Page 1

Screening Level Assessment of Risks Due to Dioxin Emissions

from Burning Oil from the BP Deepwater Horizon Gulf of Mexico Spill

John Schaum1*

, Mark Cohen3, Steven Perry2, Richard Artz3, Roland Draxler3, Jeffrey B. 

Frithsen1, David Heist2, Matthew Lorber

1

, and Linda Phillips1

1

U.S. EPA, Office of Research and Development, Washington, DC

2

U.S. EPA, Office of Research and Development, RTP, NC

3

NOAA, Air Resources Laboratory, Silver Spring, MD

*

Corresponding author e-mail: schaum.john@epa.gov: phone (703) 347- 8623; fax (703) 347-

8690

ABSTRACT

Between April 28 and July 19 of 2010, the US Coast Guard conducted in situ oil burns as one 

approach used for the management of oil spilled after the explosion and subsequent sinking of 

the BP Deepwater Horizon platform in the Gulf of Mexico. The purpose of this paper is to 

describe a screening level assessment of the exposures and risks posed by the dioxin emissions 

from these fires. Using upper estimates for the oil burn emission factor, modeled air and fish 

concentrations, and conservative exposure assumptions, the potential cancer risk was estimated 

for three scenarios: inhalation exposure to workers, inhalation exposure to residents on the 

mainland, and fish ingestion exposures to residents. U.S. EPA’s AERMOD model was used to 

estimate air concentrations in the immediate vicinity of the oil burns and NOAA’s HYSPLIT 

model was used to estimate more distant air concentrations and deposition rates. The lifetime 

incremental cancer risks were estimated as 6 x 10-8 for inhalation by workers, 6 x 10-12 for 

inhalation by onshore residents and 6 x 10-8 for fish consumption by residents. For all scenarios, 

the risk estimates represent upper bounds and actual risks would be expected to be less.
Page 2

KEY WORDS

Deepwater Horizon, dioxin, emission factor, oil spill, in situ oil burns

INTRODUCTION

The explosion and subsequent sinking of the British Petroleum (BP) Deepwater Horizon 

platform in the Gulf of Mexico occurred on April 20, 2010. Since that time until July 15 when 

the oil flow was suspended, an estimated 4.9 million barrels of crude oil (uncertainty range of 

±10%) leaked into the Gulf of Mexico (1). One approach used to reduce the spread of oil is the 

deliberate burning of crude oil on the sea surface. This practice is termed, “in situ burning”. BP 

and the US Coast Guard conducted controlled in situ burns of oil approximately 50 to 80 km

offshore from April 28 to July 19, 2010. A total of 410 controlled burns were conducted 

resulting in the combustion of an estimated 222,000 to 313,000 barrels of oil (Supporting 

Information). Lubchenco et al. (1) estimated that 5% of the leaked oil was burned corresponding 

to a range of 220,000 to 270,000 barrels, estimated by applying the ±10% uncertainty range. 

The fires have the potential to form polychlorinated dibenzo-p-dioxins (PCDDs) and 

polychlorinated dibenzofurans (PCDFs) that would subsequently be released to the environment 

and potentially result in increased human exposure. PCDD/Fs are formed from the incomplete 

combustion of organic matter in the presence of chlorine. This paper focuses on the 17 

PCDD/Fs which have established toxicity equivalents (TEQs, these 17 compounds are 

collectively referred to as dioxins hereafter). All TEQ quantities presented in this paper are based 

on the toxic equivalency factors developed in 2005 (2). Thirteen polychlorinated biphenyls, 

PCBs, are also considered dioxin-like (2) and often included in TEQ reporting. However, these 

dioxin-like PCBs are not addressed in the present study as their TEQ emissions are low 

compared to the PCDD/Fs for other combustion processes (3).

The purpose of this paper is to present the results of a screening level risk assessment to 

estimate potential cancer risks to human populations that may have resulted from exposure to 

dioxins created by the in situ oil burning in the Gulf of Mexico. This assessment is specific to 

releases from burning oil on the sea surface and does not address other types of oil burning or 

chemicals other than dioxin. The pathways considered include inhalation by workers, inhalation 

by residents living onshore, and ingestion of fish by residents. Exposure and risk via the 

terrestrial food chain will be less than those estimated for the marine food chain because the 
Page 3

nearest farm is approximately 80 km from the burn area and the deposition rate would be lower 

than those used to estimated marine impacts. 

Very little information was found on the generation of dioxins from “in situ” open 

burning of oil in water bodies. In a comprehensive review of in situ burn tests, Fingas (4) noted

that limited measurements of PCDD/Fs in particulates downwind of such burning found only 

background levels, which led him to conclude that dioxins were not being produced by the 

burning of crude oil or diesel oil. 

METHODS

The approach used here is best described as a screening assessment that produces upper 

bound risk estimates. Upper estimates were selected for each of the exposure factors and 

exposure concentrations. When these are combined, they overestimate the exposure and risks 

that could reasonably be expected to occur in the impacted populations. In a screening level 

assessment, further evaluations are warranted if the estimates suggest that risks could be of 

concern.

The evaluation of each exposure pathway requires estimates of dioxin emissions:

• Aurell and Gullett (5) measured dioxin emissions during in situ burning in the 

Gulf of Mexico over the time period of July 13-16, 2010. They derived an 

emission factor of 1.7 ng TEQ/kg of oil burned assuming that congeners below 

detection limits equal zero. If congeners below detection limits were set to their 

full detection limit, the emission factor was estimated to be 3.0 ng TEQ/kg. 

• The amount of oil burned during the entire period of burning was approximately 

222,000 to 313,000 barrels (Supporting Information). This is equivalent to 31.8 

to 44.8 million kg using a density of 0.9 kg/L, 42 gallons/barrel and 3.79 L/gallon. 

• The lower estimate of total dioxin emissions was estimated by multiplying the 

lower estimates of the emission factor (1.7 ng TEQ/kg oil burned) and the amount 

of oil burned (31.8 million kg) to get 0.0541 g TEQ. The upper estimate of total 

dioxin emissions was estimated by multiplying the upper estimates of the 

emission factor (3.0 ng TEQ/kg oil burned) and the amount of oil burned (44.8 

million kg) to get 0.134 g TEQ. 
Page 4

Two atmospheric dispersion/deposition models were used in the assessment. U.S. EPA’s 

AERMOD model was used to estimate air concentrations in the immediate vicinity of the oil 

burns and NOAA’s HYSPLIT model was used to estimate surface level air concentrations at the 

shoreline and deposition rates at various locations. 

AERMOD Model Description

AERMOD is a steady-state plume model (6) that simulates dispersion of air pollutants 

based upon planetary boundary layer turbulence structure and scaling concepts. Because the 

model assumes steady state atmospheric conditions during a simulation period of typically one 

hour, its application is generally limited to distances of less than 50 kilometers from the source 

of the pollutant. Additionally, the pollutants are assumed chemically inert over the short 

distances to the receptor locations. AERMOD model inputs include characterization of the 

source and the immediate atmospheric boundary layer, including wind speed, wind direction, air 

temperature, and height of the boundary layer and surface characteristics. AERMOD is currently 

EPA’s recommended model for near-field dispersion applications in most regulatory assessments

(7). 

Since oil burns are a unique source type involving buoyant plumes, we supplemented the 

AERMOD dispersion calculations with the plume rise computations found in the Open Burning 

Open Detonation Model or OBODM (8). The inputs to the plume rise calculations within 

OBODM include a characterization of the source (in this application that would include radius of 

the burn area, oil burn rate, density of oil, and heat content of oil) and near surface wind speeds.

HYSPLIT Model Description

To estimate the regional concentration and deposition impacts of dioxin emitted from the 

oil burns, simulations were carried out with a special research version of the NOAA Air 

Resources Laboratory’s HYSPLIT atmospheric fate and transport model -- configured to 

simulate semivolatile pollutants such as dioxin – called HYSPLIT-SV. The HYSPLIT modeling 

system (9) is used to simulate the atmospheric fate and transport of emitted compounds in 

numerous pollutant analysis and emergency response applications (10). It is primarily a 

Lagrangian model that considers the 3-dimensional atmospheric behavior of puffs or discrete 

point “particles” of pollutants; however, the latest version of the HYSPLIT model (v4.9), has 
Page 5

several enhancements including an integrated Eulerian simulation option. For this screening 

analysis, HYSPLIT-SV was run in 3-dimensional puff mode, in which puffs of pollutants grow 

vertically and horizontally as a function of atmospheric dispersion characteristics. HYSPLIT 

utilizes gridded meteorological data as inputs (e.g., 3-dimensional values of wind direction, wind 

speed, temperature, relative humidity, etc.) and estimates the transport, mixing, chemical 

transformations, and deposition (wet and dry) of emitted pollutants. The base HYSPLIT model 

has been modified to provide a specialized treatment of the atmospheric fate and transport of 

PCDD/F (11), including congener-specific vapor/particle partitioning, reaction with hydroxyl 

radical, photolysis, particle size distributions, and deposition parameters.

Dates, times, and amounts of oil burned for each of the 410 surface burn events (see 

Supporting Information) were used as input to the model with dioxin emissions calculated using 

the upper estimates of the amount burned and congener-specific emission factors. The 

simulation period started on April 28, 2010, on the day that the first reported burn event took 

place, and the model was run continuously through July 22, a few days after the last reported 

burn event that occurred on July 19. The modeling period was chosen to be a few days longer 

than the burning period to ensure that any emitted dioxin would have time to travel to shoreline 

locations should meteorological conditions result in such transport. Archived hourly 

meteorological data fields from NOAA National Center for Environmental Prediction (NCEP) 

NAM weather model (12, 13) were utilized in the simulation. These data have a horizontal 

resolution of approximately 12 km and contain surface parameters as well as data at 39 vertical 

levels above the surface with 18 of those levels within the first ~1500 m. The overall modeling 

domain was 10 x 10 degrees, centered at the DWH site. The results of the HYSPLIT simulations 

were tabulated on a grid extending 2.5 degrees in each direction from the site, with a resolution 

of 0.1 deg (~10 km), and additional time-series and other information were tabulated at 14 

selected sites in the region, for illustrative purposes. The simulation-results grid and these 

illustrative sites are shown in Figure 1.

A relatively large maximum limit of 100,000 puffs was utilized in the simulation to 

minimize the influence of inhibition of puff splitting due to numerical constraints. Buoyancydriven plume rise was estimated in the model as the final-rise height using an estimate of the heat 

release rate (expressed in Watts), wind speed, and vertical stability, for each individual burn 

event following the approach of Briggs (14). Sensitivity analyses were carried out to investigate 
Page 6

the influence of plume rise on the simulation – by comparison to simulations assuming a fixed 

plume rise (e.g., 200m), and it was found that the inclusion of specific burn-by-burn plume rise 

estimates had a significant influence on the concentration and deposition results (see Supporting 

Information). 

Simulations were performed for each of the seventeen 2,3,7,8-substituted PCDD/F 

congeners, using physical-chemical properties for each, as described in Cohen et al. (11). To 

summarize the results, the individual congener simulations were added together using the 

congener-specific emissions factor and congener-specific toxic-equivalence factor, in the usual 

manner, to create results expressed as TEQ.

Exposure Calculations

The general equation used to assess inhalation risks to workers and the general 

population was:

CR = LADD * SF (1)

LADD = (C * IR * HR * DY * ED)/(BW * LT) (2)

Where:

CR = cancer risk (unitless)

LADD = lifetime average daily dose (pg/kg-day)

SF = cancer slope factor (1/[pg/kg-day])

C = air concentration (pg TEQ/m3

)

IR = inhalation rate (m3

/hr)

HR = hours per day of exposure (hours working or hours exposed by the 

general onshore population, hr/day)

DY = days per year of exposure (days working or total days exposed for 

general population, day/yr)

ED = exposure duration (yr)

BW = body weight (kg)

LT = lifetime (days)
Page 7

For workers, assumptions include: an ED of 0.25 yr (burning occurred over 3 months), an 

IR of 2.2 m3/hr (based on 95th percentile rates for adults aged 21-60 years and assuming activity 

levels were 40% light, 40% moderate and 20% high from, 15), an HR of 10 hr/day, a DY of 250 

day/yr, a BW of 70 kg, and an LT of 25,550 day. For general residential populations, the same 

ED, BW, and LT were assumed, but the IR was 0.9 m3

/hr or 21.3 m3/day (95th percentile for 

adults aged 21-60 years from, 15), the HR was 24 hr/day, and the DY was 350 day/yr. The slope 

factor for TEQs was set to the EPA value for 2,3,7,8-TCDD (1.58 x 10-4 per pg/kg-day) (16). 

The air concentrations were based on measured and modeled values as described in the Results 

section.

For assessing fish ingestion lifetime cancer risk, the same general equation, Equation (1), 

was used, but LADD was instead calculated as:

LADD = (C x I x DY x ED)/(BW x LT) (3)

Where:

C = Concentration in fish (pg TEQ/g fish)

I = Ingestion rate of fish (g/day)

The values used for LADD, DY, BW, and LT were the same as previously defined for residents. 

The ED was set to one year based on the assumption that consumption of impacted fish would 

occur for a period longer than the actual burn time. The length of time over which elevated 

dioxin levels in fish may persist depends on a number of factors including how quickly dioxin 

levels in water dissipate and how quickly dioxin levels in fish decline. None of these are known 

with certainty, but a period of one year was judged to be a conservative assumption. The 

concentration in fish was determined using the procedure described below. The marine fish and 

shellfish consumption rate was assumed to be the 95th percentile per capita estimate for general 

population adults. This was 81 g/day (Table 10-1 in, 15). 

Fish Tissue Concentration Calculations
Page 8

The increase in dioxin concentration in caught fish due to deposition from the burn was 

estimated by applying a bioaccumulation factor (BAF) to an estimated water concentration. The 

BAF represents the process by which aquatic organisms accumulate chemicals via all routes of 

exposure (i.e., dermal contact with water, transport across the respiratory surface, and dietary 

uptake) (17), and accounts for potential biomagnification of dioxins in the food web. The first 

step was to estimate the total (sorbed phase plus dissolved phase) water concentration which was 

determined by dividing the deposition rate by a mixing depth. The deposition rate was set to 10 

pg TEQ/m2 based on HYSPLIT modeling results presented below. The mixing depth was 

assumed to be10 m based on the 7-16 m range of measured pycnocline (surface mixed layer) 

depths reported by Lehrter et al. (18) from 6 sampling events on the Louisiana continental shelf. 

This yields a total water concentration of 0.001 pg TEQ/L. The second step was to estimate the 

dissolved phase water concentration. The PCDD/Fs will partition between the water and 

suspended particulates. Several factors affect this partitioning including the particulate 

concentration in the water and organic carbon content of the particulates. Also it will vary by 

congener, with the higher chlorinated congeners partitioning toward the particle phases more 

strongly than the lower chlorinated congeners. Muir et al. (19) studied this partitioning in lake 

waters and found that the portion of PCDD/Fs in the dissolved phase was <1% for OCDD and 

10% for TCDD. For purposes of this screening analysis it is assumed that 10% of the total TEQ 

water concentration will be in the dissolved phase, yielding a dissolved concentration of 0.0001 

pg TEQ/L. 

This dissolved phase concentration was multiplied by a BAF to estimate fish 

concentration:

CF = CW * BAF (4)

Where:

CW = water concentration, pg TEQ/L

BAF = bioaccumulation factor, L/kg

Upper trophic level BAFs were estimated using the EPISUITE Model Version 4.0 (20) 

for the 4 congeners with the highest TEQ concentrations measured in the oil fire plume by Aurell 
Page 9

and Gullett (5). These ranged from 2.57 x 103 to 2.39 x 105 L/kg wet weight. For purposes of 

this screening assessment, the BAF at the upper end of the range was selected (2.39 x 105 L/kg 

wet weight). Multiplying this BAF and the TEQ dissolved water concentration yields a fish 

tissue concentration of 0.024 pg TEQ/g. 

Bioaccumulation can also be modeled on the basis of the suspended sediment 

concentrations. As discussed in the Supporting Information, this approach predicted a very 

similar fish concentration of 0.018 pg TEQ/g.

A literature search was conducted to find data which could be used to support the 

modeled values. Very little data specific to the Gulf of Mexico could be found. The increase in 

fish concentration predicted here is about 7 times less than background levels in marine fish 

which are estimated to be 0.5 pg TEQ/g (21). Fish uptake of dioxin from atmospheric 

deposition has been studied in the Baltic Sea by Vikelsoe et al. (22). As discussed in the 

Supporting Information, an analysis was conducted using the Vikelsoe et al. data to predict fish 

levels resulting from the oil burns. The predicted concentration was about 3 times higher than 

the one obtained via the BAF method. 

RESULTS 

AERMOD Dispersion Modeling Results

To estimate the potential inhalation exposure of workers in the vicinity of the in situ oil 

burns, AERMOD was used to simulate concentration fields near the water surface within a few 

kilometers of a burn. The duration of burn and total oil consumed for each of the 410 burns 

along with assumptions about burn area, and oil heat content were used to construct a “typical” 

oil-burn source for use in this screening analysis. Meteorological data (concurrent with the fires) 

from the nearest Gulf region buoy (23) and from the NOAA NCEP-NAM meteorological model 

were examined to develop a set of screening-level inputs.

Oil-burn source characterization

The distribution of 410 individual oil burns (Supporting Information) showed burn rates 

varying significantly. Based on the relationship between the upper estimates for the amount of 

oil burned and emission factor provided by Aurell and Gullett (5), the emission rates of dioxin 
Page 10

related to the distribution of all burns ranged from about 2.6 x 10-4 μg TEQ/sec to 2.7 μg 

TEQ/sec with a mean and median of 6.8 x 10-2 μg TEQ/sec and 2.6 x 10-2 μg TEQ/sec, 

respectively. For the screening analysis we chose a burn with an equivalent emission rate of 8.7

x 10-2 μg TEQ/sec (a large fire with slightly larger than average emissions). This selected 

emission rate is equivalent to a burn rate of approximately 500 gallons of oil per minute. Based 

on news videos and photographs, the horizontal radius of the modeled fire was set at 25 meters. 

The heat content of the oil, 10,850 cal/g (5.8 x 106 BTU per barrel) was based on information for 

typical American Crude (24).

Meteorology (boundary layer characterization)

Based on buoy data and NCEP-NAM output for the burn periods, the sea surface 

temperature was fairly constant (near 27° C). The near surface air temperature was also in the 

same range yet typically 1 to 3 degrees cooler during the daylight hours. This yielded a very 

slight positive heat flux and thus a near-neutral or very weak convective boundary layer. The 

vertical potential temperature gradients suggest a well mixed layer in the 200 to 500 m height 

range with a moderate to weak stable layer above. Wind speeds during the burns ranged from 

less than 1 m/s up to approximately 6 m/s (10 m/s was the limit above which burns were not to 

be initiated). Since the goal of this analysis is to predict the maximum one hour concentration 

from a burn for any steady wind direction, the wind direction was fixed and concentrations were 

computed directly downwind of the burn. 

For the AERMOD screening analysis, the range of meteorological conditions selected for 

input to the model was as follows. The 2-m wind speeds ranged from 1 to 10 m/s, the mixing 

height from 200 to 500 m, the friction velocity varied appropriately with wind speed from 0.095 

to 0.95 m/s and the Monin-Obukhov length (stability parameter) varied from -80 to -8000 m. 

The surface roughness length was set at 0.03 meters, the potential temperature gradient above the 

mixed layer at 0.01 °C/m and the sensible heat flux depending on wind speed in the range of 1 to 

10 Watts/m2

. 

Model results

For the screening conditions outlined above, AERMOD-simulated, near-surface 

concentrations were lower for the mixing height equal to 500 m as compared to 200 m (with all 
Page 11

other variables the same). This is not unexpected since the stable layer above the mixed layer 

tends to slow the plume rise and allow the plume to remain closer to the surface. With the lower 

mixed layer, this stable layer is reached sooner. Therefore we are only reporting near surface 

concentrations for the mixing height equal to 200 m (Table 1).

The Supporting Information presents discussions on how the modeled concentrations 

vary with assumptions regarding wind speed, mixing height and emission factor. Also the 

Supporting Information presents model runs using the conditions present during emission tests 

conducted by Aurell and Gullett (5). These runs predicted in-plume concentrations ranging from 

0.17 to 0.54 pg TEQ/m3 which bracket the average of 0.2 pg TEQ/m3 measured by Aurell and 

Gullett (5).

HYSPLIT Modeling Results

Due to the variations in meteorological conditions (e.g., wind speed and direction) and 

intermittent nature of the burns, the deposition flux and atmospheric concentrations at any given 

location – even from the simulated continuous emissions – are highly variable or “episodic (see 

Supporting Information). However, average concentrations and total deposition amounts over 

the entire burn period are utilized in this screening level risk assessment and so only these results 

will be presented here. Figure 1 shows the average, modeled ground-level (10 m) concentrations 

for each grid point over the entire modeling period April 28 – July 22, 2010 and (in the caption) 

average concentrations for several illustrative locations in the region.. The highest, modeled 

grid-cell average 10 m concentration was 0.051 fg TEQ/m3

, and this occurred in an area 

approximately 125 km northeast from the spill site. The highest average modeled shoreline (or 

inland) concentrations was 0.034 fg TEQ/m3, and this occurred about 50 km west of Pensacola, 

FL. As noted above, the maximum burn amounts and the maximum emissions factor (ND=DL) 

were used as inputs to the HYSPLIT modeling. Considering the range in estimated dioxin 

emissions factor for oil burning (using different assumptions for treating non-detected 

congeners), the range in maximum shoreline 10 m air concentration averaged over the burning 

period would be 0.028 – 0.034 fg TEQ/m3. 
Page 12

To assess potential ecosystem-related exposure risk, an estimate of total atmospheric 

deposition to a given ecosystem is needed. The total modeled wet and dry deposition fluxes for 

the overall modeling period are shown in Figure 2 below. It can be seen that there are large 

spatial gradients in the estimated deposition, as would be expected. Thus, an estimate of the 

average deposition flux will depend greatly on the area being considered. The maximum 

estimated deposition flux of 17,200 fg TEQ/m2 occurred at about 50 km south of the spill site. 

The continental shelf lies in the region north of the Deepwater Horizon spill site, and it is in 

these shelf regions that the deposition would be expected to have the greatest potential impact on 

food-web dioxin concentrations. The highest model-estimated PCDD/F fluxes to continentalshelf Gulf of Mexico ecosystem areas fall within the range of 1000-10,000 fg TEQ/m2 (using the 

high-end of the emissions factor range and the high end of the amount-of-oil-burned range), and 

this range can be used to estimate screening-level ecological impacts.

A deposition mass balance analysis was performed for each of the seventeen 2,3,7,8-

substituted congeners simulated with the HYSPLIT-SV model over the entire 10x10 degree 

modeling domain (see Supporting Information). For 2,3,7,8-TCDD, approximately 30% of the 

emitted mass was dry deposited in the vapor phase, about 2% was dry deposited in the particle 

phase, and the remaining 68% was wet deposited. Other congeners exhibited different behavior 

and the relative importance of different deposition pathways appears to be consistent with the 

expected vapor/particle partitioning behavior of the different congeners. The most important 

congeners contributing to deposition over the entire domain on a TEQ basis were 1,2,3,7,8-

PeCDD and 2,3,4,7,8-PeCDF. Wet deposition was the most important deposition pathway for 

these two congeners. Results varied from congener to congener, but approximately 40% of the 

emitted amount of each congener was deposited within the 10x10 degree modeling domain.

Worker Inhalation Results

Upper bound worker inhalation exposures were calculated two ways. First, it was based 

on the plume measurements by Aurell and Gullett (5). They measured a concentration of 0.2 pg 

TEQ/m3 at 200-300 m from the fire and about 75-200 m above sea level. Using this 

concentration and exposure assumptions outlined above, the LADD was 1.5 x 10-4 pg/kg-d and 

the lifetime incremental cancer risk was 2 x 10-8

. The second approach used the AERMOD 

modeled concentration from Table 1 for a location 50 m downwind of the burn site with a wind 
Page 13

speed of 5 m/sec which was 0.48 pg TEQ/m3 (the modeled values at 10 m/s (20 miles/hour) were 

considered unrealistically high for even an upper estimate of long term conditions). Using this 

concentration and exposure assumptions outlined above, the LADD was 3.7 x 10-4 pg/kg-d and 

the lifetime incremental cancer risk was 6 x 10-8.

Resident Inhalation Results

HYSPLIT modeling results suggest that the maximum long term (82-day) average air 

concentration for shoreline exposure was 0.034 fg TEQ/m3. This predicted incremental 

concentration is much less than the measured air concentrations in rural locations in the United 

States which averaged 10 fg TEQ/m3 (25). Using this concentration and exposure assumptions 

outlined above, the LADD was 3.6 x 10-8 pg/kg-d and the lifetime incremental cancer risk was 6

x 10-12. 

Fish Ingestion Results

As discussed above, the fish concentration at the point of maximum deposition was 

calculated to be 0.024 pg TEQ/g. Using this concentration and exposure assumptions outlined 

above, the LADD was 3.8 x 10-4 pg/kg-d and the lifetime incremental cancer risk was 6 x 10-8. 

The discussion section below describes how these risk estimates may change for subpopulations 

with higher fish consumption rates.

DISCUSSION

The overall approach and parameter assignments in this assessment were purposefully 

established to be conservative to meet the needs of a “screening level” assessment. For all 

scenarios, the risk estimates represent upper bounds and actual risks would be expected to be 

less.

Although the baseline screening risk assessment presented above is considered conservative 

for the adult general population, certain subpopulations may have higher fish ingestion risks. For 

example, 95th percentile fish ingestion rates are about two times higher for children than adults 

when expressed on a per body weight basis (15). This implies that their risks would also 

increase by a factor of 2. Also, a number of investigators have identified subsistence fish 
Page 14

consumers in the Gulf Coast region as a population of concern with regard to impacts from the 

oil spill (26). Only one study was found that includes information that may be relevant to 

subsistence fishing in this region. Degner et al. (27) conducted a study of fish and shellfish 

ingestion in Florida. Westat (28) analyzed the raw data from this study to estimate fish 

consumption rates for various Florida populations, including Native American Indians assumed 

to be subsistence fishers (15). The 95th percentile consumer only intake rate was 5.7 g/kg-day. 

Assuming an average body weight of 70 kg, this would be equivalent to an intake rate of 

approximately 400 g/day. The 1997 Exposure Factors Handbook (29) recommended a fish 

consumption rate of 170 g/day as a 95th percentile for Native American subsistence populations. 

The 2009 draft update of the Handbook (15) presents a summary of Native American subsistence 

fish intakes from various studies, including the study from Florida. The 95th percentiles from 

these studies average about 300 g/day. This is very similar to the 95th percentile marine fish and 

shellfish ingestion estimate for consumers only of 270 g/d (15). Accordingly, a fish/shellfish 

consumption rate of 300 g/d fish appears to be a reasonable upper percentile estimate for Gulf 

Coast subsistence fish consumers. This rate is 3.7 times greater than the upper percentile fish 

consumption rate (81 g/day) assumed for the general population. The upper excess cancer risk 

estimates for the subsistence populations would be linearly proportional to the consumption rate 

(i.e., 3.7 times greater, or 2 x 10-7

). 

Even with the increases due to subsistence fish consumers discussed above, none of the 

cancer risks exceeded 1 x 10-6. EPA typically considers the risk range of 10-6 to 10-4 to be a 

range where consideration is given to additional actions, such as site cleanup or establishment of 

regulatory policy. 

Another perspective can be gained by comparing these exposures and risks with those 

that are otherwise incurred by the general population. In 2003, EPA provided an estimate of 

general population exposures to all dioxin-like compounds (including dioxin-like PCBs) of 61 pg 

TEQ/day. That estimate was recently updated to 41 pg TEQ/day (30). The average daily intake 

from fish ingestion during the exposure period is 1.9 pg TEQ/day, about 5% of current 

background exposures. As a way to assess non-cancer risks, this daily intake can be converted to 

a per kg basis (0.028 pg/kg-day) and shown to be much less than the ATSDR chronic Minimum 

Risk Level (MRL) of 1 pg/kg-day (31).
Page 15

Acknowledgements: The authors acknowledge Daewon Byun (NOAA), Hyun Cheol Kim 

(NOAA), Mark Greenberg (EPA) and Nere Mabile (BP) who assisted with the collection and 

analysis of oil burn data, and Shawn Ryan (EPA), Peter L. deFur (Environmental Stewardship 

Concepts, LLC), Rainer Lohmann (University of Rhode Island) and Donald Mackay (DMER 

Ltd) for helpful review comments.

This document has been reviewed in accordance with U.S. Environmental Protection Agency and 

National Oceanic and Atmospheric Administration policy and approved for publication. The 

mention of trade names or commercial products does not constitute endorsement or 

recommendation for use.

SUPPORTING INFORMATION AVAILABLE 

Supporting information includes detailed data on amount of oil burned and additional 

information on modeling results. 

References 

1. Lubchenco, J.; McNutt, M.; Lehr, B.; Sogge, M.; Miller, M.; Hammond, S.; Conner, W. 

BP Deepwater Horizon Oil Budget: What Happened To the Oil? 

http://www.deepwaterhorizonresponse.com/posted/2931/Oil_Budget_description_8_3_FI

NAL.844091.pdf. 2010

2. Van den Berg, M.; Birnbaum, L.S.; Denison, M.; De Vito, M.; Farland, W.; Feeley, M.; 

Fiedler, H.; Hakansson, H.; Hanberg, A.; Haws, L.; Rose, M.; Safe, S.; Schrenk, D.; 

Tohyama, C.; Tritscher, A.; Tuomisto, J.; Tysklind, M.; Walker, N.; Peterson, R.E. 

The 2005 World Health Organization Re-evaluation of Human and Mammalian Toxic 

Equivalency Factors for Dioxins and Dioxin-like Compounds. Tox. Sci. 2006, 93, 223-

241.

3. U.S. EPA. An inventory of sources and environmental releases of dioxin-like 

compounds in the United States for the years 1987, 1995, and 2000. National Center for 

Environmental Assessment, Washington, DC; EPA/600/P-03/002F. 2006. 

4. Fingas, M.; Lambert, P.; Li, K.; Wang, Z.; Ackerman, F.; Whiticar, S.; Goldthorp, M.; 

Schutz, S.; Morganti, M.; Turpin, R.; Nadeau, R.; Campagna, P.; Hiltabrand, R. Studies 

of emissions from oil fires. International Oil Spill Conference. 2001, 539-544.
Page 16

5. Aurell, J.; Gullett, B.K. Aerial sampling of PCDD/PCDF emissions from the Gulf oil 

spill in situ burns. Submitted to Environ. Sci. Technol. 2010.

6. Cimorelli, A.; Perry, S.; Venkatram, A.; Weil, J.; Paine, R.; Wilson, R.; Lee, R.; Peters, 

W.; Brode, R. AERMOD: A dispersion model for industrial source applications. Part I: 

General model formulations and boundary layer characterization. Atmos. Environ., 2005,

44, 682-693.

7. Perry, S. A.; Cimorelli, R.; Paine, R.; Brode, J.; Weil, A.; Venkatram, R.; Wilson, R. L.; 

Peters, W. AERMOD: A dispersion model for industrial source applications. Part II: 

Model performance against 17 field study data bases. Atmos. Env. 2005, 44, 694-708.

8. Bjorklund, J.; Bowers, J.; Dodd, G.; and White, J. Open burning / open detonation 

(OBODM) User’s Guide. Volume II. Technical Description. DPG Document No. DPGTR-96-008b, U. S. Army Dugway Proving Ground, Dugway , UT. 1998. 

http://www.epa.gov/ttn/scram/userg/nonepa/obodmvol2.pdf.

9. Draxler, R.R.; Hess G.D. An overview of the HYSPLIT_4 modelling system for 

trajectories, dispersion, and deposition. Aust. Meteor. Mag. 1998, 47, 295-308.

10. Draxler, R.R.; Rolph, G.D. HYSPLIT (HYbrid Single-Particle Lagrangian Integrated 

Trajectory) Model. NOAA Air Resources Laboratory, Silver Spring, MD. 2010.

http://ready.arl.noaa.gov/HYSPLIT.php

11. Cohen, M.; Draxler, R., Artz, R., et al. Modeling the Atmospheric Transport and 

Deposition of PCDD/F to the Great Lakes. Environ. Sci. Technol. 2002, 36, 4831-4845. 

http://www.arl.noaa.gov/data/web/reports/cohen/13_cohen_et_al.pdf.

12. Janjic, Z.I. A nonhydrostatic model based on a new approach, Meteorology and 

Atmospheric Physics 2003, 82, 271-285.

13. Janjic, Z.I., Gerrity, Jr. J.P.; Nickovic, S. An alternative approach to nonhydrostatic 

modeling. Monthly Weather Review 2001, 129, 1164-1178.

14. Briggs, G.A. Plume Rise, U.S. Atomic Energy Commission, TID-25075, NTIS, 

Springfield, VA, 81p. 1969.

15. U.S. EPA. Exposure factors handbook – 2009 update. External Review Draft. National 

Center for Environmental Assessment, Washington, DC. EPA/600/R-09/052A. 2009.
Page 17

16. Basu, D.; Mukerjee, D.; Neal, M.; Olson, J.; Hee, S. Health Assessment Document for 

Polychlorinated Dibenzo-P-Dioxins. U.S. Environmental Protection Agency, 

Washington, D.C., EPA/600/8-84/014F (NTIS PB86122546), 1985.

17. Boethling, R.S.; Mackay, D. Handbook of Property Estimation Methods for Chemicals. 

Lewis Publishers, Boca Raton, pp 192-196. 2000.

18. Lehrter, J.C.; Murrell, M.C.; Kurtz, J.C. Interactions between freshwater input, light, and 

phytoplankton dynamics on the Louisiana continental shelf. Continental Shelf Research

2009, 29, 1861-1872.

19. Muir, D.C.G.; Lawrence, S.; Holoka, M.; Fairchild, W.L.; Segstro, M.D.; Webster, 

G.R.B.; Servos, M.R. Partitioning of polychlorinated dioxins and furans between water, 

sediments and biota in lake mesocosms. Chemosphere 1992, 25(l-2), 119-124.

20. U.S. EPA. Estimation Programs Interface (EPI) SuiteTM for Microsoft® Windows, v 

4.00 http://www.epa.gov/oppt/exposure/pubs/episuite.htm. 2010b. 

21. U.S. EPA. Exposure and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-pDioxin (TCDD) and Related Compounds National Academy Sciences (NAS) Review 

Draft. EPA/600/P-001C. 2003.

22. Vikelsøe, J.; Andersen, H.V.; Bossi, R.; Johansen, E.; Chrillesen, M. Dioxin in the 

Atmosphere of Denmark. A Field Study at Selected Locations. NERI Technical Report 

No. 565. 

http://www2.dmu.dk/1_viden/2_Publikationer/3_fagrapporter/rapporter/FR565.PDF

2005.

23. NOAA. National Oceanic and Atmospheric Administration. National Data Buoy Center, 

Disc Buoy Station 42040 (29°12’45”N 88°12’27”W). 2010.

http://www.ndbc.noaa.gov/station_page.php?station=42040

24. US Energy Information Administration. http://www.eia.doe.gov/iea/convheat.html. 

2006 

25. Cleverly D.; Ferrario, J.; Byrne, C.; Riggs, K.; Joseph, D.; Hartford, P. A General 

Indication of the Contemporary Background Levels of PCDDs, PCDFs, and Coplanar 

PCBs in the Ambient Air over Rural and Remote Areas of the United States. Env. Sci 

Tech. 2007, 41(5), 1537-1544
Page 18

26. Institute of Medicine of the National Academies. Assessing the effects of the Gulf of 

Mexico oil spill on human health: A Summary of the June 2010 Workshop. The National 

Academies Press, Washington D.C. 2010.

27. Degner, R.L.; Adams, C.M.; Moss, S.D.; Mack, S.K. Per capita fish and shellfish 

consumption in Florida. Gainesville, FL: University of Florida. 1994.

28. Westat. Fish consumption in Connecticut, Florida, Minnesota, and North Dakota: 

Draft final report. July 16, 2006. Submitted by Westat, Rockville, MD to EPA/ORD, 

Washington, DC. 2006. 

29. US EPA. Exposure Factors Handbook. Washington, DC: Office of Research and 

Development. EPA/600/P-95/002B. 1997.

30. Lorber, M.; Patterson, D.; Huwe, J.; Kahn, H. Evaluation of background exposures of 

Americans to dioxin-like compounds in the 1990s and 2000s. Chemosphere 2009, 77, 

640-651.

31. Agency for Toxic Substances and Disease Registry (ATSDR). Toxicological profile for 

chlorinated dibenzo-p-dioxins. 1998 

http://www.atsdr.cdc.gov/ToxProfiles/tp.asp?id=366&tid=63.
Page 19

Table 1. Near Surface Concentrations (pg TEQ/m3) for Mixing Height = 200 meters, emission 

rate = 8.7 x 10-2 μg TEQ/sec, three wind speeds at a height of 2 meters above the surface.

Wind 

Speed 

(m/s)↓

Downwind 

Distance

(m) →

50 100 250 500 1000 1500 2500

1 0.017 0.017 0.018 0.019 0.021 0.023 0.027

5 0.484 0.056 0.005 0.004 0.005 0.006 0.008

10 4.584 0.818 0.049 0.006 0.003 0.004 0.006
Page 20

Figure 1. Average ground-level concentrations (fg TEQ/m3) for each grid square over the entire modeling period 

April 28 – July 22, 2010. Illustrative locations shown, numbered in descending order from highest to lowest overall 

average concentration (fg TEQ/m3): 1 – southeast Plaquemines (0.019); 2 – Dauphin Island (0.016); 3 – Pensacola 

(0.012); 4 – Venice (0.0072); 5 – Stake Island (0.0069); 6 – Pascagoula (0.0011); 7 – Grand Isle (0.0010); 8 –

Gulfport (0.00095); 9 – Biloxi (0.00066); 10 – Grand Bay National Estuarine Research Reserve (0.00065); 11 –

Mobile (0.00052); 12 – Slidell (0.00025); 13 – Houma (0.00018); 14 – New Orleans (0.00008)
Page 21

Figure 2. Total modeled atmospheric deposition (fg TEQ/m2) for each grid 

square over the entire modeling period April 28 – July 22, 2010.