Correlations of the Elemental Compositions of Primary Coal Tar and Char

Abstract

Simulations of large-scale coal combustors rely on accurate submodels to describe the chemical and physical changes in coal during reaction. Typically, simplified empirical submodels are tuned to experimental data to reduce the computational complexity. When data are not readily available, simplifying assumptions are used, which can create inaccuracies and biases in a large simulation. One such simplifying assumption in coal research is how to describe the elemental composition of primary pyrolysis products. This paper explores several different empirical model forms to predict the dry, ash-free fractions of C, H, O, N, and S in both the char and tar, using variables such as parent coal composition, reaction conditions (temperatures and particle residence times), and key coal structural parameters derived from NMR measurements to improve the treatment of coal chemistry in large simulations. These model forms were correlated to existing data using a wide range of experimental data using a cross-validation procedure. Since coal structural values can be expensive to measure, several correlations from the literature were used to estimate these values on the basis of information from the proximate and ultimate analyses of the parent coal, including a new correlation for the coal aromaticity. These model forms were tested against a set of measured elemental compositions of tar and char to find the best fit to use in the cross-validation process. The best empirical models are presented that predict the elemental composition of the coal char and tar after devolatilization.

Carbon Structure of Coal from the CP/MAS 13C NMR Spectra: Effect of Contact Time and Potential Quantitative Modification

“…The deviations between modified aromaticity and the prediction of these empirical correlations were significantly reduced, almost always within ±10%, as shown in Figure 14b. The smallest deviation was obtained using the formula proposed by Richards et al, 46 with an average deviation of only 2%. A probable reason for this is that their correlation was built on a considerable amount of published data and therefore had the widest applicability.…”

“…They have acceptable accuracy and have been widely applied to estimate the carbon structures of coal, char, and tar. 46,47 The earliest aromaticity correlation was established by Van Krevelen et al 64,65 with respect to the volatile matter and carbon content of coal, as shown in eq 16:…”

“…Mazumdar 68 further discussed the applicable conditions and required adjustments related to the coal rank. A general correlation with nine coefficients was developed by Richards et al 46 based on a large collection of data from the literature and a comparison of several existing models, as shown in eq 19. This formula has the same form as the chemical structure parameters of the CPD coal pyrolysis model.…”

Pyrolysis of a typical low-rank coal: application and modification of the chemical percolation devolatilization model

“…3 By investigating different experimental conditions, the establishment of a coal pyrolysis kinetics model will be helpful to predict the composition distribution of pyrolysis products more accurately. 4,5 Generally, kinetics models of coal pyrolysis involve global and network models. 6 Early research on coal pyrolysis models mainly started from simplied mechanisms and proposed global models based on one-step reaction, two-step competitive reactions, or multi-stage nite parallel reactions.…”

“… 3 By investigating different experimental conditions, the establishment of a coal pyrolysis kinetics model will be helpful to predict the composition distribution of pyrolysis products more accurately. 4,5 …”