146 Meteorological Influence on Measurement Strategy and Estimated Respirable Dust and Respirable Crystalline Silica Exposure Levels Within the European Minerals Industry

Abstract

Abstract The evidence of meteorological conditions on occupational exposure measurements is limited, despite is expected to be important determinants of long-term exposures. We describe meteorological conditions for measurement and non-measurement days and evaluate associations between temperature and total precipitation and respirable dust and respirable crystalline silica (RCS) concentrations of the European Industrial Minerals Association-Dust Monitoring Programme. Geo-matched RCS and dust measurements were evaluated against meteorological data (archived satellite observations and weather station measurements). Temperature(0C) and total precipitation (mm) for RCS measurement and non-measurement days were described. A linear regression model was used to investigate the association between dust and RCS concentration and meteorological conditions. Overall, 2,840 dust measurements (GM=0.20mg/m3; GSD=3.43mg/m3) and 2,658 quartz measurements (GM=0.01mg/m3; GSD=5.23mg/m3) were collected across 96 an 94 industrial mineral sites over 262 and 259 days in 2011. Mean temperature and precipitation for dust and RCS measurements were similar for measurement and non-measurement days (dust: 10.490C and 10.830C, 2.23mm and 2.12mm; RCS: 11.050C and 10.820C, 2.08mm and 2.12mm). For respirable dust concentrations a 6.4% decrease per 1°C was estimated for temperatures<200C (p<0.001) and an 8.2% increase for temperatures≥200C (p=0.002). For RCS a 2% decrease in was estimated for every 1mm increase in total precipitation (p=0.02). No difference in meteorological conditions were seen between measurements days and non-measurement days. Associations of these conditions with exposure concentrations with showed differences between agents despite being collected and measured on the same filter. Long-term changes in meteorological conditions might be an important factor when estimating long term exposures.