International Journal of Environment Science and Technology Center for Environment and Energy Research and Studies (CEERS) ISSN: 1735-1472 EISSN: 1735-2630 Vol. 6, Num. 1, 2009, pp. 51-56

International Journal of Enviornmental Science and Technology, Vol. 6, No. 1, Winter, 2009, pp. 51-56

Chemical oxygen demand fractions of municipal wastewater for modeling of wastewater treatment

*I. Pasztor; P. Thury; J. Pulai

Department of Environmental Engineering and Chemical Technology, University of Pannonia, Veszprem, Hungary
*Corresponding Author Email: fapipa@yahoo.com Tel.:+36 30 381 07 15; Fax: +36 88 578 321

Received 15 March 2008; revised 17 July 2008; accepted 23 August 2008

Code Number: st09005

ABSTRACT

When a new wastewater treatment plant is being designed by computer simulation, detailed data about organic fractions of influent wastewater (measured as chemical oxygen demand) are usually not available, but knowledge of the typical ranges of these fractions is indispensable. The influent chemical oxygen demand fractions can substantially influence the results of simulation-based design such as reactor volumes, solids residence time, effluent quality, oxygen demand, sludge production, etc. This article attempts to give an overview of wastewater organic fractions as modeling parameters and presents new chemical oxygen demand fractionation results from Hungary. According to the data from literature, the ratio of chemical oxygen demand components in raw wastewater is very different and the average composition is as follows: Inert particulate = 17.1 %, slowly biodegradable = 57.9 %, inert soluble = 7.8 % and readily biodegradable = 17.5 %. The Hungarian wastewater samples were analyzed according to STOWA (Dutch foundation for applied water research) protocol and the obtained results were not much different from those of literature ( inert particulate = 23.7 %, slowly biodegradable = 49.8 %, inert soluble = 4.6 % and readily biodegradable = 21.9 %), but some typical characteristics were observed.

Key words: Simulation, activated sludge models, sewage, characterization

INTRODUCTION

Use of the activated sludge models (ASM) in wastewater treatment plant (WWTP) simulation is widespread. Nowadays, the design of activated sludge WWTPs is based on simulation studies instead of the empiric formulas.

Base data availability for designers

In the case of new WWTP design when wastewater samples are not available for characterization, the level of model calibration is quite low. In such cases only literature data, default values and assumptions can provide the base information needed to set influent characteristics and biokinetic parameters (Vanrolleghem et al., 2003). The assumed influent Chemical oxygen demand (COD), N, P fractions can substantially influence the results of simulation-based design such as reactor volumes, solids residence time, effluent quality, oxygen demand, recirculation rates, sludge production, etc. Many publications are available on wastewater characterization, but not a single review article on COD fractions can be found. That is why summarizing the published data on wastewater composition is important in design practice and thus in achieving accuracy in WWTP design.

Division of organic matter

Generally, influent N (ammonium, nitrate, total nitrogen) and P (orthophosphate, total phosphorous) fractions can be assessed easily because they are routinely measured in every WWTP. Moreover, characterization of nitrogen and phosphorous fractions is not necessary in as much detail as for COD because the major part of influent nitrogen is present in ammonia and most of the phosphorous occurs in orthophosphate form. In ASM1 and ASM3 models, the total influent COD (COD_TOT) of the wastewater is divided into seven fractions and in ASM2 and ASM2d models into nine (Henze et al., 1987; 1995; 1999; 2000). The most important influent COD fractions, which are used as component variables in activated sludge models, are shown in Fig. 1.

Determination of COD fractions

Several methods have been developed for wastewater characterization, but the two most commonly used processes are the biological and physical-chemical characterizations. The biological or respirometric characterization method is based on the measurement of the biomass response during substrate degradation in either continuous flow or batch type experiment. The recorded utilization rate of the dissolved oxygen or nitrate (for denitrification potential) is closely related to the quality and quantity of available substrate in the system (Spanjers et al., 1995). This method needs experienced and skilled laboratory staff, specific experimental appliances and usually model-based interpretation. It may provide higher accuracy and is therefore more suitable for research studies.

The physicochemical method is based on the assumption that COD fractions model can be separated by filtration and flocculation processes and that COD of the gained fractions is easily measurable by standard chemical methods (Mamais et al., 1993). The main problem of this process is that the filtration can not effectively separate readily and slowly biodegradable fractions because the colloidal (between soluble and particulate) matter may contribute to both fractions. The combined physical-chemical and biological method of STOWA (Dutch foundation for applied water research) includes both filtration and flocculation steps with COD and BOD measurements (Roeleveld and Loosdrecht, 2002). This method is quick and easy to use, but it completely neglects biomass fractions. Also, the information provided on Xi fraction could be false because the fraction is determined by the remainder in the last characterization step [inert particulate (X_I) = COD_TOT slowly biodegradable (X_S ) readily biodegradable (S_S) inert soluble (S_I)]. The inaccuracies of the first determined fractions can be reflected in X_I (Melcer et al., 2003). The simplicity and cheapness of this method make it suitable for new simulation users and consultants (Sin et al., 2005).

MATERIALS AND METHODS

The aim of this study was to collect and summarize the data of wastewater COD fractions from several countries, including Hungary and to provide default modeling parameters to WWTP designers. First, the wastewater characteristics of different countries were collected from literature and then their COD fractions were summarized separately as primary (settled) and raw wastewater data (Tables 1 and 2). Concurrently, COD fractions of the influent sewage of 11 Hungarian WWTPs were determined using the STOWA protocol treating municipal wastewater with only minimal industrial contribution (Roeleveld and Loosdrecht, 2002). Twenty-four-hour composite samples of influent wastewater were collected after screening, but before primary sedimentation or any kind of biological treatment. Final effluent samples were collected at the outlet of the secondary sedimentation tanks before disinfection. The capacities of examined WWTPs were between 100 and 15,000 m³/d with 12-20 d solid retention time.

The main steps and theoretical formulas of COD fractionation

S_I = 90 % of filtered (0.45 mm) effluent COD; S_S= Flocculated (ZnSO₄) and filtered (0.45 mm) influent CODS_I; S_A= Measured by ionchromatography from influent sewage; S_F= S_S-S_A; X_S = BOI_ULTIMATES_S; (X_I) = COD_TOT- S_I S_S X_I

Measurement of COD and BOD was carried out following standard methods. The measured influent COD fractions of the two examined WWTPs were validated by computer simulation which yielded good correlation.

RESULTS AND DISCUSSION

Ranges of ASM COD fractions from design viewpoint
Readily biodegradable substrate

(S_S) is the most easily available COD fraction for heterotrophic microorganisms. The quantity of S_S can be a determining factor for anaerobic and anoxic reactor volumes in model-based design because the processes of phosphate release and denitrification are very sensitive to the easily accessible substrate fractions.

According to scientific data , readily biodegradable substrate ranges between 335 % in raw wastewater and 1457 % in settled wastewater (Lesouef et al., 1992; Funamizu et al., 1997; Chachaut et al., 2005; Marquot et al., 2006). In ASM2 and ASM2d models, this component is divided into volatile fatty acids (VFA = acetic acid, propionic acid, butyric acid, etc.) and non-VFA components (alcohols, lower amino acids, simple carbohydrates) (Henze, 1992). The VFA fraction ranges between 08.8 % in raw wastewater and 016 % in primary wastewater (Henze, 1992; Henze et al., 1995; Satoh et al., 2000; Hydromantis, 2007).

Slowly biodegradable substrate

(X_S) component comprises complex organic compounds which need to be hydrolyzed by extra cellular enzymes of bacteria prior to utilization. This component is usually made up of colloidal and suspended COD fractions. That is why it can not be separated from influent samples solely by physical separation. From the design point of view, this fraction usually has the highest oxygen demand and therefore it greatly influences the air flow required to aeration tank.

This component ranges between 2874 % in raw sewage and 24.565 % in primary wastewater (Solfrank, 1988; Lesouef et al., 1992; Roeleveld and Loosdrecht, 2002; Marquot et al., 2006).

Soluble unbiodegradable

COD fraction (S_I) can not be further biologically degraded in treatment plants and therefore the influent S_I COD leaves the plant without any significant change in its concentration. Because of the soluble inert fraction of sewage, WWTPs treating strong municipal wastewaters or septic tank effluents (COD_TOT > 1500 mg/L) with even perfect carbon oxidation may find it hard to meet the strict COD effluent standards. S_I fraction, relative to the COD_TOT, is in the range of 215 % in raw wastewater and 314.3 % in primary sewage (Henze, 1992; Xu and Hultman, 1996; Satoh et al., 2000).

Particulate unbiodegradable

(X_I) component is not degraded biologically during the treatment process and hence it can be removed only by clarification. From designers' point of view, this fraction significantly influences the quantity of primary and secondary sludge and therefore it determines the required dewatering and sludge treating capacity. Raw wastewater and primary wastewater contain 8-39 % and 420 % X_I, respectively. (Ekama et al., 1986; Henze et al., 1987; Carucci et al., 1999; Roeleveld and Loosdrecht, 2002).

Biomass COD

In ASM2 and ASM2d models, bio mass is classified into three fractions: Heterotrophic biomass (X_H); autotrophic biomass (X_AUT) and phosphorous accumulating microorganisms (X_PAO). COD fractions of X_AUT and X_PAO are generally not measured; their fractions in percent of COD_TOT are assumed to be about 1 % or less. Because of the low growth rate of autotrophic and phosphate accumulating organisms, their biomass fractions have to be considered in the modeled influent, otherwise, they can be washed out in high-loaded systems (Roeleveld and Loosdrecht, 2002).

Heterotrophic biomass may constitute a significant fraction in wastewater COD. The range of X_H is 720 % in raw wastewater and 3.525 % in primary settling tank effluent (Solfrank, 1988; Henze, 1992; Lesouef et al., 1992; Gernaey and Jorgensen, 2004).

Summary of foreign and Hungarian COD fractions

Data about the COD fractions of different studies were summarized separately as fractions of raw wastewater (Table 1) and settled wastewater (Table 2).

The results of Hungarian raw wastewater measurement are presented in Table 3. When the biomass fraction is not determined separately, as is often the case, X_H can be measured as X_S. Therefore, every Table has a `X<sub>S</sub> (+X<sub>H</sub>)' column in which the biomass fraction is included in the `slowly biodegradable organic fraction' to facilitate comparison of the data. The measured Hungarian average COD fractions in raw wastewater (X_I = 23.7 %, X_S = 49.8 %, S_I = 4.6 %, S_S = 21.9 %) are not much different from the corresponding values found in the literature of foreign countries (X_I = 17.1%, X_S = 57.9 %, S_I = 7.8 %, S_S = 17.5 %) (Figs. 2 and 3). The values of COD fractions as seen in the foreign publications are very diverse and belong to the Hungary. Nevertheless, some typical characteristics can be observed in the values of some countries. For example, Dutch wastewater contains high X_I, Swiss sewage has high S_I and Hungarian wastewater has low S_I ratio. However, such generalization is not warranted with scanty data.The high X_I can be explained as due to the long hydraulic residence time in sewage pipelines where a significant portion of the substrate fraction, biologically degraded, increases the ratio of inert particulate components. Outstanding inert soluble COD fraction in the sewage of large developed cities may be the result of industrial wastewater discharges.The differences between primary and raw wastewater COD fractions are along the expected lines; the soluble fractions (S_I + S_S) in primary sewage are higher while particulate fractions (X_S + X_I) are lower than in raw wastewaters. However, the decrement of suspended fraction and the increment of soluble fraction after clarification were very little that is only 12.5 %. The total substrate fraction (X_S + S_S) is 3 % higher in primary wastewater than in raw sewage. This implies that the settling properties of biodegradable fractions are worse than those of the inert components. This is because the slowly biodegradable substrate (X_S) has always some unabsorbed colloidal fraction that can not be settled in the primary clarifier. The Hungarian wastewater samples had, on the average 8 % lower X_S and 6.6 % higher X_I than the corresponding averages of literature data and this may result in increasing the aeration needs and sludge production of the WWTP (Figs. 2 and 3). However, the most interesting result is the relatively low (4.6 %) inert soluble fraction of the Hungarian samples as compared to the average of 7.5 % in the literature. If the influent total COD concentration in Hungarian wastewater is above 1000 mg/L (typical in Hungarian rural areas), then the WWTPs may have difficulties to achieve the desired discharge limits (e.g.: 50 mg/L) in spite of the relatively low inert soluble fraction.

ACKNOWLEDGMENTS

The financial support of the Department of Environmental Engineering and Chemical Technology at Pannonia University is gratefully acknowledged.

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