A fine-scale survey of δ15N, δ13C, tissue-N in seaweeds was conducted using samples from 17 sampling points at two sites (Grandcamp-Maisy (GM), Courseulles/Mer (COU)) along the French coast of the English Channel in 2012 and 2013. Partial triadic analysis was performed on the parameter data sets and revealed the functioning of three areas: one estuary (EstA) and two rocky areas (GM∗, COU∗). In contrast to oceanic and anthropogenic reference points similar temporal dynamics characterized δ15N signatures and N contents at GM∗ and COU∗. Nutrient dynamics were similar: the N-concentrations in seawater originated from the River Seine and local coastal rivers while P-concentrations mainly from these local rivers. δ15N at GM∗ were linked to turbidity suggesting inputs of autochthonous organic matter from large-scale summer seaweed beachings made up of a mixture of Rhodophyta, Phaeophyta and Chlorophyta species. This study highlights the coupling between seaweed beachings and nitrogen sources of intertidal macroalgae.

Recent gas discoveries in the eastern Mediterranean Sea led to multiple operations with substantial economic interest, and with them there is a risk of oil spills and their potential environmental impacts. To examine the potential spatial distribution of this threat, we created seasonal maps of the probability of oil spill pollution reaching an area in the Israeli coastal and exclusive economic zones, given knowledge of its initial sources. We performed simulations of virtual oil spills using realistic atmospheric and oceanic conditions. The resulting maps show dominance of the alongshore northerly current, which causes the high probability areas to be stretched parallel to the coast, increasing contamination probability downstream of source points. The seasonal westerly wind forcing determines how wide the high probability areas are, and may also restrict these to a small coastal region near source points. Seasonal variability in probability distribution, oil state, and pollution time is also discussed.

In 2010, a massive bloom of the raphidophycean flagellate Chattonella occurred in the Ariake Sea and Tachibana Bay. Bloom dynamics and hydrographical conditions were examined by field survey. The development and decline of the bloom occurred three times in Tachibana Bay. First and third bloom developments synchronized with precipitation, and the second bloom developed in synchronization with a salinity decrease which occurred in relation to an increase of river discharge from the Chikugo River which takes several days to flow from the Ariake Sea. These results imply that the bloom was transported with the low salinity water from the Ariake Sea to Tachibana Bay. During blooms along the northern coast of Shimabara Peninsula, the predominant phytoplankton species changed from Chattonella to Skeletonema. Low salinity water intrusion induced an interregional difference of the Chattonella and Skeletonema bloom spatially-differentiated by the salinity in the Ariake Sea and Tachibana Bay.

Previous models on simulating gas releases in deepwater were not focused on the dissolved component and its impact on water quality. This paper presents a new model developed for simulating the transport/spread of dissolved methane from an underwater release and its impact on dissolved oxygen in ambient water. Methane dissolves into ambient water from gas phase, direct from hydrate phase, and from dissociating hydrates formed earlier. Dissolved methane affects the dissolved oxygen levels in ambient water due to microbial interaction and possible direct absorption of oxygen into methane bubbles. We use new model simulations of Deepspill field experiments to compare with instantaneous profiles which were unpublished until now. The comparisons are very good with a short time lag, but are within the acceptable discrepancy for models for emergency response and contingency planning. Scenario simulations show the effect on dissolved oxygen due to different methane release situations.

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.

There is growing evidence of extensive pollution of the environment by microplastic, with microfibres representing a large proportion of the microplastics seen in marine sediments. Since microfibres are ubiquitous in the environment, present in the laboratory air and water, evaluating microplastic pollution is difficult. Incidental contamination is highly likely unless strict control measures are employed. Here we describe methods developed to minimize the amount of incidental post-sampling contamination when quantifying marine microfibre pollution. We show that our protocol, adapted from the field of forensic fibre examination, reduces fibre abundance by 90% and enables the quick screening of fibre populations. These methods therefore allow an accurate estimate of microplastics polluting marine sediments. In a case study from a series of samples collected on a research vessel, we use these methods to highlight the prevalence of microfibres as marine microplastics.

This baseline study highlights the 210Po and 210Pb concentration in two species of the benthic macroalgae Sargassum from northern Gulf, also known as the ROPME Sea Area (RSA). Within the marine environment, 210Po is initially absorbed from water and concentrated by phytoplankton and macroalgae, and this concentrated 210Po can then readily be passed along to the higher trophic level of the marine food web. The 210Po concentration measured in Sargassum boveanum (22.5–25.6Bqkg−1) was higher than that in Sargassum oligocystum (20.2–22.5Bqkg−1), but is not statistically significant (p>0.064), where as the difference between 210Pb concentrations in Sargassum boveanum (15.3–16.8Bqkg−1) and Sargassum oligocystum (18.4–22.0Bqkg−1) was statistically significant (p>0.019). The measured concentration factor for 210Po in Sargassum in the northern Gulf varied between 0.55 and 1.2×104, values higher to the IAEA recommended value of 1×103. The 210Po enrichment is observed in both the species of Sargassum,210Po/210Pb ratio was >1 at all the stations for all the samples.

Due to the high surface reactivity and redox chemistry, iron (Fe) minerals have a strong control on contaminant speciation, mobility and degradation. This has been well established for sediment and solution systems, and this review evaluates the role of Fe minerals in contaminant cycling from a sediment pollution perspective. Sediment redox conditions govern the Fe mineralogy, and a detailed description is given for Fe mineral interactions with contaminants in both oxic and sub/anoxic sediment horizons. These interactions include contaminant immobilisation through adsorption and co-precipitation mechanisms and contaminant degradation and speciation changes caused by Fe redox chemistry. Based on these reductive and adsorptive capabilities, recent advances in Fe amendment technologies, particularly in the field of engineered zero-valent Fe nanoparticles, have shown promising results for the treatment of polluted soils and sediments. However, the variable chemical and physical dynamics of sediment systems remains a limitation to the global application of these technologies.

Heavy metal (Cu, Pb, Zn, Cr, Cd, As) concentrations, distribution and bioaccumulation were studied in marine organisms in Guangdong coastal regions. Heavy metal concentrations and distribution in organisms showed characteristics according to areas and species. Heavy metal concentrations in most organisms were higher in west than in east, tightly related to the local industry structure and the disequilibrium of metal discharge. Generally, high heavy metal concentrations were detected in molluscs and low concentrations were detected in fish. Bioaccumulation factor was used to assess the accumulation level of marine organisms to heavy metals, of which Cd, Cu and As were the most accumulated elements. Accumulation abilities to heavy metals varied among organism species, such as Distorsio reticulate accumulating Cu, Zn, Cd, As, Loligo beka Sasaki accumulating Pb, Cu, Cr, and Turritella bacillum Kiener accumulating Zn, Cd, As. By comparison, Johnius belengeri, Argyrosomus argentatus, Cynoglossus sinicus Wu had relatively low accumulation abilities.

Ocean acidification and pollution coexist to exert combined effects on the functions and services of marine ecosystems. Ocean acidification can increase the biotoxicity of heavy metals by altering their speciation and bioavailability. Marine pollutants, such as heavy metals and oils, could decrease the photosynthesis rate and increase the respiration rate of marine organisms as a result of biotoxicity and eutrophication, facilitating ocean acidification to varying degrees. Here we review the complex interactions between ocean acidification and pollution in the context of linkage of multiple stressors to marine ecosystems. The synthesized information shows that pollution-affected respiration acidifies coastal oceans more than the uptake of anthropogenic carbon dioxide. Coastal regions are more vulnerable to the negative impact of ocean acidification due to large influxes of pollutants from terrestrial ecosystems. Ocean acidification and pollution facilitate each other, and thus coastal environmental protection from pollution has a large potential for mitigating acidification risk.