Development of USEtox characterisation factors for dishwasher detergents using data made available under REACH.

Because of the more and more stringent regulations and customer demand, dishwasher detergent manufacturers are constantly improving the composition of the products towards better environmental performances. In order to quantify the pros and cons of these changes on the lifecycle of detergents, as compared to conventional products, the use of Life Cycle Assessment (LCA) is a meaningful opportunity. However, the application of the methodology is hampered by the lack of Characterisation Factors (CFs) relative to the specific chemical substances included in the detergents composition, which cannot be included in the impact assessment of the effluent discharge. In this study we have tackled this problem, taking advantage of the specific case of three dishwasher detergents produced by the Chemolux/McBride group: phosphate-based, eco-labelled and phosphate-free formulations. Nine CFs for freshwater ecotoxicity and seven CFs for human toxicity have been developed, using the USEtox methodology and data made available under the REACH regulation. As a result, the dishwasher effluent composition could be characterised by more than 95% for freshwater ecotoxicity whereas for human toxicity the percentage was less than 36%, due to the lack of adequate and reliable repeated dose toxicity studies. The main contributing substances to freshwater ecotoxicity were found to be sodium percarbonate and sodium triphosphate, the latter confirming the pertinence of phosphates banning in the detergent industry. Regarding human toxicity, zinc shows the highest contribution. Further comparison to previous studies and sensitivity analysis substantiated the robustness of these conclusions.

Is it better to remove pharmaceuticals in decentralized or conventional wastewater treatment plants? A life cycle assessment comparison.

After ingestion, pharmaceuticals are excreted unchanged or metabolized. They subsequently arrive in conventional wastewater treatment plants and are then released into the environment, often without undergoing any degradation. Conventional treatment plants can be upgraded with post treatment, alternatively the removal of pharmaceuticals could be achieved directly at point sources. In the European project PILLS, several solutions for decentralized treatment of pharmaceuticals at hospitals were investigated at both pilot plant and full scale, and were then compared to conventional and upgraded centralized treatment plants using Life Cycle Assessment (LCA). Within the scope of the study, pharmaceuticals were found to have a comparatively minor environmental impact. As a consequence, an additional post treatment does not provide significant benefits. In the comparison of post treatment technologies, ozonation and activated carbon performed better than UV. These results suffer however from high uncertainties due to the assessment models of the toxicity of pharmaceuticals in LCA. Our results should therefore be interpreted with caution. LCA is a holistic approach and does not cover effects or issues on a local level, which may be highly relevant. We should therefore apply the precautionary ALARA principle (As Low As Reasonably Achievable) and not conclude that the effect of pharmaceuticals is negligible in the environment.

Uncertainty analysis of penicillin V production using Monte Carlo simulation.

Uncertainty and variability affect economic and environmental performance in the production of biotechnology and pharmaceutical products. However, commercial process simulation software typically provides analysis that assumes deterministic rather than stochastic process parameters and thus is not capable of dealing with the complexities created by variance that arise in the decision-making process. Using the production of penicillin V as a case study, this article shows how uncertainty can be quantified and evaluated. The first step is construction of a process model, as well as analysis of its cost structure and environmental impact. The second step is identification of uncertain variables and determination of their probability distributions based on available process and literature data. Finally, Monte Carlo simulations are run to see how these uncertainties propagate through the model and affect key economic and environmental outcomes. Thus, the overall variation of these objective functions are quantified, the technical, supply chain, and market parameters that contribute most to the existing variance are identified and the differences between economic and ecological evaluation are analyzed. In our case study analysis, we show that final penicillin and biomass concentrations in the fermenter have the highest contribution to variance for both unit production cost and environmental impact. The penicillin selling price dominates return on investment variance as well as the variance for other revenue-dependent parameters.