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 36th Avenue W, Suite 101 

Lynnwood, Washington 98036 

(425) 921-4000 

May, 2007 

Project No. 012692 
TABLE OF CONTENTS 

Page 

1.0 INTRODUCTION.............................................................................................................1 

1.1 ORGANIZATION ......................................................................................................2 

1.2 SUMMARY OF FINDINGS .........................................................................................2 

2.0 PROJECT DESCRIPTION ...............................................................................................4 

2.1 PHYSICAL DESCRIPTION .........................................................................................4 

2.2 FUEL SUPPLY..........................................................................................................5 

2.3 POLLUTANT EMISSION RATES ................................................................................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 FEDERAL REGULATIONS.........................................................................................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 STATE AND LOCAL EMISSION REGULATIONS........................................................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 MODEL SELECTION...............................................................................................14 

4.2 MODELING PROCEDURES......................................................................................15 

4.2.1 Model Setup and Application..................................................................15 

4.2.2 Averaging Periods ...................................................................................15 

4.2.3 Chemical Transformations ......................................................................15 

4.3 ELEVATION DATA AND RECEPTOR NETWORK ......................................................16 

4.4 METEOROLOGICAL DATA .....................................................................................16 

4.5 EMISSION SOURCE RELEASE PARAMETERS ..........................................................17 

4.6 ANALYSIS RESULTS..............................................................................................17 

4.7 STARTUP ANALYSIS..............................................................................................18 

5.0 CLASS I AIR QUALITY RELATED VALUES ANALYSIS.......................................20 

5.1 MODEL SELECTION...............................................................................................20 

5.2 MODELING PROCEDURES......................................................................................21 

5.2.1 Characterization of Emissions.................................................................21 

5.2.2 Averaging Periods ...................................................................................22 
TABLE OF CONTENTS 

(Continued) 

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5.2.3 Chemical Transformations ......................................................................22 

5.3 RECEPTOR NETWORK ...........................................................................................22 

5.4 METEOROLOGICAL DATA .....................................................................................23 

5.5 AQRV CALCULATION PROCEDURES ....................................................................24 

5.6 BASELINE AQRV DATA.......................................................................................26 

5.7 ANALYSIS RESULTS..............................................................................................26 

TABLES 

Table 2-1 Cogeneration Unit Criteria 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 Criteria Pollutant Concentrations 

Table 5-1 Class I Area Distances from Proposed Project Site 

Table 5-2 Speciated Emission Rates for AQRV Analysis 

Table 5-3 Predicted Class I Area Criteria Pollutant Concentrations 

Table 5-4 Predicted Class I Area Deposition Fluxes 

Table 5-5 Ten Days with Maximum Predicted Class I Area Extinction Change 

Table 5-6 Maximum Predicted Extinction 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 Municipal Airport, Jan. 1995 to Dec. 1999 

Figure 4-3 Source and Significant Structure Locations 

Figure 4-4 Maximum Predicted 1-Hour Average CO Concentrations 

Figure 4-5 Maximum Predicted 8-Hour Average CO Concentrations 

Figure 4-6 Maximum Predicted 3-Hour Average SO2 Concentrations 

Figure 4-7 Maximum Predicted 24-Hour Average SO2 Concentrations 

Figure 4-8 Maximum Predicted Annual Average SO2 Concentrations 

Figure 4-9 Maximum Predicted 24-Hour Average PM10 Concentrations 

Figure 4-10 Maximum Predicted Annual Average PM10 Concentrations 

Figure 4-11 Maximum Predicted Annual Average NO2 Concentrations 

Figure 4-12 Maximum Predicted Net Annual Average NO2 Concentrations 
TABLE OF CONTENTS 

(Continued) 

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Figure 5-1 CALPUFF Domain and 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 NO2 Concentrations 

Figure 5-6 Maximum Predicted 24-Hour Average PM10 Concentrations 

Figure 5-7 Maximum Predicted Annual Average PM10 Concentrations 

Figure 5-8 Maximum Predicted 3-Hour Average SO2 Concentrations 

Figure 5-9 Maximum Predicted 24-Hour Average SO2 Concentrations 

Figure 5-10 Maximum Predicted Annual Average SO2 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 Project 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) 
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BIOMASS-FIRED COGENERATION PROJECT 

PREVENTION OF SIGNIFICANT DETERIORATION AND 

AUTHORITY TO CONSTRUCT PERMIT APPLICATION 

Sierra Pacific Industries Lumber Manufacturing Facility 

Anderson, California 

1.0 INTRODUCTION 

Sierra Pacific Industries (SPI) proposes to construct and operate a cogeneration unit at an 

existing lumber manufacturing facility located in Anderson, California. The boiler associated 

with the proposed cogeneration unit will burn biomass fuel (i.e., non-treated wood and 

agricultural crop residues, as well as urban wood-waste and other fuels subject to district 

approval) generated by the facility, regional lumber 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 electricity for on site use as well as for sale to the grid. Although 

no steam sales agreements are currently in place, 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 uninterrupted steam production. 

Because the existing lumber manufacturing facility is a major stationary source of emissions, 

and the proposed cogeneration unit is considered 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 Anderson 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 Consultants, Inc. (Geomatrix) 

to prepare a combined PSD/ATC application to be submitted to the AQMD on its behalf. 
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1.1 ORGANIZATION

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 Available 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 quality related values in regional Class I 

areas. 

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

1.2 SUMMARY OF FINDINGS

Geomatrix conducted an air quality impact assessment of the project using five years of hourly 

meteorological surface data from Redding Municipal Airport from 1995 to 1999. The analysis 

indicates that predicted ambient air pollutant concentrations attributable to the project will not 

cause or contribute to an exceedance of the National or California Ambient Air Quality 

Standards (NAAQS or CAAQS) established to protect human health and welfare, nor increase 

the ambient concentrations in excess of the PSD increments established to prevent deterioration 

of the area’s existing air quality. 

Geomatrix also assessed air quality related values (AQRVs) including regional haze, nitrogen 

and sulfur deposition and the effects of primary 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 visual range. These analyses indicate: 

• Predicted pollutant concentrations in Class I areas attributable to the project are less 

than the significant impact levels proposed 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 established by the National Park Service (NPS). 
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• Secondary aerosols predicted to be formed by emissions from the project operating 

at full capacity do not have the potential to degrade regional visibility in regional 

Class I areas. 
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2.0 PROJECT DESCRIPTION 

2.1 PHYSICAL DESCRIPTION

Sierra Pacific Industries (SPI) is a family-owned wood products company based in Redding, 

California. SPI currently operates an existing lumber manufacturing facility in Anderson, 

California. SPI intends to construct a new cogeneration unit at the Anderson facility that would 

burn biomass fuels in a boiler to produce steam that would be used to generate electricity and to 

heat existing lumber dry kilns at the facility. 

The cogeneration unit will consist of a biomass-fired water-wall boiler 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 turbine generator will generate up to 23 megawatts 

(MW) of electricity. Approximately 7 MW will 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 controlled extraction and used to heat the dry kilns. 

The final design of the biomass-fired boiler has not 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 million 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 percent greater than the annual average). 

The boiler will be equipped with two natural gas burners, each with a maximum rated heat 

input of 62.5 MMBtu/hr, for start up and flame stabilization. The cogeneration unit design will 

incorporate a selective non-catalytic reduction (SNCR) system to reduce emissions of oxides of 

nitrogen (NOx), as well as a multiclone and electrostatic precipitator (ESP) to control emissions 

of particulate matter (PM/PM10). A closed-loop two-cell cooling tower will be used to dispose 

of waste heat from the steam turbine. A schematic flow diagram for the cogeneration facility is 

presented in Figure 2-1. 

The proposed cogeneration unit will be located near the existing biomass-fired boiler at SPI’s 

Anderson lumber manufacturing facility. The existing facility is bordered on the northeast by 

the Sacramento River, on the northwest by a private parcel, on the southwest by Union Pacific 

Railroad tracks and SR273, and on the southeast by private parcels. The general vicinity of the 

facility and the modeling domain are shown in Figure 2-2. 
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2.2 FUEL SUPPLY

Fuel for the cogeneration unit will come from the 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 and timberlands totals 400,000 bone 

dry tons (BDT) per year. In addition, there are 50,000 BDT of agricultural and urban wood 

wastes available to SPI annually. The new boiler 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 continuously as is practicable. 

The Anderson facility currently produces approximately 160,000 BDT of wood wastes per year 

of which 60,000 BDT are consumed by the existing 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 facility, while the balance (96,000 BDT) will 

transported by truck from other SPI sources. An additional 18 truck trips per day are expected 

to be needed to deliver the additional fuel to the facility. 

The installation of the boiler will not increase emissions from any existing emission units at the 

Anderson mill. There have been no contemporaneous modifications at the Anderson mill. 

2.3 POLLUTANT EMISSION RATES

This section addresses pollutant emission rates associated with the project. The proposed boiler 

will emit NOx, carbon monoxide (CO), particulate matter smaller than ten microns (PM10), PM, 

sulfur dioxide (SO2), 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 pollutant emission rates from the cogeneration unit 

during normal operation. Boiler emission factors for NOx, CO, PM10, and VOCs were based on 

guarantees from the boiler and control device manufacturers. The SO2 emission factor is based 

on source test information from the existing biomass-fired boiler. Additional material handling 

operations associated with the project will be enclosed, and, as a result, fugitive dust emissions 

associated with the project are expected to be negligible. 
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The cooling tower will emit only PM10. 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 (gpm), and a conservative total dissolved solids 

(TDS) value of 725 milligrams per liter (mg/l), the PM10 emission rate from the cooling towers 

is 1.1 ton per year (TPY). 

Consistent with the BACT analysis in Appendix B and AQMD Rule 3:26(c)(1), SPI proposes 

the following emission limits: 

• NOx – 115 ppm (3-hour average) and 0.13 lb/MMBtu (30-day average) 

• CO – 0.6 lb/MMBtu (3-hour average) 

• PM10 – 0.01 gr/dscf (3-hour average) including filterable and condensable components 

SPI does not believe limits are warranted for SO2 or VOC emissions from the cogeneration unit 

or for PM10 emissions from the cooling tower because the emission rates are so low. 

Table 2-2 summarizes the hourly, daily, and annual emission increases associated with the 

project, including the reduction in emission rates as a result of never operating the existing 

biomass-fired boiler concurrent with the proposed unit (other than some overlap during startup 

and shutdown to ensure continuous steam production), 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 the 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 criteria pollutant emission rates is provided as Appendix B. 

2.3.2 Startup Emissions 

SPI typically shuts down its boilers 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 pipeline natural gas. Firing at full capacity, these burners will 

provide only thirty percent of rated boiler heat input and will initially be the sole source of heat 

input to the boiler during startup. 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 rate will be reduced to maintain a steady heat 
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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 needed. 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 reaches is design operating temperature. 

During the startup period, CO emission rates will exceed those experienced under normal 

operation. Unlike normal operation, it is very difficult for the boiler manufacturer to estimate 

startup CO emission rates, which vary continuously during the startup process. Because 

exhaust levels of oxygen are high and CO2 levels are low during startup, SPI proposes that the 

startup CO emission rate limit be a mass-per-unit-time limit rather than a concentration 

corrected to 12 percent CO2 as is commonly done for normal operation limits. SPI proposes a 

startup and shutdown CO emission rate limit of 400 lb/hr averaged 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, and to experience hourly 

average CO emission rates similar to those of startup. SPI proposes that the boiler be subject to 

the startup CO emission rate limits during shutdown. 

A modeling analysis was performed to demonstrate that the proposed startup/shutdown 

emission limits will comply with the CO ambient air quality standards. This analysis is 

documented in Chapter 4. 

2.3.3 Toxic Air Contaminants 

Most TAC emission factors for wood-residue fuels were based on source tests used to develop 

emission factors for AP-42 Section 1.6. However, 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 calculated using the subset of source tests in which wood-fired boilers 

were controlled by ESPs. For the hydrogen chloride (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 emission factor was calculated using 

biomass-fired boiler source tests from AP-42 source test data, after excluding source tests that 

included values based on the detection limit. The ammonia (NH3) 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 emissions are a consequence of operating an SNCR system to 

reduce boiler NOx emissions to 0.13 lbs/MMBtu. 
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In cases where no ESP-controlled source test results were available for a particular TAC, 

results associated with other particulate control equipment were used. Source test data from 

units not employing particulate controls or not reporting any control equipment were included 

where no other source test data were available. Table 2-3 presents the TAC emission factors 

and emission rates associated with the biomass-fired boiler. The cooling tower is not expected 

to emit any TACs. 
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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 regulations 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 PM10 standards. 

3.1 FEDERAL REGULATIONS

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 the 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 NOx, CO, and PM10 emissions exceed the significant emission rates (SERs), 

indicating that PSD review is required for each of these pollutants. 

PSD regulations require a BACT analysis for all air pollutants emitted by a project that exceed 

the SERs (in this case, NOx, CO, and PM10). The BACT analysis evaluates the energy, 

environmental, economic, and other costs associated with each technology, and weighs those 

costs against the reduced emissions the technology would provide. BACT analyses are 

presented in Appendix B for the biomass-fired boiler and the cooling tower. 

In addition, modeling analyses are required to demonstrate compliance with the applicable 

NAAQS and PSD increments locally, and in national parks and wilderness areas. Local and 

regional air quality modeling analyses are provided in Chapters 4 and 5, respectively. 

3.1.2 Acid Rain Program 

The EPA’s Acid Rain Program, Title IV of the Clean Air Act, is intended to achieve significant 

environmental and public health benefits through reductions in emissions of SO2 and NOx, the 

primary causes of acid rain. The biomass-fired boiler proposed by SPI will not be subject to 

the requirements of the Acid Rain Program because it is a cogeneration unit with an electrical 

generating capacity below the program 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 biomass-fired cogeneration unit is not subject to 

the program if it sells no more than one third of its potential annual electrical output capacity or 
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if it sells less than 219,000 megawatt (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 kilns at the existing lumber 

manufacturing facility. Thus, the steam will be “used twice.” Although SPI expects to sell 

more than one-third of the boiler’s annual potential electrical output capacity, the boiler will be 

an unaffected source because SPI expects to sell no more than 219,000 MWe-hrs of electricity 

annually. Due to the proposed boiler’s cogeneration 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 source 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 required 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 Standards (NSPS) usually represent a minimum level 

of control that is required of a new source. NSPS Subpart Db addresses emissions from boilers 

that have a heat input of greater 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/MMBtu 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 exhaust opacity to be 20 percent or less (6-minute average), except for 

one 6-minute period per hour, which 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 PM10 emission rates proposed 

for the cogeneration unit are less than those allowed by NSPS. 

The cogeneration unit will burn natural gas during startup. Subpart Db prescribes SO2 and NOx

limits on boilers that fire fossil fuels under certain conditions. The SO2 limits do not apply to 

boilers that combust natural gas. The NOx limits in Subpart Db do not apply to boilers that 
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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 SO2 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 pollutants (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 only sources of HAPs at the facility. The two 

would not operate concurrently other than some overlap during startup and shutdown, and the 

proposed boiler has a greater firing rate, therefore the annual HAP PTE of the proposed boiler 

constitutes the annual facility-wide HAP PTE, which is summarized in Table 3-1. The HAP 

emitted in greatest quantity will be hydrogen chloride at an annual rate 5.43 TPY. SPI 

anticipates that facility-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 STATE AND LOCAL EMISSION REGULATIONS

3.2.1 Authority to Construct Permits 

Shasta County AQMD Rule 2, Part 100 requires new or modified stationary sources to obtain 

an ATC air quality permit. The ATC permit application must provide a description of the 

facility, an inventory of pollutant emissions, and proposed control systems 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 pollutant with the potential for requiring BACT 

are listed in Table 2-2, along with the daily PTE and regulatory threshold. As shown in the 

table, BACT is required for reactive organic compounds (ROG), NOx, SO2, PM10, CO, and 

beryllium. BACT analyses are presented in Appendix B for the biomass-fired boiler and the 

cooling tower. 
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As stated in AQMD Rule 2, Part 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 cause or contribute to violations of ambient air 

quality standards. This application 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 standard cubic foot (gr/dscf), while PM10 is limited to 

0.05 gr/dscf, and combustion PM is limited to 0.10 gr/dscf. SO2 emissions are limited to 

200 parts per million (ppm), and NOx emissions are limited to 300 ppm for solid fuels, and 

250 ppm for gaseous fuels. Opacity is limited 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 facilities to which the act applies to inventory and report air toxic emissions from 

stationary sources. TAC emissions associated with the current project, calculated as described 

in Section 2.3.3, are presented in Appendix C along with prioritization scores. 

3.2.4 California Environmental Quality Act (CEQA) 

All ATCs are required to undergo a preliminary 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 California 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 standards to achieve “no net increase” in emissions (i.e., offsets) of 

those pollutants and their precursors. Although Shasta County has been designated a 

nonattainment area with respect to the State ozone and PM10 ambient air quality standards, it 

has further been classified as having “moderate air 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 attainment 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 allowable emissions will not cause or contribute to 

violation of any ambient air quality standard or increment. This is typically accomplished 

using air quality dispersion modeling to predict ambient concentrations. This chapter discusses 

the methodology used to develop near-field modeling used to predict pollutant concentrations 

attributable to project emissions in the Class II areas surrounding the proposed facility. Class II 

areas are essentially the entire country save for 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. Class II areas have been 

deemed able to accommodate normal, well-managed industrial growth, and, therefore, have 

higher PSD increments.1

4.1 MODEL SELECTION

Geomatrix reviewed regulatory modeling techniques to select the most appropriate air quality 

dispersion model to simulate dispersion of air pollutants emitted by the proposed project for a 

near-field air quality impact analysis. The selection 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 portions of the modeling domain, is relatively flat, however, 

intermediate and complex terrain exists in the southwest portion of the domain. The heights of 

proposed and existing structures, and the proposed cogeneration unit stack height, suggests that 

there is the potential for exhaust 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), superseding the ISCST3 air dispersion model. As a 

result, AERMOD is currently the model recommended 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 the 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. Additionally, the modeling domains and source 

configurations suggested the potential for exhaust plume downwash and plume impacts on 

intermediate and complex terrain. 

4.2 MODELING PROCEDURES

AERMOD was applied to both criteria pollutants and TACs using the regulatory defaults in 

addition to the options and data discussed in this section. Electronic versions 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 AERMOD (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 surrounding the facility. AERMOD 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 agricultural 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 concentrations predicted by the model were averaged over shortterm (1-, 3-, 8-, and 24-hour) and annual averaging periods as required by the applicable 

ambient criteria for each modeled pollutant. 

4.2.3 Chemical Transformations 

Geomatrix assumed that 100 percent of the emitted NOx is converted to NO2. 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 ELEVATION DATA AND RECEPTOR NETWORK

Terrain elevations for receptors and emission sources were prepared using digital elevation 

models (DEMs) developed by the United States Geological Survey (USGS) 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 indicate that some of the receptors used in the simulations were 

located in intermediate or complex terrain (above 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 METEOROLOGICAL DATA

Geomatrix has conducted a survey of available meteorological 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, supplemented by National Weather 

Service (NWS) upper air sounding data from Medford, Oregon. 

According to the Guideline, five years of representative meteorological data are considered 

adequate for dispersion modeling applications. 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 Observations (ISHWO). The airport is located 

approximately 4.5 kilometers (2.8 miles) north-northwest of the facility. A wind rose 

describing the wind speed and wind direction data recorded at the Redding 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 monitoring station at Medford, Oregon, approximately 

215 kilometers (134 miles) north of the facility. 

The meteorological data were processed using the AERMOD meteorological 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 replaces 
I:\Project\SPI\SPI_Anderson-12692\permit_application\SPI_anderson_PSD-final.doc 17 

missing or out-of-range data with missing value flags, and AERMOD treats these periods as 

calms. 

4.5 EMISSION SOURCE RELEASE PARAMETERS

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 represent 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-specific building profiles were prepared for the modeling using the 

EPA’s Building Profile Input Program for the PRIME algorithm (BPIP PRIME). The facility 

layout and building elevations provided by SPI were used to prepare data for BPIP PRIME, 

which provides the necessary input data for AERMOD. Figure 4-3 shows the configuration of 

significant structures, including those of the adjacent lumber manufacturing facility, that were 

used to develop the BPIP PRIME input files, and Table 4-2 presents the heights of the 

significant structures included 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 simulations to reflect downwash effects from 

nearby structures on the boiler stack. A similar analysis indicated that emissions from the 

cooling towers would also be subject to downwash effects, and the appropriate BPIP PRIME 

output was included in the simulations for that source as well. 

4.6 ANALYSIS RESULTS

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 applied in the dispersion modeling analysis. 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 de 
I:\Project\SPI\SPI_Anderson-12692\permit_application\SPI_anderson_PSD-final.doc 18 

minimis concentrations and the Significant Impact Levels (SILs) established 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 Table 4-3, none of the predicted concentrations 

exceeded the SILs or the monitoring de minimis concentrations, except NO2 (1.47 μg/m3), 

which exceeded the annual average SIL (1.0 μg/m3). 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 proposed boiler. The results of this simplified, 

conservative analysis were compared to the SILs, and maximum concentrations less than the 

SILs indicated that no further analysis was necessary. 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 cogeneration unit as well as non-operation of the 

existing boiler. Because the maximum NO2 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 concentration modeling simulation using the stack 

parameters shown in Table 4-1. At each receptor, the predicted annual average concentration 

attributable to the existing boiler was subtracted from the predicted annual average 

concentration attributable to the proposed cogeneration unit. The net maximum annual average 

NO2 concentration was 0.49 μg/m3

, which is less than the NO2 SIL. Therefore, no further 

analysis to assess compliance with air quality standards or PSD increment is required for any 

criteria pollutant. Figure 4-12 shows the net maximum predicted annual average NO2

concentrations, as well as the location of the maximum predicted concentration receptor. 

4.7 STARTUP ANALYSIS

AERMOD was applied using the methodology described in the previous sections to 

demonstrate that the proposed CO startup emission rate will comply with 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 operate throughout the startup 

process, but the flow will be controlled by dampers to approximately 30 percent of normal 

operation flow (approximately 59,700 actual cubic feet per minute). This resulted 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 process regardless of the fuel mix 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/m3, 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/m3) and 

4.3 ppm (approximately 4,900 μg/m3). 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 concentrations near the facility. 

Using the conservative background concentrations described above, the total predicted 

maximum concentrations (boiler startup emissions plus background) were a 1-hour average of 

10,009 μg/m3

, and an 8-hour average of 5,154 μg/m3. These concentrations are less than the 1-

hour and 8-hour average CO CAAQS of 23,000 and 10,000 μg/m3, respectively (the 

corresponding NAAQS are 40,000 and 10,000 μg/m3

). Based on this analysis, the proposed 

hourly CO emission startup limit of 400 lb/hr will not cause exceedances of the NAAQS or 

CAAQS. 

 

2

 ARB Almanac 2006 – Appendix B: Air Quality Trend Data by Pollutant: Ozone, PM10, PM2.5, CO, NO2, NOX, 

SO2, 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 quality 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 analyses 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 relation 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 allowance 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 concentration predictions were also used to assess Class I 

area increment consumption for pollutants subject to PSD review. 

5.1 MODEL SELECTION

On April 15, 2003, EPA adopted the CALPUFF modeling system as the EPA’s preferred model 

for long-range transport assessments and for evaluating potential impacts to Class I areas by 

including CALPUFF in Appendix A of the Guideline. Features of the CALPUFF modeling 

system include the ability to consider: secondary aerosol formation; gaseous and particle 

deposition; wet and dry deposition processes; complex three-dimensional wind regimes; and 

the effects of humidity on regional visibility. 

Geomatrix used CALMET version 5.53b and CALPUFF version 5.711b; the release date of the 

versions used is December 16, 2005. Although they are not currently the “official” EPA 

versions of CALMET (5.53a) and CALPUFF (5.711a), the December 16, 2005 releases correct 
I:\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 MODELING PROCEDURES

The modeling procedures used for the Class I area analyses followed the recommendations of 

the Interagency Agency Workgroup on Air Quality Modeling (IWAQM) and the FLM Air 

Quality Related Values Workgroup (FLAG), outlined in the FLAG Phase I Report (December 

2000). EPA endorsed these procedures in advance 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 Guideline model. Future more detailed guidance 

was obtained from the United States Forest Service (Suraj Ahuja) as outlined in the 

“CALPUFF Reviewer’s Guide4

” (hereafter referred to as the “Reviewer’s Guide”). Electronic 

versions of the modeling files are included on a compact disk in Appendix D 

5.2.1 Characterization of Emissions 

Data characterizing the chemical composition and size distribution of the PM10 emitted are 

needed for the regional haze assessment using the CALPUFF modeling system. PM10 was 

speciated into components as shown in Table 5-2 using AP-42 and the EPA’s SPECIATE 

database (version 3.2). AP-42 was used to calculate how PM10 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 suggested 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 sources for use in source apportionment studies. 

This information was used to estimate the fractions 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 characteristics 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 National Park Service. September 2005. 5

 PES, 2004. Recommendations for the Update and Improvement 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 SO2, 24-hour and annual average PM10, and annual 

average NOx Class I SILs. Predicted extinction coefficients and total nitrogen and sulfur 

deposition fluxes were calculated as 24-hour and annual averages, respectively. In all instances, 

comparisons with regulatory criteria were based on the maximum predicted values over the 

three year simulation for each averaging period. 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 NOx chemistry in CALPUFF depends on the ambient ammonia concentration to establish 

the equilibrium between gaseous nitric acid and ammonium nitrate. However, ambient 

ammonia concentrations are not explicitly simulated 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 weather. Since land use in the model domain is 

mixed, a 10 ppb background ammonia concentration was conservatively used for the AQRV 

studies. Such a high background is considered conservative because it ensures the conversion 

of NOx to ammonium nitrate is not limited by a lack of ammonia for the range of NOx 

concentrations predicted in this study. 

Reaction rates in the CALPUFF chemistry algorithms are also influenced by background ozone 

concentrations. A conservative background 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 during 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 was 78 ppb during 2003 through 2005. 

5.3 RECEPTOR NETWORK

The CALPUFF dispersion model simulations assessed AQRVs at discrete receptors obtained 

from the National Park Service. Figure 5-2 shows these receptor locations within each Class I 

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

 

6 http://www2.nature.nps.gov/air/Maps/Receptors/index.cfm
I:\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 the spatial variation of the calculated parameters 

throughout the modeling domain. These plots were used for diagnostic purposes, as well as to 

develop the figures presented in this permit application. Comparisons with AQRV criteria 

were always based on the discrete receptor locations and elevations. 

5.4 METEOROLOGICAL DATA

Geomatrix obtained meteorological data sets from EPA based on diagnostic numerical 

simulations of continental U.S. weather with 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 Best Available Retrofit Technology review as part for the EPA 

Regional Haze Rule. 

CALMET, the meteorological preprocessor component of the CALPUFF system, was used to 

combine the MM5 simulation data, surface observations, terrain elevations, and land use data 

into the format required by the dispersion modeling component CALPUFF. In addition to 

specifying the three-dimensional wind field, 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 geometrically 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 USGS 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 Atmospheric Research dataset ds472.0. Twenty-two of 

these stations had a data recovery of greater 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 meteorological dataset. 
I:\Project\SPI\SPI_Anderson-12692\permit_application\SPI_anderson_PSD-final.doc 24 

• Hourly precipitation data were obtained for 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 the NOAA Forecast Service Laboratory and 

processed with the CALMET utility READ62. 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-dimensional 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. Specifically, 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 treatment of over water conditions used the 

same routines as over land (JWAT1=JWAT2=100), except the variables 

characterizing the surface are appropriate for 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 and plotting the meteorological fields with the 

CALDESK software package. Wind vector plots were examined for different times of year, 

different times of the data and for all ten vertical levels. 

5.5 AQRV CALCULATION PROCEDURES

The CALPUFF modeling system was used to predict criteria pollutant concentrations, total 

deposition fluxes, and light extinction coefficients attributable to project emissions in regional 

Class I areas. These parameters were calculated from CALPUFF output files using the postprocessor program CALPOST. 

Predictions of NOx, SO2, and PM10 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. PM10 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 various conversion and deposition processes in the 
I:\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 converted to kilograms per hectare per year. 

The potential for project emissions to contribute to regional haze was predicted using 24-hour 

average extinction coefficients as a measure of visibility degradation. 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 primarily due to light extinction caused 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 that a five percent change in extinction be 

used to indicate a “just perceptible” change to a landscape. Extinction coefficients were 

calculated from the CALPUFF output files using the post-processing program CALPOST. 

CALPOST calculates extinction coefficients from concentrations of aerosols directly emitted, 

sulfate concentrations, nitrate concentrations, and relative humidity. 

The general equation applied in CALPOST divides the extinction coefficient into two 

components as follows: 

bext = bSN f(RH) + bdry (1) 

where bext is the extinction coefficient (inverse megameters or Mm-1), f(RH) is the relative 

humidity adjustment factor, bSN is the sulfate and nitrate or hygroscopic portion of the 

extinction coefficient (Mm-1), and bdry is the non-hygroscopic portion of the extinction 

coefficient (Mm-1). The hygroscopic portions of the extinction budget are calculated from the 

sulfate and nitrate concentrations predicted by CALPUFF according to: 

bSN = 3[(NH4)2SO4 + NH4NO3] (2) 

where the sulfate and nitrate concentrations have units μg/m3

 and are converted for the change 

in molecular weight due to the assumed chemical form of the aerosol. The portion of the 

extinction coefficient that does not vary with humidity is calculated from: 

bdry = 4[OC] + 1[Crustal Mass] + 0.6[Coarse Mass] + 10[EC] + bRay (3) 

where [OC] is the organic carbon portion of the PM2.5, [Crustal Mass] is the crustal portion 

(PM2.5 that cannot be classified as organic or elemental carbon) of the PM2.5, [Coarse Mass] is 
I:\Project\SPI\SPI_Anderson-12692\permit_application\SPI_anderson_PSD-final.doc 26 

the portion of the mass between PM2.5 and PM10, [EC] is the elemental carbon (soot) portion of 

PM10, and bRay is extinction due to Rayleigh scattering assumed to be 10 Mm-1. Concentrations 

in Equation 3 also have units of μg/m3

. 

5.6 BASELINE AQRV DATA

For background visibility at all Class I areas of interest, the FLAG western 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 invoked by selecting CALPOST 

Method 6 (MVISBK=6) during post-processing of the CALPUFF simulation and assigning the 

sulfate concentration to 0.2 μg/m3 and the fine crustal mass portion to 4.5 μg/m3. The 

hygroscopic portion of extinction was adjusted for relative humidity using the seasonal factors 

(f(RH)) provided by FLAG for each Class I area. 

5.7 ANALYSIS RESULTS

The CALPUFF modeling system was used to predict concentrations of NO2, SO2, and PM10 in 

regional Class I areas. The CALPUFF simulations used the emission rates presented in Table 

5-2, and the source release parameters and building downwash parameters calculated by BPIP 

PRIME as described in Section 4.4. As for the Class II analysis, the preliminary analysis 

included emissions only from the proposed cogeneration unit, and did not account for the 

decreased impacts related to non-operation of the existing boiler. The results of this simplified, 

conservative analysis were compared to the various regulatory thresholds and criteria to 

determine whether a more rigorous net impact analysis was necessary. 

Table 5-3 summarizes the predicted maximum concentrations and compares them to the Class I 

SILs and the Class I PSD increments. At this point, there are two sets of Class I SILs, those 

proposed by EPA and those recommended by the FLMs. These proposed and recommended 

SILs were obtained from the Federal Register, Vol. 61, No. 143, p. 38292, July 23, 1996. As 

shown in Table 5-3, the CALPUFF simulations indicate neither the SILs nor the increments 

will be exceeded. 

Figures 5-5 through 5-10 present the spatial variation across the simulation domain of the 

predicted maximum concentrations over the applicable averaging periods for NO2, SO2, and 

PM10 emissions attributable to the project. These 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 impacts 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 (DATs) 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 consideration 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. Figures 5-11 and 5-12 show the spatial variation of 

the predicted nitrogen and sulfur deposition fluxes attributable 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 extinction for each Class I receptor. The CALPUFF 

modeling system was used to predict both the extinction coefficient attributable to emissions 

from the project as well as the background extinction 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 established by the FLMs. The higher changes to 

extinction are predicted at receptors within the Yolla Bolly-Middle Eel Wilderness. Figure 5-13 

presents a contour plot of the predicted extinction 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 wilderness 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.htm
I:\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. 
TABLES 
TABLE 2-1 

PROPOSED COGENERATION UNIT EMISSIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Emission Rate2

Pollutant1

Emission Factor 

(lb/MMBtu) (lb/hr) (TPY) 

NOx 0.13 50.6 202 

CO 0.60 234 931 

SO2 0.016 6.23 24.8 

PM10 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 NOx, CO, PM10, and VOC/ROC emission factors are based on vendor guarantees, while the SO2 emission 

factor is based on a source test conducted on the existing boiler at the facility. The sulfuric acid (H2SO4) 

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 2-2 

PROJECT TOTAL EMISSIONS OF CRITERIA AND OTHER REGULATED POLLUTA

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Hourly Emission Rate1

(lb/hr) 

24-Hour Emission Rate2

(lb/day) 

Annual Emission Rate4

(TPY) 

Pollutant Cogen CT Total Cogen CT Total 

AQMD

BACT 

Thresh.3

(lb/day) 

Over 

BACT 

Thresh? Cogen CT Total Existin

NOx 50.6 -- 50.6 1,160 -- 1,573 25.0 Yes 202 -- 202 77.2 

CO 234 -- 234 5,355 -- 5,355 500.0 Yes 931 -- 931 128 

SO2 6.23 -- 6.23 143 -- 136 80.0 Yes 24.8 -- 24.8 1.28 

PM/PM10 7.40 0.251 7.65 170 6.02 176 80.0 Yes 29.5 1.1 30.6 3.69 

VOC/ROG 5.06 -- 5.06 116 -- 116 25.0 Yes 20.2 -- 20.2 7.14 

Sulfuric Acid 0.780 -- 0.780 18 -- 18 35.0 No 3.11 -- 3.11 1.10 

Lead 0.0193 -- 0.0193 0.44 -- 0.44 3.2 No 0.0768 -- 0.0768 0.0272 

Asbestos -- -- -- -- -- -- 0.03 No -- -- -- -- 

Beryllium 0.000604 -- 0.000604 0.014 -- 0.014 0.002 Yes 0.00241 -- 0.00241 0.00085

Mercury 0.000162 -- 0.000162 0.0037 -- 0.0037 0.5 No 0.000645 -- 0.000645 0.00022

Vinyl Chloride 0.00717 -- 0.00717 0.16 -- 0.16 5.0 No 0.0285 -- 0.0285 0.0101 

Fluorides -- -- -- -- -- -- 15.0 No -- -- -- -- 

TRS/H2S/RS6 -- -- -- -- -- -- 50.0 No -- -- -- -- 

1 Cogeneration unit hourly emission rates are based on a maximum hourly heat input of 389.2 MMBtu/hr 2 Cogeneration unit hourly emission rates are based on a maximum 24-hour average heat input of 371.9 MMBtu/hr 3 From Sierra County AQMD Rule 2:1, Part 301. 4 Cogeneration unit hourly emission rates are based on a maximum hourly heat input of 354.2 MMBtu/hr. Net annual emissions are to

existing. 

5 PSD SER = Prevention of Significant Deterioration Significant Emission Rate; from EPA’s New Source Review Workshop Manual, 

and New Source Review (NSR) Program Transitional Guidance Memorandum, issued by John S. Seitz of EPA on March 11, 1991. 

6 TRS = Total Reduced Sulfur compounds, H2S = Hydrogen Sulfide, and RS = Reduced Sulfur compounds; the PSD SER only applies 
TABLE 2-3 

COGENERATION UNIT TOXIC AIR CONTAMINANT EMISSION RATES 

SPI Lumber Manufacturing Facility 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 0.0000217 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, hexavalent4 18540-29-9 1.75E-07 0.0000683 0.00156 0.544 
TABLE 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 0.00000237 0.000822 

Dibenzo(a,h)anthracene 53-70-3 2.35E-09 0.000000915 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 

Methanol5 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 0.844 293 
TABLE 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 (N2O) 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 0.361 126 
TABLE 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 POLLUTANT EMISSION RATES 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

All emission rates are in tons per year (TPY) 

Compound CAS No. Emission Rate Compound CAS No. Emission Rate

Acetaldehyde 75-07-0 0.254 Formaldehyde 50-00-0 2.66

Acetophenone 98-86-2 5.00E-06 Hydrogen chloride 7647-01-0 5.43

Acrolein 107-02-8 0.0489 Lead 7439-92-1 0.0768

Antimony 7440-36-0 0.0355 Manganese 7439-96-5 0.152

Arsenic 7440-38-2 0.0087 Mercury 7439-97-6 0.000645

Benzene 71-43-2 1.15 Methanol 67-56-1 1.288

Beryllium 7440-41-7 0.00241 Naphthalene 91-20-3 0.147

Bis(2-ethylhexyl)phthalate 117-81-7 7.21E-05 Nickel 7440-02-0 0.00392

Bromomethane 74-83-9 0.0434 4-Nitrophenol 100-02-7 0.000266

2-Butanone (MEK) 78-93-3 0.0084 Pentachlorophenol 87-86-5 3.52E-05

Cadmium 7440-43-9 0.00450 Phenol 108-95-2 0.0195

Carbon Tetrachloride 56-23-5 0.0704 Phosphorus 7723-14-0 0.0549

Chlorine 7782-50-5 1.23 Propionaldehyde 123-38-6 0.095

Chlorobenzene 108-90-7 0.0515 Selenium 7782-49-2 0.00270

Chloroform 67-66-3 0.0427 Styrene 2.89

Chloromethane 74-87-3 0.0358 TCDD-Total 1746-01-6 3.17E-07

Chromium, trivalent 7440-47-3 0.00238 Tetrachloroethene 127-18-4 0.0593

Cobalt 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-Trichlorophenol 88-06-2 1.76E-05

1,2-Dichloropropane 78-87-5 0.0517 Vinyl Chloride 75-01-4 0.0285

2,4-Dinitrophenol 51-28-5 0.000145 Xylene 1330-20-7 0.0380

Ethylbenzene 100-41-4 0.0486 Total HAPs 16.7

 Maximum Ind. HAP 5.43
TABLE 3-2 

AIR POLLUTANT EMISSION OFFSETS 

SPI Lumber Manufacturing Facility 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 

NOx 77.2 202 124 193 

SO2 1.28 24.8 23.5 --- 

PM/PM10 3.69 30.6 26.9 226 

VOC 7.14 20.2 13.0 159 
TABLE 4-1 

POINT SOURCE RELEASE PARAMETERS 

SPI Lumber Manufacturing Facility 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 91 
TABLE 4-2 

STRUCTURE HEIGHTS 

SPI Lumber Manufacturing Facility 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 4.88 
TABLE 4-3 

MAXIMUM PREDICTED CRITERIA POLLUTANT CONCENTRATIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Concentrations are in micrograms per cubic meter (μg/m3) 

Pollutant 

Averaging 

Period 

Maximum 

Predicted SIL1

 Over SIL? 

Monitoring 

de Minimis3

Over de 

Minimis? 

NO2 Annual 1.47/0.492 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 PM10 Annual 0.22 1 No --- ---

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

SO2 24-Hour 1.08 5 No 13 No 

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 NO2 concentration attributable to the new cogeneration unit alone was 

1.47 μg/m3. When the existing annual average NO2 concentrations attributable to the existing boiler are 

subtracted from those concentrations on a matched time-period and receptor basis, the net maximum annual 

average NO2 concentration increase is 0.49 μg/m3

. NO2 was assumed to be 100 percent of the emitted NOx

based on guidance in Section 6.2.3 of the EPA’s Guideline 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 Facility 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 57 
TABLE 5-2 

SPECIATED EMISSION RATES FOR AQRV ANALYSIS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Emission rates in pounds per hour (lb/hr) 

Cogeneration 

Unit1

Species 24-hour Average 

Cooling 

Towers2

SO2 5.95 0.00 

NOx 48.35 0.00 

PM103 7.07 0.141 

Coarse Mass 0.88 0.00 

Fine Sulfate (as SO4) 0.36 0.00 

Fine Nitrate (as NO3) 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 PM10 speciated using a revision to SPECIATE 3.2 Profile # 22008 for Hogged Fuel Boiler/Stoker Boiler. 

PM10 is assumed to be 87.5% PM2.5 based on AP-42 Section 1.6 (July, 2001). The SO2 emission rates from the 

Class II analysis was not reduced by the equivalent amount fine sulfate present in PM10. PM10 is the sum of 

coarse mass and the PM2.5 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 PM10 emissions were assumed to be comprised entirely of the fine fraction (i.e., 100% PM2.5). 

3 PM10 is speciated into Fine Mass (particulate matter less than 2.5 micrometers [μm]) and Coarse Mass 

(particulate matter between 2.5 and 10 μm). Fine Mass is further speciated into Sulfate, Nitrate, 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 Facility Cogeneration Project 

Anderson, California 

Concentrations in micrograms per cubic meter (μg/m3) 

Maximum Predicted Concentration 

NO2

1

 PM10 SO2

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 SIL2 0.1 0.3 0.2 1 0.2 0.1 

FLM Recommended SIL2 0.03 0.27 0.08 0.48 0.07 0.03 

Class I Area PSD Increment3 2.5 8 4 25 5 2 

1 NOx was conservatively assumed to be 100 percent converted to NO2, 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 Increment; from 40 CFR 52.21(c) 
TABLE 5-4 

PREDICTED CLASS I AREA DEPOSITION FLUXES 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

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

Class I Area of Interest Nitrogen 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 DAT1 0.005 0.005 

1 DAT = Decision Analysis Threshold; from 
TABLE 5-5 

TEN DAYS WITH MAXIMUM PREDICTED CLASS I AREA EXTINCTION CHANGE 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Extinction coefficient in inverse megameters (1/Mm) 

bext1 bext by Comp

Class I Area Date Project2 Bckgrnd3 Total 

Change

(%) f(RH) SO4 NO3 OC E

Yolla Bolly-Middle Eel WA 11/23/02 0.47 16.30 16.77 2.88 3.00 0.023 0.398 0.022 0.Yolla Bolly-Middle Eel WA 12/03/02 0.42 16.78 17.20 2.47 3.80 0.031 0.355 0.013 0.Yolla Bolly-Middle Eel WA 01/28/02 0.34 16.78 17.12 2.02 3.80 0.025 0.291 0.010 0.Yolla Bolly-Middle Eel WA 04/03/02 0.31 15.94 16.25 1.97 2.40 0.021 0.247 0.021 0.Yolla Bolly-Middle Eel WA 01/20/03 0.27 16.78 17.05 1.63 3.80 0.029 0.227 0.008 0.Yolla Bolly-Middle Eel WA 01/19/03 0.26 16.78 17.04 1.57 3.80 0.025 0.223 0.007 0.Yolla Bolly-Middle Eel WA 12/26/01 0.25 16.78 17.03 1.51 3.80 0.019 0.216 0.008 0.Yolla Bolly-Middle Eel WA 12/16/03 0.25 16.78 17.03 1.47 3.80 0.013 0.217 0.008 0.Yolla Bolly-Middle Eel WA 01/02/03 0.23 16.78 17.01 1.35 3.80 0.016 0.196 0.007 0.Yolla Bolly-Middle Eel WA 02/06/02 0.20 16.78 16.98 1.21 3.80 0.014 0.175 0.006 0.

1 Project and background extinction values for daily period that resulted in the maximum percent change in extinction. 2 Emission rates based on continuous year-round operation for three years. 3 Background extinction derived from default annual average Western U.S. extinction components provided in FLAG guidance docum

4 Extinction coefficient components are: SO4 = fine sulfate, NO3 = fine nitrate, OC = fine organic carbon, EC = fine elemental carbon, 

PMF = fine crustal mass. 
TABLE 5-6 

MAXIMUM PREDICTED EXTINCTION CHANGE BY CLASS I AREA 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Extinction coefficient in inverse megameters (1/Mm) 

bext1 bext by Comp

Class I Area Date Project2 Bckgrnd3 Total 

Change

(%) f(RH) SO4 NO3 OC E

Caribou WA 04/26/02 0.049 15.700 15.749 0.310 2.000 0.003 0.035 0.005 0

Desolation WA 01/14/02 0.025 16.480 16.505 0.150 3.300 0.002 0.021 0.001 0

Lassen Volcanic NP 10/24/02 0.153 16.360 16.513 0.940 3.100 0.011 0.129 0.006 0

Lava Beds NM 01/31/03 0.079 16.660 16.739 0.480 3.600 0.008 0.066 0.002 0

Marble Mountain WA 01/20/03 0.161 17.140 17.301 0.940 4.400 0.017 0.135 0.004 0

Redwood NP 09/05/03 0.095 17.260 17.355 0.550 4.600 0.013 0.076 0.003 0

South Warner WA 12/01/02 0.105 16.660 16.765 0.630 3.600 0.006 0.091 0.003 0

Thousand Lakes WA 01/31/03 0.141 16.720 16.861 0.840 3.700 0.014 0.117 0.004 0

Yolla Bolly-Middle Eel WA 11/23/02 0.469 16.300 16.769 2.880 3.000 0.023 0.398 0.022 0

1 Project and background extinction values for daily period that resulted in the maximum percent change in extinction. 2 Emission rates based on continuous year-round operation for three years. 3 Background extinction derived from default annual average Western U.S. extinction components provided in FLAG guidance docum

4 Extinction coefficient components are: SO4 = fine sulfate, NO3 = fine nitrate, OC = fine organic carbon, EC = fine elemental carbon, 

PMF = fine crustal mass. 
FIGURES 
PROJECT SCHEMATIC FLOW DIAGRAM 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 
Figure 

2-2

Project No. 

012692.000.0 VISCINITY OF FACILITY AND CLASS II MODELING DOMAIN 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

012345

Sacramento River

Anderson

Cottonwood

Redding

Municipal

Airport

Redding

Modeling

Domain

SPI-Anderson

Miles
Figure 

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

4485000

UTM Northing (meters)
Figure 

4-2

Project No. 

WIND ROSE, REDDING MUNICIPAL 012692.000 AIRPORT, JAN. 1995 – DEC. 1999 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 
SOURCE AND SIGNIFICANT STRUCTURE LOCATIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

1

2

3 4

5

7

8

9

10

12

13

14

15

16

17

18

19

20

21

1 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 Stack

0 250 500 

Property Boundary
Figure 

4-4

Project No. 

012692.000 MAXIMUM PREDICTED 1-HOUR AVERAGE CO CONCENTRATIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Concentration isopleths in micrograms per cubic meter (μg/m3) 

553000 554000 555000 556000 557000 558000 559000 560000 561000 562000

UTM Easting (meters)

4476000

4477000

4478000

4479000

4480000

4481000

4482000

4483000

4484000

4485000

UTM 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 micrograms per cubic meter (μg/m3) 

553000 554000 555000 556000 557000 558000 559000 560000 561000 562000

UTM Easting (meters)

4476000

4477000

4478000

4479000

4480000

4481000

4482000

4483000

4484000

4485000

UTM Northing (meters)

= maximum predicted concentration (70.9 μg/m3)
Figure 

4-6

Project No. 

012692.000 MAXIMUM PREDICTED 3-HOUR AVERAGE SO2 CONCENTRATIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Concentration isopleths in micrograms per cubic meter (μg/m3) 

553000 554000 555000 556000 557000 558000 559000 560000 561000 562000

UTM Easting (meters)

4476000

4477000

4478000

4479000

4480000

4481000

4482000

4483000

4484000

4485000

UTM Northing (meters)

= maximum predicted concentration (1.96 μg/m3)
Figure 

4-7

Project No. 

012692.000 MAXIMUM PREDICTED 24-HOUR AVERAGE SO2 CONCENTRATIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Concentration isopleths in micrograms per cubic meter (μg/m3) 

553000 554000 555000 556000 557000 558000 559000 560000 561000 562000

UTM Easting (meters)

4476000

4477000

4478000

4479000

4480000

4481000

4482000

4483000

4484000

4485000

UTM Northing (meters)

= maximum predicted concentration (1.08 μg/m3)
Figure 

4-8

Project No. 

012692.000 MAXIMUM PREDICTED ANNUAL AVERAGE SO2 CONCENTRATIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Concentration isopleths in micrograms per cubic meter (μg/m3) 

553000 554000 555000 556000 557000 558000 559000 560000 561000 562000

UTM Easting (meters)

4476000

4477000

4478000

4479000

4480000

4481000

4482000

4483000

4484000

4485000

UTM Northing (meters)

= maximum predicted concentration (0.173 μg/m3)
Figure 

4-9

Project No. 

012692.000 MAXIMUM PREDICTED 24-HOUR AVERAGE PM10 CONCENTRATIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Concentration isopleths in micrograms per cubic meter (μg/m3) 

553000 554000 555000 556000 557000 558000 559000 560000 561000 562000

UTM Easting (meters)

4476000

4477000

4478000

4479000

4480000

4481000

4482000

4483000

4484000

4485000

UTM Northing (meters)

= maximum predicted concentration (1.59 μg/m3)
Figure 

4-10

Project No. 

012692.000 MAXIMUM PREDICTED ANNUAL AVERAGE PM10 CONCENTRATIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Concentration isopleths in micrograms per cubic meter (μg/m3) 

553000 554000 555000 556000 557000 558000 559000 560000 561000 562000

UTM Easting (meters)

4476000

4477000

4478000

4479000

4480000

4481000

4482000

4483000

4484000

4485000

UTM Northing (meters)

= maximum predicted concentration (0.223 μg/m3)
Figure 

4-11

Project No. 

012692.000 MAXIMUM PREDICTED ANNUAL AVERAGE NOX CONCENTRATIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Concentration isopleths in micrograms per cubic meter (μg/m3) 

553000 554000 555000 556000 557000 558000 559000 560000 561000 562000

UTM Easting (meters)

4476000

4477000

4478000

4479000

4480000

4481000

4482000

4483000

4484000

4485000

UTM Northing (meters)

= maximum predicted concentration (1.47 μg/m3)
Figure 

4-12

Project No. 

012692.000 MAXIMUM PREDICTED NET ANNUAL AVERAGE NOX CONCENTRATIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Concentration isopleths in micrograms per cubic meter (μg/m3) 

553000 554000 555000 556000 557000 558000 559000 560000 561000 562000

UTM Easting (meters)

4476000

4477000

4478000

4479000

4480000

4481000

4482000

4483000

4484000

4485000

UTM 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

300

North - 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 WA
Figure 

5-2

Project No. 

012692.000 CALPUFF CLASS I AREA RECEPTORS 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

250

North - 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

300

North - South LCC (

km)

K4BK

KAAT

KACV

KAPC

KBAB

KBLU

KCEC

KCIC

KEKA

KLMT KLKV

KMFR

KMHR

KMHS

KMYV

KO87

KOVE

KRBL

KRDD

KREV

KRNO

KSAC

KSIY

KSMF

KSTO

KSTS

KSUU

KSXT

KTRK

KTVL

KUKI

KVCB
Figure 

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

300

North - South LCC (

km)
Figure 

5-5

Project No. 

012692.000 MAXIMUM PREDICTED ANNUAL AVERAGE NO2 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

250

North - South LCC (k

m)

Concentration isopleths in micrograms per cubic meter (μg/m3) 
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 micrograms per cubic meter (μg/m3) 

-200 -150 -100 -50 0 50 100 150

East - West LCC (km)

-100

-50

0

50

100

150

200

250

North - South LCC (k

m)
Figure 

5-7

Project No. 

012692.000 MAXIMUM PREDICTED ANNUAL AVERAGE PM10 CONCENTRATIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Concentration isopleths in micrograms per cubic meter (μg/m3) 

-200 -150 -100 -50 0 50 100 150

East - West LCC (km)

-100

-50

0

50

100

150

200

250

North - South LCC (k

m)
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 micrograms per cubic meter (μg/m3) 

-200 -150 -100 -50 0 50 100 150

East - West LCC (km)

-100

-50

0

50

100

150

200

250

North - South LCC (k

m)
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 micrograms per cubic meter (μg/m3) 

-200 -150 -100 -50 0 50 100 150

East - West LCC (km)

-100

-50

0

50

100

150

200

250

North - South LCC (k

m)
Figure 

5-10

Project No. 

012692.000 MAXIMUM PREDICTED ANNUAL AVERAGE SO2 CONCENTRATIONS 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Concentration isopleths in micrograms per cubic meter (μg/m3) 

-200 -150 -100 -50 0 50 100 150

East - West LCC (km)

-100

-50

0

50

100

150

200

250

North - South LCC (km)
Figure 

5-11

Project No. 

012692.000 MAXIMUM PREDICTED TOTAL NITROGEN DEPOSITION FLUXES 

SPI Lumber Manufacturing Facility Cogeneration Project 

Anderson, California 

Deposition flux isopleths in kilograms 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

250

North - South LCC (k

m)
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 kilograms 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

250

North - South LCC (k

m)
Figure 

5-13

Project No. 

012692.000 PREDICTED EXT. COEFF. ATTRIBUTABLE 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

250

North - South LCC (k

m)
APPENDIX A 
 SHASTA 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 Shasta 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 plan and area map indicating receptors within 1/4 mile of the facility. 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 appropriate 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/PROPERTY OWNER AGREES TO DEFEND, INDEMNIFY, AND HOLD THE SHASTA COUNTY AIR QUALITY MANAGEMENT 

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 36th Ave W, Suite 101 

Lynnwood, WA 98036 

May 2007 

Project No. 012692 
I:\Project\SPI\SPI_Anderson-12692\permit_application\SPI Anderson BACT Analysis - final.doc i

TABLE OF CONTENTS 

Page 

1.0 INTRODUCTION.............................................................................................................1 

2.0 BIOMASS-FIRED COGENERATION UNIT BACT ANALYSIS .................................2 

2.1 NOX BACT ANALYSIS ...........................................................................................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 NOx ......................................................................9 

2.2 CO BACT ANALYSIS .............................................................................................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 ANALYSIS.......................................................................................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 ANALYSIS ........................................................................................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 ANALYSIS .........................................................................................19 

2.5.1 Identification of Possible Control Alternatives .......................................19 
TABLE OF CONTENTS 

(Continued) 

I:\Project\SPI\SPI_Anderson-12692\permit_application\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 NOx Control Technology Search Results 

Table 2 NOx Control Technology Cost-Effectiveness Summary 

Table 3 CO Control Technology Search Results 

Table 4 PM10 Control Technology Search Results 

Table 5 ROG/VOC Control Technology Search Results 

Table 6 SO2 Control Technology Search Results 

APPENDIX 

Attachment A NOx and SO2 BACT Cost-Effectiveness Calculations 
I:\Project\SPI\SPI_Anderson-12692\permit_application\SPI Anderson BACT Analysis - final.doc 1 

BACT ANALYSIS 

Sierra Pacific Industries Biomass-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 manufacturing facility in Anderson, California. The 

project would consist of a biomass-fired cogeneration unit, a steam turbine, 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 (BACT) for a given pollutant to one or more emission units, must 

conduct an analysis to ensure that BACT is being 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 PSD 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 project, require each proposed emission unit to 

apply BACT to control emissions 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 cooling tower. Based on the calculated annual 

emission rates for the proposed project and USEPA and Shasta County BACT thresholds, 

analyses are required for oxides of nitrogen (NOx), carbon monoxide (CO), particulate matter 

equal to or less than ten microns in diameter (PM10), reactive organic compounds (ROG), sulfur 

dioxide (SO2), and beryllium. 

Geomatrix queried EPA’s Reasonably Available Control Technology (RACT)/BACT/Lowest 

Achievable Control Technology (LAER) Clearinghouse (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. 
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eliminating sources that did not emit pollutants as a result of similar operation. The California 

Air Resources Board (ARB) BACT Clearinghouse was also searched for applicable permits, 

either pending or issued. The sections that follow discuss the control 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 database was conducted for biomass-fired 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 sources 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 emission rate with the heat input. 

2.1 NOX BACT ANALYSIS

NOx is generated when combustion temperatures are high enough for the nitrogen in the 

combustion air or bound in the fuel to combine with oxygen to form NO. Depending upon 

conditions, some portion of the NO will react to form NO2. 

2.1.1 Identification of Possible Control Alternatives 

There are a variety of options available for controlling NOx emissions from combustion 

sources. Some options involve combustion controls that reduce NOx formation, while others 

utilize add-on control devices to remove NOx after it is formed. 

Combustion controls reduce NOx emissions by controlling the combustion temperature and the 

availability of oxygen. Combustion air containing both nitrogen and oxygen can combine in a 

high temperature environment to form thermal NOx. The oxidation of nitrogen that is 

chemically bound in fuel sources can also form what is called fuel-bound NOx. 

Dry low-NOx (DLN) burners control thermal NOx 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 burners 
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requires a wall-fired furnace and pulverized biomass fuel that is burned in suspension with coal 

or natural gas. 

Proper combustion generally refers to control, generally computerized, 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 selective catalytic reduction (SCR) and selective non-catalytic 

reduction (SNCR) systems are widely used technologies for controlling NOx emissions from 

combustion sources. In the SCR process, ammonia is mixed with the exhaust from the 

combustion device and the mixture is passed through a catalyst bed. The NOx reacts with the 

ammonia aided by the catalyst to form nitrogen and water. Regenerative SCR (RSCR) systems 

have been developed recently to make application 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 NOx to form nitrogen and 

water, although no catalyst is used to aid the reaction. The catalyst 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 systems, in which a catalyst bed is located 

downstream of the SNCR system, have been developed where the unreacted ammonia injected 

by the SNCR system is used by the catalyst to further reduce NOx emissions. 

SCONOx is similar to SCR, except that NOx in the exhaust stream reacts with potassium 

carbonate (K2CO3) to form potassium nitrate (KNO3). This compound is reacted with 

hydrogen to form gaseous nitrogen (N2), and regenerate the K2CO3. 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 SCONOx system is also said to control carbon 

monoxide (CO) and volatile organic compounds (VOCs) by oxidation. 

2.1.2 Control Alternative Review 

The results of the database queries and permit investigations for NOx control technologies are 

presented in Table 1, sorted by permit limit, beginning with the NOx limit proposed for the 

cogeneration unit. 
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The following technologies were found for controlling NOx from biomass-fired boilers: 

• Proper combustion 

• SNCR 

• SCR 

• RSCR 

• SNCR/RSCR hybrid 

The database queries did not produce any instances of NOx 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 NOx 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 particulate matter from the exhaust stream, an SCR 

system removes NOx. The permitted NOx limit for each of the boilers at Sauder Woodworking 

is 0.20 lb/MMBtu, which is higher than the proposed 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 Stratton, Maine, and Whitefield Power & Light, in Whitefield, 

Connecticut. Both of these systems were retrofitted onto existing boilers to qualify under 

Renewable Portfolio Standards. The Boralex Stratton retrofit included the installation of an 

Ecotube system, which adds ambient air at strategic 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 NOx 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 Skagit County, Washington. For that wood-fired 

cogeneration unit, the Washington 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 are being achieved in practice using SNCR to 

control NOx from a 310 MMBtu/hr boiler in Aberdeen, Washington. The most recent biomass-
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fired boiler BACT determination in the RBLC was by the North Dakota State Department of 

Health for Archer Daniels Midland’s Northern Sun facility in North Dakota, which determined 

that 0.2 lb/MMBtu was BACT for NOx 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 NOx generated during combustion. Coen manufactures the Dual Air Zone (DAZ) 

Scroll burner, which can be used to fire pulverized biomass materials along 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 input, and require that the fuel be reduced to 

approximately 1/32 of an inch in size. With some flue gas recirculation and staged combustion, 

a NOx 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 section have been shown to be 

technically feasible for controlling NOx emissions from biomass-fired boilers. Several of the 

alternatives have either not been applied to biomass-fired boilers, or been applied to boilers 

with significantly lower heat input than that currently proposed by SPI. 

Proper Combustion
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Proper combustion refers to the application of state-of-the-art design and appropriate operation 

of a combustion unit. Current design biomass-fired mass-burner-type boilers can generally 

achieve NOx 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 NOx 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 NOx during combustion, and are generally suited to smaller 

boilers that burn wood waste containing a high percentage of resins, such as the waste from 

medium density fiberboard (MDF), plywood, or veneer operations. In this case, the emission 

rate with DLN burners (0.35 lb/MMBtu) is higher than could be achieved by an uncontrolled 

mass burner-type boiler using a combustion grate (approximately 0.20 lb/MMBtu), so this 

technology will be eliminated from 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 NOx 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 SNCR systems makes them technically feasible, and 

has resulted in them becoming the most popular add-on NOx control technology for biomassfired boilers. 

SCR, RSCR and SNCR/SCR Hybrid

An SCR system used to control NOx emissions from a wood-fired boiler has been demonstrated 

to control NOx 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 boilers. No instances of SNCR/SCR hybrid 

systems applied to biomass-fired boilers have been identified, though the components of the 
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system, SNCR and SCR, have been applied to wood-fired boilers. All three of these variations 

on SCR systems are considered technically feasible for controlling NOx emissions from a 

biomass-fired boiler. Because RSCR controls NOx 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 purposes. 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. While biomass fuels are not generally considered 

high-sulfur fuels, the AP-42 SO2 emission factor for wood-fired boilers is 0.025 lb/MMBtu, 

which is equivalent to about 7.2 lb/hr of SO2. 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 equivalent 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 control technology for controlling NOx emissions from a 

biomass-fired boiler. 

The following is a list of the technically feasible 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 technologies in more detail and ranks them by 

effectiveness. 

Proper Combustion
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A modern biomass-fired boiler furnace, operated with computerized controls to ensure proper 

combustion would result in a NOx 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 NOx emissions. 

SNCR

Currently, SNCR systems are the most common add-on control device used to reduce NOx

emissions from large biomass-fired boilers. SNCR systems rely on high temperatures to 

promote the reaction of NOx with the introduced ammonia. As a result, the control system is 

often incorporated into the boiler design to facilitate the introduction 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 NOx. 

SPI proposes to employ an SNCR integral to the boiler design to reduce NOx 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/MMBtu 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 NOx from three wood-fired boilers and 

has a permit limit of 0.1 lb/MMBtu on a 30-day rolling 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 emission rate of SPI’s proposed 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 (quarterly average) and 0.25 

lb/MMBtu (24-hour average) at the Boralex 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 emission limit of 0.07 lb/MMBtu, and 0.065 lb/MMBtu when employed 

as part of a hybrid system with the integral SNCR system. 
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2.1.2.4 Ranking by Effectiveness 

The remaining technologically feasible control 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 NOx

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 effectiveness increase between SNCR and RSCR and the 

SNCR/RSCR hybrid are in excess of $44,000 and $38,000 per ton of NOx removed, 

respectively. Based on this analysis, SNCR is deemed to be the most cost effective NOx

control technology for wood-fired boilers. As a point of comparison, a recent NOx BACT 

determination for a biomass-fired boiler in the RBLC (ADM’s Northern Sun facility) indicates 

that an incremental cost effectiveness of $6,540 per ton associated with installing an SNCR 

system instead of relying solely on combustion controls was considered to be excessive. 

2.1.3 Selection of BACT for NOx

Based on the analysis presented in this section, SPI proposes that BACT for the control of NOx

from biomass-fired mass-burner-type boilers is the use of an integral SNCR system. NOx

emissions would be limited to 0.13 lb/MMBtu (30-day average), which is approximately 

equivalent to 202 TPY at the anticipated annual average operating capacity. 

2.2 CO BACT ANALYSIS

Carbon monoxide (CO) is a product of the chemical reaction between carbonaceous fuels and 

oxygen. In fuel-rich mixtures, CO occurs as the product of combustion. In fuel-lean mixtures 

CO can result due to poor mixing of fuel and air 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 CO2 into CO (Wark and Warner, 1981). 
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2.2.1 Identification of Possible Control Alternatives 

As for NOx, the control technology options available for reducing CO emissions from 

combustion sources include combustion controls that encourage complete combustion to reduce 

CO formation, as well as add-on control devices that oxidize CO to CO2 after leaving the 

combustion area. 

Combustion controls for CO include adequate fuel residence times to ensure CO2 formation, 

proper fuel-air mixing, and temperature control. These measures, however, can result in an 

increase in the NOx emissions from a combustion unit. Modern boiler designs strive to balance 

these competing factors, and when combined with appropriate operation of the boiler, are 

commonly referred to as “proper 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-pollutant (in this case CO to CO2). Catalytic 

oxidizers operate in a temperature range of approximately 500 oF to 1,000 oF. At lower 

temperatures the CO conversion efficiency falls off rapidly. 

Because higher temperatures are desirable for improved conversion of CO to CO2 by the 

catalyst, the exhaust temperature must be increased, resulting in higher fuel use. In order to 

reduce catalyst masking and pressure drop across the device, a particulate 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 the higher temperature, and therefore higher 

volume, exhaust flow. Although the catalyst would 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 NOx BACT analysis) also utilizes a catalytic technique that oxidizes 

CO to CO2 in addition to controlling NOx emissions. 

2.2.2 Control Alternative Review 

The results of the database queries for CO control 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 databases searched for controlling CO from 

wood-fired boilers: 

• Oxidation Catalyst 
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• Proper Combustion 

The majority of biomass-fired boilers use proper 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 operating, and the other has 

not been constructed. Boilers with lower permit limits below 0.60 lb/MMBtu generally have 

some detail that differentiates them from “normal” biomass-fired boilers. Examples of these 

differences include: consistently available high heat-value-per-weight fuel sources, co-firing 

with fossil fuels, and lenient or nonexistent NOx and/or ammonia slip limits that allow 

operation at higher temperatures 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 technique used to limit CO emissions from woodfired boilers. Catalytic oxidation 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 facility 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 catalyst to meet that permit limit. 

As discussed in the NOx BACT analysis, SCONOx is extremely sensitive to presence of sulfur 

in the exhaust stream, and has never been demonstrated 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 submitted for the Darrington, Washington cogeneration 

project, the proposed boiler would be a fuel-cell design. Fuel-cell design boilers are typically 

bottom-supported and employ a shell of refractory tiles to achieve higher furnace temperatures 
I:\Project\SPI\SPI_Anderson-12692\permit_application\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 proposed by SPI. SPI believes that a 1-hour average 

CO emission limit of 0.60 lb/MMBtu can be achieved in practice using the top-supported 

design, while limiting NOx emissions to 0.13 lb/MMBtu and ammonia slip to 20 ppm. At the 

time this analysis was developed, the Darrington boiler had not been constructed. 

2.2.2.3 Effectiveness of Remaining Technologies 

This section describes the remaining technologies 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 NOx

emission limit (0.13 lb/MMBtu) as well as the 20 parts per million (ppm) ammonia slip limit 

required by Shasta County (Shasta County AQMD Rule 3:26.c.4), boiler operation will favor 

reduced NOx creation over reduced CO creation. 

SPI currently operates biomass-fired boilers at their Lincoln, California and Aberdeen, 

Washington lumber manufacturing facilities 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 has 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 limit 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 meeting 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 biomass-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 Oxidation
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Oxidation catalysts are generally capable of providing between 40 and 90 percent reduction in 

CO emissions. Although boiler efficiency would 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 control 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 oxidation catalyst to achieve 50 percent control of CO 

emissions from a biomass-fired boiler was calculated. There are two approaches to applying 

oxidation catalyst technology to a biomass-fired boiler. The approach that has been 

demonstrated in practice (although the unit is no longer operating) is to reduce the efficiency of 

the boiler’s waste heat recovery system in order to make the oxidation catalyst effective by 

increasing the exhaust gas temperature. 

A permit application for a similar-sized wood-fired boiler submitted to the Washington 

Department of Ecology by Darrington Cogeneration in 2003 included a cost-effectiveness 

analysis using direct and indirect costs estimated using the EPA’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 additional catalyst bed to allow semi-annual chemical cleaning), the 

additional ductwork, increasing the size of the particulate control device, and increased fuel use 

due to loss of efficiency equates to approximately $14,000 per ton of CO controlled, which was 

considered outside the envelope of acceptable costs. Even if this analysis were modified to 

represent the larger proposed boiler and an assumed 50 percent 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 the anticipated annual operating capacity. 
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2.3 PM10 BACT ANALYSIS

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 PM10

emissions is similar to the strategy used to control CO and includes adequate fuel residence 

time, proper fuel-air mixing, and temperature control 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 NOx 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 PM10 emissions from a boiler 

are electrostatic precipitators (ESPs) and baghouses. ESPs remove particles from an exhaust 

stream by imposing an electrical charge on the particles and then attracting them to an 

oppositely charged plate. The dust collected on the charged plates is periodically removed by 

vibrating or rapping of the plates. 

Baghouses, or fabric filters, use various types of materials (generally fabrics) to trap particles 

while the gas passes through the voids in the material. The dust that becomes caked on the 

fabric bags is removed periodically 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 the primary control device. 

Wet scrubbers, such as venturi scrubbers are less common because they typically have lower 

control efficiencies than either ESPs or baghouses. They also complicate waste disposal by 

introducing liquids that create sludge when combined with the removed PM10. A venturi is a 

narrowed section of duct followed by an expanded 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 efficiency, a high-energy exhaust flow is required. 
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2.3.2 Control Alternative Review 

The results of the database queries for PM10 control technologies are presented in Table 4, 

sorted by permit limit, beginning with the PM10 limit proposed by SPI for the new biomassfired cogeneration unit. 

A review of the RBL Clearinghouse indicates that the most stringent control technology for 

PM10 is use of an ESP or a baghouse. The most stringent permit limit employing ESP 

technology to control PM10 emissions is 0.02 lb/MMBtu at Sierra Pacific Industries facilities in 

Aberdeen and Skagit County, Washington, Boralex in Livermore Falls, Maine, Multitrade 

Limited Partnership in Hurt, Virginia, and Hampton 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 limits from permits issued several years ago may 

be less stringent than they appear. 

The most stringent permit limit employing baghouse technology is at Kimberly-Clark in 

Everett, Washington, which has a PM10 permit limit of 0.0084 gr/dscf at 7 percent oxygen, 

equivalent to 0.016 lb/MMBtu. It should be noted that the testing required for the KimberlyClark boiler is for filterable PM10 only. The Wheelabrator Ridge Energy facility in Ashland, 

Florida, has a permit limit of 0.008 gr/dscf at 7 percent oxygen, equivalent to 0.02 lb/MMBtu. 

This facility also requires only a filterable PM10 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 PM10 emissions from a biomass-fired boiler is an 

ESP preceded by a multiclone. Baghouses have been employed to control PM10 emissions 

from boilers in which wood is fired with other fuels such as oil or tires. The likelihood of fires 

in downstream ducting or control devices is significant because of the high carbon content of 

the ash from boilers that burn biomass fuels, but many operators and manufacturers have 
I:\Project\SPI\SPI_Anderson-12692\permit_application\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 baghouses, which generally have combustible fabric 

filters, unless expensive flame-proof bags are purchased. Venturi scrubbers are generally 

employed to control PM10 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 remaining technologies ranks them in 

order of effectiveness. 

Venturi Scrubbers

Venturi scrubbers with pressure drops of between 5 and 10 inches of water typically remove 

less than 99 percent of PM10 from exhaust flows. Units with pressure drops of 20 inches of 

water or greater can remove greater than 99 percent of PM10. 

Baghouses

Baghouses typically operate with pressure drops between 2 and 12 inches of water. PM10

control efficiencies are capable of removing over 99 percent of PM10 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 PM10 from exhaust flows. 

2.3.2.4 Ranking by Effectiveness 

The remaining technologically feasible control 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 the baghouse or scrubber is presented because SPI 

selected the ESP for the wood-fired cogeneration unit. 
I:\Project\SPI\SPI_Anderson-12692\permit_application\SPI Anderson BACT Analysis - final.doc 17 

2.3.3 Selection of BACT for PM10 

SPI proposes that BACT for PM10 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 ANALYSIS

With the exception of various chloro- and fluorocarbons, 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 incomplete fuel combustion. In the case of biomass, 

volatiles are released as the fuel 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 techniques, provide 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. 

Add-on controls used to reduce VOCs generally fall into three categories: adsorption onto a 

solid (e.g., activated carbon), absorption by a liquid, 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 control 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 emissions from a biomass-fired boiler is 

maintaining proper combustion of the fuel. As shown in Table 5, permit limits vary 

considerably, ranging over an order of magnitude. Clearly, agencies approving permit limits 

for VOC have been flexible, understanding the tradeoffs between emissions of NOx, CO, and 
I:\Project\SPI\SPI_Anderson-12692\permit_application\SPI Anderson BACT Analysis - final.doc 18 

VOC that are inherent to maintaining proper 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/MMBtu 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 research, 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 control 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., NOx). 

2.4.2.4 Ranking by Effectiveness 

Proper combustion is the only feasible control technology, therefore it is the most effective. 

2.4.2.5 Cost Effectiveness Evaluation 

Because proper combustion is the only alternative, 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 anticipated annual operating capacity. 
I:\Project\SPI\SPI_Anderson-12692\permit_application\SPI Anderson BACT Analysis - final.doc 19 

2.5 SO2 BACT ANALYSIS

Sulfur dioxide (SO2) emissions are entirely dependent upon the amount of sulfur present in the 

fuel. Sulfur contained in the fuel combines with oxygen at combustion temperatures to form 

SO2. 

2.5.1 Identification of Possible Control Alternatives 

There are two alternatives for reducing SO2 emissions combustion sources: removal of sulfur 

from the fuel before it is combusted, and removal of SO2 from the exhaust gas after 

combustion. 

Removing sulfur from fuel before it is combusted has been employed to remove sulfurcontaining nonorganically-bound minerals (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 SO2 control requirement other than the exclusive use of biomass, 

and perhaps a limit on the sulfur content of a start-up or co-fired fuel. 

Scrubbing, or flue gas desulfurization (FGD) systems remove SO2 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 which the gases pass through. The sorbent in the 

slurry comes in contact with the SO2 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 filter) must be sized to handle the additional load 

created by the SO2 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 SO2 control technologies are presented in Table 6, sorted 

by permit limit, beginning with the SO2 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 

• FGD 
I:\Project\SPI\SPI_Anderson-12692\permit_application\SPI Anderson BACT Analysis - final.doc 20 

2.5.2.2 Technical Feasibility of Control Alternatives 

FGD systems are more commonly applied to coal-fired 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 SO2 emissions from a biomass-fired boiler. 

2.5.2.3 Effectiveness of Remaining Technologies 

Wet FGD systems are considered the most effective, and can achieve greater than 90 percent 

reduction in SO2 emissions. Dry scrubbers and spray driers are capable of control efficiencies 

on the order of 90 percent. 

2.5.2.4 Ranking by Effectiveness 

The remaining technologically feasible control technologies ranked in decreasing order of 

effectiveness are: 

• None 

• FGD 

2.5.2.5 Cost Effectiveness Evaluation 

Costs for an SO2 scrubbing unit that could be applied to the proposed wood-fired boiler were 

obtained from a wood-fired boiler manufacturer (McBurney of Norcross, Georgia) and used to 

calculate cost effectiveness. As shown in the cost effectiveness calculations in Attachment A, 

reducing SO2 from a wood-fired boiler using a scrubbing system would cost approximately 

$21,000 per ton of SO2 removed, which is outside the envelope of acceptable cost 

effectiveness. 

2.5.3 Selection of BACT for SO2

SPI proposes that no control system is BACT for reducing SO2 emissions from a biomass-fired 

boiler, and that the boiler SO2 emission rate will be 0.016 lb/MMBtu based on source test data, 

which is equivalent to a mass emission rate of 24.8 tons per year. 

2.6 BERYLLIUM BACT ANALYSIS

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 tires. SPI proposes that no control system is BACT for reducing 

beryllium emissions from a biomass-fired boiler. An AP-42 source test-derived emission factor 
I:\Project\SPI\SPI_Anderson-12692\permit_application\SPI Anderson BACT Analysis - final.doc 21 

of 1.55 x 10-6 lb/MMBtu was used to calculate emissions from the 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 mist 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 Industries, Inc. The principal difference is 

that the DRU-1.5 removes the side plates on each panel, allowing the panels to be nested for a 

seamless installation. The water loading expected for the cooling towers is 4.24 gallons per 

minute per square foot (gpm/ft2) and an air velocity of 503 feet per minute (fpm). The D-15 

drift test results indicate that the drift rate associated with these values should be less than 

0.0005 percent. 

Of the three most recent instances of permits issued 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 eliminators BACT, another (Marathon Petroleum in Louisiana, 

permit issued December 27, 2006) deemed 0.005 percent drift eliminators BACT, and the third 

(Valero Refining in Louisiana, permit issued Feburary 8, 2007) deemed drift eliminators BACT 

without specifying an effectiveness. The cooling 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 cooling towers at SPI’s Aberdeen and Burlington 

facilities in Washington, and SPI proposes that this technology remains BACT for cooling 

towers. 
 

TABLES
TABLE 1 

NOX CONTROL TECHNOLOGY SEARCH RESULTS 

Sierra Pacific Industries New Biomass-Fired Cogeneration Project 

Anderson, California 

Facility Name Location 

Date of 

Permit 

Heat Input 

(MMBtu/hr) 

Permit Limit 

(lb/MMBtu) 

Control 

Technology 

Sierra Pacific Industries Anderson, CA Proposed 3541 0.13 SNCR 

Whitefield Power & Light Whitefield, NH 9/10/04 220 0.33/0.0752 RSCR B

Pittsylvania Power Hurt, VA 2/21/92 374 0.13 SNCR 

NESCO Darrington, WA 1/18/05 403 0.12/0.14,5 SNCR 

Sierra Pacific Industries Burlington, WA 9/21/05 430 0.13 SNCR 

Sierra Pacific Industries Aberdeen, WA 10/17/02 310 0.15/0.14 SNCR 

Laurentian Energy Virginia, MN 6/30/05 230 0.15 SNCR 

Hampton Lumber Darrington, WA 6/1/05 245 0.15 SNCR B

Boralex Ashland Ashland, ME 4/2/92 586 0.15 SNCR B

ADM Northern Sun Enderlin, ND 5/1/06 180 0.204 Proper Combustion 

KES Chateaugay Project Chateaugay, NY 12/19/94 275 0.23 No Controls B

Weyerhaeuser Co. Bruce, MS 5/9/95 90 0.23 Proper combustion 

Boralex, Stratton Stratton, ME 1/4/05 672 0.24 SNCR/RSCR B

Wheelabrator Energy Sherman Station, ME 4/9/99 315 0.25 Proper combustion 

Smurfit-Stone Container Stevenson, AL 1/15/97 620 0.25 Proper combustion 

Willamette Industries, Inc. Marlboro, SC 4/17/96 470 0.3 Proper combustion B

Georgia Pacific Corp. Gloster, MS 4/11/95 244 0.3 None 

Willamette Industries, Inc Campti, LA 2/4/91 940 0.3 Proper combustion 

1 Annual average heat input. 2 Quarterly average emission limit is 0.075 lb/MMBtu and the 24-hour average limit is 0.33 lb/MMBtu. 3 Based on a 30-day rolling average. 4 The first value is the 24-hour average limit, and the second is the annual average limit. 5 The NESCO project was never constructed. 
TABLE 2 

NOX CONTROL TECHNOLOGY COST-EFFECTIVENESS ANALYSIS 

Sierra Pacific Industries Lumber Manufacturing Project 

Anderson, California 

Control Technology 

Annualized Cost1

($/yr) 

Reduction 

(tons/yr) 

Cost Effectiveness 

($/ton) 

SNCR 253,474 155 1,635 

RSCR 2,319,749 202 11,509 

SNCR/RSCR Hybrid 2,332,065 209 11,141 

1 Based on 20-years at 7% interest. 
TABLE 3 

CO CONTROL TECHNOLOGY SEARCH RESULTS 

Sierra Pacific Industries Lumber Manufacturing Project 

Anderson, California 

Facility Name Location Date of Permit Heat Input (MMBtu/hr) Permit Limit (lb/MMBtu) Control Technology 

Sierra Pacific Industries Anderson, CA Proposed 3541 0.60 Proper combustion 

South Point Power South Point, OH 4/4/06 318 0.10 Oxidation catlyst 

Hampton Lumber Darrington, WA 6/1/05 245 0.23 Proper combustion 

Laurentian Energy Virginia, MN 6/30/05 230 0.3 Proper combustion 

Willamette Industries, Inc. Marlboro, SC 4/17/96 470 0.3 Proper combustion 

Boralex Ashland Ashland, ME 4/2/92 586 0.3 Proper combustion 

Willamette Industries Inc Campti, LA 2/4/91 940 0.32 Proper combustion 

Decker Energy International East Ryegate, VT 7/11/90 300 0.3 Proper combustion 

Sierra Pacific Industries Burlington, WA 9/21/05 430 0.35 Proper combustion 

NESCO – Darrington Cogeneration Darrington, WA 1/18/05 403 0.353 Proper combustion 

Sierra Pacific Industries Aberdeen, WA 10/17/02 310 0.35 Proper combustion 

KES Chateaugay Project Chateaugay, NY 12/19/94 275 0.35 Proper combustion 

Pittsylvania Power Hurt, VA 2/21/92 374 0.35 Proper combustion 

Smurfit-Stone Container Stevenson, AL 1/15/97 620 0.4 Proper combustion 

Weyerhaeuser Company Bruce, MS 5/9/95 90 0.4 Proper combustion 

Gulf States Paper Corp Moundville, AL 10/14/98 98 0.5 Proper combustion 

Inland Paperboard & Packaging Bogalusa, LA 11/23/04 788 0.60 Proper combustion 

ADM Northern Sun Enderlin, ND 5/1/06 180 0.63 Proper combustion 

Bio Energy Corp. West Hopkinton, NH 7/23/98 225 1.0 Oxidation catalyst 

Plum Creek Mfg Lp-Columbia Falls Columbia Falls, MT 7/26/95 292 1.6a Proper combustion 

1 Annual average heat input. 2 Permit limit calculated based on heat input; actual permit limit is in lb/hr. 3 The NESCO project was never constructed. 
TABLE 4 

PM10 CONTROL TECHNOLOGY SEARCH RESULTS 

Sierra Pacific Industries Lumber Manufacturing Project 

Anderson, California 

Facility Name Location Date of Permit Heat Input (MMBtu/hr) Permit Limit (lb/MMBtu) Control Technology 

Sierra Pacific Industries Anderson, CA Proposed 3541 0.019 Multiclone, ESP 

South Point Power South Point, OH 4/4/06 318 0.01252 Baghouse 

Kimberly-Clark Tissue Co. Everett, WA 7/1/93 718 0.0163 Baghouse 

Sierra Pacific Industries Burlington, WA 9/21/05 430 0.02 Multiclone, ESP 

Hampton Lumber Darrington, WA 6/1/05 245 0.02 Multiclone, ESP 

NESCO – Darrington Cogeneration Darrington, WA 1/18/05 403 0.024 Multiclone, ESP 

Sierra Pacific Industries Aberdeen, WA 10/17/02 315 0.02 Mulitclone, ESP 

Boralex Livermore Falls, ME 9/5/91 534 0.02 Multiclone, ESP 

Pittsylvania Power Hurt, VA 2/21/92 374 0.02 Multiclone, ESP 

Decker Energy International East Ryegate, VT 7/11/90 300 0.023 Mech. Collector, ES

Laurentian Energy Virginia, MN 6/30/05 230 0.025 ESP 

Smurfit-Stone Container Stevenson, AL 1/15/97 620 0.03 Multiclone, ESP 

Wheelabrator Sherman Energy Sherman Station, ME 4/9/99 630 0.036 Baghouse 

Boralex Chateaugay, NY 12/19/94 275 0.038 Multiclone, ESP 

Willamette Industries, Inc. Marlboro, SC 4/17/96 470 0.05 ESP 

ADM Northern Sun Enderlin, ND 5/1/06 180 0.08 ESP 

Gulf States Paper Corp. Moundville, AL 10/14/98 98 0.1 Multiclone, ESP 

Weyerhaeuser Co. Millport, AL 10/28/94 91 0.15 Venturi Scrubber 

1 Annual average heat input. 2 Permit limit calculated based on heat input, actual limit is in gr/dscf and permit requires filterable-only PM10 test method. 3 Permit 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 5 

ROG/VOC CONTROL TECHNOLOGY SEARCH RESULTS 

Sierra Pacific Industries Lumber Manufacturing Project 

Anderson, California 

Facility Name Location Date of Permit Heat Input (MMBtu/hr) Emission Rate (lb/MMBtu) Control Technology 

Sierra Pacific Industries Anderson, CA Proposed 3541 0.013 Proper combustion 

South Point Power South Point, OH 4/4/06 318 0.013 Oxidation catlyst 

Boralex Livermore Falls, ME 9/5/91 534 0.02 Proper combustion 

Georgia Pacific Corp Gloster, MS 4/11/95 244 0.02 None 

Sierra Pacific Industries Burlington, WA 9/21/05 430 0.0251 Proper combustion 

Hampton Lumber Darrington, WA 6/1/05 245 0.025 Proper combustion 

NESCO – Darrington Cogeneration Darrington, WA 1/18/05 403 0.0252 Proper combustion 

Sierra Pacific Industries Aberdeen, WA 10/17/02 310 0.025 Proper combustion 

Wheelabrator Sherman Energy Co. Penobscott, ME 4/9/99 315 0.03 Proper combustion 

Gulf States Paper Corp Demopolis, AL 12/10/97 775 0.03 Proper combustion 

Smurfit-Stone Container Stevenson, AL 1/15/97 620 0.03 Proper combustion 

Southern Soya Corp. Estill, SC 10/2/95 58 0.05 Proper combustion 

Weyerhaeuser Co. Millport, AL 10/28/94 91 0.05 None 

Pittsylvania Power Hurt, VA 2/21/92 374 0.07 Proper combustion 

Gulf States Paper Corp Moundville, AL 10/14/98 98 0.1 None 

Willamette Industries, Inc. Marlboro, SC 4/17/96 470 0.1 Proper combustion 

Boralex Chateaugay, NY 12/19/94 275 0.1 None 

Willamette Industries Inc Campti, LA 2/4/91 940 0.1 Proper combustion 

Scott Paper Co. Everett, WA 7/1/93 718 0.5 Proper combustion 

1 Annual average heat input. 2 The NESCO project was never constructed. 
TABLE 6 

SO2 CONTROL TECHNOLOGY SEARCH RESULTS 

Sierra Pacific Industries Lumber Manufacturing Project 

Anderson, California 

Facility Name Location Date of Permit Heat Input (MMBtu/hr) Emission Rate (lb/MMBtu) Control Technology 

Sierra Pacific Industries Anderson, CA Proposed 3541 0.016 None 

Willamette Industries, Inc Campti, LA 2/4/91 940 0.008 Fuel specification 

Pittsylvania Power Hurt, VA 2/21/92 374 0.0162 Fuel specification 

Georgia Pacific Corp Gloster, MS 4/11/95 244 0.017 None 

Boralex Livermore Falls, ME 9/5/91 534 0.023 None 

Sierra Pacific Industries Burlington, WA 9/21/05 430 0.025 None 

Hampton Lumber Darrington, WA 6/1/05 245 0.025 None 

NESCO – Darrington Cogeneration Darrington, WA 1/18/05 403 0.0253 None 

Sierra Pacific Industries Aberdeen, WA 10/17/02 310 0.025 None 

Boralex Chateaugay, NY 12/19/94 275 0.03 Fuel specification 

South Point Power South Point, OH 4/4/06 318 0.07 Spray dryer 

Smurfit-Stone Container Stevenson, AL 1/15/97 620 0.1 Proper combustion 

Willamette Industries, Inc. Marlboro, SC 4/17/96 470 0.1 None 

Scott Paper Co. Everett, WA 7/1/93 718 0.1 Fuel specification 

Wheelabrator Sherman Energy Co. Penobscott, ME 4/9/99 315 0.12 Fuel specification 

Gulf States Paper Corp Demopolis, AL 12/10/97 775 0.46 Proper combustion 

ADM Northern Sun Enderlin, ND 5/1/06 180 0.47 None 

1 Annual average heat input. 2 30-day rolling average. 3 The NESCO project was never constructed. 
ATTACHMENT A




APPENDIX C 
I:\Project\SPI\SPI_Anderson-12692\permit_application\Prioritization_Appendix_anderson-draft_040607.doc 1

APPENDIX C 

FACILITY PRIORITIZATION SCORES FOR TOXIC AIR CONTAMINANTS 

In support of the permit application, Geomatrix has 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 Assessment 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 risks, but are simple screening methods to compare 

facilities to one another with respect to potential health risks from chemical emissions. As 

requested by Shasta County AQMD, both cancer and noncancer prioritization scores were 

estimated. Two procedures for calculating prioritization scores were applied, one based simply 

on emissions, toxicity, and receptor locations (emission and potency prioritization procedure), 

and one based on emissions, receptor locations, and source characteristics (dispersion 

adjustment prioritization procedure). 

For facility emissions, the cancer prioritization scores were 26 and 21 and the noncancer 

prioritization scores were 20 and 17 by the emission and potency, and dispersion adjustment 

prioritization procedures, respectively. 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 priority threshold above or below 

this range. 

BACKGROUND ON AB 2588 

The purpose of the AB 2588 process is to identify and rank facilities based 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 Board (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 pollution control district (APCD) or 

air quality management district (AQMD) requires facilities to submit comprehensive emission 

inventory reports that list the substances and amounts of chemicals 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 prioritization score procedure, then a health risk assessment of 

the chemicals emitted must also be prepared. 
I:\Project\SPI\SPI_Anderson-12692\permit_application\Prioritization_Appendix_anderson-draft_040607.doc 2

THE EMISSIONS AND POTENCY PRIORITIZATION PROCEDURE

The first procedure to prioritize facility emissions is based on estimated emissions, the potential 

toxicity of emitted toxic air contaminants, and the 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 criteria were obtained from the Hotspots Analysis and Reporting 

Program, a risk assessment and prioritization software created by the California Air Resources 

Board (CARB, 2006) to comply with the Office of Environmental Health Hazard Assessment’s 

OEHHA’s risk assessment guidance (2003). The receptor proximity was estimated using an 

aerial photograph and a site drawing. Consistent with CAPCOA guidelines, the receptor 

proximity was estimated by adding the distance from 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 property line to the emitting source (approximately 

268 meters). The calculations and input parameters are attached in Table 1. 

Cancer Prioritization Score 

The prioritization score for carcinogenic effects was calculated as follows: 

× ×1700

⎭

⎬

⎫

⎩

⎨

⎧

TS = ∑E × P RP

c

c c (1) 

Where: 

TS = the sum of scores for all substances with carcinogenic effects 

c = specific carcinogenic substance 

Ec = Emissions of c (lbs/yr) 

Pc = Unit risk of c 

RP = Receptor proximity adjustment factor 

1700 = normalization factor 

As presented in Table 1, the cancer prioritization 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 chronic non-carcinogenic effects was calculated as 

follows: 
I:\Project\SPI\SPI_Anderson-12692\permit_application\Prioritization_Appendix_anderson-draft_040607.doc 3

RP 150 or1500 P

E TS

t

t

t ⎟× × ⎠

⎞ ⎜

⎝

⎛ = ∑ (2) 

Where: 

TS = the sum of scores for all substances with non-carcinogenic effects 

t = toxic substance 

Et = Emissions of t (lbs/hr) 

Pt = Acceptable chronic or acute exposure level of t (μg/m3

) 

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 acid emissions contributed most significantly to the 

noncancer prioritization score. 

Because the prioritization score calculated using the emissions and potency prioritization 

procedure was within the range of 10 to 100 for carcinogens and noncarcinogens, a more sitespecific prioritization procedure was used as described below. 

THE DISPERSION ADJUSTMENT PRIORITIZATION PROCEDURE

The next step in the prioritization process is the dispersion adjustment prioritization procedure, 

which is based on dispersion modeling and stack parameters (release height) in addition to 

estimated emissions, chemical toxicity, and receptor proximity. The calculation of 

prioritization scores using the dispersion adjustment prioritization procedure are described 

below. 

Cancer Prioritization Score 

The prioritization score for carcinogenic effects was calculated as follows: 

, × 28

⎭

⎬

⎫

⎩

⎨

⎧ = ∑ × × ×

c

TS Ec h Pc Dh RPh (3) 

Where: 

TS = the sum of scores for all substances with carcinogenic effects 
I:\Project\SPI\SPI_Anderson-12692\permit_application\Prioritization_Appendix_anderson-draft_040607.doc 4

c = specific carcinogenic substance 

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

Pc = Unit risk of c 

h = release height (32 meters) 

Dh = Dispersion adjustment factor for h (see Table A-2) 

RPh = Receptor proximity adjustment factor for h 

28 = normalization factor 

As presented in Table 2, the cancer prioritization score was 21 using the 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 chronic non-carcinogenic effects was calculated as 

follows: 

2.5 25 , D RP or P

E TS h h

t

t

t h ⎟× × × ⎠

⎞ ⎜

⎝

⎛ = ∑ (4) 

Where: 

TS = the sum of scores for all substances with non-carcinogenic effects 

t = specific toxic substance 

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

Pt = Acceptable chronic or acute exposure level of t (μg/m3

) 

h = release height (32 meters) 

Dh = Dispersion adjustment factor for h (see Table A-2) 

RPh = 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, the noncancer prioritization score was 17, which was 

based on the chronic effects score. Chlorine and sulfuric acid emissions contributed most 

significantly to the noncancer prioritization score. 
I:\Project\SPI\SPI_Anderson-12692\permit_application\Prioritization_Appendix_anderson-draft_040607.doc 5

The prioritization score calculated using the dispersion adjustment prioritization procedure was 

within the range of 10 to 100 for carcinogens and noncarcinogens. As stated previously, the 

AQMD makes the final decision regarding ranking the facility as a high priority under 

AB2588. 

References 

California Air Pollution Control Officers Association (CAPCOA), 1990, Air Toxics “Hot 

Spots” Program, Facility Prioritization 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 Assessment (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