Stijn Van Hulle

Coupling a hydrological water quality model and an economic optimization model to set up a cost-effective emission reduction scenario for nitrogen

A modelling approach is presented that determines the most cost-effective set of reduction measures to reach an in-stream concentration target. The framework is based on the coupling of two models: the hydrological water quality model SWAT and an economic optimization model (Environmental Costing Model, ECM). SWAT is used to determine the relationship between the modelled in-stream concentration at the river basin outlet and the associated emission reduction. The ECM is used to set up marginal abatement cost curves for nutrients and oxygen demanding substances. Results for nitrogen are presented for the Grote Nete river basin in Belgium for the year 2006. Results show that the good status for total nitrogen can be reached in the study area. The most cost-effective measures are more productive dairy cattle, implementing basic measures as defined in the WFD, winter cover crops, improved efficiency of WWTP, enhanced fodder efficiency for pigs, further treatment of industrial waste water and tuned fertilization.

Impact of enzymatic pretreatment on corn stover degradation and biogas production

Corn stover is an agricultural residue consisting of lignocellulose, cellulose and hemicellulose polymers, sheeted in a lignin barrier. Corn stover can be used as feedstock for biogas production. Previous studies have shown biological pretreatment of lignocellulose materials can increase digestibility of the substrate improving hydrolysis, the rate-limiting step in biogas production. The impact of pretreating with different enzymes (laccase, manganese peroxidase and versatile peroxidase) and different incubation times, (0, 6 and 24 h) was studied. The effect on the matrix and biomethane production was determined. Pretreatments did not yield high concentrations of phenolic compounds, inhibitors of biogas production. The laccase enzyme showed an increase in biomethane production of 25% after 24 h of incubation. Pretreatment with peroxidase enzymes increased biomethane production with 17% after 6 h of incubation. As such it can be concluded that by introducing the different enzymes at different stages during pretreatment an increased biomethane production can be obtained.

Effect of enzymatic pretreatment of various lignocellulosic substrates on production of phenolic compounds and biomethane potential.

Pretreatment of lignocellulosic biomass is necessary to enhance the hydrolysis, which is the rate-limiting step in biogas production. Laccase and versatile peroxidase are enzymes known to degrade lignin. Therefore, the impact of enzymatic pretreatment was studied on a variety of biomass. A significant higher release in total phenolic compounds (TPC) was observed, never reaching the inhibiting values for anaerobic digestion. The initial concentration of TPC was higher in the substrates containing more lignin, miscanthus and willow. The anaerobic digestion of these two substrates resulted in a significant lower biomethane production (68.8-141.7 Nl/kg VS). Other substrates, corn stover, flax, wheat straw and hemp reached higher biomethane potential values (BMP), between 241 and 288 Nl/kg VS. Ensilaged maize reached 449 Nl/kg VS, due to the ensilation process, which can be seen as a biological and acid pretreatment. A significant relation (R(2) = 0.89) was found between lignin content and BMP.

A comparative study on the efficiency of ozonation and coagulation–flocculation as pretreatment to activated carbon adsorption of biologically stabilized landfill leachate

The present work investigates the potential of coagulation-flocculation and ozonation to pretreat biologically stabilized landfill leachate before granular activated carbon (GAC) adsorption. Both iron (III) chloride (FeCl3) and polyaluminium chloride (PACl) are investigated as coagulants. Better organic matter removal is observed when leachate was treated with FeCl3. At a dose of 1mg FeCl3/mg CODo (CODo: initial COD content), the COD and α254 removal was 66% and 88%, respectively. Dosing 1mg PACl/mg CODo resulted in 44% COD and 72% α254 removal. The settle-ability of sludge generated by PACl leveled off at 252mL/g, while a better settle-ability of 154mL/g was obtained for FeCl3 after dosing 1mg coagulant/mg CODo. For ozonation, the percentage of COD and α254 removal increased as the initial COD concentration decreased. Respectively 44% COD and 77% α254 removal was observed at 112mg COD/L compared to 5% COD and 26% α254 removal at 1846mg COD/L. Subsequent activated carbon adsorption of ozonated, coagulated and untreated leachate resulted in 77%, 53% and 8% total COD removal after treatment of 6 bed volumes. Clearly showing the benefit of treating the leachate before GAC adsorption. Mathematical modeling of the experimental GAC adsorption data with Thomas and Yoon-Nelson models show that ozonation increases the adsorption capacity and breakthrough time of GAC by a factor of 2.5 compared to coagulation-flocculation.

Modeling dissolved oxygen concentration for optimizing aeration systems and reducing oxygen consumption in activated sludge processes: a review

Aeration accounts for 30% to 75% of the total energy consumption in activated sludge processes (ASPs). This percentage can be significantly reduced since most aeration systems are not optimized for unsteady influent flow rates and oxygen requirements. Reconfiguration, replacement, and the application of optimal dissolved oxygen (DO) control strategies for current aeration systems within the facility and model-based optimization of DO in wastewater treatment plants can lead to impressive increased energy efficiency and savings and improved stability of the system. These measures increase the operational lifetime of the aeration equipment and improve effluent and activated sludge quality. This article provides a review of two critical nonlinear time-varying parameters that characterize the DO concentration dynamics in an ASP: the oxygen uptake rate (OUR), related to microorganism activity, and the volumetric oxygen mass transfer function, represented by the oxygen transfer rate (OTR). Second, the physico-chemical, geometric, and dynamic factors and aerator type affecting the oxygen mass transfer coefficient (K L a) are thoroughly discussed. The article concludes with model-based optimization, explaining the usefulness of accurate DO models in wastewater treatment, and provides examples for plant-wide or water chain cycle–focused optimizations.

Removal of atrazine in water by combination of activated carbon and dielectric barrier discharge

Efficiency of modern wastewater treatment plants to remove or decompose persistent contaminants in low concentration is often insufficient to meet the demands imposed by governmental laws. Novel, efficient and cheap methods are required to address this global issue. We developed a new type of plasma reactor, in which atrazine decomposition by atmospheric dielectric barrier discharge (DBD) in dry air is combined with micropollutant adsorption on activated carbon textile and with extra bubbling of generated ozone. Investigation of reaction kinetics and by-product analysis shows that increasing input power with a factor 3.5 leads to deeper atrazine oxidation without significantly changing energy yield of atrazine removal. By-products of first and later generations are detected with HPLC-MS analysis in water and adsorbed on the activated carbon textile. Our reactor is compared in energy efficiency with reactors described in literature, showing that combination of plasma discharge with pollutant adsorption and ozone recycling is attractive for future applications of water treatment.

Filtration performance of electrospun polyamide nanofibres loaded with bactericides

Electrospinning is a process to generate nanofibrous nonwovens. With these nonwovens, many applications can be targeted, such as water filtration. In this paper, polyamide nanofibrous membranes are evaluated for their pore size, a key parameter in water filtration, and for their removal of microorganisms. To increase the removal efficiency to values exceeding the state of the art, innovative functionalization of the nanofibres is studied. The nanofibrous membranes are functionalized using a one step method. Different functionalization chemicals are investigated which are Ag nanoparticles and bactericides. Ag functionalized nanofibres are used as a reference medium to compare with a novel bactericide based functionalization system. It is seen that nanofibrous membranes functionalized with the bactericides exceed the normal removal efficiencies obtained by microfiltration membranes. Furthermore, knowledge is built up on how these bactericides are inserted in the nanofibres themselves.

Performance analysis and optimization of autotrophic nitrogen removal in different reactor configurations: a modelling study.

The autotrophic nitrogen removal process (partial nitritation combined with the Anammox process) is a new and sustainable nitrogen removal technique for nitrogen‐rich streams. A modelling study has been performed to define optimal process conditions (temperature, oxygen supply, pH and biomass retention) and to investigate the influence of chemical oxygen demand, nitrogen loading rate and hydraulic retention time on three alternative reactor configurations: a single oxygen‐limited partial nitritation reactor, a single Anammox reactor, and a combination of partial nitritation and Anammox in a single reactor. The model applied was compared to experimental data from the literature and gave good agreement for all three reactor configurations. The simulations revealed that a system with separated partial nitritation and Anammox offered a wider range of optimal process conditions than a one‐reactor system. The key factors in the successful operation of partial nitritation were found to be control of aeration, ammonium loading rate and temperature. Heterotrophs remained present in all three reactor systems and it was confirmed that interaction between heterotrophs and Anammox and between heterotrophs and ammonium oxidizers was possible.

Performance and kinetic process analysis of an Anammox reactor in view of application for landfill leachate treatment

Anammox has shown its promise and low cost for removing nitrogen from high strength wastewater such as landfill leachate. A reactor was inoculated with nitrification–denitrification sludge originating from a landfill leachate treating waste water treatment plant. During the operation, the sludge gradually converted into red Anammox granular sludge with high and stable Anammox activity. At a maximal nitrogen loading rate of 0.6 g N l−1 d−1, the reactor presented ammonium and nitrite removal efficiencies of above 90%. In addition, a modified Stover–Kincannon model was applied to simulate and assess the performance of the Anammox reactor. The Stover–Kincannon model was appropriate for the description of the nitrogen removal in the reactor with the high regression coefficient values (R2=0.946) and low Theils inequality coefficient (TIC) values (TIC<0.3). The model results showed that the maximal N loading rate of the reactor should be 3.69 g N l−1 d−1.

Calibration and statistical analysis of a simplified model for the anaerobic digestion of solid waste

Modelling is increasingly used for optimizing environmental treatment processes such as anaerobic digestion. It allows problems such as instability of the process to be solved by predicting various scenarios. The anaerobic digestion model No. 1 (ADM1) is accepted worldwide as the standard model for the description of anaerobic digestion. However, it is sophisticated and complex, so it is not user friendly. Therefore, a mathematical method was developed that allows the calculation of the reactor pH, as well as the biogas flow rate (Q) and composition (expressed as the CO2 partial pressure, pCO2), based on a small number of widely available analyses such as chemical oxygen demand and total organic carbon. Furthermore, the ADM1 model was originally designed for anaerobic digestion of wastewater. In this work, the ADM1 model is evaluated for the first time for application in the modelling of solid waste digestion. This evaluation was performed in two steps. First, a list of experimentally available lab‐scale data (pH and Q) was grouped according to the composition and origin of the treated solid waste (e.g. manure or vegetable waste). For each group the developed model for the calculation of pH, Q and pCO2 was calibrated with this lab‐scale data. After calibration, the model was validated with additional experimental results. It could be demonstrated statistically that the model was able to predict the experimental results, although the confidence region was rather large.