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An overview of methods of fine and ultrafine particle collection for physicochemical characterisation and toxicity assessments

机译:物理化学表征和毒性评估的精细和超细粒子收集方法概述

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摘要

Paniculate matter (PM) is a crucial health risk factor for respiratory and cardiovascular diseases. The smaller size fractions. ≤2.5 μrn (PM_(2.5); fine particles) and <0.1 (am (PM_(0.1); ultrafine particles), show the highest bioac-tivity 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 PM_(2.5) and PM_(0.1) 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.
机译:对呼吸和心血管疾病的关键健康危险因素是一种至关重要的健康危险因素。较小的尺寸分数。 ≤2.5μrn(pm_(2.5);细颗粒)和<0.1(am(pm_(0.1);超细颗粒),表现出最高的生物粒子,但在体外获取足够的质量,体内毒理学研究具有挑战性。我们审查可用仪器收集这些评估所需的PM质量的适用性。考虑五种不同的微环境,代表城市环境中的各种暴露条件,以建立典型的PM浓度。最高浓度的PM_(2.5)和PM_(0.1 )在交通附近(即公路和交通交叉路口),其次是室内环境,公园和路边植被后面。我们确定选择采样仪器时考虑的关键因素。这些包括PM浓度(低浓度增加采样时间),采样网站的性质(例如在室内;噪音和空间将是一个问题),设备处理和电源。物理化学表征需要麦克风RO-至毫克批量PM,它可能根据加工方法增加(例如,消化或超声处理)。 PM的毒理学评估涉及许多机制(例如炎症过程和氧化应激),需要大量PM以获得准确的结果。因此,优化空气采样技术对于具有先天物理性质的适当收集介质/过滤器是重要的,并且可能与样品相互作用。用于空气传播病毒收集的方法和仪器的评估得出结论,采样器操作旋风器采样技术(使用离心力)可有效地收集空气传播病毒。我们强调,预测建模可以帮助识别城市环境中的污染热点以获得PM质量的有效收集。本综述提供了准备和计划有效的抽样活动的指导,以便在合理的时间范围内为各种目的收集足够的PM质量。

著录项

  • 来源
    《Science of the total environment》 |2021年第20期|143553.1-143553.22|共22页
  • 作者单位

    Global Centre for Clean Air Research (GCARE) Department of Civil and Environmental Engineering Faculty of Engineering and Physical Sciences University of Surrey Guildford GU2 7XH United Kingdom Department of Civil Structural & Environmental Engineering Trinity College Dublin Dublin Ireland;

    Global Centre for Clean Air Research (GCARE) Department of Civil and Environmental Engineering Faculty of Engineering and Physical Sciences University of Surrey Guildford GU2 7XH United Kingdom;

    Department of Materials Imperial College London South Kensington London SW7 2AZ United Kingdom;

    Department of Materials Imperial College London South Kensington London SW7 2AZ United Kingdom;

    Department of Materials Imperial College London South Kensington London SW7 2AZ United Kingdom;

    Center for Nanotechnology and Nanotoxicology Department of Environmental Health T.H. Chan School of Public Health Harvard University 665 Huntington Avenue Room 1310 Boston MA 02115 USA;

    National Heart & Lung Institute Imperial College London London SW3 6LY United Kingdom;

    Department of Earth Science & Engineering Imperial College London London SW7 2AZ United Kingdom;

    Centre for Speckled Computing School of Informatics University of Edinburgh Edinburgh Scotland EH8 9AB United Kingdom;

    Data Science Institute Department of Computing Imperial College London London SW7 2BU United Kingdom;

    National Heart & Lung Institute Imperial College London London SW3 6LY United Kingdom;

    Department of Earth Science & Engineering Imperial College London London SW7 2AZ United Kingdom;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Particulate matter; Ultrafine particles; Mass collection; Physicochemical characteristics; Toxicological assessments; Artificial intelligence;

    机译:颗粒物质;超细颗粒;大众集合;物理化学特征;毒理学评估;人工智能;

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