The concentration of carcinogenic poly aromatic hydrocarbons (c-PAHs) present in water and sediment of Klang Strait as well as in the edible tissue of blood cockle (Anadara granosa) was investigated.The human health risk of c-PAHs was assessed in accordance with the standards of the United States Environmental Protection Agency (US EPA). The cancer risks of c-PAHs to human are expected to occur through the consumption of blood cockles or via gastrointestinal exposure to polluted sediments and water in Kalng Strait. The non-carcinogenic risks that are associated with multiple pathways based on ingestion rate and contact rates with water were higher than the US EPA safe level at almost all stations, but the non-carcinogenic risks for eating blood cockle was below the level of US EPA concern. A high correlation between concentrations of c-PAHs in different matrices showed that the bioaccumulation of c-PAHs by blood cockles could be regarded as a potential health hazard for the consumers.

An experiment observed the behavior of selected tagged plastic items deliberately released in different habitats of a tropical mangrove forest in NE Brazil in late rainy (September) and late dry (March) seasons. Significant differences were not reported among seasons. However, marine debris retention varied among habitats, according to characteristics such as hydrodynamic (i.e., flow rates and volume transported) and relative vegetation (Rhizophora mangle) height and density. The highest grounds retained significantly more items when compared to the borders of the river and the tidal creek. Among the used tagged items, PET bottles were more observed and margarine tubs were less observed, being easily transported to adjacent habitats. Plastic bags were the items most retained near the releasing site. The balance between items retained and items lost was positive, demonstrating that mangrove forests tend to retain plastic marine debris for long periods (months-years).

Surface sediments from the coastal area of the Leizhou Peninsula in the South China Sea were collected and analyzed and the potential ecological risks in the area were assessed based on acid-volatile sulfide (AVS) model. The AVS levels are between 0.109 and 55.6μmolg−1, with the average at 4.45μmolg−1. The high AVS-concentration zones include the aquaculture areas of Liusha Bay and the densely populated areas of Zhanjiang Bay. The simultaneously extracted metals (SEM) range from 0.026μmolg−1 to 8.61μmolg–1, with the average at 0.843μmolg–1. Most of high SEM-concentration stations were located in ports or aquaculture zones. Most of the coastal surface sediments of the Leizhou Peninsula (90%) had no adverse biological effects according to the criterion proposed by USEPA (2005); while adverse effects were uncertain in some stations (8%); even in 2 stations (2%) adverse biological effects may be expected.

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.

We examined if there is truth to the preconceptions that non-resident workers (including FIFO/DIDO’s) detract from communities. We used marine debris to test this, specifically focussing on littering behaviour and evidence of awareness of local environmental programs that focus on marine debris. Littering was most common at recreational areas, then beaches and whilst boating. Twenty-five percent of respondents that admit to littering, reported no associated guilt with their actions. Younger respondents litter more frequently. Thus, non-resident workers litter at the same rate as permanent residents, visitors and tourists in this region, within this study. Few respondents are aware of the environmental programs that operate in their local region. Awareness was influenced by a respondent’s residency (non-residents are less aware), age, and level of education. To address this failure we recommend that industries, that use non-resident workers, should develop inductions that expose new workers to the environmental programs in their region.

Continuous operational monitoring by means of remote sensing contributes significantly towards less occurrence of oil spills over European waters however, operational activities show regular occurrence of accidental and deliberate oil spills over the North Sea, particularly from offshore platform installations. Since the areas covered by oil spills are usually large and scattered over the North Sea, satellite remote sensing particularly Synthetic Aperture Radar (SAR) represents an effective tool for operational oil spill detection. This paper describes the development of a semi-automated approach for oil spill detection, optimized for near real time offshore platform sourced pollution monitoring context. Eight feature parameters are extracted from each segmented dark spot. The classification algorithm is based on artificial neural network. An initial evaluation of this methodology has been carried out on 156 TerraSAR-X images. Wind and current history information also have been analyzed for particular cases in order to evaluate their influences on spill trajectory.

Metro rail has been introduced in Delhi in 2002 to provide alternative mode of public transportation. The introduction of metro rail has resulted in passenger ridership shift from road based transport to metro rail. In order to estimate the emissions (CO, HC, NOx, PM and CO2), metro rail ridership has been converted to equivalent number of on–road vehicles which otherwise would have been playing in the absence of mass rapid transit system. The emission estimation for the year 2006 and 2011 corresponding to the completion of phase I and phase II of Delhi metro rail has been made using emission and deterioration factor(s) for different category and vintage of vehicles. The sensitivity analysis has been carried out to assess the influence of different combination of input parameters such as modal shift, engine technology, and fuel type on emissions. In addition, CO2 emissions saved due to shifting of motor vehicle ridership to metro rail has been estimated and compared with the CO2 produced (off–site) due to electricity consumption by Delhi metro rail for its various operations. The findings indicate that present modal shift scenario does not yield CO2 benefits. However, it is expected that with the increase in metro ridership, changes in modal shift and energy conservation initiatives by Delhi metro, CO2 emission saving could be possible.

Surface sediments were collected from five nearshore (wastewater discharges, aquaculture facilities and a seaport) sites in Bohai Bay and Laizhou Bay, China. The equilibrium partitioning (EqP) model and empirical sediment quality guidelines (SQGs) were applied to assess the potential metal toxicity in the collected sediments. The results show that, based on the EqP model, 35% of stations exhibited potential metal toxicity. Several metals (Cu, Ni and Cr) exceeded the empirical SQGs (9–93% of the time), however these guidelines may not be suitable for use in the Bohai Sea owing to the background concentrations. The EqP model is a more useful method for assessing potential metal toxicity in Bohai Sea sediment than the empirical SQGs. Additionally, we have provided new understanding about methods for assessing sediment metal toxicity in the Bohai Sea that may be useful in other coastal areas in China.

Uptake and depuration kinetics of dissolved [14C]C12-6-linear alkylbenzene sulfonate (LAS) were determined in the shrimp Palaemonetes varians using environmentally relevant exposure concentration. The shrimp concentrated LAS from seawater with a mean BCF value of 120Lkg−1 after a 7-day exposure. Uptake biokinetics were best described by a saturation model, with an estimated BCFss, of 159±34Lkg−1, reached after 11.5days. Shrimp weight influenced significantly BCF value with smaller individuals presenting higher affinity to LAS. To the light of a whole body autoradiography, major accumulation of LAS occurred in the cephalothorax circulatory system (gills, heart, hepatopancreas) and ocular peduncle, but not in the flesh, limiting potential transfer to human consumers. LAS depuration rate constant value of the shrimp was 1.18±0.08d−1 leading to less than 1% of remaining LAS in its tissues after 8days of depuration.

The microbial community and the nirS- and nirK-encoding denitrifiers in the intertidal sediments along Laizhou Bay in China were studied using pyrosequencing and real-time quantitative PCR (qPCR), respectively. There were three primary intertidal zones: Laizhou (La), Weifang Harbor (We), and Dongying (Do). Significant differences in composition and abundances at the different taxonomic levels were observed among the three bacterial communities. The qPCR results indicated that the nirS gene abundance varied from 8.67×105 to 5.68×106copies/gwet weight (ww), whereas the nirK gene abundance varied from 1.26×105 to 1.89×106copies/gww. The canonical correlation analysis (CCA) indicated that the sand percentage was the most important factor in shaping the bacterial community followed by silt percentage, NO2−, TOC, DO, pH, and clay percentage, whereas the clay percentage, pH, NO3−, DO, NO2−, TOC, silt percentage, and sand percentage were the most important factors associated with regulating the abundance of nirS- and nirK-encoding denitrifiers.