Carla Taciane Brasil dos Santos

Bio: Carla Taciane Brasil dos Santos is an academic researcher from Federal University of Alagoas. The author has contributed to research in topics: Geography & Land use. The author has an hindex of 1, co-authored 4 publications receiving 2 citations.

Diagnóstico espaço-temporal dos focos de calor no Brasil

Abstract: O surgimento de incendios florestais pode ser de origem antropica ou natural, ambas causam grandes prejuizos socioeconomico e ambiental, e em boa parte dessas ocorrencias sao resultantes da ocorrencia de Focos de Calor (FC). Nos ultimos anos, o Brasil tem sofrido com o aumento significativo de FC, ao qual resultaram em grandes incendios. Desta maneira, o objetivo do presente estudo foi diagnosticar o comportamento espaco-temporal dos FC no Brasil entre 1999 e 2020, baseados nos dados de dados BDQueimadas do CPTEC/INPE. Para a manipulacao e o processamento dos dados, utilizou-se o software de ambiente R versao 3.4-1. Apos o armazenamento dos dados, calculou-se os registros totais, medias anual e mensal, e a composicao dos anos mais significativos, neste caso, os anos de 2015, 2017, 2019 e 2020. Os resultados apontaram que os maiores acumulados totais e medios anuais variaram entre 10-50 mil FC e 0,5-1,5 mil FC, concentrados na regiao centro-norte do Brasil, principalmente nos estados do Maranhao, Para e Tocantins. Este padrao de alto registros de FC esta relacionado ao desmatamento e expansao agricola nessas regioes. Em escala mensal, as maiores ocorrencias de FC ocorrem entre os meses de agosto e novembro, com valores de 0,20-0,45 mil FC, devido ao periodo de estiagem. Verificou-se que nos ultimos anos, o El Nino-Oscilacao Sul influenciou a incidencia dos FC atraves da persistencia de longos periodos de estiagem, que resultaram em escassez de chuvas e grandes incendios verificados em 2020 no bioma Pantanal.

Avaliação da expansão urbana na Cidade de Maceió, Alagoas – Nordeste do Brasil

Abstract: The growth of cities, along with the disorderly formation of large metropolises around the world, results in major changes in Land Use. However, few studies relate the urban sprawl and its effects on the cities of the Northeast of Brazil (NEB). Thus, this study aimed to evaluate the urban sprawl in Maceio-Alagoas between 1985 to 2020 from orbital Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) products to detect the changes and their environmental effects. This study used orbital products acquired from the systems-sensors Landsat 5 / Thematic Mapper (TM) and 8 / Operational Land Imager (OLI). The study used four images to observe the Spatio-temporal variation of urbanization, corresponding to the years 1987, 1998, 2006, and 2020. It used the environment software R for the generation of NDVI and LST thematic maps. The results obtained pointed out substantial changes in the Land Use detected by the NDVI and increased LST over the 35 years. Such variability occurred in the neighborhoods located in the northern and northwestern portion of the city, resulting from the incentive programs of the Federal Government in 2010, mainly the Benedito Bentes Complex (CBB), with the most significant transformations in the use and occupation of the soil, mainly the largest increase in LST between 7.5-10.0 °C. The effects produced by urban sprawls have been mitigated due to the environmental protection areas.

Avaliação do comportamento Vegetation Health Index no diagnóstico de secas no Nordeste brasileiro

Abstract: Nas últimas décadas, a ocorrência de secas aumentou ao longo do globo, inclusive no Brasil, e tais episódios ocorrem com maior severidade no Nordeste brasileiro (NEB). Como consequência, essas secas desencadeiam problemas ambientais, socioeconômicos e regionais. Neste trabalho, avaliou-se o comportamento desses eventos a partir do Vegetation Health Index (VHI) sobre o NEB. Esta análise será realizada a partir dos dados do Global Vegetation Health (GVH), com base nos registros de satélites via sensor Advanced Very High-Resolution Radiometer (AVHRR), disponibilizado pelo National Oceanographic and Atmospheric Administration (NOAA). Esses dados possuem resolução temporal em escala semanal durante os anos de 1982-2019, ao qual foram convertidos para composições anuais, enquanto a resolução espacial é de 4km x 4km. A partir de uma análise prévia selecionou-se os anos de 1983, 1993, 1998 (três episódios de El Niño) e 2012 (episódio atípico de La Niña), baseadas no Oceanic Niño Index (ONI). Os resultados obtidos do comportamento do VHI anual apontaram diferenças espaciais significativas, com as classes referentes a seca severa (VHI anual entre 0-6%) e extrema (VHI anual entre 6-12%) detectadas nos estados do Ceará, Piauí, e Rio Grande do Norte durante os anos 1983, 1993 e 2012. O ano de 2012 foi o mais severo entre os anos analisados, com o maior percentual da classe referente a seca extrema e severa com os valores de 0,5% e 5,5% da área total do NEB, respectivamente, principalmente na região central da Bahia. A seca iniciada durante o La Niña de 2012 perdurou até 2017 causou efeito devastador sobre o NEB, provocando forte variabilidade nos totais pluviométricos, culminando em enormes prejuízos socioambientais e econômicos.

Mestrado Integrado em Engenharia Química

Abstract: Paraquat is a quaternary ammonium compound whose use was forbidden in Europe due to its high risk for human health. However in many countries it is still been largely used as pesticide, leading to the accumulation of paraquat in the environment. It thus become urgent to find ways that allow an efficient removal of paraquat in contaminated waters. It’s also important to assure that degradation products formed during the removal of paraquat are less dangerous than the parent compound itself. The objective of the proposed work is to detect and identify the degradation products that result from the degradation of paraquat by Fenton’s reagent, using HPLC-DAD and LC-MS and if possible to quantify the degradation products identified. The experimental methodology involved the selection of possible degradation products based on bibliographic research, the implementation of an analytical method for their detection and the identification of these substances in the degradation of paraquato with Fenton’s reagent. By degradation of an aqueous solution containing 100 mg.L of paraquat by oxidation with Fenton’s reagent (oxidation conditions: [Fe]0 = 5,0 × 10 -4 M; [H2O2]0 = 1,6 × 10 -2 M; T0 = 30°C; pH0 = 3) three compounds were identified as degradation products oxalic acid, isonicotinic acid and 4-carboxy-1methylpyridinium ion. To calculate the relative importance of each of the degradation products identified, it was estimated the conversion of paraquat into each one of them after 4 hours of reaction. The conversion values estimated are: 11% to oxalic acid, 13% do 4-carboxy-1-methylpyridinum ion and 3% to isonicotinic acid. The degradation products identified represent 68% of the organic carbon remaining after 4 hours of reaction converted into the three degradation products identified. The organic carbon remaining after 4 hours of reaction, which, in turn, representes is 40% of the initial paraquat (60% of paraquat mineralization was reached after 4 hours). Five other compounds were detected by LC-MS analysis, whose molecular ion presented m/z 201, m/z 265, m/z 267, m/z 283 and m/z 291, probably responsible for the remaining 32% of the organic carbon not identified at the end of 4 hours of reaction. Detecao dos subprodutos resultantes da degradacao do pesticida paraquato por oxidacao quimica

Interactions of Environmental Variables and Water Use Efficiency in the Matopiba Region via Multivariate Analysis

Abstract: This study aimed to evaluate the interaction of environmental variables and Water Use Efficiency (WUE) via multivariate analysis to understand the importance of each variable in the carbon–water balance in MATOPIBA. Principal Component Analysis (PCA) was applied to reduce spatial dimensionality and to identify patterns by using the following data: (i) LST (MOD11A2) and WUE (ratio between GPP-MOD17A2 and ET-MOD16A2), based on MODIS orbital products; (ii) Rainfall based on CHIRPS precipitation product; (iii) slope, roughness, and elevation from the GMTED and SRTM version 4.1 products; and (iv) geographic data, Latitude, and Longitude. All calculations were performed in R version 3.6.3 and Quantum GIS (QGIS) version 3.4.6. Eight variables were initially used. After applying the PCA, only four were suitable: Elevation, LST, Rainfall, and WUE, with values greater than 0.7. A positive correlation (≥0.78) between the variables (Elevation, LST, and Rainfall) and vegetation was identified. According to the KMO test, a series-considered medium was obtained (0.7 < KMO < 0.8), and it was explained by one PC (PC1). PC1 was explained by four variables (Elevation, LST, Rainfall, and WUE), among which WUE (0.8 < KMO < 0.9) was responsible for detailing 65.77% of the total explained variance. Positive scores were found in the states of Maranhão and Tocantins and negative scores in Piauí and Bahia. The positive scores show areas with greater Rainfall, GPP, and ET availability, while the negative scores show areas with greater water demand and LST. It was concluded that variations in variables such as Rainfall, LST, GPP, and ET can influence the local behavior of the carbon–water cycle of the vegetation, impacting the WUE in MATOPIBA.

The assessment of climatic, environmental, and socioeconomic aspects of the Brazilian Cerrado

Abstract: Abstract Background The Cerrado is the most biodiverse savanna and maintains other biomes. Aware of its significance, this paper evaluated the Brazilian Cerrado’s climatic, environmental, and socioeconomic aspects using remote sensing data and spatial statistics (correlation analysis and principal components analysis—PCA). Following the measures of sample adequacy (MSA) and Kaiser–Meyer–Olkin (KMO) tests, seventeen variables were evaluated. Results The MSA revealed that the dataset had a good quality (0.76), and nine variables were selected: elevation, evapotranspiration, active fires, Human Development Index (HDI), land use and land cover (LULC; shrubland and cropland/rainfed), rainfall (spring and autumn), and livestock. The correlation matrix indicated a positive (negative) association between HDI and autumn rainfall (HDI and active fires) with a value of 0.77 (− 0.55). The PCA results determined which three principal components (PC) were adequate for extracting spatial patterns, accounting for 68.02% of the total variance with respective values of 38.59%, 16.89%, and 12.5%. Due to economic development and agribusiness, Cerrado’s northern (central, western, and southern) areas had negative (positive) score HDI values, as shown in PC1. Climatic (rainfall—spring and fall) and environmental (cropland/rainfed and shrubland) aspects dominated the PC2, with negative scores in northern and western portions due to the transition zone between Amazon and Cerrado biomes caused by rainfall variability. On the other hand, environmental aspects (LULC-shrubland and elevation) influenced the PC3; areas with high altitudes (> 500 m) received a higher score. Conclusion Agricultural expansion substantially affected LULC, leading to deforestation-caused suppression of native vegetation.

Previsão de Focos de Calor na Região Metropolitana de Maceió Utilizando Rede Neural Artificial

Abstract: O objetivo deste estudo é o de analisar a previsão de focos de calor (FC) na Região Metropolitana de Maceió (RMM) utilizando Rede Neural Artificial (RNA). Foram usados neste estudo os dados de focos de calor no período de 1999 a 2019, disponíveis no Banco de Dados de Queimadas (BDQueimadas). A previsão foi feita com base na RNA não linear autorregressiva (NAR) com os FC sendo dados de entrada e alvo. As previsões se basearam na função de ativação Tangente Hiperbólica e Sigmoide, para averiguar qual função se adaptaria melhor ao modelo de previsão de FC na RMM. O desempenho do modelo foi verificado pelo diagrama de espalhamento (1:1), com destaque para Regressão Linear Simples (RLS), os coeficientes de determinação (R2) e de Pearson (r), seguido dos indicadores de erros (EM - Erro Médio, REQM – Raiz do Erro Quadrático Médio, EPAM – Erro Percentual Absoluto Médio). O EM variou entre -0,47 a 1,49 focos, o REQM (1,16 a 7,02 focos) e o EPAM (14,45 a 24,66%). Os coeficientes r (0,08 a 0,52) e R2 (1 a 58%). Os modelos com base nas funções de ativação foram similares entre observado e previsto, sendo satisfatória na maioria dos municípios. Os modelos não tiveram sucesso na previsão de FC elevados, principalmente nos anos 2008, 2012, 2015 e 2016, período de seca extrema. Os resultados obtidos indicam que a aplicação de RNA na previsão de FC pode auxiliar nas tomadas de decisões dos gestores públicos e no monitoramento de queimadas e incêndios em áreas urbanas.Palavras-chave: incêndios, inteligência artificial, monitoramento ambiental. Forecast of Fire Foci in the Metropolitan Region of Maceió Using Artificial Neural NetworkABSTRACTThe aim of this study is to analyze the forecast of fire foci (FF) in the Maceió Metropolitan Region (MMR) using Artificial Neural Network (ANN). It was used in the study fire foci data available in the Burning Database (BDQueimadas) in the period from 1999 to 2019. The forecast was made based on the ANN non-linear autoregressive (NAR) with the FF, being input and target data. The forecast was based Hyperbolic Tangent and Sigmoid activation function, to find out which function would best adapt to the forecast model of FF in the MMR. The model performance was based on the Scatter Diagram (1:1), with emphasis on Simple Linear Regression (SLR), the coefficients of determination (R2) and Pearson’s (r), followed by the error indicators (ME – Mean Error, RMSE – Root Mean Square Error, MAPE – Mean Absolute Percentage Error). The ME ranged from -0.47 to 1.49 foci, RMSE (1.16 to 7.02 foci), MAPE (14.45 to 24.66%). The coefficients r (0.08 to 0.52) and R2 (1 to 58%). The models based on activation function were similar between observed and predicted, being satisfactory in most municipalities. The models were not successful in forecast high FF, especially in the years 2008, 2012, 2015 and 2016, a period of extreme drought. These results obtained in the study indicate that the application of ANN in the forecast of FF can help in the decision-making of public managers and in the monitoring of burnings and fires in urban areas.Keywords: Fire foci, Artificial Intelligence, Environmental Monitoring.

Agronegócio sucroenergético e desenvolvimento no Brasil

Abstract: Neste artigo analisamos os impactos da territorializacao recente (especialmente de 2003 a 2013) do setor sucroenergetico nos municipios do estado de Sao Paulo, Brasil. Em 2003 o governo brasileiro retomou o incentivo ao setor como parte da estrategia de insercao do pais na economia mundial atraves das commodities agrominerais. O objetivo era aproveitar as discussoes internacionais sobre o desenvolvimento sustentavel e oferecer ao mercado mundial o etanol - combustivel nao fossil - como alternativa ao petroleo. O governo tambem estimulou o consumo interno deste agrocombustivel, que na atualidade e o principal destino do etanol brasileiro. O aumento da demanda fez com que o setor dobrasse de tamanho em dez anos. O estado de Sao Paulo concentra metade do agronegocio sucroenergetico brasileiro e comportou metade da expansao recente, transformando a paisagem em um “mar de cana-de-acucar”. Muitos municipios foram fortemente impactados pela intensificacao do setor. Sendo assim, o centro de nossas analises neste artigo e sobre as caracteristicas desses impactos, seus desdobramentos para o desenvolvimento economico e social e quais sao os limites deste modelo de desenvolvimento baseado no agronegocio, que e a face do desenvolvimento capitalista no campo.