Modeling of nitrate removal for ion exchange resin in batch and fixed bed experiment

8102019 Modeling of nitrate removal for ion exchange resin in batch and fixed bed experiment

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To the best of ourknowledgemost studies onnitrate removal by ionexchange resins have been performed in batch experiments and only afew have been reported in 1047297xed bed systems [19212225ndash29] In gen-eral batch experiments are used to determine the equilibrium isothermand kinetic of nitrate removal onto resin particles One disadvantage of these experiments is that theydo not give informationabout thehydro-dynamic parameters of 1047297xed bed columns such as the dispersioncoef 1047297-cient [30] Another drawback of batch processes is their discontinuity

and the need to perform complicated phase separation operations[31] Furthermore little attention has been paid to the numerical solu-tion of nitrate removal models in a 1047297xed bed column packed with ionexchange resins even though a suitable numerical solution can helpto reduce the number of experiments associated with new operatingconditions A noveland well-researched model can be used as a reliablesolution to design optimize and predict the breakthrough curves of 1047297xed bed columns in real water treatment processes

Both empirical and more theoretical isotherm models have beendeveloped to describe ion exchange equilibrium [32ndash34] Several em-pirical and semi-empirical isotherm models can be found in the liter-ature such as the Langmuir and Freundlich equations to explain ionexchange equilibrium [3536] Several researchers have used thesemethods to illustrate the equilibrium of the ion exchange process[52937ndash41] Theoretical isotherm models are basically based on thelaw of mass action In these methods the ion exchange process istreated as a chemical reaction while the concept of membrane theoryand thermodynamic description are used to illustrate the real behav-ior of ions in both the solution and resin phases [3132] It is importantto note that few comparisons have been done between empirical andtheoretical equilibrium models for ion exchange resins

The aim of the present research is to study and model the removalof nitrate from synthetic solutions and groundwater through the useof a selective ion exchange resin called IND NSSR in both batch and1047297xed bed systems The effects of 1047298ow rate initial nitrate concentra-tion and the existence of competitive ions such as sulfate on nitrateremoval were also investigated Afterwards the equilibrium datawere simulated by an adsorption isotherm and the mass action lawand the results were compared to each other under different operat-

ing conditions Then a numerical model was developed to solve theadvection dispersion equation with adsorption in columns The ad-sorption term was simulated using the mass action law isothermModel parameters were estimated and compared to those obtainedin equilibrium experiments Finally sensitivity analysis was per-formed to determine the effect of model parameters on breakthroughcurve shape

2 Experimental

21 Materials

A nitrate selective ion exchange resin named IND NSSR wasobtained from Ion Exchange India LTD This material is a macroporous

strongly basic anion resin that is suitable for the removal of nitratefrom water The effective sizes of the particles range from 04 to05 mm containing exchangeable chloride ions The unique advantageof this resin is that it has more af 1047297nity for nitrate ions in comparisonwith other existing anions Before use the resin particles werewashed with distilled water in order to remove any adhering dirtThe resin was dried at an oven temperature of 60 degC for the batch ex-periments Synthetic solutions were prepared by dissolving differentamounts of NaNO3 Na2SO4 and NaCl in distilled water in order toreach the desired concentrations The groundwater was obtainedfrom one of the drinking wells of Shiraz Iran The characteristics of this water are summarized in Table 1

Nitrate ions were analyzed using a UV spectrophotometer instru-ment (HACH DR5000) at a wavelength of 220 nm Before measure-

ment 50 ml of samples was acidi1047297ed with 1 ml of 10 N HCl in order

to eliminate the interface of hydroxide and bicarbonate ions The pHof the analyzed solution was 2plusmn01 Sulfate and chloride ions wereanalyzed using Ion Chromatography (Metrohm 761)

22 Batch mode equilibrium experiments

In order to obtain the ion exchange equilibrium data batch ex-periments were carried out in duplicate with respect to Shirazgroundwater and various synthetic solutions including solutionswith different initial nitrate concentrations and solutions containingsulfate and chloride ions A speci1047297ed amount of resin (0025 to 08 g)was added to glass bottles containing 200 ml of nitrate solution Thebottles were sealed and placed in a temperature-controlled rotatingshaker for 24 h to reach equilibrium The temperature was kept at aconstant 20 degC with a maximum tolerance of 01 degC The ion concen-tration uptake to solid phase wascomputedusing thefollowing massbalance equation

qe frac14 C 0minusC eeth THORNV

m eth1THORN

where qe (mgg) is the solid phase equilibrium adsorption concentra-tion C 0 and C e (mgl) are the initial and equilibrium liquid phase ionconcentrations and V (l) and m (g) are the volume and the resinmass respectively

23 Column mode experiments

Column tests were performed using glass columns with an inter-nal diameter of 36 cm A schematic diagram of the column setupused for the 1047297xed bed studies is shown in Fig 1 All experimentswere conducted at a constant temperature of 20plusmn1 degC The nitratesolution was passed through the resin bed in an upward directionto ensure a completely saturated bed [42] A peristaltic pump wasused to maintain a constant1047298ow rate during the experiments The ex-

periments were carried out at different conditions of 1047298ow rates in1047298u-ent concentrations and the presence of sulfate and chloride ions Theresin bed height for all tests was set at 205 cm with a tolerance of 015 cm The column experiments were continued until the completesaturation of the resins was achieved The column void portion iebed porosity was estimated through 1047297rst moment analysis of pulseloading experiments using NaCl as a tracer The effect of 1047298ow rate onnitrate adsorption was investigated by varying the 1047298ow rate from 069to 211 lh at a constant in1047298uent nitrate concentration of 120 mgl(Runs 1 to 3) Moreover the effect of the in1047298uent nitrate concentrationon the sorption performance of nitrate was examined at the values of 895 and 604 mgl (Runs 4 and 5) Run 6 and Run 7 were arranged inorder to inspect the in1047298uence of sulfate and chloride ions on the remov-al of nitrate Finally column tests were performed to investigate nitrate

removal from Shiraz groundwater (Runs 8 and 9)

Table 1

Composition of Shiraz groundwater

Species Concentration (mgl)

Fminus 076plusmn0007Clminus 1003plusmn0518SO4minusminus 236plusmn0323

HCO3minus 3603plusmn224

NO2minus 0012plusmn0005


NH3 008plusmn01Ca++ 1187plusmn271Mg++ 681plusmn0763Na+ 804plusmn0844K+ 28plusmn0128TDS 884plusmn525pH 753plusmn008

23 AA Hekmatzadeh et al Desalination 284 (2012) 22ndash 31



3 Modeling

31 Equilibrium modeling

The Langmuir isotherm model is a well-known and widely usedmodel in the literature [35] The model assumes monolayer adsorp-tion onto surfaces that take place at the 1047297nite number of identicalsites There are no lateral interactions between neighboring adsorbedmolecules [35] The Langmuir relation is stated as Eq (2)

qeNO3 frac14

Q 0 b C eNO3

1 thorn b C eNO3

eth2THORN

where Q 0 and b are known as the Langmuir constants and C eNO3 andqeNO3 are the pollution concentrations of the liquid and solid phases re-spectively Q 0 is the maximum adsorption capacity and b is a constantrelated to adsorption energy In order to calculate Q 0 and b parameters

Eq (2) can be rearranged to give the following linear equation1

qeNO3

frac14 1Q 0 b

1C eNO3

thorn 1Q 0

eth3THORN

In the mass action law approach the ion uptake by resin particlescan be treated as chemical reactions The following expression repre-sents the chemical reaction between nitrate ions and resin particles

R minusClminus thorn NOminus3 rarr R minusNOminus3 thorn Clminus eth4THORN

In this expression NO3minus and Clminus represent nitrate and chloride

concentrations in the liquid phase and R minusNO3minus and R minusClminus are the

ion concentrations in the solid phase The apparent equilibrium con-stant of reaction 4 is

k frac14C eCl qeNO3

qeCl C eNO3

eth5THORN

where qeNO3 qeCl C eNO3

and C eCl represent concentrations of nitrateand chloride ions in the resin and liquid phases at equilibrium condi-tion respectively Applying mass balance to the resin and liquidphases leads to the following isotherm equation

qeNO3 frac14

k qT C eNO3

C 0 thorn kminus1eth THORNC eNO3

eth6THORN

where qT (qT = qeNO3+ qeCl) denotes the maximum ion exchange ca-

pacity of resin and C 0 is the total anion concentration Eq (6) is

known as the competitive Langmuir isotherm in the literature [33]

It is important to note that this equation has been extracted from bi-nary systems where only nitrate and chloride are present in the initialsolution When the system contains more anions such as sulfate ad-ditional terms should be included in the nominator of Eq (6) [32]Eq (6) can be put to a linear form (Eq (7)) in order to determine k

and qT coef 1047297cients through linear regression

1

qeNO3

frac14 1

k qT

C 0

C eNO3

thorn kminus1

k qT

eth7THORN

32 Column numerical modeling

The column breakthrough curve or the concentrationndashtime pro1047297lecan be modeled by the differential mass balance of solute transport ina segment of the column The governing transport equation that in-cludes the adsorption of solute in the column is described by the fol-lowing one dimensional advection dispersion equation [43]

partC

partt frac14 D

part2C

part x2minusu

partC

part xminusρb

n

partq

partt eth8THORN

Here C and q are the nitrate concentrations in the liquid and solid

phases respectively u represents the interstitial velocity of the solu-tion through the bed D ρb and n stand for the axial dispersion coef-1047297cient bulk density and bed porosity of resin particles respectivelyIn solving Eq (8) one more relationship is needed as it containstwo unknown variables C and q Therefore assuming local equilibri-um the mass action law isotherm model was used to explain the re-lationship between C and q The last term on the right hand side of Eq (8) can be replaced with relation 9

partq

partt frac14 partq

partC

partC

partt eth9THORN

The transport Eq (8) the mass action isotherm Eqs (6) and (9)were combined to obtain the following one dependent variable par-tial differential equation

RpartC

partt frac14 D

part2C

part x2minusu

partC

part x eth10THORN

where R is the retardation factor de1047297ned as

R frac14 1 thornρb

n

kC 0qT

C 0 thorn kminus1eth THORNC eth THORN2

eth11THORN

Eq (10) can be transformed to dimensionless form as Eq (12)

RpartC

partT frac14

D

uL

part2C

part X 2minuspartC

part X eth12THORN

where X ( X frac14 xL) and T (T frac14 tu

L) are dimensionless length and time vari-

able respectively and L is the resinbed length The initial and boundaryconditions of the above equation in the present experimental set-up areas follows

C T frac14 0eth THORN frac14 0 0≺ X ≺1 eth13THORN

C X frac14 0eth THORN frac14 C 0 NO3minus 0leT eth14THORN

partC X frac14 1eth THORN

part X frac14 0 0leT eth15THORN

A computer code was developed and run in the MATLAB software

using 1047297nite difference techniques to solve Eq (12) The general form

Fig 1 Experimental setup for column tests




of the 1047297nite difference approximation of Eq (10) is in the form of Eq (16)

Rni

C nthorn1i minusC niΔT

frac14 1minusωeth THORN

( D

uL Δ X eth THORN2 C

nithorn1minus2C

ni thorn C

niminus1

minus 1Δ X

1minusαeth THORNC ni thorn αC

nithorn1minus 1minusαeth THORNC

niminus1minusαC

ni

)

thornω(

DuL Δ X eth THORN2

C nthorn1ithorn1 minus2C

nthorn1i thorn C

nthorn1iminus1

minus 1Δ X

1minusαeth THORNC nthorn1i thorn αC

nthorn1ithorn1 minus 1minusαeth THORNC

nthorn1iminus1minusαC

nthorn1i

h i)

eth16THORN

Here i and n are the time and length indices respectively Also ω and α denote temporal and spatial weighting parameters Discretiza-tion of 1047297rst order derivatives in Eq (16) ends up in a truncation errorin algebraic form which is proportional to the second derivative termof part

2C part X 2

This error forms a second order numerical dispersion whichshould be represented in Eq (16) Eq (16) is reduced to the Crankndash

Nicolson approximation centered in space when ω =α =05 In

this scheme numerical dispersion will be zero [44] In order toachieve a reliable numerical solution arti1047297cial oscillation (alsoknown as overshoots and undershoots) should be avoided It wasfound in this research that when grid spacing is such that the gridPeclet number P eg (de1047297ned by Eq (17)) is less than 2 these over-shoots and undershoots are reduced considerably

P eg frac14 uLΔ X

D eth17THORN

The governing Eq (10) contains two groups of model parametersThe 1047297rst group can be measured directly as velocity and bulk densityThese parameters were considered as 1047297xed values in modeling Thesec-ond ones need to be estimated such as the dispersion coef 1047297cient max-imum adsorption capacity and apparent equilibrium constant The later

parameters are obtained by minimizing an objective function This

function can be stated as root mean square of errors (RMSE) betweenexperimental data and model estimations

RMSE frac14

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffisum

n

ifrac141C expiminusC modeli

2

n

v uuut eth18THORN

where C exp and C model are the experimental and model predictions of nitrate concentration obtained at the column outlet The lsquolsqnonlinrsquo

function in the optimization toolbox of MATLAB software was usedto optimize the values of the aforementioned parameters This func-tion uses non-linear least square techniques to minimize the objec-tive function

4 Results and discussion

41 Batch equilibrium results

The isotherm experimental data of the batch experiments withdifferent synthetic solutions and Shiraz groundwater are reported inTables 2 and 3 respectively The initial nitrate sulfate and chlorideconcentrations of the different synthetic solutions are given inTable 4 Regression analysis was performed on the data using the lin-

ear form of the Langmuir and the mass action law isotherm models(Eqs (3) and (7)) The estimated constants of both models and relat-ed correlation coef 1047297cients (R2) and root mean square errors (RMSE)for different batch experiments are provided in Table 4 Root meansquare errors (RMSE) were calculated between experimental nitratesolid phase concentration measurements ie qeNO3 and the predic-tions of Langmuir and mass action isotherms The values of correla-tion coef 1047297cients (R2) are higher than 094 which indicates asatisfactory description of each set of equilibrium data by both iso-therm models However the estimated values of Langmuir constantb varied ranging from 047 to 283 lmeq for different cases of batchexperiments This shows that Langmuir constant b depends on the so-lution environment and changes with nitrate sulfate and chlorideconcentrations in solutions Consequently the Langmuir equation is

not fully accurate to be used in predicting the dynamic behavior of

Table 2

Batch experiments data with synthetic solutions

Syntheticsolution

WV gl

C 0meql

C emeql

qemeqg

Syntheticsolution

WV gl

C 0meql

C emeql

qemeqg

1 0101 1902 1596 3032 3 15 0897 0050 05641 0180 1902 1407 2757 3 2 0897 0036 04311 0219 1902 1345 2549 4 0127 4873 1658 19981 0332 1902 1147 2275 4 0253 4873 1454 18071 05 1902 0833 2139 4 0501 4873 1114 1590

1 1 1902 0357 1545 4 10065 4873 0664 12381 15 1902 0200 1140 4 1753 4873 0357 08861 2 1902 0136 0892 4 2501 4873 0243 06671 25 1902 0102 0731 4 4003 4873 0150 04401 3 1902 0086 0618 5 0126 6795 1739 16042 01 1407 1157 2506 5 0250 6795 1579 14482 015 1407 1049 2385 5 0502 6795 1264 13502 025 1407 0835 2288 5 1003 6795 0857 10812 05 1407 0485 1843 5 1752 6795 0518 08122 1 1407 0193 1214 5 2501 6795 0357 06332 15 1407 0114 0862 5 4002 6795 0221 04302 2 1407 0079 0664 6 0207 9871 1683 15462 25 1407 0071 0537 6 0376 9871 1478 13982 3 1407 0057 0455 6 0753 9871 1157 11243 01 0897 0685 2113 6 1504 9871 0750 08333 015 0897 0604 1951 6 2 9871 0600 07013 025 0897 0428 1873 6 25 9871 0469 0613

3 05 0897 0214 1365 6 325 9871 0364 05043 1 0897 0086 0811




columns packed with ion exchange resin In contrast the estimatedconstants of the mass action law isotherm (k and qT ) for all casesare close to each other The model constants qT and k are in therange of 213 to 281 meqg and 520 to 723 respectively Thereforeit is possible to state ion exchange equilibrium with the unique iso-therm equation using the mass action law These results show thatthe mass action law isotherm is more ef 1047297cacious for describing ionexchange equilibrium in comparison with adsorption models suchas the Langmuir isotherm Although the Langmuir model can describeequilibrium data adequately its parameters such as b depend on solu-tion conditions

Another important difference between the Langmuir and the massaction law isotherm models is related to the estimation of maximumadsorption capacity (Q 0 and qT ) As shown in Table 4 the Langmuirequation overestimates the value of maximum adsorption capacityin comparison with the mass action law equation Also the range of estimation of the Langmuir model is noticeably wider than the secondmodel The estimated values of Q 0 are between 246 and 350 meqgwhile the values of qT range from 213 to 281 meqg This shows that

the mass action law model is more reliable than the Langmuir modelThe results showed that the Langmuir coef 1047297cient b changed consid-

erably when chloride sulfate or both were present in nitrate solutionswhile the mass action law constants remained nearly constant in theseconditions The linearform of the Langmuir and the mass action lawiso-therms (Eqs (3) and (7)) were compared forsynthetic solutions1 and 4(Fig 2) The difference between these two solutions was the existenceof chloride in the latter Nitrate concentration was the same in both so-lutions Although both solutions follow the Langmuir isotherm modelindividually the predicted value of b for synthetic solution 4 is lessthan half of the b constantobtained for solution 1 Therefore it is not ac-curate to express both equilibrium data with the same Langmuir equa-tion However as Fig 2(B) shows not only are both data sets describedwell by the mass action law model but also they can be shown with

almost a single line Similar 1047297gures were obtained for the other solu-tions which they are not shown here for the sake of brevity

The Langmuir constant b is related to adsorption energy and doesnot give any information about the chemical mechanism Previouslythe Langmuir and the mass action law models were compared byMisak (2000) [45] According to his argument if the Langmuir modelis used in the ion exchange equilibrium description the Langmuir con-stant b should be equalto kC Cl where C Cl is chloride concentration in anequilibrium state This means that b is a function of C Cl and is thereforenot constant On the other hand the estimated value of b is in1047298uencedby the value of C 0 ie the total initial anions concentration Althoughthe Langmuir model is a simple and excellent representative of iso-therm data this ion exchange equilibrium cannot be represented by

Table 4

Isotherm parameters obtained for removal of nitrate by IND NSSR resin

Solutions Langmuir isotherm parameters Mass action law isotherm parameters Initial nitrate sulfate andchloride concentrations

Q 0meqg

b

lmeqR2 RMSE

meqgqT meqg

k R2 RMSEmeqg

NO3minus

mglSO4minusminus

mglClminus

mgl

Sol 1 3223 2801 0997 0157 2713 6322 0997 0157 118 0 0Sol 2 3351 2834 0991 0066 2679 5001 0991 0066 87 0 0Sol 3 2549 5669 0998 0045 2130 6082 0999 0045 56 0 0Sol 4 2848 1230 0999 0044 2441 6991 0999 0044 120 0 100Sol 5 2455 0961 0992 0030 2129 7529 0999 0030 120 236 0Sol 6 3082 0521 0985 0051 2579 6156 0986 0051 126 240 0Groundwater 3495 0472 0940 0078 2814 5196 0941 0078 63 235 100All data 1028 1351 0190 0691 2548 5893 0962 0141 ndash ndash ndash

Rsup2 = 0997

RMSE=0157 meqg

Rsup2 = 0999

RMSE=0044 meqg

0

05

1

15

2

25

0 2 4 6 8 10 12 14

1 q e N O 3

1 q e N O 3

1Ce

Nitrate solution (sol

Nitrate+chloride solution (sol

Rsup2 = 0997 RMSE=0157 meqg


0

05

1

15

2

25

0 10 20 30 40

C0Ce

Nitrate solution (sol1)

Nitrate+chloride solution (sol4)

B

A

Fig 2 Comparison of Langmuir and mass action law models using batch experimentsdata of solutions 1 and 4 for (A) linear form of Langmuir model and (B) linear formof the mass action law model

Table 3

Batch experiments data with Shiraz groundwater

WV gl

C0meql

Cemeql

qemeql

0125 8870 0908 107302085 8870 0814 1099025 8870 0814 091303755 8870 0707 089605 8870 0688 0708

0751 8870 0501 07221 8870 0465 05771502 8870 0307 049020055 8870 0243 039925 8870 0236 032325025 8870 0200 03373252 8870 0164 02704 8870 0168 0219




such an adsorption system Thus the mass action law model is a betterrepresentative of ion exchange equilibrium data

Even though Eq (6) has been obtained for binary (nitrate and chlo-ride)systems it also works well in cases where there is sulfate in the ni-trate solution In the conducted experiments solutions 5 and 6 andShiraz groundwater contained sulfate and nitrate As Fig 3 shows alldata points (ie synthetic solutions 1 to 6 and Shirazgroundwater) fol-low the mass action model line very well This also can be underscored

by the obtained correlation coef 1047297cient of 096 con1047297rming satisfactoryagreement between the isotherm data and the isotherm model Thusit may be concluded that Eq (6) which is obtained by applying themass action law to binary systems can be applied to various initial ni-trate concentrations and with or without the presence of chloride sul-fate and bicarbonate in nitrate solutions The calculated averagevalues of k and qT forall equilibrium data in theexperiments were com-puted to be 589 and 255 meql respectively

The term C 0 in Eq (6) is equal to the sum of the nitrate sulfate andchloride ion concentrations In the case of Shiraz groundwater whichalso contains bicarbonate ion the preliminary results of adsorptionexperiments showed that the existence of bicarbonate has a negligi-ble effect on nitrate uptake by this resin Therefore bicarbonate

concentration was not included in C 0 This conclusion will be veri1047297edagain later in a column test using Shiraz groundwater

42 Column test results

421 Continuous modeling

The results of columns tests were used to determine the mathe-matical model (Eqs (10) and (11)) parameters The characteristicsof column experiments and their results are listed in Table 5 The ex-perimental data and the model prediction are also provided in Fig 4There was a close agreement between the simulated and experimen-tal breakthrough curves in several column experiments includingthose with different 1047298ow rates initial nitrate concentrations andthe presence of sulfate and chloride ions in the in1047298uent All computedcorrelation coef 1047297cients are above 096 indicating a high level of agreement (Table 5)This shows that the presented mathematicalmodel including axial dispersion and the mass action law isothermsuccessfully describes the adsorption process of an ion exchange col-umn packed with this resin ie nitrate selective resin IND NSSR under diverse operating conditions

The 1047297tted isotherm parameters for all cases of column experi-ments (qT and k) reported in Table 5 are in good agreement with

the batch experiment results The estimated values of maximum ionexchange capacity qT and the apparent equilibrium constant krange from 23 to 275 meqg and from 49 to 62 respectivelyThese estimations are close to each other and are also in good agree-ment with those obtained from the batch experiments This con1047297rmsthat the mass action law isotherm is a suitable model when dealingwith ion exchange processes in a packed bed column In fact a simplemass action isotherm equation obtained from equilibrium data can beused in dynamic modeling to predict breakthrough curves in diverseoperating conditions The optimized isotherm parameters and thedispersion coef 1047297cients obtained using nonlinear least square asexplained before are presented in Table 5

422 Effect of 1047298ow rateThe breakthrough curves of column tests of different 1047298ow rates

(Runs 1 to 3) can be found in Fig 4(A) This 1047297gure shows that thebreakthrough time generally occurred faster with higher 1047298ow rates(ie higher velocity) Moreover the adsorption capacity remains near-ly constant when the1047298ow rate changes from 211 to 069 lh (Table 5)The total adsorption capacity and breakthrough adsorption capacity of these experiments are all between 551 to 560 mg nitrateml resinand 455 to 469 mg nitratemlresin respectively It seems that the ni-trate adsorption capacity is not very sensitive to variations in1047298ow ve-locity This may signify that the rate of chemical reaction or selectivityand the sorption process are high and the assumption of local equilib-rium is correct

Rsup2= 09619

RMSE = 01406meqg

0

1

2

3

4

5

0 10 20 30 40 50 60

1 q e N O 3

C0Ce

Nitrate solution (sol 1 to 3)

Nitrate+chloride (sol 4)

Nitrate+sulfate (sol 5)

Nitrate+sulfate+chloride (sol 6)

Shiraz groundwater

Fig 3 Linear form of mass action isotherm model for all equilibrium data obtainedfrom batch experiments

Table 5

Measured characteristics of column experiments and model parameter predictions

Continuous no Run 1 Run 2 Run 3 Run 4 Run 5 Run 6 Run 7 Run 8

Flow rate (lh) 2114 1401 0693 2101 2091 2108 2095 2164NO3minus (mgl) 1194 1191 1204 895 604 1191 1202 637

SO4minus (mgl) 0 0 0 0 0 237 0 236

Clminus (mgl) 0 0 0 0 0 0 102 1005Breakthrough time (h) 362 546 1116 531 829 216 305 272Breakthrough capacity (mg nitrateml resin) 455 458 459 483 500 249 363 170Total capacity (mg nitrateml resin) 551 557 560 562 568 308 418 214Breakthrough bed volume (l) 767 766 774 1116 1735 456 638 589qT (meq nitrateg resin) 261 261 263 271 275 230 268 240K 50 54 60 62 49 55 61 58D (m2s)times105 1603 1071 05453 1585 1597 08878 0965 06688




The dispersion coef 1047297cient was estimated for each column exper-iment the results appearing in Table 5 An increase in the value of D(dispersion coef 1047297cient) was observed alongside a rise in the 1047298owvelocity It is known that the dispersion coef 1047297cient is described asfollows [46]

D frac14

Dm thorn

α u

eth19

THORN

Here Dm is the molecular diffusion coef 1047297cient u is the interstitial1047298ow velocity and α is the dispersivity coef 1047297cient The molecular dif-fusion can be ignored in comparison with α u in these 1047298ow velocities[46] Therefore the value of α was calculated to be 147 cm by linerplot of D versus u which is not shown here

423 Effect of initial nitrate concentration

The effectof in1047298uentnitrateconcentrationon adsorption capacitywas

investigated using Column tests Run 1 Run 4 and Run 5 ( Fig 4(B))The breakthrough time and the treated volume of water decreasedwith the rise in in1047298uent concentration (Table 5) This indicates thatthe resin bed was saturated faster by nitrate at higher concentrationsdue to higher nitrate loading rates As reported in Table 5 the totalamount of adsorbed nitrate obtained from these experiments wasin the range of 551 to 568 mg nitrateml resin as initial nitrate concen-tration decreased from 1194 to 604 mgl It can be deduced that initialnitrate concentration has a negligible effect on the total adsorptioncapacity

Table 5 shows that the estimated values of D for different in1047298uentconcentrations are between 1585times 10minus5 to 1603times10minus5 m2s whichare nearly the same The average value of this coef 1047297cient for differentnitrate concentrations is equal to 1595times10minus5 m2s Therefore thedispersion coef 1047297cient is not in1047298uenced by initial nitrate concentra-tion The calculated dispersion coef 1047297cient in this research is compara-ble to those reported by other researcher [42]

424 Effect of competitive ions (chloride and sulfate)

Fig 4(C) shows the effect of competitive ions on nitrate adsorp-tion (Runs 1 6 and 7) The presence of both sulfate and chloridein1047298uenced the nitrate breakthrough curve and reduced the breaktime and adsorption capacity (Table 5)The total adsorption capacityof this resin was found to be between 551 and 568 mg nitratemlresin when only nitrate is present in the solution (Runs 1 to 5) Inthe cases where there was sulfate (Run 6) or chloride (Run 7) alongwith nitrate in the solution the adsorption capacity was reduced to308 and 418 mg nitrateml resin respectively Thus it can be con-cluded that a portion of resin capacity is occupied by sulfate and chlo-

ride ions In addition no nitrate peak was observed during these testslending credence to the superior selectivity of nitrate in comparisonwith sulfate

According to Table 5 the dispersion coef 1047297cient of nitrate wasin1047298uenced by the presence of chloride and sulfate in the aqueous so-lution In these cases smaller values were obtained for this coef 1047297-cient Dispersion coef 1047297cient was computed to be 0965times10minus5 m2sand 08878times10minus5 m2s for Run 6 and Run 7 which contained chlo-ride and sulfate in nitrate solutions respectively

time (h)

C C 0

C C 0

C C 0

0 40 80 120 160 200 2400

02

04

06

08

1

12

211 lh Mod

211 lh Exp (run1)

140 lh Mod

140 lh Exp (run2)

069 lh Mod

069 lh Exp (run3)

time (h)

0 40 80 120 160 1800

02

04

06

08

1

12

1194 mgl Mod

1194 mgl Exp (run1)

895 mgl Mod

895 mgl Exp (run4)

604 mgl Mod

604 mgl Exp (run5)

time (h)0 20 40 60 80 90

0

02

04

06

08

1

12

NO3- Mod

NO3- Exp (run1)

NO3-+Cl- Mod

NO3-+Cl- Exp (run7)

NO3-+SO4

- Mod

NO3-+SO4

- Exp (run6)

A

B

C

Fig 4 Measured and modeled nitrate breakthrough curves for (A) different 1047298ow rate(B) different in1047298uent concentration and (C) presence of sulfate and chloride

time (h)

C C 0

0 40 80 120 160 1850

02

04

06

08

1

12

604 mgl Mod

604 mgl Exp (run5)

Groundwater Mod

Groundwater Exp (run8)

Fig 5 Measured and modeled nitrate breakthrough curves for Shiraz groundwater

(Run 8) and synthetic solution which contained only nitrate ions (Run 5)




425 Nitrate removal from Shiraz groundwater

The results of nitrate removal from Shiraz groundwater (Run 8)and the synthetic solution which contained only nitrate ions (Run5) are compared in Fig 5 Nitrate in1047298uent concentration and the1047298ow rate in both experiments were the same The column experimentusing Shiraz groundwater was saturated muchfaster than the columntest with the synthetic solution The breakthrough time of Shirazgroundwater column tests was 272 h while this time was 829 h for

the column test with the synthetic solution (Run 5) Also a smallerslope (smaller dispersion coef 1047297cient) was observed for the break-through curve of the column test using Shiraz groundwater In thecase of the groundwater the dispersion coef 1047297cient was computed tobe 06688times10minus5 m2s in comparison with 1597times 10minus5 m2s for thesynthetic solution The presence of competitive ions in Shiraz ground-water decreased the nitrate adsorption capacity from 568 to 214 mgnitrateml resin (Table 5)

Fig 6 shows the breakthrough curves of nitrate sulfate chlorideand bicarbonate in a second column test using Shiraz groundwaterwith a 1047298ow rate of 069 lh At 1047297rst both nitrate and sulfate wereadsorbed onto the resin particles and chloride was released due tothe higher selectivity of the former anions in comparison with chlo-ride As more water passed through the resin bed sulfate ions sud-denly appeared in the ef 1047298uent at higher concentrations than that of the in1047298uent water The maximum ef 1047298uent concentration of sulfatewas 112times that ofthe in1047298uent concentration In fact the adsorbedsulfate ions were released with the nitrate ions being replaced Thisphenomenon shows that nitrate was preferentially bound to thisresin with a suf 1047297ciently high selectivity compared to sulfate Also asmall amount of bicarbonate was adsorbed at the beginning of therun because of the high number of exchangeable sites at that timeHowever after a few minutes the bicarbonate concentration at thecolumn outlet was equal to the inlet concentration This indicatesthat resin capacity is not reduced as a result of the presence of bicarbonate

426 Sensitivity analysis

Sensitivity analysis was performed on the results of the column

test (Run 1) with a nitrate in1047298uent concentration of 120 mgl a beddepth of 205 cm and a 1047298ow discharge of 211 lh The effect of axialdispersion coef 1047297cient D on the shape of the breakthrough curve ispresented in Fig 7(A) The value of D varied between 8 times lowerand 8 times higher than the optimized value (1603times10minus5 m2s) Al-though the reduction in D caused a steeper slope in the breakthroughcurve the break time was only slightly changed On the other handthe increase in D reduced the break point and the slope of

breakthrough curve Therefore a rise in D has a greater impact onthe sensitivity of the model than does a decrease in the value of thisvariable It is worth mentioning that a variation in D between twotimes higher and 2 times lower than the base value has a negligibleeffect on the breakthrough curve

The effects of change in the isotherm parameters k and qT areshown in Fig 7(B) and (C) respectively It was found that values of k exceeding three had an insigni1047297cant effect on the shape of thebreakthrough curve while values below three in1047298uenced the slope

of the breakthrough curve noticeably Any change applied to qT led

time (h)

c o n c e n t r a t i o n ( m g l )

0 40 80 120 1600

100

200

300

400

Sulfate

Chloride

Bicarbonate

Nitrate

Fig 6 Column breakthrough pro1047297les for nitrate sulfate and bicarbonate using Shiraz

groundwater (Run 9)

B

C

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12

D=1603x10-5 m2 sD=12817x10-5 m2 sD=6408x10-5 m2 sD=3205x10-5 m2 sD=0801x10-5 m2 sD=0200x10-5 m2 s

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12

k=15k=2

k=3k=5k=10

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12

qT=22 meqlqT=24 meqlqT=26 meqlqT=28 meqlqT=30 meql

A

Fig 7 Effect of variation in model parameters values on breakthrough pro1047297le based oncolumn test Run 1 (A) dispersion coef 1047297cient D (B) apparent equilibrium constant k(C) Maximum adsorption capacity qT




to a shift in the obtained values for breakthrough time whereas itsimpact on the slope of the breakthrough curve was not signi1047297cantAmong these three parameters the selected mathematical modelhad the lowest sensitivity to variations in the values of k ie thevalue of chemical reaction

5 Conclusions

Nitrate removal from different aqueous solutions in both batchand continuous systems was studied using a nitrate selective ion ex-change resin called IND NSSR The results showed that this resin is aneffective adsorbent for nitrate removal from both synthetic solutionsand Shiraz groundwater speci1047297cally in the presence of sulfate Theaverage maximum adsorption capacity obtained during the testswas 255 meqg The variations in 1047298ow rate and initial nitrate concen-tration had a negligible effect on the total nitrate adsorption capacityHowever resin capacity was reduced in the presence of chloride andsulfate Moreover the computed dispersion coef 1047297cient was not in1047298u-enced by the initial nitrate concentration Nonetheless comparativelysmaller values were obtained for this coef 1047297cient in the presence of competitive ions

The equilibrium distribution of nitrate ions between resin and liq-

uid phases was modeled by both an adsorption isotherm (the Lang-muir isotherm) and the mass action law isotherm It was found thatequilibrium data can be described well with both models HoweverLangmuir parameters especially b constant depend on the solutioncondition such as nitrate sulfate and chloride concentrations in solu-tions On the other hand it was found that a simple general modelbased on the mass action law model can be used to simulate ion ex-change equilibrium under diverse operating conditions

The advection dispersion equation including the adsorption term(Eq (8)) was considered as a mathematical model to simulate the ionexchange process in columns packed with ion exchange resins Themass action law isotherm was used to simulate the nitrate adsorptionterm in this equation The 1047297nite difference method reduced to theCrankndashNicholson scheme was used to numerically solve the above

equation The isotherm parameters and dispersion coef 1047297cient werecomputed by minimizing an error function (Eq (18)) The model pre-dictions of the breakthrough curves were in a very good agreementwith the experimental data at different 1047298ow rates in1047298uent nitrate con-centrations and thepresence of sulfate and chloride ions in thein1047298uentThe mass action isotherm parameters obtained from column experi-ments were con1047297rmed with those obtained from batch experimentsConsequently the column behavior can be predicted from the batchequilibrium data by using the mass action isotherm

Sensitivity analysis was performed on the mathematical modelparameters It was obtained that the variation of D ie dispersion co-ef 1047297cient between two times higher and lower than the base valuewas negligible Among the parameters optimized in the modelingthe selected mathematical model has the lowest sensitivity to thevalues of k ie the value of apparent chemical reaction

References

[1] C Della Rocca V Belgiorno S Mericcedil Overview of in-situ applicable nitrate re-moval processes Desalination 204 (2007) 46ndash62

[2] PC Mishra RK Patel Use of agricultural waste for the removal of nitratendash

nitrogenfrom aqueous medium J Environ Manage 90 (2009) 519ndash522[3] A Kapoor T Viraraghavan Nitrate removal fromdrinkingwatermdash review J Environ

Eng 123 (1997) 371ndash380[4] JH Winneberger Nitrogen Public Health and the Environment Ann Arbor Sci-

ence Publishers Inc Ann Arbor Michigan 1982[5] S Samatya N Kabay U Yuksel M Arda M Yuksel Removal of nitrate from aque-

ous solution by nitrate selective ion exchange resins React Funct Polym 66(2006) 1206ndash1214

[6] QWang CFeng Y Zhao CHaoDenitri1047297cationof nitrate contaminated groundwa-ter with a 1047297ber-based bio1047297lm reactor Bioresour Technol 100 (2009) 2223ndash2227

[7] wwwabfa_shirazcom

[8] D Hendricks Water Treatment Unit Processes Taylor and Francis Group BocaRaton 2006

[9] M Shrimali KP Singh New methods of nitrate removal from water EnvironPollut 112 (2001) 351ndash359

[10] C Della Rocca V Belgiorno S Meric An heterotrophicautotrophic denitri1047297cation(HAD) approach for nitrate removal from drinking water Process Biochem 41(2006) 1022ndash1028

[11] S Chatterjee S HanWoo Theremoval of nitratefrom aqueous solutions by chitosanhydrogel beads J Hazard Mater 164 (2009) 1012ndash1018

[12] JJ Schoeman A Steyn Nitrate removal with reverse osmosis in a rural areainSouth Africa Desalination 155 (2003) 15ndash26

[13] A Elmldaouli F Elhannouni MA MenkouchiSahli L Chay H Elabbassi M HafsiD Largeteau Pollution of nitrate in Moroccan ground water removal by electro-dialysis Desalination 136 (2001) 325ndash332

[14] M Boumediene D Achour Denitri1047297cation of the underground waters by speci1047297cresin exchange of ion Desalination 168 (2004) 187ndash194

[15] KJ Reddy J Lin Nitrate removal from groundwater using catalytic reductionWater Res 34 (3) (2000) 995ndash1001

[16] S Mossa Hosseini B Ataie-Ashtiani M Kholghi Nitrate reduction by nano-FeCuparticles in packed column Desalination 276 (2011) 214ndash221

[17] J Schick P Caullet J-L Paillaud J Patarin C Mangold-CallarecNitratesorptionfrom water on a Surfactant-Modi1047297ed Zeolite Fixed-bed column experimentsMicroporous Mesoporous Mater 142 (2011) 549ndash556

[18] Y Zhan J Lin Z Zhu Removal of nitrate from aqueous solution usingcetylpyridinium bromide (CPB) modi1047297ed zeolite as adsorbent J HazardMater 186 (2011) 1972ndash1978

[19] X Xing B-Y Gao Q-Q Zhong Q-Y Yue Q Li Sorption of nitrate onto amine-crosslinked wheat straw characteristics column sorption and desorption prop-erties J Hazard Mater 186 (2011) 206 ndash211

[20] BU Bae YH Jung WW Han HS Shin Improved brine recycling during nitrate

removal using ion exchange Water Res 36 (2002) 3330ndash3340[21] MB Jackson BA Bolto Effect of ion-exchange resin structure on nitrate selectiv-

ity React Polym 12 (1990) 227ndash229[22] J Dron A Dodi Comparison of adsorption equilibrium models for the study of

CL minus NO3minus and SO42minus removal from aqueous solutions by an anion exchangeresin J Hazard Mater 190 (2011) 300 ndash307

[23] SN Milmile JV Pande S Karmakar A Bansiwal T Chakrabarti RB BiniwaleEquilibrium isotherm and kinetic modeling of the adsorption of nitrates byanion exchange Indion NSSR resin Desalination 276 (2011) 38 ndash44

[24] VS Soldatov VI Sokolova GV Medyak AA Shunkevich ZI Akulich Binary ionexchange equilibria in systems containing NO3ndash Clminus and SO4

2minus on 1047297brous anionexchangers with tetraalkylammomium groups React Funct Polym 67 (2007)1530ndash1539

[25] JP Hoek WF Hoek A Klapwijk Nitrate removal from ground water mdash use of anitrate selective resin and a low concentrated regenerant Water Air Soil Pollut37 (1988) 41ndash53

[26] M Chabani A Bensmaili Kinetic modeling of the retention of nitrates by Amber-lite IRA 410 Desalination 185 (2005) 509ndash515

[27] Y Berbar M Amara H Kerdjoudj Anion exchange resin applied to a separationbetween nitrate and chloride ions in the presence of aqueous soluble polyelectro-lyte Desalination 223 (2008) 238ndash242

[28] J Beltran de Heredia JR Domınguez Y Cano I Jimenez Nitrate removal fromgroundwater using Amberlite IRN-78 modeling the system Appl Surf Sci 252(2006) 6031ndash6035

[29] M Chabani A Amrane A Bensmaili Kinetic modelling of the adsorption of ni-trates by ion exchange resin Chem Eng J 125 (2006) 111 ndash117

[30] B Fonseca A Teixeira H Figueiredo T Tavares Modelling of the Cr(VI) transportin typical soils of the North of Portugal J Hazard Mater 167 (2009) 756 ndash762

[31] AA Zagorodni Ion Exchange Materials Properties and Applications Elsevier BV2007

[32] MWH Water Treatment Principle and Design second ed John Wily amp Son Inc2005

[33] R Petrus JK Warcho Heavy metal removal by clinoptilolite An equilibriumstudy in multi-component systems Water Res 39 (2005) 819ndash830

[34] R PetrusJ Warchoł Ion exchange equilibria between clinoptilolite and aqueous so-lutions of Na +Cu2+ Na+ Cd2+ and Na+Pb2+ Microporous MesoporousMater 61 (2003) 137ndash146

[35] O Hamdaoui E Naffrechoux Modeling of adsorption isotherms of phenol andchlorophenols onto granular activated carbon Part I Two-parameter modelsand equations allowing determination of thermodynamic parameters J HazardMater 147 (2007) 381ndash394

[36] O Hamdaoui E Naffrechoux Modeling of adsorption isotherms of phenol andchlorophenols onto granular activated carbon Part II Models with more thantwo parameters J Hazard Mater 147 (2007) 401ndash411

[37] B Alyuumlz S Veli Kinetics and equilibrium studies for the removal of nickel and zincfromaqueous solutionsby ionexchange resins J Hazard Mater 167(2009)482ndash488

[38] Ouml Can D Balkoumlse S Uumllkuuml Batch and column studies on heavy metal removalusing a local zeolitic tuff Desalination 259 (2010) 17 ndash21

[39] S Ben-Shebil A Alkan-Sungur AROzdural Fixed-bedion exchange columnsoper-ating under non-equilibrium conditions estimation of mass transfer properties vianon-equilibrium modeling React Funct Polym 67 (2007) 1540ndash1547

[40] O Hamdaoui Removal of copper (II) from aqueous phase by Purolite C100-MBcation exchange resin in 1047297xed bed columns modeling J Hazard Mater 161(2009) 737ndash746

[41] FC Gazola MR Pereira MASD Barros EA Silva PA Arroyo Removal of Cr3+in 1047297xed bed using zeolite NaY Chem Eng J 117 (2006) 253 ndash261




[42] N Selvaraju S Pushpavanam Adsorption characteristics on sand and brick bedsChem Eng J 147 (2009) 130ndash138

[43] C Zheng GD Bennett Applied Contaminant Transport Modeling John Wiley andSons Inc New York 2002

[44] D PeacemanFundamental of Numerical ReservoirSimulationElsevierAmsterdam1977

[45] NZ Misak Some aspects of the application of adsorption isotherms to ion ex-change reactions React Funct Polym 43 (2000) 153ndash164

[46] RG Charbeneau Groundwater Hydraulics and Pollutant Transport Prentice-HallInc New Jersey 2000




To the best of ourknowledgemost studies onnitrate removal by ionexchange resins have been performed in batch experiments and only afew have been reported in 1047297xed bed systems [19212225ndash29] In gen-eral batch experiments are used to determine the equilibrium isothermand kinetic of nitrate removal onto resin particles One disadvantage of these experiments is that theydo not give informationabout thehydro-dynamic parameters of 1047297xed bed columns such as the dispersioncoef 1047297-cient [30] Another drawback of batch processes is their discontinuity

and the need to perform complicated phase separation operations[31] Furthermore little attention has been paid to the numerical solu-tion of nitrate removal models in a 1047297xed bed column packed with ionexchange resins even though a suitable numerical solution can helpto reduce the number of experiments associated with new operatingconditions A noveland well-researched model can be used as a reliablesolution to design optimize and predict the breakthrough curves of 1047297xed bed columns in real water treatment processes

Both empirical and more theoretical isotherm models have beendeveloped to describe ion exchange equilibrium [32ndash34] Several em-pirical and semi-empirical isotherm models can be found in the liter-ature such as the Langmuir and Freundlich equations to explain ionexchange equilibrium [3536] Several researchers have used thesemethods to illustrate the equilibrium of the ion exchange process[52937ndash41] Theoretical isotherm models are basically based on thelaw of mass action In these methods the ion exchange process istreated as a chemical reaction while the concept of membrane theoryand thermodynamic description are used to illustrate the real behav-ior of ions in both the solution and resin phases [3132] It is importantto note that few comparisons have been done between empirical andtheoretical equilibrium models for ion exchange resins

The aim of the present research is to study and model the removalof nitrate from synthetic solutions and groundwater through the useof a selective ion exchange resin called IND NSSR in both batch and1047297xed bed systems The effects of 1047298ow rate initial nitrate concentra-tion and the existence of competitive ions such as sulfate on nitrateremoval were also investigated Afterwards the equilibrium datawere simulated by an adsorption isotherm and the mass action lawand the results were compared to each other under different operat-

ing conditions Then a numerical model was developed to solve theadvection dispersion equation with adsorption in columns The ad-sorption term was simulated using the mass action law isothermModel parameters were estimated and compared to those obtainedin equilibrium experiments Finally sensitivity analysis was per-formed to determine the effect of model parameters on breakthroughcurve shape

2 Experimental

21 Materials

A nitrate selective ion exchange resin named IND NSSR wasobtained from Ion Exchange India LTD This material is a macroporous

strongly basic anion resin that is suitable for the removal of nitratefrom water The effective sizes of the particles range from 04 to05 mm containing exchangeable chloride ions The unique advantageof this resin is that it has more af 1047297nity for nitrate ions in comparisonwith other existing anions Before use the resin particles werewashed with distilled water in order to remove any adhering dirtThe resin was dried at an oven temperature of 60 degC for the batch ex-periments Synthetic solutions were prepared by dissolving differentamounts of NaNO3 Na2SO4 and NaCl in distilled water in order toreach the desired concentrations The groundwater was obtainedfrom one of the drinking wells of Shiraz Iran The characteristics of this water are summarized in Table 1

Nitrate ions were analyzed using a UV spectrophotometer instru-ment (HACH DR5000) at a wavelength of 220 nm Before measure-

ment 50 ml of samples was acidi1047297ed with 1 ml of 10 N HCl in order

to eliminate the interface of hydroxide and bicarbonate ions The pHof the analyzed solution was 2plusmn01 Sulfate and chloride ions wereanalyzed using Ion Chromatography (Metrohm 761)

22 Batch mode equilibrium experiments

In order to obtain the ion exchange equilibrium data batch ex-periments were carried out in duplicate with respect to Shirazgroundwater and various synthetic solutions including solutionswith different initial nitrate concentrations and solutions containingsulfate and chloride ions A speci1047297ed amount of resin (0025 to 08 g)was added to glass bottles containing 200 ml of nitrate solution Thebottles were sealed and placed in a temperature-controlled rotatingshaker for 24 h to reach equilibrium The temperature was kept at aconstant 20 degC with a maximum tolerance of 01 degC The ion concen-tration uptake to solid phase wascomputedusing thefollowing massbalance equation

qe frac14 C 0minusC eeth THORNV

m eth1THORN

where qe (mgg) is the solid phase equilibrium adsorption concentra-tion C 0 and C e (mgl) are the initial and equilibrium liquid phase ionconcentrations and V (l) and m (g) are the volume and the resinmass respectively

23 Column mode experiments

Column tests were performed using glass columns with an inter-nal diameter of 36 cm A schematic diagram of the column setupused for the 1047297xed bed studies is shown in Fig 1 All experimentswere conducted at a constant temperature of 20plusmn1 degC The nitratesolution was passed through the resin bed in an upward directionto ensure a completely saturated bed [42] A peristaltic pump wasused to maintain a constant1047298ow rate during the experiments The ex-

periments were carried out at different conditions of 1047298ow rates in1047298u-ent concentrations and the presence of sulfate and chloride ions Theresin bed height for all tests was set at 205 cm with a tolerance of 015 cm The column experiments were continued until the completesaturation of the resins was achieved The column void portion iebed porosity was estimated through 1047297rst moment analysis of pulseloading experiments using NaCl as a tracer The effect of 1047298ow rate onnitrate adsorption was investigated by varying the 1047298ow rate from 069to 211 lh at a constant in1047298uent nitrate concentration of 120 mgl(Runs 1 to 3) Moreover the effect of the in1047298uent nitrate concentrationon the sorption performance of nitrate was examined at the values of 895 and 604 mgl (Runs 4 and 5) Run 6 and Run 7 were arranged inorder to inspect the in1047298uence of sulfate and chloride ions on the remov-al of nitrate Finally column tests were performed to investigate nitrate

removal from Shiraz groundwater (Runs 8 and 9)

Table 1

Composition of Shiraz groundwater

Species Concentration (mgl)

Fminus 076plusmn0007Clminus 1003plusmn0518SO4minusminus 236plusmn0323

HCO3minus 3603plusmn224



NH3 008plusmn01Ca++ 1187plusmn271Mg++ 681plusmn0763Na+ 804plusmn0844K+ 28plusmn0128TDS 884plusmn525pH 753plusmn008




3 Modeling



qeNO3 frac14

Q 0 b C eNO3

1 thorn b C eNO3

eth2THORN



qeNO3

frac14 1Q 0 b

1C eNO3

thorn 1Q 0

eth3THORN






k frac14C eCl qeNO3

qeCl C eNO3

eth5THORN



qeNO3 frac14

k qT C eNO3


eth6THORN






1

qeNO3

frac14 1

k qT

C 0

C eNO3

thorn kminus1

k qT

eth7THORN



partC

partt frac14 D

part2C

part x2minusu

partC

part xminusρb

n

partq

partt eth8THORN



partq

partt frac14 partq

partC

partC

partt eth9THORN


RpartC

partt frac14 D

part2C

part x2minusu

partC

part x eth10THORN


R frac14 1 thornρb

n

kC 0qT


eth11THORN


RpartC

partT frac14

D

uL

part2C

part X 2minuspartC

part X eth12THORN















Rni



( D


nithorn1minus2C

ni thorn C

niminus1

minus 1Δ X



niminus1minusαC

ni

)

thornω(

DuL Δ X eth THORN2


nthorn1i thorn C

nthorn1iminus1

minus 1Δ X




nthorn1i

h i)

eth16THORN


2C part X 2




P eg frac14 uLΔ X

D eth17THORN




RMSE frac14


n


2

n

v uuut eth18THORN








Table 2


Syntheticsolution

WV gl

C 0meql

C emeql

qemeqg

Syntheticsolution

WV gl

C 0meql

C emeql

qemeqg

1 0101 1902 1596 3032 3 15 0897 0050 05641 0180 1902 1407 2757 3 2 0897 0036 04311 0219 1902 1345 2549 4 0127 4873 1658 19981 0332 1902 1147 2275 4 0253 4873 1454 18071 05 1902 0833 2139 4 0501 4873 1114 1590

1 1 1902 0357 1545 4 10065 4873 0664 12381 15 1902 0200 1140 4 1753 4873 0357 08861 2 1902 0136 0892 4 2501 4873 0243 06671 25 1902 0102 0731 4 4003 4873 0150 04401 3 1902 0086 0618 5 0126 6795 1739 16042 01 1407 1157 2506 5 0250 6795 1579 14482 015 1407 1049 2385 5 0502 6795 1264 13502 025 1407 0835 2288 5 1003 6795 0857 10812 05 1407 0485 1843 5 1752 6795 0518 08122 1 1407 0193 1214 5 2501 6795 0357 06332 15 1407 0114 0862 5 4002 6795 0221 04302 2 1407 0079 0664 6 0207 9871 1683 15462 25 1407 0071 0537 6 0376 9871 1478 13982 3 1407 0057 0455 6 0753 9871 1157 11243 01 0897 0685 2113 6 1504 9871 0750 08333 015 0897 0604 1951 6 2 9871 0600 07013 025 0897 0428 1873 6 25 9871 0469 0613

3 05 0897 0214 1365 6 325 9871 0364 05043 1 0897 0086 0811










Table 4



Q 0meqg

b

lmeqR2 RMSE

meqgqT meqg

k R2 RMSEmeqg

NO3minus

mglSO4minusminus

mglClminus

mgl


Rsup2 = 0997

RMSE=0157 meqg

Rsup2 = 0999

RMSE=0044 meqg

0

05

1

15

2

25

0 2 4 6 8 10 12 14

1 q e N O 3

1 q e N O 3

1Ce





0

05

1

15

2

25

0 10 20 30 40

C0Ce



B

A


Table 3


WV gl

C0meql

Cemeql

qemeql

0125 8870 0908 107302085 8870 0814 1099025 8870 0814 091303755 8870 0707 089605 8870 0688 0708

0751 8870 0501 07221 8870 0465 05771502 8870 0307 049020055 8870 0243 039925 8870 0236 032325025 8870 0200 03373252 8870 0164 02704 8870 0168 0219
















Rsup2= 09619

RMSE = 01406meqg

0

1

2

3

4

5

0 10 20 30 40 50 60

1 q e N O 3

C0Ce





Shiraz groundwater


Table 5




SO4minus (mgl) 0 0 0 0 0 237 0 236






D frac14

Dm thorn

α u

eth19

THORN










time (h)

C C 0

C C 0

C C 0

0 40 80 120 160 200 2400

02

04

06

08

1

12

211 lh Mod

211 lh Exp (run1)

140 lh Mod

140 lh Exp (run2)

069 lh Mod

069 lh Exp (run3)

time (h)

0 40 80 120 160 1800

02

04

06

08

1

12

1194 mgl Mod

1194 mgl Exp (run1)

895 mgl Mod

895 mgl Exp (run4)

604 mgl Mod

604 mgl Exp (run5)

time (h)0 20 40 60 80 90

0

02

04

06

08

1

12

NO3- Mod

NO3- Exp (run1)

NO3-+Cl- Mod

NO3-+Cl- Exp (run7)

NO3-+SO4

- Mod

NO3-+SO4

- Exp (run6)

A

B

C


time (h)

C C 0

0 40 80 120 160 1850

02

04

06

08

1

12

604 mgl Mod

604 mgl Exp (run5)

Groundwater Mod

















time (h)


0 40 80 120 1600

100

200

300

400

Sulfate

Chloride

Bicarbonate

Nitrate


groundwater (Run 9)

B

C

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12

k=15k=2

k=3k=5k=10

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


A






5 Conclusions







References
























































3 Modeling



qeNO3 frac14

Q 0 b C eNO3

1 thorn b C eNO3

eth2THORN



qeNO3

frac14 1Q 0 b

1C eNO3

thorn 1Q 0

eth3THORN






k frac14C eCl qeNO3

qeCl C eNO3

eth5THORN



qeNO3 frac14

k qT C eNO3


eth6THORN






1

qeNO3

frac14 1

k qT

C 0

C eNO3

thorn kminus1

k qT

eth7THORN



partC

partt frac14 D

part2C

part x2minusu

partC

part xminusρb

n

partq

partt eth8THORN



partq

partt frac14 partq

partC

partC

partt eth9THORN


RpartC

partt frac14 D

part2C

part x2minusu

partC

part x eth10THORN


R frac14 1 thornρb

n

kC 0qT


eth11THORN


RpartC

partT frac14

D

uL

part2C

part X 2minuspartC

part X eth12THORN















Rni



( D


nithorn1minus2C

ni thorn C

niminus1

minus 1Δ X



niminus1minusαC

ni

)

thornω(

DuL Δ X eth THORN2


nthorn1i thorn C

nthorn1iminus1

minus 1Δ X




nthorn1i

h i)

eth16THORN


2C part X 2




P eg frac14 uLΔ X

D eth17THORN




RMSE frac14


n


2

n

v uuut eth18THORN








Table 2


Syntheticsolution

WV gl

C 0meql

C emeql

qemeqg

Syntheticsolution

WV gl

C 0meql

C emeql

qemeqg

1 0101 1902 1596 3032 3 15 0897 0050 05641 0180 1902 1407 2757 3 2 0897 0036 04311 0219 1902 1345 2549 4 0127 4873 1658 19981 0332 1902 1147 2275 4 0253 4873 1454 18071 05 1902 0833 2139 4 0501 4873 1114 1590

1 1 1902 0357 1545 4 10065 4873 0664 12381 15 1902 0200 1140 4 1753 4873 0357 08861 2 1902 0136 0892 4 2501 4873 0243 06671 25 1902 0102 0731 4 4003 4873 0150 04401 3 1902 0086 0618 5 0126 6795 1739 16042 01 1407 1157 2506 5 0250 6795 1579 14482 015 1407 1049 2385 5 0502 6795 1264 13502 025 1407 0835 2288 5 1003 6795 0857 10812 05 1407 0485 1843 5 1752 6795 0518 08122 1 1407 0193 1214 5 2501 6795 0357 06332 15 1407 0114 0862 5 4002 6795 0221 04302 2 1407 0079 0664 6 0207 9871 1683 15462 25 1407 0071 0537 6 0376 9871 1478 13982 3 1407 0057 0455 6 0753 9871 1157 11243 01 0897 0685 2113 6 1504 9871 0750 08333 015 0897 0604 1951 6 2 9871 0600 07013 025 0897 0428 1873 6 25 9871 0469 0613

3 05 0897 0214 1365 6 325 9871 0364 05043 1 0897 0086 0811










Table 4



Q 0meqg

b

lmeqR2 RMSE

meqgqT meqg

k R2 RMSEmeqg

NO3minus

mglSO4minusminus

mglClminus

mgl


Rsup2 = 0997

RMSE=0157 meqg

Rsup2 = 0999

RMSE=0044 meqg

0

05

1

15

2

25

0 2 4 6 8 10 12 14

1 q e N O 3

1 q e N O 3

1Ce





0

05

1

15

2

25

0 10 20 30 40

C0Ce



B

A


Table 3


WV gl

C0meql

Cemeql

qemeql

0125 8870 0908 107302085 8870 0814 1099025 8870 0814 091303755 8870 0707 089605 8870 0688 0708

0751 8870 0501 07221 8870 0465 05771502 8870 0307 049020055 8870 0243 039925 8870 0236 032325025 8870 0200 03373252 8870 0164 02704 8870 0168 0219
















Rsup2= 09619

RMSE = 01406meqg

0

1

2

3

4

5

0 10 20 30 40 50 60

1 q e N O 3

C0Ce





Shiraz groundwater


Table 5




SO4minus (mgl) 0 0 0 0 0 237 0 236






D frac14

Dm thorn

α u

eth19

THORN










time (h)

C C 0

C C 0

C C 0

0 40 80 120 160 200 2400

02

04

06

08

1

12

211 lh Mod

211 lh Exp (run1)

140 lh Mod

140 lh Exp (run2)

069 lh Mod

069 lh Exp (run3)

time (h)

0 40 80 120 160 1800

02

04

06

08

1

12

1194 mgl Mod

1194 mgl Exp (run1)

895 mgl Mod

895 mgl Exp (run4)

604 mgl Mod

604 mgl Exp (run5)

time (h)0 20 40 60 80 90

0

02

04

06

08

1

12

NO3- Mod

NO3- Exp (run1)

NO3-+Cl- Mod

NO3-+Cl- Exp (run7)

NO3-+SO4

- Mod

NO3-+SO4

- Exp (run6)

A

B

C


time (h)

C C 0

0 40 80 120 160 1850

02

04

06

08

1

12

604 mgl Mod

604 mgl Exp (run5)

Groundwater Mod

















time (h)


0 40 80 120 1600

100

200

300

400

Sulfate

Chloride

Bicarbonate

Nitrate


groundwater (Run 9)

B

C

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12

k=15k=2

k=3k=5k=10

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


A






5 Conclusions







References

























































Rni



( D


nithorn1minus2C

ni thorn C

niminus1

minus 1Δ X



niminus1minusαC

ni

)

thornω(

DuL Δ X eth THORN2


nthorn1i thorn C

nthorn1iminus1

minus 1Δ X




nthorn1i

h i)

eth16THORN


2C part X 2




P eg frac14 uLΔ X

D eth17THORN




RMSE frac14


n


2

n

v uuut eth18THORN








Table 2


Syntheticsolution

WV gl

C 0meql

C emeql

qemeqg

Syntheticsolution

WV gl

C 0meql

C emeql

qemeqg

1 0101 1902 1596 3032 3 15 0897 0050 05641 0180 1902 1407 2757 3 2 0897 0036 04311 0219 1902 1345 2549 4 0127 4873 1658 19981 0332 1902 1147 2275 4 0253 4873 1454 18071 05 1902 0833 2139 4 0501 4873 1114 1590

1 1 1902 0357 1545 4 10065 4873 0664 12381 15 1902 0200 1140 4 1753 4873 0357 08861 2 1902 0136 0892 4 2501 4873 0243 06671 25 1902 0102 0731 4 4003 4873 0150 04401 3 1902 0086 0618 5 0126 6795 1739 16042 01 1407 1157 2506 5 0250 6795 1579 14482 015 1407 1049 2385 5 0502 6795 1264 13502 025 1407 0835 2288 5 1003 6795 0857 10812 05 1407 0485 1843 5 1752 6795 0518 08122 1 1407 0193 1214 5 2501 6795 0357 06332 15 1407 0114 0862 5 4002 6795 0221 04302 2 1407 0079 0664 6 0207 9871 1683 15462 25 1407 0071 0537 6 0376 9871 1478 13982 3 1407 0057 0455 6 0753 9871 1157 11243 01 0897 0685 2113 6 1504 9871 0750 08333 015 0897 0604 1951 6 2 9871 0600 07013 025 0897 0428 1873 6 25 9871 0469 0613

3 05 0897 0214 1365 6 325 9871 0364 05043 1 0897 0086 0811










Table 4



Q 0meqg

b

lmeqR2 RMSE

meqgqT meqg

k R2 RMSEmeqg

NO3minus

mglSO4minusminus

mglClminus

mgl


Rsup2 = 0997

RMSE=0157 meqg

Rsup2 = 0999

RMSE=0044 meqg

0

05

1

15

2

25

0 2 4 6 8 10 12 14

1 q e N O 3

1 q e N O 3

1Ce





0

05

1

15

2

25

0 10 20 30 40

C0Ce



B

A


Table 3


WV gl

C0meql

Cemeql

qemeql

0125 8870 0908 107302085 8870 0814 1099025 8870 0814 091303755 8870 0707 089605 8870 0688 0708

0751 8870 0501 07221 8870 0465 05771502 8870 0307 049020055 8870 0243 039925 8870 0236 032325025 8870 0200 03373252 8870 0164 02704 8870 0168 0219
















Rsup2= 09619

RMSE = 01406meqg

0

1

2

3

4

5

0 10 20 30 40 50 60

1 q e N O 3

C0Ce





Shiraz groundwater


Table 5




SO4minus (mgl) 0 0 0 0 0 237 0 236






D frac14

Dm thorn

α u

eth19

THORN










time (h)

C C 0

C C 0

C C 0

0 40 80 120 160 200 2400

02

04

06

08

1

12

211 lh Mod

211 lh Exp (run1)

140 lh Mod

140 lh Exp (run2)

069 lh Mod

069 lh Exp (run3)

time (h)

0 40 80 120 160 1800

02

04

06

08

1

12

1194 mgl Mod

1194 mgl Exp (run1)

895 mgl Mod

895 mgl Exp (run4)

604 mgl Mod

604 mgl Exp (run5)

time (h)0 20 40 60 80 90

0

02

04

06

08

1

12

NO3- Mod

NO3- Exp (run1)

NO3-+Cl- Mod

NO3-+Cl- Exp (run7)

NO3-+SO4

- Mod

NO3-+SO4

- Exp (run6)

A

B

C


time (h)

C C 0

0 40 80 120 160 1850

02

04

06

08

1

12

604 mgl Mod

604 mgl Exp (run5)

Groundwater Mod

















time (h)


0 40 80 120 1600

100

200

300

400

Sulfate

Chloride

Bicarbonate

Nitrate


groundwater (Run 9)

B

C

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12

k=15k=2

k=3k=5k=10

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


A






5 Conclusions







References






























































Table 4



Q 0meqg

b

lmeqR2 RMSE

meqgqT meqg

k R2 RMSEmeqg

NO3minus

mglSO4minusminus

mglClminus

mgl


Rsup2 = 0997

RMSE=0157 meqg

Rsup2 = 0999

RMSE=0044 meqg

0

05

1

15

2

25

0 2 4 6 8 10 12 14

1 q e N O 3

1 q e N O 3

1Ce





0

05

1

15

2

25

0 10 20 30 40

C0Ce



B

A


Table 3


WV gl

C0meql

Cemeql

qemeql

0125 8870 0908 107302085 8870 0814 1099025 8870 0814 091303755 8870 0707 089605 8870 0688 0708

0751 8870 0501 07221 8870 0465 05771502 8870 0307 049020055 8870 0243 039925 8870 0236 032325025 8870 0200 03373252 8870 0164 02704 8870 0168 0219
















Rsup2= 09619

RMSE = 01406meqg

0

1

2

3

4

5

0 10 20 30 40 50 60

1 q e N O 3

C0Ce





Shiraz groundwater


Table 5




SO4minus (mgl) 0 0 0 0 0 237 0 236






D frac14

Dm thorn

α u

eth19

THORN










time (h)

C C 0

C C 0

C C 0

0 40 80 120 160 200 2400

02

04

06

08

1

12

211 lh Mod

211 lh Exp (run1)

140 lh Mod

140 lh Exp (run2)

069 lh Mod

069 lh Exp (run3)

time (h)

0 40 80 120 160 1800

02

04

06

08

1

12

1194 mgl Mod

1194 mgl Exp (run1)

895 mgl Mod

895 mgl Exp (run4)

604 mgl Mod

604 mgl Exp (run5)

time (h)0 20 40 60 80 90

0

02

04

06

08

1

12

NO3- Mod

NO3- Exp (run1)

NO3-+Cl- Mod

NO3-+Cl- Exp (run7)

NO3-+SO4

- Mod

NO3-+SO4

- Exp (run6)

A

B

C


time (h)

C C 0

0 40 80 120 160 1850

02

04

06

08

1

12

604 mgl Mod

604 mgl Exp (run5)

Groundwater Mod

















time (h)


0 40 80 120 1600

100

200

300

400

Sulfate

Chloride

Bicarbonate

Nitrate


groundwater (Run 9)

B

C

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12

k=15k=2

k=3k=5k=10

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


A






5 Conclusions







References




































































Rsup2= 09619

RMSE = 01406meqg

0

1

2

3

4

5

0 10 20 30 40 50 60

1 q e N O 3

C0Ce





Shiraz groundwater


Table 5




SO4minus (mgl) 0 0 0 0 0 237 0 236






D frac14

Dm thorn

α u

eth19

THORN










time (h)

C C 0

C C 0

C C 0

0 40 80 120 160 200 2400

02

04

06

08

1

12

211 lh Mod

211 lh Exp (run1)

140 lh Mod

140 lh Exp (run2)

069 lh Mod

069 lh Exp (run3)

time (h)

0 40 80 120 160 1800

02

04

06

08

1

12

1194 mgl Mod

1194 mgl Exp (run1)

895 mgl Mod

895 mgl Exp (run4)

604 mgl Mod

604 mgl Exp (run5)

time (h)0 20 40 60 80 90

0

02

04

06

08

1

12

NO3- Mod

NO3- Exp (run1)

NO3-+Cl- Mod

NO3-+Cl- Exp (run7)

NO3-+SO4

- Mod

NO3-+SO4

- Exp (run6)

A

B

C


time (h)

C C 0

0 40 80 120 160 1850

02

04

06

08

1

12

604 mgl Mod

604 mgl Exp (run5)

Groundwater Mod

















time (h)


0 40 80 120 1600

100

200

300

400

Sulfate

Chloride

Bicarbonate

Nitrate


groundwater (Run 9)

B

C

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12

k=15k=2

k=3k=5k=10

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


A






5 Conclusions







References

























































D frac14

Dm thorn

α u

eth19

THORN










time (h)

C C 0

C C 0

C C 0

0 40 80 120 160 200 2400

02

04

06

08

1

12

211 lh Mod

211 lh Exp (run1)

140 lh Mod

140 lh Exp (run2)

069 lh Mod

069 lh Exp (run3)

time (h)

0 40 80 120 160 1800

02

04

06

08

1

12

1194 mgl Mod

1194 mgl Exp (run1)

895 mgl Mod

895 mgl Exp (run4)

604 mgl Mod

604 mgl Exp (run5)

time (h)0 20 40 60 80 90

0

02

04

06

08

1

12

NO3- Mod

NO3- Exp (run1)

NO3-+Cl- Mod

NO3-+Cl- Exp (run7)

NO3-+SO4

- Mod

NO3-+SO4

- Exp (run6)

A

B

C


time (h)

C C 0

0 40 80 120 160 1850

02

04

06

08

1

12

604 mgl Mod

604 mgl Exp (run5)

Groundwater Mod

















time (h)


0 40 80 120 1600

100

200

300

400

Sulfate

Chloride

Bicarbonate

Nitrate


groundwater (Run 9)

B

C

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12

k=15k=2

k=3k=5k=10

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


A






5 Conclusions







References


































































time (h)


0 40 80 120 1600

100

200

300

400

Sulfate

Chloride

Bicarbonate

Nitrate


groundwater (Run 9)

B

C

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12

k=15k=2

k=3k=5k=10

time (h)

C C 0

0 20 40 60 800

02

04

06

08

1

12


A






5 Conclusions







References

























































5 Conclusions







References






















































Modeling of nitrate removal for ion exchange resin in batch and fixed bed experiment

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Transcript of Modeling of nitrate removal for ion exchange resin in batch and fixed bed experiment