Protecting food with poison : Exploring ecotoxicity of agrochemicals and pharmaceuticals

Abstract: Chemicals are being emitted into the environment through human activities, such as agriculture or animal husbandry. Emissions can either occur intentionally, as pesticide application of crops, or inadvertently, such as pharmaceutical residues in wastewater effluents. Chicken manure (CM) is occasionally used as a cheap fertilizer in aquaculture pond farms to increase the productivity and the profitability. Depending on local regulation and production strategy, animal manures can contain substantial amounts of antibiotics (AB) and other pharmaceuticals used for raising animals. The benefits of this practice, however, have not been clearly established in relation to the potential adverse consequences. By analysing production data from Egyptian fish farms in Study I, I show that CM fertilization promotes eutrophication, without corresponding to increased fish yields or clear benefits for the producers. Study I support arguments to cease CM fertilization in Egyptian aquaculture if the goal is to increase fish yields or profitability. Additionally, I employ a qPCR assay to show that CM fertilization correlates with increased abundance of antibiotic resistance genes (ARGs) in pond sediment. AB emitted to the environment can induce resistance development in bacteria and promote selection of resistant genotypes. Study II aim to capture the effects of AB emitted throughout the value chain of agri-food products, and life cycle assessment (LCA) is investigated for this purpose. LCA is a framework developed to assess environmental impacts throughout the value chain of products. In Study II, I present an approach to quantify potential AB resistance enrichment in the environment within LCA. I also discuss a mass-balance approach to capture the relationship between regional AB use and regional human health impacts, in order to capture the full range of potential impacts caused by emissions of AB. Characterizations of potential toxic effects of chemicals in LCA are generally drawn from species sensitivity distribution models that aim to describe an ecosystem-wide response to chemical emission. While this provides insights into the toxicity of a chemical, predictions of the “true” ecosystem wide effects will always be shrouded by uncertainty, depending on the availability and quality of data. Detailed knowledge on adverse effects and potential hazard chemicals impose are required for stakeholders at both global and local scales to make informed decisions on how to regulate the use and emissions of chemicals. Study IV identify LCA studies where toxicological impacts are evaluated and chemicals in the inventory are classified towards ecotoxicological impact, but ecotoxicological characterizations are missing, which leads to underestimating the ecotoxicological impact. To enhance the precision of ecotoxicological effect assessments for chemicals, Study III gathers an extensive toxicological dataset and present a method to assess the uncertainty associated with ecotoxicological effect calculations. The proposed method opens up for exploring uncertainty in ecotoxicological effect calculations, but data availability is limiting the number of chemicals that can be assessed for ecotoxicological effect and uncertainty. To gap-fill information on toxic effect of chemicals, Study IV explores quantitative structure-activity relationship (QSAR) models to predict ecotoxicological effect of chemicals. However, mechanistic understanding of toxic mode of action is not provided by these models. Thus, the accuracy and validity of predicted toxicological effect data are not yet established. Since current LCA software lacks functionality to aggregate uncertainties throughout assessments, the use of predicted toxicological data is discouraged.This thesis presents some of the many challenges we face when assessing toxicological impacts from chemicals emitted to the environment, and provides methods and recommendations how to better evaluate impacts and uncertainties in toxicological characterization of chemicals.