Environ. Sci. Technol. 1999, 33, 1458-1463
Adapting the Self-Cycling Fermentor to Anoxic Conditions WAYNE A. BROWN,† D A V I D G . C O O P E R , * ,‡ A N D STEVEN N. LISS§ Department of Chemical Engineering, McGill University, 3610 University Street, Montreal, Quebec, Canada H3A 2B2, Syncrude Canada Ltd., Edmonton Research Centre, 9421-17 Avenue, Edmonton, Alberta T6N 1H4, Department of Applied Chemical and Biological Sciences, Ryerson Polytechnic University, 350 Victoria Street, Toronto, Ontario, Canada M5B 2K3
The self-cycling fermentation (SCF) technique for cell cultivation is a useful tool for studying microorganisms. To date, this method has only been applied to aerobic systems, since dissolved oxygen has been used exclusively as the feedback control parameter, which defines this technique. To extend the range of redox environments to which the SCF can be applied, an alternate measurement is required. Transient oxidation reduction potential (ORP) and carbon dioxide evolution were screened as potential feedback control parameters in a denitrifying system. The characteristic change in slope of the transient ORP profile commonly referred to as the “nitrate break point” was found to be a useful indicator of complete removal of oxidized nitrogen only in the presence of significant quantities of nitrate. An inflection point occurring after the break point was found to be a more general indicator of oxidized nitrogen removal. A control strategy based upon real-time detection of the inflection point was found to result in robust operation of the SCF. When variable amounts of nitrate (0-930 mg L-1) and nitrite (0-300 mg L-1) were added to the reactor each cycle, the control strategy automatically adjusted the cycle time, resulting in an effluent containing less than 1 mg L-1 of each of the oxidized nitrogen species.
Introduction In recent years, unsteady state biological systems, such as the sequencing batch reactor (SBR), have been applied more regularly to wastewater treatment problems (1, 2). The variable nature of these systems allows manipulation of the selective pressures on the active members of the microbial community so that the activity of the community can be dynamically adjusted to meet changing influent conditions. The SBR is periodic in nature, with each cycle composed of a sequence of steps. Determining the optimal duration of each stage is a difficult task. Historically, each step was of fixed duration, based on operating experience. This approach is of limited use, since it represents the optimum conditions for a specific influent composition. To improve the response of SBRs to changing influent conditions, efforts have been made to automate the transi* Corresponding author. Phone: (514) 398-4278; Fax: (514) 3986678; E-mail:
[email protected]. † Syncrude Canada Ltd. ‡ McGill University. § Ryerson Polytechnic University. 1458
9
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 33, NO. 9, 1999
tions between the various phases (2, 3). Much of this work has focused on the problem of nitrogen removal, in which both aerobic and anoxic redox environments are required in order to remove the reduced and oxidized nitrogen species. During the anoxic process, the oxidation/reduction potential (ORP) has been observed to undergo a change in rate upon complete removal of the oxidized nitrogen species. This point has been named the “nitrate breakpoint” or “nitrate knee”, due to its characteristic shape (4). Control of the anoxic process has been addressed on a small scale, through online determination of the breakpoint (5). The success of this approach was based on the ability of the computer algorithm to detect the breakpoint. The self-cycling fermentation (SCF) technique is also cyclical in its operation (6, 7). The defining feature of this technology is that the length of each cycle is determined automatically by the growing culture. In the SCF method, a computer assesses the metabolic state of an active aerobic culture through evaluation of the dissolved oxygen concentration. Once a minimum is detected, half of the reactor contents is removed, and an equal aliquot of fresh medium is added. The SCF system has several unique advantages over competing technologies commonly used in the study of microorganisms. Most importantly, the SCF method guarantees the complete removal of the limiting nutrient, even under varying feed conditions (6-9). Second, the cycling action of the reactor has been shown to have a synchronizing effect on the cells (6, 9, 10). Therefore, macroscopic measurements performed on the bulk culture are representative of microscopic events. Since exactly half of the cell matter is removed at the end of each cycle, the biomass only doubles once, after the system stabilizes. Thus, the cycle time equates to the doubling time of the organism (7-9). Lag times are eliminated, since a significant portion of the acclimated cells is left in the reactor at the end of each cycle. Hence, neglecting the brief period at the end of the cycle, when the limiting nutrient concentration approaches zero, the organism always grows at the maximum specific growth rate. Last, the data gathered from a series of cycles are extremely reproducible (6-10). Although the SCF technology is an obvious system with which to develop control strategies for the SBR, to date, the self-cycling fermentor has only been implemented under aerobic conditions. For the most part, this is due to the lack of adequate on-line instrumentation, which can provide the control signal necessary for operation of the SCF. The primary objective of the current work was to adapt the SCF technology to an anoxic environment. A denitrifying system was chosen for this purpose. The second goal was to develop a control strategy, which would guarantee the complete removal of oxidized nitrogen. This paper reports on a control strategy that is general enough to be applied to any denitrification system. The preferred algorithm potentially maximizes throughput while ensuring complete removal of the oxidized nitrogen species.
Materials and Methods Organism and Culture Conditions. The organism used in all experiments was Pseudomonas denitrificans ATCC 13867. The medium used was a modified version of that previously described (11). The base mixture consisted of 1.5 g of KH2PO4, 5 g of K2HPO4, 5 g of NaCl, 0.06 g of CaCl2, 0.2 MgSO4‚ H2O, 2.207 g of glutamic acid, and 0.05-0.1 mL of a trace elements solution dissolved in 1 L of distilled water. Ammonium chloride was included at a concentration of 1 g L-1, 10.1021/es980856s CCC: $18.00
1999 American Chemical Society Published on Web 03/19/1999
FIGURE 1. Experimental apparatus. where indicated. Nitrate was added as the potassium salt, and nitrite as the sodium salt, in the concentration indicated in the text. The pH was adjusted to 6.8 using NaOH. The trace elements solution consisted of 0.5 g of Na2MoO4‚2H2O, 0.5 g of MnSO4, 0.5 g of CuSO4, and 0.5 g of FeCl3 dissolved in 100 mL of distilled water. All experiments were performed at 30 °C. SCF Reactor. Experiments were carried out in a stainless steel stirred tank reactor (Figure 1). The capacity of the reactor was 4 L, but a working volume of 2 L was used for all experimental work. Dissolved oxygen (Ingold DL-531 electrode), ORP (Mettler Toledo Type 465 electrode), and carbon dioxide evolution (Oxymax, Columbus Instruments) were the measured variables. All ORP values are quoted with
respect to the Ag/AgCl redox couple. Anoxic conditions were maintained in the reactor through continuous sparging with helium. Liquid transfer to and from the reactor was accomplished by means of a series of solenoid valves. The output from a differential pressure transducer (Omega PX-170) was used to estimate the amount of liquid in the reactor at any time. All equipment and media were steam sterilized at 121 °C. The only exceptions were the ORP electrode, and the pressure transmitter. These units were sterilized with 70% ethanol for at least 1 h. Before sterilization, and following an experiment, the ORP electrode was calibrated using pH standards. The signal used for control purposes was the raw output from the ORP electrode. As such, both the control signal and adjusted ORP values are presented and clearly distinguished throughout the text. The software that governed the entire process was written in Turbo Pascal, and run on an IBM XT computer. All inputs were read into the computer by means of a data acquisition board (Data Translation DT-2801). Biomass Determination. The dry weight of biomass was determined from samples of the harvested fraction collected from the reactor at the end of each cycle. A 25 mL sample of broth was centrifuged at 11000g at 4 °C for 30 min. The pellet was resuspended in approximately 25 mL of distilled water, and centrifuged for another 30 min. The washed biomass was then dried at 105 °C to constant weight. All analyses were done in duplicate. Percent differences between replicates on the order of 1% were typical. For samples withdrawn at intermediate points throughout a cycle, the optical density (OD540) was measured at 540 nm, as previously described (12). Nitrate and Nitrite Analysis. The concentrations of nitrate and nitrite anions were measured using capillary electrophoresis (Dionnex System 1). The procedure followed was based upon that described by Dunn et al. (13). Samples were processed using a buffered phosphate solution of approximately neutral pH. Typically, a 1 mL sample volume of reactor broth was centrifuged at 10000g for 5-10 min. A fraction of the supernatant was then diluted with distilled
FIGURE 2. Automated denitrification system. Feed contained 933 mg L-1 nitrate, and 1 g L-1 NH4Cl, in addition to the base medium. The derivative (b) was estimated as per the text. Dissolved oxygen was not detected throughout the experiment. Arrows indicate periods during which fluid was exchanged with the reactor. The ORP signal was not recorded during this time. VOL. 33, NO. 9, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
1459
FIGURE 3. Transient concentration profiles throughout a cycle in the anoxic SCF. Data were acquired during cycle 9 of the experiment described in Figure 2. The vertical arrow points to the onset of the nitrate breakpoint. Symbols represent ORP (s), derivative (b), biomass (O), nitrate (2), and nitrite (0). water, and mixed with an internal standard solution of MoO42-. Detection was achieved by UV at a wavelength of 214 nm. Ammonium Analysis. Ammonium was analyzed by capillary electrophoresis, based on the method outlined by Morin et al. (14). Separation was attained using a benzylamine buffer (pH 9.4). Negative peak detection was achieved by UV at 204 nm. Samples were pretreated by centrifugation at 10000g for 5-10 min. A volume of supernatant was then diluted with water. The lithium ion, added as LiNO3, served as the internal standard.
Results and Discussion The SCF requires a signal upon which to base its feedback control strategy. For aerobic processes, dissolved oxygen has filled this role (6-8, 10). However, under anoxic conditions, dissolved oxygen is of little value as a control parameter. A maximum in carbon dioxide evolution rate (CER) has been linked to the disappearance of the limiting nutrient in an aerobic SCF (15) and also in other non-steady-state systems (16, 17). The rate of change of the oxidation reduction potential (ORP) signal during denitrification has been shown 1460
9
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 33, NO. 9, 1999
to increase upon the complete disappearance of the nitrate species (4). Therefore, both CER and ORP were screened as potential control parameters for the anoxic SCF. A comparison of the transient ORP and CER profiles during denitrification showed that both signals responded similarly. Since ORP was easier to implement, it was chosen as the control parameter. The initial strategy implemented to control the SCF was based upon detecting the nitrate breakpoint. Control strategies centered on this phenomenon have been applied to the problem of denitrification in a sequencing batch reactor (SBR) with considerable success (5). The most successful algorithms applied to date involved estimating the rate of change of the transient ORP profile with time. Most recently, the algorithm of Yu et al. (18) and the “linear ring-buffer” approach applied by Wareham et al. (3) made use of the fact that the first derivative decreases dramatically once the nitrate breakpoint has been achieved. In the current work, the first derivative of the ORP signal was approximated as the slope of ORP readings collected over a 15-20 min interval. The initial estimate was referred to as the “base” derivative. A rolling average was then updated every 30 s and was compared to
FIGURE 4. Ability of a control scheme based on detection of ORP inflection point to react to changing feed conditions. ORP, filtered using a digital Butterworth filter, provided the control signal. Symbols represent nitrate (2) and nitrite (9) in feed, nitrate (4) and nitrate (0) in the harvested fraction, biomass (b), and cycle time (O). the base derivative. Once the slope had decreased by a fixed tolerance, determined experimentally to be 1-3 µV s-1, the breakpoint was assumed to have been reached. Using this control scheme, the ORP profiles were found to be repeatable from cycle to cycle (Figure 2), as were the carbon dioxide evolution rates (data not shown). Concentrations of nitrate in the treated effluent were far below the toxic limit of 45 mg L-1, generally accepted in North America as being harmful (19, 20). Due to the operating characteristics of the SCF, the biomass was expected to exactly double throughout the course of a cycle. This has been verified for the operation of the SCF under aerobic conditions, under static feed conditions. Figure 3 suggests that this is also the case for the anoxic SCF, with control based on detecting the “nitrate knee”. Although the control strategy performed well over the majority of cycles, problems were encountered. The most significant obstacle was associated with the cycling criterion. This value was typically based on data collected over the first cycle. However, the transient ORP profiles tended to evolve throughout an experiment. Therefore, it was difficult to choose a single value for the cycling criterion that would be generally applicable to all cycles. If the value chosen was too small, signal noise and local changes in the ORP profile made premature liquid discharge a possibility. The implications associated with choosing too large a tolerance were more
complicated. As the nitrate breakpoint was approached, the rate of change of the ORP profile began to decrease at a faster rate. This acceleration continued for some time after passing through the breakpoint. Eventually, the transient ORP signal exhibited an inflection point, and the derivative reached a minimum. The derivative then climbed quickly and asymptotically approached zero. As a result of this behavior, if the tolerance were fixed at too large of a value, a cycle of infinite duration would result. This situation arose on two occasions, making manual intervention necessary. The apparent need for an evolving cycling criterion was initially addressed by updating the value throughout the experiment. Not only was this approach undesirable, but it also failed to completely prevent operational upsets. On two occasions, the cycling criterion was set at a value that did not capture the breakpoint. Similar problems have been noted when algorithms based on defining features of the transient ORP profile have been applied to the denitrification problem (5, 21). The common solution adopted has been to incorporate a secondary control strategy, which ensured that the drain sequence was activated under circumstances in which the primary control scheme failed. Often, a cycle was restricted to a certain maximum period of time. Once the predefined interval had expired, the next step of the sequence was activated. The drawback with this approach was that it was based on absolute factors, VOL. 33, NO. 9, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
1461
FIGURE 5. Degradation profile of nitrite (0) during cycle 23 of the experiment described in Figure 4. Nitrate (4), ORP (s), and the derivative (b) are also shown. which had little basis, other than experience. Therefore, premature discharge of the reactor contents was still a possibility. Furthermore, reactor throughput was compromised. The problem was addressed in the current work through development of an alternate primary control scheme. The ORP passed through an inflection point shortly after the breakpoint was achieved. As a consequence, the first derivative passed through a minimum. An algorithm was written which searched for the inflection point in the ORP profile by looking for a minimum in the first derivative of the ORP signal. As with the previous strategy, a fixed cycling criterion was chosen, based on the results obtained from an anoxic cycle performed with an open feedback control loop. The modified strategy had several distinct advantages over its predecessor. Most importantly, since the algorithm searched for an absolute minimum in the first derivative of the ORP profile, the impact of evolving ORP profiles was mitigated. Furthermore, the possibility of choosing a tolerance that was too large, leading to an infinite cycle time, was significantly reduced. Finally, a secondary control strategy was not necessary. To test the modified control strategy, the reactor was subjected to a feed containing a variable amount of nitrate. This was accomplished by filling two medium bottles with 1462
9
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 33, NO. 9, 1999
media differing only in nitrate content. The control program was modified to fill the reactor with a mixture of media from both bottles, based on a random number generated by the computer. The only constraint was that the total volume added to the reactor had to be 1 L, so that a fill fraction of 50% could be maintained. Imposing this methodology, the feed concentration to the reactor was varied between 614 and 933 mg L-1 nitrate for five cycles. The remaining cycles were performed at a constant feed concentration of 933 mg L-1 nitrate. The control algorithm was able to cope with this feed profile, as indicated by the residual concentrations of nitrate and nitrite remaining in the effluent discharged from the reactor, which were less than 2.5 mg L-1 in most cases (data not shown). A complication with the new control strategy was the presence of noise in the ORP signal. Signal noise in the control parameter was amplified through application of the derivative algorithm. This led to the creation of relative minima, which caused problems for the search algorithm, and lead in some cases to the premature initiation of the drain cycle. This problem was addressed through the application of a recursive digital filtering algorithm. Using this filter, much of the signal noise was eliminated. Unfortunately, the nitrate breakpoint was also smoothed to some extent. However, the
For those cycles that contained significant nitrate, a breakpoint was apparent (Figure 6). This characteristic change in slope occurred 30-45 min prior to activation of the fill/drain sequence by the control algorithm. Therefore, in cases where nitrate is present, the control scheme based on the inflection point introduces a significant lag. Although this represented as much as a 25-50% increase in the length of a cycle, it also guaranteed complete nitrate removal. On the basis of this work, it appears as if the inflection point is a more general characteristic than the breakpoint in denitrifying systems. In all of the ORP profiles generated, the inflection point was observed. In contrast, the breakpoint was exclusive to those cycles that involved high levels of nitrate. Therefore, where control strategies based upon detection of either the breakpoint or inflection point are equally applicable for the biological removal of nitrate, it appears as if inflection control is uniquely able to handle a charge containing a high ratio of nitrite to nitrate.
Acknowledgments The authors would like to thank the Natural Sciences and Engineering Council of Canada (NSERC) for supporting this work. FIGURE 6. Transient profiles of nitrate (4) and nitrite (0) within cycle 4 of experiment described in Figure 4. The arrow indicates the nitrate breakpoint. Nitrate (4), ORP (s), and the derivative (b) are also shown. inflection point was maintained, which was the focal point of the modified control strategy. As a final test of the revised control scheme, the reactor was subjected to a mixed feed of nitrate and nitrite. Random amounts of nitrate (0-930 mg L-1) and nitrite (0-300 mg L-1) were added to the reactor each cycle, as described above (Figure 4). After 15 cycles, the reactor was fed with medium containing 300 mg L-1 nitrite and no nitrate, to test the general applicability of the algorithm. As with previous experiments, oxygen was provided as the terminal electron acceptor for the first cycle, to generate biomass. Therefore, a significant amount of the oxidized nitrogen remained at the end of the cycle, as the oxygen tension was too high for denitrification to occur at any appreciable rate. Anoxic conditions were established for the remaining cycles. For all anoxic cycles, nitrite or nitrate was depleted to less than 1 mg L-1 in the effluent at the end of each cycle (Figure 4). As the feed composition to the reactor was changing from cycle to cycle, the biomass profile was predictably unstable. However, once nitrate was eliminated from the feed, and the concentration of nitrite in the feed was fixed at 300 mg L-1, the biomass value quickly approached a steady state. In addition, the transient ORP profiles became more reproducible, as did the cycle times (Figure 4). The advantage of the control scheme based upon detection of the inflection point was readily apparent by examining the results associated with feed containing nitrite only. These data show no evidence of a breakpoint in the ORP profile (Figures 4 and 5). Following the profile of nitrite as it is removed throughout cycle 23, it was apparent that the inflection point in the corresponding ORP profile corresponded to the complete removal of the nitrite species. This characteristic of the ORP profile was also demonstrated for experiments in which both nitrate and nitrite were added as electron acceptors. For cycles in which the initial nitrate concentration was low, the resulting ORP profile did not demonstrate a noticeable breakpoint. However, the transient did pass through an inflection point, allowing for adequate control.
Literature Cited (1) Irvine, R. L.; Wilderer, P. A.; Flemming H.-C. Water Sci. Technol. 1997, 35 (1), 1-10. (2) Chang, C. H.; Hao, O. J.; J. Chem. Technol. Biotech. 1996, 67, 27-38. (3) Wareham, D. G.; Mavinic, D. S.; Hall, K. J. Water Res. 1994, 28 (2), 373-384. (4) Koch, F. A.; Oldham, W. K. Water Sci. Technol. 1985, 17, 259281. (5) Wareham, D. G.; Hall, K. J.; Mavinic, D. S. J. Environ. Eng. 1993. 119, 120-136. (6) McCaffrey, W. C.; Cooper, D. G. J. Ferm. Bioeng. 1996, 79, 146151. (7) Sheppard, J. D.; Cooper, D. G. Biotech. Bioeng. 1990, 36, 539545. (8) Hughes, M.; Cooper, D. G. Biotech. Bioeng. 1996, 51, 112-119. (9) Brown, W. A.; Cooper, D. G. Appl. Environ. Microbiol. 1991, 57, 2901-2906. (10) Sarkis, B. E.; Cooper, D. G. Can. J. Chem. Eng. 1994, 72, 874880. (11) Wang, J.-H.; Baltzis, B. C. Biotech. Bioeng. 1995, 46, 159-171. (12) Brown, W. A.; Pinchuk, R.; Cooper, D. G. Biotech. Techniques 1997, 11, 213-216. (13) Dunn, C. D.; Hankins, M. G.; Ghowsi, K. Sep. Sci. Technol. 1994, 29 (18), 2419-2433. (14) Norin, P. H.; Francois, C.; Dreux, M. J. Liq. Chromatogr. 1994, 17, 3869-3888. (15) Van Walsum, G. P.; Cooper, D. G. Biotech. Bioeng. 1993, 42, 1175-1180. (16) Buitro´n, G.; Capdeville, B.; Horny, P. Water Sci. Technol. 1994, 29, 317-326. (17) Schro¨der, M.; Mu ¨ ller, C.; Posten, C.; Dexkwer, W.-D., Hecht, V. Biotech. Bioeng. 1997, 54, 567-576. (18) Yu, R.-F.; Liaw, S.-L.; Chang, C.-N.; Lu, H.-J.; Cheng, W.-Y. Water Sci. Technol. 1997, 35 (1), 57-66. (19) Guidelines for Canadian Drinking Water Quality; FederalProvincial Subcommittee on Drinking Water of the FederalProvincial Committee on Environmental and Occupational Health; Canada Communication Group-Publishing: Ottawa, Canada, 1996; pp 58-59. (20) Golden, J.; Oullette, R. P.; Saari, S.; Cheremisinoff, P. N. Environmental Impact Data Book; Ann Arbor Science Publishers: Ann Arbor, MI, 1979; pp 445-446. (21) Wareham, D. G.; Hall, K. J.; Mavinic, D. S. Water Sci. Technol. 1993, 28 (11-12), 273-282.
Received for review August 19, 1998. Revised manuscript received February 15, 1999. Accepted February 15, 1999. ES980856S VOL. 33, NO. 9, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
1463
