Articles | Volume 11, issue 1
https://doi.org/10.5194/amt-11-291-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-291-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
15 Jan 2018
Research article | Highlight paper |
| 15 Jan 2018
| 15 Jan 2018
A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring
Naomi Zimmerman
Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Albert A. Presto
Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Sriniwasa P. N. Kumar
Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Jason Gu
Sensevere LLC, Pittsburgh, PA 15222, USA
Aliaksei Hauryliuk
Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Ellis S. Robinson
Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Allen L. Robinson
Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA
R. Subramanian
Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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B. N. Murphy, N. M. Donahue, A. L. Robinson, and S. N. Pandis
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S. H. Jathar, N. M. Donahue, P. J. Adams, and A. L. Robinson
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A. A. Presto, T. D. Gordon, and A. L. Robinson
Atmos. Chem. Phys., 14, 5015–5036, https://doi.org/10.5194/acp-14-5015-2014, https://doi.org/10.5194/acp-14-5015-2014, 2014
T. D. Gordon, A. A. Presto, N. T. Nguyen, W. H. Robertson, K. Na, K. N. Sahay, M. Zhang, C. Maddox, P. Rieger, S. Chattopadhyay, H. Maldonado, M. M. Maricq, and A. L. Robinson
Atmos. Chem. Phys., 14, 4643–4659, https://doi.org/10.5194/acp-14-4643-2014, https://doi.org/10.5194/acp-14-4643-2014, 2014
T. D. Gordon, A. A. Presto, A. A. May, N. T. Nguyen, E. M. Lipsky, N. M. Donahue, A. Gutierrez, M. Zhang, C. Maddox, P. Rieger, S. Chattopadhyay, H. Maldonado, M. M. Maricq, and A. L. Robinson
Atmos. Chem. Phys., 14, 4661–4678, https://doi.org/10.5194/acp-14-4661-2014, https://doi.org/10.5194/acp-14-4661-2014, 2014
R. Saleh, C. J. Hennigan, G. R. McMeeking, W. K. Chuang, E. S. Robinson, H. Coe, N. M. Donahue, and A. L. Robinson
Atmos. Chem. Phys., 13, 7683–7693, https://doi.org/10.5194/acp-13-7683-2013, https://doi.org/10.5194/acp-13-7683-2013, 2013
M. Gyawali, W. P. Arnott, R. A. Zaveri, C. Song, M. Pekour, B. Flowers, M. K. Dubey, A. Setyan, Q. Zhang, J. W. Harworth, J. G. Radney, D. B. Atkinson, S. China, C. Mazzoleni, K. Gorkowski, R. Subramanian, B. T. Jobson, and H. Moosmüller
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-7113-2013, https://doi.org/10.5194/acpd-13-7113-2013, 2013
Revised manuscript not accepted
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We assessed calibration models for two low-cost stations equipped with O3 and NO2 metal oxide sensors. Environmental parameters had improved accuracy in linear and black box models. Moreover, interpretability methods like SHapley Additive exPlanations helped identify the physical patterns and potential problems of these models in a field validation. Results showed both sensors performed well with the same linear model form, but unique coefficients were required for intersensor variability.
Blake Actkinson and Robert J. Griffin
Atmos. Meas. Tech., 16, 3547–3559, https://doi.org/10.5194/amt-16-3547-2023, https://doi.org/10.5194/amt-16-3547-2023, 2023
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Data collected using air quality instrumentation deployed on automobiles and driven repeatedly in Houston neighborhoods are analyzed using a novel machine learning technique. The aim is to separate large plumes from the rest of the data in order to identify the sources of the highest levels of the pollutants. The number and nature of these plumes are characterized spatially and can be linked to emissions from different types of motor vehicles.
Adil Shah, Olivier Laurent, Luc Lienhardt, Grégoire Broquet, Rodrigo Rivera Martinez, Elisa Allegrini, and Philippe Ciais
Atmos. Meas. Tech., 16, 3391–3419, https://doi.org/10.5194/amt-16-3391-2023, https://doi.org/10.5194/amt-16-3391-2023, 2023
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As methane (CH4) contributes to global warming, more CH4 measurements are required to better characterise source emissions. Hence, we tested a cheap CH4 sensor for 338 d of landfill sampling. We derived an excellent CH4 response model in a stable environment. However, different types of air with the same CH4 level had diverse sensor responses. We characterised temperature and water vapour response but could not replicate field sampling. Thus, other species may cause sensor interactions.
Theertha Kariyathan, Ana Bastos, Julia Marshall, Wouter Peters, Pieter Tans, and Markus Reichstein
Atmos. Meas. Tech., 16, 3299–3312, https://doi.org/10.5194/amt-16-3299-2023, https://doi.org/10.5194/amt-16-3299-2023, 2023
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The timing and duration of the carbon uptake period (CUP) are sensitive to the occurrence of major phenological events, which are influenced by recent climate change. This study presents an ensemble-based approach for quantifying the timing and duration of the CUP and their uncertainty when derived from atmospheric CO2 measurements with noise and gaps. The CUP metrics derived with the approach are more robust and have less uncertainty than when estimated with the conventional methods.
Mitchell W. Alton, Harald J. Stark, Manjula R. Canagaratna, and Eleanor C. Browne
Atmos. Meas. Tech., 16, 3273–3282, https://doi.org/10.5194/amt-16-3273-2023, https://doi.org/10.5194/amt-16-3273-2023, 2023
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Mass spectrometric measurements of atmospheric composition routinely detect hundreds of different ions of varying chemical composition, creating challenges for visualization and data interpretation. We present a new analysis technique to facilitate visualization, while providing greater chemical insight. Additionally, it can aid in identifying the chemical composition of ions. A graphical user interface for performing the analysis is introduced and freely available, enabling broad applications.
Kai Krause, Folkard Wittrock, Andreas Richter, Dieter Busch, Anton Bergen, John P. Burrows, Steffen Freitag, and Olesia Halbherr
Atmos. Meas. Tech., 16, 1767–1787, https://doi.org/10.5194/amt-16-1767-2023, https://doi.org/10.5194/amt-16-1767-2023, 2023
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Inland shipping is an important source of nitrogen oxides (NOx). The amount of emitted NOx depends on the characteristics of the individual vessels and the traffic density. Ship emissions are often characterised by the amount of emitted NOx per unit of burnt fuel, and further knowledge about fuel consumption is needed to quantify the total emissions caused by ship traffic. In this study, a new approach to derive absolute emission rates (in g s−1) from onshore measurements is presented.
Lenard L. Röder, Patrick Dewald, Clara M. Nussbaumer, Jan Schuladen, John N. Crowley, Jos Lelieveld, and Horst Fischer
Atmos. Meas. Tech., 16, 1167–1178, https://doi.org/10.5194/amt-16-1167-2023, https://doi.org/10.5194/amt-16-1167-2023, 2023
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Field experiments in atmospheric chemistry provide insights into chemical interactions of our atmosphere. However, high data coverage and accuracy are needed to enable further analysis. In this study, we explore a statistical method that combines knowledge about the chemical reactions with information from measurements to increase the quality of field experiment datasets. We test the algorithm for several applications and discuss limitations that depend on the specific variable and the dynamics.
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
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Atmospheric networks are used for monitoring air quality and greenhouse gases and can provide essential information about the sources and sinks. The design of the network, specifically where to place the observations, is a critical question in order to maximize the information provided while minimizing the cost. Here, a novel method of designing atmospheric networks is presented with two examples, one on monitoring sources of methane and the second on monitoring fossil fuel emissions of CO2.
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
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A novel approach is used for the determination of greenhouse gas (GHG) emissions of small rural settlements, which may significantly differ from those of urban regions and have hardly been studied yet. Among other results, it turned out that wintertime nitrous oxide emission is significantly underestimated in the official emission inventories. Given the large number of such settlements, the underestimation may also distort the national total emission values reported to international databases.
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
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We evaluate two widely used observational techniques (Other Test Method (OTM) 33A and car drive-bys) that estimate point source gas emissions. We performed our analysis on high-resolution plume dispersion simulation. For car drive-bys we found that at least 15 repeated measurements were needed to get within 40 % of the true emissions. OTM 33A produced large errors in estimation (50 %–200 %) due to its sensitivity to dispersion coefficients and underlying simplifying assumptions.
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
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Poor air quality is a human health risk which demands high-spatiotemporal-resolution monitoring data to manage. Low-cost air quality sensors present a convenient pathway to delivering these needs, compared to traditional methods, but bring methodological challenges which can limit operational ability. In this study within Oxford, UK, we develop machine learning methods to improve the quality of low-cost sensors for NO2, PM10 (particulate matter) and PM2.5 and demonstrate their effectiveness.
Lisa J. Beck, Siegfried Schobesberger, Mikko Sipilä, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Meas. Tech., 15, 1957–1965, https://doi.org/10.5194/amt-15-1957-2022, https://doi.org/10.5194/amt-15-1957-2022, 2022
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Sulfuric acid is known to be a main compound in atmospheric new particle formation. Yet, its concentration is very low, which leads to challenges in detecting it. In our study, we derive the sulfuric acid concentration from measurements of ambient ions with a mass spectrometer. Our validation shows that the theoretical approach using the bisulfate ion and its clusters with H2SO4 captures the sulfuric acid concentration very well during daytime.
Katharina Jentzsch, Julia Boike, and Thomas Foken
Atmos. Meas. Tech., 14, 7291–7296, https://doi.org/10.5194/amt-14-7291-2021, https://doi.org/10.5194/amt-14-7291-2021, 2021
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Very small CO2 fluxes are measured at night in Arctic regions. If the sensible heat flux is not close to zero under these conditions, the WPL correction will take values on the order of the flux. A special quality control is proposed for these cases.
Seán Schmitz, Sherry Towers, Guillermo Villena, Alexandre Caseiro, Robert Wegener, Dieter Klemp, Ines Langer, Fred Meier, and Erika von Schneidemesser
Atmos. Meas. Tech., 14, 7221–7241, https://doi.org/10.5194/amt-14-7221-2021, https://doi.org/10.5194/amt-14-7221-2021, 2021
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The last 2 decades have seen substantial technological advances in the development of low-cost air pollution instruments. This study introduces a seven-step methodology for the field calibration of low-cost sensors with user-friendly guidelines, open-access code, and a discussion of common barriers. Our goal with this work is to push for standardized reporting of methods, make critical data processing steps clear for users, and encourage responsible use in the scientific community and beyond.
Alex Resovsky, Michel Ramonet, Leonard Rivier, Jerome Tarniewicz, Philippe Ciais, Martin Steinbacher, Ivan Mammarella, Meelis Mölder, Michal Heliasz, Dagmar Kubistin, Matthias Lindauer, Jennifer Müller-Williams, Sebastien Conil, and Richard Engelen
Atmos. Meas. Tech., 14, 6119–6135, https://doi.org/10.5194/amt-14-6119-2021, https://doi.org/10.5194/amt-14-6119-2021, 2021
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We present a technical description of a statistical methodology for extracting synoptic- and seasonal-length anomalies from greenhouse gas time series. The definition of what represents an anomalous signal is somewhat subjective, which we touch on throughout the paper. We show, however, that the method performs reasonably well in extracting portions of time series influenced by significant North Atlantic Oscillation weather episodes and continent-wide terrestrial biospheric aberrations.
Pramod Kumar, Grégoire Broquet, Camille Yver-Kwok, Olivier Laurent, Susan Gichuki, Christopher Caldow, Ford Cropley, Thomas Lauvaux, Michel Ramonet, Guillaume Berthe, Frédéric Martin, Olivier Duclaux, Catherine Juery, Caroline Bouchet, and Philippe Ciais
Atmos. Meas. Tech., 14, 5987–6003, https://doi.org/10.5194/amt-14-5987-2021, https://doi.org/10.5194/amt-14-5987-2021, 2021
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This study presents a simple atmospheric inversion modeling framework for the localization and quantification of unknown CH4 and CO2 emissions from point sources based on near-surface mobile concentration measurements and a Gaussian plume dispersion model. It is applied for the estimate of a series of brief controlled releases of CH4 and CO2 with a wide range of rates during the TOTAL TADI-2018 experiment. Results indicate a ~10 %–40 % average error on the estimate of the release rates.
Blake Actkinson, Katherine Ensor, and Robert J. Griffin
Atmos. Meas. Tech., 14, 5809–5821, https://doi.org/10.5194/amt-14-5809-2021, https://doi.org/10.5194/amt-14-5809-2021, 2021
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This paper describes the development of a new method used to estimate background from mobile monitoring time series. The method is tested on a previously published dataset, applied to an extensive mobile dataset, and compared with other previously published techniques used to estimate background. The results suggest that the method is a promising framework for background estimation.
Peer Nowack, Lev Konstantinovskiy, Hannah Gardiner, and John Cant
Atmos. Meas. Tech., 14, 5637–5655, https://doi.org/10.5194/amt-14-5637-2021, https://doi.org/10.5194/amt-14-5637-2021, 2021
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Machine learning (ML) calibration techniques could be an effective way to improve the performance of low-cost air pollution sensors. Here we provide novel insights from case studies within the urban area of London, UK, where we compared the performance of three ML techniques to calibrate low-cost measurements of NO2 and PM10. In particular, we highlight the key issue of the method-dependent robustness in maintaining calibration skill after transferring sensors to different measurement sites.
Toprak Aslan, Olli Peltola, Andreas Ibrom, Eiko Nemitz, Üllar Rannik, and Ivan Mammarella
Atmos. Meas. Tech., 14, 5089–5106, https://doi.org/10.5194/amt-14-5089-2021, https://doi.org/10.5194/amt-14-5089-2021, 2021
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Vertical turbulent fluxes of gases measured by the eddy covariance (EC) technique are subject to high-frequency losses. There are different methods used to describe this low-pass filtering effect and to correct the measured fluxes. In this study, we analysed the systematic uncertainty related to this correction for various attenuation and signal-to-noise ratios. A new and robust transfer function method is finally proposed.
Olli Peltola, Toprak Aslan, Andreas Ibrom, Eiko Nemitz, Üllar Rannik, and Ivan Mammarella
Atmos. Meas. Tech., 14, 5071–5088, https://doi.org/10.5194/amt-14-5071-2021, https://doi.org/10.5194/amt-14-5071-2021, 2021
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Gas fluxes measured by the eddy covariance (EC) technique are subject to filtering due to non-ideal instrumentation. For linear first-order systems this filtering causes also a time lag between vertical wind speed and gas signal which is additional to the gas travel time in the sampling line. The effect of this additional time lag on EC fluxes is ignored in current EC data processing routines. Here we show that this oversight biases EC fluxes and hence propose an approach to rectify this bias.
László Haszpra and Ernő Prácser
Atmos. Meas. Tech., 14, 3561–3571, https://doi.org/10.5194/amt-14-3561-2021, https://doi.org/10.5194/amt-14-3561-2021, 2021
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Most of the tall-tower greenhouse gas observatories apply a single gas analyzer for the sequential sampling of several intakes along the tower. The non-continuous sampling at each intake introduces excess uncertainty to the calculated hourly-average concentrations used in several applications. Based on real-world measurements, the paper systematically assesses this type of uncertainty.
Robert B. Chatfield, Meinrat O. Andreae, ARCTAS Science Team, and SEAC4RS Science Team
Atmos. Meas. Tech., 13, 7069–7096, https://doi.org/10.5194/amt-13-7069-2020, https://doi.org/10.5194/amt-13-7069-2020, 2020
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Forest burning affects air pollution and global climate. A NASA aircraft studied fire emissions including the Rim Fire near Yosemite. We found frequent confusions between the actual fire emission factors and other effects on the air samples. Effects on CO2 and CO can originate far upwind; the gases can mix variably into a smoke plume. We devised a theory of constant features in plumes. A statistical mixed-effects analysis of a co-emitted tracers model disentangles such mixing from fire effects.
Holger Vömel, Herman G. J. Smit, David Tarasick, Bryan Johnson, Samuel J. Oltmans, Henry Selkirk, Anne M. Thompson, Ryan M. Stauffer, Jacquelyn C. Witte, Jonathan Davies, Roeland van Malderen, Gary A. Morris, Tatsumi Nakano, and Rene Stübi
Atmos. Meas. Tech., 13, 5667–5680, https://doi.org/10.5194/amt-13-5667-2020, https://doi.org/10.5194/amt-13-5667-2020, 2020
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The time response of electrochemical concentration cell (ECC) ozonesondes points to at least two distinct reaction pathways with time constants of approximately 20 s and 25 min. Properly considering these time constants eliminates the need for a poorly defined "background" and allows reducing ad hoc corrections based on laboratory tests. This reduces the uncertainty of ECC ozonesonde measurements throughout the profile and especially in regions of low ozone and strong gradients of ozone.
Fan Zhou, Liwei Hou, Rui Zhong, Wei Chen, Xunpeng Ni, Shengda Pan, Ming Zhao, and Bowen An
Atmos. Meas. Tech., 13, 4899–4909, https://doi.org/10.5194/amt-13-4899-2020, https://doi.org/10.5194/amt-13-4899-2020, 2020
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On 15 July 2019, using an unmanned aerial vehicle (UAV), maritime authorities ferreted out a sailing ship whose fuel sulfur content (FSC) failed to meet Chinese regulations. This was the first time that a sailing ship had been caught for having failed the FSC regulations in China. The UAV system, method, and monitoring result utilized are discussed in this paper. We recommend that emissions from sailing ships be monitored more often in the open water in the future.
Bas Mijling
Atmos. Meas. Tech., 13, 4601–4617, https://doi.org/10.5194/amt-13-4601-2020, https://doi.org/10.5194/amt-13-4601-2020, 2020
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Many cities are experimenting with networks of low-cost sensors, complementary to their reference stations. Often the observations are published as dots on a map, as spatial interpolation is far from trivial. A new methodology to assimilate observations of different accuracy in a generic urban-air-quality model is introduced. It can be used for mapping local air quality based on reference measurements only or as a framework to integrate low-cost measurements next to official measurements.
Kukka-Maaria Kohonen, Pasi Kolari, Linda M. J. Kooijmans, Huilin Chen, Ulli Seibt, Wu Sun, and Ivan Mammarella
Atmos. Meas. Tech., 13, 3957–3975, https://doi.org/10.5194/amt-13-3957-2020, https://doi.org/10.5194/amt-13-3957-2020, 2020
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Biosphere–atmosphere gas exchange (flux) measurements of carbonyl sulfide (COS) are becoming popular for estimating biospheric photosynthesis. To compare COS flux measurements across different measurement sites, we need standardized protocols for data processing. We analyze how various data processing steps affect the calculated COS flux and how they differ from carbon dioxide (CO2) flux processing steps, and we aim to settle on a set of recommended protocols for COS flux calculation.
Michael Müller, Peter Graf, Jonas Meyer, Anastasia Pentina, Dominik Brunner, Fernando Perez-Cruz, Christoph Hüglin, and Lukas Emmenegger
Atmos. Meas. Tech., 13, 3815–3834, https://doi.org/10.5194/amt-13-3815-2020, https://doi.org/10.5194/amt-13-3815-2020, 2020
Yongbiao Weng, Alexandra Touzeau, and Harald Sodemann
Atmos. Meas. Tech., 13, 3167–3190, https://doi.org/10.5194/amt-13-3167-2020, https://doi.org/10.5194/amt-13-3167-2020, 2020
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We find that the known mixing ratio dependence of laser spectrometers for water vapour isotope measurements varies with isotope composition. We have developed a scheme to correct for this isotope-composition-dependent bias. The correction is most substantial at low mixing ratios. Stability tests indicate that the first-order dependency is a constant instrument characteristic. Water vapour isotope measurements at low mixing ratios can now be corrected by following our proposed procedure.
Pascal Wintjen, Christof Ammann, Frederik Schrader, and Christian Brümmer
Atmos. Meas. Tech., 13, 2923–2948, https://doi.org/10.5194/amt-13-2923-2020, https://doi.org/10.5194/amt-13-2923-2020, 2020
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With recent technological advances it is now possible to measure the exchange of trace gases between the land surface and the atmosphere. When using the so-called eddy-covariance method, certain corrections need to be applied to account for attenuation in the flux signal. These losses were found to be setup- and site-specific and can be up to 38 % for reactive nitrogen fluxes. We evaluated five different methods and recommend using an empirical version with locally measured cospectra.
Martin Kunz, Jost V. Lavric, Rainer Gasche, Christoph Gerbig, Richard H. Grant, Frank-Thomas Koch, Marcus Schumacher, Benjamin Wolf, and Matthias Zeeman
Atmos. Meas. Tech., 13, 1671–1692, https://doi.org/10.5194/amt-13-1671-2020, https://doi.org/10.5194/amt-13-1671-2020, 2020
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The nocturnal boundary layer (NBL) budget method enables the quantification of gas fluxes between ecosystems and the atmosphere under nocturnal stable stratification, a condition under which standard approaches struggle. However, up to now the application of the NBL method has been limited by difficulties in obtaining the required measurements. We show how an unmanned aircraft system (UAS) equipped with a carbon dioxide analyser can make this method more accessible.
Marcus Striednig, Martin Graus, Tilmann D. Märk, and Thomas G. Karl
Atmos. Meas. Tech., 13, 1447–1465, https://doi.org/10.5194/amt-13-1447-2020, https://doi.org/10.5194/amt-13-1447-2020, 2020
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The current work summarizes a long-term effort to provide an open-source code for the analysis of turbulent fluctuations of trace gases in the atmosphere by eddy covariance and disjunct eddy covariance, with a special focus on reactive gases that participate in atmospheric chemistry. The performance of the code is successfully evaluated based on measurements of minute fluxes of non-methane volatile organic compounds into the urban atmosphere.
Friedemann Reum, Mathias Göckede, Jost V. Lavric, Olaf Kolle, Sergey Zimov, Nikita Zimov, Martijn Pallandt, and Martin Heimann
Atmos. Meas. Tech., 12, 5717–5740, https://doi.org/10.5194/amt-12-5717-2019, https://doi.org/10.5194/amt-12-5717-2019, 2019
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We present continuous in situ measurements of atmospheric CO2 and CH4 mole fractions at the new station Ambarchik, located in northeastern Siberia. We describe the site, measurements and quality control, characterize the signals in comparison with data from Barrow, Alaska, and show which regions the measurements are sensitive to. Ambarchik data are available upon request.
Nathan Hilker, Jonathan M. Wang, Cheol-Heon Jeong, Robert M. Healy, Uwayemi Sofowote, Jerzy Debosz, Yushan Su, Michael Noble, Anthony Munoz, Geoff Doerksen, Luc White, Céline Audette, Dennis Herod, Jeffrey R. Brook, and Greg J. Evans
Atmos. Meas. Tech., 12, 5247–5261, https://doi.org/10.5194/amt-12-5247-2019, https://doi.org/10.5194/amt-12-5247-2019, 2019
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Increased interest in monitoring air quality near roadways, combined with traffic's often unclear contribution to elevated concentrations, has created a need for better interpretation of these data. Using 2 years of measurements collected during a near-road monitoring project in Canada, this paper contrasts three methods for estimating the fraction of roadside pollution resulting from on-road traffic. Robustness of these methods was compared with tandem measurements at background locations.
Laura Cartwright, Andrew Zammit-Mangion, Sangeeta Bhatia, Ivan Schroder, Frances Phillips, Trevor Coates, Karita Negandhi, Travis Naylor, Martin Kennedy, Steve Zegelin, Nick Wokker, Nicholas M. Deutscher, and Andrew Feitz
Atmos. Meas. Tech., 12, 4659–4676, https://doi.org/10.5194/amt-12-4659-2019, https://doi.org/10.5194/amt-12-4659-2019, 2019
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Despite extensive research, emission detection and quantification of greenhouse gases (GHGs) remain an open problem. This article presents a novel statistical framework for detecting and quantifying methane emissions and showcases its efficacy on data collected from different instruments in the 2015 Ginninderra controlled-release experiment. The developed techniques can be used to aid GHG emission reduction schemes by, for example, detecting and quantifying leaks from carbon storage facilities.
Sharad Vikram, Ashley Collier-Oxandale, Michael H. Ostertag, Massimiliano Menarini, Camron Chermak, Sanjoy Dasgupta, Tajana Rosing, Michael Hannigan, and William G. Griswold
Atmos. Meas. Tech., 12, 4211–4239, https://doi.org/10.5194/amt-12-4211-2019, https://doi.org/10.5194/amt-12-4211-2019, 2019
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Low-cost air quality sensors are enabling people to collect data to better understand their local environment and potential exposures. However, there is some concern regarding how reliable the calibrations of these sensors are in new and different environments. To explore this issue, our team colocated sensors at three different sites with high-quality monitoring instruments to compare to. We explored the transferability of calibration models as well as approaches to improve reliability.
Yanjun Zhang, Otso Peräkylä, Chao Yan, Liine Heikkinen, Mikko Äijälä, Kaspar R. Daellenbach, Qiaozhi Zha, Matthieu Riva, Olga Garmash, Heikki Junninen, Pentti Paatero, Douglas Worsnop, and Mikael Ehn
Atmos. Meas. Tech., 12, 3761–3776, https://doi.org/10.5194/amt-12-3761-2019, https://doi.org/10.5194/amt-12-3761-2019, 2019
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Recent advancements in atmospheric mass spectrometry provide large amounts of new information but at the same time present considerable challenges for the data analysis, for example, in high-resolution peak identification and separation. To address these problems, this study presents a simple and novel method, which succeeds in analyzing both synthetic and ambient datasets. We believe it will become a powerful approach in the data analysis of mass spectra.
Cheng-Hsien Lin, Richard H. Grant, Albert J. Heber, and Cliff T. Johnston
Atmos. Meas. Tech., 12, 3403–3415, https://doi.org/10.5194/amt-12-3403-2019, https://doi.org/10.5194/amt-12-3403-2019, 2019
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The open-path FTIR (OP-FTIR) is often used to measure the atmospheric gas composition and concentrations. The OP-FTIR, however, is sensitive to the changed ambient factors, which likely led to quantitative biases. This study developed methods to minimize the effect of the ambient temperature and humidity on N2O/CO2 quantification. These methods can help the users who implement the OP-FTIR to estimate gas fluxes in the agroecosystem achieve more precise and accurate estimations.
David D. Parrish, Richard G. Derwent, Simon O'Doherty, and Peter G. Simmonds
Atmos. Meas. Tech., 12, 3383–3394, https://doi.org/10.5194/amt-12-3383-2019, https://doi.org/10.5194/amt-12-3383-2019, 2019
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We present a flexible method that employs a power series expansion and Fourier series analysis to characterize the average long-term change and seasonal cycle, respectively, from a time series of observations of a trace atmospheric species. This approach maximizes the statistically significant information derived, including non-linear aspects of the long-term trends, without over fitting the data. Generally, a small set of parameter values (e.g., 7 or 8) provides this characterization.
Martin Horbanski, Denis Pöhler, Johannes Lampel, and Ulrich Platt
Atmos. Meas. Tech., 12, 3365–3381, https://doi.org/10.5194/amt-12-3365-2019, https://doi.org/10.5194/amt-12-3365-2019, 2019
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ICAD allows a precise in situ measurement of gases like NO2 in a relatively simple and compact setup. The main advantage in comparison to most other optical methods is that it does not require a stable total light intensity. This allows a simpler and mobile instrument setup and additionally it features no observed cross-interferences. We validated the high quality for an ICAD NO2 instrument in different inter-comparisons with a detection limit of 0.02 ppbv.
Shuaixi Liang, Min Qin, Pinhua Xie, Jun Duan, Wu Fang, Yabai He, Jin Xu, Jingwei Liu, Xin Li, Ke Tang, Fanhao Meng, Kaidi Ye, Jianguo Liu, and Wenqing Liu
Atmos. Meas. Tech., 12, 2499–2512, https://doi.org/10.5194/amt-12-2499-2019, https://doi.org/10.5194/amt-12-2499-2019, 2019
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A home-built instrument of an incoherent broadband cavity-enhanced absorption spectrometer is reported for sensitive detection of CHOCHO and NO2 in China's highly polluted environment. An NO2 spectral profile measured using the same spectrometer is applied as a reference spectral profile in the subsequent atmospheric spectral analysis and retrieval of NO2 and CHOCHO. This will provide an idea for solving the problem of cross-interference of strongly absorbing gases in weakly absorbing gases.
Angel J. Gomez-Pelaez, Ramon Ramos, Emilio Cuevas, Vanessa Gomez-Trueba, and Enrique Reyes
Atmos. Meas. Tech., 12, 2043–2066, https://doi.org/10.5194/amt-12-2043-2019, https://doi.org/10.5194/amt-12-2043-2019, 2019
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In 2015, a CO2/CH4/CO CRDS was installed at Izaña station (Tenerife). We present the acceptance tests, the processing of raw data applied, the ambient measurements performed, and their comparison with other continuous in situ measurements. We determine linear relationships between flow rate, CRDS inlet pressure, and CRDS outlet valve aperture; a slight CO2 correction that takes into account changes in the inlet pressure/flow rate and its origin; and the H2O correction for CO in a novel way.
Thomas Foken, Wolfgang Babel, and Christoph Thomas
Atmos. Meas. Tech., 12, 971–976, https://doi.org/10.5194/amt-12-971-2019, https://doi.org/10.5194/amt-12-971-2019, 2019
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Recently reported trends of carbon dioxide uptake pose the question of whether trends may be the result of the limited digitalization of gas analysers and sonic anemometers used in the 1990s. Modifying a 12 bit digitalization and the instrument error reported for the R2 and R3 sonic anemometers found elsewhere, the influence of these deficits in comparison to the now commonly used 16 bit digitalization were quantified. Both issues have an effect only on trace gas fluxes of small magnitude.
Carl Malings, Rebecca Tanzer, Aliaksei Hauryliuk, Sriniwasa P. N. Kumar, Naomi Zimmerman, Levent B. Kara, Albert A. Presto, and R. Subramanian
Atmos. Meas. Tech., 12, 903–920, https://doi.org/10.5194/amt-12-903-2019, https://doi.org/10.5194/amt-12-903-2019, 2019
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This paper compares several methods for calibrating data from low-cost air quality monitors to reflect the concentrations of various gaseous pollutants in the atmosphere, identifying the best-performing approaches. With these calibration methods, such monitors can be used to gather information on air quality at a higher spatial resolution than is possible using traditional technologies and can be deployed to areas (e.g. developing countries) where there are no existing monitor networks.
Ying Zhu, Ka Lok Chan, Yun Fat Lam, Martin Horbanski, Denis Pöhler, Johannes Boll, Ivo Lipkowitsch, Sheng Ye, and Mark Wenig
Atmos. Meas. Tech., 11, 6719–6734, https://doi.org/10.5194/amt-11-6719-2018, https://doi.org/10.5194/amt-11-6719-2018, 2018
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The paper presents an investigation of spatio-temporal variability of street-level NO2 in Hong Kong using mobile cavity-enhanced differential optical absorption spectroscopy (DOAS) and long-path DOAS. Measurements were conducted in December 2010 and March 2017. A significant decreasing trend in on-road NO2 was found by comparing measurements taken in 2010 and 2017. Influences of changes in bus companies' operation strategies can also be observed from the measured NO2 concentration maps.
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Short summary
Low-cost sensors promise neighborhood-scale air quality monitoring but have been plagued by inconsistent performance for precision, accuracy, and drift. CMU and SenSevere collaborated to develop the RAMP, which uses electrochemical sensors. We present a machine learning algorithm that overcomes previous performance issues and meets US EPA's data quality recommendations for personal exposure for NO2 and tougher "supplemental monitoring" standards for CO & ozone across 19 RAMPs for several months.
Low-cost sensors promise neighborhood-scale air quality monitoring but have been plagued by...
