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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
Modified from Douglas et al. (2014) Introduction to Environmental Forensics, Elsevier, New York.
Conventional Lab
Fingerprint
Forensic Lab Fingerprint
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
Environmental Forensics
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 Peel the Onion!
Priority Pollutants
Diagnostic, Non-
priority Pollutants
Tiered Approach to Chemical Fingerprinting of Hydrocarbons
General Characterization
8015M GC/FID (C9+)
GC/FID/MS (C4-C44)
TIER 1 High-resolution “fingerprint”
TPH, DRO, ORO, PHI
Contamination vs. Natural OM Hydrocarbon Product ID
Overall Weathering
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
Fuel, lube, waste specifics
Quantitative comparative analysis, weathering & mixture assessment
Detailed Characterization
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
Tier 1: What is it? TPH Interpretations
Diesel MGP Tar
Lube Oil
Tier 1: Not all TPH is contamination
Naturally-occurring organic matter
Coal ash
IS
IS
IS
29
31 27
25
Bacterial membrane debris
Plant waxes
Plant resins
Soil with 2000 mg/kg TPH
OTP
ANDROS
TANE
IS
IS
Soil with 1800 mg/kg TPH
Tier 2: Gasoline/PIANO Fingerprinting
• PIANO data (~90 analytes) can reveal meaningful differences – Weathering – General and
specific blending practices
C5 C13
alkylate
reformate
isomerate
straight-run
reformate
isopentane Methyl-naphthalenes
Former Site
Active Site
Gasoline Case Study
• 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
• 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
A
B
A
B
More weathered More SRG 1.6 glpg %Iso ~ 40 (H2SO4)
Less weathered Less SRG 0.15 glpg %Iso ~ 58 (HF)
distinct trimethylpentane isomer patterns
Gasoline Case Study
• Mixing model based on alkylate type used to estimate volume allocation
A
B
Distillate Fingerprinting
• Modified EPA Method 8015 (Tier 1) – whole oil and SHC
• Modified EPA Method 8270 (Tier 2) – Alkylated PAH – Sulfur-containing
aromatics – Low boiling
Biomarkers
Stoddard Solvent
Kerosene
Jet A
Diesel #2
sesquiterpanes
Diesel Case Study
• underground pipeline failure prompts investigation/clean-up in industrial area
Pipeline Product Pr/Ph ~ 2.0
Excavation Pr/Ph ~ 2.0
Nearby Storm Sewer
Pr/Ph ~ 2.0
Tier 1 GC/FID chromatograms (8015M)
Diesel Case Study
• nearby storm sewer diesel contains higher sulfur aromatics
Nearby Storm Sewer
DBT2/PA2: 0.40 DBT3/PA3: 0.57
Excavation DBT2/PA2: 0.29 DBT3/PA3: 0.43
Pipeline Product DBT2/PA2: 0.29 DBT3/PA3: 0.44
dibenzothiophenes phenanthrenes
Tier 2: 52 PAH-related analytes (8270M) 6-rings 2-rings
( )
Diesel Case Study
• nearby storm sewer contains distinct sesquiterpane biomarkers
Nearby Storm Sewer
Excavation
Pipeline Product
Tier 2: m/z 123 extracted ion profiles (8270M)
9 10
1
8
6
2 3
4
5 7
Abbrev. Compound Name/Group Abbrev. Compound Name/GroupD0 cis/trans-Decalin DBT0 DibenzothiopheneD1 C1-Decalins DBT1 C1-DibenzothiophenesD2 C2-Decalins DBT2 C2-DibenzothiophenesD3 C3-Decalins DBT3 C3-DibenzothiophenesD4 C4-Decalins DBT4 C4-DibenzothiophenesBT0 Benzothiophene BF Benzo(b)fluoreneBT1 C1-Benzo(b)thiophenes FL0 FluorantheneBT2 C2-Benzo(b)thiophenes PY0 PyreneBT3 C3-Benzo(b)thiophenes FP1 C1-Fluoranthenes/PyrenesBT4 C4-Benzo(b)thiophenes FP2 C2-Fluoranthenes/PyrenesN0 Naphthalene FP3 C3-Fluoranthenes/PyrenesN1 C1-Naphthalenes FP4 C4-Fluoranthenes/PyrenesN2 C2-Naphthalenes NBT0 NaphthobenzothiophenesN3 C3-Naphthalenes NBT1 C1-NaphthobenzothiophenesN4 C4-Naphthalenes NBT2 C2-NaphthobenzothiophenesB Biphenyl NBT3 C3-NaphthobenzothiophenesDF Dibenzofuran NBT4 C4-NaphthobenzothiophenesAY Acenaphthylene BA0 Benz[a]anthraceneAE Acenaphthene C0 Chrysene/TriphenyleneF0 Fluorene BC1 C1-ChrysenesF1 C1-Fluorenes BC2 C2-ChrysenesF2 C2-Fluorenes BC3 C3-ChrysenesF3 C3-Fluorenes BC4 C4-ChrysenesA0 Anthracene BBF Benzo[b]fluorantheneP0 Phenanthrene BJKF Benzo[j]fluoranthene/Benzo[k]fluoranthenePA1 C1-Phenanthrenes/Anthracenes BAF Benzo[a]fluoranthenePA2 C2-Phenanthrenes/Anthracenes BEP Benzo[e]pyrenePA3 C3-Phenanthrenes/Anthracenes BAP Benzo[a]pyrenePA4 C4-Phenanthrenes/Anthracenes PER PeryleneRET Retene IND Indeno[1,2,3-cd]pyrene
DA Dibenz[ah]anthracene/Dibenz[ac]anthraceneGHI Benzo[g,h,i]perylene
Comparison of Methods PAH-based (EPA 8270)
Parent PAH
Alkylated PAHs
C1-
C2-
C3-
C4-
Extended PAHs
Examples of PAH Fingerprinting
Pyrogenic II • Alkyl < Parent • High 4 to 6 Ring
Pyrogenic I • Alkyl < Parent • High 2 and 3 Ring
Petrogenic • Alkyl > Parent • Little 4 to 6 Ring
MGP Tar
Urban Runoff
2 3 4 5-6 O Rings
N0
N1
N2
N3
N4 B
DF
AY
AE
F0
F1
F2
F3
A0
P0
PA1
PA2
PA3
PA4
DBT
0 D
BT1
DBT
2 D
BT3
DBT
4 FL
0 PY
0 FP
1 FP
2 FP
3 FP
4 N
BT0
NBT
1 N
BT2
NBT
3 N
BT4
BA0
C0
BC1
BC2
BC3
BC4
BB
BJK BB
BE
P BA
P IN
D
DA
GH
I PE
R
RET
BF
2 3 4 5-6 O Rings
“bell-shaped” patterns
“skewed” patterns
Petroleum
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
PAH Case Study
• PAHs sources can be more confidently determined when TPH is understood
• Tier 1 TPH fingerprinting via 8015M revealed four distinct hydrocarbon sources
GRO RRO DRO
PAH Case Study 1090 mg/kg TPH
40 mg/kg TPH 0.2 mg/kg TPAH51 0.06 mg/kg TPAH16
0.03 mg/kg cPAH
1600 mg/kg TPH 33 mg/kg TPAH51 2.0 mg/kg TPAH16 0.33 mg/kg cPAH
900 mg/kg TPH 3.4 mg/kg TPAH51 0.43 mg/kg TPAH16
0.19 mg/kg cPAH
35 mg/kg TPAH51 19 mg/kg TPAH16
2.4 mg/kg cPAH
Fluoranthenes/ Pyrenes cPAH
cPAH
Phenanthrenes/ Anthracenes
Naphthalenes
PAH Case Study
MGP Tar
Combustion Residue/Ash
Diesel Fuel
Asphalt
PAH Case Study
• Spilled petroleum was a limited source of cPAH
• Historic fill (MGP tar and ash) from canal dredging is dominant source of cPAH
Increasingly Pyrogenic
Surface Soils
Increasingly Pyrogenic
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
Gasoline additives (concentration vs. presence/absence)
Blending Practices Sulfur content Lead Isotopes 206Pb/207Pb Degree of Weathering
(simple ratios, volatiles)
Common Approaches
Regulatory Limits on Lead in Gasoline
Leaded Unleaded1926 3.17 Surgeon General1959 4.23 Surgeon General
Jul-74 0.05b Federal Register 38(6), Part II, Jan. 10, 1973
Oct-82 1.1a
Jul-85 0.5a
Jan-86 0.1Jan-92 banned in CAJan-96 banned nationwide Federal Register, 1990
Leaded UnleadedJan-76 3.0 0.05Jan-87 1.1Dec-90 banned nationwideDec-90 0.1c
aaverage quarterly leaded gasoline productionbincidental lead in unleaded gasolineconly permitted in off-highway and marine use
Date
RegulationDate
Clean Air Act, Section 22, Canada Gazette, Part II, 108(15), Aug. 14, 1974
Federal Register, June 8, 1977
Canada
United States Regulation
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)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
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
glpg
(avg
.)
REGULARPREMIUM
Regional Datasets show considerable ‘scatter’ Lead in Motor Gasoline Survey 1960-1987 (District 2: Mid-Atlantic Coast Region)
0
0.5
1
1.5
2
2.5
3
3.5S
umm
er 1
960
Win
ter 1
960-
Sum
mer
196
1W
inte
r 196
1-S
umm
er 1
962
Win
ter 1
962-
Sum
mer
196
3W
inte
r 196
3-S
umm
er 1
964
Win
ter 1
964-
Sum
mer
196
5W
inte
r 196
5-S
umm
er 1
966
Win
ter 1
966-
Sum
mer
196
7W
inte
r 196
7-S
umm
er 1
968
Win
ter 1
968-
Sum
mer
196
9W
inte
r 196
9-S
umm
er 1
970
Win
ter 1
970-
Sum
mer
197
1W
inte
r 197
1-S
umm
er 1
972
Win
ter 1
972-
Sum
mer
197
3W
inte
r 197
3-S
umm
er 1
974
Win
ter 1
974-
Sum
mer
197
5W
inte
r 197
5-S
umm
er 1
976
Win
ter 1
976-
Sum
mer
197
7W
inte
r 197
7-S
umm
er 1
978
Win
ter 1
978-
Sum
mer
197
9W
inte
r 197
9-S
umm
er 1
980
Win
ter 1
980-
Sum
mer
198
1W
inte
r 198
1-S
umm
er 1
982
Win
ter 1
982-
Sum
mer
198
3W
inte
r 198
3-S
umm
er 1
984
Win
ter 1
984-
Sum
mer
198
5W
inte
r 198
5-S
umm
er 1
986
Win
ter 1
986-
g/ga
l (av
g.)
Regular
Premium
11,382 Regular gasolines9,448 Premium gasolines
Avg. ± 1σ
Blending and Lead Content Changes Coincident in 1970s
MTBE
CA ban
NY ban
O2 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
Blending Practices Sulfur content Hydrotreating Biodiesel Degree of Weathering
(simple ratios)
Common Approaches
Sulfur Concentration (Avg) On-Road Diesels
High Sulfur Era
Low Sulfur
Era Ultra-Low Sulfur Era
Distillate Hydrotreatment
No Desulfurization
Hydrodesulfurized
( )
( )
( )
( )
4
1 2
3
4
3
4,6
2,4
2,6
3,6
2,8 2,7 3,7
1,4 1,6 1,8
1,3 3,4 1,7 1,9
2,3 1,2
3E
4,6
3,6
1,4 1,6 1,8
3E
2,4,6
2,4,7 2,4,8
1,4,7
1,3,7
3,4,7
2,4,6
2,4,7 2,4,8
1,4,7
1,3,7
160 mg/kg
178 mg/kg
125 mg/kg
22.9 mg/kg (85% decrease)
45.7 mg/kg (74% decrease)
46.4 mg/kg (62% decrease)
OTP
OTP
A
B
C
Christensen & Larsen Model • Weathering-based “age-dating” method
Age from Historical Records (Years)
2219181817141211998
0.5
Table 1Location, Type of Installation,
and Age of Known Diesel Oil Spills
Location Name Type of Installation
Provestenen, DK Oil TerminalHengelo, depot, NL Oil TerminalFredericia, DK Oil TerminalIshoj, DK Service StationHaarlem, NL Service StationVanlose, DK Service StationHorsholm, DK Service StationNieuwesluis, NL Oil TerminalBrunnik, NL Service StationHengelo, loading rack, NL Oil Terminal
*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.
Thisted, DK Service StationEjby, DK Heating Oil Tank*
Christensen & Larsen (1993). Method for determining the age of diesel oil spills in the soil. Ground Water Monitoring & Remediation. 13(4); 142-149.
Premise to Christensen & Larsen
FRESH DIESEL abundant n-alkanes
n-C17/Pristane ~ 1.4
C14
C10 C20
IS IS
IS IS
IS
IS
IS
IS
BIODEGRADED DIESEL no n-alkanes
n-C17/Pristane ~ 0 nPr
Ph
Pr
nPr Ph
Pr
C17
n-Alkanes are more susceptible to biodegradation than acyclic isoprenoids TRUE
Pr
C17
Pr
C17
T (yr) = -8.4(n -C17/Pr) + 19.8Kaplan et al. (1995)
0
4
8
12
16
20
24
0 0.4 0.8 1.2 1.6 2 2.4
n -C17/pristane ratio
Age
of t
he D
iese
l Spi
ll
Data points visually picked from Christensen and Larsen (1993) Figure 4.
Christensen & Larsen Model
Kaplan et al. (1995). Pattern of chemical changes in fugitive hydrocarbon fuels in the Environment. SPE Paper No. 29754.
11.4 ± 2.1 yrs.
nC17/Pr = 1
Principal Critique of C&L Model • Too many site-specific variables control rate(s) of
biodegradation to expect a single, universal rate – O2, 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 long-
term release has occurred
Stout et al. (2002). Invited commentary on the Christensen and Larsen Technique. Environ. Forensics 3:9-11.
T (yr) = -8.4(n -C17/Pr) + 19.8Kaplan et al. (1995)
0
4
8
12
16
20
24
0 0.4 0.8 1.2 1.6 2 2.4
n -C17/pristane ratio
Age
of t
he D
iese
l Spi
ll
Data points visually picked from Christensen and Larsen (1993) Figure 4.
Elegantly Simple or Overly Simple
? ?
?
?
?
?
?
?
? ?
1.98 ± 0.83
? r2 = 0.89
r2 = 0.66
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
[email protected] (508) 380-8618
Scott Stout, Ph.D. NewFields
[email protected] (781) 681-5040 X105