Evaluation of One- and Two-Box Models as Particle Exposure Prediction Tools at Industrial Scale
One- and two-box models have been pointed out as useful tools for modelling indoor particle exposure. However, model performance still needs further testing if they are to be implemented as trustworthy tools for exposure assessment. The objective of this work is to evaluate the performance, applicab...
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MDPI AG
2021-08-01
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Online Access: | https://www.mdpi.com/2305-6304/9/9/201 |
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author | Carla Ribalta Ana López-Lilao Ana Sofia Fonseca Alexander Christian Østerskov Jensen Keld Alstrup Jensen Eliseo Monfort Mar Viana |
author_facet | Carla Ribalta Ana López-Lilao Ana Sofia Fonseca Alexander Christian Østerskov Jensen Keld Alstrup Jensen Eliseo Monfort Mar Viana |
author_sort | Carla Ribalta |
collection | DOAJ |
description | One- and two-box models have been pointed out as useful tools for modelling indoor particle exposure. However, model performance still needs further testing if they are to be implemented as trustworthy tools for exposure assessment. The objective of this work is to evaluate the performance, applicability and reproducibility of one- and two-box models on real-world industrial scenarios. A study on filling of seven materials in three filling lines with different levels of energy and mitigation strategies was used. Inhalable and respirable mass concentrations were calculated with one- and two-box models. The continuous drop and rotating drum methods were used for emission rate calculation, and ranges from a one-at-a-time methodology were applied for local exhaust ventilation efficiency and inter-zonal air flows. When using both dustiness methods, large differences were observed for modelled inhalable concentrations but not for respirable, which showed the importance to study the linkage between dustiness and processes. Higher model accuracy (ratio modelled vs. measured concentrations 0.5–5) was obtained for the two- (87%) than the one-box model (53%). Large effects on modelled concentrations were seen when local exhausts ventilation and inter-zonal variations where parametrized in the models. However, a certain degree of variation (10–20%) seems acceptable, as similar conclusions are reached. |
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issn | 2305-6304 |
language | English |
last_indexed | 2024-03-09T04:39:58Z |
publishDate | 2021-08-01 |
publisher | MDPI AG |
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series | Toxics |
spelling | doaj.art-536b325c3c4149dc971f7bf5aae3836b2023-12-03T13:22:10ZengMDPI AGToxics2305-63042021-08-019920110.3390/toxics9090201Evaluation of One- and Two-Box Models as Particle Exposure Prediction Tools at Industrial ScaleCarla Ribalta0Ana López-Lilao1Ana Sofia Fonseca2Alexander Christian Østerskov Jensen3Keld Alstrup Jensen4Eliseo Monfort5Mar Viana6The National Research Center for Work Environment (NRCWE), DK-2100 Copenhagen, DenmarkInstitute of Ceramic Technology (ITC)-AICE, Campus Universitario Riu Sec, Universitat Jaume I, 12006 Castellón, SpainThe National Research Center for Work Environment (NRCWE), DK-2100 Copenhagen, DenmarkThe National Research Center for Work Environment (NRCWE), DK-2100 Copenhagen, DenmarkThe National Research Center for Work Environment (NRCWE), DK-2100 Copenhagen, DenmarkInstitute of Ceramic Technology (ITC)-AICE, Campus Universitario Riu Sec, Universitat Jaume I, 12006 Castellón, SpainInstitute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034 Barcelona, SpainOne- and two-box models have been pointed out as useful tools for modelling indoor particle exposure. However, model performance still needs further testing if they are to be implemented as trustworthy tools for exposure assessment. The objective of this work is to evaluate the performance, applicability and reproducibility of one- and two-box models on real-world industrial scenarios. A study on filling of seven materials in three filling lines with different levels of energy and mitigation strategies was used. Inhalable and respirable mass concentrations were calculated with one- and two-box models. The continuous drop and rotating drum methods were used for emission rate calculation, and ranges from a one-at-a-time methodology were applied for local exhaust ventilation efficiency and inter-zonal air flows. When using both dustiness methods, large differences were observed for modelled inhalable concentrations but not for respirable, which showed the importance to study the linkage between dustiness and processes. Higher model accuracy (ratio modelled vs. measured concentrations 0.5–5) was obtained for the two- (87%) than the one-box model (53%). Large effects on modelled concentrations were seen when local exhausts ventilation and inter-zonal variations where parametrized in the models. However, a certain degree of variation (10–20%) seems acceptable, as similar conclusions are reached.https://www.mdpi.com/2305-6304/9/9/201mass-balance modelsoccupational exposuredustiness indexhandling energy factorindoor aerosol modellingemission rate |
spellingShingle | Carla Ribalta Ana López-Lilao Ana Sofia Fonseca Alexander Christian Østerskov Jensen Keld Alstrup Jensen Eliseo Monfort Mar Viana Evaluation of One- and Two-Box Models as Particle Exposure Prediction Tools at Industrial Scale Toxics mass-balance models occupational exposure dustiness index handling energy factor indoor aerosol modelling emission rate |
title | Evaluation of One- and Two-Box Models as Particle Exposure Prediction Tools at Industrial Scale |
title_full | Evaluation of One- and Two-Box Models as Particle Exposure Prediction Tools at Industrial Scale |
title_fullStr | Evaluation of One- and Two-Box Models as Particle Exposure Prediction Tools at Industrial Scale |
title_full_unstemmed | Evaluation of One- and Two-Box Models as Particle Exposure Prediction Tools at Industrial Scale |
title_short | Evaluation of One- and Two-Box Models as Particle Exposure Prediction Tools at Industrial Scale |
title_sort | evaluation of one and two box models as particle exposure prediction tools at industrial scale |
topic | mass-balance models occupational exposure dustiness index handling energy factor indoor aerosol modelling emission rate |
url | https://www.mdpi.com/2305-6304/9/9/201 |
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