https://tedebc.ufma.br/jspui/handle/tede/5995 Credenciado pela CAPES como Mestrado Acadêmico, na área de Geociências, o PPGC&TAmb teve início com a atualização do seu Regimento Interno em outubro de 2022, conforme decisão do Conselho de Ensino, Pesquisa, Extensão e Inovação (Consepe). Este marco reforça o compromisso da UFMA em promover a excelência acadêmica e impulsionar o avanço científico e tecnológico na região. Esta Coleção contém os trabalhos do Mestrado Acadêmico. Wed, 10 Jun 2026 02:51:29 GMT 2026-06-10T02:51:29Z https://tedebc.ufma.br/jspui/handle/tede/7038 Título: Efeito alelopático de Solanum paniculatum para o controle sustentável da planta daninha Leucaena leucocephala Autor: OLIVEIRA, Rainara Ribeiro Primeiro orientador: OLIVEIRA, Regina Maria Mendes Abstract: Despite advances in agriculture, productivity losses still occur due to the presence of invasive plants, which represent a major obstacle to agricultural production. Based on this assumption, the objective of this study was to evaluate the allelopathic potential of the crude extract and fractions of Solanum paniculatum, compared to glyphosate, on Leucaena leucocephala. The leaves of S. paniculatum were collected in the municipality of Anapurus-MA and identified in the CCAA/UFMA Herbarium under voucher no. 5399. The material was dried, crushed, and subjected to extraction. Two hundred grams of leaves were used in 99.5% ethanol and water, subjected to percolation for 30 days. The preparation of the crude extract and fractions was carried out at the Natural Products Chemistry Laboratory (LQPN/CAMQ/UFMA), followed by chemical characterization. L. leucocephala was used as the recipient plant, testing concentrations of 2% and 5%. Bioassays of bioherbicidal potential were conducted in a completely randomized design (CRD), with four treatments (including positive and negative controls) in four replicates. Statistical analysis was performed using ANOVA, followed by Tukey's test (5%), using InfoStat® (2010) and Excel® (2019) software for data tabulation and interpretation. The study evaluated the allelopathic potential of Solanum paniculatum on Leucaena leucocephala from the crude hydroalcoholic extract (EBH) and its fractions. The EBH was the most active, inhibiting 95% of germination at 5%, in addition to reducing radicle growth (76% at 5%) and hypocotyl growth (70% at 5%). Among the fractions, acetate performed best, with 65% inhibition of the radicle at 5% and 66% of the hypocotyl at 5%. The hexane phase stood out at 2%, with 72% inhibition of the radicle, while the aqueous phase was most effective at 1%, inhibiting 56% of the hypocotyl. Instituição: Universidade Federal do Maranhão Tipo do documento: Dissertação; Trabalho sob Sigilo.Motivo do sigilo: Publicação do Trabalho.Submetido, ainda não publicado. Mas no ato da submissão foi feita uma declaração de direito autoral à revista. Prazo previsto para disponibilização total: 3 anos. Thu, 26 Feb 2026 00:00:00 GMT https://tedebc.ufma.br/jspui/handle/tede/7038 2026-02-26T00:00:00Z https://tedebc.ufma.br/jspui/handle/tede/7037 Título: Síntese e caracterização de um sensor a base de polianilina (PANI) fototermicamente estimulado para detecção de amônia Autor: RIBEIRO NETO, João Durval Primeiro orientador: MENDONÇA, Leonado Tadeu Boas Abstract: The field of gas and volatile compound sensing has gained prominence in the food, beverage, and fuel industries due to sensors' ability to detect and quantify substances imperceptible to humans. However, many sensors rely on metal oxides, which require high temperatures for analysis, making the search for new materials necessary. Among conductive materials, Polyaniline (PANI) stands out due to its electrical conductivity, optical properties, and broad applicability. This study proposes modifications to PANI using nanotechnology and photothermal effects to enhance its performance. The main objective was to obtain nanostructured conductive polymers and study their electrical behavior under photothermal stimulation in the presence of gases and volatile compounds. The PANI synthesis employed the surfactant Triton X-100. For photothermal characterization, a setup was assembled with an infrared LED (780 nm, 3W) to excite the samples dispersed in water, enabling the calculation of photothermal conversion efficiency. The synthesized samples were analyzed by X-ray diffraction (XRD) at UFMA’s central analytical facility. Particle morphology was examined using scanning electron microscopy (SEM), while FT-IR, UV-Vis, and XRD spectra were obtained to correlate structural and optical properties. Sensor fabrication employed spin-coating deposition onto a substrate, developed at the Colloids Laboratory (UFMA), to form thin films. Sensor tests were conducted using ammonium hydroxide (NH4OH), injected via microsyringe (0-100 µL) at varying concentrations, with injection cycles to estimate response times and signal recovery, using a vacuum system. Electrical resistance was monitored using a controlled voltage source and a 4 ½-digit multimeter. During testing, the sensor was stimulated by an infrared LED (3V) to evaluate its photothermal performance. The results demonstrated that photothermal conversion improved selectivity and response speed due to irradiation-induced heating. The study highlighted the potential of photothermally induced nanostructured polymers as sensors for volatile compounds and gases, establishing a new research direction. Instituição: Universidade Federal do Maranhão Tipo do documento: Dissertação Tue, 15 Jul 2025 00:00:00 GMT https://tedebc.ufma.br/jspui/handle/tede/7037 2025-07-15T00:00:00Z https://tedebc.ufma.br/jspui/handle/tede/7036 Título: Microplásticos em água potável e de abastecimento: eficiência de remoção em estações de tratamento e potenciais riscos à saúde.  Autor: XIMENES, Dayara da Silva Primeiro orientador: JORGE, Marianna Basso Abstract: Microplastics (MPs) have garnered global attention as persistent emerging pollutants and that pose a threat to the environment. In addition to causing various physical and biological effects, they can act as adsorbents for hazardous contaminants. Recently, studies have detected their presence in both raw and treated water from drinking water treatment plants (DWTPs), highlighting a potential risk to human health. The study quantifies microplastics based on their shape and color, analyzes seasonal variations in supply water, evaluates the removal efficiency of microplastics in DWTPs, and estimates the daily and annual intake of these pollutants through drinking water. To achieve these objectives, surface water (SW), water column (WC), and treated drinking water (DW) samples were analyzed during both the dry and rainy seasons using a combination of sieving, density separation, digestion, oxidation, vacuum filtration, and optical microscopy techniques. Microplastics were found in all water samples, in both dry and rainy periods, with average concentrations ranging from 294 ± 73 to 118 ± 41 MPs/L in SW, from 164 ± 42 to 105 ± 35 MPs/L in WC, and from 48 ± 11 to 28 ± 12 MPs/L in DW. The comparison of samples before and after treatment showed that 68% of the particles were removed at the DWTP. The estimated daily intake for children was 2.8 ± 1.6 MPs/kg/L/day, totaling 1038 ± 590 MPs/kg/L/year, and for adults, 1.2 ± 0.6 MPs/kg/L/day, totaling 427 ± 228 MPs/kg/L/year. This study contributes to bridging the knowledge gap regarding emerging microplastic pollution in drinking water and freshwater sources, which is of concern due to the potential for human exposure to these pollutants. Instituição: Universidade Federal do Maranhão Tipo do documento: Dissertação Mon, 16 Jun 2025 00:00:00 GMT https://tedebc.ufma.br/jspui/handle/tede/7036 2025-06-16T00:00:00Z https://tedebc.ufma.br/jspui/handle/tede/7028 Título: IDENTIFICAÇÃO DE ÁREAS DE EMISSÃO DE MATERIAL PARTICULADO A PARTIR DE MODELOS FENOMENOLÓGICOS DE DISPERSÃO ATMOSFÉRICA E ALGORITMOS DE APRENDIZADO PROFUNDO Autor: PEREIRA, Lanna Almeida Primeiro orientador: VILLA-VÉLEZ, Harvey Alexander Abstract: The combined operation of multiple particulate matter (PM) emission sources in industrial and port areas creates major environmental threats and serious public health risks. Current methods of monitoring and predictive models lack sufficient capability to detect PM emission sources in real time. This study developed an integrated framework that uses Artificial Neural Networks (ANNs) and Computational Fluid Dynamics (CFD) to precisely locate PM emission sources in flat terrain. The CFD model was validated through experimental data analysis and the MoninObukhov similarity theory to precisely represent the particulate matter transport and atmospheric profiles. We created a simulation dataset containing 243 runs that tested different wind speed and direction combinations with variations in emission height and emission interval. The dataset served as training material for two deep learning models which used Long Short-Term Memory (LSTM) and a one-dimensional Convolutional Neural Network (CNN1D) to perform PM emission location classification. Both models achieved high accuracy levels with F1- scores above 0.95. The time needed to optimize hyperparameters proved the difference between models because LSTM required 4 h and 15 min and CNN1D needed 4 h and 43 min. This study proves that using CFD-generated data with ANN models allows reliable emission source localization which shows promise for environmental regulation, industrial accountability, and public health protection. The proposed framework represents a major breakthrough in real-time PM source localization in industrial and port environments. Instituição: Universidade Federal do Maranhão Tipo do documento: Dissertação Fri, 27 Feb 2026 00:00:00 GMT https://tedebc.ufma.br/jspui/handle/tede/7028 2026-02-27T00:00:00Z