skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Linear regression analysis of emissions factors when firing fossil fuels and biofuels in a commercial water-tube boiler

Abstract

This paper compares the emissions factors for a suite of liquid biofuels (three animal fats, waste restaurant grease, pressed soybean oil, and a biodiesel produced from soybean oil) and four fossil fuels (i.e., natural gas, No. 2 fuel oil, No. 6 fuel oil, and pulverized coal) in Penn State's commercial water-tube boiler to assess their viability as fuels for green heat applications. The data were broken into two subsets, i.e., fossil fuels and biofuels. The regression model for the liquid biofuels (as a subset) did not perform well for all of the gases. In addition, the coefficient in the models showed the EPA method underestimating CO and NOx emissions. No relation could be studied for SO{sub 2} for the liquid biofuels as they contain no sulfur; however, the model showed a good relationship between the two methods for SO{sub 2} in the fossil fuels. AP-42 emissions factors for the fossil fuels were also compared to the mass balance emissions factors and EPA CFR Title 40 emissions factors. Overall, the AP-42 emissions factors for the fossil fuels did not compare well with the mass balance emissions factors or the EPA CFR Title 40 emissions factors. Regression analysis of the AP-42, EPA,more » and mass balance emissions factors for the fossil fuels showed a significant relationship only for CO{sub 2} and SO{sub 2}. However, the regression models underestimate the SO{sub 2} emissions by 33%. These tests illustrate the importance in performing material balances around boilers to obtain the most accurate emissions levels, especially when dealing with biofuels. The EPA emissions factors were very good at predicting the mass balance emissions factors for the fossil fuels and to a lesser degree the biofuels. While the AP-42 emissions factors and EPA CFR Title 40 emissions factors are easier to perform, especially in large, full-scale systems, this study illustrated the shortcomings of estimation techniques. 23 refs., 3 figs., 8 tabs.« less

Authors:
;  [1]
  1. Pennsylvania State University, University Park, PA (United States). Energy Institute
Publication Date:
OSTI Identifier:
20978433
Resource Type:
Journal Article
Resource Relation:
Journal Name: Energy and Fuels; Journal Volume: 21; Journal Issue: 6; Other Information: sfm1@psu.edu
Country of Publication:
United States
Language:
English
Subject:
01 COAL, LIGNITE, AND PEAT; 09 BIOMASS FUELS; FOSSIL FUELS; BIOFUELS; EMISSION; BOILERS; REGRESSION ANALYSIS; MASS BALANCE

Citation Formats

Sharon Falcone Miller, and Bruce G. Miller. Linear regression analysis of emissions factors when firing fossil fuels and biofuels in a commercial water-tube boiler. United States: N. p., 2007. Web. doi:10.1021/ef700441d.
Sharon Falcone Miller, & Bruce G. Miller. Linear regression analysis of emissions factors when firing fossil fuels and biofuels in a commercial water-tube boiler. United States. doi:10.1021/ef700441d.
Sharon Falcone Miller, and Bruce G. Miller. 2007. "Linear regression analysis of emissions factors when firing fossil fuels and biofuels in a commercial water-tube boiler". United States. doi:10.1021/ef700441d.
@article{osti_20978433,
title = {Linear regression analysis of emissions factors when firing fossil fuels and biofuels in a commercial water-tube boiler},
author = {Sharon Falcone Miller and Bruce G. Miller},
abstractNote = {This paper compares the emissions factors for a suite of liquid biofuels (three animal fats, waste restaurant grease, pressed soybean oil, and a biodiesel produced from soybean oil) and four fossil fuels (i.e., natural gas, No. 2 fuel oil, No. 6 fuel oil, and pulverized coal) in Penn State's commercial water-tube boiler to assess their viability as fuels for green heat applications. The data were broken into two subsets, i.e., fossil fuels and biofuels. The regression model for the liquid biofuels (as a subset) did not perform well for all of the gases. In addition, the coefficient in the models showed the EPA method underestimating CO and NOx emissions. No relation could be studied for SO{sub 2} for the liquid biofuels as they contain no sulfur; however, the model showed a good relationship between the two methods for SO{sub 2} in the fossil fuels. AP-42 emissions factors for the fossil fuels were also compared to the mass balance emissions factors and EPA CFR Title 40 emissions factors. Overall, the AP-42 emissions factors for the fossil fuels did not compare well with the mass balance emissions factors or the EPA CFR Title 40 emissions factors. Regression analysis of the AP-42, EPA, and mass balance emissions factors for the fossil fuels showed a significant relationship only for CO{sub 2} and SO{sub 2}. However, the regression models underestimate the SO{sub 2} emissions by 33%. These tests illustrate the importance in performing material balances around boilers to obtain the most accurate emissions levels, especially when dealing with biofuels. The EPA emissions factors were very good at predicting the mass balance emissions factors for the fossil fuels and to a lesser degree the biofuels. While the AP-42 emissions factors and EPA CFR Title 40 emissions factors are easier to perform, especially in large, full-scale systems, this study illustrated the shortcomings of estimation techniques. 23 refs., 3 figs., 8 tabs.},
doi = {10.1021/ef700441d},
journal = {Energy and Fuels},
number = 6,
volume = 21,
place = {United States},
year = 2007,
month =
}
  • Industry and municipalities are increasingly dependent on incineration to solve waste-disposal problems. In many instances, heat recovery--usually in the form of steam generation--is necessary to obtain the energy credits needed to offset capital and operating costs. Nevertheless, the reduction of the waste is the primary function of the facility. Therefore, the heat-recovery system should be considered a fuelfollowing installation rather than a more conventional load-following one.
  • The Canadian coal-water fuel technology development program has been in progress since 1980. This phase of the work is the final stage in the demonstration of practicability of burning coal-water fuel in a boiler designed to burn oil. Early tests in small coal-capable front-wall and tangentially fired utility boilers have shown that two of the major problems to be addressed are both burner related: atomizer durability an poor carbon conversion performance. The present paper describes tests that were conducted in a 20 MWe compact, oil-designed boiler. Five burners were modified to burn coal-water fuel and oil with minimum changeover time.more » No changes were made to the boiler heat transfer tubes or to the flat furnace bottom to facilitate ash removal. The performance of the unit on coal-water fuel and oil is compared and evidence given that the derating was not as severe as had been predicted. The commercial burner supplied did show some atomizer wear, part of which could be attributed to manufacturing deficiencies. It is suggested that the performance of this small unit should be applicable to larger units in the 100 MWe range.« less
  • A Fourier transform Raman spectrometer was used to collect the Raman spectra of 208 commercial petroleum fuels. The individual motor and research octane numbers (MON and RON, respectively) were determined experimentally using the industry standard ASTM knock engine method. Partial least-squares regression analysis was used to build regression models which correlate the Raman spectra of 175 of the fuels with the experimentally determined values for MON, RON, and pump octane number (the average of MON and RON) of the fuels. Each of the models was validated using leave-one-out validation. The standard errors of validation are 0.415, 0.535, and 0.410 octanemore » units for MON, RON, and pump octane number, respectively. It is evident that the accuracy of the Raman determined values is limited by the accuracy of the training set used in creating the models. The Raman regression models were used to predict the octane numbers for the fuels which were not used to build the models. The results compare favorably with the leave-one-out validation. Also, it is demonstrated that the experimentally determined Reid vapor pressures are highly correlated with the Raman spectra of the fuel samples and can be predicted with a standard error of 0.568 psi. 11 refs., 6 figs., 2 tabs.« less
  • The performance and air pollution emissions of an experimental water/oil emulsion burner are presented. The burner was fired with two residual oils at selected emulsion water fractions. Various stoichiometric ratios and two load conditions were used to determine how operational parameters influenced the results. Particulate mass emissions and particle size distributions are presented. Examples show that, even though particulate mass may decrease, the total amount of fine particulate emissions may increase by using water/oil emulsions. The performance of the boiler is reduced when large fractions of water are used in the emulsion due to latent heat losses. This performance lossmore » may be only slightly recovered by operating at a reduced stoichiometric ratio corresponding to a smoke limit. NO/sub x/ and CO emissions data are presented for various test conditions, but neither were affected significantly by use of water/oil emulsions. 15 refs.« less