The determination of heavy metals in soils and organic amendments, such as compost, manure, biofertilizer, and sludge, generally involves the digestion of samples with aqua regia, and the determination of those in the solution using various techniques. Portable X-ray fluorescence (PXRF) has many advantages in relation to traditional analytical techniques. However, PXRF determines the total elemental content and, until now, its use for the analysis of organic amendments has been limited. The objective of this work is the calibration of a PXRF instrument to determine the aqua regia-soluble elemental contents directly in solid samples of organic amendments. Our proposal will avoid the digestion step and the use of other laboratory techniques. Using a training set of samples, calibration functions were obtained that allow the determination of the aqua regia-soluble contents from the PXRF readings of total contents. The calibration functions (obtained by multiple linear regression) allowed the quantitative determination of the aqua regia-soluble contents of Fe, K, P, S, Zn, Cu, Pb, Sr, Cr, and Mn, as well as the organic matter content and a semi-quantitative assessment of Al, Ca, V, Ba, Ni, and As contents. The readings of Si, Fe, Al, Ca, K, or S were used as correction factors, indicating that the calibrations functions found are truly based on the chemical composition of the sample matrix. This study will allow a fast, cheap, and reliable field analysis of organic amendments and of other biomass-based materials.

Portable X-ray fluorescence (pXRF) has been a widely used technique in various applications. However, its use for the analysis of organic amendments (composts, sewage sludges, organic fertilizers) is scarce. In these matrices, concentrations of some elements are below their detection limit. The objective of this work was to find multiple linear regression equations that were able to predict the aqua-regia-soluble concentrations of the elements As, Cd, Cr, Hg, Ni, and Se using the pXRF readings of other measurable elements as predictor variables. For this, a set of 30 samples of organic amendments (composts, sewage sludges, and organic fertilizers) from the Manure and Refuse Sample Exchange Programme of the Wageningen Evaluating Programs for Analytical Laboratories (MARSEP-WEPAL) was used. Several amendment type-dependent single or multiple linear functions were found based on 1, 2, or 3 predictors. The predictor readings corresponded to the concentration of elements of geogenic (Fe, Si, Ti, Cl, Zr Al, Ca, S, Mn, and Ba), anthropogenic (Zn and Pb), and agricultural (P and K) origin. The regression coefficients of these functions were r = 0.90–0.99; therefore, they allowed for the quantitative determination of the target elements. These results will allow for fast and reliable analysis of organic amendments using pXRF that is valid for quality control in treatment plants.