This study evaluates the potential impacts of hypothetical nuclear accidents at the Almirante Álvaro Alberto Nuclear Power Plant (CNAAA), located in Angra dos Reis (RJ), in the southeastern region of Brazil, through the integration of advanced atmospheric modeling and Geographic Information Systems (GIS). The study area is characterized by complex environmental features, including mountainous terrain, remnants of the Atlantic Forest, coastal ecosystems, conservation units, and intense tourist activity. To simulate accidental release scenarios of iodine-131 (¹³¹I), the WRF/CALMET/CALPUFF modeling system was applied, incorporating high-resolution meteorological data and accounting for seasonal variability as well as topographic influences. The integration of WRF and CALMET for meteorological characterization, combined with CALPUFF dispersion simulations, provided realistic representations of the wind field, conferring confidence to the simulated dispersion patterns. A comprehensive radiological dose assessment was performed, including inhalation (short-term), external exposure to the plume (short-term), soil deposition (medium-term), and milk ingestion via the pasture → milk pathway (long-term), with comparison to the intervention levels of the IAEA (GSG-2) and CNEN (NE-1.04). The results indicate that, for children in the most impacted area, the total accumulated dose over 30 days exceeds 100 mSv, justifying the need for revision of the current Emergency Planning Zones (EPZs). The periods from November to March and from May to July present unfavorable dispersion conditions, associated with climatic instability and hydrological events. In summary, the methodological framework highlights the relevance of combining atmospheric modeling and geotechnological tools to strengthen nuclear safety and enhance emergency preparedness in coastal and densely populated regions.

The role of the oceans has been fundamental for sustaining life on the planet. However, they are increasingly facing significant issues of the modern world: in many places, every cubic meter of the ocean bears multiple, often conflicting demands, leading to heightened competition for space and resources. In the future, this situation will become unsustainable. Therefore, it is essential to manage marine space to allocate and organize the activities taking place within it, that is, to develop Marine Spatial Planning (MSP). In this context, the work proposes zoning the main activities identified along the Brazilian coast, aiming to contribute to the country’s marine spatial planning, which, with 5.7 million square kilometers (a coastline exceeding 10,000 kilometers), still lacks planning in this sector. The methodology considered various global literature examples and the legal framework, also supported by digital technologies based on Geographic Information Systems (GIS), which facilitated the spatialization of data, information, and complex spatial analyses. The results suggest a mapping and analysis of the primary activities in the Brazilian Coastal Zone, a proposed zoning for the Brazilian coastal region, also presenting a set of guidelines to contribute to the study and development of the topic, aiming to continuously improve the process.

The COVID-19 pandemic significantly impacted Brazil, amplifying existing socioeconomic disparities and social vulnerabilities, particularly in the State of Alagoas, located in Eastern Northeast Brazil (ENEB). This study evaluated the climatic, environmental, and socioeconomic effects attributed to COVID-19 across the Health Regions (HR) of Alagoas. Daily data on COVID-19 cases and deaths from the 10 h were sourced from DATASUS through the Unified Health System (SUS) for the period from March 2020 to January 2023. Both datasets underwent descriptive statistical analysis, with the Spline method, Principal Component Analysis (PCA), and Case Fatality Rate (CFR

Daily violations of air quality have an impact on urban populations and cause damage to the environment. Thus, the study evaluated the violations of the daily concentrations of SO2, NO2, and PM10, in regions of the State of São Paulo (SSP), based on the National Environment Council (CONAMA) resolution no 491/2018 and the World Health Organization (WHO - World Health Organization. (2016). Ambient air pollution: a global assessment of exposure and burden of disease.) criteria. Daily SO2, NO2, and PM10data from 6 air quality stations operated by Environmental Company of the State of São Paulo CETESB (1996–2011) were organized and submitted to quality control, with data faults (gaps) being identified. The imputation of data via spline proved satisfactory in filling in the gaps (r > 0.7 and low values of Standard Error of the Estimate (SEE) and Root Mean Square Error (RMSE). The cluster analysis (CA) applied to SO2 formed only one homogeneous group (G1). Contrariwise, NO2 and PM10 formed two homogeneous groups (G1 and G2) each. The stations that showed the greatest similarity according to the CA were Cerqueira Cesar and Osasco. The cophenetic matrix generated for SO2 (0.83), NO2 (0.79), and PM10 (0.77) indicate a satisfactory adjustment of the dendrograms. The exploratory statistics applied to groups G1 and G2 point to the high variability of outliers. The WHO criteria are more restrictive than CONAMA regarding daily violations, with a reduction in SO2 and an increase in specific years for NO2 and PM10. Such variability is due to the adoption of public policies by the SSP and the influence of meteorological systems, being confirmed by the Run test that indicated oscillations in the time series, mainly in PM10, and also recognized well-defined biannual cycles.

Air quality models are essential tools to meet the United Nations Sustainable Development Goals (UN-SDG) because they are effective in guiding public policies for the management of air pollutant emissions and their impacts on the environment and human health. Despite its importance, Brazil still lacks a guide for choosing and setting air quality models for regulatory purposes. Based on this, the current research aims to assess the combined WRF/CALMET/CALPUFF models for representing SO2 dispersion over non-homogeneous regions as a regulatory model for policies in Brazilian Metropolitan Regions to satisfy the UN-SDG. The combined system was applied to the Rio de Janeiro Metropolitan Area (RJMA), which is known for its physiographic complexity. In the first step, the WRF model was evaluated against surface-observed data. The local circulation was underestimated, while the prevailing observational winds were well represented. In the second step, it was verified that all CALMET three meteorological configurations performed better for the most frequent wind speed classes so that the largest SO2 concentrations errors occurred during light winds. Among the meteorological settings in WRF/CALMET/CALPUFF, the joined use of observed and modeled meteorological data yielded the best results for the dispersion of pollutants. This result emphasizes the relevance of meteorological data composition in complex regions with unsatisfactory monitoring given the inherent limitations of prognostic models and the excessive extrapolation of observed data that can generate distortions of reality. This research concludes with the proposal of the WRF/CALMET/CALPUFF air quality regulatory system as a supporting tool for policies in the Brazilian Metropolitan Regions in the framework of the UN-SDG, particularly in non-homogeneous regions where steady-state Gaussian models are not applicable.

The Model for Prediction Across Scales (MPAS) is an Atmospheric General Circulation or Global Circulation Model (GCGA) that can be used both as a numerical weather forecast model as well as a climate forecast model. The great innovation that this model offers is the use of the Tessalation Spherical Centroidal Voronoi (TECV) mesh, which allows different spatial resolutions in the same grid. MPAS has a mesh that covers the entire globe, where each of the mesh units, called a cell, which is not a grid point, is a region that has an area with a certain spatial resolution. Such a cell area can be easily divided into n-parts, thus increasing its resolution. Each Voronoi cell is treated as a finite volume, where the physical variables are integrated and approximated by the mean values in the cells. As an important feature of the MPAS, its use in multiscale modeling stands out, with the potential to be used in climate forecasting on a global and regional scale, and especially in weather forecasting extended to a very short duration. Thus, the objective of the study is to implement and evaluate the performance of MPAS in multiscale atmospheric modeling, and mainly its application in extended weather forecasting, operational forecasting and short-term forecasting for Brazil.

Isotopic methods have become an important tool in the study of natural processes and countless applications have proven valuable in several research areas. Geologically, strontium and neodymium isotopes also fractionate in Earth surface environments. The difference is that measured radiogenic isotope ratios are normalized to a fixed stable isotope ratio during analysis, so that any natural mass dependent isotope fractionation in analysed samples is canceled. All data was obtained from academic journals and has been spatialized in a Geographic Information System (GIS), the analysis of which has subsidized the identification, where data are more clustered or dispersed. Understanding the distribution of 87 Sr/ 86 Sr e εNd(0) in different regions of South America is very important to demonstrate how Nd/Sr signatures can be used to distinguish various terrains and localities on a regional scale, through the selection, organization, inventory, and arrangement of 386 data in sedimentary basins and crystalline shields.

Due to the scarcity of studies linking the variability of rainfall and population growth in the capital cities of Northeastern Brazil (NEB), the purpose of this study is to evaluate the variability and multiscale interaction (annual and seasonal), and in addition, to detect their trends and the impact of urban growth. For this, monthly rainfall data between 1960 and 2020 were used. In addition, the detection of rainfall trends on annual and seasonal scales was performed using the Mann–Kendall (MK) test and compared with the phases of El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). The relationship between population growth data and rainfall data for different decades was established. Results indicate that the variability of multiscale urban rainfall is directly associated with the ENSO and PDO phases, followed by the performance of rain-producing meteorological systems in the NEB. In addition, the anthropic influence is shown in the relational pattern between population growth and the variability of decennial rainfall in the capitals of the NEB. However, no capital showed a significant trend of increasing annual rainfall (as in the case of Aracaju, Maceió, and Salvador). The observed population increase in the last decades in the capitals of the NEB and the notable decreasing trend of rainfall could compromise the region’s water security. Moreover, if there is no strategic planning about water bodies, these changes in the rainfall pattern could be compromising.

Forest fires have global, regional, and local socioeconomic and environmental consequences, with negative effects on ecosystem services, air quality, population health, and other relevant aspects, emphasizing their significance in the context of the United Nations Sustainable Development Goals. The study identified areas in the Rio de Janeiro State (RJS) with varying degrees of susceptibility to fire focis using remote sensing data derived from topographic, anthropogenic, meteorological, and hydrological factors based on seasonality and integrated into geographic information systems. The analytical hierarchy process was used as a method of integration and normalized hierarchy of variables, generating susceptibility maps in the annual, summer, and winter periods in the RJS’s hydrographic regions (HR), with the application of the associated chi-square test to records of fire focis from the AQUA satellite, period 2003 to 2017, without methodological variation for data acquisition, whose susceptibility was classified as very low to very high. The results show that the years with the most fire foci in the adopted time series are 2007 and 2014, with a peak in September and a fall from October onwards. According to the susceptibility map, 9% of the RJS is highly susceptible during the annual period, with HR-IX being especially vulnerable. In the summer, 0.2% of RJS is extremely vulnerable, while 32% is highly vulnerable in the winter, with 6402 km2 of HR-IX areas being extremely vulnerable. A statistical correlation was discovered between the chi-square test and susceptible areas. This work contributes as a decision-making tool in fire planning and emergency response, with the potential to assist control bodies (city halls, civil defense, environmental protection bodies, health systems) in the local and regional context in the assessment, analysis, and management of these phenomena.

Apesar dos avanços no monitoramento espaço-temporal das chuvas, suas informações em regiões de topografia complexa são escassas. A interpolação espacial baseada em dados orbitais pode suprir tal escassez. Portanto, o estudo avaliou o desempenho de interpoladores híbrido e não híbrido na estimativa da chuva na Região Hidrográfica da Baía da Ilha Grande (RHBIG), situada na Serra do Mar, nos estados de RJ e SP. Dados de chuvas de estações de superfície e de estações virtuais, derivadas do produto CHIRPS, entre os anos 2004 e 2013, foram utilizados para geração de modelos pelos interpoladores Krigagem Ordinária (KO) e Krigagem Regressão (KR), tendo como variável explicativa o Modelo Digital de Elevação (MDE). Os resultados mostraram correlação (r = 0,68) entre os dados observados e do CHIRPS, com a taxa de chuva subestimada no litoral, média da diferença (di) de -10%, e superestimada no planalto (di = 9%), o que origina distribuição espacial suavizada. Em relação aos modelos de chuva, os KR, linear e logarítmico, tenderam a extrapolar os valores mínimos e máximos, e aumentar a taxa de chuva do litoral para o planalto, com média de -28% das estações do litoral. Enquanto, nos modelos da KO, o volume tende a diminuir do litoral para o planalto (di = -1,4), o que é corroborado por estudos já realizados na RHBIG com dados observados. Por fim, os modelos de ambos interpoladores, com as estações virtuais corrigidas pelos dados observados, mostram aumento da amplitude pluviométrica, o que diminui a suavização do modelo CHIRPS. Desta forma, os modelos da KO derivados de uma rede densa e regular de estações virtuais, corrigidas por dados observados, podem ser uma alternativa para utilização dos dados CHIRPS em locais de topografia complexa sem uma rede densa de estações de superfície, o que origina em modelos de maior resolução espacial e amplitude pluviométrica.

Forest fires destroy productive land throughout the world. In Brazil, mainly the Northeast of Brazil (NEB) is strongly affected by forest fires and bush fires. Similarly, there is no adequate study of long-term data from ground and satellite-based estimation of fire foci in NEB. The objectives of this study are: (i) to evaluate the spatiotemporal estimation of fires in NEB biomes via environmental satellites during the long term over 1998–2018, and (ii) to characterize the environmental degradation in the NEB biomes via orbital products during 1998–2018, obtained from the Burn Database (BDQueimadas) for 1794 municipalities. The spatiotemporal variation is estimated statistically (descriptive, exploratory and multivariate statistics) from the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Standardized Precipitation Index (SPI) through the Climate Hazards Group InfraRed Precipitation Station (CHIRPS). Moreover, we identify 10 homogeneous groups of fire foci (G1–G10) with a total variance of 76.5%. The G1 group is the most extended group, along with the G2 group, the exception being the G3 group. Similarly, the G4–G10 groups have a high percentage of hotspots, with more values in the municipality of Grajaú, which belongs to the agricultural consortium. The gradient of fire foci from the coast to the interior of the NEB is directly associated with land use/land cover (LULC) changes, where the sparse vegetation category and areas without vegetation are mainly involved. The Caatinga and Cerrado biomes lose vegetation, unlike the Amazon and Atlantic Forest biomes. The fires detected in the Cerrado and Atlantic Forest biomes are the result of agricultural consortia. Additionally, the two periods 2003–2006 and 2013–2018 show periods of severe and prolonged drought due to the action of El Niño.

Burns are common practices in Brazil and cause major fires, especially in the Legal Amazon. This study evaluated the dynamics of the fire foci in the Legal Amazon in Brazil and their consequences on environmental degradation, particularly in the transformation of the forest into pasture, in livestock and agriculture areas, mining activities and urbanization. The fire foci data were obtained from the reference satellites of the BDQueimadas of the CPTEC/INPE for the period June 1998–May 2022. The data obtained were subjected to descriptive and exploratory statistical analysis, followed by a comparison with the PRODES data during 2004–2021, the DETER data (2016–2019) and the ENSO phases during the ONI index for the study area. Biophysical parameters were used in the assessment of environmental degradation. The results showed that El Niño’s years of activity and the years of extreme droughts (2005, 2010 and 2015) stand out with respect to significant increase in fire foci. Moreover, the significant numbers of fire foci indices during August, September, October and November were recorded as 23.28%, 30.91%, 15.64% and 10.34%, respectively, and these were even more intensified by the El Niño episodes. Biophysical parameters maps showed the variability of the fire foci, mainly in the south and west part of the Amazon basin referring to the Arc of Deforestation. Similarly, the states of Mato Grosso, Pará and Amazonas had the highest alerts from PRODES and DETER, and in the case of DETER, primarily mining and deforestation (94.3%) increased the environmental degradation. The use of burns for agriculture and livestock, followed by mining and wood extraction, caused the degradation of the Amazon biome.

The disorderly growth of metropolitan regions, combined with the lack of efficient air quality management strategies, contributes to the potential increase in O3. That impact might undoubtedly cause harmful and immediate and continuous effects on living organisms. In this sense, the primary objective of this research work is to identify and evaluate the threshold values of the O-3 concentration pattern in the expanded region of the Rio de Janeiro Metropolitan Area (RJMA). Landsat images were retrieved and showed that there was an expansion to the east and west of the RJMA at an average rate of 32 km(2). year(-1). After analyzing the air quality data in the region for the period between 2010 and 2018, excess concentrations of O-3 were registered to occur every month and across all weather seasons, mainly from October to March (spring and summer), concerning air quality standards, There are significant differences in ozone violations between Paqueta weather station (t = 184 days, 53.2 %) and Porto das Caxias weather station (t = 105 days, 30.2 %). The annual time series of O-3 violations during the study period was highly variable, with peaks in the years 2012 (14.3 +/- 20.1 violations), 2013 (12.3 +/- 15.7 violations), and 2015 (23 +/- 15.7 violations). Furthermore, there was an increase in the value of surpluses of O-3 along 2016, marked by a longer period of excess concentration from August to March. Despite advances in environmental legislation, air quality management protocols still lack effective measures to mitigate the impacts of O-3 on the environment, which highlights the need for developing timely and additional interdisciplinary investigations in the coming future.

The patterns of urban rainfall in Brazil's capitals are critical, due to population growth and extreme weather. Therefore, the objectives are: i) to identify homogeneous rainfall groups and meteorological systems, ii) to evaluate the trend of the monthly rainfall time series and iii) to apply wavelet analysis to estimate the variance at different frequencies in the rainfall series in the capitals of the Brazil. Monthly rainfall data during 1960-2020 for 27 stations located in the capitals of Brazil were used. The data were flawed, and data imputation (mtsdi package) was applied via Fully Conditional Specification (FCS). Rainfall data were submitted to descriptive, exploratory statistics (boxplot), multivariate analysis (Cluster Analysis - CA) and the Mann-Kendall (MK) test. Seven CA methods (Ward, Single, Complete, Average, McQuity, Median and Centroid) were tested using the cophenetic correlation coefficient (CCC) with a significance level of 5%, the Average method obtained CCC > 0.81 (S). The CA identified three homogeneous regions (G1, G2 and G3) in the capitals of Brazil. The G1 group is formed by the capitals of the Northeast of Brazil (NEB), except for Boa Vista, (North of Brazil - NB). The G2 group is the largest group formed by the capitals of the Midwest (MWB), Southeast (SEB) and South (SB) of Brazil. The G3 group is the smallest group, with the capitals of the NB and some of the NEB. The capitals with the category of significant growth trend were only Porto Alegre and Florian acute accent opolis (SB), Vit acute accent oria (SEB) and Bele acute accent m (NB). The category of non-significant increase trend prevailed in most capitals of Brazil, with emphasis on the corridor formed between the NB and the Center-South, except for Natal (NEB). The without trend category prevailed in the North, Northeast and Midwest regions of Brazil. Monthly precipitation analyzes for trend detection purposes via Wavelet Analysis showed that ENSO phases are significant in rainfall variability in Brazilian capitals.

Fire is used in the management of pastures, renewal and expansion of areas, and agricultural activities in South America (SA). The objectives of this study were: i) to identify the countries and regions with the highest number of fire foci in SA, and ii) to evaluate the spatial dynamics of fire foci based on the Meteorological Fire Danger Index (MFDI) and future scenarios through numerical simulations. Fire foci time series comprised 21 years (1998–2018) from the BDQueimadas database. Cluster Analysis (CA), descriptive and exploratory statistics were employed. Fire foci maps for SA were made in 10-km pixel dimensions. MFDI was used to assess fire danger via SPEEDY (Simplified Parametrizations, primitivE-Equation DYnamics) model simulations. Three simulations were performed: control scenario (1980–2015), RCP2.6 scenario (optimistic - 2016 and 2050), and RCP8.5 scenario (pessimistic - 2015 and 2050). Regionally, three homogeneous groups of fire foci (G1, G2 and G3) and one atypical (NA - Not Grouped) were identified for Brazil via CA. The highest fire foci occurred in Brazil (62.72%), followed by Bolivia (9.03%), Argentina (8.28%), Venezuela (6.11%), Paraguay (5.94%), and Colombia (3.87%), respectively. The highest density of fire foci occurred in the MATOPIBA region, the confluence of Maranhão, Tocantins, Piauí, and Bahia, - (agricultural frontier), and also in the Cerrado-Amazon transition and the states of Mato Grosso and Mato Grosso do Sul in Brazil, followed by Paraguay, Bolivia, Venezuela, and Argentina. The countries and regions of Brazil do not change, only intensify from year to year, and such fire foci variability may be associated with the El Niño-Southern Oscillation (ENSO) phases. The control scenario identified in east-central Brazil, western Bolivia, Paraguay, and northern Argentina. The optimistic scenario showed an improvement in some countries and a worsening in the territorial distribution in Brazil, Venezuela, and Colombia. The pessimistic scenario identified increased degradation compared to the previous scenarios in almost all SA countries.

Ilha Grande Bay is located in Angra dos Reis, Rio de Janeiro State, Brazil. The area is characterized by different land cover, complex topography and proximity to the Atlantic Ocean. These aspects make it susceptible to thermally and dynamically induced atmospheric circulations such as those associated with valley/mountain and land/sea breeze systems, among others. The Almirante Álvaro Alberto Nuclear Complex (CNAAA) is located in this region, with a total of two nuclear power plants (NPPs) in operation in the Brazilian territory, Angra I and Angra II. Therefore, knowledge of local atmospheric circulation has become a matter of national and international security. Considering the importance of the meteorological security tool as a support for licensing, installation, routine operation and nuclear accident mitigation, the main aim of this study is the development of combined strategies of environmental statistical modeling in the analysis of thermally and dynamically driven atmospheric circulations over mountainous and coastal environments. We identified and hierarchized the influence of the thermally and mechanically driven forcing on the wind regime and stability conditions in the coastal atmospheric boundary layer over the complex topography region. A meteorological network of ground-based instruments was used along with physiographic information for the observational characterization of the atmospheric patterns in the spatial and time–frequency domain. The predominant wind directions and intensity are attributed to the combined action of multiscale weather systems, notably, the valley/mountain and continent/ocean breeze circulations, the forced channeling due to valley axis orientation, the influence of the synoptic scale systems and atmospheric thermal tide. The observational investigation of the combined influence of terrain effects and meteorological systems aimed to understand the local atmospheric circulation serves as support for safety protocols of the NPPs, contemplating operation and environmental management. The importance of the study for the adequacy and skill evaluation of computational modeling systems for atmospheric dispersion of pollutants such as radionuclide and conventional contaminants can be also highlighted, in order that such systems are used as tools for environmental planning and managing nuclear operations, particularly those located in regions over mountainous and coastal environments with a heterogeneous atmospheric boundary layer.

This study aims to characterize the wind regime in the state of Rio de Janeiro (SRJ), Brazil, and relate it to the physiographic aspects and influence of meteorological systems, based on 12 Brazilian National Institute of Meteorology (INMET) automatic meteorological stations, for the period from 2008 to 2019. Box plots are used for the assessment of monthly and hourly patterns. Similarity was found among the stations at a monthly and daily scale. On the monthly scale, there were two well-defined cycles, a minimum (between February and July) and a maximum (between August and November), both greatly influenced by frontal systems (FS). On the hourly scale, there was a decrease in the intensity of the wind during the night and early morning, followed by an intensification in wind patterns between 11 h to 20 h, except for the Arraial do Cabo and Petrópolis stations. The stations that are located near the Serra do Mar ridge and Sepetiba Bay presented prevailing N, SW, W, ENE and NE winds, respectively. Arraial do Cabo station is located near the state’s shoreline and in the resurgence region, with predominant NE and E wind directions. Petropólis station is located in the Mountainous region, with NNW and NW wind directions. The logistic regression model identified that the rainfall, temperature (air, maximum and wet bulb) and relative humidity contributed to the probability of wind velocity above the 70 percentile (WS70) occurring in the SRJ. The South American Convergence Zone (SACZ) and FS acted as triggers of the WS70 in different areas of the state, where the influence of the SACZ was stronger than that of the FS.

Muito tem se discutido acerca das mudanças climáticas e suas respectivas consequências para o planeta, algumas delas associadas à disponibilidade dos recursos energéticos renováveis e não renováveis,

In the context of the naturally occurring radioactive material associated with petrol exploitation, it is important to determine the concentrations of(226)Ra and(228)Ra in contaminated sludge originated from this activity and stored in packages. Although measurements based on chemical analyses of samples from package content can be done, difficulties associated with the collection and analyses of samples may be avoided by employing theoretical models based on the emitting radiation levels from the mentioned packages. This article presents a methodology to estimate(226)Ra and(228)Ra concentrations in sludge stored in cylindrical drums, employing a model developed in the Mathematica software. The model takes into consideration the radiation levels measured at one meter from the top surface of the waste package containing the contaminated sludge. It also takes into consideration packaging dimensions, waste density, time of measurement, among other factors, and allows the determination of all radionuclides concentrations in the sludge, helping to minimize the costs associated with sampling and analyses. Moreover, this proposed model is an alternative solution to pre-existing methods and can also assist operators, regulators, and decision-makers in the prediction of short- and long-term radiological impacts on human beings and on the environment, due to the disposal of waste containing naturally occurring radioactive materials.

A análise tem como principal objetivo revisar e discutir os princípios do método da similaridade aplicado para camada limite em superfícies lisas e inclinadas, em regime laminar e regime turbulento. A ênfase se aplica aos aspectos teóricos relacionados com o conceito de similaridade, mas resultados foram obtidos com o objetivo de se comparar com fórmulas empíricas e resultados experimentais. Os aspectos relacionados com regime laminar têm como base o profundo estudo efetuado por Evans (1968), e em regime turbulento o texto de Kays e Crawford (1983). Foram obtidos resultados para perfis de velocidade e temperatura, e grandezas associadas, tais como coeficiente de atrito e número de Stanton, em função do parâmetro de gradiente de pressão e número de Prandtl. Soluções integrais, aproximadas, para camada limite turbulenta foram implementadas através da equação integral da quantidade de movimento, onde todas as propriedades do fluido foram consideradas constantes. Objetivo secundário é apresentar os aspectos principais do problema analisado por Falkner e Skan (1931), com foco no método da similaridade. Aplicamos o método de Runge-Kutta, a partir da expansão em série de potência como primeira aproximação para a solução. Focamos nossa apresentação nos procedimentos associados ao método da similaridade, apesar de apresentarmos resultados, numéricos e gráficos, em número suficiente para enfatizar a consistência dos mesmos quando aplicados para determinação de parâmetros relacionados às camadas limite térmica e hidrodinâmica, em superfícies lisas.