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This work is part of the IDAF program (IGAC-DEBITS-AFRICA) and is based onthe long-term monitoring of gas concentrations (1998–2007) established atseven remote sites representative of major African ecosystems. Drydeposition fluxes were estimated by the inferential method using on the one handsurface measurements of gas concentrations (NO2, HNO3, NH3,SO2 and O3) and on the other hand modeled exchange rates. Drydeposition velocities (Vd) were calculated using the big-leaf model ofZhang et al. (2003b). The bidirectional approach is used for NH3surface–atmosphere exchange (Zhang et al., 2010). Surface and meteorologicalconditions specific to IDAF sites have been used in the models ofdeposition. The seasonal and annual mean variations of gaseous drydeposition fluxes (NO2, HNO3, NH3, O3 and SO2) areanalyzed. Along the latitudinal transect of ecosystems, the annual mean dry depositionfluxes of nitrogen compounds range from −0.4 to −0.8 kg N ha−1 yr−1for NO2, from −0.7 to −1.0 kg N ha−1 yr−1 for HNO3 andfrom −0.7 to −8.3 kg N ha−1 yr−1 for NH3 over the study period(1998–2007). The total nitrogen dry deposition flux(NO2+HNO3+NH3) is more important in forests (−10 kg N ha−1 yr−1)than in wet and dry savannas (−1.6 to −3.9 kg N ha−1 yr−1).The annual mean dry deposition fluxes of ozonerange between −11 and −19 kg ha−1 yr−1 in dry and wet savannas,and −11 and −13 kg ha−1 yr−1 in forests. Lowest O3 drydeposition fluxes in forests are correlated to low measured O3concentrations, lower by a factor of 2–3, compared to other ecosystems.Along the ecosystem transect, the annual mean of SO2 dry deposition fluxespresents low values and a small variability (−0.5 to −1 kg S ha−1 yr−1).No specific trend in the interannual variabilityof these gaseous dry deposition fluxes is observed over the study period

atmospheric chemistry and physics

Dry deposition of nitrogen compounds (NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;, HNO&amp;lt;sub&amp;gt;3&amp;lt;/sub&amp;gt;, NH&amp;lt;sub&amp;gt;3&amp;lt;/sub&amp;gt;), sulfur dioxide and ozone in west and central African ecosystems using the inferential method