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Atmospheric scavenging processes have been investigated, taking into consideration a numerical simulation through the model Regional Atmospheric Modeling System (RAMS), the below-cloud scavenging model, local atmospheric conditions and local emissions in the Serra do Mar region in southeastern Brazil. The RAMS modeling was coupled with a one-dimensional (1-D) below-cloud scavenging model in order to simulate the in-cloud and below-cloud scavenging processes. RAMS modeling was also used in order to simulate the cloud structures. The aim of the modeling was to predict the average concentration of three chemical species found in rainwater: SO4=, NO3− and NH4+, scavenged from the atmosphere. The concentrations of gases and particles in the samplings, as well as the meteorological parameters obtained during the March 1993 Campaign, were the input data in both models. Another objective was to compare the modeled and the observed rainwater and determine the variability in concentration. Rainwater was obtained by using fractionated rain samplers. Variability was determined through chemical analysis. Urban and rural aerosol spectra modeling were also used in order to compare the rainwater concentration species variability. When both in-cloud and below-cloud processes are included, the general result of the March 1993 events presents a better agreement between modeled and observed data sets than only below-cloud. Preliminary results lead us to conclude that the rainwater variability of nitrate is explained by the scavenging of particles from urban spectrum size distribution, whereas rural spectra explain ammonium rainwater variability—indicating the different sources of those species. Comparing to the March 1992 events, these case studies present a significant contribution from the in-cloud scavenging, supported by the Weather Radar maps and RAMS modeling. In particular, the almost constant rainwater concentrations on 16 March (an indication of strong in-cloud contribution) are related to the rainfall event, which crossed the study area on that day. These results add an important understanding to the atmospheric wet removal processes in the region studied. [Copyright &y& Elsevier]