Deposition of nitrogen into the North Sea

Leeuw, G. de; Skjøth, Carsten Ambelas; Hertel, Ole; Jickells, Tim; Spokes, L.; Vignati, E.; Frydendall, Jan; Schulz, Mıchael; Tamm, Susanne; Sørensen, Lise Lotte; Kunz, G.J.

doi:10.1016/s1352-2310(03)00246-2

Cited by 34 publications

(21 citation statements)

References 33 publications

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“…Many studies cover the region but do not report estimates specifically for the Baltic Sea or for the surrounding catchment. Hongisto et al (2003) Several modelling studies have specifically addressed the deposition of Nr to the Baltic Sea and surrounding areas (de Leeuw et al 2001(de Leeuw et al , 2003Hertel et al 2002;Schlunzen and Meyer 2007;Bartnicki and Fagerli 2008;Langner et al 2009;Bartnicki et al 2011;Geels et al 2012b). As illustrated in Figs.…”

Section: Modelled Concentrations and Depositionmentioning

confidence: 99%

Environmental Impacts—Atmospheric Chemistry

Simpson

Bartnicki

Jalkanen

et al. 2015

Regional Climate Studies

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This chapter addresses sources and trends of atmospheric pollutants and deposition in relation to the Baltic Sea region. Air pollution is shown to have important effects, including significant contributions to nitrogen loading of the Baltic Sea area, ecosystem impacts due to acidifying and eutrophying pollutants and ozone, and human health impacts. Compounds such as sulphate and ozone also have climate impacts. Emission changes have been very significant over the past 100 years, although very different for land-and sea-based sources. Land-based emissions generally peaked around 1980-1990 and have since reduced due to emissions control measures. Emissions from shipping have been steadily increasing for decades, but recent measures have reduced sulphur and particulate emissions. Future developments depend strongly on policy developments. Changes in concentration and deposition of the acidifying components generally follow emission changes within the European area. Mean ozone levels roughly doubled during the twentieth century across the northern hemisphere, but peak levels have reduced in many regions in the past 20 years. The main changes in air pollution in the Baltic Sea region are due to changes in emissions rather than to climate change.

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Section: Modelled Concentrations and Depositionmentioning

confidence: 99%

Environmental Impacts—Atmospheric Chemistry

Simpson

Bartnicki

Jalkanen

et al. 2015

Regional Climate Studies

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“…Although the Eulerian approach is powerful and widely used for elucidating the chemical and physical mechanism in the atmosphere, the Lagrangian approach demonstrates key advantages in presenting sub-grid scale process, minimizing numerical diffusion, artificial dilution and computing resources. The Lagrangian approach has been widely adopted in various models in atmospheric ammonia modeling such as the FRAME model (Singles et al, 1998;Kryza et al, 2011;Zhang et al, 2011), the TREND model (Asman and van Jaarsveld, 1992;Asman, 2001), the ACDEP model (Hertel et al, 1995Gyldenkoerne et al, 2005;de Leeuw et al, 2003;Skjøth et al, 2002Skjøth et al, , 2004Skjøth et al, , 2011, The TERN model (ApSimon et al, 1994), and the NAME model (Redington and Derwent, 2002). Most existing Lagrangian models for atmospheric ammonia modeling are either box-based models or use a simplified dry chemical scheme.…”

Section: Wen Et Al: Modeling Atmospheric Ammonia and Ammoniummentioning

confidence: 99%

“…For simplicity all point sources were treated as surface sources, which is reasonable for NH 3 emissions. We also incorporated the Models-3 Input/Output Application Programming Interface (IOAPI) (Coats, 2003) into the model to read in emissions fields directly from SMOKE output files.…”

Section: Emissions Datasets and Processingmentioning

confidence: 99%

“…Ratio-of-the-means (ROM) values presented in Table 3 indicate that the model predicted means of p-NH 4 measurements very well, with a 2 % to 8 % over-prediction. One of the possible causes of the over-prediction is that the CAPMoN p-NH + 4 observations measured by a filter-pack system are likely to be lower than actual values because captured NH 4 NO 3 can be subject to volatility issues (Cheng and Tsai, 1997;Zhang and McMurry, 1987). The statistics in Table 3 also show that there is no significant difference in model performance between sites in agricultural regions (Egbert and Longwoods) and those in forest regions (Sprucedale and Chalk River) for p-NH + 4 simulations, in part because p-NH + 4 , unlike NH 3 , is a secondary (regional) pollutant and has smaller spatial gradients.…”

Section: P-nhmentioning

confidence: 99%

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Modeling atmospheric ammonia and ammonium using a stochastic Lagrangian air quality model (STILT-Chem v0.7)

et al. 2013

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Abstract.A new chemistry module that simulates atmospheric ammonia (NH 3 ) and ammonium (NH + 4 ) was incorporated into a backward-in-time stochastic Lagrangian air quality model (STILT-Chem) that was originally developed to simulate the concentrations of a variety of gas-phase species at receptors. STILT-Chem simulates the transport of air parcels backward in time using ensembles of fictitious particles with stochastic motions, while accounting for emissions, deposition and chemical transformation forward in time along trajectories identified by the backward-in-time simulations. The incorporation of the new chemistry module allows the model to simulate not only gaseous species, but also multi-phase species involving NH 3 and NH were compared with observations, which show broad agreement between simulated concentrations and observations. Since the model is based on back trajectories, the influence of each major process such as emission, deposition and chemical conversion on the concentration of a modeled species at a receptor can be determined for every upstream location at each time step. This makes it possible to quantitatively investigate the upstream processes affecting receptor concentrations. The modeled results suggest that the concentrations of NH 3 at those sites were significantly and frequently affected by Ohio, Iowa, Minnesota, Michigan, Wisconsin, southwestern Ontario and nearby areas. NH 3 is mainly contributed by emission sources whereas particulate NH + 4 is mainly contributed by the gas-to-aerosol chemical conversion of NH 3 . Dry deposition is the largest removal process for both NH 3 and particulate NH + 4 . This study revealed the contrast between agricultural versus forest sites. Not only were emissions of NH 3 higher, but removal mechanisms (especially chemical loss for NH 3 and dry deposition for NH + 4 ) were less efficient for agricultural sites. This combination explains the significantly higher concentrations of NH 3 and particulate NH + 4 observed at agricultural sites.

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“…Thus areas more than a few hundred km from sources receive most of their N r deposition in precipitation (Bartnicki et al, 2011;de Leeuw et al, 2003;Hertel et al, 2003), except possibly for forests whose aerodynamic roughness maximises dry deposition. Simpson et al (2006) presented calculations of the wet and dry fraction of both oxidised and reduced nitrogen over Europe, calculated with the EMEP MSC-W model for the year 2000.…”

Section: Distribution Between Dry and Wet Depositionmentioning

confidence: 99%