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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 PM 2.5 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 SO 2 and NO x emissions reducti ons. As part of the development of the remedy, EPA examined the magnitude of nitrate increases that are caused by electric generating unit (EGU) SO 2 reductions. Reductions in SO 2 emissions lead to reductions in ammonium sulfate concentrations. This in

t urn frees up ammonia gas which is then available to react with particulate nitrate to form ammonium nitrate. Therefore, reductions in SO 2 emissions can cause ammonium nitrate concentrations to increase. This phenomenon, referred to as “nitrate replacemen t” 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 mi tigate 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 SO 2 emissions reductions in the Transport Rule, E PA conducted a sensitivity test using air quality modeling, where SO 2 emission reductions were made, but NO x emissions were kept at “base case” levels. For this “SO 2 emissions reduction” scenario (2014_sox), EPA used EGU NOx emissions from the 2014 base case (2014cs), and SO 2 emissions from the 2014 AQAT calibration scenario (2014cs_noxsox). In the AQAT calibration scenario, EGU SO 2 emissions reductions are made at

t he 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 SO 2 only m odel run relative to the 2014 base case indicates nitrate replacement resulting from the EGU SO 2 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 2 014 base case and 2014 SO 2 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 2 n d and 3 rd quarters, but significant amounts of nitrate replacement in the 1 st and 4 th quarters. We present the results for the 1 st and 4 th quarters below in Table 1.2

Table 1 shows the increases in 1 st and 4 th quarter average nitrate concentrations obtaine d from the calculation of annual average PM 2.5 for several groups of sites 1

.

Table 1. Nitrate increases ( μ g/m 3 ) obtained as part of the calculation of annual average PM 2.5 design values during the 1 st and 4 th quarter s 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 Nonattain ment 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 SO 2 emissions reductions can lead to nitrate increases at many sites, through “nitrate replacement”. The largest nitrate increases occur in the 1 st quarter. The average
1 st quarter increase across all sites is 0.28 μ g/m 3 . The average 1 st quarter increase at the Transport Rule 2012 annual a verage PM 2.5 nonattainment and maintenance receptors is 0.59

μ g/m 3 . The maximum nitrate increase at a nonattainment/maintenance site is 0.88 μ g/m 3 . Since the average 1 st quarter (2014 base case) nitrate concentration at nonattainment and maintenance

rece ptors is 3.28 μ g/m 3 (not shown in the table), the 0.59 μ g/m3 average nitrate increase represents a quarterly average nitrate increase of 18%. In other words, in the absence of any NOx emission reductions, SO 2 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 PM 2.5 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 1 st and 4 th quarters s how that the winter nitrate replacement can impact PM 2.5 concentrations. It also suggests that 24

- hour, or “daily”, PM 2.5 concentrations in the winter seasons may also be sensitive to nitrate replacement. Using the model results, we also examined nitrate replacement for PM 2.5 values used in the development of the 24

- hour PM 2.5 design values. Table 2 shows the 1 st and 4 th 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)

.3

nitrate increases obtained from the daily average PM 2.5 NAAQS design value p rocessing 2 . The table shows nitrate increases for the quarterly “high days” concentrations.

Table 2. Nitrate increases ( μ g/m 3 ) for the 1 st and 4 th quarter “high days” , as obtained from the calculation of daily PM2.5 design values at all sites (718) and at 2012 nonatt ainme nt 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 PM 2.5 show that the SO 2 emissions reductions lead to nitrate increases at many sites through “nitrate replacement”. For 24

- hour PM 2.5 , as was the case with the annual
PM 2.5 assessment, the largest nitrate increases occur in the 1 st quarter (Ta ble 2). The average 1 st quarter increase across all sites is 0.89 μ g/m 3 . The average 1 st quarter increase at the 2012 daily average PM 2.5 nonattainment and maintenance receptors is 1.43 μ g/m 3 . Since the average 1 st quarter “high days” (2014 base case) nitrate concentration at nonattainment and maintenance receptors is 10.86 μ g/ m 3 (not shown in the table), the 1.43 μ g/m 3 average nitrate increase represents a quarterly “high days” nitrate increase of 13%.

The daily average design values are calculated from 98 th percentile values for each of five years (2003

- 2007). The 98 th percentile values can occur during any of the four quarters, but ~60% of the 2014 98 th percentile days at all sites come from either the 1 st or 4 th quarter. Therefore, nitrate replacement will be an important factor for many of the 98 th percentile values at many sites. These results show that on 98 th percentile days that occur in the 1 st and 4 th 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
PM 2.5 concentrations (particularly in the colder seasons). As indicated above, reductions in NOx emissions, when coupled with SO 2 reductions, may help m itigate 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 proj ection of 2005 ambient data to the future year (2014). 2005 was chosen as a representative year from 2003

- 2007 base year period.4



### Impact of NOx Emissions on PM 2.5 

### Concentrations

- Georgia Zero

- out NOx Sensitivity

As part of final Transport Rule, EPA used CAMx source apportionment modeling to quantify the contributions from NO x and SO 2 emissions in upwind states to PM 2.5 concentrations at receptors predicted to be nonattainment in the 2012 base case for the 1997 annual and/or 2006 24

- hour
PM 2.5 NAAQS. The sourc e 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 PM 2.5 source apportionment technique is called the Particul ate Source Apportionment Tool (PSAT). In this technique all of the source emissions are tracked during the model simulation to PM 2.5 concentrations. CAMx apportions the PM 2.5 concentrations to their source region and/or source category. The apportioned PM 2.5 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 SO 2 , NOx, and primary PM 2.5 from each of the upwind states are individually tracked to sulfate, nitrate, and primary PM 2.5 concentrations. In order to be able to track the secondary PM 2.5 formation, CAMx contains a set of procedures which determine how to apportion precursor emissions to sec ondary pollutants. In PSAT, each PM 2.5 component species is tracked to its “primary precursor” species. Therefore, all sulfate formed in the model is tracked back to SO 2 emissions and all nitrate formed in the model is tracked back to NO x emissions. Thi s allows for a complete accounting of all PM 2.5 species concentrations without adding or losing mass. By their very nature, secondarily formed
PM 2.5 species are the product of many different (and inter

- related) chemical reactions. In particular, NO x emis sions affect all of the secondarily formed PM 2.5 species , including sulfate, through various photochemical reactions in the model. While individually tracking NOx emissions in PSAT to nitrate and SO 2 emissions to sulfate is an appropriate approach for source apportionment, additional sensitivity modeling s tudies 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 NO x emissions) from Southern states. Using the source apportionment modeling, EPA examined annual and seasonal contributions of nitrate from Southern states. EPA also utilized additi onal 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 sensitivi ty 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 contributio ns. The concentrations from the Georgia NOx zero

- out model run were subtracted from the 2012 base5

case concentrations to estimate the impacts of Georgia’s NOx emissions on PM 2.5 concentrations in downwind states. The “difference” in sulfate and nitrate at each receptor is, then, “attributable” to the NO x emissions from Georgia. These estimates were compared with the 2012 source apportionment estimates of nitrate from Georgia at downwind locations 3

.

Model results

We compared the results for the Georgia zero

- out NOx model run to the Transport Rule n itrate 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 b oth annual and 24

- hour PM 2.5 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
PM 2.5 3) The receptors that Georgia was ”linked” to in the Transport Rule for annual and daily
PM 2.5 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 fin al Transport Rule receptors.

Average Downwind Contribution from Georgia 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 Z ero

- O ut modeling

Annual average PM 2.5 NAAQS .0044 ug/m3 .0057 ug/m3 .0153 ug/m3 2.7

Daily average PM 2.5 NAAQS .0082 ug/m3 .0107 ug/m3 .0374 ug/m3 3.5

3 There is additionally an impact from NO x emissions on downwind secondary organic carbon concentrations. However, this was not assessed since we did not quantify the state

- by

- state contributions to seconda ry 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)6

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 PM 2.5 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 run 5

. 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 nitr ate 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 PM 2.5 receptors (outside of Georgia) and 41 daily nonattainment and maintenance PM 2.5 receptors 6

.
Table 2. Downwind contributions from Georgia to the 2012 final Transport Rule nonattainment and maintenance receptors for the PM 2.5 NAAQS.

Average Downwind Contribution from Source Apportionment (nitrate) Average

Downwind Contribution from Georgia NOx Z ero

- O ut (nitrate) Average

Downwind Contribution from Georgia NOx Zero

- O ut (nitrate + sulfate) Ratio of

nitrate +sulfate contribution to nitrate alone, based on the Z ero

- O ut modeling

Annual average PM 2.5 NAAQS .0051 ug/m3 .0077 ug/m3 .0227 ug/m3 3.0

Daily average PM 2.5 NAAQS .0062 ug/m3 .0089 ug/m3 .0392 ug/m3 4.4

T he 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 PM 2.5 concentrations from NO x 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 PM 2.5 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 PM 2.5 . 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 PM 2.5 and 24

- hour PM 2.5 are identified in section IV of the Air Quality Modeling Final Rule Technical Support Document.7

Table 3. Downwind contributions from Georgia to receptors to which Georgia significantly contributes to nonattainment or maintenance for the PM 2.5 NAAQS

Average Downwind Contribution from Source Apportionment (nitrate) Average

Downwind Contribution from Georgia NOx Zero

out (nitrate) Average

Downwi nd Contribution from Georgia NOx Zero

- out (nitrate + sulfate) Ratio of

nitrate +sulfate contribution to nitrate alone, based on the Z ero

- O ut modeling

Annual average PM 2.5 NAAQS 0.0127 ug/m3 .0170 ug/m3 0. 0 651 ug/m3 3

. 8

Daily average PM 2.5 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. T he 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 PM 2.5 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 NO x emissions reductions also impact downwind sulfate concentrations. For Georgia, this is particularly true for its contribution to nearby Alabama. These results indicate that the impact s of NO x emissions on PM 2.5 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 hig hlights the importance of simultaneously reducing NO x and SO 2 emissions to reduce PM 2.5 concentrations 7

.

7 Emissions sensitivi ty modeling and source apportionment model s are not expected to give the same results, especially in non

- linear systems. CAMx PSAT was evaluated by the model developer against SO 2 zero

- out model runs for sulfate. But due to the highly non

- linear chemistr y, 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.