Articles | Volume 16, issue 1
https://doi.org/10.5194/os-16-115-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/os-16-115-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantifying the contribution of shipping NOx emissions to the marine nitrogen inventory – a case study for the western Baltic Sea
Leibniz-Institute for Baltic Sea Research Warnemünde, Seestr. 15, 18119 Rostock, Germany
Matthias Karl
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, 21502 Geesthacht, Germany
Hagen Radtke
Leibniz-Institute for Baltic Sea Research Warnemünde, Seestr. 15, 18119 Rostock, Germany
Volker Matthias
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, 21502 Geesthacht, Germany
René Friedland
Leibniz-Institute for Baltic Sea Research Warnemünde, Seestr. 15, 18119 Rostock, Germany
Thomas Neumann
Leibniz-Institute for Baltic Sea Research Warnemünde, Seestr. 15, 18119 Rostock, Germany
Related authors
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Friederike Keil, Markus Quante, Bernd Heinold, and Volker Matthias
Atmos. Chem. Phys., 26, 11561–11582, https://doi.org/10.5194/acp-26-11561-2026, https://doi.org/10.5194/acp-26-11561-2026, 2026
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Using model simulations, we studied convective weather events to see how urban aerosol emissions influence cloud microphysics and precipitation. By tracing urban air volumes from convective clouds back to their emission sources, we could isolate the effects of emissions. The results show that urban emissions affect precipitation differently depending on the meteorological situation, highlighting the complex and case-dependent role of cities in shaping local rainfall.
Pascal Simon, Martin Otto Paul Ramacher, Stefan Hagemann, Volker Matthias, Hanna Joerss, and Johannes Bieser
Earth Syst. Sci. Data, 18, 5713–5737, https://doi.org/10.5194/essd-18-5713-2026, https://doi.org/10.5194/essd-18-5713-2026, 2026
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Per- and Polyfluorinated Alkyl Substances (PFAS) constitute a group of often toxic, persistent, and bioaccumulative substances. We constructed a global Emissions model and inventory based on multiple datasets for 23 widely used PFAS. The model computes temporally and spatially resolved model ready emissions distinguishing between emissions to air and emissions to water covering the time span from 1950 up until 2020 on an annual basis to be used for chemistry transport modelling.
Hiram Meza-Landero, Julia Bruckert, Ronny Petrik, Pascal Simon, Elena Mikheeva, Heike Vogel, Volker Matthias, Johannes Bieser, and Martin Otto Paul Ramacher
Geosci. Model Dev., 19, 6587–6626, https://doi.org/10.5194/gmd-19-6587-2026, https://doi.org/10.5194/gmd-19-6587-2026, 2026
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To understand how persistent hazardous industrial chemicals travel through the air and are deposited back on Earth's surface, we created a new computer model that combines meteorology and chemistry in clouds and clean air. Using the most recent global emissions data, this model represents the trajectory and changes of these chemicals, matching patterns in many areas and overlooking others. The work seeks to improve global monitoring and modeling of hazardous chemicals.
Friederike Keil, Markus Quante, Bernd Heinold, and Volker Matthias
EGUsphere, https://doi.org/10.5194/egusphere-2026-2934, https://doi.org/10.5194/egusphere-2026-2934, 2026
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Using simulations of two differing rain events, we investigated how sensitive convective precipitation is to urban emission levels by varying emission strengths across a wide range. Low emissions produce only modest effects, but high levels can trigger systematic changes, including substantial increases in ice content and precipitation intensity accompanied by spatial and temporal shifts. The magnitude of these responses depends critically on the prevailing meteorological conditions.
Florian Börgel, Itzel Ruvalcaba Baroni, Leonie Barghorn, Leonard Borchert, Bronwyn Cahill, Cyril Dutheil, Leonie Esters, Małgorzata Falarz, Helena L. Filipsson, Matthias Gröger, Jari Hänninen, Magnus Hieronymus, Erko Jakobson, Mehdi Pasha Karami, Karol Kuliński, Taavi Liblik, H. E. Markus Meier, Gabriele Messori, Lev Naumov, Thomas Neumann, Piia Post, Gregor Rehder, Anna Rutgersson, and Georg Sebastian Voelker
Earth Syst. Dynam., 17, 415–450, https://doi.org/10.5194/esd-17-415-2026, https://doi.org/10.5194/esd-17-415-2026, 2026
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This review explains how weather patterns, guided by the polar jet stream, influence the Baltic Sea’s climate and ecosystem. It covers the North Atlantic Oscillation, blocking events and other processes and discusses how they affect temperature, rainfall, and storms from days to decades. These shifts then impact oxygen levels, productivity, and acidification in the Baltic Sea. Physical links are fairly well known, but biogeochemical pathways remain uncertain.
Thomas Neumann, Gerald Schernewski, and René Friedland
Biogeosciences, 22, 7403–7424, https://doi.org/10.5194/bg-22-7403-2025, https://doi.org/10.5194/bg-22-7403-2025, 2025
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We applied a 3D ecosystem model to the Oder Lagoon in the Baltic Sea and found that 40% of nitrogen and 12% of phosphorus are retained in the lagoon before entering the Baltic Sea. This is important for coarse-grained models that do not resolve such coastal structures. Moreover, the coastal filter supports the mitigation of eutrophication in the Baltic Sea.
Anju Mallissery, Hagen Radtke, Thomas Neumann, and H.E. Markus Meier
EGUsphere, https://doi.org/10.5194/egusphere-2025-4568, https://doi.org/10.5194/egusphere-2025-4568, 2025
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We used a computer model to study how warming affects biological and chemical processes in the Baltic Sea and controls nutrient cycling in its deep basins. We tested changes across the sea and only along the coast. In oxygen-poor waters, a small increase in the processes caused ammonium buildup and enhanced nitrogen removal. In the Bothnian Sea, the coastal zone had an outsized role, sometimes 2 to 4 times greater than basin-wide changes, altering nitrate, phosphate, and productivity.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Henry C. Bittig, Erik Jacobs, Thomas Neumann, and Gregor Rehder
Earth Syst. Sci. Data, 16, 753–773, https://doi.org/10.5194/essd-16-753-2024, https://doi.org/10.5194/essd-16-753-2024, 2024
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We present a pCO2 climatology of the Baltic Sea using a new approach to extrapolate from individual observations to the entire Baltic Sea. The extrapolation approach uses (a) a model to inform on how data at one location are connected to data at other locations, together with (b) very accurate pCO2 observations from 2003 to 2021 as the base data. The climatology can be used e.g. to assess uptake and release of CO2 or to identify extreme events.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
Geosci. Model Dev., 16, 7107–7121, https://doi.org/10.5194/gmd-16-7107-2023, https://doi.org/10.5194/gmd-16-7107-2023, 2023
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Chemical particles in nature have properties such as age or reactivity. Distributions can describe the properties of chemical concentrations. In nature, they are affected by mixing processes, such as chemical diffusion, burrowing animals, and bottom trawling. We derive equations for simulating the effect of mixing on central moments that describe the distributions. We then demonstrate applications in which these equations are used to model continua in disturbed natural environments.
Sarah Piehl, René Friedland, Thomas Neumann, and Gerald Schernewski
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-152, https://doi.org/10.5194/bg-2023-152, 2023
Revised manuscript not accepted
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We integrated observations essential for policy decisions with high-resolution 3D model results to improve the reliability of oxygen assessments. Based on our findings, we suggest merging only high temporal and/or vertical resolution station data with model data to increase confidence in oxygen assessments. While showing the strengths and limitations of our approach we show that model simulations are an useful tool for policy-relevant oxygen assessments.
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
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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.
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
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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.
Matthias Gröger, Manja Placke, H. E. Markus Meier, Florian Börgel, Sandra-Esther Brunnabend, Cyril Dutheil, Ulf Gräwe, Magnus Hieronymus, Thomas Neumann, Hagen Radtke, Semjon Schimanke, Jian Su, and Germo Väli
Geosci. Model Dev., 15, 8613–8638, https://doi.org/10.5194/gmd-15-8613-2022, https://doi.org/10.5194/gmd-15-8613-2022, 2022
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Comparisons of oceanographic climate data from different models often suffer from different model setups, forcing fields, and output of variables. This paper provides a protocol to harmonize these elements to set up multidecadal simulations for the Baltic Sea, a marginal sea in Europe. First results are shown from six different model simulations from four different model platforms. Topical studies for upwelling, marine heat waves, and stratification are also assessed.
Thomas Neumann, Hagen Radtke, Bronwyn Cahill, Martin Schmidt, and Gregor Rehder
Geosci. Model Dev., 15, 8473–8540, https://doi.org/10.5194/gmd-15-8473-2022, https://doi.org/10.5194/gmd-15-8473-2022, 2022
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Marine ecosystem models are usually constrained by the elements nitrogen and phosphorus and consider carbon in organic matter in a fixed ratio. Recent observations show a substantial deviation from the simulated carbon cycle variables. In this study, we present a marine ecosystem model for the Baltic Sea which allows for a flexible uptake ratio for carbon, nitrogen, and phosphorus. With this extension, the model reflects much more reasonable variables of the marine carbon cycle.
Ronny Badeke, Volker Matthias, Matthias Karl, and David Grawe
Geosci. Model Dev., 15, 4077–4103, https://doi.org/10.5194/gmd-15-4077-2022, https://doi.org/10.5194/gmd-15-4077-2022, 2022
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For air quality modeling studies, it is very important to distribute pollutants correctly into the model system. This has not yet been done for shipping pollution in great detail. We studied the effects of different vertical distributions of shipping pollutants on the urban air quality and derived advanced formulas for it. These formulas take weather conditions and ship-specific parameters like the exhaust gas temperature into account.
Sara Jutterström, Filip Moldan, Jana Moldanová, Matthias Karl, Volker Matthias, and Maximilian Posch
Atmos. Chem. Phys., 21, 15827–15845, https://doi.org/10.5194/acp-21-15827-2021, https://doi.org/10.5194/acp-21-15827-2021, 2021
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For the Baltic Sea countries, shipping emissions are an important source of air pollution. This study investigates the contribution of shipping emissions to the acidification and eutrophication of soils and freshwater within the airshed of the Baltic Sea in the years 2012 and 2040. The implementation of emission control areas and improving energy efficiency significantly reduces the negative impact on ecosystems expressed as a decrease in the exceedance of critical loads for sulfur and nitrogen.
Cited articles
Aksoyoglu, S., Baltensperger, U., and Prévôt, A. S. H.: Contribution of ship emissions to the concentration and deposition of air pollutants in Europe, Atmos. Chem. Phys., 16, 1895–1906, https://doi.org/10.5194/acp-16-1895-2016, 2016. a
Andersen, J. H., Halpern, B. S., Korpinen, S., Murray, C., and Reker, J.:
Baltic Sea biodiversity status vs. cumulative human pressures, Estuar.
Coast. Shelf Sci., 161, 88–92, https://doi.org/10.1016/j.ecss.2015.05.002,
2015. a
Andersen, J. H., Carstensen, J., Conley, D. J., Dromph, K., Fleming-Lehtinen,
V., Gustafsson, B. G., Josefson, A. B., Norkko, A., Villnäs, A., and
Murray, C.: Long-term temporal and spatial trends in eutrophication status of
the Baltic Sea, Biol. Rev., 92, 135–149, https://doi.org/10.1111/brv.12221, 2017. a
Appel, K. W., Napelenok, S. L., Foley, K. M., Pye, H. O. T., Hogrefe, C., Luecken, D. J., Bash, J. O., Roselle, S. J., Pleim, J. E., Foroutan, H., Hutzell, W. T., Pouliot, G. A., Sarwar, G., Fahey, K. M., Gantt, B., Gilliam, R. C., Heath, N. K., Kang, D., Mathur, R., Schwede, D. B., Spero, T. L., Wong, D. C., and Young, J. O.: Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1, Geosci. Model Dev., 10, 1703–1732, https://doi.org/10.5194/gmd-10-1703-2017, 2017. a
Bartnicki, J., Semeena, V. S., and Fagerli, H.: Atmospheric deposition of nitrogen to the Baltic Sea in the period 1995–2006, Atmos. Chem. Phys., 11, 10057–10069, https://doi.org/10.5194/acp-11-10057-2011, 2011. a
Bieser, J., Aulinger, A., Matthias, V., Quante, M., and Builtjes, P.: SMOKE for Europe – adaptation, modification and evaluation of a comprehensive emission model for Europe, Geosci. Model Dev., 4, 47–68, https://doi.org/10.5194/gmd-4-47-2011, 2011. a
Binkowski, F. S. and Roselle, S. J.: Models-3 Community Multiscale Air Quality
(CMAQ) model aerosol component 1. Model description, J. Geophys. Res.-Atmos.,
108, 4183, https://doi.org/10.1029/2001JD001409, 2003. a
Binkowski, F. S. and Shankar, U.: The Regional Particulate Matter Model: 1.
Model description and preliminary results, J. Geophys. Res.-Atmos., 100,
26191–26209, https://doi.org/10.1029/95JD02093, 1995. a
Brandt, J., Silver, J. D., Christensen, J. H., Andersen, M. S., Bønløkke,
J. H., Sigsgaard, T., Geels, C., Gross, A., Hansen, A. B., Hansen, K. M.,
Hedegaard, G. B., Kaas, E., and Frohn, L. M.: Assessment of Health-Cost
Externalities of Air Pollution at the National Level using the EVA Model
System, CEEH Scientific Report No 3, Tech. rep., Centre for Energy,
Environment and Health,
2011. a
Buhaug, O., Corbett, J. J., Endresen, O., Eyring, V., Faber, J., Hanayama, S.,
Lee, D., Lee, D., Lindstad, H., Markowaka, A., Mjelde, A., Nelissen, D.,
Nilsen, J., Palsson, C., Winebrake, J., Wu, W., and Yoshida, K.: Second IMO
GHG study, Tech. rep., IMO,
available at: http://www.imo.org/en/OurWork/Environment/PollutionPrevention/AirPollution/Documents/SecondIMOGHGStudy2009.pdf (last access: 13 January 2020),
2009. a
CEIP: WebDab Emission Export of the EU-28 countries divided into SNAP sectors,
available at: https://www.ceip.at/webdab-emission-database (last access: 13 January 2020), 2018. a
Danish EPA: Economic Impact Assessment of a NOx Emission Control Area in the
North Sea, Tech. rep., Danish EPA,
available at: https://www2.mst.dk/Udgiv/publications/2012/06/978-87-92903-20-4.pdf (last access: 13 January 2020),
2012. a
Dulière, V., Gypens, N., Lancelot, C., Luyten, P., and Lacroix, G.: Origin
of nitrogen in the English Channel and Southern Bight of the North Sea
ecosystems, Hydrobiologia, 845,
13–33, https://doi.org/10.1007/s10750-017-3419-5, 2017. a
EMEP: EMEP Status Report 1/2017 “Transboundary particulate matter,
photo-oxidants, acidifying and eutrophying components”, Joint msc-w & ccc &
ceip report, MSC-W & CCC & CEIP,
available at: http://emep.int/publ/reports/2017/EMEP_Status_Report_1_2017.pdf (last access: 13 January 2020),
2017. a
EU-2008/56/EC: Directive 2008/56/EC of the European Parliament and of the
Council on establishing a framework for community action in the field of
marine environmental policy (Marine Strategy Framework Directive), Official
Journal of the European Union,
available at: http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32008L0056 (last access: 13 January 2020),
2008. a
Feistel, R., Nausch, G., and Wasmund, N. (Eds.): State and Evolution of the
Baltic Sea, 1952–2005, Wiley-Interscience, Hoboken, New Jersey, 1st
edn., https://doi.org/10.1002/9780470283134, 2008. a, b
Foley, K. M., Roselle, S. J., Appel, K. W., Bhave, P. V., Pleim, J. E., Otte, T. L., Mathur, R., Sarwar, G., Young, J. O., Gilliam, R. C., Nolte, C. G., Kelly, J. T., Gilliland, A. B., and Bash, J. O.: Incremental testing of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7, Geosci. Model Dev., 3, 205–226, https://doi.org/10.5194/gmd-3-205-2010, 2010. a
Fountoukis, C. and Nenes, A.: ISORROPIA II: a computationally efficient thermodynamic equilibrium model for K+–Ca2+–Mg2+– –Na+– – –Cl−–H2O aerosols, Atmos. Chem. Phys., 7, 4639–4659, https://doi.org/10.5194/acp-7-4639-2007, 2007. a
Geels, C., Hansen, K. M., Christensen, J. H., Ambelas Skjøth, C., Ellermann, T., Hedegaard, G. B., Hertel, O., Frohn, L. M., Gross, A., and Brandt, J.: Projected change in atmospheric nitrogen deposition to the Baltic Sea towards 2020, Atmos. Chem. Phys., 12, 2615–2629, https://doi.org/10.5194/acp-12-2615-2012, 2012. a, b
Geyer, B.: High-resolution atmospheric reconstruction for Europe 1948–2012: coastDat2, Earth Syst. Sci. Data, 6, 147–164, https://doi.org/10.5194/essd-6-147-2014, 2014. a
Geyer, B. and Rockel, B.: coastDat-2 COSMO-CLM Atmospheric Reconstruction,
World Data Center for Climate (WDCC), Hamburg, Germany,
https://doi.org/10.1594/WDCC/coastDat-2_COSMO-CLM,
2013. a, b, c
Geyer, B., Weisse, R., Bisling, P., and Winterfeldt, J.: Climatology of North
Sea wind energy derived from a model hindcast for 1958-2012, J. Wind Eng.
Ind. Aerod., 147, 18–29, https://doi.org/10.1016/j.jweia.2015.09.005,
2015. a
Gong, S. L.: A parameterization of sea-salt aerosol source function for sub-
and super-micron particles, Global Biogeochem. Cy., 17, 1097,
https://doi.org/10.1029/2003GB002079, 2003. a
Griffies, S. M.: Fundamentals of Ocean Climate Models, Princeton University
Press, Princeton, New Jersey,
available at: https://press.princeton.edu/titles/7797.html (last access: 13 January 2020), 2004. a
Große, F., Kreus, M., Lenhart, H.-J., Pätsch, J., and Pohlmann, T.: A
Novel Modeling Approach to Quantify the Influence of Nitrogen Inputs on the
Oxygen Dynamics of the North Sea, Front. Mar. Sci., 4, 383,
https://doi.org/10.3389/fmars.2017.00383,
2017. a
Gustafsson, B. G., Schenk, F., Blenckner, T., Eilola, K., Meier, H. E. M.,
Müller-Karulis, B., Neumann, T., Ruoho-Airola, T., Savchuk, O. P., and
Zorita, E.: Reconstructing the Development of Baltic Sea Eutrophication
1850–2006, AMBIO, 41, 534–548, https://doi.org/10.1007/s13280-012-0318-x, 2012. a
Hammingh, P., Holland, M., Geilenkirchen, G., Jonson, J., and Maas, R.:
Assessment of the environmental impacts and health benefits of a nitrogen
emission control area in the North Sea, Tech. Rep. 500249001, PBL Netherlands
Environmental Assessment Agency, 2012. a
HELCOM: Baltic Sea Action Plan (BSAP), Tech. rep., HELCOM,
available at: http://www.helcom.fi/baltic-sea-action-plan (last access: 13 January 2020), 2007. a
HELCOM: Eutrophication in the Baltic Sea – An integrated thematic assessment
of the effects of nutrient enrichment and eutrophication in the Baltic Sea
region, Balt. sea environ. proc. no. 115b, HELCOM,
available at: http://www.helcom.fi/Lists/Publications/BSEP115B.pdf (last access: 13 January 2020), 2009. a
HELCOM: Summary report on the development of revised maximum allowable inputs
(mai) and updated country allocated reduction targets (cart) of the baltic
sea action plan., Tech. rep., Helcom,
available at: https://helcom.fi/media/documents/Summary-report-on-MAI-CART-1.pdf (last access: 13 January 2020),
2013c. a
HELCOM: Updated Fifth Baltic Sea Pollution Load Compilation (PLC-5.5), Baltic
Sea Environment Proceedings 145, HELCOM,
available at: http://www.helcom.fi/Lists/Publications/BSEP145_Lowres.pdf (last access: 13 January 2020),
2015. a
HELCOM: HELCOM oceanographic data – Baltic Sea Monitoring data, ICES, Copenhagen, available at: https://ocean.ices.dk/helcom/Helcom.aspx (last access: 10 January 2020), 2019. a
Hongisto, M.: Impact of the emissions of international sea traffic on airborne
deposition to the Baltic Sea and concentrations at the coastline,
Oceanologia, 56, 349–372, https://doi.org/10.5697/oc.56-2.349,
2014. a
IOWDB: The oceanographic database of the IOW, Leibniz Institute for Baltic Sea Research, Rostock, Warnemünde, https://www.io-warnemuende.de/iowdb.html (last access: 2020-01-10), 2019. a
Jalkanen, J.-P., Johansson, L., Kukkonen, J., Brink, A., Kalli, J., and Stipa, T.: Extension of an assessment model of ship traffic exhaust emissions for particulate matter and carbon monoxide, Atmos. Chem. Phys., 12, 2641–2659, https://doi.org/10.5194/acp-12-2641-2012, 2012. a
Jonson, J. E., Jalkanen, J. P., Johansson, L., Gauss, M., and Denier van der Gon, H. A. C.: Model calculations of the effects of present and future emissions of air pollutants from shipping in the Baltic Sea and the North Sea, Atmos. Chem. Phys., 15, 783–798, https://doi.org/10.5194/acp-15-783-2015, 2015. a, b
Karl, M., Bieser, J., Geyer, B., Matthias, V., Jalkanen, J.-P., Johansson, L., and Fridell, E.: Impact of a nitrogen emission control area (NECA) on the future air quality and nitrogen deposition to seawater in the Baltic Sea region, Atmos. Chem. Phys., 19, 1721–1752, https://doi.org/10.5194/acp-19-1721-2019, 2019a. a, b, c, d
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, 2019b. a
Kelly, J. T., Bhave, P. V., Nolte, C. G., Shankar, U., and Foley, K. M.: Simulating emission and chemical evolution of coarse sea-salt particles in the Community Multiscale Air Quality (CMAQ) model, Geosci. Model Dev., 3, 257–273, https://doi.org/10.5194/gmd-3-257-2010, 2010. a
Korpinen, S., Meski, L., Andersen, J. H., and Laamanen, M.: Human pressures and
their potential impact on the Baltic Sea ecosystem, Ecol. Indic., 15,
105–114, https://doi.org/10.1016/j.ecolind.2011.09.023,
2012. a
Kuznetsov, I. and Neumann, T.: Simulation of carbon dynamics in the Baltic Sea
with a 3D model, J. Mar. Syst., 111–112, 167–174,
https://doi.org/10.1016/j.jmarsys.2012.10.011,
2013. a
Los, F., Troost, T., and Beek, J. V.: Finding the optimal reduction to meet all
targets – Applying Linear Programming with a nutrient tracer model of the
North Sea, J. Mar. Syst., 131, 91–101, https://doi.org/10.1016/j.jmarsys.2013.12.001,
2014. a
Matthias, V., Aulinger, A., Backes, A., Bieser, J., Geyer, B., Quante, M., and Zeretzke, M.: The impact of shipping emissions on air pollution in the greater North Sea region – Part 2: Scenarios for 2030, Atmos. Chem. Phys., 16, 759–776, https://doi.org/10.5194/acp-16-759-2016, 2016. a
Ménesguen, A., Cugier, P., and Leblond, I.: A new numerical technique for
tracking chemical species in a multi-source, coastal ecosystem, applied to
nitrogen causing Ulva blooms in the Bay of Brest (France), Limnol. Oceanogr.,
51, 591–601, https://doi.org/10.4319/lo.2006.51.1_part_2.0591, 2006. a
Ménesguen, A., Desmit, X., Dulière, V., Lacroix, G., Thouvenin, B.,
Thieu, V., and Dussauze, M.: How to avoid eutrophication in coastal seas? A
new approach to derive river-specific combined nitrate and phosphate maximum
concentrations, Sci. Total Environ., 628–629, 400–414,
https://doi.org/10.1016/j.scitotenv.2018.02.025,
2018. a
Nausch, M., Woelk, J., Kahle, P., Nausch, G., Leipe, T., and Lennartz, B.:
Phosphorus fractions in discharges from artificially drained lowland
catchments (Warnow River, Baltic Sea), Agric. Water Manage., 187, 77–87,
https://doi.org/10.1016/j.agwat.2017.03.006,
2017. a
Neumann, D., Matthias, V., Bieser, J., Aulinger, A., and Quante, M.: Sensitivity of modeled atmospheric nitrogen species and nitrogen deposition to variations in sea salt emissions in the North Sea and Baltic Sea regions, Atmos. Chem. Phys., 16, 2921–2942, https://doi.org/10.5194/acp-16-2921-2016, 2016. a, b
Neumann, D., Matthias, V., Bieser, J., Aulinger, A., and Quante, M.: Sensitivity of modeled atmospheric nitrogen species and nitrogen deposition to variations in sea salt emissions in the North Sea and Baltic Sea regions, Atmos. Chem. Phys., 16, 2921–2942, https://doi.org/10.5194/acp-16-2921-2016, 2016. a
Neumann, D., Karl, M., Radtke, H., and Neumann, T.: MOM-ERGOM western Baltic
Sea simulations with tagging of atmospheric nitrogen deposition by CMAQ,
World Data Center for Climate (WDCC) at DKRZ,
https://doi.org/10.26050/WDCC/MOMERGOMBSCMAQ,
2019. a
Neumann, T.: Towards a 3D-ecosystem model of the Baltic Sea, J. Mar. Syst., 25,
405–419, https://doi.org/10.1016/S0924-7963(00)00030-0,
2000. a
Neumann, T.: The fate of river-borne nitrogen in the Baltic Sea – An example
for the River Oder, Estuar. Coast. Shelf Sci., 73, 1–7,
https://doi.org/10.1016/j.ecss.2006.12.005,
2007. a
Neumann, T. and Schernewski, G.: Eutrophication in the Baltic Sea and shifts in
nitrogen fixation analyzed with a 3D ecosystem model, J. Mar. Syst., 74,
592–602, https://doi.org/10.1016/j.jmarsys.2008.05.003,
2008. a
Neumann, T., Fennel, W., and Kremp, C.: Experimental simulations with an
ecosystem model of the Baltic Sea: A nutrient load reduction experiment,
Global Biogeochem. Cy., 16, 1–19, https://doi.org/10.1029/2001GB001450, 2002. a, b
Neumann, T., Siegel, H., and Gerth, M.: A new radiation model for Baltic Sea
ecosystem modelling, J. Mar. Syst., 152, 83–91,
https://doi.org/10.1016/j.jmarsys.2015.08.001,
2015. a, b
Neumann, T., Radtke, H., and Seifert, T.: On the importance of Major Baltic
Inflows for oxygenation of the central Baltic Sea, J. Geophys. Res.-Oceans, 122
1090–1101,
https://doi.org/10.1002/2016JC012525, 2017. a
Nolte, C. G., Appel, K. W., Kelly, J. T., Bhave, P. V., Fahey, K. M., Collett Jr., J. L., Zhang, L., and Young, J. O.: Evaluation of the Community Multiscale Air Quality (CMAQ) model v5.0 against size-resolved measurements of inorganic particle composition across sites in North America, Geosci. Model Dev., 8, 2877–2892, https://doi.org/10.5194/gmd-8-2877-2015, 2015. a
Paerl, H. W., Dennis, R. L., and Whitall, D. R.: Atmospheric deposition of
nitrogen: Implications for nutrient over-enrichment of coastal waters,
Estuaries, 25, 677–693, https://doi.org/10.1007/BF02804899, 2002. a
Pleim, J., Venkatram, A., and Yamartino, R.: ADOM/TADAP model development
program 4: The dry deposition module, Tech. rep., Ontario Ministry of the
Environment Toronto, Canada, 1984. a
Radtke, H., Neumann, T., Voss, M., and Fennel, W.: Modeling pathways of
riverine nitrogen and phosphorus in the Baltic Sea, J. Geophys. Res.-Oceans,
117, c09024, https://doi.org/10.1029/2012JC008119, 2012. a, b, c
Radtke, H., Neumann, T., and Fennel, W.: A Eulerian nutrient to fish model of
the Baltic Sea – A feasibility-study, J. Mar. Syst., 125, 61–76,
https://doi.org/10.1016/j.jmarsys.2012.07.010, 2013. a
Raudsepp, U., Laanemets, J., Maljutenko, I., Hongisto, M., and Jalkanen, J.-P.:
Impact of ship-borne nitrogen deposition on the Gulf of Finland ecosystem: an
evaluation, Oceanologia, 55, 837–857, https://doi.org/10.5697/oc.55-4.837,
2013. a, b, c, d
Raudsepp, U., Maljutenko, I., outs, M. K., Granhag, L., Wilewska-Bien, M.,
Hassellöv, I.-M., Eriksson, K. M., Johansson, L., Jalkanen, J.-P., Karl,
M., Matthias, V., and Moldanova, J.: Shipborne nutrient dynamics and impact
on the eutrophication in the Baltic Sea, Sci. Total Environ.,
671, 189–207, https://doi.org/10.1016/j.scitotenv.2019.03.264,
2019. a, b, c, d, e, f, g, h, i, j
Rockel, B., Will, A., and Hense, A.: The Regional Climate Model COSMO-CLM
(CCLM), Meteorol. Z., 17, 347–348, https://doi.org/10.1127/0941-2948/2008/0309,
2008. a, b
Sarwar, G., Luecken, D., and Yarwood, G.: Chapter 2.9 Developing and
implementing an updated chlorine chemistry into the community multiscale air
quality model, in: Air Pollution Modeling and its Application XVIII, edited
by Borrego, C. and Renner, E., vol. 6 of Developments in Environmental
Science, pp. 168–176, Elsevier, Amsterdam, the Netherlands,
https://doi.org/10.1016/S1474-8177(07)06029-9,
2007. a
Sarwar, G., Fahey, K., Napelenok, S., Roselle, S., and Mathur, R.: Examining
the impact of CMAQ model updates on aerosol sulfate predictions, in: 10th
Annual CMAS Conference, 24–26 October, 2011 Chapel Hill, NC,
available at: http://www.cmascenter.org/conference/2011/slides/sarwar_examining_impact_2011.pdf (last access: 13 January 2020),
2011. a
Savchuk, O. P.: Large-Scale Nutrient Dynamics in the Baltic Sea, 1970–2016,
Front. Mar. Sci., 5, 95, https://doi.org/10.3389/fmars.2018.00095,
2018. a
Schernewski, G., Friedland, R., Carstens, M., Hirt, U., Leujak, W., Nausch, G.,
Neumann, T., Petenati, T., Sagert, S., Wasmund, N., and von Weber, M.:
Implementation of European marine policy: New water quality targets for
German Baltic waters, Marine Policy, 51, 305–321,
https://doi.org/10.1016/j.marpol.2014.09.002,
2015. a
Simpson, D.: The European Nitrogen Assessment, chap. 14: Atmospheric transport
and deposition of reactive nitrogen in Europe, pp. 298–316, in:
Sutton et al. (2011), available at: http://www.nine-esf.org (last access: 13 January 2020), 2011. a
Slinn, S. and Slinn, W.: Predictions for particle deposition on natural waters,
Atmos. Environ., 14, 1013–1016, https://doi.org/10.1016/0004-6981(80)90032-3,
1980. a
Smith, T. W. P., Jalkanen, J. P., Anderson, B. A., Corbett, J. J., Faber, J.,
Hanayama, S., O'Keeffe, E., Parker, S., Johansson, L., Aldous, L., Raucci,
C., Traut, M., Ettinger, S., Nelissen, D., Lee, D. S., Ng, S., Agrawal, A.,
Winebrake, J. J., Hoen, M., Chesworth, S., and Pandey, A.: Third IMO
Greenhouse Gas Study 2014, Tech. rep., IMO,
http://www.imo.org/en/OurWork/Environment/PollutionPrevention/AirPollution/Documents/Third Greenhouse Gas Study/GHG3 Executive Summary and Report.pdf (last access: 13 January 2020),
2014. a
Sofiev, M., Kouznetsov, R., Prank, M., Soares, J., Vira, J., Tarvainen, V., and
Sofieva, V.: A Long-Term Re-Analysis of Atmospheric Composition and Air
Quality, in: Air Pollution Modeling and its Application XXV, edited by
Mensink, C. and Kallos, G., pp. 55–59, Springer International Publishing,
Cham, https://doi.org/10.1007/978-3-319-57645-9_9,
2018. a
St-Laurent, P., Friedrichs, M. A. M., Najjar, R. G., Martins, D. K., Herrmann,
M., Miller, S. K., and Wilkin, J.: Impacts of Atmospheric Nitrogen Deposition
on Surface Waters of the Western North Atlantic Mitigated by Multiple
Feedbacks, J. Geophys. Res.-Oceans, 122, 8406–8426,
https://doi.org/10.1002/2017JC013072,
2017. a
Stipa, T., Jalkanen, J.-P., Hongisto, M., Kalli, J., and Brink, A.: Emissions
of NOx from Baltic Shipping and first Estimates of their Effects on Air
Quality and Eutrophication of the Baltic Sea, Project report, Finnish
Meteorological Institute, available at: http://hdl.handle.net/10138/1209 (last access: 13 January 2020),
2007. a
Stålnacke, P., Grimvall, A., Sundblad, K., and Tonderski, A.: Estimation of
riverine loads of nitrogen and phosphorus to the Baltic Sea, 1970–1993,
Environ. Monit. Assess., 58, 173–200, https://doi.org/10.1023/A:1006073015871, 1999. a
Sutton, M. A., Howard, C. M., Erisman, J. W., Billen, G., Bleeker, A.,
Grennfelt, P., van Grinsven, H., and Grizzetti, B. (Eds.): The European
Nitrogen Assessment, Cambridge University Press, New York,
available at: http://www.nine-esf.org (last access: 13 January 2020), 2011. a
Svendsen, L. M., Pyhälä, M., Gustafsson, B., Sonesten, L., and
Knuuttila, S.: Inputs of nitrogen and phosphorus to the Baltic Sea. HELCOM
core indicator report,
available at: http://www.helcom.fi/Documents/Baltic sea trends/Eutrophication/CORE_indicator_nutrient_inputs_1995-2012.pdf (last access: 30 June 2017),
2015. a, b, c, d, e, f
Troost, T., Blaas, M., and Los, F.: The role of atmospheric deposition in the
eutrophication of the North Sea: A model analysis, J. Mar. Syst., 125,
101–112, https://doi.org/10.1016/j.jmarsys.2012.10.005, 2013. a
Tsyro, S. G. and Berge, E.: Estimation Of Acidifying Deposition In Europe Due
To International Shipping Emissions In The North Sea And The North East
Atlantic Ocean, WIT Trans. Ecol. Environ., 25, 175–184,
available at: https://www.witpress.com/Secure/elibrary/papers/CENV98/CENV98017FU.pdf (last access: 13 January 2020),
1998. a, b
Vivanco, M., Bessagnet, B., Cuvelier, C., Theobald, M., Tsyro, S., Pirovano,
G., Aulinger, A., Bieser, J., Calori, G., Ciarelli, G., Manders, A., Mircea,
M., Aksoyoglu, S., Briganti, G., Cappelletti, A., Colette, A., Couvidat, F.,
D'Isidoro, M., Kranenburg, R., Meleux, F., Menut, L., Pay, M., Rouïl, L.,
Silibello, C., Thunis, P., and Ung, A.: Joint analysis of deposition fluxes
and atmospheric concentrations of inorganic nitrogen and sulphur compounds
predicted by six chemistry transport models in the frame of the EURODELTAIII
project, Atmos. Environ., 151, 152–175,
https://doi.org/10.1016/j.atmosenv.2016.11.042,
2017. a, b
Wasmund, N.: Occurrence of cyanobacterial blooms in the baltic sea in relation
to environmental conditions, Internationale Revue der gesamten Hydrobiologie
und Hydrographie, 82, 169–184, https://doi.org/10.1002/iroh.19970820205,
1997. a
Weisse, R., Bisling, P., Gaslikova, L., Geyer, B., Groll, N., Hortamani, M.,
Matthias, V., Maneke, M., Meinke, I., Meyer, E. M., Schwichtenberg, F.,
Stempinski, F., Wiese, F., and Wöckner-Kluwe, K.: Climate services for
marine applications in Europe, Earth Perspect., 2, 1–14,
https://doi.org/10.1186/s40322-015-0029-0, 2015. a
Whitten, G. Z., Heo, G., Kimura, Y., McDonald-Buller, E., Allen, D. T., Carter,
W. P., and Yarwood, G.: A new condensed toluene mechanism for Carbon Bond:
CB05-TU, Atmos. Environ., 44, 5346–5355,
https://doi.org/10.1016/j.atmosenv.2009.12.029,
2010.
a
Wu, Q. Z., Wang, Z. F., Gbaguidi, A., Gao, C., Li, L. N., and Wang, W.: A numerical study of contributions to air pollution in Beijing during CAREBeijing-2006, Atmos. Chem. Phys., 11, 5997–6011, https://doi.org/10.5194/acp-11-5997-2011, 2011. a
Yarwood, G., Rao, S., Yocke, M., and Whitten, G. Z.: Updates to the Carbon Bond
Chemical Mechanism: CB05, Final report to project rt-04-00675, U.S.
Environmental Protection Agency, Research Triangle Park, NC 27703,
available at: http://www.camx.com/files/cb05_final_report_120805.aspx (last access: 13 January 2020),
2005. a
Zhang, Y., Song, L., Liu, X., Li, W., Lü, S., Zheng, L., Bai, Z., Cai, G.,
and Zhang, F.: Atmospheric organic nitrogen deposition in China, Atmos.
Environ., 46, 195–204, https://doi.org/10.1016/j.atmosenv.2011.09.080,
2012. a
Short summary
The study evaluates how much bioavailable nitrogen is contributed to the nitrogen budget of the western Baltic Sea by deposition of shipping-emitted nitrogen oxides. Bioavailable nitrogen compounds are nutrients for phytoplankton (algae). Excessive input of nutrients into water bodies may lead to eutrophication: more algal blooms with subsequently more oxygen limitation at the seafloor. Hence, reducing shipping emissions might reduce the anthropogenic pressure on the marine ecosystem.
The study evaluates how much bioavailable nitrogen is contributed to the nitrogen budget of the...