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Characterization of Slovenian coal and estimation of coal heating value based on proximate analysis using regression and artificial neural networks

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Kavšek D., Bednárová A., Biro M., Kranvogl R., Vončina D., Beinrohr E.

Open Chemistry

2013

vol. 11

issue 9

1481-1491

Abstract Chemical composition of Slovenian coal has been characterised in terms of proximate and ultimate analyses and the relations among the chemical descriptors and the higher heating value (HHV) examined using correlation analysis and multivariate data analysis methods. The proximate analysis descriptors were used to predict HHV using multiple linear regression (MLR) and artificial neural network (ANN) methods. An attempt has been made to select the model with the optimal number of predictor variables. According to the adjusted multiple coefficient of determination in the MLR model, and alternatively, according to sensitivity analysis in ANN developing, two descriptors were evaluated by both methods as optimal predictors: fixed carbon and volatile matter. The performances of MLR and ANN when modelling HHV were comparable; the mean relative difference between the actual and calculated HHV values in the training data was 1.11% for MLR and 0.91% for ANN. The predictive ability of the models was evaluated by an external validation data set; the mean relative difference between the actual and predicted HHV values was 1.39% in MLR and 1.47% in ANN. Thus, the developed models could be appropriately used to calculate HHV. Graphical abstract [...]

Geochemical investigation of alluvial sediments: validation of ICP-OES determination of heavy metals. A case study from the Utrata River Valley (central Poland)

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Biro M., Kavšek D., Karasiński J., Szwarczewski P., Bulska E., Vončina D.

The development and validation of a reliable analytical procedure for the determination of selected metals (Cd, Cr, Cu, Pb, Zn and Mn) in sediments accumulated in the Utrata River (Poland) is described. The aqua regia extraction followed by inductively coupled plasma optical emission spectrometry (ICP-OES) was used for this purpose. The optimized analytical procedure was validated, and adequate quality control actions were implemented in order to provide reliable data. The precision under’ within-laboratory’ reproducibility conditions was estimated from duplicate analysis. Certified reference material (CRM) was used in order to evaluate the accuracy of the results regarding the sewage sludge amended soil CRM 143R. The detection limits for all elements of interest were well-below their content in the investigated sediment samples. The obtained reliable data could be used for assessment of the relationship between human economic activity in the past and the geochemical features of the sediments.

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2 Open Chemistry

1 2014

1 2013

2 Biro M.

2 Kavšek D.

2 Vončina D.

1 Bednárová A.

1 Beinrohr E.

1 Bulska E.

1 Karasiński J.

1 Kranvogl R.

1 Szwarczewski P.

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Characterization of Slovenian coal and estimation of coal heating value based on proximate analysis using regression and artificial neural networks

Geochemical investigation of alluvial sediments: validation of ICP-OES determination of heavy metals. A case study from the Utrata River Valley (central Poland)