Articles | Volume 10, issue 12
https://doi.org/10.5194/amt-10-5063-2017
https://doi.org/10.5194/amt-10-5063-2017
Research article
 | 
22 Dec 2017
Research article |  | 22 Dec 2017

Improved methods for signal processing in measurements of mercury by Tekran® 2537A and 2537B instruments

Jesse L. Ambrose

Related subject area

Subject: Gases | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
A flexible algorithm for network design based on information theory
Rona L. Thompson and Ignacio Pisso
Atmos. Meas. Tech., 16, 235–246, https://doi.org/10.5194/amt-16-235-2023,https://doi.org/10.5194/amt-16-235-2023, 2023
Short summary
Data Quality Enhancement for Atmospheric Chemistry Field Experiments via Sequential Monte Carlo Filters
Lenard L. Röder, Patrick Dewald, Clara M. Nussbaumer, Jan Schuladen, John N. Crowley, Jos Lelieveld, and Horst Fischer
EGUsphere, https://doi.org/10.5194/egusphere-2022-1080,https://doi.org/10.5194/egusphere-2022-1080, 2022
Short summary
Real-world wintertime CO, N2O, and CO2 emissions of a central European village
László Haszpra, Zoltán Barcza, Zita Ferenczi, Roland Hollós, Anikó Kern, and Natascha Kljun
Atmos. Meas. Tech., 15, 5019–5031, https://doi.org/10.5194/amt-15-5019-2022,https://doi.org/10.5194/amt-15-5019-2022, 2022
Short summary
Evaluation of two common source estimation measurement strategies using large-eddy simulation of plume dispersion under neutral atmospheric conditions
Anja Ražnjević, Chiel van Heerwaarden, and Maarten Krol
Atmos. Meas. Tech., 15, 3611–3628, https://doi.org/10.5194/amt-15-3611-2022,https://doi.org/10.5194/amt-15-3611-2022, 2022
Short summary
Machine learning techniques to improve the field performance of low-cost air quality sensors
Tony Bush, Nick Papaioannou, Felix Leach, Francis D. Pope, Ajit Singh, G. Neil Thomas, Brian Stacey, and Suzanne Bartington
Atmos. Meas. Tech., 15, 3261–3278, https://doi.org/10.5194/amt-15-3261-2022,https://doi.org/10.5194/amt-15-3261-2022, 2022
Short summary

Cited articles

Ambrose, J.: Data Archive for: Improved methods for signal processing in measurements of mercury by Tekran® 2537A and 2537B instruments, Open Science Framework, https://doi.org/10.17605/OSF.IO/KGFYP, 2017.
Ambrose, J. L., Reidmiller, D. R., and Jaffe, D. A.: Causes of high O3 in the lower free troposphere over the Pacific Northwest as observed at the Mt. Bachelor Observatory, Atmos. Environ., 45, 5302–5315, https://doi.org/10.1016/j.atmosenv.2011.06.056, 2011.
Ambrose, J. L., Lyman, S. N., Huang, J., Gustin, M. S., and Jaffe, D. A.: Fast time resolution oxidized mercury measurements during the Reno Atmospheric Mercury Intercomparison Experiment (RAMIX), Environ. Sci. Technol., 47, 7285–7294, https://doi.org/10.1021/es303916v, 2013.
Ambrose, J. L., Gratz, L. E., Jaffe, D. A., Campos, T., Flocke, F. M., Knapp, D. J., Stechman, D. M., Stell, M., Weinheimer, A. J., Cantrell, C. A., and Mauldin III, R. L.: Mercury emission ratios from coal-fired power plants in the southeastern United States during NOMADSS, Environ. Sci. Technol., 49, 10389–10397, https://doi.org/10.1021/acs.est.5b01755, 2015.
Cole, A. S., Steffen, A., Eckley, C. S., Narayan, J., Pilote, M., Tordon, R., Graydon, J. A., St. Louis, V. L., Xu, X., and Branfireun, B. A.: A Survey of Mercury in Air and Precipitation across Canada: Patterns and Trends, Atmosphere, 5, 635–668, https://doi.org/10.3390/atmos5030635, 2014.
Download
Short summary
Scientific understanding of environmental Hg cycling is limited by analytical uncertainties. To better characterize analytical uncertainty associated with Hg measurements made with the Tekran® 2537 instrument, I developed new software-based methods for offline processing of the raw instrumental data. I demonstrate significant uncertainty associated with the Tekran® method. By comparison, my methods improve measurement accuracy and the Hg detection limit by as much as 95 % and 88 %, respectively.