Preliminary air pollution monitoring in San Miguel, Buenos Aires

Passive diffusion samplers were employed in San Miguel(Buenos Aires Metropolitan Area) for a preliminary airpollution monitoring. The highest loads were observedin downtown, compared with an urban background site.Total suspended particulate matter (TSPM) varied from0.257 to 0.033 mg cm^-2 month^-1; dust was examinedfor particle nature and size distribution. A similartrend was observed for nitrogen dioxide (NO₂) andTSPM spatial distribution, suggesting that traffic isthe major pollution source. Sulphur dioxide (SO₂)values were low and rather homogeneous. Levels for theinvestigated pollutants are below EPA's guide linevalues. Geographic (flat area, near to Rio de LaPlata) and climatologic factors (rainfalls andvariable wind directions) contribute to disperse pollutants.     

Persistent chlorinated pesticides in fish and cattle fat and their implications for human serum concentrations from the Sene-Gambian region

The concentrations of organochlorine pesticides (OCPs) in fish, shrimps, cattle fat and human serum samples from the Sene-Gambian region were measured using validated analytical methodologies. The results obtained were compared with those of other existing African studies and with data from other developing countries. In fish samples, p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) and HCB were detected with a frequency of 100%, whereas p,p'-dichlorodiphenyltrichloroethane (p,p'-DDT) was detected in eight, heptachlorepoxide in six and endosulfansulfate in five of the nine fish samples. Relatively low concentrations of OCPs were found in cattle and shrimp fat samples. p,p'-DDE and alpha-hexachlorocyclohexane (alpha-HCH) were the most frequently identified. The sum of HCHs ranged from undetected to 13.3 ng g-1 fat, the sum of DDTs from 11.1 to 199.2 ng g-1 fat and the sum of endosulfans from not detected to 49.7 ng g-1 fat in fish and shrimps. In serum samples, alpha-HCH, p,p'-DDE, o,p'-DDT and p,p'-DDT were detected in all 16 pooled serum samples, whereas endosulfansulfate, methoxychlor, mirex, heptachlorepoxide and endrin were detected in 15 samples with most of the concentrations below 10 ng mL-1. The concentrations of OCPs in human serum were given on a serum lipid and whole serum volume basis. The implications for the human diet of these OCP concentrations in serum were investigated by means of biomagnification factors related to the log Kow values of the targeted compounds. The current use of HCH mixtures was suggested to explain the unusually high alpha-HCH concentration. The distribution pattern of these OCPs in humans was also discussed and compared with that in other studies.     

Risk-Based Prioritization of Air Pollution Monitoring Using Fuzzy Synthetic Evaluation Technique

Air pollution monitoring programs aim to monitor pollutants and their probable adverse effects at various locations over concerned area. Either sensitivity of receptors/location or concentration of pollutants is used for prioritizing the monitoring locations. The exposure-based approach prioritizes the monitoring locations based on population density and/or location sensitivity. The hazard-based approach prioritizes the monitoring locations using intensity (concentrations) of air pollutants at various locations. Exposure and hazard-based approaches focus on frequency (probability of occurrence) and potential hazard (consequence of damage), respectively. Adverse effects should be measured only if receptors are exposed to these air pollutants. The existing methods of monitoring location prioritization do not consider both factors (hazard and exposure) at a time. Towards this, a risk-based approach has been proposed which combines both factors: exposure frequency (probability of occurrence/exposure) and potential hazard (consequence).This paper discusses the use of fuzzy synthetic evaluation technique in risk computation and prioritization of air pollution monitoring locations. To demonstrate the application, common air pollutants like CO, NO_x, PM₁₀ and SO_x are used as hazard parameters. Fuzzy evaluation matrices for hazard parameters are established for different locations in the area. Similarly, fuzzy evaluation matrices for exposure parameters: population density, location and population sensitivity are also developed. Subsequently, fuzzy risk is determined at these locations using fuzzy compositional rules. Finally, these locations are prioritized based on defuzzified risk (crisp value of risk, defined as risk score) and the five most important monitoring locations are identified (out of 35 potential locations). These locations differ from the existing monitoring locations.     

Preparing future engineers for challenges of the 21st century: Sustainable engineering

The field of engineering is changing rapidly as the growing global population puts added demands on the earth's resources: engineering decisions must now account for limitations in materials and energy as well as the need to reduce discharges of wastes. This means educators must revise courses and curricula so engineering graduates are prepared for the new challenges as practicing engineers. The Center for Sustainable Engineering has been established to help faculty members accommodate such changes through workshops and new educational materials, including a free access website with peer-reviewed materials.     

Comparison of gas chromatography and immunoassay methods in measuring the distribution of dieldrin in rainbow trout tissues.

Studies have been conducted to determine the distribution of dieldrin in various tissues of rainbow trout when exposed to several dieldrin concentrations. Medium sized fish with an average weight and length of 195.4 +/- 30.5 g and 25.7 +/- 1.4 cm, respectively, were placed in groups of 6 in 300 L tanks containing purified and aerated water and maintained at 10 degrees C. Following an acclimatization period of 10 days, each group of fish was exposed to one of four dieldrin concentrations ranging from 50 to 80 ppb. After 24 hours, the fish were taken out of the tanks and sacrificed. The brain, gills, liver, muscles and skin were collected from each fish. Dieldrin was extracted from each tissue using SPE techniques and analyzed by both gas chromatography (GC) and enzyme linked immunosorbent assay (ELISA). Results of analyses by the two techniques were highly correlated. The results also showed that liver and skin tissues had the highest level of dieldrin residues. In comparing the means of the six fish samples, it was found that liver or skin contained about 1.5-fold the level in brain, about 4.0 fold the level in muscles and about 6.5 fold the level in gills. Immunoassay proved to be as reliable an analytical tool as gas chromatography in this case.     

Isoproturon degradation as affected by the growth of two algal species at different concentrations and pH values.

Metabolism of [14C-u-phenyl]isoproturon [3-(4-isopropylphenyl)-1,1-dimethylurea] by two soil and freshwater microorganisms, green alga Chlorella kesslerei and cyanobacterium Anabaena inaequalis, was studied as a function of pH, pesticide concentration, and incubation time. Metabolized isoproturon, in the media, ranged from 0% (Chlorella at pH 5.5 after 1 d) to 22% (Anabaena at pH 5.5 after 10 d). Twenty-five percent faster degradation of isoproturon by Anabaena occurred at pH 5.5 versus pH 7.5, when measured over 10 d. Increased 14C incorporation into tissue, with time and at lower pH, was due mainly to bioaccumulation of [14C]isoproturon and/or its metabolites in the cells. Metabolic degradation resulted in four identifiable (by TLC) metabolites. Based on this, a degradation pathway is proposed, involving mono- and di-N-demethylation, hydroxylation of the isopropyl moiety, and hydrolysis to 4-isopropylaniline. Similarity in the metabolites produced suggests that the enzyme systems responsible for metabolizing isoproturon are almost identical in both photosynthetic micro-algae.     

Clean catalytic technology for liquid phase hydrocarbon oxidation

 Liquid phase hydrocarbon oxidation is one of the principal routes towards industrial organic chemicals. However, low product selectivity and associated by-product formation are major problems in several oxidation processes. As a result of the increasingly stringent environmental regulations, the development of oxidation catalysts has been a major challenge in the last decade. An overview of novel selective and clean oxidation catalysts and processes is presented. Received: 27 July 1998 / Accepted: 8 September 1998     

Polycyclic aromatic hydrocarbons and trace metals in mosque’s carpet dust of Riyadh,Saudi Arabia,and their health risk implications

The main objectives of this work were to identify and determine the concentrations of polycyclic aromatic hydrocarbons (PAHs) and trace metals in carpet dust samples from various mosques of the city of Riyadh and to assess the health risks associated with the exposure to these pollutants. Therefore, 31 samples of mosque’s carpet dust from Riyadh were collected. The results showed that 14 PAHs were present in the dust samples with concentrations ranged from 90 to 22,146 ng g^?1 (mean = 4096 ± 4277 ng g^?1) where low molecular weight compounds were dominant. The presence of PAHs were in the order of naphthalene > chrysene and benzo(b)fluoranthene > benzo(a)pyrene > acenaphthene and benzo(k)fluoranthene > pyrene and the absence of indeno(1,2,3-cd)pyrene and dibenz(a,h)anthracene. The diagnostic ratio coupled with principle component analysis (PCA) revealed mix sources of petrogenic from traffic, stack emission, and pyrogenic inputs from essence and perfumed wood burning. Trace metals were significant in the dust samples, and their concentrations decrease in the order of Zn, Mn, Cu, Cr, Pb, Ni, and V where Zn being the highest (94.4 ± 91.5 μg g^?1) and indium was the lowest (1.9 ± 9.3 μg g^?1). The trace metals were major in southern and central parts of Riyadh and followed the order of central Riyadh > southern Riyadh > western Riyadh > eastern Riyadh > northern Riyadh. Estimated risk based on the total PAHs was found to be 4.30 × 10^?11 for adult and 1.56 × 10^?11 for children. Elemental non-cancer risk for adults ranged from 7.9 × 10^?4 for Co to 7.58 × 10^?1 for Li and for children ranged from 3.70 × 10^?3 for Co to 3.54 for Li. Policy implication and mitigations of PAHs in Riyadh and Saudi Arabia were highlighted.     

Use of Project MOHAVE perfluorocarbon tracer data to evaluate source and receptor models

Project MOHAVE was a major monitoring, modeling, and data analysis study whose objectives included the estimation of the contributions of the Mohave Power Project (MPP) and other sources to visibility impairment in the southwestern United States, in particular at Grand Canyon National Park. A major element of Project MOHAVE was the release of perfluorocarbon tracers at MPP and other locations during 50-day summer and 30-day winter intensive study periods. Tracer data (from about 30 locations) were sequestered until several source and receptor models were used to predict tracer concentrations. None of the models was successful in predicting the tracer concentrations; squared correlation coefficients between predicted and measured tracer were all less than 0.2, and most were less than 0.1.     

Prediction of ozone concentrations in Oporto city with statistical approaches

The performance of three statistical methods: time-series, multiple linear regression and feedforward artificial neural networks models were compared to predict the daily mean ozone concentrations. The study here reported was based on data from one urban site with traffic influences and one rural background site. The studies were performed for the year 2002 and the respective four trimesters separately. In the multiple linear regression and feedforward artificial neural network models, the concentrations of ozone, the concentrations of its precursors (nitrogen oxides) and some meteorological variables for one and two days before the prediction day were used as predictors. For the application of these models in the validation step, the inputs of ozone concentration for one and two days before were replaced by the ozone concentrations predicted by the models. The results showed that time-series modelling was not profitable. In the development step, similar performances were obtained with multiple linear regression and feedforward artificial neural network. Better performance indexes were achieved with feedforward artificial neural network models in validation step. Concluding, feedforward artificial neural network models were more efficient to predict ozone concentrations.