Mobility and persistence of pesticides and emerging contaminants in age-dated and redox-classified groundwater under a range of land use types

Understanding groundwater contamination patterns is hampered by the heterogeneous groundwater age and redox status over the depth range typically sampled for identifying pesticides and emerging contaminants threats. This study explores depth patterns of groundwater age and redox status across various land use types, unraveling spatial and temporal trends of pesticides and emerging contaminants using data from groundwater quality monitoring in the south of the Netherlands. The Netherlands is an ideal testing ground due to its high population density and widespread groundwater contamination from multiple sources. 146 multi-level observation wells were age-dated using ³H/³He, and contaminant concentrations were analyzed based on recharge year, land use type, and redox conditions, mitigating uncertainties from spatial and depth-dependent variations in both groundwater age and redox status. Redox-recharge year diagrams were developed to visually evaluate contaminant patterns in relation to these factors and to assess concentration patterns in relation to contamination history. Most detections of pesticides, metabolites, and emerging contaminants occurred in the youngest recharge periods (2000-2010 and 2010-2020) and in agricultural areas. However, certain contaminants, including BAM, desphenyl-chloridazon, short-chain PFCAs, PFOA, and EDTA, were consistently found in older water and Fe- or SO₄-reduced conditions, indicating their mobility and persistence in the regional groundwater system. Comparing the presence of contaminants in specific redox classes and recharge periods with known application or leaching history provides insights into retardation (e.g., PFOS) and degradation (e.g., 2-hydroxy-atrazine, benzotriazole), explaining lower detection frequencies in earlier recharge periods. Identifying recharge years from age-dated groundwater helps relate contaminants to farmland application or river water recharge periods, revealing leaching history and contamination origins. The presented framework has the potential to enhance the interpretation of large groundwater datasets from dedicated, short-screened observation wells, such as those from the Danish GRUMO network, the Dutch monitoring networks, and parts of the US National Water Quality Program.