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. A linear regression analysis was performed on emissions factors calculated by accepted EPA methods with those determined by performing a mass balance around the boiler. In addition, AP-42 emissions factors for fossil fuels were compared to an EPA method (CFR Title 40) and a mass balance method. The EPA method emissions were identified as the "response" and the mass balance method identified as the "predictor". In general, the regression models, when considering all fuels, could predict greater than 90% (R-2) of the emissions (except for CO2, R-2 = 42.5%), suggesting there is a good relationship between the EPA method and the mass balance emissions factors. Coefficients ranged from 0.964 to 1.08. 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 (R-2 ranged from 0.1 to 73.3%). In addition, the coefficient. in the models showed the EPA method underestimating CO and NOx emissions. The fits for CO2 and NOx for the liquid biofuels were poor (R-2 = 0.1 and 73.3%, respectively). No relation could be studied for SO2 for the liquid biofuels as they contain no sulfur; however, the model showed a good relationship between the two methods for SO2 in the fossil fuels (R-2 = 99.9%). AP-42 emissions factors for the fossil fuels were also compared to the mass balance emissions factors and EPA CFR Title 40 emissions factors. (No AP-42 emissions factors exist for the biofuels tested.) 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 CO2 and SO2. However, the regression models underestimate the SO2 emissions by 33%. The regression model comparing the EPA emissions factors and the mass balance emissions factors was better at predicting the data variation (> 99% at coefficients approximately equal to 1) for CO, SO2, and NOx and 93% of the CO2 data for the fossil fuel tests (at a coefficient of 1.35). 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 especially when applied to biofuels.