Articles | Volume 13, issue 11
https://doi.org/10.5194/gmd-13-5725-2020
© 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-13-5725-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Prioritising the sources of pollution in European cities: do air quality modelling applications provide consistent responses?
Bart Degraeuwe
European Commission, Joint Research Centre (JRC), Ispra, Italy
Enrico Pisoni
CORRESPONDING AUTHOR
European Commission, Joint Research Centre (JRC), Ispra, Italy
Philippe Thunis
European Commission, Joint Research Centre (JRC), Ispra, Italy
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Manjola Banja, Monica Crippa, Diego Guizzardi, Marilena Muntean, Federico Pagani, and Enrico Pisoni
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-385, https://doi.org/10.5194/essd-2025-385, 2025
Preprint under review for ESSD
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Global efforts to decrease emissions rely on inventories that differ widely in scope and methodology. Alongside national inventories, independent databases provide yearly globally consistent emission inventories. Comparing independent inventories with countries submissions provides clear and consistent track of the real progress. Improvement of emissions inventories, reporting timelines, and statistical systems are essential to ensure reliable and comparable data.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
Geosci. Model Dev., 18, 4231–4245, https://doi.org/10.5194/gmd-18-4231-2025, https://doi.org/10.5194/gmd-18-4231-2025, 2025
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We assess relevance and utility indicators by evaluating nine Copernicus Atmospheric Monitoring Service models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and winter–summer gradients reveal issues. O3 evaluation shows that seasonal gradients are useful. Overall, the indicators reveal model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Diego Guizzardi, Monica Crippa, Tim Butler, Terry Keating, Rosa Wu, Jacek W. Kamiński, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Rachel Hoesly, Marilena Muntean, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Annie Duhamel, Tabish Ansari, Kristen Foley, Guannan Geng, Yifei Chen, and Qiang Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-601, https://doi.org/10.5194/essd-2024-601, 2025
Preprint under review for ESSD
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The global air pollution emission mosaic HTAP_v3.1 is the state-of-the-art database for addressing the evolution of a set of policy-relevant air pollutants over the past 2 decades. The inventory is made by the harmonization and blending of seven regional inventories, gapfilled using the most recent release of EDGAR (EDGARv8). By incorporating the best available local information, the HTAP_v3.1 mosaic inventory can be used for policy-relevant studies at both regional and global levels.
Monica Crippa, Diego Guizzardi, Federico Pagani, Marcello Schiavina, Michele Melchiorri, Enrico Pisoni, Francesco Graziosi, Marilena Muntean, Joachim Maes, Lewis Dijkstra, Martin Van Damme, Lieven Clarisse, and Pierre Coheur
Earth Syst. Sci. Data, 16, 2811–2830, https://doi.org/10.5194/essd-16-2811-2024, https://doi.org/10.5194/essd-16-2811-2024, 2024
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Knowing where emissions occur is essential for planning effective emission reduction measures and atmospheric modelling. Disaggregating national emissions over high-resolution grids requires spatial proxies that contain information on the location of different emission sources. This work incorporates state-of-the-art spatial information to improve the spatial representation of global emissions with the Emissions Database for Global Atmospheric Research (EDGAR).
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
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An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
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.
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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Many European people are still exposed to levels of air pollution that can affect their health. COVID-19 lockdowns in 2020 were used to assess the impact of the reduction in human mobility on air pollution across Europe by comparing measurement data with values that would be expected if no lockdown had occurred. We show that lockdown measures did not lead to consistent decreases in the concentrations of fine particulate matter suspended in the air, and we investigate why.
Monica Crippa, Diego Guizzardi, Tim Butler, Terry Keating, Rosa Wu, Jacek Kaminski, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Harrison Suchyta, Marilena Muntean, Efisio Solazzo, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Fabio Monforti-Ferrario, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Tabish Ansari, and Kristen Foley
Earth Syst. Sci. Data, 15, 2667–2694, https://doi.org/10.5194/essd-15-2667-2023, https://doi.org/10.5194/essd-15-2667-2023, 2023
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This study responds to the global and regional atmospheric modelling community's need for a mosaic of air pollutant emissions with global coverage, long time series, spatially distributed data at a high time resolution, and a high sectoral resolution in order to enhance the understanding of transboundary air pollution. The mosaic approach to integrating official regional emission inventories with a global inventory based on a consistent methodology ensures policy-relevant results.
Philippe Thunis, Alain Clappier, Enrico Pisoni, Bertrand Bessagnet, Jeroen Kuenen, Marc Guevara, and Susana Lopez-Aparicio
Geosci. Model Dev., 15, 5271–5286, https://doi.org/10.5194/gmd-15-5271-2022, https://doi.org/10.5194/gmd-15-5271-2022, 2022
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In this work, we propose a screening method to improve the quality of emission inventories, which are responsible for large uncertainties in air-quality modeling. The first step of screening consists of keeping only emission contributions that are relevant enough. In a second step, the method identifies large differences that provide evidence of methodological divergence or errors. We used the approach to compare two versions of the CAMS-REG European-scale inventory over 150 European cities.
Philippe Thunis, Alain Clappier, Alexander de Meij, Enrico Pisoni, Bertrand Bessagnet, and Leonor Tarrason
Atmos. Chem. Phys., 21, 18195–18212, https://doi.org/10.5194/acp-21-18195-2021, https://doi.org/10.5194/acp-21-18195-2021, 2021
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Air pollution's origin in cities is still a point of discussion, and approaches to assess the city's responsibility for its pollution are not harmonized and thus not comparable, resulting in sometimes contradicting interpretations. We show that methodological choices can easily lead to differences of a factor of 2 in terms of responsibility outcome and stress that methodological choices and assumptions most often lead to a systematic and important underestimation of the city's responsibility.
Philippe Thunis, Alain Clappier, Matthias Beekmann, Jean Philippe Putaud, Cornelis Cuvelier, Jessie Madrazo, and Alexander de Meij
Atmos. Chem. Phys., 21, 9309–9327, https://doi.org/10.5194/acp-21-9309-2021, https://doi.org/10.5194/acp-21-9309-2021, 2021
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Modelling simulations are used to identify the most efficient emission reduction strategies to reduce PM2.5 concentration levels in northern Italy. Results show contrasting chemical regimes and important non-linearities during wintertime, with the striking result that PM2.5 levels may increase when NOx reductions are applied in NOx-rich areas – a process that may have contributed to the absence of significant PM2.5 decrease during the COVID-19 lockdowns in many European cities.
Jean-Philippe Putaud, Luca Pozzoli, Enrico Pisoni, Sebastiao Martins Dos Santos, Friedrich Lagler, Guido Lanzani, Umberto Dal Santo, and Augustin Colette
Atmos. Chem. Phys., 21, 7597–7609, https://doi.org/10.5194/acp-21-7597-2021, https://doi.org/10.5194/acp-21-7597-2021, 2021
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To determine the impact of the COVID lockdown on air quality in northern Italy, measurements of atmospheric pollutants (NO2, PM10, O3, NO, SO2 ) were compared to the output of a model ignoring the lockdown. We found that NO2 decreased on average by −30 % to −40 %. Unlike NO2, PM10 was not significantly affected due to the compensation of decreased emissions from traffic by increased emissions from domestic heating and/or by changes in atmospheric chemistry enhancing secondary aerosol formation.
Cited articles
Amann M., Bertok, I., Borken-Kleefeld, J., Cofala, J., Heyes, C., Höglund-Isaksson, L., Klimont, Z., Nguyen, B., Posch, M., Rafaj, P., Sandler, R., Schöpp, W., Wagner, F., and Winiwarter, W.:
Cost-effective control of air quality and greenhouse gases
in Europe: modelling and policy applications, Environ. Model. Softw, 26,
1489-1501, 2011.
Carnevale, C., Finzi, G., Pisoni, E., and Volta, M.: Neuro-fuzzy and neural network
systems for air quality control, Atmos. Environ., 43, 4811–4821, 2009.
Carnevale, C., Finzi, G., Pederzoli, A., Turrini, E., Volta, M., Guariso, G.,
Gianfreda, R., Maffeis, G., Pisoni, E., Thunis, P., Markl-Hummel, L., Blond, N.,
Clappier, A., Dujardin, V., Weber, C., and Perron, G.: Exploring trade-offs between
air pollutants through an integrated assessment model, Sci. Total Environ.,
481, 7–16, 2014.
Clappier, A., Pisoni, E., and Thunis, P.: A new approach to design
source-receptor relationships for air quality modelling, Environ. Modell.
Softw., 74, 66–74, 2015.
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.
Couvidat, F., Bessagnet, B., Garcia-Vivanco, M., Real, E., Menut, L., and Colette, A.: Development of an inorganic and organic aerosol model (CHIMERE 2017β v1.0): seasonal and spatial evaluation over Europe, Geosci. Model Dev., 11, 165–194, https://doi.org/10.5194/gmd-11-165-2018, 2018.
Cuvelier, C., Thunis, P., Vautard, R., Amann, M., Bessagnet, B., Bedogni,
M., Berkowicz, R., Brandt, J., Brocheton, F., Builtjes, P., Carnavale, C.,
Coppalle, A., Denby, B., Douros, J., Graf, A., Hellmuth, O., Hodzic, A.,
Honoré, C., Jonson, J., Kerschbaumer, A., de Leeuw, F., Minguzzi, E.,
Moussiopoulos, N., Pertot, C., Peuch, V.H., Pirovano, G., Rouil, L., Sauter,
F., Schaap, M., Stern, R., Tarrason, L., Vignati, E., Volta, M., White, L.,
Wind, P., and Zuber, A.: CityDelta: A model intercomparison study to explore
the impact of emission reductions in European cities in 2010, Atmos.
Environ., 41, 189–207, https://doi.org/10.1016/j.atmosenv.2006.07.036, 2007.
Degraeuwe, B., Pisoni, E., and Thunis, P.: Routines and data to compare
different source-receptor relationships results, (Version v1.1), Zenodo,
https://doi.org/10.5281/zenodo.4059786, 2020a.
Degraeuwe, B., Pisoni, E., and Thunis P.: Source code for the SHERPA source
receptor relationships,(Version v1.0),
https://doi.org/10.5281/zenodo.4059770, 2020b.
Gómez-Losada, A., Pires, J. C. M., and Pino-Mejías, R.:
Modelling background air pollution exposure in urban environments:
Implications for epidemiological research, Environ. Modell. Softw., 106,
13–21, 2018.
Isakov, V., Barzyk, T. M., Smith, E. R., Arunachalam, S., Naess, B., and Venkatram, A.:
A web-based screening tool for near-port air quality assessments, Environ.
Modell. Softw., 98, 21–34, 2017.
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.
Pernigotti, D., Thunis, P., Cuvelier, C., Georgieva, E.,
Gsella, A., De Meij, A., Pirovano, G., Balzarini, A., Riva, G. M., Carnevale, C.,
Pisoni, E.,
Volta, M.,
Bessagnet, B.,
Kerschbaumer, A.,
Viaene, P.,
De Ridder, K.,
Nyiri, A.,
and Wind, P.: POMI: a model
inter-comparison exercise over the Po Valley, Air Qual. Atmos. Hlth.,
6, 701–715, 2013a.
Pernigotti, D., Gerboles, M., Belis, C. A., and Thunis, P.: Model quality
objectives based on measurement uncertainty. Part II: NO2 and PM10, Atmos.
Environ., 79, 869–878, 2013b.
Pisoni, E., Clappier, A., Degraeuwe, B., and Thunis, P.: Adding spatial
flexibility to source-receptor relationships for air quality modeling,
Environ. Modell. Softw., 90, 68–77, 2017.
Pisoni, E., Albrecht, D., Mara, T. A., Rosati, R., Tarantola, S., and Thunis, P.:
Application of uncertainty and sensitivity analysis to the air quality SHERPA modelling tool,
Atmospheric Environ.,
183,
84–93,
https://doi.org/10.1016/j.atmosenv.2018.04.006, 2018.
Pisoni, E., Thunis, P., and Clappier, A.: Application of the SHERPA
source-receptor relationships, based on the EMEP MSC-W model, for the
assessment of air quality policy scenarios, Atmos. Environ., 4,
100047, https://doi.org/10.1016/j.aeaoa.2019.10004, 2019.
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.
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.
Thunis, P. and Clappier, A.: Indicators to support the dynamic evaluation of
air quality models, Atmos. Environ. 98, 402–409,
https://doi.org/10.1016/j.atmosenv.2014.09.016, 2014.
Thunis, P., Rouil, L., Cuvelier, C., Stern, R., Kerschbaumer, A., Bessagnet,
B., Schaap, M., Builtjes, P., Tarrason, L., Douros, J., Moussiopoulos, N.,
Pirovano, G., and Bedogni, M.: Analysis of model responses to emission-reduction
scenarios within the CityDelta project, Atmos. Environ. 41, 208–220,
https://doi.org/10.1016/j.atmosenv.2006.09.001, 2007.
Thunis, P., Pisoni, E., Degraeuwe, B., Kranenburg, R., Schaap, M., and Clappier,
A.: Dynamic evaluation of air quality models over European regions, Atmos.
Environ., 111, 185–194, https://doi.org/10.1016/j.atmosenv.2015.04.016, 2015.
Thunis, P., Degraeuwe, B., Pisoni, E., Ferrari, F., and Clappier, A.: On the
design and assessment of regional air quality plans: The SHERPA approach, J.
Environ. Manage., 183, 952–958, https://doi.org/10.1016/j.jenvman.2016.09.049, 2016.
Thunis, P., Degraeuwe, B., Pisoni, E., Trombetti, M., Peduzzi, E., Belis,
C. A., Wilson, J., Clappier, A., Vand ignati, E.: PM2.5 source allocation in
European cities: A SHERPA modelling study, Atmos. Environ., 187, 93–106,
2018.
Thunis, P., Clappier, A., Tarrason, L., Cuvelier, C., Monteiro, A., Pisoni,
E., Wesseling, J., Belis, C. A., Pirovano, G., Janssen, S., Guerreiro, C., and
Peduzzi, E.: Source apportionment to support air quality planning: Strengths
and weaknesses of existing approaches, Environ. Int., 130, 104825, https://doi.org/10.1016/j.envint.2019.05.019,
2019.
Trombetti, M., Pisoni, E., and Lavalle, C.: Downscaling methodology to produce a high resolution
gridded emission inventory to support local/city level air quality policies,
JRC Technical Report, 10.2760/51058, 2017.
Viaene, P., Belis, C. A., Blond, N., Bouland, C., Juda-Rezler, K.,
Karvosenoja, N., Martilli, A., Miranda, A., Pisoni, E., and Volta, M.: Air quality
integrated assessment modelling in the context of EU policy: A way forward,
Environ. Sci. Policy, 65, 22–28, 2016.
Short summary
To make decisions on how to improve air quality, it is useful to identify the main sources of pollution for an area of interest. Often these sources of pollution are identified with complex models that, even if accurate, are time consuming and complex. In this work we use another approach, simplified models, to accomplish the same task. The results, computed with two different set of simplified models, show the main sources of pollution for selected cities, and the associated uncertainties.
To make decisions on how to improve air quality, it is useful to identify the main sources of...