To analyze or to throw away? On the stability of excitation-emission matrices for different water systems.

Fluorescence spectroscopy has numerous applications to characterize natural and human-influenced water bodies regarding dissolved organic matter (DOM) and contamination. Analyzing samples in a timely manner is crucial to gaining valid and reproducible excitation-emission matrices (EEM) but often difficult, specifically in transnational projects with long transport distances. In this study, eight samples of different water sources (tap water, differently polluted rivers, and wastewater treatment plant (WWTP) effluents) were stored under standardized conditions for 59 days and analyzed regularly. With this data set, the sample and fluorescence spectra stability was evaluated. Established analysis methods such as peak picking and fluorescence metrics were compared over time and benchmarked against dissolved organic carbon (DOC) and a maximal change of 10% in terms of their variability. Additional high-performance liquid chromatography (HPLC) data to identify single organic compounds provides insights into these DOM alterations and allows for conclusions about the underlying biological processes. Our results corroborate in a systematic way that the higher the organic or microbial load, the faster the sample must be processed. For all water sources, considerable changes were found between days zero and one, indicating a potential systematic bias between in-situ and laboratory measurements. The absolute signals of individual peaks vary substantially after only a few days. In contrast, relative metrics are robust for a much longer time. For specific metrics, when filtered and stored under cool and dark conditions, tap water may be stored for up to 59 days, non-polluted river water for up to 31-59 days, and WWTP effluents for up to 14-59 days. The storability thus depends both on the specific water source and the analytical plan. By systematizing our understanding of how the specific water source and DOM concentration determine the stability of samples during storage, these conclusions facilitate efforts to establish a standardized protocol.

Measuring Comprehensive, General Health Literacy in the General Adult Population: The Development and Validation of the HLS19-Q12 Instrument in Seventeen Countries.

BACKGROUND: For improving health literacy (HL) by national and international public health policy, measuring population HL by a comprehensive instrument is needed. A short instrument, the HLS19-Q12 based on the HLS-EU-Q47, was developed, translated, applied, and validated in 17 countries in the WHO European Region. METHODS: For factorial validity/dimensionality, Cronbach alphas, confirmatory factor analysis (CFA), Rasch model (RM), and Partial Credit Model (PCM) were used. For discriminant validity, correlation analysis, and for concurrent predictive validity, linear regression analysis were carried out. RESULTS: The Cronbach alpha coefficients are above 0.7. The fit indices for the single-factor CFAs indicate a good model fit. Some items show differential item functioning in certain country data sets. The regression analyses demonstrate an association of the HLS19-Q12 score with social determinants and selected consequences of HL. The HLS19-Q12 score correlates sufficiently highly (r ≥ 0.897) with the equivalent score for the HLS19-Q47 long form. CONCLUSIONS: The HLS19-Q12, based on a comprehensive understanding of HL, shows acceptable psychometric and validity characteristics for different languages, country contexts, and methods of data collection, and is suitable for measuring HL in general, national, adult populations. There are also indications for further improvement of the instrument.

Enhanced statistical evaluation of fluorescence properties to identify dissolved organic matter dynamics during river high-flow events.

Fluorescence spectroscopy has become a widely used technique to characterize dissolved organic matter (DOM) and organic hazardous micro-pollutants in natural and human-influenced water bodies. Especially in rivers highly impacted by municipal and industrial wastewater treatment plants' effluents, the fluorescence signal at low-flow is mainly dominated by these discharges. At river high-flow, their influence decreases due to dilution effects, and at the same time, other compounds of DOM, stemming from diffuse inputs, can increase or even dominate. Therefore, whereas the analysis of DOM is little informative on the changing sources and pathways of emissions, fluorescence spectroscopy can enhance our understanding and our possibilities of monitoring such dynamics in river catchments. This paper analyzed samples from seven high-flow events in an Austrian river. Firstly, independent DOM components were discriminated using a parallel factor analysis (PARAFAC) to show the varying composition of DOM during different phases of high-flow events. Furthermore, partial least squares (PLS) and sparse PLS (sPLS) regression were applied to identify excitation and emission wavelengths, serving as proxy parameters for quantifying dissolved organic carbon (DOC) and chloride. The PLS models show the best prediction accuracy but use the entire excitation-emission matrix in exchange. In selecting predictors, the use of excitation and emission wavelengths adjusted via sPLS is superior to the extracted PARAFAC components. The sPLS model yields 16 wavelength combinations for DOC (RMSEsPLS = 0.41 mg L-1) and 18 wavelength combinations for chloride (RMSEsPLS = 2.21 mg L-1). In contrast to other established optical measurement methods, which require different calibrations for low- and high-flow conditions, these models based on sPLS succeed in quantifying those parameters across the entire range of flow conditions and events of various magnitudes with a relative precision of about 5 %. These results show how the application of multivariate statistical techniques enhances the exploitation of the information provided by fluorescence spectroscopy.

Systematic data-driven exploration of Austrian wastewater and sludge treatment - implications for phosphorus governance, costs and environment.

Within the new policy framework shaped by the EU Green Deal and the Circular Economy Action Plans, the field of wastewater and sludge treatment in Europe is subject to high expectations and new challenges related to mitigation of greenhouse gas emissions, micropollutant removal and resource recovery. With respect to phosphorus recovery, several technologies and processes have been thoroughly investigated. Nevertheless, a systemic and detailed understanding of the existing infrastructure and of the related environmental and economic implications is missing. Such basis is essential to avoid unwanted consequences in designing new strategies, given the long lifespan of any infrastructural change. This study couples a newly collected and highly detailed database for all wastewater treatment plants in Austria bigger than 2000 population equivalent with a combination of analyses, namely Substance Flow Analysis with focus on nutrient and metal distribution in different environmental and anthropogenic compartments, Energy Flow Analysis, Life Cycle Assessment and cost estimation. The case study of Austria is of special interest, given its highly autonomous administration in federal states and its contrasting traits, ranging from flat metropolitan areas like Vienna to low-populated alpine areas. The significant impact of electricity demand of wastewater treatment on the overall Cumulative Energy Demand (CED) shows the importance of optimization measures. Further, the current system of wastewater and sludge disposal have a low efficiency in recovering nutrients and in directing pollutants as heavy metals into final sinks. Sludge composting with subsequent use in landscaping does not only show an unfavorable environmental balance, but it is the only relevant route leading to additional CED and Global Warming Potential emissions and to the highest transport volume. Altogether, the outcomes of this study provide a sound basis to further develop national strategies for resource recovery aimed to optimize trade-offs between different economic and environmental objectives.