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Oil in the Sea IV: Inputs, Fates, and Effects (2022)

Chapter: Appendix C: Estimating Land-Based Sources of Oil in the Sea

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Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

Appendix C

Estimating Land-Based Sources of Oil in the Sea

C.1 INTRODUCTION

Due to the scarcity of individual data samples for estimating land-based loads of oil to the sea, the loading estimates calculated in this analysis were based on loading per unit of urban land area. These calculations assume that most land-based runoff of oil is from urban areas. This approach was used for the United States and Canada and then extrapolated to estimate the other regions of the world. This appendix is an update of Oil in the Sea III, Appendix I.

C.1.1 Methodology and Sources of the Data

A review of The Water Quality Portal’s STORET data indicated that oil and grease data had been collected for the major rivers in the United States; however, eight of those rivers had fewer than 10 observations. Only three rivers—Columbia, Mississippi, and Potomac—had petroleum hydrocarbon data.

Quantified estimates of oil and grease and petroleum hydrocarbon loadings were made for the United States and Canada. These estimates were made using unit loadings per urban land area. The annual loadings were calculated according to the coastal zones defined in this study, and the overall loadings for the United States and Canada were extrapolated to the world. For the calculations in the United States and Canada, the land-based sources were separated into two categories: inland basins and coastal basins. It was assumed that inland basins discharged into one of the following major river basins that outlet to the sea along the coast of the United States and Canada (coastal basins were assumed to discharge directly to the sea):

  • Alabama–Tombigbee
  • Apalachicola
  • Altamaha
  • Brazos
  • Colorado (Texas)
  • Columbia
  • Copper (Alaska)
  • Delaware
  • Hudson
  • James
  • Mississippi
  • Neuse
  • Potomac
  • Rio Grande
  • Roanoke
  • Sabine
  • Sacramento
  • San Joaquin
  • Santee
  • Saskatchewan
  • Savannah
  • St. Lawrence
  • Susquehanna

C.1.2 Calculations for the Inland Rivers of the United States and Canada

The following methodology was used to estimate the loading of oil and grease to the sea from inland river basins in the United States and Canada:

  1. Using the locations designated in Oil in the Sea III (see Table C.1), water quality data were requested from STORET. Using the Water Quality Portal, searches were made for all surface water quality data collected within these regions. Data with the Characteristic Group: Organics, Other and the following characteristics:
    • Oil and grease
    • Hydrocarbons, petroleum
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×
  1. Averages of all reported values from STORET were compiled for each river (see Table C.2) with the following assumptions (rivers not shown in Table C.2 did not have any usable oil and grease data):
    • Data were collected from 2000 onward
    • During calculations for each river, NA (not available) data were not included in the averages
  2. An average annual load in tonne/yr was calculated for those rivers with reported oil and grease data by using the following formula:

    Equation C-1

Li = ci Qi,

whereLi = average annual load for river i (tonne/yr),

ci = average oil and grease concentration for river i (mg/L),

Qi = average annual flow for river i (m3/yr), tonne = 106 g.

The average annual flow (per calendar year) was determined from U.S. Geological Survey (USGS) daily flow data available for each of the rivers at either the same station from Oil in the Sea III or the closest non-tidally influenced station to the collection site for the oil and grease samples (see Table C.3). The average annual flow of the major inland rivers is compared to the flows from 1980 to 1999, similar to the period of record in Oil in the Sea III, in order to assess the changes in river flow since the last report (see Table C-4).

  1. Using data obtained from the State and Metropolitan Area Data Book (2010, 2020), unit loads per urban land area were calculated as follows:

    Equation C-2

Image

where lai = unit load per urban land area for river i (g/m2yr),
Aui = 2019 urban land area for river i (m2)

The 2019 urban land area in each river basin was determined by Table B-1 in State and Metropolitan Area Data Book 2020. Metropolitan areas in this table were partitioned in the major river basins identified in Table C.1, coastal areas, the Great Lakes, or areas not discharging to the coast of the United States or Canada (e.g., Great Salt Lake basin). Urban areas contributing to the Great Lakes fall within one of the counties defined by Indiana Business Research Center (2016). Metropolitan areas contributing urban runoff to the Great Lakes or areas not discharging to the coast of the United States or Canada were not included further in the analysis.

  1. For the majority of the inland river basins, no usable oil and grease data were available in STORET. In addition, the number of non-NA observations for the Columbia, Delaware, James, Roanoke, Sacramento, San Joaquin, Susitna, and Susquehanna rivers were very small. It was therefore decided to use an alternative procedure based on the unit loads of oil and grease per urban land area and per capita calculated from Steps 1–4 to estimate the contributions of oil and grease from these other river basins. The procedure was as follows:
    1. The unit loads of oil and grease per urban land area calculated from Steps 1–4 were used for the other river basins with the following assumptions:
      • The Hudson, James, and Susquehanna rivers were assumed to have unit loads of oil and grease per urban land area of 12.34 g/m2yr, the value calculated from four observations on the Delaware River (this small number of observations was deemed sufficient due to the consistency with the values of samples presented in Oil in the Sea III). The high unit loadings on the Delaware River are due to the highly industrialized nature of the waterway, and these three rivers are also very industrialized and in a similar geographic area.
      • It is assumed that the Alaskan rivers Copper and Susitna did not contribute significant loads of oil and grease to the ocean.
      • All other rivers for which the measured data were not adequate or were unavailable were assumed to have unit loads of oil and grease per urban land area of 0.15 g/m2yr. This value was calculated from 404 non-NA observations on the Potomac. Rivers for which this value applied includes the Alabama–Tombigbee, Altamaha, Apalachicola, Brazos, Colorado (Texas), Columbia, Mississippi, Neuse, Rio Grande, Roanoke, Sabine, Sacramento, Santee, San Joaquin, Saskatchewan, Savannah, St. Lawrence, Trinity, and Yukon rivers.
    2. Using data obtained from the State and Metropolitan Area Data Book (2020) and Statistics Canada (2016), the annual loads per unit land area (Lai) were calculated as follows:

      Equation C-3

      Lai = lai Aui (tonne/106 g)

      where lai was the unit load for river i as described in Step 5.a. The urban land area, Aui was calculated in the same manner as described in Step 4 for metropolitan areas

Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

in the United States. For metropolitan areas in Canada, Aui was calculated using data from Statistics Canada (2016). The urban land area and population for each inland river was compared for the 1990s, 2000s, and 2010s to understand the comparative growth of urban land area and population within each river basin (see Table C.5).

C.1.3 Calculations for the Coastal Zones of the United States and Canada

For the United States, metropolitan areas in State and Metropolitan Area Data Book (2020) were classified as contributing to coastal basins if they fell within 1 of the 254 non–Great Lakes bordering coastal counties defined by Culliton et al. (1990). The individual coastal basin metropolitan areas were then aggregated into the appropriate coastal zones. The data for 2019 urban land area for metropolitan areas (State and Metropolitan Area Data Book, 2020) were then compiled for each coastal zone. Similarly, data from Statistics Canada (2016) for Canadian metropolitan areas along the coast were grouped into the appropriate coastal zones.

The annual load Lai was calculated for urban areas in each coastal zone i in the United States and Canada using Equation C-3. The unit load per urban land area for coastal zone i, lai, was 12.34 g/m2yr for Coastal Zone D, and 0.15 g/m2yr for all other coastal zones. The unit loads were set higher for Coastal Zone D because it is the coastal zone to which the Delaware River discharges.

The total oil and grease loading was determined by adding discharges from inland rivers and urban coastal areas to the appropriate coastal zones.

C.1.4 World Estimates of Oil and Grease

The data used for the calculations of oil and grease loading for North American were not available for other regions of the world. Therefore, a method to extrapolate the North American calculations to the rest of the world was used. It is widely thought that land-based contributions of oil and grease are due primarily to vehicle operation and maintenance (Fam et al., 1987; Hoffman and Quinn, 1987a,b; Latimer et al., 1990; Bomboi and Hernández, 1991; Zeng and Vista, 1997; Latimer and Quinn, 1998). Thus, oil and grease loading estimates for the world were based on the number of motor vehicles in different regions of the world as calculated by the motor vehicles per 1000 persons for each country and population of each country (World Bank, 2020). Oil and grease loading per vehicle was based on the calculations from Oil in the Sea III, 0.01573 tonne/vehicle yr. Redoing the original calculations with the new values found in this report produced a similar value of 0.01593 tonne/veh yr, so the value from the original report was used in order to compare more closely between the two reports.

The number of vehicles in regions of the world was determined by applying Equation C-4 to country data and then compiling for each region. These numbers of vehicles were then multiplied by the loading per vehicle in North America calculated in Oil in the Sea III to obtain a world estimate of loading of oil and grease to the sea via land-based contributions. Because data on actual vehicle usage and maintenance in other countries were unavailable, it was assumed that the loadings of oil and grease per vehicle in North America were representative of oil and grease loadings per vehicle in other parts of the world. This assumption was considered reasonable because, while motor vehicles in other countries of the world are not as well maintained as vehicles in North America and therefore would likely contribute more oil and grease per vehicle while running, motor vehicles are less frequently used in other regions of the world.

C.1.5 Estimates of Petroleum Hydrocarbons and Polycyclic Aromatic Hydrocarbons

Within the STORET data, there were hydrocarbons and petroleum data for three rivers: Columbia, Mississippi, and Potomac (see Table C.2). In Oil in the Sea III, petroleum hydrocarbons loadings were estimated to be 1.5% of the oil and grease loadings. In contrast, the Potomac River data presents a proportion of petroleum hydrocarbons to oil and grease of about 90%. Without information to the contrary, the polycyclic aromatic hydrocarbon (PAH) proportion was considered to be 1% of the hydrocarbons and petroleum data as found in Oil in the Sea III.

C.2 RESULTS

The average annual loads of oil and grease discharged to the sea were calculated for those rivers with reported oil and grease data in STORET (see Table C.6). These total loads were then normalized to unit loads per urban land area. The final estimates of land-based contributions of oil and grease to the sea via all major inland river basins in the United States and Canada were then determined using the oil and grease

Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

data for the Delaware and Potomac rivers (see Table C.7) with urban land area data from State and Metropolitan Area Data Book (2020) and Statistics Canada (2016). About one-seventh of the estimated loading in North America was determined from actual measured data in STORET, with the remainder determined using the unit load approach.

The estimates of land-based contributions of oil and grease to the sea from both major inland rivers and coastal areas in the United States and Canada were totaled by coastal basin, based on the loads calculated in Table C.7 (see Table C.8). The total loading for North America (2.9 million tonne/yr; 4.5 million tonne/yr) was used to obtain a world estimate of land-based oil and grease loading (18.8 million tonne/yr; see Table C.10). The regional distribution of this loading shows that Europe, North America, and Asia contribute the majority of land-based oil and grease to the sea. The population and number of vehicle growth between the years 2000 and 2019 was also looked at for each region (see Table C.9).

Based on the calculations of Oil in the Sea III, a factor of 0.015 was applied to the total oil and grease loading to estimate the fraction of hydrocarbons in oil and grease. The estimated worldwide loading of hydrocarbons to the sea from land-based sources was 259,000 tonnes based on Table C.8 (see Table C.11). Based on Oil in the Sea III, a factor of 0.00015 was applied to the total oil and grease loading to estimate the fraction of PAH in oil and grease. The estimated worldwide loading of PAH to the sea from land-based sources was 2,584 tonne/yr based on Table C.8 (see Table C.11).

C.2.1 Discussion

The method used to estimate land-based oil and grease, hydrocarbon, and PAH contributions to the sea involved a large degree of uncertainty due to a number of factors, including (but not limited to):

  • Lack of data; only 10 major rivers in the United States had oil and grease data in the U.S. Environmental Protection Agency’s STORET database, and many of these consisted of very few observations.
  • Estimating the proportion of petroleum-related hydrocarbons and PAH in oil and grease measurements; the data demonstrate a vastly different proportion of petroleum and hydrocarbon in oil and grease measurements in comparison to the original estimates in Oil in the Sea III.

Quantifying the uncertainty in the estimates presented in this analysis was not possible, but a reasonable estimate of the low and high ranges of the calculated oil and grease values was made (see Table C.12). The low estimate is the lowest unit load per urban land area, 0.15 for the Potomac River. The best estimate was either based on the calculation from available oil and grease data for the river (i.e., Columbia, Delaware, James, Potomac, Roanoke, Sacramento, San Joaquin, Savannah, Susitna, and Susquehanna) or, if those data were not available, an estimate of 1.25 from Oil in the Sea III was used. The estimate of 12.34 was the best estimate for Coastal D, Delaware, and Hudson. The high estimate is the highest unit load per urban land area, 15.88 for the Susquehanna River. Based on these estimates, the range of worldwide loadings of land-based sources of oil and grease to the sea was 7.4–82.5 million tonne/yr, with a best estimate of 21.1 million tonne/yr. For the vehicle-based calculations, the loading per vehicle is based on Oil in the Sea III. The low estimate for loading per vehicle is 0.007619, the best estimate is 0.01573, and the high estimate is 0.055799.

To estimate the range of total petroleum hydrocarbons, STORET data from the Columbia, Potomac, and Mississippi rivers was used. The low estimate was the lowest value for each region from Table C.8. The best estimate was built on the oil and grease and the hydrocarbon and petroleum STORET data, namely the average hydrocarbons and petroleum per urban land area and average oil and grease per urban land area (i.e., ~0.2). The high estimate is based on the proportion of Potomac oil and grease, and hydrocarbon and petroleum data (i.e., ~0.9). The best and high estimates were both proportions of the best estimates of oil and grease annual load (see Table C.12). The estimates of PAH followed suit, assuming PAH constitute 1% of total petroleum hydrocarbons (see Table C.13). The range of land-based petroleum hydrocarbon loading to the sea was 254,000–18,127,000 tonne/yr, with a best estimate of 4,028,000 tonne/yr. The range of PAH loading to the sea from land-based sources was 2,536–181,272 tonne/yr, with a best estimate of 40,281 tonne/yr.

C.2.2 Comparison of Estimates of Land-Based Loading with Other Estimates

The calculations of oil and grease loadings presented in this analysis were based on unit loadings per urban land area. Comparison calculations were also made based on unit loadings per capita urban population using 2019 urban populations in the United States obtained from the State and Metropolitan Area Data Book (2020) and 2016 urban populations in Canada from Statistics Canada (2016). These calculations resulted in oil and grease loadings of the same magnitude as calculations based on unit loadings per urban land area (see Table C.14).

The estimates of the land-based loadings of oil and grease were compared to global and regional oil consumption. According to BP Amoco (2020), North America consumed 1,029 million tonnes of oil in 2019. (The 2019 data was used for comparison, rather than 2020, due to the changes in global oil consumption due to the COVID-19 pandemic.) Assuming that all of the 5.8 million tonne/yr of oil and

Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

grease estimated in this study as returning to the sea from land-based sources were petroleum-derived, then only about 0.56% of consumed oil was returned to the sea from land-based sources. Furthermore, BP Amoco (2020) estimated that the North American annual consumption of oil was broken down as follows:

  • Light Distillates (Gasoline, Naphtha): 519.3 million tonne/yr
  • Middle Distillates (Diesel, Kerosene): 359.5 million tonne/yr
  • Fuel Oil: 20.2 million tonne/yr
  • Other: 312.6 million tonne/yr
  • Total: 1211.6 million tonne/yr

Table C.15 shows comparisons of the computed land-based loads presented in the current study for North America and other regions with the BP Amoco (2020) data.

The best estimate of petroleum hydrocarbon loading from land-based sources was about 3 times as large as the best estimate from the National Research Council (1985), and 28 times as large as Oil in the Sea III (see Table C.16). These discrepancies indicate an increase in oil and grease loadings in the past two decades.

TABLE C.1 Regions Searched for Oil and Grease and Hydrocarbon Data from STORET

River Latitude Longitude Radius (mi)
Alabama-Tombigbee 32°00’00”, 30°00’00” -87°15’00”, -88°15’00” a
Altamaha 32°31’30” -81°15’45” 50
Apalachicola b
Brazos 29°34’56” -95°45’27” 50
Colorado (Texas) 28°58’26” -96°00’44” 30
Columbia 46°10’55” -123°10’50” 50
Copper (Alaska) 61°00’00” -144°45’00” 50
Delaware 39°30’03” -75°34’07” 30
Hudson 41°43’18” -73°56’28” 40
James 37°24’00” -77°18’00” 50
Mississippi 29°16’26” -89°21’00” 50
Neuse 35°06’33” -77°01’59” 50
Potomac 38°55’46” -77°07’02” 75
Rio Grande 25°52’35” -97°27’15” 30
Roanoke 35°54’54” -76°43’22” 70
Sabine 30°18’13” -93°44’37” 50
Sacramento 37°30’00”, 38°30’00” -121°00’00”, -123°00’00” a
San Joaquin 37°30’00”, 38°30’00” -121°00’00”, -123°00’00” a
Santee 33°14’00” -79°30’00” 40
Saskatchewan b
Savannah 32°31’30” -81°15’45” 50
St. Lawrence 45°00’22” -74°47’43” 50
Susitna 61°35’00” -150°22’00” 40
Susquehanna 39°42’00” -76°15’00” 50
Trinity 29°50’10” -94°44’57” 30
Yukon 62°45’00” -164°30’00” 30

a Rectangular polygons formed by the latitudinal and longitudinal coordinates were searched for these rivers

b No data were requested for the Appalachicola and Saskatchewan Rivers.

Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

TABLE C.2 STORET Data Used to Calculate Average Oil and Grease; Hydrocarbons, Petroleum Concentration in Major Inland Rivers

River Monitoring Location Characteristic Name Number of Observations
(non-NA)
Date(s) of Observations Average Concentration
(mg/L)
Columbia River/Stream at Superfund site Hydrocarbons, Petroleum 249 (249) 4/27/04–11/30/05 1.35
Oil and Grease 6 (6) 11/02/04–4/25/05 5.03
Delaware River/Stream 2,000 yds up buoy Oil and Grease 14 (4) 4/24/00–1/26/05 12.55
James Logging runoff from land Oil and Grease 6 (6) 4/19/01–4/28/15 6.83
Mississippi Hurricane Rita/Urban Floodwater Hydrocarbons, Petroleum 4 (2) 9/30/05–10/09/05 1.1
Potomac Peter Pan Run Stream Hydrocarbons, Petroleum 404 (404) 1/10/00–9/21/06 1.43
Oil and Grease 413 (404) 1/10/00–9/21/06 1.55
Roanoke Oil and Grease 2 (2) 5/10/01–8/06/01 5
Sacramento Oil and Grease 20 (1) 1/24/12–3/26/14 0.68
San Joaquin DELS Oil and Grease 6 (6) 4/26/00 0
Savannah Stream BMP intake Oil and Grease 101 (82) 4/07/05–11/07/06 9.74
Susitna Ship Creek, River/Stream Oil and Grease 10 (5) 5/20/11–9/28/11 2.04
Susquehanna Oil and Grease 39 (6) 2/15/001/26/05 11.9

TABLE C.3 Calculations of Average Annual Flows for Major Inland Rivers

River Station Name Period of Record Used Average Annual Flow
(m3/yr)
Alabama–Tombigbee 02469761: Tombigbee River at Coffeeville L&D near Coffeeville, AL 2000–2012; 2014–2015; 2017–2019 24,596,158,257
Altamaha 02226000: Altamaha River at Doctortown, GA 2000–2020 9,894,382,025
Brazos 08114000: Brazos River at Richmond, TX 2000–2020 7,256,268,535
Colorado (Texas) 08162500: Colorado River near Bay City, TX 2000–2007 2,565,942,193
Columbia 14246900: Columbia River at Port Westward, near Quincy, OR 2000–2019 204,666,350,394
Copper (Alaska) 15214000: Copper River at Million Dollar Bridge near Cordova, AK 2010–2011; 2017–2019 59,627,302,886
Delaware 01463500: Delaware River at Trenton, NJ 2000–2019 12,109,284,340
Hudson 01335754: Hudson River above Lock 1 near Waterford, NY 2000–2019 8,257,334,855
James 02037500: James River Near Richmond, VA 2000–2020 6,636,808,160
Mississippi 07289000: Mississippi River at Vicksburg, MS 2000–2020 689,140,762,304
Neuse 02089500: Neuse River at Kinston, NC 2000–2015; 2017–2020 2,391,360,966
Potomac 01608500: South Branch Potomac River near Springfield, WV 2000–2020 1,274,215,458
Rio Grande 08375300: Rio Grande at Rio Grande Village, Big Bend NP, TX 2008–2019 682,154,193
Roanoke 02080500: Roanoke River at Roanoke Rapids, NC 2000–2020 7,115,455,412
Sabine 08030500: Sabine River near Ruliff, TX 2000–2020 7,064,129,254
Sacramento 11425500: Sacramento River at Verona, CA 2000–2020 15,926,970,319
San Joaquin 11303500: San Joaquin R near Vernalis, CA 2000–2020 5,720,145,091
Santee 02198500: Savannah River near Cylo, GA 2000–2020 3,107,890,290
Savannah 02171645: Rediv Canal at Santee River near St. Stephen, SC 2000–2020 8,292,980,383
Susitna 15292000: Susitna River at Gold Creek, AK 2002–2019 9,086,707,310
Susquehanna 01576000: Susquehanna River at Marietta, PA 2000–2020 36,942,927,072
Trinity 08066500: Trinity River at Romayor, TX 2000–2020 8,261,002,528
Yukon 15565447: Yukon River at Pilot Station, AK 2002–2019 210,866,737,379
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

TABLE C.4 Comparison and Change of Average Annual Flow

River Station Name Period of Record Used Average Annual Flow
(m3/yr)
Percent Change
Alabama–Tombigbee 02469761: Tombigbee River at Coffeeville L&D near Coffeeville, AL 1980–1999 26,969,450,885
2000–2012; 2014–2015; 2017–2019 24,596,158,257 -8.80%
Altamaha 02226000: Altamaha River at Doctortown, GA 1980–1999 12,222,829,113
2000–2020 9,894,382,025 -19.05%
Brazos 08114000: Brazos River at Richmond, TX 1980–1999 7,083,041,689
2000–2020 7,256,268,535 2.45%
Colorado (Texas) 08162500: Colorado River near Bay City, TX 1980–1999 2,639,422,583
2000–2007 2,565,942,193 -2.78%
Columbia 14246900: Columbia River at Port Westward, near Quincy, OR 1992–1999 225,024,486,103
2000–2019 204,666,350,394 -9.05%
Copper (Alaska) 15214000: Copper River at Million Dollar Bridge near Cordova, AK 1989–1994 56,287,190,436
2010–2011; 2017–2019 59,627,302,886 5.93%
Delaware 01463500: Delaware River at Trenton, NJ 1980–1999 10,046,323,612
2000–2019 12,109,284,340 20.53%
Hudson 01335754: Hudson River above Lock 1 near Waterford, NY 1980–1999 7,065,137,067
2000–2019 8,257,334,855 16.87%
James 02037500: James River Near Richmond, VA 1980–1999 6,606,492,983
2000–2020 6,636,808,160 0.46%
Mississippi 07032000: Mississippi River at Memphis, TN 1980–1994 492,828,070,403
07289000: Mississippi River at Vicksburg, MS 2000–2020 689,140,762,304 39.83%
Neuse 02089500: Neuse River at Kinston, NC 1983–1999 2,643,275,872
2000–2015; 2017–2020 2,391,360,966 -9.53%
Potomac 01608500: South Branch Potomac River near Springfield, WV 1980–1999 1,327,513,867
2000–2020 1,274,215,458 -4.01%
Rio Grande 08361000: Rio Grande Below Elephant Butte Dam, NM 1980–1999 1,001,672,071
08375300: Rio Grande at Rio Grande Village, Big Bend NP, TX 2008–2019 682,154,193 -31.90%
Roanoke 02080500: Roanoke River at Roanoke Rapids, NC 1980–1999 7,469,397,536
2000–2020 7,115,455,412 -9.82%
Sabine 08030500: Sabine River near Ruliff, TX 1980–1999 7,890,714,278
2000–2020 7,064,129,254 -10.48%
Sacramento 11425500: Sacramento River at Verona, CA 1980–1999 18,506,011,951
2000–2020 15,926,970,319 -13.94%
San Joaquin 11303500: San Joaquin River near Vernalis, CA 1980–1999 4,962,946,910
2000–2020 3,107,890,290 -37.38%
Santee 02171645: Rediv Canal at Santee River near St. Stephen, SC 1987–1999 8,653,431,256
2000–2020 5,720,145,091 -33.90%
Savannah 02198500: Savannah River near Cylo, GA 1980–1985; 1987–1999 10,554,679,518
2000–2020 8,292,980,383 -21.43%
Susitna 15292000: Susitna River at Gold Creek, AK 1980–1986 8,904,929,565
2002–2019 9,086,707,310 2.04%
Susquehanna 01576000: Susquehanna River at Marietta, PA 1980–1999 32,899,408,125
2000–2020 36,942,927,072 12.29%
Trinity 08066500: Trinity River at Romayor, TX 1980–1999 8,461,251,087
2000–2020 8,261,002,528 -2.37%
Yukon 15565447: Yukon River at Pilot Station, AK 1980–1995 209,056,554,789
2002–2019 210,866,737,379 0.86%
Total 1980–1999 1,169,104,231,699
2000–2020 1,341,483,269,604 14.74%
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

TABLE C.5 Percent Change of Urban Land Area and Population in River Basins

River Decade Urban Land Area
(m2)
Percent Change Population Percent Change
Alabama–Tombigbee 1990 19,848,114,806 1,601,369
2000 35,059,114,917 2,270,148
2010 35,197,938,279 77% 2,339,409 46%
Altamaha 1990 5,498,803,735 454,600
2000 8,114,173,718 553,202
2010 8,482,211,028 54% 629,155 38%
Apalachicola 1990 21,708,503,258 4,016,893
2000 32,739,780,573 6,013,671
2010 34,848,289,886 61% 6,692,579 67%
Brazos 1990 14,384,534,909 987,859
2000 27,235,019,866 1,246,704
2010 31,468,355,415 119% 1,493,268 51%
Colorado (Texas) 1990 14,887,769,596 1,173,671
2000 17,605,703,109 1,762,165
2010 19,992,118,114 34% 2,349,110 100%
Columbia 1990 30,466,548,018 1,263,460
2000 101,947,370,591 2,316,164
2010 123,850,640,954 307% 2,953,885 134%
Delaware 1990 5,082,592,647 967,893
2000 6,004,369,412 1,211,805
2010 12,315,393,416 142% 3,419,661 253%
Hudson 1990 21,972,423,045 1,432,124
2000 23,837,991,474 1,587,549
2010 23,789,040,699 8% 1,598,036 12%
James 1990 7,686,825,682 354,043
2000 9,722,802,098 440,200
2010 9,751,305,197 27% 482,181 36%
Mississippi 1990 464,341,095,531 39,900,057
2000 654,764,272,610 48,226,561
2010 699,320,096,893 51% 53,628,488 34%
Neuse 1990 10,472,875,881 1,162,035
2000 11,483,230,239 1,692,198
2010 12,851,520,952 23% 2,158,283 86%
Potomac 1990 1,950,520,038 99,122
2000 6,960,852,018 339,811
2010 12,880,010,821 560% 793,235 700%
Rio Grande 1990 43,843,577,556 1,410,081
2000 52,220,376,067 1,689,829
2010 54,583,999,208 24% 1,912,049 36%
Roanoke 1990 4,830,068,808 337,136
2000 7,478,590,639 403,891
2010 7,461,755,716 54% 414,864 23%
Sabine 1990 6,964,737,000 374,973
2000 7,028,191,708 406,023
2010 9,326,547,148 34% 519,408 39%
Sacramento 1990 30,438,835,145 2,152,519
2000 33,061,198,097 2,873,315
2010 33,037,888,204 9% 3,159,043 47%
San Joaquin 1990 45,968,921,790 2,382,323
2000 49,560,458,289 3,062,479
2010 49,554,242,317 8% 3,366,051 41%
Santee 1990 26,807,930,828 3,183,877
2000 32,722,945,651 3,985,324
2010 40,737,922,825 52% 5,225,755 64%
Savannah 1990 6,342,621,858 457,228
2000 8,492,052,982 534,218
2010 9,015,748,576 42% 608,980 33%
Susquehanna 1990 27,400,261,106 2,788,354
2000 26,140,749,893 2,855,770
2010 27,676,612,837 1% 3,071,255 10%
Trinity 1990 23,581,064,654 4,683,013
2000 23,283,216,023 6,300,006
2010 22,465,556,779 25% 7,573,136 62%
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

TABLE C.6 Calculated Annual Load and Unit Load per Urban Land Area for Major Inland Rivers from STORET Data

River Average Annual Flow
(m3/yr) 2000–2020
Average Concentration
(mg/L)
Average Annual Load
(tonne/yr)
Urban Land Area
(m2) (2019)
Unit Load per Urban Land Area
(g/m2/yr)
Columbia 204,666,350,394 5.03 1,029,471.74 123,850,640,954 8.31
Delaware 12,109,284,340 12.55 151,971.52 12,315,393,416 12.34
James 6,636,808,160 6.83 45,329.4 9,751,305,197 4.65
Potomac 1,274,215,458 1.55 1,975.03 12,880,010,821 0.15
Roanoke 7,115,455,412 5 35,577.28 7,461,755,716 4.77
Sacramento 15,926,970,319 0.68 10,830.34 33,037,888,204 0.33
San Joaquin 3,107,890,290 0 0 49,554,242,317 0
Savannah 8,292,980,383 9.74 80,773.63 9,015,748,576 8.96
Susitna 9,086,707,310 2.04 18,536.88 0 0
Susquehanna 36,942,927,072 11.9 439,620.83 27,676,612,837 15.88

TABLE C.7 Estimates of Land-Based Contributions of Oil and Grease to the Sea via Major Inland River Basins

River Number of Non-NA Observations Average Concentration of Oil and Grease,
(mg/L)
Average Annual Flow
(m3/yr)
Urban Land Area in Watershed
(m2)
Annual Load
(tonne/yr)
Unit Load per Urban Land Area
(g/m2/yr)
Calculated from STORET data
Delaware 4 12.55 12.1 × 109 12.3 × 109 151,972 12.34
Potomac 404 1.55 1.3 × 109 12.9 × 109 1,975 0.15
Subtotal 25.2 × 109 153,947
Calculated from alternative method
Alabama–Tombigbee 35.2 × 109 5,280 0.15
Altamaha 8.5 × 109 1,275 0.15
Apalachicola 35.8 × 109 5,370 0.15
Brazos 31.5 × 109 4,725 0.15
Colorado (Texas) 20 × 109 3,000 0.15
Columbia 123.9 × 109 18,585 0.15
Copper (Alaska) 0 0 0
Hudson 23.8 × 109 293,692 12.34
James 9.8 × 109 120,932 12.34
Mississippi 699.3 × 109 104,895 0.15
Neuse 12.9 × 109 1,935 0.15
Rio Grande 54.6 × 109 8,190 0.15
Roanoke 7.5 × 109 1,125 0.15
Sabine 9.3 × 109 1,395 0.15
Sacramento 33 × 109 4,590 0.15
Santee 40.7 × 109 6,105 0.15
San Joaquin 49.6 × 109 7,440 0.15
Saskatchewan 2.1 × 109 315 0.15
Savannah 9 × 109 1,350 0.15
St. Lawrence 19.7 × 109 2,955 0.15
Susitna 0 0 0
Susquehanna 27.7 × 109 341,818 12.34
Trinity 22.5 × 109 3,375 0.15
Yukon 19 × 109 2,850 0.15
Subtotal 1,295.4 × 109 941,197
Average 2.01
Total 1,320.6 × 109 1,095,144
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

TABLE C.8 Estimate of Land-Based Oil and Grease to the Sea by Coastal Zone Based on Table C.7

Coastal Zone Description Urban Population in Watershed, Pi Urban Land Area in Watershed, Aui (m2) Annual Load, Lai (tonne/yr) z
A No urban areas 0 0 0 0
B Coastal 0 0 0 0
Saskatchewan 3,009,130 2,113,000,000 317 0.15
Subtotal 3,009,130 2,113,000,000 317
C Coastal 1,680,653 1,555,000,000 233 0.15
St. Lawrence 6,278,758 19,676,169,378 2,951 0.15
Coastal 7,959,411 21,231,169,378 3,184
D Coastal 51,808,560 139,545,968,840 1,721,998 12.34
Delaware 3,419,661 12,315,393,416 151,967 12.34
Hudson 1,598,036 23,789,040,699 293,556 12.34
James 482,181 9,751,305,197 120,327 12.34
Potomac 793,235 12,880,010,821 1,932 0.15
Susquehanna 3,071,255 27,676,612,837 341,534 12.34
Subtotal 61,172,928 225,958,331,810 2,631,314
E Coastal 17,810,577 102,074,021,009 15,311 0.15
Altamaha 629,155 8,482,211,028 1,272 0.15
Neuse 2,158,283 12,851,520,952 1,928 0.15
Roanoke 414,864 7,461,755,716 1,119 0.15
Santee 5,225,755 40,737,922,825 6,111 0.15
Savannah 608,980 9,015,748,576 1,352 0.15
Subtotal 26,847,614 180,623,180,106 27,093
F Coastal 8,252,789 52,675,177,978 7,901 0.15
Alabama–Tombigbee 2,339,409 35,197,938,279 5,280 0.15
Apalachicola 6,692,579 34,848,289,886 5,227 0.15
Subtotal 17,284,777 122,721,406,143 18,408
G Coastal 12,773,639 97,880,830,275 14,682 0.15
Brazos 1,493,268 31,468,355,415 4,720 0.15
Colorado (Texas) 2,349,110 19,992,118,144 2,999 0.15
Mississippi 53,628,488 699,320,096,893 104,898 0.15
Rio Grande 1,912,049 54,583,999,208 8,188 0.15
Sabine 519,408 9,326,547,148 1,399 0.15
Trinity 7,573,136 22,465,556,779 3,370 0.15
Subtotal 80,249,098 935,037,503,862 140,256
I No urban areas 0 0 0 0
K Coastal 22,049,766 98,888,335,646 14,833 0.15
L Coastal 9,239,070 46,772,595,098 7,016 0.15
Sacramento 3,159,043 33,037,888,204 4,956 0.15
San Joaquin 3,366,051 49,554,242,317 7,433 0.15
Subtotal 15,764,164 129,364,725,619 19,405
M Coastal 8,542,083 72,757,945,705 10,914 0.15
Columbia 2,953,885 123,850,640,954 18,578 0.15
Subtotal 11,495,968 196,608,586,659 29,492
N Coastal 1,141,980 4,566,149,020 685 0.15
O Coastal 3,011,719 1,367,000,000 205 0.15
P Coastal 396,317 68,430,075,590 10,265 0.15
Copper 0 0 0 0
Susitna 0 0 0 0
Subtotal 396,317 68,430,075,590 10,265
Q Coastal 0 0 0 0
Yukon 96,849 18,984,612,773 2,848 0.15
Subtotal 96,849 18,984,612,773 2,848
Total 250,479,721 2,005.9 × 109 2,880,805
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

TABLE C.9 Percent Change of Global Population and Number of Vehicles

Region Year Population Population Percent Change Number of Vehicles Vehicle Percent Change
Africa 2000 778,484,000 15,569,680
2019 1,306,033,375 68% 44,902,492 188%
Europe 2000 729,406,000 196,939,620
2019 743,131,357 2% 346,027,255 76%
North America 2000 304,078,000 218,936,160
2019 365,889,132 20% 284,430,084 30%
Central America 2000 130,710,000 14,378,100
2019 217,693,617 67% 44,441,062 209%
South America 2000 331,889,000 29,870,010
2019 428,615,774 29% 84,113,596 182%
Asia 2000 3,588,877,000 107,666,310
2019 4,566,180,071 27% 370,533,424 244%
Oceania 2000 29,460,000 12,667,800
2019 42,461,759 44% 22,194,093 75%
Total 2000 5,892,904,000 596,027,680
2019 7,670,005,085 30% 1,196,642,006 101%

TABLE C.10 World Estimates of Land-Based Sources of Oil and Grease to the Sea

Region Population Motor Vehicles per Capita Number of Vehicles Loading per Vehicle Loading (tonne/year)
Africa 1,306,033,375 0.03 44,902,492 0.01573 706,316
Europe 743,131,357 0.47 346,027,255 0.01573 5,443,009
North America 365,889,132 0.78 284,430,084 0.01573 4,474,085
Central America 217,693,617 0.204 44,441,062 0.01573 699,058
South America 428,615,774 0.196 84,113,596 0.01573 1,323,107
Asia 4,566,180,071 0.08 370,533,424 0.01573 5,828,491
Oceania 42,461,759 0.52 22,194,093 0.01573 349,113
Total 7,670,005,085 1,196,642,006 0.01573 18,823,179
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

TABLE C.11 Estimates of Worldwide Land-Based Contributions of Hydrocarbons and PAH to the Sea Based on Table C.8

World Region Coastal Zone Description Hydrocarbon (tonne/year) PAH (tonne/year)
North America A No urban area 0 0
B Coastal 0 0
Saskatchewan 5 0
Subtotal 5 0
C Coastal 3 0
St. Lawrence 44 0
Subtotal 47 0
D Coastal 25,830 258
Delaware 2,280 23
Hudson 4,403 44
James 1,805 18
Potomac 29 0
Susquehanna 5,123 51
Subtotal 39,470 394
E Coastal 230 2
Altamaha 19 0
Neuse 29 0
Roanoke 17 0
Santee 92 1
Savannah 20 0
Subtotal 407 3
F Coastal 119 1
Alabama–Tombigbee 79 1
Apalachicola 78 1
Subtotal 276 3
G Coastal 220 2
Brazos 71 1
Colorado (TX) 45 0
Mississippi 1,573 16
Rio Grande 123 1
Sabine 21 0
Trinity 51 1
Subtotal 2,104 21
I No urban areas 0 0
K Coastal 222 2
L Coastal 105 1
Sacramento 74 1
San Joaquin 111 1
Subtotal 290 3
M Coastal 164 2
Columbia 279 3
Subtotal 443 5
N Coastal 10 0
O Coastal 3 0
P Coastal 154 2
Copper 0 0
Susitna 0 0
Subtotal 154 2
Q Coastal 0 0
Yukon 43 0
Subtotal 43 0
Subtotal 43,474 433
Africa 10,595 106
Europe 81,645 816
Central America 10,486 105
South America 19,847 198
Asia 87,427 874
Oceania 5,237 52
TOTAL 258,711 2,584
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

TABLE C.12 Ranges of Worldwide Land-Based Contributions of Oil and Grease to the Sea

World Region Coastal Zone Description Unit Load Based on Urban Area (g/m2/yr) Annual Load (tonne/yr)
Low Best Estimate High Low Best Estimate High
North America A No urban area 0 0 0 0 0 0
B Coastal 0 0 0 0 0 0
Saskatchewan 0.15 1.25 15.88 317 2,641 33,554
Subtotal 317 2,641 33,554
C Coastal 0.15 1.25 15.88 233 1,944 24,693
St. Lawrence 0.15 1.25 15.88 2,951 24,595 312,455
Subtotal 3,184 26,539 337,148
D Coastal 0.15 12.34 15.88 20,932 1,721,998 2,215,990
Delaware 12.34 12.34 12.34 151,967 151,967 151,967
Hudson 0.15 12.34 15.88 3,568 293,556 377,769
James 0.15 4.65 15.88 1,463 45,342 154,846
Potomac 0.15 0.15 0.15 1,932 1,932 1,932
Susquehanna 0.15 15.88 15.88 4,152 439,511 439,511
Subtotal 184,014 2,654,306 3,342,015
E Coastal 0.15 1.25 15.88 15,311 127,593 1,620,935
Altamaha 0.15 1.25 15.88 1,326 11,053 140,411
Neuse 0.15 1.25 15.88 1,928 16,065 204,090
Roanoke 0.15 4.77 15.88 1,119 35,594 118,497
Santee 0.15 1.25 15.88 6,111 50,923 646,919
Savannah 0.15 8.96 15.88 1,352 80,783 143,174
Subtotal 27,147 322,011 2,874,026
F Coastal 0.15 1.25 15.88 7,901 65,844 836,479
Ala-Tom 0.15 1.25 15.88 5,280 43,998 558,944
Apalachicola 0.15 1.25 15.88 5,227 43,560 553,386
Subtotal 18,408 153,402 1,948,859
G Coastal 0.15 1.25 15.88 14,682 122,351 1,554,350
Brazos 0.15 1.25 15.88 4,720 39,335 499,712
Colorado (TX) 0.15 1.25 15.88 2,999 24,990 317,473
Mississippi 0.15 1.25 15.88 104,898 847,150 11,105,202
Rio Grande 0.15 1.25 15.88 8,188 68,230 866,794
Sabine 0.15 1.25 15.88 1,399 11,659 148,113
Trinity 0.15 1.25 15.88 3,370 28,083 356,760
Subtotal 140,256 1,141,798 14,848,404
I No urban areas 0 0 0 0 0 0
K Coastal 0.15 1.25 15.88 14,833 123,610 1,570,341
L Coastal 0.15 1.25 15.88 7,016 58,466 742,755
Sacramento 0.15 0.33 15.88 4,956 10,903 524,643
San Joaquin 0.15 1.25 15.88 7,433 61,943 786,918
Subtotal 19,405 131,312 2,054,336
M Coastal 0.15 1.25 15.88 10,914 90,948 1,155,397
Columbia 0.15 8.31 15.88 18,578 1,029,202 1,966,754
Subtotal 29,492 1,120,150 3,122,151
N Coastal 0.15 1.25 15.88 685 5,708 72,508
O Coastal 0.15 1.25 15.88 205 1,709 21,708
P Coastal 0.15 1.25 15.88 10,265 85,538 1,086,668
Copper 0 0 0 0 0 0
Susitna 0 0 0 0 0 0
Subtotal 10,265 85,538 1,086,668
Q Coastal 0 0 0 0 0 0
Yukon 0.15 1.25 15.88 2,848 23,731 301,482
Subtotal 2,848 23,731 301,482
Subtotal 451,059 5,792,445 31,613,200
Africa 342,112 706,316 2,505,514
Europe 2,636,381 5,443,009 19,307,975
Central America 338,597 699,058 2,479,767
South America 640,862 1,323,107 4,693,455
Asia 2,823,094 5,828,491 20,675,395
Oceania 169,097 349,113 1,238,408
TOTAL 7,401,202 20,141,549
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

TABLE C.13 Ranges of Worldwide Land-Based Contributions of Hydrocarbons and PAH to the Sea

World Region Coastal Zone Description Hydrocarbons (tonne/yr) PAH (tonne/yr)
Low Best Estimate High Low Best Estimate High
North America A No urban area 0 0 0 0 0 0
B Coastal 0 0 0 0 0 0
Saskatchewan 5 528 2,377 0 5 24
Subtotal 5 528 2,377 0 5 24
C Coastal 3 389 1,750 0 4 18
St. Lawrence 44 4,919 22,136 0 49 221
Subtotal 47 5,308 23,886 0 53 239
D Coastal 25,579 344,400 1,549,798 256 3,444 15,498
Delaware 2,257 30,393 136,770 23 304 1,368
Hudson 4,403 58,711 264,200 44 587 2,642
James 1,787 9,068 40,808 18 91 408
Potomac 29 386 1,739 0 4 17
Susquehanna 519 87,902 395,560 5 879 3,956
Subtotal 34,574 530,860 2,388,875 346 5,309 23,889
E Coastal 230 25,519 114,834 2 255 1,148
Altamaha 19 2,211 9,948 0 22 99
Neuse 29 3,213 14,459 0 32 145
Roanoke 17 7,119 32,035 0 71 320
Santee 92 10,185 45,831 1 102 458
Savannah 20 16,157 72,705 0 162 727
Subtotal 407 64,414 289,812 3 644 2,897
F Coastal 88 13,169 59,260 1 132 593
Ala-Tom 79 8,800 39,598 1 88 396
Apalachicola 78 8,712 39,204 1 87 392
Subtotal 245 30,681 138,062 3 307 1,381
G Coastal 220 24,470 110,116 2 245 1,101
Brazos 71 7,867 35,402 1 79 354
Colorado (TX) 45 4,998 22,491 0 50 225
Mississippi 1,573 169,430 762,435 16 1,694 7,624
Rio Grande 123 13,646 61,407 1 136 614
Sabine 21 2,332 10,493 0 23 105
Trinity 51 5,617 25,274 1 56 252
Subtotal 2,104 228,360 1,027,618 21 2,283 10,275
I No urban areas 0 0 0 0 0 0
K Coastal 222 24,722 111,249 2 247 1,112
L Coastal 105 11,693 52,619 1 117 526
Sacramento 74 2,181 9,813 1 22 98
San Joaquin 111 12,389 55,749 1 124 557
Subtotal 290 26,263 118,181 3 263 1,181
M Coastal 164 18,190 81,853 2 182 819
Columbia 279 205,840 926,282 3 2,058 9,263
Subtotal 443 224,030 1,008,135 5 2,240 10,082
N Coastal 10 1,142 5,137 0 11 51
O Coastal 3 342 1,538 0 3 15
P Coastal 154 17,108 76,984 2 171 770
Copper 0 0 0 0 0 0
Susitna 0 0 0 0 0 0
Subtotal 154 17,108 76,984 2 171 770
Q Coastal 0 0 0 0 0 0
Yukon 41 4,746 21,358 0 47 214
Subtotal 41 4,746 21,358 0 47 214
Subtotal 38,545 1,158,504 5,213,212 385 11,583 52,130
Africa 10,595 141,263 635,684 106 1,413 6,357
Europe 81,645 1,088,602 4,898,708 816 10,886 48,987
Central America 10,486 139,812 629,152 105 1,398 6,292
South America 19,847 264,621 1,190,796 198 2,646 11,908
Asia 87,427 1,165,698 5,245,642 874 11,657 52,456
Oceania 5,237 69,823 314,202 52 698 3,142
TOTAL 253,782 4,028,323 18,127,396 2,536 40,281 181,272
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

TABLE C.14 Comparison of Estimates of Worldwide of Land-Based Oil and Grease Based on Population and Area

World Region Coastal Zone Description Annual Load Based on Population (tonne/yr) Annual Load Based on Area (tonne/yr)
North America A No urban area 0 0
B Coastal 0 0
Saskatchewan 7,329 317
Subtotal 7,329 317
C Coastal 4,093 233
St. Lawrence 15,293 2,951
Subtotal 19,386 3,184
D Coastal 2,302,331 1,721,998
Delaware 151,967 151,967
Hudson 71,015 293,556
James 45,342 45,342
Potomac 1,932 1,932
Susquehanna 439,511 439,511
Subtotal 3,012,098 2,654,306
E Coastal 43,526 15,311
Altamaha 1,532 1,272
Neuse 5,257 1,928
Roanoke 35,594 35,594
Santee 12,728 6,111
Savannah 80,783 80,783
Subtotal 179,420 140,999
F Coastal 21,100 7,901
Alabama–Tombigbee 5,698 5,280
Apalachicola 16,300 5,227
Subtotal 43,098 18,408
G Coastal 31,111 14,682
Brazos 3,637 4,720
Colorado (TX) 5,721 2,999
Mississippi 130,617 104,898
Rio Grande 4,657 8,188
Sabine 1,265 1,399
Trinity 18,445 3,370
Subtotal 195,453 140,256
I No urban areas 0 0
K Coastal 53,704 14,833
L Coastal 22,502 7,016
Sacramento 10,903 10,903
San Joaquin 8,198 7,433
Subtotal 41,603 25,352
M Coastal 20,805 10,914
Columbia 1,029,202 1,029,202
Subtotal 1,050,007 1,040,116
N Coastal 2,781 685
O Coastal 7,335 205
P Coastal 965 10,265
Copper 0 0
Susitna 0 0
Subtotal 965 10,265
Q Coastal 0 0
Yukon 236 2,848
Subtotal 236 2,848
Subtotal 4,613,415 4,051,774
Africa 1,027,411 706,316
Europe 7,917,425 5,443,009
Central America 1,016,853 699,058
South America 1,924,597 1,323,107
Asia 8,478,149 5,828,491
Oceania 507,822 349,113
TOTAL 25,485,672 18,400,868
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

TABLE C.15 Comparison of Oil Consumption with Estimated Oil and Grease Loading from Land-Based Sources to the Sea

Location 2019 Oil Consumption
(million tonne/yr)
Oil and Grease Loading to the Sea from Land-Based Sources
(million tonne/yr)
Ratio of Oil and Grease Loading to the Sea to Oil Consumption
(percent)
North America 1,029 5.8 0.56
South and Central America 274.2 2 0.73
Europe 700 5.4 0.77
Africa 190.1 0.7 0.37
Asia 2,229.3 5.8 0.26
World 4,422.7 20.1 0.45

C.3 UNDERSTANDING LAND-BASED INPUTS OF FOSSIL FUEL HYDROCARBONS TRANSPORTED VIA THE ATMOSPHERE

To understand the inputs of fossil fuel hydrocarbons that are emitted from land and transported via the atmosphere, numerous sampling campaigns to measure petroleum hydrocarbons, specifically PAHs, in marine atmospheres and surface waters have been performed. This increase in data covers a broad geographic area and provides insights into the inputs and sources of PAH compounds to marine surface waters (see Table C.17).

The methods used in these studies are a combination of a high-volume sampler (air) or direct intake (water) passed through a filter to remove particulate matter, followed by a polyurethane foam (PUF; air) or resin (water and sometimes air) sampler to collect the compounds of interest (exception is Lohmann et al., 2011, and Zheng et al., 2021, which used passive polyethylene samplers). The PUF or resin is then extracted with an organic solvent and analyzed primarily via gas chromatography–mass spectrometry (GC-MS) in all but one instance (Nizzetto et al., 2008, uses high-performance liquid chromatography). Quality assurance and quality control including laboratory and field blanks, recoveries and analytical limits are reported in all studies described in the Table C.17. For González-Gaya et al. (2016), the quantification of the semivolatile aromatic-like compounds is more challenging as these compounds cannot be resolved by the gas chromatographic techniques used and are therefore not identified. Given this, the source of these compounds cannot be confirmed, and further examination is required to determine what these compounds are and what their source is. For example, there may be potential inputs from dissolved organic matter derived from biogenic sources. Quantification of the semivolatile aromatic-like compounds also requires further verification before this dataset could provide reliable estimates of inputs in the same way that the PAH measurements are.

TABLE C.16 Comparison of Petroleum Hydrocarbon Loading Estimates from Land-Based Sources from This Work and Other Studies

Hydrocarbon Loading (tonne/yr)
Reference Comments Low Best Estimate High
World estimates
Baker (1983) Petroleum hydrocarbons from municipal wastes, industrial waste, and runoff 700,000 1,400,000 2,800,000
National Research Council (1985) World estimate of land-based sources 600,000 1,200,000 3,100,000
Van Vleet and Quinn (1978) Petroleum hydrocarbons from municipal wastes only based on Rhode Island treatment plants 200,000
Oil in the Sea III (2003) World estimate of land-based sources 6,800 141,000 5,000,000
This work World estimate of land-based sources 254,000 4,000,000 18,000,000
Ratio (This work: Oil in the Sea III) 37 28 3.6
North American estimates
Eganhouse and Kaplan (1982) U.S. input of petroleum hydrocarbons based on mass emission rate for wastewater effluent in southern California 120,600
Oil in the Sea III (2003) North American estimate of land-based sources 2,500 52,000 1,800,000
This work North American estimate of land-based sources 38,500 1,158,500 5,213,200
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
×

TABLE C.17 Studies Examining Polycyclic Aromatic Hydrocarbons in Marine Surface Waters and Atmospheres

Location Sample Type Date Proposed Sources Reference
Atlantic and Indian Ocean Marine aerosol ~15 m above the sea surface (81 samples) 1999 Predominantly fossil fuel with some biomass Crimmins et al., 2004
South Atlantic Air and water samples (14 samples) 2005 Uncombusted fuel, oil spills, gas flaring, ship transport, biomass burning Nizzetto et al., 2008
Narragansett Bay, Atlantic Ocean Air and water samples (72 of each) 2006 Fossil fuel combustion Lohmann et al., 2011
Mediterranean and Black Sea Gas and aerosol (66 samples) and 43 water samples (2–3 m depth) 2006
2007
Gas phase is pyrogenic, aerosol phase is mixture of pyrogenic and petrogenic Castro-Jiménez et al., 2012
East and South China Seas, Bay of Bengal, Indian Ocean, Atlantic Ocean Gaseous (60 samples, 9 PAH) and particle bound (44 samples, 15 PAH) from marine boundary layer 2008 Coal and coke from Mainland China, biomass burning in Africa and Southeast Asia Xu et al., 2012
Southern Ocean Gas (22 samples) and aerosol phase (30 samples) 2005
2008
2009
Long-range transport and local sources, specifics not provided Cabrerizo et al., 2014
Tropical Atlantic Ocean Water (57 samples) and air (47 samples) 2009 Traffic emissions and petroleum combustion products Lohmann et al., 2013
North Pacific toward the Arctic Ocean Boundary layer air (17 samples) and surface seawater (18 samples) 2010 Biomass or coal in air, mixture in seawater Ma et al., 2013
Tropical and subtropical Atlantic, Pacific, Indian Oceans Gas and aerosol (108 samples) and water samples (68) 2010 Mixed sources. SALC also calculated, but quantification more challenging González-Gaya et al., 2016
North Pacific-Arctic Oceans Atmospheric (32) and surface seawater (16) 2014 Combustion-derived via long-range transport, and sea ice melting and runoff Zheng et al., 2021
Livingston Island, Antarctica Air (52 samples), seawater (26 samples, 0.5–1 m depth) 2014
2015
Mixed sources (long-range and local) Casal et al., 2018
Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
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Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
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Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
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Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
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Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
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Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
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Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
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Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
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Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
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Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
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Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
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Suggested Citation:"Appendix C: Estimating Land-Based Sources of Oil in the Sea." National Academies of Sciences, Engineering, and Medicine. 2022. Oil in the Sea IV: Inputs, Fates, and Effects. Washington, DC: The National Academies Press. doi: 10.17226/26410.
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Oil and natural gas represent more than 50 percent of the worldwide energy supply, with high energy demand driven by population growth and improving standards of living. Despite significant progress in reducing the amount of oil in the sea from consumption, exploration, transportation, and production, risks remain. This report, the fourth in a series, documents the current state-of-knowledge on inputs, fates and effects of oil in the sea, reflecting almost 20 additional years of research, including long-term effects from spills such as the Exxon Valdez and a decade-long boom in oil spill science research following the Deepwater Horizon oil spill.

The report finds that land-based sources of oil are the biggest input of oil to the sea, far outweighing other sources, and it also notes that the effects of chronic inputs on the marine environment, such as land-based runoff, are very different than that from an acute input, such as a spill. Steps to prevent chronic land-based oil inputs include reducing gasoline vehicle usage, improving fuel efficiency, increasing usage of electric vehicles, replacing older vehicles. The report identifies research gaps and provides specific recommendations aimed at preventing future accidental spills and ensuring oil spill responders are equipped with the best response tools and information to limit oil’s impact on the marine environment.

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