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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2019-66
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-66
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 05 Apr 2019

Research article | 05 Apr 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Methodology for High Quality Mobile Measurement with Focus on Black Carbon and Particle Mass Concentrations

Honey Dawn C. Alas1, Kay Weinhold1, Francesca Costabile2, Antonio Di Ianni2, Thomas Müller1, Sascha Pfeifer1, Luca Di Liberto2, Jay R. Turner3, and Alfred Wiedensohler1 Honey Dawn C. Alas et al.
  • 1Leibniz Institute for Tropospheric Research, Permoserstrasse 15, 04318, Leipzig, Germany
  • 2Institute of Atmospheric Science and Climate, National Research Council, Via Fosso del Cavaliere, 100 – 00133, Rome, Italy
  • 3James McKelvey School of Engineering, Washington University, One Brookings Drive, St. Louis, Missouri, 63130, USA

Abstract. Measurements of air pollutants such as black carbon (BC) and particle mass concentration in general, using mobile platforms equipped with high time-resolution instruments have gained popularity over the last decade due to its wide range of applicability. Assuring the quality of mobile measurement, data has become more essential particularly, when the personal exposure to pollutants is related to its spatial distribution. In the following, we suggest a methodology to achieve data from mobile measurements of equivalent black carbon (eBC) and PM2.5 mass concentrations with high data quality. Besides frequent routine quality assurance measures of the instruments, the methodology includes the following steps. a) Measures to ensure the quality of mobile instruments through repeated collocated measurements using identical instrumentation, b) inclusion of a fixed station along the route containing quality-assured reference instruments and c) sufficiently long and frequent intercomparisons between the mobile and reference instruments to correct the particle number and mass size distributions obtained from mobile measurements. The application of the methodology can provide following results. First, collocated mobile measurements with sets of identical instruments allow identification of undetected malfunctions of the instruments. Second, frequent intercomparisons against the reference instruments will ensure the quality of the mobile measurement data of the eBC mass concentration. Third, the intercomparison data between the mobile optical particle size spectrometer (OPSS) and a reference mobility particle size spectrometer (MPSS) allows for the adjustment of the OPSS particle number size distribution using physical meaningful corrections. Matching the OPSS and MPSS volume particle size distributions is crucial for the determination of PM2.5 mass concentration. Using size-resolved complex refractive indices and time-resolved fine mode volume correction factors of the fine particle range, the calculated PM2.5 was within 5 % of the reference instruments (MPSS+APSS). However, due to the non-sphericity and an unknown imaginary part of the complex refractive index of supermicrometer particles, a conversion to a volume equivalent diameter yields high uncertainties of the particle mass concentration greater than PM2.5. The proposed methodology addresses issues regarding the quality of mobile measurements, especially for health impact studies, validation of modelled spatial distribution, and development of air pollution mitigation strategies.

Honey Dawn C. Alas et al.
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Honey Dawn C. Alas et al.
Honey Dawn C. Alas et al.
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Short summary
Traffic-related air pollutants are highly variable in space. To determine their spatial distribution in relation to human exposure, portable black carbon and PM2.5 mass concentration sensors aboard mobile platforms can be used. High spatial resolution data can help improve exposure estimates. The quality of this data becomes increasingly important. This study provides a detailed methodology on how to achieve highly-quality assured data from the above-mentioned mobile measurements.
Traffic-related air pollutants are highly variable in space. To determine their spatial...
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