RESUMO
Occupational exposure to respirable crystalline silica (RCS) is common for several occupations in construction, not only because of its presence in many handling materials but also in processes such as grinding and sawing. This study investigated workplace exposure to RCS as quartz in industries and occupations within road construction in Alberta through the RCS monitoring database provided by the Alberta Roadbuilders and Heavy Construction Association (ARHCA) between 2007 and 2016. Descriptive statistics were calculated for exposure-related variables, and mixed model analysis was performed to determine factors affecting the exposure levels. Results showed that the highest exposed workers were in the sand and gravel industry (GM = 45 µg/m3). For worker occupations, geometric means ranged from 78 µg/m3 for crusher operators to 10 µg/m3 for concrete truck operators. The maximum exposure severity was 33.3 times the occupational exposure limit (OEL) for the sand and gravel and 31 times the OEL for tower operators. The results also showed the effect of seasonal variability on RCS exposure levels. The heterogeneous exposure results indicated significant room for improvement and that controls should focus more on the activity performed than the occupation to lower exposure to RCS levels in industries.
Assuntos
Poluentes Ocupacionais do Ar , Indústria da Construção , Exposição Ocupacional , Humanos , Areia , Alberta , Poeira/análise , Exposição por Inalação/análise , Dióxido de Silício , Exposição Ocupacional/análise , Local de Trabalho , Poluentes Ocupacionais do Ar/análise , Monitoramento Ambiental/métodosRESUMO
There is a growing body of research in psychology that attempts to extrapolate human lexical judgments from computational models of semantics. This research can be used to help develop comprehensive norm sets for experimental research, it has applications to large-scale statistical modelling of lexical access and has broad value within natural language processing and sentiment analysis. However, the value of extrapolated human judgments has recently been questioned within psychological research. Of primary concern is the fact that extrapolated judgments may not share the same pattern of statistical relationship with lexical and semantic variables as do actual human judgments; often the error component in extrapolated judgments is not psychologically inert, making such judgments problematic to use for psychological research. We present a new methodology for extrapolating human judgments that partially addresses prior concerns of validity. We use this methodology to extrapolate human judgments of valence, arousal, dominance, and concreteness for 78,286 words. We also provide resources for users to extrapolate these human judgments for three million English words and short phrases. Applications for large sets of extrapolated human judgments are demonstrated and discussed.