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Suggested Citation:"3.0 Summary of Results." National Academies of Sciences, Engineering, and Medicine. 2019. ACRP Web-Only Document 41: Alternative Jet Fuels Emissions: Quantification Methods Creation and Validation Report. Washington, DC: The National Academies Press. doi: 10.17226/25548.
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Page 9
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Suggested Citation:"3.0 Summary of Results." National Academies of Sciences, Engineering, and Medicine. 2019. ACRP Web-Only Document 41: Alternative Jet Fuels Emissions: Quantification Methods Creation and Validation Report. Washington, DC: The National Academies Press. doi: 10.17226/25548.
×
Page 10
Page 11
Suggested Citation:"3.0 Summary of Results." National Academies of Sciences, Engineering, and Medicine. 2019. ACRP Web-Only Document 41: Alternative Jet Fuels Emissions: Quantification Methods Creation and Validation Report. Washington, DC: The National Academies Press. doi: 10.17226/25548.
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Page 11

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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 Δf Uncertainty δ Impact Factor Δf Uncertainty δ and Estimated Uncertainties blend%=5 blend%=5 blend%=50 blend%=50 SOx ΔfSOx,[S] = 𝑏𝑙𝑒𝑛𝑑%100% ∗ [SSAJF][Sconv] - 1 . -0.037 -0.375 δΔfSOx,[S] = ΔfSOx − 𝑏𝑙𝑒𝑛𝑑%100%∗ 1 + 𝛿 𝑏𝑙𝑒𝑛𝑑%100%∗ [S]sajf-δ[S][S]conv+δ[S] – 1 0.007 0.072 nvPM (number) 𝛥f_EIn_fit = − 1.25𝐸 − 2 ∗ 𝑏𝑙𝑒𝑛𝑑% + 5.91𝐸 − 5∗ 𝑏𝑙𝑒𝑛𝑑%^2. -0.061 -0.477 δΔf_EIn_fit = { (5.23𝐸 − 3 ∗ 𝑏𝑙𝑒𝑛𝑑%)2 + (7.73𝐸 − 5∗ 𝑏𝑙𝑒𝑛𝑑%2)2}1/2 0.026 0.325 nvPM (mass) Δf_EIm_fit = − 1.90𝐸 − 2 ∗ 𝑏𝑙𝑒𝑛𝑑% + 1.20𝐸 − 4∗ 𝑏𝑙𝑒𝑛𝑑%^2 -0.092 -0.65 δΔf_EIm_fit = { (5.31𝐸 − 3 ∗ 𝑏𝑙𝑒𝑛𝑑%)2 + (6.70𝐸 − 5∗ 𝑏𝑙𝑒𝑛𝑑%^2) 2}1/2 0.026 0.314 NOx No significant impact; δΔf>Δf. (Δf_EINOx = −0.0024 ± 0.0039) -0.002 0.004 -0.002 0.004 CO Δf_EICO = – 2.16𝐸 − 3 ∗ 𝐵𝑙𝑒𝑛𝑑% -0.01 -0.108 δΔfCO,fit = 9.32𝐸 − 4 ∗ 𝑏𝑙𝑒𝑛𝑑% 0.004 0.047 UHC Δf_EIUHC = −0.3482 ∗ 𝑡𝑎𝑛ℎ (0.322∗ 𝑏𝑙𝑒𝑛𝑑%). -0.321 -0.348 δΔf_EIUHC = 0.1234 ∗ 𝑡𝑎𝑛ℎ (0.2867∗ 𝑏𝑙𝑒𝑛𝑑%). 0.11 0.123 HAPs No significant impact; δΔf>Δf.(Δf_EIHAPS = −0.006 ± 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 ΔfSOx, EI = Fractional impact factor for SOx emission index. ΔSOx = 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. ΔfSOx, [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. Δf_EIn_fit = The fractional impact factor for number-based EI based on a functional fit to tabulated data. Δf_EIm_fit = The fractional impact factor for mass-based EI based on a functional fit to tabulated data. Δf_EINOx = The fractional impact factor for NOx. Δf_EICO = The fractional impact factor for CO. Δf_EIUHC = The fractional impact factor for UHC. Δf_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.

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ACRP Web-Only Document 41: Alternative Jet Fuels Emissions: Quantification Methods Creation and Validation Report Get This Book
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One of the most challenging environmental issues facing the aviation industry today is the impact of jet fuel emissions on the global climate. The use of sustainable alternative jet fuels (SAJF) to reduce aircraft emissions will become significantly more important in coming years. Capturing the air quality benefits in a way that is useful to airports requires understanding how SAJF reduce pollutant emissions, quantifying the reduction, and demonstrating the impact through an easy-to-use tool that airports can apply to their emissions inventories.

ACRP Web-Only Document 41: Alternative Jet Fuels Emissions: Quantification Methods Creation and Validation Report represents the second phase of this ACRP work. The first phase provided an understanding of how SAJF impacts aircraft emissions. This phase analyzes the data compiled in the report to quantify SAJF emission impacts.

Results of this analysis were subsequently used to develop a simplified tool that will allow airports to easily estimate emission reductions from use of SAJF at their airport. The Alternative Jet Fuel Assessment Tool and the Sustainable Alternative Jet Fuels and Emissions Reduction Fact Sheet are the two key products from ACRP 02-80.

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