Fábio Luiz Teixeira Gonçalves

Poluição atmosférica e atendimentos por pneumonia e gripe em São Paulo, Brasil

OBJECTIVE A time series was developed to investigate the effect of air pollution levels on morbidity due to respiratory diseases such as pneumonia and influenza among elderly people from 1996 to 1998. METHODS Daily data on emergency room visits was collected at the university clinics hospital in São Paulo, Brazil. Daily levels of CO, NO2, O3, SO2 and PM10 were obtained from the State Environmental Agency. Daily measures of temperature and relative humidity were obtained from the Institute of Astronomy and Geophysics of the University of São Paulo. Generalized additive Poisson regression models were used to assess the relationship between pneumonia and influenza and air pollution, using the number of emergency room visits as dependent variable and the average daily levels of each pollutant as independent variables. The models were estimated and adjusted by seasonality (non-parametric function), weather, weekdays, motor vehicle circulation curbs periods and daily numbers of non-respiratory hospital admissions. RESULTS The pollutants O3 and SO2 showed a statistical association with pneumonia and influenza. These associations remained robust when control variables were included. An interquartile range for O3 (38.80 microgram/m3) and SO2 (15.05 microgram/m3) increased in 8.07% and 14.5%, respectively, the number of emergency room visits due to pneumonia and influenza. CONCLUSION The study results suggest that air pollution in the city of São Paulo may promote adverse health effects in elderly people.

Air pollution and pediatric respiratory hospital admissions in São Paulo, Brazil

In order to investigate the relation between air pollution and child morbidity in Sao Paulo, a time-series study was carried out. Daily records of hospital admissions for children under 13 years old were obtained at the Health State Secretary, covering 112 hospitals in the period from October 1992 to October 1993. Daily levels of PM10, ozone, SO2, CO and NO2 were obtained from the environmental state agency (CETESB), while both CETESB and the Institute of Astronomy and Geophysics (IAG) of the University of Sao Paulo provided daily measures of temperature and relative humidity. Daily counts of child respiratory admissions (RESP) were considered as the dependent variable of pollutants in regression models, controlled for months of the year, days of the week, weather factors, and the daily number of non respiratory admissions (NORESP). PM10 and ozone were the pollutants that exhibited the most robust association with RESP. The mean levels of PM10observed during the period of study (70 μg m−3) were associated with an increase of 12% in RESP. The association between air pollution and RESP was significant within a time lag between 1 to 7 days and was dose-dependent. This result indicates that air pollution represents a significant pediatric health problem in Sao Paulo. Copyright

Impact of biomass burning aerosols on precipitation in the Amazon: A modeling case study

[1] A study of the potential role of aerosols in modifying clouds and precipitation is presented using a numerical atmospheric model. Measurements of cloud condensation nuclei (CCN) and cloud size distribution properties taken in the southwestern Amazon region during the transition from dry to wet seasons were used as guidelines to define the microphysical parameters for the simulations. Numerical simulations were carried out using the Brazilian Development on Regional Atmospheric Modeling System, and the results presented considerable sensitivity to changes in these parameters. High CCN concentrations, typical of polluted days, were found to result in increases or decreases in total precipitation, depending on the level of pollution used as a reference, showing a complexity that parallels the aerosol-precipitation interaction. Our results show that on the grids evaluated, higher CCN concentrations reduced low-to-moderate rainfall rates and increased high rainfall rates. The principal consequence of the increased pollution was a change from a warm to a cold rain process, which affected the maximum and overall mean accumulated precipitation. Under polluted conditions, cloud cover diminished, allowing greater amounts of solar radiation to reach the surface. Aerosol absorption of radiation in the lower layers of the atmosphere delayed convective evolution but produced higher maximum rainfall rates due to increased instability. In addition, the intensity of the surface sensible heat flux, as well as that of the latent heat flux, was reduced by the lower temperature difference between surface and air, producing greater energy stores at the surface.

Indoor and outdoor atmospheric fungal spores in the São Paulo metropolitan area (Brazil): species and numeric concentrations

The aim of this study was to estimate the indoor and outdoor concentrations of fungal spores in the Metropolitan Area of Sao Paulo (MASP), collected at different sites in winter/spring and summer seasons. The techniques adopted included cultivation (samples collected with impactors) and microscopic enumeration (samples collected with impingers). The overall results showed total concentrations of fungal spores as high as 36,000 per cubic meter, with a large proportion of non culturable spores (around 91% of the total). Penicillium sp. and Aspergillus sp. were the dominant species both indoors and outdoors, in all seasons tested, occurring in more than 30% of homes at very high concentrations of culturable airborne fungi [colony forming units(CFU) m−3]. There was no significant difference between indoor and outdoor concentrations. The total fungal spore concentration found in winter was 19% higher than that in summer. Heat and humidity were the main factors affecting fungal growth; however, a non-linear response to these factors was found. Thus, temperatures below 16°C and above 25°C caused a reduction in the concentration (CFU m−3) of airborne fungi, which fits with MASP climatalogy. The same pattern was observed for humidity, although not as clearly as with temperature given the usual high relative humidity (above 70%) in the study area. These results are relevant for public health interventions that aim to reduce respiratory morbidity among susceptible populations.

In-cloud and below-cloud numerical simulation of scavenging processes at Serra Do Mar region, SE Brazil

Abstract 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: SO 4 = , NO 3 − and NH 4 + , 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.

Modelling and measurements of below cloud scavenging processes in the highly industrialised region of Cubatão-Brazil

Abstract Below cloud scavenging has been investigated from rainwater chemistry measurements using a one-dimensional scavenging numerical model and surface data from the local atmospheric conditions. The local emissions of pollutants from a large industrial complex in the south-eastern Brazil were also evaluated in the modelling. The scavenging model was coupled to the measurements of SO 2− 4 , NO − 3 and NH + 4 found in the rainwater samples. The concentration of gases and particles samplings and meteorological parameters measured during the study of rain episodes were used as input data in the numerical model, which simulates the raindrop interactions associated with the removal process. The results were compared with those actually measured. The variability of the rainwater concentrations estimated through the scavenging model was also compared to the chemical analysis of the rainwater collected by fractionated rain samplers. The results show a good agreement between both modelled and observed data as seen from the role of the raindrop size distribution in the below cloud scavenging of pollutants

Statistical analysis aiming at predicting respiratory tract disease hospital admissions from environmental variables in the city of São Paulo.

This study is aimed at creating a stochastic model, named Brazilian Climate and Health Model (BCHM), through Poisson regression, in order to predict the occurrence of hospital respiratory admissions (for children under thirteen years of age) as a function of air pollutants, meteorological variables, and thermal comfort indices (effective temperatures, ET). The data used in this study were obtained from the city of São Paulo, Brazil, between 1997 and 2000. The respiratory tract diseases were divided into three categories: URI (Upper Respiratory tract diseases), LRI (Lower Respiratory tract diseases), and IP (Influenza and Pneumonia). The overall results of URI, LRI, and IP show clear correlation with SO2 and CO, PM10 and O3, and PM10, respectively, and the ETw4 (Effective Temperature) for all the three disease groups. It is extremely important to warn the government of the most populated city in Brazil about the outcome of this study, providing it with valuable information in order to help it better manage its resources on behalf of the whole population of the city of Sao Paulo, especially those with low incomes.This study is aimed at creating a stochastic model, named Brazilian Climate and Health Model (BCHM), through Poisson regression, in order to predict the occurrence of hospital respiratory admissions (for children under thirteen years of age) as a function of air pollutants, meteorological variables, and thermal comfort indices (effective temperatures, ET). The data used in this study were obtained from the city of Sao Paulo, Brazil, between 1997 and 2000. The respiratory tract diseases were divided into three categories: URI (Upper Respiratory tract diseases), LRI (Lower Respiratory tract diseases), and IP (Influenza and Pneumonia). The overall results of URI, LRI, and IP show clear correlation with SO2 and CO, PM10 and O3, and PM10, respectively, and the ETw4 (Effective Temperature) for all the three disease groups. It is extremely important to warn the government of the most populated city in Brazil about the outcome of this study, providing it with valuable information in order to help it better manage its resources on behalf of the whole population of the city of Sao Paulo, especially those with low incomes.

Long-range ozone transport and its impact on respiratory and cardiovascular health in the north of Portugal

Ozone dynamics depend on meteorological characteristics such as wind, radiation, sunshine, air temperature and precipitation. The aim of this study was to determine ozone trajectories along the northern coast of Portugal during the summer months of 2005, when there was a spate of forest fires in the region, evaluating their impact on respiratory and cardiovascular health in the greater metropolitan area of Porto. We investigated the following diseases, as coded in the ninth revision of the International Classification of Diseases: hypertensive disease (codes 401–405); ischemic heart disease (codes 410–414); other cardiac diseases, including heart failure (codes 426–428); chronic obstructive pulmonary disease and allied conditions, including bronchitis and asthma (codes 490–496); and pneumoconiosis and other lung diseases due to external agents (codes 500–507). We evaluated ozone data from air quality monitoring stations in the study area, together with data collected through HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model analysis of air mass circulation and synoptic-scale zonal wind from National Centers for Environmental Prediction data. High ozone levels in rural areas were attributed to the dispersion of pollutants induced by local circulation, as well as by mesoscale and synoptic scale processes. The fires of 2005 increased the levels of pollutants resulting from the direct emission of gases and particles into the atmosphere, especially when there were incoming frontal systems. For the meteorological case studies analyzed, peaks in ozone concentration were positively associated with higher rates of hospital admissions for cardiovascular diseases, although there were no significant associations between ozone peaks and admissions for respiratory diseases.

Present climate and future projections of the thermal comfort index for the metropolitan region of São Paulo, Brazil

The metropolitan region of São Paulo (MRSP) is a densely populated area with approximately 20 million people. The impact of climate variability on the population can be estimated by the use of thermal comfort indexes. The aim of this work is to investigate the effect of projected climate change on the thermal comfort index, IPET (Indoor Perceived Equivalent Temperature), over MRSP, based on a two-weather-stations dataset. For this, four RegCM4 projections from the CREMA (CORDEX REgCM4 hyper-Matrix experiment) project for the representative concentration pathway 8.5 (RCP8.5) are used in two time slices: present (1975–2005), and future (2065–2099) climates. The IPET index is calculated for both present and future climates and the datasets are subdivided by quantiles, annual means and interpretative range categories. In the present climate, all simulation members are compared with two observed datasets representing the MRSP. The result of this comparison indicates that the simulation members properly represent the long-term means of the variables used in the IPET calculation. The trend analysis of all simulation members shows a warming pattern for IPET, which rises from 19.1–21.3°C, for the present, to 23.5–25.1°C, for the future climate. The spatial pattern indicates that the MRSP is located in a transitional zone where IPET in the future climate becomes higher than temperature due to the relative humidity increase. This result emphasizes that the increase of relative humidity plays an important role in increasing IPET. The simulations also indicate that the values of the lower and higher IPET quantiles will decrease and increase in the future, respectively. Considering thermal comfort, the IPET interpretative range distribution trends show a decrease of days in the “cool” category and an increase of days in the “warm” category. The overall results corroborate studies pointing to a warming pattern that could impact society in the MRSP. This could provide an important tool to promote the subsidization of Brazilian stakeholders wishing to take mitigative actions.

In-cloud and below-cloud scavenging analysis of sulfate in the metropolitan area of São Paulo, Brasil

The Metropolitan Area of Sao Paulo (MASP) is one of the largest urban centers in the world. The significant atmospheric concentrations of ozone, inhalable particles and other pollutants in 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 1990 and February-October 2000 campaigns. Adjusted-urban and rural spectra seem to fit better with 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.