IN-CLOUD AND BELOW-CLOUD SCAVENGING ANALYSIS OF SULFATE IN THE METROPOLITAN AREA OF SÃO PAULO , BRAZIL

The Metropolitan Area of São Paulo (MASP) is one of the largest urban centers in the world. The MASP raise serious air-quality concerns. In this study, we consider gases, particulate matter (PM) and cloud processes, with a focus on sulfate chemistry. The Regional Atmospheric Modeling System mesoscale numerical model was used in conjunction with detailed scavenging models to compare varying PM mass spectra and size distributions. Field data were collected during the July 1989-May observed results which improved the scavenging numerical modeling. Correlations between modeled and observed concentrations were better when the model included rural and adjusted-urban spectra, suggesting locally dominant below-cloud scavenging. Spatial variability analysis and numerical modeling also revealed that the varying sulfate rainwater concentrations indicate below-cloud removal process dominance.


INTRODUCTION
Most current knowledge on acid deposition was studies by both American and European researchers from various the atmosphere (Cowling, 1982).In the atmosphere, sulfur liquid phases, forming NO 3 -and SO 4 2- . These ionic pollutants are typically anthropogenic (from industrial and transportation sources) and are considered to play an important role in the formation of acid rain (Minoura and Iwasaka, 1996).More recently, various studies analyzing the chemical composition of rainwater have been conducted worldwide.Most of these studies have evaluated sulfur compounds, nitrogen compounds and the pH in bulk precipitation (Cowling, 1982).
Within the same rainfall event, chemical species concentrations can present marked temporal variations.Therefore, sequential sampling during a precipitation event is essential to the evaluation of scavenging processes.Precipitation chemistry is especially useful in the development and evaluation of acidic deposition models, which are designed to simulate and predict the removal process.Among studies evaluating the chemical composition of rainwater as well as scavenging events (monthly, weekly, daily or per-event) than on the sequential sampling of precipitation (Baez et al., 1992, Poissant and Beron, 1992, Lim et al., 1991, Durana et al., 1992).Various and, consequently, rainwater concentrations.These factors include the type of cloud, the type of precipitation, the air mass trajectory and the solubility of gaseous species, as well as the nature, size and shape of hydrometeors involved in in-cloud and below-cloud scavenging processes.
In recent years, models of in-cloud and below-cloud scavenging processes for air pollutants have been evaluated by some authors who have shown the relevance of inter-compartment transfer from the atmosphere to the hydrosphere.Numerical modeling studies have also been conducted simulating reservoir transfer in many regions around the world, especially in the most heavily polluted areas.However, very few studies have been carried out in tropical areas.The importance of these regions is based on the faster hydrological cycle where the total amount of rainfall is usually quite high.strong impact on ground-level concentrations of those elements in rainwater.The inclusion of in-cloud data was instrumental in the improved modeling of scavenging processes seen in that study.The authors employed the Regional Atmospheric Modeling System (RAMS) mesoscale atmospheric model, which addresses the spatial and temporal evolution of cloud microphysics within rainfall systems.This model is particularly useful in the analysis of cloud liquid water content, as well as the cloud droplet spectrum and vertical dimensions thereof.
On the other hand, the metropolitan area of São Paulo (MASP) is also in a tropical area, at Southeastern Brazil and faces serious air-quality problems.Through an array of numerous government-funded automatic air-quality monitoring stations, key air pollutants in the area have been measured since 1973 and continuously evaluated since 1981 (CETESB, 2003).The main source of air pollutants in São Paulo is mobile emissions from both generated from the burning of fuel used in internal-combustion emissions is attributable to industrial sources.Within the MASP, 2,000 companies (a small fraction of the total) are responsible Over the past several years, the levels of primary air pollutants have decreased but the levels of primary air pollutants have decreased but events with high levels of NO 2 , CO, particulate material and ozone still take place.Atmospheric ozone concentrations in the ozone concentrations in the protective of public health by the World Health Organization.In the 150 g/m 3 24h (CETESB, 2003).
Obviously, air pollution in the MASP is quite broad in scope and is a serious public health problem.Nevertheless, there is no regular program of wet deposition evaluation and data on rainwater composition are scarce and sampling campaigns are sporadic (Forti et al., 1990, Fornaro et al., 1993, Paiva et al., 1997).Many studies have been conducted based on wet-only precipitation between November 1988 and June 1990 (Fornaro et al., 1993, Fornaro, 1991) volume-weighted mean pH of 4.6 for rainwater.This is similar to the pH of 4.5 recorded in another study carried out from September 1993 to May 1994 (Paiva et al., 1997).
According to the monitoring air quality data (CETESB g m -3 (in 1990) to 20 g m -3 (in 2000) in MASP area.This drop can be attributed to enhanced control over sulfur emissions, owing to the enforcement of two governmental regulations: mandatory low sulfur content in diesel and gasohol, and controlled percentages As a consequence, sulfate in rainwater has also decreased, from 24.8 mol L -1 (in 1989, Fornaro et al. 1993) to 9.5 mol L -1 (in 2000).Therefore, enforcement of governmental regulations has proven effective during the last decade.
the Serra do Mar rainforest, nearby MASP (Klockow et al., 1996).Based on data, obtained during a March 1992 campaign from this study and conducted in the Cubatão region (a highly industrialized two numerical modeling studies of cloud processes: with RAMS (Regional Atmospheric Mesoscale Modeling) and a model called whereas the second (in 2002) analyzed in-cloud scavenging where this last model (B.v.2) was developed.The results showed that below-cloud scavenging dominated the scenario in the rain events studied.Because Cubatão is located at the base of a mountain (in the Serra do Mar range) and is surrounded by dispersion of atmospheric pollutants.As a result, the soil and vegetation have suffered the impact of the pollution, mainly due to the air-water transport.The high annual rainfall rates, which can reach 4,500 mm, contribute to this effect.The results of the that RAMS in-cloud scavenging simulations proved quite useful.Therefore, RAMS-based numerical modeling has demonstrated its value in the investigation of scavenging processes, contributing to the understanding of wet deposition.It is important to note that atmospheric wet deposition is quite relevant to inter-compartment global, modeling studies.
The main goal of the present paper is a preliminary investigation of sulfur transfer from the atmosphere to the hydrosphere in the MASP region, with a focus on whether the local or remote effect, through the RAMS numerical modeling paper should be on the overall improvement knowledge about the sulfur transferences at the studied region as well as the scavenging numerical modeling.

Experimental Sites
the "Parque Estadual das Fontes do Ipiranga (PEFI)" and the other on the University of São Paulo campus (Cidade measuring air humidity, temperature, wind direction, and others.The PEFI station is situated at 23.39°S and 46.37°W at an altitude of 800 m, southeast of the city center.The campus is situated at 23.34 o S and 46.44 o W, near the city center, at 15 km apart.There were two main campaigns, July 1989 (only at USP) and July 2000 (at USP and PEFI), which will be compared herein.
It is important to note that MASP area has a subtropical climate with rainfall 1400 mm per year, mainly from December to March (summer period).In the wintertime the weather is characterized by dry conditions, thermal inversions and events of high air pollutants concentrations.

Rain and aerosol sampling: observed and input data
Specific collectors, placed in both locations, were used to gather rainwater samples (wet-only), that were then analyzed for sulfate.In the 1989 campaign, a DIONEX 4000i -1 of Na 2 CO 3 and 3.9 mmol L -1 of NaHCO 3 of 1 mL min -1 regenerant solution of 20 mmol L -1 H 2 SO 4 were also used.The (Fornaro, 1991).
In the 2000 campaign, rainwater sulfate was determined by capillary zone electrophoresis using contact-less conductivity detection as described by Rocha et al. (2003), as well as by Fornaro and Gutz (2003).In the present study, a 75 m internal diameter fused silica capillary, 60 cm in length (50 cm before the detector), was employed.The injection was performed hydrostatically by elevating the standard solution or sample by 10 cm for 30 s, the detector was operated at 600 kHz, and the separation potential was -15 kV.Prior to each session, the capillary was treated with 0.2 mol L -1 NaOH for 30 min and the buffer solution for 30 min.For anion separation, a pH 6.2 buffer, consisting of 20 mmol L -1 of 2-[morphine] ethanesulfonic acid and 20 mmol L -1 of histidine, was used in combination with a solution of 0.2 mmol L -1 of cetylmethylammonium bromide In the winter (August) of 1999, aerosol collection was performed on the University of São Paulo campus (23.34°S, 46.44°W), which is situated in the NW periphery of the city.Winter samplings were performed from August 3-13 using a (MOUDI).Aerosol spectra were constructed from the data measured by the MOUDI, which has ten different stages.m and 18.0 m (inlet to cut the particles).The MOUDI has rotating impactor plates that provide nearly uniform deposits over During this campaign, the MOUDI operated on weekdays with an integration time of 10 hours during the day (diurnal samplings from 8:00 to 18:00 LT) and 14 hours at night (nocturnal samplings from 18:00 to 8:00 LT).Over the weekend, the integration time was 24 hours (from 8:00 to 8:00 LT).This and two 24-hour samples.Mass analysis was carried out by gravimetry and the elemental concentrations were measured by Particle Induced X-ray Emission (PIXE).The PIXE analysis was performed on both samples and blanks at the Physics Institute a 2.4-MeV proton beam, at a typical current of 20 nA.The X-ray spectra were accumulated for 600 s, as recommended by Miranda et al. (2002).It was considered that all the sulfur presented in the sample, analyzed by PIXE, was ammonium sulfate.Ammonium sulfate showed simple unimodal size distribution during the day (with peak diameter of 0.38 µm) and bimodal size distribution at night (0.38 and 0.59 µm).The crustal material contribution was greater in larger cutoff diameter stages.Ynoue and Andrade (2004) showed that most black carbon and, in lesser quantities, ammonium sulfate.The matter in the region and that the dominant ions are ammonium, sulfate and nitrate.The authors showed that concentrations of crustal material had elevated concentrations at higher MOUDI stages, corresponding to the coarse fraction of the aerosol.The main crustal elements found were aluminum, silicon, titanium than 1 m) receives a larger contribution from carbonaceous materials (organic carbon + black carbon) than from ammonium sulfate.The characteristics of urban aerosols in the São Paulo atmosphere are different from those in other urban areas because the primary source is mobile emission, which is also responsible The CETESB monitoring stations house automatic gas samplers for NO, NO 2 , SO 2 , CO, total HC, non-methane HC and O 3 , together with a beta gauge particulate monitor for PM10 (particulate matter with aerodynamic diameters less than 10 µm).The 29 automatic stations are distributed throughout MASP, as well as in Cubatão and other major cities within the state of São Paulo.There are 12 stations that measure SO 2 and report hourly.No biogenic emissions are included.

The scavenging modeling.
The RAMS (version 4a) and scavenging model have The spatial structure of the scavenging modeling processes between the ground and cloud base for below-cloud modeling and between cloud base and cloud top for in-cloud modeling; The gas-scavenging modeling presents similar equations for both processes.Particulate matter (PM) scavenging modeling is also similar and includes nucleation processes; The in-cloud modeling was developed using the mesoscale numerical modeling RAMS.This was done in order to evaluate the following parameters: cloud water content was used in order to obtain the cloud droplet spectra and to integrate the concentrations were obtained with a parameterization of sub-grid scale convective transport of gases and aerosol particles associated with deep and moist convection systems.Aerosol was considered without mass.The parameterization was based on the 'top-hat' method, has been coupled to the cumulus parameterization scheme of RAMS-CSU model; raindrop size distribution (DSD) was based on a given rainfall rate.No splitting, break-up events or other changes of the DSD took place during the event.Different function relations 5.2mm in diameter.The raindrop size distributions were also assumed to follow a Gamma function distribution as proposed rate for each event; The main chemical modeling reactions analyzed from gases 2 , was the gas and SO 4 = was the particulate matter, both used as input data (atmospheric concentrations).The prognostic variables were SO 4 = in rainwater.The particulate matter size distribution for all aerosol species is characterized by a lognormal function, according to Whitby (1978) and Jaenicke and Davies (1976) for rural distribution, urban and adjusted-urban distributions, within the 0.01 to 40 m radius and divided into 73 mass class sizes ( g m -3 ).Particle mass and number distributions are assumed to be temporally constant with respect to particulate aerodynamic diameter, or rather; hygroscopic growth is not considered (Figure 2).Particle density is assumed to be equal to 1 g cm -3 .A measured aerosol spectra from a MOUDI collector is also used, herein referred to as the adjusted-urban spectra, presented in Table 1 (Ynoue and Andrade, 2004).The main RAMS parameterization are: The homogeneous initialization uses the radiosonde data acquired at Congonhas Airport (usually at 09:00 LT), which is in the São Paulo city center, with or without NCEP/NCAR reanalysis.Three-dimensional nested grids are used.The the other two having 4 km and 1 km horizontal resolutions (see also Figure 1), respectively, with z of 100 m, a 1.2 z for vertical stretch.Time steps were assumed to be 20 s, with 2 s being the smallest;

Statistics methods
The following statistical tools are used in order to provide a comparison between modeled and observed data groups: this study, the variables behave as lognormal functions, therefore variables in the lognormal distribution.
In order to perform the modeling described above, case studies were selected from among rainfall events occurring on the university campus.The events of July 26, 1989, July 15, 2000and July 23, 2000 were chosen because, for these events, complete data for the modeling analysis were available for the various scenarios (below-cloud and in-cloud scavenging using size distribution spectra from rural, urban and adjusted-urban areas).Two numerical modeling simulations (below-cloud scavenging or in-cloud scavenging, both using the various spectra distributions) were designed for the July 15, 2000 and July 23, 2000 events at both locations.Observed and modeled concentrations were compared.

Synoptic description of July 26, 1989, July 15, 2000 and July 23, 2000 rainfall events
In the July 26, 1989 event, a frontal system arrived in created 46.5 mm of precipitation from 3:25 LT to 20:00 LT.The July 15, 2000 event was characterized as stratiform and was caused by a cold front approaching the site at 16:40 LT and passing at 23:00 LT.The integrated precipitation totaled 15.7 mm.The July, 23, 2000 event was also characterized as stratiform, remaining over the station from 5:00 LT to 23:00 LT and releasing 34.6 mm of total precipitation.behavior.Rural and adjusted-urban spectra provided the highest early sulfate rainwater concentrations due to the fact that there was a greater amount of larger-diameter aerosol particles (and consequently more mass in the coarse fraction) than in the urban unity for aerosols larger than 2.5 m.Consequently, the coarse fractions of both rural and adjusted-urban spectra are quickly removed, generating higher rainwater concentrations in the spectra, the rainwater concentrations show a mild decrease follows.Tables 2a and 2b show those results.These results also emphasize that rural and urban-adjusted spectra generally than urban spectrum.All results show a RMSE-to-observed values ratio lower than the observed data standard deviations,  for spectra from rural and adjusted-urban, respectively, versus 0.68 for the urban spectrum during the July 26, 1989 event (see also Figures 3a and 3b).The RMSE event averages were 0.47 for rural and adjusted-urban spectra, respectively, versus 1.48 for the urban spectrum during the same event.For the July 15, 2000 event, the rural and urban-adjusted spectra presented 0.43 for rural and urban-adjusted spectra and 0.37 for the urban data (Figures 3 to 5).On the other hand, for July 23, 2000 event, there was no average) for all three spectra.be the wind direction.Unlike the two other case studies, the third after 16:00 LT (corresponding to after 300 minutes in Figures 5a weather charts (Figure 6).It is of note that there is no advection  (Naik et al., 1994), although quantitative data is not available.

Results of the modeling for the
Figures 5a and 5b show that the behavior of the July 23, 2000 event was different from that of the other events in that after 300 minutes of rainfall.However, the direct high temporal air, which would affect rainwater concentrations.This increase could, therefore, be due to the change in wind direction, as

Results of the modeling of the July 15, 2000 and July 23, 2000 events: local differences
Table 3 shows local average rainwater concentrations with the three modeled simulated concentrations, observed data and the PEFI/USP (both locations) ratios.In these three simulations, the in-cloud + below-cloud concentrations were also included.Despite the lack of agreement among observed and modeled values, the overall results show good agreement between the USP/PEFI ratios of modeled and observed values.Additionally, the SO 2 input data was determinant to the modeled spatial variability which was found in both observed and modeled rainwater, through the USP/PEFI ratios, which emphasizes below-cloud scavenging.From Table 3, using only below-cloud modeling, modeled values are closer to observed values than when below-cloud and in-cloud processes are considered together.However, in (2002), below cloud modeled values are twice as high as observed values in the urban spectrum and in-cloud + below cloud modeled, four times higher.With the two other spectra, the values are even higher than observed values.Therefore, the below-cloud modeling seems to estimate the observed values rather than the both scavenging processes together.As results were obtained in the simulations conducted during the July 1989 campaign.
It is not that the case in the July 23, 2000 event, modeled and observed concentrations did not differ considerably, probably due to the previously mentioned shift in wind direction, which might have led to an increase in the observed data.
Therefore, there are usually significant differences between modeled and observed which could mostly be due to the non advection terms.
In general, the below-cloud process seems to play the most important role in atmospheric scavenging in these case studies, where local sources were dominant in the wet deposition contamination.This dominance was due to the pattern of wet deposition rather than to the amount of contamination.

CONCLUSIONS
scavenging dominates in winter stratiform events.We base this conclusion on the great spatial variability of the concentrations of compounds in rainwater and on the behavior of the rate of pollutant removal, as evidenced by the lower values seen in samples collected later in the event.The comparison between two different locations seems to support the idea that below-cloud scavenging dominates the stratiform event scenario.
2 also indicate a chemistry.Wind direction also plays an important role, as can be noted when there is an abrupt variation in wind direction.Modeling of scavenging processes compared favorably with the demonstrating the dominance of below-cloud scavenging.The differences The results indicate that the aerosol size distribution spectra play a major role in the removal process, which is clearly seen through the numerical modeling.Adjusted-urban (MASP) and rural spectra gave the best representation of the concentrations of the various compounds in rainwater, presenting smaller RMSE values than did the urban spectra.Our results also indicate a are surrounded by natural aerosol sources, i.e. vegetation that matches the rural spectrum or adjusted-urban, within the urban of rural and urban characteristics, though more similar to that of the rural spectrum.Those results also favor the improvement of the scavenging modeling which thereafter will use the aerosol spectra as in important input data.
(2003) used numerical modeling to evaluate gas and aerosol scavenging processes in tropical areas.The authors evaluated modeled and observed concentrations of SO 2 , SO 4 2-and NH 4 + in convective rainfall within the African and Amazonian relationship between liquid water and trace element content in convective precipitation.The results compared favorably with the evaluation of the observed data set collected during the ABLE 2B (2003) performed the sampling campaign in scavenging decreased in proportion to increases in rain intensity
, 2003 scavenging modeling was primarily divided into two main mechanisms: below-cloud and in-cloud scavenging processes.Below-cloud and in-cloud modeling were based on physical and mathematical assumptions, described in the previous works.The main modeling assumptions are:

Figure 2 -
Figure 2 -Aerosol input spectra in number per diameter class.Rural and urban adapted from Whitby (1978) and urban adjusted for sulfate Figures 3 to 5 show the observed and modeled rainwater sulfate concentrations with the three spectra: urban, adjusted-urban and rural.Compared to the rural and

Table 2b .
Root mean square errors (RMSE) for modeled values divided by mean observed sulfate rainwater concentrations for different aerosol spectra and events, adding mean observed values and their respective standard deviations.
a, only below-cloud modeling b, below-cloud + in-cloud modeling

Table 3 -
Results of the modeling for the July 15, 2000 and July 23, 2000 events, compared to the observed data for sulfate in rainwater (mg/L)