# Peer Review of Estimates of the Fraction of the Fleet with High Evaporative Emissions based on the Ken Caryl Station (Denver, Colorado)

Field Study

Prepared for

Assessment and Standards Division

Office of Transportation and Air Quality

U.S. Environm ental Protection Agency

Prepared by

Systems Research and Application Corporation

652 Peter Jefferson Parkway, Suite 300

Charlottesville, VA 22911

EPA Contract Number: EP

- C

- 11

- 007

March 2012Page 2 

# Peer Review of Estimates of the Fraction of the Fleet with Hig h Evaporative Emissions based on the Ken Caryl Station (Denver, Colorado)

Field Study

Table of Contents

Peer Review of Estimates of the Fraction of the Fleet with High Evaporative Emissions based on the Ken Caryl Station (Denver, Colorado) Field Study (High Evaporative Emissions Field Study)

, Conducted by SRA International p. 3

1. Background p. 3

2. Description of Review Process p. 5
3. Compilation of Review Comments p. 5

4. References p. 2 5 Appendices

A. Resumes of Peer Reviewers p. 2 6

B. Conflict of Interest Statements p. 10 6

C. Peer Review Charge p. 11 4

D. Reviews p. 116Page 3

TO: Kent Helmer, Connie Hart , U.S. Environmental Protection Agency, Office of

Transportation and Air Quality (OTAQ)

FROM: Brian Menard, SRA Internat ional

DATE: March 2 , 201 2

SUBJECT: Peer Review of Estimates of the Fraction of the Fleet with High Evaporative Emissions

based on the Ken Caryl Station (Denver, Colorado) Field Study (High Evaporative Emissions Field Study) , prepared by Eastern Research Group, Inc.



### 1. Background

Gasoline vehicles have evaporative emissions control systems that control excessive evaporative emissions. Gasoline vapors can also be evaporated liquid gasoline, if liquid leaks are present. When
these systems or the vehicl e’s gasoline delivery system malfunction, excessive evaporative emissions can be emitted. Few estimates of the frequency of vehicles in just such a state in the fleet exist, though vapor leaks can have an impact on the inventory of vehicle emissions.

As part of the effort to quantify evaporative emissions from the fleet of gasoline

- powered on

- road vehicles in the developing MOVES mobile sources inventory model, EPA would like to know the
distribution of the mal

- functioning , or leaking evaporative emission s control systems across all vehicles in the fleet. Evaporative emissions occur in light

- duty vehicles when volatile components of gasoline are emitted or when raw gasoline leaks from the fuel system and the evaporative emissions control system.

To meet t he evaporative emissions modeling needs of the MOVES model, EPA and its stakeholders have
conducted studies

.

The Coordinating Research Council (CRC)

- Real World Group through its E

- 77 and E

- 77

- 2 permeation evaporative emission testing programs has confi rmed that leaks, both liquid and vapor, can be a significant part of any fleet hydrocarbon inventory. The program implanted leaks of t he minimum
detectable diameter of the OBD systems , 0.020” . Orders of magnitude higher emissions were seen than a properly operating vehicle

, indicat ing a major impact for inventory, and establishing the need to define
the rate of occurrence of “leakers” in the in

- use fleet. The missing piece of information is how often the leaking vehicles are occurring. Subsequent laborat ory testing in the E

- 77

- 2c program implanted similar size leaks, not only at the gas cap but in other locations which were indicated as high occurrence in the initial field testing work. EPA’s initial estimate was that “High Evaps” make up on the order of 1% of the gasoline

- fueled vehicles in the fleet but there has been evidence that this was lower than what is occurring in the real world. This report uses Colorado evaporative emission s field data collected at I/M

stations to estimate the fractions of va rious levels of high evaporative emission vehicles in the mix of vehicles that patronized the Denver Ken Caryl I/M station during the summer of 2009. Ultimately, EPA would like to know the distribution of the mass of evaporative emissions across all vehic les in the fleet.

The study performed at the Ken Caryl IM station in Denver, C olorado, Estimates of the Fraction of the Fleet with High Evaporative Emissions based on the Ken Caryl Station (Denver, Colorado) Field Study (High Evaporative Emissions Field S tudy), built upon the prior CRC/EPA testing experience. Vehicles entering the Ken Caryl station driveway were screened by an RSD unit using an evaporative indexPage 4

described as EI23. A stratified sample of model year 1961 and newer vehicles were offered parti cipation in intensive evaporative emissions testing, which consisted of the portable sealed housing for evaporative determination ( P SHED) hot

- soak test, the visual, olfactory, and electronic HC detector examination of the vehicle (MCM test) and additional RSD measurements. Overall, the study reinforced an earlier connection seen between RSD and portable SHED values for real

- world light

- duty gasoline vehicles with testing of a wider range of model years and RSD vehicle speeds.

The objective of th e High Eva porative Emissions Field Study is to estimate the fraction of vehicles in the Denver fleet with high evaporative emissions, based on PSHED measurements obtained during summer
of 2009 , and ultimately project these rates onto the Federal fleet . This estimate can be generated by appropriately weighting measurements by their sampling fractions, assigned on the basis of remote sensing measurements obtained when vehicles entered the Ken Caryl Station during the study period

. The CRC E

- 77 and E

- 77

- 2 studies and th e Lipan (Colorado) I/M Station studies all preceded the Ken Caryl study, which provides the background and data for this report.

From the vehicle selection and testing at Ken Caryl, two data sets are used to perform this analysis. The
first is the set of 175 vehicles that were participants in the study and therefore received RSD measurements and portable SHED measurements. The second is the set of all 5830 vehicles that entered the station driveway during the study and represent the fleet of vehicles that patronize Ken Caryl. Most of these vehicles were not participants in the study and these therefore have only RSD measurements but no portable SHED measurements. The portable SHED values of the 175 participants were re

weighted using the RSD index to esti mate the distribution of portable SHED values of the 5830 vehicles that entered Ken Caryl during the study period. The results give an estimate of the fraction of “high” portable SHED vehicles for different definitions of a high portable SHED result.

The RSD and portable SHED results on the 175

- vehicle stratified sample of vehicles entering Ken Caryl

were used to establish a relationship between the EI23 evaporative emissions index and hot

- soak emissions as measured by the portable SHED test. This relati onship was then applied to the 5830

- vehicle random set, which is made up of most vehicles that entered the I/M station driveway during the study period. Standard re

- weighting techniques are used to estimate the fraction of the Ken Caryl fleet that is expe cted to have portable SHED results greater than various definitions of a high portable SHED value, “cutpoint”. The de

- stratification technique is also applied to the Ken Caryl fleet as a function of model year group. A Monte Carlo simulation provides a me ans of estimating the influence of various uncertainties in the Ken Caryl data on the uncertainty of the calculated high portable SHED result fraction. An estimate of the uncertainty is critical to understanding the quality of the results of a
calculated h igh portable SHED value fraction. This, in turn, provides important guidance to EPA for using
the results of the calculations for MOVES.

EPA sought a n expert peer review of the High Evaporative Emissions Field Study , including reviewers’ opinion on the appropriateness of the statistical techniques described in the report and their appropriateness in the context of any data accuracy/quality issues . This report documents the peer

r eview. Section 2 of this memorandum describes the process for selecting re viewers, administering the review process, and closing the peer review. Section 3 summarizes reviewer comments according to the series of specific questions set forth in the peer review charge. The appendices to the memorandum

contain the peer reviewers’ resumes, completed conflict of interest and bias questionnaires for each reviewer, and the peer review charge letter.Page 5



### 2. Description of Review Process

In October 2011, OTAQ contacted SRA International to facilitate the peer review of the High Evapor ative Emissions Field Study

. EPA provided SRA with a short list of subject matter experts from academia

, consulting, and industry to serve as a “starting point” from which to assemble a list of peer reviewer candidates. SRA selected three independent (as defined in Sections 1.2.6 and 1.2.7 of EPA’s Peer Review Handbook, Third Edition) subject matter experts to conduct the requested reviews. SRA selected subject matter experts familiar with statistical analysis and vehicle emissions . To ensure the indepe ndence and impartiality of the peer review, SRA was solely responsible for selecting the peer review panel. Appendix A of this report contains the resumes of the three peer reviewers. A crucial element in selecting peer reviewers was to determine whether reviewers had any actual or perceived conflicts of interest or bias that might prevent them from conducting a fair and impartial review of the High Evaporative Emissions Field Study . SRA required each reviewer to complete and sign a conflict of

interest and bias questionnaire. Appendix B of this report contains an explanation of the process and standards for judging conflict and bias along with copies of each reviewer’s signed questionnaire.

SRA provided the reviewers a copy of the most recent version of the High Evaporative Emissions Field Study as well as the peer review charge containing specific questions EPA asked the reviewers to address. Appendix C of this report contains the memo to reviewers from SRA with the peer review charge.

SRA delivere d the final review comments to EPA by the requested date. These reviews , contained in Appendix D of this report, included the reviewers’ response to the specific charge questions and any
additional comments the y might have had

.



### 3. Compilation of Review C omments

The High Evaporative Emissions Field Study was reviewed by Dr. H. Christopher Frey (North Carolina State University), Dr. Eric Fujita, (Desert Research Institute), and Mr. Keith Knoll (Czero) . Appendix A
contains detailed resumes for each of the reviewers. This section provides a compilation of their

comments. The complete comments of the three reviewers may be found in Appendix D.

The r eviewers were asked on the basis of their work experience and expertise to comment on the methodologies, an alysis, conclusions, and narrative of the High Evaporative Emissions Field Study . They brought a range of statistical and scientific skills to this process, as is reflected in the ir varying focuses in commenting on the report . The reviewers were in gener al agreement as to the importance of the field study and the significance of its results. Notwithstanding this, some of the reviewers were more critical than others in their comments about the quality and organization of the written report. Two reviewers provided suggestions for editi ng and reorganizing the report, with one providing substantial edits and suggesting a tho ro ugh rewriting and technical editing of the report. The comments in this compilation have been categorized as specific technical , gene ral, and editorial.Page 6



### 3.1 Specific Technical Comments

Frey: [1] There are some fundamental questions related to this work that should be part of the

objectives and that should be addressed in the technical results and conclusions:

1. Is PSHED a good surro gate for SHED?

2. Can an RSD, if appropriately interpreted, be a good surrogate for a PSHED
measurement?

The first question presumes that SHED is the reference method to which all other methods should be compared. What, however, is really measured in a SHED measurement? There are many evaporative processes. Some, such as refueling, are not addressed by SHED. Which processes are addressed?

In what ways are PSHED measurements similar to those of SHED measurements, and in what ways do they differ? Is PSHED effectively just as good as SHED?

What kinds of evaporative processes can be measured using RSD? There is an unstated hypothesis in this report that RSD measurements can provide information on evaporative emissions in a manner comparable to that of PSHE D, if only the RSD measurement is appropriate interpreted. What is the basis for this hypothesis? What evaporative processes affect the quantity of HC that is detected by remote sensing? If there was no error in the measurement, would strong concordance be expected between RSD and PSHED? If so, why? A clearer statement of hypothesis and the theoretical underpinning for it would be helpful when interpreting results.

[2] Over the years, EPA has been criticized for making public policy and developing mod eling tools to support public policy that are based on proprietary data and methods. The use of proprietary methods precludes a full understanding and review of the underlying science. A case in point are the “Method A” and “Method B” exhaust plume analy sis methods associated with the ESP remote sensing instrumentation. Since the distinction between Method A and Method B appears to be an important technical consideration in this study, the lack of disclosure of what these methods are is unacceptable.

[3] The purpose of the report is to estimate, not develop, fractions of various levels of high evaporative emissions. However, nowhere is any justification or rationale given as to why this report is focusing on the Denver fleet. Since Denver is at high altitude, and barometric pressure is a factor in evaporation, it is not clear that data from Denver would be representative of other parts of the U.S.

[4] What is the purpose of “stratification.”? Why is achieving stratification a goal in itself? E.g., page 4

- 3, “to achieve stratification, a higher fraction of vehicles...” The reader can eventually figure this out, but why can’t the authors communicate this more clearly? The purpose seems to be to evaluate a screening procedure for identifying vehicles w ith high evaporative emissions rates, but what about goals for false positives or false negatives?

[5] Is it literally the case that six RSDs were used? i.e., six remote sensing devices at six locations? Or were the two highway “RSDs” based on repeated passes by the same RSD? ThePage 7 authors need to stop using the term “RSD” to refer to a measurement. RSD = Remote Sensing Device and refers to an instrument. A measurement made using an RSD could be described as a remote sensing measurement. What is an RSD beam block? This is shop jargon (I know what it means, but most readers won’t).

[6] What is the ‘standard I/M inspection’

– for those of us not from Denver, please explain what this is. Also, explain the “Modified California Method”

– both of these sho uld be documented in the new methods chapter that needs to be written. Who does the olfactory examination? What is an ‘electronic HC sniffer”? Is this relevant to the report? If not, then
delete mention of these.

[7] Page 4

- 4: Method A was used on ES P 4000 and 4600 instruments, and Method B was used on ESP3000 series instruments. Yet, results for both Methods A and B are reported in Table 4

- 2. Were two RSD instruments used at each RSD site? Or were both Methods A and B applied
to the same data meas ured from just one RSD instrument at each site? At the end of the paragraph is it mentioned that ‘code’ was ‘added’ to the 4000 and 4600 series instruments

– it would have helped if this was mentioned up front, and if there was a prior section that more clearly disclosed the study design in terms of what instruments were deployed at what locations and what the vehicle path was through each RSD site. It would help if this text were reorganized so that there was an intro paragraph, one paragraph on Method A, one paragraph on Method B, and then a paragraph that compares Methods A and B. Are the CO, NO, and
CO2 results shown in Table 4

- 2 based on Method B? The distinction between Methods A and B with respect to how they deal with exhaust versus evaporative concentrations of HC is not clear. To merely state that “ESP believes” that one method is responsive to exhaust and another is not is quite tenuous.

[8] Page 4

- 4 (bottom): regression toward the mean.... This is stated as if it is an underlying principle i n a rather didactic manner, but the actual concept is poorly explained here. A measurement is biased if it is systematically high or systematically low. If the error is randomly distributed with a mean of zero, then the measurement is subject to random e rror, not bias. The random error can lead to false positives or false negatives if used in the context of a binary decision (e.g., vehicle is a high emitter). This context is not clearly articulated. False positives or false negatives are not necessaril y a result of bias, but rather a result of imprecision (random error). The discussion here of bias is thus without sufficient context and
therefore is unclear.

[9] What role does ambient temperature have in contributing to variability in estimated

evapo rative emissions based on RSD measurements? Since the “Temperature” in Table 4

- 2 (ambient temperature at the time of each RSD measurement?) differs from the PSHED “Seal Temperature”, what role might this have in confounding the results?

[10] Table 4

- 2: what is the meaning of negative values for HC Method A (ppmC 3) and how are these interpreted? Table 4

- 2 values of CO 2 percent appear to be what one would expect in the tailpipe, but this cannot be what was actually measured in the exhaust plume. How is
the air

- to

- fuel ratio inferred, or is it assumed to be stoichiometric? Some discussion is needed. The text barely alludes to this. More detail is needed in a methods chapter. Is RSD temperature the ambient temperature at the date and time of the measure ment?Page 8 [11] The quantity in Figure 4

- 1 labeled as “RSD EI23” needs to be clearly defined. Is this based on any numbers given in Table 4

- 2? Which specific column of Table 4

- 2 is “RSD EI23”? Which specific column of Table 4

- 2 is “PSHED Mass (g/Qhr)”? P resumably, “Measured PSHED HC at 15 Minute Soak (grams)” in Table 4

- 2 is the same as “PSHED Mass (g/Qhr)”. However, use consistent terminology in both places to avoid ambiguity. The EI23 values need to be added
to Table 4

- 2.

[12] Page 4

- 22: what role d oes ambient temperature have in the estimation of EI23? The RSD measurements are made at ambient temperature. Evaporative emissions are proportional to ambient temperature (something that needs to be introduced and discussed in a background or methodolog y section of this report). Is the EI23 metric less responsive to evaporative emissions at lower ambient temperature? Speed is not the only factor that affects inference of evaporative emissions.

[ 13 ] P age 4

- 23: W hy is model year important? Earlier, a note was made that model year was not part of the EI23 binning method.

[14] If there are multiple EI23 bin values available for some vehicles, these data should be analyzed separately to determine the robustness with which a vehicle is assigned to an EI 23 bin. Ambiguity in assignment to an EI23 bin would be a significant factor to consider in evaluating the usefulness of this method.

[15] Table 4

- 5. The table is actually of EI23 bins and model year groups, not screening remote sensing measurements. T hus, the caption is not consistent with the content of the table.

[16] Page 4

- 25: The terms sample and population in the Appendix B need some careful re

thinking or at least more clear definition. Here, the term ‘population’ is implied to describe
the to tal sample of 5,830 vehicles (which is actually a sample from a larger fleet). That is okay, but at least be clear as to the meaning of the term ‘population’ as used in Appendix B. W h is the fraction of the population of vehicles that fall into each EI23 bin. It is not clear as to the definition of “n” in Appendix B

– is this the total number of vehicles in the ‘population’? (i.e. n=5830?). L=7 (could be stated clearly). The term h is not clearly defined in appendix B in
terms of other variables. Is this the standard error of the fraction of elevated measurements in each strata? Appendix B does not actually show how one estimates the estimated fraction of the population that is above the threshold. How was the value 0.127 estimated? This
appears t o the product p h W h summed over all h. Based on the numbers given in Table 4

- 6, over 75% of the estimated ‘elevated PSHEDs’ (a sloppy term) are from Bins 1

- 4, which account for over 96% of the ‘population.’

[17] Table 4

- 8. It is not very clear as to wha t variable is implied by “High

- PSHED Fraction...” is this based on p h and W h defined in some different way compared to Table 4

- 6?

[18] The assumption of the EI23 bins is that they are bins of EI23 values. Since no assumption is made regarding model year, it is not really correct to imply that if there is a dependency on a model year that somehow the use of EI23 is inherently inappropriate. It could be that the fraction of vehicles with high PSHEDs measurements is correlated with EI23 and with model

year, but that does not imply that EI23 would not be a useful indicator. Whether EI23 is a useful indicator can be determined with or without consideration of model year. In fact, ifPage 9 EI23 has a trend with respect to model year that is consistent with the trend with respect to PSHED measurements, then there might be increased confidence in the utility of EI23 as an
indicator.

[ 19 ] Section 4.5: the discussion here suffers from a conceptual problem related to not clearly defining what is meant by “uncertainty.” The term uncertainty is used inappropriately as if it refers only to imprecision, and the notion of bias is discussed as if it distinct from “uncertainty.” Uncertainty refers to lack of knowledge regarding the true value of a quantity,
and includes both random and systematic sources of error. Random error is imprecision. Systematic error is bias and also known as lack of accuracy. Thus, bias is a component of uncertainty, not distinct from it.

[ 20 ] Uncertainties associated with small sample size are t ypically quantified based on random sampling error. The discussion of the role of ‘chance alone’ is inappropriate as written. Perhaps the intended statement is that if a different random sample of vehicles had been selected, the number of vehicles with P SHED measurements greater than 2 g/Qhr might have been different from the 2 that were observed in the available sample. Because the fraction of vehicles with PSHED measurements greater than 2 g/Qhr is based on a sample, there is ‘sampling error’ in the e stimate. If the sample is assumed to be random, then the error of the estimate can be estimated based on sampling distributions of the statistics (a statistic is a quantity estimated from a sample). The errors shown in Table 4

- 11 are of unclear basis. F or example, the ‘size of error for ‘high PSHED Definition’ of 2 is given as 0.025. There should be more detail on how this number was estimated, based on the data given in Table 4.6.

[ 21 ] PSHED measurement error should be more clearly discussed. The tex t refers to ‘two parts’ but really only one ‘measurement error’ is actually addressed. Measurement error typically refers to the imprecision and bias of the measurement method itself. Propane retention and recovery tests are an incomplete indicator of th e imprecision and bias of the PSHED method, because actual evaporative emissions are not pure propane. Variability in hot soak emissions is a measurement error only in the context of attempting to assess the repeatability of measurements of the same vehic le under the same conditions. However, it is not clear that such an experiment has actually been done. If there are underlying differences in the state or condition of the vehicle, then the variability in the measurements is not
because of the measuremen t method itself but because of the state of the vehicle being measured. The concept of repeatability of the measurement should be discussed in a separate paragraph or subsection. If the repeatability is only

- 50% to +200%, then there is significant quest ion as to the usefulness of any kind of PSHED test when compared to a ‘brightline’ threshold that is a point value.

[ 22 ] The discussion of detection limit and how it was inferred is difficult to follow. First, it would help to define what is meant by det ection limit. It is not clear how a detection limit can be inferred by making a measurement on a vehicle or any sample for which it is not known as to whether the HC concentration is actually zero. Why not use a ‘zero’ calibration gas that contains 0 ppm of HC? A baseline before a vehicle enters the PSHED does not guarantee that actual concentration was 0 ppm of HC. However, it does provide a background level. However, the text does not discuss what is background or the role of background in making

mea surements.Page 10 [ 23 ] Pa g e 4

- 32: the analysis of duplicate EI23 measurements is quite important, and the text refers to Appendix A. Appendix A is very poorly written and very unclear. It is not apparent that there are any data regarding the duplicate EI23 values in the main body of this report or in the appendix. The data and findings from these data should be disclosed.

[ 24 ] The rational for the bias in the EI23 values and the implication that it would ‘tend to elevate the high

- PSHED fraction’ needs to b e more clearly articulated.

[ 25 ] P age 4

- 33: the apparent confusion regarding detection limit and background level is evident in the second paragraph on this page. One does not subtract a detection limit from a measured value to impute an unbiased estima te. This would be done only for a background level. However, if the background is negligible compared to the measurement, this will have
little effect on the results.

[ 26 ] The discussion of a possible Monte Carlo simulation is so vague that it hardly me rits being in this report. Unless the authors can clearly define terms and propose a meaningful algorithm, the recommendation for future Monte Carlo simulation could be stated briefly, with further development left to those competent to conduct such an an alysis.

Fujita: [ 1 ] While the EI23 evaporative index would be useful for identifying gross evaporative HC

emitters, its ability to estimate fractions of high evaporative emissions within various levels of evaporative emission other than the top end of th e distribution seems limited.

[ 2 ]Conversion of EI23 measurements to Bins provides what appears to be clearer summary of the distribution of EI23 values by PSHED

- equivalent running loss levels. As I understand this procedure, this classification assigns th e estimated evaporative indices into bins with width that each corresponds to one standard deviation of the variability of a single EI23 measurement (after accounting for the effects of the exhaust HC emissions on EI23). The EI23
Bins are then associated w ith probabilities of exceeding various threshold PSHED hot

- soak emission levels. This approach allows the association to be made without regard to the quality
of the correlation between EI23 and PSHED hot

- soak levels, which we know is poor. EI23
values in at least the first three EI23 Bins (with PSHED thresholds of greater than 1, 2 and 5 g/Qhr) are probably below the method limit of detection and are really random noise. If so, there is about equal chance that any of the EI23 values in the first three Bins has a corresponding PSHED above the threshold. Therefore, it is not unexpected that fractions of
elevated PSHED in Table 4

- 6 are about the same for Bins 1 (6.7%), 2 (7.6%) and 3 (9.6%). These fractions are likely not valid given the measurement sensitivit y. If 20g/Qhr is a reasonable level where the corresponding EI23 values become reliable, then the distribution shown in
Table 4

- 4 for this High PSHED definition is valid for all EI23 Bins. The fractions are progressive
less reliable for the lower EI23 Bins at lower thresholds values.

I believe the net result is an overestimation of the fractions of elevated PSHEDS in the lower Bins. Products of these fractions with the proportionally larger numbers of vehicles in these
bins for the Random fleet will result in larger fractions of elevated PSHEDs in the larger fleet of vehicles. For example, results of the de

- stratification calculations in Table 4

- 6 shows that 12.7% of the 5830 vehicles in the random sample are estimated to have corresponding high

PSHEDs defi ned as greater than 2 g/Qhr. If the first three Bins are counted as zero, then this fraction drops to 5.5%. Also dropping Bins 4 and both 4 and 5 reduces the fraction to 2.9% andPage 11 1.6%, respectively. The more appropriate fraction is likely between 1.6 to 5. 5% rather than
12.7%.

[ 3 ] It should also be noted that the distributions are presented without quantitative estimate of uncertainty and bias that are inherent in the study approach. In addition to the poor limits of detection of RSD evaporative index, the following sources of uncertainty and bias were not assessed in the report.

The distributions are based on static SHED 15

- minute hot

- soaks and do not include diurnal evaporative emissions and may not fully account for all running emissions.

The r esidual hydrocarbon signal in the RSD measurements in excess of the regression
line of HC with CO 2 results is a crude measure of the diluted mixture of evaporative emissions from fuel permeation, vaporize fuel leaks, and fuel system venting during
vehicle operation. Unlike exhaust pollutant, there are no tracers for evaporative HC emissions to account for dispersion rate of emissions.

Replicate LSHED and PSHED tests have large variability. Section 4.5 does not address the significance of the large variabili ty of replicate SHED tests to distribution of fractions of “high evaps” at various definitions.

[ 4 ] Ambient temperature was not included as a variable in the study design and PSHED and replicate RSD measurements were all made within a short time at about the same temperature. The test sets within each EI23 Bin were conducted at ambient temperature spanning a range of up to about 30 o C. Evaporative emissions are known to increase with ambient temperature with doubling of permeation for 10 o C rise in temperatu re. This likely would not be issue if ambient temperature was a random variable in the study and test sets within each bin had similar random distribution of temperature. Was this checked? The potential bias due to differences in temperature would be minim al for the high emitter bins, but may be more important for the other bins.

[ 5 ] Most vehicles in Bins 6 and 7 had high exhaust HC emissions, which can contribute to the estimated evaporative emissions. The report asserts that this positive interference is mitigated by the binning procedure. From the relevant discussion in Appendix A, it is difficult to determine the significant of the positive interference or the effective of the binning procedure.

[6] P. 1

- 2, line 5. Are there plans for follow

- on uncerta inty analysis that can be described
here?

[7] P. 2

- 2, second full paragraph: Describe briefly the evidence, with appropriate references, that previous estimate of “high evaps” were lower that what is occurring in the real world.

[8] P. 3

- 14, last senten ce: Meaning is unclear. Why would large variability of PSHED hot

- soaks itself result in overestimation of fraction of vehicles with high hot

- soak emissions?

[9] P. 4

- 25, Table 4

- 6: What is the basis for S h in the calculation of standard error of the
frac tion of elevated PSHEDs? What are the sources of the values used in calculating the
standard deviation?Page 12 [10] P. 4

- 30, Table 4

- 10. Unless there is good reason for using natural log, give estimated error for column 2 in units of g/Qhr.

[11] P. A

- 1, item i) : Residual rather than N?

Knoll: [1] [Section 3] It would be useful to provide some further explanation regarding HE

- 3555

evaporative emissions behavior. Why did these emissions continue to increase with time? Was the evaporative purge system on the vehi cle evaluated for proper functionality? Was any testing done to identify root cause?

[2] The first bullet point under Summary of LSHED and PSHED states that vehicles with low
hot

- soak values have PSHED and LSHED results that “are very similar”. I think th is statement is misleading and may not be correct. The similar scatter shown by the data across three orders of magnitude on a log

- log plot suggests that variation at low values was indeed less than at high values. But it is not clear that the data could b e considered nearly the same. This assertion requires further justification from the data analysis.

[3] The last paragraph in

. . . section [3] providing relevance to the on

- road fleet requires clarification, further explanation and a review of the under lying assumptions. I believe the author is saying that because there is high scatter and a small number of samples available, the upper bound on extrapolating this data to the on

- road fleet is necessarily high; higher
than it would be if there were either a larger number of sample or a smaller variation in the data. If this is his message, it needs to be stated more clearly and with a more definitive confidence level. Also, is a normal distribution being assumed? If so, state it and explain why
such an assu mption is valid. If not, then what distribution is assumed and why?

[4] Paragraph 2 of Section 4: The last sentence of this paragraph suggests that two influence factors complicate extrapolation of the Ken Caryl dataset to the Denver

- wide fleet. What

exa ctly those two reasons are, however, is not clear from the paragraph text. My interpretation is summarized in the following bullets. Text of the paragraph should more clearly support the thesis statement given at the end of the paragraph.

The sample of v ehicles that visit I/M stations likely has higher emissions than the fleet

at

- large. The Denver

- wide “clean screening” program exempts about 40% of registered vehicles based on low RSD readings. Consequently, the 60% of vehicles that go to I/M

stations are the higher emitting fraction of the total Denver fleet. Using this sample population for emissions projection to the Denver

- side fleet will likely skew the overall population estimate. However, there is no reason to believe that high tailpipe emissions

ve hicles are necessarily correlated with high evaporative emissions vehicles. So the real
effect of this bias is not clear. The Ken Caryl I/M station is located in a higher income part of Denver. Consequently, the population of vehicles visiting this I/M st ation is likely to comprise newer and therefor cleaner vehicles than the Denver fleet as a whole. As far as I can tell, this bias has no mitigating factors.

[5] Accurate application of the Monte Carlo simulation method assumes a random distribution
and a large number of samples. This paragraph should include a statement regarding the limitations of this method for analyzing the current dataset. The author does provide later inPage 13 this report adequate justification that the sample population truly is random. This was well thought

- out and well reported. Including some statement in this paragraph, however, would be helpful. I do not believe the author addressed the limitation of population size. This limitation should be mentioned here. Some comment regarding th e potential impacts of this
limitation should also be stated.

[6] In Section 4.4, Table 4

- 6: It is not clear how the fourth and fifth columns are calculated from columns 2 and 3. This should be explained.

[7] [S] ection [5] of the report

goes on to dis cuss additional data that is now available for further investigation. Limitations of the additional data are also identified. For example, the PSHED data from Summer 2010 are identified as not being selected using a stratified random design. As such, these data are not suitable to the Denver

- wide fleet

. leaves the estimation of the high

- PSHED fraction of the Denver

- wide fleet incomplete. No estimation is provided because the dat a are identified as inadequate. provides no basis for extrapolating the results obtained to an estimate of the nationwide fleet as is needed by EPA. For EPA to apply this dataset to the nationwide fleet (via MOVES), additional justification would be necessary.



### 3.2 General Comments

Each o f the reviewers provided general comments on t he High Evaporative Emissions Field Study

. Among these general comments were evaluations of the report’s strengths, suggestions for improving and strengthening certain of its elements, and queries for further information.

Frey: [1] What is the main cont ribution of this report? What are the key limitations? What

additional work is needed? If the purpose is to estimate the fraction of vehicles with evaporative emissions exceeding a threshold, the method described in this report using EI23
Bins and a ‘s tratification’ approach may be reasonable; however, the uncertainty in the estimates made using this method are unknown. Such uncertainties should be estimated as the next step. Without quantification of uncertainty, the utility of this approach is uncle ar.

[2] Some key issues that should be addressed in the conclusions:

Is PSHED a useful surrogate for SHED? Can RSD measurements, if appropriately inter preted, provide an indicator of evaporative emissions?
Is EI23 a useful indicator?
Are the trends in th e results for high evaporative emissions fractions in the vehicle fleet consistent with model year? What results developed here provide some confidence that EI23 is operationally useful? What are limitations of EI23? What other indicators should be explo red? What uncertainties have been quantified? What uncertainties have not yet been quantified?Page 14 Need for further evaluation of uncertainties prior to making a decision on acceptance of this approach? Application of this or other approaches to fleets that a re more representative of the U.S.
fleet.
Others?

Fujita: [1] The experimental approach and methods are adequately documented in the report and

accompanying background document. Presentation of the results, including tables and figures, are generally cle ar except as noted

. . .

[2] P. 4

- 24, 1 st paragraph, last sentence: Are the quantifications of uncertainties and bias part
of a follow

- up report? When is this expected?

Knoll: [1] The analysis relating RSD measurements to SHED results appears valid and well thought

out. Uncertainties were investigated and sensitivity analyses were conducted. Use of RSD appears to provide considerable promise for determining high evaporative emissions vehicles
from the in

- use fleet.

[2] The limited set of vehicles (175 total) that received both RSD and PSHED measurements was used to develop a correlation between RSD readings and measured evaporative emissions. This correlation was applied to the larger set of vehicles (5830 total) that visited the Ken Caryl I/M station during the summer of 2009. In this way, an estimate was made of the percent of vehicles visiting Ken Caryl over the study period that had high evaporative emissions. This projection was well justified based on results presented in the report. Speculation w as also made regarding projecting these results to the Denver

- wide fleet. Limitations associated with such a broad projection were given. Specifically it was noted that the existing dataset from the Ken Caryl I/M station was limited in relevance to the Den ver

wide fleet for two reasons: 1) Colorado exempts about 40% of all registered vehicles from I/M inspection based on RSD measurements and 2) the Ken Caryl I/M stations is located in an
affluent section of the Denver metro area. The first caveat means that the study sample (5830 vehicles) is likely to contain a disproportionate percentage of vehicles with high emissions

– either evaporative or tailpipe. As such, the study sample is likely to be biased towards those vehicles with high evaporative emissions a nd is therefore not a random representation of the Denver fleet. The second caveat means that the study sample is likely to be composed of newer, properly functioning vehicles. Again, this introduces a bias in the database preventing it from being a random representation of the Denver fleet. Speculation was also made regarding projecting these limited results to the nationwide fleet. Limitations associated with this larger projection were not discussed.



### 3.3 Editorial Comments

Each of the reviewers in vary ing degrees a ss essed the narrative of the report and suggested improvements for accuracy, clarity, and consistency. One of the reviewers undertook a thorough critique of the report in this regard, providing significant editorial suggestions and stressing the need for a thorough re

- organization, rewrite, and technical

. To this end, all of the reviewer s highlighted typographical and formatting errors, incorrect word choice, and omissions, including missing references.Page 15

3.3.1 Drafting and Technical Edit of t he Report

Frey: [1] The review of this report was significantly hampered by the very poor quality of the report

organization and writing.

A key question when writing any report is: Who is the intended audience for this report? The
intended audience sh ould include all stakeholders of the MOVES model, since this effort appears to be aimed at providing a technical basis for quantification of the fraction of the on

road fleet that has high evaporative emissions rates. However, as written, the report is ai med at fellow technicians who are familiar with the undefined shop jargon used by the authors. This report contains repeated sloppy use of jargon that may be meaningful to the report authors, but that make the report difficult to read by anyone else. Tab le 1 is a list of terms that are introduced in the text without definition, without adequate definition, or that should be introduced, defined, and used in the text. The list of terms in Table 1 should be used to construct a glossary for this report. Whe n a term is first used in the text, it should be defined
in the text.

Table 1. Terms Introduced in Draft Report Without Definition or Explanation: these terms should be defined/explained when first mentioned. A glossary of these terms with definitions
should also be created.

Terms that Need to be Defined Comment

Aging enhanced evaporative emissions
vehicles ? given lack of definition of ‘aging,’ and ‘enhanced,’ the meaning of this is unclear to the
readers.

Aging enhanced vehicles Undefined. Explai n this.

Approximate algorithm No idea what this means. Needs to be explained.

As

- received condition Should explain what this means.

Beam block This is shop jargon. The intended meaning seems to be exhaust plume measurement. Needs to be defined/explai ned when first used.

Bench purged Presumably, this implies that the canister was removed from the vehicle and purged (how) on a lab bench. Needs more explanation for clarity.

Bias (systematic error, inaccuracy) See comments

Bin de

- stratification De

- str atification with respect to what? How?

De

- stratify (and de

- stratifications) This term is used without definition. Not clear what
this is.

Detection limit Mentioned on p 4

- 31 but not defined.

(cont.)Page 16 Terms that Need to be Defined Comment

EI23 Mentio ned numerous times without any explanation

EI23 Bins Define when first mentioned. Introduce in a new methodology chapter prior to using this term in results chapters

Electronic HC sniffer Is this relevant to the content of the report? If not,
delete. If so, then explain.

ESP ? Seems to be the name of a company. ESP, Inc.?

Evaporative emissions canister Is this a canister that produces evaporative emissions? Need to explain to the reader what this is. A corresponding conceptual diagram of the

sourc e of evaporative emissions and methods for prevention and control of evaporative emissions would help in explaining what this (and other relevant vehicle systems or components) is.

g/Qhr Is not defined until page 4

- 4, although it is used in earlier parts of the report.

Gross liquid “leakers” Is there a quantitative definition of this, or at least a working definition? Explain.

HC As good practice any abbreviation should be
defined when first used.

high evaps This is shop jargon. A formal technical rep ort should have thoughtfully developed and carefully defined terminology.

High running loss emissions What constitutes “high”? by what criterion or
criteria?

High

- PSHED, and “high

- PSHED fraction” This term is shop jargon. The intended meaning
appears t o be “vehicles with high evaporative emissions as measured using the Portable SHED

Hot 505 This is undefined. Presumably, this is a hot stabilized dyno test cycle. If so, then give the graph of speed versus time and provide some explanation.

Hot soak d efine

(cont.)Page 17 Terms that Need to be Defined Comment

IM Yes, most readers will know what this is, but as good practice any abbreviation should be defined
when first used.

Implanted leak Undefined. Explain this. Give an example.

Index/PSHED This ter m is unclear

Intrusive pressure test What is this?

Ken Caryl Introduced as if the name of a person, this should be consistently termed “Ken Caryl IM Station” or something similarly descriptive (e.g., Caryl Station).

leakers Is there a quantitative defin ition of this, or at least a working definition? Explain.

Low evap More shop jargon. A formal technical report should have thoughtfully developed and carefully defined terminology.

Low running loss emissions What constitutes “low”? by what criterion o r criteria?

Method A Define. Introduce in methods chapter.

Method B Define. Introduce in methods chapter.

Modified California Method Define. If not relevant to this report, delete.

MOVES MOVES is mentioned but never introduced or explained.

Near

- ze ro vehicle Undefined. Explain this

Noise, noisy Used on page 4

- 31 without definition

OBD code to flag I know what the authors are trying to say, but many readers will have no idea. First, explain OBD and what is an OBD code. Explain what is meant by ‘ flag’.

OBD evaporative codes What are these? Needs to be explained

Odometer Resolution What is the meaning of the codes given in Table 4

- 1?

ORVR ?

Precision (imprecision) See comments

(cont.)Page 18 Terms that Need to be Defined Comment

Pre

- enhanced veh icles Undefined. Explain this.

Pretesting Page 4

- 2

PSHED PSHED is defined on page 1

- 1 as “portable SHED”,
but “SHED” is not defined.

RSD The term RSD is used on page 1

- 1 without
definition.

RSD Method B This method should be introduced and explained in a methodology section of the report.

Running loss emissions Define/explain

Seal Barometric Pressure Table 4

- 2: this term is undefined. There needs to be a footnote to explain what this is.

Seal Temperature (F) Table 4

- 2: this term is undefined. There needs to be a footnote to explain what this is.

Selection RSD Mentioned on page 4

- 3. An “RSD” is a measurement device, but the term “RSD” is used inappropriately to refer to a measurement of a specific vehicle. The intended meaning of
“Selection R SD” is “screening remote sensing measurement.” The screening measurement is
used to determine whether the vehicle will be
recruited for addition RSD measurements and

PSHED measurements.

SHED Amazingly, SHED is not defined the first time it is mentioned, on page 1

- 1.

Slow vapor leaks What is a “slow” leak? Does this refer to a low emissions leak? Of vapor? Of evaporating liquid? Needs to be defined and explained.

Standard de

- stratification techniques ? undefined.

Standard I/M inspection Explain. Or , if not relevant, delete.

Stratified sample With respect to what? This term needs to be explained when first used.

Stratified set Explain in new methods chapter.

Uncertainty Should be defined

– see comments

(cont.)Page 19 Terms that Need to be Defined C omment

VDF Table 4

- 2: this term is undefined. There needs to be a footnote to explain what this is.

VECI Engine Family Table 4

- 1. needs to be defined in a footnote.

VECI Evap Family Table 4

- 1. needs to be defined in a footnote.

[2] The report need s substantial copy editing by a competent technical writer. For example, the report contains frequent use of the first person, which is inappropriate in formal technical writing. In numerous places, statements of belief are made (e.g., “we believe”). Th e reader
does not care what the authors ‘believe.’ The reader cares about what is known and what is not known, and reasonable interpretations based on evidence. The report contains numerous metaphors, which are inappropriate for formal technical writing . For example, several times the authors describe what an instrument ‘sees.’ Aside from these problems there are numerous instances of unclear yet repetitive statements. If a student had handed me this draft report, I would have read a few pages and th en handed it back as unacceptable.

As an example of poor writing, consider the last paragraph on page 4

- 2.

What are ‘pretesting data’? ‘All of that pretesting data was’ could simply be “These data
were.” “receive RSDs”

- this doesn’t make sense. How does a vehicle receive a remote sensing device? The intended meaning seems to be “were measured using remote sensing.” Having read the appendix, I cannot figure out the basis for the statement “Analysis of the EI23 index... “ “to allow the EI23 to b e less dependent on an exhaust emissions, we developed EI23 Bin” is awkward

– should be “To reduce dependence on exhaust emissions, EI23 Bins were developed.” Do not use first person. And so on. Aside from the poor wording, the key technical concepts ar e unclear. What are the dependences and how have they been inferred? It is frustrating to the reader to be told to go elsewhere for definition of EI23 and EI23 Bin but to be provided with details based on knowing what these concepts are, such as “EI23 Bi n has integer values of 1 through 7...” These concepts and terms should be defined, developed, explained, etc., in a methods chapter prior to producing results based on these. The paragraph introduces, perhaps for the first time, the term “running loss emi ssions,” without definition. If EI23 Bin is central to the methods and interpretation, it is simply unacceptable to push it to an appendix and to give such short and uninformative treatment to it in the main body of the
report.

[3] Page 1

- 1. The first s entence refers to ‘further developing’ something that has not yet been defined in this report. Please, hire a technical editor and have them go through this report very carefully. The first line is poorly written, and the report that follows is also very poorly

written.

[4] Page 1

- 2 “the real investigation in this study happens in...” this kind of colloquial writing has no place in a formal technical report by what is supposed to be one of the top environmental engineering consulting firms in the country to the Federal agency charged withPage 20 quantifying and regulating air quality. This report needs to be taken more seriously by the
authors.

[5] Background Chapter: this chapter is plagued with undefined jargon, lack of clarity of concepts, and is poorly orga nized. It is very qualitative and vague and provides little to no insight on the topics being addressed.

[ 6 ] “These two RSDs were measured on the same RSD instrument as the Selection RSDs.” This sentence is extremely sloppy, using the term “RSD” where the concept of a ‘remote sensing
measurement’ should be used instead.

[ 7 ] How does a vehicle “receive” an “RSD”? I have done measurements with an RSD, and I
have never seen a vehicle receive an RSD.

[8 ] Table 4

- 2: terms PSHED and RSD in caption should be spelled out. All nomenclature in column headers need to be properly defined

– e.g., use footnotes. Is RSD temperature the ambient temperature at the date and time of the measurement?

[ 9 ] Figure 4

- 1 needs better formatting. Should use a much larger font size for the numbers on the axes, and consider using scientific notation rather than decimals if showing a log scale. In the caption, spell out PSHED. What is “RSD EI23”?

[ 10 ] Table 4

- 3 is hardly a table and is not formatted well. Add a row for percentages of total to help in the interpretation. Please change the terminology

– e.g., ‘Measurement RSDs” (should be Remote Sensing Measurements).

[ 11 ] Table 4

- 4 the term “high PSHEDs” is unacceptable. The intended meaning appears to be “high PSHED measurement” “High

- PSHED Definition” should be “High PSHED Measurement
threshold” or criterion.

[ 12 ] What is ‘de

- stratifications’?

[ 13 ] “these Selection RSDs can be used to de

- stratify the stratified set and provide an estimate of the high

- PSHED fractio n of the fleet...” given the lack of clear definition of these terms, and the sloppy use of terminology, this sentence is unclear.

[ 14 ] ‘is not an unbiased’

– why not say ‘is a potentially biased’... positive statements are always more clear than negative st atements.

[ 15 ] Page 4

- 23: “For the RSD to be useful...” should be ‘for the remote sensing measurement to be useful...” why is model year important? Earlier, a note was made that model year was not part of the EI23 binning method.

[16 ] Table 4

- 5. [T] he ter m “Selection RSD” needs to be changed... e.g., “screening remote sensing measurement”? But the table is actually of EI23 bins and model year groups, not screening remote sensing measurements. Thus, the caption is not consistent with the content
of the tabl e.Page 21 [ 17 ] Page 4

- 24 “we will get started...” might be okay for a presentation but this is not how a technical report should be worded. Try reading aloud the first sentence of the last paragraph on page 4

- 24. It needs to be rewritten. Aside from being a ru n

- on sentence, it is awkward, contains repetitive points and yet is not very clear.

[ 1 8 ] Page 4

- 25: N h is defined in Appendix B but is given a lower case symbol (n h ). To avoid confusion and ambiguity, use consistent mathematical nomenclature. “Fraction of elevated PSHEDs” is given the symbol p h , which is defined in Appendix B as the “probability”... this is inconsistent. Either it is a frequency or it is a probability

- choose one and use the concept consistently. The standard error of fraction of eleva ted PHEDs is given in Table 4

- 6 based on a definition involving s h and N h , but this definition is not given in Appendix B (it should be).

[ 1 9 ] Page 4

- 27. The last sentence of the first paragraph is unclear. Rewrite. Create a flow diagram or show an a lgorithm to make this more clear.

[ 20 ] “It is important to understand that” should be deleted. “It... that” statements are passive
and contain no information.

[ 2 1 ] “jumps around”

– this kind of informal writing needs to be expunged from this report.

Fu jita: [1] P. 4

- 1, 2 nd paragraph, line 13: Rather than “accuracy”, “representativeness” may be more appropriate in this context.

[2] P. 4

- 3, 1 st paragraph, last two sentences: States that influence of variability of hot

- soak
emissions will be discussed l ater in the section. This discussion appears to be missing.

[3] P. 4

- 3, 2 nd full paragraph: References to “not simulated exhaust” and “natural exhaust” in the last two sentences are confusing.

[4] P.4

- 11, Table 4

- 2. VDF is not defined anywhere in the rep ort.

Knoll: The last sentence in Section 4.4 appears to be the beginning of an incomplete paragraph. I

expected further explanation or evaluation of how the EI23 bins are independent of model year groups. Did some additional text get inadvertently dro pped from this section?

3.3.2 Organization of the Report

Frey: [ 1 ] Aside from the poor writing, the organization of this report should be reconsidered.

Methods and results appear to be mixed together. A good technical report will have a chapter devote d to methods, organized in a manner consistent with the order in which the methods are used later in the report. Furthermore, this report tends to have too much of ‘here’s what we did’ without first introducing the purpose, key concepts, or basis/foundati on.Page 22 [2] A technical report should have the following elements:

Introduction

o states the challenge, problem, issue being addressed,

o establishes the need for new work

o clearly states the objectives of the work (note: objectives are not a list of tasks

– they relate to the purpose of the work) Background: Survey of relevant prior work, if needed. Also, a brief review of the types of evaporative emissions and factors to which they are sensitive is needed. For example, evaporative emissions are sensitive to ambient temperature.
Methods

o For each major component of the analysis, state the following:

 Overall purpose

 Basic concept

 Empirical or theoretical basis established in prior work (with citations)

o Provide sufficient information regarding the methods so that someone else could reproduce the work

– include definitions of key terms, variables, equations, algorithms, and so on

o Examples of content for this chapter (illustrative)

 Schematic of the vehicle path through the various RSDs and PSHED

 Methods A and B for estimating plume concentrations from remote sensing

measurements

 EI23 definition and definition of EI23 bins

 Approach to ‘stratification’
Results

o Results could be organized into more than one chapter if the subject matter is too much for one chapter

o Re sults should include a clearly summary of all input data and assumptions

o Results obtained should be from application of methods described in the methods chapter.

o Results should be appropriately interpreted
Conclusions

o What are the key findings that are rel ated to the objectives stated in Chapter 1?

o What are the key conclusions that are related to the objectives stated in Chapter 1?

o What are the key recommendations that are related to the objectives stated in Chapter 1?

[ 3 ] Background Chapter: this chapter is plagued with undefined jargon, lack of clarity of concepts, and is poorly organized. It is very qualitative and vague and provides little to no insight on the topics being addressed. Examples of content missing from this report include a
brief review of the types of evaporative emissions, factors to which such emissions are sensitive, the SHED measurement approach, how PSHED works, what is remote sensing, and how can remote sensing be used to infer information about evaporative emissions. What
does th e RSD actually measure that is representative of evaporative emissions, and is this similar to what is measured in PSHED? Why is there an expectation that there should be agreement between evaporative emissions inferred from RSD measurements versus those inferred from PSHEDS? Are they measuring the same processes under similar conditions? How might they differ?Page 23 [4] T he background chapter should be followed by a new chapter 3 that provides an overview of the methods used in this report, including a schema tic of the Ken Caryl IM station, the specific instruments deployed, the analysis methods used, etc. Material that is now in Appendix A and B should be rewritten into the methods chapter.

[ 5 ] The current Chapter 3 should be rewritten as “Assessment of Con cordance Between Portable and Fixed Location Evaporative Emissions Measurements.” This chapter needs technical editing. The basic information is useful and interesting. The technical analysis should include quantification of the statistical significance of each parameter in the regression equation, the standard error of the estimate, the distribution of the residuals, a normality check for the residuals, the coefficient of determination, and other basic information that would commonly be reported as diag nostic goodness

- of

- fit indicators when developing a regression model. To what extent are results such as in Figures 3

- 4
and 3

- 5 actually providing an indication of repeatability of the test

– are the conditions really the same in each test? If the repeat ability is really this poor, what are the implications for selecting a threshold for what constitutes a ‘high evap’ vehicle? It is more common to report 95% probability ranges, not 68% probability ranges

.

[ 6 ] Chapter 4: A schematic of the Ken Caryl stati on is needed to illustrate what is meant by the “driveway RSD unit” and “Measurement RSDs”

[ 7 ] A table prior to Table 4

- 5 would be more useful... i.e. distribution of vehicles by model year groups and EI23 bins for the selected (stratified?) vehicles.

[ 8 ] The first paragraph in Section 4.4 is unclear and is hampered by repeated use of terms that
are not well

- defined. Methods for stratification and de

- stratification should be in a prior methods chapter.

[ 9 ] Page 4

- 25: The Appendix B should be part of a me thods chapter given earlier in this report (could be Chapter 3).

[ 10 ] Chapter 5: The purpose of Chapter 5 is unclear. Is this meant to be a conclusions chapter? A summary chapter? A results chapter?

The lead paragraph here is probably the most cohe rent statement of the objective of

t his report. Such a statement is needed in the introduction.

The second paragraph is not useful because it is based on evidence not provided in earlier parts of the report.

The third paragraph is awkward and overly did actic. One can make the point, for example, that the use of EI23 as an indicator of evaporative emissions was explored in this work, and state the findings, conclusions, and recommendations accruing from this work. Subsequently, a recommendation can be m ade that the existing data could be analyzed using other indicators for the purpose of evaluating whether other indicators might be better than EI23. Whether ‘any evap index’ can be used depends on what variables are critical to an ‘evap index’ and whethe r they were all measured during the study at the Ken Caryl IM station. Since the report lacks even a basic overview of factorsPage 24 that lead to evaporative emissions, it is not clear as to whether all useful factors have been quantified to support development of ‘any’ evap index.

The paragraph at the bottom of page 5

- 1 is sufficiently cryptic as to be useless to anyone but those involved in the data collection or project management effort. It is not very clear as to what point is being made here.

Page 5

- 2 “to measure the RSDs”

– this makes no sense. RSDs are devices that make measurement. Why would one make a measurement on the RSD itself?

The intent of the paragraph on “RSDs of the Denver fleet” is unclear. Perhaps this is a
recommendation to calculate EI23 for a wider set of vehicles and use the Ken Caryl IM station data for fraction of high emitters to estimate a fraction of high emitters for the larger fleet. If that is the case, the intent is unclear.

Last paragraph on page 5

- 2

– seems to be intro ducing a lot of new information but in an unclear manner such that the point(s) here are unclear.

Fujita: [1] It would be helpful in Section 2 (Background) to state how the results of this study and

similar future studies will be used in the MOVES model. Should be specific enough to identify the relevant algorithms and inputs.

[2] The report does not include a summary of other testing

– modified California Method (olfactory, visual and electronic HC sniffer examination of various vehicle components). If this information is summarized elsewhere, it should be references and a brief summary of the finding should be included within this report.

[3] P.4

- 4, 1 st full paragraph, last two sentences: The reason for selecting Method B is difficult
to understand wi thout prior knowledge that EI23 is based on residuals of the linear regression. This is only explained in Appendix A. It should be mentioned briefly in the Section 4.2 for clarity.

[4] P. A

- 2: Add a description of the origin of the constants used in equ ations shown at the bottom of the page. Explain how this reduces dependence of EI23 on exhaust HC

concentrations.

Knoll: [1] Elsewhere in the literature, estimates are made providing comparison of PSHED results

with EPA’s Tier 2 requirements for evap orative emissions. 1 It would be helpful to include that
here for context.

[2] On page 3

- 12, the statistical analysis leading to the conclusions that “repeated SHED hot

soak measurements for a vehicle would fall between 40% (=1/2.51) and 251% of the vehic le’s average (characteristic) hot

- soak value 68% of the time” should include a relevant source

citation.

1 1 “Evaluation of Evaporative Leaks using RSD and Inventory Implications,” D. Hawkins, C. Hart, C. Fulper, J. Warila, D. Brzezinski, et al., Presented at the 19 th Annual Inter national Emission Inventory Conference, San Antonio, TX, Sept 27

- 30, 2010.Page 25



### 4. References

Eastern Research Group , Inc. Estimates of the Fraction of the Fleet with High Evaporative Emissions based on the Ken Caryl Station (Denv er, Colorado) Field Stud y ; Report Version 6. 2011

.

Eastern Research Group, Inc. Investigation of Techniques for High Evaporative Emissions Vehicle Detection: Denver Summer 2008 Pilot Study at Lipan Street Station; Report Version 4 . 2009.Page 26 

### Appendix A: Res umes of Peer Reviewers

H. C h r i s t o ph e r F r e y

h tt p : //www4

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. e du /~ f r e y/
f r e y @ n c s u
. e d u ( 919) 515

- 1155

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. D

. , E n g i n ee r i n g a n d P u b li c P o li c y , C a r n e g i e M e ll o n U n i v e r s it y , P i tt s b u r g h

, P A

, M a y 1991.

M a s t e r o f E n g i n ee r i n g, M ec h a n i ca l E n g i n ee r i n g, C a r n e g i e M e ll o n U n i v e r s i t y , P i tt s b u r g h

, P A

, M a y 1987.

B

. S

. , M ec h a n i ca l E n g i n ee r i n g, U n i v e r s it y o f V i r g i n i a , C h a r l ott e s v ill e , V A

, M a y 1985.

P r o f e ss io n al E x p e r

i e n ce

A ug 04

– p r e s e n t P r o f

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e n t o f C i v il

, C o n s t r u c t i o n , a n d E nv i r o n m e n t a l E n g i n ee r i n g, N o r th C a r olina State Uni ve rs it

y , R a l e i g h

, NC

A ug 06

– A ug 07 S a bb a t i ca l : E x p o s u r e M o d e li n g A d v i s o r , N a t i o n a l E x p o s u r e R e s ea r ch

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. S

. E nv i

r o n m e n t a l P r ot ec t i o n A g e n c y , R e s ea r c h Tr i a n g l e P a r k, N C.

J ul 99

– J ul 04 A ss o c i a t e P r o f e ss o r , D e p a r t m

e n t o f C i v i l E n g i n ee r i n g, N o r th C a r olina State
Uni ve rs it y , R a l e i g h

, NC

J a n 94

- J un 99 A ss i s t a n t P r o f e ss o r , D e p a r t m

e n t o f C i v i l E n g i n ee r i n g, N o r th C a r olina State
Uni ve rs it y , R a l e i g h

, NC

J un 91

- D e c 93 R e s ea r ch A ss o c i a t e ( R e s ea r c h F ac u l t y )

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- 970

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, P ro cee d i ngs, 103 r d Annual C on

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- 946

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, P ro cee d i ngs, 103 r

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- 306

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- 328

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- 2005. N A R S T O i s a t r il a t e r a l C a n a d i a n , U

. S

. , a n d M e x i ca n o r g a n i za t i o n

. ( f ) I nv it e d m

e m b e r o f o r g a n i z i n g c o mmi tt ee , G e r m a n

- A m e r i ca n F r o n t i e r s o f
E n g i n ee r i n g s y

m p o s i um f o r M a y 2005, N a t i o n a l A ca d e m y o f E n g i n ee r i n g

( g) I nv it e d L ea d A u t h o r , I n t e r g o v e r n m e n t a l P a n e l o n C lim a t e C h a n ge (I P CC )

, R e v i s i o n s t o e x i s t i n g gu i d a n c e o n u n ce r t a i n t y a n a l y s i s o f

g r ee nh o u s e g as e mi ss i o n s

. A tt e n d e d l ea d a u t h o r m ee t i n gs i n O s l o , N o r w a y , M a y 4

- 6, 2004, M a n il a , t h e P h ili pp i n e s J a n u a r y 11

- 13, 2005, a n d
S y d n e y , A u s t r a li a , D ece m

b e r 15

- 17, 2005.

( h ) I nv it e d p a r t i c i

p a n t i n W o r l d H ea l

t h O r g a n i za t i o n ( W HO) e ff o r t t o d e v e l o p i n t e r n a t i o n a l gu i d a n c e o n p r o b a b i li s t i c e x p o s u r e a ss e ss m e n t

, 2005

- 2007. M o s t r ece n t m ee t i n g w a s i n M a r c h 2007 i n B r a d f o r d,
E n g l a n d.

( i ) I nv it e d p a r t i c i

p a n t

, N A R S T O M u l

t i

- p o ll u t a n t a i r qu a li t y m a n a g e m

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, 2007. N A R S T O i s a t r il a t e r a l C a n a d i a n , U

. S

. , a n d M e x i can

o r g a n i za t i o n

. A tt e n d e d k i c k

- o f f m ee t i n g i n R T P

, NC J a n u a r y 9

- 10,Page 72 2007. W il l a tt e n d ec o l o g i ca l e ff ec t s w o r k i n g g r o up m

ee t i n g i n B u r li n g to n , V T

, A

p r i l 12

- 13, 2007.

( j ) C o

- o r g a n i ze r o f I n t e r n a t i o n a l S e mi n a r o n Tr a n s p o r t a t i o n a n d I m p ac t s , M a r ch 6, 2008, L

i s b o n , P o r t ug a l

. ( k) F o u n d i n g m

e m b e r o f c o r e g r o up o f t h e L u s o

- A m e r i ca n Tr a n s p o r t a t i o n I m p ac t S t ud i e s G r o up ( L A TI S

- G )

, f o r m e d o n M a r c h 7, 2008 i n L i s b o n , P o r t ug a l

.Page 73

ERIC M. FUJITA Research Professor Division of Atmospheric Sciences
Desert Research Institute University and Community College System of Nevada

Education

D.Env. Environmental Science 1992 University of California, Los Angeles and Engineering
M.S. Organic Chemistry 1976 California State University, Los Angeles
B.S. Chemistry 1973 University of Califor nia, Los Angeles

Experience

Dr. Fujita has over 27 years of experience in managing and conducting air quality studies. He is the principal author of the field study plans for the 2000 Central California Ozone Study and 1997 Southern California Ozone Stu dy (SCOS97

- NARSTO). His research interests include chemical characterization of emission sources, reconciliation of emission inventory estimates for VOC and PM with ambient measurements, and measurement and characterization of exposure to
toxic air contami nants. Dr. Fujita performed source apportionment analysis of fine particles in Colorado’s Northern Front Range, California’s South Coast Air Basin and San Francisco Bay Area, Phoenix, and Bangkok Thailand. Current research includes quantifying the relative contribution of gasoline and diesel exhaust to ambient PM and measuring air toxic exposures from mobile sources. Dr. Fujita also performed volatile organic compound source apportionment studies for the 1987 Southern California Air Quality Study (SCAQS), 1 990 San Joaquin Valley Air Quality Study (SJVAQS), 1993 Coastal Oxidant Assessment for Southeast Texas (COAST), 1995 Boston and Los Angeles Study, 1996 Phoenix Ozone Study, NARSTO

- Northeast 1995 Summer Ozone Study, 1995/96 Washington Ozone Transport Study, 1996 El Paso/Juarez Ozone Study, and 1998 Central Texas On

- Road Hydrocarbon Study. He has conducting similar studies in Houston and Mexicali, Mexico. Dr. Fujita also coordinated laboratory comparisons of VOC measurements during the SCOS97

- NARTSO, COAST a nd NARSTO

- Northeast ozone studies.

Prior to coming to DRI, Dr. Fujita was an Air Pollution Research Specialist for the Research Division of the California Air Resources Board where he initiated and managed extramural research in emission inventory develo pment, air quality measurements, and atmospheric processes. These studies included developing emission factors for mobile and stationary sources and assessing the effectiveness of emission control measures. Other studies included examining gas and aeroso l measurement methods and characterization of organic compounds in ambient air
and emission sources.

Professional Experience

2000

- Present Research Professor, Division of Atmospheric Sciences, Desert Research Institute,

Reno, NV.Page 74

2001 Interim Executive D irector, Division of Atmospheric Sciences, Desert Research

Institute, Reno, NV.

1996

- 2000 Associate Research Professor, Energy and Environmental Engineering Center,

Desert Research Institute, Reno, NV.

1993

- 1996 Assistant Research Professor, Energy and E nvironmental Engineering Center,

Desert Research Institute, Reno, NV.

1987

- 1992 Air Pollution Research Specialist, Atmospheric Processes Research Section,

Research Division, California Air Resources Board, Sacramento, California.

1983

- 1987 Air Pollution Research Specialist, Acid Deposition and Aerosol Research Section,

Research Division, California Air Resources Board, Sacramento, CA.

1979

- 1983 Air Pollution Research Specialist, Emission Control Technology Research

Section, Research Division, California Air Resources Board, Sacramento, CA.

1978

- 1979 Associate Air Pollution Specialist, Chemical Strategy Development Section,

Stationary Source Division, California Air Resources Board, Sacramento, CA.

1975

- 1977 Graduate Student Assistant, Aerosol Studies Se ction, Research Division,

California Air Resources Board, El Monte, CA.

Memberships

Air and Waste Management Association American Geophysical Union
American Association for Aerosol Research

Committees and Offices

Member of the National Academy of Scien ces National Research Council/Transportation Research Board study committee to evaluate the Congestion Mitigation and Air Quality Improvement (CMAQ) Program from October, 1999 to April, 2002. Chairman of the Intersociety Subcommittee #4 on Carbon and Hydro carbon Compounds Coordinating Research Council's Air Pollution Research Advisory Committee Technical Program Committee and editor of the proceedings for the Southern California Air Quality Study Data Analysis Conference

Professional Activities Invited pre sentation on Mobile Source Emission and Air Quality Past Present and Future to the staff of the California Air Resources Board, Sacramento CA, March 2, 2011. Invited presentation on Mobile Source Emission and Air Quality Past Present and Future to the
staf f of the Bay Area Air Quality Management District, San Francisco, CA, February 28,
2011.Page 75

Invited presentation on Inventory of Pollutant Emissions in the United States at the Chilean National Center for the Environment (Centro Nacional de Medio Ambiente, CE NMA): Santiago Chile, October 12, 2010. Invited presentation on Need to Reconsider Future Control Strategies for Reducing Ozone Levels in California. at the Coalition for Clean Air Brainstorming Session, Sacramento, CA, August 17, 2010. Invited presen tation on Ozone Trends in California’s South Coast Air Basin. to the staff of the Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC, June 29, 2010. Invited presentation on Mobile Source Emissions and Air Quality in California’s South Coast Air Basin Past, Present and Future at a workshop organized by the Chilean National Center for the Environment (Centro Nacional de Medio Ambiente, CENMA), Santiago Chile, June 2010. Professional Development Cours e on Recent Advances in Measurement of On

- Road Motor Vehicle Emission Factors and Composition Profiles at the 2010 AWMA International Specialty Conference in Xian, China, May 1

- 14, 2010. Invited presentation at the Integrated Program on Urban, Regional and Global Air Pollution, Workshop on Mexico Emissions Inventory, Mexico City , February 25

- 26, 2003 . Invited presentation at Health Effects Institute Workshop to Improve Estimates of Diesel and Other Emissions for Epidemiologic Studies Baltimore, MD, Decemb er 4

- 6, 2002 Invited presentation to the National Research Council Committee on Air Quality Management in the United States in Denver, CO on July 18, 2001. Contributing author in the Encyclopedia of Environmetrics (2001), A. H. El

- Shaarawi and W.W. Piegors ch, Editors. John Wiley and Sons Ltd. United Kingdom Invited presentation at the Office of Environmental Health Hazard Assessment’s Scientific Meeting on Approaches to Assessing Health Impacts of Gasoline

- Related Exposures in California

- “Ambient Apportio nment of Toxic Air Contaminants from Gasoline

Powered On

- Road Vehicles” in Oakland, CA June 26

- 27, 2000 Invited participant at the Centre for Science and Environment’s workshop to develop an air quality index for Delhi, India and review current air quality monitoring programs in Delhi, India on June 6

- 8, 2000. Invited presentation at the Society of Toxicology Workshop on “What You’ve Always Wanted to Know about Airborne Particulate Matter, but Were Afraid to Ask” in Philadelphia, PA
on March 19

- 23, 2000.
Re spondent at the Health Effects Institute Workshop on Mobile Source Air Toxics: Exposure and Risk in Washington, DC on February 8, 2000. Invited presentation at the California Air Resources Boards workshop on “Air Pollution Health Effects: Data Gaps and Imm ediate Research Needs” in Sacramento, CA on July 29

- 30, 1999. Invited presentation at the 1999 Urban Air Toxics Summer Symposium at Dedham, MA on July
8

- 10, 1999 on HAPs monitoring data. Invited presentation to the National Research Council Committee to Re view EPA’s Mobile Source Emission Factor (MOBILE) Model in Irvine, CA on March 4, 1999. Invited presentation to the Air Quality Planning and Assessment Division of the Texas Natural Resource Conservation Commission in Austin, TX on July 27, 1998 on the Nor thern Front Range Air Quality Study.Page 76

Invited presentation at the Western States Air Resources (WESTAR) Council’s PM2.5 Emissions Inventory Workshop held in Reno on July 22 and 23, 1998. Served on expert panel for the PM2.5 Monitoring Forum held in Sacramen to on March 17, 1998 by the California Air Resources Board. Invited presentation at the meeting of the U.S./Mexico Air Quality Workgroup in San Diego on October 16, 1997 on apportionment of ambient hydrocarbon in Paso del Norte region. Invited presentation in Washington D.C. on October 16, 1997 to the Federal Advisory Committee Act (FACA) Subcommittees on Modeling and In

- Use Vehicle Deterioration on the use of ambient data to evaluate emission inventories. Invited presentation at the Cascadia Tropospheric O zone Peer Review Meeting in Seattle, WA. on September 9, 1997 on apportionment of volatile organic compounds in western Washington. Reviewer of U.S. EPA Internal Research Proposals. Vice Chair, Session 15P, 1995 A&WMA 88th Annual Meeting, San Antonio, TX
R eviewer of the North American Strategy for Tropospheric Ozone Invited reviewer of EPA's Western Conifer Research Cooperative's Study the Effects of Acid Deposition on Western Forests (1986

- 87) Invited reviewer of the National Acid Precipitation Assessment Program National Acid Deposition Monitoring Program

Publications

Pine, S. and E. Fujita (1977). Ylide Autoxidation During the Stevens Rearrangement. J. Organic Chemistry, 42, 1460.

Fujita, E. and B. Croes (1990). Formaldehyde Emissions in the South Coas t Air Basin Derived from Ambient Measurements. In Transactions, Tropospheric Ozone and the Environment, R.L. Berglund, D.R. Lawson and D.J. McKee, eds. Air & Waste Management Association, Pittsburgh, PA, pp. 717

- 739.

Grosjean, D., E. Tuazon and E. Fujita (1990). Ambient Formic Acid in Southern California Air: A Comparison of Two Methods, Fourier Transform Infrared Spectroscopy and Alkaline Trap

- Liquid Chromatography with UV Detection. Environ. Sci. Technol., 24, 144.

Fujita, E., B. Croes, C. Bennett, D. L awson, F. Lurmann and H. Main (1992). Comparison of Emission Inventory and Ambient Concentration Ratios of CO, NMOG, and NOx in California's South Coast Air Basin. J. Air Waste Manage. Assoc., 42, 264.

Chow, J.C., J.G. Watson, E.M. Fujita, Z. Lu, D.R. Law son and L.L. Ashbaugh (1993). Temporal and Spatial Variations of PM2.5 and PM10 Aerosol in the Southern California Air Quality Study. Submitted to J. Exposure Anal. Environ. Epidemiology.

Fujita, E.M., editor (1993). Proceedings of the SCAQS Data Analysis Conference. Air & Waste Management Association, Pittsburgh, PA.Page 77

Fung, K., M. Porter, D. Fitz and E.M. Fujita (1993). Examination of Factors Affecting the Measurement of Hydrocarbons and Carbonyl Compounds for the Collaborative SJVAQS/AUSPEX Program. In P lanning Air Quality Measurement and Modeling Studies: A Perspective Through SJVAQS/AUSPEX, P. Solomon, ed., Air & Waste Management Association, Pittsburgh, PA.

Chow, J.C., E.M. Fujita, J.G. Watson, Z. Lu, D.R. Lawson and L.L. Ashbaugh (1994). Evaluation o f Filter

- Based Aerosol Measurements During the 1987 Southern California Air Quality Study. Environ. Monitor. Assess. 30, 49

- 80.

Chow, J.C., J.G. Watson, E.M. Fujita, Z. Lu, D.R. Lawson and L.L. Ashbaugh (1994). Temporal and Spatial Variations of PM2.5 an d PM10 Aerosol in the Southern California Air Quality Study. Atmos. Environ., 28, 2061

- 2080.

Fujita, E.M., D.R. Goff, D.R. Lawson, A. Barnett, J.H. Price, J. Gibich, K.W. Rozacky, C.L. Martin, W.A. Lonneman, S.D. Hoyt, R.A. Rasmussen, W.L. Crow and L.D. Ogle (1994). Interlaboratory Comparison for Analysis of Hydrocarbons During the Coastal Oxidant Assessment for Southeast Texas (COAST) Project. In Proceedings of the 1994 U.S. EPA/A&WMA International Symposium on Measurement of Toxic and Related Air
Pollu tants, Durham, NC, 2

- 6 May 1994, Air & Waste Management Association, Pittsburgh, PA, pp. 173

- 183.

Fujita, E.M., J.G. Watson, J.C. Chow and Z. Lu (1994). Validation of the Chemical Mass Balance Receptor Model Applied to Hydrocarbon Source Apportionment in the Southern California Air Quality Study. Environ. Sci. Technol., 28, 1633

- 1649.

Fung, K., M. Porter, D. Fitz and E.M. Fujita (1994). Evaluation and Development of Methods for the Measurement of Hydrocarbons and Carbonyl Compounds. In Planning and Mana ging Regional Air Quality Modeling and Measurement Studies, P.A. Solomon, ed. Lewis Publishers, Boca Raton, FL, pp. 711

- 736.

Gertler, A.W., E.M. Fujita, W.R. Pierson and D.N. Wittorff (1994). Apportionment of VOC Tailpipe vs Non

- Tailpipe Emissions in the Fort McHenry and Tuscarora Tunnels. In Proceedings of an International Specialty Conference on the Emission Inventory: Perception and Reality, Pasadena, California, 18

- 20 October 1993, W.R. Oliver, ed. Air & Waste Management Association, Pittsburgh, PA, 19 94, pp. 28

- 38.

Watson, J.G., J.C. Chow, E. Fujita, Z. Lu, S.L. Heisler and T. Moore (1994). Wintertime Source Contributions to Light Extinction in Tuscon, AZ. In Proceedings of the International Specialty Conference on Aerosols and Atmospheric Optics: R adiative Balance and Visual Air Quality, Snowbird, UT, 26

- 30 September 1994, Air & Waste Management Association, Pittsburgh, PA, p. 1187.

Watson, J.G., J.C. Chow, Z. Lu, E.M. Fujita, D.H. Lowenthal, D.R. Lawson and L.L. Ashbaugh (1994). Chemical Mass Bala nce Source Apportionment of PM10 During the Southern California Air Quality Study. Aerosol Sci. Technol., 21, 1

- 36.Page 78

Zielinska, B. and E.M. Fujita (1994). The Composition and Concentration of Hydrocarbons in the Range of C2 to C18 in Downtown Los Angeles, C A. Res. Chem. Intermed., 20, 321

- 334.

Zielinska, B. and E.M. Fujita (1994). Organic Gas Sampling. In Environmental Sampling for Trace Analysis, B. Markert, ed. VCH, Weinheim, Germany, 7, 163

- 184.

Chow, J.C., D. Fairley, J.G. Watson, R. De Mandel, E.M. Fu jita, D.H. Lowenthal, Z. Lu, C.A. Frazier, G. Long and J. Cordova (1995). Source Apportionment of Wintertime PM10 at San Jose, CA. J. Environ. Engineering, 21, 378

- 387.

Fujita, E.M., J.G. Watson, J.C. Chow and K.L. Magliano (1995). Receptor Model and E missions Inventory Source Apportionments of Nonmethane Organic Gases in California’s San Joaquin Valley and San Francisco Bay Area. Atmos. Environ., 29(21), 3019

- 3035.

Lawson, D.R., E.M. Fujita, J.R. Holmes, L.L. Ashbaugh and B.E. Croes (1995). The South ern California Air Quality Study: A Prototype for Collaborative Research. In Ozone: Science and Policy, M.O. Rodgers and P.A. Solomon, eds. Lewis Publishers, Chelsea, Michigan,
to be submitted.

Watson, J.G., J.C. Chow, E.M. Fujita, D.R. Lawson and D.L. Bl umenthal (1995). A Survey of Emissions, Meteorology, Chemical Transformations, and Data Sets Relevant to Receptor Modeling in Southern California. Submitted to Atmos. Environ.

Gertler, A.W., E.M. Fujita, W.R. Pierson and D.N. Wittorff (1996). Apportion ment of NMHC Tailpipe vs Non

- Tailpipe Emissions in the Fort McHenry and Tuscarora Mountain Tunnels. Atmos. Environ. 30, 2297

- 2305.

Harshfield, G., B. Zielinska, E.M. Fujita and J. Sagebiel (1996). Comparison of Tenax

- TA Data Versus Canister and Continuo us Gas Chromatographic Data for Gas

- Phase Hydrocarbons with Carbon Number >C8. Measurements of Toxic and Related Air Pollutants VIP

- 50, A&WMA, 109

- 118.

Keislar, R.E., J.B. Bowen, E.M. Fujita, D.R. Lawson and W.R. Pierson (1997). Effects of Oxygenated Fu els on Ambient Carbon Monoxide Concentrations in Provo, Utah, Int. J. of Vehicle Design, 18(3) (Special Issue), 1997.

Zielinska, B., E. Fujita, J. Sagebiel, G. Harshfield, E. Uberna, T. Hayes, and F. Keene (1998).
Arizona Hazardous Air Pollutants Monitor ing Program. J. Air Waste Manage. Assoc.

, 48: 1038

- 1050.

Watson, J., J.C. Chow, and E. Fujita (2001). Review of Volatile Organic Compound Source Apportionment by Chemical Mass Balance. Atmos. Environ . 35:1567

- 1584.Page 79

Apel, E., J. Calvert, D. Riemer, W. Pos, R. Zika, T. Kleindienst, W. Lonneman, K. Fung, E. Fujita, P. Shepson, and T. Starn (1998). Measurements Comparison of Oxygenated Volatile Organic Compounds at a Rural site During the 1995 SOS Nashville Intensive. J. Geophys. Res. , 98JD01753.

Apel, E., J. Calvert, J. Greenberg, D. Riemer, R. Zika, T. Kleindienst, W. Lonneman, K. Fung, and E. Fujita (1998). Generation and Validation of Oxygenated Volatile Organic Carbon Standards for the 1995 Southern Oxidants Study Nashville Intensive. J. Geophys. R es., in

press.

Pierson, W., E. Schorran, E. Fujita, J. Sagebiel, D. Lawson, and R. Tanner (1999). Assessment
of Non

- Tailpipe Hydrocarbon Emissions from Motor Vehicles. J. Air Waste Manage.
Assoc ., 49: 498

- 519.

McDonald, J. D., B. Zielinska, E.M. Fujit a, J.C. Sagebiel, J.C. Chow, and J.G. Watson (2000). Fine Particle and Gaseous Emission Rates from Residential Wood Combustion. Submitted to Environmental Science and Technology, 34: 2080

- 2091.

Watson, J.G., T. Zhu, J.C. Chow, J. Engelbrecht, E.M. Fujit a, and W.W. Wilson (2001). Receptor Models for Particulate Source Apportionment. Atmos. Environ. 35, 1567

- 1584.

Fujita E.M. (2001). Hydrocarbon Source Apportionment for the 1996 Paso del Norte Ozone Study. Science of the Total Environment 276, 171

- 184.

T he Committee’s final report entitled "Congestion Mitigation and Air Quality: A National Need for Local Experiments”, 2002. National Academy of Sciences National Research Council/Transportation Research Board study committee to evaluate the Congestion Mitig ation and Air Quality Improvement (CMAQ) Program.

McDonald, J. D., B. Zielinska, E.M. Fujita, J.C. Sagebiel, J.C. Chow, and J.G. Watson Jacob (2003). Emissions from Charbroiling and Grilling of Chicken and Beef. J. Air & Waste Manage. Assoc . 53: 185

- 194.

Rogers, C.F., J.C. Sagebiel, B. Zielinska, W. P. Arnott, E.M. Fujita, J.D. McDonald, J.B. Griggin, K. Kelly, D. Overacker, D. Wagner, J.S. Lighty, A. Srofim and G. Palmer (2003). Characterization of Submicron Exhaust Particles from Engines Operating
Witho ut Load on Diesel and JP

- 8 Fuels. Aerosol Sci. Technol. 37 :355

- 368.

Fujita, E.M., W.R. Stockwell, D.E. Campbell, and R.E. Keislar (2003). Evolution of the Magnitude and Spatial Extent of the Weekend Ozone Effect in California’s South Coast
Air Basin from 1981 to 2000. J. Air & Waste Manage. Assoc

. 53 :802

- 815

Fujita, E.M., D.E. Campbell, B. Zielinska, J.C. Sagebiel, J.L. Bowen, W. Goliff, W.R. Stockwell, and D.R. Lawson (2003). Diurnal and Weekday Variations in Source Contributions of Ozone Precursors in C alifornia’s South Coast Air Basin. J. Air & Waste Manage. Assoc

. 53 : 844

- 863.Page 80

Fujita, E.M., G. Harshfield, and L.H. Sheetz (2003). Performance Audits and Laboratory Comparisons for SCOS97

- NARSTO Measurements of Speciated Volatile Organic Compounds. Atmos. Environ. 37, Supplement No. 2, S135

- S147.

Zielinska, B and E.M. Fujita (2003). Characterization of Ambient Volatile Organic Compounds at the Western Boundary of the SCOS97

- NARSTO Modeling Domain. Atmos. Environ. 37, Supplement No. 2, S171

- S180.

Croes, B. E. and E.M Fujita, (2003). The 1997 Southern California Ozone Study (SCOS97

- NARSTO): Introduction and Perspective. Atmos. Environ. 37, Supplement No. 2, S3

- S26.

Rinehart, L.R., E,M. Fujita, J.C. Chow and B. Zielinska (2006). Spatial Distribution of PM2.5 Associated Organic Compounds in the San Joaquin Valley. Atmos. Environ. 40. 290

- 303.

Melvin Zeldin, Yushuo Chang, Thomas Christofk, David Campbell, Eric Fujita, and Richard Countess (2007). The Roseville Rail Yard Project: A Cooperative Program to Reduce Air
Toxics Risk. Environmental Manager , January 2007

Ceballos, D.M., B. Zielinska, J. Sagebiel and E.M. Fujita (2007) Characterization Of Solid Phase Micro Extraction And Gas Chromatography For The Analysis Of Gasoline Tracers In Different Microenvironme nts. J. Air Waste Manage. Assoc. 57 : 355

- 365.

Fujita, E.M., B. Zielinska, D.E. Campbell, W.P. Arnott, J. Sagebiel, L. Mazzoleni, J.C. Chow, N. P.A. Gabele, W. Crews, R. Snow, N. Clark, S. Wayne and D.R. Lawson (2007). Variations in speciated emissions fro m spark

- ignition and compression ignition motor vehicles in the California's South Coast Air Basin. J. Air Waste Manage. Assoc. 57 : 705

- 720.

Fujita, E. M., D. E. Campbell, W. P. Arnott, B. Zielinska (2007). Evaluations Of Source Apportionment Methods for Determining Contributions Of Gasoline and Diesel Exhaust to Ambient Carbonaceous Aerosols. J. Air Waste Manage. Assoc. 57 : 721

- 740.

Fulper, C.R., S. Kishan, R.W. Baldauf, M. Sabisch, J. Warila, E.M. Fujita, C. Scarbro1 W.C. Crews, R. Snow, P. Gabele, R. S antos, G. Tierney, and B. Cantrell (2010). Methods of Characterizing the Distribution of Exhaust Emissions from Light

- Duty, Gasoline

Powered Motor Vehicles in the U.S. Fleet. J. Air & Waste Manage. Assoc. 60:1376

- 1387.

Watson, J. G., J.C. Chow, L.

- W. A. C hen, D.H. Lowenthal, E.M. Fujita, H.D. Kuhns, D.A. Sodeman, D.E. Campbell, H. Moosmüller, D. Zhu and N. Motallebi (2011). Particulate Emission Factors for Mobile Fossil Fuel and Biomass Combustion Sources. STOTEN, in

press.Page 81

Zielinska, B., E. Fujita, W. Ol lison, D. Campbell, J. Sagebiel, P. Merritt and L. Smith (2011). Relationships of Attached Garage and Home Exposures to Fuel Type and Emission Levels of Garage Sources, Air Quality, Atmosphere and Health, in press

Mason, J. Brooks E.M. Fujita, D.E. Campb ell and B. Zielinska (2011): Evaluation of Passive Samplers for Assessment of Community Exposure to Toxic Air Contaminants and Related Pollutants, ES&T, in press

Fujita, E.M.; Campbell, D.E.; Zielinska, B.; Chow, J.C.; Lindhjem, C.E.; DenBleyker, A;
Bisho p, G.A; Schuchmann B.G.; Stedman, D.H.; Lawson, D.L. (2012). Comparison of the MOVES2010a, MOBILE6.2 and EMFAC2007 Mobile Source Emissions Models with On

- Road Traffic Tunnel and Remote Sensing Measurements. J. Air & Waste Manage. Assoc. 62:xxxx

- xxxx.

Pre sentations

Fujita, E. and J. Collins (1989). Quality Assurance for the Southern California Air Quality Study. Paper No. 89

- 111.5, presented at the 82nd Annual Meeting of the Air and Waste Management Association, Anaheim, CA, 25

- 30 June 1989.

Fujita, E. ( 1990). Volatile Organic Compound Measurements for SJVAQS/AUSPEX. Presented at the CARB/CSUF Symposium on the San Joaquin Valley Air Quality Study, Fresno, CA, 7

- 8 May 1990.

Fujita, E., B. Croes and F. Lurmann (1990). Comparisons of Ambient and Emission In ventory Data in the South Coast Air Basin. Presented at the CRC

- APRAC Vehicle Emission Modeling Workshop, Newport Beach, CA, 30

- 31 October 1990.

Ashbaugh, L., B. Croes, E. Fujita and D. Lawson (1990). Emission Characteristics of California's 1989 Random R oadside Survey. Presented at the 13th North American Motor Vehicle Emissions Control Conference, Tampa, FL, 11

- 14 December 1990.

Fung K., M. Porter, D. Fitz and E. Fujita (1991). Evaluation and Development of Methods for the Measurement of Hydrocarbons an d Carbonyl Compounds for the Collaborative SJVAQS/AUSPEX Program. Paper 91

- 72.4, presented at the 84th Annual Meeting of the Air and Waste Management Association, Vancouver, British Columbia, 16

- 21 June 1991.

Main, H., F. Lurmann and E. Fujita (1991). Ana lysis of Southern California Air Quality Study (SCAQS) NMOC Data: Spatial and Temporal Issues. Paper 91

- 66.10, presented at the 84th Annual Meeting of the Air and Waste Management Association, Vancouver, British Columbia, June 16

- 21, 1991.

Fujita, E., B. Croes, C. Bennett, D. Lawson, H. Main and F. Lurmann (1991). Comparison of Emission Estimates and Ambient Concentrations of CO, NMOC, and NOx in California's South Coast Air Basin. Presented at the International Specialty Conference on Emission Inventory Issues in the 1990's, Durham, NC, 9

- 12 September 1991.Page 82

Fujita, E. (1992). Evaluation of SCAQS Gas

- Phase Measurements. Presented at the Southern California Air Quality Study Data Analysis Conference, Los Angeles, CA, 21

- 23 July
1992.

Fujita, E. (1992). Tre nds in Emissions and Ambient Concentrations of CO, NMHC and NOX in the South Coast Air Basin. Presented at the Southern California Air Quality Study Data Analysis Conference, Los Angeles, CA, 21

- 23 July 1992.

Chow, J.C., J.G. Watson, E.M. Fujita, D.H. Low enthal, Z. Lu, C.A. Frazier, D. Fairley, R. De Mandel, G. Long and J. Cordova (1993). Results from the 1991

- 92 Pilot Study of Wintertime PM10 in the San Francisco Bay Area. Paper 93

- WA

- 75.05, presented at the Air & Waste Management Association 86th Annual Meeting, Denver, CO, 13

- 18 June 1993.

Fujita, E., J.G. Watson, J.C. Chow and K.L. Magliano (1993). Source Contributions to Volatile Organic Compounds in Central California During SJVAQS/AUSPEX. Paper No. 93

- OT3

- I.5, presented at the A&WMA International Sp ecialty Conference on Regional Photochemical Measurement and Modeling Studies, San Diego, CA, 8

- 12 November
1993.

Gertler, A.W., E.M. Fujita, W.R. Pierson and D.N. Wittorff (1993). Apportionment of VOC Tailpipe vs. Running and Resting Losses in Tuscarora and Fort McHenry Tunnels. Presented at the EPA/A&WMA International Conference on the Emission Inventory: Perception and Reality, Pasadena, CA, 18

- 20 October 1993.

Gertler, A.W., E.M. Fujita, W.R. Pierson and D.N. Wittorff (1993). Apportionment of NMHC
Tai lpipe vs. Non

- Tailpipe Emissions in Tuscarora and Fort McHenry Tunnels. Paper No.
93

- OT3

- P.2, presented at the A&WMA International Specialty Conference on Regional Photochemical Measurement and Modeling Studies, San Diego, CA, 8

- 12 November
1993.

Korc, M. E., L.R. Chinkin, P.T. Roberts, F.W. Lurmann, H.H. Main, E. Fujita and K. Magliano (1993). Reconciliation of Emission Inventory and Ambient Data: Current State of Knowledge and Implications for Photochemical Modeling. Paper No. 93

- OT3

- I.2, presented at the A&WMA International Specialty Conference on Regional Photochemical Measurement and Modeling Studies, San Diego, CA, 8

- 12 November
1993.

Lawson, D.R., E.M. Fujita, A.W. Gertler, R.L. Tanner and W.R. Pierson (1993). Mobile, Stationary and Area Source Emiss ion Research Needs and Policy Issues

— Where Do We Go from Here? Paper No. C1

- I.4, presented at the A&WMA International Specialty Conference on Regional Photochemical Measurement and Modeling Studies, San Diego, CA, 8

- 12 November 1993.Page 83

Lawson, D.R., E.M. Fu

jita, J.R. Holmes, L.L. Ashbaugh and B.E. Croes (1993). The Southern California Air Quality Study: A Prototype for Collaborative Research. Paper No. 93

- OT1

- I.3, presented at the A&WMA International Specialty Conference on Regional
Photochemical Measurement and Modeling Studies, San Diego, CA, 8

- 12 November
1993.

Fujita, E.M., D.R. Goff, D.R. Lawson, J.H. Price, J. Gibich, C.L. Martin, W.L. Lonneman, S.D. Hoyt, R.A. Rasmussen, W.L. Crow and L.D. Ogle (1994). Interlaboratory Comparison for Analysis of Hydroc arbons During the Coastal Oxidant Assessment for Southeast Texas (COAST) Project. Presented at the A&WMA International Symposium on Measurement of Toxic and Related Air Pollutants, Durham, NC, 2

- 6 May 1994.

Watson, J.G., J.C. Chow, E.M. Fujita, C.A. Fraz ier, Z. Lu, S.L. Heisler and C.T. Moore (1994). Aerosol Data Validation for the 1992

- 93 Tucson Urban Haze Study. Paper No. 94

- TA24.02, presented at the Air & Waste Management Association 87th Annual Meeting, Cincinnati, OH, 19

- 24 June 1994.

Watson, J.G., J.C. Chow, E. Fujita, Z. Lu, S.L. Heisler and T. Moore (1994). Wintertime Source Contributions to Light Extinction in Tucson, AZ. Presented at the A&WMA/AGU International Specialty Conference on Aerosols and Atmospheric Optics: Radiative
Balance and Visual Air Quality, Snowbird, UT, 26

- 30 September 1994.

Fujita, E.M. (1995) Evaluation of the Emission Inventory in the South Coast Air Basin. Presented at the Fifth CRC On

- Road Vehicle Emissions Workshop, San Diego, CA, April 1995.

Fujita, E.M. (1995). Ambie nt Versus Emission Inventory NMHC, CO, NOx Trends in the South Coast Air Basin (1987

- 1993). Paper 95

- RP113B.01, presented at the Air & Waste Management Association 88th Annual Meeting, San Antonio, TX, 18

- 23 June 1995.

Fujita, E.M., Z. Lu, J.H. Price, K. W. Rozacky, D. Brymer and J. Gibich (1995). Validation and Evaluation of the Coastal Oxidant Assessment for Southeast Texas (COAST) Volatile Organic Compound Data. Poster 95

- TP15P.01, presented at the Air & Waste Management Association 88th Annual Meetin g, San Antonio, TX, 18

- 23 June 1995.

Harshfield, G., B. Zielinska, E.M. Fujita and J.C. Sagebiel (1995). Comparison of Tenax

- TA Data Versus Canister and Continuous Gas Chromatographic Data for Gas

- Phase Hydrocarbons with Carbon Number >C8. Presented at the A&WMA/EPA International Symposium on Measurement of Toxic and Related Air Pollutants, Research Triangle Park, NC, 16

- 18 May 1995.

Zielinska, B., E.M. Fujita, J.C. Sagebiel, C. Fernandez, F. Keene, G. Monroy and J. Burchard (1995). Arizona Hazardous A ir Pollutants Monitoring Program. Paper 95

- WP82.05, presented at the Air & Waste Management Association 88th Annual Meeting, San Antonio, TX, 18

- 23 June 1995.Page 84

Zielinska, B., J.C. Sagebiel, W.R. Pierson, A.W. Gertler and E.M. Fujita (1995). Volatile Toxi c Organic Compounds Emitted from Motor Vehicles

– Diesel versus Spark Ignition. Presented at the Fourth International Congress on Toxic Combustion Byproducts, Berkeley, CA, 5

- 7 June 1995.

Fujita, E.M. (1996). Determination of Mobile Source Emission Sou rce Fraction Using Ambient Field Measurements. Presented at the Sixth CRC On

- Road Vehicle emissions workshop, San Diego, CA, March 18

- 20, 1996.

Fujita, E.M., W.A. Lonneman, A. Van Arsdale and A. Oi (1996). Narsto

- NE Hydrocarbon Laboratory Comparison. Pre sented at the A&WMA Conference and Courses: Measurement of Toxic and Related Air Pollutants, RTP, NC, May 7

- 9, 1996.

Fujita, E.M., Z. Lu, N.F. Robinson and J.G. Watson (1996). Application of Chemical Mass Balance Model to Coastal Oxidant Assessment for S outheast Texas Volatile Organic Compound Data. To be presented at the Air & Waste Management Association 89th Annual Meeting, Nashville, TN, June 23

- 28, 1996.

Keislar, R.E., J.L. Bowen, E.M. Fujita, D.R. Lawson and W.R. Pierson (1996). Effects of Oxygen ated Fuels on Ambient Carbon Monoxide Concentrations in Provo, Utah. Presented at the Sixth CRC On

- Road Vehicle Emissions Workshop, San Diego, CA, 18

- 20 March 1996.

Keislar, R.E., J.L. Bowen, E.M. Fujita, D.R. Lawson and W.R. Pierson (1996). Effect of
O xygenated Fuels on Ambient Carbon Monoxide Concentrations in Provo, Utah, U.S.A. Presented at the 3rd Symposium, Traffic Induced Air Pollution

- Emissions, Impact and Air Quality, Graz, Austria, 29

- 30 April 1996.

Keislar, R.E., J.L. Bowen, E.M. Fujita, D .R. Lawson and W.R. Pierson (1996). Effect of Oxygenated Fuels on Ambient Carbon Monoxide Concentrations in Provo, Utah. Paper
96

- WP89.07, presented at the Air & Waste Management Association 89th Annual Meeting, Nashville, TN, 23

- 28 June 1996.

Fujita, E .M., B. Zielinska, L.H. Sheetz, G. Harshfield, and E. Urberna (1996). Hydrocarbon and Carbonyl Audits for NARST

- Northeast 1996 Field Study. Presented at the First
NARSTO

- Northeast Data Analysis Symposium and Workshop, Norfolk, VA, 10

- 12 December, 1996.

Fujita, E.M., Z. Lu, L.H. Sheetz, G. Harshfield, and B. Zielinska (1997). Determination of Mobile Source Fraction Using Ambient Data. Presented at the Seventh CRC Mobile Source Emission Workshop, San Diego, CA, 9

- 11 April 1997.

Zielinska, B., G. Harshfi eld, E. Fujita, and J. Sagebiel (1997). Volatile Organic Compound Concentrations in the South Coast Air Basin (CA) during the Summers of 1995 and 1996. Presented at the A&WMA 90th Annual Meeting, Toronto, Ontario, Canada, 9

- 13 June 1997.Page 8 5

Fujita, E., J. S hire, G. Harshfield, E. Uberna, and B. Zielinska (1997). Performance Audits for Measurements of Carbonyl Compounds during the NARSTO

- Northeast 1996 Summer Ozone Study. Presented at the American Geophysical Union 1997 Fall Meeting, Sand Francisco, CA, 8

- 1 2 Dec. 1997

Fujita, E., T. Hayes, J. McDonald, J. Sagebiel, B. Zielinska, J.C. Chow, and J.G. Watson (1998). Source Apportionment of Ambient PM2.5 Carbon in the Northern Front Range of Colorado. Presented at the 8th CRC On

- Road Vehicle Emissions Works hop, San Diego, CA, 20

- 22 April, 1998.

Zielinska, B., E. Fujita, T. Hayes, J. Sagebiel, J.C. Chow, and J.G. Watson (1998). Development of the Mobile Source Chemical Composition Profiles for Application in the Source Attribution Study. Presented at the 8t h CRC On

- Road Vehicle Emissions Workshop, San Diego, CA, 20

- 22 April, 1998.

Hyde, P. and E. Fujita (1998). Evaluating VOC Inventories with Receptor Modeling and UAM Modeling. Presented at A&WMA 91st Annual Meeting & Exhibition, San Diego, CA,
14

- 18 June , 1998.

Fujita, E., J. McDonald, T. Hayes, B. Zielinska, J. Sagebiel, J.C. Chow, and J.G. Watson (1998). Northern Front Range Air Quality Study: Apportionment of Carbonaceous Particles. Presented at A&WMA 91st Annual Meeting & Exhibition, San Diego, CA , 14

- 18 June, 1998.

Fujita, E., J. Bowen, M. Green, H. Moosmuller (1998) The 1997 Southern California Ozone Study

- NARSTO: Quality Assurance and Data Management. Presented at A&WMA 91st Annual Meeting & Exhibition, San Diego, CA, 14

- 18 June, 1998.

Zieli nska, B., E. Uberna, E. Fujita, J. McDonald, and T. Hayes (1998). Northern Front Range Air Quality Study: The Analysis of Ambient Fine Particle Organic Matter. Presented at A&WMA 91st Annual Meeting & Exhibition, San Diego, CA, 14

- 18 June, 1998.

Fujita, E. and J.G. Watson (1998). Validation and Applications Protocol for Source Apportionment of Volatile Organic Compounds and Fine Particles. Presented at EPA/A&WMA 18th Symposium on Measurement of Toxic and Related Air Pollutants, Cary, NC, 1

- 3 September , 1998.

Fujita, E., T. Hayes, R. Keislar, W. Goliff, L. Sheetz, M. Keith, J. Sagebiel, and B. Zielinska, C. Harder, S. Torpey, D. Castro, L. Moon, R. Ramon, and E. Collins (1999). 1998 On

Road Hydrocarbon Study. Presented at the 9th CRC On

- Road Vehicle Emissions Workshop, San Diego, CA, 20

- 22 April, 1999.

Keislar, R., H. Moosmuller, F. Rogers, H. Kuhns, E. Fujita and J. Watson (1999). Measurement
of on

- road particulate matter emissions by LIDAR. Presented at the Ninth CRC On

- Road
Vehicle Emissions W orkshop, San Diego, CA, 20

- 22 April, 1999.Page 86

Fujita, E., (1999). Hydrocarbon source apportionment for the 1996 Paso del Norte Ozone Study. Presented at A&WMA 92nd Annual Meeting & Exhibition, St. Louis, MO, 20

- 24 June, 1999.

Fujita, E., R. Keislar, and W . Stockwell (2000). What do on

- road motor vehicle have to do with higher ozone on weekends in the South Coast Air Basin?. Presented at the 10th CRC On

Road Vehicle Emissions Workshop, San Diego, CA, 27

- 29 March, 2000.

Keislar, R., H. Moosmuller, C. Maz zoleni, H. Kuhns, V. Etyemezian, E. Fujita, and J. Watson (2000). Evaluation of Lidar Measurement of On

- Road Particulate Matter Emissions.. Presented at the 10th CRC On

- Road Vehicle Emissions Workshop, San Diego, CA, 27

- 29 March, 2000.

Arnott, P.W., C. F. Rogers, J. Sagebiel, B. Zielinska, E. Fujita, and H. Moosmuller (2000). Evaluation of Aerosol

- Bound PAHs and Elemental Carbon Aerosol in Diesel and Gasoline Vehicles. Presented at the 10th CRC On

- Road Vehicle Emissions Workshop, San Diego, CA, 27

- 29 March, 2000.

Fujita, E., (2000). Technical issues related to on

- road vehicle emissions. Presented at the 2 nd Annual Meeting of the Nevada Section of Air & Waste Management Association Conference on Air Quality Planning for Transportation Conformity and Sm oke Management in Reno, NV on May 19, 2000.

Zielinska, B., J. Sagebiel, J. Mc Donald, and E. Fujita (2000). Measurement of Diesel Emissions in Underground Gold Mines. Presented at the NARSTO 2000 Technical Symposium on Tropospheric Aerosols: Science and D ecisions in an International Community, Queretaro, Mexico, October 23

- 36, 2000.

Fujita, E., (2001). SCOS97

- NARSTO: Quality Assurance Issues. Presented at the SCOS97

- NARSTO Data Analysis Conference, Diamond Bar, CA February 13

- 15, 2001.

Fujita, E., (2001 ). Source Attribution of Ambient Hydrocarbons in the South Coast Air Basin. Presented at the SCOS97

- NARSTO Data Analysis Conference, Diamond Bar, CA February 13

- 15, 2001.

Fujita, E., R. Keislar, and W. Stockwell (2001). Why Ozone is Higher on Weekends in the South Coast Air Basin

– A 20

- Year Perspective. Presented at the SCOS97

- NARSTO Data Analysis Conference, Diamond Bar, CA February 13

- 15, 2001.

Fujita, E., (2001). Contributions of Motor Vehicles to Ambient Concentrations of PM 2.5

. Presented at the Worl d Truck Conference, Monterey, CA March 4

- 6, 2001.

Fujita, E., R. Keislar, and W. Stockwell (2001). Weekend/Weekday Ozone Observations in the South Coast Air Basin

– Phase 2 Field Study. Presented at the 11th CRC On

- Road Vehicle Emissions Workshop, San Diego, CA, 26

- 28 March, 2001.Page 87

Fujita, E.M. B. Zielinska, J.C. Sagebiel, J. Bowen, W.R. Stockwell, M. McDaniel, D.E. Campbell, T.H. Funk, D.Coe, H.H. Main, C.P. McDonald, L.R. Chinkin, P.T. Roberts, and D.R. Lawson (2001). OHVT Weekend/Weekday Ozone Study in the South Coast Air Basin, Presented at the 7th Diesel Engine Emission Reduction (DEER) Workshop, Portsmouth, VA August 5

- 9, 2001.

Fujita, E.M., (2002). Ambient Versus Emission Inventory Reconciliation in the South Coast Air Basin from1987 to 2000. Pre sented at the 12th CRC On

- Road Vehicle Emissions Workshop, San Diego, CA, 15

- 17 April, 2002.

Fujita, E.M., (2002). Ambient Versus Emission Inventory Reconciliation in the South Coast Air Basin from1987 to 2000. Presented at the 12th CRC On

- Road Vehicle Em issions Workshop, San Diego, CA, 15

- 17 April, 2002.

Fujita, E.M., W.R. Stockwell, D.E. Campbell, and D.R. Lawson (2002). OHVT Weekend/Weekday Ozone Study In The South Coast Air Basin. Presented at the 8th Diesel Engine Emission Reduction (DEER) Workshop, San Diego, CA, August 25

- 29,
2002.

Fujita, E.M. and B. Zielinska (2002). Diesel Signature Studies and Uncertainties. Presented at the HEI Workshop to Improve Estimates of Diesel and Other Emissions for Epidemiologic Studies Baltimore, MD, December 4

- 6, 20 02.

Fujita, E.M. (2003). Source Receptor Analysis for VOC and fine PM; Source Identification and Apportionment. Presented at the Integrated Program on Urban, Regional and Global Air Pollution, Workshop on Mexico Emissions Inventory, Mexico City , February 25

- 26,
2003 .

Fujita, E.M. (2003). On

- Road Vehicle Particulate Emissions, Chemical Characterization and Source Apportionment. Presented at the World Truck Conference, Monterey, California,
March 2

- 4, 2003.

Arnott, W.P., D. Campbell, E.M. Fujita, J.W. W alker, and H. Moosmüller (2003). Continuous Measurements of PM 2.5 and Black Carbon Mass: Gasoline/Diesel PM Split Study. Presented at the 13th CRC On

- Road Vehicle Emissions Workshop, San Diego, California, April 8, 2003

Fujita, E.M., D.E. Campbell, W.P . Arnott, J.W. Walker, B. Zielinska, and J.C. Chow (2003). DOE’s Gasoline/Diesel PM Split Study

– Ambient Measurements. Presented at the 13th
CRC On

- Road Vehicle Emissions Workshop, San Diego, California, April 8, 2003

Schauer, J., C. Christensen, E. Fuji ta, B. Zielinska, N. Clark, P. Gabele, and D. Lawson (2003). Molecular Marker Fingerprints For Si And Ci Vehicles Operating Over Different Driving Cycles. Presented at the 13th CRC On

- Road Vehicle Emissions Workshop, San Diego, California, April 8, 2003.Page 88

Zielinska, B., E.M. Fujita, J.C. Sagebiel, M. McDaniel and D.E. Campbell (2003). The Correlation of Lubricating Oil and Fuel Organic Composition with Tailpipe Emissions. Presented at the 13th CRC On

- Road Vehicle Emissions Workshop, San Diego, California, A pril 8, 2003.

Fujita, E.M., W.R. Stockwell, D.E. Campbell, J. Engelbrecht, R. Keislar, J. Lewis, B. Zielinska, and J.C. Chow (2003). Weekday/Weekend PM Nitrate Observations in the South Coast Air Basin. Presented at the 13th CRC On

- Road Vehicle Emissions Workshop, San Diego, California, April 8, 2003.

Fujita, E.M., D.E. Campbell, W.P. Arnott, B. Zielinska, J.C. Chow and Douglas R. Lawson (2003). Doe’s Gasoline/Diesel Pm Split Study

– Characterizations Of The Variations In Chemical Composition Of Pm2.5 In The South Coast Air Basin. Presented at the 9th Diesel Engine Emission Reduction (DEER) Workshop, Newport, RI, August 27, 2003.

Fujita, E.M. (2003). Evaluation of the On

- Road Emission Inventory: Historic Perspective in California’s South Coast Air Basin. Presented at the NARSTO Workshop on Innovative Methods for Emission Inventory Development and Evaluation, Austin, Texas, October 14

- 17, 2003.

Fujita, E.M., D.E. Campbell, W.P. Arnott, B. Zielinska and J.C. Chow (2003). DOE’s Gasoline/Diesel PM Split Stud y: Source Characterization and Apportionment. Presented
at the 22 nd Annual American Association for Aerosol Research Conference, Anaheim CA, October 20

- 24, 2003.

Zielinska, B., E.M. Fujita, J.C. Sagebiel, M. McDaniel and D.E. Campbell (2003). The Correlat ion of Lubricating Oil and Fuel Organic Composition with Tailpipe Emissions.
Presented at the 22 nd Annual American Association for Aerosol Research Conference, Anaheim CA, October 20

- 24, 2003.

Fujita, E.M. (2004). Organic Speciation Related to Source Rece ptor Modeling. Presented at the International State of Science Workshop on Organic Speciation in Atmospheric Aerosols Research, Las Vegas Nevada, April 5

- 7, 2004.

Fujita, E.M., D.E. Campbell, B. Zielinska, W.P. Arnott, J.C. Chow and D.R. Lawson (2004).
Do e’s Gasoline/Diesel PM Split Study

– Source Apportionment. Presented at the 14th
CRC On

- Road Vehicle Emissions Workshop, San Diego CA, March 29

- 31, 2004.

Lawson, D.R., P. Gabele, R. Snow, W.P. Arnott, E.M. Fujita, D.E. Campbell, J.W. Walker, H.
Moosmüller (2004). Analysis of Second

- by

- Second Emissions Data from Gasoline Vehicles in DOE’s Gasoline/Diesel PM Split Study. Presented at the 14th CRC On

- Road Vehicle Emissions Workshop, San Diego CA, March 29

- 31, 2004.Page 89

Yarwood, G., E. Fujita, C. Tran and S. Lau (2004). Sensitivity of Los Angeles Area Ozone Modeling And Ambient/Inventory Reconciliation To EMFAC Updates (CRC Project A

38). Presented at the 14th CRC On

- Road Vehicle Emissions Workshop, San Diego CA, March 29

- 31, 2004.

Fujita E.M., D.E. Campbell, B. Zielinska, and W.P. Arnott (2004). Assessing Exposure to Air Toxics in Microenvironments Dominated by Mobile Sources. Poster presented at 2004 Hei Annual Conference, Boston, MA, May 2

– 4, 2004

Fujita, E.M., D.E. Campbell, W.P. Arnott, B. Zielinska and J.C. Chow (2004). Source Contributions to Ambient Black Carbon in Colorado's Northern Front Range and California's South Coast Air Basin. Presented at the Black Carbon Emissions and Climate Change: A Technical Workshop, San Diego CA, October 13

- 15, 2004.

Fuji ta, E.M., B. Zielinska, D.E. Campbell, W.P. Arnott and D.R. Lawson (2004). Apportionment Of Mobile Source Air Toxics In The South Coast Air Basin. Presented at the CRC Mobile Source Air Toxics Workshop, Scottsdale, AZ, November 30

– December 2, 2004.

Law son, D.R., P. Gabele, R. Snow, W.P. Arnott, E.M. Fujita, D.E. Campbell, J.W. Walker, H. Moosmüller (2004). Second

- By

- Second Gas

- Phase And Pm Emissions Data And Their Relationship To Mobile Source Air Toxics Emissions From Gasoline Vehicles In Doe’s
Gasolin e/Diesel Pm Split Study. Presented at the CRC Mobile Source Air Toxics Workshop, Scottsdale, AZ, November 30

– December 2, 2004.

Zielinska, B., E.M. Fujita, J. Sagebiel, D.E. Campbell and W.M. Ollison (2004). Exposures To Mobile Source Toxics In High

- End Microenvironments In Three U.S. Cities. Presented at the CRC Mobile Source Air Toxics Workshop, Scottsdale, AZ, November 30

– December 2, 2004.

Fujita, E.M., D.E. Campbell, B. Zielinska and W.P. Arnott (2004). Assessing Exposure To Air Toxics In Microenv ironments Dominated By Mobile Sources. Poster presented at the CRC Mobile Source Air Toxics Workshop, Scottsdale, AZ, November 30

– December 2,
2004.

Fujita, E.M., Barbara Zielinska, William P. Arnott and David E. Campbell (2005). Recent Chemical Charact erization Of Mobile Source Emissions

– Relation To Ambient Measurements In Vehicle Dominated And Urban Background Locations. Presented at the AAAR PM Supersites Program and Related Studies, International Specialty Conference, Atlanta, GA, February 7

- 11, 20 05

Fujita, E.M., B. Zielinska and D.E. Campbell (2005). Characterizing Exhaust Emissions from Light

- Duty Gasoline Vehicles In The Kansas City Metropolitan Area

– Chemical Speciation. Presneted at the 15th CRC On

- Road Vehicle Emissions Workshop, San Diego CA, April 4

- 6, 2005.Page 90

Lawson D., E. Fujita, D. Campbell, B. Zielinska, W. Arnott, J. Chow, J. Schauer, C. Christensen, N. Clark, P. Gabele and W.Crews (2005). DOE’s Gasoline/Diesel PM Split Study

– Source Apportionment Results. Presented at the 15th CRC On

- Road Vehicle Emissions Workshop, San Diego CA, April 4

- 6, 2005.

Fujita, E.M., D.E. Campbell, A. Centric, W.P. Arnott, B. Zielinska, and J.C.Chow (2005) Exposure to Air Toxics Along Southern California Roadways. Presented at the Health
Effects Institute Annual Meeting, Baltimore, MD, April 17

- 19, 2005

Fujita, E.M., B. Zielinska, D.E. Campbell, W.P. Arnott, and J.C. Chow (2005). DOE’s Gasoline/Diesel PM Split Study. Presented at the 11th Diesel Engine Emission Reduction (DEER) Workshop, Chicago, Il , Aug ust 21

- 25, 2005

Fujita, E.M., B. Zielinska, D.E. Campbell, W.P. Arnott, and J.C. Chow (2005). DOE’s Gasoline/Diesel PM Split Study. Presented California Air Resources Board Chairman’s Air Pollution Seminar Series, Sacramento, CA, September 7, 2005

Fujit a, E.M., D.E. Campbell, W.P. Arnott, A. Centric, B. Zielinska and J.C. Chow (2005). Assessing Exposure to Air Toxics in Microenvironments Dominated by Mobile Sources. Presented at the 24th Annual American Association for Aerosol Research Conference,
Austin , Texas, October 17

- 21, 2005.

Fujita , E.M., B. Zielinska, D.E. Campbell, W.P. Arnott, and J.C. Chow (2005). Contributions of Gasoline and Diesel Vehicle Emissions to Urban, Near

- Road and On

- Road Exposures to Carbonaceous Particles in Southern California . Presented at the 4th Asian Aerosol Conference, Mumbai, India, December 13

- 16, 2005.

Fujita , E.M. and B. Zielinska (2006). Ambient Measurements of 1,3

- Butadiene, Acrolein and Particulate Organic Compounds: Challenges and Lessons. Presented at the Confer ence on Community Environmental Monitoring Programs, AWMA Golden West Chapter, San Francisco, CA, February 1, 2006.

Fujita , E.M. and B. Zielinska (2006). Application of Organic Molecular Markers for Ambient Apportionment of Fine Particulate Matter. Prese nted at the Bay Area Air Quality Management District Community Air Risk Evaluation Task Force Meeting, San Francisco, February 23, 2006.

Fujita, E.M. (2006). Source Apportionment of Ambient PM. Presented at the Bay Area Air Quality Management District Adv isory Council Meeting, San Francisco, March 22, 2006

Fujita, E.M., D.E. Campbell, S. Uppapalli, A. King, B. Zielinska and J.C. Chow (2006). Characterizing Exhaust Emissions from LDGVs in the Kansas City Metropolitan Area

– Chemical Speciation. Presented at the 15th CRC On

- Road Vehicle Emissions Workshop San Diego, CA, March 28

– 30, 2006.Page 91

Fujita, E.M., D.E. Campbell and B. Zielinska (2006). Assessing Exposure to Air Toxics in Microenvironments Dominated by Mobile Sources. Poster Presentation at the 2006 Health Effects Institute Annual Conference, San Francisco, California, April 9

– 11, 2006

Fujita , E.M. and B. Zielinska (2006). Source Apportionment of Fine Particulate Matter. Presented at the Conference on Ultrafine Particles, Los Angeles, California, April 30

- May 2, 2006.

Fujita, E.M., W.R. Stockwell, D.E. Campbell1, and D.R. Lawson (2006). Evolution of the Magnitude and Spatial Extent of the Weekend Ozone Effect in California’s South Coast Air Basin from 1981 to 2004. Presented at the AWMA’s 99th A nnual Conference New Orleans, Louisiana, June 20

- 23, 2006.

Fujita, E.M., D.E. Campbell, W.P. Arnott and B. Zielinska (2006). Source Attribution of Mobile Source Air Toxics. Presented at the 2006 CRC MSAT Workshop Phoenix, AZ, October 23

- 25, 2006.

Fujita , E.M., D.E. Campbell, J. Sagebiel and B. Zielinska (2006). Assessing Exposure to Air Toxics in Microenvironments Dominated by Mobile Sources. Presented at the 2006 CRC MSAT Workshop Phoenix, AZ, October 23

- 25, 2006.

Campbell, D.E., E.M. Fujita, B. Zielin ska, and J.C. Chow (2006). Characterization of Mobile Source Air Toxics Emissions from LDGVs in the Kansas City Metropolitan Area (A Preliminary Assessment). Presented at the 2006 CRC MSAT Workshop Phoenix, AZ, October 23

- 25, 2006.

Campbell D.E., E.M. Fuj ita, W.P. Arnott, and J. Walker (2007). Real

- Time Measurements Of Pm And Black Carbon Emissions Compared To Filter

- Based Pm And Elemental Carbon For Gasoline And Diesel Vehicles. Presented at the 16th CRC On

- Road Vehicle Emissions Workshop San Diego, CA, M arch 26

– 28, 2007.

Fujita, E.M., D.E. Campbell and B. Zielinska (2007). Chemical Analysis of Lubrication Oil Samples from LDGV in the Kansas City Metropolitan Area. Presented at the 16th CRC
On

- Road Vehicle Emissions Workshop San Diego, CA, March 26

– 28 , 2007.

Lawson, D.R., P. Gabele, E.M. Fujita, D.E. Campbell, B. Zielinska, and W.P. Arnott (2007).
Gas

- Phase and PM Emissions Characteristics from Gasoline Vehicles in DOE’s Gasoline/Diesel PM Split Study. Presented at the 16th CRC On

- Road Vehicle Emissi ons Workshop San Diego, CA, March 26

– 28, 2007.

Fujita, E.M. (2007). Assessment of Exposures to Mobile Source Air Toxics. Presented at the Air Toxics Workshop, Houston, TX, June 12

- 13, 2007.

Fujita, E., D. Campbell, and B. Zielinska (2007). Characteriza tion of Particle Emission from Light

- Duty Gasoline Vehicles in the Kansas City Metropolitan Area. Presented at the 5 th Asian Aerosol Conference in Kaoshiung, Taiwan, August 26

- 29, 2007.Page 92

Fujita, E.M. (2007). Mobile Source Emissions and Air Quality inCalifor nia’s South Coast Air
Basin

– Past, Present and Future. Presented to the Japanese Automotive Manufacturers Association in Tokyo Japan on September 4, 2007.

Fujita, E.M. (2007). Community and Microenvironmental Exposure Assessment. Presented at the Confere nce on Health Impacts of Air Pollution on Communities in Carson, CA on September 19

- 20, 2007.

Zielinska, B., E.Fujita, W. Ollison, D. Campbell, P. Merritt, L. Smith, and J. Sagebiel (2010) Relationships of Attached Garage and Home Exposures to Fuel Type a nd Emission Levels of Garage Sources, presented at the AAAR Specialty Conference, Air Pollution and Health San Diego, CA March 22

- 26, 2010

Fujita, E.M., D.E. Campbell, P. Arnott, B. Zielinska, T. Johnson and J. Mozier (2010) Measurements of Mobile Sourc e Air Pollutants in Urban Microenvironments, presented at the AAAR Specialty Conference, Air Pollution and Health San Diego, CA March 22

- 26, 2010

Fujita, E.M., J.B. Mason, D.E. Campbell and B. Zielinska (2010). Harbor Communites Monitoring Study (HCMS) Sa turation Monitoring of Toxic Air Contaminants and Related Pollutans. California Air Resources Board Webcast Seminar, Sacramento, CA, April 26, 2010.

Fujita, E.M., J.B. Mason, D.E. Campbell and B. Zielinska (2010): Saturation Monitoring for Assessment of C ommunity Exposure to Toxic Air Contaminants and Related Pollutants, poster presented at the 2010 AWMA International Specialty Conference in Xian, China, May 1

- 14, 2010.

Zielinska, B., E. Fujita and I.A. Khalek (2010) Comparison of New and Old Diesel Engin e Emissions, presented at the 29th Annual AAAR Conference, October 25

- 29, Portland,
OR

Zielinska, B., E. Fujita and D. Campbell (2010) Monitoring of Emissions from Barnett Shale Natural Gas Production Facilities for Population Exposure Assessment, invited presentation at the Mickey Leland NUATRC 2010 Symposium Credible Science to Address Texan’s Health: Exposure to Air Toxics Dallas TX, November 16, 2010.

Zielinska, B., E. Fujita, D. Campbell, V. Samburova, E. Hendler and C.S. Beskid (2010): Monitoring of Emissions from Natural Gas Production Facilities in Barnett Shale Area for Population Exposure Assessment, poster presented at the AGU Fall meting in San Francisco, Dec 13

- 17, 2010

Campbell, D., E. Fujita, W.Patrick Arnott, P. Martien and V. Lau (2010). West Oakland Monitoring Study Saturation Monitoring of Air Toxics. Presented at the 2010 CRC Mobile Source Air Toxics Workshop, November 30

- December 2, 2010, Sacramento,
CAPage 93

Fujita, E., B. Zielinska, J. Carroll, K. Whitney, I. Khalek, L. Smith and D. Law son (2010). Collaborative Lubricating Oil Study on Emissions (CLOSE) Project Update

- Role of Fuel and Lubricating Oil in PM Emissions from a Normal

- and a High

- Emitting Light

Duty Gasoline Vehicle. Presented at the 2010 CRC Mobile Source Air Toxics Worksh op, November 30

- December 2, 2010, Sacramento, CA

Reports

Fujita, E. and L. Shepard (1978). Consideration of Model Rule for the Control of Volatile Organic Emissions from Metal Furniture and Fixture Coating Operations. Prepared for California Air Resour ces Board, Sacramento, CA, June 1978.

Fujita, E., L. Shepard, D. Saito, R. Cargill, J. Pantalone and G. Shiroma (1978). Consideration of a Proposed Model Rule for the Control of Volatile Organic Compound Emissions from the Surface Coating of Manufactured Metal Parts and Products. Prepared for California Air Resources Board, Sacramento, CA, September 1978.

Sanders, J., E. Fujita, K. Tonnessen, D. Westerdahl, L. Ashbaugh, M. Ahuja, C. Robertson and P. Amar (1984). Second Annual Report to the Governor and th e Legislature on the Air Resources Board's Acid Deposition Research and Monitoring Program. Prepared for the Research Division, California Air Resources Board, Sacramento, CA, December 1984.

Ashbaugh, L., E. Fujita, M. Ahuja, J. Sanders, K. Tonnessen, D. Westerdahl and P. Amar (1985). The Third Annual Report to the Governor and the Legislature on the Air Resources Board's Acid Deposition Research and Monitoring Program. Prepared for the Research Division, California Air Resources Board, Sacramento, CA, Dec ember 1985.

Fujita, E., P. Amar, L. Ashbaugh, W. Walker, K. Tonnessen, M. Ahuja and D. Westerdahl (1986). The Fourth Annual Report to the Governor and the Legislature on the Air Resources Board's Acid Deposition Research and Monitoring Program. Prepared f or the Research Division, California Air Resources Board, Sacramento, CA, December 1986.

Amar, P., L. Ashbaugh, E. Fujita, K. Tonnessen, M. Ahuja, D. Westerdahl, H. Cabrera, E. Ota, C. Unger, S. Champomier and N. Weir (1988). Fifth Annual Report to the Go vernor and the Legislature on the Air Resources Board's Acid Deposition Research and Monitoring Program. Prepared for the Research Division, California Air Resources Board, Sacramento, CA, January 1988.

Blanchard, C., M. Ahuja, L. Ashbaugh, S. Champomier, B. Croes, E. Fujita, S. Prasad, K. Wagner and D. Westerdahl (1989). The Health and Welfare Effects of Acid Deposition in California: Technical Assessment. Prepared for California Air Resources Board, Sacramento, CA, June 1989.Page 94

Bode, R., A. Delao, L. Doli slager, J. Fernandez, E. Fujita, N. Montez, M. Nystrom and G. Shahinian (1991). Amendments to Regulations Regarding the State 24

- Hour Ambient Air Quality Standard for Sulfur Dioxide, Staff Report. Prepared for the Research Division, California Air Resource s Board, Sacramento, CA, August 1991.

Chow, J.C., J.G. Watson, R. De Mandel, W. Chan, J. Cordova, D. Fairley, E.M. Fujita, D. Levaggi, G. Long, T. Perardi, and M. Rothenberg (1993). Measurements and Modeling of PM10 in San Francisco's Bay Area Volume I: P rogram Plan. DRI Document No. 3654.1D3. Prepared for Bay Area Air Quality Management District, San Francisco, CA,
June 1993.

Diaz, S., E.M. Fujita and D.R. Lawson (1994). On

- Road Vehicle Emissions Measurements Test Sites

– Sacramento Pilot Project First Int erim Report. Prepared for Bureau of Automotive Repair, May 23, 1994.

Diaz, S., E.M. Fujita and D.R. Lawson (1994). On

- Road Vehicle Emissions Measurements Test Sites

– Sacramento Pilot Project Second Interim Report. Prepared for Bureau of Automotive Repair, June 17, 1994.

Fujita, E.M., D.R. Lawson, J.C. Sagebiel, J.G. Watson, P.T. Roberts, P.M. Roth and S.D. Reynolds (1994). Quantification of Underestimates in the SARMAP Emissions Inventory. Draft Final Report, prepared for California Air Resources Board, Sa cramento, CA, 20 October 1994.

Stoeckenius, T.E., G. Yarwood, M.P. Ligocki, J.P. Cohen, S.B. Shepard, R.E. Looker, E.M. Fujita, H.H. Main and P.T. Roberts (1995). Feasibility Study for a 1995

- 1996 Southern California Air Quality Monitoring Program. Final Report, prepared for Coordinating Research Council, Atlanta, GA by Systems Applications International, San Rafael, CA, January 1995.

Diaz, S., E.M. Fujita and D.R. Lawson (1995). Program for the Use of Remote Sensing Devices to Detect High

- Emitting Vehicl es

— Program Plan. Final Report, prepared for the South Coast Air Quality Management District, Diamond Bar, CA, by the Desert Research Institute, Reno, NV, 30 January 1995.

Fujita, E.M., N. Robinson, Z. Lu, and R.T. Egami (1995). Database Utilities for Est imating and Compiling Hazardous Air Pollutant Emissions Using Emission Factors and Source Composition Profiles. Final Report. Prepared for State of Nevada, Department of Conservation and Natural Resources, Division of Environmental Protection, Carson Cit y, NV.

Keislar, R.E., J.L. Bowen, E.M. Fujita,and D.R. Lawson (1995). Effect of Oxygenated Fuels on Ambient Carbon Monoxide Concentrations in Provo, Utah, Final Report. Prepared for Geneva Steel Company, P.O. Box 2500, Provo, Utah, 31 August 1995.Page 95

Fuji ta, E.M., Z. Lu, J. Sagebiel, G. Harshfield, and B. Zielinska (1995). Validation and Evaluation of the Coast Oxidant Assessment for Southeast Texas (COAST) Volatile Compound Data. Final report prepared for the Texas Natural Resource Conservation Commissi on, August 1995.

Fujita, E.M., Z. Lu, J. Sagebiel, N.F. Robinson, and J. G. Watson (1995). VOC Source Apportionment for the Coast Oxidant Assessment for Southeast Texas. Final report prepared for the Texas Natural Resource Conservation Commission, Augus t 1995.

Fujita, E.M., M.C. Green, R.E. Keislar, D.R. Koracin, H. Moosmuller, and J.G. Watson (1996). 1997 Southern California Ozone Study (SCOS97) Operational Program Plan

– Working Draft. Prepared for the California Air Resource Board, Sacramento, CA, F ebruary, 1996.

Lawson, D.R., S. Diaz, E.M. Fujita, S.L. Wardenburg, R.E. Keislar, Z. Lu and D.E. Schorran (1996). Program for the Use of Remote Sensing Devices to Detect High

- Emitting Vehicles. Final Report. Prepared for Technology Advancement Office, South Coast Air Quality Management District, Diamond Bar, CA, April 16, 1996.

Fujita, E., J.G. Watson, D. Cobb, D. Dietrich, W. Neff, and L.W. Richards (1996). Northern Front Range Air Quality Study Winter 1996/97 Field Study Plan. Prepared for Colorado State University, Ft. Collins, CO, December, 1996.

Pierson W.R., D.R. Lawson, D.E. Schorran, E.M.Fujita, J.C. Sagebiel, and R.L. Tanner (1996).
Assessment of Non

- Tailpipe Hydrocarbon Emissions from Motor Vehicles. CRC Project
No. VE

- 11

- 7. Final Report prepared for the Coordinating Research Council, Atlanta, GA, December 1996

Fujita, E.M., Z. Lu, C. Frazier, and J.G. Watson (1997). Application of the Chemical Mass Balance Receptor Model to Apportionment of Suspended Particulate Matter in the Bangkok M etropolitan Region. Prepared for Radian International, LLC, Austin, TX, January 26, 1997.

Fujita, E., J.G. Watson, B. Zielinska, J. McDonald, L. Sheetz, R. Purcell, J. Sagebiel, and F. Rogers (1997). Northern Front Range Air Quality Study Winter 1996/97 Field Study Plan Measurement and Characterization of Particulate Emissions from Residential Wood Combustion and Meat Cooking. Prepared for Colorado State University, Ft. Collins, CO February 24, 1997.

Fujita, E. and Z. Lu (1997). Hydrocarbon Receptor M odeling for the 1996 Phoenix Ozone Study. Final Report prepared for ENSR, Camarillo, CA, March 5, 1997.

Fujita, E.M., J.L. Bowen, M.C. Green, and H. Moosmuller (1997). 1997 Southern California Ozone Study (SCOS97) Quality Assurance Plan. Prepared for t he California Air Resource Board, Sacramento, CA April, 1997.Page 96

Zielinska, B., J. Sagebiel, G. Harshfield, and E. Fujita (1997). Air Monitoring Program for Determination of the Impacts of the Introduction of California’s Phase 2 Reformulated
Gasoline on Am bient Air Quality in the South Coast Air Basin. Draft Final Report prepared for the California Air Resources Board, Sacramento, CA May 5, 1997.

Fujita, E.M., Z. Lu, L. Sheetz, G. Harshfield, and B. Zielinska (1997). Determination of Mobile Source Emissi on Source Fraction Using Ambient Field Measurements. Final Report prepared for the Coordinating Research Council, Atlanta, GA, July 1997.

Fujita, E., Z. Lu, G. Harshfield, and B. Zielinska (1997). NARSTO

- Northeast: Hydrocarbon and Carbonyl Measurement Au dits for the 1995 Field Study. Final Report prepared for the Electric Power Research Institute, Palo Alto, CA, July 1997

Fujita, E.M. (1997). Technical Review of the Phoenix Voluntary Early Ozone Plan

– Application of Hydrocarbon Speciation Measurements and Source Apportionment in the Development of the VEOP Alternative Plausible Emission Inventory. Prepared for ENVAIR, September 1997.

Fujita, E., Z. Lu, G. Harshfield, and B. Zielinska (1997). NARSTO

- Northeast: Hydrocarbon and Carbonyl Measurement Audi ts for the 1995 Field Study. Final Report prepared for the Electric Power Research Institute, Palo Alto, CA, July 1997

Fujita, E.M., Z. Lu, L. Sheetz, G. Harshfield, T. Hayes, and B. Zielinska (1997). Hydrocarbon Source Apportionment in Western Washingto n. Report prepared for the State of Washington Department of Ecology, Lacy, WA, September, 1997.

Yarwood, G., J. Heiken, C. Tran, M. Jiminez, E. Fujita, and Z. Lu (1997). Speciated VOC Emissions for the Dallas/Fort Worth Nonattainment Area. Final repor t prepared for the Texas Natural Resource Conservation Commission, Austin, TX, October 1997

Chow J., B. Zielinska, J.G. Watson, E. Fujita, L. Richards, W. Neff, D. Dietrich, and S. Herring (1998). Northern Front Range Air Quality Study Volume A: Ambient Measurements. Final report prepared for the Colorado State University, Fort Collins, CO., June 30, 1998

Fujita, E. (1998). Hydrocarbon Source Apportionment for the 1996 Paso del Norte Ozone Study.
EPA Contract No. 68

- D3

- 0030. Final report prepared for U.S. Environmental Protection Agency, Dallas, TX., March 1998.

Fujita, E., and Z. Lu (1998). Analysis of Data From the 1995 NARSTO

- Northeast Study. Volume III: Chemical Mass Balance Receptor Modeling. Draft final report prepared for Coordinating Re search Council, Atlanta, GA, April 1998.

Fujita, E., J.G. Watson, J.C. Chow, N. Robinson, L. Richards, and N. Kumar (1998). Northern Front Range Air Quality Study. Volume C: Source Apportionment and Simulation Methods and Evaluation. Final report pre pared for Colorado State University, Fort Collins, CO, June 30, 1998.Page 97

Watson, J., E. Fujita, J.C. Chow, B. Zielinska, L. Richards, W. Neff, and D. Dietrich (1998). Northern Front Range Air Quality Study. Final report prepared for Colorado State Universit y, Fort Collins, CO, June 30, 1998.

Watson, J.G., N.F. Robinson, E.M. Fujita, J.C. Chow, T.G. Pace, C. Lewis, and T. Coulter (1998). CMB8 Applications and Validation Protocol for PM2.5 and VOCs. Prepared for U.S. Environmental Protection Agency, Researc h Triangle Park, NC, by Desert Research Institute, Reno, NV.

Zielinska, B. J. McDonald, T. Hayes, J.C. Chow, E. Fujita, and J.G. Watson (1998). Northern Front Range Air Quality Study. Volume B: Source Measurements. Final report prepared for Colorado St ate University, Fort Collins, CO, June 30, 1998.

Fujita, E. (1998). Emission Source Profiles Applicable to CMB Receptor Modeling of Texas PAMS VOC Data. TNRCC Contract No. 98 80078200. Final report prepared for the Texas Natural Resource Conservation C ommission, Austin, TX, November 1998.

Fujita, E. (1998). MAG Brown Cloud Study Source Attribution of PM2.5. MAG Contract 0069 Work Task 7.1. Final Report prepared for the Maricopa Association of Governments, Phoenix, AZ, December, 1998.

Zielinska, B., J. Sagebiel, G. Harshfield, and E. Fujita (1999). Air Monitoring Program for Determination of the Impacts of the Introduction of California’s Phase 2 Reformulated Gasoline on Ambient Air Quality in the South Coast Air Basin. Prepared for the California Air Resources Board, Sacramento, CA, February, 1999.

Fujita, E.M., R.E. Keislar, J.L. Bowen, W. Goliff, F. Zhang, L.H. Sheetz, M.D. Keith, J.C. Sagebiel, and B. Zielinska (1999). 1998 Central Texas On

- Road Hydrocarbon Study. Draft final report prepared for the Texas Department of Transportation, Austin, TX under subcontract to PBS&J, Austin, TX, March, 1999.

Fujita, E. (1999). VOC Source Signatures in Houston, TX Phase 1: Sample Collection. Prepared for the Texas Natural Resource Conservation Commissio n (Contract No. 980069300) under subcontract to MCNC

- North Carolina Supercomputing Center, Research Triangle Park, NC, August, 1999.

Fujita, E. (1999). Analysis of Ambient Air Quality Data in and Near Northern Baja California, Mexico, VOC Sampling and S ource Apportionment

- Sampling and Quality Assurance Plan. Prepared for the California Air Resources Board (Contract No. 98

- 541) under subcontract to Sonoma Technology, Inc. Petaluma, CA, September, 1999.

Fujita, E., R. Keislar, W. Stockwell, H. Moosmul ler, D. DuBois, D. Koracin, and B. Zielinska (1999). Central California Ozone Study

– Volume I Field Study Plan. Prepared for the CCOS Technical Committee c/o California Air Resources Board, Sacramento, CA, November 1999.Page 98

Fujita, E.M., H. Moosmuller, M. C. Green, J.L. Bowen, Leon Dolislager, Ash Lashgari, Nehzat Motallebi, Randy Pasek, and Jim Pederson (1997). SCOS97

- NARSTO 1997 Southern California Ozone Study and Aerosol Study: Volume IV Summary of Quality Assurance. Prepared for the California Air Res ource Board, Sacramento, CA December, 1999.

Zielinska, B., J.C. Sagebiel, J. Mc Donald, C.F. Rogers, and E. Fujita (2000). Diesel Emissions Exposure Measurements in Underground Mines. Draft final report prepared for the Health Effects Institute, Boston, M A, March 2000.

Fujita, E., R. Keislar, W. Stockwell, D. Freeman, J. Bowen, and R. Tropp (2000). Central California Ozone Study

– Volume II Field Operations Plan. Prepared for the CCOS Technical Committee c/o California Air Resources Board, Sacramento, C A, May 2000.

Fujita, E.M., W. Stockwell, R.E. Keislar, D.E. Campbell, P.T. Roberts, E.H. Funk, C.P. McDonald, H.H. Main, and LR. Chinkin (2000). Weekend/Weekday Ozone Observations in the South Coast Air Basin: Retrospective Analysis of Ambient and Emissio ns Data and Refinement of Hypotheses, Volume I

– Executive Summary. Prepared for the National Renewable Energy Laboratory, Golden, CO, December 2000.

Fujita, E.M., W. Stockwell, R.E. Keislar, and D.E. Campbell (2000). Weekend/Weekday Ozone Observations in the South Coast Air Basin: Retrospective Analysis of Ambient and Emissions Data and Refinement of Hypotheses, Volume II

– Desert Research Institute Tasks 1 and 2. Prepared for the National Renewable Energy Laboratory, Golden, CO, December 2000.

Fujita, E.M., R. Keislar, D. Campbell, R. Keislar, and J. Bowen, (2001). Central California Ozone Study (CCOS)

– Volume III: Summary of Field Operations. Final report prepared for the CCOS Technical Committee c/o California Air Resources Board, Sacramento, CA, February 2001.

Fujita, E.M., and D.E. Campbell, W. Stockwell, B. Zielinska, JC. Sagebiel, W. Goliff, M. Keith, J.L. Bowen (2001). Weekend/Weekday Ozone Observations in the South Coast Air Basin: Phase II Field Study. Interim report prepared by the Desert Research Institute for the National Renewable Energy Laboratory, Golden, CO, October 2001.

Fujita, E.M., D.E. Campbell, W. Stockwell, P.T. Roberts, T.H. Funk, C.P. MacDonald, H.H. Main, and LR. Chinkin (2002). Weekend/Weekday Ozone Observations in the So uth Coast Air Basin Volume I

– Executive Summary. Report prepared by the Desert Research Institute, Reno, NV and Sonoma Technology, Petaluma, CA for the National Renewable Energy Laboratory, Golden, CO, and the Coordinating Research Council, May 2002.

Fu jita, E.M., D.E. Campbell, W. Stockwell, R. Keislar, B. Zielinska, J.C. Sagebiel, W. Goliff, M. Keith, and J.L. Bowen (2002). Weekend/Weekday Ozone Observations in the South Coast Air Basin Volume II: Analysis of Air Quality Data. Final report prepared by thePage 99

Desert Research Institute, Reno, NV for the National Renewable Energy Laboratory, Golden, CO, and the Coordinating Research Council, April 2002.

Fujita, E.M., D.E. Campbell, W. Stockwell, P.T. Roberts, T.H. Funk, C.P. MacDonald, H.H. Main, and LR. Chi nkin (2002). Weekend/Weekday Ozone Observations in the South Coast Air Basin Volume I

– Executive Summary. Report prepared by the Desert Research Institute, Reno, NV and Sonoma Technology, Petaluma, CA for the National Renewable Energy Laboratory, Golden, CO, and the Coordinating Research Council, May 2002.

Fujita, E.M., D.E. Campbell, W. Stockwell, R. Keislar, B. Zielinska, J.C. Sagebiel, W. Goliff, M. Keith, and J.L. Bowen (2002). Weekend/Weekday Ozone Observations in the South Coast Air Basin Volume II: Analysis of Air Quality Data. Final report prepared by the Desert Research Institute, Reno, NV for the National Renewable Energy Laboratory, Golden, CO, and the Coordinating Research Council, April 2002.

Zielinska, B., J. Sagebiel, E.Fujita, D. Campbell, J. McDonald, T. Kelly and D. Joseph (2002). Section 211(B) Tier 2 High

- End Exposure Screening Study Of Baseline and Oxygenated Gasoline

– Pilot Study. Report prepared for the American Petroleum Institute, Washington, DC, June 13, 2002.

Zielinska, B., E.F ujita, J. Sagebiel, D. Campbell, J. McDonald, L. Smith, and T. Johnson (2002). Exposure Protocol and Study Plan for the Section 211(B) Tier 2 High End Exposure Screening Study of Baseline and Oxygenated Gasoline. Report prepared for the American
Petroleum Institute, Washington, DC, September 30, 2002.

Zielinska, B., E.Fujita, J. Sagebiel, D. Campbell, J. McDonald (2002). Interim Data Report for Section 211(B) Tier 2 High End Exposure Screening Study of Baseline and Oxygenated Gasoline. Report prepared for the American Petroleum Institute, Washington, DC, November 15, 2002.

Fujita, E.M. and D. Campbell (2003). PAMS Data Analysis for Southern California Volume VII: Source Apportionment of Volatile Organic Compounds. Final report prepared for the South Coast Air Quality Management District, Diamond Bar, CA, June 20, 2003.

Fujita, E.M. and D. Campbell (2003). Validation and Application Protocol for Source Apportionment of Photochemical Assessment Monitoring Stations (PAMS) Ambient Volatile Organic Compound (VO C) Data. Final report prepared for the U.S. Environmental Protection Agency under EPA Star Grant #GR826237

- 01

- 0, August 31,
2003.

Fujita, E.M., D. Koracin, D. Freeman, R.E. Keislar, D. Podnar, T.E. McCord, D.E. Campbell, and W.R. Stockwell (2003). State I mplementation Plan (SIP) Planning Service for the Sacramento Ozone Nonattainment Area: Volume 1

– Data Analysis and Episode Selection for SIP Modeling. Prepared for the Sacramento Metropolitan Air Quality Management District, Sacramento CA, September 9, 20 03.Page 100

Yarwood, G., C. Tran, S. Lau and E. Fujita (2003). Impact of Updates to On

- Road Mobile Source Emission Factor Models (EMFAC) for the Los Angeles Region: Ozone Model Sensitivity and Ambient/Inventory Reconciliation. Final report prepared for the Coordin ating Research Council, Alpharetta GA, September 29, 2003.

Fujita, E.M., J.G.Watson, J.C. Chow and B. Zielinska (2003). Demonstration PM Study Plan for Pune, Maharastra, India. Prepared for U.S. Environmental Protection Agency Office of
International Aff

airs, Washington DC, November 24, 2003.

Fujita, E. (2004) Validation Of The U.S. EPA Mobile6 Highway Vehicle Emission Factor Model Crc Project E

- 64 Task 4 Guidance Document for Validation of On

- Road Vehicle Emissions Inventory. Prepared for the Coordinati ng Research Council, Alpharetta GA, February 12, 2004.

Stockwell W.R., E.M. Fujita, I. Shumyatsky, D. Freeman, D.E. Campbell, D. Koracin, D. Podnar, T.E. McCord, and (2004). State Implementation Plan (SIP) Planning Service for the Sacramento Ozone Nonatt ainment Area: Volume 2

– Protocol for State Implementation Plan (SIP) Modeling. Draft report prepared for the Sacramento Metropolitan Air Quality Management District, Sacramento CA, April 1, 2004.

Stockwell W.R., E.M. Fujita, I. Shumyatsky, D. Freeman, D .E. Campbell, D. Koracin, D. Podnar, T.E. McCord (2004). State Implementation Plan (SIP) Planning Service for the Sacramento Ozone Nonattainment Area: Volume 3

– State Implementation Plan (SIP) Modeling. Draft report prepared for the Sacramento Metropolita n Air Quality Management District, Sacramento CA, May 28, 2004.

ERG, BKI, NuStats and DRI (2004). Kansas City PM Characterization Study, Draft Pilot Testing Report. Prepared for the U.S. Environmental Protection Agency, Ann Arbor, MI, June 18, 2004

Fuji ta, E.M., D.E. Campbell and W.P. Arnott (2004). Quality Management Plan (QMP) and Quality Assurance Project Plan (QAPP) for Characterizing Exhaust Emissions from Light

- Duty Gasoline Vehicles in the Kansas City Metropolitan Area. Prepared by Division of Atm ospheric Sciences, Desert Research Institute for U.S. Environmental Protection Agency under Subcontract to Eastern Research Group Inc. June 23, 2004.

Fujita E.M., D.E. Campbell, R. Keislar and B. Zielinska (2004). Analysis of Ambient Air Quality Data Coll ected In and Near Northern Baja California, Mexico: Task 4

- VOC Sampling and Source Apportionment. Prepared for the California Air Resources Board, Sacramento CA, August 19, 2004.

Fujita E.M., B. Zielinska, J. Sagebiel and D.E. Campbell (2004) Kansas Ci ty PM Characterization Study Pilot Study Testing Report

– Addendum: Effect of Sampling Temperature on Chemical Speciation 1,3

- Butadiene Stability Experiments. Prepared for U.S. Environmental Protection Agency, Ann Arbor, MI and U.S. Department of Energy
Na tional Renewable Energy Laboratory, Golden, CO, October 27, 2004.Page 101

Fujita, E. (2005). Validation of the U.S. EPA MOBILE6 Highway Vehicle Emission Factor Model, Task 4: Guidance Document for Validation of On

- Road Vehicle Emissions Inventory. Final report sub mitted to the Lake Michigan Air Directors Consortium, April 24, 2005

Yarwood, G., R. Morris, S. Rao, S. Lau, E.M. Fujita, D.E. Campbell and W. White (2005). Evaluating VOC Receptor Models Using Grid

- Model Simulations CRC Project A

- 34. Final report submit ted to Coordinating Research Council, Alpharetta, GA, April 27,
2005.

Campbell, D.E. and E.M. Fujita (2005). Deployment of DRI Mobile Van in Support of the Roseville Rail Yard Air Monitoring Project. Final report submitted to Placer County Air Pollution C ontrol District, Auburn, CA, May 6, 2005.

Fujita, E.M., D.E. Campbell and T. Snorradottir, (2005). Central California Ozone Study (CCOS): Data Validation. Final report submitted to the Joaquin Valleywide Air Pollution Study Agency, c/o California Air Reso urces Board, Planning and Technical Support Division, Sacramento, CA, May 9, 2005.

Fujita, E.M., B. Zielinska, W.P. Arnott, D.E. Campbell, L. Rinehart, J.C. Sagebiel and J.C. Chow (2006). Gasoline/Diesel PM Split Study: Source and Ambient Sampling, Chemic al Analysis, and Apportionment Phase. Final report submitted to the U.S. Department of Energy National Renewable Energy Laboratory, Golden, CO, January 19, 2006.

Campbell, D.E. and E.M Fujita (2006). Data Analysis on the Roseville Rail Yard Air
Monitorin g Project. Final report submitted to the Placer County Air Pollution Control District, Auburn, CA, March 15, 2006.

Zielinka, B., E.M. Fujita, J.C. Sagebiel, and D.E. Campbell (2006). Section 211(B) Tier 2 High End Exposure Study of Conventional and Oxygen ated Gasoline. Final Report submitted to the American Petroleum Institute, Washington, D.C., July 19, 2006.

Kishan, S., A. Burnett, S. Fincher, M. Sabisch, W. Crews, R. Snow, M.Zmud, R. Santos, S. Bricka, E. Fujita, D. Campbell, P.Arnott (2006). Kansas Ci ty PM Characterization Study, Final report submitted to the U.S. Environmental Protection Agency, Ann Arbor, MI, October 27, 2006.

Fujita, E.M. and D.E. Campbell (2006). Spatial and Temporal Variations in Exposure to Air Toxics in the South Coast Air Basi n. Final report submitted to the National Renewable Energy Laboratory, NREL Contract No. RCL

- 4

- 44113, Golden, CO, December 31, 2006.

Fujita, E.M., D.E. Campbell, B. Zielinska (2006). Chemical Analysis of Lubrication Oil Samples from a Study to Characteriz e Exhaust Emissions from Light

- Duty Gasoline Vehicles in the Kansas City Metropolitan Area. Final report submitted to the National Renewable Energy Laboratory, NREL Contract No. ACI

- 5

- 55528

- 01, Golden, CO, and the Coordinating Research Council, CRC E

- 69A, Alpharetta, GA, December 31, 2006.Page 102

Fujita, E.M., D.E. Campbell, B. Zielinska, W.P. Arnott, J.C. Chow (2008). Concentrations of Air Toxics in Motor Vehicle Dominated Microenvironments. Final report submitted to the Health Effects Institute, HEI contract 47 04

- RFA03

- 1/02

- 16, Boston, MA, January 13,
2008.

Fujita, E.M., D.E. Campbell, B. Mason, B. Zielinska (2009). Harbor Community Monitoring Study (HCMS) Saturation Monitoring. Final report submitted to the California Air Resources Board, Sacramento CA, May 15 , 2009.

Fujita, E.M., D.E. Campbell, J. Engelbrecht, B. Zielinska (2009). Characterization of Fine Particle Mass Using Particle

- Phase Organic Compounds as Tracers. Final report submitted to Southeastern States Air Resources Managers, Inc. Forest Park, NC, June 30, 2009.

Zielinska, B., E. Fujita, and D. Campbell (2010). Barnett Shale Oil and Gas Production. Final report prepared for the Mickey Leland National Urban Air Toxics Research Center, Houston, Texas, July 30, 2010.

Fujita, E.M. and D.E. Campbell ( 2010). West Oakland Monitoring Study. Final report prepared for the Bay Area Air Quality Management District, San Francisco, CA, October 7, 2010.Page 103 KEITH KNOLL 525 Fox Glove Court Fort Collins, CO 80524 (303) 305

- 8573 Keith.Knoll@Czero

- Solutions.com

HIGH LIGHTS OF QUALIFICATIONS

Proficiency with light

- duty vehicle emissions testing protocols and procedures, emissions calculations, and atmospheric impact analyses. Strong background in engine component design and development

– primarily diesel fuel injectio n equipment. Proficiency with MATLAB for component design, data analysis, and data presentation. Experience in preparing and delivering technical presentations to both expert and non

expert audiences. Skill in leading small and large, multi

- year research p rojects managing technical, financial, and contract issues.

EXPERIENCE

Senior Project Engineer Czero, Inc., Fort Collins, CO 2011

– Present Consulting engineering specializing in combustion, emissions and alternative fuels utilization. Expertise in early

- stage R&D on engines, hydraulics and hybrid powertrain technologies.

Senior Engineer National Renewable Energy Lab, Golden, CO 2007

– 2011 Leading numerous biofuel

- related vehicle emissions research projects. Collaborating with industry partners to condu ct vehicle emissions, fuel system, and engine durability impact studies with mid

- level ethanol blends. In the process developed critical database used by EPA to for E15 waiver decision. Conducting light

- duty vehicle emissions research projects to understa nd air quality impacts of increased flexible

- fuel vehicle (FFV) use with E85 fuel.

Project Leader Sturman Industries, Woodland Park, CO 1998

– 2006 Led successful $2.4 million HVA (Hydraulic Valve Actuation) project combining objectives from three custome rs with installations and engine tests at three sites. Had direct responsibility for proposal, technical specification, laboratory test and development, and engine start

- up / shakedown at customer sites. Managed small team of engineers and technicians, pro viding technical direction for design, analysis, test, and software development. Created test specifications, developed test set

- up, executed tests, and analyzed and presented data for various HVA and advanced diesel fuel system projects.

Development Engi neer Diesel Technology Company, Grand Rapids, MI 1996

– 1998 Led advanced FIS (Fuel Injection System) development team developing new fuel system to reduce diesel engine emissions and meet US04 and Euro III standards.Page 104

Implemented new FIS technology at cust omer sites to verify and document improved engine emissions performance.

Technical Specialist Cummins Engine Company, Columbus, IN 1993

– 1996 Led common rail injection control valve development, coordinating goals and activities of team to achieve sub

- sy stem technical specification. Tested and developed injection control valve to optimize performance and recommend design iterations.

Research Engineer II Babcock & Wilcox, Alliance, OH 1989

– 1993 Analyzed experimental data and documented results in final report for development of next generation steam generator for U.S. Navy nuclear program. Developed and evaluated new measurement technologies for thermal

- hydraulic application.

EDUCATION

P URDUE U NIVERSITY M.S., Mechanical Engineering, 1989
GPA: 5.73 / 6.00 Thesis: Coal Water Slurry Atomization
N ORTH C AROLINA S TATE U NIVERSITY B.S., Mechanical Engineering, 1986 Major GPA: 3.80 / 4.00

PUBLICATIONS

“The Impacts of Mid

- level Biofuel Content in Gasoline on SIDI Engine

- out and Tailpipe
Particulate Matter Emissions,” X. He, J. Ireland, B. Zigler, M. Ratcliff, K. Knoll, T. Alleman, and J. Tester, SAE Technical Paper, 2010

- 01

- 2125, October 2010.

“Effects of Mid

- Level Ethanol Blends on Conventional Vehicle Emissions,” K. Knoll, B. West, S. Huff, J. Thomas, J . Orban, and C. Cooper, SAE Technical Paper, 2009

- 01

- 2723, November
2009.

“Effects of Intermediate Ethanol Blends on Legacy Vehicles and Small Non

- Road Engines, Report 1

– Updated,” K. Knoll, B. West, W. Clark, R. Graves, J. Orban, S. Przesmitzki, and T. Theiss, NREL/TP

- 540

- 43543 and ORNL/TM

- 2008/117, February 2009.

“Venturi Performance with Internal Sense

- Line Configuration,” presented at the 1992 ASME Fluids Engineering Conference, Los Angeles, CA, June 1992.

“Investigation of an Electromagnetic Flowme ter for Gas

- Liquid Two

- Phase Flow Measurement,”
7 th Proceedings of Nuclear Thermal Hydraulics, ANS, November 1991.Page 105

“Flat Sheet Two

- Fluid Atomization of High Viscosity Fluids. Part III. Coal

- Water Slurries,” written with P.E. Sojka, ASME Heat Transfer Div ision, Vol. 187, pp. 45

- 50, December 1991.

“Physical Mechanisms and Predictive Equations for Coal

- Water Slurry Atomization,” presented with P.E. Sojka at the Annual Coal Fuel Heat Engine Cleanup Systems Contractors Review Meeting, Morgantown, WV, June 198 9.

“Influence of Nozzle Geometry on Coal

- Water Slurry Atomization,” presented with P.E. Sojka at the First Annual Conference on Liquid Atomization and Spray Systems, Madison, WI, May
1987.Page 106 

### Appendix B : Conflict of Interest Statements

Conflict of Inter est and Bias for Peer Review

Background

Identification and management of potential conflict of interest (COI) and bias issues are vital to the successes and credibility of any peer review consisting of external experts. The questionnaire that follows i s consistent with EPA guidance concerning peer reviews. 2

. Definitions

Experts in a particular field will, in many cases, have existing opinions concerning the subject of the peer review. These opinions may be considered bias, but are not necessarily con flicts of
interest.

Bias : For a peer review, means a predisposition towards the subject matter to be discussed that could influence the candidate's viewpoint.

Examples of bias would be situations in which a candidate:

1. Has previously expressed a pos ition on the subject(s) under consideration by the panel; or

2. Is affiliated with an industry, governmental, public interest, or other group which has expressed a position concerning the subject(s) under consideration by the panel.

Conflict of Interest : For a peer review, as defined by the National Academy of Sciences, 3 includes any of the following:

1. Affiliation with an organization with financial ties directly related to the outcome;

2. Direct personal/financial investments in the sponsoring organ ization or related to the subject; or

3. Direct involvement in the documents submitted to the peer review panel

... that could impair the individual's objectivity or create an unfair competitive advantage for the individual or organization.

2 U.S. EPA (200 9 ). Science Policy Council Peer Review Handbook

. OMB (2004). Final Information Quality Bulletin for Peer Review.
3 NAS (2003). "Policy and Procedures on Committee Composition and Balance and Conflict or Interest for Committees Used in the Development of Reports" (www.nationalacademies.org/coi).Page 107

Policy and Pro cess

● Candidates with COI, as defined above, will not be eligible for membership on those panels where their conflicts apply.

● In general, candidates with bias, as defined above, on a particular issue will be eligible for all panel memberships; however , extreme biases, such as those likely to impair a candidate's ability to contribute to meaningful scientific discourse, will disqualify a candidate.

● Ideally, the composition of each panel will reflect a range of bias for a particular subject, striving for balance.

● Candidates who meet scientific qualifications and other eligibility criteria will be asked to provide written disclosure through a confidential questionnaire of all potential COI and bias issues during the candidate identification and selec tion process.

● Candidates should be prepared, as necessary, to discuss potential COI and bias issues.

● All bias issues related to selected panelists will be disclosed in writing in the final peer review record.Page 108 Conflict of Interest and Bias Questionn aire

High Evaporative Emissions Study Peer Review

Instructions to Candidate Reviewers

1. Please check YES/NO/DON'T KNOW in response to each question.

2. If your answer is YES or DON'T KNOW, please provide a brief explanation of the
circumstances.

3. Please make a reasonable effort to answer accurately each question. For example, to the extent a question applies to individuals (or entities) other than you (e.g., spouse, dependents, or their employers), you should make a reasonable inquiry, such as em ailing the questions to such individuals/entities in an effort to obtain information necessary to accurately answer the questions.

Questions

1. Are you (or your spouse/partner or dependents) or your current employer, an author, contributor, or an earlier reviewer of the document(s) being reviewed by this panel?

YES___ NO_ X

_ DON'T KNOW___

2. Do you (or you spouse/partner or dependents) or your current employer have current plans to conduct or seek work related to the subject of this peer review followin g the completion of this peer review panel?

YES___ NO_ X

_ DON'T KNOW___

3. Do you (or your spouse/partner or dependents) or your current employer have any known financial stake in the outcome of the review (e.g., investment interest in a business related to the subject of peer review)?

YES___ NO_ X

_ DON'T KNOW___

4. Have you (or your spouse/partner or dependents) or your current employer commented, reviewed, testified, published, made public statements, or taken positions regarding the subject of this p eer review?

YES___ NO_ X

_ DON'T KNOW___Page 109

5. Do you hold personal values or beliefs that would preclude you from conducting an objective, scientific evaluation of the subject of the review?

YES___ NO_ X

_ DON'T KNOW___

6. Do you know of any reason that yo u might be unable to provide impartial advice or comments on the subject review of the panel?

YES___ NO_ X

_ DON'T KNOW___

7. Are you aware of any other factors that may create potential conflict of interest or bias issues for you as a member of the panel ?

YES___ NO_ X

_ DON'T KNOW___

Acknowledgment

I declare that the disclosed information is true and accurate to the best of my knowledge, and that no real, potential, or apparent conflict of interest or bias is known to me except as disclosed. I
further declare that I have made reasonable effort and inquiry to obtain the information needed to answer the questions truthfully, and accurately. I agree to inform SRA promptly of any change in circumstances that would require me to revise the answers that I h ave provided.

H. Christopher Frey

______ Name

December 8, 2011 Signature DatePage 110 Conflict of Interest and Bias Questionnaire

High Evaporative Emissions Study Peer Review

Instructions to Candidate Reviewers

1. Please check YES/NO/DON'T KNOW in response to each question.

2. If your answer is YES or DON'T KNOW, please provide a brief explanation of the
circumstances.

3. Please make a reasonable effort to answer accurately each question. For example, to the extent a question applies to individu als (or entities) other than you (e.g., spouse, dependents, or their employers), you should make a reasonable inquiry, such as emailing the questions to such individuals/entities in an effort to obtain information necessary to accurately answer the questio ns.

Questions

1. Are you (or your spouse/partner or dependents) or your current employer, an author, contributor, or an earlier reviewer of the document(s) being reviewed by this panel?

YES___ NO_ X

_ DON'T KNOW___

2. Do you (or you spouse/partner or de pendents) or your current employer have current plans to conduct or seek work related to the subject of this peer review following the completion of this peer review panel?

YES___ NO_ X

_ DON'T KNOW___

3. Do you (or your spouse/partner or dependents) or y our current employer have any known financial stake in the outcome of the review (e.g., investment interest in a business related to the subject of peer review)?

YES___ NO_ X

_ DON'T KNOW___

4. Have you (or your spouse/partner or dependents) or your curre nt employer commented, reviewed, testified, published, made public statements, or taken positions regarding the subject of this peer review?

YES___ NO_ X

_ DON'T KNOW___Page 111

5. Do you hold personal values or beliefs that would preclude you from conducting an objective, scientific evaluation of the subject of the review?

YES___ NO_ X

_ DON'T KNOW___

6. Do you know of any reason that you might be unable to provide impartial advice or comments on the subject review of the panel?

YES___ NO_ X

_ DON'T KNOW___

7. Are you aware of any other factors that may create potential conflict of interest or bias issues for you as a member of the panel?

YES___ NO_ X

_ DON'T KNOW___

Acknowledgment

I declare that the disclosed information is true and accurate to the best of m y knowledge, and that no real, potential, or apparent conflict of interest or bias is known to me except as disclosed. I further declare that I have made reasonable effort and inquiry to obtain the information needed to answer the questions truthfully, an d accurately. I agree to inform SRA promptly of any change in circumstances that would require me to revise the answers that I have provided.

Eric M. Fujita

______ Name

11/14/11

_ Signature DatePage 112 Conflict of Interest and Bias Questionnaire

High Ev aporative Emissions Study Peer Review

Instructions to Candidate Reviewers

1. Please check YES/NO/DON'T KNOW in response to each question.

2. If your answer is YES or DON'T KNOW, please provide a brief explanation of the
circumstances.

3. Please make a reasonable effort to answer accurately each question. For example, to the extent a question applies to individuals (or entities) other than you (e.g., spouse, dependents, or their employers), you should make a reasonable inquiry, such as emailing the qu estions to such individuals/entities in an effort to obtain information necessary to accurately answer the questions.

Questions

1. Are you (or your spouse/partner or dependents) or your current employer, an author, contributor, or an earlier reviewer of the document(s) being reviewed by this panel?

YES___ NO_ X

_ DON'T KNOW___

2. Do you (or you spouse/partner or dependents) or your current employer have current plans to conduct or seek work related to the subject of this peer review following the complet ion of this peer review panel?

YES___ NO_ X

_ DON'T KNOW___

3. Do you (or your spouse/partner or dependents) or your current employer have any known financial stake in the outcome of the review (e.g., investment interest in a business related to the subje ct of peer review)?

YES___ NO_ X

_ DON'T KNOW___

4. Have you (or your spouse/partner or dependents) or your current employer commented, reviewed, testified, published, made public statements, or taken positions regarding the subject of this peer review?

YES___ NO_ X

_ DON'T KNOW___Page 113

5. Do you hold personal values or beliefs that would preclude you from conducting an objective, scientific evaluation of the subject of the review?

YES___ NO_ X

_ DON'T KNOW___

6. Do you know of any reason that you might be un able to provide impartial advice or comments on the subject review of the panel?

YES___ NO_ X

_ DON'T KNOW___

7. Are you aware of any other factors that may create potential conflict of interest or bias issues for you as a member of the panel?

YES___ NO_ X

_ DON'T KNOW___

Acknowledgment

I declare that the disclosed information is true and accurate to the best of my knowledge, and that no real, potential, or apparent conflict of interest or bias is known to me except as disclosed. I
further declare that I have made reasonable effort and inquiry to obtain the information needed to answer the questions truthfully, and accurately. I agree to inform SRA promptly of any change in circumstances that would require me to revise the answers that I have provided.

__ Keith Knoll

______________ Name

__ ______ __ 12/7/2011

_ Signature DatePage 114 

### Appendix C : Peer Review Charge

Charge to Peer Reviewers of Estimates of the Fraction of the Fleet with High Evaporative Emissions

based on the Ken Caryl Station (Denver, Co lorado) Field Study

Gasoline vehicles have evaporative emissions control systems that control excessive evaporative emissions. Gasoline vapors can also be evaporated liquid gasoline, if liquid leaks are present. When these systems or the vehicle’s gasol ine delivery system malfunction, excessive evaporative emissions can be emitted. Few estimates of the frequency of vehicles in just such a state in the fleet exist, though vapor leaks can have an impact on the inventory of vehicle emissions.

As part of t he effort to quantify evaporative emissions from the fleet of gasoline

- powered on

- road vehicles in the developing MOVES mobile sources inventory model, EPA would like to know the distribution of the mass of evaporative emissions across all vehicles in the fleet. Evaporative emissions occur in light

- duty vehicles when volatile 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 th e MOVES model, EPA and its stakeholders have conducted studies to be able to model these evaporative emissions in MOVES.

The Coordinating Research Council

- Real World Group through its E

- 77 and E

- 77

- 2 permeation evaporative emission testing programs has confirmed that leaks, both liquid and vapor, can be a significant part of any fleet hydrocarbon inventory. This indicated a major impact for inventory, establishing the need to define the rate of occurrence of “leakers” in the in

- use fleet. The missing p iece of information is how often the leaking vehicles are occurring. Subsequent laboratory testing in the E

77

- 2c program implanted similar size leaks, not only at the gas cap but in other locations which were indicated as high occurrence in the initial f ield testing work. EPA’s initial estimate was that “High Evaps” make up on the order of 1% of the gasoline

- fueled vehicles in the fleet but there has been evidence that this was lower than what is occurring in the real world. This report uses Colorado I/ M evaporative emission data to estimate the fractions of various levels of high evaporative emission vehicles, the prevalence of High Evaps, in the mix of vehicles that patronized the Denver Ken Caryl I/M station during the summer of 2009. Ultimately, EPA would like to know the distribution of the mass of evaporative
emissions across all vehicles in the fleet.

The study performed at the Ken Caryl IM station in Denver, CO built upon the prior CRC/EPA testing experience. Vehicles entering the Ken Caryl stat ion driveway were screened by an RSD unit using an evaporative index described as EI23. A stratified sample of model year 1961 and newer vehicles were offered participation in intensive evaporative emissions testing, which consisted of the portable sealed housing for evaporative determination (SHED) hot

- soak test, the visual, olfactory, and electronic sniffer examination of the vehicle (MCM test) and additional RSD measurements. Overall, the study reinforced an earlier connection seen between RSD and porta ble SHED values for real

- world light

- duty gasoline vehicles with testing of a wider range of model years and RSD vehicle speeds.

The objective of this report is to provide estimates of the high evaporative emission fraction of the Denver fleet based on po rtable SHED data. One estimate of this fraction can be made by de

- stratifying the portable SHED measurements collected summer of 2009 at the Ken Caryl I/M station according to the distribution of EI23 Bin values observed in the sample of vehicles that patr onized that station duringPage 115

the study period. The CRC E

- 77 and E

- 77

- 2 studies and the Lipan (Colorado) I/M Station studies all preceded the Ken Caryl study, which provides the background and data for this report.

From the vehicle selection and testing at Ken Caryl, two data sets are used to perform this analysis. The first is the set of 175 vehicles that were participants in the study and therefore received RSD measurements and portable SHED measurements. The second is the set of all 5830 vehicles that ent ered the station driveway during the study and represent the fleet of vehicles that patronize Ken Caryl. Most of these vehicles were not participants in the study and these therefore have only RSD measurements but no portable SHED measurements. The portab le SHED values of the 175 participants were de

stratified using the RSD index to estimate the distribution of portable SHED values of the 5830 vehicles that entered Ken Caryl during the study period. The results give an estimate of the fraction of “high” portable SHED vehicles for different definitions of a high portable SHED result.

The RSD and portable SHED results on the 175

- vehicle stratified sample of vehicles entering Ken Caryl was used to establish a relationship between the EI23 evaporative emissi ons index and hot

- soak emissions as measured by the portable SHED test. This relationship was then applied to the 5830

- vehicle random set, which is made up of most vehicles that entered the I/M station driveway during the study period. Standard de

- strati fication techniques are used to estimate the fraction of the Ken Caryl fleet that is expected to have portable SHED results greater than various definitions of a high portable SHED value, “cutpoint”. The de

- stratification technique is also applied to the Ken Caryl fleet as a function of model year group. A Monte Carlo simulation provides a means of estimating the influence of various uncertainties in the Ken Caryl data on the uncertainty of the calculated high portable SHED
result fraction. An estimate of the uncertainty is critical to understanding the quality of the results of a calculated high portable SHED value fraction. This, in turn, provides important guidance to EPA for using
the results of the calculations for MOVES.

You are asked to review a nd provide expert comments on the Estimates of the Fraction of the Fleet with High Evaporative Emissions based on the Ken Caryl Station (Denver, Colorado) Field Study (High Evap Study)

. You are being provided the High Evap Study under cover of this charge and will be provided a background document separately.

Your written comments should address all aspects of the report (methodologies, analysis, conclusions, and narrative) and should be sufficiently clear and detailed to allow readers to thoroughly unde rstand their relevance to the High Evap Study. Please deliver your final written comments to SRA by Friday,
December 30.

All materials provided to you as well as your comments should be treated as confidential, and should
neither be released nor discusse d with others outside of the review panel. Once EPA has made its reports and supporting documentation public, EPA will notify you that you may release or discuss the peer review materials and your review comments with others.

Should you have questions ab out what is required in order to complete this review or need additional background material, please contact Brian Menard at SRA ( Brian_Menard@sra.com ) or (434

- 817

- 4133)

.Page 116 

### Appendix D: Reviews

Peer Review of

Est imates of the Fraction of the Fleet with High Evaporative Emissions based on the Ken Caryl Station (Denver, Colorado) Field Study

Prepared by:

H. Christopher Frey, Ph.D. Independent Consultant Raleigh, NC

Prepared for:

SRA International, Inc.

December 30, 2011

This is a peer review of a report drafted by Eastern Research Group, Inc. of Austin, TX for the U.S. Environmental Protection Agency. The review was commissioned by SRA International, Inc. on behalf of

U.S. EPA.



### Synopsis

The subject report is a summary of measurements of evaporative emissions made on samples of vehicles in the Denver, Colorado area using a portable “SHED” method. The term SHED is undefined in the ERG report but refers to Sealed Housing for Evaporative Determination (SHED), and is an existing and established method for measuring evaporative emissions from vehicles. A portable SHED (PSHED) was used at a particular inspection and maintenance (IM) station in the Denver area, known as the Ken Caryl IM Station, to measure a sampl e of vehicles. Vehicles were selected for PSHED measurements based on a screening measurement made with a Remote Sensing Device (RSD). Remote sensing measurements were used to estimate a quantity “EI23.” Depending on the value of the EI23 quantity,
each vehicle passing through the screening RSD site was assigned to an EI23 “Bin.” A prior estimate was made of the probability that a vehicle in each bin would be a ‘high’ emitter of evaporative emissions. Based on the assignment to an EI23 bin, and the pri or estimated probability of being a high emitter, vehicles were invited at random for additional measurements. If the driver accepted the invitation, the vehicle underwent additional remote sensing measurements and also underwent a PSHED

measurement.

In prior work, measurements were made on a different vehicle fleet to assess the concordance between SHED and PSHED measurements. The two methods were found to produce similar results on average, with a small bias in the PSHED measurement compared to the SHE D measurement. However, there appears to be substantial random deviation of individual PSHED measurements compared to SHED measurements of the same vehicle under approximately similar conditions. A key assumption in the analysis of Ken Caryl IM Station d ata is that the PSHED measurement is a suitable substitute for the more widely accepted SHED measurement.Page 117

Based on the ‘stratified’ sample of vehicles that underwent additional measurements at the Ken Caryl IM Station, inferences were made regarding the o bserved fraction of vehicles in each EI23 Bin that had ‘high’ evaporative emissions rates according to PSHED measurements. These data were used to estimate the overall fraction of high evaporative emitters for all vehicles that entered the Ken Caryl IM

St ation during the study period. The report concludes with some comments about uncertainties in the estimates and regarding a possible future Monte Carlo study to more thoroughly quantify such

uncertainties.



### Report Writing

The review of this report was s ignificantly hampered by the very poor quality of the report organization and writing.

A key question when writing any report is: Who is the intended audience for this report? The intended audience should include all stakeholders of the MOVES model, sin ce this effort appears to be aimed at providing a technical basis for quantification of the fraction of the on

- road fleet that has high evaporative emissions rates. However, as written, the report is aimed at fellow technicians who are
familiar with the u ndefined shop jargon used by the authors. This report contains repeated sloppy use of jargon that may be meaningful to the report authors, but that make the report difficult to read by anyone else. Table 1 is a list of terms that are introduced in the te xt without definition, without adequate definition, or that should be introduced, defined, and used in the text. The list of terms in Table 1 should be used to construct a glossary for this report. When a term is first used in the text, it
should be defi ned in the text.

Table 1. Terms Introduced in Draft Report Without Definition or Explanation: these terms should be defined/explained when first mentioned. A glossary of these terms with definitions should also be
created.

Terms that Need to be Define d Comment

Aging enhanced evaporative emissions vehicles ? given lack of definition of ‘aging,’ and ‘enhanced,’ the meaning of this is unclear to the
readers.

Aging enhanced vehicles Undefined. Explain this.

Approximate algorithm No idea what this mean s. Needs to be explained.

As

- received condition Should explain what this means.

Beam block This is shop jargon. The intended meaning seems to be exhaust plume measurement. Needs to be defined/explained when first used.

Bench purged Presumably, this i mplies that the canister was removed from the vehicle and purged (how) on a lab bench. Needs more explanation for clarity.

(cont.)Page 118 Terms that Need to be Defined Comment

Bias (systematic error, inaccuracy) See comments

Bin de

- stratification De

- strat ification with respect to what? How?

De

- stratify (and de

- stratifications) This term is used without definition. Not clear what
this is.

Detection limit Mentioned on p 4

- 31 but not defined.

EI23 Mentioned numerous times without any explanation

EI23 Bin s Define when first mentioned. Introduce in a new methodology chapter prior to using this term in results chapters

Electronic HC sniffer Is this relevant to the content of the report? If not, delete. If so, then explain.

ESP ? Seems to be the name of a company. ESP, Inc.?

Evaporative emissions canister Is this a canister that produces evaporative emissions? Need to explain to the reader what this is. A corresponding conceptual diagram of the source of evaporative emissions and methods for preventio n and control of evaporative emissions would help in explaining what this (and other relevant vehicle systems or components) is.

g/Qhr Is not defined until page 4

- 4, although it is used in earlier parts of the report.

Gross liquid “leakers” Is there a qu antitative definition of this, or at least a working definition? Explain.

HC As good practice any abbreviation should be
defined when first used.

high evaps This is shop jargon. A formal technical report should have thoughtfully developed and carefully defined terminology.

High running loss emissions What constitutes “high”? by what criterion or
criteria?

High

- PSHED, and “high

- PSHED fraction” This term is shop jargon. The intended meaning appears to be “vehicles with high evaporative

emissions as me asured using the Portable SHED

(cont.)Page 119 Terms that Need to be Defined Comment

Hot 505 This is undefined. Presumably, this is a hot stabilized dyno test cycle. If so, then give the graph of speed versus time and provide some explanation.

Hot soak de fine

IM Yes, most readers will know what this is, but as good practice any abbreviation should be defined
when first used.

Implanted leak Undefined. Explain this. Give an example.

Index/PSHED This term is unclear

Intrusive pressure test What is this?

Ken Caryl Introduced asif the name of a person, this should be consistently termed “Ken Caryl IM Station” or something similarly descriptive (e.g., Caryl Station).

leakers Is there a quantitative definition of this, or at least a working definition? Ex plain.

Low evap More shop jargon. A formal technical report should have thoughtfully developed and carefully defined terminology.

Low running loss emissions What constitutes “low”? by what criterion or
criteria?

Method A Define. Introduce in methods chapter.

Method B Define. Introduce in methods chapter.

Modified California Method Define. If not relevant to this report, delete.

MOVES MOVES is mentioned but never introduced or explained.

Near

- zero vehicle Undefined. Explain this

Noise, noisy Us ed on page 4

- 31 without definition

OBD code to flag I know what the authors are trying to say, but many readers will have no idea. First, explain OBD and what is an OBD code. Explain what is meant by ‘flag’.

(cont.)Page 120 Terms that Need to be Defined Com ment

OBD evaporative codes What are these? Needs to be explained

Odometer Resolution What is the meaning of the codes given in Table 4

- 1?

ORVR ?

Precision (imprecision) See comments

Pre

- enhanced vehicles Undefined. Explain this.

Pretesting Page 4

- 2

PSHED PSHED is defined on page 1

- 1 as “portable SHED”,
but “SHED” is not defined.

RSD The term RSD is used on page 1

- 1 without
definition.

RSD Method B This method should be introduced and explained in a methodology section of the report.

Running lo ss emissions Define/explain

Seal Barometric Pressure Table 4

- 2: this term is undefined. There needs to be a footnote to explain what this is.

Seal Temperature (F) Table 4

- 2: this term is undefined. There needs to be a footnote to explain what this is

.

Selection RSD Mentioned on page 4

- 3. An “RSD” is a measurement device, but the term “RSD” is used inappropriately to refer to a measurement of a specific vehicle. The intended meaning of “Selection RSD” is “screening remote sensing
measurement.” The screening measurement is
used to determine whether the vehicle will be
recruited for addition RSD measurements and

PSHED measurements.

SHED Amazingly, SHED is not defined the first time it is mentioned, on page 1

- 1.

Slow vapor leaks What is a “slow” leak ? Does this refer to a low emissions leak? Of vapor? Of evaporating liquid? Needs to be defined and explained.

Standard de

- stratification techniques ? undefined.

(cont.)Page 121 Terms that Need to be Defined Comment

Standard I/M inspection Explain. Or, if not relevant, delete.

Stratified sample With respect to what? This term needs to be explained when first used.

Stratified set Explain in new methods chapter.

Uncertainty Should be defined

– see comments

VDF Table 4

- 2: this term is undefined. Th ere needs to be a footnote to explain what this is.

VECI Engine Family Table 4

- 1. needs to be defined in a footnote.

VECI Evap Family Table 4

- 1. needs to be defined in a footnote.

The report needs substantial copy editing by a competent technical wri ter. For example, the report contains frequent use of the first person, which is inappropriate in formal technical writing. In numerous places, statements of belief are made (e.g., “we believe”). The reader does not care what the
authors ‘believe.’ The reader cares about what is known and what is not known, and reasonable interpretations based on evidence. The report contains numerous metaphors, which are inappropriate for formal technical writing. For example, several times the authors describe what an instrument ‘sees.’ Aside from these problems there are numerous instances of unclear yet repetitive statements. If a student had handed me this draft report, I would have read a few pages and then handed it back as unacceptable.

As an example of poor writing, consider the last paragraph on page 4

- 2.

What are ‘pretesting data’? ‘All of that pretesting data was’ could simply be “These data were.”
“receive RSDs”

- this doesn’t make sense. How does a vehicle receive a remote sensing device?

T he intended meaning seems to be “were measured using remote sensing.” Having read the appendix, I cannot figure out the basis for the statement “Analysis of the EI23 index... “ “to allow the EI23 to be less dependent on an exhaust emissions, we developed EI23 Bin” is
awkward

– should be “To reduce dependence on exhaust emissions, EI23 Bins were developed.” Do not use first person. And so on. Aside from the poor wording, the key technical concepts are unclear. What are the dependences and how have they been inferred? It is frustrating to the reader to be told to go elsewhere for definition of EI23 and EI23 Bin but to be provided with details based on knowing what these concepts are, such as “EI23 Bin has integer values of 1 through 7...” These concepts a nd terms should be defined, developed, explai ned, etc., in a methods chapter prior to producing results based on these. The paragraph introduces, perhaps for the first time, the term “running loss emissions,” without definition. If EI23 Bin is central to the methods and interpretation, it is simply unacceptable to push it to an appendix and to give such short and uninformative treatment to it in the main body of the report.

Aside from the poor writing, the organization of this report should be reconsider ed. Methods and results appear to be mixed together. A good technical report will have a chapter devoted to methods, organized in a manner consistent with the order in which the methods are used later in the report.Page 122

Furthermore, this report tends to hav e too much of ‘here’s what we did’ without first introducing the purpose, key concepts, or basis/foundation.

A technical report should have the following elements:

Introduction

o states the challenge, problem, issue being addressed,

o establishes the nee d for new work

o clearly states the objectives of the work (note: objectives are not a list of tasks

– they relate to the purpose of the work) Background: Survey of relevant prior work, if needed. Also, a brief review of the types of evaporative emissions and factors to which they are sensitive is needed. For example, evaporative emissions are sensitive to ambient temperature.
Methods

o For each major component of the analysis, state the following:

 Overall purpose

 Basic concept

 Empirical or theoretical basi s established in prior work (with citations)

o Provide sufficient information regarding the methods so that someone else could reproduce the work

– include definitions of key terms, variables, equations, algorithms,
and so on

o Examples of content for this cha pter (illustrative)

 Schematic of the vehicle path through the various RSDs and PSHED

 Methods A and B for estimating plume concentrations from remote sensing

measurements

 EI23 definition and definition of EI23 bins

 Approach to ‘stratification’
Results

o Resul ts could be organized into more than one chapter if the subject matter is too much for one chapter

o Results should include a clearly summary of all input data and assumptions

o Results obtained should be from application of methods described in the methods
ch apter.

o Results should be appropriately interpreted
Conclusions

o What are the key findings that are related to the objectives stated in Chapter 1?

o What are the key conclusions that are related to the objectives stated in Chapter 1?

o What are the key recommend ations that are related to the objectives stated in Chapter
1?



### Use of Proprietary Methods

Over the years, EPA has been criticized for making public policy and developing modeling tools to support public policy that are based on proprietary data and metho ds. The use of proprietary methods precludes a full understanding and review of the underlying science. A case in point are the “Method A” and “Method B” exhaust plume analysis methods associated with the ESP remote sensingPage 123

instrumentation. Since the di stinction between Method A and Method B appears to be an important technical consideration in this study, the lack of disclosure of what these methods are is unacceptable.



### Fundamental Questions

There are some fundamental questions related to this work that should be part of the objectives and
that should be addressed in the technical results and conclusions:

1. Is PSHED a good surrogate for SHED?

2. Can an RSD, if appropriately interpreted, be a good surrogate for a PSHED measurement?

The first questi on presumes that SHED is the reference method to which all other methods should be compared. What, however, is really measured in a SHED measurement? There are many evaporative processes. Some, such as refueling, are not addressed by SHED. Which proces ses are addressed?

In what ways are PSHED measurements similar to those of SHED measurements, and in what ways do they differ? Is PSHED effectively just as good as SHED?

What kinds of evaporative processes can be measured using RSD? There is an unstate d hypothesis in this report that RSD measurements can provide information on evaporative emissions in a manner comparable to that of PSHED, if only the RSD measurement is appropriate interpreted. What is the basis for this hypothesis? What evaporative pr ocesses affect the quantity of HC that is detected by remote sensing? If there was no error in the measurement, would strong concordance be expected between RSD and PSHED? If so, why? A clearer statement of hypothesis and the theoretical underpinning fo r it would be helpful when interpreting results.



### Specific Technical Comments

Page 1

- 1. The first sentence refers to ‘further developing’ something that has not yet been defined in this report. Please, hire a technical editor and have them go through th is report very carefully. The first line is poorly written, and the report that follows is also very poorly written.

The purpose of the report is to estimate, not develop, fractions of various levels of high evaporative emissions. However, nowhere is an y justification or rationale given as to why this report is focusing on the Denver fleet. Since Denver is at high altitude, and barometric pressure is a factor in evaporation, it is not clear that data from Denver would be representative of other parts of the U.S.

A number of terms are mention on this page without definition, including SHED, Ken Caryl, RSD. This is a bad way to start a report.

Page 1

- 2 “the real investigation in this study happens in...” this kind of colloquial writing has no place in

a formal technical report by what is supposed to be one of the top environmental engineering consulting firms in the country to the Federal agency charged with quantifying and regulating air quality. This report needs to be taken more seriously by the autho rs.

Background Chapter: this chapter is plagued with undefined jargon, lack of clarity of concepts, and is poorly organized. It is very qualitative and vague and provides little to no insight on the topics beingPage 124

addressed. Examples of content missing fr om this report include a brief review of the types of evaporative emissions, factors to which such emissions are sensitive, the SHED measurement approach, how PSHED works, what is remote sensing, and how can remote sensing be used to infer information
abou t evaporative emissions. What does the RSD actually measure that is representative of evaporative emissions, and is this similar to what is measured in PSHED? Why is there an expectation that there should be agreement between evaporative emissions inferr ed from RSD measurements versus those inferred from PSHEDS? Are they measuring the same processes under similar conditions? How might they differ?

The background chapter should be followed by a new chapter 3 that provides an overview of the
methods used in this report, including a schematic of the Ken Caryl IM station, the specific instruments deployed, the analysis methods used, etc. Material that is now in Appendix A and B should be rewritten into the methods chapter.

The current Chapter 3 should be rewritten as “Assessment of Concordance Between Portable and Fixed Location Evaporative Emissions Measurements.” This chapter needs technical editing. The basic information is useful and interesting. The technical analysis should include quantification of the statistical significance of each parameter in the regression equation, the standard error of the estimate, the distribution of the residuals, a normality check for the residuals, the coefficient of determination,
and other basic information that wou ld commonly be reported as diagnostic goodness

- of

- fit indicators when developing a regression model. To what extent are results such as in Figures 3

- 4 and 3

- 5 actually providing an indication of repeatability of the test

– are the conditions really the sa me in each test? If the repeatability is really this poor, what are the implications for selecting a threshold for what constitutes a ‘high evap’ vehicle? It is more common to report 95% probability ranges, not 68% probability ranges.

Chapter 4:

A sche matic of the Ken Caryl station is needed to illustrate what is meant by the “driveway RSD unit”
and “Measurement RSDs”

What is the purpose of “stratification.”? Why is achieving stratification a goal in itself? E.g., page 4

- 3,
“to achieve stratificati on, a higher fraction of vehicles...” The reader can eventually figure this out, but why can’t the authors communicate this more clearly? The purpose seems to be to evaluate a screening procedure for identifying vehicles with high evaporative emissions rat es, but what about goals for false positives or false negatives?

Is it literally the case that six RSDs were used? i.e., six remote sensing devices at six locations? Or were the two highway “RSDs” based on repeated passes by the same RSD? The authors need to stop using the term “RSD” to refer to a measurement. RSD = Remote Sensing Device and refers to an instrument. A measurement made using an RSD could be described as a remote sensing measurement. What is an RSD beam block? This is shop jargon (I know what it means, but most readers won’t).

“These two RSDs were measured on the same RSD instrument as the Selection RSDs.” This sentence is extremely sloppy, using the term “RSD” where the concept of a ‘remote sensing measurement’ should
be used inste ad. How does a vehicle “receive” an “RSD”? I have done measurements with an RSD, and I have never seen
a vehicle receive an RSD.Page 125

What is the ‘standard I/M inspection’

– for those of us not from Denver, please explain what this is. Also, explain the “Modi fied California Method”

– both of these should be documented in the new methods chapter that needs to be written. Who does the olfactory examination? What is an ‘electronic HC sniffer”? Is this relevant to the report? If not, then delete mention of the se.

Page 4

- 4: Method A was used on ESP 4000 and 4600 instruments, and Method B was used on ESP3000 series instruments. Yet, results for both Methods A and B are reported in Table 4

- 2. Were two RSD
instruments used at each RSD site? Or were both Method s A and B applied to the same data measured from just one RSD instrument at each site? At the end of the paragraph is it mentioned that ‘code’ was
‘added’ to the 4000 and 4600 series instruments

– it would have helped if this was mentioned up front,
and i f there was a prior section that more clearly disclosed the study design in terms of what instruments were deployed at what locations and what the vehicle path was through each RSD site. It would help if this text were reorganized so that there was an in tro paragraph, one paragraph on Method A, one paragraph on Method B, and then a paragraph that compares Methods A and B. Are the CO, NO,
and CO2 results shown in Table 4

- 2 based on Method B? The distinction between Methods A and B with respect to how the y deal with exhaust versus evaporative concentrations of HC is not clear. To merely state that “ESP believes” that one method is responsive to exhaust and another is not is quite tenuous.

Page 4

- 4 (bottom): regression toward the mean.... This is stated as if it is an underlying principle in a rather didactic manner, but the actual concept is poorly explained here. A measurement is biased if it is systematically high or systematically low. If the error is randomly distributed with a mean of zero, then
the measurement is subject to random error, not bias. The random error can lead to false positives or false negatives if used in the context of a binary decision (e.g., vehicle is a high emitter). This context is not clearly articulated. False positives or false negatives are not necessarily a result of bias, but rather a result of imprecision (random error). The discussion here of bias is thus without sufficient context and
therefore is unclear.

What role does ambient temperature have in contributing to variability in estimated evaporative emissions based on RSD measurements? Since the “Temperature” in Table 4

- 2 (ambient temperature at the time of each RSD measurement?) differs from the PSHED “Seal Temperature”, what role might this have in confounding the results?

Table 4

- 2: what is the meaning of negative values for HC Method A (ppmC 3) and how are these interpreted? Table 4

- 2 values of CO 2 percent appear to be what one would expect in the tailpipe, but this cannot be what was actually measured in t he exhaust plume. How is the air

- to

- fuel ratio inferred, or is it assumed to be stoichiometric? Some discussion is needed. The text barely alludes to this. More detail is needed in a methods chapter.

Table 4

- 2: terms PSHED and RSD in caption should b e spelled out. All nomenclature in column headers need to be properly defined

– e.g., use footnotes. Is RSD temperature the ambient temperature at the
date and time of the measurement?

The quantity in Figure 4

- 1 labeled as “RSD EI23” needs to be clearl y defined. Is this based on any numbers given in Table 4

- 2? Which specific column of Table 4

- 2 is “RSD EI23”? Which specific column
of Table 4

- 2 is “PSHED Mass (g/Qhr)”? Presumably, “Measured PSHED HC at 15 Minute Soak (grams)” in
Table 4

- 2 is the same as “PSHED Mass (g/Qhr)”. However, use consistent terminology in both places to avoid ambiguity. The EI23 values need to be added to Table 4

- 2.Page 126

Figure 4

- 1 needs better formatting. Should use a much larger font size for the numbers on the axes, and

cons ider using scientific notation rather than decimals if showing a log scale. In the caption, spell out
PSHED. What is “RSD EI23”?

Table 4

- 3 is hardly a table and is not formatted well. Add a row for percentages of total to help in the interpretation. Please change the terminology

– e.g., ‘Measurement RSDs” (should be Remote Sensing Measurements).

Table 4

- 4 the term “high PSHEDs” is unacceptable. The intended meaning appears to be “high PSHED measurement” “High

- PSHED Definition” should be “High PSHE D Measurement threshold” or criterion.

What is ‘de

- stratifications’?

Page 4

- 22: what role does ambient temperature have in the estimation of EI23? The RSD measurements are made at ambient temperature. Evaporative emissions are proportional to ambient temperature (something that needs to be introduced and discussed in a background or methodology section of this report). Is the EI23 metric less responsive to evaporative emissions at lower ambient temperature? Speed is not the only factor that affects i nference of evaporative emissions.

“these Selection RSDs can be used to de

- stratify the stratified set and provide an estimate of the high

PSHED fraction of the fleet...” given the lack of clear definition of these terms, and the sloppy use of terminolog y, this sentence is unclear.

‘is not an unbiased’

– why not say ‘is a potentially biased’... positive statements are always more clear than negative statements.

Page 4

- 23: “For the RSD to be useful...” should be ‘for the remote sensing measurement to be use ful...” however, why is model year important? Earlier, a note was made that model year was not part of the EI23 binning method.

If there are multiple EI23 bin values available for some vehicles, these data should be analyzed separately to determine the rob ustness with which a vehicle is assigned to an EI23 bin. Ambiguity in assignment to an EI23 bin would be a significant factor to consider in evaluating the usefulness of this
method.

Table 4

- 5. the term “Selection RSD” needs to be changed... e.g., “screen ing remote sensing measurement”? But the table is actually of EI23 bins and model year groups, not screening remote sensing measurements. Thus, the caption is not consistent with the content of the table.

A table prior to Table 4

- 5 would be more useful... i.e. distribution of vehicles by model year groups and EI23 bins for the selected (stratified?) vehicles.

Page 4

- 24 “we will get started...” might be okay for a presentation but this is not how a technical report should be worded. Aside from this, the fi rst paragraph in Section 4.4 is unclear and is hampered by repeated use of terms that are not well

- defined. Methods for stratification and de

- stratification should be in a prior methods chapter.Page 127

Try reading aloud the first sentence of the last paragraph on page 4

- 24. It needs to be rewritten. Aside from being a run

- on sentence, it is awkward, contains repetitive points and yet is not very clear.

Page 4

- 25: The Appendix B should be part of a methods chapter given earlier in this report (could be Chapte r 3). N h is defined in Appendix B but is given a lower case symbol (n h ). To avoid confusion and ambiguity, use consistent mathematical nomenclature. “Fraction of elevated PSHEDs” is given the symbol p h , which is defined in Appendix B as the “probability ”... this is inconsistent. Either it is a frequency or it is a probability

- choose one and use the concept consistently. The standard error of fraction of elevated PHEDs is given in Table 4

- 6 based on a definition involving s h and N h , but this
definition is not given in Appendix B (it should be). The terms sample and population in the Appendix B
need some careful re

- thinking or at least more clear definition. Here, the term ‘population’ is implied to describe the total sample of 5,830 vehicles (which is actually a sample from a larger fleet). That is okay, but at least be clear as to the meaning of the term ‘population’ as used in Appendix B. W h is the fraction of the population of vehicles that fall into each EI23 bin. It is not clear as to the defin ition of “n” in Appendix B

– is this the total number of vehicles in the ‘population’? (i.e. n=5830?). L=7 (could be stated clearly). The term h is not clearly defined in appendix B in terms of other variables. Is this the
standard error of the fracti on of elevated measurements in each strata? Appendix B does not actually show how one estimates the estimated fraction of the population that is above the threshold. How was the value 0.127 estimated? This appears to the product p h W h summed over all h. Based on the numbers given in Table 4

- 6, over 75% of the estimated ‘elevated PSHEDs’ (a sloppy term) are from Bins

1

- 4, which account for over 96% of the ‘population.’

Page 4

- 27. The last sentence of the first paragraph is unclear. Rewrite. Create a flow diagram or show an algorithm to make this more clear.

Table 4

- 8. It is not very clear as to what variable is implied by “High

- PSHED Fraction...” is this based on

p h and W h defined in some different way compared to Table 4

- 6?

“It is important to und erstand that” should be deleted. “It... that” statements are passive and contain no information. The assumption of the EI23 bins is that they are bins of EI23 values. Since no assumption is made regarding model year, it is not really correct to imply that if there is a dependency on a model year that somehow the use of EI23 is inherently inappropriate. It could be that the fraction of vehicles with high PSHEDs measurements is correlated with EI23 and with model year, but that does not imply that EI23 woul d not be a useful indicator. Whether EI23 is a useful indicator can be determined with or without consideration of model year. In fact, if EI23 has a trend with respect to model year that is consistent with the trend with respect to PSHED measurements, t hen there might be increased confidence in the utility of EI23 as an indicator.

Section 4.5: the discussion here suffers from a conceptual problem related to not clearly defining what is meant by “uncertainty.” The term uncertainty is used inappropriat ely as if it refers only to imprecision, and the notion of bias is discussed as if it distinct from “uncertainty.” Uncertainty refers to lack of knowledge regarding the true value of a quantity, and includes both random and systematic
sources of error. R andom error is imprecision. Systematic error is bias and also known as lack of accuracy. Thus, bias is a component of uncertainty, not distinct from it.

Uncertainties associated with small sample size are typically quantified based on random sampling

er ror. The discussion of the role of ‘chance alone’ is inappropriate as written. Perhaps the intended statement is that if a different random sample of vehicles had been selected, the number of vehiclesPage 128

with PSHED measurements greater than 2 g/Qhr might h ave been different from the 2 that were observed in the available sample. Because the fraction of vehicles with PSHED measurements greater than 2 g/Qhr is based on a sample, there is ‘sampling error’ in the estimate. If the sample is assumed to
be random , then the error of the estimate can be estimated based on sampling distributions of the statistics (a statistic is a quantity estimated from a sample). The errors shown in Table 4

- 11 are of unclear basis. For example, the ‘size of error for ‘high PSHED Definition’ of 2 is given as 0.025. There should be more detail on how this number was estimated, based on the data given in Table 4.6.

PSHED measurement error should be more clearly discussed. The text refers to ‘two parts’ but really only one ‘measure ment error’ is actually addressed. Measurement error typically refers to the imprecision and bias of the measurement method itself. Propane retention and recovery tests are an incomplete indicator of the imprecision and bias of the PSHED method, because actual evaporative emissions are not pure propane. Variability in hot soak emissions is a measurement error only in the context of attempting to assess the repeatability of measurements of the same vehicle under the same conditions. However, it is not cl ear that such an experiment has actually been done. If there are underlying differences in the state or condition of the vehicle, then the variability in the measurements
is not because of the measurement method itself but because of the state of the vehi cle being measured. The concept of repeatability of the measurement should be discussed in a separate paragraph or subsection. If the repeatability is only

- 50% to +200%, then there is significant question as to the usefulness of any kind of PSHED test w hen compared to a ‘brightline’ threshold that is a point
value.

The discussion of detection limit and how it was inferred is difficult to follow. First, it would help to define what is meant by detection limit. It is not clear how a detection limit can be inferred by making a measurement on a vehicle or any sample for which it is not known as to whether the HC concentration is actually zero. Why not use a ‘zero’ calibration gas that contains 0 ppm of HC? A baseline before a
vehicle enters the PSHED doe s not guarantee that actual concentration was 0 ppm of HC. However, it does provide a background level. However, the text does not discuss what is background or the role of background in making measurements.

Page 4

- 32 : the analysis of duplicate EI23 measurements is quite important, and the text refers to Appendix A. Appendix A is very poorly written and very unclear. It is not apparent that there are any data regarding the duplicate EI23 values in the main body of this report or in the appendix. T he data and findings from these data should be disclosed.

The rational for the bias in the EI23 values and the implication that it would ‘tend to elevate the high

PSHED fraction’ needs to be more clearly articulated.

Page 4

- 33: the apparent confusion re garding detection limit and background level is evident in the second paragraph on this page. One does not subtract a detection limit from a measured value to impute an unbiased estimate. This would be done only for a background level. However, if the
b ackground is negligible compared to the measurement, this will have little effect on the results.

“jumps around”

– this kind of informal writing needs to be expunged from this report.

The discussion of a possible Monte Carlo simulation is so vague that i t hardly merits being in this report. Unless the authors can clearly define terms and propose a meaningful algorithm, the recommendationPage 129

for future Monte Carlo simulation could be stated briefly, with further development left to those competent to conduct such an analysis.

Chapter 5:

The lead paragraph here is probably the most coherent statement of the objective of this report. Such a
statement is needed in the introduction.

The second paragraph is not useful because it is based on evidence not provid ed in earlier parts of the
report.

The purpose of Chapter 5 is unclear. Is this meant to be a conclusions chapter? A summary chapter? A results chapter?

The third paragraph is awkward and overly didactic. One can make the point, for example, that t he use of EI23 as an indicator of evaporative emissions was explored in this work, and state the findings, conclusions, and recommendations accruing from this work. Subsequently, a recommendation can be made that the existing data could be analyzed using other indicators for the purpose of evaluating whether other indicators might be better than EI23. Whether ‘any evap index’ can be used depends on what variables are critical to an ‘evap index’ and whether they were all measured during the study at the

Ke n Caryl IM station. Since the report lacks even a basic overview of factors that lead to evaporative emissions, it is not clear as to whether all useful factors have been quantified to support development of ‘any’ evap index.

The paragraph at the bottom of page 5

- 1 is sufficiently cryptic as to be useless to anyone but those involved in the data collection or project management effort. It is not very clear as to what point is being made here.

Page 5

- 2 “to measure the RSDs”

– this makes no sense. RSDs are devices that make measurement. Why
would one make a measurement on the RSD itself?

The intent of the paragraph on “RSDs of the Denver fleet” is unclear. Perhaps this is a recommendation
to calculate EI23 for a wider set of vehicles and use the Ken C aryl IM station data for fraction of high emitters to estimate a fraction of high emitters for the larger fleet. If that is the case, the intent is
unclear.

Last paragraph on page 5

- 2

– seems to be introducing a lot of new information but in an unclear m anner such that the point(s) here are unclear.

What is the main contribution of this report? What are the key limitations? What additional work is needed? If the purpose is to estimate the fraction of vehicles with evaporative emissions exceeding a
th reshold, the method described in this report using EI23 Bins and a ‘stratification’ approach may be reasonable; however, the uncertainty in the estimates made using this method are unknown. Such uncertainties should be estimated as the next step. Without quantification of uncertainty, the utility of this approach is unclear.Page 130

Some key issues that should be addressed in the conclusions:

Is PSHED a useful surrogate for SHED? Can RSD measurements, if appropriately interpreted, provide an indicator of evapor ative
emissions?
Is EI23 a useful indicator? Are the trends in the results for high evaporative emissions fractions in the vehicle fleet consistent with model year? What results developed here provide some confidence that EI23 is operationally useful?
Wha t are limitations of EI23? What other indicators should be explored? What uncertainties have been quantified? What uncertainties have not yet been quantified? Need for further evaluation of uncertainties prior to making a decision on acceptance of this

a pproach? Application of this or other approaches to fleets that are more representative of the U.S. fleet.
Others?Page 131

Eric M. Fujita's Comments:
The objective of this study is to estimate the fractions of various levels of high evaporative emissions acros s the Denver fleet. Approach used in the study relates indices of evaporative emissions (EI23) that were derived from RSD readings to levels of PSHED hot

- soak evaporative emissions based upon correlations of a smaller stratified set of paired PSHED and
RSD readings. The experimental approach and methods are adequately documented in the report and accompanying background document. Presentation of the results, including tables and figures, are generally clear except as noted in the following comments.

The da ta show that the measured PSHED 15 minute hot

- soaks emissions are correlated with EI23, but with co nsiderable scatter (Figure 4

- 1). We can see from this plot that the detection limit for the RSD EI23 index is poor and considerably worse than for the SHED m easurements. Most of the EI23 values are clustered around 100 with corresponding PSHED emissions ranging from 0.01 to 20 g/Qhr. The preliminary study with induced evaporative emissions showed that the RSD evaporative index had a 50% chance of detecting eva porative emissions with PSHED

equivalent running loss level corresponding to about 20 g/Qhr (equivalent to EI23 Bins of 5 or below). While the EI23 evaporative index would be useful for identifying gross evaporative HC emitters, its ability to estimate fra ctions of high evaporative emissions within various levels of evaporative emission other than the top end of the distribution seems limited.
Conversion of EI23 measurements to Bins provides what appears to be clearer summary of the distribution of EI23 va lues by PSHED

- equivalent running loss levels. As I understand this procedure, this classification assigns the estimated evaporative indices into bins with width that each corresponds to one standard deviation of the variability of a single EI23 measurement (after accounting for the effects of the exhaust HC emissions on EI23). The EI23 Bins are then associated with probabilities of exceeding various threshold PSHED hot

- soak emission levels. This approach allows the association to be made without regard to t he quality of the correlation between EI23 and PSHED hot

- soak levels, which we know is poor. EI23 values in at least the first three EI23 Bins (with PSHED thresholds of greater than 1, 2 and 5 g/Qhr) are probably below the method limit of detection and are really random noise. If so, there is about equal chance that any of the EI23 values in the first three Bins has a corresponding PSHED above the threshold. Therefore, it is not unexpected that fractions of elevated PSHED in Table 4

- 6 are about the same for Bins 1 (6.7%), 2 (7.6%) and 3 (9.6%). These fractions are likely not valid given the measurement sensitivity. If 20g/Qhr is a reasonable level where the corresponding EI23 values become reliable, then the distribution shown in Table 4

- 4 for this High PSHE D definition is valid for all EI23 Bins. The fractions are progressive less reliable for the lower EI23 Bins at lower thresholds values.

I believe the net result is an overestimation of the fractions of elevated PSHEDS in the lower Bins. Products of these fractions with the proportionally larger numbers of vehicles in these bins for the Random fleet will result in larger fractions of elevated PSHEDs in the larger fleet of vehicles. For example, results of the de

- stratification calculations in Table 4

- 6 sho ws that 12.7% of the 5830 vehicles in the random sample are estimated to have corresponding high

PSHEDs defined as greater than 2 g/Qhr. If the first three Bins are counted as zero, then this fraction drops to 5.5%. Also dropping Bins 4 and both 4 and 5 re duces the fraction to 2.9% and 1.6%, respectively. The more appropriate fraction is likely between 1.6 to 5.5% rather than 12.7%.Page 132

It should also be noted that the distributions are presented without quantitative estimate of uncertainty and bias that are inherent in the study approach. In addition to the poor limits of detection of RSD evaporative index, the following sources of uncertainty and bias were not assessed in the report.

The distributions are based on static SHED 15

- minute hot

- soaks and do not include diurnal evaporative emissions and may not fully account for all running emissions.

The residual hydrocarbon signal in the RSD measurements in excess of the regression line of HC with CO 2 results is a crude measure of the diluted mixture of evaporative emissions from fuel permeation, vaporize fuel leaks, and fuel system venting during vehicle operation. Unlike exhaust pollutant, there are no tracers for evaporative HC emissions to account for dispersion rate of emissions.

Replicate LSHED and PSHED tests have large variability. Section 4.5 does not address the significance of the large variability of replicate SHED tests to distribution of fractions of “high evaps” at various definitions.

Other General Comments

1. Ambient temperature was not inc luded as a variable in the study design and PSHED and replicate RSD measurements were all made within a short time at about the same temperature. The test sets within each EI23 Bin were conducted at ambient temperature spanning a range of up to about 30 o C. Evaporative emissions are known to increase with ambient temperature with doubling of permeation for 10 o C rise in temperature. This likely would not be issue if ambient temperature was a random variable in the study and test sets within each bin had simil ar random distribution of temperature. Was this checked? The potential bias due to differences in temperature would be minimal for the high emitter bins, but may be more important for the other bins.

2. It would be helpful in Section 2 (Background) to state h ow the results of this study and similar future studies will be used in the MOVES model. Should be specific enough to identify the relevant algorithms and inputs.

3. Most vehicles in Bins 6 and 7 had high exhaust HC emissions, which can contribute to
the est imated evaporative emissions. The report asserts that this positive interference is mitigated by the binning procedure. From the relevant discussion in Appendix A, it is difficult to determine the significant of the positive interference or the effective o f the binning procedure.

4. The report does not include a summary of other testing

– modified California Method (olfactory, visual and electronic HC sniffer examination of various vehicle components). If this information is summarized elsewhere, it should be references and a brief summary of the finding should be included within this report.

Specific Comments

1. P. 1

- 2, line 5. Are there plans for follow

- on uncertainty analysis that can be described
here?Page 133

2. P. 2

- 2, second full paragraph: Describe briefly the evid ence, with appropriate references, that previous estimate of “high evaps” were lower that what is occurring in the real
world.

3. P. 3

- 14, last sentence: Meaning is unclear. Why would large variability of PSHED hot

soaks itself result in overestimation of fr action of vehicles with high hot

- soak emissions?

4. P. 4

- 1, 2 nd paragraph, line 13: Rather than “accuracy”, “representativeness” may be more appropriate in this context.

5. P. 4

- 3, 1 st paragraph, last two sentences: States that influence of variability of hot

- soak emissions will be discussed later in the section. This discussion appears to be missing.

6. P. 4

- 3, 2 nd full paragraph: References to “not simulated exhaust” and “natural exhaust” in the last two sentences are confusing.

7. P.4

- 4, 1 st full paragraph, last two sentences: The reason for selecting Method B is difficult to understand without prior knowledge that EI23 is based on residuals of the linear regression. This is only explained in Appendix A. It should be mentioned briefly in the Section 4.2 for clarit y.

8. P.4

- 11, Table 4

- 2. VDF is not defined anywhere in the report.

9. P. 4

- 24, 1 st paragraph, last sentence: Are the quantifications of uncertainties and bias part of a follow

- up report? When is this expected?

10. P. 4

- 25, Table 4

- 6: What is the basis for S h i n the calculation of standard error of the fraction of elevated PSHEDs? What are the sources of the values used in calculating the standard deviation?

11. P. 4

- 30, Table 4

- 10. Unless there is good reason for using natural log, give estimated
error for column 2 in units of g/Qhr.

12. P. A

- 1, item i): Residual rather than N?

13. P. A

- 2: Add a description of the origin of the constants used in equations shown at the bottom of the page. Explain how this reduces dependence of EI23 on exhaust HC
concentrations.Page 134 Revie w of ERG report

“Estimates of the Fraction of the Fleet with High Evaporative Emissions based on the Ken Caryl Station (Denver, CO) Field Study,”

Version 6, September 25, 2010

Reviewed by: Keith Knoll, Czero Inc. Review Date: 20 January 2012

1.0 Su mmary: The subject report describes efforts by ERG and CDPHE to estimate the occurrence of high evaporative emissions vehicles in the Denver fleet. Estimation is based on a fleet study of vehicles from the Ken Caryl I/M station using direct measurements. Three methods were employed for evaporative emissions measurement: RSD, PSHED and LSHED (Remote Sensing Device, Portable Sealed Housing for Evaporative Determination, and Laboratory Sealed Housing for Evaporative Determination, respectively). Results of
di rect measurements (mostly PSHED) from the study group are extrapolated to the broader Ken Caryl I/M fleet based on a relationship developed between RSD and PSHED results. The analysis relating RSD measurements to SHED results appears valid and well thought out. Uncertainties were investigated and sensitivity analyses were conducted. Use of RSD appears to provide considerable promise for determining high evaporative emissions vehicles from the in

- use fleet.

The limited set of vehicles (175 total) that rece ived both RSD and PSHED measurements was used to develop a correlation between RSD readings and measured evaporative emissions. This correlation was applied to the larger set of vehicles (5830 total) that visited the Ken Caryl I/M station during the summer of 2009. In this way, an estimate was made of the percent of vehicles visiting Ken Caryl over the study period that had high evaporative emissions. This projection was well justified based on results presented in the report. Speculation was also made rega rding projecting these results to the Denver

- wide fleet. Limitations associated with such a broad projection were given. Specifically it was noted that the existing dataset from the Ken Caryl I/M station was limited in relevance to the Denver

- wide fleet fo r two reasons: 1) Colorado exempts about 40% of all registered vehicles from I/M inspection based on RSD measurements and 2) the Ken Caryl I/M stations is located in an affluent section of the Denver metro area. The first caveat means that the study sample (5830 vehicles) is likely to contain a disproportionate percentage of vehicles with high emissions

– either evaporative or tailpipe. As such, the study sample is likely to be biased towards those vehicles with high evaporative emissions and is therefore n ot a random representation of the Denver fleet. The second caveat means that the study sample is likely to be composed of newer, properly functioning vehicles. Again, this introduces a bias in the database preventing it from being a random representation o f the Denver fleet. Speculation was also made regarding projecting these limited results to the nationwide fleet. Limitations associated with this larger projection were not discussed.

Specific comments for each section of the report regarding methodologi es, analysis, narrative and conclusions are given below. Many of these comments include specific recommendations to the authors for modifications prior to report publication. None of these recommendations is considered essential; the quality of the report is generally considered acceptable as

- is. However, the quality of the report could be improved with some attention to the details included below.Page 135

2.0 Background: A cursory review of CRC’s E

- 77 suite of studies is provided. The E

- 77 studies showed that v ehicle evaporative emissions do have a significant impact on the emissions inventory. Results also suggested that to quantify this impact, it would be important to determine the rate of occurrences of “leakers” in
the on

- road fleet. Per the referenced Cali fornia study (ref 5), high evaporative emissions vehicles make up about 1% of the gasoline fueled vehicles in the on

- road fleet. The ERG report suggests that this 1% estimate may be on the low side.

ERG’s prior report from the summer of 2008 (the Lipan s tudy) is also briefly reviewed. These results are particularly relevant to the current report as they explain how RSD measurements can be used to estimate vehicle evaporative emissions.

3.0 PSHED and LSHED Hot

- Soak Emissions Measurement Characteristics This study found that PSHED (portable SHED) measurements of evaporative emissions were generally higher than similar LSHED (laboratory SHED) measurements.

 Analysis showed that this bias was not likely a test order issue
 Analysis also showed that this was not a time issue (with the exception of HE

- 3555 which was shown to have continuously increasing evap emissions with time.)
 It is assumed this was an artifact of the test apparatus.

Comparison of PSHED and LSHED evaporative emissions results generally showed that scatter of the data about the parity line was equally distributed.

Comments to the report authors:  Elsewhere in the literature, estima tes are made providing comparison of PSHED results with EPA’s Tier 2 requirements for evaporative emissions. 4 It would be helpful to include that here for

context.

 It would be useful to provide some further explanation regarding HE

- 3555 evaporative
emi ssions behavior. Why did these emissions continue to increase with time? Was the evaporative purge system on the vehicle evaluated for proper functionality? Was any testing done to identify root cause?

 On page 3

- 12, the statistical analysis leading to t he conclusions that “repeated SHED hot

- soak measurements for a vehicle would fall between 40% (=1/2.51) and 251% of the vehicle’s average (characteristic) hot

- soak value 68% of the time” should include a relevant source

citation.

 The first bullet point under Summary of LSHED and PSHED states that vehicles with low hot

soak values have PSHED and LSHED results that “are very similar”. I think this statement is misleading and may not be correct. The similar scatter shown by the data across three orders of magnitude on a log

- log plot suggests that variation at low values was indeed less than at high

4 1 “Evaluation of Evaporative Leaks using RSD and Inventory Implications, ” D. Hawkins, C. Hart, C. Fulper, J. Warila, D. Brzezinski, et. al., Presented at the 19 th Annual International Emission Inventory Conference, San Antonio, TX, Sept 27

- 30, 2010.Page 136

values. But it is not clear that the data could be considered nearly the same. This assertion requires further justification from the data analysis.

 The last paragraph in this section providing relevance to the on

- road fleet requires clarification, further explanation and a review of the underlying assumptions. I believe the author is saying that because there is high scatter and a small number of sa mples available, the upper bound on extrapolating this data to the on

- road fleet is necessarily high; higher than it would be if there were either a larger number of sample or a smaller variation in the data. If this is his message, it
needs to be stated m ore clearly and with a more definitive confidence level. Also, is a normal distribution being assumed? If so, state it and explain why such an assumption is valid. If not, then what distribution is assumed and why?

4.0 Estimated High

- PSHED Fraction of t he Ken Caryl IM Station Fleet Using EI23 Bin De

- Stratification

Comments to the report authors:  Use of the term EI23 requires definition prior to use. This term is later defined in the Appendix, however, a general definition in the body of the report wo uld be useful and should be included. Also, it might be useful to include some basis for the use of this term

– where did the name “EI23” originate? ...not essential, but would be useful.

 “Stratified” data and “de

- stratified” data: It would be helpful to the reader (and still helpful to me after reading this report thoroughly) to have a better understanding of what is meant by these two terms. A layman’s explanation of these terms near the beginning of Section 4 is
advised.

 Paragraph 2 of Section 4: T he last sentence of this paragraph suggests that two influence factors complicate extrapolation of the Ken Caryl dataset to the Denver

- wide fleet. What exactly those two reasons are, however, is not clear from the paragraph text. My interpretation is

summa rized in the following bullets. Text of the paragraph should more clearly support the thesis statement given at the end of the paragraph.

1. The sample of vehicles that visit I/M stations likely has higher emissions than the fleet at

large. The Denver

- wi de “clean screening” program exempts about 40% of registered vehicles based on low RSD readings. Consequently, the 60% of vehicles that go to I/M stations are the higher emitting fraction of the total Denver fleet. Using this sample population for emission s projection to the Denver

- side fleet will likely skew the overall population estimate. However, there is no reason to believe that high tailpipe emissions vehicles are necessarily correlated with high evaporative emissions vehicles. So the real
effect of this bias is not clear.

2. The Ken Caryl I/M station is located in a higher income part of Denver. Consequently, the population of vehicles visiting this I/M station is likely to comprise newer and therefor
cleaner vehicles than the Denver fleet as a who le. As far as I can tell, this bias has no mitigating factors.

 Accurate application of the Monte Carlo simulation method assumes a random distribution and a large number of samples. This paragraph should include a statement regarding the limitations of this method for analyzing the current dataset. The author does p rovide later in this reportPage 137

adequate justification that the sample population truly is random. This was well thought

- out and well reported. Including some statement in this paragraph, however, would be helpful. I do
not believe the author addressed the lim itation of population size. This limitation should be mentioned here. Some comment regarding the potential impacts of this limitation should also
be stated.

 In Section 4.4, Table 4

- 6: It is not clear how the fourth and fifth columns are calculated from columns 2 and 3. This should be explained.

 The last sentence in Section 4.4 appears to be the beginning of an incomplete paragraph. I expected further exp lanation or evaluation of how the EI23 bins are independent of model year groups. Did some additional text get inadvertently dropped from this section?

5.0 Estimated High

- PSHED Fraction of the Denver On

- Road Fleet from De

- Stratifications Based on
Advanc ed RSD Evaporative Emissions Indices

This section of the report goes on to discuss additional data that is now available for further investigation. Limitations of the additional data are also identified. For example, the PSHED data from

Summer 2010 are i dentified as not being selected using a stratified random design. As such, these data
are not suitable to the Denver

- wide fleet.

This last section of the report leaves the estimation of the high

- PSHED fraction of the Denver

- wide fleet incomplete. No esti mation is provided because the data are identified as inadequate.

This last section of the report also provides no basis for extrapolating the results obtained to an estimate of the nationwide fleet as is needed by EPA. For EPA to apply this dataset to t he nationwide fleet (via MOVES), additional justification would be necessary.