pH buffer capacity based monitoring of algal wastewater treatment

35 Pages·2000·0.17 MB·English

buffer capacity based monitoring of algal wastewater treatment
pH
LievenVanVooren ,PaulLessard ,Jean-PierreOttoy andPeterA.Vanrolleghem
1(cid:3) 2 1 1
DepartmentofAppliedMathematics,BiometricsandProcessControl(BIOMATH),
1
UniversityGent,CoupureLinks653,B-9000Gent,Belgium
De´partementdeGe´nieCivil,PavilionPouliot,Universite´ Laval,Que´bec,CanadaG1K7P4
2
Abstract
A buffercapacitybasedmethod formultivariatemonitoring of tertiaryalgalwastewater treatment
pH
systemsispresented.Apilotplantwithalgalbiomassreceivingtheeffluentofacarbonremovingactivated
sludge municipal wastewater treatment plant was used for the experimental work. Two types of buffer
capacityprofilesareconsidered,firstresultingfromatitrationfromtheactual to 2.5(downtitration),
pH pH
and second asa result of atitration from 2.5to 11 (uptitration). Theexperiments wereconducted
pH pH
withalaboratorytitratorandthebuffercapacityprofileswereprocessedbyfittingmathematicalmodelsof
buffersystems to them. This allowed to quantify theinorganic carbon (IC)bufferfromthe down titration
profiles. IC is of major importance, because it is the only carbon source used by algae. It is shown that
the IC concentration derived from the buffer capacity profile gives different process information than a
standardalkalinitymeasurement. Theuptitration profilesweresuccessfullyusedforthequantificationof
and - , although an exact comparison of the laboratory results and the buffer capacity based
+
NH4 o PO4
results is difficult, because of the filtration step preceding laboratory analyses and possible interferences
caused by unmodeled buffer systems. No filter device was used, which makes it possible to implement
thismeasurementmethodinarobustandfieldapplicablesensor. Thecompletemeasurementcycle(down
titration followed by up titration and datainterpretation) canbe performedin less than 1 hour, with little
manipulation,thatcouldeasilybeautomated.
Keywords
buffercapacity,algalwastewatertreatment,alkalinity,on-linemonitoring,mathematical modeling
pH
(cid:3)Authortowhomallcorrespondenceshouldbeaddressed.[Fax:[phone],E-mail:[email protected]]
1
Introduction
Algal wastewater treatment: Traditionally, the aims of wastewater treatment have been to reduce the con-
centrationoforganicmatterandthenumberofpathogens.However,inmanytreatmentplantstypicalprimary
andsecondarytreatmentscannotmeettheincreasinglystringentrequirementsofwaterpollutioncontrol. Al-
though secondary effluents may contain low levels of and , they still contain high levels of in-
BOD5 COD
organic nutrients ( , , ). These nutrients are primarily responsible for eutrophication of the
+ (cid:0) 3(cid:0)
NH4 NO3 PO4
receivingwaters[19][27].
Nowadaysmoreandmoreplantsadaptand/orextendtheirsecondarytreatmentfacilitiestowards“nutri-
ent removal capacity” [2] [17] [25], but even effluents with low concentrations of thesepollutants can have a
negativeimpactontheenvironmentiftheyaredischargedinhighvolume,especiallyifthereceivingwateris
arathersmallriver. Tertiarytreatmentisbecominganecessitytominimizetheharmfulimpactofeffluentson
theenvironment.
Besidesbiologicalnitrogenandphosphorusremoval,numerousphysico-chemicaltreatmentssuchaschem-
ical coagulation, breakpoint chlorination, -stripping, reverse osmosis and filtration have been proposed
NH3
for removing nitrogen and phosphorus. However, due to costs and operational practices, thesetechnologies
arenotimplementableformunicipalwastewatertreatmentofsmallcommunities[20].
As an alternative, tertiary treatment involving micro-algae or cyanobacteria is shown to be effective in
nitrogenandphosphorusremoval[20][19]. Theprocessisquiteattractivebecauseofitscapacitytotransform
wastes into useful biomass using sunlight as an energy source. However these algal treatment systems also
havesomedrawbacks: Thegenerationtimeoftheorganismsinvolvedislongcomparedtobacteria;thereisa
necessityforsunlight;theactivepartofthebiomassissmallandharvestingofbiomassisdifficult[27][7].
Inrecentyears,researchhasbeenconductedtoovercometheproblemsrelatedtoalgaltertiarywastewater
treatment, and to optimize the treatment process [20] [18] [34] [38] [8]. The harvesting problem of the algal
biomasshasbeensolvedbyusingorganismslikethecyanobacteriumPhormidiumbohneri,whichhastheability
toformflocksthatsettle,thusfacilitating harvest[30].
Algal wastewater treatment processes often are discontinuous, of SBR (sequencing batch reactor) type,
where one treatment cycle consists of a filling phase, an aeration phase, a settling phase and an effluent dis-
charge phase. Such processes need continuous monitoring of the most important process variables, in order
toobtainanoptimalnutrientremovalcapacityatminimalcosts. Especiallywhenonerealizesthatnutrientre-
moval processesareoftenrelatedtophasesofluxuryuptake(e.g. phosphates)andphasesofnutrientrelease,
2
theusefulnessofon-linemeasurementsisobvious.
Alkalinity related to algal processes: The alkalinity of a water sample is defined as the amount of acid
necessarytodecreasethe toapredefinedendvalue. Twoendvaluesareconsidered[14]:
pH
1. End value 8.3 (only relevant if the sample is higher than 8.3): this is called the phenolphtalein or
pH
carbonate alkalinity (symbol C), and is a measure of the amount of strong bases, carbonates and alkali
presentinthesample.
2. Endvalue4.5(onlyrelevantifthesample ishigherthan4.5): thisiscalledthetotalalkalinity(symbol
pH
T),andisameasureoftheamountofstrongandweakbases(likebicarbonates).
Thealkalinitycanbemeasuredinthelaboratoryusingarecipientofknownvolumeofsampleandaburette
containingastrongacid(e.g. HCl0.02N).Itcanbeexpressedin orin .
(cid:0)1 (cid:0)1
meql mgCaCO3l
Alkalinityisapopularmeasurementusedintheprocesscontrolofdiversewatertreatmentprocesses,e.g.
in activated sludgetreatment[28] [40] [29] or in anaerobic wastewatertreatment[9] [5]. In practice alkalinity
isoftenusedasapracticalmeasureoftheamountofcarbonatesandbicarbonatesinthewater. Therearesome
particularremarksconcerningtheuseofalkalinityas“(bi)carbonate” estimator:
In cases the sample is loaded with weak acid buffering systems other than the subsystem (like
(cid:15) CO2
ammonium,phosphatesandVFA’s),thesecomponentswillbeincludedinthealkalinityandwillsuggest
thatmore(bi)carbonatesarepresentthaninreality[6].
For the meter method, it is advised to choose the end value in function of the alkalinity (end-value
(cid:15) pH
rangingfrom 4.3 to 4.9 forhightolowalkalinity respectively)[39]. Forcolorindicator methods,
pH pH
likethebromcresolmethod,the value4.5correspondswiththeinflectionpointonthetitrationcurve
pH
where the color indicator will switch to its other state. In case the inflection point is not so sharp, or
the solution contains strong coloring substances, the color switch will be difficult to observe. For this
reasons,the metermethodismostlypreferredabovetheoldercolorindicatormethods.
pH
Intheapplication area ofwastewatertreatment,modifiedorextendedmethodsofthealkalinity measure-
menthavebeendeveloped.Examplesofextendedmethodswheremorethan1endvalueinthetitrationprofile
areconsideredareathree-pointmethod[1]andafive-pointmethod[22]forthedeterminationofbicarbonate
and VFA. Methods using more than 5 points for bicarbonate and VFA estimation have also been developed
3
[3] [26]. Toeliminate theeffect ofinterfering bufferswhenoneis onlyinterestedin bicarbonate content,a
pH
method was developed where the is strippedfrom the sample by addition of strong acid. The stripped
CO2
can be directly measured by the volumetric [16] [15] or pressure [9] build-up of . The described
CO2 CO2
methods have been used in the application area of anaerobic treatment, where high concentrations of both
bicarbonate and VFA’s are present[5] [6]. Anoverview of measurementmethodsfor and bicarbonate is
CO2
givenin[10][24].
Alkalinity related techniques for bicarbonate estimation are well developedin applications where is
CO2
continuously generated by micro-organisms degrading organics. In these areas possible interferences with
other buffering components are negligible. In the area of algal treatment, on the other hand, is con-
pH CO2
sumed by the algae, resulting in relatively low or even limiting concentrations of bicarbonate in the water
samples. Inorganic carbon (IC) is of major importance, because it is the only carbon source used by algae.
AmongthedifferentformsofIC( , and ),onlythetwofirstonesaretakenupbythealgal
(cid:0) 2(cid:0)
CO2(aq) HCO3 CO3
biomass, and thus useful as a carbon substrate [11] [13] [36]. The preference for or uptake
(cid:0)
CO2(aq) HCO3
is dependent [42] and an adaptation period to switch between the and transport system
(cid:0)
pH CO2(aq) HCO3
may be required [11]. The importance of the IC buffer system in relation to photosynthetic algal growth is
widely describedin literature [31] [35] [23] [37]. Therefore, the usefulnessof quantifying the IC buffer for al-
gal wastewater treatment is twofold. First, a precise knowledgeof the inorganic carbon content can indicate
whether the IC becomes limiting [23], and whether IC supply is needed [31] [37]. Second, because IC is the
only carbon source used by the algae, the rate of IC consumption under light conditions can be used as a
processandcontrolvariable,e.g. indicatingapossiblereactorfailureiftheICconsumptionistoolow.
Theoretical Model for Buffer Capacity Curves
pH
In generalthe buffer action of a systemis definedby itsresistanceagainst changeswhenacid ( ) or
pH pH CA
base( )areadded. Thesymbolforbuffercapacityis or (bufferindex)[33],anditsunitis .
(cid:0)1 (cid:0)1
CB (cid:12) (cid:25) meql pH
dCB dCA (i)
(cid:12) = =(cid:0)
dpH dpH
The origin of the buffer capacity are conjugated acid/base systems. A weak monoprotic acid ( )
(cid:0)1
Ca mol l
dissolvedinwaterwilldissociateuntilanequilibriumbetweentheacid( )andthebase( )formisestab-
(cid:0)
HA A
lished:
(ii)
+ (cid:0)
HA*) H +A
4
Amathematical representationofthischemical equilibriumisbasedonthreeequations: amassbalance,a
dissociationequationandanelectro-neutralityequation. First,amassbalancefor canbewritten:
HA
(iii)
(cid:0)
Ca =[HA]+[A ]
Second,theequilibriumisdrivenbyitsdissociationconstant ordissociationexponent [33]:
Ka pKa
[H+][A(cid:0)] and (iv)
Ka = pKa =(cid:0)logKa
[HA]
The valueisafunctionofthethermodynamic ,thetemperatureandtheionicstrength[10][32]. Water
0
pKa pKa
itself can be consideredtobe a weakmonoproticacid, with concentration = 55.5 and = 15.74
(cid:0)1
Cw moll pKw
(atT= ),thusasimilarmassbalanceandequilibriumequationcanbewritten:
o
25 C
(v)
(cid:0)
Cw =[H2O]+[OH ]
[H+][OH(cid:0)] and (vi)
Kw = pKw =(cid:0)logKw
[H2O]
The influence of the water buffer on the experimental buffer capacity curve is only significant at or
pH < 5
[43]. In a water sample containing several buffering components, one can write that the total buffer
pH > 9
capacity is equal to the buffer capacity of the water itself summed with the buffer capacity of the
(cid:12) (cid:12)w (cid:12)i
differentcomponents inthesample:
i
n
(vii)
(cid:12) = (cid:12)w + (cid:12)i
i=1
Consider a water sample with 1 monoprotic buffering coXmponent (HA) at low , to which a small volume
pH
ofstrongbase(e.g. NaOH) witha concentration ( )isadded. Third,theelectro-neutralityhastobe
(cid:0)1
CB moll
maintained:
(viii)
+ + (cid:0) (cid:0)
[Na ]+[H ]=[OH ]+[A ]
Basedonthiselectro-neutralityequationonecanwriteforaninfinitesimaladditionof :
CB
(ix)
dCB =(cid:0)d[H+]+d[OH(cid:0)]+d[A(cid:0)]
orintermsofbuffercapacity :
(cid:12)
dCB d[H+] d[OH(cid:0)] d[A(cid:0)] (x)
(cid:12) = =(cid:0) + +
dpH dpH dpH dpH
After substitutionof by , followed by differentiation (using ) and using the
pH (cid:0)log[H+] d(logu) = u1 loge du
massbalances(iii)and(v),togetherwiththeequilibriumequations(iv)and(vi),onecanrewrite(x):
+ [H+] [H+] (xi)
(cid:12) =2:303 [H ]+CwKw +CaKa
+ 2 + 2
([H ]+Kw) ([H ]+Ka) !
5
If differentmonoproticweakacids are presentin thesample,theequationfor can beextendedwithsimilar
(cid:12)
additionalterms. Forpolyprotonicacidstheadditionaltermsaresomewhatmorecomplex. Foradiproticacid
withconcentration inwater:
Cb
+ [H+] [H+]2+4Kb2[H+]+Kb1Kb2 (xii)
(cid:12) =2:303 [H ]+CwKw + 2 +CbKb1 + 2 + 2
([H ]+Kw) ([H ] +Kb1[H ]+Kb1Kb2) !
Andforatriproticacidwithconcentration inwater:
Cc
+
+ [H ]
(cid:12) =2:303 [H ]+CwKw
+ 2
([H ]+Kw)
[H+]4+4Kc2[H+]3 +(Kc1 +9Kc3)Kc2[H+]2 +(4[H+]+Kc2)Kc1Kc2Kc3 (xiii)
+CcKc1 + 3 + 2 + 2
([H ] +Kc1[H ] +Kc1Kc2[H ]+Kc1Kc2Kc3) !
Ageneralequationcanbewrittenforthebuffercapacityofasamplecontaining monoprotic, diproticand
l m
triproticweakacids:
n
+ [H+] l m n (xiv)
(cid:12) = 2:3030[H ]+CwKw([H+]+Kw)2 + (term1)i+ (term2)j + (term3)k1
i j k
X X X
Theobjectiveofthi@spaperistodevelopa buffercapacitybasedsensor,capableofextractiAngconcentra-
pH
tions of buffering components from on-line measured titration curves coming from the influent, effluent
pH
and reactor content of an algal pilot plant. The information that can be extracted from the buffer capacity
profiles using mathematical modeling is evaluated towards its usefulness related to tertiary algal treatment
processes. Therelationshipbetweenthealkalinity andtheIC buffer capacity will bediscussed,aswell as the
ammonium andortho-phosphateassessmentfromthebuffercapacityprofile. Inthelattercase,IC, and
+
NH4
- will be incorporated in equation (xiv) as diprotic, monoprotic and triprotic weak acids respectively.
o PO4
The results obtained with the buffer capacity sensor seem promising as input to develop a control strategy,
althoughthisisnottheobjectiveofthispaper.
Materials and Methods
Thealgalpilotplant: Apilotreactorwithalgal biomass,installedattheoutletoftheactivatedsludgeplant
ValcartiernearQuebeccity(Canada),wasusedforthesamplecollectionbetweenJuly22andAugust12,1997.
The activated sludgeplant was treating domestic wastewaterof the military base Valcartier, and received an
influent flow of around 2500 . Theplant was operatingin partially nitrifying mode and the secondary
3 (cid:0)1
m d
effluentnitrogenwaspresentintwoforms, and .
+ (cid:0)
NH4 NO3
6
The algal bioreactor with a triangular cross-section had a volume of 6 and combined aeration and
3
m
mixing was obtained by means of a perforated flexible tube at the bottom of the reactor. This pilot reactor
was in use for 2 years and its function was to further decrease the nutrient concentrations of the secondary
effluent. The reactor was usedin batch mode, in cycles of 1 or 2 days. A cycle consistedof a filling phase (in
themorning),anaerationphaseof12or36hours,asedimentationphase(atnight)toallowthealgaetosettle
down, and a decantation phase (in the morning) to remove an upperliquid layer of around 75 % of the total
reactorvolume. Thebiomassconcentrationinthereactorwaskeptbetween100and600 .
(cid:0)1
mgDW l
Sampling and laboratory measurements: Light, , DO and temperaturewere monitoredcontinuouslyin
pH
thealgalpilotplant. Threedifferentkindsofsamplesweretakenforfurtheranalysisinthelaboratory:
TheEffluentoftheValCartierplant(samplecodeEVC),beingtheinfluentofthealgalpilotreactor;
(cid:15)
ThecontentoftheAlgalPilot(samplecodeAP),3hoursafterthereactorwasfilledandcompletelymixed
(cid:15)
bytheaeration;
TheEffluentoftheAlgalPilotplant(samplecodeEAP).
(cid:15)
The EVC and EAP samples were taken with a peristaltic pump in the inlet and outlet of the pilot plant
during filling and decantation phasesrespectively. The AP samples were taken as manual grab samples. All
sampleswerestoredimmediatelyinthefridge( )andprocessedinthelaboratorywithin1day.
o
4 C
Prior to the laboratory analyses ( , , - ), all samples were filtered on a Whatman 934 AH
+ (cid:0)
NH4 NO3 o PO4
filter, with a pore size of 1.5 . The analyses were conducted according to Standard Methods [14]. For the
(cid:22)m
totalalkalinitymeasurementsinthelaboratory,the metermethodwasused[14].
pH
Titration curves: Titrations were performed with a Titrino 716 titrator (Metrohm, Switzerland). Data ac-
quisition was performed with a 386 PC connected to the titrator. The titrated sample volume was 100 ,
ml
and titration took place in a completely closed magnetically stirred titration vessel containing a scrub-
CO2
ber (bowed glass tube with soda lime pellets) to prevent entrance of from the air. The headspace of the
CO2
titrationvesselwas150 . Priortotitration,therefrigeratedsampleswereequilibratedto withawarm
o
ml 25 C
waterbath,andtheywereimmediatelytitratedatroomtemperature,whichvariedbetween20and . Two
o
25 C
differenttypesoftitrationprofileswerecollected:
1. Downtitrationprofile: Thesampleassuchwastitratedwith0.1NHClfromtheactual to 2.5using
pH pH
amonotonicendpointtitration(MET)method[21],withfixedstepsof0.05 . Thistypeoftitrationwas
ml
7
usedforthedeterminationoftheICbuffer.
2. Uptitrationprofile: Thedowntitratedsamplewas stronglyagitatedwitha magnetic stirrerfor15 min-
utes to remove all , while the titration vessel was open to the air. Next, the vessel was closed and
CO2
the sample was titrated with 0.1 N NaOH to 11 using a dynamic endpoint titration (DET) method
pH
[21]. ThedifferencewiththeMETmethodisthattheDETmethoddoesnottakefixedvolumesteps,but
variablevolumesteps(smallversusbigstepswhenthebuffercapacityisloworhighrespectively). This
typeoftitrationwasusedforthedeterminationofammoniumandortho-phosphate.
Data processing software: Software developed in C++ was used for the calculation of the buffer capacity
profiles. Such a profile is the inverse of the first derivative of the titration profile. The calculation of the
derivative was performed using a parabolic regression in a moving window of 5 experimental data points
of the titration curve. No further smoothing algorithms were necessary to obtain a smooth buffer capacity
profile. The same software was used to fit several mathematical models to the calculated buffer capacity
curve. For the parameter optimization, the PRAXIS algorithm [4], which is freely available on the internet,
wasimplementedinthesoftware. Themathematical modelspecificationsweredefinedinaspecialinputfile,
read by the program. The software was running on an INDIGO workstation(Silicon Graphics, U.S.) and the
dataprocessingof1experimentaldatafileneededapproximately1minute.
Mathematicalmodels: Themathematicalmodelsusedwereallbasedonthegeneralbuffercapacityequation
(xiv). Foreachmodelused,thefollowingconsiderationsweretakenintoaccount:
1. Whatisthe intervalusedfordataprocessing.
pH
2. Which bufferingcomponentshavetobeincludedinthemodel.
pH
3. Whataretheinitialguessesfortheconcentrationsand valuesofthedifferentbufferingcomponents.
pKa
4. Which concentrations and values are to be adjusted in order to fit the simulation model to the
pKa
experimental data. The parameters that are to be estimated are specified with a lower and upper limit
(constrained optimization). The reason for optimizing values instead of keeping them fixed at the
pKa
oranothervalueistotakeintoaccounttheresidualeffectsoftemperature,ionicstrengthandpossi-
0
pKa
bleelectrodeerrorsonthepositionofthe valuesintheexperimentalbuffercapacitycurve.
pKa
8
Forthedowntitrationsasimulationintervalbetween 4and 7.3wastaken. Eveniftheinitial of
pH pH pH
thesamplewasmuchhigherthan7.3,itwasnotworthwhiletoextendthesimulationintervalandincorporate
ortho-phosphateorammoniuminthemodel,becausethemagnitudeoftheICbufferwouldinterferewiththe
othersmallerbuffersystems. Fortheuptitrations,asimulationintervalbetween 4and 10waschosen.
pH pH
In the software, concentrations can be specified in or . More detailed model specifications for
(cid:0)1 (cid:0)1
moll mg l
thedownanduptitrationsareshowninTable1andTable2respectively.
[Table1abouthere.]
[Table2abouthere.]
The “soap” term in the models stands for a range of components that all have a buffer capacity in the range
of 4 to5.5, e.g. numerousorganic acids. The “blank1” termstandsfor an unknownbuffering component
pH
around 10,foundtobepresentinalmostall samplesanalyzed. Thereasonforincorporatingthe“carbon”
pH
componentin theuptitrationmodel,despitethefact thatthesampleis priorlymade free,isthatduring
CO2
up titration the initially present in the headspace above the vessel can enter the sample and typically
CO2
accountsfor0.07 .
(cid:0)1
meqIC l
Furthermore,oncethetotalconcentration (whichis )isdeterminedusing
2(cid:0) (cid:0)
CIC [CO3 ]+[HCO3 ]+[CO2(aq)]
the simulation model, the partitioning of these 3 forms can be calculated as function of the actual [39].
pH
Using the mass balance and the 3 equilibrium equations for IC, the concentrations , (cid:0) and
[CO2(aq)] [HCO3 ]
2(cid:0) are given by equations (xv), (xvi) and (xvii) respectively. Details on obtaining these equations can be
[CO3 ]
foundin[33][39].
(cid:0)2pH (xv)
10
[CO2(aq)]= (cid:0)2pH (cid:0)(pH+pKa1) (cid:0)(pKa1+pKa2)CIC
10 +10 +10
(cid:0) 10(cid:0)2pH +10(cid:0)(pKa1+pKa2) (xvi)
[HCO3 ]= 1(cid:0) (cid:0)2pH (cid:0)(pH+pKa1) (cid:0)(pKa1+pKa2) CIC
10 +10 +10 !
(cid:0)2pH (cid:0)(pH+pKa1) (xvii)
[CO32(cid:0)]= 1(cid:0) (cid:0)2pH 10 (cid:0)(pH++p1K0a1) (cid:0)(pKa1+pKa2) CIC
10 +10 +10 !
Importanttoremarkisthatthelatter3equationsareonlyvalidinacompletelyclosedandequilibratedsystem.
Asthealgalreactorisanopensystem,theconcentrationof isalsodrivenbyHenry’slaw[32]:
CO2(aq)
(xviii)
[CO2(aq)]= KH (cid:2)pCO2(air)
With (at )and ,equation(xviii)leadstoanair/liquid
(cid:0)2 (cid:0)1 o (cid:0)2
KH =3:410 atm M T =25 C pCO2(air) =310 atm
equilibriumconcentrationof or0.012 ,whichisaverylowvalue. Furthermore,
(cid:0)5 (cid:0)1
[CO2(aq)] =1:210 M meql
9
onehastotakeintoaccountthatabiologicalactivesystemlikeandalgalsystemisquiteseldominequilibrium
withtheatmosphere,socarefuluseofequation(xviii) isadvised.
Results and Discussion
Alkalinity and IC buffer capacity: A random sample from the algal pilot reactor AP, taken in the morning
ofa sunnydaywasanalyzed withthetitratorandinthelaboratory. Afilteredandanunfilteredsamplewere
titratedfrom theactual to 2.5 (Figure1). Bothsamples werealso analyzed onthetotal alkalinity with
pH pH
twostandardmethods.
[Figure1abouthere.]
From the titration curves, the correspondingbuffer capacity curves (Figure 2) were calculated and the simu-
lation model(equation (xiv) and Table 1) was usedtoquantify theconcentration of theIC buffer. Thebestfit
simulationresultfortheunfilteredandfilteredsampleisgiveninFigure2.
[Figure2abouthere.]
Forthetotalalkalinity determination,theend-point valueforthe metermethodwassetat 4.5,
pH pH pH
accordingtothestandardmethod[14]. ThismethodwasalsoappliedtothetitrationcurvesofFigure1,where
aninterpolationbetween2successivedatapointswasusedtomakeareadingoftheamountofacidnecessary
to bring the to 8.3 and 4.5 respectively. For comparison reasons, the simulation results to quantify the IC
pH
bufferwerealsoexpressedas .
(cid:0)1
meql
TheresultsofthealkalinitymeasurementsandthesimulationresultsforICarepresentedinTable3.
[Table3abouthere.]
The precision of the total alkalinity measurements (both the meter method and from the titration curve),
pH
expressed as relative standard deviation (r.s.d.), was between 1 and 2 %. The r.s.d. of the simulated IC con-
centrationbasedondowntitrationprofileswas2%. Onecannoticethattheresultsforthefilteredsampleare
onlyabout7%lowerthantheunfilteredsample. ThismeansthatthealkalinityorICbuffercapacityismainly
relatedtothesolublephaseandnottothealgalbiomassphase. Thetotalalkalinitywiththestandard meter
pH
methodwasnotsignificantlydifferentfromthetotalalkalinitycalculatedfromthetitrationcurvesinFigure1
(t-test; =5%). AninterestingfeatureofthisexperimentisfoundwhencomparingtheICcontentfoundwith
(cid:11)
10