Performance of a Sequential Reactive Barrier for Bioremediation of Coal Tar Contaminated Groundwater

Following a thorough site investigation, a biological Sequential Reactive Barrier (SEREBAR), designed to remove Polycyclic Aromatic Hydrocarbons (PAHs) and BTEX compounds, was installed at a Former Manufactured Gas Plant (FMGP) site. The novel design of the barrier comprises, in series, an interceptor and six reactive chambers. The first four chambers (2 nonaerated-2 aerated) were filled with sand to encourage microbial colonization. Sorbant Granular Activated Carbon (GAC) was present in the final two chambers in order to remove any recalcitrant compounds. The SEREBAR has been in continuous operation for 2 years at different operational flow rates (ranging from 320 L/d to 4000 L/d, with corresponding residence times in each chamber of 19 days and 1.5 days, respectively). Under low flow rate conditions (320-520 L/d) the majority of contaminant removal (>93%) occurred biotically within the interceptor and the aerated chambers. Under high flow rates (1000-4000 L/d) and following the installation of a new interceptor to prevent passive aeration, the majority of contaminant removal (>80%) again occurred biotically within the aerated chambers. The sorption zone (GAC) proved to be an effective polishing step, removing any remaining contaminants to acceptable concentrations before discharge down-gradient of the SEREBAR (overall removals >95%).

A novel continuous forward algorithm for RBF neural modelling

A continuous forward algorithm (CFA) is proposed for nonlinear modelling and identification using radial basis function (RBF) neural networks. The problem considered here is simultaneous network construction and parameter optimization, well-known to be a mixed integer hard one. The proposed algorithm performs these two tasks within an integrated analytic framework, and offers two important advantages. First, the model performance can be significantly improved through continuous parameter optimization. Secondly, the neural representation can be built without generating and storing all candidate regressors, leading to significantly reduced memory usage and computational complexity. Computational complexity analysis and simulation results confirm the effectiveness.

Developments in Performance Monitoring of Concrete Exposed to Extreme Environments

The performance of the surface zone of concrete is acknowledged as a major factor governing the rate of deterioration of reinforced concrete structures as it provides the only barrier to the ingress of water containing dissolved ionic species such as chlorides which, ultimately, initiate corrosion of the reinforcement. In-situ monitoring of cover-zone concrete is therefore critical in attempting to make realistic predictions as to the in-service performance of the structure. To this end, this paper presents developments in a remote interrogation system to allow continuous, real-time monitoring of the cover-zone concrete from an office setting. Use is made of a multi-electrode array embedded within cover-zone concrete to acquire discretized electrical resistivity and temperature measurements, with both parameters monitored spatially and temporally. On-site instrumentation, which allows remote interrogation of concrete samples placed at a marine exposure site, is detailed, together with data handling and processing procedures. Site-measurements highlight the influence of temperature on electrical resistivity and an Arrhenius-based temperature correction protocol is developed using on-site measurements to standardize resistivity data to a reference temperature; this is an advancement over the use of laboratory-based procedures. The testing methodology and interrogation system represents a robust, low-cost and high-value technique which could be deployed for intelligent monitoring of reinforced concrete structures.

Catalytic performance of sheet-like Fe/ZSM-5 zeolites for the selective oxidation of benzene with nitrous oxide

Hierarchical Fe/ZSM-5 zeolites were synthesized with a diquaternary ammonium surfactant containing a hydrophobic tail and extensively characterized by XRD, Ar porosimetry, TEM, DRUV-Vis, and UV-Raman spectroscopy. Their catalytic activities in catalytic decomposition of NO and the oxidation of benzene to phenol with NO as the oxidant were also determined. The hierarchical zeolites consist of thin sheets limited in growth in the b-direction (along the straight channels of the MFI network) and exhibit similar high hydrothermal stability as a reference Fe/ZSM-5 zeolite. Spectroscopic and catalytic investigations point to subtle differences in the extent of Fe agglomeration with the sheet-like zeolites having a higher proportion of isolated Fe centers than the reference zeolite. As a consequence, these zeolites have a somewhat lower activity in catalytic NO decomposition (catalyzed by oligomeric Fe), but display higher activity in benzene oxidation (catalyzed by monomeric Fe). The sheet-like zeolites deactivate much slower than bulk Fe/ZSM-5, which is attributed to the much lower probability of secondary reactions of phenol in the short straight channels of the sheets. The deactivation rate decreases with decreasing Fe content of the Fe/ZSM-5 nanosheets. It is found that carbonaceous materials are mainly deposited in the mesopores between the nanosheets and much less so in the micropores. This contrasts the strong decrease in the micropore volume of bulk Fe/ZSM-5 due to rapid clogging of the continuous micropore network. The formation of coke deposits is limited in the nanosheet zeolites because of the short molecular trafficking distances. It is argued that at high Si/Fe content, coke deposits mainly form on the external surface of the nanosheets. © 2012 Elsevier Inc. All rights reserved.

Effect of feed space allowance and period of access to food on dairy cow performance

Two experiments were conducted to examine the ‘long-term’ effect of feed space allowance and period of access to feed on dairy cow performance. In Experiment 1, three horizontal feed space allowances (20, 40 and 60 cm cow−1) were examined over a 127-d period (14 cows per treatment). In Experiment 2, 48 dairy cows were used in a continuous design (10-week duration) 2 × 2 factorial design experiment comprising two horizontal feed space allowances (15 and 40 cm cow−1), and two periods of access to feed (unrestricted and restricted). With the former, uneaten feed was removed at 08·00 h, while feeding took place at 09·00 h. With the latter, uneaten feed was removed at 06·00 h, while feeding was delayed until 12·00 h. Mean total dry-matter (DM) intakes were 19·0, 18·7 and 19·3 kg cow−1 d−1 with the 20, 40 and 60 cm cow−1 treatments in Experiment 1, and 18·1 and 18·2 kg cow−1 d−1 with the ‘restricted feeding time’ treatments, and 17·8 and 18·1 kg d−1 with the ‘unrestricted feeding time’ treatments (15 and 40 cm respectively) in Experiment 2. None of milk yield, milk composition, or end-of-study live weight or condition score were significantly affected by treatment in either experiment (P > 0·05), while fat + protein yield was reduced with the 15-cm treatment in Experiment 2 (P < 0·05). When access to feed was restricted by space or time constraints, cows modified their time budgets and increased their rates of intake.

Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data

The main objective of this work was to develop a novel dimensionality reduction technique as a part of an integrated pattern recognition solution capable of identifying adulterants such as hazelnut oil in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points. The maintenance of the continuous structure of the data manifold enables the better visualisation of this examined classification problem and facilitates the more accurate utilisation of the manifold for detecting the adulterants. The performance of the proposed technique is validated with two different spectroscopic techniques (Raman and Fourier transform infrared, FT-IR). In all cases studied, CLPP accompanied by k-Nearest Neighbors (kNN) algorithm was found to outperform any other state-of-the-art pattern recognition techniques.