Mathematical Modeling of Bioremediation of Soil Contaminated With Spent Motor Oil

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1 Journal of Emerging Trend in Engineering and Applied Science (JETEAS) 3 (4): Scholarlink Reearch Intitute Journal, 1 (ISSN: ) jetea.cholarlinkreearch.org Journal of Emerging Trend in Engineering and Applied Science (JETEAS) 3(4) (ISSN: ) Mathematical Modeling of Bioremediation of Soil Contaminated With Spent Motor Oil Abdulalam Surajudeen Chemical Engineering Programme, School of Engineering and Engineering Technology, Abubakar Tafawa Balewa Univerity, Bauchi PMB 48, Bauchi, Bauchi State-Nigeria. Abtract A tudy wa carried out on mathematical modeling of oil contaminated with pent motor oil. Thi reearch work i important for the prediction of bioremediation time of hydrocarbon contaminated oil. Mathematical model for a typical oil contaminated with pent motor oil wa derived from baic principle. The Oil and Greae (O&G) content and carbon dioxide ( ) releaed from bioremediation experiment were ued a indicator for monitoring bioremediation. The model developed wa baed on evolution and it wa evaluated uing kinetic data, and compared with experimental reult. Reult obtained from thi tudy revealed a goodne of fit between the experimental and predicted value. In addition, at 95% confidence level there wa no ignificant difference between the experimental and predicted cumulative generation uing the Chiquare (χ ) tatitical tool. It wa oberved that the profile obtained from the evaluated model concurred with the hifting order kinetic (1-). Therefore, the developed model can be ued for the prediction of bioremediation. Keyword: bioremediation; evolution; baic principle; experimental value; predicted value; ignificant difference. INTRODUCTION Bioremediation i a cleaning technology ued from time immemorial to detoxify or reduce pollutant level of harmful chemical uch a hydrocarbon, heavy metal, etc to acceptable level by the regulatory authoritie by the action of micro-organim. It ue a a treatment option wa unpopular until recently when attention ha hifted to the area of biotechnology. Economic advantage, environmental friendline and eae of application were in no doubt factor that make thi remediation technology popular in recent time. Bioremediation i not a pinnacle but meant to complement exiting remediation option uch a the thermal treatment, dig and dump method, chemical method, eparation technique and tabilization/olidification technology with can be broadly claified a the phyicochemical technologie. In addition, thee technologie have their limitation uch a high cot to implement at full cale, complexity in technology, detruction of oil texture and characteritic, and above all, mot of them are not environmentally friendly (Le and Senior, 1995; Vidali, 1). More o, the phyicochemical technologie do not alway reult in complete neutralization of pollutant (Yeruhalmi et al., 3). From the aforementioned, there i no doubt that bioremediation option i gaining more acceptability over other treatment option where ever it can be applied. Great deal of literature have reported that 654 bioremediation technologie are alternative and or upplement to the phyicochemical technologie, ome of thee literature include; Le and Senior (1995); Vidali (1); Yeruhalmi et al. (3). In addition, mot of the work carried out on bioremediation were baic proof of concept, practical oriented but not geared toward modeling and imulation or proce development. Some of the work done on modeling of bioremediation procee were mainly on in-itu procee (Yaghmaei, ). The dig and dump method currently ued in dipoing oil contaminated with pent motor oil polluted land i expenive and only tranfer the contamination from one place to another. Thi dipoal technique i very prominent in the developing countrie, where there were no trict enforcement on environmental regulatory policie. In no doubt, the dig and dump practice ha lead to the contamination of million of other ite remote from their place of initial contamination and therefore, urgent action need to be taken for environmental afety in general and of importance public health. In Nigeria, oil pill at auto-mechanic workhop have been left uncared for over the year and it continuou accumulation i of eriou environmental concern becaue of the hazard aociated with them. For intance, ued motor oil dipoed of improperly contain potentially toxic ubtance; uch a benzene

2 Journal of Emerging Trend in Engineering and Applied Science (JETEAS) 3(4) (ISSN: ) (carcinogen), lead, arenic, zinc and cadmium, which can eep into the water table and contaminate ground water (Http. ). In addition, one gallon of ued motor oil can contaminate one million gallon of freh water (Http.1; Http. ) and render four-acre of oil unuable for planting for decade (Http. ). In recent time, aerobic fixed bed bioreactor i the mot frequently ued olid-phae bioreactor for the treatment of ite polluted with minor oil pill. However, the variou type of aerobic fixed bed bioreactor currently in ue are lacking in afety factor uch a the containment of volatile organic compound (VOC). For intance, Croft et al. (1995) and Baptita et al. (5) carried out bioremediation experiment in aerobic fixed bed bioreactor but their experimental deign were lacking in the containment for volatile organic compound. Furthermore, in the lat few year a great deal of work ha been done on everal apect of bioremediation mainly becaue of it environmental friendline, cot effectivene and implicity in technology (Admon and Avnimelech, 1; Odukuma and Dickon, 3; Baptita et al., 5). However, mot of the work carried out were baic proof of concept, practical oriented and not geared toward modeling and imulation or proce development. Aim and objective of thi reearch work are to develop a afe, robut and economical treatment technology for the rehabilitation of oil contaminated with ued motor oil uing bioremediation technique and to develop a mathematical model for the prediction of bioremediation of oil contaminated with ued motor oil. The problem of oil contamination ariing from pill of ued motor oil need to be given priority attention becaue of the hazard aociated with them, hence the need to addre thi problem for human and environmental afety. In addition, a realitic model will enable u to predict the time required to detoxify a contaminated ite. MATERIALS AND METHODS Thee biodegradation invetigation were carried out in ix aerobic fixed bed bioreactor (TR1 to TR6), a preented in Fig. 1. Each bioreactor contained 1.5 kg of contaminated oil; thi included, where appropriate, the variou additive at room temperature. The bioreactor were completely cloed in order to avoid leakage to the environment before paing into the trap. The moiture content in all the ix treatment wa et at % of the total weight of the oil at the initiation of bioremediation. The airflow rate wa maintained in all cae at an average rate of 1 L/h uing a flow meter for fourteen (14) hour daily for the period of invetigation. At the beginning of thi invetigation the contaminated oil wa teted in order to provide the baeline data for the tudy. The phyicochemical and microbiological integritie of the oil were teted uing tandard method well detailed in Abdulalam (11a). In addition, the following phyicochemical and microbiological tet were alo carried out on all the treatment on weekly bai: oil and greae content (O&G), moiture content, ph, temperature. More o, carbon dioxide ( ) repiration rate wa monitored every 48 h throughout the duration of the experimental work. Method of analye are alo detailed in Abdulalam (11a). RESULTS AND DISCUSSION Oil and Greae Biodegradation The level of reduction in the oil and greae content at different period during the coure of thi tudy were hown in Fig.. From thi figure, the percentage O&G content removal increaed with time, which i typical of any degradation proce. The proce wa characterized by a period of fat decreae in hydrocarbon concentration during the firt five week (4, 45, 51, 4, 59 and 63% for TR1, TR, TR3, TR4, TR5 and TR6 repectively), followed by a period of lower activity (pat Week 5). The degradation pattern followed hifting order (1-) degradation (Okpokwaili and Nweke, 5). At the initiation of bioremediation (at time zero), the concentration of O&G content in bioreactor TR1, TR, TR3, TR4, TR5, and TR6 were 9 1, , , , 3 7 and mg/kg dry weight repectively. After 7 day, their concentration reduced to , 14 88, 1 85, , and 9 83 mg/kg dry weight, which tranlate to 5, 63, 66, 57, 68 and 75% loe in O&G content Of the ix treatment employed in thi tudy, TR6 in which the indigenou microorganim were timulated with NPK (: 1: 1) and KH PO 4 reulted in the maximum bioremediation repone of 75% reduction in the initial O&G content. Thi obervation i in line with the literature that biotimulation trive well in aged contaminated ite (Koteck and Calabree, 1991). 655

3 Journal of Emerging Trend in Engineering and Applied Science (JETEAS) 3(4) (ISSN: ) Oil and Greae Content (mg/kg dry oil) week week 1 week week 3 week4 week 5 week 6 week 7 week 8 week 9 week Treatment Option Fig. : Variation in the oil and greae content with time for variou treatment option (Source: Experimental Reult) Generation in Bioreactor evolution wa alo ued a indicator of bacteria repiration (a product of bioremediation proce). The evolution wa monitored on 48-hourly bai and thi enable u to compute the cumulative generation preented in Fig. 3. From thi figure, all the treatment (TR1 to TR6) appear to how a trend of adaptation period (1 to 1 day), maximum oil degrading period (5 to 55 day) and a decaying rate of oil degradation period (pat 6 day). The cumulative generation in each bioreactor increaed with pollutant or oil degradation. The cumulative generation for TR1, TR, TR3, TR4, TR5 and TR6 were 4 76, 5 6, 5 493, 5 79, and 6 49 mg/kg repectively for thi tudy. Treatment option 6 (TR6), gave the bet generation, which correpond to the bet O&G content (75%) removal. The control (TR1), howed the leat generation, which alo correpond to the leat O&G removal of 5%. Fig. 3: Cumulative rate of generation of in for variou treatment option (Source: Experimental Reult) Selection of a Treatment Technology Baed on the reult obtained for the O&G content and generation, treatment option 6 (TR6), the ample timulated with NPK (:1:1) and KH PO 4 gave the bet reult. Therefore, TR6 could be ued to develop a afe, robut and economical full-cale treatment technology for oil contaminated with ued motor oil. Since treatment option ix (TR6) gave the bet reult in thi tudy, the parameter obtained from it wa employed in analyzing mathematical model developed. MATHEMATICAL MODEL FOR PREDICTION OF BIOREMEDIATION Model Formulation In thi tudy, mathematical model for the prediction of the cumulative rate of carbon dioxide ( ) generation for the treatment technology (TR6) wa developed from baic principle. The model formulation i a follow: Figure 4: Schematic Diagram of an Aerobic Fixed Bed Bioreactor Conidering the chematic diagram of an aerobic fixed bed bioreactor a indicated in Fig. 4. Material balance around the bioreactor ytem i expre a: Rateof flowof Rateof formation Rateof flowof Rateof accumulation materialint o bybiochemical materialoutof of materialwithinthe thebioreactor reaction bioreactor bioreactor Taking balance around the bioreactor; Since i not upplied into the bioreactor, the firt term of Equation (1) equal to zero. Therefore, we have: Rate of formation Rate of of by biochemica l out of reaction in bioreactor bioreactor flow of Rate of accumulati on of within the bioreactor Mathematically, equation () can be expre a: d x. V F. V. (3) dt Where: (αµ+β) i the pecific rate of product ( ) formation (Leudeking and Piret, 1959) α i growth-related product formation coefficient and β i non-growth related product formation coefficient. Both α and β are dependent on the treatment option employed or bioremediation approach ued. (1) () 656

4 Journal of Emerging Trend in Engineering and Applied Science (JETEAS) 3(4) (ISSN: ) µ i the pecific growth rate of microorganim x i the cell concentration V i the active or effective volume of bioreactor F i the volumetric feed flow rate Dividing equation (3) by V and auming that the rate of generation of in the bioreactor i equal to the rate of leaving the ytem. Therefore, equation (3) reduce to: x D. (4) where: D i the dilution factor However, we know that: dx x dt (5) In addition, µ could be repreented by the popular microbial growth equation (i.e. the Monod equation), given by: max. (6) k where: µ max i the maximum pecific growth rate k i the ubtrate aturation contant or Monod contant Subtituting equation (5) and (6) in (4), we have: dx (7). D. max. dt k Neverthele, the ubtrate concentration () i a function of cell ma (x) and the relationhip between them i given by equation (8): dx d (8a) dt dt or x x (8b) Subtituting equation (8b) in (7) and rearranging give: Y. k Y x x x x dx. D. (9) dt max xx Further rearranging equation (9) and integrating give: x Y x x x x x In x x D. t k. (1) max x Evaluating give: 1. xx x x ln (11) Dt. max max. 657 Equation (11) i the model equation for the prediction of cumulative rate of carbon dioxide ( ) generation in an aerobic fixed bed bioreactor. In term of ubtrate concentration, equation (11) become: 1 Y ( ) ln (1) x Dt. max max Model Validation The mathematical model developed (Eqn. 1) wa teted for the prediction of generation. Reult obtained indicate a good fit between the experimental and predicted value (Fig. 5). In addition, a goodneof-fit tet wa carried out between the experimental and predicted cumulative generated uing the Chiquare (χ ) tatitical tool. Reult obtained alo, indicate that there wa no ignificant difference between the experimental and predicted value at 95% confidence level. Therefore, the developed model can be ued for the prediction of bioremediation. The model parameter α and β (Table 1) were obtained by iterative method uing Microoft Excel. C u m u l a ti v e C O G e n e ra te d (m m o l / k g ) Experimental Predicted Time (week) Fig. 5: Cumulative generated by the treatment technology Table 1: Summary of Model Parameter for TR6 Parameter Value α.675z Z+.35 for Z=-6, R = Ln (Z)-18.1 for Z=6-1, R =.9998 β 1.115*1-15 Z: time interval It hould be noted that α i dependent on the time interval (Z) from the tarting point ince it i a growth dependent coefficient (the firt time interval take the value of 1; the econd, ; the third, 3 and o on) and in addition, the value of α and β depend on the treatment option employed.

5 Journal of Emerging Trend in Engineering and Applied Science (JETEAS) 3(4) (ISSN: ) Phyical Significance of Model Parameter (α and β) The growth dependent contant, α increaed with increaing cumulative generation. At high ubtrate concentration, α i directly proportional to the cumulative generation and can be repreented by a firt order reaction, neglecting the lag phae (i.e. between Week and 6). At low ubtrate concentration (pat Week 6), α i characterized by low increaed in cumulative generation and hence, the profile approached a plateau, which i bet decribed by zero order phenomena (Fig. 3). From thee obervation, it can be concluded that the predicted model followed a imilar pattern a the kinetic profile (Abdulalam, 11b). Limitation of Mathematical Model Haven identified how repreentative the developed model wa in predicting bioremediation; the following limitation were alo identified; 1) The model cannot predict accurately the experimental data at the tart of bioremediation (i.e. between week and ). ) The model parameter, α (i.e. the variable parameter) wa repreented by two equation (i.e. at low and high value of ). NCLUSIONS AND REMMENDATIONS Concluion From the reult obtained in thi tudy, the following can be concluded; 1) The hydrocarbon removal efficiency can reach 75% in an aerobic fixed bed bioreactor within the experimental data ued over a period of eventy day. ) The bio-timulation option can gave the bet hydrocarbon removal efficiency in thi tudy (75% removal of the initial oil and greae content in 7 day) and hence can be employed to develop a realitic pilot plant for the treatment of oil contaminated with pent motor oil. 3) The mathematical model developed wa effective in the prediction of bioremediation. REMMENDATION I wih to recommend that the reult of thi invetigation hould be ued to ize a pilot plant for the treatment of hydrocarbon contaminated oil and alo the model developed hould be employed for the prediction of bioremediation. ACKNOWLEDGEMENT I wih to acknowledge the financial upport of the Academic Staff Union of Nigerian Univeritie (ASUU) and Abubakar Tafawa Balewa Univerity (ATBU), Bauchi without which thi tudy would not have come to reality. REFERENCES Abdulalam, S. (11a), Bioremediation of Soil Contaminated with Ued Motor Oil: concept, proce development and mathematical modeling, Lambert Academic Publihing, Germany. ISBN: Abdulalam, S. (11b), Kinetic tudie of carbon dioxide ( ) repiration rate in bioremediation of oil contaminated with pent motor oil, Bioremediation Journal, 15(4): Admon, S., Green, M. and Avnimelech, Y. (1). Biodegradation kinetic of hydrocarbon in oil during land treatment of oily ludge, Bioremediation Journal, 5(3): Baptita, J. S., Cammarota, C. M., and Carvalhofreire, D. D. (5). Production of in crude oil bioremediation in clay oil, Brazilian Archive of Biology and Technology, Vol. 48, no. pe Croft, C.B., Swannell, J.P.S., Grant, L.A. and Lee, K. (1995). The effect of bioremediation agent on biodegradation in medium-fine and, Applied Bioremediation of Petroleum Hydrocarbon, Battelle Pre. Acceed on December 8, 5 Ued motor oil. Acceed on December 8, 5 Koteck, P.T. and Calabree, E.J. (1991). Bioremediation of Hydrocarbon Contaminated Soil: The Microbial Ecology Approach. In Hydrocarbon contaminated oil and Groundwater, Lewi Publiher, Inc. United State, Vol. 1, pp Le, Z.M. and Senior, E. (1995). Bioremediation. A Practical Solution to Land Pollution: In Clean Technology and the Environment, Chapman and Hall, New York pp Leudeking, R. and Piret, E. L. (1959). A kinetic tudy of the lactic acid fermentation, J. Biochem. Microbiol, Technol. Eng., 1:393 Odukuma, L. O. and Dickon, A. A. (3). Bioremediation of a crude oil polluted tropical rain foret oil, Global Journal of Environmental Science, Vol. 1, 9-4, Available online at home.att.net/~africantech/ GJES/ bioremediation/oil oil 1.htm Acceed on January 31, 6 658

6 Journal of Emerging Trend in Engineering and Applied Science (JETEAS) 3(4) (ISSN: ) Okpokwaili, G. C. and Nweke, C. O. (5). Microbial growth and ubtrate utilization kinetic, African Journal of Biotechnology, Vol. 5 (4), pp Available online at Vidali, M. (1). Bioremediation: An overview, Journal of Applied Chemitry, Vol. 73, No. 7, pp Yaghmaei, S. (), Mathematical Modeling of Natural In-Situ Bioremediation to Etimate Initial Contaminant Concentration Effect, International Journal of Engineering, Vol. 15, No. : Yeruhalmi, L., Rocheleau, S., Cimpoia, R., Sarrazin, M., Sunahara, G., Peiajovich, A., Leclair, G. and Guiot, R.S. (3). Enhanced bioremediation of petroleum hydrocarbon in contaminated oil, Bioremediation Journal, 7(1): Figure 1: Proce flow diagram of an experimental rig for bioremediation tudie (Source: Abdulalam, 11a) 659