Photodegradation,Photocatalytic, and Aerobic Biodegradation of Sulfisomidine and Identification of Transformation Products by LC–UV‐MS/MS

Much attention has recently been devoted to the fate and effects of pharmaceuticals in the water cycle. Removal of antibiotics in effluents by photo‐treatment or biodegradation is a topic currently under discussion. Degradation and removal efficiencies of sulfisomidine (SUI) by photodegradation and aerobic biodegradability were studied. SUI behavior was monitored during photolysis and photocatalysis (catalyst titanium dioxide) using 150‐W medium‐pressure Hg lamp. Also an aerobic bacterial degradation test from the OECD series (closed bottle test (CBT, OECD 301 D)) was performed. The primary elimination of SUI was monitored. Structures of photo‐degradation products were assessed by chromatographic separation on a C18 column with ultraviolet detection at 270 nm and ion trap MS. The results demonstrate that SUI is not readily biodegradable in CBT. Photo catalysis was more is effective than photolysis. SUI underwent photodegradation and several SUI photoproducts were identified. Accordingly, the photodegradation pathway of SUI was postulated. When reaching the aquatic environment, SUI and its photo products can constitute a risk to the environment.     

Soil organic carbon pools in particle-size fractions as affected by slope gradient and land use change in hilly regions, western Iran

This study was conducted to explore the effects of topography and land use changes on particulate organic carbon(POC),particulate total nitrogen(PTN),organic carbon(OC) and total nitrogen(TN) associated with different size primary particle fractions in hilly regions of western Iran.Three popular land uses in the selected site including natural forest(NF),disturbed forest(DF) and cultivated land(CL) and three slope gradients(0-10 %,S1,10-30 %,S2,and 30-50%,S3) were employed as the basis of soil sampling.A total of 99 soil samples were taken from the 0-10 cm surface layer in the whole studied hilly region studied.The results showed that the POC in the forest land use in all slope gradients was considerably more than the deforested and cultivated lands and the highest value was observed at NF-S1 treatment with 9.13%.The values of PTN were significantly higher in the forest land use and in the down slopes(0.5%) than in the deforested and cultivated counterparts and steep slopes(0.09%) except for the CL land use.The C:N ratios in POC fraction were around 17-18 in the forest land and around 23 in the cultivated land.In forest land,the silt-associated OC was highest among the primary particles.The enrichment factor of SOC,EC,was the highest for POC.For the primary particles,EC of both primary fractions of silt and clay showed following trend for selected land uses and slope gradients:CL> DF> NF and S3 > S2> S1.Slope gradient of landscape significantly affected the OC and TN contents associated with the silt and clay particles,whereas higher OC and TN contents were observed in lower positions and the lowest value was measured in the steep slopes.Overall,the results showed that native forest land improves soil organic carbon storage and can reduce the carbon emission and soil erosion especially in the mountainous regions with high rainfall in west of Iran.     

Distribution of radioactive pollution of 238U, 232Th, 40K and 137Cs in northwestern coasts of Persian Gulf, Iran

A reconnaissance study has been made of the distribution of 238U, 232Th, 40K and 137Cs and geochemical features in soils and sediments samples at various locations in the northwestern coast of Persian Gulf. Activity concentration levels due to radionuclides were measured in 30 soil and sediment samples collected from this region. From the measured spectra, activity concentrations were determined for 40K (range from 146 to 500 Bq kg(-1)), 137Cs (from 5 to 20 Bq kg(-1)), 238U (from 21 to 65 Bq kg(-1)) and 232Th (from 15 to 45 Bq kg(-1)) with lowest limit detection (LLD) of 68, 3.2, 4.3 and 4.3 Bq kg(-1), respectively. The dose rate from ambient air at the soil ranges was between 19 and 58 nGy h(-1) with an average of 37.41+/-9.66 nGy h(-1).     

Operational performance of current synthetic aperture radar sensors in mapping soil surface characteristics in agricultural environments: application to hydrological and erosion modelling

Synthetic aperture radar (SAR) sensors are often used to characterize the surface of bare soils in agricultural environments. They enable the soil moisture and roughness to be estimated with constraints linked to the configurations of the sensors (polarization, incidence angle and radar wavelength). These key soil characteristics are necessary for different applications, such as hydrology and risk prediction. This article reviews the potential of currently operational SAR sensors and those planned for the near future to characterize soil surface as a function of users' needs. It details what it is possible to achieve in terms of mapping soil moisture and roughness by specifying optimal radar configurations and the precision associated with the estimation of soil surface characteristics. The summary carried out for the present article shows that mapping soil moisture is optimal with SAR sensors at low incidence angles (<35 ). This configuration, which enables an estimated moisture accuracy greater than 6% is possible several times a month taking into account all the current and future sensors. Concerning soil roughness, it is best mapped using three classes (smooth, moderately rough, and rough). Such mapping requires high‐incidence data, which is possible with certain current sensors (RADARSAT‐1 and ASAR both in band C). When L‐band sensors (ALOS) become available, this mapping accuracy should improve because the sensitivity of the radar signal to Soil Surface Characteristics (SSC) increases with wavelength. Finally, the polarimetric mode of certain imminent sensors (ALOS, RADARSAT‐2, TerraSAR‐X, etc.), and the possibility of acquiring data at very high spatial resolution (metre scale), offer great potential in terms of improving the quality of SSC mapping. Copyright © 2007 John Wiley & Sons, Ltd.     

Saturation effect on electrical properties of hematitic sandstone in the audio frequency range using non-polarizing electrodes

This paper is devoted to study the effect of saturation, with distilled water, on AC electrical conductivity and dielectric constant of a fully and partially saturated hematitic sandstone sample (Aswan area, Egypt). The saturation of the sample was changed from full saturation to partial saturation by air drying. Complex resistivity measurements at room temperature (∼16° C) were performed in the frequency range from 10 Hz to 100 kHz. We used non-polarizing Cu/CuSO₄ gel electrodes. Experimental electrical spectra indicate, generally, that the electrical conductivity and dielectric constant vary strongly with water saturation and frequency. The low-frequency electrical conductivity and dielectric constant are supposed to be mainly controlled by surface conduction and polarization of the electrical double layer. Power law behaviours with frequency were noticed. The change in electrical conductivity and dielectric constant with increasing water content is fast at low saturations and slow at high saturations. The behaviour of the electrical conductivity and dielectric constant, with increasing water content, was argued to be the orientational polarization of bound water for very low saturations, displacement of the excess surface charges for relatively low saturations and free exchange of excess ions in double layer with the bulk electrolyte and generation of transient diffusional potentials, which lag behind the applied field for high saturations in addition to membrane polarization on clay and at inter-grain and grain surface water throats having selective charge transport properties. Also, from the data a semi-percolation behaviour was found that has a peak of dielectric constant at a certain concentration and an abrupt change in conductivity at another saturation.     

Application of GA in optimization of pore network models generated by multi-cellular growth algorithms

In pore network modeling, the void space of a rock sample is represented at the microscopic scale by a network of pores connected by throats. Construction of a reasonable representation of the geometry and topology of the pore space will lead to a reliable prediction of the properties of porous media. Recently, the theory of multi-cellular growth (or L-systems) has been used as a flexible tool for generation of pore network models which do not require any special information such as 2D SEM or 3D pore space images. In general, the networks generated by this method are irregular pore network models which are inherently closer to the complicated nature of the porous media rather than regular lattice networks. In this approach, the construction process is controlled only by the production rules that govern the development process of the network. In this study, genetic algorithm has been used to obtain the optimum values of the uncertain parameters of these production rules to build an appropriate irregular lattice network capable of the prediction of both static and hydraulic information of the target porous medium.     

Evaluation of total load sediment transport formulas using ANN

The calculated results from various sediment transport formulas often differ from each other and from measured data. Some parameters in the sediment transport formulas are more effective than others to estimate total sediment load. In this study, an Artificial Neural Network （ANN） model is trained using four dominant parameters of sediment transport formulas. ANN models are able to reveal hidden laws of natural phenomena such as sediment transport process. The results of ANN and some total bed material load sediment transport formulas have been compared to indicate the importance of variables which can be used in developing sediment transport formulas. To train ANN, average flow velocity, water surface slopes, average flow depth, and median particle diameter are used as dominant parameters to estimate total bed material load. Two hundreds and fifty samples are used to train the ANN model. Twenty-four sets of field data not used in the training nor calibration of ANN are used to compare or verify the accuracy of ANN and some well-known total bed material load formulas. The test results show that the ANN model developed in this study using minimum number of dominant factors is a reliable and uncomplicated method to predict total sediment transport rate or total bed material load transport rate. Results show that the accuracy of formulas in descending order are those by Yang （1973）, Laursen （1958）, Engelund and Hansen （1972）, Ackers and White （1973）, and Toffaleti （1969）. These results are similar to those made by ASCE （1982） based on laboratory and field data not used in this paper. Study results also show that the formulas based on physical laws of sediment transport, like those formulas that were developed based on power concept, are more accurate than other formulas for estimating total bed material sediment load in rivers.     

Bacterial flora and antibiotic resistance from eggs of green turtles Chelonia mydas: An indication of polluted effluents

Sea turtles migrate to various habitats where they can be exposed to different pollutants. Bacteria were collected from turtle eggs and their resistance to antibiotics was used as pollutant bio-indicators of contaminated effluents. Eggs were collected randomly from turtles when they were laying their eggs. A total of 90 eggs were collected and placed into sterile plastic bags (3 eggs/turtle) during June-December of 2003. The bacteria located in the eggshell, albumen and yolk were examined, and 42% of the eggs were contaminated with 10 genera of bacteria. Pseudomonas spp. were the most frequent isolates. The albumen was found to be the part of the egg to be the least contaminated by bacterial infection. Bacterial isolates tested with 14 antibiotics showed variations in resistance. Resistance to ampicillin was the highest. The presence of antibiotic resistant bacteria in eggs indicates that the green turtle populations were subjected to polluted effluents during some of their migratory routes and feeding habitats. Scanning electron microscopy revealed that Salmonella typhimurium penetrated all eggshell layers.     

The selection of corrosion prior distributions for risk based integrity modeling

The deterioration of the condition of process plants assets has a major negative impact on the safety of its operation. Risk based integrity modeling provides a methodology to quantify the risks posed by an aging asset. This provides a means for the protection of human life, financial investment and the environmental damage from the consequences of its failures. This methodology is based on modeling the uncertainty in material degradations using probability distributions, known as priors. Using Bayes theorem, one may improve the prior distribution to obtain a posterior distribution using actual inspection data. Although the choice of priors is often subjective, a rational consensus can be achieved by judgmental studies and analyzing the generic data from the same or similar installations. The first part of this paper presents a framework for a risk based integrity modeling. This includes a methodology to select the prior distributions for the various types of corrosion degradation mechanisms, namely, the uniform, localized and erosion corrosion. Several statistical tests were conducted based on the data extracted from the literature to check which of the prior distributions follows data the best. Once the underlying distribution has been confirmed, one can estimate the parameters of the distributions. In the second part, the selected priors are tested and validated using actual plant inspection data obtained from existing assets in operation. It is found that uniform corrosion can be best described using 3P-Weibull and 3P-Lognormal distributions. Localized corrosion can be best described using Type1 extreme value and 3P-Weibull, while erosion corrosion can best be described using the 3P-Weibull, Type1 extreme value, or 3P-Lognormal distributions.     

Study of near bed stochastic turbulence and sediment entrainment over the ripples at the bed of open channel using image processing technique

In this study, the coherent structure in near bed bursting events over the ripples and mechanism of sediment bed load transport were investigated experimentally. The experiments in this study were carried out in the laboratory flume, in two parts; fixed bed ripple and mobile bed ripple. Tow artificial ripples, were built and used for making both fixed and mobile bed. For the fixed bed part, velocity fluctuations were measured using an Acoustic Doppler Velocimeter. In order to apply bursting analysis for obtained data, a computer program was written in visual basic language. Then, variation of turbulence shear stress associated with different bed form geometries was determined and mechanism of sediment transport by ripple shape at the bed of open channel was investigated. For the mobile bed part, artificial ripples were used as mould to make ripples. An image processing technique was used to record amount of sediment particles which are entrained and deposited over the same selected points at the fixed bed part. Results of mobile bed part, confirmed the results of shear stress analysis of fixed bed part.