Articles | Volume 14, issue 11
https://doi.org/10.5194/gmd-14-7021-2021
© Author(s) 2021. 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-14-7021-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
18 Nov 2021
Model evaluation paper |
| 18 Nov 2021
| 18 Nov 2021
Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements
School of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Road, Edinburgh, EH9 3FJ, UK
UK Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian, EH26 0QB, UK
School of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Road, Edinburgh, EH9 3FJ, UK
David S. Stevenson
School of GeoSciences, University of Edinburgh, Crew Building, Alexander Crum Brown Road, Edinburgh, EH9 3FF, UK
Peter Wind
The Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313, Oslo, Norway
Massimo Vieno
UK Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian, EH26 0QB, UK
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Yao Ge, Sverre Solberg, Mathew R. Heal, Stefan Reimann, Willem van Caspel, Bryan Hellack, Thérèse Salameh, and David Simpson
Atmos. Chem. Phys., 24, 7699–7729, https://doi.org/10.5194/acp-24-7699-2024, https://doi.org/10.5194/acp-24-7699-2024, 2024
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Lily Gouldsbrough, Ryan Hossaini, Emma Eastoe, Paul J. Young, and Massimo Vieno
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Gemma Purser, Mathew R. Heal, Edward J. Carnell, Stephen Bathgate, Julia Drewer, James I. L. Morison, and Massimo Vieno
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Atmos. Chem. Phys., 23, 6083–6112, https://doi.org/10.5194/acp-23-6083-2023, https://doi.org/10.5194/acp-23-6083-2023, 2023
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David S. Stevenson, Richard G. Derwent, Oliver Wild, and William J. Collins
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Yao Ge, Massimo Vieno, David S. Stevenson, Peter Wind, and Mathew R. Heal
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Svetlana Tsyro, Wenche Aas, Augustin Colette, Camilla Andersson, Bertrand Bessagnet, Giancarlo Ciarelli, Florian Couvidat, Kees Cuvelier, Astrid Manders, Kathleen Mar, Mihaela Mircea, Noelia Otero, Maria-Teresa Pay, Valentin Raffort, Yelva Roustan, Mark R. Theobald, Marta G. Vivanco, Hilde Fagerli, Peter Wind, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, and Mario Adani
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Particulate matter (PM) air pollution causes adverse health effects. In Europe, the emissions caused by anthropogenic activities have been reduced in the last decades. To assess the efficiency of emission reductions in improving air quality, we have studied the evolution of PM pollution in Europe. Simulations with six air quality models and observational data indicate a decrease in PM concentrations by 10 % to 30 % across Europe from 2000 to 2010, which is mainly a result of emission reductions.
Fanlei Meng, Yibo Zhang, Jiahui Kang, Mathew R. Heal, Stefan Reis, Mengru Wang, Lei Liu, Kai Wang, Shaocai Yu, Pengfei Li, Jing Wei, Yong Hou, Ying Zhang, Xuejun Liu, Zhenling Cui, Wen Xu, and Fusuo Zhang
Atmos. Chem. Phys., 22, 6291–6308, https://doi.org/10.5194/acp-22-6291-2022, https://doi.org/10.5194/acp-22-6291-2022, 2022
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PM2.5 pollution is a pressing environmental issue threatening human health and food security globally. We combined a meta-analysis of nationwide measurements and air quality modeling to identify efficiency gains by striking a balance between controlling NH3 and acid gas emissions. Persistent secondary inorganic aerosol pollution in China is limited by acid gas emissions, while an additional control on NH3 emissions would become more important as reductions in SO2 and NOx emissions progress.
Ernesto Reyes-Villegas, Upasana Panda, Eoghan Darbyshire, James M. Cash, Rutambhara Joshi, Ben Langford, Chiara F. Di Marco, Neil J. Mullinger, Mohammed S. Alam, Leigh R. Crilley, Daniel J. Rooney, W. Joe F. Acton, Will Drysdale, Eiko Nemitz, Michael Flynn, Aristeidis Voliotis, Gordon McFiggans, Hugh Coe, James Lee, C. Nicholas Hewitt, Mathew R. Heal, Sachin S. Gunthe, Tuhin K. Mandal, Bhola R. Gurjar, Shivani, Ranu Gadi, Siddhartha Singh, Vijay Soni, and James D. Allan
Atmos. Chem. Phys., 21, 11655–11667, https://doi.org/10.5194/acp-21-11655-2021, https://doi.org/10.5194/acp-21-11655-2021, 2021
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This paper shows the first multisite online measurements of PM1 in Delhi, India, with measurements over different seasons in Old Delhi and New Delhi in 2018. Organic aerosol (OA) source apportionment was performed using positive matrix factorisation (PMF). Traffic was the main primary aerosol source for both OAs and black carbon, seen with PMF and Aethalometer model analysis, indicating that control of primary traffic exhaust emissions would make a significant reduction to Delhi air pollution.
James M. Cash, Ben Langford, Chiara Di Marco, Neil J. Mullinger, James Allan, Ernesto Reyes-Villegas, Ruthambara Joshi, Mathew R. Heal, W. Joe F. Acton, C. Nicholas Hewitt, Pawel K. Misztal, Will Drysdale, Tuhin K. Mandal, Shivani, Ranu Gadi, Bhola Ram Gurjar, and Eiko Nemitz
Atmos. Chem. Phys., 21, 10133–10158, https://doi.org/10.5194/acp-21-10133-2021, https://doi.org/10.5194/acp-21-10133-2021, 2021
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We present the first real-time composition of submicron particulate matter (PM1) in Old Delhi using high-resolution aerosol mass spectrometry. Seasonal analysis shows peak concentrations occur during the post-monsoon, and novel-tracers reveal the largest sources are a combination of local open and regional crop residue burning. Strong links between increased chloride aerosol concentrations and burning sources of PM1 suggest burning sources are responsible for the post-monsoon chloride peak.
Robbie Ramsay, Chiara F. Di Marco, Mathew R. Heal, Matthias Sörgel, Paulo Artaxo, Meinrat O. Andreae, and Eiko Nemitz
Biogeosciences, 18, 2809–2825, https://doi.org/10.5194/bg-18-2809-2021, https://doi.org/10.5194/bg-18-2809-2021, 2021
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The exchange of the gas ammonia between the atmosphere and the surface is an important biogeochemical process, but little is known of this exchange for certain ecosystems, such as the Amazon rainforest. This study took measurements of ammonia exchange over an Amazon rainforest site and subsequently modelled the observed deposition and emission patterns. We observed emissions of ammonia from the rainforest, which can be simulated accurately by using a canopy resistance modelling approach.
Gemma Purser, Julia Drewer, Mathew R. Heal, Robert A. S. Sircus, Lara K. Dunn, and James I. L. Morison
Biogeosciences, 18, 2487–2510, https://doi.org/10.5194/bg-18-2487-2021, https://doi.org/10.5194/bg-18-2487-2021, 2021
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Short-rotation forest plantations could help reduce greenhouse gases but can emit biogenic volatile organic compounds. Emissions were measured at a plantation trial in Scotland. Standardised emissions of isoprene from foliage were higher from hybrid aspen than from Sitka spruce and low from Italian alder. Emissions of total monoterpene were lower. The forest floor was only a small source. Model estimates suggest an SRF expansion of 0.7 Mha could increase total UK emissions between < 1 %–35 %.
Y. Sim Tang, Chris R. Flechard, Ulrich Dämmgen, Sonja Vidic, Vesna Djuricic, Marta Mitosinkova, Hilde T. Uggerud, Maria J. Sanz, Ivan Simmons, Ulrike Dragosits, Eiko Nemitz, Marsailidh Twigg, Netty van Dijk, Yannick Fauvel, Francisco Sanz, Martin Ferm, Cinzia Perrino, Maria Catrambone, David Leaver, Christine F. Braban, J. Neil Cape, Mathew R. Heal, and Mark A. Sutton
Atmos. Chem. Phys., 21, 875–914, https://doi.org/10.5194/acp-21-875-2021, https://doi.org/10.5194/acp-21-875-2021, 2021
Short summary
Short summary
The DELTA® approach provided speciated, monthly data on reactive gases (NH3, HNO3, SO2, HCl) and aerosols (NH4+, NO3−, SO42−, Cl−, Na+) across Europe (2006–2010). Differences in spatial and temporal concentrations and patterns between geographic regions and four ecosystem types were captured. NH3 and NH4NO3 were dominant components, highlighting their growing relative importance in ecosystem impacts (acidification, eutrophication) and human health effects (NH3 as a precursor to PM2.5) in Europe.
Cited articles
Adams, P. J., Seinfeld, J. H., and Koch, D. M.: Global concentrations of tropospheric sulfate, nitrate, and ammonium aerosol simulated in a general circulation model, J. Geophys. Res.-Atmos., 104, 13791–13823, https://doi.org/10.1029/1999JD900083, 1999.
Aleksankina, K., Reis, S., Vieno, M., and Heal, M. R.: Advanced methods for uncertainty assessment and global sensitivity analysis of an Eulerian atmospheric chemistry transport model, Atmos. Chem. Phys., 19, 2881–2898, https://doi.org/10.5194/acp-19-2881-2019, 2019.
Bellouin, N., Rae, J., Jones, A., Johnson, C., Haywood, J., and Boucher, O.: Aerosol forcing in the Climate Model Intercomparison Project (CMIP5) simulations by HadGEM2-ES and the role of ammonium nitrate, J. Geophys. Res., 116, D20206, https://doi.org/10.1029/2011JD016074, 2011.
Bergström, R., Hallquist, M., Simpson, D., Wildt, J., and Mentel, T. F.: Biotic stress: a significant contributor to organic aerosol in Europe?, Atmos. Chem. Phys., 14, 13643–13660, https://doi.org/10.5194/acp-14-13643-2014, 2014.
Bergström, R., Jenkin, M., Hayman, G., and Simpson, D.: Update and comparison of atmospheric chemistry mechanisms for the EMEP MSC-W model system – EmChem19a, EmChem19X, CRIv2R5Em, CB6r2Em, and MCMv3.3Em, in preparation, 2021.
Bian, H., Chin, M., Hauglustaine, D. A., Schulz, M., Myhre, G., Bauer, S. E., Lund, M. T., Karydis, V. A., Kucsera, T. L., Pan, X., Pozzer, A., Skeie, R. B., Steenrod, S. D., Sudo, K., Tsigaridis, K., Tsimpidi, A. P., and Tsyro, S. G.: Investigation of global particulate nitrate from the AeroCom phase III experiment, Atmos. Chem. Phys., 17, 12911–12940, https://doi.org/10.5194/acp-17-12911-2017, 2017.
Burnett, R., Chen, H., Szyszkowicz, M., Fann, N., Hubbell, B., Pope, C. A., Apte, J. S., Brauer, M., Cohen, A., Weichenthal, S., Coggins, J., Di, Q., Brunekreef, B., Frostad, J., Lim, S. S., Kan, H., Walker, K. D., Thurston, G. D., Hayes, R. B., Lim, C. C., Turner, M. C., Jerrett, M., Krewski, D., Gapstur, S. M., Diver, W. R., Ostro, B., Goldberg, D., Crouse, D. L., Martin, R. V., Peters, P., Pinault, L., Tjepkema, M., van Donkelaar, A., Villeneuve, P. J., Miller, A. B., Yin, P., Zhou, M., Wang, L., Janssen, N. A. H., Marra, M., Atkinson, R. W., Tsang, H., Quoc Thach, T., Cannon, J. B., Allen, R. T., Hart, J. E., Laden, F., Cesaroni, G., Forastiere, F., Weinmayr, G., Jaensch, A., Nagel, G., Concin, H., and Spadaro, J. V.: Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter, P. Natl. Acad. Sci. USA, 115, 9592, https://doi.org/10.1073/pnas.1803222115, 2018.
Byun, D. and Schere, K. L.: Review of the Governing Equations, Computational Algorithms, and Other Components of the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System, Appl. Mech. Rev., 59, 51–77, 2006.
Carozzi, M., Loubet, B., Acutis, M., Rana, G., and Ferrara, R. M.: Inverse dispersion modelling highlights the efficiency of slurry injection to reduce ammonia losses by agriculture in the Po Valley (Italy), Agr. Forest Meteorol., 171–172, 306–318, https://doi.org/10.1016/j.agrformet.2012.12.012, 2013.
Chapman, E. G., Gustafson Jr., W. I., Easter, R. C., Barnard, J. C., Ghan, S. J., Pekour, M. S., and Fast, J. D.: Coupling aerosol-cloud-radiative processes in the WRF-Chem model: Investigating the radiative impact of elevated point sources, Atmos. Chem. Phys., 9, 945–964, https://doi.org/10.5194/acp-9-945-2009, 2009.
Cheng, Y., Duan, F.-k., He, K.-b., Du, Z.-y., Zheng, M., and Ma, Y.-l.: Sampling artifacts of organic and inorganic aerosol: Implications for the speciation measurement of particulate matter, Atmos. Environ., 55, 229–233, https://doi.org/10.1016/j.atmosenv.2012.03.032, 2012.
Ciarelli, G., Theobald, M. R., Vivanco, M. G., Beekmann, M., Aas, W., Andersson, C., Bergström, R., Manders-Groot, A., Couvidat, F., Mircea, M., Tsyro, S., Fagerli, H., Mar, K., Raffort, V., Roustan, Y., Pay, M.-T., Schaap, M., Kranenburg, R., Adani, M., Briganti, G., Cappelletti, A., D'Isidoro, M., Cuvelier, C., Cholakian, A., Bessagnet, B., Wind, P., and Colette, A.: Trends of inorganic and organic aerosols and precursor gases in Europe: insights from the EURODELTA multi-model experiment over the 1990–2010 period, Geosci. Model Dev., 12, 4923–4954, https://doi.org/10.5194/gmd-12-4923-2019, 2019.
Crippa, M., Solazzo, E., Huang, G., Guizzardi, D., Koffi, E., Muntean, M., Schieberle, C., Friedrich, R., and Janssens-Maenhout, G.: High resolution temporal profiles in the Emissions Database for Global Atmospheric Research, Sci. Data, 7, 121, https://doi.org/10.1038/s41597-020-0462-2, 2020.
Denby, B. R., Gauss, M., Wind, P., Mu, Q., Grøtting Wærsted, E., Fagerli, H., Valdebenito, A., and Klein, H.: Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model, Geosci. Model Dev., 13, 6303–6323, https://doi.org/10.5194/gmd-13-6303-2020, 2020.
EMEP/EEA: EMEP/EEA air pollutant emission inventory guidebook, European Environment Agency, Luxembourg, 15 pp., 2019.
EMEP MSC-W: metno/emep-ctm: OpenSource rv4.34 (202001), rv4_34, Zenodo [code], https://doi.org/10.5281/zenodo.3647990, 2020.
Erisman, J. W., Domburg, N., de Vries, W., Kros, H., de Haan, B., and Sanders, K.: The Dutch N-cascade in the European perspective, Sci. China Ser. C, 48, 827–842, 2005.
Fagerli, H., Tsyro, S., Denby, B. R., Nyíri, Á., Gauss, M., Simpson, D., Wind, P., Benedictow, A., Jonson, J. E., Klein, H., Schulz, M., Griesfeller, J., Aas, W., Hjellbrekke, A.-G., Solberg, S., Platt, S. M., Fiebig, M., Yttri, K. E., Rud, R. O., Tørseth, K., Mareckova, K., Pinterits, M., Tista, M., Ullrich, B., and Wankmüller, R.: EMEP Status Report 1/2017: Transboundary particulate matter, photo-oxidants, acidifying and eutrophying components (Joint MSC-W & CCC & CEIP Report), Meteorological Synthesizing Centre-West of EMEP(MSC-W of EMEP), European Monitoring and Evaluation Programme (EMEP), 41, 2017.
Fagerli, H., Tsyro, S., Jonson, J. E., Nyíri,
Á., Gauss, M., Simpson, D., Wind, P., Benetictow, A., Klein, H.,
Mortier, A., Aas, W., Hjellbrekke, A.-G., Solberg, S., Platt, S. M.,
Yttri, K. E., Tørseth, K., Gaisbauer, S., Mareckova, K.,
Matthews, B., Schindlbacher, S., Sosa, C., Tista, M., Ullrich, B.,
Wankmüller, R., Scheuschner, T., Bergström, R., Johanson,
L., Jalkanen, J.-P., Metzger, S., van der Gon, H. A. C. D., Kuenen,
J. J. P., Visschedijk, A. J. H., Barregård, L., Molnár, P.,
and Stockfelt, L.: Updates to the EMEP MSC-W model, 2018–2019, in:
Transboundary particulate matter, photo-oxidants, acidifying and
eutrophying components, Meteorologisk Institutt – Norwegian
Meteorological Institute, Oslo, Norway, 15046109 (ISSN), 44, 2019.
Ge, Y.: Dataset for evaluation of global EMEP MSC-W (rv4.34)-WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements, Zenodo [data set], https://doi.org/10.5281/zenodo.5037080, 2021.
Gusev, A., MacLeod, M., and Bartlett, P.: Intercontinental transport of persistent organic pollutants: a review of key findings and recommendations of the task force on hemispheric transport of air pollutants and directions for future research, Atmos. Pollut. Res., 3, 463–465, https://doi.org/10.5094/APR.2012.053, 2012.
Hauglustaine, D. A., Balkanski, Y., and Schulz, M.: A global model simulation of present and future nitrate aerosols and their direct radiative forcing of climate, Atmos. Chem. Phys., 14, 11031–11063, https://doi.org/10.5194/acp-14-11031-2014, 2014.
Hjellbrekke, A.-G.: Data Report 2015 Particulate matter, carbonaceous and inorganic compounds, EMEP Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe, Chemical Co-ordinating Centre of EMEP (CCC), EMEP/CCC Reports, 143 pp., 2017.
Hood, C., MacKenzie, I., Stocker, J., Johnson, K., Carruthers, D., Vieno, M., and Doherty, R.: Air quality simulations for London using a coupled regional-to-local modelling system, Atmos. Chem. Phys., 18, 11221–11245, https://doi.org/10.5194/acp-18-11221-2018, 2018.
Janssens-Maenhout, G., Crippa, M., Guizzardi, D., Dentener, F., Muntean, M., Pouliot, G., Keating, T., Zhang, Q., Kurokawa, J., Wankmüller, R., Denier van der Gon, H., Kuenen, J. J. P., Klimont, Z., Frost, G., Darras, S., Koffi, B., and Li, M.: HTAP_v2.2: a mosaic of regional and global emission grid maps for 2008 and 2010 to study hemispheric transport of air pollution, Atmos. Chem. Phys., 15, 11411–11432, https://doi.org/10.5194/acp-15-11411-2015, 2015.
Jonson, J. E., Borken-Kleefeld, J., Simpson, D., Nyíri, A., Posch, M., and Heyes, C.: Impact of excess NO x emissions from diesel cars on air quality, public health and eutrophication in Europe, Environ. Res. Lett., 12, 094017, https://doi.org/10.1088/1748-9326/aa8850, 2017.
Karl, M., Jonson, J. E., Uppstu, A., Aulinger, A., Prank, M., Sofiev, M., Jalkanen, J.-P., Johansson, L., Quante, M., and Matthias, V.: Effects of ship emissions on air quality in the Baltic Sea region simulated with three different chemistry transport models, Atmos. Chem. Phys., 19, 7019–7053, https://doi.org/10.5194/acp-19-7019-2019, 2019.
Khan, M. A. H., Lowe, D., Derwent, R. G., Foulds, A., Chhantyal-Pun, R., McFiggans, G., Orr-Ewing, A. J., Percival, C. J., and Shallcross, D. E.: Global and regional model simulations of atmospheric ammonia, Atmos. Res., 234, 104702, https://doi.org/10.1016/j.atmosres.2019.104702, 2020.
Klimont, Z., Kupiainen, K., Heyes, C., Purohit, P., Cofala, J., Rafaj, P., Borken-Kleefeld, J., and Schöpp, W.: Global anthropogenic emissions of particulate matter including black carbon, Atmos. Chem. Phys., 17, 8681–8723, https://doi.org/10.5194/acp-17-8681-2017, 2017.
Kong, L., Tang, X., Zhu, J., Wang, Z., Fu, J. S., Wang, X., Itahashi, S., Yamaji, K., Nagashima, T., Lee, H.-J., Kim, C.-H., Lin, C.-Y., Chen, L., Zhang, M., Tao, Z., Li, J., Kajino, M., Liao, H., Wang, Z., Sudo, K., Wang, Y., Pan, Y., Tang, G., Li, M., Wu, Q., Ge, B., and Carmichael, G. R.: Evaluation and uncertainty investigation of the NO2, CO and NH3 modeling over China under the framework of MICS-Asia III, Atmos. Chem. Phys., 20, 181–202, https://doi.org/10.5194/acp-20-181-2020, 2020.
Laskin, A., Laskin, J., and Nizkorodov, S. A.: Chemistry of atmospheric brown carbon, Chem. Rev., 115, 4335–4382, 2015.
Li, C., Martin, R. V., van Donkelaar, A., Boys, B. L., Hammer, M. S., Xu, J.-W., Marais, E. A., Reff, A., Strum, M., Ridley, D. A., Crippa, M., Brauer, M., and Zhang, Q.: Trends in Chemical Composition of Global and Regional Population-Weighted Fine Particulate Matter Estimated for 25 Years, Environ. Sci. Technol., 51, 11185–11195, https://doi.org/10.1021/acs.est.7b02530, 2017.
Lin, Y. and Colle, B. A.: A New Bulk Microphysical Scheme That Includes Riming Intensity and Temperature-Dependent Ice Characteristics, Mon. Weather Rev., 139, 1013–1035, https://doi.org/10.1175/2010MWR3293.1, 2011.
Liu, L., Zhang, X., Wong, A. Y. H., Xu, W., Liu, X., Li, Y., Mi, H., Lu, X., Zhao, L., Wang, Z., Wu, X., and Wei, J.: Estimating global surface ammonia concentrations inferred from satellite retrievals, Atmos. Chem. Phys., 19, 12051–12066, https://doi.org/10.5194/acp-19-12051-2019, 2019.
McFiggans, G., Mentel, T. F., Wildt, J., Pullinen, I., Kang, S., Kleist, E., Schmitt, S., Springer, M., Tillmann, R., Wu, C., Zhao, D., Hallquist, M., Faxon, C., Le Breton, M., Hallquist, Å. M., Simpson, D., Bergström, R., Jenkin, M. E., Ehn, M., Thornton, J. A., Alfarra, M. R., Bannan, T. J., Percival, C. J., Priestley, M., Topping, D., and Kiendler-Scharr, A.: Secondary organic aerosol reduced by mixture of atmospheric vapours, Nature, 565, 587–593, https://doi.org/10.1038/s41586-018-0871-y, 2019.
Mills, G., Sharps, K., Simpson, D., Pleijel, H., Broberg,
M., Uddling, J., Jaramillo, F., Davies, W. J., Dentener, F., Van den
Berg, M., Agrawal, M., Agrawal, S. B., Ainsworth, E. A., Büker, P., Emberson, L., Feng, Z., Harmens, H., Hayes, F., Kobayashi, K., Paoletti, E., and Van Dingenen, R.: Ozone pollution will compromise efforts to increase global wheat production, Glob. Change Biol., 24, 3560–3574, https://doi.org/10.1111/gcb.14157, 2018.
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, https://doi.org/10.1016/j.atmosenv.2013.07.045, 2013.
Pommier, M., Fagerli, H., Schulz, M., Valdebenito, A., Kranenburg, R., and Schaap, M.: Prediction of source contributions to urban background PM10 concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0 – Part 1: The country contributions, Geosci. Model Dev., 13, 1787–1807, https://doi.org/10.5194/gmd-13-1787-2020, 2020.
Pringle, K. J., Tost, H., Message, S., Steil, B., Giannadaki, D., Nenes, A., Fountoukis, C., Stier, P., Vignati, E., and Lelieveld, J.: Description and evaluation of GMXe: a new aerosol submodel for global simulations (v1), Geosci. Model Dev., 3, 391–412, https://doi.org/10.5194/gmd-3-391-2010, 2010.
Pye, H. O. T., Liao, H., Wu, S., Mickley, L. J., Jacob, D. J., Henze, D. K., and Seinfeld, J. H.: Effect of changes in climate and emissions on future sulfate-nitrate-ammonium aerosol levels in the United States, J. Geophys. Res.-Atmos., 114, D01205, https://doi.org/10.1029/2008JD010701, 2009.
Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, J., Nadiga, S., Tripp, P., Kistler, R., Woollen, J., Behringer, D., Liu, H., Stokes, D., Grumbine, R., Gayno, G., Wang, J., Hou, Y.-T., Chuang, H.-y., Juang, H.-M. H., Sela, J., Iredell, M., Treadon, R., Kleist, D., Van Delst, P., Keyser, D., Derber, J., Ek, M., Meng, J., Wei, H., Yang, R., Lord, S., van den Dool, H., Kumar, A., Wang, W., Long, C., Chelliah, M., Xue, Y., Huang, B., Schemm, J.-K., Ebisuzaki, W., Lin, R., Xie, P., Chen, M., Zhou, S., Higgins, W., Zou, C.-Z., Liu, Q., Chen, Y., Han, Y., Cucurull, L., Reynolds, R. W., Rutledge, G., and Goldberg, M.: The NCEP Climate Forecast System Reanalysis, B. Am. Meteorol. Soc., 91, 1015–1058, https://doi.org/10.1175/2010BAMS3001.1, 2010.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D., Duda, M. G., Huang, X.-y., Wang, W., and Powers, J. G.: A Description of the Advanced Research WRF Version 3 (No. NCAR/TN-475+STR), University Corporation for Atmospheric Research, https://doi.org/10.5065/D68S4MVH, 2008 (data available at: http://www.wrf-model.org, last access: 20 May 2021).
Shaddick, G., Thomas, M. L., Mudu, P., Ruggeri, G., and Gumy, S.: Half the world's population are exposed to increasing air pollution, npj Climate and Atmospheric Science, 3, 23, https://doi.org/10.1038/s41612-020-0124-2, 2020.
Sickles, I. J. E., Hodson, L. L., and Vorburger, L. M.: Evaluation of the filter pack for long-duration sampling of ambient air, Atmos. Environ., 33, 2187–2202, https://doi.org/10.1016/S1352-2310(98)00425-7, 1999.
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.
Simpson, D., Bergström, R., Imhof, H., and Wind, P.: Updates to the EMEP/MSC-W model, 2016–2017, in: Transboundary particulate matter, photo-oxidants, acidifying and eutrophying components, The Norwegian Meteorological Institute, Oslo, Norway, Status Report 1/2017, 115–122, available at: https://www.emep.int (last access: 20 May 2021), 2017.
Simpson, D., Bergström, R., Briolat, A., Imhof, H., Johansson, J., Priestley, M., and Valdebenito, A.: GenChem v1.0 – a chemical pre-processing and testing system for atmospheric modelling, Geosci. Model Dev., 13, 6447–6465, https://doi.org/10.5194/gmd-13-6447-2020, 2020.
Skamarock, W. C., Klemp, J. B., Dudhia, J., David O. Gill, D. O., Barker, D., Duda, M. G., Huang, X. Y., Wang, W., and Powers, J. G.: A Description of the Advanced Research WRF Version 3, NCAR, Tech. Note NCAR/TN-475+STR, 113 pp., https://doi.org/10.5065/D68S4MVH, 2008.
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.
Stadtler, S., Simpson, D., Schröder, S., Taraborrelli, D., Bott, A., and Schultz, M.: Ozone impacts of gas–aerosol uptake in global chemistry transport models, Atmos. Chem. Phys., 18, 3147–3171, https://doi.org/10.5194/acp-18-3147-2018, 2018.
Tan, J., Fu, J. S., Dentener, F., Sun, J., Emmons, L., Tilmes, S., Sudo, K., Flemming, J., Jonson, J. E., Gravel, S., Bian, H., Davila, Y., Henze, D. K., Lund, M. T., Kucsera, T., Takemura, T., and Keating, T.: Multi-model study of HTAP II on sulfur and nitrogen deposition, Atmos. Chem. Phys., 18, 6847–6866, https://doi.org/10.5194/acp-18-6847-2018, 2018.
Tang, Y. S., Braban, C. F., Dragosits, U., Dore, A. J., Simmons, I., van Dijk, N., Poskitt, J., Dos Santos Pereira, G., Keenan, P. O., Conolly, C., Vincent, K., Smith, R. I., Heal, M. R., and Sutton, M. A.: Drivers for spatial, temporal and long-term trends in atmospheric ammonia and ammonium in the UK, Atmos. Chem. Phys., 18, 705–733, https://doi.org/10.5194/acp-18-705-2018, 2018a.
Tang, Y. S., Braban, C. F., Dragosits, U., Simmons, I., Leaver, D., van Dijk, N., Poskitt, J., Thacker, S., Patel, M., Carter, H., Pereira, M. G., Keenan, P. O., Lawlor, A., Conolly, C., Vincent, K., Heal, M. R., and Sutton, M. A.: Acid gases and aerosol measurements in the UK (1999–2015): regional distributions and trends, Atmos. Chem. Phys., 18, 16293–16324, https://doi.org/10.5194/acp-18-16293-2018, 2018b.
Tang, Y. S., Flechard, C. R., Dämmgen, U., Vidic, S., Djuricic, V., Mitosinkova, M., Uggerud, H. T., Sanz, M. J., Simmons, I., Dragosits, U., Nemitz, E., Twigg, M., van Dijk, N., Fauvel, Y., Sanz, F., Ferm, M., Perrino, C., Catrambone, M., Leaver, D., Braban, C. F., Cape, J. N., Heal, M. R., and Sutton, M. A.: Pan-European rural monitoring network shows dominance of NH3 gas and NH4NO3 aerosol in inorganic atmospheric pollution load, Atmos. Chem. Phys., 21, 875–914, https://doi.org/10.5194/acp-21-875-2021, 2021.
Thunis, P., Pernigotti, D., and Gerboles, M.: Model quality objectives based on measurement uncertainty. Part I: Ozone, Atmos. Environ., 79, 861–868, https://doi.org/10.1016/j.atmosenv.2013.05.018, 2013.
Tørseth, K., Aas, W., Breivik, K., Fjæraa, A. M., Fiebig, M., Hjellbrekke, A. G., Lund Myhre, C., Solberg, S., and Yttri, K. E.: Introduction to the European Monitoring and Evaluation Programme (EMEP) and observed atmospheric composition change during 1972–2009, Atmos. Chem. Phys., 12, 5447–5481, https://doi.org/10.5194/acp-12-5447-2012, 2012.
Tsyro, S., Aas, W., Soares, J., Sofiev, M., Berge, H., and Spindler, G.: Modelling of sea salt concentrations over Europe: key uncertainties and comparison with observations, Atmos. Chem. Phys., 11, 10367–10388, https://doi.org/10.5194/acp-11-10367-2011, 2011.
Vecchi, R., Valli, G., Fermo, P., D'Alessandro, A., Piazzalunga, A., and Bernardoni, V.: Organic and inorganic sampling artefacts assessment, Atmos. Environ., 43, 1713–1720, https://doi.org/10.1016/j.atmosenv.2008.12.016, 2009.
Vieno, M., Dore, A. J., Stevenson, D. S., Doherty, R., Heal, M. R., Reis, S., Hallsworth, S., Tarrason, L., Wind, P., Fowler, D., Simpson, D., and Sutton, M. A.: Modelling surface ozone during the 2003 heat-wave in the UK, Atmos. Chem. Phys., 10, 7963–7978, https://doi.org/10.5194/acp-10-7963-2010, 2010.
Vieno, M., Heal, M. R., Hallsworth, S., Famulari, D., Doherty, R. M., Dore, A. J., Tang, Y. S., Braban, C. F., Leaver, D., Sutton, M. A., and Reis, S.: The role of long-range transport and domestic emissions in determining atmospheric secondary inorganic particle concentrations across the UK, Atmos. Chem. Phys., 14, 8435–8447, https://doi.org/10.5194/acp-14-8435-2014, 2014.
Vieno, M., Heal, M. R., Williams, M. L., Carnell, E. J., Nemitz, E., Stedman, J. R., and Reis, S.: The sensitivities of emissions reductions for the mitigation of UK PM2.5, Atmos. Chem. Phys., 16, 265–276, https://doi.org/10.5194/acp-16-265-2016, 2016.
Wagner, R., Bertozzi, B., Höpfner, M., Höhler, K., Möhler, O., Saathoff, H., and Leisner, T.: Solid Ammonium Nitrate Aerosols as Efficient Ice Nucleating Particles at Cirrus Temperatures, J. Geophys. Res.-Atmos., 125, e2019JD032248, https://doi.org/10.1029/2019JD032248, 2020.
Weiss, A. and Norman, J. M.: Partitioning solar radiation into direct and diffuse, visible and near-infrared components, Agr. Forest Meteorol., 34, 205–213, https://doi.org/10.1016/0168-1923(85)90020-6, 1985.
West, J. J., Emberson, L., Anenberg, S. C., Arnold, S., Ashmore, M., Atkinson, R., Bellouin, N., Cohen, A., Collins, B., and Delmelle, P.: Impacts on Health, Ecosystems, and Climate, in: Hemispheric Transport of Air Pollution: Part A: Ozone and Particulate Matter, Air Pollution Studies, edited by: Dentener, F., Keating, T., and Akimoto, H., United Nations, New York and Geneva, Chapter 5, 199–251, 2010.
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011.
Xu, L. and Penner, J. E.: Global simulations of nitrate and ammonium aerosols and their radiative effects, Atmos. Chem. Phys., 12, 9479–9504, https://doi.org/10.5194/acp-12-9479-2012, 2012.
Xu, W., Luo, X. S., Pan, Y. P., Zhang, L., Tang, A. H., Shen, J. L., Zhang, Y., Li, K. H., Wu, Q. H., Yang, D. W., Zhang, Y. Y., Xue, J., Li, W. Q., Li, Q. Q., Tang, L., Lu, S. H., Liang, T., Tong, Y. A., Liu, P., Zhang, Q., Xiong, Z. Q., Shi, X. J., Wu, L. H., Shi, W. Q., Tian, K., Zhong, X. H., Shi, K., Tang, Q. Y., Zhang, L. J., Huang, J. L., He, C. E., Kuang, F. H., Zhu, B., Liu, H., Jin, X., Xin, Y. J., Shi, X. K., Du, E. Z., Dore, A. J., Tang, S., Collett Jr., J. L., Goulding, K., Sun, Y. X., Ren, J., Zhang, F. S., and Liu, X. J.: Quantifying atmospheric nitrogen deposition through a nationwide monitoring network across China, Atmos. Chem. Phys., 15, 12345–12360, https://doi.org/10.5194/acp-15-12345-2015, 2015.
Xu, W., Zhang, L., and Liu, X.: A database of atmospheric nitrogen concentration and deposition from the nationwide monitoring network in China, Sci. Data, 6, 51, https://doi.org/10.1038/s41597-019-0061-2, 2019.
Yu, X.-Y., Lee, T., Ayres, B., Kreidenweis, S. M., Collett, J. L., and Malm, W.: Particulate Nitrate Measurement Using Nylon Filters, JAPCA J. Air Waste Ma., 55, 1100–1110, https://doi.org/10.1080/10473289.2005.10464721, 2005.
Zheng, J. Y., Yin, S. S., Kang, D. W., Che, W. W., and Zhong, L. J.: Development and uncertainty analysis of a high-resolution NH3 emissions inventory and its implications with precipitation over the Pearl River Delta region, China, Atmos. Chem. Phys., 12, 7041–7058, https://doi.org/10.5194/acp-12-7041-2012, 2012.
Short summary
This study reports the first evaluation of the global EMEP MSC-W ACTM driven by WRF meteorology, with a focus on surface concentrations and wet deposition of reactive N and S species. The model–measurement comparison is conducted both spatially and temporally, covering 10 monitoring networks worldwide. The statistics from the comprehensive evaluations presented in this study support the application of this model framework for global analysis of the budgets and fluxes of reactive N and SIA.
This study reports the first evaluation of the global EMEP MSC-W ACTM driven by WRF meteorology,...
