Use of Forensics in Petroleum Spill Cases NYSBA Oil Spill Symposium June 7, 2017 Jim Occhialini Alpha Analytical Scott A. Stout, Ph.D. NewFields, Rockland MA
Topics for Discussion Introduction Chemical fingerprinting Gasoline case study Diesel case study PAH case study Age-dating
Introduction About Alpha Analytical Conventional & Specialty Laboratory Services Advanced hydrocarbon analysis Saturated hydrocarbons Alkylated PAHs Geochemical biomarkers PIANO PHI About NewFields Environmental Forensics Consultants/Experts (technical and litigation) Frequent collaboration with Alpha Analytical Industrial and governmental clients
Introduction to Petroleum Analysis What s your application? Regulatory compliance Generally a quantitative determination i.e. TPH Lots of methods Risk assessment Quantitative, but can have qualitative aspects Risk based corrective action (RBCA) ITRC TPH Workgroup Qualitative determinations What is it? Routine ( & not so routine ) product identification Whose is it? Forensic / source allocation
Qualitative Analysis Routine Environmental Lab Fingerprinting Methods can identify - Presence or absence of common products ID based on pattern recognition Forest vs. trees Limitations ~ 20 minute chromatographic run time Trouble with mixtures, weathered samples Unknown product ID
Conventional Lab Fingerprint Forensic Lab Fingerprint Modified from Douglas et al. (2014) Introduction to Environmental Forensics, Elsevier, New York.
Environmental Forensics WHAT and WHERE? Unambiguous contaminant identification(s) Well-defined spatial extent of contaminant(s) WHEN and WHO? Age-dating of contaminant(s) Defensible Allocation of Responsibility Integrated Approach Chemical Fingerprinting Site/Regulatory History Process Forensics Geology and Hydrology Transport Modeling Numerical Analysis Allocation
Limitations of Standard (SW-846) Methods Standard methods were developed to establish nature and extent of prescribed lists of COPCs Priority pollutant chemicals (n=~130) are only a subset of chemicals contained in complex mixtures of products released into the environment Many co-occurring, nonpriority, pollutant chemicals provide clues as to the source of the priority pollutant chemicals Priority Pollutants Peel the Onion! Diagnostic, Nonpriority Pollutants
Tiered Approach to Chemical Fingerprinting of Hydrocarbons General Characterization 8015M GC/FID (C 9 +) GC/FID/MS (C 4 -C 44 ) TIER 1 High-resolution fingerprint TPH, DRO, ORO, PHI Contamination vs. Natural OM Hydrocarbon Product ID Overall Weathering Detailed Characterization TIER 2 Detailed quantitative fingerprint VOC: PIANO, ethers, ethanol, alkyl lead SVOC: PAHs, Alkyl-PAHs, Sulfur-PAHs, PAH isomers, HPAHs, decalins, n- alkylcyclohexanes, biomarkers, biodiesels 8260M P&T GC/MS (PIANO/Ethers) 8270M GC/MS Alkyl Lead Ethanol 8270M GC/MS-SIM PAHs et al. 8270M GC/MS-SIM Biomarkers Diamondoids FAMEs Fuel, lube, waste specifics Quantitative comparative analysis, weathering & mixture assessment
Tier 1: What is it? TPH Interpretations Diesel MGP Tar Lube Oil
Tier 1: Not all TPH is contamination Soil with 2000 mg/kg TPH IS 29 IS Plant resins IS 25 Plant waxes 27 31 Bacterial membrane debris Naturally-occurring organic matter Soil with 1800 mg/kg TPH IS OTP IS ANDROSTANE Coal ash
Tier 2: Gasoline/PIANO Fingerprinting PIANO data (~90 analytes) can reveal meaningful differences Weathering General and specific blending practices C5 isopentane straight-run isomerate alkylate reformate reformate C13 Methylnaphthalenes
Gasoline Case Study Former Site Active Site Former site with historic impacts observes NAPL increase; suspected impact from upgradient active site NAPLs (10) and active site dispensed gasolines (3) analyzed via modified EPA Methods 8015, 8260 (PIANO), and 8270 (organic lead).
Gasoline Case Study More weathered More SRG 1.6 glpg %Iso ~ 40 (H 2 SO 4 ) A A B Less weathered Less SRG 0.15 glpg %Iso ~ 58 (HF) distinct trimethylpentane isomer patterns B differences in degree of weathering, SRG abundance, and lead concentrations are evident specific alkylate type (%Iso) differences (independent of weathering) are also evident alkylate type varies by refining process
Gasoline Case Study A B Mixing model based on alkylate type used to estimate volume allocation
Distillate Fingerprinting Stoddard Solvent Kerosene Jet A Diesel #2 Modified EPA Method 8015 (Tier 1) whole oil and SHC Modified EPA Method 8270 (Tier 2) Alkylated PAH Sulfur-containing aromatics Low boiling Biomarkers sesquiterpanes
Diesel Case Study Pipeline Product Pr/Ph ~ 2.0 Excavation Pr/Ph ~ 2.0 Nearby Storm Sewer Pr/Ph ~ 2.0 underground pipeline failure prompts investigation/cleanup in industrial area Tier 1 GC/FID chromatograms (8015M)
Diesel Case Study Pipeline Product DBT2/PA2: 0.29 phenanthrenes DBT3/PA3: 0.44 dibenzothiophenes Excavation DBT2/PA2: 0.29 DBT3/PA3: 0.43 nearby storm sewer diesel contains higher sulfur aromatics Nearby Storm Sewer DBT2/PA2: 0.40 DBT3/PA3: 0.57 2-rings 6-rings Tier 2: 52 PAH-related analytes (8270M)
( ) Diesel Case Study 1 Pipeline Product 9 10 2 3 4 8 5 6 7 Excavation Nearby Storm Sewer nearby storm sewer contains distinct sesquiterpane biomarkers Tier 2: m/z 123 extracted ion profiles (8270M)
Comparison of Methods PAH-based (EPA 8270) Abbrev. Compound Name/Group Abbrev. Compound Name/Group D0 cis/trans-decalin DBT0 Dibenzothiophene D1 C1-Decalins DBT1 C1-Dibenzothiophenes D2 C2-Decalins DBT2 C2-Dibenzothiophenes D3 C3-Decalins DBT3 C3-Dibenzothiophenes D4 C4-Decalins DBT4 C4-Dibenzothiophenes BT0 Benzothiophene BF Benzo(b)fluorene BT1 C1-Benzo(b)thiophenes FL0 Fluoranthene BT2 C2-Benzo(b)thiophenes PY0 Pyrene BT3 C3-Benzo(b)thiophenes FP1 C1-Fluoranthenes/Pyrenes BT4 C4-Benzo(b)thiophenes FP2 C2-Fluoranthenes/Pyrenes N0 Naphthalene FP3 C3-Fluoranthenes/Pyrenes N1 C1-Naphthalenes FP4 C4-Fluoranthenes/Pyrenes N2 C2-Naphthalenes NBT0 Naphthobenzothiophenes N3 C3-Naphthalenes NBT1 C1-Naphthobenzothiophenes N4 C4-Naphthalenes NBT2 C2-Naphthobenzothiophenes B Biphenyl NBT3 C3-Naphthobenzothiophenes DF Dibenzofuran NBT4 C4-Naphthobenzothiophenes AY Acenaphthylene BA0 Benz[a]anthracene AE Acenaphthene C0 Chrysene/Triphenylene F0 Fluorene BC1 C1-Chrysenes F1 C1-Fluorenes BC2 C2-Chrysenes F2 C2-Fluorenes BC3 C3-Chrysenes F3 C3-Fluorenes BC4 C4-Chrysenes A0 Anthracene BBF Benzo[b]fluoranthene P0 Phenanthrene BJKF Benzo[j]fluoranthene/Benzo[k]fluoranthene PA1 C1-Phenanthrenes/Anthracenes BAF Benzo[a]fluoranthene PA2 C2-Phenanthrenes/Anthracenes BEP Benzo[e]pyrene PA3 C3-Phenanthrenes/Anthracenes BAP Benzo[a]pyrene PA4 C4-Phenanthrenes/Anthracenes PER Perylene RET Retene IND Indeno[1,2,3-cd]pyrene DA Dibenz[ah]anthracene/Dibenz[ac]anthracene GHI Benzo[g,h,i]perylene Parent PAH Alkylated PAHs C1- C2- C3- C4-
Examples of PAH Fingerprinting Petrogenic Alkyl > Parent Little 4 to 6 Ring Extended PAHs bell-shaped patterns Petroleum Rings 2 3 4 5-6 O Pyrogenic I Alkyl < Parent High 2 and 3 Ring skewed patterns MGP Tar Rings 2 3 4 5-6 O Pyrogenic II Alkyl < Parent High 4 to 6 Ring Urban Runoff N0 N1 N2 N3 N4 B DF AY AE F0 F1 F2 F3 A0 P0 PA1 PA2 PA3 PA4 DBT0 DBT1 DBT2 DBT3 DBT4 FL0 PY0 FP1 FP2 FP3 FP4 NBT0 NBT1 NBT2 NBT3 NBT4 BA0 C0 BC1 BC2 BC3 BC4 BB BJK BB BEP BAP IND DA GHI PER RET BF
PAH Case Study Former fuel storage facility located in industrial area along canal cpah source(s) in surface soils elevated and attributed to spilled fuel by regulator Chemical fingerprinting study conducted to evaluate source(s) of PAH in surface soils Tier 1: 8015M Tier 2: 8270M
GRO DRO PAH Case Study RRO PAHs sources can be more confidently determined when TPH is understood Tier 1 TPH fingerprinting via 8015M revealed four distinct hydrocarbon sources
PAH Case Study 1090 mg/kg TPH Phenanthrenes/ Anthracenes 35 mg/kg TPAH 51 19 mg/kg TPAH 16 2.4 mg/kg cpah Fluoranthenes/ Pyrenes cpah 40 mg/kg TPH 0.2 mg/kg TPAH 51 0.06 mg/kg TPAH 16 0.03 mg/kg cpah cpah 1600 mg/kg TPH Naphthalenes 33 mg/kg TPAH 51 2.0 mg/kg TPAH 16 0.33 mg/kg cpah 900 mg/kg TPH 3.4 mg/kg TPAH 51 0.43 mg/kg TPAH 16 0.19 mg/kg cpah
PAH Case Study MGP Tar Combustion Residue/Ash Diesel Fuel Asphalt
PAH Case Study Surface Soils Increasingly Pyrogenic Increasingly Pyrogenic Spilled petroleum was a limited source of cpah Historic fill (MGP tar and ash) from canal dredging is dominant source of cpah
Age-Dating of Gasoline Contamination Never simple Mixing always confounding Chemistry is not magic Constrain the age thru combination of: chemistry site or regulatory history F&T modeling Common Approaches Gasoline additives (concentration vs. presence/absence) Blending Practices Sulfur content Lead Isotopes 206 Pb/ 207 Pb Degree of Weathering (simple ratios, volatiles)
Regulatory Limits on Lead in Gasoline Date United States Leaded Unleaded Regulation 1926 3.17 Surgeon General 1959 4.23 Surgeon General Jul-74 0.05 b Federal Register 38(6), Part II, Jan. 10, 1973 Oct-82 1.1 a Federal Register, June 8, Jul-85 0.5 a 1977 Jan-86 0.1 Jan-92 banned in CA Jan-96 banned nationwide Federal Register, 1990 Date Leaded Canada Unleaded Jan-76 3.0 0.05 Jan-87 1.1 Dec-90 banned nationwide Dec-90 0.1 c a average quarterly leaded gasoline production Regulation Clean Air Act, Section 22, Canada Gazette, Part II, 108(15), Aug. 14, 1974 b incidental lead in unleaded gasoline c only permitted in off-highway and marine use Stout et al. (2006) Automotive Gasoline. Environmental Forensics, Academic Press, p. 465-531.
Lead Concentration (Avg) LEAD IN LEADED GASOLINES - 1946-1987 (data from Dickson et al., 1987; Shelton et al. 1982) 3.5 3.0 REGULAR PREMIUM glpg (avg.) 2.5 2.0 1.5 1.0 0.5 0.0 Winter 1946 Winter 1947 Winter 1948 Winter 1949 Winter 1950 Winter 1951 Winter 1952 Winter 1953 Winter 1954 Winter 1955 Winter 1956 Winter 1957 Winter 1958 Winter 1959 Winter 1960 Winter 1961 Winter 1962 Winter 1963 Winter 1964 Winter 1965 Winter 1966 Winter 1967 Winter 1968 Winter 1969 Winter 1970 Winter 1971 Winter 1972 Winter 1973 Winter 1974 Winter 1975 Winter 1976 Winter 1977 Winter 1978 Winter 1979 Winter 1980 Winter 1981 Winter 1982 Winter 1983 Winter 1984 Winter 1985 Winter 1986
Regional Datasets show considerable scatter 3.5 Lead in Motor Gasoline Survey 1960-1987 (District 2: Mid-Atlantic Coast Region) Regular 3 Premium 2.5 Avg. ± 1σ g/gal (avg.) 2 1.5 1 0.5 0 11,382 Regular gasolines 9,448 Premium gasolines Summer 1960 Winter 1960- Summer 1961 Winter 1961- Summer 1962 Winter 1962- Summer 1963 Winter 1963- Summer 1964 Winter 1964- Summer 1965 Winter 1965- Summer 1966 Winter 1966- Summer 1967 Winter 1967- Summer 1968 Winter 1968- Summer 1969 Winter 1969- Summer 1970 Winter 1970- Summer 1971 Winter 1971- Summer 1972 Winter 1972- Summer 1973 Winter 1973- Summer 1974 Winter 1974- Summer 1975 Winter 1975- Summer 1976 Winter 1976- Summer 1977 Winter 1977- Summer 1978 Winter 1978- Summer 1979 Winter 1979- Summer 1980 Winter 1980- Summer 1981 Winter 1981- Summer 1982 Winter 1982- Summer 1983 Winter 1983- Summer 1984 Winter 1984- Summer 1985 Winter 1985- Summer 1986 Winter 1986-
Blending and Lead Content Changes Coincident in 1970s
MTBE CA ban NY ban O 2 min. lifted
Age-Dating of Diesel Contamination Never simple Mixing always confounding Chemistry is not magic Constrain the age thru combination of: chemistry site or regulatory history F&T modeling Common Approaches Blending Practices Sulfur content Hydrotreating Biodiesel Degree of Weathering (simple ratios)
Sulfur Concentration (Avg) On-Road Diesels High Sulfur Era Low Sulfur Era Ultra-Low Sulfur Era
Distillate Hydrotreatment No Desulfurization Hydrodesulfurized ( ) A 4 160 mg/kg 4 OTP 22.9 mg/kg (85% decrease) 3 3 2 OTP 1 B 3E 4,6 3,6 2,6 2,4 2,8 2,7 3,7 1,4 1,6 1,8 178 mg/kg 1,3 3,4 1,7 1,9 2,3 1,2 3E ( ) 4,6 3,6 1,4 1,6 1,8 45.7 mg/kg (74% decrease) C 2,4,6 ( ) 2,4,7 2,4,8 1,3,7 1,4,7 125 mg/kg 3,4,7 2,4,6 ( ) 2,4,7 2,4,8 1,4,7 1,3,7 46.4 mg/kg (62% decrease)
Christensen & Larsen Model Weathering-based age-dating method Location Name Table 1 Location, Type of Installation, and Age of Known Diesel Oil Spills Provestenen, DK Hengelo, depot, NL Fredericia, DK Ishoj, DK Haarlem, NL Vanlose, DK Horsholm, DK Nieuwesluis, NL Brunnik, NL Hengelo, loading rack, NL Thisted, DK Ejby, DK Type of Installation Oil Terminal Oil Terminal Oil Terminal Service Station Service Station Service Station Service Station Oil Terminal Service Station Oil Terminal Service Station Heating Oil Tank* Age from Historical Records (Years) 22 19 18 18 17 14 12 11 9 9 8 0.5 Christensen & Larsen (1993). Method for determining the age of diesel oil spills in the soil. Ground Water Monitoring & Remediation. 13(4); 142-149. *The site was included because the location was in all respects similar to the other locations. Heating and diesel oils are basically the same, except for additives.
Premise to Christensen & Larsen n-alkanes are more susceptible to biodegradation than acyclic isoprenoids TRUE C10 C14 C17 IS Pr npr Ph IS C20 IS IS C17 Pr FRESH DIESEL abundant n-alkanes n-c17/pristane ~ 1.4 Pr IS IS Pr BIODEGRADED DIESEL no n-alkanes n-c17/pristane ~ 0 npr Ph IS IS C17
Christensen & Larsen Model 24 20 Age of the Diesel Spill 16 12 8 11.4 ± 2.1 yrs. T (yr) = -8.4(n -C 17 /Pr) + 19.8 Kaplan et al. (1995) 4 0 Data points visually picked from Christensen and Larsen (1993) Figure 4. nc17/pr = 1 0 0.4 0.8 1.2 1.6 2 2.4 n -C 17 /pristane ratio Kaplan et al. (1995). Pattern of chemical changes in fugitive hydrocarbon fuels in the Environment. SPE Paper No. 29754.
Principal Critique of C&L Model Too many site-specific variables control rate(s) of biodegradation to expect a single, universal rate O 2, nutrient availability, etc. NAPL mass/concentration Insufficient data presented by C&L to evaluate correlation/statistics Starting ratio of spilled fuels vary Almost never know if a single, multiple, or longterm release has occurred Stout et al. (2002). Invited commentary on the Christensen and Larsen Technique. Environ. Forensics 3:9-11.
Elegantly Simple or Overly Simple Age of the Diesel Spill 24 20 16 12 8 4 0??? r 2 = 0.89 Data points visually picked from Christensen and Larsen (1993) r 2 Figure = 0.66 4.? T (yr) = -8.4(n -C 17 /Pr) + 19.8 Kaplan et al. (1995)???? 0 0.4 0.8 1.2 1.6 2 2.4 n -C 17 /pristane ratio 1.98 ± 0.83?
Conclusions Environmental forensics (what, who, when?) requires appropriate data and interpretation Tiered analytical approach whose design depends on questions/ objectives Integration of good data with knowledgeable interpretation yields greater defensibility in conclusions
Questions? Jim Occhialini Alpha Analytical jocchialini@alphalab.com (508) 380-8618 Scott Stout, Ph.D. NewFields sstout@newfields.com (781) 681-5040 X105