Parametrization of surface resistance for the quantification of atmospheric deposition of acidifying pollutants and ozone

Ozone dry deposition measurements were carried out during approximately one year over a #at grass "eld in Portugal. The results show prominent diurnal and seasonal patterns in deposition #ux, dry deposition velocity and surface resistance, especially for the daytime period. Dry deposition velocities vary diurnally from a minimum of 0.1 cm s\ , during the night to a maximum of 0.2}0.5 cm s\ during the day. The observed canopy resistance (R ) varies from values higher than 500 s m\ , at night, to a minimum of 200 s m\ , around noon. Seasonal variation is characterised by daytime R values much larger in summer than in winter and spring, while nighttime values do not show any evident seasonal pattern. This behaviour can be ascribed to the stomatal intake, which represents the most important controlling factor on ozone dry deposition. The Wesely parameterisation scheme of surface resistance predicts R diurnal cycles reasonably well. However, the observed canopy resistance seasonal cycle is completely di!erent from Wesely predictions, since season parameters in Wesely's parameterisation were de"ned for a vegetation growing cycle di!erent from that prevailing in our conditions.

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“…Aerodynamic and quasi-laminar resistances were computed according to formulation presented in Erisman et al (1994a):…”

Section: Methodsmentioning

confidence: 99%

“…By computing < B , R and R , directly from micro-meteorological measurements Erisman et al, 1994a), the overall canopy resistance, R , can be derived from Eq. (2).…”

Section: Dry Deposition Modellingmentioning

confidence: 99%

Seasonal variability of ozone dry deposition under southern European climate conditions, in Portugal

Pio

Feliciano

Vermeulen

et al. 2000

Atmospheric Environment

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“…The dry deposition of gases and aerosols is parametrised by the surface-atmosphere interaction model DEPAC (Erisman et al, 1994). From a 1.1×1.1 km 2 resolution land use database the fraction of surface in each grid cell covered by the land use classes used in DEPAC have been calculated (Nijenhuis and Groten, 1999).…”

Section: Removal Processes and Boundary Conditionsmentioning

confidence: 99%

Secondary inorganic aerosol simulations for Europe with special attention to nitrate

Loon²,

et al. 2004

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Abstract.Nitrate is an important component of (secondary inorganic) fine aerosols in Europe. We present a model simulation for the year 1995 in which we account for the formation of secondary inorganic aerosols including ammonium sulphate and ammonium nitrate, a semi volatile component. For this purpose, the chemistry-transport model LOTOS was extended with a thermodynamic equilibrium module and additional relevant processes to account for secondary aerosol formation and deposition. During winter, fall and especially spring high nitrate levels are projected over north western, central and eastern Europe. During winter nitrate concentrations are highest in Italy, in accordance with observed data. In winter nitric acid, the precursor for aerosol nitrate is formed through heterogeneous reactions on the surface of aerosols. Modelled and observed sulphate concentrations show little seasonal variation. Compared to sulphate levels, appreciable ammonium nitrate concentrations in summer are limited to those areas with high ammonia emissions, e.g. the Netherlands, since high ammonia concentrations are necessary to stabilise this aerosol component at high temperatures. As a consequence of the strong seasonal variation in nitrate levels the AOD depth of nitrate over Europe is especially significant compared to that of sulphate in winter and spring when equal AOD values are calculated over large parts of Europe. Averaged over all stations the model reproduces the measured concentrations for NO 3 , SO 4 , NH 4 , TNO 3 (HNO 3 +NO 3 ), TNH 4 (NH 3 +NH 4 ) and SO 2 within 20%. The daily variation is captured well, albeit that the model does not always represent the amplitude of single events. The model underestimates wet deposition which was attributed to the crude representation of cloud processes.Comparison of retrieved and computed aerosol optical depth (AOD) showed that the model underestimates AOD signifiCorrespondence to: M. Schaap (m.schaap@mep.tno.nl) cantly, which was expected due to the lack of carbonaceous aerosols, sea salt and dust in the model. The treatment of ammonia was found to be a major source for uncertainties in the model representation of secondary aerosols. Also, inclusion of sea salt is necessary to properly assess the nitrate and nitric acid levels in marine areas.

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“…Turbulent and laminar resistance are calculated following Padro (1993) from surface roughness, Monin-Obukhov length, friction velocity, molecular diffusivity. Surface resistance is computed following Erisman and Pul (1994) for different surfaces (leaves, soils, . .…”

Section: Dry and Wet Depositionmentioning

confidence: 99%

PM measurement campaign HOVERT in the Greater Berlin area: model evaluation with chemically specified particulate matter observations for a one year period

et al. 2007

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Abstract. The HOVERT (HOrizontal and VERtical Transport of ozone and particulate matter) campaign held in the Berlin Brandenburg area in Eastern Germany from September 2001 to September 2002 allowed to collect a unique data set of the aerosol chemical speciation (daily averages) at traffic, urban and rural sites. These observations are used for a thorough evaluation of the aerosol part in the REM-CALGRID model (RCG) developed at the Free University of Berlin (FUB). For inorganic ions (sulphate, nitrate and ammonium), simulated annual averages agree to observations within ±30% at more than half of the sites and always within a factor of two. Correlation coefficients are larger than in previous studies for SO 2− 4 and NH + 4 (>0.7). For nitrate, less elevated correlations, 0.4-0.7 in the cold season, 0.2-0.4 in the warm season, are encountered. To our knowledge, this is one of the first comparisons of air quality model simulated elemental and organic carbon (EC and OC) with daily observations for a whole year. It suggests an overestimation of EC and OC emissions in the Berlin area (through a scaling techniques between EC, OC and NO x and when assuming correct NO x emissions), and an underestimation of EC and OC at rural sites. Secondary organic aerosol (SOA) formation, recently introduced into the model (SORGAM module, Schell et al., 2001), is simulated as a very variable process, SOA levels varying from close to zero for most days to more than 5 µg/m 3 . Correlation between simulated SOA to observed OC is about 0.6, indicating that simulated variability partly corresponds to reality.

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Parametrization of surface resistance for the quantification of atmospheric deposition of acidifying pollutants and ozone

Cited by 345 publications

References 53 publications

Seasonal variability of ozone dry deposition under southern European climate conditions, in Portugal

Seasonal variability of ozone dry deposition under southern European climate conditions, in Portugal

Secondary inorganic aerosol simulations for Europe with special attention to nitrate

PM measurement campaign HOVERT in the Greater Berlin area: model evaluation with chemically specified particulate matter observations for a one year period

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