Heavy metal pollution across sites affecting the intestinal helminth communities of the Egyptian lizard, Chalcides ocellatus (Forskal, 1775)

This study aimed to investigate the possible effects of heavy metal pollution across sites and some biological factors on helminth communities infecting the lizard, Chalcides ocellatus. The possibility of heavy metal accumulation by such helminths was also investigated. A total of 202 C. ocellatus were collected from three different sites (industrial, rural, and urban systems) in Ismailia governorate, Egypt, during summer 2009. The lizards were classified according to their sex and size and were examined for the intestinal helminths. Heavy metal levels were detected in the intestinal tissue of the lizards and the recovered helminths. Species richness was 6, 5, and 3 in rural, urban, and industrial systems, respectively. Significant site variations regarding infection prevalence, intensity, and abundance were encountered at different levels. Some noticeable effects of the host size were found. The significant differences found between the metal levels of the intestinal tissues and the recovered helminths and the other relations found in this study may be indications for a possible metals accumulation capacity by helminths. The cestode Oochoristica tuberculata could be a promising biomonitor for Cu and Pb, while the intestinal nematodes were less sensitive to the pollution. Differences in the accumulation capacity may be attributed to the intensity of infection, parasite species, and metal. The observed patterns of distribution and occurrence of helminths and the metals accumulation capacity reflect the need for more studies since this study proposes the model intestinal helminth/C. ocellatus as another promising bioindication system in the terrestrial habitat, especially in areas where the lizard C. ocellatus are available.     

Bio-monitoring for uranium using stream-side terrestrial plants and macrophytes

This study evaluated the abilities of various plant species to act as bio-monitors for environmental uranium (U) contamination. Vegetation and soil samples were collected from a U processing facility. The water-way fed from facility storm and processing effluents was the focal sample site as it represented a primary U transport mechanism. Soils and sediments from areas exposed to contamination possessed U concentrations that averaged 630 mg U kg(-1). Aquatic mosses proved to be exceptional accumulators of U with dry weight (dw) concentrations measuring as high as 12,500 mg U kg(-1) (approximately 1% of the dw mass was attributable to U). The macrophytes (Phragmites communis, Scripus fontinalis and Sagittaria latifolia) were also effective accumulators of U. In general, plant roots possessed higher concentrations of U than associated upper portions of plants. For terrestrial plants, the roots of Impatiens capensis had the highest observed levels of U accumulation (1030 mg kg(-1)), followed by the roots of Cyperus esculentus and Solidago speciosa. The concentration ratio (CR) characterized dry weight (dw) vegetative U levels relative to that in associated dw soil. The plant species that accumulated U at levels in excess of that found in the soil were: P. communis root (CR, 17.4), I. capensis root (CR, 3.1) and S. fontinalis whole plant (CR, 1.4). Seven of the highest ten CR values were found in the roots. Correlations with concentrations of other metals with U were performed, which revealed that U concentrations in the plant were strongly correlated with nickel (Ni) concentrations (correlation: 0.992; r-squared: 0.984). Uranium in plant tissue was also strongly correlated with strontium (Sr) (correlation: 0.948; r-squared: 0.899). Strontium is chemically and physically similar to calcium (Ca) and magnesium (Mg), which were also positively-correlated with U. The correlation with U and these plant nutrient minerals, including iron (Fe), suggests that active uptake mechanisms may influence plant U accumulation.     

Validation of evacuated canisters for sampling volatile organic compounds in healthcare settings

Healthcare settings present a challenging environment for assessing low-level concentrations of specific volatile organic compounds (VOCs) in the presence of high background concentrations of alcohol from the use of hand sanitizers and surface disinfectants. The purposes of this laboratory-based project were to develop and validate a sampling and analysis methodology for quantifying low-level VOC concentrations as well as high-level alcohol concentrations found together in healthcare settings. Sampling was conducted using evacuated canisters lined with fused silica. Gas chromatography/mass spectrometry analysis was performed using preconcentration (for ppb levels) and loop injection (for ppm levels). For a select list of 14 VOCs, bias, precision, and accuracy of both the preconcentration and loop injection methods were evaluated, as was analyte stability in evacuated canisters over 30 days. Using the preconcentration (ppb-level) method, all validation criteria were met for 13 of the 14 target analytes-ethanol, acetone, methylene chloride, hexane, chloroform, benzene, methyl methacrylate, toluene, ethylbenzene, m,p-xylene, o-xylene, alpha-pinene, and limonene. Using the loop injection (ppm-level) method, all validation criteria were met for each analyte. At ppm levels, alpha-pinene and limonene remained stable over 21 days, while the rest of the analytes were stable for 30 days. All analytes remained stable over 30 days at ppb levels. This sampling and analysis approach is a viable (i.e., accurate and stable) methodology that will enable development of VOC profiles for mixed exposures experienced by healthcare workers.     

A Multiple Criteria Decision Analysis Model Based on ELECTRE TRI-C for Erosion Risk Assessment in Agricultural Areas

This paper deals with a real-world decision-aiding problem for zoning the risk of erosion, total suspended solids emissions, and ecological consequences of their transfers towards the streams. One of these consequences is the decrease of fishes into the streams in agricultural watersheds, because of the clogging of spawning areas. Given the multiple criteria nature of the problem, the originality of our research is to adapt a new decision-aiding sorting method, ELECTRE TRI-C, for identifying risk zones in rural areas, where measures must be taken. The developed model was applied in a small watershed (Low Normandy, France) where the objective was to assess the most appropriate intervention for protecting the reproduction habitat of the salmonid fishes. Agricultural parcels were evaluated on multiple criteria for grouping them into four risk categories, which are related to risk levels as well as priorities on the improvement works. The decision-aiding sorting model is co-constructed, within a constructive approach, through an interaction process between decision-aiding analysts, environmental experts, and local actors for improving transparency and communication on the results. This model is linked with a geographical information system (GIS) for assessing a set of criteria and the visualization of the farming parcels along with their type of intervention they should be submitted to best practices. The assignment results were validated by the environmental experts. These results have a strong impact on the agricultural practices of the farmers into the watersheds. The model proposed in this paper can be considered as a useful decision aid tool in any regions for implementing public agricultural and environmental policies for protecting the ecological areas.     

Large and mesoscale meteo-oceanographic patterns in local responses of biogeochemical concentrations

Investigations surrounding the variability of productivity in upwelling regions are necessary for a better understanding the physical-biological coupling in these regions by monitoring systems of environmental impacts according to the needs of the regional coastal management. Using a spatial and temporal database from National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric (NCAR) Research reanalysis, Quick Scatterometer vector wind, and surface stations from the Southeast coast of Brazil, we investigate the meteorological influences due to the large-scale systems in the variability of the nutrient and larvae concentration, and chlorophyll a, describing statistically relationships between them in upwelling regions. In addition, we used multivariate analysis, such as PCA and clustering to verify spatial and temporal variances and describe more clear the structure and composition of the ecosystem. Correlation matrix analyses were applied for different water masses present in the study area to identify the relations between physical and biogeochemical parameters in a region, where frequently upwelling occur. Statistical approaches and seasonal variability show that the period of November to March is more sensitive to nutrients (1.20?mg/m(3) for chlorophyll a, 2.20?μmol/l for total nitrogen and 5.5?ml/l for DO) and larvae concentrations (120 org/m(3) for most of the larvae, except for cirripedia that presented values around 370 org/m(3)) relating to the influence of large and mesoescale meteorological patterns. The spatial and temporal variables analyzed with multivariate approach show meaningful seasonality variance of the physical and biological samples, characterizing the principal components responsible for this variance in spring and summer (upwelling period), emphasizing the monitoring of species as crustaceans and mussels that are present in the local economy. Then, the spring and summer season are characterized by high productivity due to the occurrence of upwelling in this period.     

Long-term seasonal changes of the Danube River eco-chemical status in the region of Serbia

Seasonal spatial and temporal changes of selected eco-chemical parameters in section of the Danube River flowing through Serbia were analyzed. Data for electrical conductivity (EC), dry and suspended matter, residue on ignition, chemical oxygen demand (COD), biochemical oxygen demand (BOD-5), ultraviolet extinction, dissolved oxygen (DO), oxygen saturation, pH, nitrates, total phosphorus, and nitrogen were collected between 1992 and 2006. The use of monthly medians combined with linear regression and two-sided t test has been proven to be the best approach for resolving trends from natural variability of investigated parameters and for determining trend significance. Patterns of temporal changes between different months were examined. It was also determined that spatial trends of some parameters oscillate in predictable manner, increasing in one part of the year and declining in the other. Regression slope coefficients, an excellent indicator for determining when the water quality is changing the most along the course of the Danube, reach their maximum during summer for temperature (t), electric conductivity, nitrates, and total N, while in the same season suspended matter, COD, BOD-5, DO, and oxygen saturation coefficients reach their minimum. Correlations for used data sets of selected parameters were analyzed for better understanding of their behavior and mutual relations. It was observed that as Danube flows through Serbia, its general eco-chemical status either stagnates or improves, but the rate of river self-purification often depends on the season of the year.     

Fish scales as indicators of wastewater toxicity from an international water channel Tung Dhab drain

The effect of wastewater exposure on scales and chromatophores of freshwater fish Channa punctatus was studied using wastewater dilutions (60–100%) from an international water channel Tung Dhab drain at an interval of 15 and 30 days. The exposed fish showed significant alterations such as uprooted and damaged lepidonts and dispersal of chromatophores. These observations strongly suggest that fish scales can be successfully employed as indicators of wastewater pollution.     

Groundwater contamination evolution in the Guadiamar and Agrio aquifers after the Aznalcóllar spill: assessment and environmental implications

In 1998, the Agrio and Guadiamar rivers underwent an enormous environmental disaster caused by the rupture of the Aznalcóllar tailings dam and the release of 6 hm³ of pyrite sludge and acidic water. Both rivers run over recent alluvial materials which form a small-sized aquifer which is however important because underground water feeds the flow of the rivers. This work analyzes the state of groundwater 10 years after the spill. Before the dam failure, this aquifer was already contaminated in the zone nearest to the mine, to which the impact of the spill was added. Contamination levels in the alluvial aquifer of the Agrio River have decreased remarkably. However, they are still important, with acidic pH values and high concentrations of toxic elements (maximum values of 16 mg/L of Zn and 15 mg/L of Al). There are also important levels of contamination in the Guadiamar alluvial area closest to the mine, as well as in specific zones located further south. The concentration of toxic elements is mainly controlled by pH. The evolution of contaminant levels show a sharp decrease after the first years following the spill, followed by a subsequent stabilization. It is necessary to take measures for the recovery of the aquifer because, otherwise, groundwater will continue contributing contaminants into the Agrio and Guadiamar rivers.     

Development of geomorphologic instantaneous unit hydrograph for a large watershed

Hill torrents cause a lot of environmental and property damage in Pakistan every year. Proper assessment of direct runoff in the form of hill torrents is essential for protection of environment, property, and human life. In this paper, direct surface runoff hydrograph (DSRH) was derived for a large catchment using the geomorphologic instantaneous unit hydrograph concept. The catchment with hill torrent flows in semi-arid region of Pakistan was selected for this study. It was divided into series of linear cascades and hydrologic parameters required for Nash's conceptual model, and were estimated using geomorphology of the basin. Geomorphologic parameters were derived from satellite images of the basin and ERDAS and ArcGIS were used for data processing. Computer program was developed to systematically estimate the dynamic velocity, its related parameters by optimization and thereby to simulate the DSRH. The data regarding rainfall-runoff and satellite images were collected from Punjab Irrigation and Power Department, Pakistan. Model calibration and validation was made for 15 rainfall-runoff events. Ten events were used for calibration and five for validation. Model efficiency was found to be more than 90% and root mean square error to be about 5%. Impact of variation in model parameters (shape parameter and storage coefficient) on DSRH was investigated. For shape parameter, the number of linear cascades varied from 1 to 3 and it was found that the shaper parameter value of 3 produced the best DSRH. Various values of storage coefficient were used and it was observed that the value determined from geomorphology and the dynamic velocity produced the best results.     

A survey on the utility of the USEPA CADDIS stressor identification procedure

The Environmental Protection Agency (EPA) has made available on the worldwide web a systematic stream stressor identification procedure, the “Causal Analysis/Diagnosis Decision Information System” or CADDIS. We report here the results of a survey of regulators and scientists in 11 states who use CADDIS or another stressor identification procedure in their work. The 13 survey questions address guidelines as to what impairment scenarios to approach with stressor identification, what information is needed to perform stressor identification, and what the stakeholder role is in performing stressor identification. At the time of this survey (the summer of 2009), the EPA CADDIS website was less commonly used among the state regulators surveyed than the published EPA stressor identification document on which it is based. The respondents generally find the EPA stressor identification procedure useful and capable of being adapted to their individual needs. Survey respondents all use stressor identification in their Total Maximum Daily Load work, but also in a wide variety of other applications. All the “types of evidence” included in the CADDIS stressor identification procedure are used by the practitioners surveyed with the exception of the results of ecological simulation models. While the CADDIS documentation encourages the involvement of stakeholders in stressor identification, most respondents do not assemble stakeholder teams of local officials and citizens to participate in stressor analyses.