Articles | Volume 13, issue 5
https://doi.org/10.5194/gmd-13-2451-2020
© 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-13-2451-2020
© 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
| 
27 May 2020
Development and technical paper |
| 27 May 2020
| 27 May 2020
Satellite-derived leaf area index and roughness length information for surface–atmosphere exchange modelling: a case study for reactive nitrogen deposition in north-western Europe using LOTOS-EUROS v2.0
Shelley C. van der Graaf
CORRESPONDING AUTHOR
Cluster Earth and Climate, Department of Earth Sciences, Faculty of
Science, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, the Netherlands
Richard Kranenburg
TNO, Climate Air and Sustainability, Utrecht, 3584 CB, the Netherlands
Arjo J. Segers
TNO, Climate Air and Sustainability, Utrecht, 3584 CB, the Netherlands
Martijn Schaap
TNO, Climate Air and Sustainability, Utrecht, 3584 CB, the Netherlands
Institute for Meteorology, Free University Berlin, 12165 Berlin,
Germany
Jan Willem Erisman
Cluster Earth and Climate, Department of Earth Sciences, Faculty of
Science, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, the Netherlands
Louis Bolk Institute, 3981 Bunnik, the Netherlands
Related authors
Ruben B. Schulte, Jordi Vilà-Guerau de Arellano, Susanna Rutledge-Jonker, Shelley van der Graaf, Jun Zhang, and Margreet C. van Zanten
Biogeosciences, 21, 557–574, https://doi.org/10.5194/bg-21-557-2024, https://doi.org/10.5194/bg-21-557-2024, 2024
Short summary
Short summary
We analyzed measurements with the aim of finding relations between the surface atmosphere exchange of NH3 and the CO2 uptake and transpiration by vegetation. We found a high correlation of daytime NH3 emissions with both latent heat flux and photosynthetically active radiation. Very few simultaneous measurements of NH3, CO2 fluxes and meteorological variables exist at sub-diurnal timescales. This study paves the way to finding more robust relations between the NH3 exchange flux and CO2 uptake.
Daan Swart, Jun Zhang, Shelley van der Graaf, Susanna Rutledge-Jonker, Arjan Hensen, Stijn Berkhout, Pascal Wintjen, René van der Hoff, Marty Haaima, Arnoud Frumau, Pim van den Bulk, Ruben Schulte, Margreet van Zanten, and Thomas van Goethem
Atmos. Meas. Tech., 16, 529–546, https://doi.org/10.5194/amt-16-529-2023, https://doi.org/10.5194/amt-16-529-2023, 2023
Short summary
Short summary
During a 5-week comparison campaign, we tested two set-ups to measure half hourly ammonia fluxes. The eddy covariance and flux gradient systems showed very similar results when the upwind terrain was both homogeneous and free of obstacles. We discuss the technical performance and practical limitations of both systems. Measurements from these instruments can facilitate the study of processes behind ammonia deposition, an important contributor to eutrophication and acidificationin natural areas.
Shelley van der Graaf, Enrico Dammers, Arjo Segers, Richard Kranenburg, Martijn Schaap, Mark W. Shephard, and Jan Willem Erisman
Atmos. Chem. Phys., 22, 951–972, https://doi.org/10.5194/acp-22-951-2022, https://doi.org/10.5194/acp-22-951-2022, 2022
Short summary
Short summary
CrIS NH3 satellite observations are assimilated into the LOTOS-EUROS model using two different methods. In the first method the data are used to fit spatially varying NH3 emission time factors. In the second method a local ensemble transform Kalman filter is used. Compared to in situ observations, combining both methods led to the most significant improvements in the modeled concentrations and deposition, illustrating the usefulness of CrIS NH3 to improve the spatiotemporal distribution of NH3.
Simeng Li, Enrico Dammers, Arjo Segers, and Jan Willem Erisman
EGUsphere, https://doi.org/10.5194/egusphere-2025-2826, https://doi.org/10.5194/egusphere-2025-2826, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Between 2019 and 2022, a notable reduction in livestock numbers has been observed on Schiermonnikoog, a small island in the north of the Netherlands. We have assessed ammonia emissions using real-world measurements on the island, demonstrated emission decrease, and proposed a network to improve emission monitoring.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
Short summary
Short summary
Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
Short summary
Short summary
Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Marc Guevara, Augustin Colette, Antoine Guion, Valentin Petiot, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Andrea Bolignano, Paula Camps, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilia D’Elia, Hugo Denier van der Gon, Gaël Descombes, John Douros, Hilde Fagerli, Yalda Fatahi, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Risto Hänninen, Kaj Hansen, Oriol Jorba, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Victor Lannuque, Frédérik Meleux, Agnes Nyíri, Yuliia Palamarchuk, Carlos Pérez García-Pando, Lennard Robertson, Felicita Russo, Arjo Segers, Mikhail Sofiev, Joanna Struzewska, Renske Timmermans, Andreas Uppstu, Alvaro Valdebenito, and Zhuyun Ye
EGUsphere, https://doi.org/10.5194/egusphere-2025-1287, https://doi.org/10.5194/egusphere-2025-1287, 2025
Short summary
Short summary
Air quality models require hourly emissions to accurately represent dispersion and physico-chemical processes in the atmosphere. Since emission inventories are typically provided at the annual level, emissions are downscaled to a refined temporal resolution using temporal profiles. This study quantifies the impact of using new anthropogenic temporal profiles on the performance of an European air quality multi-model ensemble. Overall, the findings indicate an improvement of the modelling results.
Ioannis Kioutsioukis, Christian Hogrefe, Paul A. Makar, Ummugulsun Alyuz, Jessy O. Bash, Roberto Bellasio, Roberto Bianconi, Tim Buttler, Olivia E. Clifton, Philippe Cheung, Alma Hodzic, Richard Kranenburg, Aurelia Lupascu, Kester Momoh, Juan Luis Perez-Camaño, John Pleim, Young-Hee Ryu, Robero San Jose, Donna Schwede, Ranjeet Sokhi, and Stefano Galmarini
EGUsphere, https://doi.org/10.5194/egusphere-2025-1091, https://doi.org/10.5194/egusphere-2025-1091, 2025
Short summary
Short summary
Deposition is a key in air quality modelling. An evaluation of the AQMEII4 models is performed prior to analysing the different deposition schemes in relation to the LULC used. Such analysis is unprecedented. Among the results, LULC masks have to be harmonised and up-to-date information used in place of outdated and too course masks. Alternatively LULC masks should be evaluated and intercom pared when multiple model results are analysed.
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data, 17, 1121–1152, https://doi.org/10.5194/essd-17-1121-2025, https://doi.org/10.5194/essd-17-1121-2025, 2025
Short summary
Short summary
This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
Paul A. Makar, Philip Cheung, Christian Hogrefe, Ayodeji Akingunola, Ummugulsum Alyuz, Jesse O. Bash, Michael D. Bell, Roberto Bellasio, Roberto Bianconi, Tim Butler, Hazel Cathcart, Olivia E. Clifton, Alma Hodzic, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Jason A. Lynch, Kester Momoh, Juan L. Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Thomas Scheuschner, Mark W. Shephard, Ranjeet S. Sokhi, and Stefano Galmarini
Atmos. Chem. Phys., 25, 3049–3107, https://doi.org/10.5194/acp-25-3049-2025, https://doi.org/10.5194/acp-25-3049-2025, 2025
Short summary
Short summary
The large range of sulfur and nitrogen deposition estimates from air quality models results in a large range of predicted impacts. We used models and deposition diagnostics to identify the processes controlling atmospheric sulfur and nitrogen deposition variability. Controlling factors included the uptake of gases and aerosols by hydrometeors, aerosol inorganic chemistry, particle dry deposition, ammonia bidirectional fluxes, gas deposition via plant cuticles and soil, and land use data.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Leon Geers, Ruud Janssen, Gudrun Thorkelsdottir, Jordi Vilà-Guerau de Arellano, and Martijn Schaap
EGUsphere, https://doi.org/10.5194/egusphere-2025-426, https://doi.org/10.5194/egusphere-2025-426, 2025
Short summary
Short summary
High-resolution data on reactive nitrogen deposition are needed to inform cost-effective policies. Here, we describe the implementation of a dry deposition module into a large eddy simulation code. With this model, we are able to represent the turbulent exchange of tracers at the hectometer resolution. The model calculates the dispersion and deposition of NOx and NH3 in great spatial detail, clearly showing the influence of local land use patterns.
Christian Hogrefe, Stefano Galmarini, Paul A. Makar, Ioannis Kioutsioukis, Olivia E. Clifton, Ummugulsum Alyuz, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Tim Butler, Philip Cheung, Alma Hodzic, Richard Kranenburg, Aurelia Lupascu, Kester Momoh, Juan Luis Perez-Camanyo, Jonathan E. Pleim, Young-Hee Ryu, Roberto San Jose, Martijn Schaap, Donna B. Schwede, and Ranjeet Sokhi
EGUsphere, https://doi.org/10.5194/egusphere-2025-225, https://doi.org/10.5194/egusphere-2025-225, 2025
Short summary
Short summary
Performed under the umbrella of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4), this study applies AQMEII4 diagnostic tools to better characterize how dry deposition removes pollutants from the atmosphere in regional-scale models. The results also strongly suggest that improvement and harmonization of the representation of land use in these models would serve the community in their future development efforts.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, Ivar R. van der Velde, and Ilse Aben
Atmos. Chem. Phys., 25, 555–574, https://doi.org/10.5194/acp-25-555-2025, https://doi.org/10.5194/acp-25-555-2025, 2025
Short summary
Short summary
The production of steel coincides with large emissions of greenhouse gases and air pollutants including carbon monoxide. European facilities are required to report their emissions, which are estimated using a variety of methods. We evaluate these estimates using carbon monoxide concentrations measured via satellite. We find generally good agreement between our values and those reported but also identify some uncertainties, showing that satellites can provide insights into these emissions.
Augustin Colette, Gaëlle Collin, François Besson, Etienne Blot, Vincent Guidard, Frederik Meleux, Adrien Royer, Valentin Petiot, Claire Miller, Oihana Fermond, Alizé Jeant, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Dene Bowdalo, Jorgen Brandt, Gino Briganti, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilia D’Elia, Massimo D’Isidoro, Hugo Denier van der Gon, Gaël Descombes, Enza Di Tomaso, John Douros, Jeronimo Escribano, Henk Eskes, Hilde Fagerli, Yalda Fatahi, Johannes Flemming, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Guido Guarnieri, Marc Guevara, Antoine Guion, Jonathan Guth, Risto Hänninen, Kaj Hansen, Ulas Im, Ruud Janssen, Marine Jeoffrion, Mathieu Joly, Luke Jones, Oriol Jorba, Evgeni Kadantsev, Michael Kahnert, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Anne Caroline Lange, Joachim Langner, Victor Lannuque, Francesca Macchia, Astrid Manders, Mihaela Mircea, Agnes Nyiri, Miriam Olid, Carlos Pérez García-Pando, Yuliia Palamarchuk, Antonio Piersanti, Blandine Raux, Miha Razinger, Lennard Robertson, Arjo Segers, Martijn Schaap, Pilvi Siljamo, David Simpson, Mikhail Sofiev, Anders Stangel, Joanna Struzewska, Carles Tena, Renske Timmermans, Thanos Tsikerdekis, Svetlana Tsyro, Svyatoslav Tyuryakov, Anthony Ung, Andreas Uppstu, Alvaro Valdebenito, Peter van Velthoven, Lina Vitali, Zhuyun Ye, Vincent-Henri Peuch, and Laurence Rouïl
EGUsphere, https://doi.org/10.5194/egusphere-2024-3744, https://doi.org/10.5194/egusphere-2024-3744, 2024
Short summary
Short summary
The Copernicus Atmosphere Monitoring Service – Regional Production delivers daily forecasts, analyses, and reanalyses of air quality in Europe. The Service relies on a distributed modelling production by eleven leading European modelling teams following stringent requirements with an operational design which has no equivalent in the world. All the products are full, free, open and quality assured and disseminated with a high level of reliability.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
Short summary
Short summary
This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
Short summary
Short summary
HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Ruben B. Schulte, Jordi Vilà-Guerau de Arellano, Susanna Rutledge-Jonker, Shelley van der Graaf, Jun Zhang, and Margreet C. van Zanten
Biogeosciences, 21, 557–574, https://doi.org/10.5194/bg-21-557-2024, https://doi.org/10.5194/bg-21-557-2024, 2024
Short summary
Short summary
We analyzed measurements with the aim of finding relations between the surface atmosphere exchange of NH3 and the CO2 uptake and transpiration by vegetation. We found a high correlation of daytime NH3 emissions with both latent heat flux and photosynthetically active radiation. Very few simultaneous measurements of NH3, CO2 fluxes and meteorological variables exist at sub-diurnal timescales. This study paves the way to finding more robust relations between the NH3 exchange flux and CO2 uptake.
Lea Fink, Matthias Karl, Volker Matthias, Sonia Oppo, Richard Kranenburg, Jeroen Kuenen, Sara Jutterström, Jana Moldanova, Elisa Majamäki, and Jukka-Pekka Jalkanen
Atmos. Chem. Phys., 23, 10163–10189, https://doi.org/10.5194/acp-23-10163-2023, https://doi.org/10.5194/acp-23-10163-2023, 2023
Short summary
Short summary
The Mediterranean Sea is a heavily trafficked shipping area, and air quality monitoring stations in numerous cities along the Mediterranean coast have detected high levels of air pollutants originating from shipping emissions. The current study investigates how existing restrictions on shipping-related emissions to the atmosphere ensure compliance with legislation. Focus was laid on fine particles and particle species, which were simulated with five different chemical transport models.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
Short summary
Short summary
This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Lea Fink, Matthias Karl, Volker Matthias, Sonia Oppo, Richard Kranenburg, Jeroen Kuenen, Jana Moldanova, Sara Jutterström, Jukka-Pekka Jalkanen, and Elisa Majamäki
Atmos. Chem. Phys., 23, 1825–1862, https://doi.org/10.5194/acp-23-1825-2023, https://doi.org/10.5194/acp-23-1825-2023, 2023
Short summary
Short summary
Potential ship impact on air pollution in the Mediterranean Sea was simulated with five chemistry transport models. An evaluation of the results for NO2 and O3 air concentrations and dry deposition is presented. Emission data, modeled year and domain were the same. Model run outputs were compared to measurements from background stations. We focused on comparing model outputs regarding the concentration of regulatory pollutants and the relative ship impact on total air pollution concentrations.
Daan Swart, Jun Zhang, Shelley van der Graaf, Susanna Rutledge-Jonker, Arjan Hensen, Stijn Berkhout, Pascal Wintjen, René van der Hoff, Marty Haaima, Arnoud Frumau, Pim van den Bulk, Ruben Schulte, Margreet van Zanten, and Thomas van Goethem
Atmos. Meas. Tech., 16, 529–546, https://doi.org/10.5194/amt-16-529-2023, https://doi.org/10.5194/amt-16-529-2023, 2023
Short summary
Short summary
During a 5-week comparison campaign, we tested two set-ups to measure half hourly ammonia fluxes. The eddy covariance and flux gradient systems showed very similar results when the upwind terrain was both homogeneous and free of obstacles. We discuss the technical performance and practical limitations of both systems. Measurements from these instruments can facilitate the study of processes behind ammonia deposition, an important contributor to eutrophication and acidificationin natural areas.
Jianbing Jin, Bas Henzing, and Arjo Segers
Atmos. Chem. Phys., 23, 1641–1660, https://doi.org/10.5194/acp-23-1641-2023, https://doi.org/10.5194/acp-23-1641-2023, 2023
Short summary
Short summary
Aerosol models and satellite retrieval algorithms rely on different aerosol size assumptions. In practice, differences between simulations and observations do not always reflect the difference in aerosol amount. To avoid inconsistencies, we designed a hybrid assimilation approach. Different from a standard aerosol optical depth (AOD) assimilation that directly assimilates AODs, the hybrid one estimates aerosol size parameters by assimilating Ängström observations before assimilating the AODs.
Pascal Wintjen, Frederik Schrader, Martijn Schaap, Burkhard Beudert, Richard Kranenburg, and Christian Brümmer
Biogeosciences, 19, 5287–5311, https://doi.org/10.5194/bg-19-5287-2022, https://doi.org/10.5194/bg-19-5287-2022, 2022
Short summary
Short summary
For the first time, we compared four methods for estimating the annual dry deposition of total reactive nitrogen into a low-polluted forest ecosystem. In our analysis, we used 2.5 years of flux measurements, an in situ modeling approach, a large-scale chemical transport model (CTM), and canopy budget models. Annual nitrogen dry deposition budgets ranged between 4.3 and 6.7 kg N ha−1 a−1, depending on the applied method.
Li Fang, Jianbing Jin, Arjo Segers, Hai Xiang Lin, Mijie Pang, Cong Xiao, Tuo Deng, and Hong Liao
Geosci. Model Dev., 15, 7791–7807, https://doi.org/10.5194/gmd-15-7791-2022, https://doi.org/10.5194/gmd-15-7791-2022, 2022
Short summary
Short summary
This study proposes a regional feature selection-based machine learning system to predict short-term air quality in China. The system has a tool that can figure out the importance of input data for better prediction. It provides large-scale air quality prediction that exhibits improved interpretability, fewer training costs, and higher accuracy compared with a standard machine learning system. It can act as an early warning for citizens and reduce exposure to PM2.5 and other air pollutants.
Peter Bergamaschi, Arjo Segers, Dominik Brunner, Jean-Matthieu Haussaire, Stephan Henne, Michel Ramonet, Tim Arnold, Tobias Biermann, Huilin Chen, Sebastien Conil, Marc Delmotte, Grant Forster, Arnoud Frumau, Dagmar Kubistin, Xin Lan, Markus Leuenberger, Matthias Lindauer, Morgan Lopez, Giovanni Manca, Jennifer Müller-Williams, Simon O'Doherty, Bert Scheeren, Martin Steinbacher, Pamela Trisolino, Gabriela Vítková, and Camille Yver Kwok
Atmos. Chem. Phys., 22, 13243–13268, https://doi.org/10.5194/acp-22-13243-2022, https://doi.org/10.5194/acp-22-13243-2022, 2022
Short summary
Short summary
We present a novel high-resolution inverse modelling system, "FLEXVAR", and its application for the inverse modelling of European CH4 emissions in 2018. The new system combines a high spatial resolution of 7 km x 7 km with a variational data assimilation technique, which allows CH4 emissions to be optimized from individual model grid cells. The high resolution allows the observations to be better reproduced, while the derived emissions show overall good consistency with two existing models.
Sudhanshu Pandey, Sander Houweling, and Arjo Segers
Geosci. Model Dev., 15, 4555–4567, https://doi.org/10.5194/gmd-15-4555-2022, https://doi.org/10.5194/gmd-15-4555-2022, 2022
Short summary
Short summary
Inversions are used to calculate methane emissions using atmospheric mole-fraction measurements. Multidecadal inversions are needed to extract information from the long measurement records of methane. However, multidecadal inversion computations can take months to finish. Here, we demonstrate an order of magnitude improvement in wall clock time for an iterative multidecadal inversion by physical parallelization of chemical transport model.
Jianbing Jin, Mijie Pang, Arjo Segers, Wei Han, Li Fang, Baojie Li, Haochuan Feng, Hai Xiang Lin, and Hong Liao
Atmos. Chem. Phys., 22, 6393–6410, https://doi.org/10.5194/acp-22-6393-2022, https://doi.org/10.5194/acp-22-6393-2022, 2022
Short summary
Short summary
Super dust storms reappeared in East Asia last spring after being absent for one and a half decades. Accurate simulation of such super sandstorms is valuable, but challenging due to imperfect emissions. In this study, the emissions of these dust storms are estimated by assimilating multiple observations. The results reveal that emissions originated from both China and Mongolia. However, for northern China, long-distance transport from Mongolia contributes much more dust than Chinese deserts.
Christian Brümmer, Jeremy J. Rüffer, Jean-Pierre Delorme, Pascal Wintjen, Frederik Schrader, Burkhard Beudert, Martijn Schaap, and Christof Ammann
Earth Syst. Sci. Data, 14, 743–761, https://doi.org/10.5194/essd-14-743-2022, https://doi.org/10.5194/essd-14-743-2022, 2022
Short summary
Short summary
Field campaigns were carried out to investigate the biosphere–atmosphere exchange of selected reactive nitrogen compounds over different land surfaces using two different analytical devices for ammonia and total reactive nitrogen. The datasets improve our understanding of the temporal variability of surface–atmosphere exchange in different ecosystems, thereby providing validation opportunities for inferential models simulating the exchange of reactive nitrogen.
Pascal Wintjen, Frederik Schrader, Martijn Schaap, Burkhard Beudert, and Christian Brümmer
Biogeosciences, 19, 389–413, https://doi.org/10.5194/bg-19-389-2022, https://doi.org/10.5194/bg-19-389-2022, 2022
Short summary
Short summary
Fluxes of total reactive nitrogen (∑Nr) over a low polluted forest were analyzed with regard to their temporal dynamics. Mostly deposition was observed with median fluxes ranging from −15 to −5 ng N m−2 s−1, corresponding to a range of deposition velocities from 0.2 to 0.5 cm s−1. While seasonally changing contributions of NH3 and NOx to the ∑Nr signal were found, we estimate an annual total N deposition (dry+wet) of 12.2 and 10.9 kg N ha−1 a−1 in the 2 years of observation.
Shelley van der Graaf, Enrico Dammers, Arjo Segers, Richard Kranenburg, Martijn Schaap, Mark W. Shephard, and Jan Willem Erisman
Atmos. Chem. Phys., 22, 951–972, https://doi.org/10.5194/acp-22-951-2022, https://doi.org/10.5194/acp-22-951-2022, 2022
Short summary
Short summary
CrIS NH3 satellite observations are assimilated into the LOTOS-EUROS model using two different methods. In the first method the data are used to fit spatially varying NH3 emission time factors. In the second method a local ensemble transform Kalman filter is used. Compared to in situ observations, combining both methods led to the most significant improvements in the modeled concentrations and deposition, illustrating the usefulness of CrIS NH3 to improve the spatiotemporal distribution of NH3.
Vilma Kangasaho, Aki Tsuruta, Leif Backman, Pyry Mäkinen, Sander Houweling, Arjo Segers, Maarten Krol, Ed Dlugokencky, Sylvia Michel, James White, and Tuula Aalto
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-843, https://doi.org/10.5194/acp-2021-843, 2021
Revised manuscript not accepted
Short summary
Short summary
Understanding the composition of carbon isotopes can help to better understand the changes in methane budgets. This study investigates how methane sources affect the seasonal cycle of the methane carbon-13 isotope during 2000–2012 using an atmospheric transport model. We found that emissions from both anthropogenic and natural sources contribute. The findings raise a need to revise the magnitudes, proportion, and seasonal cycles of anthropogenic sources and northern wetland emissions.
Stefano Galmarini, Paul Makar, Olivia E. Clifton, Christian Hogrefe, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Tim Butler, Jason Ducker, Johannes Flemming, Alma Hodzic, Christopher D. Holmes, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Juan Luis Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Sam Silva, and Ralf Wolke
Atmos. Chem. Phys., 21, 15663–15697, https://doi.org/10.5194/acp-21-15663-2021, https://doi.org/10.5194/acp-21-15663-2021, 2021
Short summary
Short summary
This technical note presents the research protocols for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This initiative has three goals: (i) to define the state of wet and dry deposition in regional models, (ii) to evaluate how dry deposition influences air concentration and flux predictions, and (iii) to identify the causes for prediction differences. The evaluation compares LULC-specific dry deposition and effective conductances and fluxes.
Jianbing Jin, Arjo Segers, Hai Xiang Lin, Bas Henzing, Xiaohui Wang, Arnold Heemink, and Hong Liao
Geosci. Model Dev., 14, 5607–5622, https://doi.org/10.5194/gmd-14-5607-2021, https://doi.org/10.5194/gmd-14-5607-2021, 2021
Short summary
Short summary
When discussing the accuracy of a dust forecast, the shape and position of the plume as well as the intensity are key elements. The position forecast determines which locations will be affected, while the intensity only describes the actual dust level. A dust forecast with position misfit directly results in incorrect timing profiles of dust loads. In this paper, an image-morphing-based data assimilation is designed for realigning a simulated dust plume to correct for the position error.
Ioanna Skoulidou, Maria-Elissavet Koukouli, Astrid Manders, Arjo Segers, Dimitris Karagkiozidis, Myrto Gratsea, Dimitris Balis, Alkiviadis Bais, Evangelos Gerasopoulos, Trisevgeni Stavrakou, Jos van Geffen, Henk Eskes, and Andreas Richter
Atmos. Chem. Phys., 21, 5269–5288, https://doi.org/10.5194/acp-21-5269-2021, https://doi.org/10.5194/acp-21-5269-2021, 2021
Short summary
Short summary
The performance of LOTOS-EUROS v2.2.001 regional chemical transport model NO2 simulations is investigated over Greece from June to December 2018. Comparison with in situ NO2 measurements shows a spatial correlation coefficient of 0.86, while the model underestimates the concentrations mostly during daytime (12 to 15:00 local time). Further, the simulated tropospheric NO2 columns are evaluated against ground-based MAX-DOAS NO2 measurements and S5P/TROPOMI observations for July and December 2018.
Maria-Elissavet Koukouli, Ioanna Skoulidou, Andreas Karavias, Isaak Parcharidis, Dimitris Balis, Astrid Manders, Arjo Segers, Henk Eskes, and Jos van Geffen
Atmos. Chem. Phys., 21, 1759–1774, https://doi.org/10.5194/acp-21-1759-2021, https://doi.org/10.5194/acp-21-1759-2021, 2021
Short summary
Short summary
In recent years, satellite observations have contributed to monitoring air quality. During the first COVID-19 lockdown, lower levels of nitrogen dioxide were observed over Greece by S5P/TROPOMI for March and April 2020 (than the preceding year) due to decreased transport emissions. Taking meteorology into account, using LOTOS-EUROS CTM simulations, the resulting decline due to the lockdown was estimated to range between 0 % and −37 % for the five largest Greek cities, with an average of ~ −10 %.
Xinrui Ge, Martijn Schaap, Richard Kranenburg, Arjo Segers, Gert Jan Reinds, Hans Kros, and Wim de Vries
Atmos. Chem. Phys., 20, 16055–16087, https://doi.org/10.5194/acp-20-16055-2020, https://doi.org/10.5194/acp-20-16055-2020, 2020
Short summary
Short summary
This article is about improving the modeling of agricultural ammonia emissions. By considering land use, meteorology and agricultural practices, ammonia emission totals officially reported by countries are distributed in space and time. We illustrated the first step for a better understanding of the variability of ammonia emission, with the possibility of being applied at a European scale, which is of great significance for ammonia budget research and future policy-making.
Jianbing Jin, Arjo Segers, Hong Liao, Arnold Heemink, Richard Kranenburg, and Hai Xiang Lin
Atmos. Chem. Phys., 20, 15207–15225, https://doi.org/10.5194/acp-20-15207-2020, https://doi.org/10.5194/acp-20-15207-2020, 2020
Short summary
Short summary
Data assimilation provides a powerful tool to estimate emission inventories by feeding observations. This emission inversion relies on the correct assumption about the emission uncertainty, which describes the potential spatiotemporal spreads of sources. However, an unrepresentative uncertainty is unavoidable. Especially in the complex dust emission, the uncertainties can hardly all be taken into account. This study reports how adjoint can be used to detect errors in the emission uncertainty.
Emmanuele Russo, Silje Lund Sørland, Ingo Kirchner, Martijn Schaap, Christoph C. Raible, and Ulrich Cubasch
Geosci. Model Dev., 13, 5779–5797, https://doi.org/10.5194/gmd-13-5779-2020, https://doi.org/10.5194/gmd-13-5779-2020, 2020
Short summary
Short summary
The parameter space of the COSMO-CLM RCM is investigated for the Central Asia CORDEX domain using a perturbed physics ensemble (PPE) with different parameter values. Results show that only a subset of model parameters presents relevant changes in model performance and these changes depend on the considered region and variable: objective calibration methods are highly necessary in this case. Additionally, the results suggest the need for calibrating an RCM when targeting different domains.
Cited articles
Abida, R., Attié, J.-L., El Amraoui, L., Ricaud, P., Lahoz, W., Eskes, H., Segers, A., Curier, L., de Haan, J., Kujanpää, J., Nijhuis, A. O., Tamminen, J., Timmermans, R., and Veefkind, P.: Impact of spaceborne carbon monoxide observations from the S-5P platform on tropospheric composition analyses and forecasts, Atmos. Chem. Phys., 17, 1081–1103, https://doi.org/10.5194/acp-17-1081-2017, 2017.
Ammann, C.: FLUXNET2015 CH-Oe1 Oensingen grassland, 2002–2008, Dataset, https://doi.org/10.18140/FLX/1440135, 2016.
Banzhaf, S., Schaap, M., Kerschbaumer, A., Reimer, E., Stern, R., Van Der
Swaluw, E., and Builtjes, P.: Implementation and evaluation of pH-dependent
cloud chemistry and wet deposition in the chemical transport model
REM-Calgrid, Atmos. Environ., 49, 378–390, 2012.
Bauer, S. E., Tsigaridis, K., and Miller, R.: Significant atmospheric
aerosol pollution caused by world food cultivation, Geophys. Res. Lett., 43,
5394–5400, 2016.
Behera, S. N., Sharma, M., Aneja, V. P., and Balasubramanian, R.: Ammonia in
the atmosphere: a review on emission sources, atmospheric chemistry and
deposition on terrestrial bodies, Environ. Sci. Pollut.
Res., 20, 8092–8131, 2013.
Bernhofer, C., Grünwald, T., Moderow, U., Hehn, M., Eichelmann, U., Prasse, H., and Postel, U.: FLUXNET2015 DE-Akm Anklam, 2009–2014, Dataset, https://doi.org/10.18140/FLX/1440213, 2016a.
Bernhofer, C., Grünwald, T., Moderow, U., Hehn, M., Eichelmann, U., and Prasse H.: FLUXNET2015 DE-Gri Grillenburg, 2004–2014, Dataset, https://doi.org/10.18140/FLX/1440147, 2016b.
Bernhofer, C., Grünwald, T., Moderow, U., Hehn, M., Eichelmann, U., and Prasse, H.: FLUXNET2015 DE-Kli Klingenberg, 2004–2014, Dataset, https://doi.org/10.18140/FLX/1440147, 2016c.
Bernhofer, C., Grünwald, T., Moderow, U., Hehn, M., Eichelmann, U., and Prasse, H.: FLUXNET2015 DE-Obe Oberbärenburg, 2008–2014, Dataset, https://doi.org/10.18140/FLX/1440151, 2016d.
Bernhofer, C., Grünwald, T., Moderow, U., Hehn, M., Eichelmann, U., and Prasse, H.: FLUXNET2015 DE-Tha Tharandt, 1996–2014, Dataset, https://doi.org/10.18140/FLX/1440152, 2016e.
Berveiller, D., Delpierre, N., Dufrêne, E., Pontailler, J. Y., Vanbostal, L., Janvier, B., Mottet, L., and Cristinacce, K.: FLUXNET2015 FR-Fon Fontainebleau-Barbeau, 2005–2014, Dataset, https://doi.org/10.18140/FLX/1440161, 2016.
Bobbink, R., Hicks, K., Galloway, J., Spranger, T., Alkemade, R., Ashmore,
M., Bustamante, M., Cinderby, S., Davidson, E., and Dentener, F.: Global
assessment of nitrogen deposition effects on terrestrial plant diversity: a
synthesis, Ecol. Appl., 20, 30–59, 2010a.
Bobbink, R., Hicks, K., Galloway, J., Spranger, T., Alkemade, R., Ashmore,
M., Bustamante, M., Cinderby, S., Davidson, E., Dentener, F., Emmett, B.,
Erisman, J. W., Fenn, M., Gilliam, F., Nordin, A., Pardo, L., and De Vries,
W.: Global assessment of nitrogen deposition effects on terrestrial plant
diversity: a synthesis, Ecol. Appl., 20, 30–59, https://doi.org/10.1890/08-1140.1, 2010b.
Bolle, H. and Streckenbach, B.: Flux estimates from remote sensing, The
Echival Field Experiment in a Desertification Threatened Area (EFEDA), final
report, 406–424, 1993.
Brümmer, C., Lucas-Moffat, A. M., Herbst, M., and Kolle, O.: FLUXNET2015 DE-Geb Gebesee, 2001–2014, Dataset, https://doi.org/10.18140/FLX/1440146, 2016.
Brutsaert, W.: Evaporation into the atmosphere: theory, history and
applications, Springer Science & Business Media, 2013.
Businger, J. A., Wyngaard, J. C., Izumi, Y., and Bradley, E. F.:
Flux-profile relationships in the atmospheric surface layer, J.
Atmos. Sci., 28, 181–189, 1971.
Butterbach-Bahl, K., Nemitz, E., Zaehle, S., Billen, G., Boeckx, P., Erisman, J. W., Garnier, J., Upstill-Goddard, R., Kreuzer, M., and Oenema, O.: Nitrogen as a threat to the European greenhouse gas balance, in: The European nitrogen assessment: sources, effects and policy perspectives, Cambridge University Press, 434–462, 2011.
Claussen, M.: Area-averaging of surface fluxes in a neutrally stratified,
horizontally inhomogeneous atmospheric boundary-layer, Atmos. Environ.,
24, 1349–1360, 1990.
Colette, A., Andersson, C., Manders, A., Mar, K., Mircea, M., Pay, M.-T., Raffort, V., Tsyro, S., Cuvelier, C., Adani, M., Bessagnet, B., Bergström, R., Briganti, G., Butler, T., Cappelletti, A., Couvidat, F., D'Isidoro, M., Doumbia, T., Fagerli, H., Granier, C., Heyes, C., Klimont, Z., Ojha, N., Otero, N., Schaap, M., Sindelarova, K., Stegehuis, A. I., Roustan, Y., Vautard, R., van Meijgaard, E., Vivanco, M. G., and Wind, P.: EURODELTA-Trends, a multi-model experiment of air quality hindcast in Europe over 1990–2010, Geosci. Model Dev., 10, 3255–3276, https://doi.org/10.5194/gmd-10-3255-2017, 2017.
Curier, R., Kranenburg, R., Segers, A., Timmermans, R., and Schaap, M.:
Synergistic use of OMI NO2 tropospheric columns and LOTOS–EUROS to evaluate
the NOx emission trends across Europe, Remote Sens. Environ., 149, 58–69,
2014.
Dammers, E., McLinden, C. A., Griffin, D., Shephard, M. W., Van Der Graaf, S., Lutsch, E., Schaap, M., Gainairu-Matz, Y., Fioletov, V., Van Damme, M., Whitburn, S., Clarisse, L., Cady-Pereira, K., Clerbaux, C., Coheur, P. F., and Erisman, J. W.: NH3 emissions from large point sources derived from CrIS and IASI satellite observations, Atmos. Chem. Phys., 19, 12261–12293, https://doi.org/10.5194/acp-19-12261-2019, 2019.
Davi, H., Soudani, K., Deckx, T., Dufrene, E., Le Dantec, V., and Francois,
C.: Estimation of forest leaf area index from SPOT imagery using NDVI
distribution over forest stands, Int. J. Remote Sens., 27, 885–902, 2006.
De Ligne, A., Manise, T., Moureaux, C., Aubinet, M., and Heinesch, B.: FLUXNET2015 BE-Lon Lonzee, 2004–2014, Dataset, https://doi.org/10.18140/FLX/1440129, 2016a.
De Ligne, A., Manise, T., Heinesch, B., Aubinet, M., and Vincke, C.: FLUXNET2015 BE-Vie Vielsalm, 1996–2014, Dataset, https://doi.org/10.18140/FLX/1440130, 2016b.
Didan, K.: MYD13A3 MODIS/Aqua Vegetation Indices Monthly L3 Global 1 km SIN
Grid V006, NASA EOSDIS LP DAAC, https://doi.org/10.5067/MODIS/MYD13A3.006, 2015.
Dolman, H., Hendriks, D., Parmentier, F. J., Marchesini, L. B., Dean, J., and van Huissteden, K.: FLUXNET2015 NL-Hor Horstermeer, 2004–2011, Dataset, https://doi.org/10.18140/FLX/1440177, 2016.
Dušek, J., Janouš, D., and Pavelka, M.: FLUXNET2015 CZ-wet Trebon (CZECHWET), 2006–2014, Dataset, https://doi.org/10.18140/FLX/1440145, 2016.
Emberson, L., Simpson, D., Tuovinen, J., Ashmore, M., and Cambridge, H.:
Towards a model of ozone deposition and stomatal uptake over Europe, EMEP
MSC-W Note, 6, 1–57, 2000.
EMEP: The European Monitoring and Evaluation Programme EMEP Status Report,
2016.
Erisman, J. and Schaap, M.: The need for ammonia abatement with respect to
secondary PM reductions in Europe, Environ. Pollut., 129, 159–163, 2004.
Erisman, J. W., Van Pul, A., and Wyers, P.: Parametrization of surface
resistance for the quantification of atmospheric deposition of acidifying
pollutants and ozone, Atmos. Environ., 28, 2595–2607, 1994.
Erisman, J. W., Galloway, J., Seitzinger, S., Bleeker, A., and
Butterbach-Bahl, K.: Reactive nitrogen in the environment and its effect on
climate change, Curr. Opin. Env. Sust., 3, 281–290, 2011.
European Environmental Agency: CLC2012 Addendum to CLC2006 Technical
Guidelines, EEA Report, 2014.
European Environmental Agency: Airbase dataset,
available at: http://discomap.eea.europa.eu (last access: 1 March 2020), 2019.
Fang, H., Wei, S., and Liang, S.: Validation of MODIS and CYCLOPES LAI
products using global field measurement data, Remote Sens. Environ., 119,
43–54, 2012.
Flechard, C. R., Nemitz, E., Smith, R. I., Fowler, D., Vermeulen, A. T., Bleeker, A., Erisman, J. W., Simpson, D., Zhang, L., Tang, Y. S., and Sutton, M. A.: Dry deposition of reactive nitrogen to European ecosystems: a comparison of inferential models across the NitroEurope network, Atmos. Chem. Phys., 11, 2703–2728, https://doi.org/10.5194/acp-11-2703-2011, 2011.
Flechard, C., Massad, R.-S., Loubet, B., Personne, E., Simpson, D., Bash,
J., Cooter, E., Nemitz, E., and Sutton, M.: Advances in understanding,
models and parameterizations of biosphere-atmosphere ammonia exchange, in:
Review and Integration of Biosphere-Atmosphere Modelling of Reactive Trace
Gases and Volatile Aerosols, Springer, 11–84, 2013.
Flechard, C. R., Ibrom, A., Skiba, U. M., de Vries, W., van Oijen, M., Cameron, D. R., Dise, N. B., Korhonen, J. F. J., Buchmann, N., Legout, A., Simpson, D., Sanz, M. J., Aubinet, M., Loustau, D., Montagnani, L., Neirynck, J., Janssens, I. A., Pihlatie, M., Kiese, R., Siemens, J., Francez, A.-J., Augustin, J., Varlagin, A., Olejnik, J., Juszczak, R., Aurela, M., Berveiller, D., Chojnicki, B. H., Dämmgen, U., Delpierre, N., Djuricic, V., Drewer, J., Dufrêne, E., Eugster, W., Fauvel, Y., Fowler, D., Frumau, A., Granier, A., Gross, P., Hamon, Y., Helfter, C., Hensen, A., Horváth, L., Kitzler, B., Kruijt, B., Kutsch, W. L., Lobo-do-Vale, R., Lohila, A., Longdoz, B., Marek, M. V., Matteucci, G., Mitosinkova, M., Moreaux, V., Neftel, A., Ourcival, J.-M., Pilegaard, K., Pita, G., Sanz, F., Schjoerring, J. K., Sebastià, M.-T., Tang, Y. S., Uggerud, H., Urbaniak, M., van Dijk, N., Vesala, T., Vidic, S., Vincke, C., Weidinger, T., Zechmeister-Boltenstern, S., Butterbach-Bahl, K., Nemitz, E., and Sutton, M. A.: Carbon–nitrogen interactions in European forests and semi-natural vegetation – Part 1: Fluxes and budgets of carbon, nitrogen and greenhouse gases from ecosystem monitoring and modelling, Biogeosciences, 17, 1583–1620, https://doi.org/10.5194/bg-17-1583-2020, 2020.
Fowler, D., Steadman, C. E., Stevenson, D., Coyle, M., Rees, R. M., Skiba, U. M., Sutton, M. A., Cape, J. N., Dore, A. J., Vieno, M., Simpson, D., Zaehle, S., Stocker, B. D., Rinaldi, M., Facchini, M. C., Flechard, C. R., Nemitz, E., Twigg, M., Erisman, J. W., Butterbach-Bahl, K., and Galloway, J. N.: Effects of global change during the 21st century on the nitrogen cycle, Atmos. Chem. Phys., 15, 13849–13893, https://doi.org/10.5194/acp-15-13849-2015, 2015.
Gallagher, M., Nemitz, E., Dorsey, J., Fowler, D., Sutton, M., Flynn, M.,
and Duyzer, J.: Measurements and parameterizations of small aerosol
deposition velocities to grassland, arable crops, and forest: Influence of
surface roughness length on deposition, J. Geophys. Res.-Atmos., 107, AAC 8-1–AAC 8-10, https://doi.org/10.1029/2001JD000817, 2002.
Gallego, F. J.: A population density grid of the European Union, Popul. Environ., 31, 460–473, https://doi.org/10.1007/s11111-010-0108-y, 2010.
Galloway, J. N., Aber, J. D., Erisman, J. W., Seitzinger, S. P., Howarth, R.
W., Cowling, E. B., and Cosby, B. J.: The nitrogen cascade, AIBS Bulletin,
53, 341–356, 2003.
Galloway, J. N., Dentener, F. J., Capone, D. G., Boyer, E. W., Howarth, R.
W., Seitzinger, S. P., Asner, G. P., Cleveland, C. C., Green, P., and
Holland, E. A.: Nitrogen cycles: past, present, and future, Biogeochemistry,
70, 153–226, 2004.
Galloway, J. N., Townsend, A. R., Erisman, J. W., Bekunda, M., Cai, Z. C.,
Freney, J. R., Martinelli, L. A., Seitzinger, S. P., and Sutton, M. A.:
Transformation of the nitrogen cycle: Recent trends, questions, and
potential solutions, Science, 320, 889–892, https://doi.org/10.1126/science.1136674, 2008.
Hatfield, J.: Large scale evapotranspiration from remotely sensed surface
temperature, Planning Now for Irrigation and Drainage in the 21st Century,
ASCE, 502–509, 1988.
Hendriks, C., Kranenburg, R., Kuenen, J. J. P., Van den Bril, B., Verguts,
V., and Schaap, M.: Ammonia emission time profiles based on manure transport
data improve ammonia modelling across north western Europe, Atmos. Environ.,
131, 83–96, https://doi.org/10.1016/j.atmosenv.2016.01.043, 2016.
Hörtnagl, L., Feigenwinter, I., Fuchs, K., Merbold, L., Buchmann, N., Eugster, W., and Zeeman, M.: FLUXNET2015 CH-Cha Chamau, 2005–2014, Dataset, https://doi.org/10.18140/FLX/1440131, 2016a.
Hörtnagl, L., Feigenwinter, I., Fuchs, K., Merbold, L., Buchmann, N., Eugster, W., and Zeeman, M.: FLUXNET2015 CH-Fru Früebüel, 2005–2014, Dataset, https://doi.org/10.18140/FLX/1440133, 2016b.
Hörtnagl, L., Eugster, W., Buchmann, N., Paul-Limoges, E., Etzold S., and Haeni, M.: FLUXNET2015 CH-Lae Lägern, 2004–2014, Dataset, https://doi.org/10.18140/FLX/1440134, 2016c.
Hörtnagl, L., Maier, R., Eugster, W., Buchmann, N., and Emmel, C.: FLUXNET2015 CH-Oe2 Oensingen crop, 2004–2014, Dataset, https://doi.org/10.18140/FLX/1440136, 2016d.
Houborg, R. and Boegh, E.: Mapping leaf chlorophyll and leaf area index
using inverse and forward canopy reflectance modeling and SPOT reflectance
data, Remote Sens. Environ., 112, 186–202, 2008.
Janssens, I.: FLUXNET2015 BE-Bra Brasschaat, 1996–2014, Dataset, https://doi.org/10.18140/FLX/1440128, 2016.
Jonckheere, I., Fleck, S., Nackaerts, K., Muys, B., Coppin, P., Weiss, M.,
and Baret, F.: Review of methods for in situ leaf area index determination:
Part I. Theories, sensors and hemispherical photography, Agr. Forest
Meteorol., 121, 19–35, 2004.
Klatt, J., Schmid, H. P., Mauder, M., and Steinbrecher, R.: FLUXNET2015 DE-SfN Schechenfilz Nord, 2012–2014, Dataset, https://doi.org/10.18140/FLX/1440219, 2016.
Knohl, A., Tiedemann, F., Kolle, O., Schulze, E. D., Kutsch, W., Herbst, M., and Siebicke, L.: FLUXNET2015 DE-Hai Hainich, Dataset, https://doi.org/10.18140/FLX/1440148, 2016.
Kobayashi, H., Delbart, N., Suzuki, R., and Kushida, K.: A satellite-based
method for monitoring seasonality in the overstory leaf area index of
Siberian larch forest, J. Geophys. Res.-Biogeo., 115, G01002, https://doi.org/10.1029/2009JG000939,
2010.
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.
Lankreijer, H., Hendriks, M., and Klaassen, W.: A comparison of models
simulating rainfall interception of forests, Agr. Forest Meteorol., 64,
187–199, 1993.
Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D., and Pozzer, A.: The contribution of outdoor air pollution sources to premature mortality on a global scale, Nature, 525, 367–371, 2015.
Lolkema, D. E., Noordijk, H., Stolk, A. P., Hoogerbrugge, R., van Zanten, M. C., and van Pul, W. A. J.: The Measuring Ammonia in Nature (MAN) network in the Netherlands, Biogeosciences, 12, 5133–5142, https://doi.org/10.5194/bg-12-5133-2015, 2015.
Mailler, S., Menut, L., Khvorostyanov, D., Valari, M., Couvidat, F., Siour, G., Turquety, S., Briant, R., Tuccella, P., Bessagnet, B., Colette, A., Létinois, L., Markakis, K., and Meleux, F.: CHIMERE-2017: from urban to hemispheric chemistry-transport modeling, Geosci. Model Dev., 10, 2397–2423, https://doi.org/10.5194/gmd-10-2397-2017, 2017.
Majumdar, A. K. and Ricklin, J. C. (Eds.): Free-space laser
communications: principles and advances, Vol. 2, Springer Science &
Business Media, 2010.
Manders, A. M. M., Builtjes, P. J. H., Curier, L., Denier van der Gon, H. A. C., Hendriks, C., Jonkers, S., Kranenburg, R., Kuenen, J. J. P., Segers, A. J., Timmermans, R. M. A., Visschedijk, A. J. H., Wichink Kruit, R. J., van Pul, W. A. J., Sauter, F. J., van der Swaluw, E., Swart, D. P. J., Douros, J., Eskes, H., van Meijgaard, E., van Ulft, B., van Velthoven, P., Banzhaf, S., Mues, A. C., Stern, R., Fu, G., Lu, S., Heemink, A., van Velzen, N., and Schaap, M.: Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model, Geosci. Model Dev., 10, 4145–4173, https://doi.org/10.5194/gmd-10-4145-2017, 2017.
Mason, P.: The formation of areally-averaged roughness lengths, Q. J. Roy.
Meteor. Soc., 114, 399–420, 1988.
McNaughton, K. G. and Van Den Hurk, B. J. J. M.: A “Lagrangian” revision of
the resistors in the two-layer model for calculating the energy budget of a
plant canopy, Bound.-Lay. Meteorol., 74, 261–288, https://doi.org/10.1007/bf00712121, 1995.
Moors, E. and Elbers, J.: FLUXNET2015 NL-Loo Loobos, 1996–2014, Dataset, https://doi.org/10.18140/FLX/1440178, 2016.
Moran, M. S.: A satellite-based approach for evaluation of the spatial distribution of evapotranspiration from agricultural lands, PhD thesis, University of Arizona, Tucson, USA, 1990.
Myneni, R., Knyazikhin, Y., and Park, T.: MCD15A2H MODIS/Terra+Aqua Leaf
Area Index/FPAR 8-day L4 Global 500m SIN Grid V006, NASA EOSDIS Land
Processes DAAC, https://doi.org/10.5067/MODIS/MCD15A2H.006, 2015.
Nakai, T., Sumida, A., Daikoku, K. i., Matsumoto, K., van der Molen, M. K., Kodama, Y., Kononov, A. V., Maximov, T. C., Dolman, A. J., and Yabuki, H.: Parameterisation of aerodynamic roughness over boreal, cool-and warm-temperate forests, Agr. Forest Meteorol., 148, 1916–1925, 2008.
Paerl, H. W., Gardner, W. S., McCarthy, M. J., Peierls, B. L., and Wilhelm,
S. W.: Algal blooms: noteworthy nitrogen, Science, 346, p. 175, 2014.
Pastorello, G., Papale, D., Chu, H., Trotta, C., Agarwal, D., Canfora, E., Baldocchi, D., and Torn, M.: The FLUXNET2015 dataset: The longest record of global carbon, water, and energy fluxes is updated, EOS T. Am. Geophys. Un., 98, https://doi.org/10.1029/2017EO071597, 2017.
Plate, E. J.: Aerodynamic Characteristics of Atmospheric Boundary Layers,
Argonne National Lab., Ill. Karlsruhe Univ., 1971.
Raupach, M.: Simplified expressions for vegetation roughness length and
zero-plane displacement as functions of canopy height and area index,
Bound.-Lay. Meteorol., 71, 211–216, 1994.
Reis, S., Pinder, R. W., Zhang, M., Lijie, G., and Sutton, M. A.: Reactive nitrogen in atmospheric emission inventories, Atmos. Chem. Phys., 9, 7657–7677, https://doi.org/10.5194/acp-9-7657-2009, 2009.
Schaap, M., Manders, M., Hendriks, E., Cnossen, J., Segers, A., van der Gon, H. D., Jozwicka, M., Sauter, F., Velders, G., and Mathijssen, J.: Regional modelling of particulate matter for the Netherlands, Technical Report BOP, 2009.
Schaap, M., Banzhaf, S., Scheuschner, T., Geupel, M., Hendriks, C., Kranenburg, R., Nagel, H.-D., Segers, A. J., von Schlutow, A., Wichink Kruit, R., and Builtjes, P. J. H.: Atmospheric nitrogen deposition to terrestrial ecosystems across Germany, Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-491, in review, 2017.
Schaudt, K. and Dickinson, R.: An approach to deriving roughness length and
zero-plane displacement height from satellite data, prototyped with BOREAS
data, Agr. Forest Meteorol., 104, 143–155, 2000.
Schmidt, M. and Graf, A.: FLUXNET2015 DE-RuR Rollesbroich, 2011–2014, Dataset, https://doi.org/10.18140/FLX/1440215, 2016a.
Schmidt, M. and Graf, A.: FLUXNET2015 DE-RuS Selhausen Juelich, 2011–2014, Dataset, https://doi.org/10.18140/FLX/1440216, 2016b.
Schneider, K. and Schmidt, M.: FLUXNET2015 DE-Seh Selhausen, 2007–2010, Dataset, https://doi.org/10.18140/FLX/1440217, 2016.
Schrader, F. and Brummer, C.: Land Use Specific Ammonia Deposition
Velocities: a Review of Recent Studies (2004–2013), Water Air Soil. Poll.,
225, 2114, https://doi.org/10.1007/s11270-014-2114-7, 2014.
Schrader, F., Brümmer, C., Flechard, C. R., Wichink Kruit, R. J., van Zanten, M. C., Zöll, U., Hensen, A., and Erisman, J. W.: Non-stomatal exchange in ammonia dry deposition models: comparison of two state-of-the-art approaches, Atmos. Chem. Phys., 16, 13417–13430, https://doi.org/10.5194/acp-16-13417-2016, 2016.
Silva, J., Ribeiro, C., and Guedes, R.: Roughness length classification of Corine Land Cover classes, Proceedings of the European Wind Energy Conference, Milan, Italy, 710, p. 110, 2007.
Simard, M., Pinto, N., Fisher, J. B., and Baccini, A.: Mapping forest canopy
height globally with spaceborne lidar, J. Geophys. Res.-Biogeo., 116, G04021, https://doi.org/10.1029/2011jg001708, 2011.
Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D., Gauss, M., Jonson, J. E., Jenkin, M. E., Nyíri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, Á., and Wind, P.: The EMEP MSC-W chemical transport model – technical description, Atmos. Chem. Phys., 12, 7825–7865, https://doi.org/10.5194/acp-12-7825-2012, 2012.
Skjøth, C. A., Geels, C., Berge, H., Gyldenkærne, S., Fagerli, H., Ellermann, T., Frohn, L. M., Christensen, J., Hansen, K. M., Hansen, K., and Hertel, O.: Spatial and temporal variations in ammonia emissions – a freely accessible model code for Europe, Atmos. Chem. Phys., 11, 5221–5236, https://doi.org/10.5194/acp-11-5221-2011, 2011.
Soudani, K., François, C., Le Maire, G., Le Dantec, V., and Dufrêne,
E.: Comparative analysis of IKONOS, SPOT, and ETM+ data for leaf area
index estimation in temperate coniferous and deciduous forest stands, Remote
Sens. Environ., 102, 161–175, 2006.
Tian, Y., Dickinson, R. E., Zhou, L., Zeng, X., Dai, Y., Myneni, R., Knyazikhin, Y., Zhang, X., Friedl, M., and Yu, H.: Comparison of seasonal and spatial variations of leaf area index and fraction of absorbed photosynthetically active radiation from Moderate Resolution Imaging Spectroradiometer (MODIS) and Common Land Model, J. Geophys. Res.-Atmos., 109, D01103, https://doi.org/10.1029/2003JD003777, 2004.
Troen, I. and Petersen, E. L.: European Wind Atlas. Risø National Laboratory, Roskilde, 656 pp., ISBN 87-550-1482-8, 1989.
Turner, D. P., Cohen, W. B., Kennedy, R. E., Fassnacht, K. S., and Briggs,
J. M.: Relationships between leaf area index and Landsat TM spectral
vegetation indices across three temperate zone sites, Remote Sens. Environ.,
70, 52–68, 1999.
Van Zanten, M., Kruit, R. W., Hoogerbrugge, R., Van der Swaluw, E., and Van
Pul, W.: Trends in ammonia measurements in the Netherlands over the period
1993–2014, Atmos. Environ., 148, 352–360, 2017.
van Zanten, M. C., Sauter, F. J., Wichink Kruit, R. J., van Jaarsveld, J.
A., and van Pul, M. A. J.: Description of the DEPAC module: Dry deposition
modelling with DEPAC_GCN2010, Rivm Report 680180001/2010,
RIVM, Bilthoven, Netherlands, 2010.
Wang, Y., Woodcock, C. E., Buermann, W., Stenberg, P., Voipio, P.,
Smolander, H., Häme, T., Tian, Y., Hu, J., and Knyazikhin, Y.:
Evaluation of the MODIS LAI algorithm at a coniferous forest site in
Finland, Remote Sens. Environ., 91, 114–127, 2004.
Watson, D. J.: Comparative physiological studies on the growth of field
crops: I. Variation in net assimilation rate and leaf area between species
and varieties, and within and between years, Ann. Bot., 11, 41–76,
1947.
Wesely, M.: Parameterization of surface resistances to gaseous dry
deposition in regional-scale numerical models, Atmos. Environ.,
23, 1293–1304, 1989.
Wichink Kruit, R. J., Schaap, M., Sauter, F. J., van Zanten, M. C., and van Pul, W. A. J.: Modeling the distribution of ammonia across Europe including bi-directional surface–atmosphere exchange, Biogeosciences, 9, 5261–5277, https://doi.org/10.5194/bg-9-5261-2012, 2012.
Wieringa, J.: Representative roughness parameters for homogeneous terrain,
Bound.-Lay. Meteorol., 63, 323–363, 1993.
Wu, Z., Schwede, D. B., Vet, R., Walker, J. T., Shaw, M., Staebler, R., and
Zhang, L.: Evaluation and intercomparison of five North American dry
deposition algorithms at a mixed forest site, J. Adv.
Model. Earth Sy., 10, 1571–1586, 2018.
Xing, Q., Wu, B., Yan, N., Yu, M., and Zhu, W.: Evaluating the relationship between field aerodynamic roughness and the MODIS BRDF, NDVI, and wind speed over grassland, Atmosphere, 8, 16, https://doi.org/10.3390/atmos8010016, 2017.
Xu, B., Li, J., Park, T., Liu, Q., Zeng, Y., Yin, G., Zhao, J., Fan, W.,
Yang, L., and Knyazikhin, Y.: An integrated method for validating long-term
leaf area index products using global networks of site-based measurements,
Remote Sens. Environ., 209, 134–151, 2018.
Yan, K., Park, T., Yan, G., Liu, Z., Yang, B., Chen, C., Nemani, R. R., Knyazikhin, Y., and Myneni, R. B.: Evaluation of MODIS LAI/FPAR product collection 6. Part 2: Validation and intercomparison, Remote Sens., 8, 460, https://doi.org/10.3390/rs8060460, 2016.
Yang, R. and Friedl, M. A.: Determination of roughness lengths for heat and
momentum over boreal forests, Bound.-Lay. Meteorol., 107, 581–603, 2003.
Yu, M., Wu, B., Yan, N., Xing, Q., and Zhu, W.: A method for estimating the aerodynamic roughness length with NDVI and BRDF signatures using multi-temporal Proba-V data, Remote Sensing, 9, 6, https://doi.org/10.3390/rs9010006, 2017.
Zwally, H., Schutz, B., Abdalati, W., Abshire, J., Bentley, C., Brenner, A.,
Bufton, J., Dezio, J., Hancock, D., and Harding, D.: ICESat's laser
measurements of polar ice, atmosphere, ocean, and land, J.
Geodyn., 34, 405–445, 2002.
Short summary
Chemical transport models (CTMs) are important tools to determine the fate of reactive nitrogen (Nr) emissions. The parameterization of the surface–atmosphere exchange in CTMs is often only linked to fixed, land-use-dependent values. In this paper, we present an approach to derive more realistic, dynamic leaf area index (LAI) and roughness length (z0) input maps using multiple satellite products. We evaluate the effect on Nr concentration and deposition fields modelled in the LOTOS-EUROS CTM.
Chemical transport models (CTMs) are important tools to determine the fate of reactive nitrogen...
