United States
Environmental Protection
Agency
Office of Air Quality
Planning and Standards
Research Triangle Park, NC 27711
EPA-454/R-00-041
December 2000
Air
Quality Assurance Report
Calendar Year 1999
The PM2 5 Ambient Air
Monitoring Program
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PM2.5 CY99 QA Report December 2000
Foreword
This document is available on hardcopy as well as accessible as a PDF file on the Internet under the
Ambient Monitoring Technical Information Center (AMTIC) Homepage
(http://www.epa. gov/ttn/amtic/pmqa.htmD. The document can be read and printed using Adobe Acrobat
Reader software, which is freeware that is available from many Internet sites (including the EPA web
site). Hardcopy versions are available by writing or calling:
OAQPS Library
MD-16
RTP,NC27711
(919)541-5514
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PM2.5 CY99 QA Report December 2000
Abstract
This report documents the quality assurance activities that were undertaken for the PM2.5 environmental
data operations for the calendar year January 1, 1999 to December 31, 1999 (CY99), which was the
first year of implementation the PM2 5 monitoring program. The QA Report evaluates the adherence to
the quality assurance requirements described in 40 CFR 58 App. A and evaluates the data quality
indicators of precision, accuracy, bias, completeness, comparability and detectabilty.
The criteria pollutant defined as particulate matter is a general term used to describe a broad class of
substances that exist as liquid or solid particles over a wide range of sizes. As part of the Ambient Air
Quality Monitoring Program, EPA measures two particle size fractions: those less than or equal to [a
nominal] 10 micrometers, and those less than or equal to [a nominal] 2.5 micrometers, hereafter referred
to as PM10 or PM2 5 respectively. In general, the measurement goal of the PM2 5 Ambient Air Quality
Monitoring Program is to estimate the concentration, in units of micrograms per cubic meter (|ig/m3), of
particulates less than or equal to 2.5 micrometers ([im) that have been collected on a 46.2mm
polytetrafluoroethylene (PTFE) filter. For the State and Local Air Monitoring Network (SLAMS), the
primary goal is to compare the PM2 5 concentrations to the annual and 24-hour National Ambient Air
Quality Standard (NAAQS). The national primary and secondary ambient air quality standards for
PM2.5 are 15.0 micrograms per cubic meter ( |ig/m3) annual arithmetic mean concentration and 65
|ig/m3 24-hour average concentration measured in ambient air. A description of the NAAQS and its
calculation can be found in the July 18,1997 Federal Register Notice.
A quality system for the PM2.5 program was developed in order to achieve the data quality objectives
(DQOs) that were developed for this program. In order to meet these DQOs, measurement quality
objectives were developed for the data quality indicators of precision, bias, accuracy and
completeness. In addition, this report will discuss the data quality indicators of comparability and
detectabilty.
The report briefly discusses some of the implementation aspects of the quality assurance program
through the first and second years of implementation. The report identifies the data quality indicators
and how the estimates of these indicators were derived, evaluates the results, and provides conclusions
and recommendations for future improvements.
The data evaluated in this report is based upon a data extraction in AIRS on 7/26/00. This date was
chosen because it was after the July 1 certification date, and in the interest to report data quality results
to the States and EPA in a timely manner.
In general, the results show that most routine and QA data have not met completeness requirements.
The lack of information affects the confidence by which one can make assessments of precision,
accuracy and bias at various levels of aggregation. However, precision, accuracy and bias estimates at
national levels of aggregation appear to be meeting the data quality objective of the program.
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PM2.5 CY99 QA Report December 2000
Contents
Section Page
Foreword i
Abstract ii
Figures iv
Tables iv
List of Abbreviations v
Acknowledgments vi
Executive Summary vii
1. Introduction
Organization of QA Report 1
Program Overview 1
Data Quality Objectives 3
Quality System Implementation 4
Additional QA guidance provided in CY99 4
Implementation of 40 CFR Part 58 Appendix A Requirements 5
Development, Submission and Approval of QA Project Plans 5
Technical Systems Audits 7
Data Quality Indicators 8
Completeness Estimation- Routine and Quality Assurance Data 9
Precision, Accuracy and Bias Estimation 13
Detectability 17
Comparability 17
2. Assessment of Data Quality Indicators
Data Completeness 19
Routine Data 19
Collocated Precision 22
Flow Rate Audits 23
Performance Evaluation Program and Routine Data Bias Pairs 24
Precision - Collocated Sampling 26
Accuracy - Flow Rate Audits 28
Bias-Performance Evaluation Program and Routine Data 29
3. Conclusions and Recommendations
Conclusions 33
Recommendations 37
Attachments
1-1 Manipulation of Data Prior to Estimation of Precision, Bias or Accuracy
2-1 PM2.5 Routine Data Completeness
2-2 Summary of PM2.5 Data Flags
2-3 PM2.5 Collocated Precision Data Completeness
2-4 PM2.5 Flow Rate Audit Data Completeness
2-5 Performance Evaluation Program Sites without a Routine Data Value Match
2-6 Collocated Precision Data with Percent Difference > +/- 50%
2-7 Collocated Precision Data Aggregated by Reporting Organizations
2-8 Routine and Performance Evaluation Program Pairs with Accuracy > +/- 50%
111
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PM2.5 CY99 QA Report December 2000
Figure
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
2.10
2.11
2.12
2.13
2.14
2.15
2.16
2.17
Table
1-1
2-1
2-2
2-3
2-4
2-5
2-6
2-7
2-8
3-1
3-2
Figures
Title
Routine data completeness
Routine data completeness as of 7/26/00
Sites reporting routine data
Breakdown of routine concentration values in AIRS
Completeness of collocated precision data
Breakdown of precision completeness
Completeness of flow rate audit accuracy data
Breakdown of flow rate audit data
Completeness of Performance Evaluation Program data
Precision estimate based on CFR requirements
Precision estimate with outliers removed
CY99 Flow rate summary
Bias estimate based on requirements and guidance
Bias estimates with outliers removed
Bias estimates of Andersen and R & P Sequentials using current bias requirements
guidance
CY99 Andersen Sequential bias estimates
R & P Sequential bias estimates
Tables
Title
PM2.5 Reporting Organization QAPP Approval Status
Total and Percentages of Precision Sites Located at Sites Around the Annual
NAAQS
1999 PEP Site Completeness
CY99 Paired PEP/Routine data
Paired Concentration Values Used in Each National Precision Estimate
CY99 Flow Rate Summary
Paired Bias Values Used in Each Bias Estimate
Paired Andersen Sequential Bias Data
Paired R & P Sequential Bias Data
National Completeness Summary for CY99
National Estimates of Primary Data Quality Indicators for CY99
Section
2
2
2
2
2
2
2
2
2
2
2
2
2
2
and 2
2
2
Section
1
2
2
2
2
2
2
2
2
3
3
Page
19
20
21
21
22
22
23
24
24
26
26
28
29
29
30
30
31
Page
6
23
25
25
27
28
29
30
31
33
33
IV
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PM2.5 CY99 QA Report
December 2000
List of Abbreviations
AIRS Aerometric Information Retrieval System
CFR Code of Federal Regulations
CV coefficient of variation
DQA data quality assessment
DQOs data quality objectives
EDO environmental data operation
EMAD Emissions, Monitoring, and Analysis Division
EPA Environmental Protection Agency
ESAT Environmental Services Assistance Team
FEM Federal Equivalent Method
FRM Federal Reference Method
FS field scientist- Performance Evaluation Program
MQAG Monitoring and Quality Assurance Group
MQOs measurement quality objectives
NAAQS National Ambient Air Quality Standards
NAMS national air monitoring stations
NERL National Exposure Research Laboratory
NIST National Institute of Standards and Technology
OAQPS Office of Air Quality Planning and Standards
ORD Office of Research and Development
PE performance evaluation
PEP Performance Evaluation Program
PM25 particulate matter < 2.5 microns
PTFE polytetrafluoroethylene
QA quality assurance
QAPP quality assurance project plan
QA/QC quality assurance/quality control
QMP quality management plan
R&P Rupprecht and Patashnick
SLAMS state and local monitoring stations
SOP standard operating procedure
TSA technical systems audit
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PM2.5 CY99 QA Report December 2000
Acknowledgments
We are grateful to a number of individuals who have helped in the development or review of this
document. We would like to thank Herb Barden, EPA Region 4 and Karen Marisigan, EPA Region
10 with help from Greg Noag, Stephanie Riddle and Edlin Vinluan of the Environmental Services
Assistance Team (ESAT) for their support in providing the validated Performance Evaluation Program
data base. We acknowledge Andy Clayton and Michael Riggs, Research Triangle Institute, for their
help and insight into some of the evaluation techniques. The document went through a peer review
process and we appreciate the comments received from: Nancy Wentworth, Director of the EPA
Quality Staff; Michael Davis, EPA Region 7 and Anna Kelly, Hamilton County Department of
Environmental Services. In addition, we thank individuals from OAQPS, the EPA Regions and the
monitoring agencies who reviewed the document and sent us comments.
VI
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PM2.5 CY99 QA Report
December 2000
Executive Summary
This report documents the quality assurance activities that were undertaken for EPA's PM2.5
environmental data operations for the calendar year January 1, 1999 to December 31, 1999 (CY99),
which was the first year of implementation of the PM25 monitoring program.
As part of the Ambient Air Quality Monitoring Program, EPA measures two particle size fractions,
those less than or equal to 10 micrometers (PM10), and those less than or equal to 2.5 micrometers
(PM25). In general, the measurement goal of the PM2 5 Ambient Air Quality Monitoring Program is to
estimate the concentration, in units of micrograms per cubic meter (|ig/m3), of particulate matter less
than or equal to [a nominal] 2.5 micrometers ([im) that have been collected on a 46.2mm
polytetrafluoroethylene (PTFE) filter. For the State and Local Air Monitoring Network (SLAMS), the
primary goal is to compare the PM2 5 concentrations to the annual and 24-hour National Ambient Air
Quality Standard (NAAQS). The national primary and secondary ambient air quality standards for
PM2.5 are 15.0 micrograms per cubic meter ( |ig/m3) annual arithmetic mean concentration and 65
|ig/m3 24-hour average concentration measured in ambient air. A description of the NAAQS and its
calculation can be found in the July 18, 1997 Federal Register Notice.
A quality system for the PM2 5 program was developed in order to achieve the data quality objectives
(DQOs). The resulting quality assurance requirements are described in 40 CFR 58 App. A. This QA
Report evaluates the adherence to these requirements and evaluates the data quality indicators of
precision, accuracy, bias, completeness, comparability and detectabilty.
Table 1 summarizes data completeness and Table 2 summarizes estimates of the primary data quality
indicators of precision, accuracy, and bias at a national level. Summary comments about these tables
follow.
Table 1. National Completeness Summary for CY99 (as of 7/26/00)
Data Type
Routine Data
Collocation Precision
Flow Rate Accuracy
Performance Evaluations
Performance Evaluation
Pairs
Sites Meeting overall
completeness requirements for all
4 quarters
%
24%
10%
18%
100%
65%
Number
239
25
176
247
160
% Sites meeting 75% Completeness
for Each Quarter
1
31%
27%
35%
73%
49%
2
56%
46%
42%
113%
79%
3
60%
52%
44%
111%
80%
4
67%
54%
40%
104%
77%
vu
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PM2.5 CY99 QA Report
December 2000
Table 2. National Estimates of Primary Data Quality Indicators for CY99 (as of 7/26/00)
Data Type
Precision -Collocation
Accuracy-Flow Rate
Bias - Performance
Evaluations
Acceptance
Criteria
<10%CV
< + 4% Std.
< + 5% Design
< + 10%
National
Estimate
9.1%
0.02%
1.7%
Quarterly Estimate
1
12.1%
0.11%
9.0%
2
9.9%
0.08%
1.9%
3
6.6%
-0.04%
-0.9%
4
7.6%
-0.04%
-0.49%
Routine Data
Completeness - The completeness evaluation is based upon the strictest interpretation of the
completeness requirement in 40 CFR 50, App Nihat a site must collect 75% valid data in every
quarter in order for comparison to the NAAQS. There are other techniques, such as data substitution,
that can be used to allow more information to be used for the NAAQS comparison that are not
evaluated in this report. Therefore, the 24% overall completeness estimate is the most conservative
estimate of completeness for CY99. Since the requirement is based on 4 quarters, the overall
completeness estimate cannot be higher than the lowest quarterly completeness percentage.
Based on early reviews of completeness in March 2000, OAQPS provided guidance to allow the use
of data qualifiers (flags) in an attempt to increase the completeness of routine data that some
organizations may have felt uncertain about entering to AIRS. An additional 4.7% of the routine data
was captured using the new data qualifiers. However, two States accounted for 67% of these data
qualifiers, one that flagged all their data and a second that flagged 45%.
Precision - Collocation
Completeness- The number of sites that have met the 75% completeness goal for all 4 quarters is very
low. A marked improvement in completeness occurred from the first to second quarter but only
marginal improvement in the last three quarters. As with routine data, the overall completeness value
cannot be higher than the lowest quarterly value since the requirement is based on 4 quarters. Due to
some of the start-up problems in the first quarter, some reporting organizations had to substitute their
collocated instruments for the routine instruments. In addition, whenever a routine value was invalidated,
a collocated value could be substituted. The lack of information on collocated precision will make it
difficult to assess the precision data quality objective at lower levels of aggregation such as reporting
organizations or federal reference method designation (sampling monitor type). It may be necessary to
institute quarterly assessments of precision completeness in order to identify where information is
lacking and to improve the capture rate of this information.
Values around the NAAQS- In order to focus quality assurance activities around the data most
crucial in decision making, 40 CFR 58 App A required that 80% of the collocated monitors be placed
at the sites that the State, local and Tribal monitoring organization felt would provide annual averages at
vui
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PM2.5 CY99 QA Report December 2000
concentrations > 90% of the annual or 24-hour NAAQS. Presently, only 48% (105 sites) of the
collocated sites reporting data are located at sites with annual means > 13.5 jig/m3 and there are 426
routine sites with an annual mean > 13.5 |ig/m3. Since some reporting organizations may not have any
or only few sites reporting average annual concentrations >13.5 |ig/m3, it was not expected that 80%
percent of the collocated sites in the network would have average annual concentrations >13.5 |ig/m3.
However, if reporting organizations review their routine and collocated sites (Attachments 2-1 and 2-3)
it appears that some reporting organizations can relocate collocated monitors to sites where precision
and bias estimates are most crucial.
Precision Results - It must be emphasized that the precision data quality objective (DQO) is based on
three years of precision data (75% complete). Therefore, any one year or any quarter may exceed the
criteria and still meet the precision data quality objectives. An early analysis of precision suggests that
the DQO can be achieved, at least at the national level.
It was discovered that 232 outliers (percent differences greater than + 50%), which represented 2.8%
of the precision data, change the national estimate from 9.1% CV to 6.8% CV and lowered the first
quarter estimate from 12.1% CV to 8.2% CV. OAQPS will ask State and locals to review these
outliers to ensure their validity. For this report the outliers are considered valid and therefore
incorporated into the overall and quarterly precision estimate. Another interesting observation is that
OAQPS did not plan on assessing any collocated pairs that had one or both values below 6 |ig/m3. It
was assumed that these values were close to the sensitivity of the measurement system and that small
actual variance at these low levels would provide large coefficients of variance. This did not prove to
be the case and, in fact, the outliers had more influence on the precision estimate.
OAQPS investigated whether there was any significant difference in precision for different method
designations. From the available data, all the method designations appear to have comparable
precision. Based on the national precision estimates being very close to the DQO, it is anticipated that
some reporting organization precision estimates will be above the data quality objective. The effect of
the additional variability would be less confidence in estimates of individual or aggregate concentrations.
Accuracy -Flow Rate
Completeness- Flow rate accuracy overall completeness was low for CY99. A positive or negative
bias in flow rate can have a direct effect on the cut point of the paniculate matter collected on the filter
and also affects the 24 hour air volume estimate that goes into the derivation of the concentration.
OAQPS will work the EPA Regions and States to ensure a better capture rate of this data for future
calendar years.
Accuracy Results - For the information available, the results of the accuracy audits are very good.
The national average accuracy estimate is 0.02% which is well within the acceptance criteria of ฑ4% of
the standard and ฑ5% of the design (see Table 2). For the method designations that had more than
100 flow rate audits performed in CY99, the percentage of audits meeting the criterion of ฑ4% of the
standard was 94% and the percentage meeting the criterion of + 5% of the 16.67 L/min design flow
rate was 99%. Additionally, these percentages did not vary by method designation.
rx
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PM2.5 CY99 QA Report December 2000
Bias - Performance Evaluation Program and Routine Data
Completeness - Completeness of the performance evaluation data is a little more complicated
because it involves two data points that are collected by different organizations. The bias estimate must
rely on Performance Evaluation Program (PEP) data collected by technical support contractors
provided through the EPA Environmental Services Assistance Team (ESAT) contract. The routine
PM2 5 data is collected by the State, local and tribal Nations. The PEP achieved its completeness
requirement by collecting valid data at 247 sites, which was just over the anticipated 245 sites (25% of
the 979 sites established in AIRS). However, when the data for these 247 sites were matched with
their respective routine data in AIRS, only 160 sites produced valid site/pairs that met the completeness
requirement. If one looks at actual valid samples that were taken, of the 984 valid PEP values, there
are only 697 that have a routine sample match in AIRS. Reasons for missing routine values could be
due to PEP or routine samples mistakenly sampled on different days, or data not yet entered into AIRS.
However, the missing 287 values account for 30% of the performance evaluation information which
affects the confidence in the bias estimates, particularly when one attempts to assess bias at a reporting
organization or method designation level.
Bias results
As with precision, the bias data quality objective is based on three years of bias data (75% complete).
At a national level, the average bias is estimated at 1.7% and it appears that the bias data quality
objective is being met. However, there are three factors that affect the bias estimates: 1) lack of paired
data, 2) outliers, and 3) method designations..
Lack of paired data - A performance evaluation is only performed on 25% of the sites and each site
is audited 1 time each quarter. It is difficult to determine a statistically significant bias at lower levels of
aggregation such as reporting organization or method designation with only one years worth of
information and with 287 paired values missing.
Outliers - Similar to the findings in the precision data, there is almost no difference in the bias estimate
in keeping or removing a pair when one or both values is below 6 |ig/m3. However, it appears outliers
had an effect on bias in the first quarter of 1999. An outlier was any paired value that had an accuracy
estimate greater than +50%. Removing outliers from the national estimate changed the bias estimate
from 1.7% to -0.49%. However, 6 outliers (6 % of the quarters total) in the first quarter changed the
bias estimate from 9.0% to 3.6%. OAQPS will ask State and locals to review these outliers to ensure
their validity. For this report the outliers are considered valid and incorporated into the overall and
quarterly bias estimate.
Method Designations - It appeared that method designations did play a role in the bias estimates,
particularly in the first and possibly the second quarter of 1999. For the first quarter, the Andersen
sequential bias estimate (25.7%) was substantially higher than the R & P sequential bias estimate
(-1.01%). However, all 6 (17% of the quarters values for Andersen) outliers identified in the first
quarter where related to the Andersen instrument which would change the bias estimate from 25.7% to
12.42%. Outliers did not have any significant effects on R & P sequential data. There was not enough
data to make any statements about single channel instruments. The third and fourth quarter estimates
do not appear to vary by method designation and are therefore more comparable. This may be due to
improvements in sampling and analytical techniques and vendor modifications to the FRM monitors.
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PM2.5 CY99 QA Report December 2000
1. Introduction
This report documents the quality assurance activities that were undertaken for the PM2 5 environmental
data operations for the calendar year January 1, 1999 to December 31, 1999 (CY99). The QA Report
evaluates the adherence to the quality assurance requirements described in 40 CFR 58 App. A and
evaluates the data quality indicators of precision, accuracy, bias, completeness, comparability and
detectabilty. The QA Report should be viewed as an annual snapshot to determine whether or not the
quality system, in general, is providing data of acceptable quality for its primary use. Therefore, the
report will provide evaluations at higher levels of aggregation (national levels or by method designation).
Data used in this report was extracted from AIRS on 7/26/99.
Organization of QA Report
The report has been organized into 3 main sections:
ป Section 1: overview of the PM2 5 monitoring program, the CY99 implementation aspects of the
quality system in relation to the quality assurance requirements described in 40 CFR 58 App A, and a
description of the procedures used to assess data quality.
ป Section 2: results of the data quality assessment.
> Section 3: summary and conclusions of the data quality assessment results and recommendations
based upon experiences of CY99 implementation.
Program Overview
The criteria pollutant defined as paniculate matter is a general term used to describe a broad class of
substances that exist as liquid or solid particles over a wide range of sizes. As part of the Ambient Air
Quality Monitoring Program, two particle size fractions are measured; those less than or equal to [a
nominal] 10 micrometers, and those less than or equal to [a nominal] 2.5 micrometers, hereafter referred
to as PM10 or PM2.5 respectively.
The background and rationale for the implementation of the PM2 5 ambient air monitoring network can be
found in the Federal Register 40 CFR 50 July 18, 1997 . In general, the measurement goal of the
PM2.5 network is to estimate the concentration, in units of micrograms per cubic meter (|ig/m3), of
paniculate matter less than or equal to 2.5 micrometers (fim) aerodynamic diameter collected over a 24
hour period. Appendix L of 40 CFR 50 also provides the following summary of the measurement
principle:
An electrically powered air sampler draws ambient air at a constant volumetric flow rate into a specially shaped inlet and
through an inertial particle size separator (impactor) where the suspended particulate matter in the PM2 5 size range is
separated for collection on a polytetrafluoroethylene (PTFE) filter over the specified sampling period.
Each filter is weighed (after moisture and temperature equilibration) before and after sample collection to determine the
net weight (mass) gain due to collected PM2 5. The total volume of air sampled is determined by the sampler from the
measured flow rate at actual ambient temperature and pressure and the sampling time. The mass concentration of PM2 5
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PM2.5 CY99 QA Report December 2000
in the ambient air is computed as the total mass of collected particles in the PM2 5 size range divided by the actual volume
of air sampled, and is expressed in micrograms per actual cubic meter of air (ug/m ).
A major objective for the collection of the data is to compare daily PM2 5 concentrations to the annual
(15.0 |ig/m3 annual arithmetic mean concentration) and 24-hour (65 |ig/m3 24-hour average
concentration) national ambient air quality standard (NAAQS). A description of the NAAQS and its
calculation can be found in the July 18, 1997 Federal Register notice.
As described in the following section (DQOs), OAQPS designed a quality system based upon the
primary objective of the network, which was the comparison of data to the NAAQS. For this
comparison, State, local, and Tribal monitoring organizations are required to sample using a Federal
Reference Method (FRM) or Federal Equivalent Method (FEM). The description of the PM2.5 FRM
is included in 40 CFR 50, App. Z, published as a final rule in the Federal Register on July 18, 1997.
There are a number of designated federal reference method samplers at this time including:
Single channel FRM samplers:
Andersen Model RAAS2.5-100 PM2.5 Ambient Air Sampler; designated 6/11/98.
BGI Inc. Model PQ200 Ambient Fine Particle Sampler; designated 4/16/98.
Rupprecht & Patashnick Partisolฎ-FRM Model 2000 Air Sampler; designated 4/16/98.
Thermo Environmental Instruments, Inc. Model 605 "CAPS" Sampler; designated 10/29/98.
Sequential FRM samplers:
Andersen Model RAAS2.5-300 PM2.5 Sequential Ambient Air Sampler; designated 6/11/98.
Rupprecht & Patashnick Partisolฎ-Plus Model 2025 Sequential Air Sampler; designated
4/16/98.
Portable FRM audit samplers (used in the quality assurance program):
Andersen Model RAAS2.5-200 PM2 5 Ambient Audit Air Sampler; designated 3/11/99.
BGI Inc. Model PQ200A Ambient Fine Particle Sampler; designated 4/16/98.
Rupprecht & Patashnick Partisolฎ Model 2000 Audit Sampler; designated 4/19/99.
The PM2 5 federal equivalent methods (FEM) vary from this basic FRM definition and are divided
into three categories, Class I, U, and IE. Definitions for each of these are provided in 40 CFR 53.7,
published as a final rule in the Federal Register on July 18, 1997. There are no designated equivalent
PM2 5 methods at this time, nor have any manufacturers formally pursued this type of designation.
It is important to emphasize that all PM2 5 sampling sites that provide data for comparison to either
the 24-hour or the annual PM2 5 NAAQS for the purposes of addressing attainment and nonattainment
decisions must employ designated FRM/FEM sampling techniques.
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PM2.5 CY99 QA Report December 2000
Data Quality Objectives (DQOs)
DQOs are qualitative and quantitative statements derived from the DQO Process that clarify the
monitoring objectives, define the appropriate type of data, and specify the tolerable levels of potential
decision errors that will be used as the basis for establishing the quality and quantity of data needed to
support decisions1. By applying the DQO Process to the development of a quality system for PM2.5
network, the EPA guards against committing resources to data collection efforts that do not support a
defensible decision. During the months from April to July of 1997, the DQO Process was implemented
for the PM2 5 program. The DQOs were based on the ability of the decision maker(s) to make
NAAQS comparisons within an acceptable probability of decision errors. Based upon the acceptable
decision error of 5%, the DQO for acceptable precision (10% CV) and bias (+ 10%) were identified.
Decision errors are based on two general types of uncertainty, population uncertainty and measurement
uncertainty. Population uncertainty is defined as the natural spatial and temporal variability in the
population of the data being evaluated. Confidence in estimates of population uncertainty can be
controlled through the use of statistical sampling design techniques, the proper placement of ambient air
quality monitors, and spatial averaging (as allowed by the PM2 5 NAAQS). Since the population of
concern for the PM2.5 NAAQS violation decision is a single instrument, the population uncertainty
would be an estimate of the uncertainty over the 3-year averaging period. During the development of
the NAAQS, population uncertainty, due to temporal variability, was incorporated into the standard by
stating that 3 complete years of data (every day sampling) determines a violation of the NAAQS, even
though the expected value may be different. Therefore, population variability was considered to be
zero, as long as every day sampling was implemented. However, l-in-6 day sampling and l-in-3 day
sampling, or any deviation from every day sampling, have a population variance that must be
understood, and if possible, quantified.
Total measurement uncertainty is the total error associated with the environmental data operation. The
environmental data operation for PM2 5 represents various data collection activities or phases including:
the initial weighing of the filters (and the conditions in which they are weighed), the transportation of the
filters, the calibration of the instrument and its maintenance, the handling and placement of the filters, the
proper operation of the instrument (sample collection), the removal, handling and transportation of the
filter, the storage and weighing of the sampled filter, and finally, the data reduction and reporting of the
value. At each phase of this process, errors can occur, that in most cases, are additive. The goal of a
QA program is to control and document total measurement uncertainty (precision and bias) to an
acceptable level through the use of various quality control and evaluation techniques. In a resource
constrained environment, it is most important to be able to calculate/evaluate the total measurement
uncertainty and compare this to the DQO. Measurement precision will be estimated using the PM2 5
collocated samplers while bias will be estimated using the Performance Evaluation Program. These and
other "data quality indicators" are discussed below.
This QA Report will focus on the evaluation of measurement uncertainty. Population uncertainty is being
evaluated by other data analysis groups.
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PM2.5 CY99 QA Report December 2000
Quality System Implementation
Upon promulgation of the July 18, 1997 NAAQS, an implementation start date of Jan 1, 1999 was
identified. OAQPS developed a 2-year phased approach for the implementation of a 1500 site
network where approximately 950 sites would be operational in CY99 with the remainder in CYOO.
Requirements for the implementation activities are found in 40 CFR 50, 53 and 58. In addition to the
regulations, a number of guidance documents, videos and broadcasts were developed in 1998 and 99
to assist in the implementation of the monitoring network.
Monitoring organizations also had to meet certain quality assurance requirements. The majority of the
quality assurance requirements are defined in:
40 CFR Part 50 Appendix L - which describes many of the critical quality control
requirements for the FRM sampler, the filter handling requirements and the laboratory facilities
and equipment.
40 CFR Part 58 Appendix A - identifies the quality assurance requirements.
Quality Assurance Guidance Document 2.12 Monitoring PM2.5 in Ambient Air Using
Designated Reference or Class I Equivalent Method - provides more detail and guidance to
support CFR Parts 50 and 58.
Quality Assurance Guidance Document Model Quality Assurance Project Plan for the
PM2.5 Ambient Air Monitoring Programs at State and Local Air Monitoring Stations
(SLAMS) - provides a model for the development of a PM2 5 QA project plan.
Additional QA Guidance provided in CY99
During CY99 implementation, various technical issues arose that required additional guidance or
clarification. The following guidance was developed in CY99 and CYOO and was distributed to the
EPA Regions as well as posted on the Ambient Monitoring Technology Information Center (AMTIC)
PM2 5 site. Since certification of CY99 data takes place in July of 2000, the guidance distributed in
CYOO may apply to CY99 data.
Flexibility in sample transport conditions - guidance was distributed on 1/20/00 that
provided an interpolation between the two temperature transport requirements (25ฐC/10 day
and 4ฐC/30 day) that allows one to determine the number of days available for sample
weighing from the sample end data and time, based upon the average temperature of the
sample upon arrival at the laboratory.
Standard Time - guidance was distributed on 6/22/99 to set and leave all instruments on local
standard time.
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PM2.5 CY99 QA Report December 2000
Archiving PM2 5 Samples - Some additional guidance for acceptable procedures for
archiving PM2 5 samples was distributed on 2/7/00
Collocated substitution and POC codes- guidance was distributed on 1/3/00 to reiterate
earlier PM10 guidance that collocated data can be substituted for routine data when the
routine sampler was inoperable or otherwise caused the routine sample to be invalidated.
However, in order to identify that the collocated value was used, it was suggested that the
value be placed in pollutant occurrence code 2 (POC-2). This would help in completeness
assessments for P & A. In addition, this memo went on to designate all POCS (1-9) for the
PM2 5 monitoring (mass, speciation and continuous).
Flagging - A memo, distributed 3/27/00 from OAQPS to the Regions, provided for the use
of 6 data qualifiers.
Implementation of 40 CFR 58 Appendix A Requirements.
40 CFR 58 App. A provides the quality assurance requirements for the State and local air monitoring
station (SLAMS) network. The requirements for PM2 5 include:
> Development, submission, approval and implementation of QA project plans
> Implementation of technical systems audits
> Implementation of quarterly flow rate audits (see Section 2)
> Implementation of collocated sampling (see Section 2)
> Implementation of a performance evaluation program (see Section 2)
The implementation of the quarterly flow rates, the collocated sampling and the performance evaluation
will be discussed in the data quality indicators section (below) and evaluated in (Section 2)
Development, Submission and Approval of QA Project Plans
The QA Project Plan (QAPP) is used to document planning results for environmental data operations
and to provide a project specific "blueprint" for obtaining the type and quality of environmental data
needed for a specific decision or use2. All EPA funded environmental data operations are required to
have an approved QAPP prior to the collection of environmental data. QAPPs were required for each
reporting organization. Reporting organization is defined in 40 CFR 58 App. A. Table 1-1 provides a
status of the QAPP approvals for all PM2 5 reporting organizations. All reporting organizations have a
approved or conditionally approved QAPP. In some cases, QAPPs were not approved prior to
implementation of environmental data operations. Memos related to QAPP submission, approval, and
data entry to AIRS were distributed to the EPA Regions on January 21, 1999 and February 11, 1999.
The February 11 memo indicated that there would be no submission of data to AIRS prior to QAPP
approval. The memo also stated that data collected prior to QAPP approval could be accepted and
subsequently submitted to AIRS if and only if the QAPP was fully or conditionally approved upon
submission or upon completion of technical system audit (TSA), conducted by the EPA Regions, that
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PM2.5 CY99 QA Report
December 2000
determined ongoing conformance to the QAPP that was submitted prior to conditional or full approval.
Table 1-1 also indicates the ISA's conducted by the EPA Regions in CY99.
Data has been submitted by reporting organizations that have not conformed to the 2/11/99 memo.
OAQPS will ensure that the QAPP approval dates will be included in the AIRS data base. In addition,
OAQPS has created a flag (6) which will be placed on any raw data value not meeting the
requirements stated above.
Table 1-1 PM2.5 Reporting Organization QAPP Approval Status (as of 7/26/00)
Reg.
1
2
3
4
State
CT
MA
ME
NH
RI
VT
NJ
NY
PR
VI
DE
DC
MD
PA- Philadelphia County
PA -Allegheny County
PA
VA
WV
ALDEM
FLDEP
GA
KYDEP
MSDEQ
NCDEM
SCDHEC
TN DAPC
AL -Birmingham- Jefferson County
AL- Huntsville
KY- Louisville- Jefferson County
TN- Nashville-Davidson County
TN- Chattanooga-Hamilton County
TN- Knoxville-Knox County
TN- Memphis-Shelby County
QAPP
Submissions
01/08/99
12/10/98
12/31/98
01/20/99
02/05/99
12/30/98
11/98
7/99
12/98
2/99
8 QAPPS
received
Nov/Dec 1998
12/01/98
01/29/99
07/28/98
11/02/98
01/07/99
11/25/98
01/11/99
10/22/98
11/30/98
12/01/98
11/30/98
01/13/99
11/24/98
11/30/98
12/02/98
QAPP
Approval
Date
12/30/99
10/05/99
07/01/99
01/11/00
08/30/99
09/27/99
02/04/99
05/20/99
07/15/99
02/12/99
06/10/99
06/17/99
06/22/00
06/22/00
06/22/00
02/15/00
06/22/00
06/22/00
06/22/00
06/22/00
01/12/99
02/05/99
10/01/99
01/14/99
01/12/99
01/12/99
01/12/99
02/17/99
01/12/99
12/19/98
01/12/99
12/30/98
01/28/99
02/17/99
01/28/99
03/03/99
01/23/99
04/27/99
01/26/99
Cond (C)
or Full (F)
F
F
F
F
F
F
Ctill
3/15/99
F
F
C
F
F
F
F
F
F
F
F
F
F
F
C
F
F
F
F
F
C
F
F
F
F
C
F
C
F
C
F
F
ISA
N
N
N
N
N
N
Lab
Lab
Lab
Lab
Lab
Lab
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
ISA
Date
01/99
10/99
04/99
04/99
06/99
04/99
9/99
9/99
9/99
11/99
9/09/99
5/13/99
6/15/99
8/19/99
5/25/99
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PM2.5 CY99 QA Report
December 2000
Reg.
5
6
7
8
9
10
State
MN
WI
MI
OH
IL
IN
AR
LA
OK
NM
NM -Albuquerque
Texas
ITEC (Tribal)
AIPC (Tribal)
MO
KS
IA -Linn County
IA- Polk County
NE-
U of Iowa
CO
MT
ND
SD
UT
WY
AZ
CA -ARE
CA - Bay Area AQMD
CA - South Coast AQMD
San Diego APCD
HI
NV- Pima County
NV- Washoe County
NV- Clark County
AK
ID
OR
WA
QAPP
Submissions
04/01/99
01/22/99
05/12/99
01/29/99
02/08/99
01/01/99
08/20/99
12/21/99
9/98
11/98
11/18/98
11/98
12/2/98
9/98
2/99
12/98
QAPP
Approval
Date
02/08/99
02/03/99
02/04/99
01/19/99
01/26/99
01/26/99
07/01/99
02/03/99
05/24/99
02/04/99
02/02/99
02/04/99
09/28/99
04/11/99
12/23/98
12/16/98
12/09/98
12/29/98
01/29/99
02/04/99
02/18/99
05/18/99
12/22/98
08/06/99
03/26/99
07/22/99
03/02/99
08/05/99
12/07/99
12/21/98
12/21/98
12/21/98
12/21/98
12/07/98
12/07/98
07/20/99
02/02/99
01/15/99
11/10/98
11/30/98
12/04/98
Cond (C)
or Full (F)
F
F
F
F
F
F
F
F
F
F
F
F
F
F
C
C
F
F
F
C
C
F
F
F
C
F
F
F
C
C
C
C
C
C
C
C
C
F
F
F
F
ISA
Y
Y
Y
Y
Y
Y
Y
N
Y
N
N
Y
N
N
Y
Y
N
N
N
N
Y
Y
Y
Y
Y
Y
N
N
N
N
N
N
N
Y
Y
N
N
Y
Y
ISA
Date
06/03/99
04/07/99
05/05/99
05/20/99
04/21/99
05/1 1/99
7/19/99
7/7/99
7/99
7/99
9/99
8/99
8/99
9/99
3/99
9/99
8-9/99
10-11/99
Technical Systems Audits
Technical systems audits (TSAs) are a thorough, systematic, on-site, qualitative audit of facilities,
equipment, personnel, training, procedures, record keeping, data validation, data management, and
reporting aspects of a system. TSAs are also qualitative on-site evaluations of a complete phase of an
environmental data operation (EDO) such as sampling, preparation, or analysis. This audit can be
performed prior to the data collection activity in order to verify the existence and to evaluate the
adequacy, of equipment, facilities, supplies, personnel, and procedures that have been documented in
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PM2.5 CY99 QA Report December 2000
the QAPP. TSAs are also employed during the data collection activity in order to verify and evaluate
the EDO.
Technical systems audits are required to be performed every three years on all reporting organizations
by the EPA Regions. Table 1-1 provides a report of the audits conducted in CY99.
Data Quality Indicators
Once a DQO is established, the quality of the data must be evaluated and controlled to ensure that it is
maintained within the established acceptance criteria. Measurement quality objectives are designed to
evaluate and control various phases (sampling, preparation, analysis) of the measurement process to
ensure that total measurement uncertainty is within the range prescribed by the DQOs. The MQOs can
be defined in terms of the following data quality indicators:
Completeness - a measure of the amount of valid data obtained from a measurement system
compared to the amount that was expected to be obtained under correct, normal conditions. Data
completeness requirements are included in the reference methods (40 CFR 50).
Precision - a measure of mutual agreement among individual measurements of the same
property usually under prescribed similar conditions. This is the random component of error.
Bias - the systematic or persistent distortion of a measurement process which causes error in
one direction. Bias will be determined by estimating the positive and negative deviation from the
true value as a percentage of the true value.
Detectabilitv- The determination of the low range critical value of a characteristic that a method
specific procedure can reliably discern.
Comparability - a measure of confidence with which one data set can be compared to another.
Representativeness - a measure of the degree which data accurately and precisely represent a
characteristic of a population, parameter variations at a sampling point, a process condition, or an
environmental condition. Representativeness, which deals mainly the population variability
indicators (spatial and temporal variability) will not be addressed in this document.
Accuracy has been a term frequently used to represent closeness to "truth" and includes a combination
of precision and bias error components. This term has been used throughout the CFR and in some of
the sections of this document.
Acceptance criteria have been developed for four of these data quality indicators: completeness,
precision, accuracy and bias. The process and statistics used to evaluate the data quality indicators will
be discussed below. The results of the assessments will be discussed in Section 2.
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PM2.5 CY99 QA Report December 2000
Completeness Estimation - Routine and Quality Assurance Data
For this report, data completeness was computed for the routine 1999 Federal Reference Method
(FRM) data, for 1999 precision information, for 1999 accuracy transactions, and for 1999 bias data
extracted from AIRS on 7/26/00.
Routine Data Completeness Estimation Procedure
The following statement is made in 40 CFR 50 App. N Section 2.1:
" For the annual PM25 standard, a year meets data completeness requirements when 75
percent of the scheduled sampling days for each quarter have valid data. However,
years with high concentrations and more than a minimal amount of data (a least 11
samples in each quarter) shall not be ignored just because they are comprised of quarters
with less than complete data... "
Completeness was computed as prescribed for the NAAQS per the following references: 1) 40 CFR
50 APP N, 2) Guideline on Data Handling for the PM NAAQS, and 3) Use of Make-up PM Samples
to Replace Scheduled PM Samples. The specific computations, caveats, and rationale employed for
this report are described below. All utilized data were extracted from AIRS on 7/26/00. This date
allowed several State updates beyond the official July 1 'certification' deadline. The listing that is
referred to in the following information can be found as Attachment 2-1.
Completeness was computed on an individual site basis. Only data for Primary POC's (the lowest
number POC - generally ' 1') were used.
A sample frequency was derived for each site-quarter. The quarterly frequency was computed as:
mode (days between samples). If the mode was not equal to 1 (every day) or 3 (every 3rd day), a
default of 6 (every 6th day - the least stringent frequency) was used. Some of these data-derived
frequencies were 'corrected' with feedback received from Regions, States, and MQAG staff.
There was no attempt to reconcile the utilized frequencies with the CFR requirements (based on
metropolitan statistical area population).
Null data codes were not counted as valid samples but were used to ascertain sampling frequency.
Flagged data were considered valid for the purpose of data completeness.
Completeness percentages were based on the entire calender year 1999; that is, monitors were
assumed to have operated (or have been able to operate) the full year. There were no adjustments
made for later start-up or for monitor closing. MQAG recognizes that some monitors did begin
operating later in the year due to a variety of circumstances and thus, the calculated completeness
percentages may not accurately portray actual 'performance'. The full-year approach was used (as
opposed to the partial-year method) so that the results would more closely coincide with NAAQS
usage requirements.
. The official EPA 1999 3-day and 6-day monitoring schedules were used to ascertain scheduled
sampling days
. 'Make-up' logic was incorporated as stipulated in reference 3: Missed samples on an 'every 3rd
day' schedule were counted as taken if an extra ('make-up') sample was reported 1, 2, or 7 days
later. Missed samples on an 'every 6th day' schedule were counted as taken if an extra sample was
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PM2.5 CY99 QA Report December 2000
reported 1, 2, 3, 4, 5, or 7 days later. The number of replacement samples permitted in any
quarter was limited to no more than 5. Some concessions to these 'guidelines' were granted on
request.
Extra 'unscheduled' samples were included in the completeness computations by adding the
applicable number to the numerator and denominator of the equation. For actual NAAQS usage
this approach may be unacceptable, especially if the extra samples were purposely taken all near
the end of the quarter, on low concentration days, etc. By adding these samples to the numerator
and denominator, we are basically allowing the monitor to temporarily shift sampling frequencies to
'every day sampling'.
The final formula used for computing completeness was:
(# of scheduled samples taken) + (# of make - up samples) + (# of unscheduled samp les taken)
- quarter =
(# of scheduled samples) + (# of unscheduled samp les taken)
Data substitution logic was not incorporated in this iteration. However, since States will be
permitted to show Annual NAAQS attainment (over a 3-year period) using quarters less than 75 %
but at least 50% complete (by substituting maximum quarterly values or collocated PM2.5, PM10,
or TSP for their missing data), metrics using the 50% threshold were calculated in addition to ones
using the 75% cutoff.
Since non-attainment of the Annual NAAQS can be determined with as few as 11 samples in a
quarter (which could be as little as 12% of the number of required samples), a metric using the 11
sample cutoff was also included.
Collocated Precision Completeness Estimation Procedure
Information used to compute PM2.5 precision and associated completeness were culled from 2 sources,
from the AIRS precision area (polled via an AMP250 - P/A Monitor Raw Data retrieval) and from the
AIRS raw data area (polled via an AMP350 - Raw Data Listing retrieval). Precision data are
supposed to be submitted to AIRS with transaction type 8 and, hence, be deposited in the former area.
However, since there has been some confusion with regards to this requirement, additional paired data
were retrieved from the latter area and results merged. Both AIRS data extractions were performed on
7/26/00. Below are some additional details of the precision completeness analysis. The listing that is
referred to in the following information can be found as Attachment 2-3.
Per 40 CFR 58 App. A, Sec. 3.5.2, each PM2.5 Reporting Organization is required to collocate
25% (but at least 1) of their FRM monitors for the purpose of calculating measurement precision.
State summary lines in the precision completeness report show the total number of FRM sites for
1999 [the number with 88101 monitor records], the number of sites that reported routine FRM
data, the number of sites where collocation was required [25% of the total], the number of sites
reporting precision information, and the number of sites with 4 complete quarters of precision
information. MQAG recognizes that States and Reporting Organizations are not totally
synonymous.
If an attempt was made to run collocated instruments on a particular day, a site was given credit for
that attempt, even if one (or both) of the samples was invalidated. That is, null codes did not
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PM2.5 CY99 QA Report December 2000
reduce data completeness. Hence, completeness computations were less stringent for precision
than for the routine data.
Completeness percentages were based on whole quarters of calender year 1999. On the listing,
sites were only held accountable for quarters starting with the first one in which routine information
were reported. If a site's first reported 1999 routine FRM data point occurred in the 2nd quarter,
the site was not expected to produce precision information until that quarter. Blanks on the site
listing are different from zeroes. Blanks indicate no precision data present but no FRM data
reported either in that quarter. Zeroes indicate no precision data reported but routine FRM data
are present that quarter. Completeness percentages for the 'initial' quarters were not prorated
according to when in the quarter that 1st FRM point occurred; the denominator for the ratio was the
whole quarter (number of every 6th days).
40 CFR 58 App A Sect. 3.5 requires a 6-day sampling schedule for precision collocation. All
possible 6-day schedules were evaluated (by quarter) and the one with the greatest capture (most
precision pairs) was used for the completeness calculation. A majority of sites appear to have used
the official EPA 1999 6-day monitoring schedule. Make-up sampling (on days other than one-in-
six) were not credited for completeness. In the attached site listing, a count is provided (by quarter)
of the number of total pairs reported and the number reported on the predominant 6-day schedule.
Although some quarterly 6-day schedules yielded 16 possible precision pairs, a denominator of 15
was always used. (In cases where 16 pairs were actually reported, the completeness statistic was
capped at 100%.)
Totally complete sites (defined as ones that reported 73% or more [11/15=73%] in each quarter)
are flagged.
A flag is also provided on the listing to indicate if the site's corresponding 1999 annual mean is
greater or equal to 13.5 |ig/m3. 40 CFR 58 App A Sect 3.5 notes that during the initial deployment
of the PM2.5 network, special emphasis for collocation should be placed on sites in areas likely to
exceed the NAAQS. Once areas are determined to be in violation of the NAAQS, 80% of the
areas' collocated monitors are to be deployed at sites with concentration > 90% of the NAAQS or
13.5 |ig/m3. In general (Nationwide), it appears that we are falling short of the 80% goal. States
may need to consider moving some of their collocated monitors to higher concentration areas.
Flow Rate Accuracy Completeness Estimation Procedure
Information used to compute PM2.5 accuracy and associated completeness was pulled from the AIRS
accuracy area with an AMP250 - P/A Monitor Raw Data retrieval on 7/26/00. Comments on the
completeness analysis are shown below. The listing that is referred to in the following information can
be found as Attachment 2-4.
Per 40 CFR 58, App. A, Sec. 3.5.1.2, each calender quarter every FRM sampler's flow rate is to
be audited at least once with a certified standard. State summary lines in the accuracy
completeness report show the total number of FRM sites for 1999 [the number with 88101 monitor
records], the number of sites that reported routine FRM data, the number of sites where collocation
was required [All sites], the number of sites reporting accuracy transactions, and the number of
sites with 4 quarters of accuracy data. Again, MQAG realizes that States and Reporting
Organizations are not totally synonymous
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PM2.5 CY99 QA Report December 2000
Since only 1 audit was required per quarter and it was either present or not, no actual completeness
percentages were computed. An indicator is shown for each site that reported accuracy
information in all 4 quarters.
Like precision, sites were only held accountable for quarters starting with the first one containing a
routine FRM data point. Blanks on the site listing are different from zeroes. Blanks indicate no
accuracy data present but no FRM data reported either in that quarter. Zeroes indicate no
accuracy reported but routine FRM data are present that quarter.
Note that some sites reported more than 1 accuracy check per site-quarter. States are cautioned
that the flow rate standard used for auditing must not be the same flow rate standard to calibrate the
analyzer. Calibration results should not be submitted to AIRS as accuracy transactions.
Performance Evaluation Program Completeness Estimation Procedure
Information used to compute PM2.5 bias and associated completeness is predicated on the
completeness of the routine network in addition to the completeness of the Performance Evaluation
Program (PEP). The completeness of the routine network is described above. The completeness of
the PEP is described in this section.
As per 40 CFR 58, App. A, Sec. 3.5.3, approximately 25% of each method designation of the routine
sites within each reporting organization are supposed to be visited 4 times in a year by the PEP,
preferably once per quarter. Thus, the PEP is complete if approximately 25% of the PM2.5 monitoring
network is evaluated at least 3 times (75% of 4) in a year. To evaluate completeness of the PEP,
information was pulled from the data bases maintained by the two regional laboratories supporting the
PEP (Region 4 and 10) and from the data base maintained by the RTF laboratory, which supported the
PEP during the early phase. The Region 4 data base was queried on 8/7/00, the Region 10 data base
on 7/31/00, and the RTF data base on 7/26/00. These three data bases were merged together and
completeness statistics were calculated according to the following procedure.
Any PEP data points with an invalid code (PEVALID=0) were deleted prior to completeness
calculations. That is, only valid PEP data were used to calculate completeness.
Any PEP data points not associated with routine sampling (e.g. internal precision collocations) were
deleted prior to completeness calculations, even if the study had a collocated FRM.
For some site/day combinations, there are multiple observations in the PEP data base. This likely is
due to multiple PEP samplers being run. In such cases, only the first valid observation in the data
base was used.
Since a site is supposed to be visited by the PEP 4 times within a year, if 3 (75% of 4) or more
visits were made and resulted in valid data, then the site was considered complete, regardless of
how the visits were spread among the quarters.
The resulting PEP completeness is summarized only at the national level in Section 2 of this report. The
national-level summaries show how complete the various sites are although it does not show whether
25% of each method designation of the routine sites within each reporting organization was evaluated.
Such a summary will be prepared at a later date.
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PM2.5 CY99 QA Report December 2000
Bias Completeness Estimation Procedure
The preceding section describes the completeness of the PEP data base. To estimate completeness of
bias, AIRS routine data is merged with the PEP data base since both a PEP and a routine
concentration are needed to calculate bias. As per 40 CFR 58 App. A, Sec. 3.5.3, approximately
25% of each method designation of the routine sites within each reporting organization are supposed to
be visited 4 times in a year by the PEP, preferably once per quarter. Thus bias is complete if
approximately 25% of the PM2.5 monitoring network has 3 (75% of 4) pairs of valid PEP and routine
data.
The data used to estimate bias completeness originated from an AMP350 Raw Data Listing extraction
from AIRS on 7/26/00 and from the PEP data base described above. Completeness statistics are
calculated according to the following procedure.
Only non-null routine data and valid PEP data were used in the calculation of completeness.
Any PEP data points associated with "parking lot studies" were deleted prior to completeness
calculations, even if the study had a collocated FRM.
For some site/day combinations, there are multiple observations in the PEP data base or in the
AIRS data base. For the PEP, only the first valid observation was used. For AIRS, the lowest
POC with a valid observation was used.
If a site has at least 3 (75% of 4) valid pairs of PEP and routine data, then it is considered
complete, regardless of how the visits were spread among the quarters.
The resulting bias completeness is summarized only at the national level in Section 2 of this report. The
national-level summaries show how complete the various sites are although it does not show whether
25% of each method designation of the routine sites within each reporting organization was evaluated.
Such a summary will be prepared at a later date.
Precision, Accuracy and Bias Estimation
Three quality control (QC) procedures, at the national level, will be used to evaluate uncertainty for the
PM2 5 network. All of the statistics described in this section can be found in 40 CFR 58 App. A,
Section 5.5.1. The equation numbers from CFR are included in the discussion for reference.
1. Flow rate checks - Since flow rate is checked against standards of known value, this check
provides estimates of accuracy and/or bias at the instrument level. The following is a description of
the process used to estimate accuracy based on the annual flow rate checks.
Accuracy is estimated by using pairs of true and measured values for flow rate measured in liters
per minute (L/min). The pairs are for the same site and same day. Specifically, for a given site and
day, if Xt is the audit standard flow rate and Yt is the measured flow rate, then accuracy (CFR
Equation 13), defined as the percent difference (4) is calculated as
d = Yl~^ x 100 (Equation 1)
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PM2.5 CY99 QA Report December 2000
In this report, estimates of accuracy are presented for various levels of aggregation, sometimes
aggregating over time (such as quarterly or annually), sometimes aggregating over samplers (such as
all samplers of a specific method designation), and sometimes aggregating over both time and
samplers (such as annually for a specific method designation). These various levels of aggregation
are achieved using the same basic statistic. This statistic averages the individual accuracy values
from Equation 1 to the desired level of aggregation. Specifically, if ซ,- is the number of flow rate
checks and dhd2, ..., dnj are the resulting accuracy values, then the average accuracy estimate
(CFR Equations 14, 15, 16, 17, and 18) is
1 ^
D = x y di (Equation 2)
nj
i=\
For this report, average accuracy values (Equation 2) are calculated for each method designation
by quarter and for the entire year. Additionally, the number of flow rate checks that are within 4%
of the audit standard and the number within 5% of the design flow rate of 16.67 L/min are also
calculated. These results are presented in Section 2.
2. Collocated measurements - Since the true concentrations sampled from collocated samples are
unknown, these checks provide an estimate of precision of the measurement system. However,
the statistic developed to summarize the collocated measurements has one component attributable
to precision and another component attributable to bias. For now, this document describes only the
results for the combined effect for precision and bias. The individual components will be described
at a later date.
Following is a description of the statistics used to estimate precision based on the collocated
instruments. Precision is estimated by using pairs of collocated PM2.5 measurements. The pairs of
measurements are for the same site and same day. Specifically, for a given site and day, if Xt is the
concentration (|ig/m3) produced from the primary sampler (the routine monitor) and Yf is the
concentration produced from the duplicate sampler (the monitor used for quality control), then the
percent difference, 4(CFR Equation 19), is calculated as
-y. _ vr
d = -. - r-r- x 100 (Equation 3)
^
The percent difference from Equation 3 is used to calculate the coefficient of variation for a single
site and day (CFR Equation 20) as follows
Ml
CVi = -i-pr (Equation 4)
A/2
In this report, estimates of precision are presented for various levels of aggregation, sometimes
aggregating over time, sometimes aggregating over samplers, and sometimes aggregating over both
time and samplers. These various levels of aggregation are all achieved using the same basic
statistic. This statistic pools the individual coefficients of variation described above in Equation 4 to
the desired level of aggregation. Specifically, if w, is the number of pairs and CV}, CV2, ..., CVnj
Page -14-
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PM2.5 CY99 QA Report December 2000
are the coefficients of variation for each of the pairs to be pooled, then the precision estimate
(approximately CFR Equation 21) is
- - (Equation 5)
Confidence intervals can be constructed for these pooled estimates of precision in Equation 5 by
using the following equations, one for the lower limit (CFR Equation 22) and one for the upper limit
(CFR Equation 23).
ni
Lower 90% Confidence Limit = CV '
v2
A0.95,nj
n
Upper 90% Confidence Limit = CV '
In these equations, %QQ5 ^ and Xo95dfare ^ ^-05 and 0.95 quantiles of the chi-square
distribution with degrees of freedom (df) equal to ซ,-.
There are a few issues with calculating individual and pooled estimates of precision. (A) In
calculating the percent differences in Equation 3, 40 CFR 58 App A Sect 5.5.2 states that only
pairs where both concentrations are greater than 6 g/m3 are to be used. For this report, precision
was estimated both including these low pairs and excluding them. The impact of these low values is
discussed in Section 2. (B) In the equation for the pooled estimate of precision, individual
coefficients of variation are squared before being averaged. If there is a large individual coefficient
of variation, it can have a very strong influence on the resulting pooled estimate. Hence, pooled
estimates of precision were calculated both including all individual coefficients of variation and
excluding large coefficients of variation. The impact of these large values is discussed in Section 2.
(C) Comparing one pooled estimate of precision to another (such as comparing quarterly estimates
or comparing one site to another) requires some care because one estimate may be based on just a
few values and hence be less robust than an estimate based on more values. For comparisons of
precision for different times or different places, it is important to look at the upper and lower
confidence limits to get an understanding of how robust the estimates are.
3. Federal Reference Method (FRM) Evaluation - This evaluation is performed by comparing a
monitoring instrument against an instrument that is considered "truth" and can provide an estimate of
measurement system bias. Following is a description of the statistics used to estimate bias.
Bias is estimated by using pairs of PM2.5 measurements, where one of the measurements is from a
routine, State-operated monitor and the second measurement is from a monitor operated as part of
the Performance Evaluation Program. The pairs of measurements are for the same site and same
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PM2.5 CY99 QA Report December 2000
day. Specifically, for a given site and day, if Xt is the concentration produced from the PEP
sampler and Yt is the concentration produced from the State-operated sampler, then accuracy
(CFR Equation 26), defined as the percent difference (d,) is calculated as is calculated as
di = Y'~Xl x 100 (Equation6)
xi
In this report, estimates of bias are presented for various levels of aggregation, sometimes
aggregating over time, sometimes aggregating over samplers, and sometimes aggregating over both
time and samplers. These various levels of aggregation are achieved using the same basic statistic.
This statistic averages the individual biases (4) described in Equation 6 to the desired level of
aggregation. Specifically, if ซ,- is the number of pairs and dh d2, ..., dnj are the biases for each of the
pairs to be averaged, then the aggregate bias estimate (CFR Equations 27, 31 and 35) D is
1 nj
D = x y^ d (Equation 6)
=
Confidence intervals can be constructed for these average bias estimates in Equation 6. Such
intervals require an estimate of the variability of average bias. Since bias likely varies by site and
quarter, the estimate of the variability of the average bias should be based on a pooled estimate of
site/quarter variability. However, the PEP usually evaluates each site just once per quarter, which is
not sufficient for estimating the site/quarter variability. Since site/quarter variability is not estimable
with the current PEP design, the site variability (using all 4 bias estimates for the year) or the quarter
variability (using all sites for a quarter) can be used, with the understanding that these estimates of
variability are confounded with other sources of variability. Specifically, an estimate of the
variability of the average bias is
s=}\ (Equation!)
The 95% confidence interval for the average bias is then calculated as
Lower 95% Confidence Limit = D -10 975 df x s/
/ni
Upper 95% Confidence Limit = D +10 975 df x y
3
where tQ 975 df is the 0.975 quantile of Student's t distribution with degrees of freedom (df) equal
to nj and s as defined in Equation 7.
One note about the bias estimates in this report. Two very anomalous values were deleted from the
analysis, even though they were validated by the states and the PEP. One pair is from a site in
California on 11/2/99 and has a state value of 22.9 g/m3 and a PEP value of 74.2 g/m3. The
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PM2.5 CY99 QA Report December 2000
second pair is from a site in Missouri on 12/14/99 and has a state value of 24.2 g/m3 and a PEP
value of 109.5 g/m3.
Detectability
There are many definitions and even more interpretations for a method detection limit. Sometimes
detection limits are based on protecting against false positive conclusions, that is, concluding that a
measured concentration has been detected when in fact there is nothing to detect, and sometimes they
are based on protecting against both false positive and false negative conclusions. In Appendix L to 40
CFR 50, it is stated in Section 3.1 that the lower detection limit of the mass concentration range is
estimated to be approximately 2 g/m3. In Appendix A to 40 CFR 55, it is stated in Section 5.5.2 that
collocated measurement pairs are to be used in precision calculations only when both measurements are
above 6 g/m3. These are two separate issues that need to be addressed. One is that detectability
needs to be quantified so that two methods can be compared. For example, a method with a lower
limit of detection is generally preferable to one with a higher limit, especially when concentrations are
expected to be "low." The second is a cutoff value that needs to be defined so that statistics, such as
precision and possibly bias, behave as desired for the entire range of possible measurements.
This report does not attempt to evaluate the currently stated method detection limit of 2 g/m3. In
future reports, this method detection limit may be assessed using statistical procedures like those
described in some EPA reports and papers (see references 5 & 6).
With regard to a cutoff value for estimation of precision, this report describes the impact of pairs
involving concentrations less than or equal to 6 g/m3. Since more than 20% of all the 1999 precision
pairs and more than 20% of all the 1999 bias pairs has one or both measurements less than or equal to
6 g/m3, it is important to understand the stability of the estimators to these small concentrations. As
shown in Section 2, both the precision and bias estimators appear to be well behaved, even when
including pairs involving concentrations less than or equal to 6 g/m3. OAQPS will continue to review
the reasonableness of the 6ซ g/m3 cutoff and minimally will continue to report estimates that include
these small values and estimates that exclude these small values.
Comparability
The goal of comparability is to determine whether two measurements can be compared. For example,
if one instrument that has a 50% bias and another has no bias, then making statements about how the
measurements from one instrument relate to the measurements from the other instrument are
questionable.
There is interest in comparing PM2 5 measurements from multiple types of instruments, multiple points in
time, multiple points in space, and various combinations of instrument, time and place. If the
completeness, precision, bias, and detection limit are similar for all the PM2.5 instruments, then such
comparisons are reasonable. They may be reasonable even if some of these data quality indicators are
not similar, depending on the purpose of the analysis.
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PM2.5 CY99 QA Report December 2000
Section 2 begins to discuss the comparability of the data from one quarter to the next, at the national
level. More discussion is needed, especially at a finer spatial resolution. However, due to the lack of
data for these data quality indicators at a spatial level less than the nation, it is not yet feasible to
perform such comparisons. When a sufficient quantity of data become available, OAQPS will prepare
several graphics to depict comparability. These graphics will include quarterly maps of data
completeness, precision at the reporting organization level, and bias at the reporting organization level.
Additionally, formal statistical procedures will be applied to the precision and bias data to determine
whether there are "clusters" of reporting organizations that appear to have different precision and/or
bias.
References
1. U.S. EPA. 2000. Guidance for the Data Quality Objective Process EPA QA/G4, EPA/600/R-
96/055, August 2000
2. U. S. EPA. 1998 Guidance for Quality Assurance Project Plans EPA QA/G-5, EPA/600/R-
98/018, February 1998
3. 40 CFR 58 (62 FR 38763, July 18, 1997)
4. 40 CFR 50 (62 FR 38651, July 18, 1997)
5. Clayton, C.A.; Flines, J.W.; Hartwell, T.D.; Burrows, P.M. "Demonstration of a Technique for
Estimating Detection Limits with Specified Assurance Probabilities"; Research Triangle Institute
Technical Report 2757/05-0IF, Environmental Protection Agency Contract No. 68-01-6826;
Research Triangle Institute; Research Triangle Park, NC, 1986.
6. Clayton, C.A.; Hines, J.W.; Elkins, P.D. "Detection Limits with Specified Assurance Probabilities"
Anal. Chem. 1987, 59, 2506-2514
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PM2.5 CY99 QA Report
December 2000
Section 2 Assessment of Data Quality Indicators
This section will provide an assessment of the data quality indicators of completeness, precision, bias,
accuracy and comparability. In addition, there will be a brief discussion of techniques being looked at
to determine the sensitivity of the measurement system to detect low PM2 5 concentrations. It must be
noted that all assessments were implemented on data present in AIRS on 7/26/00. This date
was chosen because it was after the July 1 certification date and because OAQPS wanted to report the
data quality results to the States and EPA in a timely manner. OAQPS will update the assessment of
CY99 data in late January 2001, assuming there is a significant increase of data in AIRS.
Data Completeness
This section will evaluate the completeness statistics for routine PM2.5 concentration data and the quality
assurance data for the collocated precision, the quarterly flow rate audits, and the Performance
Evaluation Program.
Completeness - Routine Data
Figure 2.1 represents CY1999 routine data completeness as of 7/26/00. Figure 2.2 shows a
geographic illustration of this information. Section 1 provided an explanation of the process to generate
this information which is based upon the completeness requirements for comparison to the NAAQS (40
CFR 50 App N, Sect 2). Attachment 2-1 provides a listing of completeness for each site in 1999.
Completeness - Routine (FRM)
7/26/00 AIRS Extraction
Data Capture by Quarter, 1999
Primary samplers only (lowest POC)
800
979
FRM sites
operated
in 1999
(1052 FRM
Sites
operating
as of 8/00)
Quarter 1
Quarter 2
Quarter 3
75% or more D 50-75% D < 50% |
Number of sites
reporting data:
753
845
Quarter 4
887
924 FRM sites have data in AIRS (7/26/00).
Of these, 239 sites have 4 complete quarters (> 75%).
Figure 2.1 Routine data completeness
Page -19-
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TO
e
bJ
hd
3
n
o
3
a
1999 PM2.5 FRM Data Completeness
OQ
to
o
O
o
Notes
As of AIRS, 7/26/00
Site basis; only primary monitors included
Only sites that operated in 1999 included
979 Total Sites
Map Legend
75% complete in all 4 quarters [239]
Other sites with data [685]
Sites with no 1999 data in AIRS [55]
n
O
a
o
G
re
o
re
cr
re
o
o
o
-------
PM2.5 CY99 QA Report
December 2000
Number of sites reporting data in...
55
D Zero quarters
D Only 1 quarter
CD Any 2 quarters
CD Any 3 quarters
D All 4 quarters
For calendar year 1999, State and local monitoring organizations reported 979 active sites to AIRS.
Of these 979 sites, 924 (94%) sites reported PM2 5 concentration data; 55 sites did not report
concentration data by 7/26/00. Of the 924 sites reporting concentration data, 239 sites (26%)
reported 4 complete quarters of data, meaning they had greater than or equal to 75% of the anticipated
data reported for each quarter. This level of completeness is important since comparison to the
NAAQS for purposes of attainment determinations requires, with some exceptions, that all four
quarters meet the completeness statistic. Figure 2.1 also indicates the number of sites reporting data for
each quarter (689, 753, 845, 887 respectively). Using these values, one can compare how many sites
met the completeness criteria for any quarter. The first quarter had about 43% of the reporting sites
meeting the 75% completeness goal, whereas the second, third and fourth quarters each had
approximately 72% of the sites reporting data to AIRS meeting the 75% completeness goals. Figure
2.1 also displays statistics for sites having between 50% and 75% completeness because these sites
may also be used for NAAQS comparisons based on
the average concentration in the quarter, acceptable
data substitution for the missing data, and Regional
Administrator approval. In addition, for non-
attainment purposes, the Regional Administrator may
use sites that have as few as 11 values per quarter if
the average quarterly concentration is above the
NAAQS (40 CFR 50 App N, Sect 2) and less under
unusual conditions. Information on completeness
using these exceptions are not generated for this
report. The pie chart, illustrated in Figure 2.3
indicates how many sites reported any concentration
data (not necessarily meeting the
completeness statistic) in any combination of
quarters.
Flagged data were included in the
completeness count; null value data were not.
Flagged data values can be data qualifiers
(provided in a March 27, 2000 OAQPS
guidance memorandum), sampler generated
flags, or exceptional events. Figure 2.4
provides a breakdown of the routine
concentration data in AIRS relative to flagged,
unflagged, and null value code data.
Attachment 2-2 provides a listing of flag use
by State and flag type.
(979 total sites operating; 924 reported data)
7/26/00 AIRS Extraction
Figure 2.3 Sites reporting routine data
Breakdown of the 108, 816 PM2.5 Data Points Reported To AIRS
Null Values
10.8%
4 2o/0 Data Qualifiers
3 9% Sarnpler Generated
0.5% Exceptional Events
80.6%
Values w/out Qualifiers
7/26/00 AIRS Extraction
Figure 2.4 Breakdown of routine concentration values in
AIRS
It is assumed that some of the data flagged
with a data qualifier or sampler generated code (approximately 8% of the data) may be invalidated
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PM2.5 CY99 QA Report
December 2000
which may impact routine completeness. OAQPS and the States will be determining the quality of the
flagged information over the next year.
Completeness - Collocated Precision
Completeness - Precision
7/26/00 AIRS Extraction
Data Completeness by Quarter, 1999
Overall Goal =
245 sites In '99
(Precision
checks
required at
25% of sites)
Quarter 1
Quarter 2
Quarter 4
Benchmark (25% of Mass Reporting Sites) I
O Sites reporting precision data
I Sites w/ 73% or more
(11/15=73%)
Currently, 25 sites have 4 complete quarters (> 73%)
Figure 2.5 Completeness of collocated precision data
Twenty five percent of the monitoring
sites for a reporting organization are
required to provide collocated data at
a frequency of every 6 days (-15
values per quarter). Figure 2.5
provides completeness information for
collocated data in AIRS as of 7/26/00.
Attachment 2-3 provides a listing, by
site, of the precision completeness.
Of the 979 active sites in AIRS,
approximately 245 sites should have
reported collocated precision data for
1999. This is not an exact calculation
since the actual number of collocated
sites are determined on a reporting
organization/method designation basis. However, for this assessment, 245 collocated sites will be used
as an estimate of 25% of the monitoring network. For each quarter, a benchmark value is generated as
25% of the sites that reported any concentration information in that quarter. For example, Figure 2.1
reported that 689 sites reported data in quarter 1; 25% of this value is 172 which is the benchmark
reported in quarter 1 of Figure 2.5. The second column (Fig 2.5) for each quarter provides information
on sites reporting any precision values. The last column in the quarter reports sites that have complete
(11 or more collocated measurements per quarter) precision data. For the first quarter 27% of the
sites had complete precision reporting. For the second, third, and fourth quarters, the percentage of
sites reporting complete data were 46%, 52% and 54%. Even though there was a large increase in
percentage of complete sites from the first quarter to
the second quarter, this trend has not continued into
the third and fourth quarters. As of the 7/26/00 AIRS
extraction there are only 24 sites reporting 4 complete
quarters (> 73%) of precision data.
Number of sites reporting precision data in...
EH Zero quarters
EH Only 1 quarter
EH Any 2 quarters
EH Any 3 quarters
EH All 4 quarters
(245 sites should have reported precision; 220 actually did)
7/26/00 AIRS Extraction
Figure 2.6 Breakdown of precision completeness
Figure 2.6 presents a breakdown of the number of
sites providing any precision data (not necessarily
meeting the completeness statistic) in various
combinations of quarters.
Another goal was to establish 80% of the collocated
monitors at the sites that the State, local and tribal
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PM2.5 CY99 QA Report
December 2000
monitoring organization felt would provide annual averages at concentrations > 90% of the annual or
24-hour NAAQS (if that is affecting the area). Table 2-1 provides this information for the annual
NAAQS. Since 46% of the routine sites (426 sites) had 1999 mean concentrations > 13.5 |ig/m3 and
a goal of 196 collocated sites would be needed to meet the 80% criteria, it appears that more sites
could be collocated at sites with mean concentrations near or exceeding the annual standard. As of the
7/26/00 AIRS extraction, approximately 50% of the collocated sites (105 sites) had 1999 mean
concentrations > 13.5 |ig/m3. Since some reporting organizations may not have any or only few sites
reporting average annual concentrations >13.5 jig/m3 it was not expected that 80% percent of the
collocated sites in the network would have average annual concentrations >13.5 jig/m3. However, if
reporting organizations review their routine and collocated sites (Attachments 2-1 and 2-3) it appears
that some can relocate collocated monitors to sites near or exceeding the NAAQS.
Table 2-1 Total and Percentages of Precision Sites Located at Sites Around the Annual NAAQS
Of 924 routine sites
where...
C Y99 mean > 13.5 ug/m3
CY99mean<13.5 ug/m3
Total
Count
426
498
% of 924
Total
46%
54%
Of 220 precision data
sites where..
C Y99 mean > 13.5 ug/m3
CY99mean< 13. 5 ug/m3
Precision
Count
105
115
% of 220
Total
48%
52%
Completeness - Flow Rate Audits
As with collocated precision, the States and local monitoring organizations are required to perform and
submit flow rate accuracy audits on all their routine samplers every quarter. Figure 2.7 presents the
completeness of this information. Attachment 2-4 provides a listing by State and site of the flow rate
audit completeness.
Completeness - Accuracy
7/26/00 AIRS Extraction
Data Completeness by Quarter, 1999
1000
800
600
400
200
0
Overall Goal =
979 sites In '99
(Accuracy checks
required at all sites)
Quarter 1 Quarter 2 Quarter 3 Quarter 4
| U Benchmark (All Reporting Sites) D Sites reporting accuracy data |
Currently, 176 sites reported accuracy transactions in
all 4 quarters (at least 1 per quarter)
Figure 2.7 Completeness of flow rate audit accuracy data.
Based on active sites in AIRS,
979 sites (as indicated in the
routine data completeness
section) should have reported
flow rate audits in each
quarter. However, since sites
started up different times of the
year, OAQPS used a
"benchmark" of sites reporting
data in each quarter of 1999,
as indicated in Figure 2.1, to
assess completeness. Since
only one accuracy value is
required for each site, the site
for any one quarter is either
complete or it is not. The
percentage of sites reporting
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PM2.5 CY99 QA Report
December 2000
Number of sites reporting accuracy data in.
CD Zero quarters
O Only 1 quarter
O Any 2 quarters
O Any 3 quarters
D All 4 quarters
(979 sites should have reported accuracy; 456 actually did)
7/26/00 AIRS Extraction
Figure 2.8 Breakdown of flow rate audit data
flow rate audits is around 40% for each quarter,
meaning that less than half of the network has flow rate
audit information reported to AIRS. For the year, the
average completeness for the nation was around 40%
for sites reporting data, meaning that, on average, fewer
than 2 flow rate accuracy audits are being reported
when 4 are required. Currently, 176 sites or
approximately 18% of the networks sites meet the
accuracy completeness requirements for all four
quarters
Figure 2.8 reports the number of sites reporting any
accuracy data (not necessarily meeting the
completeness statistic) in various combinations of
quarters.
Completeness - Performance Evaluation Program (PEP) and Routine Data Bias Pairs
CY99 Completeness
Performance Evaluation Program
7/26/00 AIRS Extraction
Quarter 1 Quarter2 Quarters Quarter4
Benchmark (25% of MassP 75% Goal
Reporting Sites)
Annual
Valid Pairs
Similar to the collocated
precision completeness goal, the
completeness goal of the PEP
was to collect data from 25% of
each method designation in a
reporting organization at a
frequency of once per quarter.
Using the number of active sites
in calendar year 1999 (979),
-245 sites would require a
performance evaluation. This is
not an exact calculation since the
actual number of performance
evaluation sites must be
determined on a reporting
organization/method designation basis. However, for this assessment, an initial goal of 245 performance
evaluation sites is used. Figure 2.9 provides an evaluation of this goal. The completeness goals were
not met for the first quarter; but were met for the other three. The overall completeness goal, based on
paired PEP/routine samples was 71%.
PEP Data Completeness -
The PEP completeness goal required that 75% of the samples be valid for each site, or 3 out of the 4
expected samples would be collected from each site. In addition, it was a goal to visit the performance
evaluation sites in all four quarters. Table 2-2 presents the evaluation of these completeness goals. The
Figure 2.9 Completeness of Performance Evaluation/routine sample pairs
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PM2.5 CY99 QA Report
December 2000
goals are based on the overall goal of 245 sites (25% of the 979 active sites). Table 2-2 indicates that
a total of 281 sites were visited in 1999, which is greater than the goal of 245. However, 34 sites had
only one or two PEP visits and therefore did not meet the goal of at least 3 visits per year. The shaded
portion of the table indicates the sites that meet the requirement of at least 3 visits, which total 247 sites.
This meets the completeness goal. Out of the 247, 7 sites had 3 PEP visits but they occurred in 2
quarters, leaving 240 sites that met the goal of at least 3 visits in 3 different quarters. Thus the PEP had
a completeness of 98%.
PEP/Routine Sample Completeness -
For every PEP sample, there must be a corresponding valid routine value to be able to calculated bias.
The third column in each quarter and the annual estimate provides this completeness evaluation. Table
2-3 provides the number of paired PEP/routine samples as of 7/26/00. Out of the 281 sites with valid
PEP data, only 239 sites have data to pair with the PEP data, and only 160 sites have at least 3 pairs.
Table 2-2 1999 PEP Site Completeness
Frequency
1 or 2 PEP visits
3 PEP Visits
4 PEP Visits
> 4 PEP Visits
Total Sites
Total Samples
Number of Quarters Visits Were Made
1
Quarter
17
0
0
0
17
19
2
Quarters
17
7
0
0
24
55
3
Quarters
NA
65
33
3
101
342
4
Quarters
NA
NA
127
12
139
568
Total
Sites
34
72
160
15
281
Site with
>3 visits
r
Valid
Samples
53
216
640
75
247 |
rsn
Table 2-3 CY99 Paired PEP/Routine Data
Frequency
1 or 2 pairs
3 Pairs
4 Pairs
> 4 Pairs
Total Sites
Total Samples
Number of Quarters Visits Were Made
1
Quarter
31
0
0
0
31
31
2
Quarters
48
5
0
0
53
111
3
Quarters
NA
67
17
0
84
269
4
Quarters
NA
NA
69
2
71
286
Total
Sites
79
72
86
2
239
Sites with
>3 pairs
Valid
Samples
127
216
344
10
160 |
II 697 II
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PM2.5 CY99 QA Report
December 2000
If one looks at the last column in each table, of the 984 valid PEP values, there are only 697 that have a
non-null routine sample match in AIRS, which leaves 287 PEP values without a routine value. Forty-
five of these PEP values are matched with routine values that are null value codes. The remaining 242
PEP values are shown in attachment 2-5. Possible reasons for missing values could be due to PEP or
routine samples taken on different days or data not yet entered into AIRS. However, the missing 287
values account for 30% of the performance evaluation information which affects the confidence in the
bias estimates made later on in this section, particularly when one attempts to assess bias at a reporting
organization or method designation level
Precision - Collocated Sampling
All precision data were aggregated to provide a national estimate. Figures 2.10 and 2.11 provide three
estimates of precision for calendar year 1999 from data extracted from AIRS on 7/26/00. Figure 2.10
presents a national estimate as described in 40 CFR 58 where pairs that have one or both
10
#
5
0
CY99 Collocated Precision Estimate
Pairs with any value <6 ug/m3 removed
7/26/00 AIRS Extraction
DQO
"^^ I
_^
Q1 02 03 CM annual
Quarters and Annual Estimate
CY99 Collocated Precision Estimate
7/26/00 AIRS Extraction
10
Outliers removed, <6 ug/m3 kept
Outliers removed, <6 ug/m3 removed
DQO
01
Q2 03 04
Quarters and Annual Estimate
Annual
Figure 2.10 Precision estimate based on CFR
requirements
Figure 2.11 Precision estimates with outliers removed
concentration values less than or equal to 6 |ig/m3 removed. The second, third, fourth quarter and the
annual precision estimate met the DQO of 10% coefficient of variation. This estimate is based on a data
base where less than 50% of the sites have complete precision data for 1999 (see precision
completeness above). OAQPS evaluated precision by method designation (e.g. Andersen
Sequentials, R&P Sequentials etc.) and did not find any significant difference between the precision
estimates at the national level, based upon the limited data set.
Figure 2.11 presents two additional national precision estimates: 1) where 232 outliers where removed
but pairs with values less than or equal to 6 jig/m3 were kept and, 2) where the outliers were removed
and the pairs with values less than or equal to 6 jig/m3 were removed. An outlier was defined as any
value with a percent difference greater than + 50%. (See Equation 3 of Section 1 for a definition of
percent difference.) Of these 232 outliers, 81 were less than -100% or greater than 100%. The 232
outliers represent 2.8% of all paired precision values. Attachment 2-6 provides a listing of these
outliers. Table 2-4 provides a comparison of the number of paired values behind the three precision
estimates described above.
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PM2.5 CY99 QA Report
December 2000
Table 2-4 Paired Concentration Values Used in Each National Precision Estimate (as of 7/26/00)
Quarter
1
2
3
4
Annual
Total
Pairs
1424
1938
2369
2497
8228
Pairs s 6 u,g/m3
removed
1172
1401
1886
2041
6500
Outliers removed,
pairs s 6 u,g/m3 kept
1397
1916
2353
2480
8146
Outliers removed,
pairs s 6 u,g/m3 removed
1145
1379
1870
2024
6418
Based on the evaluations of both figures, it appears that the outliers, which numbered on average about
55 per quarter, affect the quarterly precision estimates more in the first and second quarters than the 6
jig/m3 criteria. As an example, 27 collocated "outlier" pairs, out of a total of 1172 pairs, increased the
first quarter precision estimate from 8.2% to 12.1%.
Given that the outliers are removed, Figure 2.11 illustrates that the precision estimates are fairly similar
with or without the use of pairs with a concentration value of less than or equal to 6 |ig/m3. This might
suggest that the precision comparisons can be made with confidence at lower concentrations. Table
2.4 also shows that keeping the pairs with concentrations less than or equal to 6 jig/m3 increased the
pair count by 1,646 pairs.
The precision estimates in Figure 2.10 provide an indication of the observed precision during 1999.
The precision estimates in Figure 2.11 may provide a better estimate of the expected precision for the
future. If the large outliers seen in the first and second quarters of 1999 are the result of start-up issues,
then the outliers are not expected to exist in future years and hence removing them before estimating
precision is appropriate. If, instead, the large outliers in the first and second quarters are due to
something seasonal, then the outliers may occur in future years and hence should be retained in the
estimation of precision. Analysis of the precision data from 2000 will begin to determine whether the
outliers from 1999 are in fact anomalies associated with start-up or are regular occurrences. In the
meantime, with the assumption that valid data has been entered in AIRS, OAQPS can not remove or
edit outliers and therefore will report the estimates generated in Figure 2.10 which includes outliers.
To this point, the discussion about precision has been at the national level. However, the DQO for
precision was established at the reporting organization level. Attachment 2-7 presents estimates of
precision for each reporting organization on a quarterly and annual basis. Note that all of the estimates
in Attachment 2-7 should be multiplied by 100 to be interpreted as percentages. For example, a
precision estimate of 0.121 represents a coefficient of variation of 12.1%. Also, an "A" in the AIRS
SITE NUMBER column means that the estimates are for the reporting organization and an "A" in the
QUARTER column means that the estimates are for the entire year.
Also included in the attachment is information about the precision for each of the collocated sites within
the reporting organization. The site-level precision is being provided to help focus resources on sites
where the data appear to be more variable, so that the cause of the increased variability can be
understood and hopefully reduced. Note that due to the lack of data, precision at a reporting
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PM2.5 CY99 QA Report
December 2000
organization level, and even more so at the site level, may be based on very few values and hence the
aggregate precision may not accurately reflect the true, underlying precision.
The number of pairs behind each of the precision estimates is presented in the attachment. Also
included in the attachment are confidence intervals for each of the precision estimates. Again, multiply
by 100 to interpret as percentages. Preferably, the interval should be small and be entirely below 10%.
If the interval is not small, there may be several reasons. These reasons include:
(a) There are few observations being used to estimate the precision.
(b) One or both of the instruments at the site are imprecise.
(c) There is a consistent difference between the two samplers. For example, one of the samplers
may consistently be 10% above the other one. Such consistent differences elevate the
precision estimate. The final columns of Attachment 2-7 provide an estimate of this consistent
difference. For example, an estimated relative difference of-0.086 means that the
concentration measured by the collocated sampler is 8.6% lower than the concentration
measured by the routine sampler, on average. Confidence intervals for the relative differences
are provided in the final columns of the attachment. If a precision estimate is large, the relative
difference should be checked. If the relative difference is large, then one or both of the
instruments likely is biased.
(d) A combination of any of the above can be causing the large interval.
Accuracy - Flow Rate Audits
Although the average completeness for flow rate audits is about 40%, the data from these audits
indicates that the Federal Reference Method samplers are well within the acceptance requirements.
There are two acceptance criteria for flow rate: 1) the flow rate measured by the FRM must be within
4% of the flow rate measured by an independent transfer standard and 2) the flow rate measured by
the FRM instrument must be within 5% of the 16.67 L/min design flow rate. Table 2-5 provides a flow
rate summary for the instruments providing flow rate data to AIRS as of the 7/26/00 extraction date.
Table 2-5 CY99 Flow Rate Summary (as of 7/26/00)
FRM
Instrument
BGI Single
R&P Single
R&P Sequential
Andersen
Single
Andersen
Sequential
National
Estimate
Number
of Audits
32
154
1308
7
264
1765
Number
3
11
75
0
18
107
Number
2
1
15
0
4
22
Average
Accuracy
-0.72 |
0.48
-0.06
0.57
0.20
0.02
ฃ
H 0
1-4
'
CY 99 Flow Rate Accuracy
Acceptance <4% from Standard < 5% from Design
-- And Seep*- RP Secf*" RP Sing*- National
Q1 Q2 Q3 Q4
Quarters
Figure 2.12 CY99 Flow rate summary (as of
7/26/00)
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PM2.5 CY99 QA Report
December 2000
Figure 2.12 provides quarterly average accuracy values of those instruments that had greater than 100
flow rate audits in CY99. Based on this data, 94% of the audits were within the + 4% criteria and 99%
within + 5% of the 16.67 L/min design flow rate.
Bias- Performance Evaluation Program and Routine Data
Similar to the evaluation of collocated precision, a number of estimates were used to summarize bias
using the performance evaluation data and the routine data extracted from AIRS on 7/26/00. Figure
2.13 presents the bias estimates as described in 40 CFR 58 and guidance. The estimates in Figure
2.13 are based on all available pairs, excluding pairs that had one or both sample concentrations less
than or equal to 6 jig/m3. For the data available in AIRS, it appears that the DQO, at a national level, is
being achieved.
CY99 Bias Estimate
Pairs with any value < 6 ug/m3 removed
7/26/00 AIRS Extraction
02 03 CM
Quarters and Annual Estimate
1-
Annual
Figure 2.13 Bias estimate based on requirements and
guidance
Bias Estimates Without Outliers
CY99 Data
7/26/00 AIRS Extraction
"*" Outliers removed, <6 ug/m3 kept
~*~ Outliers removed, <6 ug/m3 removed
Q2 Q3 Q4
Quarters and Annual Estimates
Annual
Figure 2.14 Bias estimates with outliers removed
Figure 2.14 provides estimates with outliers removed from the data set. An outlier is defined as any
paired value that had an accuracy greater than +50%. (See Equation 6 of Section 1 for a definition of
accuracy.) There were 30 outliers identified representing 4.3% of all bias pairs, and these are listed in
Attachment 2-8. Table 2-6 provides a comparison of the number of paired values behind the quarterly
and annual bias estimates.
Table 2-6 Paired Bias Values Used in Each Bias Estimate
Quarter
1
2
3
4
Annual
Total
Pairs
117
190
190
184
681
Pairs ^ 6 u,g/m3
removed
97
144
156
151
548
Outliers removed,
pairs s 6 u,g/m3 kept
111
184
188
182
665
Outliers removed,
pairs s 6 u,g/m3 removed
91
138
154
149
532
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PM2.5 CY99 QA Report
December 2000
Similar to the findings in the precision data, there is almost no difference in the bias estimates whether
keeping or removing a pair when one or both values is less than or equal to 6 |ig/m3, as illustrated in
Figure 2.14. However, it appears outliers had an effect on the national bias estimate in the first quarter
of 1999. The first quarter 1999 bias estimate including outliers was 9.0% and excluding outliers was
3.8%.
Another illustration of the effects of first
quarter data can be seen when reviewing
bias estimates for two method
designations, the Andersen Sequential and
the R & P Sequential. Figure 2.15
provides a comparison of these two
method designations. Figure 2.15 shows
both that the large national bias for the first
quarter is mainly driven by the large
estimate for the Andersen Sequentials and
that the bias estimate for the Andersen
Sequentials has dropped dramatically since
the first quarter.
CY99 Bias Estimates
7/26/00 AIRS Extraction
-*~ Andersen Sequentials, < 6ug/m3 removed
~~*~ R&P Sequentials, < 6ug/m3 removed
ฃ 30
!ง 20
m
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PM2.5 CY99 QA Report
December 2000
data. As indicated in the bias completeness section, there are still 287 pairs of data missing from the
overall bias comparison, some of which might reduce the effect of outliers on the first quarter bias
estimate. Once outliers were removed, there were no significant differences between the precision
estimates when one kept or removed pairs that had a sample concentrations less than or equal to 6
jig/m3. In all three precision estimates Andersen Sequential exceeded the bias DQO for the first
quarter.
Figure 2.17, represents the R&P Sequential
bias using the three precision estimates.
Neither outliers nor values less than or equal
to 6 ug/m3 seemed to have had much effect on
the bias estimate. Based upon the data
available on 7/26/00, all bias estimates are
well within the DQO limits but appear to be
biased slightly negative compared to the PEP.
Table 2-8 provides the number of paired
values used to generate the estimates in Figure
2.17. There was more paired information
available for these estimates than were
available for the Andersen Sequentials. In
addition, it appears that
most of the outliers had
at least one or both
values less than or equal
to the 6 ug/m3 criteria
which is why the values
for these two columns
(2nd and 4th column) are
very close.
CY99 R&P Sequential Bias Estimates
7/26/00 AIRS Extraction
~*~ < 6ug/m3 removed ~*~ Outliers removed, < 6ug/m3 removed
~~*~ Outliers removed
10
1
ffi 0
8,
&
9
5-10
1
~ ^^==*=^J 1
Q1 Q2 Q3 04 Annual
Quarters and Annual Estimates
Figure 2.17 R & P sequential bias estimates
Table 2-8 Paired R&P Sequential Bias Data (as of 7/26/00)
R&P Sequential
Quarter
1
2
3
4
Annual
Total
Pairs
67
111
119
125
422
Pairs <6 u,g/m3
removed
55
86
95
103
339
Outliers removed,
pairs < 6 u,g/m3
kept
67
105
119
123
414
Outliers removed,
pairs < 6 u,g/m3
removed
55
80
95
101
331
To this point, the
discussion about bias
has been at the national level. The DQO for bias was established at the reporting organization level.
However, the reporting organization level statistics are not presented in this report for two reasons.
First, there are few data points at the reporting organization level. Specifically, the number of bias
estimates for 1999 for each reporting organization should be approximately equal to the number of sites
within the reporting organization. Secondly, although it is straight forward to estimate the average bias
for each reporting organization, it is less simple to estimate the confidence interval for the average. The
confidence intervals are important to understanding the interpretation of an average. Small intervals
imply that the average value can be given a lot of credence whereas a large interval implies that the
average is less certain. The confidence intervals presented in 40 CFR 58 App A Sect. 5 were
predicated on the assumption that there would be more than one PEP visit to a site per quarter. Since
this does not occur under the current PEP schedule, the confidence intervals need to be modified. Any
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PM2.5 CY99 QA Report December 2000
modification will require confounding sources of variability, site to site, seasonally, or both. Once it is
determined which of these approaches is preferable, the reporting organization level biases and their
associated confidence intervals will be presented. This likely will not occur until the 2001 QA Report.
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PM2.5 CY99 QA Report
December 2000
Section 3 Conclusions and Recommendations
This section will summarize the evaluation of the data quality indicators and make recommendations in
an effort to improve the ambient air monitoring quality system and the resultant data quality.
Conclusions
Tables 3-1 and 3-2 provide a summary of data completeness and estimates of our primary data quality
indicators. Summary comments about these tables follow.
Table 3-1. National Completeness Summary for CY99 (as of 7/26/00)
Data Type
Routine Data
Collocation Precision
Flow Rate Accuracy
Performance Evaluations
Performance Evaluation
Pairs
Sites meeting overall
completeness requirements
for all 4 quarters
%
24%
10%
18%
100%
65%
Number
239
25
176
247
160
Sites Meeting 75% Completeness for Each
Quarter
1
31%
27%
35%
73%
49%
2
56%
46%
42%
113%
79%
3
60%
52%
44%
111%
80%
4
67%
54%
40%
104%
77%
Table 3.2. National Estimates of Primary Data Quality Indicators for CY99 (as of 7/26/00)
Data Type
Precision -Collocation
Accuracy-Flow Rate
Bias - Performance
Evaluations
Acceptance
Criteria
<10%CV
< + 4% Std.
< + 5% Design
< + 10%
National
Estimate
9.1%
0.02%
1.7%
Quarterly Estimate
1
12.1%
0.11%
9.0%
2
9.9%
0.08%
1.9%
3
6.6%
-0.04%
-0.9%
4
7.6%
-0.04%
-0.49%
Routine Data
Completeness - The completeness evaluation is based upon the strictest interpretation of the
completeness requirement in 40 CFR 50 App. TV that a site must collect 75% valid data in every
quarter in order for comparison to the NAAQS. There are other techniques, such as data substitution,
that can be used to allow more information to be used for the NAAQS comparison that are not
evaluated in this report. Therefore, the 24% overall completeness estimate is the most conservative
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PM2.5 CY99 QA Report December 2000
estimate of completeness for CY99. Since the requirement is based on 4 quarters, the overall
completeness estimate cannot be higher than the lowest quarterly completeness percentage. Therefore,
the first quarter is responsible for the overall low completeness value. Since only 24% of the sites met
completeness in all 4 quarters, the first quarter completeness value of 31% indicates that 22% of the
first quarter sites did not achieve acceptable completeness in one or more of the other three quarters.
The lack of completeness in quarter 1 can be attributed to a number of start up problems related to the
instruments, field and lab operations and data entry. The intent of this document is to report the quality
of the data and will therefore not attempt to address or associate these problems with the loss of data.
Quarters 2, 3 and 4 had better completeness estimates. In addition, data entered into AIRS after the
7/26/00 may improve the current completeness evaluation.
Based on early reviews of completeness in March 2000, OAQPS provided guidance to allow the use
of data qualifiers (flags) in an attempt to increase the completeness of routine data that some
organizations may have felt uncertain about entering to AIRS. An additional 4.7% of the routine data
was captured using the new data qualifiers. However, two States accounted for 67% of these data
qualifiers, one that flagged all their data and a second that flagged 45%.
Precision - Collocation
Completeness- The number of sites that have met the 75% completeness goal for all 4 quarters is very
low. A marked improvement in completeness occurred from the first to second quarter but only
marginal improvement in the last three quarters. As with routine data, the overall completeness value
cannot be higher than the lowest quarterly value since the requirement is based on 4 quarters. Due to
some of the start-up problems in the first quarter, some reporting organizations had to substitute their
collocated instruments for the routine instrument. In addition, whenever a routine value was invalidated,
a collocated value, collected on the same day/site, could be substituted. OAQPS provided data
substitution guidance asking the reporting organization to place the collocated information in the AIRS
parameter occurrence code 2 (POC-2) in order to be able to give the reporting organization credit for
having performed a collocation. However, some reporting organizations may not have followed this
guidance and therefore the collocated data can not be identified and counted in the completeness
estimate. The lack of information on collocated precision will make it difficult to assess the precision
data quality objective at lower levels of aggregation such as reporting organizations or method
designation. It may be necessary to institute quarterly assessments of precision completeness in order to
identify where information is lacking and to improve the capture rate of this information.
Values around the NAAQS-- In order to focus quality assurance activities around the data most
crucial in decision making, 40 CFR 58 App A Sect 3.5 required that 80% of the collocated monitors
be placed at the sites that the State, local and tribal monitoring organization felt would provide annual
averages at concentrations > 90% of the annual or 24-hour NAAQS (if that is affecting the area).
Presently, only 48% (105 sites) of the collocated sites reporting data are located at sites with annual
means > 13.5 |ig/m3 and there are 426 routine sites with an annual mean > 13.5 ug/m3. Since some
reporting organizations may not have any or only few sites reporting average annual concentrations
>13.5 jig/m3 it was not expected that 80% percent of the collocated sites in the network would have
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PM2.5 CY99 QA Report December 2000
average annual concentrations >13.5 |ig/m3. However, if reporting organizations review their routine
and collocated sites (Attachments 2-1 and 2-3) it appears that some reporting organizations can
relocate collocated monitors to sites where precision and bias estimates are most crucial. Currently, the
requirement only establishes the lower limit ( > 90% of NAAQS) but it should have also established
the upper limit. CFR should be revised to require 80% of the collocated sites be located at sites >90 to
110% of the NAAQS (13.5 to 16.5 |ig/m3).
Precision Results - It must be emphasized that the precision data quality objective (DQO) is based on
three years of precision data (75% complete). Therefore, any one year or any quarter may be above
the criteria and still meet the precision data quality objectives. An early analysis of precision suggests
that the DQO can be achieved, at least at the national level.
It was discovered that 232 outliers, which represented 2.8% of the precision data, change the national
estimate from 9.1% CV to 6.8% CV and brought down the first quarter estimate from 12.1% CV to
8.2% CV. OAQPS will ask State and locals to review these outliers to ensure their validity. For this
report they are considered valid and therefore incorporated into the overall and quarterly precision
estimates. Another interesting observation is that OAQPS did not plan on assessing any collocated
pairs that had one or both values below 6 |ig/m3. It was assumed that these values were close to the
sensitivity of the measurement system and that small actual variance at these low concentrations would
provide large coefficients of variance. This did not prove to be the case and it appears the outliers had
more influence on the precision estimate.
OAQPS investigated whether there was any significant difference in precision for different method
designations. From the available data, all the method designations appear to have comparable
precision. Based on the national precision estimates being very close to the DQO, it is anticipated that
some reporting organization precision estimates will be above the data quality objective. The effect of
the additional variability would be less confidence in estimates of individual or aggregate concentrations.
Accuracy - Flow Rate
Completeness- Flow rate accuracy overall completeness was low for CY99. A positive or negative
bias in flow rate can have a direct effect on the cut point of the paniculate matter collected on the filter
and also affects the 24-hour air volume estimate that goes into the derivation of the concentration. A
10% bias in flow rate will cause a 10% change in the PM2 5 concentration. The quarterly flow rates,
using an independent standard, ensures that the sampling instruments are operating within acceptable
limits and also ensure that the working check standard is not out of specification. OAQPS will work
the EPA Regions and States to ensure a better capture rate of this data for future calendar years.
Accuracy Results - The results of the accuracy audits are very good. The national average accuracy
estimate is 0.02% which is well within the acceptance criteria of ฑ4% of the standard and ฑ5% of the
design (see Table 3-2). For the method designations that had more than 100 flow rate audits
performed in CY99, the percentage of audits meeting the criterion of ฑ4% of the standard was 94%
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PM2.5 CY99 QA Report December 2000
and the percentage meeting the criterion of ฑ5% of the 16.67 L/min design flow rate was 99%.
Additionally, these percentages did not vary by method designation.
Bias - Performance Evaluation Program and Routine Data
Completeness - Completeness of the performance evaluation data is a little more complicated
because it involves two data points that are collected by different organizations. The bias estimate must
rely on Performance Evaluation Program (PEP) data collected by technical support contractors
provided through the EPA Environmental Services Assistance Team (ESAT) contract. The routine
PM2 5 data is collected by the State, local and tribal Nations. The PEP achieved its completeness
requirement by collecting valid data at 247 sites, which was just over the anticipated 245 sites (25% of
the 979 sites established in AIRS). However, when the data for these 247 sites were matched with
their respective routine data in AIRS, only 160 sites produced valid site/pairs that met the completeness
requirement. If one looks at actual valid samples that were taken, of the 984 valid PEP values, there
are only 697 that have a routine sample match in AIRS. Reasons for missing routine values could be
due to PEP or routine samples mistakenly sampled on different days, or data not yet entered into AIRS.
However, the missing 287 values account for 30% of the performance evaluation information which
affects the confidence in the bias estimates, particularly when one attempts to assess bias at a reporting
organization or method designation level.
Bias results
As with precision, the bias data quality objective is based on three years of bias data (75% complete).
At a national level, the average bias is estimated at 1.7% and it appears that the bias data quality
objective is being met. However, there are three factors that affect the bias estimates: 1) lack of paired
data, 2) outliers, and 3) method designations.
Lack of paired data - A performance evaluation is only performed on 25% of the sites and each site
is audited 1 time each quarter. It is difficult to determine a statistically significant bias at lower levels of
aggregation at the reporting organization or method designation level with only one years worth of
information and with 287 paired values missing.
Outliers - Similar to the findings in the precision data, there is almost no difference in the bias estimate
in keeping or removing a pair when one or both values is below 6 |ig/m3. However, it appears outliers
had an effect on bias in the first quarter of 1999. An outlier was any paired value that had an accuracy
estimate greater than +50%. Removing outliers from the national estimate changed the bias estimate
from 1.7% to -0.49%. However, 6 outliers (6 % of the quarters total) in the first quarter changed the
bias estimate from 9.0% to 3.6%. OAQPS will ask State and locals to review these outliers to ensure
their validity. For this report the outliers are considered valid and incorporated into the overall and
quarterly bias estimate.
Method Designations - It appeared that method designations did play a role in the bias estimates,
particularly in the first and possibly the second quarter of 1999. For the first quarter, the Andersen
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PM2.5 CY99 QA Report December 2000
sequential bias estimate (25.7%) was substantially higher than the R & P sequential bias estimate (-
1.01%). However, all 6 (17% of the quarters values for Andersen) outliers identified in the first quarter
where related to the Andersen instrument which would change the bias estimate from 25.7% to
12.42%. Outliers did not have any significant effects on R & P sequential data. There was not enough
data to make any statements about single channel instruments. The third and fourth quarter estimates
do not appear to vary by method designation and are therefore more comparable. This may be due to
improvements in sampling and analytical techniques and vendor modifications to the FRM monitors.
Recommendations
The following recommendations are made in order to improve the capture rate of information and
improve the PM2 5 quality system over the next year.
Quarterly Completeness Assessments- OAQPS will run the completeness estimates for routine,
precision and accuracy data quarterly and submit this information to AMTIC or the EPA Regions in
order to help identify where improvements in data capture are needed. These assessments will follow
the quarterly AIRS submission requirement.
Quarterly Precision, Accuracy, and Bias Assessments - OAQPS will run the similar data quality
assessments on a quarterly basis and submit this information to AMTIC or the EPA Regions in order to
provide more real time assessments of data quality. OAQPS will also identify outliers either through the
new AIRS critical data review reports or through this assessment in order to ensure the effect of outliers
on data quality is minimized.
Consistent Placement of Accuracy Data in AIRS - In the AIRS accuracy transaction files there
appeared to be some inconsistency in the placement of data in the "actual" and "indicated" levels. If
monitoring organizations can be consistent in their input, the data can be useful in determining flow rate
bias. The "actual" value for flow rate should be the value reported by the standard; the "indicated"
value is the value reported by the monitoring instrument.
Assessment of data qualifiers - OAQPS will assess flagged data to determine whether this
information is of adequate quality for use in NAAQS comparison. OAQPS will need to work with
individual State, local or Tribal agencies to determine what quality control criteria was violated in order
to determine whether this acceptance criteria has a significant impact on data quality. This assessment
will help determine whether certain critical or operational quality control criteria can be revised to
reduce the QA burden where appropriate.
Relocation of collocated monitors - It is recommended that collocated monitors at low concentration
sites be moved to sites whose annual mean is > 13.5 |ig/m3. Each reporting organization should try to
locate 80% of their monitors within >90 to 110% of the NAAQS (13.5 to 16.5 |ig/m3).
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PM2.5 CY99 QA Report December 2000
CFR corrections - There are a number of corrections to the language and the statistical equations in
40 CFR 58 App A that would make the requirements more "understandable". OAQPS will attempt the
correct CFR in FY2001.
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Attachments
Section 1 -Introduction
Number Title Pages
1-1 Manipulation of Data Prior to Estimation of Precision, Bias, or Accuracy 4
Section 2- Assessment of Data Quality Indicators
Number Title Pages
2-1 PM2.5 Routine Data Completeness 15
2-2 Summary of PM2.5 Data Flags 2
2-3 PM2.5 Collocated Precision Data Completeness 4
2-4 PM2.5 Flow Rate Audit Data Completeness 16
2-5 Performance Evaluation Program Sites without a Routine Data Value Match 6
2-6 Collocated Precision Data with Percent Difference > +/- 50% 7
2-7 Collocated Precision Data Aggregated by Reporting Organizations 36
2-8 Routine and Performance Evaluation Program Pairs with Accuracy > +/- 50% 1
Section 3 -Summary and Conclusions
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Attachment 1-1
Manipulation of Data
Prior to Estimation of Precision, Bias, or Accuracy
The following text and tables describe some data handling issues that had to be addressed prior to the
estimation of the precision, bias, and accuracy statistics. These issues are listed both to bring
awareness to them in addition to documenting how they were handled.
Issue # 1 - Precision and Accuracy: Sites with more than one method designation
Background- Estimates of both precision and accuracy are summarized at the method designation
level. A review of the CY99 data shows that there are some sites that have more than one method
designation recorded. There are three patterns for changing method designations. Some sites report
one method designation for a period of time and then report a different method designation after a
certain date. This is consistent with a change of equipment, if such has occurred. Other sites report the
precision transactions with one method designation and the accuracy transactions with a different
method. Lastly, some sites have the method designation changing without any apparent pattern. Table
1 contains a list of the sites for which there are multiple method designations reported on the accuracy
and/or precision transactions and a note about whether the pattern in method designations appears to
be related to a date, transaction type, or unknown.
Action for QA Report- OAQPS used the method designations as they are reported on the precision
and accuracy transactions.
Issue # 2A - Accuracy: Wrong units
Background - Accuracy data should be reported with units volume flow rate units code 73 (L/min).
Some accuracy data is being reported with code 105 which is concentration units (jig/m3). Table 2A
contains a list of the site/days with incorrect units for accuracy.
Action for QA Report - OAQPS assumed the units are (L/min) for all of these site/days except for
the two site/days in Pennsylvania. The two site/days for PA were omitted since they are associated
with performance evaluations.
-------
Issue # 2B - Precision: Wrong units
Background - Precision data should be reported with units code 105 (jig/m3). Some precision data is
being reported with units 73 which is volume flow rate units (L/min). Table 2B contains a list of the
site/days with incorrect units for precision.
Action for QA Report - OAQPS assumed the units are |ig/m3 for all of these site/days.
Issue # 3 - Accuracy: Apparent outliers
Background- The one point accuracy checks should produce a volume close to the design flow rate
16.67 (L/min). There are 4 accuracy checks reported that are quite divergent from the design value
and may actually be precision data that was submitted in the accuracy fields. Table 3 contains a listing
of site/days for which neither the actual nor the indicated flow rate is within 5% or 16.67.
Action for QA Report - OAQPS omitted any accuracy transaction when both values (primary
monitor flow rate and standard flow rate) are greater than 5% of the design value.
Issue # 4 - Precision: Data reported in POCs rather than precision transactions
Background - Some monitoring organizations are reporting their precision data in POCs rather than in
precision transactions. Guidance was distributed to allow for substitution of the primary sampler data
that was determined to be invalid with collocated data by placing the collocated data in POC 2. Some
States may have misconstrued this guidance and put all their data in POC 2. Other States have
submitted all collocated data in POC 2 as well in precision transactions.
Action for QA Report - OAQPS assumed that if a site does not have any data in the precision
transaction area for a given date but does have data in POC 2 then the data in POC 2 is collocated
precision data. OAQPS did not look for precision data in any POCs other than 2.
-------
Issue # 5 - Accuracy: Interchanging of actual and indicated values
Background - On an accuracy transaction, the "actual" value should contain the true value of the
standard which is challenging the instrument, and the "indicated" value should contain the flowrate
estimated by the instrument. It is uncertain whether field personnel are utilizing these field s
appropriately and consistently. It appears that some organizations may be placing the design value
(16.67) in one of these fields, or could possibly be transposing the wrong information in either actual or
indicated fields. This will have an impact both on the sign of the estimated accuracy as well as on the
value of the statistic.
Note that is it not possible easily to surmise whether a similar miscoding is occurring with the precision
data. However, if it is occurring, it only impacts the sign of the estimated percent difference and does
not impact the estimated precision.
Action for QA Report - OAQPS assumed that the data are correctly coded, even though it appears
that this is not the case.
Issue # 6 - Flagged Data
Background - Routine data can be flagged using data qualifiers, sampler generated flags and
exceptional event flags (see Attachment 2-2). These flags indicate that the concentration data may be
compromised either by natural causes (exceptional events) or by the measurement process. However,
data in the P & A transaction file cannot be flagged and therefore it is very difficult to determine
whether one or both the routine and collocated samplers had been flagged which could help explain
greater imprecision than would be expected.
Action for QA Report - All data available for precision estimates were used. Flagged data should not
have a large effect on national estimates generated for the QA Report.
Issue # 7 - Accuracy: Multiple Groups/Levels
Background - The accuracy transactions allow for the entry of more than one pair of actual and
indicated values for a given site and day by permitting several levels within several groups. Some States
are using reporting data in more than one group/level combination, likely to report the flow rate audit
information for both the primary and collocated sampler.
Action for QA Report - OAQPS used the accuracy information only in the lowest level of the lowest
group for a given site and day.
-------
Table 1. Sites With Multiple Method Designations on P&A Transactions
(based on AMP250 extraction dated 07/26/2000)
State
Alaska
California
Massachusetts
South Dakota
Utah
Site
Type of
Transactions Method
Reported* Designations Pattern**
0202000181
0211000042
0602500051
0607100141
0607300061
0611310031
2500960011
4601100021
4610300171
4901100011
4903530071
4904500021
4905700071
P&A
P&A
P&A
P&A
P&A
A
A
A
A
A
A
A
A
117,
117,
119,
119,
119,
117,
119,
119,
119,
117,
117,
117,
117,
118
118
120
120
120
120
120
120
120
118
118
118
118
Temporal
Temporal
Tran. type
Tran. type
Tran. type
Unknown
Unknown
Temporal
Temporal
Temporal
Temporal
Temporal
Temporal
Wisconsin
5502700071
A
117, 118
Temporal
P=Precision, A=Accuracy.
Pattern of change in method designation.
-------
Table 2A. Site/Days With Incorrect Units for Accuracy Transactions
(based on AMP250 extraction dated 07/26/2000)
State
Georgia
Missouri
North Carolina
Site
1306300911
1308920011
1311500051
1321500011
1321500111
1324500911
2907700321
2918920031
2918950011
3702100341
3708700101
Date
03/29/99
03/22/99
03/30/99
03/23/99
03/23/99
03/24/99
03/11/99, 03/12/99
03/17/99, 03/18/99,
09/02/99, 09/03/99
03/30/99
03/24/99
03/24/99
Pennsylvania
4210100041
4210101361
08/25/99
08/23/99
Table 2B. Site/Days With Incorrect Units for Precision Transactions
(based on AMP250 extraction dated 07/26/2000)
State
Florida
Site
1200100231
1201110021
1203300041
1207100051
1209520021
1210560061
1211500131
1211710021
1211110021
Date
All
All
All
All
All
All
All
All
All
Table 3. Site/Days with Neither Actual nor Indicated Flow Rate
within 5% of 16.67
(based on AMP250 extraction dated 07/26/2000)
State
Florida
Site
1203300041
1208140121
Date
02/02/99
11/16/99
Pennsylvania
4210100041
4210101361
08/25/99
08/23/99
-------
Attachment 2-1
PM2.5 Routine Data Completeness
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
STATE
ALABAMA
SITE POC
r>4%
*^ /o
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
CALIFORNIA
Total # of FRM Sites=19;
31 0270001 1
31 0331 002 1
310491003 1
310690002 1
310730023 1
310731005 1
310732003 1
310732006 1
310735002 1
310970002 1
310972005 1
311010007 1
311030010 1
311130001 1
311170006 1
311190002 1
311210002 1
311250003 1
311270002 1
Total # of FRM Sites= 7;
320200018 1
320200044 1
320900010 2
321100004 2
321100026 1
321300008 1
321700008 1
Total # of FRM Sites=10;
340031005 1
340051008 1
340070008 1
340139990 1
340139991 1
340139992 1
340139997 1
340190011 1
340191028 1
340230004 1
Total # of FRM Sites=18;
350010001 1
350030003 1
350310001 1
350350004 1
350510002 1
350690005 1
350890001 1
350910001 1
350910004 1
351070001 1
351130002 1
351150003 1
351190003 1
351190007 1
351191008 1
351310008 1
351390004 1
351430003 1
Total # of FRM Sites=76;
360010007 1
360011001 1
360070002 1
360090001 1
360111002 1
360130002 1
360170011 1
360190008 1
360195001 1
360231002 1
360250003 1
360250005 1
360251003 1
Number w/ Data=19;
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/03(99
01/01/99
01/03(99
01/03(99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
Number w/ Data= 7;
11/1088
01/01/99
10/23(98
11/19/98
12/18(99
10/28(99
12/19/98
Number w/ Data=10;
01/12188
01/06(99
02/1 1/99
01/06(99
01/21/99
03/19/99
01/01/99
01/01/99
01/01/99
01/06(99
Number w/ Data=17;
01/07/99
03/26(99
03/12/99
04/01/99
03/09(99
02/18(99
04/02/99
05/05(99
05/05(99
04/05(99
03/30/99
02/26(99
01/06(99
01/22/99
04/02/99
04/01/99
02/22/99
03/15(99
Number w/Data= 76;
12/01/99
01/01/99
12/19/98
01/06(99
12/16(98
01/01/99
01/06(99
01/03(99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
Number Complete (75%+ in each Q)= 0;
01/03(99 3 50%
01/03(99 3 50%
01/03(99 3 63%
01/03(99 3 60%
01/01/99 1 96%
01/03(99 3 93%
01/01/99 1 94%
01/03(99 3 1 00%
01/03(99 3 1 00%
01/03(99 3 80%
01/03(99 3 97%
01/03(99 3 90%
01/03(99 3 77%
01/03(99 3 90%
01/03(99 3 0%
01/03(99 3 47%
01/03(99 3 87%
01/03(99 3 83%
01/03(99 3 80%
Number Complete (75%+ in each Q)= 0;
01/01/99
04/06(99
02/18(99
04/10/99
12/18(99
10/28(99
01/03(99
1 60%
6 56%
3 53%
Number Complete (75%+ in each Q)= 4;
01/12188
01/06(99
02/1 1/99
01/06(99
01/21/99
03/19/99
01/06(99
01/06(99
01/06(99
01/06(99
6 67%
6 73%
3 47%
3 87%
1 56%
1 14%
1 79%
1 73%
3 77%
6 1 00%
Number Complete (75%+ in each Q)= 0;
07/05(99
07/05(99
07/05(99
07/02/99
07/05(99
07/05(99
07/02/99
07/05(99
07/11/99
07/05(99
07/05(99
07/05(99
06/30/99
07/02/99
07/05(99
07/05(99
07/02/99
Number Complete (75%+ in each Q)=31 ;
12/02/99
01/03(99
01/06(99
01/06(99
01/06(99
01/08(99
01/12/99
01/03(99
01/03(99
01/08(99
01/03(99
01/03(99
01/03(99
3 60%
6 1 00%
6 100%
6 100%
3 17%
6 93%
3 93%
3 80%
6 94%
3 1 00%
3 87%
3 100%
Number w/ 50% in each Q= 0; Number w/ 1 1+ samples in each Q= 0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Number w/ 50% in each Q= 2; Number w/ 11+ samples in each Q= 2
3 63%
3 57%
3 81 %
3 53%
3 73%
3
3
3
3
3
Number w/ 50% in each Q=
6 73%
6 100%
3 77%
3 90%
1 82%
1 80%
1 90%
1 91 %
3 87%
6 87%
6
6
3
3
1
1
1
1
3
6
90%
94%
69%
65%
87%
1
3
6
3
6
3
3
50% 1 1
97%
42%
80%
20%
40%
80% 1 1
6; Number w/ 1 1+ samples in each Q= 9
7%
1 00%
77%
100%
96%
1 00%
99%
83%
97%
93%
6
6
3
3
1
1
1
1
3
6
93%
87% 1 1
87% 1
100% 1 1 1
87% 1 1
92% 1
90% 1 1 1
42% 1
80% 1 1 1
93% 1 1 1
Number w/ 50% in each Q= 0; Number w/ 1 1+ samples in each Q= 0
6 7%
6
6
6
3
6
6
6
6
6
6
6
6
1
3
3
6
3
100%
93%
93%
74%
67%
87%
75%
40%
47%
80%
73%
100%
82%
84%
84%
87%
77%
6
6
6
3
6
6
6
6
6
6
6
6
1
3
3
6
3
80%
93%
87%
80%
73%
80%
53%
33%
100%
80%
87%
87%
90%
83%
93%
80%
67%
1
1
1
1
1
1
1
1
1
1
1
1
1
Number w/ 50% in each Q=48; Number w/ 11+ samples in each Q=53
6 87%
6 100%
6 100%
3 73%
6 73%
6 100%
1 82%
6 100%
6 100%
3 80%
3 90%
3 90%
6
6
6
3
6
6
1
6
6
3
3
3
1 00%
93%
100%
75%
1 00%
1 00%
96%
100%
93%
45%
100%
94%
3
3
6
6
3
1
6
1
3
6
3
3
3
30%
1 00% 1 1
100% 1 1 1
93% 1 1 1
74% 1 1
80%
100% 1 1 1
91% 1 1 1
93% 1 1 1
93% 1 1 1
7%
77% 1 1 1
77% 1 1 1
1
1
1
1
1
1
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
STATE
SITE POC
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
COLORADO
D60271003 1
D60290010 1
D60290011 1
D60290012 1
D60290014 1
D60310004 1
D60333001 1
D60370002 1
D60371002 1
D60371103 1
D60371201 1
D60371301 1
D60371601 1
D60372005 1
D60374002 1
D60379002 1
D60450006 1
D60472510 1
D60490001 1
D60531002 1
D60570005 1
D60571001 1
D60590001 1
D60592022 1
D60610006 1
D60631006 1
D60631008 1
D60651003 1
D60652002 1
D60658001 1
D60670006 1
D60670010 1
D60674001 1
D60710014 1
D60710025 1
D60712002 1
D60718001 1
D60719004 1
D60730001 1
D60730003 1
D60730006 1
D60731002 1
D60731007 1
D60750005 1
D60771002 1
D60792002 1
D60798001 1
D60811001 1
D60830010 1
D60831007 1
D60850004 2
D60852003 1
D60870007 1
D60890004 1
D60950004 1
D60970003 1
D60990005 1
D61010003 1
D61 072002 1
D61 110007 1
D61 112002 1
D61 113001 1
D61131003 1
Total * of FRM Sites=16;
D80010001 1
D80050005 1
D801 30003 1
D80130012 1
D80310002 1
D80310013 1
D80310017 1
D80390001 1
09/01/98
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
04/01/99
01/1399
01/01/99
12/30/98
03/31/99
01/01/99
06/15^99
12/31/98
03/26S9
03/25S9 02/09/00
01/01/99
01/01/99
01/01/99
01/03^99
1 2/13^98
02/02/99
01/01/99
01/01/99
01/01/99
02/08(99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/03(99
01/01/99
01/01/99
01/01/99
01/01/99
08/04(99
01/01/99
01/01/99
01/01/99
12/19(98
01/01/99
01/01/99
01/03(99
12/19(98
01/03(99
01/01/99
01/01/99
01/01/99
01/09(99
Number w/ Data=14;
12/01/98
12/01/98
12/01/98
12/01/98
12/01/98
11/15(99
11/15(99
12/01/98
01/03(99
01/03(99
03/01/99
06/26(99
01/03(99
01/03(99
01/06(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/07/99
04/1 2/99
01/12199
01/15(99
01/03(99
03/31/99
01/03(99
06/17/99
01/06(99
03/26(99
03/25(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
02/02/99
01/03(99
01/03(99
01/03(99
02/08(99
01/03(99
01/03(99
01/01/99
01/03(99
01/01/99
01/01/99
01/03(99
01/03(99
01/06(99
01/06(99
01/03(99
01/06(99
10/03(99
01/06(99
01/03(99
01/06(99
01/06(99
02/20/99
01/24/99
01/03(99
01/06(99
01/03(99
01/03(99
01/03(99
01/03(99
01/09(99
3 83%
3 93%
3 30%
1 48%
3 80%
6 87%
1 70%
3 73%
1 53%
3 53%
3 77%
3 73%
3 30%
1 71 %
3 97%
6 1 00%
6 80%
3 45%
6 93%
6 7%
1 67%
6 1 00%
3 7%
3 7%
3 87%
3 43%
1 70%
3 97%
3 97%
3 67%
3 80%
3 90%
3 89%
3 60%
3 73%
3 90%
1 89%
3 87%
1 59%
1 68%
3 43%
3 100%
6 93%
6 1 00%
3 35%
6 93%
3 3%
3 33%
3 48%
6 94%
3 27%
3 60%
3 100%
6 100%
3 87%
3 90%
3 90%
3 63%
3 93%
Number Complete (75%+ in each Q)= 1;
01/26(99
03/10/99
01/22/99
01/30(99
01/01/99
05/28(99
3 37%
3 17%
3 74%
3 43%
1 61 %
3 70%
6 80%
3 97%
6 13%
1 97%
6 80%
6 88%
3 93%
3 80%
3 93%
3 47%
3 97%
3 97%
3 97%
3 93%
3 100%
6 93%
6 60%
6 100%
3 97%
6 100%
3 23%
3 17%
3 17%
6 100%
3 77%
3 83%
3 97%
3 80%
3 97%
3 97%
1 85%
3 94%
3 100%
3 77%
3 97%
3 73%
3 77%
3 80%
1 88%
3 83%
1 68%
1 86%
6 60%
3 90%
6 80%
6 100%
6 87%
6 93%
6 93%
6 80%
3 100%
6 93%
6 87%
6 80%
3 83%
6 63%
3 82%
3 90%
3 87%
3 97%
3 97%
3
6
3
3
1
6
6
3
3
3
3
3
3
3
3
3
6
6
6
3
6
3
3
3
6
3
3
3
3
3
3
1
3
3
3
3
3
3
3
1
3
1
1
6
3
6
6
6
6
6
6
3
6
6
6
3
6
3
3
3
3
3
65%
93%
90%
61%
96%
100%
40%
94%
1 00%
100%
35%
94%
97%
97%
97%
90%
94%
100%
93%
56%
80%
53%
10%
97%
1 00%
71%
68%
1 00%
58%
65%
0%
91%
97%
97%
68%
97%
94%
97%
94%
89%
77%
80%
89%
1 00%
94%
87%
93%
1 00%
93%
1 00%
80%
22%
88%
93%
80%
94%
94%
97%
94%
87%
61%
94%
3
3
3
3
1
3
6
3
3
3
3
3
3
3
3
3
6
3
6
6
3
3
3
6
3
3
3
3
3
3
1
1
3
3
3
3
3
3
1
3
1
1
1
3
6
6
3
6
6
1
1
6
3
3
3
6
3
3
3
3
3
10%
100% 1 1 1
77%
83%
82% 1
93% 1 1 1
93%
37% 1
97% 1 1
97% 1 1
100% 1
97% 1 1 1
1 00% 1 1
90%
87% 1 1
83% 1 1 1
93% 1 1 1
97%
100% 1 1 1
73% 1 1
70%
80%
1 00%
93% 1 1 1
81%
78%
80% 1 1 1
93% 1
83% 1 1
22%
80% 1 1 1
85% 1 1
93% 1 1 1
83% 1 1
97% 1 1 1
93% 1 1
97% 1 1
77% 1 1 1
84% 1 1 1
80% 1 1 1
64% 1 1
75% 1 1
91%
94% 1 1 1
100% 1 1 1
100% 1 1 1
97% 1
93% 1 1 1
93%
95%
90%
93% 1 1 1
93%
90% 1 1
97% 1 1 1
75% 1
100% 1 1 1
90% 1 1 1
97% 1 1 1
83% 1 1
38% 1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Number w/ 50% in each Q= 2; Number w/ 1 1+ samples in each Q= 5
3 87%
3 90%
3 90%
3 57%
1 80%
3 30%
3
3
3
3
1
3
97%
97%
88%
97%
0%
82%
3
3
3
3
3
97% 1
87%
100% 1 1
97% 1
88%
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
STATE
SITE POC
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
D80410008 1
D80410011 1
D80690009 1
D80770003 1
D81010012 1
D81 070003 1
D81 230006 1
D81 230008 1
CONNECTICUT Total # of FRM Sites=11;
D90010010 1
D90011123 1
D90012124 1
D90019003 1
D90031003 1
D90031018 1
D90090018 1
D90091123 1
D90092123 1
D90099005 1
D901 13002 1
DELAWARE Total # of FRM Sites= 8;
100010002 1
100010003 1
100031003 1
100031007 1
100031011 1
100031012 1
100032004 1
100051002 1
DISTRICT OF COLUM Total * of FRM Sites= 3;
110010041 1
110010042 1
110010043 1
FLORIDA Total * of FRM Sites=27;
120010023 1
120111002 1
120112004 1
120113002 1
120170005 1
120251016 1
120256001 1
120310098 1
120310099 1
120330004 1
120570030 1
120571075 1
120710005 1
120730012 1
120814012 1
120830003 1
120951004 1
120952002 1
120990009 1
120992003 1
121030018 1
121031008 1
121056006 1
121111002 1
121150013 1
121171002 1
121275002 1
GEORGIA Total # of FRM Sites=24;
130210007 1
130210012 1
130510017 1
130510091 1
130590001 1
130630091 1
130670003 1
130890002 1
130892001 1
130950007 1
12/01/98
12/01/98
12/01/98
12/01/98
12/01/98
12/01/98
12/01/98
12/01/98
Number w/ Data=11;
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
Number w/ Data= 8;
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99 12/16/99
12/15(99
01/01/99
01/01/99
Number w/ Data= 3;
01/01/99
01/01/99
01/01/99
Number w/Data=26;
01/06(99
01/01/99
04/01/99
04/03(99
02/05(99
02/04/99
01/27/99
06/01/99
06/01/99
01/03(99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/07/99
01/01/99
01/01/99
12/04(99
01/01/99
01/01/99
01/27/99
01/01/99
01/03(99
01/03(99
01/07/99
01/04/99
Number w/ Data=24;
02/02/99
02/11/99
01/21/99
01/21/99
01/21/99
01/09(99
02/07/99
01/22/99
01/01/99
02/02/99
07/02/99
02/19(99
07/10(99
01/06(99
02/20/99
06/23(99
02/13(99
08/04/99
1 39%
3 87%
3 37%
3 47%
Number Complete (75%+ in each Q)= 0;
01/03(99
01/03(99
01/03(99
01/06(99
01/01/99
01/03(99
01/03(99
01/03(99
01/03(99
02/05(99
01/03(99
3 90%
3 43%
3 40%
6 33%
1 53%
3 43%
3 67%
3 57%
3 70%
3 0%
3 63%
Number Complete (75%+ in each Q)= 3;
01/03(99
02/11/99
01/03(99
01/03(99
03/10(99
12/16(99
02/14/99
01/03(99
3 83%
3 43%
3 87%
3 80%
1 20%
1 28%
3 93%
Number Complete (75%+ in each Q)= 0;
02/21/99
03/20/99
01/15(99
1 40%
6 25%
1 48%
Number Complete (75%+ in each Q)=14;
01/09/99
01/01/99
04/02/99
04/03(99
02/04/99
01/27/99
06/30/99
06/30/99
01/06(99
01/01/99
01/20(99
01/06(99
01/03(99
01/30(99
01/21/99
01/01/99
01/03(99
12/04(99
01/05(99
01/01/99
01/27/99
01/06(99
01/06(99
01/03(99
01/09(99
01/06(99
3 83%
1 86%
1 46%
3 63%
3 90%
1 84%
1 77%
3 57%
3 77%
3 47%
3 47%
1 92%
1 92%
1 87%
1 94%
3 73%
3 37%
3 90%
3 77%
3 80%
3 93%
Number Complete (75%+ in each Q)= 3;
02/02/99
02/11/99
01/21/99
01/21/99
01/30(99
01/09(99
02/07/99
01/22/99
01/01/99
02/02/99
3 40%
3 37%
3 67%
3 70%
3 63%
3 77%
3 33%
1 49%
1 82%
3 33%
1 0%
3 100%
3 0%
6 13%
3 90%
3
3
3
3
3
6
3
3
Number w/ 50% in each Q= 4
3 67%
3 30%
3 17%
6 47%
1 29%
3 23%
3 60%
3 57%
3 63%
3 20%
3
3
3
6
1
3
3
3
3
3
3
Number w/ 50% in each Q= 4;
3 93%
3 90%
3 90%
3 73%
1 69%
1 77%
3 80%
3
3
3
3
1
1
3
Number w/ 50% in each Q= 0;
1 86%
3 62%
1 97%
Number w/ 50% in <
3 93%
1 93%
1 92%
3 87%
1 85%
3 90%
6 7%
6 7%
3 97%
1 90%
1 85%
3 97%
3 94%
3 93%
3 90%
1 92%
1 100%
1 95%
1 93%
3 94%
3 63%
3 100%
3 93%
3 93%
3 80%
1
3
1
50%
48%
53%
77%
63%
82%
61%
65%
3
3
3
3
3
6
3
3
79%
81%
88%
100% 1 1 1
82%
87%
88% 1
94%
; Number w/ 1 1+ samples in each Q= 5
94%
48%
52%
60%
72%
61%
97%
97%
97%
71%
55%
3
3
3
6
1
3
3
3
3
3
3
93% 1 1
83%
83%
80%
91% 1
80%
97% 1 1
93% 1 1
97% 1 1
93%
97%
1
1
1
Number w/ 11+ samples in each Q= 7
77%
71%
87%
71%
82%
86%
77%
3
3
3
3
1
1
1
3
87% 1 1 1
87% 1
93% 1 1 1
87% 1 1
39% 1
17%
88% 1
93% 1 1 1
1
1
1
1
1
1
Number w/ 11+ samples in each Q= 2
86%
49%
54%
1
3
1
72% 1
55%
87% 1
1
1
1
;ach Q=17; Number w/ 11+ samples in each Q=21
3
1
1
3
1
3
1
1
3
1
1
3
3
3
3
1
1
1
1
3
3
3
3
3
3
97%
87%
89%
97%
83%
84%
59%
60%
90%
89%
90%
97%
94%
84%
94%
93%
95%
76%
96%
97%
74%
94%
94%
84%
91%
3
1
1
3
1
3
1
1
3
1
1
3
3
3
3
1
1
1
1
1
3
3
3
3
3
3
97% 1 1 1
100% 1 1 1
92%
97%
88% 1
97% 1 1
86%
90%
93% 1 1 1
75% 1 1 1
80% 1 1 1
1 00% 1 1
87% 1 1 1
80% 1
87% 1
100% 1 1 1
99% 1 1 1
23%
92% 1 1 1
98% 1 1 1
93% 1 1
80% 1
97% 1 1 1
100% 1 1 1
87% 1 1 1
97% 1 1 1
1
1
Number w/ 50% in each Q=12; Number w/ 11+ samples in each Q=17
3 97%
3 87%
3 80%
3 70%
3 97%
3 80%
3 97%
1 86%
1 86%
3 93%
3
3
3
3
3
3
3
1
1
3
96%
84%
94%
19%
81%
90%
74%
82%
89%
94%
3
3
3
3
3
3
3
1
1
3
91% 1
100% 1
80% 1 1
83%
87% 1 1
97% 1 1 1
90%
86% 1
87% 1 1 1
74%
1
1
1
1
1
1
1
1
1
1
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
STATE
SITE POC
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
HAWAII
131150005
131210032
131210039
131211001
131270004
131270006
131390003
132150001
132150011
132230003
132450005
132450091
133030001
133190001
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Total * of FRM Sites; 5;
150030010
150031001
150031004
150032004
150090006
1
1
1
1
1
Total # of FRM Sites=14;
160010011
160010017
160050006
160050015
160170001
160190010
160210001
160270004
160270005
160550006
160690009
160790017
160830006
160830010
0
1
1
0
0
1
1
1
1
2
1
1
1
1
Total # of FRM Sites=25;
170191001
170310014
170310022
170310050
170310052
170311016
170311701
170312001
170313301
170314006
170314201
170434002
171150013
171170002
171190023
171191007
171193007
171430037
171570001
171610003
171630010
171670012
171971002
171971011
172010010
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Total # of FRM Sites=28;
180030004
180190005
180390003
180431004
180670003
180890006
180890022
180891003
180891016
180892004
1
1
1
1
1
1
1
1
1
1
01/1 Eras
01/01/99
01/21/99
01/01/99
01/21/99 0860/99
08/31/99
02/14(99
03/04(99
01/21/99
01/24(99
01/21/99
02/08(99
01/30/99
01/01/99
Number w/ Data= 5;
01/01/99
01/01/99
10/01/99
01/01/99
01/28(99
Number w/ Data=13;
12/13(98
11/01/98
08/10(99
05/01/99
11/01/98
12/07/98
07/23(99
10/04(99
09/03(99
12/13(98
12/08(99
Number w/Data=25;
01/01/99
01/01/99
01/01/99
01/01/99
01/01/98
01/01/99
01/01/99 12/31/99
01/01/99
01/01/99
01/01/99
01/01/98
01/01/99
01/01/99
01/01/99 1261/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
02/01/99
Number w/ Data=26;
01/01/99
01/01/99
05/12/99
01/01/99
06/11/99
01/27/99
03/04(99
01/27/99
01/01/99
02/11/99
01/18(99
01/01/99
01/21/99
01/01/99
01/21/99
08/31/99
02/14(99
03/04(99
01/21/99
01/24(99
01/21/99
02/08(99
01/30/99
04/1 2/99
3 63%
1 63%
3 77%
3 68%
3 47%
3 43%
3 27%
3 68%
3 57%
3 70%
3 47%
6 69%
Number Complete (75%+ In each Q)= 2;
01/03(99
01/01/99
10/03(99
01/01/99
01/30/99
3 83%
1 88%
1 91 %
3 50%
Number Complete (75%+ in each Q)= 8;
01/03(99
01/06(99
01/06(99
01/03(99
01/03(99
08/31/99
01/03(99
01/06(99
07/23(99
10/04(99
09/03(99
01/06(99
12/08(99
3 100%
6 100%
6 1 00%
3 1 00%
3 97%
3 1 00%
6 100%
6 80%
Number Complete (75%+ in each Q)=17;
01/28(99
01/06(99
01/06(99
01/06(99
01/06(99
01/06(99
01/06(99
01/06(99
01/06(99
01/18(99
01/08(99
01/24(99
01/08(99
01/06(99
01/06(99
01/06(99
01/06(99
01/18(99
01/21/99
01/06(99
01/09(99
01/07/99
01/06(99
01/06(99
02/13(99
6 53%
6 81 %
6 87%
6 87%
6 93%
6 93%
6 93%
6 93%
6 87%
6 73%
6 93%
6 80%
6 53%
6 93%
6 93%
6 69%
6 81 %
6 69%
6 87%
6 80%
6 87%
6 88%
6 93%
6 87%
6 56%
Number Complete (75%+ in each Q)= 0;
01/21/99
01/30(99
05/15(99
01/18(99
06/23(99
01/30(99
03/05(99
02/02/99
01/01/99
02/11/99
3 73%
3 63%
3 60%
1 39%
1 18%
3 47%
1 90%
3 33%
3 90%
1 84%
3 77%
3 80%
3 70%
3 97%
3 90%
3 87%
3 90%
3 100%
3 87%
6 100%
3 77%
3
1
3
3
3
3
3
3
3
3
3
3
6
3
1 00%
80%
90%
97%
0%
32%
97%
87%
97%
77%
81%
87%
93%
81%
3
1
3
3
3
3
3
3
3
3
3
6
3
77% 1 1
88% 1 1
93% 1 1 1
93% 1 1
80%
93% 1
87%
93% 1 1
93% 1 1
77% 1 1
60% 1
1 00% 1 1
97%
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Number w/ 50% in each Q= 4; Number w/ 11+ samples in each Q= 4
3 97%
1 97%
1 90%
3 97%
3
1
1
3
Number w/ 50% in each Q=
3 100%
6 100%
6 93%
3 97%
3 100%
3 97%
6 100%
6 87%
3
3
6
3
3
6
3
3
3
6
6
88%
90%
93%
71%
3
1
6
1
3
53% 1 1
87% 1 1 1
100%
92% 1 1 1
87% 1 1
8; Number w/ 1 1+ samples in each Q= 8
97%
81%
83%
81%
94%
13%
1 00%
81%
71%
27%
80%
3
3
3
3
3
6
3
3
3
6
6
6
6
100% 1 1 1
100% 1 1 1
100% 1 1 1
97% 1 1 1
100% 1 1 1
81%
97% 1 1 1
100% 1 1 1
97%
88%
93%
80% 1 1 1
27%
1
Number w/ 50% in each Q=24; Number w/ 11+ samples in each Q=21
6 93%
6 81 %
6 100%
6 100%
6 100%
6 93%
6 100%
6 100%
6 100%
6 72%
6 100%
6 100%
6 80%
6 100%
6 87%
6 100%
6 80%
6 93%
6 93%
6 100%
6 93%
6 100%
6 100%
6 87%
6 81 %
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
93%
100%
1 00%
1 00%
27%
100%
1 00%
94%
100%
94%
94%
87%
93%
93%
1 00%
1 00%
100%
100%
1 00%
1 00%
100%
93%
1 00%
73%
88%
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
93% 1
100% 1 1 1
100% 1 1 1
100% 1 1 1
100%
100% 1 1 1
88% 1 1 1
100% 1 1 1
100% 1 1 1
74% 1 1
100% 1 1 1
93% 1 1 1
100% 1
100% 1 1 1
100% 1 1 1
1 00% 1 1
100% 1 1 1
93% 1 1
100% 1 1 1
100% 1 1 1
100% 1 1 1
100% 1 1 1
100% 1 1 1
100% 1 1
1 00% 1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Number w/ 50% in each Q= 3; Number w/ 1 1+ samples in each Q= 8
3 60%
3 80%
3 47%
3 80%
3 10%
1 67%
1 49%
3 63%
1 47%
3 57%
3
3
3
3
3
1
1
3
1
3
35%
71%
94%
97%
71%
64%
83%
68%
78%
74%
3
3
3
3
3
1
1
3
1
3
67% 1
83% 1 1
83%
83% 1 1
87%
64% 1
82% 1
80% 1
73% 1
87%
1
1
1
1
1
1
1
1
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
STATE
SITE POC
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
IOWA
KENTUCKY
LOUISIANA
180892010
180950009
180970042
180970043
180970066
180970078
180970079
180970081
180970083
181270020
181270024
181411008
181412004
181570007
181630006
181630012
181630016
181670018
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Total*ofFRMSites=15;
190130008
190330019
190450021
191032001
191130036
191130037
191390016
191530059
191532510
191532520
191550009
191630015
191630018
191692530
191930017
1
1
1
1
1
1
1
2
1
1
1
2
1
1
1
Total # of FRM Sites=13;
200910007
200910008
200910009
201070002
201730008
201730009
201730010
201770010
201770011
201770012
201910002
202090021
202090022
1
1
1
1
1
1
1
1
1
1
1
1
1
Total* of FRM Sltes=21;
210130002
210190017
210290006
210370003
210430500
210470006
210590014
210670012
210670014
210730006
210930005
211010006
211110043
211110044
211110048
211110051
211170007
211451004
211510003
211950002
212270007
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Total * of FRM Sites=18;
220171002
1
01/27/99
03/19(99
10/01/99
01/24/99
02/05(99
03/07/99
10/01/99
01/22/99
01/22/99
03/04(99
01/27/99
04/01/99
04/01/99
04/01/99
04/15(99
04/15(99
06/05(99
03/19(99
Number w/ Data=15;
01/15(99
07/01/99
01/27/99
01/27/99
01/15(99
01/15(99
01/27/99 03(31/00
11/01/99
02/01/99
02/01/99
07/01/99
01/27/99
07/01/99
02/01/99
01/30(99
Number w/ Data=13;
01/21/99
01/12199
01/12199
01/21/99
01/27/99
01/27/99
01/12199
01/27/99
01/27/99
06/14(99
11/17/99
04/27/99
04/30/99
Number w/Data=21;
07/15(99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
12/21/98
01/01/99
01/01/99 1 on 8/99
01/01/99
06/15(98
06/15(98
01/01/99
06/15(98
01/01/99
01/01/99
06/15(98
01/01/99
01/01/99
Number w/ Data=18;
01/01/99
03/07/99
03/19(99
01/24/99
02/05(99
03/07/99
01/22/99
01/22/99
03/13(99
01/30(99
04/15(99
04/15(99
05/15(99
04/15(99
04/15(99
06/1 1/99
03/19(99
3 30%
3 17%
3 63%
3 43%
3 27%
1 62%
1 72%
3 20%
3 57%
3 17%
Number Complete (75%+ In each Q)= 0;
02/06(99
07/02/99
01/27/99
01/27/99
01/30/99
01/30/99
01/27/99
11/08(99
02/05(99
02/05(99
07/02/99
01/27/99
07/02/99
02/05(99
01/30(99
3 63%
3 70%
3 69%
3 70%
3 57%
3 74%
3 37%
3 50%
3 63%
3 30%
3 67%
Number Complete (75%+ in each Q)= 2;
01/21/99
01/12199
01/12199
01/21/99
01/27/99
01/27/99
01/12199
01/27/99
01/27/99
06/20/99
11/17/99
04/27/99
04/30/99
3 33%
3 77%
3 80%
3 59%
3 73%
3 70%
3 74%
3 67%
3 67%
Number Complete (75%+ in each Q)= 3;
08/16(99
02/02/99
01/21/99
01/27/99
02/02/99
01/30/99
02/01/99
01/21/99
01/30(99
01/30/99
01/27/99
02/02/99
01/02/99
01/01/99
01/06(99
01/02/99
01/27/99
01/30(99
01/30(99
02/02/99
01/30/99
3 57%
3 73%
3 63%
3 63%
3 70%
3 63%
3 70%
3 63%
3 67%
3 63%
3 53%
1 79%
1 77%
3 77%
6 88%
3 50%
3 67%
3 37%
3 57%
3 63%
Number Complete (75%+ in each O)=17:
01/03(99
3 100%
3 43%
3 87%
3 100%
3 100%
3 93%
1 99%
1 93%
3 87%
3 87%
3 73%
3 63%
3 37%
3 60%
3 40%
3 20%
3 80%
3
3
3
3
3
3
3
3
3
3
3
6%
45%
84%
94%
97%
84%
94%
84%
71%
87%
90%
3
3
3
3
3
3
3
3
3
3
80%
93%
87% 1 1
67%
93%
93%
53%
87%
83%
93%
1
1
1
1
1
1
1
1
1
Number w/ 50% in each Q= 9; Number w/ 11+ samples in each Q=10
3 97%
3 94%
3 100%
3 93%
3 100%
3 97%
3 97%
3 100%
3 100%
3 100%
3 100%
3
3
3
3
3
3
3
3
3
3
3
3
3
3
Number w/ 50% in each Q=
3 77%
3 77%
3 77%
3 77%
3 97%
3 87%
3 93%
3 90%
3 80%
3 13%
3 67%
3 53%
Number w/ 50% In e
3 80%
3 83%
3 100%
3 83%
3 100%
3 76%
3 100%
3 100%
3 90%
3 90%
3 70%
1 98%
1 95%
3 80%
6 80%
3 87%
3 83%
3 93%
3 97%
3 90%
Number w/ 50% In <
3 100%
3
3
3
3
3
3
3
3
3
3
3
3
1 00%
94%
100%
100%
94%
1 00%
100%
94%
1 00%
74%
1 00%
1 00%
100%
97%
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
1 00% 1 1
1 00%
100% 1 1
100% 1 1
94% 1 1
97% 1 1
100% 1 1
40%
84% 1
93% 1 1
93%
1 00% 1 1
1 00%
100%
100% 1 1
1
8; Number w/ 1 1+ samples in each Q= 8
90%
81%
94%
94%
90%
94%
81%
1 00%
94%
87%
1 00%
77%
3
3
3
3
3
3
3
3
3
3
3
3
3
1 00%
93% 1 1 1
100% 1 1 1
93% 1 1
90% 1 1
87% 1 1
87% 1 1
90% 1 1
97% 1 1
97%
40%
97%
87%
1
achd=18; Number w/ 11+ samples in each Q=19
6
3
3
3
3
3
3
3
3
3
3
3
1
1
3
6
3
3
3
3
3
33%
87%
84%
100%
74%
1 00%
90%
100%
97%
94%
100%
87%
98%
98%
87%
1 00%
91%
87%
94%
1 00%
1 00%
6
3
3
3
3
3
3
3
3
3
3
3
1
1
3
6
3
3
3
3
3
73%
97% 1 1
87% 1 1
83% 1 1
84% 1 1
97% 1 1
1 00% 1 1
93% 1 1
100% 1 1
1 00% 1 1
3%
70% 1 1
86% 1 1 1
93% 1 1 1
73% 1 1
81% 1 1 1
80% 1 1
93% 1 1
97% 1
1 00% 1 1
1 00% 1 1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
;ach Q=18; Number w/ 11+ samples in each Q=17
3
100%
3
100% 1 1 1
1
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
STATE
MAINE
MASSACHUSETTS
Jl 1 1= rww Began Ended W Beg. Wl 70 Freg, W^70
220190009 1
220190010 1
220290002 1
220330002 1
220330009 1
220331001 1
220470005 1
220470009 1
220511001 1
220512001 1
220550005 1
220710010 1
220710012 1
220730004 1
220790001 1
221050001 1
221210001 1
Total * of FRM Sites=13;
230010011 1
230030013 1
230031011 1
230050015 1
230050026 1
230050027 1
230052003 1
230090103 1
230110016 1
230172011 1
230190002 1
230194003 1
230310008 1
Total # of FRM Sites=18;
240030014 1
240030019 1
240031003 1
240032002 1
240051007 1
240053001 1
240150003 1
240251001 1
240313001 1
240330001 1
240338001 1
240430009 1
245100006 1
245100007 1
245100035 1
245100040 1
245100049 1
245100052 1
Total # of FRM Sites=18;
250035001 1
250052004 1
250053001 1
250092006 1
250095005 1
250096001 1
250130008 1
250130016 1
250132007 1
250154002 1
250171102 1
250210007 1
250230004 1
250250002 1
250250027 1
250250042 1
250270020 1
250272004 1
Total # of FRM Sites=22;
260050003 1
260210014 1
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
Number w/ Data=12;
01/01/99
01/01/99
10/01/97
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
12/01/98
01/01/99
01/01/99
01/12/99
Number w/ Data=16;
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
04/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
Number w/Data=18;
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
04/03(99
01/01/99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
03/20/99
01/03(99
01/03(99
Number w/ Data=22;
10/31/98
11/07/98
01/12/99 6
01/06(99 3
01/03(99 6
01/15(99 3
01/01/99 1
01/06(99 6
01/12199 6
01/06(99 6
01/06(99 1
01/06(99 6
01/03(99 3
01/06(99 3
01/06(99 3
01/06(99 3
01/06(99 6
01/06(99 6
01/01/99 1
60%
83%
81%
83%
97%
93%
93%
93%
91%
80%
97%
97%
80%
83%
93%
93%
89%
Number Complete (75%+ in each Q)= 2;
01/24(99 3
01/21/99 3
01/21/99 3
01/24(99 6
01/24(99 3
01/24(99 6
01/24(99 6
02/05(99 6
01/24(99 6
01/27/99 3
01/24(99 6
01/24(99 6
50%
70%
63%
67%
57%
60%
67%
53%
80%
57%
80%
33%
Number Complete (75%+ in each Q)= 0;
08/07/99
08/13(99
09/03(99
08/04(99
12/11/99
08/04(99
07/26(99
08/01/99
08/07/99
12/17/99
07/26(99
07/29(99
10/21/99
06/17/99
08/01/99
05/1 2/99
Number Complete (
01/03(99 3
01/03(99 3
01/03(99 3
01/03(99 3
01/03(99 3
04/03(99
01/01/99 1
01/03(99 3
01/03(99 3
01/03(99 3
01/03(99 3
01/03(99 3
01/03(99 3
01/03(99 3
01/03(99 3
03/20/99 1
01/03(99 3
01/03(99 3
Number Complete (
01/03(99 1
01/03(99 3
75%+ in each Q)= 8;
73%
77%
77%
43%
87%
57%
97%
77%
97%
77%
83%
83%
73%
1 00%
13%
90%
80%
75%+ in each Q)= 5;
77%
90%
6 80%
3 97%
6 100%
3 93%
1 98%
6 87%
6 93%
6 87%
1 99%
6 100%
3 93%
3 93%
3 87%
3 93%
6 93%
6 93%
1 91 %
FiS5.
6
3
6
3
1
6
6
6
1
6
3
3
3
3
6
6
1
Number w/ 50% in each Q
3 83%
3 97%
3 100%
6 93%
3 77%
3 100%
3 77%
6 100%
6 80%
3 76%
6 81 %
6 87%
3
3
3
6
3
3
3
6
6
3
6
6
WO 70
87%
100%
80%
84%
99%
100%
100%
75%
99%
100%
97%
1 00%
84%
87%
80%
93%
96%
Frig,
6
3
6
3
1
6
6
6
1
6
3
3
3
3
6
6
1
W*t 'ฐ cor
87%
100%
93%
93%
96%
87%
93%
87%
96%
100%
100%
1 00%
80%
87%
100%
1 00%
86%
!2E
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
=11; Number w/ 11+ samples in each Q= 7
84%
97%
1 00%
93%
94%
94%
91%
100%
1 00%
88%
87%
93%
3
3
3
6
3
6
6
6
6
3
6
6
63%
97%
1 00%
87%
80%
80%
94%
100%
93%
94%
93%
87%
1
1
Number w/ 50% in each Q= 0; Number w/ 1 1+ samples in each Q= 0
3 3%
6 20%
3
3
3
3
3
3
3
3
3
3
3
3
3
58%
45%
26%
42%
35%
65%
58%
52%
65%
35%
58%
68%
65%
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
80%
53%
43%
50%
20%
63%
67%
53%
67%
17%
60%
30%
40%
60%
10%
67%
Number w/ 50% in each Q=14; Number w/ 11+ samples in each Q=16
3 87%
3 100%
3 100%
3 97%
3 93%
3 90%
1 9%
3 100%
3 93%
3 97%
3 87%
3 100%
3 80%
3 93%
3 83%
1 76%
3 97%
3 73%
3
3
3
3
3
3
1
3
3
3
3
3
3
3
3
1
3
3
94%
100%
100%
90%
94%
69%
37%
1 00%
100%
90%
87%
97%
100%
97%
97%
62%
100%
84%
3
3
3
3
3
3
1
3
3
3
3
3
3
3
3
1
3
3
83%
93%
93%
97%
70%
74%
96%
93%
93%
90%
63%
100%
73%
97%
87%
18%
93%
90%
1
1
1
1
1
1
1
1
Number w/ 50% in each Q=10; Number w/ 1 1+ samples in each Q=1 1
1 84%
3 100%
1
3
99%
97%
1
3
98%
97%
1
1
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
STATE
SITE POC
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
MINNESOTA
MISSOURI
260490021 1
260550003 1
260650012 1
260770008 1
260810020 1
260990009 1
261150005 1
261210040 1
261250001 1
261390005 1
261450018 1
261470005 1
261610005 1
261610008 1
261630001 1
261630015 1
261630016 1
261630025 1
261630033 1
261630036 1
Total # of FRM Sites=21 ;
270376018 1
270475401 1
270530960 1
270530961 1
270531007 1
270532006 1
270757608 1
270854301 1
270953051 1
271112012 1
271230021 1
271230866 1
271230868 1
271230871 1
271230872 1
271230873 1
271377001 1
271377550 1
271453052 1
271630301 1
271713201 1
Total # of FRM Sites=16;
280010004 1
280110001 1
280330002 1
280350004 1
280450001 1
280470008 1
280490010 1
280490018 1
280590006 1
280670002 1
280750003 1
280810005 1
280870001 1
281210001 1
281230001 1
281490004 1
Total * of FRM Sites=20;
290210010 1
290390001 1
290470005 1
290470026 1
290470041 1
290770032 1
290910003 1
290950036 1
290952002 1
290970003 1
290990012 1
291370001 1
12/1 eras
12/1499
11/07/98
11/19/98
10/23(98
12/22/98
12/17/99
12/18(98
12/25(98
11/07/98
02/23(99
01/03(99
03/28(99
08/04(99
05/1 2/99
02/26ra9
05/12/99
08/22/99
02/OEra9
02/20/99
Number w/ Data=21 ;
04/24/99
10/01/99
04/21/99
04/12/99
04/24(99
04/24(99
10/01/99
10/01/99
12/06/99
11/14/99
04/21/99
04/01/99
03/31/99
04/24/99
04/12/99
04/21/99
05/30/99
05/06(99
12/20/99
10/01/99
10/01/99
Number w/ Data=16;
03/10/99
05/21/99
02/14(99
03/07/99
02/14/99
04/03(99
02/14(99
02/14/99
02/14/99
03/07/99
04/03(99
02/14/99
03/07/99
03/07/99
08/22/99
03/07/99
Number w/ Data=19;
12/15(98
01/01/99
01/01/99
01/01/99
01/01/99
01/03(99
01/01/99
01/03(99 03(12/00
01/03(99
01/01/99
01/01/99
01/01/99
01/03(99
12/14(99
02/06(99
01/03(99
01/02/99
01/03(99
12/17/99
01/08(99
01/03(99
01/03(99
03/04(99
01/03(99
06/26(99
08/07/99
05/1 2/99
02/26(99
05/12/99
08/22/99
02/05(99
02/20/99
3 70%
1 28%
3 77%
1 92%
3 83%
1 74%
3 81 %
3 93%
3 30%
3 80%
3 30%
3 30%
3 27%
Number Complete (75%+ in each Q)= 0;
04/24(99
11/08(99
04/21/99
04/12/99
04/24(99
04/24(99
11/08(99
11/08(99
12/08(99
11/14/99
04/21/99
04/03(99
03/31/99
04/24/99
04/12/99
04/21/99
05/30/99
05/06(99
12/20/99
11/26(99
11/26(99
6 7%
Number Complete (75%+ in each Q)= 0;
03/10/99
05/21/99
02/14(99
03/07/99
02/14/99
04/03(99
02/14(99
02/14/99
02/14/99
03/07/99
04/03(99
02/14/99
03/07/99
03/07/99
08/22/99
03/07/99
3 23%
3 53%
3 30%
3 53%
3 50%
3 53%
3 53%
3 30%
3 50%
3 27%
3 30%
3 27%
Number Complete (75%+ in each Q)=13;
01/03(99
01/03(99
01/03(99
01/01/99
01/02/99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
02/05(99
3 83%
3 97%
3 77%
1 68%
1 82%
3 1 00%
3 90%
3 90%
3 80%
3 80%
3 81 %
3 53%
3 77%
3 63%
3 70%
1 96%
3 73%
3 94%
3 60%
3 100%
3 67%
3 83%
6 13%
1 53%
3 90%
1 31 %
3 87%
3 57%
3
3
3
1
3
3
3
3
3
3
3
3
1
3
1
3
3
3
1 00%
90%
65%
93%
100%
65%
81%
94%
87%
90%
94%
58%
85%
81%
86%
47%
90%
84%
3
3
3
3
1
3
3
3
3
3
3
3
3
3
1
3
1
3
3
3
83% 1 1
20%
100% 1
97% 1 1
95% 1 1 1
90% 1 1
17%
80% 1 1
87% 1 1
97% 1 1 1
60%
90% 1 1 1
90%
93%
90%
83%
89%
61%
97%
68%
1
1
1
1
1
1
1
1
1
Number w/ 50% in each Q= 0; Number w/ 1 1+ samples in each Q= 0
6 80%
1 43%
6 87%
6 80%
6 73%
1 47%
6 100%
6 94%
6 80%
6 93%
1 48%
6 40%
6 60%
6
1
6
6
6
1
6
6
6
6
1
6
6
Number w/ 50% in each Q=
3 73%
3 43%
3 97%
3 93%
3 93%
3 93%
3 87%
3 97%
3 100%
3 100%
3 87%
3 97%
3 100%
3 100%
3 93%
Number w/ 50% in <
3 97%
3 87%
3 97%
1 92%
1 73%
3 100%
3 90%
3 93%
3 100%
3 97%
3 93%
3 93%
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
80%
32%
80%
100%
93%
32%
87%
93%
87%
87%
25%
87%
67%
6
6
1
6
6
6
6
6
6
6
1
6
6
6
6
1
6
6
6
6
6
93%
60%
38%
1 00%
93%
60%
44%
33%
27%
53%
34%
75%
88%
93%
1 00%
32%
60%
73%
13%
40%
40%
1
6; Number w/ 1 1+ samples in each Q= 6
1 00%
100%
100%
1 00%
97%
100%
90%
90%
1 00%
97%
94%
97%
94%
100%
45%
97%
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
1 00%
93%
93% 1 1
1 00%
97% 1 1
93%
97% 1 1
87% 1 1
1 00% 1 1
93%
93%
93% 1 1
1 00%
97%
93%
93%
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
;ach Q=17; Number w/ 11+ samples in each Q=17
3
3
3
1
1
3
3
3
3
3
3
3
1 00%
90%
84%
93%
97%
1 00%
87%
97%
1 00%
87%
97%
100%
3
3
3
1
1
3
3
3
3
3
3
3
100% 1 1 1
90% 1 1 1
97% 1 1 1
92% 1 1
92% 1 1
100% 1 1 1
90% 1 1 1
100% 1 1 1
100% 1 1 1
93% 1 1 1
97% 1 1 1
100% 1 1
1
1
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
STATE
SITE POC
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
NEBRASKA
NEVADA
NEW HAMPSHIRE
NEW JERSEY
NEW MEXICO
291831002 1
291860006 1
291892003 1
291895001 1
295100007 1
295100085 1
295100086 1
295100087 1
Total # of FRM Sites= 9;
300290039 1
300290043 1
300290047 1
300490018 1
300530018 1
300630024 1
300630031 1
300930005 1
301111065 1
Total * of FRM Sltes=13;
310250002 1
310270001 1
310310001 1
310490001 1
310550019 1
310550051 1
310550052 1
310790003 1
311090022 1
311111002 1
311530007 1
311570003 1
311770002 1
Total * of FRM Sltes= 7;
320030022 1
320030560 1
320031019 1
320032002 1
320050008 1
320310016 1
320312002 1
Total * of FRM Sites; 9;
330012003 1
330050007 1
330070014 1
330110019 1
330111007 1
330130003 1
330135001 1
330150009 1
330190003 1
Total # of FRM Sites=19;
340030003 1
340070003 1
340071007 1
340130011 1
340130015 1
340155001 1
340171003 1
340172002 1
340210008 1
340218001 1
340230006 1
340270004 1
340273001 1
340292002 1
340310005 1
340390004 1
340390006 1
340392003 1
340410006 1
Total*ofFRMSItes=13;
350010023 1
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
03/30/99
01/01/99
11/06(99
Number w/ Data= 9;
01/01/99
01/01/99 06(24/99
06/26(99
01/01/99
01/01/99
01/01/99
01/01/99
02/1 1/99
01/01/99
Number w/ Data=13;
03/01/99
09/21/99
08/04(99
08/04(99
01/01/99
01/01/99
01/01/99
03/01/99
01/01/99
03/01/99
03/01/99
03/01/99
04/06(99
Number w/ Data= 7;
01/01/99
01/01/99
01/01/99
01/01/99
12/23(99
01/01/99
06/05(99
Number w/ Data= 0;
01/01/99
01/01/99
01/01/99
08/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
Number w/ Data=19;
01/01/99
01/01/99
01/01/99
01/01/99
04/21/99
09/03(99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
05/30/99
01/01/99
02/1 1/99
01/01/99
01/01/99
01/01/99
12/11/99
08/10/99
Number w/ Data=10;
03/03(99
01/06(99
01/08(99
01/03(99
01/03(99
04/01/99
01/01/99
11/06(99
3
3
3
3
1
83%
87%
63%
87%
86%
Number Complete (75%+ in each Q)= 1;
01/03(99
01/03(99
06/26(99
01/03(99
01/03(99
01/03(99
01/03(99
02/1 1/99
01/03(99
3
3
3
3
3
3
3
3
40%
73%
73%
50%
63%
60%
47%
77%
Number Complete (75%+ in each Q)= 1;
03/04/99
09/21/99
08/04(99
08/04(99
02/06(99
02/02/99
06/10(99
03/07/99
01/03(99
03/01/99
03/04(99
03/13(99
04/06(99
3
1
3
3
3
6
3
6
33%
6%
17%
20%
93%
20%
20%
19%
Number Complete (75%+ in each Q)= 2;
01/03(99
01/14/99
01/03(99
01/03(99
12/23(99
01/03(99
06/05(99
3
1
3
3
3
100%
72%
83%
80%
97%
Number Complete (75%+ in each Q)= 0;
Number Complete (75%+ in each Q)= 0;
02/08(99
03/04(99
02/14(99
02/17/99
04/21/99
10/06(99
02/26(99
08/04/99
02/26(99
02/17/99
02/14/99
05/30/99
02/20/99
02/18(99
02/14/99
02/26(99
02/20/99
12/17/99
10/03(99
3
3
3
3
3
3
3
3
3
3
3
3
3
53%
33%
50%
47%
37%
40%
47%
43%
47%
37%
47%
40%
47%
Number Complete (75%+ in each Q)= 1;
03/03(99
1
27%
3 90%
3 93%
3 97%
3 90%
1 93%
1 98%
3
3
3
3
1
1
1 00%
94%
100%
97%
97%
98%
3
3
3
3
1
1
1
97% 1 1 1
100% 1 1 1
100% 1 1
100% 1 1 1
99%
93% 1 1 1
60%
1
1
1
1
1
1
1
Number w/ 50% in each Q= 5; Number w/ 11+ samples in each Q= 7
3 97%
3 93%
3 7%
3 87%
3 70%
3 100%
3 87%
3 100%
3 87%
3
3
3
3
3
3
3
3
71%
74%
81%
72%
84%
55%
90%
94%
3
3
3
3
3
3
3
3
93% 1
97%
93% 1 1
93% 1 1
93% 1 1
97% 1 1
93% 1
100% 1 1 1
1
Number w/ 50% in each Q= 1; Number w/ 11+ samples in each Q= 1
3 90%
1 19%
3 20%
1 0%
3 77%
3 90%
3 70%
3 57%
3 67%
3 50%
3
3
3
3
1
3
1
3
3
3
3
3
3
Number w/ 50% In each Q=
3 100%
1 90%
3 30%
3 10%
3 100%
3 23%
3
1
3
3
3
3
Number w/ 50% In each Q=
Number w/ 50% in each Q=
3 97%
3 100%
3 90%
3 77%
3 60%
3 83%
3 100%
3 94%
3 93%
3 37%
3 87%
3 63%
3 87%
3 93%
3 100%
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
81%
13%
58%
65%
41%
42%
36%
61%
87%
94%
84%
74%
65%
3
3
3
1
3
6
3
3
3
3
3
3
87%
87%
77%
46%
66%
80%
83%
90% 1 1 1
1 00%
87%
90%
88%
1
3; Number w/ 11+ samples in each Q= 3
97%
96%
94%
90%
90%
87%
3
1
3
3
3
3
3
100% 1 1 1
97% 1 1
90%
93%
10%
100% 1 1 1
1 00%
0; Number w/ 11+ samples in each Q= 0
2; Numberw/ 11+ samples in each Q=11
1 00%
94%
97%
77%
87%
77%
58%
97%
90%
97%
97%
87%
77%
84%
97%
97%
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
93% 1 1
83%
83% 1 1
33%
70%
93%
97% 1
60%
100% 1
90% 1
77% 1
93%
93% 1
68% 1
83% 1
97% 1
67% 1
17%
33%
1
1
1
1
1
1
1
1
Number w/ 50% in each Q= 6; Number w/ 11+ samples in each Q=10
1 88%
1
90%
1
98% 1
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
STATE
SITE POC
22% ^03% ^04%
350010024 1
350050005 1
350130017 1
350131006 1
350171002 1
350250007 1
350431003 1
350439001 1
350439003 1
350450006 1
350490020 1
350499002 1
NEW YORK Total # of FRM Sites=42;
360010005 1
360010012 1
360050073 1
360050080 1
360050083 1
360050110 1
360130011 1
360271004 1
360290002 1
360290005 1
360291007 1
360310003 1
360470011 1
360470052 1
360470076 1
360470118 1
360551004 1
360552002 1
360556001 1
360590005 1
360590008 1
360590011 1
360610010 1
360610056 1
360610062 1
360610115 1
360610117 1
360632008 1
360652001 1
360670019 1
360671015 1
360710002 1
360810094 1
360810097 1
360810116 1
360850055 1
360850067 1
360893001 1
360930003 1
361010003 1
361030001 1
361030005 1
NORTH CAROLINA Total # of FRM Sites=35;
370010002 1
370210034 1
370250004 1
370330001 1
370350004 1
370370004 1
370510009 1
370570002 1
370610002 1
370630001 1
370650003 1
370670022 1
370670024 1
370710016 1
370810009 1
370811005 1
02/03(99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
09/01/99
09/01/99
01/01/99
01/01/99
09/01/99
Number w/ Data=33;
01/01/99
01/01/99
01/01/99 07/15/99
01/01/99
01/01/99
09/15(99
01/01/99
07/01/99
01/01/99
01/01/99
12/15(99
07/01/99
01/01/99
12/15(99
01/01/99
12/31/99
01/01/99 02/28/99
12/15(99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
12/31/99
12/31/99
01/01/99
01/01/99
08/01/99
01/01/99
12/31/99
07/01/99
01/01/99
12/31/99
09/01/99
01/01/99
10/01/99
01/01/99
08/01/99
01/01/99
12/31/99
Number w/Data=35;
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
03/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
02/03(99
01/15(99
01/09(99
01/15(99
01/06(99
01/21/99
01/06(99
01/15(99
01/06(99
1
3
3
3
3
3
3
3
3
49%
43%
60%
71%
67%
63%
67%
70%
87%
1
3
3
3
3
3
3
3
3
Number Complete (75%+ in each Q)= 0;
07/02/99
07/02/99
07/01/99
07/02/99
07/02/99
09/15(99
07/02/99
07/02/99
07/02/99
07/02/99
12/17/99
07/02/99
07/02/99
07/02/99
08/31/99
07/02/99
07/02/99
07/02/99
07/01/99
07/02/99
07/02/99
07/02/99
07/02/99
08/01/99
07/02/99
07/02/99
07/02/99
12/11/99
07/02/99
10/12/99
07/02/99
08/02/99
07/02/99
Number Complete (75%+ In each Q|=17;
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/01/99
03/01/99
01/01/99
01/03(99
01/03(99
01/01/99
01/03(99
3
3
3
3
3
3
3
3
3
1
3
1
3
3
1
3
70%
87%
90%
60%
88%
73%
67%
73%
80%
90%
20%
89%
100%
97%
80%
47%
3
3
3
3
3
3
3
3
3
1
3
1
3
3
1
3
93%
88%
94%
91%
74%
82%
91%
94%
94%
1
3
3
3
3
3
3
3
3
92%
92%
97%
89%
82%
86%
94%
54%
88%
1
3
3
3
1
3
3
3
3
91% 1
94% 1
94% 1 1
97% 1 1
34% 1
89% 1 1
89% 1 1
94% 1 1
97% 1 1 1
Number w/ 50% in each Q= 0; Number w/ 1 1+ samples in each Q= 0
3
3
1
3
3
1
3
3
3
3
1
3
3
3
3
3
3
1
3
3
3
3
3
3
3
3
3
3
1
3
45%
19%
12%
52%
48%
1%
55%
74%
77%
74%
48%
58%
42%
29%
68%
48%
65%
49%
61%
42%
61%
68%
32%
65%
26%
90%
58%
52%
45%
39%
3
3
3
3
1
3
3
3
3
3
1
3
3
3
3
3
3
1
3
3
3
3
3
3
3
3
3
3
3
3
1
3
80%
73%
60%
73%
72%
77%
73%
83%
83%
17%
65%
73%
57%
73%
83%
77%
67%
60%
60%
80%
77%
93%
87%
83%
77%
77%
17%
60%
77%
87%
73%
60%
1
1
1
1
1
1
1
1
1
1
1
Number w/ 50% in each Q=26; Number w/ 11+ samples in each Q=28
90%
94%
97%
73%
97%
83%
83%
87%
93%
90%
90%
86%
97%
90%
81%
35%
3
3
3
3
3
3
3
3
3
1
3
1
3
3
1
3
90%
97%
77%
84%
87%
94%
97%
97%
94%
89%
65%
89%
68%
100%
80%
87%
3
3
3
3
3
3
3
3
3
1
3
1
3
3
1
3
77% 1 1
83% 1 1 1
100% 1 1 1
83% 1 1
93% 1 1 1
87% 1 1
93% 1 1
73% 1 1
97% 1 1 1
91% 1 1 1
43%
89% 1 1 1
90% 1 1
90% 1 1 1
61% 1 1
70% 1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
10
STATE
SITE POC
r>4%
*^ /o
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
NORTH DAKOTA
OKLAHOMA
370870010 1
371070004 1
371110004 1
371190010 1
371190034 1
371190040 1
371190041 1
371210001 1
371230001 1
371290009 1
371330005 1
371350007 1
371390002 1
371470005 1
371550004 1
371730002 1
371830014 1
371830015 1
371910005 1
Total # of FRM Sites= 7;
380130002 1
380130003 1
380150003 1
380171004 1
380350004 1
380570004 1
380910001 1
Total # of FRM Sites=37;
390090003 1
390170003 1
390350013 1
390350027 1
390350038 1
390350045 1
390350060 1
390350065 1
390350066 1
390351002 1
390490024 1
390490025 1
390490081 1
390610014 1
390610040 1
390610041 1
390617001 1
390618001 1
390810016 1
390811001 1
390851001 1
390870010 1
390932003 1
390950024 1
390950025 1
390950026 1
390990005 1
391130014 1
391130031 1
391330002 1
391351001 1
391450013 1
391510017 1
391510020 1
391530017 1
391530023 1
391550007 1
Total # of FRM Sites=24;
400159008 1
400179001 1
400190294 1
400190295 1
400219002 1
400310648 1
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
07/30/99
01/01/99
07/16(99
01/01/99
01/01/99
01/01/99
04/28(99
03/01/99
03/1 0/99
01/01/99
01/01/99
01/01/99
01/01/99
Number w/ Data= 7;
04/01/99
09/03(99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
Number w/Data=37;
01/03(99
01/01/99
01/29/99
01/08(99
01/08(99
12/14(99
01/08(99
01/29/99
01/08(99
01/08(99
01/01/99
01/01/99
01/01/99
01/01/99
04/01/99
03/25(99
01/30(99
03/25(99
01/21/99
02/1 1/99
01/03(99
01/24(99
01/01/99
02/1 1/99
03/01/99
05/29/99
01/01/99
01/15(99
01/14(99
01/30(99
01/21/99
01/15(99
01/03(99
01/03(99
01/01/99
01/01/99
01/01/99
Number w/ Data=19;
11/01/99
07/01/99
02/04/99 1 1/05/99
12/13(99
07/01/99
02/04(99
01/03(99 3
01/03(99 3
01/03(99 3
01/01/99 1
01/01/99 1
01/03(99 3
07/30(99
01/03(99 3
07/17/99
01/03(99 3
01/03(99 3
01/03(99 3
04/30/99
03/01/99 3
03/10(99 3
01/03(99 3
01/01/99 1
01/03(99 3
01/03(99 3
77%
77%
93%
94%
96%
90%
83%
83%
87%
77%
10%
17%
90%
81%
77%
71%
Number Complete (75%+ in each Q)= 2;
04/06(99
09/03(99
01/03(99 3
01/03(99 3
01/03(99 3
01/05(99 6
01/06(99 6
47%
70%
43%
94%
93%
Number Complete (75%+ in each Q)=12;
01/03(99 3
01/01/99 1
01/29/99 3
01/08(99 1
01/08(99 1
12/14(99
01/08(99 3
01/29/99 3
01/08(99 3
01/08(99 3
01/01/99 1
01/01/99 1
01/03(99 3
01/01/99 1
04/03(99
03/25(99 3
01/30(99 1
03/25(99 3
01/21/99 3
02/1 1/99 1
01/03(99 3
01/24(99 3
01/03(99 3
02/1 1/99 1
03/01/99 3
05/29/99
01/01/99 1
01/15(99 1
01/14(99 1
01/30(99 3
01/21/99 3
01/15(99 3
01/03(99 3
01/03(99 3
01/01/99 1
01/01/99 1
01/01/99 1
57%
90%
70%
70%
84%
83%
70%
90%
87%
94%
76%
93%
69%
10%
63%
7%
70%
34%
90%
27%
97%
33%
17%
86%
76%
54%
70%
68%
70%
83%
90%
83%
90%
92%
Number Complete (75%+ in each Q)= 0;
08/16(99
04/24/99
12/20/99
08/22/99
04/06(99
3 97%
3 80%
3 87%
1 98%
1 99%
3 93%
3 90%
3 90%
3 93%
3 90%
3 57%
3 84%
3 100%
3 97%
1 88%
3 90%
3 87%
3
3
3
1
1
3
1
3
3
3
3
3
3
3
3
3
1
3
3
94%
48%
97%
1 00%
32%
94%
68%
90%
68%
94%
94%
84%
65%
74%
94%
97%
82%
74%
81%
3
3
3
1
3
1
3
3
3
3
3
3
3
3
3
1
3
3
90% 1 1 1
93% 1
93% 1 1 1
97% 1 1 1
100% 1 1 1
98%
100% 1 1 1
83%
100% 1 1 1
93% 1 1 1
97% 1 1 1
83%
63%
90%
90% 1 1 1
97% 1 1 1
90% 1 1
73% 1 1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Number w/ 50% in each Q= 3; Number w/ 11+ samples in each Q= 5
6 73%
3 80%
3 94%
3 84%
6 87%
6 100%
6
6
3
3
3
6
6
73%
20%
81%
90%
87%
93%
93%
6
6
3
3
3
6
6
87%
87%
100% 1
1 00% 1 1
90% 1
93% 1 1 1
87% 1 1 1
Number w/ 50% in each Q=26; Number w/ 11+ samples in each Q=29
3 87%
1 99%
3 100%
1 87%
1 90%
3 97%
3 100%
3 87%
3 97%
1 70%
1 91 %
3 73%
1 92%
3 70%
3 97%
1 62%
3 7%
3 90%
1 78%
3 97%
3 0%
3 94%
1 55%
3 80%
1 32%
1 97%
1 92%
1 85%
3 93%
3 81 %
3 77%
3 83%
3 83%
1 95%
1 96%
1 86%
3
1
3
1
1
3
3
3
3
1
1
3
1
3
3
1
3
3
1
3
3
3
1
3
1
1
1
1
3
3
3
3
3
1
1
1
1 00%
95%
97%
90%
84%
97%
1 00%
94%
100%
65%
82%
90%
95%
45%
1 00%
86%
45%
90%
90%
97%
0%
84%
89%
100%
85%
91%
66%
72%
90%
91%
100%
87%
90%
92%
92%
93%
3
1
3
1
1
3
3
3
3
3
1
1
3
1
3
3
1
3
3
1
3
3
3
1
3
1
1
1
1
3
3
3
3
3
1
1
1
87% 1 1
35% 1
97% 1 1
86% 1 1
65% 1 1
20%
100% 1 1 1
90% 1 1
97% 1 1 1
97% 1 1 1
53% 1 1
92% 1 1 1
97% 1 1
66% 1 1
43%
1 00%
57% 1 1
83%
93% 1 1
67% 1
90% 1 1 1
90%
80% 1 1 1
88% 1
81%
84%
93% 1 1 1
55% 1 1
80% 1 1
83% 1 1
13%
93% 1 1
100% 1 1 1
100% 1 1 1
96% 1 1 1
97% 1 1 1
88% 1 1 1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Number w/ 50% in each Q= 0; Number w/ 1 1+ samples in each Q= 0
6 13%
6 73%
6
6
6
6
33%
93%
33%
67%
6
6
6
6
6
60%
27%
7%
60%
80%
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
11
STATE
SITE POC
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
OREGON
PENNSYLVANIA
400390852 1
400470554 1
400710602 1
400719003 1
400819005 1
400970186 1
401010169 1
401090035 1
401090038 1
401091037 1
401159004 1
401179007 1
401190614 1
401210415 1
401250054 1
401339006 1
401430110 1
401430131 1
Total * of FRM Sites=27;
410030013 1
410090004 1
410170113 1
410290133 1
410291001 1
410292129 1
410330107 1
410350004 1
410370001 1
410370003 1
410390060 1
410391007 1
410392013 1
410430009 1
410470040 1
410470109 1
410470110 1
410510080 1
410510244 1
410510246 1
410590121 1
410610006 1
410610117 1
410619103 1
410650007 1
410670111 1
410671003 1
Total # of FRM Sites=37;
420010001 1
420030008 1
420030021 1
420030064 1
420030067 1
420030093 1
420030095 1
420030097 1
420030116 1
420030131 1
420031008 1
420031301 1
420039002 1
420070014 1
420110009 1
420170012 1
420210011 1
420430401 1
420450002 1
420490003 1
420692006 1
420710007 1
420770004 1
420791101 1
420910013 1
01/01/99
01/26(99
03/01/99
11/01/99
11/01/99
02/28(99
01/25(99
01/01/99
01/20/99
01/01/99
07/01/99
11/01/99
01/29/99
04/01/99
01/23(99
11/01/99
01/01/99
01/01/99
Number w/ Data=27;
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
09/15(99
01/01/99
01/01/99
01/01/99
09/09/99
01/01/99
01/01/99
01/01/99
10/27/99
01/01/99
01/01/99
06/17/99
01/01/99
12/17/98
08/27/99
01/01/99
01/01/99
07/01/99
07/01/99
08/06(99
01/01/99
08/20/99
Number w/ Data=35;
01/01/99
02/23(99
02/14(99
01/23(99
04/12/99
03/25(99
01/30(99
01/31/99
01/30/99
02/05(99
02/13(99
01/30/99
01/24(99
12/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
04/06(99
04/06(99
05/06(99
04/1 2/99
04/06(99
04/01/99
04/06(99
04/06(99
08/16(99
04/06(99
04/06(99
04/06(99
04/02/99
04/03(99
Number Complete (75%+ in each Q)=10;
01/03(99 3
01/01/99 1
01/06(99 6
01/01/99 1
01/01/99 1
09/15(99
08/31/99
01/06(99 6
01/06(99 6
09/09/99
01/01/99 1
02/02/99 3
01/01/99 1
10/27/99
01/09(99 3
01/01/99 1
07/29/99
01/01/99 1
01/01/99 1
08/27/99
01/06(99 6
01/06(99 6
09/15(99
09/15(99
12/14/99
01/01/99 1
09/15(99
Number Complete (
01/01/99 1
02/23(99 3
02/14(99 3
01/23(99 1
04/12/99
03/25(99 6
01/30(99 6
01/31/99 6
01/31/99 3
02/05(99 6
02/13(99 3
01/30/99 6
01/24(99 6
01/30/99 3
02/11/99 3
02/14(99 3
01/01/99 1
01/06(99 3
01/30(99 3
01/30(99 1
01/09/99 3
01/30/99 1
01/05(99 1
02/14(99 3
90%
91%
93%
94%
86%
100%
1 00%
92%
67%
92%
93%
96%
91%
88%
73%
93%
94%
75%+ in each Q)= 0;
67%
37%
33%
44%
7%
38%
20%
55%
31%
47%
33%
73%
43%
43%
50%
66%
50%
29%
39%
50%
20%
50%
50%
6 60%
6 67%
6 40%
6 40%
6 33%
1 73%
3 60%
6 73%
6 73%
3 57%
6 67%
1 64%
3 57%
Number w/ 50% in <
3 87%
1 93%
6 94%
1 74%
1 96%
6 80%
6 100%
1 97%
3 93%
1 73%
3 94%
1 71 %
1 90%
1 89%
6 87%
6 87%
1 91 %
6
6
6
6
6
1
3
6
6
6
3
6
1
3
93%
87%
93%
53%
53%
35%
65%
47%
40%
93%
45%
53%
34%
50%
6
6
6
6
6
1
3
6
6
6
3
6
1
3
93%
87%
93%
87%
93%
88%
73%
80%
80%
93%
80%
100%
89%
90%
;ach Q=15; Number w/ 11+ samples in each Q=15
3
3
6
1
3
1
3
6
6
6
1
3
1
3
3
1
1
1
6
6
1
6
1
3
87%
84%
97%
87%
94%
16%
29%
97%
1 00%
27%
98%
87%
91%
87%
58%
97%
95%
37%
1 00%
80%
14%
20%
74%
13%
3
3
1
1
3
1
3
1
1
6
1
3
1
3
3
3
1
1
1
1
1
6
6
3
3
93% 1 1 1
90% 1 1 1
96% 1 1 1
100% 1 1
87% 1 1 1
99%
97%
91% 1 1 1
95% 1 1 1
1 00%
98% 1 1 1
1 00% 1 1
91% 1 1
73%
97% 1 1 1
1 00%
90% 1 1 1
93% 1 1 1
90%
70% 1 1
90%
93%
20%
97% 1 1
97%
1
1
Number w/ 50% in each Q=10; Number w/ 1 1+ samples in each Q=21
1 86%
3 10%
3 83%
1 58%
3 70%
6 38%
6 53%
3 56%
6 73%
3 87%
3 80%
6 87%
3 80%
3 57%
3 73%
1 85%
3 83%
3 33%
1 78%
3 93%
1 87%
1 70%
3 60%
1
3
3
1
3
6
6
6
3
6
3
3
6
3
3
3
1
3
3
1
3
1
1
3
63%
57%
69%
54%
84%
33%
67%
33%
77%
40%
52%
74%
67%
90%
55%
68%
85%
87%
10%
88%
71%
24%
84%
65%
1
1
3
1
3
6
6
6
3
6
3
3
6
3
3
3
1
3
3
1
3
1
1
3
78% 1 1
45%
78%
51% 1
73%
33%
20%
67%
71% 1 1
20%
74% 1
72%
60% 1
87% 1
67% 1
73% 1 1
33% 1
90% 1 1
53%
78% 1
80% 1 1
72% 1
72% 1 1
83% 1 1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
12
STATE
PUERTO RICO
RHODE ISLAND
SOUTH CAROLINA
SOUTH DAKOTA
TENNESSEE
Jl 1 1= rww Began Ended W Beg. Wl 70 Freg, W^70
420950025 1
420990301 1
421010004 1
421010020 1
421010024 1
421010047 1
421010136 1
421250005 1
421250200 1
421255001 1
421290008 1
421330008 1
Total # of FRM Sites= 9;
720210009 1
720530003 1
720570008 1
720590016 1
720610005 1
720810001 1
720970003 1
721130004 1
721270003 1
Total * of FRM Sites= 7;
440030002 1
440070020 1
440070022 1
440070023 1
440071005 1
440071010 1
440090007 1
Total # of FRM Sites=17;
450130007 1
450190046 1
450190048 1
450190049 1
450290002 1
450370001 1
450410002 1
450430009 1
450450009 1
450470003 1
450630005 1
450630008 1
450730001 1
450790007 1
450790019 1
450830010 1
450910006 1
Total * of FRM Sites; 8;
460110002 1
460990006 1
460990007 1
461030014 1
461030015 1
461030016 1
461030017 1
461031001 1
Total* of FRM Sites=21;
470090005 1
470370023 1
470450004 1
470650031 1
470650032 1
470654002 1
470930028 1
470931017 1
470931020 1
470990002 1
471130004 1
471192007 1
471251009 1
471410001 1
01/01/99
12/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
Number w/ Data= 9;
02/02/99
04/20(99
01/15(99
01/15(99
01/15(99
01/15(99
01/24/99
01/15(99
03/21/99
Number w/ Data= 7;
01/06(99
01/06(99
01/01/99
12/01/99
01/06(99
01/06(99
01/01/99
Number w/Data=17;
03/25(99
01/15(99
04/15(99
11/26(98
04/15(99
04/30(99
02/23(99
01/15(99
05/30/99
12/04(98
11/19(98
12/01/98
12/31/98
11/01/98
11/26(98
11/13(98
12/10/98
Number w/ Data= 8;
01/01/99
01/01/99
01/01/99
12/31/98
01/01/99
01/01/99
01/01/99
01/01/99
Number w/ Data=12;
10/01/98
01/01/99
08/22/99
05/06(99
06/05(99
01/01/99
01/01/99
01/01/99
01/01/99
10/01/98
10/01/98
12/25(98
10/01/98
12/25(98
01/05(99
02/04(99
02/1 1/99
02/17/99
02i2aaa
02/04(99
01/15(99
01/18(99
01/08(99
02/11/99
01/09/99
1 20%
1 39%
3 19%
3 17%
3 33%
1 33%
3 67%
3 63%
1 44%
3 40%
3 70%
Number Complete (75%+ in each Q)= 0;
02/02/99
04/21/99
01/24/99
01/24/99
01/23(99
01/21/99
01/24/99
01/24/99
03/21/99
3 50%
3 60%
3 63%
1 66%
3 53%
3 65%
3 63%
1 10%
Number Complete (75%+ in each Q)= 0;
01/06(99
01/06(99
01/06(99
12/11/99
01/06(99
01/06(99
01/06(99
3 0%
6 0%
1 0%
3 0%
1 0%
3 0%
Number Complete (75%+ in each Q)= 7;
03/25(99
01/15(99
04/15(99
01/01/99
04/15(99
04/30(99
02/23(99
01/15(99
05/30/99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/01/99
01/03(99
3 0%
3 87%
1 98%
3 37%
3 83%
3 80%
3 87%
3 90%
3 77%
3 68%
3 90%
1 82%
3 83%
Number Complete (75%+ in each Q)= 1;
04/03(99
04/03(99
01/03(99
01/03(99
01/03(99
01/03(99
04/03(99
04/03(99
3 63%
3 80%
3 80%
3 63%
Number Complete (75%+ in each Q)= 0;
01/03(99
08/25(99
01/03(99
01/01/99
01/01/99
01/03(99
01/03(99
01/06(99
01/03(99
09/15(99
3 43%
3 80%
1 72%
1 0%
3 37%
3 0%
3 50%
3 37%
1 89%
1 57%
3 61 %
3 20%
3 43%
1 42%
3 70%
3 57%
1 79%
3 67%
3 93%
FiS5.
1
1
3
3
3
1
3
3
1
3
3
WO 70
34%
83%
90%
81%
87%
29%
61%
84%
83%
84%
71%
Frig,
1
1
3
3
3
1
3
3
1
3
3
W*t 'ฐ cor
54%
76%
93%
93%
87%
9%
43%
50%
79%
37%
83%
iiE
Number w/ 50% in each Q= 5; Number w/ 11+ samples in each Q= 6
3 73%
1 58%
3 83%
3 47%
1 73%
3 57%
3 87%
3 93%
1 86%
3
1
3
3
1
3
3
3
1
Number w/ 50% in each Q=
3 100%
6 73%
1 87%
3 93%
1 92%
3 77%
3
6
1
3
1
3
77%
83%
81%
77%
65%
32%
68%
65%
86%
3
1
3
3
1
3
3
3
1
71%
15%
73%
70%
74%
40%
57%
73%
62%
0; Number w/ 11+ samples in each Q= 0
1 00%
93%
97%
1 00%
98%
100%
3
6
1
3
3
1
3
1 00%
93%
96%
20%
93%
99%
97%
Number w/ 50% in eachd=11; Number w/ 11+ samples in each Q=12
3 73%
3 87%
1 76%
1 98%
3 53%
3 63%
3 84%
3 90%
1 32%
3 100%
3 97%
3 87%
3 67%
3 90%
3 97%
1 100%
3 50%
3
3
1
1
3
3
3
3
1
3
3
3
3
3
3
1
3
94%
87%
86%
78%
77%
94%
100%
81%
86%
94%
100%
94%
78%
81%
97%
76%
74%
3
3
1
1
3
3
3
3
1
3
3
3
3
3
3
1
3
80%
87%
99%
80%
80%
93%
87%
93%
1 00%
63%
93%
97%
87%
87%
90%
97%
87%
1
1
1
1
1
1
1
Number w/ 50% in each Q= 4; Number w/ 11+ samples in each Q= 4
3 77%
3 97%
3 74%
3 87%
3 100%
3 87%
3 87%
3 93%
3
3
3
3
3
3
3
3
53%
90%
63%
77%
87%
94%
94%
97%
3
3
3
3
3
3
3
3
87%
87%
77%
73%
91%
82%
74%
91%
1
Number w/ 50% in each Q= 0; Number w/ 1 1+ samples in each Q= 3
3 47%
3 70%
1 49%
1 0%
3 30%
3 13%
3 20%
3 27%
3
3
3
1
1
3
3
3
3
3
87%
29%
52%
16%
0%
61%
26%
74%
48%
13%
3
3
3
1
1
3
3
3
3
3
77%
63%
47%
14%
13%
63%
90%
80%
73%
70%
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
1
1 1
1
1
1 1
1 1
1
1
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
13
STATE
SITE POC
r>4%
*^ /o
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
VERMONT
471450004 1
471570014 1
471570038 1
471570047 1
471571004 1
471631007 1
471650007 1
Total # of FRM Sites=47;
480290034 1
480290052 1
480290053 1
480370004 1
480391003 1
480550062 1
480612002 1
480850005 1
481130020 1
481130035 1
481130050 1
481130057 1
481130069 1
481130087 1
481350003 1
481410002 1
481410010 1
481410037 1
481410038 1
481410043 1
481410044 1
481410045 1
481670053 1
481671005 1
482010024 1
482010026 1
482010051 1
482010058 1
482010062 1
482011035 1
482011037 1
482011039 1
482150042 1
482150043 1
483030001 1
483150050 1
483390089 1
483550020 1
483550032 1
483750005 1
484390063 1
484391002 1
484391003 1
484393006 1
484530020 1
484530021 1
484790016 1
Total # of FRM Sites=11;
490110001 1
490350003 1
490350012 1
490353006 1
490353007 1
490450002 1
490490002 1
490494001 1
490495010 1
490570001 1
490570007 1
Total * of FRM Sites; 5;
500030005 1
500070007 1
500070012 1
500210002 1
10/01/98
12/01/98
12/01/98
12/01/98
12/01/98
10/01/98
10/01/98
Number w/ Data=40;
01/01/99 10/07/9
01/01/99
10/06(99
01/06(99
01/06(99
01/03(99
01/03(99
01/06(99
01/01/99
01/03(99
01/01/99
01/06(99
01/01/99
01/03(99
01/03(99
01/01/99
01/06(99
01/01/99
01/06(99
01/03(99 12/14/9
01/01/99
01/06(99
01/06(99
01/03(99
01/01/99
01/01/99
01/06(99
01/06(99
01/06(99
01/01/99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
11/05(99
01/03(99
01/06(99
01/03(99
01/03(99
01/01/99
01/01/99
01/01/99
01/01/99
09/29(99
01/06(99
Number w/Data=11;
01/01/99
01/01/98
01/01/99
01/01/98
01/21/99
01/01/99
01/01/98
01/01/98
01/01/99
01/01/98
01/01/99
Number w/ Data= 5;
01/03(99
01/03(99
07/29(99
01/03(99
01/03(99 3
01/03(99 3
3%
40%
Number Complete (75%+ in each Q)= 0;
9 04/01/99
03/31/99 1
10/06(99
02/17/99 6
11/26(99
03/31/99 3
03/13(99 6
03/1 1/99 1
01/06(99 3
01/01/99 1
01/06(99 6
03/1 1/99 1
01/03(99 3
03/28(99 6
04/02/99
12/02/99
01/30(99 1
12/14(99
9 01/30/99 3
01/30/99 1
02/05(99 6
06/05(99
10/15(99
10/26(99
08/16(99
08/16(99
04/06(99
04/01/99
08/28(99
07/05(99
01/09/99 3
02/14/99 3
11/26(99
01/30(99 3
03/11/99 1
08/14/99
02/03(99 1
03/1 2/99 1
10/30(99
08/10/99
Number Complete (
01/04(99 3
01/03(99 3
01/03(99 3
01/01/99 1
01/24/99 3
01/03(99 3
01/03(99 3
01/01/99 1
01/03(99 3
01/03(99 3
01/03(99 3
1%
53%
3%
13%
9%
17%
13%
27%
9%
17%
13%
40%
43%
38%
13%
10%
33%
27%
8%
18%
8%
75%+ in each Q)= 9;
100%
97%
93%
89%
63%
63%
100%
84%
97%
97%
80%
Number Complete (75%+ In each Q)= 3;
01/03(99 3
01/03(99 3
07/29(99
01/03(99 3
77%
70%
87%
3 20%
3 27%
3
3
23%
55%
3
3
40%
63%
1
1
Number w/ 50% in each Q= 0; Number w/ 1 1+ samples in each Q= 4
1 24%
1 18%
6 33%
3 23%
6 13%
1 40%
3 30%
1 15%
6 7%
1 35%
3 27%
3 23%
1 25%
1 37%
3 30%
1 53%
6 40%
6 7%
6 13%
1 15%
3 23%
3 23%
1 7%
1 26%
1 16%
1
6
3
6
1
3
1
6
1
3
3
1
3
1
6
6
6
6
6
1
3
3
3
3
3
1
1
1
1
6
Number w/ 50% in each Q=11
3 93%
3 100%
3 93%
1 92%
3 100%
3 81 %
3 100%
1 90%
3 83%
3 100%
3 93%
3
3
3
1
3
3
4%
47%
3%
33%
35%
45%
70%
20%
26%
29%
10%
25%
45%
20%
7%
7%
27%
13%
40%
30%
35%
6%
10%
35%
16%
17%
30%
30%
45%
13%
1
1
3
6
6
3
6
1
3
1
6
1
3
3
1
6
1
6
3
1
6
6
3
1
6
6
6
1
3
3
3
3
6
3
1
1
1
1
1
6
5%
23%
23%
53%
7%
33%
40%
85%
57%
33% 1
67%
97%
70%
80%
35%
33%
63% 1
13%
60%
71% 1
53%
33%
43%
15%
40%
13%
53%
77%
70%
7%
57%
1 00%
13%
83%
98%
76%
99% 1
87%
54%
60%
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
; Number w/ 11+ samples in each Q=11
94%
97%
97%
79%
97%
87%
3 100%
1
3
3
3
Number w/ 50% in each Q= t;
3 100%
3 87%
3 81 %
3
3
3
3
99%
87%
97%
94%
3
3
3
1
3
3
3
1
3
3
3
100% 1 1 1
100% 1 1 1
97% 1 1 1
85% 1 1 1
80% 1 1
94% 1 1
100% 1 1 1
92% 1 1 1
97% 1 1 1
87% 1 1 1
80% 1 1 1
Number w/ 11+ samples in each Q= 4
90%
81%
71%
77%
3
3
3
3
100% 1 1 1
93% 1 1
87%
97% 1 1 1
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
14
STATE
VIRGIN ISLANDS
SITE POC
O4%
*^ /o
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
WASHINGTON
WEST VIRGINIA
WISCONSIN
500230005 1
Total * of FRM Sites= 1;
780010012 1
Total # of FRM Sites=20;
510130020 1
510360002 1
510410003 1
510590030 1
510591004 1
510595001 1
510870014 1
510870015 1
511071005 1
511390004 1
515200006 1
515500012 1
516500004 1
516800014 1
517000013 1
517100024 1
517600020 1
517700014 1
517750010 1
518100008 1
Total # of FRM Sites=23;
530050002 1
530090009 1
530110013 1
530330004 1
530330017 1
530330021 1
530330024 1
530330027 1
530330057 1
530330080 1
530332004 1
530530029 1
530530031 1
530531018 1
530570014 1
530610005 1
530611007 1
530630016 1
530630047 1
530639000 1
530670013 1
530730015 1
530770012 1
Total * of FRM Sltes=14;
540030003 1
540090005 1
540110006 1
540290011 1
540291004 1
540330003 1
540390009 1
540391005 1
540511002 1
540610003 1
540690008 1
540810002 1
540890001 1
541071002 1
Total * of FRM Sites=28;
550090005 1
550090025 1
550090026 1
550250025 1
550250047 1
550270007 1
550290004 1
550310025 1
01/12/99
Number w/ Data= 1;
01/12199
Number w/ Data=20;
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
10/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
01/01/99
Number w/ Data=23;
12/16(98
10/03(99
11/19/98
12/07/98 10/03/99
12/28(98
12/23(98
03/10/99
08/04(99
10/17/98
11/01/98
10/28(98
10/03(99
10/28(98
10/28(98
12/03(99
10/03(99
10/28(98
12/19/98
12/04(98
11/07/98
10/31/98
02/05(99
01/09/99 08(31/99
Number w/Data=14;
02/14(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99 05(09/00
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
Number w/ Data=28;
01/01/99
01/01/99
01/01/99
01/03(99
01/03(99
01/06(99
01/01/99
01/01/99
01/12/99
3 87%
Number Complete (75%+ In each Q)= 0;
01/12199
6 60%
Number Complete (75%+ in each Q)= 0;
01/29/99
01/30(99
02/02/99
01/29/99
01/30/99
01/30(99
01/28(99
01/28(99
02/05(99
11/23(99
01/30(99
01/31/99
01/30/99
01/28(99
02/08(99
01/30/99
01/27/99
02/02/99
01/30(99
02/02/99
3 57%
3 63%
3 20%
1 62%
3 50%
3 57%
3 60%
3 67%
3 63%
3 57%
1 59%
3 70%
3 47%
1 31 %
3 57%
1 61 %
3 63%
3 63%
3 56%
Number Complete (75%+ in each Q)= 9;
02/28(99
10/03(99
01/09/99
01/03(99
01/03(99
01/01/99
03/10/99
08/04(99
01/01/99
01/03(99
01/03(99
10/03(99
01/01/99
01/01/99
12/14(99
10/03(99
01/03(99
01/01/99
01/03(99
01/06(99
01/03(99
02/05(99
01/09/99
3 40%
3 87%
3 93%
3 57%
1 99%
3 27%
1 99%
3 93%
3 90%
1 96%
1 92%
3 93%
1 67%
3 60%
6 100%
3 93%
3 50%
3 80%
Number Complete (75%+ in each Q)=10;
02/14(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
01/03(99
3 50%
3 97%
3 93%
3 93%
3 73%
3 83%
3 87%
3 100%
3 100%
3 83%
3 97%
3 90%
3 57%
3 73%
Number Complete (75%+ in each Q)=18;
01/21/99
01/03(99
01/03(99
01/03(99
01/16(99
01/06(99
01/03(99
01/03(99
3 74%
3 83%
3 71 %
3 97%
3 72%
6 1 00%
3 84%
3 90%
3 93%
3
Number w/ 50% In each Q=
6 40%
6
94%
3
97% 1 1 1
0; Number w/ 11+ samples in each Q= 0
33%
6
33%
Number w/ 50% in eachd=11; Number w/ 11+ samples in each Q=16
3 90%
3 77%
3 53%
1 84%
3 100%
3 77%
3 70%
3 67%
3 100%
3 80%
1 98%
3 94%
3 73%
3 94%
3 87%
1 92%
3 90%
3 97%
3 94%
3
3
3
1
3
3
3
3
3
3
1
3
3
3
3
1
3
3
3
97%
77%
81%
71%
90%
97%
81%
77%
97%
77%
88%
97%
55%
97%
97%
93%
65%
74%
91%
3
3
3
1
3
3
3
6
3
3
3
1
3
3
3
3
1
3
3
3
57% 1 1
50% 1 1
47%
47% 1
43% 1
33%
50% 1 1
67% 1 1
60% 1 1
23%
87% 1 1
51% 1 1
47% 1
10%
53% 1
47% 1
54% 1 1
67% 1 1
53% 1 1
53% 1 1
1
1
1
1
1
1
1
1
1
1
1
1
1
Number w/ 50% in each Q=12; Number w/ 1 1+ samples in each Q=14
3 73%
3 93%
3 93%
3 60%
1 99%
3 100%
1 100%
3 93%
3 100%
1 100%
1 100%
3 100%
1 76%
3 94%
6 100%
3 97%
3 97%
3 70%
Number w/ 50% in <
3 70%
3 90%
3 100%
3 100%
3 87%
3 100%
3 100%
3 87%
3 100%
3 100%
3 100%
3 100%
3 100%
3 81 %
Number w/ 50% in <
3 83%
3 70%
3 84%
3 87%
3 85%
6 100%
3 90%
3 100%
3
3
3
1
3
3
1
3
3
1
1
3
1
3
6
3
3
3
39%
87%
94%
1 00%
1 00%
52%
92%
84%
1 00%
96%
99%
100%
61%
35%
93%
81%
81%
58%
3
6
3
3
1
3
3
1
3
3
1
1
1
6
3
3
1
3
6
3
3
75%
93%
93% 1
93% 1 1
93% 1 1 1
90%
97%
90% 1 1 1
95% 1 1 1
97% 1 1 1
92%
96% 1 1 1
97% 1 1 1
20%
100%
93% 1 1 1
57% 1 1
61% 1
93% 1 1 1
90% 1 1 1
93% 1 1
1
;ach Q=14; Number w/ 11+ samples in each Q=14
3
3
3
3
3
3
3
3
3
3
3
3
3
3
87%
1 00%
1 00%
100%
77%
90%
1 00%
97%
100%
94%
87%
97%
84%
90%
3
3
3
3
3
3
3
3
3
3
3
3
3
3
97% 1 1
87% 1 1 1
100% 1 1 1
97% 1 1 1
97% 1 1
93% 1 1 1
100% 1 1 1
97% 1 1 1
100% 1 1 1
97% 1 1 1
80% 1 1 1
93% 1 1 1
93% 1 1
90% 1 1
1
1
1
1
1
1
1
1
1
1
1
1
1
;ach Q=26; Number w/ 11+ samples in each Q=25
3
3
3
3
3
3
3
3
97%
94%
90%
81%
94%
94%
94%
94%
3
3
3
3
3
3
3
3
87% 1 1
90% 1 1
97% 1 1
97% 1 1 1
1 00% 1 1
87% 1 1 1
80% 1 1 1
87% 1 1 1
stateraug.123
-------
1999 PM2.5 Data Completeness, Routine FRM (as of AIRS 7/26/00)
15
STATE
SITE POC
r>4%
*^ /o
a4Q,75% ซ4Q50% All4Qw/ll
cgmplete cgmplete samples
550430009
550550008
550590019
550710007
550790010
550790026
550790043
550790050
550790051
550790059
550790099
550870009
550890008
551050002
551091002
551250001
551330027
551330034
551390011
551410016
1
1
3
1
2
1
1
1
1
2
1
1
1
1
1
1
2
1
1
1
Total # of FRM Sites= 3;
560210001
560330001
560330002
1
1
1
01/06(99
01/01/99
12/25(98
01/01/99
01/01/99
01/01/99
01/1399
03/13(99
02/05(99
12/25(98
02/05(99
01/01/99
03/19/99
01/03(99
01/01/99
01/01/99
01/01/99
01/21/99
01/01/99
01/03(99
Number w/ Data= 3;
10/15(98
10/01/98
10/01/98
01/06(99
01/03(99
01/03(99
01/03(99
01/05(99
01/01/99
01/21/99
03/13(99
02/05(99
01/03(99
02/05(99
01/03(99
03/25(99
01/03(99
01/09(99
01/06(99
01/03(99
01/21/99
01/03(99
01/03(99
6 93%
3 90%
3 97%
3 90%
1 92%
1 97%
3 70%
3 20%
3 63%
3 80%
3 68%
3 93%
6 13%
3 100%
6 87%
6 93%
3 93%
3 77%
3 93%
3 93%
Number Complete (75%+ in each Q)= 3;
01/03(99
01/03(99
01/03(99
3 90%
3 100%
3 1 00%
6 80%
3 93%
3 100%
3 100%
1 98%
1 99%
3 100%
3 91 %
3 100%
3 97%
3 100%
3 97%
3 90%
3 94%
6 67%
6 100%
3 100%
3 94%
3 100%
3 100%
6
3
3
3
1
1
3
3
3
3
3
3
3
3
6
6
3
3
3
3
94%
94%
97%
81%
95%
95%
97%
97%
97%
100%
100%
90%
97%
97%
87%
93%
94%
100%
97%
94%
6
3
3
3
1
1
3
3
3
3
3
3
3
3
6
6
3
3
3
3
100% 1 1 1
78% 1 1 1
97% 1 1 1
90% 1 1 1
97% 1 1 1
90% 1 1 1
87% 1 1
1 00%
93% 1 1
97% 1 1 1
100% 1 1
97% 1 1 1
97%
97% 1 1 1
93% 1
94% 1 1 1
97% 1 1 1
100% 1 1 1
87% 1 1 1
84% 1 1 1
1
1
1
1
1
1
1
1
1
Number w/ 50% in each Q= 3; Number w/ 11+ samples in each Q= 3
3 97%
3 100%
3 93%
3
3
3
77%
87%
1 00%
3
3
3
83% 1 1 1
100% 1 1 1
100% 1 1 1
stateraug.123
-------
Attachment 2-2
Summary ofPM2.5Data Qualifiers Flags
The following attachments list the four types of data qualifiers used in the PM25 Program. Definitions of
the data qualifiers are provided below.
Null value codes- Code that replaces the actual routine value
Code
9967
9968
9969
9970
9971
9972
9973
9974
9975
9976
9977
9978
9979
9980
9981
Explanation
Sample Pressure Out of Limits
Technician Unavailable
Construction/Repairs in Area
Shelter Storm Damage
Shelter Temperature Outside Limits
Scheduled But Not Collected
Sample Time Out of Limits
Sample Flow Rate Out of Limits
Insufficient Data (Can't Calculate)
Filter Damage
Filter Leak
Voided by Operator
Miscellaneous Void
Machine Malfunction
Bad Weather
Code
9982
9983
9984
9985
9986
9987
9988
9989
9991
9992
9993
9994
9995
9997
9998
Explanation
Vandalism
Collection Error
Lab Error
Poor Quality Assurance Results
Calibration
Monitoring Waived
Power Failure (POWR)
Wildlife Damage
Quality Control (QC) Control Points (zero/span)
QC Audit
Maintenance/Routine Repairs
Unable to Reach Site
Multi-point Calibration
Building/Site Repair
Precision/Zero/Span
Exceptional Events
A
E
J
I
High Winds
Forest Fire
Construction/Demolition
Unusual Traffic Congestion
L
P
Q
U
Highway Construction
Roofing Operation
Prescribed Burning
Sahara Dust
Sampler Generated flags
T
W
Multiple PM2.5 Validity Flags (W or X flag)
Flow rate average out of spec.
X
Y
Filter Temperature difference out of spec
Elapsed sample time out of Spec.
Data Qualifiers
1
2
3
Deviation from a CFR method requirement-
Operational Deviations- Out of some pre-defined
threshold value.
Field Issue- possible field contamination
4
5
6
Lab Issue- possible lab contamination
Outlier -outside the normal/expected range of
concentrations or fails various statistical or
comparison tests
QAPP - Data collection prior to QAPP approval
-------
Summary of AIRS PM2.5 Data Flags by State
State
ALABAMA
ALASKA
ARIZONA
ARKANSAS
CALIFORNIA
COLORADO
CONNECTICUT
DELAWARE
DISTRICT OF COLUMBIA
FLORIDA
GEORGIA
HAWAII
IDAHO
ILLINOIS
INDIANA
IOWA
KANSAS
KENTUCKY
LOUISIANA
MAINE
MARYLAND
MASSACHUSETTS
MICHIGAN
MINNESOTA
MISSISSIPPI
MISSOURI
MONTANA
NEBRASKA
NEVADA
NEW HAMPSHIRE
NEW JERSEY
NEW MEXICO
NEW YORK
NORTH CAROLINA
NORTH DAKOTA
OHIO
OKLAHOMA
OREGON
PENNSYLVANIA
PUERTO RICO
RHODE ISLAND
SOUTH CAROLINA
SOUTH DAKOTA
TENNESSEE
TEXAS
UTAH
VERMONT
VIRGIN ISLANDS
VIRGINIA
WASHINGTON
WEST VIRGINIA
WISCONSIN
WYOMING
Totals
Total # Mon.
with Data
20
7
12
22
88
17
15
11
5
26
26
7
16
25
33
15
17
27
18
12
17
23
28
24
16
19
9
17
8
0
21
10
43
42
7
37
24
27
38
9
9
21
8
15
40
11
6
1
20
23
16
28
3
1039
Total
# Values
574
451
1685
773
8183
1122
1248
1121
667
4578
2722
876
880
1389
2477
1370
1321
2546
2259
909
449
2415
2953
810
1472
2856
784
958
864
0
1509
1471
1648
4831
457
6444
936
3946
4095
1098
909
2574
716
804
2078
1655
574
25
2141
3010
1764
3366
341
97104
Total
# Flags
C
8
401
0
548
63
79
309
66
0
422
28
-3
0
71
54
39
74
0
0
0
2415
0
181
656
34
0
13
91
0
0
165
63
1197
0
286
2
g
141
222
24
93
593
541
52
0
0
2
308
93
83
0
0
9435
Percent of Flagged Va
Flag %
of Values
0.9%
1.8%
23.8%
0.0%
6.7%
5.6%
6.3%
27.6%
9.9%
0.0%
15.5%
3.2%
0.3%
0.0%
2.9%
3.9%
3.0%
2.9%
0.0%
0.0%
0.0%
100.0%
0.0%
22.3%
44.6%
1.2%
0.0%
1.4%
10.5%
0.0%
0.0%
11.2%
3.8%
24.8%
0.0%
4.4%
0.3%
0.2%
3.4%
20.2%
2.6%
3.6%
82.8%
67.3%
2.5%
0.0%
0.0%
8.0%
14.4%
3.1%
4.7%
0.0%
0.0%
9.7%
ues
Percent of Total Values
Data Qualifiers
1
4
25
34
656
4
19
107
849
9.0%
0.9%
2
81
16
67
59
2415
536
3174
33.6%
3.3%
3
15
9
24
0.3%
0.0%
4
205
205
2.2%
0.2%
5
5
351
356
3.8%
0.4%
6
0
0.0%
0.0%
Sampler Generated Flags
w
2
1
2
3
7
4
1
48
68
0.7%
0.1%
X
5
4
42
446
16
52
2
17
5
3
22
40
37
23
180
30
13
31
163
63
160
122
9
19
22
37
14
4
36
193
83
14
1907
20.2%
2.0%
y
2
11
10
1
28
10
2
5
2
6
1
4
11
42
2
4
2
1
13
2
10
10
179
1.9%
0.2%
t
2
97
14
37
1
19
12
13
13
g
4
53
2
1000
118
1
11
54
579
1
T
65
31
2139
22.7%
2.2%
Exceptional Events
a
8
16
24
0.3%
0.0%
e
2
1
41
38
2
28
112
1.2%
0.1%
J
155
6
161
1.7%
0.2%
I
216
216
2.3%
0.2%
P
3
3
0.0%
0.0%
q
9
1
10
0.1%
0.0%
u
6
2
8
0.1%
0.0%
-------
Summary of AIRS PM2.5 Null Value Reason Codes by State
State
ALABAMA
ALASKA
ARIZONA
ARKANSAS
CALIFORNIA
COLORADO
CONNECTICUT
DELAWARE
DISTRICT OF COLUMBIA
=LORIDA
GEORGIA
HAWAII
DAHO
LLINOIS
NDIANA
OWA
-------
Attachment 2-3
PM2.5 Collocated Precision Data Completeness
-------
1999 PM2.5 Data Completeness, Precision (as of AIRS 7/26/00)
II 1st Quarter |
SITE
# Precision* |
2nd Quarter
\ 3rd Quarter |
Percent | # Precision* | Percent | # Precision* |
ALABAMA Total* Sites =19; (*w/data=19); *where Prec. Required (25% of Tot.)=5;
010730023
010731005
010732003
010732006
010735002
010970002
011010007
10/ 6
1/ 1
13/ 7
1/ 1
1/ 1
17/12
16/10
40%
7%
47%
7%
7%
80%
67%
01 0
01 0
01 0
01 0
01 0
01 0
01 0
0% 01
0% 01
0% 01
0% 01
0% 01
0% 01
0% 01
0
0
0
0
0
0
0
4th Quarter | All 4 Q's | Number of
Percent | # Precision* | Percent | Complete |Qw/Pdata
*w/Prec.
0%
0%
0%
0%
0%
0%
0%
Data = 7; *w/4Comp.Q Prec.Data = 0
01 0 0% 1
01 0 0% 1
01 0 0% 1
01 0 0% 1
01 0 0% 1
01 0 0% 1
01 0 0% 1
99 Mean
>=13.5
1
1
1
1
1
ALASKA
ARIZONA
Total*Sites = 7; (*w/data = 7); *where Prec. Required (25% of Tot.)= 2; *w/Prec. Data = 4; *w/4Comp. QPrec.Data = 0
020200018 20/ 5 33% 01 0 0% 26/15 100% 14/ 9 60% 3
020900010 01 0 0% 01 0 0% 01 0 0% 4/ 4 27% 1
021100004 0/0 0% 9/9 60% 14/12 80% 2
021700008 8/6 40% 9/8 53% 11/10 67% 12/12 80% 4
Total*Sites =10; (*w/data =10); *where Prec. Required (25% of Tot.)=3; *w/Prec. Data = 3; *w/4Comp. Q Prec.Data = 1
040070008 8/8 53% 13/13 87% 15/15 100% 15/15 100% 4
040191028 01 0 0% 7/ 7 47% 6/ 6 40% 7/ 7 47% 3
040230004 15/15 100% 15/15 100% 15/15 100% 15/15 100% 1 4
Total*Sites =18; (*w/data =17); *where Prec. Required (25% of Tot.)=5; *w/Prec. Data = 5; *w/4Comp.Q Prec.Data = 0
CALIFORNIA
COLORADO
CONNECTICUT
DELAWARE
050010001
050310001
051190007
051191008
051310008
Total* Sites =76;
060170011
060190008
060250005
060271003
060290014
060450006
060571001
060670006
060710014
060730006
060798001
061010003
061110007
Total* Sites =16;
080010001
080410011
080770003
Total* Sites =11;
090010010
090090018
090091123
090092123
Total* Sites = 8;
100031011
100031012
100032004
DISTRICT OF COLUMBIA Total * Sites = 3;
FLORIDA
GEORGIA
110010041
110010043
Total* Sites =27;
120010023
120111002
120330004
120710005
120952002
121056006
121111002
121171002
Total* Sites =24;
130210007
130510017
130892001
131210032
132150001
132450005
01 0
(*w/ data =76); *where Prec
14/13 87% 15/15
18/13 87% 18/12
14/14 93% 12/12
14/14 93% 15/15
6/6 40% 14/14
14/14 93% 14/14
01 0 0% 01 0
8/7 47% 13/13
6/6 40% 14/14
12/12 80% 6/6
8/ 8 53% 9/ 9
15/15 100% 9/7
12/12 80% 10/9
(*w/ data =14); *wherePrec
3/2 13% 23/12
3/ 2 13% 12/ 6
14/ 7 47% 28/14
(*w/ data =11); *wherePrec
6/ 4 27% 10/ 5
51 3
3/ 2
3/ 2
(*w/data = 8);
51 3
10/ 7
(*w/data = 3);
10/ 2
12/ 3
(*w/ data =26)
01 0
13/13
11/11
4/ 4
01 0
41 4
13/13
01 0
(*w/ data =24)
9/ 5
19/10
12/ 7
7/ 5
4/ 2
8/ 5
20%
13%
13%
10/ 6
6/ 4
18/10
# where Prec.
20%
47%
15/ 8
16/ 9
* where Prec.
13%
20%
01 0
241 6
; # where Prec
0%
87%
73%
27%
0%
27%
87%
0%
01 0
11/11
10/10
01 0
14/14
8/ 8
15/15
13/13
; * where Prec
33%
67%
47%
33%
13%
33%
9/ 9
10/ 7
9/ 9
7/ 7
15/ 9
11/11
13/13 87% 10/10 67% 2
12/12 80% 9/ 9 60% 2
0% 31/13 87% 13/13 87% 2
5/4 27% 13/13 87% 2
12/12 80% 12/12 80% 2
. Required (25% ofTot.)=19; *w/ Prec. Data =13; *w/4Comp. QPrec.Data = 1
100% 15/15 100% 15/15 100% 1 4
80% 14/13 87% 12/10 67% 4
80% 12/12 80% 5/5 33% 4
100% 15/14 93% 1/1 7% 4
93% 12/12 80% 13/13 87% 4
93% 1/1 7% 0/0 0% 3
0% 1/ 1 7% 11/11 73% 2
87% 01 0 0% 10/10 67% 3
93% 12/12 80% 15/15 100% 4
40% 31 3 20% 8/ 8 53% 4
60% 10/10 67% 12/12 80% 4
47% 14/13 87% 11/10 67% 4
60% 12/12 80% 8/8 53% 4
. Required (25% of Tot.)= 4; *w/ Prec. Data = 3; *w/4Comp.Q Prec.Data = 0
80% 13/13 87% 13/13 87% 4
40% 51 4 27% 9/ 9 60% 4
93% 11/10 67% 15/15 100% 4
. Required (25% of Tot.)= 3; *w/ Prec. Data = 4; *w/4Comp.Q Prec.Data = 0
33% 19/10 67% 18/10 67% 4
40%
27%
67%
24/14
20/11
17/10
Required (25% of Tot.)= 2;
53%
60%
22/12
23/12
Required (25% ofTot.)=1;
0%
40%
. Required (25%
0%
73%
67%
0%
93%
53%
100%
87%
. Required (25%
60%
47%
60%
47%
60%
73%
01 0
41 1
ofTot.)=7;
01 0
13/13
01 0
01 0
01 0
91 9
11/11
11/11
ofTot.)=6;
12/12
11/ 9
11/10
12/12
11/11
10/10
93%
73%
67%
*w/ Prec.
80%
80%
*w/ Prec.
0%
7%
*w/Prec
0%
87%
0%
0%
0%
60%
73%
73%
*w/Prec
80%
60%
67%
80%
73%
67%
26/14
22/12
18/10
Data = 3;
13/ 7
6/ 3
19/10
Data = 2;
01 0
01 0
. Data = 8
14/14
15/15
01 0
12/12
15/15
14/13
14/14
12/12
. Data = 6
01 0
01 0
01 0
01 0
01 0
01 0
93% 4
80% 4
67% 4
#w/4 Comp. Q Prec. Data = 0
47% 4
20% 1
67% 4
*w/4 Comp. Q Prec. Data = 0
0% 1
0% 3
; *w/4Comp.QPrec.Data = 2
93% 1
100% 1 4
0% 2
80% 2
100% 2
87% 4
93% 1 4
80% 3
; *w/4Comp.QPrec.Data = 0
0% 3
0% 3
0% 3
0% 3
0% 3
0% 3
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
HAWAII
IDAHO
Total*Sites = 5; (*w/data = 5); *where Prec. Required (25% of Tot.)= 1; *w/Prec. Data = 2; *w/4Comp. QPrec.Data = 0
150031001 13/13 87% 15/15 100% 13/13 87% 4/4 27% 4
150032004 13/13 87% 13/13 87% 13/12 80% 7/7 47% 4
Total*Sites =14; (*w/data =13); *where Prec. Required (25% of Tot.)=4; *w/Prec. Data = 7; *w/4Comp.Q Prec.Data = 0
ILLINOIS
INDIANA
160010011 13/13 87% 15/15 100% 3/ 3
160050015 13/12 80% 13/11 73% 21 2
160170001 15/15 100% 16/15 100% 2/2
160270004 0/0 0% 0/0 0% 9/ 9
160550006 10/ 8
160690009
160830010
Total* Sites =25; (*w/ data =25); *where Prec. Required (25% ofTot.)=6;
Total* Sites =28; (*w/ data =26); *where Prec. Required (25% ofTot.)=7;
180431004
180891016
180950009
180970081
180970083
181411008
8/ 8
4/ 4
21 2
61 6
9/ 9
53%
27%
13%
40%
60%
41 4
41 4
51 5
14/14
13/13
21 2
27%
27%
33%
93%
87%
13%
01 0
01 0
01 0
01 0
01 0
01 0
20%
13%
13%
60%
53%
*w/Prec.
*w/Prec.
0%
0%
0%
0%
0%
0%
01 0 0%
01 0 0%
01 0 0%
15/15 100%
12/12 80%
11/11 73%
3/ 3 20%
Data = 0; #w/4Comp.
Data = 7; *w/4Comp.
01 0 0%
01 0 0%
01 0 0%
01 0 0%
01 0 0%
01 0 0%
3
3
3
2
2
1
1
Q Prec. Data = 0
Q Prec. Data = 0
2
2
2
2
2
1
1
1
1
1
1
* Total number of precision records reported / Number reported on any 6-day schedule
statepaug.123
-------
1999 PM2.5 Data Completeness, Precision (as of AIRS 7/26/00)
1 st Quarter
2nd Quarter
3rd Quarter
4th Quarter
STATE
SITE
| # Precision* | Percent | # Precision* | Percent | # Precision* | Percent | # Precision* | Percent
AlUQ's
Complete
Number of I
Qw/Pdata
'99 Mean
>=13.5
181630006 31 3 20% 0/0 0% 0/0 0% 1
IOWA Total*Sites =15; (*w/data =15); *where Prec. Required (25% of Tot.)=4; *w/Prec. Data = 4; *w/4Comp.Q Prec.Data = 0
191130037 11/6 40% 28/14 93% 29/16 100% 28/14 93% 4
191532520 7/5 33% 24/14 93% 30/15 100% 25/13 87% 4
191550009 19/10 67% 24/13 87% 2
191630015 18/10 67% 30/15 100% 31/16 100% 30/15 100% 4
KANSAS Total*Sites =13; (*w/data=13); *where Prec. Required (25% of Tot.)=3; *w/Prec. Data = 4; *w/4Comp.Q Prec.Data = 0
KENTUCKY
LOUISIANA
MAINE
MARYLAND
MASSACHUSETTS
MICHIGAN
MINNESOTA
MISSISSIPPI
200910007
201070002
201730010
202090021
Total* Sites =21;
210190017
210590014
210670012
211110043
211950002
212270007
Total* Sites =18;
220171002
220330009
220550005
220710012
Total* Sites =13;
230050027
230110016
230190002
Total* Sites =18;
245100035
Total* Sites =18;
2501 3001 6
250210007
250230004
250250027
250270020
Total* Sites =22;
260650012
260770008
260810020
261210040
261450018
261630001
Total* Sites =21;
271230866
271230868
271377550
Total* Sites =16;
280330002
6/6 40% 11/11
6/ 6 40% 8/ 8
10/10 67% 12/12
11/10
(*w/ data =21); *wherePrec.
10/10 67%
8/ 8 53%
9/ 8 53%
12/8 53%
8/ 8 53%
10/10 67%
8/ 7
10/ 7
14/14
16/15
13/13
13/13
(*w/ data =18); *wherePrec.
13/13 87%
14/14 93%
13/13 87%
12/12 80%
15/15
15/14
14/14
10/10
(*w/ data =12); *wherePrec.
51 5 33%
71 7 47%
01 0 0%
4/ 4
13/13
01 0
(*w/ data =16); *wherePrec.
(*w/ data =18); *wherePrec.
20/11 73%
21 1 7%
19/ 9 60%
11 / 6 40%
24/14 93%
29/15
01 0
23/12
15/ 8
27/14
(*w/ data =22); *wherePrec.
23 / 6 40%
14/ 7 47%
24/11 73%
17/8 53%
8/ 5 33%
17/ 9
21/11
10/10
10/10
16/ 8
61 6
(*w/ data =21); *wherePrec.
01 0 0%
01 0
01 0
51 5
(*w/ data =16); *wherePrec.
51 5 33%
13/13
73%
53%
80%
67%
Required (25%
47%
47%
93%
100%
87%
87%
Required (25%
100%
93%
93%
67%
Required (25%
27%
87%
0%
Required (25%
Required (25%
100%
0%
80%
53%
93%
Required (25%
60%
73%
67%
67%
53%
40%
Required (25%
0%
0%
33%
Required (25%
87%
14/12
12/12
51 5
15/15
ofTot.)=5;
13/13
11/11
15/15
14/ 9
14/14
13/13
ofTot.)=5;
15/15
15/15
15/15
9/ 9
ofTot.)=3;
12/12
14/14
01 0
ofTot.)=5;
ofTot.)=5;
27/14
10/ 5
28/14
26/14
27/14
ofTot.)=6;
26/14
20/11
13/13
71 7
20/10
11/11
ofTot.)=5;
13/13
10/10
11/11
ofTot.)=4;
15/15
80%
80%
33%
100%
*w/Prec.
87%
73%
100%
60%
93%
87%
*w/Prec.
100%
100%
100%
60%
*w/Prec.
80%
93%
0%
*w/Prec.
*w/Prec.
93%
33%
93%
93%
93%
*w/Prec.
93%
73%
87%
47%
67%
73%
*w/Prec.
87%
67%
73%
*w/Prec.
100%
14/14
13/13
13/13
14/14
Data = 6;
13/13
12/11
12/12
01 0
9/ 9
15/15
Data = 4;
15/15
14/14
14/14
11/11
Data = 3;
11/11
9/ 9
51 5
Data = 1;
31 2
Data = 5;
22/11
26/14
13/ 8
11/ 6
23/12
Data = 6;
29/15
28/15
13/13
11/11
11/ 6
10/ 9
Data = 3;
11/11
13/13
11/11
Data = 3;
01 0
93%
87%
87%
93%
#w/4 Comp.
87%
73%
80%
0%
60%
100%
#w/4 Comp.
100%
93%
93%
73%
*w/4Comp.
73%
60%
33%
#w/4 Comp.
13%
*w/4Comp.
73%
93%
53%
40%
80%
*w/4Comp.
100%
100%
87%
73%
40%
60%
*w/4Comp.
73%
87%
73%
#w/4 Comp.
0%
Q Prec.Data
Q Prec.Data
1
1
1
Q Prec.Data
Q Prec.Data
Q Prec.Data
1
1
Q Prec.Data
Q Prec.Data
Q Prec.Data
4
4
4
3
= 0
4
4
4
3
4
4
= 3
4
4
4
4
= 0
4
4
1
= 0
1
= 2
4
3
4
4
4
= 0
4
4
4
4
4
3
= 0
2
2
3
= 0
3
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
MISSOURI
MONTANA
NEVADA
NEW HAMPSHIRE
NEW JERSEY
NEW MEXICO
NEW YORK
290210010
290470026
290770032
291831002
291892003
295100085
9/ 8
9/ 9
15/15
7/ 7
01 0
53%
60%
100%
47%
0%
23/12
11/11
15/15
25/13
12/12
01 0
80%
73%
100%
87%
80%
0%
14/ 7
13/13
14/14
29/15
01 0
70/15
47%
87%
93%
100%
0%
100%
28/14
15/15
15/15
29/15
01 0
87/15
93%
100%
100%
100%
0%
100%
NORTH CAROLINA
280350004 4/4 27% 12/12 80% 11/11 73% 0/0 0% 3 1
281210001 5/5 33% 11/10 67% 10/10 67% 0/0 0% 3 1
Total*Sites =20; (*w/data =19); *where Prec. Required (25% of Tot.)=5; *w/Prec. Data = 6; *w/4Comp.Q Prec.Data = 1
4
4
4
4 1
1 1
2 1
Total* Sites = 9; (*w/data = 9); *where Prec. Required (25% of Tot.)= 2; *w/Prec. Data = 2; *w/4 Comp. Q Prec.Data = 0
300530018 0/0 0% 0/0 0% 0/0 0% 11/11 73% 1 1
300630024 9/8 53% 15/15 100% 11/11 73% 12/12 80% 4
Total*Sites =13; (*w/data =13); *where Prec. Required (25% of Tot.)=3; *w/Prec. Data = 4; *w/4Comp.Q Prec.Data = 1
310550019 01 0 0% 01 0 0% 51 5 33% 31 3 20% 2
310550052 0/0 0% 4/4 27% 11/11 73% 2
311090022 12/12 80% 12/12 80% 12/12 80% 11/11 73% 1 4
311530007 3/2 13% 9/9 60% 13/13 87% 12/12 80% 4
Total* Sites = 7; (*w/data = 7); *where Prec. Required (25% of Tot.)= 2; * w/Prec. Data = 1; *w/4 Comp. Q Prec.Data = 1
320310016 15/15 100% 15/15 100% 17/15 100% 16/15 100% 1 4
Total* Sites = 9; (*w/data = .); *where Prec. Required (25% of Tot.)=2; * w/Prec. Data = 0; *w/4Comp.Q Prec.Data = 0
Total*Sites =19; (*w/data =19); *where Prec. Required (25% of Tot.)=5; *w/Prec. Data = 2; *w/4Comp.Q Prec.Data = 0
340070003 5/5 33% 15/15 100% 12/12 80% 10/10 67% 4
340390004 6/6 40% 5/5 33% 15/15 100% 15/15 100% 4 1
Total*Sites =13; (*w/data =10); *where Prec. Required (25% of Tot.)=3; *w/Prec. Data = 3; *w/4Comp.Q Prec.Data = 1
350010023 0/0 0% 0/0 0% 13/4 27% 56/10 67% 2
350450006 16/8 53% 28/12 80% 19/8 53% 31/13 87% 4
350490020 22/11 73% 24/11 73% 29/13 87% 33/14 93% 1 4
Total*Sites =42; (*w/data =33); *where Prec. Required (25% of Tot.)=11; *w/Prec. Data =10; *w/4Comp. QPrec.Data = 0
360010005
360050073
360050110
360470011
360556001
360610056 31/16 100% 30/15 100% 2 1
360610062 17/9 60% 30/15 100% 2 1
360632008 31/16 100% 30/15 100% 2 1
360671015
360810094
Total*Sites =35; (*w/data =35); *where Prec. Required (25% of Tot.);
370210034 12/12 80% 13/13 8
31/16
51 3
61 3
SI 4
11/ 6
31/16
17/ 9
31/16
31/16
12/ 6
of Tot.)= 9;
14/14
100%
20%
20%
27%
40%
100%
60%
100%
100%
40%
*w/Prec.
93%
30/15
01 0
30/15
01 0
30/15
30/15
30/15
30/15
30/15
30/15
Data =11;
12/12
100%
0%
100%
0%
100%
100%
100%
100%
100%
100%
#w/4Comp.
80%
2
1
2
1
2
2
2
2
2
2
Q Prec.Data = 1
1 4
* Total number of precision records reported / Number reported on any 6-day schedule
statepaug.123
-------
1999 PM2.5 Data Completeness, Precision (as of AIRS 7/26/00)
STATE
NORTH DAKOTA
OHIO
OKLAHOMA
OREGON
PENNSYLVANIA
I I
1 st Quarter
| 2nd Quarter |
3rd Quarter |
| SITE | # Precision* | Percent | # Precision* | Percent | # Precision* |
370510009
370670024
370710016
370810009
371190034
371190040
371210001
371290009
371470005
371830014
Total* Sites = 7;
380171004
380570004
Total* Sites =37
390170003
390610014
390610041
390811001
391530017
Total* Sites =24
400219002
400310648
400470554
401090035
401430110
Total* Sites =27
410290133
410330107
410370001
410390060
410510080
410650007
410671003
Total* Sites =37
420030008
420030064
420031 301
420450002
420692006
420710007
421010004
421250005
421330008
01 0
14/13
01 0
01 0
13/13
01 0
01 0
01 0
01 0
01 0
(*w/data = 7);
12/ 7
15/12
(*w/ data =37)
14/14
8/ 8
21 2
01 0
13/13
(*w/ data =19)
(*w/ data =27)
01 0
01 0
01 0
01 0
(*w/ data =35)
01 0
71 3
01 0
61 6
61 6
51 5
51 3
9/ 9
51 5
0% 01 0
87% 15/14
0% 01 0
0% 01 0
87% 14/13
0% 01 0
0% 01 0
0% 01 0
0% 01 0
0% 01 0
# where Prec.
47% 18/10
80% 11/11
; * where Prec
93% 15/15
53% 15/14
13% 15/15
0% 01 0
87% 15/15
; # where Prec
01 0
01 0
01 0
01 0
; # where Prec
0% 21/13
0% 01 0
0% 26/13
0% 27/14
; # where Prec
0% 01 0
20% 11 / 3
0% 31 3
40% 12/12
40% 71 7
33% 10/10
20% 51 5
60% 8/ 8
33% 11/11
0%
93%
0%
0%
87%
0%
0%
0%
0%
0%
10/10
10/10
14/14
01 0
41 4
8/ 8
12/12
11/11
13/12
8/ 8
Required (25% of Tot.)= 2;
67%
73%
. Required (25%
100%
93%
100%
0%
100%
. Required (25%
0%
0%
0%
0%
. Required (25%
87%
0%
87%
93%
. Required (25%
0%
20%
20%
80%
47%
67%
33%
53%
73%
25/13
13/13
of Tot )= 9
15/15
15/14
15/15
11/11
15/15
ofTot.)=6
51 5
51 5
10/10
51 5
51 5
ofTot.)=7
13/13
01 0
01 0
24/12
14/14
1/ 1
ofTot.)=9
1/ 1
14/ 3
4/ 4
13/13
10/10
61 6
9/ 9
01 0
51 5
Percent |
67%
67%
93%
0%
27%
53%
80%
73%
80%
53%
#w/ Prec.
87%
87%
#w/Prec
100%
93%
100%
73%
100%
#w/Prec
33%
33%
67%
33%
33%
#w/Prec
87%
0%
0%
80%
93%
7%
#w/Prec
7%
20%
27%
87%
67%
40%
60%
0%
33%
4th Quarter I
# Precision* | Percent |
13/13
14/ 8
13/13
31 3
01 0
10/10
12/12
13/13
71 7
13/13
Data = 2;
30/15
14/14
. Data = 5
9/ 9
11/11
14/14
51 5
61 6
. Data = 5
71 7
01 0
01 0
01 0
01 0
. Data = 7
15/15
13/13
15/15
28/15
13/12
21 2
14/14
. Data = 9
10/ 2
10/ 2
13/10
13/13
12/12
12/12
13/12
61 6
13/13
87%
53%
87%
20%
0%
67%
80%
87%
47%
87%
#w/4Comp.
100%
93%
#w/4Comp
60%
73%
93%
33%
40%
#w/4 Comp
47%
0%
0%
0%
0%
#w/4 Comp
100%
87%
100%
100%
80%
13%
93%
#w/4 Comp
13%
13%
67%
87%
80%
80%
80%
40%
87%
All 4 Q's I Number of
Complete |ow/Pdata
2
4
2
1
3
2
2
2
2
2
Q Prec. Data = 1
4
1 4
. Q Prec. Data = 0
4
4
4
2
4
. Q Prec. Data = 0
2
1
1
1
1
. Q Prec. Data = 0
3
1
1
3
3
1
2
. Q Prec. Data = 0
2
4
3
4
4
4
4
3
4
'99 Mean
>=13.5
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
PUERTO RICO
RHODE ISLAND
SOUTH CAROLINA
SOUTH DAKOTA
TENNESSEE
UTAH
VERMONT
VIRGIN ISLANDS
VIRGINIA
WASHINGTON
WEST VIRGINIA
WISCONSIN
Total*Sites = 9; (#w/data = 9); #where Prec. Required (25% of Tot.)= 2; #w/Prec. Data = 0; #w/4Comp. QPrec.Data = 0
Total*Sites = 7; (#w/data = 7); #where Prec. Required (25% of Tot.)= 2; #w/Prec. Data = 2; #w/4Comp. QPrec.Data = 2
440070022 15/15 100% 15/15 100% 15/15 100% 15/15 100% 1 4
440071010 15/15 100% 15/15 100% 15/14 93% 15/15 100% 1 4
Total*Sites =17; (#w/data =17); #where Prec. Required (25% of Tot.)=4; #w/Prec. Data = 4; #w/4Comp.Q Prec.Data = 1
450190048 10/10 67% 13/13 87% 14/14 93% 3
450430009 21/11 73% 24/13 87% 21/11 73% 26/13 87% 1 4
450450009 2/2 13% 8/8 53% 13/13 87% 3
450790019 0/0 0% 18/9 60% 30/16 100% 21/11 73% 3
Total*Sites = 8; (#w/data = 8); #where Prec. Required (25% of Tot.)= 2; #w/Prec. Data = 2; #w/4Comp. QPrec.Data = 0
460990006 0/0 0% 12/11 73% 14/14 93% 2
461031001 01 0 0% 23/10 67% 14/ 7 47% 2
Total*Sites =21; (#w/data =12); #where Prec. Required (25% of Tot.)=5; #w/Prec. Data = 3; #w/4Comp.Q Prec.Data = 2
470931017 14/14 93% 15/15 100% 15/15 100% 14/14 93% 1 4
471130004 0/0 0% 0/0 0% 12/6 40% 29/15 100% 2
471650007 28/14 93% 30/15 100% 31/16 100% 30/15 100% 1 4
Total*Sites =47; (#w/data =40); #where Prec. Required (25% of Tot.)=12; #w/Prec. Data =10; #w/4Comp. QPrec.Data = 0
2
1
3
1
3
1
2
1
3
3
?c.Data = 0
3
Total*Sites = 5; (#w/data = 5); #where Prec. Required (25% of Tot.)= 1; #w/Prec. Data = 0; #w/4Comp. QPrec.Data = 0
Total*Sites = 1; (#w/data = 1); #where Prec. Required (25% of Tot.)= 1; #w/Prec. Data = 0; #w/4Comp. QPrec.Data = 0
Total*Sites =20; (#w/data =20); #where Prec. Required (25% of Tot.)=5; #w/Prec. Data = 3; #w/4Comp.Q Prec.Data = 0
510130020 15/7 47% 26/13 87% 30/16 100% 16/8 53% 4
517100024 16/8 53% 23/12 80% 30/16 100% 11/7 47% 4
517600020 19/9 60% 28/14 93% 28/14 93% 16/8 53% 4
Total*Sites =23; (#w/data =23); #where Prec. Required (25% of Tot.)=6; #w/Prec. Data = 5; #w/4Comp. Q Prec.Data = 1
480290034
481130050
481130069
481410010
481410044
481671005
482011035
484391002
484393006
484530020
Total* Sites =11;
490494001
1/ 1
01 0
1/ 1
61 6
01 0
31 3
21 2
(#w/ data =11)
01 0
7%
0%
7%
40%
0%
20%
13%
31 3
01 0
31 3
8/ 8
1/ 1
01 0
4/ 4
31 3
; # where Prec.
0%
14/14
20%
0%
20%
53%
7%
0%
27%
20%
Required (25%
93%
01 0
01 0
01 0
01 0
01 0
01 0
01 0
01 0
ofTot.)=3;
12/11
0%
0%
0%
0%
0%
0%
0%
0%
#w/Prec.
73%
01 0
31 3
12/12
4/ 4
10/10
1/ 1
71 7
31 3
13/13
8/ 8
Data = 1; #v
13/13
0%
20%
80%
27%
67%
7%
47%
20%
87%
53%
ป/4Com[
87%
530330057
530530031
530630016
530730015
530770012
12/12
13/13
61 5
61 6
10/ 9
40%
14/14
13/12
10/ 9
12/12
10/10
93%
11/11
13/13
8/ 7
51 5
9/ 9
73%
87%
47%
33%
13/11
11/10
8/ 4
8/ 8
01 0
1
Total*Sites =14; (#w/data =14); #where Prec. Required (25% of Tot.)=4; #w/Prec. Data = 2; #w/4Comp.Q Prec.Data = 2
540290011 25/13 87% 26/13 87% 26/14 93% 29/15 100% 1 4
540391005 29/15 100% 21/11 73% 28/14 93% 23/12 80% 1 4
Total*Sites =28; (#w/data =28); #where Prec. Required (25% of Tot.)= 7; #w/Prec. Data = 7; #w/4Comp. Q Prec.Data = 1
* Total number of precision records reported / Number reported on any 6-day schedule
statepaug.123
-------
1999 PM2.5 Data Completeness, Precision (as of AIRS 7/26/00)
STATE
ISITE
550090005
550250025
550310025
550790026
550790059
551091002
551330027
(1st Quarter
# Precision* | Percent
18/10 67%
28/14 93%
26/13 87%
12/10 67%
51 4 27%
01 0 0%
9/ 8 53%
2nd Quarter
# Precision* |
21/11
26/13
28/14
14/11
01 0
01 0
15/15
Percent
73%
87%
93%
73%
0%
0%
100%
I 3rd Quarter |
# Precision* |
28/14
23/11
30/15
15/15
10/10
4/ 4
12/12
Percent |
93%
73%
100%
100%
67%
27%
80%
4th Quarter I
# Precision* | Percent |
22/11 73%
19/10 67%
22/12 80%
13/11 73%
11/11 73%
11/11 73%
15/14 93%
All 4 Q's
Complete
1
I Number of
Qw/Pdata
4
4
4
4
3
2
4
'99 Mean
>=13.5
1
1
1
WYOMING
US TOTAL
Total*Sites = 3; (#w/data = 3); #where Prec. Required (25% of Tot.)= 1; #w/Prec. Data = 1; #w/4Comp. QPrec.Data = 1
560330002 14/14 93% 14/14 93% 15/15 100% 13/13 87% 1 4
Total # Sites =979; (# w/ data = 924|; # where Precision Required (25% of Tot.|= 245; # w/ Precision Data = 220; # w/ 4 Complete Q Prec. Data = 25
* Total number of precision records reported / Number reported on any 6-day schedule
statepaug.123
-------
Attachment 2-4
PM2.5 Flow Rate Audit Data Completeness
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
STATE SI
rE 01 |
ALABAMA Total* Sites =19; (#w/ data =19); #whereAcc
010270001 0
010331002 0
010491003 0
010690002 0
010730023 1
010731005 1
010732003 1
010732006 1
010735002 1
010970002 0
010972005 0
011010007 0
011030010 0
011130001 0
011170006 0
011190002 0
011210002 0
011250003 0
011270002 0
ALASKA Total # Sites = 7; (#w/data = 7); # where Ace.
020200018 1
020200044
020900010 1
021100004 1
# of Accuracy Records
Q2 | Q3
Reqrd(AII)=19; # w/ Accuracy Data
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Reqrd (All)= 7; # w/ Accuracy Data =
1
0
1
1
021100026
021300008
021700008 1
ARIZONA Total* Sites =10; (#w/ data =10); #whereAcc
040031005 0
040051008 0
040070008 0
040139990 0
040139991 0
040139992 0
040139997 0
040190011 0
040191028 0
040230004 0
ARKANSAS Total* Sites =18; (#w/ data =17); # where Ace
1
Reqrd (All)=10; # w/ Accuracy Data
0
0
0
0
0
0
0
0
0
0
Reqrd(AII)=18; # w/ Accuracy Data
050010001
050030003
050310001
050350004
050510002
050690005
050890001
050910001
050910004
051070001
051130002
051150003
051190003
051190007
0
051191008
051310008
051390004
051430003
CALIFORNIA Total # Sites =76; (#w/ data =76); # where Ace
Reqrd (All)=76; # w/ Accuracy Data
060010007
060011001 0
060070002 0
060090001 0
060111002 0
060130002 0
0
0
0
0
0
# Q's w/ Accuracy in
| Q4 Accuracy All 4 Q
= 5; # w/ 4 Q Acc.= 0
000
000
000
000
0 0 1
0 0 1
0 0 1
0 0 1
0 0 1
000
000
000
000
000
000
000
000
000
000
6; #W4QAcc.= 2
1 0 3
1 1 2
1 1 41
1 1 41
0 0
1 1
0 1 3
= 1; #w/4QAcc.= 0
000
000
000
000
000
000
000
000
0 1 1
000
= 0; # w/ 4 Q Acc.= 0
000
000
000
000
000
000
000
0
000
000
000
000
000
000
000
000
000
000
=30; #w/4QAcc.= 0
0 0
1 0 1
1 0 1
1 0 1
000
1 0 1
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
# of Accuracy Records
STATE SITE Q1 | Q2 | Q3
060170011 0 0
060190008 0 0
060195001 0 0
060231002 0 0
060250003 0 0
060250005 1 0
060251003 0 0
060271003 0 0
060290010 0 0
060290011 0 0
060290012 0
060290014 1 0
060310004 0 0
060333001 0 0
060370002 0 1
060371002 0 0
060371103 0 0
060371201 0 0
060371301 0 0
060371601 0 0
060372005 0 0
060374002 0 0
060379002 0 0
060450006 0 0
060472510 0
060490001 0 0
060531002 1 0
060570005 0 0
060571001 0 0
060590001 0 0
060592022 0
060610006 0 0
060631006 0 0
060631008 0 0
060651003 0 0
060652002 0 0
060658001 0 0
060670006 0 0
060670010 0 0
060674001 0 0
060710014 1 0
060710025 0 0
060712002 0 0
060718001 0 0
060719004 0 0
060730001 0 0
060730003 1 0
060730006 1 0
060731002 1 0
060731007 1 0
060750005 0 0
060771002 0 0
060792002 0 0
060798001 0 0
060811001 0 0
060830010 0 0
060831007
060850004 0 0
060852003 0 0
060870007 1 0
060890004 0 0
060950004 0 0
060970003 0 0
060990005 0 0
061010003 0 0
# Q's w/ Accuracy in
| Q4 Accuracy All 4 Q
1 0 1
000
000
000
000
0 0 1
000
0 1 1
000
000
0 1 1
0 0 1
000
0 1 1
1 0 2
000
000
000
000
000
000
000
000
000
000
000
0 0 1
1 0 1
1 0 1
000
000
000
1 0 1
000
000
000
000
1 0 1
000
000
0 0 1
000
000
000
000
000
0 1 2
1 0 2
0 0 1
0 0 1
1 0 1
000
000
000
1 0 1
000
0 0
1 0 1
1 0 1
0 0 1
000
1 0 1
1 0 1
000
1 0 1
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
STATE SI
rE 01 |
061072002 0
061110007 0
061112002 0
061113001 0
061131003 1
COLORADO Total* Sites =16; (#w/ data =14); #whereAcc
080010001 1
080050005 1
080130003 1
080130012 1
080310002 1
# of Accuracy Records
Q2 | Q3
0
0
0
0
0
#Q
| Q4 Acci
0 0
0 0
0 0
0 0
0 0
s w/ Accuracy in
racy All 4 Q
0
0
0
0
1
Reqrd(AII)=16; #w/ Accuracy Data =14; #w/4QAcc.= 9
1
1
1
1
1
1 1
1 1
1 1
1 1
0 0
080310013
080310017
080390001
080410008 1
080410011 1
0
1
1
080690009
080770003 1
081010012 1
081070003
081230006 1
1
1
0
1
081230008
CONNECTICUT Total* Sites =11; (#w/ data =11); #whereAcc
090010010 0
090011123 0
090012124 0
090019003 0
090031003 0
090031018 0
090090018 0
090091123 0
090092123 0
090099005 0
090113002 0
DELAWARE Total # Sites = 8; (#w/data = 8); # where Ace.
100010002 1
100010003 1
100031003 1
100031007 1
100031011 0
Reqrd(AII)=11; # w/ Accuracy Data
0
0
0
0
0
0
0
0
0
0
0
Reqrd (All)= 8; # w/ Accuracy Data =
1
1
1
1
1
100031012
100032004 0
100051002 1
DISTRICT OF COLUMBI Total* Sites = 3; (#w/data = 3); #whereAcc.
110010041 0
110010042 0
110010043 0
FLORIDA Total # Sites =27; (# w/ data =26); #whereAcc
120010023 1
120111002 1
120112004
120113002
1
1
Reqrd (All)= 3; # w/ Accuracy Data =
0
0
0
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
= 0; # w/ 4 Q Acc.= 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
7; #W4QAcc.= 4
1 1
0 1
1 1
1 1
1 1
0
1 1
1 1
0; #W4QAcc.= 0
0 0
0 0
0 0
4 1
4 1
4 1
4 1
2
0
0
2
4 1
4 1
2
4 1
4 1
2
4 1
2
0
0
0
0
0
0
0
0
0
0
0
4 1
3
4 1
4 1
3
0
3
4 1
0
0
0
Reqrd (All)=27; #w/ Accuracy Data =25; # w/4 Q Acc.=13
1
1
1
1
1 1
1 1
1 1
1 1
120170005
120251016 0
120256001 0
120310098
120310099
120330004 1
120570030 1
120571075 1
120710005 1
120730012 0
120814012 1
120830003 1
120951004 1
2
1
0
0
1
1
1
1
0
1
1
1
1 1
1 1
1 0
1 0
1 1
1 1
1 1
1 1
0 0
1 0
1 0
1 0
4 1
4 1
3
3
0
3
3
1
1
4 1
4 1
4 1
4 1
0
3
3
3
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
STATE SI
# of Accuracy Records # Q'
TE Q1 | Q2 | Q3
120952002 1 1
120990009
120991004
120992003 1 1
121030018 1 1
121031008 1 1
121056006 1 1
121111002 1 1
121150013 1 1
121171002 1 1
121275002 1 1
| Q4 Acci
1 0
0
1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 0
s w/ Accuracy in
racy All 4 Q
3
0
1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
3
GEORGIA Total # Sites =24; (#w/ data =24); # where Ace. Reqrd (All)=24; # w/ Accuracy Data =22; #w/4QAcc.= 0
130210007 0 1
130210012 0 1
130510017 0 0
130510091 0 1
130590001 0 1
130630091 1 1
130670003 0 1
130890002 0 0
130892001 1 1
130950007 0 1
131150005 1 1
131210032 0 1
131210039 0 1
131211001 0 1
131270004 0 0
131270006
131390003 0 1
132150001 1 1
132150011 1 1
132230003 0 1
132450005 0 1
132450091 1 1
133030001 0 1
133190001 0
HAWAII Total # Sites = 5; (# w/ data = 5); # where Ace. Reqrd (All)= 5; # w/ Accuracy Data =
150030010 0 3
150031001 0 1
150031004
150032004 0 4
150090006 0 0
0 1
0 1
0 1
0 1
0 0
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 0
0 0
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 1
5; #w/4QAcc.= 0
4 0
3 3
3
3 1
1 3
2
2
1
2
1
3
2
1
3
2
3
2
2
2
0
0
2
3
3
2
2
3
2
1
2
3
1
3
2
IDAHO Total # Sites =14; (#w/ data =13); # where Ace. Reqrd (All)=14; #w/ Accuracy Data =12; #w/4QAcc.= 6
160010011 3 3
160010017 2 1
160050006 1 1
160050015 6 0
160170001 3 3
160190010
1 0
2 1
1 1
1 1
1 1
0 1
160210001
160270004 2 2
160270005 1 1
160550006
160690009
160790017
160830006 1 1
160830010
ILLINOIS Total # Sites =25; (# w/ data =25); # where Ace. Reqrd (All)=25; # w/ Accuracy Data
170191001 0 0
170310014 0 0
170310022 0 0
170310050 0 0
170310052 0 0
170311016 0 0
170311701 0 0
3 1
2 1
2 1
1
1 1
1 1
0
= 0; # w/ 4 Q Acc.= 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
3
4 1
4 1
3
4 1
1
0
4 1
4 1
2
1
2
4 1
0
0
0
0
0
0
0
0
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
STATE SI
# of Accuracy Records
rE Q1 | Q2 | Q3
170312001 0 0
170313301 0 0
170314006 0 0
170314201 0 0
170434002 0 0
171150013 0 0
171170002 0 0
171190023 0 0
171191007 0 0
171193007 0 0
171430037 0 0
171570001 0 0
171610003 0 0
171630010 0 0
171670012 0 0
171971002 0 0
171971011 0 0
172010010 0 0
INDIANA Total # Sites =28; (# w/ data =26); # where Ace. Reqrd (All)=28; # w/ Accuracy Data
180030004 0 0
180190005 0 0
180390003 0
180431004 0 0
180670003 0
180890006 0 0
180890022 0 0
180891003 0 0
180891016 0 0
180892004 0 0
180892010 0 0
180950009 0 0
#Q
| Q4 Acci
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
= 0; #w/4QAcc.= 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
180970042
180970043 0 0
180970066 0 0
180970078 0 0
0 0
0 0
0 0
180970079
180970081 0 0
180970083 0 0
181270020 0 0
181270024 0 0
181411008 0
181412004 0
181570007 0
181630006 0
181630012 0
181630016 0
181670018 0 0
IOWA Total* Sites =15; (#w/ data =15); # where Ace. Reqrd (All)=1 5; # w/ Accuracy Data
190130008 1 1
190330019
190450021 0 2
191032001 0 1
191130036 1 1
191130037 1 1
191390016 0 1
191530059
191532510 1 1
191532520 1 1
191550009
191630015 0 1
191630018
191692530 1 1
191930017 0 2
KANSAS Total* Sites =13; (#w/ data =13); # where Ace. Reqrd (All)=1 3; # w/ Accuracy Data
200910007 0 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
=15; #w/4QAcc.= 6
1 2
1 1
2 1
1 1
1 1
1 1
1 1
1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
=13; #w/4QAcc.= 0
1 1
s w/ Accuracy in
racy All 4 Q
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4 1
2
3
3
4 1
4 1
3
1
4 1
4 1
2
3
2
4 1
3
3
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
STATE SI
# of Accuracy Records
rE Q1 | Q2 | Q3
200910008 0 1
200910009 0 1
201070002 0 1
201730008 0 0
201730009 0 0
201730010 0 0
201770010 0 1
201770011 0 1
201770012 1
201910002
202090021 1
202090022 1
KENTUCKY Total # Sites =21 ; (#w/ data =21); # where Ace. Reqrd (All|=21 ; # w/ Accuracy Data
210130002
210190017 0 1
210290006 0 1
210370003 1 1
210430500 0 0
210470006 0 1
210590014 0 1
210670012 0 1
210670014 0 1
210730006 0 1
210930005 0 1
211010006 0 1
211110043 1 1
211110044 1 1
211110048 1 1
211110051 1 1
211170007 1 0
211451004 0 1
211510003 0 1
211950002 0 1
212270007 0 1
#Q
| Q4 Acci
1 1
1 1
1 2
1 1
1 1
1 1
1 1
1 1
1 1
1
1 2
1 1
=20; #w/4QAcc.= 0
0 0
1 1
0 0
1 0
1 0
1 0
1 0
1 1
1 1
1 0
0 0
1 0
1 0
1 0
1 0
1 0
1 0
1 1
0 0
0 0
1 1
s w/ Accuracy in
racy All 4 Q
3
3
3
2
2
2
3
3
3
1
3
3
0
3
1
3
1
2
2
3
3
2
1
2
3
3
3
3
2
3
1
1
3
LOUISIANA Total* Sites =18; (#w/ data =18); # where Ace. Reqrd (All)=1 8; #w/ Accuracy Data =18; #w/4QAcc.= 5
220171002 0 1
220190009 0 1
220190010 1 1
220290002 0 1
220330002 0 1
220330009 1 1
220331001 0 1
220470005 0 1
220470009 0 1
220511001 1 0
220512001 0 1
220550005 0 1
220710010 1 1
220710012 0 1
220730004 0 1
220790001 0 1
221050001 1 1
221210001 1 1
MAINE Total* Sites =13; (#w/ data =12); # where Ace. Reqrd (All)=1 3; # w/ Accuracy Data
230010011 0 0
230030013 0 0
230031011 0 0
230050015 0 0
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 2
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
2 1
= 6; # w/ 4 Q Acc.= 0
0 0
0 0
0 0
0 1
230050026
230050027 0 0
230052003 0 0
230090103 0 0
230110016 0 0
230172011 0 0
230190002 0 0
0 1
0 1
0 1
0 0
0 0
0 2
3
3
4 1
3
3
4 1
3
3
3
3
3
3
4 1
3
3
3
4 1
4 1
0
0
0
1
0
1
1
1
0
0
1
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
STATE SI
# of Accuracy Records # Q
rE 01 |
230194003 0
230310008 0
MARYLAND Total* Sites =18; (#w/ data =16); #whereAcc
240030014
240030019
Q2 | Q3 | Q4 Acci
0 0 1
000
Reqrd(AII)=18; # w/ Accuracy Data = 0; #w/4QAcc.= 0
0 0
0 0
240031003
240032002
0 0
240051007
240053001
240150003
240251001
240313001
240330001
240338001
240430009
245100006
245100007
245100035
245100040
245100049
245100052
MASSACHUSETTS Total* Sites =18; (#w/data=18); #whereAcc
250035001 1
250052004 1
250053001 1
250092006 1
250095005 1
250096001
250130008 1
250130016 1
250132007 0
250154002 1
250171102 1
250210007 1
250230004 0
250250002 1
250250027 1
250250042 1
250270020 1
250272004 1
MICHIGAN Total # Sites =22; (# w/ data =22); #whereAcc
260050003 0
260210014 0
260490021 0
260550003
260650012 0
260770008 0
260810020 0
260990009 0
261150005
261210040 0
261250001 0
261390005 0
261450018 0
261470005 0
261610005
261610008
261630001
261630015 0
261630016
261630025
261630033 0
261630036 0
MINNESOTA Total # Sites =21 ; (#w/ data =21); #whereAcc
270376018
0 0
0
0 0
0 0
0 0
0 0
0
0 0
0 0
0
000
0 0
000
Reqrd (All)=18; #w/ Accuracy Data =18; # w/4 Q Acc.=13
1 1 1
1 1 1
1 1 1
1 1 1
1 1 1
1 1 1
0 1 1
1 1 1
1 1 1
1 1 1
1 1 1
1 1 1
1 1 1
1 1 1
1 1 1
1 1 0
1 1 1
1 1 1
Reqrd (All)=22; # w/ Accuracy Data = 0; # w/ 4 Q Acc.= 0
000
000
000
0
000
000
000
000
0
000
000
000
000
000
000
0 0
000
000
000
0 0
000
000
Reqrd (All)=21; #w/ Accuracy Data =11; #w/4QAcc.= 0
0 1 1
s w/ Accuracy in
racy All 4 Q
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4 1
4 1
4 1
4 1
4 1
3
3
4 1
3
4 1
4 1
4 1
3
4 1
4 1
3
4 1
4 1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
STATE SI
# of Accuracy Records # Q'
TE Q1 | Q2 | Q3
270475401
270530960 0
270530961 0
270531007 0
270532006 0
270757608
270854301
270953051
271112012
271230021 1
271230866 0
271230868 0 1
271230871 0
271230872 0
271230873 1
271377001 0
271377550 0
271453052
271630301
271713201
| Q4 Acci
0
1 1
1 1
1 0
1 1
0
0
0
0
1 1
1 1
1 1
1 1
1 0
1 0
0 0
0 0
0
0
0
s w/ Accuracy in
racy All 4 Q
0
2
2
1
2
0
0
0
0
3
2
3
2
1
2
0
0
0
0
0
MISSISSIPPI Total* Sites =16; (#w/ data =16); # where Ace. Reqrd (All)=1 6; #w/ Accuracy Data =16; #w/4QAcc.= 0
280010004 0 1
280110001 1
280330002 0 1
280350004 0 1
280450001 0 1
280470008 0
280490010 0 1
280490018 0 1
280590006 0 0
280670002 0 1
280750003 1
280810005 0 1
280870001 0 1
281210001 0 1
281230001
281490004 0 1
1 0
0 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
1 0
2
1
2
2
2
1
2
2
1
2
2
2
2
2
1
2
MISSOURI Total # Sites =20; (#w/ data =19); # where Ace. Reqrd (All)=20; #w/ Accuracy Data =16; # w/4 Q Acc.=10
290210010 1 1
290390001 1 1
290470005 1 1
290470026 1 1
290470041 1 1
290770032 2 2
290910003 1 1
290950036 0 0
290952002 0 0
290970003 1 1
290990012 1 0
291370001 1 1
291831002 1 1
291860006 1 0
291892003 2 2
291895001 1 1
1 1
1 1
1 1
1 1
1 1
2 2
1 1
0 0
0 0
1 1
1 1
1 1
1 1
1 1
2 0
1 0
295100007
295100085 0
295100086 0 0
295100087
MONTANA Total # Sites = 9; (# w/ data = 9); # where Ace. Reqrd (All)= 9; # w/ Accuracy Data
300290039 1 1
300290043 1 1
300290047 0
300490018 1 0
300530018 1 0
300630024 1 0
1 1
1 1
0
= 9; #w/4QAcc.= 2
1 1
0 0
1 1
1 1
1 1
1 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
0
0
4 1
3
4 1
4 1
3
3
3
0
2
2
0
4 1
2
2
3
3
3
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
STATE SI
rE 01 |
300630031 1
300930005 1
301111065 1
NEBRASKA Total* Sites =13; (#w/ data =13); #whereAcc
310250002 0
# of Accuracy Records
Q2 | Q3
1
0
0
Reqrd(AII)=13; # w/ Accuracy Data
0
310270001
310310001
310490001
310550019 0
310550051 0
310550052
310790003 0
311090022 0
311111002 0
311530007 0
311570003 0
311770002
NEVADA Total # Sites = 7; (# w/ data = 7); # where Ace.
320030022 0
320030560 0
320031019 0
320032002 0
0
0
0
0
0
0
0
0
0
Reqrd (All)= 7; # w/ Accuracy Data =
0
0
0
0
320050008
320310016 0
320312002
NEW HAMPSHIRE Total # Sites = 9; (#w/data = 0|; #whereAcc.
0
0
Reqrd (All)= 9; # w/ Accuracy Data =
330012003
330050007
330070014
330110019
330111007
330130003
330135001
330150009
330190003
NEW JERSEY Total* Sites =19; (#w/ data =19); #whereAcc
340030003 0
340070003 0
340071007 0
340130011 0
340130015
Reqrd(AII)=19; # w/ Accuracy Data
0
0
0
0
0
340155001
340171003 0
0
340172002
340210008 0
340218001 0
340230006 0
340270004
340273001 0
340292002 0
340310005 0
340390004 0
340390006 0
0
0
0
0
0
0
0
0
0
340392003
340410006
NEW MEXICO Total* Sites =13; (#w/ data =10); #whereAcc
350010023 0
350010024 0
350050005 0
350130017 0
350131006 0
350171002 0
350250007 0
350431003 0
Reqrd(AII)=13; # w/ Accuracy Data
0
0
0
0
0
0
0
0
350439001
# Q's w/ Accuracy in
| Q4 Accuracy All 4 Q
1 1 41
1 1 3
1 1 3
= 0; #w/4QAcc.= 0
000
000
000
000
000
000
000
000
000
000
000
000
000
0; #W4QAcc.= 0
000
000
000
000
0 0
000
000
0; #W4QAcc.= 0
0
0
0
0
0
0
0
0
0
= 0; # w/ 4 Q Acc.= 0
000
000
000
000
000
0 0
000
000
000
000
000
000
000
000
000
000
000
0 0
0 0
= 0; # w/ 4 Q Acc.= 0
000
000
000
000
000
000
000
000
0
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
10
STATE SI
# of Accuracy Records
re QI | 02
| Q3
#Q
| Q4 Acci
350439003
350450006 0
350490020 0
0
0
0 0
0 0
350499002
s w/ Accuracy in
racy All 4 Q
0
0
0
0
NEW YORK
NORTH CAROLINA
Total # Sites =42; (# w/ data =33|;
360010005
360010012
360050073
360050080
360050083
360050110
360130011
360271004
360290002
360290005
360291007
360310003
360470011
360470052
360470076
360470118
360551004
360552002
360556001
360590005
360590008
360590011
360610010
360610056
360610062
360610115
360610117
360632008
360652001
360670019
360671015
360710002
360810094
360810097
360810116
360850055
360850067
360893001
360930003
361010003
361030001
361030005
Total # Sites =35; (#w/data=35|;
370010002
370210034
370250004
370330001
370350004
370370004
370510009
370570002
370610002
370630001
370650003
370670022
370670024
370710016
370810009
370811005
370870010
# where Ace. Reqrd (All|=42; # w/ Accuracy Data = 0; # w/ 4 Q Acc.= 0
0
0
0
0
0
0
0
0
0
0
# where Ace. Reqrd (All|=35; # w/ Accuracy Data =35; # w/ 4 Q Acc.= 7
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
11
STATE SI
# of Accuracy Records # Q'
TE Q1 | Q2 | Q3
371070004 0 0
371110004 1 1
371190010 1 1
371190034 1 1
371190040 1 1
371190041
371210001 1 1
371230001
371290009 0 0
371330005 0 0
371350007 0 0
371390002 0
371470005 2 3
371550004 0 0
371730002 1 1
371830014 0 0
371830015 0 0
371910005 1 3
NORTH DAKOTA Total # Sites = 7; (# w/ data = 7); # where Ace. Reqrd (All)= 7; # w/ Accuracy Data =
380130002 0
380130003
380150003 1 1
380171004 1 1
380350004 1 0
380570004 1 2
380910001 1 0
OHIO Total # Sites =37; (# w/ data =37); # where Ace. Reqrd (All)=37; # w/ Accuracy Data
390090003 0 0
390170003 0 0
390350013 0 0
390350027 0 0
390350038 0 0
390350045
390350060 0 0
390350065 0 0
390350066 0 0
390351002 0 0
390490024 0 0
390490025 0 0
390490081 0 0
390610014 0 0
390610040 0
390610041 0 0
390617001 0 0
390618001 0 0
390810016 0 0
390811001 0 0
390851001 0 0
390870010 0 0
390932003 0 0
390950024 0 0
390950025 0 0
390950026 0
390990005 0 0
391130014 0 0
391130031 0 0
391330002 0 0
391351001 0 0
391450013 0 0
391510017 0 0
391510020 0 0
391530017 0 0
391530023 0 0
391550007 0 0
OKLAHOMA Total # Sites =24; (#w/ data =19); # where Ace. Reqrd (All)=24; # w/ Accuracy Data
| Q4 Acci
1 1
1 1
1 1
0 0
1 1
1 1
1 1
0 1
1 1
1 1
1 1
1 2
0 2
1 1
1 1
1 1
1 1
0 2
7; #w/4QAcc.= 3
1 1
0 2
1 1
1 1
1 1
1 1
1 1
= 0; # w/ 4 Q Acc.= 0
0 0
0 0
0 0
0 0
0 0
0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
= 0; # w/ 4 Q Acc.= 0
s w/ Accuracy in
racy All 4 Q
2
4 1
4 1
2
4 1
2
4 1
1
2
2
2
2
3
2
4 1
2
2
3
2
1
4 1
4 1
3
4 1
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
12
# of Accuracy Records
STATE SITE Q1 | Q2 | Q3
400159008
400179001
400190294 0
400190295
400219002
400310648 0
400390852 0
400470554 0
400710602 0
400719003
400819005
400970186 0
401010169 0
401090035 0
401090038 0
401091037 0
401159004
401179007
401190614 0
401210415 0
401250054 0
401339006
401430110 0
401430131 0
OREGON Total # Sites =27; (# w/ data =27|; # where Ace. Reqrd (All|=27; # w/ Accuracy Data
410030013 0 0
410090004 0 0
410170113 0 0
410290133 0 0
410291001 0 0
410292129
410330107
410350004 0 0
410370001 0 0
410370003
410390060 0 0
410391007 0 0
410392013 0 0
410430009
410470040 0 0
410470109 0 0
410470110
410510080 0 0
410510244 0 0
410510246
410590121 0 0
410610006 0 0
410610117
410619103
410650007
410670111 0 0
410671003
# Q's w/ Accuracy in
| Q4 Accuracy All 4 Q
0
000
000
0 0
000
000
000
000
000
0
0
000
000
000
000
000
000
0
000
000
000
0
000
000
= 0; # w/ 4 Q Acc.= 0
000
000
000
000
000
000
000
000
000
000
000
000
000
0 0
000
000
000
000
000
000
000
000
000
000
0 0
000
000
PENNSYLVANIA Total # Sites =37; (# w/ data =35); # where Ace. Reqrd (All)=37; #w/ Accuracy Data =23; #w/4QAcc.=23
420010001 1 1
420030008 0 0
420030021 0 0
420030064 0 0
420030067 0
420030093 0 0
420030095 0 0
420030097 0 0
420030116 0 0
420030131 0 0
420031008 0 0
420031301 0 0
1 1 41
000
000
000
000
000
000
000
000
000
000
000
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
13
STATE SI
# of Accuracy Records
re Q1 | Q2 | Q3
420039002 0 0
#Q
| Q4 Acci
0 0
420070014
420110009 1 1
420170012 1 1
420210011 1 1
420430401 1 1
420450002 1 1
420490003 1 1
420692006 1 1
420710007 1 1
420770004 1 1
420791101 1 1
420910013 1 1
420950025 1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
420990301
421010004 1 1
421010020 1 1
421010024 1 1
421010047 1 1
421010136 1 1
421250005 1 1
421250200 1 1
421255001 1 1
421290008 1 1
421330008 1 1
PUERTO RICO Total # Sites = 9; (# w/ data = 9|; # where Ace. Reqrd (All|= 9; # w/ Accuracy Data
720210009 0 0
720530003 0
720570008 0 0
720590016 0 0
720610005 0 0
720810001 0 0
720970003 0 0
721130004 0 0
721270003 0 0
RHODE ISLAND Total # Sites = 7; (#w/data = 7|; # where Ace. Reqrd (All|= 7; # w/ Accuracy Data
440030002 0 0
440070020 0 0
440070022 0 0
440070023
440071005 0 0
440071010 0 0
440090007 0 0
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
= 0; #w/4QAcc.= 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
= 0; #w/4QAcc.= 0
0 0
0 0
0 0
0
0 0
0 0
0 0
s w/ Accuracy in
racy All 4 Q
0
0
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
0
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
SOUTH CAROLINA Total* Sites =17; (#w/data=17|; # where Ace. Reqrd (All|=17; #w/ Accuracy Data =17; # w/4 Q Acc.=10
450130007 0 5
450190046 4 7
450190048 6
450190049 7 5
450290002 0
450370001 0
450410002 2 6
450430009 5 6
450450009 2
450470003 2 6
450630005 0 3
450630008 6 8
450730001 6 6
450790007 5 6
450790019 4 6
450830010 7 6
450910006 7 0
SOUTH DAKOTA Total # Sites = 8; (# w/ data = 8); # where Ace. Reqrd (All|= 8; # w/ Accuracy Data
460110002 1
460990006 1
460990007 1 1
7 6
6 7
5 7
6 6
0 6
6 6
6 6
3 7
6 6
7 6
7 5
4 8
5 7
6 6
6 7
6 6
7 5
= 8; #w/4QAcc.= 5
1 1
1 1
1 1
3
4 1
3
4 1
1
2
4 1
4 1
3
4 1
3
4 1
4 1
4 1
4 1
4 1
3
3
3
4 1
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
14
TENNESSEE
TEXAS
461030014
461030015
461030016
461030017
461031001
Total* Sites =21;
470090005
470370023
470450004
470650031
470650032
470654002
470930028
470931017
470931020
470990002
471130004
471192007
471251009
471410001
471450004
471570014
471570038
471570047
471571004
471631007
471650007
Total # Sites =47;
480290034
480290052
480290053
480370004
480391003
480550062
480612002
480850005
481130020
481130035
481130050
481130057
481130069
481130087
481350003
481410002
481410010
481410037
481410038
481410043
481410044
481410045
481670053
481671005
482010024
482010026
482010051
482010058
482010062
482011035
482011037
482011039
482150042
482150043
483030001
483150050
483390089
1
1
1
1
(#w/data=12|; # where Ace.
0
0
1
0
0
0
0
0
0
0
(# w/ data =40|; # where Ace.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
2
Reqrd(AII)=21;
0
0
1
0
0
0
0
0
0
0
Reqrd (All|=47;
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
# w/ Accuracy Data = 3; # w/ 4 Q Acc.= 0
0
0
1
0
0
0
0
0
0
0
0
0
# w/ Accuracy Data = 0; # w/ 4 Q Acc.= 0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
0
0
1
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4
4
4
4
3
0
0
0
0
0
0
2
2
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
15
STATE SI
rE 01 |
# of Accuracy Records
Q2 | Q3
#Q
| Q4 Acci
483550020
483550032
483750005
484390063 0
484391002 0
0
0
484391003
484393006 0
484530020 0
0
0
484530021
484790016
UTAH Total* Sites =11; (#w/ data =11); #whereAcc
490110001 1
490350003 0
490350012 1
490353006 1
490353007 2
490450002 2
490490002 1
490494001 1
490495010 1
490570001 1
490570007 1
VERMONT Total # Sites = 5; (# w/ data = 5|; #whereAcc.
500030005 0
500070007 0
Reqrd(AII)=11; # w/ Accuracy Data
2
1
1
1
1
2
1
1
1
1
1
Reqrd (All)= 5; # w/ Accuracy Data =
0
0
500070012
500210002 0
500230005 0
VIRGIN ISLANDS Total # Sites = 1 ; (#w/data = 1); #whereAcc.
780010012 0
VIRGINIA Total # Sites =20; (# w/ data =20); #whereAcc
510130020 1
510360002 1
510410003 1
510590030 1
510591004 1
510595001 1
510870014 1
510870015 1
511071005 1
0
0
Reqrd (All)= 1 ; # w/ Accuracy Data =
0
0 0
0 0
0 0
0 0
0 0
0
0 0
=11; #w/4QAcc.= 9
2 1
1 1
1 1
1 1
1 0
1 1
1 1
1 1
1 1
1 1
1 2
0; #w/4QAcc.= 0
0 0
0 0
0 0
0 0
0 0
0; #w/4QAcc.= 0
0 0
s w/ Accuracy in
racy All 4 Q
0
0
0
0
0
0
0
0
0
0
4 1
3
4 1
4 1
3
4 1
4 1
4 1
4 1
4 1
4 1
0
0
0
0
0
0
Reqrd (All)=20; #w/ Accuracy Data =19; # w/4 Q Acc.=19
1
1
1
1
1
1
1
1
1
511390004
515200006 1
515500012 1
516500004 1
516800014 1
517000013 1
517100024 1
517600020 1
517700014 1
517750010 1
518100008 1
WASHINGTON Total # Sites =23; (# w/ data =23); # where Ace
530050002 1
1
1
1
1
1
1
1
1
1
1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
0
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
0
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
4 1
Reqrd (All)=23; # w/ Accuracy Data =21 ; # w/4 Q Acc.=12
1
530090009
530110013 1
530330004 1
530330017 0
530330021 1
530330024 1
1
1
1
1
1
530330027
530330057 0
530330080 1
530332004 1
2
1
1
530530029
530530031 1
1
0 1
0
1 1
1 0
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1
1 1
3
0
4 1
3
3
4 1
4 1
2
3
4 1
4 1
1
4 1
stateaaug.123
-------
1999 PM2.5 Data Completeness, Accuracy (as of AIRS 7/26/00)
16
STATE SI
# of Accuracy Records
rE Q1 | Q2 | Q3
530531018 1 1
530570014
530610005
530611007 1 1
530630016 1 1
530630047 1 1
530639000 0 1
530670013 1 1
530730015 1 1
530770012 1 1
#Q
| Q4 Acci
1 1
0
1
1 1
1 1
1 1
1 1
1 1
1 1
2 0
s w/ Accuracy in
racy All 4 Q
4 1
0
1
4 1
4 1
4 1
3
4 1
4 1
3
WEST VIRGINIA Total # Sites =14; (#w/ data =14|; # where Ace. Reqrd (All|=14; #w/ Accuracy Data =14; # w/4 Q Acc.=10
540030003 0 3
540090005 1 4
540110006 2 2
540290011 1 4
540291004 1 4
540330003 0 3
540390009 1 2
540391005 1 3
540511002 1 4
540610003 0 3
540690008 1 4
540810002 2 3
540890001 2 3
541071002 0 3
WISCONSIN Total # Sites =28; (#w/data=28|; # where Ace. Reqrd (All|=28; # w/ Accuracy Data
550090005 1 1
550090025 1 1
550090026 1 1
550250025 0 0
550250047 0 1
550270007 0 1
550290004 1 1
550310025 2 0
550430009 1 0
550550008 0 0
550590019 0 0
550710007 1 1
550790010 0 0
550790026 1 0
550790043 0 0
550790050 0 0
550790051 0 0
550790059 0 0
550790099 0 0
550870009 0 2
550890008 0 1
551050002 0 1
551091002 0 1
551250001 1 1
551330027 0 0
551330034 0 0
551390011 0 2
551410016 0 0
WYOMING Total # Sites = 3; (#w/data = 3); # where Ace. Reqrd (All)= 3; # w/ Accuracy Data =
560210001 0 0
560330001 6 2
560330002 9 3
3 3
3 3
4 3
3 3
3 3
3 2
2 5
3 3
3 3
3 3
3 3
2 3
1 5
3 3
=27; #w/4QAcc.= 6
1 1
1 1
1 1
1 0
1 0
1 0
1 1
1 1
1 0
1 0
0 1
1 1
0 0
0 0
1 0
1 0
1 0
0 1
1 0
1 1
0 0
0 0
1 1
1 1
0 1
0 1
1 1
0 1
2; #w/4QAcc.= 2
0 0
2 4
3 6
3
4 1
4 1
4 1
4 1
3
4 1
4 1
4 1
3
4 1
4 1
4 1
3
4 1
4 1
4 1
1
2
2
4 1
3
2
1
1
4 1
0
1
1
1
1
1
1
3
1
1
3
4 1
1
1
3
1
0
4 1
4 1
US TOTAL
Total # Sites = 979; (# w/data = 924|; # where Ace. Reqrd (All|= 979; # w/Accuracy Data = 456; # w/4 Q Acc.= 176
stateaaug.123
-------
Attachment 2-5
Performance Evaluation Program Site/Days
without a Routine Data Value Match
-------
Site/Days where Performance Evaluation Performed
but No Matching AIRS Value Exists
State
AIRS Site
Date
AK
AL
AR
AZ
CA
CO
DE
FL
020200009
020200009
020900010
010730023
010730023
010730023
011010007
011010007
011010007
011170006
011170006
011170006
011250003
011250003
011250003
011270002
011270002
011270002
050510002
050510002
051190003
051190003
051310008
051310008
051430003
051430003
040190011
060270002
060370002
060370002
060531002
060531002
060670010
060731007
080010001
080410011
080410011
100031007
120251016
121030018
123456789
04/09/1999
07/14/1999
07/10/1999
06/17/1999
08/10/1999
12/02/1999
05/18/1999
07/20/1999
11/02/1999
05/18/1999
07/20/1999
11/02/1999
06/17/1999
08/10/1999
12/02/1999
06/17/1999
08/10/1999
12/02/1999
05/12/1999
06/23/1999
05/12/1999
06/23/1999
05/12/1999
06/23/1999
05/13/1999
06/26/1999
05/27/1999
02/10/1999
05/19/1999
05/26/1999
09/21/1999
12/08/1999
01/07/1999
11/14/1999
01/24/1999
02/02/1999
07/27/1999
11/25/1999
02/17/1999
12/08/1999
08/22/1999
GA
131270004
10/21/1999
-------
Site/Days where Performance Evaluation Performed
but No Matching AIRS Value Exists
State
AIRS Site
Date
ID
160830006
03/26/1999
IL
IN
LA
MD
170310014
170310014
170311016
170311016
170311701
170311701
170311701
170311701
170312001
170312001
170312001
170312001
170313301
170314201
170314201
171430024
171430024
171430024
171430024
180431004
180891003
180892004
180970043
180970043
180970043
180970081
180970081
220191002
220191002
220191002
220191002
240030019
240030019
240030019
240330001
240330001
240330001
245100038
245100038
245100038
245100038
245100040
245100040
245100040
05/15/1999
10/12/1999
02/14/1999
10/12/1999
01/27/1999
05/09/1999
09/06/1999
11/11/1999
01/27/1999
05/09/1999
09/06/1999
11/11/1999
10/12/1999
02/14/1999
10/12/1999
03/16/1999
05/24/1999
07/29/1999
11/08/1999
12/02/1999
07/17/1999
06/14/1999
02/17/1999
08/04/1999
11/20/1999
08/04/1999
11/20/1999
02/11/1999
04/15/1999
07/08/1999
12/02/1999
02/25/1999
04/25/1999
07/20/1999
04/25/1999
07/20/1999
12/14/1999
02/23/1999
04/21/1999
07/23/1999
12/20/1999
04/21/1999
07/23/1999
12/26/1999
-------
Site/Days where Performance Evaluation Performed
but No Matching AIRS Value Exists
State
AIRS Site
Date
MI
MN
MO
MT
ND
NE
NH
NJ
NM
NY
261470005
261630015
261630036
261630036
271230047
271230047
271230047
271230868
291831002
300360024
380570003
310050019
310050019
310550019
310550019
330050007
330050007
330050007
330111007
330111007
330111007
330130003
330130003
330130003
340030003
340070003
340130004
340130011
340130011
340130011
340130011
340390004
340390004
350010023
350010024
350130017
350350060
350430004
350430004
350430004
350430004
360050083
360050083
08/19/1999
10/06/1999
03/25/1999
08/04/1999
04/06/1999
07/08/1999
10/06/1999
07/08/1999
05/11/1999
12/08/1999
06/17/1999
06/23/1999
09/09/1999
06/06/1999
10/21/1999
08/10/1999
12/08/1999
12/14/1999
08/10/1999
12/08/1999
12/14/1999
06/17/1999
08/16/1999
12/11/1999
01/30/1999
01/30/1999
04/24/1999
01/21/1999
01/24/1999
01/30/1999
07/20/1999
01/21/1999
01/24/1999
03/20/1999
03/20/1999
03/19/1999
11/20/1999
03/22/1999
06/08/1999
08/25/1999
10/24/1999
03/04/1999
05/12/1999
-------
Site/Days where Performance Evaluation Performed
but No Matching AIRS Value Exists
State
AIRS Site
Date
NY
OH
OK
OR
PA
PR
SD
TN
360290005
360470011
360470011
360671015
360810094
360810094
360850067
360850067
360850067
390950008
390950008
390950008
390950025
400310648
400310648
401090035
401210415
401210415
401210415
401430110
410330107
410330107
410330107
410330107
420030290
420031301
420170012
420170012
420430401
420590121
420950025
420950025
421290008
421330008
720610013
720610013
720610013
720610013
721270003
721270003
461030016
471570014
471570014
471570014
471570014
05/18/1999
03/01/1999
05/06/1999
05/18/1999
03/04/1999
05/12/1999
03/01/1999
05/06/1999
05/09/1999
03/10/1999
04/21/1999
07/14/1999
11/11/1999
02/23/1999
06/23/1999
02/23/1999
02/17/1999
06/23/1999
09/15/1999
02/17/1999
03/04/1999
05/09/1999
08/07/1999
11/08/1999
03/18/1999
12/29/1999
03/20/1999
08/31/1999
12/08/1999
09/21/1999
03/20/1999
12/02/1999
06/17/1999
09/15/1999
04/07/1999
06/13/1999
09/22/1999
12/15/1999
06/10/1999
09/22/1999
08/31/1999
03/10/1999
04/21/1999
08/04/1999
10/27/1999
-------
Site/Days where Performance Evaluation Performed
but No Matching AIRS Value Exists
State
AIRS Site
Date
TN
TX
VA
471570047
471570047
471570047
471570047
471630007
471630007
471630007
471630007
480290034
481130035
481130050
481130050
481130050
481410002
481410002
481410002
481410002
481410037
481410037
481410037
481410044
481410044
481671005
481671005
481671005
481671005
482010024
482010024
482010024
482010024
482010026
482010026
482010026
482010026
482011035
482011035
482011039
482011039
482011039
484393006
484393006
484393006
484530020
484530020
484530020
511071005
517750010
517750010
518100008
03/10/1999
04/21/1999
08/04/1999
10/27/1999
03/04/1999
06/26/1999
08/31/1999
11/20/1999
07/22/1999
05/27/1999
03/03/1999
05/26/1999
07/07/1999
03/17/1999
06/06/1999
08/18/1999
10/05/1999
06/08/1999
08/18/1999
10/05/1999
06/08/1999
08/20/1999
04/27/1999
04/29/1999
05/18/1999
07/20/1999
04/27/1999
04/29/1999
07/14/1999
10/13/1999
04/27/1999
07/13/1999
10/13/1999
10/15/1999
04/28/1999
07/13/1999
04/27/1999
07/17/1999
11/17/1999
03/02/1999
05/26/1999
07/07/1999
02/17/1999
04/20/1999
10/06/1999
11/11/1999
03/11/1999
08/13/1999
03/09/1999
-------
Site/Days where Performance Evaluation Performed
but No Matching AIRS Value Exists
State
AIRS Site
Date
VI
780010012
06/19/1999
VT
500070003
500070011
500070011
500070011
09/30/1999
09/09/1999
10/30/1999
12/02/1999
WA
WI
530670013
550790043
550790043
550790044
07/29/1999
03/01/1999
10/27/1999
05/03/1999
WV
540390004
540390004
540390004
05/15/1999
08/19/1999
10/30/1999
-------
Attachment 2-6
Collocated Precision Data with Percent Differences > +/- 50%
-------
Percent Differences > 50% or < -50%
based on col located samplers (AIRS extract ion dated 7/26/00)
State
AK
AK
AK
AL
AR
AR
AR
AZ
AZ
CA
CA
CA
CA
CA
CA
REPTORG AIRS Site Method
020 020200018 118
118
118
118
020 021100004 117
117
117
118
020 021700008 117
117
117
Oil 011010007 120
120
001 050010001 117
001 051190007 118
118
118
118
001 051191008 118
118
100 040070008 120
300 040191028 120
001 060190008 120
001 061010003 117
117
117
004 060450006 120
120
120
019 060271003 120
120
120
120
036 060250005 119
036 060710014 119
119
119
Pr:
im.
Cone
8
4
5
6
4
1
1
2
5
1
0
14
12
7
31
16
20
10
15
20
13
8
13
16
56
1
3
1
5
2
16
6
4
9
15
8
11
.10
.40
.00
.00
. 10
.90
.90
. 10
.10
.30
.70
.04
.81
.80
.60
.50
.20
.30
.40
.70
.10
.80
.00
.00
.00
.00
.40
.00
.30
.83
.64
.00
.00
.71
.06
.05
.89
Colo.
Cone
22
19
11
2
0
0
3
14
3
2
0
30
1
14
13
3
11
18
28
9
25
18
23
9
7
36
7
13
2
9
9
3
2
0
77
14
22
.60
.70
.60
.90
.60
.30
.40
.70
.00
.80
.20
.00
.50
.70
.90
.50
.60
.20
.00
.00
.80
.60
.00
.00
.00
.00
.00
.30
.20
.12
.58
.00
.00
.00
.80
.55
.94
Percent Diff >
Difference 50%?
94
126
79
-69
-148
-145
56
150
-51
73
-111
72
-158
61
-77
-130
-54
55
58
-78
65
71
55
-56
-155
189
69
172
-82
105
-53
-66
-66
-200
135
57
63
.46 *
.97 *
.52 *
.66 *
.94 *
.45 *
.60 *
.00 *
.85 *
.17 *
.11 *
.48 *
.07 *
.33 *
.80 *
.00 *
.09 *
.44 *
.06 *
.79 *
.30 *
.53 *
.56 *
.00 *
.56 *
.19 *
.23 *
.03 *
.67 *
.23 *
.82 *
.67 *
.67 *
.00 *
.13 *
.52 *
.45 *
Cone
<= 6? Date
01/01/99
* 01/02/99
* 03/03/99
* 03/08/99
* 07/17/99
* 09/03/99
* 09/15/99
* 10/09/99
* 05/21/99
* 06/17/99
* 09/12/99
01/30/99
* 03/07/99
12/26/99
07/17/99
* 07/23/99
08/16/99
11/08/99
07/26/99
12/26/99
03/01/99
12/08/99
09/21/99
07/11/99
10/15/99
* 11/14/99
* 03/13/99
* 03/19/99
* 07/02/99
* 01/24/99
01/30/99
* 07/29/99
* 10/09/99
* 06/05/99
01/12/99
01/24/99
05/30/99
-------
Percent
based on collocated
Differences > 50% or < -50%
samplers (AIRS extraction dated 7/26/00)
Prim. Colo. Percent Diff > Cone
State
CA
CA
CO
CO
CT
DC
DE
FL
FL
FL
FL
FL
FL
GA
GA
HI
REPTORG AIRS Site Method
036 060710014 119
119
036 060730006 119
001 080010001 118
001 080410011 118
118
118
118
118
118
118
118
118
118
001 090091123 118
001 110010043 120
120
120
120
120
001 100031011 120
001 120330004 118
002 120010023 118
004 121056006 118
118
005 120710005 118
017 120111002 118
118
020 120952002 118
010 130892001 120
120
010 132450005 120
120 150031001 120
120
120
120
Cone
15
6
7
12
3
8
2
0
0
4
1
1
7
4
19
12
8
1
1
3
13
1
4
1
5
5
4
48
9
49
26
17
17
7
7
0
.77
.00
.21
.60
.40
.60
.20
.50
.00
.99
.25
.25
.10
.30
.00
.40
.80
.00
. 10
.30
.50
.16
.00
.00
.30
.50
.40
.40
.04
.00
.00
.00
.20
.70
.90
.50
Cone
4
11
2
6
0
2
4
5
7
1
7
6
0
0
9
6
1
19
11
7
7
0
18
8
9
14
7
6
19
17
13
10
6
0
0
6
.21
.00
.04
.29
.70
.50
.00
.40
.20
.25
.07
.24
.70
.60
.40
.30
.00
.60
.30
.90
.80
.25
.00
.00
.30
.40
.50
.00
.83
.00
.00
.00
.70
.90
.70
.40
Difference 50%?
-115
58
-111
-66
-131
-109
58
166
200
-119
139
133
-164
-151
-67
-65
-159
180
164
82
-53
-129
127
155
54
89
52
-155
74
-96
-66
-51
-87
-158
-167
171
.72 *
.82 *
.78 *
.81 *
.71 *
.91 *
.06 *
.10 *
.00 *
.87 *
.90 *
.24 *
.10 *
.02 *
.61 *
.24 *
.18 *
.58 *
.52 *
.14 *
.52 *
.08 *
.27 *
.56 *
.79 *
.45 *
.10 *
.88 *
.75 *
.97 *
.67 *
.85 *
.87 *
.14 *
.44 *
.01 *
<= 6? Date
* 06/29/99
07/29/99
* 03/25/99
03/13/99
* 04/26/99
* 04/30/99
* 05/06/99
* 06/02/99
* 06/05/99
* 07/29/99
* 08/13/99
* 08/22/99
* 10/09/99
* 12/26/99
08/13/99
04/15/99
* 05/04/99
* 05/07/99
* 05/26/99
* 06/18/99
03/31/99
* 02/05/99
* 11/20/99
* 03/01/99
* 04/30/99
* 03/01/99
* 01/18/99
* 12/14/99
05/30/99
01/15/99
03/13/99
09/21/99
01/18/99
* 02/23/99
* 03/01/99
* 03/19/99
-------
Percent
based on collocated
Differences > 50% or < -50%
samplers (AIRS extraction dated 7/26/00)
State REPTORG AIRS Site
HI 120 150031001
HI 120 150032004
IA 001 191532520
IA 002 191130037
IA 003 191550009
ID 001 160550006
IN 001 180431004
IN 001 180950009
IN 008 180970083
KS 001 200910007
KS 001 201730010
KS 001 202090021
KY 001 210190017
KY 001 210590014
Prim.
lethod
120
120
120
120
120
120
120
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
Cone
3
4
7
2
3
5
0
4
7
6
5
2
6
2
1
25
2
15
6
18
48
8
8
0
7
7
8
1
3
1
8
15
13
16
10
2
.00
.20
.00
.40
.50
.70
.80
.30
.60
.00
.10
.60
.40
.90
. 10
.80
.10
.00
.70
.00
.20
.90
.70
.70
.20
.30
.00
.70
.20
.90
.30
.50
.70
.00
.40
.50
Colo.
Cone
1
0
13
0
0
10
2
0
14
2
3
0
16
6
13
8
6
7
16
1
20
22
1
7
0
2
2
11
6
9
23
3
2
1
2
11
.10
.70
.50
.90
.60
.60
.30
.20
.50
.20
.00
.20
.00
.60
.40
.80
.80
.10
.50
.10
.70
.00
.30
.30
.50
.50
.50
.60
.90
.60
.10
.40
.40
.10
.40
.70
Percent Diff >
Difference 50%?
-92
-142
63
-90
-141
60
96
-182
62
-92
-51
-171
85
77
169
-98
105
-71
84
-176
-79
84
-148
165
-174
-97
-104
148
73
133
94
-128
-140
-174
-125
129
.68 *
.86 *
.41 *
.91 *
.46 *
.12 *
.77 *
.22 *
.44 *
.68 *
.85 *
.43 *
.71 *
.89 *
.66 *
.27 *
.62 *
.49 *
.48 *
.96 *
.83 *
.79 *
.00 *
.00 *
.03 *
.96 *
.76 *
.87 *
.27 *
.91 *
.27 *
.04 *
.37 *
.27 *
.00 *
.58 *
Cone
<= 6? Date
* 04/12/99
* 04/24/99
05/30/99
* 06/11/99
* 06/17/99
* 05/12/99
* 10/03/99
* 04/06/99
04/15/99
* 11/02/99
* 08/13/99
* 12/02/99
02/11/99
* 04/30/99
* 04/18/99
05/18/99
* 03/16/99
04/09/99
06/14/99
* 07/08/99
03/07/99
03/19/99
* 04/06/99
* 05/24/99
* 06/23/99
* 07/11/99
* 05/24/99
* 02/23/99
* 04/06/99
* 05/24/99
02/05/99
* 02/11/99
* 02/17/99
* 02/23/99
* 03/01/99
* 04/24/99
KY 001 210670012 118
1.50
6.70
126.83
04/24/99
-------
Percent
based on collocated
Differences > 50% or < -50%
samplers (AIRS extraction dated 7/26/00)
Prim. Colo. Percent Diff > Cone
Itate
KY
KY
KY
KY
LA
LA
LA
MA
MA
MA
MA
ME
MI
MN
MO
REPTORG AIRS Site Method
001 210670012 118
001 211950002 118
118
001 212270007 118
118
118
002 211110043 118
001 220330009 118
118
001 220550005 118
001 220710012 118
001 250130016 120
120
120
120
120
120
120
120
001 250230004 120
001 250250027 120
001 250270020 120
120
120
120
120
120
120
120
001 230110016 117
001 260810020 118
001 271377550 120
120
120
003 295100085 118
118
118
Cone
1
3
7
14
21
15
16
27
9
22
22
47
8
11
15
14
16
11
1
12
14
7
6
7
7
9
10
13
1
9
1
1
0
0
12
34
3
.20
.20
. 10
.40
.00
.70
.00
.30
.90
.30
.40
.60
.60
.80
.20
.40
.70
.30
.10
.50
.00
.90
.70
.60
.80
.10
.30
.60
.90
.50
.70
.50
.00
.90
.50
.20
.80
Cone
11
6
19
8
10
9
8
13
17
10
12
6
2
20
27
7
5
6
13
27
5
4
11
22
3
17
5
6
8
16
3
0
5
8
3
17
1
.30
.20
.20
.40
.90
.10
.40
.20
.10
.00
.20
.00
.30
.90
.70
.30
.30
.00
.50
.00
.60
.00
.30
.10
.50
.00
.00
.80
.40
.80
.70
.80
.00
.50
.40
.20
.30
Difference 50%?
161
63
92
-52
-63
-53
-62
-69
53
-76
-58
-155
-115
55
58
-65
-103
-61
169
73
-85
-65
51
97
-76
60
-69
-66
126
55
74
-60
200
161
-114
-66
-98
.60 *
.83 *
.02 *
.63 *
.32 *
.23 *
.30 *
.63 *
.33 *
.16 *
.96 *
.22 *
.60 *
.66 *
.28 *
.44 *
.64 *
.27 *
.86 *
.42 *
.71 *
.55 *
.11 *
.64 *
.11 *
.54 *
.28 *
.67 *
.21 *
.51 *
.07 *
.87 *
.00 *
.70 *
.47 *
.15 *
.04 *
<= 6? Date
* 05/18/99
* 03/07/99
05/18/99
04/18/99
05/18/99
06/05/99
01/18/99
01/18/99
09/09/99
06/23/99
03/01/99
* 03/04/99
* 06/17/99
06/20/99
06/29/99
08/19/99
* 08/22/99
* 08/31/99
* 12/08/99
01/03/99
* 08/19/99
* 03/10/99
03/16/99
04/18/99
* 04/24/99
04/30/99
* 05/27/99
07/08/99
* 08/16/99
02/11/99
* 06/29/99
* 09/09/99
* 10/03/99
* 10/09/99
* 10/01/99
10/05/99
* 11/02/99
-------
Percent
based on collocated
Differences > 50% or < -50%
samplers (AIRS extraction dated 7/26/00)
Prim. Colo. Percent Diff > Cone
State
MO
MS
MX
NC
NC
ND
ND
NE
NE
NE
NJ
NJ
NM
NV
NY
NY
OH
REPTORG AIRS Site Method
003 295100085 118
118
118
118
118
100 281210001 118
001 300630024 116
116
001 371210001 118
001 371830014 118
001 380171004 118
001 380570004 117
117
117
117
117
117
117
001 311090022 118
118
003 310550019 118
003 310550052 118
001 340070003 117
117
117
117
001 340390004 117
001 350490020 118
118
118
200 320310016 120
001 360610056 118
001 360671015 118
008 390170003 120
Cone
21
9
9
4
5
7
13
8
7
12
6
15
6
8
2
6
2
5
1
2
3
7
9
18
29
12
2
7
3
3
1
4
5
35
.80
.30
.70
.40
. 10
.80
.00
.70
.00
.90
.00
.30
.50
.50
.00
.30
.30
.30
.10
.20
.80
.90
.60
.80
.90
.10
.90
.30
.50
.20
.90
.60
.90
.30
Cone
8
21
5
12
23
18
6
4
12
0
3
8
3
4
5
2
4
3
9
6
0
1
3
8
12
3
23
4
7
0
3
1
2
20
.70
.80
.80
.80
.60
.60
.60
.30
.40
.20
.30
.00
.50
.30
.10
.60
.00
.00
.90
.10
.50
.80
.30
.70
.90
.00
.70
.00
.60
.20
.20
.10
.80
.20
Difference 50%?
-85
80
-50
97
128
81
-65
-67
55
-193
-58
-62
-60
-65
87
-83
53
-55
160
93
-153
-125
-97
-73
-79
-120
156
-58
73
-176
50
-122
-71
-54
.90 *
.39 *
.32 *
.67 *
.92 *
.82 *
.31 *
.69 *
.67 *
.89 *
.06 *
.66 *
.00 *
.63 *
.32 *
.15 *
.97 *
.42 *
.00 *
.98 *
.49 *
.77 *
.67 *
.45 *
.44 *
.53 *
.39 *
.41 *
.87 *
.47 *
.98 *
.81 *
.26 *
.41 *
<= 6? Date
11/09/99
11/10/99
* 12/04/99
* 12/10/99
* 12/29/99
03/25/99
04/12/99
* 08/16/99
12/14/99
* 11/08/99
* 04/12/99
02/23/99
* 03/01/99
* 04/12/99
* 05/18/99
* 05/24/99
* 06/11/99
* 07/17/99
* 10/27/99
* 12/26/99
* 09/09/99
* 10/03/99
* 06/17/99
06/23/99
07/17/99
* 11/02/99
* 07/11/99
* 01/18/99
* 03/01/99
* 08/01/99
* 03/31/99
* 07/11/99
* 12/11/99
09/27/99
-------
Percent
based on collocated
Differences > 50% or < -50%
samplers (AIRS extraction dated 7/26/00)
Prim.
State
OH
OK
OK
OR
OR
SD
SD
TN
TN
TX
TX
UT
VA
VA
WA
WA
WI
WI
REPTORG AIRS Site Method
008 390610014 120
101 401090035 118
106 400219002 118
001 410370001 118
001 410390060 118
118
118
001 460990006 119
119
119
001 461031001 120
120
120
120
001 471650007 118
004 470931017 120
120
001 481130069 118
001 482011035 118
001 490494001 118
118
118
001 517100024 118
001 517600020 118
118
001 530530031 118
118
001 530770012 118
001 550250025 118
118
118
001 550310025 118
118
Cone
14
9
4
1
3
9
12
12
4
1
8
1
3
14
22
11
9
8
17
5
14
6
5
12
10
26
2
6
6
5
2
14
2
.00
.20
.60
.40
.30
.10
.60
.50
.50
.50
.40
.60
.60
.60
.20
.80
.20
.50
.40
.70
. 10
.20
.60
.80
.80
.80
.60
.90
.20
.20
.90
.40
.40
Colo.
Cone
2
4
1
0
13
0
0
21
1
3
4
6
1
6
13
21
37
14
8
13
5
12
9
6
6
14
1
13
21
1
5
7
0
.00
.20
.90
.80
.70
.00
.00
.10
.90
.70
.70
.30
.10
.20
.20
.40
.50
.60
.70
.70
.70
.10
.40
.10
.00
.50
.40
.70
.40
.20
.20
.30
.60
Percent Diff >
Difference 50%?
-150
-74
-83
-54
122
-200
-200
51
-81
84
-56
118
-106
-80
-50
57
121
52
-66
82
-84
64
50
-70
-57
-59
-60
66
110
-125
56
-65
-120
.00 *
.63 *
.08 *
.55 *
.35 *
.00 *
.00 *
.19 *
.25 *
.62 *
.49 *
.99 *
.38 *
.77 *
.85 *
.83 *
.20 *
.81 *
.67 *
.47 *
.85 *
.48 *
.67 *
.90 *
.14 *
.56 *
.00 *
.02 *
.14 *
.00 *
.79 *
.44 *
.00 *
Cone
<= 6? Date
* 03/25/99
* 09/21/99
* 09/21/99
* 11/08/99
* 04/09/99
* 05/27/99
* 09/15/99
08/28/99
* 09/16/99
* 12/26/99
* 07/26/99
* 09/27/99
* 10/30/99
12/23/99
12/29/99
04/18/99
04/30/99
12/26/99
10/27/99
* 06/29/99
* 07/05/99
10/09/99
* 02/14/99
03/13/99
* 12/17/99
09/03/99
* 12/14/99
02/23/99
04/21/99
* 08/04/99
* 09/30/99
12/23/99
* 12/26/99
-------
Percent Differences > 50% or < -50%
based on collocated samplers (AIRS extraction dated 7/26/00)
Prim.
State REPTORG AIRS Site Method
WI 001 550790026 118
118
WI 001 550790059 118
118
WV 001 540391005 118
118
118
WV 002 540290011 118
118
118
118
118
118
WY 001 560330002 117
117
117
117
117
Cone
23
5
27
8
0
7
7
17
2
8
3
4
3
12
4
10
5
1
.20
.70
.30
.70
.90
.50
.90
.20
.30
.10
.40
.60
.80
.20
.70
.00
.00
.70
Colo.
Cone
42
3
7
15
12
15
2
0
4
15
1
20
6
4
7
5
1
5
.00
.30
.50
.20
.50
.00
.70
.50
.50
.80
.40
.30
.80
.30
.90
.80
.60
.30
Percent Diff >
Difference 50%?
57
-53
-113
54
173
66
-98
-188
64
64
-83
126
56
-95
50
-53
-103
102
.67 *
.33 *
.79 *
.39 *
.13 *
.67 *
.11 *
.70 *
.71 *
.44 *
.33 *
.10 *
.60 *
.76 *
.79 *
.16 *
.03 *
.86 *
Cone
<= 6? Date
01/30/99
* 10/03/99
02/08/99
10/15/99
* 02/20/99
10/06/99
* 10/18/99
* 07/26/99
* 09/21/99
09/27/99
* 10/24/99
* 11/05/99
* 11/17/99
* 03/13/99
* 03/25/99
* 04/30/99
* 06/11/99
* 06/23/99
-------
Attachment 2-7
Collocated Precision Data Aggregated by Reporting Organizations
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
021700008
020200018
021100004
021700008
020200018
020900010
021100004
021700008
A
A
A
A
QUARTER
1
3
3
3
4
4
4
4
1
3
4
A
EST
(90%
3
2
2
2
2
4
4
3
3
2
3
3
.6 (
.2 (
.8 (
.2 (
.1 (
.4 (
.7 (
.0 (
.6 (
.3 (
.6 (
.5 (
. REL
CONF
2.
1 .
1 .
1 .
1 .
2.
3.
2.
2.
1 .
2.
2.
. RMSE
. INTERVAL)
2
3
4
1
3
9
2
2
2
5
9
9
STATE -AK
AIRS ID
020200018
020200018
A
A
A
QUARTER
1
4
1
4
A
EST
(90%
24
2
24
2
21
.6 (
.4 (
.6 (
.4 (
.0 (
. REL
CONF
17.
1 .
17.
1 .
15.
, 10.
9.
, 44.
, 35.
4.
, 10.
9.
5.
, 10.
5.
4.
4.
4)*
6)
2)*
1)*
9)
5)*
8)
1)
4)*
6)
9)
5)
REPORTING
. RMSE
. INTERVAL)
6
5
6
5
7
STATE -AL
AIRS ID
010970002
011010007
A
A
QUARTER
1
1
1
A
EST
(90%
11
19
16
16
.0 (
.8 (
.5 (
.5 (
. REL
CONF
8.
15.
13.
13.
, 42.
7.
, 42.
7.
, 32.
0)*
0)
0)*
0)
5)*
REPORTING
. RMSE
. INTERVAL)
2
2
5
5
STATE AL
AIRS ID
010730023
010731005
010732003
QUARTER
1
1
1
(!
10
1
8
EST
)0%
.5 (
.9 (
.3 (
. REL
CONF
7.
1 .
6.
, 17.
, 28.
, 21.
, 21.
1)*
9)*
6)*
6)*
REPORTING
. RMSE
. INTERVAL)
8
0
4
, 16.
, 30.
, 12.
8)*
2)*
4)*
NO. OF
OBSERVATIONS
3
2
1
1
4
4
5
8
3
4
21
28
ORGANIZATION =020
NO. OF
OBSERVATIONS
8
3
8
3
11
ORGANIZATION=01 1
NO. OF
OBSERVATIONS
11
14
25
25
ORGAN IZATI ON=0 1 2
NO. OF
OBSERVATIONS
10
1
13
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
3
4
8
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
2
2
METHOD= 116
NO. OF
SAMPLER
QUARTERS
1
1
1
EST. REL. BIAS
(90% CONF. INTERVAL)
2.9 (-1.2, 7.1)
1.4 ( -9.3, 12.0)
2.8
-2.2
1.8 ( 0.5, 3. 1)
1.6 ( -4.0, 7.2)
3.1 ( -0.7, 6.9)
-2. 1 ( -3.6, -0.6)
EST. REL. BIAS
(90% CONF. INTERVAL)
6.8 (-10.1, 23.7)
-1.4 ( -5.4, 2.7)
EST. REL. BIAS
(90% CONF. INTERVAL)
-0.8 ( -7.1, 5.5)
10.5 ( 2.2, 18.7)
EST. REL. BIAS
(90% CONF. INTERVAL)
1.6 ( -4.7, 8.0)
-1.9
-0.3 ( -4.5, 4.0)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
010732006
010735002
A
A
QUARTER
1
1
1
A
(!
8
2
9
9
EST
)0%
.5 (
.8 (
.0 (
.0 (
. REL
CONF
4.
1 .
7.
7.
3
4
3
3
STATE -AR
AIRS ID
050010001
050310001
050010001
050310001
A
A
A
QUARTER
3
3
4
4
3
4
A
(!
2
5
15
9
4
12
8
EST
)0%
.0 (
.7 (
.4 (
.0 (
.2 (
.9 (
.9 (
. REL
CONF
1 .
4.
11 .
6.
3.
10.
7.
5
3
4
4
4
2
6
STATE AR
AIRS ID
051190007
051191008
051310008
051190007
051191008
051310008
A
A
A
QUARTER
3
3
3
4
4
4
3
4
A
(!
16
21
9
15
19
4
15
14
15
EST
)0%
.1 (
.8 (
.0 (
.5 (
.5 (
.0 (
.6 (
.7 (
.2 (
. REL
CONF
13.
14.
6.
11 .
14.
3.
13.
12.
13.
2
6
7
7
7
0
3
4
5
STATE AZ
AIRS ID
040230004
040230004
040230004
QUARTER
1
2
3
(!
9
11
4
EST
)0%
.1 (
.0 (
.5 (
. REL
CONF
6.
8.
3.
9
0
1
(continued)
. RMSE NO. OF
INTERVAL)
, 135.6)*
, 44.5)*
, 11.7)*
, 11.7)*
REPORTING
. RMSE
INTERVAL)
3.0)
8.6)
, 24.5)*
, 15.3)*
5.5)
, 17.9)*
, 10.9)*
REPORTING
. RMSE
INTERVAL)
, 20.9)*
, 45.5)*
, 14.4)*
, 23.5)*
, 29.5)*
6.2)
, 19.1)*
, 18.4)*
, 17.6)*
REPORTING
. RMSE
INTERVAL)
, 13.5)*
, 18.1)*
, 8.7)
OBSERVATIONS
1
1
26
26
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
13
12
10
8
25
18
43
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
27
5
10
12
12
11
42
35
77
ORGAN IZATI ON= 1 00
NO. OF
OBSERVATIONS
13
9
6
NO. OF
SAMPLER
QUARTERS
1
1
5
5
METHOD= 117
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
2
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
3
3
6
METHOD= 119
NO. OF
SAMPLER
QUARTERS
1
1
1
EST. REL. BIAS
(90% CONF. INTERVAL)
8.5
-2.8
EST. REL. BIAS
(90% CONF. INTERVAL)
-0.6 ( -1.6, 0.4)
0.2 ( -2.9, 3.2)
3.6 ( -5.6, 12.7)
-3.1 ( -9.1, 2.9)
EST. REL. BIAS
(90% CONF. INTERVAL)
-3. 1 ( -8.4, 2.2)
8.8 (-12.5, 30.0)
-0.4 ( -5.9, 5. 1)
1.2 ( -7.2, 9.6)
-8.6 (-18.0, 0.9)
0.2 ( -2.0, 2.5)
EST. REL. BIAS
(90% CONF. INTERVAL)
2.5 ( -2.0, 7.0)
2.7 ( -4.3, 9.7)
-1.0 ( -5.0, 3.0)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
040230004
A
A
A
A
A
QUARTER
4
1
2
3
4
A
(!
11
9
11
4
11
9
EST
)0%
.0 (
.1 (
.0 (
.5 (
.0 (
.7 (
. REL
CONF
8.
6.
8.
3.
8.
8.
. RMSE
(continued)
NO. OF
. INTERVAL)
4
9
0
1
4
3
STATE AZ
AIRS ID
040070008
040070008
040070008
A
A
A
A
QUARTER
1
2
4
1
2
4
A
EST
(90%
23
8
8
23
8
8
15
.8 (
.8 (
.6 (
.8 (
.8 (
.6 (
.5 (
. REL
CONF
16.
6.
6.
16.
6.
6.
12.
, 16.
, 13.
, 18.
8.
, 16.
, 11.
0)*
5)*
1)*
7)
0)*
9)*
REPORTING
. RMSE
. INTERVAL)
8
2
1
8
2
1
4
STATE -AZ
AIRS ID
040191028
040191028
040191028
A
A
A
A
QUARTER
2
3
4
2
3
4
A
EST
(90%
1
5
21
1
5
21
17
.3 (
.2 (
.0 (
.3 (
.2 (
.0 (
.3 (
. REL
CONF
0.
2.
14.
0.
2.
14.
12.
, 42.
, 15.
, 15.
, 42.
, 15.
, 15.
, 20.
7)*
8)*
4)*
7)*
8)*
4)*
8)*
REPORTING
. RMSE
. INTERVAL)
7
7
5
7
7
5
6
STATE CA
AIRS ID
060170011
061010003
060170011
QUARTER
1
1
2
(!
4
6
6
EST
)0%
.5 (
.4 (
.1 (
. REL
CONF
3.
4.
4.
5.
, 83.
, 40.
5.
, 83.
, 40.
, 28.
7)
5)*
3)*
7)
5)*
3)*
4)*
REPORTING
. RMSE
. INTERVAL)
0
8
5
9.
, 10.
, 10.
4)
0)
1)*
OBSERVATIONS
14
13
9
6
14
42
ORGAN IZATI ON= 1 00
NO. OF
OBSERVATIONS
7
7
7
7
7
7
21
ORGAN IZATI ON =300
NO. OF
OBSERVATIONS
2
1
6
2
1
6
9
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
5
11
9
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
4
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
3
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
3
METHOD= 117
NO. OF
SAMPLER
QUARTERS
1
1
1
EST. REL. BIAS
(90% CONF. INTERVAL)
5.2 ( 0.4, 9.9)
EST. REL. BIAS
(90% CONF. INTERVAL)
15.4 ( 1.0, 29.8)
2.3 ( -4.4, 9.0)
-1.3 ( -8.0, 5.5)
EST. REL. BIAS
(90% CONF. INTERVAL)
-0.2 ( -8.2, 7.7)
-5.2
11.5 ( -4.4, 27.4)
EST. REL. BIAS
(90% CONF. INTERVAL)
-2.8 ( -6.6, 1 .0)
1.2 ( -2.4, 4.8)
-2.0 ( -5.8, 1.8)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
061010003
060170011
061010003
060170011
061010003
A
A
A
A
A
QUARTER
2
3
3
4
4
1
2
3
4
A
(!
8
3
12
4
36
5
7
10
25
15
EST
)0%
.5 (
.9 (
.8 (
.0 (
.4 (
.9 (
.3 (
.2 (
.9 (
.1 (
. REL
CONF
6.
2.
9.
3.
26.
4.
5.
8.
20.
13.
. RMSE
(continued)
NO. OF
. INTERVAL)
1
9
8
0
9
6
8
2
7
4
STATE -C A
AIRS ID
060190008
060670006
060190008
060670006
060190008
060190008
060571001
060670006
A
A
A
A
A
QUARTER
1
1
2
2
3
4
4
4
1
2
3
4
A
(!
6
8
3
9
11
6
8
6
6
6
11
7
7
EST
)0%
.0 (
.6 (
.0 (
.8 (
.9 (
.4 (
.5 (
.3 (
.7 (
.7 (
.9 (
.0 (
.7 (
. REL
CONF
4.
5.
2.
7.
9.
4.
6.
4.
5.
5.
9.
5.
6.
, 14.
6.
, 19.
6.
, 58.
8.
, 10.
, 13.
, 35.
, 17.
6)*
5)
0)*
4)
0)*
3)
3)*
6)*
2)*
5)*
REPORTING
. RMSE
. INTERVAL)
7
8
3
2
0
9
1
6
4
4
0
8
9
STATE -C A
AIRS ID
060450006
060450006
A
A
A
QUARTER
1
2
1
2
A
(!
6
4
6
4
6
EST
)0%
.9 (
.5 (
.9 (
.5 (
.1 (
. REL
CONF
4.
2.
4.
2.
4.
8.
, 18.
4.
, 15.
, 18.
9.
, 14.
, 10.
8.
8.
, 18.
8.
8.
4)
1)*
3)
5)*
1)*
8)
6)*
0)
9)
8)
1)*
9)
8)
REPORTING
. RMSE
. INTERVAL)
9
9
9
9
6
, 12.
, 10.
, 12.
, 10.
9.
4)*
6)*
4)*
6)*
5)
OBSERVATIONS
8
9
13
10
10
16
17
22
20
75
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
17
5
14
10
12
12
8
10
22
24
12
30
88
ORGAN IZATI ON =004
NO. OF
OBSERVATIONS
7
4
7
4
11
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
2
2
2
2
8
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
2
2
1
3
8
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
EST. REL. BIAS
(90% CONF. INTERVAL)
-5.8 (-10.3, -1.2)
0.0 ( -2.6, 2.6)
-7.7 (-13.0, -2.4)
-2.2 ( -4.3, -0. 1)
-15.6 (-35.7, 4.5)
EST. REL. BIAS
(90% CONF. INTERVAL)
-0.4 ( -3.0, 2.3)
-3.8 (-12.1, 4.5)
0.3 ( -1 .2, 1.7)
-2.9 ( -8.6, 2.7)
1.0 ( -5.5, 7.4)
-3. 1 ( -6.2, -0. 1)
-1.2 ( -7.2, 4.9)
-0.4 ( -4.2, 3.4)
EST. REL. BIAS
(90% CONF. INTERVAL)
2.5 ( -2.6, 7.6)
0.3 ( -5.8, 6.3)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
060798001
060798001
060798001
060798001
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
EST
(90%
3.8 (
3.0 (
1.9 (
2.0 (
3.8 (
3.0 (
1.9 (
2.0 (
2.7 (
. REL
CONF
2.
2.
1 .
1 .
2.
2.
1 .
1 .
2.
7
2
4
5
7
2
4
5
3
STATE CA
AIRS ID
060271003
060290014
061110007
060271003
060290014
061110007
060271003
060290014
061110007
060290014
061110007
A
A
A
A
A
QUARTER
1
1
1
2
2
2
3
3
3
4
4
1
2
3
4
A
EST
(90%
18.9 (
7.6 (
6.3 (
1.2 (
4.9 (
2.3 (
8.4 (
4.3 (
3.8 (
10.0 (
9.1 (
10.8 (
3.7 (
4.8 (
9.7 (
7.6 (
. REL
CONF
12.
5.
4.
0.
3.
1 .
5.
3.
2.
7.
6.
8.
3.
3.
7.
6.
7
2
7
8
7
7
2
3
9
7
5
7
1
9
8
8
STATE CA
AIRS ID
060250005
060710014
060730006
060250005
060710014
060730006
060250005
QUARTER
1
1
1
2
2
2
3
EST
(90%
4.8 (
43.7 (
9.8 (
11.7 (
14.3 (
5.5 (
5.3 (
. REL
CONF
3.
30.
7.
8.
10.
3.
4.
7
1
3
6
8
7
0
. RMSE
INTERVAL)
6.5)
5.0)
, 3.1)
3.0)
6.5)
5.0)
, 3.1)
3.0)
, 3.4)
REPORTING
. RMSE
INTERVAL)
, 39.5)*
, 14.5)*
, 9.7)
3.6)
7.2)
, 3.7)
, 24.6)*
6.6)
5.8)
, 14.9)*
, 15.5)*
, 14.4)*
4.9)
6.2)
, 13.0)*
8.6)
REPORTING
. RMSE
INTERVAL)
7.0)
, 83.6)*
, 15.6)*
, 18.6)*
, 21.7)*
, 11.6)*
8.3)
NO. OF
OBSERVATIONS
8
9
9
12
8
9
9
12
38
ORGAN IZATI ON=0 1 9
NO. OF
OBSERVATIONS
5
6
11
3
13
10
3
12
12
13
8
22
26
27
21
96
ORGAN IZATI ON =036
NO. OF
OBSERVATIONS
14
6
10
10
12
5
11
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
3
3
3
2
11
METHOD= 119
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
EST
(90%
-3
0
-1
-0
. 1
.5
.0
.0
EST
(90%
-3
2
3
0
1
0
2
1
2
-3
5
.8
.6
.1
.3
. 1
.6
.9
.7
.3
.2
.4
EST
(90%
2
20
1
-3
5
-3
0
.0
.4
.5
.9
.3
.3
.3
. REL.
CONF.
( -4.7
( -1.4
( -2.1
( -1-1
. REL.
CONF.
(-23.6
( -3.7
( -0.1
( -2.2
( -1.3
( -0.8
(-13.5
( -0.5
( 0.7
( -8.1
( 0.1
. REL.
CONF.
( -0.2
(-14.4
( -4.4
(-10.6
( -1.9
( -8.1
( -2.8
BIAS
INTERVAL)
, -1.5)
2.5)
, 0.1)
1.1)
BIAS
INTERVAL)
, 15.9)
9.0)
6.2)
2.8)
3.6)
2.0)
, 19.2)
3.9)
3.9)
, 1.7)
, 10.6)
BIAS
INTERVAL)
4.1)
, 55.2)
, 7.5)
2.8)
, 12.5)
, 1.4)
, 3.4)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
060710014
060730006
060250005
060710014
060730006
A
A
A
A
A
QUARTER
3
3
4
4
4
1
2
3
4
A
EST
(90%
15.8 (
4.7 (
2.4 (
5.2 (
4.8 (
20.6 (
12.1 (
11.2 (
4.7 (
13.7 (
. REL
CONF
11 .
2.
1 .
4.
3.
17.
10.
9.
3.
12.
8
9
6
1
4
0
0
1
9
3
STATE -CO
AIRS ID
080010001
080410011
080770003
080010001
080410011
080770003
080010001
080410011
080770003
080010001
080410011
080770003
A
A
A
A
A
QUARTER
1
1
1
2
2
2
3
3
3
4
4
4
1
2
3
4
A
EST
(90%
27.6 (
4.7 (
2.7 (
10.2 (
17.8 (
13.0 (
2.1 (
12.8 (
6.2 (
1.6 (
14.3 (
4.4 (
11.1 (
11.9 (
5.6 (
6.8 (
8.9 (
. REL
CONF
17.
2.
2.
7.
10.
6.
1 .
7.
4.
1 .
9.
3.
8.
9.
4.
5.
7.
1
9
1
5
3
7
6
4
0
2
6
3
8
1
4
6
9
STATE CT
AIRS ID
090010010
090090018
090091123
090092123
QUARTER
1
1
1
1
EST
(90%
4.2 (
14.0 (
6.9 (
1.6 (
. REL
CONF
2.
9.
4.
1 .
9
4
3
0
(continued)
. RMSE NO. OF
INTERVAL)
, 24.4)*
, 13.9)*
5.0)
7.5)
8.6)
, 26.2)*
, 15.7)*
, 14.6)*
, 6.1)
, 15.4)*
REPORTING
. RMSE
INTERVAL)
, 80.5)*
, 13.7)*
3.9)
, 16.2)*
, 78.8)*
, 207.9)*
3.3)
, 56.6)*
, 14.8)*
2.5)
, 29.9)*
6.8)
, 15.0)*
, 17.7)*
, 7.8)
8.8)
, 10.3)*
REPORTING
. RMSE
INTERVAL)
8.0)
, 29.3)*
, 20.1)*
, 4.8)
OBSERVATIONS
11
3
5
15
7
30
27
25
27
109
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
3
3
14
10
2
1
11
2
4
11
5
11
20
13
17
27
77
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
6
5
3
3
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
3
3
3
3
12
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
3
3
3
3
12
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
EST
(90%
3
0
1
-1
1
.8
.7
.7
.7
.5
EST
(90%
-14
4
-0
-4
15
-13
0
9
4
-0
-6
-0
.1
.0
. 1
.3
.1
.0
.8
.0
.4
.3
.6
.4
EST
(90%
1
8
5
-0
.8
.5
.7
.1
. REL.
CONF.
( -5.0
( -9.0
( -0.1
( -4.0
( -2.2
. REL.
CONF.
(-63.0
( -1.3
( -1.5
( -9.9
(-45.4
( -0.4
(-48.5
( -1.6
( -1.3
(-20.1
( -2.9
. REL.
CONF.
( -1.5
( -3.4
( -2.1
( -3.4
BIAS
INTERVAL)
, 12.5)
, 10.4)
3.5)
0.6)
, 5.1)
BIAS
INTERVAL)
, 34 . 9)
9.2)
1.2)
, 1.3)
, 75.5)
1.9)
, 66 . 6)
, 10.4)
0.6)
, 7.0)
2.0)
BIAS
INTERVAL)
, 5.2)
, 20.4)
, 13.6)
3.3)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
EST. REL
AIRS ID
090010010
090090018
090091123
090092123
090010010
090090018
090091123
090092123
090010010
090090018
090091123
090092123
A
A
A
A
A
QUARTER
2
2
2
2
3
3
3
3
4
4
4
4
1
2
3
4
A
(90%
4.0
3.8
4.6
3.3
8.7
3.2
11.4
3.8
3.3
1.8
3.1
2.8
8.5
3.8
7.4
2.7
5.6
CONF.
( 3.0
( 2.8
( 3.1
( 2.6
( 6.9
( 2.6
( 9.1
( 2.9
( 2.6
( 1.5
( 2.5
( 2.2
( 6.7
( 3.2
( 6.6
( 2.4
( 5.2
STATE ~DC
EST. REL
AIRS ID
110010041
110010043
110010043
110010043
A
A
A
A
QUARTER
1
1
2
3
1
2
3
A
(90%
13.1
8.8
15.6
7.8
10.9
15.6
7.8
12.9
CONF.
( 9.4
( 6.5
( 12.2
( 5.1
( 8.6
( 12.2
( 5.1
( 10.9
STATE ~DE
EST. REL
AIRS ID
100031011
100032004
100031011
100032004
100031011
100032004
QUARTER
1
1
2
2
3
3
(90%
21.0
8.7
13.3
12.4
3.5
7.2
CONF.
(14.1
( 6.4
( 10.3
( 9.7
( 2.8
( 5.8
(continued)
. RMSE NO. OF
INTERVAL)
6.4)
6.1)
, 8.7)
, 4.7)
, 11.9)*
4.2)
, 15.6)*
, 5.3)
4.6)
2.3)
4.1)
3.9)
, 11.9)*
4.6)
8.6)
, 3.2)
6.0)
REPORTING
. RMSE
INTERVAL)
, 22.3)*
, 13.9)*
, 21.8)*
, 18.6)*
, 15.1)*
, 21.8)*
, 18.6)*
, 15.9)*
REPORTING
. RMSE
INTERVAL)
, 43.8)*
, 14.3)*
, 19.1)*
, 17.6)*
4.7)
9.5)
OBSERVATIONS
10
10
6
17
19
24
19
17
18
26
22
18
17
43
79
84
223
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
8
10
17
4
18
17
4
39
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
5
9
15
16
21
23
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
4
4
4
4
16
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
1
1
4
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
EST
(90%
2
-3
3
0
5
-2
-2
1
0
-0
-0
0
.7
.1
. 1
.8
.2
.0
.6
.5
. 1
.7
.2
. 1
EST
(90%
2
-0
-2
3
(9
-15
-3
4
-1
0
-0
.4
.5
.0
.8
EST
0%
.6
.4
.5
.0
.4
.2
. REL.
CONF
( o
( -4.
( 0.
( -0.
( 2
( -2
( -7.
( o
( -1
( -1
( -1
( -1
.9
.5
.1
.6
.3
.9
.2
.0
.3
.3
.3
.1
. REL.
CONF
( -6
( -5
( -8
( -5
.7
.8
.7
.6
. REL.
CONF
(-30
( -8
( -1
( -6
( -1
( -2
.5
.7
.3
.6
.0
.8
BIAS
INTERVAL)
4.5)
, -1.7)
6.1)
2.2)
8.0)
, -1.1)
1.9)
3.0)
, 1.6)
, -0.2)
, 1.0)
, 1.3)
BIAS
INTERVAL)
, 11.6)
4.9)
4.8)
, 13.1)
BIAS
INTERVAL)
, -0.7)
, 1.8)
, 10.4)
4.6)
, 1.7)
, 2.4)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
100031011
100031012
100032004
A
A
A
A
A
QUARTER
4
4
4
1
2
3
4
A
(!
2
4
4
14
12
5
4
9
EST
)0%
.9 (
.1 (
.8 (
.3 (
.9 (
.7 (
.1 (
.0 (
. REL
CONF
2.
2.
3.
11 .
10.
4.
3.
8.
. RMSE
(continued)
NO. OF
. INTERVAL)
2
8
8
0
7
9
4
1
STATE FL
AIRS ID
120330004
A
QUARTER
2
2
EST
(90%
12
12
.8 (
.8 (
. REL
CONF
9.
9.
4.
8.
6.
, 20.
, 16.
6.
5.
, 10.
3)
6)
6)
9)*
3)*
9)
1)
0)*
REPORTING
. RMSE
. INTERVAL)
3
3
STATE -FL
AIRS ID
120010023
A
QUARTER
4
4
EST
(90%
5
5
.3 (
.3 (
. REL
CONF
4.
4.
, 21.
, 21.
0)*
0)*
REPORTING
. RMSE
. INTERVAL)
0
0
STATE -FL
AIRS ID
121171002
121171002
121171002
A
A
A
A
QUARTER
2
3
4
2
3
4
A
(!
6
3
3
6
3
3
4
EST
)0%
.3 (
.1 (
.0 (
.3 (
.1 (
.0 (
.7 (
. REL
CONF
4.
2.
2.
4.
2.
2.
3.
8.
8.
1)
1)
REPORTING
. RMSE
. INTERVAL)
8
2
2
8
2
2
9
9.
5.
4.
9.
5.
4.
6.
6)
2)
9)
6)
2)
9)
0)
OBSERVATIONS
13
5
18
14
31
44
36
125
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
9
9
ORGAN IZATI ON =002
NO. OF
OBSERVATIONS
12
12
ORGAN IZATI ON =003
NO. OF
OBSERVATIONS
12
8
9
12
8
9
29
NO. OF
SAMPLER
QUARTERS
1
1
1
2
2
2
3
9
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
3
EST. REL. BIAS
(90% CONF. INTERVAL)
-1.3 ( -2.6, 0. 1)
-1.1 ( -5.3, 3.1)
-1.0 ( -3.0, 0.9)
EST. REL. BIAS
(90% CONF. INTERVAL)
0.9 (-7. 5, 9.3)
EST. REL. BIAS
(90% CONF. INTERVAL)
-0.9 ( -3.7, 2.0)
EST. REL. BIAS
(90% CONF. INTERVAL)
3.8 ( 1.1, 6.6)
0.4 ( -1.8, 2.6)
2.3 ( 1.0, 3.6)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
121056006
121056006
121056006
121056006
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
EST
(90%
6
8
5
4
6
8
5
4
6
.4 (
.8 (
.1 (
.8 (
.4 (
.8 (
.1 (
.8 (
.4 (
. REL
CONF
3.
6.
3.
3.
3.
6.
3.
3.
5.
. RMSE
. INTERVAL)
7
2
6
5
7
2
6
5
2
STATE FL
AIRS ID
120710005
120710005
A
A
A
QUARTER
1
4
1
4
A
EST
(90%
3
3
3
3
3
.7 (
.9 (
.7 (
.9 (
.9 (
. REL
CONF
2.
2.
2.
2.
2.
, 28.
, 15.
9.
7.
, 28.
, 15.
9.
7.
8.
3)*
9)*
2)
9)
3)*
9)*
2)
9)
3)
REPORTING
. RMSE
. INTERVAL)
2
8
2
8
9
STATE -FL
AIRS ID
121111002
121111002
121111002
121111002
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
EST
(90%
5
3
4
3
5
3
4
3
4
ST/
.7 (
.2 (
.7 (
.0 (
.7 (
.2 (
.7 (
.0 (
.4 (
iTF =
. REL
CONF
4.
2.
3.
2.
4.
2.
3.
2.
3.
FT
, 16.
6.
, 16.
6.
6.
5)*
7)
5)*
7)
2)
REPORTING
. RMSE
. INTERVAL)
3
4
2
1
3
4
2
1
7
8.
4.
9.
5.
8.
4.
9.
5.
5.
BFpnnT
6)
9)
8)
1)
6)
9)
8)
1)
4)
rwr.
NO. OF
OBSERVATIONS
2
7
7
9
2
7
7
9
25
ORGAN IZATI ON =005
NO. OF
OBSERVATIONS
2
8
2
8
10
ORGAN IZATI ON =006
NO. OF
OBSERVATIONS
12
11
5
8
12
11
5
8
36
nnr.AWT7ATTnw=ni 7
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
MFTHnn=i i s
EST. REL. BIAS
(90% CONF. INTERVAL)
5.5 (-15.4, 26.4)
2.7 ( -4.0, 9.3)
-3.1 ( -6.3, 0.2)
3.8 ( 1.9, 5.7)
EST. REL. BIAS
(90% CONF. INTERVAL)
3.4 ( -6.5, 13.3)
-1.0 ( -3.7, 1 .8)
EST. REL. BIAS
(90% CONF. INTERVAL)
2.9 ( 0.2, 5.5)
1.1 ( -0.6, 2.8)
3.0 ( -0.9, 6.9)
-0.7 ( -2.8, 1.4)
AIRS ID QUARTER
120111002 1
EST. REL. RMSE
(90% CONF. INTERVAL)
11.4 ( 8.4, 18.2)*
NO. OF
NO. OF SAMPLER
OBSERVATIONS QUARTERS
10
1
EST. REL. BIAS
(90% CONF. INTERVAL)
4.2 ( -2.3, 10.7)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
120111002
120111002
120111002
A
A
A
A
A
QUARTER
2
3
4
1
2
3
4
A
EST
(90%
12.4 (
4.0 (
3.2 (
11.4 (
12.4 (
4.0 (
3.2 (
9.7 (
. REL
CONF
9.
2.
2.
8.
9.
2.
2.
8.
1
8
2
4
1
8
2
1
STATE FL
AIRS ID
120952002
120952002
A
A
A
QUARTER
2
4
2
4
A
EST
(90%
15.7 (
11 .0 (
15.7 (
11.0 (
13.8 (
. REL
CONF
12.
8.
12.
8.
11 .
1
3
1
3
3
STATE -G A
AIRS ID
130210007
130510017
130892001
131210032
132150001
132450005
130210007
130510017
130892001
131210032
132150001
132450005
130210007
130510017
130892001
131210032
132150001
132450005
QUARTER
1
1
1
1
1
1
2
2
2
2
2
2
3
3
3
3
3
3
EST
(90%
10.0 (
6.3 (
24.7 (
13.5 (
3.2 (
3.6 (
4.1 (
8.2 (
6.2 (
8.5 (
9.7 (
8.4 (
11.1 (
6.7 (
8.7 (
5.3 (
6.8 (
12.8 (
. REL
CONF
7.
5.
18.
9.
2.
2.
3.
6.
4.
6.
7.
6.
8.
5.
6.
4.
5.
9.
3
0
6
5
1
6
0
0
6
0
5
3
4
0
5
0
1
4
(continued)
. RMSE NO. OF
INTERVAL)
, 19.7)*
, 7.2)
6.8)
, 18.2)*
, 19.7)*
, 7.2)
6.8)
, 12.2)*
REPORTING
. RMSE
INTERVAL)
, 23.0)*
, 16.7)*
, 23.0)*
, 16.7)*
, 17.9)*
REPORTING
. RMSE
INTERVAL)
, 16.5)*
8.7)
, 37.4)*
, 24.3)*
7.5)
, 6.1)
6.8)
, 13.0)*
, 10.3)*
, 15.3)*
, 13.9)*
, 13.1)*
, 16.8)*
, 10.7)*
, 13.6)*
8.0)
, 10.6)*
, 20.3)*
OBSERVATIONS
10
7
5
10
10
7
5
32
ORGANIZATION =020
NO. OF
OBSERVATIONS
14
12
14
12
26
ORGAN IZATI ON=0 1 0
NO. OF
OBSERVATIONS
9
19
12
7
4
8
9
10
9
7
15
11
12
10
11
12
11
10
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
EST
(90%
6
0
-1
.8
.8
.5
EST
(90%
2
-3
.5
.8
EST
(90%
-0
-1
-12
1
2
1
0
-5
-0
-0
2
4
-1
-1
-0
-3
1
-3
.7
.4
.1
.6
.2
.7
.5
.0
.5
.4
.2
.9
. 1
.6
.8
.0
.9
.2
. REL.
CONF.
( 0.5
( -2.3
( -4.6
. REL.
CONF.
( -5.1
( -9.4
. REL.
CONF.
( -7.3
( -4.0
(-23.7
( -9.0
( -0.8
( -0.5
( -2.2
( -8.9
( -4.6
( -7.1
( -2.2
( 0.9
( -7.1
( -5.6
( -5.8
( -5.3
( -1.8
(-10.8
BIAS
INTERVAL)
, 13.1)
3.9)
1.5)
BIAS
INTERVAL)
, 10.2)
1.8)
BIAS
INTERVAL)
5.8)
1.1)
, -0.4)
, 12.3)
5.3)
4.0)
3.2)
, -1.0)
3.5)
6.4)
6.6)
8.8)
4.9)
, 2.4)
, 4.2)
, -0.6)
, 5.7)
4.4)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
A
A
A
A
QUARTER
1
2
3
A
(!
13
8
8
10
EST
)0%
.3 (
.0 (
.9 (
.2 (
. REL
CONF
11 .
6.
7.
9.
5
9
8
4
STATE -HI
AIRS ID
150031001
150032004
150031001
150032004
A
A
A
QUARTER
1
1
2
2
1
2
A
(!
26
13
24
12
20
19
20
EST
)0%
.7 (
.2 (
.9 (
.9 (
.6 (
.8 (
.3 (
. REL
CONF
18.
9.
16.
8.
15.
14.
16.
4
3
2
4
7
3
3
STATE I A
AIRS ID
191532520
191532520
191532520
191532520
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
(!
5
3
2
2
5
3
2
2
3
EST
)0%
.3 (
.1 (
.1 (
.6 (
.3 (
.1 (
.1 (
.6 (
.0 (
. REL
CONF
3.
2.
1 .
2.
3.
2.
1 .
2.
2.
7
4
7
1
7
4
7
1
6
STATE I A
AIRS ID
191130037
191130037
191130037
QUARTER
1
2
3
(!
4
11
2
EST
)0%
.2 (
.3 (
.3 (
. REL
CONF
3.
8.
1 .
0
9
8
(continued)
. RMSE NO. OF
INTERVAL)
, 15.7)*
9.4)
, 10.4)*
, 11.2)*
REPORTING
. RMSE
INTERVAL)
, 51. 1)*
, 23.7)*
, 59.1)*
, 30.7)*
, 30.5)*
, 33.9)*
, 27.3)*
REPORTING
. RMSE
INTERVAL)
9.5)
, 4.6)
2.9)
3.6)
9.5)
, 4.6)
2.9)
3.6)
3.6)
REPORTING
. RMSE
INTERVAL)
7.2)
, 15.7)*
3.2)
OBSERVATIONS
59
61
66
186
ORGAN IZATION= 120
NO. OF
OBSERVATIONS
6
7
4
4
13
8
21
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
7
13
20
20
7
13
20
20
60
ORGAN IZATI ON =002
NO. OF
OBSERVATIONS
8
18
19
NO. OF
SAMPLER
QUARTERS
6
6
6
18
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
2
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
EST. REL. BIAS
(90% CONF. INTERVAL)
EST. REL. BIAS
(90% CONF. INTERVAL)
-7.9 (-30.9, 15.1)
-1.4 (-11.8, 9.0)
20.3 ( 0.6, 39.9)
-3.6 (-20.5, 13.3)
EST. REL. BIAS
(90% CONF. INTERVAL)
0. 1 ( -4.0, 4.3)
-1.1 ( -2.6, 0.4)
-0.8 ( -1.6, -0. 1)
-1.1 ( -2.1 , -0.2)
EST. REL. BIAS
(90% CONF. INTERVAL)
-0. 1 ( -3.2, 2.9)
3.4 ( -1.2, 7.9)
-0.1 ( -1.0, 0.9)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
191130037
A
A
A
A
A
QUARTER
4
1
2
3
4
A
EST
(90%
2.4 (
4.2 (
11.3 (
2.3 (
2.4 (
6.4 (
. REL
CONF
1 .
3.
8.
1 .
1 .
5.
9
0
9
8
9
6
STATE I A
AIRS ID
191630015
191630015
191550009
191630015
191550009
191630015
A
A
A
A
A
QUARTER
1
2
3
3
4
4
1
2
3
4
A
EST
(90%
4.0 (
4.8 (
2.9 (
1.9 (
4.8 (
2.4 (
4.0 (
4.8 (
2.2 (
3.6 (
3.6 (
. REL
CONF
3.
3.
2.
1 .
3.
1 .
3.
3.
1 .
3.
3.
1
9
2
5
8
9
1
9
9
1
3
STATE-ID
AIRS ID
160010011
160050015
160170001
160010011
160050015
160170001
160010011
160170001
160270004
160270004
160690009
160830010
A
A
QUARTER
1
1
1
2
2
2
3
3
3
4
4
4
1
2
EST
(90%
9.0 (
6.3 (
5.2 (
1.2 (
7.7 (
3.0 (
4.0 (
2.1 (
1.3 (
3.4 (
2.3 (
1.0 (
6.6 (
4.6 (
. REL
CONF
6.
4.
4.
0.
5.
2.
2.
1 .
0.
2.
1 .
0.
5.
3.
2
2
0
8
2
2
5
2
9
4
6
5
3
7
(continued)
. RMSE NO. OF
INTERVAL)
3.2)
, 7.2)
, 15.7)*
3.2)
3.2)
, 7.5)
REPORTING
. RMSE
INTERVAL)
5.6)
6.5)
4.4)
2.4)
6.5)
, 3.1)
5.6)
6.5)
2.8)
4.4)
4.0)
REPORTING
. RMSE
INTERVAL)
, 17.3)*
, 13.1)*
, 7.7)
2.9)
, 16.1)*
5.0)
, 11.8)*
9.3)
2.8)
, 6.1)
, 4.1)
, 15.7)*
, 8.7)
6.4)
OBSERVATIONS
19
8
18
19
19
64
ORGAN IZATI ON =003
NO. OF
OBSERVATIONS
17
22
12
24
20
25
17
22
36
45
120
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
6
5
13
4
5
9
3
2
5
7
7
1
24
18
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
2
2
6
METHOD= 117
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
3
3
EST
(90%
1
.0
EST
(90%
0
2
1
1
0
0
.9
.2
.2
.3
.7
.7
EST
(90%
-2
0
-2
-0
-7
0
-1
-1
-0
0
1
1
. 1
.3
.4
.4
.0
.1
.6
.5
.7
.9
.6
.0
. REL.
CONF.
( 0.2
. REL.
CONF.
( -0.8
( 0.6
( -0.3
( 0.9
( -LI
( -0.1
. REL.
CONF.
(-10.0
( -6.4
( -4.7
( -2.0
(-10.5
( -1.9
( -9.3
(-10.8
( -1.9
( -1.7
( 0.3
BIAS
INTERVAL)
1.9)
BIAS
INTERVAL)
2.6)
3.8)
2.6)
1.8)
2.6)
, 1.5)
BIAS
INTERVAL)
5.8)
, 7.0)
0.0)
1.1)
, -3.5)
, 2.1)
, 6.1)
7.9)
0.5)
3.5)
2.9)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
A
A
A
QUARTER
3
4
A
(!
2
2
4
EST
)0%
.6 (
.8 (
.9 (
. REL
CONF
1 .
2.
4.
. RMSE
(continued)
NO. OF
. INTERVAL)
9
2
3
STATE ID
AIRS ID
160550006
160550006
A
A
A
QUARTER
3
4
3
4
A
EST
(90%
4
1
4
1
3
.1 (
.8 (
.1 (
.8 (
.0 (
. REL
CONF
2.
1 .
2.
1 .
2.
4.
4.
5.
1)
0)
7)
REPORTING
. RMSE
. INTERVAL)
7
2
7
2
3
STATE I N
AIRS ID
180431004
180891016
180950009
180431004
180891016
180950009
181411008
181630006
A
A
A
QUARTER
1
1
1
2
2
2
2
2
1
2
A
(!
23
11
2
5
2
4
7
4
18
4
13
EST
)0%
.0 (
.5 (
.8 (
.5 (
.7 (
.1 (
.4 (
.5 (
.1 (
.7 (
.7 (
. REL
CONF
16.
7.
1 .
3.
1 .
2.
3.
2.
13.
3.
11.
8.
3.
8.
3.
4.
5)
4)
5)
4)
7)
REPORTING
. RMSE
. INTERVAL)
2
4
6
4
7
1
8
8
8
5
1
STATE I N
AIRS ID
180970081
180970083
180970081
180970083
QUARTER
1
1
2
2
EST
(90%
5
5
3
22
.3 (
.7 (
.7 (
.2 (
. REL
CONF
3.
4.
2.
16.
, 41.
, 27.
, 12.
, 16.
7.
, 65.
, 118.
, 13.
, 26.
7.
, 18.
4)*
2)*
4)*
0)*
9)
4)*
7)*
1)*
9)*
3)
0)*
REPORTING
. RMSE
. INTERVAL)
6
2
8
4
, 10.
9.
5.
, 35.
1)*
4)
7)
3)*
OBSERVATIONS
10
15
67
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
5
6
5
6
11
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
7
4
2
3
3
1
1
3
13
11
24
ORGAN IZATI ON =008
NO. OF
OBSERVATIONS
6
9
12
10
NO. OF
SAMPLER
QUARTERS
3
3
12
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
3
5
8
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
EST. REL. BIAS
(90% CONF. INTERVAL)
EST. REL. BIAS
(90% CONF. INTERVAL)
0.7 ( -3.6, 4.9)
-1.2 ( -2.4, 0.0)
EST. REL. BIAS
(90% CONF. INTERVAL)
9.2 ( -7.6, 25.9)
2.8 (-12.3, 17.9)
1.7 (-12.7, 16.0)
2.8 ( -7.0, 12.5)
0.4 ( -5.1, 5.9)
-4. 1
7.4
0.9 ( -8.1, 10.0)
EST. REL. BIAS
(90% CONF. INTERVAL)
-2.8 ( -6.8, 1.2)
0.5 ( -3.3, 4.2)
-0.7 ( -2.7, 1.3)
-6.9 (-19.7, 6.0)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
A
A
A
QUARTER
1
2
A
EST. REL
(90% CONF.
5.5 ( 4.3
15.2 ( 12.2
12.2 ( 10.3
CTATT7-1TC
AIRS ID
200910007
201070002
201730010
200910007
201070002
201730010
202090021
200910007
201070002
201730010
202090021
200910007
201070002
201730010
202090021
A
A
A
A
A
QUARTER
1
1
1
2
2
2
2
3
3
3
3
4
4
4
4
1
2
3
4
A
EST
(90%
7.1 (
3.7 (
27.0 (
28.6 (
13.2 (
13.9 (
11 .0 (
5.8 (
7.8 (
3.4 (
6.8 (
9.7 (
4.5 (
6.5 (
3.7 (
19.0 (
18.5 (
6.5 (
6.5 (
13.0 (
. REL
CONF.
4.8
2.6
19.9
20.8
9.1
10.0
8.0
4.3
5.7
2.2
5.2
7.2
3.2
4.8
2.7
15.3
15.4
5.5
5.5
11 .8
STATE -KY
AIRS ID
210190017
210590014
210670012
211950002
212270007
210190017
210590014
210670012
QUARTER
1
1
1
1
1
2
2
2
EST
(90%
10.4 (
34.5 (
10.0 (
9.9 (
15.0 (
6.4 (
6.2 (
13.0 (
. REL
CONF.
7.6
22.4
7.0
7.0
10.9
4.4
4.6
9.8
(continued)
. RMSE NO. OF
INTERVAL) OBSERVATIONS
8.0) 15
, 20.3)* 22
, 15.2)* 37
REPORTING nDrAWT7ATTnw_nm
. RMSE
INTERVAL)
, 14.
7.
, 42.
, 47.
, 25.
, 23.
, 18.
9.
, 12.
8.
, 10.
, 15.
7.
, 10.
5.
, 25.
, 23.
8.
8.
, 14.
8)*
1)
9)*
0)*
2)*
7)*
0)*
3)
9)*
2)
1)*
4)*
6)
3)*
7)
6)*
4)*
1)
1)
6)*
REPORTING
. RMSE
INTERVAL)
, 17.
, 81.
, 18.
, 17.
, 24.
, 12.
, 10.
, 20.
2)*
9)*
0)*
8)*
6)*
2)*
3)*
2)*
NO. OF
OBSERVATIONS
5
6
10
9
6
8
9
10
9
4
13
10
8
10
11
21
32
36
39
128
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
9
4
7
7
9
6
9
11
NO. OF
SAMPLER
QUARTERS
2
2
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
3
4
4
4
15
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
EST
(90%
EST
(90%
2
1
2
1
6
-4
3
-3
-2
1
-2
-2
-0
3
-2
.2
.8
.4
.3
.7
.7
.9
.0
.6
.4
.3
.0
. 1
.0
.6
EST
(90%
-2
13
1
2
9
-3
0
-1
.9
.9
.4
.0
.4
.5
.6
.2
. REL.
CONF.
. REL.
CONF.
( -4.9
( -1.2
(-14.0
(-17.5
( -3.5
(-14.0
( -2.8
( -6.1
( -7.5
( -2.9
( -5.6
( -7.8
( -3.3
( -0.5
( -4.1
. REL.
CONF.
( -9.5
(-29.0
( -6.4
( -5.8
( 1.7
( -8.3
( -3.5
( -8.6
BIAS
INTERVAL)
BIAS
INTERVAL)
9.4)
4.7)
, 18.8)
, 20.0)
, 16.9)
, 4.7)
, 10.6)
0.0)
2.2)
5.7)
, 1.0)
3.8)
3.1)
6.5)
, -1.1)
BIAS
INTERVAL)
, 3.7)
, 56.9)
9.3)
, 9.7)
, 17.0)
1.2)
, 4.7)
6.3)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
211950002
212270007
210190017
210590014
210670012
211950002
212270007
210190017
210590014
210670012
211950002
212270007
A
A
A
A
A
QUARTER
2
2
3
3
3
3
3
4
4
4
4
4
1
2
3
4
A
(!
20
22
3
4
2
3
4
5
2
4
2
2
15
16
3
3
10
EST
)0%
.7 (
.2 (
.1 (
.7 (
.6 (
.5 (
.6 (
.2 (
.5 (
.0 (
.2 (
.0 (
.9 (
.6 (
.7 (
.4 (
.9 (
. REL
CONF
15.
16.
2.
3.
2.
2.
3.
3.
1 .
3.
1 .
1 .
13.
14.
3.
3.
10.
8
9
4
5
0
7
5
9
9
0
5
5
4
4
3
0
1
STATE KY
AIRS ID
211110043
211110043
211110043
A
A
A
A
QUARTER
1
2
3
1
2
3
A
EST
(90%
19
4
5
19
4
5
10
.3 (
.1 (
.3 (
.3 (
.1 (
.3 (
.9 (
. REL
CONF
14.
3.
4.
14.
3.
4.
9.
4
2
0
4
2
0
2
STATE LA
AIRS ID
220171002
220330009
220550005
220710012
220171002
220330009
220550005
QUARTER
1
1
1
1
2
2
2
(!
8
14
7
15
5
5
15
EST
)0%
.6 (
.2 (
.3 (
.9 (
.2 (
.5 (
.9 (
. REL
CONF
6.
10.
5.
12.
4.
4.
12.
4
9
6
0
0
3
0
(continued)
. RMSE NO. OF
INTERVAL)
, 30.7)*
, 32.9)*
4.6)
7.3)
, 3.7)
, 5.1)
6.9)
, 8.1)
3.8)
6.1)
3.9)
2.9)
, 19.8)*
, 19.9)*
4.4)
, 4.1)
, 11.9)*
REPORTING
. RMSE
INTERVAL)
, 29.9)*
5.8)
7.8)
, 29.9)*
5.8)
7.8)
, 13.3)*
REPORTING
. RMSE
INTERVAL)
, 13.3)*
, 20.7)*
, 10.8)*
, 24.2)*
7.6)
, 7.9)
, 24.2)*
OBSERVATIONS
13
13
13
11
15
14
13
11
12
12
7
14
36
52
66
56
210
ORGAN IZATI ON =002
NO. OF
OBSERVATIONS
11
16
13
11
16
13
40
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
11
14
13
12
14
15
12
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
5
5
5
5
20
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
3
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
EST
(90%
9.3
-10.9
0.6
-1.0
2.0
0.7
1.4
-1.0
-0.1
0.8
1.9
0.9
EST
(90%
-2.5
-0. 1
1.2
EST
(90%
-3.5
-0.3
0.2
-7.7
2.5
3.7
-5.2
. REL.
CONF.
( -0.2
(-20.8
( -1.0
( -3.6
( 1.2
( -0.9
( -0.9
( -3.9
( -1.4
( -1.3
( LI
( 0.0
. REL.
CONF.
(-13.5
( -2.0
( -1.5
. REL.
CONF.
( -8.0
( -7.2
( -3.5
(-15.3
( 0.2
( 1.8
(-13.3
BIAS
INTERVAL)
, 18.8)
, -1.0)
2.1)
1.7)
2.8)
, 2.4)
3.7)
2.0)
, 1.3)
2.9)
, 2.7)
, 1.8)
BIAS
INTERVAL)
, 8.4)
1.7)
3.8)
BIAS
INTERVAL)
1.0)
6.7)
4.0)
, -0.1)
4.8)
5.6)
3.0)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
EST. REL
AIRS ID
220171002
220330009
220550005
220710012
220171002
220330009
220550005
220710012
A
A
A
A
A
QUARTER
3
3
3
3
4
4
4
4
1
2
3
4
A
(90%
5
10
5
2
3
3
7
2
12
9
7
4
8
CTi
.3
.8
.2
.1
.4
.3
.8
.6
.1
.7
.0
.8
.8
\TT7
CONF.
( 4.1
( 8.3
( 3.9
( 1.5
( 2.6
( 2.5
( 5.9
( 1.9
( 10.4
( 8.3
( 6.0
( 4.1
( 8.1
_ll \
EST. REL
AIRS ID
250130016
250210007
250230004
250250027
250270020
250130016
250230004
250250027
250270020
250130016
250210007
250230004
250250027
250270020
250130016
250210007
250230004
250250027
250270020
A
A
A
A
A
QUARTER
1
1
1
1
1
2
2
2
2
3
3
3
3
3
4
4
4
4
4
1
2
3
4
A
(90%
11
7
16
11
11
13
13
11
19
13
5
10
8
13
7
4
4
5
7
12
15
11
6
11
.1
.7
.3
.9
.2
.8
.3
.9
.3
.8
.0
.2
.4
.1
.6
.7
.9
.7
.0
.6
.3
.3
.3
.8
CONF.
( 8.7
( 4.4
( 12.7
( 8.9
( 9.0
( 11.3
( 10.3
( 9.1
( 15.6
( 11.1
( 3.4
( 8.2
( 6.8
( 10.5
( 6.1
( 3.7
( 3.6
( 4.2
( 5.5
( 11.1
( 13.5
( 10. 1
( 5.5
( 11.1
(continued)
. RMSE NO. OF
INTERVAL)
, 7.6)
, 15.8)*
, 7.8)
3.5)
4.9)
4.9)
, 11.6)*
, 4.1)
, 14.6)*
, 11.9)*
8.4)
5.8)
9.6)
REPORTING
. RMSE
INTERVAL)
, 15.5)*
, 33.8)*
, 23.2)*
, 18.4)*
, 15.1)*
, 17.9)*
, 19.1)*
, 17.7)*
, 25.6)*
, 18.5)*
, 10.5)*
, 13.7)*
, 11.2)*
, 17.5)*
, 10.3)*
, 6.4)
8.1)
9.0)
9.7)
, 14.7)*
, 17.7)*
, 12.9)*
, 7.2)
, 12.7)*
OBSERVATIONS
15
14
12
8
14
13
13
10
50
41
49
50
190
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
17
2
16
11
21
26
15
13
23
22
5
21
23
22
20
19
9
10
17
67
77
93
75
312
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
3
4
4
15
METHOD 120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
5
4
5
5
19
EST
(90%
2.8
5.9
0.4
-1.3
1.3
0.3
-0.3
-0.8
EST
(90%
-1.2
-5.4
8.6
-2. 1
2.7
4.6
5.9
2.1
9. 1
-1.8
-2.9
-2.4
1.0
-7.0
2.7
0.3
-2.7
2.3
-2.7
. REL.
CONF
( o
( 1
( -2
( -2
( -0.
( -1
( -4
( -2
.8
.5
.4
.4
.2
.5
.3
.3
. REL.
CONF
( -6
(-39
( 2
( -8
( -1
( o
( o
( -4
( 2
( -7
( -7
( -6
( -2
(-11
( -o
( -1
( -5
( -o
( -5
.0
.6
.4
.8
.5
.2
.3
.0
.9
.0
.3
.2
.1
.2
.2
.7
.4
.8
.5
BIAS
INTERVAL)
4.9)
, 10.4)
3.2)
, -0.2)
2.8)
2.0)
3.7)
, 0.7)
BIAS
INTERVAL)
3.6)
, 28.8)
, 14.9)
4.6)
6.9)
9.0)
, 11.5)
, 8.1)
, 15.4)
, 3.3)
, 1.5)
, 1.4)
4.1)
, -2.9)
5.5)
, 2.2)
, -0.0)
5.5)
, 0.1)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
245100035
A
QUARTER
4
4
EST
(90%
6
6
.6 (
.6 (
. REL
CONF
4.
4.
. RMSE
. INTERVAL)
1
1
STATE -ME
AIRS ID
230110016
230110016
230110016
230110016
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
(!
17
2
6
1
17
2
6
1
8
EST
)0%
.6 (
.9 (
.0 (
.7 (
.6 (
.9 (
.0 (
.7 (
.1 (
. REL
CONF
11 .
2.
4.
1 .
11 .
2.
4.
1 .
6.
, 19.
, 19.
1)*
1)*
REPORTING
. RMSE
. INTERVAL)
8
1
5
2
8
1
5
2
7
STATE -ME
AIRS ID
230050027
230050027
230050027
230050027
230190002
A
A
A
A
A
QUARTER
1
2
3
4
4
1
2
3
4
A
EST
(90%
5
8
2
2
5
5
8
2
3
3
.5 (
.4 (
.7 (
.7 (
.8 (
.5 (
.4 (
.7 (
.7 (
.8 (
. REL
CONF
3.
4.
2.
1 .
3.
3.
4.
2.
2.
3.
, 36.
5.
9.
2.
, 36.
5.
9.
2.
, 10.
8)*
3)
3)
9)
8)*
3)
3)
9)
2)*
REPORTING
. RMSE
. INTERVAL)
4
3
0
9
6
4
3
0
8
2
STATE M I
AIRS ID
260650012
260770008
260810020
QUARTER
1
1
1
(!
2
4
5
EST
)0%
.9 (
.6 (
.4 (
. REL
CONF
2.
3.
4.
, 16.
, 134.
4.
4.
, 16.
, 16.
, 134.
4.
5.
4.
1)*
4)*
0)
4)
9)*
1)*
4)*
0)
6)
9)
REPORTING
. RMSE
. INTERVAL)
3
5
3
4.
7.
7.
1)
2)
3)
NO. OF
OBSERVATIONS
3
3
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
5
7
11
8
5
7
11
8
31
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
3
1
12
9
3
3
1
12
12
28
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
16
11
21
NO. OF
SAMPLER
QUARTERS
1
1
METHOD= 117
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
2
5
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
EST. REL. BIAS
(90% CONF. INTERVAL)
0.4 (-13.2, 13.9)
EST. REL. BIAS
(90% CONF. INTERVAL)
7.7 ( -9.1 , 24.6)
1.1 ( -1.1, 3.2)
-0.6 ( -4.0, 2.9)
0.1 (-1.1, 1.3)
EST. REL. BIAS
(90% CONF. INTERVAL)
-5.4 ( -8.1 , -2.6)
8.4
0.8 ( -0.6, 2.2)
1.0 ( -0.6, 2.6)
4.8 ( -2.0, 11 .5)
EST. REL. BIAS
(90% CONF. INTERVAL)
-1.0 ( -2.2, 0.3)
-3.4 ( -5.2, -1.6)
0.1 ( -2.0, 2.2)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
261210040
261450018
260650012
260770008
260810020
261210040
261450018
261630001
260650012
260770008
260810020
261210040
261450018
261630001
260650012
260770008
260810020
261210040
261450018
261630001
A
A
A
A
A
QUARTER
1
1
2
2
2
2
2
2
3
3
3
3
3
3
4
4
4
4
4
4
1
2
3
4
A
EST.
REL
(90% CONF.
4.4 (
1.3 (
9.8 (
6.0 (
5.1 (
5.4 (
3.0 (
4.8 (
5.0 (
3.5 (
4.3 (
3.7 (
4.4 (
6.7 (
2.3 (
2.7 (
4.0 (
3.1 (
2.3 (
5.1 (
4.4 (
6.4 (
4.7 (
3.2 (
4.7 (
3.2
0.7
7.4
4.6
3.4
3.8
2.2
3.3
4.0
2.8
3.3
2.5
3.5
5.0
1.8
2.2
2.9
2.3
1 .6
3.8
3.9
5.5
4. 1
2.8
4.4
STATE MN
AIRS ID
271377550
271230866
271230868
271377550
271230866
271230868
271377550
A
A
A
A
QUARTER
2
3
3
3
4
4
4
2
3
4
A
EST.
REL
(90% CONF.
4.2 (
4.1 (
9.3 (
3.9 (
7.2 (
3.3 (
5.0 (
4.2 (
6.7 (
5.4 (
6.0 (
2.4
3.0
6.7
2.4
5.2
2.5
3.2
2.4
5.3
4.4
5. 1
(continued)
. RMSE NO. OF
INTERVAL)
, 7.3)
5.6)
, 14.8)*
8.6)
, 10.6)*
9.6)
, 4.8)
, 9.1)
6.6)
, 4.8)
6.3)
7.7)
6.3)
, 10.7)*
, 3.1)
, 3.5)
, 6.3)
5.0)
4.4)
8.5)
, 5.2)
, 7.6)
, 5.3)
, 3.7)
5.0)
REPORTING
. RMSE
INTERVAL)
, 18.4)*
6.8)
, 15.9)*
, 11.4)*
, 11.8)*
5.3)
, 11.8)*
, 18.4)*
9.0)
, 7.2)
, 7.2)
OBSERVATIONS
9
2
12
15
5
7
10
6
22
19
13
5
16
10
20
25
10
10
6
9
59
55
85
80
279
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
2
9
8
3
9
10
4
2
20
23
45
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
5
6
6
6
23
METHOD-120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
3
3
7
EST
(90%
2.3
1.3
2.6
-0.7
0.5
1.9
1.4
-3.9
2.6
-0.7
-0.3
3.3
-0.9
0. 1
0.4
-0.9
1.9
-2.5
-0.9
2.8
EST
(90%
3.6
-0.2
-5.5
1.0
6.4
-0.3
1.6
. REL.
CONF.
( -0.2
( 0.7
( -2.5
( -3.5
( -4.8
( -2.1
( -0.2
( -6.4
( 1.0
( -2.1
( -2.5
( 1.5
( -2.9
( -4.0
( -0.5
( -1.7
( -0.3
( -3.7
( -2.8
( -0.1
. REL.
CONF.
(-10.1
( -2.9
(-10.8
( -6.8
( 4.4
( -2.4
( -4.8
BIAS
INTERVAL)
4.8)
, 1.8)
7.7)
2.0)
5.9)
5.8)
3.1)
, -1.5)
, 4.2)
, 0.7)
, 1.9)
, 5.1)
1.1)
4.2)
1.3)
0.0)
4.0)
, -1.3)
, 1.0)
5.6)
BIAS
INTERVAL)
, 17.2)
, 2.5)
, -0.1)
8.8)
8.5)
, 1.7)
8.0)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
290210010
290470026
291831002
290210010
290470026
291831002
290210010
290470026
291831002
290210010
290470026
291831002
A
A
A
A
A
QUARTER
1
1
1
2
2
2
3
3
3
4
4
4
1
2
3
4
A
EST
(90%
2
2
2
6
2
2
3
2
2
2
3
2
2
4
2
2
3
.2 (
.5 (
.7 (
.5 (
.9 (
.3 (
.3 (
.1 (
.3 (
.0 (
.5 (
.1 (
.5 (
.4 (
.5 (
.4 (
.1 (
. REL
CONF.
1 .6
1 .8
1.9
5.0
2. 1
1.8
2.5
1 .5
1.8
1.6
2.6
1.7
2.0
3.7
2.2
2. 1
2.8
STATE MO
AIRS ID
291892003
A
QUARTER
2
2
(!
3
3
EST
)0%
.8 (
8 (
. REL
CONF.
2.8
2.8
STATE MO
AIRS ID
295100085
295100085
A
A
A
QUARTER
3
4
3
4
A
(!
3
14
3
14
10
EST
)0%
.5 (
.6 (
.5 (
.6 (
.9 (
. REL
CONF.
3.1
12.9
3. 1
12.9
10.0
. RMSE
INTERVAL)
3.
4.
4.
9.
4.
3.
5.
3.
3.
2.
5.
2.
3.
5.
3.
2.
3.
7)
2)
8)
2)
9)
1)
1)
3)
0)
6)
4)
7)
2)
3)
1)
8)
4)
REPORTING
. RMSE
INTERVAL)
6.
6.
3)
3)
REPORTING
. RMSE
INTERVAL)
4.
, 16.
4.
, 16.
, 12.
1)
8)*
1)
8)*
1)*
NO. OF
OBSERVATIONS
9
9
7
16
8
20
11
10
24
23
11
24
25
44
45
58
172
ORGAN IZATI ON =002
NO. OF
OBSERVATIONS
9
9
ORGAN IZATI ON =003
NO. OF
OBSERVATIONS
66
77
66
77
143
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
3
3
3
3
12
METHOD= 117
NO. OF
SAMPLER
QUARTERS
1
1
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
EST
(90%
0.4
0.4
-1.3
1.3
1.2
-0.7
1.9
0.8
-0.3
0.7
0.2
0.3
EST
(90%
0. 1
EST
(90%
-0.6
-0.8
. REL.
CONF.
( -1.0
( -1.2
( -3.1
( -1.6
( -0.7
( -1.6
( 0.3
( -0.4
( -LI
( -0.0
( -1.8
( -0.4
. REL.
CONF.
( -2.4
. REL.
CONF.
( -1.3
( -3.6
BIAS
INTERVAL)
1.9)
2.0)
0.6)
4.1)
3.0)
, 0.1)
, 3.4)
1.9)
0.5)
, 1.4)
2.2)
, 1.0)
BIAS
INTERVAL)
2.7)
BIAS
INTERVAL)
, 0.1)
, 1.9)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
290770032
290770032
290770032
290770032
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
EST
(90%
4.4 (
3.7 (
3.4 (
2.6 (
4.4 (
3.7 (
3.4 (
2.6 (
3.6 (
. REL
CONF
3.
2.
2.
2.
3.
2.
2.
2.
3.
4
7
5
0
4
7
5
0
1
STATE MS
AIRS ID
280330002
280350004
281210001
280330002
280350004
281210001
280330002
280350004
281210001
A
A
A
A
QUARTER
1
1
1
2
2
2
3
3
3
1
2
3
A
EST
(90%
6.3 (
7.2 (
28.4 (
15.2 (
6.3 (
15.6 (
5.3 (
6.4 (
12.9 (
17.8 (
13.0 (
8.4 (
12.3 (
. REL
CONF
4.
4.
19.
11.
4.
11.
4.
4.
9.
13.
10.
7.
11.
2
7
1
5
8
7
1
8
5
7
9
0
0
STATE MT
AIRS ID
300630024
300630024
300630024
300530018
300630024
A
A
A
A
A
QUARTER
1
2
3
4
4
1
2
3
4
A
EST
(90%
9.1 (
18.9 (
3.3 (
1.8 (
1.3 (
9.1 (
18.9 (
3.3 (
1.6 (
8.6 (
. REL
CONF
6.
13.
2.
1 .
0.
6.
13.
2.
1 .
7.
4
1
3
3
9
4
1
3
3
3
. RMSE
INTERVAL)
6.4)
5.8)
5.3)
4.1)
6.4)
5.8)
5.3)
4.1)
4.4)
REPORTING
. RMSE
INTERVAL)
, 13.2)*
, 17.1)*
, 59.4)*
, 23.0)*
9.6)
, 24.2)*
, 7.6)
, 10.0)
, 20.5)*
, 26.0)*
, 16.3)*
, 10.4)*
, 14.1)*
REPORTING
. RMSE
INTERVAL)
, 16.3)*
, 36.2)*
6.0)
2.7)
2.3)
, 16.3)*
, 36.2)*
6.0)
2.2)
, 10.7)*
NO. OF
OBSERVATIONS
14
10
11
11
14
10
11
11
46
ORGAN IZATI ON= 1 00
NO. OF
OBSERVATIONS
5
4
5
12
12
11
15
11
10
14
35
36
85
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
7
6
7
11
7
7
6
7
18
38
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
3
3
3
9
METHOD= 116
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
2
5
EST
(90%
2
2
1
0
.9
.0
.9
.3
EST
(90%
4
3
17
2
1
6
1
1
-4
.8
.7
.5
.3
.0
.3
.6
. 1
.3
EST
(90%
4
-6
1
0
-0
.8
.9
.3
.8
.3
. REL.
CONF.
( 1.3
( 0.1
( 0.3
( -1-2
. REL.
CONF.
( 0.5
( -4.8
( -6.5
( -5.8
( -2.4
( -1.9
( -0.8
( -2.5
(-11.7
. REL.
CONF.
( -1.3
(-22.8
( -LI
( -0.1
( -1.3
BIAS
INTERVAL)
4.5)
3.9)
3.5)
1.8)
BIAS
INTERVAL)
9.2)
, 12.1)
, 41.4)
, 10.4)
4.4)
, 14.5)
3.9)
4.8)
3.2)
BIAS
INTERVAL)
, 10.9)
8.9)
3.8)
1.7)
0.7)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
370510009
370710016
371210001
371290009
371470005
371830014
370510009
370710016
370810009
371210001
371290009
371470005
371830014
A
A
A
QUARTER
3
3
3
3
3
3
4
4
4
4
4
4
4
3
4
A
EST
(90%
3.4 (
2.1 (
2.8 (
4.5 (
4.0 (
2.8 (
5.5 (
1.7 (
8.8 (
12.6 (
1.9 (
12.9 (
5.5 (
3.3 (
7.7 (
5.9 (
. REL
CONF
2.
1 .
2.
3.
3.
2.
4.
1 .
5.
9.
1 .
8.
4.
2.
6.
5.
4
6
1
3
1
0
1
3
4
3
4
9
1
9
7
3
STATE -NC
AIRS ID
370670024
370670024
370670024
370670024
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
EST
(90%
5.3 (
7.0 (
5.4 (
3.6 (
5.3 (
7.0 (
5.4 (
3.6 (
5.6 (
. REL
CONF
4.
5.
4.
2.
4.
5.
4.
2.
4.
0
4
0
7
0
4
0
7
8
STATE NC
AIRS ID
371190034
371190034
371190034
371190040
371190040
A
A
QUARTER
1
2
3
3
4
1
2
EST
(90%
6.2 (
4.7 (
1.8 (
2.3 (
1.6 (
6.2 (
4.7 (
. REL
CONF
4.
3.
1 .
1 .
1 .
4.
3.
7
6
1
6
2
7
6
. RMSE
INTERVAL)
5.8)
3.1)
, 4.2)
7.4)
6.1)
, 4.8)
8.6)
2.7)
, 25.6)*
, 20.1)*
3.2)
, 24.7)*
, 8.7)
3.9)
9.1)
6.6)
REPORTING
. RMSE
INTERVAL)
8.3)
, 10.2)*
8.6)
5.5)
8.3)
, 10.2)*
8.6)
5.5)
, 6.7)
REPORTING
. RMSE
INTERVAL)
9.5)
7.0)
, 4.2)
3.9)
2.5)
9.5)
, 7.0)
NO. OF
OBSERVATIONS
8
13
12
9
12
8
11
11
3
10
8
6
10
62
59
121
ORGAN IZATI ON =002
NO. OF
OBSERVATIONS
11
14
10
12
11
14
10
12
47
ORGAN IZATI ON =003
NO. OF
OBSERVATIONS
12
13
4
8
10
12
13
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
1
6
7
13
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
EST
(90%
-1.5
1. 1
0.5
0.6
2.2
0.6
-4.3
0.9
-2.4
5.2
0.6
3.9
0.4
EST
(90%
0.4
-2.0
0.1
-2. 1
EST
(90%
1.0
-1.4
-0.8
-0.0
-0.0
. REL.
CONF
( -3.
( o
( -1
( -2.
( 0.
( -1.
( -6.
( 0.
.7
.2
.0
.3
.4
.3
.3
.1
(-19.8
( -1.
( -o.
( -7.
( -2.
.8
.7
.1
.9
. REL.
CONF
( -2.
( -5.
( -3.
( -3.
.7
.3
.2
.7
. REL.
CONF
( -2.
( -3.
( -2.
( -1.
( -1.
.3
.7
.9
.7
.0
BIAS
INTERVAL)
0.7)
2.1)
2.0)
3.6)
4.0)
2.6)
, -2.3)
1.8)
, 15.0)
, 12.2)
1.9)
, 15.0)
3.8)
BIAS
INTERVAL)
3.4)
1.3)
, 3.4)
, -0.5)
BIAS
INTERVAL)
4.3)
0.9)
, 1.3)
, 1.6)
0.9)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
A
A
A
QUARTER
3
4
A
(!
2
1
4
EST
)0%
.1 (
.6 (
.2 (
. REL
CONF
1 .
1 .
3.
. RMSE
(continued)
NO. OF
. INTERVAL)
6
2
6
STATE NC
AIRS ID
370210034
370210034
370210034
370210034
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
EST
(90%
7
7
2
6
7
7
2
6
6
.5 (
.4 (
.6 (
.6 (
.5 (
.4 (
.6 (
.6 (
.2 (
. REL
CONF
5.
5.
2.
4.
5.
5.
2.
4.
5.
3.
2.
5.
2)
5)
1)
REPORTING
. RMSE
. INTERVAL)
5
5
0
9
5
5
0
9
3
STATE ND
AIRS ID
380570004
380570004
380570004
380570004
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
EST
(90%
17
15
14
7
17
15
14
7
15
.0 (
.7 (
.3 (
.4 (
.0 (
.7 (
.3 (
.4 (
.2 (
. REL
CONF
12.
8.
9.
4.
12.
8.
9.
4.
12.
, 11.
, 11.
3.
, 10.
, 11.
, 11.
3.
, 10.
7.
9)*
5)*
8)
5)*
9)*
5)*
8)
5)*
5)
REPORTING
. RMSE
. INTERVAL)
8
0
9
6
8
0
9
6
3
STATE ND
AIRS ID
380171004
380171004
QUARTER
1
2
(!
5
11
EST
)0%
.9 (
.9 (
. REL
CONF
4.
8.
, 25.
, 250.
, 27.
, 21.
, 25.
, 250.
, 27.
, 21.
, 20.
7)*
6)*
3)*
7)*
7)*
6)*
3)*
7)*
3)*
REPORTING
. RMSE
. INTERVAL)
4
7
9.
, 19.
2)
5)*
OBSERVATIONS
12
10
47
ORGAN IZATI ON =004
NO. OF
OBSERVATIONS
10
11
13
10
10
11
13
10
44
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
12
1
6
3
12
1
6
3
22
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
11
9
NO. OF
SAMPLER
QUARTERS
2
1
5
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD= 117
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
EST. REL. BIAS
(90% CONF. INTERVAL)
EST. REL. BIAS
(90% CONF. INTERVAL)
3.6 ( -0.4, 7.6)
1.0 ( -3.3, 5.2)
1.3 ( 0.2, 2.5)
-1.6 ( -5.5, 2.4)
EST. REL. BIAS
(90% CONF. INTERVAL)
-4.3 (-13.2, 4.6)
15.7
6.3 ( -5.2, 17.9)
-2.8 (-17.0, 11.4)
EST. REL. BIAS
(90% CONF. INTERVAL)
-0.8 ( -4.2, 2.6)
3.8 ( -3.6, 11.2)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
380171004
380171004
A
A
A
A
A
QUARTER
3
4
1
2
3
4
A
(!
4
4
5
11
4
4
6
EST
)0%
.3 (
.0 (
.9 (
.9 (
.3 (
.0 (
.5 (
. REL
CONF
3.
3.
4.
8.
3.
3.
5.
. RMSE
(continued)
NO. OF
. INTERVAL)
3
2
4
7
3
2
6
STATE -NE
AIRS ID
311090022
311530007
311090022
311530007
311090022
311530007
311090022
311530007
A
A
A
A
A
QUARTER
1
1
2
2
3
3
4
4
1
2
3
4
A
EST
(90%
4
25
4
5
4
8
4
6
11
5
7
5
7
.4 (
.1 (
.8 (
.7 (
.6 (
.7 (
.1 (
.9 (
.0 (
.3 (
.0 (
.9 (
.5 (
. REL
CONF
3.
14.
3.
3.
3.
6.
2.
5.
8.
3.
5.
4.
6.
6.
5.
9.
, 19.
6.
5.
7.
5)
4)
2)
5)*
5)
4)
7)
REPORTING
. RMSE
. INTERVAL)
3
5
2
9
3
4
9
1
3
9
5
6
5
STATE -NE
AIRS ID
310550019
310550052
310550019
310550052
A
A
A
QUARTER
3
3
4
4
3
4
A
(!
7
9
12
4
7
7
7
EST
)0%
.2 (
.8 (
.2 (
.7 (
.9 (
.1 (
.4 (
. REL
CONF
4.
5.
7.
3.
5.
5.
5.
7.
, 110.
, 10.
, 12.
7.
, 14.
7.
, 11.
, 16.
8.
9.
8.
8.
0)
7)*
1)*
0)*
5)
3)*
5)
4)*
7)*
4)
6)
3)
9)
REPORTING
. RMSE
. INTERVAL)
4
0
0
4
1
2
6
, 20.
, 156.
, 53.
8.
, 18.
, 11.
, 10.
9)*
2)*
8)*
5)
7)*
7)*
9)*
OBSERVATIONS
12
21
11
9
12
21
53
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
10
2
5
5
9
9
7
9
12
10
18
16
56
ORGAN IZATI ON =003
NO. OF
OBSERVATIONS
3
1
2
7
4
9
13
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
2
2
2
2
8
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
2
4
EST. REL. BIAS
(90% CONF. INTERVAL)
0.2 ( -2.1 , 2.6)
-0.6 ( -2.2, 0.9)
EST. REL. BIAS
(90% CONF. INTERVAL)
0.8 ( -1.9, 3.4)
20.4 (-71.6, 112.4)
-0.5 ( -5.6, 4.6)
4.0 ( -0.5, 8.4)
2.0 ( -0.7, 4.7)
7.5 ( 4.5, 10.4)
0.4 ( -2.8, 3.7)
-0.8 ( -5.3, 3.8)
EST. REL. BIAS
(90% CONF. INTERVAL)
-2.4 (-16.3, 11.6)
9.8
12.1 ( 5.6, 18.7)
1.0 ( -2.7, 4.7)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
340070003
340390004
340070003
340390004
340070003
340390004
340070003
340390004
A
A
A
A
A
QUARTER
1
1
2
2
3
3
4
4
1
2
3
4
A
EST
(90%
0
6
17
8
19
2
10
5
4
15
13
7
11
.6 (
.8 (
.3 (
.5 (
.2 (
.7 (
.3 (
.7 (
.8 (
.3 (
.2 (
.7 (
.7 (
. REL
CONF
0.
4.
13.
5.
14.
2.
7.
4.
3.
12.
10.
6.
10.
4
2
1
7
4
0
5
4
3
0
7
3
3
STATE -NM
AIRS ID
350450006
350490020
350450006
350450006
350490020
350450006
350490020
A
A
A
A
A
QUARTER
1
1
2
3
3
4
4
1
2
3
4
A
(!
3
2
0
2
5
3
1
3
0
4
3
3
EST
)0%
.2 (
.8 (
.9 (
.3 (
.0 (
.5 (
.8 (
.1 (
.9 (
.1 (
.2 (
.2 (
. REL
CONF
2.
1 .
0.
1 .
3.
2.
1 .
2.
0.
2.
2.
2.
3
8
5
3
1
9
3
3
5
8
7
8
STATE NM
AIRS ID
350010023
350010023
A
A
A
QUARTER
3
4
3
4
A
(!
4
4
4
4
4
EST
)0%
.6 (
.6 (
.6 (
.6 (
.6 (
. REL
CONF
3.
4.
3.
4.
4.
5
0
5
0
0
. RMSE
INTERVAL)
1.8)
, 19.7)*
, 26.3)*
, 17.7)*
, 29.8)*
4.0)
, 16.9)*
8.2)
9.2)
, 21.4)*
, 17.3)*
, 10.2)*
, 13.6)*
REPORTING
. RMSE
INTERVAL)
5.4)
, 6.7)
, 14.9)*
, 10.3)*
, 14.5)*
, 4.6)
3.1)
4.6)
, 14.9)*
8.6)
4.0)
3.9)
REPORTING
. RMSE
INTERVAL)
6.9)
5.5)
6.9)
5.5)
5.4)
NO. OF
OBSERVATIONS
3
3
12
5
11
13
9
15
6
17
24
24
71
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
8
4
1
2
3
25
8
12
1
5
33
51
ORGAN IZATI ON =002
NO. OF
OBSERVATIONS
13
55
13
55
68
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
2
2
2
2
8
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
2
1
2
2
7
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
EST. REL.
(90% CONF.
0
4
-1
-0
-1
-1
4
-2
.5 ( -0.3
.6 ( -5.7
.9 (-11.2
. 1 ( -9.1
.1 (-12.1
.4 ( -2.5
.9 ( -1.0
.2 ( -4.7
EST. REL.
(90% CONF.
-0
-1
-0
-1
-2
-0
-0
.3 ( -2.6
.5 ( -4.7
.9
.6 (-12.0
. 1 (-11 .4
.2 ( -1.4
.2 ( -1.5
EST. REL.
(90% CONF.
0
-2
.0 ( -2.4
.0 ( -2.9
BIAS
INTERVAL)
1.3)
, 14.8)
, 7.4)
8.9)
9.9)
, -0.2)
, 10.9)
0.2)
BIAS
INTERVAL)
2.0)
, 1.8)
8.7)
7.1)
, 1.0)
1.1)
BIAS
INTERVAL)
2.4)
, -1.0)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
320310016
320310016
320310016
320310016
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
EST
(90%
4.6 (
3.9 (
2.4 (
2.8 (
4.6 (
3.9 (
2.4 (
2.8 (
3.4 (
. REL
CONF
3.
2.
1 .
2.
3.
2.
1 .
2.
2.
3
9
7
2
3
9
7
2
9
STATE NY
AIRS ID
360010005
360050073
360470011
360556001
360610056
360610062
360632008
360671015
360810094
360010005
360050110
360556001
360610056
360610062
360632008
360671015
360810094
A
A
A
QUARTER
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
3
4
A
EST
(90%
3.7 (
7.7 (
3.3 (
5.1 (
5.2 (
3.6 (
6.4 (
4.4 (
2.7 (
1.9 (
5.3 (
3.2 (
2.4 (
2.4 (
3.0 (
4.9 (
7.4 (
5.1 (
4.4 (
4.7 (
. REL
CONF
2.
4.
1 .
3.
3.
2.
5.
3.
1 .
1 .
4.
2.
1 .
1 .
2.
3.
5.
4.
4.
4.
5
8
7
6
7
7
0
2
6
3
0
4
7
9
4
6
8
4
0
3
STATE OH
AIRS ID
390811001
390811001
A
QUARTER
3
4
3
EST
(90%
3.0 (
1.8 (
3.0 (
. REL
CONF
2.
1 .
2.
2
2
2
. RMSE
INTERVAL)
8.3)
6.3)
, 4.1)
4.1)
8.3)
6.3)
, 4.1)
4.1)
, 4.2)
REPORTING
. RMSE
INTERVAL)
, 7.0)
, 22.5)*
, 53.1)*
9.2)
8.8)
, 5.4)
9.0)
7.2)
, 12.0)*
3.9)
8.2)
5.0)
, 4.7)
3.5)
4.1)
, 7.7)
, 10.5)*
6.0)
, 5.1)
, 5.2)
REPORTING
. RMSE
INTERVAL)
4.6)
3.8)
, 4.6)
NO. OF
OBSERVATIONS
7
10
8
15
7
10
8
15
40
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
6
3
1
7
8
12
16
9
2
5
11
11
6
16
18
10
16
64
93
157
ORGAN IZATI ON =004
NO. OF
OBSERVATIONS
11
5
11
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
9
8
17
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
EST
(90%
-1
1
0
0
.2
.3
.9
. 1
EST
(90%
1
-7
3
-4
3
1
-0
-1
2
1
2
-1
0
-0
0
-1
1
.0
.4
.3
.4
.6
.2
.6
.6
.0
.5
.6
.6
.9
. 1
.9
.7
.2
EST
(90%
-0
0
.9
.9
. REL.
CONF.
( -4.7
( -1.0
( -0.7
( -1.3
. REL.
CONF.
( -2.1
(-11 .5
( -6.5
( 1.0
( -0.6
( -3.5
( -4.3
( -9.3
( 0.3
( -0.1
( -3.2
( -LI
( -1-2
( -0.3
( -4.5
( -2.1
. REL.
CONF.
( -2.6
( -0.8
BIAS
INTERVAL)
2.4)
3.6)
, 2.5)
1.4)
BIAS
INTERVAL)
, 4.2)
, -3.4)
, -2.3)
6.2)
3.0)
2.2)
1.1)
, 13.4)
, 2.7)
5.2)
0.0)
3.0)
1.1)
2.1)
, 1.1)
, 4.5)
BIAS
INTERVAL)
0.7)
2.6)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
A
A
AIRS ID
391530017
391530017
391530017
391530017
A
A
A
A
A
QUARTER
4
A
QUARTER
1
2
3
4
1
2
3
4
A
EST
(90%
1.8 (
2.7 (
EST
(90%
7.7 (
7.8 (
4.4 (
2.8 (
7.7 (
7.8 (
4.4 (
2.8 (
6.4 (
. REL
CONF.
1 .2
2.1
. REL
CONF.
5.8
6.0
3.4
1 .9
5.8
6.0
3.4
1 .9
5.5
STATE OH
AIRS ID
390170003
390610014
390610041
390170003
390610014
390610041
390170003
390610014
390610041
390170003
390610014
390610041
A
A
A
A
A
QUARTER
1
1
1
2
2
2
3
3
3
4
4
4
1
2
3
4
A
EST
(90%
8.7 (
6.9 (
4.2 (
5.5 (
4.5 (
7.4 (
11.4 (
1.3 (
3.2 (
8.3 (
4.4 (
5.1 (
7.8 (
5.9 (
7.1 (
5.5 (
6.6 (
. REL
CONF.
6.5
4.8
2.4
4.2
3.4
5.6
8.7
1.0
2.5
5.6
3.3
3.9
6.2
5.0
6.0
4.6
5.9
(continued)
. RMSE NO. OF
INTERVAL) OBSERVATIONS
3.8) 5
3.8) 16
REPORTING nDrAWT7ATTnw_nnซ
. RMSE
INTERVAL)
, 11.4)*
, 11.6)*
6.6)
5.4)
, 11.4)*
, 11.6)*
6.6)
5.4)
, 7.8)
REPORTING
. RMSE
INTERVAL)
, 13.1)*
, 13.2)*
, 18.7)*
8.1)
6.9)
, 11.2)*
, 16.6)*
2.0)
, 4.7)
, 17.3)*
6.8)
, 7.5)
, 10.6)*
7.3)
8.8)
, 7.1)
, 7.3)
NO. OF
OBSERVATIONS
13
13
13
6
13
13
13
6
45
ORGAN IZATI ON =008
NO. OF
OBSERVATIONS
12
6
2
13
12
12
14
11
14
5
11
13
20
37
39
29
125
NO. OF
SAMPLER
QUARTERS
1
2
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
3
3
3
3
12
EST
(90%
EST
(90%
-2.0
-3.5
0.2
1.7
EST
(90%
0.3
-1.9
-1.2
0.7
0.4
-0.7
-3.4
-0.3
-2.0
-5.7
-0.8
-4.4
. REL.
CONF.
. REL.
CONF.
( -5.8
( -7.1
( -2.1
( -0.3
. REL.
CONF.
( -4.4
( -7.9
(-26.8
( -2.1
( -2.0
( -4.7
( -8.8
( -1.0
( -3.2
(-12.1
( -3.3
( -5.7
BIAS
INTERVAL)
BIAS
INTERVAL)
, 1.8)
, 0.1)
2.5)
3.7)
BIAS
INTERVAL)
5.0)
, 4.1)
, 24.5)
3.4)
2.9)
3.3)
1.9)
0.4)
, -0.7)
0.8)
, 1.7)
, -3.0)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
EST. REL
AIRS ID
400310648
400470554
401090035
401430110
A
A
QUARTER
3
3
3
3
3
A
(90% CONF.
1
1
3
5
2
2
.6 ( 1.
.5 ( 1.
.0 ( 1.
.8 ( 3.
.9 ( 2.
.9 ( 2.
0
1
9
6
3
3
STATE OK
EST. REL
AIRS ID
400219002
400219002
A
A
A
QUARTER
3
4
3
4
A
(!
10
3
10
3
6
)0% CONF
.2 ( 6.
.1 ( 2.
.2 ( 6.
.1 ( 2.
.9 ( 5.
7
1
7
1
1
STATE -OR
EST. REL
AIRS ID
410650007
A
QUARTER
4
4
(90% CONF.
5
5
.2 ( 3.
.2 ( 3.
0
0
STATE -OR
EST. REL
AIRS ID
410290133
410390060
410510080
410290133
410390060
410510080
410671003
410290133
410330107
410370001
410390060
QUARTER
2
2
2
3
3
3
3
4
4
4
4
(!
2
4
2
4
3
2
6
4
3
3
1
)0% CONF
.9 ( 2.
.5 ( 3.
.2 ( 1.
.6 ( 3.
.2 ( 2.
.6 ( 2.
.1 ( 3.
.0 ( 3.
.1 ( 2.
.3 ( 2.
.9 ( 1.
1
0
7
4
4
0
1
0
3
3
6
. RMSE
INTERVAL)
3.8)
2.5)
8.8)
, 17.0)*
4.0)
4.0)
REPORTING
. RMSE
INTERVAL)
, 24.3)*
5.9)
, 24.3)*
, 5.9)
, 11.0)*
REPORTING
. RMSE
INTERVAL)
, 22.8)*
, 22.8)*
REPORTING
. RMSE
INTERVAL)
5.0)
9.4)
, 3.4)
, 7.6)
4.7)
3.9)
, 96.7)*
, 5.9)
4.8)
, 5.9)
2.6)
NO. OF
OBSERVATIONS
4
9
3
3
19
19
ORGAN IZATI ON= 1 06
NO. OF
OBSERVATIONS
4
6
4
6
10
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
2
2
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
8
5
12
9
13
12
1
13
11
7
20
NO. OF
SAMPLER
QUARTERS
1
1
1
1
4
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
METHOD= 117
NO. OF
SAMPLER
QUARTERS
1
1
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
EST
(90%
-0.5
-0.4
2.8
4.3
EST
(90%
-8.2
-0.7
EST
(90%
-5. 1
EST
(90%
1.7
-2.5
1.2
1.3
1.4
1. 1
6.1
3.6
2.5
-0.6
1.1
. REL.
CONF
( -2
( -1
( o
( -3.
.6
.4
.7
.9
. REL.
CONF
(-16
( -3.
.6
.4
. REL.
CONF
( -9.
.4
. REL.
CONF
( -0.
( -6.
( 0.
( -1.
( -0.
( -0.
( 2
( 1
( -3.
( 0.
.0
.5
.2
.6
.1
.2
.6
.5
.2
.4
BIAS
INTERVAL)
1.6)
0.6)
5.0)
, 12.4)
BIAS
INTERVAL)
0.2)
2.0)
BIAS
INTERVAL)
, -0.9)
BIAS
INTERVAL)
3.4)
, 1.4)
2.2)
, 4.2)
2.8)
2.3)
, 4.5)
3.5)
, 1.9)
, 1.7)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
(continued)
AIRS ID
410510080
410671003
A
A
A
A
QUARTER
4
4
2
3
4
A
EST
(90%
4.4 (
2.5 (
3.0 (
3.5 (
3.2 (
3.2 (
. REL
CONF
3.
1 .
2.
3.
2.
2.
2
9
5
0
8
9
STATE PA
AIRS ID
420450002
420692006
420710007
421250005
421330008
420450002
420692006
420710007
421250005
421330008
420450002
420692006
420710007
421330008
420450002
420692006
420710007
421250005
421330008
A
A
A
A
A
QUARTER
1
1
1
1
1
2
2
2
2
2
3
3
3
3
4
4
4
4
4
1
2
3
4
A
EST
(90%
1.8 (
3.7 (
2.5 (
3.9 (
3.8 (
4.2 (
2.6 (
4.0 (
5.0 (
4.6 (
3.1 (
4.1 (
2.4 (
1.9 (
1.8 (
2.5 (
4.7 (
1.7 (
3.7 (
3.3 (
4.3 (
3.1 (
3.3 (
3.6 (
STATF-
. REL
CONF
1 .
2.
1 .
2.
2.
3.
1 .
2.
3.
3.
2.
2.
1 .
1 .
1 .
1 .
3.
1 .
2.
2.
3.
2.
2.
3.
PA
1
1
6
7
4
2
7
9
5
4
4
9
7
3
4
8
6
2
8
6
6
6
8
2
. RMSE
INTERVAL)
7.3)
4.0)
4.0)
4.4)
, 3.7)
3.6)
REPORTING
. RMSE
INTERVAL)
5.3)
, 16.3)*
, 5.9)
6.9)
, 11.1)*
6.6)
6.1)
6.5)
8.9)
7.3)
4.7)
, 7.3)
4.7)
4.0)
, 2.7)
4.1)
7.2)
3.3)
, 5.4)
4.6)
, 5.2)
3.9)
3.9)
3.9)
BFpnnTTwr.
NO. OF
OBSERVATIONS
9
10
25
35
70
130
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
3
2
4
7
3
11
4
9
7
10
12
7
6
5
13
9
12
6
13
19
41
30
53
143
nnr.AWT7ATTnw=nn?
NO. OF
SAMPLER
QUARTERS
1
1
3
4
6
13
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
5
5
4
5
19
MFTHTtn=1 1 8
EST
(90%
2
1
.7
.0
EST
(90%
-0
2
0
0
3
1
1
1
3
-2
-0
2
-0
-0
-0
-0
-1
0
-1
. 1
.1
.7
.6
.0
.6
.8
.0
.1
.3
.0
.2
.0
. 1
.9
.7
.8
.1
.6
. REL.
CONF.
( 0.5
( -0.4
. REL.
CONF.
( -3.9
(-17.2
( -2.6
( -2.4
( -1.7
( -0.7
( -0.7
( -1.5
( 0.1
( -4.7
( -1-7
( -0.5
( -2.2
( -2.1
( -1.7
( -2.3
( -4.2
( -1.4
( -3.3
BIAS
INTERVAL)
5.0)
, 2.4)
BIAS
INTERVAL)
3.7)
, 21.3)
4.0)
3.6)
, 7.8)
3.8)
4.3)
3.5)
6.2)
0.1)
1.7)
4.9)
2.1)
2.0)
, -0.1)
0.9)
0.6)
, 1.7)
, 0.1)
AIRS ID QUARTER
420030064 1
EST. REL. RMSE
(90% CONF. INTERVAL)
8.9 ( 6.2, 17.1)*
NO. OF
NO. OF SAMPLER
OBSERVATIONS QUARTERS
6
1
EST. REL. BIAS
(90% CONF. INTERVAL)
4.2 ( -2.9, 11.3)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
420030064
420031301
420030008
420030064
420031301
420030008
420030064
420031301
A
A
A
A
A
QUARTER
2
2
3
3
3
4
4
4
1
2
3
4
A
(!
11
0
1
5
0
7
1
3
8
10
4
4
6
EST
)0%
.9 (
.9 (
.8 (
.5 (
.9 (
.0 (
.7 (
.1 (
.9 (
.6 (
.8 (
.3 (
.7 (
. REL
CONF
8.
0.
0.
4.
0.
5.
1 .
2.
6.
8.
3.
3.
5.
. RMSE
(continued)
NO. OF
. INTERVAL)
9
5
9
2
5
0
2
3
2
1
8
5
9
STATE PA
AIRS ID
421010004
421010004
421010004
421010004
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
(!
7
11
5
9
7
11
5
9
8
EST
)0%
.6 (
.2 (
.4 (
.1 (
.6 (
.2 (
.4 (
.1 (
.2 (
. REL
CONF
4.
6.
4.
7.
4.
6.
4.
7.
6.
, 18.
2.
, 29.
8.
2.
, 11.
2.
4.
, 17.
, 15.
6.
5.
7.
4)*
5)
4)*
2)
5)
9)*
9)
5)
1)*
4)*
8)
5)
8)
REPORTING
. RMSE
. INTERVAL)
9
9
0
0
9
9
0
0
8
STATE RI
AIRS ID
440070022
440071010
440070022
440071010
440070022
440071010
A
A
A
QUARTER
2
2
3
3
4
4
2
3
4
EST
(90%
5
8
5
6
3
2
7
6
3
.2 (
.6 (
.4 (
.8 (
.8 (
.5 (
.4 (
.1 (
.2 (
. REL
CONF
3.
6.
4.
5.
2.
1 .
5.
4.
2.
, 17.
, 32.
9.
, 13.
, 17.
, 32.
9.
, 13.
, 10.
9)*
6)*
0)
5)*
9)*
6)*
0)
5)*
5)*
REPORTING
. RMSE
. INTERVAL)
7
5
1
1
9
9
9
9
6
8.
, 13.
8.
, 10.
5.
3.
, 10.
8.
4.
9)
1)*
2)
5)*
9)
7)
1)*
1)
2)
OBSERVATIONS
11
3
1
13
3
8
8
13
6
14
17
29
66
ORGAN IZATI ON =003
NO. OF
OBSERVATIONS
4
3
9
13
4
3
9
13
29
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
8
12
12
11
11
12
20
23
23
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
2
3
3
9
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
2
2
2
EST. REL.
(90% CONF.
1.9 ( -4.8
0.8 ( 0.2
-1.8
3.2 ( 0.9
-0.5 ( -1.9
-4.4 ( -8.2
0.5 ( -0.7
1.1 ( -0.3
EST. REL.
(90% CONF.
-2.7 (-12.3
-3.1 (-25.3
3.6 ( 0.9
-0.5 ( -5.2
EST. REL.
(90% CONF.
3.8 ( 1.2
2.4 ( -2.1
0. 1 ( -2.9
-1.8 ( -5.5
0.2 ( -2.0
-0.0 ( -1.3
BIAS
INTERVAL)
8.6)
, 1.4)
5.5)
0.9)
, -0.5)
1.7)
2.6)
BIAS
INTERVAL)
6.9)
, 19.1)
6.3)
4.1)
BIAS
INTERVAL)
6.3)
6.8)
3.0)
2.0)
, 2.4)
, 1.3)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3 30
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
STATE=RI REPORTING ORGANIZATION=001 METHOD=120
(continued)
NO. OF
EST. REL. RMSE NO. OF SAMPLER EST. REL. BIAS
AIRS ID QUARTER (90% CONF. INTERVAL) OBSERVATIONS QUARTERS (90% CONF. INTERVAL)
5.8 ( 5.1, 6.7)
66
AIRS ID
450430009
450190048
450430009
450450009
450790019
450190048
450430009
450450009
450790019
450190048
450430009
450450009
450790019
A
A
A
A
A
QUARTER
1
2
2
2
2
3
3
3
3
4
4
4
4
1
2
3
4
A
EST
(90%
3.4 (
3.9 (
3.9 (
1.3 (
2.3 (
9.0 (
3.0 (
2.2 (
2.5 (
2.5 (
3.5 (
2.6 (
2.8 (
3.4 (
3.4 (
4.0 (
3.0 (
3.5 (
. REL
CONF
2.
2.
3.
0.
1 .
6.
2.
1 .
2.
1 .
2.
1 .
2.
2.
2.
3.
2.
3.
. RMSE
. INTERVAL)
7
8
2
8
8
4
3
5
0
9
8
9
2
7
9
5
6
2
STATE -SD
AIRS ID
460990006
460990006
A
A
A
QUARTER
3
4
3
4
A
EST
(90%
13.5 (
11 .8 (
13.5 (
11.8 (
12.7 (
. REL
CONF
10.
8.
10.
8.
10.
4.
6.
5.
5.
3.
, 15.
4.
3.
3.
3.
4.
3.
3.
4.
4.
4.
3.
3.
6)
7)
2)
9)
3)
3)*
1)
7)
2)
9)
6)
9)
7)
6)
1)
7)
5)
8)
REPORTING
. RMSE
. INTERVAL)
0
7
0
7
1
, 21.
, 18.
, 21.
, 18.
, 17.
5)*
8)*
5)*
8)*
3)*
NO. OF
OBSERVATIONS
21
8
23
2
16
8
18
8
28
11
23
12
21
21
49
62
67
199
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
10
10
10
10
20
NO. OF
SAMPLER
EST
QUARTERS (90%
1 0
1 -1
1 0
1 -1
1 0
1 -1
1 1
1 -1
1 2
1 0
1 -0
1 -2
1 0
1
4
4
4
13
METHOD- 119
NO. OF
SAMPLER
.6
.4
.3
.3
. 1
. 1
.1
.8
.2
.6
.6
.0
.3
EST
QUARTERS (90%
1 9
1 -0
1
1
2
.1
.6
. REL.
CONF.
( -0.7
( -4.0
( -LI
( -4.4
( -1.0
( -7.5
( -0.0
( -2.6
( 1.8
( -0.7
( -1.9
( -2.9
( -0.8
. REL.
CONF.
( 3.1
( -7.8
BIAS
INTERVAL)
1.9)
, 1.2)
, 1.7)
1.9)
1.1)
5.2)
2.3)
, -0.9)
2.6)
2.0)
, 0.7)
, -1.1)
, 1.3)
BIAS
INTERVAL)
, 15.2)
6.6)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
461031001
461031001
A
A
A
QUARTER
3
4
3
4
A
EST
(90%
7
25
7
25
14
.9 (
.1 (
.9 (
.1 (
.7 (
. REL
CONF
6.
17.
6.
17.
11 .
. RMSE
. INTERVAL)
2
3
2
3
9
STATE -TN
AIRS ID
471650007
471650007
471130004
471650007
471130004
471650007
A
A
A
A
A
QUARTER
1
2
3
3
4
4
1
2
3
4
A
(!
12
15
3
3
3
12
12
15
3
8
8
EST
)0%
.1 (
.0 (
.5 (
.0 (
.5 (
.1 (
.1 (
.0 (
.1 (
.2 (
.7 (
. REL
CONF
9.
10.
2.
2.
2.
9.
9.
10.
2.
6.
7.
, 11.
, 48.
, 11.
, 48.
, 19.
2)*
1)*
2)*
1)*
7)*
REPORTING
. RMSE
. INTERVAL)
1
8
5
3
8
5
1
8
6
9
8
STATE TN
AIRS ID
470931017
470931017
470931017
470931017
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
EST
(90%
11
33
3
3
11
33
3
3
15
.3 (
.2 (
.0 (
.3 (
.3 (
.2 (
.0 (
.3 (
.9 (
. REL
CONF
8.
24.
2.
2.
8.
24.
2.
2.
13.
, 18.
, 25.
6.
4.
4.
, 17.
, 18.
, 25.
4.
, 10.
, 10.
3)*
7)*
0)
2)
5)
0)*
3)*
7)*
1)
0)
0)
REPORTING
. RMSE
. INTERVAL)
2
2
3
5
2
2
3
5
6
, 18.
, 54.
4.
5.
, 18.
, 54.
4.
5.
, 19.
5)*
6)*
3)
0)
5)*
6)*
3)
0)
2)*
NO. OF
OBSERVATIONS
16
6
16
6
22
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
12
8
8
17
25
17
12
8
25
42
87
ORGAN IZATI ON =004
NO. OF
OBSERVATIONS
9
9
14
13
9
9
14
13
45
NO. OF
SAMPLER
QUARTERS
1
1
1
1
2
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
2
2
6
METHOD=120
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
EST. REL. BIAS
(90% CONF. INTERVAL)
0.2 ( -3.4, 3.8)
-7.1 (-28.8, 14.6)
EST. REL. BIAS
(90% CONF. INTERVAL)
-8.6 (-13.2, -4.0)
3.8 ( -6.6, 14.2)
-2.8 ( -4.3, -1 .4)
0.8 ( -0.5, 2.0)
-1.4 ( -2.5, -0.2)
-0.9 ( -6.2, 4.4)
EST. REL. BIAS
(90% CONF. INTERVAL)
6.2 ( 0.0, 12.4)
17.1 ( -1.7, 35.8)
0.6 ( -0.8, 2.0)
-0.2 ( -1.9, 1.6)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
480290034
481130069
481410044
484393006
484530020
480290034
481130069
481410044
482011035
484393006
484530020
481130050
481130069
481410010
481410044
481671005
482011035
484391002
484393006
484530020
A
A
A
A
QUARTER
1
1
1
1
1
2
2
2
2
2
2
4
4
4
4
4
4
4
4
4
1
2
4
A
EST
(90%
10.3 (
0.3 (
4.7 (
4.5 (
4.3 (
8.4 (
2.0 (
6.5 (
12.0 (
4.7 (
1.7 (
3.3 (
11.4 (
2.8 (
11 .9 (
27.1 (
18.5 (
1.7 (
10.3 (
4.0 (
5.2 (
6.3 (
12.0 (
10.2 (
. REL
CONF
5.
0.
3.
2.
2.
5.
1 .
4.
6.
3.
1 .
2.
8.
1 .
8.
13.
13.
0.
7.
2.
3.
5.
10.
9.
. RMSE
. INTERVAL)
3
2
1
6
2
2
2
6
1
1
0
0
5
4
7
8
0
9
7
7
9
0
3
0
STATE UT
AIRS ID
490494001
490494001
490494001
A
A
A
A
QUARTER
2
3
4
2
3
4
A
EST
(90%
10.2 (
3.0 (
14.4 (
10.2 (
3.0 (
14.4 (
12.0 (
STATF-
. REL
CONF
7.
2.
10.
7.
2.
10.
9.
VA
, 165.
5.
9.
, 20.
, 68.
, 24.
8.
, 11.
, 191.
, 11.
7.
9.
, 17.
, 44.
, 19.
, 432.
, 33.
, 27.
, 16.
7.
8.
8.
, 14.
, 11.
0)*
2)
7)
0)*
8)*
4)*
9)
6)*
1)*
2)*
6)
6)
7)*
2)*
6)*
1)*
2)*
8)*
0)*
6)
4)
6)
3)*
7)*
REPORTING
. RMSE
. INTERVAL)
1
0
9
1
0
9
6
, 19.
7.
, 21.
, 19.
7.
, 21.
, 16.
BFpnnT
6)*
2)
8)*
6)*
2)
8)*
0)*
rwr.
NO. OF
OBSERVATIONS
1
1
5
2
1
3
2
7
1
4
2
3
11
1
9
1
7
1
11
6
10
19
50
79
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
6
4
12
6
4
12
22
nnr.AWT7ATTnw=nni
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
5
6
9
20
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
3
MFTHnn=i i s
EST. REL.
(90% CONF.
10
-0
1
4
4
-5
2
3
-12
3
1
-1
3
-2
7
27
-4
-1
4
2
.3
.3
.3 ( -3.5
.4 ( -1.0
.3
.6 (-18.4
.0 ( -0.4
.5 ( -0.8
.0
.4 ( -1.1
.7 ( -0.6
.2 ( -7.6
.2 ( -3.1
.8
.4 ( 1.2
. 1
.7 (-18.9
.7
.0 ( -1.4
.7 ( 0.2
EST. REL.
(90% CONF.
-0
1
2
.7 ( -9.9
.6 ( -1.8
. 1 ( -5.6
BIAS
INTERVAL)
, 6.1)
9.9)
, 7.1)
4.4)
7.8)
, 7.8)
4.0)
, 5.1)
9.4)
, 13.6)
9.5)
9.5)
5.3)
BIAS
INTERVAL)
8.5)
, 5.1)
9.8)
AIRS ID QUARTER
510130020 1
EST. REL. RMSE
(90% CONF. INTERVAL)
3.0 ( 2.3, 4.5)
NO. OF
NO. OF SAMPLER
OBSERVATIONS QUARTERS
12
1
EST. REL. BIAS
(90% CONF. INTERVAL)
0.4 ( -1.2, 2.0)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
(continued)
AIRS ID
517100024
517600020
510130020
517100024
517600020
510130020
517100024
517600020
510130020
517100024
517600020
A
A
A
A
A
QUARTER
1
1
2
2
2
3
3
3
4
4
4
1
2
3
4
A
EST
(90%
4.4 (
13.5 (
2.5 (
2.7 (
3.8 (
5.9 (
3.2 (
3.6 (
6.7 (
3.0 (
2.7 (
8.9 (
3.1 (
4.5 (
4.7 (
5.3 (
. REL
CONF
3.
10.
2.
2.
3.
4.
2.
2.
5.
2.
2.
7.
2.
4.
4.
4.
3
5
0
1
1
9
6
9
2
2
1
6
7
0
0
9
STATE ~WA
EST. REL
AIRS ID
530330057
530530031
530630016
530730015
530770012
530330057
530530031
530630016
530730015
530770012
530330057
530530031
530630016
530730015
530770012
530330057
530530031
530630016
530730015
A
A
A
A
QUARTER
1
1
1
1
1
2
2
2
2
2
3
3
3
3
3
4
4
4
4
1
2
3
4
(90%
2.4 (
3.4 (
8.5 (
19.6 (
18.8 (
4.6 (
2.0 (
2.3 (
7.6 (
3.9 (
9.1 (
12.8 (
5.0 (
2.8 (
6.4 (
3.9 (
2.4 (
4.6 (
1.8 (
11.3 (
4.5 (
9.3 (
3.3 (
CONF.
1.
2.
5.
12.
13.
3.
1.
1 .
5.
2.
6.
9.
3.
1 .
4.
2.
1.
3.
1 .
9.
3.
7.
2.
8
5
7
2
7
5
4
5
3
7
8
7
5
7
3
9
8
2
3
6
8
8
8
. RMSE
INTERVAL)
6.5)
, 19.1)*
3.3)
, 3.7)
5.0)
7.5)
, 4.2)
, 4.7)
9.8)
4.9)
3.9)
, 10.9)*
3.6)
, 5.2)
5.8)
, 5.8)
REPORTING
. RMSE
INTERVAL)
, 3.7)
5.6)
, 17.8)*
, 57.3)*
, 31.0)*
6.9)
3.3)
4.8)
, 14.6)*
, 7.5)
, 14.0)*
, 19.5)*
9.0)
8.0)
, 13.3)*
5.8)
3.9)
8.9)
, 3.1)
, 14.0)*
5.5)
, 11.5)*
4.1)
NO. OF
OBSERVATIONS
13
16
22
18
25
29
24
25
14
9
14
41
65
78
37
221
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
12
9
5
3
9
13
9
5
6
6
11
12
7
3
5
12
10
6
8
38
39
38
36
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
3
3
3
3
12
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
5
5
5
4
EST
(90%
2.0
-1.6
0.3
-0.8
1.5
-0.5
-0.7
0.4
-2.8
0.5
-0.1
EST
(90%
0.8
2.2
2.4
-17.0
7.2
1.4
0.6
-1.0
4.4
3.4
0.2
-3.6
1.8
2.7
3.6
-1.4
1.8
0.9
0.0
. REL.
CONF
( -0.
( -7.
( -0.
( -1.
( 0.
( -2.
( -1.
( -o
( -5
( -1
( -1
.0
.6
.6
.8
.3
.4
.8
.9
.8
.4
.4
. REL.
CONF
( -o
( o
( -6
(-37
( -4
( -o
( -o
( -3
( -1
( 1
( -5
(-10
( -1
( 1
( -2
( -3
( o
( -3
( -1
.4
.5
.3
.2
.2
.9
.7
.2
.2
.7
.0
.3
.9
.5
.1
.3
.9
.1
.3
BIAS
INTERVAL)
4.0)
, 4.5)
1.2)
0.3)
2.8)
, 1.4)
0.4)
, 1.6)
0.2)
, 2.4)
, 1.2)
BIAS
INTERVAL)
, 2.0)
3.9)
, 11.1)
3.2)
, 18.6)
, 3.6)
, 1.8)
, 1.2)
, 10.0)
5.2)
, 5.4)
, 3.1)
, 5.5)
3.9)
9.2)
0.6)
2.8)
5.0)
, 1.3)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3 34
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
STATE=WA REPORTING ORGANIZATION=001 METHOD=118
(continued)
NO. OF
EST. REL. RMSE NO. OF SAMPLER EST. REL. BIAS
AIRS ID QUARTER (90% CONF. INTERVAL) OBSERVATIONS QUARTERS (90% CONF. INTERVAL)
7.9 ( 7.2, 8.7)
151
19
AIRS ID
551091002
551091002
A
A
A
QUARTER
3
4
3
4
A
EST
(90%
3.1 (
2.2 (
3.1 (
2.2 (
2.4 (
. REL
CONF
1 .
1 .
1 .
1 .
1 .
. RMSE
. INTERVAL)
6
5
6
5
6
STATE WI
AIRS ID
550090005
550250025
550310025
550790026
550790059
551330027
550090005
550250025
550310025
550790026
551330027
550090005
550250025
550310025
550790026
550790059
551330027
550090005
550250025
550310025
550790026
550790059
551330027
A
A
QUARTER
1
1
1
1
1
1
2
2
2
2
2
3
3
3
3
3
3
4
4
4
4
4
4
1
2
EST
(90%
6.1 (
4.2 (
7.2 (
16.1 (
37.2 (
5.5 (
6.0 (
19.7 (
6.9 (
6.4 (
2.8 (
11 .9 (
4.8 (
3.4 (
10.3 (
3.6 (
3.5 (
3.5 (
2.7 (
13.3 (
14.1 (
13.9 (
6.4 (
12.2 (
11.3 (
. REL
CONF
4.
3.
5.
11.
25.
4.
4.
15.
5.
4.
2.
9.
3.
2.
7.
2.
2.
2.
2.
10.
10.
10.
4.
10.
9.
, 48.
4.
, 48.
4.
4.
8)*
6)
8)*
6)
6)
REPORTING
. RMSE
. INTERVAL)
6
4
7
8
0
0
7
5
2
6
1
4
7
5
8
6
6
7
1
3
4
0
8
8
9
9.
5.
9.
, 26.
, 77.
9.
8.
, 27.
, 10.
, 10.
4.
, 16.
6.
5.
, 15.
6.
5.
5.
3.
, 19.
, 22.
, 23.
9.
, 14.
, 13.
5)
6)
6)
5)*
6)*
0)
7)
6)*
7)*
9)*
3)
3)*
9)
2)
6)*
0)
6)
0)
9)
2)*
5)*
8)*
7)
0)*
3)*
NO. OF
OBSERVATIONS
1
5
1
5
6
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
11
22
21
9
5
9
15
17
11
8
12
19
15
11
12
9
10
15
14
15
10
8
12
77
63
NO. OF
SAMPLER
EST
QUARTERS (90%
1 3
1 0
1
1
2
METHOD 118
NO. OF
SAMPLER
. 1
.2
EST
QUARTERS (90%
1 -3
1 -1
1 -1
1 9
1 -21
1 0
1 2
1 1
1 -4
1 1
1 -0
1 0
1 1
1 0
1 5
1 0
1 -0
1 2
1 1
1 -5
1 7
1 5
1 -1
6
5
.6
.4
. 1
.6
.3
.8
.8
.4
.3
.3
.3
.7
.1
.8
.5
.5
.7
.4
.6
.5
.9
.6
.4
. REL.
CONF.
( -2.2
. REL.
CONF.
( -6.5
( -2.9
( -3.9
( 1.0
(-53.8
( -2.8
( 0.3
( -7.2
( -7.4
( -3.2
( -1.8
( -4.1
( -LI
( -LI
( 0.8
( -1.8
( -2.8
( 1.3
( 0.5
(-11 .2
( 0.7
( -3.5
( -4.8
BIAS
INTERVAL)
2.6)
BIAS
INTERVAL)
, -0.8)
0.0)
1.6)
, 18.1)
, 11.1)
4.3)
5.3)
, 10.0)
, -1.2)
5.8)
, 1.2)
5.6)
3.3)
2.6)
, 10.2)
2.9)
, 1.4)
3.6)
2.6)
0.2)
, 15.1)
, 14.7)
2.0)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
A
A
A
QUARTER
3
4
A
(!
7.
9
10
EST
)0%
.8 (
.7 (
.4 (
. REL
CONF
6.
8.
9.
. RMSE
(continued)
NO. OF
. INTERVAL)
9
6
7
STATE WV
AIRS ID
540391005
540391005
540391005
540391005
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
EST
(90%
4
8
5
12
4
8
5
12
8
.5 (
.2 (
.9 (
.4 (
.5 (
.2 (
.9 (
.4 (
.1 (
. REL
CONF
3.
6.
4.
10.
3.
6.
4.
10.
7.
9.
, 11.
, 11.
1)
2)*
1)*
REPORTING
. RMSE
. INTERVAL)
7
6
8
0
7
6
8
0
2
STATE WV
AIRS ID
540290011
540290011
540290011
540290011
A
A
A
A
A
QUARTER
1
2
3
4
1
2
3
4
A
EST
(90%
8
7
12
7
8
7
12
7
9
.6 (
.5 (
.3 (
.4 (
.6 (
.5 (
.3 (
.4 (
.1 (
. REL
CONF
6.
6.
9.
6.
6.
6.
9.
6.
8.
5.
, 11.
7.
, 16.
5.
, 11.
7.
, 16.
9.
8)
1)*
6)
6)*
8)
1)*
6)
6)*
1)
REPORTING
. RMSE
. INTERVAL)
9
1
9
0
9
1
9
0
1
STATE WY
AIRS ID
560330002
560330002
QUARTER
1
2
(!
11
10
EST
)0%
.9 (
.5 (
. REL
CONF
8.
7.
, 11.
9.
, 16.
9.
, 11.
9.
, 16.
9.
, 10.
4)*
8)
3)*
8)
4)*
8)
3)*
8)
4)*
REPORTING
. RMSE
. INTERVAL)
8
3
, 18.
, 20.
9)*
1)*
OBSERVATIONS
76
74
290
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
26
21
28
22
26
21
28
22
97
ORGAN IZATI ON =002
NO. OF
OBSERVATIONS
23
25
23
23
23
25
23
23
94
ORGAN IZATI ON =00 1
NO. OF
OBSERVATIONS
10
6
NO. OF
SAMPLER
QUARTERS
6
6
23
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD= 118
NO. OF
SAMPLER
QUARTERS
1
1
1
1
1
1
1
1
4
METHOD= 117
NO. OF
SAMPLER
QUARTERS
1
1
EST. REL. BIAS
(90% CONF. INTERVAL)
EST. REL. BIAS
(90% CONF. INTERVAL)
0.7 ( -0.8, 2.3)
1.0 ( -2.1 , 4.2)
2.3 ( 0.5, 4. 1)
5.5 ( 1.3, 9.6)
EST. REL. BIAS
(90% CONF. INTERVAL)
-4.5 ( -7.2, -1.9)
-0.5 ( -3.1 , 2.1)
-0.4 ( -4.9, 4. 1)
0.3 ( -2.4, 3.0)
EST. REL. BIAS
(90% CONF. INTERVAL)
0.2 ( -7.0, 7.5)
-1.2 (-10.6, 8.2)
-------
ESTIMATES OF RELATIVE PRECISION (REL. RMSE) BASED ON CALCULATION OPTION 3
* INDICATES UPPER BOUND OF ESTIMATED 90% CONFIDENCE INTERVAL > 10%
AIRS ID
560330002
560330002
A
A
A
A
A
QUARTER
3
4
1
2
3
4
A
EST.
REL.
(contl
RMSE
(90% CONF. INTERVAL)
6
3
11
10
6
3
8
.9 (
.1 (
.9 (
.5 (
.9 (
.1 (
.7 (
5.1,
2.2,
8.8,
7.3,
5.1,
2.2,
7.3,
11
5
18
20
11
5
10
.0)*
.1)
.9)*
.1)*
.0)*
.1)
.8)*
nued)
NO. OF
OBSERVATIONS
10
9
10
6
10
9
35
NO. OF
SAMPLER EST. REL. BIAS
QUARTERS (90% CONF. INTERVAL)
1 1.8 ( -2.2, 5.9)
1 0.1 ( -1.9, 2.2)
1
1
1
1
4
-------
Attachment 2-8
Routine and Performance Evaluation Program Pairs
with Accuracy > +/- 50%
-------
Biases > 50% or < -50%
based on 7/26/00 extractions from AIRS and PEDs
Prim.
Method
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
118
120
120
120
120
120
120
120
120
120
120
AIRS Site
081230006
180190005
180431004
180891003
201730010
211950002
230050027
280010004
290952002
340130011
360810094
410390060
450630008
490494001
490570001
518100008
550790059
040139997
040190011
060271003
060590001
110010043
250230004
390350066
391530023
461030016
470930028
State
CO
IN
IN
IN
KS
KY
ME
MS
MO
NJ
NY
OR
SC
UT
UT
VA
WI
AZ
AZ
CA
CA
DC
MA
OH
OH
SD
TN
Cone. PE Cone.
0.
24.
6.
1.
10.
7.
12.
25.
13.
5.
34.
1.
20.
17.
4.
0.
5.
16.
16.
10.
15.
12.
3.
10.
13.
7.
7.
1.
12.
13.
30
10
40
50
30
00
70
20
20
40
10
90
40
20
80
00
90
00
40
20
40
10
00
80
20
40
20
20
80
80
6
5
3
15
6
18
8
11
8
3
13
4
12
5
12
6
12
8
6
6
7
7
0
6
7
4
4
8
6
8
.20
.99
.67
.28
.70
.80
.16
.69
.61
.42
.34
.78
.44
.28
.40
.99
.15
.07
.53
. 12
.95
.70
.75
.53
.29
.24
.66
.15
.99
.32
Bias ('
-95
302
74
-90
53
-62
55
115
53
58
155
-60
64
225
-61
-100
-51
98
151
66
93
57
300
65
81
74
54
-85
83
65
)6) 50%?
.2 *
.1 *
.6 *
.2 *
.7 *
.8 *
.7 *
.6 *
.3 *
.1 *
.7 *
.3 *
.0 *
.6 *
.3 *
.0 *
4 *
.2 *
.1 *
.7 *
.8 *
. 1 *
.5 *
.3 *
.0 *
4 *
.5 *
.3 *
. 1 *
.8 *
B i as > Cone
<= 6? Quarter Date
* 2
* 1
* 3
* 4
2
2
2
2
2
* 2
4
* 1
2
* 2
* 3
* 3
* 3
4
1
3
1
3
* 4
1
1
* 3
* 1
* 4
1
1
05/24/1999
03/31/1999
09/09/1999
12/11/1999
04/27/1999
05/18/1999
06/11/1999
06/02/1999
06/17/1999
04/24/1999
11/02/1999
02/18/1999
04/06/1999
04/20/1999
08/10/1999
08/10/1999
08/04/1999
10/18/1999
02/23/1999
08/22/1999
02/24/1999
08/31/1999
10/31/1999
02/10/1999
03/02/1999
08/19/1999
03/10/1999
11/17/1999
03/16/1999
03/04/1999
-------
TECHNICAL REPORT DATA
(Please read Instructions on reverse before completing)
1. REPORT NO.
EPA-454/R-00-041
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
Quality Assurance Report: Calendar Year 1999, The PM2.5 Ambient
Air Monitoring Program
5. REPORT DATE
12/00
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
Michael Papp. Shelly Eberly, Mark Schmidt, Tim Hanley
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, NC 27711
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
12. SPONSORING AGENCY NAME AND ADDRESS
Director
Office of Air Quality Planning and Standards
Office of Air and Radiation
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
13. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
EPA/200/04
15. SUPPLEMENTARY NOTES
16. ABSTRACT
The report documents the quality assurance activities that were undertaken for the PM2 5 environmental data
operations for the calendar year January 1, 1999 to December 31, 1999 (CY99), which was the first year of
implementation the PM2.5 monitoring program. The QA Report evaluates the adherence to the quality assurance
requirements described in 40 CFR 58 App. A and evaluates the data quality indicators of precision, accuracy, bias,
completeness, comparability and detectabilty.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b. IDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
Quality Assurance
Air Pollution control
18. DISTRIBUTION STATEMENT
Release Unlimited
19. SECURITY CLASS (Report)
Unclassified
21. NO. OF PAGES
20. SECURITY CLASS (Page)
Unclassified
22. PRICE
EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDITION IS OBSOLETE
------- |