This article describes design and application of feed-forward, fully-connected, three-layer perceptron neural network model for computing the water quality index (WQI)¹ for Kinta River (Malaysia). The modeling efforts showed that the optimal network architecture was 23-34-1 and that the best WQI predictions were associated with the quick propagation (QP) training algorithm; a learning rate of 0.06; and a QP coefficient of 1.75. The WQI predictions of this model had significant, positive, very high correlation (r=0.977, p<0.01) with the measured WQI values, implying that the model predictions explain around 95.4% of the variation in the measured WQI values. The approach presented in this article offers useful and powerful alternative to WQI computation and prediction, especially in the case of WQI calculation methods which involve lengthy computations and use of various sub-index formulae for each value, or range of values, of the constituent water quality variables.

Introducing invasive species in new environments through ballast water is a specific problem of contamination and has recently become one of the main concerns of Maritime Organizations. Ultraviolet-C radiation (UV-C) is a technological alternative to prevent this maritime pollution. This study addresses the effect of UV-C on different phytoplankton cultures and also the ability to recover following exposure to damage. A UV-C low-pressure lamp irradiates the cultures. The distance from the source and the thickness of the layer prevent part of the energy from reaching the culture and the disinfective process is diminished. Some cultures such as Chlorella autotrophica and Chaetoceros calcitrans can easily recover from UV-C damage. However, Phaeocystis globosa does not have this ability. C. calcitrans forms cysts and exhibits two different behaviours depending on the dose applied.

This paper describes different numerical models of ocean circulation the output of which can be applied to study patterns and pathways of drifting marine debris. The paper focuses on model output that is readily available rather than on numerical models that could be configured and run locally. These include operational models from the US Navy (the Navy Layered Ocean Model (NLOM), Coastal Ocean Model (NCOM), and Hybrid Coordinate Ocean Model (HYCOM)), data assimilating reanalysis models (the Simple Ocean Data Assimilation (SODA), the Global Ocean Data Assimilation Experiment (GODAE) models), and the European Center for Medium-Range Weather Forecasts (ECMWF) ocean reanalysis (Ocean Reanalysis System, ECMWF/ORA-S3). The paper describes the underlying physics in each model system, limitations, and where to obtain the model output.

Levels and trends of persistent organic pollutants and trace elements in seabirds breeding in the vast Canadian Arctic have been monitored since 1975. Data from this monitoring have indicated both spatial and temporal variation across the region, attributable in part to differences in species’ diets, differences in regional deposition patterns, and unidirectional trends in contaminants reaching this area from emissions in temperate and tropical areas to the south. Seabird tissues have served as effective biomonitors to examine this variation, and national and international collaboration in this monitoring effort has promoted valuable synthetic assessments of spatial and temporal patterns in Arctic contaminants. Here we review the history of the monitoring program, the critical role played by Environment Canada’s National Wildlife Specimen Bank, and we summarize important spatial and temporal trends in various contaminants in Canadian Arctic seabirds.

This paper presents results related to the occurrence and distribution of estrogens along the Brazilian coast. Three mangrove areas were chosen to evaluate the presence of estrogens in surface sediments of mangrove forests. The presence of estrogens was observed in all studied sites. 17-α-Ethinylestradiol (EE2), a synthetic estrogen, was the most common and has been found in higher concentration (0.45–129.78ng/g) compared to 17-β-estradiol (E1) and estrone (E2) (both being natural estrogens). The concentrations of E1 and E2 ranged from 0.02 to 49.27ng/g and 0.03 to 39.77ng/g, respectively. Theoretically, under anaerobic conditions EE2 can be reduced to E1 even in environments such as sediments of mangrove forests, which are essentially anaerobic. Even if the concentrations of estrogens seem to be insignificant in some samples, the effects remain uncertain.

The clams Ruditapes philippinarum were used to assess the impact of metal contaminants when transplanted to seven study sites along the Maluan Bay (China). Metal concentrations in digestive gland tissues of clams after 7-day in situ cage exposure were determined in conjunction with antioxidant enzyme activities. The results showed the importance of specific antioxidant biomarkers to assess complex pollutant mixtures and their good correlations to the pollutant compositions of deployment sites. Multivariate analysis indicated causal relationship between the chemicals at each study site and the biochemical “response” of the caged clams at these sites and demonstrated the potential presence of two different contaminant sources. This study suggested that the incorporation of tissue residue analysis with biomarkers response in caged clams together with factor analysis can be a useful biomonitoring tool for the identification of causal toxic pollutants and the assessment of complex metal pollutions in marine coastal environment.

To investigate the influence of mangrove reforestation on the accumulation of PCBs, the concentrations and homologue patterns of polychlorinated biphenyls in surface sediments from different mangrove forests and their adjacent mud flats in Guangdong Province were determined. The total PCB concentrations in the sediments ranged from 3.03 to 46.62ngg⁻¹ (dry weight). Differences in the accumulation and distribution of PCBs were found between the mangrove sites and the mud flats. Furthermore, the natural forests and restored mangrove forests of native species showed slight PCB contamination, whereas the exotic species Sonneratia apetala exacerbated the PCB pollution at certain sites. It was suggested that the native mangrove species Kandelia candel and Aegiceras corniculatum could represent good choices for the phytoremediation of PCB contamination.

Tropical coastal ecosystems, including the Great Barrier Reef (GBR) of Australia are increasingly threatened by pollution; yet few studies have investigated the sensitivity of GBR species to these pollutants. Here we exposed juveniles of the tropical reef fish Acanthochromis polyacanthus (spiny damselfish) to three concentrations of the insecticide chlorpyrifos (CPF) and measured (i) muscle cholinesterase (ChE) activity; (ii) hepatic glutathione-S-transferase (GST) activity; and (iii) coenzyme Q (CoQ) redox balance, after 6h and 96h of exposure. After 96h, muscle ChE activity was significantly inhibited by 26%, 49% and 53% when fish were exposed to 1, 10 or 100μg/L CPF, respectively. Muscle ChE characterization revealed three types of ChEs, including two atypical forms. Hepatic CoQ antioxidant form significantly increased at 10μg/L after 6h of exposure, potentially demonstrating an early response to CPF-induced oxidative stress in liver. Hepatic GST was not affected by CPF exposure.

We assessed the occurrence of pollution indicators and antibiotic resistant bacterial isolates from water and sediment samples of three different eco-regions of the Chennai coast between March – May of 2010. Total of 960 bacterial strains belonging to four genera were isolated which show the highest frequencies of resistance to vancomycin (53.6%) and penicillin (52.6%) (except Enterococcus sp., which is highly resistant to erythromycin) and lowest frequencies of resistance to chloramphenicol (3.43%), ciprofloxacin (3.95%), gentamicin (4.68%), and tetracycline (6.97%). The E. coli, Vibrio sp., Salmonella sp. and Enterococcus sp. show high frequency of resistance to 2–5 antibacterials of 60.4%, 45.83%, 69.16% and 46.6%, respectively. High pollution indices (PI – 6.66–14.06) and antibiotic resistance indices (ARI – 0.29–0.343) indicate that the coastal environment is highly exposed to antibiotic sources that suggesting to avoid direct contact.