The effect of different sewage concentrations (0, 20, 60 and 100%), vegetation (Bare, Avicennia marina or Rhizophora mucronata) and immersion periods (immersion/emersion period of 12/12 h or 3/3 days just for 100%) conditions were studied for 6 months on survival and growth rates of Terebralia palustris (Linnaeus, 1767). Gastropods' activity and ecosystem engineering preformed at bare and A. marina planted cells and 3 sewage conditions (0, 20 and 60%) were determined. Survival rates were higher than 70% in all treatments. Growth rate decreased significantly with increasing sewage concentrations (mainly at unplanted conditions) and longer immersion periods. A complete shift (from immersion to emersion periods) and a significant decrease in mobility and consequently its engineer potential, due to sewage contamination, lead to a 3–4 fold decrease in the amount of sediment disturbed. Sewage contamination, primary producers' abundance and environmental conditions may have influenced the gastropods survival, growth and its ecosystem engineering potential. Terebralia palustris high ecosystem engineering potential in constructed mangrove wetlands.

Heavy metal contamination has been and continues to be a worldwide phenomenon that has attracted a great deal of attention from governments and regulatory bodies. In this context, our study proposes a regression-tree model to predict the concentration level of zinc in the soils of northern Lebanon (as a case study of Mediterranean landscapes) under a GIS environment. The developed tree-model explained 88% of variance in zinc concentration using pH (100% in relative importance), surroundings of waste areas (90%), proximity to roads (80%), nearness to cities (50%), distance to drainage line (25%), lithology (24%), land cover/use (14%), slope gradient (10%), conductivity (7%), soil type (7%), organic matter (5%), and soil depth (5%). The overall accuracy of the quantitative zinc map produced (at 1:50.000 scale) was estimated to be 78%. The proposed tree model is relatively simple and may also be applied to other areas. GIS regression-tree analysis explained 88% of the variability in field/laboratory Zinc concentrations.

We investigated foliar and litter responses of European aspen (Populus tremula L.) to urbanization, including factors such as increased temperature, moisture stress and nitrogen (N) deposition. Leaf samples were collected in 2006-2008 from three urban and three rural forest stands in the Helsinki Metropolitan Area, southern Finland, and reciprocal litter transplantations were established between urban and rural sites. Urban leaves exhibited a higher amount of epicuticular waxes and N concentration, and a lower C:N ratio than rural ones, but there was no difference in specific leaf area. Urban litter had a slightly higher N concentration, lower concentrations of lignin and total phenolics, and was more palatable to a macrofaunal decomposer. Moreover, litter decay was faster at the urban site and for urban litter. Urbanization thus resulted in foliar acclimatization in terms of increased amount of epicuticular waxes, as well as in accelerated decomposition of the N-richer leaf litter.

Stomatal O3 fluxes to a mixed beech/spruce stand (Fagus sylvatica/Picea abies) in Central Europe were determined using two different approaches. The sap flow technique yielded the tree-level transpiration, whereas the eddy covariance method provided the stand-level evapotranspiration. Both data were then converted into stomatal ozone fluxes, exemplifying this novel concept for July 2007. Sap flow-based stomatal O3 flux was 33% of the total O3 flux, whereas derivation from evapotranspiration rates in combination with the Penman-Monteith algorithm amounted to 47%. In addition to this proportional difference, the sap flow-based assessment yielded lower levels of stomatal O3 flux and reflected stomatal regulation rather than O3 exposure, paralleling the daily courses of canopy conductance for water vapor and eddy covariance-based total stand-level O3 flux. The demonstrated combination of sap flow and eddy covariance approaches supports the development of O3 risk assessment in forests from O3 exposure towards flux-based concepts.

In this study Pb isotope signatures were used to identify the provenance of contaminant metals and establish patterns of downstream sediment dispersal within the River Maritsa catchment, which is impacted by the mining of polymetallic ores. A two-fold modelling approach was undertaken to quantify sediment-associated metal delivery to the Maritsa catchment; employing binary mixing models in tributary systems and a composite fingerprinting and mixing model approach in the wider Maritsa catchment. Composite fingerprints were determined using Pb isotopic and multi-element geochemical data to characterize sediments delivered from tributary catchments. Application of a mixing model allowed a quantification of the percentage contribution of tributary catchments to the sediment load of the River Maritsa. Sediment delivery from tributaries directly affected by mining activity contributes 42-63% to the sediment load of the River Maritsa, with best-fit regression relationships indicating that sediments originating from mining-affected tributaries are being dispersed over 200 km downstream.

The aim of this study was to explore how atmospherically derived soil pollution is affected by environmental processes at two typical boreal catchment landscape type settings: wetlands and forested areas. Measurements of hydrophobic organic compounds (HOCs) in forest soil and peat from an oligotrophic mire at various depths were performed at a remote boreal catchment in northern Sweden. HOCs in peat were evenly distributed throughout the body of the mire while levels of HOCs in the forest soil increased with increased amount of organic matter. Evaluation of HOC composition by principal component analysis (PCA) showed distinct differences between surface soils and deeper soil and peat samples. This was attributed to vertical transport, degradation and/or shifting sources over time. The calculated net vertical transport differed between surface layers (0.3%) and deeper soils (8.0%), suggesting that vertical transport conditions and processes differ in the deeper layers compared to the surface layers.

The mass transfer rates and equilibrium partitioning behaviour of 14 diverse organochlorine pesticides (OCP) between water and polyethylene (PE) passive samplers, cut from custom made PE sheets and commercial polyethylene plastic bags, were quantified. Overall mass transfer coefficients, kO, estimated PE membrane diffusion coefficients, DPE, and PE-water partitioning coefficients, KPE-water, are reported. In addition, the partitioning of three polycyclic aromatic hydrocarbons (PAHs) from water to PE is quantified and compared with literature values. KPE-water values agreed mostly within a factor of two for both passive samplers and also with literature values for the reference PAHs. As PE is expected to exhibit similar sorption behaviour to long-chain alkanes, PE-water partitioning coefficients were compared to hexadecane-water partitioning coefficients estimated with the SPARC online calculator, COSMOtherm and a polyparameter linear free energy relationship based on the Abraham approach. The best correlation for all compounds tested was with COSMOtherm estimated hexadecane-water partitioning coefficients.

Element load, conventional biomarkers and altered protein expression profiles were studied in Carcinus maenas crabs, to assess contamination of “Domingo Rubio” stream, an aquatic ecosystem that receives pyritic metals, industrial contaminants, and pesticides. Lower antioxidative activities – glucose-6-phosphate and 6-phosphogluconate dehydrogenases, catalase – were found in parallel to higher levels of damaged biomolecules – malondialdehyde, oxidized glutathione –, due to oxidative lesions promoted by contaminants, as the increased levels of essential – Zn, Cu, Co – and nonessential – Cr, Ni, Cd – elements. Utility of Proteomics to assess environmental quality was confirmed, especially after considering the six proteins identified by de novo sequencing through capLC-μESI-ITMS/MS and homology search on databases. They include tripartite motif-containing protein 11 and ATF7 transcription factor (upregulated), plus CBR-NHR-218 nuclear hormone receptor, two components of the ABC transporters and aldehyde dehydrogenase (downregulated). These proteins could be used as novel potential biomarkers of the deleterious effects of pollutants present in the area.

The aim of this work was to investigate if engineered endophytes can improve phytoremediation of co-contaminations by organic pollutants and toxic metals. As a model system, yellow lupine was inoculated with the endophyte Burkholderia cepacia VM1468 possessing (a) the pTOM-Bu61 plasmid, coding for constitutive trichloroethylene (TCE) degradation, and (b) the ncc-nre Ni resistance/sequestration system. Plants were exposed to Ni and TCE and (a) Ni and TCE phytotoxicity, (b) TCE degradation and evapotranspiration, and (c) Ni concentrations in the roots and shoots were determined. Inoculation with B. cepacia VM1468 resulted in decreased Ni and TCE phytotoxicity, as measured by 30% increased root biomass and up to 50% decreased activities of enzymes involved in anti-oxidative defence in the roots. In addition, TCE evapotranspiration showed a decreasing trend and a 5 times higher Ni uptake was observed after inoculation.

During the winters of 2006/2007 and 2007/2008, PM2.5 source apportionment programs were carried out within five western Montana valley communities. Filter samples were analyzed for mass and chemical composition. Information was utilized in a Chemical Mass Balance (CMB) computer model to apportion the sources of PM2.5. Results showed that wood smoke (likely residential woodstoves) was the major source of PM2.5 in each of the communities, contributing from 56% to 77% of the measured wintertime PM2.5. Results of 14C analyses showed that between 44% and 76% of the measured PM2.5 came from a new carbon (wood smoke) source, confirming the results of the CMB modeling. In summary, the CMB model results, coupled with the 14C results, support that wood smoke is the major contributor to the overall PM2.5 mass in these rural, northern Rocky Mountain airsheds throughout the winter months. This manuscript describes how woodsmoke is the largest source of PM2.5 in the Northern Rocky Mountains of the US.