Appendix K to Part 50 - Interpretation of the National Ambient Air Quality Standards for Particulate Matter
40:2.0.1.1.1.0.1.20.12 : Appendix K
Appendix K to Part 50 - Interpretation of the National Ambient Air
Quality Standards for Particulate Matter 1.0 General
(a) This appendix explains the computations necessary for
analyzing particulate matter data to determine attainment of the
24-hour standards specified in 40 CFR 50.6. For the primary and
secondary standards, particulate matter is measured in the ambient
air as PM10 (particles with an aerodynamic diameter less than or
equal to a nominal 10 micrometers) by a reference method based on
appendix J of this part and designated in accordance with part 53
of this chapter, or by an equivalent method designated in
accordance with part 53 of this chapter. The required frequency of
measurements is specified in part 58 of this chapter.
(b) The terms used in this appendix are defined as follows:
Average refers to the arithmetic mean of the estimated
number of exceedances per year, as per Section 3.1.
Daily value for PM10 refers to the 24-hour average
concentration of PM10 calculated or measured from midnight to
midnight (local time).
Exceedance means a daily value that is above the level of
the 24-hour standard after rounding to the nearest 10 µg/m 3
(i.e., values ending in 5 or greater are to be rounded
up).
Expected annual value is the number approached when the
annual values from an increasing number of years are averaged, in
the absence of long-term trends in emissions or meteorological
conditions.
Year refers to a calendar year.
(c) Although the discussion in this appendix focuses on
monitored data, the same principles apply to modeling data, subject
to EPA modeling guidelines.
2.0 Attainment Determinations 2.1 24-Hour Primary and Secondary
Standards
(a) Under 40 CFR 50.6(a) the 24-hour primary and secondary
standards are attained when the expected number of exceedances per
year at each monitoring site is less than or equal to one. In the
simplest case, the number of expected exceedances at a site is
determined by recording the number of exceedances in each calendar
year and then averaging them over the past 3 calendar years.
Situations in which 3 years of data are not available and possible
adjustments for unusual events or trends are discussed in sections
2.3 and 2.4 of this appendix. Further, when data for a year are
incomplete, it is necessary to compute an estimated number of
exceedances for that year by adjusting the observed number of
exceedances. This procedure, performed by calendar quarter, is
described in section 3.0 of this appendix. The expected number of
exceedances is then estimated by averaging the individual annual
estimates for the past 3 years.
(b) The comparison with the allowable expected exceedance rate
of one per year is made in terms of a number rounded to the nearest
tenth (fractional values equal to or greater than 0.05 are to be
rounded up; e.g., an exceedance rate of 1.05 would be rounded to
1.1, which is the lowest rate for nonattainment).
2.2 Reserved 2.3 Data Requirements
(a) 40 CFR 58.12 specifies the required minimum frequency of
sampling for PM10. For the purposes of making comparisons with the
particulate matter standards, all data produced by State and Local
Air Monitoring Stations (SLAMS) and other sites submitted to EPA in
accordance with the part 58 requirements must be used, and a
minimum of 75 percent of the scheduled PM10 samples per quarter are
required.
(b) To demonstrate attainment of the 24-hour standards at a
monitoring site, the monitor must provide sufficient data to
perform the required calculations of sections 3.0 and 4.0 of this
appendix. The amount of data required varies with the sampling
frequency, data capture rate and the number of years of record. In
all cases, 3 years of representative monitoring data that meet the
75 percent criterion of the previous paragraph should be utilized,
if available, and would suffice. More than 3 years may be
considered, if all additional representative years of data meeting
the 75 percent criterion are utilized. Data not meeting these
criteria may also suffice to show attainment; however, such
exceptions will have to be approved by the appropriate Regional
Administrator in accordance with EPA guidance.
(c) There are less stringent data requirements for showing that
a monitor has failed an attainment test and thus has recorded a
violation of the particulate matter standards. Although it is
generally necessary to meet the minimum 75 percent data capture
requirement per quarter to use the computational equations
described in section 3.0 of this appendix, this criterion does not
apply when less data is sufficient to unambiguously establish
nonattainment. The following examples illustrate how nonattainment
can be demonstrated when a site fails to meet the completeness
criteria. Nonattainment of the 24-hour primary standards can be
established by the observed annual number of exceedances (e.g.,
four observed exceedances in a single year), or by the estimated
number of exceedances derived from the observed number of
exceedances and the required number of scheduled samples (e.g., two
observed exceedances with every other day sampling). In both cases,
expected annual values must exceed the levels allowed by the
standards.
2.4 Adjustment for Exceptional Events and Trends
(a) An exceptional event is an uncontrollable event caused by
natural sources of particulate matter or an event that is not
expected to recur at a given location. Inclusion of such a value in
the computation of exceedances or averages could result in
inappropriate estimates of their respective expected annual values.
To reduce the effect of unusual events, more than 3 years of
representative data may be used. Alternatively, other techniques,
such as the use of statistical models or the use of historical data
could be considered so that the event may be discounted or weighted
according to the likelihood that it will recur. The use of such
techniques is subject to the approval of the appropriate Regional
Administrator in accordance with EPA guidance.
(b) In cases where long-term trends in emissions and air quality
are evident, mathematical techniques should be applied to account
for the trends to ensure that the expected annual values are not
inappropriately biased by unrepresentative data. In the simplest
case, if 3 years of data are available under stable emission
conditions, this data should be used. In the event of a trend or
shift in emission patterns, either the most recent representative
year(s) could be used or statistical techniques or models could be
used in conjunction with previous years of data to adjust for
trends. The use of less than 3 years of data, and any adjustments
are subject to the approval of the appropriate Regional
Administrator in accordance with EPA guidance.
3.0 Computational Equations for the 24-Hour Standards 3.1
Estimating Exceedances for a Year
(a) If PM10 sampling is scheduled less frequently than every
day, or if some scheduled samples are missed, a PM10 value will not
be available for each day of the year. To account for the possible
effect of incomplete data, an adjustment must be made to the data
collected at each monitoring location to estimate the number of
exceedances in a calendar year. In this adjustment, the assumption
is made that the fraction of missing values that would have
exceeded the standard level is identical to the fraction of
measured values above this level. This computation is to be made
for all sites that are scheduled to monitor throughout the entire
year and meet the minimum data requirements of section 2.3 of this
appendix. Because of possible seasonal imbalance, this adjustment
shall be applied on a quarterly basis. The estimate of the expected
number of exceedances for the quarter is equal to the observed
number of exceedances plus an increment associated with the missing
data. The following equation must be used for these
computations:
Where: eq = the estimated number of exceedances
for calendar quarter q; vq = the observed number of exceedances for
calendar quarter q; Nq = the number of days in calendar quarter q;
nq = the number of days in calendar quarter q with PM10 data; and q
= the index for calendar quarter, q = 1, 2, 3 or 4.
(b) The estimated number of exceedances for a calendar quarter
must be rounded to the nearest hundredth (fractional values equal
to or greater than 0.005 must be rounded up).
(c) The estimated number of exceedances for the year, e, is the
sum of the estimates for each calendar quarter.
(d) The estimated number of exceedances for a single year must
be rounded to one decimal place (fractional values equal to or
greater than 0.05 are to be rounded up). The expected number of
exceedances is then estimated by averaging the individual annual
estimates for the most recent 3 or more representative years of
data. The expected number of exceedances must be rounded to one
decimal place (fractional values equal to or greater than 0.05 are
to be rounded up).
(e) The adjustment for incomplete data will not be necessary for
monitoring or modeling data which constitutes a complete record,
i.e., 365 days per year.
(f) To reduce the potential for overestimating the number of
expected exceedances, the correction for missing data will not be
required for a calendar quarter in which the first observed
exceedance has occurred if:
(1) There was only one exceedance in the calendar quarter;
(2) Everyday sampling is subsequently initiated and maintained
for 4 calendar quarters in accordance with 40 CFR 58.12; and
(3) Data capture of 75 percent is achieved during the required
period of everyday sampling. In addition, if the first exceedance
is observed in a calendar quarter in which the monitor is already
sampling every day, no adjustment for missing data will be made to
the first exceedance if a 75 percent data capture rate was achieved
in the quarter in which it was observed.
Example 1
a. During a particular calendar quarter, 39 out of a possible 92
samples were recorded, with one observed exceedance of the 24-hour
standard. Using Equation 1, the estimated number of exceedances for
the quarter is:
eq = 1 × 92/39 = 2.359 or 2.36.
b. If the estimated exceedances for the other 3 calendar
quarters in the year were 2.30, 0.0 and 0.0, then, using Equation
2, the estimated number of exceedances for the year is 2.36 + 2.30
+ 0.0 + 0.0 which equals 4.66 or 4.7. If no exceedances were
observed for the 2 previous years, then the expected number of
exceedances is estimated by: ( 1/3) × (4.7 + 0 + 0) = 1.57 or 1.6.
Since 1.6 exceeds the allowable number of expected exceedances,
this monitoring site would fail the attainment test.
Example 2
In this example, everyday sampling was initiated following the
first observed exceedance as required by 40 CFR 58.12. Accordingly,
the first observed exceedance would not be adjusted for incomplete
sampling. During the next three quarters, 1.2 exceedances were
estimated. In this case, the estimated exceedances for the year
would be 1.0 + 1.2 + 0.0 + 0.0 which equals 2.2. If, as before, no
exceedances were observed for the two previous years, then the
estimated exceedances for the 3-year period would then be ( 1/3) ×
(2.2 + 0.0 + 0.0) = 0.7, and the monitoring site would not fail the
attainment test.
3.2 Adjustments for Non-Scheduled Sampling Days
(a) If a systematic sampling schedule is used and sampling is
performed on days in addition to the days specified by the
systematic sampling schedule, e.g., during episodes of high
pollution, then an adjustment must be made in the equation for the
estimation of exceedances. Such an adjustment is needed to
eliminate the bias in the estimate of the quarterly and annual
number of exceedances that would occur if the chance of an
exceedance is different for scheduled than for non-scheduled days,
as would be the case with episode sampling.
(b) The required adjustment treats the systematic sampling
schedule as a stratified sampling plan. If the period from one
scheduled sample until the day preceding the next scheduled sample
is defined as a sampling stratum, then there is one stratum for
each scheduled sampling day. An average number of observed
exceedances is computed for each of these sampling strata. With
nonscheduled sampling days, the estimated number of exceedances is
defined as:
Where: eq = the estimated number of exceedances
for the quarter; Nq = the number of days in the quarter; mq = the
number of strata with samples during the quarter; vj = the number
of observed exceedances in stratum j; and kj = the number of actual
samples in stratum j.
(c) Note that if only one sample value is recorded in each
stratum, then Equation 3 reduces to Equation 1.
Example 3
A monitoring site samples according to a systematic sampling
schedule of one sample every 6 days, for a total of 15 scheduled
samples in a quarter out of a total of 92 possible samples. During
one 6-day period, potential episode levels of PM10 were suspected,
so 5 additional samples were taken. One of the regular scheduled
samples was missed, so a total of 19 samples in 14 sampling strata
were measured. The one 6-day sampling stratum with 6 samples
recorded 2 exceedances. The remainder of the quarter with one
sample per stratum recorded zero exceedances. Using Equation 3, the
estimated number of exceedances for the quarter is:
Eq = (92/14) × (2/6 + 0 + . . . + 0) = 2.19.
[71 FR 61224, Oct. 17, 2006]