WP6: Risks and Mitigation

ASR11: Sophie Mentzel

ESR12: Sam Welch

ESR 13: Joanke van Dijk

ESR contributions


Assessing the combined toxicity, cumulative hazard, and cumulative risk of PPCP in wastewaters in the future

As the world’s population grows and ages, pharmaceutical consumption is forecast to grow, driving a likely increase in environmental risk due to the high potential of therapeutic agents to act on non-target wildlife as well as their human targets. Research into pharmaceuticals as pollutants has lagged behind work on more prominent contaminants such as pesticides and heavy metals, due in part to the difficulty of monitoring and predicting the concentrations of such a wide range of substances.

In Norway, where my PhD is based, the Norwegian Institute for Public Health records every sale of pharmaceuticals in the country. I plan to use this data to predict environmental concentrations in previous years, allowing for not only prediction of current risks using publicly available but also extrapolation of risk in the future. By developing a Bayesian network in conjunction with ESR 12’s work, I further hope to create a probabilistic prediction of risk under future climate change and population demographic scenarios, with the ultimate goal of developing a prioritisation list of high-right and soon to be high-risk pharmaceuticals on which risk mitigation efforts should be focused.

Forecasting future changes in chemical risks in urban and agricultural systems and assessing mitigation possibilities

Chemicals form a core part of our everyday lives as they provide vital services for our health, food security and industrial production. However, their use can also result in emissions to the environment. Over the last decades, the worldwide consumption of chemicals has increased both in volume and in diversity and these trends are expected to continue. As society develops, new chemicals will continue to be introduced into the environment. Together with increased water use and increased production and use of chemicals the chemical burden on the aquatic environment rise, highlighting the need for effective mitigation options to reduce chemical emissions to these environments.
We are interested in assessing multiple options across a chemicals life-cycle (i.e. from their design and regulation to their use and waste stage) that can prevent or reduce the emission of chemicals to the environment and close the gap towards a toxic-free environment.


6.1. Develop and apply a probabilistic models for risk assessment of agricultural chemicals under current and future GC scenarios.

6.2. Apply probabilistic models for assessment of pharmaceuticals and personal care products (PPCP) from waste water emissions under current and future GC scenarios.

6.3. Assess the effectiveness of different mitigation options to improve future waste water quality.

Description of Work and Role of Specific Beneficiaries / Partner Organisations

WP6 will assess the risk of emerging chemicals from agricultural and urban sources, separately and in mixtures, under current and future scenarios. Hazard/risk quotient derivation will be used for quantitative risk assessments based on results from WP4 (Exposure) and WP5 (Effects). A probabilistic modelling approach (Bayesian network – BN) will be applied to integrate the risk assessments with future global change scenarios (WP3), as well as with effects of mitigation measures. The BN approach will also be used to address uncertainty associated with emerging chemicals, throughout the causal chain from scenarios to biological effects. While the general modelling approach will be applicable for all results from ECORISK2050, specific models will be adapted risk assessment for geographic regions and specific chemical types (pesticides (ESR11; NIVA); urban chemicals (ESR12; NIVA)) and for assessment of mitigation measures and backcasting (ESR13; UU). Partner organisations will contribute to assessment of combined toxicity and cumulative hazard (NIBIO) and to evaluation of mitigation options (KWR).

Working Package Deliverables

6.1            Risk assessment model (Bayesian network) for agricultural chemicals developed for one of the case study regions

6.2            Prioritisation of pharmaceuticals and PHCP which pose highest risk

6.3            Robust implementation of mitigation strategies to close the gap to a non-toxic environment in 2050