# ARIZONA DEPARTMENT OF 

# ENVIRONMENTAL QUALITY

1110West Washington Street Phoenix, Arizona 85007 Janice K. Brewer (602)771-2300 www.azdeq.gov Henry R. Darwin Governor Director



### DeborahJordan Air Director, U.S. EPA Region IX 75 Hawthorn Street Mail CodeAir 

### - 1 

### San Francisco, CA 94105

Re: Arizona Regional Haze State Implementation Plan

On February 28, 2011, 

### ADEQ adopted and submitted to the Environmental Protection Agency (EPA), Arizona's State Implementation Plan (SIP) forRegional Haze under Section 308 ofthe Federal Regional Haze Rule. EPA has identified approvability issues regarding visibility degradation on best days at two IMPROVE monitors. The two monitoring sites are SaguaroNM (SAGUI)and ChiricahuaNM (CHIRI). The monitor SAGUl represents Saguaro National Park, East Unit and CHIRl represents Chiricahua National Monument, Chiricahua Wilderness, and Galiuro Wilderness. ADEQ reviewed visibility monitoring data, emissions inventories, and modeling information used for developing the regional haze SIP. Based on this review, ADEQ maintainsthat degradation will not occur at these monitors and offers thefollowingexplanation in support ofapprovingArizona's Regional Haze SIP. Section 308(d)(l) ofthe Regional Haze Rulerequires that states ensure no degradation in visibility forthe least impaired (best) days. Visibility projections however, show degradation at two IMPROVE monitors, CHIRl and SAGUl



### . Thedegradation at the CHIRl and SAGU1 

### monitors amountsto 0.03 deciview (dv) and 0.1 dv, respectively. According to established literature, the change in deciview that is perceptible to the human eye is 0.5 dv. Even though the amount of degradation is very small, ADEQ agrees that it needstobe addressed. The degradation is a comparison of the 2000-2004 monitored data tothe modeled projections using the CMAQ model, which is based on a projected 2018 emission inventory (titled PRP18b) assembled by the Western Regional Air Partnership (WRAP). Table 

### I below shows the light extinction from each pollutant on the 20% best days for both the 2000-2004 baseline period average and the 2018 projection for the SaguaroNational Monument (SAGUl), alongwith the total light extinction and dv impacts. Table 1also includes the 2005-2009 progress average. It should be noted that the total light extinction value includes a Rayleigh scattering value of 10 inverse megameters (~m-') (per EPA guidance) which constitutes half ofthe light extinction. Table 2 shows the sameinformation for ChiricahuaNational Monument (CHIRI).

Southern Regional Office 400 West Congress Street Suite 433 Tucson, AZ 85701 (520) 628-6733 Prinred on recycled paper

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Table 1: SAGU1Visibilitv Data

Source: visibility projection link on http://vista.cira.colostate.edu/tss/Results~~ePlanning.aspx Table 2: CHIRl Visibilitv Data Sulfate Nitrate Organic Carbon



# 1 Sulfate 

# 1 2.3 

# I 2.3 

# 1 2.1 

# 1 2.7 1

### .O 2.2 

### 1.3 1.1 1.8 0.1 10 20 7 I



# 1 Nitrate 

# 1 0.5 

# I 0.5 

# I 0.4 

# 1 Fine Soil Coarse Material Sea Salt Rayleigh Scattering



## ( Organic Carbon 

# I 1.4 

# 1 1.4 

# I 0.9 

# 1 2.5 1.O 2.3 0.9 1.8 1.8 0.1 10 20 7 Total light extinction Total Deciview 2.8 0.8

7



## 1 Coarse Material 

# I 1.2 

# 1 1.2 

# I 1.2 

# I 1 Elemental Carbon me~oil 

# I Sea Salt 

# I 0.0 

# I 0.0 

# i 0.1 

# I 0.7 0.3 0.4

Rayleigh Scattering Total light extinction

These tables differ slightly from what was reported in the proposed Regional Haze State Implementation Plan (SIP). The submitted SIPcarried the light extinction totwo decimal places. In order to maintain the appropriate level of significant figures, those numbers have been rounded to one decimal pIace. Moreover, in mathematical operations involving significant figures, the final values determined must be reported in such a way that it reflects the reliability of the least precise value. According to EPA's "Guidance for Tracking Progress Under the Regional Haze Rule" EPA has had a "practice of rounding each constant in the aerosol extinction calculation to one significant digit

### ..." This practice has been incorporated into the above tables forthe total light extinction calculation. This is particularly appropriate Total Deciview 10 20 7 10 20 10 20 7 7

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since the Rayleigh scattering value is only carried to one significant figure. Even if each component had been revised to be one significant figure, the resulting total light extinction is the same. Using this approach for both SAGUI and CHIRI, the difference between light extinction (and hence visibility) in the base 2000-2004 period andprojected for 2018 is zero. While the Department maintains that there is no degradation at SAGUl and CHIRl due to the above discussion regardingthe accuracy ofthe light extinction values, Table 1 shows that an increase in fine soil light extinction is the main reason for the visibility degradation that was reported at SAGUl in the SIP submittal. Thevisibility impacts of all other pollutants are projected to remain constant or decrease, with the exception of a small projected increase in organic carbon. However, when these projected values are compared to the 2005-2009 progress conditions, it can be seen that the projections are mostly conservative, and in fact for fine soil,rather than increasing by approximately 60% asprojected, visibility impactsdecreased duringthe progress period by about 30%.
Table 2 shows that an increase in fine soil and sulfate light extinction are the main reasons for the visibility degradation that was reported at CHIRl in the SIP submittal. The visibility impacts of all other pollutants are projected to remain constant or decrease. However, when these projected values are compared to the 2005-2009 progress conditions, it can be seen that the projections are conservative, the only exception being sea salt.
Part of the reason that the projected light extinction values for fine soil are so high is because of questionable assumptions regarding fine soil increases. EPA recommended that the 2018 light extinction projection be conducted using relative response factors(RRFs) to predict future monitored values using a change in modeled values. The RRFs are defined as the ratio ofthe modeled 2018 projections divided by the modeled 2002 values. The RRFs are used as multipliers for the 2002 monitored data in order to calculatethe 2018 "monitored projections" as described inthe followingequations:



### RRF = 

### Modeled201 

### 8 Monitored201

### 8 =

### Monitored2002 

## *RRF where 

### Modeled 2002

Monitored201

### 8 =

### Monitored 2002

## * Modeled201

### 8 Modeled 2002

This means that the RRFs are used to adjust the 2002 monitored data to reflect what would be the projected monitored data in 2018. For most PM25species the REWs were close to one, meaning the model predicted fairly consistent impactsfrom those emissions. However, for fine soil at SAGU1on best days, the RRF was 1.6, meaning the model projected a 60% increase in fine soil impacts. Such a large increase is likely due to poor model performance for fine soil as well as inaccurate projections of 2018 fine soil emissions, as discussed below. These results cast significant doubt on the projected 2018 total light extinction value and resulting visibility degradation.
In addition, as with any emissions inventory projected into the future, assumptions must be made regarding population, and sources (including which sourceswill be in existence atthat time and what the activity level of those sources). Based onthe concernswith the modeled degradation at the two monitors,

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ADEQ reviewed the PRP18b emissions inventory and projected light extinction impacts to evaluate its accuracy. The following information was found that indicates that the projected degradation will not occur:
Assumption of Growth Factors
In developing the PRP18b emissions inventory, the WRAP used a variety of growth factors in order to use the 2002 emission inventory to project the 2018 inventory. The WRAP used several sources to estimate the growth factors, including DOE for fuel combustion, USDA for agricultural sources, CAMD for electric utilities, and EPA's Economic Growth Analysis System (EGAS5.0) for all other sources (except oil and gas).
EGAS is an economic and activity forecast tool that provides growth factors for developing emission inventory projections. EPA recommended the use of EGASto develop 2018projections for the WRAP region in 2005. In August of 2006 EPA identified concerns with the EGAS model. Specifically, EPA observed a disconnect between the emission forecasts for sources such as industrial boilers, petroleum refiners, chemical manufacturing plants, as well as small stationary commercial, institutional, and residential non-point sources. According to EPA's August 4, 2006 draft document titled Improving EPA Emissions Forecasting For Regulatory ImpactAnalyses, "the discrepancy lead to significant over-prediction ofemissions projections.. 

### ." While separatemethods were used for road dust, agricultural dust, and exotic sourceslike fire, the fugitive dust emissions for Arizona sources such as Portland cement, asphalt batch, materials handling, road construction, among many others, were all projected using EGAS which relies on population and economic growth predictions to forecast emissions. In addition, the growth factorswere applied atthe state-level, which doesnot account for the variability in growth within various counties and regions in the state. Therefore, the fugitive dust emission in Arizona are likely over predicted, thus calling into question the visibility impacts from fine soil across all monitors in Arizona, including SAGU

### I and CHlRI



### . The growth factors used for agricultural tilling were taken from USDA Baseline Projections, February 2005. The projections cover a 12-year period from 2003 to 2014 for estimated harvested acres of eight major field crops and assume that the 2002 Farm Act remains in effect for the entire projection period. The baseline scenario is also based on specific assumptions regarding the macroeconomy, policy, weather, and international developments,with no shocks to the agricultural market. For the 2002 and 2018 WRAP modeling scenarios, the projections were extrapolated to get estimates for 2002 and 2018. The growth factors were derived from estimated data not actual harvested acres for agricultural tilling. Similar to the issues identified with the EGAS model, the growth factor derived from the USDA projections does not account for changes and variability inherent to agricultural operations. It also does not reflect projections based on actual harvested acres. Comparing the 2002-20 18extrapolated growth rate to the more recent USDA projected data shows that the growth factorwas should have been 1.2% rather than 3.6%. Thus statewide emissions from agricultural operations are likely overstated. Stationary Source Assumptions Assumptions made during the creation of the PRP18b inventory did not include Best Available Retrofit Technology (BART) determinations, mostly because such determinations had not been

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made when the inventory was prepared. Instead,the WRAP made assumptions onwhat limitsthe facilities would be subject to. The following list details changes that should have been incorporated into the inventory:



### o Apache Generating Station BART limits will reduce the amount of NOx emitted from the facility by 1,600 tpy as compared to PRP 

### 18b. The Apache Station is the largest source nearthe CHIR

### I monitor. 

### o SRPCoronado BART resulted in a 2,000 tpy reduction of SO2when comparedto PRPl8b (BARTlimit 0.08 IbIMMBtu,PRPl8bestimated at 0.15). BARTresulted in approximately 3,000 tpy reduction ofNOxas comparedto PRP18b.
In addition, several other inclusions in the PRPI8b inventory are likely overstated. The following list identifies some of the discrepancies:



### o The Arizona Clean Fuels Refinery (proposed to be built east ofYuma) was included in the PRPl8b inventory has not been (and may not be) built. SO2 and NOx emissions included inthe inventory are 25 1 

### and 352 tpy, respectively; 

### o SO2projections from the ASARCO Hayden Smelter are 3,000 tons per year higher than anytime period in the last 10years. In addition, the companywill be required to reduce emissions of SO2as the area is currently exceedingthe 1-hourSO2standard; 

### o SO2projections from the Arizona Portland Cement Plant are 80 tons per year more than actually emitted from the facility, even during periods of increased economic activity (APC is near the SAGU1 

### monitor).
While the WRAP emissions inventory and modeling is the best information available, and significant time and research went into the project, the 0.1 dv and 0.03 dv degradation reported in the SIP submittal are well within the uncertainty and error of the model and emissions inventory. Upon further reflection ADEQ has concluded that such degradation will likely not occur as there are significant questions about the modeling performance and emissions inventory. In addition, the 2005-2009 progress period does not reflect the degradation that was predicted. Based on the above discussion, ADEQ asks that EPA approve the submitted SIP. Ifyou have any questions,please contact me at (602) 77 1-2288. Sincerely, 

# -

Air ~ualp6Vision

cc. / 

### Colleen McKaughan, EPA Tom Webb, EPA