R.S. Ettouney

Forecasting of ozone pollution using artificial neural networks

Purpose – The objective of this study is to develop and validate a neural‐based modelling methodology applicable to site‐specific short‐ and medium‐term ozone concentration forecasting. A novel modelling technique utilizing two feed forward artificial neural networks (FFNN) is developed to improve the performance of time series predictions.Design/methodology/approach – Air pollution and meteorological data were collected for one year in two locations in Kuwait. The hourly averages of the data were processed to generate a covariance matrix and analyzed to generate the principal component method. A two‐FFNN model is then used to predict the actual data.Findings – The newly developed model improves the prediction accuracy over the conventional method. Owing to the presence of noise and other minor disturbances in the data, shorter‐range modelling gives better modelling results.Originality/value – A novel modelling technique is developed to predict the time series of zone concentration.

An assessment of the air pollution data from two monitoring stations in Kuwait

This article assesses the air pollution data from two monitoring stations in Kuwait. The measurements cover major pollutants, i.e., CO, CO2, methanated and non-methanated hydrocarbons, NO x , SO2, O3, and particulate matter (PM10). The data also includes meteorological parameters, i.e., solar intensity, temperature, wind speed, and wind direction, and has been collected over a period 4 years, from 2001 to 2004. Data analysis includes the assessment of annual hourly averages and 1-h maxima. Typical pollutant concentration trends, similar to those previously reported for Kuwait and for other locations around the world, are observed except for particulate matter measurements, which have higher values because of proximity to the desert. Emissions of nitrogen oxides show a consistent increase over the years. This is caused by the increase in the number of motor vehicles and the expansion in power generation and industrial activities. The data collected is a subset of the air quality criteria, as defined by the US EPA (United States Environmental Protection Agency).

Salt recovery from brine generated by large-scale seawater desalination plants

AbstractWater shortages in the Middle East and North Africa (MENA) region countries mandate the installation of large-scale desalination plants. Concentrate management requires properly operated cost-effective technologies to reduce the environmental impacts arising from brine discharge. Significant improvement in economics may be obtained by the recovery of chemicals from brines. This study addresses the management of modular brine streams generated from large-scale reverse osmosis desalination plants with microfiltration and nanofiltration (NF) as pretreatment stages. Appropriate salt recovery schemes have been identified and analyzed from the performance and environmental points of view. The economics of salt recovery schemes from NF and reverse osmosis (RO) brine based on evaporation ponds, brine evaporator and membrane crystallizer (MCr) are analyzed and compared. Phased application of the salt recovery program is considered. The results indicate that using NF as pretreatment and adopting salt recove...

Emissions inventory, ISCST, and neural network modelling of air pollution in Kuwait

This paper focuses on modelling of emission inventory, pollutant dispersion by the industrial source complex short term model (ISCST), and neural network analysis of air pollution in Kuwait. A novel neural network‐based scheme is suggested and applied to site‐specific short‐ and medium‐term forecasting of ozone concentrations. Two feed forward artificial neural networks (ANN) are used to improve the performance of time series predictions. Results show that this forecasting technique represents a significant improvement over the conventional ANN approach.

Flue gas desulfurization and humidification dehumidification in power plants

Abstract Performance evaluation is presented for flue gas desulfurization (FGD), humidification and dehumidification desalination (HDD) of flue gases emitted from power plants. The proposed system is based on use of seawater for SO2 absorption and removal from the flue gases. The FGD and HDD processes are separated in order to achieve the highest possible efficiency. This is because FGD requires low temperatures to achieve high rates of absorption and removal of SO2. On the other hand, HDD requires higher temperatures to provide sufficient temperature difference and driving force for humidification and dehumidification. Analysis of both systems is applied to the emission rate data of power plants in Kuwait. The design results of the seawater SO2 absorption column showed variations in the column height between 8.1–12.6 m as the power plant capacity was increased from 244–4173 MW. Analysis of the HDD system show that it might not be the optimum desalination alternative because of its limited production capa...

Mass transfer- fluid flow interactions in perforated plate extractive reactors

Coupling between extraction, reaction, and liquid-liquid contact hydrodynamics have quantitative as well as qualitative implications on the performance of un-agitated perforated plate extractive reactors. Models, which take into account the effect of flow dynamics on mass transfer performance, are developed to analyze the steady state behavior of such columns when conducting a chemical reaction in the continuous extract phase. New expressions are derived for the composition profiles in the cases of physical extraction, slow, and infinitely fast reactions. Typical results show that the raffinate purity may either increase or decrease on increasing the solvent rate depending on the interaction between column fluid dynamics, mass transfer, and reaction kinetics.

Extraction–Stripping Process Synthesis with Multiple Solvent Circulation Loops

A flow scheme is suggested for synthesizing solvent extraction–solvent regeneration processes consisting of sets of mixer-settlers. The proposed scheme is based on equal partitioning of the separation capacity between the extraction and stripping cascades with each pair of stages interconnected via an independent solvent circulation loop. A dimensionless linear steady-state model is developed for analysing the behaviour of the proposed multi-loop scheme. It enabled the identification of limiting design conditions and the generation of results relating the combination of strippant consumption and solvent circulation rates required to achieve a given purification duty in a given number of stages. A simple numerical (graphical) method is also suggested for the analysis when equilibrium relations in the extractor and stripper are non-linear. The superiority of the proposed multi-loop scheme over the conventional method of coupling the extraction and stripping cascades via a single solvent circulation loop is illustrated quantitatively. Compared with the conventional scheme the proposed flow structure enables the same purification to be achieved with the same total separation capacity, but at lower solvent circulation rates and strippant consumption. This is obviously reflected as savings in both equipment and operating costs.