Testimony of Dr. Gi

- Dong Kim Page 1 of 10 STATE OF NEW MEXICO BEFORE THE ENVIRONMENTAL IMPROVEMENT BOARD

IN THE MATTER OF PROPOSED REVISIONS TO THE STATE IMPLEMENTATION PLAN FOR THE SAN JUAN GENERATING STATION BEST AVAILABLE RETROFIT TECHNOLOGY DETERMINATION No. EIB 13

- 02(R)

_____________________________________________________________________________
NMED EXHIBIT 1 2

– WRITTEN TESTMONY OF Dr. GI

- DONG KIM

______________________________________________________________________________ Statement of Witness Qualifications

Gi

- Dong Kim is a Modeling Specialist in the Modeling Unit of the Air Quality Burea u’s Planning and Policy Section, where he has worked for eleven years. D r. Kim h olds a Ph

. D

. and a Master of Science Degree in Environmental Engineering from the University of Tennessee. His responsibilities with the Bureau include the r eview and perform ance of computer

- based dispersion modeling in support of permitting, enforcement and regulati on development actions

.
Dr. Kim has performed approximately 154 modeling analyses for the Bureau. He was responsible for reviewing the dispersion modeling analysis performed by PNM throughout the BART determination process. His resume is attached as exhibit 12a.
Testimony

Introduction

T he major steps involved in performing this visibility modeling analysis were to: 1

o Determine natural visibility conditions as a baseline visibility condition ; 2

o Evaluate the emission rates of the pollutants that deteriorate visibility ; 3

o Run CALMET meteorology model with 2001 year of meteorological data ; 4

o Run CALPUFF model with the emission rates and the output of CALMET model ; 5

o Run CALSUM post

- processor ; 6

o Run CALPOST post

- processor to perform visi bility calculations ; and 7

o Repeat all the procedures mentioned above with 2002 and 2003 years of 8 meteorological data

. 9 10
Natural visibility (or background) conditions are used as a reference for determination of 11
the impact of the facility sources. More specif ically, CALPOST, which is a post

- processor of the 12Testimony of Dr. Gi

- Dong Kim Page 2 of 10 CAL P UFF modeling system, calculates delta deciviews values that are the difference between 1
deciviews including the impact of the facility sources and the natural visibility condition and 2

deciviews of the na tural visibility condition alone. From among these daily values for each year 3

modeled, the value of the 98 th percentile (approximately equivalent to the 8 th highest value (or 4
day)) is used for comparing the effects of each scenario in improving visibility

. 5
The governing requirements for this analysis are found in 40 C

. F

. R

. Part 51 Appendix Y
, 6

EPA BART Guidelines, and the Western Regional Air Partnership (WRAP) BART modeling 7
guidelines developed by a collaborative effort of tribal governments, state governm ents and 8
various federal agencies to comply with EPA’s regional haze regulations. 9
My role for this project was to make sure that PNM’s visibility modeling analysis was 10

consistent with the BART Modeling Guidelines and then evaluate the visibility improvemen t of 11
each NOx control technology, using PNM’s visibility modeling results. 12
PNM’s Modeling Submissions 13
In 2007, PNM provided NMED with all the modeling results performed on a year

- to

- year 14
basis for the facility

- wide impact for each control scenario. PNM modeled visibility impacts of 15
nitrogen oxides ( NOx )
, sulfur dioxide ( SO 2 ) , and particulate matter (PM), which are the visibility 16
impairing pollutants emitted by the facility. PNM submitted updated modeling analyses 17
performed with revised emission rates and different ammonia background concentrations several 18
times between 2007 and 2012, using the same 2007 modeling approach. PNM submitted the 19
most updated modeling analysis in 2013

. 20
The 2013 modeling was performed with the revised emission rates for Sulfu r Dioxide 21

(SO 2 ), Sulfuric Acid (H 2 SO 4 ), and Total Particulate Matter (TPM) and available NOx control 22
technologies including selective catalytic reduction (SCR), selective non

- catalytic reduction 23Testimony of Dr. Gi

- Dong Kim Page 3 of 10 (SNCR), and also considering unit retirements as an alternati ve operating scenario that ha d not 1
been discussed previously. More specifically, the 2013 modeling analysis incorporated the new 2

SO 2 emission rate of 0.15 lb/MMBtu, total particulate matter (TPM) emission rate of 0.034 3

lb/MMBtu, and H 2 SO 4 emission rates o f 0.00026 lb/MMBtu and 0.000046 lb/MMBtu for SCR 4

and non

- SCR, respectively, from the current NSR permit dated August 31 , 2012. These new 5
emission limits have been incorporated into the Baseline modeling scenario and each NOx 6
control scenario, including EP A’s Federal Implementation Plan (FIP) scenario representing four 7

SCRs, and NMED’s 2011 State Implementation Plan (SIP) scenario representing four SNCRs

. 8

For the State Alternative representing SNCR on Units 1 and 4, and shutdown of Units 2 and 3
, 9

the modeli ng is based on these same emission rates for TPM and H 2 SO 4 , while for SO 2 a rate of 10

0.10 lb/MMBtu is used, as specified in the Term Sheet

. The PNM modeling analysis was 11
performed on a year

- by

- year basis for the facility

- wide impact for the four scenario s. 12
The most significant difference from prior modeling is that the 2013 modeling analysis 13
considered two unit retirements, with SNCR for the other two units, as an alternative operating 14

scenario. 15
In terms of methodology, the major difference between the 2007 and 2013 modeling 16
analyses is that in 2007, PNM used a non

- regulatory version of the CALPUFF modeling system 17

(Version 6.1). In 2013, PNM used a regulatory version of the CALPUFF modeling system
, 18

V ersion 5.8. Another difference is that in 2007, PNM u sed a National Park Service methodology 19
to calculate inorganic condensable partic ulate matter, H 2 SO 4 . In 2013, PNM used the inorganic 20
condensable particulate matter emission rates based on the facility’s total particulate matter 21
emission limit as established in the NSR permit effective August 31 , 2012
, which is more 22

realistic. An additional difference is that the 201 3 modeling analysis was performed with a more 23Testimony of Dr. Gi

- Dong Kim Page 4 of 10 representative ammonia background concentration and an improved method to calculate 1
visibility impacts. T he 2013 modeling approach is more conservative than the 2007 modeling 2
approach. 3

Evaluation of PNM’s Mod eling 4

I determined that t he PM modeling was performed according to th e WR A P BART 5
modeling guidelines and EPA Guidelines

. T he PNM BART modeling was performed using an 6

EPA

- approved version of the CALPUFF model to account for the chemical transformation of 7

N Ox and SO 2 , an EPA

- compiled meteorological data set, and modified EPA’s modeling input 8
files to include the source specific parameters for PNM specific modeling scenarios. The 9
modeled CALPUFF domain, receptors, ozone, and the meteorological data used in the analysis 10
all came directly from E PA modeling. 11
As previously described, PNM modeled the following scenarios: 12

13 Table 1. Target Emissions for Modeling Scenarios 14 Scenario Operation and Target Emissions Baseline Units 1

- 4 operating only with existing air pollution control technology and new permitted SO 2 and Total Particulate Matter (TPM) emission rates of 0.15 lb/MMBtu and 0.034 lb/MMBtu, respectively Sulfuric Acid (H 2 SO 4 ) emission rate of 0.000046 lb/MMBtu for non

- SCR

EPA FIP Units 1

- 4 operating with existing air pollution control technology and with new SCR installation; NOx at 0.05 lb/MMBtu and new permitted SO 2 and TPM emission rates of 0.15 lb/MMBtu and 0.034 lb/MMBtu, respectively Sulfuric Acid (H 2 SO 4 ) emission rate of 0.00026 lb/ MMBtu for SCR

2011 NMEDSIP Units 1

- 4 operating with existing air pollution control technology and with new SNCR installation; NOx at 0.23 lb/MMBtu and new permitted SO 2 and TPM emission rates of 0.15 lb/MMBtu and 0.034 lb/MMBtu, respectively Sulfuric Aci d (H 2 SO 4 ) emission rate of 0.000046 lb/MMBtu for non

- SCR

State Alternative Units 2 & 3 retired, Units 1 & 4 operating with existing air pollution control technology and with new SNCR installation; NOx at 0.23 lb/MMBtu, new permitted TPM emission rate of 0.034 lb/MMBtu, and aTestimony of Dr. Gi

- Dong Kim Page 5 of 10 reduced SO 2 emission rate of 0.10 lb/MMBtu Sulfuric Acid (H 2 SO 4 ) emission rate of 0.000046 lb/MMBtu for non

- SCR 1 After determining that PNM’s modeling conformed to applicable requirements and 2
guidelines, I explored the PNM modeling results to estimate the visibility improvement in three 3

ways recommended by EPA : 98 th percentile deciview (dv) at each Class I area for the four 4

scenario s , average and maximum days exceeding the threshold value of 0.5 dv , and deciview 5
improvement at each C lass I area with addition al NOx control technologies on the existing air 6
pollution control technology

. 7
Figure 1 show s the 98 th percentile deciview values of each NOx control scenario at the 16 8

Class I a reas for comparing the effects of each scenario in imp roving visibility

. D eciview s are 9

the measure of visibility. More specifically, the higher the deciview value is
, the worse the 10
visibility condition is. As shown in Figure 1, the EPA FIP and State Alternative outperform the 11

2011 NMED SIP from the comparison of the three years from 2001 through 2003. Mesa Verde 12
National Park shows the highest 98 th percentile among the 16 Class I areas which is the nearest 13

Class I area to SJGS, located approximately 40 km north of the facility. Grand Canyon Nationa l 14

Park shows the lowest 98 th percentile which is located in the most distant area, located 15
approximately 300 km west of the SJGS. 16
When the frequency of the occurrence of the peak 98 th percentile is compared to each 17
BART technology scenario, the figure il lustrate s that the State Alternative and the EPA FIP more 18
significantly reduce the peak 98 th percentiles than the NMED SIP scenario does. Figure 2 shows 19

t he cumulative 98 th percentile value of the sixteen Class I area for each scenario for the 20
comparison of a general visibility improvement

. 21
Figure 3 shows t he days exceeding a 0 .5 dv threshold at each Class I area for each BART 22
technology scenario for each year of the three years. The figure indicates that the State 23Testimony of Dr. Gi

- Dong Kim Page 6 of 10 Alternative and the EPA FIP significant ly improve visibility as compared to the Baseline and 1

2011 NMED SIP scenarios. The State Alternative closely matches the EPA FIP scenario’s days 2
comparison. 3
Figure 4 shows t he visibility improvement with additional NOx control technologies on 4
top of the base case. The results indicate that the State Alternative and the EPA FIP are better 5
than visibility impacts projected for the 2011 NMED SIP scenario. The State Alternative is 6
comparable to the EPA FIP in improving visibility. 7Testimony of Dr. Gi

- Dong Kim Page 7 of 10 Figure 1. 98 th Percentile on the 16 Class I areasTestimony of Dr. Gi

- Dong Kim Page 8 of 10 Figure 2. Visibility Impact ResultsTestimony of Dr. Gi

- Dong Kim Page 9 of 10 Figure 3. Average and Maximum Days Compared to 0.5 dvTestimony of Dr. Gi

- Dong Kim Page 10 of 10 Figure 4. Visibility Improvement of Each Scenario