Articles | Volume 12, issue 9
https://doi.org/10.5194/amt-12-4659-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-12-4659-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Sep 2019
Research article |
| 02 Sep 2019
| 02 Sep 2019
Bayesian atmospheric tomography for detection and quantification of methane emissions: application to data from the 2015 Ginninderra release experiment
School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, Australia
Andrew Zammit-Mangion
School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, Australia
Sangeeta Bhatia
Centre for Research in Mathematics, Western Sydney University, Parramatta, Australia
currently at: School of Public Health, Imperial College London, London, UK
Ivan Schroder
Geoscience Australia, Canberra, Australia
Frances Phillips
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
Trevor Coates
School of Agriculture and Food, University of Melbourne, Melbourne, Australia
Karita Negandhi
Department of Earth and Planetary Sciences, Macquarie University, Sydney, Australia
currently at: Office of Environment and Heritage, Parramatta, Australia
Travis Naylor
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
Martin Kennedy
Department of Earth and Planetary Sciences, Macquarie University, Sydney, Australia
Steve Zegelin
CSIRO Oceans and Atmosphere, Canberra, Australia
Nick Wokker
Department of Industry, Innovation and Science, Canberra, Australia
Nicholas M. Deutscher
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
Andrew Feitz
Geoscience Australia, Canberra, Australia
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Benedikt Herkommer, Carlos Alberti, Paolo Castracane, Jia Chen, Angelika Dehn, Florian Dietrich, Nicholas M. Deutscher, Matthias Max Frey, Jochen Groß, Lawson Gillespie, Frank Hase, Isamu Morino, Nasrin Mostafavi Pak, Brittany Walker, and Debra Wunch
EGUsphere, https://doi.org/10.5194/egusphere-2023-3089, https://doi.org/10.5194/egusphere-2023-3089, 2024
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The Total Carbon Column Observing Network is a network of ground based Fourier Transform Infrared (FTIR) spectrometers used mainly for satellite validation. To ensure the highest quality validation data, the network needs to be highly consistent. This is a major challenge, which so far is solved by site comparisons with airborne in-situ measurements. In this work, we describe the use of a portable FTIR spectrometer as a Travel Standard for evaluating the consistency of TCCON sites.
Joshua L. Laughner, Geoffrey C. Toon, Joseph Mendonca, Christof Petri, Sébastien Roche, Debra Wunch, Jean-Francois Blavier, David W. T. Griffith, Pauli Heikkinen, Ralph F. Keeling, Matthäus Kiel, Rigel Kivi, Coleen M. Roehl, Britton B. Stephens, Bianca C. Baier, Huilin Chen, Yonghoon Choi, Nicholas M. Deutscher, Joshua P. DiGangi, Jochen Gross, Benedikt Herkommer, Pascal Jeseck, Thomas Laemmel, Xin Lan, Erin McGee, Kathryn McKain, John Miller, Isamu Morino, Justus Notholt, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Haris Riris, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Steven C. Wofsy, Minqiang Zhou, and Paul O. Wennberg
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-331, https://doi.org/10.5194/essd-2023-331, 2023
Revised manuscript accepted for ESSD
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This paper describes a new version, called GGG2020, of a dataset containing column-integrated observations of greenhouse and related gases (including CO2, CH4, CO, and N2O) made by ground stations located around the world. Compared to the previous version (GGG2014), improvements have been made towards site-to-site consistency. This dataset plays a key role in validating space-based greenhouse gas observations and in understanding the carbon cycle.
Yifan Guan, Gretchen Keppel-Aleks, Scott C. Doney, Christof Petri, Dave Pollard, Debra Wunch, Frank Hase, Hirofumi Ohyama, Isamu Morino, Justus Notholt, Kei Shiomi, Kim Strong, Rigel Kivi, Matthias Buschmann, Nicholas Deutscher, Paul Wennberg, Ralf Sussmann, Voltaire A. Velazco, and Yao Té
Atmos. Chem. Phys., 23, 5355–5372, https://doi.org/10.5194/acp-23-5355-2023, https://doi.org/10.5194/acp-23-5355-2023, 2023
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We characterize spatial–temporal patterns of interannual variability (IAV) in atmospheric CO2 based on NASA’s Orbiting Carbon Observatory-2 (OCO-2). CO2 variation is strongly impacted by climate events, with higher anomalies during El Nino years. We show high correlation in IAV between space-based and ground-based CO2 from long-term sites. Because OCO-2 has near-global coverage, our paper provides a roadmap to study IAV where in situ observation is sparse, such as open oceans and remote lands.
Yu Someya, Yukio Yoshida, Hirofumi Ohyama, Shohei Nomura, Akihide Kamei, Isamu Morino, Hitoshi Mukai, Tsuneo Matsunaga, Joshua L. Laughner, Voltaire A. Velazco, Benedikt Herkommer, Yao Té, Mahesh Kumar Sha, Rigel Kivi, Minqiang Zhou, Young Suk Oh, Nicholas M. Deutscher, and David W. T. Griffith
Atmos. Meas. Tech., 16, 1477–1501, https://doi.org/10.5194/amt-16-1477-2023, https://doi.org/10.5194/amt-16-1477-2023, 2023
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The updated retrieval algorithm for the Greenhouse gases Observing SATellite level 2 product is presented. The main changes in the algorithm from the previous one are the treatment of cirrus clouds, the degradation model of the sensor, solar irradiance, and gas absorption coefficient tables. The retrieval results showed improvements in fitting accuracy and an increase in the data amount over land. On the other hand, there are still large biases of XCO2 which should be corrected over the ocean.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Angharad C. Stell, Michael Bertolacci, Andrew Zammit-Mangion, Matthew Rigby, Paul J. Fraser, Christina M. Harth, Paul B. Krummel, Xin Lan, Manfredi Manizza, Jens Mühle, Simon O'Doherty, Ronald G. Prinn, Ray F. Weiss, Dickon Young, and Anita L. Ganesan
Atmos. Chem. Phys., 22, 12945–12960, https://doi.org/10.5194/acp-22-12945-2022, https://doi.org/10.5194/acp-22-12945-2022, 2022
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Nitrous oxide is a potent greenhouse gas and ozone-depleting substance, whose atmospheric abundance has risen throughout the contemporary record. In this work, we carry out the first global hierarchical Bayesian inversion to solve for nitrous oxide emissions. We derive increasing global nitrous oxide emissions over 2011–2020, which are mainly driven by emissions between 0° and 30°N, with the highest emissions recorded in 2020.
Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
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We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Yohanna Villalobos, Peter J. Rayner, Jeremy D. Silver, Steven Thomas, Vanessa Haverd, Jürgen Knauer, Zoë M. Loh, Nicholas M. Deutscher, David W. T. Griffith, and David F. Pollard
Atmos. Chem. Phys., 22, 8897–8934, https://doi.org/10.5194/acp-22-8897-2022, https://doi.org/10.5194/acp-22-8897-2022, 2022
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We study the interannual variability in Australian carbon fluxes for 2015–2019 derived from OCO-2 satellite data. Our results suggest that Australia's semi-arid ecosystems are highly responsive to variations in climate drivers such as rainfall and temperature. We found that high rainfall and low temperatures recorded in 2016 led to an anomalous carbon sink over savanna and sparsely vegetated regions, while unprecedented dry and hot weather in 2019 led to anomalous carbon release.
Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Oliver Schneising, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Robert J. Parker, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Markus Rettinger, Coleen Roehl, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, and Thorsten Warneke
Atmos. Meas. Tech., 15, 3401–3437, https://doi.org/10.5194/amt-15-3401-2022, https://doi.org/10.5194/amt-15-3401-2022, 2022
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We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products.
In addition to an increased number of XCO2 data, v3 also includes products for XCH4 (full-physics and proxy), XH2O and the relative ratio of HDO to H2O (δD). For GOSAT-2, we also present first XCO and XN2O results. All FOCAL data products show reasonable spatial distribution and temporal variations and agree well with TCCON. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb.
Carlos Alberti, Frank Hase, Matthias Frey, Darko Dubravica, Thomas Blumenstock, Angelika Dehn, Paolo Castracane, Gregor Surawicz, Roland Harig, Bianca C. Baier, Caroline Bès, Jianrong Bi, Hartmut Boesch, André Butz, Zhaonan Cai, Jia Chen, Sean M. Crowell, Nicholas M. Deutscher, Dragos Ene, Jonathan E. Franklin, Omaira García, David Griffith, Bruno Grouiez, Michel Grutter, Abdelhamid Hamdouni, Sander Houweling, Neil Humpage, Nicole Jacobs, Sujong Jeong, Lilian Joly, Nicholas B. Jones, Denis Jouglet, Rigel Kivi, Ralph Kleinschek, Morgan Lopez, Diogo J. Medeiros, Isamu Morino, Nasrin Mostafavipak, Astrid Müller, Hirofumi Ohyama, Paul I. Palmer, Mahesh Pathakoti, David F. Pollard, Uwe Raffalski, Michel Ramonet, Robbie Ramsay, Mahesh Kumar Sha, Kei Shiomi, William Simpson, Wolfgang Stremme, Youwen Sun, Hiroshi Tanimoto, Yao Té, Gizaw Mengistu Tsidu, Voltaire A. Velazco, Felix Vogel, Masataka Watanabe, Chong Wei, Debra Wunch, Marcia Yamasoe, Lu Zhang, and Johannes Orphal
Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, https://doi.org/10.5194/amt-15-2433-2022, 2022
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Space-borne greenhouse gas missions require ground-based validation networks capable of providing fiducial reference measurements. Here, considerable refinements of the calibration procedures for the COllaborative Carbon Column Observing Network (COCCON) are presented. Laboratory and solar side-by-side procedures for the characterization of the spectrometers have been refined and extended. Revised calibration factors for XCO2, XCO and XCH4 are provided, incorporating 47 new spectrometers.
Edward Malina, Ben Veihelmann, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, and Isamu Morino
Atmos. Meas. Tech., 15, 2377–2406, https://doi.org/10.5194/amt-15-2377-2022, https://doi.org/10.5194/amt-15-2377-2022, 2022
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Methane retrievals from remote sensing instruments are fundamentally based on spectroscopic parameters, which indicate spectral-line positions, and their characteristics. These parameters are stored in several databases that vary in their make-up. Here we assess how concentrations of methane isotopologues measured from the same Total Carbon Column Observing Network (TCCON) instruments vary across a range of spectral windows using different spectroscopic databases and comment on the implications.
Stephen J. Chuter, Andrew Zammit-Mangion, Jonathan Rougier, Geoffrey Dawson, and Jonathan L. Bamber
The Cryosphere, 16, 1349–1367, https://doi.org/10.5194/tc-16-1349-2022, https://doi.org/10.5194/tc-16-1349-2022, 2022
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We find the Antarctic Peninsula to have a mean mass loss of 19 ± 1.1 Gt yr−1 over the 2003–2019 period, driven predominantly by changes in ice dynamic flow like due to changes in ocean forcing. This long-term record is crucial to ascertaining the region’s present-day contribution to sea level rise, with the understanding of driving processes enabling better future predictions. Our statistical approach enables us to estimate this previously poorly surveyed regions mass balance more accurately.
Thomas E. Taylor, Christopher W. O'Dell, David Crisp, Akhiko Kuze, Hannakaisa Lindqvist, Paul O. Wennberg, Abhishek Chatterjee, Michael Gunson, Annmarie Eldering, Brendan Fisher, Matthäus Kiel, Robert R. Nelson, Aronne Merrelli, Greg Osterman, Frédéric Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Cheng Liu, Martine De Mazière, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Matthias Schneider, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, and Debra Wunch
Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, https://doi.org/10.5194/essd-14-325-2022, 2022
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We provide an analysis of an 11-year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite. The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.
Andrew Zammit-Mangion, Michael Bertolacci, Jenny Fisher, Ann Stavert, Matthew Rigby, Yi Cao, and Noel Cressie
Geosci. Model Dev., 15, 45–73, https://doi.org/10.5194/gmd-15-45-2022, https://doi.org/10.5194/gmd-15-45-2022, 2022
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We present a framework for estimating the sources and sinks (flux) of carbon dioxide from satellite data. The framework is statistical and yields measures of uncertainty alongside all estimates of flux and other parameters in the underlying model. It also allows us to generate other insights, such as the size of errors and biases in the data. The primary aim of this research was to develop a fully statistical flux inversion framework for use by atmospheric scientists.
Yohanna Villalobos, Peter J. Rayner, Jeremy D. Silver, Steven Thomas, Vanessa Haverd, Jürgen Knauer, Zoë M. Loh, Nicholas M. Deutscher, David W. T. Griffith, and David F. Pollard
Atmos. Chem. Phys., 21, 17453–17494, https://doi.org/10.5194/acp-21-17453-2021, https://doi.org/10.5194/acp-21-17453-2021, 2021
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Semi-arid ecosystems such as those in Australia are evolving and might play an essential role in the future of climate change. We use carbon dioxide concentrations derived from the OCO-2 satellite instrument and a regional transport model to understand if Australia was a carbon sink or source of CO2 in 2015. Our research's main findings suggest that Australia acted as a carbon sink of about −0.41 ± 0.08 petagrams of carbon in 2015, driven primarily by savanna and sparsely vegetated ecosystems.
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
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This paper presents, for the first time, Sentinel-5 Precursor methane and carbon monoxide validation results covering a period from November 2017 to September 2020. For this study, we used global TCCON and NDACC-IRWG network data covering a wide range of atmospheric and surface conditions across different terrains. We also show the influence of a priori alignment, smoothing uncertainties and the sensitivity of the validation results towards the application of advanced co-location criteria.
Beata Bukosa, Jenny Fisher, Nicholas Deutscher, and Dylan Jones
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-173, https://doi.org/10.5194/gmd-2021-173, 2021
Revised manuscript not accepted
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Human activities led to rising levels of greenhouse gases (carbon dioxide (CO2), methane (CH4), carbon monoxide (CO)) in the atmosphere, threatening our future. We use models and measurements to predict and understand the climatological impact of these gases. Here, we describe a new simulation in the GEOS-Chem model that uses a more accurate method to simulate CO2, CH4 and CO, through their chemical dependence. Relative to the original simulations our results agree better with measurements.
Ilya Stanevich, Dylan B. A. Jones, Kimberly Strong, Martin Keller, Daven K. Henze, Robert J. Parker, Hartmut Boesch, Debra Wunch, Justus Notholt, Christof Petri, Thorsten Warneke, Ralf Sussmann, Matthias Schneider, Frank Hase, Rigel Kivi, Nicholas M. Deutscher, Voltaire A. Velazco, Kaley A. Walker, and Feng Deng
Atmos. Chem. Phys., 21, 9545–9572, https://doi.org/10.5194/acp-21-9545-2021, https://doi.org/10.5194/acp-21-9545-2021, 2021
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We explore the utility of a weak-constraint (WC) four-dimensional variational (4D-Var) data assimilation scheme for mitigating systematic errors in methane simulation in the GEOS-Chem model. We use data from the Greenhouse Gases Observing Satellite (GOSAT) and show that, compared to the traditional 4D-Var approach, the WC scheme improves the agreement between the model and independent observations. We find that the WC corrections to the model provide insight into the source of the errors.
Matthieu Dogniaux, Cyril Crevoisier, Raymond Armante, Virginie Capelle, Thibault Delahaye, Vincent Cassé, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. Garcia, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, David F. Pollard, Coleen M. Roehl, Kei Shiomi, Kimberly Strong, Yao Té, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 14, 4689–4706, https://doi.org/10.5194/amt-14-4689-2021, https://doi.org/10.5194/amt-14-4689-2021, 2021
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We present the Adaptable 4A Inversion (5AI), an implementation of the optimal estimation (OE) algorithm, relying on the Automatized Atmospheric Absorption Atlas (4A/OP) radiative transfer model, that enables the retrieval of greenhouse gas atmospheric weighted columns from infrared measurements. It is tested on a sample of Orbiting Carbon Observatory-2 observations, and its results satisfactorily compare to several reference products, thus showing the reliability of 5AI OE implementation.
Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Isamu Morino, Justus Notholt, Hirofumi Ohyama, Christof Petri, James R. Podolske, David F. Pollard, Mahesh Kumar Sha, Kei Shiomi, Ralf Sussmann, Yao Té, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 14, 3837–3869, https://doi.org/10.5194/amt-14-3837-2021, https://doi.org/10.5194/amt-14-3837-2021, 2021
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We present the first GOSAT and GOSAT-2 XCO2 data derived with the FOCAL retrieval algorithm. Comparisons of the GOSAT-FOCAL product with other data reveal long-term agreement within about 1 ppm over 1 decade, differences in seasonal variations of about 0.5 ppm, and a mean regional bias to ground-based TCCON data of 0.56 ppm with a mean scatter of 1.89 ppm. GOSAT-2-FOCAL data are preliminary only, but first comparisons show that they compare well with the GOSAT-FOCAL results and TCCON.
Mei Bai, José I. Velazco, Trevor W. Coates, Frances A. Phillips, Thomas K. Flesch, Julian Hill, David G. Mayer, Nigel W. Tomkins, Roger S. Hegarty, and Deli Chen
Atmos. Meas. Tech., 14, 3469–3479, https://doi.org/10.5194/amt-14-3469-2021, https://doi.org/10.5194/amt-14-3469-2021, 2021
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The development and validation of management practices to mitigate methane (CH4) emissions from livestock require accurate emission measurements. We compared the inverse dispersion modelling (IDM) and tracer-ratio techniques to measure CH4 emissions from cattle. Both measurements agreed well but were higher than IPCC estimates. We suggest that the IDM approach can provide an accurate method of estimating cattle emissions, and IPCC estimates may have larger uncertainties.
Nicholas M. Deutscher, Travis A. Naylor, Christopher G. R. Caldow, Hamish L. McDougall, Alex G. Carter, and David W. T. Griffith
Atmos. Meas. Tech., 14, 3119–3130, https://doi.org/10.5194/amt-14-3119-2021, https://doi.org/10.5194/amt-14-3119-2021, 2021
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This work describes the performance of an open-path measurement system for greenhouse gases in an extended field trial. The instrument obtained measurement repeatability of 0.1 % or better for CO2 and CH4 measurements over a 1.55 km one-way pathway. Comparison to co-located in situ measurements allows characterisation of biases relative to global reference scales. The research was done to show the applicability of the technique and its ability to detect atmospheric-relevant sources and sinks.
Alba Lorente, Tobias Borsdorff, Andre Butz, Otto Hasekamp, Joost aan de Brugh, Andreas Schneider, Lianghai Wu, Frank Hase, Rigel Kivi, Debra Wunch, David F. Pollard, Kei Shiomi, Nicholas M. Deutscher, Voltaire A. Velazco, Coleen M. Roehl, Paul O. Wennberg, Thorsten Warneke, and Jochen Landgraf
Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, https://doi.org/10.5194/amt-14-665-2021, 2021
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TROPOMI aboard Sentinel-5P satellite provides methane (CH4) measurements with exceptional temporal and spatial resolution. The study describes a series of improvements developed to retrieve CH4 from TROPOMI. The updated CH4 product features (among others) a more accurate a posteriori correction derived independently of any reference data. The validation of the improved data product shows good agreement with ground-based and satellite measurements, which highlights the quality of the TROPOMI CH4.
Robert J. Parker, Alex Webb, Hartmut Boesch, Peter Somkuti, Rocio Barrio Guillo, Antonio Di Noia, Nikoleta Kalaitzi, Jasdeep S. Anand, Peter Bergamaschi, Frederic Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Coleen Roehl, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Thorsten Warneke, Paul O. Wennberg, and Debra Wunch
Earth Syst. Sci. Data, 12, 3383–3412, https://doi.org/10.5194/essd-12-3383-2020, https://doi.org/10.5194/essd-12-3383-2020, 2020
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This work presents the latest release of the University of Leicester GOSAT methane data and acts as the definitive description of this dataset. We detail the processing, validation and evaluation involved in producing these data and highlight its many applications. With now over a decade of global atmospheric methane observations, this dataset has helped, and will continue to help, us better understand the global methane budget and investigate how it may respond to a future changing climate.
Hirofumi Ohyama, Isamu Morino, Voltaire A. Velazco, Theresa Klausner, Gerry Bagtasa, Matthäus Kiel, Matthias Frey, Akihiro Hori, Osamu Uchino, Tsuneo Matsunaga, Nicholas M. Deutscher, Joshua P. DiGangi, Yonghoon Choi, Glenn S. Diskin, Sally E. Pusede, Alina Fiehn, Anke Roiger, Michael Lichtenstern, Hans Schlager, Pao K. Wang, Charles C.-K. Chou, Maria Dolores Andrés-Hernández, and John P. Burrows
Atmos. Meas. Tech., 13, 5149–5163, https://doi.org/10.5194/amt-13-5149-2020, https://doi.org/10.5194/amt-13-5149-2020, 2020
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Column-averaged dry-air mole fractions of CO2 and CH4 measured by a solar viewing portable Fourier transform spectrometer (EM27/SUN) were validated with in situ profile data obtained during the transfer flights of two aircraft campaigns. Atmospheric dynamical properties based on ERA5 and WRF-Chem were used as criteria for selecting the best aircraft profiles for the validation. The resulting air-mass-independent correction factors for the EM27/SUN data were 0.9878 for CO2 and 0.9829 for CH4.
Ilya Stanevich, Dylan B. A. Jones, Kimberly Strong, Robert J. Parker, Hartmut Boesch, Debra Wunch, Justus Notholt, Christof Petri, Thorsten Warneke, Ralf Sussmann, Matthias Schneider, Frank Hase, Rigel Kivi, Nicholas M. Deutscher, Voltaire A. Velazco, Kaley A. Walker, and Feng Deng
Geosci. Model Dev., 13, 3839–3862, https://doi.org/10.5194/gmd-13-3839-2020, https://doi.org/10.5194/gmd-13-3839-2020, 2020
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Systematic errors in atmospheric models pose a challenge for inverse modeling studies of methane (CH4) emissions. We evaluated the CH4 simulation in the GEOS-Chem model at the horizontal resolutions of 4° × 5° and 2° × 2.5°. Our analysis identified resolution-dependent biases in the model, which we attributed to discrepancies between the two model resolutions in vertical transport in the troposphere and in stratosphere–troposphere exchange.
Maximilian Reuter, Michael Buchwitz, Oliver Schneising, Stefan Noël, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Antonio Di Noia, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Lianghai Wu, Otto P. Hasekamp, Ilse Aben, Akihiko Kuze, Hiroshi Suto, Kei Shiomi, Yukio Yoshida, Isamu Morino, David Crisp, Christopher W. O'Dell, Justus Notholt, Christof Petri, Thorsten Warneke, Voltaire A. Velazco, Nicholas M. Deutscher, David W. T. Griffith, Rigel Kivi, David F. Pollard, Frank Hase, Ralf Sussmann, Yao V. Té, Kimberly Strong, Sébastien Roche, Mahesh K. Sha, Martine De Mazière, Dietrich G. Feist, Laura T. Iraci, Coleen M. Roehl, Christian Retscher, and Dinand Schepers
Atmos. Meas. Tech., 13, 789–819, https://doi.org/10.5194/amt-13-789-2020, https://doi.org/10.5194/amt-13-789-2020, 2020
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We present new satellite-derived data sets of atmospheric carbon dioxide (CO2) and methane (CH4). The data products are column-averaged dry-air mole fractions of CO2 and CH4, denoted XCO2 and XCH4. The products cover the years 2003–2018 and are merged Level 2 (satellite footprints) and merged Level 3 (gridded at monthly time and 5° x 5° spatial resolution) products obtained from combining several individual sensor products. We present the merging algorithms and product validation results.
Jonas Simon Wilzewski, Anke Roiger, Johan Strandgren, Jochen Landgraf, Dietrich G. Feist, Voltaire A. Velazco, Nicholas M. Deutscher, Isamu Morino, Hirofumi Ohyama, Yao Té, Rigel Kivi, Thorsten Warneke, Justus Notholt, Manvendra Dubey, Ralf Sussmann, Markus Rettinger, Frank Hase, Kei Shiomi, and André Butz
Atmos. Meas. Tech., 13, 731–745, https://doi.org/10.5194/amt-13-731-2020, https://doi.org/10.5194/amt-13-731-2020, 2020
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Through spectral degradation of GOSAT measurements in the 1.6 and 2.0 μm spectral bands, we mimic a single-band, passive satellite sensor for monitoring of CO2 emissions at fine spatial scales. We compare retrievals of XCO2 from these bands to TCCON and native GOSAT retrievals. At spectral resolutions near 1.3 nm, XCO2 retrievals from both bands show promising performance, but the 2.0 μm band is favorable due to better noise performance and the potential to retrieve some aerosol information.
Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, John P. Burrows, Tobias Borsdorff, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Christian Hermans, Laura T. Iraci, Rigel Kivi, Jochen Landgraf, Isamu Morino, Justus Notholt, Christof Petri, David F. Pollard, Sébastien Roche, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Voltaire A. Velazco, Thorsten Warneke, and Debra Wunch
Atmos. Meas. Tech., 12, 6771–6802, https://doi.org/10.5194/amt-12-6771-2019, https://doi.org/10.5194/amt-12-6771-2019, 2019
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We introduce an algorithm that is used to simultaneously derive the abundances of the important atmospheric constituents carbon monoxide and methane from the TROPOMI instrument onboard the Sentinel-5 Precursor satellite, which enables the determination of both gases with an unprecedented level of detail on a global scale. The quality of the resulting data sets is assessed and the first results are presented.
Susan S. Kulawik, Sean Crowell, David Baker, Junjie Liu, Kathryn McKain, Colm Sweeney, Sebastien C. Biraud, Steve Wofsy, Christopher W. O'Dell, Paul O. Wennberg, Debra Wunch, Coleen M. Roehl, Nicholas M. Deutscher, Matthäus Kiel, David W. T. Griffith, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Mazière, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, Dave F. Pollard, Isamu Morino, Osamu Uchino, Frank Hase, Dietrich G. Feist, Sébastien Roche, Kimberly Strong, Rigel Kivi, Laura Iraci, Kei Shiomi, Manvendra K. Dubey, Eliezer Sepulveda, Omaira Elena Garcia Rodriguez, Yao Té, Pascal Jeseck, Pauli Heikkinen, Edward J. Dlugokencky, Michael R. Gunson, Annmarie Eldering, David Crisp, Brendan Fisher, and Gregory B. Osterman
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-257, https://doi.org/10.5194/amt-2019-257, 2019
Publication in AMT not foreseen
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This paper provides a benchmark of OCO-2 v8 and ACOS-GOSAT v7.3 XCO2 and lowermost tropospheric (LMT) errors. The paper focuses on the systematic errors and subtracts out validation, co-location, and random errors, looks at the correlation scale-length (spatially and temporally) of systematic errors, finding that the scale lengths are similar to bias correction scale-lengths. The assimilates of the bias correction term is used to place an error on fluxes estimates.
Jacob K. Hedelius, Tai-Long He, Dylan B. A. Jones, Bianca C. Baier, Rebecca R. Buchholz, Martine De Mazière, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Laura T. Iraci, Pascal Jeseck, Matthäus Kiel, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Sébastien Roche, Coleen M. Roehl, Matthias Schneider, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Colm Sweeney, Yao Té, Osamu Uchino, Voltaire A. Velazco, Wei Wang, Thorsten Warneke, Paul O. Wennberg, Helen M. Worden, and Debra Wunch
Atmos. Meas. Tech., 12, 5547–5572, https://doi.org/10.5194/amt-12-5547-2019, https://doi.org/10.5194/amt-12-5547-2019, 2019
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We seek ways to improve the accuracy of column measurements of carbon monoxide (CO) – an important tracer of pollution – made from the MOPITT satellite instrument. We devise a filtering scheme which reduces the scatter and also eliminates bias among the MOPITT detectors. Compared to ground-based observations, MOPITT measurements are about 6 %–8 % higher. When MOPITT data are implemented in a global assimilation model, they tend to reduce the model mismatch with aircraft measurements.
Voltaire A. Velazco, Nicholas M. Deutscher, Isamu Morino, Osamu Uchino, Beata Bukosa, Masataka Ajiro, Akihide Kamei, Nicholas B. Jones, Clare Paton-Walsh, and David W. T. Griffith
Earth Syst. Sci. Data, 11, 935–946, https://doi.org/10.5194/essd-11-935-2019, https://doi.org/10.5194/essd-11-935-2019, 2019
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We present ground-based measurements of atmospheric carbon dioxide columns from a portable spectrometer taken in a semiarid region of Australia. We compared these measurements to space-based retrievals from the Greenhouse Gases Observing Satellite (GOSAT) and calibrated them against a Total Carbon Column Observing Network (TCCON) instrument to ascertain a retrieval bias. We also present the unique opportunities that Central Australia could offer in the context of satellite product validation.
Beata Bukosa, Nicholas M. Deutscher, Jenny A. Fisher, Dagmar Kubistin, Clare Paton-Walsh, and David W. T. Griffith
Atmos. Chem. Phys., 19, 7055–7072, https://doi.org/10.5194/acp-19-7055-2019, https://doi.org/10.5194/acp-19-7055-2019, 2019
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The carbon greenhouse gases (CO2, CH4 and CO) were proven to have a large impact on the global carbon cycle and our climate. To understand the variability of the carbon cycle and predict future climate change scenarios, we need to study the processes that drive the changes of these gases in the atmosphere. We study the sources and sinks of CO2, CH4 and CO with a combination of measurements and chemical transport modelling to identify missing, underestimated or overestimated sources in Australia.
Debra Wunch, Dylan B. A. Jones, Geoffrey C. Toon, Nicholas M. Deutscher, Frank Hase, Justus Notholt, Ralf Sussmann, Thorsten Warneke, Jeroen Kuenen, Hugo Denier van der Gon, Jenny A. Fisher, and Joannes D. Maasakkers
Atmos. Chem. Phys., 19, 3963–3980, https://doi.org/10.5194/acp-19-3963-2019, https://doi.org/10.5194/acp-19-3963-2019, 2019
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We used five atmospheric observatories in Europe measuring total column dry-air mole fractions of methane and carbon monoxide to infer methane emissions in the area between the observatories. We find that the methane emissions are overestimated by the state-of-the-art inventories, and that this is likely due, at least in part, to the inventory disaggregation. We find that there is significant uncertainty in the carbon monoxide inventories that requires further investigation.
Matthias Frey, Mahesh K. Sha, Frank Hase, Matthäus Kiel, Thomas Blumenstock, Roland Harig, Gregor Surawicz, Nicholas M. Deutscher, Kei Shiomi, Jonathan E. Franklin, Hartmut Bösch, Jia Chen, Michel Grutter, Hirofumi Ohyama, Youwen Sun, André Butz, Gizaw Mengistu Tsidu, Dragos Ene, Debra Wunch, Zhensong Cao, Omaira Garcia, Michel Ramonet, Felix Vogel, and Johannes Orphal
Atmos. Meas. Tech., 12, 1513–1530, https://doi.org/10.5194/amt-12-1513-2019, https://doi.org/10.5194/amt-12-1513-2019, 2019
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In a 3.5-year long study, the long-term performance of a mobile EM27/SUN spectrometer, used for greenhouse gas observations, is checked with respect to a co-located reference spectrometer. We find that the EM27/SUN is stable on timescales of several years, qualifying it for permanent carbon cycle studies.
The performance of an ensemble of 30 EM27/SUN spectrometers was also tested in the framework of the COllaborative Carbon Column Observing Network (COCCON) and found to be very uniform.
Minqiang Zhou, Bavo Langerock, Kelley C. Wells, Dylan B. Millet, Corinne Vigouroux, Mahesh Kumar Sha, Christian Hermans, Jean-Marc Metzger, Rigel Kivi, Pauli Heikkinen, Dan Smale, David F. Pollard, Nicholas Jones, Nicholas M. Deutscher, Thomas Blumenstock, Matthias Schneider, Mathias Palm, Justus Notholt, James W. Hannigan, and Martine De Mazière
Atmos. Meas. Tech., 12, 1393–1408, https://doi.org/10.5194/amt-12-1393-2019, https://doi.org/10.5194/amt-12-1393-2019, 2019
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N2O is an important atmospheric gas which is observed by two ground-based FTIR networks (TCCON and NDACC). The difference between NDACC and TCCON XN2O measurements is discussed. It is found that the bias between the two networks is within their combined uncertainties. However, TCCON measurements are affected by a priori profiles. In addition, the TCCON and NDACC N2O measurements are compared with the GEOS-Chem model simulations.
David F. Pollard, Vanessa Sherlock, John Robinson, Nicholas M. Deutscher, Brian Connor, and Hisako Shiona
Earth Syst. Sci. Data, 9, 977–992, https://doi.org/10.5194/essd-9-977-2017, https://doi.org/10.5194/essd-9-977-2017, 2017
Jenny A. Fisher, Lee T. Murray, Dylan B. A. Jones, and Nicholas M. Deutscher
Geosci. Model Dev., 10, 4129–4144, https://doi.org/10.5194/gmd-10-4129-2017, https://doi.org/10.5194/gmd-10-4129-2017, 2017
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Carbon monoxide (CO) simulation in atmospheric chemistry models is used for source–receptor analysis, emission inversion, and interpretation of observations. We introduce a major update to CO simulation in the GEOS-Chem chemical transport model that removes fundamental inconsistencies relative to the standard model, resolving biases of more than 100 ppb and errors in vertical structure. We also add source tagging of secondary CO and demonstrate it provides added value in low-emission regions.
Zhiting Wang, Thorsten Warneke, Nicholas M. Deutscher, Justus Notholt, Ute Karstens, Marielle Saunois, Matthias Schneider, Ralf Sussmann, Harjinder Sembhi, David W. T. Griffith, Dave F. Pollard, Rigel Kivi, Christof Petri, Voltaire A. Velazco, Michel Ramonet, and Huilin Chen
Atmos. Chem. Phys., 17, 13283–13295, https://doi.org/10.5194/acp-17-13283-2017, https://doi.org/10.5194/acp-17-13283-2017, 2017
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In this paper we separate the biases of atmospheric methane models into stratospheric and tropospheric parts. It is observed in other studies that simulated total columns of atmospheric methane present a latitudinal bias compared to measurements. The latitudinal gradients are considered to be from the stratosphere. However, our results show that the latitudinal biases could come from the troposphere in two of three models evaluated in this study.
Matthias Buschmann, Nicholas M. Deutscher, Mathias Palm, Thorsten Warneke, Christine Weinzierl, and Justus Notholt
Atmos. Meas. Tech., 10, 2397–2411, https://doi.org/10.5194/amt-10-2397-2017, https://doi.org/10.5194/amt-10-2397-2017, 2017
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The column averaged dry-air mole fractions of CO2 and CH4 (xCO2 and xCH4) of the Total Carbon Column Observing Network (TCCON) are retrieved from solar absorption Fourier transform infrared (FTIR) spectrometry. At the Ny-Ålesund site in the high arctic, however, during the polar night no solar measurements are possible. Here, we present a new method to measure xCO2 and xCH4 using the moon as a light source in the near-infrared and present the complete seasonal cycles of xCO2 and xCH4.
Debra Wunch, Paul O. Wennberg, Gregory Osterman, Brendan Fisher, Bret Naylor, Coleen M. Roehl, Christopher O'Dell, Lukas Mandrake, Camille Viatte, Matthäus Kiel, David W. T. Griffith, Nicholas M. Deutscher, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Maziere, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, David Pollard, John Robinson, Isamu Morino, Osamu Uchino, Frank Hase, Thomas Blumenstock, Dietrich G. Feist, Sabrina G. Arnold, Kimberly Strong, Joseph Mendonca, Rigel Kivi, Pauli Heikkinen, Laura Iraci, James Podolske, Patrick W. Hillyard, Shuji Kawakami, Manvendra K. Dubey, Harrison A. Parker, Eliezer Sepulveda, Omaira E. García, Yao Te, Pascal Jeseck, Michael R. Gunson, David Crisp, and Annmarie Eldering
Atmos. Meas. Tech., 10, 2209–2238, https://doi.org/10.5194/amt-10-2209-2017, https://doi.org/10.5194/amt-10-2209-2017, 2017
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This paper describes the comparisons between NASA's Orbiting Carbon Observatory (OCO-2) column-averaged dry-air mole fractions of CO2 with its primary ground-based validation network, the Total Carbon Column Observing Network (TCCON). The paper shows that while the standard bias correction reduces much of the spurious variability in the satellite measurements, residual biases remain.
Liang Feng, Paul I. Palmer, Hartmut Bösch, Robert J. Parker, Alex J. Webb, Caio S. C. Correia, Nicholas M. Deutscher, Lucas G. Domingues, Dietrich G. Feist, Luciana V. Gatti, Emanuel Gloor, Frank Hase, Rigel Kivi, Yi Liu, John B. Miller, Isamu Morino, Ralf Sussmann, Kimberly Strong, Osamu Uchino, Jing Wang, and Andreas Zahn
Atmos. Chem. Phys., 17, 4781–4797, https://doi.org/10.5194/acp-17-4781-2017, https://doi.org/10.5194/acp-17-4781-2017, 2017
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We use the GEOS-Chem global 3-D model of atmospheric chemistry and transport and an ensemble Kalman filter to simultaneously infer regional fluxes of methane (CH4) and carbon dioxide (CO2) directly from GOSAT retrievals of XCH4:XCO2, using sparse ground-based CH4 and CO2 mole fraction data to anchor the ratio. Our results show that assimilation of GOSAT data significantly reduced the posterior uncertainty and changed the a priori spatial distribution of CH4 emissions.
Dmitry A. Belikov, Shamil Maksyutov, Alexander Ganshin, Ruslan Zhuravlev, Nicholas M. Deutscher, Debra Wunch, Dietrich G. Feist, Isamu Morino, Robert J. Parker, Kimberly Strong, Yukio Yoshida, Andrey Bril, Sergey Oshchepkov, Hartmut Boesch, Manvendra K. Dubey, David Griffith, Will Hewson, Rigel Kivi, Joseph Mendonca, Justus Notholt, Matthias Schneider, Ralf Sussmann, Voltaire A. Velazco, and Shuji Aoki
Atmos. Chem. Phys., 17, 143–157, https://doi.org/10.5194/acp-17-143-2017, https://doi.org/10.5194/acp-17-143-2017, 2017
Katherine M. Saad, Debra Wunch, Nicholas M. Deutscher, David W. T. Griffith, Frank Hase, Martine De Mazière, Justus Notholt, David F. Pollard, Coleen M. Roehl, Matthias Schneider, Ralf Sussmann, Thorsten Warneke, and Paul O. Wennberg
Atmos. Chem. Phys., 16, 14003–14024, https://doi.org/10.5194/acp-16-14003-2016, https://doi.org/10.5194/acp-16-14003-2016, 2016
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Current approaches to constrain the global methane budget assimilate total column measurements into models, but model biases can impact results. We use tropospheric methane columns to evaluate model transport errors and identify a seasonal time lag in the Northern Hemisphere troposphere masked by stratospheric compensating effects. We find systematic biases in the stratosphere will alias into model-derived emissions estimates, especially those in the high Northern latitudes that vary seasonally.
Jason Beringer, Lindsay B. Hutley, Ian McHugh, Stefan K. Arndt, David Campbell, Helen A. Cleugh, James Cleverly, Víctor Resco de Dios, Derek Eamus, Bradley Evans, Cacilia Ewenz, Peter Grace, Anne Griebel, Vanessa Haverd, Nina Hinko-Najera, Alfredo Huete, Peter Isaac, Kasturi Kanniah, Ray Leuning, Michael J. Liddell, Craig Macfarlane, Wayne Meyer, Caitlin Moore, Elise Pendall, Alison Phillips, Rebecca L. Phillips, Suzanne M. Prober, Natalia Restrepo-Coupe, Susanna Rutledge, Ivan Schroder, Richard Silberstein, Patricia Southall, Mei Sun Yee, Nigel J. Tapper, Eva van Gorsel, Camilla Vote, Jeff Walker, and Tim Wardlaw
Biogeosciences, 13, 5895–5916, https://doi.org/10.5194/bg-13-5895-2016, https://doi.org/10.5194/bg-13-5895-2016, 2016
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OzFlux is the regional Australian and New Zealand flux tower network that aims to provide a continental-scale national facility to monitor and assess trends, and improve predictions, of Australia’s terrestrial biosphere and climate. We describe the evolution, design, and status as well as an overview of data processing. We suggest that a synergistic approach is required to address all of the spatial, ecological, human, and cultural challenges of managing Australian ecosystems.
Andreas Ostler, Ralf Sussmann, Prabir K. Patra, Sander Houweling, Marko De Bruine, Gabriele P. Stiller, Florian J. Haenel, Johannes Plieninger, Philippe Bousquet, Yi Yin, Marielle Saunois, Kaley A. Walker, Nicholas M. Deutscher, David W. T. Griffith, Thomas Blumenstock, Frank Hase, Thorsten Warneke, Zhiting Wang, Rigel Kivi, and John Robinson
Atmos. Meas. Tech., 9, 4843–4859, https://doi.org/10.5194/amt-9-4843-2016, https://doi.org/10.5194/amt-9-4843-2016, 2016
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Our evaluation of column-averaged methane (XCH4) in models and TCCON reveals latitudinal biases between 0.4 % and 2.1 % originating from an inter-model spread in stratospheric CH4. Substituting model stratospheric CH4 fields by satellite data significantly reduces the large XCH4 bias observed for one model. For other models, showing only minor biases, the impact is ambiguous; i.e., the satellite uncertainty range hinders a more accurate model evaluation needed to improve inverse modeling.
Makoto Inoue, Isamu Morino, Osamu Uchino, Takahiro Nakatsuru, Yukio Yoshida, Tatsuya Yokota, Debra Wunch, Paul O. Wennberg, Coleen M. Roehl, David W. T. Griffith, Voltaire A. Velazco, Nicholas M. Deutscher, Thorsten Warneke, Justus Notholt, John Robinson, Vanessa Sherlock, Frank Hase, Thomas Blumenstock, Markus Rettinger, Ralf Sussmann, Esko Kyrö, Rigel Kivi, Kei Shiomi, Shuji Kawakami, Martine De Mazière, Sabrina G. Arnold, Dietrich G. Feist, Erica A. Barrow, James Barney, Manvendra Dubey, Matthias Schneider, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Toshinobu Machida, Yousuke Sawa, Kazuhiro Tsuboi, Hidekazu Matsueda, Colm Sweeney, Pieter P. Tans, Arlyn E. Andrews, Sebastien C. Biraud, Yukio Fukuyama, Jasna V. Pittman, Eric A. Kort, and Tomoaki Tanaka
Atmos. Meas. Tech., 9, 3491–3512, https://doi.org/10.5194/amt-9-3491-2016, https://doi.org/10.5194/amt-9-3491-2016, 2016
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In this study, we correct the biases of GOSAT XCO2 and XCH4 using TCCON data. To evaluate the effectiveness of our correction method, uncorrected/corrected GOSAT data are compared to independent XCO2 and XCH4 data derived from aircraft measurements. Consequently, we suggest that this method is effective for reducing the biases of the GOSAT data. We consider that our work provides GOSAT data users with valuable information and contributes to the further development of studies on greenhouse gases.
Susan Kulawik, Debra Wunch, Christopher O'Dell, Christian Frankenberg, Maximilian Reuter, Tomohiro Oda, Frederic Chevallier, Vanessa Sherlock, Michael Buchwitz, Greg Osterman, Charles E. Miller, Paul O. Wennberg, David Griffith, Isamu Morino, Manvendra K. Dubey, Nicholas M. Deutscher, Justus Notholt, Frank Hase, Thorsten Warneke, Ralf Sussmann, John Robinson, Kimberly Strong, Matthias Schneider, Martine De Mazière, Kei Shiomi, Dietrich G. Feist, Laura T. Iraci, and Joyce Wolf
Atmos. Meas. Tech., 9, 683–709, https://doi.org/10.5194/amt-9-683-2016, https://doi.org/10.5194/amt-9-683-2016, 2016
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To accurately estimate source and sink locations of carbon dioxide, systematic errors in satellite measurements and models must be characterized. This paper examines two satellite data sets (GOSAT, launched 2009, and SCIAMACHY, launched 2002), and two models (CarbonTracker and MACC) vs. the TCCON CO2 validation data set. We assess biases and errors by season and latitude, satellite performance under averaging, and diurnal variability. Our findings are useful for assimilation of satellite data.
Yuting Wang, Nicholas M. Deutscher, Mathias Palm, Thorsten Warneke, Justus Notholt, Ian Baker, Joe Berry, Parvadha Suntharalingam, Nicholas Jones, Emmanuel Mahieu, Bernard Lejeune, James Hannigan, Stephanie Conway, Joseph Mendonca, Kimberly Strong, J. Elliott Campbell, Adam Wolf, and Stefanie Kremser
Atmos. Chem. Phys., 16, 2123–2138, https://doi.org/10.5194/acp-16-2123-2016, https://doi.org/10.5194/acp-16-2123-2016, 2016
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OCS could provide an additional constraint on the carbon cycle. The FTIR networks have existed for more than 20 years. For the first time, we used FTIR measurements of OCS and CO2 to study their relationship. We put the coupled CO2 and OCS land fluxes from the Simple Biosphere Model (SiB) into a transport model, and compared the simulations to the measurements. Looking at OCS and CO2 together inspires some new thoughts in how the biospheric models reproduce the carbon cycle in the real world.
Matthias Buschmann, Nicholas M. Deutscher, Vanessa Sherlock, Mathias Palm, Thorsten Warneke, and Justus Notholt
Atmos. Meas. Tech., 9, 577–585, https://doi.org/10.5194/amt-9-577-2016, https://doi.org/10.5194/amt-9-577-2016, 2016
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The column-averaged dry-air mole fraction of CO2 has been retrieved from high-resolution solar absorption spectra from two different measurement networks. We investigate the differences between these retrievals and find that their sensitivity differs greatly. As a result the direct comparison of the two retrievals remains challenging.
Sébastien Massart, Anna Agustí-Panareda, Jens Heymann, Michael Buchwitz, Frédéric Chevallier, Maximilian Reuter, Michael Hilker, John P. Burrows, Nicholas M. Deutscher, Dietrich G. Feist, Frank Hase, Ralf Sussmann, Filip Desmet, Manvendra K. Dubey, David W. T. Griffith, Rigel Kivi, Christof Petri, Matthias Schneider, and Voltaire A. Velazco
Atmos. Chem. Phys., 16, 1653–1671, https://doi.org/10.5194/acp-16-1653-2016, https://doi.org/10.5194/acp-16-1653-2016, 2016
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This study presents the European Centre for Medium-Range Weather Forecasts (ECMWF) monitoring of atmospheric CO2 using measurements from the Greenhouse gases Observing Satellite (GOSAT). We show that the modelled CO2 has a better precision than standard CO2 satellite products compared to ground-based measurements. We also present the CO2 forecast based on our best knowledge of the atmospheric CO2 distribution. We show that it has skill to forecast the largest scale CO2 patterns up to day 5.
L. Feng, P. I. Palmer, R. J. Parker, N. M. Deutscher, D. G. Feist, R. Kivi, I. Morino, and R. Sussmann
Atmos. Chem. Phys., 16, 1289–1302, https://doi.org/10.5194/acp-16-1289-2016, https://doi.org/10.5194/acp-16-1289-2016, 2016
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There is an on-going debate on the larger European biospheric uptake inferred from GOSAT XCO2 retrievals than those inferred from in situ data. Using a set of 15 experiments, we found that the elevated uptake over Europe could largely be explained by mis-fitting data due to regional XCO2 biases: 50–80 % of the elevated European uptake is due to retrievals outside the immediate European; and a varying monthly bias of up to 0.5 ppm for XCO2 retrievals over Europe could explain most of the remainder.
H. Lindqvist, C. W. O'Dell, S. Basu, H. Boesch, F. Chevallier, N. Deutscher, L. Feng, B. Fisher, F. Hase, M. Inoue, R. Kivi, I. Morino, P. I. Palmer, R. Parker, M. Schneider, R. Sussmann, and Y. Yoshida
Atmos. Chem. Phys., 15, 13023–13040, https://doi.org/10.5194/acp-15-13023-2015, https://doi.org/10.5194/acp-15-13023-2015, 2015
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Atmospheric carbon dioxide concentration varies seasonally mainly due to plant photosynthesis in the Northern Hemisphere. We found that the satellite GOSAT can capture this variability from space to within 1ppm. We also found that models can differ by more than 1ppm. This implies that the satellite measurements could be useful in evaluating models and their prior estimates of carbon dioxide sources and sinks.
R. J. Parker, H. Boesch, K. Byckling, A. J. Webb, P. I. Palmer, L. Feng, P. Bergamaschi, F. Chevallier, J. Notholt, N. Deutscher, T. Warneke, F. Hase, R. Sussmann, S. Kawakami, R. Kivi, D. W. T. Griffith, and V. Velazco
Atmos. Meas. Tech., 8, 4785–4801, https://doi.org/10.5194/amt-8-4785-2015, https://doi.org/10.5194/amt-8-4785-2015, 2015
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Atmospheric CH4 is an important greenhouse gas. Long-term global observations are necessary to understand its behaviour, with satellite observations playing a key role. The "proxy" retrieval method is one of the most successful but relies on the contribution from atmospheric CO2 models. This work assesses the significance of the uncertainty from the model CO2 within the retrieval and determines that despite this uncertainty the data are still valuable for determining sources and sinks of CH4.
A. Ostler, R. Sussmann, P. K. Patra, P. O. Wennberg, N. M. Deutscher, D. W. T. Griffith, T. Blumenstock, F. Hase, R. Kivi, T. Warneke, Z. Wang, M. De Mazière, J. Robinson, and H. Ohyama
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-20395-2015, https://doi.org/10.5194/acpd-15-20395-2015, 2015
Preprint withdrawn
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We find that stratospheric model-transport errors are common for chemical transport models that are used for inverse estimates of CH4 emissions. These model-transport errors cause latitudinal as well as seasonal biases in simulated stratospheric and, hence, column-averaged CH4 mixing ratios (XCH4). Such a model bias corresponds to an overestimation of arctic and mid-latitude CH4 emissions if inversion studies do not apply an ad hoc bias correction before inverting fluxes from XCH4 observations.
J. Heymann, M. Reuter, M. Hilker, M. Buchwitz, O. Schneising, H. Bovensmann, J. P. Burrows, A. Kuze, H. Suto, N. M. Deutscher, M. K. Dubey, D. W. T. Griffith, F. Hase, S. Kawakami, R. Kivi, I. Morino, C. Petri, C. Roehl, M. Schneider, V. Sherlock, R. Sussmann, V. A. Velazco, T. Warneke, and D. Wunch
Atmos. Meas. Tech., 8, 2961–2980, https://doi.org/10.5194/amt-8-2961-2015, https://doi.org/10.5194/amt-8-2961-2015, 2015
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Long-term data sets of global atmospheric carbon dioxide concentrations based on observations from different satellite instruments may suffer from inconsistencies originating from the use of different retrieval algorithms. This issue has been addressed by applying the Bremen Optimal Estimation DOAS retrieval algorithm to SCIAMACHY and TANSO-FTS observations. Detailed comparisons with TCCON and CarbonTracker show good consistency between the SCIAMACHY and TANSO-FTS data sets.
A. J. Turner, D. J. Jacob, K. J. Wecht, J. D. Maasakkers, E. Lundgren, A. E. Andrews, S. C. Biraud, H. Boesch, K. W. Bowman, N. M. Deutscher, M. K. Dubey, D. W. T. Griffith, F. Hase, A. Kuze, J. Notholt, H. Ohyama, R. Parker, V. H. Payne, R. Sussmann, C. Sweeney, V. A. Velazco, T. Warneke, P. O. Wennberg, and D. Wunch
Atmos. Chem. Phys., 15, 7049–7069, https://doi.org/10.5194/acp-15-7049-2015, https://doi.org/10.5194/acp-15-7049-2015, 2015
R. A. Scheepmaker, C. Frankenberg, N. M. Deutscher, M. Schneider, S. Barthlott, T. Blumenstock, O. E. Garcia, F. Hase, N. Jones, E. Mahieu, J. Notholt, V. Velazco, J. Landgraf, and I. Aben
Atmos. Meas. Tech., 8, 1799–1818, https://doi.org/10.5194/amt-8-1799-2015, https://doi.org/10.5194/amt-8-1799-2015, 2015
S. Barthlott, M. Schneider, F. Hase, A. Wiegele, E. Christner, Y. González, T. Blumenstock, S. Dohe, O. E. García, E. Sepúlveda, K. Strong, J. Mendonca, D. Weaver, M. Palm, N. M. Deutscher, T. Warneke, J. Notholt, B. Lejeune, E. Mahieu, N. Jones, D. W. T. Griffith, V. A. Velazco, D. Smale, J. Robinson, R. Kivi, P. Heikkinen, and U. Raffalski
Atmos. Meas. Tech., 8, 1555–1573, https://doi.org/10.5194/amt-8-1555-2015, https://doi.org/10.5194/amt-8-1555-2015, 2015
M. Reuter, M. Buchwitz, M. Hilker, J. Heymann, O. Schneising, D. Pillai, H. Bovensmann, J. P. Burrows, H. Bösch, R. Parker, A. Butz, O. Hasekamp, C. W. O'Dell, Y. Yoshida, C. Gerbig, T. Nehrkorn, N. M. Deutscher, T. Warneke, J. Notholt, F. Hase, R. Kivi, R. Sussmann, T. Machida, H. Matsueda, and Y. Sawa
Atmos. Chem. Phys., 14, 13739–13753, https://doi.org/10.5194/acp-14-13739-2014, https://doi.org/10.5194/acp-14-13739-2014, 2014
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Current knowledge about the European terrestrial biospheric carbon sink relies upon bottom-up and global surface flux inverse model estimates using in situ measurements. Our analysis of five satellite data sets comprises a regional inversion designed to be insensitive to potential retrieval biases and transport errors. We show that the satellite-derived sink is larger (1.0±0.3GtC/a) than previous estimates (0.4±0.4GtC/a).
A. Ostler, R. Sussmann, M. Rettinger, N. M. Deutscher, S. Dohe, F. Hase, N. Jones, M. Palm, and B.-M. Sinnhuber
Atmos. Meas. Tech., 7, 4081–4101, https://doi.org/10.5194/amt-7-4081-2014, https://doi.org/10.5194/amt-7-4081-2014, 2014
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Ground-based FTIR soundings of column-average methane from NDACC and TCCON can be combined without the need to apply an overall calibration factor. NDACC and TCCON measurements complement one another and provide valuable information for satellite validation, evaluation of chemical-transport models, and source-sink inversions. The impact of dynamical variability on NDACC and TCCON retrievals of column-average methane is reflected in different smoothing effects.
A. Agustí-Panareda, S. Massart, F. Chevallier, S. Boussetta, G. Balsamo, A. Beljaars, P. Ciais, N. M. Deutscher, R. Engelen, L. Jones, R. Kivi, J.-D. Paris, V.-H. Peuch, V. Sherlock, A. T. Vermeulen, P. O. Wennberg, and D. Wunch
Atmos. Chem. Phys., 14, 11959–11983, https://doi.org/10.5194/acp-14-11959-2014, https://doi.org/10.5194/acp-14-11959-2014, 2014
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This paper presents a new operational CO2 forecast product as part of the Copernicus Atmospheric Services suite of atmospheric composition products, using the state-of-the-art numerical weather prediction model from the European Centre of Medium-Range Weather Forecasts.
The evaluation with independent observations shows that the forecast has skill in predicting the synoptic variability of CO2. The online simulation of CO2 fluxes from vegetation contributes to this skill.
Z. Wang, N. M. Deutscher, T. Warneke, J. Notholt, B. Dils, D. W. T. Griffith, M. Schmidt, M. Ramonet, and C. Gerbig
Atmos. Meas. Tech., 7, 3295–3305, https://doi.org/10.5194/amt-7-3295-2014, https://doi.org/10.5194/amt-7-3295-2014, 2014
N. M. Deutscher, V. Sherlock, S. E. Mikaloff Fletcher, D. W. T. Griffith, J. Notholt, R. Macatangay, B. J. Connor, J. Robinson, H. Shiona, V. A. Velazco, Y. Wang, P. O. Wennberg, and D. Wunch
Atmos. Chem. Phys., 14, 9883–9901, https://doi.org/10.5194/acp-14-9883-2014, https://doi.org/10.5194/acp-14-9883-2014, 2014
K. M. Saad, D. Wunch, G. C. Toon, P. Bernath, C. Boone, B. Connor, N. M. Deutscher, D. W. T. Griffith, R. Kivi, J. Notholt, C. Roehl, M. Schneider, V. Sherlock, and P. O. Wennberg
Atmos. Meas. Tech., 7, 2907–2918, https://doi.org/10.5194/amt-7-2907-2014, https://doi.org/10.5194/amt-7-2907-2014, 2014
E. Sepúlveda, M. Schneider, F. Hase, S. Barthlott, D. Dubravica, O. E. García, A. Gomez-Pelaez, Y. González, J. C. Guerra, M. Gisi, R. Kohlhepp, S. Dohe, T. Blumenstock, K. Strong, D. Weaver, M. Palm, A. Sadeghi, N. M. Deutscher, T. Warneke, J. Notholt, N. Jones, D. W. T. Griffith, D. Smale, G. W. Brailsford, J. Robinson, F. Meinhardt, M. Steinbacher, T. Aalto, and D. Worthy
Atmos. Meas. Tech., 7, 2337–2360, https://doi.org/10.5194/amt-7-2337-2014, https://doi.org/10.5194/amt-7-2337-2014, 2014
B. Dils, M. Buchwitz, M. Reuter, O. Schneising, H. Boesch, R. Parker, S. Guerlet, I. Aben, T. Blumenstock, J. P. Burrows, A. Butz, N. M. Deutscher, C. Frankenberg, F. Hase, O. P. Hasekamp, J. Heymann, M. De Mazière, J. Notholt, R. Sussmann, T. Warneke, D. Griffith, V. Sherlock, and D. Wunch
Atmos. Meas. Tech., 7, 1723–1744, https://doi.org/10.5194/amt-7-1723-2014, https://doi.org/10.5194/amt-7-1723-2014, 2014
A. Galli, S. Guerlet, A. Butz, I. Aben, H. Suto, A. Kuze, N. M. Deutscher, J. Notholt, D. Wunch, P. O. Wennberg, D. W. T. Griffith, O. Hasekamp, and J. Landgraf
Atmos. Meas. Tech., 7, 1105–1119, https://doi.org/10.5194/amt-7-1105-2014, https://doi.org/10.5194/amt-7-1105-2014, 2014
F. Deng, D. B. A. Jones, D. K. Henze, N. Bousserez, K. W. Bowman, J. B. Fisher, R. Nassar, C. O'Dell, D. Wunch, P. O. Wennberg, E. A. Kort, S. C. Wofsy, T. Blumenstock, N. M. Deutscher, D. W. T. Griffith, F. Hase, P. Heikkinen, V. Sherlock, K. Strong, R. Sussmann, and T. Warneke
Atmos. Chem. Phys., 14, 3703–3727, https://doi.org/10.5194/acp-14-3703-2014, https://doi.org/10.5194/acp-14-3703-2014, 2014
D. Wunch, P. O. Wennberg, J. Messerschmidt, N. C. Parazoo, G. C. Toon, N. M. Deutscher, G. Keppel-Aleks, C. M. Roehl, J. T. Randerson, T. Warneke, and J. Notholt
Atmos. Chem. Phys., 13, 9447–9459, https://doi.org/10.5194/acp-13-9447-2013, https://doi.org/10.5194/acp-13-9447-2013, 2013
Y. Yoshida, N. Kikuchi, I. Morino, O. Uchino, S. Oshchepkov, A. Bril, T. Saeki, N. Schutgens, G. C. Toon, D. Wunch, C. M. Roehl, P. O. Wennberg, D. W. T. Griffith, N. M. Deutscher, T. Warneke, J. Notholt, J. Robinson, V. Sherlock, B. Connor, M. Rettinger, R. Sussmann, P. Ahonen, P. Heikkinen, E. Kyrö, J. Mendonca, K. Strong, F. Hase, S. Dohe, and T. Yokota
Atmos. Meas. Tech., 6, 1533–1547, https://doi.org/10.5194/amt-6-1533-2013, https://doi.org/10.5194/amt-6-1533-2013, 2013
J. Messerschmidt, N. Parazoo, D. Wunch, N. M. Deutscher, C. Roehl, T. Warneke, and P. O. Wennberg
Atmos. Chem. Phys., 13, 5103–5115, https://doi.org/10.5194/acp-13-5103-2013, https://doi.org/10.5194/acp-13-5103-2013, 2013
R. A. Scheepmaker, C. Frankenberg, A. Galli, A. Butz, H. Schrijver, N. M. Deutscher, D. Wunch, T. Warneke, S. Fally, and I. Aben
Atmos. Meas. Tech., 6, 879–894, https://doi.org/10.5194/amt-6-879-2013, https://doi.org/10.5194/amt-6-879-2013, 2013
H. Boesch, N. M. Deutscher, T. Warneke, K. Byckling, A. J. Cogan, D. W. T. Griffith, J. Notholt, R. J. Parker, and Z. Wang
Atmos. Meas. Tech., 6, 599–612, https://doi.org/10.5194/amt-6-599-2013, https://doi.org/10.5194/amt-6-599-2013, 2013
M. Schneider, S. Barthlott, F. Hase, Y. González, K. Yoshimura, O. E. García, E. Sepúlveda, A. Gomez-Pelaez, M. Gisi, R. Kohlhepp, S. Dohe, T. Blumenstock, A. Wiegele, E. Christner, K. Strong, D. Weaver, M. Palm, N. M. Deutscher, T. Warneke, J. Notholt, B. Lejeune, P. Demoulin, N. Jones, D. W. T. Griffith, D. Smale, and J. Robinson
Atmos. Meas. Tech., 5, 3007–3027, https://doi.org/10.5194/amt-5-3007-2012, https://doi.org/10.5194/amt-5-3007-2012, 2012
Related subject area
Subject: Gases | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
Detection and long-term quantification of methane emissions from an active landfill
Research of low-cost air quality monitoring models with different machine learning algorithms
New insights from the Jülich Ozone Sonde Intercomparison Experiment: calibration functions traceable to one ozone reference instrument
Identification of spikes in continuous ground-based in situ time series of CO2, CH4 and CO: an extended experiment within the European ICOS Atmosphere network
Data treatment and corrections for estimating H2O and CO2 isotope fluxes from high-frequency observations
Measurements of volatile organic compounds in ambient air by gas-chromatography and real-time Vocus PTR-TOF-MS: calibrations, instrument background corrections, and introducing a PTR Data Toolkit
Development of low-cost air quality stations for next-generation monitoring networks: calibration and validation of NO2 and O3 sensors
Detecting plumes in mobile air quality monitoring time series with density-based spatial clustering of applications with noise
Characterising the methane gas and environmental response of the Figaro Taguchi Gas Sensor (TGS) 2611-E00
Reducing errors on estimates of the carbon uptake period based on time series of atmospheric CO2
Generalized Kendrick analysis for improved visualization of atmospheric mass spectral data
Determination of NOx emission rates of inland ships from onshore measurements
Data quality enhancement for field experiments in atmospheric chemistry via sequential Monte Carlo filters
A flexible algorithm for network design based on information theory
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
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
Pramod Kumar, Christopher Caldow, Grégoire Broquet, Adil Shah, Olivier Laurent, Camille Yver-Kwok, Sebastien Ars, Sara Defratyka, Susan Warao Gichuki, Luc Lienhardt, Mathis Lozano, Jean-Daniel Paris, Felix Vogel, Caroline Bouchet, Elisa Allegrini, Robert Kelly, Catherine Juery, and Philippe Ciais
Atmos. Meas. Tech., 17, 1229–1250, https://doi.org/10.5194/amt-17-1229-2024, https://doi.org/10.5194/amt-17-1229-2024, 2024
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This study presents a series of mobile measurement campaigns to monitor the CH4 emissions from an active landfill. These measurements are processed using a Gaussian plume model and atmospheric inversion techniques to quantify the landfill CH4 emissions. The methane emission estimates range between ~0.4 and ~7 t CH4 per day, and their variations are analyzed. The robustness of the estimates is assessed depending on the distance of the measurements from the potential sources in the landfill.
Gang Wang, Chunlai Yu, Kai Guo, Haisong Guo, and Yibo Wang
Atmos. Meas. Tech., 17, 181–196, https://doi.org/10.5194/amt-17-181-2024, https://doi.org/10.5194/amt-17-181-2024, 2024
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A low-cost multi-parameter air quality monitoring system (LCS) based on different machine learning algorithms is proposed. The LCS can measure particulate matter (PM) and gas pollutants simultaneously. The performance of the different algorithms (RF, MLR, KNN, BP, GA-BP) with the parameters such as R2 and RMSE are compared and discussed. These measurements indicate the LCS based on the machine learning algorithms can be used to predict the concentrations of PM and gas pollution.
Herman G. J. Smit, Deniz Poyraz, Roeland Van Malderen, Anne M. Thompson, David W. Tarasick, Ryan M. Stauffer, Bryan J. Johnson, and Debra E. Kollonige
Atmos. Meas. Tech., 17, 73–112, https://doi.org/10.5194/amt-17-73-2024, https://doi.org/10.5194/amt-17-73-2024, 2024
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This paper revisits fundamentals of ECC ozonesonde measurements to develop and characterize a methodology to correct for the fast and slow time responses using the JOSIE (Jülich Ozone Sonde Intercomparison Experiment) simulation chamber data. Comparing the new corrected ozonesonde profiles to an accurate ozone UV photometer (OPM) as reference allows us to evaluate the time response correction (TRC) method and to determine calibration functions traceable to one reference with 5 % uncertainty.
Paolo Cristofanelli, Cosimo Fratticioli, Lynn Hazan, Mali Chariot, Cedric Couret, Orestis Gazetas, Dagmar Kubistin, Antti Laitinen, Ari Leskinen, Tuomas Laurila, Matthias Lindauer, Giovanni Manca, Michel Ramonet, Pamela Trisolino, and Martin Steinbacher
Atmos. Meas. Tech., 16, 5977–5994, https://doi.org/10.5194/amt-16-5977-2023, https://doi.org/10.5194/amt-16-5977-2023, 2023
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We investigated the application of two automatic methods for detecting spikes due to local emissions in greenhouse gas (GHG) observations at a subset of sites from the ICOS Atmosphere network. We analysed the sensitivity to the spike frequency of using different methods and settings. We documented the impact of the de-spiking on different temporal aggregations (i.e. hourly, monthly and seasonal averages) of CO2, CH4 and CO 1 min time series.
Robbert P. J. Moonen, Getachew A. Adnew, Oscar K. Hartogensis, Jordi Vilà-Guerau de Arellano, David J. Bonell Fontas, and Thomas Röckmann
Atmos. Meas. Tech., 16, 5787–5810, https://doi.org/10.5194/amt-16-5787-2023, https://doi.org/10.5194/amt-16-5787-2023, 2023
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Isotope fluxes allow for net ecosystem gas exchange fluxes to be partitioned into sub-components like plant assimilation, respiration and transpiration, which can help us better understand the environmental drivers of each partial flux. We share the results of a field campaign isotope fluxes were derived using a combination of laser spectroscopy and eddy covariance. We found lag times and high frequency signal loss in the isotope fluxes we derived and present methods to correct for both.
Andrew R. Jensen, Abigail R. Koss, Ryder B. Hales, and Joost A. de Gouw
Atmos. Meas. Tech., 16, 5261–5285, https://doi.org/10.5194/amt-16-5261-2023, https://doi.org/10.5194/amt-16-5261-2023, 2023
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Quantification of a wide range of volatile organic compounds by proton-transfer-reaction mass spectrometry (PTR-MS) can be achieved with direct calibration of only a subset of compounds, characterization of instrument response, and simple reaction kinetics. We characterized our Vocus PTR-MS and developed a toolkit as a guide through this process. A catalytic zero air generator provided the lowest detection limits, and short, frequent calibrations informed variability in instrument response.
Alice Cavaliere, Lorenzo Brilli, Bianca Patrizia Andreini, Federico Carotenuto, Beniamino Gioli, Tommaso Giordano, Marco Stefanelli, Carolina Vagnoli, Alessandro Zaldei, and Giovanni Gualtieri
Atmos. Meas. Tech., 16, 4723–4740, https://doi.org/10.5194/amt-16-4723-2023, https://doi.org/10.5194/amt-16-4723-2023, 2023
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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.
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.
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Short summary
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.
Despite extensive research, emission detection and quantification of greenhouse gases (GHGs)...
