Sensitivity of Portuguese forest fires to climatic, human, and landscape variables: subnational differences between fire drivers in extreme fire years and decadal averages

Within the changing fire regimes of Portugal, the relative importance of humans and climatic variability for regional fire statistics remains poorly understood. This work investigates the statistical relationship between temporal dynamics of fire events in Portugal and a set of socioeconomic, landscape, and climatic variables for the time periods of 1980–1990, 1991–2000, and extreme fires years. For 10 of 15 districts, it was possible to observe moderate shifts in the significance of fire drivers for the first two decadal periods. For others, pronounced changes of the significance of fire drivers were found across time. Results point toward a dynamic (perhaps highly non-linear) behavior of socioeconomic and landscape fire drivers, especially during the occurrence of extreme fire years of 2003 and 2005. At country level, population density alone explained 42% of the inter-annual and inter-district deviance in number of fires. At the same temporal and spatial scale, the explanatory power of temperature anomalies proved to explain 43% of area burnt. We highlight the necessity of including a broad set of socioeconomic and landscape fire drivers in order to account for potential significance shifts. In addition, although climate does trigger broad favorable fire conditions across Portugal mainland, socioeconomic and landscape factors proved to determine much of the complex fire patterns at a subnational scale.     

A biology-based dynamic approach for the reconciliation of acute and chronic toxicity tests: application to Daphnia magna

There is the need to integrate existing toxicity data in a coherent framework for extending their domain of applicability as well as their extrapolation potential. This integration would also reduce time and cost-consuming aspects of these tests and reduce animal usage. In this work, based on data extracted from literature, we have assessed the advantages that a dynamic biology-toxicant fate coupled model for Daphnia magna could provide when assessing toxicity data, in particular, the possibility to obtain from short-term (acute) toxicity test long-term (chronic) toxicity values taking into account the inherent variability of D. magna populations and the multiple sources of data. The results show that this approach overcomes some of the limitations of existing toxicity tests and that the prediction errors are considerably reduced when compared with the factor from 2 to 5 obtained using acute-to-chronic ratios.     

Enhanced retention of linuron, alachlor and metalaxyl in sandy soil columns intercalated with wood barriers

A study has been made of the effect a reactive barrier made of pine (softwood) or oak (hardwood) wood intercalated in a sandy soil column has on the retention of linuron, alachlor and metalaxyl (pesticides with contrasting physicochemical characteristics). The leaching of pesticides has been carried out under a saturated flow regime and breakthrough curves (BTCs) have been obtained at flow rates of 1 mL min⁻¹ (all pesticides) and 3 mL min⁻¹ (linuron). The cumulative curves in the unmodified soil indicate a leaching of pesticides >80% of the total amount of compound added. After barrier intercalation, linuron leaching decreases significantly and a modification of the leaching kinetics of alachlor and metalaxyl has been observed. The theoretical R factors increased ∼2.6-3.3, 1.2-1.6-fold, and 1.4-1.7-fold and the concentration of the maximum peak decreased ∼6-12-fold, 2-4-fold and 1.2-2-fold for linuron, alachlor and metalaxyl, respectively. When considering the three pesticides, significant correlations have been found between the theoretical retardation factor (R) and the pore volume corresponding to the maximum peaks of the BTCs (r = 0.77; p < 0.05) or the total volume leached (r = −0.78; p < 0.05). The results reveal the efficacy of reactive wood barriers to decrease the leaching of pesticides from point sources of pollution depends on the type of wood, the hydrophobicity of the pesticide and the adopted water flow rate. Pine was more effective than oak in decreasing the leaching of hydrophobic pesticide linuron or in decreasing the maximum peak concentration of the less hydrophobic pesticides in soils. Efficacy of these wood barriers was limited for the least hydrophobic pesticide metalaxyl.     

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis.     

Arsenic distribution in soils and plants of an arsenic impacted former mining area

A mining area affected by the abandoned exploitation of an arsenical tungsten deposit was studied in order to assess its arsenic pollution level and the feasibility of native plants for being used in phytoremediation approaches. Soil and plant samples were collected at different distances from the polluting sources and analysed for their As content and distribution. Critical soil total concentrations of As were found, with values in the range 70-5330 mg kg⁻¹ in the uppermost layer. The plant community develops As tolerance by exclusion strategies. Of the plant species growing in the most polluted site, the shrubs Salix atrocinerea Brot. and Genista scorpius (L.) DC. exhibit the lowest bioaccumulation factor (BF) values for their aerial parts, suggesting their suitability to be used with revegetation purposes. The species Scirpus holoschoenus L. highlights for its important potential to stabilise As at root level, accumulating As contents up to 3164 mg kg⁻¹.     

Accumulation,biotransformation, and biochemical responses after exposure to arsenite and arsenate in the estuarine polychaete <Emphasis Type="BoldItalic">Laeonereis acuta</Emphasis> (Nereididae)

Introduction  

This study aimed to analyze antioxidant responses and oxidative damage induced by two inorganic forms of arsenic (As; As^III and As^V) in an estuarine polychaete species, Laeonereis acuta (Nereididae). The capacity of arsenic biotransformation was also evaluated through the methylation process considering the activity of a key enzyme involved in the metabolization process.     

Larvicidal and pupicidal activities of eco-friendly phenolic lipid products from Anacardium occidentale nutshell against arbovirus vectors

Environmental Science and Pollution Research - Aedes aegypti and Culex quinquefasciatus are vectors of diseases that constitute public health problems. The discovery of products capable of...     

Simultaneous removal of metronidazole and Pb(II) from aqueous solution onto bifunctional activated carbons

Environmental Science and Pollution Research - In this work, it was analyzed the behavior of three commercial activated carbons with different textural and chemical properties to adsorb...     

Assessing spatial variability of SO2 field as detected by an air quality network using Self-Organizing Maps,cluster, and Principal Component Analysis

In Bilbao (Spain), an air quality network measures sulphur dioxide levels at 4 locations. The objective of this paper is to develop a practical methodology to identify redundant sensors and evaluate a network's capability to correctly follow and represent SO₂ fields in Bilbao, in the frame of a continuous network optimization process.The methodology is developed and tested at this particular location, but it is general enough to be useable at other places as well, since it is not tied neither to the particular geographical characteristics of the place nor to the phenomenology of the air quality over the area.To assess the spatial variability of SO₂ measured at 4 locations in the area, three different techniques have been used: Self-Organizing Maps (SOMs), cluster analysis (CA) and Principal Component Analysis (PCA). The results show that the three techniques yield the same results, but the information obtained via PCA can be helpful not only for that purpose but also to throw light on the major mechanisms involved. This might be used in future network optimization stages. The main advantage of cluster analysis and SOMs is that they provide readily interpretable results. All the calculations have been carried out using the freely available software R.