Biosorption Process For Removal and
Recovery of Heavy and Precious Metals from
Aqueous Solutions: Past, Present and Future
Dr J. Paul Chen
Department of Chemical & Environmental Engineering
National University of Singapore, Singapore
Presented at International Symposium on Water Resources
Wuhan, China
November 9, 2003
Outline of Presentation
Motivation
Historical background
Current development
Application
Mechanisms
Future trends
Summary
Major Industries in Singapore
Major Industry Sectors (2001)
Engineering
18.3%
General
Industries
1.4%
Chemical Industry
Chemical Output Share (2001)
Biomedical
Sciences
9.2%
Specialty Chemicals
15%
Others
1%
Petrochemicals
23%
Petroleum
62%
Chemicals
20.8%
Electronics
50.3%
Total Manufacturing Output : S$ 135 billion
Chemical Cluster Output : S$ 28.9 billion
Jurong Island: Integrated Petrochemical Hub
• Originally 7 islands of total area of 900ha
Reclamation efforts: 2,650ha in 2001, to increase to 3,200ha in 2003
• 55 companies on site (e.g. DuPont, Chevron, Celanese, ExxonMobil, Eastman, Sumitomo)
• Target output from chemical industries: S$75 billion by 2010
Why do we care about metal contamination ?
 Human activities and natural processes inevitably would
produce metal wastes.
 Typical industries are






metal-plating and metal-finishing operations, e.g. semiconductor
mining and ore processing operations,
metal processing, battery and accumulator manufacturing operations,
thermal power generation (coal-fired plants in particular),
nuclear power generation,
Military practices, e.g. U
 Naturally occurring metal wastes include arsenic and arsenite.
Why do we care ... metal ? Cont’d
 EPAs have become more concerned the impacts.
 In the USA, important regulations are Cu-Pb and As rule (new
ruling of 10-ppb AS in drinking water in 2001)
 Searching cost-effective technologies becomes crucial.
 Technologies:
Precipitation,
adsorption,
ion exchange,
electro-coagulation,
electrochemical reduction,
membrane filtration
 However, the costs and efficiencies still remain as a major
concern.
Affinity of metal with organics
L-2-Aminopropanoic Acid (Alanine) with various metal
Metal Ions
Log K
Ca2+
1.30
Co2+
4.31
Ni2+
5.36
Cu2+
8.11
Zn2+
4.58
Cd2+
3.98
Pb2+
4.15
NH2
|
CH 3CHCOOH
M 2   L2   ML
{ML}
K
{M 2  }{L2  }
1. Immobilization of organics; 2. use of organics in natural biosolids
Historical background: 1980-1995
Biosorption by the materials derived directly and/or indirectly
by various organisms has long recognized
However, the applications of biosorption started to appear in
scientific literatures in early 1980s.
Credit - One of earlier researchers, B. Volesky of McGill
Univ., had contributed significantly by publishing a series of
papers, mainly on screening of biosorbents and measurement of
biosorptive capacities.
What is biosorption ?
• Biosorption is a property of certain types of
inactive/active organisms to bind and concentrate heavy
metals from even very dilute aqueous solutions.
• Biosorbents can be classified into:
a. Inactive organisms (mainly) include algae, fungi and bacteria
b. Their derivatives which are termed as biopolymers.
• Opposite to biosorption is metabolically driven active
bioaccumulation by living substances.
What are typical biosorbents ?
• Some of the biomass types come as a waste by-product of
large-scale industrial fermentations (the mold Rhizopus,
the bacterium Bacillus subtilis and waste activated
sludge).
• Other metal-binding biomass types, certain abundant
seaweeds (particularly brown algae e.g. Sargassum,
Ecklonia ), can be readily collected from the oceans.
• Biopolymers are normally extracted from inactive
organisms and processed before use (e.g. Ca-Alginate)
• These biosorbents can accumulate in excess of 25% of
their dry weight in deposited metals: Pb, Ag, Au, U, Cu.
Case presents
• Raw seaweeds – collected in Singapore
• Ca-alginate beads
• Ca-alginate based ion exchange resin
(CABIER)
Examples: Marine Algal collected in Singapore
Padina sp.
Sargassum sp.
Why biosorption ?
Cu sorption
Characterization of biosorbents by instrumental analysis
• Fourier transform infrared spectroscopic (FTIR) and X-ray
Photoelectron Spectroscopic (XPS) studies show that
biosorbents have significant amount of COO, OH, C=O,
and C-O.
• These organic functional groups would be responsible for
metal uptake onto the biosorbents due to the high affinity
for metal ions.
• SEM shows less pore development in bisorbents
Biosorption Equilibrium
Metal biosorptive properties: pH effect
SOH + Mm+ = SO-Mm+ + H+
20
100
Cr3+
12
Metal removal, %
q, mg/g
16
CrO4-
8
4
80
60
40
Cu
Pb
20
[Pb]o=[Cu]o=1x10-4 M
[CABIER]=0.15 g/L
0
0
0
1
2
3
4
5
6
7
8
1
2
3
4
5
pH
Final pH
Sargassum
Ca-alginate
6
7
Metal biosorptive properties: pH effect
Effect of Ionic Strength on Copper Removal
TCu=5x10-5 M, 2mL of 1.5 % alginate
Metal biosorptive properties: ionic strength effect
100
Copper Removal,%
80
60
40
I=0.005 M
I=0.050 M
I=0.500 M
20
0
1
2
3
4
pH
5
6
Algae as the biosorbents
Biomass
Ascophyllum spp.
Chlorella sp.
Cladophora sp.
Cyclotella sp.
Cymodocea spp.
Fucus sp.
Gracilaria sp.
Metal ions
qmax (mmol/g)
Ni, Pb, Cd, Cu 1.03-1.43
Cd
0.99
Pb
0.35
Cu
0.41
Cu, Zn
0.71-0.83
Pb
1.6
Pb
0.2-0.26
Padina spp.
Pb, Cu
0.31-1.05
Phaeodactylum sp.
Polysiphonia sp.
Porphyridium sp.
Cu
Pb
Cu
1.67mg/g
0.49
0.27mg/g
Sargassum spp.
Pb, Cu, Cd, Ni 0.71-1.99
Scenedesmus spp.
Schizomeris spp.
Spirulina sp.
Ulva sp.
Cu, Cd
Pb, Cd
Cd
Pb
0.06-0.21
0.31-0.44
0.87
0.61
References
Volesky etal., 2000
Aksu, 2001
Jalali etal., 2002
Schmitt etal., 2001
Sanchez etal., 1999
Volesky, 1994
Jalali etal., 2002
Volesky, 1994; Jalali
etal., 2002; Kaewsarn, 2002
Schmitt etal., 2001
Jalali etal., 2002
Schmitt etal., 2001
Volesky etal., 1994,2000;
Jalali etal., 2002
Schmitt etal., 2001
Ozer etal., 1999
Rangsayatorn etal., 2002
Jalali etal., 2002
Mechanisms of metal biosorption
 Instrumental investigations through XPS, FTIR,
titration and equilibrium experiments reveal that
the biosorption is a complex chemical
phenomenon.
 Depended on the types of bisorbents applied, the
metal uptake may be due to:
 metal surface complex formation (MSCF)
 ion exchange, and
 elementary coordination
XPS spectra of Pb- and Cu-adsorbed CABIER
1400
1200
600
Pb 4f7/2 137
Cu 2p3/2
550
1000
Intensity
Intensity
500
800
600
400
450
935.0
400
200
350
0
300
130
135
140
145
150
155
932.8
250
Binding Energy (eV)
920
930
940
950
Binding energy (eV)
-O-M-O-
960
XPS Analysis
577.5
574
578
582
574
579.5
578
582
Binding Energy (eV)
Binding Energy (eV)
Raw Padina
577.1
577.2
574
Cr(VI): pH 1
578.5
579.2
578
582
574
578
Binding Energy (eV)
Binding Energy (eV)
Cr(VI): pH 2
Cr(III): pH 4
582
• Note that BE
values of 577.2
and 579
represent Cr (III)
and Cr (VI)
• Uptake 
reduction and
MSCF
biosorption of Metal Ions:
Surface Complex Formation Model
Surface Plane
Inner Helmholtz Plane
Outer Helmholtz Plane
_
+
+
+ _
+
+ _
+
_
+
_
+
_
+ _
+
+
+
+
+
_
_
+
_
_
_
+
+
_
+
_
+
_
_
+
_
+
+
+
+
+
+
o d

Potential

d
0  d
Distance
+
biosorption results from
reactions between
functional groups of
adsorbents and metal ion
species.
Two-pK Triple-Layer Model - MSCF
KH1
SOH + H  exp(  y o )  
+
SOH 2
KH 2

SOH - H  exp(  y o )  SO 
KX
SOH + X  H  exp( yo )  exp( y  )  SOH2 X -
+
+
KNa
SOH + Na - H  exp( y  )  exp(  y  )  SO - Na +
+
SOH  M
SOH  M
SOH  Cu
2
2
+
2
KCu

 2 exp( y  )  H  exp( y0 )  SO M 2
KCuOH
 exp( y  )  2H  exp( y0 )  SO MOH 



KCuCl
 Cl  exp( y  )  2H  exp( y0 )  SO CuCl 
M=Cu, or Zn, or Co, X=Cl, or NO3, or ClO4
yo=eo / kT and y=e / kT referred to o-layer and -layer
MSCF for Cu biosorption by Ca-alginate beads
C opper R em oval, %
100
80
60
40
20
0
1
2
3
4
5
6
7
pH
Chen, J.P., et al., Environmental Science and Technology, Vol.
31, No. 5, pp. 1433-1439, 1997.
Conceptual model for the metal
removal by ion exchange.
+ Ca2+
M = Cu and Pb
Ion exchange in biosorption (e.g. by CABIER)
1. M2+ + Ca-R  M-R + Ca2+ (ion exchange)
2. M2+ + R2-  M-R (R: unreacted group)
(elementary coordination)
3. 2H+ + Ca-R  H2-R + Ca2+ (pH effect) and
4. solution and precipitation reactions……..
Chen, J.P. et al., Langmuir, Vol. 18, No. 24, pp. 9413-9421, 2002.
Prediction of pH Effect on Metal Removal by CABIER
100
Removal, %
80
60
40
20
Cu
Pb
0
1
2
3
4
5
6
7
pH
[Pb]o= 1.010-4 M, m=1 g/L, [Cu]o=1.010-4 M, m=0.15 g/L.  modeling
[Pb]o = 1.63x10-4 M
[Cu]o = 1.81x10-4 M
modeling
16
12
8
4
100
4
80
3
60
2
40
1
20
0
0
0.0
0.2
0.4
0.6
0.8
Resin applied, g/L
1.0
0
20
40
60
80
100
Initial copper concentration X 105, M
0
120
Residual lead concentration X 105, M
Residual Metal Conc. x105, M
20
Residual copper concentration X 105, M
Prediction of Competitive Biosorption by CABIER
Generalized approach for the simulations- MINEQL
Solution Reactions:
xi 
Kix
Na x
a
ck ik
k 1

,
i  1,2,..., M x
Adsorption Reactions:
yi 
N
y
y  a aik
K i  ck
k 1

 N s b y  a y aiy
 sk ik coio c ,
k 1

EDL
Precipitation Reactions:
1
K ip
i  1,2,..., M y
Na
p
aik
ck
k 1

,
i  1,2,..., M p
Solution and Precipitation Reactions in the Modeling
Cu 2  nOH  Cu(OH)2n n
Cu 2  nCl  CuCl 2n n
Cu 2  2OH  Cu(OH)2 (s)
Cu 2  2OH  CuO(s)  H 2 O
Pb2  nOH  Pb(OH)2nn
Pb2  nCl  PbCl2n n
Pb2  2OH  Pb(OH)2 (s)
Pb2  2OH  PbO(s)  H2O
2Pb2  4OH  Pb2O(OH)2 (s)  H2O
……………
Chen, J.P. and Lin, M.S. Water Research, Vol. 35, No. 10, pp. 2385-2394, 2001.
How about modeling for metal reduction ?
• NO solution yet !!!
• It is on-going; but we may have hard time !!!
Bisorption Kinetics
Biosorption kinetics: four types of seaweeds
vs. “novel” CABIER
0.8
100
0.6
80
q (mg/g)
q (mmol/g)
1.0
0.4
copper
0.2
0.0
60
[Pb2+]o = 20 ppm
40
Padina
Sargassum
Ulva
Gracillaria
pH=5.0
m=1.0g/L, C0=1.0mmol/L
[Pb2+]o = 36.8 ppm
20
[Ca2+]o = 0, [Na+]o = 0
0
0
100
200
300
time (min)
seaweeds
400
500
0
30
60
90
120
Time (min)
CABIER
150
180
Sorption Kinetics of Metal Ions:
Diffusion-Controlled Model
Concentration
Sorption rate results from
either mass transfer of ion
species to the surface of
sorbents or complexation
reactions between functional
groups of sorbents and ion
species.
m
Porous
Adsorbent
rp, ep
Bulk Liquid
Cj
kf j
Liquid Film
Dp j
Model Parameters
c j(r=ap)

cj
cj

qj
qj
ap
r, distance measured from
adsorbent particle center

Rate-controlling mechanism
(i.e., transport-controlled or
reaction-controlled cases)
Rate parameters (i.e., diffusion
and mass transfer coefficients or
rate constants)
Characterization of sorbents
An Intraparticle Diffusion Model
for Metal Uptake Kinetics
  2q
2 q 
q


De 


2

r r 
t
 r
q
De
 ρ p  k f (C  C*)
r
q
 0
r
kinetics of metal biosorption
[Pb2+]o = 36.8 ppm
100
q (mg/g)
80
60
[Pb2+]o = 20 ppm
40
20
[Ca2+]o = 0, [Na+]o = 0
0
0
30
60
90
120
150
180
Time (min)
2
pH = 4-5, m = 0.4 g/L, De = 2.95×10-11 m /s, kf = 2.41×10-4 m/s
Engineering applications
Continuously operated system for metal
treatment – an engineered approach
us
mp
z
Fixed-bed ?
cin
L
V
Batch/CSTR ?
Kinetics: external mass transfer and
internal diffusion
Fluidized-bed ?
Equilibrium: capacity as function of
chemistry and adsorbents
Mixing: dispersion and advection
20
17
18
16
16
15
Bed Height,cm
Efflunet concentration, ppm
Continuously operated fluidized-bed
14
12
10
8
6
14
13
12
11
4
10
2
9
0
0
10
20
30
Time, hr
40
50
8
0
10
20
Time, hr
30
40
Major obstacles and challenges
•
•
•
•
•
Reluctance to use by industries
Organic leaching
Waste biosorbent disposoal
Physical properties
Optimization of specific biosorption process
Prevention of TOC leaching-most
recently development
• Organic leaching has been extremely if raw
seaweeds are used.
• formaldehyde has been used for surface
modification and the resulting TOC
significantly reduces to below 5 ppm
• The biosorptive capacity increases and pH
becomes more stable.
Summary
• Biosorption of metals becomes more attractive due
to high removal capacity, high kinetics, low cost
and possibility to recover metals.
• Biosorption is highly depended on pH.
• Various mechanisms lead to the metal uptake.
• Kinetics is mainly controlled by diffusion.
• Various reactor configurations can be used.
• Challenges still remain in the way leading to fullscale industrial application.
acknowledgement
 Professor Sotira Yiacoumi of Georgia Tech
 Professor L. Hong of NUS for XPS and FTIR
 Post-graduate students in NUS:
 Dr S.N. Wu
 Ms J. Peng
 Ms L. Wang
 Mr P.X. Sheng
 Mr L. Yang
 Ms. LH Tan