Environ. Sci. Technol. 2002, 36, 2736-2741
Rapid, Simple, and Accurate Method for Measurement of VFA and Carbonate Alkalinity in Anaerobic Reactors O R I L A H A V , * ,† B A R A K E . M O R G A N , ‡ A N D RICHARD E. LOEWENTHAL‡ Faculty of Agricultural Engineering, TechnionsIsrael Institute of Technology, Haifa, 32000, Israel, and Department of Civil Engineering, University of Cape Town, Rondebosch 7700, South Africa
This paper presents a new simple, rapid, and accurate method suitable for on-site measurement of volatile fatty acids (VFA) and carbonate alkalinity in anaerobic reactors. This titrimetric method involves eight pH observations, and typically, the full procedure takes approximately 15 min. An important feature of the method is a built-in quality control mechanism allowing the user a rapid means of assessing the reliability of the experimental procedure. To evaluate the accuracy of the method, both laboratorymade waters and industrial UASB effluent were tested. High accuracy for both VFA and carbonate alkalinity measurements (error within 2% and 1%, respectively) plus good repetition (average standard deviation of 6.7% and 1.45%, respectively) was obtained. The method takes into account the effects of the phosphate, ammonium, and sulfide weak acid subsystems. Appraisal of the effect of an input error in these subsystems revealed that VFA measurement is fairly insensitive to phosphate and ammonium concentrations. It is, however, sensitive to H2S loss during titration where the sulfide concentration is higher than approximately 100 mg/L as S. With regard to the carbonate alkalinity measurement, error in concentration of either phosphate or sulfide or H2S loss might result in a significant error. Short guidelines for correct execution of the method are given in an appendix.
Introduction Startup and successful control of anaerobic treatment facilities are notoriously difficult and delicate processes, requiring both patience and accurate and rapid monitoring techniques. The control strategy hinges around maintaining a low concentration of volatile fatty acids (VFA) and a pH in the range of 6.6 < pH < 7.4. Normally, in such reactors, the carbonate system forms the main weak acid system responsible for maintaining the pH around neutrality, while the VFA systems (acetic, propionic, and butyric acids) are the major cause for pH decline. Under stable operating conditions, the H2 and acetic acid formed due to acidogenic and acetogenic bacterial activity are utilized immediately by the methanogens and converted * Corresponding author phone: 972 4 8292191; fax: 972 4 8221529; e-mail:
[email protected]. † TechnionsIsrael Institute of Technology. ‡ University of Cape Town. 2736
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to methane. Consequently, the VFA concentration is typically very low, carbonate alkalinity is not consumed, and the pH is stable. Conversely, under overload conditions or in the presence of toxins or inhibitory substances, the activity of the methanogenic and acetogenic populations is reduced causing an accumulation of VFA which, in turn, increases the total acidity in the water, reducing the pH. The extent of the pH drop depends on the H2CO3* alkalinity concentration (the term H2CO3* alkalinity is used here to define the proton accepting capacity of the carbonate weak acid subsystem). In medium and well-buffered waters, high concentrations of VFA would have to form in order to cause a detectable pH drop, by which time reactor failure would have occurred. Therefore, pH measurement cannot form the sole control means, and direct measurement of either (or both) VFA or H2CO3* alkalinity concentrations is necessary. Measurement of H2CO3* alkalinity in a mixture of weak acid subsystems cannot be executed via direct titration to the H2CO3* equivalence point (around pH 4.5) because at that pH the VFA weak acid subsystem has significant buffering capacity and no clear end point can be defined (1). Characterization of the carbonate subsystem can be carried out using an inorganic carbon analyzer; however, this instrument, apart from not being generally available on-site, is prone to gross inaccuracy due to CO2 loss. Therefore, VFA concentration is the most practical measurement for monitoring any indication of stress in an anaerobic treatment system. If the system is not rectified at this early stage, failure is likely. This control problem has gained importance in recent years due to the introduction and wide use of high-rate anaerobic treatment processes, where control needs to be fine-tuned. In addition to conventional anaerobic digesters, other treatment systems such as biological sulfate removal reactors and hydrolysis reactors (prefermenters) depend on VFA measurement as a principal means of monitoring reactor performance. Therefore, there is a need for a simple, rapid, and accurate on-site means of measuring VFA and H2CO3* alkalinity. Currently, VFA can be measured by straight distillation, steam distillation, a colorimetric technique (2, 3) or using gas chromatography. However, all of these methods are time-consuming, the latter three require specialized equipment and a dedicated operator, and generally the equipment will not be available on-site. Conversely, in terms of simplicity, speed, and cost-effectiveness, it is generally accepted that titrative methods are superior for the purpose of routine monitoring and control. During the last 4 decades, a considerable number of quantitative and semiquantitative titrimetric methods have been proposed for the measurement of either VFA or H2CO3* concentrations or both. Most of these methods were reviewed elsewhere (4) and found to be either too elaborate or too approximate for general practical application. Recently, Munch and Greenfield (5), using a number of simplifying assumptions, suggested an approximate relationship between VFA, carbonate species alkalinity, and pH, allowing VFA estimation based only on pH readings. This method was developed based on criteria confined to prefermenters working at low pH and high VFA concentrations and, therefore, cannot be generalized to most other anaerobic reactors. The most comprehensive work on the subject to-date was presented by Moosbrugger and co-workers (6, 7). They devised a rapid and simple strong acid titration technique for both VFA and alkalinity measurement termed “The 5-Point Titration Method”. When applied within limitations, the 10.1021/es011169v CCC: $22.00
2002 American Chemical Society Published on Web 05/10/2002
method has proved to be accurate (8). However, there are theoretical factors associated with the method that tend to undermine the confidence of the user (9). The method uses a mathematical algorithm for calculation, whose solution requires imposing a systematic correction on all pH observations. The necessity for correcting observed values was attributed to either a residual liquid junction potential (error in pH measurements caused by differences in the dissolved solids concentration between the buffer solution used to calibrate the probe and the test solution) or from poor pH meter calibration (6). With regard to errors emanating from residual liquid junction potential: the total dissolved solids concentrations in the samples tested varied between 500 and 1000 mg/L (after dilution), which is very close to the dissolved solids concentration in standard buffer solutions. It is therefore difficult to ascribe a “systematic pH error” to the liquid junction effects. This is particularly obvious when taking into consideration that (a) the relatively small residual liquid potential error of 0.075 pH units estimated in high TDS seawater samples (10, 11), (b) from a theoretical/ semiempirical approach, the Henderson equation gives residual liquid junction values of less than 0.003 pH units for the TDS range of the solutions tested, and (c) the five-point method, when applied to a series of tests on a particular sample, applied pH error corrections between tests that varied between 0.02 and 0.08 pH units. This leads to a conclusion that the error in pH observations is random rather than systematic. A second problem associated with the five-point method is that it is not generally applicable to anaerobic treatment processes, in particular when the VFA concentration is higher than half the total carbonate concentration (6). Another problem is that the method does not include any means of assessing the reliability of the output, that is, poor execution of the method (for example, too vigorous mixing during titration causing excessive loss of CO2) can result in gross errors which cannot be readily detected. In this paper, a new strong acid titration method for VFA and H2CO3* alkalinity measurement is developed. The method requires eight pH observations. These observations are used within a mathematical model to determine VFA and H2CO3* alkalinity. The model extends the five-point method by resolving the mathematical and analytical problems which gave rise to the “systematic pH error” of the Moosbrugger approach. In addition, the new method can be applied generally (irrespective of the VFA/carbonate species ratio) and also possesses both self-assessment and selfrectification mechanisms of the output data for quality control purposes.
where [y]x indicates molar concentration of species y after addition of x mL of standard acid (mol/L), [A-] ) dissociated short chain VFA species concentration (mol/L), and Vs ) volume of sample (l). Equation 2 can be reformulated in terms of total weak acid species concentrations using equilibrium equations for the weak acid subsystems and mass balance equations for each of the weak acid subsystems as represented in eqs 3-7 below. (For brevity reasons, only the VFA and carbonate subsystems are given. The other subsystems follow the same approach.) For the carbonate subsystem
(H+)x × [HCO3-]x/[H2CO3*]x ) KC1′
(3)
(H+)x × [CO32-]x/[HCO3-]x ) KC2′
(4)
CTVs/(Vx + Vs) ) [H2CO3*]x + [HCO3-]x + [CO32-]x (5) where ( ) denotes activity, [ ] denotes molarity, and K′ equals apparent equilibrium constant after adjustment for DebyeHuckel effects. For the VFA subsystem (all of the VFA are considered to constitute a single weak acid system with an equilibrium constant Ka′ because they all have pK values very close to each other)
(H+)x × [A-]x/[HA]x ) Ka′
(6)
ATVs/(Vx + Vs) ) [HA]x + [A-]x
(7)
Solving for CT from eqs 3-5 and for AT from eqs 6 and 7, respectively, gives the desired equations
[HCO3-]x )
CTVs/(Vx + Vs)/{1 + KC2′/(H+)x + (H+)x/KC1′} (8)
[CO32-]x )
CTVs/(Vx + Vs) × KC2′/{(H+)x + KC2′ + ((H+)x)2/KC1′} (9) [A-]x ) ATVs /(Vx + Vs) × Ka′/{(H+)x + Ka′}
(10)
Model Derivation The basic model approach involves equating a mass balance relationship for alkalinity in terms of the volume of standard strong acid titrant added (eq 1) to a mass balance of alkalinity in terms of species concentration of all proton accepting species likely to be present in an anaerobic reactor (eq 2).
Mtotal alk(x) ) VeCa - VxCa
(1)
where Mtotal alk (x) ) total mass of alkalinity after the addition of Vx mL of standard strong acid (mol), Ve ) the unknown volume of standard strong acid to be added to the alkalimetric end point (l), Vx ) the volume of standard strong acid added to a point x with pH equal to pHx (l), and Ca ) concentration of standard strong acid titrant (mol/L).
Mtotal alk (x) ) {[HCO3-]x + 2[CO32-]x + [A-]x + [HS-]x + 2[S2-]x + [NH3]x + 3[PO43-]x + 2[HPO42-]x +
[H2PO4-]x + [OH-]x - [H+]x} × (Vx + Vs) (2)
Similar equations can be developed for the phosphate, sulfide, and ammonium proton accepting species. Substituting the equations for each of the species concentration into eq 2 (for example, as given in eqs 8-10 for the carbonate and VFA subsystems) gives an equation for total mass of alkalinity in terms of AT, CT, PT, NT, ST, and pHx
Mtotal alk (x) ) {CTVs/(Vs + Vx) × Fn1(pH)x + ATVs/(Vs + Vx) × Fn2(pH)x + PTVs/(Vs + Vx) × Fn3(pH)x + STVs/ (Vs + Vx) × Fn4(pH)x + NTVs/(Vs + Vx) × Fn5(pH)x + 10-(14-pHx)/fm - 10-pHx/fm} × (Vs + Vx) (11) where PT, ST, and NT represent the total phosphate, sulfide, and ammonium concentrations, fm ) monovalent activity coefficient, and Fn1-Fn5 are functions of pHx and equilibrium constants for the carbonate, acetate, phosphate, sulfide, and ammonium subsystems. VOL. 36, NO. 12, 2002 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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Equating eqs 1 and 11 gives the desired equation linking the mass of alkalinity based on acid added to the mass of alkalinity based on species concentrations
pH range of 2.4 < pH < 2.7. In this pH region, the species CO32-, HCO3-, A-, PO43-, HPO42-, NH3, HS-, S2-, and OHare negligible and eq 11 reduces to
(Ve - Vx) × Ca ) {CTVs/(Vs + Vx) × Fn1(pH)x + ATVs/ (Vs + Vx) × Fn2(pH)x + PTVs/(Vs + Vx) × Fn3(pH)x + STVs/(Vs + Vx) × Fn4(pH)x + NTVs/(Vs + Vx) ×
total alkalinityx ) VeCa - VxCa ) {[H2PO4-]x - [H+]x} × (Vx + Vs) (13)
Fn5(pH)x + 10-(14-pHx)/fm - 10-pHx/fm} × (Vs + Vx) (12) At each point in the titration (i.e., for each Vx and corresponding pHx), eq 12 includes three unknowns: Ve, AT, and CT, provided the phosphate, sulfide, and ammonium concentrations are measured and temperature and TDS (or EC) are known so that the various equilibrium constants can be determined. Thus, to solve for Ve, AT, and CT, only three data pairs (i.e., three values for corresponding Vx and pHx pairs) need to be known. This however leads to poor prediction. Calculation of the First Estimate for AT and CT. Moosbrugger et al. (6) found that the best first estimate for AT and CT and can be obtained from four titration data points (i.e., two pairs of data points), each pair symmetrical about pKC1 and pKa (they suggested approximately half a unit of pH to either side of the respective pK values). When inserted into eq 12, the data from the four titration points give four equations. The pair of observations around pKa (i.e., the third and the fourth points) is in a region where the buffer capacity of the VFA system dominates that of the carbonate system and vice versa for the first and second titration points. Consequently, subtracting the equation formed from the fourth data point from that derived from the third gives an equation in terms of CT and AT in which the VFA alkalinity term (i.e., the species [A-]x) dominates. Similarly, subtracting the equation formed from the second data point from that derived from the first, gives an equation in terms of CT and AT in which the H2CO3* alkalinity term, namely, [HCO3-]x, significantly dominates. This technique enables a relative separation between the two subsystems in which the third and the fourth point are mainly responsible for the VFA derivation. Therefore, an error in the first two pH observations (that may arise from either CO2 loss or H2S loss, or from inaccurate PT or ST input) would be mainly “absorbed” by the carbonate subsystem, minimizing the effect on the VFA calculation. The influence of such errors on the method is discussed later in the paper. The two new equations are now solved to produce the first estimate of AT and CT. Assessment and Improvement of the First Estimate. In the Moosbrugger approach, correction of the first estimate was carried out as follows: a second estimate of AT and CT is calculated by again taking two pH pairs, one symmetrical about pKa (i.e., pH3/pH4) but the other asymmetrical about pKc1 (i.e., pH1/pH4). Subsequently, these two CT values (calculated in the first and second estimate) are compared and, if different, all pH observations are adjusted by ∆pH and the calculation procedure is repeated (by changing ∆pH) until the difference between the two CT values is negligible. Lahav and Loewenthal (9) showed that final accurate results could be obtained from the same data used by Moosbrugger et al. (6) without invoking the “systematic pH error” approach, simply by adopting a technique of error minimization. In this paper, an improved approach is developed by accurately measuring total alkalinity (defined here as the total proton accepting capacity of all species in the sample) and using this value in addition to the first estimate of AT and CT to give the final result. Such a total alkalinity measurement can be obtained using a Gran titration (12). This calculation requires a further three pairs of (Vx, pHx) points taken at a 2738
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Expressing H2PO4- as a function of PT and equilibrium constants and rearranging terms gives
(PTVs/(Vs + Vx)/{1 + (H+)x/KP1′ + KP2′/(H+)x +
KP3′KP2′/((H+)x)2} - 10-pHx)(Vs + Vx) ) Ca(Ve - Vx) (14)
The left-hand side of eq 14, for which all variables are known, is now defined as Fx. Plotting Fx versus Vx gives a linear relationship where interception with the vertical axis (i.e., where Fx equals zero) gives the value of Ve . It should be noted that the three Vx and pHx data points used in the Gran function calculation are independent of protonated gas species (namely, CO2 and H2S) loss. Consequently, rapid mixing of the sample can be applied at this stage in the titration. The Gran function measurement is an extremely accurate procedure and, as such, can be used for assessing and improving the results arising from the first estimate. The assessment of the first estimate of AT and CT is effected as follows: AT and CT (determined from the first estimate) and Ve (determined from the Gran function analysis) are inserted in eq 12 together with the initial pH value (i.e., where Vx ) 0). Furthermore, both AT and CT are now multiplied by a proportional term “x”, to account for inconsistencies in pH observations, yielding
VeCa ) {xCTFn1(pH0) + xATFn2(pH0) + const} × Vs (15) where const ) a constant representing the proton accepting term for the phosphate, sulfide, ammonium, and water subsystems at the initial pH (pH0). Solving for x gives an assessment of the first estimate for AT and CT. The closer x is to unity, the better the first estimate conforms to the accurately measured Ve. An acceptable value for x is a relative error (|(x - 1)| × 100) of less than 5%. Higher relative error indicates an unacceptable execution of the method or a gross error in one of the parameters used. The improved values for AT and CT are then obtained by multiplying each of the two parameters by x to conform to the accurately measured Ve using the initial pH. For the final output of the algorithm, the improved AT gives the final value for VFA concentration and the improved CT is used to calculate the final value for H2CO3* alkalinity using the initial pH. It should be noted that when the initial pH is lower than about 6.85, a known volume of standard base should be added to the sample to allow acid titration to the prescribed pH points. In such cases, the algorithm is changed as follows: (i) Vs is modified by the volume of NaOH addition, and (ii) Ve is derived as before and then modified giving
Ve (final) ) (Ve(Gran function)Ca - VNaOHCNaOH)/Ca (16) where VNaOH ) volume of standard NaOH solution added to lift pH above 6.85 (l) and CNaOH ) concentration of standard NaOH solution (mol/L).
Model Verification Model verification was carried out by using both laboratorymade solutions and effluent from an operating industrial treatment plant. Because the mathematics involved is laborious and time-consuming, all calculations were carried out using a computer program. The input to the computer
TABLE 1. Measurements of Laboratory-Made Solutions measured values: average + (standard deviation)
composition of laboratory-made solutions
sample no.
no. of samples
CH3COOH added (mg/L as HAc)
1 2 3 4 5 6
6 6 5 4 4 4
50 100 150 200 500 700
total proportional measured relative alkalinity error in total alkalinity error in added (mg/ first estimate (from Gran function) total alkalinity L as CaCO3) (|x - 1| × 100) (%) (mg/L as CaCO3) calculation (%) 1000 1000 1000 1000 1000 1000
0.68 (1.37) 1.04 (1.44) 1.6 (1.03) 1.23 (1.14) 0.99 (2.3) 1.22 (0.57)
993 (13.7) 1010 (15.9) 1002.5 (5.5) 1000.9 (6.5) 1015.1 (22.7) 1004 (15.4)
0.68 (1.3) 1.04 (1.44) 0.378 (0.56) 0.09 (0.64) 1.5 (2.3) 0.42 (1.54)
measured VFA (mg/L as HAc)
relative measured error in VFA H2CO3* alkalinity measurement (mg/L as CaCO3) (%)
49.1 (7.8) 97.8 (9.9) 149.9 (10.9) 198.5 (6.1) 502.4 (9.5) 688.0 (15.5)
1.9 2.2 0.06 0.75 0.48 1.7
950 (14.7) 929 (17.1) 880 (14.32) 835 (6.3) 601 (17.2) 442 (6.2)
TABLE 2. Effect of Error in Phosphate Input on H2CO3* Alkalinity and VFA Results (Average of Three Laboratory-Made Waters Composed of Carbonate Alkalinity ) 1000 mg/L as CaCO3 + VFA ) 200 mg/L as HAc, + PT ) 47.5 mg/L as P) PO4-P concentration applied to program (mg/L as P)
average proportional error in first estimate (%)
VFA concentration (mg/L as HAc)
relative error in VFA concentration (%)
H2CO3* alkalinity (in sample) (mg/L as CaCO3)
relative error in H2CO3* alkalinity (%)
47.5 (true value) 0 95 200
1.15 2.02 -0.66 -6.39
198.0 (6.1) 195.7 (6.8) 199.6 (4.7) 197.5 (4.9)
1.0 2.1 0.2 1.2
873 (13.2) 937 (8.5) 816 (9.4) 705 (31)
+7.3 -6.5 -19.1
program consists of the initial pH of the sample, seven pairs of Vx and pHx values, sample TDS and temperature, and the total concentrations of dissolved ammonium, phosphate, and sulfide. With regard to the titration data, four (Vx, pHx) pairs (for first estimate calculation) were taken at pH values of approximately 6.85, 5.85, 5.25, and 4.25 (all values (0.1 pH value), and the other three pairs (for Ve determination via Gran function) were obtained at a pH range of 2.4 < pH < 2.7. The experiments were conducted at a temperature range of 16 to 22 °C. Table 1 shows the results of the laboratory-made solutions tested. The samples simulate a typical build-up of VFA in a reactor containing a total alkalinity of 1000 mg/L as CaCO3. When the data listed in Table 1 is referred to, the following is found. (i) The accuracy of the total alkalinity measurement (via the Gran titration) was, on average, greater than 99%, substantiating the assumption that it can serve to assess and improve the first VFA and H2CO3* alkalinity estimate. (ii) The measured average VFA concentrations were generally within 2% of the laboratory-made water values. It should also be noted that, for the majority of the experiments reported here, the first estimate of AT (as shown in the “proportional error” column) was also extremely good. (iii) For a particular experiment, the standard deviation of the measured VFA and H2CO3* alkalinity data varied from 7.8 to 15.5 mg/L as HAc (average standard deviation of 6.7% for all samples) and from 6.2 to 17.2 mg/L as CaCO3 (average standard deviation of 1.45%), respectively, representing very good repetition in results. (iv) The proportional error column, representing a comparison between Ve as measured by the Gran function (the final three points of a particular experiment) and the Ve value derived from the first four data points used to determine the first estimate of AT and CT show that these two independent measurements are closely equal. This gives credence to the method and a means of fine-tuning the output data. Effect of the Phosphate, Ammonium, and Sulfide Weak Acid Subsystems. Normally, bioprocesses in which VFA and carbonate weak acid subsystems are present also contain the phosphate, ammonium, and sometimes the sulfide weak acid subsystems. When the total species concentrations for these subsystems are measured and known, they become integrated into the algorithm as constants, as shown previously. Normally, these species concentrations do not vary significantly in bioprocesses and there is little need for daily
measurement. However, when incorrect values of PT, NT, and ST are used in the algorithm, they will directly affect the H2CO3* alkalinity but may or may not influence VFA determined. Whether the VFA is effected or not depends on the relative values of AT and CT. The influence(s) of incorrect input values of these weak acid subsystems on the method can be explained from theoretical considerations. Earlier, it was stated that the calculation of the first estimate arises from four pH titration data points, the first two giving rise to an equation dominated by the H2CO3* alkalinity term. In this equation, around 50% of the total carbonate alkalinity is represented while the VFA alkalinity component is represented by around 7.5% of its total value. Because normally, in anaerobic reactors, CT is greater than AT, the H2CO3* alkalinity term is much higher. The second two pH points (the third and the fourth) are used to form a second equation dominated by the VFA alkalinity component providing that the CT to AT ratio is lower than about 7. It should be noted that the first equation represents the buffer region where the influence of the P and S subsystems (and, to a lesser extent, the N subsystem) is significant, whereas in the second equation representing a lower pH range, these subsystems will be practically negligible. Consequently, errors in PT, NT, and ST will influence the determination of CT (and H2CO3* alkalinity), but the VFA determination will be largely unaffected provided that the ratio CT to AT is less than about 7 to 1. It is shown next that, for a specific case where CT is 5 times greater than AT, the method gives excellent prediction for VFA even for large errors in PT, NT, and ST. However, for digesters where CT is significantly greater than AT, correct input of PT and ST is imperative for attaining accurate results. Effect of the Phosphate Weak Acid Subsystem. To assess the effect of error in PT input on the H2CO3* alkalinity and VFA prediction, a solution comprising 47.5 mg/L PO4-P, 200 mg/L VFA as HAc, and an carbonate alkalinity of 1000 mg/L as CaCO3 was made in the laboratory and tested using the method. The PT input to the algorithm was then varied from the actual value to 0, 95, and 200 mg/L as P. Results predicted from the titration data using the algorithm are presented in Table 2. From Table 2, it is apparent that the VFA concentration is insensitive to errors in the phosphate concentrations of up to 200 mg/L as P. Conversely, the CT (and therefore H2CO3* alkalinity) concentration is sensitive to errors in the phosphate input value. The reason for this is that the input VOL. 36, NO. 12, 2002 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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TABLE 3. Effect of H2S Loss on VFA Output (Average Measurement of Duplicates of Laboratory-Made Samples Composed of Initial Carbonate Alkalinity ) 1000 mg/L as CaCO3 + VFA ) 300 mg/L as HAc, + various ST Concentrations Measured at Dilution Ratio 4 to 1) sulfide concentration (mg/L as S)
average proportional error in first estimate (%)
VFA concentration (mg/L as HAc)
relative error in VFA concentration (%)
0 30 50 100 200
0.93 -0.66 0.59 -0.66 -7.22
291.2 298.9 294.2 290.8 264.4
2.9 0.4 1.9 3.1 11.9
error is virtually “absorbed” by the first two pH observations because the relevant equilibrium constant of the phosphate system (i.e., pKp2 ) 7.2) is much closer to pKC1 than to Pka. Consequently, for this CT to AT ratio, the algorithm predicts VFA concentration accurately irrespective of errors in PT value, but if accurate determination of H2CO3* alkalinity is required, an accurate phosphate concentration value needs to be known. This conclusion also applies to input errors in ST because the pK of the sulfide subsystem is in the same region (pKS ) 7.0). Effect of the Sulfide Weak Acid Subsystem. Normally, in standard anaerobic digesters, sulfide concentrations (ST) are low and their effect on the proposed method of measuring VFA and H2CO3* alkalinity is expected to be minimal. However, in some industrial applications or in sulfatereducing reactors, ST (total sulfide concentration) can be as high as 200 mg/L as S. At high concentrations, the volatility of the protonated form, H2S, during the titration procedure can cause an inaccuracy in pH observations that may lead to errors in the algorithm output. H2S loss does not influence the total alkalinity value, because it is not a proton-accepting species and, hence, will not effect the accuracy of the determination of Ve via the Gran function. However, sulfide losses change the ST during titration, and because the first estimate in the algorithm is based on a constant ST assumption, errors will occur. In this respect, an erroneous ST due to H2S loss is not equivalent to an inaccurate ST input. In the latter, the error is constant throughout the calculation, whereas in the former case the ST value changes during the titration as a function of the rate it is lost to the atmosphere. To appraise the extent of the error caused by H2S loss, a sample composed of a 1000 mg/L H2CO3* alkalinity and VFA ) 300 mg/L as HAc with various sulfide concentrations was titrated with standard acid (dilution ratio, 1 to 4) using the method. Results are presented in Table 3. The results indicate that, for ST up to 100 mg/L as S (in the undiluted sample), there is practically no H2S loss during the titration and no significant error occurs. For sulfide concentration of 200 mg/L as S (50 mg/L in the diluted sample), a consistent error of around 12% in the VFA measurement arises. Therefore, in the rare cases of sulfide concentrations, higher than about 100 mg/L as S, precautions should be made in executing the method. One possible way of overcoming the problem is
FIGURE 1. VFA, H2CO3* alkalinity, total alkalinity, and CT concentrations measured from UASB effluent samples with known additions of acetic acid. increasing the dilution ratio so that the sulfide concentration in the diluted sample is lower than 25 mg/L as S. Care should be taken to avoid “camouflaging” the VFA concentration by adjusting the acid strength and sample volume accordingly. Effect of the Ammonium Weak Acid Subsystem. From a theoretical standpoint, the high pK of the ammonium subsystem makes its effect on CT and AT determination largely insignificant in reactors operated at pH < 8 and with ammonium concentrations of up to about 1000 mg/L as N. To verify this statement experimentally and to assess the influence of an input error in NT on the program’s output, a laboratory-made solution containing 800 mg/L NH4-N, 200 mg/L VFA as HAc, and carbonate alkalinity of 1000 mg/L as CaCO3 was tested using the procedure suggested in this paper, and an error in NT concentration was then applied in the input data to the algorithm. Results are presented in Table 4. From Table 4, it can be concluded that the effect of errors in the ammonium input on the VFA and H2CO3* alkalinity concentrations are negligible and very small, respectively. Therefore, although it is recommended that accurate ammonium values be used, in most cases, it is not imperative for accurate execution of the method. Industrial Effluent. The objective here was to apply the method to “real life” effluent. Because the VFA concentration in well-controlled treatment systems is relatively low, the approach was to add known concentrations of acetic acid to the effluents and to determine whether the algorithm’s solution reflected the increase in VFA. Filtered effluent from a UASB reactor treating juice industry wastewater and comprising 86 mg/L NH4-N, 3.2 mg/L PO4-P, and EC ) 368 ms/m was tested using the proposed titration procedure. Thereafter, increasing aliquots of acetic acid were added and the samples were tested again. Results are presented in Figure 1. Figure 1 shows plotted the measured values for VFA, H2CO3* alkalinity, total alkalinity (as determined via the Gran approach), and CT determined versus the VFA (acetic acid) added. As expected, because no alkalinity and carbonate species were added, no changes in total alkalinity and CT were found. With regard to the VFA, the change in concen-
TABLE 4. Effect of Error in Ammonium Input on H2CO3* Alkalinity and VFA Results (Average of Three Laboratory-Made Samples Composed of Carbonate Alkalinity of 1000 mg/L as CaCO3 + VFA of 200 mg/L as HAc + NT of 800 mg/L as N) NH4-N concentration applied to program (mg/L as N)
average proportional error in first estimate (%)
VFA concentration (mg/L as HAc)
relative error in VFA concentration (%)
H2CO3* alkalinity (in sample) (mg/L as CaCO3)
relative error in H2CO3* alkalinity (%)
800 (true value) 0 2000
1.1 2.3 0.8
202.4 (3.9) 203.2 (3.7) 201.7 (3.6)
1.2 1.6 0.85
815 (2.3) 836 (3.9) 784 (3.5)
+2.5 -3.8
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tration measured closely equals the amount of acetic acid added for aliquots varying from 50 to 700 mg/L as HAc and resulted in a nearly linear line. Similarly, for H2CO3* alkalinity, the measured values decreased linearly with HAc added. H2CO3* destruction is to be expected because the HAc added to the sample is all converted to the dissociated form in the pH range of all the samples after addition (6.62 < pH < 8.16). Total alkalinity (representing proton accepting capacity of all weak acid subsystems) remained unchanged with acetic acid addition, because the H2CO3* alkalinity decreased by the same concentration that the VFA alkalinity increased. It should be noted that the industrial process treating this effluent employed lime addition for alkalinity control. It was found that CaCO3 precipitation occurred directly after filtration, resulting in interference in the test procedure. In all probability, the presence of organic matter in the undiluted solution inhibited such precipitation. The degree of precipitation (and interference) depended on the amount of time between filtration and test initiation. If the test is applied immediately, no observable interference is encountered.
Appendix: Abbreviated Guidelines for Correct Execution of the Method Apparatus. Good general-purpose pH meter and electrode, auto-titrator machine, magnetic stirrer with both slow and even stirring. Standards. Prepare and calibrate standard HCl and NaOH solutions at a concentration range of 0.06-0.08 M (NaOH is needed only if the samples are at pH lower than 6.85) as set out in Standard Methods (2). Procedure. 1. Filter the sample (preferably using 0.45 µm filter). 2. Measure EC (or TDS), phosphate, ammonium, and sulfide concentrations of the filtrate. 3. Dilute the raw sample to CT between 150 and 350 mg/L as CaCO3. 4. Recommended sample volume of 50-100 mL. 5. Record the temperature. 6. Stir slowly and allow pH to stabilize and then record initial pH. If this is lower than 6.85, add a known volume of standard NaOH solution. 7. Continue slow stirring and subsequently, titrate, using the standard acid down to pH values of approximately 6.85, 5.85, 5.25, and 4.25, all values (0.1 pH unit. Record each of these pH values and corresponding Vx. Make sure the pH reading is stable before continuing between points (this stage takes around 10 min in total).
8. After the final pH reading in step 7, add standard acid to lower the pH to around 2.7. At this stage, you can stir vigorously to attain faster mixing, but slow stir again before taking a pH reading (to avoid stirring effects on the probe). Record Vx and corresponding pHx values and a further two pairs of values down to around pH 2.4 (this stage takes around 2 min). 9. Enter data into computer program (available from the authors). The program will then give the following output: VFA concentration (mg/L as HAc), H2CO3* alkalinity (mg/L as CaCO3), CT (mg/L as CaCO3), the proportional error x, total alkalinity derived from the Gran function analysis (mg/L as CaCO3), and its regression coefficient (R2). 10. If the method has been executed with care, the proportional error should have a value of less than 5%, and the accuracy of the total alkalinity value should have a linear regression coefficient greater than 99.9%. If not, the most common problem occurs in obtaining a satisfactory proportional error value. Values in excess of 5% usually arise due to over vigorous stirring (causing CO2 loss) during the first four points of the titration or inadequate dilution of the raw sample.
Literature Cited (1) Loewenthal, R. E.; Ekama, G. A.; Marais G. v. R. Water SA 1989, 15 (1), 3-24. (2) APHA. Standard Methods for the Examination of Water and Wastewater, 18th ed.; APHA: 1992. (3) Montgomery, H. A. C.; Dymock, J. F.; Thom, N. S. Analyst 1962, 947-952. (4) Moosbrugger, R. E.; Wentzel, M. C.; Ekama, G. A.; Marais, G. v. R. Water SA 1993, 19 (1), 1-9. (5) Munch, E. V.; Greenfield, P. F. Water Res. 1998, 32 (8), 24312441. (6) Moosbrugger, R. E.; Wentzel, M. C.; Loewenthal, R. E.; Ekama, G. A.; Marais, G. v. R. Water SA 1993, 19 (1), 29-39. (7) Moosbrugger, R. E.; Wentzel, M. C.; Ekama, G. A.; Marais, G.v. R. Water Sci. Technol. 1993, 28 (2), 237-245. (8) Buchauer, K. Water SA 1998, 24 (1), 49-56. (9) Lahav, O.; Loewenthal, R. E. Water SA 2000, 26 (3), 389-391. (10) Loewenthal, R. E.; Marais, G. v. R. Water Research Commission of South Africa; Research Report No. W46; 1983. (11) Bates, R. G.; Macaskill, J. B. Analytical methods in oceanography. Adv. Chem. Ser. 1975, 147, 110. (12) Gran, G. Analyst 1952, 77, 661-671.
Received for review July 30, 2001. Revised manuscript received April 9, 2002. Accepted April 11, 2002. ES011169V
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