http://hdl.handle.net/10174/37666 Sat, 04 Apr 2026 09:19:05 GMT 2026-04-04T09:19:05Z http://hdl.handle.net/10174/40476 Title: Reappraisal of active tectonics of the Porto Alto buried fault zone (Portugal) considering new geophysical shallow studies Authors: Carvalho, J.; Cabral, J.; Borges, J.; Dias, R. Editors: LNEG - Comunicações Geológicas Abstract: The Lower Tagus Valley area (LTV), where Lisbon is located, has been affected by several destructive, M 6+ earthquakes whose sources remain to be determined. The identification of expectable surface or near surface ruptures in the area is a challenging task that requires a multidisciplinary analysis that includes geophysical techniques, as the source faults are mainly buried despite likely to deform Upper Pleistocene to Holocene alluvial cover of the Tagus River. This paper focuses on the characterization of the Porto Alto fault zone for seismic hazard mitigation purposes. The Porto Alto fault zone was recognized in oil-industry P-wave 1980’s seismic reflection data as an important, Miocene reactivated, deep structure in the LTV. High-resolution P-wave seismic reflection data were later acquired in the early 2000’s to investigate related Holocene fault activity, leading to the identification of a shallow fault zone near the surface. However, the vertical resolution of the acquired P-wave seismic reflection data was considered insufficient to corroborate any presumably small vertical offset related to fault rupture in the ca. 50 m thick alluvium cover. Trenching for the recognition and characterization of surface faulting was previously tested in the study region but it proved to be a challenging and poorly efficient methodology due to the very shallow water table (at ~1 m) and low cohesion of the sediments. Due to these constraints, we revisited the former fault study site to acquire higher resolution S-wave seismic and ground penetrating radar (GPR) data. The new seismic profiles show interruption of the reflectors in the stacked sections. Diffracted energy, changes in amplitude/shape of the reflection hyperbolae in the shot gathers and spatially coincident low velocity anomalies, also indicate the presence of several shallow fault strands deeper than 10 m. The GPR profile, overlapping and extending the seismic profiles in 30 m reaches a maximum investigation depth of about 15 m and shows the presence of deformation at three locations, one of which matches with one of the fault strands detected in the high-resolution S-wave seismic data. In this profile, sediment disruption was detected extending upwards to a depth as shallow as ca. 3.5 m, corresponding to alluvium with a poorly constrained age of ca. 2,300 yrs. Slip rate, maximum earthquake magnitude and recurrence, and other parameters are also estimated for the Porto Alto fault zone. These recently acquired seismic and GPR datasets indicate that there were at most three to five maximum earthquakes generated by the fault in the last 13,100 years, with an average recurrence of approximately 4,400 to 2,600 years respectively. However, the data show a grouping of these earthquakes in time, the first two in the period 13,100-12,300 years, separated by about 800 years, and the third or the last grouped three having occurred in the past 2,300 years with a similar average recurrence time of ca. 800 years. However, the regional historical and instrumental seismicity does not show an obvious link of any known major earthquake with the Porto Alto fault zone. Mon, 01 Jan 2024 00:00:00 GMT http://hdl.handle.net/10174/40476 2024-01-01T00:00:00Z http://hdl.handle.net/10174/40334 Title: AI-Driven Estimation of Aerosol Optical Thickness using Remote Sensing and Meteorological Data Authors: Marinho, David; Gonçalves, Teresa; Costa, Maria João Abstract: Accurately estimating Aerosol Optical Thickness (AOT) is essential for understanding atmospheric aerosol dynamics and their climatic effects. In this study, a machine learning model was developed using the Random Forest (RF) algorithm, to estimate AOT at 500 nm. The reference AOT data are obtained from the AERONET network, using data from the Évora Atmospheric Sciences Observatory (Portugal), ensuring high-quality training and validation. The RF model, configured with 160 estimators and a maximum depth of 35, was trained using a dataset of global horizontal radiation, solar zenith angle, precipitable water vapor and meteorological variables. The model achieves a root mean square error (RMSE) of 0.0594, demonstrating its effectiveness in capturing AOT variability. This AI-driven approach offers a promising tool for estimating AOT in regions with limited direct aerosol observations, thereby enhancing atmospheric monitoring and climate research. Wed, 01 Jan 2025 00:00:00 GMT http://hdl.handle.net/10174/40334 2025-01-01T00:00:00Z http://hdl.handle.net/10174/40038 Title: Instrumento de gestão de áreas contaminadas por metais combinando dados de Química, Geofísica, Deteção Remota, Inteligência Artificial e Gestão – Projeto INCOME Authors: Oliveira, Rui; Caldeira, Bento; Palma, Patricia; Costa, Maria João; Fialho, Ana Editors: Oliveira, Rui; Caldeira, Bento; Bortoli, Daniele; Guerrero-Rascado, Juan Luis; Costa, Maria João; Bezzeghoud, Mourad; Salgueiro, Vanda Abstract: O Projeto INCOME tem como objetivo propor a criação de um modelo de gestão ambiental para áreas mineiras contaminadas por metais potencialmente tóxicos. Este modelo integra os resultados da aplicação de um conjunto de métodos analíticos e instrumentos de monitorização de áreas contaminadas, como análises da vegetação, química de solos e águas, geofísica e deteção remota por satélite. Estes dados serão utilizados como inputs em algoritmos de inteligência artificial, o que permitirá a produção de modelos de monitorização da contaminação utilizando menos dados do que as metodologias-padrão. Propõe-se a criação de um modelo de gestão sustentável, baseado na combinação de ferramentas a desenvolver, que permitirá a otimização e poupança de recursos nas fases de amostragem e análise, fornecendo informação importante em tempo real para a tomada de decisão com vista à gestão integrada das áreas contaminadas. O instrumento terá ampla aplicabilidade na deteção de contaminação por metais, abrindo a possibilidade à transferência de tecnologia para diferentes áreas geográficas e para outros cenários de contaminação por metais, como aterros sanitários, indústria e explorações agrícolas. O retorno ambiental, social e económico para as áreas contaminadas deriva da incorporação de novas estratégias às rotinas atuais; redução e otimização de procedimentos e tempos de execução; economia de recursos; recuperação mais eficaz do local contaminado; equilíbrio dos ecossistemas; retorno para empresas; redução da pegada ambiental; e promoção da sustentabilidade social, ambiental e económica da região. Sat, 31 May 2025 23:00:00 GMT http://hdl.handle.net/10174/40038 2025-05-31T23:00:00Z http://hdl.handle.net/10174/40010 Title: FONTE DO SISMO DE MARROCOS DE 2023 (MW6.8) INFERIDA A PARTIR DO CRUZAMENTO DE DADOS SÍSMICOS E GEODÉSICOS Authors: Caldeira, Bento; Bezzeghoud, Mourad; Oliveira, Rui; Borges, José; Hamak, Ines; Buforn, Elisa Editors: Oliveira, Daniel; Lourenço, Paulo; Guerreiro, Luís; Silva, Rui Abstract: On September 8, 2023, at 22:11 UTC, an earthquake of magnitude 6.8 with epicenter near the village of Talat N'Yaaqoub, province of Al Haouz (Morocco), High Atlas region, shook violently the entire epicentral zone within a radius of more of 70km, seriously affecting the structures of more than 78,000 buildings and causing approximately 5,600 injuries and around 3,000 fatalities. This work presents part of the detailed source study of this earthquake, based on the interpretation of seismic and geodetic data, applying a crossing of methods. The results reveal a rupture beginning at a depth of 24km and evolving for around 10 s, on a sub-vertical fault plane oriented ENE-WSW with a dip towards NNW. The slips on the fault plane are mostly upward (reverse) but with a strike slip component in the WSW direction (left-lateral). The total seismic moment released by this source was M0=2.8x1019Nm Mon, 01 Jan 2024 00:00:00 GMT http://hdl.handle.net/10174/40010 2024-01-01T00:00:00Z