Predicting Environmental Risks from Pharmaceuticals under Future Scenarios: A Norwegian Example
Abstract
Pharmaceuticals are an important part of human pollution. Their use has been linked to several well-known wildlife crises, such as a population collapse of vultures in India and Pakistan, or the feminisation of fish populations in European rivers. However, the majority of environmental impacts are unknown and unquantified. We developed methods for predicting the environment concentrations of pharmaceuticals in Norwegian waters from sales records. We then used these predictions to assess which pharmaceuticals pose the greatest risk to the Norwegian environment. Finally, we developed a set of Bayesian networks – graphical, probabilistic models – to forecast the probability of different magnitudes of pharmaceutical risk to the environment. By varying the starting scenario, we were able to forecast how the risk of a panel of pharmaceuticals might change under different plausible futures. Our work yields a useful foundation for the probabilistic environmental risk assessment of pharmaceuticals. When paired with environmental measurement and other risk assessment approaches, it will contribute to a better understanding of how pharmaceuticals affect the environment. This will allow for more targeted and efficient risk management.List of papers
Paper I. Welch SA, Olsen K, Nouri Sharikabad M et al. Pharmaceutical pollution: Prediction of environmental concentrations from national wholesales data [version 2; peer review: 2 approved, 1 approved with reservations] Open Research Europe 2022, 2:71. doi: 10.12688/openreseurope.14129.2. The article is included in the thesis. Also available at: https://doi.org/10.12688/openreseurope.14129.2 |
Paper II: Predicting Environmental Risks of Pharmaceuticals from Wholesales Data: An Example from Norway. Welch, S.A., Moe, S.J., Nouri Sharikabad, M., Tollefsen, K.E., Olsen, K., Grung, M., 2022b. Predicting Environmental Risks of Pharmaceuticals from Wholesales Data: An Example from Norway. Environ. Toxicol. Chem. First published: 21 June 2023. doi: 10.1002/etc.5702. The article is included in the thesis. Also available at: https://doi.org/10.1002/etc.5702 |
Paper III: Bayesian Networks for the Assessment of Future Pharmaceutical Environmental Risk. Welch, S.A., Grung, M., Madsen, A.L., Moe, S.J., 2023. Probabilistic risk calculation for chemical mixtures: environmental risk of pharmaceuticals under future scenarios. OSF Preprints. The paper is not available in DUO awaiting publishing. Available at OFS preprints archive: https://doi.org/10.31219/osf.io/zbgp7 |