# Investigation of Techniques for High Evaporative Emissions Vehicle Detection:

Denver Summer 2008 Pilot Study at Lipan Street Station

Report Version 5

Prepared for:

U.S. Environmental Protection Agency

December 9, 2009 Revised December 15, 2011 through review processT:\Library\EPA-111215.docx ERG: 0218.02.002.001


### Investigation of Techniques for High Evaporative Emissi ons Vehicle Detection:

Denver Summer 2008 Pilot Study at Lipan Street Station

REPORT Version 5

as part of

Determine Percentage of High Evaporative Emi ssion Vehicles in the On-Road Fleet of Motor Vehicle Passenger Car and Light Tr ucks Pilot Program (CRC E-77-3)

Work Assignment 2-2

Submitted to:

Constance Hart U.S. Environmental Protection Agency 2565 Plymouth Road Ann Arbor, MI 48105

Submitted by:

Timothy H. DeFries Jim Lindner Sandeep Kishan Cindy Palacios Eastern Research Group, Inc. 3508 Far West Blvd., Suite 210 Austin, TX 78731

December 9, 2009 Revised December 15, 2011 through review processi Table of Contents

1.0 Introduction ............................................................................................................... 1- 1 1.1 Pilot Study Objectives....................................................................................... 1-2 1.2 Description of Pilot Study Tasks ...................................................................... 1-4 1.3 Target Population and Coverage ....................................................................... 1-5 1.4 Funding Partners and Cooperative Participants ................................................ 1-5 2.0 Background ............................................................................................................... 2-1 2.1 Findings from California RSD Pilot Project ..................................................... 2-2 2.2 Findings from Colorado DPHE ........................................................................ 2-5 2.3 RSD4000/4600 Data Acquisition and C oncentration Calculations .................. 2-6 2.4 Influences of Evaporative Emissions on Method A and B Calculations ........ 2-12 3.0 Data Collection ............................................................................................................. 3 -1 3.1 Sequence of Field Testing Procedures for the Pilot Study ............................... 3-2 3.2 Stratified Random Sample of Ve hicles for Field Testing ................................. 3-7 3.3 New Test Procedures for the Pilot Study ........................................................ 3-10 3.3.1 Modified California Method ............................................................... 3-11 3.3.2 Infrared Video Camera ....................................................................... 3-12 3.3.3 Evaluation of the Portable SHED ....................................................... 3-12 4.0 Analytical Methods ....................................................................................................... 4-1 4.1 RSD Emissions Instruments ............................................................................. 4-1 4.2 SEMTECH-G Analyzer for Portab le SHED Measurements ............................ 4-4 4.3 HC Sniffer for Modified California Procedure ................................................. 4-7 4.4 Infrared Video Camera ..................................................................................... 4-8 4.5 Management of Field Data ................................................................................ 4-9 5.0 Analysis ............................................................................................................... 5-1 5.1 Evaluation of Using the Infrared Video Camera to Detect High Evaps ........... 5-2 5.2 Evaluation of the Modified Californi a Method to Detect High Evaps ............. 5-3 5.3 Evaluation of Using RSD to Detect High Evaps .............................................. 5-5 5.3.1 RSD Evap Index 1 Description ............................................................. 5-5 5.3.2 Paired RSD and PSHED Observations ................................................. 5-8 5.3.3 Prediction of PSHED Value Using RSD Evap Index 1 ...................... 5-10 5.3.4 Prediction of PSHED “High Evap” Proba bility Using Evap Index 1 . 5-11 6.0 References ............................................................................................................... 6-1 Appendix A Data Packet Appendix B Stratified Sampling Appendix C California Evaporativ e Visual Inspection Method Appendix D Participating Vehicle Data Appendix E Selection RSD Data Appendix F Conditioning Drive Data Appendix G Measurement RSD Data Appendix H PSHED Data Appendix I Modified California Method Data Appendix J Driver Interview Information Appendix K I/M Gas Cap Inspection Resultsii List of Tables

Table 3-1. Expected High Evap Fracti ons Using California RSD Data ................................... 3-8 Table 3-2. Random Number Thresholds for Soliciting at the Lipan Station ............................ 3-9 Table 3-3. Field Method Eval uation Stratified Sampling Design for RSD HC Bins ............ 3-10 Table 4-1. ESP RSD-4000 Instru ment Specifications ............................................................. 4-3 Table 4-2. SEMTECH-G Measurem ent HC Specifications .................................................... 4-6 Table 4-3. SEMTECH-G Ambien t Air Specifications ............................................................ 4-7 Table 5-1. Comparison of PSHED and MCM Overall Results ............................................... 5-4 Table 5-2. Counts of High Evap Designations ...................................................................... 5-12

List of Figures

Figure 2-1. ASM CO vs. RSD CO .............................................................................................. 2 -3 Figure 2-2. ASM NO vs. RSD NO ............................................................................................. 2- 3 Figure 2-3. ASM HC vs. RSD HC ............................................................................................... 2 -4 Figure 2-4. Reported RSD4000 HC on the Audit Tr uck with Induced Evaporative Emissions 2-6 Figure 2-5 Time Histories with Zero Evaporative Emissions and 1100 ppmC 3 Tailpipe HC Emissions ..................................................................................................................... .... 2-8 Figure 2-6. Pollutant Attenuations with Zero Evaporative Emissions and 1100 ppmC 3 Tailpipe HC Emissions Versus CO 2 with Regression Lines Superimposed .................................. 2-9 Figure 2-7. Time Histories with 15 sc fh Evaporative Emissions and 1100 ppmC 3 Tailpipe HC Emissions ..................................................................................................................... .. 2-11 Figure 2-8. Pollutant Attenuations with 15 scfh Evaporative Emissions and 1100 ppmC 3 Tailpipe HC Emissions with Regr ession Lines Superimposed ...................................... 2-12 Figure 2-9. Pollutant Attenuations with No Evaporative Emissions and 1100 ppmC 3 Tailpipe HC Emissions with Methods A and B Lines Superimposed ......................................... 2-13 Figure 2-10. Pollutant Attenuations with 15 scfh Evaporative Emissions and 1100 ppmC 3 Tailpipe HC Emissions with Methods A and B Lines Superimposed ........................... 2-14 Figure 3-1. Vehicle Testing Flow .............................................................................................. .. 3-4 Figure 3-2. Comparison of 15-Minute PSHED and 60-Minute LSHED Measurements ......... 3-15 Figure 4-1. Typical On-Roa d RSD-4600 Set-Up ........................................................................ 4-2 Figure 4-2. HC Sniffer ....................................................................................................... ......... 4-7 Figure 4-3. FLIR GasFindIR Gas Detection Video Camera ....................................................... 4-9 Figure 5-1. RSD Evap Index 1 and PSHED Values (Speed is approximately 12 mph) ............ 5-9 Figure 5-2. Linear Correlati on of PSHED and Transforme d RSD Evap Index 1 ..................... 5-11 Figure 5-3. RSD Evap Index 1 and PSHED Values ................................................................. 5-121-1 

### 1.0 Introduction

EPA is currently developing the MOVES mobile sources inventory model. As part of that effort, EPA needs to be able to model the evap orative emissions of gasoline-powered on-road vehicles. Evaporative emissions occur when volat ile components of gasoline are emitted or when raw gasoline leaks from the fuel system and the evaporative emissions control system. To meet the evaporative emissions modeling needs of the MOVES model, EPA, with the support of the Coordinating Research Council (CRC), is conducting studies to quantify fleet evaporative emissions. Ultimately, EPA would like to know th e distribution of the mass of evaporative
emissions across all vehi cles in the fleet.

This project follows the CRC projects looking at aging enhanced ev aporative emission
vehicles. E-77 Pilot and E-77-2 we re laboratory testing studies wh ich looked at ethanol and RVP fuel effects as well as implanted leak effects on different laboratory test procedures to capture evaporative emissions. The implanted leak data i ndicates there may be significant effects from small leaks which can multiply in the invent ory. This follow-on study can shed light on determining how often the leaks or “High Evap” are found in the fleet.

The effort begins by concentrating on the fleet vehicles that have high evaporative emissions (High Evaps). Initiall y, the objective is to find the pe rcentage of High Evaps in the average fleet of on-road motor vehicle passenger cars and light-duty trucks. Our initial estimate is that High Evaps are 1% of the gasoline-fueled vehicles in the fleet . The remaining 99% of gasoline-fueled vehicles in the fleet also ha ve evaporative emissions , but their evaporative
emissions are low.

This work assignment was in support of the EPA’s National Portable Emissions Measurement System (PEMS) Deployment contr act, and is intended to serve as a research project designed to develop methods to estimate evaporative emissions from light-duty vehicles. Innovative methods for measuring and testing real-world evaporat ive emissions were studied and procedures were developed, to al low the evaporative emission testi ng of a larger fleet at a later
date.

In response to recommendations from th e scientific community and interested stakeholders, EPA and the CRC are continuing to collect data designed to improve the methods and tools used to estimate evapor ative emissions from the light-dut y vehicle fleet. This data collection effort includes this pilot test program, which was designed to develop a quick, inexpensive test procedure to quantify evapora tive emissions from the light-duty fleet in an Inspection Maintenance (IM) styl e setting. The target populati on for the methodol ogical pilot1-2 was 50 to 100 vehicles in the Denver area. Ve hicles were screened for high evaporative emissions using a newly developed technique, and then subjected to a battery of evaporative tests
to determine both the effectiveness of each short te st vis a vis the other proposed short tests, and the standard laboratory evaporative SHED test.

An important focus of this study was to i nvestigate a number of options for measuring evaporative emissions. The primary requirement s in the work assignment specified that the screening method be non-intrus ive, quick, inexpensive, not require owner cooperation, and correlate well with accepted evaporative measur ement techniques, i.e. Sealed Housing for Evaporative Determination (SHED) tests. Give n these criteria, the method which appears to hold the most promise is use of remote-sensing devices (RSD).

1.1 Pilot Study Objectives

The goal of the project’s initial effort is to estimate the percentage of high evaporative emissions vehicles in the on-road fleet of ga soline-powered passenger car s and light-duty trucks. Specifically, the primary question is:

What fraction of the fleet is made up of high evaporative emissions vehicles?

A large field effort to answer this pr imary question immediately encounters two problems. First, using the standard method to m easure the evaporative emi ssions of vehicles is expensive, time-consuming, and requires special te st facilities – speci fically, a standard laboratory SHED. Second, there is not a clear, well-accepted de finition of “high evaporative emitters.” To make it practical to answer the pr imary question in a field testing environment, the primary question can be re-stated in terms of two secondary questions:

A. What field method can serve as a practical and substantially accurate method of identifying high-emitting evaporative emissions vehicles (High Evaps)? B. What fraction of the fleet is made up of High Evaps as defined by the above field method?

The primary focus of this pilot study was to answer Question A. The primary focus of subsequent studies will be to answer Question B. In summary, the effort to determine the percentage of the fleet that is made up of High Evaps is made up of two studies:

1) The Pilot Study – The pilot study is the subject of this report. The data from the pilot study will be used to develop the me thods, procedures, and design to be used in the main study. The conclusion of this pilot study was the development of a1-3 detailed work plan for a larger study to be conducted in a non-IM area that would use the testing methodology identi fied in this pilot. 2) The Main Study – The main study is the large-scale field study and is the subject of a future work assignment to determin e the fraction of High Evaps in the fleet. This kind of study could include the use of Remote Sensing Data (RSD) data from a large on-road program to estimate the fraction of high emitters in the fleet using the relationships developed in the pilot study.

The pilot study was conducted for the purposes of refining procedures for the main study. Specifically, the pilot study was to determine wh ether the portable SHED should be used in the main study as a field version of the standard laboratory SHED to measure hot-soak and gross liquid leak emissions. The following questions were investigated in the pilot study:

a) How well do the results of the portabl e SHED method agree w ith the results of the standard laboratory SHED method? Wh at are the characteristics of portable SHED testing for measuring the evaporative emissions of vehicles in the field? This includes issues such as ease of imp lementation, cost, number of vehicles tested in the portable SHED per da y, level of personnel necessary, and measurement precis ion and accuracy.

b) Can portable SHED measurements be pe rformed in a way such that the results can be used to estimate the distributi on of evaporative emissions of the fleet?

c) What is the approximate fraction of the fleet that is made up of high evaporative emissions vehicles?

d) What are the characteristics of thre e methods (RSD, modifi ed California method, infrared video camera) for screening vehicles as High Evaps?

- What are the accuracy characteristic s (four-quadrant, true-positive, and false-positive) of the screening met hods for identifying high evaporative emitters? - What are the practical characterist ics of the screening methods? This includes issues such as ease of implementation, cost, time to complete one test, level of personnel necessa ry (both quantity and skill).

e) Based on the experience of the pilo t study, what refinement s or modifications would be considered for the design of a larger study?

In order to answer the ques tions above, a test proce dure and sampling plan were developed to characterize the high-emissions ta il of the distribution of evaporative emitting vehicles in the relatively new fl eet of aging enhanced evaporat ive emissions on-road light-duty
motor vehicles. The current fleet consists of ve hicles with newer enhanced evaporative emission1-4 technologies, which are now aging and have a pote ntially different incide nce of high evaporative vehicles in the fleet than prev ious technologies at similar ages . No frequency data currently exists on the range of higher evaporative emi ssion vehicles for these newer technologies.

1.2 Description of Pilot Study Tasks

In this work assignment, ERG conducted a pr oject to develop a sampling plan and test procedures for identifying vehicles with high evaporative emissions. In this pilot study, a number of technologies and ideas were e xplored, including non- intrusive RSD-style measurements, identification of evaporative leaks using a hydrocarbon sniffer device, and portable SHED (PSHED) measurements. In ad dition to those intrus ive and non-intrusive methods, technologies used in other industries were investigated to determin e if other tools could
be of use in the measurement of mo bile source evaporative emissions.

Field work for this pilot study was conduc ted in July and August 2008 in Denver, Colorado, in collaboration with the Colorado De partment of Public He alth and Environment (CDPHE). CDPHE has recently done work meas uring evaporative emissions using RSD, and they also have facilities that allowed official laboratory SH ED tests to be performed during the pilot study on a subset of the vehicles which had PSHEDs.

This study was preceded by the Pre-Testing study. The pre-tes ting investigation was performed on simulated high evaporative emissi ons vehicles to develop field methods for detecting High Evaps and measuring their evapora tive emissions. This work has been reported separately [1].

This study was a field method evaluation. Te sting on 85 vehicles that were recruited from the general public was used to develop and evaluate vehicle se lection and emissions
measurement. This work is the focus of this report.

The key variables that were su rveyed or measured include:

 Vehicle identifiers: License plate and Vehicle Identification Number.

 Vehicle description: Mo del year, make, model, and odometer reading.

 Vehicle usage and maintenance hist ory through a vehicle owner survey.

 Fuel type was assumed from local area fuels.

 Time trace of cumulative HC concentrati on of the air inside the portable SHED after a vehicle’s engine is turned off and the portable SHED doors are sealed [6]1-5  Measured values of evaporative emissions vehicle screening methods:

 Remote Sensing Device HC measurement, and HC concentration relative to CO 2 concentration

 Modified California Method (Under-hood vi sual inspection and electronic HC vapor leak detector inspection)

 Infrared video camera

1.3 Target Population and Coverage

The target population includes all gasoline-powered light-duty vehicles and trucks. Lightduty vehicles have gross vehicle weight ratings of less than 8 500 lbs. Light-duty trucks are trucks with gross vehicle weight ratings of less than 8500 lbs. Passenger cars and light-duty trucks form the majority of the on-road moto r vehicle fleet. Nationa lly, they account for 96.6%
of the on-road vehicle fleet a nd 89.0% of the total on-road vehi cle miles traveled. Heavy-duty
vehicles account for the remainder of the on-road vehicle fleet and the on-road vehicle miles
traveled.

The geographical area used fo r pre-testing and this study was Denver, Colorado. Denver was chosen for several reasons. The Colorado Depa rtment of Public Health and Environment, which is located in Denver, operates a laborator y SHED, runs the state’ s inspection/maintenance (I/M) program, and runs the state’s on-ro ad RSD measurement program. Those CDPHE resources were used in the pilot study. The Lipa n Street I/M inspection station was used as a convenient source of private vehicles to solici t for the pilot study. Finally, the team that originally developed the RS D technique is located at the University of Denver.

1.4 Funding Partners and Cooperative Participants

Funds were contributed by two government part ners and one industry partner. The first government partner is the Assessment & Stan dards Division within the EPA Office of Transportation and Air Quality (OTAQ) and the second partner is the Colorado Department of Public Health and Environment (CDPHE). The industry advisor is the Coordinating Research Council (CRC), a nonprofit research organizatio n whose members include the American Petroleum Institute (API), the Society of Auto motive Engineers (SAE), General Motors, Ford Motor, Chrysler, Toyota, M itsubishi, Nissan, Volkswagen, and Honda. The Colorado Department of Public Health and Environmen t supported EPA’s test program by providing RSD equipment and staff to operate the equipment to support the RSD portion of the test program.2-1 

### 2.0 Background

Evaporative emissions from gasoline vehicles have been evaluated and regulated since the early 1970s. Gasoline vehicles have eva porative emissions contro l systems that control excessive evaporative emissions, which are usually gasoline vapors but can also be evaporated liquid gasoline if liquid leaks are present. When these systems or the gasoline delivery system of a vehicle malfunction, excessive evaporative emi ssions can be emitted. The mass of evaporative emissions from individual vehicles has been qua ntified in previous st udies [2, 3, 4], but the frequency of vehicles in such a condition in the general population has only been estimated based on limited data [2, 4, 5].

The Coordinating Research Council Real World Group has been conducting permeation evaporative emission testing in the E-77 and E- 77-2 programs. In the pilot E-77 program the permeation test procedure was refined before usi ng it in a larger program. Most of the vehicles were specifically recruited as aging enha nced vehicles, model years 1996-2000. Three preenhanced vehicles and one newer, near-zero emi ssions vehicle were also tested. A focus was on non-ethanol fuel looking at both 7 and 9 RVP. The program also looked at 24-hour diurnals at the traditional temperature range of 65-105  F and a higher temperature diurnal of 85-120  F. A
subset of the vehicles was tested for 72-hour diurnals. The higher temperature diurnal data indicated that the predictions that hydrocarbon emissions double every 10  C was correct and therefore, no further investigative testing was necessary. There were, however, unexpected findings for the influence of fuel volatility (RVP).

One of the aging enhanced vehicles had an im planted leak. The series of tests were run both before and after implanting the leak. This was accomplished by making a small hole in the evaporative control system. Th e size of the hole, 0.02 inch eq uivalent diameter, was the minimum detectable size necessary for an on-board diagnostic (OBD) code to flag. The laboratory testing results show the resulting hyd rocarbon emissions to be several orders of magnitude larger with the implanted leak. This indicates a potential impact for the emissions inventory, establishing the need to define the rate of occurrence of “leakers” in the in-use fleet. Such implanted leaks can be in liquid or vapor form.

Vapor leaks can also have an impact on the inventory. Traditional evaporative emissions testing, as well as the current E-77 testing, has shown a range of evaporative emissions, particularly with aging vehicles. The higher em ission levels (but lower than the gross liquid “leakers”) are associated with slow vapor leaks possibly occurr ing as the system ages. The enhanced evaporative emission technology is now starting to age, and we do not have2-2 information on the number of higher emission vehi cles in the fleet. The High Evap occurrence rate is anticipated to be much lower than in the past, but leaks do occur.

Previous E-77 testing has confirmed that l eaks, both liquid and vapor, can be an important part of any hydrocarbon inventory. The missing piece of information is how often the leaking vehicles occur. A comprehensive progra m for finding the quantity of these vehicles in the existing fleet has not been attempted since th e American Petroleum Institute “Raw Fuel Leak Survey in I/M Lanes” in 1998 [2], or the Calif ornia Bureau of Automotive Repair “Evaporative Emission Impact of Smog Check” in 2000 [4]. Th e current fleet consists of aging enhanced evaporative emissions vehicles which were not part of or still too new in the older studies.

2.1 Findings from California RSD Pilot Project

Recent data collected in the Ca lifornia RSD Pilot project [7] suggest that the tailpipe HC
channel of the RSD instrument used in that st udy, the ESP Accuscan 4000, may be influenced by a vehicle’s evaporative emissions, which are HCs.

The RSD instrument uses a light beam shin ing across the roadway to measure pollutants in a vehicle’s tailpipe plume. The instrument has HC, CO, NO and CO 2 channels. In the California study, a few days to several months af ter vehicles were measured by the on-road RSD instrument, a subset of the vehicles received their regular state insp ection program tailpipe emissions test, known as the Accel eration Simulation Mode (ASM) te st. Analysis of bins of the 76,982 paired RSD and ASM results showed a quite linear relationship for CO and NO when the logit 1 of the ASM failure rate was plotted agains t the natural log of the RSD concentration. Figures 2-1 and 2-2 show the relationships for CO and NO. Straight line fits of the trends and 95% confidence limits on the individual points are included. The upwar d trend in both plots shows that, on the average, vehi cles that have higher RSD tailp ipe concentrations were more likely to fail their state tailpipe emissions inspection for the same pollutant.

1 The logit (x) = ln (x/(1-x)), where x is a fraction between 0 and 1. In this case, the logit represents the “log of the odds of failure”.2-3 Figure 2-1. ASM CO vs. RSD CO

-6 -5 -4 -3 -2 -1 0

-4 -3 -2 -1 0 1 2 3 ln(RSD CO) (%)logit (ASM CO Fail Fraction)

Figure 2-2. ASM NO vs. RSD NO

-5 -4 -3 -2 -1 0 1

3 4 5 6 7 8 91 0 ln(RSD NO) (ppm)logit (ASM NO Fail Fraction)2-4 Figure 2-3. ASM HC vs. RSD HC

-5 -4 -3 -2 -1 0 1

2345678 9 ln(RSD HC) (ppm)logit (ASM HC Fail Fraction)

However, when the same type of plot is made for the analysis of bins of the paired data for HC, two different regions of behavior ar e observed. See Figure 2-3. In the low RSD HC region (ln RSD HC < 6), the ASM HC fail rate follo ws the trends seen for CO and NO. That is, vehicles with higher and higher on-road RSD HC c oncentrations are more and more likely to fail the inspection station ASM HC tailpipe test. Th e data fall on a relativ ely linear trend as approximated by the solid red line. However, on th e right side of the pl ot (ln RSD HC > 6), a second, different trend is obser ved. Here, the data points reac h a plateau (logit ASM HC fail fraction = -1), which means that about 27% of the vehicles fail the tailpipe ASM HC tailpipe test even though their on-road RSD HC concentratio ns range from 400 ppm up to 4000 ppm. That is, in the high RSD HC region, ever increasing RS D HC concentrations do not translate into an ever increasing probability of failing the inspection stat ion ASM HC tailpipe test.

One explanation, but perhaps not the only expl anation, for the observed HC behavior is the presence of High Evaps in the fleet samp le. High Evaps could pass the inspection station ASM HC test because the ASM test is a tailpip e test, and therefore it is not influenced by evaporative emissions, which are emitted only from the fuel and fuel vapor handling systems of vehicles – not from their tailpipes. However, when a vehicle drives on the road, evaporative emissions can be detected with tailpipe emissi ons in the plume behind the vehicle. Depending on2-5 how the RSD instrument processes the data obtain ed from its light beam , evaporative emissions could increase the reported RSD HC readings over what one would expect on the basis of tailpipe emissions alone. If the evaporative emi ssions are very high, the increase could be large enough to cause points on the linear trend in Figure 2-3 to be moved to th e right of the expected trend depicted by the red line.

Since evaporative emissions were not measur ed in the California RSD Pilot study, this explanation of the trends in Figure 2-3 is unconfirmed. Nevertheless, the explanation makes sense. In addition, Don Stedman, the developer of the RSD technique, is familiar with the data processing algorithm of the Accuscan-4000 inst rument and believes that its high RSD HC readings may be influenced by High Evaps. Sinc e algorithms of other RSD instruments may be less sensitive to evaporative emissions, this find ing, if confirmed, could l ead to the development of new RSD processing algorithms that could specifically target the on-road measurement of evaporative emissions.

2.2 Findings from Colorado DPHE

CDPHE has empirical evidence that the RSD 4000 instrument can detect evaporative emissions and liquid gasoline leaks. CDPHE has been involved with remote sensing devices since 1996. The Department’s RSD experience spans several generations of ESP’s RSD technology (RSD2000, 3000, 4000, and 4600). In recent years, CDPHE and the Regional Air Quality Council (RAQC) have participated in an RSD-based, high hydrocarbon emitter identification and repair pilot program funded by the Congestion Mitigation and Air Quality Improvement Program (CMAQ). The goal of the study was to use RSD to find vehicles emitting more than 550 ppm HC as hexane from the tailpi pe. An unexpected result of the effort was the apparent ability of the RSD4000 instrument to find evaporative emissions and gasoline liquid leakers. Several RSD-identified high HC emitters brought to state IM Tech Centers for an IM240 confirmatory exhaust emissions test easily pa ssed EPA IM240 final standards but were found to have gasoline vapor and/or liquid leaks.

A simple, semi-quantitative follow up e xperiment by CDPHE staff used an RSD4000 instrument with metered amounts of propane, unmetered amounts of liquid gasoline, and known
concentrations of simulated exhaust from an RS D audit truck. This experiment resulted in a small empirical dataset that seemed to corr oborate the claim by state IM Technical Center personnel that the RSD was identifying evaporativ e and liquid leaks. The data shown in Figure 2-4 were obtained using the audit truck. This in formation illustrates that RSD technology appears to detect evaporative emissions. Both sets of RSD data introducing an evaporative emissions2-6 problem, gas cap removal 2 and canister disconnection, are noticeably higher than the “no problem” RSD data. A second, very brief qual itative investigation using unknown amounts of liquid gasoline, an IM240-passing 2000 model year passenger vehicle, and an RSD3000 instrument produced only invalid RSD readings, which indicated th ere might be something other than high exhaust emissions.

This disparity between the RSD4000 and RSD3 000 results prompted an inquiry to Don Stedman of the University of Denver. He clar ified that the calculat ions used by the RSD3000 instrument were specifically designed to see only tailpipe HC, but the RSD4000 instrument and its offspring, the RSD4600, could theore tically see HC from any source.

Figure 2-4. Reported RSD4000 HC on the Audit Truck with Induced Evaporative Emissions

2.3 RSD4000/4600 Data Acquisition a nd Concentration Calculations

Some background on the operation and calcula tions of the RSD4000/4600 instrument is useful for understanding the c onditions under which RSD might be able to detect vehicle evaporative emissions. While the de tailed calculations that are us ed in RSD instrument software

2 The gas cap removal shows minimal impact on HC concentration levels compared to disconnecting the canister. This compares to the CRC E-77 lab data on implanted leak s. There was a negligible increase in HC emissions when a leak was implanted in a gas cap on an ORVR equipped vehicle compared to one which did not have ORVR or a leak implanted near the canister or the top of the tank.2-7 are proprietary to ESP, ESP personnel have prov ided some general info rmation about how their current instrument operates and calc ulates emissions concentrations.

The pollutants in the exhaust gas coming from th e tailpipe of a vehicle are assumed to be
well mixed and are assumed to be released from onl y the tailpipe outlet. It is also assumed that
after emission from the tail pipe, the HC, CO, NO and CO 2 all disperse into the ambient air at the

same rate.

When a vehicle drives past the RSD instrument, the RSD light beam passes through a portion of the dispersing tailpipe plume. The in strument measures the attenuation of IR or UV light caused by the presence of the chemical speci es in the plume 50 times at 10ms intervals. The size of the attenuation is the product of the concentration and the path length and therefore has units of ppm-cm for HC and NO and %-cm for CO and CO 2 . If the only source of the pollutants is the tailpipe exhaust, and if the am bient air has no pollutant s, then the ratios of attenuations of any two pollutants will be cons tant for multiple readings taken in a vehicle’s exhaust plume even though the pollutant concentra tions change as the plume disperses. Figure 2-5 shows example time traces of th e attenuations of HC, CO, NO, and CO 2 as recorded by an
RSD instrument for Test Set 18 and VDF 5 from the Summer 2008 Pre-Testing study [1]. The plot clearly shows that for this case, which does not have evapor ative emissions, the attenuations move up and down together with time. That is, ignoring the different vert ical scales, the time traces of all four pollutant s have very similar shapes.2-8 Figure 2-5 Time Histori es with Zero Evaporative Emissions and 1100 ppmC 3 Tailpipe HC Emissions

0 50 100 150 200 250 300 350 400 450 0 5 10 15 20 25 30 35 40 45

Time (msec)Pollutant Absorbance HC (ppm-cm) / 100 CO (%-cm) CO2 (%-cm) NOx (ppm-cm) / 100

However, the purpose of the RSD instrument is not to determine the time dependence of the pollutant attenuations but instead is to dete rmine the exhaust concentration of the pollutants at a given moment in time. To arrive at an estimate of the pollutant exhaust concentrations requires two steps. In the first step, the instru ment uses the assumption that exhaust pollutant gases disperse together from the common exhaust point. If this is tr ue, then plots of the attenuations of one pollutant against the atte nuations of any other pollutant should produce a straight line passing th rough the origin. Figure 2-6 show s the HC, CO, and NO attenuations plotted against the CO 2 absorbance for the data shown in Figure 2-5. The plot shows that the lines are quite straight with little scatter and pass near the origin.2-9 Figure 2-6. Pollutant Attenuations wi th Zero Evaporative Emissions and 1100 ppmC 3 Tailpipe HC Emissions Versus CO 2 with Regression Lines Superimposed

5 10 15 20 25 30 35 40 45 0 5 10 15 20 25 30 35 40

CO2 (%-cm)Pollutant Absorbance HC (ppm-cm) / 100 CO (%-cm) NOx (ppm-cm) / 100

If ambient pollutants are present before the vehicle passes by, then the instrument will also pick up contributions to the attenu ations from the background. The RSD4000/4600 instrument attempts to correct for the backgroun d by taking a measurement of all four pollutants just before the vehicle blocks the beam. Thes e “front bumper” backgr ound attenuation values are subtracted from the raw tailpipe plume a ttenuation values to arrive at the backgroundcorrected attenuation values that are used to calc ulate the tailpipe emissions concentrations. The 50 10ms attenuation observations provided with each RSD beam block and those plotted in Figures 2-5 and 2-6 have already had the background correction appl ied. Thus, if the background correction is accura te, plots of HC, CO, and NO attenuations versus CO 2 attenuation should always pass through the origin. However, we have observed that even for vehicles with no evaporative emissions the regression lines th rough the data almost never pass through the origin and generally tend to have pos itive pollutant attenuation intercept values.

Our understanding is that the RSD3000 calcu lation method (also known as Method B) uses the slope of the regression of the HC attenuation versus CO 2 attenuation to calculate the
concentration of HC relative to CO 2 . On the other hand, the RS D4000 calculation (also known2-10 as Method A) uses the sum of the HC attenuations divided by the sum of the CO 2 attenuations to
determine the concentration of HC relative to CO 2
.
The second step in the calculation uses co mbustion stoichiometry. The RSD instrument calculations assume a particular composition for gasoline that contains carbon, hydrogen, and oxygen which when combusted with air will produce a mixture of HC, CO, NO, and CO 2 . The balanced chemical equation for this reaction is then used to convert the relative pollutant concentrations as determined from the slopes of the 50 10ms attenuation measurements of the
RSD instrument into estimates of the absolute pollutant concentrations by assuming that the gasoline in the vehicle has approximately the same composition as the average gasoline used for the calculations. This second step is us ed both for Method A and Method B calculations.

The RSD4600 instrument uses the measur ed attenuations of HC, CO, NO, and CO 2 plus the combustion stoichiometry of the combustion of typical gasoline to arrive at the reported RSD concentrations for the four pollutants. Base d on 29,723 RSD measurements made in San Antonio in November 2008, the RSD4600’s reported concentr ations always obey the following equation:

[CO 2 ] = 150537.66 - 0.7168 * [CO] - 0.3011 * [HC] - 0.3584 * [NO]

where: [CO 2 ] is the CO 2 concentration in ppm, [CO] is the CO concentration in ppm, [HC] is the HC concentration in ppmC 3 , i.e., ppm Propane, and [NO] is the NO concentration in ppm.

Now we need to consider the situation wh en evaporative emissions are present. Evaporative emissions on a vehicle are predomin antly HC (some oxygenates may be present if the fuel contains them) and can be emitted from the vehicle from one or multiple sources but the source of evaporative emissions will never be the tailpipe. Accordingly, the characteristics of dispersion of evaporative emissions will be different from the dispersion of the tailpipe emissions. Evaporative emissions can be emitted as vapor or as leaking liquid gasoline. Since the RSD instrument can detect only vapor, liquid l eaks must at least partially evaporate for an
RSD instrument to detect them. A vehicle’s evaporative emissions plume will not necessarily intermingle with its ta ilpipe plume. However, it may pass through the RSD instrument’s light beam at the same time that the tailpipe plum e is passing through the light beam. When an evaporative emissions plume does th is, it will cause the HC attenuati on to be larger than it would be if the evaporative emissi ons were not present.

Figure 2-7 shows the time series of the attenua tions for the audit truck for Test Set 18 and VDF 11 when evaporative and tailpipe emissions were forced to occur. In this case, the shapes2-11 of the time series for CO, NO, and CO 2 are similar to each other, but the shape of the time series for HC is different. Comparison of the HC trend with the CO, NO, and CO 2 trends indicates that the HC attenuation has a large increase beginning at about 100ms. This trend is much more
obvious when the attenuations for the tim e series are plotted versus the CO 2 attenuations as shown in Figure 2-8. While the CO versus CO 2 and NO versus CO 2 plots remain as straight lines, the HC versus CO 2 curve shows an increase in HC attenuation relative to CO 2 attenuation and also shows a non-linear behavior. The quantifi cation of this non-linear behavior can be used to develop an RSD evapor ative emissions index.

Figure 2-7. Time Histor ies with 15 scfh Evaporat ive Emissions and 1100 ppmC 3 Tailpipe HC Emissions

0 50 100 150 200 250 300 350 400 450 -20

0 20 40 60 80 100

Time (msec)Pollutant Absorbance HC (ppm-cm) / 100 CO (%-cm) CO2 (%-cm) NOx (ppm-cm) / 1002-12 Figure 2-8. Pollutant Attenuations with 15 scfh Evaporative Emissions and 1100 ppmC 3 Tailpipe HC Emissions with Regression Lines Superimposed

0 10 20 30 40 50 60 -20

0 20 40 60 80 100

CO2 (%-cm)Pollutant Absorbance

HC (ppm-cm) / 100 CO (%-cm) NOx (ppm-cm) / 100

2.4 Influences of Evaporative Emissi ons on Method A and B Calculations

Methods A and B use two differe nt calculations that are bot h based on the same 50 10ms absorbance pairs to arrive at different estimat es of vehicle HC concentrations. Based on our understanding of the calculations, we believe that the difference between the reported values by the two methods provides an initial RSD evapora tive index. This subsection describes why this might be the case.

Figure 2-9 contains actual HC and CO 2 attenuation data from an RSD beam block of the audit truck when it was producing simulated ex haust emissions but no simulated evaporative emissions. The slope of the line (blue dashed line ) that connects the origin with the centroid of
the HC attenuation versus CO 2 attenuation cluster of points re presents the Method A result. When the Method B regression line (red solid li ne) through the string of points passes through or near the origin, as in Figure 2-9, the slopes calc ulated by Methods A and B will be close to each other and will therefore produce sim ilar RSD HC reported values.2-13 Figure 2-9. Pollutant Attenuations wi th No Evaporative Emissions and 1100

ppmC 3 Tailpipe HC Emissions with Methods A and B Lines Superimposed

0 5 10 15 20 25 30 35 40 45

0 10 20 30 40


### CO 2 

### (%-cm)HC (ppm-cm) / 100

HC/100 vs. CO2
Method A line
Method B line

On the other hand, consider Figure 2-10 whic h contains actual RSD attenuation values
for a case where the audit truck had simulated exha ust emissions and high artificial evaporative emissions. In this case, for Method A, the slope of the dashed blue line connecting the origin with the centroid of the string of points has a slop e that is much larger than the slope of the red solid line through the points by regression. Thus , the reported value of RSD HC by Method A would be substantially larger than the value re ported by Method B. The reason that the slope by Method A is larger than the co rresponding line in Figur e 2-9 is that the HC attenuation values have been shifted higher because of the pres ence of the evaporative emissions. When evaporative emissions are presen t but are not extremely high, we would expect that the HC attenuations would be higher than if evaporative emissions were not present but not as high as they are when evaporative emissions are higher.2-14 Figure 2-10. Pollutant Attenuations with 15 scfh Evaporative Emissions and 1100 ppmC 3 Tailpipe HC Emissions with Methods A and B Lines Superimposed

0 20 40 60 80 100 120

0 10 20 30 40 50 60


### CO 2 

### (%-cm)HC (ppm-cm) / 100

HC/100 vs. CO2
Method A line
Method B line

Overall, therefore, the Method A calculation produces an RSD HC concentration that tends to be influenced both by the exhaust HC and the evaporative HC emissions. On the other hand, the Method B calculation tends to produce a reported HC concentration that is less influenced by evaporative HC emissions than the Method A calculation. As a consequence of
these different sensitivities of Methods A and B to evaporative emissions, the difference between the Method A and Method B reported values coul d be a useful measure of the level of evaporative emissions that a vehi cle produces. In addition, it is possible that this measure of evaporative emissions may be relatively i ndependent of the level of exhaust hydrocarbon
emissions from vehicles. We will call Method A minus Method B the RSD Evap Index 0. RSD Evap Index 0 will serve as the starting point for development of future RSD evaporative emissions indices. RSD Evap Index 0 is ba sed on a calculation involving the backgroundcorrected 50 10ms absorbance values from each beam block. Many different RSD evaporative emissions indices could be developed from th ese 50 10ms observations. Since there is no particular reason to believe that RSD Evap I ndex 0 is the best index, a search for better performing indices can be made.3-1 

### 3.0 Data Collection

The goal was to perform testing on about 100 vehicles for the purposes of evaluating screening methods that could id entify vehicles with high evaporative emissions, to develop and qualify a field method that could distinguish between vehicles with low and high evaporative emissions, and to make an initial estimate of th e fraction of high evaporative emissions vehicles in the fleet. Tests were ultimately performed on 85 vehicles by generating data in the pilot study which was performed in Denver, Colorado.

To reduce the time associated with identifyi ng high evaporative emissions vehicles, we tested vehicles in three steps, which ar e elaborated upon in Sections 3.1 through 3.3:

In the first step, we screened the HC emissi ons of all vehicles en tering the Lipan Street I/M station as they drove by a remote sensing de vice placed in the station’s entrance driveway. Based on their RSD HC emissions levels, these ve hicles were categorized into 9 emitter groups that covered the entire range of RSD HC emissions (see Table 3-1).

In the second step, we drew a stratified random sample of vehicles for participation in the field method evaluation (see Section 3.2). This set of vehicles was recruited and tested on site to evaluate three different evapora tive emissions screening methods. Each vehicle also had its hotsoak and gross liquid leak emissions measured in the portable SHED (see Section 3.3.3).

In the third step, a fraction of vehicles participating in th e field method ev aluation were requested to have evaporative emissions meas ured in CDPHE’s labora tory SHED near the recruitment site, and ultimately 23 were tested on both the PSHED and in a laboratory SHED. These data were compared with the portabl e SHED results to qualify the portable SHED technique for use in subsequent Work Assignments (this portion of the work has been previously reported [6]).

The types of data that were su rveyed or measured included:

 Vehicle identifiers and description: licen se plate, vehicle id entification number, model year, make, model, odometer read ing, and other identifying information on vehicles that participated in the study. Photographs were taken of each vehicle to assist in data quality control. The vehicl e pictures were taken from various angles and included a white board which included th e test number assigned to the vehicle. Photos of the VECI label and VIN were also taken.

 Vehicle usage and maintenance: A vehicle owner survey was used to acquire vehicle usage and maintenance history.3-2  Portable SHED measurements: These include the evaporative emissions measured in the portable SHED environment. These emissions are expressed in terms of the mass evaporative emissions released in to the portable SHED, the maximum HC concentration within the SHED, or the tim e trace of HC concentration of the air inside the portable SHED af ter a vehicle’s engine is turned off and the portable SHED doors are sealed. They are th e study’s measure of the estimated evaporative emissions from each vehicle.

 RSD HC emissions measurements: Thes e are the exhaust and evaporative emissions measured for the purposes of screening high evaporative emitters.

 Qualitative observations of evaporative em issions: Vehicle observations via HC sniffer and visual inspection and infrared video camera were recorded by on-site technical staff.

The experimental design and results for the Pr e-Testing have already been described in a separate report [1], and the Portable SHED Evaluation has also been reported [6]. The procedures used for collecting data for the fi eld evaluation are described in the following subsections. The different types of data that were collected ar e described in Section 3.1. The sampling plan that was used for recruitment of vehicles based on an RSD observation is described in Section 3.2, as well as a description of the test seque nce that was performed on each of the sampled vehicles.

3.1 Sequence of Field Testing Procedures for the Pilot Study

For the pilot study, ERG conducted measurem ents on vehicles owned by the general public. Vehicles were screened for participation us ing RSD as they approached an I/M Station. Participating vehicles were subj ected to a series of RSD measurements, evaporative emissions measurements, and visual inspection.

The stratified sample system described in S ection 3.2 was used to preferentially select higher evaporative emitting vehicles. The owners of vehicles that were identified as potential study participants were solicited by ERG personnel while they waited for their I/M test. They were asked if they would like to participate in the study, allowing thei r vehicle to undergo additional evaporative emissions testing. Thos e that agreed to part icipate were given a questionnaire that would help determine the most recent repairs, re-fuelin gs, usage patterns, and other information. The additional evaporative emissions tests were then performed on the
vehicle.

Solicitors and other testing personnel did not have knowledge of the observed RSD
emissions of the candidate or selected vehicles.3-3 The diagram in Figure 3-1 below illustrates how the procedures flowed from the initial RSD HC screening through the various evaporative emissions tests. A total of 85 vehicles were ultimately tested with this test matrix.3-4 Figure 3-1. Vehicl e Testing Flow

I/M Testin g

Collect Final Vehicle Info Portable SHED Non-Participants

Participants 1: Selection RSD

3. Evaporative Emissions Data Collection

Modified California Method

Release Vehicle Conditioning Drive + 2 Measurement RSDs 2: Solicitation (+ Collect Participant Initial Vehicle Info)

IR Camera3-5 Flow Diagram Step 1: Screenin g Using Remote Sensing Device All vehicles entering the IM station drivew ay had the emissions plume scanned by an
RSD-4600 instrument to measure emissions conc entrations. RSD instruments perform these measurements by shining a light beam across the roadway. While the driver could see the equipment, measurements were performed without notifying the vehicle driver that they were being taken. For each vehicle the following quant ities were automatically taken as the vehicle passed by the RSD instrument:

 DateTime: The date, hour, minute, and second of the RSD measurement.

 Speed and Acceleration: The speed and acceleration of the vehicle.

 The calculated VSP of the vehicle.

 RSD-4000 Emissions 3 : The concentrations of HC, CO, and NO in the vehicle’s plume according to the Method A calculation.

 RSD-3000 Emissions: The concentrations of HC, CO, and NO in the vehicle’s plume according to an approximation of the Method B calculation.

 License Plate: A digital image of the rear of the vehicle was recorded so that the license plate could be determined.

3.1.1.1 Flow Diagram Step 2: Solicitation

Based on the screening Method A HC values , the VSP, and the number of vehicles desired for each RSD/age bin in the stratified random plan, a sample of passenger cars and lightduty trucks was approached by the solicitor. Th e solicitation was usually made as the owner’s vehicle was waiting in line fo r the inspection to begin. The solicitor performed the following
activities:

 Introduction: The solicitor explained that a U.S. EPA emissions study was being conducted and measurements would take about one hour. The solicitor explained that the measurements would involve dr iving the vehicle for about 20 minutes, driving past the RSD unit two times, performing under-hood visual inspections, and testing the air in the portable SHED after the vehicle had sat in it for 15 minutes.

 Ownership: The solicitor asked if the driv er owned the vehicle. Only vehicles with their owners driving were eligible for participation. Company vehicles or dealer vehicles were not allowed as participants.

3 A single instrument was deployed, but the different calculation methods were used to estimate emissions: “RSD4000” and “RSD-3000”.3-6  Incentive: The solicitor offered a $20 cash incentive. The incentive was provided whether or not the vehicle owner participated.

 Vehicle Information: The solicitor colle cted an initial vehicle description including license plate, model year, ma ke, model, and color as described in Appendix A.

 Owner Questionnaire: The solicitor admi nistered the owner questionnaire to gather recent vehicle usage and maintenance history information. (Appendix A).

Flow Diagram Step 3: Evaporat ive Emissions Data Collection

Following completion of the IM inspection, pa rticipating vehicles would then undergo the following tests:

 RSD Emissions: A technician conditioned the vehicle for 20 minutes on a set 8- mile route 4 , which simulated the Federal Test Procedure (FTP) typically used as preconditioning for a Hot Soak laboratory test. Then drove it past the RSD unit two times to obtain RSD measurements th at were independent of the screening RSD used to select the vehicle for part icipation. The same type of data was recorded as for the screening drive. The technician driver verified with the RSD technician that all RSD results were valid and that the VSP was in range.

 Portable SHED Emissions: With the engi ne still running, the vehicle was driven just outside the open PSHED door. Upon command from the PSHED technician, the engine was turned off, the vehicle was pushed into the PSHED, and the PSHED door was sealed. The HC emission concentration of the air inside the PSHED was measured continuously w ith the SEMTECH-G for 15 minutes. Following the measurement, the vehicle was driven out of the PSHED, and the air in the PSHED was flushed.

 Modified California Method: A visual and olfactory inspection of evaporative emission control system and the fuel sy stem was performed to look for missing, malfunctioning, damaged, or disconnected components. At the same time, a handheld electronic HC vapor detector was used to try to find sources of evaporative emissions by moving the small probe of the detector around components, fittings, and hoses.

 Infrared Video Camera: The infrared video camera recorded video of those areas around the vehicle where evaporative emissi ons might be present. This included over the engine compartment with th e hood opened and closed, and around the gasoline fill pipe.

4 Turn north on Lipan Street. Drive 200m. Turn east on W. Evans Avenue. Drive 675 m. Turn south on S. Santa Fe Drive. Drive 2875 m. Turn west on W. Hampden Avenue. Drive 2000 m. Turn north on S. Federal Blvd. Drive 3000 m. Turn east on W. Evans Avenue. Drive 2000 m. Turn south on Lipan Street. Drive 200 m.3-7  Detailed Vehicle Information: Vehicle information was collected including VIN, engine family, evap family, odometer r eading, transmission type, and photos as shown in the data packet in Appendix A. Digital photographs of serial numbers and equipment specification tags were ta ken as indicated, to help correct any inaccurate information recorded during on-site inventories.

 Final Check: After verifying that all items were collected and were complete, the vehicle was released to it s owner (unless the vehicl e was a candidate for the portable SHED / laborat ory SHED evaluation).

Of the 85 vehicles that completed the steps described above, a subset of 23 vehicles participated in a portable SHED / laboratory SH ED evaluation. A laboratory-grade 1-hour hotsoak 5 was conducted at CDPHE facilities for these 23 vehicles. Results of the portable SHED / laboratory SHED evaluation have previously been reported [6].

3.2 Stratified Random Sample of Vehicles for Field Testing

During the planning phase of the study, we es timated that 99% of all vehicles are not High Evaps. Since most vehicles are not excessive emitters of evaporative emissions, stratified random sampling was used to seek a preferentially larger number of vehicles that were potential high evaporative emitters. In this pilot study, we us ed RSD HC to screen vehicles into nine HC emitting categories. We selected vehicles from each of the nine screening RSD HC bins to be solicited for participation in th e pilot study. The sample was stratified with allocation among
RSD HC emissions bins.

As described in Section 2 (Background), we have circumstantial evidence that the HC channel of certain types of RSD in struments may be able to detect vehicles with high evaporative emissions levels. By preferentially sampling more vehicles from the higher RSD HC bins of screening RSD measurements, we attempted to cap ture a larger fraction of High Evaps in the pilot study than could be captured by completely ra ndomized sampling from the fleet as a whole.

Design of a stratified sampling strategy to achieve the desired precision required an estimate of the abundance of High Evaps in the fl eet as a function of th e stratifying variable. Unfortunately, no dataset existed that could cl early define High Evap levels. However, we assumed that the trends in Figur e 2-3 were caused by High Evaps. Therefore, the data collected in the California study was used to devel op a stratified sampling design for this study.

5 The lab SHED test was a standard one-hour hotsoak test. It was done with standard pre-conditioning, at standard SHED temperature for a hot-soak, and it was performed using the in-use fuel in the vehi cle’s fuel tank. The singlevalue hot-soak result and the minute by minute SHED HC conc entrations were both report ed for each hot-soak test.3-8 Table 3-1 summarizes the data from the Calif ornia study that were used to develop a stratified sampling plan for this study. Columns B and C give the bi n definitions in terms of the RSD HC as determined by Method A, which is influenced by evaporative emissions and exhaust emissions. Columns D and E give th e distribution of vehicles that had an inspection station ASM
test that followed the on-road RSD measurement. These columns indicate that the distribution of RSD HC emissions in the fleet is highly skewed with about 83% of the vehicles having RSD HC emissions below 148 ppm. Column F shows the numb er of High Evaps that we estimated from Figure 2-3. Specifically, we assumed that the gap between the data points and the red line in Figure 2-3 is caused by the presen ce of High Evaps in the fleet. Column G gives the estimated probability (=F/D) that vehicles in each bin are High Evaps. The fleet estimate from this data suggested 0.75% of the vehicles based on the California data are hi gh evaporative emitters.

Table 3-1. Expected High Evap Fr actions Using California RSD Data

A B C D E F G Bin Definitions: RSD HC (ppm)

by Method A Vehicle Population High Evap Vehicles (estimated)

Bin Greater Than Less Than

or Equal To Number of Vehicles

in Bin Population Fraction

in Bin (W h ) Number of High Evaps in Bin Fraction of Vehicles in

Bin that are High

Evaps

(p h ) 1 -Inf 0 24101 0.3131 0 0.000002 2 0 90 32959 0.4281 1 0.00005 3 90 148 7094 0.0922 3 0.0005 4 148 245 5476 0.0711 15 0.0027 5 245 403 3644 0.0473 49 0.013 6 403 665 2138 0.0278 107 0.050 7 665 1097 917 0.0119 143 0.156 8 1097 1808 365 0.0047 112 0.308 9 1808 Inf 288 0.0037 148 0.513

All 76982 1.0000 578 0.75%

From the information in Columns A through G, we used the technique for optimum stratified sampling, which is described in Appe ndix B, to develop a plan for achieving the precision target. The optimum plan was modified, how ever, to meet the obj ectives of this study
and to address the vulnerabilities to sub-optimal sampling.[9]

A random number generator was used to dete rmine whether or not a vehicle observed by RSD entering the Lipan Street IM station would be solicited for the study. A threshold between3-9 zero and one was assigned to each of the nine bi ns, with a higher threshold for the higher RSD HC bins. The random number generator assigne d a random number between zero and one to each vehicle that was observed by RSD. The vehi cle was then assigned to one of the nine bins,
based on its RSD HC value. If the vehicle’s ra ndom number was below the threshold number for the vehicle’s bin, then the vehi cle was solicited for the study. These thresholds represented selection probabilities. The random number thresholds for the nine bins were modified at times during the pilot study, as initial results were used to determ ine whether the actual sampled vehicles were falling into the desired distribution among the ni ne bins. The random number
thresholds that were used and the dates that they were used are listed in Table 3-2.

Table 3-2. Random Number Thresholds for Soliciting at the Lipan Station

A B C D E F Bin Definitions: RSD HC (ppm)

By Method A Random Threshold

Bin Greater Than Less Than or Equal To 7/28/2008 – 8/7/2008 8/7/2008 – 8/12/2008 8/12/2008 – 8/30/2008 1 -Inf 0 0.000883 0.0026 0.0280 2 0 90 .00412 .0124 .0160 3 90 148 .01299 .0361 .093 4 148 245 .0318 .0579 .118 5 245 403 .1535 .2257 .54 6 403 665 .288 .2191 .42 7 665 1097 .480 .2085 .52 8 1097 1808 .622 .2477 1.00 9 1808 Inf .657 .0627 .30

There are at least two reasons that the rate of occurrence of High Evaps in each of the nine bins might not turn out to be the same as the expected values shown in Column G of Table 3-1. First, our method to determine the rates was based on our interpretation of the trends seen in Figure 2-3 in terms of evaporative emissions . Second, while RSD can estimate the average emissions of a fleet of vehicles, RSD’s ability to properly classify i ndividual vehicles in emissions bins is subject to considerable unc ertainty caused by the variability of vehicle emissions and by variability in the RSD technique itself.

Vehicles were screened for possible partic ipation in the study based on their first RSD HC emissions measurement. However, RSD HC m easurements are subject to large variability. Therefore, because of large e xpected regression-toward-the-mean effects, it was important to recognize that the RSD HC bin assignments and all data analyses must be based on a second RSD reading. Because the set of vehicles were selected by RSD HC, a measurement subject to3-10 error, the second RSD HC measurements, on which th e results of the study were based, were, in many cases, different from the first RSD HC measurement.

The final sampling design for the Pilot Study is shown in Table 3-3. Of the 113 vehicles that were to be sampled, nine vehicl es were expected to be High Evaps 6 as shown at the bottom of Column H. The primary High-Evap-occurrence re sults of the pilot stu dy would be the nine High Evap fractions shown in Column I. With th ese nine values and population fractions for any application population (such as the nationwide fleet ), the overall fraction of High Evaps in the application population could be calculated as desc ribed in Appendix B.

Table 3-3. Field Method Evaluation Stratified Samp ling Design for RSD HC Bins

A B C E F G H I

Bin Definitions: RSD-4600 HC (ppm) Planned Allocations in RSD Screening Bins Expected Allocations in RSD Measurement Bins

Bin Greater Than Less Than

or Equal

To Population Fraction

in Bin Size of Screening

Sample Needed to

Fill Bin Number of Vehicles Number of Vehicles Number of High Evaps Fraction of Vehicles in

Bin that are High

Evaps 1 -Inf 0 0.3131 0 0 7 0 0.000 2 0 90 0.4281 0 0 15 0 0.000 3 90 148 0.0922 0 0 8 0 0.000 4 148 245 0.0711 0 0 13 0 0.000 5 245 403 0.0473 681 32 18 0 0.000 6 403 665 0.0278 737 21 20 1 0.050 7 665 1097 0.0119 1647 20 15 2 0.133 8 1097 1808 0.0047 7298 34 8 2 0.250 9 1808 Inf 0.0037 1514 6 9 4 0.444 All 1.0000 113 113 9

3.3 New Test Procedures for the Pilot Study

Several of the testing procedures that were used in this pi lot study were new to the field of mobile source evaporative emissions, and underw ent preliminary testing and validation at the beginning of the study. This included the Modi fied California Method (see Section 3.3.1) and the IR Camera (see Section 3.3.2). Additionall y, the use of the portable SHED (as opposed to the laboratory SHED) was new. The portable sh ed was tested and results compared to the laboratory SHED as part of sepa rate task under this project, and those results have already been reported [6]. However, since the use of the portable SHED is integral to the pilot study

6 Note that for this project there was no agreed-upon definition of High Evap. For Table 3-3 a High Evap is defined as any vehicle that would cause the black dots to deviate from the red line in Figure 2-3, which was derived from the California RSD data.3-11 described here, the results of the portable SHED to laborat ory SHED comparisons will be
summarized in Section 3.3.3.

3.3.1 Modified California Method

We used a modified version of the Califor nia IM Liquid Leak Test Procedure. See Appendix C for the standard operating procedure for the California Procedure, which is the visual inspection portion. The procedure was identical to the visual check implemented in January 2008 by the California Bureau of Automo tive Repair, with the addition of a HC sniffer
to aid in leak detection. Califor nia’s procedure is as follows:

 The liquid fuel leak inspec tion shall be conducted with the engine running. Use extreme caution when working around movi ng parts and ensure the transmission is in “park” or “neutral” with the parking brake on.

 Definition: For the purpose of conducting this inspection, a “Liquid fuel leak” is defined as follows: “Liquid fuel leak” means any fuel emanating from a vehicle’s fuel delivery, metering, or evaporation sy stems in liquid form that has created a visible drop or more of fuel on a component of a vehicl e’s fuel delivery, metering or evaporation system or has crea ted a fuel puddle on, around, or under a component of a vehicle’s fuel deliver y, metering, or evaporation system.

 Inspection: With the engine running, the smog check technician shall visually inspect the following components of the vehi cle, if they are exposed and visually accessible, for liquid fuel leaks:

Gasoline Fuel Tanks Carburetors Fuel Injectors Gasoline fill pipes and associat ed hoses, tanks, connections Gas Caps Fuel pressure regulators External fuel pumps Charcoal canisters Fuel delivery and return lines Any valves connected to any ot her fuel evaporative component Fuel vapor hoses Fuel filers

The California procedure was modified by the addition of a HC sniffer. The “sniffing” test was conducted simultaneously with and at the same vehicle locations as the visual inspection. The HC sniffer (see Section 4.3) is a hand held combustible gas detector that has been found useful in locating small liquid and va por leaks. These units are typically used by3-12 home appliance installers to verify gas tight c onnections and in the automotive trade industry to pinpoint liquid and vapor gasoline leaks.

When the unit detects hydrocar bons it signals the operator by flashing a small red light and creating an audible click. As the concentr ation of vapors increases, the frequency of the light and audible pulses increases. The sensitivity of the unit is adjusted to just stop pulsing at
ambient HC levels. The flexible wand is then used to direct the detector tip to the vicinity of suspected leaks. This unit is ex tremely sensitive to HC vapor, and has been successfully used in a number of emission laboratory applications . Additional recommended tools are a small flashlight, an extendible inspection mirror, and a mechanic’s creeper to view under body fittings and components.

3.3.2 Infrared Video Camera

A technician used an infrared video camera (see Section 4.4) to “film” areas under the hood, around the fuel tank, and around fuel lines. The IR video camera recorded video of those areas around the vehicle where evap orative emissions might be pres ent. This included areas near the engine compartment with the hood opened and closed, and around the gasoline fill pipe.

The IR camera was used to capture evaporativ e emission images from a vehicle with the fuel cap removed. Again, this was done to es tablish confidence that the unit is capable of detecting gross level evaporativ e emissions. The possibility th at the background heat from the engine could negatively impact the IR camera performance meant that extra care was taken during this portion of the experiment to develop detailed instructions for how the unit should be used to best capture evaporative images from a vehicle.

3.3.3 Evaluation of the Portable SHED

One of the field methods that was tested as part of this pilot was the use of a portable SHED (Sealed Housing for Evaporative Determin ation) or PSHED to perform a short hot-soak
emission test in an I/M lane setting. The development of th is technique included performing regular propane retention and r ecovery tests to establish th e integrity of the PSHED. Additionally, paired hot-soak da ta on 23 vehicles were obtaine d to allow the comparison of
PSHED measurements to the trad itional laboratory SH ED (LSHED) measurements. It should be noted that other evaporative emissions tests are commonly performed dur ing EPA’s certification testing, such as running loss and diurnal testing; however, these are considerably more complex than a hot-soak test, and therefore these tests we re not attempted using the PSHED equipment.3-13 The PSHED is a portable 10’ x 20’ x 8’ sealed enclosure 7 . To determine the evaporative emissions produced by a vehicle, the vehicle is warmed-up by driving it for about 8 miles and is then immediately placed in the PSHED with the e ngine off, and the enclosure is sealed. During
the next 15 minutes the HC concentration in th e air inside the PSHED is measured as any evaporative emissions leave the vehicle. At the end of 15 minutes the HC concentration is used
to calculate the mass of HC that has been emitted by the vehicle. This PSHED mass is the quantity that is used to determine whet her or not the vehicle is a High Evap.

The results of the PSHED evaluation are briefly summarized below; additional detail may be found in the PSHED evaluation report [6].

Recovery and Retention Data - A recovery test consists of injecting a known amount of propane into the PSHED and then measuring the amount of propane detected in the PSHED after a short period of time. This test verifies that the analytical equipment is working and establishes a baseline level of propane above the ordinary ambient background level. The retention test is the measurement of the propane level in the PSHED after 15 minutes, and it establishes the integrity of the PSHED ensuring that there ar e no major leaks during the time period that a
vehicle would be tested.

Both retention and recovery va lues are presented as a percent of the measured mass of propane injected initially. Values will likely be less than 100% because it is far more likely the propane will be lost from the PSHED (or any en closure) than introduced into the enclosure by the ambient background or some other mechanism. For the purposes of this study, we believe
the retention values reveal information about th e accuracy of the PSHED since retention reflects directly on the unit’s leak in tegrity and will inherently ca pture recovery information. Additionally, the recovery data is superior to the paired vehicl e data between the PSHED and the LSHED for evaluating PSHED performance simply due to the inescapable vehicle test-to-test variability.

The average and standard deviation PSH ED recovery and 15-minute retention measurements are presented below. This data was collected at the star t of each day of vehicle testing and ensured that the analytical equi pment was functioning properly and the PSHED had not developed any significant leaks. It can be se en from these values th at the unit’s performance was good and in fact exceeded expectations for a PSHED unit costing less than $400 plus

7 Purchased through elitedeals.com. Manufactured by Ki ng Canopy, 1730 Five Points Lane, Fuquay-Varina, NC 27526, (800)800-6296, Kingcanopy.com.3-14 instrumentation and gas costs could provide such accurate and precise retention and recovery
values.

Average Recovery 97.6% Recovery Standard Deviation 3.3%

Average Retention for 15 minutes 95.7% Retention Standard Deviation 2.3%

PSHED vs. LSHED - The PSHED performed in the IM lane consisted of a 15-minute test that was performed after a test vehicl e had been taken on a conditioning drive over a prescribed route. The conditioning drive was important because laboratory SHED hot soak evaporative emissions are measured following a standardized drive cy cle on a dynamometer. Therefore, to mimic this procedure with the understanding that future PSHED measurements would likely be performed without any access to a dynamometer, the test vehicles were
conditioned on the road over a set route. In addition to the standard dynamometer conditioning drive cycle, an LSHED is also a one hour test, with strict temper ature and fuel level controls. Given the objective of developing a quick evap orative test, the PSHED was only 15 minutes in duration and there was no attempt made to control the temperature or the fuel level of the
vehicle.

The results of the paired tests are illustra ted in Figure 3-2 below. The results are encouraging; however, closer agreement between the PSHED and LSHED measurements was hoped for given the PSHED retention and recovery re sults. At this time the major cause for this discrepancy is believed to be the non-repeatable natu re of a vehicle’s evaporative emissions, which can be exacerbated by malfunctioning evaporat ive emission systems, the variability in the on-road preconditioning driving fo r the PSHED vs. the dynamometer FTP as well as the widely varying uncontrolled ambient temperat ures for the PSHED measurements.3-15 Figure 3-2. Comparison of 15- Minute PSHED and 60-Minute LSHED Measurements

0 2 4 6 8 10 12 14 16 18

0 2 4 6 8 10 12 14 16 18 

### LSHED HC (g/60min)PSHED HC (g/15min)4-1 

### 4.0 Analytical Methods

The following instrumentation was used to take the measurements for this study. Each is described in the following sub-sections.

 ESP RSD-4600 remote sens ing instrumentation

 SEMTECH-G portable gas analyzer

 SnapOn hand-held combustible gas detector

 FLIR GasFindIR hydrocarbon vapor video camera

4.1 RSD Emissions Instruments

This pilot study used a single RSD-4600 unit for all RSD measurements. RSD systems are designed for non-intrusive measurement of vehi cle emissions. They generate and monitor a light beam emitted and reflected approximately 10 to 18 inches above a single lane road. The
RSD-4600 detects vehicle emissions when a car dr ives through an invisible light beam the system projects across a roadway. Figure 4-1 cont ains a diagram of a t ypical on-road set-up. The process of measuring emissions remotely be gins when the RSD-4600 Source/Detector Module (SDM) sends an infrared (IR) and ultraviolet (UV) light beam across a single lane of road to a Corner Cube Mirror (CCM). The CCM reflects the beam back across the roadway (creating a dual beam path) into a series of detectors in the SDM.

Fuel-specific concentrations of HC, CO, CO 2 , NO and smoke are measured in vehicle exhaust plumes based on their absorption of IR/UV light in the dual beam path. During this process, the Speed/Acceleration Module (S/A) measures the sp eed and acceleration of each vehicle while the Video System Ca mera captures an image of the re ar of the vehicle. Emissions
concentration values and other related data are stored in a computer pr ocessor monitored by an operator stationed in a mobile unit parked safely along the road side. This entire process is accomplished in less than a second.

The internal combustion equation assumes a non-oxygenated fuel with a hydrogen to carbon ratio of 1.85 to 1.0. Accuracy specifications apply when the distance between the SDM
and the CCM is from 15 ft to 23 ft.

The performance of the RSD-4600 Remote Se nsing Device will meet or exceed the absolute and relative accuracy specifications shown in Tabl e 4-1. These data are based on internal instrument specifications, not on-road controlled conditions.4-2 Figure 4-1. Typical On-Road RSD-4600 Set-Up4-3 Table 4-1. ESP RSD-4000 In strument Specifications

RSD-4600 General Specifications

RSD-4600 specifications for CO 2 plume greater than 20%-cm

RSD-4600 specifications for CO 2 plume less than 20%-cm

The usual calculations used by the RSD- 4600 instrument are provided by Method A. However, for this pilot study, a sp ecial supplemental query was writte n to also calculate reported emissions concentrations according to an approxi mation of Method B. Also, a special query was written to bin the Selection RSDs for every ve hicle entering the IM station and to randomly
select vehicles within each bin for solicitation.

CO % / CO 2 % 0.015 or ±15% of reading, whichever is greater HC ppm / CO 2 % ±10 or ±15% of read ing, whichever is greater (propane) NO ppm / CO 2 % ±10 or ±15% of read ing, whichever is greater CO % 0.15 or ±15% of r eading, whichever is greater HC (propane) ppm 150 or ±15% of reading, whichever is greater NO ppm ±225 or ±15% of r eading, whichever is greater Smoke number 0.1 or ±15% of readi ng, whichever is greater CO % / CO 2 % 0.007 or ±10% of reading, whichever is greater HC ppm / CO 2 % ±6.6 or ±10% of read ing, whichever is greater (propane) NO ppm / CO 2 % ±10 or ±10% of read ing, whichever is greater CO % 0.1 or ±10% of r eading, whichever is greater HC (propane) ppm ±100 or ±10% of reading, whichever is greater NO ppm ±150 or ±10% of r eading, whichever is greater Smoke number ±0.05 or ±10% of reading, whichever is greater Ambient Temperature •Operating: -7°C to +49°C (20°F to 120°F) •Storage: -30°C to 60°C Ambient Humidity 0 to 95% (non-condensing) Altitude (operating) -1000 ft to 10,000 ft (-305 to 305 m) Speed Accuracy ±1 mph (5 – 70 mph) Acceleration Accuracy ±0.5 mph/second (5 – 70 mph)4-4 4.2 SEMTECH-G Analyzer for Portable SHED Measurements

The SEMTECH-G analyzer is primarily inte nded for on-vehicle emission monitoring of gasoline (spark-ignition engine) powered vehicles . The analyzer can also be used for emission monitoring in other mobile applic ations, and also stationary app lications such as engine test cells, where SEMTECH-G can be easily moved from one test cell to another. In this pilot study
the SEMTECH-G was used to record the HC con centrations in the PSHED as vehicles produced evaporative emissions.

The SEMTECH® (Sensors Emission Technolog y) product line is based on a number of modular, stand-alone measurement subsystems . The following is a list of measurement subsystems included in the SEMTECH-G emission analyzer.

 Heated Flame Ionization Detector (FID) for total hydrocarbon (THC)
measurement

 Non-Dispersive Ultraviolet (NDUV) analyzer for nitric oxide (NO) measurement

 Non-Dispersive Infrared (NDIR) analyzer for carbon monoxide (CO) and carbon dioxide (CO 2 ) measurement

 Electrochemical sensor for oxygen (O 2 ) measurement

All of the SEMTECH subsystems have been de signed to match as closely as possible the analytical performance of laboratory grade instrumentation, and yet meet the special requirements of on-vehicle emission monitoring a pplication. This requires a reduction in size, weight, and power consumption co mbined with reduced sensitivit y to vibration and changes in ambient temperature, pressure, and humidity.

In addition to above listed measurement subsystems SEMTECH-G includes following
modules:

 Data logger, I/O, and system control module

 Wireless communication module for remo te monitoring and control using a personal computer (PC) or a pers onal digital assistant (PDA)

 Weather probe for ambient temperature and humidity measurement

Total Hydrocarbon Heated FID Analyzer – To accurately measure total hydrocarbons (THC) over the range of 0 to 40,000 ppmC, a hi gh-precision heated FID is used in the SEMTECH-G. A fraction of the sampled gas is r outed through the stainl ess steel heated FID
chamber for measurement. The FID chamber is heated to 191 °C.4-5 All aspects of the THC FID are electronically controlled by the SEMTECH-G embedded control software. FID flame ignition and extinction is performed on demand from the user via the host computer software graphic user interface. A ll internal parameters, such as flow rates and pressures are monitored and controlled automatically by SEMTECH-G.

The user can select a range of 100, 1,000, 10,000, or 40,000 ppmC. All enabled ranges are individually calibrated each time a zero calibration command is given, so the number of enabled ranges is minimized to reduce this process time. The user can also select a data rate of up to 4 Hz through the SENSOR Tech-PC application software.

The THC FID fuel consists of a 40/60 ble nd of hydrogen/helium. The fuel cylinder is housed inside the SEMTECH-G chassis, and include s an electronic pressure sensor connected to the data acquisition system so the user can monitor the fuel capacity from the SENSOR Tech-PC application software. A warning will occur when the fuel pressure drops too low. The fuel pressure is regulated at the bot tle with a two-stage, stainless steel regulator. Th e bottle holds 105 liters (compressed), which will last approximately eight hours. The bottles are available both in the U.S. and Europe by Scott Gas, and are refillable. There is also an auxiliary FID fuel connection port for external cylinde rs for use in stationary envir onments such as test cells.4-6 Table 4-2. SEMTECH-G M easurement HC Specifications

User Selectable Ranges

0 –100 ppmC 0 –1,000 ppmC 0 – 10,000 ppmC 0 – 40,000 ppmC

Accuracy ±2.0 % of reading or ±5 ppmC whichever is greater ±2.0 % of reading or ±5 ppmC whichever is greater ±2.0 % of reading or ±25 ppmC whichever is greater ±2.0 % of reading or ±25 ppmC whichever is greater
Resolution 0.1 ppmC 1.0 ppmC 1.0 ppmC 10.0 ppmC

Linearity ±1.0 % of reading or ±3 ppmC whichever is greater ±1.0 % of reading or ±3 ppmC whichever is greater ±1.0 % of reading or ±10 ppmC whichever is greater ±1.0 % of reading or ±10 ppmC whichever is greater

Repeatability ±1.0 % of reading or ±2 ppmC whichever is greater ±1.0 % of reading or ±2 ppmC whichever is greater ±1.0 % of reading or ±10 ppmC whichever is greater ±1.0 % of reading or ±10 ppmC whichever is greater
Noise ±2 ppmC ±2 ppmC ±10 ppmC ±20 ppmC

Span drift (over 8 hours) ±1.0 % of reading or 3 ppmC whichever is greater ±1.0 % of reading or 3 ppmC whichever is greater ±1.0 % of reading or 15 ppmC whichever is greater ±1.0 % of reading or 20 ppmC whichever is greater
Zero drift ( over 2 hours ) 5 ppmC 5 ppmC 10 ppmC 20 ppmC

Zero drift ( over 8 hours ) 10 ppmC 10 ppmC 20 ppmC 40 ppmC

Warm up time 60 minutes 60 minutes 60 minutes 60 minutes
Response time T90 < 2 seconds T90 < 2 seconds T90 < 2 seconds T90 < 2 seconds

Flow rate 2 lpm 2 lpm 2 lpm 2 lpm

Data rate Up to 4 Hz, configurable Up to 4 Hz, configurable Up to 4 Hz, configurable Up to 4 Hz, configurable Operating Temperature 191 °C 191 °C 191 °C 191 °C4-7 Ambient Air Sensors – The standard weather stati on for the SEMTECH product family consists of a remote mounted temperature and re lative humidity sensing device. This package is connected to the SEMTECH-G front panel using th e supplied cable. Cables of three meters in length are standard. The ambient pressure sens or is located in the SEMTECH-G unit and is vented through the rear panel.

Table 4-3. SEMTECH-G Am bient Air Specifications

Sensor Temperature Relative Humidity Pressure
Range of measurement -39 °C to 60 °C 0.8% to 100% RH 15 to 115 kPa

Accuracy ±0.2 °C ±2% RH at 0 to 90% RH
±3% RH at 90 to 100% RH ±1.5% 0 to 85 °C

Response time T90 < 10 seconds at 20 °C T90 < 4 seconds

4.3 HC Sniffer for Modifi ed California Procedure

Another evaporative emissions test was conducted using a handheld combustible gas detector that has been found useful in locating sma ll liquid and vapor leaks. The unit used in this pilot study is the Combustible Gas Detector (Stock# ACT790) sold by SnapOn tools for $299.99, and shown in Figure 4-2. According to Snap-On, th e unit can be used to find leaks in fuel and exhaust systems. Detectable compounds include acetylene, isobutane, methane, ethane, propane, hydrogen, acetone, methanol and gasoline. The batte ry-operated unit uses a solid electrolyte to detect hydrocarbons with a propa ne sensitivity of < 10 ppm.

Figure 4-2. HC Sniffer4-8 4.4 Infrared Video Camera

Open-path gas detection units, or IR cameras , are used to detect leaks in industrial settings, and it is possible they may be useful in detecting evaporative le aks from vehicles as well. Although there is no standa rd test procedure for detecting HC leaks from vehicles, the oil and gas industry routinel y monitors VOC leaks, and some of the methods used in that setting may prove promising for vapor and liqui d leak detection in vehicles.

In this pilot study, the FLIR (F orward Looking InfraRed) Systems 8 GasFindIR video
camera was used for about two weeks to evalua te its efficacy for detecting the evaporative emissions of light-duty gasoline vehicles. A photo of the GasFindIR unit is shown in Figure 4-3. According to FLIR, the unit is a hand portable, battery-powered open-path gas monitor providing fast response and broad dynamic range. They are permanently calibrated, small and light (less than 5kg). Alignment is easy and stable. Monitor response does not depend on path length, so a series of paths of different lengths (betw een 1m and 1000m) can be measured in quick succession. These systems are typically used to provide exceptional detection capability of gas/vapor concentrations ranging fr om as low as ppm levels to Lower Explosive Limit levels in a wide range of hazardous conditions and ambient air monitoring applications. The device forms an image using infrared radiation, similar to a common video camera that forms an image using visible light. Instead of the 450–750 nanometer ra nge of the visible light camera, infrared cameras operate in wavelengths as long as 14,000 nm (14 μm).

According to the flir.com website, independent laboratory testing confir ms that the GasFindIR cameras can see the following gases at th e minimum detected leak rate (MDLR):

1-Pentene - 5.6g/hr Benzene - 3.5g/hr Butane -0.4g/hr Ethane - 0.6g/hr Ethanol - 0.7g/hr Ethylbenzene - 1.5g/hr Ethylene - 4.4g/hr Heptane - 1.8g/hr Hexane - 1.7g/hr Octane - 1.2g/hr Pentane - 3.0g/hr Propane - 0.4g/hr Propylene - 2.9g/hr Toluene - 3.8g/hr Xylene - 1.9g/hr

8 25 Esquire Road, N. Billerica, MA , 01862, (978) 901-8000, www.flir.com.4-9 Figure 4-3. FLIR GasFindIR Gas Detection Video Camera

In infrared photography, the film or image sensor used is sensitive to infrared light. The part of the spectrum used is referred to as near -infrared to distinguish it from far-infrared, which is the domain of thermal imaging. Wavelength s used for photography range from about 700 nm to about 900 nm. Usually an “infrared filter” is us ed; this lets IR light pass through to the camera
but blocks all or most of the vi sible light spectrum (a nd thus looks black or deep red). There are two different methods employed by IR cameras, one is known as Backscatter Absorption Gas Imaging (BAGI) and the other Image Multi-Spectral Sensing (IMSS). The former views the area illuminated by the IR source light and the camera im ages the reflected light. Volatile Organic Compound vapors absorb IR light, so the image pr oduced is a negative. The cameras using the IMSS method capture an image using the full light spectrum and th e optics separate and recombine selected wavelengths to create an image.

Studies indicate that the BAGI style IR camer a can detect VOC leaks from 6 to 17 feet away with leak rates ranging from 3-60 grams/hr. Work in the area of refi nery leak detection has progressed to the point that emission factors ha ve been developed for various piping components
and Monte Carlo simulation methods have been employed to aid in the estimation of VOC fugitive emission releases.

4.5 Management of Field Data

Vehicle information was collected on hard copy forms similar to the “Vehicle Data Collection Forms” included in Appendix A. VINs , make, model, model year numbers and other4-10 information was also collected, as available. Ph otographs were taken of unique identifiers such
as VINs to serve as conformation information and to correct or clarify tr anscription errors and discrepancies. Vehicle information was transmitted to an ERG office for entry into a spreadsheet
or database.5-1 

### 5.0 Analysis

This section of the report will present an initial analysis of the data collected in this pilot study. The main goal here is to describe the gene ral trends in the data. Data observations are shown in Appendices D through K for particip ating vehicle information, selection RSDs, conditioning drives, measurement RSDs, PSHED results, modified California method results, driver interviews, and I/M gas cap inspection results.

In this study the reference method for determ ining the evaporative emissions of vehicles was the measurement of hot-soak emissions produ ced by a vehicle while it soaked in the PSHED
for 15 minutes. Three methods were evaluated as candidate methods for de tecting vehicles that have high PSHED values:

IR video camera – This qualitative method uses a speci al IR detector coupled to a video recorder that can see the motion of HC vapors as they are emitted. The results of these tests are reported in Section 5.1.

Modified California Method – This qualitative method supplements a visual and olfactory inspection of the gasoline liquid a nd vapor handling systems of a vehicle (the California Method) with a hand-held electronic HC vapor detector. Th e results of this testing is reported in Section 5.2.

RSD – This quantitative method uses the detail ed absorbance information from an RSD
beam block to calculate an “index” that is related to evaporative emissions. 9 Section 5.3 describes the relationship between RSD Evap Index 1 10 and the PSHED measurements in this pilot study. Note that since better RSD evaporative emissions indi ces will probably be developed in the future, this analysis is just an early l ook at the potential for RS D to detect evaporative
emissions.

Section 5.4 demonstrates how to estimate the fr action of High Evap vehicles in a sample of a fleet. In this calculation, fleet on-road RS D measurements are used to calculate RSD Evap Index 1, which is in turn used to estimate each vehicle’s probability of being a High Evap.

9 Since RSD instruments were developed with the goal of detecting vehicles with elevated exhaust emissions, finding an index that is sensitive to evaporative emissions without being infl uenced by exhaust HC emissions is a challenge. We expect that no theory can be used to dete rmine the perfect index. Instead, evap index development is a signal analysis problem. Consequently, ever improved indices can be developed as index developers get more inventive.
10 Developed by H.J. Williamson [11] using the Summer 2008 PreTesting data.5-2 5.1 Evaluation of Using the Infrared Video Camera to Detect High Evaps

FLIR Systems, Inc. has developed an infrared video camera for the detection of a variety of hydrocarbon gases. The camera used in the pilot study was the FLIR ThermaCAM
GasFindIR Infrared Camera. This camera feat ures a high resolution video image based on an indium antimonite (InSb) focal plane array. The visual detection of hydrocarbon gases is provided by a narrow band pass cold filter specifically centered in the spectrum to detect various hydrocarbon gases. The camera is a hand held package weighing less than five pounds and uses a separate video recorder with an LCD scr een. The camera was designed to find fugitive emissions such as those that might be present as small hydrocarbon vapor le aks in the piping of a refinery or chemical plant.

The IR video camera was used in this p ilot study from August 1 through 15, 2008. To initially test the ability of the IR camera to se e evaporative emissions, we removed the gas cap of a vehicle after it had been driven on the 8-mile conditioning drive. Since the ambient temperature was hot, we expected th at the fuel tank temperature at the end of the drive would be especially elevated, and theref ore a substantial amount of gasoline vapor should be emitted from the open fuel fill pipe. When the gas cap was removed the vehicle, the video camera showed quite clearly the hydrocarbon emissions coming fr om the opening. Thus, this first test was encouraging. The features that made the hydroc arbon emissions visible in the video were the relative motion of the darkly co lored image of hydrocarbon vapors co mpared with the stationary background of the fender of the vehicle. If the vehicle fender was light colored, then it was easy to see the hydrocarbon emissions. However, if th e fender of the vehicle was darkly colored, then it was difficult or impossible to see the motion of the hydrocarbon emissions.

During the routine testing of pr ivate vehicles during the two w eeks that we had rented the IR camera, we used the camera to search for ev aporative emissions from the fuel cap, under the hood, and under the vehicle near the fuel ta nk. We found that wh en the background was complex (e.g., under the hood) or was dark (e.g., unde r the vehicle, in the fender well, or under the hood) the video camera operator would probably not be able to see the wisps of hydrocarbons that might be being emitted as evaporative emissions. It was also rather difficult to aim the camera at the fuel system or evaporative em ission system components under the vehicle and
under the hood and at the same time watch the vi deo screen for wisps of hydrocarbon with the complex background and poor lighting conditions. Thos e difficulties hampered the ability of the operator to interpret the video. We found that th e use of the hand-held hydrocarbon sniffer with its audio clicking was a far better tool for det ecting and locating evaporative emissions leaks. Therefore, after about one week of attempting to use the IR video camera, we abandoned it.5-3 5.2 Evaluation of the Modified Cali fornia Method to Detect High Evaps

In this subsection, the modified Califor nia method (MCM), which includes visual, olfactory, and hand-held electr onic HC vapor sniffer inspection components, was evaluated against the PSHED results (g HC / 15 minutes ) for the 85 vehicles participating in the evaporative emissions testing at the Lipan Street station.

The sequence of the PSHED and MCM tests is important to the interpretation of the results. Participating vehicles were given an 8-mile on-road conditioning drive and two IM station driveway RSDs. Then, the vehicle was dr iven to the PSHED door, the engine was shut down, and the vehicle was pushed into the PSHED for the 15-minute test. During this 15 minutes
the vehicle cooled somewhat. At the end of th e PSHED test the vehicle was started in the PSHED and backed out of the enclosure approxim ately 50 feet, but the vehicle was still inside the IM station. The MCM inspection was then performed. For the first part of the MCM the engine was left running. For the la st part the engine was off. B ecause of the 8-mile conditioning drive immediately before the PSH ED test but not immediately be fore the MCM test and the 15- minute cooling during the PSHED te st, it is likely that the MCM test was conducted under less severe evaporative emissions condi tions than the PSHED test. This may mean that in some cases the MCM test may not have dete cted evaporative emissions that might have occurred if the vehicle had been just as severely conditioned as for the PSHED test.

In addition to the different conditioning used for the PSHED test and for the MCM test,
there was another factor that could have affected the MCM results. Personnel conducting the MCM test always knew the PSHED test result. Therefore, if the PSHED result was high, the MCM inspectors worked hard to try to find th e source of the HC emissions. In fact, we instructed the MCM inspectors to try to find the exact source of the emissions on high-PSHED vehicles. On the other hand, it w ould only be human nature that an inspector would not look so
hard to find a leak on a vehicle that he knew to have a low PSHED result.

In this study the PSHED result was treated as the true evaporativ e emissions of each vehicle. In reality, the PSHED result is closes t to a hot-soak evaporative emissions result and may be only a crude estimate of diurnal, runni ng losses, resting losses, or fugitive evaporative emissions. The PSHED results, which are given in the last column of the table in Appendix H, are repeated in Table 5-1.5-4 Table 5-1. Comparison of PSH ED and MCM Overall Results

PacketID PSHED (g / 15 minutes) MCM (1=Detected, 0=NotDetected) PacketID PSHED (g / 15 minutes) MCM (1=Detected, 0=NotDetected) 10 0.130 0 191 0.087 0 11 14.022 1 193 11.219 0 16 0.538 1 194 24.073 0 19 14.809 1 200 0.171 0 22 1.301 0 203 0.022 0 24 11.194 1 213 0.890 1 29 0.088 1 217 0.066 0 35 15.472 1 218 0.354 0 46 11.998 . 220 1.094 0 50 0.903 1 221 0.133 0 60 0.109 1 222 2.795 0 61 0.079 0 223 2.022 1 62 0.082 0 225 0.335 0 63 0.186 0 226 0.174 0 65 0.177 0 229 3.438 1 70 0.040 0 236 1.047 1 72 0.186 0 240 0.109 0 78 0.312 1 242 9.021 1 79 0.021 0 245 0.134 0 84 0.153 0 247 2.203 1 89 0.385 1 248 1.115 0 98 0.032 0 250 0.709 1 108 0.705 0 251 0.027 0 110 3.121 1 254 0.333 0 116 6.753 1 256 2.181 0 117 0.256 0 257 0.076 0 118 9.364 1 258 0.028 0 123 0.209 0 266 0.133 0 124 0.152 0 270 1.062 1 128 3.461 0 271 1.292 1 130 0.156 0 272 1.365 0 131 1.940 1 274 0.022 0 132 1.516 0 281 0.262 0 137 0.285 0 283 0.068 0 138 0.046 0 284 0.067 0 146 1.589 1 286 13.180 1 151 0.354 0 287 2.988 0 157 0.178 1 290 1.227 0 161 3.366 1 294 0.064 0 165 0.262 1 298 0.045 0 169 2.998 0 299 0.323 0 174 0.048 0 300 0.266 0 177 0.068 0 304 0.167 1 184 0.044 05-5 The detailed results of the MCM inspection as reported on the data packets are shown in Appendix I. When the MCM inspection found evid ence of evaporative emissions, various types
of comments were recorded.

In many cases, especially for the newer vehi cles, it was difficult to access much of the fuel system with a sniffer. Vehicle designs are much more tightly packed and without invasive diagnostics (i.e. hoisting the vehicle and pulli ng down the fuel tank and fuel lines), the
technicians were unable to determine the source of leaks in even high PSHED readings as can be
seen in Table 5-1.

5.3 Evaluation of Using RS D to Detect High Evaps
5.3.1 RSD Evap Index 1 Description

The RSD instrument uses a light beam shin ing across the roadway to measure pollutants in a vehicle’s tailpipe plume. The instrument has HC, CO, NO, and CO 2 channels. When a vehicle drives past the instrument, the light be am shines through the emissions plume behind the vehicle and takes 50 10-millisecond-spaced measur ements for each of these channels.

For vehicles with zero evaporative emissions , the 50 data points in the HC-versus-CO 2 plot tend to fall on a straight line. As descri bed in Section 2.3, the exhaust HC emissions concentration is closely related to the slope of the line. This met hod used to calculate exhaust HC
concentration from the 50 10ms RSD data is a standard method and has been known for many years. However, the Denver pilot study also found that for vehicles with high evaporative emissions, the 50 data points in the HC-versus-CO 2 plot tend to not fall on a straight line. We believe this is a consequence of the HC evaporative emissions plume, which is produced by nontailpipe sources on the vehicle, wafting into the li ght beam at the same time as the tailpipe plume is in the light beam. Thus, the de gree to which the 50 data points deviate from a straight line in
the HC-vs-CO 2 plot is a measure of the amount of eva porative emissions produced by the vehicle at the time that it passes thr ough the RSD light beam. The evaporative emissions that may be observed by RSD represent the “running losses” of th e vehicle, that is, the evaporative emissions that take place while the vehicle is being driven.

We investigated several measures of the charact eristics of the deviations from the straight line as they relate to evaporative emissions. Th e statistical measures that were investigated included the average deviation from the strai ght line, correlation co efficient, principal component analysis, and spectral analysis. Each approach has a dvantages and disadvantages, but5-6 using the average deviation from the straight line outperforms the other measures in most cases. Therefore, this measure was used in this study, and is referred to as the RSD Evap Index 1.

For the analysis of the data in this pilot study, we used the RSD Evap Index 1, which is the best second generation evap index that we ha ve developed. It is an improvement over the RSD Evap Index 0, which was simply the difference between the Method A and Method B RSD HC values. The following text, which was taken from H.J. Williamson’s report [11] on the development of RSD evaporative emissions indi ces, provides a description of the RSD Evap
Index 1:

Each RSD beam block typically produces 50 attenuations (concentration times path length) with 10 ms spacing for each pollutant. The attenuations generally decrease with time after the ve hicle has passed the RSD unit because of the dispersion of the plume in ambient air. The light beam for the RSD unit is placed so that it is at tailpipe elev ation. The above-mentioned gasses [HC, CO, NO x , CO 2 ] emitted from the tailpipe are well mixed and disperse together. Therefore, the [RSD optical] path length for each tailpipe pollutant is the same, and the RSD attenuations reflect only the ratios of the tailpipe pollutant concentrations.

On the other hand, evaporative gasses (only HC) are emitted from nontailpipe sources – even multiple sources. Therefore, evaporative emissions do not disperse in the same way the tailpipe em issions do. The difference in dispersion between evaporative and tailpipe emissions is the key quality that can be used to detect evaporative emissions. The evaporat ive emissions can waft into and out of the RSD’s light beam.

If hydrocarbon fuel is being burned, the CO 2 emissions will be above the detection limit. Thus, CO 2 is an effective tracer for the tailpipe dispersion effect in any case of interest. This is not guaranteed to be the case with CO, NO x , or HC.

Thus, consider the following. Suppos e we perform a regression analysis of the 50 attenuations for HC on CO 2 . If the HC measurements are above the detection limit, this regression analysis wi ll account for the tail pipe-related part of the trend in the HC measurements. The residuals, that is, the observed minus predicted values, contain what is left af ter the trend associated with the tailpipe effect has been mathematically removed.

If there are no evaporative emissions, the residuals should be at the noise level. If there are significant evaporativ e emissions, the residuals will typically contain a remaining trend that is larger than the noise level. The evaporative trend may not be strictly independent of the tailpipe trend, but the evaporative trend is not expected to be the same as the tailpipe trend. Differences between the5-7 time histories for tailpipe emissions and evaporative emissions produce the remaining trend that allows us to detect evaporative emissions.

If the HC measurements are below the detection limit, they will be essentially noise. If the HC measurem ents are this low, both the tailpipe and evaporative emissions are probably quite low. There will be no tailpipe trend to remove, and the residuals will be at the noise level.

Now suppose the car has very low tail pipe emissions but has significant evaporative emissions. For reasons disc ussed above, we do not expect the time history for the HC evaporative emissions to have the same characteristics as the tailpipe CO 2 emissions. Thus, as in the case wi th measurable tailpipe emissions and significant evaporative emissions, we expect the residuals to have a remaining trend that is larger than the noise level.

Therefore, using the residuals appear s to satisfy our need to remove the tailpipe HC trend if it is present. Wh ether the tailpipe emissions are measurable or not, the residuals are ch aracteristic of noise in the absence of evaporative emissions. Further, the residuals typically have a remaining trend above the noise level if there are significant evaporativ e emissions. Therefore, the residuals appear to provide an avenue for calcu lating measures that have a common meaning in different scenarios.

The residuals have othe r characteristics that we can exploit. If the residuals are characteristic of noise alone , they are likely to oscillate back and forth about zero fairly rapidly. But, if present, the evaporative plume probably does not waft into and out of the RSD’ s light beam with high frequency. The influence of the evaporative plume is lik ely to produce sustained periods when the residuals are positive and sustained periods when the residuals are negative. Again, the residual is the HC value afte r the trend associated with tailpipe emissions has been mathematically removed.

We have experimented with various measur es that are based on the properties discussed above. The measure, which we call RSD Evap Inde x 1,that is related to the presence or absence of evaporative emissions can be described as follows:

1) First, discard th e first four HC and CO 2 attenuations. These typica lly contain noise that can degrade the sensitiv ity of the index to evaporative emissions.

2) Second, regress the remain ing HC attenuations on the CO 2 attenuations using ordinary least squares regression, and calcula te the 46 regression residuals.

3) Third, exclude the smallest residual and the largest residu al (some would say the most negative and most positive residuals). This step eliminates isolated outliers, if present.5-8 4) Finally, average the absolute values of the remaining residuals. This is the value of the RSD Evap Index 1.

5.3.2 Paired RSD and PSHED Observations

While RSD observes the running losses of a ve hicle, the PSHED testmeasures the “hotsoak” evaporative emissions of a vehicle. However, we expect that a vehicle with a malfunctioning evaporative emissions control system could be expected to have elevated PSHED
hot-soak emissions and elevated RSD running loss emissions.

Accordingly, we examined the correlati on between the RSD Evap Index 1 and the PSHED test using the 175 observations of the Denver pilot study. Each of 85 PSHED tests was paired with two (and in several cases, more than two) RSD observations, for a total of 175 paired observations. Each RSD measurement produced th e 50-sample-point data, which in turn was used to calculate the RSD Evap Index 1 value for the RSD beam block. In this study, all RSD measurements were made in the driveway entr ance to the I/M stati on. Speeds were about 12 mph.

The 85 vehicles tested in this pilot study we re selected using a st ratified random sampling plan. Therefore, the measured PSHED and RSD results do not directly represent the Colorado fleet; the results would need to be de -stratified. However, the relationship between the RSD and
the PSHED results is an estim ate of the relationship that the Colorado fleet follows.

Figure 5-1 shows a plot of the 175 observations . The vertical axis is the PSHED result, and the horizontal axis is the RSD Evap Index 1. The plot shows widely scattered data with positively skewed values on both axes. The skewed nature of the PSHED values is derived from the fact that most vehicles (eve n those in this stratified sample) have low evaporative emissions; only a few vehicles are “High Evaps.” In spite of the scatter of the data points, the plot shows that at low values of the RSD Evap Index, most vehicles have low PSHED emissions. In addition, the group of data points with the highe st PSHED values increase with increasing RSD Evap Index 1. Thus, it is reasonable to conclude that vehicles with higher RSD Evap Index 1 tend to have higher PSHED values. The relatio nship between RSD Evap Index 1 and PSHED value needed to be quantified so that it can be used as a predictive tool.5-9 Figure 5-1. RSD Evap Index 1 and PSHED Values (Speed is approximately 12 mph)

Two different approaches may be used to quantify the relationship between the PSHED
and RSD values. Because the RSD observations of evaporative emissions represent running losses, while the PSHED test measures hot so ak evaporative emissions, the two tests do not actually measure the same type of evaporative emissions. Therefore, a logical correlation
between the two tests would seek to determine wh ether or not there is a gross problem with the evaporative emissions system of a vehicle, rath er than attempting to use evaporative emissions observed by RSD to predict a specifi c level of the different type of evaporative emissions that are measured in a PSHED test. Nevertheless, we wa nt a quantitative relationship to predict if a vehicle is likely to be a High Evap.

In one approach, the PSHED HC mass is regr essed against the RSD Evap Index 1 value, to identify an equation to estimate the PSHED HC mass based on a measured RSD Evap Index 1 value. This approach is expl ored below in Section 5.3.3. Alte rnatively, each PSHED value can5-10 be compared to a high-evap PSHED benchmark va lue to classify each PSHED measurement as a low-evap or a high-evap value. Then, the classi fications are compared to the RSD Evap Index 1 using logistic regression to arrive at a model that calculates the probability that a vehicle is a High Evap based on its measured RSD Evap Inde x 1. This approach is described in Section
5.3.4.

5.3.3 Prediction of PSHED Va lue Using RSD Evap Index 1

To quantify the relationship between the PSH ED value and the RSD Evap Index 1, we performed a linear regression. Firs t, we found that the natural log of the RSD Evap Index 1 was an advantageous transformation. It caused the va riances of the RSD Evap Index 1 to be more nearly homogeneous. Using the log transforma tion, the PSHED value was predicted from the RSD Evap Index 1 as:

PSHED_g = -12.1209 + 3.24789 * ln(RSD Evap Index 1)

The r 2 for the regression was 0.52, indicating that th e data include a substantial amount of scatter. The 175 paired data points and the linear correlation are s hown in Figure 5-2.5-11 Figure 5-2. Linear Correlation of PSH ED and Transformed RSD Evap Index 1

5.3.4 Prediction of PSHED “High E vap” Probability Using Evap Index 1

For the purposes of this analysis, we used a PSHED value of 3 grams was used as the standard for “High Evaps” when measured in the PSHED. Accordingly, the 175 paired RSD and PSHED data points are shown again in Figure 5-3 with a dashed horizontal reference line at 3 grams. Points above this line represent “High Evaps.” High-evap PSHED HC mass values other than 3 grams could also be used as the definition of a High Evap.

Rather than attempt to predict the PSHED va lue based on the RSD Evap Index 1, here we choose to calculate the probability that a vehicle w ith a given RSD Evap Index 1 is likely to be a High Evap. To help visualize the trend in probab ility, vertical dashed lines at 80, 270, and 900 in Figure 5-3 are used to divide the plot into four RSD Evap Index 1 bins. The count of the number
of observations within each of these bins and the number of “H igh Evaps” within each of the bins is given in Table 5-2. The table shows a monotonically increasing Hi gh Evap fraction as the RSD Evap Index 1 increases.5-12 Figure 5-3. RSD Evap I ndex 1 and PSHED Values

Table 5-2. Counts of High Evap Designations

Range of RSD Evap Index 1 Count Measured High Evap (fraction) Modeled High Evap (fraction) Low High PSHED > 3g Total

0 80 7 112 0.06 0.054
80 270 8 41 0.20 0.225
270 900 10 16 0.63 0.568 900 Inf 5 6 0.83 0.8565-13 To further quantify the relationship, we perf ormed a logistic regression to predict the probability that the PSHED value would be larger than 3 grams using RSD Evap Index 1 as a predictor. First, we found that the natural log of the RSD Evap Index 1 was an advantageous
transformation. It caused the values of the RSD Evap Index 1 to be more nearly homogeneous. The log transformation also was able to predict the PSHED failu re probability from a simple expression with no lack of fit, wh ich indicates that the model is an adequate fit to these data:

P fail = exp (arg) / (1 + exp(arg))

Where

P fail = Probability that the PSHED te st has a value above 3 grams,

arg = -7.5262 + 1.2582 * ln(RSD Evap Index 1)

During model development, we found that the model had only a small dependence on
exhaust emissions level. This means that the RSD Evap Index 1 is largely independent of exhaust emissions influence and therefore a given RS D Evap Index 1 value has the same meaning whether the vehicle has high e xhaust emissions or low exhaust emissions. Thus, even though older model year vehicles tend to have higher exhaust emissions, the RSD Evap Index 1 is independent of model year.

The model development also revealed that alte rnative High Evap definitions (other than a PSHED value of 3 grams in 15 minutes) could also be used to develop a logistic regression models with the same favorable properties. The concordance 11 for the logistic regression was
79.6%.

The PSHED failure probabilities predicted by th e model at the center of the ln(RSD Evap Index 1) bins are given in the last column of Table 5-2. The values calculated by the model are reasonably close to the values deri ved from the counts in Table 5-2.

11 Concordance is a statistic that evaluates the agreement between the predicted probabilities of a logistic regression model and the pass and fail values of the individual observa tions in the training set. Concordance can have a value from 0% to 100%. If the predicted probabilities complete ly agree with the pass and fail values of the response variable, then the concordance is 100%.6-1 

### 6.0 References

1. T.H. DeFries, J.H. Lindner, C.F. Palacios , S. Kishan, “Investigation of RSD for High Evaporative Emissions Vehicle Detecti on: Denver Summer 20 08 Pre-Testing Study (Version 1),” EPA-090306, prepared for U. S. Environmental Protection Agency, prepared by Eastern Research Gr oup, Austin, Texas, March 6, 2009.

2. D. McClement, “Raw Fuel Leak Survey in I/M Lanes,” prepared for American Petroleum Institute and Coordinating Research Council, prepared by Automotive Testing Laboratories, Mesa, Arizona, June 10, 1998.

3. H.M. Haskew, T.F. Liberty, D. McClement, “Fuel Permeation from Automotive Systems,” CRC Project No. E-65, prepared for California Air Resources Board and Coordinating Research Council, prepared by Harold Haskew & Associates and Automotive Testing Laboratories, September 2004.

4. D. Amlin, R. Carlisle, S. Kishan, R.F. Kl ausmeier, H. Haskew, “Evaporative Emissions Impact of Smog Check,” prepared for Califor nia Bureau of Automotive Repair, prepared by California Bureau of Automotive Repair , Eastern Research Group, de la Torre Klausmeier Consulting, Harold Hask ew & Associates, September 15, 2000.

5. L.C. Landman, “Evaporative Emissions of Gross Liquid Leakers in MOBILE6,” M6.EVP.009, U.S. Environmental Protec tion Agency, EPA420-R-01-024, April 2001.

6. J. Lindner, T.H. DeFries, “Evaluation of Portable SHED Char acteristics,” Draft Technical Note, EPA-090209, prepared for US Environmental Protection Agency, prepared by Eastern Resear ch Group, February 9, 2009.

7. A.D. Burnette, S. Kishan, T.H. DeFries, “Evaluation of Remote Sensing for Improving California’s Smog Check Program (Versi on 15 final),” Final Report, ARB-080303, prepared for California Air Resources Bo ard and California Bureau of Automotive Repair, prepared by Eastern Research Group, Austin, Texas, March 3, 2008.

8. R.O. Gilbert, Statistical Methods for Envi ronmental Pollution Monitoring, Van Nostrand Reinhold, New York, 1987.

9. T.H. DeFries, S. Kishan, “ICR Part B,” submitted to U.S. Environmental Protection Agency, prepared by Eastern Research Group, EPA-080508b, May 8, 2008.

10. J. Kemper, J. Sidebottom, J.H. Lindner, S. Kishan, T.H. DeFries, C. Hart, D. Brzezinski, J. Warila, C. Fulper, H.J. Williamson, “Invest igation of the Ability of RSD to Detect Evaporative Emissions,” presented by T.H. DeFries, presented at the Nineteenth Coordinating Research Council On-Road Vehicle Emissions Workshop, San Diego, California, March 23, 2009.

11. H.J. Williamson, “Measures Useful for Id entifying Vehicles with High Evaporative Emissions,” CACI, 11211 Taylor Drap er Lane, Austin, Texas 78759, CACI-081222, December 22, 2008.

### Appendix A Data Packet1

A-1 

# Packet ID______ (give to RSD van) 

# Date __________ Time __________ am/pm

Vdf # ____ /____/____ (get from RSD van)



# Make__________ Model_________ MY____________ Color_________

State_____Plate __________ Metal Paper 

# Participant: Yes No LSHED: Yes No

Participant First Name _________________________

Pilot Testing Lipan Street Station

Denver, Colorado2

A-2 

## First Contact

Are you the owner of this vehicle? Y N

Is this a Fleet Vehicle? Y N

What is the MY of this vehicle?

______ Is this your normal, every-day car? Y N (no cream puffs, collector’s cars, mechanics specials)


## Your vehicle is eligible for this study. Are you interested in hearing about the project? Y N

I, _____________________, would like to participate in this study. (printed name)

____________________________ Signature

____________________________ Date3

A-3 

## I have received $20.00.

____________________________ Signature

____________________________ Date4

A-4 

### Driver Questionnaire



## I am a contractor for the Envir onmental Protection Agency. We are conducting a study to u nderstand the evaporative em issions of the vehicle fleet. We would like to do some testing of your vehicle. Th e testing of your vehicle would take about 1 hour. Your vehicle was randomly selected for this study. Your participation is voluntary.

1. How many miles do you drive in a given year (12,000 is average)? (a)< 8,000 (b) 8,000-12,000 (c)12,000-24,000 (d) > 24,000 (e) Don’t know


## 2. How long have you owned your car? ________ months / years Don’t know


## 3. At night, do you park this vehicle: (a) Inside a garage (b ) Outside (c) Both



## 4. When was the last time you fueled your vehicle? (a) Last 24 hours (b) 2 days ago (c ) 5 days ago or greater (d) Don’t know


## 5. Does this vehicle get regular, ro utine maintenance from you or someone else? (a) Yes (b) No (c) Don’t know


## 6. Have you had any of the listed maintenance performed on the vehicle, and if so, how long ago? a b c d e Oil Change: Y N ? /// 0-3 months 4-6 months 7 -12 months Don’t Know Tune Up: Y N ? /// 0-3 months 4-6 months 7-12 months Don’t Know NewGasCap: Y N ? /// 0-3 months 4-6 months 7-12 months Don’t Know Fuel System: Y N ? /// 0-3 months 4-6 months 7-12 months Don’t Know MajEngWrk: Y N ? /// 0-3 months 4-6 months 7-12 months Don’t Know



## 7. Have you ever had a gasoli ne smell around your vehicle? Yes No If yes, could you descri be the circumstance. If yes, have you done anything to fix it?



## 8. Has the car ever been in an accident to your knowledge?5

A-5 

## Copy of I/M Inspection Report

(staple here)6

A-6 

## RSD and P-SHED Testing

Start Pre-Condition 7-mile Drive. Time: ____________ am / pm (Lipan, Evans, 85, 285, Federal, Evans, Lipan)

Drive past RSD #2. Ti me: ____________ am / pm

Drive past RSD #3. Ti me: ____________ am / pm

Label Semtech file as: ___ ___ ___ . xml using Data Packet ID

Time HC (ppmC) P baro 

## (mb) T (  C) Initial P-SHED

Put vehicle in SHED and seal the door. Door Sealed

Final P-SHED

Remove vehicle from SHED.7

A-7 

## Vehicle Information Sheet 2

Photos: Front Quarter View (with white board and Packet ID#) All four sides of vehicle License plate close-up (rear) VECI close-up photo VIN close-up photo (windshield or door frame)

VECI label (under hood): Certification Year: ___________

Engine Family: ______

________________ ___________ Evap Family: ________

________________ __________

VIN:

Interior: Transmission Type: Manual Automatic

Fuel Level (circle one) F 3/4 1/2 1/4 <1/4

Odometer Reading

________________________ Odometer Digit Resolution (circle one) 5 68

A-8 

## Modified California Method

Locate and identify the source of strong fuel odors. 

## Fuel Metering Type: Carburetted Fuel-Injected

Engine warmed up and running (Check one descriptor for each Locatio n and each of the 3 methods.)

Location Visual Sniffer IR Camera Underbody fuel lines 0 m S G NP Y N NP Y N NP Bottom of fuel pump 0 m S G NP Y N NP Y N NP Fuel pump to carb 0 m S G NP Y N NP Y N NP In-line fuel filter 0 m S G NP Y N NP Y N NP Fuel rail + connectors 0 m S G NP Y N NP Y N NP All fuel-injectors 0 m S G NP Y N NP Y N NP Ground under vehicle 0 m S G NP Y N NP Y N NP

Engine off (Check one descriptor for each Locatio n and each of the 3 methods.)

Location Visual Sniffer IR Camera Fuel fill pipe to tank joint 0 m S G NP Y N NP Y N NP Tank: rust,straps,damage 0 m S G NP Y N NP Y N NP Non-OEM installations 0 m S G NP Y N NP Y N NP
IR Camera avi file: ____________

General comments:

Descriptors: 0 =No visual evidence of liquid fuel leaks m =Minor signs of fuel (stain ing, damp spots), wicking<1" S =Significant leaks with single drops of f uel from vehicle to the ground, wicking>1" G =Gross leaks, regular flow of drops to t he ground, or a large pool of fuel, wicking>1" NP =Not Performed Y =Positive Instrument Response (Sniffer & IR Camera only) N =Negative Instrument Response (Sniffer & IR Camera only)9

A-9 

## Permission for Additional Testing

We would like to perform additional te sting on your vehicle. This will require overnight laboratory testing at:

Colorado Department of Public Health and Environment 15608 East 18 th 

## Avenue Aurora, Colorado 80011

Your vehicle will be returned to this inspection facility on _________________ by _ : am / pm

I give my permission for this testing.

Signature: ____

______________________ Name: __________

___________________ Street: __________

___________________ City/State: ____

______________________ ZIP: _____________

__________________

Circle Primary Phone Number to Contact

Home (_____) _______--___________

Work (_____) _______--___________

Cell (_____) _______--___________10

A-10 

## Rental Car Checkout

Staple here:

Photocopy of Driver’s License (front and back)

Visual Pre-Inspection of Owner’s Vehicle (Use this only when we keep ow ner’s vehicle over night.)11

A-11 

## Colorado Lab SHED Test

Perform a 1-hour hotsoak test with LA-4 pre-conditioning and in-use fuel

Date _________________ Time_______________ am / pm

License Plate _____________________

State ___________________________

Test Number _____________________

Average SHED Temperature (  F) __________________________

Average SHED Pressure (mm Hg)__________________________

Hotsoak Emissions ___________ g during first 15 minutes

___________ g over 1 hour

The name of the file with mi nute-by-minute hotsoak data is

___________________________

### Appendix B Stratified SamplingB-1 The equations pertaining to stratified sampling di scussed in this section are presented by Gilbert [8]. The goal is to determine the number of obser vations to be taken from each of several strata so that the variability of the mean is minimize d. The equation for the optimal sample size for a given stratum is:

  

#  h h L

1 = h h h h W W n

= n

where

n h = the sample size in stratum number h, n = the total sample size for all strata, W h = the fraction of the actual populat ion that falls in stratum h, L = the number of strata, and

σ h = the standard deviation of the di stribution from which the individual data values in stratum h are sampled.

This equation follows conceptual guidelines. The number of points taken from a stratum is directly proportional to the fract ion of the population comprised of that stratum (the fraction is W h ). Also, the number of points from a stratum is directly proportional to σ h , which is a measure of the variability in the stratum.

The estimate of the population mean, pop x , is the weighted mean of the stratum means, 

### : x h

x W = x h h L

1 = h pop 

## 

The point here is that the strata are not sampled proportionately to their actual representation in the population. If a simple arith metic average of the complete st ratified sample were calculated, the different strata would be weighted dispropor tionately to their repres entation in the population, and a biased average would result. The weighting scheme in the calculation of pop x accounts for the nature of the sample and produces an unbiased estimate of the population mean. The formulation here produces the unb iased estimate of the population mean with the minimum error variance, given the total sample size , n. The standard error of the mean is the square root of its error variance. The standard error of this weighted mean estimate is as follows:

x W = x h h L

1 = h pop 

## 

where f h is the number of data points in stratum h divided by the population si ze of this stratum.

) f

- (1

n W = h h 2 h 2 h L

1 = h x pop   

# B-2 The factor (1-f h ) accounts for the finitude of the population in stratum h. If the sample sizes are small compared to the sizes of the strata in the population, this f actor can be ignored. The result is somewhat conservative (larger) estimates of the standard errors for the stratified results. The factor (1-f h ) has been ignored (set to 1) in the calculati ons presented below, so the standard errors for the stratified analysis are somewhat conservative. In practice the true standard deviations, σ h , are not known and are estimated on the basis of historical data that exist before the planned st ratified sampling effort. The sample standard deviation, s h , based on a sample, x h,i , i=1 to m, is:



### 1 m- ) x - x (

= s 2 h i h, m

1 = i h 

# 

where h 

### x is the arithmetic mean.

When the individual data values are dichotomous, for example, 1 for a vehicle with high evap and 0 for a vehicle with low evap, then the sta ndard deviation can also be expressed using the probability p h that the vehicle has high evap:

h h h q p = s

where:

p h is the probability that a vehicl e in stratum h has high evap, and
q h is the probability that a vehi cle in stratum h has low evap (q h = 1- p h ).

### Appendix C California Evaporative Visual Inspection MethodC-1 In three CRC studies, signs of some fuel staining were noted on many vehicles. Evidence of liquid fuel including, for exam ple, areas where oil and grease on the engine block had been rinsed away, were noted. Gross liquid leaks were reported on other vehicl es. Identification of leaks in this study differentiated between minor si gns of fuel (staining, damp spots) and those leaks with certain potential for re duction in evaporative emissions. The latter type of leak results in appreciable pools of liquid fuel or regular drops of fuel from th e vehicle to the ground. These
leaks are further classified as si gnificant (single drops of fuel) a nd gross (a regular flow of drops or a large pool of fuel).

A mechanic inspected vehicles using the attach ed procedure and tools. Vehicles were not to be repaired. Owners were notified if liquid fuel leaks were detected. They were told that the liquid fuel inspection was not a part of the state I/M procedure, but that the liquid fuel presents
an extreme hazard that warrant s immediate attention.

Inspection results were tabulated to provide statistics regarding major and minor leaks detected by model year inspected. Vehicles were additionally be categorized with respect to carburetion/fuel injection and accumulated odometer at time of inspection. Both cars and trucks were included in the sample.

We estimated that an inspector could inspec t up to six vehicles per hour when vehicles were available for inspection.

Inspection Procedure

Tools

Inspection mirror - 2 X 4" typical, extension handle, ball joint Small flashlight - 6" - to mane uver in and around underhood components Forceps - 12" Folded paper towels, blotter paper, or filter paper. Infrared “snoop” HC analyzer

The corner of a folded paper towel or other blotter will "wick" up fuel from a significant pool, but not a minor drop or a surface stain. Forceps can be used to hold the paper and to approach a suspect area otherwis e blocked by vehicle hardware. To differentiate between a "damp" area and a "liquid" area, the corner of the paper was touc hed to a suspect area. Visual inspection indicated if a signifi cant amount of liquid was absorb ed by the paper (more than 1 inch wet spot). A strong gasoline fuel odor w ould be detected from fuel leaks. Water,C-2 antifreeze, oil, windshield washer solvent, or othe r leaks would result in the strong gasoline odor. The “snoop” analyzer was used to pi npoint the source of HC vapors.

Using the inspection mirror and flashlight, the procedure was to inspect as applicable:

With engine warmed up and running:

Inspect bottom of fuel pump and around pressure line from fuel pump to carb. Inspect in-line fuel filter Inspect fuel inlet to carb Check underbody fuel delivery and return lines. Check fuel rail, connectors and individual fuel injectors. Check floor under vehicle for any sign of fuel accumulation. When strong fuel odors are noted , locate and identify the source.

Additional checks which can be performed with engine off:

Check fuel fill pipe, particularly around joint to tank. Check bottom of tank, particularly around ru st spots, mounting st raps, and any spots showing road damage. Non OEM installations (particu larly second fuel tank add-on s) merit close inspection.

The carburetor base plate, fuel pump and othe r areas will typically show signs of slow fuel seepage (fuel stains or o il deposits washed off). These are not counted as gross leakers unless a measurable pool of fuel or droplets of fuel are detected.

Record model year, make, model, vehi cle type (car, pi ckup, van), fuel injection/carbureted, odometer, and results of inspection.

### Appendix D Participating Vehicle DataD-1 packetID pi_plate pi_metalorpaper pi_state pi_ModelYear pi_Make pi_Model pi_style pi_VECICertYear pi_EngineFamil y pi_EvapFamil y pi_VIN pi_Transmission pi_FuelLevel pi_Odometer pi_OdoResolution pi_FuelMeteringPacketNumber PlatePaperorMetalPlate? StateModelYear Make Model StyleVECICertYear Engine Family Evap Family VINTransmissionFuelLevel OdometerOdometerResolutionFuelMeteringPIL_010 371416G 1994 Subaru Legacy Sedan 1993 RFJ2.2VJGAEK RFJ1030BYM03A . 209748 . FPIL_011 137SJM P CO 1977 Chevrolet Pickup Pickup 1977A . 30209 . CPIL_016 LUV4LK 1995 Chevrolet Monte Carlo Sedan 1995 SIG3.1V8GFEA SIG1058AYMOAA . 160288 . FPIL_019 030284F P CO 1965 Ford Mustang Sedan 1965M . 73450 . CPIL_022 721IGF 2002 Subaru Impreza Sedan 2002 2FJXV02.5JEJ 2FJXR01251BBM . 61240 6 FPIL_024 AC00919 CO 1991 Toyota Corolla Sedan 1991 MTY1.6V5FFD5 EV-EA . 108957 . FPIL_029 921887F P CO 1995 Chevrolet Corsica Sedan 1995 SIG3.1V8GFEA SIG1058AYMOAA . 114398 . FPIL_035 1992 Ford Explorer Sedan 1992 NFM4.0T5FYH8 4.0L-0HM0.25 . . FPIL_046 158EVO M CO 1988 Dodge Pickup Pickup .A 0 50180 5 .PIL_050 266BZR M CO 1994 Subaru Legacy Sedan 1994 RFJ22VJGAEK RFJ1030BYM03A 0.5 172871 6 FPIL_060 620722E P CO 1984 Lincoln Towncar Sedan 1984A 0.25 94222 6 FPIL_061 3957796 P CO 1991 Plymouth Acclaim Sedan .A 0 221478 6 FPIL_062 914EXZ M CO 1991 Toyota Camry Wagon 1991 MTY2.0V5FFF1 EV-EA 0 223286 6 FPIL_063 PBT3734 M CO 1991 Chevrolet Cavalier Sedan 1991M 0.5 102682 6 FPIL_065 124IOG M CO 1996 Mitsubishi Eclipse Convertibl 1996A 0.25 144876 6 FPIL_070 398718G P CO 2000 Chevrolet Suburban SUV 2000 YGMXT05.3182 YGMXE0111920A 0.5 196712 6 FPIL_072 ADH889 M CO 1989 Mercedes 190E Sedan 1989 KMB2.6V6FA12 KMBV62A 0 90100 6 FPIL_078 316KWT M CO 1991 GMC Jimmy SUV 1990 M3G4.3T5XEB2 MBO-3EA 0.5 190360 6 CPIL_079 5978395 M LA 1997 Ford F150 Pickup 1997 VFM5.458GFEK VFM1160AYMFDA 0.25 217264 6 FPIL_084 185371G P CO 1995 Nissan MaximaSedan 1995 SNS3.0VGBEK SNS1057BYM0AA 0 121661 6 FPIL_089 401250G P CO 1995 Ford ContourSedan 1995 SFM2.5VJGFEA SFM1045AYP0AA 0.5 126863 6 FPIL_098 524JJX M CO 1997 Dodge Dakota Pickup 1997 VCR5.928GFGK VCR1090AYPBBA 0.5 151552 6 FPIL_108 549NPA M CO 1995 Jeep Wrangler SUV 1995 SCR2.578GAEA SCR1058AYMONM 0.5 163885 6 FPIL_110 410451G P CO 1987 Chevrolet Blazer SUV 1985 FIG2.8T2TRA3M 0.5 229954 6 FPIL_116 821HBR M CO 1994 GMC Jimmy SUV 1994 R3G4.329GFEA R361053AYMONA 0.5 142248 6 FPIL_117 35061AA M CO 1992 Ford F150 Truck 1992 5.0L-OHM NFM5.8T5HZL1-0LA 0.5 170483 6 FPIL_118 803KWW M CO 2001 Nissan XterraSUV 2001 1NSXT03.3C5A 1N5XR0120RCAA 0 105648 6 FPIL_123 275NFE M CO 1992 Dodge Stealth Sedan 1992 NMT3.0V5FFD6 IBM 0.75 109020 6 FPIL_124 184129G P CO 1989 Ford Bronco SUV . KFM5.875HZZ4A 0.75 15486 5 FPIL_128 921NPB M CO 1994 Chevrolet Sierra1500 Pickup 1994 REG5.785GAEB R3G1085AYM0AA 0.5 235330 6 FPIL_130 404917G P CO 1994 Dodge Ram Pickup 1990 LCR5.9T5H6F8 LCRTEA 0.5 194740 6 FPIL_131 278ITC M CO 1994 Jeep Cherokee SUV 1994 RCR4.078GAEA RCR1058AYMONA 0.25 229501 6 FPIL_132 401442G P CO 1995 Pontiac Grand PrixSE Sedan 1995 S1G3.1V8GFEA SIG1058AYMOAA 0.25 177033 6 FPIL_137 938268F P CO 1989 Ford Aerostar Van 1989 KKFM3.0T5FYK2A 1 78611 5 FPIL_138 039302F P CO 1999 Infinity C20 Sedan 1999 XNSXV02.0AZA XNSXE011OMBAM 1 91634 6 FPIL_146 939783F P CO 1994 Jeep Cherokee SUV 1994 RCR4.078GAEA RCR1058AYMONA 0.5 155203.3 6 FPIL_151 318NAA M CO 1986 Chevrolet Sprint Plus Sedan 1986 OSK1.0V2FFL5 EV1M 0.25 88813 5 CPIL_157 461NOU M CO 1989 Chevrolet Blazer SUV 1989 K3G5.7T5TYA3 KDO-3CM 0.25 81287 5 FPIL_161 679NAZ M CO 1991 Subaru Legacy Wagon 1991 MFJ2.2V5FFE1 Y-HUA . 225480 6 FPIL_165 801774E P CO 1992 Saturn SLSedan 1992 N4G1.9V5JPH5 NAO-4BA 0.5 64669 6 FPIL_169 475MPG M CO 1987 Porsche 944 Sedan 1987 19HPR151V5FE39? ..K?M 0.5 163538 6 FPIL_174 051LIT M CO 2000 Toyota Corolla Sedan 2000 YTYXV01.8FFA YTYXR0115AK1A 0.25 68100 6 FPIL_177 29262 P CO 2002 Toyota Camry Sedan 2002 2TYXV02.4JJASFI 2TYXR0135AK1M 0.5 105292 6 FPIL_184 BLM831 M CO 1991 Honda Civic Sedan .M 0.75 165882 6 FPIL_191 499NXU M CO 1994 Toyota Tercel Sedan 1994 RTY1.5BHGAFA RTY1047DYM00M 0.25 183633 6PIL_193 YLL142 M CO 1998 Ford Mustang Sedan 1998 WFMXE0045AAAA . 153203 6 FPIL_194 833GTT M CO 1990 Ford TaurusSedan 1990 LFM3.0V5FXG5 TWC-H02J1MPIA 1 91937 5 FD-2 packetID pi_plate pi_metalorpaper pi_state pi_ModelYear pi_Make pi_Model pi_style pi_VECICertYear pi_EngineFamil y pi_EvapFamil y pi_VIN pi_Transmission pi_FuelLevel pi_Odometer pi_OdoResolution pi_FuelMeteringPacketNumber PlatePaperorMetalPlate? StateModelYear Make Model StyleVECICertYear Engine Family Evap Family VINTransmissionFuelLevel OdometerOdometerResolutionFuelMeteringPIL_200 51966ML M CO 1988 GMC Sierra Pickup 1988 1364.3T5TAA0 3F0-3BA 0.75 145096 6 FPIL_203 643KCU M CO 2000 Ford Taurus Sedan .A 0.5 151771 6 FPIL_213 VTTBOTS M CO 1987 ToyotaCamry Sedan 1987 HTY2.0V5FBB4 EV-EM 1 192201 6 FPIL_217 028RJT M CO 2001 Mercury SableSedan 2001 1FMXV03.0VF3 3.0L-FMXR011SBAA 0.5 153356 6 FPIL_218 850FTE M CO 1984 Porsche 944 Sedan 1984 151V5FE03 ?HM 0.75 . . FPIL_220 348AOP M CO 1996 Ford Ranger Pickup 1996 TFM4.028GKEK TEM1045AYPBAM 0 231013 6 FPIL_221 NO PLATE 1993 Buick LeSabre Sedan 1993 PIG3.8V8JGB4 PBO-1RA 0.5 193041 6 FPIL_222 034KAT M CO 1989 Dodge Caravan Van 1989 KCR3.0T5FBL6 KCRTCA 0.5 225879 6 FPIL_223 340FUB M CO 1994 Mazda B2300 Pickup 1994 RTK2.318GFEA 2-3L-RTK1065AYPM 0 151816 6 FPIL_225 939231F P CO 1985 Jeep CJ7 SUV 1994 P5249610M 0.5 121987 6 FPIL_226 NO PLATE 1991 Ford F250 Pickup 1990 LFM07.585WX 7.5C9HWM 1 61329 5 FPIL_229 292AKJ M CO 1985 Chrysler New Yorker Sedan .A 0.25 155701 6 FPIL_236 401454G P CO 1995 Ford ContourSedan 1995 SFM2.5VJGFEA SFM1045AYP0AA 0.25 126863 6 FPIL_240 034366F P CO 1997 Isuzu Rodeo SUV 1997 VSZ3.22JGKFK VSZ1095AYMEOM 0.25 108522 6 FPIL_242 PAX259 M CO 1993 Jeep Wrangler SUV 1994 RCR4.078GAEA RCR1058AYMONM 0 83662 6 FPIL_245 358NPT M CO 1997 Lincoln Towncar Sedan 1997 VFM4.6V8GKFL VFM1090AYMEPA 0.5 125885 6 FPIL_247 937581F P CO 1992 Cadillac Deville Sedan 1992 N2G4.9V8XGA8 NG0-2BA 0.5 169427 6 FPIL_248 581LNL M CO 1987 Ford F150 Pickup 1987 HFM5.0Y5HAGX 5.0L-7HMM 1 46394 5 FPIL_250 399022G P CO 1990 Volvo 740GLE Wagon 1990 LVV2.3V5F897 E3A 0.25 182338 6 FPIL_251 PBN6774 M CO 1990 Mercury Topaz Sedan .A 0.25 16238 5 FPIL_254 371MVY M CO 1996 Jeep Grand Cherokee SUV 1996 TCRA4.028GKEK TCR1073AYPBPA 0.25 117718 6 FPIL_256 NO PLATE 1999 Oldsmobile Alero Sedan 1999 XGMXV03.4042 XGMXR0124912A 0 124136 6 FPIL_257 754KCN M CO 1990 Chevrolet S10 Pickup .M 0.5 74866 6 FPIL_258 761JBG M CO 2002 Chevrolet Trailblazer SUV 2002 2GMXT04.2185 2GMXR0175922A 0.5 50049 6 FPIL_266 UFF9944 M CO 1989 Volkswagen Golf Wagon .M 0.25 22696 5 FPIL_270 406626G P CO 1992 Jeep Wrangler SUV .M 1 122720 6 FPIL_271 842NNA M CO 1991 Dodge Dakota Pickup 1993 PCR3.9T5FFL7 PTAPFA 0.5 107371 6 CPIL_272 665ELF M CO 1990 Jeep Wrangler SUV 1990 LAM4.2T2HEA4 LAM4.2F-1PA 0.25 199329 6 FPIL_274 405028G P CO 1999 Dodge IntrepidSedan 1999 XCRV02.7VB0 XCRXR0101GBFA 0 184036 6 FPIL_281 PN7271 M CO 1986 Honda Accord Sedan .M 0.25 278622 6 FPIL_283 938NNI M CO 1986 Ford Mustang Sedan 1986 GFM5.0V5HBF9 5-0L6HMM 0.75 33505 5 FPIL_284 403NEV M CO 1991 Toyota Tercel Sedan 1991 MTY1.5V5FFF1 EV-EM 0.5 226004 6 FPIL_286 ADV872 M CO 1983 Toyota Landcruiser SUV 1983 DTY4.2T2AFF3 EV-FM 0.75 151573 6 CPIL_287 99051AA M CO 1996 Ford F150 Pickup 1996 TFM4.958GFJK 4.9L-TFM1045AYMM 0.25 134467 6 FPIL_290 360GNT M CO 1998 Nissan AltimaSedan 1998 WNSXV02.433B WNSXR0110RCAA 0 123860 . FPIL_294 916BPC M CO 2001 Subaru Legacy Wagon 2002 2FJXV02.5JHM 2FJXR01251CCA 0.25 144387 6 FPIL_298 579XBG M CO 2002 Mazda Protege Sedan 2002 2TKXV02.0GJA 2TKXR0125PMAA 0.5 67273 6 FPIL_299 405129G P CO 1986 Chevrolet Chevette Sedan 1986 G1G1.6V2NEA3 6B5-1AA 0.5 42044 5 CPIL_300 551PAU M CO 2003 Ford Focus Sedan 2003 3FMXV02.0VH1 3FMXR0080BBEA 0.25 64080 6 FPIL_304 781NPM M CO 1993 Jeep Cherokee SUV .A 0.25 173573 6 F

### Appendix E Selection RSD DataE-1 packetID HCBinFlagAll RndThreshAll sR_1stcontactdate sR_1stcontacttime sR_date sR_vdf bs_samSpeed bs_samAccel VSP bn_HC3000_ppmC3 bs_HC4000_ppmC3 bs_CO4000_pct bs_NX4000_ppm bs_CO24000_pct RSDEvpIndex0 RSDEvpIndex1PacketNumberRSD4000HC BinFractionof SampleSelectedFirstContactDateFirstContactTimeSelectionRSDDateSelectionRSDVDFSpeed(mph)Accel(mph/s)VSP(kW/Mg)RSD3000HC(ppmC3)RSD4000HC(ppmC3)RSD4000CO(%)RSD4000NO(ppm)RSD4000CO2(%)RSDEvapIndex 0RSDEvapIndex 1PIL_010 1 0.000883 07/30/08 11:19 07/30/08 47 14.4 0.2 1.7 -54 -4 0.04 -8 15.03 50 53PIL_011 9 0.657 07/30/08 13:44 07/30/08 104 5.5 0.1 0.5 12425 11579 3.50 778 12.17 -846 161PIL_016 7 0.48 07/30/08 16:26 07/30/08 206 12.2 0.6 2.5 489 874 1.91 709 13.63 385 149PIL_019 8 0.622 07/31/08 12:51 07/31/08 112 11.0 1.9 5.2 927 1133 3.94 324 12.19 206 287PIL_022 6 0.288 07/31/08 14:40 07/31/08 163 6.6 2.1 3.4 483 617 4.74 75 11.64 134 76PIL_024 8 0.622 08/01/08 10:39 08/01/08 67 11.9 2.0 6.1 495 1221 0.06 475 14.96 726 96PIL_029 8 0.622 08/01/08 13:55 08/01/08 175 19.9 0.5 3.7 780 1261 0.74 103 14.48 481 132PIL_035 9 0.657 08/01/08 16:35 08/01/08 266 14.5 0.5 2.7 6331 4174 0.82 110 14.33 -2157 821PIL_046 8 0.622 08/04/08 14:50 08/04/08 258 16.0 3.5 13.4 -1943 1757 0.08 1791 14.88 3700 1006PIL_050 6 0.288 08/04/08 15:17 08/04/08 272 20.1 5.3 24.9 26 453 3.95 602 12.19 428 29PIL_060 7 0.48 08/05/08 12:52 08/05/08 147 13.7 3.0 9.9 730 789 7.62 57 9.56 59 120PIL_061 7 0.48 08/05/08 13:19 08/05/08 163 15.0 3.9 14.0 504 700 4.19 1000 11.99 197 64PIL_062 6 0.288 08/05/08 13:40 08/05/08 173 11.4 2.9 8.0 491 632 0.30 1274 14.77 141 91PIL_063 5 0.1535 08/05/08 14:14 08/05/08 186 13.5 1.0 4.1 271 298 0.49 168 14.69 26 30PIL_065 8 0.622 08/05/08 15:16 08/05/08 256 11.3 1.9 5.6 1046 1670 1.36 37 14.03 625 682PIL_070 8 0.622 08/06/08 13:00 08/06/08 140 13.9 1.8 6.6 1468 1619 1.62 285 13.83 151 42PIL_072 7 0.48 08/07/08 10:45 08/07/08 69 16.5 6.3 23.9 742 933 8.60 321 8.85 192 42PIL_078 6 0.2191 08/08/08 9:50 08/08/08 50 14.6 3.2 11.2 381 489 1.08 1451 14.21 108 28PIL_079 3 0.0361 08/08/08 10:35 08/08/08 71 11.3 1.6 4.7 182 118 0.02 289 15.03 -63 27PIL_084 2 0.0124 08/08/08 13:39 08/08/08 182 17.4 6.2 25.3 41 69 0.15 666 14.92 28 39PIL_089 9 0.0627 08/09/08 10:30 08/09/08 64 11.7 2.3 6.8 1786 2052 4.28 -6 11.92 266 107PIL_098 2 0.0124 08/11/08 13:58 08/11/08 201 12.6 2.0 6.5 -51 31 0.14 323 14.94 81 24PIL_108 4 0.118 08/12/08 16:19 08/12/08 252 13.1 2.2 7.3 -49 186 0.22 202 14.88 235 42PIL_110 9 0.3 08/12/08 16:51 08/12/08 266 15.1 3.3 11.9 5820 5599 5.71 332 10.78 -221 228PIL_116 7 0.52 08/13/08 10:56 08/13/08 72 12.0 1.4 4.6 -1291 725 0.06 69 14.98 2015 162PIL_117 9 0.3 08/13/08 11:15 08/13/08 81 13.3 1.8 6.3 1871 2137 0.65 1222 14.48 265 128PIL_118 5 0.54 08/13/08 11:45 08/13/08 92 15.8 3.3 12.7 -69 356 0.24 16 14.87 425 51PIL_123 1 0.028 08/13/08 15:08 08/13/08 189 14.2 1.2 4.9 -64 -44 0.13 -68 14.97 20 38PIL_124 3 0.093 08/13/08 15:52 08/13/08 218 10.6 1.2 3.5 34 132 0.05 340 15.00 98 48PIL_128 7 0.52 08/14/08 9:40 08/14/08 49 9.9 1.5 4.0 1113 983 0.53 1951 14.57 -131 84PIL_130 6 0.42 08/14/08 11:20 08/14/08 100 15.7 4.2 15.8 467 529 6.05 419 10.69 62 42PIL_131 8 1 08/14/08 12:30 08/14/08 142 13.2 1.8 6.3 154 1270 0.63 1549 14.51 1116 128PIL_132 6 0.42 08/14/08 12:45 08/14/08 153 12.8 1.8 6.0 126 495 0.05 133 15.00 368 81PIL_137 6 0.42 08/14/08 16:45 08/14/08 272 16.6 3.5 13.9 408 494 2.25 1453 13.37 86 43PIL_138 3 0.093 08/18/08 9:00 08/18/08 16 15.0 4.2 15.0 33 92 0.06 440 14.99 59 38PIL_146 5 0.54 08/18/08 13:00 08/18/08 151 7.2 1.6 3.1 136 357 0.01 -42 15.04 221 96PIL_151 5 0.54 08/18/08 15:40 08/18/08 246 10.2 3.0 7.4 234 261 4.16 19 12.06 28 37PIL_157 7 0.52 08/19/08 11:15 08/19/08 112 14.6 1.4 5.6 997 827 1.80 691 13.72 -169 27PIL_161 5 0.54 08/19/08 14:34 08/19/08 222 13.6 0.9 3.6 121 324 0.28 110 14.84 203 132PIL_165 7 0.52 08/19/08 16:48 08/19/08 276 11.6 1.7 5.1 373 757 1.40 39 14.03 384 67PIL_169 5 0.54 08/20/08 10:34 08/20/08 74 12.4 1.4 4.6 332 358 0.64 1909 14.52 26 32PIL_174 1 0.028 08/20/08 12:17 08/20/08 129 17.2 4.0 16.5 -31 -12 0.03 342 15.02 19 34PIL_177 1 0.028 08/20/08 14:41 08/20/08 202 15.7 1.4 6.1 -30 -8 0.01 32 15.05 22 39PIL_184 5 0.54 08/21/08 9:42 08/21/08 45 13.7 3.7 12.2 -18 261 1.16 464 14.20 279 41E-2 packetID HCBinFlagAll RndThreshAll sR_1stcontactdate sR_1stcontacttime sR_date sR_vdf bs_samSpeed bs_samAccel VSP bn_HC3000_ppmC3 bs_HC4000_ppmC3 bs_CO4000_pct bs_NX4000_ppm bs_CO24000_pct RSDEvpIndex0 RSDEvpIndex1PacketNumberRSD4000HC BinFractionof SampleSelectedFirstContactDateFirstContactTimeSelectionRSDDateSelectionRSDVDFSpeed(mph)Accel(mph/s)VSP(kW/Mg)RSD3000HC(ppmC3)RSD4000HC(ppmC3)RSD4000CO(%)RSD4000NO(ppm)RSD4000CO2(%)RSDEvapIndex 0RSDEvapIndex 1PIL_191 8 1 08/21/08 13:37 08/21/08 162 17.6 1.1 5.6 1120 1139 3.88 1235 12.19 19 37PIL_193 3 0.093 08/21/08 14:12 08/21/08 174 16.1 2.4 9.8 63 115 0.18 53 14.92 52 49PIL_194 8 1 08/21/08 14:25 08/21/08 178 8.4 2.7 5.7 1083 1426 2.32 298 13.34 343 41PIL_200 6 0.42 08/22/08 9:30 08/22/08 34 15.7 2.5 9.8 413 435 0.41 836 14.71 22 49PIL_203 4 0.118 08/22/08 11:51 08/22/08 124 19.0 5.2 23.4 189 208 4.92 39 11.52 19 43PIL_213 8 1 08/23/08 8:23 08/23/08 29 13.1 1.8 6.1 969 1119 0.29 2021 14.74 150 171PIL_217 5 0.54 08/23/08 10:50 08/23/08 107 8.3 2.7 5.5 198 267 -0.09 -157 15.11 69 90PIL_218 3 0.093 08/23/08 11:30 08/23/08 120 9.2 4.7 10.0 109 137 0.57 1289 14.59 28 55PIL_220 4 0.118 08/23/08 12:19 08/23/08 154 16.9 2.1 8.9 -17 170 0.52 42 14.67 186 51PIL_221 5 0.54 08/25/08 9:10 08/25/08 31 10.5 0.9 2.8 19 373 0.17 377 14.91 354 44PIL_222 8 1 08/25/08 9:45 08/25/08 50 14.7 1.1 4.6 897 1364 0.35 1159 14.72 467 47PIL_223 6 0.42 08/25/08 10:31 08/25/08 85 8.2 2.9 5.8 133 575 0.02 44 15.02 442 182PIL_225 9 0.3 08/25/08 12:05 08/25/08 144 12.8 2.2 7.1 7149 7301 12.24 1268 6.01 152 830PIL_226 6 0.42 08/25/08 12:15 08/25/08 147 14.5 2.9 10.1 -43 441 1.47 2266 13.91 484 36PIL_229 4 0.118 08/25/08 15:12 08/25/08 251 12.2 3.5 10.3 172 179 0.46 1241 14.67 6 47PIL_236 8 1 08/26/08 9:11 08/26/08 37 15.1 0.9 4.2 2140 1684 0.33 818 14.74 -456 88PIL_240 4 0.118 08/26/08 10:20 08/26/08 76 18.7 5.6 24.5 136 178 2.86 94 13.00 42 61PIL_242 8 1 08/26/08 12:12 08/26/08 138 15.0 0.5 2.7 993 1106 0.03 32 15.00 112 347PIL_245 4 0.118 08/26/08 13:40 08/26/08 182 17.9 0.7 4.2 -162 187 0.05 31 15.01 350 53PIL_247 9 0.3 08/26/08 16:43 08/26/08 273 13.6 3.3 10.9 1830 5098 0.27 454 14.69 3268 271PIL_248 6 0.42 08/27/08 9:20 08/27/08 31 16.7 4.9 19.1 824 560 1.99 1475 13.56 -264 100PIL_250 7 0.52 08/27/08 11:20 08/27/08 91 16.8 4.2 16.7 301 705 0.15 436 14.91 404 193PIL_251 5 0.54 08/27/08 11:55 08/27/08 106 16.3 4.0 15.4 241 379 0.23 3169 14.77 138 33PIL_254 3 0.093 08/27/08 12:40 08/27/08 135 16.0 3.1 12.1 111 136 0.41 2508 14.66 26 35PIL_256 4 0.118 08/27/08 13:50 08/27/08 175 13.9 4.5 14.7 210 210 0.03 338 15.01 0 102PIL_257 1 0.028 08/27/08 14:15 08/27/08 184 14.2 0.9 3.7 -39 -20 -0.05 -12 15.09 19 43PIL_258 1 0.028 08/27/08 14:30 08/27/08 187 11.6 2.4 7.0 -72 -6 0.01 58 15.05 66 55PIL_266 8 1 08/28/08 9:55 08/28/08 41 16.7 6.4 24.7 1165 1115 0.81 3724 14.30 -50 67PIL_271 6 0.42 08/28/08 12:05 08/28/08 105 18.8 5.1 22.6 608 584 5.95 395 10.76 -24 49PIL_272 7 0.52 08/28/08 12:21 08/28/08 108 12.1 2.6 7.9 724 977 4.50 443 11.78 253 66PIL_274 6 0.42 08/28/08 12:40 08/28/08 134 11.1 1.4 4.1 377 405 0.18 439 14.90 28 36PIL_281 5 0.54 08/28/08 16:45 08/28/08 275 13.5 2.7 8.9 242 334 0.94 589 14.35 92 41PIL_283 5 0.54 08/29/08 9:31 08/29/08 57 13.9 3.6 12.2 207 248 0.24 455 14.86 41 70PIL_284 5 0.54 08/29/08 9:55 08/29/08 70 11.8 3.0 8.6 322 345 0.41 233 14.74 23 67PIL_286 7 0.52 08/29/08 11:55 08/29/08 150 12.6 0.8 3.1 467 850 0.96 2114 14.26 383 112PIL_287 7 0.52 08/29/08 13:00 08/29/08 196 16.5 6.0 23.1 533 900 0.72 245 14.50 366 286PIL_290 6 0.42 08/29/08 14:05 08/29/08 227 10.1 1.9 5.0 610 561 0.02 31 15.02 -49 181PIL_294 1 0.028 08/29/08 16:25 08/29/08 346 10.6 1.4 4.0 -53 -20 0.83 -27 14.46 33 81PIL_298 6 0.42 08/30/08 9:03 08/30/08 29 14.8 2.2 8.2 35 507 0.02 -4 15.03 472 53PIL_299 5 0.54 08/30/08 9:25 08/30/08 44 12.8 2.9 9.0 98 343 0.09 3722 14.85 244 79PIL_300 5 0.54 08/30/08 9:45 08/30/08 51 15.7 4.4 16.2 78 298 0.19 67 14.90 220 99PIL_304 7 0.52 08/30/08 11:42 08/30/08 115 18.9 1.7 8.4 685 708 10.09 300 7.79 24 60

### Appendix F Conditioning Drive DataF-1 packetID dr_date dr_time Packet Number Drive Date Drive Time PIL_010 07/30/08 11:46 PIL_011 07/30/08 14:01 PIL_016 07/30/08 17:05 PIL_019 07/31/08 13:17 PIL_022 07/31/08 15:22 PIL_022 07/31/08 16:45 PIL_024 08/01/08 11:18 PIL_029 08/02/08 8:17 PIL_029 08/04/08 7:53 PIL_035 08/01/08 17:12 PIL_046 08/04/08 15:35 PIL_050 08/04/08 15:50 PIL_050 08/04/08 16:20 PIL_060 08/05/08 13:22 PIL_061 08/05/08 13:43 PIL_062 08/05/08 14:38 PIL_063 08/05/08 15:19 PIL_065 08/05/08 16:31 PIL_070 08/06/08 13:30 PIL_072 08/07/08 12:25 PIL_078 08/08/08 10:22 PIL_079 08/08/08 11:11 PIL_084 08/08/08 14:12 PIL_089 08/09/08 11:18 PIL_098 08/11/08 14:16 PIL_108 08/12/08 17:10 PIL_110 08/12/08 17:50 PIL_116 08/13/08 13:15 PIL_117 08/13/08 11:42 PIL_118 08/13/08 12:16 PIL_123 08/13/08 15:19 PIL_124 08/13/08 16:14 PIL_128 08/14/08 10:20 PIL_130 08/14/08 11:40 PIL_131 08/14/08 12:55 PIL_132 08/14/08 13:35 PIL_137 08/14/08 17:02 PIL_138 08/18/08 9:37 PIL_146 08/18/08 13:30 PIL_151 08/18/08 16:10 PIL_157 08/19/08 11:52 PIL_161 08/19/08 15:07 PIL_165 08/20/08 8:16 PIL_169 08/20/08 11:27 PIL_174 08/20/08 12:51 PIL_177 08/20/08 15:13 PIL_184 08/21/08 10:14 PIL_191 08/21/08 14:07 PIL_193 08/21/08 14:36 PIL_194 08/21/08 15:12 PIL_200 08/22/08 10:10F-2 packetID dr_date dr_time Packet Number Drive Date Drive Time PIL_203 08/22/08 12:36 PIL_213 08/23/08 8:58 PIL_217 08/23/08 11:23 PIL_218 08/23/08 11:59 PIL_220 08/23/08 12:54 PIL_221 08/25/08 9:44 PIL_222 08/25/08 10:21 PIL_223 08/25/08 11:08 PIL_225 08/25/08 13:30 PIL_226 08/25/08 12:45 PIL_229 08/25/08 15:53 PIL_236 08/26/08 9:56 PIL_240 08/26/08 11:20 PIL_242 08/26/08 12:58 PIL_245 08/26/08 14:29 PIL_247 08/26/08 17:39 PIL_248 08/27/08 9:36 PIL_250 08/27/08 11:41 PIL_251 08/27/08 15:09 PIL_254 08/27/08 13:23 PIL_256 08/27/08 14:29 PIL_257 08/28/08 8:50 PIL_258 08/27/08 16:07 PIL_266 08/28/08 10:34 PIL_270 08/28/08 12:20 PIL_271 08/28/08 13:43 PIL_272 08/28/08 13:01 PIL_274 08/28/08 14:26 PIL_281 08/28/08 17:15 PIL_283 08/29/08 10:05 PIL_284 08/29/08 10:48 PIL_286 08/29/08 13:17 PIL_287 08/29/08 14:10 PIL_290 08/29/08 14:50 PIL_294 08/29/08 16:51 PIL_298 08/30/08 9:37 PIL_299 08/30/08 10:13 PIL_300 08/30/08 10:51 PIL_304 08/30/08 12:15

### Appendix G Measurement RSD DataG-1 packetID mR_date mR_time mR_vdf bs_samSpeed bs_samAccel VSP bn_HC3000_ppmC3 bs_HC4000_ppmC3 bs_CO4000_pct bs_NX4000_ppm bs_CO24000_pct RSDEvpIndex0 RSDEvpIndex1PacketNumberMeasurementRSDDateMeasurementRSDTimeMeasurementRSDVDFSpeed(mph)Accel(mph/s)VSP(kW/Mg)RSD3000HC(ppmC3)RSD4000HC(ppmC3)RSD4000CO(%)RSD4000NO(ppm)RSD4000CO2(%)RSDEvapIndex0RSDEvapIndex1PIL_010 07/30/08 12:02 68 15.8 2.810.9 26 21 0.03 901 15.00 -5 38PIL_010 07/30/08 12:04 70 17.3 3.313.9 27 36 0.14 1204 14.91 8 48PIL_011 07/30/08 15:50 195 16.1 2.710.7 11662 10456 11.71 478 6.32 -1206 1969PIL_011 07/30/08 16:10 205 16.4 2.710.9 11635 10705 12.33 607 5.87 -930 1146PIL_019 07/31/08 13:35 135 15.4 2.810.7 834 1252 0.80 1321 14.39 418 665PIL_019 07/31/08 13:38 138 15.7 3.814.2 1151 1384 0.80 2054 14.36 233 223PIL_022 07/31/08 15:38 197 19.8 4.822.5 24 165 0.19 60 14.91 141 42PIL_022 07/31/08 17:11 247 20.5 5.024.3 126 99 0.01 23 15.04 -26 61PIL_022 07/31/08 17:13 248 19.6 4.922.5 25 12 0.03 167 15.03 -13 45PIL_024 08/01/08 11:32 98 17.3 3.113.1 992 1845 0.09 1052 14.90 853 305PIL_024 08/01/08 11:34 99 16.7 2.610.7 927 2268 0.06 1232 14.90 1341 568PIL_029 08/02/08 8:33 17 19.6 3.717.4 -13 42 0.15 49 14.94 54 28PIL_029 08/02/08 8:35 18 18.5 3.716.5 3 37 0.05 69 15.02 34 38PIL_029 08/04/08 8:09 14 19.3 3.516.6 -3 80 0.12 760 14.94 83 49PIL_029 08/04/08 8:10 15 0.0 0.00.0 72 40 0.04 4284 14.87 -32 32PIL_035 08/01/08 18:12 282 17.5 3.213.5 8050 4951 1.57 97 13.77 -3100 815PIL_035 08/01/08 18:13 283 18.0 3.816.2 4109 3975 6.00 29 10.63 -134 2135PIL_046 08/04/08 15:58 301 15.7 0.63.2 -1565 2127 0.06 750 14.92 3692 715PIL_046 08/04/08 16:00 302 19.9 4.320.3 -198 1268 2.74 473 13.03 1466 770PIL_050 08/04/08 16:05 304 15.3 4.014.7 43 296 0.09 361 14.97 252 39PIL_050 08/04/08 16:08 306 19.6 4.018.8 299 473 4.00 298 12.16 174 50PIL_050 08/04/08 16:40 326 20.5 4.823.0 312 428 4.48 286 11.82 116 45PIL_050 08/04/08 16:42 327 20.2 3.718.0 255 445 2.68 430 13.11 189 33PIL_060 08/05/08 13:35 176 15.6 3.312.3 353 399 1.85 105 13.71 46 55PIL_060 08/05/08 13:42 180 16.3 4.015.5 286 323 1.59 334 13.89 38 56PIL_061 08/05/08 13:57 191 15.4 3.713.7 538 557 0.55 2733 14.54 19 45PIL_061 08/05/08 14:07 196 16.8 3.815.4 746 728 2.53 1606 13.16 -18 57PIL_062 08/05/08 14:53 220 15.9 3.714.2 269 285 0.19 2031 14.84 15 50PIL_062 08/05/08 15:01 232 11.0 42.0102.6 286 278 0.30 1797 14.77 -7 30PIL_063 08/05/08 15:36 246 20.7 8.037.8 7 222 0.27 1366 14.80 214 46G-2 packetID mR_date mR_time mR_vdf bs_samSpeed bs_samAccel VSP bn_HC3000_ppmC3 bs_HC4000_ppmC3 bs_CO4000_pct bs_NX4000_ppm bs_CO24000_pct RSDEvpIndex0 RSDEvpIndex1PacketNumberMeasurementRSDDateMeasurementRSDTimeMeasurementRSDVDFSpeed(mph)Accel(mph/s)VSP(kW/Mg)RSD3000HC(ppmC3)RSD4000HC(ppmC3)RSD4000CO(%)RSD4000NO(ppm)RSD4000CO2(%)RSDEvapIndex0RSDEvapIndex1PIL_063 08/05/08 15:39 248 20.5 7.635.8 132 220 0.27 1791 14.79 87 28PIL_065 08/05/08 16:52 284 18.9 5.724.9 520 579 8.38 38 9.03 59 152PIL_065 08/05/08 16:57 286 19.2 5.625.2 294 315 7.28 94 9.82 21 46PIL_070 08/06/08 13:46 168 13.9 3.010.1 913 988 1.37 37 14.04 75 61PIL_070 08/06/08 13:50 171 14.7 3.211.4 1347 1564 5.66 330 10.94 217 65PIL_072 08/07/08 12:42 127 17.7 6.626.9 973 962 6.59 255 10.29 -11 55PIL_072 08/07/08 12:45 132 15.5 4.115.2 484 498 3.25 261 12.70 14 54PIL_078 08/08/08 10:35 72 15.9 4.215.7 -19 105 0.13 2523 14.87 124 41PIL_078 08/08/08 10:41 81 15.2 3.613.1 202 275 0.33 1117 14.77 73 50PIL_079 08/08/08 11:27 108 19.1 2.813.0 60 90 0.62 243 14.60 31 30PIL_079 08/08/08 11:29 119 16.7 2.911.8 42 22 0.16 71 14.94 -21 41PIL_084 08/08/08 14:28 214 15.9 3.513.4 59 76 0.55 115 14.65 17 48PIL_084 08/08/08 14:34 220 15.8 4.115.3 85 68 0.38 340 14.77 -17 73PIL_089 08/09/08 11:32 92 14.7 2.910.5 1364 1674 2.18 380 13.43 309 62PIL_089 08/09/08 11:40 105 15.2 4.215.2 170 192 3.28 413 12.68 21 44PIL_098 08/11/08 14:32 225 18.8 5.122.4 -171 48 0.16 2126 14.86 219 78PIL_098 08/11/08 14:35 231 18.9 4.8 21.2 32 -19 0.01 331 15.03 -52 39PIL_108 08/12/08 17:22 277 16.1 4.015.5 271 721 1.76 547 13.75 450 155PIL_108 08/12/08 17:25 278 15.5 3.412.8 180 301 0.45 419 14.71 121 128PIL_110 08/12/08 18:05 279 19.7 2.010.1 2120 2431 6.44 -34 10.36 311 108PIL_110 08/12/08 18:07 280 17.7 3.314.2 1270 1958 9.69 171 8.04 687 162PIL_116 08/13/08 13:30 141 25.0 1.610.9 75 472 0.11 124 14.95 397 29PIL_116 08/13/08 13:32 144 18.0 5.121.4 -129 527 0.06 3313 14.88 656 91PIL_117 08/13/08 11:55 98 18.5 5.222.4 888 984 3.61 589 12.42 96 203PIL_117 08/13/08 11:58 99 18.6 5.122.2 1078 1650 3.76 527 12.29 572 223PIL_118 08/13/08 12:26 122 23.4 2.816.1 -2 61 0.58 0 14.63 62 50PIL_118 08/13/08 12:30 123 18.8 4.118.5 303 276 0.03 124 15.02 -27 79PIL_123 08/13/08 15:33 208 17.6 3.2 13.8 -81 -47 0.36 219 14.79 33 46PIL_123 08/13/08 15:35 209 18.5 6.427.5 288 351 2.59 754 13.16 63 97PIL_124 08/13/08 16:31 234 23.2 1.17.3 785 920 0.48 1183 14.64 136 106G-3 packetID mR_date mR_time mR_vdf bs_samSpeed bs_samAccel VSP bn_HC3000_ppmC3 bs_HC4000_ppmC3 bs_CO4000_pct bs_NX4000_ppm bs_CO24000_pct RSDEvpIndex0 RSDEvpIndex1PacketNumberMeasurementRSDDateMeasurementRSDTimeMeasurementRSDVDFSpeed(mph)Accel(mph/s)VSP(kW/Mg)RSD3000HC(ppmC3)RSD4000HC(ppmC3)RSD4000CO(%)RSD4000NO(ppm)RSD4000CO2(%)RSDEvapIndex0RSDEvapIndex1PIL_124 08/13/08 16:32 235 24.2 0.75.8 3668 2510 1.89 464 13.61 -1157 222PIL_128 08/14/08 10:37 76 23.4 2.615.2 296 626 0.67 2855 14.46 330 44PIL_128 08/14/08 10:39 79 22.5 2.313.3 330 412 0.67 2777 14.46 83 52PIL_130 08/14/08 11:56 125 20.2 2.813.8 382 365 3.77 846 12.31 -17 42PIL_130 08/14/08 11:58 126 20.8 2.714.0 360 431 3.39 1004 12.58 72 44PIL_131 08/14/08 13:15 170 26.6 0.97.6 733 1217 2.76 1400 12.99 484 122PIL_131 08/14/08 13:16 172 21.1 2.714.1 215 966 0.26 2503 14.75 751 166PIL_132 08/14/08 13:52 187 24.7 4.828.3 -49 207 0.03 1602 14.97 256 67PIL_132 08/14/08 13:55 188 21.8 4.020.9 -346 300 0.04 348 15.00 646 53PIL_137 08/14/08 17:18 282 18.1 4.318.4 435 522 1.68 2268 13.76 86 69PIL_137 08/14/08 17:22 283 17.6 4.016.9 507 615 1.59 2542 13.80 109 34PIL_138 08/18/08 9:52 52 18.5 4.720.5 -7 83 0.11 805 14.94 90 68PIL_138 08/18/08 9:55 55 16.4 4.115.9 56 165 0.11 310 14.96 109 44PIL_146 08/18/08 13:49 190 14.3 3.311.4 -504 633 0.08 802 14.95 1137 112PIL_146 08/18/08 13:51 194 14.6 3.512.2 -114 476 0.07 1004 14.95 590 83PIL_151 08/18/08 16:25 280 14.2 3.311.2 30 35 0.20 152 14.91 5 40PIL_157 08/19/08 12:07 143 12.8 2.57.8 274 443 0.20 1641 14.84 169 71PIL_157 08/19/08 12:08 145 12.7 2.06.4 110 209 0.48 1305 14.66 100 34PIL_161 08/19/08 15:22 243 15.6 4.014.8 63 455 0.23 973 14.84 391 99PIL_161 08/19/08 15:24 244 14.2 3.311.4 97 622 0.27 542 14.82 526 95PIL_165 08/20/08 8:32 11 15.6 3.212.2 137 221 0.98 29 14.35 84 24PIL_165 08/20/08 8:37 18 15.8 2.610.1 200 343 1.61 149 13.88 143 40PIL_169 08/20/08 11:43 115 15.3 3.211.8 311 377 0.55 2737 14.55 65 53PIL_169 08/20/08 11:44 117 15.1 3.211.7 341 418 0.63 2915 14.49 77 46PIL_174 08/20/08 13:05 159 16.1 3.814.7 5 0 0.04 68 15.02 -5 58PIL_174 08/20/08 13:06 160 15.3 4.315.6 35 44 0.05 55 15.02 9 46PIL_184 08/21/08 10:29 66 16.4 2.911.7 23 42 0.19 3087 14.81 20 26PIL_184 08/21/08 10:30 67 15.5 2.910.9 169 202 1.45 449 13.99 33 35PIL_191 08/21/08 14:22 186 5.7 0.40.8 437 516 0.17 1210 14.87 79 28PIL_191 08/21/08 14:23 187 0.0 0.00.0 799 860 1.33 1828 14.01 62 37G-4 packetID mR_date mR_time mR_vdf bs_samSpeed bs_samAccel VSP bn_HC3000_ppmC3 bs_HC4000_ppmC3 bs_CO4000_pct bs_NX4000_ppm bs_CO24000_pct RSDEvpIndex0 RSDEvpIndex1PacketNumberMeasurementRSDDateMeasurementRSDTimeMeasurementRSDVDFSpeed(mph)Accel(mph/s)VSP(kW/Mg)RSD3000HC(ppmC3)RSD4000HC(ppmC3)RSD4000CO(%)RSD4000NO(ppm)RSD4000CO2(%)RSDEvapIndex0RSDEvapIndex1PIL_193 08/21/08 15:02 206 17.4 4.418.2 225 312 6.08 63 10.68 87 60PIL_193 08/21/08 15:03 211 18.3 3.716.4 558 1170 6.49 12 10.36 613 371PIL_194 08/21/08 15:27 228 20.3 1.68.7 2224 5476 2.50 63 13.10 3251 2616PIL_194 08/21/08 15:29 229 18.7 1.47.3 1515 10592 2.05 -61 13.27 9077 2268PIL_200 08/22/08 10:26 68 16.9 3.614.6 267 347 0.37 2345 14.70 80 66PIL_200 08/22/08 10:27 70 16.2 2.18.5 443 571 0.34 2145 14.72 128 32PIL_203 08/22/08 12:53 148 16.7 4.216.8 -149 12 0.02 69 15.04 161 54PIL_203 08/22/08 12:54 149 17.4 4.317.7 13 24 0.07 65 15.00 11 66PIL_213 08/23/08 9:16 67 16.5 4.818.7 473 559 0.40 1416 14.70 86 104PIL_213 08/23/08 9:17 69 15.6 4.516.5 588 765 1.46 1782 13.92 178 202PIL_217 08/23/08 11:39 140 15.9 4.215.9 34 65 0.51 72 14.68 31 61PIL_217 08/23/08 11:40 141 15.6 4.315.8 -7 27 0.08 77 14.99 34 81PIL_218 08/23/08 12:15 155 14.1 3.612.2 140 192 0.29 1055 14.81 52 31PIL_218 08/23/08 12:16 156 14.6 4.314.9 103 118 0.23 1165 14.85 14 56PIL_220 08/23/08 13:09 171 20.8 4.622.5 -59 857 0.09 1455 14.91 916 178PIL_220 08/23/08 13:10 172 20.9 4.723.1 117 401 0.42 -51 14.74 284 121PIL_221 08/25/08 10:02 64 18.5 4.820.8 -106 29 0.09 1430 14.94 135 44PIL_221 08/25/08 10:04 66 18.6 4.720.4 26 82 0.06 1221 14.96 55 42PIL_222 08/25/08 10:37 88 20.2 4.823.0 -7967 3758 0.38 3493 14.54 11725 1214PIL_222 08/25/08 10:38 90 18.7 4.620.2 1108 1474 1.47 1795 13.89 366 230PIL_223 08/25/08 11:24 126 18.2 4.017.6 53 291 0.11 43 14.96 237 40PIL_223 08/25/08 11:26 129 17.5 4.016.6 219 279 0.09 112 14.98 60 66PIL_225 08/25/08 13:45 201 0.0 0.00.0 961 1075 10.10 230 7.77 114 121PIL_225 08/25/08 13:48 204 0.0 0.00.0 961 963 7.35 502 9.74 2 25PIL_226 08/25/08 13:05 177 17.6 5.422.4 189 177 0.77 3106 14.38 -12 72PIL_226 08/25/08 13:07 181 18.8 6.126.6 -28 170 0.51 3112 14.57 198 33PIL_229 08/25/08 16:09 284 16.1 4.717.9 82 125 0.73 1568 14.47 43 32PIL_229 08/25/08 16:11 285 16.0 4.516.9 137 190 0.58 1411 14.58 53 89PIL_236 08/26/08 10:12 77 16.0 4.517.0 1139 1460 0.74 987 14.44 321 309PIL_236 08/26/08 10:14 80 15.0 4.315.2 3073 3288 3.59 489 12.37 215 401G-5 packetID mR_date mR_time mR_vdf bs_samSpeed bs_samAccel VSP bn_HC3000_ppmC3 bs_HC4000_ppmC3 bs_CO4000_pct bs_NX4000_ppm bs_CO24000_pct RSDEvpIndex0 RSDEvpIndex1PacketNumberMeasurementRSDDateMeasurementRSDTimeMeasurementRSDVDFSpeed(mph)Accel(mph/s)VSP(kW/Mg)RSD3000HC(ppmC3)RSD4000HC(ppmC3)RSD4000CO(%)RSD4000NO(ppm)RSD4000CO2(%)RSDEvapIndex0RSDEvapIndex1PIL_240 08/26/08 11:36 120 19.6 4.219.4 29 63 0.15 1148 14.90 34 32PIL_240 08/26/08 11:38 123 15.7 4.015.0 12 58 0.11 1110 14.93 46 45PIL_242 08/26/08 13:15 163 14.8 5.217.9 -1038 413 0.11 855 14.93 1452 471PIL_242 08/26/08 13:17 166 14.3 4.615.5 -1425 1000 0.11 601 14.92 2426 727PIL_245 08/26/08 14:43 218 19.9 5.525.7 49 113 3.30 -9 12.69 64 49PIL_245 08/26/08 14:45 219 18.6 5.524.1 69 85 4.05 31 12.15 16 43PIL_247 08/26/08 17:55 292 17.8 5.824.0 -849 1486 0.16 1886 14.83 2335 95PIL_247 08/26/08 17:57 293 17.3 5.723.0 -2535 2745 0.14 1866 14.80 5280 793PIL_248 08/27/08 9:57 44 14.8 3.211.3 532 549 0.88 2048 14.34 16 116PIL_248 08/27/08 9:59 49 15.9 2.59.9 409 386 0.14 1922 14.87 -24 81PIL_250 08/27/08 11:56 109 17.9 5.020.9 442 468 0.17 732 14.89 26 89PIL_250 08/27/08 11:59 111 17.8 5.021.0 311 511 0.35 637 14.76 200 150PIL_251 08/27/08 15:27 232 17.6 4.217.4 245 316 1.02 2427 14.23 71 41PIL_251 08/27/08 15:28 235 16.0 4.115.6 199 305 0.95 2459 14.28 105 38PIL_254 08/27/08 13:39 174 18.3 4.218.2 79 173 0.44 3261 14.61 94 45PIL_254 08/27/08 13:41 176 18.2 3.816.6 97 139 0.34 2975 14.70 41 60PIL_256 08/27/08 14:45 211 19.4 4.821.9 776 1015 0.02 623 14.98 239 291PIL_256 08/27/08 14:47 213 19.9 5.023.5 1168 1656 0.03 539 14.97 489 615PIL_257 08/28/08 9:04 19 16.5 4.316.8 79 48 0.14 550 14.93 -32 40PIL_257 08/28/08 9:06 23 12.1 3.08.8 103 44 0.04 2470 14.94 -59 45PIL_258 08/27/08 16:24 270 19.1 5.223.1 -13 9 0.03 12 15.03 22 50PIL_258 08/27/08 16:26 271 16.6 4.818.9 20 47 0.01 3 15.05 27 40PIL_266 08/28/08 10:48 63 20.1 3.918.9 481 567 0.56 2893 14.53 86 52PIL_266 08/28/08 10:50 64 21.4 2.915.2 345 440 0.40 2816 14.65 95 35PIL_270 08/28/08 12:37 131 14.1 4.113.7 -24 60 0.01 2032 14.97 84 59PIL_270 08/28/08 12:41 136 17.3 3.414.0 -1 72 0.03 599 15.01 73 52PIL_271 08/28/08 13:57 182 18.6 3.816.7 567 568 4.47 337 11.82 1 60PIL_271 08/28/08 13:59 185 18.2 4.920.8 390 580 3.52 539 12.49 190 85PIL_272 08/28/08 13:17 156 18.4 3.415.3 511 657 3.15 963 12.74 147 57PIL_272 08/28/08 13:19 160 13.5 2.27.4 833 937 5.99 383 10.72 104 70G-6 packetID mR_date mR_time mR_vdf bs_samSpeed bs_samAccel VSP bn_HC3000_ppmC3 bs_HC4000_ppmC3 bs_CO4000_pct bs_NX4000_ppm bs_CO24000_pct RSDEvpIndex0 RSDEvpIndex1PacketNumberMeasurementRSDDateMeasurementRSDTimeMeasurementRSDVDFSpeed(mph)Accel(mph/s)VSP(kW/Mg)RSD3000HC(ppmC3)RSD4000HC(ppmC3)RSD4000CO(%)RSD4000NO(ppm)RSD4000CO2(%)RSDEvapIndex0RSDEvapIndex1PIL_274 08/28/08 14:43 207 18.2 4.720.4 540 549 0.16 1906 14.85 9 42PIL_274 08/28/08 14:45 210 18.7 4.419.5 421 422 0.17 1525 14.86 1 49PIL_281 08/28/08 17:33 290 19.1 3.415.7 83 137 0.27 814 14.83 54 45PIL_281 08/28/08 17:35 291 22.5 3.418.6 292 317 2.08 1220 13.51 25 30PIL_283 08/29/08 10:23 87 16.3 4.617.9 285 317 0.25 1240 14.82 33 82PIL_283 08/29/08 10:25 88 21.6 4.523.0 286 285 0.37 1276 14.73 -1 58PIL_284 08/29/08 11:06 114 21.6 3.618.8 619 703 0.49 1557 14.63 84 69PIL_284 08/29/08 11:08 116 18.3 3.515.6 561 727 0.44 1082 14.68 166 63PIL_286 08/29/08 13:35 211 21.7 2.312.9 133 916 0.17 1867 14.84 783 307PIL_286 08/29/08 13:37 214 18.6 2.712.3 267 340 0.09 2610 14.89 73 177PIL_287 08/29/08 14:25 252 19.7 3.516.7 454 403 0.01 815 15.00 -51 204PIL_287 08/29/08 14:27 254 20.1 2.914.4 417 1153 0.03 231 14.99 736 308PIL_290 08/29/08 15:07 302 17.0 5.320.9 188 263 3.79 52 12.33 76 89PIL_290 08/29/08 15:10 306 17.7 5.121.1 354 492 0.18 49 14.91 138 221PIL_294 08/29/08 17:11 362 14.6 5.3 18.1 -48 -11 0.02 10 15.04 37 51PIL_294 08/29/08 17:12 363 16.1 5.319.9 60 64 0.07 8 15.00 5 88PIL_298 08/30/08 9:50 59 18.6 4.9 21.3 -3 8 0.02 -32 15.04 11 68PIL_298 08/30/08 9:52 60 17.7 4.217.8 -13 18 0.02 0 15.04 32 92PIL_299 08/30/08 10:28 78 14.5 2.17.8 263 313 0.05 2467 14.92 49 100PIL_299 08/30/08 10:30 80 15.8 2.18.4 239 299 0.04 2545 14.92 59 67PIL_300 08/30/08 11:05 98 15.6 3.412.8 65 339 0.05 -32 15.01 274 125PIL_300 08/30/08 11:07 99 15.5 3.011.5 15 104 0.03 32 15.03 89 62PIL_304 08/30/08 12:31 143 17.4 3.615.2 737 744 8.96 367 8.59 7 130PIL_304 08/30/08 12:32 144 18.1 3.916.7 799 874 12.00 275 6.42 75 93

### Appendix H PSHED DataH-1 packetID PS_date PS_SealTime PS_DoorSealHC_ppmC PS_DoorSealP_mb PS_DoorSealTemp_C PS_FinalTime PS_FinalHC_ppmC PS_FinalP_mb PS_FinalTemp_C PS_Min0_g PS_Min1_g PS_Min2_g PS_Min3_g PS_Min4_g PS_Min5_g PS_Min6_g PS_Min7_g PS_Min8_g PS_Min9_g PS_Min10_g PS_Min11_g PS_Min12_g PS_Min13_g PS_Min14_g PS_Min15_gPacketNumberPSHEDDatePSHEDSealTimePSHEDSealHC(ppmC)PSHEDSealPbaro(mb)PSHEDSealTemperature(C)PSHEDFinalTimePSHEDFinalHC(ppmC)PSHEDFinalPbaro(mb)PSHEDFinalTemperature(C)Cumulative PSHED HC Mass atMinutes Since Door Seal (g)0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15PIL_010 07/30/08 12:05 2 836 34 12:22 8 836 40 0.00 0.02 0.02 0.04 0.04 0.05 0.07 0.07 0.08 0.09 0.09 0.11 0.11 0.11 0.13 0.13PIL_011 07/30/08 16:13 25 834 38 16:28 850 834 42 0.00 0.27 0.98 1.91 2.16 4.73 4.89 6.20 7.32 7.69 8.67 10.19 10.98 12.20 12.81 14.02PIL_016 07/30/08 17:43 24 834 36 18:00 28 833 42 0.00 0.42 0.49 0.49 0.50 0.51 0.52 0.52 0.52 0.52 0.52 0.53 0.54 0.54 0.54 0.54PIL_019 07/31/08 13:44 36 837 35 13:59 729 837 40 0.00 0.46 1.11 1.83 2.54 3.24 3.96 4.81 5.70 6.91 7.96 9.38 10.57 12.44 13.8614.81PIL_022 07/31/08 17:14 3 835 36 17:30 . . . 0.00 0.03 0.07 0.14 0.24 0.36 0.46 0.57 0.69 0.81 0.93 1.03 1.11 1.19 1.26 1.30PIL_024 08/01/08 11:38 170 837 36 11:53 529 837 40 0.00 0.32 2.61 4.22 6.09 6.62 7.70 8.60 8.99 9.49 9.90 10.36 10.53 10.78 10.93 11.19PIL_029 08/02/08 8:37 2 836 31 8:52 6 836 34 0.00 0.00 0.00 0.00 0.00 0.02 0.02 0.02 0.04 0.04 0.05 0.07 0.07 0.07 0.09 0.09PIL_029 08/04/08 8:11 2 837 26 8:28 6 . . 0.00 0.00 0.01 0.02 0.02 0.02 0.04 0.05 0.05 0.07 0.07 0.07 0.07 0.07 0.09 0.09PIL_035 08/01/08 17:37 . 834 40 17:53 . 834 41 0.00 1.21 4.43 6.07 6.70 7.71 9.01 9.99 10.40 11.63 12.07 12.44 13.15 13.98 14.92 15.47PIL_046 08/04/08 16:02 41 838 34 . . . . 0.00 0.41 1.01 1.51 2.01 2.69 3.55 4.49 6.10 7.98 8.67 9.40 10.11 10.71 11.35 12.00PIL_050 08/04/08 16:42 3 838 33 16:59 46 838 37 0.00 0.36 0.44 0.50 0.55 0.61 0.69 0.74 0.78 0.79 0.81 0.83 0.84 0.87 0.89 0.90PIL_060 08/05/08 13:45 2 842 31 14:01 7 842 37 0.00 0.00 0.01 0.02 0.02 0.04 0.04 0.04 0.06 0.07 0.07 0.08 0.09 0.09 0.11 0.11PIL_061 08/05/08 14:07 3 840 33 14:23 7 841 34 0.00 0.02 0.02 0.02 0.03 0.04 0.04 0.04 0.04 0.04 0.06 0.07 0.07 0.07 0.07 0.08PIL_062 08/05/08 15:04 2 841 30 15:19 . 841 . 0.00 0.00 0.00 0.02 0.03 0.02 0.02 0.04 0.04 0.04 0.04 0.06 0.07 0.07 0.07 0.08PIL_063 08/05/08 15:44 2 841 31 16:00 . . . 0.00 0.02 0.03 0.05 0.05 0.08 0.08 0.10 0.10 0.12 0.12 0.14 0.14 0.16 0.17 0.19PIL_065 08/05/08 16:56 7 842 31 17:12 10 842 35 0.00 0.11 0.11 0.12 0.13 0.13 0.13 0.13 0.15 0.16 0.16 0.16 0.16 0.16 0.18 0.18PIL_070 08/06/08 13:52 2 841 31 14:09 4 841 40 0.00 0.00 0.01 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.03 0.04 0.04 0.04PIL_072 08/07/08 12:45 2 843 27 13:00 10 843 33 0.00 0.02 0.03 0.05 0.07 0.06 0.09 0.10 0.11 0.12 0.14 0.15 0.16 0.17 0.18 0.19PIL_078 08/08/08 10:42 1 839 26 10:57 15.4 838 31 0.00 0.01 0.04 0.06 0.10 0.12 0.15 0.17 0.19 0.21 0.24 0.25 0.27 0.28 0.29 0.31PIL_079 08/08/08 11:40 2 838 27 11:55 2.6 838 34 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.02PIL_084 08/08/08 14:35 3 836 29 14:50 9.3 836 33 0.00 0.02 0.02 0.04 0.05 0.05 0.06 0.07 0.08 0.10 0.10 0.11 0.13 0.13 0.15 0.15PIL_089 08/09/08 11:42 3 836 29 11:57 20 836 36 0.00 0.07 0.09 0.11 0.14 0.17 0.19 0.22 0.24 0.27 0.29 0.32 0.33 0.35 0.37 0.39PIL_098 08/11/08 14:36 1 836 32 14:51 2 836 40 0.00 0.01 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.01 0.01 0.02 0.01 0.03PIL_108 08/12/08 17:28 14 839 32 17:45 . . . 0.00 0.13 0.09 0.25 0.27 0.34 0.44 0.52 0.57 0.62 0.66 0.67 0.69 0.71 0.71 0.71PIL_110 08/12/08 18:11 5 839 32 18:28 171 839 37 0.00 0.12 0.44 0.57 0.80 0.98 1.25 1.48 1.63 1.75 1.88 2.07 2.31 2.56 2.87 3.12PIL_116 08/13/08 13:34 41 841 32 13:57 314 841 37 0.00 1.03 1.73 2.34 3.18 3.71 4.25 4.74 5.14 5.53 5.95 6.11 6.38 6.48 6.65 6.75PIL_117 08/13/08 11:59 1 842 31 12:14 13 841 38 0.00 0.02 0.03 0.04 0.05 0.07 0.08 0.10 0.11 0.13 0.15 0.18 0.20 0.21 0.23 0.26PIL_118 08/13/08 12:38 13 841 32 12:56 465 841 38 0.00 0.28 1.08 2.02 2.67 3.48 4.17 4.87 5.57 6.28 6.94 7.47 7.94 8.52 8.88 9.36PIL_123 08/13/08 15:38 2 841 32 15:55 13 841 37 0.00 0.02 0.02 0.04 0.04 0.07 0.07 0.09 0.10 0.12 0.13 0.15 0.16 0.18 0.20 0.21PIL_124 08/13/08 16:34 2 840 33 16:51 10 840 40 0.00 0.02 0.04 0.04 0.06 0.07 0.07 0.09 0.09 0.11 0.11 0.13 0.13 0.13 0.15 0.15PIL_128 08/14/08 10:42 29 845 25 10:59 160.1 845 31 0.00 0.39 0.69 1.22 1.56 1.83 2.11 2.38 2.55 2.77 2.98 3.09 3.17 3.31 3.403.46PIL_130 08/14/08 12:01 3 844 27 12:18 9 844 32 0.00 0.03 0.05 0.07 0.09 0.09 0.09 0.11 0.11 0.11 0.11 0.12 0.13 0.13 0.14 0.16PIL_131 08/14/08 13:18 32 844 27 13:36 89 844 . 0.00 0.17 0.71 1.07 1.38 1.67 1.87 1.96 1.97 1.96 1.96 1.96 1.95 1.95 1.94 1.94PIL_132 08/14/08 13:57 4 844 27 14:14 87.1 844 31 0.00 0.09 0.16 0.27 0.36 0.45 0.55 0.70 0.80 0.89 1.01 1.10 1.22 1.33 1.43 1.52PIL_137 08/14/08 17:22 3 843 28 17:39 15 843 33 0.00 0.04 0.05 0.07 0.09 0.11 0.12 0.14 0.16 0.18 0.19 0.21 0.23 0.24 0.26 0.29PIL_138 08/18/08 9:57 0 845 22 10:12 1 845 28 0.00 0.00 0.00 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.04 0.05 0.05PIL_146 08/18/08 13:53 5 845 26 14:08 72 . . 0.00 0.15 0.44 0.58 0.71 0.81 0.94 1.04 1.13 1.22 1.29 1.37 1.43 1.49 1.55 1.59PIL_151 08/18/08 16:29 2 844 27 16:44 17 844 31 0.00 0.02 0.05 0.05 0.07 0.08 0.11 0.14 0.16 0.18 0.21 0.24 0.27 0.30 0.34 0.35PIL_157 08/19/08 12:10 2 842 28 12:25 9 842 34 0.00 0.02 0.02 0.04 0.06 0.07 0.09 0.10 0.11 0.13 0.13 0.15 0.16 0.16 0.17 0.18PIL_161 08/19/08 15:27 13 841 30 15:42 171.2 841 35 0.00 0.86 1.46 1.97 2.48 2.70 2.92 3.05 3.17 3.21 3.24 3.28 3.28 3.30 3.323.37PIL_165 08/20/08 8:39 2 840 22 8:56 15 840 26 0.00 0.02 0.04 0.05 0.07 0.09 0.10 0.13 0.14 0.16 0.17 0.19 0.21 0.23 0.24 0.26PIL_169 08/20/08 11:47 5 839 29 12:02 153.2 839 33 0.00 0.07 0.17 0.40 0.58 0.79 1.00 1.25 1.47 1.69 1.94 2.18 2.36 2.62 2.80 3.00PIL_174 08/20/08 13:11 1 838 31 13:26 3 838 35 0.00 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.05PIL_177 08/20/08 15:34 3 839 29 15:51 5 839 30 0.00 0.01 0.02 0.02 0.02 0.02 0.03 0.05 0.05 0.05 0.06 0.05 0.06 0.06 0.07 0.07PIL_184 08/21/08 10:33 2 839 29 10:54 3 838 32 0.00 0.00 0.00 0.00 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.03 0.04PIL_191 08/21/08 14:28 2 836 34 14:43 6 836 37 0.00 0.00 0.02 0.02 0.02 0.02 0.04 0.04 0.04 0.05 0.07 0.07 0.07 0.07 0.08 0.09PIL_193 08/21/08 15:05 200 836 35 15:20 515.4 836 41 0.00 2.34 5.38 7.46 9.13 9.72 10.15 10.60 10.94 11.15 11.19 11.30 11.32 11.32 11.26 11.22H-2 packetID PS_date PS_SealTime PS_DoorSealHC_ppmC PS_DoorSealP_mb PS_DoorSealTemp_C PS_FinalTime PS_FinalHC_ppmC PS_FinalP_mb PS_FinalTemp_C PS_Min0_g PS_Min1_g PS_Min2_g PS_Min3_g PS_Min4_g PS_Min5_g PS_Min6_g PS_Min7_g PS_Min8_g PS_Min9_g PS_Min10_g PS_Min11_g PS_Min12_g PS_Min13_g PS_Min14_g PS_Min15_gPacketNumberPSHEDDatePSHEDSealTimePSHEDSealHC(ppmC)PSHEDSealPbaro(mb)PSHEDSealTemperature(C)PSHEDFinalTimePSHEDFinalHC(ppmC)PSHEDFinalPbaro(mb)PSHEDFinalTemperature(C)Cumulative PSHED HC Mass atMinutes Since Door Seal (g)0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15PIL_194 08/21/08 15:37 33 835 36 15:52 1151.2 835 42 0.00 8.03 14.41 20.62 24.32 24.31 24.26 24.23 24.22 24.15 24.15 24.15 24.15 24.13 24.07 24.07PIL_200 08/22/08 10:29 4 842 29 10:45 12 842 34 0.00 0.02 0.04 0.05 0.07 0.09 0.09 0.11 0.11 0.11 0.13 0.13 0.15 0.15 0.15 0.17PIL_203 08/22/08 12:52 2 842 29 13:07 2 844 35 0.00 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02PIL_213 08/23/08 9:19 10 849 23 9:35 43.1 849 28 0.00 0.26 0.27 0.35 0.41 0.47 0.53 0.58 0.63 0.68 0.70 0.75 0.79 0.83 0.86 0.89PIL_217 08/23/08 11:41 4 847 26 11:56 7 847 32 0.00 0.02 0.02 0.02 0.02 0.02 0.03 0.04 0.04 0.04 0.04 0.05 0.07 0.07 0.07 0.07PIL_218 08/23/08 12:19 4 847 27 12:33 20 847 32 0.00 0.03 0.05 0.07 0.09 0.12 0.14 0.17 0.19 0.21 0.24 0.27 0.29 0.31 0.33 0.35PIL_220 08/23/08 13:11 17 846 28 13:28 54.1 846 32 0.00 0.11 0.20 0.31 0.65 0.75 0.80 0.84 0.88 0.91 0.96 0.98 1.02 1.05 1.08 1.09PIL_221 08/25/08 10:08 . . . 10:23 8 843 33 0.00 0.02 0.02 0.02 0.04 0.05 0.05 0.07 0.07 0.08 0.09 0.09 0.11 0.11 0.13 0.13PIL_222 08/25/08 10:43 4 843 29 10:58 127 843 33 0.00 . . . . . . . . . . . . . . 2.80PIL_223 08/25/08 11:29 10 843 28 11:44 94 843 34 0.00 0.22 0.28 0.46 0.65 0.81 0.97 1.10 1.23 1.34 1.51 1.61 1.74 1.85 1.93 2.02PIL_225 08/25/08 13:52 0 841 33 14:11 19 841 38 0.00 0.03 0.05 0.07 0.10 0.12 0.14 0.16 0.19 0.22 0.24 0.26 0.28 0.30 0.32 0.34PIL_226 08/25/08 13:11 2 842 33 13:26 10 841 39 0.00 . . . . . . . . . . . . . . 0.17PIL_229 08/25/08 16:15 30 840 32 16:30 158 840 36 0.00 0.02 0.13 1.01 1.66 2.43 2.95 3.26 3.42 3.46 3.46 3.45 3.44 3.45 3.44 3.44PIL_236 08/26/08 10:18 4 838 30 10:33 48 838 35 0.00 0.07 0.10 0.13 0.17 0.25 0.34 0.43 0.60 0.70 0.80 0.87 0.93 0.99 1.02 1.05PIL_240 08/26/08 11:41 1 837 32 11:56 6 837 37 0.00 0.02 0.02 0.03 0.04 0.04 0.05 0.07 0.07 0.07 0.09 0.09 0.09 0.09 0.10 0.11PIL_242 08/26/08 13:21 50 837 33 13:36 425 837 38 0.00 0.68 1.81 2.72 3.53 4.25 4.94 5.56 6.19 6.77 7.17 7.65 7.94 8.37 8.67 9.02PIL_245 08/26/08 14:49 3 837 35 15:04 8 836 40 0.00 0.04 0.05 0.07 0.07 0.08 0.09 0.09 0.10 0.11 0.11 0.11 0.13 0.13 0.13 0.13PIL_247 08/26/08 18:02 30 836 33 18:17 109 837 38 0.00 0.24 0.77 0.96 1.11 1.32 1.48 1.60 1.68 1.78 1.86 1.94 2.01 2.07 2.15 2.20PIL_248 08/27/08 10:03 5 844 22 10:18 53 844 28 0.00 0.12 0.24 0.35 0.44 0.53 0.60 0.67 0.73 0.79 0.86 0.91 0.97 1.02 1.08 1.12PIL_250 08/27/08 12:03 6 842 25 12:18 34 841 31 0.00 0.09 0.22 0.31 0.38 0.44 0.48 0.53 0.56 0.59 0.61 0.64 0.65 0.67 0.69 0.71PIL_251 08/27/08 15:37 0 837 31 15:52 1 837 35 0.00 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.03 0.03 0.03PIL_254 08/27/08 13:45 5 840 28 14:00 16 839 34 0.00 0.07 0.13 0.17 0.20 0.23 0.26 0.28 0.29 0.31 0.31 0.31 0.31 0.31 0.33 0.33PIL_256 08/27/08 14:51 10 838 30 15:06 100 838 36 0.00 0.22 0.23 0.61 1.07 1.50 1.75 1.94 2.07 2.15 2.18 2.20 2.19 2.20 2.18 2.18PIL_257 08/28/08 9:11 1 847 22 9:26 4 847 27 0.00 0.02 0.02 0.02 0.03 0.05 0.05 0.05 0.05 0.06 0.07 0.07 0.07 0.07 0.07 0.08PIL_258 08/27/08 16:30 2 837 33 16:45 3 837 41 0.00 0.01 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.03PIL_266 08/28/08 10:53 2 847 23 11:08 8 847 28 0.00 0.02 0.02 0.04 0.04 0.04 0.06 0.07 0.07 0.09 0.09 0.11 0.11 0.11 0.13 0.13PIL_270 08/28/08 12:44 2 846 26 12:59 48 846 29 0.00 0.04 0.12 0.22 0.34 0.45 0.53 0.60 0.68 0.75 0.80 0.87 0.91 0.97 1.01 1.06PIL_271 08/28/08 14:03 4 845 27 14:18 62 845 33 0.00 0.03 0.06 0.09 0.14 0.26 0.40 0.56 0.69 0.84 0.94 1.02 1.09 1.16 1.23 1.29PIL_272 08/28/08 13:24 3 846 27 13:39 57 846 31 0.00 0.01 0.23 0.39 0.52 0.64 0.75 0.88 0.98 1.02 1.10 1.18 1.23 1.27 1.32 1.37PIL_274 08/28/08 14:48 2 845 27 15:03 3 845 33 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.02 0.02 0.02PIL_281 08/28/08 17:38 0 844 27 17:53 12 843 32 0.00 0.02 0.02 0.03 0.05 0.06 0.08 0.09 0.11 0.13 0.15 0.17 0.19 0.22 0.24 0.26PIL_283 08/29/08 10:29 2 846 25 10:44 4 846 30 0.00 0.02 0.02 0.02 0.02 0.03 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.07 0.07 0.07PIL_284 08/29/08 11:11 3 846 26 11:26 5.5 846 30 0.00 0.01 0.02 0.02 0.02 0.02 0.03 0.05 0.05 0.05 0.05 0.04 0.04 0.04 0.06 0.07PIL_286 08/29/08 13:41 4 844 29 13:56 620 844 36 0.00 0.05 0.19 0.66 1.35 2.38 3.76 4.99 6.48 7.79 8.89 10.11 11.02 11.51 12.6813.18PIL_287 08/29/08 14:30 13 844 30 14:45 136 844 38 0.00 0.25 0.82 1.18 1.46 1.69 1.95 2.18 2.34 2.51 2.66 2.78 2.86 2.90 2.94 2.99PIL_290 08/29/08 15:13 20 843 31 15:28 58 843 35 0.00 0.34 0.58 0.73 0.94 1.06 1.14 1.18 1.19 1.20 1.20 1.21 1.22 1.22 1.22 1.23PIL_294 08/29/08 17:15 4 842 31 17:30 6 842 35 0.00 0.02 0.04 0.04 0.04 0.03 0.04 0.04 0.04 0.04 0.04 0.04 0.06 0.06 0.06 0.06PIL_298 08/30/08 9:56 1 842 26 10:11 3 842 30 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.04 0.05 0.05PIL_299 08/30/08 10:33 1 842 27 10:48 19 842 31 0.00 0.02 0.04 0.05 0.06 0.07 0.09 0.09 0.12 0.13 0.16 0.19 0.21 0.23 0.27 0.32PIL_300 08/30/08 11:11 3 841 28 11:26 13 841 33 0.00 0.04 0.06 0.09 0.13 0.15 0.16 0.18 0.18 0.20 0.20 0.20 0.23 0.25 0.26 0.27PIL_304 08/30/08 12:36 0 840 30 12:51 8 840 37 0.00 0.01 0.02 0.05 0.05 0.07 0.07 0.09 0.09 0.11 0.11 0.12 0.13 0.14 0.15 0.17

### Appendix I Modified California Method Data

Legend:

0 No visual evidence of fuel leaks

m Minor visual signs of fuel (staining, damp spots), paper towel wicking < 1 inch

S Significant visual leaks with single drops of fuel from vehi cle to the ground, paper towel wicking > 1 inch

G Gross visual leaks, regular flow of drops to the ground, or a large pool of fuel, paper towel wicking > 1 inch

NP Not Performed (usually because component wa s not present, could not be found, or was hidden)

Y Positive HC sniffer response

N No HC sniffer response

# Data entry was missing from data packetI-1 packetID MCM_Date MCM_Time MCM_UnderbodyV MCM_FuelPumpV MCM_PumpToCarbV MCM_FuelFilterV MCM_FuelRailV MCM_FuelInjectorsV MCM_UnderVehicleV MCM_FillPipeToTankV MCM_TankV MCM_NonOEMV MCM_UnderbodyS MCM_FuelPumpS MCM_PumpToCarbS MCM_FuelFilterS wMCM_FuelRailS MCM_FuelInjectorsS MCM_UnderVehicleS MCM_FillPipeToTankS MCM_TankS MCM_NonOEMS pi_VideoFileNum pi_CommentsPacketNumberMCMDateMCMTimeVisual SnifferVideoFileNumber Comments

Underbod y Fuel Pump Pump to Carb Fuel Filter Fuel Rail Fuel Injectors Under Vehicle Fill Pipe to Tank Tank Non-OEM Underbod y Fuel Pump Pump to Carb Fuel Filter Fuel Rail Fuel Injectors Under Vehicle Fill Pipe to Tank Tank Non-OEMPIL_010 07/30/08 12:22 0 0 0 0 0 0 0 0 0 NP # # # # # # # # # NP None No problems found.PIL_011 07/30/08 16:28 0 0 0 0 0 0 0 0 0 0 # # Y # # # # Y # # NoneThe end of the fuel filler neck is damaged. The flangewhere the gas cap should seal is smashed. After-marketlocking gas cap does not seal well. Gas cap almost falls offthe vehicle. Non-OEM open air filter. Non-OEM fuel fillpipe is homemade of PVCelbows and rubber to metalconnections. Second fueltank is disconnected andcrossover valve is bypassed. Vapor and liquid leaks.PIL_016 07/30/08 18:00 0 NP NP 0 0 0 0 0 0 NP # # # # # # # # # # NoneBad vapor leak at cap, failedfuel cap IM test. Canistersaturated.PIL_019 07/31/08 13:59 0 0 0 NP NP NP 0 0 0 0 # # # # # # # # # # NoneNew fuel tank, no liquid leaks, lots of carb vapors, OEMcap is vented, a pre-evap-control vehicle.PIL_022 07/31/08 17:30 0 0 NP NP 0 0 0 0 0 NP # # # # ## # # # # None Clean. No sniffer beeps or leaks.PIL_024 08/01/08 11:53 0 NP NP NP 0 0 0 0 0 0 # # # # # ## Y # # 96 Sniffer: trace at fill pipe to tank joint.PIL_029 08/02/08 8:52 0 NP NP 0 0 0 0 m 0 0 # # # ## # # # # # None No problems found, m=stain at tank.PIL_035 08/01/08 17:53 0 NP NP NP 0 0 # ## # NP NP NP NPY Y NP Y Y # NoneNo visual signs of fuel. Around fuel rail. Fuel fill pipe atgas cap, bottom of inlet to tank, top of tank. Vapor leak topof tank.PIL_046 08/04/08 16:19 # # # # # # # # # # # # # # # # # # # # None Pass I/M and cap.PIL_050 08/04/08 16:59 0 NP NP 0 00 0 0 0 NP N N N N N N N Y # #103, 104,105Vapor return at cap trace, traceat vapor return to inside offuel inlet return. Also vdf 326 and 327 on 8/4/08.PIL_060 08/05/08 14:01 0 NP NP 0 0 NP 0 M M 0 # # # # # # # Y NN 106 Trace fill pipe at tank. Slight by cap, Trace by cap.PIL_061 08/05/08 14:23 0 NP NP 0 0 NP 0 0 0 0 N N NN N N N N N N 107 Pass I/M and cap, no problems found.PIL_062 08/05/08 15:19 0 NP NP 0 0 0 0 00 0 N NP NP N N N N N N NP 108PIL_063 08/05/08 16:00 0 NP NP 0 0 NP 0 00 0 N NP NP N N NP N N N NP 109PIL_065 08/05/08 17:12 0 NP NP 0 0 0 0 0 0 NPN NP NP N N N N N N NP None Bad miss,fail I/M. Could not video. Camera problems.PIL_070 08/06/08 14:09 0 NP NP 0 0 0 00 0 NP N NP NP N N N N N N NP 110Very clean - recently detailed. Large (40 gal?) tank. Noproblems found.PIL_072 08/07/08 13:00 0 NP NP NP 0 0 0 0 0 NPN NP NP NP N N N N NNP 115 File corrupted.PIL_078 08/08/08 10:57 0 NP 0 NP 0 0 00 0 NP Y NP N NP N N N N N # 113Passed IM, previous IM - cap failed, new cap - no problemsfound.PIL_079 08/08/08 11:55 0 NP NP 0 0 0 0 0 0 NPN NP NP N N N N N N # 114 No problems found.PIL_084 08/08/08 14:50 0 NP NP 0 0 00 0 0 NP N NP NP N N N N N N NP 119 Pass IM cap, no defects found.PIL_089 08/09/08 11:57 0 NP NP 0 0 0 00 0 NP N NP NP N N N N Y N # 120No gas cap, strong sniff signal at top of tank, leaking oil,overheating, holes punched in catalyst.PIL_098 08/11/08 14:51 0 0 NP # 0 0 0 0 0NP N N NP N N N N N N NP NonePIL_108 08/12/08 17:45 0 0 0 0 0 0 0 0 0 NP N N NP # N NP NN N NP None Rejected from IM240 for drive trace problems.PIL_110 08/12/08 18:28 S 0 NP 0 S S S # m # Y N NP N Y Y Y # Y # None This is definite leaker, smell gas.PIL_116 08/13/08 13:57 0 NP NP 0 0 0 0 0 0 0 # # # # # ## Y NP NP None Possible leak on top of fuel tank.PIL_117 08/13/08 12:14 0 0 NP 0 0 0 0 0 0 NP NN NP N N N N N N NPN/A Dual fuel tanks.PIL_118 08/13/08 12:56 0 NP NP 0 0 0 0 00 NP N NP NP N N N N NN NP N/A Strong fuel smell, no visual leaks.PIL_123 08/13/08 15:55 0 NP NP NP 0 0 0 0 0NP N NP NP NP N NN N N NP NonePIL_124 08/13/08 16:51 0 0 0 0 0 0 0 0 0 0 N N N N N N N N N N NonePIL_128 08/14/08 10:59 0 NP NP 0 0 0 0 0 0NP N NP NP N N N N N N NP NonePIL_130 08/14/08 12:18 0 NP NP 0 0 0 0 0 0 NP N NPNP N N N N N N # None No dyno, unsafe on dyno.I-2 packetID MCM_Date MCM_Time MCM_UnderbodyV MCM_FuelPumpV MCM_PumpToCarbV MCM_FuelFilterV MCM_FuelRailV MCM_FuelInjectorsV MCM_UnderVehicleV MCM_FillPipeToTankV MCM_TankV MCM_NonOEMV MCM_UnderbodyS MCM_FuelPumpS MCM_PumpToCarbS MCM_FuelFilterS wMCM_FuelRailS MCM_FuelInjectorsS MCM_UnderVehicleS MCM_FillPipeToTankS MCM_TankS MCM_NonOEMS pi_VideoFileNum pi_CommentsPacketNumberMCMDateMCMTimeVisual SnifferVideoFileNumber Comments

Underbod y Fuel Pump Pump to Carb Fuel Filter Fuel Rail Fuel Injectors Under Vehicle Fill Pipe to Tank Tank Non-OEM Underbod y Fuel Pump Pump to Carb Fuel Filter Fuel Rail Fuel Injectors Under Vehicle Fill Pipe to Tank Tank Non-OEMPIL_131 08/14/08 13:36 0 NP NP 0 0 0 00 0 NP N NP NP N Y Y N N N NP None #2 and #4 injectors are leaking.PIL_132 08/14/08 14:14 0 NP NP 0 0 0 0 0 0NP N NP NP N N N N N N NP NonePIL_137 08/14/08 17:39 0 NP NP 0 0 0 0 00 NP N NP NP N N N N N N NP NoneOwner says miles are actual,although vehicle was justpurchased used.PIL_138 08/18/08 10:12 0 0 NP NP 0 0 0 0 0NP N N NP NP N N N N N NP NonePIL_146 08/18/08 14:08 0 NP NP NP 0 0 0 mm NP N NP NP NPN N N Y Y NP NoneTank very rusty. Leak on top of fuel tank at fuel pump orfill pipe. Cannot see on top of tank.PIL_151 08/18/08 16:44 0 NP 0 NP NP NP 0 0 0NP N NP N NP NP NPN N N NP NonePIL_157 08/19/08 12:25 0 NP NP 0 0 0 0 0 0 NPN NP NP N N N N N N N None Leak atPCV/Throttle body vacuum line tee fitting.PIL_161 08/19/08 15:42 0 NP NP 0 0 0 0 0 0 NPN NP NP N N Y N N N NP None Leakingat injector/intake boss on cylinder number 4.PIL_165 08/20/08 8:56 0 NP NP 0 0 0 0 0 0 NPN NP NP N Y N N N N NP N/AFuel leak along intake/fuel rail. Could not pinpoint it.PIL_169 08/20/08 12:02 0 NP NP 0 0 0 0 0 0 NP N NPNP N N N N N N NP None Could not find leak.PIL_174 08/20/08 13:26 0 NP NP 0 0 00 0 0 NP N NP NP N N N N N NNP None No leaks, 3ppm shed.PIL_177 08/20/08 15:51 0 NP NP 0 0 0 0 0 0 NPN NP NP N N N N N N NP None Rained during drive. No 2nd or 3rd RSD. Clean shed.PIL_184 08/21/08 10:54 0 NP NP 0 0 0 0 0 0 NPN NP NP N N N N N N NP None Appears tobe Canadian import, gray market, clean, noHC.PIL_191 08/21/08 14:43 0 NP NP NP 0 0 0NP 0 NP N NP NP NP NN N N N NP None Smokes from tailpipe while running.PIL_193 08/21/08 15:20 0 NP NP 0 0 0 0 0 0 NP N NPNP N N N N N N NP None Could not find leak.PIL_194 08/21/08 15:52 0 NP NP 0 0 0 0 00 NP N NP NP N N N N N N # NoneUnable to find the leak(s). Very high HC emissions, 1200ppm, no visible leaks detected.PIL_200 08/22/08 10:45 0 NP NP 0 0 0 0 0 0NP N NP NP N N N N N N NP NonePIL_203 08/22/08 13:07 0 NP NP 0 0 0 0 0 0 NPN NP NP N N N N N N NP NoneNo emissions labels, very clean. Shed >= 3ppm @ 15 min.PIL_213 08/23/08 9:35 0 NP NP 0 0 0 0 0 0 NPN NP NP N N N N Y N NP None Filler neckleaks near top and at tank (smoke test).PIL_217 08/23/08 11:56 0 NP NP 0 0 0 0 0 0 NPN NP NP N N N N N N NP None Clean.PIL_218 08/23/08 12:33 0 NP 0 NP 0 0 0 NP NPNP N NP N NP N NN NP NP NP NoneQuestionnaire Driver comment: when tank is topped offthere is a leak on the top of filler neck.PIL_220 08/23/08 13:28 0 NP NP 0 0 0 0 0 0 NP NNP NP N N N N N N NP None No leak found.PIL_221 08/25/08 10:23 0 NP NP 0 0 0 0 00 NP N NP NP N N N N N N NP NoneComputer bombed when started PSHED. Session file wasstill open when rebooted.PIL_222 08/25/08 10:58 0 NP 0 0 0 0 0 0 0NP NP NP N N N NN N NP NP NoneCould not find leak. Used smoketest too. Results of smoketest: N; N; NPPIL_223 08/25/08 11:44 0 NP NP 0 0 0 0 m 0 NPN NP NP N N N N Y N NP None Leak atfiller neck/tank joint area on top of tank.PIL_225 08/25/08 14:11 0 0 NP 0 0 0 0 0 0 0 N N NP N N N N N N N None Aftermarket fuel injection.Emissions label lists as a 1994.PIL_226 08/25/08 13:26 NP NP 0 0 0 00 0 0 NP NP NP NPNP NP NP NP NP NPNP None No leak.PIL_229 08/25/08 16:30 0 NP 0 NP m 0 0 00 NP N NP N NP N N N N N NP NoneCould not find leak. Significant corrosion on underbodyfuel lines.PIL_236 08/26/08 10:33 0 NP 0 0 0 0 0 0 0NP N NP N Y N N NP N N NP NoneNo I/M due to coolant warning light. New gas cap. Leak atfuel filter (per sniffer).PIL_240 08/26/08 11:56 0 0 0 NP 0 0 0 0 0 NPN N N NP N N NP N N NP NonePIL_242 08/26/08 13:36 0 NP NP 0 0 0 0 0 0NP N NP NP N N NNP Y N NP NoneLeaks at gas cap, top of fill neck, and tank/fill neck jointarea (top of tank).PIL_245 08/26/08 15:04 0 NP NP NP 00 0 0 0 NP NP NP NP NP N NNP N N NP None Very clean.PIL_247 08/26/08 18:17 0 NP NP 0 0 0 0 0 0 NP NNP NP N N Y NP N N NP None Small leak inarea of injectors, large leak at carbon canister.PIL_248 08/27/08 10:18 0 NP NP 0 0 00 0 0 NP N NP NP N N N NP NN NP None Could not find leak.PIL_250 08/27/08 12:18 NP NP NP NP 0 0 0 0 0NP NP NP NP NP YY NP N N NP None2 Leaks: 3rd injector from front and union of flexible fuelline and fuel rail.I-3 packetID MCM_Date MCM_Time MCM_UnderbodyV MCM_FuelPumpV MCM_PumpToCarbV MCM_FuelFilterV MCM_FuelRailV MCM_FuelInjectorsV MCM_UnderVehicleV MCM_FillPipeToTankV MCM_TankV MCM_NonOEMV MCM_UnderbodyS MCM_FuelPumpS MCM_PumpToCarbS MCM_FuelFilterS wMCM_FuelRailS MCM_FuelInjectorsS MCM_UnderVehicleS MCM_FillPipeToTankS MCM_TankS MCM_NonOEMS pi_VideoFileNum pi_CommentsPacketNumberMCMDateMCMTimeVisual SnifferVideoFileNumber Comments

Underbod y Fuel Pump Pump to Carb Fuel Filter Fuel Rail Fuel Injectors Under Vehicle Fill Pipe to Tank Tank Non-OEM Underbod y Fuel Pump Pump to Carb Fuel Filter Fuel Rail Fuel Injectors Under Vehicle Fill Pipe to Tank Tank Non-OEMPIL_251 08/27/08 15:52 NP NP NP NP 0 0 00 0 NP NP NP NP NP NPNP NP NP NP NP None Ratty, but vapor tight.PIL_254 08/27/08 14:00 0 NP NP 0 0 0 0 0 0NP N NP NP N N N N N N NP None Noleak detected, even at gas cap.PIL_256 08/27/08 15:06 NP NP NP NP0 0 0 0 0 NP NP NP NP NP N NNP N N NP None No leak found. Difficult to visual/sniff due toshrouding.PIL_257 08/28/08 9:26 0 NP NP NP 0 0 0 0 0 NPN NP NP NP N N NPN N NP NonePIL_258 08/27/08 16:45 NP NP NP NP 00 0 0 NP NP NP NP NPNP NP NP NP NPNP NP None Clean. Difficultto visual/sniff due to shrouding.PIL_266 08/28/08 11:08 0 NP NP NP 0 00 0 0 NP N NP NP NPN N NP N N NP None Ratty, but no leak found.PIL_270 08/28/08 12:59 0 NP NP NP 0 0 0 m 0NP N NP NP NP NN NP Y N NP NoneGas cap was off during 2nd and 3rd RSD runs and PSHEDtest.PIL_271 08/28/08 14:18 0 NP NP NP 0 NP 0 0 0NP N NP NP NP N NPNP N N NP NoneLeak at carbon canister lineconnection. Running hot, fanclutch out, boiled coolantbefore entering PSHED.PIL_272 08/28/08 13:39 0 NP NP 0 0 0 0 0 0 NP N NPNP NP N N NP N N NPNone No leak found.PIL_274 08/28/08 15:03 0 NP NP NP 0 0 0 0 0 NPN NP NP NP N N NPN N NP NonePIL_281 08/28/08 17:53 0 NP NP NP 0 0 0 00 NP N NP NP NP N N NPN N NP None Rusty body, but solid fuel system.PIL_283 08/29/08 10:44 0 NP NP NP 0 0 0 0 0 NPN NP NP NP N N NPN N NP NonePIL_284 08/29/08 11:26 0 0 NP 0 0 0 0 0 0 NPN N NP N N N NP N N NP NonePIL_286 08/29/08 13:56 0 S 0 0 0 NP 0 0 0 NP NY N N N NP NP Y N NP NoneLeaks at fuel pump body and top of fill pipe near or at cap.PIL_287 08/29/08 14:45 0 0 0 NP 0 0 0 0 0NP N N N NP N N NP N N NP NoneRapid screened. No leakfound, could not reach intoinjectors but no visual sign of leak either.PIL_290 08/29/08 15:28 0 NP NP 0 0 0 0 0 0 NP N NPNP N N N NP N N NP None No leak found.PIL_294 08/29/08 17:30 0 0 0 0 0 0 0 0 0 NPN N N N N N NP N N NP NonePIL_298 08/30/08 10:11 0 NP NP NP 0 0 0 0 0 NPN NP NP NP N N NPN N NP NonePIL_299 08/30/08 10:48 0 0 0 0 0 NP 0 0 0 NP N N N N NNP NP N N NP None Rebuilt engine. No leaks found.PIL_300 08/30/08 11:26 0 NP NP 0 0 0 0 0 0 NPN NP NP N N N NP N N NP NonePIL_304 08/30/08 12:51 0 0 NP 0 m m 0 0 0NP N N NP N Y Y NP N N NP NoneLeaks at several injectors andcarbon canister, some may befalse positives because exhaust had enough unburnt fuel toset off the sniffer.

### Appendix J Driver Interview InformationJ-1 packetID pi_FleetVehicle pi_ModelYear_gt1980 pi_EveryDayCar pi_Eligible pi_MilesYear pi_MonthsOwned pi_ParkingLocation pi_LastTimeFueled pi_RegularMaintenance pi_OilChange pi_TuneUp pi_NewGasCap pi_FuelSystemRepairs pi_MajorEngineWork pi_SmelledGasoline pi_AccidentEverPacketNumberFleetVehicle?ModelYear> 1980?EveryDayCar? Eligible?Milesperyear?Monthsowned?Parkinglocation?LastTimeFueled?RegularMaintenance?OilChange?Tuneup?NewGasCap?FuelSystemRepairs?MajorEngineWork?SmelledGasoline?Accidentever?PIL_010 N Y Y Y A 1 B A Y B A A A A N NPIL_011 N N Y Y B 1 B C N A A A A A Y UPIL_016 N Y Y Y C 48 A C Y C A B B B Y YPIL_019 N N N Y A 14 B C Y C C A A A Y NPIL_022 N Y Y Y B 72 B C N A A A A A N NPIL_024 N Y Y Y C 120 B B Y D D A A A N NPIL_029 N Y Y Y E 1 B A C E E E E E N NPIL_035 N Y Y Y A 12 B C N A A A A A N NPIL_046 N Y Y Y A 108 B C Y D B C D A N YPIL_050 N Y Y Y C 156 B C B B B A A A N YPIL_060 N Y Y Y B 2 B C A B B E A A N NPIL_061 N Y Y Y B 1 B C A B B A A A N NPIL_062 N Y Y Y B 1 B B A B B A A A N NPIL_063 N Y Y Y B 204 B A A B B A A E N YPIL_065 N Y Y Y B 0 B A A C A A A C Y NPIL_070 N Y Y Y B 0 B B A C C A A A N NPIL_072 N Y N Y A 180 A C A B D A A A N NPIL_078 N Y Y Y A 96 B B A B D B A A N NPIL_079 N Y Y Y B 1 B A A C E A B A N YPIL_084 N Y Y Y B 1 A A A B B A A A N NPIL_089 N Y Y Y C 2 B A A B B B E E Y UPIL_098 N Y Y Y B 60 A A A C D A A A N YPIL_108 N Y Y Y A 48 B C Y B B A A A N NPIL_110 N Y Y Y C 2 B A A B B B A A N YPIL_116 N Y Y Y B 96 A C A C C C A A Y NPIL_117 N Y Y Y B 156 B C A B C A A A N NPIL_118 N Y Y Y D 36 A B A B E A A A Y NPIL_123 N Y Y Y A 144 A C A B D A A A N NPIL_124 N Y Y Y B 0 B B C E E E E E Y UPIL_128 N Y Y Y B 144 B A A B B A B A N YPIL_130 N Y Y Y A 3 B B A B B B A A N NPIL_131 N Y Y Y B 36 B A A B A A A A N NPIL_132 N Y Y Y B 0 B D C B E E E E N UPIL_137 N Y Y Y C 1 A A C B B A A A N UPIL_138 N Y Y Y B 0 B A C E E E E E N YJ-2 packetID pi_FleetVehicle pi_ModelYear_gt1980 pi_EveryDayCar pi_Eligible pi_MilesYear pi_MonthsOwned pi_ParkingLocation pi_LastTimeFueled pi_RegularMaintenance pi_OilChange pi_TuneUp pi_NewGasCap pi_FuelSystemRepairs pi_MajorEngineWork pi_SmelledGasoline pi_AccidentEverPacketNumberFleetVehicle?ModelYear> 1980?EveryDayCar? Eligible?Milesperyear?Monthsowned?Parkinglocation?LastTimeFueled?RegularMaintenance?OilChange?Tuneup?NewGasCap?FuelSystemRepairs?MajorEngineWork?SmelledGasoline?Accidentever?PIL_146 N Y Y Y A 12 B B C B B A B A Y UPIL_151 N Y Y Y A 36 B C A B C A A A N NPIL_157 N Y Y Y B 36 A A A B D C A A N YPIL_161 N Y Y Y B 24 B B Y D B A A A N YPIL_165 N Y Y Y E 0 A C A B B B A A N YPIL_169 N Y Y Y A 24 B A A C D A A A N NPIL_174 N Y Y Y B 36 A C A C E A A A N NPIL_177 N Y Y Y C 1 B C C A A A A A N NPIL_184 N Y Y Y A 72 A D A D A B A A N YPIL_191 N Y Y Y B 48 B C A B B A A A N YPIL_193 N Y Y Y C 120 A C A C D A A A Y NPIL_194 N Y Y Y A 36 B A B D D A B A N YPIL_200 N Y Y Y A 1 B C C B B A E A N NPIL_203 N Y Y Y B 72 A C A B D B A A N NPIL_213 N Y Y Y A 168 B A A C E A A A Y NPIL_217 N Y Y Y E 0 B B A B B A A A N NPIL_218 N Y Y Y A 48 B A A B D A A A Y NPIL_220 N Y Y Y D 96 B B A B D A A A N NPIL_221 N Y Y Y A 3 B A A A B A A A N NPIL_222 N Y Y Y A 60 B A A E A E A A N NPIL_223 N Y Y Y E 1 B A A A A A A A N YPIL_225 N Y Y Y A 144 A A A B B A A A N NPIL_226 N Y Y Y A 1 C A A B A A B A N NPIL_229 N Y Y Y A 240 B C A D D A A A Y NPIL_236 N Y Y Y B 4 B A A B B B A A Y NPIL_240 N Y Y Y A 3 B C A B E A A A N NPIL_242 N Y Y Y A 180 B C A B B A A A N YPIL_245 N Y Y Y A 36 A C A C D A A A N NPIL_247 N Y Y Y B 0 B B A A A A A A N NPIL_248 N Y Y Y D 132 B C B B B A A A N NPIL_250 N Y Y Y C 0 B B A A A A A A N NPIL_251 N Y Y Y A 204 B D B B B A A A N NPIL_254 N Y Y Y A 72 B A A C C A D A Y NPIL_256 N Y Y Y B 2 B B B A A A B A N NPIL_257 N Y Y Y A 72 B A A B A A A A N NPIL_258 N Y Y Y B 72 A C A C A A A A N NJ-3 packetID pi_FleetVehicle pi_ModelYear_gt1980 pi_EveryDayCar pi_Eligible pi_MilesYear pi_MonthsOwned pi_ParkingLocation pi_LastTimeFueled pi_RegularMaintenance pi_OilChange pi_TuneUp pi_NewGasCap pi_FuelSystemRepairs pi_MajorEngineWork pi_SmelledGasoline pi_AccidentEverPacketNumberFleetVehicle?ModelYear> 1980?EveryDayCar? Eligible?Milesperyear?Monthsowned?Parkinglocation?LastTimeFueled?RegularMaintenance?OilChange?Tuneup?NewGasCap?FuelSystemRepairs?MajorEngineWork?SmelledGasoline?Accidentever?PIL_266 N Y Y Y A 144 B C A B B E A A Y YPIL_270 N Y Y Y A 1 B A A B B E E E N NPIL_271 N Y Y Y A 204 B B A B B A A A N YPIL_272 N Y Y Y A 104 B D A B B D A A N NPIL_274 N Y Y Y A 1 B C A E E E E E N NPIL_281 N Y Y Y A 264 B C A B E E E A N YPIL_283 N Y Y Y A 24 A A A B E E A A N NPIL_284 N Y Y Y A 72 B A A B B D C A N NPIL_286 N Y Y Y B 300 B C A C B E E A Y YPIL_287 N Y Y Y C 96 C A A B D B A A Y NPIL_290 N Y Y Y B 12 B A A B B B B B N NPIL_294 N Y Y Y B 36 B B A B B E E E N NPIL_298 N Y Y Y B 48 B C B D A A A A N NPIL_299 N Y Y Y A 264 B C A B B A B B N NPIL_300 N Y Y Y A 18 A D A E E E E E N NPIL_304 N Y Y Y C 48 B A A C C E A A N N

### Appendix K I/M Gas Cap Inspection ResultsK-1 packetID pi_CapResult
Packet Number IM Gas Cap Inspection Result PIL_010 P PIL_011 PIL_016 F PIL_019 PIL_022 P PIL_024 P PIL_029 P PIL_035 P PIL_046 P PIL_050 P PIL_060 P PIL_061 P PIL_062 P PIL_063 F PIL_065 P PIL_070 P PIL_072 P PIL_078 P PIL_079 P PIL_084 P PIL_089 F PIL_098 P PIL_108 PIL_110 P PIL_116 P PIL_117 P PIL_118 P PIL_123 P PIL_124 P PIL_128 F PIL_130 PIL_131 P PIL_132 P PIL_137 P PIL_138 P PIL_146 P PIL_151 P PIL_157 P PIL_161 P PIL_165 P PIL_169 P PIL_174 P PIL_177 P PIL_184 P PIL_191 P PIL_193 PK-2 packetID pi_CapResult
Packet Number IM Gas Cap Inspection Result PIL_194 P PIL_200 P PIL_203 P PIL_213 P PIL_217 P PIL_218 P PIL_220 P PIL_221 P PIL_222 P PIL_223 PIL_225 P PIL_226 PIL_229 P PIL_236 PIL_240 P PIL_242 F PIL_245 F PIL_247 P PIL_248 P PIL_250 P PIL_251 P PIL_254 F PIL_256 P PIL_257 P PIL_258 P PIL_266 P PIL_270 P PIL_271 P PIL_272 P PIL_274 P PIL_281 P PIL_283 P PIL_284 P PIL_286 P PIL_287 PIL_290 P PIL_294 P PIL_298 P PIL_299 P PIL_300 P PIL_304 P