This study is an attempt to explore the effectiveness of satellite data in predicting hourly PM2.5 (Respirable particulate matter with aerodynamic diameter below 2.5 μm) concentrations for a chosen number of forward time steps over eastern China. MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth (AOD), hourly forecasted meteorological variables, along with respective pollutant predictors from 2013 to 2015 were used as input to a multi-layer perceptron (MLP) type of back-propagation neural network. A novel approach, based on the correlation coefficients between surface PM2.5 and meteorological variables, was employed in selecting the averaging periods for meteorological input. Backward air mass trajectory was combined with AOD so as to explicitly measure the contribution of regional transport. Owing to the spatial variability of the AOD-PM2.5 relationship, each grid cell on the AOD retrievals was assigned to a prediction model trained by the nearest monitoring station from them. The proposed model seems to perform better in southern China. Also predictions incorporating transport predictor tend to have higher rates of detecting PM2.5 exceedance hours. We further introduced a sensitive analysis in Beijing by testing a model with surface PM2.5 input, evaluated versus the AOD input one. The two models were evaluated on the perturbed test set with input values ranging from 10 to 40%. It is found that PM model significantly outperforms the AOD one when the prediction horizon is longer than 36 h. This approach shows potential to be adapted for other regions, but will be most useful for areas without access to sophisticated deterministic models.

Mercury bioaccumulation is frequently observed in marine ecosystems, often with stronger effects at higher trophic levels. We compared total mercury (THg) and methylmercury (MeHg) from muscle with length, comparative isotopic niche, and diet (via δ13C and δ15N) among four sympatric coastal sharks in Florida Bay (USA): blacknose, blacktip, bull, and lemon. Mercury in blacknose and blacktip sharks increased significantly with size, whereas bull and lemon sharks had a high variance in mercury relative to size. Both δ13C and δ15N were consistent with general resource use and trophic position relationships across all species. A significant relationship was observed between δ13C and mercury in blacktip sharks, suggesting an ontogenetic shift isotopic niche, possibly a dietary change. Multiple regression showed that δ13C and δ15N were the strongest factors regarding mercury bioaccumulation in individuals across all species. Additional research is recommended to resolve the mechanisms that determine mercury biomagnification in individual shark species.

Marine caves are unique and vulnerable habitats, threatened by multiple global and local disturbances. Whilst the effects of climate change on marine caves have already been investigated, no information exists about the effects of local human impacts, such as coastal development, on these habitats. This study investigated the impact of the construction of a touristic harbour on two shallow underwater marine caves in the Ligurian Sea (NW Mediterranean). As a standard methodology for monitoring marine caves does not exist yet, changes over time on the benthic community were assessed adopting two different non-taxonomic descriptors: trophic guilds and growth forms. Harbour construction caused an increase of sediment load within the caves, with a consequent decline of filter feeder organisms. Abundance of small organisms, such as encrusting and flattened sponges, was greatly reduced in comparison to organisms with larger and erect growth forms, such as domed mounds and pedunculated sponges. Our study indicated that growth forms and trophic guilds are effective descriptors for evaluating changes over time in marine caves, and could be easily standardised and applied in monitoring plans. In addition, as the harbour construction impacted differently according to the cave topography, the use of a systematic sampling in different zones of an underwater cave is recommended.

At present, few studies have investigated the marine litter abundance, composition and distribution on rocky bottoms due to sampling constraints. We surveyed by means of the ROV imaging technique a system of biogenic rocky outcrops classified as a Site of Community Importance in the Adriatic Sea. A mean density of 3.3 (±1.8) items/100m2 was recorded, with a strong dominance of fishing- and aquaculture-related debris, accounting for 69.4% and 18.9% of the total, respectively. The abundance of litter over the rocky bottoms was significantly higher than that on soft substrates, and its spatial distribution proved to be related to hydrographic factors. Litter-fauna interactions were high, with most of the debris (65.7%) entangling or covering benthic organisms, in particular habitat constructors such as the endangered sea sponge Geodia cydonium. Unless appropriate measures are undertaken to address this problem, the abundance of marine litter in the area is likely to increase.

In this study marine litter (ML) surveys were conducted in 8 beaches along the Bulgarian Black Sea coastline within 4 seasons for 2015–2016. The monitoring applied OSPAR guideline, classifying ML in eight categories and 167 types. The results exhibited predominance of artificial polymer materials - 84.3%. ML densities ranged from 0.0587±0.005 to 0.1343±0.008 n/m2, highest on the urban beaches. The seasonal dynamics of most top 10 ML showed highest quantities in summer than the other seasons, as the differences are of high statistical significance (0.001≤P≤0.05). Top 1 ML item for most of the beaches was cigarette butts and filters reaching 1008±10.58 nos. in summer and from 19±3.41 to 89±7.81 nos. during the rest of the seasons (P<0.001). For the pronounced seasonality contributed the recreational activities, increased tourist flow and the wild camping. The investigation will enrich data scarcity for Descriptor 10 “Marine litter”.

Seawater, sediment and fish (anchovy) samples consumed in the Rize province of the Eastern Black Sea region of Turkey were collected from five different stations. The radioactivity levels (226Ra, 232Th, 40K and 137Cs) were determined in all the samples using a high-purity germanium detector. While 226Ra, 232Th and 40K radionuclides were detected in all samples, the radionuclide concentration of 137Cs, except for the sediment samples (mean activity is 9±1.4Bqkg−1), was not detected for the seawater and fish samples. The total annual effective dose rates from the ingestion of these radionuclides for fish were calculated using the measured activity concentrations in radionuclides and their ingested dose conversion factor. Also, the concentrations of some heavy metals in all the samples were determined. The activity and heavy metal concentration values that were determined for the seawater, sediment and fish samples were compared among the locations themselves and with literature values.

Trophic-functional groupings are an important biological trait to summarize community structure in functional space. The heterogeneity of the tropic-functional pattern of protozoan communities and its environmental drivers were studied in coastal waters of the Yellow Sea during a 1-year cycle. Samples were collected using the glass slide method at four stations within a water pollution gradient. A second-stage matrix-based analysis was used to summarize spatial variation in the annual pattern of the functional structure. A clustering analysis revealed significant variability in the trophic-functional pattern among the four stations during the 1-year cycle. The heterogeneity in the trophic-functional pattern of the communities was significantly related to changes in environmental variables, particularly ammonium-nitrogen and nitrates, alone or in combination with dissolved oxygen. These results suggest that the heterogeneity in annual patterns of protozoan trophic-functional structure may reflect water quality status in coastal ecosystems.

Particulate matter (PM2.5, PM10, and TSP), black carbon (BC), and PM constituent components were measured at a location in an urban residential neighborhood of Kathmandu Valley, Nepal. PM2.5, TSP, and BC were measured during winter, and PM2.5, PM10, and their chemical composition was measured during the summer monsoon periods in 2014. Both indoor and outdoor measurements were collected during the winter season. There was a distinct seasonal profile of PM2.5 concentration, with the 24-hour mean larger during winter (76 ± 18 μg/m3) than monsoon (21 ± 8 μg/m3). This site was located approximately 15 m above the street, but was still influenced by roadway combustion sources indicated by large BC concentration (15 ± 3 μgC/m3 during winter) and large rush hour PM and BC peaks. Two rush hour peaks of PM and BC were observed during morning and evening. Indoor and outdoor PM2.5 and BC concentration measured during winter were similar suggesting the heavy influence of outdoor traffic activities on such indoor environments. Mean 24-hour TSP during winter and PM10 during monsoon was 109 μg/m3 and 34 μg/m3, respectively. PM2.5 accounted for 75% of TSP during winter and 61% of PM10 during monsoon indicating a high degree of influence by PM2.5 sources. Sulfate, ammonium, and calcium were the dominant components of water-soluble ions, and silica, iron, aluminum, and barium were the major elements in both PM10 and PM2.5 during monsoon indicating the most important emission sources as traffic emissions and road/soil/construction-related dust.

Of the wide variety of dumped objects containing radioactive materials in the Arctic seas, the submarine K-27 constitutes a major risk due to the large amount of highly enriched uranium onboard and its location in shallow waters. As the matter of potential operations involving raising of the submarine have entered the public arena, a priori assessment of the contamination in the Arctic marine environment that could result after a possible accident during such operations is a matter of some interest. The dispersion of contaminants within the Arctic has been assessed using a large scale hydrodynamic model for a series of plausible accident scenarios and locations under different oceanographic regimes. Results indicate that, depending primarily on the nature of a release (i.e. instantaneous or continuous), large areas of the Arctic marine environment will exhibit contamination to varying degrees.

As oil transport increasing in the Texas bays, greater risks of ship collisions will become a challenge, yielding oil spill accidents as a consequence. To minimize the ecological damage and optimize rapid response, emergency managers need to be informed with how fast and where oil will spread as soon as possible after a spill. The state-of-the-art operational oil spill forecast modeling system improves the oil spill response into a new stage. However uncertainty due to predicted data inputs often elicits compromise on the reliability of the forecast result, leading to misdirection in contingency planning. Thus understanding the forecast uncertainty and reliability become significant. In this paper, Monte Carlo simulation is implemented to provide parameters to generate forecast probability maps. The oil spill forecast uncertainty is thus quantified by comparing the forecast probability map and the associated hindcast simulation. A HyosPy-based simple statistic model is developed to assess the reliability of an oil spill forecast in term of belief degree. The technologies developed in this study create a prototype for uncertainty and reliability analysis in numerical oil spill forecast modeling system, providing emergency managers to improve the capability of real time operational oil spill response and impact assessment.