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Air Quality Impact Analysis for the Gregory Canyon Landfill Project – CO (TPD1308148)

AIR QUALITY IMPACT ANALYSIS FINAL REVIEW REPORT

GREGORY CANYON LANDFILL PROJECT APPLICATION 985364

August 5, 2013

Prepared For Mechanical Engineering

San Diego Air Pollution Control District 10124 Old Grove Road

San Diego, California 92131

Prepared By Ralph DeSiena

Monitoring and Technical Services San Diego Air Pollution Control District

10124 Old Grove Road San Diego, California 92131

1.0 INTRODUCTION

An Air Quality Impact Analysis (AQIA) dated September 14, 2010, (Attachment 1, Volume VII: Updated Air Quality Impact Analysis and Health Risk Assessment) was performed for the Gregory Canyon Landfill (GCL) by Kleinfelder, Inc. (KLF) of San Diego, CA. The September 14, 2010 AQIA is an update (replacement) of previous analyses submitted in 2007 and 2008 (Volume V-Air Quality Impact Analysis) by PCR Corporation of Santa Monica, CA. In addition to the September 14, 2010 AQIA several additional supplemental analyses (Attachment 2, dated 12/29/11, 1/23/12 and 5/2/12) were conducted by KLF at District request in order to evaluate changes in source emissions and other assumptions. This review report summarizes the results of the AQIA and supplemental analyses.

2.0 PROJECT DESCRIPTION

Gregory Canyon Ltd., LLC is proposing to build a Class III non-hazardous (municipal) solid waste landfill, known as the Gregory Canyon Landfill (GCL), on a 308 acre portion of a 1,770 acre property in San Diego County. The actual refuse area footprint covers approximately 183 acres, or roughly 10 percent of the total site. The GCLF project includes construction, operation, and closure of the landfill. GCLF is permitted to receive up to 5,000 tons per day and 1,000,000 tons per year of Class III non-hazardous (municipal) solid waste.

3.0 AIR QUALITY IMPACT ANALYSIS

Dispersion modeling was conducted for potential emissions from landfill construction and operations. The emissions, including fugitive dust from vehicle travel and material handling (e.g., cover soil), landfill gas emissions from a Land Fill Gas Collection System (LFGCS) and fugitive emissions of landfill gas from the landfill surface. Dispersion modeling was conducted for potential emissions of NO₂, CO, SO₂, PM₁₀ and PM_2.5. The Applicant and their consultant, KLF, worked closely with the District in developing modeling and analysis procedures in support of demonstrating compliance with all applicable New Source review (NSR) requirements. Modeling was performed in order to determine whether emissions would result in exceedances of any State and/or Federal Ambient Air Quality Standard for all criteria pollutants, or additional exceedances of a standard if it is already being exceeded (e.g., California 24-hour PM₁₀ standard). Additional modeling was also conducted by the District to determine whether project emissions would result in Significant Impacts at nearby Class I areas; the closest being the Agua Tibia Wilderness Area. Exceedance of Class I area Significant Impact Levels (SILs) for any criteria pollutant would require that some provisions of Prevention of Significant Deterioration (PSD) also be met.

3.1 MODELING METHODOLOGIES

EPA’s AERMOD model was used to assess the potential impact of emissions from the project. In addition, potential emissions from blasting activities were assessed with EPA’s Open Burn/Open Detonation Model (OBODM model, Version 1.3). All modeling was performed in accordance with EPA guidance and District standard procedures. Regulatory default settings were used. The receptor grid was sufficiently dense to identify maximum impacts.

Operations at the landfill vary from year to year in both the magnitude of the activity and location. For purposes of analysis only, the AQIA assumed that 5,000 tons per day of municipal solid waste (MSW) were received on each day of operations (i.e., 307 days per year) and that 1,535,000 tons of MSW were received per year. (Follow-up supplemental analyses requested by the District used 1,000,000 tons per year, as discussed in Section 5). This was done to provide a conservative, worst case assessment that would ensure that the maximum potential air quality impacts of the project were evaluated. Based on this conservative, worst case assumption; the landfill will reach capacity at the end of the 22nd year after first receipt of waste. A set of construction and operational years were selected for analysis of both the emissions and the potential ambient air quality impact of the emissions as follows:

Year -2: This is the first year of construction. Construction activities during this year are the most significant and closest to the property boundaries. The second year of construction (Year -1) will have the same or lower emissions and ambient air quality impacts than Year -1. Therefore Year -2 represents the maximum construction emissions.

Year 1: This is the first year of operation, i.e., year in which MSW is received and placed in the landfill. Year 1 operations are at the toe of the landfill, closest to the property boundaries. In addition, during Year 1 there will be continuing construction activities along with MSW disposal operations.

Year 8: This is the first year of standard operations, where MSW is placed in lifts and additional construction of liners and cells is not needed. Also, at this time, meaningful amounts of landfill gas are being generated.

Year 17: Although operations during Year 17 are essentially the same as Years 8 through 16, according to some landfill gas generation models, Year 17 is the year when landfill gas generation reaches its peak. Therefore, Year 17 was also assessed.

Year 22: This is the final year of operation. Activities are the same as Years 17 through 21, but the locations change.

Year 23: This is the year of closure when final cover is placed and, according to the USEPA landfill gas generation models, the year when landfill gas generation is greatest. After Year 23, there are no more on-site activities other than cover maintenance and operation and maintenance of the LFGCS. Therefore Year 23 represents the maximum combined impact of landfill gas and site operations.

3.2 METEOROLOGICAL DATA USED FOR DISPERSION MODELING

Meteorological data used for EPA’s AERMOD model were prepared by the District using EPA’s AERMET meteorological data processor (Version 06341) to produce AERMOD- ready files. Meteorological years 2002 and 2003 were processed, as on-site meteorological data were obtained by the Applicant for those two years. The data sources were as follows:

Wind speed, wind direction, standard deviation of the horizontal wind direction and temperature from the Applicant’s on-site meteorological monitoring station.

Twice-daily upper-air soundings from Miramar Marine Corps Air Station, San Diego, CA.

Cloud height and total opaque cloud amount from Ramona Airport, Ramona, CA.

Wind speed, wind direction and temperature data from Ramona Airport, Ramona, CA, for replacement of missing data in the Gregory Canyon data set.

4.0 AIR QUALITY IMPACT ANALYSIS RESULTS

In accordance with EPA and San Diego Air Pollution Control District NSR Guidance and the modeling methodologies described above, maximum predicted concentrations associated with facility operations were determined for each of the required criteria pollutants and the applicable averaging period during the five different operating conditions described above. The maximum predicted concentrations occurring during any of the operating conditions modeled were added to worst-case background concentrations for comparison to Federal and State Ambient Air Quality Standards. Worst case background concentrations were determined as follows:

1-hour NO₂: For evaluation with the California standard, the maximum first high 1-hour monitored value from the District’s Escondido monitoring station for calendar years 2007 through 2009 was used. For evaluation with the Federal 1- hour standard (expressed as the 98th percentile), the average daily 7th-high value for calendar years 2007 through 2009 was used. The 7th-high value was chosen because missing data required, in accordance with 40 CFR Part 50 Appendix S, the rank must be decreased.

Annual NO₂: The maximum annual average from Escondido for calendar years 2007 through 2009 was used.

1-hour CO: The maximum 1-hour concentration from Escondido for calendar years 2005 through 2009 was used.

8-hour CO: The maximum 8-hour concentration from Escondido for calendar years 2005 through 2009 was used.

1-hour SO₂: The maximum 1-hour concentration from San Diego for calendar years 2003 through 2005 was used.

3-hour SO₂: The maximum 1-hour concentration from San Diego for calendar years 2003 through 2005 was used.
24-hour SO₂: The maximum 1-hour concentration from San Diego for calendar years 2003 through 2005 was used.

24-hour PM₁₀: The Applicant monitored PM₁₀ at the proposed project site on the EPA-standard once per six day monitoring schedule in calendar years 2002 and 2003. These on-site data were used. Consistent with District policy, when evaluating 24-hour PM₁₀ impacts, a day by day analysis where the maximum impact on a modeled day occurred was added to the maximum background on that day.

Annual PM₁₀: The Applicant’s monitored annual average PM₁₀ data for 2002 and 2003 were not considered representative as the meteorological and emissions characteristics (e.g., wild fires) in 2002 and 2003 are not representative. Therefore, the nearest available PM₁₀ data for non-wildfire years (2004 through 2006) from Aqua Tibia Wilderness were used. However, the 2004 through 2006 Aqua Tibia data were scaled up by the ratio of the on-site annual average data compared to Aqua Tibia for 2002 and 2003. The maximum annual average thus calculated for 2004 through 2006 was used for the annual average background, even though this value was about 20 percent greater than the other two years.

24-hour PM_2.5: There were no on-site PM_2.5 data available, thus the ratio of Aqua Tibia PM_2.5 to PM₁₀ was applied to the on-site PM₁₀ data to derive background PM_2.5 data. Since PM_2.5 impacts are relatively low (i.e., the proposed project is not a significant source of PM_2.5), the maximum 24-hour PM_2.5 concentration from 2002 and 2003 was used for the background. Furthermore, rather than the 98^th percentile, the first-high background value was used

Annual PM_2.5: The same ratio of annual PM₁₀ data from on-site monitoring compared to Aqua _Tibia wa_s used to derive an annual PM_2.5 concentration based on Aqua Tibia data from 2004 through 2006. The highest annual average from the three years was used.

Table 4-1 summarizes the worst case backgrou_nd concentrations used in the impact assessment. The Escondido data were from the California Air ^Resources Board air quality data web site. The Aqua Tibia data were from the IMPROVE web site. The maximum values used in the impact assessment are shown in bold font.

TABLE 4-1

MAXIMUM BACKGROUND CONCENTRATIONS for the PROJECT AREA

(µg/m³)

Pollutant	Averaging Time	Data Source	Calendar Year/Value
			2007	2008	2009
NO ¹ 2	1-hour 1^st-high	Escondido	135	152	137
	1-hour 7^th-high	Escondido	113	134	109
	1-hour 7^th-high, 3- year average	Escondido		118
	Annual	Escondido	30	34	30
			2003	2004	2005
SO₂	1-hour		94	110	105
	3-hour		94³	110³	105³
	24-hour		21	24	24
			2005	2006	2007
CO²	1-hour	Escondido	6743	6514	5943
CO²	8-hour	Escondido	3543	4114	3657
				2002	2003
PM₁₀	24-hour	On-Site		32.9	36.9
			2004	2005	2006
	Annual	On-Site Adjusted	17.6	14.4	15.0
				2002	2003
PM2.5	24-hour	On-Site based on Aqua Tibia		13.8	15.5
			2004	2005	2006
	Annual	On-Site based on Aqua Tibia	7.2	6.2	6.9

Source: Applicant’s AQIA dated September 14, 2010

¹ Conversion of NO2 ppm to ug/m³ is at sea level and 25 degrees C (0.100 ppm = 188 ug/m³)

² Conversion of CO ppm to ug/m³ is at sea level and 25 degrees C (1.0 ppm = 1143 ug/m³)

³ Used 1-hour SO2 background value

Table 4-2 summarizes the ambient air quality impact of the proposed project as evaluated by the District. The maximum impact from the various operational years and meteorological year is reported. All of the total impacts are less than standards.

TABLE 4-2

AMBIENT AIR QUALITY IMPACT MODELING RESULTS

(µg/m³)

Pollutant		Back- ground	Maximum Modeled Impact AERMOD	Total Impact	Operational Year	Meteorological Year	California Standard	Federal Standard
NO₂	1-hour 1^st High	152	69.8	221.8	Year -2	2002	339	—
	1-hour 7^th High¹	118	69.8	187.8	Year -2	2002	—	188
	Annual	34	1.0⁶	35.0	Year 23	2002	57	100
CO²	1-hour	6,743	94⁶	6,837	Year 23	2003	23,000	40,000
	8-hour	4,114	22⁶	4,136	Year 23	2003	10,000	10,000
SO₂	1-hour	110	106⁶	216	Year 23	2003	655	—
SO₂	3-hour	110⁴	59⁶	169	Year 23	2003	—	1300
SO₂	24-hour	24	12⁶	36	Year 23	2003	105	—
SO₂	Federal 1-hour	110⁴	815,6	191	Year 23	2003	—	196
PM₁₀	24-hour²	36.9	12.9⁶	49.8	Year 22	October 24, 2003	50	150
	Annual	17.6	2.4	20.0	Year 1	2003	20	—
PM_2.5	24-hour³	15.5	8.3	23.8	Year -2	2003	—	35
	Annual	7.2	1.0⁶	8.2	Year 22	2003	12	15

Source: Applicant AQIA dated September 14, 2010 as updated by letters dated December 29, 2011 and January 23, 2012 for annual PM10, and May 2, 2012 for CO, annual NO2, 24-hour PM10 and annual PM2.5.

¹ 1^st-high NO2 impact added to the 3-year average 7^th-high background value, overstating the impact with respect to the Federal standard.

² Maximum PM10 impact evaluated by adding the maximum impact on a monitored day to background on that day. ³ 1^st-high PM2.5 impact added to 1^st-high background, thus significantly over-stating impact with respect to the Federal standard which is the 3-year average 98^th percentile.

4 1-hour maximum SO2 background value.

⁵ 99^th percentile SO2 value.

⁶ Includes updated flare location impact per May 2, 2012 supplemental analyses

5.0 SUPLEMENTAL ANALYSES

The District evaluated in detail the emissions and impact modeling presented in the Applicant’s September 14, 2010 AQIA. As a result of that evaluation, the District requested a number of supplemental analyses to evaluate changes in emission and operational scenarios. These supplemental analyses were conducted to ensure that the maximum potential impact of the proposed project was considered. The supplemental analyses were as follows:

Calculate landfill gas emissions with an assumed waste in place density of 0.85 tons per cubic yard, 1,000,000 tons per year of MSW received, and 90,565 tons per year of processed green material (PGM) used as alternative daily cover,

assuming that the PGM generates landfill gas at the same rate as MSW. (Analysis submitted in letters dated December 29, 2011; and January 23, 2012

and May 2, 2012.)

Change all road speeds to 15 mph from 7.5 mph to reflect the permit condition that the applicant was willing to accept. However, the applicant used a nonrepresentative speed for scrapers, 6 mph, on a key portion of the BAA haul road when modeling 24-hour PM10 emission impacts.

Decrease the annual amount of waste received from 1.535,000 tons per year to 1,000,000 tons per year (daily maximum waste received remained at 5000 tons per day).

Increase required control efficiency on the unpaved, unstabilized portion of haul roads to 95% from 90%.

Remove any control efficiency credit for rain from 24-hour PM₁₀ and PM_2.5 modeling.Change the vehicle mix to a more representative mix (i.e., greater number of vehicles, wheels, and weights) than was modeled in the September 14, 2010 AQIA. (Analysis submitted in letter dated December 29, 2011.)

Change the road widths to values requested by the District. (Analysis submitted in letter dated December 29, 2011.) However, the applicant failed to change the corresponding volume source parameters appropriately for a section of the paved road as recommended by the District.

Change the location of modeled Year 1 activities to be closer to the property boundary and change the road alignment to reduce the grade of the road and add additional wind erosion area. (Analysis submitted in letter dated December 29, 2011.)

Change all road alignments such that the grade of the road is less than about 15 percent. (Analysis submitted in letter dated December 29, 2011.) However, a District analysis indicates that some internal haul roads in the modeling scenario significantly exceed 15%—the maximum the District believes is reasonable and the maximum identified in the Joint Technical Document (JTD). The main waste haul road has a gradient of about 7%, which the District finds is reasonable for a road for on-road vehicles, except for a short portion as it enters the landfill footprint). The District adjusted emissions from these roads in the engineering analysis to account for the excessive grades, which shorten the roads and reduce the estimated particulate emissions from their representative levels. In addition, the elevation levels of certain roads—especially the Borrow Area B Road in Year -2, were not representative of expected elevation levels.

Change the location of material handling at the Borrow/Stockpile Areas A and B such that the daily activities are at the closest possible location to the property boundary and internal borrow/stockpile road lengths are greatest. (Analysis submitted in letter dated December 29, 2011.)
Add additional disturbed acreage subject to wind erosion. (Analysis submitted in letter dated December 29, 2011.)

Change flares station location and emissions to a location consistent with the JTD. (Analysis submitted in letter dated May 2, 2012.)

The various supplemental analyses resulted in changes to the maximum potential impacts of the proposed project from those presented in the September 14, 2010 AQIA, as follows:

The December 29, 2011, and January 23, 2012 applicant’s supplemental analyses showed that if the vehicle mix, road widths, road alignments and grades, locations for material handling, and areas subject to potential wind erosion were all changed to a worst case combination, the maximum annual PM₁₀ impact of the proposed project increased by 0.5 percent (total impact of

20.0 µg/m³ instead of 19.9 µg/m³). However, after adjustment by the District to representative operational parameters and District emission factors, the impacts increased significantly in some scenarios (see the engineering evaluation for the details).

The May 2, 2012 supplemental analysis showed that if the flare station were located closer to the toe of landfill, the annual PM₁₀ and PM_2.5 impact increases by 4 percent, about 0.1 µg/m³, the annual NO₂ increases by 0.6 percent, and the 1-hour CO impact increases by 0.01 percent; but all impacts were below the applicable ambient air quality standards.

5.1 SUPLEMENTAL ANALYSES FOR 24-HOUR PM₁₀ IMPACTS

In order to ensure that project emissions during certain years of operation would not result in a violation of the California 24-Hour PM₁₀ standard all days that the background PM10 was monitored were modeled by the District. The results of this modeling are presented in Table 5.1 below. The maximum impact values resulting from the supplemental analyses are also included in Table 4-2.

PM10 MODELING RESULTS FOR MONITORED BACKGROUND DAYS

Model Run ID

Run Description

Operational Year and Averaging Time

Modeled Impact (µg/m³)

Year/Day of Modeled Impact

Background (µg/m³)

Modeled Impact Plus Background

(µg/m³)

S25

Unload soil at Borrow Area A

next to the edge of the Borrow Area on the south end

Year -2 24-hour

12.8

10/24/2003

36.9

49.7

S27

Landfill activities on eastern edge of first 23 acres and unload soil next to the edge of Borrow

Area B in the southwest corner

Year 1 24-hour

40.0

1/9/2003

9.7

49.7

S28

Landfill activities on eastern edge of first 23 acres and unload soil next to the edge of Borrow Area B

in the southeast corner

Year 1 24-hour

11.3

10/24/2003

36.9

48.2

S33

Load soil (no excavation) next to

edge of Borrow Area A in the northwest corner

Year 22 24-hour

20.1

10/24/2003

36.9

57.0

S33B

Excavate and load soil 44 meters away from edge of Borrow Area A in the northwest

corner

Year 22 24-hour

12.8

10/24/2003

36.9

49.7

S34

Load soil (no excavation) next to

edge of Borrow Area A in the southwest corner

Year 22 24-hour

17.5

10/24/2003

36.9

54.4

S34B

Excavate and load soil 44 meters

away from edge of Borrow Area A in the southwest corner

Year 22 24-hour

12.7

10/24/2003

36.9

49.6

The results indicate that in Year 22 excavating and loading soil from Borrow Area A must occur no closer than 44 meters from the edge of the northwest corner of the area and no closer than 44 meters from the edge of the southwest corner of the area in order to not cause and exceedance of the California 1-Hour PM₁₀ standard.

5.2 SUPLEMENTAL ANALYSES FOR REVISED FLARE EMISSIONS AND LOCATIONS

Predicted impacts for the flares were included in the applicant’s September 14, 2010 AQIA. This modeling was revised to reflect both manufacturer’s guaranteed emission factors and new flare locations that were based upon information contained in the Gregory Canyon Landfill Joint Technical Document (JTD). A comparison of the results determined in the AQIA and supplemental analyses are shown in Table 5.2 below. The maximum impact values resulting from the supplemental analyses are also included in Table 4-2.

PMODELING RESULTS FOR REVISED FLARE EMISSIONS AND LOCATIONS

Operating Year	Pollutant and Averaging Time	Meteorological Year and Model Run	Impact with AQIA Flare Location and Emissions (µg/m³)	Impact with JTD Flare Location and Updated Emissions (µg/m³)	Background (µg/m³)	Total Impact (µg/m³)	Most Stringent Standard (µg/m³)
22	24-hour PM₁₀	2003 Supplemental Run S33B	12.8	12.9	36.9 October 24, 2003	49.8	50
22	24-hour PM₁₀	2003 Supplemental Run S34B	12.7	12.8	36.9 October 24, 2003	49.7	50
22	Annual PM₁₀	2003 Supplemental Run S32	2.1	2.1	17.6	19.7	20
22	24-hour PM2.5	2003 AQIA Run	7.6	7.6	15.5	23.1	35
22	Annual PM2.5	2003 AQIA Run	0.7	1.0	7.2	8.2	12
23	1-hour 1^st High NO₂	2003 AQIA Run	38.6	37.7	152	189.7	339
23	1-hour 7^th High NO₂	2003 AQIA Run	38.6	37.7	118	155.7	188
23	Annual NO₂	2002 AQIA Run	0.8	1.0	34	35.0	57
23	1-hour CO	2003 New Run	36.2	93.6	6743	6836	23000
23	8-hour CO	2003 New Run	11.4	21.9	4114	4136	8000

5.3 SUPLEMENTAL ANALYSES FOR AFTER-HOURS OPERATIONS

Normal operating hours for the Gregory Canyon Landfill are 7:00 A.M. to 6 P.M. Monday through Friday and 8:00 A.M. to 5:00 P.M. on Saturdays. The applicant asked if they could perform certain operations, such as transporting cover material to the active landfill face, after closing. The District performed additional modeling to simulate one additional hour per day for a maximum of 66 days per year for these activities. Predicted maximum annual PM10 impacts were determined for operational years 1, 8, 17 and 22. These predicted impacts were compared to the California annual PM10 standard. No violation of this standard will results from the requested additional landfill operations. The results are provided in Table 5.3 below.

PM10 ANNUAL IMPACTS FOR THE INCLUSION OF AFTER HOURS OPERATIONS

Operational Year and Averaging Time	Modeled Impact (µg/m³)	Background (µg/m³)	Total Impact (µg/m³)	California Standard
Year 1 Annual	2.7	17.6	20¹	20
Year 8 Annual	2.8	17.6	20¹	20
Year 17 Annual	1.8	17.6	19¹	20
Year 22 Annual	2.3	17.6	20¹	20

¹ Value rounded to the closest integer per the form of the California annual standard

5.4 SUPLEMENTAL ANALYSES FOR 24-HOUR PM₁₀ IMPACTS BY OPERATION/ SOURCE GROUP)

The District performed additional modeling for facility operations occurring in Years

-2, 1, 17 and 22 in order to determine the maximum predicted impact for all sources and the predicted impact resulting from each facility operation as defined by a source group for each year modeled. The latest version of AERMOD (12345) was used for this modeling. Changes to the model formulation resulted in some differences to the maximum predicted impact value and location for all sources for each year modeled. Table 5.4.1 summarizes the results for the 24-Hour maximum impact plus background day for the operational years modeled. Tables 5.4.2 through 5.4.8 provide summaries of the maximum predicted 24-Hour impact plus background concentration for all days modeled (monitored background days) for each year modeled. Tables 5.4.9 through 5.4.15 provide the 24-Hour predicted impact by each source group for the maximum impact plus background day at the maximum impacted receptor for each year modeled. Tables 5.4.16 through 5.4.19 provide the maximum predicted annual impact for each source group at the point of maximum impact (PMI) receptor.

The results provided here are without additional adjustments to operational parameters and emission factors to ensure the actual potential to emit was modeled in each scenario. These adjustments are discussed in the Engineering Evaluation. As also discussed in the Engineering Evaluation, the resulting impacts from the adjusted values were used to develop emission impact equations that are used to establish permit conditions that will ensure compliance with all Federal and California PM₁₀ air quality standards.

TABLE 5.4.1

SUMMARY OF MAXIMUM 24-H0UR PM₁₀ IMPACT PLUS BACKGROUND MODEL RUN RESULTS

Model Run	UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
S25	488659.8	3688456	11.181	3102424	36.9	48.08
S27	489288.9	3688007	7.958	3102424	36.9	44.86
S28	489988.7	3688024	36.348	3121724	16.9	53.25
S31	489938.7	3688023	8.782	3102424	36.9	45.68
S33B	488662.6	3688706	14.161	3102424	36.9	51.06
S33	488662.6	3688706	39.815	3121724	16.9	56.72
S34	488662.1	3688656	11.879	3102424	36.9	48.78

TABLE 5.4.2

YEAR -2, 24-H0UR PM₁₀ IMPACT PLUS BACKGROUND MODEL RESULTS FOR ALL PM₁₀ MONITORING DAYS (MODEL RUNS25)

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
488659.8	3688456.3	28.174	3010924	9.7	37.874
492317.5	3692143.9	0.000	3020224	32.6	32.600
488659.8	3688456.3	13.556	3020824	13.5	27.056
488659.8	3688456.3	9.295	3021524	10.1	19.395
488659.8	3688456.3	13.277	3022024	13	26.277
488659.8	3688456.3	8.969	3022624	10.3	19.269
488659.8	3688456.3	23.243	3030424	7	30.243
492317.5	3692143.9	0.000	3031024	19.3	19.300
492317.5	3692143.9	0.000	3031624	13.2	13.200
492317.5	3692143.9	0.000	3032224	17.7	17.700
488659.8	3688456.3	14.976	3032824	15.2	30.176
492317.5	3692143.9	0.000	3040324	9.2	9.200
488659.2	3688406.3	9.196	3040924	19.7	28.896
488659.2	3688406.3	15.098	3041524	8.5	23.598
488659.8	3688456.3	11.375	3042324	13.1	24.475
492317.5	3692143.9	0.000	3042724	13	13.000
488659.8	3688456.3	6.892	3050924	16.8	23.692
488659.8	3688456.3	9.172	3051524	17.7	26.872
488659.8	3688456.3	5.953	3052124	31.3	37.253
488659.8	3688456.3	3.753	3052724	23.5	27.253
492317.5	3692143.9	0.000	3060224	23.1	23.100

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
492317.5	3692143.9	0.000	3060824	11.6	11.600
492317.5	3692143.9	0.000	3061424	24.2	24.200
488660.4	3688506.3	10.689	3062024	17.8	28.489
488659.8	3688456.3	3.949	3062624	28.8	32.749
488659.8	3688456.3	5.457	3070224	30.4	35.857
488659.8	3688456.3	5.432	3070824	26.7	32.132
488659.8	3688456.3	3.190	3071424	29.9	33.090
491294.7	3689218.6	0.204	3072024	22.1	22.304
488659.8	3688456.3	3.478	3072624	22.6	26.078
488659.8	3688456.3	4.679	3080124	16.2	20.879
488660.4	3688506.3	6.565	3080724	22	28.565
488659.2	3688406.3	9.563	3081324	32.9	42.463
488659.8	3688456.3	4.794	3082524	22.5	27.294
492317.5	3692143.9	0.000	3083124	26	26.000
488659.8	3688456.3	3.588	3090624	36.8	40.388
492317.5	3692143.9	0.000	3091224	28.8	28.800
488659.8	3688456.3	7.094	3091824	32.1	39.194
488659.8	3688456.3	4.001	3092424	33	37.001
488659.8	3688456.3	8.047	3100624	35.1	43.147
491825.1	3689393.9	0.295	3101224	26.8	27.095
488659.8	3688456.3	6.995	3101824	30.5	37.495
488659.8	3688456.3	11.182	3102424	36.9	48.082
490386.7	3689589.2	1.005	3103024	17	18.005
488659.8	3688456.3	10.416	3110524	16.5	26.916
488659.8	3688456.3	15.070	3111124	21.6	36.670
488659.8	3688456.3	20.586	3111724	9.6	30.186
492317.5	3692143.9	0.000	3112324	14.7	14.700
488660.4	3688506.3	13.244	3112924	16.3	29.544
488660.4	3688506.3	31.591	3121124	11.5	43.091
488659.8	3688456.3	20.925	3121724	16.9	37.825

TABLE 5.4.3

YEAR 1, 24-H0UR PM₁₀ IMPACT PLUS BACKGROUND MODEL RESULTS FOR ALL PM₁₀ MONITORING DAYS (MODEL RUN S27)

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
489279.6	3687985	22.978	3010924	9.7	32.678
492317.5	3692144	0.000	3020224	32.6	32.600
490279	3689593	4.601	3020824	13.5	18.101
490328.9	3689591	4.420	3021524	10.1	14.520
489288.9	3688007	8.359	3022024	13	21.359
490229	3689595	6.707	3022624	10.3	17.007
489288.9	3688007	18.144	3030424	7	25.144
491825.1	3689144	2.050	3031024	19.3	21.350
492317.5	3692144	0.000	3031624	13.2	13.200
492317.5	3692144	0.000	3032224	17.7	17.700
489288.9	3688007	11.775	3032824	15.2	26.975
492317.5	3692144	0.000	3040324	9.2	9.200
489088.9	3688002	2.164	3040924	19.7	21.864
489138.9	3688003	7.796	3041524	8.5	16.296
489288.9	3688007	4.317	3042324	13.1	17.417
492317.5	3692144	0.000	3042724	13	13.000
490279	3689593	5.123	3050924	16.8	21.923
490378.9	3689590	3.092	3051524	17.7	20.792
491291.8	3688919	1.775	3052124	31.3	33.075
491292.3	3688969	2.390	3052724	23.5	25.890
492317.5	3692144	0.000	3060224	23.1	23.100
492317.5	3692144	0.000	3060824	11.6	11.600
492317.5	3692144	0.000	3061424	24.2	24.200
490079.1	3689600	10.166	3062024	17.8	27.966
490328.9	3689591	4.461	3062624	28.8	33.261
489288.9	3688007	2.637	3070224	30.4	33.037
490029.1	3689602	2.455	3070824	26.7	29.155
490328.9	3689591	3.077	3071424	29.9	32.977
491288.8	3688619	0.338	3072024	22.1	22.438
491291.8	3688919	2.324	3072624	22.6	24.924
491290.8	3688819	1.857	3080124	16.2	18.057
488939	3687998	2.114	3080724	22	24.114
489088.9	3688002	3.855	3081324	32.9	36.755
491291.8	3688919	1.882	3082524	22.5	24.382
492317.5	3692144	0.000	3083124	26	26.000
490386.7	3689589	2.963	3090624	36.8	39.763

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
491290.8	3688819	0.993	3091224	28.8	29.793
489288.9	3688007	3.845	3091824	32.1	35.945
491291.3	3688869	3.701	3092424	33	36.701
489288.9	3688007	3.855	3100624	35.1	38.955
491289.8	3688719	0.523	3101224	26.8	27.323
489238.9	3688005	3.196	3101824	30.5	33.696
489288.9	3688007	7.958	3102424	36.9	44.858
490386.7	3689589	3.038	3103024	17	20.038
490079.1	3689600	12.081	3110524	16.5	28.581
489288.9	3688007	9.576	3111124	21.6	31.176
489238.9	3688005	14.817	3111724	9.6	24.417
492317.5	3692144	0.000	3112324	14.7	14.700
490029.1	3689602	11.150	3112924	16.3	27.450
489288.9	3688007	23.894	3121124	11.5	35.394
490079.1	3689600	21.002	3121724	16.9	37.902

TABLE 5.4.4

YEAR 1, 24-H0UR PM₁₀ IMPACT PLUS BACKGROUND MODEL RESULTS FOR ALL PM₁₀ MONITORING DAYS (MODEL RUN S28)

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
489988.7	3688023.9	30.261	3010924	9.7	39.96
492317.5	3692143.9	0.000	3020224	32.6	32.60
489988.7	3688023.9	9.064	3020824	13.5	22.56
489938.7	3688022.7	9.196	3021524	10.1	19.30
489938.7	3688022.7	17.661	3022024	13	30.66
489988.7	3688023.9	10.238	3022624	10.3	20.54
489938.7	3688022.7	37.822	3030424	7	44.82
489988.7	3688023.9	2.564	3031024	19.3	21.86
492317.5	3692143.9	0.000	3031624	13.2	13.20
492317.5	3692143.9	0.000	3032224	17.7	17.70
489938.7	3688022.7	20.746	3032824	15.2	35.95
492317.5	3692143.9	0.000	3040324	9.2	9.20
489938.7	3688022.7	6.585	3040924	19.7	26.28
489938.7	3688022.7	12.875	3041524	8.5	21.38
489938.7	3688022.7	11.985	3042324	13.1	25.08
492317.5	3692143.9	0.000	3042724	13	13.00
489938.7	3688022.7	6.921	3050924	16.8	23.72

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
489938.7	3688022.7	7.626	3051524	17.7	25.33
489938.7	3688022.7	5.342	3052124	31.3	36.64
489988.7	3688023.9	3.634	3052724	23.5	27.13
492317.5	3692143.9	0.000	3060224	23.1	23.10
492317.5	3692143.9	0.000	3060824	11.6	11.60
492317.5	3692143.9	0.000	3061424	24.2	24.20
489988.7	3688023.9	10.746	3062024	17.8	28.55
490386.7	3689589.2	4.259	3062624	28.8	33.06
489938.7	3688022.7	6.937	3070224	30.4	37.34
489988.7	3688023.9	5.774	3070824	26.7	32.47
489988.7	3688023.9	3.362	3071424	29.9	33.26
491288.8	3688618.6	0.338	3072024	22.1	22.44
489988.7	3688023.9	3.840	3072624	22.6	26.44
489988.7	3688023.9	4.941	3080124	16.2	21.14
489938.7	3688022.7	4.861	3080724	22	26.86
489938.7	3688022.7	6.153	3081324	32.9	39.05
489988.7	3688023.9	4.400	3082524	22.5	26.90
492317.5	3692143.9	0.000	3083124	26	26.00
489988.7	3688023.9	3.996	3090624	36.8	40.80
489988.7	3688023.9	1.053	3091224	28.8	29.85
489938.7	3688022.7	8.067	3091824	32.1	40.17
489988.7	3688023.9	4.602	3092424	33	37.60
489938.7	3688022.7	8.715	3100624	35.1	43.81
491289.8	3688718.6	0.523	3101224	26.8	27.32
489938.7	3688022.7	7.432	3101824	30.5	37.93
489988.7	3688023.9	13.937	3102424	36.9	50.84
490386.7	3689589.2	3.004	3103024	17	20.00
489988.7	3688023.9	19.774	3110524	16.5	36.27
489938.7	3688022.7	16.147	3111124	21.6	37.75
489938.7	3688022.7	26.890	3111724	9.6	36.49
492317.5	3692143.9	0.000	3112324	14.7	14.70
489988.7	3688023.9	16.880	3112924	16.3	33.18
489988.7	3688023.9	32.987	3121124	11.5	44.49
489988.7	3688023.9	36.348	3121724	16.9	53.25

TABLE 5.4.5

YEAR 17, 24-H0UR PM₁₀ IMPACT PLUS BACKGROUND MODEL RESULTS FOR ALL PM₁₀ MONITORING DAYS (MODEL RUN S31)

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
489854.6	3687985.1	17.046	3010924	9.7	26.75
490462.6	3689995.4	0.174	3020224	32.6	32.77
489938.7	3688022.7	5.515	3020824	13.5	19.01
489938.7	3688022.7	7.730	3021524	10.1	17.83
489938.7	3688022.7	16.590	3022024	13	29.59
489938.7	3688022.7	11.247	3022624	10.3	21.55
489938.7	3688022.7	34.456	3030424	7	41.46
491825.1	3689643.9	1.581	3031024	19.3	20.88
489769.6	3689681.4	0.133	3031624	13.2	13.33
487325.1	3688143.9	0.275	3032224	17.7	17.98
489938.7	3688022.7	23.582	3032824	15.2	38.78
488268.7	3689967.2	0.138	3040324	9.2	9.34
489888.7	3688021.5	6.475	3040924	19.7	26.18
489888.7	3688021.5	16.790	3041524	8.5	25.29
489938.7	3688022.7	9.321	3042324	13.1	22.42
489575.1	3691643.9	0.208	3042724	13	13.21
489938.7	3688022.7	5.240	3050924	16.8	22.04
489888.7	3688021.5	6.012	3051524	17.7	23.71
489938.7	3688022.7	3.514	3052124	31.3	34.81
489938.7	3688022.7	2.415	3052724	23.5	25.92
490344.6	3689681.4	0.249	3060224	23.1	23.35
490403.6	3689679.8	0.468	3060824	11.6	12.07
490328.9	3689591.2	0.083	3061424	24.2	24.28
490002.8	3689602.5	6.784	3062024	17.8	24.58
490386.7	3689589.2	3.488	3062624	28.8	32.29
489938.7	3688022.7	5.656	3070224	30.4	36.06
489938.7	3688022.7	2.861	3070824	26.7	29.56
490386.7	3689589.2	2.524	3071424	29.9	32.42
490458.7	3689974.7	0.416	3072024	22.1	22.52
491292.8	3689018.6	1.978	3072624	22.6	24.58
490138.6	3688027.7	2.724	3080124	16.2	18.92
489938.7	3688022.7	3.623	3080724	22	25.62
489888.7	3688021.5	6.090	3081324	32.9	38.99
489938.7	3688022.7	3.237	3082524	22.5	25.74
490328.9	3689591.2	0.305	3083124	26	26.31

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
489988.7	3688023.9	2.136	3090624	36.8	38.94
491291.8	3688918.6	0.924	3091224	28.8	29.72
489938.7	3688022.7	7.483	3091824	32.1	39.58
491292.8	3689018.6	3.208	3092424	33	36.21
489938.7	3688022.7	8.217	3100624	35.1	43.32
489122.9	3690174.5	0.396	3101224	26.8	27.20
489938.7	3688022.7	6.574	3101824	30.5	37.07
489938.7	3688022.7	8.782	3102424	36.9	45.68
490229	3689594.7	1.765	3103024	17	18.76
490079.1	3689599.9	9.566	3110524	16.5	26.07
489938.7	3688022.7	18.348	3111124	21.6	39.95
489888.7	3688021.5	18.398	3111724	9.6	28.00
488267.4	3689867.2	0.323	3112324	14.7	15.02
489929.6	3687960.1	9.042	3112924	16.3	25.34
490029.1	3689601.6	18.289	3121124	11.5	29.79
489929.6	3687960.1	16.598	3121724	16.9	33.50

TABLE 5.4.6

YEAR 22, 24-H0UR PM₁₀ IMPACT PLUS BACKGROUND MODEL RESULTS FOR ALL PM₁₀ MONITORING DAYS (MODEL RUN S33)

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
488662.6	3688706.3	32.627	3010924	9.7	42.33
490462.6	3689995.4	0.217	3020224	32.6	32.82
488663.2	3688756.3	21.303	3020824	13.5	34.80
488662.6	3688706.3	14.458	3021524	10.1	24.56
488662.6	3688706.3	20.895	3022024	13	33.89
488662.6	3688706.3	12.918	3022624	10.3	23.22
488662.6	3688706.3	30.159	3030424	7	37.16
488662.6	3688706.3	2.693	3031024	19.3	21.99
489769.6	3689681.4	0.167	3031624	13.2	13.37
487325.1	3688143.9	0.342	3032224	17.7	18.04
488662.6	3688706.3	24.975	3032824	15.2	40.18
488268.7	3689967.2	0.171	3040324	9.2	9.37
488662.6	3688706.3	21.157	3040924	19.7	40.86
488662.6	3688706.3	24.243	3041524	8.5	32.74
488662.6	3688706.3	16.103	3042324	13.1	29.20

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
489575.1	3691643.9	0.261	3042724	13	13.26
488662.6	3688706.3	9.227	3050924	16.8	26.03
488662.6	3688706.3	16.041	3051524	17.7	33.74
488662.6	3688706.3	11.267	3052124	31.3	42.57
488662.6	3688706.3	5.171	3052724	23.5	28.67
490344.6	3689681.4	0.309	3060224	23.1	23.41
490403.6	3689679.8	0.579	3060824	11.6	12.18
490328.9	3689591.2	0.103	3061424	24.2	24.30
488662.6	3688706.3	12.413	3062024	17.8	30.21
488662.6	3688706.3	4.424	3062624	28.8	33.22
488662.6	3688706.3	7.823	3070224	30.4	38.22
488662.6	3688706.3	6.608	3070824	26.7	33.31
488662.6	3688706.3	3.715	3071424	29.9	33.62
490458.7	3689974.7	0.516	3072024	22.1	22.62
488662.6	3688706.3	4.325	3072624	22.6	26.92
488662.6	3688706.3	5.748	3080124	16.2	21.95
488662.6	3688706.3	10.078	3080724	22	32.08
488662.6	3688706.3	15.165	3081324	32.9	48.06
488662.6	3688706.3	6.613	3082524	22.5	29.11
490328.9	3689591.2	0.379	3083124	26	26.38
488662.6	3688706.3	4.662	3090624	36.8	41.46
488662.6	3688706.3	1.188	3091224	28.8	29.99
488662.6	3688706.3	12.241	3091824	32.1	44.34
488662.6	3688706.3	5.149	3092424	33	38.15
488662.6	3688706.3	9.034	3100624	35.1	44.13
489122.9	3690174.5	0.493	3101224	26.8	27.29
488662.6	3688706.3	13.575	3101824	30.5	44.07
488662.6	3688706.3	19.045	3102424	36.9	55.95
490279	3689592.9	2.495	3103024	17	19.49
488662.6	3688706.3	30.216	3110524	16.5	46.72
488662.6	3688706.3	22.886	3111124	21.6	44.49
488662.6	3688706.3	42.064	3111724	9.6	51.66
488267.4	3689867.2	0.404	3112324	14.7	15.10
488662.6	3688706.3	16.572	3112924	16.3	32.87
488662.6	3688706.3	35.253	3121124	11.5	46.75
488662.6	3688706.3	39.815	3121724	16.9	56.72

TABLE 5.4.7

YEAR 22, 24-H0UR PM₁₀ IMPACT PLUS BACKGROUND MODEL RESULTS FOR ALL PM₁₀ MONITORING DAYS (MODEL RUN S33B)

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
488662.6	3688706.3	27.871	3010924	9.7	37.57
490462.6	3689995.4	0.217	3020224	32.6	32.82
488663.2	3688756.3	16.962	3020824	13.5	30.46
488662.6	3688706.3	9.081	3021524	10.1	19.18
488662.1	3688656.3	13.783	3022024	13	26.78
488662.6	3688706.3	8.294	3022624	10.3	18.59
488662.6	3688706.3	21.236	3030424	7	28.24
488662.6	3688706.3	2.216	3031024	19.3	21.52
489769.6	3689681.4	0.167	3031624	13.2	13.37
487325.1	3688143.9	0.345	3032224	17.7	18.05
488662.6	3688706.3	16.779	3032824	15.2	31.98
488268.7	3689967.2	0.172	3040324	9.2	9.37
488662.6	3688706.3	15.674	3040924	19.7	35.37
488662.1	3688656.3	18.069	3041524	8.5	26.57
488662.6	3688706.3	9.871	3042324	13.1	22.97
489575.1	3691643.9	0.261	3042724	13	13.26
488662.6	3688706.3	5.849	3050924	16.8	22.65
488662.6	3688706.3	9.709	3051524	17.7	27.41
488662.6	3688706.3	8.346	3052124	31.3	39.65
488662.6	3688706.3	3.910	3052724	23.5	27.41
490344.6	3689681.4	0.311	3060224	23.1	23.41
490403.6	3689679.8	0.584	3060824	11.6	12.18
490328.9	3689591.2	0.104	3061424	24.2	24.30
488662.6	3688706.3	7.466	3062024	17.8	25.27
488662.6	3688706.3	2.710	3062624	28.8	31.51
488662.6	3688706.3	5.514	3070224	30.4	35.91
488662.6	3688706.3	4.009	3070824	26.7	30.71
490328.9	3689591.2	2.446	3071424	29.9	32.35
490458.7	3689974.7	0.519	3072024	22.1	22.62
488662.6	3688706.3	2.638	3072624	22.6	25.24
488662.6	3688706.3	3.422	3080124	16.2	19.62
488662.6	3688706.3	6.645	3080724	22	28.64
488662.6	3688706.3	9.649	3081324	32.9	42.55
488662.6	3688706.3	4.602	3082524	22.5	27.10
490328.9	3689591.2	0.381	3083124	26	26.38
488662.6	3688706.3	2.804	3090624	36.8	39.60

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
488662.6	3688706.3	0.893	3091224	28.8	29.69
488662.6	3688706.3	7.817	3091824	32.1	39.92
488662.6	3688706.3	3.273	3092424	33	36.27
488662.6	3688706.3	5.309	3100624	35.1	40.41
489122.9	3690174.5	0.496	3101224	26.8	27.30
488662.6	3688706.3	8.868	3101824	30.5	39.37
488662.6	3688706.3	14.161	3102424	36.9	51.06
490279	3689592.9	2.554	3103024	17	19.55
488662.6	3688706.3	24.135	3110524	16.5	40.64
488662.6	3688706.3	15.207	3111124	21.6	36.81
488662.6	3688706.3	29.654	3111724	9.6	39.25
488267.4	3689867.2	0.405	3112324	14.7	15.11
488662.6	3688706.3	14.799	3112924	16.3	31.10
488662.6	3688706.3	29.180	3121124	11.5	40.68
488662.6	3688706.3	31.747	3121724	16.9	48.65

TABLE 5.4.8

YEAR 22, 24-H0UR PM₁₀ IMPACT PLUS BACKGROUND MODEL RESULTS FOR ALL PM₁₀ MONITORING DAYS (MODEL RUN S34)

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
488662.1	3688656.3	25.627	3010924	9.7	35.33
490462.6	3689995.4	0.217	3020224	32.6	32.82
488660.4	3688506.3	22.959	3020824	13.5	36.46
488659.8	3688456.3	10.187	3021524	10.1	20.29
488659.8	3688456.3	17.251	3022024	13	30.25
488659.8	3688456.3	9.976	3022624	10.3	20.28
488659.8	3688456.3	25.554	3030424	7	32.55
488662.1	3688656.3	1.728	3031024	19.3	21.03
489769.6	3689681.4	0.167	3031624	13.2	13.37
487325.1	3688143.9	0.342	3032224	17.7	18.04
488659.8	3688456.3	21.887	3032824	15.2	37.09
488268.7	3689967.2	0.171	3040324	9.2	9.37
488654.9	3688466.4	15.470	3040924	19.7	35.17
488659.8	3688456.3	22.316	3041524	8.5	30.82
488659.8	3688456.3	10.329	3042324	13.1	23.43
489575.1	3691643.9	0.261	3042724	13	13.26
488659.8	3688456.3	5.770	3050924	16.8	22.57

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
488659.8	3688456.3	10.983	3051524	17.7	28.68
488654.9	3688491.4	8.221	3052124	31.3	39.52
488654.9	3688491.4	4.172	3052724	23.5	27.67
490344.6	3689681.4	0.309	3060224	23.1	23.41
490403.6	3689679.8	0.579	3060824	11.6	12.18
490328.9	3689591.2	0.103	3061424	24.2	24.30
488662.1	3688656.3	10.823	3062024	17.8	28.62
488662.1	3688656.3	3.387	3062624	28.8	32.19
488660.4	3688506.3	6.212	3070224	30.4	36.61
488662.1	3688656.3	4.890	3070824	26.7	31.59
488662.1	3688656.3	2.776	3071424	29.9	32.68
490458.7	3689974.7	0.516	3072024	22.1	22.62
488662.1	3688656.3	3.090	3072624	22.6	25.69
488662.1	3688656.3	4.073	3080124	16.2	20.27
488659.8	3688456.3	7.108	3080724	22	29.11
488659.8	3688456.3	11.821	3081324	32.9	44.72
488654.9	3688491.4	4.739	3082524	22.5	27.24
490328.9	3689591.2	0.379	3083124	26	26.38
488662.1	3688656.3	3.271	3090624	36.8	40.07
488662.1	3688656.3	0.738	3091224	28.8	29.54
488659.8	3688456.3	9.118	3091824	32.1	41.22
488662.1	3688656.3	3.546	3092424	33	36.55
488662.1	3688656.3	6.829	3100624	35.1	41.93
489122.9	3690174.5	0.493	3101224	26.8	27.29
488659.8	3688456.3	10.505	3101824	30.5	41.00
488662.1	3688656.3	11.879	3102424	36.9	48.78
490279	3689592.9	2.510	3103024	17	19.51
488654.9	3688491.4	20.198	3110524	16.5	36.70
488659.8	3688456.3	18.591	3111124	21.6	40.19
488659.8	3688456.3	26.600	3111724	9.6	36.20
488267.4	3689867.2	0.404	3112324	14.7	15.10
488662.1	3688656.3	11.331	3112924	16.3	27.63
488662.1	3688656.3	24.939	3121124	11.5	36.44
488662.1	3688656.3	26.581	3121724	16.9	43.48

TABLE 5.4.9

YEAR -2, 24-H0UR PM₁₀ IMPACTS BY OPERATION (MODEL RUN S25)

GROUP ID	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.01938	3102424	488659.8	3688456	107.27	560.61
UPS	0.00732	3102424	488659.8	3688456	107.27	560.61
UP	0.03178	3102424	488659.8	3688456	107.27	560.61
FILLRD	0.10524	3102424	488659.8	3688456	107.27	560.61
SPBRD	0.00413	3102424	488659.8	3688456	107.27	560.61
SPARD	5.40711	3102424	488659.8	3688456	107.27	560.61
SPAUN	1.91846	3102424	488659.8	3688456	107.27	560.61
FILLUN	0.03414	3102424	488659.8	3688456	107.27	560.61
LFEXCAV	0.49153	3102424	488659.8	3688456	107.27	560.61
LFWIND	0	0	0	0	0	0
SPAWIND	0	0	0	0	0	0
SPBWIND	0	0	0	0	0	0
BLAST	0	0	0	0	0	0
ROCKCR	0.01988	3102424	488659.8	3688456	107.27	560.61
CLAYLIN	0.03086	3102424	488659.8	3688456	107.27	560.61
SPBRDELF	0.00032	3102424	488659.8	3688456	107.27	560.61
SPBRDESP	0.00019	3102424	488659.8	3688456	107.27	560.61
SPARDESP	3.01993	3102424	488659.8	3688456	107.27	560.61
SPARDELF	0.05291	3102424	488659.8	3688456	107.27	560.61
DRILL	0	0	0	0	0	0
ROCKLOAD	0	0	0	0	0	0
SPBUN	0	0	0	0	0	0
SPBUNX	0.03861	3102424	488659.8	3688456	107.27	560.61
ALL	11.18179	3102424	488659.8	3688456	107.27	560.61

TABLE 5.4.10

YEAR 1, 24-H0UR PM₁₀ IMPACTS BY OPERATION (MODEL RUN S27)

GROUP ID	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.00902	3102424	489288.9	3688007	207.3	560.6
UPS	0.03101	3102424	489288.9	3688007	207.3	560.6
UP	0.02128	3102424	489288.9	3688007	207.3	560.6
LFRD	0.01146	3102424	489288.9	3688007	207.3	560.6
DCRD	0.05963	3102424	489288.9	3688007	207.3	560.6
FILLRD	0.0014	3102424	489288.9	3688007	207.3	560.6

GROUP ID	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
SPBRD	3.16076	3102424	489288.9	3688007	207.3	560.6
DCUNLOAD	0.01086	3102424	489288.9	3688007	207.3	560.6
FILLUN	0.06269	3102424	489288.9	3688007	207.3	560.6
SPBUN	1.57248	3102424	489288.9	3688007	207.3	560.6
CLAYLIN	0.03605	3102424	489288.9	3688007	207.3	560.6
ROCKCR	0.02778	3102424	489288.9	3688007	207.3	560.6
ROCKLOAD	0.0233	3102424	489288.9	3688007	207.3	560.6
DRILL	0	0	0	0	0.0	0.0
BLAST	0	0	0	0	0.0	0.0
AFWIND	0	0	0	0	0.0	0.0
SPBWIND	0	0	0	0	0.0	0.0
LFUNWIND	0	0	0	0	0.0	0.0
LFWIND	0	0	0	0	0.0	0.0
DCRDELF	0.00326	3102424	489288.9	3688007	207.3	560.6
DCRDESP	0.02129	3102424	489288.9	3688007	207.3	560.6
RKRDEBLT	0.00091	3102424	489288.9	3688007	207.3	560.6
RKRD	0.00108	3102424	489288.9	3688007	207.3	560.6
SPBRELF	0.04593	3102424	489288.9	3688007	207.3	560.6
SPBRDESP	2.07505	3102424	489288.9	3688007	207.3	560.6
ALL	7.95907	3102424	489288.9	3688007	207.3	560.6

TABLE 5.4.11

YEAR 1, 24-H0UR PM₁₀ IMPACTS BY OPERATION (MODEL RUN S28)

GROUP ID	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.01044m	3121724	489988.7	3688024	293.92	560.61
UPS	0.03314m	3121724	489988.7	3688024	293.92	560.61
UP	0.01575m	3121724	489988.7	3688024	293.92	560.61
LFRD	0.00985m	3121724	489988.7	3688024	293.92	560.61
DCRD	0.02432m	3121724	489988.7	3688024	293.92	560.61
FILLRD	0.00025m	3121724	489988.7	3688024	293.92	560.61
SPBRD	7.04787m	3121724	489988.7	3688024	293.92	560.61
DCUNLOAD	0.00656m	3121724	489988.7	3688024	293.92	560.61
FILLUN	0.01114m	3121724	489988.7	3688024	293.92	560.61
LFEXCAV	0.14716m	3121724	489988.7	3688024	293.92	560.61
SPBUN	17.65647m	3121724	489988.7	3688024	293.92	560.61
CLAYLIN	0.00669m	3121724	489988.7	3688024	293.92	560.61
ROCKCR	0.00585m	3121724	489988.7	3688024	293.92	560.61

GROUP ID	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
ROCKLOAD	0.00363m	3121724	489988.7	3688024	293.92	560.61
DRILL	0	0	0	0	0	0
BLAST	0	0	0	0	0	0
AFWIND	0	0	0	0	0	0
SPBWIND	0	0	0	0	0	0
LFUNWIND	0	0	0	0	0	0
LFWIND	0	0	0	0	0	0
DCRDELF	0.00210m	3121724	489988.7	3688024	293.92	560.61
DCRDESP	0.00399m	3121724	489988.7	3688024	293.92	560.61
RKRDEBLT	0.00015m	3121724	489988.7	3688024	293.92	560.61
SPBRDELF	0.00836m	3121724	489988.7	3688024	293.92	560.61
RKRD	0.00020m	3121724	489988.7	3688024	293.92	560.61
SPBRDESP	11.35415m	3121724	489988.7	3688024	293.92	560.61
ALL	36.34807m	3121724	489988.7	3688024	293.92	560.61

TABLE 5.4.12

YEAR 17, 24-H0UR PM₁₀ IMPACTS BY OPERATION (MODEL RUN S31)

GROUP ID	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.00783	3102424	489938.7	3688022.7	289.87	560.61
UPS	0.22242	3102424	489938.7	3688022.7	289.87	560.61
UP	0.1437	3102424	489938.7	3688022.7	289.87	560.61
BABROAD	0.91625	3102424	489938.7	3688022.7	289.87	560.61
FLARES	0.03754	3102424	489938.7	3688022.7	289.87	560.61
BABWIND	0	0	0	0	0	0
BABUNWD	0	0	0	0	0	0
LFWIND	0	0	0	0	0	0
LFUNWIND	0	0	0	0	0	0
LFDRD	0.15892	3102424	489938.7	3688022.7	289.87	560.61
BABOPS	7.0283	3102424	489938.7	3688022.7	289.87	560.61
ROCKCR	0.04966	3102424	489938.7	3688022.7	289.87	560.61
BLAST	0	0	0	0	0	0
DRILL	0	0	0	0	0	0
LFOPS	0.12338	3102424	489938.7	3688022.7	289.87	560.61
BABRDELF	0.03539	3102424	489938.7	3688022.7	289.87	560.61
BABRDEBA	0.05824	3102424	489938.7	3688022.7	289.87	560.61
ALL	8.78161	3102424	489938.7	3688022.7	289.87	560.61

TABLE 5.4.13

YEAR 22, 24-H0UR PM₁₀ IMPACTS BY OPERATION (MODEL RUN S33)

GROUP ID	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.23058m	3121724	488662.6	3688706	97.68	560.61
UPS	0.04552m	3121724	488662.6	3688706	97.68	560.61
UP	0.21348m	3121724	488662.6	3688706	97.68	560.61
LFDRD	0.22393m	3121724	488662.6	3688706	97.68	560.61
BABRD	0.01570m	3121724	488662.6	3688706	97.68	560.61
BAARD	2.80608m	3121724	488662.6	3688706	97.68	560.61
LFOPS	0.17548m	3121724	488662.6	3688706	97.68	560.61
BAAOPS	32.48621m	3121724	488662.6	3688706	97.68	560.61
BABOPS	0	0	0	0	0	0
FLARE	0.00256m	3121724	488662.6	3688706	97.68	560.61
BABWIND	0	0	0	0	0	0
BABUNWD	0	0	0	0	0	0
BAAWIND	0	0	0	0	0	0
BAAUNWD	0	0	0	0	0	0
LFWIND	0	0	0	0	0	0
LFUNWIND	0	0	0	0	0	0
BABRDELF	0.00063m	3121724	488662.6	3688706	97.68	560.61
BABRDEBA	0.00092m	3121724	488662.6	3688706	97.68	560.61
BAARDEBA	3.55012m	3121724	488662.6	3688706	97.68	560.61
BAARDELF	0.06420m	3121724	488662.6	3688706	97.68	560.61
ALL	39.81540m	3121724	488662.6	3688706	97.68	560.61

TABLE 5.4.14

YEAR 22, 24-H0UR PM₁₀ IMPACTS BY OPERATION (MODEL RUN S33B)

GROUP ID	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.12932	3102424	488662.6	3688706	97.68	560.61
UPS	0.0347	3102424	488662.6	3688706	97.68	560.61
UP	0.14961	3102424	488662.6	3688706	97.68	560.61
LFDRD	0.14764	3102424	488662.6	3688706	97.68	560.61
BABRD	0.0052	3102424	488662.6	3688706	97.68	560.61
BAARD	0.94546	3102424	488662.6	3688706	97.68	560.61
LFOPS	0.10909	3102424	488662.6	3688706	97.68	560.61
BAAOPS	11.87124	3102424	488662.6	3688706	97.68	560.61
BABOPS	0	0	0	0	0	0

FLARE	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
BABWIND	0.02364	3102424	488662.6	3688706	97.68	560.61
BABUNWD	0	0	0	0	0	0
BAAWIND	0	0	0	0	0	0
BAAUNWD	0	0	0	0	0	0
LFWIND	0	0	0	0	0	0
LFUNWIND	0	0	0	0	0	0
BABRDELF	0	0	0	0	0	0
BABRDEBA	0.00038	3102424	488662.6	3688706	97.68	560.61
BAARDEBA	0.00021	3102424	488662.6	3688706	97.68	560.61
BAARDELF	0.70208	3102424	488662.6	3688706	97.68	560.61
ALL	0.04264	3102424	488662.6	3688706	97.68	560.61
PAVED	14.16122	3102424	488662.6	3688706	97.68	560.61

TABLE 5.4.15

YEAR 22, 24-H0UR PM₁₀ IMPACTS BY OPERATION (MODEL RUN S34)

GROUP ID	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.12289	3102424	488662.1	3688656	97.15	560.61
UPS	0.03471	3102424	488662.1	3688656	97.15	560.61
UP	0.15121	3102424	488662.1	3688656	97.15	560.61
LFDRD	0.15039	3102424	488662.1	3688656	97.15	560.61
BABRD	0.00603	3102424	488662.1	3688656	97.15	560.61
BAARD	9.97314	3102424	488662.1	3688656	97.15	560.61
LFOPS	0.11179	3102424	488662.1	3688656	97.15	560.61
BAAOPS	1.30588	3102424	488662.1	3688656	97.15	560.61
BABOPS	0	0	0	0	0	0
FLARE	0.02332	3102424	488662.1	3688656	97.15	560.61
BABWIND	0	0	0	0	0	0
BABUNWD	0	0	0	0	0	0
BAAWIND	0	0	0	0	0	0
BAAUNWD	0	0	0	0	0	0
LFWIND	0	0	0	0	0	0
LFUNWIND	0	0	0	0	0	0
BABRDELF	0.00039	3102424	488662.1	3688656	97.15	560.61
BABRDEBA	0.00031	3102424	488662.1	3688656	97.15	560.61
BAARDEBA	0.40691	3102424	488662.1	3688656	97.15	560.61
BAARDELF	0.04324	3102424	488662.1	3688656	97.15	560.61
ALL	11.87936	3102424	488662.1	3688656	97.15	560.61

TABLE 5.4.16

YEAR -2, ANNUAL PM₁₀ IMPACTS BY OPERATION (MODEL RUN S25- ANNUAL AVERAGE)

GROUP ID	Modeled Impact (µg/m³)	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.08974	490029.1	3689602	118.59	560.61
UPS	0.05433	490029.1	3689602	118.59	560.61
UP	0.13036	490029.1	3689602	118.59	560.61
FILLRD	0.28568	490029.1	3689602	118.59	560.61
SPBRD	0.00608	490029.1	3689602	118.59	560.61
SPARD	0.67154	490029.1	3689602	118.59	560.61
SPAUN	0.01267	490029.1	3689602	118.59	560.61
SPBUN	0	0	0	0	0
FILLUN	0.10775	490029.1	3689602	118.59	560.61
LFEXCAV	1.39796	490029.1	3689602	118.59	560.61
LFWIND	0.01686	490029.1	3689602	118.59	560.61
SPAWIND	0.00606	490029.1	3689602	118.59	560.61
SPBWIND	0.0004	490029.1	3689602	118.59	560.61
DRILL	0	0	0	0	0
BLAST	0.01575	490029.1	3689602	118.59	560.61
ROCKCR	0.05736	490029.1	3689602	118.59	560.61
CLAYLIN	0.11454	490029.1	3689602	118.59	560.61
ROCKLOAD	0	0	0	0	0
SPBRDELF	0.00083	490029.1	3689602	118.59	560.61
SPBRDESP	0.00013	490029.1	3689602	118.59	560.61
SPARDESP	0.00937	490029.1	3689602	118.59	560.61
SPARDELF	0.14129	490029.1	3689602	118.59	560.61
ALL	3.11872	490029.1	3689602	118.59	560.61

TABLE 5.4.17

YEAR 1, ANNUAL PM₁₀ IMPACTS BY OPERATION (MODEL RUN S26)

GROUP ID	Modeled Impact (µg/m³)	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.33478	490002.8	3689603	113.99	560.61
UPS	0.70585	490002.8	3689603	113.99	560.61
UP	0.25825	490002.8	3689603	113.99	560.61
LFRD	0.20838	490002.8	3689603	113.99	560.61
DCRD	0.11657	490002.8	3689603	113.99	560.61
FILLRD	0.01366	490002.8	3689603	113.99	560.61
SPBRD	0.20505	490002.8	3689603	113.99	560.61

GROUP ID	Modeled Impact (µg/m³)	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
DCUNLOAD	0.16802	490002.8	3689603	113.99	560.61
FILLUN	0.00305	490002.8	3689603	113.99	560.61
LFEXCAV	0.22476	490002.8	3689603	113.99	560.61
SPBUN	0.01248	490002.8	3689603	113.99	560.61
CLAYLIN	0.01596	490002.8	3689603	113.99	560.61
ROCKCR	0.00963	490002.8	3689603	113.99	560.61
ROCKLOAD	0.00759	490002.8	3689603	113.99	560.61
DRILL	0	490002.8	3689603	113.99	560.61
BLAST	0.00002	490002.8	3689603	113.99	560.61
AFWIND	0.00967	490002.8	3689603	113.99	560.61
SPBWIND	0.00176	490002.8	3689603	113.99	560.61
LFUNWIND	0.00003	490002.8	3689603	113.99	560.61
LFWIND	0.00009	490002.8	3689603	113.99	560.61
DCRDELF	0.03228	490002.8	3689603	113.99	560.61
DCRDESP	0.00684	490002.8	3689603	113.99	560.61
RKRDEBLT	0.0314	490002.8	3689603	113.99	560.61
RKRDEBRD	0.01465	490002.8	3689603	113.99	560.61
RKRD	0.05123	490002.8	3689603	113.99	560.61
SPBRELF	0.01706	490002.8	3689603	113.99	560.61
SPBRDESP	0.0087	490002.8	3689603	113.99	560.61
ALL	2.45774	490002.8	3689603	113.99	560.61

TABLE 5.4.18

YEAR 17, ANNUAL PM₁₀ IMPACTS BY OPERATION (MODEL RUN S29)

GROUP ID	Modeled Impact (µg/m³)	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.30168	490079.1	3689599.9	125.88	560.61
UPS	1.91144	490079.1	3689599.9	125.88	560.61
UP	0.05428	490079.1	3689599.9	125.88	560.61
BABROAD	0.02853	490079.1	3689599.9	125.88	560.61
FLARES	0.07584	490079.1	3689599.9	125.88	560.61
BABWIND	0.00029	490079.1	3689599.9	125.88	560.61
BABUNWD	0.00025	490079.1	3689599.9	125.88	560.61
LFWIND	0	0	0	0	0
LFUNWIND	0	490079.1	3689599.9	125.88	560.61
LFDRD	0.0481	490079.1	3689599.9	125.88	560.61
BABOPS	0.028	490079.1	3689599.9	125.88	560.61
ROCKCR	0.00076	490079.1	3689599.9	125.88	560.61

GROUP ID	Modeled Impact (µg/m³)	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
BLAST	0.00002	490079.1	3689599.9	125.88	560.61
DRILL	0.00001	490079.1	3689599.9	125.88	560.61
LFOPS	0.03462	490079.1	3689599.9	125.88	560.61
BABRDELF	0.00823	490079.1	3689599.9	125.88	560.61
BABRDEBA	0.00691	490079.1	3689599.9	125.88	560.61
ALL	2.49894	490079.1	3689599.9	125.88	560.61

TABLE 5.4.19

YEAR 22, ANNUAL PM₁₀ IMPACTS BY OPERATION (MODEL RUN S32)

GROUP ID	Modeled Impact (µg/m³)	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.32646	490029.1	3689602	118.59	560.61
UPS	0.25312	490029.1	3689602	118.59	560.61
UP	0.52449	490029.1	3689602	118.59	560.61
LFDRD	0.32205	490029.1	3689602	118.59	560.61
BABRD	0.13522	490029.1	3689602	118.59	560.61
BAARD	0.09351	490029.1	3689602	118.59	560.61
LFOPS	0.19981	490029.1	3689602	118.59	560.61
BAAOPS	0.02212	490029.1	3689602	118.59	560.61
BABOPS	0.01572	490029.1	3689602	118.59	560.61
FLARE	0.09411	490029.1	3689602	118.59	560.61
BABWIND	0.00026	490029.1	3689602	118.59	560.61
BABUNWD	0.00026	490029.1	3689602	118.59	560.61
BAAWIND	0.00099	490029.1	3689602	118.59	560.61
BAAUNWD	0.00086	490029.1	3689602	118.59	560.61
LFWIND	0.00117	490029.1	3689602	118.59	560.61
LFUNWIND	0.00118	490029.1	3689602	118.59	560.61
BABRDELF	0.02125	490029.1	3689602	118.59	560.61
BABRDEBA	0.00263	490029.1	3689602	118.59	560.61
BAARDEBA	0.00671	490029.1	3689602	118.59	560.61
BAARDELF	0.02722	490029.1	3689602	118.59	560.61
ALL	2.04915	490029.1	3689602	118.59	560.61

5.5 SUPLEMENTAL ANALYSES FOR 24-HOUR PM₁₀ IMPACTS NEAR BORROW AREA A WITH NEW RECEPTOR GRID

The District performed additional modeling for facility operations occurring in Year 22 in order to determine the maximum predicted impact in proximity to Borrow Area A for all sources as well as the predicted impact resulting from each facility operation as defined by a source group. The latest version of AERMOD (12345) was used for this modeling. A new fine resolution receptor grid in the area west of Borrow Area A was used for this modeling. The new model grid, as well as recent changes to the model formulation, resulted in some differences to the maximum predicted impact value and location. Table 5.5.1 summaries the maximum predicted 24-Hour impact plus background concentration for all days modeled (monitored background days). Tables 5.5.2 provides the 24-Hour predicted impact by each source group for the day (10/24/03) potential impacts are the most sensitive to changes in facility emissions.

TABLE 5.5.1

YEAR 22, 24-H0UR PM₁₀ IMPACT PLUS BACKGROUND MODEL RESULTS FOR ALL PM₁₀ MONITORING DAYS NEAR BORROW AREA A

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
488676.5	3688721	37.0935	3010924	9.7	46.7935
488676.5	3688311	0.01215	3020224	32.6	32.61215
488676.5	3688741	25.13039	3020824	13.5	38.63039
488676.5	3688701	13.60809	3021524	10.1	23.70809
488676.5	3688691	21.58171	3022024	13	34.58171
488676.5	3688711	11.99591	3022624	10.3	22.29591
488676.5	3688711	29.83154	3030424	7	36.83154
488676.5	3688711	2.91997	3031024	19.3	22.21997
488676.5	3688781	0.00083	3031624	13.2	13.20083
488676.5	3688211	0.00073	3032224	17.7	17.70073
488676.5	3688691	25.80332	3032824	15.2	41.00332
488676.5	3688211	0.0008	3040324	9.2	9.2008
488676.5	3688701	21.79862	3040924	19.7	41.49862
488676.5	3688681	27.57521	3041524	8.5	36.07521
488676.5	3688701	14.85556	3042324	13.1	27.95556
488676.5	3688211	0.00053	3042724	13	13.00053
488676.5	3688701	8.59709	3050924	16.8	25.39709
488676.5	3688691	15.44762	3051524	17.7	33.14762
488676.5	3688711	11.59905	3052124	31.3	42.89905
488676.5	3688711	5.4038	3052724	23.5	28.9038

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
488676.5	3688731	0.00001	3060224	23.1	23.10001
488676.5	3688401	0.00121	3060824	11.6	11.60121
488676.5	3688251	0.00002	3061424	24.2	24.20002
488676.5	3688711	11.3738	3062024	17.8	29.1738
488676.5	3688711	4.05089	3062624	28.8	32.85089
488676.5	3688711	7.95021	3070224	30.4	38.35021
488676.5	3688711	6.08312	3070824	26.7	32.78312
488676.5	3688711	3.42451	3071424	29.9	33.32451
488376.5	3688781	0.00469	3072024	22.1	22.10469
488676.5	3688711	3.98499	3072624	22.6	26.58499
488676.5	3688711	5.24994	3080124	16.2	21.44994
488676.5	3688701	9.80769	3080724	22	31.80769
488676.5	3688691	15.18358	3081324	32.9	48.08358
488676.5	3688711	6.47684	3082524	22.5	28.97684
488676.5	3688781	0.00259	3083124	26	26.00259
488676.5	3688711	4.26438	3090624	36.8	41.06438
488676.5	3688711	1.2388	3091224	28.8	30.0388
488676.5	3688701	11.83264	3091824	32.1	43.93264
488676.5	3688711	4.85351	3092424	33	37.85351
488676.5	3688701	8.47858	3100624	35.1	43.57858
488376.5	3688781	0.013	3101224	26.8	26.813
488676.5	3688701	13.34552	3101824	30.5	43.84552
488676.5	3688711	19.69844	3102424	36.9	56.59844
488676.5	3688711	1.1476	3103024	17	18.1476
488676.5	3688721	32.53143	3110524	16.5	49.03143
488676.5	3688701	22.58325	3111124	21.6	44.18325
488676.5	3688691	43.82163	3111724	9.6	53.42163
488676.5	3688211	0.00181	3112324	14.7	14.70181
488676.5	3688711	18.54594	3112924	16.3	34.84594
488676.5	3688711	37.48206	3121124	11.5	48.98206
488676.5	3688711	42.54346	3121724	16.9	59.44346

TABLE 5.5.2

YEAR 22, 24-H0UR PM₁₀ IMPACTS BY OPERATION NEAR BORROW AREA A F0R OCTOBER 24, 2003

GROUP ID	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.12996	3102424	488676.54	3688710.86	98.18	560.61
UPS	0.03519	3102424	488676.54	3688710.86	98.18	560.61
UP	0.15188	3102424	488676.54	3688710.86	98.18	560.61
LFDRD	0.15007	3102424	488676.54	3688710.86	98.18	560.61
BABRD	0.00528	3102424	488676.54	3688710.86	98.18	560.61
BAARD	1.05465	3102424	488676.54	3688710.86	98.18	560.61
LFOPS	0.11094	3102424	488676.54	3688710.86	98.18	560.61
BAAOPS	17.07249	3102424	488676.54	3688710.86	98.18	560.61
BABOPS	0	0	0	0	0	0
FLARE	0.02368	3102424	488676.54	3688710.86	98.18	560.61
BABWIND	0	0	0	0	0	0
BABUNWD	0	0	0	0	0	0
BAAWIND	0	0	0	0	0	0
BAAUNWD	0	0	0	0	0	0
LFWIND	0	0	0	0	0	0
LFUNWIND	0	0	0	0	0	0
BABRDELF	0.00039	3102424	488676.54	3688710.86	98.18	560.61
BABRDEBA	0.00021	3102424	488676.54	3688710.86	98.18	560.61
BAARDEBA	0.92034	3102424	488676.54	3688710.86	98.18	560.61
BAARDELF	0.04336	3102424	488676.54	3688710.86	98.18	560.61
ALL	19.69844	3102424	488676.54	3688710.86	98.18	560.61

5.6 SUPLEMENTAL ANALYSES FOR 24-HOUR AND ANNUAL PM₁₀ IMPACTS FROM OPERATIONS AT THE SOUTH END OF LANDFILL EMISSIONS

The District performed additional modeling for facility operations occurring in Year 17 in order to determine the maximum predicted 24-Hour and Annual impacts in proximity to the south end of the landfill for all sources. Additionally, the predicted impacts resulting from each facility operation as defined by source groups were also determined. The latest version of AERMOD (12345) was used for this modeling. A new fine resolution receptor grid in an area just south of the south end of the landfill footprint was added for this modeling. Any receptors that were along the southern border of the landfill property but determined to be on Gregory Canyon property were removed. Changes were also made to some source locations and how sources were defined. For the 24-Hour model impacts some sources were redefined as line volume sources. These were both landfill (LFOPS) and Borrow Area B (BABOPS) operations, the Borrow Area B Road (BABRD), Land Fill Deck Road (LFDRD) and Unpaved Road (UP). A new Unpaved,

Stabilized Road at the 900 foot landfill level (UPS900) was added. For the annual model predicted impacts, sources that were depicted as line volume sources included parts of the Borrow Area B Road (BABRD), the Land Fill Deck Road (LFDRD), the Unpaved Road (UP) and the new Unpaved, Stabilized Road at the 900 foot landfill level (UPS900). The original Borrow Area B wind erosion, Land Fill wind erosion, Borrow Area B unwind and Land Fill unwind were replaced with two larger area sources called Borrow Area B Wind (BABWND) and Land Fill Wind (LFWND). Table 5.6.1 summaries the maximum predicted 24-Hour impact plus background concentration for all days modeled (monitored background days). Tables 5.6.2 and 5.6.3 provide the 24-Hour predicted impact by each source group for the days (10/24/03 and 03/04/03) potential impacts are the most sensitive to changes in facility emissions. March 4, 2003 was the 24-Hour maximum impact day. Table 5.6.4 provides the maximum predicted annual impact for each source group at the point of maximum impact (PMI) receptor.

TABLE 5.6.1

YEAR 17, 24-H0UR PM₁₀ IMPACT PLUS BACKGROUND MODEL RESULTS FOR ALL PM₁₀ MONITORING DAYS NEAR THE LANDFILL SOUTHEND

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
490411.5	3688006	29.99459	3010924	9.7	39.69459
490454.5	3689983	0.16581	3020224	32.6	32.76581
490423.3	3688007	17.48152	3020824	13.5	30.98152
490411.5	3688006	19.60393	3021524	10.1	29.70393
490400.7	3688005	35.82201	3022024	13	48.82201
490411.5	3688006	22.61485	3022624	10.3	32.91485
490411.5	3688006	96.54471	3030424	7	103.5447
490411.5	3688006	2.24395	3031024	19.3	21.54395
489769.6	3689681	0.13286	3031624	13.2	13.33286
487325.1	3688144	0.27535	3032224	17.7	17.97535
490411.5	3688006	49.08789	3032824	15.2	64.28789
488276.8	3689967	0.13948	3040324	9.2	9.33948
490380.7	3688004	11.32969	3040924	19.7	31.02969
490380.7	3688004	29.39674	3041524	8.5	37.89674
490411.5	3688006	25.71139	3042324	13.1	38.81139
489575.1	3691644	0.20837	3042724	13	13.20837
490411.5	3688006	13.75258	3050924	16.8	30.55258
490400.7	3688005	13.00197	3051524	17.7	30.70197
490423.3	3688007	10.63192	3052124	31.3	41.93192
490423.3	3688007	6.87754	3052724	23.5	30.37754
490344.6	3689681	0.24891	3060224	23.1	23.34891

UTM, X (meters)	UTM, Y (meters)	MAX IMPACT (µg/m³)	DATE	PM10 Background (µg/m³)	Impact + Background (µg/m³)
490398.4	3689680	0.45603	3060824	11.6	12.05603
490677.1	3690219	0.0751	3061424	24.2	24.2751
490423.3	3688007	19.94792	3062024	17.8	37.74792
490423.3	3688007	7.72848	3062624	28.8	36.52848
490423.3	3688007	15.79424	3070224	30.4	46.19424
490423.3	3688007	10.66259	3070824	26.7	37.36259
490423.3	3688007	6.01022	3071424	29.9	35.91022
490454.5	3689983	0.41354	3072024	22.1	22.51354
490423.3	3688007	7.18778	3072624	22.6	29.78778
490423.3	3688007	10.49377	3080124	16.2	26.69377
490400.7	3688005	8.99209	3080724	22	30.99209
490380.7	3688004	12.02366	3081324	32.9	44.92366
490411.5	3688006	8.79345	3082524	22.5	31.29345
490319.6	3689606	0.29725	3083124	26	26.29725
490423.3	3688007	7.97932	3090624	36.8	44.77932
490411.5	3688006	1.23223	3091224	28.8	30.03223
490400.7	3688005	16.67803	3091824	32.1	48.77803
490423.3	3688007	8.01209	3092424	33	41.01209
490411.5	3688006	21.70142	3100624	35.1	56.80142
489136.9	3690166	0.39681	3101224	26.8	27.19681
490400.7	3688005	15.04199	3101824	30.5	45.54199
490411.5	3688006	22.40959	3102424	36.9	59.30959
490294.6	3689606	1.56055	3103024	17	18.56055
490411.5	3688006	25.88767	3110524	16.5	42.38767
490400.7	3688005	36.1978	3111124	21.6	57.7978
490400.7	3688005	36.1235	3111724	9.6	45.7235
488274.8	3689817	0.32149	3112324	14.7	15.02149
490400.1	3687956	17.37974	3112924	16.3	33.67974
490411.5	3688006	41.74637	3121124	11.5	53.24637
490411.5	3688006	45.69245	3121724	16.9	62.59245

TABLE 5.6.2

YEAR 17, 24-H0UR PM₁₀ IMPACTS BY OPERATION NEAR THE LANDFILL SOUTHEND F0R OCTOBER 24, 2003

GROUP ID	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.0076	3102424	490004.6	3687999	290.72	560.61
UPS	0.15853	3102424	490004.6	3687999	290.72	560.61
FLARES	0.03585	3102424	490004.6	3687999	290.72	560.61
BABOPS	10.04595	3102424	490004.6	3687999	290.72	560.61
BABRDBA	0.12598	3102424	490004.6	3687999	290.72	560.61
BABRDELF	0.07117	3102424	490004.6	3687999	290.72	560.61
BABRDLF	0.27361	3102424	490004.6	3687999	290.72	560.61
LFDRD	0.29483	3102424	490004.6	3687999	290.72	560.61
LFOPS	0.23491	3102424	490004.6	3687999	290.72	560.61
UP	0.39433	3102424	490004.6	3687999	290.72	560.61
BABEBA	0.84913	3102424	490004.6	3687999	290.72	560.61
UPS900	0.40144	3102424	490004.6	3687999	290.72	560.61
BABWND	0	0	0	0	0	0
LFWIND	0	0	0	0	0	0
ALL	12.89332	3102424	490004.6	3687999	290.72	560.61

TABLE 5.6.3

YEAR 17, 24-H0UR PM₁₀ IMPACTS BY OPERATION NEAR THE LANDFILL SOUTHEND F0R MARCH 4, 2003

GROUP ID	Modeled Impact (µg/m³)	YYMMDDHH	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.00714m	3030424	490411.5	3688006.2	284.83	560.61
UPS	0.27825m	3030424	490411.5	3688006.2	284.83	560.61
FLARES	0.04263m	3030424	490411.5	3688006.2	284.83	560.61
BABOPS	0.62571m	3030424	490411.5	3688006.2	284.83	560.61
BABRDBA	0.06373m	3030424	490411.5	3688006.2	284.83	560.61
BABRDELF	14.10039m	3030424	490411.5	3688006.2	284.83	560.61
BABRDLF	0.85544m	3030424	490411.5	3688006.2	284.83	560.61
LFDRD	14.92954m	3030424	490411.5	3688006.2	284.83	560.61
LFOPS	59.66853m	3030424	490411.5	3688006.2	284.83	560.61
UP	4.45108m	3030424	490411.5	3688006.2	284.83	560.61
BABEBA	0.10900m	3030424	490411.5	3688006.2	284.83	560.61
UPS900	1.39302m	3030424	490411.5	3688006.2	284.83	560.61
BABWND	0	0	0	0	0	0
LFWIND	0	0	0	0	0	0
ALL	96.52446m	3030424	490411.5	3688006.2	284.83	560.61

TABLE 5.6.4

YEAR 17, ANNUAL PM₁₀ IMPACTS BY OPERATION NEAR THE LANDFILL SOUTHEND

GROUP ID	Modeled Impact (µg/m³)	UTM EAST (meters)	UTM WEST (meters)	RECEPTOR ELEV (meters)	HILL ZFL (meters)
PAVED	0.30183	490079.1	3689599.9	125.87	560.61
UPS	1.8547	490079.1	3689599.9	125.87	560.61
BABRDBA	0.01364	490079.1	3689599.9	125.87	560.61
FLARES	0.07582	490079.1	3689599.9	125.87	560.61
BABOPS	0.02351	490079.1	3689599.9	125.87	560.61
ROCKCR	0.00319	490079.1	3689599.9	125.87	560.61
BLAST	0.00002	490079.1	3689599.9	125.87	560.61
DRILL	0.00006	490079.1	3689599.9	125.87	560.61
BABRDEBA	0.00663	490079.1	3689599.9	125.87	560.61
LFWND	0.00001	490079.1	3689599.9	125.87	560.61
BABWIND	0.00045	490079.1	3689599.9	125.87	560.61
UPS900	0.0679	490079.1	3689599.9	125.87	560.61
UP	0.05534	490079.1	3689599.9	125.87	560.61
LFDRD	0.04485	490079.1	3689599.9	125.87	560.61
LFOPS	0.03353	490079.1	3689599.9	125.87	560.61
BABRDELF	0.00851	490079.1	3689599.9	125.87	560.61
BABRLF	0.01081	490079.1	3689599.9	125.87	560.61
ALL	2.5008	490079.1	3689599.9	125.87	560.61

6.0 POTENTIAL IMPACTS FROM BLASTING

Emissions and potential ambient air quality impacts from blasting are included in the results shown in Table 4-2. Blasting impacts were assessed with a combination of the AERMOD and the USEPA-approved Open Burn/Open Detonation Dispersion Model (OBODM) model. OBODM was used to determine the height of the gaseous plume associated with blasting. For particulate impacts, it was assumed that blasting-related particulate was released at ground level even though there is some plume rise of particulates from blasting. This assumption over-estimates particulate impacts. For the gases associated with blasting (e.g., NO_x) the mid-point of the plume height predicted by the OBODM model was used as the release height in AERMOD. OBODM was used only for the plume rise calculation; AERMOD was used to assess dispersion. The maximum 1-Hour impact for NO2 was 69.8 µg/m³. For CO, the maximum 1-Hour impact was 1376 µg/m³ and the maximum 8-hour impact was 178 µg/m³. These results are for a one half acre blast size 650 meters from the north fence line.

Blasting will occur during construction of the landfill, Years -2 and -1, and may occur when material is excavated from Borrow Area B (BAB), assumed to occur in

Year 17 for purposes of the impact assessment. Blasting is not anticipated to be needed when excavating material from Borrow Area A. The applicant conducted a geotechnical survey to identify where blasting may be needed when excavating native material in the waste disposal area and BAB. To assess the impacts from blasting, a series of model runs were conducted with various sizes of blasts located at various distances from the property line in order to identify the worst case combination of blast size and location. The results of that analysis are shown in Table 6-1.

TABLE 6-1

MINIMUM BLASTING DISTANCES

Approximate Blast Area	Tons of ANFO Used	Minimum Distance from Northern Property Line for the Landfill Area (meters)	Minimum Distance from Western Property Line for Borrow Area B (meters)	Minimum Distance from Eastern Property Line for Borrow Area B (meters)
One-sixteenth acre	1	250	285	165
One-eighth acre	2	265	300	175
One-quarter acre	4	415	475	275
One-half acre	8	650	750	430

7.0 ANALYSIS OF SIGNIFICANT IMPACTS ON CLASS I AREAS

The Agua Tibia Wilderness area is the closest Class I Area to the project site (less than 10 km northeast). In accordance with District Rule 20.3(d)(3)(i), if a project is expected to have a significant impact on any Class I area, as determined by an AQIA, the provisions of subsections (d)(3)(ii) through (vii) of District Rule 20.3 shall apply.

Modeling was performed by the District in order to determine the 24-Hour Maximum impact for PM₁₀, NO₂, SO₂ and CO in the Agua Tibia Wilderness area. Predicted project impacts were then compared to the maximum impact thresholds listed in Table 20.1-12 of District Rule 20.1, New Source Review, and General Provisions. The results of the modeling are presented in Table 7.1 below.

TABLE 7.1

PREDICTED IMPACTS AND SIGNIFICANT IMPACT LEVELS FOR THE AGUA TIBIA WILDERNESS AREA CLASS I AREA

POLLUTANT	OPERATION YEAR	24-HOUR MAXIMUM IMPACT	24-HOUR SIGNIFICANT IMPACT LEVEL
PM₁₀	1	0.33	1.0
CO	23	0.08	1.0
SO₂	23	0.08	1.0
NO₂	23	0.03	1.0

The modeling results indicate that the maximum Significant Impact Levels for these criteria pollutants will not be exceeded due to proposed operations of the facility.

8.0 CONCLUSION

The results of the modeling indicate that the proposed facility operations including construction, routine operations, final closure, after hours operations, and landfill gas collection and recovery will not cause or contribute to an exceedance of the Federal and California Ambient Air Quality Standards for NO₂, SO2, CO or PM_2.5. For PM_10, facility permit conditions will limit emissions as determined by the modeling results in order to maintain compliance with Federal and California Ambient Air Quality Standards.

ATTACHMENT 1

AIR QUALITY IMPACT ANALYSIS FINAL REVIEW REPORT FOR THE PROPOSED GREGORY CANYON LANDFILL

AUGUST 5, 2013

VOLUME VII: UPDATED AIR QUALITY IMPACT ANALYSIS AND HEALTH RISK

ASSESSMENT FOR THE PROPOSED GREGORY CANYON LANDFILL

Kleinfelder

4815 List Drive, Suite 115 Colorado Springs, CO 80919

September 14, 2010

UNAUTHORIZED USE OF THIS DOCUMENT IS STRICTLY PROHIBITED BY ANYONE OTHER THAN THE CLIENT FOR THE SPECIFIC PROJECT.

Volume VII:

Updated Air Quality Impact Analysis and Health Risk Assessment For the Proposed Gregory Canyon Landfill

Prepared for :

Gregory Canyon Limited

160 Industrial Street, Suite 200 San Marcos, CA 92078

Kleinfelder Project No: 100847 Prepared by:

Russell E. Erbes, CCM

Senior Principal Air Quality Scientist

Reviewed by:

KLEINFELDER

4815 List Drive, Suite 115 Colorado Springs, CO 80919

September 14, 2010

TABLE OF CONTENTS

Section Page

1.0 EXECUTIVE SUMMARY……………………………………………………………………………………… 1

1.1 INTRODUCTION………………………………………………………………………………………. 1

1.2 PRE-PROJECT AMBIENT CONCENTRATIONS OF CO, NO₂, AND PARTICULATE MATTER…………………………………………………………………………… 2

1.3 REFINED PARTICULATE EMISSION ESTIMATES……………………………………… 3

1.4 DISPERSION MODELING AND IMPACT ASSESSMENT…………………………….. 5

1.5 SUPPLEMENTAL HEALTH RISK ASSESSMENT………………………………………… 6

1.6 SUMMARY………………………………………………………………………………………………. 7

2.0 PRE-PROJECT BACKGROUND AMBIENT AIR QUALITY……………………………………… 8

2.1 NO₂ BACKGROUND…………………………………………………………………………………. 8

2.2 CO BACKGROUND………………………………………………………………………………….. 9

2.3 ON-SITE AMBIENT PARTICULATE MONITORING……………………………………. 10

2.4 AMBIENT PARTICULATE MONITORING AT AQUA TIBIA WILDERNESS AREA12

2.5 DETERMINATION OF BACKGROUND AMBIENT PARTICULATE CONCENTRATIONS FOR THE PROPOSED PROJECT IMPACT AREA 13

2.5.1 Background Concentrations for the Annual Standards………………………. 13

2.5.2 Background Concentrations for the 24-Hour Standards……………………… 14

3.0 REFINED EMISSION ESTIMATES……………………………………………………………………… 16

3.1 REFINED EMISSION ESTIMATES FOR WIND EROSION, LOADING, UNLOADING, AND EXCAVATION……………………………………………………………. 16

3.1.1 Silt Content of Fill/Cover Material……………………………………………………. 16

3.1.2 Refined Emission Factor for Wind Erosion……………………………………….. 17

3.1.3 Refined Emission Rate for Excavation…………………………………………….. 19

3.1.4 Refined Emission Factor for Loading and Unloading…………………………. 19

3.1.5 Refined Emission Factor for Handling Clay Liner Material………………….. 20

3.1.6 Potential Wind Erosion Emissions from De-silting Basins…………………… 20

3.2 REFINED EMISSION ESTIMATES FOR ADDITIONAL ACTIVITIES…………….. 20

3.2.1 Rock crushing……………………………………………………………………………….. 20

3.2.2 Municipal Solid Waste Spreading and Compacting…………………………… 21

3.2.3 Cover Material Compacting……………………………………………………………. 21

3.2.4 Blasting………………………………………………………………………………………… 21

3.2.5 Road Maintenance and Grading……………………………………………………… 22

3.3 REFINED EMISSION ESTIMATES FOR ON-SITE ROADS…………………………. 22

3.3.1 Paved Roads………………………………………………………………………………… 22

3.3.2 Unpaved Stabilized Roads……………………………………………………………… 22

3.3.3 Unpaved Unstabilized Roads………………………………………………………….. 23

3.3.4 Road Ends……………………………………………………………………………………. 23

3.4 REFINED EMISSION ESTIMATES FOR LANDFILL GAS……………………………. 23

3.5 PM_2.5 EMISSION ESTIMATES………………………………………………………………….. 25

3.5.1 PM_2.5 Emission Factor for Blasting…………………………………………………… 25

3.5.2 PM_2.5 Emission Factor for Excavation, Loading and Unloading Soil…….. 25

3.5.3 PM_2.5 Emission Factor for Unpaved and Paved Roads………………………. 26

3.5.4 PM_2.5 Emission Factor for Wind Erosion…………………………………………… 26

3.5.5 PM_2.5 Emission Factor for Excavation and Daily Cover Operations……… 27

3.5.6 PM_2.5 Emission Factor for Drilling…………………………………………………….. 27

3.5.7 PM_2.5 Emission Factor for Landfill Gas Flares…………………………………… 27

3.6 EMISSION ESTIMATES FOR DIESEL PARTICULATE MATTER………………… 27

TABLE OF CONTENTS (Continued)

3.7 REFINED EMISSION ESTIMATES FOR AIR TOXICS………………………………… 28

3.8 SUMMARY OF EMISSION ESTIMATES……………………………………………………. 28

4.0 DISPERSION MODELING AND IMPACT ASSESSMENT……………………………………… 30

4.1 AMBIENT AIR QUALITY STANDARDS…………………………………………………….. 30

4.2 METEOROLOGICAL DATA AND DISPERSION MODEL…………………………….. 31

4.3 NITROGEN OXIDES CONVERSION………………………………………………………… 32

4.4 NO₂ IMPACT RESULTS…………………………………………………………………………… 35

4.5 PARTICULATE MATTER IMPACT RESULTS……………………………………………. 37

4.5.1 Landfill Operational Schedule…………………………………………………………. 37

4.5.2 24-Hour and Annual Emission Calculations………………………………………. 38

4.5.3 Revised Modeling Parameters………………………………………………………… 39

4.5.4 PM₁₀ Impact Results for 24-Hour AAQS………………………………………….. 39

4.5.5 PM₁₀ Impact Results for Annual AAQS……………………………………………. 45

4.5.6 PM_2.5 Impact Results for 24-Hour AAQS………………………………………….. 46

4.5.7 PM_2.5 Impact Results for Annual AAQS……………………………………………. 46

5.0 SUPPLEMENTAL HEALTH RISK ASSESSMENT………………………………………………… 48

5.1 HARP MODEL SETTINGS……………………………………………………………………….. 48

5.2 HARP MODEL RESULTS………………………………………………………………………… 49

5.2.1 Potential Cancer Risk and Hazard Indices……………………………………….. 49

5.2.2 Potential Lead Health Effects…………………………………………………………. 53

6.0 SUMMARY………………………………………………………………………………………………………. LIV

TABLES

Table 1-1 Pre-project (Background) Ambient Concentrations of CO and NO₂………………………… 3

Table 1-2 Pre-project (Background) Ambient Concentrations of Particulate Matter…………………. 3

Table 1-3 Proposed GCLF Annual PM₁₀, and PM_2.5, and NO₂, Emission Estimates………………… 4

Table 1-4 Proposed GCLF Maximum Hourly PM₁₀, and PM_2.5, and NO₂, Emission Estimates…………………………………………………………………………………………………….. 5

Table 1-5 Proposed GCLF Annual and Maximum Hourly Air Toxic Emission Estimates………….. 5

Table 1-6 Maximum NO₂, PM₁₀, and PM_2.5 Impacts…………………………………………………………….. 6

Table 1-7 Health Risk Assessment Results………………………………………………………………………… 7

Table 2-1 Background NO₂ Concentrations (ppm)………………………………………………………………. 9

Table 2-2 Background NO₂ Concentrations (ug/m³)……………………………………………………………. 9

Table 2-3 Background CO Concentrations (ppm)……………………………………………………………… 10

Table 2-4 On-site 24-Hour Ambient PM₁₀, Calendar Year 2002………………………………………….. 10

Table 2-5 On-site 24-Hour Ambient PM₁₀, Calendar Year 2003………………………………………….. 11

Table 2-6 On-Site Annual Average Ambient PM₁₀ Concentration………………………………………… 12

Table 2-7 Aqua Tibia Ambient PM₁₀ and PM_2.5, Annual Averages for 2002-2008………………….. 12

Table 2-8 Aqua Tibia and On-Site PM₁₀, Averages of 2002-2003……………………………………….. 14

Table 2-9 Estimated On-Site Annual Average PM₁₀ Concentrations for 2004-2006……………… 14

Table 2-10 Pre-project (Background) Ambient Concentrations of Particulate Matter…………….. 15

Table 3-1 Proposed GCLF Annual PM₁₀, and PM_2.5, and NO₂, Emission Estimates………………. 29

Table 3-2 Proposed GCLF Maximum Hourly PM₁₀, and PM_2.5, and NO₂, Emission Estimates…………………………………………………………………………………………………… 29

Table 3-3 Proposed GCLF Annual and Maximum Hourly Air Toxic Emission Estimates………… 29

Table 4-1 Relevant National and California Ambient Air Quality Standards……………………… 30

Table 4-2 Surface Characteristics Used for Processing the On-Site Meteorological Data……… 31

Table 4-3 Meteorological Data Capture……………………………………………………………………………. 32

Table 4-4 Maximum Potential 1-Hour Impact of NO₂…………………………………………………………. 36

(in terms of ug/m³)…………………………………………………………………………………………………………. 36

Table 4-5 Maximum Potential Annual Impact of NO₂…………………………………………………………. 36

(in terms of ug/m³)…………………………………………………………………………………………………………. 36

Table 4-6 Minimum Blasting Distances…………………………………………………………………………….. 37

Table 4-7 Maximum PM₁₀ Impacts for Operational Year -2………………………………………………… 40

Table 4-8 Maximum PM₁₀ Impacts for Operational Year 1………………………………………………….. 41

Table 4-9 Maximum PM₁₀ Impacts for Operational Year 8………………………………………………….. 42

TABLES (Continued)

Table 4-10 Maximum PM₁₀ Impacts for Operational Year 17………………………………………………. 43

Table 4-11 Maximum PM₁₀ Impacts for Operational Year 22………………………………………………. 44

Table 4-12 Maximum PM₁₀ Impacts for Operational Year 23………………………………………………. 45

Table 4-13 Maximum Potential Annual Impact of PM₁₀………………………………………………………. 46

(in terms of ug/m³)…………………………………………………………………………………………………………. 46

Table 4-14 Maximum Potential 24-Hour Impact of PM_2.5……………………………………………………. 46

(in terms of ug/m³)…………………………………………………………………………………………………………. 46

Table 4-15 Maximum Potential Annual Impact of PM_2.5……………………………………………………… 47

(in terms of ug/m³)…………………………………………………………………………………………………………. 47

Table 5-1 HARP Model Results for 2002 Meteorology……………………………………………………….. 49

Table 5-2 HARP Model Results for 2003 Meteorology……………………………………………………….. 50

APPENDICES

Appendix A Proposed Project Emissions for Operational Year -2 Appendix B Proposed Project Emissions for Operational Year 1 Appendix C Proposed Project Emissions for Operational Year 8 Appendix D Proposed Project Emissions for Operational Year 17 Appendix E Proposed Project Emissions for Operational Year 22 Appendix F Proposed Project Emissions for Operational Year 23 Appendix G Fill/Cover Material Silt Content Estimate

Appendix H SOILTAC Material Safety Data Sheet Appendix I SOILTAC Chemical Analysis Appendix J LANDGEM Landfill Gas Emissions

Appendix K Compact Disc Emission Spreadsheets and Model Runs

AAQS	Ambient Air Quality Standards
AERMET	Program to process meteorological data
AERMOD	Dispersion model
AQIA	Air Quality Impact Analysis
ATC	Authority to Construct
BACT	Best Available Control Technology
bhp	brake horsepower
CAAQS	California Ambient Air Quality Standards
CO	Carbon monoxide

cy Cubic yard(s)

DPM Diesel Particulate Matter

GCL Gregory Canyon Ltd.

GCLF Gregory Canyon Landfill

HARP Hotspots Analysis Reporting Program HI Hazard Index

IMPROVE Interagency Monitoring of Protected Visual Environments lb/day pound per day

lb/hour pound per hour

lb/ton pound per ton

LANDGEM Landfill Gas Emissions Model LFG landfill gas

MEIR Maximum Exposed Individual, Residential MEIW Maximum Exposed Individual, Worker

Mg Megagram (one million grams)

MRI Midwest Research Institute

mph miles per hour

m/sec meters per second

MSDS Material Safety Data Sheet

NAAQS National Ambient Air Quality Standards NO₂ Nitrogen dioxide

NO_x Oxides of nitrogen

OEHHA Office of Environmental Health Hazard Assessment OLM Ozone Limiting Method

PM₁₀ Particulate matter less than 10 micron mean aerodynamic diameter PM_2.5 Particulate matter less than 2.5 micron mean aerodynamic diameter

PMI	Point of Maximum Impact
ppm	parts per million (by volume)
PTC	Permit to Construct
REL	Reference Exposure Level
SDAPCD	San Diego Air Pollution Control District
tpy	ton per year
TSP	Total Suspended Particulate
μg/m³	microgram per cubic meter (of air)
URF	Unit Risk Factor
USEPA	United States Environmental Protection Agency
WBAN	Weather-Bureau-Army-Navy
WMO	World Meteorological Organization

1.0
EXECUTIVE SUMMARY

1.1 INTRODUCTION

Gregory Canyon Ltd. (GCL) is proposing to build a Class III non-hazardous (municipal) solid waste landfill, known as the Gregory Canyon Landfill (GCLF), on a 308 acre portion of 1,770 acres property in San Diego County. The GCLF project includes construction, operation, and closure of the landfill. The project includes a lined landfill, an access road and bridge from SR 76 to the landfill, a scale area, a recyclable goods collection center, a facilities and operations area, two borrow/stockpile areas, a leachate collection and removal system, a water treatment plant, an administration building, a maintenance office, a shop and yard, a fueling station/storage area, a water tank, a water supply well, groundwater monitoring wells, a landfill gas collection and control system, and a groundwater subdrain collection system.

GCLF is permitted to receive up to 5,000 tons per day of Class III non-hazardous (municipal) solid waste. Assuming 5,000 tons per day of solid waste is received each day of operation (6 days per week, 307 days per year), the landfill would reach capacity 22 years after opening. This assumption was made in order to be consistent with the Environmental Impact Report for the landfill.

GCL filed an authority to construct (ATC) permit application to the San Diego Air Pollution Control District (SDAPCD) in April 2007. As of September 2010, this permit application consisted of seven volumes:

Volume I: Permit Application and Forms, submitted April 2007

Volume II: BACT Analysis, submitted May 2008 and updated October 2008 Volume III: Regulatory Analysis, submitted November 2007

Volume IV: Annual Emission Inventory, submitted May 2008 and updated October 2008

Volume V: Air Quality Impact Analysis (AQIA) for Carbon Monoxide (CO), and Nitrogen Oxides (NO_x), submitted February 2008

Volume VI: Health Risk Assessment, submitted May 2008 and updated October 2008

Volume VII: Particulate Matter Air Quality Impact Analysis and Supplemental Health Risk Assessment for the Proposed Gregory Canyon Landfill, submitted March 2009.

This document is intended to replace the previously submitted Volume VII of the permit application. This Volume VII update includes an AQIA for nitrogen dioxide (NO₂), carbon monoxide (CO), and particulate matter (PM₁₀ and PM_2.5), and an update to the previously submitted HRA (Volume VI). The purpose of this Volume VII update is to address revised and refined emission estimates, more recent advances in dispersion modeling, the new Federal 1-hour ambient air quality standard (AAQS) for NO₂, updated (pre-project) ambient air quality background data, new reference exposure levels (RELs) published by the California Office of Environmental Health Hazard Assessment (OEHHA) through August 2010, and diesel particulate matter (DPM) emissions from off-road equipment.

To prepare this updated AQIA and HRA, several steps had to be completed as follows: determine the pre-project (background) ambient concentration of NO₂, CO, PM_10, and PM_2.5 in the potential GCLF impact area, refine the emission estimates to represent emissions from proposed operations, perform dispersion modeling to assess potential ambient air quality impacts compared to national and state AAQS, and perform air toxic risk assessment modeling. Each of these steps is discussed in the following paragraphs which correspond to major sections of this document.

1.2 PRE-PROJECT AMBIENT CONCENTRATIONS OF CO, NO₂, AND PARTICULATE MATTER

The proposed GCLF will be located in northern San Diego County off Highway 76 approximately three miles east of Interstate 15 and two miles southwest of the community of Pala. Figures showing the location of the proposed project have been provided in previous Volumes of this permit application and are not repeated here.

The nearest SDAPCD ambient air quality monitoring station to the proposed project site is the Escondido station located about 15 miles south. This station monitors, among other parameters, CO and NO₂. Data from 2005 through 2009 were examined, and the maximum pre-project background concentrations are shown in Table 1-1. The

methodology and the basis for using the 7^th high background NO₂ value are discussed in Section 2 of this document. Note that the maximum background CO concentration did not change from that reported in the February 2008 Volume. Therefore, this update does not discuss potential CO impacts further, as that was discussed in Volume V.

Table 1-1

Pre-project (Background) Ambient Concentrations of CO and NO₂

Pollutant	Averaging Time	Background Concentration
CO	1-hour	5.9 ppm
CO	8-hour	3.6 ppm
NO₂	Daily First High 1-hour	152 ug/m³
	Daily 7^th High 1-hour	118 ug/m³
	Annual	34 ug/m³

Two years of meteorological and ambient air quality (PM₁₀ only) monitoring was conducted by GCL in calendar year 2002 and 2003. In order to determine the pre- project background concentrations of PM, the on-site PM₁₀ data were coupled with additional PM₁₀ and PM_2.5 monitoring data for calendar years 2002 through 2008 (2009 data are not available) at the Aqua Tibia Wilderness Area located approximately 10 miles northeast of the proposed project. The pre-project background PM₁₀ and PM_2.5 concentrations, along with the California and National AAQS (CAAQS and NAAQS) are shown in Table 1-2. More details are provided in Section 2 of this document,

Table 1-2

Pre-project (Background) Ambient Concentrations of Particulate Matter

Pollutant	Averaging Time	NAAQS (μg/m³)	CAAQS (μg/m³)	Most Stringent AAQS (μg/m³)	Background Concentration (μg/m³)
PM₁₀	24-hour	150	50	50	36.9
PM₁₀	Annual	None	20	20	17.6
PM2.5	24-hour	35	None	35	15.5
PM2.5	Annual	15	12	12	7.2

1.3 REFINED PARTICULATE EMISSION ESTIMATES

Emission estimates for all operations with the potential to emit pollutants have been provided in previous volumes of this permit application. However, the emission factors

and estimates in those volumes were conservative, upper bound estimates used primarily to determine applicable regulations and do not represent expected emissions. In order to better represent the potential ambient air quality impact of PM emissions, some of the emission estimates had to be refined – specifically emission estimates for unpaved roads, paved roads, excavation and unloading of landfill cover, wind erosion of exposed landfill surfaces, and blasting. The refinements are discussed in Section 3 of this document, and spreadsheets showing the PM emission calculations are included in Appendices A through F. Appendices G through J contain backup material for some of the emission calculations. Electronic versions of the spreadsheets are included electronically on a compact disc in Appendix K.

Refined emission estimates were calculated for Operational Years -2, 1, 8, 17, 22, and 23 (Operational Year -2 is initial construction of the landfill access roads and cells. Waste is first received in Operational Year 1). The basis for selection of these years is discussed in Section 3 of this document. The emission estimates are shown in Tables 1-3 through 1-5. The toxic emission totals in Table 1-5 include air toxics from fugitive landfill gas, landfill gas combusted in the flares, metals and other toxics contained in native soils, and DPM. The NO_x emissions do not include NO_x from off-road equipment, but those emissions are not considered to make a significant off-site impact as discussed in Section 4.3.

Table 1-3

Proposed GCLF Annual PM₁₀, and PM_2.5, and NO₂, Emission Estimates

Operational Year	PM₁₀	PM2.5	NO₂
Operational Year	Annual Emissions (tpy)	Annual Emissions (tpy)	Annual Emissions (tpy)
Year -2	68.2	15.3	1.5
Year 1	82.4	21.0	0.07
Year 8	55.0	16.8	9.6
Year 17	58.5	20.1	20.2
Year 22	37.4	16.3	25.1
Year 23	62.7	20.4	26.1

Table 1-4

Proposed GCLF Maximum Hourly PM₁₀, and PM_2.5, and NO₂, Emission Estimates

Operational Year	PM₁₀	PM2.5	NO₂
Operational Year	Maximum Hourly Emissions (lb/hour)	Maximum Hourly Emissions (lb/hour)	Maximum Hourly Emissions (lb/hour)
Year -2	131.7	21.2	68.0
Year 1	187.4	29.8	136.0
Year 8	60.6	13.1	2.2
Year 17	58.0	13.3	21.6
Year 22	50.3	11.2	5.7
Year 23	195.2	33.0	6.0

Table 1-5

Proposed GCLF Annual and Maximum Hourly Air Toxic Emission Estimates

Operational Year	Total toxics	Total toxics
Operational Year	Annual Emissions (tpy)	Maximum Hourly Emissions (lb/hour)
Year -2	8.7	15.7
Year 1	11.9	22.3
Year 8	14.9	9.6
Year 17	24.6	11.3
Year 22	18.9	26.7
Year 23	30.8	27.1

1.4 DISPERSION MODELING AND IMPACT ASSESSMENT

Dispersion models are used to estimate the potential off-site impact of project emissions. For this AQIA, the United States Environmental Protection Agency (USEPA)-approved AERMOD model was used with processed on-site meteorological data for calendar year 2002 and 2003. The on-site meteorological data were processed with the USEPA-approved AERMET processor by the SDAPCD with upper air data from the San Diego Miramar Station (World Meteorological Organization [WMO] No. 72293), surface meteorological data (primarily cloud cover) from the Ramona Airport, and on-site surface characteristics derived by the SDAPCD using the AERSURFACE processor. Effective data capture (i.e., the combination of on-site, upper air, and surface meteorological data) for 2002 was approximately 95% and data capture for 2003 approximately 85%. Meteorological data processing is further

discussed in Section 4 of this document. All six operational years were modeled for both meteorological data years and for NO₂, PM₁₀, and PM_2.5. The maximum impacts from the twelve combinations of modeled operational years and meteorological data years are shown in Table 1-6.

Table 1-6

Maximum NO₂, PM₁₀, and PM_2.5 Impacts

Pollutant	Operational Year	Meteorology Data Year	Averaging Time	Most Stringent AAQS (μg/m³)	Background Concentration (μg/m³)	GCLF Impact at PMI (μg/m³)	Project Background plus Project Impact
NO₂	-2	2002	1-hour	188 (Fed)	118	69.8	187.8
NO₂	23	2002	Annual	57 (CA)	0.8	34.0	34.8
PM₁₀	-2	2003	24-hour	50	9.9*	39.9	49.8
PM₁₀	22	2003	Annual	20	2.3	17.6	19.9
PM2.5	-2	2003	24-hour	35	8.3	15.5	23.8
PM2.5	22	2003	Annual	12	0.7	7.2	7.9

*Background value is for maximum impact day.

1.5 SUPPLEMENTAL HEALTH RISK ASSESSMENT

Volume VI of this permit application, submitted in May 2008 and updated in October 2008, presented a detailed Health Risk Assessment (HRA) for all potential toxic emissions from the landfill, including fugitive landfill gas, landfill gas flare emissions, and potential mineral and metal content of particulate emissions associated with handing native soils at the project site during landfill construction and operations. However, OEHHA published new RELs (chronic and acute) in December 2008 for six chemicals, four of which – arsenic, manganese, formaldehyde, and mercury – are potentially emitted from the proposed project. Also, the HRA was prepared using the Industrial Source Complex (ISC) dispersion model and a pre-December 2008 “express” version of the Hotspots Analysis and Reporting Program (HARP) model. Thus, an updated HRA is required. The HRA was conducted with the emissions and dispersion modeling discussed in Sections 3 and 4 of this document. The results are discussed in Section 5 of this document and are summarized in Table 1-7.

Table 1-7

Health Risk Assessment Results

Criteria	Location	Operational Year	Meteorological Data Year	Maximum HRA Results	Threshold of Concern
Cancer Risk	MEIR	Total all Years	2003	< 7.8 x 10^-6	10 x 10^-6
Cancer Risk	MEIW	Total all Years	2003	< 5.1 X 10^-6	10 x 10^-6
Chronic HI	MEIR	Year 1	2003	0.22	1.0
Chronic HI	MEIW	Year 1	2003	0.19	1.0
Acute HI	MEIR	Years 22, 23	2002, 2003	0.14	1.0
Acute HI	MEIW	Year 22	2003	0.13	1.0

1.6 SUMMARY

This Volume VII update of the air quality permit application shows that the emissions of NO₂, CO, PM₁₀, PM_2.5, and air toxics will not cause an exceedance of the relevant ambient air quality standards and health thresholds of concern.

2.0
PRE-PROJECT BACKGROUND AMBIENT AIR QUALITY

2.1 NO₂ BACKGROUND

There are no on-site ambient NO₂ data available, and the nearest ambient NO₂ data are from the Escondido, California site located about 15 miles south of the proposed project site. The Escondido data are available from the California Air Resources Board (CARB) Air Quality Almanac. Three different background values must be determined: daily 1-hour 1^st-high, daily 1-hour 8^th_high, and annual average concentrations. This is because the California 1-hour AAQS is a “not to exceed” value and the Federal 1-hour AAQS is a 98^th percentile average over 3 years value. The daily 8^th-high value is determined by recording the values of the top unique 8^th-highest days (i.e., a single day counts once).

Background data are available through calendar year 2009. Table 2-1 summarizes the 1-hour and annual average background in terms of parts per million (ppm) for the most recent three years of available data (as published by the CARB). Table 2-2 summarizes the same data in terms of micrograms per cubic meter (ug/m³). The conversion was based on sea-level pressure and 25 degrees Celsius per USEPA regulations (0.100 ppm = 188 ug/m³). In Tables 2-1 and 2-2, the daily 7^th-high concentration is used to represent the AAQS-relevant daily 8^th-high concentration. This is because USEPA regulations state that when data are incomplete, the rank has to be decreased to account for the missing data. Appendix S of 40 CFR Part 50 states that if between 15 and 64 days are missing, then the daily 7^th-high must be used. In 2007, approximately 36 days (875 hours) were missing; in 2008, approximately 50 days

(1,206 hours) were missing; and in 2009, approximately 19 days (449 hours) were missing. Thus, the daily 7^th-high is appropriate.

Table 2-1

Background NO₂ Concentrations (ppm)

Calendar Year	1^st-High 1-hour Concentration	Daily 7^th-High 1-hour Concentration	Annual Average Concentration
Calendar Year	(ppm)	(ppm)	(ppm)
2007	0.072	0.060	0.016
2008	0.081	0.071	0.018
2009	0.073	0.058	0.016
Maximum	0.081	NA	0.018
3-year Average	NA	0.063	NA

Annual is an arithmetic average. NA = not relevant for published AAQS.

Table 2-2

Background NO₂ Concentrations (ug/m³)

Calendar Year	1^st-High 1-hour Concentration	Daily 7^th-High 1-hour Concentration	Annual Average Concentration
Calendar Year	(μg/m³)	(μg/m³)	(μg/m³)
2007	135	113	30
2008	152	134	34
2009	137	109	30
Maximum	152	NA	34
3-year Average	NA	118	NA

Annual is an arithmetic average. NA = not relevant for published AAQS.

2.2 CO BACKGROUND

The previously submitted Volume V: Air Quality Impact Analysis (AQIA) for Carbon Monoxide (CO), and Nitrogen Oxides (NO_x), submitted February 2008, used calendar years 2005 through 2007 CO background data as those were the most recent data available at the time or preparation of Volume V. Table 2-3 compares the maximum values from 2005 through 2007 to those for 2007 to 2009. As shown, the older values are still the largest. Therefore, the previously submitted Volume V impact analysis for CO does not need to be updated.

Table 2-3

Background CO Concentrations (ppm)

Calendar Year	1^st-High 1-hour Concentration	1^st-High 8-hour Concentration
Calendar Year	(ppm)	(ppm)
2005	5.9	3.1
2006	5.7	3.6
2007	5.2	3.2
2008	5.6	2.8
2009	4.4	3.5
Maximum	5.9	3.6

2.3 ON-SITE AMBIENT PARTICULATE MONITORING

Two years of meteorological and ambient air quality (PM₁₀ only) monitoring was conducted by GCL in calendar year 2002 and 2003. PM₁₀ monitoring was conducted once every six days per the USEPA protocol and included a primary and co-located sampler. The 24-hour daily results are shown in Table 2-4 for year 2002 and Table 2-5 for year 2003. Annual averages are shown in Table 2-6.

Table 2-4

On-site 24-Hour Ambient PM₁₀, Calendar Year 2002

Date	Primary Sampler	Date	Primary Sampler
Date	PM₁₀ (μg/m³)	Date	PM₁₀ (μg/m³)
1/3/2002	16.8	7/1/2002	21.6
1/9/2002	19.7	7/7/2002	21.5
1/15/2002	19.9	7/13/2002	17.1
1/21/2002	18.0	7/19/2002	19.2
1/27/2002	14.9	7/25/2002	22.6
2/2/2002	13.6	7/31/2002	24.8
2/8/2002	19.3	8/6/2002	21.7
2/14/2002	24.4	8/12/2002	30.0
2/20/2002	16.3	8/18/2002	25.2
2/26/2002	25.2	8/24/2002	23.4
3/10/2002	16.8	8/30/2002	23.1
3/18/2002	9.2	9/5/2002	32.6
3/21/2002	18.4	9/11/2002	28.1
3/27/2002	13.4	9/17/2002	21.8
4/2/2002	19.7	9/23/2002	32.9
4/8/2002	18.6	9/29/2002	6.8

Date	Primary Sampler	Date	Primary Sampler
Date	PM₁₀ (μg/m³)	Date	PM₁₀ (μg/m³)
4/14/2002	21.1	10/5/2002	25.6
4/20/2002	22.3	10/11/2002	18.4
4/26/2002	10.2	10/17/2002	19.4
5/2/2002	16.1	10/23/2002	17.3
5/8/2002	22.0	11/4/2002	36.4
5/14/2002	36.0	11/10/2002	10.2
5/20/2002	12.4	11/16/2002	11.5
5/26/2002	16.9	11/22/2002	17.1
6/1/2002	16.6	11/28/2002	15.7
6/7/2002	18.4	12/4/2002	16.7
6/13/2002	23.3	12/10/2002	14.9
6/19/2002	28.2	12/16/2002	15.0
6/25/2002	23.0	12/22/2002	8.0
		12/28/2002	10.5

Table 2-5

On-site 24-Hour Ambient PM₁₀, Calendar Year 2003

Date	Primary Sampler	Date	Primary Sampler
Date	PM₁₀ (μg/m³)	Date	PM₁₀ (μg/m³)
1/9/2003	9.7	7/2/2003	30.4
2/2/2003	32.6	7/8/2003	26.7
2/8/2003	13.5	7/14/2003	29.9
2/15/2003	10.1	7/20/2003	22.1
2/20/2003	13.0	7/26/2003	22.6
2/26/2003	10.3	8/1/2003	16.2
3/4/2003	7.0	8/7/2003	22.0
3/10/2003	19.3	8/13/2003	32.9
3/16/2003	13.2	8/25/2003	22.5
3/22/2003	17.7	8/31/2003	26.0
3/28/2003	15.2	9/6/2003	36.8
4/3/2003	9.2	9/12/2003*	28.8
4/9/2003	19.7	9/18/2003*	32.1
4/15/2003	8.5	9/24/2003*	33.0
4/23/2003	13.1	10/6/2003*	35.1
4/27/2003	13.0	10/12/2003*	26.8
5/9/2003	16.8	10/18/2003*	30.5
5/15/2003	17.7	10/24/2003*	36.9
5/21/2003	31.3	10/30/2003*	17.0

Date	Primary Sampler	Date	Primary Sampler
Date	PM₁₀ (μg/m³)	Date	PM₁₀ (μg/m³)
5/27/2003	23.5	11/5/2003*	16.5
6/2/2003	23.1	11/11/2003*	21.6
6/8/2003	11.6	11/17/2003*	9.6
6/14/2003	24.2	11/23/2003*	14.7
6/20/2003	17.8	11/29/2003*	16.3
6/26/2003	28.8	12/11/2003*	11.5
		12/17/2003*	16.9

*The primary sampler failed after September 6, 2003, and thus the co-located sampler data were added to the data set for September 12, 2003 through December 17, 2003.

Table 2-6

On-Site Annual Average Ambient PM₁₀ Concentration

Date	Primary Sampler
Date	PM₁₀ (μg/m³)
2002*	19.7
2003*	20.6

*Arithmetic average

2.4 AMBIENT PARTICULATE MONITORING AT AQUA TIBIA WILDERNESS AREA In addition to the on-site PM₁₀ monitoring data, there are PM₁₀ and PM_2.5 data available from the Aqua Tibia Wilderness Area IMPROVE station located approximately 10 miles northeast of the GCL proposed location. The average concentrations of PM₁₀ and PM_2.5 for years 2002 to 2008 are shown in Table 2-7. (Only the first three quarters of 2009 data from Aqua Tibia data are available as of August 2010, and thus no annual average is available).

Table 2-7

Aqua Tibia Ambient PM₁₀ and PM_2.5, Annual Averages for 2002-2008

Year	PM₁₀ (μg/m³)	PM_2.5 (μg/m³)
2002	19.9	8.5
2003	16.9	7.8
2004	16.1	6.6
2005	13.2	5.7
2006	13.7	6.3
2007	17.6	6.7
2008	15.4	6.2

2.5 DETERMINATION OF BACKGROUND AMBIENT PARTICULATE CONCENTRATIONS FOR THE PROPOSED PROJECT IMPACT AREA

2.5.1 Background Concentrations for the Annual Standards

Normally, the ambient air quality data collected by GCL at the proposed site would be used to determine the pre-project background concentrations. However, the 2002 and 2003 ambient data are not representative of conditions that will exist in calendar years 2011 through 2035 for the GCLF (i.e., two years to start operations and operations through Operational Year 22) because of at least three notable circumstances: (1) there was an aggregate quarry operating next to the proposed project location in 2002 and 2003, (2) there were significant wild fires in San Diego County in 2002 and 2003,

(3) background ambient air quality continues to improve despite additional population. Therefore, a more complex analysis had to be performed to determine the annual average background to be used in this particulate matter AQIA.

Since the extreme wildfires occurred during 2002 and 2003, neither the data from the on-site monitor nor the Aqua Tibia data during those time periods could be used for background data. Rather, the highest concentration from a non-wildfire year nearest the 2002 and 2003 monitoring period was used. Those years are 2004, 2005 and 2006.

Since there were no on-site data in 2004, 2005, or 2006, the Aqua Tibia data were used as a base but were scaled up by the ratio of on-site to Aqua Tibia data for 2002 and 2003. This does not account for the quarry but does account for the wild fire problem.

Table 2-8 shows the on-site versus Aqua Tibia annual average concentrations for 2002 and 2003. The average of both years was used to determine the scaling factor. Table 2-8 shows that the on-site data were a factor of 1.092 greater than the Aqua Tibia data (20.15 divided by 18.45 = 1.092).

Table 2-8

Aqua Tibia and On-Site PM₁₀, Averages of 2002-2003

Location	Year	PM₁₀ (μg/m³)	PM₁₀ Average (μg/m³)
Aqua Tibia	2002	19.9	18.45
Aqua Tibia	2003	17.0	18.45
On-Site	2002	19.7	20.15
On-Site	2003	20.6	20.15

This factor was then applied to the 2004 through 2006 Aqua Tibia data as shown in Table 2-9, and the maximum value of all three years (17.6 μg/m³ in 2004) was used as the annual background concentration of PM₁₀.

Table 2-9

Estimated On-Site Annual Average PM₁₀ Concentrations for 2004-2006

Year	PM₁₀ (μg/m³)	Factor for Increasing PM₁₀	PM₁₀ (μg/m³)
2004	16.1	1.092	17.6
2005	13.2	1.092	14.4
2006	13.7	1.092	15.0

Since there were no on-site PM_2.5 monitoring data, an annual average PM_2.5 value had to be derived. The same on-site to Aqua Tibia ratio of 1.092 was applied to the maximum monitored PM_2.5 at Aqua Tibia for 2004, 2005, and 2006. This results in a PM_2.5 annual average background of 7.2 μg/m³ (6.6 μg/m³ [for 2004 from Table 2-7] times 1.092 = 7.2 μg/m³).

2.5.2 Background Concentrations for the 24-Hour Standards

For the 24-hour PM₁₀ impact assessment, the maximum background PM₁₀ concentration on the maximum impact day was added to the maximum modeled impact. This maximum value was compared to the standard. If the maximum impact day occurred on a day where no data were taken (i.e., the ambient data were taken per the USEPA once every six day schedule), the data were interpolated between the two observed values.

No on-site data exist for PM_2.5, and therefore, the 24-hour background concentration for PM_2.5 must also be derived. Table 2-7 shows that at Aqua Tibia, the annual PM_2.5 is 42 percent of the annual PM₁₀ (The average annual PM₁₀ concentration for 2002 through

2008 is 16.1 ug/m³, and the average annual PM_2.5 concentration for the same period is

6.8 ug/m³.) This percentage from Aqua Tibia data was applied to the on-site PM₁₀ data to derive the PM_2.5 24-hour concentrations. Thus, the maximum 24-hour PM_2.5 concentration was 15.5 μg/m³ [(36.9 μg/m³) x (42%)].

In summary, the annual and 24-hour background concentrations for PM₁₀ and PM_2.5 are shown in Table 2-10. Note that the 24-hour PM_2.5 standard is stated in terms of the 98^th percentile. However, for purposes of this AQIA, the maximum values were used (i.e., the 1^st-high modeled impact was added to the 1^st-high background).

Table 2-10

Pre-project (Background) Ambient Concentrations of Particulate Matter

Pollutant	Averaging Time	Background Concentration (μg/m³)
PM₁₀	24-hour	36.9*
PM₁₀	Annual	17.6
PM2.5	24-hour	15.5
PM2.5	Annual	7.2

*Note that on a given maximum impact day,

the actual monitored background PM10 value is used.

3.0
REFINED EMISSION ESTIMATES

Volume IV of this permit application, submitted in May 2008 and updated in October 2008, presented emission estimates for all potential emissions, including particulate matter and air toxics. However, the methods used to prepare the emission estimates in October 2008 were conservative, upper bound estimates used primarily to determine applicable regulations. In order to perform a representative NO₂, PM₁₀, and PM_2.5 AQIA and HRA, refined emission estimates for some of the proposed project activities had to be made. Refined emission estimates for particulate matter were made for the following Operational Years:

Year -2 is the start of construction;
Year 1 is the first year of operation with continuing construction;
Year 8 represents standard operating conditions;
- Year 17 represents standard operating conditions and is the operational year where landfill gas emissions may be greatest according to one landfill gas generation model (the BAS model; see Section 3.4 of this document);
- Year 22 is the last year of full operation; and
  - Year 23 represents final closure activities and the maximum landfill gas emissions based on the SDAPCD parameters for the LANDGEM model.

The basis for these years as maximum impact years is discussed in Volumes IV and V of this permit application. Appendices A through F contain hard copy printouts of the refined emission spreadsheets for Operational Years -2, 1, 8, 17, 22, and 23. Electronic versions of the spreadsheets are contained on the enclosed compact disc in Appendix K. Some of the refined emission factors are discussed in the following sections, while details regarding all emission factors and assumptions are contained in the Appendices.

3.1 REFINED EMISSION ESTIMATES FOR WIND EROSION, LOADING, UNLOADING, AND EXCAVATION

3.1.1 Silt Content of Fill/Cover Material

The landfill will be designed and operated such that adequate cover material is capable of being obtained on-site. The silt content of that material is a key parameter in estimating particulate emissions. Therefore an analysis of available data was conducted to estimate the silt content.

The fill/cover material is derived from either the landfill excavation material or borrow/stockpile area excavation materials. The fill/cover will include soils, weathered rock and hard rock. The derivation of the average silt content of the mixture of materials is provided in Appendix G. Based on the material quantities, location of derivation and volumes, the silt content is estimated as 20.7% from materials derived from the landfill and 33% from materials derived from the borrow/stockpile areas. The borrow/stockpile area silt content estimate is considered conservatively high as it is based on soil borings taken in areas where hollow stem augers are advanced into softer alluvium, which is not likely representative of all borrow/stockpile area materials.

Use of the borrow/stockpile area soils will begin after Operational Year 8, and a silt content of 33% is used where this soil is loaded, unloaded, spread, compacted, or stored. However, during Operational Years -2 through 8 in which materials are blasted and excavated, the landfill soils will incorporate a mix of several different types of soil and rock. For these operational years, the silt content is based on the test data and analysis shown in Appendix G. The silt content for hard rock of 4% is based on the recommended value by SDAPCD and is assumed to be conservatively high silt content. The silt contents for top soil of 50.33% and weathered rock of 20.99% are calculated values based on the geometric mean of soil boring silt test data, where the geometric mean is based on the bulldozer emissions equation. Finally, the weighted silt content percentage was derived using the geometric mean silt content values for topsoil, weathered rock, and hard rock using the quantities of materials based on the soil balance sheet from Appendix F of Volume IV of the Air Permit Application, dated October 2008.

3.1.2 Refined Emission Factor for Wind Erosion

Emissions of particulates will occur from wind erosion in areas that are being actively disturbed and also in areas that have previously been disturbed and not fully vegetated. Areas that are fully vegetated are assumed to have zero emissions from wind erosion as these areas will not have increased emissions from landfill operations over those from natural conditions. Unvegetated areas that are not being actively disturbed will have lower emissions than the areas that are being actively disturbed because the inactive areas are likely to form a crust on top of the soil as well as naturally becoming

revegetated. Consequently, the inactive non-vegetated areas have a lower emission rate than the active areas. Typically, for municipal solid waste operations, no more than two acres will be actively disturbed at any time within the landfill area. The previously disturbed areas that are not yet vegetated will include areas that have been disturbed within the past year. It is assumed that previously disturbed areas will become fully vegetated within one year.

The wind erosion emission factors are derived from the United States Department of Agriculture wind erosion equation as required by SDAPCD. This equation is applicable to wind erosion from open areas and over-estimates wind erosion for GCL due to the canyon nature of the landfill. The landfill area as well as the borrow/stockpile areas are subject to wind erosion during the lifetime of the landfill. The landfill area will become disturbed during construction of the landfill as well as during landfill operations. During construction, the disturbed portions of the landfill during a calendar year could be on the order of 60 acres. The borrow/stockpile areas are also large areas (22 acres for Area A and 64 acres for Area B). The “stockpiles” would be created as excess cover material is moved from the landfill area during construction phases. Because scrapers would be used for the movement to the “stockpile” areas and not a conveyor stacker, the areas would be developed in large flat layers and not stacked into a typical conical shape. Further, the approximate dimensions of Stockpile A would be 1,200 feet by 850 feet, and the approximate dimensions of Stockpile B would be 2,200 feet by 1,200 feet. Thus, the areas would be described as large open flat regions rather than conical regions. Therefore, the stockpile areas can be considered “open areas” subject to the wind erosion equation used for other areas of the landfill.

In the dispersion modeling, wind erosion is modeled as occurring for 24 hours per day, 365 days per year as wind erosion occurs whether the landfill is in operation or not. However, per the USEPA in AP-42 Section 13.2 (USEPA 2006d), wind erosion does not occur if the wind speed is less than 12 mph. A wind threshold velocity of 12 miles per hour (mph) or greater must occur to scour particles from an open exposed area in order for there to be windblown dust emissions. As a result the wind erosion emissions were turned off for hours with wind speeds below 12 mph. In order to account for all the calculated mass of emissions, however, the modeled emission rates were scaled in the model to ensure that all potential mass emitted was modeled.

3.1.3 Refined Emission Rate for Excavation

The emission factor for excavation was derived from the AP-42 bulldozing equation from Section 11.9, Western Surface Coal Mining (USEPA 1998). This equation calculates emissions in pounds per hour. For landfill construction and operations, the volume of material excavated was known; therefore, the AP-42 bulldozing equation was multiplied by the production rate of a typical bulldozer used for similar applications to convert the equation to pounds of emissions per 1000 cubic yards of material excavated. The emission factor equation is:

where,

EFex =

1.0(k )(S)^1.5

(M )1.4

EF_ex = Excavation emission factor (lbs/1000 cubic yards) k = Scaling factor (0.75 for PM₁₀)

S = Silt value of material being excavated

M =Moisture value of the material for controlled conditions R = Bulldozer production value (cubic yards/hour).

The silt value used in this equation was the silt value of the material as explained in Section 3.1.1; 20.7% for material originating from the landfill area or 33% for material originating from the borrow/stockpile areas. The moisture used in the equation was the moisture value at controlled conditions. The native moisture value (uncontrolled) of the material was assumed to be 6.71%, which is the average moisture value of the test data that was used for the silt calculations (Appendix G). Emissions are controlled through wetting, and the moisture content would be increased by 1.75%, to a total of 8.46%.

3.1.4 Refined Emission Factor for Loading and Unloading

Material loading and unloading at the landfill would be accomplished by the use of scrapers. Because scrapers load or unload material by spreading it and not via a batch dump, the AP-42 bulldozing equation as explained in Section 3.1.3 was also used for scraper activities. Further, because the scraper must travel as it is loading or unloading

material, emissions from scraper travel were also accounted for by using the AP-42 unpaved road equation from Section 13.2.2.

3.1.5 Refined Emission Factor for Handling Clay Liner Material

Clay liner material is imported to the site for construction of the landfill cells. This material is delivered wet and does not have a potential for significant emissions. The efficiency of clay liners is impaired if they are allowed to dry out during placement, therefore, the material is kept sufficiently wet, with approximately 18% moisture content. Emission factors were identified based on AP-42 Section 11.3 for Bricks and Related Clay Products. AP-42 Section 11.3 provides a PM₁₀ emission factor for raw (“dry”) clay with 4% moisture content of 0.53 lb/ton processed. AP-42 Section 11.3 also provides an emission factor for “wet” clay with 13% moisture content as 0.0023 lb/ton processed. Thus, there is a control efficiency of slightly more than 99.5% between 4% moisture and 13% moisture clay. Although this control efficiency was demonstrated, for purposes of estimating emissions at GCL, a more conservative control efficiency of 90% used for clay and applied to the SDAPCD’s emission factors for uncontrolled dozer and compactor emission equations. The resulting emission factors are shown in the Appendices.

3.1.6 Potential Wind Erosion Emissions from De-silting Basins

The de-silting basins are used to capture storm water runoff and, therefore, the material in the basins is wet and does not have the potential for wind erosion. Prior to the dry season, the material will be cleaned out and/or covered with gravel so that no dry, erodible material is exposed. Thus, there are no wind erosion emissions from the de- silting basins.

3.2 REFINED EMISSION ESTIMATES FOR ADDITIONAL ACTIVITIES

3.2.1 Rock crushing

During the early years of construction and excavation, a rock crusher will be used to crush rock that is used as part of the cover material. The annual emissions from the rock crusher are based on the amount of rock to be crushed and individual emission factors for each of the pieces of equipment used in the crusher. Hourly and daily emissions from the rock crusher are based on the maximum throughput of the equipment. The emission factors are based on AP-42, Fifth Edition, Volume I (January

1995), and from SDAPCD guidance documents as noted in the footnotes to the Appendices. Rock is crushed only down to gravel size material with a silt content of less than 4 percent. There is additional rock (i.e., shot rock and boulders) that is also excavated from the landfill area, but it is simply stored, not crushed.

3.2.2 Municipal Solid Waste Spreading and Compacting

When the municipal solid waste arrives at the facility, after weighing, it is placed in the active cell. The refuse is then spread with a bulldozer and compacted. Emissions from spreading the refuse are calculated with the AP-42 bulldozing equation as shown in Section 3.1.3. Emissions from compacting the municipal solid waste are calculated from the AP-42 bulldozing equation presented in Section 3.1.3 and the unpaved road equation from AP-42, Section 13.2.2 because the compactor must travel as it compacts down the refuse. The emission factors and emissions from this activity are detailed in the Appendices.

3.2.3 Cover Material Compacting

Daily cover is placed over the municipal solid waste (either soil or alternative daily cover [ADC]) after it has been spread and compacted. Daily cover material would have been previously spread from the scraper unloading activity. It will then be compacted down similar to the compacting of the municipal solid waste; however, the silt and moisture values are that of the soil material as presented in Section 3.1.1. The emission factors and emissions from this activity are detailed in the Appendices.

3.2.4 Blasting

During construction of the landfill, blasting of hard rock will occur as part of the excavation. There will be no more than one blast per day, and the acreage blasted at any one time can range from one-sixteenth of an acre to one-half of an acre. The amount of material that needs to be blasted varies from year to year, with most blasting occurring during Operational Year -2, but a limited amount of blasting could occur during operational years when cover material is being excavated from Borrow/Stockpile Area B, such as in Operational Year 17.

In order to estimate emissions from blasting, emission factors from AP-42 Section

11.9.2 were used as shown in the Appendices. One-sixteenth, one-eighth, one-quarter,

and one-half acre blasts were used in combination based on the potential location of the blasts and the amount of material that must be blasted.

3.2.5 Road Maintenance and Grading

The unpaved roads and other areas of the active landfill will need to be maintained with a road grader. Potential emissions from road grading were estimated with AP-42, Fifth Edition, Volume I, Section 11.9, and the operational assumptions shown in the Appendices.

3.3 REFINED EMISSION ESTIMATES FOR ON-SITE ROADS

There are four types of roads on the proposed project site: paved, unpaved stabilized, unpaved unstabilized, and unpaved roads at the active face of refuse fill and soil borrow/stockpile areas (Areas A and B), termed “road ends”. Different emission factors were used for each type of road as follows.

3.3.1 Paved Roads

Paved road emissions were estimated with the equations in AP-42, Fifth Edition, Section 13.2.1 and the addition of a speed factor as requested by SDAPCD. The AP- 42 emission factors are based on all types of road including freeways. The data used to develop the emission factors in AP-42 were for speeds of 10 miles per hour (mph) to 55 mph, a mid-point speed of 32.5 mph. However, at the proposed site, traffic will average a speed of less than 7.5 mph (one-half the speed limit of 15 mph). Therefore, the AP-42 emission factors were adjusted by a factor of 7.5/32.5 or 0.23. The equations and other factors are detailed in the Appendices. No emission control efficiency was assumed for the paved roads even though they will be actively maintained and controlled to minimize potential particulate emissions.

3.3.2 Unpaved Stabilized Roads

One of the key variables in determining particulate emissions from unpaved roads is the control efficiency that can be attained using biodegradable organic polymer suppressants, water, road design and construction, and other techniques. For this AQIA, it was assumed that an emission control efficiency of 97 percent could be attained. This was based on numerous conversations with various dust suppressant vendors who confirmed that better than 97 percent reduction in airborne emissions from haul roads in an industrial setting is achievable.

The second key parameter is silt content of the surface soil on the haul road. The SDAPCD document, “Haul Road Emissions” (SDAPCD 1998c), specifies a default value for surface material silt content for an unpaved road of 15 percent. This silt content value was used, despite the fact that the data provided by the SDAPCD (SDAPCD 2009b) shows a median silt content for soils in the vicinity of the project of

9.8 percent.

The remaining parameters and emission factor equations are shown in the Appendices.

3.3.3 Unpaved Unstabilized Roads

It is not possible to actively stabilize all of the unpaved roads, since the stabilization effort requires engineering and “building” the unpaved road. Some of the roads change location too frequently to be stabilized sufficiently to achieve 97 percent control. For these roads, 90 percent control efficiency was assumed, which can be achieved with watering and/or application of an organic polymer to non-engineered unpaved roads.

3.3.4 Road Ends

For road ends of the scraper roads near the active areas of excavation or daily cover operations, the silt content was increased to 20.7 percent or 33 percent to match the cover soil silt content associated with the area of activity. It was assumed that approximately 200 to 500 feet of each end of the scraper haul road and the last 200 feet of the main haul road for refuse trucks would have the higher silt content. A control efficiency of 90 percent was assumed, which can be achieved with watering and/or application of an organic polymer to non-engineered unpaved roads.

3.4 REFINED EMISSION ESTIMATES FOR LANDFILL GAS

The October 2008 update to Volume IV, Annual Emission Inventory, presented an analysis of potential landfill gas (LFG) generation quantities and the required capacity of the landfill gas flares. The range of methane gas generation rates was based on a proprietary landfill gas generation model developed by Bryan A. Stirrat and Associates (BAS), and the number of flares, flare capacity, and maximum flare emissions were based on the USEPA default landfill gas generation model, LANDGEM.

The BAS model is based on USEPA first order decomposition equation but considers site specific factors related to the local climate and geology. The model was developed based on experience in LFG collection and control system design and analysis of operating data from landfills in Southern California. While the specific parameters for this model are proprietary, the resulting methane production was illustrated in Figure 10-1 in Volume IV. That figure shows several methane production curves with potential methane production ranging from approximately 1,800 scfm up to 4,500 scfm.

Volume IV also showed a USEPA LANDGEM methane production curve in Figure 10-1. The figure shows that using USEPA LANDGEM, the methane production peaked at approximately 3,250 scfm, using LANDGEM parameters of k = 0.02 (year^-1) and Lo = 100 (m³/Mg). These values are the recommended defaults for arid landfills on page 2.4-4 of AP-42, Fifth Edition, Volume I, Section 2.4, Municipal Solid Waste Landfills,Final Section.

The Methane Generation Rate Constant (k) determines the rate of landfill gas generation. The constant “k” is a function of moisture content in the landfill refuse, availability of nutrients for methanogens, pH, and temperature. For areas receiving less than 25 inches of rainfall per year, the recommended value for k is 0.02.

The Potential Methane Generation Capacity (Lo) is a constant that represents the potential capacity of a landfill to generate methane. “Lo” depends on the amount of cellulose (mostly green waste) in the refuse. Given the increasing use of green waste for compost or energy generation, and that processed green waste is a secondary source of alternative daily cover, the landfill is not likely to accept substantial amounts of green waste for disposal or alternative daily cover, and it is acceptable to use a relatively low Lo value such as the 100 m³/Mg used in Volume IV.

However, the SDAPCD has its own default parameters for LANDGEM that are slightly different from the USEPA parameters. The SDAPCD uses a k of 0.02 and a Lo of 3,530 ft³/ton. Converting the SDAPCD Lo value to m³/Mg gives a Lo of a 110 m³/Mg. If LANDGEM is run with those parameters, peak methane production is 3,675 scfm or about 13% greater than the peak of 3,250 scfm presented in Volume IV. The LANDGEM model run is shown in Appendix J and included on the Appendix K compact

disc. Note that the maximum methane generation occurs in Year 23 with the SDAPCD parameters rather than Year 17 with the Volume IV parameters.

All of the landfill gas and flare emissions in this updated AQIA and HRA are based on the SDAPCD parameters, and do not utilize the BAS estimates. In addition, it is assumed that at least 90 percent of the landfill gas generated in the landfill will be captured and combusted in the flares.

3.5 PM_2.5 EMISSION ESTIMATES

For some of the emissions sources, such as unpaved roads, scaling factors for calculating PM_2.5 emission factors are published in AP-42. For other emission sources, PM_2.5 to PM₁₀ ratios had to be determined from references other than AP-42. Unpaved roads, wind erosion, unloading, and blasting were sources that had AP-42 PM_2.5 scaling factors. Of those sources with AP-42 references, two methods were applied: calculating PM_2.5 emission factors directly by using the appropriate scaling factor, or applying a ratio based on k-factors. For the sources without AP-42 references, general guidance from a Midwest Research Institute (MRI) document (MRI 2006) was applied. This reference stated that for typical uncontrolled fugitive dust sources, existing test data supports PM_2.5 to PM₁₀ ratios in the range of 0.1 to 0.15. To be conservative, the

0.15 value was used for sources without direct AP-42 references.

3.5.1 PM_2.5 Emission Factor for Blasting

The PM_2.5 emission factor for blasting was calculated directly out of AP-42. Volume IV of this air permit application uses AP-42, Section 11.9 for Western Surface Coal Mining (USEPA 1998b) for the PM₁₀ emission factor. Table 11.9-1 in AP-42 lists the TSP emission factor equation for blasting of coal or overburden along with the scaling factors for both PM₁₀ and PM_2.5. The scaling factor of 0.03 was applied to the TSP equation to get the corresponding PM_2.5. The corresponding PM₁₀ scaling factor is 0.52; therefore, the percentage of PM₁₀ that is PM_2.5 resulting from blasting is 6%.

3.5.2 PM_2.5 Emission Factor for Excavation, Loading and Unloading Soil

The emission factor for unloading soil was presented in Section 3.1.4 of this document. The current version of AP-42 (USEPA 2006b) lists a particle size multiplier (k-factor) of

0.053 for PM_2.5. This value was applied to the equation presented in Section 3.1.3 of

this document. Since the corresponding k-factor for PM₁₀ is 0.35, the percentage of PM₁₀ that is PM_2.5 resulting from unloading is 15%.

3.5.3 PM_2.5 Emission Factor for Unpaved and Paved Roads

Volume IV of this air permit application references the SDAPCD document “Haul Road Emissions” (SDAPCD 1998c) for calculating emissions from unpaved roads. The SDAPCD document uses the unpaved haul road equation from Section 13.2.2 of AP-42 (USEPA 1995c). This version of AP-42 lists k-factors of 0.36 and 0.095 for PM₁₀ and PM_2.5 respectively. These k-factors result in PM_2.5 being 26% of PM₁₀. However, the current version of AP-42 (USEPA 2006a) lists k-factors of 1.5 and 0.15 for PM₁₀ and PM_2.5 respectively. Since the unpaved haul road equation in the current version of AP- 42 is different from the January 1995 version, these updated k-factors could not be directly applied. Since the updated k-factors result in a PM_2.5 to PM₁₀ ratio of 0.1, the PM_2.5 emissions used in this AQIA for unpaved roads are approximately 2.6 times greater than would be calculated with the newer version of AP-42.

Likewise, paved road emissions are calculated with an older version of the paved road equation from Section 13.2.1 of AP-42 (USEPA 1995c), as requested by SDAPCD. This version of AP-42 lists k-factors of 0.016 and 0.0073 for PM₁₀ and PM_2.5 respectively. These k-factors result in PM_2.5 being 7.7% of PM₁₀. However, the current version of AP-42 (USEPA 2006a) lists k-factors of 0.016 and 0.0024 for PM₁₀ and PM_2.5 respectively. Thus, the paved road PM_2.5 emissions used in this AQIA are approximately 3.0 times greater than would be calculated with the newer version of AP- 42.

3.5.4 PM_2.5 Emission Factor for Wind Erosion

As stated in Section 3.1.2 of this document, the emission factors for wind erosion were referenced from the USDA aggregate wind erosion equation. The current version of AP-42 (USEPA 2006c), Section 13.2.5 for Industrial Wind Erosion contains a PM_2.5 to PM₁₀ ratio of 0.15 based on k-factors. Although the equation for industrial wind erosion presented in the November 2006 version of AP-42 was not used to derive the wind erosion emission factor for PM₁₀, the AP-42 ratio was applied.

3.5.5 PM_2.5 Emission Factor for Excavation and Daily Cover Operations

Section 3.1.2 of this document discusses the PM₁₀ emission factor used for excavation. It was assumed that the PM_2.5 to PM₁₀ ratio for excavation and daily cover operations would be the same as for unloading of soil since the processes all involve the creation of fugitive dust by moving soil. Thus, a PM_2.5 to PM₁₀ ratio of 0.15 was applied to emissions from excavation and daily cover operations.

3.5.6 PM_2.5 Emission Factor for Drilling

The PM₁₀ emission factor for wet drilling was referenced out of AP-42 (USEPA 2004a), Section 11.19.2 for Crushed Stone Processing and Pulverized Mineral Processing. There is no PM_2.5 emission factor for wet drilling, so an estimation based on a similar mechanical process was used. Table 11.19.2-2 from AP-42 (USEPA 2004a) lists emission factors for both PM₁₀ (0.00054 lb/ton) and PM_2.5 (0.00010 lb/ton) for controlled tertiary rock crushing (controlled tertiary rock crushing is also a wet process). Since wet drilling and controlled tertiary rock crushing are both wet mechanical processes performed on rock, their PM_2.5 to PM₁₀ ratios should be similar. Therefore, a PM_2.5 to PM₁₀ ratio of 0.185 (0.00010 divided by 0.00054) was used to estimate PM_2.5 emissions from drilling.

3.5.7 PM_2.5 Emission Factor for Landfill Gas Flares

The PM₁₀ emission factor for emissions from landfill gas flares is referenced in Table 2- 9 of Volume IV of this air permit application; however, a PM_2.5 emission factor is not listed in Volume IV. Emissions from flares are produced by combusting the landfill gas in the flares. Combustion processes produce much smaller particles than mechanical processes such as moving soil. Therefore, it was assumed that 100% of the PM₁₀ emissions produced by combustion of landfill gas in the flares would be PM_2.5.

3.6 EMISSION ESTIMATES FOR DIESEL PARTICULATE MATTER

Potential emissions of diesel particulate matter (DPM) from off-road equipment are included in the PM₁₀ and PM_2.5 emission totals and are also included in the individual air toxic and summary air toxic emissions. The methodology and DPM emission factors are shown in the Appendices. It was assumed that the off-road equipment would meet Tier 2 standards (i.e., the engines would be newer than model year 2000 for equipment greater than or equal to 300 brake horsepower [bhp] and model year 2002 for equipment less than 300 bhp). It is likely some of the off-road equipment will actually

meet Tier 3 or 4 emission limits, thus this is a conservative (i.e., over-estimate) assumption for DPM emission factors. It was assumed that all DPM is PM_2.5 or smaller.

3.7 REFINED EMISSION ESTIMATES FOR AIR TOXICS

The Appendices detail the methods used to calculate potential air toxic emissions. These emissions include constituents of the soil, emissions of DPM from off-road equipment, constituents of fugitive landfill gas that may escape from the surface of the landfill, and constituents of the landfill gas that is combusted using flares.

As discussed in the previous section, the unpaved roads will be stabilized with the use of a bio-degradable soil stabilizer such as SOILTAC®, manufactured by Soilworks®, LLC. It has been reported (a September 4, 2009 Material Safety Data Sheet, MSDS, shown in Appendix G) that SOILTAC® may contain trace amounts of two volatile organic chemicals as trace constituents of the organic polymer that constitutes SOILTAC®. The two chemicals are acetone and vinyl acetate. Acetone is not a volatile organic chemical as defined by regulation, and it also does not have any published health thresholds contained in the HARP model (see the section on toxics modeling). Vinyl acetate is included in HARP.

However, a more recent chemical analysis indicates that neither acetone nor vinyl acetate are contained in the SOILTAC® organic polymer (which is expected). The chemical analysis showing this fact is contained in Appendix I. Although Soilworks® is certain that neither acetone nor vinyl acetate are contained in the organic polymer, for purposes of this AQIA and HRA, emissions from both chemicals have been estimated and included in the air toxics emissions and HRA. The emissions are shown on the spreadsheets contained in the Appendices.

3.8 SUMMARY OF EMISSION ESTIMATES

The refined emission estimates result in the NO₂, PM₁₀, and PM_2.5 annual and daily emission estimates shown in Table 3-1, maximum hourly emission rates shown in Table 3-2, and potential total air toxic emissions shown in Table 3-3.

Refined emission estimates were calculated for Operational Years -2, 1, 8, 17, 22, and

23. The emission estimates are shown in Tables 3-1 through 3-3. The toxic emission totals in Table 3-3 include air toxics from fugitive landfill gas, landfill gas combusted in

the flares, metals and other toxics contained in native soils, and DPM. The NO_x emissions do not include NO_x from off-road equipment, but those emissions are not considered to make a significant off-site impact as discussed in Section 4.3.

Table 3-1

Proposed GCLF Annual PM₁₀, and PM_2.5, and NO₂, Emission Estimates

Operational Year	PM₁₀	PM2.5	NO₂
Operational Year	Annual Emissions (tpy)	Annual Emissions (tpy)	Annual Emissions (tpy)
Year -2	68.2	15.3	1.5
Year 1	82.4	21.0	0.07
Year 8	55.0	16.8	9.6
Year 17	58.5	20.1	20.2
Year 22	37.4	16.3	25.1
Year 23	62.7	20.4	26.1

Table 3-2

Proposed GCLF Maximum Hourly PM₁₀, and PM_2.5, and NO₂, Emission Estimates

Operational Year	PM₁₀	PM2.5	NO₂
Operational Year	Maximum Hourly Emissions (lb/hour)	Maximum Hourly Emissions (lb/hour)	Maximum Hourly Emissions (lb/hour)
Year -2	131.7	21.2	68.0
Year 1	187.4	29.8	136.0
Year 8	60.6	13.1	2.2
Year 17	58.0	13.3	21.6
Year 22	50.3	11.2	5.7
Year 23	195.2	33.0	6.0

Table 3-3

Proposed GCLF Annual and Maximum Hourly Air Toxic Emission Estimates

Operational Year	Total toxics	Total toxics
Operational Year	Annual Emissions (tpy)	Maximum Hourly Emissions (lb/hour)
Year -2	8.7	15.7
Year 1	11.9	22.3
Year 8	14.9	9.6
Year 17	24.6	11.3
Year 22	18.9	26.7
Year 23	30.8	27.1

4.0
DISPERSION MODELING AND IMPACT ASSESSMENT

Ambient air quality impact modeling was previously conducted and reported in Volumes V and VI of this permit application. Volume V presented an AQIA for CO and NO_x, while Volume VI presented an HRA. The modeling in Volume VI was based on the ISC model and on-site surface and San Diego Miramar Station (WMO No. 72293) upper air meteorological data for calendar years 2002 and 2003. However, in December 2006 the USEPA published revised modeling guidelines that require the use of a dispersion model called AERMOD. The AERMOD model uses a combination of on-site, off-site surface, and off-site upper air meteorological data to better represent dispersion at the proposed project site. The modeling in Volume V was based on the AERMOD model with on-site surface, San Diego Miramar Station (WMO No. 72293) upper air meteorological data, and San Diego Miramar Station (Weather-Bureau-Army-Navy [WBAN]) No. 93107) off-site surface meteorological data for calendar years 2002 and 2003.

4.1 AMBIENT AIR QUALITY STANDARDS

For the NO₂, PM₁₀, and PM_2.5 impact assessment, the total impact of the proposed project plus background is compared to the California and Federal AAQS. Table 4-1 shows the relevant standards.

Table 4-1

Relevant National and California Ambient Air Quality Standards

(Source: California Air Resources Board, August 3, 2010) (All standards expressed in ug/m³ except as noted.

Converted at sea level and 25 degrees Celsius)

Pollutant	Averaging Time	CAAQS (ug/m³)	NAAQS (ug/m³)	Most Stringent Standard (ug/m³)
NO₂	1-hour	339	188 (Note 1)	188 (Note 1)
NO₂	Annual	57	100	57
PM₁₀	24-hour	50	150	50
PM₁₀	Annual	20	No separate standard	20
PM2.5	24-hour	No separate standard	35 (Note 2)	35 (Note 2)
PM2.5	Annual	12	15	12

Note 1: Three-year average of the 98th percentile of the daily maximum 1-hour concentration.

Note 2: Three year average of the 98th percentile daily concentration.

4.2 METEOROLOGICAL DATA AND DISPERSION MODEL

For this Updated AQIA and HRA, the calendar years 2002 and 2003 on-site meteorological data were supplemented by Ramona Airport surface and San Diego Miramar Station (WMO No. 72293) upper air data. The meteorological data were processed by the SDAPCD and provided to GCL for this purpose. The SDAPCD specified the surface characteristics and supplemental surface meteorological data to be used. The key surface characteristics are presented in Table 4-1. The meteorological data were processed with the AERMET processor (Version 06341) and the AERSURFACE processor (Version 08009). AERSURFACE is a processor that uses land cover data to evaluate surface characteristics by month of the year and sector for input into AERMET. Twelve sectors were used for determining surface characteristics, but the only parameter that differed by sector for each month was surface roughness. The surface roughness values in Table 4-2 are averages of the twelve sectors. Ramona surface meteorological data were used to supplement the on- site data because the on-site data did not contain measurements of cloud cover and other required parameters.

Table 4-2

Surface Characteristics Used for Processing the On-Site Meteorological Data

	Autumn	Transitional Spring	Midsummer
Months	January – February, October – December	March – April	May – September
Albedo	0.18	0.16	0.18
Bowen Ratio	1.08	0.62	0.71
Average Surface Roughness	0.301	0.252	0.301

To reflect the limitations of the on-site wind instrumentation used, the wind speed threshold used in AERMET was set at 0.4 m/sec. Therefore, any on-site wind speed measurement below 0.4 m/sec was treated as calm.

The resultant data capture for the processed data is shown in Table 4-3. The data capture for on-site data included parameters of wind speed, wind direction, temperature, and sigma theta. The Ramona Airport data capture included parameters of station pressure, precipitation, opaque/total sky cover, temperature, relative humidity, wind direction, and wind speed. Finally, the Miramar upper air data capture included

parameters of atmospheric pressure, height, dry bulb temperature, and dew point temperature. The data capture for the processed data is calculated as the percentage of hours with missing data out of the total annual hours. For example, the AERMOD output file reports 2002 as having 497 hours with missing data out of 8760 hours for the entire year. The processed meteorological data set used is included on the Appendix K compact disc.

Table 4-3 Meteorological Data Capture

	2002	2003
On-site	99.5%	96.9%
Ramona Airport	94.9%	93.0%
Miramar Upper Air	96.5%	96.6%
Combined Processed Data	94.3%	84.9%

The processed meteorological data were used in conjunction with the refined emission estimates discussed in Section 3 of this volume and the AERMOD model (AERMOD Breeze 07026, Breeze Version 6.2.2) to evaluate potential ambient particulate impacts for 1-hour, 24-hour, and annual averages.

4.3 NITROGEN OXIDES CONVERSION

Most processes initially emit nitrogen oxide (NO), not nitrogen dioxide (NO₂). The NO is converted to NO₂ over time in the atmosphere through various reactions but primarily through reaction with ozone. In fact, it is generally recognized that the amount of ozone available in the atmosphere controls the amount of NO to NO₂ conversion that can occur on an annual basis (this is termed “ozone limiting”). Short term conversion of NO to NO₂ has not generally been a topic of significant study by the USEPA because until recently (early 2010), only an annual AAQS for NO₂ had been federally published and the California 1-hour NO₂ standard was relatively large.

There are two significant sources of NO₂ emissions at the proposed project: NO_x emissions from the combustion of landfill gas in the flare and NO_x emissions from combustion of ANFO during blasting. A third potential source is off-road equipment. However, on an hourly basis, the total NO_x emissions from off-road equipment are on the order of one-third the flare and blasting emissions, and the NO_x emissions from off- road equipment are spread out over a large area (where the blasting and flare emissions are single point source emissions). Accordingly, the contribution of off-road

diesel NO_x emissions to the potential ambient air quality impact at the points of maximum impact (PMIs) for blasting and the flare will be insignificant. On an annual basis, NO_x emissions from off-road equipment are on the order of one-half total NO_x emissions. Again, since the equipment is spread out over a large area, the contribution of off-road equipment to the PMIs for blasting and the flare will be insignificant.

It is well established that normal natural gas combustion occurs at temperatures that cause the initial ratio of NO_x to NO₂ to be about 10 to 1. Therefore, for this AQIA, it was assumed that initially 10 percent of the NO_x was NO₂. On an annual basis, the USEPA suggests three methods for assessing conversion: the Ozone Limiting Method (OLM), the Plume Volume Molar Ratio Method (PVMRM), and a default 75 percent conversion method. The most conservative assumption is to simply assume that 100 percent of the NO_x is converted to NO₂. The default 75 percent conversion method is based on a nation-wide average of monitored NO₂ to NO_x ratios. It is not source or geographic specific. The PVMRM method is less conservative (i.e., predicts lower conversion percentages) than OLM, as it also considers the rate of entrainment of ozone into the plume. OLM assumes that the only limiting factor on conversion is the amount of available ozone (i.e., there is infinite time and infinite mixing available for conversion). It is geographic and source specific and conservative. To evaluate the ambient annual average impact of NO₂ from the flare, 100 percent conversion was conservatively assumed. For the 1-hour average evaluation, it was conservatively assumed that OLM applies, even though OLM only applies when there is a relatively long time for conversion. This is because the flare has continuous NO_x emissions.

The blasting NO_x emissions are quite different from flare emissions. During a blast, combustion occurs nearly instantaneously, and there is only one blast per day. Secondly, the blasting temperatures are much higher, so the initial amount of NO₂ versus NO_x is much smaller. Four research papers examined the relative proportion of NO₂ in the NO_x emitted from ANFO blasts. The most relevant paper examined NO₂ conversion at an open cut coal mine in Australia (NO_x Emissions from Blasting Operations in Open-cut Coal Mining, Atmospheric Environment 42 (2008) pages 7874 – 7883). This paper found the average ratio of NO to NO₂ was 27 to 1 (or NO_x to NO₂ ratio of 28 to 1, i.e., NO₂ is 3.6% of NO_x). This average was over a time frame of zero to about 10 minutes. The other papers used blast chambers to assess the NO₂

conversion. One paper calculated a rate constant for conversion (Behavior of Nitrogen Oxides in the Product Gases from Explosive Detonation, R. Mainiero, J. Rowland III, M. Harris, and M. Sapko, NIOSH). This paper showed 2% conversion at 1 minute after the blast, 4% after 2 minutes, 6% after 3 minutes, 8% after 4 minutes, 9% after 5 minutes, and 19% after 10 minutes. Two other papers using a blast chamber reported conversion after 10 minutes of 35% and 50%.

The maximum off-site impact of NO₂ from blasting occurs when the blast is very near the property boundary (on the order of 100 to 250 meters) and there is a low wind speed such that there is limited dispersion and entrainment into the plume of ambient air. If the wind speed is 1 meter per second (m/s) it takes the plume only 2 minutes to reach the property boundary (i.e., to travel 120 meters). Therefore, the 10-minute conversion times are not relevant. However, a comparison of the 10-minute papers does show that the one paper that calculated a rate constant may underestimate conversion by as much as a factor of approximately 2.5 (i.e., if the conversion percentage is 50% after 10 minutes and the rate constant calculations show only 19% conversion, the rate constant calculation under calculates conversion by 50/19 = approximately 2.5). For a 2 minute travel time, the rate constant method resulted in 4% conversion. If the rate constant underestimates by a factor of 2.5, then at 2 minutes, the conversion could be 10% instead of 4%. It is also recognized that blasting may occur at distances further from the property boundary. Although at further distances, the increased dispersion reduces the concentration of NO₂ faster than conversion percentages increase the concentration of NO₂. To be conservative, (i.e., over estimate), a constant 19% conversion was assumed for the 1-hour NO₂ impact of blasting. This is most likely a factor of at least 2 to 5 times too great. For the annual average impact assessment, 100% conversion was conservatively assumed.

There are two additional complexities related to evaluating the potential ambient air quality impact of blasting: plume height for NO₂ and PM emissions, and the nature of the 1-hour federal NO₂ standard compared to the California standard.

For plume height, for PM emissions, it was assumed that the PM is emitted at ground level, even though there is some plume rise of particulates, and thus this is a conservative (over-estimate) assumption. On the other hand, since NO_x emissions are

caused by combustion and there is considerable thermal buoyancy associated with the blast, a plume height had to be calculated. The USEPA-recommended OBODM (Open Burning, Open Detonation) model was used to calculate the plume height. The plume height calculated by OBODM was about 10 to 50 meters; depending on the size (i.e., amount of ANFO and acreage) of the blast (the OBODM runs are included electronically on the Appendix K compact disc). For dispersion modeling, the release height is the mid-point of the plume rise, which was used in the model.

The federal NO₂ AAQS is stated as a three-year average probability, while the California standard is stated as “not to exceed”. Accordingly, for evaluation of the potential impacts compared to the California standard evaluation, the first-high modeled concentration was added to the first-high background concentration. For evaluation of the potential impacts compared to the Federal standard, the first-high modeled concentration was added to the 7^th-high background (as discussed previously). This is an over-estimate of the potential impact, as the probability distribution is a combination of modeled plus background values; not simply background. Nevertheless, it will be used for this AQIA.

4.4 NO₂ IMPACT RESULTS

Potential ambient NO₂ impacts of blasting and the flare were modeled for all six operational years, using the methodology discussed previously. For the 1-hour AAQS, blasting was assumed to occur at a location that was nearest the property boundary and produces the greatest potential impact (a one-sixteenth acre blast about 250 meters from the north property boundary for landfill blasting). For the annual AAQS, the total amount of blasting needed in each operational year was compiled with a weighted average into a single blast source near the centroid of the areas that could experience blasting. The results are shown in Tables 4-4 and 4-5. The potential NO₂ impacts are less than the relevant California or Federal standards.

Maximum Potential 1-Hour Impact of NO₂

(in terms of ug/m³)

Operational Year	Year -2	Year 1	Year 8	Year 17	Year 22	Year 23
Meteorological Year	2002	2003	2003	2003	2003	2003
Maximum 1-hour Impact (1^st-High)	69.8	61.5	14.3	45.8	37.3	38.6
1^st-High 1-hour Background (California)	152	152	152	152	152	152
Total 1-hour Impact (California)	221.8	213.5	166.3	197.8	189.3	190.6
California AAQS	339	339	339	339	339	339
7^th-High 1-hour Background (Federal)	118	118	118	118	118	118
Total 1-hour Impact (Federal)	187.8	179.5	132.3	163.8	155.3	156.6
Federal AAQS	188	188	188	188	188	188

Table 4-5

Maximum Potential Annual Impact of NO₂

(in terms of ug/m³)

Operational Year	Year -2	Year 1	Year 8	Year 17	Year 22	Year 23
Meteorological Year	2003	2002	2002	2002	2002	2002
Maximum Annual Impact	0.03	0.001	0.3	0.6	0.7	0.8
Annual Background	34	34	34	34	34	34
Total Annual Impact	34.0	34.0	34.3	34.6	34.7	34.8
California AAQS	57	57	57	57	57	57
Federal AAQS	100	100	100	100	100	100

Various sizes of blasts will be needed depending on the nature of the material being blasted and the distance of the blast from the property boundary. As a sensitivity analysis, different blast sizes (one-sixteenth, one-eighth, one-quarter, and one-half of an acre) were modeled in both the landfill area and Borrow/Stockpile Area B. The smallest blast size and distance to the property boundary were determined where the 1- hour federal NO₂ standard would still be protected (the Federal standard is more stringent than the California standard). Table 4-6 shows these minimum distances. The sensitivity model runs are included on the Appendix K compact disc.

Minimum Blasting Distances

Blast Size	Minimum Distance from Northern Property Line for the Landfill Area (meters)	Minimum Distance from Western Property Line for Borrow/Stockpile Area B (meters)	Minimum Distance from Eastern Property Line for Borrow/Stockpile Area B (meters)
One-sixteenth acre	250	285	165
One-eighth acre	265	300*	175*
One-quarter acre	415	475*	275*
One-half acre	650	750*	430*

*For Borrow/Stockpile Area B, only the one-sixteenth acre scenario was modeled and the minimum distances determined. The distances for larger blasts were estimated from the ratio of distances at the Landfill Area compared to the Borrow/Stockpile Area B for one-sixteenth acre (e.g., 285 m for west end Borrow/Stockpile Area B divided by

250 m for Landfill Area at one-sixteenth acre times 265 m for Landfill Area one-eighth acre = 300 m for Borrow/Stockpile Area B one-eighth acre). Calculated values were rounded to the nearest 5 meters.

4.5 PARTICULATE MATTER IMPACT RESULTS

4.5.1 Landfill Operational Schedule

As stated in Volume IV and Volume VI of this air permit application, the landfill will operate Monday through Saturday, except for holidays, for a total of 307 days per year. During construction (Operational Years -2 and -1), it was assumed that construction would occur 10 hours per day (7:00 a.m. to 5:00 p.m.) on Monday through Friday and nine hours per day on Saturday (8:00 a.m. to 5:00 p.m.). During landfill operation (Operational Years 1 through 22), the landfill will operate for eleven hours per day (7:00

a.m. to 6:00 p.m.) on Monday through Friday and nine hours per day on Saturday (8:00

a.m. to 5:00 p.m.).

This operational schedule was incorporated into the dispersion model by using variable emission rates in the model. Since the years that were modeled were operational years, the emission sources were turned on in the model from 7:00 a.m. to 6:00 p.m., and turned off the rest of the hours for Monday to Friday. For Saturdays, the model was turned on from 8:00 a.m. to 5:00 p.m.; however, since the emission rates were calculated based on an eleven hour day, a source scaling factor of 1.22 (11 divided by 9) was used for the hours that the model was turned on. This is the same as modeling the amount of activity in an eleven hour day into a nine hour day for mass balance consistency, and is a conservative approach. Sundays were completely turned off in the model. The only exceptions to the above operational schedule were for flares,

landfill gas and wind erosion. These sources were modeled as occurring 24 hours per day, 7 days per week, and 365 days per year.

As stated above, the landfill will operate for 307 days per year. However, with the model turned off on Sundays, 313 days per year are being modeled as the holidays cannot be accounted for in the model. Therefore, when annual emission rates were being calculated, it was assumed that emissions were occurring over 313 days instead of 307 for mass balance consistency. Again, this is a conservative approach in that six extra days are being considered in the model over actual operations.

Especially during construction and some of the operational years, it is not possible for all activities to occur at the maximum individual daily rate simultaneously. For example, the maximum daily amount of excavation is 10,000 cubic yards (cy) of material per day. On any given day, all of that material may be transported to only Borrow/Stockpile Area B, or some may be left in the landfill footprint and the remaining material transported to both of the borrow/stockpile areas, and/or blasting may occur. However, one would never conduct blasting of hard rock at the same time as moving blasted hard rock (i.e., shot rock) to one of the borrow/stockpile areas, or blasting would never occur at the same time as drilling holes for loading ANFO. Therefore, a sensitivity analysis was conducted for each combination of activities and, for example, in Operational Year -2, it was found that the maximum potential particulate matter impact occurs when there is a combination of (1) excavating and moving 5,000 cy of material to Borrow/Stockpile Area A, (2) excavating and moving 5,000 cy of material to the fill area for construction (no more than 5,000 cy of material will be moved to Borrow/Stockpile Area A in any given day), and (3) blasting one-quarter acre. In short, it was found that blasting creates more emissions than hauling hard rock to the borrow/stockpile areas. The worst case combination of operational impacts is shown in the model input files contained on the compact disc of Appendix K, and were used in this AQIA.

4.5.2 24-Hour and Annual Emission Calculations

In calculating 24-hour emissions, daily operational parameters were taken from Appendix F of Volume IV (GCL 2008a) of this air permit application. Daily vehicle miles traveled for the trash haul trucks were calculated from the maximum amount of waste that the landfill can accept (5,000 tons/day). Emissions for operations involving the movement of soil, such as excavation, unloading, and travel on stockpile roads, were

calculated based on maximum daily equipment usages and maximum daily soil balances. Hourly emissions were typically calculated as the daily emission value divided by eleven operational hours per day.

Annual emissions were calculated using annual operational parameters that were taken from Appendix F of Volume IV (GCL 2008a) of this air permit application. Annual vehicle miles traveled for the trash haul trucks were calculated assuming the maximum daily amount of trash will be accepted each day the landfill is operating (5,000 tons/day x 307 days/year = 1,535,000 tons/year). Annual emissions for operations involving the movement of soil were based on annual soil balance needs rather than maximum daily equipment thresholds or daily soil balances.

Further, as part of the emission refinement for this AQIA, for both the annual and 24- hour emissions calculations, the “average” road lengths used in Volume IV of this permit application to calculate emissions were not used, rather the actual expected road lengths in each year were used.

4.5.3 Revised Modeling Parameters

Most of the modeling parameters for this Volume VII update were kept consistent with what was used in Volume VI of this air permit application; however, a few modeling parameters were revised to better represent the landfill operations and configuration. One of the parameters modified was the height of the trash haul trucks. Originally in Volume VI of this air permit application, all vehicles were estimated at a height of 15 feet; however, it was determined that a more accurate height estimate for trash haul trucks would be 10 feet. The scrapers that travel on the stockpile haul roads were set at a height of 12 feet.

The results of the modeling are discussed in the following sections. The model input and output files are included electronically on the Appendix K compact disc, and these files show the UTM coordinates of the points of maximum impact.

4.5.4 PM₁₀ Impact Results for 24-Hour AAQS

For the 24-hour impact assessment, for each operational year, the ten-highest modeled impact days were combined with the background concentrations on those days to

calculate the maximum potential impact. The results are shown in Tables 4-7 through 4-12.

Table 4-7¹

Maximum PM₁₀ Impacts for Operational Year -2

Rank	Model Impact (µg/m³)	Daily Background (µg/m³)	Combined Impact (µg/m³)	Date
Meteorological Year 2002
1st	24.5	15.2	39.7	12/9/2002
2nd	16.6	19.3	35.9	1/17/2002
3rd	15.3	12.7	27.6	12/18/2002
4th	14.9	16.2	31.6	11/26/2002
5th	13.4	15.2	28.6	12/9/2002
6th	13.3	9.7	23.0	12/26/2002
7th	12.9	8.8	21.7	12/24/2002
8th	12.6	8.8	21.4	12/24/2002
9th	11.6	17.5	29.1	1/22/2002
10th	10.5	16.4	26.9	11/25/2002
Meteorological Year 2003
1st	39.9	9.9	49.8	1/6/2003
2nd	32.7	15.5	48.2	11/26/2003
3rd	15.7	9.7	25.4	1/9/2003
4th	15.5	16.9	32.4	12/24/2003
5th	14.8	10.7	25.5	1/10/2003
6th	14.5	29.4	43.9	2/3/2003
7th	12.7	16.9	29.6	12/23/2003
8th	11.6	19.9	31.5	2/62003
9th	11.4	14.5	25.9	1/14/2003
10th	11.4	10.2	21.6	1/1/2003

¹ Table updated January 10, 2011

Rank	Model Impact (µg/m³)	Daily Background (µg/m³)	Combined Impact (µg/m³)	Date
Meteorological Year 2002
1st	20.2	15.9	36.1	11/29/2002
2nd	16.4	15.9	32.3	11/27/2002
3rd	14.9	16.8	31.7	1/2/2002
4th	14.1	16.1	30.2	12/6/2002
5th	12.7	19.3	32.0	1/17/2002
6th	11.6	16.2	27.8	11/26/2002
7th	11.4	9.9	21.3	9/30/2002
8th	11.2	17.5	28.7	1/22/2002
9th	11.0	19.9	30.9	1/14/2002
10th	10.5	14.3	24.8	1/30/2002
Meteorological Year 2003
1st	31.5	9.9	41.4	1/6/2003
2nd	28.3	9.9	38.2	1/6/2003
3rd	24.5	9.8	34.3	1/8/2003
4th	19.2	29.4	48.6	2/3/2003
5th	19.1	9.7	28.8	1/9/2003
6th	17.8	11.5	29.3	12/11/2003
7th	12.9	12.4	25.3	2/10/2003
8th	12.5	16.9	29.4	12/23/2003
9th	10.6	11.8	22.4	2/11/2003
10th	10.3	16.4	26.7	1/16/2003

Rank	Model Impact (µg/m³)	Daily Background (µg/m³)	Combined Impact (µg/m³)	Date
Meteorological Year 2002
1st	12.7	15.9	28.6	11/29/2002
2nd	11.3	15.2	26.5	12/9/2002
3rd	8.4	8.8	17.2	12/24/2002
4th	7.8	16.4	24.2	12/5/2002
5th	7.7	13.8	21.5	2/1/2002
6th	7.1	11.5	18.6	12/19/2002
7th	6.9	11.5	18.4	12/19/2002
8th	6.8	11.5	18.3	12/19/2002
9th	6.2	16.4	22.6	12/2/2002
10th	6.1	12.7	18.8	12/18/2002
Meteorological Year 2003
1st	13.1	15.5	28.6	11/26/2003
2nd	10.6	9.9	20.5	1/6/2003
3rd	9.3	15.5	24.8	11/26/2003
4th	8.9	9.8	18.7	1/8/2003
5th	7.5	14.5	22.0	1/14/2003
6th	7.3	15.1	22.4	12/2/2003
7th	7.1	12.3	19.4	12/9/2003
8th	7.1	10.1	17.2	1/3/2003
9th	7.0	15.1	22.1	12/2/2003
10th	7.0	16.9	23.9	12/17/2003

¹ Table updated January 10, 2011

Rank	Model Impact (µg/m³)	Daily Background (µg/m³)	Combined Impact (µg/m³)	Date
Meteorological Year 2002
1st	13.4	15.9	29.3	11/29/2002
2nd	12.7	15.9	28.6	11/29/2002
3rd	10.0	8.8	18.8	12/24/2002
4th	8.8	16.4	25.2	12/5/2002
5th	8.1	13.8	21.9	2/1/2002
6th	8.0	10.1	18.1	12/27/2002
7th	7.8	19.3	27.1	1/17/2002
8th	7.1	11.5	18.6	12/19/2002
9th	7.0	16.4	23.4	12/2/2002
10th	6.8	16.4	23.2	12/2/2002
Meteorological Year 2003
1st	15.1	9.8	24.9	1/8/2003
2nd	14.6	10.7	25.3	1/10/2003
3rd	12.0	9.7	21.7	1/9/2003
4th	11.6	29.4	41.0	2/3/2003
5th	8.9	11.5	20.4	12/11/2003
6th	8.7	16.9	25.6	12/24/2003
7th	8.5	16.9	25.4	12/23/2003
8th	8.3	9.9	18.2	1/6/2003
9th	7.8	10.2	18.0	1/2/2003
10th	7.8	29.4	37.2	2/3/2003

¹ Table updated January 10, 2011

Rank	Model Impact (µg/m³)	Daily Background (µg/m³)	Combined Impact (µg/m³)	Date
Meteorological Year 2002
1st	20.9	15.2	36.1	12/9/2002
2nd	16.3	16.4	32.7	12/2/2002
3rd	14.5	16.4	30.9	12/2/2002
4th	14.3	10.1	24.4	12/27/2002
5th	12.8	13.4	26.2	11/18/2002
6th	12.0	15.9	27.9	11/29/2002
7th	11.4	27.7	39.1	11/6/2002
8th	11.0	27.7	38.7	11/6/2002
9th	10.9	8.4	19.3	12/23/2002
10th	10.4	15.0	25.4	12/13/2002
Meteorological Year 2003
1st	29.2	15.5	44.7	11/26/2003
2nd	18.8	24.0	42.8	1/24/2003
3rd	16.2	9.7	25.9	1/9/2003
4th	14.7	12.4	27.1	12/12/2003
5th	14.4	15.5	29.9	11/26/2003
6th	13.8	16.9	30.7	12/24/2003
7th	13.0	23.1	36.1	1/23/2003
8th	12.7	15.5	28.2	11/26/2003
9th	12.6	16.0	28.6	12/16/2003
10th	12.2	23.1	35.3	1/23/2003

¹ Table updated January 10, 2011

Maximum PM₁₀ Impacts for Operational Year 23

Rank	Model Impact (µg/m³)	Daily Background (µg/m³)	Combined Impact (µg/m³)	Date
Meteorological Year 2002
1st	21.9	15.9	37.8	11/27/2002
2nd	13.9	16.2	30.1	11/26/2002
3rd	12.4	16.4	28.8	11/25/2002
4th	11.0	19.0	30.0	1/18/2002
5th	9.0	12.7	21.7	12/18/2002
6th	8.8	14.3	23.2	1/30/2002
7th	8.8	16.4	25.2	11/25/2002
8th	8.3	15.2	23.5	12/9/2002
9th	7.7	14.5	22.2	1/29/2002
10th	7.6	19.0	26.6	1/18/2002
Meteorological Year 2003
1st	35.3	9.9	45.2	1/6/2003
2nd	29.5	15.5	45.0	11/26/2003
3rd	13.8	9.8	23.7	1/8/2003
4th	13.1	9.8	22.9	1/7/2003
5th	11.5	10.2	21.7	1/1/2003
6th	11.3	10.2	21.5	1/1/2003
7th	8.7	17.3	26.0	1/17/2003
8th	8.6	16.9	25.5	12/22/2003
9th	7.9	17.3	25.2	1/17/2003
10th	7.6	16.9	24.6	12/23/2003

¹ Table updated January 10, 2011

The maximum PM₁₀ impact occurs in Operational Year -2 and is 49.8 ug/m³ compared to the most stringent AAQS of 50 ug/m³ (California).

4.5.5 PM₁₀ Impact Results for Annual AAQS

The maximum annual PM₁₀ impacts are shown in Table 4-13. The maximum impact occurs in Operational Year 22 with 2003 meteorology and is 19.9 ug/m³ compared to the most stringent AAQS of 20 ug/m³ (California).

Maximum Potential Annual Impact of PM₁₀

(in terms of ug/m³)

Operational Year	Year -2	Year 1	Year 8	Year 17	Year 22	Year 23
Meteorological Year	2003	2003	2003	2003	2003	2003
Maximum Annual Impact	1.8	1.8	1.5	1.7	2.3	1.6
Annual Background	17.6	17.6	17.6	17.6	17.6	17.6
Total Annual Impact	19.4	19.4	19.1	19.3	19.9	19.2
California AAQS	20	20	20	20	20	20
Federal AAQS	None	None	None	None	None	None

4.5.6 PM_2.5 Impact Results for 24-Hour AAQS

The maximum 24-hour PM_2.5 impacts are shown in Table 4-14. The maximum impact occurs in Operational Year -2 with 2003 meteorology and is 23.8 ug/m³ compared to the most stringent AAQS of 35 ug/m³ (Federal). (Note that the maximum combined impact in Table 4-14 is the 1^st-high modeled impact plus the 1^st-high background, which is much more conservative methodology than required for the Federal standard, which is stated as a 3-year average 98^th percentile.)

Table 4-14¹

Maximum Potential 24-Hour Impact of PM_2.5

(in terms of ug/m³)

Operational Year	Year -2	Year 1	Year 8	Year 17	Year 22	Year 23
Meteorological Year	2003	2003	2003	2002	2003	2003
Maximum 24-Hour Impact	8.3	7.5	3.6	3.7	7.6	6.1
24-hour Background	15.5	15.5	15.5	15.5	15.5	15.5
Total Annual Impact	23.8	23.0	19.1	19.2	22.1	21.6
California AAQS	None	None	None	None	None	None
Federal AAQS	35	35	35	35	35	35

¹ Table updated January 10, 2011

Note: The Federal AAQS is a 98th percentile standard. But for purposes of this table, the maximum first-high values are shown.

4.5.7 PM_2.5 Impact Results for Annual AAQS

The maximum annual PM_2.5 impacts are shown in Table 4-15. The maximum impact occurs in Operational Year 22 with 2003 meteorology and is 7.9 ug/m³ compared to the most stringent AAQS of 12 ug/m³ (California).

Table 4-15

Maximum Potential Annual Impact of PM_2.5

(in terms of ug/m³)

Operational Year	Year -2	Year 1	Year 8	Year 17	Year 22	Year 23
Meteorological Year	2003	2003	2003	2003	2003	2002
Maximum Annual Impact	0.4	0.5	0.5	0.5	0.7	0.5
Annual Background	7.2	7.2	7.2	7.2	7.2	7.2
Total Annual Impact	7.6	7.7	7.7	7.7	7.9	7.7
California AAQS	12	12	12	12	12	12
Federal AAQS	15	15	15	15	15	15

5.0
SUPPLEMENTAL HEALTH RISK ASSESSMENT

Volume VI of this permit application, submitted in May 2008 and updated in October 2008, presented a detailed Health Risk Assessment (HRA) for all potential toxic emissions from the landfill, including fugitive landfill gas, landfill gas flare emissions, and potential mineral and metal content of particulate emissions associated with handling native soils at the project site during landfill operations. However, the HRA was prepared using the ISC dispersion model and a pre-December 2008 “express” version of the HARP model. In December 2008, OEHHA published new RELs (chronic and acute) for six chemicals, four of which, arsenic, manganese, formaldehyde, and mercury, are potentially emitted from the proposed project. In addition, the previous HRA used the BAS landfill gas generation model. Therefore, the HRA had to be updated. The HRA was conducted using the emissions discussed in Section 3 of this document and shown in the Appendices, plus the most current version of the HARP model as of August 2010. HARP model runs are included on the Appendix K compact disc. HARP model runs were conducted for all six operational years.

5.1 HARP MODEL SETTINGS

The HARP model was run with the settings required by the SDAPCD. Specifically the model settings include the following:

Applied the most current pollutant and health database (health.mdb February 2009) for the RELs and cancer risk factors.
For Residential exposure, the exposure pathways were enabled for inhalation, home grown produce (at 0.15 ingestion fractions), dermal absorption, soil ingestion, and mothers milk;
There is no still water bodies near the proposed landfill site, nor any meaningful source of aquatic food, and thus the water pathway was not included for residential or worker receptors;
For Worker exposure, the exposure pathways were enabled for inhalation, dermal absorption and soil ingestion;
Applied a Deposition Rate of 0.5 m/s
- Applied the “Derived (Adjusted) Cancer Risk” adjustment in accordance with the Air Resources Board Recommended Interim Risk Management Policy for Inhalation-Based Residential Cancer Risk, dated October 9, 2003; and
- Applied worker exposure adjustment factors to reflect the operating schedule as 24/11 hrs/day x 7/6 days per week = 2.545, except for Operational Year -2 where the operating schedule was 24/10 hrs/day x 7/6 days per week = 2.8.

5.2 HARP MODEL RESULTS

5.2.1 Potential Cancer Risk and Hazard Indices

The HARP model results for Operational Years -2, 1, 8, 17, 22, and 23 are shown in Table 5-1 for 2002 meteorology and Table 5-2 for 2003 meteorology. The results for the chronic and acute hazard indices are well below the threshold of concern (hazard index of 1.0).

Table 5-1

HARP Model Results for 2002 Meteorology

Criteria	Location	Year -2	Year 1	Year 8	Year 17	Year 22	Year 23
Cancer Risk (x 10^-6)	MEIR	7.5	29.5	6.1	7.7	11.0	12.8
	Receptor	18	82	43	45	44	43
	MEIW	2.8	10.8	1.1	3.4	4.4	4.6
	Receptor	46	46	46	46	46	46
Chronic HI	MEIR	0.15	0.21	0.12	0.10	0.08	0.15
	Receptor	18	82	43	43	18	18
	MEIW	0.10	0.18	0.07	0.10	0.07	0.10
	Receptor	46	46	46	46	46	46
Acute HI	MEIR	0.02	0.03	0.03	0.10	0.14	0.14
	Receptor	47	47	44	80	44	27
	MEIW	0.03	0.02	0.02	0.10	0.12	0.12
	Receptor	46	46	46	20	20	20

Table 5-2

HARP Model Results for 2003 Meteorology

Criteria	Location	Year -2	Year 1	Year 8	Year 17	Year 22	Year 23
Cancer Risk (x 10^-6)	MEIR	8.0	31.8	6.8	8.4	11.8	13.7
	Receptor	18	82	43	45	44	43
	MEIW	3.0	12.0	1.3	3.8	5.1	5.2
	Receptor	46	46	46	46	46	46
Chronic HI	MEIR	0.15	0.22	0.12	0.11	0.05	0.09
	Receptor	18	82	43	43	18	18
	MEIW	0.10	0.19	0.08	0.11	0.08	0.11
	Receptor	46	46	46	46	46	46
Acute HI	MEIR	0.03	0.05	0.03	0.10	0.14	0.14
	Receptor	18	41	43	111	14	27
	MEIW	0.03	0.05	0.02	0.11	0.13	0.12
	Receptor	46	46	46	19	19	20

The cancer risk results presented in Tables 5-1 and 5-2 assume a continuous 70-year exposure. However, as the Tables show, the impact for each operational year is highly variable as it is a function of operations in any given year. Operational Years -2, -1 and 1 are construction years (including in Year 1 the start of refuse disposal). Therefore, the potential cancer risk for those years only last one year each and are caused by on-site diesel emissions. The potential cancer risk in Operational Years 17, 22 and 23 is from flare operations during the peak of landfill gas generation (peak landfill gas generation is Year 23). However, landfill gas generation reaches a peak in only a single year, and for other years it starts as zero (little or no refuse has been decomposed in the first year and all of the refuse has been decomposed in the last year). Furthermore, after 23 years the landfill has reached capacity and is closed, therefore, there are no further diesel emissions. Accordingly, the potential cancer risk results in Tables 5-1 and 5-2 must be interpreted in light of the variability in operations and landfill gas generation rates.

For the Maximum Exposed Individual Residential (MEIR) receptor, two different analyses were conducted to identify the 70-year period that results in the largest total potential cancer risk. First, an analysis was conducted to identify the 70-year period that included the maximum amount of landfill gas emissions and associated risk. The results of that analysis are as follows:

Appendix K provides the result of the landfill gas generation model based on SDAPCD parameters. The maximum landfill gas generation occurs in Year 23, and is 3.649 x 10⁴ megagrams methane. The entire distribution of landfill gas generation in the model was evaluated to find the maximum total 70 years of landfill gas generation. The maximum total 70 years generation occurred from Year 8 through 77. This total was 1.601 x 10⁶ megagrams methane, or an average landfill gas generation rate over 70 years of

2.287 x 10⁴ megagrams methane per year. Thus, the dose over 70 years is

2.287 x 10⁴ divided by 3.649 x 10⁴, or 0.627 (63 percent) of the peak, and the potential cancer risk over 70 years is 63 percent of the cancer risk if the maximum landfill gas generation rate occurred for 70 years.

Meteorological year 2003 yields the maximum potential cancer risk. In Year 23, the total maximum cancer risk from Table 5-2 is 13.7 x 10^-6. Diesel particulate is responsible for 2.4 x 10^-6 of the total, and 11.3 x 10^-6 is from landfill gas and particulate matter emissions during facility closure. The landfill gas is responsible for most of the risk.

If one assumed that all of the non-diesel risk in Year 23 is from landfill gas, then the 70-year risk from landfill gas for Year 8 through 78 is 0.627 times 11.3 x 10^-6, or 7.1 x 10^-6 risk. This is a conservative over-estimate since part of the 11.3 x 10^-6 risk is from particulate matter emissions that will not occur beyond Year 23.

The diesel-only risk in Year 8 is 5.7 x 10^-6, Year 17 it is 2.8 x 10^-6, Year 22 it is

2.1 x 10^-6, and Year 23 it is 2.4 x 10^-6, or an average diesel risk of 3.3 x 10^-6. However, this risk only occurs for 15 years (Years 8 through 23). The equivalent 70-year diesel risk is, therefore, 3.3 x 10^-6 times 15 divided by 70, or 0.7 x 10^-6.

The total 70-year cancer risk is, therefore, 7.1 x 10^-6 (landfill gas and particulate) plus 0.7 x 10^-6 (diesel), or 7.8 x 10^-6.

The second analysis was similar, but included Year -2, Year -1, and Years 1 through

The results of that analysis are as follows:

Appendix K provides the result of the landfill gas generation model based on SDAPCD parameters. The maximum landfill gas generation occurs in Year 23, and is 3.649 x 10⁴ megagrams methane. The total landfill gas generated from Year -2 through Year 68 is a total of 1.491 x 10⁶ megagrams methane, or an average landfill gas generation rate over 70 years of

2.130 x 10⁴ megagrams methane per year. Thus the dose over 70 years is

2.130 x 10⁴ divided by 3.649 x 10⁴, or 0.584 (58 percent) of the peak, and the potential cancer risk over 70 years is 58 percent of the cancer risk if the maximum landfill gas generation rate occurred for 70 years.

Meteorological year 2003 yields the maximum potential cancer risk. In Year 23, the total maximum cancer risk from Table 5-2 is 13.7 x 10^-6. Diesel particulate is responsible for 2.4 x 10^-6 of the total, and 11.3 x 10^-6 is from landfill gas and particulate matter emissions during facility closure. The landfill gas is responsible for most of the risk.

If one assumed that all of the non-diesel risk in Year 23 is from landfill gas, then the 70-year risk from landfill gas for Year -2 through Year 68 is 0.584 times 11.3 x 10^-6, or 6.6 x 10^-6 risk. This is a conservative over-estimate since part of the

11.3 x 10^-6 risk is from particulate matter emissions that will not occur beyond Year 23.

The diesel-only risk in Year 8 is 5.7 x 10^-6, Year 17 it is 2.8 x 10^-6, Year 22 it is

The non-landfill gas risk for Year -2 is 8.0 x 10^-6, but this occurs only for one year, so the 70-year risk is 8.0 x 10^-6 divided by 70, or 0.11 x 10^-6. It is assumed that Year -1 will have the same risk as Year -2, i.e., 0.11 x 10^-6.
The Year 1 non-landfill gas risk is 31.8 x 10^-6, but for only 1 year, or 0.45 x 10^-6 over 70 years.
For Years 2 through 7, it was conservatively assumed (overestimated) that the Year 8 diesel-only risk occurred, or 5.7 x 10^-6 divided by 70 times 6 years, or 0.49 x 10^-6.
The sum of the individual risks over 70 years is therefore, 6.6 x 10^-6 plus 0.7 x 10^-6 plus 0.11 x 10^-6 plus 0.11 x 10^-6 plus 0.45 x 10^-6 plus 0.49 x 10^-6, or a total of 8.46 x 10^-6.

The maximum total 70-year cancer risk from the proposed project, including construction, is 8.5 x 10^-6.

A similar analysis could be conducted for the Maximum Exposed Individual Worker receptor (MEIW). However, the MEIW results are all well less than 10 x 10^-6 for all years except Operational Year 1. The average potential cancer risk shown in Table 5-2 for the MEIW over the 23 years of operation plus the construction Years of -2 and -1, even assuming that the maximum landfill gas generation rate occurs for the entire 46 year worker exposure duration is 5.1 x 10^-6. The maximum risk is less than this value due to the same reasons as discussed for the MEIR.

5.2.2 Potential Lead Health Effects

To address this lead threshold, special lead-only AERMOD runs were conducted. OEHHA has published a method for evaluating potential health effects from lead emissions based on a 30-day average impact and a threshold of of 0.12 ug/m³ over 30 days. The method is based on calculating annual lead emissions but then assuming that all of those emissions could be emitted in a 30-day period. Then the AERMOD model is run with lead emissions only over a 30-day averaging period during the hours of operation. The AERMOD model does not do rolling 30-day averages, only monthly averages. However, if the maximum 24-hour average is less than the threshold, certainly the 30-day average will be also. The resulting maximum modeled impact is then compared to the 0.12 ug/m³ threshold. The maximum 24-hour average lead impact was found to be 0.006 ug/m³_,for meteorological year 2002 and 0.007 ug/m³ for meteorological year 2003, which is less than 6 percent of the threshold, or a Hazard Index of less than 0.06. The model runs for this procedure are included in the Appendix K compact disc.

6.0 SUMMARY

This document is an update that replaces Volume VII of the permit application which includes an updated AQIA for NO₂, CO, and PM₁₀ and PM_2.5, and an update to the HRA to address more refined emission estimates, more recent advances in dispersion modeling and new RELs published by OEHHA. The AQIA emission estimates and modeling methodology are consistent with extensive discussions held with the SDAPCD.

The analysis showed that the maximum ambient impacts of NO₂, PM₁₀, and PM_2.5, including worst-case background concentrations, are less than both Federal and California ambient air quality standards. The analysis also showed that even with the new, more stringent RELs, the maximum health risks at the maximally exposed off-site worker and resident are less than thresholds of concern.

100847/CSP10R131 September 14, 2010

ATTACHMENT 2

AIR QUALITY IMPACT SUPLEMENTAL ANALYSES DATED

12/29/11, 1/23/12 and 5/2/12

FOR THE PROPOSED GREGORY CANYON LANDFILL AUGUST 5, 2013

December 29, 2011

Mr. Steve Moore

San Diego Air Pollution Control District

10124 Old Grove Road San Diego, CA 92131

Subject: Sensitivity Analysis of Impact Modeling for the Proposed Gregory Canyon Landfill

Dear Mr. Moore:

10044 Granite Hill Drive

Parker, CO

80134

p| 303.840.4571

f| 303.840.4579

kleinfelder.com

You have requested a set of model runs to assess the sensitivity of the modeled impact results presented in the September 14, 2010 Air Quality Impact Analysis (AQIA) for the proposed Gregory Canyon Landfill (GCLF).

You requested the sensitivity analysis to evaluate how the modeled impacts would change if different input parameters were used in the models. The AQIA presented the modeling results based on a reasonable worst-case set of assumptions and parameters that had been discussed with San Diego Air Pollution Control District (SDAPCD or District) staff. Additional review by District staff resulted in your request to model a different hypothetical set of assumptions that could not occur, but are of interest to the District. This letter presents those model runs. The different assumptions are discussed in the following paragraphs.

Vehicle Travel On-Site

You requested a sensitivity analysis assuming that all vehicles travel at an average speed of 15 miles per hour (mph), 95 percent emission control on unstabilized unpaved roads from watering, no road layout would exceed approximately 15 percent grade, the grader would travel 14 passes per day at the landfill active face, and the emission factor for the grader at the landfill active face was tripled. Tripling the grader emission factor is to make the grader emissions at the active face similar to a bulldozer emission factor instead of a grader. You also asked us to use different vehicle weights and payloads for vehicles bringing waste to the landfill. The requested vehicle weights are shown in Tables 1 and 2.

Table 1

Vehicle Weights Requested by SDAPCD – Daily Mix

(Maximum 5,000 tons per day MSW and 295 tons per day PGM)

TRUCK WEIGHTS AND WHEELS DATA

Payload (tons)

Loaded Weight (tons)

Tare Weight (tons)

Average Weight (tons)

Number Wheels

Percent of Applicable Material Intake

Tons per Day

Number of Waste + Other Trucks per Day at 5,000 tpd

Waste

MSW in transfer

semitrailer

22.15

39.7

17.55

28.625

59.2%

2959.7

134

MSW in pods

13.1

34.37

21.27

27.82

10.3%

516.7

MSW in general refuse vehicles

4.89

17.51

12.62

15.065

8.86

30.5%

1523.5

312

Processed Green Material (ADC) in transfer trailers

22.31

39.09

16.78

27.935

23.4%

69.1

Processed Green Material (ADC) in refuse vehicles

3.73

14.3

10.57

12.435

8.17

76.6%

225.9

Internal light duty

vehicles

0.0

TOTAL

5295

574

Table 2

Vehicle Weights Requested by SDAPCD – Annual Mix

(Annual 1,000,000 tons per year MSW and 90,565 tons per year PGM)

TRUCK WEIGHTS AND WHEELS DATA

Payload (tons)

Loaded Weight (tons)

Tare Weight (tons)

Average Weight (tons)

Number Wheels

Percent of Applicable Material Intake

Tons per Year

Number of Waste + Other Trucks per Year at 1,000,000 tpy

Waste

MSW in transfer

semitrailer

22.15

39.7

17.55

28.625

59.2%

591943.2

26724

MSW in pods

13.1

34.37

21.27

27.82

10.3%

103349.1

7889

MSW in general refuse vehicles

4.89

17.51

12.62

15.065

8.86

30.5%

304707.7

62312

Processed Green Material (ADC) in transfer trailers

22.31

39.09

16.78

27.935

23.4%

21209.5

951

Processed Green Material (ADC) in refuse vehicles

3.73

14.3

10.57

12.435

8.17

76.6%

69355.5

18594

Internal light duty

vehicles

0.0

7675

TOTAL

1090565

124145

As we have discussed on numerous occasions, the payloads and vehicle mix in Tables 1 and 2 are certainly not representative of the types of vehicles that will arrive at GCLF. Thus the weights and vehicle mix in Tables 1 and 2 certainly greatly over-estimate potential emissions from vehicle travel. The assumption that all vehicles travel at the maximum allowed speed

everywhere in the landfill at all times also greatly over-estimates emissions. Nevertheless, for purposes of the sensitivity analysis, the vehicle weights and mix in Tables 1 and 2 and the 15 mph speed were used.

Modeling Assumptions for Road Widths

You requested that the modeled road widths be changed to reflect more recent draft modeling guidance that has not been published but has become available to the District. The requested modeled road widths are shown in Table 3. The change in model road widths has no effect on the modeled impacts, but they were used as requested. (Note that the modeled road widths are not the physical road widths, as the model input parameters are adjusted for dispersion.)

Table 3

Modeled Road Widths Requested by SDAPCD

Road Segment	Widths to Use in Model
Paved Main Access Road from SR76 to end of bridge	24 feet plus 6 meters
Paved Main Access Road from end of bridge to entrance of ancillary facilities	8.5 feet plus 6 meters
Main Internal Access Roads	24 feet plus 6 meters
Other internal haul road including borrow and stockpile roads	13 feet plus 6 meters
Landfill Deck Road	24 feet plus 6 meters

Year 1 Landfill Activities and Roads

The AQIA presented a typical landfill activity for Year 1. However, Year 1 activities could be limited to a relatively small (23 acre) area on the northern end of the landfill. You also requested us to analyze the possibility that there could be additional inactive disturbed area (another 23 acres) that has not yet been vegetated and is subject to wind erosion. Furthermore, the access road for disposal of waste in the landfill could be further east than modeled in the AQIA. We have modeled a new access road alignment, added wind erosion, and modeled both annual and 24-hour activities in a hypothetical location that yields the maximum potential impacts of landfill activities. On an annual basis, the activities are modeled in the middle of the active landfill, but on a 24-hour basis, they are modeled on the eastern edge where the potential impacts will be greatest. The attached figure shows the modeled 23 acre Year 1 area and access road to that area. We also modeled a maximum daily waste (MSW) received of 5,000 tpd plus another 295 tpd of processed green material (PGM) used as alternative daily cover (ADC); although in Year 1 these maximum potential values will not occur.

Landfill Haul Road Grades

You requested us to modify the modeled roads such that no road has greater than approximately 15 percent grade. We have done that and the new alignments are in the attached model runs. However, construction equipment, including scrapers, can traverse roads with greater than 15 percent grade.

Material Handling at the Borrow Areas

The AQIA modeled typical locations of material handling that could occur at the borrow areas. There are three types of material handling: (1) unloading of soil to build the borrow area, (2) removal and loading of previously placed material for use as landfill cover, and (3) excavation (ripping) of additional native soil to be used as landfill cover. As a sensitivity analysis, you asked us to analyze potential impacts of material handling should they occur at the nearest possible location to the property line (i.e., northwest and southwest corners of Borrow Area A and southwest and southeast corners of Borrow Area B). We have modeled maximum 24- hour activities in those locations. Unloading and loading of previously placed soil can occur at the edge of the Borrow Area A; however, ripping of native soil will not occur at the edge, but rather 20 to 40 feet away from the edge of Borrow Area A. For purposes of the model sensitivity runs, it was assumed that ripping of native soil occurs more than 80 to 100 feet away from the property line near Borrow Area A (i.e., 20 to 40 feet away from the edge of Borrow Area A). For Borrow Area B, unloading, loading, and ripping of native soil can occur at the edge of the borrow area. For purposes of the sensitivity analysis, once the scraper was loaded, it was assumed to take about 200 feet to reach the maximum speed of 15 mph and it was assumed that the scraper would decelerate for about 200 feet to its unloading location (these distances are termed “road ends” in the models). The road ends were modeled with a scarper speed of 6 miles per hour (3 mph for about 50 feet, 5 mph for about 50 feet, 7 mph for about 50 feet, and 9 mph for about 50 feeet). At all other locations, the scraper was assumed to travel at the maximum 15 mph speed.

Additional Disturbed Area Subject to Wind Erosion

The AQIA modeled wind erosion as potentially occurring from (1) “disturbed” areas that are being actively disturbed (e.g., active face of the landfill, active building or excavation of the Borrow Areas); and (2) “undisturbed” areas that had been previously disturbed but have not had time to re-vegetate. The emission factors for these two types of areas that were used in the AQIA were provided by the District and are much greater than emission factors for wind erosion used by the USEPA and other air districts. For the AQIA, the area subject to wind erosion at the landfill was estimated by dividing the total landfill surface by the operational life of the landfill to arrive at 8 acres per year disturbed. It was assumed that the 8 acres would take one year to re-vegetate and that another 8 acres would be disturbed in a given year. Therefore, the total acreage subject to wind erosion would be 16 acres, but 2 of those acres

are actively disturbed at the landfill face. Therefore, the AQIA modeled 14 acres as “undisturbed” and 2 acres as actively “disturbed” at the landfill. (Additional wind erosion areas occur at the Borrow Areas).

You have indicated that in your opinion, in Operational Year 22, as much as 39 acres could be actively disturbed. We do not know how that number was arrived at, but for purposes of a sensitivity analysis, we modeled Year 22 with 39 acres of actively disturbed area (and 14 acres of undisturbed) and compared that model result to the result using the AQIA acreage. The results are shown in the attached Model Runs 35 and 35A. The increased wind erosion acreage makes essentially no difference in the results (increases the annual PM₁₀ maximum impact from 2.10 to 2.11 ug/m³).

You have also indicated that in Operational Year 17 there could be as much as 63 acres actively disturbed and another 12 acres undisturbed but not re-vegetated. As discussed, the AQIA assumed that there were 2 acres of actively disturbed area and 14 acres of undisturbed but not re-vegetated area at the landfill. The 63 acre number for a single operational year cannot be representative, since the entire landfill surface is only on the order of 180 acres. We believe that the same assumptions used in Operational Year 22 would also apply to Year 17, i.e., 2 acres disturbed and 14 acres undisturbed. Even if your assumption of 39 disturbed acres was correct for Year 17, it would make no difference in the modeled impact results, as demonstrated for Year 22.

Summary of Sensitivity Model Results

The sensitivity model runs and emissions spreadsheets are attached to this letter. Table 4 summarizes the results of the sensitivity runs. All of the sensitivity runs use the vehicle weights and mix requested by you, 15 mph on roads, model road widths shown in Table 3, road grades less than approximately 15 percent, and meteorological year 2003 since that year yields the highest impacts. All of the results are less than the most stringent ambient air quality standard and are consistent with the AQIA results.

Table 4

Summary of Model Sensitivity Results

Model Run ID

Purpose of Run

Operational Year and Averaging Time

Maximum Modeled Impact (ug/m³)

Year/Day of Maximum Modeled

Impact

Background (ug/m³)

Modeled Impact Plus Background (ug/m³)

S25

Unload soil at Borrow Area A

next to the edge of the Borrow Area on the south end

Year -2 24-hour

35.8

1/9/2003

9.7

45.5

S26

First 23 acres of landfill activities

Year 1

Annual

2.4

2003

17.6

20.0

Model Run ID

Purpose of Run

Operational Year and Averaging Time

Maximum Modeled Impact (ug/m³)

Year/Day of Maximum Modeled

Impact

Background (ug/m³)

Modeled Impact Plus Background (ug/m³)

S27

Landfill activities on eastern edge of first 23 acres and unload soil next to the edge of Borrow

Area B in the southwest corner

Year 1 24-hour

40.0

1/9/2003

9.7

49.7

S28

Landfill activities on eastern edge of first 23 acres and unload soil next to the edge of Borrow

Area B in the southeast corner

Year 1 24-hour

38.1

3/4/2003

7.0

45.1

S29

Excavate and load soil in Borrow

Areas on an Annual Basis

Year 17

Annual

2.4

2003

17.6

20.0

S30

Excavate and load soil next to edge of Borrow Area B in the

southwest corner

Year 17 24-hour

26.6

1/9/2003

9.7

36.3

S31

Excavate and load soil next to

edge of Borrow Area B in the southeast corner

Year 17 24-hour

32.4

3/4/2003

7.0

39.4

S32

Excavate and load soil in Borrow

Areas on an Annual Basis

Year 22

Annual

2.1

2003

17.6

19.7

S33

Load soil (no excavation) next to edge of Borrow Area A in the

northwest corner

Year 22 24-hour

42.3

3/4/2003

7.0

49.3

S33A

Excavate and load soil 6 meters away from edge of Borrow Area

A in the northwest corner

Year 22 24-hour

42.6

3/4/2003

7.0

49.6

S34

Load soil (no excavation) next to

edge of Borrow Area A in the southwest corner

Year 22 24-hour

30.8

3/4/2003

7.0

37.8

S34A

Excavate and load soil 12 meters away from edge of Borrow Area

A in the southwest corner

Year 22 24-hour

40.2

3/4/2003

7.0

47.2

S35

PMI Run to evaluate contribution of wind erosion – AQIA acreage of 2 acres actively disturbed and 14 acres disturbed and not

vegetated

Year 22 Annual

2.10

2003

17.6

19.7

S35A

Increase landfill actively disturbed acreage to 39 acres and 14 acres disturbed and not

vegetated

Year 22 Annual

2.11

2003

17.6

19.7

Clay Delivery for Landfill Liner

As we have discussed, there will be a permit condition that limits emissions from vehicle travel. The limit will be calculated with a formula that accounts for the actual vehicle mix that occurs.

The formula and permit condition will be in terms of pounds of particulate (PM₁₀) emissions per day (lb/day). You have asked us to confirm that when clay is brought to the landfill as part of liner construction the landfill will be able to meet the formula limits. Obviously, if clay is brought on site, the amount of waste that day will have to decrease in order to stay within the permit limit. The analysis below shows that reasonable amounts of clay and waste can be brought on site and the permit condition can still be met.

According to the landfill design engineer, the landfill will use 777,000 cubic yards (un- compacted) of clay over the life of the landfill. The liners will be built over a period of from about 15 to 17 years. On average the amount of clay used per year is about 46,000 to 52,000 cubic yards. The landfill operates 307 days per year, so on average, the amount of clay brought on site is 150 to 170 cubic yards per day. For purposes of a sensitivity analysis, assume that as much as 1,000 cubic yards of clay could arrive in one day. (This value is not a maximum limit, it is only a number chosen for the sensitivity analysis shown below. The value is more than five times greater than the average amount of clay). Also assume that the clay arrives in what are termed “Super-18 Soil Haulers”, with tare weight of 15 tons, payload of 25 tons, and these trucks use a stinger such that there are 20 wheels. These trucks were chosen since they have the maximum weight and number of wheels of soil haulers. The density of clay is assumed to be 1 ton per cubic yard (1.2 grams per cubic centimeter). Therefore, each truck brings 25 cubic yards of clay, or at 1,000 cubic yards per day, 40 trucks per day, and 1,000 tons per day (tpd) of clay. Table 5 presents the results of the sensitivity analysis when using these parameters and some example road lengths.

Table 5

Emission Comparison when Soil Trucks Used

Road Segment	Road Length (feet)	Modeled Maximum Emissions with No Soil Trucks, 5,000 tpd MSW, 295 tpd PGM, and 25 light duty vehicles per day (lb/day)	Modeled Maximum Emissions with 1,000 tpd Soil, 4,000 tpd MSW, 295 tpd PGM, and 25 light duty vehicles per day (lb/day)
Paved	2,800	12.0	11.2
Unpaved Stabilized	9,900	257.0	239.3
Unpaved Unstabilized	500	21.7	20.2
Unpaved Unstabilized Road Ends	200	23.6	22.1
Total Emissions		314.2	292.8

As indicated, Table 5 is only an example, not a maximum amount of clay. If more than 1,000 tons of clay were needed in a day, the amount of MSW or PGM would decrease so that the total emissions were not exceeded.

The District provided the landfill gas (LFG) generation parameters for the AP-42 Landfill Gas Emissions Model (LANDGEM) and those parameters were used in the September 14, 2010 AQIA. You also asked us to analyze potential LFG emissions using draft AP-42 emission factors, and those results were reported in a letter dated September 8, 2011. The District’s parameters were derived from landfills operating in the early 1990s prior to restrictions on green waste being deposited in landfills. Thus the District’s parameters over-estimate the amount of landfill gas that can be generated in modern landfills that have much less green material present. Nevertheless, for the AQIA and the September 8, 2011 analysis, the District’s parameters were used for LFG emissions. The LFG emissions were calculated assuming a maximum waste disposal rate of 5000 tpd MSW every day of operations (1,535,000 tons per year).

However, annual waste disposal at GCLF will be limited to 1,000,000 tons per year (tpy), or an average of about 3,257 tpd rather than 5,000 tpd. Therefore, the AQIA waste disposal rate was over-estimated. The AQIA was also based on an assumed waste in place density of about 0.7 tons per cubic yard.

You have now asked us to analyze potential LFG generation assuming 1,000,000 tons per year MSW, that the MSW could be packed into the landfill at a density of 0.85 tons per cubic yard, and there will be 295 tpd of decomposable PGM used each day for ADC. An MSW density of 0.85 tons per cubic yard is an extremely high density and not realistic and PGM will not be a significant source of LFG. Nevertheless, we have performed such an analysis, using the District’s LFG generation parameters that are known to over-estimate LFG generation, an MSW in place density of 0.85 tons per cubic yard that is known to be an over-estimate, and PGM used as ADC decomposing at the same rate as MSW that is known not to occur. The LANDGEM run for this hypothetical scenario is attached. The model reports maximum LFG generation rate of 1.715 x 10⁵ Megagrams per year. This can be compared to the maximum LFG generation rate of 1.503 x 10⁵ Megagrams per year reported in the AQIA, or an increase of 14%. Note that this is for the single peak maximum year. LFG generation follows a bell curve gradually increasing to the peak and then gradually decreasing from the peak. We have presented discussion in the AQIA to account for this known variable nature of LFG generation rates in the Health Risk Assessment (HRA).

If the LFG generation rate is 14 percent greater than reported in the AQIA, then the HRA risk results would increase by about 14 percent as well. The risk results reported in the AQIA as well as the risk results reported in a letter dated September 8, 2011 are much less than 10 in a million, and even if the LFG were increased by 14 percent, the results would remain less than 10 in a million. The September 8, 2011 letter reported maximum potential cancer risk of 1.6 in a million without diesel particulate matter (DPM) from mobile equipment and 3.9 in a million if

increase to 1.8 in a million without DPM and 4.4 with DPM.

CONCLUSION

The sensitivity analyses you requested have confirmed that the impact assessment and risk results reported in the September 14, 2010 AQIA are representative and demonstrate that the proposed landfill project will not cause an exceedance of the ambient air quality standards or an exceedance of the risk reporting thresholds.

If you have any questions, feel free to call me at 303-840-4571. Sincerely,

KLEINFELDER, INC.

Russell E. Erbes, CCM

Senior Principal Air Quality Scientist Attachments:

Attachment A: Operational Year 1 Layout Attachment B: LANDGEM Sensitivity Run

Attchment B: CD of Emissions Spreadsheets and Impact Model Sensitivity Runs for Operational Year -2, Year 1, Year 17, and Year 22

January 23, 2012

Mr. Steve Moore

San Diego Air Pollution Control District

10124 Old Grove Road San Diego, CA 92131

Subject: Additional Sensitivity Analyses

for the Proposed Gregory Canyon Landfill

Dear Mr. Moore:

10044 Granite Hill Drive

Parker, CO

80134

p| 303.840.4571

f| 303.840.4579

kleinfelder.com

In a letter dated December 29, 2011 we provided an extensive set of sensitivity analyses that you had requested for the proposed Gregory Canyon Landfill (GCLF). You have since requested three additional analyses that are provided in this letter.

Additional Impact Days

The December 29, 2011 sensitivity analyses modeled the maximum 24-hour impact days and reported the results in Table 4 of that letter. For Operational Year 22 and Borrow Area A you have requested an analysis of all days, not just the maximum impact day. The results are presented in the attached model runs (Attachment A). For these additional sensitivity analyses, it was assumed that unloading and loading of previously placed soil can occur at the edge of the Borrow Area A; however, ripping of native soil will not occur at the edge, but rather 20 to 25 meters away from the edge of Borrow Area A. For purposes of the model sensitivity runs, it was assumed that ripping of native soil occurs more than 125 to 145 feet away from the property line near Borrow Area A (i.e., 65 to 85 feet away from the edge of Borrow Area A).

Landfill Gas Generation

The December 29, 2011 letter presented landfill gas generation rates based on a collection of parameters requested by the District and an assumed municipal solid waste (MSW) density of

0.85 tons per cubic yard of air space. You have requested an additional analysis using the

0.85 tons of MSW per cubic yard (cy) of net airspace, defined as the total cubic yards available for MSW and daily cover. GCLF will have 56,990,147 cubic yards of net airspace. Thus, if the District’s density factor is used, there could theoretically be 48,441,625 tons of MSW disposed. You have also asked us to include the processed green material (PGM) –

used as alternative daily cover (ADC) – as additional material that could decompose (i.e., in addition to the MSW deposited). There will be a maximum of 295 tons per day of PGM used as ADC (the actual amount used will be significantly less). The landfill can accept up to 1,000,000 tons of MSW per year and on average about 3,200 tons per day. Therefore, in order to deposit 48,441,527 tons of waste will take 48 years (to deposit 48,000,000 tons of MSW) plus 138 days (for the remaining 441,527 tons / 3,200 tons per day). The landfill operates a maximum of 307 days per year, or 14,874 days before the maximum theoretical amount of waste is deposited (48 years x 307 days per year + 138 days = 14,874 days). The amount of PGM deposited could theoretically be 4,387,830 tons over the life of the landfill (14,874 days x 295 tons per day = 4,387,830 tons). The maximum annual amount of MSW plus PGM deposited is 1,090,565 tons (1,000,000 MSW + [307 days per year x 295 tons PGM per day]).

This MSW and PGM deposit rate (1,090,565 tons per year) was used in the USEPA AP-42 Landfill Gas Emissions Model (LANDGEM) model along with those parameters requested by the District that were used in the September 14, 2010 AQIA and the results of the LFG emissions analysis using draft AP-42 emission factors (reported in a letter dated September 8, 2011). The District’s parameters were derived from landfills operating in the early 1990s prior to restrictions on green waste being deposited in landfills. Thus the District’s parameters over- estimate the amount of landfill gas that can be generated in modern landfills that have much less green material present. Nevertheless, for the AQIA and the September 8, 2011 analysis, the District’s parameters were used for LFG emissions.

An MSW density of 0.85 tons per cubic yard is an extremely high density and not realistic and PGM will not be a significant source of LFG. Nevertheless, we have performed such an analysis, using the District’s LFG generation parameters that are known to over-estimate LFG generation, an MSW in place density of 0.85 tons per cubic yard that is known to be an over- estimate, and PGM used as ADC decomposing at the same rate as MSW that is known not to occur. The LANDGEM run for this hypothetical scenario is included as Attachment B. The model reports maximum LFG generation rate of 1.851 x 10⁵ Megagrams per year. This can be compared to the maximum LFG generation rate of 1.503 x 10⁵ Megagrams per year reported in the AQIA, or an increase of approximately 23%. Note that this is for the single peak maximum year. LFG generation follows a bell curve gradually increasing to the peak and then gradually decreasing from the peak. We have presented discussion in the AQIA to account for this known variable nature of LFG generation rates in the Health Risk Assessment (HRA).

If the LFG generation rate is 23 percent greater than reported in the AQIA, then the HRA risk results would increase by about 23 percent as well. The risk results reported in the AQIA as well as the risk results reported in a letter dated September 8, 2011 are much less than 10-in- one million, and even if the LFG were increased by 23 percent, the results would remain less than 10-in-one million. The September 8, 2011 letter reported maximum potential cancer risk

of 1.6-in-one million without diesel particulate matter (DPM) from mobile equipment and 3.9-in- one million if DPM were included. If these values were increased by 23 percent, the cancer risk would increase to approximately 2.0-in-one million without DPM and 4.8-in-one million with DPM.

Trucks Instead of Scrapers

We have discussed the fact that articulated trucks (Caterpillar Model 740) may be used to transport soil at GCLF instead of scrapers or in addition to scrapers (i.e., a mix of scrapers and trucks may be used). We have analyzed the emission factors for scrapers compared to trucks (Attachment C) and have found that scraper emission factors are greater than trucks. Therefore, the model runs based on the use of scrapers would yield a worst-case assessment.

If you have any questions, feel free to call me at 303-840-4571. Sincerely,

KLEINFELDER, INC.

Russell E. Erbes, CCM

Senior Principal Air Quality Scientist Attachments:

Attachment A: Model Runs 33B and 34B Attachment B: LANDGEM Sensitivity Run

Attachment C: Scraper versus Truck Emission Factors

May 2, 2012

Mr. Steve Moore

San Diego Air Pollution Control District

10124 Old Grove Road San Diego, CA 92131

Subject: Gregory Canyon Landfill Flare Impact Sensitivity Analysis

Dear Mr. Moore:

10044 Granite Hill Drive

Parker, CO

80134

p| 303.840.4571

f| 303.840.4579

kleinfelder.com

You have requested a sensitivity analysis related to ambient air quality impacts of emissions from the flare station at the proposed Gregory Canyon Landfill (“GCLF”). The sensitivity analysis addresses possible updated emission factors for the flares and a possible updated flare station location. Potential impacts of emissions from the flares were assessed in the September 14, 2010 Air Quality Impact Analysis (AQIA). However, since the AQIA was completed, additional information has been gained regarding the flare location and emission factors. This letter is to assess the potential change in impacts as a result of this additional information.

Flare Location

The AQIA had the flare station located on the far side of the facilities area with the first flare located at UTM coordinates 489664.5 easting, 3689402.99 northing. Subsequently, it was determined that it may be more efficient to locate the flare station closer to the toe of the landfill, about 600 feet east and south of the AQIA location, with the first flare located at UTM coordinates 489869.0 easting, 368394.5 northing. No final decision to relocate the flare station has been made. However, were that done, the change in flare location, although slight, could possibly change the potential ambient air quality and health risk impacts of the facility.

Flare Emissions

In the AQIA, the emission factors for the flares were based on the San Diego Air Pollution Control District (SDAPCD or District) default emission factors. Recent conversations with flare manufacturers have indicated that modern flares may have lower emissions than the SDAPCD

default factors for some pollutants. Table 1 compares the SDAPCD emission factors to the lowest emission factors that flare manufacturers will guarantee.

Table 1

Comparison of Flare Emission Factors

Pollutant	Default SDAPCD Factor (lb/mmscf LFG)	SDAPCD Factor (lb/mmscf CH₄)	SDAPCD Factor (lb/mmBtu)	Flare Manufacturer Guarantee Factor (lb/mmBtu)	Flare Manufacturer Factor (lb/mmscf CH₄)	Flare Manufacturer Factor (lb/mmscf LFG)
NO_x	40	90.9	0.090	0.025	25.3	11.1
CO	1.5	3.4	0.003	0.060	60.6	26.7
PM10/2.5	10	22.7	0.023	NA	NA	NA

The conversion of the SDAPCD emission factors from the stated units (pounds per million cubic feet of LFG, lb/mmscf LFG) to methane (lb/mmscf CH₄) and Btu (lb/mmBtu) was done using the District-specified 44 percent methane for GCLF and 1010 BTU per standard cubic foot of methane. (The default factors used 50 percent methane, so the converted values in Table 1 are slightly different than the converted values used by the District). For example:

NO_x = 30 lb/mmscf LFG x 1 cf LFG / 0.44 cf CH₄ = 68.2 lb/mmscf CH₄ x 1 scf CH₄ / 1010 Btu =

0.068 lb/mmBtu

The same conversion was used to convert the manufacturer guarantee (lb/mmBtu) to methane (lb/mmscf CH₄) and LFG (lb/mmscf LFG) as follows:

NO_x = 0.025 lb/mmBtu x 1010 Btu / scf CH₄ = 25.3 lb/mmscf CH₄ x 0.44 cf CH₄ / 1 cf LFG =

11.1 lb/mmscf LFG

Note from Table 1 that manufacturers do not guarantee PM₁₀ emissions since the flare does not create particulate matter; particulate emissions are related to pre-combustion particulate in the combustion air and landfill gas. Therefore, the District’s PM₁₀ emission factor was not changed from the AQIA. Note also that for a flare to achieve extremely low NO_x emissions, CO emissions increase. Since NO_x is related to potential ozone formation, the extremely low NO_x emission factor will be used with the concomitant increase in CO emissions.

Impact Modeling Results for Health Risk

The AQIA included a health risk assessment (HRA). After the AQIA was prepared, the District requested a sensitivity analysis related to the use of draft toxic air contaminant emission

factors published by the USEPA in October 2008 compared to the USEPA approved emission factors used in the AQIA. The results of that comparison were provided to the District in a letter dated September 8, 2011. To evaluate the possible effect of the a possible change of the flare station location on the HRA results, Year 23 flare emissions (i.e., maximum flare emissions) were modeled for emissions from the possible new location compared to the AQIA location. Only the USEPA draft emission factors were used for this comparison since the same results would occur with the AQIA emission factors. Likewise only cancer risk was evaluated since the non-cancer health risks are much less than thresholds of interest and again, the non-cancer comparison would be the same. Table 2 shows how the flare location affects the HRA results. The change in location does not change the HRA results. The cancer risk results shown in Table 2 are the total risk, including diesel particulate and assuming continuous emissions at the maximum level for 70 years. The HARP model runs are included in Attachment A.

Table 2

Comparison of Cancer Risk Results

Meteorological Year	Operating Year	Receptor Type	Cancer Risk with AQIA Flare Location (per million)	Cancer Risk with Updated Flare Location (per million)
2002	23	MEIW	2.75	2.75
2002	23	MEIR	7.68	7.68
2003	23	MEIW	3.15	3.16
2003	23	MEIR	8.84	8.84

Impact Modeling Results for Criteria Pollutants

After the AQIA was submitted, the District requested a number of sensitivity analyses for PM₁₀ impacts. These analyses were presented in letters dated December 29, 2011 and January 23, 2012. These sensitivity analyses showed that Sensitivity Runs 33B, 34B, and 32 for operational year 22 yield the maximum 24-hour and annual PM₁₀ impacts. Therefore, for PM₁₀ impacts, these three model runs were used to compare the maximum impacts with the AQIA flare location and emissions to the possible change in flare station location and the manufacturer guarantee and District PM₁₀ and PM_2.5 emission factors shown in Table 1. For PM_2.5 and NO_x impacts, the AQIA model runs for the maximum impact operational and meteorological years were used for the comparison. For CO, the September 14, 2010 AQIA did not re-analyze CO impacts because the impacts are very low compared to the standard and thus no update from the 2007/2008 analyses was needed. Therefore, to analyze the effect of the possible change in location and emissions, new CO impact runs had to be completed. The results of the impact analysis are shown in Table 3. Note that the NO_x impacts in Table 3 assume complete conversion of NO_x to NO₂. The model runs are included in Attachment B.

Table 3

Criteria Pollutant Impacts with Updated Flare Location and Emission Factors

Operating Year	Pollutant and Averaging Time	Meteorological Year and Model Run	Impact with AQIA Flare Location and Emissions (ug/m³)	Impact with Updated Flare Location and Emissions (ug/m³)	Background (ug/m³)	Total Impact (ug/m³)	Most Stringent Standard (ug/m³)
22	24-hour PM₁₀	2003 Run S33B	12.8	12.9	36.9 October 24, 2003	49.8	50
22	24-hour PM₁₀	2003 Run S34B	12.7	12.8	36.9 October 24, 2003	49.7	50
22	Annual PM₁₀	2003 Run S32	2.1	2.1	17.6	19.7	20
22	24-hour PM2.5	2003 AQIA Run	7.6	7.6	15.5	23.1	35
22	Annual PM2.5	2003 AQIA Run	0.7	1.0	7.2	8.2	12
23	1-hour NO₂	2003 AQIA Run	38.6	37.7	118	155.7	188
23	Annual NO₂	2002 AQIA Run	0.8	1.0	34	35.0	57
23	1-hour CO	2003 New Run	36.2	93.6	6743	6836	23000
23	8-hour CO	2003 New Run	11.4	21.9	4114	4136	8000

Conclusion

The possible change in flare location and manufacturer guarantee emission factors for the flares do not significantly change the results of the AQIA and the impacts are less than the most stringent ambient air quality standards.

Please feel to contact me if you have any questions. Sincerely,

KLEINFELDER, INC.

Russell E. Erbes, CCM

Senior Principal Air Quality Scientist

Attachments:

HRA Model Runs
Criteria Pollutant Model Runs

Reference Library

Air Quality Impact Analysis for the Gregory Canyon Landfill Project – CO (TPD1308148)

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