Assessment of heavy metal enrichment in the offshore fine-grained sediments of the Caspian Sea

Sampling of the offshore seabed sediments of southwestern part of the Caspian Sea was carried out by gravity corer in order to study heavy metal concentration and the physicochemical factors controlling their distribution in the fine-grained fraction. The grain size distribution, amount, and type of clay minerals, total organic carbon (TOC) content, and Eh–pH of the sediments were determined. The average concentrations of the heavy metals in ppm are Mn (563), Cu (207.5), Sr (187), Zn (94), Pb (26.3), Ni (14.5), Co (11.5), Cd (2.56), and Ag (1.04) in their order of abundances. Co and Zn mostly indicate increase in silt-size fraction of the sediments suggesting their probable detrital provenance but the Mn, Ni, Cu, Sr, Pb, Cd, and Ag concentrations show a similar trend to distribution of the clay-size fraction. The concentrations of Mn, Co, and Cd increase with increase in the TOC content but the Cu, Pb, Ni, Ag, and Sr concentrations decrease with increase of the TOC content. The amounts of Zn, Cu, Sr, Pb, Cd, and Ag increase with increase in the CaCO₃ content. The calculated enrichment factor indicates that the sediments are very strong to extremely enriched in Ag, significantly enriched in Cu and Cd, and depleted to mineral for Pb, Sr, Co, Ni, and Zn. Variations of the Cu, Sr, Cd, Ag, and Pb concentrations are similar to the clay and CaCO₃ distributions.     

The use of sensory perception indicators for improving the characterization and modelling of total petroleum hydrocarbon (TPH) grade in soils

This paper proposes a multistep approach for creating a 3D stochastic model of total petroleum hydrocarbon (TPH) grade in potentially polluted soils of a deactivated oil storage site by using chemical analysis results as primary or hard data and classes of sensory perception variables as secondary or soft data. First, the statistical relationship between the sensory perception variables (e.g. colour, odour and oil–water reaction) and TPH grade is analysed, after which the sensory perception variable exhibiting the highest correlation is selected (oil–water reaction in this case study). The probabilities of cells belonging to classes of oil–water reaction are then estimated for the entire soil volume using indicator kriging. Next, local histograms of TPH grade for each grid cell are computed, combining the probabilities of belonging to a specific sensory perception indicator class and conditional to the simulated values of TPH grade. Finally, simulated images of TPH grade are generated by using the P-field simulation algorithm, utilising the local histograms of TPH grade for each grid cell. The set of simulated TPH values allows several calculations to be performed, such as average values, local uncertainties and the probability of the TPH grade of the soil exceeding a specific threshold value.     

Modeling of Cr contamination in the agricultural lands of three villages near the leather industry in Kasur,Pakistan, using statistical and GIS techniques

Kasur is one of the hubs of leather industry in the Punjab, Pakistan, where chrome tanning method of leather processing is extensively being used. Chromium (Cr) accumulation levels in the irrigation water, soil, and seasonal vegetables were studied in three villages located in the vicinity of wastewater treatment plant and solid waste dumping site operated by the Kasur Tanneries Waste Management Agency (KTWMA). The data was interpreted using analysis of variance (ANOVA), clustering analysis (CA), and principal component analysis (PCA). Interpolated surface maps for Cr were generated using the actual data obtained for the 30 sampling sites in each of the three villages for irrigation water, soil, and seasonal vegetables. The level of contamination in the three villages was directly proportional to their distance from KTWMA wastewater treatment plant and the direction of water runoff. The highest level of Cr contamination in soil (mg kg^?1) was observed at Faqeeria Wala (37.67), intermediate at Dollay Wala (30.33), and the least in Maan (25.16). A gradational variation in Cr accumulation was observed in the three villages from contaminated wastewater having the least contamination level (2.02–4.40 mg L^?1), to soil (25.16–37.67 mg kg^?1), and ultimately in the seasonal vegetable crops (156.67–248.33 mg kg^?1) cultivated in the region, having the highest level of Cr contamination above the permissible limit. The model used not only predicted the current situation of Cr contamination in the three villages but also indicated the trend of magnification of Cr contamination from irrigation water to soil and to the base of the food chain. Among the multiple causes of Cr contamination of vegetables, soil irrigation with contaminated groundwater was observed to be the dominant one.     

Mathematical models for accurate prediction of atmospheric visibility with particular reference to the seasonal and environmental patterns in Hong Kong

Atmospheric visibility impairment has gained increasing concern as it is associated with the existence of a number of aerosols as well as common air pollutants and produces unfavorable conditions for observation, dispersion, and transportation. This study analyzed the atmospheric visibility data measured in urban and suburban Hong Kong (two selected stations) with respect to time-matched mass concentrations of common air pollutants including nitrogen dioxide (NO(2)), nitrogen monoxide (NO), respirable suspended particulates (PM(10)), sulfur dioxide (SO(2)), carbon monoxide (CO), and meteorological parameters including air temperature, relative humidity, and wind speed. No significant difference in atmospheric visibility was reported between the two measurement locations (p > or = 0.6, t test); and good atmospheric visibility was observed more frequently in summer and autumn than in winter and spring (p < 0.01, t test). It was also found that atmospheric visibility increased with temperature but decreased with the concentrations of SO(2), CO, PM(10), NO, and NO(2). The results showed that atmospheric visibility was season dependent and would have significant correlations with temperature, the mass concentrations of PM(10) and NO(2), and the air pollution index API (correlation coefficients mid R: R mid R: > or = 0.7, p < or = 0.0001, t test). Mathematical expressions catering to the seasonal variations of atmospheric visibility were thus proposed. By comparison, the proposed visibility prediction models were more accurate than some existing regional models. In addition to improving visibility prediction accuracy, this study would be useful for understanding the context of low atmospheric visibility, exploring possible remedial measures, and evaluating the impact of air pollution and atmospheric visibility impairment in this region.     

Solid phase extraction of Cu(II), Ni(II), Pb(II), Cd(II) and Mn(II) ions with 1-(2-thiazolylazo)-2-naphthol loaded Amberlite XAD-1180

A new method for separation and preconcentration of trace amounts of Cu(II), Ni(II), Pb(II), Cd(II) and Mn(II) ions in various matrices was proposed. The method is based on the adsorption and chelation of the metal ions on a column containing Amberlite XAD-1180 resin impregnated with 1-(2-thiazolylazo)-2-naphthol (TAN) reagent prior to their determination by flame atomic absorption spectrometry (FAAS). The effect of pH, type, concentration and volume of eluent, sample volume, flow rates of sample and elution solutions, and interfering ions have been investigated. The optimum pH for simultaneous retention of all the metal ions was 9. Eluent for quantitative elution was 20 ml of 2 mol l(-1) HNO(3). The optimum sample and eluent flow rates were found as 4 ml min(-1), and also sample volume was 500 ml, except for Mn (87% recovery). The sorption capacity of the resin was found to be 0.77, 0.41, 0.57, and 0.30 mg g(-1) for Cu(II), Ni(II), Cd(II), and Mn(II), respectively. The preconcentration factor of the method was 200 for Cu(II), 150 for Pb(II), 100 for Cd(II) and Ni(II), and 50 for Mn(II). The recovery values for all of the metal ions were > or = 95% and relative standard deviations (RSDs) were < or = 5.1%. The detection limit values were in the range of 0.03 and 1.19 microg l(-1). The accuracy of the method was confirmed by analysing the certified reference materials (TMDA 54.4 fortified lake water and GBW 07605 tea samples) and the recovery studies. This procedure was applied to the determination of Cu(II), Ni(II), Pb(II), Cd(II) and Mn(II) in waste water and lake water samples.     

Online detection of waterborne bioavailable copper by valve daily rhythms in freshwater clam Corbicula fluminea

Freshwater clam Corbicula fluminea, a surrogate species in metal toxicity testing, is a promising bioindicator of impairment in aquatic ecosystems. Little is known, however, about the relationship between clam valve daily rhythmic response and metal bioavailability related to a metal biological early warning system (BEWS) design. The purpose of this study was to link biotic ligand model (BLM)-based bioavailability and valve daily rhythm in C. fluminea to design a biomonitoring system for online in situ detection of waterborne copper (Cu). We integrated the Hill-based dose-time-response function and the fitted daily rhythm function of valve closure into a constructed programmatic mechanism. The functional presentation of the present dynamic system was completely demonstrated by employing a LabVIEW graphic control program in a personal computer. We used site-specific effect concentration causing 10% of total valve closure response (EC10) as the detection threshold to implement the proposed C. fluminea-based Cu BEWS. Here our results show that the proposed C. fluminea-based BEWS could be deliberately synthesized to online in situ transmit rapidly the information on waterborne bioavailable Cu levels under various aquatic environmental conditions through monitoring the valve daily rhythmic changes. We suggested that the developed C. fluminea-based dynamic biomonitoring system could assist in developing technically defensible site-specific water quality criteria to promote more efficient uses in water resources for protection of species health in aquatic environments.     

Risk assessment and distribution of soil Pb in Guangdong, China

In this study, the spatial distributions of soil lead (Pb) concentration in three horizontal soils in Guangdong, China, were surveyed and analyzed using geostatistics and geography information systems (GIS). Findings indicated that the Pb geometric mean concentration of 23.3 mg/kg in surface soils was found to be higher than those in global soils, which ranged from 2.3–235 mg/kg. In addition, the Pb geometric mean concentrations from A- to C-horizon were found to be 23.3, 27.2, and 28.6 mg/kg, respectively. The classification of a soil Pb environmental risk in an area was likewise presented based on the different levels of environmental quality of Pb and was done by GIS technology. Accordingly, there is a higher local concentration of Pb in the surrounding areas of Guangzhou where there is higher population density and in the north of Guangdong, which is a historic mining area. The results obtained by the environmental risk assessment reveal that about 46% of total surveyed area was above the background value, that is, 2.7% of the total area was at risk of pollution.     

Experimental Verification of Diffusion Battery Theory

The diffusion battery, an assembly of circular tubes or rectangular channels, is one of the best devices available for measuring the size and size distribution of submicron aerosols in the diameter range 0.002 to 0.2 µ m. The performance of these batteries is known from molecular diffusion theory, but until now has not been checked experimentally in this size range because of the lack of the necessary monodisperse aerosols. Experimental measurements on singly charged monodisperse aerosols from 0.01 µm to 0.1 µ m are described using a General Electric and a Pollak condensation nucleus counter to measure the aerosol penetration through the stages of a set of portable diffusion batteries in series. Particle sizes in the range tested could be selected at will by adjusting the voltage of an electric mobility classifier. The fraction of aerosol of a given size passing through each battery stage was found to agree closely with the penetration calculated from molecular diffusion theory for that size. This shows that the theory is correct and confirms that the aerosol produced by the electric mobility classifier was monodisperse. In addition, it was found that the difference in penetration between a charged versus a neutralized aerosol was insignificant except for the smallest aerosols used.