- Email: [email protected]
Dynamic modelling for operational design of a respirometer
•
Pergamon
Wat. Sci. Tech. Vo!. 33, No. I, pp. 297-309,1996. Copyright © 1996 IAWQ. Published by Elsevier Science Ltd Printed in Great Britain. All rights reserved. 0273-1223196 $15'00 + 0'00
PII:S0273-1223(96)OOI83-7
DYNAMIC MODELLING FOR OPERATIONAL DESIGN OF A RESPIROMETER E. Y. Giroux*, H. Spanjers*, G. G. Patry* and I. Takacs** * Department of Civil Engineering, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada ** Hydromantis Inc., 1685 Main Street W., Suite 302, Hamilton, Ontario, US 1G5, Canada
ABSTRACT The purpose of this paper is to demonstrate how dynamic modelling and simulation can effectively be used to assess the operation of an on-site respirometer. A dynamic model of the respirometer was developed using the General Purpose Simulator (GPS-X). The approach is appropriate for operational design of the respirometer in allowing the user to experiment with the instrument, through simulation, before it is actually operated. The model was able to replicate the operational modes of the respirometer. The dynamic model was found to be particularly useful in assessing difficulties associated with multiple respiration rate calculations, the effect of temperature on the respiration rate, and the detection of the endogenous respiration rate. Copyright © 1996 IAWQ. Published by Elsevier
Science Ltd
KEYWORDS Biochemical oxygen demand; modelling; oxygen uptake rate; respirometer; simulation.
INTRODUCTION Several investigators have suggested that respirometers could effectively be used for operational control of wastewater treatment plants. Watts and Garber (1993) described the features of a respirometer designed to provide plant personnel with real-time information on the oxygen uptake rate of activated sludge. Vanrolleghem et ai. (1994) described the features of an on-line respirographic bio-sensor for the characterization of load and toxicity of wastewater, while Spanjers et ai. (1994) described how respirometry could be used to measure short• term biochemical oxygen demand (BODst). Recently, Witteborg et ai. (1996) discussed how respirometry can be used to determine the influent readily biodegradable substrate (Ss) concentration. 297
E. Y. GIROUX
elal.
While there seems to have been a surge of recent activity on respirometry (lAWQ, in preparation), few plants are equipped with reliable maintenance free respirometers. It is only recently that the technology has evolved to a point where it can be used for real-time operational control of the activated sludge process. There is still some controversy as to the merit and usefulness of respirometric data, and it can be argued that existing respirometers may not provide all the information necessary for effective operational control. The inherent difficulty in the design and testing of respirometric instruments does warrant the use of dynamic modelling and simulation, and recent advances in these domains make possible the development of practical and representative models. Accordingly, the purpose of this paper is to illustrate how dynamic modelling and simulation can be used to define and assess the operational characteristics of an on-site respirometer.
THE RESPIROMETRIC CARAVAN The University of Ottawa respirometric caravan consists of two Minworth Systems Ltd. (MSL) respirometers located in a mobile caravan along with a variety of other instruments, including pH, temperature, conductivity and suspended solids monitors. The caravan has the advantage of offering protection against the harsh conditions commonly found at wastewater treatment plants, as well as providing a flexible and convenient environment for conducting research activities. It is equipped with two submersible pumps continuously feeding sludge and sewage through their respective sampling loops travelling through the caravan. Several ports located along the sampling loops allow for manual and computer-controlled sampling. The caravan and respirometers are shown in Figures I(a) ann l(b), respectively.
(a) Respirometric caravan.
(b) Respirometers.
Fig.!. The University of Ottawa respirometric caravan. Respirometers Whil,e the two ~espirometers are ~imilar i~ many aspects they differ slightly in design. Both respirometers con~Ist of a .10 lItre reactor fitted WIth a varIable speed mechanical mixer and air diffuser. Respirometer no. 1 is equIpped WIth. a MADOS-II self-cleanin~, self-calibrating dissolved oxygen probe along with a temperature sens?f. The dIssolved oxygen probe conSIsts of an LTH Electronics probe model OEI5 modified by MSL. In respIro~eter no. 2, most of the instrume~ts (dissolved oxygen, pH, temperature and conductivity probes) are housed In .a flow-t~rough celll?cated outSIde the reactor. The suspended solids concentration is measured in the reactor USIn~ MSL.s self-cleam~g suspend~d solids probe. The suspended solids concentration of the sewage is measured dIrectly In the samplIng loop USIng a BTG-MET 3000 monitor. The two respirometers also differ in
Dynamic modelling of a respirometer
299
their operational characteristics; partial sludge replacement for dilution of the biodegradable organic matter is only possible in respirometer no. 1, while addition of sewage, settling, and drawing can only be done in respirometer no. 2. Each respirometer is connected to a user-programmable computer control system. One of the key features of the system is the operational programming flexibility available to the user. A library of commands allows the user to customize and define different operating modes. They are: - actual respiration rate mode; - time to endogenous respiration rate mode; - time k) endogenous respiration rate mode (partially replaced sludge); - respjrogram mode. Respirometer no. 1 can operate in the first three modes, while respirometer no. 2 is operated in the respirogram mode. Measuring principle The respiration rate is calculated according to the principle in which the depletion of dissolved oxygen (DO) concentration is measured after ceasing the aeration in the respirometer (APRA, 1989). The respiration rate is the slope of the dissolved oxygen depletion curve. Oxygen transfer from the air surface should be minimized during DO depletion in order to get an accurate measure of the respiration rate. The aeration may be switched on and off alternately for additional cycles of respiration rate calculations. Alternatively, the sample can be removed and a new sludge sample introduced. A typical difficulty with this principle is the effect of limiting substrate and DO concentrations causing non• linear DO depletion. To address that, the respirometer is capable of calculating multiple respiration rates from a single depletion curve. The DO sampling frequency is user definable, as well as the interval over which the respiration rate is calculated. The number of DO values used to calculate the respiration rate can therefore be adjusted. Since respiration rates cannot be calculated during re-aeration of the sample, it is difficult with this method to obtain equally spaced points other than within the same DO depletion curve. MODELLING OF TRE RESPIROMETER A dynamic model of the respirometer was developed using the General Purpose Simulator (GPS-X) (Hydromantis, 1995). GPS-X is a modular multi-purpose modelling system for the simulation of wastewater treatment dynamics. While GPS-X is particularly well suited for dynamic modelling of large-scale wastewater treatment plants, it can also be used to model the intricate operation of a respirometer. The scheduling of discrete events (e.g. air on, air off, sample injection, etc.) can be specified and controlled. In addition to the comprehensive basic library of unit processes, GPS-X users can define their own process objects (e.g. respirometer object) which can then be added to the process library. In contrast to other simulation tools, GPS• X is a 'simulator', in that it allows users to interactively control all elements of the simulation as the simulation progresses (control variables as well as design variables). Building the respirometer model The development of a simulation model in GPS-X involves three basic steps: layout design; model selection; and parameter specification.
E. Y. GIROUX
30()
el
ul.
The respirometer layout is shown in Figure 2. The following objects were selected: two influent o~jects for sewage and activated sludge, a flow combiner, and a sequencing batch reactor (SBR) for the ~esplrometer. Because of the operational flexibility of the SBR, a single layout was used to model and simulate both respirometers. The influent objects for sewage and activated sludge addition act as a bridge between the respirometer and t.he 'real world'. They would ideally be replaced by a connection to a full-scale treatment plant model or fed with real data. The SBR object was selected because of the operational characteristics of respirometer no. 2 where settling and drawing operations are performed. LAVOUf~
I
locAlo~1 ~fIOCt\SS l'A&l.l\1 fIlE ~) --
w;w rj
~
~ ~ &tUOG€
MACkO 1I1UllYi enD'"
tp$-k
ti8ft.,
O£F1NC SOl,lRCt
SIM.lllAn..
1
I
ft£PlAet
I (It\£'lf.llloVli r aMftS£ I 'l.Ol;l(l
C()tmOl$ r \ • OUTflUT or
~). OPTll'Il2f ..
S(WACt
"",j""'..===;;Ea"""""===' ..... ~ .•0000iIiteaJ~r.; ...; =·=
Fig. 2. Model layout for the respirometer consisting of four objects: activated sludge influent, sewage influent, flow combiner, and SBR (respirometer). The following mathematical models were assigned to the individual objects: states-based model for both influent objects, and mantis model for the SBR. (The flow combiner does not require a model as it simply combines the incoming streams. During simulation, however, sewage addition and activated sludge addition can never be done at the same time). The mantis model for activated sludge is a superset of the IAWQ activated sludge model no. 1 (Henze et al., 1987). It differs from the IAWQ model in several ways: kinetic parameters are temperature dependent; two additional growth processes for autotrophic and heterotrophic bacteria are modelled; and alkalinity is not modelled. The mantis model was selected because temperature effects were to be investigated during simulation. The settling phase of the SBR uses a simple, one-dimensional settler model (Takacs et al., 1991). Default parameter values were used for all the models, except for the activated sludge object. Since an influent object was selected for the latter, biomass concentrations had to be adjusted to typical values found in aeration tanks. Simulation control panels were defined to allow interactive control of the simulation. An example of a control panel is presented in Figure 3. Three different types of control are shown: sliders, up/down button, and pull
Dynamic modelling of a respirometer
301
~own ~enu (e.g. control mode).
All control variables can thus be changed interactively and the effect is immediately seen on the simulator's output graphs.
Fig. 3. Example of a simulation control panel. The following variables were selected for graphical display (some are shown in Figure 2): - Suspended solids profile in the reactor; - Volume of liquid in the reactor; - Time required for a sludge sample to reach the endogenous respiration rate; - Number of sewage additions, and partial sludge replacements; - Number of re-aerations performed on a sample; - BOD st ; and - Variables used for the endogenous detection routine. Modes of operation As mentioned earlier, four modes of operation are currently available in the respirometric caravan. Because of the operational features of the respirometer, the sequence of actions performed by the instrument within each mode had to be programmed in the simulator's user-customizable files based on the ACSL simulation language (Mitchell and Gauthier Associates, 1995). This is in contrast to the normal use of the simulator where customization with the ACSL language is seldom done. This section will describe each simulated mode of operation.
Actual respiration rate mode. This mode was implemented to simulate the basic functionality of the respirometer, i.e. measuring the actual respiration rate. The term 'actual' is used here to denote the respiration rate of the sludge when it is sampled from the aeration tank. In this mode, the respiration reactor is first filled with activated sludge and aerated after which the respiration rate calculation is done. The sample is then removed and replaced with a fresh one. Watts and Garber (1993) described the operational aspects of this mode. The sequence of steps necessary to calculate the actual respiration rate is shown in Figure 4. The respiration rate is the slope of the DO depletion curve. The DO is sampled every three seconds. The solid line in the figure is the instantaneous respiration rate calculated by the activated sludge model assigned to the SBR object.
E.
302
Y. GIROUX et al.
In this case, the time between respiration rate calculations is approximately six minutes, however this can ~aI) considerably depending on the reactor volume, the DO set points, and the characteri.stics of the slud~e. The tI~e between sludge sampling and respiration rate calculation is approximately four mmutes due to fil.hn~, aerating and idle time during DO sampling. This can possibly yield a rate lower than the 'real' actual reSpIratIOn rate of the sludge at the time of sampling. 70 ,----_----------~---~--__, 10
•
9
60
8 -
respiration rate (instantaneous)
7 ~
• respiration rate (respirometer)
6
• DO concentration
5
....... -....•
. '
10 ---.•----
..'
-.-
..
aerating
calculating respiration rate
§
~
E Ql
o
....... .'
.s
4 § o
"--- ...............
emptying tank
..-'"
o
3 0 2 1
filling tank OL---~---...L---~~----J----~------'O
L1
min--l
time
Fig. 4. Actual respiration rate mode.
Time to endogenous respiration rate mode. This mode is similar to the previous one except that instead of replacing the activated sludge sample after one respiration rate calculation, the aeration is switched on and off alternately while the respiration rate is calculated until the endogenous respiration rate is detected. MSL's respirometers use a routine where the endogenous respiration rate is detected when the current respiration rate and the change between the current and previous rate are less than user definable values. This routine lacks robustness and should be improved. Because the endogenous respiration rate detection is important in respirometry, a proper detection routine should be developed. Following is a description of the routine. Due to the nature of the activated sludge process, it is very difficult to detect automatically the time when all the readily biodegradable substrate is exhausted. The approach used to model decay in the mantis activated sludge model is based on the death-regeneration concept. Consequently, readily biodegradable substrate is always present and there will never be a constant endogenous respiration rate. In order to minimize the effect of DO measurement errors on the calculated respiration rates, a moving average on the respiration rate is calculated. The number of points used in this moving average can be adjusteJ, but would typically range between three and five points. The standard deviation of the respiration rate values used in the moving average is calculated. Set points are then defined for both the moving average and the standard deviation, and an endogenous respiration rate detection is triggered when both fall below their respective set points. Based on experience with the model and observation of the time series for the individual substrate components, the user can adjust the set points to appropriate values. It is important to note that the endogenous respiration rate detection is currently applied to instantaneous respiration rates calculated by the activated sludge model assigned to the SBR object. Work is under way to test and adapt the detection routine on respiration rates calculated by the respirometer.
Dynamic modelling of a respirometer
303
Typical results for this mode are depicted in Figure 5. As in the previous mode, the first respiration rate value is calculated approximately four minutes after the activated sludge is sampled. Subsequent respiration rates are calculated every 48 seconds within a single DO depletion curve (the linear regression being done on 17 DO values sampled every three seconds). No respiration rates are calculated during re-aeration. 60 -r-~--~-----~---.,..--~--~---,
50
10 Time 10 endogenous
M - - - - - - - - respiration rale - - - - - - - -....
o ~ 10 min-l Time
Fig. 5. Time to endogenous respiration rate mode. Time to endogenous respiration rate mode (partially replaced sludge). In this mode, rather than replacing the total activated sludge sample when the endogenous respiration rate is detected, only a fraction of it is drawn and replaced before starting the next sequence of respiration rate calculations. The fraction of sludge is drawn while the sludge is mixed to prevent changes in biomass concentration. This operation leads to a dilution of biodegradable organic material in the fresh sludge, and a smaller respirogram is obtained (see Figure 6).
The time needed to reach the endogenous respiration rate for the partially replaced sample is shorter than the equivalent time needed for the undiluted sludge sample. The latter can be calculated by taking into account the dilution factor. In Figure 6, the endogenous respiration rate of the partially replaced sample was 76 minutes. Four litres of sludge were then replaced (in a total volume of 10 litres), and the time needed for the partially replaced sludge to reach the endogenous respiration rate was 32 minutes. Taking into account the dilution factor, this gives a time to endogenous respiration rate of 80 minutes which is close to the measured 76 minutes.
E. Y. GIROUX
304 60
et af.
,.----~----~------~.-.-.~~-
50
10
• • Time to endogenous
•
~. espiration rate (partialfy Time to endogenous I replaced sludge) 1 4 - - - - - respiration rate -----+~
~
OL.-----';----~---~----'--~--~--'--~
L20min-J
time
Fig. 6. Time to endogenous respiration rate mode (partially replaced sludge). Respirogram mode. Under this mode of operation the reactor is filled with activated sludge and respiration rate measurements are started. When the model detects the endogenous respiration rate, a user-definable volume of sewage is introduced into the reactor. Respiration rate calculations are repeated until all the readily biodegradable matter is oxidized (endogenous respiration rate reached). The addition of sewage can be repeated until a pre-defined volume is reached. The sludge content of the reactor is then allowed to settle, and a pre• defined volume of clarified water is drawn from the top of the reactor. The addition of sewage and associated respiration rate calculations generate a respirogram.
A simulation output for this mode of operation is presented in Figure 7. The initial measurements (first 76 minutes) are in fact analogous to the output from the time to endogenous modes shown previously (Figures 5 and 6). This is done to ensure that the readily biodegradable substrate in the activated sludge sampled from the aeration tank is exhausted (endogenous respiration rate) before proceeding with the sewage sample addition. The BODst of the sewage sample can be calculated by integrating the area under the respirogram and subtracting the endogenous respiration area. In Figure 7, two successive identical sewage additions were completed before the reactor was settled and supernatant drawn. The apparent decrease in the maximum respiration rate attained for the second sewage addition is the result of sludge dilution. This can easily be accounted for when calculating the BODst •
Dynamic modelling of a respirometer
305
6Or-----..--~--~---,--__._--....,......--.,..__-_.,
50
10
time
Fig. 7. Respirogram mode. SIMULATION EXPERIMENTS The following examples illustrate how the information obtained through simulation can be used to assess the operation of the respirometer. Effect of DO sample size Because of inherent measurement errors in DO concentrations, the respiration rate is very sensitive to the number of DO values used when calculating the slope of the DO depletion curve. This is illustrated in Figure 8 where three different sample sizes were used for calculating the respiration rate. Two consecutive DO depletion curves using 10 seconds DO sampling intervals are shown in Figure 8. In Figure 8(a), all the points (n=40) within one DO depletion curve were used to calculate the respiration rate, while sample sizes of 20 and 5 DO points were used in Figure 8(b) and 8(c), respectively. This shows that a decrease in sample size results in more respiration rates being calculated, but also introduces more noise in the calculated rates. Examples of simulated respirograms obtained by calculating the respiration rate with two different DO sample sizes are shown in Figure 9. Sample sizes of 9 and 17 data points were used in Figure 9(a) and 9(b), respectively. The noise on the respiration rate in Figures 9(a) is obviously unacceptable. The choice of the optimum sample size is influenced by the magnitude of measurement error on the DO concentration, as well as the accuracy and extent of information needed.
E. Y. GIROUX er al.
306
20
4.5
.--....
....... ..""-. .... ...... ....
...
.....
~35 0:
9
10
3
~
i
~
. ....
..... .....
2 .5
...
2
Ie Z 17 !16 o!! ~ 15
......
.....
8
n-4O
19
8
...... ......
iI 14
~
! 13 12
II
1.5 400
200
0
10
1000
800
600
200
0
600
400
800
1000
time(s)
time (5)
(a) 20
4.5
.•..... l3.5 ........ ....... i .
..... ...... .....
4
3
~
.....
~
8 2 .5 2
.....
Ie
:c 17
......
..... ...
!,6 .! ~ 15
~ 14
... ...
....
n-20
19
~
.....
I!! 13 12 11
1.5 200
0
400
600
eoo
10
1000
0
200
600
400
800
1000
time(s)
time(s)
(b) 20
4.5
...5
19 4
18
~3.5
:C17
t'
.! ! 15
8
t'6
~ 14
2 .5
1,3
....
2
12 11 10
1.5 0
200
400
600
800
1000
time (5)
0
200
400
600 time(s)
(C) Fig. 8. Effect of the DO sample size on the calculated respiration rate.
800
1000
307
Dynamic modelling of a respirometer
4 O r - - - - - - - _ - -_ _--_-..,
4Or-----------------.,
35
35
30
. ..
o ~ 8 min
..
...
---I
30
..... .
..
o
Time
(a) Sample size 9.
~
8 min
----I
Time
(b) Sample size 17.
Fig. 9. Effect of the DO sample size on simulated respirograms. Another consequence of the choice of DO sample size on the calculated respiration rate is the introduction of a time shift. Given that the respiration rate calculation is done at the end of the interval over which DO is sampled, and is stamped with the time at which the calculation is made, a time shift of half the total DO sampling interval is introduced. For example, a respiration rate calculated over a total sampling interval of one minute would be time-stamped 30 seconds later than it should. This time shift is obviously shorter as the respiration rate calculation frequency increases. The effect of the time shift is illustrated in Figure 10. In this figure, only one respiration rate is calculated for each DO depletion curve. Also apparent in the figure is the irregular frequency of the respiration rate calculation. The solid line is the instantaneous respiration rate calculated by the activated sludge model. 40
\,»1,
35
30 ':2
J
-a, 25
§. C1l
~ 20 c: 0
""
\,
l-
.[ 15
l-, -~
l!l
10 5 0
-_ .. 8min
._._-Time
Fig. 10. Effect of the DO sample size on calculated respiration rate: time shift.
Temperature effects Other simulations were conducted to investigate the effect of temperature on the BODs! calculated from the respirogram. The effect of temperature can be important because of the seasonal temperature variations in the caravan. A sludge sample that is to stay in the respirometers for some time may gradually warm up which may have a significant impact on the respiration rate.
E. Y. GIROUX et al.
308
In the simulation shown in Figure 11, the respirometer was in the respirogram mode, and two successive sewagl additions were done. Each sewage sample had the same characteristics except for the liquid temperature. The first sewage sample was at 20°C, while the second was at 15°C. The effect of temperature on the respiratior rate is obvious: at 15°C, the maximum respiration rate obtained was lower, and the time for the sample to read the endogenous respiration rate was longer. From the simulated respirograms, the effect of temperature on BODs! can also be assessed. Since both sewage samples were identical (BODs! 220 mg/l), the area under both respirogram should lead to the sam~ value. In thi~ example, the area under the first and second respirogram was 210.8 mg/l and 2~9.2. mg/l, re~pect1vely. The are, under the respirogram is sensitive to the time at which the endogenous respiratIOn rate IS detected, and the results suggest that detection of the endogenous respiration rate was properly done in this case. 40
- - - - - - - - - - --_. - - - - -.- -- - - - - . - - - "
40
35
35
30
30
. o
10
o
L.-1O m1n-l
..
L.-l0mln
time
Fig. 11 Effect of the temperature on respirograms.
SUMMARY AND CONCLUSIONS The purpose of this work was to develop a dynamic model capable of describing the operation of an on-site respirometer. The simulation environment used (GPS-X) proved to be suitable for the development of the model. The model was able to successfully reproduce the current operational state of the respirometer. The routine used to detect the endogenous respiration rate in the respirometer is currently causing problems and a more robust routine had to be developed in the model. The routine developed is currently applied tc instantaneous respiration rates calculated by the activated sludge model, and work is under way to apply it tc respiration rates calculated by the respirometer model. The dynamic model provided us with a bettel understanding of the behaviour of the instrument. Moreover, the model can easily be enhanced to include anc test new modes of operation before they are actually implemented in the respirometer. The effect of the DO sample size on the calculated respiration rate was found to be important, and care must bl taken to ensure that measurement errors are kept to a minimum to ensure reliable respiration rate measurements The calculation of multiple respiration rates along a single DO depletion curve provides more respiration ratl data and is a more accurate representation of reality in case of limiting DO and substrate, but also produces nois: respiration rates. This project is part of a more comprehensive study designed to maXlITuze the information content 0 respirograms and respirometric experiments. As part of this project dynamic model parameters estimation wi] be linked directly to respirometric data, allowing us to maintain model calibration and monitor changes i
Dynamic modelling of a respirometer
309
biochemical parameters. A number of technologies will be coupled together in order to maximize the information content resulting from the operation of a respirometer. Technologies that will be investigated include: neural networks, decision support systems, qualitative modelling and statistically based models.
ACKNOWLEDGEMENTS This work was funded in part by: the Ministry of Environment and Energy (Ontario) under the ETP program; the Wastewater Technology Centre (Burlington, Ontario); Hydromantis, Inc.; and the Natural Sciences and Engineering Research Council of Canada (Grant no. 0156887). REFERENCES APHA (1989). Standard Methods for the examination of Water and Wastewater, 17th edition, American Public Health Association, Washington, DC, USA. Henze, M., Grady, C.P.L. Jr., Gujer, W., Marais, G.v.R. and Matsuo, T. (1987). IAWPRC Task Group on Mathematical Modelling for Design and Operation of Biological Wastewater Treatment. Activated Sludge Model No.1, Scientific and Technical Reports No.1, IAWPRC, London, England. Hydromantis, Inc. (1995). GPS-X Technical Reference. Hydromantis, Inc., Hamilton, Ontario, Canada. IAWQ. Respirometry in Control ofActivated Sludge Processes. Scientific and Technical Report. To be published. Mitchell and Gauthier Associates (1995). Advanced Continuous Simulation Language (ACSL). Reference Manual. Mitchell and Gauthier Associates, Concord, Massachusetts. Spanjers, H., Olsson, G. and Klapwijk, A. (1994). Determining short-term biochemical oxygen demand and respiration rate in an aeration tank by using respirometry and estimation. Wat. Res., 28 (7), 1571-1583. Takacs, 1., Patry, G. G. and Nolasco, D. (1991). A dynamic model of the clarification-thickening process. Wat. Res., 25 (10),1263-1271. Vanrolleghem, P., Kong, Z., Rombouts, G. and Verstraete, W. (1994). An On-line Respirographic Biosensor for the Characterization of Load and Toxicity of Wastewaters. J. Chem. Tech/. Biotechnol., 59,321-333. Watts, J. B. and Garher, W. F. (1993). On-line Respirometry: A Powerful Tool for Activated Sludge Plant Operation and Design. Wat. Sci. Tech., 28(11-12), 389-399. Witteborg, A., van der Last, A., Hamming, R. and Hemmers, 1. (1996). Respirometry for determination of the influent Ss-concentration. Wat. Sci. Tech., 33(1), this issue.
JWST 33:1-L
Pergamon
Wat. Sci. Tech. Vo!. 33, No. I, pp. 297-309,1996. Copyright © 1996 IAWQ. Published by Elsevier Science Ltd Printed in Great Britain. All rights reserved. 0273-1223196 $15'00 + 0'00
PII:S0273-1223(96)OOI83-7
DYNAMIC MODELLING FOR OPERATIONAL DESIGN OF A RESPIROMETER E. Y. Giroux*, H. Spanjers*, G. G. Patry* and I. Takacs** * Department of Civil Engineering, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada ** Hydromantis Inc., 1685 Main Street W., Suite 302, Hamilton, Ontario, US 1G5, Canada
ABSTRACT The purpose of this paper is to demonstrate how dynamic modelling and simulation can effectively be used to assess the operation of an on-site respirometer. A dynamic model of the respirometer was developed using the General Purpose Simulator (GPS-X). The approach is appropriate for operational design of the respirometer in allowing the user to experiment with the instrument, through simulation, before it is actually operated. The model was able to replicate the operational modes of the respirometer. The dynamic model was found to be particularly useful in assessing difficulties associated with multiple respiration rate calculations, the effect of temperature on the respiration rate, and the detection of the endogenous respiration rate. Copyright © 1996 IAWQ. Published by Elsevier
Science Ltd
KEYWORDS Biochemical oxygen demand; modelling; oxygen uptake rate; respirometer; simulation.
INTRODUCTION Several investigators have suggested that respirometers could effectively be used for operational control of wastewater treatment plants. Watts and Garber (1993) described the features of a respirometer designed to provide plant personnel with real-time information on the oxygen uptake rate of activated sludge. Vanrolleghem et ai. (1994) described the features of an on-line respirographic bio-sensor for the characterization of load and toxicity of wastewater, while Spanjers et ai. (1994) described how respirometry could be used to measure short• term biochemical oxygen demand (BODst). Recently, Witteborg et ai. (1996) discussed how respirometry can be used to determine the influent readily biodegradable substrate (Ss) concentration. 297
E. Y. GIROUX
elal.
While there seems to have been a surge of recent activity on respirometry (lAWQ, in preparation), few plants are equipped with reliable maintenance free respirometers. It is only recently that the technology has evolved to a point where it can be used for real-time operational control of the activated sludge process. There is still some controversy as to the merit and usefulness of respirometric data, and it can be argued that existing respirometers may not provide all the information necessary for effective operational control. The inherent difficulty in the design and testing of respirometric instruments does warrant the use of dynamic modelling and simulation, and recent advances in these domains make possible the development of practical and representative models. Accordingly, the purpose of this paper is to illustrate how dynamic modelling and simulation can be used to define and assess the operational characteristics of an on-site respirometer.
THE RESPIROMETRIC CARAVAN The University of Ottawa respirometric caravan consists of two Minworth Systems Ltd. (MSL) respirometers located in a mobile caravan along with a variety of other instruments, including pH, temperature, conductivity and suspended solids monitors. The caravan has the advantage of offering protection against the harsh conditions commonly found at wastewater treatment plants, as well as providing a flexible and convenient environment for conducting research activities. It is equipped with two submersible pumps continuously feeding sludge and sewage through their respective sampling loops travelling through the caravan. Several ports located along the sampling loops allow for manual and computer-controlled sampling. The caravan and respirometers are shown in Figures I(a) ann l(b), respectively.
(a) Respirometric caravan.
(b) Respirometers.
Fig.!. The University of Ottawa respirometric caravan. Respirometers Whil,e the two ~espirometers are ~imilar i~ many aspects they differ slightly in design. Both respirometers con~Ist of a .10 lItre reactor fitted WIth a varIable speed mechanical mixer and air diffuser. Respirometer no. 1 is equIpped WIth. a MADOS-II self-cleanin~, self-calibrating dissolved oxygen probe along with a temperature sens?f. The dIssolved oxygen probe conSIsts of an LTH Electronics probe model OEI5 modified by MSL. In respIro~eter no. 2, most of the instrume~ts (dissolved oxygen, pH, temperature and conductivity probes) are housed In .a flow-t~rough celll?cated outSIde the reactor. The suspended solids concentration is measured in the reactor USIn~ MSL.s self-cleam~g suspend~d solids probe. The suspended solids concentration of the sewage is measured dIrectly In the samplIng loop USIng a BTG-MET 3000 monitor. The two respirometers also differ in
Dynamic modelling of a respirometer
299
their operational characteristics; partial sludge replacement for dilution of the biodegradable organic matter is only possible in respirometer no. 1, while addition of sewage, settling, and drawing can only be done in respirometer no. 2. Each respirometer is connected to a user-programmable computer control system. One of the key features of the system is the operational programming flexibility available to the user. A library of commands allows the user to customize and define different operating modes. They are: - actual respiration rate mode; - time to endogenous respiration rate mode; - time k) endogenous respiration rate mode (partially replaced sludge); - respjrogram mode. Respirometer no. 1 can operate in the first three modes, while respirometer no. 2 is operated in the respirogram mode. Measuring principle The respiration rate is calculated according to the principle in which the depletion of dissolved oxygen (DO) concentration is measured after ceasing the aeration in the respirometer (APRA, 1989). The respiration rate is the slope of the dissolved oxygen depletion curve. Oxygen transfer from the air surface should be minimized during DO depletion in order to get an accurate measure of the respiration rate. The aeration may be switched on and off alternately for additional cycles of respiration rate calculations. Alternatively, the sample can be removed and a new sludge sample introduced. A typical difficulty with this principle is the effect of limiting substrate and DO concentrations causing non• linear DO depletion. To address that, the respirometer is capable of calculating multiple respiration rates from a single depletion curve. The DO sampling frequency is user definable, as well as the interval over which the respiration rate is calculated. The number of DO values used to calculate the respiration rate can therefore be adjusted. Since respiration rates cannot be calculated during re-aeration of the sample, it is difficult with this method to obtain equally spaced points other than within the same DO depletion curve. MODELLING OF TRE RESPIROMETER A dynamic model of the respirometer was developed using the General Purpose Simulator (GPS-X) (Hydromantis, 1995). GPS-X is a modular multi-purpose modelling system for the simulation of wastewater treatment dynamics. While GPS-X is particularly well suited for dynamic modelling of large-scale wastewater treatment plants, it can also be used to model the intricate operation of a respirometer. The scheduling of discrete events (e.g. air on, air off, sample injection, etc.) can be specified and controlled. In addition to the comprehensive basic library of unit processes, GPS-X users can define their own process objects (e.g. respirometer object) which can then be added to the process library. In contrast to other simulation tools, GPS• X is a 'simulator', in that it allows users to interactively control all elements of the simulation as the simulation progresses (control variables as well as design variables). Building the respirometer model The development of a simulation model in GPS-X involves three basic steps: layout design; model selection; and parameter specification.
E. Y. GIROUX
30()
el
ul.
The respirometer layout is shown in Figure 2. The following objects were selected: two influent o~jects for sewage and activated sludge, a flow combiner, and a sequencing batch reactor (SBR) for the ~esplrometer. Because of the operational flexibility of the SBR, a single layout was used to model and simulate both respirometers. The influent objects for sewage and activated sludge addition act as a bridge between the respirometer and t.he 'real world'. They would ideally be replaced by a connection to a full-scale treatment plant model or fed with real data. The SBR object was selected because of the operational characteristics of respirometer no. 2 where settling and drawing operations are performed. LAVOUf~
I
locAlo~1 ~fIOCt\SS l'A&l.l\1 fIlE ~) --
w;w rj
~
~ ~ &tUOG€
MACkO 1I1UllYi enD'"
tp$-k
ti8ft.,
O£F1NC SOl,lRCt
SIM.lllAn..
1
I
ft£PlAet
I (It\£'lf.llloVli r aMftS£ I 'l.Ol;l(l
C()tmOl$ r \ • OUTflUT or
~). OPTll'Il2f ..
S(WACt
"",j""'..===;;Ea"""""===' ..... ~ .•0000iIiteaJ~r.; ...; =·=
Fig. 2. Model layout for the respirometer consisting of four objects: activated sludge influent, sewage influent, flow combiner, and SBR (respirometer). The following mathematical models were assigned to the individual objects: states-based model for both influent objects, and mantis model for the SBR. (The flow combiner does not require a model as it simply combines the incoming streams. During simulation, however, sewage addition and activated sludge addition can never be done at the same time). The mantis model for activated sludge is a superset of the IAWQ activated sludge model no. 1 (Henze et al., 1987). It differs from the IAWQ model in several ways: kinetic parameters are temperature dependent; two additional growth processes for autotrophic and heterotrophic bacteria are modelled; and alkalinity is not modelled. The mantis model was selected because temperature effects were to be investigated during simulation. The settling phase of the SBR uses a simple, one-dimensional settler model (Takacs et al., 1991). Default parameter values were used for all the models, except for the activated sludge object. Since an influent object was selected for the latter, biomass concentrations had to be adjusted to typical values found in aeration tanks. Simulation control panels were defined to allow interactive control of the simulation. An example of a control panel is presented in Figure 3. Three different types of control are shown: sliders, up/down button, and pull
Dynamic modelling of a respirometer
301
~own ~enu (e.g. control mode).
All control variables can thus be changed interactively and the effect is immediately seen on the simulator's output graphs.
Fig. 3. Example of a simulation control panel. The following variables were selected for graphical display (some are shown in Figure 2): - Suspended solids profile in the reactor; - Volume of liquid in the reactor; - Time required for a sludge sample to reach the endogenous respiration rate; - Number of sewage additions, and partial sludge replacements; - Number of re-aerations performed on a sample; - BOD st ; and - Variables used for the endogenous detection routine. Modes of operation As mentioned earlier, four modes of operation are currently available in the respirometric caravan. Because of the operational features of the respirometer, the sequence of actions performed by the instrument within each mode had to be programmed in the simulator's user-customizable files based on the ACSL simulation language (Mitchell and Gauthier Associates, 1995). This is in contrast to the normal use of the simulator where customization with the ACSL language is seldom done. This section will describe each simulated mode of operation.
Actual respiration rate mode. This mode was implemented to simulate the basic functionality of the respirometer, i.e. measuring the actual respiration rate. The term 'actual' is used here to denote the respiration rate of the sludge when it is sampled from the aeration tank. In this mode, the respiration reactor is first filled with activated sludge and aerated after which the respiration rate calculation is done. The sample is then removed and replaced with a fresh one. Watts and Garber (1993) described the operational aspects of this mode. The sequence of steps necessary to calculate the actual respiration rate is shown in Figure 4. The respiration rate is the slope of the DO depletion curve. The DO is sampled every three seconds. The solid line in the figure is the instantaneous respiration rate calculated by the activated sludge model assigned to the SBR object.
E.
302
Y. GIROUX et al.
In this case, the time between respiration rate calculations is approximately six minutes, however this can ~aI) considerably depending on the reactor volume, the DO set points, and the characteri.stics of the slud~e. The tI~e between sludge sampling and respiration rate calculation is approximately four mmutes due to fil.hn~, aerating and idle time during DO sampling. This can possibly yield a rate lower than the 'real' actual reSpIratIOn rate of the sludge at the time of sampling. 70 ,----_----------~---~--__, 10
•
9
60
8 -
respiration rate (instantaneous)
7 ~
• respiration rate (respirometer)
6
• DO concentration
5
....... -....•
. '
10 ---.•----
..'
-.-
..
aerating
calculating respiration rate
§
~
E Ql
o
....... .'
.s
4 § o
"--- ...............
emptying tank
..-'"
o
3 0 2 1
filling tank OL---~---...L---~~----J----~------'O
L1
min--l
time
Fig. 4. Actual respiration rate mode.
Time to endogenous respiration rate mode. This mode is similar to the previous one except that instead of replacing the activated sludge sample after one respiration rate calculation, the aeration is switched on and off alternately while the respiration rate is calculated until the endogenous respiration rate is detected. MSL's respirometers use a routine where the endogenous respiration rate is detected when the current respiration rate and the change between the current and previous rate are less than user definable values. This routine lacks robustness and should be improved. Because the endogenous respiration rate detection is important in respirometry, a proper detection routine should be developed. Following is a description of the routine. Due to the nature of the activated sludge process, it is very difficult to detect automatically the time when all the readily biodegradable substrate is exhausted. The approach used to model decay in the mantis activated sludge model is based on the death-regeneration concept. Consequently, readily biodegradable substrate is always present and there will never be a constant endogenous respiration rate. In order to minimize the effect of DO measurement errors on the calculated respiration rates, a moving average on the respiration rate is calculated. The number of points used in this moving average can be adjusteJ, but would typically range between three and five points. The standard deviation of the respiration rate values used in the moving average is calculated. Set points are then defined for both the moving average and the standard deviation, and an endogenous respiration rate detection is triggered when both fall below their respective set points. Based on experience with the model and observation of the time series for the individual substrate components, the user can adjust the set points to appropriate values. It is important to note that the endogenous respiration rate detection is currently applied to instantaneous respiration rates calculated by the activated sludge model assigned to the SBR object. Work is under way to test and adapt the detection routine on respiration rates calculated by the respirometer.
Dynamic modelling of a respirometer
303
Typical results for this mode are depicted in Figure 5. As in the previous mode, the first respiration rate value is calculated approximately four minutes after the activated sludge is sampled. Subsequent respiration rates are calculated every 48 seconds within a single DO depletion curve (the linear regression being done on 17 DO values sampled every three seconds). No respiration rates are calculated during re-aeration. 60 -r-~--~-----~---.,..--~--~---,
50
10 Time 10 endogenous
M - - - - - - - - respiration rale - - - - - - - -....
o ~ 10 min-l Time
Fig. 5. Time to endogenous respiration rate mode. Time to endogenous respiration rate mode (partially replaced sludge). In this mode, rather than replacing the total activated sludge sample when the endogenous respiration rate is detected, only a fraction of it is drawn and replaced before starting the next sequence of respiration rate calculations. The fraction of sludge is drawn while the sludge is mixed to prevent changes in biomass concentration. This operation leads to a dilution of biodegradable organic material in the fresh sludge, and a smaller respirogram is obtained (see Figure 6).
The time needed to reach the endogenous respiration rate for the partially replaced sample is shorter than the equivalent time needed for the undiluted sludge sample. The latter can be calculated by taking into account the dilution factor. In Figure 6, the endogenous respiration rate of the partially replaced sample was 76 minutes. Four litres of sludge were then replaced (in a total volume of 10 litres), and the time needed for the partially replaced sludge to reach the endogenous respiration rate was 32 minutes. Taking into account the dilution factor, this gives a time to endogenous respiration rate of 80 minutes which is close to the measured 76 minutes.
E. Y. GIROUX
304 60
et af.
,.----~----~------~.-.-.~~-
50
10
• • Time to endogenous
•
~. espiration rate (partialfy Time to endogenous I replaced sludge) 1 4 - - - - - respiration rate -----+~
~
OL.-----';----~---~----'--~--~--'--~
L20min-J
time
Fig. 6. Time to endogenous respiration rate mode (partially replaced sludge). Respirogram mode. Under this mode of operation the reactor is filled with activated sludge and respiration rate measurements are started. When the model detects the endogenous respiration rate, a user-definable volume of sewage is introduced into the reactor. Respiration rate calculations are repeated until all the readily biodegradable matter is oxidized (endogenous respiration rate reached). The addition of sewage can be repeated until a pre-defined volume is reached. The sludge content of the reactor is then allowed to settle, and a pre• defined volume of clarified water is drawn from the top of the reactor. The addition of sewage and associated respiration rate calculations generate a respirogram.
A simulation output for this mode of operation is presented in Figure 7. The initial measurements (first 76 minutes) are in fact analogous to the output from the time to endogenous modes shown previously (Figures 5 and 6). This is done to ensure that the readily biodegradable substrate in the activated sludge sampled from the aeration tank is exhausted (endogenous respiration rate) before proceeding with the sewage sample addition. The BODst of the sewage sample can be calculated by integrating the area under the respirogram and subtracting the endogenous respiration area. In Figure 7, two successive identical sewage additions were completed before the reactor was settled and supernatant drawn. The apparent decrease in the maximum respiration rate attained for the second sewage addition is the result of sludge dilution. This can easily be accounted for when calculating the BODst •
Dynamic modelling of a respirometer
305
6Or-----..--~--~---,--__._--....,......--.,..__-_.,
50
10
time
Fig. 7. Respirogram mode. SIMULATION EXPERIMENTS The following examples illustrate how the information obtained through simulation can be used to assess the operation of the respirometer. Effect of DO sample size Because of inherent measurement errors in DO concentrations, the respiration rate is very sensitive to the number of DO values used when calculating the slope of the DO depletion curve. This is illustrated in Figure 8 where three different sample sizes were used for calculating the respiration rate. Two consecutive DO depletion curves using 10 seconds DO sampling intervals are shown in Figure 8. In Figure 8(a), all the points (n=40) within one DO depletion curve were used to calculate the respiration rate, while sample sizes of 20 and 5 DO points were used in Figure 8(b) and 8(c), respectively. This shows that a decrease in sample size results in more respiration rates being calculated, but also introduces more noise in the calculated rates. Examples of simulated respirograms obtained by calculating the respiration rate with two different DO sample sizes are shown in Figure 9. Sample sizes of 9 and 17 data points were used in Figure 9(a) and 9(b), respectively. The noise on the respiration rate in Figures 9(a) is obviously unacceptable. The choice of the optimum sample size is influenced by the magnitude of measurement error on the DO concentration, as well as the accuracy and extent of information needed.
E. Y. GIROUX er al.
306
20
4.5
.--....
....... ..""-. .... ...... ....
...
.....
~35 0:
9
10
3
~
i
~
. ....
..... .....
2 .5
...
2
Ie Z 17 !16 o!! ~ 15
......
.....
8
n-4O
19
8
...... ......
iI 14
~
! 13 12
II
1.5 400
200
0
10
1000
800
600
200
0
600
400
800
1000
time(s)
time (5)
(a) 20
4.5
.•..... l3.5 ........ ....... i .
..... ...... .....
4
3
~
.....
~
8 2 .5 2
.....
Ie
:c 17
......
..... ...
!,6 .! ~ 15
~ 14
... ...
....
n-20
19
~
.....
I!! 13 12 11
1.5 200
0
400
600
eoo
10
1000
0
200
600
400
800
1000
time(s)
time(s)
(b) 20
4.5
...5
19 4
18
~3.5
:C17
t'
.! ! 15
8
t'6
~ 14
2 .5
1,3
....
2
12 11 10
1.5 0
200
400
600
800
1000
time (5)
0
200
400
600 time(s)
(C) Fig. 8. Effect of the DO sample size on the calculated respiration rate.
800
1000
307
Dynamic modelling of a respirometer
4 O r - - - - - - - _ - -_ _--_-..,
4Or-----------------.,
35
35
30
. ..
o ~ 8 min
..
...
---I
30
..... .
..
o
Time
(a) Sample size 9.
~
8 min
----I
Time
(b) Sample size 17.
Fig. 9. Effect of the DO sample size on simulated respirograms. Another consequence of the choice of DO sample size on the calculated respiration rate is the introduction of a time shift. Given that the respiration rate calculation is done at the end of the interval over which DO is sampled, and is stamped with the time at which the calculation is made, a time shift of half the total DO sampling interval is introduced. For example, a respiration rate calculated over a total sampling interval of one minute would be time-stamped 30 seconds later than it should. This time shift is obviously shorter as the respiration rate calculation frequency increases. The effect of the time shift is illustrated in Figure 10. In this figure, only one respiration rate is calculated for each DO depletion curve. Also apparent in the figure is the irregular frequency of the respiration rate calculation. The solid line is the instantaneous respiration rate calculated by the activated sludge model. 40
\,»1,
35
30 ':2
J
-a, 25
§. C1l
~ 20 c: 0
""
\,
l-
.[ 15
l-, -~
l!l
10 5 0
-_ .. 8min
._._-Time
Fig. 10. Effect of the DO sample size on calculated respiration rate: time shift.
Temperature effects Other simulations were conducted to investigate the effect of temperature on the BODs! calculated from the respirogram. The effect of temperature can be important because of the seasonal temperature variations in the caravan. A sludge sample that is to stay in the respirometers for some time may gradually warm up which may have a significant impact on the respiration rate.
E. Y. GIROUX et al.
308
In the simulation shown in Figure 11, the respirometer was in the respirogram mode, and two successive sewagl additions were done. Each sewage sample had the same characteristics except for the liquid temperature. The first sewage sample was at 20°C, while the second was at 15°C. The effect of temperature on the respiratior rate is obvious: at 15°C, the maximum respiration rate obtained was lower, and the time for the sample to read the endogenous respiration rate was longer. From the simulated respirograms, the effect of temperature on BODs! can also be assessed. Since both sewage samples were identical (BODs! 220 mg/l), the area under both respirogram should lead to the sam~ value. In thi~ example, the area under the first and second respirogram was 210.8 mg/l and 2~9.2. mg/l, re~pect1vely. The are, under the respirogram is sensitive to the time at which the endogenous respiratIOn rate IS detected, and the results suggest that detection of the endogenous respiration rate was properly done in this case. 40
- - - - - - - - - - --_. - - - - -.- -- - - - - . - - - "
40
35
35
30
30
. o
10
o
L.-1O m1n-l
..
L.-l0mln
time
Fig. 11 Effect of the temperature on respirograms.
SUMMARY AND CONCLUSIONS The purpose of this work was to develop a dynamic model capable of describing the operation of an on-site respirometer. The simulation environment used (GPS-X) proved to be suitable for the development of the model. The model was able to successfully reproduce the current operational state of the respirometer. The routine used to detect the endogenous respiration rate in the respirometer is currently causing problems and a more robust routine had to be developed in the model. The routine developed is currently applied tc instantaneous respiration rates calculated by the activated sludge model, and work is under way to apply it tc respiration rates calculated by the respirometer model. The dynamic model provided us with a bettel understanding of the behaviour of the instrument. Moreover, the model can easily be enhanced to include anc test new modes of operation before they are actually implemented in the respirometer. The effect of the DO sample size on the calculated respiration rate was found to be important, and care must bl taken to ensure that measurement errors are kept to a minimum to ensure reliable respiration rate measurements The calculation of multiple respiration rates along a single DO depletion curve provides more respiration ratl data and is a more accurate representation of reality in case of limiting DO and substrate, but also produces nois: respiration rates. This project is part of a more comprehensive study designed to maXlITuze the information content 0 respirograms and respirometric experiments. As part of this project dynamic model parameters estimation wi] be linked directly to respirometric data, allowing us to maintain model calibration and monitor changes i
Dynamic modelling of a respirometer
309
biochemical parameters. A number of technologies will be coupled together in order to maximize the information content resulting from the operation of a respirometer. Technologies that will be investigated include: neural networks, decision support systems, qualitative modelling and statistically based models.
ACKNOWLEDGEMENTS This work was funded in part by: the Ministry of Environment and Energy (Ontario) under the ETP program; the Wastewater Technology Centre (Burlington, Ontario); Hydromantis, Inc.; and the Natural Sciences and Engineering Research Council of Canada (Grant no. 0156887). REFERENCES APHA (1989). Standard Methods for the examination of Water and Wastewater, 17th edition, American Public Health Association, Washington, DC, USA. Henze, M., Grady, C.P.L. Jr., Gujer, W., Marais, G.v.R. and Matsuo, T. (1987). IAWPRC Task Group on Mathematical Modelling for Design and Operation of Biological Wastewater Treatment. Activated Sludge Model No.1, Scientific and Technical Reports No.1, IAWPRC, London, England. Hydromantis, Inc. (1995). GPS-X Technical Reference. Hydromantis, Inc., Hamilton, Ontario, Canada. IAWQ. Respirometry in Control ofActivated Sludge Processes. Scientific and Technical Report. To be published. Mitchell and Gauthier Associates (1995). Advanced Continuous Simulation Language (ACSL). Reference Manual. Mitchell and Gauthier Associates, Concord, Massachusetts. Spanjers, H., Olsson, G. and Klapwijk, A. (1994). Determining short-term biochemical oxygen demand and respiration rate in an aeration tank by using respirometry and estimation. Wat. Res., 28 (7), 1571-1583. Takacs, 1., Patry, G. G. and Nolasco, D. (1991). A dynamic model of the clarification-thickening process. Wat. Res., 25 (10),1263-1271. Vanrolleghem, P., Kong, Z., Rombouts, G. and Verstraete, W. (1994). An On-line Respirographic Biosensor for the Characterization of Load and Toxicity of Wastewaters. J. Chem. Tech/. Biotechnol., 59,321-333. Watts, J. B. and Garher, W. F. (1993). On-line Respirometry: A Powerful Tool for Activated Sludge Plant Operation and Design. Wat. Sci. Tech., 28(11-12), 389-399. Witteborg, A., van der Last, A., Hamming, R. and Hemmers, 1. (1996). Respirometry for determination of the influent Ss-concentration. Wat. Sci. Tech., 33(1), this issue.
JWST 33:1-L