Search Results (3)

This paper represents a comparative study of two rivers, namely, the Andarax River, Spain, and the River Liffey, Ireland, considering different climatic conditions and human activities and their influences on most water quality parameters. Water samples collected from different sampling sites along each river were analysed for field parameters such as the pH, dissolved oxygen (DO), total dissolved solids (TDS), electrical conductivity (EC), and nitrates, phosphates, and potassium (NPK) levels of floodplain soil. Spatial changes were assessed using various geostatistical methods such as the Pearson correlation, multiple linear regression (MLR), and water quality index (WQI). The Andarax River had a higher TDS and was turbidly higher with EC due to agricultural activities and the naturally higher evaporation in the semiarid climate. In contrast, DO levels varied widely in the River Liffey, especially in reaches under the influence of urbanisation and agricultural runoff. The artificial surface and agriculture are the strongest negative determinants of water quality in both rivers, with artificial surfaces contributing about 35.72% to the DO variation. The WQI identified the water quality in the Andarax River as poor to very poor in certain locations, while the River Liffey exhibited a good to medium quality overall, although with localised degradation in areas of high human activity. The results of this study are important for developing targeted remedial measures in diversified climate conditions and a customised water sustainability plan to address the challenges of each area. Full article

This research evaluates water quality in two contrasting hydro-climatic regions: the River Liffey in Ireland and the Andarax River in Spain. It utilizes an Artificial Neural Network (ANN) to simulate potential changes in key water-quality parameters based on field measurements. The ANN models showed strong predictive efficiency and performance, achieving R² values of 0.89 for dissolved oxygen (DO), 0.98 for electrical conductivity (EC), 0.87 for pH, 0.95 for total dissolved solids (TDS), and 0.96 for turbidity. The root mean-square-error (RMSE) values for important parameters were DO (1.25 mg/L), EC (48.06 µS/cm), and turbidity (8.9 FNU). The models were able to capture complex nonlinear relationships under different environmental conditions. The results showed that DO levels in the Liffey will decline by up to 20% over the next decade due to rising nutrient pollution, while TDS levels in the Andarax River are expected to rise by approximately 15% during the same period as a result of ongoing agricultural runoff. The study also simulated potential future hypothetical scenarios by applying the model to four different “what-if” situations. Overall, the research underscores the significance of machine learning in understanding intricate water-quality dynamics. Full article

Endocrine-disrupting compounds (EDCs) constitute a wide variety of chemistries with diverse properties that may/can pose risks to both humans and the environment. Herein, a total of 26 compounds, including steroids, flame retardants, and plasticizers, were monitored in three major and heavily urbanized river catchments: the R. Liffey (Ireland), the R. Thames (UK), and the R. Ter (Spain), by using a single solid-phase extraction liquid chromatography-mass spectrometry (SPE-LC-MS/MS) method. Occurrence and frequency rates were investigated across all locations over a 10-week period, with the highest concentration obtained for the flame retardant tris(2-chloroethyl) phosphate (TCEP) at 4767 ng∙L⁻¹ in the R. Thames in Central London. Geographical variations were observed between sites and were partially explained using principal component analysis (PCA) and hierarchical cluster analysis (HCA). In particular, discrimination between the R. Ter and the R. Thames was observed based on the presence and concentration of flame retardants, benzotriazole, and steroids. Environmental risk assessment (ERA) across sites showed that caffeine, a chemical marker, and bisphenol A (BPA), a plasticizer, were classified as high-risk for the R. Liffey and R. Thames, based on relative risk quotients (rRQs), and that caffeine was classified as high-risk for the R. Ter, based on RQs. The total risks at each location, namely ΣRQ_river, and ΣrRQ_river, were: 361, 455, and 723 for the rivers Liffey, Thames, and Ter, respectively. Caffeine, as expected, was ubiquitous in all 3 urban areas, though with the highest RQ observed in the R. Ter. High contributions of BPA were also observed across the three matrices. Therefore, these two compounds should be prioritized independently of location. This study represents a comprehensive EDC monitoring comparison between different European cities based on a single analytical method, which allowed for a geographically independent ERA prioritization to be performed. Full article