| Popis: |
The European Union aim to have all soils healthy by 2050. However, a major challenge to soil health monitoring is identifying key metrics for soil health indicators. Moreover, how to analyse numerous soil properties which are time-consuming, labour intensive and expensive. MIR spectroscopy is a rapid, non-destructive cheaper alternative to wet chemical methods. Here, we combined known soil properties that limit transport of heavy metals (i.e. drainage class, depth, organic matter, particle size/texture, bulk density and cation-exchange-capacity) to develop a topsoil (≤50 cm) leaching potential model (n = 3,515). The study area consisted of mostly grassland soils which had mainly high and moderately low leaching potential (43 and 36 %, respectively), with lower coverage of high and intermediate classes (10 and 11 %, respectively). However, known topsoil prediction models of 5–25 cm (n = 4759) were extrapolated to deeper samples 30–50 cm. As a result, 26 % of samples were identified as ‘out of control’ in peatland transition areas. For full spatial coverage for environmental modelling from spectral data, reference values are needed for the deeper samples in peatland transition areas.Furthermore, this study used a geological survey of the northern half of Ireland at ≤4 km2 resolution to map regions of naturally high levels of As, Cd, Cr, Cu, Ni and Pb by ICP and XRF spectroscopy. Geospatial clipping of heavy metal thresholds showed high coverage of As and Ni in Eastern regions, and Cd in the Midland regions of Ireland. Therefore, it would be useful to include fertiliser loadings, transport pathways or any source/recipient data to assess heavy metal movement throughout the soil profile, particularly in these regions. |
