Toxicity assessment of common xenobiotic compounds on municipal activated sludge: comparison between respirometry and Microtox

The toxicity of four xenobiotic compounds 3,5-dichlorophenol, formaldehyde, 4-nitrophenol and dichloromethane, representative of industrial wastewater contaminants was evaluated by a simple respirometric procedure set up on the basis of OECD Method 209 and by the Microtox bioassay. Very good reproducibility was observed for both methods, the variation coefficients being in the range of 2-10% for the respirometric procedure and 6-15% for Microtox, values that can be considered very good for a biological method. Comparison of EC(50) data obtained with the two methods shows that in both cases 3,5-dichlorophenol is more toxic than other compounds investigated and dichloromethane has a very low toxicity value. Intermediate EC(50) values were found for the two other chemicals, formaldehyde and 4-nitrophenol. Moreover, the Microtox EC(50) values are generally lower (except for dichloromethane) than the respirometric ones: these differences could be explained by the fact that the Microtox method uses a pure culture of marine species and, therefore, should not necessarily be expected to behave like a community of activated sludge bacteria. In conclusion, both methods can be usefully applied for toxicity detection in wastewater treatment plants but it is advisable to take into account that Microtox is more sensitive than respirometry in estimating the acute toxicity effect on the biomass operating in the plant.     

The inhibitory effects of heavy metals and organic compounds on the net maximum specific growth rate of the autotrophic biomass in activated sludge

A respirometry technique can be applied as an effective method to determine the net maximum specific growth rate of autotrophic biomass under both normal conditions and when inhibition occurs. The net maximum specific growth rate of uninhibited autotrophic biomass, expressed as (mu(A)-b(A)), is approximately 0.8 per day [Proceeding of the International Congress on CHISA, Prague, 2002, p. 1]. Several heavy metals and organic compounds have inhibitory effects. Copper (Cu(2+)) has stronger inhibitory effects than zinc (Zn(2+)), and inhibits the nitrification process by 50% at 0.08 mg/l [(mu(A)-b(A)) = 0.4 per day], while the same concentration of Zn(2+) establishes 12% inhibition only [(mu(A)-b(A)) = 0.75 per day]. Inhibition with Cu(2+) starts at concentrations above 0.05 mg/l, while this is above 0.3mg/l for Zn(2+). The inhibition of the nitrification process is complete at 1.2mg/l for both Cu(2+) and Zn(2+). Among the selected organic compounds tested n the experiments, the degree of inhibition decreases as follow: chlorobenzene>trichloroethylene (TCE)>phenol>ethylbenzene. Chlorobenzene already inhibits the autotrophic biomass at 0.25 mg/l. The nitrification process is totally inhibited by adding 0.75 mg/l of chlorobenzene. TCE has a less inhibitory effect on the nitrification process and 50% inhibition is noticed at 0.75 mg/l TCE. The nitrification process is totally inhibited at 1mg/l TCE. Phenol inhibits the nitrification for 50% at 3 mg/l. The inhibitory effect of phenol is almost constant in the range 4-10 mg/l and complete inhibition is reached at 50 mg/l. The inhibitory effect of ethylbenzene is 50% at 8 mg/l and the autotrophic biomass is totally inhibited at 50 mg/l. Experimental findings are compared with literature data, which generally and significantly overestimate the inhibition threshold concentrations.     

Inorganic carbon limitations on nitrification: experimental assessment and modelling

Nitrification is a two-step process that involves two different biomass populations: ammonia oxidising biomass (AOB) and nitrite oxidising biomass (NOB). Both populations are autotrophic (i.e. their carbon source is inorganic). Therefore, a deficit of this substrate should result in a decrease of the process rate. Recent technology advances such as the SHARON process have brought new scenarios in biological nitrogen removal where these limitations should be considered. Hence, this work examines the inorganic carbon limitation using respirometric and titrimetric techniques. For this aim, the nitrification rate was measured at different total inorganic carbon (TIC) concentrations. The experimental results obtained show that AOB was limited at TIC concentrations lower than 3mmol CL(-1). At the same time, no carbon source limitation for NOB was observed in spite of the low TIC concentrations attained (lower than 0.1mmol CL(-1)). The AOB limitation could be successfully modelled using Monod, Tessier and sigmoidal kinetics. The best fit was obtained with sigmoidal kinetics. However, unexpected biomass activity (oxygen consumption) was observed despite a very low TIC concentration (lower than 0.1mmol CL(-1)).     

Variability estimation of urban wastewater biodegradable fractions by respirometry

This paper presents a methodology for assessing the variability of biodegradable chemical oxygen demand (COD) fractions in urban wastewaters. Thirteen raw wastewater samples from combined and separate sewers feeding the same plant were characterised, and two optimisation procedures were applied in order to evaluate the variability in biodegradable fractions and related kinetic parameters. Through an overall optimisation on all the samples, a unique kinetic parameter set was obtained with a three-substrate model including an adsorption stage. This method required powerful numerical treatment, but improved the identifiability problem compared to the usual sample-to-sample optimisation. The results showed that the fractionation of samples collected in the combined sewer was much more variable (standard deviation of 70% of the mean values) than the fractionation of the separate sewer samples, and the slowly biodegradable COD fraction was the most significant fraction (45% of the total COD on average). Because these samples were collected under various rain conditions, the standard deviations obtained here on the combined sewer biodegradable fractions could be used as a first estimation of the variability of this type of sewer system.     

Assessing wastewater metal toxicity with bacterial bioluminescence in a bench-scale wastewater treatment system

The effectiveness of a previously developed toxicity monitoring method for activated sludge wastewater treatment employing a bioluminescent bacterium (Shk1) was evaluated in batch experiments and a bench-scale activated sludge system exposed to heavy metals (Cu, Zn, Ni, and Cd). Influent wastewater (primary clarifier supernatant) and activated sludge from a municipal wastewater treatment plant were used in both batch experiments and in the bench-scale wastewater treatment system. Shk1 bioluminescence was most sensitive to Cd and Zn, followed by Cu, and then Ni in order of decreasing sensitivity. In contrast, activated sludge specific oxygen uptake rate was most sensitive to Cu, followed by Cd and Zn, and finally Ni. The same pattern of sensitivity was observed in batch and bench-scale evaluations. Batch experiments examining the effect of metal adsorption were performed. The adsorption of metals to activated sludge and reduction in bioavailability due to chelation by soluble organics or by precipitation in wastewater was found to be an important effect in mediating differences in toxicity response between bioluminescence and respirometry. Batch adsorption experiments indicated that the activated sludge adsorption capacity was highest for Cu, followed by Cd, Ni, and then Zn. A simple mathematical model for the soluble metal concentration in the aeration basin and clarifier was developed utilizing metal distribution coefficients determined from the batch adsorption experiments. Model predictions compared well with results from the bench-scale activated sludge experiments.     

Utilization of landfill leachate parameters for pretreatment by Fenton reaction and struvite precipitation—A comparative study

This paper reports results of laboratory studies on two pretreatment methods, struvite precipitation using aeration with H₃PO₄ and Fenton oxidation. These methods utilized specific properties of the leachate: high magnesium content (172 mg L⁻¹) for struvite precipitation and a high iron concentration (56 mg L⁻¹) for Fenton treatment. Struvite precipitation (H₃PO₄, 700 mg L⁻¹) removed 36% of NH₃-N and 24% of SCOD. Fenton treatment (at pH 3.5) required 650 mg L⁻¹ of H₂O₂ and removed 66% of SCOD. The effect of each pretreatment on the returned activated sludge (RAS) was evaluated using respirometry. Both methods reduced the inhibitory effect of the leachate and substantially increased biokinetic parameters. The BOD₅/SCOD ratio increased from 0.63 for raw leachate to 0.82 (struvite) and 0.88 (Fenton). Estimation of capital and operational costs of the total leachate treatment indicated that aeration with struvite precipitation, followed by biological treatment, would be the preferred option.     

Exploring temporal variations of oxygen saturation constants of nitrifying bacteria

Activated sludge models (ASM) are generally accepted as state-of-the-art in modeling wastewater treatment plants. In this paper, we assess the temporal variability of an ASM parameter-the oxygen half-saturation constant of autotrophic bacteria (K(O),(AUT)). A series of respirometric experiments is performed for conventional activated sludge and sludge from a membrane bioreactor. K(O) values are estimated for both ammonium-oxidizing and nitrite-oxidizing bacteria. For parameter estimation, the Monod kinetic model structure is extended by a sensor model. Still remaining systematic deviations between data and model are considered by a thorough residual analysis: (1) uncertainty estimates of K(O) are corrected to reflect model structure deficiencies and (2) the inter-experimental cross-correlation of residuals is taken into account to assess temporal changes. We conclude that K(O),(AUT) is a time variable parameter and should be considered accordingly.     

Extensions to modeling aerobic carbon degradation using combined respirometric-titrimetric measurements in view of activated sludge model calibration

Recently a model was introduced to interpret the respirometric (OUR) -titrimetric (Hp) data obtained from aerobic oxidation of different carbon sources in view of calibration of Activated Sludge Model No.1 (ASM1). The model requires, among others, the carbon dioxide transfer rate (CTR) to be relatively constant during aerobic experiments. As CTR is an inherently nonlinear process, this assumption may not hold for certain experimental conditions. Hence, we extended the model to describe the nonlinear CTR behavior. A simple calibration procedure of the CO2 model was developed only using titrimetric data. The identifiable parameter subset of this model when using titrimetric data only contained the first equilibrium constant of the CO2 dissociation, pK1, the initial aqueous CO2 concentration, C(Tinit) and the nitrogen content of biomass, i(NBM). The extended model was then successfully applied to interpret typical data obtained from respirometric-titrimetric measurements with a nonlinear CO2 stripping process. The parameter estimation results using titrimetric data were consistent with the results estimated using respirometric data (OUR) alone or combined OUR and Hp data, thereby supporting the validity of the dynamic CO2 model and its calibration approach. The increased range of applicability and accurate utilization of the titrimetric data are expected to contribute particularly to the improvement of calibration of ASM models using batch experiments.     

Reliability of parameter estimation in respirometric models

When modelling a biochemical system, the fact that model parameters cannot be estimated exactly stimulates the definition of tests for checking unreliable estimates and design better experiments. The method applied in this paper is a further development from Marsili-Libelli et al. [2003. Confidence regions of estimated parameters for ecological systems. Ecol. Model. 165, 127-146.] and is based on the confidence regions computed with the Fisher or the Hessian matrix. It detects the influence of the curvature, representing the distortion of the model response due to its nonlinear structure. If the test is passed then the estimation can be considered reliable, in the sense that the optimisation search has reached a point on the error surface where the effect of nonlinearities is negligible. The test is used here for an assessment of respirometric model calibration, i.e. checking the experimental design and estimation reliability, with an application to real-life data in the ASM context. Only dissolved oxygen measurements have been considered, because this is a very popular experimental set-up in wastewater modelling. The estimation of a two-step nitrification model using batch respirometric data is considered, showing that the initial amount of ammonium-N and the number of data play a crucial role in obtaining reliable estimates. From this basic application other results are derived, such as the estimation of the combined yield factor and of the second step parameters, based on a modified kinetics and a specific nitrite experiment. Finally, guidelines for designing reliable experiments are provided.     

Online titrimetric and off-gas analysis for examining nitrification processes in wastewater treatment

The two steps of nitrification, namely the oxidation of ammonia to nitrite and nitrite to nitrate, often need to be considered separately in process studies. For a detailed examination, it is desirable to monitor the two-step sequence using online measurements. In this paper, the use of online titrimetric and off-gas analysis (TOGA) methods for the examination of the process is presented. Using the known reaction stoichiometry, combination of the measured signals (rates of hydrogen ion production, oxygen uptake and carbon dioxide transfer) allows the determination of the three key process rates, namely the ammonia consumption rate, the nitrite accumulation rate and the nitrate production rate.Individual reaction rates determined with the TOGA sensor under a number of operation conditions are presented. The rates calculated directly from the measured signals are compared with those obtained from offline liquid sample analysis. Statistical analysis confirms that the results from the two approaches match well. This result could not have been guaranteed using alternative online methods.As a case study, the influences of pH and dissolved oxygen (DO) on nitrite accumulation are tested using the proposed method. It is shown that nitrite accumulation decreased with increasing DO and pH. Possible reasons for these observations are discussed.