Fast pyrolysis of cassava rhizome in the presence of catalysts

Cassava rhizome was catalytically pyrolysed at 500 °C using analytical pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) in order to investigate the effect of catalysts on bio-oil properties. The catalysts studied were zeolite ZSM-5, two aluminosilicate mesoporous materials Al-MCM-41 and Al-MSU-F, and a proprietary commercial catalyst alumina-stabilised ceria MI-575. The influence of catalysts on pyrolysis products was observed through the yields of aromatic hydrocarbons, phenols, lignin-derived compounds, carbonyls, methanol and acetic acid. Results showed that all the catalysts produced aromatic hydrocarbons and reduced oxygenated lignin derivatives, thus indicating an improvement of bio-oil heating value and viscosity. Among the catalysts, ZSM-5 was the most active to all the changes in pyrolysis products. In addition, all the catalysts with the exception of MI-575 enhanced the formation of acetic acid. This is clearly a disadvantage with respect to the level of pH in the liquid bio-fuel.

Nitrogen cycle of effluent-irrigated energy crop plantations:from wastewater treatment to thermo-chemical conversion processes

This paper reviews nitrogen (N) cycle of effluent-irrigated energy crop plantations, starting from wastewater treatment to thermo-chemical conversion processes. In wastewater, N compounds contribute to eutrophication and toxicity in water cycle. Removal of N via vegetative filters and specifically in short-rotation energy plantations, is a relatively new approach to managing nitrogenous effluents. Though combustion of energy crops is in principle carbon neutral, in practice, N content may contribute to NOx emissions with significant global warming potential. Intermediate pyrolysis produces advanced fuels while reducing such emissions. By operating at intermediate temperature (500°C), it retains most N in char as pyrrolic-N, pyridinic-N, quaternary-N and amines. In addition, biochar provides long-term sequestration of carbon in soils.

Evaluation of catalytic pyrolysis of cassava rhizome by principal component analysis

Rhizome of cassava plants (Manihot esculenta Crantz) was catalytically pyrolysed at 500 °C using analytical pyrolysis–gas chromatography/mass spectrometry (Py–GC/MS) method in order to investigate the relative effect of various catalysts on pyrolysis products. Selected catalysts expected to affect bio-oil properties were used in this study. These include zeolites and related materials (ZSM-5, Al-MCM-41 and Al-MSU-F type), metal oxides (zinc oxide, zirconium (IV) oxide, cerium (IV) oxide and copper chromite) catalysts, proprietary commercial catalysts (Criterion-534 and alumina-stabilised ceria-MI-575) and natural catalysts (slate, char and ashes derived from char and biomass). The pyrolysis product distributions were monitored using models in principal components analysis (PCA) technique. The results showed that the zeolites, proprietary commercial catalysts, copper chromite and biomass-derived ash were selective to the reduction of most oxygenated lignin derivatives. The use of ZSM-5, Criterion-534 and Al-MSU-F catalysts enhanced the formation of aromatic hydrocarbons and phenols. No single catalyst was found to selectively reduce all carbonyl products. Instead, most of the carbonyl compounds containing hydroxyl group were reduced by zeolite and related materials, proprietary catalysts and copper chromite. The PCA model for carboxylic acids showed that zeolite ZSM-5 and Al-MSU-F tend to produce significant amounts of acetic and formic acids.

Predicting and diagnosing faults in wastewater treatment process by Bayesian Belief Networks

Diagnosing faults in wastewater treatment, like diagnosis of most problems, requires bi-directional plausible reasoning. This means that both predictive (from causes to symptoms) and diagnostic (from symptoms to causes) inferences have to be made, depending on the evidence available, in reasoning for the final diagnosis. The use of computer technology for the purpose of diagnosing faults in the wastewater process has been explored, and a rule-based expert system was initiated. It was found that such an approach has serious limitations in its ability to reason bi-directionally, which makes it unsuitable for diagnosing tasks under the conditions of uncertainty. The probabilistic approach known as Bayesian Belief Networks (BBNS) was then critically reviewed, and was found to be well-suited for diagnosis under uncertainty. The theory and application of BBNs are outlined. A full-scale BBN for the diagnosis of faults in a wastewater treatment plant based on the activated sludge system has been developed in this research. Results from the BBN show good agreement with the predictions of wastewater experts. It can be concluded that the BBNs are far superior to rule-based systems based on certainty factors in their ability to diagnose faults and predict systems in complex operating systems having inherently uncertain behaviour.

A method for the in-situ determination of the hydraulic conductivity of gravels as used in constructed wetlands for wastewater treatment

A new instrument and method are described that allow the hydraulic conductivities of highly permeable porous materials, such as gravels in constructed wetlands, to be determined in the field. The instrument consists of a Mariotte siphon and a submersible permeameter cell with manometer take-off tubes, to recreate in-situ the constant head permeameter test typically used with excavated samples. It allows permeability to be measured at different depths and positions over the wetland. Repeatability obtained at fixed positions was good (normalised standard deviation of 1–4%), and results obtained for highly homogenous silica sand compared well when the sand was retested in a lab permeameter (0.32 mm.s–1 and 0.31 mm.s–1 respectively). Practical results have a ±30% associated degree of uncertainty because of the mixed effect of natural variation in gravel core profiles, and interstitial clogging disruption during insertion of the tube into the gravel. This error is small, however, compared to the orders of magnitude spatial variations detected. The technique was used to survey the hydraulic conductivity profile of two constructed wetlands in the UK, aged 1 and 15 years respectively. Measured values were high (up to 900 mm.s –1) and varied by three orders of magnitude, reflecting the immaturity of the wetland. Detailed profiling of the younger system suggested the existence of preferential flow paths at a depth of 200 mm, corresponding to the transition between more coarse and less coarse gravel layers (6–12 mm and 3–6 mm respectively), and transverse drift towards the outlet.

Modelling of wastewater treatment plants:how far shall we go with sophisticated modelling tools?

Several levels of complexity are available for modelling of wastewater treatment plants. Modelling local effects rely on computational fluid dynamics (CFD) approaches whereas activated sludge models (ASM) represent the global methodology. By applying both modelling approaches to pilot plant and full scale systems, this paper evaluates the value of each method and especially their potential combination. Model structure identification for ASM is discussed based on a full-scale closed loop oxidation ditch modelling. It is illustrated how and for what circumstances information obtained via CFD (computational fluid dynamics) analysis, residence time distribution (RTD) and other experimental means can be used. Furthermore, CFD analysis of the multiphase flow mechanisms is employed to obtain a correct description of the oxygenation capacity of the system studied, including an easy implementation of this information in the classical ASM modelling (e.g. oxygen transfer). The combination of CFD and activated sludge modelling of wastewater treatment processes is applied to three reactor configurations, a perfectly mixed reactor, a pilot scale activated sludge basin (ASB) and a real scale ASB. The application of the biological models to the CFD model is validated against experimentation for the pilot scale ASB and against a classical global ASM model response. A first step in the evaluation of the potential of the combined CFD-ASM model is performed using a full scale oxidation ditch system as testing scenario.

A finite element approach to modelling the hydrological regime in horizontal subsurface flow constructed wetlands for wastewater treatment

A Finite Element Analysis (FEA) model is used to explore the relationship between clogging and hydraulics that occurs in Horizontal Subsurface Flow Treatment Wetlands (HSSF TWs) in the United Kingdom (UK). Clogging is assumed to be caused by particle transport and an existing single collector efficiency model is implemented to describe this behaviour. The flow model was validated against HSSF TW survey results obtained from the literature. The model successfully simulated the influence of overland flow on hydrodynamics, and the interaction between vertical flow through the low permeability surface layer and the horizontal flow of the saturated water table. The clogging model described the development of clogging within the system but under-predicted the extent of clogging which occurred over 15 years. This is because important clogging mechanisms were not considered by the model, such as biomass growth and vegetation establishment. The model showed the usefulness of FEA for linking hydraulic and clogging phenomenon in HSSF TWs and could be extended to include treatment processes. © 2011 Springer Science+Business Media B.V.

Fertigation potential of domestic wastewater for tree plantations

This study analyses feasibility of using domestic wastewater for fertigation of tree crops. Wastewater samples from different sources in domestic sector were analyzed and evaluated in terms of water quality and quantity. Water is rich in plant nutrients. However, due to possible presence of toxic ions and microbial load, it is recommended that direct use of wastewater for fertigation be limited to timber plantation and energy generation from biomass.