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1.
Med Lav ; 95(3): 198-210, 2004.
Article in Italian | MEDLINE | ID: mdl-15293376

ABSTRACT

BACKGROUND: Occupational noise exposure can be monitored directly by personal sampling or indirectly, by area sampling. Personal sampling is performed using an integrating sound level meter, worn by the worker while performing his/her job. When area sampling is used, measurements need to be made in all locations where a typical worker stays while performing his/her tasks; the respective partial lengths of exposure need to be accurately monitored, and the time-weighted average sound level of the measured noise levels must be calculated. OBJECTIVES: Current regulations identify three different thresholds, corresponding to different types of action, but they do not propose any standard criteria to decide whether a threshold has been exceeded. Defining standard procedures to assess occupational noise exposure and identifying such thresholds is crucial. METHODS: Using empirical data collected in the field, the effects are illustrated of the number of sampling locations and of the partial lengths of exposure on area sampling measurements, and the effects of duration of noise exposure on both area and personal samplings. RESULTS: When dealing with area samplings, an accurate definition of both sampling locations and partial lengths of exposure is crucial. When arbitrary decisions are taken in selecting sampling locations and/or establishing partial lengths of exposure, spatial changes in noise level and operator' displacements while performing his/her tasks may affect results. Sampling for less than the duration of noise exposure is the major contributor to measurement error, particularly under conditions of unpredictable variation in noise level. In fact, as noise level in the non-monitored time fraction is unknown, measurement error cannot be determined. We estimate that, even under the most favorable circumstances, sampling should last not less than 40% of the duration of a given noise-generating occurrence, for repeated measurements to be dispersed within a range not wider than that generated by the instrumental error. Inter-daily variability is another important aspect in personal noise exposure evaluation. This is a general occurrence, whose effects cannot be controlled by simply considering weekly instead of daily exposures. Results of an investigation, covering about 60 different jobs within a primary aluminum plant, show an inter-daily variability in noise exposure greater than 5 dBA in about 75% of cases. CONCLUSIONS: Personal sampling, when correctly performed and covering the total duration of exposure, provides the most reliable result as it integrates noise over all locations where the worker actually stays while performing his/her tasks, and over the total length of time spent in each task. We propose extending personal sampling to the total duration of actual noise exposure as the standard procedure for monitoring daily personal noise exposure, and valid for the majority of work places. When the range of daily noise exposure includes one regulatory threshold, corresponding to a given type of action, we propose as a standard decision criterion to refer prudentially to the upper 95% confidence limit of the LEP,d arithmetic mean. Such criterion would allow to standardize procedures and decision methods, with the prospect of further improvements in the assessment of exposure to noise.


Subject(s)
Noise, Occupational/statistics & numerical data , Occupational Exposure/statistics & numerical data , Humans , Italy , Noise, Occupational/legislation & jurisprudence , Occupational Exposure/legislation & jurisprudence , Research Design , Time Factors
2.
Med Lav ; 88(1): 37-48, 1997.
Article in Italian | MEDLINE | ID: mdl-9229673

ABSTRACT

Personal monitoring of noise exposure was conducted in a small dry dock, where mainly tug-boats and high sea fishing-boats are refitted. Manual tools were the prevalent noise sources. Noise exposure could be affected and amplified by factors extraneous to workers' tasks. The workers might be employed in different jobs simultaneously also in confined and small areas, and were mainly involved in non-routine tasks. Six different tasks were investigated: dry-dock supervisor, welder/ship-wrights, painters, electricians, woodworkers and unskilled workers. The number of workers employed in the tasks, with the exclusion of the supervisor, might change from day to day according to the particular work phase carried out on the boat. Daily personal exposure was measured using Larson Davis mod. 700 integrating sound level meters. The all shift time history of short equivalent continuous sound level with 10 s integrating time was collected for each selected worker. A 1/2 inch microphone was attached to the helmet at a distance of 11 +/- 1 cm from the right outer ear. Measurements were repeated over 13 days and randomly distributed over about four months. The number of data-points collected was nine for the supervisor, twenty-seven for the welders, eighteen for the painters, twelve for the electricians, six for the woodworkers and eleven for the unskilled workers. Ranges of the daily noise exposure level were from 15 to 30 dBA for all tasks, with the exclusion of the woodworkers. The time histories relative to workers grouped in the same task were matched to verify the correlation. The daily exposure levels derived from correlated samples were substituted by their arithmetic mean. The analysis of variance applied to experimental distributions of daily exposure for four of the welders indicates that the difference of means (p > 0.3) is not significant. A similar conclusion is reached for painters when only this task is considered. If we take into account the exposures of painters employed also in different tasks, the probability is included in a range of lower significance, between 0.1 and 0.05. The experimental distributions of daily noise exposure for all tasks fit the normal distribution. The Kolmogorov-Smirnov test was used at a p > 0.1 confidence level. These results may have an important role in defining sampling strategies for collecting noise exposure data both for compliance and epidemiological purposes.


Subject(s)
Noise, Occupational , Occupations , Ships , Confidence Intervals , Data Interpretation, Statistical , Humans , Male , Time Factors
3.
Med Lav ; 83(3): 278-88, 1992.
Article in Italian | MEDLINE | ID: mdl-1528166

ABSTRACT

A criterion is proposed for planning personal noise exposure surveys. For measurements taken at random over entire work shifts, the aim is to achieve preset confidence limits of the arithmetic mean of daily personal exposure (i.e., +/- 2 dBA or +/- 1 dBA). Five or six measurements are sufficient to estimate the standard deviation. By following simple rules to calculate the confidence limits for a population with unknown variance, it is possible to fix the number of measurements N with sufficient accuracy to achieve this goal. This number is a function of daily personal exposure variability. The choice of the confidence limits determines the accuracy of the personal noise exposure assessment, provided that it is the exponential mean of N measurements. This method allows the survey to be planned according to the desired accuracy of the final result. An example is provided of a survey carried out in a refractory brick factory, which shows that if the daily personal exposure range is 4-6 dBA, a 5-measurement survey is sufficient to achieve a +/- 2 dBA confidence interval, while 10-12 measurements are necessary to achieve a +/- 1 dBA confidence interval. If the range is 14-15 dBA the same results are achieved with 12-14 measurement in the first case and with about 50 in the second. The latter results shows that if the survey is stopped after 5 measurements, the probability of accepting a value of integrated personal noise exposure outside the N-integrated +/- 1 dBA range may reach 50%, mainly among groups of workers with greater variability in daily exposure.


Subject(s)
Noise, Occupational , Analysis of Variance , Confidence Intervals , Humans , Methods , Noise, Occupational/adverse effects , Noise, Occupational/statistics & numerical data
4.
Med Lav ; 81(2): 96-100, 1990.
Article in Italian | MEDLINE | ID: mdl-2250614

ABSTRACT

In acoustic free fields the human body changes the energy distribution surrounding it, mainly under narrow band or pure tone noise conditions. Hence, sound levels measured close to the body should be intrinsically incorrect if performed via personal sampling. An experiment was carried out to verify whether this statement is still valid in a diffuse field, such as occurs in industrial workplaces. Noise measurements were made in diffuse field laboratory conditions without the presence of a person (steady state) and were repeated close to the ear of a person (perturbed state). The measurements were carried out with integrating precision sound level meters and also with personal noise dose meters. The trials were repeated in an industrial environment. The states 1/3 octave band levels were matched, as also were the equivalent continuous levels. These findings show that in diffuse fields the human body does not significantly affect equivalent continuous level measurements performed near the body. The mean differences between equivalent continuous levels measured by sound level meter were less than 0.3 dBA, and ranged from -0.6 to 0 dBA between levels measured by sound level meter and by personal noise dose meter. The results of the trial performed in the plant showed closer differences between steady and perturbed states and between sound level meter and personal noise dose meter measurements.


Subject(s)
Noise, Occupational , Ear , Humans , Weights and Measures
6.
G Ital Med Lav ; 4(4-5): 181-6, 1982.
Article in Italian | MEDLINE | ID: mdl-7185632

ABSTRACT

We present the most interesting results of an environmental survey carried out in a factory producing steel-cord. On the basis of our data it results that the most important risks are due to the exposition to noise, to microclimate (particularly during summer) and to some gaseous pollutants which are present only in some departments. We briefly analyse the main lines of technical prevention.


Subject(s)
Environmental Pollutants , Metallurgy , Occupational Diseases , Dust , Gases , Hot Temperature , Humans , Humidity , Noise , Risk
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