Air Quality Impact Analysis for the Gregory Canyon Landfill Project - CO

Ralph DeSiena, Monitoring and Technical Services San Diego Air Pollution Control District
2013-08-05
Mechanical Engineering San Diego Air Pollution Control District

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

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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 PM2.5. 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 PM2.5:  There were no on-site PM2.5 data available, thus the ratio of  Aqua Tibia PM2.5 to PM10 was applied to the on-site PM10 data to derive background PM2.5 data. Since PM2.5 impacts are relatively low (i.e., the  proposed project is not a significant source of PM2.5), the maximum 24-hour PM2.5 concentration from 2002 and 2003 was used for the background. Furthermore, rather than the 98th percentile, the first-high background value was used

  • Annual PM2.5: The same ratio of annual PM10 data from on-site monitoring compared to Aqua Tibia was used to derive an annual PM2.5 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 background 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 1st-high

Escondido

135

152

137

1-hour 7th-high

Escondido

113

134

109

1-hour 7th-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

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 1st High

152

69.8

221.8

Year -2

2002

339

--

 

1-hour 7th 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

--

    PM2.5   

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 1st-high NO2 impact added to the 3-year average 7th-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 1st-high PM2.5 impact added to 1st-high background, thus significantly over-stating impact with respect to the Federal standard which is the 3-year average 98th percentile.

4 1-hour maximum SO2 background value.

5 99th 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 PM2.5 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 PM2.5 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 1st High NO2

2003

AQIA Run

38.6

37.7

152

189.7

339

23

1-hour 7th 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., NOx) 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 PM2.5. For PM10, 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

 

 

 

 

 

 

 

Copyright 2010 Kleinfelder All Rights Reserved

 

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          PM2.5 EMISSION ESTIMATES............................................................................. 25

3.5.1      PM2.5 Emission Factor for Blasting............................................................ 25

3.5.2      PM2.5 Emission Factor for Excavation, Loading and Unloading Soil........ 25

3.5.3      PM2.5 Emission Factor for Unpaved and Paved Roads............................ 26

3.5.4      PM2.5 Emission Factor for Wind Erosion................................................... 26

3.5.5      PM2.5 Emission Factor for Excavation and Daily Cover Operations......... 27

3.5.6      PM2.5 Emission Factor for Drilling.............................................................. 27

3.5.7      PM2.5 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      PM2.5 Impact Results for 24-Hour AAQS.................................................. 46

4.5.7      PM2.5 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 PM2.5, and NO2, Emission Estimates..................... 4

Table 1-4 Proposed GCLF  Maximum  Hourly  PM10,  and  PM2.5,  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 PM2.5 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 PM2.5, 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 PM2.5, and NO2, Emission Estimates................... 29

Table 3-2 Proposed GCLF  Maximum  Hourly  PM10,  and  PM2.5,  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 PM2.5............................................................. 46

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

Table 4-15 Maximum Potential Annual Impact of PM2.5............................................................... 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

NOx                   Oxides of nitrogen

 

OEHHA            Office of Environmental Health Hazard Assessment OLM          Ozone Limiting Method

 

PM10                 Particulate matter less than 10 micron mean aerodynamic diameter PM2.5   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 (NOx), 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 PM2.5), 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, PM10, and PM2.5 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 7th 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

8-hour

3.6 ppm

 

 

NO2

Daily First High 1-hour

152 ug/m3

Daily 7th 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 PM2.5 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 PM2.5 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

Annual

None

20

20

17.6

PM2.5

24-hour

35

None

35

15.5

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 NOx emissions do not include NOx 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 PM2.5, and NO2, Emission Estimates

 

 

Operational Year

PM10

PM2.5

NO2

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 PM2.5, and NO2, Emission Estimates

 

Operational Year

PM10

PM2.5

NO2

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

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 PM2.5. 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 PM2.5 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

23

2002

Annual

57 (CA)

0.8

34.0

34.8

PM10

-2

2003

24-hour

50

9.9*

39.9

49.8

22

2003

Annual

20

2.3

17.6

19.9

PM2.5

-2

2003

24-hour

35

8.3

15.5

23.8

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

MEIW

Total all Years

2003

< 5.1 X 10-6

10 x 10-6

Chronic HI

MEIR

Year 1

2003

0.22

1.0

MEIW

Year 1

2003

0.19

1.0

Acute HI

MEIR

Years 22, 23

2002, 2003

0.14

1.0

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, PM2.5, 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 1st-high, daily 1-hour 8th_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 98th percentile average over 3 years value. The daily 8th-high value is determined by recording the values of the top unique 8th-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 7th-high concentration is used to represent the AAQS-relevant daily 8th-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 7th-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 7th-high is appropriate.

 

Table 2-1

Background NO2 Concentrations (ppm)

 

Calendar Year

1st-High 1-hour Concentration

Daily 7th-High

1-hour Concentration

Annual Average Concentration

(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

 

1st-High 1-hour Concentration

Daily 7th-High 1-hour Concentration

Annual Average Concentration

(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 (NOx), 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

1st-High 1-hour Concentration

1st-High 8-hour Concentration

(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

PM10 (μg/m3)

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

PM10 (μg/m3)

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

PM10 (μg/m3)

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

PM10 (μg/m3)

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

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 PM2.5 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 PM2.5 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 PM2.5, Annual Averages for 2002-2008

Year

PM10 (μg/m3)

PM2.5 (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

2003

17.0

On-Site

2002

19.7

20.15

2003

20.6

 

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 PM2.5 monitoring data, an annual average PM2.5 value had to be derived. The same on-site to Aqua Tibia ratio of 1.092 was applied to the maximum monitored PM2.5 at Aqua Tibia for 2004, 2005, and 2006. This results in a PM2.5 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 PM2.5, and therefore, the 24-hour background concentration for PM2.5 must also be derived. Table 2-7 shows that at Aqua Tibia, the annual PM2.5 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 PM2.5 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 PM2.5 24-hour concentrations. Thus, the maximum 24-hour PM2.5 concentration was 15.5 μg/m3 [(36.9 μg/m3) x (42%)].

In summary, the annual and 24-hour background concentrations for PM10 and PM2.5 are shown in Table 2-10. Note that the 24-hour PM2.5 standard is stated in terms of the 98th percentile. However, for purposes of this AQIA, the maximum values were used (i.e., the 1st-high modeled impact was added to the 1st-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*

Annual

17.6

PM2.5

24-hour

15.5

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 PM2.5 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

R

(M )1.4

 

EFex = 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       PM2.5 EMISSION ESTIMATES

For some of the emissions sources, such as unpaved roads, scaling factors for calculating PM2.5 emission factors are published in AP-42. For other emission sources, PM2.5 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 PM2.5 scaling factors. Of those sources with AP-42 references, two methods were  applied:  calculating PM2.5 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 PM2.5 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       PM2.5 Emission Factor for Blasting

The PM2.5 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 PM2.5. The scaling factor of 0.03 was applied to the TSP equation to get the corresponding PM2.5. The corresponding PM10 scaling factor is 0.52; therefore, the percentage of PM10 that is PM2.5 resulting from blasting is 6%.

 

3.5.2       PM2.5 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 PM2.5.  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 PM2.5 resulting from unloading is 15%.

 

3.5.3       PM2.5 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 PM2.5 respectively. These k-factors result in PM2.5 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 PM2.5 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 PM2.5 to PM10 ratio of 0.1, the PM2.5 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 PM2.5 respectively. These k-factors result in PM2.5 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 PM2.5 respectively. Thus, the paved road PM2.5 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       PM2.5 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 PM2.5 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       PM2.5 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 PM2.5 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 PM2.5 to PM10 ratio of 0.15 was applied to emissions from excavation and daily cover operations.

 

3.5.6       PM2.5 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 PM2.5 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 PM2.5 (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 PM2.5 to PM10 ratios should be similar. Therefore, a PM2.5 to PM10 ratio of 0.185 (0.00010 divided by 0.00054) was used to estimate PM2.5 emissions from drilling.

 

3.5.7       PM2.5 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 PM2.5 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 PM2.5.

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 PM2.5 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 PM2.5 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 PM2.5 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 NOx emissions do not include NOx 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 PM2.5, and NO2, Emission Estimates 

 

Operational Year

PM10

PM2.5

NO2

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 PM2.5, and NO2, Emission Estimates

 

 

Operational Year

PM10

PM2.5

NO2

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

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 NOx,  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 PM2.5 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)

Annual

57

100

57

 

PM10

24-hour

50

150

50

Annual

20

No separate standard

20

 

PM2.5

24-hour

No separate standard

35 (Note 2)

35 (Note 2)

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: NOx emissions from the combustion of landfill gas in the flare and NOx emissions from combustion of ANFO during blasting. A third potential source is off-road equipment. However, on an hourly basis, the total NOx emissions from off-road equipment are on the order of one-third the flare and blasting emissions, and the NOx 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 NOx 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, NOx emissions from off-road equipment are on the order of one-half total NOx 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 NOx to NO2 to be about 10 to 1. Therefore, for this AQIA, it was assumed that initially 10 percent of the NOx 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 NOx is converted to NO2. The default 75 percent conversion method is based on a nation-wide average of monitored NO2 to NOx 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 NOx emissions.

 

The blasting NOx 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 NOx is much smaller. Four research papers examined the relative proportion of NO2 in the NOx emitted from ANFO blasts. The most relevant paper examined NO2 conversion at an open cut coal mine in Australia (NOx 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 NOx to NO2 ratio of 28 to 1, i.e., NO2 is 3.6% of NOx).  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 NOx 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 7th-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 (1st-High)

69.8

61.5

14.3

45.8

37.3

38.6

1st-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

7th-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       PM2.5 Impact Results for 24-Hour AAQS

The maximum 24-hour PM2.5 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 1st-high modeled impact plus the 1st-high background, which is much more conservative methodology than required for the Federal standard, which is stated as a 3-year average 98th percentile.)

 

 

Table 4-141

Maximum Potential 24-Hour Impact of PM2.5

(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       PM2.5 Impact Results for Annual AAQS

The maximum annual PM2.5 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 PM2.5

(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:

 

 

  1. 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.

 

  1. 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.

 

  1. 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.

 

  1. 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.

 

  1. 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

  1. The results of that analysis are as follows:

 

 

  1. 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.

 

  1. 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.

 

  1. 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.

 

  1. 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.

  1. 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.
  2. 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.
  3. 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.
  4. 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 PM2.5, 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 PM2.5, 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

Copyright 2010 Kleinfelder

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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.

 

 

 

 

 

Copyright Kleinfelder, Inc. 2011

 

 

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

 

18

 

59.2%

 

2959.7

 

134

MSW in pods

13.1

34.37

21.27

27.82

18

10.3%

516.7

39

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

 

18

 

23.4%

 

69.1

 

3

Processed Green Material (ADC) in refuse vehicles

 

3.73

 

14.3

 

10.57

 

12.435

 

8.17

 

76.6%

 

225.9

 

61

Internal light duty

vehicles

 

NA

 

3

 

3

 

3

 

4

 

0%

 

0.0

 

25

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

 

18

 

59.2%

 

591943.2

 

26724

MSW in pods

13.1

34.37

21.27

27.82

18

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

 

18

 

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

 

NA

 

3

 

3

 

3

 

4

 

0%

 

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) -

Copyright Kleinfelder, Inc. 2011

 

 

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

 

Copyright Kleinfelder, Inc. 2011

 

 

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)

NOx

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:

 

NOx = 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:

 

NOx = 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 NOx emissions,  CO emissions increase. Since NOx is related to potential ozone formation, the extremely low NOx 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 PM2.5 emission factors shown in Table 1. For PM2.5 and NOx 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 NOx  impacts in Table 3 assume complete conversion of NOx 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:

  1. HRA Model Runs
  2. Criteria Pollutant Model Runs
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