High resolution mapping of total deposition of acidifying pollutants
Highlights
► A framework is developed to map high resolution acid deposition in Southern Belgium. ► Results for 2008–2009 are compared with results of long range transport (LRT) models. ► There is a good agreement between the annual totals averaged over Southern Belgium. ► The framework provides consistent deposition patterns for several pollutants. ► The framework provides higher resolution deposition maps than LRT models.
Introduction
Dry and wet deposition processes are fundamental removal mechanisms for tropospheric substances, both gaseous and in the form of aerosols (Ruijrok et al., 1995; Wesely and Hicks, 2000; Petroff et al., 2008). The deposition of these substances and their penetration in the soil and the vegetation can lead to a variety of perturbations of the ecosystem, e.g. acidification, eutrophication, destruction of the crops (Bobbink et al., 2010; Sutton et al., 2011; Bell, 1986). The understanding of the wet and dry deposition processes is therefore essential to assess these environmental impacts and eventually prevent them.
Our main concern here are the atmospheric substances involved in the evaluation of the “total potential acid deposition”, as defined in the context of the UNECE LRTAP convention (UNECE Convention on Long-Range Transboundary Air Pollution, 2004). These substances include gases, e.g. nitrogen dioxide NO2, sulfur dioxide SO2, ammonia NH3, nitric acid vapor HNO3 (and in a lesser extent, nitrogen monoxide NO) and aerosols, e.g. ammonium NH4+, nitrate NO3− and sulfate SO42−. Deposition of base cations is also needed in order to assess the critical loads, but will not be addressed in the present study.
In Belgium, deposition is currently estimated using emission-based long range transport (LRT) eulerian models, such as EMEP (Simpson et al., 2003) or BelEUROS (cf. for example, Deutsch, 2008). Despite the advantages of such models, this approach suffers from one systematical flaw: the value of the critical loads exceedances is strongly dependent on the spatial scale of the grid on which both the deposition and these loads are mapped (Bak, 2001; Smith et al., 1995; Spranger et al., 2001). Such models calculate deposition patterns across Europe, while inferential (high resolution) models are used to compute deposition patterns across a country or region. No detailed inferential model exists for Southern Belgium, and the purpose of the present study is to fill this gap.
The purpose of the present study is firstly to construct a framework that can provide high resolution wet and dry deposition estimates over Southern Belgium for various pollutants (on a 5 × 5 km2 grid), secondly to present the resulting maps using 2008 and 2009 data, and finally to evaluate the maps by comparing the results with LRT model outputs. The framework will make use of pollutants concentrations in the air and in the precipitation, measured in the different networks and on merged radar-gauge rain observations (Goudenhoofdt and Delobbe, 2009). Time- and space-dependent dry deposition velocities are computed using the models described in Zhang et al., 2001, Zhang et al., 2003, with local meteorological data from the ALADIN model run at the Royal Meteorological Institute of Belgium (www.kmi.be), as well as assimilated ALADIN fields (Brasseur et al., 2004).
In the following sections, our methodology is detailed in Section 2, results are detailed in Section 3 and major conclusions are summarized in Section 4.
Section snippets
Measurement networks
A number of pollutants of interest have been measured in regional networks in Belgium (Fig. 1). SO2 is measured in the regional telemetric networks, covering the whole country and yielding concentrations every hour (i.e. the mean of two half-hourly values). In 2008, 70 stations have measured SO2 concentrations in Belgium. Considering the area of Belgium (30,528 km2), the telemetric network is quite dense. The NOx ≡ NO + NO2 are measured in the telemetric networks, like the SO2, on a hourly
Results
Deposition of the different pollutants is computed for the years 2008 and 2009 on a 5 × 5 km2 grid. The time step for the computation varies from pollutant to pollutant, ranging from one hour for SO2 and NOx to one week for precipitation ions, as explained in Section 2.1.
Conclusions
We have developed a framework for the computation of wet and dry deposition over Southern Belgium. Improvements on the previous framework both for inferential modeling and wet deposition estimation include computation of time- and space-dependent deposition velocities for gases and aerosols, on the basis of local meteorology (ALADIN) and land use (COSW), incorporation of a modified kriging interpolation method (RIO), and high resolution radar-based precipitation data.
This framework produces
Acknowledgments
We would like to thank the two anonymous referees for their constructive comments and suggestions. T. de Vos acknowledges O. Brasseur for his kind advice concerning meteorological data treatment, D. Andrieux for his numerous insightful comments, the IRM for providing the precipitation data and the ISSeP for the land use data.
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