Evaluation of a novel high throughput screening tool for relative emissions of industrial chemicals used in chemical products

Tens of thousands of chemicals are currently marketed worldwide, but only a small number of these compounds has been measured in effluents or the environment to date. The need for screening methodologies to select candidates for environmental monitoring is therefore significant. To meet this need, the Swedish Chemicals Agency developed the Exposure Index (EI), a model for ranking emissions to a number of environmental matrices based on chemical quantity used and use pattern. Here we evaluate the EI. Data on measured concentrations of organic chemicals in sewage treatment plants, one of the recipients considered in the EI model, were compiled from the literature, and the correlation between predicted emission levels and observed concentrations was assessed by linear regression analysis. The adequacy of the parameters employed in the EI was further explored by calibration of the model to measured concentrations. The EI was found to be of limited use for ranking contaminant levels in STPs; the r² values for the regressions between predicted and observed values ranged from 0.02 (p = 0.243) to 0.14 (p = 0.007) depending on the dataset. The calibrated version of the model produced only slightly better predictions although it was fitted to the experimental data. However, the model is a valuable first step in developing a high throughput screening tool for organic contaminants, and there is potential for improving the EI algorithm.     

How well is farmers’ social situation captured by sustainability assessment tools? A Swedish case study

Recent research indicates that sustainability assessment tools (SAT) for farms need to be contextually adapted to be acceptable and useful. Focusing specifically on social sustainability, this study sought to identify important aspects of relevance for Swedish (livestock) farmers’ social situation and compare these aspects with social indicators used in three existing SATs (RISE, SAFA, IDEA). A survey revealed that social issues of key importance for the self-reported overall life satisfaction of Swedish livestock farmers are: having a good financial situation, having a similar standard of living as others, not experiencing too much stress, having meaningful work, having decent working hours, and having a desirable family situation. Of the three SATs evaluated, RISE appears best equipped to capture the social situation of Swedish farmers but does not fully address the aspect of finding work meaningful. SAFA and IDEA both fail to capture many aspects of importance for describing the social situation of Swedish farmers. We present a novel method for testing the relevance of social indicators for farmers in a specific context. Applying this method before choosing, applying, and adapting SATs for farm-level sustainability assessments would increase the relevance of the social sustainability dimension, but deeper stakeholder engagement than offered by our survey is needed.