Šikoparija, B., Matavulj, P., Mimić, G., Smith, Matt ORCID: https://orcid.org/0000-0002-4170-2960, Grewling, Ł. and Podraščanin, Z. (2022) Real-time automatic detection of starch particles in ambient air. Agricultural and Forest Meteorology, 323 (109034). ISSN 0168-1923
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Abstract
Considerable amounts of starch granules can be present in the atmosphere from both natural and anthropogenic sources. The aim of this study is to investigate the variability and potential origin of starch granules in ambient air recorded at six cities situated in a region with dominantly agricultural land use. This is achieved by using a combination of laser spectroscopy bioaerosol measurements with 1 min temporal resolution, traditional volumetric Hirst type bioaerosol sampling and atmospheric modelling. The analysis of wind roses identified potential sources of airborne starch (i.e., cereal grain storage facilities) in the vicinity of all aerobiological stations analysed in this study. The analysis of the CALPUFF dispersion model confirmed that emission of dust from the location of storage towers situated about 2.5 km north of the aerobiological station in Novi Sad is a plausible source of high airborne concentrations of starch granules. This study is important for environmental health since it contributes body of knowledge about sources, emission, and dispersion of airborne starch, known to be involved in phenomena such as thunderstorm-triggered asthma. The presented approach integrates monitoring and modelling, and provides a roadmap for examining a variety of bioaerosols previously considered to be outside the scope of traditional aerobiological measurements.
Item Type: | Article |
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Additional Information: | This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) |
Uncontrolled Discrete Keywords: | Aerobiology, Airborne starch, Automatic monitoring, Dispersion modelling, Emission sources |
Divisions: | College of Health, Life and Environmental Sciences > School of Science and the Environment |
Related URLs: | |
Copyright Info: | © 2022 The Author(s). Published by Elsevier B.V. |
Depositing User: | Miranda Jones |
Date Deposited: | 15 Aug 2022 12:07 |
Last Modified: | 15 Aug 2022 12:07 |
URI: | https://eprints.worc.ac.uk/id/eprint/12417 |
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