data.)

FIGURE 12.10 Probability densities for monthly fecal coliforms entering and leaving Listowel, Ontario, Systems 4 and 5 System 4 had

aspect ratio L:W  84:1, whereas System 5 had aspect L:W  5:1 (Data from Herskowitz (1986) Listowel Artificial Marsh Project Report Ontario Ministry of the Environment, Water Resources Branch: Toronto, Ontario.)

0.0 0.2 0.4 0.6 0.8 1.0

Pathogens 495

and is reflective of two points discussed previously First,

there is a nonzero background for this indicator organism

group, and that background is itself quite variable

Dis-infected influents tend to emerge from an FWS wetland

in the range 10–1,000 CFU/100 mL, with a median of 60

CFU/100 mL for those wetlands that receive a disinfected

inflow Second, when inlet concentrations are above about

1,000 CFU/100 mL, there is a log10 reduction of about two,

but results are widely variable from wetland to wetland The

addition of the hydraulic loading rate to the variables, in the

form of a loading plot, does little or nothing to reduce the

TABLE 12.6

Reduction of Fecal Coliforms in FWS Wetlands

Inlet (CFU/100 mL)

Outlet (CFU/100 mL)

Reduction (log 10 ) Reference

West Jackson County, Mississippi 1–2 Annual 90 95 578 −0.79 NADB v.2 (1998)

University of SW Louisiana 2 Annual 1994–95 3,716 1,599 0.37 NADB v.2 (1998)

University of Connecticut 1 Annual 1994/95 28,811 1,265 1.36 NADB v.2 (1998)

Sand Mountain, Alabama 1 Annual 1990–91 175,164 3,005 1.77 NADB v.2 (1998)

Oregon State University, Oregon 1 Annual 94 1,198,419 138,916 0.94 NADB v.2 (1998) Neshaminy, Pennsylvania All — 1,290,600 5,600 2.36 Unpublished data

Waldo, Florida All — 7,700,000 270,000 1.46 Schuerman et al (1989)

12.4 REMOVAL OF OTHER INDICATOR

BACTERIA IN FWS WETLANDS

T OTAL C OLIFORMS

The coliform group has been used as the standard for

assess-ing fecal contamination of waters throughout the twentieth

century (Gerba, 2000) Although total coliforms have been

widely used in older studies and monitoring, many of the

organisms in this broad group are not limited to fecal sources

Accordingly, the subgroup of fecal coliforms has become the

1.E – 01 1.E + 00 1.E + 01 1.E + 02 1.E + 03 1.E + 04 1.E + 05 1.E + 06

1.E – 02 1.E – 01 1.E + 00 1.E + 01 1.E + 02 1.E + 03 1.E + 04 1.E + 05 1.E + 06 1.E + 07

preferred indicator, which includes the genera Escherichia and Klebsiella A simple lab test allows differentiation.

Here, it is noted that FWS treatment wetlands reduce high numbers of incoming total coliforms Wetland data have been acquired for a number of systems, with examples listed in Table 12.7 As for fecal coliforms, wetlands rein-troduce total coliforms to a disinfected influent, to a lim-ited degree, as evidenced by the Orlando Easterly Wetland (OEW) data For nondisinfected influents, there are reduc-tions of one to two log10

Pathogens 497 FECAL STREPTOCOCCUS

Fecal streptococcus belongs to the genera Enterococcus and

Streptococcus These are considered to have advantages

over fecal coliforms as an indicator because (1) they rarely

multiply in water, (2) are more resistant to environmental

stress, and (3) generally persist longer in the environment

(Gerba, 2000) A high ratio of fecal streptococci to fecal

coliforms is taken as strong evidence that the source is of

human origin

Inflow and outflow densities of fecal streptococcus

bac-teria have been monitored at a number of pilot and full-scale

wetland treatment systems Table 12.8 summarizes these data

for some of the wetland treatment systems receiving

munici-pal wastewater, pretreated to differing extents Data for

dis-infected influents again show reintroduction in treatment

wetlands, with effluent numbers in the range 50–200 CFU

per 100 mL For nondisinfected influents, there are

reduc-tions of one to two log10

E SCHERICHIA COLI

Escherichia coli is found in the intestinal tract of all

warm-blooded animals and is usually considered harmless

(Gerba, 2000) However, several strains are capable of

caus-ing gastroenteritis and include organisms that may cause

hemorrhagic colitis, a dangerous disease, especially for

the elderly For this reason, E coli has found favor in some

instances as a replacement for fecal coliforms as an

indica-tor organism

E coli has the ability to regrow or to be reintroduced

in FWS wetlands Considerable numbers were found in the

wetland effluents at Tres Rios, Arizona, for a disinfected

influent (Table 12.9) Conversely, large reductions may

occur when the wetland influent has large numbers Such

reductions may be quite large for highly

compartmental-ized wetlands of high aspect ratio, for instance, the Brawley,

California, wetlands

MISCELLANEOUS BACTERIA

Clostridium perfringens is exclusively of fecal origin It is

regarded as particularly resistant to pH and temperature

stress and was therefore chosen for monitoring at the

Lis-towel, Ontario, system (Herskowitz, 1986) Salmonella is a

large group, all of which are pathogenic to humans

Salmo-nella causes typhoid and paratyphoid fevers, and is found

in a large variety of both warm-blooded and cold-blooded

animals Yersinia enterocolitica, a bacterium that causes

gastroenteritis, was found in large numbers in the Listowel

lagoons Because it survives well at cold temperatures, it was

monitored in the Listowel project Pseudomonas aeruginosa

is associated with the disease otitis externa, or “swimmers

ear” (Herskowitz, 1986) All these organisms, plus others,

have been found to be reduced in FWS treatment wetlands (Table 12.10)

12.5 PARASITE AND VIRUS REMOVAL

IN FWS WETLANDS PARASITES

Parasites include protozoa and helminths In the United States,

the two protozoa of special interest are Giardia lamblia and

Cryptosporidium parvum The former is the most frequently

identified intestinal parasite in the United States (Maier

et al., 2000) The latter was implicated in an outbreak in

1993 in Milwaukee, Wisconsin, in which over 400,000

people were infected Giardia is of special interest in

con-nection with wetlands because beavers and muskrats are

believed to be reservoirs of infection Worldwide,

Asca-ris lumbricoides is the most prevalent parasitic infection,

with an estimated 22% of the world population affected

(Maier et al., 2000) Adult Ascaris are roundworms which

inhabit the intestine, but they are ingested as eggs Two

other prevalent infectious worms are Trichuris trichiuria and Taenia saginata, and these are of special concern in

warm climates

FWS wetlands reduce the numbers of these parasitic organisms by reducing the number of eggs or cysts that survive in the aquatic environment (Table 12.11) One mechanism is presumably sedimentation of eggs, followed

by eventual inactivation Nelson (2003) reports egg bers in pond sludges ranging from less than ten per dry

num-gram in France, to thousands of Ascaris eggs per dry num-gram

in Brazil Inactivation may take more than a year However,

Stott et al (2001) determined that oocysts of

Cryptospo-ridium parvum were effectively ingested by protozoans,

notably Paramecium caudatum and Stylonychia mytilus.

Therefore, predation may also be a factor in the observed reductions

V IRUSES

The average viral content of domestic sewage in the United States is about 7,000 particles per liter (Gersberg and Gearheart, 1989) Because the potential infective dose

of viruses can be so low (10 particles), and viruses are generally hardier in natural environments than bacterial pathogens, there has been considerable concern about their fate in wetland and conventional treatment systems However, because viruses are more costly and difficult to monitor analytically, they have not received as much study

as bacterial indicator populations Existing research cates that wetlands are generally hostile environments for viruses (Table 12.12)

indi-TABLE 12.8

Reduction of Fecal Streptococcus in FWS Wetlands

Time Period

Inlet (CFU/100 mL)

Outlet (CFU/100 mL)

Reduction (log 10 ) Reference

Byron Bay, Australia Research 1990–1993 25,570 1,915 1.13 Unpublished data

Byron Bay, Australia To WB2–3 1990–1993 25,570 4,839 0.72 Unpublished data

Byron Bay, Australia To WB3–4 1990–1993 25,570 2,378 1.03 Unpublished data

Byron Bay, Australia To WB4–5 1990–1993 25,570 1,358 1.27 Unpublished data

Byron Bay, Australia To WB5–6 1990–1993 25,570 654 1.59 Unpublished data

Byron Bay, Australia To WB6–7 1990–1993 25,570 1,522 1.23 Unpublished data

a There are 15 cells prior to MM7

b There are 17 cells prior to HS10