On the application of loss functions for determining hazardous concentrations

The Hazardous Concentration to x% of an assemblage (HCx) of biological species is the environmental concentration which for a randomly selected species from the assemblage yields an x% probability of violating the species’ toxicological endpoint. Probabilistic methods for estimating the HCx appeal to the probabilistic concept of Species Sensitivity Distributions (SSDs) – a statistical proxy description of interspecies variation within the assemblage. A commonly used estimator class, derived by Aldenberg and Jaworska (2000; Ecotoxicol Environ Saf 46: 1-18), appealed to classical sampling theory, but also coincided with a Bayesian estimator. Two popular estimators from the class are the 50% and 95% (one-sided) underestimate of the HCx. However, whilst choice of x can have ecological significance, choice of confidence remains arbitrary. We reduce the problem to a Bayesian decision theoretic one; and show that their estimator class is equivalent to Bayes Rules under a class of (a-) symmetric linear loss functions, parameterised by the relative cost of over-estimation to under-estimation. A loss function in this sense measures the ‘cost’, which needn’t be monetary, of over- and under-estimation of the HCx estimator. Bayes rules are estimators which minimise expected loss with respect to the posterior SSD – updated with respect to the toxicity data. This potentially opens the way for high-stakes realism to be incorporated into risk assessments. We propose an alternative loss function known as Scaled LINear Exponential (LINEX) which is non-linearly asymmetric in a precautionary way, such that overestimation and underestimation are punished at an exponential and linear rate respectively. We use this loss function to derive an alternative class of HCx estimators

Training Course on Steering an Expert Knowledge Elicitation : Final Report

EFSA’s scientific expertise and capacity consists of the members of the Scientific Panels, the Scientific Committee, their Working Groups, and the Authority’s own scientific staff as well as the scientists in Member State institutions working with EFSA. The overall objective of this project was to organize and deliver high quality training courses to meet the needs identified by EFSA to implement Expert Knowledge Elicitation (EKE) approach for quantifying uncertainty in food safety risk assessment. As outcome of the project a training course was developed on ‘Steering an Expert KnowledgeElicitation’. The course covered two working days and was conducted three times during the year 2015. The three courses had 73 participants in total, whereof 17 EFSA experts, 50 EFSA Staff and 6 Network members. This report contains a summary of the project, a technical description of the training, the final curriculum, the training materials, results from evaluation of the course by the participants, and recommendations for future training on this subject

A Kinetic Model of Furfural Hydrogenation to 2-Methylfuran on Nanoparticles of Nickel Supported on Sulfuric Acid-Modified Biochar Catalyst

Lignocellulosic biomass can uptake CO2 during growth, which can then be pyrolysed into three major products, such as biochar (BC), syngas, and bio-oil. Due to presence of oxygenated organic compounds, the produced bio-oil is not suitable for direct use as a fuel and requires up-grading via hydrodeoxygenation (HDO) and hydrogenation. This is typically carried out over a supported metal catalyst. Regarding circular economy and sustainability, the BC from the pyrolysis step can potentially be activated and used as a novel catalyst support, as reported here. A 15wt% Ni/BC catalyst was developed by chemically modifying BC with sulfuric acid to improve mesoporous structure and surface area. When compared to the pristine Ni/BC catalyst, sulfuric activated Ni/BC catalyst has excellent mesopores and a high surface area, which increases the dispersion of Ni nanoparticles and hence improves the adsorptive effect and thus catalytic performance. A liquid phase hydrogenation of furfural to 2-methylfuran was performed over the developed 15wt% Ni/BC catalyst. Langmuir–Hinshelwood-Hougen-Watson (LHHW) kinetic type models for adsorption of dissociative H2 were screened based on an R2 value greater than 99% demonstrating that the experimental data satisfactorily fit to three plausible models: competitive (Model I), competitive at only one type of adsorption site (Model II), and non-competitive with two type of adsorption sites (Model III). With a correlation coefficient greater than 99% between the experimental rates and the predicted rate, model III, which is a dual-site adsorption mechanism involving furfural adsorption and hydrogen dissociative adsorption and surface reaction, is the best fit. The Ni/BC catalyst demonstrated comparative performance and significant cost savings over previous catalysts, a value of 24.39 kJ mol-1 was estimated for the activation energy, -11.43 kJmol-1 for the enthalpy of adsorption for H2, and -5.86 kJmol-1 for furfural. The developed Ni/BC catalyst demonstrated excellent stability in terms of conversion of furfural (96%) and yield of 2-methylfuran (54%) at the fourth successive experiments. Based on furfural conversion and yield of products, it appears that pores are constructed slowly during sulfuric acid activation of the biochar

A robust Bayesian analysis of the impact of policy decisions on crop rotations.

We analyse the impact of a policy decision on crop rotations, using the imprecise land use model that was developed by the authors in earlier work. A specific challenge in crop rotation models is that farmer’s crop choices are driven by both policy changes and external non-stationary factors, such as rainfall, temperature and agricultural input and output prices. Such dynamics can be modelled by a non-stationary stochastic process, where crop transition probabilities are multinomial logistic functions of such external factors. We use a robust Bayesian approach to estimate the parameters of our model, and validate it by comparing the model response with a non-parametric estimate, as well as by cross validation. Finally, we use the resulting predictions to solve a hypothetical yet realistic policy problem

Species non-exchangeability in probabilistic ecotoxicological risk assessment

Current ecotoxicological risk assessment for chemical substances is based on the assumption that tolerances of all species in a specified ecological community are a priori exchangeable for each new substance. We demonstrate non-exchangeability by using a large database of tolerances to pesticides for fish species and extend the standard statistical model for species tolerances to allow for the presence of a single species which is considered non-exchangeable with others. We show how to estimate parameters and adjust decision rules that are used in ecotoxicological risk management. Effects of parameter uncertainty are explored and our model is compared with a previously published less tractable alternative. We conclude that the model and decision rules that we propose are pragmatic compromises between conflicting needs for more realistic modelling and for straightforwardly applicable decision rules

Species non-exchangeability for ecotoxicological risk assessment [poster spotlight]

In aquatic based chemical risk assessments, there is a wealth of statistical techniques for use in lower tier risk assessment. In particular, we focus on estimation of the hazardous concentration to x% of an ecological community (HCx); a concept based on the idea of Species Sensitivity Distribution (SSD). The SSD is typically assumed to act as a proxy distribution to model the inter-species variation in the biological assemblage. Over time, a number of criticisms have been made of the SSD concept, but we focus on one in particular – species non-exchangeability. The concept was first discussed within a semi-probabilistic setting by an opinion of the European Food Safety Authority (EFSA) Scientific Panel on Plant Production products and their Residues (EFSA Journal, 2005). We build on their findings to demonstrate, statistically, that the Rainbow trout (Oncorhynchus mykiss) is not exchangeable with other species. By this term, we mean that, a priori, before observing the toxicity value of the species, we do not believe it to be a realisation from the same distribution as the other species in the assemblage. In fact, the Rainbow trout is typically more sensitive than the average fish species across a wide range of substances. In addition, we briefly demonstrate how to exploit historical databases of toxicity data featuring the Rainbow trout to quantify this non-exchangeability in order to derive new estimators for the HCx

Feedstock blending as a strategy for hydrothermal liquefaction: lipid-rich scum from primary sedimentation and wastewater sludge

One salient advantage of hydrothermal liquefaction (HTL) is the ability to process diverse feedstocks individually or as blends. This creates an opportunity for using wet organic waste feedstocks that in many cases pose a disposal liability. The low cost associated with the feedstock enables cost-effective deployment of smaller, decentralized processing plants that match the geographic availability of wet waste resources. Two underutilized sources of wet waste biomass are wastewater sludge and fats, oils, and greases (FOG). In the United States, these each represent about 20% of the total HTL biocrude production potential from wet wastes. In this study, the selected FOG stream is decanted scum from the primary sedimentation operation of the same wastewater treatment plant (WWTP) that provided the sludge. Among the types of FOG, wastewater scum is one of the more complex and challenging. Scum contains entrained water, plant matter like leaves and seeds, and bits of garbage (paper and plastic). For most other processes to access the lipids in scum, some combination of heating, filtering, and solvent extraction would be required, leading to costly and/or inefficient recovery. HTL is preferable because it is a wet process and the scum can be blended directly to capture the whole energy content in the blended feed. Using a blend of primary and secondary sludge from Central Contra Costa Sanitary District (CCCSD) and decanted scum from CCCSD primary sedimentation as the source of FOG, a blend of sludge and scum was successfully prepared and processed in a bench scale continuous flow HTL system. A total of 54 L of blended slurry was converted to 4.2 L of biocrude oil. The scum was blended with the sludge such that it represented 20 wt% of the total dry, ash-free (daf) solids in the feed. The resulting biocrude had a much lower density (0.95 g/cm3) than the biocrude from CCCSD sludge alone (0.99 g/cm3) leading to improved gravity separation from the aqueous phase. The biocrude was also lower in moisture. During the oral presentation, the focus will be on the process of feedstock selection, evaluation, and characteristics including detailed steps and equipment used to format the blended feedstock for use in the HTL reactor system. The poster will include data for the integrated process including mass balance, yields, and characterization of products