Chemical Composition and Screening-Level Environmental

4 Jun 2013 - BioEnergy and Environmental Laboratory (BEEL), Masdar Institute of Science and Technology, P.O. 54224, Abu Dhabi, United Arab Emirates...
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Chemical Composition and Screening-Level Environmental Contamination Risk of Bioderived Synthetic Paraffinic Kerosene (BioSPK) Jet Fuels Nour Mezher,† Wayne E. Rathbun,‡ Haiyan Wang,‡ and Farrukh Ahmad*,§ †

BioEnergy and Environmental Laboratory (BEEL), Masdar Institute of Science and Technology, P.O. 54224, Abu Dhabi, United Arab Emirates ‡ UOP LLC, A Honeywell Company, 25 E Algonquin Road, Des Plaines, Illinois 60017-5017, United States § BEEL, Institute Center for Water Advanced Technology and Environmental Research (iWATER), Masdar Institute of Science and Technology, P.O. 54224, Abu Dhabi, Abu Dhabi, United Arab Emirates ABSTRACT: Bioderived synthetic paraffinic kerosenes (Bio-SPKs) are a promising new solution for the steadily increasing anthropogenic carbon emissions from the global aviation industry. Compositional analyses were performed on samples of camelina- and jatropha-derived Bio-SPKs as well as conventional Jet A fuel. A screening-level health risk from potential environmental spills of Bio-SPKs was evaluated using an indicator/surrogate approach for hydrocarbon mixtures and compared to the risk posed by Jet A. Compositional analysis of three Bio-SPKs demonstrated a complete absence of benzene, a carcinogenic health risk-driver present at 65 ppm in the Jet A sample. Among the three exposure pathways evaluated, the soil-togroundwater leaching pathway led to the highest carcinogenic and systemic toxic risk, while the soil pathway (i.e., dermal contact, soil particulate inhalation, and vegetable consumption) led to the least. For systemic toxicity, Jet A posed the highest risk, while the jatropha-based Bio-SPK posed the lowest risk due to its lower mobility. Critical soil protective-concentration-levels (PCLs) were calculated for the 4 fuels and a 50%:50% (v:v) blend of camelina-derived Bio-SPK:Jet A, using reverse modeling for the dominant soil-to-groundwater leaching pathway. Based on the compositional data available for these samples, all Bio-SPKs’ whole-fuel critical soil PCLs were 4−12 times greater than the critical soil PCL of Jet A, indicating lower toxicity of Bio-SPKs with respect to Jet A. The critical soil PCL for the blend was inversely related to its Jet A content.

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INTRODUCTION The global aviation sector as a whole currently accounts for an estimated 3% of global anthropogenic carbon emissions.1 This percentage is expected to steadily rise into the future, with the Intergovernmental Panel on Climate Change (IPCC) projecting aviation carbon emissions at 5−15% by the year 2050.1 To tackle the climate impacts of aviation, the United States has set goals that include carbon neutral growth by the year 2020 (from a 2005 baseline) and an absolute reduction in greenhouse gas emissions by the year 2050.2,3 Consequently, the development and demonstration of sustainable aviation alternative fuels has become a key element of the U.S. Next Generation Air Transportation System (NextGen) strategy, recognizing the fact that efficiency improvements in the national airspace system (NAS) alone are not sufficient to meet these ambitious climate goals.2 Capital investment requirements for delivery infrastructure and engine modifications as well as strict fuel certification requirements limit the adoption of unconventional alternative fuels and instead favor “drop-in” candidates that can be easily blended into conventional jet fuel without any significant compromise on combustion characteristics, engine performance, or emissions profile.1,4 Studies on Synthetic Paraffinic Kerosene (SPK), a drop-in aviation fuel alternative that fits this profile, have demonstrated that blends with up to 50% by volume should have no impact on engine operation.4 SPKs can be broadly divided into two categories based on the processes © XXXX American Chemical Society

employed to generate them: (1) Fischer−Tropsch (F−T) SPKs produced from synthesis gas or “syngas” (i.e., hydrogen and carbon monoxide) using the Fischer−Tropsch process and (2) hydrotreated renewable jet (HRJ) fuels, also known as bioderived SPKs (Bio-SPKs), produced from deoxygenation and hydrocracking of plant oils.5,6 Both types of SPKs exhibit low total aromatic organic compound content and low total sulfur content.6,7 In SPKs, aromatic content can be less than 1% by volume, while conventional jet fuels range from 10 to 25%, with a typical average of about 18%.4,5 Similarly, total sulfur is typically nondetectable (detection limit 0.01 ppm) in Bio-SPKs, while it is present at concentrations as high as 490 ppm in Jet A/A1.4,5 The environmental impact of postcombustion emissions of SPKs resulting from its compositional difference from conventional jet fuel has been recently studied in detail under the Federal Aviation Administration-sponsored PARTNER (Partnership for Air Transportation Noise and Emission Reduction) program and the CAAFI (Commercial Aviation Alternative Fuels Initiative) initiative,2,5−7 leading to the development of the new American Society for Testing and Materials (ASTM) International synthetic fuel standard, ASTM D7566-11a.8 In addition, “well-to-wake” life cycle greenhouse gas inventories Received: April 11, 2013 Revised: June 4, 2013

A

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ECN > 21−35.20 For systemic toxicity risk, this TPHCWG approach has been applied, largely unchanged, for over a decade to numerous petroleum-, oil-, and lubricant-contaminated sites with modifications only to the hydrocarbon extraction procedure from environmental samples and to the analysis of only those fractions relevant to the type of fuel.13,19 It must be noted that the TPHCWG approach, while being primarily a surrogate fraction-based approach, nevertheless encourages the evaluation of carcinogenic risk using indicator compounds.20 An indicator/surrogate approach for chemical mixtures11 was utilized to select target constituents of concern (COCs) for this study. The approach has its origins at the USEPA15 and is favored when mixture constituents are chemically similar and nonreactive and ample data on the mixture exist.14 Risk-driving aromatic compounds, BTEX and naphthalene,23 were selected for their higher toxicity and used as indicator compounds to represent the risk from the aromatic fraction of the aviation fuels. Aliphatic fractions from the TPHCWG approach were adopted as surrogates for evaluating the risk from the aliphatic fraction of aviation fuels. A listing of these target COCs relevant to aviation jet fuels together with their toxicity factors and fate and transport properties are presented in Tables 1 and 2, respectively.

have been estimated for alternative jet fuels and compared to conventional jet fuels.6 However, so far, little has been published regarding the molecular makeup of the aromatic fraction of SPKs or the human-health risk from exposure to the pure or blended renewable jet fuel product. Many of the monoaromatics in conventional fuel, such as the BTEX (benzene, toluene, ethylbenzene, and xylenes) compounds, are the primary drivers for human-health risk in the case of fuel spills because some have carcinogenic properties.9 These riskdrivers are less of an artifact of the starting materials for conventional petroleum-based fuel refining, and more a product of specific processes used to generate or enhance refined fuels, such as catalytic reforming. 10 Still other hydrocarbon components of fuels pose systemic risk to human health.11 In this article, we present hydrocarbon compositional results for Bio-SPKs that were derived from two different plant sources, camelina (Camelina sativa) and jatropha (Jatropha curcas), using the Honeywell UOP Renewable Jet Process,11 one of only two commercial processes available to produce BioSPKs. We then proceed to compare the hydrocarbon composition of Bio-SPK to that of conventional jet fuel, Jet A. Following this, we perform a comparative (i.e., among BioSPKs and between Bio-SPKs and Jet A) screening-level quantitative human-health risk assessment for aviation fuel spills. Fuels typically require a complex methodology for risk assessment because, unlike single known compounds, fuels are mixtures of hundreds of known and unknown compounds.12,13 Therefore, quantitative risk assessment must be performed using a combined indicator-surrogate approach for nonreactive mixtures, which has its origins at the United States Environmental Protection Agency (USEPA).14,15 The combined indicator-surrogate approach must address both carcinogenic and system toxicity risk from the hydrocarbon mixture.16−18 In this study, we employ known risk-driving aromatic compounds as indicator compounds and equivalent carbon number (ECN) aliphatic fractions, outlined in the total petroleum hydrocarbon criteria working group (TPHCWG) approach, as surrogates.19,20 Finally, critical protective concentration levels (PCLs) in soil are back-calculated for Bio-SPKs, Jet A, and their blend, based on regulated values for aromatic risk-drivers and aliphatic fuel fractions in environmental media.

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Table 1. Toxicity Values (Reference Dose [RfD], Reference Concentration [RfC], and Cancer Slope Factors) Assigned to the Constituents of Concern (COCs) Found in Aviation Jet Fuels by the TPHCWG and the USEPA11,24a,b inhalation RfC (mg/m3)

cancer slope factor (mg/kg/ day)−1

5 5 0.1

18.4 18.4 1.0

N/A N/A N/A

ECN > 10−12

0.1

1.0

N/A

ECN > 12−16

0.1

1.9

N/A

ECN > 16−21

2

NA

N/A

0.004

0.28

0.055

toluene

0.08

5

N/A

ethylbenzene

0.1

1.0

N/A

xylene

0.2

0.1

N/A

naphthalene

0.02

0.003

N/A

constituent of concern (COC) Aliphatic ECN > 5−6 ECN > 6−8 ECN > 8−10

Aromatic benzene

EXPERIMENTAL SECTION

General Methodology for Environmental Risk Assessment of Hydrocarbon Fuels. In the late 1990s, several stakeholders including private and governmental entities and academic institutions came together in the United States under the umbrella of the TPHCWG to develop a protocol for human-health risk assessment for environmental releases of petroleum-based refined and crude products, which are all multicomponent hydrocarbon mixtures. The TPHCWG approach, as it came to be known, divides complex hydrocarbon mixtures into individual aliphatic and aromatic fractions that are bound by straight chain alkanes during gas chromatographic (GC) analysis.20,21 Each equivalent carbon number (ECN)-range fraction, so designated, consists of a smaller mixture of unknown compounds, all of which have boiling points falling within the range of boiling points of the n-alkane markers that demarcate that fraction. The TPHCWG approach divides all petroleum-based products into a total of 13 aliphatic and aromatic fractions ranging from ECN5 to ECN35 and assigns toxicity and transport properties to each fraction, so that they can be treated as individual compounds during risk assessment.11,22 The aliphatic fractions are as follows: ECN > 5−6, ECN > 6−8, ECN > 8−10, ECN > 10−12, ECN > 12−16, and ECN > 16− 21.20 The aromatics fractions are as follows: ECN > 5−7, ECN > 7−8, ECN > 8−10, ECN > 10−12, ECN > 12−16, ECN > 16−21, and

oral and dermal RfD (mg/kg/ day)

MCL in mg/L (source) 15 (WHO) 15 (WHO) 0.3 (WHO) 0.3 (WHO) 0.3 (WHO) 0.3 (WHO) 0.005 (USEPA) 0.7 (USEPA) 1.0 (USEPA) 10.0 (USEPA) 0.005 (USEPA)

a

Lowest maximum contaminant level (MCL) values of target COCs in groundwater as set by the USEPA or the WHO.25,26. bNA = not available, N/A = not applicable, MCL = maximum contaminant level, WHO = World Health Organization, USEPA = United States Environmental Protection Agency. Compositional Analysis. The fuel samples consisted of three bioderived SPK samples and one petroleum-derived commercial Jet A fuel. Bio-SPK1 was derived from a single grower of camelina, whereas Bio-SPK2 and Bio-SPK3 were composite samples derived from different seed sources of camelina and jatropha, respectively. Compositional analysis of all fuels were performed at Honeywell UOP using a comprehensive two-dimensional gas chromatograph (GCxGC) coupled to a flame ionization detector (FID). The method is detailed in UOP methods 965-1028 and 990-1129 and can be accessed through the ASTM International standards Web site. UOP Method 965-10 forms the basis of ASTM Work Item Standard B

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Table 2. Fate and Transport Parameters Associated with the Target COCs22,27 COC Aliphatic ECN > 5−6 ECN > 6−8 ECN > 8−10 ECN > 10−12 ECN > 12−16 ECN > 16−21 Aromatic benzene toluene ethylbenzene xylene naphthalene

solubility (mg/L) 3.6 5.4 4.3 3.4 7.6 2.5

× × × × × ×

101 10° 10−1 10−2 10−4 10−6

1.77 × 103 5.3 × 102 1.69 × 102 1.98 × 102 3.14 × 101

vapor pressure (atm) 3.5 6.3 6.3 6.3 4.8 1.1

× × × × × ×

9.50 2.82 9.60 8.06 8.89

10−1 10−2 10−3 10−4 10−5 10−6

× × × × ×

101 101 10° 10° 10−2

log KOC (c/c)

Henry’s law constant (cm3/cm3)

2.9 3.6 4.5 5.4 6.7 8.8

3.3 × 101 5.0 × 101 8.0 × 101 1.20 × 102 5.2 × 102 4.9 × 103

1.82 2.15 2.31 2.38 3.19

2.27 2.76 3.28 2.93 2.00

WK28230 currently under development by ASTM Subcommittee D02. In brief, each aviation fuel sample was injected into a GC that was equipped with a two-stage thermal modulator system, primary and secondary fused silica capillary GC columns, and a FID. The modulator served as an interface between the two GC columns. The primary column was a conventional high-resolution capillary GC column to separate molecules based on volatility. The secondary GC column was a short and narrow column for fast separations based on polarity. The modulator repetitively accumulated, focused, and reinjected the effluents eluting off the primary column onto the secondary column which was connected to the FID.30 The outcome was a series of high speed chromatograms from the secondary column which were transformed by computer software into a two-dimensional array, with one dimension representing the retention time from the primary column and the other representing the retention time from the secondary column. Alternatively, the data could be displayed as a 3-dimensional plot containing a third dimension which represents the FID signal intensity. A template was used to identify the boundaries between the different hydrocarbon types and to label the separated components. The mass percent composition of the sample was obtained by internal normalization, wherein the sum of all peak volumes was normalized to 100%. As a secondary check, a sample of Bio-SPK from Honeywell UOP was also subjected to confirmation analysis by gas chromatography−mass spectrometry (GC-MS) analysis at Honeywell UOP. Exposure Pathways. The initial assumption of the modeling aspect of this study was an accidental spill of aviation fuel, Bio-SPK or Jet A, that leaves unweathered residual nonaqueous phase liquid (NAPL) contamination31 of fresh aviation fuel as a contamination source in soil near a residential area with no public utility water (i.e., potable water supplied using independent groundwater wells). The transport effects of components within this spill were studied through three different exposure pathways: (1) soil-to-groundwater leaching; (2) soil volatilization into outdoor air; and (3) soil dermal contact, including soil particulate inhalation and consumption of vegetables grown in the soil.27 These three transport pathways serve as the “connection” between the contaminant source zone and the human receptor. They can be used, together with the physical/chemical properties of each target COC, either to determine concentration of the COC in environmental media in the vicinity of the receptor or to back-calculate COC-specific critical PCLs in the source zone soil using regulatory thresholds in environmental media at the point-of-exposure (POE), together with the particular COC’s weight percentage in fresh fuel. Both of these forward and backward calculation modes were employed in this study. Each pathway was controlled by environmental media- and contaminant-specific parameters, which were used to calculate natural attenuation factors (NAFs) within each pathway. The NAFs for the pathways evaluated included soil-to-groundwater leaching factor, leachate/groundwater dilution factor, and soil particulate emission factor, among others. The risk values were

× × × × ×

10−1 10−1 10−1 10−1 10−2

diffusivity in air (cm2/s)

diffusivity in water (cm2/s)

1.0 1.0 1.0 1.0 1.0 1.0

× × × × × ×

10−1 10−1 10−1 10−1 10−1 10−1

1.0 1.0 1.0 1.0 1.0 1.0

× × × × × ×

10−5 10−5 10−5 10−5 10−5 10−5

8.8 8.7 7.5 7.4 5.9

× × × × ×

10−2 10−2 10−2 10−2 10−2

9.8 8.6 7.8 8.5 7.5

× × × × ×

10−6 10−6 10−6 10−6 10−6

calculated for two types of adult receptors: a resident living immediately adjacent to the contaminated site and a construction worker working on-site. These types of receptors represent two common exposure scenarios as defined by the USEPA.32 Toxicity Evaluation. For the purpose of human-health risk assessment, contaminant toxicity generally falls into one of two categories: carcinogenic or systemic (i.e., noncarcinogenic or targetorgan) toxicity. The toxicity threshold associated with carcinogenic compounds is the cancer risk, while the value associated with noncarcinogenic compounds is the hazard index (HI). Both values are related to the average daily intake (ADI) of COCs and result in different toxic end points: increased lifetime cancer risk (ILCR) in a population of receptors for carcinogens and target organ toxicity for noncarcinogens. The ADI was calculated from the POE concentration of the COCs and standard exposure factors for human receptor behavior.11,32 For fuels and other mixtures, the HI is an accumulation of the hazard quotients (HQs) of all target COCs present. For example, in the ingestion exposure route, the HQ is calculated by dividing the ADI of the compound by its reference dose (RfD) (Table 1 lists all the RfD and RfC [reference concentration] values for the aliphatic fractions and risk-driving aromatic compounds typically present in aviation fuels). The TPHCWG surrogate RfD and RfC values for the aliphatic fractions and the aromatic indicator compounds were utilized to determine the HQs.11 For CR, the aromatic compound-specific ILCR was calculated by multiplying a COC’s ADI by its cancer slope factor (CSF). Among these compounds, only benzene is known to have a regulated (USEPA) CSF (Table 1). When accidental releases of fuel occur, remediation is usually done immediately to recover any free-product or mobile NAPL. Further remediation of any residual NAPL remaining in soil can be done after free-product recovery. If some time passes from the time of release, the residual fuel mixture may become weathered, resulting in a change in its composition. For the forward calculation of toxicity in this study, it was assumed that free product recovery had already removed any mobile NAPL from the soil and that residual unweathered fuel contamination remained in the soil. According to Brost and DeVaull,31 who studied and compiled data from numerous residual fuel contaminated sites, the minimum soil saturation level (Csat) of middle distillate fuels (an ECN range that includes kerosene and kerosene-based fuels) in fine-to-medium grained sandy soils is 9 mg/kg, while the maximum residual saturation level (Cresid) is 8000 mg/kg. These values were set as the minimum and maximum soil concentrations of the aviation fuels considered as they represent the sorptive limit and mobility limit, respectively, of the fuel contamination in soil. A number of intermediate concentrations in sandy soils (50, 100, 500, 1000, and 4000 mg/kg) were also selected to estimate the concentrations at which noncarcinogenic and carcinogenic risks were exceeded by each fuel. The concentration of each COC, fraction or compound, was determined by multiplying the total fuel concentration in soil by its mass percentage in the fuel as C

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Table 3. Weight Percentages Derived from GCxGC-FID Analytical Data from Analysis of Bio-SPK and Jet A Analysis Using UOP Method 965-10 COC Aliphatic ECN > 5−6 ECN > 6−8 ECN > 8−10 ECN > 10−12 ECN > 12−16 ECN > 16−21 remaining aliphatics Aromatic benzene toluene ethylbenzene xylene naphthalene remaining aromatics Unknown TOTAL

SPK1

SPK2

SPK3

Jet A

0.0184 4.6226 37.5522 34.2416 21.6669 0.0017 1.8683

0.0208 1.6816 42.0385 28.9060 25.9790 0.4466 0.7425

0.0000 0.2160 13.4740 25.0644 47.2576 13.2197 0.7089

0.0326 1.3847 13.6245 34.3254 19.0263 0.8098 8.4404

0.0000 0.0000 0.0000 0.0002 0.0000 0.0281 0.0000 100

0.0000 0.0003 0.0006 0.0108 0.0000 0.1685 0.0048 100

0.0000 0.0001 0.0001 0.0007 0.0002 0.0582 0.0000 100

0.0065 0.0867 0.1189 0.5101 0.0932 21.1482 0.3928 100

whole-fuel TPH-based critical PCLs were calculated from target COCspecific soil PCLs by assuming the compositional information of the target COC in the original fuel type to be fixed (Table 3), i.e., assuming the source zone to remain unweathered. From these calculations, the lowest (i.e., most stringent) TPH number or wholefuel PCL was selected as the critical PCL of each fuel. Note that no biodegradation or weathering fate processes were assumed to occur in order to select the most conservative calculations of PCLs. Also, TPHbased critical PCLs were capped at the middle distillate fuel NAPL mobility limit, Cresid, because an exceedance of this threshold would most likely require an immediate corrective action. The reader must take note that the critical PCL levels calculated are Tier 1 screening levels that assume the most conservative conditions. Hence, the development of site-specific critical PCLs must entail additional site investigation. For blends, an upper allowable limit for drop-in fuel blends (i.e., 50%:50% of Bio-SPK1:Jet A by volume) was selected, in which volumes were assumed to be directly summative and densities were assumed to be constant. Conservation of volume for the blend was a good assumption in our case because both petroleum-based Jet A and Bio-SPK fall in the kerosene range, indicating that they contain similar types of compounds. After making this assumption, critical PCLs were calculated as described before.

determined by compositional analysis. Residual fuel contamination was assumed to be homogeneously distributed in the source zone soil. Determination of Critical PCLs. The critical PCL, the lowest or most conservative Tier 1 screening-level soil concentration, is a representation of the maximum concentration of the fuel mixture allowed in the soil, which reduces risk below all acceptable toxicity thresholds. The calculated values for critical PCLs of fuel in soil determine the extent to which contamination can be left in-place without excess human health risk, provided the exposure pathways and exposure scenarios remain the same. Furthermore, the difference between the measured field value of fuel contamination at a given site and its critical PCL determines the extent of remediation required at the site. It must be noted that in calculating Tier 1 screening levels, the most conservative assumptions are left in-place, which favor maximum exposure of the human receptor to the fuel contamination at the source. Assumptions in this vein include no loss from possible weathering effects such as biodegradation and volatilization and soil properties that favor high levels of contaminant migration through environmental media en route to the receptor. The COC-specific PCLs for the four aviation fuels (BIO-SPK1, 2, 3, and Jet A) and a 50:50 blend were back-calculated from the target COC’s most conservative Maximum Contaminant Level (MCL) in groundwater as stipulated by either the WHO26 or the USEPA25 (Table 1), using fate and transport calculations.25,26 The fate and transport model used for determining PCLs was the Soil Attenuation Model (SAM)33,34 for the soil-to-groundwater leaching pathway, the pathway found to be the critical pathway in the toxicity and exposure pathway evaluation exercise. Two different conservative situations were selected for the calculations: (1) the default ASTM RBCA soil parameters, which assume that the entire 3m soil column in the vadose zone below the spill is contaminated,27 and (2) ASTM default parameters with one exception - depth of the contaminated soil source zone changed to a more finite mass loading represented by a thickness of 1 m below ground surface.35 In the SAM model, the depth of contamination parameter controls the mass loading of the contaminants on the transport pathway as the model assumes a continuous infiltration of precipitation. Further details on all default parameters and assumptions utilized in exposure modeling are available in the literature referenced. The COC-specific soil concentrations or PCLs that resulted from direct back-calculations are suitable only when fuel fractions and specific health-risk-driving compounds are measured in soil samples collected at a site in the source zone. Total petroleum hydrocarbon (TPH) measurements are more likely to be conducted at fuel contaminated sites.27 Therefore, whole-fuel TPH-based critical PCLs must be developed for aviation fuel contamination. For this purpose,

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RESULTS AND DISCUSSION

Renewable and Nonrenewable Aviation Jet Fuel Composition. Chemical compositions of the three Bio-SPK fuels (two camelina-based and one jatropha-based designated SPK1, SPK2, and SPK3, respectively) and Jet A were identified and then quantified using GCxGC-FID analysis. The composition analysis data pertaining to the aliphatic and aromatic target COCs as well as any unknown peaks (i.e., aliphatic, aromatic, or unknown) occurring in the chromatograms are presented by their weight percentages in Table 3 for the four aviation fuels tested. Because of the selection of a fixed range of ECN fractions for the aliphatics (ECN > 5−21), the unknown aliphatics were 21. A comparison among aliphatic, aromatic, and unknown fractions for the four fuels clearly shows the high D

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aromatic content (approximately 22%) in the sample of conventional aviation fuel, Jet A, as compared to the samples of Bio-SPKs (12−16) as opposed to the smaller molecular weight aliphatic fractions in camelina Bio-SPK (ECN >8−10)

Figure 1. Distribution of aliphatic fractions analyzed in Bio-SPKs and Jet A by their different equivalent-carbon-number (ECN) ranges. The percentages in the horizontal axis show the total weight percentage of aliphatics in the fuel. The aliphatic drivers for SPK1, SPK2, SPK3, and Jet A are ECN > 8−10, ECN > 8−10, ECN > 12−16, and ECN > 10− 12. Camelina-based (SPK1 and 2) and jatropha-based (SPK3) BioSPKs as well as Jet A show a clear difference in aliphatics distribution, with the dominant fractions being ECN > 8−10, ECN > 12−16, and ECN > 10−12 in camelina Bio-SPK, jatropha BioSPK, and Jet A, respectively.

fraction in camelina-based Bio-SPKs, SPK1 and SPK2, was the ECN > 8−10 fraction, while ECN > 12−16 and ECN > 10−12 fractions are heaviest in jatropha-based Bio-SPK (SPK3) and Jet A, respectively. The type of dominant aliphatic fraction influences the environmental fate and transport properties of fuel contamination. As indicated in Table 2, both the aqueous solubility and the vapor pressure decrease with increasing aliphatic ECN, making the fuel constituents less water-soluble and less volatile, barring any multicomponent cosolvent effects. Figure 2 and Table 3 compare the mass of BTEX compounds and naphthalene in Bio-SPKs to that in Jet A. The aromatic indicator COCs in Bio-SPKs occur in low concentrations compared to those in Jet A. The highest aromatic COC is the Bio-SPK2 (camelina-based) total xylene content at 2.11% of the 5101 ppm amount found in Jet A. The benzene content of BioSPKs is essentially zero, eliminating the possibility of calculable carcinogenic risk as benzene is the only target COC in the list that has an established cancer slope factor. Based on the methodology employed in this study, a calculable carcinogenic risk can arise only from Jet A, in which benzene is present at approximately 65 ppm similar to values reported in the E

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Figure 4. Carcinogenic risk posed by Jet A via the soil-to-groundwater leaching pathway. The carcinogenic risk exceeded the common ILCR regulatory limit of 1 × 10−5 (upper red line) at concentrations as low as 1000 mg/kg of Jet A in soil. The more conservative ILCR of 1 × 10−6 (lower red line) was exceeded at Jet A residual soil concentrations of 100 mg/kg and above.

Figure 3. Pathway-specific hazard indices for the Bio-SPKs and Jet A. For all fuels, the highest hazard indices were those corresponding to the soil-to-groundwater leaching pathway (GW), while the lowest hazard indices were those corresponding to the soil pathway (Soil). The fuel that exhibited the highest hazard index (HI) for the soil-togroundwater leaching pathway was Jet A, while the fuel with the lowest hazard index for the same pathway was Bio-SPK3, the jatropha-based aviation biofuel. Values in parentheses next to the pathway and fuel label indicate the decreasing order of exceedance of the HI of 1. Pathway-Fuel combinations without numbers did not exceed the HI threshold of 1 at any concentration up to the NAPL mobility limit of middle distillate fuels.

Soil Critical PCLs for Jet Fuel Contamination. Fuel critical soil PCLs represent the amount of residual fuel that can be left unrecovered and untreated in soil, without posing an environmental health risk. The most conservative target COCspecific regulatory MCL values in groundwater (Table 1) as well as the ASTM Risk-Based Corrective Action (RBCA) default soil parameters were used in the SAM model for the soil-to-groundwater leaching pathway to calculate the targetCOC-specific soil PCLs. These values are presented in Table 4 for both contamination depths of 3 m and 1 m. The lowest COC-specific PCL values were observed for benzene (1.84 × 10−2 mg/kg), while the highest were observed for the aliphatic ECN > 16−21 fraction (2.65 × 107 mg/kg). In the case of benzene and naphthalene, these results reflect the low

and Jet A (ECN >10−12). The lowest environmental health risk of jatropha derived Bio-SPKs gives some advantage to this crop over camelina, which is being heavily promoted in North America as a biomass feedstock for fuels.38 Carcinogenic risk was posed only by Jet A because of its benzene content, the only target COC that had an established cancer slope factor. This finding has an important implication in the preparation and handling of blends of conventional and renewable aviation jet fuels2,4 as the carcinogenic exposure risk posed by blends will likely be controlled by the conventional fuel content rather than the Bio-SPK. The most significant cancer risk was posed by the soil-to-groundwater leaching pathway (Figure 4), perhaps because of the relatively high solubility of benzene when compared to the other target COCs. The carcinogenic risk exceeded an ILCR of 1 × 10−5, which is commonly used by the United States as a regulatory limit for occupational settings, at residual soil concentrations of 1000 mg/kg of Jet A and higher. The more conservative ILCR of 1 × 10−6 was exceeded at residual soil concentrations of 100 mg/kg and above. The dominant pathway for both the hazard indices and the carcinogenic risk values was found to be the soil-to-groundwater leaching pathway. Hence, this was the pathway selected for calculating soil critical PCLs for the four fuels using a reverse calculation. Jet A was the fuel that was found to be the most harmful to human health among the four fuels analyzed, in terms of both carcinogenic and noncarcinogenic risk. Among the three Bio-SPKs, the camelina-based SPK1 was found to have the highest noncarcinogenic risk. Jet A was the only fuel that is potentially carcinogenic because of its benzene content. It is likely that the benzene content of Jet A will influence the carcinogenicity of its fuel blends with renewable jet fuels, albeit at a lower level.

Table 4. Reverse Calculation of Critical Protective Concentration Levels (PCLs) in Soila soil levels (mg/kg) COC Aliphatic ECN > 5−6 ECN > 6−8 ECN > 8−10 ECN > 10−12 ECN > 12−16 ECN > 16−21 Aromatic benzene toluene ethylbenzene xylene naphthalene

default ASTM (3 m)

affected depth (1 m)

9.32 3.42 4.78 3.59 7.18 8.97

× × × × × ×

1002 1003 1002 1003 1004 1006

2.75 1.01 1.41 1.06 2.12 2.65

× × × × × ×

1003 1004 1003 1004 1005 1007

1.84 5.07 1.04 1.20 3.74

× × × × ×

10−02 1000 1001 1002 10−01

5.43 1.50 3.07 3.53 1.10

× × × × ×

10−02 1001 1001 1002 1000

a

Critical PCLs were calculated from regulated MCLs (Table 1) yield COC-specific (fraction or compound) cleanup values that can be utilized directly if environmental site investigations perform COCspecific analysis on source zone environmental soil samples. Such COC-specific critical PCL values for both a RBCA default 3 m contamination depth and a 1 m contamination depth are presented.

F

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hazard indices are greatly affected by the lighter and more mobile aliphatic ECN fractions, while carcinogenicity is linked to the presence of benzene in the aviation fuel. Finally, the critical soil PCL for the 50/50 blend was inversely related to its Jet A content since this correlated with the presence of benzene in the blend.

regulatory levels allowed for these contaminants in water (Table 1), and for benzene they also reflect the physical and chemical properties that favor its mobility in the environment, such as its high solubility (Table 2). The latter point is corroborated by the high PCL values obtained for the aliphatic ECN > 16−21 fraction, which has transport properties that conversely inhibit its mobility in the environment. In general, the aromatic risk drivers had the most stringent COC-specific soil PCL requirements, with the least conservative or largest value for these compounds (353 mg/kg for xylene, Table 4) being lower than the most conservative or lowest PCL value for the aliphatic fractions (478 mg/kg for ECN > 8−10, Table 4). The critical whole-fuel PCLs for the 4 fuels and a 50/50 (v/ v) blend of Bio-SPK1 and Jet A are presented graphically in Figure 5 for the two respective contamination depths. Benzene

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CONCLUSIONS This study has important implications for the health-risk-based environmental cleanup of aviation biofuels and their blends. Compositional analysis performed with the aim of risk analysis demonstrated the Bio-SPKs to have very low aromatic content when compared to conventional Jet A. Exposure analysis of an unweathered spill in a forward calculation mode indicated soilto-groundwater leaching pathway to be the dominant migration pathway for camelina-based Bio-SPKs and conventional petroleum-derived Jet A but not jatropha Bio-SPK. Critical soil PCLs for the fuels calculated in this study can possibly serve as initial Tier 1 screening-level cleanup end points for the remediation of recent unweathered spills of aviation biofuels and their drop-in blends with conventional petroleum-based fuels. Based on our results, cleanup costs of any aviation biofuel spills are expected to be substantially lower than those for conventional aviation fuels because of their higher critical PCLs. Overall, these findings can help shape preliminary governmental regulations pertaining to the handling, storage, transport, and remediation of aviation biofuels and their blends, prior to the introduction of Bio-SPKs to the market. Once introduced, additional case- and site-specific studies would be needed to characterize on-the-ground uncertainty using more comprehensive compositional analysis of Bio-SPKs and variations in assumptions for exposure modeling to calculate more site- and condition-specific cleanup levels.

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Figure 5. Comparison of the whole-fuel critical PCLs among all aviation fuels considered, including the 50%−50% (v/v) blend of BioSPK1 and Jet A. Darker bars show the ASTM RBCA default of 3 m for contamination thickness as opposed to 1 m for the lighter bars. Jet A was found to have the lowest and most conservative cleanup level driven by its carcinogenic benzene content. Among the Bio-SPKs, the critical PCLs were controlled by the ECN > 8−10 aliphatic fraction, with Bio-SPK2 (camelina-based) and Bio-SPK3 (jatropha-based) fuels posing the most and the least hazard, respectively. The red bar signifies the cap level of 8000 mg/kg, the mobility limit of middle distillates in fine to medium grained sands.31 The critical PCL for Bio-SPK3 at 1 m contamination depth was capped at the middle distillate mobility limit of 8000 mg/kg, because its calculated value exceeded this threshold.

AUTHOR INFORMATION

Corresponding Author

*Phone: +971-2-810-9114. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research work was funded and supported by the Masdar Institute. The authors also acknowledge support and approval from Honeywell UOP management for this research.

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controlled the critical PCL of Jet A and its blends with renewable jet fuels, while the aliphatic ECN > 8−10 fraction controlled the critical PCLs of Bio-SPKs in soil. The results show that the critical PCL for pure Jet A is approximately an order of magnitude lower than that of the Bio-SPKs in the 3 m depth scenario, indicating that Jet A is significantly more harmful to human health than the Bio-SPKs, and, consequently, it must be cleaned up to a much more stringent cleanup level. All Bio-SPKs’ whole-fuel critical soil PCLs were four to 12 times greater than the critical PCL of Jet A, implying that the Bio-SPKs are much safer than conventional aviation fuels. The Bio-SPK results further show that the jatropha-based Bio-SPK (SPK3) had critical PCLs that were almost three times higher than those of the camelina-based Bio-SPKs and, in fact, exceeded the NAPL mobility limit of Cresid at the lower contamination depth of 1 m. These findings further reiterate the results presented in previous sections, which indicated that

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