Document ID: EPA-HQ-OAR-2003-0225-0009
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2007-11-28T05:00Z

PART B OF THE SUPPORTING STATEMENT

Populations, Usage and Emissions of Diesel Nonroad Equipment

OMB Control Number 2060-0553

USEPA Agency Form Number 2156.02

1	Survey Objectives, Key Variables and Other Preliminaries tc \l1 "1
Survey Objectives, Key Variables and Other Preliminaries 

1(a)	Survey Objectives tc \l2 "1(a)	Survey Objectives 

This collection is a pilot survey designed to inform development of
methods and protocols for programmatic collection designed to estimate
the population, usage and emissions of nonroad equipment. In this
context, nonroad equipment is synonymous with (nonroad vehicle( as
defined in the Clean Air Act:

... (nonroad vehicle( is defined as a vehicle that is powered by a
nonroad engine...( ((216 (11).

A nonroad engine, in turn, is defined as (an internal combustion engine
(including fuel system) that is not used in a motor vehicle... (or
vehicle used solely for competition),( and (motor vehicle( is defined as
(any self-propelled vehicle designed for transporting persons or
property on a street or highway( (( 216 (10)).

Because of the breadth of the category, it is simpler to define nonroad
equipment in negative  rather than positive terms. The statutory
definition includes vehicles powered by combustion engines, designed to
perform a wide variety of tasks other than street or highway
transportation. Thus, the term (nonroad equipment( covers a broad
variety of machines including lawnmowers, snowmobiles, forklifts,
crawler dozers, tractors, and excavators. Lists of equipment types
commonly used in specific economic sectors and subsectors are provided
in Appendix B.1.

The main objective of the pilot collection is to evaluate a survey
method based on a frame that lists equipment owners (commercial
establishments), rather than equipment itself. This approach is
indicated because unlike on-highway motor vehicles, nonroad equipment is
not registered by states. Thus, frame lists of equipment pieces are
impractical to construct, whereas adequate lists of establishments are
available. To achieve this goal, the pilot will answer specific research
questions:

What fraction of establishments in each targeted economic sector (e.g.,
construction, manufacturing, etc.), use diesel nonroad equipment?
Estimates of this parameter will inform estimation of the numbers of
establishments in each sector that must be drawn to obtain desired
samples of eligible engines.

What are the fractions of the equipment populations are owned by
employers or by non-employers? Do these fractions vary by economic
sector?

Can selection of counties and establishments on the basis of
(probability proportional to size( (PPS) effectively reduce differences
in sampling probabilities between individual engines? 

Do response rates differ among employers and non-employers?

What is the average number of diesel engines used per establishment? How
variable is this parameter?   Does it differ among economic sectors, or
among employers and non-employers?

What techniques can be used to access the electronic control systems of
engines so equipped (Control Area Network, CAN)? Electronic controls
became available on engines produced in during the late nineties Our
goal is to successfully access the network on 90% of engines so
equipped. 

How does engine speed as measured by  using a data-logger correlate with
that recorded through the engine’s own CAN interface For engines
equipped with CAN, our goal is to successfully correlate CAN
measurements with independent data-logger measurements on 90% of
measured engines.

A critical aspect of measuring particulate matter is to draw a
continuous sample of exhaust flow of known volume that is directly
proportional to the engine’s entire exhaust flow.  In terms of its
results, the proportionality model must achieve adequate correlation
between sample and exhaust flows. Adequacy is defined as a linear
coefficient of determination of 0.98 or better, or as a standard error
of estimation of 3% or lower at high exhaust flow.

1(b)	Key Variables tc \l2 "1(b)	Key Variables 

Variables to be surveyed or measured include:

Equipment Use Fraction. The fraction of establishments that use nonroad
equipment, where (use( means (own, rent or lease.( Only establishments
that use equipment are eligible respondents, but eligibility cannot be
determined in advance from the sample frame. This parameter will be
estimated for each targeted economic sector.

Equipment Density. This variable is defined as the average number of
diesel engines per establishment. Density can be multiplied by numbers
of establishments to estimate equipment populations at local or regional
scales.

Equipment Activity. This variable represents equipment usage, express in
terms of operating time per reference period (e.g., hours/week,
hours/month, hours/quarter, hours/year).

Engine speed:  the number of revolutions of the engine per unit time
(revolutions per minute rpm).

Coefficient of determination for independent measurements of engine
speed.

Coefficient of determination for the proportional exhaust sampling model

Emission Rates. This variable represents exhaust or (tailpipe(
emissions, expressed in terms of mass normalized to fuel consumption (
g/gal, g/kg). Emissions will be measured for the following exhaust
constituents:

-	carbon dioxide (CO2),

-	oxides of nitrogen (NOx), 

-	carbon monoxide (CO),

-	total hydrocarbon (THC)

-	particulate matter (PM).

Measurement of CO2 provides the basis for estimation of fuel
consumption and derivation of fuel-based emission rates. Oxides of
nitrogen, carbon monoxide, and particulate matter are criteria air
pollutants regulated under the Clean Air Act. Engine standards also
exist for total hydrocarbons due to their role in formation of ozone,
another criteria pollutant. 

1(c)	Statistical Approach tc \l2 "1(c)	Statistical Approach 

While not all objectives for this collection are to be evaluated
statistically, we plan to conduct employ statistical sampling.  The
reason for this approach is that we plan to continue to develop methods
of conducting emissions measurement in the field in the context of a
sampling design. It is our goal to acquire experience in the deployment
of the sample design as well as the measurement methods.

1(d)	Feasibility

 tc \l2 "1(d)	Feasibility Obstacles to Participation.  We do not
anticipate substantial obstacles to participation, because we have
modified the design and proposed collection methods that remove or
minimize obstacles that have limited participation in similar past
studies. Until recently, a statistical survey of heavy equipment
emissions would have been infeasible and prohibitively expensive. It
would have been necessary to bring equipment to an adequately equipped
laboratory, lift the engine, and place it in a test cell. This process
is slow and expensive, with costs on the order of $100,000 to conduct
measurements on a single engine. The geographic scope of any study would
also have been limited to areas where such facilities exist. Finally, it
would also have been unduly burdensome and costly for respondents to
donate their equipment for the time periods necessary to conduct
laboratory measurements.

Fortunately, the availability of portable instrumentation changes this
situation. It is now possible to (take the laboratory to the
respondent,( and to conduct measurements in the field in an efficient
and cost-effective way. We can measure emissions from heavy equipment on
site during its normal operation, using non-intrusive portable
instruments. This approach also dramatically reduces respondent burden.
Aside from responding to brief interviews, the respondent need not
modify their schedule or operation to participate. There is no need to
make time to take equipment off-site, or to operate in the absence of
key equipment pieces, because technicans can install the instruments
during down periods, and instrumentation does not interfere with the
equipments( operation. 

Availability of Funds. At present we expect to have adequate funds
available to conduct the survey as designed. Funds will be contributed
by two government partners and one industry partner. The first
government partner is the Assessment & Standards Division within the EPA
Office of Transportation and Air Quality (OTAQ). The industry partner is
the Coordinating Research Council (CRC), a nonprofit research
organization whose members include the American Petroleum Institute
(API),   the Society of Automotive Engineers (SAE), General Motors, Ford
Motor, Chrysler, Volkswagen and Honda.

However, if funding shortfalls occur, we can take measures to reduce
sampling costs. One possibility would be to reduce the number of primary
sampling units (counties), and increase the size of second-stage
clusters (sample more establishments and equipment pieces per county).
This approach would reduce costs primarily by reducing travel time to
and from PSUs. We do not anticipate that this measure would
substantially affect the survey results, because we do not expect that
intraclass correlation within counties would be high enough to
noticeably affect sampling efficiency.

Another approach that could be implemented alone or in combination with
the first would be to reduce the numbers of engines to be measured, or
reduce the measurement period for emissions measurement.

2	Survey Design tc \l1 "2	Survey Design 

2(a)	Target Population and Coverage tc \l2 "2(a)	Target Population and
Coverage 

The target population includes equipment powered by nonroad diesel
engines, as defined above in section 1, used by commercial
establishments in the construction and  manufacturing sectors (NAICS 23
and 31-33).

Work is to be conducted in two areas.  The first area  includes Clay
County, MO and Shawnee County, MO. The purpose for working in these
areas is to complete work initiated during the  previous approval
period. The second area is EPA Region 5 (including states of WI, IL, ID,
MI and OH).

2(b)	Sample Design tc \l2 "2(b)	Sample Design 

2(b)(i)	Sample Frame

 tc \l3 "2(b)(i)	Sample Frame Development 

The sample frame will include listings of commercial establishments for
the defined study area. 

In work to date, we have drawn samples of establishments from the
Comprehensive Business Samples database (CBS), compiled and maintained
by Survey Sampling, Inc., Fairfield, CT (SSI).  SSI compiles listings
from telephone directories and additional industry-specific sources,
including government listings, bank records, trade directories, city
directories and proprietary sources. Listings are verified and updated
on a continuous basis. To our knowledge, this source is the most
comprehensive listing of industrial and commercial establishments
publicly available.

In our experience, this listing has a very high rate of frame blanks,
meaning in this context that over 50% of establishments listed as
construction establishments did not report themselves as being in
construction. The high incidence of blanks requires that large numbers
of establishments must be screened to identify eligible establishments.

To address this problem, we propose to supplement SSI with one or more
additional sources. A promising candidate is a database compiled by
Equipment Data Associates, Inc. (EDA). This database is a nation-wide
compilation of Uniform-Commercial-Code filings that record transactions
in which nonroad equipment are financed, leased or used as collateral
(UCC).  EDA specializes in compiling such UCC records and marketing the
resulting database. Their typical clients include equipment dealers who
use the database to identify potential sales prospects within their
territories.  In combination with SSI, the EDA database could
substantially reduce the screening needed to identify establishments
that lease or own equipment. Another advantage of the EDA database is
that it allows construction of direct measures of establishment size in 
terms of numbers of pieces for purposes of sampling. 

2(b)(ii)	Sample Sizes

The goal is to measure emissions on 50 pieces and activity on 50 pieces,
with the possibility that both may be measured on some pieces. Due to
the methodological nature of this work, these samples are based on
practical rather than statistical considerations.

Sample sizes for interviews will be based on the amount of screening
needed to achieve the targets for measurement. Based on our experience,
it has been necessary to screen, verify eligibility and attempt
recruitment for approximately 30 establishments to obtain participation
and successful completion of emissions and activity measurements.  On
this basis, we project a need to interview up 1,500 establishments,
although this number may be lower if the supplementary frame reduces the
level of screening.

2(b)(iii)	Stratification Variables tc \l3 "2(b)(iii)	Stratification
Variables 

Due to the pilot nature of the survey, our intent has been to keep
stratification to a minimum. However, to address potential difficulties
in implementing the design, we plan to employ two levels of
stratification.

Sampling Certainty.   In the first stage of sampling, no stratification
is planned, for reasons described in ‘Sampling Methods’ below.

In the second stage, we plan to stratify establishments by size, where
‘size’ is defined as the number of equipment pieces owned or leased
by the establishment.  Establishments having more than 50 equipment
pieces will be sampled with certainty, and those having 50 pieces or
fewer will be sampled with uncertainty.

Economic Sector.  In drawing second-stage samples of establishments, we
plan to employ stratification by economic sector.  In this case, the
reason for stratification is primarily to ensure representation in each
sector.  Sampling will be allocated proportionally among sectors.

2(b)(iv)	Sampling methods tc \l3 "2(b)(iv)	Sampling methods 

To reduce travel time and associated expense for field technicians
installing and maintaining instrumentation on site, we plan to draw the
equipment sample in three stages, as follows:

First Stage	(Primary)	County or groups of counties

Second Stage	(Secondary)	Establishment (within county)

Third Stage	(Tertiary)	Equipment Piece (within establishment)

Specifics of the design at each stage are discussed in sub-section
2(b)(v), (Multi-stage sampling.(

2(b)(v)	Multi-stage sampling tc \l3 "2(b)(v)	Multi-stage sampling 

2(b)(v)(1)	First-stage Sample tc \l4 "2(b)(v)(1)	First-stage Sample 

In the previous approval period, we  rew samples of counties as primary
sampling units (PSUs) with probability-proportional-to-size (PPS)
techniques. For construction and manufacturing establishments, we used
the estimated number of employees in these sectors as a measure of size
(MOS).  Experience with this approach has shown that this MOS performed
poorly, as the correlation between the MOS used and the numbers of
equipment pieces owned by establishments is not high enough.

Additionally, we have concluded that it is logical to include
non-employers as well as employers in the study population, which would
require adoption of an MOS not defined in terms of employees.

To avoid the need for sampling by size in the first stage, we propose to
construct PSUs of roughly equal size, where size will be defined as the
numbers of establishments in the PSU, as obtained from sources such as
County Business Patterns and Census non-employer statistics. 2(b)(v)(2)
Second-stage Sample tc \l4 "2(b)(v)(2)	Second-stage Sample 

Within each PSU, commercial establishments will be the secondary
sampling unit (SSU), drawn with selection probabilities proportional to
size. The establishment MOS will be an estimate of the number of
equipment pieces owned or leased by the establishment, as constructed
from the Equipment Data Associates database.

2(b)(v)(3)	Third-stage Sample tc \l4 "2(b)(v)(3)	Third-stage Sample 

In the third stage, two to six equipment pieces will be drawn for
emissions or activity measurement from a listing of eligible pieces used
by each selected establishment (nequip).   Equipment will be selected
with probability proportional to size and usage, using a stratified
approach as shown in table B-?. In this context, ‘size’ means an
equipment pieces’s rated power, with pieces rated as <= 100  or > 100
hp as “small” and “large,” respectively.  “Usage” refers to
“life-time average usage,” calculated as the machine’s hour-meter
reading divided by its age (hr/yr).  Pieces with <= 500 hr/yr and > 500
hr/yr are classified as “low” and “high” usage, respectively. If
either size or usage cannot be classified, the piece is assigned to an
“unknown” stratum.  on each piece’s size and life-time average
usage, differential weights are assigned to each piece, also shown in
the table.

Table B-1    Differential weights assigned to equipment pieces in
third-stage sampling

Size	Life-time Average Usage (hr/yr)

	“high usage”	“low usage”	“unknown”

“large”	3	2	1

“small”	2	1	1

“unknown”	1	1	1

2(c)	Precision Requirements tc \l2 "2(c)	Precision Requirements 

2(c)(i)	Precision Targets tc \l3 "2(c)(i)	Precision Targets 

Screening interviews.

Questions targeted for statistical analysis include whether response
rates for screening interviews differ between non-employers and
employers, or between construction and manufacturing establishments. To
examine differences in response rates for screening interviews, the
numbers of establishments projected for screening interviews will allow
testing of actual response rates against a no-effect scenario with 90%
power at the 95% confidence level.

2(c)(ii)	Non-Sampling Error

 tc \l3 "2(c)(ii)	Non-Sampling Error 

2(c)(ii)(1)	Frame-coverage error tc \l4 "2(c)(ii)(1)	Frame-coverage
error 

This error is defined as potential bias in key variables resulting from
imperfections in the sample frame. One issue of concern is the presence
of (foreign elements( or (blanks( in the sample frame, where these terms
are defined as follows. (Foreign elements( are establishments listed in
the frame that are not members of the defined target populations,
whereas (blanks( are empty listings, for example, establishments that
have moved, changed names or gone out of business (Kish, 1965). However,
the central issue is incomplete coverage, in which members of the target
population are simply absent from the frame. The bias that may result
from incomplete coverage may reduce the representativeness of the sample
in a way analogous to that from whole-survey non-response. We have
incorporated measures in the survey plan to detect and reduce the
effects of these errors on the survey results.

Foreign elements and blanks. The Equipment Ownership Questionnaire
contains questions specifically designed to identify establishments that
are not members of the target population. Based on binary responses to
these questions, we can calculate a binomial proportion of foreign
elements in the frame before drawing the equipment samples. After
estimating this proportion and its confidence interval, we can use the
proportion to adjust the number of establishments drawn for the
equipment sample to achieve the desired sample sizes. 

Incomplete Coverage.  To address issues related to incomplete coverage,
we propose to employ the following measures:

We have defined target populations to correspond exactly to populations
as defined for the Economic Census and the Census Bureau’s
Non-employer statistics.  Based on these definitions, it is possible to
evaluate establishment counts in the frame to those reported by the
Census Bureau for the study areas selected.

2(c)(ii)(2)	Non-response error tc \l4 "2(c)(ii)(2)	Non-response error 

As in any survey, non-response is one of the most important potential
sources of error in final results. Survey non-response occurs when no
response at all is obtained from a potential participant in the study,
whereas (item-nonresponse( occurs when a respondent provides responses
to some but not all items. Survey non-response occurs if a respondent
refuses to participate, or if they prove to be unavailable after
multiple attempts at contact.

Item-nonresponse may occur in a number of ways. A respondent may answer
some items but refuse others, or may break off an interview for
unrelated reasons.  A form of item-nonresponse detrimental to emissions
measurement but unrelated to the respondent could occur in cases where
equipment malfunction or measurement errors make emissions or activity
datasets for specific equipment pieces unsuitable for subsequent
analysis.

2(c)(ii)(3)	Measurement error tc \l4 "2(c)(ii)(3)	Measurement error 

The measurement of emissions, and to a lesser extent activity, during
normal equipment operation requires the use of complex instrumentation
in a harsh environment. The Emissions-measurement instrument is
specifically designed to collect data from heavy nonroad equipment
during normal operation. Its components have been (ruggedized( to
withstand the sharp and powerful shocks that an object mounted to the
frame of a piece of heavy equipment experiences.  Nonetheless, despite
rugged design, additional steps will be take prior to and following data
collection to detect measurement errors in resulting data.

Calibration. Prior to installation and following removal, the
instrument(s sensors and analyzers will be calibrated. The outcome of
the calibration is an equation or system of equations that translates
voltage output from sensors into values of target variables, e.g.,
exhaust volume in the case of the flowmeter, and relative concentration
in the case of the oxygen sensor. Technicians will record settings and
results for pre- and post-calibrations. Comparison of the sets of
coefficients demonstrates that the instrument(s calibration was stable
over the measurement period, i.e., that the instrument did not show
substantial (drift( between installation and removal. During analysis,
knowledge of both sets of coefficients allows estimation of the degree
of measurement error expected for results obtained from a given machine.

Equipment malfunction. Following download of the data, additional
quality-assurance measures will be taken to verify that the instrument
operated correctly and that the results are reliable for further
analysis.  These measures involve the use of computer programs that
automatically scan the time-series for patterns that may suggest
instrument error, combined with graphic presentation of the data to
allow case-by-case visual inspection.  Quality-assurance measures are
are further described in subsection 5(a)(ii).

Respondent error. The emphasis on collection of key information for the
survey through direction inspection and instrumentation involves a
conscious decision to reduce reliance on human memory to the maximum
extent possible. A primary example is the use of electronic dataloggers
to measure equipment activity. Previous efforts in this area have relied
on one to three interview questions to solicit information on operation
or fuel usage from users of equipment such as all-terrain vehicles or
snowmobiles (CPSC, 1998; Rubin et al., 2001). Analysis of the results
obtained through such surveys shows that some proportion of respondents
give answers that seem implausible, but which are difficult to disprove
directly, or that different questioning strategies give widely divergent
results. Hence we believe that the use of instrumentation is more
objective and reliable and simultaneously reduces respondent burden.

Despite the emphasis on measurement, it remains necessary to request
respondents to report information about their operations and equipment.
As much as possible, we have restricted interview items to general
questions that can be easily answered without involved or detailed
estimation and without heavy reliance on human memory. Additionally, the
interview questions themselves, while important, primarily set the stage
for the equipment selection and measurement to follow.

Data entry error.  Information obtained through phone interviews,
personal interviews and field inspections will entered directly into
computer databases. To reduce the potential for data entry error,
(double-entry( methods will be employed. All information will be entered
independently by two persons, and the two file versions checked against
each other.

Emissions results and other data collected electronically will not be
input manually. Data files will be downloaded directly from the
measurement instrument and transferred to the database, following
quality-assurance procedures.

2(d)	Questionnaire Design tc \l2 "2(d)	Questionnaire Design 

2(d)(i)	Equipment Ownership Questionnaire tc \l3 "2(d)(i)	Equipment
Ownership Questionnaire 

The equipment ownership questionnaire will be administered to all
establishments. It is very short, containing only thirteen items
designed to support evaluation of the proposed frames in relation to
target populations, to obtain direct estimates of proposed measures of
establishment size, and to estimate proportions of eligible
establishments in each sector.

At the outset, the interviewer will identify themselves, and let the
respondent know that the call concerns a study of diesel equipment or
machinery used by organizations in the respondent(s sector. If the
respondent appears unclear on the meaning of the term (nonroad diesel
equipment or machinery,( the interviewer will read examples from a list
of equipment types commonly used. The interviewer will then briefly
describe the study, and attempt to obtain the respondent(s consent to
proceed with questionnaire items, as follows:

Item 1:	Verify Respondent(s Name and Address: This item is intended to
verify that the party contacted is in fact the intended respondent, and
whether the respondent has changed its name or address since the last
update of the sample frame.

Item 2:	Verify Respondent(s Primary Business Activity: This item
contributes to frame development by verifying that the sample frame
correctly classifies the respondent by business activity, defined as the
three-digit NAICS category. 

Item 3:	Respondent(s Diesel Equipment Usage. This item verifies that the
respondent uses at least one piece of diesel machinery or equipment,
where (use( is defined as (own,( (rent( or (lease.( Establishments that
reply in the negative are not eligible for further questions, and the
interviewer will end the interview at this point. The question solicits
a binary response, to contribute directly to estimation of the
proportion of establishments in the two-digit NAICS sector that do not
use diesel equipment as targeted by the survey.

Item 4:	Respondent(s Employer Status. This item contributes to on-going
frame development by ascertaining whether the respondent employer or
non-employer subgroups or the target population The answer will be yes
or no, with results used to estimate a proportions  of employers and
non-employers in the establishment population.

Item 5:	Self-Reported Number of Paid Employees. This item requests the
respondent to report the number of paid employees in the organization.
The response will serve as a direct self-reported estimate of the
proposed measure of establishment size for respondent group 1. The
response will also support frame development by providing a check on
classification of respondents by establishment size class in the sample
frame, measured by a proportion of correctly classified establishments.

Item 6:	Respondent(s Self-reported Number of Employees. This item is a
follow-up on item 5, if the respondent seems unable or reluctant to
report an exact number of employees in item five. It restates the
question in a more passive mode, asking the respondent to identify the
establishment size class that best fits their organization, using the
size classes listed in Table B.19.

Item 7:	Number of Equipment Pieces used by Respondent: This item serves
two objectives. The first is to get an estimate of (establishment size(
in terms of equipment pieces. Responses will be correlated in relation
to that from the supplementary sample frame, if available  This item
also provides the basis for initial estimates of the number of equipment
pieces per establishment in the target sectors.

Item 8:	Respondent(s Self-reported Number of Equipment Pieces. This item
is a follow-up on item 8, if the respondent seems unable or reluctant to
report an exact number of equipment pieces. It restates the question in
a more passive mode, asking the respondent to identify a size class that
best fits their organization, where (size( is defined in terms of the
number of equipment pieces.

Items 9-10:	Eligibility for Emissions Measurement. This item requests
respondents to report whether at least one the diesel equipment pieces
used by the organization has an engine power rating of at least 25 or 50
 horsepower or more. This criterion identifies the presence of at least
one equipment piece large enough to allow installation of the emissions
measurement instrument.  

Item s 11-12:	Respondent’s Equipment Acquisition:  These items
requests respondents to report whether they acquire equipment by
purchase, leasing or both, and whether equipment acquisition is
financed.  It contributes to evaluation of the supplementary frame
(Equipment Data Associates) by determining whether an establishment
would be expected to be present in EDA. 

	 	

2(d)(ii)	On-site Equipment Inventory tc \l3 "2(d)(ii)	On-site Equipment
Inventory 

For respondents determined to be eligible, the step following the
initial ownership interview is to obtain a listing of equipment that is
eligible for instrumentation. This listing serves as a third-stage
sample frame, and also will serve to describe the age and size
distribution of equipment used by the respondent.  The interviewer will
continue with additional questions regarding the respondent(s operation
and use of equipment. For respondents who use equipment at multiple
sites or on a continuous shift basis, additional sampling steps will be
employed as appropriate to access  equipment while retaining control of
selection probabilities for individual pieces.  The interviewer
continues with the items below:

Item 13:	Respondent(s work sites. This question is intended to determine
if a respondent has equipment stored or in operation at sites other than
the home site listed in the establishment sample frame.

Item 14:	No. work sites with equipment. This question determines the
number of work sites at which the respondent stores or uses equipment. 
If the number is greater than 1, the technicians will select one site,
using SRS, to reduce the number of sites to be visited. This step
simplifies field operations and reduces respondent burden, as it may be
impractical to schedule multiple appointments at different sites and
times to inventory all pieces used by the respondent. Also for practical
purposes, technicians may consider remote sites ineligible if they are
beyond a pre-determined maximum distance from the respondent(s home
site.

Item 15:	Listing of work sites.  The interviewer requests the respondent
to list multiple work sites at which equipment is used.

Item 16:	Additional Contact Information. If a remote site is selected,
the interviewer will request a name(s) and contact information for one
or more contacts at the remote site.

Item 17:	Contact(s Information.  The interviewer will request name and
phone number for remote contact(s). 

Item 18:	Contact times. This item requests one or more times at which
the knowledgeable respondent or remote contacts can be reached.

Items 19-20:	No. Shifts per 24-hour Period.  These items determine
whether the respondent operates equipment in shifts and whether
equipment is operated over more than one shift in a 24-hour period. The
object is to determine whether a site visit can be scheduled at any time
when all equipment would be idle. If the number is greater than one, the
technicians will select one shift, using SRS, and schedule a time to
inventory the equipment when it is off-shift.

Item 21:	Shifts Operated: If the respondent operates equipment in
shifts, the interviewer will request confirmation regarding during which
shifts equipment is operated. 

After selection of the home site or a remote site for piece selection,
the technicians will complete an inventory of all equipment pieces on
the site. They will obtain five items needed to uniquely identify
individual pieces and their specifications. These items include:

-	equipment type, 

-	equipment manufacturer, 

-	equipment model, 

-	equipment model year, and 

-	equipment serial number. 

In addition, acquisition of these items allows the technicians to
determine other equipment specifications directly without burdening the
respondent with additional highly specific questions. For example, the
equipment serial number allows determination of the equipment model year
through commercially available serial number guides (EquipmentWatch,
2001a). Determination of manufacturer and model also allows
determination of other specifications such as power and speed ratings
from commercially available specification references or manufacturers(
specifications (EquipmentWatch, 2001b). Again, the goal is to avoid the
need to trouble respondents with detailed questions that are difficult
to remember or that may require consultation of records.

Equipment Piece Selection (Third-stage sampling). To select equipment
pieces, interviewers will perform sampling with probability proportional
to weighting as described above.  After selection of an eligible
equipment piece for either emissions or activity measurement,
interviewers will confirm the owner’s consent to instrument the piece.

2(d)(iii)	Equipment Identification, Description and Instrumentation
Parameters tc \l3 "2(d)(iii)	Equipment Identification, Description and
Instrumentation Parameters 

In the course of instrumenting an equipment piece, the technicians will
acquire additional information necessary to properly install the
instrument(s) and reduce and apply resulting data. This information will
be provided by technicians directly or obtained through direct
inspection of the equipment piece itself. The respondent need not be
present and acquisition of this information imposes no additional burden
on respondents. Each information block is briefly described below.

Equipment Selection: This block contains information needed to determine
the selection probability for the selected piece:(1) the number of sites
from the piece(s site was chosen, (2) the number of shifts over which
equipment operated, and (3) the number of eligible pieces at the site.

Equipment Description: This information duplicates the information
obtained during the site inventory, which again serves to uniquely
identify the piece to be instrumented, and provide a means to determine
the piece(s detailed specifications.

Hour-meter: Whereas motor vehicles typically have odometers that record
the number of miles traveled by the vehicle, nonroad equipment often has
hour-meters that record the number of hours operated.  This item records
the piece(s hour-meter reading, if available, plus auxiliary information
needed to use the reading to estimate the piece(s average lifetime
annual activity (hours/year).

Visual inspection: This block records results of an inspection to
determine whether an  instrument can be installed on the piece. For
example, a piece with major leaks evident in the exhaust system cannot
be instrumented for emissions, because the exhaust flow volume cannot be
accurately measured. Similarly, an unreliable alternator speed signal
precludes installation of either instrument, because engine speed cannot
be accurately measured.

Date & Time: This block records the date and time for installation and
removal of an instrument.

Engine rating: This block stores the engine(s speed and power ratings.
This information, whether determined from the engine plate or from a
reference source, is vital in assessing the reliability of data
collected by the instrument.

Installation parameters. This block primarily contains exhaust pipe
measurements used in installation of the flowmeter on the outlet.

Instrument identification: This block indicates the type of instrument
installed and uniquely identifies the components of a specific
instrument.

Instrument calibration: This block identifies calibration curves for
the emissions measurement instrument. Each instrument is to be
calibrated prior to installation and following removal from an equipment
piece. The calibration equations, which are unique to each instrument,
convert voltage signals from different sensors into appropriate units.
For example, the flow-meter calibration converts voltage to exhaust flow
volume, and the oxygen sensor calibration converts voltage to oxygen
concentration. Comparison of pre- and post- calibrations is a
quality-assurance step that ensures that the sensors were stable over
the measurement period.

Maintenance Log: This log records the reason and outcome of visits, if
any, during a measurement period to tend or maintain an instrument. It
will record the reasons for a visit, any actions taken and the outcome
in relation to the acceptability of data collected prior to the visit.

3	Pretests and Pilot Tests tc \l1 "3	Pretests and Pilot Tests 

3(a)	Pretests tc \l2 "3(a)	Pretests 

As the instruments proposed for this collection have been tested and
fielded,  we do not plan additional pre-testing.

3(b)	Pilot Tests tc \l2 "3(b)	Pilot Tests 

At the outset, of the collection, an initial PSU will be fielded as a
test of the instruments, sampling, recruitment and logistics involved in
implementing the collection.  These interviews and site visits will
serve to further test the revised instruments and modify questions or
items found to be unclear or impractical. Following completion of the
initial samples, respective quality-assurance steps and operating
procedures will be finalized before the resumption of data collection
and field measurements.

4	Collection Methods and Follow-up tc \l1 "4	Collection Methods and
Follow-up 

4(a)	Collection Methods tc \l2 "4(a)	Collection Methods 

The initial screening and eligibility interview will be administered by
phone. This method was selected due to the simplicity and brevity of the
initial interview. The interview was designed so that a respondent with
knowledge of the establishment(s operation will be able to quickly and
easily provide answers to all items without a need to consult associates
or records. Using telephone as the collection mode will also enable
interviewers to identify and make contact with a knowledgeable
respondent, especially for large respondents where targeting a mail-out
questionnaire to a knowledgeable respondent would be difficult.

Due to the simple factual nature of the interview questions, it is more
important that interviewers have training and experience in recruitment
and interview methods than extensive technical knowledge in the survey(s
subject matter. Nonetheless, project-specific training for interviewers
will be provided, and will cover an introduction to common equipment
types in the targeted economic sectors, as well as the NAICS
classification of the target sectors to the three-digit level.

After obtaining consent to instrument an equipment piece, equipment
emissions and activity will be measuring using electronic
instrumentation. 

To install and maintain the instruments, technicians require knowledge
of basic physical and chemical concepts involving measurement of
compressible air-flow and concentrations of chemical constituents at
variable temperature and pressure conditions, and calibration and
operation of standard laboratory and electronic instrumentation. An
associate(s or higher degree in engineering technology, engineering or
related physical sciences will be considered adequate academic
preparation. In addition, technicians will be provided with intensive
project-specific training in the conceptual basis and practical aspects
of instrument installation and operation. To review and interpret data
for purposes of validation and quality-assurance, knowledge of the
design, operation and emissions characteristics of diesel engines is
required. Personnel reviewing and interpreting data will have bachelor(s
or higher degrees in engineering or related physical sciences.

4(a)(i)	Emissions measurement tc \l4 "4(a)(ii)(1)	Emissions measurement 

Exhaust emissions will be measured using portable on-board
instrumentation. These systems enable quick and inexpensive measurement
of emissions from heavy equipment during normal operation. In addition
to their portability, the instruments are non-intrusive. Installation
does not require removal of any components or modification of the
equipment piece in any way. A team of several technicians can install
the instrument while the equipment is not operating or off-shift,
without assistance from the respondent. Once installed, the instrument
does not interfere with the equipment(s normal operation. 

Within the instrument, different sensors measure key engine parameters
during normal operation, at intervals of one second (1.0 hertz). Primary
parameters measured include:

-	engine speed (revolutions per minute, rpm),

-	oxygen concentration in the exhaust stream ([O2], percent by weight,
wt%),

-	oxides of nitrogen concentration in the exhaust stream ([NOx], parts
per million, ppm),

-	carbon monoxide concentration in the exhaust stream ([CO], percent by
weight, wt%)

-	total hydrocarbon concentration in the exhaust stream, ([THC), parts
per million, ppm)

-	particulate concentration in the exhaust stream ([PM], ng/m3)

-	ambient temperature ((C),

-	exhaust temperature ((C),

-	relative humidity (%), and

-	barometric pressure (kilo-Pascals, kPa).

-	date/time stamp

Collection of the primary parameters observed allows derivation of
secondary parameters, which include the key variables for the survey. 
Derived measurements include:

-	exhaust flow volume (adjusted to standard temperature and pressure,
cu. ft/min),

-	fuel flow volume (kg/sec),

-	carbon dioxide emission rate (kg/sec, kg/gal),

-	pollutant emission rates for NOx, CO, THC, and PM,  (g/sec, g/gal).

The typical measurement period for emissions will be one work day.

4(a)(ii)	Activity measurement tc \l4 "4(a)(ii)(2)	Activity measurement 

Equipment usage or activity will be measured by on-board
instrumentation, based on tested, (off-the-shelf( technology.  The
instrument is very simple, consisting of a data-logger that records when
the engine is turned on and off, along with an associated date/time
stamp.  These data allow the characterization of when and how long the
equipment was operated while the instrument was installed.

These instruments are also non-intrusive, and do not interfere with
normal equipment operation. Active tending by a technician during data
collection is not required, nor is tending or effort on the part of the
respondent is required.

The target measurement period for activity approximately one month. This
period is long enough to directly measure daily, weekly and monthly
usage, and with appropriate caution, also allows reasonable
extrapolation to annual periods.

4(b)	Contacts and Expected Response tc \l2 "4(b)	Contacts and Expected
Response 

4(b)(i)	Contact and Followup Schedule tc \l3 "4(b)(i)	Contact and
Followup Schedule 

The goal for the initial interview is to make contact with a
knowledgeable respondent by phone and to complete the Equipment
Ownership interview over a period of approximately two weeks. At the
outset, each contact will be mailed a letter that describes the survey,
stresses importance of response, and lets the contact know that they
will be contacted by phone for a brief interview.

After mailing the letter, interviewers will attempt to contact the
respondent by telephone over a period of two work weeks.  Interviewers
will make repeated attempts to reach respondents, and will rely on their
experience and judgment in deciding how to reach particular respondents.
Interviewers will document each attempt and its outcome. Information
recorded for all contacts will include date, time, outcome, any
comments, and the interviewer I.D. number.

Following completion of the interview, if the respondent is eligible,
the interviewer will solicit participation for emissions or activity
measurement. After obtaining consent, the interviewer will make an
appointment for an additional  site visit, as necessary. At a mutually
agreed-upon time, the interviewer and one or more technicians will
complete the site inventory and the on-site equipment inventory and then
select an equipment piece for instrumentation. After confirming consent
to instrument a particular piece, the technician will arrange a time to
return to the site to instrument the piece while it is off-shift.
Following selection of an equipment piece, the technician will complete
the Equipment Identification, Description and Installation Parameters at
the time of instrumentation.

4(b)(ii)	Calculation of Response Rate tc \l3 "4(b)(ii)	Calculation of
Response Rate 

The target response rate for the survey will be 75%. This target value
applies separately to both the establishment and equipment samples. In
addition, separate response rates will be calculated for each key
variable, as appropriate, to address both whole-survey and item
non-response. For a specific key variable, the response rate will be
calculated as:

where terms as defined as follows:

-	total completions: the number of useable responses obtained following
all follow-up steps.

-	total contacts attempted: defined as the sum of:

(1) total completions, as above,

(2) unuseable responses, and

(3) refusals, defined as establishments contacted that decline to
respond following all follow-up steps and a reasonable waiting period,

 less the sum of:

(4) ineligible establishments, and

(5) establishments proving unreachable at addresses and phone numbers
listed in the sample database. 

The sum of (2) and (3) will be designated as total non-response. With
respect to item (4), note that eligibility is defined differently for
the establishment and equipment samples.

Follow-up efforts will characterize establishments or households that
decline to participate or fail to respond. General data items, such as
industrial category, establishment size, and geographic location can be
readily compiled from the sampling frame. 

4(b)(iv)	Nonresponse Followup tc \l3 "4(b)(iv)	Nonresponse Followup 

To address issues related to item or survey non-response, we plan to
derive non-response adjustment weights, as described in sub-section
5(b)(ii), (Non-response adjustment weights.(

We also plan to conduct analyses to detect and estimate the magnitude
and direction of frame-coverage and non-response biases, as described in
sub-sections 2(c)(ii) (Non-sampling error,( and 5(b)(iv) (Bias
detection.( These analyses will be performed for each key variable, as
appropriate.

5	Analyzing and Reporting Survey Results tc \l1 "5	Analyzing and
Reporting Survey Results 

5(a)	Data Preparation tc \l2 "5(a)	Data Preparation 

5(a)(i)	Interview and Equipment Inventory Information tc \l3 "5(a)(i)
Interview and Equipment Inventory Information 

Phone interviewing will be conducted using computer-assisted telephone
interviewing (CATI). 

When conducting site inventories, technicians will record respondents(
information on paper data sheets. At the end of each shift or workday,
personnel will enter results into computer files to prevent loss of data
should the originals be lost or damaged.

5(a)(ii)	Emissions and Activity Data tc \l3 "5(a)(ii)	Emissions and
Activity Data 

Technicians will download emissions and activity data directly from the
instruments prior to removal. Following calibration and
quality-assurance, these data will be loaded into the Mobile-Source
Observation Database (MSOD), a relational database of emissions
measurements and supporting data developed and maintained by the USEPA
National Vehicle and Fuel Emissions Laboratory.

During the process of loading the data into MSOD, quality assurance
measures will be taken to ensure that the instruments were operating
correctly and that the data are reliable for further analysis. Computer
programs have been written and tested that detect problems in
time-series data. 

In addition, computer programs have been written to graphically
represent the entire time-series for an equipment piece on a daily and
hourly basis. These plots allow visual inspection of an entire dataset
for irregular or unexpected behavior in the engine(s operating
parameters, and also to compare measurements to ranges expected, given
the size of the machine.  A variety of comparisons of this type can be
made:

-	Idle and peak engine speeds can be compared to the engine(s ratings.
For example, diesel engines typically idle at speeds between 550 and 750
rpm, and peak speeds are typically around 2,200-2,300 rpm.

-	Ambient temperatures should increase gradually during the day,
decrease at night, and be reasonable given the date and location of the
measurement.

-	Exhaust flow volume should be in a reasonable range given the size of
the engine.

-	Exhaust flow temperatures should increase sharply and exponentially
when the engine shifts from idle to work, and should decline
exponentially and stabilize during extended idle.

-	Oxygen concentrations should not exceed 21% and never be less than 0%.

Again, graphs will be interpreted on a case-by-case basis by engineers
and scientists, who will decide whether to reject portions of datasets
or entire datasets for individual machines.

5(b)	Data Analysis tc \l2 "5(b)	Data Analysis 

5(b)(i)	Multi-stage Sampling Weights tc \l3 "5(b)(i)	Multi-stage
Sampling Weights 

Three-Stage Equipment Sample. The three-stage selection probability for
an equipment piece will be product of the first-, second- and
third-stage probabilities (PPSU, PSSU and PTSU, respectively), given by

Where	n1 =	the number of counties (PSUs) in the first-stage sample (30),

n2 =	the number of establishments (SSUs) in a given PSU,

n3 =	the number of equipment pieces (TSUs) in a given SSU,

w3 =	the weight assigned to each equipment piece, depending on its size
and activity classes,

nPSU =	total number of PSUs in the study area,

MOS2 =	the measure of size value for a given PSU,

MOSPSU	 =	the measure of size value for the entire study area, equal to
the sum of all MOS2.

The third-stage sampling weight for each piece is the reciprocal of the
sampling probability, or 1/Ppiece. Similarly, the second-stage sampling
weight for each establishment will be calculated in a manner identical
to that for the equipment sample, except that the final stage is the
establishment, rather than the equipment piece. The two-stage selection
probability Pestabl will be given by P1P2, as defined above, and the
corresponding second-stage sampling weight wsample,2 will be given by
1/Pestabl.

5(b)(ii)	 Analysis of Key Variables tc \l3 "5(b)(v)	 Analysis of Key
Variables 

The section describes analyses designed to derive the key variables for
the survey. Evaluation of these results will provide answers to the
survey(s research questions. All analyses will incorporate the use of
final sampling weights.

5(b)(ii)(1)	Frame Blank Fraction  tc \l4 "5(b)(v)(1)	Frame Blank
Fraction  

This parameter will be defined as the proportion of blank elements in
the sample frame, calculated separately for each economic sector. It
will represent the proportion of establishments that have moved out of a
PSU, have gone out of business, or who prove unreachable based on the
frame listings. The proportion will be defined as the ratio of the sums
of final second-stage weights for establishment listings determined to
be blanks (YES) and all listed establishments (YES+NO), given by

5(b)(ii)(2)	Equipment Use Fraction tc \l4 "5(b)(v)(2)	Equipment Use
Fraction  

This parameter will be defined as the proportion of establishments in
each target sector that use diesel nonroad equipment. We will calculate
it from the results of the screening interviews, based on item 7 of the
Equipment Ownership Questionnaire. It will be defined as the ratio of
the sums of final two-stage weights for those establishments reporting
use of equipment (YES) and all establishments (YES+NO), given by

5(b)(ii)(3)	Equipment Density (D) tc \l4 "5(b)(v)(6)	Equipment Density
(D) 

Equipment density will be defined as the number of pieces of diesel
equipment per establishment in a given economic sector (Dsector),
calculated as the weighted mean

where w2 are sampling weights and nequip,j is the equipment count for
establishment j, out of a total of nestabl establishments in the sample.
 Equipment density provides a means of estimating equipment populations
for larger areas such as states or Region 7, as the product of Dsector
and estimated establishment populations, as reported by the Economic
Census or the Census of Agriculture.  Calculation of variances and
standard errors for Dsector will give estimates of the magnitude of
sampling error in the resulting equipment populations.

5(b)(ii)(4)	Engine speed correlation

For engines equipped with electronic controls, we will acquire two
independent measures of engine speed, one through the machine’s
control area network (CAN), and a second from a separate datalogger. For
purposes of quality assurance, the goal is to correlate the data logger
measurement against that obtained from the CAN. The correlation will be
performed for all eligible engines measured, with the goal of achieving
a simple R2 of 98% for at least 95% of engines measured.

5(b)(ii)(5)	Verification of Exhaust Flow Sampling

For engines instrumented for emissions measurement, proportional sample
flow volume will be correlated with total exhaust flow volume. This
analysis will be repeated for all instrumented engines, with the goal of
achieving a simple R2 of 98% on at least 95% of measured engines.

5(c)	Reporting Results tc \l2 "5(c)	Reporting Results 

Results of the survey will be made available to the public and within
the Agency through the following means:

Mobile-Source Observation Database. Results of the survey will be
uploaded into Mobile Source Observation Database (MSOD).  The MSOD is a
database of emissions measurements and supporting data, developed and
maintained by the USEPA National Vehicle & Fuel Emissions Laboratory.
Results for key variables plus necessary supporting data, such as final
sampling weights, will be entered. However, the identities of
respondents will be protected. Any information that could serve to
identify a specific respondent will not be entered, or will be modified
so as to prevent indirect disclosure of the identities of respondents.
Disclosure prevention methods will be applied in described in Part A,
3(f).  This database is available to the public upon request, in CD-ROM
format.

Data Sharing.  Results or summaries of results will be made available to
respondents and study co-sponsors, upon their request. 

Guidance Development. Based on survey results and experience gained
during the conduction of this collection, we plan to draft a guidance
document for states or other interested parties to initiate similar data
collections to meet regional and local data collection needs.  States
and their regional Air Quality Associations have a strong demand for
emissions inventory data that is more specific geographically than EPA
can provide. Given the availability of portable instruments for 
emissions and activity measurement, a guidance will provide a blueprint
for state and local agencies to follow to develop representative
emission inventories at regional and smaller scales.

REFERENCES tc \l1 "REFERENCES 

Consumer Product Safety Commission. 1998. Report on 1997 ATV Exposure
Survey. Part I, All-Terrain Vehicle Exposure, Injury, Death, and Risk
Studies. Directorate for Economic Analysis, Bethesda, Maryland.

EquipmentWatch.( 2001a. 2002 Serial Number Guide. 34th Edition, PRIMEDIA
Business Directories & Book Group, San Jose, CA.

EquipmentWatch.( 2001b. Specification Reference Book for Heavy
Construction Equipment and Cranes. 8th Edition, PRIMEDIA Business
Directories & Book Group, San Jose, CA.

Kish, L. 1965. Survey Sampling. John Wiley & Sons, New York.

United States Census Bureau. 2000. 1997 Economic Census: Construction,
Subject Series. U. S. Department of Commerce, Economics and Statistics
Administration. EC97C23S-IS.

APPENDIX B-1

Questionnaires

Screening and Equipment Inventory InterviewsPopulations, Usage and
Emissions of Diesel Nonroad Equipment in EPA Region 7

Integrated Sample Full Interview  

Phase 01 (EOI) and Phase 02 (Inventory/Instrumentation)

INTRO PHASE 01

Hello.  May I speak with <FIRST NAME> <LAST NAME>?  My name is ________
and I am calling on behalf of the Environmental Protection Agency. We
are conducting a study with construction companies about the diesel
equipment and machinery used in their daily operations.  

REPEAT INTRO ONLY IF REFERRED TO A MORE KNOWLEDGEABLE RESPONDENT 

Hello, Mr./Ms. <FIRST NAME—DO NOT READ> <LAST NAME>?  My name is
________ and I am calling on behalf of the Environmental Protection
Agency. We are conducting a study with construction companies about the
diesel equipment and machinery used in their daily operations. IF
NEEDED: Examples of the types of equipment that we’re interested in
include, 

Loaders 			Dozers 				Generator sets 			Cranes				Excavators 			Backhoes

Paving/surfacing equipment 	Backhoes			Forklifts

Graders 			Off-highway trucks 

We would like to do a brief survey with you that lasts less than ten
minutes. Your company was scientifically selected for this study.  Your
participation is voluntary and your name and company will not be
connected with your answers in any way.  .  

1.  First, I would like to verify that your organization is
<Establishment Name> and that your address is <Establishment Address>. 
Is this correct?

	YES					01

	NO					02

	DK					98

	RF					99

IF ‘NO,’ OBTAIN UPDATED ADDRESS OR ESTABLISHMENT NAME.

2.  Now, I would like to verify that your organization’s primary
function is construction-related.  Please specify whether you perform
one or more of the following construction-related services.  

Building, developing and general contracting			01

Heavy construction			02

Special trade contractor			03

Concrete contractor			04

Water well drilling 			05

Structural steel erection			06

Excavation			07

Wrecking and demolition			08

Machinery or equipment installation			09

OTHER (SPECIFY)			97

DK				98  	TERMINATE 01

RF				99	TERMINATE 01

  Does your organization own, rent or lease at least one item of
equipment or machinery that runs on diesel fuel?  IF UNSURE READ
EXAMPLES FROM ATTACHED LIST FOR APPROPRIATE PRIMARY FUNCTION SPECIFIED
IN Q2.

	YES			01

	NO			02	TERMINATE 01

	DK			98	ASK FOR MORE 

KNOWLEDGEABLE PERSON

	RF			99 	ASK FOR MORE 

KNOWLEDGEABLE PERSON

	

Aside from owners, proprietors or partners, did your organization have
one or more paid employees at any time during the last twelve months?

	YES			01

	NO			02	TERMINATE 01

IF NECESSARY, CLARIFY THAT ‘PAID EMPLOYEE’ INCLUDES FULL OR PART
TIME, PERMANENT, TEMPORARY OR SEASONAL EMPLOYEES.

  How many paid employees work for your organization? 

		Specify Number		_________		SKIP to Q.7

		DK ( PROBE FOR BEST GUESS Q.6			98

		RF ( PROBE FOR BEST GUESS Q.6			99

  I’m going to read you some numbers. Stop me when you think I get to
the one that best describes your organization.

	2 to 4 employees	01

	5 to 9 employees	02

	10 to 19 employees	03

	20 to 49 employees	04

	50 or more employees	05

	DK	98

	RF	99

 Earlier you mentioned that you owned, rented or leased at least one
piece of equipment.  About how many pieces of diesel equipment or
machinery are used by your organization?

	SPECIFY NUMBER	_________ 	SKIP to Q.9

	DK	98

	RF	99

8.  I’m going to read you some numbers.  Stop me when you think I get
to the one that best describes the number of equipment units or machines
are used by your organization

	1 to 4 pieces	01

	5 to 9 pieces	02

	10 to 19 pieces 	03

	20 to 49 pieces	04

	50 or more pieces	05

	DK	98

	RF	99

Of the equipment you’ve told me about, does at least one piece have a
25-horsepower or larger engine?

	YES	01

	NO	02	

	DK	98	

	RF	99	

Does at least one piece have a 50-horsepower or larger engine?

	YES	01

	NO	02

	DK	98

	RF	99

Do you buy any or have you bought any of the equipment that you use?

	YES	01

	NO	02	GO TO Q.13

	DK	98	GO TO Q.13

	RF	99	GO TO Q.13

12. When your company buys equipment, do you finance the purchase?

	YES	01

	NO	02

	DK	98

	RF	99

<SCRIPT NOTE:  END OF EOI>

14-INTRO: FOR ALL RESPONDENTS:

To help EPA gather emissions data on diesel off-road equipment we’d
like to list the equipment your company uses and then take measures on
one or two pieces.  This would involve sending a technical specialist to
inventory the equipment at one of your worksites and scientifically
selecting one or two pieces for instrumentation.  Trained technicians
would install the instrument before a workday begins and remove it after
the workday ends.  The process doesn’t affect equipment performance in
any way.  And you or someone from your company are welcome to observe
the installation. 

Do you have any questions about this phase of the study before I ask you
just a few more questions?

PROGRAMMER NOTE:

NEED A DISPOSITION AT THIS POINT TO MONITOR RESPONDENT BAIL OUT RATE.  

Is all of your equipment located at your company address <READ ADDRESS>
or do you also have equipment located or in use at other work sites?

	Equipment is all at company address	01 	Skip to Q.17

	Equipment is at other work sites	02

	DK	98	

	RF	99

IF Q14 = DK/RF (98 or 99) ASK FOR MORE KNOWLEDGEABLE PERSON AND REPEAT
14-INTRO, PREFACED WITH THE FOLLOWING:

Hello.  My name is ________ and I am calling on behalf of the
Environmental Protection Agency. We are conducting a study with
construction companies about the off-road diesel equipment and machinery
used in their daily operations.  <INSERT NAME OF PREVIOUS RESPONDENT>
has been participating with us on this study and has referred me to you
as the person more knowledgeable about the equipment and machinery used
by your company.  Let me tell you about it. CONTINUE WITH 14-INTRO.

At how many sites or facilities do you have equipment stored or in
operation?

	ENTER NUMBER: 	

	 

Okay, we would like to select one of those sites at random, list the
equipment there and select at least one piece of equipment for
instrumentation.  What is the name and location (address and city is
okay) of each of the sites or facilities where you have equipment stored
or in operation?

	LIST ALL SITES:	

INTERVIEWER OR PROGRAMMER:  RANDOMLY SELECT ONE SITE.

We would like to inventory equipment at the <SITE DESCRIPTION>site.  Is
there someone at the site that we should contact to schedule an
appointment and let know that we have permission to visit the site and
inventory the equipment?

	NO, I AM THE CONTACT	01	SKIP TO Q19.

	YES	02 

What is the name and phone number of this person(s)?

	ENTER NAME1:	

	ENTER PHONE1:	

	ENTER NAME2:	

	ENTER PHONE2:	

	

What would be the best times to contact < you or that person/them>?  

	ENTER TIME1:	

	ENTER TIME2:	

At this site, do you have equipment operating around the clock, in
shifts?

	YES	01

	NO	02 	TERMINATION 02

	DK/NOT CERTAIN	98	TERMINATION 02

Does the equipment operate more than one shift in a 24-hour period?

	YES	01

	NO	02 	TERMINATION 02

	DK/NOT CERTAIN	98	TERMINATION 02

Okay, what are the shifts that typically operate over a 24-hour period?

	RECORD TIMES OF SHIFTS		TERMINATION 02

	DK/NOT CERTAIN		TERMINATION 02

 

TERMINATION TEXT:  

TERMINATION 01 (RESPONDENT IS NOT QUALIFIED). Thank you.  Those are all
the questions I have.  We appreciate your taking time to help with this
study.

TERMINATION 02 (RESPONDENT IS QUALIFIED).  Thank you.  In the next few
days, a technical specialist will call to schedule a time to perform the
inventory at <name of site>.  We appreciate your taking time to help
with this study. 

  SEQ CHAPTER \h \r 1 

APPENDIX B-2 tc "APPENDIX B-3" 

Equipment Identification, Description and Instrumentation Parameters

EQUIPMENT SELECTION 

Respondent ID __ __ __ __ __ __ __ __ __ __	PieceID __ __ __ __ __ __ __
__ 	Date:__ __/__ __ /__ __ __ __

EQUIPMENT DESCRIPTION

Equipment Type:

Equipment manufacturer:	Engine manufacturer:

Equipment model:	Engine model:

Equipment model year:	Engine model year:

Equipment serial no.:__ __ __ __ __ __ __ __ __ __ __ __.	Engine serial
no.:__ __ __ __ __ __ __ __ __ __ __ __.

Equipment Plate Code: ___ ___.	Engine Plate Code: ___ ___.

Equipment Comments:

	Engine Comments:

Equipment Plate Codes:

01 = Not present

02 = Cannot locate

03 = Present but not specs not legible

04 = Present and legible

05 = Other	Engine Plate Codes:

11 = Not present

12 = Cannot locate

13 = Present but specs not legible

14 = Present and legible

15 = Other

HOUR-METER

Hour-meter function code 1: ___ ___.	Hour-meter function code 2: ___
___.

Beginning date for current meter reading 

(mm/dd/yyyy): __ __/__ __/__ __ __ __.	Engine hour-meter reading:__ __
__ __ ,__ __ __.

Hour-meter comments:

Hour-meter Code 1: 

21 = Meter not present

22 = Meter present but not functioning

23 = Original meter; reading can be presumed to represent hours since
original purchase

24 = Original meter reset following maintenance or resale, can identify
beginning date for current reading

25 = Original meter reset following maintenance or resale, CANNOT
identify beginning date for current reading

26 = NOT original meter, can identify beginning date for current reading

27 = NOT original meter, CANNOT identify beginning date for current
reading

28 = Other (DESCRIBE IN HOUR-METER COMMENTS) 

Hour-meter Code 2:

30 = No reading available

31 = Current reading presumed accurate

31 = Current reading not accurate, reliable adjustment possible
(DESCRIBE IN HOUR-METER COMMENTS)

33 = Current reading not accurate, reliable adjustment not possible
(DESCRIBE IN HOUR-METER COMMENTS)

34 = Other (DESCRIBE IN HOUR-METER COMMENTS)  

VISUAL INSPECTION

Are major exhaust leaks present?	Y	N	(IF ‘YES,’ DO NOT INSTALL
INSTRUMENT)

Is alternator speed signal reliable?	Y	N	(IF ‘NO,’ DO NOT INSTALL
INSTRUMENT)

Are obvious modifications or mal-maintenance evident?	Y	N	(IF ‘YES,’
INSTALL INSTRUMENT AND DESCRIBE IN COMMENTS)

Comments:

IF CANNOT INSTALL INSTRUMENT ON SELECTED PIECE, RECLASSIFY SELECTED
PIECE AS ‘INELIGIBLE,’ SELECT ADDITIONAL PIECE AND REPEAT EQUIPMENT
DESCRIPTION.

	

INSTALLATION DATE & TIME

Date installed: ___ ___ / ___ ___ /___ ___ ___ ___.	Time installed:  ___
___: ___ ___ am    pm

Date removed: ___ ___ / ___ ___ /___ ___ ___ ___.	Time removed:  ___
___: ___ ___ am    pm

Comments:

	

ENGINE RATING

Rated Power

	number:___ ___ ___ ___.	units code: ___ ___.	source code:___ ___.
method code:___ ___.

Rated Speed

	number:___ ___ ___ ___.	units:   RPM .	source code:___ ___.	method
code:___ ___.

Peak torque

	number:___ ___ ___ ___.	units code: ___ ___.	source code:___ ___.
method code:___ ___.

Peak Speed

	number:___ ___ ___ ___.	units:   RPM .	source code:___ ___.	method
code:___ ___.

Comments:

Units codes

11 = horsepower (gross)

12 = horsepower (net)

13 = kilowatts (gross)

14 = kilowatts (net)

15 = foot-lbs(ft-lb)

16 = newton-meters (nm)

17 = Other (DESCRIBE)	Source codes

21 = Owner’s/user’s verbal report

22 = Engine plate

23 = Manufacturer’specifications

24 = Reference source

25 = Unavailable

26 = Other (DESCRIBE)

	Method Codes

31 = NETT SAE

32 = ISO

33 = Unknown

34 = Unavailable

35 = Other (DESCRIBE)

INSTALLATION PARAMETERS

Is exhaust after-treatment present?	Y (= 1)		N (= 0)

DESCRIBE AFTER-TREATMENT TECHNOLOGY:

Unit Power (volts): ___ ___ ___.

Tailpipe Dimensions:

Outer diameter (inches):	___ ___ | ___ ___ ___	(MEASURE TO THREE DECIMAL
PLACES).

Pipe wall thickness (inches):	___ ___ | ___ ___ ___	(MEASURE TO THREE
DECIMAL PLACES)

Inner diameter (inches):	___ ___ | ___ ___ ___	(OD - 2× wall thickness)

INSTRUMENT IDENTIFICATION

Instrument Code: ___ ___.

Box No.: __ __-__ __.	Datalogger ID: __ __-__ __	Flowmeter ID.: __ __-__
__.	NOx/O2 Sensor Serial No.

__ __ __ __ __ __ __ __ __ __

Cell No. __ __ __ -__ __ __ -__ __ __ __.

Instrument Codes

01 = PAMS

02 = SPOT

03 = SEMTECH-D

04 = Other

	

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