Ash content, as a crucial indicator of coal quality, its rapid and accurate determination is pivotal to improve the energy utilization of coal and reduce environmental pollution. Traditional spectroscopic methods face significant challenges in acquiring accurate information from coal samples due to the notorious matrix effects arising from their complex composition, vast molecular structure, and diverse coal types. In this study, the feasibility of total reflection X-ray fluorescence (TXRF) combined with partial least squares (PLS) for the determination of coal ash was firstly investigated based on the TXRF being unaffected by matrix effects. Firstly, coal samples were prepared as suspensions, and the effects of sample particle size and different dispersants on the results of TXRF analyses were evaluated. The accuracy and applicability of the chosen sample preparation strategies were further validated using inductively coupled plasma mass spectrometry (ICP-MS) and two certified reference materials (CRMs). Subsequently, based on the analysis of 19 coal samples, the impact of three different predictive variables on the performance of the PLS model was investigated: (a) TXRF full spectrum normalized by the net intensity of the internal standard; (b) net intensity of characteristic peaks for 12 elements (Al, Si, K, Ca, Ti, Fe, Cr, Mn, Cu, Ni, and Sr) normalized by the net intensity of the internal standard; (c) concentrations of the aforementioned 12 elements. The results demonstrate that the PLS model constructed usingthe TXRF full spectrum normalized by the net intensity of the internal standard exhibits the best predictive capabilities, with the determination coefficient of calibration set (R) and mean square error (MSE) of the prediction set reaching 0.9736 and 0.99 %, respectively. Moreover, the measurement accuracy of this model was six times greater than that obtained with traditional X-ray fluorescence (XRF). Presented analytical results display the possibilities of combining TXRF with PLS for coal quality evaluation.
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http://dx.doi.org/10.1016/j.talanta.2024.126747 | DOI Listing |
Environ Sci Technol
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CNRS, IRCELYON, UMR 5256, Université Claude Bernard Lyon 1, F-69100 Villeurbanne, France.
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Department of Radiology, Kindai University, Faculty of Medicine, Osakasayama 589-8511, Osaka, Japan.
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January 2025
Centro de Investigaciones Económicas y Empresariales, Universidad Privada Boliviana, La Paz, Bolivia.
In this research we show that ambitious increases in tobacco tax rates can substantially reduce tobacco consumption, increase fiscal revenue, and provide net positive social benefits even in contexts of low consumption prevalence and intensity. Low nicotine intake still constitutes a grave disease risk factor, and the effectiveness of tax increases might be questioned if income effects are small. We adapt spatial variation of price methodologies to deal with low prevalence and intensity, censored data, and small samples using the Bolivian case as an illustration.
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January 2025
School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, No.219, Ningliu Road, Nanjing, 210044, Jiangsu, China.
Heat extremes become increasingly frequent and severe, posing adverse risks to public health and environment. Previous research on extreme heat mostly used meteorological observations or reanalysis data, which cannot well capture detailed spatial patterns. This study developed a seamless air temperature (T) dataset from remote sensing data to characterize the spatio-temporal variations of heat extremes in the Yangtze River Delta (YRD) from 2001 to 2023.
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January 2025
School of Civil and Environmental Engineering, Harbin Institute of Technology Shenzhen, Shenzhen 518055, China.
Due to the global outbreaks caused by pathogens, disinfection has attracted widespread attention, especially as the final inactivation step in wastewater treatment plants (WWTPs). Ultraviolet (UV) radiation is regarded as one of low carbon disinfection methods without chemical agents, but in practice, the effects are sometimes unsatisfactory, e.g.
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