Predicting persistence in the sediment compartment with a new automatic software based on the k-Nearest Neighbor (k-NN) algorithm.

The ability of a substance to resist degradation and persist in the environment needs to be readily identified in order to protect the environment and human health. Many regulations require the assessment of persistence for substances commonly manufactured and marketed. Besides laboratory-based testing methods, in silico tools may be used to obtain a computational prediction of persistence. We present a new program to develop k-Nearest Neighbor (k-NN) models. The k-NN algorithm is a similarity-based approach that predicts the property of a substance in relation to the experimental data for its most similar compounds. We employed this software to identify persistence in the sediment compartment. Data on half-life (HL) in sediment were obtained from different sources and, after careful data pruning the final dataset, containing 297 organic compounds, was divided into four experimental classes. We developed several models giving satisfactory performances, considering that both the training and test set accuracy ranged between 0.90 and 0.96. We finally selected one model which will be made available in the near future in the freely available software platform VEGA. This model offers a valuable in silico tool that may be really useful for fast and inexpensive screening.

Chemical characterization and ecotoxicity of three soil foaming agents used in mechanized tunneling.

The construction of tunnels and rocks with mechanized drills produces several tons of rocky debris that are today recycled as construction material or as soil replacement for covering rocky areas. The lack of accurate information about the environmental impact of these excavated rocks and foaming agents added during the excavation process has aroused increasing concern for ecosystems and human health. The present study proposes an integrated approach to the assessment of the potential environmental impact of three foaming agents containing different anionic surfactants and other polymers currently on the market and used in tunnel boring machines. The strategy includes chemical characterization with high resolution mass spectrometry techniques to identify the components of each product, the use of in silico tools to perform a similarity comparison among these compounds and some pollutants already listed in regulatory frameworks to identify possible threshold concentrations of contamination, and the application of a battery of ecotoxicological assays to investigate the impact of each foaming mixture on model organisms of soil (higher plants and Eisenia andrei) and water communities (Daphnia magna). The study identified eleven compounds not listed on the material safety data sheets for which we have identified possible concentrations of contamination based on existing regulatory references. The bioassays allowed us to determine the no effect concentrations (NOAECs) of the three mixtures, which were subsequently used as threshold concentration for the product in its entirety. The technical mixtures used in this study have a different degree of toxicity and the predicted environmental concentrations based on the conditions of use are lower than the NOAEC for soils but higher than the NOAEC for water, posing a potential risk to the waters due to the levels of foaming agents in the muck.

Acute phytotoxicity of seven metals alone and in mixture: Are Italian soil threshold concentrations suitable for plant protection?

Metals can pollute soils in both urban and rural areas with severe impacts on the health of humans, plants and animals living there. Information on metal toxicity is therefore important for ecotoxicology. This study investigated the phytotoxicity of different metals frequently found as pollutants in soils: arsenic, cadmium, chromium, lead, mercury, nickel and zinc. Cucumber (Cucumis sativus), sorghum (Sorghum saccharatum) and cress (Lepidium sativum) seeds were used as models for other plants used in human nutrition such as cereals, rice, fruits and vegetables. The 72-h germination rate and root elongations were selected as short-term ecotoxicological endpoints in seeds exposed to single metals and mixtures. Metals were spiked onto OECD standard soils in concentrations comparable to current Italian contamination threshold concentrations for residential and commercial soils. Arsenic, chromium, mercury and nickel were the most toxic metals in our experimental conditions, particularly to cress seeds (5.172, 152 and 255.4 mg/kg as 72 h IC50 for arsenic, mercury and nickel respectively). Italian limits were acceptable for plant protection only for exposure to each metal alone but not for the mixtures containing all the metals concentrations expected by their respective legislative threshold. The effects of the mixture were class-specific: trends were comparable in dicots but different in monocots. The response induced by the mixture at high concentrations differed from that theoretically obtainable by summing the effects of the individual metals. This might be due to partial antagonism of the metals in soil or to the formation of complexes between the metals, which reduce the bioavailability of the pollutants for plants.