Modeling of High Nanoparticle Exposure in an Indoor Industrial Scenario with a One-Box Model

Carla Ribalta, Antti J. Koivisto, Apostolos Salmatonidis, Ana López-Lilao, Eliseo Monfort and Mar Viana
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Carla Ribalta: Institute of Environmental Assessment and Water Research (IDÆA-CSIC), C/ Jordi Girona 18, 08034 Barcelona, Spain
Antti J. Koivisto: Institute for Atmospheric and Earth System Research (INAR), University of Helsinki, PL 64, FI-00014 Helsinki, Finland
Apostolos Salmatonidis: Institute of Environmental Assessment and Water Research (IDÆA-CSIC), C/ Jordi Girona 18, 08034 Barcelona, Spain
Ana López-Lilao: Institute of Ceramic Technology (ITC)- AICE - Universitat Jaume I, Campus Universitario Riu Sec, Av. Vicent Sos Baynat s/n, 12006 Castellón, Spain
Eliseo Monfort: Institute of Ceramic Technology (ITC)- AICE - Universitat Jaume I, Campus Universitario Riu Sec, Av. Vicent Sos Baynat s/n, 12006 Castellón, Spain
Mar Viana: Institute of Environmental Assessment and Water Research (IDÆA-CSIC), C/ Jordi Girona 18, 08034 Barcelona, Spain

IJERPH, 2019, vol. 16, issue 10, 1-16

Abstract: Mass balance models have proved to be effective tools for exposure prediction in occupational settings. However, they are still not extensively tested in real-world scenarios, or for particle number concentrations. An industrial scenario characterized by high emissions of unintentionally-generated nanoparticles (NP) was selected to assess the performance of a one-box model. Worker exposure to NPs due to thermal spraying was monitored, and two methods were used to calculate emission rates: the convolution theorem, and the cyclic steady state equation. Monitored concentrations ranged between 4.2 × 10 4 –2.5 × 10 5 cm −3 . Estimated emission rates were comparable with both methods: 1.4 × 10 11 –1.2 × 10 13 min −1 (convolution) and 1.3 × 10 12 –1.4 × 10 13 min −1 (cyclic steady state). Modeled concentrations were 1.4-6 × 10 4 cm −3 (convolution) and 1.7–7.1 × 10 4 cm −3 (cyclic steady state). Results indicated a clear underestimation of measured particle concentrations, with ratios modeled/measured between 0.2–0.7. While both model parametrizations provided similar results on average, using convolution emission rates improved performance on a case-by-case basis. Thus, using cyclic steady state emission rates would be advisable for preliminary risk assessment, while for more precise results, the convolution theorem would be a better option. Results show that one-box models may be useful tools for preliminary risk assessment in occupational settings when room air is well mixed.

Keywords: prediction; emission rates; air exchange rate; ultrafine particles; unintentional nanoparticles; incidental nanoparticles; plasma spraying; worker exposure; particle mass concentration (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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