We studied abundance, size and polymer type of microplastic down to 10μm along a transect from the European Coast to the North Atlantic Subtropical Gyre (NASG) using an underway intake filtration technique and Raman micro-spectrometry. Concentrations ranged from 13 to 501itemsm−3. Highest concentrations were observed at the European coast, decreasing towards mid-Atlantic waters but elevated in the western NASG. We observed highest numbers among particles in the 10–20μm size fraction, whereas the total volume was highest in the 50–80μm range. Based on a numerical model size-dependent depth profiles of polyethylene microspheres in a range from 10–1000μm were calculated and show a strong dispersal throughout the surface mixed layer for sizes smaller than 200μm. From model and field study results we conclude that small microplastic is ubiquitously distributed over the ocean surface layer and has a lower residence time than larger plastic debris in this compartment.

In order to assess marine sediment quality of a semi-enclosed bay, sediment and meiofaunal samples were analyzed at 35 stations in coastal waters of Bohai Bay, China. Concentrations of heavy metals (Cd, Cr, Cu, Ni, Pb, Zn, Co and Mn) in sediment were measured and the Hakanson potential ecological risk index coupled with the ratio of nematodes to copepods (N/C ratio) was used. Results showed that the concentration of Mn was the highest while Cd was the main risk contributor. The Hakanson potential ecological risk index indicated that all pollutants posed low risks in the study area. However, the N/C ratio exhibited different results compared with Hakanson potential ecological risk index. BIOENV analysis identified the concentration of Ni and sediment grain size as the most important environmental variables influencing meiofaunal assemblages. The present study indicated that, in marine sediment quality assessments, meiofaunal assemblages should be involved besides pollutant concentrations.

Little is known about the recovery trajectory from small to moderate spills (<1000t), particularly in the sub-tropics. On 11 March 2009 the MV Pacific Adventurer spilt 270t of bunker fuel oil 13km off Moreton Island, Australia, impacting wetlands, sandy beaches and rocky shores. This study examines the recovery of the rocky shore community four years after the spill. Results indicate that recovery on Moreton Island is taking longer than the 3–4years suggested by the literature. The upper shore is recovering faster than the mid shore and is nearly recovered while the mid shore is still in the recovery process. These results indicate that small to moderate sized spills can have environmental impacts on par with much larger spills and emphasizes the need for a clear definition of a recovery endpoint. Long term studies are required to gain a full understanding of trajectories of recovery after oil spill impacts.

The formation of acid mine drainage (AMD), a highly acidic and metal-rich solution, is the biggest environmental concern associated with coal and mineral mining. Once produced, AMD can severely impact the surrounding ecosystem due to its acidity, metal toxicity, sedimentation and other deleterious properties. Hence, implementations of effective post-mining management practices are necessary to control AMD pollution. Due to the existence of a number of federal and state regulations, it is necessary for private and government agencies to come up with various AMD treatment and/or control technologies. This review describes some of the widely used AMD remediation technologies in terms of their general working principles, advantages and shortcomings. AMD treatment technologies can be divided into two major categories, namely prevention and remediation. Prevention techniques mainly focus on inhibiting AMD formation reactions by controlling the source. Remediation techniques focus on the treatment of already produced AMD before their discharge into water bodies. Remediation technologies can be further divided into two broad categories: active and passive. Due to high cost and intensive labor requirements for maintenance of active treatment technologies, passive treatments are widely used all over the world. Besides the conventional passive treatment technologies such as constructed wetlands, anaerobic sulfate-reducing bioreactors, anoxic limestone drains, open limestone channels, limestone leach beds and slag leach beds, this paper also describes emerging passive treatment technologies such as phytoremediation. More intensive research is needed to develop an efficient and cost-effective AMD treatment technology, which can sustain persistent and long-term AMD load.

The complexity of analyzing and predicting smoke plumes that originate from forest fire events and impact populated regions of southern Ontario motivates the innovative application of analytical techniques including trajectory–based receptor modeling for spatial source apportionment of the observed near–real–time particulate matter (PM) impacts. PM2.5 was selected as an indicator of a pollutant emitted by fires that could be transported over long distances (when entrained into the transport layer above the planetary boundary layer (PBL), and subject to sink and transformation processes) and be monitored using the existing air quality monitoring network. The source term modeling technique of simplified Quantitative Transport Bias Analysis (sQTBA) was applied to several summertime forest fire events to identify the locations of sources affecting air quality in Ontario during these events. Complementary techniques that helped to understand the movement of smoke plumes included satellite remote sensing of carbon monoxide and aerosols. All of these techniques, along with meteorological analysis, jointly provide a means of identifying the forest fire events that resulted in noticeably higher pollutant levels in Ontario. Specifically, three forest fire events in July of 2011, 2012 and 2013 were analyzed, and source regions of near–real–time PM2.5 concentrations were revealed to be both within Ontario and across northern Canada from Quebec to Yukon. The sQTBA was found to successfully identify the relative importance of various source regions contributing plumes from forest fires and non–wildfire related sources that caused higher pollutant levels that were measured in Ontario. The use of near–real–time PM2.5 data in this study facilitates the identification of the exact periods with high pollution impacts across multiple receptor sites, thus improving the overall quality of the analyses. This work shows how trajectory–based receptor models can be integrated with meteorological analyses for thorough source apportionment of wildfire–related pollution events.

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.

Intensive fire ignition and cracker work activities takes place during the festival of light called Diwali in India, celebrated for a period of few days in the month of October or November every year. The firecracker releases several pollutants [such as particulate matter (PM), black carbon (BC), organics, trace gases] near the surface. The effect of firecrackers on the atmospheric constituents is evaluated over Dibrugarh by monitoring the concentrations of PM, PM10 (particle radius ≤10 µm), PM2.5 (particle radius ≤2.5 µm) and BC during the Diwali and post-Diwali days (5 days after the Diwali Festival) in the years 2009 and 2010. Monthly average concentrations of each species except for the Diwali and post Diwali days is considered as the background concentrations. The concentration levels of the pollutants as recorded on the Diwali days are found to be a number of times higher (5.33 and 2.50 times for PM10, 5.74 and 2.65 times for PM2.5, 1.21 and 1.66 times for BC for the year 2009 and 2010, respectively) than the background levels at the peak hours of the fire work activity. To delineate the contribution of fireworks to the high concentrations of the species we performed air mass back trajectory analysis using the NOAA–HYSPLIT model in order to examine the existence of the transported aerosols. The ten day accumulated MODIS fire maps are also analyzed to mark out the contribution of aerosols from biomass burning. These analyses reveal that the higher concentrations of near surface aerosols including BC during the festival is due to the local effect of firework activities, neither because of long–range transport nor due to biomass burning activities. However, the higher concentration of pollutants for short periods has not degraded air quality substantially to cause health risks to people exposed to the festival in this environment.

Elasmobranchs can bioaccumulate considerable amounts of persistent organic pollutants (POPs) and utilize several reproductive strategies thereby influencing maternal transfer of contaminants. This study provides preliminary data on the POP transfer from pregnant females to offspring of three species (Atlantic stingrays, bonnethead, blacktip sharks) with different reproduction modes (aplacental, placental viviparity). Polychlorinated biphenyl (PCB) levels were generally higher than any other POPs. Stingrays and blacktip shark embryos contained the lowest POP concentrations while bonnetheads and the blacktip adult female had the highest concentrations. Results suggest that POPs are more readily transferred from the mother to the embryo compared to what is transferred to ova in stingrays. Statistically significant differences in levels of selected POPs were found between embryos from the left and right uterus within the same litter as well as between female and male embryos within the same litter for bonnetheads, but not for the blacktip sharks.

The aim of this study was to analyze the density, diversity, biomass and assemblage composition of the phytoplankton in relation to environmental conditions (physical, chemical, hydrological and meteorological variables), measured under the different scenarios caused by the ENSO phenomenon in the period between 2005 and 2012, in six sampling sites in the tidal freshwater zone of the Río de la Plata estuary, covering almost 100km of coastline. The results revealed changes in the structure of the phytoplankton, such as a significant reduction of diversity, and decreases in biomass and phytoplankton density, particularly during El Niño phases. Cyanobacteria were more abundant in the neutral periods, Chlorophyceae dominated La Niña phase while Bacyllariophyceae dominated El Niño. However, no complete replacement of species between cycles was observed. The results obtained were highly variable due to the inherent natural variability of the Río de la Plata, emphasized by the anthropogenic impact in this area.

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.