Literature DB >> 28148457

Identification of technical problems affecting performance of DustTrak DRX aerosol monitors.

Ioar Rivas1, Mandana Mazaheri2, Mar Viana3, Teresa Moreno3, Samuel Clifford4, Congrong He5, Oliver F Bischof6, Vânia Martins3, Cristina Reche3, Andrés Alastuey3, Mar Alvarez-Pedrerol7, Jordi Sunyer8, Lidia Morawska5, Xavier Querol3.   

Abstract

The TSI DustTrak Aerosol Monitor is a portable real-time instrument widely used for particulate matter (PM) mass concentrations monitoring. The aim of this work is to report on issues that have arisen from the use of the latest generation models DustTrak DRX (8533 and 8534) in the BREATHE, UPTECH and IMPROVE projects that can compromise data quality. The main issue we encountered was the occurrence of sudden artefact jumps in PM concentration, which can involve an increase from a few to some hundreds of μg·m-3. These artefact jumps can sometimes be easily recognised ("obvious jump"), while others can be difficult to identify because the difference in the concentrations before and after the jump might be just few μg·m-3 ("possible jump") or because the jump is sustained over the whole monitoring period and only detectable if PM concentrations are simultaneously measured by other instruments ("hidden jump"). Moreover, in areas of relatively low PM levels, the unit reported concentration of 0μg·m-3 for ambient PM concentration or even negative concentration values which may seriously compromise the dataset. These data suggest issues with the detection of low PM concentrations, which could be due to an incorrect instrument offset or the factory calibration setting being inadequate for these PM concentrations. The upward and downward artefact jumps were not related to especially dusty or clean conditions, since they have been observed in many kinds of environments: indoor and outdoor school environments, subway stations and in ambient urban background air. Therefore, PM concentration data obtained with the TSI DustTrak DRX models should be handled with care and meticulously revised before being considered valid. To prevent these issues the use of auto zero module is recommended, so the DustTrak monitor is automatic re-zeroed without requiring the presence of any user.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Mass concentration; PM(x); Performance; Portable instrument; TSI DustTrak

Year:  2017        PMID: 28148457     DOI: 10.1016/j.scitotenv.2017.01.129

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  5 in total

1.  A Comparison of Particulate Exposure Levels during Taxi, Bus, and Metro Commuting among Four Chinese Megacities.

Authors:  Ying Zhang; Zhengdong Huang; Jiacheng Huang
Journal:  Int J Environ Res Public Health       Date:  2022-05-10       Impact factor: 4.614

2.  Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution.

Authors:  Florentin Michel Jacques Bulot; Hugo Savill Russell; Mohsen Rezaei; Matthew Stanley Johnson; Steven James Johnston Ossont; Andrew Kevin Richard Morris; Philip James Basford; Natasha Hazel Celeste Easton; Gavin Lee Foster; Matthew Loxham; Simon James Cox
Journal:  Sensors (Basel)       Date:  2020-04-15       Impact factor: 3.576

3.  Estimation of PM10 Levels and Sources in Air Quality Networks by Digital Analysis of Smartphone Camera Images Taken from Samples Deposited on Filters.

Authors:  Selena Carretero-Peña; Lorenzo Calvo Blázquez; Eduardo Pinilla-Gil
Journal:  Sensors (Basel)       Date:  2019-11-04       Impact factor: 3.576

4.  Properties of Particulate Matter in the Air of the Wieliczka Salt Mine and Related Health Benefits for Tourists.

Authors:  Karolina Bralewska; Wioletta Rogula-Kozłowska; Dominika Mucha; Artur Jerzy Badyda; Magdalena Kostrzon; Adrian Bralewski; Stanisław Biedugnis
Journal:  Int J Environ Res Public Health       Date:  2022-01-12       Impact factor: 3.390

5.  Field Evaluation and Calibration of Low-Cost Air Pollution Sensors for Environmental Exposure Research.

Authors:  Jianwei Huang; Mei-Po Kwan; Jiannan Cai; Wanying Song; Changda Yu; Zihan Kan; Steve Hung-Lam Yim
Journal:  Sensors (Basel)       Date:  2022-03-19       Impact factor: 3.576

  5 in total

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