Phase 1 of the TIE method was applied to samples of elutriates from sediments of the Itajaí-Açu estuary and adjacent coastal region in southern Brazil. Embryo-larval toxicity assays were used with the sea urchin Arbacia lixula in samples of raw elutriate, and treated with Ulva fasciata, EDTA and sodium thiosulfate. Inside the estuary, ammonia was responsible for more than 40% of the toxicity in both the dredged and undredged regions. A toxicity gradient was observed, between the estuary and the coastal region, with an increase in the importance of metals for the latter. Temporally, there is strong evidence of the influence of dredging and disposal of sediments in the contamination of the coastal dumping site. The results indicating that this area presents limitations in its saturation capacity. Chemical analysis indicated the metal Cu is probably responsible for the toxicity of the sediments observed, without the interference of ammonia.

Within the European Water Framework Directive, many studies have been conducted to evaluate the sensitivity/robustness of a variety of indices in relation to natural or anthropogenic disturbance events. However, these indices have rarely been applied to verify the impacts of disturbances in offshore environments, though the Marine Strategy Framework Directive recommends their use for assessing benthic community conditions and functionality. The aim of this paper was to determine which biotic indicator performed the best for detecting the impacts of offshore structures on benthic populations in the Adriatic Sea. The impacts of four rigs were investigated six months after their installation, and the H′, AMBI, m-AMBI, BENTIX, and BOPA indices were assessed. Although these five indices delivered some contradictory results because of the differences in their structure and discrepancies in their assignment of species sensitivity, the BENTIX, H′ and BOPA indices appear to evaluate stress levels better than the AMBI and m-AMBI indices, which tend to provide results that are slightly overly optimistic.

To assess the effect of cage fish-farming on the coral reef ecosystem off Xiaoliuchiu Island, southern Taiwan, geographical differences in the food chain of each of two damselfishes, Pomacentrus vaiuli and Chromis margaritifer, were examined using a stable-isotope approach. For each damselfish, individuals were found to consume similar foods at all sites. However, specimens collected at sites near the cage farm (as the experimental sites) exhibited lower δ13C and higher δ15N signatures compared to those from reference sites. Similar trends also occurred in the zooplankton and detritus, two major food sources for both damselfishes. This finding indicates that particulate organic matter released by the farm may have entered the coral reef ecosystem through the pelagic food chain. Artificial reef emplacement is recommended to provide extra habitats under cage farms to support additional pelagic-feeding fish populations, thereby reducing environmental impacts of cage farming on coral reefs.

Increased frequency and enhanced damage to the marine environment and to human society caused by green macroalgae blooms demand improved high-resolution early detection methods. Conventional satellite remote sensing methods via spectra radiometers do not work in cloud-covered areas, and therefore cannot meet these demands for operational applications. We present a methodology for green macroalgae bloom detection based on RADARSAT-2 synthetic aperture radar (SAR) images. Green macroalgae patches exhibit different polarimetric characteristics compared to the open ocean surface, in both the amplitude and phase domains of SAR-measured complex radar backscatter returns. In this study, new index factors are defined which have opposite signs in green macroalgae-covered areas, compared to the open water surface. These index factors enable unsupervised detection from SAR images, providing a high-resolution new tool for detection of green macroalgae blooms, which can potentially contribute to a better understanding of the mechanisms related to outbreaks of green macroalgae blooms in coastal areas throughout the world ocean.

For heavy metals, quality standards indicating good environmental status are designed to evaluate concentrations in the whole fish body, whereas monitoring of metals is often conducted using muscle or liver tissue. As most metals accumulate at different rates in different parts of fish, data should be adjusted to reflect whole fish body concentrations; however, this requires knowledge on distribution of metal concentrations within fish. Here, concentrations of cadmium, mercury, and lead were analyzed in the liver, muscle and whole fish of herring and perch to create conversion factors for transformation of heavy metal concentrations between these tissues. Species-specific accumulation of metals between muscle, liver, and whole fish were observed. Relationships between different tissues were used to recalculate data from monitoring programs in the Baltic Sea region. Based on whole fish concentrations, environmental status for cadmium and mercury in herring improved compared to assessments based on muscle or liver concentrations alone.

The Marano and Grado Lagoon is one of the best conserved transitional environment in the whole Mediterranean area. On the other hand, it suffers from industrial, agricultural and fisheries activities, which could have an important impact on its environmental quality. With the application of the WFD, the sediment chemical status was investigated. In this work, 16 polycyclic aromatic hydrocarbons included by the US EPA within the priority pollutants were considered. PAHs values ranged from non-detectable to 1056ngg−1 showing the highest contamination close to the Aussa-Corno River mouth, which received the industrial inputs. The contamination level was comparable to that observed in low contaminated sites of the Mediterranean region, and lower than the adjacent Gulf of Trieste. The ratios of selected PAHs congeners pointed out the prevalence of pyrolitic sources. Moreover, the application of the ERL/ERM displayed an environment, which should not have a potential biological impact.

We evaluated the biodegradability of physically (WAF) and chemically (CEWAF) dispersed oil in brackish water (salinity ∼6.5g/L), and the influence of nutrient availability (low nutrient-LN: background water vs. high nutrient-HN: addition of 100mgNO3-N/L and 10mg PO4-P/L to background water) on oil biodegradation rates at 15±0.5°C for 42days. No oil removal occurred in WAF compared with CEWAF: 24% in HN and 14% in LN within two weeks. The oil biodegradation concerned mainly alkanes as confirmed by GC/MS analyses. Higher O2 consumption (10.30mgL−1day−1) and CO2 production (3.89mg CL−1day−1) were measured in HN compared with LN (O2: 2.79mgL−1day−1, CO2:0.18mg CL−1day−1). Estimated biomass of hydrocarbon degraders and heterotrophic bacteria was at least an order of magnitude larger in HN than in LN. Combining dispersants with nutrients could enhance oil biodegradation and help improve oil spill mitigation responses.

Ocean-color remote sensing has been used as a tool to detect phytoplankton size classes (PSCs). In this study, a three-component model of PSC was reparameterized using seven years of pigment measurements acquired in the South China Sea (SCS). The model was then used to infer PSC in a cyclonic eddy which was observed west of Luzon Island from SeaWiFS chlorophyll-a (chla) and sea-surface height anomaly (SSHA) products. Enhanced productivity and a shift in the PSC were observed, which were likely due to upwelling of nutrient-rich water into the euphotic zone. The supply of nutrients promoted the growth of larger cells (micro- and nanoplankton), and the PSC shifted to greater sizes. However, the picoplankton were still important and contributed ∼48% to total chla concentration. In addition, PSC time series revealed a lag period of about three weeks between maximum eddy intensity and maximum chlorophyll, which may have been related to phytoplankton growth rate and duration of eddy intensity.

Source apportionment study of aerosols over Bay of Bengal (BOB) were investigated during Integrated Campaign on Aerosol Radiation Budget (ICARB) in the pre–monsoon (March–April 2006) and winter (December–January 2008–09) seasons. Positive matrix factorization (PMF) was applied to identify sources of ambient particulate matter using daily chemical composition data collected in the pre–monsoon (total suspended particles, TSP) and winter season (particles with a diameter < 10μm, PM10). Sea salt (SS), secondary aerosol (SA), Si–dust, fossil fuel combustion (FFC), biomass burning (BB) sources have been identified in both seasons, however their relative contributions were different. The combined contribution of Si–dust, secondary aerosol and fossil fuel combustion, constitute ~67% of particulate matter in pre–monsoon, whereas, secondary aerosols and biomass burning were the major contributors (63.2%) to particulate matter in winter. The identified sources effectively predict the measured particulate concentration in the pre–monsoon (r2=0.74) and winter season (r2=0.82). Another receptor model, principal component analysis (PCA) was done to increase the plausibility of the results obtained by PMF. PCA resulted in the identification of the sources that were comparable to the PMF outputs. PCA of TSP in the pre–monsoon season resulted in the extraction of three components (crustal dust + secondary aerosol, biomass burning, fossil fuel combustion + industrial emissions) that explained the 83% of the variance in the data. Similarly, in winter season, PCA resulted in the extraction of four components (biomass burning + secondary aerosol, industrial emission, crustal dust, sea salt) that explained the 86% of the variance of the data.