Exploring the long-term and interannual variability of biogeochemical variables in coastal areas by means of a data assimilation approach

Dynamic Harmonic Regression (DHR) models are applied here to the investigation of the interannual changes in the trend and seasonality of biogeochemical variables monitored in coastal areas. A DHR model can be regarded as a time-series component model, where the phases and amplitudes of the seasonal component, as well as the trend, are parameters that vary with time, reflecting relevant changes in the evolution of the biogeochemical variables. The model parameters and their confidence bounds are estimated by data assimilation algorithms, i.e. the Kalman filter and the Fixed Interval smoother. The DHR model structure is here identified by a preliminary spectral analysis and a subsequent minimization of the Bayesian Information Criterion, thus avoiding subjective choices of the frequencies in the seasonal component. The methodology was applied to the investigation of the long-term and interannual variability of ammonia, nitrate, orthophosphate and chlorophyll-a monitored monthly in the lagoon of Venice (Italy) during the years 1986–2008. It was found that the long-term evolutions of the biogeochemical variables were characterized by non-linear patterns and by statistically significant changes in the trend. The seasonal cycles of all the variables were characterized by a marked interannual variability. In particular, the changes in the seasonality of chlorophyll and nitrate were significantly related to the changes in the seasonality of water temperature at the study site and of nutrient concentrations in river discharges, respectively. These results indicate that the methodology could be a sound alternative to more traditional approaches for investigating the impacts of changes in environmental and anthropogenic forcings on the evolution of biogeochemical variables in coastal areas.     

Radio frequency self-interference from a data processing centre at a radio telescope site

Apart from externally generated Radio Frequency Interference (RFI), the occurrence of self-interference is a major concern at any modern radio telescope site. Antenna servo motor controllers, data acquisition processors, and fast computing capabilities operate very close to extremely sensitive and wideband radio astronomical receivers. In this paper, we present a set of measurements of the RFI level generated by a cluster of computers that will be installed at the site of the Sardinia Radio Telescope (SRT). The measured levels are compared to Recommendation ITU-R RA.769-2, which gives the threshold levels for interference detrimental to radio astronomy observations. Our analysis shows that, with proper shielding of the noisiest devices, it will be possible to preserve the present excellent RFI conditions of the SRT site.     

Sediment chemical contamination of a shallow water area close to the industrial zone of Porto Marghera (Venice Lagoon, Italy)

The industrial zone of Porto Marghera is one the most important "contaminated sites of national interest" (SIN) in Italy, being identified as an area of high environmental risk. The site includes a wide shallow water area of the Venice Lagoon extending toward the city of Venice, which was investigated in order to acquire information on the pollutant level and distribution. Grain-size, heavy metal, nutrient, and organic micropollutant concentrations were determined in the surface sediment layers (0-5 and 5-10 cm depths) of 51 sites. A generally low contamination was found, except for Hg concentration, which increases the toxicological risk in most of the sites of the area, according to the results of a comparison with Sediment Quality Guidelines. A heavy pollution fingerprint (Cd, Cu, Hg, Pb, and Zn up to 15.2, 257, 11.9, 248, and 3010 mg/kg d.w., respectively) was instead found near the Tresse Island, which is ascribed to the spill of pollutants from the contaminated sediment disposed therein. Grain-size and heavy metal profiles down to a depth of 40 cm in eight selected sites, finally show a probable decrease of the pollution affecting the area in recent years.     

Constraining the degree of the dominant mode in QQ Vir

We present early results of the application of a method which uses multicolor photometry and spectroscopy for ? discrimination. This method has been successfully applied to the pulsating hot subdwarf Balloon?090100001. Here we apply the method to QQ?Vir (PG1325+101). This star was observed spectroscopically and photometrically in 2008. Details on spectroscopy can be found in Telting et al. (Astrophys. Space Sci. 2010, this volume), while photometry and preliminary results on ? discrimination are provided here. The main aim of this work was to compare the value of the ? parameter derived for the main mode in QQ?Vir to previously published values derived by using different methods.     

Climate, agriculture, and cycles of human occupation over the last 4000 yr in southern Zacatecas, Mexico

Scholars attribute the growth and decline of Classic period (AD 200-900) settlements in the semi-arid northern frontier zone of Mesoamerica to rainfall cycles that controlled the extent of arable land. However, there is little empirical evidence to support this claim. We present phytolith, organic carbon, and magnetic susceptibility analyses of a 4000-yr alluvial record of climate and human land use from the Malpaso Valley, the site of one such Classic frontier community. The earliest farming occupation is detected around 500 BC and appears related to a slight increase of aridity, similar to the level of the modern day valley. By AD 500, the valley's Classic period Mesoamerican settlements were founded under these same dry conditions, which continued into the Postclassic period. This indicates that the La Quemada occupation did not develop during a period of increased rainfall, but rather an arid phase. The most dramatic changes detected in the valley resulted from the erosion associated with Spanish Colonial grazing and deforestation that began in the 16th century. The landscape of the modern Malpaso Valley is thus primarily the product of a series of intense and rapid transformations that were concentrated within the last 400 yr.     

GIS-based environmental risk assessment in the Ribeira Valley,São Paulo,Brazil

The Ribeira Valley region (State of Sao Paulo, Brazil) hosts the largest Brazilian Atlantic forest reserve. The region was an important mineral district during the ‘60s, from where several tons of lead and other metals were exploited. Residual materials produced by the mining are diffused in the environment until today. The area also encompasses a regional arsenium anomaly associated with unexplored gold deposits. The population presently living in this region performs basic farming activities, from which most of their food is yielded. These features coupled together imply in a complex relationship between natural and anthropogenic factors that are likely to affect the life and health of the local communities. The aim of this paper is to apply digital data integration techniques for environmental risk assessment in the Ribeira Valley using environmental geochemistry. Geochemical, digital elevation and remote sensing data (Landsat Thematic Mapper) were merged and analyzed using a geographical information system. The assumed model considered environmental mobilization through erosion and anomalous As–Pb areas. Data were analyzed through Boolean and fuzzy logic techniques. Fuzzy logic proved superior in this case study as it allowed not only the detection but also the distinction between low, moderate and high environmental risk areas.     

Periodic orbits and non-integrability of Armbruster-Guckenheimer-Kim potential

In this paper we study the periodic orbits of the Hamiltonian system with the Armburster-Guckenheimer-Kim potential and its $\mathcal{C}^{1}$ non-integrability in the sense of Liouville-Arnold.     

Anthropic Exposure Indicator for River Basins Based on Landscape Characterization and Fuzzy Inference

Water Resources - The objective of this study is to develop an anthropic exposure indicator for river basins using quantitative and qualitative aspects of the landscape and morphometric analysis...     

Physics‐based probabilistic seismic hazard and loss assessment in large urban areas: A simplified application to Istanbul

A set of 3D physics‐based numerical simulations (PBS) of possible earthquakes scenarios in Istanbul along the North Anatolian Fault (Turkey) is considered in this article to provide a comprehensive example of application of PBS to probabilistic seismic hazard (PSHA) and loss assessment in a large urban area. To cope with the high‐frequency (HF) limitations of PBS, numerical results are first postprocessed by a recently introduced technique based on Artificial Neural Networks (ANN), providing broadband waveforms with a proper correlation of HF and low‐frequency (LF) portions of ground motion as well as a proper spatial correlation of peak values also at HF, that is a key feature for the seismic risk application at urban scale. Second, before application to PSHA, a statistical analysis of residuals is carried out to ensure that simulated results provide a set of realizations with a realistic within‐ and between‐event variability of ground motion. PBS results are then applied in a PSHA framework, adopting both the “generalized attenuation function” (GAF) approach, and a novel “footprint” (FP)‐based approach aiming at a convenient and direct application of PBS into PSHA. PSHA results from both approaches are then compared with those obtained from a more standard application of PSHA with empirical ground motion models. Finally, the probabilistic loss assessment of an extended simplified portfolio of buildings is investigated, comparing the results obtained adopting the different approaches: (i) GMPE, (ii) GAF, and (iii) FP. Only FP turned out to have the capability to account for the specific features of source and propagation path, while preserving the proper physically based spatial correlation characteristics, as required for a reliable loss estimate on a building portfolio spatially distributed over a large urban area.