Water Quality Modeling of Municipal Discharges from Sea Outfalls,Mumbai

The island city of Mumbai with a population of about 10 million generates about 2000 million liters per day (mld) of sewage from the seven service areas of the city sewerage network and discharges it into the adjoining west coast and the two creeks in the Arabian Sea. This has resulted in degradation of coastal water quality, contamination of the adjoining beaches and seafronts. The Municipal Corporation of Greater Mumbai has therefore, undertaken the task of delineating appropriate sewage disposal system to achieve cleaner marine ecosystem through marine outfalls at specific locations. This paper presents the results of the mathematical simulations on the impacts of discharge is-a-vis the length of the outfall and level of land treatment apriori. The results of the simulation indicate the level of bacterial pollution to be higher near the diffuser locations as compared to nearshore regions. 48 hsimulation result analysis shows that FC counts nearthe diffuser location will be in the range of 2000–8000 counts per 100 ml.     

Influence of Building Density and Roof Shape on the Wind and Dispersion Characteristics in an Urban Area: A Numerical Study

The Computational Fluid Dynamics code CFX-TASCflow is used for simulating the wind flow and pollutant concentration patterns in two-dimensional wind-tunnel models of an urban area. Several two-dimensional multiple street canyon configurations are studied corresponding to different areal densities and roof shapes. A line source of a tracer gas is placed at the bottom of one street canyon for modelling street-level traffic emissions. The flow fields resulting from the simulations correspond to the patterns observed in street canyons. In particular and in good agreement with observations, a dual vortex system is predicted for a deep flat-roof street canyon configuration, while an even more complex vortex system is evidenced in the case of slanted-roof square street canyons. In agreement with measurement data, high pollutant concentration levels are predicted either on the leeward or the windward side of the street canyon, depending on the geometrical details of the surrounding buildings.     

Physical Modeling of Emissions from Naturally Ventilated Underground Parking Garages

The dispersion of pollutants from naturally ventilated underground parking garages has been studied in a boundary layer wind tunnel. Two idealized model setups have been analysed, one was simulating pollutant dispersion around an isolated rectangular building and one was representing dispersion in a finite array of idealized building blocks. Flow and dispersion close to modelled ground level emission sources was measured. The results illustrate the complexity of the flow around buildings and provide insight in pollutant transport from ground level sources located directly on building surfaces. As a result, areas critical with respect to high pollutant concentrations could be visualized. Particularly, the results show high concentration gradients on the surface of the buildings equipped with modelled emission sources. Inside the boundary layers on the building walls, a significant amount of pollutants is transported to upwind locations on the surface of the building. The paper documents the potential of physical modelling to be used for the simulation and measurement of dispersion close to emission sources and within complex building arrangements.     

Modelling Tracer Dispersion from Landfills

Several wind tunnel experiments of tracer dispersion from reduced-scale landfill models are presented in this paper. Different experimental set-ups, hot-wire anemometry, particle image velocimetry and tracer concentration measurements were used for the characterisation of flow and dispersion phenomena nearby the models. The main aim of these experiments is to build an extensive experimental data set useful for model validation purposes. To demonstrate the potentiality of the experimental data set, a validation exercise on several mathematical models was performed by means of a statistical technique. The experiments highlighted an increase in pollutant ground level concentrations immediately downwind from the landfill because of induced turbulence and mean flow deflection. This phenomenon turns out to be predominant for the dispersion process. Tests with a different set-up showed an important dependence of the dispersion phenomena from the landfill height and highlighted how complex orographic conditions downwind of the landfill do not affect significantly the dispersion behaviour. Validation exercises were useful for model calibration, improving code reliability, as well as evaluating performances. The Van Ulden model proved to give the most encouraging results.     

Extension of the EUROS Integrated Air Quality Model to Fine Particulate Matter by Coupling to CACM/MADRID 2

The European Operational Smog (EUROS) integrated air quality modelling system has been extended to model fine particulate matter (PM). From an extended literature study, the Caltech Atmospheric Chemistry Mechanism and the Model of Aerosol Dynamics, Reaction, Ionisation and Dissolution were selected and recently coupled to EUROS. Currently, modelling of mass and chemical composition of aerosols in two size fractions (PM_2.5 and PM_10–2.5) is possible. The chemical composition is expressed in terms of seven components: ammonium, nitrate, sulphate, elementary carbon, primary inorganic compounds, primary organic compounds and secondary organic compounds. Calculated PM₁₀ concentrations and chemical composition are presented for two summer months of the year 2003 (1 July to 31 August).     

Improving inverse model fitting in trees—Anisotropy,multiplicative effects,and Bayes estimation

Model fitting for individual-based effects in forests has some problems. Because samples measuring the separate influence of each individual are rarely available, the measured value in the sample represents the influence of all surrounding individual trees. Therefore, it is helpful to build inverse models that use the spatial pattern of the variable as well as that of the source trees. For example, since seed dispersal is influenced by wind effects, a model is discussed describing anisotropic effects to ensure an unbiased estimate of the total fruit number. Further, we present a model describing the absorption of radiation by trees. In this case a multiplicative combination of individual effects yields the total effect. Our approach uses logarithmic transformations of the original data to model multiplicative combinations as sum of transformed single effects. For fitting model parameters we propose an approach based on Bayesian statistics, to ensure ecologically interpretable parameters.     

QSAR trout toxicity models on aromatic pesticides

The pesticides originally designed to kill target organisms are dangerous for many other wild species. Since they are applied directly to the environment, they can easily reach the water basins and the topsoil. A dataset of 125 aromatic pesticides with well-expressed aquatic toxicity towards trout was subjected to quantitative structure activity relationships (QSAR) analysis aimed to establish the relationship between their molecular structure and biological activity. A literature data for LC₅₀ concentration killing 50% of fish was used. In addition to the standard 2D-QSAR analysis, a comparative molecular field analysis (CoMFA) analysis considering the electrostatic and steric properties of the molecules was also performed. The CoMFA analysis helped the recognition of the steric interactions as playing an important role for aquatic toxicity. In addition, the transport properties and the stability of the compounds studied were also identified as important for their biological activity.     

Value of information in product recovery decisions: a Bayesian approach

There is a widespread recognition of the need for better information sharing and provision to improve the viability of end-of-life (EOL) product recovery operations. The emergence of automated data capture and sharing technologies such as RFID, sensors and networked databases has enhanced the ability to make product information; available to recoverers, which will help them make better decisions regarding the choice of recovery option for EOL products. However, these technologies come with a cost attached to it, and hence the question ‘what is its value?’ is critical. This paper presents a probabilistic approach to model product recovery decisions and extends the concept of Bayes' factor for quantifying the impact of product information on the effectiveness of these decisions. Further, we provide a quantitative examination of the factors that influence the value of product information, this value depends on three factors: (i) penalties for Type I and Type II errors of judgement regarding product quality; (ii) prevalent uncertainty regarding product quality and (iii) the strength of the information to support/contradict the belief. Furthermore, we show that information is not valuable under all circumstances and derive conditions for achieving a positive value of information.     

Fault-dynamic modelling of a phthalic anhydride reactor

A new methodology, fault-dynamic modelling, has been developed for analysis of potentially hazardous situations in the process industries. Traditional fault-tree analysis is used to determine the combinations of component failure that can lead to a particular process upset condition. Realistic dynamic modelling is then used to calculate the time available for corrective action once the upset has started. The method is applied to a phthalic anhydride reactor. The results of the analysis identify three process upsets that can lead to catastrophic failure in 2–5 min if left uncorrected. Other process upsets lead to safe conditions.