Articles | Volume 13, issue 6
https://doi.org/10.5194/gmd-13-2695-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-2695-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
18 Jun 2020
Development and technical paper |
| 18 Jun 2020
| 18 Jun 2020
Optimizing a dynamic fossil fuel CO2 emission model with CTDAS (CarbonTracker Data Assimilation Shell, v1.0) for an urban area using atmospheric observations of CO2, CO, NOx, and SO2
Department of Climate, Air and Sustainability, TNO, P.O. Box 80015,
3508 TA Utrecht, the Netherlands
Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Hugo A. C. Denier van der Gon
Department of Climate, Air and Sustainability, TNO, P.O. Box 80015,
3508 TA Utrecht, the Netherlands
Michiel K. van der Molen
Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Stijn N. C. Dellaert
Department of Climate, Air and Sustainability, TNO, P.O. Box 80015,
3508 TA Utrecht, the Netherlands
Wouter Peters
Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Centre for Isotope Research, Energy and Sustainability Research
Institute Groningen, University of Groningen, Nijenborgh 4, 9747 AG Groningen, the Netherlands
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Atmos. Chem. Phys., 23, 8081–8101, https://doi.org/10.5194/acp-23-8081-2023, https://doi.org/10.5194/acp-23-8081-2023, 2023
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Mehliyar Sadiq, Paul I. Palmer, Mark F. Lunt, Liang Feng, Ingrid Super, Stijn N. C. Dellaert, and Hugo A. C. Denier van der Gon
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We make use of high-resolution emission inventory of CO2 and co-emitted tracers, satellite measurements, together with nested atmospheric transport model simulation, to investigate how reactive trace gases such as nitrogen dioxide and carbon monoxide can be used as proxies to determine the combustion contribution to atmospheric CO2 over Europe. We find stronger correlation in ratios of nitrogen dioxide and carbon dioxide between emission and satellite observed and modelled column concentration.
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Ingrid Super, Hugo A. C. Denier van der Gon, Michiel K. van der Molen, Hendrika A. M. Sterk, Arjan Hensen, and Wouter Peters
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-409, https://doi.org/10.5194/essd-2023-409, 2023
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Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
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Foteini Stavropoulou, Katarina Vinković, Bert Kers, Marcel de Vries, Steven van Heuven, Piotr Korbeń, Martina Schmidt, Julia Wietzel, Pawel Jagoda, Jaroslav M. Necki, Jakub Bartyzel, Hossein Maazallahi, Malika Menoud, Carina van der Veen, Sylvia Walter, Béla Tuzson, Jonas Ravelid, Randulph Paulo Morales, Lukas Emmenegger, Dominik Brunner, Michael Steiner, Arjan Hensen, Ilona Velzeboer, Pim van den Bulk, Hugo Denier van der Gon, Antonio Delre, Maklawe Essonanawe Edjabou, Charlotte Scheutz, Marius Corbu, Sebastian Iancu, Denisa Moaca, Alin Scarlat, Alexandru Tudor, Ioana Vizireanu, Andreea Calcan, Magdalena Ardelean, Sorin Ghemulet, Alexandru Pana, Aurel Constantinescu, Lucian Cusa, Alexandru Nica, Calin Baciu, Cristian Pop, Andrei Radovici, Alexandru Mereuta, Horatiu Stefanie, Alexandru Dandocsi, Bas Hermans, Stefan Schwietzke, Daniel Zavala-Araiza, Huilin Chen, and Thomas Röckmann
Atmos. Chem. Phys., 23, 10399–10412, https://doi.org/10.5194/acp-23-10399-2023, https://doi.org/10.5194/acp-23-10399-2023, 2023
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In this study, we quantify CH4 emissions from onshore oil production sites in Romania at source and facility level using a combination of ground- and drone-based measurement techniques. We show that the total CH4 emissions in our studied areas are much higher than the emissions reported to UNFCCC, and up to three-quarters of the detected emissions are related to operational venting. Our results suggest that oil and gas production infrastructure in Romania holds a massive mitigation potential.
Jean-Philippe Putaud, Enrico Pisoni, Alexander Mangold, Christoph Hueglin, Jean Sciare, Michael Pikridas, Chrysanthos Savvides, Jakub Ondracek, Saliou Mbengue, Alfred Wiedensohler, Kay Weinhold, Maik Merkel, Laurent Poulain, Dominik van Pinxteren, Hartmut Herrmann, Andreas Massling, Claus Nordstroem, Andrés Alastuey, Cristina Reche, Noemí Pérez, Sonia Castillo, Mar Sorribas, Jose Antonio Adame, Tuukka Petaja, Katrianne Lehtipalo, Jarkko Niemi, Véronique Riffault, Joel F. de Brito, Augustin Colette, Olivier Favez, Jean-Eudes Petit, Valérie Gros, Maria I. Gini, Stergios Vratolis, Konstantinos Eleftheriadis, Evangelia Diapouli, Hugo Denier van der Gon, Karl Espen Yttri, and Wenche Aas
Atmos. Chem. Phys., 23, 10145–10161, https://doi.org/10.5194/acp-23-10145-2023, https://doi.org/10.5194/acp-23-10145-2023, 2023
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Luana S. Basso, Chris Wilson, Martyn P. Chipperfield, Graciela Tejada, Henrique L. G. Cassol, Egídio Arai, Mathew Williams, T. Luke Smallman, Wouter Peters, Stijn Naus, John B. Miller, and Manuel Gloor
Atmos. Chem. Phys., 23, 9685–9723, https://doi.org/10.5194/acp-23-9685-2023, https://doi.org/10.5194/acp-23-9685-2023, 2023
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Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 23, 8899–8919, https://doi.org/10.5194/acp-23-8899-2023, https://doi.org/10.5194/acp-23-8899-2023, 2023
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We present a fast method to evaluate carbon monoxide emissions from cities in Africa. Carbon monoxide is important for climate change in an indirect way, as it is linked to ozone, methane, and carbon dioxide. Our measurements are made with a satellite that sees the entire globe every single day. This means that we can check from space whether the current knowledge of emission rates is up to date. We make the comparison and show that the emission rates in northern Africa are underestimated.
Jinghui Lian, Thomas Lauvaux, Hervé Utard, François-Marie Bréon, Grégoire Broquet, Michel Ramonet, Olivier Laurent, Ivonne Albarus, Mali Chariot, Simone Kotthaus, Martial Haeffelin, Olivier Sanchez, Olivier Perrussel, Hugo Anne Denier van der Gon, Stijn Nicolaas Camiel Dellaert, and Philippe Ciais
Atmos. Chem. Phys., 23, 8823–8835, https://doi.org/10.5194/acp-23-8823-2023, https://doi.org/10.5194/acp-23-8823-2023, 2023
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This study quantifies urban CO2 emissions via an atmospheric inversion for the Paris metropolitan area over a 6-year period from 2016 to 2021. Results show a long-term decreasing trend of about 2 % ± 0.6 % per year in the annual CO2 emissions over Paris. We conclude that our current capacity can deliver near-real-time CO2 emission estimates at the city scale in under a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories.
Marc Guevara, Hervé Petetin, Oriol Jorba, Hugo Denier van der Gon, Jeroen Kuenen, Ingrid Super, Claire Granier, Thierno Doumbia, Philippe Ciais, Zhu Liu, Robin D. Lamboll, Sabine Schindlbacher, Bradley Matthews, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 8081–8101, https://doi.org/10.5194/acp-23-8081-2023, https://doi.org/10.5194/acp-23-8081-2023, 2023
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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.
Ruben Urraca, Greet Janssens-Maenhout, Nicolás Álamos, Lucas Berna-Peña, Monica Crippa, Sabine Darras, Sitjn Dellaert, Hugo Denier van der Gon, Mark Dowell, Nadine Gobron, Claire Granier, Giacomo Grassi, Marc Guevara, Diego Guizzardi, Kevin Gurney, Nicolás Huneeus, Sekou Keita, Jeoren Kuenen, Ana Lopez-Noreña, Enrique Puliafito, Geoffrey Roest, Simone Rossi, Antonin Soulie, and Antoon Visschedijk
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-210, https://doi.org/10.5194/essd-2023-210, 2023
Revised manuscript accepted for ESSD
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CoCO2-MOSAIC 1.0 is a global mosaic of regional bottom-up inventories providing gridded (0.1˚×0.1˚) monthly CO2 emissions fluxes. Regional datasets include country-specific information and finer spatial resolution than global inventories. Therefore, CoCO2-MOSAIC can be considered as a regionally accepted reference to assess the quality of global emission inventories and to evaluate the sensitivity of inverse models to the bottom-up emissions used as priors.
Zhendong Wu, Alex Vermeulen, Yousuke Sawa, Ute Karstens, Wouter Peters, Remco de Kok, Xin Lan, Yasuyuki Nagai, Akinori Ogi, and Oksana Tarasova
EGUsphere, https://doi.org/10.5194/egusphere-2023-1173, https://doi.org/10.5194/egusphere-2023-1173, 2023
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This study focuses on exploring the differences in calculating global surface CO2 and its growth rate, considering the impact of analysis methodologies and site selection. Our study reveals that the current global CO2 network has a good capacity to represent global surface CO2 and its growth rate and trends in atmospheric CO2 mass changes, although small differences exist in different analyses due to the impact of methodology and site selection.
Andreas Forstmaier, Jia Chen, Florian Dietrich, Juan Bettinelli, Hossein Maazallahi, Carsten Schneider, Dominik Winkler, Xinxu Zhao, Taylor Jones, Carina van der Veen, Norman Wildmann, Moritz Makowski, Aydin Uzun, Friedrich Klappenbach, Hugo Denier van der Gon, Stefan Schwietzke, and Thomas Röckmann
Atmos. Chem. Phys., 23, 6897–6922, https://doi.org/10.5194/acp-23-6897-2023, https://doi.org/10.5194/acp-23-6897-2023, 2023
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Large cities emit greenhouse gases which contribute to global warming. In this study, we measured the release of one important green house gas, methane, in Hamburg. Multiple sources that contribute to methane emissions were located and quantified. Methane sources were found to be mainly caused by human activity (e.g., by release from oil and gas refineries). Moreover, potential natural sources have been located, such as the Elbe River and lakes.
Fabian Manuel Maier, Ingeborg Levin, Sébastien Conil, Maksym Gachkivskyi, Hugo Denier van der Gon, and Samuel Hammer
EGUsphere, https://doi.org/10.5194/egusphere-2023-1237, https://doi.org/10.5194/egusphere-2023-1237, 2023
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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We assess the uncertainty of continuous fossil fuel carbon dioxide (ffCO2) estimates derived from carbon monoxide (CO) observations and radiocarbon (14CO2) flask measurements from an urban and a rural site. This study provides the basis for using continuous CO-based ffCO2 observations in atmospheric transport inversion frameworks to derive ffCO2 emissions estimates. We also compare the flask-based CO / ffCO2 ratios with modelled ratios to validate an emission inventory for Central Europe.
Samuel Upton, Markus Reichstein, Fabian Gans, Wouter Peters, Basil Kraft, and Ana Bastos
EGUsphere, https://doi.org/10.5194/egusphere-2023-805, https://doi.org/10.5194/egusphere-2023-805, 2023
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In order to reduce the mismatch between the estimates of the net flux of carbon dioxide from the biosphere to the atmosphere (NEE) from bottom-up data-driven flux models and best estimates of regional and global NEE from top-down atmospheric inverse model, this study creates a dual-constraint for a data-driven flux model from atmospheric inversion data and eddy-covariance observations. The resulting model produces consistent estimates both of the local NEE and at regional and global scales.
Michael Steiner, Wouter Peters, Ingrid Luijkx, Stephan Henne, Huilin Chen, Samuel Hammer, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2023-853, https://doi.org/10.5194/egusphere-2023-853, 2023
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The Paris Agreement increased the interest in estimating GHG emissions of individual countries, but top-down emission estimation is not yet considered policy-relevant. It is therefore paramount to reduce the large errors and to build systems that are based on the newest atmospheric transport models (e.g., ICON-ART). In this study, we present the first application of ICON-ART in inverse modelling of GHG fluxes with an Ensemble Kalman Filter and present our results for European CH4 emissions.
Ida Storm, Ute Karstens, Claudio D'Onofrio, Alex Vermeulen, and Wouter Peters
Atmos. Chem. Phys., 23, 4993–5008, https://doi.org/10.5194/acp-23-4993-2023, https://doi.org/10.5194/acp-23-4993-2023, 2023
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In this study, we evaluate what is in the influence regions of the ICOS atmospheric measurement stations to gain insight into what land cover types and land-cover-associated fluxes the network represents. Subsequently, insights about strengths, weaknesses, and potential gaps can assist in future network expansion decisions. The network is concentrated in central Europe, which leads to a general overrepresentation of coniferous forest and cropland and underrepresentation of grass and shrubland.
Marc Guevara, Santiago Enciso, Carles Tena, Oriol Jorba, Stijn Dellaert, Hugo Denier van der Gon, and Carlos Pérez García-Pando
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-95, https://doi.org/10.5194/essd-2023-95, 2023
Revised manuscript accepted for ESSD
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A global dataset of emissions from thermal power plants was created for the year 2018. The resulting catalogue reports annual emissions of CO2 and co-emitted species (NOx, CO, SO2 and CH4) for more than 16000 individual facilities at their exact geographical location. Information on the temporal and vertical distribution of the emissions is also provided at the facility level. The dataset is intended to support current and future satellite emission monitoring and inverse modelling efforts.
Auke M. van der Woude, Remco de Kok, Naomi Smith, Ingrid T. Luijkx, Santiago Botía, Ute Karstens, Linda M. J. Kooijmans, Gerbrand Koren, Harro A. J. Meijer, Gert-Jan Steeneveld, Ida Storm, Ingrid Super, Hubertus A. Scheeren, Alex Vermeulen, and Wouter Peters
Earth Syst. Sci. Data, 15, 579–605, https://doi.org/10.5194/essd-15-579-2023, https://doi.org/10.5194/essd-15-579-2023, 2023
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To monitor the progress towards the CO2 emission goals set out in the Paris Agreement, the European Union requires an independent validation of emitted CO2. For this validation, atmospheric measurements of CO2 can be used, together with first-guess estimates of CO2 emissions and uptake. To quickly inform end users, it is imperative that this happens in near real-time. To aid these efforts, we create estimates of European CO2 exchange at high resolution in near real time.
Kim A. P. Faassen, Linh N. T. Nguyen, Eadin R. Broekema, Bert A. M. Kers, Ivan Mammarella, Timo Vesala, Penelope A. Pickers, Andrew C. Manning, Jordi Vilà-Guerau de Arellano, Harro A. J. Meijer, Wouter Peters, and Ingrid T. Luijkx
Atmos. Chem. Phys., 23, 851–876, https://doi.org/10.5194/acp-23-851-2023, https://doi.org/10.5194/acp-23-851-2023, 2023
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The exchange ratio (ER) between atmospheric O2 and CO2 provides a useful tracer for separately estimating photosynthesis and respiration processes in the forest carbon balance. This is highly relevant to better understand the expected biosphere sink, which determines future atmospheric CO2 levels. We therefore measured O2, CO2, and their ER above a boreal forest in Finland and investigated their diurnal behaviour for a representative day, and we show the most suitable way to determine the ER.
Srijana Lama, Sander Houweling, K. Folkert Boersma, Ilse Aben, Hugo A. C. Denier van der Gon, and Maarten C. Krol
Atmos. Chem. Phys., 22, 16053–16071, https://doi.org/10.5194/acp-22-16053-2022, https://doi.org/10.5194/acp-22-16053-2022, 2022
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Hydroxyl radical (OH) is the important chemical species that determines the lifetime of some greenhouse gases and trace gases. OH plays a vital role in air pollution chemistry. OH has a short lifetime and is extremely difficult to measure directly. OH concentrations derived from the chemistry transport model (CTM) have uncertainties of >50 %. Therefore, in this study, OH is derived indirectly using satellite date in urban plumes.
Stijn Naus, Lucas G. Domingues, Maarten Krol, Ingrid T. Luijkx, Luciana V. Gatti, John B. Miller, Emanuel Gloor, Sourish Basu, Caio Correia, Gerbrand Koren, Helen M. Worden, Johannes Flemming, Gabrielle Pétron, and Wouter Peters
Atmos. Chem. Phys., 22, 14735–14750, https://doi.org/10.5194/acp-22-14735-2022, https://doi.org/10.5194/acp-22-14735-2022, 2022
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We assimilate MOPITT CO satellite data in the TM5-4D-Var inverse modelling framework to estimate Amazon fire CO emissions for 2003–2018. We show that fire emissions have decreased over the analysis period, coincident with a decrease in deforestation rates. However, interannual variations in fire emissions are large, and they correlate strongly with soil moisture. Our results reveal an important role for robust, top-down fire CO emissions in quantifying and attributing Amazon fire intensity.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Fabian Maier, Christoph Gerbig, Ingeborg Levin, Ingrid Super, Julia Marshall, and Samuel Hammer
Geosci. Model Dev., 15, 5391–5406, https://doi.org/10.5194/gmd-15-5391-2022, https://doi.org/10.5194/gmd-15-5391-2022, 2022
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We show that the default representation of point source emissions in WRF–STILT leads to large overestimations when modelling fossil fuel CO2 concentrations for a 30 m high observation site during stable atmospheric conditions. We therefore introduce a novel point source modelling approach in WRF-STILT that takes into account their effective emission heights and results in a much better agreement with observations.
Marc Guevara, Hervé Petetin, Oriol Jorba, Hugo Denier van der Gon, Jeroen Kuenen, Ingrid Super, Jukka-Pekka Jalkanen, Elisa Majamäki, Lasse Johansson, Vincent-Henri Peuch, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 14, 2521–2552, https://doi.org/10.5194/essd-14-2521-2022, https://doi.org/10.5194/essd-14-2521-2022, 2022
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To control the spread of the COVID-19 disease, European governments implemented mobility restriction measures that resulted in an unprecedented drop in anthropogenic emissions. This work presents a dataset of emission adjustment factors that allows quantifying changes in 2020 European primary emissions per country and pollutant sector at the daily scale. The resulting dataset can be used as input in modelling studies aiming at quantifying the impact of COVID-19 on air quality levels.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Tobias Christoph Valentin Werner Riess, Klaas Folkert Boersma, Jasper van Vliet, Wouter Peters, Maarten Sneep, Henk Eskes, and Jos van Geffen
Atmos. Meas. Tech., 15, 1415–1438, https://doi.org/10.5194/amt-15-1415-2022, https://doi.org/10.5194/amt-15-1415-2022, 2022
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This paper reports on improved monitoring of ship nitrogen oxide emissions by TROPOMI. With its fantastic resolution we can identify lanes of ship nitrogen dioxide (NO2) pollution not detected from space before. The quality of TROPOMI NO2 data over sea is improved further by recent upgrades in cloud retrievals and the use of sun glint scenes. Lastly, we study the impact of COVID-19 on ship NO2 in European seas and compare the found reductions to emission estimates gained from ship-specific data.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Jeroen Kuenen, Stijn Dellaert, Antoon Visschedijk, Jukka-Pekka Jalkanen, Ingrid Super, and Hugo Denier van der Gon
Earth Syst. Sci. Data, 14, 491–515, https://doi.org/10.5194/essd-14-491-2022, https://doi.org/10.5194/essd-14-491-2022, 2022
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This paper presents an 18-year time series for anthropogenic emissions for the main air pollutants in Europe, distinguishing 15 main source categories. It provides a complete overview of emissions to air and is designed to support air quality modelling. The data build where possible on official country total emissions used in the policy processes, but where necessary alternative data were used. The emission data are spatially distributed at high resolution (~ 6 km x 6 km) in a consistent way.
Nicolás Álamos, Nicolás Huneeus, Mariel Opazo, Mauricio Osses, Sebastián Puja, Nicolás Pantoja, Hugo Denier van der Gon, Alejandra Schueftan, René Reyes, and Rubén Calvo
Earth Syst. Sci. Data, 14, 361–379, https://doi.org/10.5194/essd-14-361-2022, https://doi.org/10.5194/essd-14-361-2022, 2022
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This study presents the first high-resolution national inventory of anthropogenic emissions for Chile (Inventario Nacional de Emisiones Antropogénicas, INEMA). Emissions for vehicular, industrial, energy, mining and residential sectors are estimated for the period 2015–2017 and spatially distributed onto a high-resolution grid (1 × 1 km). This inventory will support policies seeking to mitigate climate change and improve air quality by providing qualified scientific spatial emission information.
Linda M. J. Kooijmans, Ara Cho, Jin Ma, Aleya Kaushik, Katherine D. Haynes, Ian Baker, Ingrid T. Luijkx, Mathijs Groenink, Wouter Peters, John B. Miller, Joseph A. Berry, Jerome Ogée, Laura K. Meredith, Wu Sun, Kukka-Maaria Kohonen, Timo Vesala, Ivan Mammarella, Huilin Chen, Felix M. Spielmann, Georg Wohlfahrt, Max Berkelhammer, Mary E. Whelan, Kadmiel Maseyk, Ulli Seibt, Roisin Commane, Richard Wehr, and Maarten Krol
Biogeosciences, 18, 6547–6565, https://doi.org/10.5194/bg-18-6547-2021, https://doi.org/10.5194/bg-18-6547-2021, 2021
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The gas carbonyl sulfide (COS) can be used to estimate photosynthesis. To adopt this approach on regional and global scales, we need biosphere models that can simulate COS exchange. So far, such models have not been evaluated against observations. We evaluate the COS biosphere exchange of the SiB4 model against COS flux observations. We find that the model is capable of simulating key processes in COS biosphere exchange. Still, we give recommendations for further improvement of the model.
Margarita Choulga, Greet Janssens-Maenhout, Ingrid Super, Efisio Solazzo, Anna Agusti-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Monica Crippa, Hugo Denier van der Gon, Richard Engelen, Diego Guizzardi, Jeroen Kuenen, Joe McNorton, Gabriel Oreggioni, and Antoon Visschedijk
Earth Syst. Sci. Data, 13, 5311–5335, https://doi.org/10.5194/essd-13-5311-2021, https://doi.org/10.5194/essd-13-5311-2021, 2021
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People worry that growing man-made carbon dioxide (CO2) concentrations lead to climate change. Global models, use of observations, and datasets can help us better understand behaviour of CO2. Here a tool to compute uncertainty in man-made CO2 sources per country per year and month is presented. An example of all sources separated into seven groups (intensive and average energy, industry, humans, ground and air transport, others) is presented. Results will be used to predict CO2 concentrations.
Mehliyar Sadiq, Paul I. Palmer, Mark F. Lunt, Liang Feng, Ingrid Super, Stijn N. C. Dellaert, and Hugo A. C. Denier van der Gon
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-816, https://doi.org/10.5194/acp-2021-816, 2021
Publication in ACP not foreseen
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We make use of high-resolution emission inventory of CO2 and co-emitted tracers, satellite measurements, together with nested atmospheric transport model simulation, to investigate how reactive trace gases such as nitrogen dioxide and carbon monoxide can be used as proxies to determine the combustion contribution to atmospheric CO2 over Europe. We find stronger correlation in ratios of nitrogen dioxide and carbon dioxide between emission and satellite observed and modelled column concentration.
Antoine Berchet, Espen Sollum, Rona L. Thompson, Isabelle Pison, Joël Thanwerdas, Grégoire Broquet, Frédéric Chevallier, Tuula Aalto, Adrien Berchet, Peter Bergamaschi, Dominik Brunner, Richard Engelen, Audrey Fortems-Cheiney, Christoph Gerbig, Christine D. Groot Zwaaftink, Jean-Matthieu Haussaire, Stephan Henne, Sander Houweling, Ute Karstens, Werner L. Kutsch, Ingrid T. Luijkx, Guillaume Monteil, Paul I. Palmer, Jacob C. A. van Peet, Wouter Peters, Philippe Peylin, Elise Potier, Christian Rödenbeck, Marielle Saunois, Marko Scholze, Aki Tsuruta, and Yuanhong Zhao
Geosci. Model Dev., 14, 5331–5354, https://doi.org/10.5194/gmd-14-5331-2021, https://doi.org/10.5194/gmd-14-5331-2021, 2021
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We present here the Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is a programming protocol to allow various inversion bricks to be exchanged among researchers.
The ensemble of bricks makes a flexible, transparent and open-source Python-based tool. We describe the main structure and functionalities and demonstrate it in a simple academic case.
Ana Maria Roxana Petrescu, Matthew J. McGrath, Robbie M. Andrew, Philippe Peylin, Glen P. Peters, Philippe Ciais, Gregoire Broquet, Francesco N. Tubiello, Christoph Gerbig, Julia Pongratz, Greet Janssens-Maenhout, Giacomo Grassi, Gert-Jan Nabuurs, Pierre Regnier, Ronny Lauerwald, Matthias Kuhnert, Juraj Balkovič, Mart-Jan Schelhaas, Hugo A. C. Denier van der
Gon, Efisio Solazzo, Chunjing Qiu, Roberto Pilli, Igor B. Konovalov, Richard A. Houghton, Dirk Günther, Lucia Perugini, Monica Crippa, Raphael Ganzenmüller, Ingrid T. Luijkx, Pete Smith, Saqr Munassar, Rona L. Thompson, Giulia Conchedda, Guillaume Monteil, Marko Scholze, Ute Karstens, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2363–2406, https://doi.org/10.5194/essd-13-2363-2021, https://doi.org/10.5194/essd-13-2363-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CO2 fossil emissions and CO2 land fluxes in the EU27+UK. The data integrate recent emission inventories with ecosystem data, land carbon models and regional/global inversions for the European domain, aiming at reconciling CO2 estimates with official country-level UNFCCC national GHG inventories in support to policy and facilitating real-time verification procedures.
Anteneh Getachew Mengistu, Gizaw Mengistu Tsidu, Gerbrand Koren, Maurits L. Kooreman, K. Folkert Boersma, Torbern Tagesson, Jonas Ardö, Yann Nouvellon, and Wouter Peters
Biogeosciences, 18, 2843–2857, https://doi.org/10.5194/bg-18-2843-2021, https://doi.org/10.5194/bg-18-2843-2021, 2021
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In this study, we assess the usefulness of Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval (SIFTER) data from the GOME-2A instrument and near-infrared reflectance of vegetation (NIRv) from MODIS to capture the seasonality and magnitudes of gross primary production (GPP) derived from six eddy-covariance flux towers in Africa in the overlap years between 2007–2014. We also test the robustness of sun-induced fluoresence and NIRv to compare the seasonality of GPP for the major biomes.
Marc Guevara, Oriol Jorba, Carles Tena, Hugo Denier van der Gon, Jeroen Kuenen, Nellie Elguindi, Sabine Darras, Claire Granier, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 13, 367–404, https://doi.org/10.5194/essd-13-367-2021, https://doi.org/10.5194/essd-13-367-2021, 2021
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The temporal variability of atmospheric emissions is linked to changes in activity patterns, emission processes and meteorology. Accounting for the change in temporal emission characteristics is a key aspect for modelling the trends of air pollutants. This work presents a dataset of global and European emission temporal profiles to be used for air quality modelling purposes. The profiles were constructed considering the influences of local sociodemographic factors and climatological conditions.
Marc Guevara, Oriol Jorba, Albert Soret, Hervé Petetin, Dene Bowdalo, Kim Serradell, Carles Tena, Hugo Denier van der Gon, Jeroen Kuenen, Vincent-Henri Peuch, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 21, 773–797, https://doi.org/10.5194/acp-21-773-2021, https://doi.org/10.5194/acp-21-773-2021, 2021
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Most European countries have imposed lockdowns to combat the spread of the COVID-19 pandemic. Such a socioeconomic disruption has resulted in a sudden drop of atmospheric emissions and air pollution levels. This study quantifies the daily reductions in national emissions and associated levels of nitrogen dioxide (NO2) due to the COVID-19 lockdowns in Europe, by making use of multiple open-access measured activity data as well as artificial intelligence and modelling techniques.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
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The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Hossein Maazallahi, Julianne M. Fernandez, Malika Menoud, Daniel Zavala-Araiza, Zachary D. Weller, Stefan Schwietzke, Joseph C. von Fischer, Hugo Denier van der Gon, and Thomas Röckmann
Atmos. Chem. Phys., 20, 14717–14740, https://doi.org/10.5194/acp-20-14717-2020, https://doi.org/10.5194/acp-20-14717-2020, 2020
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Methane accounts for ∼ 25 % of current climate warming. The current lack of methane measurements is a barrier for tracking major sources, which are key for near-term climate mitigation. We use mobile measurements to identify and quantify methane emission sources in Utrecht (NL) and Hamburg (DE) with a focus on natural gas pipeline leaks. The measurements resulted in fixing the major leaks by the local utility, but coordinated efforts are needed at national levels for further emission reductions.
Srijana Lama, Sander Houweling, K. Folkert Boersma, Henk Eskes, Ilse Aben, Hugo A. C. Denier van der Gon, Maarten C. Krol, Han Dolman, Tobias Borsdorff, and Alba Lorente
Atmos. Chem. Phys., 20, 10295–10310, https://doi.org/10.5194/acp-20-10295-2020, https://doi.org/10.5194/acp-20-10295-2020, 2020
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Rapid urbanization has increased the consumption of fossil fuel, contributing the degradation of urban air quality. Burning efficiency is a major factor determining the impact of fuel burning on the environment. We quantify the burning efficiency of fossil fuel use over six megacities using satellite remote sensing data. City governance can use these results to understand air pollution scenarios and to formulate effective air pollution control strategies.
Erik van Schaik, Maurits L. Kooreman, Piet Stammes, L. Gijsbert Tilstra, Olaf N. E. Tuinder, Abram F. J. Sanders, Willem W. Verstraeten, Rüdiger Lang, Alessandra Cacciari, Joanna Joiner, Wouter Peters, and K. Folkert Boersma
Atmos. Meas. Tech., 13, 4295–4315, https://doi.org/10.5194/amt-13-4295-2020, https://doi.org/10.5194/amt-13-4295-2020, 2020
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With our improved algorithm we have generated a stable, long-term dataset of fluorescence measurements from the GOME-2A satellite instrument. In this study we determined a correction for the degradation of GOME-2A in orbit and applied this correction along with other improvements to our SIFTER v2 retrieval algorithm. The result is a coherent dataset of daily and monthly averaged fluorescence values for the period 2007–2018 to track worldwide changes in photosynthetic activity by vegetation.
Getachew Agmuas Adnew, Thijs L. Pons, Gerbrand Koren, Wouter Peters, and Thomas Röckmann
Biogeosciences, 17, 3903–3922, https://doi.org/10.5194/bg-17-3903-2020, https://doi.org/10.5194/bg-17-3903-2020, 2020
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We measured the effect of photosynthesis, the largest flux in the carbon cycle, on the triple oxygen isotope composition of atmospheric CO2 at the leaf level during gas exchange using three plant species. The main factors that limit the impact of land vegetation on the triple oxygen isotope composition of atmospheric CO2 are identified, characterized and discussed. The effect of photosynthesis on the isotopic composition of CO2 is commonly quantified as discrimination (ΔA).
Jia Chen, Florian Dietrich, Hossein Maazallahi, Andreas Forstmaier, Dominik Winkler, Magdalena E. G. Hofmann, Hugo Denier van der Gon, and Thomas Röckmann
Atmos. Chem. Phys., 20, 3683–3696, https://doi.org/10.5194/acp-20-3683-2020, https://doi.org/10.5194/acp-20-3683-2020, 2020
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We demonstrate for the first time that large festivals can be significant methane sources, though they are not included in emission inventories. We combined in situ measurements with a Gaussian plume model to determine the Oktoberfest emissions and show that they are not due solely to human biogenic emissions, but are instead primarily fossil fuel related. Our study provides the foundation to develop reduction policies for such events and new pathways to mitigate fossil fuel methane emissions.
Martin Jung, Christopher Schwalm, Mirco Migliavacca, Sophia Walther, Gustau Camps-Valls, Sujan Koirala, Peter Anthoni, Simon Besnard, Paul Bodesheim, Nuno Carvalhais, Frédéric Chevallier, Fabian Gans, Daniel S. Goll, Vanessa Haverd, Philipp Köhler, Kazuhito Ichii, Atul K. Jain, Junzhi Liu, Danica Lombardozzi, Julia E. M. S. Nabel, Jacob A. Nelson, Michael O'Sullivan, Martijn Pallandt, Dario Papale, Wouter Peters, Julia Pongratz, Christian Rödenbeck, Stephen Sitch, Gianluca Tramontana, Anthony Walker, Ulrich Weber, and Markus Reichstein
Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, https://doi.org/10.5194/bg-17-1343-2020, 2020
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We test the approach of producing global gridded carbon fluxes based on combining machine learning with local measurements, remote sensing and climate data. We show that we can reproduce seasonal variations in carbon assimilated by plants via photosynthesis and in ecosystem net carbon balance. The ecosystem’s mean carbon balance and carbon flux trends require cautious interpretation. The analysis paves the way for future improvements of the data-driven assessment of carbon fluxes.
Ingrid Super, Stijn N. C. Dellaert, Antoon J. H. Visschedijk, and Hugo A. C. Denier van der Gon
Atmos. Chem. Phys., 20, 1795–1816, https://doi.org/10.5194/acp-20-1795-2020, https://doi.org/10.5194/acp-20-1795-2020, 2020
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Emission data contain uncertainties introduced by the methodology and the data used. We quantified uncertainties in gridded emissions using the uncertainty in underlying data, showing that disaggregation in space and time significantly increases the uncertainty. Understanding uncertainties helps to interpret atmospheric measurements and the gap with modelled concentrations. Moreover, our analyses help identify regions with large uncertainties, which require further scrutiny.
Ying Chen, Yafang Cheng, Nan Ma, Chao Wei, Liang Ran, Ralf Wolke, Johannes Größ, Qiaoqiao Wang, Andrea Pozzer, Hugo A. C. Denier van der Gon, Gerald Spindler, Jos Lelieveld, Ina Tegen, Hang Su, and Alfred Wiedensohler
Atmos. Chem. Phys., 20, 771–786, https://doi.org/10.5194/acp-20-771-2020, https://doi.org/10.5194/acp-20-771-2020, 2020
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Particulate nitrate is one of the most important climate cooling agents. Our results show that interaction with sea-salt aerosol can shift nitrate to larger sized particles (redistribution effect), weakening its direct cooling effect. The modelling results indicate strong redistribution over coastal and offshore regions worldwide as well as continental Europe. Improving the consideration of the redistribution effect in global models fosters a better understanding of climate change.
Jianhui Jiang, Sebnem Aksoyoglu, Imad El-Haddad, Giancarlo Ciarelli, Hugo A. C. Denier van der Gon, Francesco Canonaco, Stefania Gilardoni, Marco Paglione, María Cruz Minguillón, Olivier Favez, Yunjiang Zhang, Nicolas Marchand, Liqing Hao, Annele Virtanen, Kalliopi Florou, Colin O'Dowd, Jurgita Ovadnevaite, Urs Baltensperger, and André S. H. Prévôt
Atmos. Chem. Phys., 19, 15247–15270, https://doi.org/10.5194/acp-19-15247-2019, https://doi.org/10.5194/acp-19-15247-2019, 2019
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We use an air quality model with a modified organic aerosol (OA) module based on chamber experiments to identify the OA sources and their contributions in Europe. Comparisons with long-term measurements at nine sites in 2011 show an improvement in OA simulation. Our results suggest that the biomass burning and biogenic emissions are the dominant sources in winter and summer, respectively. Contributions of diesel and gasoline vehicles are relatively small compared to a previous study in the US.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
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The Global Carbon Budget 2019 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
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The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Rocío Baró, Pedro Jiménez-Guerrero, Martin Stengel, Dominik Brunner, Gabriele Curci, Renate Forkel, Lucy Neal, Laura Palacios-Peña, Nicholas Savage, Martijn Schaap, Paolo Tuccella, Hugo Denier van der Gon, and Stefano Galmarini
Atmos. Chem. Phys., 18, 15183–15199, https://doi.org/10.5194/acp-18-15183-2018, https://doi.org/10.5194/acp-18-15183-2018, 2018
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Particles in the atmosphere, such as pollution, desert dust, and volcanic ash, have an impact on meteorology. They interact with incoming radiation resulting in a cooling effect of the atmosphere. Today, the use of meteorology and chemistry models help us to understand these processes, but there are a lot of uncertainties. The goal of this work is to evaluate how these interactions are represented in the models by comparing them to satellite data to see how close they are to reality.
Antoon J. H. Visschedijk, Hugo A. C. Denier van der Gon, Hans C. Doornenbal, and Lorenzo Cremonese
Adv. Geosci., 45, 125–131, https://doi.org/10.5194/adgeo-45-125-2018, https://doi.org/10.5194/adgeo-45-125-2018, 2018
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Electricity produced by gas instead of coal is more climate-friendly as it emits 2 times less CO2 but with methane leakage rates > 3 % of production this advantage is lost. Ethane in (shale)gas can be used to identify gas leakage. The ratio of ethane/methane for European shale gas plays is derived and emission under different production and leakage scenarios is quantified. This can be used to design an atmospheric monitoring system that alerts competent authorities if unacceptable leakage occurs.
Filippo Xausa, Pauli Paasonen, Risto Makkonen, Mikhail Arshinov, Aijun Ding, Hugo Denier Van Der Gon, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 18, 10039–10054, https://doi.org/10.5194/acp-18-10039-2018, https://doi.org/10.5194/acp-18-10039-2018, 2018
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Our project describes the feasibility of implementing particle number emissions taken from the GAINS model in global climate modeling through a simulation with the ECHAM-HAM global climate model. The results from the simulations have important implications regarding modeled particle number concentrations and future climate effects. Our findings represent an important starting point for further simulations concerning climate effects derived from anthropogenic particle emissions on a global scale.
Truls Andersen, Bert Scheeren, Wouter Peters, and Huilin Chen
Atmos. Meas. Tech., 11, 2683–2699, https://doi.org/10.5194/amt-11-2683-2018, https://doi.org/10.5194/amt-11-2683-2018, 2018
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We developed and field-tested a UAV-based active AirCore for atmospheric measurements of CO2, CH4, and CO. AirCore is an innovative tool that passively samples air using the atmospheric pressure gradient during descent. Here we have taken further steps to change the “active” sampling process with a pump, miniaturize it, and deploy it on a UAV. The active AirCore system opens up a wide variety of opportunities, e.g., quantifying CH4 emissions from wetlands, landfills, other CH4 hot spots.
Ivar R. van der Velde, John B. Miller, Michiel K. van der Molen, Pieter P. Tans, Bruce H. Vaughn, James W. C. White, Kevin Schaefer, and Wouter Peters
Geosci. Model Dev., 11, 283–304, https://doi.org/10.5194/gmd-11-283-2018, https://doi.org/10.5194/gmd-11-283-2018, 2018
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We explored an inverse modeling technique to interpret global atmospheric measurements of CO2 and the ratio of its stable carbon isotopes (δ13C). We detected the possible underestimation of drought stress in biosphere models after applying combined atmospheric CO2 and δ13C constraints. This study highlights the importance of improving the representation of the biosphere in carbon–climate models, in particular in a world where droughts become more extreme and more frequent.
Hugo A. C. Denier van der Gon, Jeroen J. P. Kuenen, Greet Janssens-Maenhout, Ulrike Döring, Sander Jonkers, and Antoon Visschedijk
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2017-124, https://doi.org/10.5194/essd-2017-124, 2017
Revised manuscript has not been submitted
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A gridded European emission inventory for CO2 from fossil fuels and biofuels (2000–2014) is made to support carbon cycle modelling and city-scale identification of emissions. Future projections following a “business as usual” and a climate change scenario are included to study possible CO2 emission changes between Paris Agreement stocktake years (2023-2028-2033). The data can be used for testing GHG verification modelling and sensitivity tests for designing a future observational system.
Astrid M. M. Manders, Peter J. H. Builtjes, Lyana Curier, Hugo A. C. Denier van der Gon, Carlijn Hendriks, Sander Jonkers, Richard Kranenburg, Jeroen J. P. Kuenen, Arjo J. Segers, Renske M. A. Timmermans, Antoon J. H. Visschedijk, Roy J. Wichink Kruit, W. Addo J. van Pul, Ferd J. Sauter, Eric van der Swaluw, Daan P. J. Swart, John Douros, Henk Eskes, Erik van Meijgaard, Bert van Ulft, Peter van Velthoven, Sabine Banzhaf, Andrea C. Mues, Rainer Stern, Guangliang Fu, Sha Lu, Arnold Heemink, Nils van Velzen, and Martijn Schaap
Geosci. Model Dev., 10, 4145–4173, https://doi.org/10.5194/gmd-10-4145-2017, https://doi.org/10.5194/gmd-10-4145-2017, 2017
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The regional-scale air quality model LOTOS–EUROS has been developed by a consortium of Dutch institutes. Recently, version 2.0 of the model was released as an open-source version. Next to a technical description and model evaluation for 2012, this paper presents the model developments in context of the history of air quality modelling and provides an outlook for future directions. Key and innovative applications of LOTOS–EUROS are also highlighted.
Ingrid Super, Hugo A. C. Denier van der Gon, Michiel K. van der Molen, Hendrika A. M. Sterk, Arjan Hensen, and Wouter Peters
Atmos. Chem. Phys., 17, 13297–13316, https://doi.org/10.5194/acp-17-13297-2017, https://doi.org/10.5194/acp-17-13297-2017, 2017
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In this research we examined the use of different models to simulate CO2 concentrations in and around urban areas. We find that in the presence of large stack emissions in a gridded model is insufficient to represent the small dimensions of the CO2 plumes. A plume model improves this representation up to 10–14 km from the stack. Better model results can improve the estimate of CO2 emissions from urban areas and assist in identifying efficient emission reduction policies.
Vitali Fioletov, Chris A. McLinden, Shailesh K. Kharol, Nickolay A. Krotkov, Can Li, Joanna Joiner, Michael D. Moran, Robert Vet, Antoon J. H. Visschedijk, and Hugo A. C. Denier van der Gon
Atmos. Chem. Phys., 17, 12597–12616, https://doi.org/10.5194/acp-17-12597-2017, https://doi.org/10.5194/acp-17-12597-2017, 2017
Ingrid T. van der Laan-Luijkx, Ivar R. van der Velde, Emma van der Veen, Aki Tsuruta, Karolina Stanislawska, Arne Babenhauserheide, Hui Fang Zhang, Yu Liu, Wei He, Huilin Chen, Kenneth A. Masarie, Maarten C. Krol, and Wouter Peters
Geosci. Model Dev., 10, 2785–2800, https://doi.org/10.5194/gmd-10-2785-2017, https://doi.org/10.5194/gmd-10-2785-2017, 2017
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The CarbonTracker Data Assimilation Shell (CTDAS) is the new modular implementation of the CarbonTracker Europe (CTE) data assimilation system. We present and document CTDAS and demonstrate its ability to estimate global carbon sources and sinks. We present the latest CTE results including the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans. We show the versatility of CTDAS with an overview of the wide range of other applications.
Reza Shaiganfar, Steffen Beirle, Hugo Denier van der Gon, Sander Jonkers, Jeroen Kuenen, Herve Petetin, Qijie Zhang, Matthias Beekmann, and Thomas Wagner
Atmos. Chem. Phys., 17, 7853–7890, https://doi.org/10.5194/acp-17-7853-2017, https://doi.org/10.5194/acp-17-7853-2017, 2017
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We determine NOx emissions for Paris in summer 2009 and winter 2009/2010 by combining car MAX-DOAS measurements of NO2 with wind fields. We compare the results with simulations from the CHIMERE model. We derive daily average NOx emissions for Paris of 4.0 × 1025 molecules s−1 for summer and of 6.9 × 1025 molecules s−1 in winter. These values are a factor of about 1.4 and 2.0 larger than the corresponding emissions in the MACC-III emission inventory.
Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, Renato Spahni, Sander Houweling, Marko Laine, Ed Dlugokencky, Angel J. Gomez-Pelaez, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, Jgor Arduini, Francesco Apadula, Christoph Gerbig, Dietrich G. Feist, Rigel Kivi, Yukio Yoshida, and Wouter Peters
Geosci. Model Dev., 10, 1261–1289, https://doi.org/10.5194/gmd-10-1261-2017, https://doi.org/10.5194/gmd-10-1261-2017, 2017
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In this study, we found that the average global methane emission for 2000–2012, estimated by the CTE-CH4 model, was 516±51 Tg CH4 yr-1, and the estimates for 2007–2012 were 4 % larger than for 2000–2006. The model estimates are sensitive to inputs and setups, but according to sensitivity tests the study suggests that the increase in atmospheric methane concentrations during 21st century was due to an increase in emissions from the 35S-EQ latitudinal bands.
Ioannis Kioutsioukis, Ulas Im, Efisio Solazzo, Roberto Bianconi, Alba Badia, Alessandra Balzarini, Rocío Baró, Roberto Bellasio, Dominik Brunner, Charles Chemel, Gabriele Curci, Hugo Denier van der Gon, Johannes Flemming, Renate Forkel, Lea Giordano, Pedro Jiménez-Guerrero, Marcus Hirtl, Oriol Jorba, Astrid Manders-Groot, Lucy Neal, Juan L. Pérez, Guidio Pirovano, Roberto San Jose, Nicholas Savage, Wolfram Schroder, Ranjeet S. Sokhi, Dimiter Syrakov, Paolo Tuccella, Johannes Werhahn, Ralf Wolke, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 16, 15629–15652, https://doi.org/10.5194/acp-16-15629-2016, https://doi.org/10.5194/acp-16-15629-2016, 2016
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Four ensemble methods are applied to two annual AQMEII datasets and their performance is compared for O3, NO2 and PM10. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill at each station over the single models and the ensemble mean. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way.
Friderike Kuik, Axel Lauer, Galina Churkina, Hugo A. C. Denier van der Gon, Daniel Fenner, Kathleen A. Mar, and Tim M. Butler
Geosci. Model Dev., 9, 4339–4363, https://doi.org/10.5194/gmd-9-4339-2016, https://doi.org/10.5194/gmd-9-4339-2016, 2016
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The study evaluates the performance of a setup of the Weather Research and Forecasting model with chemistry and aerosols (WRF–Chem) for the Berlin–Brandenburg region of Germany. Its sensitivity to updating urban input parameters based on structural data for Berlin is tested, specifying land use classes on a sub-grid scale, downscaling the original emissions to a resolution of ca. 1 km by 1 km for Berlin based on proxy data and model resolution.
Sander van der Laan, Swagath Manohar, Alex Vermeulen, Fred Bosveld, Harro Meijer, Andrew Manning, Michiel van der Molen, and Ingrid van der Laan-Luijkx
Atmos. Meas. Tech., 9, 5523–5533, https://doi.org/10.5194/amt-9-5523-2016, https://doi.org/10.5194/amt-9-5523-2016, 2016
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A new methodology is presented to estimate regional-scale surface fluxes of 222Rn. 222Rn is an increasingly important trace gas which is used to calculate regional-scale greenhouse gas emissions and to validate atmospheric transport models. We tested our method at two atmospheric research stations in the Netherlands and compared our results with measurements from accumulation chambers and two recently published 222Rn soil flux maps for Europe.
Ying Chen, Yafang Cheng, Nan Ma, Ralf Wolke, Stephan Nordmann, Stephanie Schüttauf, Liang Ran, Birgit Wehner, Wolfram Birmili, Hugo A. C. Denier van der Gon, Qing Mu, Stefan Barthel, Gerald Spindler, Bastian Stieger, Konrad Müller, Guang-Jie Zheng, Ulrich Pöschl, Hang Su, and Alfred Wiedensohler
Atmos. Chem. Phys., 16, 12081–12097, https://doi.org/10.5194/acp-16-12081-2016, https://doi.org/10.5194/acp-16-12081-2016, 2016
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Sea salt aerosol (SSA) is important for primary and secondary aerosols on a global scale. During 10–20 September 2013, the SSA mass concentration was overestimated by a factor of 8–20 over central Europe by WRF-Chem model, stem from the uncertainty of its emission scheme. This could facilitate the coarse-mode nitrate formation (~ 140 % but inhibit the fine-mode nitrate formation (~−20 %). A special long-range transport mechanism could broaden this influence of SSA to a larger downwind region.
Ingrid Super, Hugo A. C. Denier van der Gon, Michiel K. van der Molen, Hendrika A. M. Sterk, Arjan Hensen, and Wouter Peters
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-807, https://doi.org/10.5194/acp-2016-807, 2016
Revised manuscript not accepted
Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, Renato Spahni, Sander Houweling, Marko Laine, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, and Wouter Peters
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-181, https://doi.org/10.5194/gmd-2016-181, 2016
Revised manuscript has not been submitted
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In this study, we found that methane emission estimates, driven by the CTE-CH4 model, depend on model setups and inputs, especially for regional estimates. An optimal setup makes the estimates stable, but inputs, such as emission estimates from inventories, and observations, also play significant role. The results can be used for an extended analysis on relative contributions of methane emissions to atmospheric methane concentration changes in recent decades.
Pauli Paasonen, Kaarle Kupiainen, Zbigniew Klimont, Antoon Visschedijk, Hugo A. C. Denier van der Gon, and Markus Amann
Atmos. Chem. Phys., 16, 6823–6840, https://doi.org/10.5194/acp-16-6823-2016, https://doi.org/10.5194/acp-16-6823-2016, 2016
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In this paper we show the first results of size-segregated anthropogenic particle number emissions from the GAINS emission scenario model. The shares of different sources and their predicted changes from 2010 to 2030 are described, showing clear difference in sources dominating the particle number and mass emissions. We also point out the main uncertainties in number emissions. The GAINS particle number emissions can be applied in improving the evaluation of aerosol climate and health effects.
Marje Prank, Mikhail Sofiev, Svetlana Tsyro, Carlijn Hendriks, Valiyaveetil Semeena, Xavier Vazhappilly Francis, Tim Butler, Hugo Denier van der Gon, Rainer Friedrich, Johannes Hendricks, Xin Kong, Mark Lawrence, Mattia Righi, Zissis Samaras, Robert Sausen, Jaakko Kukkonen, and Ranjeet Sokhi
Atmos. Chem. Phys., 16, 6041–6070, https://doi.org/10.5194/acp-16-6041-2016, https://doi.org/10.5194/acp-16-6041-2016, 2016
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Aerosol composition in Europe was simulated by four chemistry transport models and compared to observations to identify the most prominent areas for model improvement. Notable differences were found between the models' predictions, attributable to different treatment or omission of aerosol sources and processes. All models underestimated the observed concentrations by 10–60 %, mostly due to under-predicting the carbonaceous and mineral particles and omitting the aerosol-bound water.
Christos Fountoukis, Athanasios G. Megaritis, Ksakousti Skyllakou, Panagiotis E. Charalampidis, Hugo A. C. Denier van der Gon, Monica Crippa, André S. H. Prévôt, Friederike Fachinger, Alfred Wiedensohler, Christodoulos Pilinis, and Spyros N. Pandis
Atmos. Chem. Phys., 16, 3727–3741, https://doi.org/10.5194/acp-16-3727-2016, https://doi.org/10.5194/acp-16-3727-2016, 2016
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We use PMCAMx with high grid resolution over Paris to simulate carbonaceous aerosol during the summer and winter MEGAPOLI campaigns. PMCAMx reproduces BC observations well. Addition of cooking organic aerosol emissions of 80 mg per day per capita is needed to reproduce the corresponding observations. While the oxygenated organic aerosol predictions during the summer are encouraging a major wintertime source appears to be missing.
Ying Chen, Ya-Fang Cheng, Stephan Nordmann, Wolfram Birmili, Hugo A. C. Denier van der Gon, Nan Ma, Ralf Wolke, Birgit Wehner, Jia Sun, Gerald Spindler, Qing Mu, Ulrich Pöschl, Hang Su, and Alfred Wiedensohler
Atmos. Chem. Phys., 16, 1823–1835, https://doi.org/10.5194/acp-16-1823-2016, https://doi.org/10.5194/acp-16-1823-2016, 2016
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We evaluated the EC point sources in Germany with high-resolution simulation by WRF-Chem, and find out that point sources contribute too much EC in the coarse mode aerosol mass. The area emissions in Eastern Europe and Russia also allocate too much EC emission in coarse mode in the EUCAARI EC emission inventory. Because of the shorter life time of coarse mode EC, about 20–40 % less EC can be transported to Melpitz from Eastern Europe. Size segregation information is important for EC inventories.
J. Kukkonen, M. Karl, M. P. Keuken, H. A. C. Denier van der Gon, B. R. Denby, V. Singh, J. Douros, A. Manders, Z. Samaras, N. Moussiopoulos, S. Jonkers, M. Aarnio, A. Karppinen, L. Kangas, S. Lützenkirchen, T. Petäjä, I. Vouitsis, and R. S. Sokhi
Geosci. Model Dev., 9, 451–478, https://doi.org/10.5194/gmd-9-451-2016, https://doi.org/10.5194/gmd-9-451-2016, 2016
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For analyzing the health effects of particulate matter, it is necessary to consider not only the mass of particles, but also their sizes and composition. A simple measure for the former is the number concentration of particles. We present particle number concentrations in five major European cities, namely Helsinki, Oslo, London, Rotterdam, and Athens, in 2008, based mainly on modelling. The concentrations of PN were mostly influenced by the emissions from local vehicular traffic.
M. K. van der Molen, R. A. M. de Jeu, W. Wagner, I. R. van der Velde, P. Kolari, J. Kurbatova, A. Varlagin, T. C. Maximov, A. V. Kononov, T. Ohta, A. Kotani, M. C. Krol, and W. Peters
Hydrol. Earth Syst. Sci., 20, 605–624, https://doi.org/10.5194/hess-20-605-2016, https://doi.org/10.5194/hess-20-605-2016, 2016
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Boreal Eurasia contains extensive forests, which play an important role in the terrestrial carbon cycle. Droughts can modify this cycle considerably, although very few ground-based observations are available in the region. We test whether satellite-observed soil moisture may be used to improve carbon cycle models in this region. This paper explains when and where this works best. The interpretation of satellite soil moisture is best in summer conditions, and is hampered by snow, ice and ponding.
G. Janssens-Maenhout, M. Crippa, D. Guizzardi, F. Dentener, M. Muntean, G. Pouliot, T. Keating, Q. Zhang, J. Kurokawa, R. Wankmüller, H. Denier van der Gon, J. J. P. Kuenen, Z. Klimont, G. Frost, S. Darras, B. Koffi, and M. Li
Atmos. Chem. Phys., 15, 11411–11432, https://doi.org/10.5194/acp-15-11411-2015, https://doi.org/10.5194/acp-15-11411-2015, 2015
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This paper provides monthly emission grid maps at 0.1deg x 0.1deg resolution with global coverage for air pollutants and aerosols anthropogenic emissions in 2008 and 2010.
Countries are consistently inter-compared with sector-specific implied emission factors, per capita emissions and emissions per unit of GDP.
The emission grid maps compose the reference emissions data set for the community modelling hemispheric transport of air pollution (HTAP).
V. Marécal, V.-H. Peuch, C. Andersson, S. Andersson, J. Arteta, M. Beekmann, A. Benedictow, R. Bergström, B. Bessagnet, A. Cansado, F. Chéroux, A. Colette, A. Coman, R. L. Curier, H. A. C. Denier van der Gon, A. Drouin, H. Elbern, E. Emili, R. J. Engelen, H. J. Eskes, G. Foret, E. Friese, M. Gauss, C. Giannaros, J. Guth, M. Joly, E. Jaumouillé, B. Josse, N. Kadygrov, J. W. Kaiser, K. Krajsek, J. Kuenen, U. Kumar, N. Liora, E. Lopez, L. Malherbe, I. Martinez, D. Melas, F. Meleux, L. Menut, P. Moinat, T. Morales, J. Parmentier, A. Piacentini, M. Plu, A. Poupkou, S. Queguiner, L. Robertson, L. Rouïl, M. Schaap, A. Segers, M. Sofiev, L. Tarasson, M. Thomas, R. Timmermans, Á. Valdebenito, P. van Velthoven, R. van Versendaal, J. Vira, and A. Ung
Geosci. Model Dev., 8, 2777–2813, https://doi.org/10.5194/gmd-8-2777-2015, https://doi.org/10.5194/gmd-8-2777-2015, 2015
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This paper describes the air quality forecasting system over Europe put in place in the Monitoring Atmospheric Composition and Climate projects. It provides daily and 4-day forecasts and analyses for the previous day for major gas and particulate pollutants and their main precursors. These products are based on a multi-model approach using seven state-of-the-art models developed in Europe. An evaluation of the performance of the system is discussed in the paper.
H. Petetin, M. Beekmann, A. Colomb, H. A. C. Denier van der Gon, J.-C. Dupont, C. Honoré, V. Michoud, Y. Morille, O. Perrussel, A. Schwarzenboeck, J. Sciare, A. Wiedensohler, and Q. J. Zhang
Atmos. Chem. Phys., 15, 9799–9818, https://doi.org/10.5194/acp-15-9799-2015, https://doi.org/10.5194/acp-15-9799-2015, 2015
A. Babenhauserheide, S. Basu, S. Houweling, W. Peters, and A. Butz
Atmos. Chem. Phys., 15, 9747–9763, https://doi.org/10.5194/acp-15-9747-2015, https://doi.org/10.5194/acp-15-9747-2015, 2015
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We compare two different data assimilation systems for estimating sources and sinks of CO_2 from concentration measurements. The systems are CarbonTracker and TM5-4DVar, which have both been used in a number of scientific studies. We analyze the differences between both models as well as the sensitivity of the estimated sources and sinks to the observation coverage. The results provide a lower limit for the uncertainty of surface carbon fluxes with the current measurement network.
M. Beekmann, A. S. H. Prévôt, F. Drewnick, J. Sciare, S. N. Pandis, H. A. C. Denier van der Gon, M. Crippa, F. Freutel, L. Poulain, V. Ghersi, E. Rodriguez, S. Beirle, P. Zotter, S.-L. von der Weiden-Reinmüller, M. Bressi, C. Fountoukis, H. Petetin, S. Szidat, J. Schneider, A. Rosso, I. El Haddad, A. Megaritis, Q. J. Zhang, V. Michoud, J. G. Slowik, S. Moukhtar, P. Kolmonen, A. Stohl, S. Eckhardt, A. Borbon, V. Gros, N. Marchand, J. L. Jaffrezo, A. Schwarzenboeck, A. Colomb, A. Wiedensohler, S. Borrmann, M. Lawrence, A. Baklanov, and U. Baltensperger
Atmos. Chem. Phys., 15, 9577–9591, https://doi.org/10.5194/acp-15-9577-2015, https://doi.org/10.5194/acp-15-9577-2015, 2015
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A detailed characterization of air quality in the Paris (France) agglomeration, a megacity, during two summer and winter intensive campaigns and from additional 1-year observations, revealed that about 70% of the fine particulate matter (PM) at urban background is transported into the megacity from upwind regions. Unexpectedly, a major part of organic PM is of modern origin (woodburning and cooking activities, secondary formation from biogenic VOC).
S. Fuzzi, U. Baltensperger, K. Carslaw, S. Decesari, H. Denier van der Gon, M. C. Facchini, D. Fowler, I. Koren, B. Langford, U. Lohmann, E. Nemitz, S. Pandis, I. Riipinen, Y. Rudich, M. Schaap, J. G. Slowik, D. V. Spracklen, E. Vignati, M. Wild, M. Williams, and S. Gilardoni
Atmos. Chem. Phys., 15, 8217–8299, https://doi.org/10.5194/acp-15-8217-2015, https://doi.org/10.5194/acp-15-8217-2015, 2015
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Particulate matter (PM) constitutes one of the most challenging problems both for air quality and climate change policies. This paper reviews the most recent scientific results on the issue and the policy needs that have driven much of the increase in monitoring and mechanistic research over the last 2 decades. The synthesis reveals many new processes and developments in the science underpinning climate-PM interactions and the effects of PM on human health and the environment.
H. A. C. Denier van der Gon, R. Bergström, C. Fountoukis, C. Johansson, S. N. Pandis, D. Simpson, and A. J. H. Visschedijk
Atmos. Chem. Phys., 15, 6503–6519, https://doi.org/10.5194/acp-15-6503-2015, https://doi.org/10.5194/acp-15-6503-2015, 2015
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Residential wood combustion (RWC) is increasing in Europe but may cause high emissions of particulate matter (PM). A revised bottom-up emission inventory was made which included the semi-volatile components. The revised RWC emissions are 2–3 times higher than the previous inventory. It significantly improved the modeling of PM and comparison with observations. Our results suggest primary PM2.5 emission from RWC as reported in Europe is underestimated and emission inventories need to be revised.
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
M. Köchy, A. Don, M. K. van der Molen, and A. Freibauer
SOIL, 1, 367–380, https://doi.org/10.5194/soil-1-367-2015, https://doi.org/10.5194/soil-1-367-2015, 2015
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Using ranges for variables in a model of organic C stocks of the top 1m of soil on a global 0.5° grid, we assessed the (un)certainty of changes in stocks over the next 75 years. Changes are more certain where land-use change strongly affects carbon inputs and where higher temperatures and adequate moisture favour decomposition, e.g. tropical mountain forests. Global stocks will increase by 1% with a certainty of 75% if inputs to the soil increase due to CO₂ fertilization of the vegetation.
S. Banzhaf, M. Schaap, R. Kranenburg, A. M. M. Manders, A. J. Segers, A. J. H. Visschedijk, H. A. C. Denier van der Gon, J. J. P. Kuenen, E. van Meijgaard, L. H. van Ulft, J. Cofala, and P. J. H. Builtjes
Geosci. Model Dev., 8, 1047–1070, https://doi.org/10.5194/gmd-8-1047-2015, https://doi.org/10.5194/gmd-8-1047-2015, 2015
G. Curci, L. Ferrero, P. Tuccella, F. Barnaba, F. Angelini, E. Bolzacchini, C. Carbone, H. A. C. Denier van der Gon, M. C. Facchini, G. P. Gobbi, J. P. P. Kuenen, T. C. Landi, C. Perrino, M. G. Perrone, G. Sangiorgi, and P. Stocchi
Atmos. Chem. Phys., 15, 2629–2649, https://doi.org/10.5194/acp-15-2629-2015, https://doi.org/10.5194/acp-15-2629-2015, 2015
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Particulate matter (PM) at ground level is of primary concern for the quality of the air we breathe. Most direct sources of PM are near the ground, but an important fraction of PM is produced by photochemical processes happening also in the upper atmospheric layers. We investigated the contribution of those layers to the PM near the ground and found a significant impact. Nitrate is a major player in the “vertical direction”, owing to its sensitivity to ambient temperature and relative humidity.
S. Kulkarni, N. Sobhani, J. P. Miller-Schulze, M. M. Shafer, J. J. Schauer, P. A. Solomon, P. E. Saide, S. N. Spak, Y. F. Cheng, H. A. C. Denier van der Gon, Z. Lu, D. G. Streets, G. Janssens-Maenhout, C. Wiedinmyer, J. Lantz, M. Artamonova, B. Chen, S. Imashev, L. Sverdlik, J. T. Deminter, B. Adhikary, A. D'Allura, C. Wei, and G. R. Carmichael
Atmos. Chem. Phys., 15, 1683–1705, https://doi.org/10.5194/acp-15-1683-2015, https://doi.org/10.5194/acp-15-1683-2015, 2015
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This study presents a regional-scale modeling analysis of aerosols in the Central Asia region including detailed characterization of seasonal source region and sector contributions along with the predicted changes in distribution of aerosols using 2030 future emission scenarios. The influence of long transport and impact of varied emission sources including dust, biomass burning, and anthropogenic sources on the regional aerosol distributions and the associated transport pathways are discussed.
J. E. Jonson, J. P. Jalkanen, L. Johansson, M. Gauss, and H. A. C. Denier van der Gon
Atmos. Chem. Phys., 15, 783–798, https://doi.org/10.5194/acp-15-783-2015, https://doi.org/10.5194/acp-15-783-2015, 2015
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In order to assess the effects of ship emissions in and around the
Baltic Sea and the North Sea, regional model calculations are made
with the EMEP air pollution model. Ship emissions are based on
accurate ship positioning data. The effects on depositions and air
pollution and the resulting number of years of life lost (YOLLs)
are calculated by comparing model calculations with and without
ship emissions, with ship emissions before and after 2010, and for future
projections.
M. Combe, J. Vilà-Guerau de Arellano, H. G. Ouwersloot, C. M. J. Jacobs, and W. Peters
Biogeosciences, 12, 103–123, https://doi.org/10.5194/bg-12-103-2015, https://doi.org/10.5194/bg-12-103-2015, 2015
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This study investigates the interactions among the carbon, water and heat cycles above a maize field at the diurnal scale. We couple two land-surface schemes, corresponding to two different modelling approaches, to the same atmospheric boundary-layer (ABL) model. We find the simpler meteorological approach best reproduces the surface and upper-air observations. Finally, we show that the interaction of subsidence with ABL dynamics is key to explain the daytime atmospheric CO2 budget.
K. A. Masarie, W. Peters, A. R. Jacobson, and P. P. Tans
Earth Syst. Sci. Data, 6, 375–384, https://doi.org/10.5194/essd-6-375-2014, https://doi.org/10.5194/essd-6-375-2014, 2014
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Observation Package (ObsPack) is a framework designed to bring together atmospheric greenhouse gas measurements from a variety of sampling platforms, prepare them with specific applications in mind, and package and distribute them in a self-consistent and well-documented product. The framework includes a unique distribution stategy designed to improve communication between product users and data providers. The concepts presented are general and may be easily applied to other scientific data.
S. Nordmann, Y. F. Cheng, G. R. Carmichael, M. Yu, H. A. C. Denier van der Gon, Q. Zhang, P. E. Saide, U. Pöschl, H. Su, W. Birmili, and A. Wiedensohler
Atmos. Chem. Phys., 14, 12683–12699, https://doi.org/10.5194/acp-14-12683-2014, https://doi.org/10.5194/acp-14-12683-2014, 2014
I. R. van der Velde, J. B. Miller, K. Schaefer, G. R. van der Werf, M. C. Krol, and W. Peters
Biogeosciences, 11, 6553–6571, https://doi.org/10.5194/bg-11-6553-2014, https://doi.org/10.5194/bg-11-6553-2014, 2014
S. Archer-Nicholls, D. Lowe, S. Utembe, J. Allan, R. A. Zaveri, J. D. Fast, Ø. Hodnebrog, H. Denier van der Gon, and G. McFiggans
Geosci. Model Dev., 7, 2557–2579, https://doi.org/10.5194/gmd-7-2557-2014, https://doi.org/10.5194/gmd-7-2557-2014, 2014
J. J. P. Kuenen, A. J. H. Visschedijk, M. Jozwicka, and H. A. C. Denier van der Gon
Atmos. Chem. Phys., 14, 10963–10976, https://doi.org/10.5194/acp-14-10963-2014, https://doi.org/10.5194/acp-14-10963-2014, 2014
A. G. Megaritis, C. Fountoukis, P. E. Charalampidis, H. A. C. Denier van der Gon, C. Pilinis, and S. N. Pandis
Atmos. Chem. Phys., 14, 10283–10298, https://doi.org/10.5194/acp-14-10283-2014, https://doi.org/10.5194/acp-14-10283-2014, 2014
H. N. Mbufong, M. Lund, M. Aurela, T. R. Christensen, W. Eugster, T. Friborg, B. U. Hansen, E. R. Humphreys, M. Jackowicz-Korczynski, L. Kutzbach, P. M. Lafleur, W. C. Oechel, F. J. W. Parmentier, D. P. Rasse, A. V. Rocha, T. Sachs, M. K. van der Molen, and M. P. Tamstorf
Biogeosciences, 11, 4897–4912, https://doi.org/10.5194/bg-11-4897-2014, https://doi.org/10.5194/bg-11-4897-2014, 2014
C. Fountoukis, A. G. Megaritis, K. Skyllakou, P. E. Charalampidis, C. Pilinis, H. A. C. Denier van der Gon, M. Crippa, F. Canonaco, C. Mohr, A. S. H. Prévôt, J. D. Allan, L. Poulain, T. Petäjä, P. Tiitta, S. Carbone, A. Kiendler-Scharr, E. Nemitz, C. O'Dowd, E. Swietlicki, and S. N. Pandis
Atmos. Chem. Phys., 14, 9061–9076, https://doi.org/10.5194/acp-14-9061-2014, https://doi.org/10.5194/acp-14-9061-2014, 2014
D. Bozhinova, M. K. van der Molen, I. R. van der Velde, M. C. Krol, S. van der Laan, H. A. J. Meijer, and W. Peters
Atmos. Chem. Phys., 14, 7273–7290, https://doi.org/10.5194/acp-14-7273-2014, https://doi.org/10.5194/acp-14-7273-2014, 2014
H. F. Zhang, B. Z. Chen, I. T. van der Laan-Luijk, T. Machida, H. Matsueda, Y. Sawa, Y. Fukuyama, R. Langenfelds, M. van der Schoot, G. Xu, J. W. Yan, M. L. Cheng, L. X. Zhou, P. P. Tans, and W. Peters
Atmos. Chem. Phys., 14, 5807–5824, https://doi.org/10.5194/acp-14-5807-2014, https://doi.org/10.5194/acp-14-5807-2014, 2014
D. C. S. Beddows, M. Dall'Osto, R. M. Harrison, M. Kulmala, A. Asmi, A. Wiedensohler, P. Laj, A.M. Fjaeraa, K. Sellegri, W. Birmili, N. Bukowiecki, E. Weingartner, U. Baltensperger, V. Zdimal, N. Zikova, J.-P. Putaud, A. Marinoni, P. Tunved, H.-C. Hansson, M. Fiebig, N. Kivekäs, E. Swietlicki, H. Lihavainen, E. Asmi, V. Ulevicius, P. P. Aalto, N. Mihalopoulos, N. Kalivitis, I. Kalapov, G. Kiss, G. de Leeuw, B. Henzing, C. O'Dowd, S. G. Jennings, H. Flentje, F. Meinhardt, L. Ries, H. A. C. Denier van der Gon, and A. J. H. Visschedijk
Atmos. Chem. Phys., 14, 4327–4348, https://doi.org/10.5194/acp-14-4327-2014, https://doi.org/10.5194/acp-14-4327-2014, 2014
S. Banzhaf, M. Schaap, R. J. Wichink Kruit, H. A. C. Denier van der Gon, R. Stern, and P. J. H. Builtjes
Atmos. Chem. Phys., 13, 11675–11693, https://doi.org/10.5194/acp-13-11675-2013, https://doi.org/10.5194/acp-13-11675-2013, 2013
P. Peylin, R. M. Law, K. R. Gurney, F. Chevallier, A. R. Jacobson, T. Maki, Y. Niwa, P. K. Patra, W. Peters, P. J. Rayner, C. Rödenbeck, I. T. van der Laan-Luijkx, and X. Zhang
Biogeosciences, 10, 6699–6720, https://doi.org/10.5194/bg-10-6699-2013, https://doi.org/10.5194/bg-10-6699-2013, 2013
J. Genberg, H. A. C. Denier van der Gon, D. Simpson, E. Swietlicki, H. Areskoug, D. Beddows, D. Ceburnis, M. Fiebig, H. C. Hansson, R. M. Harrison, S. G. Jennings, S. Saarikoski, G. Spindler, A. J. H. Visschedijk, A. Wiedensohler, K. E. Yttri, and R. Bergström
Atmos. Chem. Phys., 13, 8719–8738, https://doi.org/10.5194/acp-13-8719-2013, https://doi.org/10.5194/acp-13-8719-2013, 2013
F. Deng, J. M. Chen, Y. Pan, W. Peters, R. Birdsey, K. McCullough, and J. Xiao
Biogeosciences, 10, 5335–5348, https://doi.org/10.5194/bg-10-5335-2013, https://doi.org/10.5194/bg-10-5335-2013, 2013
Q. J. Zhang, M. Beekmann, F. Drewnick, F. Freutel, J. Schneider, M. Crippa, A. S. H. Prevot, U. Baltensperger, L. Poulain, A. Wiedensohler, J. Sciare, V. Gros, A. Borbon, A. Colomb, V. Michoud, J.-F. Doussin, H. A. C. Denier van der Gon, M. Haeffelin, J.-C. Dupont, G. Siour, H. Petetin, B. Bessagnet, S. N. Pandis, A. Hodzic, O. Sanchez, C. Honoré, and O. Perrussel
Atmos. Chem. Phys., 13, 5767–5790, https://doi.org/10.5194/acp-13-5767-2013, https://doi.org/10.5194/acp-13-5767-2013, 2013
M. Krol, W. Peters, P. Hooghiemstra, M. George, C. Clerbaux, D. Hurtmans, D. McInerney, F. Sedano, P. Bergamaschi, M. El Hajj, J. W. Kaiser, D. Fisher, V. Yershov, and J.-P. Muller
Atmos. Chem. Phys., 13, 4737–4747, https://doi.org/10.5194/acp-13-4737-2013, https://doi.org/10.5194/acp-13-4737-2013, 2013
G. R. van der Werf, W. Peters, T. T. van Leeuwen, and L. Giglio
Clim. Past, 9, 289–306, https://doi.org/10.5194/cp-9-289-2013, https://doi.org/10.5194/cp-9-289-2013, 2013
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Dynamic Meteorology-induced Emissions Coupler (MetEmis) development in the Community Multiscale Air Quality (CMAQ): CMAQ-MetEmis
Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1)
A global grid model for the estimation of zenith tropospheric delay considering the variations at different altitudes
Simulating heat and CO2 fluxes in Beijing using SUEWS V2020b: sensitivity to vegetation phenology and maximum conductance
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
A Python library for computing individual and merged non-CO2 algorithmic climate change functions: CLIMaCCF V1.0
The three-dimensional structure of fronts in mid-latitude weather systems in numerical weather prediction models
The development and validation of the Inhomogeneous Wind Scheme for Urban Street (IWSUS-v1)
GPU-HADVPPM V1.0: a high-efficiency parallel GPU design of the piecewise parabolic method (PPM) for horizontal advection in an air quality model (CAMx V6.10)
Variability and combination as an ensemble of mineral dust forecasts during the 2021 CADDIWA experiment using the WRF 3.7.1 and CHIMERE v2020r3 models
Breakups are complicated: an efficient representation of collisional breakup in the superdroplet method
An optimized semi-empirical physical approach for satellite-based PM2.5 retrieval: embedding machine learning to simulate complex physical parameters
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
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In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Owen K. Hughes and Christiane Jablonowski
Geosci. Model Dev., 16, 6805–6831, https://doi.org/10.5194/gmd-16-6805-2023, https://doi.org/10.5194/gmd-16-6805-2023, 2023
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Atmospheric models benefit from idealized tests that assess their accuracy in a simpler simulation. A new test with artificial mountains is developed for models on a spherical earth. The mountains trigger the development of both planetary-scale and small-scale waves. These can be analyzed in dry or moist environments, with a simple rainfall mechanism. Four atmospheric models are intercompared. This sheds light on the pros and cons of the model design and the impact of mountains on the flow.
Zhongwei Luo, Yan Han, Kun Hua, Yufen Zhang, Jianhui Wu, Xiaohui Bi, Qili Dai, Baoshuang Liu, Yang Chen, Xin Long, and Yinchang Feng
Geosci. Model Dev., 16, 6757–6771, https://doi.org/10.5194/gmd-16-6757-2023, https://doi.org/10.5194/gmd-16-6757-2023, 2023
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This study explores how the variation in the source profiles adopted in chemical transport models (CTMs) impacts the simulated results of chemical components in PM2.5 based on sensitivity analysis. The impact on PM2.5 components cannot be ignored, and its influence can be transmitted and linked between components. The representativeness and timeliness of the source profile should be paid adequate attention in air quality simulation.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6635–6670, https://doi.org/10.5194/gmd-16-6635-2023, https://doi.org/10.5194/gmd-16-6635-2023, 2023
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Most current studies on planetary boundary layer (PBL) parameterization schemes are relatively fragmented and lack systematic in-depth analysis and discussion. In this study, we comprehensively evaluate the performance capability of the PBL scheme in five typical regions of China in different seasons from the mechanism of the scheme and the effects of PBL schemes on the near-surface meteorological parameters, vertical structures of the PBL, PBL height, and turbulent diffusion.
William Rudisill, Alejandro Flores, and Rosemary Carroll
Geosci. Model Dev., 16, 6531–6552, https://doi.org/10.5194/gmd-16-6531-2023, https://doi.org/10.5194/gmd-16-6531-2023, 2023
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It is important to know how well atmospheric models do in mountains, but there are not very many weather stations. We evaluate rain and snow from a model from 1987–2020 in the Upper Colorado River basin against the available data. The model works rather well, but there are still some uncertainties in remote locations. We then use snow maps collected by aircraft, streamflow measurements, and some advanced statistics to help identify how well the model works in ways we could not do before.
Angel Liduvino Vara-Vela, Christoffer Karoff, Noelia Rojas Benavente, and Janaina P. Nascimento
Geosci. Model Dev., 16, 6413–6431, https://doi.org/10.5194/gmd-16-6413-2023, https://doi.org/10.5194/gmd-16-6413-2023, 2023
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A 1-year simulation of atmospheric CH4 over Europe is performed and evaluated against observations based on the TROPOspheric Monitoring Instrument (TROPOMI). A good general model–observation agreement is found, with discrepancies reaching their minimum and maximum values during the summer peak season and winter months, respectively. A huge and under-explored potential for CH4 inverse modeling using improved TROPOMI XCH4 data sets in large-scale applications is identified.
Zhaojun Tang, Zhe Jiang, Jiaqi Chen, Panpan Yang, and Yanan Shen
Geosci. Model Dev., 16, 6377–6392, https://doi.org/10.5194/gmd-16-6377-2023, https://doi.org/10.5194/gmd-16-6377-2023, 2023
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We designed a new framework to facilitate emission inventory updates in the adjoint of GEOS-Chem model. It allows us to support Harmonized Emissions Component (HEMCO) emission inventories conveniently and to easily add more emission inventories following future updates in GEOS-Chem forward simulations. Furthermore, we developed new modules to support MERRA-2 meteorological data; this allows us to perform long-term analysis with consistent meteorological data.
Rui Zhu, Zhaojun Tang, Xiaokang Chen, Xiong Liu, and Zhe Jiang
Geosci. Model Dev., 16, 6337–6354, https://doi.org/10.5194/gmd-16-6337-2023, https://doi.org/10.5194/gmd-16-6337-2023, 2023
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A single ozone (O3) tracer mode was developed in this work to build the capability of the GEOS-Chem model for rapid O3 simulation. It is combined with OMI and surface O3 observations to investigate the changes in tropospheric O3 in China in 2015–2020. The assimilations indicate rapid surface O3 increases that are underestimated by the a priori simulations. We find stronger increases in tropospheric O3 columns over polluted areas and a large discrepancy by assimilating different observations.
Ewa M. Bednarz, Ryan Hossaini, N. Luke Abraham, and Martyn P. Chipperfield
Geosci. Model Dev., 16, 6187–6209, https://doi.org/10.5194/gmd-16-6187-2023, https://doi.org/10.5194/gmd-16-6187-2023, 2023
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Development and performance of the new DEST chemistry scheme of UM–UKCA is described. The scheme extends the standard StratTrop scheme by including important updates to the halogen chemistry, thus allowing process-oriented studies of stratospheric ozone depletion and recovery, including impacts from both controlled long-lived ozone-depleting substances and emerging issues around uncontrolled, very short-lived substances. It will thus aid studies in support of future ozone assessment reports.
Shaohui Zhou, Chloe Yuchao Gao, Zexia Duan, Xingya Xi, and Yubin Li
Geosci. Model Dev., 16, 6247–6266, https://doi.org/10.5194/gmd-16-6247-2023, https://doi.org/10.5194/gmd-16-6247-2023, 2023
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The proposed wind speed correction model (VMD-PCA-RF) demonstrates the highest prediction accuracy and stability in the five southern provinces in nearly a year and at different heights. VMD-PCA-RF evaluation indices for 13 months remain relatively stable: the forecasting accuracy rate FA is above 85 %. In future research, the proposed VMD-PCA-RF algorithm can be extrapolated to the 3 km grid points of the five southern provinces to generate a 3 km grid-corrected wind speed product.
Simone Tilmes, Michael J. Mills, Yunqian Zhu, Charles G. Bardeen, Francis Vitt, Pengfei Yu, David Fillmore, Xiaohong Liu, Brian Toon, and Terry Deshler
Geosci. Model Dev., 16, 6087–6125, https://doi.org/10.5194/gmd-16-6087-2023, https://doi.org/10.5194/gmd-16-6087-2023, 2023
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We implemented an alternative aerosol scheme in the high- and low-top model versions of the Community Earth System Model Version 2 (CESM2) with a more detailed description of tropospheric and stratospheric aerosol size distributions than the existing aerosol model. This development enables the comparison of different aerosol schemes with different complexity in the same model framework. It identifies improvements compared to a range of observations in both the troposphere and stratosphere.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
Geosci. Model Dev., 16, 6161–6185, https://doi.org/10.5194/gmd-16-6161-2023, https://doi.org/10.5194/gmd-16-6161-2023, 2023
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To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and assess its performance against TROPOMI v2 over power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind directions and prior emissions.
Jiangshan Zhu and Ross Noel Bannister
Geosci. Model Dev., 16, 6067–6085, https://doi.org/10.5194/gmd-16-6067-2023, https://doi.org/10.5194/gmd-16-6067-2023, 2023
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We describe how condensation and evaporation are included in the existing (otherwise dry) simplified ABC model. The new model (Hydro-ABC) includes transport of vapour and condensate within a dynamical core, and it transitions between these two phases via a micro-physics scheme. The model shows the development of an anvil cloud and excitation of atmospheric waves over many frequencies. The covariances that develop between variables are also studied together with indicators of convective motion.
Jiangyong Li, Chunlin Zhang, Wenlong Zhao, Shijie Han, Yu Wang, Hao Wang, and Boguang Wang
Geosci. Model Dev., 16, 6049–6066, https://doi.org/10.5194/gmd-16-6049-2023, https://doi.org/10.5194/gmd-16-6049-2023, 2023
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Photochemical box models, crucial for understanding tropospheric chemistry, face challenges due to slow computational efficiency with large chemical equations. The model introduced in this study, ROMAC, boosts efficiency by up to 96 % using an advanced atmospheric solver and an adaptive optimization algorithm. Moreover, ROMAC exceeds traditional box models in evaluating the impact of physical processes on pollutant concentrations.
Lina Vitali, Kees Cuvelier, Antonio Piersanti, Alexandra Monteiro, Mario Adani, Roberta Amorati, Agnieszka Bartocha, Alessandro D'Ausilio, Paweł Durka, Carla Gama, Giulia Giovannini, Stijn Janssen, Tomasz Przybyła, Michele Stortini, Stijn Vranckx, and Philippe Thunis
Geosci. Model Dev., 16, 6029–6047, https://doi.org/10.5194/gmd-16-6029-2023, https://doi.org/10.5194/gmd-16-6029-2023, 2023
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Air quality forecasting models play a key role in fostering short-term measures aimed at reducing human exposure to air pollution. Together with this role comes the need for a thorough assessment of the model performances to build confidence in models’ capabilities, in particular when model applications support policymaking. In this paper, we propose an evaluation methodology and test it on several domains across Europe, highlighting its strengths and room for improvement.
Wenfu Tang, Louisa K. Emmons, Helen M. Worden, Rajesh Kumar, Cenlin He, Benjamin Gaubert, Zhonghua Zheng, Simone Tilmes, Rebecca R. Buchholz, Sara-Eva Martinez-Alonso, Claire Granier, Antonin Soulie, Kathryn McKain, Bruce C. Daube, Jeff Peischl, Chelsea Thompson, and Pieternel Levelt
Geosci. Model Dev., 16, 6001–6028, https://doi.org/10.5194/gmd-16-6001-2023, https://doi.org/10.5194/gmd-16-6001-2023, 2023
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The new MUSICAv0 model enables the study of atmospheric chemistry across all relevant scales. We develop a MUSICAv0 grid for Africa. We evaluate MUSICAv0 with observations and compare it with a previously used model – WRF-Chem. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Based on model–satellite discrepancies, we find that future field campaigns in an eastern African region (30°E–45°E, 5°S–5°N) could substantially improve the predictive skill of air quality models.
Shuzhuang Feng, Fei Jiang, Zheng Wu, Hengmao Wang, Wei He, Yang Shen, Lingyu Zhang, Yanhua Zheng, Chenxi Lou, Ziqiang Jiang, and Weimin Ju
Geosci. Model Dev., 16, 5949–5977, https://doi.org/10.5194/gmd-16-5949-2023, https://doi.org/10.5194/gmd-16-5949-2023, 2023
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We document the system development and application of a Regional multi-Air Pollutant Assimilation System (RAPAS v1.0). This system is developed to optimize gridded source emissions of CO, SO2, NOx, primary PM2.5, and coarse PM10 on a regional scale via simultaneously assimilating surface measurements of CO, SO2, NO2, PM2.5, and PM10. A series of sensitivity experiments demonstrates the advantage of the “two-step” inversion strategy and the robustness of the system in estimating the emissions.
Megan A. Stretton, William Morrison, Robin J. Hogan, and Sue Grimmond
Geosci. Model Dev., 16, 5931–5947, https://doi.org/10.5194/gmd-16-5931-2023, https://doi.org/10.5194/gmd-16-5931-2023, 2023
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Cities' materials and forms impact radiative fluxes. We evaluate the SPARTACUS-Urban multi-layer approach to modelling longwave radiation, describing realistic 3D geometry statistically using the explicit DART (Discrete Anisotropic Radiative Transfer) model. The temperature configurations used are derived from thermal camera observations. SPARTACUS-Urban accurately predicts longwave fluxes, with a low computational time (cf. DART), but has larger errors with sunlit/shaded surface temperatures.
Daehyeon Han, Jungho Im, Yeji Shin, and Juhyun Lee
Geosci. Model Dev., 16, 5895–5914, https://doi.org/10.5194/gmd-16-5895-2023, https://doi.org/10.5194/gmd-16-5895-2023, 2023
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To identify the key factors affecting quantitative precipitation nowcasting (QPN) using deep learning (DL), we carried out a comprehensive evaluation and analysis. We compared four key factors: DL model, length of the input sequence, loss function, and ensemble approach. Generally, U-Net outperformed ConvLSTM. Loss function and ensemble showed potential for improving performance when they synergized well. The length of the input sequence did not significantly affect the results.
Fabien Margairaz, Balwinder Singh, Jeremy A. Gibbs, Loren Atwood, Eric R. Pardyjak, and Rob Stoll
Geosci. Model Dev., 16, 5729–5754, https://doi.org/10.5194/gmd-16-5729-2023, https://doi.org/10.5194/gmd-16-5729-2023, 2023
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The Quick Environmental Simulation (QES) tool is a low-computational-cost fast-response framework. It provides high-resolution wind and concentration information to study complex problems, such as spore or smoke transport, urban pollution, and air quality. This paper presents the particle dispersion model and its validation against analytical solutions and wind-tunnel data for a mock-urban setting. In all cases, the model provides accurate results with competitive computational performance.
Tao Wang, Hang Liu, Jie Li, Shuai Wang, Youngseob Kim, Yele Sun, Wenyi Yang, Huiyun Du, Zhe Wang, and Zifa Wang
Geosci. Model Dev., 16, 5585–5599, https://doi.org/10.5194/gmd-16-5585-2023, https://doi.org/10.5194/gmd-16-5585-2023, 2023
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This paper developed a two-way coupled module in a new version of a regional urban–street network model, IAQMS-street v2.0, in which the mass flux from streets to background is considered. Test cases are defined to evaluate the performance of IAQMS-street v2.0 in Beijing by comparing it with that simulated by IAQMS-street v1.0 and a regional model. The contribution of local emissions and the influence of on-road vehicle control measures on air quality are evaluated by using IAQMS-street v2.0.
Denis E. Sergeev, Nathan J. Mayne, Thomas Bendall, Ian A. Boutle, Alex Brown, Iva Kavčič, James Kent, Krisztian Kohary, James Manners, Thomas Melvin, Enrico Olivier, Lokesh K. Ragta, Ben Shipway, Jon Wakelin, Nigel Wood, and Mohamed Zerroukat
Geosci. Model Dev., 16, 5601–5626, https://doi.org/10.5194/gmd-16-5601-2023, https://doi.org/10.5194/gmd-16-5601-2023, 2023
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Three-dimensional climate models are one of the best tools we have to study planetary atmospheres. Here, we apply LFRic-Atmosphere, a new model developed by the Met Office, to seven different scenarios for terrestrial planetary climates, including four for the exoplanet TRAPPIST-1e, a primary target for future observations. LFRic-Atmosphere reproduces these scenarios within the spread of the existing models across a range of key climatic variables, justifying its use in future exoplanet studies.
Roland Eichinger, Sebastian Rhode, Hella Garny, Peter Preusse, Petr Pisoft, Aleš Kuchař, Patrick Jöckel, Astrid Kerkweg, and Bastian Kern
Geosci. Model Dev., 16, 5561–5583, https://doi.org/10.5194/gmd-16-5561-2023, https://doi.org/10.5194/gmd-16-5561-2023, 2023
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The columnar approach of gravity wave (GW) schemes results in dynamical model biases, but parallel decomposition makes horizontal GW propagation computationally unfeasible. In the global model EMAC, we approximate it by GW redistribution at one altitude using tailor-made redistribution maps generated with a ray tracer. More spread-out GW drag helps reconcile the model with observations and close the 60°S GW gap. Polar vortex dynamics are improved, enhancing climate model credibility.
Xueying Liu, Yuxuan Wang, Shailaja Wasti, Wei Li, Ehsan Soleimanian, James Flynn, Travis Griggs, Sergio Alvarez, John T. Sullivan, Maurice Roots, Laurence Twigg, Guillaume Gronoff, Timothy Berkoff, Paul Walter, Mark Estes, Johnathan W. Hair, Taylor Shingler, Amy Jo Scarino, Marta Fenn, and Laura Judd
Geosci. Model Dev., 16, 5493–5514, https://doi.org/10.5194/gmd-16-5493-2023, https://doi.org/10.5194/gmd-16-5493-2023, 2023
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With a comprehensive suite of ground-based and airborne remote sensing measurements during the 2021 TRacking Aerosol Convection ExpeRiment – Air Quality (TRACER-AQ) campaign in Houston, this study evaluates the simulation of the planetary boundary layer (PBL) height and the ozone vertical profile by a high-resolution (1.33 km) 3-D photochemical model Weather Research and Forecasting-driven GEOS-Chem (WRF-GC).
Stijn Van Leuven, Pieter De Meutter, Johan Camps, Piet Termonia, and Andy Delcloo
Geosci. Model Dev., 16, 5323–5338, https://doi.org/10.5194/gmd-16-5323-2023, https://doi.org/10.5194/gmd-16-5323-2023, 2023
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Precipitation collects airborne particles and deposits these on the ground. This process is called wet deposition and greatly determines how airborne radioactive particles (released routinely or accidentally) contaminate the surface. In this work we present a new method to improve the calculation of wet deposition in computer models. We apply this method to the existing model FLEXPART by simulating the Fukushima nuclear accident (2011) and show that it improves the simulation of wet deposition.
Thibaud Sarica, Alice Maison, Yelva Roustan, Matthias Ketzel, Steen Solvang Jensen, Youngseob Kim, Christophe Chaillou, and Karine Sartelet
Geosci. Model Dev., 16, 5281–5303, https://doi.org/10.5194/gmd-16-5281-2023, https://doi.org/10.5194/gmd-16-5281-2023, 2023
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A new version of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) is developed to represent heterogeneities of concentrations in streets. The street volume is discretized vertically and horizontally to limit the artificial dilution of emissions and concentrations. This new version is applied to street networks in Copenhagen and Paris. The comparisons to observations are improved, with higher concentrations of pollutants emitted by traffic at the bottom of the street.
Junsu Gil, Meehye Lee, Jeonghwan Kim, Gangwoong Lee, Joonyoung Ahn, and Cheol-Hee Kim
Geosci. Model Dev., 16, 5251–5263, https://doi.org/10.5194/gmd-16-5251-2023, https://doi.org/10.5194/gmd-16-5251-2023, 2023
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In this study, the framework for calculating reactive nitrogen species using a deep neural network (RND) was developed. It works through simple Python codes and provides high-accuracy reactive nitrogen oxide data. In the first version (RNDv1.0), the model calculates the nitrous acid (HONO) in urban areas, which has an important role in producing O3 and fine aerosol.
Daniel Yazgi and Tinja Olenius
Geosci. Model Dev., 16, 5237–5249, https://doi.org/10.5194/gmd-16-5237-2023, https://doi.org/10.5194/gmd-16-5237-2023, 2023
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We present flexible tools to implement aerosol formation rate predictions in climate and chemical transport models. New-particle formation is a significant but uncertain factor affecting aerosol numbers and an active field within molecular modeling which provides data for assessing formation rates for different chemical species. We introduce tools to generate and interpolate formation rate lookup tables for user-defined data, thus enabling the easy inclusion and testing of formation schemes.
Vineet Yadav, Subhomoy Ghosh, and Charles E. Miller
Geosci. Model Dev., 16, 5219–5236, https://doi.org/10.5194/gmd-16-5219-2023, https://doi.org/10.5194/gmd-16-5219-2023, 2023
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Measuring the performance of inversions in linear Bayesian problems is crucial in real-life applications. In this work, we provide analytical forms of the local and global sensitivities of the estimated fluxes with respect to various inputs. We provide methods to uniquely map the observational signal to spatiotemporal domains. Utilizing this, we also show techniques to assess correlations between the Jacobians that naturally translate to nonstationary covariance matrix components.
Mingzhao Liu, Lars Hoffmann, Sabine Griessbach, Zhongyin Cai, Yi Heng, and Xue Wu
Geosci. Model Dev., 16, 5197–5217, https://doi.org/10.5194/gmd-16-5197-2023, https://doi.org/10.5194/gmd-16-5197-2023, 2023
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We introduce new and revised chemistry and physics modules in the Massive-Parallel Trajectory Calculations (MPTRAC) Lagrangian transport model aiming to improve the representation of volcanic SO2 transport and depletion. We test these modules in a case study of the Ambae eruption in July 2018 in which the SO2 plume underwent wet removal and convection. The lifetime of SO2 shows highly variable and complex dependencies on the atmospheric conditions at different release heights.
Bernhard M. Enz, Jan P. Engelmann, and Ulrike Lohmann
Geosci. Model Dev., 16, 5093–5112, https://doi.org/10.5194/gmd-16-5093-2023, https://doi.org/10.5194/gmd-16-5093-2023, 2023
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An algorithm to track tropical cyclones in model simulation data has been developed. The algorithm uses many combinations of varying parameter thresholds to detect weaker phases of tropical cyclones while still being resilient to false positives. It is shown that the algorithm performs well and adequately represents the tropical cyclone activity of the underlying simulation data. The impact of false positives on overall tropical cyclone activity is shown to be insignificant.
Sepehr Fathi, Mark Gordon, and Yongsheng Chen
Geosci. Model Dev., 16, 5069–5091, https://doi.org/10.5194/gmd-16-5069-2023, https://doi.org/10.5194/gmd-16-5069-2023, 2023
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We have combined various capabilities within a WRF model to generate simulations of atmospheric pollutant dispersion at 50 m resolution. The study objective was to resolve transport processes at the scale of measurements to assess and optimize aircraft-based emission rate retrievals. Model performance evaluation resulted in agreement within 5 % of observed meteorological and within 1–2 standard deviations of observed wind fields. Mass was conserved in the model within 5 % of input emissions.
Dylan Reynolds, Ethan Gutmann, Bert Kruyt, Michael Haugeneder, Tobias Jonas, Franziska Gerber, Michael Lehning, and Rebecca Mott
Geosci. Model Dev., 16, 5049–5068, https://doi.org/10.5194/gmd-16-5049-2023, https://doi.org/10.5194/gmd-16-5049-2023, 2023
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The challenge of running geophysical models is often compounded by the question of where to obtain appropriate data to give as input to a model. Here we present the HICAR model, a simplified atmospheric model capable of running at spatial resolutions of hectometers for long time series or over large domains. This makes physically consistent atmospheric data available at the spatial and temporal scales needed for some terrestrial modeling applications, for example seasonal snow forecasting.
Li Fang, Jianbing Jin, Arjo Segers, Hong Liao, Ke Li, Bufan Xu, Wei Han, Mijie Pang, and Hai Xiang Lin
Geosci. Model Dev., 16, 4867–4882, https://doi.org/10.5194/gmd-16-4867-2023, https://doi.org/10.5194/gmd-16-4867-2023, 2023
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Machine learning models have gained great popularity in air quality prediction. However, they are only available at air quality monitoring stations. In contrast, chemical transport models (CTM) provide predictions that are continuous in the 3D field. Owing to complex error sources, they are typically biased. In this study, we proposed a gridded prediction with high accuracy by fusing predictions from our regional feature selection machine learning prediction (RFSML v1.0) and a CTM prediction.
Willem Elias van Caspel, David Simpson, Jan Eiof Jonson, Anna Maria Katarina Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah Walker, and Mathew Heal
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-147, https://doi.org/10.5194/gmd-2023-147, 2023
Revised manuscript accepted for GMD
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Radiation coming from the sun is essential to atmospheric chemistry, driving the break-up, or photo-dissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of these photo-dissociation effects is therefore essential in atmospheric chemistry modeling. One such models is the EMEP MSC-W model, for which in this paper a new way of calculating the photo-dissociation rates is tested and evaluated.
Manu Goudar, Juliëtte C. S. Anema, Rajesh Kumar, Tobias Borsdorff, and Jochen Landgraf
Geosci. Model Dev., 16, 4835–4852, https://doi.org/10.5194/gmd-16-4835-2023, https://doi.org/10.5194/gmd-16-4835-2023, 2023
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A framework was developed to automatically detect plumes and compute emission estimates with cross-sectional flux method (CFM) for biomass burning events in TROPOMI CO datasets using Visible Infrared Imaging Radiometer Suite active fire data. The emissions were more reliable when changing plume height in downwind direction was used instead of constant injection height. The CFM had uncertainty even when the meteorological conditions were accurate; thus there is a need for better inversion models.
Drew C. Pendergrass, Daniel J. Jacob, Hannah Nesser, Daniel J. Varon, Melissa Sulprizio, Kazuyuki Miyazaki, and Kevin W. Bowman
Geosci. Model Dev., 16, 4793–4810, https://doi.org/10.5194/gmd-16-4793-2023, https://doi.org/10.5194/gmd-16-4793-2023, 2023
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We have built a tool called CHEEREIO that allows scientists to use observations of pollutants or gases in the atmosphere, such as from satellites or surface stations, to update supercomputer models that simulate the Earth. CHEEREIO uses the difference between the model simulations of the atmosphere and real-world observations to come up with a good guess for the actual composition of our atmosphere, the true emissions of various pollutants, and whatever else they may want to study.
Yosuke Yamazaki
Geosci. Model Dev., 16, 4749–4766, https://doi.org/10.5194/gmd-16-4749-2023, https://doi.org/10.5194/gmd-16-4749-2023, 2023
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The Earth's atmosphere can support various types of global-scale waves. Some waves propagate eastward and others westward, and they can have different zonal wavenumbers. The Fourier–wavelet analysis is a useful technique for identifying different components of global-scale waves and their temporal variability. This paper introduces an easy-to-implement method to derive Fourier–wavelet spectra from 2-D space–time data. Application examples are presented using atmospheric models.
Bok H. Baek, Carlie Coats, Siqi Ma, Chi-Tsan Wang, Yunyao Li, Jia Xing, Daniel Tong, Soontae Kim, and Jung-Hun Woo
Geosci. Model Dev., 16, 4659–4676, https://doi.org/10.5194/gmd-16-4659-2023, https://doi.org/10.5194/gmd-16-4659-2023, 2023
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To enable the direct feedback effects of aerosols and local meteorology in an air quality modeling system without any computational bottleneck, we have developed an inline meteorology-induced emissions coupler module within the U.S. Environmental Protection Agency’s Community Multiscale Air Quality modeling system to dynamically model the complex MOtor Vehicle Emission Simulator (MOVES) on-road mobile emissions inline without a separate dedicated emissions processing model like SMOKE.
Christoph Neuhauser, Maicon Hieronymus, Michael Kern, Marc Rautenhaus, Annika Oertel, and Rüdiger Westermann
Geosci. Model Dev., 16, 4617–4638, https://doi.org/10.5194/gmd-16-4617-2023, https://doi.org/10.5194/gmd-16-4617-2023, 2023
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Numerical weather prediction models rely on parameterizations for sub-grid-scale processes, which are a source of uncertainty. We present novel visual analytics solutions to analyze interactively the sensitivities of a selected prognostic variable to multiple model parameters along trajectories regarding similarities in temporal development and spatiotemporal relationships. The proposed workflow is applied to cloud microphysical sensitivities along coherent strongly ascending trajectories.
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-139, https://doi.org/10.5194/gmd-2023-139, 2023
Revised manuscript accepted for GMD
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The existing ZTD models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data for modeling. This model considers the daily-cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
Yingqi Zheng, Minttu Havu, Huizhi Liu, Xueling Cheng, Yifan Wen, Hei Shing Lee, Joyson Ahongshangbam, and Leena Järvi
Geosci. Model Dev., 16, 4551–4579, https://doi.org/10.5194/gmd-16-4551-2023, https://doi.org/10.5194/gmd-16-4551-2023, 2023
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The performance of the Surface Urban Energy and Water Balance Scheme (SUEWS) is evaluated against the observed surface exchanges (fluxes) of heat and carbon dioxide in a densely built neighborhood in Beijing. The heat flux modeling is noticeably improved by using the observed maximum conductance and by optimizing the vegetation phenology modeling. SUEWS also performs well in simulating carbon dioxide flux.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
EGUsphere, https://doi.org/10.5194/egusphere-2023-1181, https://doi.org/10.5194/egusphere-2023-1181, 2023
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With the worlwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However meteorological models that predict among others things solar radiation, have errors. Therefore, we so wanted to know in which situtaions these errors are most significant. We found that errors mostly occurs in cloudy situations, and different errors were highlighted depending of the cloud altitude. Several potential sources of errors were identified.
Simone Dietmüller, Sigrun Matthes, Katrin Dahlmann, Hiroshi Yamashita, Abolfazl Simorgh, Manuel Soler, Florian Linke, Benjamin Lührs, Maximilian M. Meuser, Christian Weder, Volker Grewe, Feijia Yin, and Federica Castino
Geosci. Model Dev., 16, 4405–4425, https://doi.org/10.5194/gmd-16-4405-2023, https://doi.org/10.5194/gmd-16-4405-2023, 2023
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Climate-optimized aircraft trajectories avoid atmospheric regions with a large climate impact due to aviation emissions. This requires spatially and temporally resolved information on aviation's climate impact. We propose using algorithmic climate change functions (aCCFs) for CO2 and non-CO2 effects (ozone, methane, water vapor, contrail cirrus). Merged aCCFs combine individual aCCFs by assuming aircraft-specific parameters and climate metrics. Technically this is done with a Python library.
Andreas A. Beckert, Lea Eisenstein, Annika Oertel, Tim Hewson, George C. Craig, and Marc Rautenhaus
Geosci. Model Dev., 16, 4427–4450, https://doi.org/10.5194/gmd-16-4427-2023, https://doi.org/10.5194/gmd-16-4427-2023, 2023
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We investigate the benefit of objective 3-D front detection with modern interactive visual analysis techniques for case studies of extra-tropical cyclones and comparisons of frontal structures between different numerical weather prediction models. The 3-D frontal structures show agreement with 2-D fronts from surface analysis charts and augment them in the vertical dimension. We see great potential for more complex studies of atmospheric dynamics and for operational weather forecasting.
Zhenxin Liu, Yuanhao Chen, Yuhang Wang, Cheng Liu, Shuhua Liu, and Hong Liao
Geosci. Model Dev., 16, 4385–4403, https://doi.org/10.5194/gmd-16-4385-2023, https://doi.org/10.5194/gmd-16-4385-2023, 2023
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The heterogeneous layout of urban buildings leads to the complex wind field in and over the urban canopy. Large discrepancies between the observations and the current simulations result from misunderstanding the character of the wind field. The Inhomogeneous Wind Scheme in Urban Street (IWSUS) was developed to simulate the heterogeneity of the wind speed in a typical street and then improve the simulated energy budget in the lower atmospheric layer over the urban canopy.
Kai Cao, Qizhong Wu, Lingling Wang, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongqing Li, and Lanning Wang
Geosci. Model Dev., 16, 4367–4383, https://doi.org/10.5194/gmd-16-4367-2023, https://doi.org/10.5194/gmd-16-4367-2023, 2023
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Offline performance experiment results show that the GPU-HADVPPM on a V100 GPU can achieve up to 1113.6 × speedups to its original version on an E5-2682 v4 CPU. A series of optimization measures are taken, and the CAMx-CUDA model improves the computing efficiency by 128.4 × on a single V100 GPU card. A parallel architecture with an MPI plus CUDA hybrid paradigm is presented, and it can achieve up to 4.5 × speedup when launching eight CPU cores and eight GPU cards.
Laurent Menut
Geosci. Model Dev., 16, 4265–4281, https://doi.org/10.5194/gmd-16-4265-2023, https://doi.org/10.5194/gmd-16-4265-2023, 2023
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This study analyzes forecasts that were made in 2021 to help trigger measurements during the CADDIWA experiment. The WRF and CHIMERE models were run each day, and the first goal is to quantify the variability of the forecast as a function of forecast leads and forecast location. The possibility of using the different leads as an ensemble is also tested. For some locations, the correlation scores are better with this approach. This could be tested on operational forecast chains in the future.
Emily de Jong, John Ben Mackay, Oleksii Bulenok, Anna Jaruga, and Sylwester Arabas
Geosci. Model Dev., 16, 4193–4211, https://doi.org/10.5194/gmd-16-4193-2023, https://doi.org/10.5194/gmd-16-4193-2023, 2023
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In clouds, collisional breakup occurs when two colliding droplets splinter into new, smaller fragments. Particle-based modeling approaches often do not represent breakup because of the computational demands of creating new droplets. We present a particle-based breakup method that preserves the computational efficiency of these methods. In a series of simple demonstrations, we show that this representation alters cloud processes in reasonable and expected ways.
Caiyi Jin, Qiangqiang Yuan, Tongwen Li, Yuan Wang, and Liangpei Zhang
Geosci. Model Dev., 16, 4137–4154, https://doi.org/10.5194/gmd-16-4137-2023, https://doi.org/10.5194/gmd-16-4137-2023, 2023
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The semi-empirical physical approach derives PM2.5 with strong physical significance. However, due to the complex optical characteristic, the physical parameters are difficult to express accurately. Thus, combining the atmospheric physical mechanism and machine learning, we propose an optimized model. It creatively embeds the random forest model into the physical PM2.5 remote sensing approach to simulate a physical parameter. Our method shows great optimized performance in the validations.
Cited articles
Akaike, H.: A new look at the statistical model identification, in: Selected
papers of Hirotugu Akaike. Springer Series in Statistics (Perspectives in
Statistics), edited by: Parzen, E., Tanabe, K., and Kitagawa, G., Springer,
New York, NY, 215–222, https://doi.org/10.1007/978-1-4612-1694-0_16, 1974.
Andres, R. J., Boden, T. A., and Higdon, D.: A new evaluation of the
uncertainty associated with CDIAC estimates of fossil fuel carbon dioxide
emission, Tellus B, 66, 23616, https://doi.org/10.3402/tellusb.v66.23616, 2014.
Andres, R. J., Boden, T. A., and Higdon, D. M.: Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example, Atmos. Chem. Phys., 16, 14979–14995, https://doi.org/10.5194/acp-16-14979-2016, 2016.
Angevine, W. M., Brioude, J., McKeen, S., and Holloway, J. S.: Uncertainty in Lagrangian pollutant transport simulations due to meteorological uncertainty from a mesoscale WRF ensemble, Geosci. Model Dev., 7, 2817–2829, https://doi.org/10.5194/gmd-7-2817-2014, 2014.
Asefi-Najafabady, S., Rayner, P. J., Gurney, K. R., McRobert, A., Song, Y.,
Coltin, K., Huang, J., Elvidge, C., and Baugh, K.: A multiyear, global
gridded fossil fuel CO2 emission data product: Evaluation and analysis of results, J. Geophys. Res.-Atmos., 119, 10213–210231, https://doi.org/10.1002/2013jd021296, 2014.
Basu, S., Miller, J. B., and Lehman, S.: Separation of biospheric and fossil fuel fluxes of CO2 by atmospheric inversion of CO2 and 14CO2 measurements: Observation System Simulations, Atmos. Chem. Phys., 16, 5665–5683, https://doi.org/10.5194/acp-16-5665-2016, 2016.
Boon, A., Broquet, G., Clifford, D. J., Chevallier, F., Butterfield, D. M., Pison, I., Ramonet, M., Paris, J.-D., and Ciais, P.: Analysis of the potential of near-ground measurements of CO2 and CH4 in London, UK, for the monitoring of city-scale emissions using an atmospheric transport model, Atmos. Chem. Phys., 16, 6735–6756, https://doi.org/10.5194/acp-16-6735-2016, 2016.
Boschetti, F., Thouret, V., Maenhout, G. J., Totsche, K. U., Marshall, J., and Gerbig, C.: Multi-species inversion and IAGOS airborne data for a better constraint of continental-scale fluxes, Atmos. Chem. Phys., 18, 9225–9241, https://doi.org/10.5194/acp-18-9225-2018, 2018.
Bréon, F. M., Broquet, G., Puygrenier, V., Chevallier, F., Xueref-Remy, I., Ramonet, M., Dieudonné, E., Lopez, M., Schmidt, M., Perrussel, O., and Ciais, P.: An attempt at estimating Paris area CO2 emissions from atmospheric concentration measurements, Atmos. Chem. Phys., 15, 1707–1724, https://doi.org/10.5194/acp-15-1707-2015, 2015.
Brioude, J., Angevine, W. M., Ahmadov, R., Kim, S.-W., Evan, S., McKeen, S. A., Hsie, E.-Y., Frost, G. J., Neuman, J. A., Pollack, I. B., Peischl, J., Ryerson, T. B., Holloway, J., Brown, S. S., Nowak, J. B., Roberts, J. M., Wofsy, S. C., Santoni, G. W., Oda, T., and Trainer, M.: Top-down estimate of surface flux in the Los Angeles Basin using a mesoscale inverse modeling technique: assessing anthropogenic emissions of CO, NOx and CO2 and their impacts, Atmos. Chem. Phys., 13, 3661–3677, https://doi.org/10.5194/acp-13-3661-2013
Brophy, K., Graven, H., Manning, A. J., White, E., Arnold, T., Fischer, M. L., Jeong, S., Cui, X., and Rigby, M.: Characterizing uncertainties in atmospheric inversions of fossil fuel CO2 emissions in California, Atmos. Chem. Phys., 19, 2991–3006, https://doi.org/10.5194/acp-19-2991-2019, 2019.
Broquet, G., Bréon, F.-M., Renault, E., Buchwitz, M., Reuter, M., Bovensmann, H., Chevallier, F., Wu, L., and Ciais, P.: The potential of satellite spectro-imagery for monitoring CO2 emissions from large cities, Atmos. Meas. Tech., 11, 681–708, https://doi.org/10.5194/amt-11-681-2018, 2018.
Chevallier, F., Viovy, N., Reichstein, M., and Ciais, P.: On the assignment
of prior errors in Bayesian inversions of CO2 surface fluxes, Geophys. Res. Lett., 33, L13802, https://doi.org/10.1029/2006GL026496, 2006.
Ciais, P., Paris, J. D., Marland, G., Peylin, P., Piao, S. L., Levin, I.,
Pregger, T., Scholz, Y., Friedrich, R., Rivier, L., Houwelling, S., and
Schulze, E. D.: The European carbon balance. Part 1: Fossil fuel emissions,
Glob. Change Biol., 16, 1395–1408, https://doi.org/10.1111/j.1365-2486.2009.02098.x, 2010.
Deng, A., Lauvaux, T., Davis, K. J., Gaudet, B. J., Miles, N., Richardson,
S. J., Wu, K., Sarmiento, D. P., Hardesty, R. M., Bonin, T. A., Brewer, W.
A., and Gurney, K. R.: Toward reduced transport errors in a high resolution
urban CO2 inversion system, Elementa (Wash. D.C.), 5, 20,
https://doi.org/10.1525/elementa.133, 2017.
Denier van der Gon, H. A. C., Hendriks, C., Kuenen, J., Segers, A., and
Visschedijk, A.: Description of current temporal emission patterns and
sensitivity of predicted AQ for temporal emission patterns, Report, TNO, Utrecht, 2011.
Djuricin, S., Pataki, D. E., and Xu, X.: A comparison of tracer methods for
quantifying CO2 sources in an urban region, J. Geophys. Res., 115, D11303, https://doi.org/10.1029/2009JD012236, 2010.
Fauser, P., Sørensen, P. B., Nielsen, M., Winther, M., Plejdrup, M. S.,
Hoffmann, L., Gyldenkærne, S., Mikkelsen, M. H., Albrektsen, R., Lyck,
E., Thomsen, M., Hjelgaard, K., and Nielsen, O.-K.: Monte Carlo (Tier 2)
uncertainty analysis of Danish Greenhouse gas emission inventory, Greenhouse
Gas Measurement and Management, 1, 145–160, https://doi.org/10.1080/20430779.2011.621949,
2011.
Fischer, M. L., Parazoo, N., Brophy, K., Cui, X., Jeong, S., Liu, J.,
Keeling, R., Taylor, T. E., Gurney, K., Oda, T., and Graven, H.: Simulating
estimation of California fossil fuel and biosphere carbon dioxide exchanges
combining in situ tower and satellite column observations, J. Geophys.
Res.-Atmos., 122, 3653–3671, https://doi.org/10.1002/2016jd025617, 2017.
Gerbig, C., Lin, J. C., Wofsy, S. C., Daube, B. C., Andrews, A. E.,
Stephens, B. B., Bakwin, P. S., and Grainger, C. A.: Toward constraining
regional-scale fluxes of CO2 with atmospheric observations over a
continent: 2. Analysis of COBRA data using a receptor-oriented framework, J.
Geophys. Res., 108, 4757, https://doi.org/10.1029/2003JD003770, 2003.
Göckede, M., Turner, D. P., Michalak, A. M., Vickers, D., and Law, B.
E.: Sensitivity of a subregional scale atmospheric inverse CO2 modeling framework to boundary conditions, J. Geophys. Res., 115, D24112,
https://doi.org/10.1029/2010JD014443, 2010.
Graven, H., Fischer, M. L., Lueker, T., Jeong, S., Guilderson, T. P.,
Keeling, R. F., Bambha, R., Brophy, K., Callahan, W., Cui, X., Frankenberg,
C., Gurney, K. R., LaFranchi, B. W., Lehman, S. J., Michelsen, H., Miller,
J. B., Newman, S., Paplawsky, W., Parazoo, N. C., Sloop, C., and Walker, S.
J.: Assessing fossil fuel CO2 emissions in California using atmospheric observations and models, Environ. Res. Lett., 13, 065007,
https://doi.org/10.1088/1748-9326/aabd43, 2018.
Gurney, K. R., Patarasuk, R., Liang, J., Song, Y., O'Keeffe, D., Rao, P., Whetstone, J. R., Duren, R. M., Eldering, A., and Miller, C.: The Hestia fossil fuel CO2 emissions data product for the Los Angeles megacity (Hestia-LA), Earth Syst. Sci. Data, 11, 1309–1335, https://doi.org/10.5194/essd-11-1309-2019, 2019.
He, W., van der Velde, I. R., Andrews, A. E., Sweeney, C., Miller, J., Tans, P., van der Laan-Luijkx, I. T., Nehrkorn, T., Mountain, M., Ju, W., Peters, W., and Chen, H.: CTDAS-Lagrange v1.0: a high-resolution data assimilation system for regional carbon dioxide observations, Geosci. Model Dev., 11, 3515–3536, https://doi.org/10.5194/gmd-11-3515-2018, 2018.
Hirth, L., Mühlenpfordt, J., and Bulkeley, M.: The ENTSO-E Transparency
Platform – A review of Europe's most ambitious electricity data platform,
Appl. Energ., 225, 1054–1067, https://doi.org/10.1016/j.apenergy.2018.04.048, 2018.
Hogue, S., Marland, E., Andres, R. J., Marland, G., and Woodard, D.:
Uncertainty in gridded CO2 emissions estimates, Earth's Future, 4, 225–239, https://doi.org/10.1002/2015EF000343, 2016.
Huijnen, V., Williams, J., van Weele, M., van Noije, T., Krol, M., Dentener, F., Segers, A., Houweling, S., Peters, W., de Laat, J., Boersma, F., Bergamaschi, P., van Velthoven, P., Le Sager, P., Eskes, H., Alkemade, F., Scheele, R., Nédélec, P., and Pätz, H.-W.: The global chemistry transport model TM5: description and evaluation of the tropospheric chemistry version 3.0, Geosci. Model Dev., 3, 445–473, https://doi.org/10.5194/gmd-3-445-2010, 2010.
Hutchins, M. G., Colby, J. D., Marland, G., and Marland, E.: A comparison of
five high-resolution spatially-explicit, fossil-fuel, carbon dioxide
emission inventories for the United States, Mitig. Adapt. Strat. Gl., 22,
947–972, https://doi.org/10.1007/s11027-016-9709-9, 2017.
IEA: World Energy Outlook 2008, International Energy Agency, Paris, 2008.
Jansen, B. I.: Vernieuwd emissiemodel houtkachels, TNO-rapport, TNO 2016 R10318, 28 pp., TNO, Delft, 2016.
Jun, P., Gillenwater, M., and Barbour, W.: CO2, CH4, and N2O emissions from transportation – water-borne navigation, in: Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories, Intergovernmental Panel on Climate Change, Paris, France, 71–92, 2000.
Kuenen, J. J. P., Visschedijk, A. J. H., Jozwicka, M., and Denier van der Gon, H. A. C.: TNO-MACC_II emission inventory; a multi-year (2003–2009) consistent high-resolution European emission inventory for air quality modelling, Atmos. Chem. Phys., 14, 10963–10976, https://doi.org/10.5194/acp-14-10963-2014, 2014.
Kuhlmann, G., Broquet, G., Marshall, J., Clément, V., Löscher, A., Meijer, Y., and Brunner, D.: Detectability of CO2 emission plumes of cities and power plants with the Copernicus Anthropogenic CO2 Monitoring (CO2M) mission, Atmos. Meas. Tech., 12, 6695–6719, https://doi.org/10.5194/amt-12-6695-2019, 2019.
LaFranchi, B. W., Pétron, G., Miller, J. B., Lehman, S. J., Andrews, A. E., Dlugokencky, E. J., Hall, B., Miller, B. R., Montzka, S. A., Neff, W., Novelli, P. C., Sweeney, C., Turnbull, J. C., Wolfe, D. E., Tans, P. P., Gurney, K. R., and Guilderson, T. P.: Constraints on emissions of carbon monoxide, methane, and a suite of hydrocarbons in the Colorado Front Range using observations of 14CO2, Atmos. Chem. Phys., 13, 11101–11120, https://doi.org/10.5194/acp-13-11101-2013, 2013.
Lauvaux, T., Miles, N. L., Richardson, S. J., Deng, A., Stauffer, D. R.,
Davis, K. J., Jacobson, G., Rella, C., Calonder, G. P., and Decola, P. L.:
Urban emissions of CO2 from Davos, Switzerland: The first real-time
monitoring system using an atmospheric inversion technique, J. Appl.
Meteorol. Clim., 52, 2654–2668, https://doi.org/10.1175/JAMC-D-13-038.1, 2013.
Lauvaux, T., Miles, N. L., Deng, A., Richardson, S. J., Cambaliza, M. O.,
Davis, K. J., Gaudet, B., Gurney, K. R., Huang, J., O'Keefe, D., Song, Y.,
Karion, A., Oda, T., Patarasuk, R., Razlivanov, I., Sarmiento, D., Shepson,
P., Sweeney, C., Turnbull, J., and Wu, K.: High-resolution atmospheric
inversion of urban CO2 emissions during the dormant season of the
Indianapolis Flux Experiment (INFLUX), J. Geophys. Res.-Atmos., 121,
5213–5236, https://doi.org/10.1002/2015jd024473, 2016.
Levin, I. and Karstens, U.: Inferring high-resolution fossil fuel CO2
records at continental sites from combined 14CO2 and CO
observations, Tellus B, 59, 245–250,
https://doi.org/10.1111/j.1600-0889.2006.00244.x, 2007.
Liander: Innovatie & Diensten: Open data, available at:
https://www.liander.nl/over-liander/innovatie/open-data/data, last access: February 2018.
Lin, J. C., Gerbig, C., Wofsy, S. C., Andrews, A. E., Daube, B. C., Davis,
K. J., and Grainger, C. A. C.: A near-field tool for simulating the upstream
influence of atmospheric observations: The Stochastic Time-Inverted
Lagrangian Transport (STILT) model, J. Geophys. Res., 108, 4493,
https://doi.org/10.1029/2002jd003161, 2003.
Lindenmaier, R., Dubey, M. K., Henderson, B. G., Butterfield, Z. T., Herman,
J. R., Rahn, T., and Lee, S. H.: Multiscale observations of CO2,
13CO2, and pollutants at Four Corners for emission verification
and attribution, P. Natl. Acad. Sci. USA, 111, 8386–8391, 2014.
Lopez, M., Schmidt, M., Delmotte, M., Colomb, A., Gros, V., Janssen, C., Lehman, S. J., Mondelain, D., Perrussel, O., Ramonet, M., Xueref-Remy, I., and Bousquet, P.: CO, NOx and 13CO2 as tracers for fossil fuel CO2: results from a pilot study in Paris during winter 2010, Atmos. Chem. Phys., 13, 7343–7358, https://doi.org/10.5194/acp-13-7343-2013
McKain, K., Wofsy, S. C., Nehrkorn, T., Eluszkiewicz, J., Ehleringer, J. R.,
and Stephens, B. B.: Assessment of ground-based atmospheric observations for
verification of greenhouse gas emissions from an urban region, P. Natl. Acad. Sci. USA, 109, 8423–8428, 2012.
Meirink, J. F., Bergamaschi, P., Frankenberg, C., d'Amelio, M. T. S.,
Dlugokencky, E. J., Gatti, L. V., Houweling, S., Miller, J. B.,
Röckmann, T., Villani, M. G., and Krol, M. C.: Four-dimensional
variational data assimilation for inverse modeling of atmospheric methane
emissions: Analysis of SCIAMACHY observations, J. Geophys. Res., 113, D17301,
https://doi.org/10.1029/2007jd009740, 2008.
Miller, J. B., Lehman, S. J., Montzka, S. A., Sweeney, C., Miller, B. R.,
Karion, A., Wolak, C., Dlugokencky, E. J., Southon, J., Turnbull, J. C., and
Tans, P. P.: Linking emissions of fossil fuel CO2 and other
anthropogenic trace gases using atmospheric 14CO2, J. Geophys.
Res., 117, D08302, https://doi.org/10.1029/2011jd017048, 2012.
Monni, S., Syri, S., and Savolainen, I.: Uncertainties in the Finnish
greenhouse gas emission inventory, Environ. Sci. Policy, 7, 87–98,
https://doi.org/10.1016/j.envsci.2004.01.002, 2004.
Mues, A., Kuenen, J., Hendriks, C., Manders, A., Segers, A., Scholz, Y., Hueglin, C., Builtjes, P., and Schaap, M.: Sensitivity of air pollution simulations with LOTOS-EUROS to the temporal distribution of anthropogenic emissions, Atmos. Chem. Phys., 14, 939–955, https://doi.org/10.5194/acp-14-939-2014, 2014.
Nakicenovic, N., Alcamo, J., Davis, G., De Vries, B., Fenhann, J., Gaffin,
S., Gregory, K., Grübler, A., Jung, T. Y., Kram, T., La Rovere, E. L.,
Michaelis, L., Mori, S., Morita, T., Pepper, W., Pitcher, H., Price, L.,
Riahi, K., Roehrl, A., Rogner, H.-H., Sankovski, A., Schlesinger, M.,
Shukla, P., Smith, S., Swart, R., Van Rooijen, S., Victor, N., and Dadi, Z.:
IPCC Special Report on Emissions Scenarios, edited by: Calvo, E., Chadwick, M., Ishiumi, Y., and Parikh, J., Cambridge University Press,
Cambridge, UK, 599 pp., 2000.
Nassar, R., Napier-Linton, L., Gurney, K. R., Andres, R. J., Oda, T., Vogel,
F. R., and Deng, F.: Improving the temporal and spatial distribution of
CO2 emissions from global fossil fuel emission data sets, J. Geophys.
Res.-Atmos., 118, 917–933, https://doi.org/10.1029/2012jd018196, 2013.
Nathan, B., Lauvaux, T., Turnbull, J., and Gurney, K.: Investigations into
the use of multi-species measurements for source apportionment of the
Indianapolis fossil fuel CO2 signal, Elementa, 6, 21, https://doi.org/10.1525/elementa.131, 2018.
Nehrkorn, T., Eluszkiewicz, J., Wofsy, S. C., Lin, J. C., Gerbig, C., Longo,
M., and Freitas, S.: Coupled weather research and forecasting-stochastic
time-inverted lagrangian transport (WRF-STILT) model, Meteorol. Atmos.
Phys., 107, 51–64, https://doi.org/10.1007/s00703-010-0068-x, 2010.
Netherlands PRTR: Netherlands Pollutant Release & Transfer Register:
http://www.emissieregistratie.nl/, last access: March 2018.
Palmer, P. I., O'Doherty, S., Allen, G., Bower, K., Bösch, H., Chipperfield, M. P., Connors, S., Dhomse, S., Feng, L., Finch, D. P., Gallagher, M. W., Gloor, E., Gonzi, S., Harris, N. R. P., Helfter, C., Humpage, N., Kerridge, B., Knappett, D., Jones, R. L., Le Breton, M., Lunt, M. F., Manning, A. J., Matthiesen, S., Muller, J. B. A., Mullinger, N., Nemitz, E., O'Shea, S., Parker, R. J., Percival, C. J., Pitt, J., Riddick, S. N., Rigby, M., Sembhi, H., Siddans, R., Skelton, R. L., Smith, P., Sonderfeld, H., Stanley, K., Stavert, A. R., Wenger, A., White, E., Wilson, C., and Young, D.: A measurement-based verification framework for UK greenhouse gas emissions: an overview of the Greenhouse gAs Uk and Global Emissions (GAUGE) project, Atmos. Chem. Phys., 18, 11753–11777, https://doi.org/10.5194/acp-18-11753-2018, 2018.
Peters, W., Miller, J. B., Whitaker, J., Denning, A. S., Hirsch, A., Krol,
M. C., Zupanski, D., Bruhwiler, L., and Tans, P. P.: An ensemble data
assimilation system to estimate CO2 surface fluxes from atmospheric
trace gas observations, J. Geophys. Res., 110, D24304,
https://doi.org/10.1029/2005JD006157, 2005.
Peters, W., Krol, M. C., Van der Werf, G. R., Houweling, S., Jones, C. D.,
Hughes, J., Schaefer, K., Masarie, K. A., Jacobson, A. R., Miller, J. B.,
Cho, C. H., Ramonet, M., Schmidt, M., Ciattaglia, L., Apadula, F., Heltai,
D., Meinhardt, F., Di Sarra, A. G., Piacentino, S., Sferlazzo, D., Aalto,
T., Hatakka, J., Ström, J., Haszpra, L., Meijer, H. A. J., Van der Laan,
S., Neubert, R. E. M., Jordan, A., Rodó, X., Morguí, J. A.,
Vermeulen, A. T., Popa, E., Rozanski, K., Zimnoch, M., Manning, A. C.,
Leuenberger, M., Uglietti, C., Dolman, A. J., Ciais, P., Heimann, M., and
Tans, P.: Seven years of recent European net terrestrial carbon dioxide
exchange constrained by atmospheric observations, Glob. Change Biol., 16,
1317–1337, https://doi.org/10.1111/j.1365-2486.2009.02078.x, 2010.
Ramírez, A. R., De Keizer, C., and Van der Sluijs, J. P.: Monte Carlo
analysis of uncertainties in the Netherlands Greenhouse Gas Emission
Inventory for 1990–2004, Copernicus Institute for Sustainable Development
and Innovation, Utrecht, Report no: NWS-E-2006-58, 111 pp., 2006.
Rao, P., Gurney, K. R., Patarasuk, R., Song, Y., Miller, C. E., Duren, R.
M., and Eldering, A.: Spatio-temporal Variations in on-road CO2 Emissions in the Los Angeles Megacity, AIMS Geosciences, 3, 239–267,
https://doi.org/10.3934/geosci.2017.2.239, 2017.
Raupach, M. R., Marland, G., Ciais, P., Le Quéré, C., Canadell, J.
G., Klepper, G., and Field, C. B.: Global and regional drivers of
accelerating CO2 emissions, P. Natl. Acad. Sci. USA, 104, 10288–10293, https://doi.org/10.1073/pnas.0700609104, 2007.
Rayner, P. J., Raupach, M. R., Paget, M., Peylin, P., and Koffi, E.: A new
global gridded data set of CO2 emissions from fossil fuel combustion:
Methodology and evaluation, J. Geophys. Res., 115, D19306, https://doi.org/10.1029/2009jd013439, 2010.
Sargent, M., Barrera, Y., Nehrkorn, T., Hutyra, L. R., Gately, C. K., Jones,
T., McKain, K., Sweeney, C., Hegarty, J., Hardiman, B., Wang, J. A., and
Wofsy, S. C.: Anthropogenic and biogenic CO2 fluxes in the Boston urban region, P. Natl. Acad. Sci. USA, 115, 7491–7496, https://doi.org/10.1073/pnas.1803715115, 2018.
Sauter, F., Van Zanten, M., Van der Swaluw, E., Aben, J., De Leeuw, F., and
Van Jaarsveld, H.: The OPS-model. Description of OPS 4.5.0, National
Institute for Public Health and the Environment (RIVM), Bilthoven, 115 pp., 2016.
Staufer, J., Broquet, G., Bréon, F.-M., Puygrenier, V., Chevallier, F., Xueref-Rémy, I., Dieudonné, E., Lopez, M., Schmidt, M., Ramonet, M., Perrussel, O., Lac, C., Wu, L., and Ciais, P.: The first 1-year-long estimate of the Paris region fossil fuel CO2 emissions based on atmospheric inversion, Atmos. Chem. Phys., 16, 14703–14726, https://doi.org/10.5194/acp-16-14703-2016, 2016.
Su, H., Yang, Z. L., Niu, G. Y., and Wilson, C. R.: Parameter estimation in
ensemble based snow data assimilation: A synthetic study, Adv. Water
Resour., 34, 407–416, https://doi.org/10.1016/j.advwatres.2010.12.002, 2011.
Super, I., Denier van der Gon, H. A. C., van der Molen, M. K., Sterk, H. A. M., Hensen, A., and Peters, W.: A multi-model approach to monitor emissions of CO2 and CO from an urban–industrial complex, Atmos. Chem. Phys., 17, 13297–13316, https://doi.org/10.5194/acp-17-13297-2017, 2017a.
Super, I., Denier van der Gon, H. A. C., Visschedijk, A. J. H., Moerman, M.
M., Chen, H., Van der Molen, M. K., and Peters, W.: Interpreting continuous
in-situ observations of carbon dioxide and carbon monoxide in the urban port
area of Rotterdam, Atmos. Pollut. Res., 8, 174–187,
https://doi.org/10.1016/j.apr.2016.08.008, 2017b.
Super, I., Dellaert, S. N. C., Visschedijk, A. J. H., and Denier van der Gon, H. A. C.: Uncertainty analysis of a European high-resolution emission inventory of CO2 and CO to support inverse modelling and network design, Atmos. Chem. Phys., 20, 1795–1816, https://doi.org/10.5194/acp-20-1795-2020, 2020.
Terrenoire, E., Bessagnet, B., Rouïl, L., Tognet, F., Pirovano, G., Létinois, L., Beauchamp, M., Colette, A., Thunis, P., Amann, M., and Menut, L.: High-resolution air quality simulation over Europe with the chemistry transport model CHIMERE, Geosci. Model Dev., 8, 21–42, https://doi.org/10.5194/gmd-8-21-2015, 2015.
Tolk, L. F., Meesters, A. G. C. A., Dolman, A. J., and Peters, W.: Modelling representation errors of atmospheric CO2 mixing ratios at a regional scale, Atmos. Chem. Phys., 8, 6587–6596, https://doi.org/10.5194/acp-8-6587-2008, 2008.
Turnbull, J. C., Miller, J. B., Lehman, S. J., Tans, P. P., Sparks, R. J.,
and Southon, J.: Comparison of 14CO2, CO, and SF6 as tracers for recently added fossil fuel CO2 in the atmosphere and implications for biological CO2 exchange, Geophys. Res. Lett., 33, L01817, https://doi.org/10.1029/2005GL024213, 2006.
Turnbull, J. C., Sweeney, C., Karion, A., Newberger, T., Lehman, S. J.,
Tans, P. P., Davis, K. J., Lauvaux, T., Miles, N. L., Richardson, S. J.,
Cambaliza, M. O., Shepson, P. B., Gurney, K., Patarasuk, R., and Razlivanov,
I.: Toward quantification and source sector identification of fossil fuel
CO2 emissions from an urban area: Results from the INFLUX experiment,
J. Geophys. Res.-Atmos., 120, 292–312, https://doi.org/10.1002/2014jd022555, 2015.
UNFCCC: Paris Agreement, UNFCCC, NY, United States, 2015.
van der Laan-Luijkx, I. T., van der Velde, I. R., van der Veen, E., Tsuruta, A., Stanislawska, K., Babenhauserheide, A., Zhang, H. F., Liu, Y., He, W., Chen, H., Masarie, K. A., Krol, M. C., and Peters, W.: The CarbonTracker Data Assimilation Shell (CTDAS) v1.0: implementation and global carbon balance 2001–2015, Geosci. Model Dev., 10, 2785–2800, https://doi.org/10.5194/gmd-10-2785-2017, 2017.
Van der Laan, S., Van der Laan-Luijkx, I. T., Zimmermann, L., Conen, F., and
Leuenberger, M.: Net CO2 surface emissions at Bern, Switzerland
inferred from ambient observations of CO2, δ(O2∕N2),
and 222Rn using a customized radon tracer inversion, J. Geophys.
Res.-Atmos., 119, 1580–1591, https://doi.org/10.1002/2013JD020307, 2014.
Van Jaarsveld, J. A.: The Operational Priority Substances model. Description
and validation of OPS-Pro 4.1, National Institute for Public Health and the
Environment, Bilthoven, Report no.: 500045001/2004, 156 pp., 2004.
Vogel, F. R., Thiruchittampalam, B., Theloke, J., Kretschmer, R., Gerbig,
C., Hammer, S., and Levin, I.: Can we evaluate a fine-grained emission model
using high-resolution atmospheric transport modelling and regional fossil
fuel CO2 observations?, Tellus B, 65, 18681, https://doi.org/10.3402/tellusb.v65i0.18681, 2013.
Wang, Y., Broquet, G., Ciais, P., Chevallier, F., Vogel, F., Wu, L., Yin, Y., Wang, R., and Tao, S.: Potential of European 14CO2 observation network to estimate the fossil fuel CO2 emissions via atmospheric inversions, Atmos. Chem. Phys., 18, 4229–4250, https://doi.org/10.5194/acp-18-4229-2018, 2018.
Whitaker, J. S. and Hamill, T. M.: Ensemble data assimilation without
perturbed observations, Mon. Weather Rev., 130, 1913–1924,
https://doi.org/10.1175/1520-0493(2002)130<1913:EDAWPO>2.0.CO;2, 2002.
Zhou, Y., and Gurney, K. R.: Spatial relationships of sector-specific fossil
fuel CO2 emissions in the United States, Global Biogeochem. Cy., 25, GB3002, https://doi.org/10.1029/2010gb003822, 2011.
Short summary
Understanding urban CO2 fluxes is increasingly important to support emission reduction policies. In this work we extended an existing framework for emission verification to increase its suitability for urban areas and source-sector-based decision-making by using a dynamic emission model. We find that the dynamic emission model provides a better understanding of emissions at small scales and their uncertainties. By including co-emitted species, emission can be related to specific source sectors.
Understanding urban CO2 fluxes is increasingly important to support emission reduction policies....
