Impact of desertification on temperature trends in the Middle East

The intense interest in desertification and climate change has stimulated detailed studies of temperature records in many areas of the world. In this investigation, the temperature records from the Middle East region are analyzed over the period 1950–1990. Results reveal a linear, statistically significant temperature increase of 0.07 °C/decade over the 41-year period. An analysis of spatial controls on these temperature changes reveals a warming effect associated with both overgrazing and the degree of human-induced desertification. The results of this study are consistent with theoretical and empirical studies predicting and demonstrating a warming signal associated with these land surface changes in the world's dryland areas.     

Pesticide burden on some insects of economic importance in Lucknow (India)

Some insects of economic importance from Lucknow (India) have been investigated for their pesticide burden. Chlorinated pesticide residues of DDT, BHC and aldrin along with their metabolites and isomers have been detected in crop pollinating insects, honeybees (Apis indica) and butterflies (Danais chrysippus and Eurema sp.) and predators, dragonfly (Platythemis sp.) and wasps (Polistes herebreus). DDT and their metabolites were present in concentrations which varied from 231–796 ng g^–1, followed by BHC (10–60 ng g^–1), and aldrin (0.26–6.68 ng g^–1). This finding is likely to stimulate newer interest in the area of pesticide research and start meaningful investigation to find if bioaccumulated pesticides would have adverse impact on otherwise beneficial potentials of such insects in our ecosystems.     

Environmental and biological monitoring of methyl ethyl ketone (MEK)

This study was conducted to evaluate the usefulness of various biological parameters for monitoring of workers exposed to methyl ethyl ketone (MEK). Fifty male workers from a large magnetic videotape factory participated in this study. Personal air samples were collected using 3M organic vapor monitors and analysed for MEK by gas chromatography with flame ionisation detector (FID). 10 mL of urine; blood (1 mL) and exhaled air were also collected at the end of an 8-hour workshift. The headspace GC method was applied for measurement of urinary and blood MEK. MEK in expired air was analysed directly by using a GC/FID.The correlation coefficients (r) between environmental MEK and all other biological parameters measured show significant positive relationships. The r for environmental MEK and urine MEK was 0.84; for blood 0.73 and for breath 0.64. The correlation coefficients between blood and urine was 0.72; blood and breath was 0.88 and urine and breath 0.60. These findings suggest that measurements of unmetabolised MEK in blood, exhaled air and urine can be used for biological monitoring of MEK exposure. Nevertheless, laboratory methodological assessment is in favour of measuring urinary MEK as it is non-invasive and does not have to be analysed immediately after collection.     

Spectrophotometric determination of ferbam (iron(III) dimethyldithiocarbamate) in commercial sample and wheat grains using 4,7-diphenyl-1,10-phenanthroline after extraction into mesityl oxide

A procedure has been developed for the determination of iron(III) dimethyldithiocarbamate by converting it into iron(II)-bathophenanthroline complex, which is then extracted into mesityl oxide in the presence of potassium perchlorate. The absorbance is then measured at 534 nm against a reagent blank. Beer's law is obeyed over the concentration range 0.5-20 microg ml(-1) in the final solution. The method is sensitive, highly selective and can be used for the determination of ferbam in a commercial sample, and in mixtures with various dithiocarbamates (ziram, zineb, maneb, etc.) and in wheat grains.     

Organophosphate flame retardants and plasticisers in wastewater treatment plants

Previous studies have revealed that chlorinated and non-chlorinated organophosphorous flame retardants and plasticisers are important contaminants in German surface waters and it has been demonstrated that wastewater treatment plants contribute to the emission of these substances. In this study temporal development as well as elimination efficiency were determined in two wastewater treatment plants (STP) in the Ruhr/Rhine area at different stages of the wastewater treatment process. The samples were analysed for the non-chlorinated organophosphate esters tri-n-butylphosphate (TnBP), tri-iso-butylphosphate (TiBP), tris-(butoxyethyl)-phosphate (TBEP) and triphenylphosphate (TPP) and the chlorinated organophosphate esters tris-(2-chloro, 1-methylethyl)-phosphate (TCPP), tris-(2-chloro-, 1-chloromethylethyl)-phosphate (TDCP) and tris-(2-chloroethyl)-phosphate (TCEP). The study showed that there were significant differences in the elimination of chlorinated and non-chlorinated organophosphorous flame retardants. The elimination rates ranged from 57-86% for TiBP, TnBP and TBEP at both STP's. No elimination of the chlorinated flame retardants TCPP, TDCP and TCEP was observed in any of the sampled STPs. At both STPs the first treatment steps and the final filtration did not contribute to the elimination of the non-chlorinated organophosphorous flame retardants while the aeration step did. At both STPs the efficiency of the cleaning process concerning the flame retardants was comparable. Thus the type of construction of the STP was not relevant for the elimination of these substances. Additionally a strong day-to-day variation was observed, while in one STP a temporal trend for TCPP during the week was found.     

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.     

Interpretation of roadside PM10 monitoring data from Sunderland,United Kingdom

Roadside PM₁₀ has been monitored by Partisol® at three sitesin Sunderland between August 1997 and February 1998. The sites chosen were an inner city kerbside site; a roadside site adjacentto a dual carriageway on the outskirts of Sunderland with an openaspect; and a rural site.The results indicate that there is a seasonal variation in the relationship between the sites in terms of monitored PM₁₀.In the winter there is a poor correlation between the sites whereas in the summer significant correlations are obtained. Of the sites monitored PM₁₀ is consistently highest at the inner city roadside site. During the summer, exceedances of theU.K. 50 g m^-3 standard (DETR, 2000) are associated with conditions suitable for the build-up of photochemical pollutionhowever during the winter period exceedances are recorded duringa variety of weather conditions.At the dual carriageway site PM_2.5 has also been recorded and contributions to measured PM₁₀ are 77% in summer and68% in winter. The results illustrate a number of inconsistencies between this study utilising the Partisol® andothers reporting results where PM₁₀ has been monitored by TEOM®.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Comparison of Two Manual Methods of Nitrogen Dioxide Determination in Ambient Air

Sodium arsenite (modified Jacobs and Hochheiser method; hereafter referred as SA), the most widely used manual monitoring method for determination of nitrogen dioxide (NO₂) in ambient air, particularly in developing countries has been evaluated and compared with US EPA recommended equivalent method of TGS-ANSA (hereafter referred as ANSA). NO₂ concentrations generated from laboratory test atmosphere were analyzed by these two methods and were compared statistically. Laboratory evaluations showed that SA method has high sensitivity to different sampling conditions, which normally vary during actual field monitoring. Hence, correction factors for absorption efficiency were estimated for SA and ANSA methods. Absorption efficiency of NO₂ in SA method was found to be much lower (64%) as against the reported value of 82% at the method recommended sampling conditions, whereas for ANSA method, it was found 1.0 as against the reported value of 0.93. After applying derived correction factors, both the methods produced almost similar concentration values of NO₂.