CHARACTERIZING EMISSIONS FROM AGRICULTURAL BURNING IN A PILOT-SCALE REACTOR AND IN THE FIELD PROJECT NUMBER A-04-02 KIRK L. WENDEL, UNIVERSITY OF UTAH DAVID A. WAGNER, UNIVERSITY OF UTAH KERRY E. KELLY, UNIVERSITY OF UTAH GEOFFREY D. SILCOX, UNIVERSITY OF UTAH PORFIRIO CABALLERO MATA, INSTITUTO TECNOLÓGICO Y DE ESTUDIOS

SUPERIORES DE MONTERREY GERARDO MANUEL MEJIA-VELÁSQUEZ, INSTITUTO TECNOLÓGICO Y DE ESTUDIOS

SUPERIORES DE MONTERREY NARRATIVE SUMMARY The burning of agricultural crop residues is of concern due the low combustion efficiency, difficulty in regulation, and the fact that emissions are released at ground level. Concern over the health and environmental effects from crop burning in the U.S.-Mexican boarder region has led to field studies of the emissions. Due to the expense and difficulty of field-testing, laboratory studies are an attractive alternative. Laboratory testing is less expensive, allows more complete analysis, and gives more control of the test environment. A two-level factorial design was chosen for the preliminary pilot-scale experiments. The variables included crop residue loading (kilogram [kg]/meter [m]2), wind speed, and moisture content in the residue. Crop residue was collected from Mexicali, Baja California and El Centro, California, and burned in a pilot-scale facility. Field emission measurements were also performed in El Centro. Emission factors (EF), based on lab testing for the Mexicali and El Centro residues, were determined for carbon dioxide (CO2), carbon monoxide (CO), nitrous oxide (NO), and particulate matter (PM10), and were in the same range as previous field and laboratory measurements. Emission factors for twelve polycyclic aromatic hydrocarbons (PAH) for the El Centro field and lab data were determined by high-pressure liquid chromatography (HPLC). Similar PAH results for residues collected in Mexicali were not obtained because analysis was by gas chromatography/mass spectrometry (GC/MS) and the concentrations were below the detection limits. The field PAH emissions showed fairly consistent patterns with respect to the relative quantities of twelve compounds for all fuels tested. This suggests that PAH might be a suitable marker for identifying agricultural sources of particulate in ambient air samples. The laboratory PAH data showed similar patterns but there was some variation between the field and lab values. The lab and field emission factors for CO are in better agreement than those for PAH.

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CHARACTERIZING EMISSIONS FROM AGRICULTURAL BURNING IN A PILOT-SCALE REACTOR AND IN THE FIELD PROJECT NUMBER A-04-02 KIRK L. WENDEL, UNIVERSITY OF UTAH DAVID A. WAGNER, UNIVERSITY OF UTAH KERRY E. KELLY, UNIVERSITY OF UTAH GEOFFREY D. SILCOX, UNIVERSITY OF UTAH PORFIRIO CABALLERO MATA, INSTITUTO TECNOLÓGICO Y DE ESTUDIOS

SUPERIORES DE MONTERREY GERARDO MANUEL MEJIA-VELÁSQUEZ, INSTITUTO TECNOLÓGICO Y DE ESTUDIOS

SUPERIORES DE MONTERREY INTRODUCTION Advances in science and medicine have led to a greater understanding of the different health effects, including heart disease (Pope et al. 2004, Henneberger et al. 2005) and cancer, which result from products of incomplete combustion. Emissions from the burning of agricultural waste are of particular concern due to the low combustion efficiency of open burning, difficulty in regulation, and the fact that emissions are released at ground level. Large-scale crop burning takes place in the U.S.-Mexican border region. Burning agricultural waste has long been practiced to prepare land for planting, return nutrients to the soil, increase harvests, and control pests. The pollutants that are released into the atmosphere include carbon monoxide (CO), nitrogen oxides (NOx), sulfur oxides (SOx), and particulate matter (PM) consisting primarily of ash, polycyclic aromatic hydrocarbons (PAH), and soot. PAH are a class of compounds that form from incomplete combustion of hydrocarbons. They attach themselves to PM, primarily soot, and can enter the body through inhalation, ingestion, or the skin. They are classified by the U.S. Department of Health and Human Services as “reasonably anticipated as human carcinogens” and are found in several known carcinogens such as coke oven emissions, coal tars, and soot. To better characterize the emissions from agricultural burning, field measurements are often made. Due to the difficulty of these measurements and their uncertainty, laboratory testing is an attractive option. The laboratory setting allows for better control of conditions and more complete characterization of the process. RESEARCH OBJECTIVES The primary objectives of this study were to (1) characterize emission factors from burning agricultural material and (2) compare lab and field data to determine if the laboratory approach could accurately replace field data. Several parameters were examined in the lab including wind speed, crop moisture content, and drop residue density. The experiments have provided useful emission factors for PAH and suggest

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that patterns in the relative concentrations of PAH could be used for source apportionment from agricultural burns. RESEARCH METHODOLOGY/APPROACHES Fuels The residues used in this study included domestic wheat, Mexican wheat, barley, canola, flax, Bermuda grass, Klein grass, and asparagus. Domestic wheat was burned initially as a trial for the test facility and to systematically examine the effects of moisture, wind speed, and density (kilogram [kg]/meter [m]2) as described below. The Mexican wheat, barely, canola, and flax were collected from the Mexicali, Baja California, region in conjunction with a previous Southwest Consortium for Environmental Research and Policy project (A-03-02). A chemical analysis of these crops is given in Table 1. Bermuda grass, Klein grass, and asparagus were sampled and collected in El Centro, California, and their chemical analysis is not available. Laboratory Combustion Facility All of the laboratory testing was done in a steel and glass enclosure referred to as “the Burn Box”. The 16-foot [ft]-by-16-ft-by-14.67-ft (4.9-by-4.9-by-4.17-meters [m]) structure is shown schematically in Figure 1. The biomass was placed on a one-inch [in] (2.54-centimeter [cm]) thick refractory board measuring 3-ft-by-4-ft (0.91-m-by-1.22-m). The board rested on a scale to continuously measure the weight. Typical weight loss data are shown in Figure 2 for domestic wheat. The scale rested on a steel frame that was 8-ft-by-8-ft-by-1.5 ft (2.45-m-by-2.45-m-by-0.46 m) located in the center of the burn box. Twelve removable panels, 20-in-by-32 in (0.51-m-by-0.81 m), were located along the bottom of the box to allow different airflow patterns. Only one panel was removed to achieve a direct air flow across the burning waste. A pitot tube, placed just upwind of the biomass, measured the wind speed. The flowing air was channeled over the burning waste by a 12-ft-by-8-ft (3.7-m-by-2.4-m) sheet metal panel. A fan pulled air through the 14-inch (0.36-m) exhaust duct at the top of the burn box. The flow rate was adjusted using a damper in the duct. The duct contained a pitot tube, a thermocouple, and ports for gas and particulate sampling. Laboratory Burning Technique From 0.55 to 1.65 pounds (lb) of residue was evenly spread over the refractory board to give densities ranging from 0.0512 to 0.153 lb/ft2 (0.25 to 0.75 kg/m2). This range was based on field estimates from Jenkins et al. (1996). The fuel was ignited with a propane torch on the upwind edge and the flame was drawn by the wind across the board. Combustion gases were drawn through the exhaust duct. The fuel was allowed to smolder for 10 to 20 minutes until CO concentrations returned to ambient levels. Laboratory Sampling The gas and particle sampling equipment is shown schematically in Figure 1. Solids were collected on a quartz filter for subsequent analysis using gas chromatography/ mass spectrometry (GC/MS) or high pressure, liquid chromatography (HPLC). A separate particulate sample was analyzed for black carbon (BC). The stream for PM was first passed through an eductor which was looped to a dilution manifold that also

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cooled the gas. A photoacoustic analyzer containing a tuned laser and sensitive microphones determined the amount of BC (Arnott et al. 1999, Arnott, Moosmüller, and Walker 2000). A portion of this particulate stream was also sent to a TSI DusTrak™ to measure the amount of PM10 using a gravimetric impact technique. Finally, a stream was removed from the exhaust duct, cooled to remove moisture, and analyzed for CO2, CO, NO, and O2. No analysis was performed for SO2 because the experiments were becoming too complex to manage. Field Sampling Field studies were performed in cooperation with the Imperial County Air Pollution Control District in El Centro, California. The crops included asparagus, Bermuda grass, and Klein grass. The crops had been harvested and the growers were waiting for permission to burn the stubble to prepare for the next planting. The burns were supervised by the Air Pollution Control District to ensure safety and proper burning conditions. The equipment available for the field sampling included a DusTrak to measure PM10, a TSI IAQ-Calc™ CO/CO2 analyzer, and a filter sampler for collecting particulate. This equipment was assembled on a backpack with a battery as shown in Figure 3. A sampling probe and pump were part of system. The 1.5-m-long, PVC sampling probe was held 12-16 inches above the smoldering residue. The high temperatures occasionally caused the probe to droop. This was corrected by rotating it 180 degrees. Sampling from flaming portions of the fields was not possible due to the extreme temperatures. GC/MS and HPLC Analysis Filter samples collected during the burns were sent to the Instituto Tecnológico y de Estudios Superiores de Monterrey (ITESM) for analysis. The filters were extracted in a soxhlet for 15 hours using dichloromethane as solvent according to EPA Method 3540C. Extracts were concentrated to 1 mL in a rotor evaporator. The extracts were analyzed for semi-volatile organic compounds (SVOC) by GC/MS following EPA Method 8270. Complex mixtures of signals were identified in the extracts that included PAH, fatty acids, hydrocarbons, and small chain oxidized hydrocarbons. Since PAH signals from the GC/MS were small and difficult to quantify, their quantification was by HPLC analysis with a fluorescence detector according to EPA Method 8310. The HPLC was calibrated with a certified standard solution, TCL Polynuclear Aromatic Hydrocarbons Mixture, from Supelco, lot number LB20553. Emission Factor Calculations The results in this study are reported entirely in terms of emission factors (EF). Calculating emission factors involves finding the ratio of the amount of a specified component, such as CO2, that is found in the exhaust gas to the amount of dry fuel consumed in combustion. According to Lemieux et al. (2000) the emission factor of component i is:

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m

tQCEF i

i

⋅⋅= (1)

where

EFi = emission factor [grams [g/kg dry fuel]

Ci = concentration in flue gas [gi/L]

Q = flow rate of combustion gases [L/min]

t = burn time [min]

m = mass of dry fuel [kg]

Because Q is constant and Ci varies with time, the emission factors are actually calculated using

EFi =Q

mCik

k

∑ ∆tk

where ∆t is the sampling interval. Figure 4 shows, for example, how the concentration of CO varies with time. Almost 30 minutes are required for the CO levels to fall to zero. The gas analysis equipment reported concentration measurements in units of ppm; a conversion to grams/liter was performed:

ii

i MWTR

PppmC ⋅

⋅⋅=

610 (2)

where

Ci = concentration [g/L]

ppmi = concentration [ppm by volume]

P = atmospheric pressure [atm]

R = 0.08206

L ⋅ atm

mol ⋅ K

T = temperature [K]

MWi = molecular weight [g/mol]

The pitot tube in the exhaust duct yielded the flue gas velocity (V). The calculation of

volumetric flow rate (Q) was based on the ideal gas law for density (ρ), a plug flow assumption, and the cross-sectional area of the duct (A):

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Q = ρAV

The amount of fuel consumed, m, was measured with the scale. For the laboratory tests, the ash was analyzed by hot foil loss on ignition (HFLOI) to determine the amount of unburned char. About 8% (by weight, wet basis) of the waste remained as ash and the loss on ignition of the ash was typically 40% (by weight, dry basis). Emission factors are also estimated using emission ratios (ER) when the amount of fuel burned is unknown, as it is in the field measurements discussed below. Emission ratios allow the emission factor of a species that is difficult to measure to be estimated from a carbon balance. This method bases the EF of component i on a reference emission factor of another well quantified component j and an ER. Reference emission factors,

EFj,ref , based on laboratory data were used. The following relationships between ER

and EF were used to analyze field data (Lemieux, Lutes, and Santoianni 2004). Note

that concentrations Ci and Cj are both measured in the field.

ERi j =Ci

Cj

(3)

EFi = ERi j ⋅ EFj,ref (4)

where

ERi/j = mass emission ratio of species i with respect to species j, field

C = concentration [g/L], field

EFref = emission factor [g/kg dry fuel], lab

EFi = emission factor, field

For flaming periods, CO2 is most often used as component j. For smoldering periods, CO is more accurate. Factorial Design and Key Variables The Burn Box provided a controlled environment that allowed determination of the effects of loading, wind speed, and moisture on emissions. A two-level factorial design was initially used to determine the main effects of these three variables and their interactions for domestic wheat. The values for each variable are summarized in Table 2 and the two-level design is shown in Tables 3 and 4. Each variable was given a high (+) and a low (-) value for a total of eight tests. The loading and moisture content were chosen based on field levels reported by Jenkins et al. (1996). The high wind speed was low enough to avoid extinguishing the fire. Domestic wheat was chosen for these tests because large amounts were available. Each test was repeated three or four times to determine the average emission factors and to develop statistics.

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The moisture content (wet basis) in the domestic wheat was determined by measuring the weight loss after drying it in an oven. The moisture content at ambient conditions was used as the low value and for the wheat samples this was typically 9%. To increase the moisture content of the wheat straw, it was placed on a rack in a 55 gallon, polyethylene barrel, about eight inches (20 cm) above the bottom. A humidifier was place in the bottom and the residues were mixed every 15 minutes for an hour. PROBLEMS/ISSUES ENCOUNTERED Field sampling of sugar cane burns in Texas were originally part of the experimental plan. The Sugar Cane Growers Association denied permission to sample from their fields. For this reason the field sampling was moved to Southern California (El Centro). The Imperial County Air Pollution Control District was helpful. Analysis of filter samples for PAH, from both field and lab experiments, by GC/MS was unsuccessful. The concentrations of PAH were too low. Subsequent efforts to quantify PAH by HPLC were successful. This suggests that future SCERP efforts to measure PAH in emissions or ambient air should focus on HPLC techniques. A portion of the waste collected in El Centro was not reserved for ultimate and proximate analysis. The analysis is not expected to be significantly different from the domestic and Mexicali samples that are summarized in Table 1. The emission factors for PAH measured in the lab and field differ by as much as a factor of four. There are several possible reasons for this. The cumulative volumes passed through the filters are inaccurate, particularly in the field, because as the filter cake accumulated, air flows rapidly dropped. Additional field measurements would be helpful now that the sensitivity of flow rates to cake thickness is better understood. In addition, the field measurements were based only on the smoldering stage of combustion, whereas the lab measurements included burning and smoldering. RESEARCH FINDINGS Laboratory Results with Domestic Wheat and Factorial Design The factorial design was applied only to laboratory experiments with domestic wheat. The factorial design showed that the emission factors for PM10, CO, and NO were sensitive to loading (kg/m2), moisture, and wind. In what follows, the uncertainties are all standard errors. The average emission factor for PM10 was 7.3 ± 0.5 g/kg dry fuel. Increasing the loading from 0.25 to 0.75 kg/m2 caused an increase by almost 60% to 11.4 ± 1.0 g/kg. An increase in moisture content increased EFPM10 to 11.3 ± 1.0 g/kg dry fuel. Density and moisture also increased the emission factor for CO. The average emission factor of 44.4 ± 0.9 g/kg dry fuel increased with increasing density by 25% to 55.5 ± 1.8 and with increasing moisture by 18% to 52.3 ± 1.8 g/kg. A two-factor interaction was seen when both the density and wind were increased causing EFCO to increase by 11% to 49.5 ± 1.8 g/kg dry fuel. The average EFNO of 0.39 ± 0.05 g/kg dry fuel dropped below

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our detection limit, because of dilution and lower temperatures, when the wind speed was increased to 7 mph. The increases seen in EFPM10 and EFCO due to higher density, wind, and moisture were probably due to less efficient combustion and lower combustion temperature. This was also evident in the lower EFNO since NOx formation decreases with decreasing temperature. Based on these observations, the laboratory tests were performed at intermediate and low values: density of 0.10 lb/ft2 (0.5 kg/m2), wind speed of 4.5 mph (2.0 m/s), and moisture level of nine percent (wet basis). Laboratory Results with Crop Residues Collected in Border Areas The emission factors for CO, CO2, NOx, and PM10 from laboratory tests of the Mexicali and El Centro crops are shown in Tables 5 and 6. These values were calculated using (1). Standard errors are reported for all values. The two sets of data are fairly consistent for EFCO2, EFCO, and EFNO. For asparagus, however, the emission factor for black carbon is over six times that for Bermuda and Klein grasses and the Mexicali crops. This may be due to elevated entrainment of ash and char particles due to the light, lacy nature of asparagus residue and ash. All three of the El Centro crops also had much higher emission factors for PM10 than the Mexicali crops, averaging 7.09 ± 1.48 versus 2.16 ± 0.58 g/kg dry fuel. This may again be due to the lacy nature of the grasses from El Centro. The backpack-mounted IAQ-Calc CO/CO2 analyzer was placed in the burn box to compare emission factors based on the lab and field sampling equipment. Samples for the portable unit were drawn above the burning material at the trailing edge of the wind panel. The results are summarized in Table 7. Using the ERCO/CO2 from (3) and (4) along with an EFCO2 reference of 1029 g/kg dry fuel (average EFCO2 of Mexicali biomass) the average emissions of CO measured by the IAQ-Calc were within the standard error of the average measured by the laboratory equipment. A direct comparison of CO concentrations was not possible because the lab instrument drew its sample from the flue, while the portable unit was operated in a manner that was similar to that in the field. Filter samples from the laboratory burning of El Centro crops were analyzed for PAH using HPLC. Table 8 summarizes the emission factors for the 12 PAH that were detected. Naphthalene, acenaphthylene, acenaphthene, and fluorene were below the limits of detection. These four compounds have the lowest boiling points and may not

have been collected on the filters. The filters had a temperature of approximately 40°C in the lab and field experiments. PAH emission factors were calculated using (1) and ranged from 0.12 – 50 mg/kg dry fuel. Asparagus consistently had higher emission factors than the Klein and Bermuda grasses - as much as 78 times higher for benzo[g,h,i]perylene. The lacy structure of the asparagus residues may have contributed to the high emissions. The emission factors are compared in Figure 5. The three highest PAH for Bermuda and Klein grass were pyrene, fluoranthene, and phenanthrene. Pyrene and fluoranthene were also the

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highest for the asparagus but benzo[b]fluoranthene was five times higher than phenanthrene. Field Results for El Centro Crops The loading (kg/m2) of the crop residue in the El Centro fields was not measured because of the difficulty of obtaining representative samples. For this reason the emission factors for the field experiments were calculated using ERCO/CO2 (from the field measurements) and the average EFCO2 of 1030 g/kg dry fuel from the laboratory studies of Mexicali residues. Table 9 summarizes the Bermuda and Klein grass CO emission factors: 49 ± 16 and 55 ± 7 g/kg dry fuel. These values are close to the laboratory values in Table 6. The EFCO for asparagus was 75 ± 25 g/kg dry, considerably higher than the grasses and also much higher than the EF for asparagus based on lab data. The lacy structure of the asparagus residues may have contributed to the high emissions. Due to the high concentration of PM in the field and the unavailability of dilution air, the DusTrak could not accurately measure PM. Emission factors for PM10 are not reported for the field samples. The extraction of filter samples from the El Centro fields and analysis of the extracts by HPLC identified 16 PAH and quantified 12 of them with concentrations above the limits of detection. To calculate emission factors for the field data, the laboratory ERPAH/CO from (3) and the EFCO of 45.8 g/kg dry fuel (average EFCO from Mexicali lab data in Table 5) were used in (4) along with a multiplicative correction factor. The need for the correction may be due to differences in sampling between the lab and field. In the field the sampling probe was held just inches above the smoldering residue. In the lab the probe was located in the exhaust duct. However, there is also a large inconsistency between EFPAH based on (1) and EFPAH based on (3) and (4) for the laboratory data. The correction factor, fc, is the ratio of the EF based on (1) with lab data, to the EF based on the ER ((3) and (4) with lab data). It was calculated for each type of residue using:

fc =EFi,1

EFi,34

lab

(5)

where

EFi,1 = Emission factor using equation 1, lab PAH

EFi,34 = Emission factor using equations 3 and 4, lab PAH

The correction factors are summarized in Table 10 and range from 131 for the Bermuda grass to 338 for asparagus. Equation 4 was modified with the correction factor fc to calculate the emission factors for the field data:

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EFPAH,field = ERPAH,field /CO,field ⋅ EFCO,lab ⋅ fc (6)

The resulting PAH emission factors for the fields burned in El Centro are shown in Table 11. They range from 0.336 – 18.9 mg/kg dry fuel. The data are plotted in Figure 6 and several trends are apparent. First, asparagus and Klein grass have consistently higher emission factors than the Bermuda grass. There is no correlation between the PAH field emissions and the PM10 lab emissions shown in Table 6. All three crops show the highest emissions for pyrene, fluoranthene, and phenanthrene. Figure 7 shows that all three crops display the same decreasing emission pattern with respect to the PAH. The uncertainties in the PAH emission factors could not be determined because of the combination of multiple samples to provide adequate sample sizes for the HPLC analyses. The pattern in Figure 7 does not correlate with the relative volatilities of the PAH. Data that relates relative amounts of PAH to combustion conditions, particularly for field data, is not available. Jenkins et al. (1996) note that PAH emissions increase with increasing particulate emissions. Our data do not support that correlation based on the PM10 values from our laboratory experiments. Field levels of PM10 could not be measured. Comparison of Laboratory and Field Emissions Lab and field emission factors of CO and PAH were compared. Particulate emissions were not compared because they could not be measured in the field. The average EFCO for all wastes burned in the laboratory was 45 ± 6 g/kg, and for the field was 60 ± 14 g/kg dry fuel. The EFCO for the lab may be lower due to more efficient combustion. The dry, flat, insulating board on which the waste burned in the lab may have increased combustion efficiencies and temperatures relative to the rough, uneven ground in the field. The emission factors for PAH for the lab and the field are quite different. Figure 8 compares the asparagus data. The field emission was 40% higher for phenanthrene and 10% higher for anthracene, but the laboratory emissions for the other PAH were three to six times higher than those in the field. Figure 9 compares the Klein grass data. In this case the field and laboratory PAH emissions were much closer than for the asparagus. The field emissions were higher with the exception of benz[a]anthracene. The benzo[k]fluoranthene and benzo[g,h,i]perylene field emissions were 4 and 8 times higher than the laboratory values. The other field PAH values averaged 1.5 times the lab emissions. Figure 10 compares the Bermuda grass data. The field emission of PAH was consistently higher, ranging from two to five times higher. As shown in Figure 11, most of the lab and field PAH emission data followed the same descending pattern. If the asparagus laboratory emission factors and those of

benz[a]anthracene are excluded, all of the PAH results follow the same decreasing pattern. This suggests that PAH may serve as a suitable class of compounds to identify the source of ambient particulate. However, laboratory studies show that PAH is rapidly oxidized in sunlight with half-lives of a few hours (Haynes 1991).

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Comparison with Literature The emission factors of CO, CO2, NOx, and PM10 of field and laboratory tests were within the range of values found by other studies for similar crops (Jenkins et al. 1996, Lemieux, Lutes, and Santoianni 2004, Andreae and Merlet 2001). Asparagus, however, had an EFCO of 75 ± 25 g/kg dry fuel which was moderately higher than expected, but the standard deviation is large. The El Centro biomass had lab EFPM10 values that were approximately three times higher (7.1 ± 1.5 g/kg dry fuel) than the Mexicali biomass (2.2 ± 0.6 g/kg dry fuel); however, they are still lower than those reviewed by Lemieux, Lutes, and Santoianni (2004), which reports 11 g/kg burned material. The PAH emission factors are of the same order of magnitude as those of Jenkins et al. (1996); however, those results do not show the descending pattern shown in Figure 11. A notable difference was seen with respect to naphthalene. It was not detected in this study, but it was the dominant PAH in Jenkins’ study. Note that Jenkins suspected possible contamination due to the breakdown of XAD-2 sorbent in his sampling system. CONCLUSIONS The emission factors for CO, CO2, and PAH, determined in the laboratory, were similar to those measured in the field and were reasonably close to values reviewed by Lemieux, Lutes, and Santoianni (2004) and Andreae and Merlet (2001). Emission factors for PM10 in the field were not measured because the particulate concentrations exceeded the range of the analytical equipment. The laboratory measurement of emission factors for black carbon ranged from 0.113 – 1.02 g/kg dry fuel. The agreement between PAH emission factors from the laboratory and the field is not as close as that for CO and CO2; they sometimes differ by a factor of six. The overall agreement between lab and field data suggests that properly designed laboratory experiments can provide reliable data that approximates what happens in the field. Analysis of filter samples for PAH, from both field and lab experiments, by GC/MS was unsuccessful. The concentrations of PAH were too low. Subsequent efforts to quantify PAH by HPLC were successful. This suggests that future SCERP efforts to measure PAH in emissions or ambient air should consider HPLC techniques. The analysis and comparison of the PAH data from the lab and field was complicated by sampling issues. A correction factor, based entirely on laboratory data, was created to adjust the emission ratio approach represented by (4) so that it agreed with results from (1). This correction factor was then used to calculate PAH emission factors for all of the field data using emission ratios per (5). The lab and field PAH emissions showed a fairly consistent descending pattern with respect to the relative quantities of twelve compounds for all fuels tested. This suggests that PAH might be a suitable marker for identifying agricultural sources of particulate in ambient air samples. The laboratory PAH emission factor data show similar patterns. However, laboratory studies show that PAH is rapidly oxidized in sunlight with half-lives of a few hours.

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RECOMMENDATIONS The emission factors for PAH from the lab and field are somewhat different. The reasons for this are not known. It is possible that the sample volumes measured for the filters in the field were inaccurate because as the filter cake accumulated, air flows rapidly dropped. This was not a significant problem in the lab. Additional field measurements would be helpful given our awareness of the sensitivity of flow rates to cake thickness. The backpack was useful for collecting filter samples to be analyzed for PAH. Due to the buildup of particulate on the filter, the air flow rates changed with time and this added considerable uncertainty to the total volume sampled. Future configurations of the backpack should include a totalizer for determining the cumulative volume sampled. Analysis of filter samples for PAH, from both field and lab experiments, by GC/MS was unsuccessful. The concentrations of PAH were too low. Subsequent efforts to quantify PAH by HPLC were successful. This suggests that future SCERP efforts to measure PAH in emissions or ambient air should consider HPLC techniques. RESEARCH BENEFITS This study suggests that laboratory experiments to measure emission factors can provide values that are reasonably close to those measured in the field. The emission factors reported for PAH and PM10 are an important addition to the available data, and they focus on crops that are significant in the U.S.-Mexican border region. The emission factors should help regulators access risk and design regulations to minimize exposure to PAH and particulate emissions in the border region. A preliminary version of this report was presented by Geoff Silcox at the 9th International Congress on Combustion By-Products and their Health Effects, “Characterizing Emissions from Agricultural Burning with Attention to the U.S.-Mexico Border Region,” June 12-15, 2005, Tucson, Arizona. The primary author of this report was Kirk Wendel and this report constitutes his senior thesis. Kirk graduated Spring 2006 with a Bachelor of Science Degree in Chemical Engineering from the University of Utah. He performed most of the laboratory work and assisted David Wagner in preparing for the field experiments. Kirk learned a great deal about designing experiments, analyzing data, making measurements, and report writing. All of the analysis of filter samples for PAH was performed by Porfirio Caballero Mata and his colleagues at ITESM. This fruitful collaboration made the calculation of emission factors for PAH possible. ACKNOWLEDGMENTS This work was sponsored by the Southwest Consortium for Environmental Research and Policy (SCERP) through a cooperative agreement with the U.S. Environmental

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Protection Agency. SCERP can be contacted for further information through www.scerp.org and scerp@mail.sdsu.edu. REFERENCES Andreae, M. O., and P. Merlet. 2001. “Emission of Trace Gases and Aerosols from Biomass Burning.” Global Biogeochemical Cycles 15 (4): 955-966. Arnott, W. P., H. Moosmüller, C. F. Rogers, T. Jin, and R. Bruch. 1999. “Photoacoustic Spectrometer for Measuring Light Absorption by Aerosol: Instrument Description.” Atmospheric Environment 33: 2845-2852. Arnott, W. P., H. Moosmüller, and J. W. Walker. 2000. “Nitrogen Dioxide and Kerosene-Flame Soot Calibration of Photoacoustic Instruments for Measurement of Light Absorption by Aerosols.” Review of Scientific Instruments 71 (7): 4545-4552. Haynes, B. S. 1991. “Soot and Hydrocarbons in Combustion,” in Fossil Fuel Combustion: A Source Book, William Bartok and Adel F. Sarofim, Editors, p. 261, John Wiley & Sons, Inc., New York. Henneberger, A., W. Zareba, A. Ibald-Mulli, R. Rückerl, J. Cyrys, J. Couderc, B. Mykins, G. Woelke, H. E. Erich Wichmann, and A. Peters. 2005. “Repolarization Changes Induced by Air Pollution in Ischemic Heart Disease Patients.” Environmental Health Perspectives 113: 440-446. Jenkins, B. M., A. D. Jones, S. Q. Turns, and R. B. Williams. 1996. “Emission Factors for Polycyclic Aromatic Hydrocarbons from Biomass Burning.” Environmental Science & Technology 30 (8): 2462-2469. Lemieux, P. M., C. C. Lutes, and D. A. Santoianni. 2004. “Emissions of organic air toxins from open burning: a comprehensive review.” Progress in Energy and Combustion Science 30 (1): 1-32. Lemieux, P. M., C. C. Lutes, J. A. Abbott, K. M. Aldous. 2000. “Emissions of Polychlorinated Dibenzo-p-dioxins and Polychlorinated Dibenzofurans from the Open Burning of Household Waste in Barrels.” Environmental Science & Technology 34 (3): 377-384. National Toxicology Program (NTP), Department of Health and Human Services. 2005. “The Report on Carcinogens, Eleventh Edition: Polycyclic Aromatic Hydrocarbons, 15 Listings.” (cited 16 December), http://ntp.niehs.nih.gov/ntp/roc/eleventh/profiles/s150pah.pdf. Pope III, C. A., M. L. Hansen, R. W. Long, K. R. Nielsen, N. L. Eatough, W. E. Wilson, and D. J. Eatough. 2004. “Ambient Particulate Air Pollution, Heart Rate Variability, and Blood Markers of Inflammation in a Panel of Elderly Subjects.” Environmental Health Perspectives 112 (3): 339-345.

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APPENDIX

Table 1. Ultimate and Proximate Analyses of Crop Residues

Domestic Wheat Mexican Wheat Canola Flax Barley

Ultimate Analysis (% dry weight)

Carbon 46.27 45.99 46.06 49.68 47.54

Hydrogen 5.03 4.91 4.83 5.53 5.31

Nitrogen 0.64 0.52 0.68 0.72 0.72

Sulfur 0.20 0.63 0.28 0.16 0.12

Ash 11.19 11.73 10.01 4.66 7.65

Oxygen* 36.67 36.22 38.14 39.25 38.66

Proximate Analysis (% dry weight)

Ash 11.19 11.73 10.01 4.66 7.65

Volatile 74.49 73.40 74.88 77.01 77.37

Fixed Carbon 14.32 14.87 15.11 18.33 14.98

Higher Heating Value (Btu/lb dry weight)

7340 7250 7316 8056 7600

*Oxygen by difference

16

Table 2. High and Low Values in Factorial Design

Variables High value Low value Density (kg/m2) 0.75 0.25 Moisture (%, wet basis) 14 9

Wind (mph) 2 7

Table 3. Key Variables and Factorial Design

Test # Density(kg/m2) Moisture (%, wet basis) Wind (mph)

1 0.75 9 2

2 0.75 9 7

3 0.75 14 2

4 0.75 14 7

5 0.25 9 2

6 0.25 9 7

7 0.25 14 2

8 0.25 14 7

Table 4. High and Low Values for Factorial Design (“+” high value, “-” low value)

Test # Density Moisture Wind

1 + - -

2 + - +

3 + + -

4 + + +

5 - - -

6 - - +

7 - + -

8 - + +

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Table 5. Emission Factors (g/kg dry fuel) for Mexicali Crops Burned in the Lab

CO2 CO NO BC PM10

Abatti Wheat 1054 ± 43 38.2 ± 2.5 1.06 ± 0.08 0.113 ± 0.019 0.91 ± 0.18

South Date Wheat 974 ± 27 39.6 ± 0.1 1.46 ± 0.05 0.071 ± 0.038 2.17 ± 0.55

Calexico Flax 1089 ± 19 52.9 ± 3.6 1.41 ± 0.21 0.241 ± 0.076 2.69 ± 0.34

Calexico Canola 964 ± 42 56.3 ± 4.2 0.51 ± 0.48 0.125 ± 0.024 2.74 ± 1.11

Calexico Wheat 1066 ± 52 42.1 ± 2.3 1.08 ± 0.20 0.147 ± 0.034 2.30 ± 0.75

Average 1029 ± 57 45.8 ± 8.2 1.10 ± 0.38 0.140 ± 0.063 2.16 ± 0.74

Table 6. Emission Factors (g/kg dry fuel) for El Centro Crops Burned in the Lab

CO2 CO NO BC PM10

Asparagus 1144 ± 23 45.2 ± 5.0 1.20 ± 0.06 1.02 ± 0.26 5.72 ± 0.74

Bermuda Grass 1269 ± 283 41.5 ± 8.7 1.76 ± 0.42 0.15 ± 0.05 7.66 ± 2.38

Klein Grass 988 ± 44 46.4 ± 7.7 1.60 ± 0.09 0.13 ± 0.07 7.87 ± 1.32

Average 1134 ± 131 44.3 ± 2.5 1.52 ± 0.29 0.43 ± 0.51 7.09 ± 1.19

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Table 7. Comparison of Emission Factors for CO (g/kg dry fuel) Using the Backpack-Mounted TSI IAQ-Calc CO/CO2

Analyzer and Rack-Mounted CO/CO2 Analyzers. All Data Were Obtained in the Burn Box for this Comparison

TSI IAQ-Calc Laboratory

Asparagus 38.0 ± 2.9 45.2 ± 5.0

Bermuda Grass 51.4 ± 5.0 41.5 ± 8.7

Klein Grass 58.1 ± 5.0 46.4 ± 7.7

Average 49.2 ± 10.2 44.3 ± 2.5

Table 8. Emission Factors for PAH (mg/kg dry fuel) for El Centro Crop Residues Burned in the Lab

Phe An Fla Pyr B[a]An Chy B[b]Fla B[k]Fla B[a]P DB[ah]

An B[ghi]P I[123]P

Asparagus 6.916 1.537 38.420 49.946 13.831 14.215 35.346 19.210 12.678 1.153 9.221 9.221

Klein Grass

4.565 0.884 5.007 7.658 3.829 2.062 2.504 0.589 0.736 0.295 0.118 0.442

Bermuda Grass

3.147 0.760 4.015 5.969 1.085 1.194 2.496 0.760 0.760 0.217 0.651 0.326

Abbreviations: Phe (phenanthrene), An (anthracene), Fla (fluoranthene), Pyr (pyrene), B[a]An (benz[a]anthracene), Chy (chrysene), B[b]Fla (benzo[b]fluoranthene), B[k]Fla (benzo[k]fluoranthene), B[a]P (benzo[a]pyrene), DB[ah]An (dibenz[a,h]anthracene), B[ghi]P (benzo[g,h,i]perylene), I[123]P (indeno[1,2,3-cd]pyrene).

19

Table 9. Emission Factors for CO (g/kg dry fuel) Measured in the Field

Field

Asparagus 75.01 ± 24.88

Bermuda Grass 48.73 ± 16.22

Klein Grass 55.45 ± 7.45

Average 59.7 ± 13.7

20

Table 10. Correction Factors for PAH Emission Factors Based on Laboratory Data for El Centro Crop Residues

Correction Factor

Asparagus 338.4

Klein Grass 132.9

Bermuda Grass 130.8

Table 11. Emission Factors for PAH (mg/kg dry fuel) for El Centro Crop Residue Burned in the Field

Phe An Fla Pyr B[a]An Chy B[b]Fla B[k]Fla B[a]P DB[ah]

An B[ghi]P I[123]P

Asparagus 11.040 1.752 12.968 18.926 3.680 3.855 8.411 4.030 2.979 0.350 1.577 1.472

Klein Grass

5.499 1.203 8.249 11.514 2.578 3.265 4.640 2.578 1.719 0.344 1.031 0.687

Bermuda Grass

10.569 1.678 12.247 16.776 4.362 5.033 8.891 4.194 2.852 0.336 1.510 1.342

Abbreviations: Phe (phenanthrene), An (anthracene), Fla (fluoranthene), Pyr (pyrene), B[a]An (benz[a]anthracene), Chy (chrysene), B[b]Fla (benzo[b]fluoranthene), B[k]Fla (benzo[k]fluoranthene), B[a]P (benzo[a]pyrene), DB[ah]An (dibenz[a,h]anthracene), B[ghi]P (benzo[g,h,i]perylene), I[123]P (indeno[1,2,3-cd]pyrene).

21

Air in

Exhaust

Burning

materialFilter assembly withPump and impactor

ChemiluminescentNO, NO2, NOx analyzer

Zirconia oxideOxygen analyzer

NDIR CO/CO2analyzer

Dilution manifold

Black carbonPA analyzer

DusTrakParticle monitor

Air in

Exhaust

Burning

materialFilter assembly withPump and impactor

ChemiluminescentNO, NO2, NOx analyzer

Zirconia oxideOxygen analyzer

NDIR CO/CO2analyzer

Dilution manifold

Black carbonPA analyzer

DusTrakParticle monitor

Figure 1. Schematic of Laboratory Facility for Burning Crop Residues

22

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

0 5 10 15 20 25 30 35

Time (min)

Wei

gh

t (l

b)

High loading, low moisture, low wind

Figure 2. Weight Loss as a Function of Time as Measured for Domestic Wheat

23

TSI-IAQ-CalcTM

CO/CO2 MonitorCyclone

FilterFlowmeter

Pump

TSI DustTrakPM-10 Monitor

10 micron InletImpactor

Sample

Figure 3. Equipment Mounted on Backpack for Field Sampling

0

20

40

60

80

100

120

140

160

180

200

0 5 10 15 20 25 30 35

Time (min)

Co

nce

ntr

atio

n (

pp

m)

CO

NO

High loading, low moisture, low wind

Figure 4. CO and NO as a Function of Time for Domestic Wheat in the Burn Box

24

0

10

20

30

40

50

60

Phe An Fla Pyr B[a]An Chy B[b]Fla B[k]Fla B[a]P DB[ah]

An

B[ghi]P I[123]P

PAHs

EF

(m

g/k

g d

ry f

uel

)

Asparagus Lab

Klein Grass Lab

Bermuda Grass Lab

Figure 5. Emission Factors for PAH (mg/kg dry fuel) for El Centro Crop Residue

Burned in Laboratory Experiments

25

0

2

4

6

8

10

12

14

16

18

20

Phe An Fla Pyr B[a]An Chy B[b]Fla B[k]Fla B[a]P DB[ah]

An

B[ghi]P I[123]P

PAHs

EF

(m

g/k

g d

ry f

uel

)

Asparagus Field

Klein Grass Field

Bermuda Grass Field

Figure 6. Emission Factors for PAH (mg/kg dry fuel) for El Centro Crop Residue Burned in the Field

26

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

Pyr Fla Phe B[b]Fla Chy B[k]Fla B[a]An B[a]P An B[ghi]P I[123]P DB[ah]

An

PAHs

EF

(m

g/k

g d

ry f

uel

)

Asparagus Field

Klein Grass Field

Bermuda Grass Field

Figure 7. Emission Factors for PAH (mg/kg dry fuel) for El Centro Crop Residues Burned in the Field, Showing Descending Emission Pattern

27

0

10

20

30

40

50

60

Phe An Fla Pyr B[a]An Chy B[b]Fla B[k]Fla B[a]P DB[ah]

An

B[ghi]P I[123]P

PAHs

EF

(m

g/k

g d

ry f

uel

)

Asparagus Field

Asparagus Lab

Figure 8. Comparison of Laboratory and Field Emission Factors for PAH (mg/kg

dry fuel) for Asparagus

28

0

2

4

6

8

10

12

14

Phe An Fla Pyr B[a]An Chy B[b]Fla B[k]Fla B[a]P DB[ah]

An

B[ghi]P I[123]P

PAHs

EF

(m

g/k

g d

ry f

uel

)

Klein Grass Field

Klein Grass Lab

Figure 9. Comparison of Laboratory and Field Emission Factors for PAH (mg/kg dry fuel) for Klein Grass

29

0

2

4

6

8

10

12

14

16

18

Phe An Fla Pyr B[a]An Chy B[b]Fla B[k]Fla B[a]P DB[ah]

An

B[ghi]P I[123]P

PAHs

EF

(m

g/k

g d

ry f

uel

)

Bermuda Grass Field

Bermuda Grass Lab

Figure 10. Comparison of Laboratory and Field Emission Factors for PAH (mg/kg dry fuel) for Bermuda Grass

30

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

Pyr Fla Phe B[b]Fla Chy B[k]Fla B[a]An B[a]P An B[ghi]P I[123]P DB[ah]

An

PAHs

EF

(m

g/k

g d

ry f

uel

)

Asparagus Field

Klein Grass Field

Bermuda Grass Field

Klein Grass Lab

Bermuda Grass Lab

Figure 11. PAH Emission Factors for Field and Lab Data (Asparagus Lab Data Not Included Because It Is Exceptionally High) Showing the Descending

Emission Trend Common to Most