Recovery of infauna macrobenthic invertebrates in oil-polluted tropical soft-bottom tidal flats: 7 years post spill.

Coastal oil spills constitute significant threat to biotic energy distribution, and biodiversity integrity amongst others. This study monitored the recovery of low-intertidal, soft-bottom infauna macrobenthic invertebrates in Bodo Creek intermittently over a 7-year period post oil spill. Samples were taken twice a month (spring and neap low tides) for 6 months (September 2015-February 2016) at sites previously studied (pre-spill baseline studies, 3-year and 5-year post-spill studies) for the effects of oil pollution using the same sampling methods used during initial studies of the same area.

Prediction of bioavailability and toxicity of complex chemical mixtures through machine learning models.

Empirical data from a 6-month mesocosms experiment were used to assess the ability and performance of two machine learning (ML) models, including artificial neural network (NN) and random forest (RF), to predict temporal bioavailability changes of complex chemical mixtures in contaminated soils amended with compost or biochar. From the predicted bioavailability data, toxicity response for relevant ecological receptors was then forecasted to establish environmental risk implications and determine acceptable end-point remediation. The dataset corresponds to replicate samples collected over 180 days and analysed for total and bioavailable petroleum hydrocarbons and heavy metals/metalloids content.

Linking bioavailability and toxicity changes of complex chemicals mixture to support decision making for remediation endpoint of contaminated soils.

A six-month laboratory scale study was carried out to investigate the effect of biochar and compost amendments on complex chemical mixtures of tar, heavy metals and metalloids in two genuine contaminated soils. An integrated approach, where organic and inorganic contaminants bioavailability and distribution changes, along with a range of microbiological indicators and ecotoxicological bioassays, was used to provide multiple lines of evidence to support the risk characterisation and assess the remediation end-point. Both compost and biochar amendment (p = 0.

Insights into mixed contaminants interactions and its implication for heavy metals and metalloids mobility, bioavailability and risk assessment.

Mobility of heavy metals at contaminated sites is mainly influenced by the soil physicochemical properties and environmental conditions, therefore assessing heavy metals (HMs) and metalloids fractionation can provide insights into their potential risk and the mechanisms that regulate bioavailability. A 12-months mesocosms experiment was setup to investigate the effect of physicochemical factors (pH, moisture, and temperature) and weathering (time) on HMs and metalloids fractionation in three different multi-contaminated soil matrices (low, medium, and high contamination) collected from a soil treatment facility located in the United Kingdom, and two rural contaminated soil samples. The study demonstrates that even though Pb and Zn were found associated with the exchangeable fraction in the soil with the highest contamination (total average Pb 3400 mg/kg, and total average Zn 2100 mg/kg in Soil C), neither the condition applied nor the weathering caused an increase in their mobility.

Assessing bioavailability of complex chemical mixtures in contaminated soils: Progress made and research needs.

Understanding the distribution, behaviour and interactions of complex chemical mixtures is key for providing the evidence necessary to make informed decisions and implement robust remediation strategies. Much of the current risk assessment frameworks applied to manage land contamination are based on total contaminant concentrations and the exposure assessments embedded within them do not explicitly address the partitioning and bioavailability of chemical mixtures. These oversights may contribute to an overestimation of both the eco-toxicological effects of the fractions and the mobility of contaminants.