The aim of this study was to assess the levels of heavy metal pollution in the clay/silt fraction (<63μm fraction) of marine sediments from Quintero Bay, Chile. For this, sediment samples were collected from 14 sites from the bay and analyzed for major and minor element determination. The metal concentrations found suggest an anthropogenic origin related with Cu, Se, Mo, As, Sb and Pb. The mineralogical characteristics of the samples were determined by XRD and selected samples were examined by SEM to determine morphological differences. The results showed heavy metal-bearing particles such as Cu, Zn, As and Pb, which are most likely associated with by the copper smelter.

Pacific angel sharks (Squatina californica) are a benthic elasmobranch that occupy intermediate trophic level positions in coastal food webs. Angel sharks’ life history characteristics make them susceptible to accumulating high amounts of contaminants. Four angel sharks were opportunistically captured in southern California and their liver and uterine contents were analyzed for PCBs, DDTs and other pesticides. High DDT:PCB ratios were found in the sharks indicating direct or indirect foraging near a local EPA Superfund Site. Organic contaminants were measured in ovulated eggs, indicating that females are able to maternally offload contaminants. Despite the potential mismatch between ovarian and uterine fecundity, we estimated females to offload approximately 13±5% of their total body load, which represents the upper limit of this capability. Although low in sample size, the initial findings from this study suggest that habitat use might play an important role in contaminant accumulation in this species.

Sea grasses are foundation species for estuarine ecosystems. The available light for sea grasses diminishes rapidly during pollutant spills, effluent releases, disturbances such as intense riverine input, and tidal changes. We studied how sea grasses’ remote-sensing signatures and light-capturing ability respond to short term light alterations. In vivo responses were measured over the entire visible-light spectra to diminishing white-light on whole-living-plants’ spectral reflectance, including 6h of full oceanic-light fluences from 10% to 100%. We analyzed differences by various reflectance indices. We compared the sea grasses species responses of tropical vs. temperate and intertidals (Halodule wrightii, and Zostera marina) vs. subtidal (Thalassia testudinum). Reflectance diminished with decreasing light intensity that coincided with greater accessory pigment stimulation (anthocyanin, carotenoids, xanthins). Chlorophyll a and Chlorophyll b differed significantly among species (Thalassia vs. Halodule). Photosynthetic efficiency diminished at high light intensities. The NDVI index was inadequate to perceive these differences. Our results demonstrate the leaf-level utility of data to remote sensing for mapping sea grass and sea grass stress.

Lindane is an organochlorine pesticide that has been widely used to treat agricultural pests. It is of particular concern because of its toxicity, persistence and tendency to bioaccumulate in terrestrial and aquatic ecosystems. In this context, we investigated the ability of the demosponge Hymeniacidon perlevis to bioremediate lindane polluted seawater during in vitro experimentation. Lindane was extracted by solid-phase micro-extraction (SPME) and determined by gas chromatography–mass spectrometry (GC–MS). Furthermore, we assessed the role exerted in lindane degradation by bacteria isolated from the sponge. Sponges showed low mortality in experimental conditions (lindane concentration 1μg/L) and were able to remove about 50% of the lindane content from seawater in 48h. Bacteria isolated from sponges showed a remarkable remediating capacity (up to 97% of lindane removed after 8-days). A lindane metabolite was identified, 1,3,4,5,6-pentachloro-cyclohexene. The results obtained are a prelude to the development of future strategies for the in situ bioremediation of this pollutant.

Metal pollution has been of great concern in the estuaries in Southern China. In this study, metabolic differences between oysters Crassostrea hongkongensis from clean and metal-polluted sites were characterized using NMR-based metabolomics. We collected oyster samples from one clean (Jiuzhen) and two metal polluted sites (Baijiao and Fugong). The metal concentrations in oyster gills indicated that both the Baijiao and Fugong sites were severely polluted by several metals, including Cr, Ni, Cu, Zn, Ag, Cd and Pb. In particular, Cu and Zn were the major contaminants from the Baijiao and Fugong sites. Compared with those oysters from the clean site (JZ), metal pollution in BJ and FG induced disturbances in osmotic regulation and energy metabolism via different metabolic pathways, as indicated by different metabolic biomarkers. This study demonstrates that NMR-based metabolomics is a useful tool for characterizing metabolic responses induced by metal pollution.

An experiment was carried out on an estuarine mudflat to assess impacts of inorganic nutrients used to fertilize sugar-cane fields on the surrounding aquatic ecosystem, through changes in the nematode community structure. During 118days, nine quadrats each 4m2 were sampled six times after the beginning of fertilizer addition. The fertilizer was introduced weekly in six areas, at two different concentrations (low and high doses), and three areas were used as control. The introduction of nutrients modified key nematode community descriptors. In general, the nematodes were negatively affected over the study period. However, Comesa, Metachromadora, Metalinhomoeus, Spirinia and Terschellingia were considered tolerant, and other genera showed different degrees of sensitivity. Nutrient input also affect the availability and quality of food, changing the nematode trophic structure. The use of inorganic fertilizer should be evaluated with care because of the potential for damage to biological communities of coastal aquatic systems.

Aerosol samples were collected from a site near Qinghai Lake (QHL) on the northeastern margin of the Tibetan Plateau (TP) to investigate PM2.5 mass levels and chemical composition, especially their seasonal patterns and sources. The PM2.5 ranged from 5.7 to 149.7μg m–3, and it was predominately crustal material (-40% on average). The combined mass of eight water–soluble inorganic ions ranged from 1.0 to 41.5μg m–3, with the largest contributions from SO42– NO3-, and Ca2+. Low abundances of organic carbon (OC, range: 1.0 to 8.2μg m–3) and elemental carbon (EC, 0.2 to 2.3μg m–3) were found in QHL. Weak seasonality in the OC/EC ratio (4.5±2.0) indicated simple and stable sources for carbonaceous particles. The water–soluble ions, OC and EC accounted for ~30%, 10% and 2% of the PM2.5, respectively. Water–soluble organic carbon (WSOC, range: 0.5 to 4.3μg m–3) accounted for 47.8% of the OC. Both OC and WSOC were positively correlated with water–soluble K+(r=0.70 and 0.73 respectively), an indicator of biomass burning. Higher WSOC and stronger correlations between WSOC and EC in spring and winter compared with summer and autumn are evidence for primary biomass burning aerosols. The concentrations of mass and major compositions were 2–10 times higher than those for some TP or continental background sites but much lower than urban areas. Compared with particles produced from burning yak dung (a presumptive source material), PM2.5 had higher SO42–/OC ratios. The higher ratios were presumed as a result of fossil fuel combustion. After excluding data for dust storms events, the relative percentages of OM, EC, K+, NH4+, NO3– and mineral dust showed little difference among seasons despite different monsoons dominated in four seasons; implying that the PM2.5 sources were relatively stable. The results from QHL evidently reflect regional cha racteristics of the aerosol.

Concentrations of nickel (Ni), copper (Cu), zinc (Zn) and lead (Pb) in beach and dune sands from thirteen Havana (Cuba) resorts were estimated by X-ray fluorescence analysis. Determined mean metal contents (in mg·kg−1) in beach sand samples were 28±12 for Ni, 35±12 for Cu, 31±11 for Zn and 6.0±1.8 for Pb, while for dune sands were 30±15, 38±22, 37±15 and 6.8±2.9, respectively. Metal-to-iron normalization shows moderately severe and severe enrichment by Cu. The comparison with sediment quality guidelines shows that dune sands from various resorts must be considered as heavily polluted by Cu and Ni. Almost in every resort, the Ni and Cu contents exceed their corresponding TEL values and, in some resorts, the Ni PEL value. The comparison with a Havana topsoil study indicates the possible Ni and Cu natural origin.

Parameter optimization is important for developing a water quality dynamic model. In this study, we applied data-driven method to select and optimize parameters for a complex three-dimensional water quality model. First, a data-driven model was developed to train the response relationship between phytoplankton and environmental factors based on the measured data. Second, an eight-variable water quality dynamic model was established and coupled to a physical model. Parameter sensitivity analysis was investigated by changing parameter values individually in an assigned range. The above results served as guidelines for the control parameter selection and the simulated result verification. Finally, using the data-driven model to approximate the computational water quality model, we employed the Particle Swarm Optimization (PSO) algorithm to optimize the control parameters. The optimization routines and results were analyzed and discussed based on the establishment of the water quality model in Xiangshan Bay (XSB).