Extended Analytical Turbulent Diffusion Model for Particle Dispersion and Deposition in a Horizontal Pipe: Comparison with CFD Simulation

A 2D analytical turbulent diffusion model for particle dispersion and deposition at different heights along the pipe flow and circumferential deposition has been developed. This liquid–solid turbulent diffusion model presented in this paper has emanated from an existing gas–liquid turbulent diffusion model. This model can be used as a handy tool for quick estimation one and two-dimensional deposition fluxes of particles in water distribution networks. A comprehensive 3D numerical investigation has been carried out using multiphase mixture model available in “Fluent 6.2” to verify the above analytical model. Different particles sizes and densities were used for 3D numerical investigations. The deposition was studied as a function of particle diameter, density, and fluid velocity. The deposition of particles, along the periphery of the pipe wall and at different depths, was investigated. Both the models findings matched with qualitative phenomena such as deposition of heavier particles at the bottom of the pipe wall were higher at lower velocities and lower at higher velocities. The lighter particles were found mostly suspended with homogeneous distribution. Smaller particles were also suspended with marginal higher concentration near the bottom of the pipe wall. This marginal higher concentration of the smaller particles was found to be slightly pronounced for lower velocity. These analogies of particles are well discussed with the ratio between free-flight velocity and the gravitational settling velocity. Extended analytical model results were compared with the 3D computational fluid dynamics simulation results. Discrepancies in the model results were discussed.     

Application of the Morris algorithm for sensitivity analysis of the REALM model for the Goulburn irrigation system

The REALM modelling shell is widely used in Australia as a water allocation modelling tool. It has been used to develop the Goulburn System Model (GSM) of the Goulburn, Broken, Loddon and Campaspe Rivers in northeastern Victoria. REALM represents the river and irrigation system as a network of storages and carriers. The model has been optimised to best represent the water harvesting and allocation for use by water management authorities. The model is analysed to assess the sensitivity of a subset of the model outputs, to a subset of the system parameters. The New Morris algorithm uses sampling paths generated in the space of the parameters, to generate points at which the model is run (to generate the model outputs). These model runs are then used to estimate the first and second-order effects of the parameters on the outputs. The results illustrate the mild linkage of the Goulburn and Broken systems, and the Broken system also shows differences between minimum and average outflows. The Goulburn is more sensitive to some of the numerical convergence parameters used in the allocation software, while the Broken is less sensitive to these factors. The numerical convergence factors also lead to important second-order effects.     

Selection and Calibration of Numerical Modeling in Flow and Water Quality

Numerical modeling is frequently used in coastal engineering research and application. One possible issue associated with using this method however, is that initial outcomes might differ from expectation. Modeling manipulation addresses this issue by changing the initial parameters which in turn affects the final output results.The advancement of modeling techniques in recent years has seen a gradual but steady accruement of knowledge regarding the relationship between input parameters and possible outputs, which has resulted in improved accuracy and efficiency methods. The advancements within this field have predominantly occurred on an individual basis and as such lack standardisation. An expert numerical modeler may use this knowledge subconsciously, yet may not know how to convey it to the model users. This paper has been written to introduce a systematic intelligent coding schema designed to organise current coastal engineering modeling manipulation knowledge into a standardised format. This system is relevant to the development of appropriate strategies for improved accuracy and efficiency as well as model modification to simulate specific real phenomena in prototype application cases.     

Fuzzy clustering analysis in environmental impact assessment — A complement tool to environmental quality index

In spite of rapid progress achieved in the methodological research underlying environmental impact assessment (EIA), the problem of weighting various parameters has not yet been solved. This paper presents a new approach, fuzzy clustering analysis, which is illustrated with an EIA case study on Baoshan-Wusong District in Shanghai, China. Fuzzy clustering analysis may be used whenever a composite classification of environmental quality/impact incorporates multiple parameters. In such cases the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering analysis, the classification is determined by a fuzzy relation. After a fuzzy similarity matrix has been established and the fuzzy relation stabilized, a dynamic clustering chart can be developed. Given a suitable threshold, the appropriate classification can be accomplished. The methodology is relatively simple and the results can be interpreted to provide valuable information to support decision making and improve management of the environment.     

Modeling of SO<Subscript>2</Subscript> distribution in Istanbul using artificial neural networks

Urban air pollution is a growing problem in developing countries. Some compounds especially sulphur dioxide (SO₂) is considered as typical indicators of the urban air quality. Air pollution modeling and prediction have great importance in preventing the occurrence of air pollution episodes and provide sufficient time to take the necessary precautions. Recently, various stochastic image-processing algorithms such as Artificial Neural Network (ANN) are applied to environmental engineering. ANN structure employs input, hidden and output layers. Due to the complexity of the problem, as the number of input–output parameters differs, ANN model settings such as the number of neurons of these layers changes. The ability of ANN models to learn, particularly capability of handling large amounts (or sets) of data simultaneously as well as their fast response time, are invariably the characteristics desired for predictive and forecasting purposes. In this paper, ANN models have been used to predict air pollutant parameter in meteorological considerations. We have especially focused on modeling of SO₂ distribution and predicting its future concentration in Istanbul, Turkey. We have obtained data sets including meteorological variables and SO₂ concentrations from Istanbul-Florya meteorological station and Istanbul-Yenibosna air pollution station. We have preferred three-layer perceptron type of ANN which consists of 10, 22 and 1 neurons for input, hidden and output layers, respectively. All considered parameters are measured as daily mean. The input parameters are: SO₂ concentration, pressure, temperature, humidity, wind direction, wind speed, strength of sunshine, sunshine, cloudy, rainfall and output parameter is the future prediction of SO₂. To evaluate the performance of ANN model, our results are compared to classical nonlinear regression methods. The over all system finds an optimum correlation between input–output variables. Here, the correlation parameter, r is 0.999 and 0.528 for training and test data. Thus in our model, the trend of SO₂ is well estimated and seasonal effects are well represented. As a result, we conclude that ANN is one of the compromising methods in estimation of environmental complex air pollution problems.     

Selection and Calibration of Numerical Modeling in Flow and Water Quality

Numerical modeling is frequently used in coastal engineering research and application. One possible issue associated with using this method however, is that initial outcomes might differ from expectation. Modeling manipulation addresses this issue by changing the initial parameters which in turn affects the final output results. The advancement of modeling techniques in recent years has seen a gradual but steady accruement of knowledge regarding the relationship between input parameters and possible outputs, which has resulted in improved accuracy and efficiency methods. The advancements within this field have predominantly occurred on an individual basis and as such lack standardisation. An expert numerical modeler may use this knowledge subconsciously, yet may not know how to convey it to the model users. This paper has been written to introduce a systematic intelligent coding schema designed to organise current coastal engineering modeling manipulation knowledge into a standardised format. This system is relevant to the development of appropriate strategies for improved accuracy and efficiency as well as model modification to simulate specific real phenomena in prototype application cases.     

Decision support methods for the environmental assessment of contamination at mining sites

Polluting mine accidents and widespread environmental contamination associated with historic mining in Europe and elsewhere has triggered the improvement of related environmental legislation and of the environmental assessment and management methods for the mining industry. Mining has some unique features such as natural background pollution associated with natural mineral deposits, industrial activities and contamination located in the three-dimensional sub-surface space, the problem of long-term remediation after mine closure, problem of secondary contaminated areas around mine sites and abandoned mines in historic regions like Europe. These mining-specific problems require special tools to address the complexity of the environmental problems of mining-related contamination. The objective of this paper is to review and evaluate some of the decision support methods that have been developed and applied to mining contamination. In this paper, only those methods that are both efficient decision support tools and provide a ‘holistic’ approach to the complex problem as well are considered. These tools are (1) landscape ecology, (2) industrial ecology, (3) landscape geochemistry, (4) geo-environmental models, (5) environmental impact assessment, (6) environmental risk assessment, (7) material flow analysis and (8) life cycle assessment. This unique inter-disciplinary study should enable both the researcher and the practitioner to obtain broad view on the state-of-the-art of decision support methods for the environmental assessment of contamination at mine sites. Documented examples and abundant references are also provided.     

Composite use of numerical groundwater flow modeling and geoinformatics techniques for monitoring Indus Basin aquifer, Pakistan

The integration of the Geographic Information System (GIS) with groundwater modeling and satellite remote sensing capabilities has provided an efficient way of analyzing and monitoring groundwater behavior and its associated land conditions. A 3-dimensional finite element model (Feflow) has been used for regional groundwater flow modeling of Upper Chaj Doab in Indus Basin, Pakistan. The approach of using GIS techniques that partially fulfill the data requirements and define the parameters of existing hydrologic models was adopted. The numerical groundwater flow model is developed to configure the groundwater equipotential surface, hydraulic head gradient, and estimation of the groundwater budget of the aquifer. GIS is used for spatial database development, integration with a remote sensing, and numerical groundwater flow modeling capabilities. The thematic layers of soils, land use, hydrology, infrastructure, and climate were developed using GIS. The Arcview GIS software is used as additive tool to develop supportive data for numerical groundwater flow modeling and integration and presentation of image processing and modeling results. The groundwater flow model was calibrated to simulate future changes in piezometric heads from the period 2006 to 2020. Different scenarios were developed to study the impact of extreme climatic conditions (drought/flood) and variable groundwater abstraction on the regional groundwater system. The model results indicated a significant response in watertable due to external influential factors. The developed model provides an effective tool for evaluating better management options for monitoring future groundwater development in the study area.     

Numerical integration of chemical ODE problems arising in air pollution models

The numerical treatment of a regional air pollution model (such models are, as a rule, described mathematically by systems of partial differential equations) leads to the solution of very large computational problems. The chemical submodel of an air pollution model is normally the most timeconsuming part of the computational work. The application of appropriate discretization and splitting procedures reduces the chemical submodel to a large number of relatively small ODE systems (one such system per gridpoint). In the process of searching for efficient numerical algorithms for the chemical submodels one can carry out experiments by using only one such ODE system in order to facilitate the work. This approach has been used in connection with a particular chemical scheme, the condensed CBM IV scheme, which is used in several large air pollution models. Six integration algorithms have been tested on a set of typical scenarios (consisting of different starting concentrations and/or of different values of the emissions). The advantages and the disadvantages of the algorithms tested are discussed. The final decision about the most efficient algorithm, among the algorithms tested, should be made after a second series of experiments. The coupling of the chemical process with the transport of air pollution (on, at least, a twodimensional domain) together with the application of highspeed computers has to be studied in the second series of experiments, which will be performed in a subsequent paper.     

Environmental assessment of arsenic released from potential pollution sources

An assessment study of the environmental pathways of arsenic released from a coal-fired power plant (CFPP) or introduced into soil as a contaminant by phosphatic fertilizers has been carried out using a time-dependent forecasting model.The long-term predictions indicate that arsenic can be taken up by plants and that it can migrate into the groundwater system through soil layers. However, arsenic exhibits such a high degree of mobility that its retention and accumulation in biota should remain low. This fact may explain the relatively low concentrations of arsenic in environmental media as well as in groundwater systems.     

Biosorption of Pb(II) and Cr(III) from aqueous solutions: breakthrough curves and modeling studies

The sorption capacity parameters obtained for batch studies provide useful information about biosorption system. However, such data fail to explain the process under continuous-flow conditions. The present study is an attempt to explore the biosorption of Pb(II) and Cr(III) by straw from local wheat (Triticum aestivum). The biosorbent has been characterized by using Fourier transform infrared spectroscopy and surface area and elemental analyses and found to be porous and polyfunctional. S-shaped breakthrough curves were obtained at different column heights for the both metal ions. Various breakthrough parameters and saturation times have been determined. The column data have been successfully used to study the Bohart–Adams' bed depth service time (BDST) model and Yoon and Nelson's model. It was found that BDST model quite efficiently explained the whole column data whereas Yoon and Nelson model could explain it below 90 % breakthrough concentration. The predicted and calculated BDST parameters were in agreement with each other. Yoon and Nelson's constant decreased with an increase in the column height for both metal ions. Effect of change in flow rate on the Pb(II) biosorption has also been discussed with respect to BDST approach.     

Assessment of water quality of some swimming pools: a case study in Alexandria, Egypt

In spite of the importance and popularity of swimming pools in summer, they have been identified as posing some public health risks to users due to either chemical or microbiological contamination. This study was carried out aiming at assessing the quality of water for some Alexandria's swimming pools in order to determine its compliance with the Egyptian standards no. 418/1995. Five swimming pools were selected randomly from different districts. Physical and chemical parameters, as well as biological examination of a total of 30 samples, were carried out using standard analytical methods. Water samples were collected from the studied swimming pools monthly over 6?months and pool water monitoring was carried out during afternoon of the weekends when the pools were most heavily used. The results indicated overall poor compliance with the standards. Compliance of the pool water to the microbial parameters, residual chlorine, pH, and turbidity were 56.7% (17 samples), 20% (6 samples), 46.7% (14 samples), and 46.7% (14 samples), respectively. Statistical analysis showed significant association between water contamination with microbial indicators and physical–chemical aspects such as residual chlorine, temperature, turbidity, and load of swimmers. Furthermore, Cryptosporidium oocysts and Giardia lamblia cysts has been found in 10% of samples. It was concluded that there is a need to improve disinfection and cleaning procedures, with consideration given to safety, and size of the pool in relation to bathing load. There is also a need to monitor swimming pool water quality continuously, and to increase bather hygienic practices and awareness of the risks as well as training of governmental inspectors.     

Application of data envelopment analysis in environmental impact assessment of a coal washing plant: A new sustainable approach

The main problem of traditional methods of environmental impact assessment (EIA) is that in most of the existing algorithms and methods, such as Leopold, Folchi and RIAM, the main attention is to the destructive effects of the proposed plan, and the advantages of the industrial project are less noticeable. This has led to a permanent challenge between environmental organizations and industrial stakeholders. Data envelopment analysis (DEA) is a new approach of assessing the industrial units. Besides, it considers the positive economic and social impacts of the project and provides a comprehensive assessment of the industrial unit. With this approach, the environmental impacts of an industrial unit have been considered as “inputs” and its positive economic and social impacts considered as the “outputs” of the DEA models. Therefore, the problem of impact assessment changes into a DEA model. In the present study, the Alborz Sharghi Coal washing plant in northern Iran has been considered as a case study for implementing the DEA-EIA approach, and 19 plant activities and 11 environmental components have been used to evaluate the environmental effects of the plant. To solve the EIA problem, two commonly used DEA approaches, called CRS (constant returns to scale) and VRS (variable returns to scale), have been used. The DEA results identified the critical environmental components of the plant that should be considered seriously. Also, drawing the “potential improvement” diagram in the DEA method is an effective tool for determining the high risk activities of the factory and applying them in development plans. Besides, using the VRS model with maximize-output approach showed that some of the plant activities had the most differences with optimal mode and these components should be considered in future development plans. Finally, it can be concluded that, assessing the environmental impacts of the mineral industries with VRS maximize-output approach, is closer to the concept of sustainable development and cost-benefit analysis.     

Sampling and analysis for radon-222 dissolved in ground water and surface water

Radon-222 is a naturally occurring radioactive gas in the uranium-238 decay series that has traditionally been called, simply, radon. The lung cancer risks associated with the inhalation of radon decay products have been well documented by epidemiological studies on populations of uranium miners.The realization that radon is a public health hazard has raised the need for sampling and analytical guidelines for field personnel. Several sampling and analytical methods are being used to document radon concentrations in ground water and surface water worldwide but no convenient, single set of guidelines is available. Three different sampling and analytical methods-bubbler, liquid scintillation, and field screening-are discussed in this paper. The bubbler and liquid scintillation methods have high accuracy and precision, and small analytical method detection limits of 0.2 and 10 pCi/l (picocuries per liter), respectively. The field screening method generally is used as a qualitative reconnaissance tool.     

Characterization of soil contamination by lead around a former battery factory by applying an analytical hybrid method

Former battery factories have created environmental and health problems for years and the exposure to lead in surface soils has been underestimated. Nonetheless, the identification of lead contamination and its spatial distribution is crucial. The determination of heavy metals in soils can be performed using inductively coupled plasma mass spectrometry (ICP-MS). However, alternative techniques such as X-ray fluorescence (XRF) have been used lately in environmental studies since measurements can be taken in the field in a prompt manner, despite its lower accuracy. In this study, a former battery factory site in Monterrey, Mexico, has been studied in order to detect lead contamination. Soil samples were assessed for contamination by using an analytical hybrid method that comprises both analytical techniques, namely, ICP-MS and XRF. Samples were taken in 215 locations and, after a simple homogenization process, they were analyzed by using a portable XRF device. Within those 215 sampling points, 25 samples were analyzed concurrently by using ICP-MS according to international sampling guidelines. Results obtained were adjusted in order to define an analytical hybrid method, which encompasses the advantages of each technique. An improved characterization was achieved by using the proposed analytical hybrid method since maps of lead distribution and calculated areas of concern showed better predictability. The combination of spectroscopic techniques is of great applicability for environmental agencies and decision makers.     

STUMOD—a Tool for Predicting Fate and Transport of Nitrogen in Soil Treatment Units

A typical onsite wastewater treatment system consists of a septic tank and a soil treatment unit to treat wastewater before it is discharged through the vadose zone to an aquifer. A tool was developed for the purpose of predicting the fate and transport of nitrogen in soil treatment units (STUMOD or Soil Treatment Unit Model). STUMOD calculates nitrogen species concentrations and the fraction of total nitrogen reaching the aquifer or a specified soil depth. Input data include parameters for hydraulics and nutrient transport and transformation. An analytical solution is used to calculate the profile of pressure based on Darcy’s equation and the relationships between suction head, unsaturated hydraulic conductivity, and soil moisture. Chemical transport is based on simplification of the advection–dispersion equation. STUMOD is relatively simple to use but accounts for important processes such as ammonium sorption, nitrification, and denitrification. STUMOD accounts for the effect of soil moisture content (a surrogate for redox conditions) on nitrification and denitrification reactions. The model has provisions to handle the influence of temperature and organic carbon content on nitrogen transformation. Model outputs, generated based on input parameters obtained from extensive literature review, were compared to a numerical model and data from laboratory tests and field sites. Both measured data and STUMOD outputs show a relatively higher removal in clayey soils compared to sandy soils. Consistent with literature data for most soils, STUMOD predicted ammonium conversion to nitrate within the first foot below the trench infiltrative surface.     

Numerical modelling of the groundwater inflow to an advancing open pit mine: Kolahdarvazeh pit,Central Iran

The groundwater inflow into a mine during its life and after ceasing operations is one of the most important concerns of the mining industry. This paper presents a hydrogeological assessment of the Irankuh Zn-Pb mine at 20 km south of Esfahan and 1 km northeast of Abnil in west-Central Iran. During mine excavation, the upper impervious bed of a confined aquifer was broken and water at high-pressure flowed into an open pit mine associated with the Kolahdarvazeh deposit. The inflow rates were 6.7 and 1.4 m³/s at the maximum and minimum quantities, respectively. Permeability, storage coefficient, thickness and initial head of the fully saturated confined aquifer were 3.5?×?10^?4 m/s, 0.2, 30 m and 60 m, respectively. The hydraulic heads as a function of time were monitored at four observation wells in the vicinity of the pit over 19 weeks and at an observation well near a test well over 21 h. In addition, by measuring the rate of pumping out from the pit sump, at a constant head (usually equal to height of the pit floor), the real inflow rates to the pit were monitored. The main innovations of this work were to make comparison between numerical modelling using a finite element software called SEEP/W and actual data related to inflow and extend the applicability of the numerical model. This model was further used to estimate the hydraulic heads at the observation wells around the pit over 19 weeks during mining operations. Data from a pump-out test and observation wells were used for model calibration and verification. In order to evaluate the model efficiency, the modelling results of inflow quantity and hydraulic heads were compared to those from analytical solutions, as well as the field data. The mean percent error in relation to field data for the inflow quantity was 0.108. It varied between 1.16 and 1.46 for hydraulic head predictions, which are much lower values than the mean percent errors resulted from the analytical solutions (from 1.8 to 5.3 for inflow and from 2.16 to 3.5 for hydraulic head predictions). The analytical solutions underestimated the inflow compared to the numerical model for the time period of 2–19 weeks. The results presented in this paper can be used for developing an effective dewatering program.     

Strategically designed sample composition for fastest screening of polychlorinated biphenyl congeners in water samples

A new strategy for preparing composite samples of special interest and applicability in environmental screening studies is presented. The use of supersaturated experimental design matrices to conduct the sample composition of water sample specimens in screening studies is demonstrated. In contrast to well known conventional sample composition, this strategic approach provides analytical objects allowing the accurate prediction of analyte concentration levels in the original individual sample specimens while fixing the number of experiments to be carried out down to the very number of sample specimens. This will be of special importance when dealing with analytes that require complicated, labour intensive and expensive analytical processes. To reach this goal, two main conditions must be fulfilled. The first one is the sparsity effect (Pareto principle) which holds for the specimens in the sampling campaign. This means that the number of really anomalous or contaminated specimens, as compared to the total number of specimens to be analysed, is low. In environmental screening studies, frequently this situation can be reasonably assumed. The second condition is to have an effective manner to develop and solve the experimental designs required to build-up the composite samples. The challenging problem of screening PCBs in water samples has been tackled to show the usefulness of this strategic approach by combining chemometrically assisted sample composition and rapid analysis using solid-phase microextraction of the composite samples.     

Quality assurance in measuring the elemental composition of the alga Fucus vesiculosus

Algae are increasingly used for the purpose of environmental biomonitoring, for instance in the long-term program of the Federal Environmental Specimen Bank of Germany. Therefore, for the studies presented here, freeze-dried samples of Fucus vesiculosus collected from the North Sea shores were analyzed for a broad range of elements by instrumental neutron activation analysis (INAA), while inductively coupled plasma atomic emission spectrometry (ICP-AES) and mass spectrometry (ICP-MS) were carried out on digests. The entire analytical procedures, including field sampling, cleaning of material, sample handling, determination of blanks and instrumental parameters, are described. Certified reference materials analyzed in parallel with real samples and intermethod comparisons were used for assuring the accuracy of the analytical data. Reproducibility of INAA measurements was between 4 and 6% depending on the element considered. Possible sources of uncertainty and variation of the contaminant origins are discussed. Boundary conditions for the performance of algae sampling within environmental monitoring programs and the application of this marine bioindicator for the purpose of controlling time-dependent and local differences in element patterns are presented.