Effects of Different Retention Parameter Estimation Methods on the Prediction of Surface Runoff Using the SCS Curve Number Method

Quantifying different hydrological components is an initial step for sustainable water resources planning and management. One rising concern is the conflict between the environment, hydropower and agriculture mainly in lowland areas where a large share of the base flows need to be abstracted. The Soil and Water Assessment Tool (SWAT) model was used to understand the hydrological processes of the Upper Awash River Basin with the emphasis on analyzing the different options for surface runoff generation using the Soil Conservation Service (SCS) Curve Number (CN) method. In this study, SWAT was applied incorporating two methods for estimating the retention parameter (S) for the SCS-CN method. The first allowed S to vary with soil profile moisture content (SM method) and the second allowed S to vary with accumulated plant evapotranspiration (PT method). Hydrograph comparison indicated that the PT method was better in simulating peak flows while the SM method was better in simulating the low flows. While the predicted stream flow hydrographs showed an agreement between the two methods, the simulated annual water balance indicated a disagreement in quantifying the different hydrological components. After evapotranspiration, base flow was the dominant component simulated in the SM method whereas surface runoff was the foremost in the PT method simulation. The analysis indicated that care must be taken when selecting an appropriate tool for quantifying hydrologic system to be used for decision making especially for un-gauged catchments where validation of model results is not possible.     

Artificial Neural Network modeling of a hydrogen dual fueled diesel engine characteristics: An experiment approach

The rapid growth of vehicular pollution; mostly running on the diesel engine, emissions emerging are the concerns of the day. Owing to clean burn characteristics features, Hydrogen (H₂) as a fuel is the paradigm of the researcher. Extensive research presented in the literature on H₂ dual fueled diesel engine reveals, the significant role of H₂ in reducing emissions and enhancing the performance of a dual fueled diesel engine. With meager qualitative experiment data, the feasibility to develop an efficient Artificial Neural Network (ANN) model is investigated, the developed model can be utilized as a tool to investigate the H₂ dual fueled diesel engine further. In the process of developing an ANN model, engine load and H₂ flow rate are varied to register performance and emission characteristics. The creditability of the experiment is ascertained with uncertainty analysis of measurable and computed parameters. Leave-out-one method is adopted with 16 data sets; seven training algorithms are explored with eight transfer function combinations to evolve a competent ANN model. The efficacy of the developed model is adjudged with standard benchmark statistic indices. ANN model trained with Broyden, Fletcher, Goldfarb, & Shanno (BFGS) quasi-Newton backpropagation (trainbfg) stand out the best among other algorithms with regression coefficient ranging between 0.9869 and 0.9996.     

Inversion with regularization for the retrieval of tropospheric aerosol parameters from multiwavelength lidar sounding

We present an inversion algorithm for the retrieval of particle size distribution parameters, i.e., mean (effective) radius, number, surface area, and volume concentration, and complex refractive index from multiwavelength lidar data. In contrast to the classical Tikhonov method, which accepts only that solution for which the discrepancy reaches its global minimum, in our algorithm we perform the averaging of solutions in the vicinity of this minimum. This averaging stabilizes the underlying ill-posed inverse problem, particularly with respect to the retrieval of number concentration. Results show that, for typical tropospheric particles and 10% error in the optical data, the mean radius could be retrieved to better than 20% from a lidar on the basis of a Nd:YAG laser, which provides a combination of backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm. The accuracy is improved if the lidar is also equipped with a hydrogen Raman shifter. In this case two additional backscatter coefficients at 416 and 683 nm are available. The combination of two extinction coefficients and five backscatter coefficients then allows one to retrieve not only averaged aerosol parameters but also the size distribution function. There was acceptable agreement between physical particle properties obtained from the evaluation of multiwavelength lidar data taken during the Lindenberg Aerosol Characterization Experiment in 1998 (LACE 98) and in situ data, which were taken aboard aircraft.     

Polychlorinated naphthalenes in Swedish background air

Polychlorinated naphthalenes (PCNs) with four to eight chlorines were studied in air collected at two background stations in Sweden, one southerly and one northerly. Air was sampled with a high-volume sampler, and gas-phase adsorbents and filters were analyzed separately. The sum of TeCNs to HxCNs in the gaseous phase ranged between 1 and 10 pg/m3 with significantly higher concentrations at the southern location Hoburgen. HpCNs and OCN were below the detection limit. The highest concentrations were found in two samples from Hoburgen with the air masses coming from SW and W and during warm weather (+11 degrees C). The lowest concentration was found in a sample from the northern location Ammarn?s at cold weather (-22 degrees C) when the air came from the east. A correlation was found between logP and 1/T indicating that temperature has a larger effect than location on the concentration in the gas phase. The TeCNs constituted 50-75% in the gaseous phase. In most filter samples TeCNs and PeCNs were below the limit of quantitation. PUF samples with air trajectories from W to NE had relatively higher concentrations of late eluting TeCNs and PeCNs, while in samples with winds from SE to S the early eluting congeners dominated. Samples with early eluting congeners were mainly collected at lower temperature. TriCNs constituted the dominant homologue group both in the gaseous and particulate phase of air samples as well as in bulk deposition from a rural monitoring station south of Stockholm. The octanol-air partition coefficient described the gas/particle interaction well for samples collected at temperatures down to -8 degrees C.     

Direct electron transfer of cytochrome P450 2B4 at electrodes modified with nonionic detergent and colloidal clay nanoparticles

A method for construction of biosensors with membranous cytochrome P450 isoenzymes was developed based on clay/detergent/protein mixed films. Thin films of sodium montmorillonite colloid with incorporated cytochrome P450 2B4 (CYP2B4) with nonionic detergent were prepared on glassy carbon electrodes. The modified electrodes were electrochemically characterized, and bioelectrocatalytic reactions were followed. CYP2B4 can be reduced fast on clay-modified glassy carbon electrodes in the presence of the nonionic detergent Tween 80. In anaerobic solutions, reversible oxidation and reduction is obtained with a formal potential between -0.292 and -0.305 V vs Ag/AgCl 1 M KCl depending on the preparation of the biosensor. In air-saturated solution, bioelectrocatalytic reduction currents can be obtained with the CYP2B4-modified electrode on addition of typical substrates such as aminopyrine and benzphetamine. This reaction was suppressed when methyrapone, an inhibitor of P450 reactions, was present. Measurement of product formation also indicates the bioelectrocatalysis by CYP2B4.     

Aerosol lidar intercomparison in the framework of the EARLINET project. 1. Instruments

In the framework of the European Aerosol Research Lidar Network to Establish an Aerosol Climatology (EARLINET), 19 aerosol lidar systems from 11 European countries were compared. Aerosol extinction or backscatter coefficient profiles were measured by at least two systems for each comparison. Aerosol extinction coefficients were derived from Raman lidar measurements in the UV (351 or 355 nm), and aerosol backscatter profiles were calculated from pure elastic backscatter measurements at 351 or 355, 532, or 1064 nm. The results were compared for height ranges with high and low aerosol content. Some systems were additionally compared with sunphotometers and starphotometers. Predefined maximum deviations were used for quality control of the results. Lidar systems with results outside those limits could not meet the quality assurance criterion. The algorithms for deriving aerosol backscatter profiles from elastic lidar measurements were tested separately, and the results are described in Part 2 of this series of papers [Appl. Opt. 43, 977-989 (2004)]. In the end, all systems were quality assured, although some had to be modified to improve their performance. Typical deviations between aerosol backscatter profiles were 10% in the planetary boundary layer and 0.1 x 10(-6) m(-1) sr(-1) in the free troposphere.     

Cobalt-containing catalysts for the high-temperature combustion of methane

Cobalt was supported on ZrO₂, La-doped ZrO₂ and La₂O₃ through atomic layer epitaxy (ALE) and wet impregnation. The rate data obtained at 770 K is compared with literature information about cobalt inserted in other matrixes. The ALE technique using ZrO₂ and La-doped ZrO₂ yielded the best cobalt-containing catalysts. Bulk and surface characterization techniques provided key clues to understand the origin of the large difference in catalytic activity reported for cobalt-containing formulations.     

A GC–MS-based metabonomic investigation of blood serum from irritable bowel syndrome patients undergoing intervention with acidified milk products

In the present study, the use of gas chromatography mass spectrometry (GC–MS)-based metabonomics to characterize blood serum in an intervention study of patients suffering from the common gastrointestinal disorder irritable bowel syndrome (IBS) was investigated. The patients included in the study consumed an acidified milk product with (n = 30) or without probiotics (n = 31) (Lactobacillus paracasei F19, Lactobacillus acidophilus LA-5 and Bifidobacterium lactis BB-12) for an 8-week period, and blood serum samples were collected before and after the intervention. Acidified milk is commonly used as a delivering vector for probiotics in commercial consumer settings. The serum samples were extracted and derivatized using N-Methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA), and GC–MS analysis was carried out. Multivariate data analysis including principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), and S-plot was applied on the obtained GC–MS data, which revealed higher serum lactate, glutamine, proline creatinine/creatine, and aspartic acid levels and lower serum glucose levels after the intervention period for both treatment groups. Consequently, the present study indicated an effect of acidified milk consumption on the plasma metabolite profile, which was independent of a concomitant intake of probiotics. In addition, the present study demonstrates that GC–MS is a useful analytical technique for metabonomics studies of blood serum.