Testing the performance of one and two box models as tools for risk assessment of particle exposure during packing of inorganic fertilizer

Modelling of particle exposure is a useful tool for preliminary exposure assessment in workplaces with low and high exposure concentrations. However, actual exposure measurements are needed to assess models reliability. Worker exposure was monitored during packing of an inorganic granulate fertilizer at industrial scale using small and big bags. Particle concentrations were modelled with one and two box models, where the emission source was estimated with the fertilizer's dustiness index. The exposure levels were used to calculate inhaled dose rates and test accuracy of the exposure modellings. The particle number concentrations were measured from worker area by using a mobility and optical particle sizer which were used to calculate surface area and mass concentrations. The concentrations in the worker area during pre-activity ranged 63,797–81,073 cm−3, 4.6 × 106 to 7.5 × 106 μm2 cm−3, and 354 to 634 μg m−3 (respirable mass fraction) and during packing 50,300 to 85,949 cm−3, 4.3 × 106 to 7.6 × 106 μm2 cm−3, and 279 to 668 μg m−3 (respirable mass fraction). Thus, the packing process did not significantly increase the exposure levels. Chemical exposure was also under control based on REACH standards. The particle surface area deposition rate in respiratory tract was up to 7.6 × 106 μm2 min−1 during packing, with 52%–61% of deposition occurring in the alveolar region. Ratios of the modelled and measured concentrations were 0.98 ± 0.19 and 0.84 ± 0.12 for small and big bags, respectively, when using the one box model, and 0.88 ± 0.25 and 0.82 ± 0.12, when using the two box model. The modelling precision improved for both models when outdoor particle concentrations were included. This study shows that exposure concentrations in a low emission industrial scenario, e.g. during packing of a fertilizer, can be predicted with a reasonable accuracy by using the concept of dustiness and mass balance models.

This research was founded by the Spanish MINECO (CGL2015-66777-C2-1-R, 2-R), Generalitat de Catalunya AGAUR 2017 SGR41, the Spanish Ministry of the Environment (13CAES006), FEDER (European Regional Development Fund) “Una manera de hacer Europa” and H2020 project caLIBRAte (Work Package 7). M.C. Minguillón acknowledges the Ramón y Cajal Fellowship awarded by the Spanish Ministry of Economy, Industry and Competitiveness. The authors also acknowledge the company in which the measurements were carried out for their support. The authors declare no conflict of interest relating to the material presented in this article.

Peer reviewed