Microscopic and chemical studies of metal particulates in tree bark and attic dust : evidence for historical atmospheric smelter emissions, Humberside, UK.

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 m 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

Characterising changes in fluorescence properties of dissolved organic matter and links to N cycling in agricultural floodplains

Sand and gravel aquifer systems are common features below and adjacent to river networks and are important in providing a hydrological link between terrestrial and aquatic ecosystems. They are often used for intensive agriculture and therefore provide a conduit for the transport of nutrients to aquatic systems. Understanding the biogeochemical cycles of C and N in such systems is essential in efforts to improve water quality, with a major link being the transfer and properties of DOM which drives microbial processing of nutrients. In this work undertaken in the Trent Valley, U.K., the differences in dissolved organic matter (DOM) properties in the soil, aquifer ground water and river water are examined using excitation–emission matrix fluorescence spectroscopy (EEM), in addition to chemical analysis. In the aquifer system studied the water table is ∼1.5 m below the land surface, suggesting that DOM and nutrient transfer would occur between the soil and groundwater. Nitrate levels in the ground water were ∼50 mg L−1 NO3-N. Soil DOM properties were measured in KCl extracts used to extract inorganic and organic N so that further information could be obtained regarding possible sources and properties of the DON and the biodegradability of the DOC pool. Within the soils tested, fulvic-like properties and the humification index (HI) were significantly (P < 0.05) higher in sandy soils suggesting that microbial accessibility to organic matter was greater. The applicability of assessing DOM characteristics in the different matrices were assessed and quantitative or qualitative comparisons made. Properties of DOM in both the soils and aquifer waters all showed a typical terrestrial source with principal component analysis (PCA) showing strong correlations between DOC, fulvic-like properties, the HI and tryptophan-like properties. A major finding was that the HI was generally higher in the groundwater, suggesting continued processing of DOM within the aquifer whilst qualitative comparisons showed the groundwater possessed a higher fluorescence index (FI). Whilst DON and the tyrosine-like proteins were correlated in the soil, the tryptophan-like proteins were strongly correlated to fulvic-like substances in both the soil and groundwater. This suggested that phenolic compounds were also being identified in this part of the EEM matrix, emphasising the need for additional compound analysis to fully understand the nature of DOM in these systems

Using 206/207Pb isotope ratios to estimate phosphorus sources in historical sediments of a lowland river system

Purpose Engineering and dredging strategies to manage sediment, along with river-scouring, can reveal older sediments. These present a unique opportunity to assess past sources of phosphorus (P) inputs into river sediments. We used the sediment concentrations of P, lead (Pb) and 206/207Pb isotopes to produce ‘first-order’ estimates of the source (diffuse agricultural or sewage treatment) of phosphorus. Materials and methods Sediment cores (n = 30) were collected from the length of the non-tidal River Nene, a lowland river in eastern England. Cores were analysed for sediment elemental concentrations and Pb isotopes. Principal component analysis and linear regression modelling were used to assess the relationships between P, Pb and Pb isotopes. Monte-Carlo simulations and boot-strapping were undertaken to estimate, with 95% confidence intervals, the source of P in these sediments. Results and discussion Analysis of the relationships between PTotal, PbTotal and 206/207Pb isotope ratios suggested that sediments were deposited largely prior to the phasing out of tetra-ethyl Pb (PbBHT) from petrol. Regression models showed positive correlations between PTotal and PbTotal (R2 = 0.85). Principal component analysis suggested a strong sewage treatment signal for Pb and P enrichment. In the rural upper three water bodies, little sewage treatment work (STW)-derived P was found in the sediment, a consequence of limited STW input and greater sediment transport. In the more urbanised water bodies 4–6, ‘first-order estimates’ of STW P suggest that median concentrations were 30–40% of PTotal. Conclusions The strong relationships between Pb and P concentrations in river water provided the opportunity to use 206/207Pb isotope ratios to calculate ‘first-order’ estimates of the proportion of P released from STWs in the historical sediment. Understanding the sources of historical sediment P can be used to assess the success of current sediment management strategies and to base further mitigation measures. Results suggest that whilst much recent sediment P is removed, the legacy sediment remains to contribute P to the water body. Thus, options regarding the practical removal of these sediments and the extent to which this would improve water P status need to be assessed and balanced against options such as further decreasing soil P or STW P stripping

Implications of short-range spatial variation of soil bulk density for adequate field-sampling protocols: methodology and results from two contrasting soils

Soil bulk density (BD) is measured during soil monitoring. Because it is spatially variable, an appropriate sampling protocol is required. This paper shows how information on short-range variability can be used to quantify uncertainty of estimates of mean BD and soil organic carbon on a volumetric basis (SOCv) at a sampling site with different sampling intensities. We report results from two contrasting study areas, with mineral soil and with peat. More sites should be investigated to develop robust protocols for national-scale monitoring, but these results illustrate the methodology. A 20 × 20-m2 monitoring site was considered and sampling protocols were evaluated under geostatistical models of our two study areas. At sites with local soil variability comparable to our mineral soil, sampling at 16 points (4 × 4 square grid of interval 5 m) would achieve a root mean square error (RMSE) of the sample mean value of both BD and SOCv of less than 5% of the mean (topsoil and subsoil). Pedotransfer functions (PTFs) gave predictions of mean soil BD at a sample site, comparable to our study area on mineral soil, with similar precision to a single direct measurement of BD. On peat soils comparable to our second study area, the mean BD for the monitoring site at depth 0–50 cm would be estimated with RMSE to be less than 5% of the mean with a sample of 16 cores, but at greater depths this criterion cannot be achieved with 25 cores or fewer

How the composition of sandstone matrices affects rates of soil formation

Soils deliver multiple ecosystem services and their long-term sustainability is fundamentally controlled by the rates at which they form and erode. Our knowledge and understanding of soil formation is not commensurate with that of soil erosion, in part due to the difficulty of measuring the former. However, developments in cosmogenic radionuclide accumulation models have enabled soil scientists to more accurately constrain the rates at which soils form from bedrock. To date, all three major rock types – igneous, sedimentary and metamorphic lithologies – have been examined in such work. Soil formation rates have been measured and compared between these rock types, but the impact of rock characteristics on soil formation rates, such as rock matrices and mineralogy, have seldom been explored. In this UK-based study, we used cosmogenic radionuclide analysis to investigate whether the lithological variability of sandstone governs pedogenesis. Soil formation rates were measured on two arable hillslopes at Woburn and Hilton, which are underlain by different types of arenite sandstone. Rates were faster at Woburn, and we suggest that this is due to the fact that the Woburn sandstone formation is less cemented that that at Hilton. Similarly, rates at Woburn and Hilton were found to be faster than those measured at two other sandstone-based sites in the UK, and faster than those compiled in a global inventory of cosmogenic studies on sandstone-based soils. We suggest that the cementing agents present in matrix-abundant wackes studied previously may afford these sandstones greater structural integrity and resistance to weathering. This work points to the importance of factoring bedrock matrices into our understanding of soil formation rates, and the biogeochemical cycles these underpi

Predicting trace metal solubility and fractionation in urban soils from isotopic exchangeability

Metal-salt amended soils (MA, n = 23), and historically-contaminated urban soils from two English cities (Urban, n = 50), were investigated to assess the effects of soil properties and contaminant source on metal lability and solubility. A stable isotope dilution method, with and without a resin purification step, was used to measure the lability of Cd, Cu, Ni, Pb and Zn. For all five metals in MA soils, lability (%E-values) could be reasonably well predicted from soil pH value with a simple logistic equation. However, there was evidence of continuing time-dependent fixation of Cd and Zn in the MA soils, following more than a decade of storage under air-dried conditions, mainly in high pH soils. All five metals in MA soils remained much more labile than in Urban soils, strongly indicating an effect of contaminant source on metal lability in the latter. Metal solubility was predicted for both sets of soil by the geochemical speciation model WHAM-VII, using E-values as an input variable. For soils with low metal solution concentrations, over-estimation of Cd, Ni and Zn solubility was associated with binding to the Fe oxide fraction while accurate prediction of Cu solubility was dependent on humic acid content. Lead solubility was most poorly described, especially in the Urban soils. Generally, slightly poorer estimation of metal solubility was observed in Urban soils, possibly due to a greater incidence of high pH values. The use of isotopically exchangeable metal to predict solubility is appropriate both for historically contaminated soils and where amendment with soluble forms of metal is used, as in toxicological trials. However, the major limitation to predicting solubility may lie with the accuracy of model input variables such as humic acid and Fe oxide contents where there is often a reliance on relatively crude analytical estimations of these variables

Scope to predict soil properties at within-field scale from small samples using proximally sensed γ-ray spectrometer and EM induction data

Spatial predictions of soil properties are needed for various purposes. However, the costs associated with soil sampling and laboratory analysis are substantial. One way to improve efficiencies is to combine measurement of soil properties with collection of cheaper-to-measure ancillary data. There are two possible approaches. The first is the formation of classes from ancillary data. A second is the use of a simple predictive linear model of the target soil property on the ancillary variables. Here, results are presented and compared where proximally sensed gamma-ray (γ-ray) spectrometry and electromagnetic induction (EMI) data are used to predict the variation in topsoil properties (e.g. clay content and pH). In the first instance, the proximal data is numerically clustered using a fuzzy k-means (FKM) clustering algorithm, to identify contiguous classes. The resultant digital soil maps (i.e. k = 2–10 classes) are consistent with a soil series map generated using traditional soil profile description, classification and mapping methods at a highly variable site near the township of Shelford, Nottinghamshire UK. In terms of prediction, the calculated expected value of mean squared prediction error (i.e. σ2p,C) indicated that values of k = 7 and 8 were ideal for predicting clay and pH. Secondly, a linear mixed model (LMM) is fitted in which the proximal data are fixed effects but the residuals are treated as a combination of a spatially correlated random effect and an independent and identically distributed error. In terms of prediction, the expected value of the mean squared prediction error from a regression (σ2p,R) suggested that the regression models were able to predict clay content, better than FKM clustering. The reverse was true with respect to pH, however. We conclude that both methods have merit. In the case of the clustering the approach is able to account for soil properties which have non-linearity's with the ancillary data (i.e. pH), whereas the LMM approach is best when there is a strong linear relationship (i.e. clay)

Environment and Rural Affairs Monitoring & Modelling Programme - ERAMMP Report-57: Image Resolution Testing for Soil Erosion and Damage Features

Maintaining healthy soils in Wales is important in order to ensure the sustainable management of natural resources under the environment act. Monitoring of soils in Wales is conducted in order to assess the state and change of soils and forms part of the state of natural resources reporting cycle (SoNaRR), quantify the impact of Glastir on soil health and contribute to a range of other reporting requirements. Soil monitoring by ERAMMP is primarily based on structured sampling of topsoil but has also used aerial photography for peat condition and modelling. This report details work that examines the potential use of remote sensing for assessing the extent of soil erosion and damage (SED), and landsliding from space. The objective was to test different remote sensing imagery data sources, e.g. sentinel (~10m) and planet data (~3m) against high resolution APGB aerial imagery (~0.25m, by Bluesky International Limited), to determine if the resolution of the imagery is acceptable to replace aerial photographs for identifying features. The report summarises two tests of the data, one on the extent of soil erosion and damage and the other on coastal erosion and landslides