ph. D_____REMOVAL OF ACRYLONITRILE AND ACRYLIC ACID FROM AQUEOUS SOLUTION USING ADSORPTION.ppt

REMOVAL OF ACRYLONITRILE AND ACRYLIC ACID FROM AQUEOUS SOLUTION USING ADSORPTION

1. IIT, Roorkee 1
REMOVAL OF ACRYLONITRILE AND ACRYLIC ACID FROM
AQUEOUS SOLUTION USING ADSORPTION
By
Arvind Kumar
Supervisor
Dr. B. Prasad
DEPARTMENT OF CHEMICAL ENGINEERING
INDIAN INSTITUTE OF TECHNOLOGY, ROORKEE
ROORKEE – 247667

2. IIT, Roorkee 2
INTRODUCTION
•The release of the industrial effluents containing toxic/hazardous
organics into the receiving water bodies is a matter of great
environmental concern.
•Toxic compound like acrylonitrile (AN) & acrylic acid (AA) frequently
encountered together in waste waters (petrochemical industry)
•Monitoring and subsequent removal of toxic compound like AN & AA
from the industrial effluents is important before their safe disposal.

3. IIT, Roorkee 3
Guide lines for CN and/or AA discharged
into water receiving bodies
•US health services
•US EPA
•German and Swis regulation
•CPCB New Delhi
•US EPA
•0.01 mg/l as guide lines and 0.2 mg/l as
the permissible limit
•0.2 mg/l [Rouse et al. 1990]
•0.01 mg/l for surface water and 0.05 for
sewers [Desai and Ramakrishna, 1998]
•0.2 mg/l
•100 mg/l of AA in effluent [IPCS report]

4. IIT, Roorkee 4
Discharge standards for liquid effluents from
petrochemical plants in India [CPCB, 2001]
Parameter Concentration not to exceed, (mg/l) (except pH)
pH 6.5 - 8.5
BOD (3 days at 27°C) 50
Phenol 5
Sulphide as S 2
COD 250
Cyanide as CN 0.2
Fluoride as F 15
Total suspended solids 100
Chromium
Hexavalent 0.1
Total 2.0

5. IIT, Roorkee 5
TOXICITY AND TOXIC MATERIALS
Toxicity is the ability of a chemical molecule or compound to produce
injury once it reaches a susceptible site in or on the body of living
creatures.The toxic material is a chemical material or compound which
causes toxicity.
There are several species and organic compounds which are toxic in
nature. This presentation deal with the toxicity of AN and AA and their
adsorptive removal.

6. IIT, Roorkee 6
AN and AA can be manufactured through several routes [Mall, 2007].
AN, an EPA priority pollutant, is among the top 50 most widely used
industrial compounds in the USA [Keith and Telliard, 1979; Reisch,
1993]. AN and AA are soluble in water and very toxic in nature
[Bretherick, 1981; HSDB, 1993; RTECS, 1993; US EPA, 1983; 1984;
1994, 1999; NOISH, 1997; Sittig, 1985; IRIS, 1994; 1999; IARC,
1999; Howard, 1989]. AN and AA are emitted from industrial plants in
the form of vapors and in aqueous effluents; exposure of the population
living near plants to these chemicals, therefore, is expected.
Contamination of food and water is also possible
TOXICITY REPORTED

7. IIT, Roorkee 7
Characteristics of Acrylonitrile and Acrylic Acid
[Cheremisinoff, 1999]
Characteristics Acrylonitrile (AN) Acrylic Acid (AA)
CHEMICAL DESIGNATION
Synonyms Cyanoethylene, Fumigrain,
Ventox, Vinyl Cyanide
Propenoic Acid
Chemical Formula CH
2=CHCN CH
2=CHCOOH
OBSERVABLE CHARACTERISTICS
Physical State Liquid Liquid
Color Colorless Colorless
Odor Mild Pungent, resembling that of
peach seed kernels
Acrid

8. IIT, Roorkee 8
Characteristics of Acrylonitrile and Acrylic Acid [Cheremisinoff, 1999] (Contd.)
PHYSICAL AND CHEMICAL PROPERTIES
Physical State at 15
o
C and 1 atm. Liquid Liquid
Molecular Weight (kg/kmol) 53.06 72.06
Boiling Point at 1 atm (
o
C) 77.4 141.3
Freezing Point(
o
C) -83.6 12.3
Critical Temperature(
o
C) 263 342
Critical Pressure (atm) 45 57
Specific Gravity 0.8074 1.0497 at 20
o
C (Liquid)
Latent Heat of Vaporization
(kJ/kg)
147 151.15
Heat of Combustion (kJ/kg) -7930 -4500
Heat of Decomposition (kJ/kg)Not pertinent Not pertinent
HEALTH HAZARD INFORMATION
Inhalation Weakness, Headache,
Sneezing, abdominal pain
and vomiting
Eye and nasal irritation and
lacrimation
Ingestion May cause severe damage to
the gastrointestinal tract
May cause severe damage to the
gastrointestinal tract

9. IIT, Roorkee 9
Characteristics of Acrylonitrile and Acrylic Acid [Cheremisinoff, 1999] (Contd.)
TREATMENT FOR EXPOSURE
Inhalation Remove victim to fresh air Remove victim to fresh air
Ingestion Induce vomiting by strong
solution of salt water
Do not induce vomiting
Skin and Eye Remove contaminated clothing
and wash affected area, wash
with fresh water
Flush with water for at least 15 min
Toxicity by Inhalation (Threshold
limit value) (TLV, mg/l)
20 Data not available
Short term exposure limit (STEL,
mg/l)
40 mg/l for 30 min Data not available
Toxicity by Ingestion (mg/kg
(rat))
50 – 500 0.5 – 5
Late Toxicity Data not available Not pertinent
Vapor Irritant CharacteristicsModerately irritating such that a
person will not usually tolerate
moderate or high vapor
concentrations
Vapor is moderately irritating such
that person will not usually tolerate
moderate or high vapor
concentrations
Liquid or Solid Irritant
Characteristics
If spilled on clothing and allowed
to remain may cause smarting
and reddening of the skin
Fairly severe skin irritant, may cause
pain second-degree burns after a few
min contact
Odor Threshold (mg/l) 21.4 Data not available

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Hazard ranking of acrylonitrile and acrylic acid. Source: Scorecard, Pollution information
site http://www.scorecard.org/chemical- profiles/hazard-indicators (accessed May 2007)
Hazard Rankings Acrylonitrile (AN) Acrylic Acid (AA)




Human Health Rankings
Toxicity only
Ingestion Toxicity Weight
Inhalation Toxicity Weight
Human Health Effects Score
Toxicity and exposure potential
Cancer Risk Score – Air Releases
Cancer Risk Score – Water Releases
Noncancer Risk Score – Air Releases
Noncancer Risk Score – Water Releases
Worker Exposure Hazard Score

Ecological Health Rankings
Toxicity only
Ecological Effects Score
Toxicity and persistence
Environmental Hazard Value Score


Integrated Environmental Rankings
Combined human and ecological scores
Total Hazard Value Score
Total Hazard Value Score

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Characteristic of a typical petrochemical industrial wastewater
from ACN plant
Characteristic Value
TDS (mg/l) 2,65,500
Conductivity (

S/m) 4,08,500
pH 8.2
Turbidity (NTU) 850
CODavg (mg/l) 3,55,000
Alkalanity (mg/l) 30,000
Sodium (mg/l) 9,600
Nitrate (mg/l) 8,675
Sulphate (mg/l) 1,30,000
BODavg (3 days) (mg/l) 30, 000
Acrylonitrile (g/l) 1.5-2
Acrylic acid (g/l) 10-20
Acetonitrile (mg/l) 150-200
Adiponitrile (mg/l) 50-75
Benzonitrile (mg/l) 25-40
CN
-
(mg/l) 50
Total CN (mg/l) 1.2-1.500
Cd (mg/l) 14
Ni (mg/l) 56.4
Mn (mg/l) 9.7
Fe (mg/l) 89

12. IIT, Roorkee 12
Treatment methods for the removal of acrylonitrile and acrylic acid
from water and wastewater.
Adsorbate Treatment
method
Adsorbent References
Acrylonitrile Adsorption Cu and Cu-Pd CatalystsVozdvizhenskii et al. (1983)
Petrochemical waste Adsorption Activated carbon Ramakrishna et al. (1989)
Polyacrylonitrile Adsorption Silica gel, alumina and
calcium carbonate
Joseph et al. (1994)
Acrylonitrile Adsorption Activated carbon Wang et al. (2006)
Acrylonitrile and Polyacrylic
acid
Adsorption Zinc oxide Kislenko and Verlinskaya (2002)
Acrylonitrile ChemisorbedFe, Ni and Cu
polycrystalline surfaces
Cripsin et al. (2001)
Acrylonitrile vapour Tricle-bed air
biofilter
Lu et al. (2000)
Acrylonitrile Microbial Arthrobacter sp. IPCB-3Ramakrishna and Desai et al. (1993)
Acrylonitrile Microbial Comamonas testosteroni
and Acidovorax sp.
Wang et al. (2004)
Acrylic acid Adsorption Mercury surface Plavsic and Cosovic (1994)
Acrylic acid Adsorption Aluminium Bournel et al. (1996)
Acrylic acid Adsorption-
desorption
Clay Minerals Blockhaus et al. (1997)
Acrylic acid Adsorption Alumina Mao and Fung (1997)
Poly(acrylic acid) Adsorption Titanium dioxide Esumi et al. (1998)
Acrylic acid Wet oxidationManganese-based oxidesSilva et al. (2003)
Acrylic acid Microbial Bacillus thuringiensisWang and Lee (2006)
Petrochemical waste Microbial Pseudomonas putida Desai and Ramakrishna et al. (1998)

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Levels of residual acrylonitrile found in various products
Product Acrylonitrile content
Acrylic and modacrylic fibres 1 mg/kg
Acrylonitrile-butadiene-styrene resins30-50 mg/kg
Styrene-acrylonitrile resins 15 mg/kg
Nitrile rubber and latex material0-750 mg/kg
Acrylamide 25-50 mg/kg
Polyether polymer polyols 100-300 mg/kg
Shelled walnuts 0-8.5 mg/kg
US cigarettes (non-filtered) 1-2 mg/100 cigarettes

14. IIT, Roorkee 14
•low-cost adsorbents with good surface area, exhibiting
good adsorption potential for the removal of toxic
compounds from wastewater is an important area.
•Bagasse fly ash (BFA) is a waste material formed during
the combustion of bagasse, as a fuel in the boilers of the
sugar mills.
•Bagasse Fly ash has been used by many researchers as an
adsorbent for the removal of various metals and other
chemical from the wastewaters.
BAGASSE FLY ASH (BFA) AS ADSORBENTS

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Physico-chemical characteristics of adsorbents
Characteristic PAC GAC BFA
Proximate analysis (sample as received)
Moisture (%) 5.65 7.70 3.39
Ash (%) 8.74 9.73 72.60
Volatile matter (%) 4.46 6.49 4.81
Fixed carbon (%) 81.12 76.08 19.20
Bulk density (kg/m
3
) 562 725 185.51
Carbon pH 5.33 10.38 -
Heating value (MJ/kg) 4.59 6.88 19.23
Average particle size 250 mesh 3-5 mm 167.35 mm
Ultimate analysis (dry basis)(%)
C 80.25 77.16 16.36
H 1.658 5.105 9.77
N 0.158 0.025 2.55
S 0.052 0.741 -
Chemical analysis of ash (%)
Insoluble Matter 3.5 2.90 78.35
Silica 1.5 2.50 2.46
Ferric & Alumina 3.8 3.90 2.92
CaO 84.0 84.0 14.00
Mg 2.0 2.90 1.09

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Physico-chemical characteristics of adsorbents (Contd.)
Surface area (m
2
/g)
BET 798.49 870.57 379.64
Langmuir 1007.37 1015.43 445.59
t-plot micropore 804.26 965.29 421.20
t-plot external 203.12 50.14 24.38
Single point 790.06 863.19 376.22
BJH adsorption cumulative 192.63
a
76.16
a
29.83
b
Pore Volume (cm
3
/g)
Single point total pore volume 0.76 0.53 0.298
t- plot micropore volume 0.25 0.33 0.145
BJH adsorption cumulative 0.30
a
0.07
a
0.032
Pore size (Å)
BET Adsorption average pore width 38.25 24.67 31.45
BJH adsorption average pore diameter63.39 42.00 49.30
a
pores between 17 Å and 2000 Å ;
b
pores between 17 Å and 3000 Å

17. IIT, Roorkee 17
The adsorption properties of BFA are highly influenced with the firing
practices of bagasse. Several investigators have recently shown interest in
the use of bagasse fly ash as an adsorbent. It has been used for the COD
removal from sugar mill (Mall et al., 1994), and paper mill effluents
(Srivastava et al., 2005). BFA has also been used for the adsorptive removal
of phenolic compounds (Mall et al., 2003; Srivastava et al., 2006a), dyes
(Mall et al., 2005a, b; 2006), and pyridine and 2-picoline (Lataye et al.,
2006, 2007) from wastewaters.
USE OF BAGASSE FLY ASH AS AN ADSORBENT

18. IIT, Roorkee 18
BOX-BEHNKEN DESIGN OF EXPERIMENTAL
METHODOLOGY
Box-Behnken design of experimental methodology has been used
extensively in carrying out experiments and devising a strategy for
quality control in the manufacturing industries. Box-Behnken
method to improve quality of the products depends heavily on
designing and testing a system based on engineer's judgment of
selected materials, parts and nominal product/process parameters
based on current technology. It has been expensively used in various
physico-chemical processes (Jyotsna et al. 2005; Andeson et al. 2005
and Ravi kumar et al. 2005) in the recent decade.

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To characterize the agri-based like bagasse fly ash (BFA) and
commercial grade activated carbon (PAC & GAC) for their physico-
chemical and adsorption properties. These characteristics include the
analysis of particle size and pore size distribution, proximate and
ultimate analysis, and the surface and functional characteristics by
FTIR, XRD and SEM analyses.
To utilize BFA, and Activated carbons as adsorbents for the
treatment of AN & AA bearing synthetic wastewater and to compare
their performance with that of available activated carbons.
To study the effect of various parameters like initial pH (pH
0),
adsorbent dose (m), contact time (t), initial concentration (C
0
), and
temperature (T) on the removal of AN & AA from the aqueous
solution in batch study.
OBJECTIVES OF THE STUDY

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To perform the equilibrium adsorption and the kinetics study of
adsorption of AN &AA onto adsorbents and to analyze the
experimental data using various kinetic and isotherm models.
To understand the thermodynamics of adsorption for AN & AA
onto, PAC, GAC and BFA
To utilize Box-Behnken design of experimental methodology
approach for estimating the effects of various parameters and their
identification of their interactive effects in single component
adsorption system in the batch adsorption study.
To perform desorption study for the possible regeneration of
adsorbents and develop a method for disposing the spent
adsorbents.
OBJECTIVES OF THE STUDY (Contd.)

21. IIT, Roorkee 21
Vozdvizhenskii et al. (1983) found that the AN adsorption over Cu and Cu-Pd
catalysts decreases the CN-bond order. The addition of palladium enhances AN
adsorption and promotes the stabilization of copper in the zero-valent state.
Strongly bound forms of adsorbed water molecules were not likely to be involved in
AN hydration.
Wyatt and Knowles (1995) isolated a range of bacteria that can grow on, or convert
all of the organic components of effluent from the manufacture of AN. These
bacteria can be used as the basis of a mixed culture system to treat the effluent.
Bournel et al. (1996) studied the interface between AA (CH
2 = CH-COOH) and
polycrystalline aluminum at 300 K by different spectroscopies to determine the
adsorption mechanism. X-ray photoemission spectroscopy (XPS) probed the
occupied states (core levels) of the system; near edge X-ray absorption fine structure
(NEXAFS) where the synchrotron beam specified the unoccupied ones and
reflection absorption infrared spectroscopy (RAIRS) measured the vibration modes
between acrylic acid and polycrystalline interface.
REVIEW OF LITERATURE

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The adsorption of AA and maleic acid on alumina was studied by Mao and Fung
(1997). The adsorption of the acids was found to be dependent on the of the solutions.
The optimal for acrylic acid and maleic acids were respectively, 4.5 and 1.1–1.6.
Lu et al. (2000) investigated the system performance of a trickle-bed air bio-filter
(TBAB) for treating AN vapor from waste gases under different gas flow rates and
influent AN concentrations. In steady-state conditions, the AN elimination capacity
increased but the AN removal efficiency decreased with the increase of influent AN
load. More than 95% AN removals were achieved for AN loads below 490 g AN m
3
/h.
Crispin et al. (2001) found through X-ray and UV photoelectron spectroscopy that AN
was chemisorbed on iron, nickel and copper polycrystalline surfaces via the carbon
and nitrogen atoms. Depending on the conditions used, different adsorption
geometries were found.
Bournel et al. (2002) performed comparative study of the adsorption modes of
acetonitrile and of the conjugated molecule AN on Si (0 0 1)-2X1 at room temperature,
using synchrotron radiation photoemission spectroscopy (PES) and near edge X-ray
absorption fine structure (NEXAFS) spectroscopy. Both molecules chemisorb on the
surface.

23. IIT, Roorkee 23
Wang et al. (2004) studied the ability of two bacterial strains isolated from an
acrylonitrile-butadiene-styrene (ABS) resin manufacturing wastewater treatment
system to remove high AN concentrations.
Wang and Lee (2006) isolated twenty strains of the AA utilizing bacteria from the
ABS resin factory wastewater treatment system. The results showed that twelve of
them could utilize 600 mg/l AA for growth. Seven of twelve strains could tolerate the
AN and acrylamide toxicity, when the concentration was below 300 mg/l. Bacillus
thuringiensis was one of the seven strains and the optimum growth temperature was
32
o
C.
Wang et al. (2006) investigated the adsorption equilibrium and dynamics of AN
acrylonitrile (ACN), methyl acrylate (MA) and the ACN-MA mixture on activated
carbon (AC) in a packed bed column at 40
o
C. The study indicated that the
adsorption isotherms of the pure components belong to the classical Langmuir type;
in the case of the binary mixture adsorption.

24. IIT, Roorkee 24
Studies on removal of various adsorbate by PAC
Adsorbates AdsorbentsOperating mode References
Acrylic acid PAC Batch Kumar et al. Doi:
10.1002/ceat.200700084
Taste and Odor compounds PAC Batch Kim and Bae
Doi: 10.1016/j.watres.2007.02.005
Odorant 2-methylisoborneol (MIB),PAC Batch Tennant et al. (2007)
Nonpolar organics PAC Batch Pakula et al. (2007)
Surfactant sodium
dodecylbenzenesulphonate
PAC Batch Rivera-Utrilla et al. (2006)
Atrazine PAC Batch Jia et al. (2006)
Organic matters PAC Batch Kim et al. (2005)
dark coloured compounds from
peach pulp
PAC Batch Arslanoglu et al. (2005)
Atrazine PAC Batch Jia et al. (2005)
Dyestuff PAC Batch Kargi et al. (2005)
Phenol and p-methylphenol PAC Sequencing batch
reactor (SBR)
Lee and Lim (2005)

25. IIT, Roorkee 25
Studies on removal of various adsorbate by GAC
Phenol and
4-Nitrophenol
GAC Batch Kumar et al.
Doi:10.1016/j.jhazmat.2006.12.062
Heavy metals (Pb
2+
, Ni
2+
) GAC Sequencing Batch
Reactor
Sirianuntapiboon and Ungkaprasatcha
(2007)
Dye compounds, direct fast light
turquoise
blue GL, direct scarlet 4BE, and
pink red
GAC Batch Wang et al. (2007)
Cr(VI) GAC Open batch systemQuintelas et al.
Doi:10.1016/j.cej.2007.03.082
Polycyclic aromatic hydrocarbonsGAC Batch Valderrama et al.
Doi:10.1016/j.jcis.2007.01.039
Cr (VI) GAC continuous flow
system
Lameiras et al.
Doi:10.1016/j.biortech.2007.01.040
Trinitrotoluene GAC fixed-bed adsorptionLee et al. (2007)
Ethyl-2,4-decadienoate GAC Fixed-bed columnsDiban et al. (2007)
Phenolic compounds GAC Batch Hamdaouia and Naffrechoux
Doi:10.1016/j.jhazmat.2007.01.023
TiO2 GAC Fixed bed adsorptionAreerachakul et al. (2007)
Fluorobenzene GAC Batch Carvalho et al.
Doi:10.1016/j.biortech.2006.11.001
Imidaclopride GAC Batch Daneshvar et al.
Doi:10.1016/j.jhazmat.2006.09.081

26. IIT, Roorkee 26
Studies on removal of various adsorbate by BFA
Cadmium, nickel and zinc BFA Batch Srivastava et al.
Doi:10.1016/j.cej.2007.01.007
Methyl parathion pesticide BFA, rice,
bran, rice
husk
Batch Akhtar et al. (2007)
Phenol BFA Batch adsorption Srivastava et al. (2006)
cadmium and nickel BFA Batch adsorptionSrivastava et al. (2006)
Orange-G (OG), and Methyl Violet
(MV)
BFA Batch Mall et al. (2006)
Auramine-O BFA Batch Mall et al.
Doi:10.1016/j.jhazmat.2006.09.059
Malachite green dye BFA Batch adsorptionMall et al. (2005)
Congo red BFA Batch Mall et al. (2005)
Ni
2+
, Cr
4+
BFA Batch Rao et al. (2002)

27. IIT, Roorkee 27
Application of response surface methodology (RSM) and
Box-Behnken statistical design in adsorption
Ricou-hoeffer et al. (2001) used DOE to define operating conditions which conciliate
a high removal of the five metallic cations (Cu
2+
, Ni
2+
, Zn
2+
, Cd
2+
, Pb
2+
) and a low
desorption of these metal ions from the contaminated sorbents.
Bacaoui et al. (2001) used Doehlert matrix to optimize the experimental conditions
of the preparation of AC from olive-waste cakes. A series of ACs were prepared by
physical activation with steam. Adsorption of N (77 K), CO (273 K) and mercury
porosimetry experiments were carried out to determine the characteristics of all
carbons prepared. Adsorption of iodine and methylene blue was used as a primary
indicator of the adsorption capacity of these carbons.
Echeverrı et al. (2003) studied the simultaneous effect of , initial concentration, ionic
strength, and temperature on the retention of Ni on illite by RSM. Adsorption
isotherms at 15, 25 and 35
o
C ( = 7.5) were performed to deduce thermodynamic
parameters.
Ferreira et al. (2004) described a method for preconcentration and determination of
trace amounts of cadmium in high saline samples. It was based on the adsorption of
the metal in the AC as complex Cd(II)-4-(2-pyridylazo-resorcinol) (PAR). The final
determination was carried by flame atomic absorption spectrometry. The
optimization of extraction parameters such as the effect, PAR mass, AC mass and
shaking time was carried out using a two-level full factorial design (24) and two
Doehlert matrix designs.

28. IIT, Roorkee 28
Rio et al. (2005) optimized experimental conditions of sorbent preparation from
sewage sludge using DOE. Series of carbonaceous sorbents were prepared by
chemical activation with sulfuric acid.
Ravikumar et al. (2005) investigated adsorption of Neolan Blue 2G (Acid Blue 158)
and Basic Methylene Blue (Basic Blue 9) using a hybrid adsorbent that was
prepared by pyrolysing a mixture of carbon and fly ash at 1:1 ratio. A 24 full
factorial central composite design with nine replicates at the center point, and thus,
a total of 31 experiments were successfully employed for batch experimental design
and analysis of the results.
Zulkali et al. (2006) investigated the effects of initial concentration of lead,
temperature, biomass loading and for an optimized condition of lead uptake from
the aqueous solution. The optimization process was analyzed using Central
Composite Face-Centered Experimental Design in RSM. The design was employed
to derive a statistical model for the effect of parameters studied on the removal of
lead ion from aqueous solution.
Brasil et al. (2006) carried out three statistical design of experiments in order to
reduce the total number of experiments for achieving the best conditions for Cr
6+

uptake using Araucaria angustifolia (named pinhao) wastes as a biosorbent. A full
24 factorial design with two blocks and two central points (20 experiments) was
experimented (, initial metallic ion concentration-Co, biosorbent concentration-X
and time of contact-t), showing that all the factors were significant; besides, several
interactions among the factors were also significant.

29. IIT, Roorkee 29
Sher et al. (2007) used RSM, using 32 factorial design to study drug adsorption and
its release patterns from microporous polypropylene in the absence of additives.
Ibuprofen, as model drug, was adsorbed on the polymer by solvent evaporation
using two organic solvents methanol (M) and dichloromethane (DCM).
Ravikumar et al. (2007) studied decolourization of Verofix Red (Reactive Red 3GL)
and Lanasyam Brown Grl (Acid Brown 29) from aqueous solution by adsorption
technique using a hybrid adsorbent that was prepared by pyrolysing a mixture of
carbon and fly ash in 1:1 ratio. A 24 full factorial central composite design was
successfully employed for experimental design and analysis of the results.
Garg et al. (2007) investigated the effect of adsorbent dose, pH and agitation speed
on nickel removal from aqueous medium using an agri-waste biomass, i e.
sugarcane bagasse. Batch mode experiments were carried out to assess the
adsorption equilibrium. The influence of three parameters, namely, the adsorbent
dose, pH and stirring speed on the removal of nickel was also examined using RSM.
The central composite face-centered experimental design in RSM was used for
designing the experiments as well as for full response surface estimation.
Kiran et al. (2007) investigated the potential use of alginate immobilized algal beads
for the removal of chromium from aqueous solution under optimized conditions
using a novel cyanobacterium, Lyngbya puteal was isolated from metal
contaminated soil. Batch experiments were performed to determine the adsorption
equilibrium and kinetics.

30. IIT, Roorkee 30
ADSORPTION FUNDAMENTALS
Adsorption is defined as the separation/accumulation of a solute,
which may be molecules in a gas stream or a dissolved or suspended
substance in a liquid stream, on the surface of a solid. In an
adsorption process, molecules or atoms or ions in a gas or liquid get
concentrated or accumulated on the surface of a solid, where they
bond with the solid surface or are held there by weak inter-
molecular forces. The accumulated or concentrated material on the
surface of solid is called adsorbate, and the solid material is known
as an adsorbent.

31. IIT, Roorkee 31
In order to investigate the adsorption processes, various kinetic models
are used. These include:
 pseudo-first-order
 pseudo-second-order,
 intra-particle diffusion model.
ADSORPTION KINETICS
Pseudo first-order equation is given as:
t
k
qqq
f
ete
303.2
log)log( 
where, K
f
is first-order rate constant (min
-1
), q
e
and q
t
are adsorption
uptake (mg g
-1
) at equilibrium and any time, t (min.)
PSEUDO-FIRST-ORDER MODEL

32. IIT, Roorkee 32
PSEUDO-SECOND-ORDER MODEL
2
)(
teS
t
qqk
dt
dq

where, k
S
is pseudo second-order constant (g mg
-1
) min
-1
for q
t
= 0 at t = 0,
the following equation is obtained:
t
qqkq
t
eeSt
11
2

2
eSqkh
The pseudo-second-order model can be represented as [Ho and
Mckay, 1999]:
h is the initial sorption rate (mg g
-1
min
-1
) h, is the initial sorption rate
(mg g
-1
min
-1
)
INTRA-PARTICLE DIFFUSION STUDY
Itkq
idt

5.0

33. IIT, Roorkee 33
ADSORPTION EQUILIBRIUM STUDY
Various isotherm equations used in the present study are:
1. Two Parameter equations
•Langmuir isotherm
•Freundlich isotherm and
•Tempkin isotherm
2. Three parameter equations
•Redlich-Peterson (R-P)

34. IIT, Roorkee 34
LANGMUIR ISOTHERM [1918]
eL
eLm
e
CK
CKq
q


1
where,
q
e
= equilibrium amount adsorbed (mg g
-1
),
C
e
= equilibrium liquid-phase concentration (mg dm
-3
),
q
m = maximum amount of sorbate per unit weight of sorbent (adsorption
capacity) to form a complete mono-layer (mg g
-1
), and
K
L
= Langmuir constant related to the affinity between sorbent and sorbate.
Assumptions :
mLm
e
e
e
qKq
C
q
C 1

OR
(1)surface is homogeneous, which means that the adsorption energy is
constant over all surface adsorption sites
(2)adsorbed atoms or molecules are adsorbed at definite sites, and
(3)that each site can accommodate only one molecule or atom.

35. IIT, Roorkee 35
FREUNDLICH ISOTHERM EQUATION [1906]
n
eFe CKq
/1
 OR
eFe C
n
Kq ln
1
lnln 
where,
K
F = Freundlich constant (dm
3
mg),
1/n = heterogeneity factor.
Assumptions :
(1)the surface is heterogeneous in the sense that the adsorption energy is
distributed and that the surface topography is patchwise, i. e. the sites
having the same adsorption energy are grouped together into one patch.
(2)on each patch, the adsorbate molecule adsorbs onto one and only one
adsorption site.

36. IIT, Roorkee 36
)ln(
eTe CK
b
RT
q
eTe CBKBq lnln
11 
b
RT
B
1

Where

K
T
is the equilibrium binding constant (dm
3
mg) corresponding to the
maximum binding energy and constant B
1
is related to the heat of
adsorption.
TEMPKIN ISOTHERM EQUATION [1940]
OR
Assumptions :
(1)the heat of adsorption of all the molecules in the layer decreases linearly
with coverage due to adsorbate-adsorbate interactions, and
(2)that the adsorption is characterized by a uniform distribution of binding
energies up to some maximum binding energy [Temkin and Pyzhev, 1940;
Kim et al., 2004]

37. IIT, Roorkee 37

REDILICH-PETERSON ISOTHERM
[1959]

eR
eR
e
Ca
CK
q


1
eR
e
e
R Ca
q
C
K lnln1ln 








OR
where,
K
R
is R–P isotherm constant (dm
3
g),
a
R
is R–P isotherm constant (dm
3
g) and
β is the exponent which lies between 0 and 1,
Assumption :
The R-P isotherm can be applied in homogenous as well as heterogeneous
systems.

38. IIT, Roorkee 38

ADSORPTION DIFFUSION
STUDY
There are essentially four stages in the adsorption of an organic/inorganic
species by a porous adsorbent [Mckay, 2001].
1.Transport of adsorbate from the bulk of the solution to the exterior film
surrounding the adsorbent particle;
2.Movement of adsorbate across the external liquid film to the external
surface sites on the adsorbent particle (film diffusion);
3.Migration of adsorbate within the pores of the adsorbent by intraparticle
diffusion (pore diffusion);
4.Adsorption of adsorbate at internal surface sites.

39. IIT, Roorkee 39
INTRA-PARTICLE DIFFUSION
STUDY
A functional relationship common to most of the treatments of intraparticle
transport is that uptake varies almost proportionally with the square root of
time
Itkq
idt

5.0
where, is the intra-particle diffusion rate constant k
id
(mg/g min
1/2
)
and I (mg/g) is a constant that gives an idea about the thickness of
the boundary layer

40. IIT, Roorkee 40
STATISTICAL ADSORPTION
THERMODYNAMICS
A variable number of particles in statistical physics can be extended to
explain the adsorption process [Wang and Jiang, 2007].
The probability of distribution of a variable number of particles, for systems
of such a type, is given by [Landau and Lifshitz, 1980]
where,
B is the normalizing coefficient,
 the chemical potential (which is dependent on the temperature and
concentration of the donor particles),
i the number of donor particles distributed in the system,
the distribution module,

i the energy of the system that contains i donor particles (which is
assumed to be approximately equal for the systems that contain the
same number of donor particles)
( , ) exp
i
i
i B



  
 
 
 

41. IIT, Roorkee 41
STATISTICAL ADSORPTION THERMODYNAMICS
(Contd.)
1
1
exp
1 exp
n
i
i
n
i
i
i
i
n
i
i






  
  
 

  
  
 

1
1 exp
n


 
 

 
 
1 ln
ln
o
G RT C
  
 
 
 
 
where,  is related to the concentration of adsorbate for a fixed dosage

42. IIT, Roorkee 42
FACTORS CONTROLLING ADSORPTION
•Nature of Adsorbent
•Adsorbent Dose
•pH of solution
•Contact Time
•Initial concentration
•Temperature
•Agitation speed
The amount of adsorbate adsorbed by an adsorbent from aqueous
solution is dependent upon the following factors:

43. IIT, Roorkee 43
1.Materials
Adsorbents, adsorbates and other chemicals
2. Adsorbent Characterization
a) Particle size
b) Surface area, Pore area, pore volume distribution
c) Bulk Density
d) SEM, XRD, FTIR, CHNS, TGA
e) Chemical analysis
EXPERIMENTAL PROGRAMME

44. IIT, Roorkee 44
BATCH EXPERIMENTAL PROGRAMME
1. Effect of pH
0
2. Kinetic study
3. Adsorption equilibrium study
4. Effect of temperature and calculation of thermodynamic parameters
5. Analysis of AN & AA
Percentage removal =
Amount of adsorbate adsorbed per g of adsorbent
0
0
( )
100
e
C C
C

0
( )
e
e
C C V
q
W



45. IIT, Roorkee 45
6. Error Analysis
2
,exp ,
1 ,exp
( )100
n
e e calc
i e
i
q q
HYBRID
n p q

 
  
   

a. Hybrid Fraction error function
b. Marquardt’s percent standard deviation









 


n
i
i
e
calcee
q
qq
pn
MPSD
1
2
exp,
,exp,
)(1
100

46. IIT, Roorkee 46
RESPONSE SURFACE METHODOLOGY:
BOX BEHNKEN DESIGN
Number of trials is significantly reduced
Important decision variables which control and improve the performance of the
product or the process, can be identified
Optimal setting of the parameters can be found out
Qualitative estimation of parameters can be mad
Experimental error can be determined
Inference regarding the effect of parameters on the characteristics of the process
can be made
Response surface methodology, or RSM, is a collection of mathematical and
statistical techniques that are useful for the modeling and analysis of problems in
which a response of interest is influenced by several variables and the objective is
to optimize this response
Advantages

47. IIT, Roorkee 47
In order to estimate the regression coefficients, a number of experimental design
technique are available such as Face centered central composite design, central
composite design etc. Box and Behnken [1962] have proposed that the scheme based on
rotatable design fits the second order response surfaces quite accurately.
Designs for three factors (k = 3). (a) A Box-Behnken design, (b) A central
composite design, and (c) A face-centered central composite design
+1
-1
-1 +1
-1
+1
x
0
x
1
x
2
+1
-1
-1 +1
-1
+1
x
0
x
1
x
2 +1
-1
-1 +1
-1
+1
x
0
x
1
x
2
(a) (b) (c)

48. IIT, Roorkee 48
Basis:Rotatability is a reasonable basis for the selection of response surface
design. Because the purpose of RSM is optimization at the location of
optimum is unknown prior to running the experiment, it makes sense to use
design that provide equal precisions of estimation in all directions
It is a special case of central
composite design. It is not
rotatable because the axial
point is always set equal to
one
It requires a greater number
of experiments, which is
calculated according to
N = k
k
+2
k
+c
p
,
It requires an experiment
number according to
N = k
2
+k +c
p
, where, (k)
is the factor number and (c
p
)
is the replicate number of the
central point. Box–Behnken
is a spherical, revolving
design can be viewed as a
cube
Face centered central
composite
Central composite designBox–Behnken design

49. IIT, Roorkee 49
A Three-Variable Box-Behnken Design
Run
1
x
2
x
3
x
1 -1-10
2 -110
3 1-10
4 110
5 -10-1
6 -101
7 10-1
8 101
9 0-1-1
100-11
1101-1
12011
13000
14000
15000
16000
17000

50. IIT, Roorkee 50
9. Analysis and disposal of spent-adsorbent
Analytical techniques/instrument used for the determination of various
parameters of blank and spent adsorbents.
Sl. No. Parameter Method
1. AN & AA HPLC
2. CHNS CHNS analyzer
3. Heating value of residues Bomb calorimeter
4 Bulk Density MAC density meter
5 Oxidation characteristics of residuesTGA/DTA analyzer
6 Phases and crystallinity of adsorbentsX-ray diffractometer
7 Morphology of solid samples SEM
8 Functional groups on the adsorbentsFTIR Spectrometer

51. IIT, Roorkee 51
RESULTS AND DISCUSSION
•Characterization of adsorbents,
•Batch adsorption study,
•Optimization of parameters for single component batch
adsorption study using Box-Behnken design of experiments
(DOE) methodology,
•Desorption of AN &AA from spent adsorbents

52. IIT, Roorkee 52
(a) (b)
(a) (b)
(c) (d)
SEM of (a) Virgin PAC, (b) Water loaded PAC,
(c) AN loaded PAC and (d) AA loaded PAC at 5 KX

53. IIT, Roorkee 53
SEM of (a) Virgin GAC, (b) Water loaded GAC,
(c) AN loaded GAC and (d) AA loaded GAC at 5 KX
(a) (b)
(c) (d)

54. IIT, Roorkee 54
SEM of (a) BFA virgin, (b) Water loaded BFA,
(c) AN loaded BFA at 1 KX

(a) (b )
(c)

55. IIT, Roorkee 55
XRD Spectra of PAC, GAC and BFA
5 15 25 35 45 55 65 75 85 95
2 Theta
I
n
t
e
n
s
i
t
y
1. PAC
2. GAC
3. BFA
2

1
2
3
C
a
l
c
i
u
m
o
r
t
h
o
s
i
l
i
c
a
t
e
Q
u
a
r
t
z
A
l
u
m
i
n
a
Quartz
S
i
l
i
c
a

56. IIT, Roorkee 56
FTIR spectra of virgin, AN- and AA- loaded
PAC.

57. IIT, Roorkee 57
FTIR spectra of virgin, AN- and AA- loaded GAC.

58. IIT, Roorkee 58
FTIR spectra of virgin and AN loaded BFA.

59. IIT, Roorkee 59
FT-IR SPECTRA ANALYSIS
Broad band between
•3100-3700 cm
-1
(in all adsorbents)- free and hydrogen bonded –OH groups [Kamath and
Proctor, 1998]
•3400 cm
-1
- due to both the silanol groups (Si-OH) and adsorbed water [abou-mesalam, 2003].
•2843 cm
-1
-O-H stretching vibration orignating in the molecule
•2347 cm
-1
-O-H stretching for carboxylic acids
•1600-1800 cm
-1
- CO group stretching from aldehydes and ketones [Davila-Jimenez et al.
2005].
•1383 cm
-1
- symmetrical CO2- stretching
•1247-1111 cm
-1
CH2 deformation
•725-621 cm
-1
- represents the presence of alkynes
•1050-1290 cm
-1
- CO group in lactones [Davila-Jimenez et al. 2005].
•1360-1380 cm
-1
- Aromatic CH and carboxyl-carbonate structures.
•1100 cm
-1
- –C-O-H stretching and –OH deformation values
•1620 cm
-1
- NH deformation.
•With the loading of adsorbates onto adsorbents, shifting of the peaks occurs both to higher
and lower wave numbers from about 3450, 2850, 1600, 1400 cm
-1
•This means that the functional groups at these wave numbers viz. –CO-, -OH, -Si-OH, -SiH
and –C-OH groups are effective in the adsorption.

60. IIT, Roorkee 60
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0 100 200 300 400 500 600 700
Pore diameter, Å
P
o
r
e

v
o
l
u
m
e
,

m
3
/
g
0
50
100
150
200
250
P
o
r
e

a
r
e
a
,

m
2
/
g
PAC - Pore volume GAC - Pore volume BFA - Pore volume
PAC - Pore area GAC - Pore area BFA - Pore area
Pore size distribution of PAC, GAC and BFA.

61. IIT, Roorkee 61
Effect of adsorbent dose on the removal of AN and AA by PAC,
GAC and BFA. T = 303 K, t = 6 h, C
o
= 100 mg/l.
0
20
40
60
80
100
120
0 20 40 60 80 100
Dose (g/l)
%

R
e
m
o
v
a
l
AN-PAC
AN-GAC
AN-BFA
AA-PAC

62. IIT, Roorkee 62
Effect of contact time on the removal of AN and AA by PAC, GAC
and BFA at natural pH. T = 303 K, t = 6 h, C
o
= 100 mg/l.
0
20
40
60
80
100
120
0 50 100 150 200 250 300 350 400
Time (min)
%

R
e
m
o
v
a
l
AA-PAC
AN-BFA
AN-PAC
AN-GAC

63. IIT, Roorkee 63
Effect of initial concentration on the sorptive uptake of
AN by PAC. T = 303 K, t = 6 h, m = 20 g/l
0
5
10
15
20
25
0 50 100 150 200 250 300 350 400 450
Time (min)
q
e

(
m
g
/
g
)
50 mg/l
100 mg/l
200 mg/l
500 mg/l
C0

64. IIT, Roorkee 64
Time course of system pH during the sorption of AN and
AA onto PAC, GAC and BFA. T = 303 K, C
0
= 100 mg/l.
0
2
4
6
8
10
12
0 50 100 150 200 250 300 350 400 450
Time (min)
p
H
AN-PAC
AN-GAC
AN-BFA
AA-PAC

65. IIT, Roorkee 65
Pseudo-second-order kinetic plot for AN-PAC system.
T = 303 K, m = 20 g/l
0
5
10
15
20
25
0 100 200 300 400 500
Time (min)
q
t (m
g
/g
)
50 mg/l 100 mg/l
200 mg/l 500 mg/l

66. IIT, Roorkee 66
Pseudo-second-order kinetic plot for AN-GAC system.
T = 303 K, m = 20 g/l.
0
5
10
15
20
25
0 100 200 300 400 500
Time (min)
q
t
(
m
g
/
g
)
50 mg/l 100 mg/l
200 mg/l 500 mg/l

67. IIT, Roorkee 67
Pseudo-second-order kinetic plot for AN-BFA system.
T = 303 K, m = 20 g/l.
0
20
40
60
80
100
0 100 200 300 400 500
Time (min)
q
t (m
g
/g
)
50 mg/l 100 mg/l
200 mg/l 500 mg/l

68. IIT, Roorkee 68
Pseudo-second-order kinetic plot for AA-PAC system.
T = 303 K, m = 20 g/l.
0
5
10
15
20
25
0 100 200 300 400 500
Time (min)
q
t (m
g
/g
)
50 mg/l 100 mg/l
200 mg/l 500 mg/l

69. IIT, Roorkee 69
Effect of temperature on AN-PAC system.
C
0
= 100 mg/l, m = 20 g/l.
0
10
20
30
40
0 25 50 75 100 125
Ce (mg/l)
q
e

(
m
g
/
g
)
303 K
313 K
323 K
333 K

70. IIT, Roorkee 70
Effect of temperature on AN-GAC system.
C
0
= 100 mg/l, m = 20 g/l.
0
10
20
30
40
0 50 100 150 200
C
e (mg/l)
q
e

(
m
g
/
g
)
303 K
313 K
323 K
333 K

71. IIT, Roorkee 71
Effect of temperature on AN-BFA system.
C
0 = 100 mg/l, m = 20 g/l.
0
10
20
30
40
50
60
70
0 100 200 300 400 500
C
e (mg/l)
q
e

(
m
g
/
g
)
303 K
313 K
323 K
333 K

72. IIT, Roorkee 72
Equilibrium isotherms for AN-PAC system at 303 K.
0
10
20
30
40
50
0 10 20 30 40 50 60 70 80 90 100
C
e (mg/l)
q
e

(
m
g
/
g
)
Experimental
Freundlich
Langmuir
R-P
Temkin

73. IIT, Roorkee 73
Equilibrium isotherms for AN-GAC system at 303 K.
0
10
20
30
40
50
0 20 40 60 80 100
C
e (mg/l)
q
e

(
m
g
/
g
)
Experimental
Freundlich
Langmuir
R-P
Temkin

74. IIT, Roorkee 74
Equilibrium isotherms for AN-BFA system at 303 K.
0
10
20
30
40
50
60
70
0 50 100 150 200 250 300
Ce (mg/l)
q
e

(
m
g
/
g
)
Experimental
Freundlich
Langmuir
R-P
Temkin

75. IIT, Roorkee 75
The effect of temperature on the equilibrium distribution coefficient for AN
and AA sorption onto PAC, GAC and BFA. C
0 = 50 mg/l, t = 6 h, m = 20 g/l.
4
5
6
7
8
9
10
2.85 2.95 3.05 3.15 3.25 3.35
1/T x 10
3
(K
-1
)
l
n
(
q
e
/C
e
)
AA-PAC AA-GAC AN-PAC
AN-GAC AN-BFA

76. IIT, Roorkee 76
Two-step Langmuir isotherm for AN-BFA system at 303-333 K, w= 4 g/l, t = 6 h
Isotherm plot
0
10
20
30
40
50
60
70
0 50 100 150 200 250 300 350 400
Ce (mg/l)
q
e
(
m
g
/
g
)
303 K
313 K
323 K
333 K

77. IIT, Roorkee 77
Kinetic parameters for the removal of AN by PAC, GAC and BFA.
AN-PAC adsorption systemAN-GAC adsorption systemAN-BFA adsorption system
Equations
50 mg/l
100
mg/l
200
mg/l
500
mg/l
50
mg/l
100
mg/l
200
mg/l
500
mg/l
50
mg/l
100
mg/l
200
mg/l
500
mg/l
Pseudo 2nd order
equation
eS
eS
t
qtk
qtk
q


1
2
sk(g/mg min)0.7730.0770.2070.0710.2170.0250.0250.0120.00750.03350.00530.0023
h (mg/g min)4.6351.77119.47334.5521.2542.3370.5960.886
caleq
,
(mg/g)2.4484.7969.69922.0692.4049.6654.88321.053
12.16522.4744.6483.34
2
R 1 0.99961 1 1 1 0.9970.9920.99990.99980.99900.9994
Kinetic parameters for the removal of AA-PAC system

78. IIT, Roorkee 78
Isotherm parameters for AN adsorption onto PAC, GAC and BFA.
AN-PAC AN-GAC AN-BFA
Freundlich
Temp. (K)
FK
[(mg/g)/(mg/l)
1/n
]
n1
2
R
FK
[(mg/g)/(mg/l)
1/n
]
n1
2
R
FK
[(mg/g)/(mg/l)
1/n
]
n1
2
R
30311.14370.38370.98342.50530.64050.98782.71110.69890.9574
3133.99930.45350.97972.74830.58360.99342.50530.64050.9878
3234.12230.38910.99152.49400.55900.99142.43570.60580.9935
3334.42100.32960.89892.19900.52660.99342.13190.57340.9846
Langmuir
Temp. (K)
mq (mg/g)
L
K
(l/mg)
2
R mq (mg/g)
L
K
(l/mg)
2
R mq (mg/g)
LK (l/mg)
2
R
30384.47640.04250.985946.62860.03700.987351.72100.04270.9610
31361.82950.01340.953641.55450.04230.989046.62860.03700.9873
32346.35940.01390.971739.16530.03450.977043.09800.03530.9924
33345.62060.00800.881637.21390.02380.974142.51830.02290.9579
Tempkin
Temp. (K)
TK (l/mg)
TB
2
R TK (l/mg)
TB
2
R TK (l/mg)
TB
2
R
3031.043013.6700.96080.67618.13680.96550.68459.57700.9874
3130.194511.8070.94410.76687.33240.97280.67618.13680.9655
3230.23558.44040.95900.67876.76540.95930.65197.51690.9674
3330.28236.58720.82550.59325.94140.94240.55906.73270.9350
R-P
Temp. (K)
RK (l/g)aR (l/mg)
2
R RK (l/g)aR (l/mg)
2
R RK (l/g)aR (l/mg)
2
R
3031.9833 4.19000.81800.50700.97033.00000.28400.55420.7442
3131.29240.02770.99080.98652.98400.30150.69570.99924.17730.81290.50770.9703
32314.18403.09900.62870.99665.86071.53620.52770.98874.30560.94590.52220.9907
333121.429427.04880.67320.972382.725336.75830.47800.991725.032610.83170.44280.9720

79. IIT, Roorkee 79
Isotherm parameters for AA adsorption onto PAC and GAC.
AA-PAC
Freundlich
Temp. (K)
F
K
[(mg/g)/(mg/l)
1/n
]
n1
2
R
303 0.977 0.756 0.9983
318 0.821 0.735 0.9979
333 0.991 0.652 0.9957
348 1.07 0.613 0.9927
Langmuir
Temp. (K)
m
q (mg/g)
L
K (l/mg)
2
R
303 36.23 0.021 0.9933
318 35.34 0.016 0.9952
333 28.24 0.021 0.9957
348 20.28 0.036 0.9545
Tempkin
Temp. (K)
T
K (l/mg)
T
B
2
R
303 0.233 8.868 0.8925
318 0.1827 8.275 0.907
333 0.204 7.05 0.9062
348 0.217 6.393 0.9184
R-P
Temp. (K)
R
K (l/g)
R
a (l/mg) 
2
R
303 2.07 1.28 0.3183 0.9854
318 0.845 0.3 0.4608 0.9922
333 1.009 0.367 0.5188 0.9892
348 3.922 2.985 0.4206 0.9825

80. IIT, Roorkee 80
Two-step Langmuir isotherm parameters for AN
adsorption onto BFA
Temp.
(C
o
)
1m
q
(mg/g)
2m
q
(mg/g)
1L
K
(l/mg)
2L
K
(l/mg)
MPSD1 MPSD2
2
1
R
2
2
R
30 48 89 0.038 0.008 9.07 2.85 0.9918 0.9996
40 42.09 91.15 0.032 0.004 8.03 4.93 0.9931 0.9640
50 27.61 84.91 0.057 0.003 7.21 4.67 0.9779 0.9957
60 19.26 89.53 0.163 0.002 13.66 3.96 0.9417 0.9900

81. IIT, Roorkee 81
Error analyses functions for adsorption of AN onto PAC, GAC and BFA.
AN-PAC AN-GAC AN-BFA
Freundlich
Temp. (K) HY MP HY MP HY MP
303 -4.0352 28.4812 -1.1965 16.0037 4.557 19.5925
313 -1.1965 16.0037 -0.6262 11.4029 3.5628 20.8468
323 -0.6181 11.2359 -0.7669 12.1977 4.1683 21.1619
333 -1.5343 19.2853 -0.5923 11.2364 4.3784 35.2201
Langmuir
Temp. (K) HY MP HY MP HY MP
303 -0.2031 19.3395 0.5774 15.3297 -0.9205 13.7093
313 0.5774 15.3296 2.4043 13.634 -0.6644 11.4444
323 1.3492 13.9598 2.9759 19.1517 -0.2041 16.3515
333 1.9496 27.1498 3.5568 25.8657 -2.2844 21.8335
Tempkin
Temp. (K) HY MP HY MP HY MP
303 6.1072 38.6607 16.0114 88.924 0.6677 12.0616
313 16.0114 88.924 14.709 59.9385 0.9786 17.4999
323 16.2277 80.4538 14.4891 78.4516 0.866 15.1723
333 13.6463 104.4845 13.6653 88.0334 4.0007 34.5125
R-P
Temp. (K) HY MP HY MP HY MP
303 -4.0493 28.4402 -1.2528 14.6701 -1.4833 12.5986
313 -1.2544 14.668 -0.0835 2.9459 -1.9509 15.4849
323 -0.4285 8.8838 -0.7345 11.5099 -0.2154 16.4154
333 -1.6874 19.761 -0.6189 11.3591 -2.3298 21.9379
HY=HYBRID; MP=MPSD

82. IIT, Roorkee 82
Error analyses functions for adsorption of AA onto PAC and GAC.
AA-PAC
Freundlich
Temp. (K) HY MP
303 0.300 3.960
318 0.276 24.14
333 0.166 6.110
348 0.201 7.920
Langmuir
Temp. (K) HY MP
303 5.544 16.460
318 3.703 13.250
333 4.128 15.620
348 8.265 27.930
Tempkin
Temp. (K) HY MP
303 17.490 83.440
318 16.032 74.560
333 13.480 61.430
348 12.970 72.520
R-P
Temp. (K) HY MP
303 0.3536 4.300
318 0.099 3.520
333 0.277 5.720
348 0.346 8.490
HY=HYBRID; MP=MPSD

83. IIT, Roorkee 83
Isotherm fits for
•Langmuir
•R-P
•Two-step Langmuir
• Freundlich and R-P
•AN-PAC
•AN-GAC
•AN-BFA
•AA-PAC

84. IIT, Roorkee 84
Thermodynamic parameters for the sorption of adsorbate ions onto
PAC, GAC and BFA.
Thermodynamic parameters using classical statistical physics for different
adsorption system
0
G (kJ/mol)Adsorption
systemTemperature, C
o
0
H
(kJ/mol)
0
S
(J/mol

K)
30405060
AN-PAC-48.13-37.40-35.31-33.87-181-448.41
AN-GAC-36.20-33.54-32.69-31.32-82.76-155.02
AN-BFA-22.86-22.70-22.21-22.13-30.96-26.67
Temperature, C
o
30456075
AA-PAC-38.33-36.02-32.37-31.96-20.61-151.78

85. IIT, Roorkee 85
ISOSTERIC HEAT OF ADSORPTION
,
2
ln  

st ae
Hd C
dT RT
or
,
ln
(1/ )
 
e
e
st a
q
d C
H R
d T
Apparent isosteric heat of adsorption (H
st,a) at constant
surface coverage is calculated using the Clausius-Clapeyron
equation [Young and Crowell, 1962]

86. IIT, Roorkee 86
1
2
3
4
5
6
2.9 3 3.1 3.2 3.3 3.4
1/T x 10
3
(K
-1
)
ln
C
e
10
20
30
40
50
qe (mg/g)
1
2
3
4
5
6
7
2.9 3 3.1 3.2 3.3 3.4
1/T x 10
3
(K
-1
)
l
n
C
e
10
20
30
40
50
q
e (mg/g)
1
2
3
4
5
6
7
8
2.9 3 3.1 3.2 3.3 3.4
1/T x 10
3
(K
-1
)
l
n

C
e
10
20
30
40
50
q
e (mg/g)
1
2
3
4
5
6
7
2.9 3 3.1 3.2 3.3 3.4
1/T x 10
3
(K
-1
)
l
n

C
e
8
16
24
32
40
q
e (mg/g)
Adsorption isosters for determining isosteric
heat of adsorption for AN-PAC system
Adsorption isosters for determining isosteric
heat of adsorption for AN-GAC system
Adsorption isosters for determining isosteric
heat of adsorption for AN-BFA system
Adsorption isosters for determining isosteric
heat of adsorption for AA-PAC system

87. IIT, Roorkee 87
Variation of H
st,a with respect to surface loading
-70
-60
-50
-40
-30
-20
-10
0
0 10 20 30 40 50 60
qe (mg/g)

H
s
t
,
a

(
K
J
/
m
o
l
)
AN-PAC
AN-GAC
AN-BFA
AA-PAC
Isosteric enthalpy of AN or AA adsorption onto PAC, GAC and BFA
astH
, (kJ/mol)
astH
, (kJ/mol)
e
q (mg/g)AN-PACAN-GACAN-BFA
e
q (mg/g)AA-PAC
10-22.2367-20.0976-30.05808-13.6137
20-28.2356-26.4451-44.593516-19.9834
30-31.7447-30.1581-53.096224-23.7094
40-34.2344-32.7925-59.129032-26.3530
50-36.1656-34.8359-63.808440-28.4036

88. IIT, Roorkee 88
Desorption efficiencies of AN and/or AA from PAC, GAC
and BFA by methanol.
0
10
20
30
40
50
60
70
80
90
100
AN-PAC AN-GAC AN-BFA AA-PAC
Adsorbate-Adsorbent System
P
e
r
c
e
n
t
d
e
s
o
r
p
t
i
o
n

89. IIT, Roorkee 89
Experimental responses of for AN and AA adsorption onto
PAC, GAC and BFA.
Variable levels
exp
YExp.
no.
wTtAN-PAC AN-GAC AN-BFA AA-PAC
1-1-10 58.75 94.47 49.24 79.54
21-10 90.64 91.32 69.93 96.5
3-110 45.18 70.19 65.13 63.57
4110 83.86 92.33 79.76 89.92
5-10-1 51.18 40.97 15.57 73.61
6+10-1 80.02 83.29 40.36 96.34
7-10+1 67.87 73.96 55.61 71.4
8+10+1 86.55 91.23 83.5 93.29
90-1-1 80.39 59.8 42.98 97.34
100+1-1 63.72 66.22 43.13 89.13
110-1+1 90.96 90.67 69.93 90.16
120+1+1 81.49 81.13 58.4 88.73
13000 84.76 92 70.31 89.85
14000 84.69 92.21 69.21 89.99
15000 85.21 92.21 69.49 91.21
16000 83.5 90 70.77 90.31
17000 87.71 91 68 90
expY is the experimental response.

90. IIT, Roorkee 90
Response surface graph for AN removal versus adsorbent dose versus (a) temperature (b) time for
AN-PAC adsorption system
50
60
70
80
90
Y
4.00
12.00
20.00
28.00
36.00
30.00
37.50
45.00
52.50
60.00
w
T
50
60
70
80
90
Y
4.00
12.00
20.00
28.00
36.00
5.00
77.50
150.00
222.50
295.00
w
t
50
62
73
85
97
Y
4.00
12.00
20.00
28.00
36.00
5.00
78.00
150.00
222.00
295.00
w
t
68
76
84
92
100
Y
4.00
12.00
20.00
28.00
36.00
30.00
37.50
45.00
52.50
60.00
w
T
Response surface graph for AN removal versus adsorbent dose versus (a) temperature (b) time for
AN-GAC adsorption system

91. IIT, Roorkee 91
Response surface graph for AN removal versus adsorbent dose versus (a) temperature (b) time for
AN-BFA adsorption system
Response surface graph for AA removal versus adsorbent dose versus (a) temperature (b) time for
AA-PAC adsorption system
61
69
77
85
93
Y
5.00
8.75
12.50
16.25
20.00
30.00
37.50
45.00
52.50
60.00
w
T
61
69
77
85
93
Y
5.00
8.75
12.50
16.25
20.00
5.00
77.50
150.00
222.50
295.00
w
t
65
73
81
89
96
Y
4.00
12.00
20.00
28.00
36.00
30.00
40.00
50.00
60.00
70.00
w
T
74
80
86
93
99
Y
4.00
12.00
20.00
28.00
36.00
5.00
92.50
180.00
267.50
355.00
w
t

92. IIT, Roorkee 92
Equation obtained from Design Expert software for different
adsorbate –adsorbent system

93. IIT, Roorkee 93
Level of variables chosen
Variables Levels
Coded level 1 0 -1
w : Dose )(g 4 20 36
T: Temp. )(C
o
30 45 60
t : Time (min) 5 150 295

ANOVA table for Y
AN-PAC
Source Sum of
squares
d.f Mean
square
F-value p>F Remark
Model 2905.16 9 322.80 16.10 0.0007 Significant
w 1743.16 1 1743.16 86.93 <0.0001 Highly
Significant
t 113.03 1 113.03 5.64 0.0493 Significant
w
2
865.47 1 865.47 43.16 0.0003 Significant
Residual 140.36 7 20.05
Lack of fit 130.72 3 43.57 18.08 0.0086 Significant
Pure error 9.64 4 2.41
Cor. total 3045.52 16


2
R0.9539, predicted 
2
R0.3083; adjusted 
2
R0.8947, adequate precision = 13.087

94. IIT, Roorkee 94
ANOVA table for Y
AN-GAC
Source Sum of
squares
d.f Mean
square
F-value p>F Remark
Model 3331.22 9 370.14 9.83 0.0032 Significant
w 771.85 1 771.85 20.50 0.0027 Significant
t 939.83 1 939.83 24.97 0.0016 Significant
t
2
1060.72 1 1060.72 28.18 0.0011 Significant
Residual 263.50 7 37.64
Lack of fit 259.74 3 86.58 92.18 0.0004 Significant
Pure error 3.76 4 0.94
Cor.total 3594.71 16


2
R 0.9267, predicted 
2
R-0.1577; adjusted 
2
R0.8325, adequate precision = 11.579

95. IIT, Roorkee 95
Level of variables chosen
ANOVA table for Y
AN-BFA
Variables Levels
Coded level 1 0 -1
w : Dose )/(lg 0.8 4 7.2
T : Temp (C) 30 45 60
t : Time (min) 5 150 295

Source Sum of
squares
d.f. Mean
square
F-
Value
p>F Remark
Model 4274.92 9 474.99 7.84 0.0064 Significant
w 968 1 968 15.98 0.0052 Significant
t 1965.65 1 1965.65 32.45 0.0007 Significant
t
2
1160.32 1 1160.32 19.16 0.0032 Significant
Residual 424.03 7 60.58 - - -
Lack of fit 419.44 3 139.81 121.91 0.0002 Significant
Pure error 4.59 4 1.15 - - -
Corr. total 4698.95 16 - - - -


2
R0.9098, predicted 
2
R-0.4297; adjusted 
2
R0.7937, adequate precision = 9.119

96. IIT, Roorkee 96
Level of variables chosen
ANOVA table for Y
AA-PAC
VariablesLevels
Coded level10-1
w: Dose )/(lg42036
T: Temp (

C)304560
t: Time (min)5180355
SourceSum of squaresd.f.Mean squareF-Valuep Remark
Model 1035.10 9115.0142.34<0.0001Highly
Significant
w 758.36 1758.36279.19<0.0001Highly
Significant
T 61.22 161.2222.540.0021Significant
t 20.54 120.547.56 0.0285Significant
2
w 179.77 1179.7766.18<0.0001Significant
Residual19.01 72.72 -
Lack of fit17.81 35.94 19.690.0074Significant
Pure error1.21 40.30 - - -
Corr. total1054.11 16- - - -

2
R0.9820, predicted 
2
R0.7279; adjusted 
2
R0.9588, adequate precision = 19.799

97. IIT, Roorkee 97
Process parameters for batch adsorption study using Box-Behnken design
Parameters
Systemw
(g/l)
T
)(C
o
t
(min)
Optimized
value
Actual value
AN-PAC253020092 95
AN-GAC253010094 89
AN-BFA16302597 94
AA-PAC20305 91 89

98. IIT, Roorkee 98
THERMAL DEGRADATION KINETICS
OF THE SPENT ADSORBENTS
Distribution of volatiles released during thermal degradation of blank and loaded
adsorbents in an air and nitrogen atmosphere at a flow rate of 200 ml/min.
Adsorbent
(Blank/
loaded)
%Weight loss in air atmosphere (approximate)
%Weight loss in
nitrogen atmosphere
(approximate)
<200
o
C200-400
o
C400-700
o
C >700
o
C <200
o
C200-975
o
C
%Total volatile
matter including
moisture in air
%Total volatile
matter including
moisture in nitrogen
PAC 13.83 1.64 81.79 23.35 17.09 6.26 97.62 23.35
AN-PAC 18.48 3.46 76.51 27.21 18.83 8.38 99.29 27.21
AA-PAC 15.15 2.59 79.71 23.81 13.56 10.25 97.77 23.81
GAC 14.38 1.48 83.48 22.27 17.36 4.91 99.43 22.27
AN-GAC 14.48 1.31 64.22 21.93 16.69 5.24 80.03 21.93
BFA 6.98 8.00 78.03 29.79 7.68 22.11 94.29 29.79
AN-BFA 9.20 5.40 78.55 24.94 8.23 16.71 94.31 24.94

99. IIT, Roorkee 99
Thermal degradation characteristics of blank and loaded adsorbents in air and nitrogen
atmosphere at a flow rate of 200 ml/min
Adsorbent
(Blank/loaded)
Air atmosphere Nitrogen atmosphere
Drying
Range
(
o
C)
Moisture
(%)
Degradation
Range
(
o
C)
Tmax
(
o
C)
Max.
Rate of
Weight
Loss
(mg/min)
Drying
Range
(
o
C)
Moisture
(%)
Degradation
Range
(
o
C)
Tmax
(
o
C)
Max.
Rate of
Weight
Loss
(mg/min)
PAC 24-10012.89 >200 552 3.1 24-10016.08 >200 83 0.7
AN-PAC 22-10617.47 >200 552 2.5 23-10017.43 >200 88 0.8
AA-PAC 25-10014.02 >200 552 2.4 25-10012.46 >200 245 0.1
GAC 21-12914.38 >200 594 2.0 26-12816.87 >200 96 0.8
AN-GAC 22-12413.73 >200 641 2.2 24-12015.88 >200 97 0.7
BFA 22-99 5.41 >200 490 0.7 21-1006.15 >200 365 0.051
AN-BFA 23-1007.78 >200 547 1.2 23-1006.76 >200 355 0.035

100. IIT, Roorkee 100
DTA for the blank and loaded adsorbents in the air and nitrogen atmosphere
at flow rate 200 ml/min
Air atmosphere Nitrogen atmosphere
Adsorbent
(Blank/loaded)
1H(MJ/kg)T1i
(
o
C)
T2f
(
o
C)
2H(MJ/kg)T1i
(
o
C)
T2f
(
o
C)
H(MJ/kg)T1i
(
o
C)
T2f
(
o
C)
PAC 25165135-634540965033335175
AN-PAC35250155-665646565238250160
AA-PAC26450150-559045566524950165
GAC 30255165-716047572533255175
AN-GAC30865160-719848575034355160
BFA - -- -7107395550- --
AN-BFA- -- -7245375580- --

101. IIT, Roorkee 101
List of different kinetic models for thermal degradation of the adsorbents
M e c h a n i s m S y m b o l D i f f e r e n t i a l k i n e t i c f u n c t i o n
)(Xf
I n t e g r a l K i n e t i c
F u n c t i o n )(Xg
D i f f u s i o n m o d e l s
O n e - d i m e n s i o n a l
d i f f u s i o n
D 1 X2/1
2
X
T w o - d i m e n s i o n a l
d i f f u s i o n
D 2
1
)]1l n ([

 X )1l n ()1( XXX 
T h r e e - d i m e n s i o n a l
d i f f u s i o n
D 3
13132
))1(1()1(2

 XX
231
))1(1( X
Z h u r a v l e v D i f f u s i o n Z D
5 3 1 3 1
( 2 / 3 ) ( 1 ) [ 1 ( 1 ) ]X X

  
1 3 2
[ ( 1 ) 1 ]X

 
G i n s t l i n g - B r o u n s h t e i n G B
3/13/1
)1(1/)1)(3/2( XX 
3/2
)1(3/21 XX 

102. IIT, Roorkee 102
Kinetic and thermodynamic parameters calculated for the blank and adsorbate loaded
PAC using different models: heating rate = 25 K/min, air flow rate = 200 ml/min
Parameters D1 D2 D3 GD GB
PAC
n
k
0 (min
-1
)
E (kJ/mol)
k (min
-1
)
ΔS (J/mol K)
ΔH (kJ/mol)
ΔG (kJ/mol)
Ps
R
2
1
0.36
12.92
0.04
-251.85
7.03
202.54
2.10e-014
1
1
2.40
13.85
0.31
-261.55
7.00
222.55
2.17e-014
0.31
1
0.24
14.07
0.03
-261.87
7.22
223.04
2.09e-014
0.32
1
0.14
14.54
0.01
-261.94
7.68
223.56
2.07e-014
0.33
1
0.36
13.92
0.04
-261.81
7.07
222.84
2.10e-014
0.32
AN-PAC
n
k0 (min
-1
)
E (kJ/mol)
k (min
-1
)
ΔS (J/mol K)
ΔH (kJ/mol)
ΔG (kJ/mol)
Ps
R
2
1
4.16
14.01
0.54
-261.49
7.15
223.03
2.18e-014
1
1
1.23
14.30
0.15
-261.66
7.43
223.46
2.14e-014
0.32
1
0.21
14.60
0.03
-261.90
7.74
223.96
2.09e-014
0.34
1
0.19
15.21
0.02
-261.93
8.35
224.59
2.08e-014
0.35
1
1.24
14.11
0.17
-261
7.45
203.46
2.35e-014
0.33
AA-PAC
n
k0 (min
-1
)
E (kJ/mol)
k (min
-1
)
ΔS (J/mol K)
ΔH (kJ/mol)
ΔG (kJ/mol)
Ps
R
2
1
7.25
13.85
0.97
-261.42
6.98
222.73
2.22e-014
1
1
1.31
14.11
0.17
-261.66
7.25
223.19
2.15e-014
0.34
1
0.20
14.38
0.03
-261.92
7.52
223.68
2.09e-014
0.35
1
0.15
14.92
0.02
-261.96
8.07
224.26
2.08e-014
0.36
1
0.25
14.20
0.04
-261.89
7.34
223.47
2.09e-014
0.34

103. IIT, Roorkee 103
CONCLUSIONS
From the present study, the following conclusions can be drawn:
The FTIR spectra of the adsorbents indicated the presence of various
types of functional groups e.g. free and hydrogen bonded OH group,
the silanol groups (Si-OH), CO group stretching from aldehydes and
ketones on the surface of adsorbents.
Optimum activated carbons (PAC & GAC) and BFA dosages were
found to be 20, 20 and 4 g dm
-3
, for =100 mg dm
-3
of AN & AA
respectively. 6 h could be taken as the equilibrium contact time for
adsorption.
The sorption kinetics could be represented by the pseudo-second-order
kinetic model.
An increase in temperature induces a negative effect on the sorption
process. Redlich-Peterson, isotherms generally well represent the
equilibrium adsorption of AN & AA for the adsorption on PAC, GAC,
and BFA.

104. IIT, Roorkee 104
The heat of adsorption and change in entropy for AN & AA adsorption on
PAC, GAC and BFA were found to be in the range of 2-16 kJ/mol and 1.5-58
kJ/mol K, respectively.
The positive isosteric heat of adsorption and negative energy change value
confirms the endothermic nature of adsorption system in all cases.
The Box-Behnken experimental design (DOE) methodology was found to be
very economical in the experimental sorption studies for AN & AA removal.
This approach facilitated the understanding of the factors such as adsorbent
dose, temperature and contact time at three levels.
The use of the CH3OH showed higher recovery efficiencies (≈ 90 %) for
GAC, PAC and BFA.
The spent adsorbents can be used as a fuel.
The order of efficiency of these adsorbents is BFA > GAC > PAC.

105. IIT, Roorkee 105
On the basis of the present studies, the following recommendations may
be made for future studies:
RECOMMENDATIONS
Adsorbents from different sources should be characterized for their physico-
chemical parameters and surface characteristics so that the results can be
correlated on their utilization as low-cost adsorbents in effluent treatment.
Scale-up studies should be conducted to evaluate the suitability of BFA as
adsorbents and the engineering detailing and feasibility of the adsorption
process.
BFA has enough amount of silica which may be tested to make the bricks.
BBD design of experiments methodology should be evaluated further for its
application in effluent treatment experiments using adsorption process and
the design of scaled-up adsorption systems.

106. IIT, Roorkee 106
REFERENCES
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Public Health Service, U.S. Department of Health and Human Services, Atlanta, GA. (1990).
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ASTM: D- 3838-05, Standard Test method for pH of activated carbon
Bretherick, L. Hazards in the Chemical Laboratory, 3
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Cheremisinoff, N. P. Hand Book of Industrial Toxicology and Hazardous Materials, Marcel Dekker,
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Desai, J. D.; Ramakrishna, C. Microbial degradation of cyanides and its applications. J. Sci. Ind. Res.
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Dohanyous, M. Z.; Zabranska, J. Anaerobic breakdown of acrylic acid. Proc. 5
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Howard, P. H. Handbook of environmental fate and exposure data for organic chemicals, Vol. I
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Lataye, D. H.; Mishra, I. M.; Mall, I. D. Adsorption of 2-picoline onto bagasse fly ash from aqueous
solution, Chem. Eng. J., 2007, doi:10.1016/j.cej.2007.05.043.
Lataye, D. H.; Mishra, I. M.; Mall, I. D. Removal of pyridine from aqueous solution by adsorption on
bagasse fly ash, Ind. Eng. Chem. Res., 45(11), 3934 -3943 (2006).
Lu, C.; Lin M,-R.; Lin J. Removal of acrylonitrile vapor from waste gases by a trickle-bed air
biofilter. Bioresource Technol 2000, 75, 35-41.
Mall, I.D.; Srivastava, V. C.; Agarwal, N. K.; Mishra, I. M. Removal of congo red from aqueous
solution by bagasse fly ash and activated carbon: kinetic study and equilibrium isotherm
analyses. Chemosphere, 2005, 492, 50 - 61.

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REFERENCES (Contd.)
Mall, I. D.; Upadhyay, S. N.; Sharma, Y. C. A review on economical treatment of wastewaters and
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Mall, I. D. Petrochemical Process Technology; I
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National Institute for Occupational Safety and Health (NIOSH). Pocket guide to chemical Hazards.
U.S. Department of Health and Human Services, Public Health Service, Centers for Disease
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Sax, N. I. Dangerous Properties of Industrial Materials, 3
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Silva, A. M. T.; Marques R, R. N.; Quinta-Ferreira, R. M. Catalysts based in cerium oxide for wet
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Sittig, M. Handbook of Toxic and Hazardous Chemicals and Carcinogens. 2nd ed. Noyes Publications,
Park Ridge, NJ. 1985.
Srivastava, V. C.; Swamy, M. M.; Mall, I. D.; Prasad, B.; Mishra, I. M. Adsorptive Removal of
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U.S. Department of Health and Human Services. Hazardous Substances Data Bank (HSDB, online
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U.S. Environmental Protection Agency. Integrated Risk Information System (IRIS) on Acrylic Acid.
National Center for Environmental Assessment, Office of Research and Development,
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Viraraghavan, T.; Alfaro, F.M. Adsorption of phenol from wastewater by peat, fly ash and bentonite.
J. Hazard. Mater, 1998, 57, 59-70.

108. IIT, Roorkee 108
PUBLICATION FROM THE THESIS
International Journals
Kumar, A.; Prasad, B.; Mishra, I. M. Process parametric study for ethene carboxylic
acid removal onto powder activated carbon using Box-Behnken design. Chem.
Eng. Technol. 2007, 30(7), 932-937.
Kumar, A.; Prasad, B.; Mishra, I. M. Adsorptive removal of acrylonitrile by
commercial grade activated carbon: Kinetics, equilibrium and thermodynamics.
J. Hazard. Mater. 2007, Doi: 10.1016/j.jhazmat. 2007.07.048.
Kumar, A.; Prasad, B.; Mishra, I. M. Optimization of process parameters for
acrylonitrile removal by a low cost adsorbent using Box-Behnken design. J.
Hazard. Mater., 2008, 150, 174-182.

109. IIT, Roorkee 109
OTHER PUBLICATIONS
Papers in Conference Proceedings
Arvind Kumar, B. Prasad, I.M. Mishra. Estimation of Instant Air Borne Particulate Loading
From Road Surfaces Due to Vehicular Transportation: An Empirical. Proceedings of
Seminar on Environmental Degradation: Problems and preventions, Organized by the
Dept. of Chemical & Alcohol Tech., S. D. College of Engg. & Tech., Jansath Road,
Muzaffarnagar (U.P.) INDIA, 17th Sept. 2005.
Arvind Kumar, B. Prasad, I.M. Mishra. Chemical Speciation of Particulate matter at IIT
Roorkee campus and adjoining areas. All India Seminar on Air Pollution & Health Impact
(AISAPHI), Organised by The Institution of Engineers (INDIA), Roorkee Local Centre
(Opp. C.B.R.I) Roorkee, Uttranchal, INDIA, Feb. 23 –24, 2006
Arvind Kumar, S.P. Singh, P. Tripathi. Advanced Analytical Technique in wastewaters
Ananlysis. Seminar on Recent Trends in Science, technology &its applications, organized
by S. D. College of Engineering & Technology, Jansath Road, Muzaffarnagar (U.P.)
INDIA, 7-8 Jan. 2006.
Arvind Kumar, B. Prasad, I.M. Mishra. Acrylonitrile: A hazardous component in
petrochemical industrial effluent. National Seminar on Public Participation for
Environmental Control, organized by S. D. College of Engineering & Technology, Jansath
Road, Muzaffarnagar (U.P.) INDIA, 7th April, 2007

110. IIT, Roorkee 110
CONFERENCES/SEMINARS/SYMPOSIA/SHORT-TERM COURSES ATTENDED
Seminar on Environmental Degradation: Problems and preventions, Organized by the Dept. of
Chemical & Alcohol Tech. S. D. College of Engg. & Tech., Jansath Road, Muzaffarnagar
(U.P.) INDIA, 17 Sept. 2005
Seminar on Recent Trends in Science, technology &its applications, organized by S. D. College
of Engineering & Technology, Jansath Road, Muzaffarnagar (U.P.) INDIA, 7-8 Jan. 2006
All India Seminar on Air Pollution & Health Impact (AISAPHI), Organised by The Institution
of Engineers (INDIA), Roorkee Local Centre (Opp. C.B.R.I) Roorkee, Uttranchal, INDIA,
Feb. 23-24, 2006
Authorization, Procedures, Technologies, Treatment, Recycling and Reprocessing of Hazardous
Waste held at IIT Roorkee on Nov. 20-24, 2006.
Novel Separation Techniques in Process Industries held at The Institution of Engineers (India),
Roorkee local centre on Dec 4-8, 2006.
All India Seminar on Energy and Environmental issues related to chemical industry, Organized
by The Institution of Engineers (India), U. P. State Center, Lucknow, 10th & 11th March,
2007.
Hazardous Waste Management held at IIT Roorkee on March 27-31, 2007.
National Seminar on Public Participation for Environmental Control, organized by S. D.
College of Engineering & Technology, Jansath Road, Muzaffarnagar (U.P.) INDIA, 7th
April, 2007

111. IIT, Roorkee 111