Biomedical subjects

P S Vinzents

Publications and source records attributed to P S Vinzents.

6 recordsLinked to original sources

PubMed2002

Passive sampler used for simultaneous measurement of breathing zone size distribution, inhalable dust concentration and other size fractions involving large particles.

The particle size-dependent sampling velocity of the passive dust sampler developed by Vinzents (1996) is investigated under field conditions. Microscopical determination of the projected area equivalent diameter is used to quantify particles deposited on the sampler foils. Parameters for a semi-empirical model for particle deposition velocities on upward and forward facing foils are fitted to the data and it is shown that deposition mechanisms other than gravitational settling on the upward facing foil can be neglected. For calculation of airborne mass concentration no information on particle density is needed and only the ratio between the dynamic and volume shape factors needs to be known. Given the sampling velocity, the airborne mass per diameter interval is calculated from samples obtained in the wood industry, from which inhalable dust concentrations are calculated. The results are in line with parallel samples obtained with an inhalable dust sampler. A 'total' dust sampling characteristic can be fitted which reproduces measured 'total' dust with a closed face monitor. The results of this study demonstrate the validity of the passive dust sampling principle in environments involving even large (>100 microm) particles and the potential to predict the concentration of several size fractions.

Air Pollutants, Occupational↗

PubMed2001

Wood dust exposure in the Danish furniture industry using conventional and passive monitors.

A study of wood dust exposure at furniture factories in one county in Denmark was performed as a cross sectional study. Dust exposure was measured with personal passive dust monitors and calibrated against active sampling on filters. Measurements of 1685 workers were included in the exposure assessment. The passive dust monitor conversion models for equivalent concentrations of inhalable dust and total dust based on data from the present study were not significantly different from the original models. Therefore models based on all available data were used. The parameters of the distribution of equivalent concentration of inhalable dust were 0.94 mg/m3 (geometric mean) and 2.10 (geometric standard deviation). Compared with a national cross sectional study from 1988 the exposure level (geometric mean) was reduced by a factor 2.0. Inhalable dust exposure was about 50% higher than exposure measured by the Danish 'total' dust method.

Air Pollutants, Occupational↗

PubMed2001

Variations in exposure to inhalable wood dust in the Danish furniture industry. Within- and between-worker and factory components estimated from passive dust sampling.

Variability of exposure to wood dust at large factories in the Danish furniture industry was studied. Three repeated exposure measurements of 292 workers at 38 factories were included in the study. The measurements were carried out by use of personal passive dust monitors. The components of variance were estimated by means of a random effects ANOVA model. The ratio of within- to between-worker variance was 1.07. Based on this result, and three repeated exposure measurements, the observed relation between health outcome and exposure will be attenuated to 74% of the true value. Grouping by factory showed very poor exposure contrast, as the contrast in exposure level among factories was as low as 0.15.

Air Pollutants, Occupational↗

PubMed1995

A method for establishing tentative occupational exposure limits for inhalable dust.

Four-fold classification tables are used on five datasets containing 112 parallel personal measurements of total dust and inhalable dust. The classification are carried out in such a way that the frequency of non-compliance is equal for total dust and inhalable dust. The results can be used as tentative occupational exposure limits (OELs) for inhalable dust, and the results range from 0.7 to 3.4 of OELs for total dust. The results depend on the industry and the content of the dust.

Dust↗

PubMed1994

Mass distribution of inhalable aerosols in swine buildings.

Nine measurements of mass distributions of inhalable aerosols in swine buildings were performed at two pig breeding farms using personal sampling. The overall log-normal mass distribution was: geometric mean = 26 microns aerodynamic diameter, and geometric standard deviation = 2.9. No differences in parameters of mass distributions were found, but the concentration of inhalable aerosol was decreased at the farm where fat had been added to the feed. The aerosols reported in this study were coarser than those reported in earlier studies.

Aerosols↗

PubMed1991

Bias and random errors in historical data of exposure to organic solvents.

The biases and random errors in data from industrial hygiene measurements have been evaluated. Such data are often used for exposure assessment in epidemiologic studies by people who are not professional industrial hygienists. The quality of such data is, therefore, of paramount importance. Data sets from two investigations of the exposure to organic solvents in the same industry have been analyzed. The study shows that the errors and analysis of field samples are larger than errors determined from laboratory data but smaller than errors from other sources. One exception, in which laboratory errors are large, is when data originate from different ways of determining recovery. Very large biases may arise for certain combinations of analytes and extraction liquid when the "equilibrium method" is used. The data sets from the two investigations had a bias, which was as large as a factor of 5 to 10. This bias is believed to be caused by use of two different sampling strategies. In all industrial hygiene data, large random errors are embedded because of day-to-day variations in exposure levels; therefore, the data are mostly used grouped into three classes of low, medium, and high exposure. To do so is meaningful, as a large amount of data will compensate for misclassifications. But a large amount of data cannot compensate for the bias introduced when merging data generated under different sampling strategies. Data describing the same object, but originating from different sampling strategies, should not be pooled without proper tests, which show that data are comparable.(ABSTRACT TRUNCATED AT 250 WORDS)

Bias↗