We present a simple neural network and data pre–selection framework, discriminating the most essential input data for accurately forecasting the concentrations of PM10, based on observations for the years between 2002 and 2006 in the metropolitan region of Lisbon, Portugal. Starting from a broad panoply of different data sets collected at several air quality and meteorological stations, a forward stepwise regression procedure is applied enabling to automatically identify the most important variables for predicting the pollutant and also to rank them in order of importance. The importance of this variable ranking is discussed, showing that it is very sensitive to the urban location where measurements are obtained. Additionally, the importance of Circulation Weather Types is highlighted, characterizing synoptic scale circulation patterns and the concentration of pollutants. We then quantify the performance of linear and non–linear neural network models when applied to PM10 concentrations. In the light of contradictory results of previous studies, our results show no clear superiority for the case studied of non–linear models over linear models. While all models show similar predictive performances, we find important differences in false alarm rates and demonstrate the importance of removing weekly cycles from input variables.

Liaohe River has received significant attention in the northeast region and even in the entire country. As part of a recently completed water quality assessment, a series of water column and sediment toxicity tests was performed throughout the watershed. In the current study, we subjected sediments from the Liaohe River to toxicity identification evaluation manipulations and tests for chronic toxicity with midge (Chironomus riparius), with survival as the end point. In Phase I, the sediments were treated with zeolite, cation-exchange resin, and powdered coconut charcoal. Results confirmed that ammonia compounds were the major contaminants in terms of toxicity, although toxic effects from metals were also a concern in at least three sites. In Phase II identification, chemical analysis provided a strong evidence that the metals As and Cd are the probable causes of toxicity in the sediments, without the influence of ammonia. Temporally, ammonia is responsible for the toxicity of the selected sediments.

This study establishes regional background levels and upper thresholds (geochemical baseline) for Zn, Cu, Pb, Cr, Mn, and Fe from surface samples and profiles taken in 16 sedimentary environments of the Parnaíba River Delta estuary, NE–Brazil. Three approaches were applied to evaluate metal contamination: normalization to Fe, statistical analysis and sediment quality guidelines or environmental assessment criteria (TEL–PEL). Metal concentrations in sediments ranged from 2.4 to 31mgZnkg−1, 1.5 to 48mgCukg−1, 1.3 to 28mgPbkg−1, 1.5 to 38mgCrkg−1; 145 to 1,356mgMnkg−1, and 0.3% to 2.5% for Fe. All metals showed positive correlations with the <0.63μm sediment fraction, indicating a significant association with rich lithogenic sources of iron oxide–hydroxides. Results suggest a low probability of adverse effects to the local aquatic biota. The background values of the area were lower than those reported for other areas of the northeastern coast of Brazil.

This work investigates the dependence of the sampling rate (Rs) of semi-permeable membrane devices (SPMDs) on flow rate and temperature. The in situ Rs values were obtained using performance reference compounds (PRCs) with weighted polynomial regression and used to estimate the bioavailable polycyclic aromatic hydrocarbon (PAH) concentrations in seawater. The in situ Rs values did not vary with flow rate and temperature. The empirical equation of the Rs value from the SPMDs was established. This infers that PRCs could be avoided by using an established empirical equation under similar field conditions. The sum of the bioavailable PAHs ranged from 0.281 to 0.611ngL−1 on the eastern side of the Taiwan Strait and from 0.438 to 1.10ngL−1 on the western side. Distinct sources and toxicity of these bioavailable PAHs were observed and mainly resulted from different types of energy consumption.

Air quality management in urban areas requires the use of advanced modeling tools, able to predict and evaluate the pollution level under different traffic and meteorological conditions. In the present paper, the Artificial Compressibility version of the Characteristic Based Split algorithm (AC–CBS) was used to assess the performance of the Spalart–Allmaras based Detached Eddy Simulation (SA–DES) model, for the calculation of incompressible turbulent flow in different urban street canyon configurations. To our knowledge, the DES version of the SA turbulence model was applied in this work for the first time for the simulation of turbulent flow in a street canyon. The proposed DES model was able to accurately reproduce the turbulent characteristics of the flow compared with results from real street canyon experiments, wind tunnel experiments, and also to that obtained with RANS simulations. These results are very similar to the ones obtained from Large Eddy Simulation (LES) of street canyons flow reported in some recent publications, but with the potential characteristic of reduced computational costs. The DES approach is very promising for the simulation of transient turbulent flows in urban areas when complex three–dimensional domains are considered. The performance of the DES model evaluated for the mean dimensionless streamwise velocity profiles was comparable to that of Reynolds–Averaged Navier–Stokes RANS approach if referred to Hit Rate (HR) validation metric, and even better if referred to Factor of two observation (FAC2) validation metric. An accurate reproduction of the turbulent flow is crucial for urban pollutant dispersion simulations, since the distribution of the pollutant concentrations could differ by order of magnitude in the different points of the street canyon. DES approach results were able to accurately predict the unsteadiness characteristic of the flow, and to reproduce some minor vortex structures, which were not observed in the RANS cases, that will lead to a more accurate reproduction of the pollutant concentrations.

We consider hourly PM10 measurements from 22 monitoring stations located in Basse–Normandie and Haute–Normandie regions (France) and also in the neighboring regions. All considered monitoring stations are either urban background stations or rural ones. The paper focuses on the statistical detection of outliers of the hourly PM10 concentrations from a spatial point of view. The general strategy uses a jackknife type approach and is based on the comparison of the actual measurement with some robust spatial prediction. Two spatial predictions are considered: the first one is based on the median of the concentrations of the closest neighboring stations which directly consider weighted concentrations while the second one is based on kriging increments, instead of more traditional pseudo–innovations. The two methods are applied to the PM10 monitoring network in Normandy and are fully implemented by Air Normand (the official association for air quality monitoring in Haute–Normandie) in the Measurements Quality Control process. Some numerical results are provided on recent data from January 1, 2013 to May 31, 2013 to illustrate and compare the two methods.

Development of human activities in the Klaipėda strait generates a wide spectrum of underwater noise. In the fall of 2013, at the liquid natural gas terminal construction site in the shallow Curonian Lagoon area, an assessment of possible negative impacts on migrating salmon fish caused by pile driving noise was made. It is well known that impact hammer pile driving generates pulses with extremely high underwater noise levels. The obtained results proved that the pile hammering into the lagoon bottom generated pulses with a sound exposure level of 218dB re 1μPa2s @1m thus posing a risk to the migrating fish.

Marine clams Ruditapes philippinarum were exposed under laboratory conditions to sediments sampled at five sites affected by wastewater effluents at the Bay of Cádiz (SW, Spain). Contamination and early biological stress were determined. Metabolism and antioxidant system differed according to seasons. Health status diminished in summer. Metabolism of detoxification, and oxidative effect were related to concentration of metals, PAH, secondary alkane sulfonates (SAS) and antibiotics in winter. Antioxidant system and DNA damage were linked to metals and pharmaceutical products. Phase I and antioxidant system were associated to PAH and SAS in summer. Oxidative stress and effects were related to pharmaceuticals. Phase II was linked to metals and pharmaceuticals. Seasonality of sediment contamination by organic compounds and biological responses was determined. Clams were useful bioindicators, since the set of biomarkers applied was validated as potential tools for sediment quality assessment of wastewater discharges areas.

Sediments collected from the coastal area of China, embracing west coast of Bohai Sea, south coast of Shandong Peninsula, and the Changjiang estuary (listed in order of decreasing north latitude), were analyzed for polycyclic aromatic hydrocarbons (PAHs). ∑PAH (Sixteen US EPA priority PAHs) were 2.7–350.9ng/g. Petroleum residue was the major contributor of PAHs in the coastal sediments of China due to oil leakage from ships and offshore oil fields. The contribution of vehicular emissions in coast of North China was significantly lower than that in the Changjiang Estuary, and the reverse was true for coal combustion. PAH concentrations in the sediment core of the Changjiang estuary steadily increased upward and the variation was primarily due to economic development and severe floods. The impact on PAHs by vehicular emissions (37.2%) and petrogenic sources (45.8%) overwhelmed combustion sources (17.0%).

There is at present a growing concern, on an international level, over environmental offences caused by oil discharges into the sea from vessels. The objective of the Spanish Maritime Administration is to prevent the illegal discharges of polluting substances in Spanish maritime waters by vessels in transit. To combat such discharges, since 2007 Spain has reinforced its means of response with the use of aircrafts that provide services of maritime surveillance, identifying the Alleged Offending Vessels and acting as a deterrent.The objective of the present study is both to introduce the concept and to analyze certain aspects of the so-called “Alleged Offending Vessel” (AOV) that have been detected within Spanish Search and Rescue (SAR) jurisdiction waters in the period 2008–2012, in order to build a profile of such a vessel. For this purpose, an analysis methodology is formalized based on the GINI index and Lorenz curves, associated with certain aspects of vessels: type, flag and sailing area.