An overview of methods of fine and ultrafine particle collection for physicochemical characterisation and toxicity assessments.
File(s)1-s2.0-S0048969720370844-main.pdf (1.41 MB)
Published version
Author(s)
Type
Journal Article
Abstract
Particulate matter (PM) is a crucial health risk factor for respiratory and cardiovascular diseases. The smaller size fractions, ≤2.5 μm (PM2.5; fine particles) and ≤0.1 μm (PM0.1; ultrafine particles), show the highest bioactivity but acquiring sufficient mass for in vitro and in vivo toxicological studies is challenging. We review the suitability of available instrumentation to collect the PM mass required for these assessments. Five different microenvironments representing the diverse exposure conditions in urban environments are considered in order to establish the typical PM concentrations present. The highest concentrations of PM2.5 and PM0.1 were found near traffic (i.e. roadsides and traffic intersections), followed by indoor environments, parks and behind roadside vegetation. We identify key factors to consider when selecting sampling instrumentation. These include PM concentration on-site (low concentrations increase sampling time), nature of sampling sites (e.g. indoors; noise and space will be an issue), equipment handling and power supply. Physicochemical characterisation requires micro- to milli-gram quantities of PM and it may increase according to the processing methods (e.g. digestion or sonication). Toxicological assessments of PM involve numerous mechanisms (e.g. inflammatory processes and oxidative stress) requiring significant amounts of PM to obtain accurate results. Optimising air sampling techniques are therefore important for the appropriate collection medium/filter which have innate physical properties and the potential to interact with samples. An evaluation of methods and instrumentation used for airborne virus collection concludes that samplers operating cyclone sampling techniques (using centrifugal forces) are effective in collecting airborne viruses. We highlight that predictive modelling can help to identify pollution hotspots in an urban environment for the efficient collection of PM mass. This review provides guidance to prepare and plan efficient sampling campaigns to collect sufficient PM mass for various purposes in a reasonable timeframe.
Date Issued
2021-02-20
Date Acceptance
2020-11-02
Citation
Science of the Total Environment, 2021, 756, pp.1-22
ISSN
0048-9697
Publisher
Elsevier
Start Page
1
End Page
22
Journal / Book Title
Science of the Total Environment
Volume
756
Copyright Statement
© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license.
License URL
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/33239200
PII: S0048-9697(20)37084-4
Grant Number
EP/T003189/1
Subjects
Artificial intelligence
Mass collection
Particulate matter
Physicochemical characteristics
Toxicological assessments
Ultrafine particles
Publication Status
Published
Coverage Spatial
Netherlands
Date Publish Online
2020-11-06