Search Results (94)

This study explores the potential for afforestation in Portugal that could balance wood and non-wood forest production under future climate change scenarios. The Climate Envelope Models (CEM) approach was employed with three main objectives: (1) to model the current distribution of key Portuguese forest species—eucalypts, maritime pine, umbrella pine, chestnut, and cork oak—based on their suitability for wood and non-wood production; (2) to project their potential distribution for the years 2070 and 2090 under two Shared Socioeconomic Pathway (SSP) scenarios: SSP2–4.5 (moderate) and SSP5–8.5 (high emissions); and (3) to generate integrated species distribution maps identifying both current and future high-suitability zones to support afforestation planning, reflecting climatic compatibility under fixed thresholds. Species’ current CMEs were produced using an additive Boolean model with a set of environmental variables (e.g., temperature-related and precipitation-related, elevation, and soil) specific to each species. Species’ current CEMs were validated using forest inventory data and the official Land Use and Land Cover (LULC) map of Portugal, and a good agreement was obtained (>99%). By the end of the 21st century, marked reductions in species suitability are projected, especially for chestnut (36%–44%) and maritime pine (25%–35%). Incorporating future suitability projections and preventive silvicultural practices into afforestation planning is therefore essential to ensure climate-resilient and ecologically friendly forest management. Full article

Wildfires are among the most frequent and destructive natural hazards in Europe, particularly in Portugal. They have severe impacts on forests, ecosystems, human health, and infrastructure, leading to substantial socio-economic losses due to firefighting efforts and post-fire recovery costs. Moreover, wildfires cause numerous casualties each year, highlighting the need for a deeper understanding of fire behaviour to support effective firefighting strategies and ensure the safety of both responders and communities. This study examines the influence of wind flow velocity variation on fire behaviour, both in the presence and absence of an edge wall in the fuel bed, aiming to replicate the characteristics of real wildfire fronts at a laboratory scale. Experimental tests were conducted at the Forest Fire Research Laboratory (LEIF) of the University of Coimbra using a shrub mixture, composed of Ulex europaeus, Baccharis trimera, and Caralluma adscendens, representing one of the most common fine fuels in Portuguese forested landscapes. This research provides novel insights by experimentally analyzing the combined effect of wind velocity variation and fuel bed edge presence on fire behaviour, paving the way for future comparisons with numerical simulations and real wildfire fronts. As expected, increasing wind velocity and the presence of fuel bed edges resulted in higher values of rate of spread, fireline intensity, and fire intensity. Full article

Forests play a central role in climate change mitigation by acting as biogenic carbon reservoirs and providing renewable biomass for energy systems. In Portugal, where fire-prone landscapes and species composition dynamics pose increasing management challenges, understanding the carbon storage potential of forest biomass is crucial for designing effective decarbonization strategies. This study provides a comprehensive characterization of the Portuguese forest and quantifies the biogenic carbon stored in live and dead biomass across the main forest species. Species-specific carbon contents, rather than the conventional 50% assumption widely used in the literature, were applied to National Forest Inventory data, enabling more realistic and representative carbon stock estimates expressed in kilotonnes of CO₂ equivalent. While the approach relies on inventory-based biomass data and literature-derived carbon fractions and is therefore subject to associated uncertainties, it provides an improved representation of species-level carbon storage at the national scale. Results show that Pinus pinaster, Eucalyptus globulus, and Quercus suber together represent the largest share of carbon storage, with approximately 300,000 kilotonnes of CO₂ equivalent retained in living trees. Wood is the dominant carbon pool, but roots and branches also account for a substantial fraction, emphasizing the need to consider both above- and below-ground biomass in carbon accounting. In parallel, a bibliometric analysis based on the systematic evaluation of scientific publications was conducted to characterize the evolution, thematic focus, and geographic distribution of global research on forest-based biogenic carbon. This analysis reveals a rapidly expanding scientific interest in biogenic carbon, particularly since 2020, reflecting its growing relevance in climate change mitigation frameworks. Overall, the results underscore both the strategic importance of Portuguese forests and the alignment of this research with the broader international scientific agenda on forest-based biogenic carbon. Full article

Road traffic accidents remain a major global challenge, contributing to significant human and economic losses each year. In Portugal, the analysis and prevention of severe accidents are critical for optimizing the allocation of law enforcement resources and improving emergency response strategies. This study aims to develop and evaluate predictive models for accident severity using real-world data collected by the Portuguese Guarda Nacional Republicana (GNR) between 2019 and 2023. Four algorithms, Random Forest, XGBoost, Multilayer Perceptron (MLP), and Deep Neural Networks (DNN), were implemented to capture both linear and non-linear relationships within the dataset. To address the natural class imbalance, class weighting, Synthetic Minority Oversampling Technique (SMOTE), and Random Undersampling were applied. The models were assessed using Recall, F1-score, and G-Mean, with particular emphasis on detecting severe accidents. Results showed that DNNs achieved the best balance between sensitivity and overall performance, especially under SMOTE and class weighting conditions. The findings highlight the potential of classical machine learning and deep learning models to support proactive road safety management and inform resource allocation decisions in high-risk scenarios.This research contributes to sustainability by enabling data-driven road safety management, which reduces human and economic losses associated with traffic accidents and supports more efficient allocation of public resources. By improving the prediction of severe accidents, the study reinforces sustainable development goals related to safe mobility, resilient infrastructure, and effective disaster prevention and response policies. Full article

Monitoring agricultural land in regions undergoing rapid change is essential for supporting management, policy development, and biodiversity conservation. Dam construction and associated irrigation systems drive land use change transitions from annual to permanent crops and intensify cultivation systems. Mapping crop types at the parcel level, particularly permanent crops, is therefore critical. The EU Crop Map 2018, the first attempt to map annual crops across the European Union using remote sensing and machine learning, aggregates permanent crops into the generic class “shrublands and woodlands”. This study refines the EU Crop Map classification by distinguishing permanent crop types using an automated machine learning model integrating Sentinel S1 and S2 imagery. The study area surrounds the Alqueva reservoir in southern Portugal, one of the Europe’s largest artificial lakes, where recent irrigation system expansion has driven rapid permanent crop adoption. The model achieved 91% overall accuracy, demonstrating strong performance in distinguishing permanent crops, forests, and other occupations. It effectively identified almond groves (F1 score = 0.90), and distinguished three major olive grove cultivation systems (F1-score ≥ 0.78), though performance was lower for vineyards (0.71) and other permanent crops (0.48). Comparison with the Portuguese official land use product COS 2018 showed strong overall spatial alignment, despite several inconsistencies, and lower F1 scores (0.60) in the direct comparison the new mapping produced. This study used a large reference dataset, enabling the assessment of the effect of training set size on classification accuracy. While overall accuracy remained above 83%, even with only 5% of the training data, underrepresented classes experienced significant performance degradation, highlighting the critical need to address class imbalance in agricultural land cover mapping. Full article

The increasing emphasis on environmental sustainability has placed biomass as a versatile and renewable resource, while the management and disposal of forest byproducts remain a significant challenge. This study explores the valorization of forest biomass residues derived from Pinus pinaster, Pinus pinea, and the invasive species Acacia dealbata, with a focus on their potential application as bioadsorbents. A comprehensive physicochemical characterization was conducted for different biomass fractions (leaves, needles, and branches of varying diameters). Leaves and needles contained higher amounts of extractives (from 7.7% in acacia leaves to 18.8% in maritime pine needles) and ash (3.4 and 4.2% in acacia leaves and stone pine needles, respectively), whereas branches contained more holocellulose (from 59.6% in P. pinea small branches to 79.2% in P. pinaster large branches). ATR-FTIR and pHpzc analyses indicated compositional and surface charge differences, with higher pHpzc values in A. dealbata relative to Pinus. TG analysis showed that acacia large branches degraded at a lower temperature (320 °C) compared to Pinus species (440–450 °C). Overall, the findings highlight the suitability of these underutilized forest byproducts as bioadsorbents, contributing to the advancement of circular economy practices. Full article

Portugal’s commitment to carbon neutrality by 2050 has intensified the search for renewable energy alternatives, with biomass gasification emerging as a promising pathway for hydrogen production. This comprehensive review analyzes the potential of 39 Portuguese biomass species for gasification processes, based on extensive laboratory characterization data including proximate analysis, ultimate analysis, heating values, and metal content. The studied biomasses encompass woody shrubland species (matos arbustivos lenhosos), forest residues, and energy crops representative of Portugal’s diverse biomass resources. Results indicate significant variability in gasification potential, with moisture content ranging from 0.5% to 14.9%, ash content from 0.5% to 5.5%, and higher heating values between 16.8 and 21.2 MJ/kg. Theoretical hydrogen yield calculations suggest that Portuguese biomasses could produce between 85 and 120 kg H₂ per ton of dry biomass, with species such as Eucalyptus globulus, Pinus pinaster, and Cytisus multiflorus showing the highest potential. Statistical analysis reveals strong negative correlations between moisture content and hydrogen yield potential (r = −0.63), while carbon content shows positive correlation with gasification efficiency. The comprehensive characterization provides essential data for optimizing gasification processes and establishing Portugal’s biomass-to-hydrogen production capacity, contributing to the national hydrogen strategy and renewable energy transition. Full article

The National Museum of Natural History and Science holds a historical collection of 279 small African mammal specimens (Macroscelidea and Rodentia), representing 32 species, gathered during the Portuguese colonial period in Mozambique, Angola, and Guinea-Bissau. This study examines the collection, updates the small mammal species lists for each country, and highlights its importance as a historical baseline for biodiversity research. Rodents dominate the collection, reflecting their natural abundance and diversity, while Macroscelidea are less represented. The Angolan subset of the collection has the highest number of both specimens and species represented. Mozambique is underrepresented, and the Guinea-Bissau subset offers an extensive rodent representation of the country’s inventory. The most well-represented species are Gerbilliscus leucogaster, Lemniscomys striatus, Lemniscomys griselda (from Angola), and Heliosciurus gambianus (from Guinea-Bissau). Notably, the collection includes the neo-paratype of Dasymys nudipes (from Angola). Most species are common and not currently threatened, with geographic origin corresponding to savanna and forest habitats. These findings underscore the importance of integrating historical data and current biodiversity assessments to support multidisciplinary studies on target species, regions, or countries. In this context, the collection remains a valuable key resource for advanced research on African small mammals. Full article

Active and abandoned mining sites are significant sources of heavy metals and metalloid pollution, leading to serious environmental issues. This study assessed the environmental risks posed by potentially toxic elements (PTEs), specifically arsenic (As) and antimony (Sb), in the Technosols (mining residues) of the former Pejão coal mine complex in Northern Portugal, a site impacted by forest wildfires in October 2017 that triggered underground combustion within the waste heaps. Our methodology involved determining the “pseudo-total” concentrations of As and Sb in the collected heap samples using microwave digestion with aqua regia (ISO 12914), followed by analysis using hydride generation-atomic absorption spectroscopy (HG-AAS). The concentrations of As an Sb ranging from 31.0 to 68.6 mg kg⁻¹ and 4.8 to 8.3 mg kg⁻¹, respectively, were found to be above the European background values reported in project FOREGS (11.6 mg kg⁻¹ for As and 1.04 mg kg⁻¹ for Sb) and Portuguese Environment Agency (APA) reference values for agricultural soils (11 mg kg⁻¹ for As and 7.5 mg kg⁻¹ for Sb), indicating significant enrichment of these PTEs. Based on average I_geo values, As contamination overall was classified as “unpolluted to moderately polluted” while Sb contamination was classified as “moderately polluted” in the waste pile samples and “unpolluted to moderately polluted” in the downhill soil samples. However, total PTE content alone is insufficient for a comprehensive environmental risk assessment. Therefore, further studies on As and Sb fractionation and speciation were conducted using the Shiowatana sequential extraction procedure (SEP). The results showed that As and Sb levels in the more mobile fractions were not significant. This suggests that the enrichment in the burned (BCW) and unburned (UCW) coal waste areas of the mine is likely due to the stockpiling of lithic fragments, primarily coals hosting arsenian pyrites and stibnite which largely traps these elements within its crystalline structure. The observed enrichment in downhill soils (DS) is attributed to mechanical weathering, rock fragment erosion, and transport processes. Given the strong association of these elements with solid phases, the risk of leaching into surface waters and aquifers is considered low. This work underscores the importance of a holistic approach to environmental risk assessment at former mining sites, contributing to the development of sustainable remediation strategies for long-term environmental protection. Full article

The Portuguese forest plays a crucial role in maintaining ecological balance and fostering socio-economic sustainability within rural areas. Nonetheless, it is currently facing significant challenges due to the increasing intensity and frequency of forest fires observed in recent decades. The deterioration of traditional agricultural practices, the proliferation of monocultures, and alterations in land use patterns have significantly exacerbated these challenges. Consequently, the landscape has undergone considerable transformations, resulting in a decline in biodiversity and a weakening of local economies. This study examines land use in mainland Portugal from 1995 to 2018, utilising data on land occupation, land cover, and burnt areas from the Institute for Nature Conservation and Forests. The cartographic analysis of three periods—1995, 2007, and 2018—along with the fire data recorded between 1996 and 2018, enabled the observation of changes in the predominant land use and land cover (LULC) classes, particularly among forests, scrubland, and agricultural areas. The results highlight a significant increase in forested areas, especially eucalyptus, as well as urbanisation, while scrubland and agricultural areas have decreased. Using specific LULC level 4, and burnt (BA) and unburnt (NB) areas, temporary crops decreased substantially (−14% NB/−4% BA 1995–2007; −23% NB by 2018). Eucalyptus showed strong continuous growth (16% NB/35% BA 1995–2007; 23% NB/47% BA 2007–2018). Maritime pine suffered severe losses, especially in burnt areas (−42%/−28%). Cork oak remained stable (1–4% growth). Other oaks showed minimal changes. Bushes (scrubland) declined sharply post-2007 (−31% BA/−6% NB). The most significant transformation occurred between 1995 and 2007, particularly in the south of Portugal, where wildfires promoted the replacement of maritime pine with eucalyptus, a species that offers greater profitability, leading to agricultural abandonment in burned areas. Full article

The exposure to elevated levels of ozone contributes to respiratory diseases and ecosystem degradation. Mediterranean countries are among those most affected by high ozone concentrations, which are generally overestimated by chemistry transport models underscoring the importance of improving the accuracy of air quality modelling. This study introduces an enhanced Mediterranean dry deposition description within the LOTOS-EUROS model framework, focusing on refining key vegetation parameters for the Mediterranean climate zone, with the goal to better estimate deposition and connected concentration values. Adjustments were made to the vegetation type dependent Jarvis functions for temperature and vapour pressure deficit, as well as to the maximum stomatal conductance across four land use types: arable land, crops, deciduous broadleaf forest, and coniferous evergreen forest. The model’s baseline run showed a widespread overestimation of ozone. Adjustments to the dry deposition routines reduced this overestimation, but the model simulation incorporating all changes still showed elevated ozone levels. Both runs displayed moderate spatial correlation with observations from 117 rural background monitoring stations, and most stations exhibited a temporal correlation between 0.5 and 0.8. An improved RMSE and bias were noted at the majority of the stations (114 out of 117) for the model simulation incorporating all changes. The monthly analysis indicated consistent overestimation at two Portuguese sites beginning in March. The model effectively tracked temporal changes overall. However, the diurnal analysis revealed site-specific differences: an overestimation at the station closest to highly populated areas at night, while rural stations aligned better with observed values. These results highlight the benefits of region-specific model adaptations and lay the groundwork for further advancements, such as incorporating detailed vegetation classifications and seasonal variations. Full article

The key objectives of both European Union and Portuguese policies are energy efficiency and carbon neutrality in the building sector. Timber construction offers unique advantages in achieving these goals, such as increased productivity through faster and more efficient building processes, using renewable resources with lower carbon emissions during production and throughout the lifecycle, and contributions to forest conservation. However, in many countries, timber construction remains underutilised due to concerns about its thermal and acoustic performance, fire safety, and limited availability of raw materials. This study addresses these challenges by evaluating the potential of various insulation materials, including polystyrenes, mineral wools, natural fibres, composites, and acoustic mats, for incorporation into prefabricated timber components. Key performance criteria included thermal insulation, sound absorption, fire reaction, environmental impact, and local availability. Among the materials analysed, glass wool, rock wool, and cork emerged as the most favourable options, offering excellent thermal and acoustic performance and presenting strong results in other key parameters. These findings underscore the potential of incorporating these materials into timber construction systems, contributing to developing sustainable and high-performance building solutions. Full article

Portugal’s increasing wildfire frequency has led to home destruction, large areas burned, ecological damage, and economic loss, emphasizing the need for effective fire exposure assessments. This study builds on a Canadian approach to wildfire exposure and evaluates wildfire exposure in the Portuguese municipality of Mafra, using artificial territories (AT) as a proxy for the wildland–urban interface (WUI) and integrates land use land cover (LULC) data with a neighborhood analysis to map exposure at the municipal scale. Fire exposure was assessed for three fire transmission distances: radiant heat (RH, <30 m), short-range spotting (SRS, <100 m), and longer-range spotting (LRS, 100–500 m) using fine resolution (5 m) LULC data. Results revealed that while AT generally exhibited lower exposure (<16% “very high” exposure), adjacent hazardous LULC subtypes significantly increase wildfire hazard, with up to 51% of LULC subtypes classified as “very high exposure”. Field validation confirmed the accuracy of exposure maps, supporting their use in wildfire risk reduction strategies. This cost-effective, scalable approach offers actionable insights for forest and land managers, civil protection agencies, and policymakers, aiding in fuel management prioritization, community preparedness, and the design of evacuation planning. The methodology is adaptable to other fire-prone regions, particularly mediterranean landscapes. Full article

The pine cone is an important forest product for the Portuguese economy. However, it is associated with environmental impacts, such as the generation of waste and the increased risk of forest fires. The objective of this research is to valorise waste from the production of Pinus pinaster Aiton in the form of natural dyes. The pine cone extracts were characterised in different alkaline solutions (1%, 5% and 10% NaOH) in order to evaluate the dyeing process on cotton knitwear, using the CIELab coordinates. The dyed samples were also subjected to light and water fastness tests. The extracts showed an increase in solids content with increasing alkalinity and a reduction in antioxidant content. The phenol content increased in the extract with 5% but decreased with the 10% concentration. All the dyes expressed a pink colour but with different shades. About the L* coordinate (luminosity), the colours became lighter as the NaOH increased. In the a* coordinate, all the samples had a reddish colour, and, in the b* coordinate, all the samples had a yellowish colour. About light and water fastness, all the samples lost colour, but in the water test, it was not noticeable. Full article

This study investigates the physical interactions and between forest fires and the atmosphere, which often lead to conditions favourable to instability and the formation of pyrocumulus (PyCu). Using the coupled atmosphere–fire spread modelling framework, WRF-SFIRE, the Portuguese October 2017 Quiaios wildfire, in association with tropical cyclone Ophelia, was simulated. Fire spread was imposed via burnt area data, and the fire’s influence on the vertical and surface atmosphere was analysed. Simulated local atmospheric conditions were influenced by warm and dry air advection near the surface, and moist air in mid to high levels, displaying an inverted “V” profile in thermodynamic diagrams. These conditions created a near-neutrally unstable atmospheric layer in the first 3000 m, associated with a low-level jet above 1000 m. Results showed that vertical wind shear tilted the plume, resulting in an intermittent, high-based, shallow pyroconvection, in a zero convective available potential energy environment (CAPE). Lifted parcels from the fire lost their buoyancy shortly after condensation, and the presence of PyCu was governed by the energy output from the fire and its updrafts. Clouds formed above the lifted condensation level (LCL) as moisture fluxes from the surface and released from combustion were lifted along the fire plume. Clouds were primarily composed of liquid water (1 g/kg) with smaller traces of ice, graupel, and snow (up to 0.15 g/kg). The representation of pyroconvective dynamics via coupled models is the cornerstone of understanding the phenomena and field applications as the computation capability increases and provides firefighters with real time extreme fire conditions or predicting ahead of time. Full article