Luiz Claudio Gomes Pimentel

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.

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.

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.

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.

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.

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.

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.

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.