Mitigating glyphosate levels in surface waters: Long-term assessment in an agricultural catchment in Belgium.

The increasing concern over pesticide pollution in water bodies underscores the need for effective mitigation strategies to support the transition towards sustainable agriculture. This study assesses the effectiveness of landscape mitigation strategies, specifically vegetative buffer strips, in reducing glyphosate loads at the catchment scale under realistic conditions. Conducted over six years (2014-2019) in a small agricultural region in Belgium, our research involved the analysis of 732 water samples from two monitoring stations, differentiated by baseflow and event-driven sampling, and before (baseline) and after the implementation of mitigation measures. The results indicated a decline in both the number and intensity of point source losses over the years. Additionally, there was a general decrease in load intensity; however, the confluence of varying weather conditions (notably dry years during the mitigation period) and management practices (the introduction of buffer strips) posed challenges for a statistically robust evaluation of each contributing factor. A reduction of loads was measured when comparing mitigation with baseline, although this reduction is not statistically significant. Glyphosate loads during rainfall events correlated with a rainfall index and runoff ratio. Overall, focusing the mitigation strategy on runoff and erosion was a valid approach. Nevertheless, challenges remain, as evidenced by the continuous presence of glyphosate in baseflow conditions, highlighting the complex dynamics of pesticide transport. The study concludes that while progress has been made towards reducing pesticide pollution, the complexity of interacting factors necessitates further research. Future directions should focus on enhancing farmer engagement in mitigation programs and developing experiments with more intense data collection that help to assess underlying dynamics of pesticide pollution and the impact of mitigation strategies in more detail, contributing towards the goal of reducing pesticide pollution in water bodies.

Geostatistical analysis of active human cysticercosis: Results of a large-scale study in 60 villages in Burkina Faso.

Cysticercosis is a neglected tropical disease caused by the larval stage of the zoonotic tapeworm (Taenia solium). While there is a clear spatial component in the occurrence of the parasite, no geostatistical analysis of active human cysticercosis has been conducted yet, nor has such an analysis been conducted for Sub-Saharan Africa, albeit relevant for guiding prevention and control strategies. The goal of this study was to conduct a geostatistical analysis of active human cysticercosis, using data from the baseline cross-sectional component of a large-scale study in 60 villages in Burkina Faso. The outcome was the prevalence of active human cysticercosis (hCC), determined using the B158/B60 Ag-ELISA, while various environmental variables linked with the transmission and spread of the disease were explored as potential explanatory variables for the spatial distribution of T. solium. A generalized linear geostatistical model (GLGM) was run, and prediction maps were generated. Analyses were conducted using data generated at two levels: individual participant data and grouped village data. The best model was selected using a backward variable selection procedure and models were compared using likelihood ratio testing. The best individual-level GLGM included precipitation (increasing values were associated with an increased odds of positive test result), distance to the nearest river (decreased odds) and night land temperature (decreased odds) as predictors for active hCC, whereas the village-level GLGM only retained precipitation and distance to the nearest river. The range of spatial correlation was estimated at 45.0 [95%CI: 34.3; 57.8] meters and 28.2 [95%CI: 14.0; 56.2] km for the individual- and village-level datasets, respectively. Individual- and village-level GLGM unravelled large areas with active hCC predicted prevalence estimates of at least 4% in the south-east, the extreme south, and north-west of the study area, while patches of prevalence estimates below 2% were seen in the north and west. More research designed to analyse the spatial characteristics of hCC is needed with sampling strategies ensuring appropriate characterisation of spatial variability, and incorporating the uncertainty linked to the measurement of outcome and environmental variables in the geostatistical analysis. Trial registration: ClinicalTrials.gov; NCT0309339.

A multi-proxy magnetic approach for monitoring large-scale airborne pollution impact.

The interpretive utility of environmental magnetic proxies for investigating airborne particulate matter (PM) pollution impact is restricted by differences in soil composition, land cover and land use. For soil magnetic applications, land use strongly influences magnetic particle distribution down the soil profile, even in homogeneous soil environments. Here, an adaptive approach is engineered to provide accurate magnetic proxy information for pollution monitoring across different land use types. In an 81-km2 area between two industrial harbours, the irregular distribution of forests, arable lands, pasture and residential areas prevented robustly relating topsoil magnetic susceptibility data to known pollution impacts. Although normalized topsoil susceptibility values showed improved potential for deriving airborne pollution impacts, optimal results were obtained by depth-integrating magnetic susceptibility logs, revealing long-term impacts of both active and decommissioned industrial facilities. Complementing soil magnetic observations, active and passive (bio)magnetic monitoring allowed discriminating short-term pollution patterns and evaluating changes in PM impact across the study area. Hereby, active PM receptors (strawberry leaves and plastic coated cardboards (PCCs)) provided promising results, yet passive receptors allowed estimating pollution impacts more efficiently. For the latter, species-independent grass leaf sampling reflected airborne PM depositional patterns most accurately, whereas wiped anthropogenic surfaces proved too sensitive to wash-off.

Mapping of Agricultural Subsurface Drainage Systems Using a Frequency-Domain Ground Penetrating Radar and Evaluating Its Performance Using a Single-Frequency Multi-Receiver Electromagnetic Induction Instrument.

Subsurface drainage systems are commonly used to remove surplus water from the soil profile of a poorly drained farmland. Traditional methods for drainage mapping involve the use of tile probes and trenching equipment that are time-consuming, labor-intensive, and invasive, thereby entailing an inherent risk of damaging the drainpipes. Effective and efficient methods are needed in order to map the buried drain lines: (1) to comprehend the processes of leaching and offsite release of nutrients and pesticides and (2) for the installation of a new set of drain lines between the old ones to enhance the soil water removal. Non-invasive geophysical soil sensors provide a potential alternative solution. Previous research has mainly showcased the use of time-domain ground penetrating radar, with variable success, depending on local soil and hydrological conditions and the central frequency of the specific equipment used. The objectives of this study were: (1) to test the use of a stepped-frequency continuous wave three-dimensional ground penetrating radar (3D-GPR) with a wide antenna array for subsurface drainage mapping and (2) to evaluate its performance with the use of a single-frequency multi-receiver electromagnetic induction (EMI) sensor in-combination. This sensor combination was evaluated on twelve different study sites with various soil types with textures ranging from sand to clay till. While the 3D-GPR showed a high success rate in finding the drainpipes at five sites (sandy, sandy loam, loamy sand, and organic topsoils), the results at the other seven sites were less successful due to the limited penetration depth of the 3D-GPR signal. The results suggest that the electrical conductivity estimates produced by the inversion of apparent electrical conductivity data measured by the EMI sensor could be a useful proxy for explaining the success achieved by the 3D-GPR in finding the drain lines.

Evaluating the potential of topsoil magnetic pollution mapping across different land use classes.

Soil magnetic measurements are used increasingly to estimate the impact of airborne, combustion-related particulate matter (PM) pollution in dense measurement grids. Although many studies have proven the potential of topsoil magnetic measurements in environmental monitoring, their application is not straightforward when factors such as parent material or land use have to be accounted for. Often, the influence of land use on the soil magnetic signal is circumvented by targeting forest soils, where deposited magnetic particles are best preserved in the topsoil. However, when large forests are absent, e.g. in densely populated areas or environments with more heterogeneous land use, this approach often impedes reliable and comprehensive spatial sampling. We evaluated if topsoil magnetic pollution mapping across different land use classes, against a homogeneous geological environment of sandy soils, could help increase the spatial reliability of results in regional scale surveys. Although detailed magnetic property analysis and evaluation of trace metal concentrations in soils on arable land, forest and pasture showed the impact of atmospheric pollution, topsoil susceptibility measurements did not allow delineating the magnetic footprint of PM pollution. Land use strongly influenced the distribution of magnetic particles through soil, and the evaluation of anomalous magnetic topsoil enhancement required the integration of downhole susceptibility soundings. We conclude that topsoil susceptibility mapping remains a useful tool to evaluate PM pollution impact, yet its application potential across land use classes is limited.

Urban soil exploration through multi-receiver electromagnetic induction and stepped-frequency ground penetrating radar.

In environmental assessments, the characterization of urban soils relies heavily on invasive investigation, which is often insufficient to capture their full spatial heterogeneity. Non-invasive geophysical techniques enable rapid collection of high-resolution data and provide a cost-effective alternative to investigate soil in a spatially comprehensive way. This paper presents the results of combining multi-receiver electromagnetic induction and stepped-frequency ground penetrating radar to characterize a former garage site contaminated with petroleum hydrocarbons. The sensor combination showed the ability to identify and accurately locate building remains and a high-density soil layer, thus demonstrating the high potential to investigate anthropogenic disturbances of physical nature. In addition, a correspondence was found between an area of lower electrical conductivity and elevated concentrations of petroleum hydrocarbons, suggesting the potential to detect specific chemical disturbances. We conclude that the sensor combination provides valuable information for preliminary assessment of urban soils.