## Biomass-Fired Cogeneration Project Prevention of Significant Deterioration and Authority to Construct Permit Application
Anderson, California

Prepared for:

Sierra Pacific Industries P.O. Box 496028 Redding, California 96049

May, 2007
Project No. 012692

## Biomass-Fired Cogeneration Project Prevention of Significant Deterioration and Authority to Construct Permit Application
Anderson, California

Prepared for:

Sierra Pacific Industries P.O. Box 496028 Redding, California 96049

Prepared by:
Geomatrix Consultants, Inc. 19203 36 th Avenue W, Suite 101 Lynnwood, Washington 98036 (425) 921-4000

May, 2007
Project No. 012692TABLE OF CONTENTS

Page
1.0 INTRODUCTION.............................................................................................................1 1.1 O RGANIZATION ......................................................................................................2 1.2 S UMMARY OF F INDINGS .........................................................................................2
2.0 PROJECT DESCRIPTION ...............................................................................................4 2.1 P HYSICAL D ESCRIPTION .........................................................................................4 2.2 F UEL S UPPLY ..........................................................................................................5 2.3 P OLLUTANT E MISSION R ATES ................................................................................5 2.3.1 Criteria Pollutants......................................................................................5 2.3.2 Startup Emissions ......................................................................................6 2.3.3 Toxic Air Contaminants ............................................................................7
3.0 REGULATORY SETTING ..............................................................................................9 3.1 F EDERAL R EGULATIONS .........................................................................................9 3.1.1 Prevention of Significant Deterioration.....................................................9 3.1.2 Acid Rain Program....................................................................................9 3.1.3 Air Operating Permit Program ................................................................10 3.1.4 New Source Performance Standards .......................................................10 3.1.5 Maximum Achievable Control Technology............................................11 3.2 S TATE AND L OCAL E MISSION R EGULATIONS ........................................................11 3.2.1 Authority to Construct Permits................................................................11 3.2.2 General Air Pollution Control Regulations .............................................12 3.2.3 Air Toxics Hot Spots (AB 2588).............................................................12 3.2.4 California Environmental Quality Act (CEQA)......................................12 3.2.5 Offsets......................................................................................................12 4.0 CLASS II AIR QUALITY IMPACTS ANALYSIS .......................................................14 4.1 M ODEL S ELECTION ...............................................................................................14 4.2 M ODELING P ROCEDURES ......................................................................................15 4.2.1 Model Setup and Application..................................................................15 4.2.2 Averaging Periods ...................................................................................15 4.2.3 Chemical Transformations ......................................................................15 4.3 E LEVATION D ATA AND R ECEPTOR N ETWORK ......................................................16 4.4 M ETEOROLOGICAL D ATA .....................................................................................16 4.5 E MISSION S OURCE R ELEASE P ARAMETERS ..........................................................17 4.6 A NALYSIS R ESULTS ..............................................................................................17 4.7 S TARTUP A NALYSIS ..............................................................................................18 5.0 CLASS I AIR QUALITY RELATED VALUES ANALYSIS.......................................20 5.1 M ODEL S ELECTION ...............................................................................................20 5.2 M ODELING P ROCEDURES ......................................................................................21 5.2.1 Characterization of Emissions.................................................................21 5.2.2 Averaging Periods ...................................................................................22TABLE OF CONTENTS (Continued)

I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc ii 5.2.3 Chemical Transformations ......................................................................22 5.3 R ECEPTOR N ETWORK ...........................................................................................22 5.4 M ETEOROLOGICAL D ATA .....................................................................................23 5.5 AQRV C ALCULATION P ROCEDURES ....................................................................24 5.6 B ASELINE AQRV D ATA .......................................................................................26 5.7 A NALYSIS R ESULTS ..............................................................................................26

TABLES Table 2-1 Cogeneration Unit Crit eria Pollutant Emission Rates Table 2-2 Project Criteria Pollutant Emission Increases Table 2-3 Cogeneration Unit Toxic Air Contaminant Emission Factors and Rates Table 3-1 Facility-Wide Hazardous Air Pollutant Emissions Table 4-1 Point Source Release Parameters Table 4-2 Significant Structure Heights Table 4-3 Maximum Predicted Crite ria Pollutant Concentrations Table 5-1 Class I Area Distan ces from Proposed Project Site Table 5-2 Speciated Emission Rates for AQRV Analysis Table 5-3 Predicted Class I Area Cr iteria Pollutant Concentrations Table 5-4 Predicted Class I Area Deposition Fluxes Table 5-5 Ten Days with Maximum Pred icted Class I Area Extinction Change Table 5-6 Maximum Predicted Ex tinction Change by Class I Area

FIGURES Figure 2-1 Project Schematic Flow Diagram Figure 2-2 Vicinity of Facility and Class II Modeling Domain Figure 4-1 Final Receptor Locations for Class II Analysis Figure 4-2 Wind Rose, Redding Municipa l Airport, Jan. 1995 to Dec. 1999 Figure 4-3 Source and Significant Structure Locations Figure 4-4 Maximum Predicted 1-H our Average CO Concentrations Figure 4-5 Maximum Predicted 8-H our Average CO Concentrations Figure 4-6 Maximum Predicted 3-Hour Average SO 2 Concentrations Figure 4-7 Maximum Predicted 24-Hour Average SO 2 Concentrations Figure 4-8 Maximum Predicted Annual Average SO 2 Concentrations Figure 4-9 Maximum Predicted 24-Hour Average PM 10 Concentrations Figure 4-10 Maximum Pred icted Annual Average PM 10 Concentrations Figure 4-11 Maximum Predicted Annual Average NO 2 Concentrations Figure 4-12 Maximum Predicted Net Annual Average NO 2 ConcentrationsTABLE OF CONTENTS (Continued)

I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc iii Figure 5-1 CALPUFF Domain a nd Class I Area Locations Figure 5-2 CALPUFF Class I Area Receptor Locations Figure 5-3 Surface Meteorology Stations Used in CALMET Figure 5-4 Precipitation Data Stations Used in CALMET Figure 5-5 Maximum Predicted Annual Average NO 2 Concentrations Figure 5-6 Maximum Predicted 24-Hour Average PM 10 Concentrations Figure 5-7 Maximum Predicted Annual Average PM 10 Concentrations Figure 5-8 Maximum Predicted 3-Hour Average SO 2 Concentrations Figure 5-9 Maximum Predicted 24-Hour Average SO 2 Concentrations Figure 5-10 Maximum Pred icted Annual Average SO 2 Concentrations Figure 5-11 Maximum Predicted Total Nitrogen Deposition Fluxes Figure 5-12 Maximum Predicted Total Sulfur Deposition Fluxes Figure 5-13 Predicted Extinction Coefficients Attributable to Proj ect on November 23, 2002

APPENDICES Appendix A SCAQMD and PSD Forms Appendix B BACT Analysis Appendix C Air Toxics Hot Spot (AB 2588) Prioritization Analysis Appendix D Air Quality Dispersion Modeling Files (CD)I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 1 

### BIOMASS-FIRED COGE NERATION PROJECT PREVENTION OF SIGNIFI CANT DETERIORATION AND

AUTHORITY TO CONSTRUC T PERMIT APPLICATION

Sierra Pacific Industries Lumb er Manufacturing Facility Anderson, California

1.0 INTRODUCTION
Sierra Pacific Industries (SPI) proposes to c onstruct and operate a c ogeneration unit at an existing lumber manufacturing facility located in Anderson, California. The boiler associated with the proposed cogeneration unit will bur n biomass fuel (i.e., non-treated wood and agricultural crop residues, as we ll as urban wood-waste and othe r fuels subject to district approval) generated by the facility, regional lumb er manufacturing facilities, and other biomass fuel sources to produce approximately 200,000 pounds of steam per hour. The steam will be used to dry lumber in existing kilns and for a steam turbine; the steam turbine will drive a generator that will produce electr icity for on site use as well as for sale to the grid. Although no steam sales agreements are currently in pl ace, steam may also be sold to other nearby businesses. The existing biomass-fired boiler will remain operational, but will not operate concurrently with the proposed unit other than periods of operational overlap necessary to ensure adequate uninte rrupted steam production.

Because the existing lumber manufacturing facility is a major stationary source of emissions, and the proposed cogeneration unit is consid ered a major modification, a Prevention of Significant Deterioration (PSD ) permit must be obtained. On March 3, 2003, the U.S. Environmental Protection Agency (EPA) withdrew the PSD delegation from several authorities in EPA Region IX, including Shasta County Air Quality Management District (AQMD), making EPA the PSD permitting authority for Shasta County. However, AQMD issued the initial PSD permit for the Ande rson facility in 1994. Additionally, AQMD Rule 2-1A requires a new or modified emission source to obtain an Authority to Construct (ATC) from the AQMD prior to commencing construction. SPI has retained Geomatrix C onsultants, Inc. (Geomatrix) to prepare a combined PSD/ATC application to be submitted to the AQMD on its behalf.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 2 

### 1.1 O RGANIZATION The key components of this permit application are:

• A description of the project and expected air pollutant emissions;

• A discussion of applicable air quality regulations;

• An analysis of Best Availa ble Control Technology (BACT);

• Analysis of compliance with ambient air quality standards and toxic air pollutant criteria; and

• Analysis of the project’s impact on air qua lity related values in regional Class I

areas.

Standard forms related to the PSD and AT C process are provided in Appendix A.



### 1.2 S UMMARY OF 

### F INDINGS Geomatrix conducted an air quality impact assessme nt of the project usin g five years of hourly meteorological surface data from Redding Muni cipal Airport from 1995 to 1999. The analysis indicates that predicted ambient air pollutant con centrations attributable to the project will not cause or contribute to an exceedance of th e National or California Ambient Air Quality Standards (NAAQS or CAAQS) established to pr otect human health and welfare, nor increase the ambient concentrations in excess of the PSD increments established to prevent deterioration of the area’s exis ting air quality.

Geomatrix also assessed air qua lity related values (AQRVs) including regional haze, nitrogen and sulfur deposition and the effects of primar y and secondary pollutants on sensitive plants and soils at Class I areas in the region. Geomatrix conducted a regional modeling analysis designed to provide realistic estimates of secondary aerosol formation, deposition flux, and light extinction coefficients for visu al range. These analyses indicate:

• Predicted pollutant concentrations in Class I areas attributable to the project are less than the significant impact levels pr oposed by the EPA and those recommended by the Federal Land Managers (FLMs).

• Predicted nitrogen and sulfur deposition fluxes containing primary and secondary aerosols attributable to the project is a small fraction of the existing total deposition and do not exceed the thresholds establis hed by the National Park Service (NPS).I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 3 • Secondary aerosols predicted to be form ed by emissions from the project operating at full capacity do not have th e potential to degrade region al visibility in regional Class I areas.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 4 2.0 PROJECT DESCRIPTION



### 2.1 P HYSICAL 

### D ESCRIPTION Sierra Pacific Industries (SPI) is a family -owned wood products company based in Redding, California. SPI currently operates an existi ng lumber manufacturing facility in Anderson, California. SPI intends to cons truct a new cogeneration unit at th e Anderson facility that would burn biomass fuels in a boiler to produce steam that would be used to gene rate electricity and to heat existing lumber dry kilns at the facility.

The cogeneration unit will consist of a biomass-fired water-wall bo iler with a vibrating grate, a steam turbine, and a generator. The boiler will burn biomass fuels to produce high-pressure steam for the steam turbine. The steam turbin e generator will generate up to 23 megawatts (MW) of electricity. Approximately 7 MW w ill be used to power on-site equipment; the remainder will be sold to a public utility. Low- pressure steam will be extracted from the steam turbine through a controlle d extraction and used to heat the dry kilns.

The final design of the biomass-fired boiler has no t been determined, but it will be similar to a unit designed by the McBurney Corp. of Norcross, Georgia. It will have a maximum annual average heat input of approximately 354.2 m illion British thermal units per hour (MMBtu/hr) and a maximum steam generation rate of 200,000 pounds per hour (lb/hr). Over short-term periods, the boiler may be fired at heat input rates that exceed the annual average rate: an hourly maximum of 389.2 MMBtu/hr (10 percent greater than the annual average), and a maximum 24-hour average of 371.9 MMBtu/hr (5 pe rcent greater than th e annual average). The boiler will be equipped with two natural ga s burners, each with a maximum rated heat input of 62.5 MMBtu/hr, for start up and flame st abilization. The cogeneration unit design will incorporate a selective non-catal ytic reduction (SNCR) system to reduce emissions of oxides of nitrogen (NOx), as well as a multiclone and elec trostatic precipitator (ESP) to control emissions of particulate matter (PM/PM 10 ). A closed-loop two-cell cooli ng tower will be used to dispose of waste heat from the steam turbine. A schema tic flow diagram for the cogeneration facility is presented in Figure 2-1.

The proposed cogeneration unit will be located n ear the existing biomass-fired boiler at SPI’s Anderson lumber manufacturing f acility. The existing facility is bordered on the northeast by the Sacramento River, on the northwest by a pr ivate parcel, on the southwest by Union Pacific Railroad tracks and SR273, and on the southeast by pr ivate parcels. The general vicinity of the facility and the modeling domain are shown in Figure 2-2.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 5 

### 2.2 F UEL 

### S UPPLY Fuel for the cogeneration unit will come from th e existing SPI facilities in California at Arcata, Anderson, Shasta Lake, and Red Bluff, as well as in-forest materials from SPI-owned or controlled timberlands, and various sources of agricultural and urban wood wastes. The available supply from SPI-owned or controlled facilities a nd timberlands totals 400,000 bone dry tons (BDT) per year. In addition, ther e are 50,000 BDT of agricultural and urban wood wastes available to SPI annually. The new bo iler will consume an average of approximately 20 BDT of biomass fuel per hour which equates to 176,000 BDT per year since it is expected to operate as near to contin uously as is practicable.

The Anderson facility currently produces a pproximately 160,000 BDT of wood wastes per year of which 60,000 BDT are consumed by the ex isting cogeneration facility, 20,000 BDT are trucked to other biomass power plants, and the balance is trucked to other markets (e.g., wood chips to pulp mills). The new facility will consume 176,000 BDT per year, 80,000 BDT of which will be generated by SPI’s Anderson f acility, while the bala nce (96,000 BDT) will transported by truck from other SPI sources. An additional 18 tr uck trips per day are expected to be needed to deliver the a dditional fuel to the facility.

The installation of the boiler will not increase em issions from any existing emission units at the Anderson mill. There have been no contemporan eous modifications at the Anderson mill.



### 2.3 P OLLUTANT 

### E MISSION 

### R ATES This section addresses pollutant emission rates associated with the project. The proposed boiler will emit NO x , carbon monoxide (CO), particulate ma tter smaller than ten microns (PM 10 ), PM, sulfur dioxide (SO 2 ), and volatile organic compounds (VOCs) , as well as several substances identified as TACs by the Air Resources Board (ARB).

2.3.1 Criteria Pollutants Table 2-1 presents anticipated criteria pollu tant emission rates from the cogeneration unit during normal operation. Boiler emission factors for NO x , CO, PM 10 , and VOCs were based on guarantees from the boiler and control device manufacturers. The SO 2 emission factor is based on source test information from the existing biom ass-fired boiler. Additional material handling operations associated with the project will be en closed, and, as a result, fugitive dust emissions associated with the project are expected to be negligible.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 6 The cooling tower will emit only PM 10 . The drift eliminators to be used as part of the cooling tower design (DRU-1.5) will achieve a drift of 0.0005 percent or less. Assuming this drift rate, a water flow rate of 27,600 gallons per minute (g pm), and a conservative total dissolved solids (TDS) value of 725 milligrams per liter (mg/l), the PM 10 emission rate from the cooling towers is 1.1 ton per year (TPY).

Consistent with the BACT analysis in Appe ndix B and AQMD Rule 3:26(c)(1), SPI proposes the following emission limits:

• NO x – 115 ppm (3-hour average) and 0.13 lb/MMBtu (30-day average)

• CO – 0.6 lb/MMBtu (3-hour average)

• PM 10 – 0.01 gr/dscf (3-hour average) includi ng filterable and condensable components

SPI does not believe limits are warranted for SO 2 or VOC emissions from the cogeneration unit or for PM 10 emissions from the cooling tower becau se the emission rates are so low.

Table 2-2 summarizes the hourly, daily, and annu al emission increases associated with the project, including the reduction in emission rate s as a result of neve r operating the existing biomass-fired boiler concurrent with the proposed unit (other than some overlap during startup and shutdown to ensure continuous steam pr oduction), and compares them to the PSD significant emission rates (SERs) and AQMD BACT thresholds. As discussed in Chapter 3, the emission rates trigger applicability of th e PSD permit path. Chapters 4 and 5 present dispersion modeling analyses that indicate the emissions will not significantly deteriorate ambient air quality or affect existing compliance with ambient air quality standards. A BACT analysis supporting the criter ia pollutant emission rates is provided as Appendix B.

2.3.2 Startup Emissions SPI typically shuts down its boile rs at least twice per year for maintenance. During the subsequent startup, the boiler is heated gradually to avoid stresses that could physically damage the boiler if it were heated too quickly. The startup period may last up to 24 hours when starting with a “cold” (ambient temperature) furnace, and will be accomplished using the natural gas-fired burners firing pi peline natural gas. Firing at full capacity, these burners will provide only thirty percent of ra ted boiler heat input and will init ially be the sole source of heat input to the boiler during start up. Heating will continue using the natural gas burners until the furnace is hot enough to introduce biomass fuel to the furnace. After biomass fuel is introduced to the furnace, the natural gas firing ra te will be reduced to maintain a steady heatI:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 7 rate. For the remainder of the startup period, the biomass-fuel feed rate will increase until the desired firing rate is achieved and the natural gas firing is no longer need ed. The startup period will end when stable burning of biomass fuel is established under good combustion practices at the desired firing rate and the boiler r eaches is design operating temperature.

During the startup period, CO emission rate s will exceed those experienced under normal operation. Unlike normal operation, it is very di fficult for the boiler manufacturer to estimate startup CO emission rates, which vary conti nuously during the start up process. Because exhaust levels of oxygen are high and CO 2 levels are low during star tup, SPI proposes that the startup CO emission rate limit be a mass-per- unit-time limit rather than a concentration corrected to 12 percent CO 2 as is commonly done for normal operation limits. SPI proposes a startup and shutdown CO emission rate li mit of 400 lb/hr aver aged over 1 hour.

The natural gas burners are also used during boiler shutdown to burn any remaining wood ash in order to prevent temperature excursions in the ESP. The shutdown process is expected to require up to 24 hours for the furnace to reach ambient temperature, a nd to experience hourly average CO emission rates similar to those of star tup. SPI proposes that the boiler be subject to the startup CO emission rate limits during shutdown.

A modeling analysis was performed to dem onstrate that the proposed startup/shutdown emission limits will comply with the CO ambien t air quality standards. This analysis is documented in Chapter 4.

2.3.3 Toxic Air Contaminants
Most TAC emission factors for wood-residue fuel s were based on source tests used to develop emission factors for AP-42 Section 1.6. Howeve r, whereas the EPA combined all source test data to calculate the AP-42 emission factors regardless of control technology, the emission factors used here were calculat ed using the subset of source te sts in which wood-fired boilers were controlled by ESPs. For the hydrogen chlori de (HCl) emission factor , this subset of ESPcontrolled source tests was further reduced by removing source tests performed on units burning municipal solid waste. The hexavalent chromium emissi on factor was calculated using biomass-fired boiler source tests from AP-42 sour ce test data, after excluding source tests that included values based on the de tection limit. The ammonia (NH 3 ) emission rate was based on an anticipated exhaust ammonia concentration of 20 parts per million (ppm), as required by AQMD Rule 3:26.c.4. Ammonia emi ssions are a consequence of operating an SNCR system to reduce boiler NO x emissions to 0.13 lbs/MMBtu.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 8 In cases where no ESP-controlled source test re sults were available for a particular TAC, results associated with other particulate contro l equipment were used. Source test data from units not employing particulate controls or not reporting any control e quipment were included where no other source test data were available. Table 2-3 pr esents the TAC emission factors and emission rates associated with the biomass-fi red boiler. The cooling tower is not expected to emit any TACs.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 9 3.0 REGULATORY SETTING
The proposed biomass-fired cogeneration unit project is subject to federal, state, and local regulations. The following section discusses the applicable regulat ions and why certain regulatory programs are not applicable. It should be noted that the project will be located in an area that is in attainment of all federal ambient air quality standards, but has been designated as not in attainment with the state ozone and PM 10 standards.



### 3.1 F EDERAL 

### R EGULATIONS
3.1.1 Prevention of Significant Deterioration For purposes of new source review, construction of the proposed cogeneration unit is a major modification subject to the requirement of th e PSD program because, as shown in Table 2-2, annual CO emissions have the potential to exceed 250 tons per year. Table 2-2 also shows that potential NO x , CO, and PM 10 emissions exceed the signif icant emission rates (SERs), indicating that PSD review is requi red for each of these pollutants.

PSD regulations require a BACT analysis for a ll air pollutants emitted by a project that exceed the SERs (in this case, NO x , CO, and PM 10 ). The BACT analysis evaluates the energy, environmental, economic, and other costs associ ated with each technology, and weighs those costs against the reduced emissions the tec hnology would provide. BACT analyses are presented in Appendix B for the biomass-fi red boiler and the cooling tower.

In addition, modeling analyses are required to demonstrate co mpliance with th e applicable NAAQS and PSD increments locally, and in nati onal parks and wilderne ss areas. Local and regional air quality modeling an alyses are provided in Chap ters 4 and 5, respectively.

3.1.2 Acid Rain Program The EPA’s Acid Rain Program, Title IV of the Cl ean Air Act, is intended to achieve significant environmental and public health benefits through reductions in emissions of SO 2 and NO x , the primary causes of acid rain. The biomass-fire d boiler proposed by SPI will not be subject to the requirements of the Acid Rain Program becau se it is a cogeneration unit with an electrical generating capacity below the pr ogram applicability threshold.

40 CFR 72.6 identifies criteria used to determine whether a facility is subject to the Acid Rain Program. Section 72.6(b)(4)(ii) states that a bi omass-fired cogeneration unit is not subject to the program if it sells no more th an one third of its potential a nnual electrical output capacity orI:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 10 if it sells less than 219,000 me gawatt (electric)-hours (MWe-hrs ) of electricity annually. A cogeneration unit meeting either of these criteria is not subject to the Acid Rain Program.

The biomass-fired cogeneration unit proposed by SPI meets the definition of a “cogeneration unit” in 40 CFR 72.2 because at least a portion of the steam generated by the boiler will be delivered first to the steam turbine and then used to heat lumber dry kiln s at the existing lumber manufacturing facility. Thus, the steam will be “used twice.” Although SPI expects to sell more than one-third of the boile r’s annual potential el ectrical output capacity, the boiler will be an unaffected source because SPI expects to se ll no more than 219,000 MWe-hrs of electricity annually. Due to the proposed boiler’s cogenera tion status and proposed electrical sales, this boiler is considered an unaffected source.

3.1.3 Air Operating Permit Program The lumber manufacturing facility is a major s ource subject to the Title V air operating permit program. Because the proposed cogeneration unit is a major modification requiring a PSD permit, a significant permit modification is re quired under AQMD Rule 5, Section IV.B.3. The cogeneration unit may not commence operation until the permit revision is approved.

3.1.4 New Source Performance Standards EPA has established performance standards for a number of air pollution sources in 40 CFR Part 60. These New Source Performance Standard s (NSPS) usually represent a minimum level of control that is requi red of a new source. NSPS Subpart Db addresses emissions from boilers that have a heat input of gr eater than 100 MMBtu/hr, and will apply to the cogeneration boiler because the maximum heat input is expected to be 354 MMBtu/hr.

Subpart Db limits PM emissions to 0.03 lb/M MBtu for newly constructed units. At the proposed maximum firing rate, this limit translates into an emission rate of 43 lb PM/hr. Subpart Db also requires exhaus t opacity to be 20 percent or less (6-minute average), except for one 6-minute period per hour, whic h cannot exceed 27 percent opacity. These standards do not apply during startup, shutdown, or a malfunction. The emission rates proposed by SPI reflect BACT (which is more stringent than these NSPS limits), and the PM 10 emission rates proposed for the cogeneration unit are less than those allowed by NSPS.

The cogeneration unit will burn natural gas dur ing startup. Subpart Db prescribes SO 2 and NO x limits on boilers that fire fossil fu els under certain conditions. The SO 2 limits do not apply to boilers that combust natural gas. The NO x limits in Subpart Db do not apply to boilers thatI:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 11 have an annual fossil fuel capacity factor of less than ten percent. SPI will maintain on-site records of the quantities and times that natural gas is fired in the boiler to ensure that gas provides less than 10 percent of the annual fuel input. Consequently, neither the SO 2 nor the NOx emission limits identified in Subpart Db will apply.

3.1.5 Maximum Achievable Control Technology The Clean Air Act Amendments of 1990 require EPA to establish technology-based standards to control hazardous air polluta nts (HAPs). For MACT purposes, a major source is defined as one with a potential to emit (PTE) greater than 10 TPY of a single HAP or more than 25 TPY of all HAPs combined.

The existing and proposed boiler will be the onl y sources of HAPs at th e facility. The two would not operate concurrently other than some overlap during startup and shutdown, and the proposed boiler has a greater fi ring rate, therefore the annual HAP PTE of the proposed boiler constitutes the annual facility -wide HAP PTE, which is summa rized in Table 3-1. The HAP emitted in greatest quantity will be hydrogen chlo ride at an annual rate 5.43 TPY. SPI anticipates that facil ity-wide emissions of all 47 HAPs combined will be 16.7 TPY. The project will not exceed either of the MACT thresholds used to designate a major source, and, as a result, will not be subject to the MACT program.



### 3.2 S TATE AND 

### L OCAL 

### E MISSION 

### R EGULATIONS
3.2.1 Authority to Construct Permits Shasta County AQMD Rule 2, Part 100 requires ne w or modified stationary sources to obtain an ATC air quality permit. The ATC permit a pplication must provide a description of the facility, an inventory of pollutant emissions, and proposed control syst ems for the applicable pollutants. The reviewing agency considers whether BACT has been employed and evaluates predicted ambient concentrations attributable to these emissions to ensure compliance with ambient air quality standards.

BACT applicability is determined based on daily emission thresholds provided in AQMD Rule 2 Part 301. The daily emissions of each pol lutant with the potential for requiring BACT are listed in Table 2-2, along with the daily P TE and regulatory threshold. As shown in the table, BACT is required for re active organic compounds (ROG), NO x , SO 2 , PM 10 , CO, and beryllium. BACT analyses are presented in Appendix B for the biomass-fired boiler and the cooling tower.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 12 As stated in AQMD Rule 2, Pa rt 300, an ATC permit cannot be granted unless the agency determines the project (1) will meet applicable state and federal emission limits; (2) will employ BACT where required; and (3) will not caus e or contribute to violations of ambient air quality standards. This app lication provides the information to enable the AQMD to make those determinations.

3.2.2 General Air Pollution Control Regulations Regulations addressing emissions of specific air contaminants from a single source are contained in AQMD Rule 3, Part 2. For sources constructed after July 1, 1986, PM emissions are limited to 0.15 grains per dry sta ndard cubic foot (gr/dscf), while PM 10 is limited to 0.05 gr/dscf, and combustion PM is limited to 0.10 gr/dscf. SO 2 emissions are limited to 200 parts per million (ppm), and NO x emissions are limited to 300 ppm for solid fuels, and 250 ppm for gaseous fuels. Opacity is lim ited to Ringelmann #2 and/or 40 percent.

3.2.3 Air Toxics Hot Spots (AB 2588) The “Hot Spots” Act, also known as AB 2588 or the Health and Safety Code Section 44300 et seq., requires facilitie s to which the act applies to inventor y and report air toxic emissions from stationary sources. TAC emissions associated with the current project, calculated as described in Section 2.3.3, are presen ted in Appendix C along w ith prioritization scores.

3.2.4 California Environmental Quality Act (CEQA) All ATCs are required to undergo a preliminar y review by the AQMD to determine if any possibility of a significant environmental effect exists. Following this review, the AQMD will determine whether further environmental review is required. If further review is warranted, a determination will be made as to whether or not the AQMD is the Lead Agency or a Responsible Agency, and the Environmental Review will proceed as described in AQMD Environmental Review Guidelines (November, 2003).

3.2.5 Offsets Sections 40918, 40919, 40920, and 40920.5 of the Calif ornia Health & Saftey (H&S) Code require areas that are designated as being in nonattainment with respect to one or more criteria pollutant State or Federal standa rds to achieve “no net increase” in emissions (i.e., offsets) of those pollutants and their pr ecursors. Although Shasta C ounty has been designated a nonattainment area with respec t to the State ozone and PM 10 ambient air quality standards, it has further been classified as having “moderate ai r pollution.” Areas that are not classified has having “extreme air pollution” are allowed, by H&S Section 40918.5, to not include a no-net-I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 13 increase permitting program in their attain ment plan, which the AQMD did in 1997 by repealing Parts 302 and 303 of AQMD Rule 2: 1. Thus, no offsets are required by the AQMD new source review air permitting program.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 14 4.0 CLASS II AIR QUALITY IMPACTS ANALYSIS
Neither an ATC nor a PSD permit can be issued unless the proposed new source or modification can demonstrate that the allowabl e emissions will not cause or contribute to violation of any ambient air quality standard or increment. This is typically accomplished using air quality dispersion modeli ng to predict ambient concentra tions. This chapter discusses the methodology used to develop near-field modeli ng used to predict pollu tant concentrations attributable to project emissions in the Class II areas surrounding the proposed facility. Class II areas are essentially the entire country save fo r areas designated as Class I areas, which are National Parks, Wilderness Areas, and other areas where the smallest PSD increments have been imposed to allow the smallest degree of air quality deterioration. Cl ass II areas have been deemed able to accommodate normal, well-manag ed industrial growth, and, therefore, have higher PSD increments. 1



### 4.1 M ODEL 

### S ELECTION Geomatrix reviewed regulatory modeling technique s to select the most appropriate air quality dispersion model to simulate dispersion of ai r pollutants emitted by the proposed project for a near-field air quality impact analysis. The se lection of a modeling tool is influenced by the potential for exhaust plumes from point sources to be influenced by nearby on-site structures and to impact complex terrain. The terrain at and immediately surrounding the facility, as well as in the north and east por tions of the modeling domain, is relatively flat, however, intermediate and complex terrain exists in the southwest portion of the do main. The heights of proposed and existing structures, and the proposed cogeneration un it stack height, suggests that there is the potential for exhaus t plume downwash to occur.

The U.S. EPA recently established AERMOD as the preferred air dispersion model in the Agency's "Guideline on Air Quality Models" (codified as Appendix W to 40 CFR Part 51, hereafter referred to as the Guideline), supers eding the ISCST3 air dispersion model. As a result, AERMOD is currently the model recomm ended by the EPA’s Guideline on Air Quality Models (codified as Appendix W to 40 CFR Part 51, hereafter referred to as the Guideline) as the preferred dispersion model for complex source configurations and for sources subject to exhaust plume downwash. AERMOD incorporates numerical plume rise algorithms (called the PRIME algorithm) that include the downwash effects a structure may have on an exhaust plume implicitly rather than using the wind tunnel based empirical algorithms of ISCST3.

1 U.S. EPA, New Source Review Workshop Manual, Prevention of Significant Deterioration and Nonattainment Area Permitting. October, 1990.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 15 Importantly, the PRIME algorithm also treats th e geometry of upwind and downwind structures and their relationship to the emission point more precisely, and is able to calculate concentrations within building cavities.

AERMOD was selected for the modeling analysis primarily because it is the most up-to-date dispersion model currently available. A dditionally, the modeling domains and source configurations suggested th e potential for exhaust plume downwash and plume impacts on intermediate and complex terrain.



### 4.2 M ODELING 

### P ROCEDURES AERMOD was applied to both criteria pollutant s and TACs using the regulatory defaults in addition to the options and data discussed in th is section. Electronic ve rsions of the modeling files are provided on a compact disk in Appendix D.

4.2.1 Model Setup and Application
The most recent version of AE RMOD (Version 04300) was applied with the default options for dispersion that depend on local meteorological data, regional upper air data, and the local physical characteristics of land use surroundi ng the facility. AERM OD contains several options for urban dispersion that were not selected for these analyses. The facility is located near, Anderson, California, and the majority of the study domain is ag ricultural land, rangeland, or forest. The effects of surface roughness and other physical characteristics associated with the types of land use in the modeling domain were included in the analysis as part of the meteorological database, described in Section 4.4.

4.2.2 Averaging Periods Criteria and toxic air pollutant co ncentrations predicted by the m odel were averaged over shortterm (1-, 3-, 8-, and 24-hour) and annual av eraging periods as requi red by the applicable ambient criteria for each modeled pollutant.

4.2.3 Chemical Transformations Geomatrix assumed that 100 percent of the emitted NO x is converted to NO 2 . This is a conservative assumption because Section 6.2.3 of the Guideline indicates that a 75 percent conversion ratio is acceptable.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 16 

### 4.3 E LEVATION 

### D ATA AND 

### R ECEPTOR 

### N ETWORK Terrain elevations for receptors and emission s ources were prepared using digital elevation models (DEMs) developed by the United States Geological Survey (USG S) of four 7.5-minute quadrangles obtained from the internet (http://www. mapmart.com): Cottonwood, Enterprise, Olinda, and Redding. These data have a horizontal spatial resolution of 10 meters (m). Terrain heights surrounding the facility indi cate that some of the receptor s used in the simulations were located in intermediate or complex terrain (a bove stack or plume height). The 10-kilometer (km) square simulation domain that was used to assess Class II impacts is shown in Figure 2-2.

Receptors were spaced 500 m apart covering the Class II simulation domain, with 200-m and 50-m spacing receptors grids covering 5-km and 2.5-km nested square areas, respectively. Receptors were also located at 25-m intervals along the facility property boundary. The final receptor locations are shown in Figure 4-1.



### 4.4 M ETEOROLOGICAL 

### D ATA Geomatrix has conducted a survey of available me teorological data for use in the simulations. A representative data set was prepared using a combination of surface data from meteorological station located at the nearby Redding Municipal Airport, su pplemented by National Weather Service (NWS) upper air sounding da ta from Medford, Oregon.

According to the Guideline, five years of repr esentative meteorological data are considered adequate for dispersion modeling applicati ons. Hourly wind speed, wind direction, temperature, ceiling height, and cloud cover data collected from January 1995 until December 1999 at Redding Municipal Airport were extracted from the National Climatic Data Center’s (NCDC’s) Integrated Surface Hourly Weather Ob servations (ISHWO). Th e airport is located approximately 4.5 kilometers (2.8 miles) nort h-northwest of the facility. A wind rose describing the wind speed and wind direction data recorded at the Redd ing Municipal Airport meteorological monitoring station over the entire five-year dataset is shown in Figure 4-2. The wind rose shows that the winds are generally bimodal, with winds generally coming from the north and south, following the broad Sacramento River valley. Upper air radiosonde data for the same period were obtained for the monito ring station at Medfor d, Oregon, approximately 215 kilometers (134 miles) north of the facility.

The meteorological data were processed usi ng the AERMOD meteorol ogical preprocessor, AERMET (Version 04300). AERMET was used to check parameter ranges, identify missing data, and calculate boundary layer parameters for use by AERMOD. The program replacesI:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 17 missing or out-of-range data with missing valu e flags, and AERMOD treats these periods as calms.



### 4.5 E MISSION 

### S OURCE 

### R ELEASE 

### P ARAMETERS Figure 4-3 shows the proposed location of the cogeneration unit stack, as well as significant structures that could potentially influence emissions from the stack. Table 4-1 summarizes the release parameters that were used to repres ent the cogeneration unit stack and the cooling towers in the simulations.

In addition to the release parameters discussed in the previous section, the building dimensions and facility configuration were provided to AERMOD to assess potential plume downwash effects. Wind-direction-specifi c building profiles were prepar ed for the modeling using the EPA’s Building Profile Input Program for the PR IME algorithm (BPIP PRIME). The facility layout and building elevations pr ovided by SPI were used to prepare data for BPIP PRIME, which provides the necessary input data for AE RMOD. Figure 4-3 shows the configuration of significant structures, including t hose of the adjacent lumber manu facturing facility, that were used to develop the BPIP PRIME input files, and Table 4-2 presents the heights of the significant structures incl uded in the simulations.

Based on the site layout shown in Figure 4-3 and the structure heights in Table 4-2, the most significant structure affecting the cogeneration unit stack in the simulations was the boiler building, which is 105 feet (ft), or 32 m, high. For the boiler stack, good engineering practice (GEP) stacks at the same location would have to exceed the maximum creditable GEP height (213 ft or 65 m) to ensure protection against downwash. Therefore, all necessary information provided by BPIP PRIME was included in the s imulations to reflect downwash effects from nearby structures on the boiler st ack. A similar analysis indi cated that emissions from the cooling towers would also be subject to downw ash effects, and the appropriate BPIP PRIME output was included in the simula tions for that source as well.



### 4.6 A NALYSIS 

### R ESULTS To evaluate the potential ambient air pollutant concentrations (i.e., impacts on air quality) attributable to the project, the emission rates and source release parameters described in the previous sections were applie d in the dispersion modeling anal ysis. A preliminary analysis included only the emission increase associated with the proposed cogeneration unit, without accounting for the decreased emissions from the existing boiler. Table 4-3 summarizes the predicted maximum concentrations and compares them to both the applicable monitoring deI:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 18 minimis concentrations and the Significant Imp act Levels (SILs) esta blished in EPA’s New Source Review Workshop Manual (October 1990). The SILs represent incremental, projectspecific impact levels that EPA generally accepts as insignificant with respect to maintaining compliance with the NAAQS. As shown in Tabl e 4-3, none of the pred icted concentrations exceeded the SILs or the monitoring de minimis concentrations, except NO 2 (1.47 μg/m 3 ), which exceeded the annual average SIL (1.0 μg/m 3 ). Figures 4-4 through 4-11 show the spatial variations in the maximum predicted criteria pollutant concentrations , averaged over periods consistent with the applicable ambient standards. The maximum predicted receptor and concentration are also shown.

The preliminary analysis outlined above considered ambient concentrations attributable solely to emission increases associated with the propos ed boiler. The results of this simplified, conservative analysis were compared to the SI Ls, and maximum concentrations less than the SILs indicated that no further analysis was n ecessary. However, because the existing boiler will not be fired concurrently with the proposed boiler (other than during startup and shutdown for steam production continuity), it is appropriate to evaluate the net ambient concentrations resulting from operation of the proposed coge neration unit as well as non-operation of the existing boiler. Because the maximum NO 2 concentration predicted by the preliminary analysis was greater than the applicable SIL, a more rigorous analysis to determine the net ambient concentration increase was necessary for comparison to the SIL.

The existing boiler was included in the net c oncentration modeling simulation using the stack parameters shown in Table 4-1. At each rece ptor, the predicted annual average concentration attributable to the existing boiler was subt racted from the predicted annual average concentration attributable to the proposed c ogeneration unit. The net maximum annual average
NO 2 concentration was 0.49 μg/m 3 , which is less than the NO 2 SIL. Therefore, no further analysis to assess compliance with air quality st andards or PSD increment is required for any criteria pollutant. Figure 4-12 shows th e net maximum predicted annual average NO 2 concentrations, as well as the location of th e maximum predicted concentration receptor.



### 4.7 S TARTUP 

### A NALYSIS AERMOD was applied using the methodology de scribed in the previous sections to demonstrate that the proposed CO startup emi ssion rate will comply w ith both the one- and eight-hour average ambient CO standards.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 19 Both the forced-air and the induced-draft fans in the boiler will opera te throughout the startup process, but the flow will be controlled by dampers to appr oximately 30 percent of normal operation flow (approximately 59,700 act ual cubic feet per minute). This resu lted in an exhaust velocity of 14.0 feet per second. The exhaust temperature during startup will be about 250 oF, approximately 150 oF cooler than normal operation. These conditions were assumed to be constant throughout the startup pr ocess regardless of the fuel mi x used after the first two hours of startup.

Assuming an hourly average CO emission rate of 400 lb/hr, the maximum predicted 1-hour and 8-hour average concentrations were 1,009 and 254 μg/m 3 , respectively. To determine compliance with the NAAQS, these results were combined with background values based on the average of the maximum monitored 1-hour and 8-hour average concentrations in the Sacramento Valley for 2002, 2003, and 2004. 2 The maximum three-year average 1-hour and 8- hour concentrations for the Sacramento Valley were 7.9 ppm (approximately 9,000 μg/m 3 ) and 4.3 ppm (approximately 4,900 μg/m 3 ). Because the Anderson area is likely to be less urban than the most impacted CO monitor in the Sacramento Valley, these background values most likely overstate the actual CO concen trations near th e facility.

Using the conservative background concentra tions described above, the total predicted maximum concentrations (boiler startup emissi ons plus background) were a 1-hour average of 10,009 μg/m 3 , and an 8-hour average of 5,154 μg/m 3 . These concentrations are less than the 1- hour and 8-hour average CO CAAQS of 23,000 and 10,000 μg/m 3 , respectively (the corresponding NAAQS are 40,000 and 10,000 μg/m 3 ). Based on this analysis, the proposed hourly CO emission startup limit of 400 lb/hr wi ll not cause exceedances of the NAAQS or CAAQS.

2 ARB Almanac 2006 – Appendix B: Air Quality Trend Data by Pollutant: Ozone, PM 10 , PM 2.5 , CO, NO 2 , NO X , SO 2 , p. 403.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 20 5.0 CLASS I AIR QUALITY RELATED VALUES ANALYSIS
PSD guidance requires an analysis of potential impacts to air qua lity related values (AQRVs) in Federal Class I areas within 100 km (62.1 miles) of the proposed site from pollutants emitted by the project subject to PSD review. However, for most applications the Federal Land Managers (FLMs) request anal yses of AQRV impacts for additional Class I areas within 200 km (124 miles) of the site.

The locations of all nearby Class I areas in re lation to the proposed project and the modeling domain are shown in Figure 5-1. The Yolla Bolly – Middle Eel Wilderness Area is the Class I area nearest to the site proposed for the facility, about 57 km (35 miles) to the southeast. As shown in Table 5-1, there are four Class I areas where an AQRV analysis is required based on the distance from the proposed project site, and five other areas that are within the expanded range. The modeling domain was selected to be large enough to encompass the Class I area of interest with some allo wance for recirculation.

The AQRVs of concern include visibility, soil , flora, fauna, and aquatic resources. The CALPUFF modeling system is currently recommended for evaluating impacts to AQRVs in Class I areas affected by long-range transport. Potential impacts are characterized based on predictions of total nitrogen and/or sulfur deposition flux, change in light extinction, and pollutant concentrations. Pollutant concentratio n predictions were also used to assess Class I area increment consumption for pollutants subject to PSD review.



### 5.1 M ODEL 

### S ELECTION On April 15, 2003, EPA adopted th e CALPUFF modeling system as the EPA’s preferred model for long-range transport assessments and for ev aluating potential impacts to Class I areas by including CALPUFF in Appendix A of the Guid eline. Features of the CALPUFF modeling system include the ability to consider: sec ondary aerosol formation; gaseous and particle deposition; wet and dry deposit ion processes; complex three- dimensional wind regimes; and the effects of humidity on regional visibility.

Geomatrix used CALMET version 5.53b and CALP UFF version 5.711b; the release date of the versions used is December 16, 2005. Although th ey are not currently the “official” EPA versions of CALMET (5.53a) and CALPUFF (5.711a ), the December 16, 2005 releases correctI:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 21 several errors present in the last official EPA versions of CALMET and CALPUFF. These errors are outlined in Model Change Bulletin B from the model author’s Internet site. 3



### 5.2 M ODELING 

### P ROCEDURES The modeling procedures used for the Class I ar ea analyses followed the recommendations of the Interagency Agency Workgroup on Air Quality Modeling (IWAQM) and the FLM Air Quality Related Values Workgroup (FLAG), ou tlined in the FLAG Phase I Report (December 2000). EPA endorsed these procedures in adva nce in the IWAQM Phase II report (December 1998), and reiterated this endorsement in the April 15, 2003 Federal Register notice (Volume 68, Number 72) that adopted CALPUFF as a Guid eline model. Future more detailed guidance was obtained from the United States Forest Service (Suraj Ahuja) as outlined in the “CALPUFF Reviewer’s Guide 4 ” (hereafter referred to as the “Reviewer’s Guide”). Electronic versions of the modeling files are in cluded on a compact di sk in Appendix D

5.2.1 Characterization of Emissions Data characterizing the chemical com position and size distribution of the PM 10 emitted are needed for the regional haze assessment using the CALPUFF modeling system. PM 10 was speciated into components as shown in Ta ble 5-2 using AP-42 and the EPA’s SPECIATE database (version 3.2). AP-42 was used to calculate how PM 10 should be divided into coarse and fine fractions for emissions from the wood-fired boiler. For the wood-fired boiler emissions, fine mass was divided into fractions according to s uggested revisions to SPECIATE Profile 22008 for wood waste fired boilers. 5 SPECIATE is the EPA repository of particulate and organic compound profiles for a variety of s ources for use in source apportionment studies. This information was used to estimate the fr actions of elemental carbon (EC), organic carbon (OC), sulfate, nitrate, and crustal mass that make up the fine fraction of the emitted particulate matter. Cooling tower emissions were assumed to be entirely in the fine fraction, or less than 2.5 micrometers in diameter and assumed to have scattering char acteristics similar to crustal material.

3 CALPUFF Version 5.71 Model Change Bulletin B can be obtained at http://www.src.com/calpuff/MCB_b.txt.
4 Gebhart, Howard. CALPUFF Reviewer’s Guide (Draft). Prepared by Air Resource Specialists, Inc. for the USDA Forest Service and the Nationa l Park Service. September 2005.
5 PES, 2004. Recommendations for the Update and Improveme nt of Existing PM2.5 Split Factors. EPA Contract 68-D-02-104/WA1-05, Pacific Environmental Services, PO Box 120077, Research Triangle Park, NC 27709, September 29, 2003.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 22 5.2.2 Averaging Periods Predicted pollutant concentrations attributable to the project were averaged for comparison with 3-hour, 24-hour, and annual average SO 2 , 24-hour and annual average PM 10 , and annual average NO x Class I SILs. Predicted extinction coe fficients and total nitrogen and sulfur deposition fluxes were calculated as 24-hour and annual averages, respectively. In all instances, comparisons with regulatory criteria were ba sed on the maximum predicted values over the three year simulation for each averaging pe riod. The simulations were performed using estimated maximum short-term emission rates and thus are conservative with respect to the annual criteria.

5.2.3 Chemical Transformations
The NO x chemistry in CALPUFF depends on the ambi ent ammonia concentration to establish the equilibrium between gaseous nitric acid and ammonium n itrate. However, ambient ammonia concentrations are not explicitly simu lated by CALPUFF and the user must select an appropriate background concentration. The IWAQM Phase II Recommendations suggest typical ammonia concentrations are: 10 parts per billion (ppb) for grasslands, 0.5 ppb for forests, and 1 ppb for arid lands during warmer w eather. Since land use in the model domain is mixed, a 10 ppb background ammonia concentrati on was conservatively used for the AQRV studies. Such a high background is considered co nservative because it ensures the conversion of NO x to ammonium nitrate is not limited by a lack of ammonia for the range of NOx concentrations predic ted in this study.

Reaction rates in the CALPUFF chemistry algorithms are also influenced by background ozone concentrations. A conservative backgr ound ozone concentration of 80 ppb was used throughout the modeling domain for all hours of the day and seasons of the year. Based on monitoring data collected within the study domain dur ing 2003 through 2005, ozone concentrations are generally less than 80 ppb except for a few episodes a year in the Sacramento Valley. The highest 8-hour average ozone concentrations recorded at Lassen Volcanic National Park wa s 78 ppb during 2003 through 2005.



### 5.3 R ECEPTOR 

### N ETWORK The CALPUFF dispersion model simulations asse ssed AQRVs at discrete receptors obtained from the National Park Service. Figure 5-2 show s these receptor locations within each Class I

area. 6 In addition to the discrete receptors, a r eceptor grid with 4-km spacing was also used

6 http://www2.nature.np s.gov/air/Maps/Receptors/index.cfmI:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 23 throughout the CALPUFF modeling domain for AQRV predictions. The 4-km mesh size receptors were used to construct plots showing th e spatial variation of the calculated parameters throughout the modeling domain. Th ese plots were used for diagnostic purposes, as well as to develop the figures presented in this permit application. Co mparisons with AQRV criteria were always based on the discrete receptor locations and elevations.



### 5.4 M ETEOROLOGICAL 

### D ATA Geomatrix obtained meteorological data se ts from EPA based on diagnostic numerical simulations of continental U.S. weather w ith the Penn State and National Center of Atmospheric Research Mesoscale Model (MM5). The AQRV analysis used three years of hourly 36-km horizontal mesh size MM5 output data from January 2001 to December 2003. These same MM5 datasets are also be used by the Western Regional Air Partnership to assess industrial sources subject to Be st Available Retrofit Technology review as part for the EPA Regional Haze Rule.

CALMET, the meteorological preprocessor compone nt of the CALPUFF system, was used to combine the MM5 simulation data, surface observa tions, terrain elevations, and land use data into the format required by the dispersion m odeling component CALPUFF. In addition to specifying the three-dimensional wind fiel d, CALMET also estimates the boundary layer parameters used to characterize diffusion and deposition by the dispersion model. Major features of the CALMET application and input data preparation are as follows:

• The model domain is depicted in Figure 5-1 and Figure 5-2. The horizontal mesh size was 4 km and the domain covered an area of 400 km-by-400 km. There were ten vertical levels, ranging geometrica lly from the surface to 4000 m. A Lambert Conformal Coordinate system was used with an origin of 40N, 122W and standard latitudes of 30N and 60N.

• Land use and terrain data were prepared using the processing tools accompanying the CALPUFF modeling system and the US GS 1:250,000 scale data sets available on the Internet resulting in 4-km mesh size fields. Figure 5-2 shows the 4-km mesh size terrain used in the simulations.

• Surface weather observations were obtained at the 30 stations shown in Figure 5-3 from the National Center of Atmospheri c Research dataset ds472.0. Twenty-two of these stations had a data recovery of gr eater than 95 percent. In order for CALMET to complete a simulation of each hour, key variables are needed for every hour of the year. For seven key stations within the domain, missing data were replaced assuming persistence in order to obtain a continuous surface mete orological dataset.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 24 • Hourly precipitation data were obtained fo r the 39 stations shown in Figure 5-4 from the National Climatic Data Center . These data were processed with the CALMET utility PMERGE.

• Three upper air stations were used for twice-daily soundings. Data from Oakland, Medford, and Reno were obtained from th e NOAA Forecast Service Laboratory and processed with the CALMET utility READ 62. Missing soundings for each station were filled in with the average monthly sounding at that site.

• MM5 winds based on a 36-km grid spacing for January 2001 to December 2003 were used to initialize the three-dimensi onal wind field predictions. The MM5 data are available in 5 day simulation blocks. The MM5 data were processed with the CALMM5 utility for use by CALMET.

• Interpolation options were selected using the general guidance in the CALPUFF Reviewers Guide to blend the MM5 initial fields with the surface, precipitation and upper air observations. Specifica lly, RMAX1=36, RMAX2=72, TERRAD=18, R1=18, R2=36, SIGMAP=20 were selected after consideration of the complex terrain within the domain balanced against the need to match the observations near these sites.

• Options were selected such that the treat ment of over water conditions used the same routines as over land (JWAT1 =JWAT2=100), except the variables characterizing the surface are appropriate fo r the ocean. The assumptions result in a near neutral boundary layer over the ocean.
Selected hours of the three-year CALMET/MM5 three-dimensional data set were examined by extracting data from the CALMET output files a nd plotting the meteorological fields with the CALDESK software package. Wi nd vector plots were examined for different times of year, different times of the data and for all ten vertical levels.



### 5.5 AQRV C ALCULATION 

### P ROCEDURES The CALPUFF modeling system was used to pred ict criteria pollutant concentrations, total deposition fluxes, and light extinction coefficients attributable to project emissions in regional Class I areas. These parameters were calcu lated from CALPUFF output files using the postprocessor program CALPOST.

Predictions of NO x , SO 2 , and PM 10 concentrations in the Class I areas of interest account for the transport, conversion, and deposition of each compound resulting in a concentration over selected averaging periods at each receptor. PM 10 concentration estimates include both primary and secondary aerosols and account for the molecular weights of each compound. Deposition fluxes are similarly an accounting of the vari ous conversion and deposit ion processes in theI:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 25 model, resulting in a mass per unit area per unit time at each receptor. For comparison to FLM deposition criteria the fluxes were convert ed to kilograms per hectare per year.

The potential for project emissions to contri bute to regional haze was predicted using 24-hour average extinction coefficients as a measure of visibility degr adation. The analysis included the potential for direct fine particle emissions and secondary aerosols formed from the gases emitted by the project to reduce visual ranges in Class I areas. The procedure assumes regional visibility degradation is primar ily due to light extinction cause d by scattering by fine particles including sulfates and nitrates, and by light absorption from soot particles.

In the FLAG Phase I Report, the FLMs recommend th at a five percent cha nge in extinction be used to indicate a “just perceptible” change to a landscape. Extinction coefficients were calculated from the CALPUFF output files usi ng the post-processing program CALPOST. CALPOST calculates extinction coefficients from concentrations of aerosols directly emitted, sulfate concentrations, nitrate concen trations, and relative humidity.

The general equation applied in CALPOST divides the extinction coefficient into two components as follows:

b ext = b SN f(RH) + b dry (1)

where b ext is the extinction coefficien t (inverse megameters or Mm -1 ), f(RH) is the relative humidity adjustment factor, b SN is the sulfate and nitrate or hygroscopic portion of the extinction coefficient (Mm -1 ), and b dry is the non-hygroscopic portion of the extinction coefficient (Mm -1 ). The hygroscopic portions of the ex tinction budget are calculated from the sulfate and nitrate concentrations predicted by CALPUFF according to:

b SN = 3[(NH 4 )2SO 4 + NH 4 NO 3 ] (2)

where the sulfate and nitrate concentrations have units μ g/m 3 and are converted for the change in molecular weight due to the assumed chemi cal form of the aerosol. The portion of the extinction coefficient that does not vary with humidity is calculated from:

b dry = 4[OC] + 1[Crustal Mass] + 0.6[Coarse Mass] + 10[EC] + b Ray (3)

where [OC] is the organic carbon portion of the PM2.5, [Crustal Mass] is the crustal portion (PM 2.5 that cannot be classified as orga nic or elemental carbon) of the PM 2.5 , [Coarse Mass] isI:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 26 the portion of the mass between PM 2.5 and PM 10 , [EC] is the elemental carbon (soot) portion of
PM 10 , and b Ray is extinction due to Rayleigh scattering assumed to be 10 Mm -1 . Concentrations in Equation 3 also have units of μ g/m 3

.



### 5.6 B ASELINE 

### AQRV D ATA For background visibility at all Class I areas of interest, the FLAG wester n U.S. defaults were used for the hygroscopic (0.6 Mm -1 ), dry (4. 5 Mm -1 ), and Rayleigh scattering (10.0 Mm -1 ) portions of the extinction coefficient. The procedures were invoke d by selecting CALPOST Method 6 (MVISBK=6) during pos t-processing of the CALPUFF simulation and assigning the sulfate concentration to 0.2 μg/m 3 and the fine crustal mass portion to 4.5 μg/m 3 . The hygroscopic portion of extinction was adjusted for re lative humidity using the seasonal factors ( f(RH) ) provided by FLAG for each Class I area.



### 5.7 A NALYSIS 

### R ESULTS The CALPUFF modeling system was used to predict concentrations of NO 2 , SO 2 , and PM 10 in regional Class I areas. The CALPUFF simulations used the emission rates presented in Table 5-2, and the source release parameters and bu ilding downwash paramete rs calculated by BPIP PRIME as described in Section 4.4. As for th e Class II analysis, the preliminary analysis included emissions only from the proposed c ogeneration unit, and did not account for the decreased impacts related to non-oper ation of the existing boiler. The results of this simplified, conservative analysis were compared to the va rious regulatory threshol ds and criteria to determine whether a more rigorous ne t impact analysis was necessary.

Table 5-3 summarizes the predicted maximum concen trations and compares them to the Class I SILs and the Class I PSD increments. At this po int, there are two sets of Class I SILs, those proposed by EPA and those recommended by th e FLMs. These proposed and recommended SILs were obtained from the Federal Re gister, Vol. 61, No. 143, p. 38292, July 23, 1996. As shown in Table 5-3, the CALPUFF simulations i ndicate neither the SILs nor the increments will be exceeded.

Figures 5-5 through 5-10 presen t the spatial variation across the simulation domain of the predicted maximum concentrations over th e applicable averaging periods for NO 2 , SO 2 , and
PM 10 emissions attributable to the project. Thes e figures were constructed from the maximum predictions obtained at the 4-km mesh size grid and are provided so the Federal Land Managers can assess the spatial extent of potential impacts from the project.I:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 27 CALPUFF was also used to predict the imp acts of acid-forming compounds emitted by the project on soils and vegetation in regional Class I areas. The deposition analysis results are shown in Table 5-4. There are no promulgated standards for evaluation of these incremental impacts to soils and vegetation in California. However, the National Park Service has established Deposition Analysis Thresholds (DAT s) for nitrogen and sulfur of 0.005 kilograms per hectare per year (kg/ha/yr). 7 These “thresholds” are based on natural background deposition estimates culled from various research efforts, a variability factor, and a safety factor that accounts for cumulative effects. The DATs are not adverse impact thresholds, but are intended as conservative screening criteria that allow the FLMs to identify potential deposition fluxes that require their co nsideration on a case-by-case basis.

The nitrogen and sulfur deposition flux results of the CALPUFF simulations are summarized in Table 5-4 for each Class I area. As shown in Table 5-4 predicted maximum nitrogen and sulfur deposition fluxes do not exceed the DATs. Figure s 5-11 and 5-12 show the spatial variation of the predicted nitrogen a nd sulfur deposition fluxes attributab le to the project over the entire simulation domain. Based on these results, nitrogen and sulfur deposition is not expected to significantly impact soils and vegetation within the Class I areas.

Compliance with the FLMs recommended criteria for regional visibility impacts was assessed by calculating the change in 24-hour extincti on for each Class I receptor. The CALPUFF modeling system was used to predict both the ex tinction coefficient attributable to emissions from the project as well as the background exti nction coefficients. The ten days with the highest maximum predicted changes in extinction are shown in Table 5-5. Table 5-6 lists the highest prediction in each Class I area.

The FLMs recommend in the FLAG Phase I Report that a five percent change in extinction be used to indicate a “just perceptible” change to a landscape. As shown in Tables 5-5 and 5-6, the maximum predicted change in extinction on any day of the simulation was 2.88 percent, which is less than the 5 percent threshold es tablished by the FLMs. The higher changes to extinction are predicted at receptors within th e Yolla Bolly-Middle Eel Wilderness. Figure 5-13 presents a contour plot of the predicted exti nction caused by emissions attributable to the project on the day predicted to experience the maximum change in extinction (November 23, 2002). Note, only the eastern edge of the w ilderness was predicted to have a 2.88 percent

7 Guidance on Nitrogen and Sulfur Deposition Analysis Thresholds , available on the FLAG internet site at http://www2.nature.nps.gov/ard /flagfree/NSDATGuidance.htmI:\Project\SPI\SPI_Anderson-12692\permit_ application\SPI_anderson_PSD-final.doc 28 change to extinction and the average over the entire Class I area was much less than this

amount.

# TABLESTABLE 2-1
PROPOSED COGENERATION UNIT EMISSIONS SPI Lumber Manufacturing Faci lity Cogeneration Project Anderson, California

Emission Rate 2
Pollutant 1 Emission Factor (lb/MMBtu) (lb/hr) (TPY)
NO x 0.13 50.6 202 CO 0.60 234 931 SO 2 0.016 6.23 24.8 PM 10 0.019 7.40 29.5 VOC/ROC 0.013 5.06 20.2 Sulfuric Acid 0.0020 0.780 3.11 Lead 4.95E-05 0.0193 0.0768

1 NO x , CO, PM 10 , and VOC/ROC emission factors are based on vendor guarantees, while the SO 2 emission factor is based on a source test conducted on the existing boiler at the facility. The sulfuric acid (H 2 SO 4 ) emission factor is based on the assumption that sulfate comprises 10.038 percent of PM10 emissions, which was obtained from EPA’s SPECIATE 3.2 Profile # 12709 for Hogged Fuel Boiler/Stoker Boiler.

2 Pound per hour emission rate is based on a maximum 1-hour average heat input of 389.2 MMBtu/hr, and the tons per year emission rates is based on an annual average heat input rate of 354.2 MMBtu/hr and continuous operation (8,760 hours per year).TABLE 2-2PROJECT TOTAL EMISSIONS OF CRITERIA AND OTHER REGULATED POLLUTANTSSPI Lumber Manufacturing Facility Cogeneration ProjectAnderson, CaliforniaHourly Emission Rate1(lb/hr)24-Hour Emission Rate2(lb/day)Annual Emission Rate4(TPY)PollutantCogen CT Total Cogen CT TotalAQMDBACTThresh.3(lb/day)OverBACTThresh?Cogen CT Total Existing NetPSDSER5(TPY)OverSER?NOx50.6 -- 50.6 1,160 -- 1,573 25.0 Yes 202 -- 202 77.2 124 40 YesCO 234 -- 234 5,355 -- 5,355 500.0 Yes 931 -- 931 128 803 100 YesSO26.23 -- 6.23 143 -- 136 80.0 Yes 24.8 -- 24.8 1.28 23.5 40 NoPM/PM107.40 0.251 7.65 170 6.02 176 80.0 Yes 29.5 1.1 30.6 3.69 25.8 25/15 YesVOC/ROG 5.06 -- 5.06 116 -- 116 25.0 Yes 20.2 -- 20.2 7.14 13.0 40 NoSulfuric Acid 0.780 -- 0.780 18 -- 18 35.0 No 3.11 -- 3.11 1.10 2.01 7 NoLead 0.0193 -- 0.0193 0.44 -- 0.44 3.2 No 0.0768 -- 0.0768 0.0272 0.0496 0.6 NoAsbestos -- -- -- -- -- -- 0.03 No -- -- -- -- -- -- --Beryllium 0.000604-- 0.0006040.014 -- 0.014 0.002 Yes 0.00241 -- 0.00241 0.000853 0.00155 -- --Mercury 0.000162-- 0.0001620.0037 -- 0.0037 0.5 No 0.000645 -- 0.000645 0.000228 0.000416 -- --Vinyl Chloride 0.00717-- 0.007170.16 -- 0.16 5.0 No 0.0285 -- 0.0285 0.0101 0.0184 -- --Fluorides -- -- -- -- -- -- 15.0 No -- -- -- -- -- 3 NoTRS/H2S/RS6-- -- -- -- -- -- 50.0 No -- -- -- -- -- 10 No1Cogeneration unit hourly emission rates are based on a maximum hourly heat input of 389.2 MMBtu/hr2Cogeneration unit hourly emission rates are based on a maximum 24-hour average heat input of 371.9 MMBtu/hr3From Sierra County AQMD Rule 2:1, Part 301.4Cogeneration unit hourly emission rates are based on a maximum hourly heat input of 354.2 MMBtu/hr. Net annual emissions aretotal proposed minusexisting.5PSD SER = Prevention of Significant Deterioration SignificantEmission Rate; from EPA’s New Source Review Workshop Manual, October 1990, Table A-4,and New Source Review (NSR) Program Transitional Guidance Memorandum, issued by John S. Seitz of EPA on March 11, 1991.6TRS = Total Reduced Sulfur compounds, H2S = Hydrogen Sulfide, and RS = Reduced Sulfur compounds; the PSD SER only applies to TRS (including H2S)TABLE 2-3
COGENERATION UNIT TOXIC AIR CONTAMINANT EMISSION RATES SPI Lumber Manufacturing Faci lity Cogeneration Project Anderson, California

Page 1 of 4

Emission Rate Compound CAS No. Emission Factor (lb/MMBtu) (lb/hr) 1 (lb/day) 2 (lb/yr) 3 Acenaphthene 83-32-9 8.37E-09 0.00000326 0.0000747 0.026 Acenaphthylene 208-96-8 1.91E-06 0.000745 0.0171 5.93

Acetaldehyde 75-07-0 1.64E-04 0.0639 1.46 509 Acetone 67-64-1 2.15E-04 0.0838 1.92 667 Acetophenone 98-86-2 3.23E-09 0.00000126 0.0000288 0.01 Acrolein 107-02-8 3.15E-05 0.0123 0.282 97.9 Ammonia 7664-41-7 2.57E-02 10 229 79,800 Anthracene 120-12-7 6.47E-08 0.0000252 0.000577 0.201 Antimony 7440-36-0 2.29E-05 0.00892 0.204 71.1

Arsenic 7440-38-2 5.62E-06 0.00219 0.0501 17.4 Barium 7440-39-3 3.47E-04 0.135 3.1 1,080 Benzaldehyde 100-52-7 8.45E-07 0.000329 0.00754 2.62 Benzene 71-43-2 7.42E-04 0.289 6.62 2,300 Benzo(a)anthracene 56-55-3 2.43E- 09 0.000000948 0.0 000217 0.00755

Benzo(a)pyrene 50-32-8 3.27E-09 0.00000127 0.0000292 0.0102 Benzo(b)fluoranthene 205-99-2 2.42E-09 0.000000942 0.0000216 0.0075 Benzo(e)pyrene 192-97-2 2.59E-09 0.00000101 0.0000231 0.00804 Benzo(g,h,i)perylene 191-24-2 4.62E-09 0.0000018 0.0000413 0.0143 Benzo(j)fluoranthene 205-82-3 1.56E-07 0.0000606 0.00139 0.483 Benzo(k)fluoranthene 207-08-9 2.38E-09 0.000000928 0.0000213 0.00739 Benzoic Acid 65-85-0 4.68E-08 0.0000182 0.000418 0.145

Beryllium 7440-41-7 1.55E-06 0.000604 0.0138 4.81 Bis(2-ethylhexyl)phthalate 117-81-7 4.65E-08 0.0000181 0.000415 0.144 Bromomethane 74-83-9 2.80E-05 0.0109 0.25 86.9 2-Butanone (MEK) 78-93-3 5.39E-06 0.0021 0.0481 16.7 Cadmium 7440-43-9 2.90E-06 0.00113 0.0259 9 Carbazole 86-74-8 1.79E-06 0.000697 0.016 5.55 Carbon Dioxide (CO2) 37210-16-5 1.92E+02 75000 1,720,000 597,000,000 Carbon Tetrachloride 56-23-5 4.54E-05 0.0177 0.405 141 Chlorine 7782-50-5 7.92E-04 0.308 7.07 2,460 Chlorobenzene 108-90-7 3.32E-05 0.0129 0.296 103

Chloroform 67-66-3 2.75E-05 0.0107 0.246 85.4 Chloromethane 74-87-3 2.31E-05 0.009 0.206 71.7 2-Chloronaphthalene 91-58-7 2.41E-09 0.000000937 0.0000215 0.00746 2-Chlorophenol 108-43-0 3.37E-08 0.0000131 0.000301 0.105 Chromium, hexavalent 4 18540-29-9 1.75E-07 0.0000683 0.00156 0.544TABLE 2-3
COGENERATION UNIT TOXIC AIR CONTAMINANT EMISSION RATES SPI Lumber Manufacturing Facility Anderson, California

Page 2 of 4

Emission Rate Compound CAS No. Emission Factor (lb/MMBtu) (lb/hr) 1 (lb/day) 2 (lb/yr) 3 Chromium, trivalent 7440-47-3 1.54E-06 0.000599 0.0137 4.77 Chrysene 218-01-9 2.81E-09 0.00000109 0.0000251 0.00871

Cobalt 7440-48-4 1.25E-07 0.0000487 0.00112 0.388 Copper 7440-50-8 7.44E-06 0.0029 0.0664 23.1 Crotonaldehyde 4170-30-3 9.91E-06 0.00386 0.0885 30.7 Decachlorobiphenyl 2051-24-3 2.65E- 10 0.000000103 0.0 0000237 0.000822 Dibenzo(a,h)anthracene 53-70-3 2.35E-09 0.0000 00915 0.000021 0.00729

1,2-Dibromoethene 106-93-4 5.48E-05 0.0214 0.489 170 Dichlorobiphenyl 2050-68-2 3.79E-10 0.000000148 0.00000338 0.00118 1,2-Dichloroethane 107-06-2 2.92E-05 0.0114 0.261 90.6 Dichloromethane 75-09-2 2.87E-04 0.112 2.56 891 1,2-Dichloropropane 78-87-5 3.33E-05 0.013 0.297 103

2,4-Dinitrophenol 51-28-5 9.33E-08 0.0000363 0.000832 0.289

Ethylbenzene 100-41-4 3.13E-05 0.0122 0.279 97.1 Fluoranthene 206-44-0 6.87E-07 0.000268 0.00613 2.13

Fluorene 86-73-7 6.78E-08 0.0000264 0.000605 0.21 Formaldehyde 50-00-0 1.72E-03 0.669 15.3 5330 Heptachlorobiphenyl 28655-71-2 6.57E-11 2.56E-08 0.000000586 0.000204 Hexachlorobiphenyl 26601-64-9 2.89E-10 0.000000113 0.00000258 0.000897 HpCDD-Total 37871-00-4 3.09E-11 0.000000012 0.000000275 0.0000957 HpCDF-Total 38998-75-3 6.40E-12 2.49E-09 5.71E-08 0.0000198 HxCDD-Total 34465-46-8 8.55E-11 3.33E-08 0.000000763 0.000265 HxCDF-Total 55684-94-1 1.53E-11 5.97E-09 0.000000137 0.0000476 Hexanal 66-25-1 6.96E-06 0.00271 0.0621 21.6 Hydrogen chloride 7647-01-0 3.50E-03 1.36 31.2 10,900 Indeno(1,2,3-c,d)pyrene 193-39-5 2.37E-09 0.000000925 0.0000212 0.00737 Iron 7439-89-6 9.93E-04 0.387 8.86 3,080 Isobutyraldehyde 78-84-2 1.15E-05 0.00448 0.103 35.7 Lead 7439-92-1 4.95E-05 0.0193 0.442 154 Manganese 7439-96-5 9.81E-05 0.0382 0.876 304

Mercury 7439-97-6 4.16E-07 0.000162 0.00371 1.29 Methane 74-82-8 2.00E-02 7.79 179 62,100 Methanol 5 67-56-1 8.30E-04 0.323 7.41 2,580 2-Methylnaphthalene 91-57-6 2.75E-07 0.000107 0.00245 0.853 Molybdenum 7439-98-7 2.07E-06 0.000805 0.0184 6.41 Monochlorobiphenyl 2051-60-7 2.18E-10 8.49E-08 0.00000195 0.000676 Naphthalene 91-20-3 9.46E-05 0.0368 0.844 293TABLE 2-3
COGENERATION UNIT TOXIC AIR CONTAMINANT EMISSION RATES SPI Lumber Manufacturing Facility Anderson, California

Page 3 of 4

Emission Rate Compound CAS No. Emission Factor (lb/MMBtu) (lb/hr) 1 (lb/day) 2 (lb/yr) 3
Nickel 7440-02-0 2.53E-06 0.000984 0.0225 7.84 Nitric Oxide (NO) 10102-43-9 1.30E-01 50.6 1,160 403,000

2-Nitrophenol 88-75-5 1.06E-07 0.0000414 0.000948 0.33 4-Nitrophenol 100-02-7 1.71E-07 0.0000667 0.00153 0.531 Nitrous Oxide (N 2 O) 10024-97-2 1.33E-02 5.19 119 41,300 OCDD 3268-87-9 2.78E-09 0.00000108 0.0000248 0.00862 OCDF 39001-02-0 1.41E-10 5.48E-08 0.00000125 0.000436 PeCDD-Total 36088-22-9 1.72E-10 6.68E-08 0.00000153 0.000532 PeCDF-Total 30402-15-4 4.19E-11 1.63E-08 0.000000374 0.00013 Pentachlorobiphenyl 25429-29-2 6.49E-10 0.000000253 0.00000579 0.00201 Pentachlorophenol 87-86-5 2.27E-08 0.00000884 0.000203 0.0704 Perylene 198-55-0 5.18E-10 0.000000202 0.00000462 0.00161 Phenanthrene 86-01-8 2.25E-06 0.000877 0.0201 6.98 Phenol 108-95-2 1.25E-05 0.00489 0.112 38.9 Phosphorus 7723-14-0 3.54E-05 0.0138 0.316 110 Potassium 7440-09-7 3.88E-02 15.1 346 120,000 Propionaldehyde 123-38-6 6.11E-05 0.0238 0.545 190 Pyrene 129-00-0 3.97E-07 0.000155 0.00354 1.23 Selenium 7782-49-2 1.74E-06 0.000679 0.0156 5.41

Silver 7440-22-4 1.74E-03 0.676 15.5 5,380 Sodium 7440-23-5 3.63E-04 0.141 3.24 1,120 Strontium 7440-24-6 1.01E-05 0.00392 0.0898 31.2

Styrene 100-42-5 1.86E- 0.725 16.6 5,770 Sulfuric Acid 7664-93-9 2.00E-03 0.780 17.9 6,210 TCDD-Total 1746-01-6 2.05E-10 7.97E-08 0.00000183 0.000635 TCDF-Total 30402-14-3 1.63E-10 6.33E-08 0.00000145 0.000504 Tetrachlorobiphenyl 26914-33-0 1.60E-09 0.000000623 0.0000143 0.00496

Tetrachloroethene 127-18-4 3.82E-05 0.0149 0.341 119 Tin 7440-31-5 6.63E-06 0.00258 0.0592 20.6 Titanium 7440-32-6 2.01E-05 0.00783 0.179 62.4 o-Tolualdehyde 529-20-4 7.15E-06 0.00279 0.0638 22.2 p-Tolualdehyde 104-87-0 1.13E-05 0.0044 0.101 35.1 Toluene 108-88-3 2.13E-05 0.00828 0.19 65.9 Trichlorobiphenyl 15862-07-4 1.78E-09 0.000000694 0.0000159 0.00552 1,1,1-Trichloroethane 71-55-6 3.07E-05 0.012 0.274 95.4 Trichloroethene 79-01-6 3.03E-05 0.0118 0.271 94.1 Trichlorofluoromethane 75-69-4 4.05E-05 0.0158 0.361 126TABLE 2-3
COGENERATION UNIT TOXIC AIR CONTAMINANT EMISSION RATES SPI Lumber Manufacturing Facility Anderson, California

Page 4 of 4

Emission Rate Compound CAS No. Emission Factor (lb/MMBtu) (lb/hr) 1 (lb/day) 2 (lb/yr) 3 2,4,6-Trichlorophenol 88-06-2 1.14E-08 0.00000442 0.000101 0.0352 Vanadium 1314-62-1 1.36E-06 0.00053 0.0121 4.22 Vinyl Chloride 75-01-4 1.84E-05 0.00717 0.164 57.1 Xylene 1330-20-7 2.45E-05 0.00954 0.219 76 Yttrium 7440-65-5 3.01E-07 0.000117 0.00269 0.935

Zinc 7440-66-6 2.32E-04 0.0904 2.07 720

1 Based on a maximum hourly heat input rate of 389.2 MMBtu/hr.

2 Based on a maximum daily average heat input rate of 371.9 MMBtu/hr and continuous 24-hour operation.

3 Based on an annual average heat input rate of 354.2 MMBtu/hr and 8,760 hours of operation per year.

4 Hexavalent chromium emission factor for wood-fired boilers from AP-42 source test data, excluding source tests with data estimated based on detection limits.

5 Methanol emission factor for wood-fired boilers from NCASI Technical Bulletin No. 858 (February 2003).TABLE 3-1
HAZARDOUS AIR POLLUTA NT EMISSION RATES

SPI Lumber Manufacturing Faci lity Cogeneration Project Anderson, California

All emission rates are in tons per year (TPY)

Compound CAS No. Emi ssion Rate Compound CA S No. Emission Rate Acetaldeh y de 75-07-0 0.254 Formaldeh y de 50-00-0 2.66 Aceto p henone 98-86-2 5.00E-06 H y dro g en chloride 7647-01-0 5.43 Acrolein 107-02-8 0.0489 Lead 7439-92-1 0.0768 Antimon y 7440-36-0 0.0355 Man g anese 7439-96-5 0.152

Arsenic 7440-38-2 0.0087 Mercur y 7439-97-6 0.000645 Benzene 71-43-2 1.15 Methanol 67-56-1 1.288 Ber y lliu m 7440-41-7 0.00241 N a p hthalene 91-20-3 0.147 Bis ( 2-eth y lhex y l )p hthalate 117-81-7 7.21E-05 N ickel 7440-02-0 0.00392 Bromomethane 74-83-9 0.0434 4- N itro p henol 100-02-7 0.000266 2-Butanone ( MEK ) 78-93-3 0.0084 Pentachloro p henol 87-86-5 3.52E-05 Cadmiu m 7440-43-9 0.00450 Phenol 108-95-2 0.0195 Carbon Tetrachloride 56-23-5 0.0704 Phos p horus 7723-14-0 0.0549 Chlorine 7782-50-5 1.23 Pro p ionaldeh y de 123-38-6 0.095 Chlorobenzene 108-90-7 0.0515 Seleniu m 7782-49-2 0.00270

Chlorofor m 67-66-3 0.0427 St y rene 2.89 Chloromethane 74-87-3 0.0358 TCDD-Total 1746-01-6 3.17E-07 Chromium
, trivalen t 7440-47-3 0.00238 Tetrachloroethene 127-18-4 0.0593 Cobal t 7440-48-4 0.000194 Toluene 108-88-3 0.0330 1
, 2-Dibromoethene 106-93-4 0.085 1
, 1
, 1-Trichloroethane 71-55-6 0.0477 1
, 2-Dichloroethane 107-06-2 0.0453 Trichloroethene 79-01-6 0.0470 Dichloromethane 75-09-2 0.445 2
, 4
, 6-Trichloro p henol 88-06-2 1.76E-05 1
, 2-Dichloro p ro p ane 78-87-5 0.0517 Vin y l Chloride 75-01-4 0.0285

2
, 4-Dinitro p henol 51-28-5 0.000145 X y lene 1330-20-7 0.0380

Eth y lbenzene 100-41-4 0.0486 Total HAPs 16. 7 M

aximum Ind. HA P 5.43TABLE 3-2
AIR POLLUTANT EMISSION OFFSETS SPI Lumber Manufacturing Faci lity Cogeneration Project Anderson, California

All emission rates are in tons per year (TPY)

Pollutant Average Historic Actual Emissions Proposed Potential To Emit Net Emission Rate Increase Banked ERCs
NO x 77.2 202 124 193 SO 2 1.28 24.8 23.5 --- PM/PM 10 3.69 30.6 26.9 226

VOC 7.14 20.2 13.0 159TABLE 4-1
POINT SOURCE RELEA SE PARAMETERS SPI Lumber Manufacturing Faci lity Cogeneration Project Anderson, California

Source Height (ft) Diameter (ft) Exit Velocity (ft/s) Temperature (°F) Proposed Cogeneration Unit 105 8.0 58.0 400 Existing Boiler 80 8.3 34.6 350 Cooling Tower (each, 2 cells) 41 31.6 24.2 91TABLE 4-2
STRUCTURE HEIGHTS SPI Lumber Manufacturing Faci lity Cogeneration Project Anderson, California

Height Structure (feet) (meters) Truck Shop 16 4.88 Equipment Shop 27 8.23 Fabrication Shop 43 13.11 Warehouse 32 9.75 Dry Shed 52 15.85

Planer 60 18.29 Kilns 24 7.32 Existing Cooling Tower 30 9.14 Diesel Fuel 16 4.88 Forestry Lab 29 8.84 Lumber Storage Shed 26 7.92 Existing Boiler 43 13.11 Sawmill 54 16.46 Chipper/Hog 29 8.84 Fuel House 52 15.85

Turbine 40 12.19 Proposed Cooling Tower 30 9.14 Proposed Boiler 105 32.00 Proposed Economizer 50 15.24 ESP 50 15.24 Truck Shop 16 4.88TABLE 4-3
MAXIMUM PREDICTED CRITERIA POLLUTANT CONCENTRATIONS SPI Lumber Manufacturing Faci lity Cogeneration Project Anderson, California

Concentrations are in micrograms per cubic meter (μg/m 3 )

Pollutant Averaging Period Maximum Predicted SIL 1 Over SIL? Monitoring de Minimis 3 Over de Minimis?
NO 2 Annual 1.47/0.49 2 1 No 14 No 1-Hour 154 2,000 No --- --- CO 8-Hour 70.9 500 No 575 No 24-Hour 1.59 5 No 10 No PM 10 Annual 0.22 1 No ---

--- 3-Hour 1.96 25 No ---

--- 24-Hour 1.08 5 No 13 No SO 2 Annual 0.17 1 No ---

---

1 SIL = Significant Impact Level, from EPA’s New Source Review Workshop Manual (October, 1990), Table C-4..

2 The maximum annual average NO 2 concentration attributable to the new cogeneration unit alone was 1.47 μg/m 3 . When the existing annual average NO 2 concentrations attributable to the existing boiler are subtracted from those concentrations on a matched time-period and receptor basis, the net maximum annual average NO 2 concentration increase is 0.49 μg/m 3 . NO 2 was assumed to be 100 percent of the emitted NO x based on guidance in Section 6.2.3 of the EPA’s Guidelin e on Air Quality Models (codified as Appendix W to 40 CFR Part 51).

3 Monitoring de Minimis concentrations from 40 CFR 52.21(i)(8)(i).TABLE 5-1
CLASS I AREA DISTANCES FROM PROPOSED PROJECT SPI Lumber Manufacturing Faci lity Cogeneration Project Anderson, California

Distances in kilometers.

Class I Area Distance
Caribou Wilderness Area 89 Desolation Wilderness Area 240 Lassen Volcanic National Park 64 Lava Beds National Monument 148 Marble Mountain Wilderness Area 116 Redwood National Park 147 South Warner Wilderness Area 192 Thousand Lakes Wilderness Area 62 Yolla Bolly-Middle Eel Wilderness Area 57TABLE 5-2 SPECIATED EMISSION RATES FOR AQRV ANALYSIS SPI Lumber Manufacturing Faci lity Cogeneration Project Anderson, California

Emission rates in pounds per hour (lb/hr)

Cogeneration Unit 1 Species 24-hour Average Cooling Towers 2

SO 2 5.95 0.00 NO x 48.35 0.00
PM 10 3 7.07 0.141 Coarse Mass 0.88 0.00 Fine Sulfate (as SO 4 ) 0.36 0.00 Fine Nitrate (as NO 3 ) 0.00 0.00 Fine Elemental Carbon 0.87 0.00

Fine Organic Carbon 2.41 0.00 Fine Crustal Material 2.41 0.141

1 PM 10 speciated using a revision to SPECIATE 3.2 Profile # 22008 for Hogged Fuel Boiler/Stoker Boiler. PM 10 is assumed to be 87.5% PM 2.5 based on AP-42 Section 1.6 (July, 2001). The SO 2 emission rates from the Class II analysis was not reduced by the eq uivalent amount fine sulfate present in PM 10 . PM 10 is the sum of coarse mass and the PM 2.5 components: ammonium sulfate, ammonium nitrate, fine crustal material, elemental carbon and organic carbon. The simulation emission rates were based on continuous daily operation (24- hours) and a maximum 24-hour average heat input of 371.9 MMBtu/hr.

2 Cooling tower PM 10 emissions were assumed to be comprised entirely of the fine fraction (i.e., 100% PM 2.5 ).

3 PM 10 is speciated into Fine Mass (particul ate matter less than 2.5 micrometers [ μ m]) and Coarse Mass (particulate matter between 2.5 and 10 μ m). Fine Mass is further speciated into Sulfate, Ni trate, Elemental Carbon, Organic Carbon, and Crustal Mass, which is the portion of the Fine Mass than cannot be classified as elemental or organic carbon.TABLE 5-3
PREDICTED CLASS I AREA CRITERIA POLLUTANT CONCENTRATIONS SPI Lumber Manufacturing Faci lity Cogeneration Project Anderson, California

Concentrations in micrograms per cubic meter (μg/m 3 )

Maximum Predicted Concentration
NO 2 1 PM 10 SO 2

Class I Area of Interest Annual Average 24-Hour Average Annual Average 3-Hour Average 24-Hour Average Annual Average
Caribou WA 0.0002 0.0098 0.0006 0.0121 0.0024 0.0001 Desolation WA 0.0000 0.0029 0.0001 0.0007 0.0003 0.0000 Lassen Volcanic NP 0.0003 0.0191 0.0009 0.0071 0.0020 0.0002 Lava Beds NM 0.0005 0.0109 0.0009 0.0259 0.0046 0.0002 Marble Mountain WA 0.0004 0.0164 0.0007 0.0120 0.0023 0.0001 Redwood NP 0.0001 0.0082 0.0003 0.0038 0.0011 0.0000 South Warner WA 0.0001 0.0113 0.0005 0.0033 0.0009 0.0001 Thousand Lakes WA 0.0009 0.0179 0.0012 0.0407 0.0068 0.0003 Yolla Bolly-Middle Eel WA 0.0006 0.0617 0.0023 0.0486 0.0113 0.0004

Class I Area Max. Conc. 0.0009 0.0617 0.0023 0.0486 0.0113 0.0004

EPA Proposed SIL 2 0.1 0.3 0.2 1 0.2 0.1 FLM Recommended SIL 2 0.03 0.27 0.08 0.48 0.07 0.03 Class I Area PSD Increment 3 2.5 8 4 25 5 2

1 NO x was conservatively assumed to be 100 percent converted to NO 2 , per Section 6.2.3 of EPA’s Guideline on Air Quality Models (Appendix W to 40 CFR Part 51).

2 SIL = Significant Impact Level; EPA proposed and FLM recommended from the Federal Register, Vol. 61, No. 142, p. 38292, July 23, 1996.

3 PSD Increment = Prevention of Significant Deterioration In crement; from 40 CFR 52.21(c)TABLE 5-4
PREDICTED CLASS I AREA DEPOSITION FLUXES

SPI Lumber Manufacturing Faci lity Cogeneration Project Anderson, California

Deposition fluxes in kilograms per hectare per year (kg/ha/yr)

Class I Area of Interest Nitroge n Deposition Sulfur Deposition
Caribou Wilderness Area 0.0003 0.0001 Desolation Wilderness Area 0.0000 0.0000 Lassen Volcanic National Park 0.0006 0.0002 Lava Beds National Monument 0.0005 0.0002 Marble Mountain Wilderness Area 0.0005 0.0002 Redwood National Park 0.0002 0.0001 South Warner Wilderness Area 0.0002 0.0001 Thousand Lakes Wilderness Area 0.0007 0.0002 Yolla Bolly-Middle Eel Wilderness Area 0.0005 0.0002 Maximum Deposition 0.0007 0.0002 NPS DAT 1 0.005 0.005

1 DAT = Decision Analysis Threshold; fromTABLE 5-5TEN DAYS WITH MAXIMUM PREDICTED CLASS I AREA EXTINCTION CHANGESPI Lumber Manufacturing Facility Cogeneration ProjectAnderson, CaliforniaExtinction coefficient in inverse megameters (1/Mm)bext1bextby Component4Class I Area DateProject2Bckgrnd3TotalChange(%)f(RH)SO4NO3OC EC PMC PMFYolla Bolly-Middle Eel WA 11/23/02 0.47 16.30 16.77 2.88 3.00 0.023 0.398 0.022 0.019 0.001 0.006Yolla Bolly-Middle Eel WA 12/03/02 0.42 16.78 17.20 2.47 3.80 0.031 0.355 0.013 0.012 0.000 0.004Yolla Bolly-Middle Eel WA 01/28/02 0.34 16.78 17.12 2.02 3.80 0.025 0.291 0.010 0.009 0.000 0.003Yolla Bolly-Middle Eel WA 04/03/02 0.31 15.94 16.25 1.97 2.40 0.021 0.247 0.021 0.019 0.001 0.006Yolla Bolly-Middle Eel WA 01/20/03 0.27 16.78 17.05 1.63 3.80 0.029 0.227 0.008 0.007 0.000 0.002Yolla Bolly-Middle Eel WA 01/19/03 0.26 16.78 17.04 1.57 3.80 0.025 0.223 0.007 0.007 0.000 0.002Yolla Bolly-Middle Eel WA 12/26/01 0.25 16.78 17.03 1.51 3.80 0.019 0.216 0.008 0.007 0.000 0.002Yolla Bolly-Middle Eel WA 12/16/03 0.25 16.78 17.03 1.47 3.80 0.013 0.217 0.008 0.007 0.000 0.002Yolla Bolly-Middle Eel WA 01/02/03 0.23 16.78 17.01 1.35 3.80 0.016 0.196 0.007 0.006 0.000 0.002Yolla Bolly-Middle Eel WA 02/06/02 0.20 16.78 16.98 1.21 3.80 0.014 0.175 0.006 0.005 0.000 0.0021Project and background extinction values for daily period that resulted in the maximum percent change in extinction.2Emission rates based on continuous year-round operation for three years.3Background extinction derived from default annual average Western U.S. extinction components provided in FLAG guidance document.4Extinction coefficient components are: SO4= fine sulfate, NO3= fine nitrate, OC = fine organic carbon, EC= fine elemental carbon, PMC = coarse mass,PMF = fine crustal mass.TABLE 5-6MAXIMUM PREDICTED EXTINCTION CHANGE BY CLASS I AREASPI Lumber Manufacturing Facility Cogeneration ProjectAnderson, CaliforniaExtinction coefficient in inverse megameters (1/Mm)bext1bextby Component4Class I Area DateProject2Bckgrnd3TotalChange(%)f(RH)SO4NO3OC EC PMC PMFCaribou WA 04/26/02 0.049 15.700 15.749 0.310 2.000 0.003 0.035 0.005 0.005 0.000 0.001Desolation WA 01/14/02 0.025 16.480 16.505 0.150 3.300 0.002 0.021 0.001 0.001 0.000 0.000Lassen Volcanic NP 10/24/02 0.153 16.360 16.513 0.940 3.100 0.011 0.129 0.006 0.006 0.000 0.002Lava Beds NM 01/31/03 0.079 16.660 16.739 0.480 3.600 0.008 0.066 0.002 0.002 0.000 0.001Marble Mountain WA 01/20/03 0.161 17.140 17.301 0.940 4.400 0.017 0.135 0.004 0.003 0.000 0.001Redwood NP 09/05/03 0.095 17.260 17.355 0.550 4.600 0.013 0.076 0.003 0.002 0.000 0.001South Warner WA 12/01/02 0.105 16.660 16.765 0.630 3.600 0.006 0.091 0.003 0.003 0.000 0.001Thousand Lakes WA 01/31/03 0.141 16.720 16.861 0.840 3.700 0.014 0.117 0.004 0.004 0.000 0.001Yolla Bolly-Middle Eel WA 11/23/02 0.469 16.300 16.769 2.880 3.000 0.023 0.398 0.022 0.019 0.001 0.0061Project and background extinction values for daily period that resulted in the maximum percent change in extinction.2Emission rates based on continuous year-round operation for three years.3Background extinction derived from default annual average Western U.S. extinction components provided in FLAG guidance document.4Extinction coefficient components are: SO4= fine sulfate, NO3= fine nitrate, OC = fine organic carbon, EC= fine elemental carbon, PMC = coarse mass,PMF = fine crustal mass.

# FIGURESFigure2-1Project No.012692.000.0PROJECT SCHEMATIC FLOW DIAGRAMSPI Lumber Manufacturing Facility Cogeneration ProjectAnderson, CaliforniaFigure 2-2 Project No. 012692.000.0 VISCINITY OF FACILITY AND CLASS II MODELING DOMAIN SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California 

### 012345 S a

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### Anderson

Cottonwood Redding Municipal

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### MilesFigure 4-1 Project No. 012692.000 FINAL RECEPTOR LOCATIONS FOR CLASS II ANALYSIS

SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California 553000 554000 555000 556000 557000 558000 559000 560000 561000 562000 UTM Easting (meters) 4476000 4477000 4478000 4479000 4480000 4481000 4482000 4483000 4484000 4485000UTM Northing (meters)Figure 4-2 Project No. 012692.000 WIND ROSE, REDDING MUNICIPAL AIRPORT, JAN. 1995 – DEC. 1999 SPI Lumber Manufacturing Facility Cogeneration Project Anderson, CaliforniaFigure4-3Project No.012692.000.0SOURCE AND SIGNIFICANT STRUCTURE LOCATIONSSPI Lumber Manufacturing Facility Cogeneration ProjectAnderson, California1234567891011121314151617181920211 Truck Shop2 Equipment Shop3 Fab Shop4 Warehouse5 Dry Shed6 Planer7 N Kilns8 Old Cooling Tower9 Diesel Fuel10 Forestry Lab11 Lumber Storage Shed12 Old Boiler & Stack13 Sawmill14 Chipper/Hog15 S Kilns16 Fuel House17 Turbine18 New Cooling Tower19 New Boiler20 Economizer21 ESP & New Boiler Stack0 250 500 750 1000FeetProperty BoundaryFigure 4-4 Project No. 012692.000 MAXIMUM PREDICTED 1-HOUR AVERAGE CO CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) 553000 554000 555000 556000 557000 558000 559000 560000 561000 562000 UTM Easting (meters) 4476000 4477000 4478000 4479000 4480000 4481000 4482000 4483000 4484000 4485000UTM Northing (meters)

= maximum predicted concentration (154 μg/m3)Figure 4-5 Project No. 012692.000 MAXIMUM PREDICTED 8-HOUR AVERAGE CO CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) 553000 554000 555000 556000 557000 558000 559000 560000 561000 562000 UTM Easting (meters) 4476000 4477000 4478000 4479000 4480000 4481000 4482000 4483000 4484000 4485000UTM Northing (meters)

= maximum predicted concentration (70.9 μg/m3)Figure 4-6 Project No. 012692.000 MAXIMUM PREDICTED 3-HOUR AVERAGE SO 2 CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) 553000 554000 555000 556000 557000 558000 559000 560000 561000 562000 UTM Easting (meters) 4476000 4477000 4478000 4479000 4480000 4481000 4482000 4483000 4484000 4485000UTM Northing (meters)

= maximum predicted concentration (1.96 μg/m3)Figure 4-7 Project No. 012692.000 MAXIMUM PREDICTED 24-HOUR AVERAGE SO 2 CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) 553000 554000 555000 556000 557000 558000 559000 560000 561000 562000 UTM Easting (meters) 4476000 4477000 4478000 4479000 4480000 4481000 4482000 4483000 4484000 4485000UTM Northing (meters)

= maximum predicted concentration (1.08 μg/m3)Figure 4-8 Project No. 012692.000 MAXIMUM PREDICTED ANNUAL AVERAGE SO 2 CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) 553000 554000 555000 556000 557000 558000 559000 560000 561000 562000 UTM Easting (meters) 4476000 4477000 4478000 4479000 4480000 4481000 4482000 4483000 4484000 4485000UTM Northing (meters)

= maximum predicted concentration (0.173 μg/m3)Figure 4-9 Project No. 012692.000 MAXIMUM PREDICTED 24-HOUR AVERAGE PM 10 CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) 553000 554000 555000 556000 557000 558000 559000 560000 561000 562000 UTM Easting (meters) 4476000 4477000 4478000 4479000 4480000 4481000 4482000 4483000 4484000 4485000UTM Northing (meters)

= maximum predicted concentration (1.59 μg/m3)Figure 4-10 Project No. 012692.000 MAXIMUM PREDICTED ANNUAL AVERAGE PM 10 CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) 553000 554000 555000 556000 557000 558000 559000 560000 561000 562000 UTM Easting (meters) 4476000 4477000 4478000 4479000 4480000 4481000 4482000 4483000 4484000 4485000UTM Northing (meters)

= maximum predicted concentration (0.223 μg/m3)Figure 4-11 Project No. 012692.000 MAXIMUM PREDICTED ANNUAL AVERAGE NO X CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) 553000 554000 555000 556000 557000 558000 559000 560000 561000 562000 UTM Easting (meters) 4476000 4477000 4478000 4479000 4480000 4481000 4482000 4483000 4484000 4485000UTM Northing (meters)

= maximum predicted concentration (1.47 μg/m3)Figure 4-12 Project No. 012692.000 MAXIMUM PREDICTED NE T ANNUAL AVERAGE NO X CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) 553000 554000 555000 556000 557000 558000 559000 560000 561000 562000 UTM Easting (meters) 4476000 4477000 4478000 4479000 4480000 4481000 4482000 4483000 4484000 4485000UTM Northing (meters)

= maximum predicted concentration (0.490 μg/m3)Figure 5-1 Project No. 012692.000 CALPUFF DOMAIN AND CLASS I AREA LOCATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California -250 -200 -150 -100 -50 0 50 100 150 200 East - West LCC (km) -200 -150 -100 -50

0 50 100 150 200 250 300North - South LCC (km)

200 km 100 km 50 km

CALPUFF Domain Marble Mtn. WA Lave Beds NM

Redwood NP

Yolly Bolly Middle Eel WA Thousand Lakes WA Lassen Volcanic NP Caribou WA S. Warner WA

SPI-Anderson

Desolation WAFigure 5-2 Project No. 012692.000 CALPUFF CLASS I AREA RECEPT ORS AND CALMET TERRAIN SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California -200 -150 -100 -50 0 50 100 150 East - West LCC (km ) -100 -50

0 50 100 150 200 250North - South LCC (km)Figure 5-3 Project No. 012692.000 SURFACE AND UPPER AIR STATIONS NEAR STUDY DOMAIN SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California -250 -200 -150 -100 -50 0 50 100 150 200 East - West LCC (km) -250 -200 -150 -100 -50

0 50 100 150 200 250 300North - South LCC (km) K4BK

KAAT

KACV

KAPC KBAB KBLU KCEC

KCIC KEKA KLKV KLMT KMFR

KMHR KMHS

KMYV KO87

KOVE KRBL KRDD

KREV KRNO

KSAC KSIY

KSMF KSTO KSTS

KSUU KSXT

KTRK

KTVL KUKI

KVCBFigure 5-4 Project No. 012692.000 PRECIPITATION STATIONS NEAR STUDY DOMAIN SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California -250 -200 -150 -100 -50 0 50 100 150 200 East - West LCC (km) -200 -150 -100 -50

0 50 100 150 200 250 300North - South LCC (km)Figure 5-5 Project No. 012692.000 MAXIMUM PREDICTED ANNUAL AVERAGE NO 2 CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California -200 -150 -100 -50 0 50 100 150 East - West LCC (km) -100 -50

0 50 100 150 200 250North - South LCC (km)

Concentration isopleths in mi crograms per cubic meter (μg/m 3 )Figure 5-6 Project No. 012692.000 MAXIMUM PREDICTED 24-HOUR AVERAGE PM10 CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) -200 -150 -100 -50 0 50 100 150 East - West LCC (km) -100 -50

0 50 100 150 200 250North - South LCC (km)Figure 5-7 Project No. 012692.000 MAXIMUM PREDICTED ANNUAL AVERAGE PM10 CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) -200 -150 -100 -50 0 50 100 150 East - West LCC (km) -100 -50

0 50 100 150 200 250North - South LCC (km)Figure 5-8 Project No. 012692.000 MAXIMUM PREDICTED 3-HOUR AVERAGE SO2 CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) -200 -150 -100 -50 0 50 100 150 East - West LCC (km) -100 -50

0 50 100 150 200 250North - South LCC (km)Figure 5-9 Project No. 012692.000 MAXIMUM PREDICTED 24-HOUR AVERAGE SO2 CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) -200 -150 -100 -50 0 50 100 150 East - West LCC (km) -100 -50

0 50 100 150 200 250North - South LCC (km)Figure 5-10 Project No. 012692.000 MAXIMUM PREDICTED ANNUAL AVERAGE SO2 CONCENTRATIONS SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Concentration isopleths in mi crograms per cubic meter (μg/m 3 ) -200 -150 -100 -50 0 50 100 150 East - West LCC (km) -100 -50

0 50 100 150 200 250North - South LCC (km)Figure 5-11 Project No. 012692.000 MAXIMUM PREDICTED TOTAL NI TROGEN DEPOSITION FLUXES SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Deposition flux isopleths in kilogr ams per hectare-year (kg/ha/yr) -200 -150 -100 -50 0 50 100 150 East - West LCC (km) -100 -50

0 50 100 150 200 250North - South LCC (km)Figure 5-12 Project No. 012692.000 MAXIMUM PREDICTED TOTAL SULFUR DEPOSITION FLUXES SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Deposition flux isopleths in kilogr ams per hectare-year (kg/ha/yr) -200 -150 -100 -50 0 50 100 150 East - West LCC (km) -100 -50

0 50 100 150 200 250North - South LCC (km)Figure 5-13 Project No. 012692.000 PREDICTED EXT. COEFF. ATTRIBUTABL E TO PROJECT ON NOV. 23, 2002 SPI Lumber Manufacturing Facility Cogeneration Project Anderson, California Extinction coefficient isopleths in inverse megameters (1/Mm) -200 -150 -100 -50 0 50 100 150 East - West LCC (km) -100 -50

0 50 100 150 200 250North - South LCC (km)

# APPENDIX ASHASTA COUNTY DEPARTMENT OF RESOURCE MANAGEMENT AIR QUALITY MANAGEMENT DISTRICT 1855 PLACER STREET, SUITE 101, REDDING, CALIFORNIA 96001 VOICE (530)225-5674/FAX (530)225-5237 APPLICATION FOR AUTHORITY TO CONSTRUCT/PERMIT TO OPERATE

INSTRUCTIONS PERMIT NUMBER # -POEach applicant for an Authority to Construct shall provide to the District the following: A. One application form for each emission unit or multi-component system at the facility. B. A $75 one time filing fee for each application or a $15 transfer of ownership * or name change fee made payable to the Shas ta County AQMD. (*Furnish a copy of the sales agreement or a signed statement from the seller.) C. Adequate drawings of each emissions unit, including plot pl an and area map indicating receptors within 1/4 mile of the faci lity. Any public or private school with an outer boundary within 1000 feet of the emissions unit must be included on the map. D. A signature of a responsible member of the organization on each application. E. An annual permit fee must be paid before a Permit to Operate is granted. The District shall notify the applicant of the a ppropriate amount due following an initial inspection of the permitted device(s).

1. Business Name: Sierra Pacific Industries

2. Email: syoung@spi-ind.com

3. Assessor's Parcel Number: 05011025 Telephone: (530) 378-8350 Fax: (530) 378-8360

4. Type of Business: Lumber manufacturing

5. Mailing Address: P.O. Box 10939, Anderson, CA 96007

6. Address of Equipment: 19758 Riverside Ave., Anderson, CA 96007

7. Equipment Description (use additional sheets if required): See permit application documentation

8. Application to: (check one) 9. Type of Organization: Operate Existing Equipment _ _ Corporation _x

_ New Construction _ _ Partnership _

_ Change of Location _ _ Individual Owner _

_ Modification _x _ Government Agency _

_ Exempt Equipment _

_ Change of Ownership* _ _ (Copy of agreement or statement attached? Yes No )

10. Planned construction dates; Start: 1/1/2008 End: 12/31/2008

11. Is a plot plan attached? Yes: See permit application documentation No:
12. Is this emission unit within 1000 feet from the outer boundary of any public or private school? Yes: No: X__

13. Name of Owner(s)/Principles: Sierra Pacific Industries

14. Signature of Applicant: Date: May___, 2007

15. Type/Print Signer's Name: Shane Young Title: Division Manager

BY SIGNING THIS APPLICATION, THE APPLICANT/PR OPERTY OWNER AGREES TO DEFEND, INDEMNIFY, AND HOLD THE SHASTA COUNTY AIR QUALITY M ANAGEMENT DISTRICT HARMLESS FROM ANY CLAIM, ACTION, OR PROCEEDING BROUGHT TO ATTACK, SET ASIDE, VOID OR ANNUL THE DISTRICT’S APPROVAL OF THIS APPLICATION, ISSUANCE OF ANY ASSOCIATED PERMIT, AND ANY ENVIRONMENTAL REVIEW ASSOCIATED WITH THE PROPOSED PROJECT.

Other Division Review Air Quality Fees Collected

General Plan/Zoning: Type Date Amount Receipt # Rec'd By

Use requires use permit: Yes No Filing

Use requires building permit: Yes No Permit

Planning: Building: Date: Date:

Z:\My Documents\Stationary Source Permitting Forms\01_APPLICATION_030404.wpd

# APPENDIX B

## Biomass-Fired Cogeneration Unit Project Best Available Control Technology Analysis
Anderson, California

Prepared for:

Sierra Pacific Industries P.O. Box 496028 Redding, CA 96049

Prepared by:
Geomatrix Consultants, Inc. 19203 36 th Ave W, Suite 101 Lynnwood, WA 98036

May 2007

Project No. 012692I:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc i TABLE OF CONTENTS

Page
1.0 INTRODUCTION.............................................................................................................1
2.0 BIOMASS-FIRED COGENERATI ON UNIT BACT ANALYSIS .................................2 2.1 NO X BACT A NALYSIS ...........................................................................................2 2.1.1 Identification of Possible Control Alternatives .........................................2 2.1.2 Control Alternative Review.......................................................................3 2.1.2.1 Summary of Possible Control Alternatives ...................................5 2.1.2.2 Technical Feasibility of Control Alternatives ...............................5 2.1.2.3 Effectiveness of Remaining Technologies ....................................7 2.1.2.4 Ranking by Effectiveness ..............................................................9 2.1.2.5 Cost-Effectiveness Analysis..........................................................9 2.1.3 Selection of BACT for NO x ......................................................................9 2.2 CO BACT A NALYSIS .............................................................................................9 2.2.1 Identification of Possible Control Alternatives .......................................10 2.2.2 Control Alternative Review.....................................................................10 2.2.2.1 Summary of Possible Control Alternatives .................................11 2.2.2.2 Technical Feasibility of Control Alternatives .............................11 2.2.2.3 Effectiveness of Remaining Technologies ..................................12 2.2.2.4 Ranking by Effectiveness ............................................................13 2.2.2.5 Evaluation of Cost Effectiveness.................................................13 2.2.3 Selection of BACT for CO......................................................................13 2.3 PM10 BACT A NALYSIS .......................................................................................14 2.3.1 Identification of Possible Control Alternatives .......................................14 2.3.2 Control Alternative Review.....................................................................15 2.3.2.1 Summary of Possible Control Alternatives .................................15 2.3.2.2 Technical Feasibility of Control Alternatives .............................15 2.3.2.3 Effectiveness of Remaining Technologies ..................................16 2.3.2.4 Ranking by Effectiveness ............................................................16 2.3.2.5 Cost Effectiveness Evaluation.....................................................16 2.3.3 Selection of BACT for PM10..................................................................17 2.4 ROG BACT A NALYSIS ........................................................................................17 2.4.1 Identification of Possible Control Alternatives .......................................17 2.4.2 Control Alternative Review.....................................................................17 2.4.2.1 Summary of Possible Control Alternatives .................................18 2.4.2.2 Technical Feasibility of Control Alternatives .............................18 2.4.2.3 Effectiveness of Remaining Technologies ..................................18 2.4.2.4 Ranking by Effectiveness ............................................................18 2.4.2.5 Cost Effectiveness Evaluation.....................................................18 2.4.3 Selection of BACT for VOCs..................................................................18 2.5 SO2 BACT A NALYSIS .........................................................................................19 2.5.1 Identification of Possible Control Alternatives .......................................19TABLE OF CONTENTS (Continued)

I:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc ii 2.5.2 Control Alternative Review.....................................................................19 2.5.2.1 Summary of Possible Control Alternatives .................................19 2.5.2.2 Technical Feasibility of Control Alternatives .............................20 2.5.2.3 Effectiveness of Remaining Technologies ..................................20 2.5.2.4 Ranking by Effectiveness ............................................................20 2.5.2.5 Cost Effectiveness Evaluation.....................................................20 2.5.3 Selection of BACT for SO2 ....................................................................20
3.0 COOLING TOWER BACT ANALYSIS .......................................................................21

TABLES

Table 1 NO x Control Technology Search Results Table 2 NO x Control Technology Cost-Effectiveness Summary Table 3 CO Control Technology Search Results Table 4 PM 10 Control Technology Search Results Table 5 ROG/VOC Control Technology Search Results Table 6 SO 2 Control Technology Search Results

APPENDIX

Attachment A NO x and SO 2 BACT Cost-Effectiveness CalculationsI:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 1 

### BACT ANALYSIS Sierra Pacific Industries Biom ass-Fired Cogeneration Project Anderson, California

1.0 INTRODUCTION
Sierra Pacific Industries (SPI) proposes to construct and operate a new biomass-fired cogeneration unit at an existing lumber manufac turing facility in Anderson, California. The project would consist of a biomass-fired coge neration unit, a steam tu rbine, and a cooling
tower. The boiler associated with the cogeneration unit would have a maximum heat input of up to 354 million British thermal units per hour (MMBtu/hr).

A new or modified source requiring an air permit, and required by regulations to apply the best available control technology (BAC T) for a given pollutant to one or more emission units, must conduct an analysis to ensure that BACT is be ing proposed in the permit application. The U.S. Environmental Protection Agency’s (USEPA’s) Prevention of Significant Deterioration (PSD) program requires that all proposed emission units must apply BACT to control any pollutant for which the proposed project would exceed the PS D Significant Emission Rate (SER) for that pollutant. 1 In addition, Shasta County has established daily emission rate thresholds for various pollutants, which, if exceeded by the proposed pr oject, require each proposed emission unit to apply BACT to control emi ssions of that pollutant. 2

A BACT analysis evaluates the energy, environmental, economic, and other costs associated with each potential control technology, and weighs those costs against the reduced emissions the technology would provide. As new sources of emissions, BACT analyses are required for the biomass-fired cogeneration unit and the coo ling tower. Based on the calculated annual emission rates for the proposed project and USEPA and Shasta County BACT thresholds, analyses are required fo r oxides of nitrogen (NO x ), carbon monoxide (CO), particulate matter equal to or less than ten microns in diameter (PM 10 ), reactive organic co mpounds (ROG), sulfur dioxide (SO 2 ), and beryllium.

Geomatrix queried EPA’s Reasonably Availa ble Control Technology (RACT)/BACT/Lowest Achievable Control Technology (LAER) Cleari nghouse (RBLC) database for recent BACT determinations involving wood- fired boilers. This initial broad search was refined by

1 40 CFR 51.21(b)(23)(i).
2 Shasta County Air Quality Management District Rule 2:1, Part 301.I:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 2 eliminating sources that did not emit pollutants as a result of similar operation. The California Air Resources Board (ARB) BACT Clearinghouse was also search ed for applicable permits, either pending or issued. The sections that fo llow discuss the contro l technologies available and, ultimately, the selection of BACT for each emission unit and pollutant.

2.0 BIOMASS-FIRED COGENERATION UNIT BACT ANALYSIS

A review of EPA’s RBLC databa se was conducted for biomass-fi red boilers. The search included all entries made after January 1, 1990 for biomass-fired, stoker-type boilers. The initial search was further refined by eliminating s ources that operate in a significantly different manner (e.g., fluidized bed boiler designs, use of fuels other than or in combination with biomass).

All biomass-fired boiler permits meeting the criteria outlined above were included in the review. Permitted emission limits were compared on a pound per MMBtu (lb/MMBtu) basis. An equivalent lb/MMBtu emission limit was calculated for sources that had permit limits expressed only as an emission rate over some short-term period (e.g., pounds per hour [lb/hr], pounds per day [lb/day]) by combining the em ission rate with the heat input.



### 2.1 NO X 

### BACT A NALYSIS
NO x is generated when combustion temperatur es are high enough for th e nitrogen in the
combustion air or bound in the fuel to co mbine with oxygen to form NO. Depending upon conditions, some portion of the NO will react to form NO 2 .

2.1.1 Identification of Possible Control Alternatives There are a variety of options available for controlling NO x emissions from combustion sources. Some options involve co mbustion controls that reduce NO x formation, while others
utilize add-on control devices to remove NO x after it is formed.

Combustion controls reduce NO x emissions by contro lling the combustion temperature and the availability of oxygen. Combustion air contai ning both nitrogen and oxygen can combine in a high temperature environment to form thermal NO x . The oxidation of nitrogen that is chemically bound in fuel sources can al so form what is called fuel-bound NO x .
Dry low-NO x (DLN) burners control thermal NO x formation by avoiding high temperature combustion zones and uneven oxygen distribution. This is accomplished by burner designs that carefully control the mixing of fuel and combustion air. Generally, use of DLN burnersI:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 3 requires a wall-fired furnace and pulverized biomass fu el that is burned in suspension with coal or natural gas.

Proper combustion generally refers to control, generally comput erized, of the amount of flue gas recirculation (FGR), the fuel feed rate, and the amount of over- or under-fire combustion air in the furnace. This type of control is common on boilers constructed in the last few
decades.

Add-on controls such as sele ctive catalytic redu ction (SCR) and selective non-catalytic reduction (SNCR) systems are widely us ed technologies for controlling NO x emissions from combustion sources. In the SCR process, am monia is mixed with the exhaust from the
combustion device and the mixture is passed through a catalyst bed. The NO x reacts with the ammonia aided by the catalyst to form nitrogen and water. Regenerative SCR (RSCR) systems have been developed recently to make applicat ion of an SCR system more economical by using a regenerative ceramic bed to recover some heat from the reheated flue gases.

The SNCR process is similar to SCR in that a reagent reacts with NO x to form nitrogen and water, although no catalyst is used to aid the reaction. The cataly st used in SCR systems allows
the reactions to occur at lower temperatures than is possible in SNCR systems (450 oF for SCR as opposed to 1,550 oF for SNCR). The SNCR reagent can be urea, aqueous ammonia, or anhydrous ammonia, and is typically vaporized and mixed with hot flue gas from the combustion device. Hybrid SNCR/RSCR system s, in which a catalyst bed is located downstream of the SNCR system, have been de veloped where the unreacted ammonia injected by the SNCR system is used by th e catalyst to further reduce NO x emissions.

SCONOx is similar to SCR, except that NO x in the exhaust stream reacts with potassium carbonate (K 2 CO 3 ) to form potassium nitrate (KNO 3 ). This compound is reacted with hydrogen to form gaseous nitrogen (N 2 ), and regenerate the K 2 CO 3 . The lower exhaust temperature limit required for the reactions in the SCONOx to take place is less than that of SCR (300 oF as opposed to 450 oF). The SCON Ox system is also said to control carbon monoxide (CO) and volatile orga nic compounds (VOCs) by oxidation.

2.1.2 Control Alternative Review The results of the database queries and permit investigations for NO x control technologies are presented in Table 1, sorted by permit limit, beginning with the NO x limit proposed for the cogeneration unit.I:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 4 The following technologies were found for controlling NO x from biomass-fired boilers:

• Proper combustion

• SNCR

• SCR

• RSCR

• SNCR/RSCR hybrid
The database queries did not produce any instances of NO x emissions from biomass-fired boilers controlled by DLN burner, SCR, RSCR, or SNCR/RSCR hybrid systems. Although not identified in the RBLC database, there is one SCR system, and at least two RSCR systems being used to control NO x emissions from biomass-fired boilers. Sauder Woodworking in Archbold, Ohio operates two 57 MMBtu/hr boilers fired with wood waste from furniture making operations. After an ESP removes partic ulate matter from the exhaust stream, an SCR system removes NO x . The permitted NO x limit for each of the boilers at Sauder Woodworking is 0.20 lb/MMBtu, which is higher than the prop osed emission limit for SPI’s new cogeneration
unit.

RSCR systems have been added to control NOx emissions from existing wood-fired boilers at Boralex Stratton Energy in Stra tton, Maine, and Whitefield Power & Light, in Whitefield, Connecticut. Both of these systems were re trofitted onto existing boi lers to qualify under
Renewable Portfolio Standards. The Boralex St ratton retrofit included the installation of an Ecotube system, which adds ambient air at strate gic locations to improve combustion efficiency
and reduce emissions. Because Ecotubes are also capable of injecting ammonia to act as an SNCR system, the Boralex facility has installed a de facto SNCR/RSCR hybrid NO x control system.

According to the RBLC database and the ARB BACT clearinghouse, the last biomass-fired boiler permitted in California was at SPI’s Quincy facility. The last biomass-fired boiler permitted by SPI was for a facility in Skag it County, Washington. For that wood-fired cogeneration unit, the Washingt on Department of Ecology determined that a 24-hour average of 0.13 lb/MMBtu and an annual average of 0.1 lb/MMBtu were BACT for NOx emissions
from a wood-fired boiler. The Skagit County boiler has only been combusting wood since February 2007, but similar emission levels ar e being achieved in pr actice using SNCR to
control NOx from a 310 MMBtu/hr boiler in Aber deen, Washington. The most recent biomass-I:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 5 fired boiler BACT determination in the RBLC was by the North Dakota State Department of
Health for Archer Daniels Midland’s Northern Su n facility in North Dakota, which determined
that 0.2 lb/MMBtu was BACT for NO x emissions from a 280 MMBtu/hr wood-waste and hullfired boiler employing combustion control. .

There are several instances of biomass-fired boilers using DLN burner technology to limit the
amount of NO x generated during combustion. Coen ma nufactures the Dual Air Zone (DAZ) Scroll burner, which can be used to fire pulver ized biomass materials al ong with some natural gas (approximately ten percent of total heat input). These burners have generally been installed in units with less than 100 MMBtu/hr heat inpu t, and require that the fuel be reduced to approximately 1/32 of an inch in size. With some flue gas re circulation and staged combustion,
a NO x emission rate of 0.35 lb/MMBtu at the furnace exit has been achieved.

2.1.2.1 Summary of Possible Control Alternatives
Based on literature and database searches the following alternatives are possible for controlling
NOx emissions from a biomass-fired boiler:

• Proper combustion

• DLN burner

• SCR

• RSCR

• SNCR

• SNCR/SCR hybrid

• SCONOx

2.1.2.2 Technical Feasibility of Control Alternatives
Most of the control alternatives described in the previous se ction have been shown to be technically feasible for controlling NO x emissions from biomass-fire d boilers. Several of the
alternatives have either not been applied to biomass-fired boiler s, or been applied to boilers with significantly lower heat input than that currently proposed by SPI.

Proper CombustionI:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 6 Proper combustion refers to the application of state-of-the-art design and appropriate operation of a combustion unit. Current design bioma ss-fired mass-burner-type boilers can generally
achieve NO x emission rates of 0.20 lb/MMBtu when operated in the manner recommended by the boiler designer and manufacturer. Proper combustion is a ubiquitous and technically feasible technology for controlling NO x emissions from biomass-fired boilers.

DLN Burner

For a boiler of the size proposed by SPI, two or more DLN burners would be required. With such burners, the fuel would be burned in suspension using wall-mounted burners, which would be a significant departure from SPI’s proposed boiler design, which has combustion occurring on a moving grate. These burners are generally intended to limit the amount of fuelbound nitrogen that is converted to NO x during combustion, and are generally suited to smaller
boilers that burn wood waste cont aining a high percentage of resi ns, such as the waste from medium density fiberboard (MDF), plywood, or ve neer operations. In this case, the emission rate with DLN burners (0.35 lb/MMBtu) is highe r than could be achieved by an uncontrolled mass burner-type boiler using a combustion grat e (approximately 0.20 lb /MMBtu), so this technology will be eliminated fr om consideration as BACT.

SNCR

Ammonia injection nozzles can be positioned at the furnace exit and use the relatively high temperatures there to promote the reaction of NO x and ammonia. SNCR system design is often incorporated into the overall boiler design, and can be located at the furnace exit because SNCR systems do not rely on a catalyst which is subject to plugging from particulate matter in the flue gases. The relative simplicity of SN CR systems makes them technically feasible, and
has resulted in them becomi ng the most popular add-on NO x control technology for biomassfired boilers.

SCR, RSCR and SNCR/SCR Hybrid

An SCR system used to control NO x emissions from a wood-fired boiler has been demonstrated
to control NO x emissions to 0.20 lb/MMBtu on two 57 MMBtu/hr boilers (the Sauder Woodworking boilers). RSCR systems have been applied to 220 MMBtu/hr (Whitefield) and 672 MMBtu/hr (Boralex Stratton) wood-fired bo ilers. No instances of SNCR/SCR hybrid systems applied to biomass-fired boilers have been identified, though the components of theI:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 7 system, SNCR and SCR, have been applied to wood-fired boilers. All three of these variations on SCR systems are considered tech nically feasible for controlling NO x emissions from a
biomass-fired boiler. Because RSCR controls NO x as effectively as an SCR system, and is more economical because of the heat recovery feature, only RSCR systems will remain in consideration from this point forward.

SCONOx

To date, SCONOx has been designed and used only on small- to medium-sized natural gasfired stationary turbines for demonstration purpo ses. The technology has never been applied to a biomass-fired boiler. Also, the SCONOx system is sensitive to sulfur in the exhaust, which can degrade the performance of the system. Wh ile biomass fuels are not generally considered high-sulfur fuels, the AP-42 SO2 emission f actor for wood-fired boilers is 0.025 lb/MMBtu, which is equivalent to about 7.2 lb/hr of SO 2. Natural gas, the combustion fuel most commonly associated with SCONOx applications, has maximum sulfur limit of one grain per 100 standard cubic feet (gr/scf) of gas in California, where SCONOx has been applied. On a heat input basis, this is equiva lent to an SO2 emission rate of 0.43 lb/hr. The sensitivity to sulfur, combined with a lack of comparable existing applications suggests that SCONOx is technologically infeasible as a co ntrol technology for controlling NO x emissions from a
biomass-fired boiler.

The following is a list of the technically f easible NOx control technologies and possible
combinations:

• Proper combustion

• SNCR

• RSCR

• SNCR/RSCR hybrid

2.1.2.3 Effectiveness of Remaining Technologies This section describes the remaining tec hnologies in more detail and ranks them by
effectiveness.

Proper CombustionI:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 8 A modern biomass-fired boiler fu rnace, operated with computeriz ed controls to ensure proper
combustion would result in a NO x emission limit of between 0.23 and 0.25 lb/MMBtu. The boiler design proposed by SPI would emit 0.20 lb/MMBtu when utilizing only proper combustion techniques to reduce NO x emissions.

SNCR

Currently, SNCR systems are the most common add-on control device used to reduce NO x emissions from large biomass-fired boilers. SNCR systems rely on high temperatures to promote the reaction of NO x with the introduced ammonia. As a result, the control system is often incorporated into the boile r design to facilitate the intro duction of the ammonia as close to the furnace as possible. Emission limits of between 0.1 and 0.2 lb/MMBtu have been achieved using SNCR systems to control NO x .
SPI proposes to employ an SNCR integral to the boiler design to reduce NO x emissions to 0.15 lb/MMBtu. A boiler permitted by NESCO in Darrington, Washington with a 0.12 lb/MMBtu 24-hour average limit and a 0.1 lb/MMB tu annual average limit is unlikely to ever be constructed and may not have consistently achieved that limit with an acceptable ammonia slip. Dominion – Pittsylvania Power Station (formerly Multitrade of Pittsylvania County, L.P.), in Hurt, Virginia, uses SNCR systems to control NO x from three wood-fired boilers and has a permit limit of 0.1 lb/MMBtu on a 30-day ro lling average basis. It should be noted that, while a 0.1 lb/MMBtu permit limit based on a 30-day rolling average is more stringent than the same limit based on an annual average, but can result in higher daily concentrations than a 0.13 lb/MMBtu limit based on a 24-hour average.

RSCR and SNCR/RSCR Hybrid

The Sauder boilers to which SCR systems have been applied have emission limit of 0.20 lb/MMBtu, which is equivalent to the emi ssion rate of SPI’s pr oposed boiler using only proper boiler design and combustion. The RSCR systems which have been applied to woodfired boilers have resulted in permit limits of 0.075 lb/MMBtu (quart erly average) and 0.25 lb/MMBtu (24-hour average) at the Borale x Stratton facility, and 0.33 lb/MMBtu at the Whitefield facility. When applied to a new boiler of modern design, the RSCR system could achieve a guaranteed emissi on limit of 0.07 lb/MMBtu, and 0.065 lb/MMBtu when employed as part of a hybrid system with the integral SNCR system.I:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 9 2.1.2.4 Ranking by Effectiveness The remaining technologically feasible contro l technologies ranked in decreasing order of
effectiveness are:

• SNCR/RSCR hybrid

• RSCR

• SNCR

• Proper combustion

2.1.2.5 Cost-Effectiveness Analysis The cost-effectiveness of SNCR, RSCR, and an SNCR/RSCR hybrid control system were calculated. The calculations for each system are presented in Attachment A, and are summarized in Table 2. As shown in Table 2, SNCR provides the lowest cost per ton of NO x removed, and is seven times more cost effective than RSCR. In addition, Table 2 presents the
incremental cost effectiveness of two more effective (and more costly) technologies. As shown in Table 2, the incremental cost effectiv eness increase between SNCR and RSCR and the SNCR/RSCR hybrid are in excess of $44,000 and $38,000 per ton of NO x removed, respectively. Based on this analysis, SNCR is deemed to be the most cost effective NO x control technology for wood-fired boilers. As a point of comparison, a recent NO x BACT
determination for a biomass-fired boiler in th e RBLC (ADM’s Northern Sun facility) indicates
that an incremental cost effectiveness of $6,540 per ton associated w ith installing an SNCR system instead of relying solely on combustion controls was considered to be excessive.

2.1.3 Selection of BACT for NO x Based on the analysis presented in this section, SPI proposes th at BACT for the control of NO x from biomass-fired mass-burner-type boilers is the use of an integral SNCR system. NO x emissions would be limited to 0.13 lb/MMBtu (30-day average), which is approximately equivalent to 202 TPY at the anticipated annual average oper ating capacity.



### 2.2 CO BACT A NALYSIS Carbon monoxide (CO) is a product of the chem ical reaction between carbonaceous fuels and oxygen. In fuel-rich mixtures, CO occurs as th e product of combustion. In fuel-lean mixtures CO can result due to poor mixing of fuel and ai r in the combustion zone (so the sub-region is fuel-rich) or because of very high temperatures in the combustion zone (above 1,727 C), which
causes dissociation of CO 2 into CO (Wark and Warner, 1981).I:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 10 2.2.1 Identification of Possible Control Alternatives
As for NO x , the control technology options availa ble for reducing CO emissions from
combustion sources include combustion controls that encourage complete combustion to reduce CO formation, as well as add-on cont rol devices that oxidize CO to CO 2 after leaving the
combustion area.

Combustion controls for CO include adequa te fuel residence times to ensure CO 2 formation, proper fuel-air mixing, and temperature control. These measures, however, can result in an
increase in the NO x emissions from a combustion unit. M odern boiler designs strive to balance these competing factors, and when combined with appropriate operati on of the boiler, are commonly referred to as “prope r combustion” practices.

Catalytic oxidizers use a matrix or “bed” coated with noble metals (e.g., platinum) to facilitate
the conversion of a criteria pollutant to a non-pollutan t (in this case CO to CO 2 ). Catalytic oxidizers operate in a temperature range of approximately 500 o F to 1,000 o F. At lower temperatures the CO conversion e fficiency falls off rapidly.

Because higher temperatures are desira ble for improved conversion of CO to CO 2 by the catalyst, the exhaust temperature must be increase d, resulting in higher fuel use. In order to reduce catalyst masking and pressure drop across the device, a particulat e control system (e.g., an ESP) must be located upstream of the catalyst bed. Also, the size of the particulate control system must be increased to accommodate th e higher temperature, and therefore higher volume, exhaust flow. Although the catalyst w ould be located downstream of a particulate control device, a steam injection system is used to periodically remove particulate matter from the catalyst.

SCONOx (described in the NO x BACT analysis) also utilizes a catalytic technique that oxidizes
CO to CO 2 in addition to controlling NOx emissions.

2.2.2 Control Alternative Review The results of the database queries for CO contro l technologies are presented in Table 3, sorted by permit limit, beginning with the CO limit proposed for the project.

The following technologies were found in the da tabases searched for controlling CO from
wood-fired boilers:

• Oxidation CatalystI:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 11 • Proper Combustion
The majority of biomass-fired boilers use prope r combustion to limit CO emissions. There are two instances where permits have been issued for biomass-fired boilers using catalytic
oxidation to limit CO emissions. One of these boilers is no longer opera ting, and the other has
not been constructed. Boilers with lower permit limits belo w 0.60 lb/MMBtu generally have
some detail that differentiates them from “norma l” biomass-fired boilers. Examples of these differences include: consistently available high heat-value-per-weight fu el sources, co-firing with fossil fuels, and lenient or nonexistent NO x and/or ammonia slip limits that allow operation at higher temperatur es that limit CO formation.

2.2.2.1 Summary of Possible Control Alternatives
Based on literature and database searches the following control alternatives are possible for the
boiler:

• Proper combustion

• Catalytic oxidation

• SCONOx

2.2.2.2 Technical Feasibility of Control Alternatives Proper combustion is the most widespread tech nique used to limit CO emissions from woodfired boilers. Catalytic oxidati on using a catalyst has been used in at least one instance (Bio Energy in West Hopkinton, NH), and is therefore considered technically feasible, although the facility employing the technology is no longer operating. A facil ity in South Point, OH has proposed to use oxidation catalysts to limit CO emissions to 0.1 lb/MMBtu, but, although a permit has been issued, the proponent has not begun construction and has not identified a vendor that will supply the catalys t to meet that permit limit.

As discussed in the NO x BACT analysis, SCONOx is extremel y sensitive to presence of sulfur in the exhaust stream, and has never been demons trated on a boiler of the size proposed by SPI. Therefore, SCONOx is not considered technically feasible for controlling CO emissions from a
wood-fired boiler.

According to the permit application submitte d for the Darrington, Washington cogeneration project, the proposed boile r would be a fuel-cell design. Fuel -cell design boile rs are typically bottom-supported and employ a shell of refractory tiles to achieve higher furnace temperaturesI:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 12 and lower CO emissions. The boiler proposed by SPI would have a top-supported design that does not include a refractory lining, and, because of weight and structural concerns, is the only feasible approach for a boiler of the size propos ed by SPI. SPI believes that a 1-hour average
CO emission limit of 0.60 lb/MMBtu can be ach ieved in practice using the top-supported design, while limiting NO x emissions to 0.13 lb/MMBtu and ammonia slip to 20 ppm. At the time this analysis was developed, the Da rrington boiler had not been constructed.

2.2.2.3 Effectiveness of Remaining Technologies This section describes the remaining tec hnologies in more detail and ranks them by
effectiveness.

Combustion Controls

Combustion controls provide a wide range of control effectiveness, depending on the configuration of the system. Generally, emissions resulting from incomplete combustion (CO and VOC) are balanced with emissions related to high furnace temperatures (NOx) to achieve optimally low emissions of all pollutants. However, in order to achieve the proposed NO x emission limit (0.13 lb/MMBtu) as well as the 20 parts per million (ppm) ammonia slip limit required by Shasta County (Shasta County AQM D Rule 3:26.c.4), boiler operation will favor
reduced NO x creation over reduced CO creation.

SPI currently operates biomass-fired boilers at their Lincoln, Calif ornia and Aberdeen, Washington lumber manufacturing f acilities that are similar in design to the proposed boiler. Both of these boilers were permitted with CO permit limits of (or equivalent to) 0.35 lb/MMBtu. However, the Aberdeen boiler ha s an ammonia slip limit of 50 ppm and is able to meet the CO emission limit, while the Lincoln boiler has a 20 ppm ammonia slip limit, and has had difficulty meeting the CO permit lim it to the point where Placer County APCD has recently increased the cogeneration unit’s CO permit limit to 170 lb/hr, which is roughly equivalent to 0.60 lb/MMBtu. While meeti ng the CO permit limit of 0.35 lb/MMBtu, the Aberdeen unit experiences ammonia slip in the 40 to 50 ppm range. At least two relatively recent permits have been issued for bioma ss-fired boilers (ADM-Northern Sun in North Dakota, and Inland Paperboard & Packaging in Louisiana) with CO permit limits of 0.60 lb/MMBtu or greater.

Catalytic OxidationI:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 13 Oxidation catalysts are generally capable of providing between 40 and 90 percent reduction in CO emissions. Although boiler efficiency w ould be sacrificed to increase the exhaust temperature, the catalyst temperature would be in the lower portion of the range over which the desired reaction occurs resulting in lower control efficiencies.

2.2.2.4 Ranking by Effectiveness The remaining technologically feasible contro l technologies ranked in decreasing order of
effectiveness are:

• Proper combustion

• Catalytic oxidation

2.2.2.5 Evaluation of Cost Effectiveness The cost effectiveness of installing an oxidati on catalyst to achieve 50 percent control of CO
emissions from a biomass-fired boiler was calcu lated. There are two ap proaches to applying oxidation catalyst technology to a biomass-fired boiler. The approach that has been demonstrated in practice (although the unit is no l onger operating) is to reduce the efficiency of the boiler’s waste heat recovery system in or der to make the oxidation catalyst effective by increasing the exhaust gas temperature.

A permit application for a similar-sized w ood-fired boiler submitted to the Washington Department of Ecology by Darrington Cogenera tion in 2003 included a cost-effectiveness analysis using direct and indir ect costs estimated using the EP A’s “Air Pollution Cost Manual" (Sixth Edition, January 2002, EPA/452/B-02-001). In that analysis, the cost of the oxidation catalyst itself (including an addi tional catalyst bed to allow semi -annual chemical cleaning), the additional ductwork, increasing the size of the part iculate control device, and increased fuel use due to loss of efficiency equates to approxi mately $14,000 per ton of CO controlled, which was considered outside the envelope of acceptable cost s. Even if this analysis were modified to represent the larger proposed boiler and an assumed 50 per cent reduction in VOC emissions, the cost per ton of pollutant would be approximately $8,200.

2.2.3 Selection of BACT for CO Based on the analysis presented in this section, SPI proposes that BACT for the control of CO
from biomass-fired boilers is the use of a mass burner-type boiler with proper combustion
controls. CO emissions would be limited to 0.60 lb/MMBtu (3-hour average), which is approximately equivalent to 931 TPY at th e anticipated annual operating capacity.I:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 14 

### 2.3 PM10 BACT A NALYSIS PM10 is produced by combustion processes as unburned solid carbon (soot), unburned vapors or gases that subsequently condense, and the unburnable portion of the fuel (ash).

2.3.1 Identification of Possible Control Alternatives The concept of applying combustion controls or “proper combustion” to minimize PM 10 emissions is similar to the strategy used to c ontrol CO and includes adequate fuel residence time, proper fuel-air mixing, and temperature cont rol to ensure the maximum amount of fuel is combusted. As discussed in the analysis of BACT for CO emissions, optimization of these
factors for PM10 control can result in an increase in the NO x emissions. Thus, operators strive
to balance the factors under their control to achieve the lowest possible emissions of all pollutants.

The two most popular add-on control technologies for control of PM 10 emissions from a boiler are electrostatic precipitators (ESPs) and baghouses . ESPs remove particles from an exhaust stream by imposing an electrical charge on the part icles and then attracting them to an oppositely charged plate. The dust collected on th e charged plates is periodically removed by vibrating or rapping of the plates.

Baghouses, or fabric filters, use various types of ma terials (generally fabric s) to trap particles while the gas passes through the voids in the ma terial. The dust that becomes caked on the fabric bags is removed periodical ly by shaking, by blowing jets of air, or by using sonic horns. Often a mechanical collector, such as a multiclone , is used to remove larger particulate matter
before the exhaust reaches th e primary control device.

Wet scrubbers, such as venturi scrubbers are le ss common because they typically have lower
control efficiencies than either ESPs or ba ghouses. They also complicate waste disposal by introducing liquids that create sludge when combined with the removed PM 10 . A venturi is a narrowed section of duct followed by an expande d section of duct, with scrubbing liquid injected at the constricted section. The liquid in atomized by the increased velocity exhaust flow, and the particles impact the droplets and are collected. Because the liquid must be atomized to ensure high collection efficien cy, a high-energy exhaust flow is required.I:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 15 2.3.2 Control Alternative Review The results of the database queries for PM 10 control technologies ar e presented in Table 4, sorted by permit limit, beginning with the PM 10 limit proposed by SPI for the new biomassfired cogeneration unit.

A review of the RBL Clearinghouse indicates that the most stringent control technology for
PM 10 is use of an ESP or a baghouse. Th e most stringent permit limit employing ESP technology to control PM 10 emissions is 0.02 lb/MMBtu at Sierra Pacific Industries facilities in Aberdeen and Skagit County, Washington, Borale x in Livermore Falls , Maine, Multitrade Limited Partnership in Hurt, Virginia, and Ha mpton Lumber in Darrington, Washington. Until recently, many permit limits did not include both the filterable and condensable portions of particulate emissions, so some of the emission li mits from permits issued several years ago may be less stringent than they appear.

The most stringent permit limit employing bagho use technology is at Kimberly-Clark in Everett, Washington, which has a PM 10 permit limit of 0.0084 gr/dscf at 7 percent oxygen, equivalent to 0.016 lb/MMBtu. It should be note d that the testing required for the KimberlyClark boiler is for filterable PM 10 only. The Wheelabrator Ridge Energy facility in Ashland, Florida, has a permit limit of 0.008 gr/dscf at 7 percent oxygen, equivale nt to 0.02 lb/MMBtu. This facility also requ ires only a filterable PM 10 test method to confirm compliance with the permit limit.

2.3.2.1 Summary of Possible Control Alternatives
Based on literature and database searches the following control alternatives are possible for the
boiler:

• ESP preceded by a multiclone

• Baghouse

• Venturi scrubber

2.3.2.2 Technical Feasibility of Control Alternatives The most common technology for controlling PM 10 emissions from a biomass-fired boiler is an ESP preceded by a multiclone. Baghouses have been employed to control PM 10 emissions
from boilers in which wood is fire d with other fuels such as oil or tires. The lik elihood of fires in downstream ducting or control devices is si gnificant because of th e high carbon content of the ash from boilers that burn biomass fuels, but many operators and manufacturers haveI:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 16 engineered designs to minimize this risk. ESPs, constructed mostly of metal, suffer considerably less damage from fires than baghous es, which generally have combustible fabric filters, unless expensive flame-proof bags are purchased. Venturi scrubbers are generally employed to control PM 10 from smaller boilers with lower exhaust flow, and typically have lower control efficiencies than ESPs or baghouses

2.3.2.3 Effectiveness of Remaining Technologies This section briefly describes the effectiveness of the remain ing technologies ranks them in
order of effectiveness.

Venturi Scrubbers

Venturi scrubbers with pressure drops of between 5 and 10 inch es of water typically remove less than 99 percent of PM 10 from exhaust flows. Units with pressure drops of 20 inches of water or greater can remove greater than 99 percent of PM 10 .
Baghouses

Baghouses typically operate with pressure dr ops between 2 and 12 in ches of water. PM 10 control efficiencies are capable of removing over 99 percent of PM 10 from gas streams.

ESPs

ESPs, which typically experience pressure losses of around 0.5 inches of water, are capable of removing over 99 percent of PM 10 from exhaust flows.

2.3.2.4 Ranking by Effectiveness The remaining technologically feasible contro l technologies ranked in decreasing order of
effectiveness are:

• ESP; Baghouse (judged to be equally effective)

• Venturi Scrubber

2.3.2.5 Cost Effectiveness Evaluation No cost effectiveness evaluation comparing th e baghouse or scrubber is presented because SPI
selected the ESP for the w ood-fired cogeneration unit.I:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 17 2.3.3 Selection of BACT for PM10 SPI proposes that BACT for PM 10 emissions from a biomass-fired boiler is the use of a mechanical collector followed by an ESP, and an emission rate of 0.01 grains per dry standard cubic foot (gr/dscf), which is equivalent to 0.019 lb/MMBtu (3-hour average), or a mass emission rate of 29.5 TPY.



### 2.4 ROG/VOC BACT A NALYSIS With the exception of various chloro- and fluor ocarbons, ROG is the same as EPA’s definition of volatile organic compounds (VOC). Because most permits include limits for VOCs instead of ROG, and because they are so similar, this BACT analysis is for VOC, but all statements and
conclusions could be drawn for ROG as well.

VOC emissions are generally the result of incomple te fuel combustion. In the case of biomass,
volatiles are released as the fu el is heated in the furnace, some portion of which escapes combustion by improper mixing with oxygen or zones of relatively low temperature.

2.4.1 Identification of Possible Control Alternatives Combustion controls, or proper combustion t echniques, provide wide range of control effectiveness depending on the c onfiguration of the system. Generally, emissions resulting from incomplete combustion (CO and VOC) are balanced with emissions related to high furnace temperatures (NO x ) to achieve optimally low emi ssions of all pollutants.

Add-on controls used to reduce VOCs generally fa ll into three categories: adsorption onto a solid (e.g., activated carbon), absorption by a liq uid, and incineration by a flame or using a catalyst. There are no instances in the RBLC of any of these approaches having been used to
control VOCs from a biomass-fired boiler.

2.4.2 Control Alternative Review The results of the database queries for VOC co ntrol technologies are presented in Table 5, sorted by permit limit, beginning with the VOC limit proposed by SPI for the new cogeneration
unit.

The only technology employed as BACT for VOC em issions from a bioma ss-fired boiler is maintaining proper combustion of the fuel. As shown in Table 5, permit limits vary considerably, ranging over an or der of magnitude. Clearly, ag encies approving permit limits for VOC have been flexible, understanding the tradeoffs between emissions of NO x , CO, andI:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 18 VOC that are inherent to maintaining prope r combustion. Two permit limits have been
identified that are lower than the VOC limit proposed by SPI for the new wood-fired cogeneration unit. In both cases, higher permit limits have been deemed BACT after the lower permit limits were approved. In one case, the Maine Department of Environmental Protection
determined that a limit of 0.02 lb/MMBtu was BACT for a facility constructed in 1991, and
that 0.03 lb/MMBtu was BACT for another facility in 1999. In Washington, SPI’s facility in Aberdeen received permit limit for 0.025 lb/MMB tu in 2002, and SPI’s Burlington facility received a permit limit of 0.019 lb/MMBtu in 2006.

2.4.2.1 Summary of Possible Control Alternatives Based on database queries and other researc h, proper combustion is the only possible VOC
control alternative for a biomass-fired boiler.

2.4.2.2 Technical Feasibility of Control Alternatives Proper combustion is a technically feasible cont rol alternative that is used to control VOC
emissions from most biomass-fired boilers.

2.4.2.3 Effectiveness of Remaining Technologies The effectiveness of proper combustion as a VOC control technology varies considerably, and is largely dependent on tradeoffs made in the design and operation of the boiler to minimize other pollutants (e.g., NO x ).

2.4.2.4 Ranking by Effectiveness Proper combustion is the only feas ible control technology, therefore it is the most effective.

2.4.2.5 Cost Effectiveness Evaluation Because proper combustion is the only alternativ e, it is, by default, the most cost effective.

2.4.3 Selection of BACT for VOCs Based on the above discussion, proper combustion is proposed to be BACT for VOC emissions from the biomass-fired boiler. SPI proposes a VOC emission rate of 0.013 lb/MMBtu, equivalent to 20.2 TPY at the anti cipated annual operating capacity.I:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 19 

### 2.5 SO 2 

### BACT A NALYSIS Sulfur dioxide (SO 2 ) emissions are entirely dependent upon th e amount of sulfur present in the
fuel. Sulfur contained in the fuel combines with oxygen at combustion temperatures to form
SO 2 .

2.5.1 Identification of Possible Control Alternatives There are two alternatives for reducing SO 2 emissions combustion sources: removal of sulfur from the fuel before it is combusted, and removal of SO 2 from the exhaust gas after
combustion.

Removing sulfur from fuel before it is co mbusted has been employed to remove sulfurcontaining nonorganically-bound mine rals (e.g., pyrites) from coal , but this practice is not feasible for biomass fuels, where the sulfur is organically bound in the fuel. All permitted
biomass-fired boilers have no SO 2 control requirement other than the exclusive use of biomass, and perhaps a limit on the sulfur conten t of a start-up or co-fired fuel.

Scrubbing, or flue gas desulfuriz ation (FGD) systems remove SO 2 from the exhaust gases after they leave the furnace using a slurry of lime or limestone (some systems use sodium or other sorbent materials) and water into a chamber wh ich the gases pass through. The sorbent in the slurry comes in contact with the SO 2 in the exhaust gas and reacts with it. Depending upon the design of the system, the reacted sorbent slurry can remain wet or be dried by the hot exhaust such that only dry reacted sorbent remains. In dry FGD systems and spray driers, the particulate control system (usually a fabric filt er) must be sized to handle the additional load created by the SO 2 control system. Both wet and dry FGD systems require waste handling operations to remove the reacted sorbent material.

2.5.2 Control Alternative Review The results of the database queries for SO 2 control technologies are presented in Table 6, sorted by permit limit, beginning with the SO 2 limit proposed by SPI for the new boiler.

2.5.2.1 Summary of Possible Control Alternatives
Based on literature and database searches the following control alternatives are possible for the
boiler:

• None

• FGDI:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 20 2.5.2.2 Technical Feasibility of Control Alternatives FGD systems are more commonly applied to coal-f ired boilers, and, while there are no apparent technical restrictions to application of FGD systems to biomass-fired boilers, there are no instances of this technology being used to reduce SO 2 emissions from a biomass-fired boiler.

2.5.2.3 Effectiveness of Remaining Technologies Wet FGD systems are considered the most effec tive, and can achieve greater than 90 percent
reduction in SO 2 emissions. Dry scrubbers and spray drie rs are capable of control efficiencies on the order of 90 percent.

2.5.2.4 Ranking by Effectiveness The remaining technologically feasible contro l technologies ranked in decreasing order of
effectiveness are:

• None

• FGD

2.5.2.5 Cost Effectiveness Evaluation
Costs for an SO 2 scrubbing unit that could be applied to the proposed wood-fired boiler were
obtained from a wood-fired boiler manufacturer (McBurney of Norc ross, Georgia) and used to
calculate cost effectiveness. As shown in the cost effectiveness calculations in Attachment A, reducing SO 2 from a wood-fired boiler using a scr ubbing system would cost approximately $21,000 per ton of SO 2 removed, which is outside the envelope of acceptable cost
effectiveness.

2.5.3 Selection of BACT for SO 2 SPI proposes that no control system is BACT for reducing SO 2 emissions from a biomass-fired boiler, and that the boiler SO 2 emission rate will be 0.016 lb/MMBtu based on source test data, which is equivalent to a mass emi ssion rate of 24.8 tons per year.



### 2.6 B ERYLLIUM 

### BACT A NALYSIS Beryllium emissions are entirely a function of the beryllium content of the fuel. The RBLC contains three biomass-fired units with beryllium permit limits, one co-fires fossil fuels (oil and coal), and the other two burn tire s. SPI proposes that no contro l system is BACT for reducing beryllium emissions from a biomass-fired boiler. An AP-42 source test-d erived emission factorI:\Project\SPI\SPI_Anderson-12692\permit_applicat ion\SPI Anderson BACT Analysis - final.doc 21 of 1.55 x 10 -6 lb/MMBtu was used to cal culate emissions from th e proposed cogeneration unit (approximately 4.81 lb/yr).

3.0 COOLING TOWER BACT ANALYSIS
In 2002, the Olympic Region Clean Air Agency (ORCAA) permitted a cooling tower for a new Sierra Pacific sawmill in Aberdeen, Washington. ORCAA determined that BACT for cooling towers was the use of DRU-1.5 high-efficiency mi st eliminators with a drift loss of less than 0.0005 percent. This drift eliminator design is based on the D-15, originated by Munters Corporation, which is now owned by Brentwood I ndustries, Inc. The principal difference is that the DRU-1.5 removes the side plates on each pa nel, allowing the panels to be nested for a seamless installation. The water loading expect ed for the cooling towers is 4.24 gallons per minute per square foot (gpm/ft 2 ) and an air velocity of 503 feet per minute (fpm). The D-15
drift test results indicate that the drift rate a ssociated with these values should be less than 0.0005 percent.

Of the three most recent instances of permits issu ed for projects including cooling towers in the RBLC, one (Western Greenbrier Cogeneration in West Virginia, permit issued April 26, 2006) deemed 0.00005 percent drift elim inators BACT, another (Marat hon Petroleum in Louisiana, permit issued December 27, 2006) deemed 0.005 per cent drift eliminators BACT, and the third (Valero Refining in Louisiana, permit issued Fe burary 8, 2007) deemed drift eliminators BACT without specifying an effectiveness. The coo ling tower proposed for the new cogeneration unit project at SPI’s Anderson lumber manufacturing facility would use the same high-efficiency mist eliminators as the cogeneration unit coo ling towers at SPI’s Aberdeen and Burlington facilities in Washington, and SPI proposes that this technol ogy remains BACT for cooling

towers.

# TABLESTABLE 1NOXCONTROL TECHNOLOGY SEARCH RESULTSSierra Pacific Industries New Biomass-Fired Cogeneration ProjectAnderson, CaliforniaFacility NameLocationDate ofPermitHeat Input(MMBtu/hr)Permit Limit(lb/MMBtu)ControlTechnologyBasisSierra Pacific Industries Anderson, CA Proposed 35410.13 SNCR BACT-PSDWhitefield Power & Light Whitefield, NH 9/10/04 220 0.33/0.0752RSCR BACT-OTHERPittsylvania Power Hurt, VA 2/21/92 374 0.13SNCR BACT-PSDNESCO Darrington, WA 1/18/05 403 0.12/0.14,5SNCR BACT-PSDSierra Pacific Industries Burlington, WA 9/21/05 430 0.13 SNCR BACT-PSDSierra Pacific Industries Aberdeen, WA 10/17/02 310 0.15/0.14SNCR BACT-PSDLaurentian Energy Virginia, MN 6/30/05 230 0.15 SNCR BACT-PSDHampton Lumber Darrington, WA 6/1/05 245 0.15 SNCR BACT-OTHERBoralex Ashland Ashland, ME 4/2/92 586 0.15 SNCR BACT-OTHERADM Northern Sun Enderlin, ND 5/1/06 180 0.204Proper Combustion BACT-PSDKES Chateaugay Project Chateaugay, NY 12/19/94 275 0.23 No Controls BACT-OTHERWeyerhaeuser Co. Bruce, MS 5/9/95 90 0.23 Proper combustion BACT-PSDBoralex, Stratton Stratton, ME 1/4/05 672 0.24 SNCR/RSCR BACT-OTHERWheelabrator Energy Sherman Station, ME 4/9/99 315 0.25 Proper combustion BACT-PSDSmurfit-Stone Container Stevenson, AL 1/15/97 620 0.25 Proper combustion BACT-PSDWillamette Industries, Inc. Marlboro, SC 4/17/96 470 0.3 Proper combustion BACT-OTHERGeorgia Pacific Corp. Gloster, MS 4/11/95 244 0.3 None BACT-PSDWillamette Industries, Inc Campti, LA 2/4/91 940 0.3 Proper combustion BACT-PSD1Annual average heat input.2Quarterly average emission limit is 0.075 lb/MMBtu and the 24-hour average limit is 0.33 lb/MMBtu.3Based on a 30-day rolling average.4The first value is the 24-hour average limit, and the second is the annual average limit.5 The NESCO project was never constructed.TABLE 2NOXCONTROL TECHNOLOGY COST-EFFECTIVENESS ANALYSISSierra Pacific Industries Lumber Manufacturing ProjectAnderson, CaliforniaControl TechnologyAnnualized Cost1($/yr)Reduction(tons/yr)Cost Effectiveness($/ton)IncrementalCost Effectiveness($/ton)SNCR253,474 155 1,635 ---RSCR2,319,749 202 11,509 44,421SNCR/RSCR Hybrid2,332,065 209 11,141 38,3021Based on 20-years at 7% interest.TABLE 3CO CONTROL TECHNOLOGY SEARCH RESULTSSierra Pacific Industries Lumber Manufacturing ProjectAnderson, CaliforniaFacility NameLocationDate ofPermitHeat Input(MMBtu/hr)Permit Limit(lb/MMBtu)ControlTechnologyBasisSierra Pacific Industries Anderson, CA Proposed 35410.60 Proper combustion BACT-PSDSouth Point Power South Point, OH 4/4/06 318 0.10 Oxidation catlyst BACT-PSDHampton Lumber Darrington, WA 6/1/05 245 0.23 Proper combustion BACT-OTHERLaurentian Energy Virginia, MN 6/30/05 230 0.3 Proper combustion BACT-PSDWillamette Industries, Inc. Marlboro, SC 4/17/96 470 0.3 Proper combustion BACT-OTHERBoralex Ashland Ashland, ME 4/2/92 586 0.3 Proper combustion BACT-OTHERWillamette Industries Inc Campti, LA 2/4/91 940 0.32Proper combustion BACT-PSDDecker Energy International East Ryegate, VT 7/11/90 300 0.3 Proper combustion BACT-PSDSierra Pacific Industries Burlington, WA 9/21/05 430 0.35 Proper combustion BACT-PSDNESCO – Darrington Cogeneration Darrington, WA 1/18/05 403 0.353Proper combustion BACT-PSDSierra Pacific Industries Aberdeen, WA 10/17/02 310 0.35 Proper combustion BACT-PSDKES Chateaugay Project Chateaugay, NY 12/19/94 275 0.35 Proper combustion BACT-OTHERPittsylvania Power Hurt, VA 2/21/92 374 0.35 Proper combustion BACT-PSDSmurfit-Stone Container Stevenson, AL 1/15/97 620 0.4 Proper combustion BACT-PSDWeyerhaeuser Company Bruce, MS 5/9/95 90 0.4 Proper combustion BACT-PSDGulf States Paper Corp Moundville, AL 10/14/98 98 0.5 Proper combustion BACT-PSDInland Paperboard & Packaging Bogalusa, LA 11/23/04 788 0.60 Proper combustion BACT-PSDADM Northern Sun Enderlin, ND 5/1/06 180 0.63 Proper combustion BACT-PSDBio Energy Corp. West Hopkinton, NH 7/23/98 225 1.0 Oxidation catalyst BACT-OTHERPlum Creek Mfg Lp-Columbia Falls Columbia Falls, MT 7/26/95 292 1.6aProper combustion BACT-PSD1Annual average heat input.2Permit limit calculated based on heat input; actual permit limit is in lb/hr.3 The NESCO project was never constructed.TABLE 4PM10CONTROL TECHNOLOGY SEARCH RESULTSSierra Pacific Industries Lumber Manufacturing ProjectAnderson, CaliforniaFacility NameLocationDate ofPermitHeat Input(MMBtu/hr)Permit Limit(lb/MMBtu)ControlTechnologyBasisSierra Pacific Industries Anderson, CA Proposed 35410.019 Multiclone, ESP BACT-PSDSouth Point Power South Point, OH 4/4/06 318 0.01252Baghouse BACT-OTHERKimberly-Clark Tissue Co. Everett, WA 7/1/93 718 0.0163Baghouse BACT-OTHERSierra Pacific Industries Burlington, WA 9/21/05 430 0.02 Multiclone, ESP BACT-PSDHampton Lumber Darrington, WA 6/1/05245 0.02 Multiclone, ESP BACT-OTHERNESCO – Darrington Cogeneration Darrington, WA 1/18/05 403 0.024Multiclone, ESP BACT-PSDSierra Pacific Industries Aberdeen, WA10/17/02 315 0.02 Mulitclone, ESP BACT-PSDBoralex Livermore Falls, ME 9/5/91 534 0.02 Multiclone, ESP BACT-PSDPittsylvania Power Hurt, VA 2/21/92374 0.02 Multiclone, ESP BACT-PSDDecker Energy International East Ryegate, VT 7/11/90 300 0.023Mech. Collector, ESP BACT-PSDLaurentian Energy Virginia, MN 6/30/05 230 0.025 ESP BACT-PSDSmurfit-Stone Container Stevenson, AL1/15/97 620 0.03 Multiclone, ESP BACT-PSDWheelabrator Sherman Energy Sherman Station, ME 4/9/99 630 0.036 Baghouse BACT-PSDBoralex Chateaugay, NY 12/19/94 275 0.038 Multiclone, ESP BACTWillamette Industries, Inc. Marlboro, SC 4/17/96 470 0.05 ESP BACT-OTHERADM Northern Sun Enderlin, ND 5/1/06 180 0.08 ESP BACT-PSDGulf States Paper Corp. Moundville, AL10/14/98 98 0.1 Multiclone, ESP BACT-PSDWeyerhaeuser Co. Millport, AL 10/28/94 91 0.15 Venturi Scrubber BACT-PSD1Annual average heat input.2Permit limit calculated based on heat input, actual limit is in gr/dscf and permit requires filterable-only PM10 test method.3Permit limit calculated based on heat input, actual limit is in gr/dscf, and permit requires filterable-only PM10 test method.4 The NESCO project was never constructed.TABLE 5ROG/VOC CONTROL TECHNOLOGY SEARCH RESULTSSierra Pacific Industries Lumber Manufacturing ProjectAnderson, CaliforniaFacility NameLocationDate ofPermitHeat Input(MMBtu/hr)Emission Rate(lb/MMBtu)ControlTechnologyBasisSierra Pacific Industries Anderson, CA Proposed 35410.013 Proper combustion BACT-PSDSouth Point Power South Point, OH 4/4/06 318 0.013 Oxidation catlyst BACT-PSDBoralex Livermore Falls, ME 9/5/91 534 0.02 Proper combustion BACT-PSDGeorgia Pacific Corp Gloster, MS 4/11/95 244 0.02 None BACT-PSDSierra Pacific Industries Burlington, WA 9/21/05 430 0.0251Proper combustion BACT-PSDHampton Lumber Darrington, WA 6/1/05 245 0.025 Proper combustion BACT-OTHERNESCO – Darrington Cogeneration Darrington, WA 1/18/05 403 0.0252Proper combustion BACT-OTHERSierra Pacific Industries Aberdeen, WA 10/17/02 310 0.025 Proper combustion BACT-PSDWheelabrator Sherman Energy Co. Penobscott, ME 4/9/99 315 0.03 Proper combustion BACT-PSDGulf States Paper Corp Demopolis, AL 12/10/97 775 0.03 Proper combustion BACT-PSDSmurfit-Stone Container Stevenson, AL 1/15/97 620 0.03 Proper combustion BACT-PSDSouthern Soya Corp. Estill, SC 10/2/95 58 0.05 Proper combustion LAERWeyerhaeuser Co. Millport, AL 10/28/94 91 0.05 None BACT-PSDPittsylvania Power Hurt, VA 2/21/92 374 0.07 Proper combustion BACT-PSDGulf States Paper Corp Moundville, AL 10/14/98 98 0.1 None BACT-PSDWillamette Industries, Inc. Marlboro, SC 4/17/96 470 0.1 Proper combustion BACT-OTHERBoralex Chateaugay, NY 12/19/94 275 0.1 None BACT-OTHERWillamette Industries Inc Campti, LA 2/4/91 940 0.1 Proper combustion BACT-PSDScott Paper Co. Everett, WA 7/1/93 718 0.5 Proper combustion BACT-OTHER1Annual average heat input.2 The NESCO project was never constructed.TABLE 6SO2 CONTROL TECHNOLOGY SEARCH RESULTSSierra Pacific Industries Lumber Manufacturing ProjectAnderson, CaliforniaFacility NameLocationDate ofPermitHeat Input(MMBtu/hr)Emission Rate(lb/MMBtu)ControlTechnologyBasisSierra Pacific Industries Anderson, CA Proposed 35410.016 None BACT-PSDWillamette Industries, Inc Campti, LA 2/4/91 940 0.008 Fuel specification BACT-PSDPittsylvania Power Hurt, VA 2/21/92 374 0.0162Fuel specification BACT-PSDGeorgia Pacific Corp Gloster, MS 4/11/95 244 0.017 None BACT-PSDBoralex Livermore Falls, ME 9/5/91 534 0.023 None BACT-PSDSierra Pacific Industries Burlington, WA 9/21/05 430 0.025 None BACT-PSDHampton Lumber Darrington, WA 6/1/05 245 0.025 None BACT-OTHERNESCO – Darrington Cogeneration Darrington, WA 1/18/05 403 0.0253None BACT-OTHERSierra Pacific Industries Aberdeen, WA 10/17/02 310 0.025 None BACT-PSDBoralex Chateaugay, NY 12/19/94 275 0.03 Fuel specification BACT-OTHERSouth Point Power South Point, OH 4/4/06 318 0.07 Spray dryer BACT-PSDSmurfit-Stone Container Stevenson, AL 1/15/97 620 0.1 Proper combustion BACT-PSDWillamette Industries, Inc. Marlboro, SC 4/17/96 470 0.1 None BACT-OTHERScott Paper Co. Everett, WA 7/1/93 718 0.1 Fuel specification BACT-OTHERWheelabrator Sherman Energy Co. Penobscott, ME 4/9/99 315 0.12 Fuel specification BACT-PSDGulf States Paper Corp Demopolis, AL 12/10/97 775 0.46 Proper combustion BACT-PSDADM Northern Sun Enderlin, ND 5/1/06 180 0.47 None BACT-PSD1Annual average heat input.230-day rolling average.3 The NESCO project was never constructed.

# ATTACHMENT A

# APPENDIX CI:\Project\SPI\SPI_Anders on-12692\permit_application\Prioritiza tion_Appendix_anderson-draft_040607.doc 1 APPENDIX C

FACILITY PRIORITIZATION SCORES FOR TOXIC AIR CONTAMINANTS

In support of the permit application, Geomatrix ha s calculated prioritization scores for chemical emissions from the SPI Anderson facility based on Facility Prioritization Guidelines (CAPCOA, 1990). The Facility Prioritization Guidelines were developed in support of the Air Toxics Hot Spots Information and Assessmen t Act of 1987 (Hot Spots or AB 2588) (AB 2588, Connelly, Statutes of 1987; Health and Safety Code Section 44300 et seq.). Prioritization scores are not estimates of potential health risk s, but are simple screen ing methods to compare facilities to one another with respect to potentia l health risks from ch emical emissions. As requested by Shasta County AQMD, both cance r and noncancer prioritiz ation scores were estimated. Two procedures for ca lculating prioritizati on scores were applied, one based simply on emissions, toxicity, and receptor locations (e mission and potency prioritization procedure), and one based on emissions, receptor locations , and source characte ristics (dispersion adjustment prioritization procedure).

For facility emissions, the can cer prioritization scores were 26 and 21 and the noncancer prioritization scores were 20 and 17 by the em ission and potency, and dispersion adjustment prioritization procedures, resp ectively. CAPCOA guidelines recommend cancer and noncancer prioritization scores between 10 and 100 as the range of threshold for ranking facilities as high priority. However, the AQMD has discretion to set their high prio rity threshold above or below this range.

B ACKGROUND ON AB 2588

The purpose of the AB 2588 process is to identify and rank facilities ba sed on their release of toxic air contaminants and to evaluate the potential health risks to the community exposed to
these releases. The California Air Resources Boar d (ARB) promulgates the list of air toxics for which emissions need to be quantified.

In order to identify and rank the various facilities, each air polluti on control district (APCD) or air quality management district (AQMD) requi res facilities to submit comprehensive emission inventory reports that list the substances and amounts of chemi cals from individual emission units within the facility. If the facility is identified as a high priority facility by the local APCD or AQMD, often done using the prio ritization score procedure, then a health risk assessment of the chemicals emitted must also be prepared.I:\Project\SPI\SPI_Anders on-12692\permit_application\Prioritiza tion_Appendix_anderson-draft_040607.doc 2 T HE E MISSIONS AND P OTENCY P RIORITIZATION P ROCEDURE The first procedure to prioritize facility emissi ons is based on estimated emissions, the potential toxicity of emitted toxic air contaminants, and th e proximity to potential receptors. Chemical emission rates for the boiler were estimated as outlined in Section 2.3.3 of the permit application. The toxicity crit eria were obtained from the Hotspots Analysis and Reporting Program, a risk assessment and prioritization so ftware created by the California Air Resources Board (CARB, 2006) to comply with the Office of Environmental Hea lth Hazard Assessment’s OEHHA’s risk assessment guidance (2003). The receptor proximity was estimated using an aerial photograph and a site drawing. Cons istent with CAPCOA guidelines, the receptor proximity was estimated by adding the distance fr om the facility property line to the nearest potential receptor (the fence line of Siskiyou Forest Products approximately 5 meters to the west) to the distance from the facility propert y line to the emitting source (approximately 268 meters). The calculati ons and input parameters are attached in Table 1.

Cancer Prioritization Score The prioritization score for carcinogenic effects was calculated as follows:

1700 × × ⎭ ⎬ ⎫ ⎩ ⎨ ⎧

× = 

# ∑ RP P E TS c

c c (1)

Where:

TS = the sum of scores for all s ubstances with carcinogenic effects c = specific carcinogenic substance

E c = Emissions of c (lbs/yr)

P c = Unit risk of c RP = Receptor proximity adjustment factor
1700 = normalization factor

As presented in Table 1, the cancer prioritizati on score was 26 using the emissions and potency procedure. Hexavalent chromium, benzene, and arsenic emissions contributed most significantly to the cancer prioritization score.

Noncancer Prioritization Score The prioritization score for acute and chroni c non-carcinogenic effect s was calculated as
follows:I:\Project\SPI\SPI_Anders on-12692\permit_application\Prioritiza tion_Appendix_anderson-draft_040607.doc 3 1500 150 or RP P E TS t

t t × × ⎟ ⎠ ⎞ ⎜ ⎝ ⎛

= 

## ∑ (2)

Where:

TS = the sum of scores for all subs tances with non-carcinogenic effects
t = toxic substance

E t

= Emissions of t (lbs/hr)

P t

= Acceptable chronic or acute exposure level of t ( μ g/m 3 ) RP = Receptor proximity adjustment factor
150 = chronic normalization factor
1500 = acute normalization factor

The higher of the two noncancer prioritization scores (acute or chronic) is used for the facility prioritization. As presented in Table 1, the noncancer prioritization score was 20, based on the
chronic effects score. Chlorine and sulfuric ac id emissions contributed most significantly to the noncancer prioritization score.

Because the prioritization score calculated us ing the emissions and potency prioritization procedure was within the range of 10 to 100 fo r carcinogens and noncarci nogens, a more sitespecific prioritization procedure was used as described below.

T HE D ISPERSION A DJUSTMENT P RIORITIZATION P ROCEDURE The next step in the prioritization process is th e dispersion adjustment pr ioritization procedure, which is based on dispersion modeling and stack parameters (release height) in addition to estimated emissions, chemical toxicity, a nd receptor proximity. The calculation of prioritization scores using the dispersion adjustment prioriti zation procedure are described
below.

Cancer Prioritization Score The prioritization score for carcinogenic effects was calculated as follows:

28

, × ⎭ ⎬ ⎫ ⎩ ⎨ ⎧

× × × = 

## ∑ c

h h c h c RP D P E TS (3)

Where:

TS = the sum of scores for all s ubstances with carcinogenic effectsI:\Project\SPI\SPI_Anders on-12692\permit_application\Prioritiza tion_Appendix_anderson-draft_040607.doc 4 c = specific carcinogenic substance

E c,h = Emissions of c (lbs/yr) at h

P c = Unit risk of c h = release height (32 meters)

D h = Dispersion adjustment f actor for h (see Table A-2)

RP h = Receptor proximity adjustment factor for h
28 = normalization factor

As presented in Table 2, the cancer prioritizati on score was 21 using th e dispersion adjustment procedure. Hexavalent chromium, benzene, and arsenic emissions contributed most significantly to the cancer prioritization score.

Noncancer Prioritization Score The prioritization score for acute and chroni c non-carcinogenic effect s was calculated as
follows:

25 5

. 2 , or RP D P E TS h h t

t h t × × × ⎟ ⎠ ⎞ ⎜ ⎝ ⎛

= 

## ∑ (4)

Where:

TS = the sum of scores for all subs tances with non-carcinogenic effects t = specific toxic substance

E t,h = Emissions of t (lbs/hr) at h

P t

= Acceptable chronic or acute exposure level of t ( μ g/m 3 ) h = release height (32 meters)

D h = Dispersion adjustment f actor for h (see Table A-2)

RP h = Receptor proximity adjustment factor for h
2.5 = chronic normalization factor
25 = acute normalization factor

The higher of the two noncancer prioritization scores (acute or chronic) is used for the facility prioritization. As presented in Table 2, th e noncancer prioritization score was 17, which was based on the chronic effects score. Chlorine and sulfuric acid emi ssions contributed most significantly to the noncancer prioritization score.I:\Project\SPI\SPI_Anders on-12692\permit_application\Prioritiza tion_Appendix_anderson-draft_040607.doc 5 The prioritization score calculated using the di spersion adjustment prio ritization procedure was within the range of 10 to 100 for carcinogens a nd noncarcinogens. As stated previously, the AQMD makes the final decision regarding ranki ng the facility as a high priority under
AB2588.

References

California Air Pollution Control Officers Asso ciation (CAPCOA), 1990, Air Toxics “Hot Spots” Program, Facility Prioritizat ion Guidelines, AB2588 Risk Assessment Committee of the California Air Pollution Control Officers Association, July.
California Air Resources Board (CARB), 2006, Hotspots Analysis and Reporting Program (HARP), Version 1.3, October.

Office of Environmental Health Hazard Asse ssment (OEHHA), 2003, Air Toxics Hot Spots Risk Assessment Guidelines, The Air Toxics Hot Spots Guidance Manual for Preparation of Health Risk Assessments, California Environmental Protection Agency, August

# APPENDIX D