Abteilung Umweltchemie

Background: Pesticide use is increasing in low- and middle-income countries (LMICs) including Costa Rica. This increase poses health risks to farm owners, farm workers, and communities living near agricultural farms.

Objective: We aimed to examine the health effects associated with occupational pesticide exposure in farm owners and workers from conventional and organic smallholder farms in Costa Rica.

Methods: We conducted a cross-sectional study involving 300 owners and workers from organic and conventional horticultural smallholder farms in Zarcero County, Costa Rica. During the baseline study visit, we administered a structured, tablet-based questionnaire to collect data on sociodemographic characteristics, pesticide exposure, and health conditions (eg, respiratory and allergic outcomes and acute pesticide intoxication symptoms) and administered a neurobehavioral test battery (eg, Finger Tapping Test and Purdue Pegboard); we measured blood pressure, anthropometry (height, weight, and waist circumference), and erythrocytic acetylcholinesterase activity and also collected urine samples. In addition, a functional neuroimaging assessment using near-infrared spectroscopy was conducted with a subset of 50 study participants. During the follow-up study visit (~2-4 weeks after the baseline), we administered participants a short questionnaire on recent pesticide exposure and farming practices and collected hair, toenail, and urine samples. Urine samples will be analyzed for various pesticide metabolites, whereas toenails and hair will be analyzed for manganese (Mn), a biomarker of exposure to Mn-containing fungicides. Self-reported pesticide exposure data will be used to develop exposure intensity scores using an exposure algorithm. Furthermore, exposure-outcome associations will be examined using linear and logistic mixed-effects regression models.

Results: Fieldwork for our study was conducted between May 2016 and August 2016. In total, 113 farm owners and 187 workers from 9 organic and 83 conventional horticultural smallholder farms were enrolled. Data analyses are ongoing and expected to be published between 2019 and 2020.

Conclusions: This study is one of the first to examine differences in health effects due to pesticide exposure between farm owners and workers from organic and conventional smallholder farms in an LMIC. We expect that this study will provide critical data on farming practices, exposure pathways, and how occupational exposure to pesticides may affect farm owners and workers’ health. Finally, we hope that this study will allow us to identify strategies to reduce pesticide exposure in farm owners and workers and will potentially lay the groundwork for a future longitudinal study of health outcomes in farm owners and workers exposed to pesticides.

Cette synthèse de deux projets 62a illustre à l’aide d’exemples les effets des mesures de réduction des risques liés aux produits phytosanitaires (PPh) sur les données du monitoring. Au vu des multiples facteurs d’influence externes aux projets, ce lien entre les mesures prises par les agriculteurs et les données chimiques, biologiques et écotoxicologiques est parfois difficile à caractériser. Néanmoins, l’analyse des données de ces deux projets pilotes en Suisse permet de tirer de nombreuses leçons pour les projets en cours ou futurs, ainsi que pour le plan d’action PPh.

Water pollution is ubiquitous globally, yet how the effects of pollutants propagate through natural ecosystems remains poorly understood. This is because the interactive effects of multiple stressors are generally hard to predict. Agriculture and municipal wastewater treatment plants (WWTPs) are often major sources of contaminants for streams, but their relative importance and the role of different pollutants (e.g. nutrients or pesticides) are largely unknown. Using a 'real world experiment' with sampling locations up- and downstream of WWTPs, we studied how effluent discharges affected water quality and macroinvertebrate communities in 23 Swiss streams across a broad land-use gradient.
Variation partitioning of community composition revealed that overall water quality explained approximately 30% of community variability, whereby nutrients and pesticides each independently explained 10% and 2%, respectively. Excluding oligochaetes (which were highly abundant downstream of the WWTPs) from the analyses, resulted in a relatively stronger influence (3%) of pesticides on the macroinvertebrate community composition, whereas nutrients had no influence. Generally, the macroinvertebrate community composition downstream of the WWTPs strongly reflected the upstream conditions, likely due to a combination of efficient treatment processes, environmental filtering and organismal dispersal. Wastewater impacts were most prominently by the Saprobic index, whereas the SPEAR index (a trait-based macroinvertebrate metrics reflecting sensitivity to pesticides) revealed a strong impact of arable cropping but only a weak impact of wastewater.
Overall, our results indicate that agriculture can have a stronger impact on headwater stream macroinvertebrate communities than discharges from WWTP. Yet, effects of wastewater-born micropollutants were clearly quantifiable among all other influence factors. Improving our ability to further quantify the impacts of micropollutants requires highly-resolved water quality and taxonomic data with adequate spatial and temporal sampling. These improvements would help to better account for the underlying causal pathways that drive observed biological responses, such as episodic contaminant peaks and dispersal-related processes.

Cyanobacterial bloom events that produce natural toxins occur in freshwaters across the globe, yet the potential risk of many cyanobacterial metabolites remains mostly unknown. Only microcystins, one class of cyanopeptides, have been studied intensively and the wealth of evidence regarding exposure concentrations and toxicity led to their inclusion in risk management frameworks for water quality. However, cyanobacteria produce an incredible diversity of hundreds of cyanopeptides beyond the class of microcystins. The question arises, whether the other cyanopeptides are in fact of no human and ecological concern or whether these compounds merely received (too) little attention thus far. Current observations suggest that an assessment of their (eco)toxicological risk is indeed relevant: First, other cyanopeptides, including cyanopeptolins and anabaenopeptins, can occur just as frequently and at similar nanomolar concentrations as microcystins in surface waters. Second, cyanopeptolins, anabaenopeptins, aeruginosins and microginins inhibit proteases in the nanomolar range, in contrast to protein phosphatase inhibition by microcystins. Cyanopeptolins, aeruginosins, and aerucyclamide also show toxicity against grazers in the micromolar range comparable to microcystins. The key challenge for a comprehensive risk assessment of cyanopeptides remains their large structural diversity, lack of reference standards, and high analytical requirements for identification and quantification. One way forward would be a prevalence study to identify the priority candidates of tentatively abundant, persistent, and toxic cyanopeptides to make comprehensive risk assessments more manageable.