vailable online at www.pelagiaresearclibrary.com European Journal of Experimental Biology, 2013, 3(2):430-436 ISSN: 2248 9215 CODEN (US): EJEBU BOD 5 removal kinetics and wastewater flow pattern of stabilization pond system in Birjand Rasoul Kusravi 1, Maryam Kodadadi 1, bdolmajid Golizade 2, Esan bouee Merizi 2*, Taer Sariary 1 and bdoljavad Sania 3 1 Faculty of Healt Scool, Birjand University of Medical Sciences, Birjand, Iran 2 Faculty of Healt Scool, Nort Korasan University of Medical Sciences, Bojnurd, Iran 3 Water and Wastewater Healt, Water and Wastewater Company of Sout Korasan, Iran BSTRCT Wastewater stabilization ponds (WPs) are one of te simplest tecniques available for te treatment of municipal wastewater wic eventually benefit from te simplicity and reliability of teir operation. ltoug many WPs ave been establised and made operational, but still te dynamics of pollutants in tese systems are not well understood and tis can lead to improper design and poor removal efficiency of pollutants and also operational problems. Since in te most used wastewater treatment stabilization ponds, te removal of organic matter (BOD 5 ) is te primary goal of design systems, so preliminary determination of BOD 5 removal kinetics and wastewater flow pattern is often required. In tis study, to analysis of kinetic data, four kinetic models tat can be used in te WPs ave been compared. Te studied models combine te different kinetics of Monod and First order kinetic models wit continuous stirred-tank reactor (CSTR) and plug flow regimes. Finally, te models were analyzed using statistical parameters. Te combined model of te Monod s kinetic equation and plug flow pattern presented nearest matematical relationsip between teoretical and actual data of WPs. In te tree ybrid models except te Monod and plug flow, BOD 5 removal coefficients decreased wit increasing BOD 5 loading. bout te prediction of organic materials removal in WPs, a significant relationsip between te ratio of BOD / COD and removal coefficients was not found, suggesting tat te decomposition of organic matter in te stabilization ponds are not susceptible rater tan organic waste nature. Keywords: wastewater stabilization ponds, wastewater treatment, modeling, Birjand. INTRODUCTION Te main objectives of wastewater treatment is often producing an effluent suitable for discarging into receiving environments someow complies wit effluent standards and ave no damages for te environment[1]. Terefore, te wastewater treatment not only would cause environment protection and public ealt improvement, but also return water to te consumption cycle directly or indirectly. Due to te water crisis in te last century, te importance of tis issue as been even more apparent. Terefore, several treatment systems weter biological or cemical and or mixed one may be employed. Natural treatment mecanisms are considered as one of te most popular systems [1, 2]. 430
Waste stabilization ponds (WSPs) as natural treatment systems are widely used in developing countries especially in rural areas because of teir low cost and simplicity of construction, operation, and maintenance[3] and often consist of anaerobic, facultative and aerobic (maturation) ponds. Te anaerobic pond, wic is te initial treatment reactor, is designed to eliminate suspended solids and some of te soluble organic matter. Te residual organic matter is furter removed troug te activity of algae and eterotropic bacteria in te facultative pond. Te final stage of patogens and nutrients removal takes place in te maturation pond [4, 5]. Wastewater treatment in stabilization ponds mainly results from settling and complex symbiosis of bacteria and algae were te oxidation of organic matter is accomplised by bacteria in te presence of dissolved oxygen supplied by algal potosyntesis and surface reaeration [6, 7]. During te wastewaters storage, anoter different processes can also occur in ponds suc as te water volume decrease under natural evaporation, organic and inorganic compounds degradation and mineralization by microbiological flora, volatilization of some compounds and finally infiltration of wastewaters troug soil layers [8-10]. Tus, were land is somewat inexpensive, te weater is good and tere is a lack of equipments and skilled operations and also simple metod is considered, te wastewater stabilization ponds are te best options[11, 12]. ltoug many ponds ave been establised and operated, but still te pollutants dynamics in tese systems is not well understood[4]. To better perception of ydraulic conditions, many fundamental researc and scientific debates on te wastewater systems and kinetics of decomposition of pollutants separately ave been conducted[13]. For example, te pattern of a continuous tank flow in te Plug flow regime and te kinetics of first-order model versus te Monod equation kinetics ave been reported. Te practical performance of WSPs systems is dependent upon several factors, including: te type of wastewater; te organic loading regime; te geometry and pysical arrangement of te pond system; and ecological conditions suc as air temperature and te amount of wind and incident sunligt to wic te pond is exposed [14]. In addition to tese influential criteria, te ydraulic beavior of wastewater witin a pond system is also of principal importance in determining its overall treatment efficiency, since it controls te ydraulic residence time (HRT) and also te residence time distribution (RTD) wic governs te dispersion (mixing) of waste substrates and cemical and biological entities witin te reactor basin[15]. Meanwile in majority of applied wastewater stabilization ponds, te removal of organic matter (BOD 5 ) is te primary goal to design systems. Miscompreension of te dynamics of contaminants in te system can lead to incorrect design; it usually appears in improper sape of stabilization ponds, as results low pollutant removal efficiency and operational problems suc as clogging and sort circuiting. In order to allow optimization, better understanding of BOD 5 removal kinetics and sewage flow pattern are needed, wic can be acieved by using matematical models [16]. Suc developed studies potentially leading to tat te models of removing contaminants are more accurate wic results from te more correctly design. Gatering sufficient quality data for te accuracy of a kinetic model is often difficult and wen te model is applied to complex environmental parameters and according to guesswork kinetic coefficients, it can only lead to incorrect design[11, 12]. In tis study, a complete approac is detailed for a full-scale WSP system. Te aim of tis paper is analyze te flow caracteristics in a WSP, develop and validate a kinetic pattern wit data obtained from te influent and effluent analysis, and develop a metodology tat uses te BOD5 pattern predictions to build a compartmental model. MTERILS ND METHODS Data gatering Te researc is a cross-sectional study tat te wastewater treatment plant of Birjand city wic its wastewater treatment system is WSPs was investigated. In tis treatment plan, te wastewater, after passing troug te screening and flow measurement, was entered into te anaerobic pond wic te most portion of wastewater was treated into tis section. Subsequently te sewage entered into a facultative pond. fter tis step, te effluent drains into a secondary facultative pond wic acts as te ultimate unit. Te clorination unit as been built at te end of system but it is currently inactive. Sampling was conducted as two times per eac mont and for 6 monts duration. t every sampling time, all samples taken at tree intervals during a day. Simultaneously, te flow measurements and data recording of treatment plant input and output were carried out. To enance te range and accuracy of data, eac of samples was 431
analyzed separately twice and te averages were considered. ll tests were performed in te water and wastewater laboratory of Birjand city. Te kinetic models Figure 1 sow simple design equations wic relate te values of te input and output data of WSPs. Tese equations were developed from combination of CSTR or Plug flow kinetic models wit first order or Monod s models. Figure 1: Four modeling metods for stabilization pond; (1): combined model of first-order and Plug flow, (2): combined model of Firstorder and CSTR regime, (3): combined model of Plug flow and Monod, (4): combined model of Monod and CSTR. [11, 12]. Combining of Plug flow regime and first-order reaction kinetic creates te first design equation (Equation Kickut) wic is te easiest and most useful equation commonly in designing of WSPs. [11, 12] Q(lnCin C K 1 ) out = (Eq.1) : pond area, m 2 Q: flow rate, m 3 /d C in : input BOD 5 concentration, mg/l C out :output BOD 5 concentration, mg/l K 1 : velocity constant (m/d) lso, te combination of CSTR flow kinetic equation wit first-order reaction derived an equation tat associated wit simple values of input and output BOD 5 of WSPs. [11, 12]. dc dt 1 1 C in = C out τ τ + (Eq.2) Q( C C K C in out = (Eq.3) 2 out ) Were: τ represents a ydraulic retention time (d), and K 2 is te velocity constant (m/d). From te combination of simplified Monod s equation (Eq. 4) wit Plug flow or CSTR, te equation 5 and 6 were obtained, respectively [11, 12]. 432
dc C = K max (Eq.4) dt C + C alf Q( C C + 60ln( C K 3 / C )) in out in out = (Eq.5) Q( C C )( C + 60) K C in out out = (Eq. 6) 4 out Were: K max is te maximum BOD 5 removed in WSPs regardless te effect of temperature, (g/m 3.d). C alf is te amount of wastewater BOD 5 wile te removed BOD 5 value is alf of K max ; wic in tis study as been considered equal to 60 mg/l tat is te common value used in Monod s Eq[11, 12] In wastewater. lso in a study done in 2009 by Guangzi and et al. onto 80 WSPs, te C alf was considered 60 mg /l [11, 12]. Model ssessment ltoug equation (1) is used in te design of stabilization ponds for more tan two decades, but Eq 3, 5 and 6 were presented by Guangzi et al. for te first time in 2009 and used in tis study. Te accuracy and reliability of te results can be evaluated by comparison wit existing based practice data. Watever te equations sow closer matematical calculation, tey would be more accurate models. ll equations of 1, 3, 5 and 6 can be come as te following general formula: F Cin, Cout ) = K Q ( (Eq.7) For eac stabilization pond, te value of K can be obtained from linear regression and F (C in, C out ) and ( /Q) can be calculated using te average data. RESULTS ND DISCUSSION Matcing design equations Te conformity of Equations 1, 3, 5 and 6 were evaluated by comparing te documented values F (C in, C out ) wit te equations and actual data of stabilization ponds. Te values of K 1, K 2, K 3 and K 4 were obtained troug data regression. In eac of four equations, wen te data are placed in te general form of Equation 7, te value of K is obtained as following: parameter For: K 1 =0.08 d -1 (Eq.1) K 2 =0.201 md -1 (Eq.3) K 3 =8.73 g BOD 5 m -2 d -1 (Eq.5) K 4 =20.16 g BOD 5 m -2 d -1 (Eq.6) In te equations 1, 3 and 6, te linear relationsips between F (C in, C out ) and ( /Q) are somewat weak. Equation 1 (Equation Kickut) wic used typically in te design of stabilization ponds, sowed lower matematical relationsip between teoretical and actual results. comparing of statistical parameters also indicated tat te combination of two equations of 1 and 3 ave generated closer matematical relations, fter tat te coefficients of K 1 - K 4 obtained separately, te amounts of input BOD 5 were plotted vs. organic loading values. lso te coefficient of K 1 - K 4 resulted from te combined relationsips were plotted vs. Subsequently, in order to investigate te relationsip between te ratio of BOD / COD values and K 1 - K 4 obtained from combined equations, te BOD / COD vs. K 1 - K 4 were plotted in Figure 2. 433
K1 value - Eqn 1,m d-1 0.6 0.5 0.4 0.3 0.2 0.1-1E-15-0.1-0.2-0.3-0.4-0.5-0.6 y = 0.099x + 0.019 R² = 0.515 K1 value - Eqn 2,m d-1 1 0.8 0.6 0.4 0.2-1E-15-0.2-0.4-0.6 y = 2.434x - 1.181 R² = 0.384 K1 value - Eqn 3,m d-1 30 26 22 18 14 10 6 2-2 -6-10 y = 12.47x + 2.147 R² = 0.766 K1 value - Eqn 4,m d-1 40 35 30 25 20 15 10 5 0-5 -10 y = 42.33x - 8.038 R² = 0.626 Figure2.Trend of Regression coefficients (K 1) of combined equations of 1-4 versus BOD/COD ratios BOD remove g/m2.d 6.5 6 5.5 5 4.5 4 3.5 3 y = 0.320x + 2.199 R² = 0.841 3 4 5 6 7 8 9 BOD Loading. g/m2.d Figure3.Regression if BOD 5 amounts removal versus organic matter loading in studied stabilization ponds 434
CONCLUSION ccording to statistical parameter of R 2 obtained from two ypoteses kinetic equation of te first order kinetics Monod and Plug flow regime CSTR, it was identified tat te Plug flow regime sowed te closer matematical data tan CSTR flow regime wic confirms tat te Plug flow is te dominant flow regime in wastewater stabilization ponds in Birjand. lso between te four used models, te combined model of te Monod and Plug flow provided te best matematical relationsip between te teoretical predictions and te actual data of stabilization ponds. In a study conducted in 2009 by Guangzi and et al. using a combination of four models mentioned above, te combination model of Plug flow pattern and Monod s kinetics model provided te best matematical correlation. From obtained results of previous conducted researces and current study, it can be concluded tat te Monod s kinetics and Plug flow regime are dominance in stabilization ponds. lso, te resulted models for te COD data sowed lower values of statistical parameters (especially R 2 ) and tere was no significant correlation between te kinetic equations of te flow regime. Variation of kinetic coefficients: BOD 5 and flow rate data provided te possibility to assess canges of coefficients, pollutant loading and BOD / COD ratio. s te coefficients K 1 - K 4 of different substrates obtained, te organic loading values were plotted versus te amounts of input BOD 5 and it revealed tat in combined equations of 1, 2 and 4, te greater input BOD 5 values was consistent wit te sligtly lower kinetic coefficients wile tis status was reversed in te combined equation (3)and te larger input BOD 5 values was consistent wit sligtly larger kinetic coefficients tat in equations 1, 2 and 4, te speed of biological reactions was almost constant and as not canged wit cange of teir input loading. Meanwile Equation 3 indicates wic te rate of biological reactions would be increasing by increasing in te input loading of system and tis will confirm te applicability of predicted model of Monod and Plug flow regime for stabilization ponds of Birjand. Te first-order kinetics and Monod were able to predict te organic removal increasing wit increasing loading rates. lso in many oter studies, increased loading rates were consistent wit sligtly lower kinetic coefficients in eac of four combined models. However, in te present study, only te Monod model would indicate tis status. Te effect of Biodegradability Te BOD / COD ratio is generally used as an indicator of potential biodegradation of organic matter. If tis ratio be 0.5 or larger, te organic materials are considered as simple biodegradable wile if tis ratio be 0.3 or less, tey are considered as low biodegradable. Figure 2 sows tat tere are no statistically significant relationsip between te kinetic coefficients and te ratio of input BOD / COD. Tis as also been reported by Caselles-Osorio and Guangzi. Te removal of organic matter in stabilization ponds is not sensitive to te nature of te organic matter, weter tey are readily biodegradable or slowly. bout te input loading to te system and te removal of organic matter, it was also determined tat te removal of organic materials would increased wit increasing organic loading, indicating te iger organic loading capacity of te system rater tan its current state (see Figure 3). cknowledgment Tereby, te researcers are grateful from Water and Wastewater Company of Birjand Province and te Healt scool in order to elp in conducting tis researc. REFERENCES [1] lvarado,., et al.,. Water Researc, 2012. 46(2): p. 521-530. [2] Papadopoulos, F.H., V.. Tsirintzis, and.g. Zdragas,. Journal of Environmental Management, 2011. 92(12): p. 3130-3135. [3] Yi, Q., C. Hur, and Y. Kim,. Ecological Engineering, 2009. 35(1): p. 75-84. [4] Olukanni, D.O. and J.J. Ducoste,. Ecological Engineering, 2011. 37(11): p. 1878-1888. [5] Heaven, S., et al., Water Researc, 2012. 46(7): p. 2307-2323. [6] Beran, B. and F. Kargi,. Ecological modelling, 2005. 181(1): p. 39-57. [7] bbas, H., R. Nasr, and H. Seif,. Ecological Engineering, 2006. 28(1): p. 25-34. [8] Jarboui, R., et al.,. Journal of azardous materials, 2010. 176(1): p. 992-1005. 435
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