Solid Phase Microextraction (SPME) was applied to provide the first large scale dataset of freely dissolved concentrations for 9 polycyclic aromatic hydrocarbons (PAHs) in Baltic Sea sediment cores. Polydimethylsiloxane (PDMS) coated glass fibers were used for ex-situ equilibrium sampling followed by automated thermal desorption and GC–MS analysis. From the PAH concentrations in the fiber coating we examined (i) spatially resolved freely dissolved PAH concentrations (Cfree); (ii) baseline toxicity potential on the basis of chemical activities (a); (iii) site specific mixture compositions; (iv) diffusion gradients at the sediment water interface and within the sediment cores and (v) site specific distribution ratios. Contamination levels were low in the northern Baltic Sea, moderate to elevated in the Baltic Proper and highest in the Gulf of Finland. Chemical activities were well below levels expected to cause narcosis to benthos organisms. The SPME method is a very sensitive tool that opens new possibilities for studying the PAHs at trace levels in marine environments.

Peninsular Malaysia has gone through fast development during recent decades resulting in the release of large amounts of petroleum and its products into the environment. Aliphatic hydrocarbons are one of the major components of petroleum. Surface sediment samples were collected from five rivers along the west coast of Peninsular Malaysia and analyzed for aliphatic hydrocarbons. The total concentrations of C10 to C36 n-alkanes ranged from 27,945 to 254,463ng·g−1dry weight (dw). Evaluation of various n-alkane indices such as carbon preference index (CPI; 0.35 to 3.10) and average chain length (ACL; 26.74 to 29.23) of C25 to C33 n-alkanes indicated a predominance of petrogenic source n-alkanes in the lower parts of the Rivers, while biogenic origin n-alkanes from vascular plants are more predominant in the upper parts, especially in less polluted areas. Petrogenic sources of n-alkanes are predominantly heavy and degraded oil versus fresh oil inputs.

Using the vas deferens sequence index (VDSI) and relative penis size index (RPSI) in dogwhelks (Nucella lapillus), imposex levels were assessed at 63 sites within 11 sea inlets during 2010/2011 and compared these with levels gathered since 1987. Sterile females (VDS>5.0) were found at 14 of the 63 sites and 47 sites (75%) met the EcoQO (VDSI<2.0). The absence of imposex in ‘control’ areas on the west coast is due to the lack of vessel paint applications or net dips with TBT being used as an active anti-fouling ingredient. A significant decline was observed following 2005 when comparing VDSI levels which is consistent with the decline of TBT usage. Current levels are consistent with an overall improvement towards achieving Good Environmental Status according to the requirements under the Marine Strategy Framework Directive.

During the 20th century Idefjord was considered one of the most polluted marine areas in Scandinavia. For decades it received high discharges from paper/pulp industry, which made it anoxic and extremely polluted by heavy metals and organic contaminants. Today the fjord is close to fulfil a complete pollution-recovery cycle, which is recorded in its sediment archives. Here we report results from five sediment cores studied for TC, C/N, heavy metals and benthic foraminifera. All of the cores have laminations deposited during 1940–1980s and indicative of long-lasting anoxia; high TC and heavy metal content, poor foraminiferal faunas and lack of macrofauna. The upper part of the cores deposited since 1980s shows a gradual pollutant decrease and partial foraminiferal recovery. The majority of foraminiferal species in Idefjord are agglutinated opportunistic and stress-tolerant taxa, which to some extent tolerate hypoxia and are early colonisers of previously disturbed environments. The current study demonstrates a value of benthic foraminiferal stratigraphy as a useful tool in understanding processes driving environmental degradation and recovery of coastal ecosystems.

The influence of nutrients on the growth of Ulva prolifera was studied in the SYS by field experiments. The wet weight of U. prolifera gradiently increased from 11.94% to 25.92% in proportion to contents of DIN supply, which indicated DIN content was essentially decisive for the output of U. prolifera blooms. Continuous nutrient supply could promote the growth of U. prolifera, indicated by the increase of growth rate from 10.46% of the batch culture to 42.17% of the in situ culture. The higher P utilized rate in all treatments showed P was the potential limited factor for the growth of U. prolifera. Moreover, it was calculated about 4.1×105t organic matter was begot by U. prolifera in the whole Yellow Sea based on the statistical relationship between output of U. prolifera and DIN content. This work could be convenient to evaluate biomass and prepare enough tools to manage U. prolifera.

Microplastics (MPs) are a newly recognized type of environmental pollution in aquatic systems; however no monitoring of these contaminants is conducted, mostly due to the lack of routine quantification. In the net samples collected with a 90-μm WP2 net, pelagic MP abundance was quantified by light microscopy and evaluated as a function of inshore–offshore gradient, depth, and season; the same samples were used for zooplankton analysis. The MP abundance was ∼102–104particlesm−3, with no significant inshore–offshore gradient during summer but increasing offshore in winter. MP abundance in deeper layers was positively affected by zooplankton abundance in the upper layers and significantly lower during winter compared to summer. These findings indicate heterogeneity of MP distribution due to biotic and abiotic factors and suggest that samples collected for other purposes can be used for quantification of MPs in the Baltic Sea, thus facilitating integration of MP assessment into existing monitoring schemes.

The statistical regression and specific computational intelligence based models are presented in this paper for the forecasting of hourly NO2 concentrations at a historical monument Taj Mahal, Agra. The model was developed for the purpose of public health oriented air quality forecasting. Last ten–year air pollution data analysis reveals that the concentration of air pollutants increased significantly. It is also observed that the pollution levels are always higher during the months of November at around Taj Mahal, Agra. Therefore, the hourly observed data during November were used in the development of air quality forecasting models for Agra, India. Firstly, multiple linear regression (MLR) was used for building an air quality–forecasting model to forecast the NO2 concentrations at Agra. Further, a novel approach, based on regression models, principal component analysis (PCA) was analyzed to find the correlations of different predictor variables between meteorology and air pollutants. Then, the significant variables were taken as the input parameters to propose the reliable physical artificial neural network (ANN)-multi layer perceptron model for forecasting of air pollution in Agra. MLR and PCA–ANN models were evaluated through statistical analysis. The correlation coefficients (R) were 0.89 and 0.91 respectively, for PCA–ANN and were 0.69 and 0.89 respectively for MLR in the training and validation periods. Similarly, the values of normalized mean square error (NMSE), index of agreement (IOA) and fractional bias (FB) were in good agreement with the observed values. It was concluded that PCA–ANN model performs better and can be used for forecasting air pollution at Taj Mahal, Agra.

In order to compare the effects of weathering on two types of mixed oil, simulated weathering experiments were performed. The first sample was a mixture of two fresh oils and the second sample was a mixture of one fresh oil and another oil sample that had undergone a serious weathering process. Comparative studies evaluated decay rates and changes in diagnostic ratios of some fingerprinting biomarkers. Results showed that the mixing process affected the weathering rate of some compounds in the oils and also that certain diagnostic ratios are more suitable for estimating mixing proportions. A Pr/n-C17 versus Ph/n-C18 plot can be used to identify the end-numbers of mixed oils and the (C13+C14)/(C25+C26) ratio is a useful diagnostic ratio to detect the degree of weathering. Finally, hopane, sterane, and alkylated PAH fingerprints were found to give useful insights about the sources of the mixed oils.