Characterisation of humidity dependence of a metal oxide semiconductor (MOS) sensor array using Partial Least Squares (PLS)

Metal oxide semiconductor (MOS) sensors are a class of chemical sensor that have potential for being a practical core sensor module for an electronic nose system in various environmental monitoring applications. However, the responses of these sensors may be affected by changes in humidity and this must be taken into consideration when developing calibration models. This paper characterises the humidity dependence of a sensor array which consists of 12 MOS sensors. The results were used to develop calibration models using partial least squares. Effects of humidity on the response of the sensor array and predictive ability of partial least squares are discussed. It is shown that partial least squares can provide proper calibration models to compensate for effects caused by changes in humidity.

Characterisation of humidity dependence of a metal oxide semiconductor sensor array using partial least squares

Metal oxide semiconductor (MOS) sensors are a class of chemical sensors that have potential for being a practical core sensor module for an electronic nose system in various environmental monitoring applications. However, the responses of these sensors may be affected by changes in humidity and this must be taken into consideration when developing calibration models. This paper characterises the humidity dependence of a sensor array which consists of 12 MOS sensors. The results were used to develop calibration models using partial least squares (PLS). Effects of humidity on the response of the sensor array and predictive ability of partial least squares are discussed. It is shown that partial least squares can provide proper calibration models to compensate for effects caused by changes in humidity. Special Issue: Selected Paper from the 12th International Symposium on Olfaction and Electronic Noses - ISOEN 2007, International Symposium on Olfaction and Electronic Noses.

Process studies of odour emissions from effluent ponds using machine-based odour measurement

Replicable experimental studies using a novel experimental facility and a machine-based odour quantification technique were conducted to demonstrate the relationship between odour emission rates and pond loading rates. The odour quantification technique consisted of an electronic nose, AromaScan A32S, and an artificial neural network. Odour concentrations determined by olfactometry were used along with the AromaScan responses to train the artificial neural network. The trained network was able to predict the odour emission rates for the test data with a correlation coefficient of 0.98. Time averaged odour emission rates predicted by the machine-based odour quantification technique, were strongly correlated with volatile solids loading rate, demonstrating the increased magnitude of emissions from a heavily loaded effluent pond. However, it was not possible to obtain the same relationship between volatile solids loading rates and odour emission rates from the individual data. It is concluded that taking a limited number of odour samples over a short period is unlikely to provide a representative rate of odour emissions from an effluent pond. A continuous odour monitoring instrument will be required for that more demanding task.

Odour emissions from anaerobic piggery ponds. 2: Improving estimates of emission rate through recognition of spatial variability

Odour emission rates were measured for seven different anaerobic ponds treating piggery wastes at six to nine discrete locations across the surface of each pond on each sampling occasion over a thirteen month period. Significant variability in emission rates were observed for each pond. Measurement of a number of water quality variables in pond liquor samples collected at the same time and from the same locations as the odour samples indicated that the composition of the pond liquor was also variable. The results indicated that spatial variability was a real phenomenon and could have a significant impact on odour assessment practices. Considerably more odour samples would be required to characterise pond emissions than currently recommended by most practitioners, or regulatory agencies.

Odour emissions from anaerobic piggery ponds. 1. Results of a three season, 14-month survey

Odour emission rates were measured for seven different anaerobic ponds treating piggery wastes at six to nine discrete locations across the surface of each pond on each sampling occasion over a 14-month period. Emission rate values varied between ponds, between seasons for the same pond and even for the same pond on different days of a sampling week. Average seasonal emission rates ranged from 7.9 to 46.5 OU/m2 s, while average emission rates ranged from 16.0 to 29.0 OU/m2 s. Factors potentially responsible for the variability in emission rates were investigated, including air and pond liquor temperatures, time of day of sample collection, season and the impact of a prolonged drought.

Noble Metal Ionic Catalysts

Because of growing environmental concerns and increasingly stringent regulations governing auto emissions, new more efficient exhaust catalysts are needed to reduce the amount of pollutants released from internal combustion engines. To accomplish this goal, the major pollutants in exhaust-CO, NOx, and unburned hydrocarbons-need to be fully converted to CO2, N-2, and H2O. Most exhaust catalysts contain nanocrystalline noble metals (Pt, Pd, Rh) dispersed on oxide supports such as Al2O3 or SiO2 promoted by CeO2. However, in conventional catalysts, only the surface atoms of the noble metal particles serve as adsorption sites, and even in 4-6 nm metal particles, only 1/4 to 1/5 of the total noble metal atoms are utilized for catalytic conversion. The complete dispersion of noble metals can be achieved only as ions within an oxide support. In this Account, we describe a novel solution to this dispersion problem: a new solution combustion method for synthesizing dispersed noble metal ionic catalysts. We have synthesized nanocrystalline, single-phase Ce1-xMxO2-delta and Ce1-x-yTiyMxO2-delta (M = Pt, Pd, Rh; x = 0,01-0.02, delta approximate to x, y = 0.15-0.25) oxides in fluorite structure, In these oxide catalysts, pt(2+), Pd2+, or Rh3+ ions are substituted only to the extent of 1-2% of Ce4+ ion. Lower-valent noble metal ion substitution in CeO2 creates oxygen vacancies. Reducing molecules (CO, H-2, NH3) are adsorbed onto electron-deficient noble metal ions, while oxidizing (02, NO) molecules are absorbed onto electron-rich oxide ion vacancy sites. The rates of CO and hydrocarbon oxidation and NOx reduction (with >80% N-2 selectivity) are 15-30 times higher in the presence of these ionic catalysts than when the same amount of noble metal loaded on an oxide support is used. Catalysts with palladium ion dispersed in CeO2 or Ce1-xTixO2 were far superior to Pt or Rh ionic catalysts. Therefore, we have demonstrated that the more expensive Pt and Rh metals are not necessary in exhaust catalysts. We have also grown these nanocrystalline ionic catalysts on ceramic cordierite and have reproduced the results we observed in powder material on the honeycomb catalytic converter. Oxygen in a CeO2 lattice is activated by the substitution of Ti ion, as well as noble metal ions. Because this substitution creates longer Ti-O and M-O bonds relative to the average Ce-O bond within the lattice, the materials facilitate high oxygen storage and release. The interaction among M-0/Mn+, Ce4+/Ce3+, and Ti4+/Ti3+ redox couples leads to the promoting action of CeO2, activation of lattice oxygen and high oxygen storage capacity, metal support interaction, and high rates of catalytic activity in exhaust catalysis.

Non-specific conducting polymer-based array capable of monitoring odour emissions from a biofiltration system in a piggery building

A commercial non-specific gas sensor array system was evaluated in terms of its capability to monitor the odour abatement performance of a biofiltration system developed for treating emissions from a commercial piggery building. The biofiltration system was a modular system comprising an inlet ducting system, humidifier and closed-bed biofilter. It also included a gravimetric moisture monitoring and water application system for precise control of moisture content of an organic woodchip medium. Principal component analysis (PCA) of the sensor array measurements indicated that the biofilter outlet air was significantly different to both inlet air of the system and post-humidifier air. Data pre-processing techniques including normalising and outlier handling were applied to improve the odour discrimination performance of the non-specific gas sensor array. To develop an odour quantification model using the sensor array responses of the non-specific sensor array, PCA regression, artificial neural network (ANN) and partial least squares (PLS) modelling techniques were applied. The correlation coefficient (r(2)) values of the PCA, ANN, and PLS models were 0.44, 0.62 and 0.79, respectively.

Study of surface acidity of oxide catalysts by photoacoustic spectroscopy

Photoacoustic spectroscopy has been employed to estimate quantitatively the acid sites on oxide catalysts. The technique involves the measurement of the ratio of intensities of absorption bands due to conjugate bases and acids of indicators adsorbed on the catalyst surface as a function of the amount of added n-butylamine. Basic sites in sodium-impregnated alumina samples have been examined by adsorbing phenolphthalein on these surfaces.

NMR spectrum of pyridine-N-oxide in a thermotropic nematic phase

Absract is not available.

Cuprous oxide catalyzed air oxidation of thiosulfate and tetrathionate

Thiosulfate (S2O32−) and tetrathionate (S4O62−)are oxidized to sulfate by air at atmospheric pressure and 50–70°C in the presence of cuprous oxide (Cu2O) as catalyst. Sulfate is produced from S2O32− by series-parallel reaction paths involving S4O62− as an intermediate. The rate data obtained for air oxidation of S2O32− on Cu2O agree well with a pseudo-homogeneous first order kinetic scheme, yielding values of rate constants for series parallel reaction paths which have been used in modelling the catalyzed air oxidation of S2O32−. Air oxidation of S4O62− on Cu2O proceeds at a higher rate in the presence of S2O32− than in its absence. Cu2O is less active than Cu2S for the air oxidation of S2O32−, as shown by the rate constant values which for Cu2O catalyzed oxidation are an order of magnitude smaller than those for the Cu2S catalyzed oxidation.

Odour emissions from tunnel-ventilated broiler sheds: case study of nine Queensland farms.

Odour emission rates were measured from nine tunnel-ventilated broiler farms in south-eastern Queensland, Australia. At one farm, odour emission rates were measured over two sequential batches approximately weekly, while at the remaining farms, odour emission rates were measured just before the first pickup (around Day 35 of the batch) when bird liveweight was greatest and peak odour emission rates were expected. Odour samples were analysed using dynamic olfactometry (to AS/NZS 4323.3:2001), and an artificial olfaction system was used to continuously monitor odour emission rates at one farm. Odour emission rates ranged from 330 to 2960 ou/s per 1000 birds and from 0.19 to 2.12 ou/s.kg, with a significant amount of variability observed throughout the batch and throughout each sampling day. While the wide range in odour emission rates was primarily due to changes in bird liveweight and ventilation requirements, other factors were also involved. The artificial olfaction system proved useful for quantifying the range and variability of odour emission rates, especially when olfactometry analysis was impractical.

A novel combustion process for the synthesis of fine particle α-alumina and related oxide materials

Synthesis of fine particle α-alumina and related oxide materials such as MgAl2O4, CaAl2O4, Y3Al5O12 (YAG), Image , β′-alumina, LaAlO3 and ruby powder (Image ) has been achieved at low temperatures (500°C) by the combustion of corresponding metal nitrate-urea mixtures. Solid combustion products have been identified by their characteristic X-ray diffraction patterns. The fine particle nature of α-alumina and related oxide materials has been investigated using SEM, TEM, particle size analysis and surface area measurements.