# Department of Pesticide Regulation

Mary-Ann Warmerdam
Director 

### M E M O R A N D U M Arnold Schwarzenegger
Governor

1001 I Street • P.O. Box 4015 • Sacramento, California 95812-4015 • www.cdpr.ca.gov

A Department of the California Environmental Protection Agency

Printed on recycled paper, 100% post-consumer--processed chlorine-free. TO: Randy Segawa Environmental Program Manager I Environmental Monitoring Branch

FROM: Bruce Johnson, Ph.D. Original signed by
Research Scientist III Environmental Monitoring Branch
916-324-4106

Frank C. Spurlock, Ph.D. Original signed by
Research Scientist III Environmental Monitoring Branch

DATE: January 23, 2009

SUBJECT: DOMINANT SOIL TYPES ASSOCI ATED WITH FUMIGANT APPLICATIONS

IN OZONE NONATTAINMENT AREAS

Background

The Environmental Monitoring Branch is inves tigating the ability of computer simulation models to describe post-applica tion fumigant fluxes. The primary objective is to simulate total
cumulative volatilization for differe nt application methods and fumi gants for use in the volatile organic compound (VOC) program. The purpose of this memorandum is to document a procedure for determining the dominant soil type s associated with fumi gant use in different regions of California.

Methods

Database operations were perf ormed using Oracle and SAS. Fumi gant use records consisting of pounds of fumigant active ingr edient (A.I.), and acres treate d, county, meridian, township, range, and section were extracted from the 2006 pesticide use report (PUR). Data for 1,3-dichloropropene (1,3-d), methyl bromide, ch loropicrin, metam sodium , and metam potassium were included, and only records for use duri ng the May 1 through October 31, 2006 ozone season were included. Applications were also restrict ed to nonattainment areas (NAAs) as defined by a lookup table of county, meridian, township, range, section (COMTRS) in each NAA created for the VOC calculation program. The five NAAs are S acramento Valley (Sacvalley), San Joaquin Valley (SJV), Southeast Desert (SE_desert), S outh Coast (SoCoast), and Ventura. For each COMTRS, the sum of pounds applied a nd acres treated were determined.

In parallel, the following surface soil informati on was extracted from an existing Oracle table (Troiano.layer99): soil texture cl ass, textural subclass modifier, area of soil class within the
COMTRS and COMTRS area. The soils data in Troiano.layer99 were originally obtained fromRandy Segawa January 23, 2009 Page 2

Soil Conservation Service county soil surveys (Soil Conservati on Service, 1973; Soil Survey Staff, 1997). An additional variable named class_ frac that describes the fraction of soil type
within each COMTRS was created by dividing the acreage of each soil type within a section by the total COMTRS acreage. These sectional soil factors were then merged with the use information by COMTRS, and sections with no fumigant use were di scarded. The Appendix
contains a more detailed se t of notes on these operations.

This resulted in a set of records for each application of each fumi gant in each section containing COMTRS, soil class, fraction by acreage of this soil class within section, NAA, and both pounds of fumigant applied and acres treated during the 2006 ozone s eason. An application within a section would potentially be listed several times, depending on how many soil types were in that section. The pounds applied and acres treated were apportioned over the soil types using class_frac, the fraction of each soil type within th e section. In other words, use within each soil type within a section was indexe d in two ways: (1) the product of class_frac and pounds applied and (2) the product of class_frac and acres treated. An important methodological feature was that
all soils within a section were listed if there was any fumigant use within the section, regardless of whether fumigant use actually occurred on that soil type. The available information does not enable locating individual applications on specific soil types. Thus , strictly speaking, the soil classes determined in this analysis cannot be described as those soils upon which these fumigants were applie d. Rather, these soils represent the dominant soils in sections where fumigants were used.

For each fumigant within each NAA, these weighted use measures were summed by soil class (using Excel pivot table) producing a table of NAA x soil type of pounds applied and acreage treated. Subsequently we decided that pounds applied was the most important index of use and acreage was not in cluded in the write up.

The soil classification sche me in Troiano.layer99 included modifiers such as fine sandy loam and coarse sandy loam. which resulted in 18 classes. In addition, a soil class “unknown” was assigned to sections which did not have soil mapping information. In order to further Soil classes with finer

divisions Broader soil classes (soil textural triangle) CLAY clay CLAYLOAM clayloam
COARSESAND sand COARSESANDYLOAM sandyloam
FINESAND sand FINESANDYLOAM sandyloam
LOAM loam LOAMYCOARSESAND loamysand LOAMYFINESAND loamysand LOAMYSAND loamysand
SAND sand SANDYCLAYLOAM sandyclayloam SANDYLOAM sandyloam
SILTLOAM siltloam SILTYCLAY siltyclay SILTYCLAYLOAM siltyclayloam
UNKNOWN unknown VERYFINESANDYLOAM sandyloam Table 1. Soil class mapping from finer division to
broader divisions. All classes are USDA/SCS soil

classes.Randy Segawa January 23, 2009 Page 3

simplify, these 18 groups were aggregated into 12 soil types, plus unknown (Table 1). These 12 soil types are those listed in the USDA/SCS soil triangle.

Results

The distribution of the five fumigants over th e NAAs was highly uneven (Table 2). The SJV

NAA received the largest total pounds of app lied fumigants, consisting of 5,439,391 pounds. The next largest was Ventura with about one-fifth of SJV at 1,118,998 pounds. The other three NAAs had totals which were smaller than SJV by more than an order of magnitude. Pounds applied in SJV and Ventura comprised 94% of the total pou nds applied. The largest two fumigants were metam sodium and 1,3-d at 3,149,867 and 1,721,848 pounds A.I., respectively. These two fumigants accounted for 70% of the pounds of fumi gants applied in these five NAAs in the 2006 VOC season (May to October).

The fraction of use in each soil type by NAA and fu migant is depicted in Table 3. The first and second highest fractions within ea ch NAA are highlighted by orange and light blue, respectively. Sandy loam dominates the soil types in the SJV ove r all five fumigants. Similarly, in Ventura sandy loam is the highest fraction, except for me tam sodium, where loamy sand is the highest and sandy loam is the second highest. Outside of the Sacvalley, four soil classes appear to dominate the areas where fumigants are used : loam, loamy sand, sand, and sandy loam. In the Sacvalley clay loam, silty clay loam, and silt lo am were amongst the top two soil types present in sections with fumigant applic ations. As discussed previously , the spatial resolution of the fumigant PUR data is only to the section leve l. Consequently, Table 3 does not describe the extent to which fumigants are actually applied to specific soil types, but rather the use-weighted fraction of soil types in sections were fumigants were applied for each NAA. Sacvalley SE_desert SJV SoCoast Ventura Total

Methyl Bromide 300 671 399,589 57,258 310,895 768,713 Chloropicrin 2,401 6,213 100,397 74,444 383,645 567,098
Metam Sodium 38,051 163,340 2,805,682 5,379 137,415 3,149,867 1,3-d 40,042 7,825 1,361,078 25,860 287,043 1,721,848

Metam Potassium 7,742 0 772,645 0 0 780,387

Total 88,535 178,049 5,439,391 162,941 1,118,998 6,987,914 Table 2. Pounds of A.I. applied in NAAs from May through October 2006.Randy Segawa January 23, 2009 Page 4

The representation of four cl asses: loam, loamy sand, sandy lo am, and sand is explicitly presented in Table 4. Generally, fr actions exceeded 0.5. It was not possible to classify soils in some sections and these application pounds were assigned to the unknown soil class. Soil type unknown was prominent in SE_desert for metam sodium, SJV and SoCoast for 1,3-d and SJV for metam potassium (Table 3). Soil Class Sacvalley SE_desert SJV SoCoast Ventura Soil Class Sacvalley SE_desert SJV SoCoast Ventura

clay 0.00 0.00 0.01 0.01 0.00 clay 0.00 0.00 0.00 0.00 0.03 clayloam 0.30 0.00 0.02 0.04 0.01 clayloam 0.20 0.00 0.02 0.03 0.02

loam 0.08 0.00 0.08 0.87 0.09 loam 0.14 0.00 0.09 0.65 0.26 loamysand 0.21 0.00 0.05 0.00 0.02 loamysand 0.00 0.00 0.06 0.10 0.05

sand 0.00 1.00 0.02 0.00 0.02 sand 0.00 0.46 0.08 0.00 0.02 sandyclayloam 0.00 0.00 0.00 0.00 0.00 sandyclayloam 0.00 0.00 0.00 0.00 0.00

sandyloam 0.39 0.00 0.81 0.06 0.58 sandyloam 0.11 0.47 0.65 0.06 0.52

siltloam 0.02 0.00 0.00 0.00 0.00 siltloam 0.20 0.00 0.00 0.04 0.00 siltyclay 0.00 0.00 0.00 0.00 0.00 siltyclay 0.12 0.00 0.00 0.00 0.00 siltyclayloam 0.00 0.00 0.01 0.00 0.28 siltyclayloam 0.23 0.07 0.01 0.07 0.10

unknown 0.00 0.00 0.02 0.03 0.00 unknown 0.00 0.00 0.09 0.04 0.00

Soil Class Sacvalley SE_desert SJV SoCoast Ventura Soil Class Sacvalley SE_desert SJV SoCoast Ventura

clay 0.02 0.06 0.00 0.00 0.01 clay 0.06 0.00 0.04 0.02 0.00 clayloam 0.05 0.08 0.00 0.00 0.01 clayloam 0.00 0.00 0.06 0.01 0.02

loam 0.33 0.01 0.01 0.02 0.03 loam 0.01 0.00 0.07 0.28 0.08 loamysand 0.00 0.01 0.17 0.04 0.55 loamysand 0.00 0.00 0.09 0.01 0.02

sand 0.00 0.00 0.31 0.02 0.05 sand 0.00 0.82 0.04 0.00 0.02 sandyclayloam 0.00 0.01 0.00 0.00 0.00 sandyclayloam 0.00 0.00 0.00 0.00 0.00

sandyloam 0.09 0.42 0.47 0.69 0.21 sandyloam 0.69 0.15 0.51 0.37 0.61

siltloam 0.24 0.01 0.03 0.00 0.14 siltloam 0.15 0.03 0.00 0.00 0.00 siltyclay 0.00 0.00 0.00 0.00 0.00 siltyclay 0.00 0.00 0.00 0.00 0.00 siltyclayloam 0.27 0.00 0.01 0.23 0.00 siltyclayloam 0.09 0.00 0.01 0.14 0.24

unknown 0.00 0.41 0.00 0.00 0.00 unknown 0.00 0.00 0.17 0.16 0.01

Soil Class Sacvalley SJV

clay 0.21 0.02 clayloam 0.00 0.32

loam 0.01 0.02 loamysand 0.00 0.04

sand 0.00 0.04 sandyloam 0.06 0.40

siltloam 0.33 0.00 siltyclay 0.19 0.01 siltyclayloam 0.20 0.00

unknown 0.00 0.15 Metam Potassium Table 3. Fumigant use (pounds of active ingredient applied) expressed as normalized weights within each NAA as distributed over basic soil types based on 2006 PUR restricted to five NAAs and for applications from May through October. The shaded cells represent the highest and second highest soil use weights within each NAA. For example, sandyloam was highest at 0.81 for SJV and loam was second at 0.08.

Methyl Bromide Chloropicrin

Metam Sodium 1,3-dichloropropeneRandy Segawa January 23, 2009 Page 5

Conclusion

The PUR for 2006 was queried for fumigant use within the five NAAs for 2006. The resulting section by section use information was merged with soils information and the dominant soil types within sections associated with fumigant use was quantifie d. Excluding the Sacvalley, four dominant soil types occurred in sections with fumigant use: loam, loamy sand, sandy loam, and
sand. Sacvalley SE_desert SJ V SoCoast V entura Methyl Bromide 0.69 1.00 0.95 0.92 0.72 Chloropicrin 0.25 0.93 0.88 0.81 0.84
Metam Sodium 0.42 0.44 0.96 0.77 0.85 1,3-dichloropropene 0.70 0.97 0.71 0.66 0.72

Metam Potassium 0.07 0.49 Table 4. Summary of fraction of soils in the groups: loam, sandy loam, loamy

sand and loam.Randy Segawa January 23, 2009 Page 6

References

Soil Conservation Service. 1983. National soils handbook. Soil Conservation Service, U.S. Department of Agriculture, U.S. Govt. Print. Off., Washington D.C.

Soil Survey Staff. 1997. Title 430 Nationa l Soil Survey Handbook, Revision Issued December, 1997. National Resources Conserva tion Service, Washington D.C., U.S. Government Printing Office, December 1997.Randy Segawa January 23, 2009 Page 7

APPENDIX

PROCEDURE FOR ESTIMATING FRACTI ONS OF FUMIGANT APPLICATIONS

APPLIED TO DIFFERENT SOIL TEXTURES IN NAAs

1. create 2006 ozone season fumigant use data ( lbs applied, acres_treated ) listed by comtrs, fumigant, and NAA. a. source is PUR (see example SQL query)and then imported into SAS. Unit_treated =’A’ only; chemicals = chloropicrin, methyl bromide, 1,3-d, metam sodium and metam potassium.
b. screen comtrs to include only sections in each NAA using VOC NAA comtrs lookup table, file=new_statewide_AB_NAA.dat

c. create sum_lbs_applied and sum_acre_treated for each comtrs d. dataset created=WORK.FUMI

2. run “import_all_soildata.sas”
a concatenate 92 excel files to create data set WORK.S OIL containing:
ssaid (soil survey number)

musym (soil type) county_cd
ddlat (centroid coord, used in diagnostics, discarded in ouput file) ddlong (centroid coord, used in diagnos tics, discarded in ouput file)

mtrs

co_mtrs (a variable that contains errors , it is discarded and recreated as comtrs in subsequent processing) Total_acres_section (total acres in section) Soil_musym_acres (total acres soil type in section)

3. Create SAS data set called WORK.TEXTURE fr om ASCII data file MUSYM_texture.lst. a. This data file is an SQL download from the ORACLE table Troia no.layer99 (located in ORACLE EMON partition). The ASC II file contains variables ssaid,musym, layernum,

texture and was downloaded taking ONLY layernum =1 (i.e. surface soil).
b. The variable texture is a code describing main textural class (e.g. sand), textural subclass (e.g. coarse sand) and modifier (e.g. gravelly, cobbely etc).

c. create muid from concatenation of ssaid and musymRandy Segawa January 23, 2009 Page 8

4. Run program “get_textureNO_OTHER.sas” a. generates corrected comtrs and muid (concatenation of ssaid and musym – the muid is the actual soil type code used from here on out). b. merge with WORK.FUMI by comtrs iff comtrs is in WORK.FUMI, creating WORK.JOIN. This merge is used only to eliminate comtrs where fumigants are not used in step d below. Actual fumigant PUR data is merged in the last step of this section as
described below. c. assign main textural class from texture in WORK.TEXTURE. This step removes textural class modifiers, creating a variable called class that describes main textural class plus sub_class each muid (e.g. VeryFineSandyLoam, Loam yCoarseSand etc.). Note: all records missing texture are assigned class =‘OTHER’ (this include sections that are missing soil survey data.) Also, nonstandard te xture designations such as “variable” or “fragments” are assigned class =‘OTHER.’ d. merge WORK.JOIN with WORK.TEXTURE by muid ; this retains only soil data from sections where fumigants are actually used and EXCLUDING class =OTHER. Dataset
created = WORK.JOIN2.

e. calculate classfrac (=class fraction) for each class in each comtrs : classfrac = ∑ (acres each class in section)/ ∑ (total acres all cl asses in section). NOTE: as program is currently written, the deno minator is summed excluding class =other). Dataset created =

WORK.CLASSFRAC f. Merge WORK.CLASSFR AC with WORK.FUMI by comtrs (a one to many merge – multiple comtrs listed for each comtrs in WORK.CLASSFRAC). Also note this file contains fumigant use data for comtrs that have no class designation because soil survey data are not available for every comtrs . These comtrs are assigned classfrac =1 and class = ‘.’ (i.e. missing data). EXPORT to EX CEL: file=get_textureNO_OTHER.xls. In EXCEL, assign class = ‘.’ to class =UNKNOWN.