Assessment of advective–dispersive contaminant transport in heterogeneous aquifers using a meshless method

Groundwater solute transport phenomena typically occur in water-bearing zones with heterogeneous solute dispersive characteristics and/or media hydraulic properties. A radial basis function collocation method (RBFCM)-based numerical method was developed in order to investigate the ability of RBFCM to accurately portray solute transport phenomena under heterogeneous conditions. Simulations were performed for 1-D and 2-D transport scenarios in which scale-dependent dispersivity fields were taken into consideration and compared with available analytical solutions. Different radial basis functions (RBFs) were employed for assessing the sensitivity of the present method on the selected RBFs. The simulation results were also compared with the results of MT3DMS which is a modular three-dimensional transport model with alternative solution schemes including the method of characteristics, the implicit central finite difference and the third order total variation diminishing finite volume. The proposed model was also used to simulate a real case condition where solute transport through a two-layer soil medium had been investigated experimentally. The results showed that RBFCM represented a powerful tool for predicting the solute transport occurrence under heterogeneous conditions with high accuracy.     

Direct interpretation of magnetotelluric sounding data based on the frequency-normalized impedance function

An important aspect of any non-linear inversion method is the generation of a suitable or good initial model as this controls the rate of convergence and accuracy of the result. To overcome the problem, a numerical method is presented for direct interpretation of magnetotelluric sounding data based on the frequency-normalized impedance (FNI) function. The expressions used to calculate the parameters are developed, first for a two-layer case under the assumption that deeper layers do not contribute to the early part of the FNI curve, and they are then generalized for an n -layer situation. The parameters of the first layer are computed by using successive sample values and the final estimate is obtained from the arithmetic mean of selected values by excluding unacceptable results in the logarithmic space. The top layer is then removed using a reduction equation. The repetition of the procedure on successive branches of the FNI function gives successive layer parameters, the resistivity of the substratum being obtained at the final step, when the reduction equation becomes equal to the square root of that resistivity.   The proposed method can be used as a complementary method for iterative inversion as it creates an initial guess which is close to the optimal solution. The solution produced by the direct interpretation may also be modified by the interpreter to incorporate prior geological information before being input to iterative interpretation schemes.     

Chromatographic Separation and Analytic Procedure for Priority Organic Pollutants in Urban Air

A separation procedure was developed for analysis of polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides (OCPs) in urban air, while simultaneously eliminating the interfering compounds. This was carried out by optimization of a column chromatograph with regard to the eluent type (n‐hexane and n‐pentane), volume of eluent, type of sorbent material (silica gel and florisil) and activation level of the sorbent material. The determination of the level of PCBs and PAHs was carried out using gas chromatography (GC) equipped with a mass selective detector (MSD), while determination of the OCPs was carried out by GC equipped with an electron capture detector (μ‐ECD). The use of a silica gel column (10 g, 5% deactivated with H₂O) with 70 mL of n‐hexane gave satisfactory separation of PCBs from PAHs and OCPs. After collecting the PCBs with 70 mL of n‐hexane, 3·20 mL of n‐hexane:ethyl acetate, (1:1, v:v) was adequate for elution of the PAHs and OCPs from the column. The primary aim of this study was to develop a multimethod for analyses of PCBs, PAHs, and OCPs in urban air as well as reducing solvent and sorbent consumption and analysis time during the clean‐up procedure compared to the US EPA standard methods (EPA methods TO‐13A for PAHs and TO‐4A for both PCBs and OCPs).     

Two-dimensional joint inversion of radiomagnetotelluric and direct current resistivity data

An algorithm for the two-dimensional (2D) joint inversion of radiomagnetotelluric and direct current resistivity data was developed. This algorithm can be used for the 2D inversion of apparent resistivity data sets collected by multi-electrode direct current resistivity systems for various classical electrode arrays (Wenner, Schlumberger, dipole-diplole, pole-dipole) and radiomagnetotelluric measurements jointly. We use a finite difference technique to solve the Helmoltz and Poisson equations for radiomagnetotelluric and direct current resistivity methods respectively. A regularized inversion with a smoothness constrained stabilizer was employed to invert both data sets. The radiomagnetotelluric method is not particularly sensitive when attempting to resolve near-surface resistivity blocks because it uses a limited range of frequencies. On the other hand, the direct current resistivity method can resolve these near-surface blocks with relatively greater accuracy. Initially, individual and joint inversions of synthetic radiomagnetotelluric and direct current resistivity data were compared and we demonstrated that the joint inversion result based on this synthetic data simulates the real model more accurately than the inversion results of each individual method. The developed 2D joint inversion algorithm was also applied on a field data set observed across an active fault located close to the city of Kerpen in Germany. The location and depth of this fault were successfully determined by the 2D joint inversion of the radiomagnetotelluric and direct current resistivity data. This inversion result from the field data further validated the synthetic data inversion results.