O Programa de Pós-Graduação em Ciência & Tecnologia Ambiental (PPGC&TAmb) da Universidade Federal do Maranhão (UFMA) tem como objetivo central fomentar a produção de conhecimento e formar recursos humanos para a pesquisa científica, tecnológica e de inovação, com ênfase nas Ciências e Tecnologias Ambientais. Sua criação representa um avanço significativo no ciclo de desenvolvimento do Centro de Ciências Exatas e Tecnologia (CCET) da UFMA, fortalecendo a pesquisa no contexto acadêmico da instituição. https://tedebc.ufma.br/jspui/handle/tede/5994 2026-06-04T22:46:03Z 2026-06-04T22:46:03Z RIBEIRO NETO, João Durval https://tedebc.ufma.br/jspui/handle/tede/7037 2026-06-03T19:02:53Z 2025-07-15T00:00:00Z

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

2025-07-15T00:00:00Z XIMENES, Dayara da Silva https://tedebc.ufma.br/jspui/handle/tede/7036 2026-06-03T18:46:09Z 2025-06-16T00:00:00Z

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

2025-06-16T00:00:00Z PEREIRA, Lanna Almeida https://tedebc.ufma.br/jspui/handle/tede/7028 2026-06-01T13:04:18Z 2026-02-27T00:00:00Z

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

2026-02-27T00:00:00Z MAIA, João Vitor Soares https://tedebc.ufma.br/jspui/handle/tede/6874 2026-03-26T18:47:16Z 2025-06-27T00:00:00Z

Título: Pesca artesanal e conservação de Elasmobrânquios: Avaliação da captura e indícios de um potencial berçário em um ponto crítico da pesca artesanal na Costa Amazônica Maranhense Autor: MAIA, João Vitor Soares Primeiro orientador: RINCON FILHO, Getulio Abstract: Artisanal fishing of elasmobranchs (sharks and rays) on the western coast of Maranhão was investigated with the aim of understanding its dynamics, identifying nursery areas and assessing the perception of local fishermen regarding the conservation of these animals. The study was motivated by the growing fishing pressure in the region and the lack of consistent data on catches, which makes fishing management difficult. The research was carried out in the Arapiranga-Tromaí RESEX region, through systematic monitoring of fishing landings in Carutapera, MA between 2023 and 2024, interviews with fishermen, and the use of georeferencing tools. During the 19-month cycle, 118 landings were monitored and 1.054 elasmobranch captures were recorded, comprising 11 shark species and 8 ray species, distributed across 3 shark families, 6 ray families, 2 shark orders, and 1 ray order. The species Hypanus guttatus, Rhizoprionodon porosus, and Sphyrna lewini were particularly emphasized, being recorded at all stages of development. Areas with a continuous presence of neonates and juveniles were identified, indicating the possible occurrence of nursery areas. Statistical analysis showed a composition dominated by juveniles, evidencing the vulnerability of the species to capture. The research demonstrated that fishermen possess valuable ecological knowledge, which can be integrated into management and conservation actions. It is concluded that, in addition to providing unprecedented data on local artisanal fishing, the study contributes to the formulation of public policies and strategies aimed at fisheries sustainability and the protection of marine biodiversity. Instituição: Universidade Federal do Maranhão Tipo do documento: Dissertação

2025-06-27T00:00:00Z