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A Methodology to Monitor Airborne PM(10) Dust Particles Using a Small Unmanned Aerial Vehicle

Throughout the process of coal extraction from surface mines, gases and particles are emitted in the form of fugitive emissions by activities such as hauling, blasting and transportation. As these emissions are diffuse in nature, estimations based upon emission factors and dispersion/advection equat...

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Autores principales: Alvarado, Miguel, Gonzalez, Felipe, Erskine, Peter, Cliff, David, Heuff, Darlene
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5335937/
https://www.ncbi.nlm.nih.gov/pubmed/28216557
http://dx.doi.org/10.3390/s17020343
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author Alvarado, Miguel
Gonzalez, Felipe
Erskine, Peter
Cliff, David
Heuff, Darlene
author_facet Alvarado, Miguel
Gonzalez, Felipe
Erskine, Peter
Cliff, David
Heuff, Darlene
author_sort Alvarado, Miguel
collection PubMed
description Throughout the process of coal extraction from surface mines, gases and particles are emitted in the form of fugitive emissions by activities such as hauling, blasting and transportation. As these emissions are diffuse in nature, estimations based upon emission factors and dispersion/advection equations need to be measured directly from the atmosphere. This paper expands upon previous research undertaken to develop a relative methodology to monitor PM(10) dust particles produced by mining activities making use of small unmanned aerial vehicles (UAVs). A module sensor using a laser particle counter (OPC-N2 from Alphasense, Great Notley, Essex, UK) was tested. An aerodynamic flow experiment was undertaken to determine the position and length of a sampling probe of the sensing module. Flight tests were conducted in order to demonstrate that the sensor provided data which could be used to calculate the emission rate of a source. Emission rates are a critical variable for further predictive dispersion estimates. First, data collected by the airborne module was verified using a 5.0 m tower in which a TSI DRX 8533 (reference dust monitoring device, TSI, Shoreview, MN, USA) and a duplicate of the module sensor were installed. Second, concentration values collected by the monitoring module attached to the UAV (airborne module) obtaining a percentage error of 1.1%. Finally, emission rates from the source were calculated, with airborne data, obtaining errors as low as 1.2%. These errors are low and indicate that the readings collected with the airborne module are comparable to the TSI DRX and could be used to obtain specific emission factors from fugitive emissions for industrial activities.
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spelling pubmed-53359372017-03-16 A Methodology to Monitor Airborne PM(10) Dust Particles Using a Small Unmanned Aerial Vehicle Alvarado, Miguel Gonzalez, Felipe Erskine, Peter Cliff, David Heuff, Darlene Sensors (Basel) Article Throughout the process of coal extraction from surface mines, gases and particles are emitted in the form of fugitive emissions by activities such as hauling, blasting and transportation. As these emissions are diffuse in nature, estimations based upon emission factors and dispersion/advection equations need to be measured directly from the atmosphere. This paper expands upon previous research undertaken to develop a relative methodology to monitor PM(10) dust particles produced by mining activities making use of small unmanned aerial vehicles (UAVs). A module sensor using a laser particle counter (OPC-N2 from Alphasense, Great Notley, Essex, UK) was tested. An aerodynamic flow experiment was undertaken to determine the position and length of a sampling probe of the sensing module. Flight tests were conducted in order to demonstrate that the sensor provided data which could be used to calculate the emission rate of a source. Emission rates are a critical variable for further predictive dispersion estimates. First, data collected by the airborne module was verified using a 5.0 m tower in which a TSI DRX 8533 (reference dust monitoring device, TSI, Shoreview, MN, USA) and a duplicate of the module sensor were installed. Second, concentration values collected by the monitoring module attached to the UAV (airborne module) obtaining a percentage error of 1.1%. Finally, emission rates from the source were calculated, with airborne data, obtaining errors as low as 1.2%. These errors are low and indicate that the readings collected with the airborne module are comparable to the TSI DRX and could be used to obtain specific emission factors from fugitive emissions for industrial activities. MDPI 2017-02-14 /pmc/articles/PMC5335937/ /pubmed/28216557 http://dx.doi.org/10.3390/s17020343 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Alvarado, Miguel
Gonzalez, Felipe
Erskine, Peter
Cliff, David
Heuff, Darlene
A Methodology to Monitor Airborne PM(10) Dust Particles Using a Small Unmanned Aerial Vehicle
title A Methodology to Monitor Airborne PM(10) Dust Particles Using a Small Unmanned Aerial Vehicle
title_full A Methodology to Monitor Airborne PM(10) Dust Particles Using a Small Unmanned Aerial Vehicle
title_fullStr A Methodology to Monitor Airborne PM(10) Dust Particles Using a Small Unmanned Aerial Vehicle
title_full_unstemmed A Methodology to Monitor Airborne PM(10) Dust Particles Using a Small Unmanned Aerial Vehicle
title_short A Methodology to Monitor Airborne PM(10) Dust Particles Using a Small Unmanned Aerial Vehicle
title_sort methodology to monitor airborne pm(10) dust particles using a small unmanned aerial vehicle
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5335937/
https://www.ncbi.nlm.nih.gov/pubmed/28216557
http://dx.doi.org/10.3390/s17020343
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