The native distribution of the blue crab Callinectes sapidus in the western Atlantic extends from Nova Scotia to Argentina. Introduced to Europe at the beginning of the 20th century, it is currently recorded almost ubiquitously in the Mediterranean and in the Black Sea. An overview of the occurrence, abundance, and ecological impact of the species in southern European waters is provided; additionally, we present a pragmatic assessment of its management scenarios, explicitly considering the dual nature of C. sapidus as both an invasive species and a fishery resource. We emphasise that the ongoing expansion of C. sapidus in the region may represent a stimulating challenge for the identification and implementation of future strategies in the management of invasive crustaceans. The impact of the invader could be converted into an enhancement of the services delivered by southern European coastal ecosystems, while mitigation costs could be transformed into profits for local populations.

Knowledge on baseline values of stress biomarkers in natural conditions is urgent due to the need of reference values for monitoring purposes. Here we assessed the cellular stress response of the chiton Chaetopleura angulata in situ. Biomarkers commonly used in environmental monitoring (heat shock protein 70kDa, total ubiquitin, catalase, glutathione-S-transferase, superoxide-dismutase, lipid peroxidation) were analyzed in the digestive system, gills and muscle of C. angulata, under spring and summer conditions in order to assess seasonal tissue-specific responses. Season had an effect on all targeted organs, especially affecting the digestive system which displayed clear seasonal clusters. The respective Integrated Biomarker Response (IBR) showed a 7.2-fold seasonal difference. Muscle and gills showed similar IBRs between seasons making them appropriate organs to monitor chemical pollution as they were less responsive to seasonal variation. The most stable biomarkers in these organs were ubiquitin and superoxide-dismutase thus being reliable for monitoring purposes.

Juvenile oceanic-stage sea turtles are particularly vulnerable to the increasing quantity of plastic coming into the oceans. In this study, we analysed the gastrointestinal tracts of 24 juvenile oceanic-stage loggerheads (Caretta caretta) collected off the North Atlantic subtropical gyre, in the Azores region, a key feeding ground for juvenile loggerheads. Twenty individuals were found to have ingested marine debris (83%), composed exclusively of plastic items (primarily polyethylene and polypropylene) identified by μ-Fourier Transform Infrared Spectroscopy. Large microplastics (1–5mm) represented 25% of the total number of debris and were found in 58% of the individuals sampled. Average number of items was 15.83±6.09 (±SE) per individual, corresponding to a mean dry mass of 1.07±0.41g. The results of this study demonstrate that plastic pollution acts as another stressor for this critical life stage of loggerhead turtles in the North Atlantic.

Trace metal concentrations in muscle and liver tissues from two offshore species of skate were examined. Concentrations of mercury in muscle of Leucoraja circularis (n = 20; 23–110.5 cm total length, 157–490 m water depth) and L. fullonica (n = 24; 28.5–100 cm total length, 130–426 m water depth) were 0.02–1.8 and 0.04–0.61 mg kg− 1, respectively. Concentrations of both As and Hg increased with total length. Only the largest specimen had a concentration of Hg in muscle > 1.0 mg kg− 1. Data were limited for specimens > 90 cm long, and further studies on contaminants in larger-bodied skates could usefully be undertaken.

This study was designed to identify in the pearl oyster Pinctada margaritifera, used as a bio-accumulator, molecular biomarkers for the presence of heavy metals in the lagoon environment. Pearl oysters were exposed to 2 concentrations (1 and 10 μg L− 1) of cadmium (Cd) and chromium (Cr) compared to a control. Twelve target genes encoding proteins potentially involved in the response to heavy metal contamination with antioxidant, detoxification or apoptosis activities were selected. P. margaritifera accumulated Cd but not Cr, and mortality was related to the amount of Cd accumulated in tissues. In response to Cd-Cr contamination, metallothionein (MT) was significantly up-regulated by Cd-Cr at both concentrations, while 7 others (SOD, CAT, GPX, GSTO, GSTM, CASP, MDR) were down-regulated. Based on the development of these molecular tools, we propose that the pearl oyster, P. margaritifera, could be used as a sentinel species for heavy metal contamination in the lagoons of tropical ecosystems.

The ultraviolet (UV)-based advanced oxidation process (AOP) is a powerful technology commonly utilised in recent potable water reuse (PR) schemes. The AOP involves the generation of highly reactive free radicals (e.g. hydroxyl, HO•) and is primarily applied for the removal of two target trace organic chemicals—N-nitrosodimethylamine (NDMA) and 1,4-dioxane — in the PR schemes. Both of these organics are not well removed by the reverse osmosis (RO) process. NDMA is a probable carcinogen and is often present in reclaimed water at concentrations higher than the guidelines established for PR. This review aimed to provide an understanding of the current UV-based advanced oxidation technologies for NDMA removal in PR, their limitations and the future of advanced technologies for their removal. NDMA is readily photolysed by direct UV irradiation, while an AOP such as UV/H₂O₂ process is necessary for the destruction of 1,4-dioxane. Unfortunately, the generation of hydroxyl radicals through UV photolysis of H₂O₂ is largely inefficient with conversion on the order of 20% under normal plant operations and the addition of H₂O₂ (e.g. 3 mg/L) provides only a negligible improvement in NDMA destruction. However, AOP can also be achieved without continuous chemical addition through the application of UV irradiation to heterogeneous photocatalysts (e.g. TiO₂). The UV/TiO₂ process generates hydroxyl radicals and singlet oxygen molecules, both of which degrade NDMA into by-products (e.g. methylamine or dimethylamine). Recent studies revealed that modification of the surface morphology of TiO₂ can not only enhance NDMA destruction but also alter the composition of the degradation by-products.

The characterization of inorganic elements in the produced water (PW) samples is a difficult task because of the complexity of the matrix. This work deals with a study of a methodology for dissolved Fe quantification in PW from oil industry by flame atomic absorption spectrometry (FAAS) after cloud point extraction (CPE). The procedure is based on the CPE using PAN as complexing agent and Triton X-114 as surfactant. The best conditions for Fe extraction parameters were studied using a Box-Behnken design. The proposed method presented a LOQ of 0.010μgmL−1 and LOD of 0.003μgmL−1. The precision of the method was evaluated in terms of repeatability, obtaining a coefficient of variation of 2.54%. The accuracy of the method was assessed by recovery experiments of Fe spiked that presented recovery of 103.28%. The method was applied with satisfactory performance to determine Fe by FAAS in PW samples.

We investigated the effect of combined exposure to nodavirus infection and TBT on medaka (Oryzias latipes). Medaka larvae were infected by immersion in medium containing nodavirus at titers of 102.5, 103.5, or 104.5 TCID50/mL. Infected fish then were exposed to TBT at 0, 0.17, 0.52, 1.6, or 4.7μg/L. Of the 12 groups exposed to both stressors, the mortalities of 6 (102.5 TCID50/mL+0.52, 1.6, or 4.7μg/L, 103.5 TCID50/mL+4.7μg/L and 104.5 TCID50/mL+1.6 or 4.7μg/L) were significantly higher than that of each TBT control. Specifically, mortality was 46±5.5% in the group exposed to both 102.5 TCID50/mL virus and 0.52μg/L TBT, which represent the lowest observed effective dose and concentration, respectively, among the 6 groups with increased mortalities. Our results suggest that combined exposure to both stressors suppresses antiviral mechanisms in the fish, thus increasing mortality.

The coastal seagrass meadows in the Townsville region of the Great Barrier Reef are crucial seagrass foraging habitat for endangered dugong populations. Deteriorating coastal water quality and in situ light levels reduce the extent of these meadows, particularly in years with significant terrestrial runoff from the nearby Burdekin River catchment. However, uncertainty surrounds the impact of variable seagrass abundance on dugong carrying capacity. Here, I demonstrate that a power-law relationship with exponent value of −1 (R2~0.87) links mortality data with predicted changes in annual above ground seagrass biomass. This relationship indicates that the dugong carrying capacity of the region is tightly coupled to the biomass of seagrass available for metabolism. Thus, mortality rates increase precipitously following large flood events with a response lag of <12-months. The management implications of this result are discussed in terms of climate scenarios that indicate an increased future likelihood of extreme flood events.

Air-quality forecasting is difficult because air quality time series are heterogeneous, consisting of one-dimension series data and multi-dimension panel data. Therefore, a hybrid forecasting model with both linear and nonlinear models may be appropriate to represent the complex behavior of a heterogeneous time series data set. In this paper, a new hybrid-Garch (Generalized Autoregressive Conditional Heteroskedasticity) methodology is proposed in order to integrate the individual forecasting models of the ARIMA (Autoregressive Integrated Moving Average) and SVM(Support Vector Machine). The hybrid-Garch approach for time series prediction is tested by 10-day hourly PM2.5 concentrations data including linear and non-linear, in Shenzhen, China. Empirical results from six station data sets indicate that: 1) the PM2.5 concentrations of Shenzhen experiences a regular fluctuation during the 24 h of the whole day with the peak value in working hours due to factory and vehicle emissions. 2) Spatial difference of PM2.5 concentrations is not noticeable because of the geographical and meteorological conditions. 3) The proposed hybrid model generates a more reliable and accurate forecast capability. 4) The proposed hybrid model analyses the time series data with possibly conditional heteroscedasticity characteristics and estimates the variance for the volatility of the PM2.5 concentrations.