The National Academies Press

Currently Skimming:

Pages 12-42

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.

From page 12... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 12 4.0 Pollutant-Specific Analysis In the following sections the detailed analysis undertaken to quantify the impacts for the pollutant species SOx, nvPM N, nvPM Mass, NOx, CO, UHC, and HAPs is presented. 4.1 SOx The SOx emission indices (EISOx, blend) Read the entire page →
From page 13... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 13 where EISOx, SAJF denotes the SOx emission index for the neat SAJF, and ΔSOx = EISOx,blend - EISOx,conv = 𝑏𝑙𝑒𝑛𝑑%100% ∗ (EISOx,SAJF − EISOx,conv) Read the entire page →
From page 14... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 14 STEP 5 – In Reference 6 (Beyersdorf, et al.) , a paper describing the results of the Alternative Aviation Fuel Experiment (AAFEX) Read the entire page →
From page 15... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 15 Illustrative example: To illustrate the use of the impact factor, assume an airport has normal SOx emissions of 1,000 kg/year. Assuming 12% of the jet fuel used at the airport is blended conventional/SAJF at a 50% blend (50% blend  Δf_ SOx = -0.375 and δΔf SOx,[S] Read the entire page →
From page 16... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 16 the LTO cycle power points. Line loss was accommodated in this analysis through its implicit inclusion in the published data. Read the entire page →
From page 17... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 17 Sp ec ie s En gi ne Co nv fu el SA JF bl en d% Re f # LT O pw r LT O EI n b le nd (a rb itr ar y un its ) Read the entire page →
From page 18... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 18 An uncertainty weighted least squares quadratic fit (Δf_EIn vs. blend%) Read the entire page →
From page 19... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 19 Table 6. The number-based emission index impact factor ER is defined as ERΔf_EIn = \| Δf_EIn_fit - Δf_EIn \|( ∗ ) Read the entire page →
From page 20... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 20 Table 6: Δf_EInavg, weight, Δf_EInfit, and associated ER blend% Δfavg, weight δ Δf_EIn ER 0 0 0 0 0 50 -0.48 0.10 -0.48 0.01 100 -0.66 0.33 -0.66 0.01 The fact that the curve in Figure 2 passes through the data and their associated ERs are always less than unity, reveals that the Δf_EInfit function is a good representation for the EIn impact factor data and is thereby validated. The fit coefficients (constant, linear term, quadratic term) Read the entire page →
From page 21... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 21 The impact on nvPM mass due to the SAJF for specific engines and their operating conditions is Δf_EIm = 𝐸ImPM,blend - EImPM,convEImPM,conv = 𝛼 ∗ 1 − 𝑏𝑙𝑒𝑛𝑑%100% + 𝛽 ∗ EImPM,ASJFEImPM,conv ∗ 𝑏𝑙𝑒𝑛𝑑%100% – 1 = 𝜑0 + 𝜑1 𝑏𝑙𝑒𝑛𝑑%100% 𝑤𝑖𝑡ℎ 𝜑0 = 𝛼 − 1, 𝜑1 = 𝛽 ∗ EImPM,ASJFEImPM,conv − 𝛼 . Read the entire page →
From page 22... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 22 Table 7: nvPM mass emissions data STEP 4 – Table 8 gives Δf_EImavg, weight for three values of blend%, with associated uncertainty. Δf_EIm is zero at blend%=0 with zero uncertainty, since the impact of alternate fuel is zero when there is no alternate fuel. Read the entire page →
From page 23... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 23 An uncertainty weighted least squares quadratic fit is performed using the uncertainties given in Table 8. The resulting values for the fit (Δf_EIm_fit) Read the entire page →
From page 24... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 24 Table 9: Δfavg, weight, Δf_EImfit, and associated ER blend% Δfavg, weight δ Δf_EImfit ER 50 -0.65 0.12 -0.65 0.00 100 -0.70 0.24 -0.70 0.00 The fact that the fitted curve passes through the data error bars in Figure 3 and their associated ERs are always less than unity, reveals that the Δf_EImfit function is a good representation for the EIm impact factor data and is thereby validated. The fit coefficients (constant, linear term, quadratic term) Read the entire page →
From page 25... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 25 The impact on NOx emissions due to the SAJF for specific engines and their operating conditions is 𝛥f_EINOx = EINOx,blend EINOx,convEINOx,conv = 𝛼 ∗ 1 − 𝑏𝑙𝑒𝑛𝑑%100% + 𝛽 ∗ EINOx,ASJFEINOx,conv ∗ 𝑏𝑙𝑒𝑛𝑑%100% – 1 = 𝜑0 + 𝜑1 ∗𝑏𝑙𝑒𝑛𝑑%100% (𝑤𝑖𝑡ℎ 𝜑0 = 𝛼 − 1, 𝜑1 = 𝛽 ∗ EINOx,ASJFINOx,con − 𝛼) Read the entire page →
From page 26... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 26 Sp ec ie s En gi ne ty pe Co nv fu el SA JF bl en d% Re f # Δf _E IN Ox Δf _E IN Ox _A v g δ NOx T63-A-703 JP-8 Fats & Grease 50 21 0 NOx T63-A-700 JP-8 FT GTL 50 21 0 NOx CFM56-7 JP-8 FT GTL 50 22 0 NOx CFM56-2 JP-8 FT GTL 50 22 0 NOx F117 JP-8 FT GTL 50 22 0 NOx TF33 JP-8 FT GTL 50 22 0 NOx PW308 JP-8 FT GTL 50 22 0 NOx T63-A-700 JP-8 HEFA 50 21 0 NOx CFM56-7 JP-8 HEFA 50 22 0 NOx CFM56-2 JP-8 HEFA 50 22 0 NOx F117 JP-8 HEFA 50 22 0 NOx TF33 JP-8 HEFA 50 22 0 NOx PW308 JP-8 HEFA 50 22 0 NOx JT9D-7R4G2 Jet A HVO 50 51 0 NOx GTCP85 Garret Honeywell APU Jet A1 UCO SPK 50 17 0 NOx CFM56-7B Jet A Bio-SPK 50 51 -0.05 NOx CFM56-7 Jet A1 FT-GTL 50 47 -0.0673 NOx T63-A-701 JP-8 Beef Tallow 100 21 0 -0.032 0.07233 NOx T63-A-703 JP-8 Fats & Grease 100 21 0 NOx T63-A-700 JP-8 FT GTL 100 21 0 NOx T63-A-700 JP-8 HEFA 100 21 0 NOx GTCP85 Garret Honeywell APU Jet A1 UCO SPK 100 17 0 NOx CFM56-7 Jet A1 FT-GTL 100 47 -0.1941 NOx MK113 APU Artouste Jet A1 FT-GTL 100 34 -0.030 STEP 4 –Table 11 takes selected parameters from Table 10 for further analysis. Table 11: NOx impact factors vs. Read the entire page →
From page 27... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 27 blend% Δf_EINOx_Avg δ 50 -0.0047 0.01643 100 -0.032 0.07233 Figure 4 shows a plot of Δf_EINOx, Avg vs blend% with associated uncertainties. This plot suggests that a constant function is the best fit to the data. Read the entire page →
From page 28... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 28 Figure 5: NOx impacts vs. blend%. Read the entire page →
From page 29... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 29 The fact that the error bars in Figure 5 overlap and their associated ERs are always less than unity, reveals that the Δf_EINOx function is a good representation for the EINOx impact factor data and is thereby validated. Illustrative example: To illustrate the use of the impact factor for NOx, assume an airport has normal NOx emissions of 1000 kg/year. Read the entire page →
From page 30... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 30 Table 13: CO emissions impact spreadsheet Species Engine Conv fuel SAJF blend% Ref # Δf_EI CO Δf_EI CO_Avg δ CO Combustor JP8 FT 50 44 -0.242 -0.129 0.119 CO PW2000 JP8 HRJ 50 20 -0.265 CO T63 JP8 FT shell 50 21 -0.087 CO CFM56-7 Jet A1 FT 50 47 0.007 CO T701-C JP8/JetA1 FT & HEFA 50 22 -0.059 CO Combustor JP8 FT 100 44 -0.402 -0.174 0.106 CO T63 JP8 FT shell 100 21 -0.258 CO T63 JP8 FT Rentech 100 21 -0.111 CO T63 JP8 HRJ R8 100 21 -0.129 CO T63 JP8 HRJ tallow 100 21 -0.114 CO T63 JP8 HRJ Came 100 21 -0.154 CO CFM56-7 Jet A1 FT 100 47 -0.085 CO T701-C JP8/JetA1 FT shell 100 22 -0.140 STEP 4 – Table 14 takes selected parameters from Table 13 for further analysis. Table 14: CO impact factors for selected blend%, with uncertainty blend% Δf EI CO δ 0 0 0 50 -0.129 0.0660 100 -0.174 0.1319 Read the entire page →
From page 31... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 31 Figure 6: CO impact vs. blend% Figure 6 shows a plot of Δf_EICO, Avg vs blend% with associated uncertainties. Read the entire page →
From page 32... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 32 Figure 7: CO impact vs. blend% with linear fit The original and fitted data along with an impact factor ER is given in Table 15. Read the entire page →
From page 33... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 33 The fit coefficients (constant, linear term) in the uncertainty weighted CO impact factor equation contain uncertainty. Read the entire page →
From page 34... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 34 STEP 2 AND STEP 3 – The UHC impact spreadsheet is given in Table 16 below. In the spreadsheet Δf_EIUHC denotes the UHC impact factors, and Δf_EIUHC, avg is the average of all Δf_EIUHC values recorded for blend%s of 50% and 100%. Read the entire page →
From page 35... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 35 Table 17 takes selected parameters from Table 16 for further analysis. Read the entire page →
From page 36... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 36 Table 17: UHC impact factors for selected blend%s, with uncertainty blend% Δf_EI UHC_Avg δ 0 0 0 25 -0.399 0.168 50 -0.140 0.219 75 -0.447 0.053 100 -0.257 0.053 Figure 8: UHC impact vs. blend% Figure 8 shows a plot of Δf_EIUHC, Avg vs blend% with associated uncertainties. Read the entire page →
From page 37... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 37 Figure 9: UHC impact vs. blend% with its functional fit The original and fitted data along with an impact factor ER is given in Table 18. Read the entire page →
From page 38... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 38 The fact that the error bars in Figure 9 overlap and their associated ERs are always less than unity, reveals that the Δf_EIUHC function is a good representation for the EIUHC impact factor data and is thereby validated. Illustrative example: To illustrate the use of the impact factor for UHC, assume an airport has normal UHC emissions of 1000 kg/year. Read the entire page →
From page 39... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 39 = 𝜑0 + 𝜑1 ∗ %% 𝑤𝑖𝑡ℎ 𝜑0 = 𝛼 − 1, 𝜑1 = 𝛽 ∗ EIHAPs,ASJFEIHAPs,conv − 𝛼 . Read the entire page →
From page 40... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 40 Table 20: HAPs impact factors vs. blend% blend% Δf_EI HAP_Avg δ 0 0 0 50 -0.159 0.296 75 0.161 0.173 100 -0.309 0.220 Figure 10 shows a plot of Δf_EIHAPs, Avg vs blend% with associated uncertainties. Read the entire page →
From page 41... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 41 Figure 11: HAPs impact vs. blend% The original and fitted data along with an impact factor ER is given in Table 21. Read the entire page →
From page 42... ... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 42 The fact that the error bars in Figure 11 overlap and their associated ERs are always less than unity, reveals that the Δf_EIHAPs function is a good representation for the EIHAPs impact factor data and is thereby validated. Illustrative example: To illustrate the use of the impact factor for HAPs, assume an airport has normal HAPs emissions of 1000 kg/year. Read the entire page →

From page 12...

... Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 12 4.0 Pollutant-Specific Analysis In the following sections the detailed analysis undertaken to quantify the impacts for the pollutant species SOx, nvPM N, nvPM Mass, NOx, CO, UHC, and HAPs is presented. 4.1 SOx The SOx emission indices (EISOx, blend)