Normal background concentrations (NBCs) of contaminants in English soils : final project report

The British Geological Survey (BGS) has been commissioned by the Department for Environment, Food and Rural Affairs (Defra) to give guidance on what are normal levels of contaminants in English soils in support of the Part 2A Contaminated Land Statutory Guidance. This has initially been done by studying the distribution of four contaminants – arsenic, lead, benzo[a]pyrene (BaP) and asbestos – in topsoils from England. This work was extended to a further four contaminants (cadmium, copper, nickel and mercury) which enabled methodologies developed to be tested on a larger range of contaminants. The first phase of the Project gathered data sets that were: nationally extensive; systematically collected so a broad range of land uses were represented; and collected and analysed to demonstrably and acceptable levels of quality. Information on the soil contaminant concentrations in urban areas was of particular importance as the normal background is considered to be a combination of both natural and diffuse anthropogenic contributions to the soil. Issues of soil quality are most important in areas where these affect most people, namely, the urban environment. The two principal data sets used in this work are the BGS Geochemical Baseline Survey of the Environment (G-BASE) rural and urban topsoils (37,269 samples) and the English NSI (National Soil Inventory) topsoils (4,864 samples) reanalysed at the BGS laboratories by X-ray fluorescence spectrometry (XRFS) so both data sets were highly compatible. These two data sets provide results for most inorganic element contaminants, though results explored for mercury and BaP are drawn from a variety of different and much less extensive data sets

Background concentrations of polycyclic aromatic hydrocarbons metabolites in Portuguese firemen

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental pollutants produced by the incomplete combustion of organic materials. PAHs may pose risks to human health as many of the individual compounds are cytotoxic and mutagenic to both lower and higher organisms, being some of them regarded as carcinogenic. Pyrene is by far the most characterized PAH in all sample matrices, and is classified as PAH marker of exposure while benzo(a)pyrene is considered the biomarker of carcinogenic exposure to PAHs. Among the 16 PAHs established by US EPA as priority pollutants, naphthalene, acenaphthene, fluorene, and phenanthrene are also found in almost all the matrices. Workers from industrial settings where airborne PAH levels are high such as coke works and the primary aluminium industry, show excess rates of cancers. Firemen are also exposed to high concentrations of PAHs during firefighting; however their biomonitoring is difficult and epidemiological studies are scarce. During the last decade, the urinary 1-hydroxypyrene has been used as a biomarker of environmental and occupational exposure to PAHs. Still no standard reference or occupational guidelines are available for any urinary PAH metabolite. Within the present work, sixty healthy and no smoking Portuguese firemen from ten Portuguese corporations from the district of Bragança (North of Portugal) were evaluated regarding their levels of the most important urinary hydroxyl- PAHs

Locating and quantifying gas emission sources using remotely obtained concentration data

We describe a method for detecting, locating and quantifying sources of gas emissions to the atmosphere using remotely obtained gas concentration data; the method is applicable to gases of environmental concern. We demonstrate its performance using methane data collected from aircraft. Atmospheric point concentration measurements are modelled as the sum of a spatially and temporally smooth atmospheric background concentration, augmented by concentrations due to local sources. We model source emission rates with a Gaussian mixture model and use a Markov random field to represent the atmospheric background concentration component of the measurements. A Gaussian plume atmospheric eddy dispersion model represents gas dispersion between sources and measurement locations. Initial point estimates of background concentrations and source emission rates are obtained using mixed L2-L1 optimisation over a discretised grid of potential source locations. Subsequent reversible jump Markov chain Monte Carlo inference provides estimated values and uncertainties for the number, emission rates and locations of sources unconstrained by a grid. Source area, atmospheric background concentrations and other model parameters are also estimated. We investigate the performance of the approach first using a synthetic problem, then apply the method to real data collected from an aircraft flying over: a 1600 km^2 area containing two landfills, then a 225 km^2 area containing a gas flare stack

Background Concentrations of Contaminants in the Ogallala Aquifer at Pantex: An Evaluation

This report evaluates the Department of Energy’s (DOE) Risk Reduction Rule Guidance to the Pantex Plant RFI. This evaluation was performed on behalf of Serious Texans Against Nuclear Dumping (STAND), a non-profit organization of concerned citizens. This research was completed money allocated during Round 3 of the Citizens’ Monitoring and Technical Assessment Fund (MTA Fund). Clark University was named conservator of these works. If you have any questions or concerns please contact us at [email protected]://commons.clarku.edu/stand/1001/thumbnail.jp

Geochemical indices allow estimation of heavy metal background concentration in soils

Defining background concentrations for heavy metals in soils is essential for recognizing and managing soil pollution. However, background concentrations of metals in soils can vary naturally by several orders of magnitude. Moreover, many soils have also been subject to unquantifiable anthropogenic inputs of metals, in some cases, for centuries. Hence determination of heavy metal background concentrations in soils has to date been fraught with difficulty. Here we demonstrate that there are associations between the background heavy metal and Fe or Mn contents in soils which appear to be consistent for seven important heavy metals of environmental concern. The relationships are remarkably independent of both soil type and climatic setting. These observations provide the basis for a series of general equations from which it is proposed Southeast Asian including Australian, and possibly worldwide background concentrations for As, Cr, Co, Cu, Ni, Pb, and Zn in soils can be derived.R. E. Hamon, M. J. McLaughlin, R. J. Gilkes, A. W. Rate, B. Zarcinas, A. Robertson, G. Cozens, N. Radford and L. Bettena

Quantifying the effects of background concentrations of crude oil pollution on sea ice albedo

Sea ice albedo plays an important role in modulating the climate of Earth and is affected by low background concentrations of oil droplets within the ice matrix that absorb solar radiation. In this study, the albedo response of three different types of bare sea ice (melting, first-year, and multi-year sea ice) are calculated at increasing mass ratios (0–1000 ng g−1) of crude oil by using a coupled atmosphere–sea ice radiative-transfer model (TUV-snow; Tropospheric Ultraviolet–Visible) over the optical wavelengths 400–700 nm. The different types of quasi-infinite-thickness sea ice exhibit different albedo responses to oil pollution, with a 1000 ng g−1 mass ratio of oil causing a decrease to 70.9 % in multi-year sea ice, 47.2 % in first-year sea ice, and 22.1 % in melting sea ice relative to the unpolluted albedo at a wavelength of 400 nm. The thickness of the sea ice is also an important factor, with realistic-thickness sea ices exhibiting similar results, albeit with a weaker albedo response for multi-year sea ice to 75.3 %, first-year sea ice to 66.3 %, and melting sea ice to 35.9 %. The type of oil also significantly affects the response of sea ice albedo, with a relatively opaque and heavy crude oil (Romashkino oil) causing a significantly larger decrease in sea ice albedo than a relatively transparent light crude oil (Petrobaltic oil). The size of the oil droplets polluting the oil also plays a minor role in the albedo response, with weathered submicrometre droplets (0.05–0.5 µm radius) of Romashkino oil being the most absorbing across the optical wavelengths considered. Therefore, the work presented here demonstrates that low background concentrations of small submicrometre- to micrometre-sized oil droplets have a significant effect on the albedo of bare sea ice. All three types of sea ice are sensitive to oil pollution; however, first-year sea ice and particularly melting sea ice are very sensitive to oil pollution.</p

Technical guidance on normal levels of contaminants in Welsh soil : Cadmium (Cd) : January 2013

Cadmium (Cd) is a metallic element naturally occurring in trace amounts at the Earth’s surface. It is toxic to humans, animals and plants, and known to be a human carcinogen. The metal associates with sulphide ores, mainly the mineral sphalerite (ZnS), and its cycling can be highly influenced by accumulation in plants and organic debris. Its abundance in igneous and sedimentary rocks is generally low, not exceeding 0.3 mg/kg, although Cd can concentrate in metalliferous ore deposits, in argillaceous (fine grained) rocks and in coal. A contributing factor in determining the Cd content of soil is the chemical composition of the parent material. Areas in which soils are enriched in Cd are those with high naturally occurring Cd concentrations, usually associated with sulphide mineralisation, in the underlying rocks. Cadmium is an element associated with many of the mineralised areas and the accompanying mining and processing activities such as ore smelting. Zinc smelters may cause large emissions of fumes enriched in CdO. Phosphate fertilisers and sewage sludges are also sources of Cd in soil. The presence of Cd in car tyres and motor oil often accounts for the relative accumulation of Cd in roadside soils. Other important anthropogenic sources are Ni-Cd batteries and coal burning

Modelling trace metal background to evaluate anthropogenic contamination in arable soils of south-western France

The trace metal (TM) content in arable soils has been monitored across a region of France characterised by a large proportion of calcareous soils. Within this particular geological context, the objectives were to first determine the natural levels of trace metals in the soils and secondly, to assess which sites were significantly contaminated. Because no universal contamination assessment method is currently available, four different methods were applied and compared in order to facilitate the best diagnosis of contamination. First, the TM geochemical background was determined by using basic descriptive statistics and linear regression models calculated with semi-conservative major elements as predictors. The natural concentrations of trace metals varied greatly due to the high soil heterogeneity encountered on the regional scale and were more-or-less accurately modelled according to the considered TM. Second, the basic descriptive statistics and the linear regression methods were then compared with the enrichment factor (EF) method and multivariate analysis (PCA), in order to evaluate whether the concentrations measured in soils were abnormally high or not. The advantages and disadvantages of each method were discussed and their results used to identify the most probable contamination cases, the influence of the soils characteristics, as well as the agricultural land cover. The basic descriptive method was good as a first and easy approach to describe the TM ambient concentrations, but may misinterpret the natural anomalies as contaminations. Based on geochemical associations, the linear regression method provided more realistic results even if the relationships between major and trace metals were not significant for the most mobile TM. The EF method was useful to identify high point source contaminations, but it was not suitable when considering a large dataset of low TM concentrations. Finally, the PCA method was a good preliminary tool for the description of the global TM concentrations in a studied area, but it could only give indication on the highest contaminated points. By comparing the results of the different methods in the studied region, we estimated that 24% of the arable soils were contaminated by at least one trace metal, mainly Cu in vineyards/orchards and Cd, Pb and/or Zn in grazing lands. In addition, the calcareous soils exhibited globally higher natural and anthropogenic TM concentrations than non-calcareous soils, probably because of the lower TM mobility at alkaline pH