Abstract
In this study, the variation of biomass, kinetic parameters, and stoichiometric parameters for ammoniaoxidizing bacteria (AOB) and nitriteoxidizing bacteria (NOB) in TNCU3 process were explored at different aerobic hydraulic retention time (AHRT). The results indicated that the growth rate constants of AOB were 0.92, 0.88, and 0.95 days^{−1}, respectively, meanwhile, those of NOB were 2.58 1.41, and 1.40 days^{−1}, respectively, when AHRT was 5, 6, and 7 h. The lysis rate constants for AOB and NOB were 0.13 and 0.17 days^{−1}, respectively. When AHRT was 5, 6, and 7 h, the yield coefficients of AOB were 0.20, 0.23, and 0.28 g COD g^{−1} N, respectively, meanwhile those of NOB were 0.23, 0.19, and 0.22 g COD g^{−1} N, respectively. The average percentage of AOB was 0.44, 0.61, and 0.64%, respectively, while that of NOB was 0.46, 0.61, and 0.74%, respectively. The relation between the biomass percentage of AOB and AHRT was in a good agreement with first type hyperbolic curve. The relation between the biomass percentage of NOB and AHRT was in a good agreement with seven types of curve including simple exponential curve, power exponential curve, and first type hyperbolic curve etc. When the AHRT increased from 5 to 7 h, the removal efficiency of NH_{4} ^{+}–N increased from 80.2 to 94.8%, or by 14.6%. Meanwhile, the removal efficiency of total nitrogen increased from 63.6 to 70.9%, or by 7.3%.
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Abbreviations
 b_{AOB} :

Lysis rate constant of ammoniaoxidizing bacteria (1/T)
 b_{NOB} :

Lysis rate constant of nitriteoxidizing bacteria (1/T)
 OUR_{AOB} :

Oxygen uptake rate of ammoniaoxidizing bacteria (M/T L^{3})
 OUR_{H} :

Oxygen uptake rate of heterotrophic bacteria (M/T L^{3})
 OUR_{NOB} :

Oxygen uptake rate of nitriteoxidizing bacteria (M/T L^{3})
 \( {\text{S}}_{{{\text{NH}}_{ 4} }} \) :

Concentration of ammonia (M/L^{3})
 \( {\text{S}}_{{{\text{NO}}_{ 2} }} \) :

Concentration of nitrite (M/L^{3})
 \( {\text{S}}_{{{\text{O}}_{ 2} }} \) :

Concentration of oxygen (M/L^{3})
 X_{AOB} :

Concentration of ammoniaoxidizing bacteria (M/L^{3})
 X_{NOB} :

Concentration of nitriteoxidizing bacteria (M/L^{3})
 Y_{AOB} :

Yield coefficient of ammoniaoxidizing bacteria
 Y_{NOB} :

Yield coefficient of ammoniaoxidizing bacteria
 μ_{AOB} :

Growth rate constant of ammoniaoxidizing bacteria (1/T)
 μ_{NOB} :

Growth rate constant of nitriteoxidizing bacteria (1/T)
References
Alkan U, Eleren SÇ, Nalbur BE, Odabaş E (2008) Influence of the activated sludge system configuration on heavy metal toxicity reduction. World J Microbiol Biotechnol 24:1435–1443
APHA, AWWA, WEF (1995) Standard methods for the examination of water and wastewater, 19th edn. American Public Health Association, American Water Works Association, Water Environment Federation, Washington DC
Daigger GT, Parker DS (2000) Enhancing nitrification in North American activated sludge plants. Water Sci Technol 41:97–105
Dogruel S, Genceli EA, Babuna FG, Orhon D (2006) An investigation on the optimal location of ozonation within biological treatment for a tannery wastewater. J Chem Technol Biotechnol 81:1877–1885
Fernández B, Vilar A, Ben M, Kennes C, Veiga MC (2005) Partial nitrification of wastewater from an aminoplastic resin producing factory. Water Sci Technol 52:517–524
Güven D, Kutlu Ö, İnsel G, Sözen S (2009) Modelbased process analysis of partial nitrification efficiency under dynamic nitrogen loading. Bioprocess Biosyst Eng 32:655–661
Inoue D, Wada K, Sei K, Ike M, Fujita M (2005) Comparative evaluation of quantitative polymerase chain reaction methods for routine enumeration of specific bacterial DNA in aquatic samples. World J Microbiol Biotechnol 21:1029–1035
Kappeler J, Brodmann R (1995) Low F/M bulking and scumming: towards a better understanding by modeling. Water Sci Technol 31:225–324
Kappeler J, Gujer W (1992) Estimation of kinetic parameters of heterotrophic biomass under aerobic conditions and characterization of wastewater for activated sludge modelling. Water Sci Technol 25:125–139
Leta S, Assefa F, Dalhammar G (2005) Enhancing biological nitrogen removal from tannery effluent by using the efficient Brachymonas denitrificans in pilot plant operations. World J Microbiol Biotechnol 21:545–552
Li X, Zhang R (2002) Aerobic treatment of dairy wastewater with sequencing batch reactor systems. Bioprocess Biosyst Eng 25:103–109
Nowak O, Svardal K, Schweighofer P (1995) The dynamic behaviour of nitrifying activated sludge systems8 influenced by inhibiting wastewater compounds. Water Sci Technol 31:115–124
Pai TY (2007) Modeling nitrite and nitrate variations in A^{2}O process under different return oxic mixed liquid using an extended model. Process Biochem 42:978–987
Pai TY, Ouyang CF, Su JL, Leu HG (2001) Modelling the steadystate effluent characteristics of the TNCU process under different return mixed liquid. Appl Math Model 25:1025–1038
Pai TY, Tsai YP, Chou YJ, Chang HY, Leu HG, Ouyang CF (2004a) Microbial kinetic analysis of three different types of EBNR process. Chemosphere 55:109–118
Pai TY, Chuang SH, Tsai YP, Ouyang CF (2004b) Modelling a combined anaerobic/anoxic oxide and rotating biological contactors process under dissolved oxygen variation by using an activated sludge—biofilm hybrid model. J Environ EngASCE 130:1433–1441
Pai TY, Wang SC, Lo HM, Chiang CF, Liu MH, Chiou RJ, Chen WY, Hung PS, Liao WC, Leu HG (2009a) Novel modeling concept for evaluating the effects of cadmium and copper on heterotrophic growth and lysis rates in activated sludge process. J Hazard Mater 166:200–206
Pai TY, Chang HY, Wan TJ, Chuang SH, Tsai YP (2009b) Using an extended activated sludge model to simulate nitrite and nitrate variations in TNCU2 process. Appl Math Model 33:4259–4268
Pai TY, Wang SC, Lin CY, Liao WC, Chu HH, Lin TS, Liu CC, Lin SW (2009c) Two types of organophosphate pesticides and their combined effects on heterotrophic growth rates in activated sludge process. J Chem Technol Biotechnol (In press)
Pérez J, Poughon L, Dussap C, Montesinos JL (2005) Dynamics and steady state operation of a nitrifying fixed bed biofilm reactor: mathematical model based description. Process Biochem 40:2359–2369
Ramothokang TR, Naidoo D, Bux F (2006) Morphological shifts in filamentous bacteria isolated from activated sludge processes. World J Microbiol Biotechnol 22:845–850
Siripong S, Rittmann BE (2007) Diversity study of nitrifying bacteria in fullscale municipal wastewater treatment plants. Water Res 41:1110–1120
Tartakovsky B, Kotlar E, Sheintuch M (1996) Coupled nitrification–denitrification processes in a mixed culture of coimmobilized cells: analysis and experiment. Chem Eng Sci 51:2327–2336
Tsai YP, You SJ, Pai TY, Chen KW (2006) Effect of Cd (II) on different bacterial species present in a single sludge activated sludge process for carbon and nutrient removal. J Environ EngASCE 132:173–180
Vaiopoulou E, Aivasidis A (2008) A modified UCT method for biological nutrient removal: configuration and performance. Chemosphere 72:1062–1068
Van Hulle SWH, Vanrolleghem PA (2004) Modelling and optimisation of a chemical industry wastewater treatment plant subjected to varying production schedules. J Chem Technol Biotechnol 79:1084–1091
Wang X, Ma Y, Peng Y, Wang S (2007) Shortcut nitrification of domestic wastewater in a pilotscale A/O nitrogen removal plant. Bioprocess Biosyst Eng 30:91–97
Wijffels RH, de Gooijer CD, Schepers AW, Beuling EE, Mallee LF, Tramper J (1995) Dynamic modeling of immobilized Nitrosomonas europaea: implementation of diffusion limitation over expanding microcolonies. Enzyme Microb Technol 17:462–471
Acknowledgments
The authors are grateful to the National Science Council of R.O.C. for financial support under the grant number NSC 952221E324018.
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Appendix
Appendix
Calculation of growth rate constant, lysis rate constant, yield, and biomass
The process kinetic and stoichiometry shown in Tables 3 and 4 represent the activated sludge behavior which was adopted from Taiwan Extension Activated Sludge model (TWEA; Pai et al. 2009a, b; Pai 2007).According to Tables 3 and 4, oxygen consumed by X_{AOB} with neither substrate nor oxygen limitation is:
The growth for X_{AOB} with neither substrate nor oxygen limitation can be written as follow:
Integration of Eq. 2 leads to:
Equation 3 can be introduced into Eq. 1. Then the oxygen respiration is known at any time without limitations:
The logarithmic configuration of Eq. 4 is:
When time is equal to 0, Eq. 5 becomes:
The term \( \ln \left[ {{\text{OUR}}_{\text{AOB}} ( {\text{t}}_{ 0} )} \right] \) in Eq. 6 represents the yaxis intercept of \( \ln \left[ {\text{OUR}} \right]_{\text{AOB}} \) vs. time curve. Then X_{AOB} biomass at initial time in a closed batch chamber can be calculated as follows:
Since the units of yaxis and xaxis are mg O_{2} l^{−1} h^{−1} and day in the graph of \( \ln \left[ {\text{OUR}} \right]_{\text{AOB}} \) vs. time, a converter of 24 is adopted in Eq. 7. When Eq. 4 is differentiated with respect to time t, the resulting equation is:
The term of \( \left[ {\left( {{\frac{{3.43  {\text{Y}}_{\text{AOB}} }}{{{\text{Y}}_{\text{AOB}} }}}} \right) \cdot {{\upmu}}_{\text{AOB}}  {\text{b}}_{\text{AOB}} } \right] \cdot {\text{X}}_{\text{AOB}} ( {\text{t}}_{ 0} ) \cdot {\text{e}}^{{ ( {{\upmu}}_{\text{AOB}}  {\text{b}}_{\text{AOB}} ) \cdot {\text{t}}}} \) equals \( {\text{OUR}}_{\text{AOB}} ( {\text{t)}} \) again, so Eq. 8 can be rearranged as:
Rearranging Eq. 9, the following expression can be obtained:
Integrating Eq. 10, the resulting equation is:
When time equals 0, Eq. 11 becomes:
Substituting Eq. 12 into Eq. 11, the resulting equation is:
This equation represents a straight line with (μ_{AOB} − b_{AOB}) as slope in a diagram of natural logarithm of OUR vs. time. If b_{AOB} value can be determined, μ_{AOB} can be approximately calculated:
The b_{AOB} value was determined by the following steps. First, a fixed amount of sludge was placed into a nonfed aerated batch reactor for 10 days. Second, a certain amount of sludge was taken from the above batch reactor each time and transferred into the OUR chamber to measure the OUR_{AOB}. By plotting the OUR_{AOB} vs. time, the lysis rate constant, b_{AOB} could be estimated by exponential curve fitting. The X_{NOB} biomass can be calculated according to analogous derivation and expressed as:
According to our previous work (Tsai et al. 2006), the yield coefficient for X_{AOB} can be determined using respirometer and calculated by the following equation:
The yield coefficients for X_{NOB} are calculated according to
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Pai, T., Chiou, R., Tzeng, C. et al. Variation of biomass and kinetic parameters for nitrifying species in the TNCU3 process at different aerobic hydraulic retention times. World J Microbiol Biotechnol 26, 589–597 (2010). https://doi.org/10.1007/s112740090208y
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Keywords
 Ammoniaoxidizing bacteria (AOB)
 Growth rate constant
 Hydraulic retention time (HRT)
 Lysis rate constant
 Nitriteoxidizing bacteria (NOB)
 Yield coefficient