California Air Resources Board 04/03/2003 Planning & Technical Support Division Detailed Documentation for Fugitive Dust and Ammonia Emission Inventory Changes for the SJVU APCD Particulate Matter SIP Overview The table that follows lists the internal working memos used to develop and document changes to the fugitive dust and ammonia components of the San Joaquin Valley’s PM10 emission inventory. These documents, combined with dozens of meetings with the SJV air district staff and stakeholders, served as the basis for many of the emission inventory improvements for the 2003 PM10 SIP. Following the table, each document is provided. April 2003 Planning and Technical Support Division California Air Resources Board Fugitive Dust and Ammonia Emission Inventory Documentation for the SJV 2003 SIP Revision
105
Embed
Detailed Documentation for Fugitive Dust and Ammonia ... · 2000 Ag LP and Hvst PM10.xls Output provided following first document in this table, Selection of PM10 Emission Factors
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
California Air Resources Board 04/03/2003 Planning & Technical Support Division
Detailed Documentation for Fugitive Dust and Ammonia Emission Inventory Changes for the SJVU APCD Particulate Matter SIP Overview The table that follows lists the internal working memos used to develop and document changes to the fugitive dust and ammonia components of the San Joaquin Valley’s PM10 emission inventory. These documents, combined with dozens of meetings with the SJV air district staff and stakeholders, served as the basis for many of the emission inventory improvements for the 2003 PM10 SIP. Following the table, each document is provided.
April 2003 Planning and Technical Support Division California Air Resources Board
Fugitive Dust and Ammonia Emission Inventory Documentation for the SJV 2003 SIP Revision
California Air Resources Board 04/03/2003 Planning & Technical Support Division
ARB/phg 4/3/03 EI DOCS SUMMARY.DOC 2
Summary of Working Documents Used for the San Joaquin Valley
1999 Base Year PM10 Emission Inventory for Fugitive Dust and Ammonia
File Name Description Date Land Prep & Harvest EF Selection 12_2002.doc Selection of PM10 Emission Factors
for Agricultural Harvest and Land Preparation Questions and answers regarding assignment of the UCD emission factors to crop activities Does not include refinements to harvest emission factors to assign EF to all crops. Attach detailed LP & harvest emissions spreadsheet page: Crop Specific LandPrep & Harvest Ems SJV.xls
December 3, 2002
Land Prep & Harvest EF Selection 10_2002.doc Selection of PM10 Emission Factors for Agricultural Harvest Activities (also includes land prep assignments) Questions and answers regarding assignment of the UCD emission factors to crop activities
September 4, 2002
Land Prep & Harvest EF Selection 9_2002.doc Selection of PM10 Emission Factors for Agricultural Harvest and Land Preparation
September 4, 2002
Land Prep & Harvest EF Issues 8_2002.doc Assigning UC Davis Agricultural Emission Factors to Land Preparation & Harvest Activities Initial questions for assigning UCD Efs to crop activities.
August 23, 2002
Harvest EF Documentation12_2002.doc Methodology for Assigning PM10 Emission Factors for California Agriculture Harvest Activities − Final summary of harvest EF assumptions − Does not include final table showing all crop
assignments (attach Excel data from sheet: Crop Ranking & Harvest AnalysisRev2.xls / no- attach to land prep & EF selection document instead.
December 3, 2002
California Air Resources Board 04/03/2003 Planning & Technical Support Division
ARB/phg 4/3/03 EI DOCS SUMMARY.DOC 3
File Name Description Date Harvest EF Documentation11_2002.doc Methodology for Assigning PM10 Emission Factors
for California Agriculture Harvest Activities − Final summary of harvest EF assumptions − Does not include final table showing all crop
assignments (attach Excel data from sheet: Crop Ranking & Harvest AnalysisRev2.xls / no- attach to land prep & EF selection document instead.
November 4, 2002
Harvest EF Proposal 10_2002.doc Initial Methodology For Assigning PM10 Emission Factors For California Agriculture Harvest Activities. Initial proposal with attached Excel EF assignments (see .pdf)
October 18, 2002
Ag Emissions Summary Field&Cattle.doc Update of Agricultural PM10 Emissions for Harvest, Land Preparation, and Confined Cattle Operations − Changes in harvest & land prep emissions − Bar charts showing changes by crops − Charts showing changes by county − Discussion of Efs for cattle
September 19, 2002
EFAssignToDistrictCassel.doc Prepared by UCD to discuss almond Efs Also provides discussion and Efs for land planing activities
July 12, 2002
Agricultural Emission Factors.doc Summary of UCD emission factors and assignment of crops to respective emission factors
May 14, 2002
onfarm_travel_questionsARBcomment.doc Sierra Research questionnaire with ARB comments for on-farm unpaved road travel
September 2002
Beef & Dairy PM EF Selection9_2002.doc Selection of PM10 Emission Factors for Feedlot and Dairy
Operations (Initial write-up) August 30, 2002
Beef & Dairy PM EF Selection12_2002.doc Selection of PM10 Emission Factors for Feedlot and Dairy Operations (Final write-up)
November 23, 2002
Beef & Dairy PM Estimate.doc Initial scoping estimates of PM10 emissions from beef and dairy operations. Rough estimates of beef and dairy PM using different scenarios. Compares emissions with other sources.
August 13, 2002
California Air Resources Board 04/03/2003 Planning & Technical Support Division
ARB/phg 4/3/03 EI DOCS SUMMARY.DOC 4
File Name Description Date Crop Ranking & Harvest AnalysisRev2.xls Table which provides final harvest emission factor assignments
for the SJV and statewide. Provides initial emissions summaries and ranking. Follows previous document, Methodology for Assigning PM10 Emission Factors for California Agriculture Harvest Activities.
November 2002
Crop Specific LandPrep & Harvest Ems SJV.xls Shows crops, composite emission factors, emissions, and assumptions for harvest and land preparation emissions. Includes notes, documentation, base emission factors, and temporal profiles.
November 13, 2002
2000 Ag LP and Hvst PM10.xls Output provided following first document in this table, Selection of PM10 Emission Factors for Harvest and Land Preparation. Prepared by Hong Yu. Shows crops, composite emission factors, emissions, and assumptions for harvest and land preparation emissions. See Crop Specific LandPrep & Harvest Ems SJV.xls for fully documented spreadsheet (this just includes part of one page of full sheet.)
November 13, 2002
Ag EI Change Summary 2_2003.ppt Improvements to Particulate Matter Agricultural Emission Estimates. PowerPoint presentation summarizing changes to agricultural emission inventory.
February 25, 2002
Ag Harvest Methodology4_2003.pdf ARB full methodology for estimating harvest emissions (draft)
January 2003
Ag LandPrep Methodology4_2003.pdf ARB full methodology for estimating land preparation emissions (draft)
January 2003
Unpaved Ag1999 Mar_26_2003.xls Spreadsheet showing assignments of available agricultural crop VMT data to each commodity.
March 2003
PavedRoadEmsDraft7_31_2000.pdf Documentation and analysis of the main update to paved road dust emissions. Future refinements were made which slightly altered the emissions.
July 2002
Analysis of AP42 Paved_Unpaved.doc Brief analysis of the differences between the ARB methodologies and the EPA methodologies for paved and unpaved road dust.
July 2002
NH3 Environ Draft Final Report.pdf Ammonia emission inventory documentation. Contact ARB for document (32 pages).
December 2002
California Air Resources Board 04/03/2003 Planning & Technical Support Division
ARB/phg 4/3/03 EI DOCS SUMMARY.DOC 5
File Name Description Date NH3 Environ Final Workplan All.pdf Assumptions and documentation used for ammonia
emission inventory development. Contact ARB for document (63 pages).
Prepared by: Patrick Gaffney California Air Resources Board Planning and Technical Support Division [email protected] 916-322-7303
California Air Resources Board Planning & Technical Support Division
Land Prep & Harvest EF Selection 12_2002.doc 1
MEMORANDUM
TO: SJV PM10 SIP Emission Inventory Group FROM: Patrick Gaffney, ARB DATE: December 3, 2002 SUBJECT: Selection of PM10 Emission Factors
for Agricultural Harvest and Land Preparation Objectives: This document provides the emission factors and
assumptions used for computing agricultural harvest and land preparation emissions for California. The following information is provided: 1) Harvest - Summarize the geologic PM10 emission factors
used for almond, cotton, and wheat harvesting based on California specific data.
2) Land Preparation - Assign the most appropriate geologic PM10 emission factors for agricultural land preparation using California emission factors.
For both land preparation and harvesting, activity specific California emission factors are used to replace the generic national emission factors used in the past.
Approach: In a previous ARB technical summary1, the available geologic
PM10 emission factors for harvest and land preparation were summarized and discussed. To help identify the most appropriate PM emission factors for harvest and land preparation, this initial summary was used as a basis for a teleconference with regulators, researchers, and industry representatives2. Considering the lack of comprehensive agricultural emission factor data, the majority of the teleconference focused on developing consensus on the “best-fit” emission factors. The selected factors are based on a combination of direct scientific applicability, as well as general experience and observations about the relative emissions potential of various operations.
2
Harvest Emission Factors:
For the crops show, Table 1 below summarizes the harvest emission factors3 to be used for California emission estimates. Discussion of each item in the table is provided below. Note that for many harvest operations, crop specific emission factors are not available. Therefore, the emission factors shown in Table 1 were used to assign harvest emissions to all other California crops. This approach is discussed in a separate ARB technical paper4. In the past, emissions for crops without specific emission factors were set to zero.
1) Is the updated cotton harvest EF acceptable? - It is based on more tests and more recent tests. - But, picking and cutting EFs are the same value (based on separate tests) for the updated factor. Is this reasonable? It was decided by the group that the updated UC Davis emission factor of 3.4 lbs PM10/acre is appropriate for the combination of cotton picking and stalk cutting. It was mentioned that the tests were performed under various typical conditions. Some tests were performed at dusk, which could lead to higher than average emission readings.
2) Is the most recent almond shaking EF of 3.7 lbs/acre acceptable? Is the magnitude reasonable in comparison to the almond harvest other operations? After extended discussion, the answer to this question was no. There were too few tests performed and the
3
emissions do not seem consistent with observed PM levels. Based on subjective judgment, it was agreed to use a value of 0.37 for the shaking emission EF, which is one-hundredth of the pickup emissions. This value will be updated as additional information becomes available.
3) Is the updated almond sweeping factor acceptable and a reasonable relative magnitude (13.1 lbs PM10/acre) compared to other operations? Generally, the old factors are considered invalid because plume profiling was not performed. Again, the answer to this question was no. All of the tests were performed within the canopy, which is not representative of emissions leaving the orchard. In addition, observation shows that sweeping is substantially less dusty than pickup operations. Based on subjective judgment, it was agreed to use a value of 3.7 for the sweeping emission EF, which is one-tenth of the pickup emissions. This value will be updated as additional information becomes available
4) Is the almond pickup emission factor of 36.7 lbs PM10/acre acceptable? It is in reasonable agreement with the older emission factor of 32.3. In this case, the answer was yes, this factor seems reasonable, it is based upon tests performed outside the canopy, and it is in reasonable agreement with earlier tests. Therefore, a total of 36.7 lbs PM10/acre will be used for the complete almond pickup operation. [Note 12/3/02: Some recent PM sampling comparisons by UCD and Texas A&M indicate that it may be justified to reduce the UCD almond harvest emission factor by approximately 50%. More analysis is being performed to resolve this issue, and the emissions may be updated accordingly.]
4
Land Preparation Emission Factors:
Table 2 below summarizes the new emission factors selected for land preparation activities for cotton and wheat. In the next section, these emission factors are applied to similar activities for other crops. (Previously, a single emission factor of approximately 4 lbs PM10/acre-pass was assigned to all land preparation activities.) In addition to the EFs below, UCD also has field test data from 70 to 90 additional land preparation tests that have not been analyzed. If the resources become available to analyze these data, the emission factors shown below will be updated to reflect this new information.
Table 2. Land Preparation Emission Factors.
Emission Factor3 Land Preparation Activity (lbs PM10/acre-pass)
Land Preparation Emission Factor Questions and Decisions:
1) Is the new root cutting emission factor acceptable? In the past, this operation was assigned ~4/lbs PM10/acre. Yes. The testing performed was specific to cotton
2) Is the new discing emission factor of 1.2 acceptable? In the last SIP this value was assigned a value of 4. Yes. The value is based on several representative tests for cotton and wheat, and is of a reasonable magnitude.
3) Based on UCD analysis5 (T. Cassel, 7/12/2002), the chiseling emission factor is based on very dry, but operationally valid conditions following June/July wheat harvest. It is suggested that rather than use the non-representative, worst case conditions, that an average of the discing and chiseling emission factors be used for typical chiseling. This value is 2.9 lbs PM10/acre-pass. Should the average value be used for chiseling? If not, what is the alternative? No. The average value is not acceptable because it is observed that chiseling and tilling operations are typically less dusty than discing operations, so using a larger value is not appropriate. Further, Terry also clarified that the tested operation listed as chiseling in the UCD report more closely represents ripping or subsoiling, in which a small
5
number of long shanks are used to work the soil. Therefore, it was decided to apply the UCD discing emission factor of 1.2, to tilling and chiseling. Ripping and subsoiling will be assigned to the UCD ‘chiseling’ emission factor of 4.6.
4) Based on UCD analysis5 (T. Cassel, 7/12/2002), new emission rates were provided for summer land planing and floating. The average emissions are 12.5 lbs PM10/acre-pass which is based on 3 different sites and 23 tests. Is this factor acceptable? The average EFs for each site are comparable. Although testing occurred during the summer, it is typical to perform planing/floating during relatively dry conditions, so it is likely that the factors are representative. Some were surprised about the magnitude of the planing and floating emission factor, but the data appear to be valid. Tests were performed for garbanzo, tomato, and wheat under typical moisture conditions. It was decided to use the UCD factor for land planing and floating. ARB will provide a summary of the emissions by operation to ensure that the factor does not produce unrealistic emission estimates.
5) As part of typical land maintenance, land used for field crops is periodically planed or leveled to remove high spots. Because these operations are not performed annually, they are not reflected in the default crop calendars. How often does land planing and leveling occur? In discussions with agricultural experts, it was estimated that land planing and leveling are, on average, performed once every five years for field and row crops. The emission factor assigned to these operations is 12.5 lbs PM10/acre-pass. Planing and leveling are not routinely performed for orchard or vine crops, so the land maintenance operations are not applied to these crops.
6) Currently the ARB does not include cultivation operations in our emission estimates. Because of the lack of information, it is suggested that we retain this approach. In addition, cultivation typically does not occur in the SJV during the time of the year with elevated PM levels. The weeding emission factor will not be used. In discussions with the group, it was decided that the weeding factor is applicable to various land preparation activities such as listing and rolling, so it will be used for those operations. There is not sufficient information to assign cultivation emissions. It is expected that these emissions will be relatively small and occur during the growing season, when PM levels are typically not substantially elevated.
6
Assigning Emission Factors to Land Preparation Operations:
There are a limited number of emission factors available and a large number of agricultural land preparation operations. Table 3 summarizes the activity specific emission factor assignments agreed upon by the agricultural stakeholder group. The available emission factor choices are shown in the previous table and include root cutting (0.3 lbs PM10/acre-pass), discing (1.2), ripping (4.6), land planing/floating (12.5), and weeding (0.8). The emission factor used in the previous 1997 PM10 SIP for all land preparation operations was approximately 4 lbs PM10/acre-pass.
Table 3. Land Preparation Emission Factor Assignments
Land Preparation Operation
Emissions Category
Emission Factor (lbs PM10/ acre-pass)
List Weeding 0.8 List & Fertilize Weeding 0.8 Listing Weeding 0.8 Roll Weeding 0.8 Spring Tooth Weeding 0.8 Bed Preparation Weeding 0.8 Seed Bed Preparation Weeding 0.8 Shape Beds Weeding 0.8 Shape Beds & Roll Weeding 0.8 Shaping Weeding 0.8 Terrace Weeding 0.8 Chisel Discing 1.2 Plow Discing 1.2 Mulch Beds Discing 1.2 Disc Discing 1.2 Disc & Furrow-out Discing 1.2 Disc & Roll Discing 1.2 Finish Disc Discing 1.2 Harrow Disc Discing 1.2 Post Burn/Harvest Disc Discing 1.2 Stubble Disc Discing 1.2 Unspecified Operation Discing 1.2 Land Preparation, Gen. Discing 1.2 Subsoil Ripping 4.6 Subsoil-deep chisel Ripping 4.6 Float Land planing 12.5 3 Wheel Plane Land planing 12.5 Land Plane Land planing 12.5 Laser Level Land planing 12.5 Level Land planing 12.5 Level (new vineyard) Land planing 12.5 Plane Land planing 12.5
7
Conclusions: Using the above emission factors and assumptions, the ARB
estimated statewide emissions by county. Using the current assumptions, the land preparation emissions in the SJV decreased by about 62% (34,000 tons per year to 13,000 tons per year). Harvest related emissions increased by about 75%, from 7,600 tons per year to 13,300 tons per year. In total, the land preparation and harvest PM10 emissions estimates decreased by about 37%. The attached table provides crop specific emission estimates and assumptions for the San Joaquin Valley, as well as emission factor and temporal profile summaries. The updated emissions using these new data are an important step forward in better representing agricultural PM10 emissions, especially considering that the prior default value of 4 lbs of PM10 per acre-pass was applied to every land preparation operation in California, and harvest emission factors were only assigned to four crops.
References: 1Assigning UC Davis Agricultural Emission Factors to Land
Preparation & Harvest Activities, P. Gaffney, California Air Resources Board, 8/23/2002 2Teleconference 8/29/2002. Dave Jones (SJVUAPCD), Patia Siong (SJVUAPCD), Stephen Shaw (SJVUAPCD), Terry Cassel (UCD), Paul Martin (Western United Dairymen), Roger Isom (California Cotton Ginners and Growers Association), Cynthia Corey (California Farm Bureau), Gene Beach (Almond Hullers and Processors Association), George Bluhm (CDFA), Matt Summers (CDFA), Patrick Gaffney (ARB). With additional discussion at the 10/28/2002 SJV Agricultural Technical Advisory Group regarding land maintenance. 3Sources and Sinks of PM10 in the San Joaquin Valley, Interim Report. Flocchini, R.G., James, T.A., et. al., August 10, 2002. Air Quality Group, Crocker Nuclear Laboratory, University of California, Davis. Table 6.1. 4Methodology for Assigning PM10 Emission Factors for California Agriculture Harvest Activities, P. Gaffney, California Air Resources Board, 11/04/2002 5Terry Cassel, Informal write-up for SJV Ag Tech Committee, Evaluation of ARB application of UCD emission factors, July 12, 2002
Land Prep Harvest Total Land Prep Harvest Acres Acre PassSJV TOTAL ALL CROPS 13,028 13,333 26,361 2.71 2.77 9,616,913 13,894,524
NOTES:
Generala) Only the San Joaquin Valley Air Basin part of Kern county is included in the emission estimates.b) The crop names are based on the names used in the CDFA annual crop summary for the year 2000.c) The emissions shown are for the year 2000, based on the most recent CDFA acreage data. These values were backcasted to develop the 1999 emission estimates.
Emissionsd) Land preparation geologic dust emissions are emissions resulting from discing, ripping, land planing, weeding, and other operations.e) Harvest geologic dust emissions are emissions resulting from crop harvesting. Emission estimates are based on scaling emission measurements from cotton, wheat, and almond harvesting emission factors.
Emission Factorsf) The Land Preparation emission factors shown are a composite, which are based on a combination of the emissions from the types and number of land preparation operations performed for each crop. These assignments are based upon the Crop Calendar Profile shown in the Land Prep. & Harvest Assignments category. The base emission factors are shown below.g) The Harvest emission factor is based on scaling the measured emissions from harvesting cotton, wheat, or almonds. Each crop is assigned a Base Factor and a Division factor to scale the emissions appropriately to each crop. These assignments are shown in the Land Prep. & Harvest Assignments category. The base harvest emission factor are shown below.
Activity Datah) Acres shown are the total number of acres grown within the San Joaquin Valley Air Basin. This acreage is from the annual statewide summary reports prepared by CDFA, and represents the year 2000. Acres are used in computing harvest emissions.i) Acre-Passes are the number of acres for each crop, multiplied by the annual number of land preparation operations for the crop. The number of land preparation operations is based on information in the crop calendar profile. Acre passes are used in computing land preparation emissions.
Crop Specific LandPrep & Harvest Ems SJV.xls, hyu and pgaffney DRAFT 3
California Air Resources BoardPlanning Technical Support Division
DRAFT December 3, 2002
Air Basin Crop Name
Land Preparation Harvest
Total Land Preparation and Harvest
Land Prep. (lbs/acre-pass)
Harvest (lbs/acre) Acres Acre
PassesCrop Calendar
ProfileHarvest EF Base Factor
Harvest EF Division Factor
Emissions (tons PM10/year) PM10 Emission Factors Activity Data Land Prep. & Harvest Assignments
Land Prep. & Harvest Assignmentsj) The Crop Calendar Profile is the crop calendar that was assigned to the crop for emission estimation purposes. For each crop, the calendar includes what operations are performed, how many times they are performed, and when they are performed.k) the Harvest EF Base Factor is the base emission factor used to compute the harvest emissions. The three possible selections are cotton, almonds, or wheat. For other crops, variants of these factors were assigned to compute harvesting emissions.l) The Harvest EF Division Factor is used to divide the Harvest EF Base Factor to scale the base factor appropriately for the crops that do not have specific emission factors.
Base Emission Factors for Land Preparation Activities Base Emission Factors for Harvest Activities
Land Preparation Operation Emissions Category
Emission Factor
(lbs PM10/ acre-pass)
List Weeding 0.8List & Fertilize Weeding 0.8Listing Weeding 0.8Roll Weeding 0.8Spring Tooth Weeding 0.8Bed Preparation Weeding 0.8Seed Bed Preparation Weeding 0.8Shape Beds Weeding 0.8Shape Beds & Roll Weeding 0.8Shaping Weeding 0.8Terrace Weeding 0.8Chisel Discing 1.2Plow Discing 1.2Mulch Beds Discing 1.2Disc Discing 1.2Disc & Furrow-out Discing 1.2Disc & Roll Discing 1.2Finish Disc Discing 1.2Harrow Disc Discing 1.2Post Burn/Harvest Disc Discing 1.2Stubble Disc Discing 1.2Unspecified Operation Discing 1.2Land Preparation, Gen. Discing 1.2Subsoil Ripping 4.6Subsoil-deep chisel Ripping 4.6Float Land planing 12.53 Wheel Plane Land planing 12.5Land Plane Land planing 12.5 Prepared by:Laser Level Land planing 12.5 Hong Yu ([email protected])Level Land planing 12.5 Patrick Gaffney ([email protected])Level (new vineyard) Land planing 12.5 California Air Resources BoardPlane Land planing 12.5 November 13, 2002
Agricultural Harvest Operation
Emission Factor (lbs PM10/acre)
Cotton
Wheat
3.440.85.8
Almonds
Average SJV Temporal Profiles (monthly percent)JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC5.12 4.82 9.02 1.50 1.86 1.24 1.61 1.98 1.39 8.79 31.71 30.970.07 0.07 0.14 0.14 0.14 5.10 5.24 0.37 37.47 43.96 7.22 0.07
Land PreparationHarvest
Crop Specific LandPrep & Harvest Ems SJV.xls, hyu and pgaffney DRAFT 4
DRAFT – Stakeholder Use Only / Do Not Release 9/4/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Selection of PM10 Emission Factors for Agricultural Harvest Activities Objectives: California specific emission factors are available for cotton,
almond, and wheat harvesting. Develop an approach using existing data to assign harvest emission factors to the majority of crop acreage in the San Joaquin Valley.
Approach: In a previous ARB technical summary1, the available
emission factors for harvest and land preparation were summarized and discussed. To help identify the most appropriate PM emission factors for harvest and land preparation, this initial summary was used as a basis for a teleconference with regulators, researchers, and industry representatives2. Considering the lack of comprehensive agricultural emission factor data, the majority of the teleconference focused on developing consensus on the “best-fit” emission factors. The selected factors are based on a combination of direct scientific applicability, as well as general experience and observations about the relative emissions potential of various operations. It was also agreed that emissions computed using the new emission factor assignments will be provided to for review prior to their inclusion into the SJV PM SIP.
Harvest Emission Factors:
The table below summarizes the selected harvest emission factors recommended for use in the SJV PM10 SIP. Discussion of each selection is provided below.
DRAFT – Stakeholder Use Only / Do Not Release 9/4/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Harvest Emission Factor Questions & Decisions: 1) Is the updated cotton harvest EF acceptable?
- It is based on more tests and more recent tests. - But, picking and cutting EFs are the same value (based on separate tests) for the updated factor. Is this reasonable? It was decided by the group that the updated UC Davis emission factor of 3.4 .lbs PM10/acre is appropriate for the combination of cotton picking and stalk cutting. It was mentioned that the tests were performed under various typical conditions. Some tests were performed at dusk, which could lead to higher than average emission readings.
2) Is the most recent almond shaking EF of 3.7 lbs/acre acceptable? Is the magnitude reasonable in comparison to the almond harvest other operations? After extended discussion, the answer to this question was no. There were too few tests performed and the emissions do not seem consistent with observed PM levels. Based on subjective judgment, it was agreed to use a value of 0.37 for the shaking emission EF, which is one-hundredth of the pickup emissions. This value will be updated as additional information becomes available.
3) Is the updated almond sweeping factor acceptable and a reasonable relative magnitude (13.1 lbs PM10/acre) compared to other operations? Generally, the old factors are considered invalid because plume profiling was not performed. Again, the answer to this question was no. All of the tests were performed within the canopy, which is not representative of emissions leaving the orchard. In addition, observation shows that sweeping is substantially less dusty than pickup operations. Based on subjective judgment, it was agreed to use a value of 3.7 for the sweeping emission EF, which is one-tenth of the pickup emissions. This value will be updated as additional information becomes available
4) Is the almond pickup emission factor of 36.7 lbs PM10/acre acceptable? It is in reasonable agreement with the older emission factor of 32.3. In this case, the answer was yes, this factor seems reasonable, it is based upon tests performed outside the canopy, and it is in reasonable agreement with earlier tests. Therefore, a total of 36.7 lbs PM10/acre will be used for the complete almond pickup operation.
For many harvest operations emission factors are not available. In these cases, these emissions will continue
DRAFT – Stakeholder Use Only / Do Not Release 9/4/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
to be zero as they have been historically. Fortunately, harvest emission rates are available for the highest acreage crop (cotton), and for one of the highest PM10 producing harvest activities (almond harvest).
Land Preparation Emission Factors:
The table below summarizes the new emission factors selected for land preparation activities for cotton and wheat. In the next section, these emission factors are applied to similar activities for other crops. In addition to the EFs below, UCD also has field test data from 70 to 90 additional land preparation tests that have not been analyzed. If the resources become available to analyze these data, the emission factors shown below will be updated to reflect this new information.
Emission Factor3 Land Preparation Activity (lbs PM10/acre-pass)
Land Preparation Emission Factor Questions and Decisions:
1) Is the new root cutting emission factor acceptable? In the past, this operation was assigned ~4/lbs PM10/acre. Yes. The testing performed was specific to cotton
2) Is the new discing emission factor of 1.2 acceptable? In the last SIP this value was assigned a value of 4. Yes. The value is based on several representative tests for cotton and wheat, and is of a reasonable magnitude.
3) Based on Terry’s (UCD) 7/12/2002 analysis, the chiseling emission factor is based on very dry, but operationally valid conditions following June/July wheat harvest. It is suggested that rather than use the non-representative, worst case conditions, that an average of the discing and chiseling emission factors be used for typical chiseling. This value is 2.9 lbs PM10/acre-pass. Should the average value be used for chiseling? If not, what is the alternative? No. The average value is not acceptable because it is observed that chiseling and tilling operations are typically less dusty than discing operations, so using a larger value is not appropriate.
DRAFT – Stakeholder Use Only / Do Not Release 9/4/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Further, Terry also clarified that the tested operation listed as chiseling in the UCD report more closely represents ripping or subsoiling, in which a small number of long shanks are used to work the soil. Therefore, it was decided to apply the UCD discing emission factor of 1.2, to tilling and chiseling. Ripping and subsoiling will be assigned to the UCD ‘chiseling’ emission factor of 4.6.
4) Based on Terry’s 7/12/2002 analysis, new emission rates were provided for summer land planing and floating. The average emissions are 12.5 lbs PM10/acre-pass which is based on 3 different sites and 23 tests. Is this factor acceptable? The average EFs for each site are comparable. Although testing occurred during the summer, it is typical to perform planing/floating during relatively dry conditions, so it is likely that the factors are representative. Some were surprised about the magnitude of the planing and floating emission factor, but the data appear to be valid. Tests were performed for garbanzo, tomato, and wheat under typical moisture conditions. It was decided to use the UCD factor for land planing and floating. ARB will provide a summary of the emissions by operation to ensure that the factor does not produce unrealistic emission estimates.
5) Currently the ARB does not include cultivation operations in our emission estimates. Because of the lack of information, it is suggested that we retain this approach. In addition, cultivation typically does not occur in the SJV during the time of the year with elevated PM levels. The weeding emission factor will not be used. In discussions with the group, it was decided that the weeding factor is applicable to various land preparation activities such as listing and rolling, so it will be used for those operations.
Assigning Emission Factors to Operations:
There are a limited number of emission factors and a large number of agricultural land preparation operations. The table following summarizes the emission factor assignments agreed upon by the group during our teleconference. The available emission factor choices are shown in the previous table and include root cutting (0.3 lbs PM10/acre-pass), discing (1.2), ripping (4.6), land planing/floating (12.5), and weeding (0.8). The emission factor used in the 1997 PM10 SIP for all land preparation operations was approximately 4 lbs PM10/acre-pass.
DRAFT – Stakeholder Use Only / Do Not Release 9/4/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Land Preparation Emission Factor Assignments Land Preparation Operation
Emissions Category
Emission Factor (lbs PM10/ acre-pass)
List Weeding 0.8 List & Fertilize Weeding 0.8 Listing Weeding 0.8 Roll Weeding 0.8 Spring Tooth Weeding 0.8 Bed Preparation Weeding 0.8 Seed Bed Preparation Weeding 0.8 Shape Beds Weeding 0.8 Shape Beds & Roll Weeding 0.8 Shaping Weeding 0.8 Terrace Weeding 0.8 Chisel Discing 1.2 Plow Discing 1.2 Mulch Beds Discing 1.2 Disc Discing 1.2 Disc & Furrow-out Discing 1.2 Disc & Roll Discing 1.2 Finish Disc Discing 1.2 Harrow Disc Discing 1.2 Post Burn/Harvest Disc Discing 1.2 Stubble Disc Discing 1.2 Unspecified Operation Discing 1.2 Land Preparation, Gen. Discing 1.2 Subsoil Ripping 4.6 Subsoil-deep chisel Ripping 4.6 Float Land planing 12.5 3 Wheel Plane Land planing 12.5 Land Plane Land planing 12.5 Laser Level Land planing 12.5 Level Land planing 12.5 Level (new vineyard) Land planing 12.5 Plane Land planing 12.5
Conclusions: Using the above emission factors and assumptions, the ARB
will estimate the SJV harvest and land preparation emissions. These emissions will be provided by crop and by operation for stakeholder review. It is also important that EPA and environmental group representatives be included in reviewing the emissions and underlying assumptions. The updated emissions using these new data is an important step forward in better representing agricultural PM10 emissions, especially considering that the prior default value of 4 lbs of PM10 per acre-pass was applied to every land preparation operation in California.
DRAFT – Stakeholder Use Only / Do Not Release 9/4/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
References: 1Assigning UC Davis Agricultural Emission Factors to Land
Preparation & Harvest Activities, P. Gaffney, California Air Resources Board, 8/23/2002 2Teleconference 8/29/2002. Dave Jones (SJVUAPCD), Patia Siong (SJVUAPCD), Stephen Shaw (SJVUAPCD), Terry Cassel (UCD), Paul Martin (Western United Dairymen), Roger Isom (California Cotton Ginners and Growers Association), Cynthia Corey (California Farm Bureau), Gene Beach (Almond Hullers and Processors Association), George Bluhm (CDFA), Matt Summers (CDFA), Patrick Gaffney (ARB). 3Sources and Sinks of PM10 in the San Joaquin Valley, Interim Report. Flocchini, R.G., James, T.A., et. al., August 10, 2002. Air Quality Group, Crocker Nuclear Laboratory, University of California, Davis. Table 6.1. 4Terry Cassel, Informal write-up for SJV Ag Tech Committee, Evaluation of ARB application of UCD emission factors, July 12, 2002
DRAFT – Stakeholder Use Only / Do Not Release 9/4/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Selection of PM10 Emission Factors for Agricultural Harvest and Land Preparation Objectives: Identify the most appropriate emission factors for estimating
the PM10 component of fugitive dust emissions from agricultural harvesting and land preparation operations within California.
Approach: In a previous ARB technical summary1, the available
emission factors for harvest and land preparation were summarized and discussed. To help identify the most appropriate PM emission factors for harvest and land preparation, this initial summary was used as a basis for a teleconference with regulators, researchers, and industry representatives2. Considering the lack of comprehensive agricultural emission factor data, the majority of the teleconference focused on developing consensus on the “best-fit” emission factors. The selected factors are based on a combination of direct scientific applicability, as well as general experience and observations about the relative emissions potential of various operations. It was also agreed that emissions computed using the new emission factor assignments will be provided to for review prior to their inclusion into the SJV PM SIP.
Harvest Emission Factors:
The table below summarizes the selected harvest emission factors recommended for use in the SJV PM10 SIP. Discussion of each selection is provided below.
DRAFT – Stakeholder Use Only / Do Not Release 9/4/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Harvest Emission Factor Questions & Decisions: 1) Is the updated cotton harvest EF acceptable?
- It is based on more tests and more recent tests. - But, picking and cutting EFs are the same value (based on separate tests) for the updated factor. Is this reasonable? It was decided by the group that the updated UC Davis emission factor of 3.4 .lbs PM10/acre is appropriate for the combination of cotton picking and stalk cutting. It was mentioned that the tests were performed under various typical conditions. Some tests were performed at dusk, which could lead to higher than average emission readings.
2) Is the most recent almond shaking EF of 3.7 lbs/acre acceptable? Is the magnitude reasonable in comparison to the almond harvest other operations? After extended discussion, the answer to this question was no. There were too few tests performed and the emissions do not seem consistent with observed PM levels. Based on subjective judgment, it was agreed to use a value of 0.37 for the shaking emission EF, which is one-hundredth of the pickup emissions. This value will be updated as additional information becomes available.
3) Is the updated almond sweeping factor acceptable and a reasonable relative magnitude (13.1 lbs PM10/acre) compared to other operations? Generally, the old factors are considered invalid because plume profiling was not performed. Again, the answer to this question was no. All of the tests were performed within the canopy, which is not representative of emissions leaving the orchard. In addition, observation shows that sweeping is substantially less dusty than pickup operations. Based on subjective judgment, it was agreed to use a value of 3.7 for the sweeping emission EF, which is one-tenth of the pickup emissions. This value will be updated as additional information becomes available
4) Is the almond pickup emission factor of 36.7 lbs PM10/acre acceptable? It is in reasonable agreement with the older emission factor of 32.3. In this case, the answer was yes, this factor seems reasonable, it is based upon tests performed outside the canopy, and it is in reasonable agreement with earlier tests. Therefore, a total of 36.7 lbs PM10/acre will be used for the complete almond pickup operation.
For many harvest operations emission factors are not available. In these cases, these emissions will continue
DRAFT – Stakeholder Use Only / Do Not Release 9/4/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
to be zero as they have been historically. Fortunately, harvest emission rates are available for the highest acreage crop (cotton), and for one of the highest PM10 producing harvest activities (almond harvest).
Land Preparation Emission Factors:
The table below summarizes the new emission factors selected for land preparation activities for cotton and wheat. In the next section, these emission factors are applied to similar activities for other crops. In addition to the EFs below, UCD also has field test data from 70 to 90 additional land preparation tests that have not been analyzed. If the resources become available to analyze these data, the emission factors shown below will be updated to reflect this new information.
Emission Factor3 Land Preparation Activity (lbs PM10/acre-pass)
Land Preparation Emission Factor Questions and Decisions:
1) Is the new root cutting emission factor acceptable? In the past, this operation was assigned ~4/lbs PM10/acre. Yes. The testing performed was specific to cotton
2) Is the new discing emission factor of 1.2 acceptable? In the last SIP this value was assigned a value of 4. Yes. The value is based on several representative tests for cotton and wheat, and is of a reasonable magnitude.
3) Based on Terry’s (UCD) 7/12/2002 analysis, the chiseling emission factor is based on very dry, but operationally valid conditions following June/July wheat harvest. It is suggested that rather than use the non-representative, worst case conditions, that an average of the discing and chiseling emission factors be used for typical chiseling. This value is 2.9 lbs PM10/acre-pass. Should the average value be used for chiseling? If not, what is the alternative? No. The average value is not acceptable because it is observed that chiseling and tilling operations are typically less dusty than discing operations, so using a larger value is not appropriate.
DRAFT – Stakeholder Use Only / Do Not Release 9/4/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Further, Terry also clarified that the tested operation listed as chiseling in the UCD report more closely represents ripping or subsoiling, in which a small number of long shanks are used to work the soil. Therefore, it was decided to apply the UCD discing emission factor of 1.2, to tilling and chiseling. Ripping and subsoiling will be assigned to the UCD ‘chiseling’ emission factor of 4.6.
4) Based on Terry’s 7/12/2002 analysis, new emission rates were provided for summer land planing and floating. The average emissions are 12.5 lbs PM10/acre-pass which is based on 3 different sites and 23 tests. Is this factor acceptable? The average EFs for each site are comparable. Although testing occurred during the summer, it is typical to perform planing/floating during relatively dry conditions, so it is likely that the factors are representative. Some were surprised about the magnitude of the planing and floating emission factor, but the data appear to be valid. Tests were performed for garbanzo, tomato, and wheat under typical moisture conditions. It was decided to use the UCD factor for land planing and floating. ARB will provide a summary of the emissions by operation to ensure that the factor does not produce unrealistic emission estimates.
5) Currently the ARB does not include cultivation operations in our emission estimates. Because of the lack of information, it is suggested that we retain this approach. In addition, cultivation typically does not occur in the SJV during the time of the year with elevated PM levels. The weeding emission factor will not be used. In discussions with the group, it was decided that the weeding factor is applicable to various land preparation activities such as listing and rolling, so it will be used for those operations.
Assigning Emission Factors to Operations:
There are a limited number of emission factors and a large number of agricultural land preparation operations. The table following summarizes the emission factor assignments agreed upon by the group during our teleconference. The available emission factor choices are shown in the previous table and include root cutting (0.3 lbs PM10/acre-pass), discing (1.2), ripping (4.6), land planing/floating (12.5), and weeding (0.8). The emission factor used in the 1997 PM10 SIP for all land preparation operations was approximately 4 lbs PM10/acre-pass.
DRAFT – Stakeholder Use Only / Do Not Release 9/4/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Land Preparation Emission Factor Assignments Land Preparation Operation
Emissions Category
Emission Factor (lbs PM10/ acre-pass)
List Weeding 0.8 List & Fertilize Weeding 0.8 Listing Weeding 0.8 Roll Weeding 0.8 Spring Tooth Weeding 0.8 Bed Preparation Weeding 0.8 Seed Bed Preparation Weeding 0.8 Shape Beds Weeding 0.8 Shape Beds & Roll Weeding 0.8 Shaping Weeding 0.8 Terrace Weeding 0.8 Chisel Discing 1.2 Plow Discing 1.2 Mulch Beds Discing 1.2 Disc Discing 1.2 Disc & Furrow-out Discing 1.2 Disc & Roll Discing 1.2 Finish Disc Discing 1.2 Harrow Disc Discing 1.2 Post Burn/Harvest Disc Discing 1.2 Stubble Disc Discing 1.2 Unspecified Operation Discing 1.2 Land Preparation, Gen. Discing 1.2 Subsoil Ripping 4.6 Subsoil-deep chisel Ripping 4.6 Float Land planing 12.5 3 Wheel Plane Land planing 12.5 Land Plane Land planing 12.5 Laser Level Land planing 12.5 Level Land planing 12.5 Level (new vineyard) Land planing 12.5 Plane Land planing 12.5
Conclusions: Using the above emission factors and assumptions, the ARB
will estimate the SJV harvest and land preparation emissions. These emissions will be provided by crop and by operation for stakeholder review. It is also important that EPA and environmental group representatives be included in reviewing the emissions and underlying assumptions. The updated emissions using these new data is an important step forward in better representing agricultural PM10 emissions, especially considering that the prior default value of 4 lbs of PM10 per acre-pass was applied to every land preparation operation in California.
DRAFT – Stakeholder Use Only / Do Not Release 9/4/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
References: 1Assigning UC Davis Agricultural Emission Factors to Land
Preparation & Harvest Activities, P. Gaffney, California Air Resources Board, 8/23/2002 2Teleconference 8/29/2002. Dave Jones (SJVUAPCD), Patia Siong (SJVUAPCD), Stephen Shaw (SJVUAPCD), Terry Cassel (UCD), Paul Martin (Western United Dairymen), Roger Isom (California Cotton Ginners and Growers Association), Cynthia Corey (California Farm Bureau), Gene Beach (Almond Hullers and Processors Association), George Bluhm (CDFA), Matt Summers (CDFA), Patrick Gaffney (ARB). 3Sources and Sinks of PM10 in the San Joaquin Valley, Interim Report. Flocchini, R.G., James, T.A., et. al., August 10, 2002. Air Quality Group, Crocker Nuclear Laboratory, University of California, Davis. Table 6.1. 4Terry Cassel, Informal write-up for SJV Ag Tech Committee, Evaluation of ARB application of UCD emission factors, July 12, 2002
DRAFT – Internal Use Only – Do Not Release 8/23/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Assigning UC Davis Agricultural Emission Factors to Land Preparation & Harvest Activities Objectives UC Davis has recently published particulate matter emission
factors for a variety of agricultural activities1. These factors need to be assigned to specific crop activities to replace the existing EPA AP-42 emission factor. This paper summarizes the issues and decisions that need to be made in applying the new factors to the PM10 SIP emission estimates.
Harvest Emission Factors
The table below summarizes the existing emission factors used for harvesting and the new emission factors in the UCD report. There are some dramatic differences between the old and new values. The cotton harvest estimates triple in size and the almond harvest estimates double.
* Updated value from 12 July 2002 analysis by Terry Cassel, UC Davis. Harvest Emission Factor Questions:
1) Is the updated cotton harvest EF acceptable? - It is based on more tests and more recent tests. - But, picking and cutting EFs are the same value (based on separate tests) for the updated factor. Is this reasonable?
2) Is the most recent almond shaking EF of 3.7 lbs/acre acceptable? Is the magnitude reasonable in comparison to the almond harvest other operations?
3) Is the updated almond sweeping factor acceptable and a reasonable relative magnitude (13.1 lbs PM10/acre) compared to other operations? Generally,
DRAFT – Internal Use Only – Do Not Release 8/23/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
the old factors are considered invalid because plume profiling was not performed.
4) Is the almond pickup emission factor of 36.7 lbs PM10/acre acceptable? It is in reasonable agreement with the older emission factor of 32.3.
Land Preparation Emission Factors
The table below summarizes the existing and new emission factors for land preparation activities for cotton and wheat. It is proposed that these emission factors be applied to other similar activities for other crops. In addition to the EFs below, UCD also has test data from 70 to 90 additional land preparation tests, but the resources are unavailable to analyze the data (see table 6.3 of the UCD report). As additional information becomes available, the emission factors shown will be updated. Below are two sets of questions. The first set is to clarify the acceptability of the emission factors. The second questions are to help assign the limited number of emission factors to the full array of agricultural activities.
Average (disc & chisel) 2.9 Land Planing & Floating4 12.5 1397 Weeding
≈4.0 default for all
operations
0.8 89.2 Land Preparation Emission Factor Questions:
1) Is the new root cutting emission factor acceptable? In the past, this operation was assigned ~4/lbs PM10/acre.
2) Is the new discing emission factor acceptable? 3) Based on Terry’s (UCD) 7/12/2002 analysis, the
chiseling emission factor is based on very dry, but operationally valid conditions following June/July wheat harvest. It is suggested that rather than use the non-representative, worst case conditions, that an average of the discing and chiseling emission factors be used for typical chiseling. This value is 2.9 lbs
DRAFT – Internal Use Only – Do Not Release 8/23/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
PM10/acre-pass. Should the average value be used for chiseling? If not, what is the alternative?
4) Based on Terry’s 7/12/2002 analysis, new emission rates are provided for summer land planing and floating. Based on 3 different sites and 23 tests, the average emissions are 12.5 lbs PM10/acre-pass. Is this factor acceptable? The average EFs for each site are comparable. Although testing occurred during the summer, it is typical to perform planing/floating during relatively dry conditions, so it is likely that the factors are representative.
5) Currently the ARB does not include cultivation operations in our emission estimates. Because of the lack of information, it is suggested that we retain this approach. In addition, cultivation typically does not occur in the SJV during the time of the year with elevated PM levels. The weeding emission factor will not be used.
Assigning Emission Factors to Operations
There are a limited number of emission factors and a large number of agricultural land preparation operations. The table below is an initial assignment by ARB staff. Help is needed in assigning the available factors to the most similar operations. The available emission factor choices are shown in the previous table and include root cutting (0.3 lbs PM10/acre-pass), discing (1.2), chiseling (4.6), average of discing and chiseling (2.9), land planing/floating (12.5). The emission factor used in the 1997 PM10 SIP for all land preparation operations was approximately 4 lbs PM10/acre-pass. Emission Factor Assignment Questions: Are the emission factor assignments in the following table correct? If not, please provide suggested best-fit assignments.
DRAFT – Internal Use Only – Do Not Release 8/23/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Land Preparation Operation
Emissions Category
Emission Factor (lbs PM10/ acre-pass)
Assignment Okay? (Y/N) Suggestion?
Chisel Average 2.9 Plow Average 2.9 Spring Tooth Average 2.9 Subsoil Average 2.9 Subsoil-deep chisel Average 2.9 Disc Disc 1.2 Disc & Furrow-out Disc 1.2 Disc & Roll Disc 1.2 Finish Disc Disc 1.2 Float Disc 1.2 Harrow Disc Disc 1.2 Post Burn/Harvest Disc Disc 1.2 Stubble Disc Disc 1.2 3 Wheel Plane Land plane 12.5 Bed Preparation Land plane 12.5 Land Plane Land plane 12.5 Laser Level Land plane 12.5 Level Land plane 12.5 Level (new vineyard) Land plane 12.5 Plane Land plane 12.5 Unspecified Operation Average 2.9 Land Preparation, Gen. Average 2.9 List Average 2.9 List & Fertilize Average 2.9 Listing Average 2.9 Mulch Beds Average 2.9 Roll Disc 1.2 Seed Bed Preparation Disc 1.2 Shape Beds Disc 1.2 Shape Beds & Roll Disc 1.2 Shaping Disc 1.2 Sulfur Dusting Any Ideas? 0? Terrace Average 2.9
Conclusions The above questions need to be resolved so that appropriate
emission rates can be assigned to update the PM10 estimates for land preparation and harvest activities. This information will be incorporated into the SJV PM10 SIP. Although some emission rates may not be completely definitive, they are likely a positive forward step from the previous default of 4 lbs PM10 per acre-pass for all crops and activities within California.
DRAFT – Internal Use Only – Do Not Release 8/23/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
References: 1Sources and Sinks of PM10 in the San Joaquin Valley, Interim
Report. Flocchini, R.G., James, T.A., et. al., August 10, 2002. Air Quality Group, Crocker Nuclear Laboratory, University of California, Davis. Table 6.1. 2UCD 1995, Evaluation of Fugitive PM10 Emissions from Cotton Production, Annual Report, 1995” 3Compilation of Air Pollutant Emission Factors, Volume 1, Fourth Edition, AP-42. U.S. EPA, September 1985. Section 11.2.2 4Terry Cassel, Informal write-up for SJV Ag Tech Committee, Evaluation of ARB application of UCD emission factors, July 12, 2002
California Air Resources Board 12/03/2002 Planning & Technical Support Division
Harvest EF Documentation12_2002.doc 1
MEMORANDUM
TO: SJV PM10 SIP Emission Inventory Group FROM: Patrick Gaffney, ARB DATE: December 3, 2002 SUBJECT: Methodology for Assigning PM10 Emission Factors
for California Agriculture Harvest Activities Objective: Develop a method to assign PM10 geologic dust harvest PM
emission factors to all California crops. In the past, geologic PM harvest emissions were only computed for four crops and the remaining crops were assigned zero harvest emissions.
Approach: UC Davis researchers, under contract to the USDA,
measured geologic dust particulate matter emissions from harvesting cotton, almonds, and wheat in California. These factors are shown below1. Using the available emission factors as a baseline, harvest emission factors were also approximated for the other California crops. The scaling approach used to assign the three available PM emission factors to the dozens of California crops is highly subjective. ARB staff provided the initial scaling assignments, which were then refined by members of the agricultural community2. Members of the SJV Agricultural Technical Advisory Group concluded that it was more realistic to include rough approximations of PM harvest emissions than to set the values to zero, as has been done historically. Table 1. California Harvest Emission Factors
Assumptions: The emission rate assumptions were assigned to reflect the
relative geologic PM generation potential of various harvest practices. This broad approach is a first attempt to estimate these emissions. Table 2 below provides examples of some of the emission factor assignments. Emission factor assumptions and emissions estimates for all SJV crops are provided in the detailed emissions table attached to the ARB memo, “Selection of PM10 Emission Factors for Agricultural Harvest and Land Preparation,” December 2002.3 Table 2. Example Harvest Emission Factor Assumptions
Crop AssumptionHarvest Emission
Factor (lbs PM10/acre)
Cotton Cotton 3.4 Vine Cotton/20 0.17 Tomato Cotton/20 0.17 Fruit Trees Cotton/40 0.085 Corn Wheat/2 2.8 Alfalfa Zero 0.0 Walnuts Almonds 40.8 Sugar beets, onions, potatoes
Cotton/2
2.7
As additional harvest emissions data are collected, they will be incorporated into the methodology and the emissions estimates will be recalculated. [Note 12/3/02: Some recent PM sampling comparisons by UCD and Texas A&M indicate that it may be justified to reduce the UCD almond harvest emission factor by approximately 50%. More analysis is being performed to resolve this issue, and the emissions may be updated accordingly.]
Diesel and gasoline exhaust pipe emissions from tractors and other equipment used in harvesting are computed separately as part of the ARB’s off-road mobile source emissions model, and are not included in these estimates.
Results: Using the approach shown, approximately 77% of the
geologic harvest PM10 emissions are from the three crops with measured emission factors. If walnuts are included (using the almond emission factor) this value increases to 94% of the total harvest emissions. Roughly, the SJV PM10 harvest emissions from cotton are estimated as 1400 tons PM10/year, wheat is 900 tons/year, almonds are 7900 tons/year, and walnuts are 2200 tons/year,
3
for a total of about 12,400 tons/year for these four crops. All of the remaining crops contribute an additional 930 tons/year of PM10 in the SJV, for a grand total of approximately 13,330 tons/year (36.5 tons/day) of PM10 from SJV crop harvest activities. Crop specific emission details are provided in Reference 3. As mentioned, the assumptions included in this method will need refinement as additional information become available. However, the method shown will be used for the statewide 1999 harvest emissions inventory update.
References: 1 Sources and Sinks of PM10 in the San Joaquin Valley, Interim Report. Flocchini, R.G., James, T.A., et. al., August 10, 2002. Air Quality Group, Crocker Nuclear Laboratory, University of California, Davis. Table 6.1.
2 SJV Agricultural Technical Advisory Group, 11/28/2002. Also personal communications with Roger Isom (Cotton Incorporated) and Manuel Cunha (Nisei Farmers League) on 11/29/2002 based on discussions with growers during 11/28/2002.
3 Selection of PM10 Emission Factors for Agricultural Harvest and
Land Preparation, Memorandum; California Air Resources Board; Patrick Gaffney, December 3, 2002
Contact: Patrick Gaffney, Air Resources Board [email protected] (916) 322-7303
California Air Resources Board 11/4/2002 Planning & Technical Support Division
1
MEMORANDUM
TO: SJV PM10 SIP Emission Inventory Group FROM: Patrick Gaffney, ARB DATE: November 4, 2002 SUBJECT: Methodology for Assigning PM10 Emission Factors
for California Agriculture Harvest Activities Objective: Develop a method to assign PM10 geologic dust harvest PM
emission factors to all California crops. In the past, geologic harvest PM emissions were only computed for four crops and the remaining crops were assigned zero harvest emissions.
Approach: Particulate matter harvest emission factors for geologic dust
have been measured in California for cotton, almonds, and wheat by UC Davis, under contract to the USDA. These factors are shown below. Using the available emission factors as a baseline, harvest emission factors were approximated for other California crops. The scaling approach used to assign the three available PM emission factors to the dozens of California crops is highly subjective. Initial scaling assignments were made by ARB staff, which were then refined by members of the agricultural community. Members of the SJV Agricultural Technical Advisory Group concluded that it was more realistic to include rough approximations of PM harvest emissions than to set the values to zero, as has been done historically. Table 1. California Harvest Emission Factors
California Air Resources Board 11/4/2002 Planning & Technical Support Division
2
Assumptions: The emission rate assumptions were assigned to reflect the
relative geologic PM generation potential of various harvest practices. This broad approach is a first attempt to estimate these emissions. Table 2 below provides examples of some of the emission factor assignments. Assumptions for all crops are provided on the attached table. Table 2. Example Harvest Emission Factor Assumptions
Crop AssumptionHarvest Emission
Factor (lbs PM10/acre)
Cotton Cotton 3.4 Vine Cotton/20 0.17 Tomato Cotton/20 0.17 Fruit Trees Cotton/40 0.085 Corn Wheat/2 2.8 Alfalfa Zero 0.0 Walnuts Almonds 40.8 Sugar beets, onions, potatoes
Cotton/2
2.7
As additional harvest emissions data are collected, they will be incorporated into the methodology and the emissions estimates will be recalculated. Diesel and gasoline exhaust pipe emissions from tractors and other equipment used in harvesting are computed separately as part of the ARB’s off-road mobile source emissions model.
Results: Using the approach shown, approximately 78% of the
geologic harvest PM10 emissions are from the three crops with measured emission factors. If walnuts are included (using the almond emission factor) this value increases to 94% of the total harvest emissions. Roughly, the SJV PM10 harvest emissions from cotton are estimated as 1500 tons PM10/year, wheat is 1100 tons/year, almonds are 8400 tons/year, and walnuts are 2300 tons/year, for a total of about 13,300 tons/year. All of the remaining crops contribute an additional 850 tons/year of PM10 in the SJV. This is an increase of approximately 6%, or a total of approximately 14,150 tons/year (39.7 tons/day) of PM10 from SJV harvest activities. As mentioned, the assumptions included in this method will need refinement as additional information are available. However, the method shown will be used for the 1999 SJV emission inventory update.
California Air Resources Board 11/4/2002 Planning & Technical Support Division
3
References: 1Sources and Sinks of PM10 in the San Joaquin Valley, Interim Report. Flocchini, R.G., James, T.A., et. al., August 10, 2002. Air Quality Group, Crocker Nuclear Laboratory, University of California, Davis. Table 6.1.
Contact: Patrick Gaffney, Air Resources Board [email protected] (916) 322-7303
DRAFT November 4, 2002
Assignment of Geologic PM10 Harvest Emission Factors for the SJV
SJV Crop Acreage Summary (sorted by Acreage) SJV Harvest Emission Factor Assumptions and Emissions
CDFA Crops (some consolidation performed)
Sum Of CDFA SJV Harvested
Acres
% non Pasture
total acreage
Running Total
Crop Harvest Category*
Harvest EF Category
Harvest EF Assumption
(lbs PM10/acre)
Emissions Estimate
(tons PM10/year)
% of Emissions
Running Total
COTTON UPLAND+PIMA+UNSPEC 880,976 17% 17% Field Mech Cotton 3.4 1497.7 10.6% 11%HAY ALFALFA+SEED ALFALFA+HAY GREEN 612,829 12% 29% Field Mech Zero 0 0.0 0.0% 11%GRAPES WINE+RASIN+TABLE 585,581 11% 40% Vine Cotton/20 0.17 49.8 0.4% 11%ALMONDS ALL 413,069 8% 48% Tree Nut Almonds 40.8 8426.6 59.6% 71%WHEAT ALL+SEED+BARLEY+BARLEY FEED 379,120 7% 56% Field Mech Wheat 5.8 1099.4 7.8% 78%CORN SILAGE 318,121 6% 62% Field Mech Cotton/20 0.17 27.0 0.2% 79%SILAGE 220,437 4% 66% Field Mech Cotton/20 0.17 18.7 0.1% 79%TOMATOES PROCESSING 192,469 4% 70% Field Mech Cotton/20 0.17 16.4 0.1% 79%ORANGES NAVEL 121,476 2% 72% Tree Fruit Cotton/40 0.085 5.2 0.0% 79%WALNUTS ENGLISH 111,039 2% 75% Tree Nut Almonds 40.8 2265.2 16.0% 95%FIELD CROPS UNSPECIFIED 103,942 2% 77% Field Mech Cotton/20 0.17 8.8 0.1% 95%HAY GRAIN + HAY OTHER 103,381 2% 79% Field Mech Cotton/2 1.7 87.9 0.6% 95%GRAIN CORN 92,950 2% 80% Field Mech Cotton/2 1.7 79.0 0.6% 96%PISTACHIOS 73,856 1% 82% Tree Nut Almonds/10 4.08 150.7 1.1% 97%VEGETABLES UNSPECIFIED 68,281 1% 83% Veg Mech Cotton/20 0.17 5.8 0.0% 97%SUGAR BEETS 54,155 1% 84% Field Mech Cotton/2 1.7 46.0 0.3% 97%ORANGES VALENCIA 45,010 1% 85% Tree Fruit Cotton/40 0.085 1.9 0.0% 98%COTTON SEED 44,347 1% 86% Field Mech Cotton 3.4 75.4 0.5% 98%MELONS CANTALOUPE 41,546 1% 87% Fruit Hand Cotton/40 0.085 1.8 0.0% 98%BEANS DRY EDIBLE UNSPEC. 39,499 1% 88% Field Mech Cotton/2 1.7 33.6 0.2% 98%PLUMS 37,656 1% 88% Tree Fruit Cotton/40 0.085 1.6 0.0% 98%TOMATOES FRESH 32,884 1% 89% Hand Cotton/40 0.085 1.4 0.0% 98%NECTARINES 32,780 1% 90% Tree Fruit Cotton/40 0.085 1.4 0.0% 98%PEACHES FREESTONE 32,736 1% 90% Tree Fruit Cotton/40 0.085 1.4 0.0% 98%ASPARAGUS UNSPECIFIED 26,190 1% 91% Field Mech Cotton/2 1.7 22.3 0.2% 98%BEANS LIMA LG+UNSPEC+BABY+GREEN 25,276 0% 91% Field Mech Cotton/2 1.7 21.5 0.2% 99%ONIONS 25,050 0% 92% Field Mech Cotton/2 1.7 21.3 0.2% 99%POTATOES IRISH ALL 23,600 0% 92% Field Mech Cotton/2 1.7 20.1 0.1% 99%GARLIC ALL 22,590 0% 93% Field Mech Cotton/2 1.7 19.2 0.1% 99%LETTUCE HEAD 20,610 0% 93% Veg Hand Cotton/40 0.085 0.9 0.0% 99%OLIVES 20,445 0% 93% Tree Fruit Cotton/40 0.085 0.9 0.0% 99%RICE MILLING 18,806 0% 94% Field Mech Cotton/2 1.7 16.0 0.1% 99%APPLES ALL 18,448 0% 94% Tree Fruit Cotton/40 0.085 0.8 0.0% 99%CHERRIES SWEET 18,360 0% 94% Tree Fruit Cotton/40 0.085 0.8 0.0% 99%SAFFLOWER 18,203 0% 95% Field Mech Wheat 5.8 52.8 0.4% 100%PEACHES CLINGSTONE 17,252 0% 95% Tree Fruit Cotton/40 0.085 0.7 0.0% 100%APRICOTS ALL 15,319 0% 95% Tree Fruit Cotton/40 0.085 0.7 0.0% 100%PLUMS DRIED 14,534 0% 96% Tree Fruit Cotton/40 0.085 0.6 0.0% 100%FRUITS & NUTS UNSPECIFIED 14,470 0% 96% Tree Nut Cotton/40 0.085 0.6 0.0% 100%GRAPES UNSPECIFIED 13,800 0% 96% Vine Cotton/20 0.17 1.2 0.0% 100%BEANS BLACKEYE (PEAS) 12,500 0% 96% Field Mech Cotton/2 1.7 10.6 0.1% 100%FIGS DRIED 11,987 0% 97% Tree Fruit Almond/20 2.04 12.2 0.1% 100%FIELD CROPS SEED MISC. 11,307 0% 97% Field Mech Cotton/20 0.17 1.0 0.0% 100%BROCCOLI UNSPECIFIED 11,260 0% 97% Veg Hand Cotton/40 0.085 0.5 0.0% 100%CORN SWEET ALL 10,816 0% 97% Veg Hand Cotton/40 0.085 0.5 0.0% 100%POTATOES SWEET 10,386 0% 98% Field Mech Cotton/2 1.7 8.8 0.1% 100%HAY SUDAN 9,204 0% 98% Field Mech Zero 0 0.0 0.0% 100%
California Air Resources Board, pgaffney DRAFT
DRAFT November 4, 2002
MELONS WATERMELON 7,907 0% 98% Fruit Hand Cotton/40 0.085 0.3 0.0% 100%LEMONS ALL 7,892 0% 98% Tree Fruit Cotton/40 0.085 0.3 0.0% 100%BEANS FRESH UNSPECIFIED 7,740 0% 98% Vine Cotton/20 0.017 0.1 0.0% 100%PEPPERS BELL 6,836 0% 98% Veg Hand Cotton/40 0.085 0.3 0.0% 100%SEED VEG & VINECROP 5,227 0% 98% Veg Hand Cotton/40 0.085 0.2 0.0% 100%MELONS UNSPECIFIED 4,920 0% 99% Fruit Hand Cotton/40 0.085 0.2 0.0% 100%BEANS KIDNEY RED 4,900 0% 99% Field Mech Cotton/2 1.7 4.2 0.0% 100%LETTUCE LEAF 4,800 0% 99% Veg Hand Cotton/40 0.085 0.2 0.0% 100%PUMPKINS 4,550 0% 99% Field Mech Cotton/20 0.17 0.4 0.0% 100%MELONS HONEYDEW 4,460 0% 99% Fruit Hand Cotton/40 0.085 0.2 0.0% 100%POMEGRANATES 4,205 0% 99% Tree Fruit Cotton/40 0.085 0.2 0.0% 100%ORANGES UNSPECIFIED 3,830 0% 99% Tree Fruit Cotton/40 0.085 0.2 0.0% 100%PEAS GREEN PROCESSING 3,157 0% 99% Vine Cotton/20 0.17 0.3 0.0% 100%GRAPEFRUIT ALL 3,035 0% 99% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%SPINACH UNSPECIFIED 2,870 0% 99% Veg Hand Cotton/40 0.085 0.1 0.0% 100%BEANS SEED 2,758 0% 99% Field Mech Cotton/2 1.7 2.3 0.0% 100%OATS GRAIN 2,727 0% 99% Field Mech Wheat 5.8 7.9 0.1% 100%TANGERINES & MANDARINS 2,604 0% 99% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%CUCUMBERS 2,601 0% 99% Veg Hand Cotton/40 0.085 0.1 0.0% 100%KIWIFRUIT 2,552 0% 99% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%PEARS UNSPECIFIED 2,371 0% 100% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%CAULIFLOWER UNSPECIFIED 2,290 0% 100% Veg Hand Cotton/40 0.085 0.1 0.0% 100%SEED OTHER (NO FLOWERS) 2,080 0% 100% Field Mech Cotton/20 0.17 0.2 0.0% 100%PEACHES UNSPECIFIED 1,622 0% 100% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%TANGELOS 1,470 0% 100% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%NURSERY TURF 1,370 0% 100% Field Mech Zero 0 0.0 0.0% 100%BROCCOLI FRESH MARKET 1,356 0% 100% Veg Hand Cotton/40 0.085 0.1 0.0% 100%VEGETABLES ORIENTAL ALL 1,350 0% 100% Veg Hand Cotton/40 0.085 0.1 0.0% 100%PERSIMMONS 1,303 0% 100% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%CITRUS UNSPECIFIED 1,205 0% 100% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%LETTUCE BULK SALAD PRODS. 1,170 0% 100% Veg Hand Cotton/40 0.085 0.0 0.0% 100%BERRIES STRAWBERRIES UNSPEC 1,047 0% 100% Fruit Hand Cotton/40 0.085 0.0 0.0% 100%SQUASH 1,040 0% 100% Veg Hand Cotton/20 0.17 0.1 0.0% 100%BEANS SNAP FRESH MARKET 1,036 0% 100% Vine Cotton/20 0.17 0.1 0.0% 100%POTATOES SEED 1,035 0% 100% Veg Mech Cotton/2 1.7 0.9 0.0% 100%EGGPLANT ALL 910 0% 100% Veg Hand Cotton/40 0.085 0.0 0.0% 100%PECANS 898 0% 100% Tree Nut Almond/10 4.08 1.8 0.0% 100%BROCCOLI PROCESSING 766 0% 100% Veg Mech Cotton/40 0.085 0.0 0.0% 100%AVOCADOS ALL 646 0% 100% Tree Fruit Cotton/40 0.085 0.0 0.0% 100%CAULIFLOWER FRESH MARKET 373 0% 100% Veg Hand Cotton/40 0.085 0.0 0.0% 100%BEANS GARBANZO 322 0% 100% Field Mech Cotton/2 1.7 0.3 0.0% 100%QUINCE 213 0% 100% Tree Fruit Cotton/40 0.085 0.0 0.0% 100%SORGHUM GRAIN 211 0% 100% Field Mech Wheat 5.8 0.6 0.0% 100%TOMATOES CHERRY 170 0% 100% Veg Hand Cotton/40 0.085 0.0 0.0% 100%
TOTAL ACRES 5,144,378 100% Total PM10 14,139 100.0%Total Acres Total PM10 (tpy)
*Mech = Mechanically Harvested 13289 Cotton, Almond, Hand = Hand Harvested Wheat, Walnut
850 Total - (C,A,W,Walnut)Prepared by Patrick Gaffney with Assistance from Roger Isom, Manuel Cunha, and others 6% Percent ChangeContact Information:California Air Resources BoardPlanning and Technical Support [email protected], 916-322-7303Last Revised 11/4/2002
California Air Resources Board, pgaffney DRAFT
DRAFT – Internal Use 10/18/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Initial Methodology for Assigning PM10 Emission Factors for California Agriculture Harvest Activities Objective: Credible California PM10 emission rates are available for the
harvesting of cotton, almonds, and wheat. This document provides an initial approach for assigning harvesting emissions for crops grown in California that do not have emission factors.
Approach: The table below summarizes the currently available harvest
emission factors. Other factors provided in out of publication EPA documents are not appropriate for California.
Ten crops make up nearly 80% of the total non-pasture agricultural acreage in the San Joaquin Valley. Cotton, almonds, and wheat are about one-third of the total SJV acreage, so measured emission factors are available for a significant amount of acreage. The proposed approach is to use the available California emission factors and scale these factors to roughly represent the possible PM10 emissions from harvesting other crops. Because appropriate scientific information is not available, the scaling is purely subjective, based on rough guesses by regulatory and agricultural representatives. Using this approach with initial assumptions, approximately 73% of the harvest PM10 emissions are from the three crops with measured emission factors. If walnuts are included (using the almond emission factor) this value increases to 88% of the total emissions.
DRAFT – Internal Use 10/18/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Assumptions: All assumptions are a first estimate, provided to stimulate
discussion. The assumptions were somewhat arbitrarily, but were assigned to attempt to reflect the relative PM generation potential of various harvest practices. All assumptions are provided on the attached table, but a few examples include the following:
Crop Assumption EF (lbs PM10/acre) Cotton Cotton 3.4 Vine Cotton/20 0.17 Tomato Cotton/20 0.17 Fruit Trees Cotton/40 0.085 Corn Wheat/2 2.8 Sugar beets, onions, potatoes
Cotton/2
2.7
As shown, the assumed emission factors are scaled from existing emission factors. As other crop specific information becomes available, it will be substituted for the rough assumptions provided.
Next Steps: The assumptions in the attached table need to be refined as necessary. When these are complete, the harvest emissions will be calculated using this new information. Including the harvest emission estimates for crops without specific emission factors increased the emission estimates from about 11,000 tons/year to 15,000 tons per year, or about a 38% increase.
TotalCOTTON UPLAND+PIMA+SEED+UNSPEC 925323 18% 18% Field Mech Cotton 3.4 1573.0 10.4% 10%HAY ALFALFA+HAY+GRAIN&SEED ALFALFA 716210 14% 32% Field Mech Zero 0 0.0 0.0% 10%GRAPES WINE+RASIN+WINE 585581 11% 43% Vine Cotton/20 0.17 49.8 0.3% 11%ALMONDS ALL 413069 8% 51% Tree Nut Almonds 40.8 8426.6 55.5% 66%CORN SILAGE+GRAIN CORN 411071 8% 59% Field Mech Wheat/2 2.8 575.5 3.8% 70%WHEAT ALL+SEED+BARLEY+BARLEY FEED 379120 7% 67% Field Mech Wheat 5.8 1099.4 7.2% 77%TOMATOES PROCESSING+FRESH 225353 4% 71% Field Mech Cotton/20 0.17 19.2 0.1% 77%SILAGE 220437 4% 75% Field Mech Wheat 5.8 639.3 4.2% 82%ORANGES NAVEL 121476 2% 78% Tree Fruit Cotton/40 0.085 5.2 0.0% 82%WALNUTS ENGLISH 111039 2% 80% Tree Nut Almonds 40.8 2265.2 14.9% 97%FIELD CROPS UNSPECIFIED 103942 2% 82% Field Mech Wheat/2 2.8 145.5 1.0% 98%PISTACHIOS 73856 1% 83% Tree Nut Almonds/10 4.1 151.4 1.0% 99%VEGETABLES UNSPECIFIED 68281 1% 85% Veg Mech Cotton/20 0.17 5.8 0.0% 99%SUGAR BEETS 54155 1% 86% Field Mech Cotton/2 1.7 46.0 0.3% 99%ORANGES VALENCIA 45010 1% 87% Tree Fruit Cotton/40 0.085 1.9 0.0% 99%MELONS CANTALOUPE 41546 1% 87% Field Mech Cotton/40 0.085 1.8 0.0% 99%BEANS DRY EDIBLE UNSPEC. 39499 1% 88% Vine Cotton/40 0.085 1.7 0.0% 99%PLUMS 37656 1% 89% Tree Fruit Cotton/40 0.085 1.6 0.0% 99%NECTARINES 32780 1% 90% Tree Fruit Cotton/40 0.085 1.4 0.0% 99%PEACHES FREESTONE 32736 1% 90% Tree Fruit Cotton/40 0.085 1.4 0.0% 99%ASPARAGUS UNSPECIFIED 26190 1% 91% Field Mech Zero 0 0.0 0.0% 99%ONIONS 25050 0% 91% Field Mech Cotton/2 1.7 21.3 0.1% 99%POTATOES IRISH ALL 23600 0% 92% Field Mech Cotton/2 1.7 20.1 0.1% 99%GARLIC ALL 22590 0% 92% Field Mech Cotton/2 1.7 19.2 0.1% 99%LETTUCE HEAD 20610 0% 92% Field Hand Cotton/40 0.085 0.9 0.0% 99%OLIVES 20445 0% 93% Tree Fruit Cotton/40 0.085 0.9 0.0% 99%RICE MILLING 18806 0% 93% Field Mech Cotton/20 0.17 1.6 0.0% 99%APPLES ALL 18448 0% 94% Tree Fruit Cotton/40 0.085 0.8 0.0% 99%CHERRIES SWEET 18360 0% 94% Tree Fruit Cotton/40 0.085 0.8 0.0% 99%SAFFLOWER 18203 0% 94% Field Mech Wheat 5.8 52.8 0.3% 100%PEACHES CLINGSTONE 17252 0% 95% Tree Fruit Cotton/40 0.085 0.7 0.0% 100%APRICOTS ALL 15319 0% 95% Tree Fruit Cotton/40 0.085 0.7 0.0% 100%PLUMS DRIED 14534 0% 95% Tree Fruit Cotton/40 0.085 0.6 0.0% 100%FRUITS & NUTS UNSPECIFIED 14470 0% 95% Tree Nut Cotton/40 0.085 0.6 0.0% 100%GRAPES UNSPECIFIED 13800 0% 96% Vine Cotton/20 0.17 1.2 0.0% 100%BEANS BLACKEYE (PEAS) 12500 0% 96% Vine Cotton/40 0.085 0.5 0.0% 100%FIGS DRIED 11987 0% 96% Tree Fruit Cotton/40 0.085 0.5 0.0% 100%FIELD CROPS SEED MISC. 11307 0% 96% Field Mech Cotton/2 1.7 9.6 0.1% 100%BROCCOLI UNSPECIFIED 11260 0% 97% Veg Hand Cotton/40 0.085 0.5 0.0% 100%CORN SWEET ALL 10816 0% 97% Field Mech Wheat/2 2.8 15.1 0.1% 100%POTATOES SWEET 10386 0% 97% Field Mech Cotton/2 1.7 8.8 0.1% 100%BEANS LIMA LG. DRY 9677 0% 97% Vine Cotton/40 0.085 0.4 0.0% 100%HAY SUDAN 9204 0% 97% Field Mech Zero 0 0.0 0.0% 100%
California Air Resources Board, pgaffney DRAFT
DRAFT October 18, 2002
BEANS LIMA UNSPECIFIED 9100 0% 98% Vine Cotton/40 0.085 0.4 0.0% 100%MELONS WATERMELON 7907 0% 98% Field Hand Cotton/40 0.085 0.3 0.0% 100%LEMONS ALL 7892 0% 98% Tree Fruit Cotton/40 0.085 0.3 0.0% 100%BEANS FRESH UNSPECIFIED 7740 0% 98% Vine Cotton/40 0.085 0.3 0.0% 100%PEPPERS BELL 6836 0% 98% Veg Hand Cotton/40 0.085 0.3 0.0% 100%SEED VEG & VINECROP 5227 0% 98% Veg Hand Cotton/40 0.085 0.2 0.0% 100%MELONS UNSPECIFIED 4920 0% 98% Field Mech Cotton/20 0.17 0.4 0.0% 100%BEANS KIDNEY RED 4900 0% 99% Vine Cotton/40 0.085 0.2 0.0% 100%LETTUCE LEAF 4800 0% 99% Veg Hand Cotton/40 0.085 0.2 0.0% 100%PUMPKINS 4550 0% 99% Field Mech Cotton/20 0.17 0.4 0.0% 100%MELONS HONEYDEW 4460 0% 99% Field Mech Cotton/20 0.17 0.4 0.0% 100%POMEGRANATES 4205 0% 99% Tree Fruit Cotton/40 0.085 0.2 0.0% 100%BEANS LIMA BABY DRY 4190 0% 99% Vine Cotton/40 0.085 0.2 0.0% 100%ORANGES UNSPECIFIED 3830 0% 99% Tree Fruit Cotton/40 0.085 0.2 0.0% 100%PEAS GREEN PROCESSING 3157 0% 99% Vine Cotton/40 0.085 0.1 0.0% 100%GRAPEFRUIT ALL 3035 0% 99% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%SPINACH UNSPECIFIED 2870 0% 99% Veg Hand Cotton/40 0.085 0.1 0.0% 100%BEANS SEED 2758 0% 99% Vine Cotton/40 0.085 0.1 0.0% 100%OATS GRAIN 2727 0% 99% Field Mech Zero 0 0.0 0.0% 100%TANGERINES & MANDARINS 2604 0% 99% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%CUCUMBERS 2601 0% 99% Veg Hand Cotton/40 0.085 0.1 0.0% 100%KIWIFRUIT 2552 0% 99% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%PEARS UNSPECIFIED 2371 0% 99% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%BEANS LIMA GREEN 2309 0% 100% Vine Cotton/40 0.085 0.1 0.0% 100%CAULIFLOWER UNSPECIFIED 2290 0% 100% Veg Hand Cotton/40 0.085 0.1 0.0% 100%SEED OTHER (NO FLOWERS) 2080 0% 100% Veg Hand Cotton/40 0.085 0.1 0.0% 100%PEACHES UNSPECIFIED 1622 0% 100% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%TANGELOS 1470 0% 100% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%NURSERY TURF 1370 0% 100% Field Mech Zero 0 0.0 0.0% 100%BROCCOLI FRESH MARKET 1356 0% 100% Veg Hand Cotton/40 0.085 0.1 0.0% 100%VEGETABLES ORIENTAL ALL 1350 0% 100% Veg Hand Cotton/40 0.085 0.1 0.0% 100%PERSIMMONS 1303 0% 100% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%CITRUS UNSPECIFIED 1205 0% 100% Tree Fruit Cotton/40 0.085 0.1 0.0% 100%LETTUCE BULK SALAD PRODS. 1170 0% 100% Veg Hand Cotton/40 0.085 0.0 0.0% 100%BERRIES STRAWBERRIES UNSPEC 1047 0% 100% Fruit Hand Cotton/40 0.085 0.0 0.0% 100%SQUASH 1040 0% 100% Field Mech Cotton/20 0.17 0.1 0.0% 100%BEANS SNAP FRESH MARKET 1036 0% 100% Vine Cotton/40 0.085 0.0 0.0% 100%POTATOES SEED 1035 0% 100% Veg Mech Cotton/2 1.7 0.9 0.0% 100%EGGPLANT ALL 910 0% 100% Veg Hand Cotton/40 0.085 0.0 0.0% 100%PECANS 898 0% 100% Tree Nut Cotton/40 0.085 0.0 0.0% 100%BROCCOLI PROCESSING 766 0% 100% Veg Mech Cotton/40 0.085 0.0 0.0% 100%AVOCADOS ALL 646 0% 100% Tree Fruit Cotton/40 0.085 0.0 0.0% 100%CAULIFLOWER FRESH MARKET 373 0% 100% Veg Hand Cotton/40 0.085 0.0 0.0% 100%BEANS GARBANZO 322 0% 100% Vine Cotton/40 0.085 0.0 0.0% 100%QUINCE 213 0% 100% Tree Fruit Cotton/40 0.085 0.0 0.0% 100%SORGHUM GRAIN 211 0% 100% Field Mech Wheat 5.8 0.6 0.0% 100%TOMATOES CHERRY 170 0% 100% Veg Hand Cotton/40 0.085 0.0 0.0% 100%
5144378 1 15177 100.0%Total Acres Total PM10
*Mech = Mechanically Harvested Hand = Hand Harvested
California Air Resources Board, pgaffney DRAFT
Winston H. Hickox Agency Secretary
California Environmental Protection Agency
Printed on Recycled Paper
Air Resources Board Alan C. Lloyd, Ph.D.
Chairman 1001 I Street • P.O. Box 2815 • Sacramento, California 95812 • www.arb.ca.gov
Gray DavisGovernor
MEMORANDUM
TO: SJV Ag Tech Group FROM: Patrick Gaffney DATE: September 19, 2002 SUBJECT: Update of Agricultural PM10 Emissions for Harvest, Land Preparation,
and Confined Cattle Operations We have completed preliminary SJV estimates of PM10 emissions from agricultural land preparation and harvest activities based on the most current emission factors (UCD) and emission factor assignments determined by a subgroup of the SJV Ag Tech group. In summary, using the new data, land preparation PM10 emission estimates change from about 34,000 tons/year to 9,000 tons/year (a 74% reduction from current values). However, if land maintenance is added, which assumes land leveling every 4 years (more on this later), the updated land preparation PM10 emissions are approximately 14,000 tons/year (a 59% overall reduction). Harvest PM10 emission estimates change from 7,600 tons/year to 12,400 tons/year (a 64% increase). Figure 1 illustrates these emission changes for the San Joaquin Valley. The net change in the agricultural field operations emission estimates is - 49% if land maintenance is not included, and - 37% if land maintenance is included in the estimates. Figure 2 shows the contributions of land preparation and harvest emissions for each county for both 1993 and 2000. There are two major issues remaining that need to be resolved:
1) Should the land maintenance emissions be included? For the 1997 SIP, based on grower comments we assumed that all field crop acreage (non-orchard, non-vine) was leveled once every 4 years. This activity is not included in the crop calendars. Because the land leveling emission factor is fairly large (12.5 lbs PM10/acre-pass), it does bump up the emission significantly (from 9,000 to 14,000 tons PM10/year). If used, it will also be necessary to determine how to temporally apportion the land maintenance emissions.
2) There is some concern that harvest emissions are only included for almonds, cotton, and wheat, because these are the only crops with harvest emission factors. Harvest emissions are not included for any other crops. However, for land preparation, we assign existing emission factors to similar activities to
2
perform a complete emission estimate. Should we make similar assignments for some of the large acreage crops for harvesting?
For your viewing pleasure, I have also added some additional graphics if you want to see what crops are the largest contributors (the Figure 3 series) and the detailed differences in the old versus new emission estimates (the Figure 4 series). Moving on to cattle, for dairy PM10 emissions we selected an emission factor of 5 lbs PM10/1000 head/day. This factor is based on extensive testing at a single dairy in Texas. It provides a decent ‘gut-feeling’ number when compared with the UCD feedlot number of 29 lbs PM10/1000 head/day, but several people have commented that the 5-pound number seems quite low, so let’s discuss this. Background documents describe many of the assumptions used to develop the data described in this memo. The documents are:
Land Prep & Harvest EF Issues 8_2002.doc Land Prep & Harvest EF Selection 9_2002.doc Beef & Dairy PM Estimate.doc Beef & Dairy PM EF Selection.doc
The documents are available either from me at [email protected], 916-322-7303, or through Patia with the district.
Thanks for looking this over and it will be good to hear your comments at the Ag Tech meeting on the 23rd.
3
Figure 1. 1993 Versus Updated 2000 PM10 Land Preparation and Harvest Emissions Estimates.
1993 vs 2000 Land Preparation and HarvestPM10 Emission Estimates
Updated and 1993 CEIDARS Harvest + Land Prep PM10 Emissions
0
2,000
4,000
6,000
8,000
10,000
Fresno Kern Kings Madera Merced San Joaquin Stanislaus Tulare
tons
/yr
1993 CEIDARS
Updated 2000
California Air Resources Board DRAFT
12 July 2002 Evaluation of ARB application of UCD emission factors
Emission factors obtained from the UCD Interim Report to USDA, 2001, were assigned to harvest and land preparation operations by ARB in a draft document dated 6/24/02. These assignments raised several questions about the validity of specific experimental data and the applicability of those data to the categories listed. In this document we address the following questions:
• In the reported almond harvesting emission factors, the shaking and sweeping emissions are larger than expected relative to the pickup. Also, shaking emissions are larger than expected relative to sweeping. What are the circumstances surrounding the collection of these data that may have caused this unexpected result?
• In the reported land preparation emission factors, the chiseling emissions are larger than expected relative to discing. What are the circumstances causing this result?
• In the assignment of land preparation emission factors to the land preparation operations enumerated in the 1996 crop calendar, there is a need for an emission factor for land planning. Is there data to provide a factor for the land plane?
Almond harvest operations were monitored in 1994 and in 1995. All emission factors released in 1995 (“Evaluation of Fugitive PM10 Emissions from Cotton Production, Annual Report, 1995” as cited in the draft emission factor assignments) were computed from concentrations measured at a single height in a simple box model using a plume height estimated by visual observation to be 4 meters. These data are presented in Table 5.1 and figure 5.5 in the interim report. Data collected in 1995 included concentrations measured at multiple heights. These data were used to calculate emission factors using 3 models (Table 5.2 in the Interim report, reproduced here as Table 1).
Log Integration Block Integration Simple Box Model
Almond Nut Pickup 4467±5830 (7) 3233±1956 (7) 1201±647 (8)Table 1: 1995 Almond harvest emission factors for all valid tests. When the Interim report was written, emission factors were recalculated from these data using the specific methods defined in the peer reviewed publication (Holmen et al., 2000). The tests of almond pickup operation were screened to find only those conducted outside the canopy, as tests performed within the canopy were judged to overestimate the emission from the orchard as a unit. Those emission factors are presented in Table 5.3 in the Interim report and were averaged for inclusion to Table 6.1 in the Interim report. That average emission factor for almond nut pickup is the “new” factor in the draft ARB
emission factor assignment, 4106.19 mg/m2. It can be seen that this factor is very similar to the factor initially calculated using the log integration method for all valid tests (Table 1). Evaluation of the very small number of valid shaking and sweeping tests indicated that a recalculated average emission factor for these operations would be difficult to validate, so the previously reported emission factors (Table 1) were judged to be the best available and those were included in Table 6.1 of the Interim report and thus to the draft ARB emission factor assignments. Subsequent examination of the relevant almond shaking and sweeping tests yielded the following observations (Table 2):
Table 2: Inventory of almond shaking and sweeping tests from Appendix B of the Interim report and emission factors were computable. Most of the shaking and sweeping tests included in the average emission factors reported were conducted within the canopy. Thus, those data are judged to be non-representative of emissions from the orchard as a unit. A new average using only tests conducted within the canopy for shaking will give an emission factor of 412.5 mg/m2 or about 0.25 lbs/acre. Unfortunately, there were no valid sweeping tests outside the canopy. Of the two valid tests, one was conducted without the blowers on. We cannot recommend a PM10 emission factor for almond sweeping operations from the data currently available. Chiseling, also referred to as ripping in our database, was monitored following the wheat harvest in June and July. The emission factor in the Interim report (Table 6.1, Figure 6.7) for chiseling represents the driest possible soil conditions (about 2%) and should be considered a worst-case scenario. In photographs and field observation we judge the entrainment of soil by the tracks of the Caterpillar tractor used in this operation to be sufficient to cause the observed emission factor. The emission factor measured during
Shaking teststest # E.F. (mg/m2) comment95-038 only 9 m sample valid95-039 only 9 m sample valid95-048 only 1 and 3 m samples valid95-049 increasing concentration with height, plume not adequately defined95-050 wind direction inappropriate95-066 only 1 and 3 m samples valid95-067 360 valid test95-068 465 valid test95-069 1268 in canopy95-070 912 in canopy95-071 no valid downwind data95-072 2922 in canopy95-073 only 9 m sample valid95-074 wind direction inappropriate
Sweeping tests95-051 only 1 and 3 m samples valid95-052 only 1 and 3 m samples valid95-057 2324 in canopy95-058 598 in canopy, sweeper blowers not on95-059 wind direction inappropriate
one of the tests (97-050) when the relative humidity was above 40% indicates that emissions for this operation could be substantially lower when chiseling is conducted later in the year, as when following a cotton crop. Both land planning and floating were monitored in 1999. Emission factors computed from those data were not included in the Interim report, but Krystyna Trzepla-Nabaglo and Dr. Flocchini presented some of the data in a paper last month and the results are available now. The land planning tests were conducted in September on two fields, one following garbonzos and one following tomatoes. Floating was monitored on a third field in June and July following wheat harvest. The averaged result of these tests is presented in Table 3.
Table 3: Summary of land planning and floating tests, PM10 emission factors computed as kg/km2 (equal to mg/m2). These data indicate that, for land planning and floating operations conducted in the summer months, there is not a significant difference between emissions from the two operations. Therefore, we suggest a composite average PM10 emission factor for both operations of 1397 mg/m2. Since these operations were monitored exclusively in the summer season, it is reasonable to expect a significantly lower emission factor for colder, wetter conditions. Additional measurements will be necessary to quantify such an effect. We are currently restricted by the available data to describing this “worst case” condition. Please address any questions to Teresa Cassel email [email protected], phone 530/218-5690.
COMMODITY PRACTICE OPERATION # OF TESTS AVE. EF(KG/KM2) std dev (mg/m2) SEASONGarbonzo Land Preparation Land Planing 7 1703.77 1041.96 Sep.Tomatoes Land Preparation Land Planing 7 1228.60 1317.59 SeptemberWheat Land Preparation Floating 9 1257.62 1166.62 June/July
DRAFT 5/14/2002
Harvesting Emission Factors (UCD studies) Questions: 1. Which set of emission factors should be used? 2. Should we assign emission factor to other crops? How?
Old emission factors were based on 1994 field samples, most of which were made at three meters above ground. New emission factors were the results of 1995, 1996, and 1998 field tests, which were collected at three different heights of each sample location. Land Preparation Emission Factors (UCD Studies)
0.8 89.21 1 UCD 1995, “Evaluation of Fugitive PM10 Emissions from Cotton Production, Annual Report, 1995” 2 UCD 2001, “Interim Report: Sources and sinks of PM10 in the San Joaquin Valley”. 3 EPA AP-42 emission factor, currently used by ARB.
DRAFT 5/14/2002
Draft of assigning emission factors to land preparation operations • All the land preparation operations are summarized into four preliminary
categories: Land Plane, Disc, Chisel, and Land Preparation (general). • Discing and Chiseling have available emission factors in the UCD report. • Assuming the process of land plane is similar to chiseling, we assign 4.6
lbs/acre-pass to the land plane. • Land Preparation (general) takes the average emission factor. Land Preparation (from Crop Calendar, 1996)
Preliminary category
Preliminary Emission Factor (lbs/acre-pass)
Chisel Chisel 4.6 Plow Chisel 4.6 Spring Tooth Chisel 4.6 Subsoil Chisel 4.6 Subsoil-deep chisel Chisel 4.6 Disc Disc 1.2 Disc & Furrow-out Disc 1.2 Disc & Roll Disc 1.2 Finish Disc Disc 1.2 Float Disc 1.2 Harrow Disc Disc 1.2 Post Burn/Harvest Disc Disc 1.2 Stubble Disc Disc 1.2 3 Wheel Plane Land plane 4.6 Bed Preparation Land plane 4.6 Land Plane Land plane 4.6 Laser Level Land plane 4.6 Level Land plane 4.6 Level (new vineyard) Land plane 4.6 Plane Land plane 4.6 Blank Land Preparation 2.9 Land Preparation Land Preparation 2.9 List Land Preparation 2.9 List & Fertilize Land Preparation 2.9 Listing Land Preparation 2.9 Mulch Beds Land Preparation 2.9 Roll Land Preparation 2.9 Seed Bed Preparation Land Preparation 2.9 Shape Beds Land Preparation 2.9 Shape Beds & Roll Land Preparation 2.9 Shaping Land Preparation 2.9 Sulfur Dusting Land Preparation 2.9 Terrace Land Preparation 2.9
DRAFT 5/14/2002
Cultivation Weeding? Should we attempt to include cultivation emissions? Would probably use the UCD ‘Weeding’ emission factor if the answer is yes. Crop Calendars Crop calendars should to be revised to reflect the most current practices. Prepared for SJV Ag Tech group comment by: Hong Yu California Air Resources Board 916-3234887 [email protected]
Survey of On-Farm Travel Activity General Information Q1 In terms of acreage, what is the principal crop grown on the farm?
Q2Q3 What County is your farm located in? Q3 Q2 For the crop selected above, Wwhat is the acreage of your
average acre size perlargest farm? I tried to get them to not go with averages at our meeting because it creates
too much vagueness. In the STI questions, they had the farmer answer based on just their largest farm (Question Q1 in their report). I think this is a better approach.
0 – 40 40 – 80 80 – 160 160 – 320 320 – 640
over 640 (please specify) Q5 For the farm above, hHow many miles do you travel on unpaved
roads per farm (I think the ‘per farm’ creates too much ambiguity) on the farm per year?
0 – 20 20 – 40 40 – 80 over 80 (please specify)
2
Q6 What percent of annual yearly unpaved road farm travel occurs during harvest season? (may be unclear what we mean by ‘the peak’; my wording assumes harvest is peak, is that correct?)unpaved miles of travel are at the peak? Please split your answer between the following vehicle categories. If for example if 1030% of your unpaved road travel on the farm occurs during harvest, at the peak you would split that value between the two categories, with the total equaling 30%. them.
Licensed vehicles ____ Implements of Husbandry ____
3
Survey of Farm Travel Activity (cont.) Q7 How many total days are included in your answer to Question 6? Q8 What is the maximum number of trips made on your peak harvest
day? Think of a trip as entering or leaving a field.
Licensed vehicles ____ Implements of Husbandry ____
California Air Resources Board 12/03/2002 Planning & Technical Support Division
Beef & Dairy PM EF Selection12_2002.doc 1
MEMORANDUM
TO: SJV PM10 SIP Emission Inventory Group FROM: Patrick Gaffney, ARB DATE: December 3, 2002 SUBJECT: Selection of PM10 Emission Factors
for Feedlot and Dairy Operations Objectives: Identify the most appropriate emission factors for estimating
the PM10 component of fugitive dust emissions from cattle feedlot and dairy operations. These factors will replace the generic and undocumented emission factors used in past emission estimates that only included feedlot PM10 emissions. Due to lack of information, PM10 estimates are not being performed for other livestock at this time.
Approach: In a previous ARB technical summary1, cattle feedlot and
dairy emission factors were discussed, and emissions calculated. This initial summary was used as a basis for a discussion with regulators, researchers, and industry representatives2 to help identify the most appropriate PM emission factors for feedlot and dairy cattle.
Data: Table 1 summarizes the available emission factor candidates
for beef and dairy operation PM10 fugitive dust emissions. Table 1. Feedlot and Dairy Emission Factors
Discussion: It was determined the EPA feedlot PM10 estimate did not
include adequate testing or documentation to use for feedlot emission estimates. The UCD feedlot emission estimate was based on a reasonable number of samples and accepted testing methods were used. The Texas A&M PM10 feedlot estimate is provided for comparison, but the original Texas A&M test report for feedlots has not been evaluated. For dairies, the UCD PM10 estimate was based on limited
2
and non-representative sampling, and was performed primarily for method development, so it cannot be used for emission estimates. The Texas A&M dairy PM10 estimate is based on 12 separate tests using comprehensive sampling and analysis methods. In selecting emission factors, is important to recognize that the selections are flexible. As better information becomes available, it will be used to update emission estimates. The selections below are based on current “best available science”. Feedlot PM Emission Factor Selection The ARB will use the average value of 29 lbs PM10/1000 head/day for feedlots. This value is based on the work performed by UC Davis researchers4 and is assumed to be more representative of California conditions than the Texas A&M emission factor. Dairy PM Emission Factor Selection The Texas A&M dairy emission factor5 of 4.4 lbs PM10/1000 head/day was selected as the base dairy emission factor. To make the Texas emission factor more California specific, it was multiplied by a scaling factor. The scaling factor was based on the ratio of the California feedlot emission factor to the Texas feedlot emission factor. This ratio is 29:19, which converts to a multiplier of 1.53 and produces a dairy emission factor of 6.72 lbs PM10/1000 head/day for California dairies. Additional Assumptions Feedlot population estimates were based on information from California Department of Food and Agriculture (CDFA), which was correlated with data provided by the California Cattlemen’s Association. In computing population for the San Joaquin Valley Air Basin portion of Kern county, it was estimated that 53% of the county feedlot population is in the SJV Air Basin. Dairy population estimates were based on information from CDFA. The calf and heifer populations were not included in the PM10 emission estimate, which excludes about 40% of the overall dairy cattle population. Calves and heifers were excluded because they may not be located at dairies and their handling and behavior is different than the producing animals. This assumption may warrant further discussion. For making the Kern county air basin split, it was estimated that 70% of the Kern county dairy population is in the SJV Air
3
Basin. Emissions were computed as PM10, and then converted to Total Suspended Particulate (TSP) for entry into the ARB’s emissions database. For this conversion, PM10 = TSP * 0.4818.
Results and Conclusions:
The emission factor of 29 lbs PM10/1000 head/day was selected to estimate the fugitive dust emissions for California feedlots. An emission factor of 6.73 lbs PM10/1000 head/day was selected to estimate the fugitive dust emissions for California dairies. The resulting emission estimates are shown in Table 2. Although far from perfect, these values are based on more recent and more comprehensive testing any previous estimates. Of course, as additional information becomes available, it will be used to update the emission estimates. Table 2. Fugitive PM10 Emissions for Dairies and Feedlots in the San Joaquin Valley Air Basin (tons per year) Dairy Cows Feedlot Cattle Head, 1999* PM10 (tpy) Head, 1999 PM10 (tpy) Fresno 86,150 105.1 95,524 503.3 Kern 39,227 47.9 15,046 79.3 Kings 124,890 152.4 0 0.0 Madera 36,027 44.0 16,312 85.9 Merced 191,005 233.1 0 0.0 San Joaquin 93,044 113.5 0 0.0 Stanislaus 152,344 185.9 59,309 312.5 Tulare 333,941 407.5 56,516 297.8 Entire SJV 1,056,628 1,289.2 242,707 1,278.8
* Does not include dairy calves or heifers
References: 1Initial Scoping Estimates of PM10 Emissions from Beef and Dairy
Operations, P. Gaffney, California Air Resources Board, 8/13/2002 2Teleconference 8/29/2002. Dave Jones (SJVUAPCD), Patia Siong (SJVUAPCD), Stephen Shaw (SJVUAPCD), Terry Cassel (UCD), Paul Martin (Western United Dairymen), Roger Isom (California Cotton Ginners and Growers Association), Cynthia Corey (California Farm Bureau), Gene Beach (Almond Hullers and Processors Association), George Bluhm (CDFA), Matt Summers (CDFA), Patrick Gaffney (ARB). Also, Frank Mitloehner in separate conversation with P. Gaffney. Further discussion also occurred at the 10/28/2002 meeting of the SJV Agricultural Technical Advisory Group and informally at some
4
meetings of the SJV Ag Tech Dairy Subgroup. 3Compilation of Air Pollutant Emission Factors, Volume 1, Fourth Edition, AP-42. U.S. EPA, September 1985. Section 6.15 Beef Cattle Feedlots, Table 6.15-1. 4Sources and Sinks of PM10 in the San Joaquin Valley, Interim Report. Flocchini, R.G., James, T.A., et. al., August 10, 2001. Air Quality Group, Crocker Nuclear Laboratory, University of California, Davis. Table 6.1. 5Preliminary PM10 Emission Factor for Freestall Dairies, Goodrich, L.B., Parnell, C.B., Mukhtar, S., Lacey, R.E., Shaw, B.W., Department of Biological and Agricultural Engineering, Texas A&M University, Paper presented to the 2002 ASAE Annual International Meeting, July 2002
Contact: Patrick Gaffney, Air Resources Board [email protected] (916) 322-7303 November 13, 2002
DRAFT – Stakeholder Use Only / Do Not Release 8/30/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Selection of PM10 Emission Factors for Feedlot and Dairy Operations Objectives: Identify the most appropriate emission factors for estimating
the PM10 component of fugitive dust emissions from cattle feedlot and dairy operations.
Approach: In a previous ARB technical summary1, cattle feedlot and
dairy emission factors were discussed, and emissions calculated. This initial summary was used as a basis for a discussion with regulators, researchers, and industry representatives2 to help identify the most appropriate PM emission factors for feedlot and dairy cattle.
Data: Only the following three emission factors were included in the
Discussion: It was readily determined that none of the provided emission
factors were satisfactory. The EPA feedlot value is considered very rough and is based on a report from 1977. The researchers from UCD are opposed to using their emissions rate data for emission estimates due to the limited nature of the testing. In selecting emission factors, is important to recognize that the selections are flexible, and as better information becomes available, it will be used to update emission estimates. The selections below are based on current ‘best available science’. Dairy PM Emissions George Bluhm (CDFA), in conversations with Texas A&M University, discovered that researchers there are completing a dairy PM sampling study in which 220 samples were taken at a 2000 head freestall dairy with lagoons. Some additional analysis is needed to finalize an emissions rate, but the initial estimate shows 5 lbs PM10/1000 head/day, which is substantially lower than the other available dairy emission factor (i.e., 90 from UCD).
DRAFT – Stakeholder Use Only / Do Not Release 8/30/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Because of the robustness of the testing and similarities between Texas and California dairy operations, it was agreed by the group to initially use the value of 5 lbs for the dairy PM10 emission estimates. However, in a subsequent conversation with Frank Mitloehner (UCD), he suggested that this number seems to be rather low. At present, the group agreed that the available Texas A&M emission factor be used for the initial dairy PM10 emission estimates for the SIP. George has agreed to work with Texas A&M to get the necessary information. There are two important ramifications to this decision: 1) If the low emission factor is used, any controls applied will have a lower emission reduction benefit; 2) Based on Frank’s comments, it is possible that additional testing will show higher emissions, requiring an increase in future emission inventory estimates. Feedlot PM Emissions George has also agreed to check with Texas regarding information they may have on feedlot PM emissions. Therefore, a decision was not yet made regarding emission factor use. As a placeholder, the ARB will use the UCD value of 29 lbs PM10/1000 head/day. This will be used for initial scoping estimates while additional information is being obtained.
Conclusions: At this time, a PM10 emission factor of approximately
5 lbs PM10/1000 head/day will be used for dairy operations. This is based on 220 dairy tests performed at Texas A&M. For feedlots, a value of 29 lbs PM10/1000 head/day will be used, which is based on 26 tests by UCD. Although far from perfect, these values are based on more recent and more comprehensive testing than the current EPA default feedlot emission factor of 135. Of course, as additional information becomes available, it will be used to update the emission estimates. An important next step in incorporating these emission factors into the PM10 SIP will be to discuss them with EPA and environmental groups.
References: 1Initial Scoping Estimates of PM10 Emissions from Beef and Dairy
Operations, P. Gaffney, California Air Resources Board, 8/13/2002
DRAFT – Stakeholder Use Only / Do Not Release 8/30/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
2Teleconference 8/29/2002. Dave Jones (SJVUAPCD), Patia Siong (SJVUAPCD), Stephen Shaw (SJVUAPCD), Terry Cassel (UCD), Paul Martin (Western United Dairymen), Roger Isom (California Cotton Ginners and Growers Association), Cynthia Corey (California Farm Bureau), Gene Beach (Almond Hullers and Processors Association), George Bluhm (CDFA), Matt Summers (CDFA), Patrick Gaffney (ARB). Also, Frank Mitloehner in separate conversation with P. Gaffney. 3Compilation of Air Pollutant Emission Factors, Volume 1, Fourth Edition, AP-42. U.S. EPA, September 1985. Section 6.15 Beef Cattle Feedlots, Table 6.15-1. 4Sources and Sinks of PM10 in the San Joaquin Valley, Interim Report. Flocchini, R.G., James, T.A., et. al., August 10, 2002. Air Quality Group, Crocker Nuclear Laboratory, University of California, Davis. Table 6.1.
Contact: Patrick Gaffney, Air Resources Board [email protected] (916) 322-7303 August 30, 2002
DRAFT – Internal Use Only – Do Not Release 8/13/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
Initial Scoping Estimates of PM10 Emissions from Beef and Dairy Operations Objectives: Perform a rough estimate of the PM10 emissions from beef
and dairy operations in the SJV. Compare estimates using various available emission factors. The results will only be used to provide an approximation of the potential significance of the emissions.
Method and Data:
The method consists of multiplying the number of animals by available emission factors. To expedite the calculations, existing ARB beef and dairy cattle populations computed for 1996 were used. Emission factors used are the historical feedlot emission factor from EPA1, and recent estimates by UC Davis2. In addition, various scenarios were evaluated in which emission factors were reduced in attempts to more realistically represent dairy emissions.
Results: Table 1 shows the estimated emissions first using the EPA
emission factor, which is 135 lbs PM10 per 1000 head per day. As a ‘what-if’ scenario, emissions were also computed assuming that dairy emissions are 50% of the livestock emissions. Using the UC Davis emission factors, which are 90 lbs PM10/1000 head/day for dairies, and 29 lbs PM10/1000 head/day for feedlots, three emission scenarios were run. The first scenario uses the emission factors as published, the second uses the beef emission factor for all animals, and the third scenario uses one-half of the beef emission factor for dairies, while using the beef factor for beef animals. Table 1. Beef and Dairy PM10 Rough Estimates
Emissions
(tons PM10/day) Beef Dairy Total SJV 1996 Population 453,527 1,783,959 2,237,486 EPA EF Emissions 30.6 120.3 151 EPA EF w/50% dairy 30.6 60.2 91 UCD EF Emissions 6.5 80.7 87 UCD, Beef EF for all 6.5 25.8 32 UCD, Beef EF w/50% dairy 6.5 12.9 19
DRAFT – Internal Use Only – Do Not Release 8/13/2002
Preliminary Analysis Only DRAFT Do Not Cite or Quote
For comparison, Table 2 shows the emissions from various
sources included in the 2001 emissions inventory. Even based on the lowest emission estimates for beef and dairy, the emissions are large enough to warrant additional analysis and refinement of the estimates. Table 2. PM10 Annual Emission Estimates for 2001
Comparison Emissions PM10 (tons/day) Beef & Dairy (very preliminary) 19 - 91 Fireplaces & Woodstoves 12 Land Preparation & Harvest 111 Construction 66 Paved Road Dust 115 Unpaved Road Dust 51 Prescribed & Ag Burning 40 All Mobile Sources 16 All Stationary Sources 27 Total All Sources 167
Conclusions: Based on this rough approximation of PM10 emissions from
dairies and feedlots in the San Joaquin Valley, it appears that further refinement of these emissions estimates are warranted. The most important information that is needed is credible and representative emission factor information. The EPA feedlot emission factor is based on limited testing performed in 1977. The UC Davis emission factors are based on testing performed in the San Joaquin Valley, but it is counterintuitive that the measured feedlot emissions are substantially smaller than the dairy emissions. This possible discrepancy needs to be resolved In addition, other sources of emission factors may be available which should be investigated, such as from work performed at Texas A&M University.
References: 1Compilation of Air Pollutant Emission Factors, Volume 1, Fourth
Edition, AP-42. U.S. EPA, September 1985. Section 6.15 Beef Cattle Feedlots, Table 6.15-1. 2Sources and Sinks of PM10 in the San Joaquin Valley, Interim Report. Flocchini, R.G., James, T.A., et. al., August 10, 2002. Air Quality Group, Crocker Nuclear Laboratory, University of California, Davis. Table 6.1.
Contact: Patrick Gaffney, Air Resources Board [email protected] (916) 322-7303
DRAFT
7.5-1
SECTION 7.5 AGRICULTURAL HARVEST OPERATIONS
(Revised January 2003)
METHODS AND SOURCES The activities used to harvest agricultural commodities entrain soil and plant material into the air. These emissions may simply be due to the vehicles traveling over the soil, or via the mechanical processing of the plant material and underlying soil, or, as in the case of almonds, via the actual blowing or sweeping of the crop to remove waste materials and position it for pickup. Although at the time of this update, harvest particulate matter emission factors measured in California are only available for cotton, almonds, and wheat, all other crops are assigned emission factor by scaling from these measured emission factors. The attached Table 1 shows the total particulate matter and PM10 fraction of the harvest emissions estimates for these crops. As additional measured harvest emission factors for more crops are available, they will be incorporated into this methodology. Particulate emissions from harvest operations are computed by multiplying an emission factor by an activity factor. Agricultural harvest particulate dust emissions are estimated for all crops in each county in California using the following equation:
Emissionscrop = Emission Factorcrop x Acres Harvestedcrop
The individual crop emissions for each county are summed to produce the county and statewide total particulate matter and PM10 fraction of the harvest emission estimates. For harvesting, the emission factors are based on measurements performed by UC Davis 1, and harvested acreage is based on 2000 summary data from the California Department of Food and Agriculture (CDFA) 2. The remainder of this section discusses the emission factors and acreage in more detail. Emission Factor. The emission factors used to estimate the PM10 dust emissions from agricultural harvesting are from a study performed by UC Davis 1 under contract to the USDA and their subsequent supplementary data analysis 3. PM10 emissions were measured during 1994 to 1998 harvest operations. The emission factors are shown below in Table A. Using the available emission factors as a baseline, harvest emission factors were approximated for other California crops in consultation with agricultural experts.
The emission rate assumptions were assigned to reflect the relative geologic PM10 generation potential of various harvest practices. Table B below provides examples of some of the emission factor assignments. Assumptions for all crops are provided in the attached Table 2.
Table B. Example Harvest Emission Factor Assumptions Crop Assumption
Harvest Emission
Factor (lbs PM10/acre)
Cotton Cotton 3.4 Vine Cotton/20 0.17 Tomato Cotton/20 0.17 Fruit Trees Cotton/40 0.085 Corn Wheat/2 2.8 Alfalfa Zero 0.0 Walnuts Almonds 40.8 Sugar beets, onions, potatoes Cotton/2 2.7
Unlike the soil preparations activities (e.g., discing, tilling, etc.) harvest operations tend to be fairly unique for each crop. Because of this, harvest emission factors generally combine all of the operations that go into harvesting a commodity into a single factor that includes emissions from all of the relevant operations. Because of this, acre-passes, which are used in estimating emissions from soil preparation operations, are not needed for harvesting. Although the UCD study shows trends in PM10 emission factors with environmental conditions such as relative humidity and soil moisture, the incorporation of environmental factors are still under exploration. If it is needed and there is an appropriate way to incorporate the environmental factor effects in the future, this methodology will be updated. The UC Davis researchers directly measured PM10 emissions. Because the ARB’s databases store TSP (total suspended particulate) emissions, in order to get TSP, the PM10 emissions are multiplied by 2.2, which is the ARB’s soil size speciation value for agricultural tilling dust.
DRAFT
7.5-3
Acres. The acreage data used for estimating harvest emissions are from the California Department of Food and Agriculture’s (CDFA) summary of crop acreage harvested in 2000. The acreage data, compiled from individual county agricultural commissioner reports, were subdivided by county and crop type for the entire state. Complete listings of individual county crop acreage are provided in the land preparation background document. Crop Calendar. Harvesting is performed at very specific times each year, so crop calendar data, which tells when harvest activities occur, is important. To get the best estimates possible, staff of the ARB met with producers of the various commodities to gather the most realistic and current information available on when harvesting occurs. Focusing on the largest acreage crops, we were able to gather updated information for about 90% of California’s crop acreage. For the crops that were not explicitly updated, we either applied an updated crop profile from a similar crop, or used one of the existing ARB profiles. Using these data, we created detailed temporal profiles that help to indicate when PM emissions from harvesting may be highest. The background document for soil preparation operations includes detailed calendars for each crop. ASSUMPTIONS 1. The current harvest emission factors assume that for each crop, harvesting produces the same
level emissions under all conditions for all equipment. 2. The emission factors for crops other than almonds, cotton, and wheat were assigned to reflect
the relative geologic PM10 generation potential of various harvest practices. 3. Crop calendar data collected for San Joaquin Valley crops and practices were extrapolated to
the same crops in the remainder of the state. TEMPORAL ACTIVITY Temporal activity for harvesting is derived by summing, for each county, the monthly emissions from all crops. For each crop, the monthly emissions were calculated based on its monthly profile, which reflects the percentage of harvesting activities occurs in that month. Below is an example of the monthly profile for almonds, cotton, and wheat. Because the crop composite differs by county, the monthly profiles for each county are different from each other. An example of some composite county monthly profiles is shown below in Tables C-1 through C-3. Table 3 lists the composite temporal data for each county. The background document provides details on how the monthly temporal profiles were developed. Table C-1. Temporal profile
CES Hours Days Weeks 47332 24 7 52
Table C-2. Monthly Profile of Crops Crops JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DECAlmonds 0 0 0 0 0 0 0 0 50 50 0 0 Cotton 0 0 0 0 0 0 0 0 0 50 50 0 Wheat 0 0 0 0 0 50 50 0 0 0 0 0 Table C-3. County Harvest Profile Composite County JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DECFresno 0.1 0.1 0.2 0.2 0.1 5.6 5.9 0.8 30.7 42.8 13.6 0.1
DRAFT
7.5-4
COMMENTS AND RECOMMENDATIONS The scaling approach used to assign the three available PM emission factors to the dozens of California crops is highly subjective. Initial scaling assignments were made by ARB staff, then they were refined by members of the agricultural community. Members of the SJV Agricultural Technical Advisory Group concluded that it was more realistic at this time to include rough approximations of PM harvest emissions than to set the values to zero, as has been done historically. As additional harvest emissions data are collected, they will be incorporated into the methodology and the emissions estimates will be recalculated. CHANGES IN METHOD AND EMISSION ESTIMATES There were significant improvements to the land preparation emissions estimates for this update. These include: • Incorporation of new crop specific emission factors; • Approximating emission factors for all crops by scaling measured emission factors. • Use of updated 2000 crop acreage data from the California Department of Food and
Agriculture. These changes produced an estimated emissions increase of about 80% from the previous 1993 emission inventory estimates for agricultural harvest operations. The change was predominately due to increases in the base emission factors, and the inclusion of all harvested crops, many of which were previously set to zero emissions. SUGGESTED GROWTH SURROGATES Growth in this category is based on the crop acreage projection estimated by the Department of Water Resources. The growth varies by regions. SAMPLE CALCULATIONS To estimate PM10 emissions from agricultural harvest operations, the following method is used: Step 1: Acreage. The acres harvested for a few of the crops in Fresno county are shown in the
‘Acres’ column of the table. These data are available from the county agricultural commissioner annual reports or the CDFA. The 2000 acreage data are summarized in the agricultural land preparation background document.
Step 2: Crop specified Emission Factor. Using the data in Table 2, assign the appropriate
emission factor for each crop.
DRAFT
7.5-5
Step 3: Calculate Crop PM10 emissions. Multiply the acres for each crop by the appropriate
emission factor, then divide by 2000 lbs/ton to compute annual tons of PM10 emissions. Emissions = (Acres x Emission Factor) / 2000
Step 4: County total emissions. Sum the emissions for each crop to compute the total available
PM10 emissions from harvest operations.
Table D. Estimating Harvest Operation Emissions in Fresno County
Crop Acres Emission Factor (lbs PM10/acre)
PM10 Emissions (tons PM10/yr)
Almonds All 57350 40.77 1169.1 Barley Feed 4100 5.8 11.9 … … … … Total 1189319 2088.7
REFERENCES 1. Flocchini, R.G., James, T.A., et al. Sources and Sinks of PM10 in the San Joaquin
Valley (Interim Report), a study for United States Department of Agriculture Special Research Grants Program. Contract Nos. 94-33825-0383 and 98-38825-6063. August 10, 2001.
2. California Agricultural Statistics Service. 2000 acreage extracted from agricultural
commissioner’s reports. Sacramento, CA. 3. Terry Cassel. Informal write-up for SJV Ag Tech Committee, Evaluation of ARB
application of UCD emission factors, July 12, 2002. 4. Gaffney, P.H. Methodology for Assigning PM10 Emission Factors for California
Agriculture Harvest Activities, Memorandum to SJV PM10 SIP Emission Inventory Group. December 2002.
METHODS AND SOURCES The land preparation source category includes estimates of the airborne soil particulate emissions produced during the preparation of agricultural lands for planting and after-harvest activities. Operations included in this methodology are discing, shaping, chiseling, leveling, and other mechanical operations used to prepare the soil. Dust emissions are produced by the mechanical disturbance of the soil by the implement used and the tractor pulling it. Soil preparation activities tend to be performed in the early spring and fall months. Table 1 shows the estimated soil preparation particulate emissions for each California county. Particulate emissions from land preparation are computed by multiplying a crop specific emission factor by an activity factor. The crop specific emission factors are calculated using operation specific (i.e., discing or chiseling) emission factors developed by UC Davis researchers1, which are combined with the number of operations provided in the crop calendars. The activity factor is based on the harvested acreage of each crop for each county in the state. In addition, acre-passes are computed, which are the number of passes per acre that are typically needed to prepare a field for planting a particular crop. By combining the crop acreage and the operation specific emission factor, we estimate the particulate matter produced by agricultural land preparation operations. The particulate dust emissions from agricultural land preparation are estimated for each crop in each county in California using the following equation.
cropcropcrop Acres FactorEmissionEmissions ×= The crop emissions for each county are summed to produce the county and statewide particulate matter (PM) and PM10 emission estimates. The remainder of this section discusses each component of and related to the above equation. Acres. The acreage data used for estimating land preparation emissions are from the California Department of Food and Agriculture’s (CDFA) summary of crop acreage harvested in 2000.
The acreage data are subdivided by county and crop type for the entire state, and are compiled from individual county agricultural commissioner reports. Acres for more than 200 crop commodities were reported by CDFA. Complete listings of individual county crop acreage are provided in the land preparation background document. Crop Calendars & Acre-Passes. Acre-passes are the total number of passes typically performed to prepare land for planting during a year. Acre-passes are used in computing crop specific emission factors for land preparation. These land preparation operations may occur following harvest or closer to planting, and can include discing, tilling, land leveling, and other operations. Each crop is different in the type of soil operations performed and when they occur. To get the best estimates available, staff of the ARB met with producers of the various commodities to gather the most realistic and current information available on agricultural practices. Focusing on the largest acreage crops, we were able to gather updated information for about 90 percent of California’s crop acreage. For the crops that were not explicitly updated, we either applied an updated crop profile from a similar crop, or used one of the existing ARB profiles. Table 2.a provides a listing of the land preparation operations of all crop profiles and their emission factors used in California. For updating acre-pass data, we also collected specific information on when agricultural operations occur. Using these data, it was possible to create detailed temporal profiles that help to indicate when PM emissions from land preparations may be highest. The more detailed background document includes detailed crop calendars for each crop with updated information. For all the acre-pass and crop calendar information, the farmers and other agricultural experts of the San Joaquin Valley were instrumental in helping us to update our crop information. The crop calendar consists of twenty representative crop profiles. To make better emission estimates for the over 200 crop commodities reported by CDFA, we assigned each crop to the profile with the highest similarity. The complete listings of individual crop commodities and the assigned profiles are provided in Table 3. Emission factor. The operation specific emission factors used to estimate the crop specific emission factor for agricultural land preparations were initially from a report of University of California at Davis and their subsequent supplementary data analysis 4. After discussions with regulators, researchers, and industry representatives, the emission factors were adjusted based on a combination of scientific applicability, general experience and observations. The initial emission factors were developed based on 1995-1998 test data measured in cotton and wheat fields in California. The operations tested include root cutting, discing, ripping and subsoiling, land planing and floating, and weeding, which are summarized in Table A below.
Table A. Land Preparation Operation Emission Factor Land Preparation Operations
Emission Factor (lbs PM10/acre-pass)
Root cutting 0.3 Discing, Tilling, Chiseling
1.2
Ripping, Subsoiling 4.6 Land Planing & Floating 12.5 Weeding 0.8
DRAFT
7.4-3
There are more than thirty different land preparation operations commonly used in California. With five emission factors available, the other operations were assigned “best-fit” factors based on similar potential emission levels. The assignment of emission factors for operations was based on the expertise and experience of regulators, researchers, and industry representatives. The complete list of land preparation operations and the assigned operation categories are provided in Table 2.b. For each crop, the emission factor is the sum of acre-pass weighted emission factor for each land preparation operation. Table 2.a provides the emission factors for each representative crops in the crop calendar. The figure below illustrates the entire emissions estimation process. ASSUMPTIONS 1. The land preparation emission factors for discing, tilling, etc., are assumed to produce the
same level of emissions, regardless of the crop type. 2. The land preparation emission factors do not change geographically for counties. 3. A limited number of emission factors are assigned to all land preparation activities. 4. Crop calendar data collected for San Joaquin crops and practices were extrapolated to the
same crops in the remainder of the State. Existing crop profiles were used for the small percentage of crops in which update information was not collected.
5. In addition to the activites provided in the crop calenders, it is also assumed that field and
row crop acreage receive a land planing pass once every five years. 6. UC Davis directly measured PM10 emissions. To compute TSP emissions, multiply the PM10
by 2.22, which is the ARB’s soil size speciation value for agricultural tilling dust. TEMPORAL ACTIVITY Temporal activity for harvesting is derived by summing, for each county, the monthly emissions from all crops. For each crop, the monthly emissions were calculated based on its monthly crop calendar profile, which reflects the percentage of harvesting activities that occurs in that month. Below is an example of the monthly profile for almonds, cotton, and wheat. Because the crop composite differs by county, the monthly profiles for counties are different. An example of
Operation specific Emission Factors (EF_opt)
Crop Calendar (Number of Passes)
Crop specific Emission Factor (EF_crop)
Crop specific Acres
Crop specific Emissions
Σ(EF_opt x Passes)
EF_crop x Acres
DRAFT
7.4-4
some composite county monthly profiles is shown below in Tables B-1 through B-3. Table 3 lists the composite temporal data for every county. The background document provides details on how the monthly temporal profiles were developed. Table B-1. Temporal Profiles
CES Hours Days Weeks 47332 24 7 52
Table B-2. Monthly Activity Profile of Selected Crops
Crops JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Almonds 0 0 0 0 0 0 0 0 0 0 50 50 Cotton 0 9 9 0 0 0 0 0 0 0 41 41 Grapes-wine 0 0 0 4 16 16 12 12 12 28 0 0 Table B.3 County Harvest Profile Composite
County JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Fresno 3 6 6 2 2 1 3 4 2 12 30 29 COMMENTS AND RECOMMENDATIONS Studies are ongoing by the University of California, Davis, to analyze field test data from 70 to 90 additional land preparation tests. As the UCD results become available, they will be incorporated to the emission estimation methodology. If possible, future updates could include county specific crop calendars and crop-pass information instead of being based on San Joaquin Valley practices. CHANGES IN METHOD AND EMISSION ESTIMATES There were significant improvements to the land preparation emissions estimates for this update. These include: • Incorporation of new operation specific land preparation emission factors; • Development of new crop specific emission factors; • Use of updated 2000 crop acreage data from the California Department of Food and
Agriculture. These changes produced an emissions reduction of about 50% from the previous 1997 published emission inventory estimates for agricultural land preparation. SUGGESTED GROWTH SURROGATES Growth in this category is based on the crop acreage projection estimated by the Department of Water Resources. The growth varies by regions. SAMPLE CALCULATIONS
DRAFT
7.4-5
The instructions and table below summarizes the data computations necessary to estimate the PM10 emissions from agricultural land preparations in Fresno county. The following steps are performed: Step 1: Crop Acreage. The acres harvested for a few of the crops in Fresno county are shown in
the ‘Acres’ column of the table. These data are available from the county agricultural commissioner annual reports or the CDFA. The 2000 acreage data are summarized in the agricultural tilling background document.
Step 2: Insert emission Factor for Crop. Using the crop profile in Table 2.a to get the appropriate
crop emission factor. Step 3: Compute Crop Emissions. Multiply the annual harvested acreage for each crop by the
emission factor and divide by 2000 lbs/ton to get the annual PM10 emissions. Emissions = (Acres x Emission Factor) / 2000
Step 4: Compute County Total Emissions. Sum the crop PM10 emissions for each county to
compute the total county agricultural soil preparation particulate matter emissions. Step 5: Compute TSP. Divide the PM10 emissions by a factor of 0.4543.
Table C. Estimating Agricultural Land Preparation PM10 Emissions in Fresno County
Crop Crop Profile Acres
Emission Factor
(lbs PM10/acre)
PM10 Emissions
(tons/yr)
TSP Emissions
(tons/yr) Wheat all Wheat 69500 3.7 128.6 235.8 Rice Milling Rice 6160 20 61.6 113.0 Cotton lint pima Cotton 33400 8.9 148.6 272.6 Apples All Citrus 3205 0.07 0.1 0.2 Etc… … … … … Total … … … …
REFERENCES 1. Flocchini, R.G., James, T.A., et al. Sources and Sinks of PM10 in the San Joaquin
Valley (Interim Report), a study for United States Department of Agriculture Special Research Grants Program. Contract Nos. 94-33825-0383 and 98-38825-6063. August 10, 2001.
2. California Agricultural Statistics Service. 2000 acreage extracted from agricultural
commissioner’s reports. Sacramento, CA. 3. Gaffney, P.H., Yu, H. Agricultural Harvest: Geologic Particulate Matter Emission
Estimates, Background Document. California Air Resources Board. December 2002. 4. Terry Cassel, Informal write-up for SJV Ag Tech Committee, Evaluation of ARB
application of UCD emission factors, July 12, 2002.
DRAFT
7.4-6
UPDATED BY Hong Yu, Patrick Gaffney January 2003
DRAFT
7.4-7
TABLE 1 2000 Agricultural Land Preparation PM10 and TSP Emissions
STATE TOTAL 9,374,598 26,766,332 29,499.9 64,934.9 Fraction of PM10 = 0.45 (PM10 Emissions = TSP x 0.4543)
DRAFT
7.4-8
TABLE 2.a Summary of Crop Profile, Acre-Pass, and Emission Factor
Crop profile Land Preparation Operations Category Acre-Pass Emission Factor
Operation (lbs/Acre-pass)
Crop (lbs/Acre/year)
Alfalfa Unspecified Discing 1.25 1.2 Land Maintenance Land Planing 0.2 12.5 4Almonds Float Land Planing 0.25 12.5 3.13Citrus Unspecified Discing 0.06 1.2 0.07Corn List & Fertilize Weeding 1 0.8 Mulch Beds Discing 1 1.2 Finish Disc Discing 1 1.2 Land Maintenance Land Planing 0.2 12.5 Stubble Disc Discing 1 1.2 6.9Cotton Land Preparation Discing 4 1.2 Land Maintenance Land Planing 0.2 12.5 Seed Bed Preparation Weeding 2 0.8 8.9DryBeans Land Maintenance Land Planing 0.2 12.5 Chisel Discing 1 1.2 Shaping Weeding 1 0.8 Disc Discing 2 1.2 Listing Weeding 1 0.8 7.7Garbanzo Chisel Discing 1 1.2 Listing Weeding 1 0.8 Shaping Weeding 1 0.8 Disc Discing 2 1.2 Land Maintenance Land Planing 0.2 12.5 7.7Garlic Land Maintenance Land Planing 0.2 12.5 Disc & Roll Discing 1 1.2 Chisel Discing 1 1.2 List Weeding 1 0.8 Shape Beds Weeding 1 0.8 6.5Grapes-Raisin Terrace Weeding 1 0.8 Spring Tooth Weeding 0.2 0.8 Subsoil Ripping 0.05 4.6 Disc & Furrow-out Discing 1 1.2 Level (new vineyard) Land Planing 0.02 12.5 2.6Grapes-Table Subsoil Ripping 0.05 4.6 Disc & Furrow-out Discing 0.5 1.2 0.83Grapes-Wine Level (new vineyard) Land Planing 0.02 12.5 Spring Tooth Weeding 0.2 0.8 Subsoil Ripping 0.05 4.6 Disc & Furrow-out Discing 0.75 1.2 1.5Lettuce* Land Maintenance Land Planing 0.2 12.5 Disc & Roll Discing 2/2 1.2 Chisel Discing 2/2 1.2 List Weeding 2/2 0.8 Plane Land Planing ½ 12.5 Shape Beds & Roll Weeding 2/2 0.8 12.75Melon Plow Discing 1 1.2 Shape Beds Weeding 1 0.8 Land Maintenance Land Planing 0.2 12.5 Disc Discing 1 1.2 5.7No Land Prep. Unspecified Discing 0 1.2 0Onions List Weeding 1 0.8 Shape Beds Weeding 1 0.8 Land Maintenance Land Planing 0.2 12.5 Chisel Discing 1 1.2 Disc & Roll Discing 1 1.2 6.5Rice Chisel Discing 1 1.2 Land Maintenance Land Planing 0.2 12.5 Post Burn/Harvest Disc Discing 0.5 1.2 Roll Weeding 1 0.8 3 Wheel Plane Land Planing 1 12.5 Harrow Disc Discing 1 1.2 Stubble Disc Discing 1 1.2 20Safflower List Weeding 1 0.8 Land Maintenance Land Planing 0.2 12.5 Stubble Disc Discing 1 1.2 4.5
DRAFT
7.4-9
Crop profile Land Preparation Operations Category Acre-Pass Emission Factor Operation
(lbs/Acre-pass) Crop
(lbs/Acre/year) Sugar Beets Disc Discing 1 1.2 Land Plane Land Planing 1 12.5 Subsoil-deep chisel Ripping 1 4.6 Stubble Disc Discing 1 1.2 List Weeding 1 0.8 Land Maintenance Land Planing 0.2 12.5 22.8Tomatoes Bed Preparatin Weeding 2 0.8 Land Preparation Discing 5 1.2 Land Maintenance Land Planing 0.2 12.5 10.1Vegetables Land Maintenance Land Planing 0.2 12.5 Unspecified Discing 5 1.2 8.5Wheat Stubble Disc Discing 1 1.2 Land Maintenance Land Planing 0.2 12.5 3.7
* Lettuce profile acre-passes are divided by 2 except for land maintenance operation to remove double cropping count because double cropping is accounted for in the 'Harvested Acres' in the emission calculations. (e.g., if the same land is harvested twice in the same year, the same acreage is counted twice in the county Ag. commissioner crop reports)
TABLE 2.b Summary of Land Preparation Operations and Assigned Operation Categories
Operation Category Emission Factor
(lbs/Acre-pass)Chisel Discing 1.2 Disc Discing 1.2 Disc & Furrow-out Discing 1.2 Disc & Roll Discing 1.2 Finish Disc Discing 1.2 Harrow Disc Discing 1.2 Land Preparation Discing 1.2 Mulch Beds Discing 1.2 Plow Discing 1.2 Post Burn/Harvest Disc Discing 1.2 Stubble Disc Discing 1.2 Unspecified Discing 1.2 3 Wheel Plane Land Planing 12.5 Float Land Planing 12.5 Land Plane Land Planing 12.5 Laser Level Land Planing 12.5 Level Land Planing 12.5 Level (new vineyard) Land Planing 12.5 Plane Land Planing 12.5 Land Maintenance Land Planing 12.5 Subsoil Ripping 4.6 Subsoil-deep chisel Ripping 4.6 Bed Preparatin Weeding 0.8 List Weeding 0.8 List & Fertilize Weeding 0.8 Listing Weeding 0.8 Roll Weeding 0.8 Seed Bed Preparation Weeding 0.8 Shape Beds Weeding 0.8 Shape Beds & Roll Weeding 0.8 Shaping Weeding 0.8 Spring Tooth Weeding 0.8 Terrace Weeding 0.8 Sulfur Dusting None 0
DRAFT
7.4-10
TABLE 3 Summary of CDFA Commodity and Assigned Crop Profile
CDFA Commodity
Code CDFA Crop Name Crop Profile Used Emission Factor
Code Commodity VMT/acre/year ReportedGR Grapes (All) 0.38 15 VMT/40 acres/yearCI Citrus 1.23 98 VMT/80 acres/yearTR Tree Fruit 1.24 62 VMT/50 acres/yearTF Tree & Citrus Fruit 1.23 Average of Citrus & Tree FruitNC Nut Crops 0.49 37 VMT/75 acres/yearCL Cotton (large) 0.40 64 VMT/160 acres/yearCS Cotton (small) 2.40 156 VMT/65 acres/yearEX Existing ARB 4.38 175 VMT/40 acres/yearZE Zero 0 0
Notes:
VMT data were provided by growers and compiled by Sierra research for the highlighted rows.
Assignment of VMT to CropsAssign Cotton (large) to crops assumed to typically be large acreagesAssign Cotton (small) to crops assumed to typically be small acreages and vegetablesAssign Citrus & Tree Fruit to all citrus and non-nut fruit trees (the VMT is so similar for these categories that there is no reason to have separate codes)Assign Grapes to wine, table, and raisin grapesAssign Nut Crops to all nut crops
3/6/2003Teleconference with Dave Mitchell, Patia Siong, Jason Baldwin, Manuel Cunha, Karla Fullerton, Roger Isom to get comments on initial assignments and reassign as necessary.
Prepared by:Patrick GaffneyCalifornia Air Resources [email protected] 916-322-7303February 7, 2003
Unpaved Ag1999 Mar_26_2003.xls 1
California Air Resources Board 4/3/2003
Assignment of Unpaved Road VMT Classifications to Commodities
Assignment of Unpaved Road VMT Classifications to Commodities
Commodity Code Crop Description Crop Profile
Harvest Category
VMT Category
VMT Category Description
VMT/acre /year
202999 GRAPEFRUIT, ALL Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23203999 TANGERINES & MANDARINS Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23204999 LEMONS, ALL Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23205999 LIMES, ALL Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23206999 TANGELOS Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23207999 KUMQUATS Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23208059 CITRUS, MISC BY-PROD Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23209999 CITRUS, UNSPECIFIED Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23211999 APPLES, ALL Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23212199 PEACHES, FREESTONE Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23212399 PEACHES, CLINGSTONE Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23212999 PEACHES, UNSPECIFIED Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23213199 CHERRIES, SWEET Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23214199 PEARS, BARLETT Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23214899 PEARS, ASIAN Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23214999 PEARS, UNSPECIFIED Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23215199 PLUMS Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23215399 PLUMCOTS Citrus FF_Cotton/40 TF Tree & Citrus Fruit 1.23215999 PRUNES, DRIED Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23216199 GRAPES, TABLE Grapes-Table VI_Cotton/20 CS Cotton (small) 2.40216299 GRAPES, WINE Grapes-Wine VI_Cotton/20 GR Grapes (All) 0.38216399 GRAPES, RAISIN Grapes-Raisin VI_Cotton/20 GR Grapes (All) 0.38216999 GRAPES, UNSPECIFIED Grapes-Wine VI_Cotton/20 GR Grapes (All) 0.38217999 APRICOTS, ALL Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23218199 NECTARINES Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23218299 PERSIMMONS Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23218399 POMEGRANATES Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23218499 QUINCE Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23218839 CHERIMOYAS Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23218889 ORCHARD BIOMASS Almonds TF_Cotton/40 NC Nut Crops 0.49218899 FRUITS & NUTS, UNSPEC. Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23221999 AVOCADOS, ALL Citrus TF_Cotton/40 TF Tree & Citrus Fruit 1.23224999 DATES Citrus TF_Almonds/20 TF Tree & Citrus Fruit 1.23
Unpaved Ag1999 Mar_26_2003.xls Page 3
California Air Resources Board 4/3/2003
Assignment of Unpaved Road VMT Classifications to Commodities
Assignment of Unpaved Road VMT Classifications to Commodities
Commodity Code Crop Description Crop Profile
Harvest Category
VMT Category
VMT Category Description
VMT/acre /year
393999 HORSERADISH Onions VH_Cotton/40 CS Cotton (small) 2.40394199 SALAD GREENS NEC Lettuce VH_Cotton/40 CS Cotton (small) 2.40394999 PEAS, EDIBLE POD (SNOW) DryBeans VI_Cotton/20 CS Cotton (small) 2.40395999 VEGETABLES, ORIENTAL, ALL Vegetables VH_Cotton/40 CS Cotton (small) 2.40396999 SPROUTS, ALFALFA & BEAN Lettuce VH_Cotton/40 CS Cotton (small) 2.40398199 CUCUMBERS, GREENHOUSE No Land Prep. ZO_Zero/1 ZE Zero 0.00398299 TOMATOES, GREENHOUSE No Land Prep. ZO_Zero/1 ZE Zero 0.00398399 TOMATOES, CHERRY Tomatoes VH_Cotton/40 CS Cotton (small) 2.40398499 TOMATILLO Tomatoes VH_Cotton/40 CS Cotton (small) 2.40398559 CILANTRO Lettuce VH_Cotton/40 CS Cotton (small) 2.40398599 SPICES AND HERBS Lettuce VH_Cotton/40 CS Cotton (small) 2.40398899 VEGETABLES, BABY Vegetables VH_Cotton/40 CS Cotton (small) 2.40398999 VEGETABLES, UNSPECIFIED Vegetables VM_Cotton/20 CS Cotton (small) 2.40
Unpaved Ag1999 Mar_26_2003.xls Page 7
Winston H. Hickox Agency Secretary
California Environmental Protection Agency
Printed on Recycled Paper
Air Resources Board Alan C. Lloyd, Ph.D.
Chairman 1001 I Street • P.O. Box 2815 • Sacramento, California 95812 • www.arb.ca.gov
Gray DavisGovernor
MEMORANDUM
TO: SJV PM10 SIP Emission Inventory Group FROM: Patrick Gaffney DATE: July 31, 2002 SUBJECT: Update and Review of 1999 Paved Road Dust Emissions The draft update calculations for the paved road dust emissions estimates are complete. Now, your help is needed to double check the results and make sure everything makes sense. In addition, some unresolved questions still need to be answered. The major results are provided below, as well as a summary of the major assumptions and some pending questions. For those who are deeply interested in all of this, there is a companion spreadsheet: Paved Road Dust SJV 1999.xls. The spreadsheet provides the updated emissions, and compares the current and updated values for each county and road class. The spreadsheet also includes the summarized raw VMT data, the rainfall correction data, and the emission factors.
Emissions Estimation
Based on initial estimates, the overall emissions for PM10 paved road dust in the SJV decrease by 28% using the updated VMT data and the rainfall data (23,178 to 16,721 tpy PM10). About 23% of the decrease is due the VMT apportioning
changes; the remainder is from the rainfall correction. The overall VMT for the valley shows a 1% decrease from what
is currently in the inventory for 1999. This means that the bulk of the emissions decreases are due to apportioning more of the VMT to freeways than was done previously (which produces fewer emissions per VMT). Kings county is showing a 119% emissions increase due to a
large increase in rural road VMT (726 to 1590 tpy). For the entire valley, the emission changes by road type are:
Provided by Barbara Joy from EarthMatters via email 7/10/2002. Compiled from reports generated by SJV TPAs. Some TPAs provided data as VMT, some as 1000’s VMT;
there are some possible mislabeling problems with the units. The overall VMT only decreased by 1% from values currently in
the emission inventory (29,788 to 29,617 million VMT/year). However, substantially more of the VMT is assigned to the freeways, producing a significant reduction in the emissions estimates. By road type for the entire valley, the VMT changes are:
+74% Freeway, -21% Arterial, -21% Collector, -30% Local, -4% Rural, -1% overall. Based on labeling, Merced provided year 2000 data instead of
1999. Used data as 1999. Is the Kern county data for the full county or just the
SJVUAPCD portion? For San Joaquin County VMT, the road types Rural Local (zero
VMT) and Centroid (5.9% of VMT) were provided. All VMT were assigned to Rural road category. Is this right?
Rainfall Correction
Provided by Shawn Ferreria, SJVUAPCD. Compiled from the Western Regional Climate Center.
Information from multiple sites in each county were averaged for each month. For most sites the data used is based on about 50 years of
averaged data. Monitors beyond the valley floor, at higher elevations, were
excluded. The rainfall adjustment reduced overall paved road dust
emissions by about 5%
Emission Factor
Emission factors are based on the AP-42 EPA methodology using California specific silt loadings. Assumed average vehicle fleet weight of 2.4 tons. Applied rainfall correction factor to reduce emissions based on
the number of days with measurable rain each month
AP-42 Analysis – Paved & Unpaved Road Dust 7/17/02 Paved Road Dust Methodology In September 2001, EPA published a draft updated methodology for estimating emissions from paved road dust. A key change in the methodology is the inclusion of a factor to provide an emission reduction based on precipitation. The precipitation factor is used to alter the base emission factor, and can be applied annually, seasonally, or monthly. The adjustment is of the form: Rainfall Adjustment = Emission Factor * (1 - P/2N) where P = number of days with at least 0.254 mm (0.01 in) of precipitation during the averaging
period and N = number of days in the average period (e.g., 365 for annual, 91 for seasonal, 30 for
monthly) Full EF = k(sL/2)0.65 (W/3)1.5 (1 – P/2N) (K= constant, sL = silt loading, W = average vehicle weight, 2.4 tons assumed) So, 6 wet days would reduce the estimated emissions for the month by 10%. Some issues: If used, recommend a monthly correction factor
- Is there information reasonably available showing the typical number of dry/wet days each month (possibly 10 year average)
- Ideally, would need data for each county The proposed precipitation value of 0.01 seems trivial. Should a higher
number such as 0.1 be used? If so, is the correction factor still valid? Rainfall information can be used to develop seasonal emission profiles
Unpaved Road Dust Methodology EF = [ k (s/12)a (W/3)b / Mdry/0.2)c ] x [(365 – p)/365] S = surface silt content, W = mean vehicle weight, Mdry = worst case surface moisture, p = number og days with at least 0.01 in precipitation per year ARB currently uses an average emission factor derived from UC Davis and DRI studies. Emission factor = 2.0 lbs PM10/mile traveled. Currently,. Some issues: ARB EF does not account for local emission variations, but it is from
California roads Consider application of rainfall correction factor to reduce emissions for
wet days Are averaged county rainfall values reasonably available? Currently annual emissions are apportioned monthly by rainfall profiles,
but emission factors are not adjusted Unpaved road VMT is on an annual basis and emissions are apportioned