Phosphorus Speciation in Surface Waters by Ion Chromatography With High Resolution Mass Spectrometry Detection

Phosphorus (P) containing compounds, depending on their origin, can enter freshwater systems in variety of forms. Utilization of bioavailable P, a key nutrient in living organisms, is a crucial factor in biological productivity in aquatic environment¹. An increase in the P concentration in water, resulting from both natural and anthropogenic processes, can lead to eutrophication and an excessive growth of vegetative biomass. Determination of organic and inorganic P species in ground, surface and waster is an important part of water quality control and monitoring². Analytical determination of P compounds, quantification, identification (Chapter 2) and P speciation process can be problematic due to P adsorption on storage containers, sulfate interference, presence of acid hydrolysable P species and colloidal matter, association of both inorganic and organic phosphates with iron, manganese and aluminum, biological uptake of P. Such processes have to be considered when designing an analytical procedure for analysis of P species. Analytical P compound separation by ion chromatography with mass spectrometry/Orbitrap technology for compound detection (Chapter 3) is a powerful technology with highly sensitive and selective properties capable of performing P speciation in one analytical run. Selectivity of the Orbitrap detector also allows for utilization of isotope dilution technique which can compensate for loss of P compounds during storage and transportation and thus increase accuracy of measurements and holding time of sample matrices. Analytical techniques used in the past were able to determine broad P-fractions, such as total P, total P or functional groups of inorganic and organic P compounds. Identification of variety of specific P-containing compounds of inorganic and organic origin by the methodology used in this thesis in combination with multivariate statistical analysis can be used to explain the large sets of intercorrelated analytical variables with a smaller set of independent variables (Chapter 4) and help in source identification in water pollution studies³.