Intraurban variability of PM10 and PM2.5 in an Eastern Mediterranean city

The results of the first large scale chemical characterization of PM10 and PM2.5 at three different sites in the urban city of Beirut, Lebanon, are presented. Between May 2009 and April 2010 a total of 304 PM10 and PM2.5 samples were collected by sampling every sixth day at three different sites in Beirut. Observed mass concentrations varied between 19.7 and 521.2 μg m^? 3 for PM10 and between 8.4 and 72.2 μg m^? 3 for PM2.5, respectively. Inorganic concentrations accounted for 29.7–35.6 μg m^? 3 and 46.0–53.5 μg m^? 3 of the total mass of PM10 and PM2.5, respectively. Intra-city temporal and spatial variations were assessed based on the study of three factors: correlation coefficients (R) for PM and chemical components, coefficient of divergence (CODs), and source apportionment using positive matrix factorization (PMF). Based on R and COD of PM concentrations, the three sites appear homogeneous. However, when individual elements were compared, heterogeneity among sites was found. This latter was attributed to the variability in the percent contribution of biogenic and local anthropogenic source factors such as traffic related sources and dust resuspension. Other factors included the proximity to the Mediterranean sea, the population density and the topographical structure of the city. Hence, despite its small size (20.8 km²), one PM monitoring site does not reflect an accurate PM level in Beirut.     

Advanced Mathematical Models to Predict the Compaction Properties of Coarse-Grained Soils from Various Physical Properties

An essential task in the process of construction is the determination of compaction properties of soils. Many years of laboratory test experience strengthen our belief in the existence of predictive equations that govern the compaction characteristics of soils. An advanced mathematical model developed in this research in order to uncertain the governing equations. An advanced mathematical model developed in this research in order to uncertain the governing equations. Through a comparative study among a Multiple Linear Regression (MLR) model, an Artificial Neural Network (ANN) model, Extreme Learning Machine (ELM) and a Support Vector Machine (SVM) model, the best predicting model was determined. For this purpose, Six hundred and six (606) samples collected and split into a dataset used for training the models and another used for validation of the derived model. 8 neural networks with a varying number of hidden layers and a varying number of nodes in hidden layers were employed. In ELM 1 hidden layer with varying number of units were employed. It was found that the equations derived from the ELM models described the relationship with superiority over multiple regression, ANN and SVM models for Maximum Dry Density and MLR models described the relationship with superiority over ANN, ELM and SVM models for Optimum Moisture Content.     

Use of sediment quality indicators for heavy metals contamination and ecological risk assessment in urbanized coastal zones

The urbanized coastal zones are frequently faced to various pollutant discharges mainly in the shoreline. The quantification of the pollution level was mainly based on sea-water analysis. However, in this environment, the sediment characterization, using quality indicators, may constitute an accurate approach. The latter can be particularly appropriate to define heavy metals pollution degree. Chemical analyses of Cd, Cu, Zn, and Fe were undertaken for a total of 45 surface marine sediment samples of Gabes city coast. There is a significant extension of pollution, strongly influenced by the dominant longshore current. The studied sediments were found usually enriched with Cu, Cd, and Zn. These anthropogenic heavy metals have identical behavior and similar distribution. These metals did not show any correlations with Fe chosen as natural tracer. The multi-element indices used permitted to conclude that 70% of sampling sites are highly affected by heavy metal contamination and associated with very high ecological risk. These indices use a simple contamination factor, which, however, would not take account of the sedimentary inputs and the complex sediment behavior. Consequently, modified indices, employing enrichment factor, were used and demonstrated better to assess pollution and ecological risk.     

An optimized object-based analysis for vegetation mapping using integration of Quickbird and Sentinel-1 data

This study proposed a workflow for an optimized object-based analysis for vegetation mapping using integration of Quickbird and Sentinel-1 data. The method is validated on a set of data captured over a part of Selangor located in the Peninsular Malaysia. The method comprised four components including image segmentation, Taguchi optimization, attribute selection using random forest, and rule-based feature extraction. Results indicated the robustness of the proposed approach as the area under curve of forest; grassland, old oil palm, rubber, urban tree, and young oil palm were calculated as 0.90, 0.89, 0.87, 0.87, 0.80, and 0.77, respectively. In addition, results showed that SAR data is very useful for extracting rubber and young oil palm trees (given by random forest importance values). Finally, further research is suggested to improve segmentation results and extract more features from the scene.     

Northern landscapes in transition: Evidence,approach and ways forward using the Krycklan Catchment Study

Improving our ability to detect changes in terrestrial and aquatic systems is a grand challenge in the environmental sciences. In a world experiencing increasingly rapid rates of climate change and ecosystem transformation, our ability to understand and predict how, when, where, and why changes occur is essential for adapting and mitigating human behaviours. In this context, long-term field research infrastructures have a fundamentally important role to play. For northern boreal landscapes, the Krycklan Catchment Study (KCS) has supported monitoring and research aimed at revealing these changes since it was initiated in 1980. Early studies focused on forest regeneration and microclimatic conditions, nutrient balances and forest hydrology, which included monitoring climate variables, water balance components, and stream water chemistry. The research infrastructure has expanded over the years to encompass a 6790 ha catchment, which currently includes 11 gauged streams, ca. 1000 soil lysimeters, 150 groundwater wells, >500 permanent forest inventory plots, and a 150 m tall tower (a combined ecosystem-atmosphere station of the ICOS, Integrated Carbon Observation System) for measurements of atmospheric gas concentrations and biosphere-atmosphere exchanges of carbon, water, and energy. In addition, the KCS has also been the focus of numerous high resolution multi-spectral LiDAR measurements and large scale experiments. This large collection of equipment and data generation supports a range of disciplinary studies, but more importantly fosters multi-, trans-, and interdisciplinary research opportunities. The KCS attracts a broad collection of scientists, including biogeochemists, ecologists, foresters, geologists, hydrologists, limnologists, soil scientists, and social scientists, all of whom bring their knowledge and experience to the site. The combination of long-term monitoring, shorter-term research projects, and large-scale experiments, including manipulations of climate and various forest management practices, has contributed much to our understanding of boreal landscape functioning, while also supporting the development of models and guidelines for research, policy, and management.     

Palynostratigraphy and palaeoenvironmental significance of the Cretaceous palynomorphs in the Qattara Rim-1X well,North Western Desert,Egypt

Palynological and palynofacies analyses were carried out on some Cretaceous samples from the Qattara Rim-1X borehole, north Western Desert, Egypt. The recorded palynoflora enabled the recognition of two informal miospore biozones arranged from oldest to youngest as Elaterosporites klaszii-Afropollis jardinus Assemblage Zone (mid Albian) and Elaterocolpites castelainii–Afropollis kahramanensis Assemblage Zone (late Albian–mid Cenomanian). A poorly fossiliferous but however, datable interval (late Cenomanian–Turonian to ?Campanian–Maastrichtian) representing the uppermost part of the studied section was also recorded. The palynofacies and visual thermal maturation analyses indicate a mature terrestrially derived organic matter (kerogen III) dominates the sediments of the Kharita and Bahariya formations and thus these two formations comprise potential mature gas source rocks. The sediments of the Abu Roash Formation are mostly dominated by mature amorphous organic matter (kerogen II) and the formation is regarded as a potential mature oil source rock in the well. The palynomorphs and palynofacies analyses suggest deposition of the clastics of the Kharita and Bahariya formations (middle Albian and upper Albian–middle Cenomanian) in a marginal marine setting under dysoxic–anoxic conditions. By contrast, the mixed clastic-carbonate sediments of the Abu Roash Formation (upper Cenomanian–Turonian) and the carbonates of the Khoman Formation (?Campanian–Maastrichtian) were mainly deposited in an inner shallow marine setting under prevailing suboxic–anoxic conditions as a result of the late Cenomanian and the Campanian marine transgressions. This environmental change from marginal to open (inner shelf) basins reflects the vertical change in the type of the organic matter and its corresponding hydrocarbon-prone types. A regional warm and semi-arid climate but with a local humid condition developed near/at the site of the well is thought to have prevailed.     

Hydrocarbon source potential of the Jurassic sediments of Salam-3X borehole,Khalda Concession,Northern Western Desert,Egypt

A total of 51 samples, collected from the Jurassic sediments (Ras Qattara, Yakout, Khatatba, Masajid, and Alam El Bueib (member 6) formations) of Salam-3X well, were subjected to organic geochemical analysis. Of the samples, nine have been subjected to palynofacies investigation. Based on the sedimentary organic matter, these sediments show only one palynofacies type, indicating the presence of gas- and oil-prone source rocks and reflecting deposition under marginal dysoxic–anoxic to shelf-to-basin transition conditions. The total organic content of the samples analyzed is characterized by a wide range of content, including fair, good, very good, and excellent. The organic matter quality of these samples is concentrated around types III (gas prone), III–II (gas and oil prone), and II (oil prone), reflecting gas- and oil-prone sediments, with a tendency to generate gas rather than oil; the result matches with the palynological analysis data. The temperature of maximum pyrolytic hydrocarbon generation of analyzed samples are ranging between 440 and 457 °C, reflecting thermally mature organic matter.