API PUBL 4605-1994 Investigation of MOBILE5a Emission Factors Evaluation of IM240-to-FTP Correlation and Base Emission Rate Equations《调查mobile5a排放系数 评价im240到ftp的相关性及基地发射速率方程》.pdf

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API PUBL 4605-1994 Investigation of MOBILE5a Emission Factors Evaluation of IM240-to-FTP Correlation and Base Emission Rate Equations《调查mobile5a排放系数 评价im240到ftp的相关性及基地发射速率方程》.pdf_第1页
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1、 - API PUBLU4605 94 8Bs 0732290 0535972 L49 m Investigation of MOBILE5a Emission Factors: Evaluation of IM240-to-FTP Correlation and Base Emission Rate Equations HEALTH AND ENVIRONMENTAL SCIENCES API PUBLICATION NUMBER 4605 JUNE 1994 American Petroleum InstitUte 1220 L Street, Northwest 4 Washington

2、, D.C. 20005 API PUBL*qbO5 94 0732290 0535973 085 Investigation of MOBILE5a Emission Factors Evaluation of IM240-to-FTP Correlation and Base Emission Rate Equations Health and Environmental Sciences Department API PUBLICATION NUMBER 4605 PREPARED UNDER CONTRACT BY: SIERRA RESEARCH, INC. SACRAMENTO,

3、CALI FORN IA PHILIP L. HEIRIGS ROBERT G. DULLA JUNE 1994 American Petroleum Institute API PUBL*4605 94 0732290 0535974 TLL 9 FOREWORD API PUBLICATIONS NECESSARILY ADDRESS PROBLEMS OF A GENERAL NA-. WITH RESPECT TO PARTICULAR CIRCUMSTANCES, LOCAL, STATE, AND FEDERAL LAWS AND REGULATIONS SHOULD BE REV

4、IEWED. API IS NOT UNDERTAKING TO MEET THE DUTIES OF EMPLOYERS, MANUFAC- TURERS, OR SUPPLIERS TO WARN AND PROPERLY TRAIN AND EQUIP THEIR EMPLOYEES, AND OTHERS EXPOSED, CONCERNING HEALTH AND SAFETY RISKS AND PRECAUTIONS, NOR UNDERTAKING THEIR OBLIGATIONS UNDER LOCAL, STATE, OR FEDERAL LAWS. NOTHING CO

5、NTAINED IN ANY API PUBLICATION IS TO BE CONSTRUED AS GRANTING ANY RIGHT, BY IMPLICATION OR OTHERWISE, FOR THE MANU- FACTURE, SALE, OR USE OF ANY METHOD, APPARATUS, OR PRODUCT COV- ERED BY LETTERS PATENT. NEITHER SHOULD ANYTHING CONTAINED IN ITY FOR INFRINGEMENT OF LETIERS PATENT. THE PUBLICATION BE

6、CONSTRUED AS INSURING ANYONE AGAINST LIABIL- Copyright Q 1994 American Petroleum Institute i API PUBL*i 50K)“ line represents the data that were used for TECH5 (Le., 1987 and later model years were analyzed for mileage below 50,000 and 1984-1986 model years were analyzed for mileage above 50,000); t

7、he “87+ (50K)“ line is the same as above except that the model year coverage was extended to include the 1983 model year for mileage above 50,000; and the “1983+“ line represents data from all 1983 and later model years. (The 1983 model year was considered in this analysis because that model year hi

8、storically has been used as a breakpoint between “developmental“ and standard technology.) It is clear that TECH5 is over-estimating the number of very highs and supers in the fleet beyond 75,000 miles. A final point related to EPAs development of emitter category growth rates for MOBILESa is that a

9、 different method was used for super emitters. For that category, the data were stratified into three model year groups: 1987+ for mileage below 50,000; 1983-1986 for mileage from 50,000 to 100,000; and 1981-1982 for mileage above 100,000. Further, because of the limited number of super emitters in

10、the fleet, all technologies were combined. Es-12 API PUBL*4605 94 0732290 0535995 746 1.2 1 r O 0 0.8 II ci t L Q, 0.6 e 3 v) + 0.4 I 0.2 O TECH5 87+ (c 50K)* 84-86 k 504 87+ ( 5OK) .,. t 1983+* - -.i - O 5 10 15 20 Odometer (1 0,000 miles) * Emltter fractloni bawd on Hammond data. Figure ES-5. Comp

11、afison of Very High + Super Emitter Fractions - TECH5 vs. Hammond Data for MPFIKL Vehicles This approach resulted in a step function increase in the number of super emitters at 100,000 miles from 1.7% to 3.7%. Based on a review of the procedures that EPA used to develop the emitter category emission

12、 rates and growth rates for MOBILESa, it is apparent that the data were analyzed in a subjective and inconsistent manner. Emission rates were generated in a completely different fashion than emitter growth rates, analysis methods differed by emitter category, and modifications to the methods to acco

13、unt for technology differences were not applied consistently when the emission rates and growth rates were estimated. ES-13 API PUBLx4b05 94 O732290 053599b b82 Alternative Methodoloev Because a number of assumptions used by EPA to develop the base emission rate equations for MOBILESa appear somewha

14、t questionable, an alternative analysis was performed in which HC and CO base emission rates were developed for 1983 and later MPFI/CL vehicles. Although not a detailed analysis, the evaluation provides an alternative to the MOBILE5a approach. The alternative method generally follows that developed

15、by EPA and demonstrates that with just a few seemingly minor changes (Le., basing the emitter category emission rates on 1983+ model years, and developing the emitter category growth rates with a regression technique that more appropriately reflected the influence of high mileage vehicles), the resu

16、lting base emission rates are significantly impacted. This is illustrated in Figure ES-6, which shows the HC emission rates predicted by TECH5 and the alternative analysis. As seen, the emission rates calculated by the two methods deviate substantially at mileages above 50,000. The 1983+ MPFIKL vehi

17、cle mean emission rates by vehicle mileage calculated from the Hammond data are also shown in the figure. These show much better agreement with the alternative analysis. Clearly, the base emission rates developed for MOBILE5a represent a worst-case scenario for emission control system deterioration.

18、 ES-14 API PUBL*4605 94 m 0732290 0535997 519 m n I I I TECH5 Alternative Analysis Hammond Data Q . -_- 15 v O 5 10 Odometer (I 0,000 miles) 20 Figure ES-6. Comparison of MPFIKL Exhaust Emission Rates - TECH5 vs. Alternative Analysis Methodology ES-15 API PUBL*4bOS 9Y m 0732290 0535998 455 m Section

19、 1 INTRODUCTION BACKGROUND EPAs emission factors model, MOBILESa, is being used increasingly as a regulatory tool for evaluating the impacts of policies and motor vehicle control programs. For example, MOBILE is used to evaluate compliance with enhanced I/M regulations and for conformity determinati

20、ons. Further, output from the model was used in the development of the Complex model which wili be used by refiners to determine if particular fuel formulations comply with the reformulated gasoline performance standards. Because of EPAs reliance upon the MOBILE senes of models, the American Petrole

21、um Institute (API) contracted with Sierra Research, nc. (Sierra) to perform an evaluation of MOBILESa, with particular emphasis on how inspection and maintenance programs are modeled. Subsequent to the completion of that effort*, API amended the contract and issued a revised statement of work author

22、izing the following work critique of the fuel and temperature adjustments developed by EPA to correct data collected using the IM240 emissions test procedure for variations in fuel and temperature relative to those specified for the Federal Test procedure W) ; explanation and critique of the correla

23、tions between emissions based on the IM240 test procedure and emissions measured on the FIT that were developed by EPA; evaluation and critique of the methodology used by EPA to develop the emission control system deterioration rates for MOBILESa; and assessment of the degree to which MOBLE5a predic

24、tions overestimate or underestimate actual in-use daa and recommendations for alternative methodologies to estimate in-use exhaust emission rates. * Superscripts denote references listed at the end of this report. 1-1 API PUBL+4605 94 W 0732290 0535999 391 = This report documents the additional anal

25、yses noted above and summarizes the resu1:s that were presented in the technical memoranda submitted to API during the course of this study. ORGANIZATION OF THE REPORT Immediately following this introduction, Section 2 provides a discussion of the IM240-to- FTP correlation. This includes an analysis

26、 of the fuel and temperature adjustments employed by EPA to account for variations between the lane conditions and the laboratory FTIP tests, an evaluation of the correlation procedure used by EPA, and a recommended altern- dive to that approach. Section 3 compares the exhaust emission and deteriora

27、tion rates from MOBILESa to the data that were used to develop those rates. In addition, IM240 d8ata from EPAs I/M test program in Mesa, AZ, are compared to those collected in Hammonti, IN. New correlation equations relating the IM240 results to the FTP for the Arizona data are also presented in Sec

28、tion 3, and the resulting FTP values are compared to the Hammond, IN, data. 1-2 API PUBL*4605 94 0732290 0536000 701 Section 2 IM240-TO-FIP CORRELATIONS BACKGROUND With the development of MOBILESa, EPA made a significant departure from the historical method of using its Emission Factors data base to

29、 develop exhaust base emission rate equations (Le., the non-UM emission rates input to the model). In previous versions of MOBILE, data used for the base emission rates were collected through a process often referred to as “surveillance“ testing, where vehicle owners are randomly contacted (usually

30、by letter) and asked to give up their cars for a week of testing. Over the years, EPA has become concerned that the vehicles they receive for surveillance testing are not representative of the in-use fleet, particularly with respect to the fraction of poorly maintained, high- emitting vehicles. This

31、 has been primarily attributed to a sample selection bias, e.g., if vehicle owners know that their car has been poorly maintained or has been tampered, they will not voluntarily submit it for emissions testing. To overcome sample bias concerns, EPA used IM40 emissions data collected during the initi

32、al two years of an inspection and maintenance (I/M) program in Hammond, IN, to develop the exhaust base emission rate equations for MOBILESa.* It was felt that this approach would provide an unbiased sample because vehicle owners had to participate in the program. However, because all of the exhaust

33、 emission relations (e.g., temperature corrections, speed corrections, etc.) contained in MOBILE are based on FTP testing with certification fuel (Indolene), a means to convert the IM240 data collected at the lane on tank fuel to an FT/Indolene basis was needed. This conversion process was a multi-s

34、tep procedure, consisting of the steps listed below. * Vehicles were tested in their first I/M “cycle“ and therefore the data represent emissions from a non-I/M fleet. 2-1 API PUBL*4605 94 0732290 0536001 648 Factors that accounted for the differences in ambient temperatures and fuel characteristics

35、 between conditions experienced during IM240 testing at the I/M lane and IM240 testing in the laboratory were developed from a subset of Hammond lane vehicles. Those factors were used to convert &l the Hammond lane IM240 data (tested with tank fuel) to a laboratory/Indolene IM240 basis. Correlation

36、equations between IM240 emissions measured in the lab on Indolene and FTP values in the lab on Indolene were developed from a sample of vehicles. These correlation equations were then applied to all of the Hammond IM240 data (adjusted for fuel and temperature differences) to put all data on an FTP/I

37、ndolene basis. In the application of the above correlation equations, residuals from the IM240-to-FTP regression analysis were randomly applied to the data. Although each of these steps is evaluated and discussed in detail below, it is helpful to first review the process on a single vehicle. As an e

38、xample, consider vehicle number 12612 from the Hammond data base, which was a 1985 multi-point fuel-injected, closed-loop (MPFIICL) vehicle tested on 8/9/90 with an odometer reading of 66,177 miles. The lane IM240 exhaust HC score for this vehicle was O. 18 g/mi. Applying the seasonal fuel/temperatu

39、re adjustment factor (to put the lane score on a lab/Indolene basis) gives: IM240LablIndo = 0.8229 * 0.18 g/mi = 0.148 g/mi. The IM240 lab/Indolene score is then used in conjunction with the IM240-to-FTP correlation equation: bglo(FTP - X) = b + m*Log,(IM240,In,) + res where X represents the cold start offset, b and m are the intercept and slope, respectively, from the regression analysis, and res is a randomly applied residual from the correlation 2-2

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