A pilot study to assess soil spectroscopic methods for mapping key topsoil properties in the Blackwater sub-catchments (Wensum DTC)

This report describes findings from sampling and analyses of soils across the Blackwater drain catchments, part of the Wensum demonstration test catchment (DTC) project funded by Defra. Recent studies have shown how spectroscopic techniques can be used to estimate soil properties and airborne spectroscopy could be an effective means to aid continuous mapping of soil properties across the landscape. Before an airborne survey is undertaken it is important to assess whether the relationships between infra red (IR) spectra and soil properties are sufficiently strong for the cost of the airborne survey to be justified. A secondary objective was to determine the concentrations of soil organic carbon (SOC) in soils across the cultivated parts of the catchment to determine whether there is any evidence that low SOC concentrations might indicate that the topsoil may exhibit poor structural stability contributing to enhanced sediment in stream and drainage channels

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

Optimal mapping of terrestrial gamma dose rates using geological parent material and aerogeophysical survey data

Regulatory authorities need ways to estimate natural terrestrial gamma radiation dose rates (nGy h−1) 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 (13542 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−1). The median absolute model prediction errors (nGy h−1) 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

Technologies for increasing carbon storage in soil to mitigate climate change

Means to enhance storage of carbon in soil or avoid its loss from soil are discussed and examined from the viewpoint of policy. In particular, technologies that have until now received little attention are assessed. The main means by which soil carbon might be increased are first listed. These are the following: (i) increasing the rate of input of organic matter; (ii) decreasing the rate of its decomposition by biological or chemical means; (iii) increasing the rate of its stabilization by physico-chemical protection within aggregates and organo-mineral complexes; and (iv) increasing the depth or more correctly the total soil volume sequestering carbon at maximum rate. Immediate gains in carbon storage might be made by switching to more perennial crops, especially grasses that, as a result of breeding, are able to put more carbon into soil. In the longer term, targets for research such as understanding the role of enzymes in carbon turnover and the exploitation of the capacity in subsoils are suggested. Increased fixation of CO2 as inorganic carbonate in soils by application of silicate wastes may have some role

Understanding the controls on sediment-P interactions and dynamics along a non-tidal river system in a rural–urban catchment: the River Nene

The release of Phosphorus (P) from river sediments has been identified as a contributing factor to waters failing the criteria for ‘Good Ecological Status’ under the EU Water Framework Directive (WFD). To identify the contribution of sediment-P to river systems, an understanding of the factors that influence its distribution within the entire non-tidal system is required. Thus the aims of this work were to examine the (i) total (PTotal) and labile (PLabile) concentrations in sediment, (ii) the sequestration processes and (iii) the interactions between sediment P and the river water in the six non-tidal water bodies of the River Nene, U.K. Collection of sediments followed a long period of flooding and high stream flow. In each water body, five cores were extracted and homogenised for analysis with an additional core being taken and sampled by depth increments. Comparing the distribution of sediment particle size and PTotal data with soil catchment geochemical survey data, large increases in PTotal were identified in sediments from water body 4–6, where median concentrations of PTotal in the sediment (3603 mg kg−1) were up to double those of the catchment soils. A large proportion of this increase may be related to in-stream sorption of P, particularly from sewage treatment facilities where the catchment becomes more urbanised after water body 3. A linear correlation (r = 0.8) between soluble reactive phosphate (SRP) and Boron in the sampled river waters was found suggesting increased STW input in water bodies 4–6. PLabile concentrations in homogenised cores were up to 100 mg kg−1 PO4–P (generally < 2% of PTotal) and showed a general increase with distance from the headwaters. A general increase in Equilibrium Phosphate Concentrations (EPC0) from an average of 0.9–∼1.7 μm L−1 was found between water bodies 1–3 and 4–6. Fixation within oxalate extractable phases (Al, Fe and Mn) accounted for ∼90% of P binding in water bodies 4–6, but only between 31 and 74% in water bodies 1–3. Statistical models predicting PTotal (R2 = 0.78), oxalate extractable P (R2 = 0.78) and Olsen P (R2 = 0.73) concentrations in river sediments identified Mn oxy-hydroxides (MnOx) as a strong predictive variable along with the location within the river system. It is suggested that MnOx within model predictions is identifying a pool of mixed Fe–Mn oxy-hydroxides (MnOx–FeOOH) or Fe oxy-hydroxide (FeOOH) from the wider FeOxalate pool that are particularly effective at sorbing and fixing P. The findings demonstrate how sediment and P may accumulate along a 100 km non-tidal river system, the extent to which a range of processes can fix P within mineral phases and how natural flooding processes may flush sediment from the river channel. The processes identified in this study are likely to be applicable to similar river systems over their non-tidal water bodies in eastern England

A review of climate change impacts on urban soil functions with examples and policy insights from England, UK

As of 2010, more than half of the global population resides in urban areas and relies to some extent on the functions, services and natural capital provided by urban soils. Greater extremes in climate predicted for the coming decades will impact on these urban soil functions to varying degrees. We provide an inventory of urban soil functions based on an extension to the typology of the Millennium Ecosystem Assessment (i.e. we added a carrying function to those of supporting, regulating, provisioning and cultural) and review the climate drivers which are likely to have the most significant impacts upon them, using urban soils of England as an exemplar. We identify knowledge gaps, in areas such as carbon cycling and storage, disease regulation and cultural services. We assess adaptation measures which may ameliorate these potential, climate change-related impacts including changes in construction practices, developments in green architecture and development proposals under the planning regime. We discuss the lack of policies relating to urban soils and the problem associated with monitoring their functions, as is often the case, when large quantities of soil are removed and replaced leading to major transformation of soil properties which may be un-related to pedogenic processes

Are data collected to support farm management suitable for monitoring soil indicators at the national scale?

Monitoring of topsoil properties (referred to as indicators) at the national scale has been limited in general to government-funded representative surveys. We consider a cost-effective complementary source of soil information for monitoring agricultural soil across England and Wales (E&W): soil measurements paid for by farmers that we refer to as farmers' data (FD). A potential problem in using FD for soil monitoring is any unattributable sources of bias, such as the sample design. Farmers may choose to focus their measurements (purposively) where they perceive a particular problem. Such a source of bias is avoided in the random sampling adopted by statistically designed surveys, such as the Countryside Survey (CS2007) and LUCAS (Land Use/Cover Area frame statistical Survey). We used measurements from 143 000 FD soil samples from a single laboratory to estimate national mean values and confidence intervals of five topsoil indicators (pH, available P (Olsen), K, Mg and organic matter (OM)) across three combinations of nation (England or Wales) and land use (arable and horticulture (A&H) or improved grassland (IG)). We computed mean estimates for FD over two time periods (2004–9 and 2010–2105) and assessed the significance of any change. We compared these estimates with those from representative national surveys to establish whether there was evidence for bias and whether it could be explained. Mean estimates of topsoil pH for the FD and the LUCAS survey (same analytical method) were consistent for both A&H and IG. Although FD estimates of mean Olsen P (OP) concentrations were similar to previous surveys, we show it is likely that the larger mean OP concentrations observed in the LUCAS survey compared with FD for arable topsoil in England are partly due to an attributable source of analytical bias. For such quantifiable sources of bias, it might be possible to adjust estimated mean values from FD. However, FD might also include sources of unattributable bias, such as the effect of purposive sampling. It is important that contemporaneous data from surveys with statistically unbiased designs are available so that we can assess whether unattributable sources exert a significant effect over estimates of mean values computed from FD. Highlights Assessment of farmers' data (FD) to provide a potentially cost-effective way to monitor topsoil indicators. Few studies have compared national-scale estimates of topsoil indicators with survey data from statistically unbiased designs and FD. Bias between mean estimates from national surveys and FD could be accounted for. The denser sampling of FD enables mapping of national survey data with greater accuracy

GSUE: urban geochemical mapping in Great Britain

The British Geological Survey is responsible for the national strategic geochemical survey of Great Britain. As part of this programme, the Geochemical Surveys of Urban Environments (GSUE) project was initiated in 1992 and to date, 21 cities have been mapped. Urban sampling is based upon the collection of top (0.05 to 0.20 m) and deeper (0.35 to 0.50 m) soil samples on a 500 m grid across the built environment (1 sample per 0.25 km2). Samples are analysed for c. 46 total element concentrations by X-ray Fluorescence Spectrometry (XRFS), pH and loss on ignition (LOI) as an indicator of organic matter content. The data provide an overview of the urban geochemical signature and because they are collected as part of a national baseline programme, can be readily compared with soils in the rural hinterland to assess the extent of urban contamination. The data are of direct relevance to current UK land use planning, urban regeneration and contaminated land legislative regimes. An overview of the project and applications of the data to human health risk assessment, water quality protection and contaminant source identification are presented

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

Quantifying and mapping topsoil inorganic carbon concentrations and stocks: approaches tested in France

Soils act as a sink or a source of atmospheric carbon, and great efforts are made to monitor soil organic carbon stocks, but soil inorganic carbon (SIC) stocks are not measured by many national- and continental-scale soil monitoring networks. Topsoil (0–30 cm) SIC concentrations were determined for > 2000 sites on a regular 16-km grid as part of the French, Réseau de Mesures de la Qualité des Sols (RMQS). We used design-based statistical methods to calculate unbiased estimates of the mean SIC concentration and total stocks across France. Model-based methods were used to determine the uncertainty of these estimates and to map the spatial distribution of these quantities. Observations of inorganic carbon were highly skewed and did not conform to standard statistical models. Data were normalized using a nonparametric transformation. The estimates and predictions of inorganic carbon are baselines against which the results of future phases of the network can be compared. We found that the total topsoil inorganic carbon stocks in France amount to 1070 ± 61 Tg, ca. one-third of the corresponding organic carbon stocks. Spatial distribution of SIC was strongly linked to the underlying geology. We tested the reliability of estimating SIC concentrations and stocks from the French Soil Test Database, which contains the results of 280 000 soil analyses requested by farmers between 1990 and 2004. A biased estimate of soil inorganic carbon concentrations resulted, presumably because soil samples were selected according to concerns of farmers rather than by a statistical design