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:
- 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
-
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
- 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).
- 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
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.
- 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:
- 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.
- 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-3Lai = 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
- 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:
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
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
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.
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 |
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% |
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% |
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 |
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 |
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 |
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 |
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 |
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 |
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 |
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 |
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 |
This page intentionally left blank.