Baseline data on anthropogenic seafloor debris contamination in the year 2000 is provided for 24 submersible video transects at depths of 80–900m, off the Dutch ABC-islands (Aruba, Bonaire, Curaçao), in the southeastern Caribbean Sea. In total, 202 objects were documented from a combined 21,184m of transect, ranging from sandy lower island-slope to rocky upper island-slope habitat. Debris densities differed significantly with depth. Highest debris accumulation (0.459 items 100m−2 or 4590 items per km2) occurred at depths of 300–600m on more shallow-sloping (20–30°) sand and silt bottoms. The overall average debris density was 0.27 objects per 100m2 (or 2700 items per km2), which is an order of magnitude higher than most other deepwater debris studies. What we describe may be representative for other small, populated, steep volcanic Caribbean islands. Food and beverage-related items were the single largest usage category identified (44% of objects; mostly glass beverage bottles).

The microbial community and the nirS- and nirK-encoding denitrifiers in the intertidal sediments along Laizhou Bay in China were studied using pyrosequencing and real-time quantitative PCR (qPCR), respectively. There were three primary intertidal zones: Laizhou (La), Weifang Harbor (We), and Dongying (Do). Significant differences in composition and abundances at the different taxonomic levels were observed among the three bacterial communities. The qPCR results indicated that the nirS gene abundance varied from 8.67×105 to 5.68×106copies/gwet weight (ww), whereas the nirK gene abundance varied from 1.26×105 to 1.89×106copies/gww. The canonical correlation analysis (CCA) indicated that the sand percentage was the most important factor in shaping the bacterial community followed by silt percentage, NO2−, TOC, DO, pH, and clay percentage, whereas the clay percentage, pH, NO3−, DO, NO2−, TOC, silt percentage, and sand percentage were the most important factors associated with regulating the abundance of nirS- and nirK-encoding denitrifiers.

Biotic indices are mainly aimed at assessing levels of deterioration caused by chemical or organic pollution. However, no biotic index to date has been developed to detect impacts of alien species on benthic communities. In this paper, a new biotic index, namely ALEX, is proposed to address the objectives of the Water Framework Directive and was tested in Mersin Bay (Levantine Sea, Turkey). Species were divided into four biogeographic groups, namely native species, casual species, established species and invasive species, and the metric considers the relative importance of these groups in samples. The index classified the ecological status of some stations which are shallow, and close to harbor and river mouths as bad or poor in February and October. The ALEX values were positively and significantly correlated with total nitrogen, silicate and silt percentage in sediment, and negatively correlated with depth and the distance from the harbor.

The level of mercury (Hg) concentration in soils can be estimated using certain predictors such as the content of organic carbon (Cₒᵣg) or the fine fractions (FFs) such as silt and clay. This study was focused on the potential use of Cₒᵣgand FF contents as the predictors of Hg concentration at the spatial meso-scale in forest soils derived from Triassic sandstones and claystones, Quaternary sands derived from weathering sandstones and Quaternary sands of fluvioglacial origin. To understand the importance of Cₒᵣgand FF contents for Hg retention in mineral soil, the allocation of Hg in physically separated fractions of soil samples was also tested. The experiment was designed over a regular 200 × 200-m grid, where 275 plots were established. The results implied that the concentration of total Hg in mineral soil may vary by several orders of magnitude because of the natural variation in Cₒᵣgcontent. The model where the Cₒᵣgcontent was the only variable explained 44 % of Hg concentration variability in soil, and other significantly correlated variables were the FF content and the C/N ratio. Detailed analysis revealed that the particulate organic matter fraction accumulated more Hg per unit of Cₒᵣgthan in the organic matter associated with FF. The content of Cₒᵣg, FF and C/N ratio allowed, for the local soils, a satisfactory prediction of the spatial distribution and the magnitude of total Hg concentration in soils.

In an effort to customize biochars for soil amendments, multiple feedstocks have been combined in various ratios prior to pyrolysis. The resulting variation in the chemistry and structure can affect a biochar’s adsorption capacity, which influences the bioavailability of many chemical compounds in the soil system including phenolic acids. This study characterizes the sorption of 14C-labeled ferulic acid, syringic acid, and chlorocatechol to four biochars prepared from individual feedstocks and four from mixed feedstocks using batch equilibration. Pure feedstock biochar sorption followed switchgrass< swine solids< poultry litter< pine chip for both ferulic (Kd= 1.4-75) and syringic acid (Kd= 0.07-6.03), and appeared to be influenced by the properties of the biochars as well as the chemicals themselves. All biochar Kd values, except pine chip, were lower than that of the reference soil (Waukegan silt loam). The sorptive properties of the combined feedstock biochars could not be predicted from their pure feedstock components and sorption coefficients were both unexpectedly higher and lower than the individual parent materials’ biochars. Further research is necessary to understand the characteristics of these combination biochars, particularly their sorption, which this study has shown is not merely an intermediary of its components.

The paper reports ultraviolet matrix-assisted laser desorption/ionization mass spectroscopy (UVMALDI-MS) protocol for determination of complex heterogeneous emulsion or suspension formulations. The active agents and surfactants are morpholine fungicide fenpropimorph (1), amorolfine (2), tridemorph (mixture of 2,6-dimethyl-4-alkylmorpholins 3–6), 2,6-dimethyl-4-[2-methyl-3-(6-methyl-decahydro-naphthalen-2-yl)-propyl]-morpholine (7), dodemorph (8), main metabolite of 1 fenpropimorph acid (9), sodium dodecyl sulfate (10), and stearate (11). The full method and techniques validation as well as method performance parameters are discussed in terms of their maximal representativeness toward real environmental and foodstuff assay problems. These are additionally complicated by heterogeneous laterally, vertically, and time distribution of pesticide contaminants and their major metabolites in environmental samples. The real environmental heterogeneous distribution is elucidated, studying sterilized soil fractions with particle size 2.0 μm, clay content 11.5 %, silt 23.0 %, sand 8.1 %, and pH ∈ 6.0–8.1. A statistical sampling cluster approach is used. The method performance parameters are concentration LODs of 0.026 mg kg⁻¹(res. LOQs 0.08666 mg kg⁻¹). Concentration linear dynamic ranges are ∈ 0.025–7.3 mg kg⁻¹(r² = 0.99822 and 0.99421) and ∈ 2.3–7.4 mg kg⁻¹(level of confidence of 99.33₁ %) for complex spiked heterogeneous soil samples. The data illustrates the great capability of method and its promising application for environmental contamination monitoring and controlling programs for assessment.

The widespread use of alkylphenols in European industry has led to their presence in the environment and the living organisms of the Baltic Sea. The present study (2011–2012) was designed to determine the concentrations of alkylphenols, 4-nonylphenol (NP) and 4-tert-octylphenol (OP), in surface sediments of the Gulf of Gdansk, a section of the Baltic that lies in close proximity to industrial and agricultural areas and borders with an agglomeration of nearly one million inhabitants. It is also where the Vistula, the largest Polish river, ends its course. In spring, large concentrations of 4-nonylphenol and 4-tert-octylphenol were washed off into the coastal zone with meltwater. In summertime, sediments near the beach had the highest alkylphenol concentrations (NP—2.31 ng g⁻¹dw, OP—13.09 ng g⁻¹dw), which was related to tourism and recreational activity. In silt sediments located off the coast, the highest NP (1.46 ng g⁻¹dw) and OP (6.56 ng g⁻¹dw) amounts were observed in autumn. The origin of OP and NP at those test stations was linked to atmospheric transport of black carbon along with adsorbed alkylphenols.

In the process of remediation of mine sites, the establishment of a vegetation cover is one of the most important tasks. This study tests two different approaches to manipulate soil properties in order to facilitate plant growth. Mine waste from Ingurtosu, Sardinia, Italy rich in silt, clay, and heavy metals like Cd, Cu, and Zn was used in a series of greenhouse experiments. Bacteria with putative beneficial properties for plant growth were isolated from this substrate, propagated and consortia of ten strains were used to inoculate the substrate. Alternatively, sand and volcanic clay were added. On these treated and untreated soils, seeds of Helianthus annuus, of the native Euphorbia pithyusa, and of the grasses Agrostis capillaris, Deschampsia flexuosa and Festuca rubra were germinated, and the growth of the seedlings was monitored. The added bacteria established well under all experimental conditions and reduced the extractability of most metals. In association with H. annuus, E. pithyusa and D. flexuosa bacteria improved microbial activity and functional diversity of the original soil. Their effect on plant growth, however, was ambiguous and usually negative. The addition of sand and volcanic clay, on the other hand, had a positive effect on all plant species except E. pithyusa. Especially the grasses experienced a significant benefit. The effects of a double treatment with both bacteria and sand and volcanic clay were rather negative. It is concluded that the addition of mechanical support has great potential to boost revegetation of mining sites though it is comparatively expensive. The possibilities offered by the inoculation of bacteria, on the other hand, appear rather limited.

In the present investigation, batch experiments were undertaken in the laboratory for different initial phenol concentration ranging from 10 to 40 mg/L using various types of fine-grained soils namely types A, B, C, D, and E based on physical compositions. The batch kinetic data were statistically analyzed with a three-layered feed-forward artificial neural network (ANN) model for predicting the phenol removal efficiency from the water environment. The input parameters considered were the adsorbent dose, initial phenol concentration, contact time, and percentage of clay and silt content in soils. The response output of the ANN model was considered as the phenol removal efficiency. The predicted results of phenol removal efficiency were compared with the experimental values as obtained from batch tests and also tests for goodness of fitting in ANN model with experimental results. The estimated values of coefficient of correlation (R = 0.99) and mean squared error (MSE = 0.006) reveals a reasonable closeness of experimental and predicted values. Out of five different types of soil, type E exhibited the highest removal efficiency (31.6 %) corresponding to 20 mg/L of initial phenol concentration. A sensitivity analysis was also carried out on the ANN model to ascertain the degree of effectiveness of various input variables.