Lead and cadmium in teeth,bone and kidneys of rats with a standard Pb‐Cd supply

Male Wistar rats received a combination of 25 ppm PbCl₂ and 5 ppm CdCl₂ in drinking water at different developmental stages. Pb and Cd levels of incisors, molars, epiphyses, diaphyses and kidney cortex were recorded by atomic absorption spectrophotometry. The results confirmed that Pb has an affinity for hard tissue and especially to teeth, but it also accumulated in soft tissues under the above conditions. In addition, the results indicated none or only a moderate placental or mammary barrier for Pb, and suggested a high absorption of lead from the intestine of sucklings. The results also confirmed that kidney cortex is a primary target for Cd, and indicated that Cd has crossed the placental and mammary barriers to some degree. The positive significant correlation between Cd levels in molars and kidney cortex suggested that rodent molars indicate a degree of Cd absorption, whereas incisors do not. It is supposed that rodent molars are comparable to human deciduous teeth. It is thus confirmed that human deciduous teeth indicate previous lead exposure. It is further inferred that they also can be used as indicators of previous Cd‐exposures.     

A short communication on growing Jatropha in Oman

A stripping technique has been used to cencentrate selected hydrocarbons present in water samples at the parts per billion level for analysis by gas chromatography. The chromatograms of hydrocarbons thus stripped from several different water samples show similarities. Washing out of atmospheric pollutants by rainfall is postulated as an explanation of these results. This hypothesis is supported by a comparison of the data with those for trace atmospheric analysis. The comparison shows that the same compounds are present in similar relative amounts both in water samples and the atmosphere. After a period of rain the atmospheric concentrations decrease whilst the water bound concentrations increase.     

Batch adsorption of organic pollutants from oxidation pond effluents using fly ashes

The batch shaking adsorption study was conducted to determine the potential of fly and volcanic ashes in removing organic pollutants from oxidation pond effluents. Factors affecting organic pollutant removals, such as concentrations and sizes of fly and volcanic ashes, initial pond effluent organic concentrations, washed and unwashed conditions of fly and volcanic ashes, were investigated. The TOC (total organic carbon) removal efficiency varied from 30 to 58 percent. The organic removal efficiency increased with increasing ash concentrations, with decreasing initial pond effluent organic concentrations and with decreasing sizes of ashes.     

Modelling air pollution for epidemiologic research--part II: predicting temporal variation through land use regression

Over recent years land use regression (LUR) has become a frequently used method in air pollution exposure studies, as it can model intra-urban variation in pollutant concentrations at a fine spatial scale. However, very few studies have used the LUR methodology to also model the temporal variation in air pollution exposure. The aim of this study is to estimate annual mean NO₂ and PM₁₀ concentrations from 1996 to 2008 for Greater Manchester using land use regression models. The results from these models will be used in the Manchester Asthma and Allergy Study (MAAS) birth cohort to determine health effects of air pollution exposure.The Greater Manchester LUR model for 2005 was recalibrated using interpolated and adjusted NO₂ and PM₁₀ concentrations as dependent variables for 1996-2008. In addition, temporally resolved variables were available for traffic intensity and PM₁₀ emissions. To validate the resulting LUR models, they were applied to the locations of automatic monitoring stations and the estimated concentrations were compared against measured concentrations.The 2005 LUR models were successfully recalibrated, providing individual models for each year from 1996 to 2008. When applied to the monitoring stations the mean prediction error (MPE) for NO₂ concentrations for all stations and years was -0.8 μg/m³ and the root mean squared error (RMSE) was 6.7 μg/m³. For PM₁₀ concentrations the MPE was 0.8 μg/m³ and the RMSE was 3.4 μg/m³.These results indicate that it is possible to model temporal variation in air pollution through LUR with relatively small prediction errors. It is likely that most previous LUR studies did not include temporal variation, because they were based on short term monitoring campaigns and did not have historic pollution data. The advantage of this study is that it uses data from an air dispersion model, which provided concentrations for 2005 and 2010, and therefore allowed extrapolation over a longer time period.