Heavy metal concentrations of cigarettes in Turkey

The concentration of heavy metals in most popular brands of cigarettes sold in Turkey was determined. Homogenised samples of tobacco were digested in HNO3-HClO3 mixture and after evaporation by up to 300 degreesC the residue was extracted with HNO3 and analysed with ICP-MS. The minimum, average and maximum concentrations of heavy metals (mug/g), were determined for 9 different brands of cigarettes and the values were as follows: Cd 0.49 - 1.70 - 2.62; Cr 1.34 - 1.63 - 2.22; Co 0.12 - 0.22 - 0.71; Ni 0.06 - 0.22 - 0.35; Cu 1.16 - 2.45 - 6.4; As 0.63 - 0.92 - 0.95; Hg 0.20 - 0.25 - 0.28; Pb 0.32 - 1.02 - 2.3

Evaluation of treatability for two textile mill effluents

The study emphasizes wastewater characteristics of two different textile plants as they apply to biological treatment. Although conventional characterization reveals no major differences, the effluents from the acrylic fiber and yarn dyeing plant exhibit all the properties of a non-biodegradable wastewater. Appropriate pretreatment consisting of partial chemical oxidation with H2O2 reduces its COD content to 700 mg l(-1), almost entirely biodegradable whereas COD fractionation indicates that the effluents of the cotton knit dyeing plant contain 9% residual fractions. Experimental investigation shows that most kinetic and stoichiometric properties of both wastewaters are compatible with that of domestic sewage with the exception of a much slower hydrolysis rate. (C) 1999 IAWQ Published by Elsevier Science Ltd. All rights reserved

Modeling of CO distribution in Istanbul using Artificial Neural Networks

Artificial Neural Network (ANN) is one of the popular methods in optimization of complex engineering problems compared to the classical statistical methods. ANN approximates non-linear input-output variables and finds an optimum correlation between these variables. Thus the structure of the overall system is simplified. ANN function approximation is achieved by identifying the input-output pattern pairs, using the following steps: (I) Selection of the neural structure (namely the number of layers and that of neurons), (II) Training of ANN using Back-Propagation (BP) algorithms. ANN coefficients can be trained as any system performance characteristics by monitoring test data. (III) Validation of the network to verify generalization capability

Gas emissions in Istanbul-Kemerburgaz solid waste landfill site

The amount of solid waste produced in Istanbul, the biggest city in Turkey with a population of 10,072,447 according to the 2000 census, is about 9,000 tons per day. The amount of organic substances is more than 45% and leads to the formation of high amounts of flammable and explosive solid waste gases accumulated in Istanbul land-fill sites. Because of their flammable and explosive properties, it is very important to monitor the level of emissions of these gases to ensure regulatory requirements are met. In this study the gas emission measurements of methane (CH4), acetylene (C2H2), oxygen (O-2), carbon monoxide (CO), and hydrogen sulfide (H2S) are carried out in Kemer-burgaz-Odayeri solid waste landfill site, Istanbul. The emission average values measured were as follows: 5.2-37 vol% for methane, 71.6 - 100% LEL (Lower Explosion Limit; 100% LEL= 2.3vol%) for acetylene, 2.7-20.9 vol% for oxygen, 9.6-145.8 ppm for carbon monoxide, and 22.6-95 ppm for hydrogen sulfide. Methane and acetylene concentrations were in the explosively flammable range at landfill gas vents. Also, carbon monoxide and hydrogen sulfide concentrations were remarkably high at the vents. The emission values of these landfill gases were compared with Turkey's criteria and international legal criteria

Evaluation of heat transfer correlations for HCCI engine modeling

Combustion in HCCI engines is a controlled auto-ignition of well-mixed fuel, air and residual gas. The thermal conditions of the combustion chamber are governed by chemical kinetics strongly coupled with heat transfer from the hot gas to the walls. The heat losses have a critical effect on HCCI ignition timing and burning rate, so it is essential to understand heat transfer process in the combustion chamber in the modeling of HCCI engines. In the present paper, a comparative analysis is performed to investigate the performance of well-known heat transfer correlations in an HCCI engine. The results from the existing correlations are compared with the experimental results obtained in a single-cylinder engine. Significant differences are observed between the heat transfer results obtained by using Woschni, Assanis and Hohenberg correlations

Early initiated feeding versus early reached target enteral nutrition in critically ill children: An observational study in paediatric intensive care units in Turkey

Aim: Although early enteral nutrition (EN) is strongly associated with lower mortality in critically ill children, there is no consensus on the definition of early EN. The aim of this study was to evaluate our current practice supplying EN and to identify factors that affect both the initiation of feeding within 24 h after paediatric intensive care unit (PICU) admission and the adequate supply of EN in the first 48 h after PICU admission in critically ill children