GEMAS: Phosphorus in European agricultural soil - sources versus sinks at the continental-scale - the geological perspective.

Phosphorus (P) is one of the essential elements for life on Earth. As a major nutrient it is needed for healthy growth both in plants and living organisms. Although the abundance of P in the Earth's upper continental crust is relatively high (655 mg/kg), many soil types are poor in available phosphorus.

Excess Cr and Ni in top soil: Comparing the effect of geology, diffuse contamination, and biogenic influence.

Chromium (Cr) and nickel (Ni) are among the elements that are most mined, processed and used in modern industry and society. A realistic estimate of the diffuse contamination that has left a footprint on soil during the last 200 years by worldwide industrialization requires recognition and assessment of the dominant natural and anthropogenic sources. The relations between geogenic, anthropogenic, and biogenic Cr and Ni sources are estimated from eight large-scale geochemical surveys, by comparing the cumulative distribution functions (CDF) of the elements in top- and sub soil using cumulative probability (CP) diagrams.

Quantifying diffuse contamination: Comparing silver and mercury in organogenic and minerogenic soil.

For both, silver (Ag) and mercury (Hg), the median concentrations in an aqua regia extraction of minerogenic top- and subsoil from continental scale geochemical surveys (Australia, China, Europe) are around 0.02 mg/kg. When the soil O horizon is collected as topsoil sample, the concentration of again both elements is higher by about a factor of 10 (range 7-30), with median concentrations around 0.

Identification of the co-existence of low total organic carbon contents and low pH values in agricultural soil in north-central Europe using hot spot analysis based on GEMAS project data.

Total organic carbon (TOC) contents in agricultural soil are presently receiving increased attention, not only because of their relationship to soil fertility, but also due to the sequestration of organic carbon in soil to reduce carbon dioxide emissions. In this research, the spatial patterns of TOC and its relationship with pH at the European scale were studied using hot spot analysis based on the agricultural soil results of the Geochemical Mapping of Agricultural Soil (GEMAS) project. The hot and cold spot maps revealed the overall spatial patterns showing a negative correlation between TOC contents and pH values in European agricultural soil.

Bioavailable Sr/Sr in European soils: A baseline for provenancing studies.

We present Sr/Sr isotope ratios for ~1200 selected soil samples, collected by the GEMAS consortium from grazing (Gr) and agricultural (Ap) soils in Europe with the aim to better understand the strontium isotope distribution in the bioavailable fraction of the top-soil and its potential for provenancing applications. Spatial analysis shows that there is a clear distinction between coastal (<100 km) and non-coastal (>100 km) samples in their variance and that this variance is mirrored in the sodium concentration, suggesting an important but highly variable contribution from seaspray. We present two Sr/Sr maps at 25 km × 25 km scale: one based solely on the measured data using a classical kriging approach and one based on a Random Forest model using complementary GEMAS data to predict the strontium isotope composition at the remaining 3000+ GEMAS sampling locations, including appropriate uncertainty assessment.

Reliability of geochemical analyses: Deja vu all over again.

Today the vast majority of commercial laboratories are accredited. Quality control (QC) results are documented and, upon request, available to the customer. That has led many customers of analytical services to neglect the need for their own, laboratory independent, external QC for large geochemical mapping or monitoring projects.

The large-scale distribution of Cu and Zn in sub- and topsoil: Separating topsoil bioaccumulation and natural matrix effects from diffuse and regional contamination.

A realistic estimate of diffuse contamination requires to recognize and assess the dominant natural and anthropogenic element sources. For eight large-scale geochemical surveys, the relations between geogenic, anthropogenic and biogenic Cu and Zn sources are estimated by comparing the cumulative distribution functions (CDF) of the elements in top- and subsoil using cumulative probability (CP) diagrams. Strong local contamination distorts the high-concentration end of the distribution function considerably in topsoil.

Cadmium enrichment in topsoil: Separating diffuse contamination from biosphere-circulation signals.

Eight regional to continental scale datasets providing Cd concentrations in subsoil (C horizon or mineral soil collected at depth) and topsoil are used to compare the statistical distribution of Cd in the two soil layers. Topsoil is invariably enriched in Cd when compared to subsoil. When both horizons are mineral soil the concentration ratio Cd/Cd is 1.

U-Th signatures of agricultural soil at the European continental scale (GEMAS): Distribution, weathering patterns and processes controlling their concentrations.

Agricultural soil (Ap-horizon, 0-20cm) samples were collected in Europe (33 countries, 5.6millionkm) as part of the GEMAS (GEochemical Mapping of Agricultural and grazing land Soil) soil-mapping project. The GEMAS survey area includes diverse groups of soil parent materials with varying geological history, a wide range of climate zones, and landscapes.

Geosphere-biosphere circulation of chemical elements in soil and plant systems from a 100 km transect from southern central Norway.

Geochemical element separation is studied in 14 different sample media collected at 41 sites along an approximately 100-km long transect north of Oslo. At each site, soil C and O horizons and 12 plant materials (birch/spruce/cowberry/blueberry leaves/needles and twigs, horsetail, braken fern, pine bark and terrestrial moss) were sampled. The observed concentrations of 29 elements (K, Ca, P, Mg, Mn, S, Fe, Zn, Na, B, Cu, Mo, Co, Al, Ba, Rb, Sr, Ti, Ni, Pb, Cs, Cd, Ce, Sn, La, Tl, Y, Hg, Ag) were used to investigate soil-plant relations, and to evaluate the element differentiation between different plants, or between foliage and twigs of the same plant.

GEMAS: CNS concentrations and C/N ratios in European agricultural soil.

A reliable overview of measured concentrations of TC, TN and TS, TOC/TN ratios, and their regional distribution patterns in agricultural soil at the continental scale and based on measured data has been missing - despite much previous work on local and the European scales. Detection and mapping of natural (ambient) background element concentrations and variability in Europe was the focus of this work. While total C and S data had been presented in the GEMAS atlas already, this work delivers more precise (lower limit of determination) and fully quantitative data, and for the first time high-quality TN data.

Quantifying Diffuse Contamination: Method and Application to Pb in Soil.

A new method for detecting and quantifying diffuse contamination at the continental to regional scale is based on the analysis of cumulative distribution functions (CDFs). It uses cumulative probability (CP) plots for spatially representative data sets, preferably containing >1000 determinations. Simulations demonstrate how different types of contamination influence elemental CDFs of different sample media.

Publicly available datasets on thallium (Tl) in the environment-a comment on "Presence of thallium in the environment: sources of contaminations, distribution and monitoring methods" by Bozena Karbowska, Environ Monit Assess (2016) 188:640 (DOI 10.1007/s10661-016-5647-y).

This comment highlights a whole series of datasets on thallium concentrations in the environment that were overlooked in the recent review by Karbowska, Environmental Monitoring and Assessment, 188, 640, 2016 in this journal. Geochemical surveys carried out over the last few decades all over the world at various scales and using different sampling media have reported the concentration of thallium (and dozens more elements) in tens of thousands of samples. These datasets provide a 'real-world' foundation upon which source apportionment investigations can be based, monitoring programs devised and modelling studies designed.

Establishing geochemical background variation and threshold values for 59 elements in Australian surface soil.

During the National Geochemical Survey of Australia over 1300 top (0-10cm depth) and bottom (~60-80cm depth) sediment samples (including ~10% field duplicates) were collected from the outlet of 1186 catchments covering 81% of the continent at an average sample density of 1 site/5200km. The <2mm fraction of these samples was analysed for 59 elements by ICP-MS following an aqua regia digestion. Results are used here to establish the geochemical background variation of these elements, including potentially toxic elements (PTEs), in Australian surface soil.

GEMAS: prediction of solid-solution phase partitioning coefficients (Kd) for oxoanions and boric acid in soils using mid-infrared diffuse reflectance spectroscopy.

The authors' aim was to develop rapid and inexpensive regression models for the prediction of partitioning coefficients (Kd), defined as the ratio of the total or surface-bound metal/metalloid concentration of the solid phase to the total concentration in the solution phase. Values of Kd were measured for boric acid (B[OH]3(0)) and selected added soluble oxoanions: molybdate (MoO4(2-)), antimonate (Sb[OH](6-)), selenate (SeO4(2-)), tellurate (TeO4(2-)) and vanadate (VO4(3-)). Models were developed using approximately 500 spectrally representative soils of the Geochemical Mapping of Agricultural Soils of Europe (GEMAS) program.

GEMAS: prediction of solid-solution partitioning coefficients (Kd) for cationic metals in soils using mid-infrared diffuse reflectance spectroscopy.

Partial least squares regression (PLSR) models, using mid-infrared (MIR) diffuse reflectance Fourier-transformed (DRIFT) spectra, were used to predict distribution coefficient (Kd) values for selected added soluble metal cations (Ag(+), Co(2+), Cu(2+), Mn(2+), Ni(2+), Pb(2+), Sn(4+), and Zn(2+)) in 4813 soils of the Geochemical Mapping of Agricultural Soils (GEMAS) program. For the development of the PLSR models, approximately 500 representative soils were selected based on the spectra, and Kd values were determined using a single-point soluble metal or radioactive isotope spike. The optimum models, using a combination of MIR-DRIFT spectra and soil pH, resulted in good predictions for log Kd+1 for Co, Mn, Ni, Pb, and Zn (R(2) ≥ 0.

The concept of compositional data analysis in practice--total major element concentrations in agricultural and grazing land soils of Europe.

Applied geochemistry and environmental sciences invariably deal with compositional data. Classically, the original or log-transformed absolute element concentrations are studied. However, compositional data do not vary independently, and a concentration based approach to data analysis can lead to faulty conclusions.

New soil composition data for Europe and Australia: demonstrating comparability, identifying continental-scale processes and learning lessons for global geochemical mapping.

New geochemical data from two continental-scale soil surveys in Europe and Australia are compared. Internal project standards were exchanged to assess comparability of analytical results. The total concentration of 26 oxides/elements (Al2O3, As, Ba, CaO, Ce, Co, Cr, Fe2O3, Ga, K2O, MgO, MnO, Na2O, Nb, Ni, P2O5, Pb, Rb, SiO2, Sr, Th, TiO2, V, Y, Zn, and Zr), Loss On Ignition (LOI) and pH are demonstrated to be comparable.

The performance of moss, grass, and 1- and 2-year old spruce needles as bioindicators of contamination: a comparative study at the scale of the Czech Republic.

Moss (Pleurozium schreberi), grass (Avenella flexuosa), and 1- and 2-year old spruce (Picea abies) needles were collected over the territory of the Czech Republic at an average sample density of 1 site per 290km(2). The samples were analysed for 39 elements (Ag, Al, As, Ba, Be, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, Hg, K, La, Li, Mg, Mn, Mo, Na, Nd, Ni, Pb, Pr, Rb, S, Sb, Se, Sn, Sr, Th, Tl, U, V, Y and Zn) using ICP-MS and ICP-AES techniques (the major nutrients Ca, K, Mg and Na were not analysed in moss). Moss showed by far the highest element concentrations for most elements.

Magnetic properties of terrestrial moss (Hylocomium splendens) along a north-south profile crossing the city of Oslo, Norway.

Magnetic measurements are routinely used in geophysics and environmental sciences to obtain detailed information about concentrations and quality of iron minerals. Here, magnetic properties of 38 terrestrial moss samples (Hylocomium splendens) from a ~120km south-north transect through Oslo are studied to gain better insight into the nature and origin of their Fe fraction. The concentration-dependent quantities, magnetic susceptibility k, and isothermal remanent magnetization IRM(700mT) after weight normalization have significantly higher values in urban regions, and parallel the previously found concentration signals of 16 out of 29 chemical elements (Ag, Al, Au, Bi, Cd, Co, Cr, Cu, Fe, Mo, Ni, Pb, Pt, Sb, Ti, and Zn).

Linking chemical elements in forest floor humus (Oh-horizon) in the Czech Republic to contamination sources.

While terrestrial moss and other plants are frequently used for environmental mapping and monitoring projects, data on the regional geochemistry of humus are scarce. Humus, however, has a much larger life span than any plant material. It can be seen as the "environmental memory" of an area for at least the last 60-100 years.

The bivariate statistical analysis of environmental (compositional) data.

Environmental sciences usually deal with compositional (closed) data. Whenever the concentration of chemical elements is measured, the data will be closed, i.e.

Univariate statistical analysis of environmental (compositional) data: problems and possibilities.

For almost 30 years it has been known that compositional (closed) data have special geometrical properties. In environmental sciences, where the concentration of chemical elements in different sample materials is investigated, almost all datasets are compositional. In general, compositional data are parts of a whole which only give relative information.