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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 7 2.0 Emissions Impact Quantification Methodology The work described in this report is the second phase of ACRP 02-80. The first phase was publication of State of the Industry Report on Air Quality Emissions from Sustainable Alternative Fuel, which provides 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 State of the Industry Report and the emissions analysis tool are the two key products from ACRP 02-80. The analysis in this phase validated our expectations of emissions reductions when SAJFs are employed. It also provides the basis upon which the magnitude of these reductions can be estimated. The State of the Industry Report compiled data on emissions from the use of SAJF from 51 technical publications. Data from those publications were analyzed to determine, validate, and quantify pollutant-specific impact factors, which quantify the benefits. The impact factor for an emissions species is the change in the species emissions index (EI) caused by use of a SAJF blend; the fractional impact factor is the change in the pollutant emissions index caused by use of a SAJF blend divided by the pollutantâs emissions index for the conventional fuel. A pollutant-specific tabulation of all available emissions data associated with SAJF usage was included in Section 3.0. The aviation industry is in the early phase of developing and employing SAJF and as a result, the extent of emissions testing today is somewhat limited. The earliest tests were conducted using alternative fuels that would not meet todayâs SAJF specifications. Fuels that would meet present SAJF specification, hydrotreated esters and fatty acid (HEFA) fuels that meet the ASTM1655 Annex 1 specification, have been the predominant fuels tested. The earliest tests often used measurement schemes that are not as accurate as presently certified measurement methods. Some tests were conducted on combustor rigs or auxiliary power units (APU) rather than aircraft main engines and some were conducted on commercial engines while others used military engines. For those tests conducted using aircraft main engines, a single engine design (CFM56) was primarily used. These limitations constrained the range of factors that could be used as independent variables in the analysis. Similarly, limitations on the availability of detailed fuel composition for both conventional jet fuel and the alternative jet fuels in some tests restricted specific fuel components such as hydrogen content or aromatic composition from being used as independent variables. Despite these limitations, the project team developed quantitative relationships that will allow airports to estimate changes in the mass of emissions for all pollutants resulting from use of SAJF. The methodology for quantifying emissions impacts from SAJF employs six steps: STEP 1 of the impact plan identifies critical parameters that influence the positive or negative impact of burning SAJFs. Primary metrics include engine type, engine operating condition, fuel composition, blend percentages, atmospheric conditions, etc. Different authors and test campaigns focused attention on different metrics that quantify various emissions and the effects of different alternate fuels. No one study was sufficiently comprehensive to support impact analysis for all pollutant species of interest as a function of all salient metrics. The tabulated data reveals that in many cases the engine specific emissions are engine power and fuel type dependent. However, there is insufficient data to allow the engine-fuel-
Emissions Quantification Methodology Report: ACRP 02-80 Quantifying Emissions Reductions at Airports from the Use of Alternative Jet Fuel Emissions Quantification Methodology Report Page 8 power, specific dependency to be parameterized with any statistical significance. Furthermore, for airports to address the power dependency, they would have to provide their own fuel burn vs. power profiles for their airport. In order to avoid this complexity, the power dependency has been captured for the impacts analysis by developing a weighted average impact based on the International Civil Aviation Organization (ICAO) LTO cycle fuel burn values. The ICAO LTO cycle is designed to capture normal aircraft/airport operations and hence can be used to normalize typical power usage. A term to capture any baseline EI effect was not included due to the lack of consistent data. In the case of the fuel type dependency, the reported effect is found to be weak and the fuel specific data is insufficient to permit parameterization. As a result, the impacts analysis reported in this study does not specifically address fuel composition. However, by default its impact is incorporated into the uncertainty analysis for the pollutant-specific impact factors developed. This is also the case for engine type to engine type variability. Since all campaign data sets specify blend percent for the fuel blends studied, this parameter has been selected as the critical parameter to define impacts. STEP 2 of the impact plan devises a pollutant-specific emissions spreadsheet based on the metrics identified in Step 1 and quantifies the observed impacts, typically represented by percent changes in the emission indices. STEP 3 of the impact plan assesses the pollutant-specific data to determine the viability of performing a functional analysis per metric. A functional analysis depends on the range of data per metric. The greater the range, the greater the confidence in the functional relationship. For example, if the metric is blend percentage, emission data for a minimum of two blends is required for a linear relationship with a limited confidence factor. More than two data points are required to define a non-linear relationship. STEP 4 of the impact plan develops functional impact relationships for those species identified in Step 3 as viable candidates, i.e., having sufficient data to support the functional analysis. STEP 5 of the impact plan performs the pollutant-specific functional analysis. This consists of fitting functions that best represent the relationship between the parameters of interest such as blend percentage and impact factor. General linear and non-linear least squares methodologies are used to achieve the fitting.
