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Technical Analyses in Support of the Need for Annual NOx 

Controls in the Final Transport Rule

In support of the final Transport Rule, EPA conducted two analyses to support the need for 

annual NOx controls in order to reduce PM2.5 concentrations. The following document 

summarizes these analyses. 

Analysis of “Nitrate Replacement” in the Transport Rule Modeling

The final Transport Rule remedy (the 2014 “air quality assured trading case”) includes both SO2

and NOx emissions reductions. As part of the development of the remedy, EPA examined the 

magnitude of nitrate increases that are caused by electric generating unit (EGU) SO2 reductions. 

Reductions in SO2 emissions lead to reductions in ammonium sulfate concentrations. This in 

turn frees up ammonia gas which is then available to react with particulate nitrate to form 

ammonium nitrate. Therefore, reductions in SO2 emissions can cause ammonium nitrate 

concentrations to increase. This phenomenon, referred to as “nitrate replacement” occurs when 

the formation of particulate ammonium nitrate is limited by the availability of free ammonia (See 

sections V.A.3, VI.C.1, and VI.D.1.d of the final Transport Rule preamble for additional 

information). Reductions in NOx emissions may help mitigate nitrate replacement by reducing 

the formation of nitric acid that would otherwise be available to form particulate nitrate. 

To assess the magnitude of nitrate replacement that might occur due to the SO2 emissions 

reductions in the Transport Rule, EPA conducted a sensitivity test using air quality modeling, 

where SO2 emission reductions were made, but NOx emissions were kept at “base case” levels. 

For this “SO2 emissions reduction” scenario (2014_sox), EPA used EGU NOx emissions from 

the 2014 base case (2014cs), and SO2 emissions from the 2014 AQAT calibration scenario 

(2014cs_noxsox). In the AQAT calibration scenario, EGU SO2 emissions reductions are made at 

the cost thresholds used in the proposed Transport Rule for the set of Transport Rule proposal 

states. EPA compared the nitrate concentrations for this run with the 2014 base case (i.e., no 

Transport Rule controls). Higher nitrate levels in the SO2 only model run relative to the 2014 

base case indicates nitrate replacement resulting from the EGU SO2 emission reductions. To 

calculate the concentrations of nitrate as well as the annual and daily PM2.5 design values for 

each of the two scenarios (i.e., the 2014 base case and 2014 SO2 emissions reduction scenario), 

EPA post-processed the model outputs through the Modeled Attainment Test Software (MATS). 

The magnitude of nitrate replacement varies seasonally, with the largest magnitudes occurring in 

the colder months when particulate nitrate concentrations are highest. Therefore, we examined 

the MATS outputs on a quarterly basis to better understand the seasonal variations of nitrate 

replacement. Generally, there was little or no nitrate replacement in the 2ndand 3rd quarters, but 

significant amounts of nitrate replacement in the 1st and 4th quarters. We present the results for 

the 1st and 4th quarters below in Table 1.
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Table 1 shows the increases in 1

st and 4th quarter average nitrate concentrations obtained from 

the calculation of annual average PM2.5 for several groups of sites1.

Table 1. Nitrate increases (μg/m3) obtained as part of the calculation of annual average PM2.5

design values during the 1st and 4th quarters for all sites (723 sites) and at 2012 nonattainment 

and maintenance sites (15 sites).

1

st Quarter 

Nitrate Increase 

at All Sites

1

st Quarter 

Nitrate Increase 

at 2012 

Nonattainment 

and Maintenance 

Sites*

4

th Quarter 

Nitrate Increase 

at All Sites 

4

th Quarter 

Nitrate Increase 

at 2012 

Nonattainment 

and Maintenance 

Sites*

Average 0.28 0.59 0.09 0.20

Median 0.22 0.55 0.05 0.24

Maximum 1.15 0.88 0.54 0.28

*The list of sites can be found in the Air Quality Modeling Final Rule TSD.

The results show that SO2 emissions reductions can lead to nitrate increases at many sites, 

through “nitrate replacement”. The largest nitrate increases occur in the 1st quarter. The average 

1

st quarter increase across all sites is 0.28 μg/m3

. The average 1st quarter increase at the 

Transport Rule 2012 annual average PM2.5 nonattainment and maintenance receptors is 0.59 

μg/m3. The maximum nitrate increase at a nonattainment/maintenance site is 0.88 μg/m3. Since 

the average 1st quarter (2014 base case) nitrate concentration at nonattainment and maintenance 

receptors is 3.28 μg/m3(not shown in the table), the 0.59 μg/m3 average nitrate increase 

represents a quarterly average nitrate increase of 18%. In other words, in the absence of any 

NOx emission reductions, SO2 emission reductions similar to those in the proposed Transport 

Rule increase nitrate concentrations by an average of 18% in the first quarter (when nitrate 

concentrations are high).

The impact of nitrate replacement on annual average PM2.5 concentrations is smaller than the 

numbers presented above, since these quarterly values are averaged across all four quarters to get 

the final annual average design value. But the results for the 1st and 4th quarters show that the 

winter nitrate replacement can impact PM2.5 concentrations. It also suggests that 24-hour, or 

“daily”, PM2.5 concentrations in the winter seasons may also be sensitive to nitrate replacement. 

Using the model results, we also examined nitrate replacement for PM2.5 values used in the 

development of the 24-hour PM2.5 design values. Table 2 shows the 1st and 4th quarter average 

 

1 The PM species were post-processed using the standard MATS assumptions. This assumes that nitrate

that is measured on FRM filters is fully neutralized and has water attached to the nitrate ion. 

Consequently, the nitrate values have been adjusted to account for ammonium and water. The nitrate ion 

concentrations are multiplied by 1.29 to account for ammonium and 1.12 to account for water (as 

described in the Air Quality Modeling Final Rule TSD).
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nitrate increases obtained from the daily average PM2.5 NAAQS design value processing2. The 

table shows nitrate increases for the quarterly “high days” concentrations.

Table 2. Nitrate increases (μg/m3) for the 1st and 4th quarter “high days”, as obtained from the 

calculation of daily PM2.5 design values at all sites (718) and at 2012 nonattainment and 

maintenance sites (41 sites)

1

st Quarter 

Nitrate 

Increase at All 

Sites

1

st Quarter Nitrate 

Increase at 2012 

Nonattainment and 

Maintenance Sites*

4

th Quarter 

Nitrate 

Increase at All 

Sites 

4

th Quarter Nitrate 

Increase at 2012 

Nonattainment and 

Maintenance Sites*

Average 0.89 1.43 0.43 0.75 

Median 0..61 1.29 0.12 0.56

Maximum 6.04 4.51 3.98 3.20

*the list of sites can be found in the Air Quality Modeling Final Rule TSD.

The results for daily PM2.5 show that the SO2 emissions reductions lead to nitrate increases at 

many sites through “nitrate replacement”. For 24-hour PM2.5, as was the case with the annual 

PM2.5 assessment, the largest nitrate increases occur in the 1st quarter (Table 2). The average 1st

quarter increase across all sites is 0.89 μg/m3. The average 1st quarter increase at the 2012 daily 

average PM2.5 nonattainment and maintenance receptors is 1.43 μg/m3. Since the average 1st

quarter “high days” (2014 base case) nitrate concentration at nonattainment and maintenance 

receptors is 10.86 μg/m

3 (not shown in the table), the 1.43 μg/m3

average nitrate increase 

represents a quarterly “high days” nitrate increase of 13%. 

The daily average design values are calculated from 98th percentile values for each of five years 

(2003-2007). The 98th percentile values can occur during any of the four quarters, but ~60% of 

the 2014 98th percentile days at all sites come from either the 1st or 4th quarter. Therefore, nitrate 

replacement will be an important factor for many of the 98th percentile values at many sites. 

These results show that on 98th percentile days that occur in the 1st and 4th quarters, nitrate 

replacement can be quite notable in both magnitude and as a percentage of total nitrate 

concentrations. 

In conclusion, EPA finds that “nitrate replacement” has an impact on both annual and 24-hour 

PM2.5 concentrations (particularly in the colder seasons). As indicated above, reductions in NOx 

emissions, when coupled with SO2 reductions, may help mitigate nitrate replacement by reducing 

the formation of nitric acid that would otherwise be available to form particulate nitrate.

 

2 The values in the tables are from the projection of 2005 ambient data to the future year (2014). 2005 

was chosen as a representative year from 2003-2007 base year period. 
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Impact of NOx Emissions on PM2.5 Concentrations- Georgia Zero-out NOx 

Sensitivity

As part of final Transport Rule, EPA used CAMx source apportionment modeling to quantify the 

contributions from NOx and SO2 emissions in upwind states to PM2.5 concentrations at receptors 

predicted to be nonattainment in the 2012 base case for the 1997 annual and/or 2006 24-hour 

PM2.5 NAAQS. The source apportionment modeling and contribution analyses are described in 

section V of the preamble as well as the Air Quality Modeling Technical Support Document for 

the Final Transport Rule. The CAMx PM2.5 source apportionment technique is called the 

Particulate Source Apportionment Tool (PSAT). In this technique all of the source emissions are 

tracked during the model simulation to PM2.5 concentrations. CAMx apportions the PM2.5 

concentrations to their source region and/or source category. The apportioned PM2.5

concentrations add up to the total modeled PM2.5 concentrations. That is, the pieces add up to 

the whole. No mass is lost or created in this process. 

In EPA’s source apportionment modeling, the emissions of SO2, NOx, and primary PM2.5 from 

each of the upwind states are individually tracked to sulfate, nitrate, and primary PM2.5 

concentrations. In order to be able to track the secondary PM2.5 formation, CAMx contains a set 

of procedures which determine how to apportion precursor emissions to secondary pollutants. In 

PSAT, each PM2.5 component species is tracked to its “primary precursor” species. Therefore, 

all sulfate formed in the model is tracked back to SO2 emissions and all nitrate formed in the 

model is tracked back to NOx emissions. This allows for a complete accounting of all PM2.5 

species concentrations without adding or losing mass. By their very nature, secondarily formed 

PM2.5 species are the product of many different (and inter-related) chemical reactions. In 

particular, NOx emissions affect all of the secondarily formed PM2.5 species, including sulfate,

through various photochemical reactions in the model. While individually tracking NOx 

emissions in PSAT to nitrate and SO2 emissions to sulfate is an appropriate approach for source 

apportionment, additional sensitivity modeling studies where NOx emissions are reduced can 

help elucidate the complex interactions and impacts between NOx emissions and the formation 

of nitrate, sulfate, and secondary organic aerosols. 

Several commenters on the proposed Transport Rule noted relatively small source apportionment 

contributions from nitrate (apportioned to NOx emissions) from Southern states. Using the 

source apportionment modeling, EPA examined annual and seasonal contributions of nitrate 

from Southern states. EPA also utilized additional sensitivity modeling to assess these 

contributions. In this study, we performed a sensitivity simulation in which we removed all 

anthropogenic emissions of NOx from a single state The starting point (i.e., baseline scenario) 

for this sensitivity simulation was the Transport Rule 2012 base case. The state selected for the 

zero-out of all anthropogenic NOx emissions was Georgia, since it was one of the states that 

EPA had received specific comments about its NOx emissions and nitrate contributions. The 

concentrations from the Georgia NOx zero-out model run were subtracted from the 2012 base 
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case concentrations to estimate the impacts of Georgia’s NOx emissions on PM2.5 concentrations 

in downwind states. The “difference” in sulfate and nitrate at each receptor is, then, 

“attributable” to the NOx emissions from Georgia. These estimates were compared with the 

2012 source apportionment estimates of nitrate from Georgia at downwind locations3. 

Model results

We compared the results for the Georgia zero-out NOx model run to the Transport Rule nitrate 

contribution results for 2012. The zero-out NOx model run was post-processed in the same way 

as the source apportionment runs (detailed in Appendix C of the Air Quality Modeling Final 

Rule Technical Support Document). We examined the results for both annual and 24-hour PM2.5 

concentrations at each of three sets of receptors, as follows: 

1) All receptors (monitors in the Eastern U.S. 12km modeling domain) outside of Georgia

2) All 2012 Transport Rule nonattainment and maintenance receptors for annual and daily 

PM2.5

3) The receptors that Georgia was ”linked” to in the Transport Rule for annual and daily 

PM2.5

4

Table 1 shows the downwind contributions from NOx to nitrate based on the source 

apportionment modeling and the contributions from NOx to nitrate plus sulfate from the Georgia 

NOx zero-out run. The contributions are calculated for the 695 non-Georgia downwind 

monitoring sites from the Transport Rule analysis.

Table 1. Average annual and 24-hour downwind contributions from Georgia to all 2012 final 

Transport Rule receptors.

Average 

Downwind 

Contribution from 

Georgia Source 

Apportionment 

(nitrate)

Average 

Downwind 

Contribution from 

Georgia NOx Zeroout (nitrate)

Average Downwind 

Contribution from 

Georgia NOx Zeroout (nitrate + 

sulfate) 

Ratio of nitrate+sulfate

contribution to nitrate 

alone, based on the 

Zero-Out modeling

Annual average 

PM2.5 NAAQS

.0044 ug/m3 .0057 ug/m3 .0153 ug/m3 2.7

Daily average 

PM2.5 NAAQS

.0082 ug/m3 .0107 ug/m3 .0374 ug/m3 3.5

 

 

3 There is additionally an impact from NOx emissions on downwind secondary organic carbon 

concentrations. However, this was not assessed since we did not quantify the state-by-state contributions 

to secondary organic carbon impacts in the source apportionment modeling for the Transport Rule.

4 Linkages are established between upwind states and downwind receptors when the upwind state 

contributes at or above the air quality thresholds used for the final Transport Rule (see preamble section 

V.D)
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The results show that the estimated nitrate contribution from the source apportionment and the 

zero-out techniques are of the same order of magnitude. However, the contribution of NOx to 

nitrate plus sulfate from the zero-out run is much higher than the contribution to nitrate alone. 

The average total change in PM2.5 concentrations from NOx emissions (change in sulfate plus 

nitrate concentrations) from the zero-out run is ~2.5 to 3.5 times larger than the impact of NOx 

on nitrate from the zero-out run5. 

Table 2 shows the average downwind PM2.5 contributions from NOx to nitrate in the source 

apportionment model run and the contribution from NOx on nitrate plus sulfate from the Georgia 

NOx zero-out run, at the Transport Rule 2012 nonattainment and maintenance receptors. There 

are 15 annual nonattainment and maintenance PM2.5 receptors (outside of Georgia) and 41 daily 

nonattainment and maintenance PM2.5 receptors6. 

Table 2. Downwind contributions from Georgia to the 2012 final Transport Rule nonattainment 

and maintenance receptors for the PM2.5 NAAQS. 

Average 

Downwind 

Contribution 

from Source 

Apportionment 

(nitrate)

Average 

Downwind 

Contribution from 

Georgia NOx 

Zero-Out (nitrate)

Average 

Downwind 

Contribution from 

Georgia NOx 

Zero-Out (nitrate 

+ sulfate) 

Ratio of 

nitrate+sulfate

contribution to nitrate 

alone, based on the 

Zero-Out modeling

Annual average 

PM2.5 NAAQS

.0051 ug/m3 .0077 ug/m3 .0227 ug/m3 3.0

Daily average 

PM2.5 NAAQS

.0062 ug/m3 .0089 ug/m3 .0392 ug/m3 4.4

The results at the nonattainment and maintenance receptors are similar to the “all receptors” 

results in table 1. And similar to table 1, the contribution of NOx to nitrate plus sulfate from the 

zero-out run is much higher than the contribution from NOx to nitrate alone. In this case, the 

average total change in PM2.5 concentrations from NOx emissions (change in sulfate plus nitrate 

concentrations) from the zero-out run is ~3.0 to 4.5 times larger than the amount attributed to 

NOx through nitrate, based on the zero-out run. 

Table 3 shows the average downwind PM2.5 contributions from NOx to nitrate in the source 

apportionment model run and the contribution from NOx to nitrate plus sulfate from the Georgia 

NOx zero-out run, at the two nonattainment and maintenance receptors for which Georgia was 

found to significantly contribute for both annual and daily PM2.5. Both of the receptors are in 

Jefferson County Alabama. 

 

5 As noted above, the “total” NOx contributions from the zero-out run in this analysis do not include 

impacts on secondary organic carbon. If we were to include the sulfate plus nitrate plus organic carbon 

impacts from NOx, the total impacts would be even greater.

6 The 2012 nonattainment and maintenance receptors for annual PM2.5 and 24-hour PM2.5 are identified in 

section IV of the Air Quality Modeling Final Rule Technical Support Document. 
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Table 3. Downwind contributions from Georgia to receptors to which Georgia significantly 

contributes to nonattainment or maintenance for the PM2.5 NAAQS

Average 

Downwind 

Contribution from 

Source 

Apportionment 

(nitrate)

Average 

Downwind 

Contribution from 

Georgia NOx Zeroout (nitrate)

Average 

Downwind 

Contribution 

from Georgia 

NOx Zero-out 

(nitrate + sulfate) 

Ratio of 

nitrate+sulfate

contribution to nitrate 

alone, based on the 

Zero-Out modeling

Annual average 

PM2.5 NAAQS

0.0127 ug/m3 .0170 ug/m3 0.0651 ug/m3 3.8

Daily average 

PM2.5 NAAQS

.0068 ug/m3 .0098 ug/m3 .2018 ug/m3 20.6

The nitrate results at the receptors in Jefferson County, AL to which Georgia is “linked” are 

similar to the “all receptors” and “all nonattainment and maintenance receptor” results shown in 

Tables 1 and 2. The total nitrate plus sulfate impact at these receptors from the zero-out Georgia 

NOx run are much higher than the impacts to nitrate alone. For example, for the daily PM2.5

NAAQS, the contributions from NOx emissions were 21 times higher when the impacts of NOx 

on sulfate are also considered. 

The Georgia zero-out and source apportionment impacts on downwind nitrate are similar in 

magnitude. But the zero-out modeling shows that NOx emissions reductions also impact 

downwind sulfate concentrations. For Georgia, this is particularly true for its contribution to 

nearby Alabama. These results indicate that the impacts of NOx emissions on PM2.5 

concentrations, considering the complex role of NOx in photochemical reactions involved in the 

formation of sulfate and nitrate, is substantially larger than the impacts on nitrate alone. This 

highlights the importance of simultaneously reducing NOx and SO2 emissions to reduce PM2.5 

concentrations7. 

 

7 Emissions sensitivity modeling and source apportionment models are not expected to give the same 

results, especially in non-linear systems. CAMx PSAT was evaluated by the model developer against 

SO2 zero-out model runs for sulfate. But due to the highly non-linear chemistry, nitrate evaluation 

required a more complicated analysis (see CAMx V5.30 user’s guide). It is also important to note that the 

contribution thresholds for the final Transport rule are compared against the sum total contributions of 

nitrate and sulfate.