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Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 9 3.0 Summary of Results Using the impact factor quantification plan described above, pollutant-specific functions were developed for each of the pollutant species examined in this study i.e., SOx, NOx, CO, nvPM (mass), nvPM (number), UHC and HAPs. In each case the critical parameter is blend percent (blend%). The resulting quantification functions and their associated uncertainties are given in Table 1. By way of application, example numerical impact factors are presented for a blend of 50% SAJF, which is a common boundary condition. Definitions of the terms used in Table 1 are given in Table 2. Table 1: Quantification functions, impact factors and their associated uncertainties Pollutant Species Impact Quantification Factor Functions Impact Factor Îf Uncertainty δ Impact Factor Îf Uncertainty δ and Estimated Uncertainties blend%=5 blend%=5 blend%=50 blend%=50 SOx ÎfSOx,[S] = ððððð%100% â [SSAJF][Sconv] - 1 . -0.037 -0.375 δÎfSOx,[S] = ÎfSOx â ððððð%100%â 1 + ð¿ ððððð%100%â [S]sajf-δ[S][S]conv+δ[S] â 1 0.007 0.072 nvPM (number) ð¥f_EIn_fit = â 1.25ð¸ â 2 â ððððð% + 5.91ð¸ â 5â ððððð%^2. -0.061 -0.477 δÎf_EIn_fit = { (5.23ð¸ â 3 â ððððð%)2 + (7.73ð¸ â 5â ððððð%2)2}1/2 0.026 0.325 nvPM (mass) Îf_EIm_fit = â 1.90ð¸ â 2 â ððððð% + 1.20ð¸ â 4â ððððð%^2 -0.092 -0.65 δÎf_EIm_fit = { (5.31ð¸ â 3 â ððððð%)2 + (6.70ð¸ â 5â ððððð%^2) 2}1/2 0.026 0.314 NOx No significant impact; δÎf>Îf. (Îf_EINOx = â0.0024 ± 0.0039) -0.002 0.004 -0.002 0.004 CO Îf_EICO = â 2.16ð¸ â 3 â ðµðððð% -0.01 -0.108 δÎfCO,fit = 9.32ð¸ â 4 â ððððð% 0.004 0.047 UHC Îf_EIUHC = â0.3482 â ð¡ððâ (0.322â ððððð%). -0.321 -0.348 δÎf_EIUHC = 0.1234 â ð¡ððâ (0.2867â ððððð%). 0.11 0.123 HAPs No significant impact; δÎf>Îf.(Îf_EIHAPS = â0.006 ± 0.046) -0.006 0.046 -0.006 0.046
Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 10 Table 2: Definitions for terms used in Table 1 ÎfSOx, EI = Fractional impact factor for SOx emission index. ÎSOx = impact factor for SOx emission index = Change in SOx emission index. EISOx, conv = SOx emission index for the blending conventional jet fuel. blend% = Percentage of SAJF blended with conventional jet fuel. EISOx, SAJF = Emission index for pure SAJF. ÎfSOx, [S] = Fractional impact factor for SOx expressed as function of fuel sulfur content. [SSAJF] = Fuel sulfur content of the SAJF. [Sconv] = Fuel sulfur content of the conventional jet fuel. δ... = Uncertainty in a given parameter. Îf_EIn_fit = The fractional impact factor for number-based EI based on a functional fit to tabulated data. Îf_EIm_fit = The fractional impact factor for mass-based EI based on a functional fit to tabulated data. Îf_EINOx = The fractional impact factor for NOx. Îf_EICO = The fractional impact factor for CO. Îf_EIUHC = The fractional impact factor for UHC. Îf_EIHAPs = The fractional impact factor for HAPs. For comparison, Figure 1 presents the results of the emissions reductions for CO, SOx, nvPM (number), and nvPM (mass) at 5% and 50% blends. These pollutant species provided the most significant results beyond the uncertainty bounds. The impact factor uncertainty for NOx and HAPs is greater than the corresponding impact factor, which implies that there is no statistically significant impact associated with SAJF usage for these species. The functional fit analysis for UHC impact is confounded by the extensive scatter in the small amount of data available in the literature on UHC emissions (three papers (Refs 6, 17, 21) with 80% of the data coming from Ref 17). The observed scatter appears to be driven by not only blend ratio but also engine operating condition (Ref 17). As a result, the authors caution applying the impact factors for UHC resulting from the above functional analysis. The authors further recommend the pursuit of additional experimental studies on UHC emissions associated with Figure 1: Emissions reductions at 5% and 50% SAJF blends for CO, SOx, nvPM (mass) and nvPM (#). NOX, HAPS, AND UHC UNCERTAINTY ⢠For NOx and HAPs, this study found no statistically significant impact associated with SAJF because the uncertainty in impact factors are greater than the impact factor. ⢠For UHC, there was extensive scatter in the underlying data driven by one study (Ref 17). As a result, this study did not produce statistically meaningful results for UHC impact factors.
Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 11 blended SAJFs as a function of engine operating condition in order to strengthen confidence in the resulting impact factor analysis.