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UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

RESEARCH TRIANGLE PARK, NC 27711 

MEMORANDUM 

SUBJECT: Assessments of One-Point QC Data in Response to Comments on Revisions to 

the Ambient Air Quality Assurance Regulation contained in 40 CFR part 58 

Appendix A 

FROM: Lewis Weinstock and Mike Papp (OAQPS/AQAD/AAMG) 

TO: Ambient Monitoring Rule Docket (EPA-HQ-OAR-2013-0619) 

This memorandum discusses potential changes to quality assurance requirements in 40 CFR Part 58. As 

part of a proposed rule - Revisions to Ambient Monitoring Quality Assurance and Other Requirements – 

79 FR 54356 - OAQPS received a number of comments related to the proposal to lower the 

concentrations of the one-point QC check and to require that the selection of the check concentration be 

based on the mean or median concentration of the measurements within the ambient air monitoring 

network. The comments that were received were used to revise the proposed language for the final rule to 

provide more flexibility for the monitoring organizations. However, EPA also performed some additional 

assessments of monitoring data that was used to provide some rationale for our initial decision to propose 

the changes in the regulations and we believe provide a framework for future changes to operational 

procedures in the SLAMS network. These additional details are provided below. 

BACKGROUND 

The EPA proposed to lower the audit concentrations (current section 3.2.1) of the one-point quality 

control (QC) checks to between 0.005 and 0.08 parts per million (ppm) for SO2, NO2, and O3 (currently 

0.01 to 0.1 ppm), and to between 0.5 and 5 ppm for CO monitors (currently 1 and 10 ppm). With the 

development of more sensitive monitoring instruments with lower detection limits, technical 

improvements in calibrators, and lower ambient air concentrations in general, the EPA felt this revision 

would better reflect the precision and bias of the ambient air data being measured at a majority of the sites 

across the network. 

The majority of the comments (19 of 26 responding to the quality assurance proposal) received on 

appendix A related to this proposed change. Most of the commenters expressed similar technical concerns 

which can be categorized below: 

 The SLAMS network is in place mainly for decisions related to the NAAQS therefore QC checks 

should be around NAAQS values. 

 Some of the federal reference methods (FRM) or federal equivalent methods (FEM) that are still 

in use may operate acceptably at concentrations around the NAAQS but these older methods are 

not as sensitive at lower concentrations (i.e., mean or median concentrations) so QC checks at 

these lower levels are beyond the limits of the instrumentation. 
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 The instrumentation necessary to challenge the monitors at the lower concentrations (calibrators 

with additional mass flow controllers or gas cylinders of lower concentrations) would be required 

to comply and therefore represent an added expense and burden. 

 The lower concentrations affect the percent different statistic so there is more chance that the QC 

check will fail the acceptance requirements and therefore invalidate data that the monitoring 

organization feels is of acceptable quality. 

DATA ANALYSIS 

In order to provide some context to the proposal, EPA extracted routine data and all one-point QC data 

for the 4 gaseous criteria pollutants for SLAMS sites for calendar year 2013. The following evaluation 

provides summary information about the routine data and the one-point QC checks reported by states. It 

must be noted that the one-point QC regulation, prior to the proposal, stated that “ the QC check gas 

concentration selected should be related to the routine concentrations normally measured at sites within 

the monitoring network in order to appropriately reflect the precision and bias at these routine 

concentration ranges”1

. Based on the 2013 data presented below, it is evident that many monitoring 

organizations did not follow this recommendation and was the reason EPA formally proposed the revision 

to this requirement. 

Nitrogen Dioxide - In Figure 1 (and similar figures for the other gaseous pollutants), the graph on the left 

represents the mean, 99th percentile and max value for 1-hour routine ambient air data for 43 states and 

territories (x-axis) reporting NO2 data in 2013. The y-axis is concentration in ppb. The green line (80 

ppb) represents the proposed upper range of the one-point QC check while the red line represents the 

current upper range (100 ppb) for the one-point QC check. Of the 43 states reporting hourly NO2 data, 

only three states had maximum hourly values (highest value for the year) above the NAAQS (100 ppb) 

and 99 percent of all the states had hourly values that were below 60 ppb. The graph on the right is a 

frequency distribution of the one-point QC checks for 2013. 85 percent of the one-point QC checks 

reported for 2013 were above 99 percent of the routine data. 

                                                            

1 40 CFR Part 58 Appendix A section 3.2.1
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Figure 2 below (and similar figures for the other gaseous 

pollutants), provides an assessment of the one-point QC 

checks using box and whisker plots (example on left). In 

the figures presented below, the mean is not identified. In 

Figure 2, the graph on the left provides the difference 

between the measured value and the audit standard value; 

the graph on the right is the same data set but reports the 

percent difference which is the statistic presently in use for 

the gaseous pollutants2

. The one-point QC data is 

segregated into 10 ppb segments (0-10 ppb, 10-20 ppb etc.) 

in order to evaluate whether the lower QC concentrations have an effect on the precision and bias 

estimates. The green vertical line on the graph on the right represents the proposed 80 ppb high QC range 

and the blue shaded area represents where the QC checks would be selected if monitoring organizations 

selected a QC concentration related to the mean or median routine air concentration. The red lines 

represent the current percent difference acceptance criteria (+15%)3

. In this case, the NO2 variability, 

based on the 25th – 75th percentile spread, does not appear to be significantly different at lower QC 

concentrations than the higher QC concentration data. 

 

                                                            

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40 CFR Part 58 Appendix A Section 4.1.1   3 Validation Templates in QA Handbook Volume II and on AMTIC http://www.epa.gov/ttnamti1/qalist.html  
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Ozone (Fig. 3) - Of the 51 states and territories reporting hourly ozone data, 48 states had maximum 

values over the NAAQS (75 ppb) but had 99 percent of their hourly values below the NAAQS. In 

addition, 90 percent of the one-point QC checks were above 99 percent of the routine data. 

Similar to NO2, Figure 4 presents the differences (left graph) and percent differences (right graph) of the 

one-point QC checks segregated into the ten concentration ranges. The ozone acceptance criteria is tighter 

than NO2 (+7 percent difference) but the variability of the 25th – 75th percentile spread at these lower 

ranges does not appear to be significantly different from the one-point QC checks variability at higher 

concentration ranges. 

 
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Sulfur Dioxide (Fig. 5) - In order to provide a readable graph, the left hand graph of Figure 5 does not 

include maximum values since some states did measure SO2 values that were quite high. Of the 48 states 

and territories providing hourly sulfur dioxide data, 23 states had maximum values over the NAAQS (75 

ppb) and 47 states had 99 percent of their values below 36 ppb. 75 percent of the one-point QC checks 

were above 99 percent of the routine data. 

Figure 6 presents the differences (left graph) and percent differences (right graph) of the one-point QC 

checks segregated into the ten concentration ranges. The SO2 acceptance criteria is +10% (percent 

difference). The variability, based on the 25th – 75th percentile spread, at these lower ranges does not 

appear to be significantly different from the one-point QC checks at higher concentration ranges. 
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Carbon Monoxide (Fig. 7) - of the 51 states and territories reporting hourly carbon monoxide data, no 

state was reporting maximum values greater than the one-hour NAAQS (35 ppm) and only three states 

were reporting hourly maximum values above the eight hour NAAQS (9 ppm). In addition, 99 percent of 

all states hourly data was below 3.0 ppm. States were providing one-point QC values at lower ranges 

(graph on right) but about 60 percent of the one-point QC checks were being performed at concentrations 

greater than 99 percent of the routine ambient air data. 

Similar to the other gaseous pollutants, the variability of percent differences, based on the 25th – 75th 

percentile spread of the box and whisker plots, does not appear to be significantly different between the 

higher and the lower one-point QC concentration values. 
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The 2013 data at the lower concentration levels used in this assessment may represent monitoring 

organizations that have invested in the technology (i.e., analyzers, calibration devices and standards at 

NCore sites) necessary to adequately calibrate and estimate precision and bias at the concentrations 

measured at ambient levels more reflective of mean concentrations. However, the data also demonstrates 

that the technology is available to measure and report precision and bias at mean/median ambient air 

concentration levels. 

As indicated in these results described above, challenging ambient air analyzers with a one-point QC 

check at the level of the NAAQS provides an incomplete characterization of the precision and bias of the 

data actually reported to the AQS since, in most cases, the precision and bias estimates from the 2013 QC 

checks represent the uncertainty at a concentration level above 99 percent of the SLAMS data reported to 

AQS. These estimates may not be reflective of the precision and bias of these instruments at 

concentrations routinely measured. 

IMPLICATIONS 

Over the years, EPA has developed guidance to reflect a different paradigm for the use of a number of QC 

checks in the ambient air quality system. Figure 9 represents a view of the way various QC checks are 

currently implemented. This example chart represents data from an ozone monitor with an operating 

range of 500 ppb (typical operating ranges are 500 or 1000 ppb). The routine data is from a monitoring 

organization and represents the distribution of typical values seen in a routine monitoring organization. 

For the 2013 data reported above, the mean and median concentrations for all states reporting ozone was 

30 ppb (lower than the 50 ppb mean reported in Fig.9). 
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Calibrations- Multipoint calibrations were evenly spaced over the operating range (0-500 ppb). 

Span Check- a span check is normally set at 80% of the operating range (in this case 400 ppb). 

One-point QC check- The current one-point QC check in appendix A (prior to the proposal) had a range 

of 10 – 100 ppb and although the regulation suggested that the checks should represent routine 

concentrations, 90 percent of the checks in the 2013 data for ozone were between 60-100 ppb. Based on 

this scenario (Fig. 9) and the concentrations of routine data in the ambient air network, one can see that 

few quality control points reflect where the majority of the data are measured. 

EPA has made strides, with the assistance of monitoring organizations, to develop more useful quality 

control information, as illustrated in Figure 10. In this case, instead of calibrating all the way to the 

operating range, monitoring organizations can select a calibration scale that is based on the maximum 

values reported at the site (or monitoring agency) or at some value just above a historical max. This 

allows more calibration points to be placed at concentration ranges found in routine data. The span point 

can still be placed at 80 percent of the calibration range but can also be selected to represent a 

concentration close to the NAAQS. This would eliminate the concern by commenters that the one-point 

QC should represent the NAAQS since the span point is implemented at the same frequency (minimally 

every two weeks) as the one-point precision check. The one-point QC check can then be measured in a 

concentration range that is more reflective of the routine concentrations. 
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EPA also realizes that the distribution of routine data does not always fall as “nicely” as the ozone data in 

Figure 9 indicate. Figure 11 provides a national frequency distribution of the SO2 data. This figure 

represents average state values for the various percentiles across all states (with the exception of Hawaii 

which has some very extreme SO2 values due to natural events). For example, the high value (104 ppb) 

is the average of the 47 state max values (not including Hawaii). What this is meant to demonstrate is 

that EPA will need to evaluate each pollutant in order to determine the best process to utilize the QC 

information so that it can reflects the precision and bias of the routine ambient air being measured as well 

as the precision and bias around the NAAQS. 
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SUMMARY

As has been shown, monitoring agencies can test and achieve acceptable precision and bias results at 

lower concentration levels. Providing data users with estimates of precision and bias where the majority 

of our ambient air data are measured should be a programmatic goal and monitoring organizations should 

be working with EPA Regional Offices to develop the budgets necessary for purchasing the updated 

equipment and revising related procedures. The EPA will continue to endorse this approach to make the 

QC checks more meaningful and will consider future revisions to Appendix A to either require QC checks 

at two concentration levels (i.e., one around the mean concentrations and one related to the NAAQS) or 

require the span check to be reported to AQS. In addition, to alleviate concerns about failing the 

acceptance criteria at lower QC concentrations, EPA will evaluate suggestions by monitoring 

organizations to raise acceptance criteria or look at alternative acceptance criteria (e.g. difference instead 

of percent difference). Since acceptance criteria is included in guidance, EPA will have the opportunity to 

perform the evaluations without effecting the regulation. In 2011, EPA developed similar guidance for 

lower concentration levels of the annual performance evaluation audits.