The effect of EDTA and fulvic acid on Cd, Zn, and Cu toxicity to a bioluminescent construct (pUCD607) of Escherichia coli

The hypothesis, that metal toxicity is dominated by free ion activity, was tested by comparing calculated metal activities with measured toxic responses to a genetically modified, luminescent bacterium, Escherichia coli. The toxicity of Cd, Cu, and Zn sulphate salts in the presence of EDTA and fulvic acid in well-defined solutions was measured. Good agreement between free metal activity and toxicity was found for Cu but not for Zn and Cd. The toxicity relationships were altered by glucose addition to the organism. Stable chloride complexes may have contributed to the toxicity of Cd under the test conditions. The results suggest that there is not always a simple relationship between toxicity and free-ion metal concentration and that further account should be taken of competitive interactions between living cells and ligands and the physiological status of the organism.     

Uptake of dioxin-like compounds from sewage sludge into various plant species--assessment of levels using a sensitive bioassay

A bioassay for the detection of dioxin-like compounds was used to estimate uptake of dioxin-like compounds in carrots, oil seed rape seeds, zucchinis and cucumbers grown in soil amended with sewage sludge from Swedish sewage treatment plants (STP). This sensitive bioassay is based on 7-ethoxyresorufin O-deethylase (EROD)-induction in cultured chicken embryo livers and reflects the combined biological effect of all dioxin-like compounds in a sample, including ones that seldom are analyzed. The bioassay detected low concentrations of dioxin-like compounds in all carrot, zucchini and cucumber samples, but did not detect any dioxin-like compounds in the rape seeds. In carrots the concentrations were increased up to seven times when grown in soil amended with high applications of some of the sludge samples, while others did not increase the concentrations compared to control. More realistic sludge applications only increased the concentrations slightly. The sludge-fertilized carrots contained the highest concentrations of the investigated plants (up to 14 pg bioassay-derived TCDD equivalents (bio-TEQs)/g d.w.). In the carrots, differences in uptake of dioxin-like compounds depended on the sludge origin, which may be due to more easily bioaccumulated dioxin-like compounds in some sludge samples, or other components that facilitated uptake into the carrots. In the cucumbers, a more than two-fold increase (from 0.2 to 0.5 pg bio-TEQs/g d.w.) was observed in specimens grown in sludge-amended soil when compared to controls, suggesting a small uptake from the roots to the shoots. No sludge-dependent increase in uptake was seen in the zucchini fruits. The bio-TEQ levels were generally low in the consumable above ground plant parts of the investigated species. However, the question if repeated sludge application results in a soil accumulation of dioxin-like compounds, thereby increasing the risk of plant uptake, remains to be investigated.     

Separation of toxaphene by high resolution gas chromatography

A summary is given about the separation of toxaphenes by high resolution gas chromatography (HRGC). The suitability of different stationary phases for isomer and/or enantiomer-selective separations is compared. Multidimensional and tandem techniques are also presented. In addition, problems caused by thermal degradation in the injector and on the column are addressed. Furthermore, a brief survey is included about detection methods such as electron capture detection and different mass spectrometric methods.     

The influence on partial order ranking from input parameter uncertainty. Definition of a robustness parameter

The method of partial order ranking has been used within the environmental area for a variety of purposes as an attractive way of handling complex information. However, the environmental data are often associated with a significant degree of uncertainty. In this investigation the general nature of the influence from data uncertainty on the partial order ranking is analyzed. A Monte Carlo type analysis is performed in which a series of randomly formed data are used to test the influence of data uncertainty. The partial order ranking is interpreted, where the results are transferred to a one-dimensional ranking scale taking into account that not all elements are ranked with the same certainty. A simple general robustness parameter (E) in form of the expected number of comparisons for each ranking element is defined and correlated to the uncertainty analysis results. A simple equation relates E to the number of elements and the number of parameters, respectively. The magnitude of the ranking uncertainty is shown to increase rapidly when the E value decreases below 4-5 comparisons per element. When the E value exceeds 5 the ranking uncertainty becomes nearly constant and independent on the actual E value.     

Application of a purge and trap TDS-GC/MS procedure for the determination of emissions from flame retarded polymers

Emissions of volatile organic compounds (VOCs) from different thermoplastic polymers used in electrotechnical applications were investigated using a purge and trap procedure that involved adsorption on Tenax GR. Results were compared to those for an operating TV set monitored in a test chamber. The analyses were in both cases carried out using thermodesorption gas chromatography with mass spectrometric detection (TDS-GC/MS). Substances identified were monomers, volatile additives, or related compounds. Special attention was given to the detection of halogenated compounds. Their origin was studied using reference samples and synthetic standards.     

Structural study on inclusion complexes of cyclodextrins with organophosphorus pesticides by use of rotational strength analysis method

For inclusion complexes of cyclodextrins with parathinons and paraoxon, inclusion depths were estimated with the rotational strength analysis method. The inclusion depths of pesticides were sensitive to the difference in the hydrophobic properties of the phosphate and monothiophosphate groups and were in close correlations with the substrate-specificity for the cyclodextrin-catalyzed hydrolysis of pesticides. The inclusion depths were also characteristically affected by surfactant material having high solubilization functions to aquatic environmental chemicals.     

An evaluation of three empirical air-to-leaf models for polychlorinated dibenzo-p-dioxins and dibenzofurans

Three empirical air-to-leaf models for estimating grass concentrations of polychlorinated dibenzo-p-dioxins and dibenzofurans (abbreviated dioxins and furans) from air concentrations of these compounds are described and tested against two field data sets. All are empirical in that they are founded on simplistic bioconcentration and related approaches which rely on field data for their parameterization. One of the models, identified as the EPA Model, partitions the total air concentration into vapor and particle phases, and separately models the impact of both. A second model addresses only the vapor phase; grass concentrations are modeled as a function of vapor deposition. For the third model, it is assumed that the grass plants "scavenge" a fixed volume of air of dioxins, and hence grass concentrations are modeled as a simple product of total air concentration and a constant scavenging coefficient. Field data from two sites, a rural and an industrial site in the United Kingdom, included concurrent measurements of dioxins in air and field grass, and dioxin and furan depositions, for one 6-week sampling period. Principal findings include: (1) the EPA Model underpredicted grass concentrations at the rural field site by a factor of 2, while the Scavenging Model underpredicted grass concentrations by a factor of 3.8, and the Vapor Deposition Model significantly underpredicted grass concentrations (by a factor greater than 10), (2) the presence of high soil concentrations for some of the dioxins and furans at the industrial site appears to have caused higher grass concentrations and confounded the air-to-plant modeling exercise, (3) the Scavenging Model could be calibrated to the data set; however, a key premise of this model that vapor and particle phase dioxins equally impact the plants, is not supported by the field data, (4) measured depositions are highly correlated to but systematically lower than modeled depositions, which could be due to modeling assumptions or a systematic measurement bias.     

Application of a stochastic, Weibull probability generator for replacing missing data on ambient concentrations of gaseous pollutants

A stochastic, three-parameter, Weibull frequency distribution, probability generator was tested by using theoretical data. Subsequently, it was applied to replace missing values of hourly atmospheric concentrations of trace gases that were continuously monitored at three study sites, for 2 years. The results were highly accurate and realistic. The cumulative means and the medians calculated by the Weibull method were intermediate between corresponding values calculated by uniform substitution of missing values with 'zero' or with half of the minimum detection limit of the appropriate measurement instrument used. Furthermore, the Weibull method allowed the replacement of as many as 100 missing values on either side of a measured data sub-set, without altering the overall characteristics of the true frequency distribution of the entire data set.     

Determination of Q1, an unknown organochlorine contaminant, in human milk, Antarctic air, and further environmental samples

Q1, an organochlorine component with the molecular formula C(9)H(3)Cl(7)N(2) and of unknown origin was recently identified in seal blubber samples from the Namibian coast (southwest of Africa) and the Antarctic. In these samples, Q1 was more abundant than PCBs and on the level of DDT residues. Furthermore, Q1 was more abundant in seals from the Antarctic than the Arctic. To prove this assumption, gas chromatography-electron-capture negative ion mass spectrometry (GC/ECNI-MS), which is sensitive and selective for Q1, allowed for screening of traces of Q1 even in samples with particularly high levels of other organochlorine contaminants. Q1 was isolated by high-performance liquid chromatography (HPLC) from a skua liver sample. A 1:1 mixture with trans-nonachlor in electron-capture detectors (ECDs) was used to determine the relative response factor with ECNI-MS. The ECNI-MS response of Q1 turned out to be 4.5 times higher than that of trans-nonachlor in an ECD. With GC/ECNI-MS in the selected ion-monitoring mode, four Antarctic and four Arctic air samples were investigated for the presence of Q1. In the Antarctic air samples, Q1 levels ranged from 0.7 to 0.9 fg/m(3). In Arctic air samples, however, Q1 was below the detection limit (<0.06 fg/m(3) or 60 ag/m(3)). We also report on high Q1 levels in selected human milk samples (12-230 microg/kg lipid) and, therefore, suggested that the unknown Q1 is an environmental compound whose origin and distribution should be investigated in detail. Our data confirm that Q1 is a bioaccumulative natural organochlorine product. Detection of a highly chlorinated natural organochlorine compound in air and human milk is novel.     

Monitoring, modelling and environmental exposure assessment of industrial chemicals in the aquatic environment

Monitoring and laboratory data play integral roles alongside fate and exposure models in comprehensive risk assessments. The principle in the European Union Technical Guidance Documents for risk assessment is that measured data may take precedence over model results but only after they are judged to be of adequate reliability and to be representative of the particular environmental compartments to which they are applied. In practice, laboratory and field data are used to provide parameters for the models, while monitoring data are used to validate the models' predictions. Thus, comprehensive risk assessments require the integration of laboratory and monitoring data with the model predictions. However, this interplay is often overlooked. Discrepancies between the results of models and monitoring should be investigated in terms of the representativeness of both. Certainly, in the context of the EU risk assessment of existing chemicals, the specific requirements for monitoring data have not been adequately addressed. The resources required for environmental monitoring, both in terms of manpower and equipment, can be very significant. The design of monitoring programmes to optimise the use of resources and the use of models as a cost-effective alternative are increasing in importance. Generic considerations and criteria for the design of new monitoring programmes to generate representative quality data for the aquatic compartment are outlined and the criteria for the use of existing data are discussed. In particular, there is a need to improve the accessibility to data sets, to standardise the data sets, to promote communication and harmonisation of programmes and to incorporate the flexibility to change monitoring protocols to amend the chemicals under investigation in line with changing needs and priorities.