Suchergebnisse

Abstract
The waste management sector takes a central part in the transition towards circular economy and is subject to technological progress and the implementation of new work operations. Traditional waste collection and processing systems are characterized by numerous tasks that favour waste workers' exposure to bioaerosols, whereas exposure in modern automated waste sorting plants remains elusive. Moreover, there is still a lack of health-risk based exposure limits for most components contained in bioaerosols. We investigated occupational exposure to bioaerosols in traditional and automated waste sorting plants. The results revealed significant differences in various exposure levels, such as total dust (GM automated: 0.34 mg/m3, GM manual: 0.66 mg/m3), endotoxins (GM automated: 51 EU/m3, GM manual: 32 EU/m3) and microorganisms between and within type of plant. An assessment of the composition of air-borne fungal particles (FESEM based immunodetection method) showed significantly increased levels of fungal spores at automated waste sorting plants (GM automated: 1.2 × 105 spores/m3, GM manual: 2.1 × 104 spores/m3). Elevated total dust levels and concentrations of submicronic fungal fragments were significantly correlated to the occurrence of symptoms of the extrathoracic region, such as congested nose, in exposed workers. The results of this study showed high variation in exposure levels between and within type of waste sorting plant, as well as seasonal variation for some parameters, such as total dust and endotoxins. This indicates that Norwegian waste workers are potentially exposed to high levels of dust and microorganisms that may cause adverse health effects in receptible individuals.

Abstract

Objectives
Sawmill workers have an increased risk of adverse respiratory outcomes, but knowledge about exposure–response relationships is incomplete. The objective of this study was to assess exposure determinants of dust, microbial components, resin acids, and terpenes in sawmills processing pine and spruce, to guide the development of department and task-based exposure prediction models.


Methods
2474 full-shift repeated personal airborne measurements of dust, resin acids, fungal spores and fragments, endotoxins, mono-, and sesquiterpenes were conducted in 10 departments of 11 saw- and planer mills in Norway in 2013–2016. Department and task-based exposure determinants were identified and geometric mean ratios (GMRs) estimated using mixed model regression. The effects of season and wood type were also studied.


Results
The exposure ratio of individual components was similar in many of the departments. Nonetheless, the highest microbial and monoterpene exposure (expressed per hour) were estimated in the green part of the sawmills: endotoxins [GMR (95% confidence interval) 1.2 (1.0–1.3)], fungal spores [1.1 (1.0–1.2)], and monoterpenes [1.3 (1.1–1.4)]. The highest resin acid GMR was estimated in the dry part of the sawmills [1.4 (1.2–1.5)]. Season and wood type had a large effect on the estimated exposure. In particular, summer and spruce were strong determinants of increased exposure to endotoxin (GMRs [4.6 (3.5–6.2)] and [2.0 (1.4–3.0)], respectively) and fungal spores (GMRs [2.2 (1.7–2.8)] and [1.5 (1.0–2.1)], respectively). Pine was a strong determinant for increased exposure to both resin acid and monoterpenes. Work as a boilerman was associated with moderate to relatively high exposure to all components [1.0–1.4 (0.8–2.0)], although the estimates were based on 13–15 samples only. Cleaning in the saw, planer, and sorting of dry timber departments was associated with high exposure estimates for several components, whereas work with transportation and stock/finished goods were associated with low exposure estimates for all components. The department-based models explained 21–61% of the total exposure variances, 0–90% of the between worker (BW) variance, and 1–36% of the within worker (WW) variances. The task-based models explained 22–62% of the total variance, 0–91% of the BW variance, and 0–33% of the WW variance.


Conclusions
Exposure determinants in sawmills including department, task, season, and wood type differed for individual components, and explained a relatively large proportion of the total variances. Application of department/task-based exposure prediction models for specific exposures will therefore likely improve the assessment of exposure–response associations.