Preprints
https://doi.org/10.5194/amt-2020-517
https://doi.org/10.5194/amt-2020-517

  16 Feb 2021

16 Feb 2021

Review status: a revised version of this preprint is currently under review for the journal AMT.

Analysis of mobile monitoring data from the microAeth® MA200 for measuring changes in black carbon on the roadside in Augsburg

Xiansheng Liu1,2, Hadiatullah Hadiatullah3, Xun Zhang4,5, L. Drew Hill6, Andrew H. A. White6,7, Jürgen Schnelle-Kreis1, Jan Bendl1,8, Gert Jakobi1, Brigitte Schloter-Hai1, and Ralf Zimmermann1,2 Xiansheng Liu et al.
  • 1Joint Mass Spectrometry Center, Cooperation Group Comprehensive Molecular Analytics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
  • 2Joint Mass Spectrometry Center, Chair of Analytical Chemistry, University of Rostock, 18059 Rostock, Germany
  • 3School of Pharmaceutical Science and Technology, Tianjin University, 300072 Tianjin, China
  • 4Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer Science and Engineering, Beijing Technology and Business University, 100048 Beijing, China
  • 5Key Laboratory of Resources Utilization and Environmental Remediation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101 Beijing, China
  • 6AethLabs, San Francisco, CA, USA
  • 7Yale School of Medicine, New Haven, CT, USA
  • 8Institute for Environment Studies, Faculty of Science, Charles University, Prague, Czech Republic

Abstract. The portable microAeth® MA200 (MA200) is widely applied for measuring black carbon (BC) in human exposure characterization and mobile air quality monitoring. However, the field lacks information about this instrument's performance under various settings. This study evaluated the real-time performance of the MA200 in an urban area, Augsburg, Germany. Noise reduction and negative value mitigation were explored using different data processing methods: local polynomial regression (LPR), optimized noise reduction averaging (ONA), and centered moving average (CMA) under different interval time (5 s, 10 s, and 30 s). After noise reduction, the data were evaluated and compared by (1) the relative number of negative values; (2) more detailed microenvironmental change information retained after noise reduction; (3) the reduction of the peak values and number of peak samples; (4) more detailed microenvironmental change retained after the background correction. Our results showed that CMA showed a good prospect to analyze the raw BC concentration data in terms of the interval time due to its proportions of negative values and the detail microenvironmental change. Moreover, the CMA method has the highest reduction peak values and the number of peak samples compared to ONA and LPR. Furthermore, after background correction, the CMA treatment results remained more detailed microenvironmental changes in pollutants than others. Therefore, based on a comprehensive comparison, CMA offered a good approach to post-process the raw BC concentration data. These findings provide new insight for the noise reduction approach that applied in mobile monitoring campaign using BC instruments.

Xiansheng Liu et al.

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Xiansheng Liu et al.

Xiansheng Liu et al.

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Short summary
The study evaluated the real-time performance of the MA200 in urban area due to lacks information about this instrument’s performance under various settings for black carbon measurement. Noise reduction and negative value were explored using different data processing methods. The result showed that center moving average offered a good approach to post-process the raw BC concentration. These findings provide new insight for the noise reduction approach that applied in mobile monitoring campaign.