2 Acle, Norfolk, United Kingdom (17)

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A. Idris et al.

Table 10.7

Average performance of wetland in Acle, Norfolk in 1988 (17)

Parameter

BOD

AN

SS



Influent (mg/L)



Effluent (mg/L)



Removal efficiency (%)



38

6.1

76



4.8

5.3

28



87

13

63



The support medium used was 0.60-m soil from sugar beet washing, and the vegetation was

Phragmites australis. The floor slope was in the ratio of 1:50. The wastewater flow through a

slotted pipe buried in gravel and the treated effluent was discharged using a height adjustable

bellmouth.

The wetland has an average flow of 240 m3 /d, average hydraulic load of 0.07 m3 /m2 /d, and

plan surface area of 2.92 m2 /pe. The performance of the wetland can be seen in Table 10.7.



9.3. Arcata, California (10)

Arcata is located on the northern coast of California about 240 miles north of San Francisco.

The population of Arcata is about 15,000. The major local industries are logging, wood

products, fishing, and Humbolt State University. The surface flow (SF) constructed wetland

located in Arcata is one of the most famous in the United States.

The community was originally served, starting in 1949, with a primary treatment plant that

discharged undisinfected effluent to Arcata Bay. In 1957, oxidation ponds were constructed,

and chlorine disinfection was added in 1966. In 1974, the State of California prohibited

discharge to bays and estuaries unless “enhancement” could be proven, and the construction

of a regional treatment plant was recommended. In response, the City of Arcata formed a

task force of interested participants, and this group began research on lower-cost alternative

treatment processes using natural systems. From 1979 to 1982, research conducted at pilotscale wetland units confirmed their capability to meet the proposed discharge limits. In 1983,

the city was authorized by the state to proceed with development, design, and construction of

a full-scale wetland system.

Construction was completed in 1986, and the system has been in continuous service

since that time. The wetland system proposed by the city was unique in that it included

densely vegetated cells dedicated for treatment followed by “enhancement” marsh cells with

a large percentage of open water for final polishing and habitat and recreational benefits. This

combined system has been successful since start-up and has become the model for many

wetland systems elsewhere.

Two NPDES permits are required for system operation: one for discharge to the enhancement wetlands for protection of public access and one for discharge to the bay. The NPDES

limits for both discharges are BOD 30 mg/L and TSS 30 mg/L, pH 6.5–9.5, and fecal coliforms

of 200 CFU/100 mL. Since public access is allowed to the enhancement marshes, the state

required disinfection prior to transfer of the pond/treatment marsh effluent. The state then

required final disinfection/dechlorination prior to final discharge to Arcata Bay. The effluent



Wetlands for Wastewater Treatment



345



from the final enhancement marsh is pumped back to the treatment plant for this final

disinfection step.

The basic system design for the treatment and enhancement marshes was prepared by

researchers at Humbolt State University. The design was based on experience with a pilot

wetland system that was studied from 1979 through 1982. The pilot wetland system included

12 parallel wetland cells, each 20-ft wide and 200-ft long (L:W 10:1), with a maximum

possible depth of 4 ft. These were operated at variable hydraulic loadings, variable water

depths, and variable initial plant types during the initial phase of the study. Hardstem bulrush

(Scirpus validus) was used as the sole type of vegetation on all cells. The inlet structure for

each cell was a 60◦ V-notch weir, and the outlet used an adjustable 90◦ V-notch weir, permitting

control of the water depth. Heavy clay soils were used for construction of these cells, so

a liner was not necessary and seepage was minimal. The second phase of the pilot study

focused on the influence of open water zones, plant harvesting, and kinetics optimization for

BOD, TSS, and nutrient removal. Some of the cells, for example, were subdivided into smaller

compartments with baffles and weirs along the flow path. The results from these pilot studies

not only provided the basis for full-scale system design but have contributed significantly to

the state-of-the-art for design of all wetland systems.

The full-scale treatment wetlands, with a design flow of 2.9 mgd, utilize three cells operated

in parallel. Cells 1 and 2 have surface areas of about 2.75 acres each (L ≈ 600 ft, W ≈ 200 ft),

and cell 3 is about 2.0 acres (L ≈ 510 ft, W ≈ 170 ft). The original design water depth was

2 ft, but at the time of the 1997 site visit for this report they were being operated with a

4-ft depth. Hardstem bulrush was again used as the only plant species on these treatment

marshes. Clumps of plant shoots and rhizomes were hand planted on about 1-m centers. Since

nutrient removal is not a requirement for the full-scale system, the treatment marshes could

be designed for a relatively short detention time primarily for removal of BOD and TSS.

The HRT in these three cells is 1.9 d at design flow and a 2-ft water depth. These treatment

marshes were designed to produce an effluent meeting the NPDES limits for BOD and TSS

(30/30 mg/L) on an average basis. These wetland cells utilized the bottom area of former

lagoon cells. A schematic diagram of the operating system is shown in Fig. 10.10.

The final “enhancement” marshes were intended to provide for further effluent polishing

and to provide significant habitat and recreational benefits for the community. These three

cells are operated in series at an average depth of 2.0 ft and have a total area of about 31 acres.

Retention time is about 9 d at average flow rates. The first cell (Allen Marsh), completed

in 1981, was constructed on former log storage area and contains about 50% open water.

The second cell (Gearheart Marsh), completed in 1981, was constructed on former pasture

land and contains about 80% open water. The third cell (Hauser Marsh) was constructed

in a former borrow pit and contains about 60% open water. These 31 acres of constructed

freshwater (effluent) marshes have been supplemented with an additional 70 acres of salt

water marshes, freshwater wetlands, brackish ponds, and estuaries to form the Arcata Marsh

and Wildlife Sanctuary, all of which has been developed with trails, an interpretive center,

and other recreational features. The shallow water zones in these marshes contain a variety

of emergent vegetation. The deeper zones contain submerged plants (Sago pondweed) that



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A. Idris et al.



Fig. 10.10. Schematic diagram of wetland system at Arcata, CA (11).



provide food sources for ducks and other birds and release oxygen to the water to further

enhance treatment.

The construction costs for the entire system, including modifications to the primary treatment plant, disinfection/dechlorination, pumping stations, and so forth were USD 5,300,000

(1985). Construction costs for the treatment wetlands are only estimated to be about USD

225,000, or USD 30,000 per acre, or USD 78 per 1,000 gpd of design capacity (including

removal of sludge from this site, which was previously a sedimentation pond for an aerated

lagoon). This does not include pumping costs to transfer final effluent back to the chlorination

contact basin, disinfection facilities, or the pumping and piping costs to reach the enhancement

marshes. Land costs also are not included since the treatment wetlands were located on cityowned property.

Performance data were collected for a two-year period during the Phase 1 pilot testing

program. This program varied the flow rate and water depth in each of the two cells to

compare BOD removal performance at different detention times and loading rates that would

represent the potential range for full-scale application at Arcata. These data are summarized

in Table 10.8. The BOD and TSS in the pond effluent varied considerably during this period,

and not all of the cells were uniformly vegetated. Seasonal variations in performance were

observed, but Table 10.8 presents only the average effluent characteristics for each of the cells

over the entire study period. It is apparent from the data that the wetlands were able to produce

excellent effluent quality over the full range of loadings and detention times used.

The long-term average performance of the Arcata system is summarized in Table 10.9. It

is clear that both the treatment and enhancement marshes provide significant treatment for

BOD and TSS. The long-term removals follow the pilot project results. Most of the nitrogen

is removed during the final stage in the enhancement marshes. This is because of the long

hydraulic detention time (HRT = 9 d), the availability of oxygen and nitrifying organisms

in the open water zones, and anoxic conditions for denitrification in the areas with emergent

vegetation.



Wetlands for Wastewater Treatment



347



Table 10.8

Summary of results, phase 1 pilot testing, Arcata, CA (11)

Item

Influent

Effluent

Cell 1

Cell 2

Cell 3

Cell 4

Cell 5

Cell 6

Cell 7

Cell 8

Cell 9

Cell 10

Cell 11

Cell 12



HRT (d)



HLR (gal/ft2 d)



BOD (mg/L)



26

2.1/10.7

1.5/17

2.7/29

1.5/15

3.7

5.2

5.2

5.2

6.6

3.8

7.6

5.5



TSS (mg/L)



37



5.89/1.22

5.89/0.5

4.66/0.5

5.39/0.5

2.94

2.4

4.4

2.4

1.71

1.71

1.47

1.47



Fecal coliform

(CFU/100 mL)



3,183



11

14.1

13.3

12.7

14.0

10.7

13.3

15.3

11.9

12.6

9.4

9.0



6.8

4.3

4.7

5.6

4.3

4.0

7.3

7.2

9.4

4.9

5.7

4.3



317

272

419

549

493

345

785

713

318

367

288

421



Table 10.9

Long term average performance, Arcata (11)

Location

Raw influent

Primary effluent

Pond effluent

Wetlands

Enhancement marshes



BOD (mg/L)



TSS (mg/L)



TN (mg/L)



174

102

53

28

3.3



214

70

58

21

3



40

40

40

30

3



The treatment wetlands (7.5 acres), with nominal HRTs of 3 days, met weekly limits of

30-mg/L BOD and TSS 90% of the time. The enhancement wetlands (28 acres), with a

nominal HRT of 11 days, met weekly limits of less than 5-mg/L BOD/TSS 90% of the time.

Performance of both wetlands results primarily from proper operation and appropriate design

that involves a combination of emergent vegetation and open water zones. TSS levels are

higher in cell effluents where outlets are located in open water zones. Recent advances in

wetland waste treatment can be found from the literature (18–20).



NOMENCLATURE

Symbol Definition Units (SI)

AN = Ammoniacal nitrogen

As = Surface area of wetland, m2

BOD = Biochemical oxygen demand, mg/L



348



A. Idris et al.



C = Carbon

Ce = Effluent pollutant concentration, mg/L

CH4 = Methane

Co = Influent pollutant concentration, mg/L

CO2 = Carbon dioxide

COD = Chemical oxygen demand

◦

C = Degree Celsius (centigrade), ◦ C

dm = Depth of media, m

dw = Depth of water from media surface, m

EPA = Environmental protection agency

FWS = Free water surface

HFS = Horizontal flow system

HLR = Hydraulic loading rate, m/d

HRT = Hydraulic retention time

kT = Temperature dependent first-order reaction rate constant, d−1

k20 = Rate constant at 20◦ C

L = Length of the wetland cell, m

n = Porosity, or the space available for water to flow through the wetland decimal

N = Nitrogen

NH+ = Ammonium ion

4

NO2 = Nitrogen dioxide

N2 = Nitrogen

N2 O = Nitrous oxide

NO− = Nitrite

2

NO− = Nitrate

3

NH3 = Free ammonia, mg/L

NH4eff = Effluent ammonia, mg/L

NO3 inf = Influent nitrate, mg/L

NO4eff = Effluent nitrate, mg/L

O2 = Oxygen

P = Phosphorus

Q = The average flow through the wetland, m3 /d

RZM = Root zone method

RRF = Rock–reed filter

r z = The percent of wetland bed depth occupied by root zone decimal

SF = Surface flow

SSF = Subsurface flow

SS = Suspended solids, mg/L

SSe = Effluent SS, mg/L

SSo = Influent SS, mg/L

spp. = Species

t = Hydraulic retention time, d

T = Temperature



Wetlands for Wastewater Treatment



349



TKN = Total Kjeldahl nitrogen, mg/L

TSS = Total suspended solids

TN = Total nitrogen

US = United States

V = Volume of water in the system, m3

VFS = Vertical flow system

VSB = Vegetated submerged bed

W = Width of the wetland cell, m

θ = Temperature coefficient



REFERENCES

1. Hammer DA (1989) Constructed wetlands for wastewater treatment – municipal, industrial and

agricultural. Lewis Publishers, Chelsea, MI

2. http://www.ramsar.org/key_guide_list_e.htm

3. Campbell CS, Ogden MH (1999) Constructed wetlands in the sustainable landscape. Wiley, NY

4. Hairston JE (1995) Municipal wastewater treatment constructed wetlands: a new concept in treating wastewater; ANR-790–3.1.3; Agricultural And Natural Resources: Water Quality: Managing

Wastewater; Alabama Cooperative Extension System (Alabama A & M and Auburn Universities),

USA

5. Reddy KR, De-Busk TA (1987) State-of-the-art utilisation of aquatic plants in water pollution

control. Wat Sci Technol 19(10):61–79

6. Armstrong W, Armstrong J, Beckett PM (1990) Measurement and modeling of oxygen release

from roots of Phragmites australis. In: Cooper PF, Findlater BC (eds) Use of constructed wetlands

in water pollution control. Pergamon Press, Oxford, pp 41–53

7. Brix H, Schierup HH (1990) Soil oxygenation in constructed reed beds: the role of macrophyte

and soil-atmosphere interface oxygen transport. Water Res 29(2):259–266

8. US EPA (1988) Design Manual: Constructed Wetlands and Aquatic Plant Systems for Municipal

Wastewater Treatment. EPA/625/1–88/022. Office of Research and Development, Cincinnati,

OH 45268

9. Brix H (1997) Do macrophytes play a role in constructed treatment wetlands? Wat Sci Technol

35(5):11–17

10. US EPA (2001) Manual: Constructed Wetlands Treatment of Municipal Wastewaters. EPA/625/R99/010. Office of Research and Development, Cincinnati, OH 45268

11. Davis L (1995) A handbook of constructed wetland. A guide to creating wetlands for: agricultural

wastewater, domestic wastewater, coal mine drainage, stormwater in the Mid-Atlantic Region,

Volume 1: General Considerations. Prepared for the United States Department of Agriculture

(USDA) Natural resources Conservation Service and the Environment Protection Agency (EPA)

Region III in cooperation with the Pennsylvania Department of Environmental Resources

12. Crites RW, Tchobanoglous G (1998) Small and decentralized wastewater management systems.

WCB/McGraw Hill, San Francisco, CA

13. Reed SC, Crites RW, Middlebrooks EJ (1995) Natural systems for waste management and treatment, 2nd edn. McGraw Hill, New York

14. Beharrel M, Lim WH, Gan J (2002) Good practices in wetland management and conservation. In: Ahyaudin A, Salmah CR, Mansor M, Nakamura R, Ramakrishna S, Mundkur T (eds)



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15.

16.

17.



18.

19.



20.



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Proceedings of a workshop on the Asian wetlands: bringing partnerships into good wetland

practices, pp 582–594

Majizat A (2003) Operation and management of Putrajaya lake and wetlands, National Seminar

on Constructed Wetlands, Putrajaya, Malaysia

Ibrahim ZZ, Noordin N (2003). Putrajaya lake and wetlands: from concept to reality. National

Seminar on Constructed Wetlands, Putrajaya, Malaysia

Nuttall PM, Boon AG, Rowell MR (1997) Review of the design and management of constructed

wetlands; Report 180; Construction Industry Research and Information Association (CIRIA),

London, United Kingdom

White KD, Wang LK (2000) Natural treatment and on-site processes. Water Environ Res 72(5):

1–12

Shammas NK, Wang LK (2009) Natural biological treatment processes, Chapter 15. In: Wang

LOK, Shammas NK, Humg, YT (eds) Advanced Biological Treatment Processes. Humana Press,

Totowa, NJ, pp 583–618

Wang LK, Ivanov V, Tay JH, Hung YT (2010) Environmental Biotechnology. Humana Press,

Totowa, NJ, 975 pp



11

Modeling of Biosorption Processes

Khim Hoong Chu and Yung-Tse Hung

CONTENTS

I NTRODUCTION

BATCH O PERATION

C OLUMN O PERATION

E XAMPLES

N OMENCLATURE

R EFERENCES

Abstract Biosorption entails the use of microbial or plant biomass, usually inactivated, to

remove toxic metal ions in aqueous solutions. It is particularly effective in dealing with low

concentration, high volume metal waste streams. Although biosorption processes have not

yet been commercialized to any significant extent, they offer a promising area for future

developments. This chapter presents several process models that can facilitate the design and

analysis of batch and fixed bed biosorption systems.



1. INTRODUCTION

The pollution and health problems that are caused by toxic metals are of increasing concern

to the general public. In addition to anthropogenic sources, metal pollution may be attributed

to natural processes. For example, arsenic is a naturally occurring element in the earth’s crust.

Its presence in ground and surface waters in many parts of the world is believed to originate

from geological reactions. Arsenic is considered as a soft metal and its toxicity effects are

similar to those of lead and mercury (1). Ingesting high levels of arsenic over many years

can cause cancers of the skin, liver, lung, kidney, and bladder as well as neurological and

cardiovascular problems.

It has been well documented that arsenic contamination in drinking water has created a

serious health crisis in countries like India and Bangladesh, where millions of people already

show symptoms of arsenic poisoning. The United States Geological Survey reported that more

than 10% of tested groundwater samples had arsenic concentrations exceeding 10 μg/L in

24% of the US counties surveyed (2). Regulations in many parts of the world stipulate that

metals such as mercury, copper, cadmium, lead, chromium, and arsenic be removed from

From: Handbook of Environmental Engineering, Volume 11: Environmental Bioengineering

Edited by: L. K. Wang et al., DOI: 10.1007/978-1-60327-031-1_11, c Springer Science + Business Media, LLC 2010



351



352



K.H. Chu and Y.-T. Hung



potable water supplies and waste streams down to parts per billion levels. For instance, the

World Health Organization’s recommended guideline for arsenic in drinking water is 10 μg/L,

and public water systems in the USA must comply with a new EPA standard of 10 μg/L

for arsenic in drinking water beginning January 2006. The increasingly stringent regulations

are posing formidable challenges to the scientific community involved in developing highly

efficient metal removal technologies while keeping costs to a minimum. One potential metal

removal technology, which may satisfy the dual requirement of high efficiency and low cost,

is biosorption. The cost of biomass can be kept to a minimum through the use of industrial

biomass byproducts generated by the fermentation industry, biomass propagated through

inexpensive means, or biomass harvested from nature.

Biosorption entails the use of microbial or plant biomass, usually inactivated, to remove

metal ions in aqueous solutions. It is particularly effective in dealing with low concentration,

high volume metal waste streams. Over the last 20 years, numerous biomass types including

bacteria, yeasts, fungi, microalgae, and macroalgae as well as heterogeneous biomass such

as activated sludge have been tested for their ability to treat water contaminated with trace

quantities of metal ions (3). The metal sequestration ability of biological materials is attributed

to the presence of a myriad of functional groups or ligands on the biomass surface, which are

able to interact with metal ions. The interactions of metal ions with these functional groups

are various and, for the most part, not well understood. Results reported to date indicate

that most biomass species are capable of interacting with a wide range of heavy metal ions.

Efforts have been made to impart specificity through chemical modification of the ligands of

biomass. Nevertheless, given the numerous species of biomass, it is not inconceivable that a

natural biomass may be found that can remove a specifically targeted metal ion from complex

mixtures. Consequently, biosorption may have potential use not only for the remediation of

metal-contaminated waste streams, but also for the recovery of metals for recycling. Although

biosorption processes have not yet been commercialized to any significant extent, they offer a

promising area for future developments.

Because most natural biomass is soft and fragile, the use of biomass on a large scale causes

troublesome solids handling problems. Commercial applications of biosorbents will most

likely be conducted using fixed bed columns that are widely used in conventional activated

carbon and ion exchange systems. Such applications require that the mechanical strength of

biomass be enhanced in order to avoid operational problems such as clogging or pressure

drop fluctuations. Indeed, three commercial biosorbents developed so far (Bio-FixTM , AMTBIOCLAIMTM, and AlgaSORBTM ) are produced in the form of porous beads, which can be

packed into fixed bed columns. A large body of knowledge exists in the adsorption literature

that is applicable to the design and analysis of biosorption processes based on spherical,

porous beads (4, 5). This chapter presents several process models that can facilitate the design

and analysis of biosorption systems. Mathematical models for predicting the performance

of batch and fixed bed biosorption processes are included. Because of mathematical and

numerical complexities associated with rigorous adsorption process models, which are usually

cast in the form of partial differential equations, this chapter places emphasis on models that

can be solved analytically or simplified to yield analytical approximations. Modern high-speed

computers coupled with the availability of user-friendly software packages for solving sets of



Modeling of Biosorption Processes



353



partial differential equations have greatly reduced the need for analytic solutions. Nonetheless,

from the perspective of preliminary process design, analytic expressions are more convenient

to use, computationally simpler, and could have immediate practical benefits. Moreover, more

rigorous mathematical models than those discussed here generally require inordinate effort to

generate substantial data for model validation and parameter estimation.



2. BATCH OPERATION

2.1. Batch Process Models

Batch biosorption processes are relatively simple to operate, requiring easily available

equipment such as vessels and stirrers. Batch operation is especially suited for treating low

concentration, high volume waste streams containing toxic metal contaminants. A typical

batch operation comprises a series of steps. First, a vessel containing a metal-laden solution

in contact with a biosorbent is agitated for a period of time to allow the wastewater to reach

the discharge limits. Second, the treated solution is withdrawn for discharge. Third, a small

amount of an eluant is added to the vessel which is agitated for a period of time to elute the

adsorbed metal. Fourth, the spent eluant containing the eluted metal is withdrawn. Fifth, a

wash step may be used to condition the biosorbent for reuse in the next cycle of treatment.

A typical design problem entails estimating the quantity of biosorbent needed to process a

given volume of a metal-contaminated waste solution. The design procedures are fairly simple

for well mixed batch systems, where equilibrium is achieved. However, biosorption may be

slow in cases where immobilized biomass beads are used owing to intrabead mass transfer

resistance. If sufficient time is allowed for equilibrium to be reached, the design of singlestage batch systems is based on mass balances and thermodynamic equilibrium relationships.

The mass balance is given by:

V (co − ce ) = Vm (qe − qo ),



(1)



where co and ce are the initial and final metal concentration in the bulk solution, qo and qe

are the initial and final metal concentration in the biosorbent, V is the amount of solution,

and Vm is the amount of biosorbent. qo is of course equal to zero when a biosorbent initially

free from the metal contaminant is used. When the properties of the waste solution to be

treated (co and V) and the discharge limit (ce ) are specified, it is still not possible to estimate

the amount of biosorbent required (Vm ) from Eq. (1) because qe is unknown. Equation

(1) must be solved in conjunction with the equilibrium isotherm, which relates qe to ce at

constant temperature. Unlike gas-phase isotherms, liquid-phase isotherms are generally a

weak function of temperature, but they are strongly affected by factors such as solution pH

and ionic strength. In general, the equilibrium isotherm for a given metal–biosorbent system

cannot be predicted from theory and experiments are imperative. In Sect. 2, we consider how

biosorption equilibrium data are generated and modeled.



2.2. Equilibrium Isotherms

An equilibrium isotherm defines the equilibrium distribution of a metal contaminant

between the solution and the biosorbent at a fixed temperature. Biosorption equilibrium data



354



K.H. Chu and Y.-T. Hung



can virtually never be predicted, but must be measured. Batch experiments are often used

to generate equilibrium data owing to their simplicity. When equilibrium is established in a

single-metal batch biosorption system, from the mass balance given in Eq. (1) we can write:

qe = qo +



V

(co − ce ).

Vm



(2)



It is generally difficult to measure qe directly. The standard approach is to measure ce ; qe can

then be calculated from Eq. (2) for batch experiments with known initial solution concentration (co ), amount of solution (V), amount of biosorbent (Vm ), and initial metal concentration

on the biosorbent (qo ). A series of batch experiments is conducted by varying either the initial

metal concentration or amount of biosorbent to generate pairs of qe vs. ce data. These experimentally generated qe vs. ce equilibrium data are used to construct the equilibrium isotherm

graphically. For biosorption systems containing a single metal contaminant, the equilibrium

isotherm is a function of environmental factors such as pH, ionic strength, and temperature.

Once these factors are fixed, the equilibrium isotherm is, in principle, independent of the

experimental conditions employed to measure it. In other words, a unique isotherm can be

generated by using any convenient measurement method (batch or continuous-flow) and by

varying either co or V / Vm.

Biosorption equilibria can be expressed in mathematical form by fitting the data on qe vs. ce

to isotherm equations that are commonly used in the gas adsorption literature (4). Because

most biosorption data on qe vs. ce over a wider range of solution concentration concave

toward the abscissa, they are described as “favorable.” A typical favorable isotherm is shown

in Fig. 11.1. Such favorable shape can be described in mathematical form by the well-known

Langmuir equation (6), which is given by:

qe =



qm bce

,

1 + bce



(3)



where qm is the maximum or saturation uptake capacity and b is an affinity constant. The two

adjustable parameters qm and b provide good flexibility in correlating the favorable isotherm

commonly observed in biosorption. It should be noted that metal biosorption isotherms



qe



Favorable

Rectangular



Linear



ce

Fig. 11.1. Shapes of favorable, linear, and rectangular isotherms.