Articles | Volume 9, issue 2
https://doi.org/10.5194/amt-9-347-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-347-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
04 Feb 2016
Research article |
| 04 Feb 2016
Mobile sensor network noise reduction and recalibration using a Bayesian network
Y. Xiang
CORRESPONDING AUTHOR
College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
Y. Tang
College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
W. Zhu
College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
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
Data Quality Enhancement for Atmospheric Chemistry Field Experiments via Sequential Monte Carlo Filters
Real-world wintertime CO, N2O, and CO2 emissions of a central European village
Evaluation of two common source estimation measurement strategies using large-eddy simulation of plume dispersion under neutral atmospheric conditions
Machine learning techniques to improve the field performance of low-cost air quality sensors
Estimation of sulfuric acid concentration using ambient ion composition and concentration data obtained with atmospheric pressure interface time-of-flight ion mass spectrometer
Importance of the Webb, Pearman, and Leuning (WPL) correction for the measurement of small CO2 fluxes
Unravelling a black box: an open-source methodology for the field calibration of small air quality sensors
An algorithm to detect non-background signals in greenhouse gas time series from European tall tower and mountain stations
Mobile atmospheric measurements and local-scale inverse estimation of the location and rates of brief CH4 and CO2 releases from point sources
SIBaR: a new method for background quantification and removal from mobile air pollution measurements
Machine learning calibration of low-cost NO2 and PM10 sensors: non-linear algorithms and their impact on site transferability
The high-frequency response correction of eddy covariance fluxes – Part 2: An experimental approach for analysing noisy measurements of small fluxes
The high-frequency response correction of eddy covariance fluxes – Part 1: An experimental approach and its interdependence with the time-lag estimation
Uncertainty of hourly-average concentration values derived from non-continuous measurements
Emissions relationships in western forest fire plumes – Part 1: Reducing the effect of mixing errors on emission factors
A new method to correct the electrochemical concentration cell (ECC) ozonesonde time response and its implications for “background current” and pump efficiency
Monitoring the compliance of sailing ships with fuel sulfur content regulations using unmanned aerial vehicle (UAV) measurements of ship emissions in open water
High-resolution mapping of urban air quality with heterogeneous observations: a new methodology and its application to Amsterdam
Towards standardized processing of eddy covariance flux measurements of carbonyl sulfide
Integration and calibration of non-dispersive infrared (NDIR) CO2 low-cost sensors and their operation in a sensor network covering Switzerland
Correcting the impact of the isotope composition on the mixing ratio dependency of water vapour isotope measurements with cavity ring-down spectrometers
Correcting high-frequency losses of reactive nitrogen flux measurements
Surface flux estimates derived from UAS-based mole fraction measurements by means of a nocturnal boundary layer budget approach
InnFLUX – an open-source code for conventional and disjunct eddy covariance analysis of trace gas measurements: an urban test case
Accurate measurements of atmospheric carbon dioxide and methane mole fractions at the Siberian coastal site Ambarchik
Traffic-related air pollution near roadways: discerning local impacts from background
Bayesian atmospheric tomography for detection and quantification of methane emissions: application to data from the 2015 Ginninderra release experiment
Evaluating and improving the reliability of gas-phase sensor system calibrations across new locations for ambient measurements and personal exposure monitoring
A novel approach for simple statistical analysis of high-resolution mass spectra
Application of open-path Fourier transform infrared spectroscopy (OP-FTIR) to measure greenhouse gas concentrations from agricultural fields
Flexible approach for quantifying average long-term changes and seasonal cycles of tropospheric trace species
The ICAD (iterative cavity-enhanced DOAS) method
Development of an incoherent broadband cavity-enhanced absorption spectrometer for measurements of ambient glyoxal and NO2 in a polluted urban environment
Atmospheric CO2, CH4, and CO with the CRDS technique at the Izaña Global GAW station: instrumental tests, developments, and first measurement results
Possible errors in flux measurements due to limited digitalization
Development of a general calibration model and long-term performance evaluation of low-cost sensors for air pollutant gas monitoring
Analysis of spatial and temporal patterns of on-road NO2 concentrations in Hong Kong
Testing the performance of field calibration techniques for low-cost gas sensors in new deployment locations: across a county line and across Colorado
Calibration of isotopologue-specific optical trace gas analysers: a practical guide
Uncertainty of eddy covariance flux measurements over an urban area based on two towers
Examination on total ozone column retrievals by Brewer spectrophotometry using different processing software
Uncertainty analysis of total ozone derived from direct solar irradiance spectra in the presence of unknown spectral deviations
Identification of spikes associated with local sources in continuous time series of atmospheric CO, CO2 and CH4
Bootstrap inversion technique for atmospheric trace gas source detection and quantification using long open-path laser measurements
Adaptive selection of diurnal minimum variation: a statistical strategy to obtain representative atmospheric CO2 data and its application to European elevated mountain stations
A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring
Improved methods for signal processing in measurements of mercury by Tekran® 2537A and 2537B instruments
CH4 emission estimates from an active landfill site inferred from a combined approach of CFD modelling and in situ FTIR measurements
Eddy covariance carbonyl sulfide flux measurements with a quantum cascade laser absorption spectrometer
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.
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
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Field experiments in atmospheric chemistry provide insights into chemical interactions of our atmosphere. However, high data coverage and accuracy is 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 data sets. We test the algorithm for several applications and discuss limitations that depend on the specific variable and the dynamics.
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.
Joanna Gordon Casey and Michael P. Hannigan
Atmos. Meas. Tech., 11, 6351–6378, https://doi.org/10.5194/amt-11-6351-2018, https://doi.org/10.5194/amt-11-6351-2018, 2018
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Low-cost sensors have the potential to improve understanding of air quality in complex regions like oil and gas production basins. Regression methods have been used to quantify pollutants from sensor signals, but these methods have not been tested when sensors are moved to new sampling locations, away from model training locations. We use sensor data collected at multiple sites to test how well these field calibration methods perform when they are extended to new locations and times.
David W. T. Griffith
Atmos. Meas. Tech., 11, 6189–6201, https://doi.org/10.5194/amt-11-6189-2018, https://doi.org/10.5194/amt-11-6189-2018, 2018
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In recent years optical spectroscopic techniques have become commonly used in the determination of mole fractions of trace gases in air. These techniques in many cases determine the mole fractions of only individual isotopic variants (
isotopologues) of the trace gas, while for many applications the total mole fraction of all isotopologues is required. This paper sets out the measurements and calculations required to convert between individual isotopologue and total trace gas amounts.
Leena Järvi, Üllar Rannik, Tom V. Kokkonen, Mona Kurppa, Ari Karppinen, Rostislav D. Kouznetsov, Pekka Rantala, Timo Vesala, and Curtis R. Wood
Atmos. Meas. Tech., 11, 5421–5438, https://doi.org/10.5194/amt-11-5421-2018, https://doi.org/10.5194/amt-11-5421-2018, 2018
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Identical EC systems on two sides of a building in central Helsinki were used to assess the uncertainty of the vertical fluxes on the single measurement point from July 2013 to September 2015. Sampling at only one point yielded up to 12% underestimation in the cumulative carbon fluxes; for sensible and latent heat the respective values were up to 5 and 8%. The commonly used statistics, kurtosis and skewness, are not necessarily suitable for filtering out data in a densely built urban area.
Anna Maria Siani, Francesca Frasca, Francesco Scarlatti, Arianna Religi, Henri Diémoz, Giuseppe R. Casale, Massimiliano Pedone, and Volodya Savastiouk
Atmos. Meas. Tech., 11, 5105–5123, https://doi.org/10.5194/amt-11-5105-2018, https://doi.org/10.5194/amt-11-5105-2018, 2018
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Total ozone columns (TOCs) measured by Brewer spectrophotometers located at Rome and Aosta (Italy) were calculated using different processing software packages, and the differences in the TOC retrievals are investigated. Large differences in TOC retrievals can be experienced when the instrumental sensitivity exhibits a long-term drift. The variability in TOC retrievals depends on the algorithm for calculating the standard lamp correction.
Anna Vaskuri, Petri Kärhä, Luca Egli, Julian Gröbner, and Erkki Ikonen
Atmos. Meas. Tech., 11, 3595–3610, https://doi.org/10.5194/amt-11-3595-2018, https://doi.org/10.5194/amt-11-3595-2018, 2018
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In this work, we introduce a Monte Carlo uncertainty analysis that takes into account possible systematic spectral deviations in the atmospheric full spectrum ozone retrieval method. Accounting for possible systematic spectral deviations in the spectral data is important since they produce larger total ozone column uncertainties than uncorrelated noise-like variations that traditional uncertainty estimations predict.
Abdelhadi El Yazidi, Michel Ramonet, Philippe Ciais, Gregoire Broquet, Isabelle Pison, Amara Abbaris, Dominik Brunner, Sebastien Conil, Marc Delmotte, Francois Gheusi, Frederic Guerin, Lynn Hazan, Nesrine Kachroudi, Giorgos Kouvarakis, Nikolaos Mihalopoulos, Leonard Rivier, and Dominique Serça
Atmos. Meas. Tech., 11, 1599–1614, https://doi.org/10.5194/amt-11-1599-2018, https://doi.org/10.5194/amt-11-1599-2018, 2018
Caroline B. Alden, Subhomoy Ghosh, Sean Coburn, Colm Sweeney, Anna Karion, Robert Wright, Ian Coddington, Gregory B. Rieker, and Kuldeep Prasad
Atmos. Meas. Tech., 11, 1565–1582, https://doi.org/10.5194/amt-11-1565-2018, https://doi.org/10.5194/amt-11-1565-2018, 2018
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The location and sizing leaks of methane from natural gas operations poses a real challenge for greenhouse gas emission mitigation efforts and for accurate quantification of emissions inventories. We demonstrate, with synthetic and field tests, a new statistical method for the location and sizing of small trace gas point sources dispersed over large areas, based on measurements of ambient atmospheric conditions made with long-range, open-path laser-based atmospheric observations.
Ye Yuan, Ludwig Ries, Hannes Petermeier, Martin Steinbacher, Angel J. Gómez-Peláez, Markus C. Leuenberger, Marcus Schumacher, Thomas Trickl, Cedric Couret, Frank Meinhardt, and Annette Menzel
Atmos. Meas. Tech., 11, 1501–1514, https://doi.org/10.5194/amt-11-1501-2018, https://doi.org/10.5194/amt-11-1501-2018, 2018
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This paper presents a novel statistical method, ADVS, for baseline selection of representative CO2 data at elevated mountain measurement stations. It provides insights on how data processing techniques are critical for measurements and data analyses. Compared with other statistical methods, our method appears to be a good option as a generalized approach with improved comparability, which is important for research on measurement site characteristics and comparisons between stations.
Naomi Zimmerman, Albert A. Presto, Sriniwasa P. N. Kumar, Jason Gu, Aliaksei Hauryliuk, Ellis S. Robinson, Allen L. Robinson, and R. Subramanian
Atmos. Meas. Tech., 11, 291–313, https://doi.org/10.5194/amt-11-291-2018, https://doi.org/10.5194/amt-11-291-2018, 2018
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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.
Jesse L. Ambrose
Atmos. Meas. Tech., 10, 5063–5073, https://doi.org/10.5194/amt-10-5063-2017, https://doi.org/10.5194/amt-10-5063-2017, 2017
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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.
Hannah Sonderfeld, Hartmut Bösch, Antoine P. R. Jeanjean, Stuart N. Riddick, Grant Allen, Sébastien Ars, Stewart Davies, Neil Harris, Neil Humpage, Roland Leigh, and Joseph Pitt
Atmos. Meas. Tech., 10, 3931–3946, https://doi.org/10.5194/amt-10-3931-2017, https://doi.org/10.5194/amt-10-3931-2017, 2017
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The waste sector is the second largest source of methane in the UK. However, uncertainties of methane emissions from landfill sites still remain. In this study we present a new approach for the estimation of methane emissions from a landfill site by applying a computational fluid dynamics (CFD) model for precise measurements of methane with in situ Fourier-transform infrared (FTIR) spectroscopy. Different source areas could be distinguished with this method and their emissions were assessed.
Katharina Gerdel, Felix Maximilian Spielmann, Albin Hammerle, and Georg Wohlfahrt
Atmos. Meas. Tech., 10, 3525–3537, https://doi.org/10.5194/amt-10-3525-2017, https://doi.org/10.5194/amt-10-3525-2017, 2017
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Short summary
Motivated by unreliable sensor readings and the difficulties in calibrating sensors, we developed a Bayesian-network-based method to remove the abnormal readings and re-calibrate the sensors.
Motivated by unreliable sensor readings and the difficulties in calibrating sensors, we...
