TREATMENT WETLANDS - CHAPTER 8 ppt

W ETLAND C HEMISTRY OF C ARBON Dissolved Inorganic Carbon Of the hundreds of carbon compounds that may occur in the wetland environment, relatively few are inorganic.. O RGANIC C ARBON B

Carbon compounds interact strongly with wetland

ecosys-tems The carbon cycle in wetlands is vigorous and typically

provides carbon exports from the wetland to receiving

eco-systems Many internal wetland processes are fueled by

car-bon imports and by the carcar-bon formed from decomposition

processes

Treatment wetlands frequently receive large external

supplies of carbon in the added wastewater Any of several

measures of carbon content may be made, with biochemical

oxygen demand (BOD) being the most frequent in the

treat-ment of municipal wastewater Degradable carbon compounds

are rapidly utilized in wetland carbon processes At the same

time, a variety of wetland decomposition processes produce

available carbon The balance between uptake and

produc-tion provides the carbon exports In general, the amounts of

carbon cycled in the wetland are comparable to the quantities

added in domestic wastewater

The growth of wetland plants requires carbon dioxide

(CO2) for photosynthesis A variety of organisms release CO2

as a product of respiration Many pathways lead to the

micro-bial production of CO2, as well as methane (CH4) Both gases

dissolve in water to a limited extent; so there are active

trans-fers of carbon to and from the atmosphere

In terms of treatment, it is therefore not surprising to find

good carbon reductions for the added wastewater,

accompa-nied by nonzero background levels of various carbon

com-pounds and the related BOD For purposes of wetland design

for BOD removal, the challenge is to find relatively simple

design tools despite the enormously complex set of wetland

functions

8.1 WETLAND CARBON SPECIATION

AND PROCESSING

A wide spectrum of carbon compounds exists in either

dis-solved or particulate forms in aquatic systems The usual

dividing line is a 0.45-Mm filter The following distinctions

are made as a result of analytical methods:

TC total carbon (includes all dissolved and

In soils or biomass, samples are subjected to combustion and dissolution, followed by analysis for total carbon

BOD, COD, AND TOC

Different analytical techniques are used to measure the amount

of organic material in the wastewater BOD is a measure of the oxygen consumption of microorganisms in the oxidation

of organic matter It is measured as the oxygen consumption

in an airtight incubation of the sample This test normally runs for five days, and the result is then more properly des-ignated as BOD5 Some oxygen may be used in nitrification

if the necessary organisms are present in the sample If this potential nitrogenous oxygen demand is inhibited chemically during the test, the result is carbonaceous biochemical oxy-gen demand (CBOD5)

Chemical oxygen demand (COD) is the amount of a cal oxidant, usually potassium dichromate, required to oxidize the organic matter This measure is larger than BOD, because the strong oxidant attacks a larger group of compounds How-ever, nitrogenous compounds, such as ammonia, are not oxi-dized by the COD test Oxygen or oxidant consumption may

chemi-be measured chemi-before or after filtration, leading to measures of total and soluble BOD and COD In the wetland environment, the presence of humic materials leads to COD values that are much larger than BOD values In a northern peatland, the ratio was approximately 0.05 (BOD5 5 mg/L:COD  100 mg/L) (unpublished data from the Houghton Lake, Michigan, peatland) At Tres Rios, Arizona, wetlands treating nitrified secondary effluent, four wetlands gave ratios of 0.055 o 0.004, averaged over seven years In municipal wastewaters, the ratio

is typically 0.4–0.8 (Metcalf and Eddy, Inc., 1991) Industrial wastewaters may have lower ratios

Total organic carbon (TOC) is measured by chemical oxidation followed by analysis for CO2 In a northern peat-land, the ratio BOD5:TOC was approximately 0.2 (BOD5 5 mg/L:TOC Lake peatland), and was 0.28 at Estevan, Saskatchewan At Tres Rios wetlands treating nitrified secondary effluent, four wet-lands gave ratios of CBOD5:TOC  0.25 o 0.08, averaged over

seven years In municipal wastewaters, the ratio is 1.0:1.6

(Metcalf and Eddy Inc., 1991)

The interrelation among the various measures of carbon

and oxygen demand are given in Table 8.1 The interpretation

of these ratios is that natural wetlands cycle at low levels of

biologically usable carbon compounds, whereas municipal

wastewaters are rich in usable carbon compounds

Wetlands are efficient users of external carbon sources,

manifested by excellent reductions in BOD5 and COD

How-ever, wetlands possess nonzero background levels of both

BOD and COD, which depend on the type and status of the

wetland Typical ranges for background concentrations are

1–10 mg/L for BOD5 and 10–100 mg/L for COD

W ETLAND C HEMISTRY OF C ARBON

Dissolved Inorganic Carbon

Of the hundreds of carbon compounds that may occur in the

wetland environment, relatively few are inorganic Dissolved

inorganic carbon consists primarily of CO2, carbonate, and

bicarbonate

In pure water solution, the principal carbonate species

are related to atmospheric CO2by the temperature and

pH-dependent dissolution and dissociation series:

2

3

H CO2 3

(8.6)

the notation of Pankow (1991) has been adopted Brackets indicate the concentration of the chemical species, in molar-ity; and all are in water except for atmospheric CO2 The

value of the equilibrium constant Ky 650, and hence most

of the dissolved carbon is present as CO2 Equations 8.1–8.6 may be solved for concentrations, given the partial pressure

of CO2 and the various equilibrium constants

 K

TABLE 8.1 Comparison of Oxygen Consumption Parameters for Various Waters

From Crites and Tchobanoglous

Source: WWTP values from Crites and Tchobanoglous (1998) Small and Decentralized Wastewater Management Systems McGraw-Hill, New York; Metcalf and Eddy Inc (1991) Wastewater Engineering, Treatment, Disposal, and Reuse Tchobanoglous and Burton (Eds.), Third Edition, McGraw-Hill, New York.

CO H CO

2 3

2

§© ¶¸  K K H K P

The equilibrium constants, and hence the various

concentra-tions, are all pH- and temperature-dependent These forms

are distributed in water at 25°C as shown in Figure 8.1

(Pan-kow, 1991) However, it must be noted that wetland waters

are more complex than the pure water system and therefore

will not follow such idealized chemistry precisely

Modifi-cations of the calculation (APHA, 1992) deal with expected

deviations due to dissolved solids, but not the full suite of

biological variations that may be expected in wetlands

Pro-duction and consumption of CO2 in the wetland may

signifi-cantly alter the chemical balance in the water

An important feature of the carbonate system is its

influ-ence on pH under mediation by algae Algal consumption of

CO2 drives pH upward, and may give rise to 9  pH  10 in

unshaded wetland environments or ponds

Precipitates

A variety of cations can precipitate carbonates under certain

conditions The most important is calcium carbonate, CaCO3

A major process in periphyton-dominated wetlands is

chemi-cal precipitation of CaCO3 under conditions of high pH created

by the algae (Gleason, 1972) Similarly, in beds of submerged

aquatic vegetation, CO2 and bicarbonate are consumed during

photosynthesis, thereby raising the water column pH and

pro-moting CaCO3 precipitation (Dierberg et al., 2002).

A variety of cations can precipitate carbonate under

cer-tain conditions Some important mineral precipitates in the

wetland environment are:

Calcite: CaCO

Aragonite: CaCO

Magnesite: MgCO

3 3 3D

Dolomite: CaMg(CO )3 2

Calcium carbonate saturation indices may be calculated in

a number of ways (APHA, 1992) However, overall carbon

mineral chemistry is very complex; consequently, accurate calculations of solubilities are generally not possible, espe-cially in wetland environments

O RGANIC C ARBON

Biomass: Growth, Death, Decomposition

The wetland cycle of growth, death, and partial decomposition uses atmospheric carbon, and produces gases, dissolved organ-ics, and solids (Figure 8.2) Decomposition involves the sugars, starches, and low molecular weight celluloses in the dead plant material Gaseous products include methane and regenerated

CO2 A spectrum of soluble large organic molecules,

collec-tively termed humic substances, are released into the water The

solid residual of plant decomposition is peat or organic ment, which originated as celluloses and lignins in the plants These wetland soil organics are broadly classified as fulvic material, humic material, and humin, based upon whether they are acid soluble, base soluble, or insoluble (NRCC, 1979).The sediments, soils, and biomass in a wetland contain major proportions of carbon The carbon content of 28 species

sedi-of wetland plants has been reported by Boyd (1978) as 41.1%

o 0.7% (dry weight, mean o SE) Typha latifolia values from

30 sites ranged from 43.3% to 47.2% (Boyd and Hess, 1970)

Reddy et al (1991) reported 44.0% o 2.5% for peats in the

upper 30 cm of the soil column Soil scientists sometimes use

a concentration of 58% for the carbon content of soil organic matter (the Van Bemmelen factor; Collins and Kuehl, 2001) Thus nearly half of the dry wetland plant and soil material is carbon

The internal wetland carbon cycle is large A general idea

of the magnitudes of the various carbon transfers in a northern treatment marsh may be gained from considering the annual growth and decomposition patterns (see Chapter 3) A eutrophic treatment marsh grows about 3,000 dry g/m2 of aboveground biomass each year, with a carbon content of about 43% This translates to an annual average requirement for 35 kg/ha·d of carbon In northern climates, this requirement is utilized dur-ing a growing season of approximately four months In the case of emergent macrophytes, some of this carbon may be withdrawn from the atmosphere However, submerged veg-etation draws carbon from the aquatic carbonate system.Decomposition of the resultant litter returns a significant portion of that carbon to the atmosphere and to wetland waters, but in treatment wetlands, a small fraction, on the order of 15%

or 20%, is stored in accreted soil and sediments That storage (burial) fraction therefore amounts to about 5 kg/ha·d as an annual average for the eutrophic marsh example The balance, about 30 kg/ha·d, is processed via one or more mechanisms involving a variety of electron acceptors (oxidants), or via anaerobic digestion which generates methane

The oxygen consumed by aerobic decomposition of sediments and litter is termed the sediment oxygen demand (SOD) In stream environments with large wastewater influ-ences, the rate of consumption of oxygen by the stream sediments may be estimated as 20–100 kg/ha·d (Metcalf and

FIGURE 8.1 Distribution of carbonate species in water at 25°C The

partial pressure of CO 2 in the air is taken as 3.16 r 10 −4 atm (From

Metcalf and Eddy Inc (1998) Wastewater Engineering, Treatment,

Disposal, and Reuse, Tchobanoglous et al (Eds.), Fourth Edition,

McGraw-Hill, New York Reprinted with permission.)

Eddy Inc., 1991) In the eutrophic marsh example, if all the

decomposition were to proceed via oxidation with dissolved

oxygen as the electron acceptor, and CO2 as the product, the

equivalent SOD loading would be (32/12) r 30  80 kg/ha·d

As will be subsequently shown, this potential SOD loading is

at the upper end of the range of external BOD loadings (BLI)

for treatment wetlands

The wetland environment is more complicated than the

stream environment Some of the carbon is processed

above-water, as standing dead material oxidizes Some of the

sub-merged sediments and litter are processed into soluble organic

compounds that contribute to CBOD in the water, thus

cre-ating a nonzero background CBOD in a wetland

environ-ment Starches, sugars, and cellulose are degraded to amino

acids and fatty acids (Reddy and Graetz, 1988) In addition

to dissolved oxygen, a variety of electron acceptors may be

involved in decomposition

C ARBON P ROCESSING IN W ETLAND N ECROMASS AND S OILS

A rough representation of the various decomposition

“reactions” may be set down (Mitsch and Gosselink, 1993)

These occur in different horizons in the wetland, as indicated

3

2 +

FIGURE 8.2 Carbon storages and transfers in the wetland environment DC  dissolved carbon; PC  particulate carbon; DIC  dissolved

inor-ganic carbon; DOC  dissolved orinor-ganic carbon; CH 4  methane; CO 2  carbon dioxide Biomass carbon consists of living and dead biomass, as

well as organic decomposition products (From Kadlec and Knight (1996) Treatment Wetlands First Edition, CRC Press, Boca Raton, Florida.)

CH COO3 4 H2l 2 CH4 H O2 OH

The relative percentages of these reactions were

inves-tigated in controlled SSF wetland microcosms by Burgoon

(1993), using acetate as the carbon source His results

dem-onstrated that all routes can be important, depending upon

physical and chemical conditions

It is apparent that the wetland provides a spectrum of

potential pathways for the utilization of organic carbon

com-pounds Sufficient information is not available to quantify

both the complex chemistry and the spatial distribution of

chemical compounds Therefore, the interactions must be

described via correlations and rate equations, which are

sup-portable by wetland performance data

8.2 BOD REMOVAL IN FWS WETLANDS

A large amount of BOD data now exists for FWS wetlands

treating a variety of wastewaters There are a number of ways

to summarize this information, including removal rate

mod-els and graphical summaries When waters with moderate

to large concentrations of BOD flow through a wetland, a

decrease in concentration to a nonzero plateau is typically

observed This behavior is illustrated in Figure 8.4 for one of the continuous flow Sacramento, California, wetlands (Nolte and Associates, 1997) Samples were taken along the wetland

Zone IV and V

Eh = –300 to 100 mV Anaerobic respiration

Dissimilatory nitrate reduction

Fe S

Short chain fatty acids

Energy

Methane formation

Organic

CH4

H2

FIGURE 8.3 Pathways of organic carbon decomposition in wetland soils Aerobic, facultative anaerobic, and obligate anaerobic processes

are all typically present at different depths in the soil (From Reddy and Graetz (1988) In The Ecology and Management of Wetlands Hook

(Ed.), Croom Helm, London, United Kingdom, pp 307–318 Reprinted with permission.)

5 4

3 2

Time (days) 1

0 0 5

10

15 20 25

FIGURE 8.4 Profiles of BOD concentration in Cell 7B of the

Sacra-mento, California, treatment wetlands on May 3 and May 4, 1995 The

plateau is at 3.1 mg/L (Data from Nolte and Associates (1997)

Sac-ramento Regional Wastewater Treatment Plant Demonstration lands Project 1996 Annual Report to Sacramento Regional County

Wet-Sanitation District, Nolte and Associates: Sacramento, California.)

length, at positions corresponding to increasing nominal

deten-tion time The same sort of response is seen in the results

of Lakhsman (1981) for batch wetland treatment of lagoon

effluents A set of wetlands were charged with wastewater,

then closed in, with no water additions or withdrawals Typical

response data showed a sharp decrease in BOD5 to a nonzero,

fluctuating background (Figure 8.5) The decrease is steep—

perhaps exponential—but to a nonzero background BOD5

A NNUAL I NPUT –O UTPUT C ONCENTRATION R ELATIONS

The concentration of carbonaceous compounds is reduced

in FWS wetlands for incoming concentrations above

back-ground If, however, incoming BOD is below background,

concentrations may increase upon passage through the

sys-tem As inlet concentrations increase, outlet concentrations

increase, in a log-linear progression (Figure 8.6) There is

considerable intersystem variability, but the data exhibit a

lower bound, which may be interpreted as the lowest

back-ground concentration corresponding to a given inlet

concen-tration This curve is approximated by

 iimit background BOD concentration, mg/L

Depending on hydraulic conditions, and the character of the

incoming BOD, individual wetlands will typically exhibit

different C*-values as model calibration parameters, which

may be larger than C**.

F IRST -O RDER M ODELING

The P-k-C* first-order model can readily account for

obser-vations, for appropriate values of parameters (see Chapter 6)

However, parameter values are known to depend on system hydraulics (Kadlec, 2000), as well as on speciation of the BOD (Crites and Tchobanoglous, 1998; Kadlec, 2003a).BOD and COD are water quality parameters measured by procedures that lump individual chemical compounds into an overall, or total, concentration for that class of materials It is clear that the individual components of such mixtures may be degraded or removed at different rates, and that there is a cor-responding difference in removal rate constants (Crites and

Tchobanoglous, 1998; Tchobanoglous et al., 2000; Kadlec,

2003a) There is therefore a distribution of rate constants across the various mass fractions of the mixture As water con-taining such a mixture passes through the wetland, its compo-sition changes because different fractions of the mixture are

reduced at different rates The mixture becomes weathered, a

term coined to describe the selective stripping of light volatile materials upon exposure to outdoor environments In the case

of BOD and COD, the easy-to-degrade substances are lost first; more recalcitrant compounds persist for longer times

The BOD test itself reflects only a fraction of the naceous mixture, because it is terminated before all compo-nents are oxidized For municipal wastewater, the five-day BOD test typically measures about two thirds of the ultimate BOD (UOD) (Metcalf and Eddy, Inc., 1991; Crites and Tcho-banoglous, 1998)

carbo-Effects of Lumping on Removal Models

The potential effects of speciation in lumped contaminant measures, particularly BOD, as manifested in changing rates, have been known for several years (Tchobanoglous, 1969;

Crites and Tchobanoglous, 1998; Shepherd et al., 2001)

35 30 25

Time (days) 5

FIGURE 8.5 The progression of BOD concentrations in three

wet-lands operated in the batch mode The plateau is at 11.3 mg/L (Data

from Lakhsman (1981) A Demonstration Project at Humboldt to

Provide Tertiary Treatment to the Municipal Effluent Using Aquatic

Plants SRC Publication No E-820-4-E-81 74 pp Saskatchewan

10 1

0.1 0.1 1 10 100

1,000

Co = Ci

Trend Lower

FIGURE 8.6 Input–output concentration for BOD in FWS

wet-lands Each point represents an annual average for one wetland There are 385 wetland·years of data for 138 wetlands The trend

line is y  1.13 x0.67 (R 2  0.75 logarithmic) The lower bound line is

y  0.6 0.065 x, and includes 98% of the annual averages.

Crites and Tchobanoglous (1998) set forth a formulation for

a “retarded rate expression.” However, Kadlec (2003a)

dem-onstrated that this concept was subsumed by a relaxed

tanks-in-series (TIS) model The P-k-C* model is here defined to

be (see Chapter 6):

o i

The parameter P accounts for two effects: the detention time

distribution (DTD) and the k-value distribution (kVD) (see

Chapter 6) The value of P is always less than the number

of tanks determined from a tracer test For broad

distribu-tions of k-values, such as may occur for BOD, a

hydrau-lic TIS number of four (see Table 6.3) will be reduced to a

P-value of one or two However, the C*-value in Equation

8.20 reflects several possible different causes There may be a

real irreducible component of BOD (hard to imagine, because

it all disappears in the lab test), or there may be wetland

eco-system feedback of BOD constituents But in addition, DTDs

and kVDs may create an apparent C* as an artifact of model

parameter fitting These may be considered “bypassing C*”

and “weathering C*”, respectively.

Reasonable data fits may be obtained for specific wetlands

or specific sites Seven Gustine, California, wetlands were

operated at different hydraulic loadings (different detention

times) for a calendar year (Walker and Walker, 1990) The

P-k-C* model parameters determined from that input–output

data were: P  1, k  63 m/yr, and C*  9.7 mg/L (R2 0.60)

Those parameters also provided a reasonable fit to transect

data (Figure 8.7, R2  0.59) However, it is uncommon to

have multiple wetlands and multiple loadings from which to

derive these types of calibrations

Concentration Profiles and Modeling Pitfalls

Difficulties with the P-k-C* first-order model are compounded

by the problem that data sets are very often poorly conditioned

to produce good estimates of both k and C* by any of the

sev-eral methods of parameter estimation This is easily visualized

from Figures 8.4, 8.5, and 8.8, which contain examples of the

early exponential decline (governed by k), together with the

late plateau (governed by C*) There are insufficient data in

the exponential region for Sacramento and Humboldt to get

a good estimate of k, but plenty of data to define C*

Con-versely, the Arcata pilot, Benton, and Gustine data sets never

reach a plateau; all the data is concentrated in the

exponen-tial decline region Thus, for these wetlands, transect data will

provide a good estimate of k, but a very poor estimate of C*

Input–output data for these sites may nonetheless be fitted to the model In addition to the Gustine results given above, Ben-

ton input–output data over a two-year span resulted in P 1,

k  260 m/yr, and C*  5 mg/L At the Arcata pilot, input– output data over a two-year span resulted in P  1, k  53 m/yr, and C*  4 mg/L.

It is tempting to arbitrarily pick some low concentration to

represent C*, but that is counter-indicated by the importance

of C* in wetland sizing, as shall be seen in the following

sec-tions There is not an existing method to make such an estimate with confidence One need look no further than data from two wetlands in the same geographical region: Humboldt, Sas-

katchewan, shows C*  11.3, but not far away, Oak Hammock, Manitoba, shows C*  2.4 Both are batch systems treating

domestic lagoon effluent We shall also see that k-values are

widely variable, both across years for one wetland nual variability) and across wetlands (intersystem variability) Thus, to the dismay of researchers seeking to do THE definitive design model calibration study, no such study can be trusted in and of itself

(interan-1.0 0.9 0.8 0.7 0.6 0.5 0.4 Fractional Distance 0.3

0.2 0.1 0.0 0 100 200

300

400 500 600 700

800

Transect Data

P-k-C* Model

FIGURE 8.7 BOD profile in the flow direction for wetland 1D at

Gustine, California The model curve was derived from independent input–output data for seven wetlands over a calendar year (From

Kadlec and Knight (1996) Treatment Wetlands First Edition, CRC

Press, Boca Raton, Florida.)

12 11 10 9 8 7 6 Nominal HRT (days) 5

4 3 2 1 1

10

100 1,000

0

Gustine Arcata Pilot Benton

FIGURE 8.8 Initial exponential declines in BOD for FWS

wet-lands These systems did not achieve any apparent plateau.

Distribution of k-Values

It is instructive to examine multiple data sets that provide a

dis-tribution of k-values and C*-values If all data are considered

together, the inter- and intrasystem effects are compounded

by a shift in the probable mechanisms of BOD reduction, as

detailed in Equations 8.10–8.18 As loadings increase, aerobic

processes become less of a probable factor, and are replaced by

anoxic processes Therefore, four levels of inlet concentration

are considered: tertiary (0  Ci 30 mg/L); secondary (30  Ci

 100 mg/L); primary (100  Ci 200 mg/L); and “super” (Ci

 200 mg/L) The effect of BOD weathering, which produces

lower k-values as reaction proceeds, is quite strong for BOD

Data fits are better for P-values that are considerably lower

than the tracer-determined number of tanks-in-series (NTIS)

values In general, data fits are best at P 1, as noted earlier for

Gustine, Benton, and Arcata If the annual performance

data-base is used for calibration, a value of P somewhat less than 1

is found, and therefore analysis has been performed using P

1 For purposes of uniformity, the presumptive C*-values are

taken to be those of Equation 8.20, leading to C*  2, 5, 10, and

20 mg/L for the four categories, respectively

The resultant annual average k-values are given in

Table 8.2 The median values are not much different for

ter-tiary, secondary, and primary applications (median  37 o

4 m/yr), but increases for the stronger influents (super) to

189 m/yr The spread of these distributions is quite large,

imply-ing that the characteristics of individual wetlands, or individual

years in the period of record, can have strong influences on

performance

Annual Loading Relations

The BOD concentration produced in treatment wetland

depends upon three primary variables (area, water flow, and

inlet concentration), as well as numerous secondary ables (vegetation type, internal hydraulics, depth, event pat-terns, and others) It is presumed that the area effect may be combined with flow as the hydraulic loading rate (flow per unit area), because two side-by-side wetlands with double the flow should produce the same result as one at nominal flow Therefore, two primary variables are often considered:

vari-hydraulic loading rate (q  HLR) and inlet concentration (Ci).Previous performance analyses have been based upon these two variables (Kadlec and Knight, 1996)

An equivalent approach is to rearrange the primary

vari-ables, without loss of generality, by using BLI rate (q·Ci) and

concentration (Ci) Thus it is expected that the outlet

concen-tration produced (Co) will depend upon BLI and Ci A cal display has often been adopted in the literature (Kadlec and Knight, 1996; U.S EPA, 2000a; Wallace and Knight, 2006) In the broad context, multiple data sets are represented by a trend

graphi-that shows decreasing Co with decreasing BLI (Figure 8.9) Scatter is presumably due to secondary variable differences, such as the relative proportions of different vegetation types, hydraulic efficiencies, and other factors The points at lowest loadings are for systems receiving very low BOD

Each point in Figure 8.9 represents the average of one year’s data for a given FWS wetland Both BOD and CBOD data are represented; therefore, it is understood that some of the scatter is due to the difference between these two measures The use of annual averages removes seasonal variability, if any, and precludes the effects of synoptic error (see Chapter 6)

M ODEL C URVES

The data cloud in Figure 8.9 has been reproduced in

various parameter values The hydraulic loading is also an

TABLE 8.2 Distribution of Annual Areal Rate Coefficients

kA (m/yr) for BOD in FWS Wetlands

independent parameter in that model It is seen that the data

are bounded by Line 1, which represents high C* and low

HLR and k; and Line 2, which conversely represents low C*

and high HLR and k These correspond to a very wide range

of potential k and C*-values; in fact, so wide that there is little

resolution of the data by the model Lines 3 and 4 represent a central tendency of the data, but do not entirely resolve either

the k or C* variability Thus it is seen that the intersystem data

FIGURE 8.9 Outlet BOD concentration versus BOD loading for FWS wetlands Each of the 383 points represents an annual average for one

of 136 wetlands Data groups are for tertiary (0  C i 30 mg/L); secondary (30  Ci 100 mg/L); primary (100  Ci  200 mg/L); and “super”

does not aid in pinpointing narrow ranges of model parameters

In semiquantitative terms, the ranges that span the data are:

15 < < 250 m/yr

2 < < 20 mg/L

1 < < 2

k C P

*

It is noteworthy that the central tendency reported by Kadlec

and Knight (1996), i.e., k  34 m/yr and C* y 3.5 mg/L for

P ∞, is still a good central estimate for the much larger data

set now available

V ARIABILITY IN A NNUAL P ERFORMANCES

Interestingly, the intrasystem interannual variability

(year-to-year variability for one wetland with several (year-to-years’ data) is not

necessarily much smaller than the intersystem variability

(vari-ability among several wetlands) Some single wetlands span

the data cloud from one extreme to the other for different years

of operation As examples, the annual values of a few wetlands

have been identified in Figure 8.11 For some, such as

Poinci-ana, Arcata Enhancement, and Cannon Beach, the interannual

variation is a significant fraction of the intersystem variation at

the same loading (about

annual variability, such as Reedy Creek and Dove Creek, but

still about half of the intersystem variation

In terms of model parameters, the result is a large spread

in k-values This may be illustrated by examining the spread

of k-values (for P  1 and C*  2) for the various years and

systems at Arcata, all working at the same site (Figure 8.12)

Out of this modeling effort, the central messages are that

(1) the P-k-C* model spans the intersystem data (as it should),

but that (2) there is no resolution of the wide range of parameter

values that might be selected Consequently, the P-k-C* model

by itself is insufficient for wetland design This simple model can be fit to a single profile or input–output data set, and repre-sent it very well; but inherent variabilities remain quite large It

is not possible to say with certainty what next year’s k-value will

be, nor what the next wetland’s k-value will be Unfortunately, this is also true for C*-values It is informative to seek further

understanding of the factors that may control performance

E FFECTS OF D ESIGN AND O PERATING C ONDITIONS

Water Depth

were possible as limiting cases of first-order removal models:

FIGURE 8.11 Single system performance within the general milieu of annual data.

Rate Constant (m/yr)

FIGURE 8.12 Rate constants for BOD removal for the aggregate

of Arcata, California, data sets The basis is C*  2 mg/L and P  1

There are 23 annual average points for the pilot cells (12 cells over two years), 12 years for the combined treatment marsh cells, and 12

years for the combined enhancement marsh cells The site k 54 o

39 m/yr (mean o SD).

either (1) the contaminant was processed everywhere within

the water column, in proportion to the water volume; or (2)

the contaminant was processed in proportion to the wetland

planar area In terms of model equations, the influence is

exerted through the depth dependence of removal:

The question arises whether kA is constant, or whether kV is

constant In the former case, the extra detention time created

by deeper operation is of no benefit, because kV is reduced

as depth increases; in the latter case, increased depth creates

no penalty in decreased kV-values, and performance can be

increased by increasing the water depth

As one test of the two possibilities, operational data

from a wetland with sequentially varied depths may be

examined The Listowel wetlands were operated at various

depths over a four-year period, with the resulting ability

to examine Equation 8.22 There is a strong increase in kV

-values with (1/hn) for depths above about 5 cm (Figure 8.13),

indicating that kA is more nearly constant than kV It is

pos-sible that the drop in kV for depths less than 5 cm is due to the

incomplete wetting of the wetland surface

A second test is to compare side-by-side wetlands ated at different depths The Arcata pilot wetlands were oper-ated in that fashion for two years Each of three hydraulic loadings was replicated at two depths For each loading, the

oper-value of kV was lower at the larger depth (Table 8.3) Over the entire suite of experiments, a 35% depth increase resulted in

a 35% kV decrease This also indicates that kA is more nearly

constant than kV

Either kA or kV can be used to represent a data set or be

used in design However, the use of kV requires the

accom-panying information on water depth (h) because of the depth

dependence indicated in Equation 8.22 This depth dence also means that more detention time created by deeper water is counteracted by a decrease in the volumetric rate constant The hydraulic loading rate is not depth-dependent,

depen-25 20

15 10

Reciprocal Depth (m –1 ) 5

0 0.0 0.5 1.0

System 4 System 5 3.5

4.0

FIGURE 8.13 Variation of the volumetric rate constant for BOD

removal for Listowel, Ontario, Systems 4 and 5 The parameters P

Note: Twelve pilot cells were operated as duplicates at two depths and three hydraulic loading rates, over a period of two years, beginning one year after

start-up The P-k-C* model parameters were fixed at P  1 and C*  2 mg/L.

Source: From analysis of data in Gearheart et al (1989) In Constructed Wetlands for Wastewater Treatment: Municipal, Industrial, and Agricultural Hammer

(Ed.), Lewis Publishers, Chelsea, Michigan, pp 121–137.

and the same data indicate that kA is nearly independent of

depth The use of areal coefficients does not require depth

For many FWS wetlands, especially large ones, depth is not

known to a reasonable degree of accuracy (see Chapter 2)

For these reasons, the parameter k is used herein.

Loading Effect on k-Values

Importantly, both kV and k depend to some degree upon BLI

rate This is the observed trend of the data from a large

num-ber of free water surface wetlands (Figure 8.14) The selected

parameters were P  2 and C*  2 mg/L Although the

cor-relation depends to some extent upon the values of P and C*,

there is no selection of these parameters that removes the

dependence of kV and k on the BLI rate.

The first-order model has increased sensitivity to loading

if the value of C* is chosen to be zero (Kadlec, 2000) Under

that assumption, the values of kV1 are nearly proportional to

BLI, or inversely proportional to the detention time, for low

hydraulic loadings The additional subscript “1” indicates

that the model contains only one parameter, the k-value, as

opposed to two (k and C*) This sensitivity is exacerbated if

the plug flow model is used, i.e., P ∞ The

near-proportional-ity of kV1PF to BLI has been repeatedly recognized (Reed et al.,

1995; Kadlec, 2000; Water Environment Federation, 2001;

Ran et al., 2004) WEF (2001) report the following relation:

k rrate constant withC*0, d-1

This dependence leads to a design paradox The required

wet-land area is inversely proportional to the k-value, whereas the

inlet BLI is inversely proportional to wetland area Suppose a BLI has been chosen as a first estimate, and the correspond-

ing k-value determined (e.g., from Equation 8.23); and the

predicted outlet BOD is too high The obvious correction is to increase area However, that lowers the inlet BLI, and accord-

ing to Equation 8.23, also lowers the k-value Clearly, this is a useless procedure Reed et al (1995) dispose of the difficulty

by ignoring Equation 8.23 This regression is an example of the spurious correlation caused by hydraulic loading appear-ing in both the abscissa and ordinate (see Chapter 6)

Temperature

The first-order model has been reliable for predicting removal rates of organic matter in most wastewater treatment pro-cesses (Metcalf and Eddy Inc., 1991) The modified Arrhe-nius relationship is commonly used to adjust the removal rate coefficient for temperature in traditional wastewater treat-ment processes:

V1 V1,20Q( 20 )

(8.24)where

-1rate constant at 20°C, dwater tempe

The treatment wetland literature is replete with the assertion that a Q-value of about 1.06 applies to FWS wet-

lands (Reed et al., 1988: 1.10; U.S EPA, 1988b: 1.10; Reed

et al., 1995: 1.06; Crites and Tchobanoglous, 1998: 1.06;

Campbell and Ogden, 1999: 1.06; U.S EPA, 2000a: 1.04)

These reports all referred to the plug flow model with C*  0

However, Kadlec and Knight (1996) could not find a perature dependence in wetland BOD data That finding was subsequently supported by analysis of more systems (Kadlec and Reddy, 2001)

tem-The two most closely related companion technologies for BOD reduction are overland flow and stabilization ponds The former involves very shallow (a few centimeters depth

at most) water flow over a vegetated surface, and the latter represent algal-aquatic systems with typical depths of one to two meters Thus, these technologies may be regarded as the shallow- and deepwater extremes of treatment wetlands The

data from those systems yield temperature coefficients that

are close to 1.00 for ponds (1.005 o 0.014) and overland flow

(1.01 o 0.01) (Kadlec and Reddy, 2001) U.S EPA (1983a)

suggests several different design approaches for facultative

ponds, including equivalents to the first-order model

pre-sented above The suggested design temperature factors are

Q  1.085 and 1.090 However, U.S EPA (1983a) show a

data basis that produces Q  0.995 The authors explain this

as follows: “The logical explanation for the lack of

influ-ence by temperature is that the pond systems are so large

that the temperature effect is masked by other factors.” No

explanation was offered for rejecting the observed behavior

in the recommended design calculations This lack of a

tem-perature effect in ponds has more recently been reported by

Abis (2002)

Here the temperature effect on performance of

sev-eral wetland systems has been re-analyzed with the P-k-C*

model, with P 1 (Table 8.4) The Q-value is 0.985 o 0.021,

meaning slightly worse performance at higher temperatures

Little or no variance is removed by adding a Q-factor to the

model It is clear that the complex of wetland ecosystem

pro-cesses is masking the known microbial temperature

sensitiv-ity expected for suspended growth systems One candidate

explanation is oxygen transfer, which must be adequate to

justify the first-order approximation However, as seen in the

earlier section on carbon processing, many other processes

can influence BOD removal

The preponderance of evidence suggests that wetland BOD removal is not improved at higher wetland water temperatures

S EASONAL T RENDS

There are typically gentle annual cycles in the effluent BOD from FWS wetlands (Figure 8.15) A maximum is seen in spring or summer, and the amplitude of the annual cycle is

on the order of 30% of the mean (Table 8.5) The trend is described by

concentration, mg/Lmean annual conc

yearday, dyearday fomax

t t

 rr maximum concentration, dannual period,

These cycles often do not reflect contemporary influent BOD

or the contemporary hydraulic loading to the wetland This is evidenced in Figure 8.15, where minima of the inlet concen-tration correspond to maxima of the outlet concentration, for relatively uniform hydraulic loading throughout the year

TABLE 8.4

Temperature Factors for the P-k-C* Model for Example FWS Wetlands

Data (years)

The considerable scatter in effluent concentrations

con-tributes to low R2-values for the trend lines (Table 8.5) This

behavior is of concern in wetland sizing, if the peak values of

the concentrations are of importance in the regulatory

com-pliance for the project

Variability around Seasonal Trends

Because stochastic behavior is present in moderate amount,

it is necessary to quantify performance variability, and

ulti-mately to modify sizing based upon that understanding

Aver-age effluent BOD values over short time periods are subject

to variation from the annual mean The longer the averaging period, the closer the short-term mean value is to the annual mean value For FWS wetlands, average effluent BOD con-centrations are distributed approximately according to the log normal distribution Examples of these distributions are given

The averaging period has a very strong influence on the higher percentiles, which form the basis for permit require-ments The example given in Figure 8.17 shows that for the Columbia, Missouri, system, the daily maximum is about triple the monthly maximum, and the weekly maximum is about double the monthly maximum These ratios shrink as

13

Cycle In Cycle Out BOD Out

BOD In

Cycle In Cycle Out CBOD Out

CBOD In

Cycle In Cycle Out COD Out

Sample Frequency

Averaging Period

Trend Mean (mg/L)

Trend Fractional Amplitude

CBOD

TOC

COD

* POR = period of record

100 10

CBOD (mg/L) 1

FIGURE 8.16 Frequency distributions for monthly BOD

(Can-non Beach, Oregon; Listowel, Ontario) and weekly CBOD (Arcata,

California).

32 28 24

Daily Weekly Monthly

20 16 BOD (mg/L) 12

8 4 0 0.0 0.1 0.2 0.3 0.4 0.5 0.6

0.7 0.8 0.9 1.0

FIGURE 8.17 Frequency distributions at the Columbia, Missouri,

wetlands for daily (five days out of seven), weekly (average of five dailies), and monthly BOD values (average of 22 dailies) The 90th percentile is about 1.6 times the mean However, the maximum daily value is about triple the mean.