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Hydrocarbon degradation (HD) potential by autochthonous microorganisms in the coastal sediments of the NW area of Portugal (coastal sandy beaches and estuaries of the rivers Minho and Douro) was evaluated, investigating if water and sediment contamination/characteristics influence it. Sediments were characterized for microbial abundance (by DAPI), HD microorganisms' abundance (by MPN), microbial community structure (by ARISA), hydrocarbons (by FTIR and SPME-GC-MS), hazardous and noxious substances (SPME-GC-MS) and metals (by AAS). To our knowledge, this is the first time all these pollutants, including the selected HNS, were measured simultaneously in sediments of the selected coastal area. Higher contaminants concentrations were, generally, registered in Douro samples. A clear differentiation of the microbial community structure between beaches and estuaries was observed, as well as, between Douro and Minho river estuaries. BIO-ENV analysis indicated both sediment characteristics (e.g. OM content) and contaminants presence/concentrations (e.g. tetrachloroethylene presence) affected the structure of the microbial community along the studied areas. In all the selected sites, the characterized autochthonous microbial communities showed potential for hydrocarbons degradation, with HD microorganisms being found in all collected sediments. These microorganisms can be a valuable asset to recover contaminated areas, but sediment characteristics and contaminants presence/levels need to be taken into account as they can affect their bioremediation potential and the success of their application as biotechnological tool. © 2018 Elsevier This research was partially supported by the Strategic Funding UID/Multi/04423/2013 through national funds provided by FCT – Foundation for Science and Technology and European Regional Development Fund (ERDF), in the framework of the programme PT2020, by the structured Program of R&D&I INNOVMAR - Innovation and Sustainability in the Management and Exploitation of Marine Resources, reference NORTE-01-0145-FEDER-000035 , namely within the Research Line ECOSERVICES (Assessing the environmental quality, vulnerability and risks for the sustainable management of the NW coast natural resources and ecosystem services in a changing world) within the R&D Institution CIIMAR (Interdisciplinary Centre of Marine and Environmental Research), supported by the Northern Regional Operational Programme ( NORTE2020 ), through the European Regional Development Fund (ERDF) and by the research project SpilLess - First line response to oil spills based on native microorganisms cooperation ( EASME/EMFF/2016/1.2.1.4/010 ) supported by the Executive Agency for Small and Medium-sized Enterprises (EASME) delegated by the European Commission. Appendix A

Quantitative structure-activity relationship (QSAR) models are expected to play a crucial role in reducing the number of animals to be used for toxicity testing resulting from the adoption of the new European Union chemical control system called Registration, Evaluation, and Authorization of Chemicals (REACH). The objective of the present study was to generate in vitro acute toxicity data that could be used to develop a QSAR model to describe acute in vivo toxicity of chlorinated alkanes. Cytotoxicity of a series of chlorinated alkanes to Chinese hamster ovary (CHO) cells was observed at concentrations similar to those that have been shown previously to be toxic to fish. Strong correlations exist between the acute in vitro toxicity of the chlorinated alkanes and (i) hydrophobicity [modeled by the calculated log Kow (octanol-water partition coefficient); r2 = 0.883 and rint2 = 0.854] and (ii) in vivo acute toxicity to fish (r2 = 0.758). A QSAR model has been developed to predict in vivo acute toxicity to fish, based on the in vitro data and even on in silico log Kow data only. The developed QSAR model is applicable to chlorinated alkanes with up to 10 carbon atoms, up to eight chlorine atoms, and log Kow values lying within the range from 1.71 to 5.70. Out of the 100204 compounds on the European Inventory of Existing Chemicals (EINECS), our QSAR model covers 77 (0.1%) of them. Our findings demonstrate that in vitro experiments and even in silico calculations can replace animal experiments in the prediction of the acute toxicity of chlorinated alkanes. © 2008 American Chemical Society.