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.     

What is the potential measurement error in occupational exposure studies?

This paper demonstrates statistical methods that estimate measurement error from available industrial hygiene data. Errors in measuring a continuous exposure variable may arise when all individuals in a work area are assigned the same exposure. An example is when the mean of exposure measurements obtained on a sample of individuals is assigned to all workers with similar jobs. This may lead to inaccurate point and interval estimates in exposure-response modeling. A method of simulating the distribution of true (i.e., unobserved) individual exposures is described in order to estimate the mean and variance of measurement error. The minimum variance unbiased estimator approximates the mean of lognormally distributed exposure measurements. The distribution of true individual exposures is approximated by the distribution of simulated estimates of mean exposure. The methodology is illustrated by exposure data from work areas manufacturing refractory ceramic fiber (RCF) and RCF products. Results show that exposure is slightly underestimated in work areas with between 25 and 113 exposure measurements; measurement error variance averages about 1.3% of the total variance.     

Carbon disulfide at a Chinese viscose factory external and internal exposure assessment

This article presents the results of carbon disulfide exposure measurements in a Chinese viscose rayon factory. The objectives of the study were to identify the external exposure levels at a large factory and to investigate the 2-thiothiazolidine-4-carboxylic acid (TTCA) concentrations in the urine of the subjects who were exposed to carbon disulfide in the working place atmosphere. The metabolism of carbon disulfide in the exposed subjects was also studied in order to demonstrate the best points in time for the internal exposure sampling. The measurement of the amount of personal exposure to carbon disulfide in the air of the workplace was performed by GC-FPD; the presence of TTCA in the workers urine was analyzed by use of a modified HPLC method. The kinetics of TTCA excretion was studied by analyses at different time-points both during and after exposure to carbon disulfide in the subjects. A total of 155 personal samples were obtained. The carbon disulfide concentration in the staple viscose hall was 13.72 +/- 1.12 mg m-3 in terms of the geometric mean +/- geometric standard deviation, and was 20.05 +/- 1.33 mg m-3 in the filament spinning hall. The TTCA values in the subjects who worked in the staple spinning hall were 1.18 +/- 0.43 mg g-1 creatinine and 1.07 +/- 0.38 mg g-1 creatinine for subjects working in the filament spinning hall. The best time for TTCA sampling is at the end of the working shift, the TTCA excretion was stable for a period of 4-12 h after exposure of the subjects to the carbon disulfide. It might be that the Chinese have different anthropometric characteristics; a sampling bias may therefore appear among different races.