RESUMEN
Regulatory authorities need ways to estimate natural terrestrial gamma radiation dose rates (nGy h⻹) across the landscape accurately, to assess its potential deleterious health effects. The primary method for estimating outdoor dose rate is to use an in situ detector supported 1 m above the ground, but such measurements are costly and cannot capture the landscape-scale variation in dose rates which are associated with changes in soil and parent material mineralogy. We investigate the potential for improving estimates of terrestrial gamma dose rates across Northern Ireland (13,542 km²) using measurements from 168 sites and two sources of ancillary data: (i) a map based on a simplified classification of soil parent material, and (ii) dose estimates from a national-scale, airborne radiometric survey. We used the linear mixed modelling framework in which the two ancillary variables were included in separate models as fixed effects, plus a correlation structure which captures the spatially correlated variance component. We used a cross-validation procedure to determine the magnitude of the prediction errors for the different models. We removed a random subset of 10 terrestrial measurements and formed the model from the remainder (n = 158), and then used the model to predict values at the other 10 sites. We repeated this procedure 50 times. The measurements of terrestrial dose vary between 1 and 103 (nGy h⻹). The median absolute model prediction errors (nGy h⻹) for the three models declined in the following order: no ancillary data (10.8) > simple geological classification (8.3) > airborne radiometric dose (5.4) as a single fixed effect. Estimates of airborne radiometric gamma dose rate can significantly improve the spatial prediction of terrestrial dose rate.
Asunto(s)
Contaminantes Radiactivos del Aire/análisis , Rayos gamma , Dosis de Radiación , Monitoreo de Radiación/métodos , Atmósfera/química , Modelos Químicos , Irlanda del Norte , Contaminantes Radiactivos del Suelo/análisisRESUMEN
We investigated the use of metals accumulated on tree bark for mapping their deposition across metropolitan Sheffield by sampling 642 trees of three common species. Mean concentrations of metals were generally an order of magnitude greater than in samples from a remote uncontaminated site. We found trivially small differences among tree species with respect to metal concentrations on bark, and in subsequent statistical analyses did not discriminate between them. We mapped the concentrations of As, Cd and Ni by lognormal universal kriging using parameters estimated by residual maximum likelihood (REML). The concentrations of Ni and Cd were greatest close to a large steel works, their probable source, and declined markedly within 500 m of it and from there more gradually over several kilometres. Arsenic was much more evenly distributed, probably as a result of locally mined coal burned in domestic fires for many years. Tree bark seems to integrate airborne pollution over time, and our findings show that sampling and analysing it are cost-effective means of mapping and identifying sources.
Asunto(s)
Contaminantes Atmosféricos/análisis , Interpretación Estadística de Datos , Monitoreo del Ambiente/métodos , Industrias , Metales Pesados/análisis , Corteza de la Planta/química , Acero , Arsénico/análisis , Cadmio/análisis , Ciudades , Inglaterra , Monitoreo del Ambiente/instrumentación , Níquel/análisisRESUMEN
Tree barks and attic dusts were examined as historical archives of smelter emissions, with the aim of elucidating the pathways of pollution associated with a plume of Sn and Pb contamination in top soils, found close to the former Capper Pass smelter, Humberside, UK. Samples were collected from three villages within the area of the contamination plume. Scanning electron microscopy (SEM) and bulk chemical analyses were used to assess particle type, number and deposition patterns. SEM analysis of dusts and bark revealed that Sn and Pb particles were present in samples from all three villages along with copper, zinc and iron particles. These were almost entirely <10 microm in diameter and occurred mostly as oxides, frequently forming clusters of sub-micron crystals. Samples further from the smelter contained considerably fewer particles. We present images of smelter derived Sn particles. Chemical assays of the barks and attic dusts demonstrated that concentrations of Sn, Pb, Cu, As, Sb and Cd diminished with increasing distance from the source. Strong positive correlations were found between Sn and Pb, As, Sb and Cd in the attic dusts. Enrichment factors (EF) were calculated for these trace elements based on topsoil element concentrations obtained from the soil survey of the study area. Decreases in these trace element concentrations and EF values with distance away from the smelter are consistent with trends found in the soil survey for Sn and Pb and are typical of deposition patterns around smelter stacks. The study demonstrates that tree bark and attic dusts can be effective archives of metal particulates deposited from large static emission sources.
Asunto(s)
Contaminación del Aire Interior/análisis , Polvo/análisis , Metales Pesados/análisis , Corteza de la Planta/química , Contaminantes del Suelo/análisis , Monitoreo del Ambiente/métodos , Humanos , Industrias , Plomo/análisis , Microscopía Electrónica de Rastreo/métodos , Tamaño de la Partícula , Corteza de la Planta/ultraestructura , Estaño/análisis , Oligoelementos/análisis , Reino UnidoRESUMEN
When a smelter has ceased operation, and in the absence of historical emission data, high-resolution geochemical surveys of the soil can reveal historical loads to the surrounding land. We use measurements of lead and tin in the soil at two depths to estimate the total quantities of these metals deposited on 286 km(2) of land around the former Capper Pass smelter (north-east England). We subtracted median background concentrations for three parent material types outside the region of deposition from the data within it. We then constructed a statistical model of metal deposition based on the adjusted data. The data were from irregularly spaced sites and were strongly skewed with a spatial trend. We mapped the concentrations of the metals by lognormal universal kriging with the parameters for the trend and residuals modelled simultaneously by residual maximum likelihood (REML). The maps suggest that metal was deposited up to 24 km to the north-east of the smelter by the prevailing wind. We estimated total excess metal in the soil over the area of deposition to be 2500 t of lead and 830 t of tin.