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CHAPTER 5 - Acid Mine Drainage Loadings
Michael Ziegenfuss
Patrick Center for Environmental Research
The Academy of Natural Sciences of Philadelphia
1900 Benjamin Franklin Parkway
Philadelphia, PA 19103-1195
INTRODUCTION
Land use activities in the Chesapeake Bay watershed are diverse and contribute significantly
to water quality. Because of the long history of coal mining in the upper reaches of the Chesapeake
Bay watershed, much concern has been generated regarding the impact of acid drainage from
abandoned coal mines. It is believed that active mines are not a significant source of contaminants
to the Bay since they are permitted, controlled, and treatment programs are in place. The U.S.
Environmental Protection Agency has singled out acid drainage from abandoned coal mines as the
number one water quality problem hi Appalachia. The 1994 Chesapeake Bay Basinwide Toxics
Reduction and Prevention Strategy calls for establishing more complete baseline loadings and source
identification for acid mine drainage and setting reduction targets to be achieved over the next
decade. The Toxics Subcommittee funded a literature synthesis to provide initial loadings estimate
for acid mine drainage and methodologies for remediation. The key loadings information from this
literature synthesis is summarized in this chapter. This is the first time that acid mine drainage
loadings have been reported hi the Toxics Loadings and Release Inventory.
Acid mine drainage from abandoned coal mines has been considered the most severe and
extensive water pollution problem in western Maryland, West Virginia, and northeast, north central
and western Pennsylvania. Within the Chesapeake Bay Basin, drainage from abandoned coal mines
poses a significant threat to water quality in the Susquehanna, West Branch Susquehanna, and
Juniata River basins in Pennsylvania, as well as the North Branch Potomac River and its tributaries
in West Virginia and Maryland.
Acid mine drainage (AMD) is formed when mining operations expose coal and bedrock high
in pyrite (iron-disulfide) to oxygen and moisture. The drainage is characterized by low pH (less than
6.0) and high concentrations of sulfates, acidity, and metals (dissolved/particulate) such as iron,
manganese and aluminum. Other principal elements of coal mine drainage include calcium,
magnesium, sodium and potassium (Clark, 1969). Additional trace metals that have been detected
in AMD in decreasing order of abundance are strontium, zinc, nickel, cobalt, lithium, barium, boron,
copper, lead and cadmium (Wood, 1996).
Factors that affect the concentrations of AMD chemical constituents in coal mine drainage
are mineral content of the coal, overburden (material above the coal deposits), and associated host
5-7
-------
Acid Mine Drainage Loadings
rock; quantity of water flowing through the mine workings; residence time of water circulation in
mine workings; the availability of oxygen and dissolved oxygen in the mine water; method of
mining (e.g., deep underground or surface mining); water removal from mines through pumping; and
the exposed surface area of pyritic minerals.
Efforts to characterize AMD discharges must consider the common variability in flow and
quality. Drainage occurs through various entryways to the mine (e.g., tunnels, shafts, slopes and
drifts). Deep mine discharges in the Anthracite Region are less numerous than in the Bituminous
Field, but contribute a much higher acid loading per discharge. Surface or strip mines in both
Anthracite and Bituminous regions also contribute to AMD. Improperly graded strip pits can trap
surface runoff and form pools containing high concentrations of dissolved salts. During periods of
heavy rainfall, the strip mine pools may overflow and discharge acidic water into nearby streams.
Water trapped in the mine pits frequently emerges as seeps downslope from the mine site causing
pollution of receiving streams. Leachate from coal refuse piles associated with abandoned mine sites
are common sources of AMD. Refuse piles usually cover large areas and provide a source of
minerals for the formation of acid drainage.
TEMPORAL AND SPATIAL COVERAGE
Chemical contaminant loadings from acid mine drainage are summarized from the following
sources: the Susquehanna River Basin (Anthracite Coal Region), West Branch Susquehanna and
Juniata River basins (Bituminous Coal Region) in Pennsylvania, and the North Branch Potomac
River and its tributaries (Bituminous Coal Region) in West Virginia and Maryland. Much of the
available data related to mine drainage was generated during early comprehensive investigations to
identify impacted watersheds and sources of mine acid for the purpose of determining appropriate
AMD abatement measures. These investigations, for the most part, are limited to acid, iron and
sulfate loading estimates and do not contain information on additional pollutants. Consequently,
there are insufficient data on other metals directly associated with mine drainage discharges to
estimate loads from data in these reports.
METHODOLOGY
For the most part, models used to evaluate AMD loads in surface waters have been designed
to evaluate acid loading within a watershed for purposes of designing appropriate abatement
measures to mitigate the adverse impact of acidic conditions. The extensive evaluations of AMD
impacted watersheds conducted by engineering firms in the 1970's monitored all detectable sources
of mine drainage in a watershed for chemical constituents and discharge flow data. In order to define
the extent of AMD loads, it was necessary to determine the volume and chemical quality
(concentrations) of mine drainage at discharge points within the watershed. In-stream water samples
and flow measurements were obtained in addition to mine drainage discharge data to establish
stream quality. Data used for calculating loads were generally collected at regular intervals, usually
5-2
-------
Acid Mine Drainage Loadings
monthly, over the course of one year to evaluate loads during low, average, and high flow
conditions.
UNCERTAINTY
Much of the available data related to mine drainage was generated during comprehensive
investigations conducted in the early 1970's and 1980's to identify impacted watersheds and sources
of mine acid for the purpose of determining appropriate AMD abatement measures. Although these
previous investigations thoroughly identified sources of AMD and associated loads 25-30 years ago,
there is some uncertainty as to whether the historical data are currently applicable.
Estimating AMD loads from in-stream measurements downstream from all sources leads to
uncertainties as to what is attributable to mine discharges versus other point and non-point sources
of the chemical constituents. On the other hand, estimating loads by addition of individual
discharges also has uncertainties as to what proportion of the load is ultimately delivered
downstream. Biological and chemical processes in receiving streams alter chemical concentrations
in mine drainage subsequent to discharge from the AMD source. Iron and aluminum, as well as other
trace metals in mine drainage, commonly precipitate and coat stream beds and, through oxidative-
reductive reactions, sorb and desorb from particles in the receiving stream. These processes alter the
delivery of mine drainage constituents downstream. Data correlating AMD loads in upper reaches
of the Chesapeake Bay watershed with loadings of contaminants entering the Bay are lacking.
DISCUSSION
Acid mine drainage from abandoned coal mines is thought to be the single greatest source
of pollution in the Susquehanna River Basin, West Branch Susquehanna River Subbasin and North
Branch Potomac River Subbasin. Acid mine drainage has impacted 1100 mi in 158 streams in the
Chesapeake Bay drainage area, as indicated in the 1996 Pennsylvania, Maryland and West Virginia
303(d) reports (Table 5.1). The causes cited for water quality degradation from AMD are, for the
most part, related to pH and/or metals. Most of the mines that once produced coal are now
abandoned, but continue to produce and discharge acid drainage. Acid mine drainage is characterized
by low pH and elevated levels of sulfates, acidity and metals such as iron, manganese and aluminum.
Although severe stream degradation from acid occurs within subwatersheds and segments of the
Susquehanna River, West Branch Susquehanna River and North Branch Potomac River, natural
alkaline reserves are capable of neutralizing all acid downstream from the coal regions.
5-5
-------
Acid Mine Drainage Loadings
Table 5.1. Streams in the Chesapeake drainage affected by acid mine drainage and miles impacted.
Compiled from Pennsylvania, West Virginia and Maryland 1996 303(d) lists.
Stream Name
Miles Degraded
Upper Susquehanna River Subbasin
Tioga River
Morris Run
Fall Brook
Long Valley Run
3
1
2
1.6
Upper Central Susquehanna River Subbasin
Lackawanna River
Roaring Brook
Aylesworth Creek
Powderly Creek
Coal Brook
Wilson Creek
Susquehanna River
Newport Creek
Solomon Creek
Black Creek
Little Nescopeck Creek
Catawissa Creek
Tomhickon Creek
Sugarloaf Creek
2.6
4
0.5
1.9
1.9
0.6
20
4.8
2.4
4.3
9.1
27.5
10.6
5.5
Lower Susquehanna River Subbasin
Mahanoy Creek
Zerbe Run
Crab Run
Shenandoah Creek
Shamokin Creek
Carbon Run
Coal Run
Quaker Run
Locust Creek
North Branch Shamokin Cr.
Wiconisco Creek
Rattling Creek
52.2
5.8
1.3
5
34.7
3.7
3
1.3
1.6
4.6
16.2
2.2
5-4
-------
Acid Mine Drainage Loadings
Table 5.1 (continued). Streams in the Chesapeake drainage affected by acid mine drainage and miles impacted.
Compiled from Pennsylvania, West Virginia and Maryland 1996 303(d) lists.
Stream Name
Miles Degraded
(based on length of study segment)
Lower Susquehanna River Subbasin
West Branch Rattling Cr.
Doc Smith Run
Shale Run
East Branch Rattling Cr.
Stone Cabin Run
Nine O'Clock Run
Bear Creek
Pine Creek
Deep Creek
Hans Yost Creek
Rausch Creek
West Br. Rausch Cr.
East Br. Rausch Cr.
Swatara Creek
Baird Creek
West Branch Fishing Creek
Lower Rausch Creek
Lorberry Creek
Stumps Run
Middle Creek
Good Spring Creek
Poplar Creek
Coal Run
Gebhard Run
Panther Creek
5.2
1.5
0.8
3.8
1.8
0.6
4.4
6
4.5
1
1.7
3.5
1.9
21.3
1.4
3.6
6.8
1
0.4
17.5
5.8
0.9
1.6
1.9
1.7
Upper West Branch Susquehanna River Subbasin
Sinnemahoning Creek
Bennett Branch Sinnemahoning Cr.
Dents Run
Trout Run
Spring Run
West Creek
15.8
66.6
6.5
1
1.7
12
5-5
-------
Acid Mine Drainage Loadings
Table 5.1 (continued). Streams in the Chesapeake drainage affected by acid mine drainage and miles
impacted. Compiled from Pennsylvania, West Virginia and Maryland 1996 303(d) lists.
Stream Name
Miles Degraded
(based on length of study segment)
Upper West Branch Susquehanna River Subbasin (cont'd)
Montgomery Creek
West Branch Susquehanna River
Laurel Run
Woods Run
North Branch Montgomery Cr.
Tinker Run
Hartshorn Run
Anderson Creek
Kratzer Run
Irvin Branch
Little Anderson Cr.
Wilson Run
North Camp Run
Rock Run
Bear Run
South Branch Bear Run
Alder Run
Sandy Creek
Big Run
Deer Creek
Surveyor Run
Little Surveyor Run
Trout Run
Taylor Springs Run
Pine Run
Lick Run
Fork Run
Clearfield Creek
Sanbourne Run
North Branch Upper Morgan Run
Little Muddy Run
2.6
79.7
1
3
0.9
0.7
1
10.3
5.1
1.5
5.7
1
1.4
3
2.9
3.3
0.7
2.8
1
5
4
2
5
0.4
2.2
3.7
3.8
71.9
2.2
2.7
4.5
5-6
-------
Acid Mine Drainage Loadings
Table 5.1 (continued). Streams in the Chesapeake drainage affected by acid mine drainage and miles
impacted. Compiled from Pennsylvania, West Virginia and Maryland 1996 303(d) lists.
Stream Name
Miles Degraded
(based on length of study segment)
Upper West Branch Susquehanna River Subbasin (cont'd)
Dutch Run
Brubaker Run
Birch Island Run
Little Birch Island Run
Amos Branch
1.3
2
6.2
4.3
1.6
Upper West Branch Susquehanna River Subbasin
Sterling Run
Mosquito Creek
Curley's Run
Grimes Run
Moshannon Creek
Black Moshannon Creek
Cold Stream
Laurel Run
Goss Run
9.7
6
1.2
2
1
26.2
1
1
0.5
Central West Branch Susquehanna River Subbasin
Pine Creek
Otter Run
Left Fork Otter Run
Right Fork Otter Run
Babb Creek
Wilson Creek
West branch Susquehanna R.
Lick Run
Tangascootack Creek
Drury Run (basin)
Stony Run
Woodley Draft Run
Sandy Run
Kettle Run
Two Mile Run
4
3.8
1.5
0.4
23
2.3
50.6
3.7
8.4
7.3
1.3
1.7
1
3
1.9
5-7
-------
Acid Mine Drainage Loadings
Table 5.1 (continued). Streams in the Chesapeake drainage affected by acid mine drainage and miles
impacted. Compiled from Pennsylvania, West Virginia and Maryland 1996 303(d) lists.
Stream Name
Miles Degraded
(based on length of study segment)
Central West Branch Susquehanna River Subbasin (cont'd)
Hidden Branch Two Mile Rim
Cooks Run (basin)
Crowley Hollow
Camp Run
Rock Run
Beech Creek (basin)
Middle Branch Big Run
East Branch Big Run
Logway Run
Northfork Beech Creek
2.1
6.8
3.1
2
1.2
26
5.5
2.4
0.8
5.9
Lower West Branch Susquehanna River Subbasin
Red Run
West Branch Susquehanna R.
13.4
3
Upper Juniata River Subbasin
Bear Loop Run
Beaver Dam Branch
Sugar Run
Burgeon Run
Kittanning Run
Glenwhite Run
Shoup Run
Miller Run
HartmanRun
Six Mile Run
Sandy Run
Longs Run
Kimber Run
0.8
2.3
6.3
3
4.2
3.2
4.7
1.4
0.6
3.5
2.9
2.5
2.7
5-5
-------
Acid Mine Drainage Loadings
Table 5.1 (continued). Streams in the Chesapeake drainage affected by acid mine drainage and miles
impacted. Compiled from Pennsylvania, West Virginia and Maryland 1996 303(d) lists.
North Branch Potomac River Subbasin
Gladdens Run
Stony River
North Branch Potomac River
Slaughterhouse Run
Montgomery Run
Piney Swamp Run
Abram Creek
Emory Run
Glade Run
Little Creek
DeakinRun
Wills Creek
Georges Creek
Savage River
11.8
24.5
50
2.17
2.81
5.51
18.5
2.25
3.04
0.68
1.15
NA
NA
NA
Tables 5.2-5.4 summarize the cumulative acid mine drainage chemical contaminant loads
in the tributaries of the Susquehanna River, the West Branch Susquehanna River, and the North
Branch Potomac River.
RECOMMENDATIONS
> Current water quality and discharge flow data are needed to support or revise the estimated
loads presented. Recent mine drainage discharge data for the Anthracite Coal Fields were
limited to a single sampling sweep of large discharges. Recent data for discharges in the
West Branch Susquehanna River were not available during the preparation of this literature
synthesis; however new data are being collected by watershed groups. When they become
available, these new data will provide improved estimates of contaminant loading from coal
mine drainage.
> Additional studies are needed to evaluate the transport of AMD chemical constituents
(metals) from the upper reaches of the watershed to the Bay.
> Data correlating AMD loads in upper reaches of the Chesapeake Bay watershed with
loadings of contaminants entering the Bay are lacking.
5-9
-------
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CHAPTER 6 - Fall Line Loadings
Greg Foster Cherie Miller
George Mason University US Geological Survey
4400 University Drive 8789 Yellow Brick Road
Fairfax, VA 22030-4444 Baltimore, MD 21237
INTRODUCTION
The Chesapeake Bay Fall Line Toxics Monitoring Program (FLTMP) was established in
the spring of 1990 as a pilot study to quantify annual loadings of trace metal and organic
contaminants to the Bay from above the fall lines of the major tributaries. The fall line is the
physiographic boundary in the eastern United States between the Piedmont and Atlantic Coastal
Plain provinces, and as the natural geographic break between the tidal and non-tidal regions of
the Bay watershed, the fall line is a convenient location to measure tributary fluxes of
contaminants to the tidal Chesapeake Bay. Loadings above the river fall line represent an
integration and interaction of upstream point and nonpoint sources of contaminants. Factors
such as transport, retention, and attenuation of chemicals from upstream sources affect the
loading at the fall line.
Trace contaminants monitored by the FLTMP have included twelve individual chemicals
and polychlorinated biphenyls (PCBs) derived from the Chesapeake Bay Toxics of Concern list
in addition to other related organonitrogen and organophosphorus (organo-N/P) pesticides,
organochlorine insecticides (OCs), and polycyclic aromatic hydrocarbons (PAH). The goals of
the FLTMP since its inception have been to (a) quantify the inputs of contaminants from the
major tributaries to Chesapeake Bay, (b) assist water quality managers by determining the
concentrations of contaminants in downstream waters of the tributary basins, and (c) characterize
the hydrographic behavior of contaminants in fluvial transport at the fall lines of the major
tributaries. In addition, riverine fluxes are being used in the development of a first-order mass
balance model describing the inputs, transport, fate and cycling of contaminants within the
Chesapeake Bay (Velinsky, 1997).
TEMPORAL AND SPATIAL COVERAGE
Results from the 1990 and 1991 FLTM have been reported previously in the 1994
Chesapeake Bay Basin Toxics Loadings and Release Inventory and will not be provided herein.
The FLTMP has continued from 1992 through 1997, and the tributaries monitored during this
period are summarized in Table 6.1. Different tributaries have been examined in various years of
the FLTMP to provide broad spatial coverage of the Bay basin and to allow for comparisons of
loadings among the major tributary basins. Trace metal and organic contaminants analyzed
through the FLTMP are listed in Tables 6.2 - 6.5 for each year from 1992 to 1997. Monitored
6-1
-------
Fall Line Loadings
organic compounds have included chemicals present on the Toxics of Concern List as well as
additional, structurally related contaminants. Many of the organonitrogen and organophosphorus
pesticides represent high volume agrochemicals used throughout the Chesapeake Bay basin
(Table 6.2). Monitored contaminants in the tributaries, including both inorganics and organic
contaminants, have increased through the years because of greater capabilities available through
the USGS, the University of Delaware, and the George Mason University Environmental
Chemistry Laboratory. Loadings for all monitored organic contaminants have been included in
this report.
Because trace contaminant transport is known to occur in both the dissolved and
particulate phases, loadings in many cases are provided for both phases. Knowledge of the
transport phase is relevant to understanding ultimate geochemical fate in Chesapeake Bay as well
as more accurately defining the exposure of the Bay's living resources to contaminants.
Table 6.1. Summary of Chesapeake Bay Fall Line Toxics Monitoring Program sampling between 1992
and 1997.
Calendar
Year
1992
1993
1994
1995
1996
1997
Tributaries Monitored
Susquehanna, Potomac, and James
Susquehanna
Susquehanna River
Susquehanna, Potomac, James,
Patuxent, Choptank, Nanticoke,
Pamunkey, Mattaponi, Rappahannock
No fall line sampling
Potomac
Chesterville Branch and Nanticoke
Sampling Frequency
Monthly: Feb. - June
Bimonthly: July - Jan. + major storms
2-3 times daily from 3/25/93 -4/3/93
and 1 1 times between 4/4/93 - 5/6/93
for high flow; biweekly from June -
Dec.
Biweekly: Feb. - July
Monthly: Aug.- Dec. + major storms
Spring and Fall synoptic
-
Bimonthly + two major storms
Constituents
metals +
organics
(USGS)a
metals only
(USGS)
metals +
organics
metals +
organics
(USGS, UDE,
GMU)
-
metals only
(UDE)
metals +
organics
(USGS, GMU)
aAgency coordinating contaminant sampling and analysis is indicated in parentheses: USGS, United States
Geological Survey; UDE, University of Delaware; and GMU, George Mason University.
6-2
-------
Fall Line Loadings
Table 6.2. List of organonitrogen and organophosphorus pesticides monitored at the fall line by year.
Organonitrogen & Organophosphorus
Pesticides
Simazine
Prometon
Atrazine
Diazinon
Alachlor
Metolachlor
Malathion
Cyanazine
Hexazinone
1992
X
X
X
X
X
X
X
X
1993
ns
ns
ns
ns
ns
ns
ns
ns
ns
1994
X
X
X
X
X
X
X
X
X
1995
ns
ns
ns
ns
ns
ns
ns
ns
ns
1996
ns
ns
ns
ns
ns
ns
ns
ns
ns
X, constituent monitored; ns, not sampled.
Table 6.3. List of polycyclic aromatic hydrocarbons monitored at the fall line by year.
Polycyclic Aromatic Hydrocarbons
Naphthalene (Nap)a
2-Methylnaphthalene (MN)
2,6-Dimethylnaphthalene (DMN)
Acenaphthylene (ACE)
Acenaphthene (CAN)
Fluorene (FLU)
Phenanthrene (PHE)
Fluoranthene (FLR)
Pyrene (PYR)
Benz[a] anthracene (BAA)
Chrysene (CHR)
Benzofajpyrene (BAP)
Perylene (PER)
1992
X
X
X
X
1993
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
1994
X
X
X
X
X
X
X
X
X
X
X
X
X
1995
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
1996
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
1 PAH abbreviations; X, constituent monitored; ns, not sampled.
6-3
-------
Fall Line Loadings
Table 6.4. List of organochlorine contaminants monitored at the fall line by year.
Organochlorines
alpha-HCH
beta-HCH
gamma-HCH
Heptachlor
Aldrin
Heptachlor epoxide
Oxychlordane
trans-Chlordane
Endosulfan I
cis-Chlordane
trans-Nonachlor
Dieldrin
p,p'-DDE
o,p'-DDD
Endrin
p,p'-DDD
o,p'-DDD
p,p'-DDT
Methoxychlor
PCBs
Hexachlorobenzene
cis- and trans-Permethrin
1992
X
X
X
X
X
X
116CS
X
1993
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
1994
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
116CS
X
1995
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
1996
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
X, constituent monitored; ns, not sampled; CS, PCB congeners
6-4
-------
Fall Line Loadings
Table 6.5. List of trace metals monitored at the fall line by year.
TRACE METALS
Al (dis)
Al (par)
As (dis)
As (TR)
Ba (TR)
Cd (dis)
Cd (par)
Cd (TR)
Cr (dis)
Cr(par)
Cr (TR)
Cu (dis)
Cu (par)
Cu (TR)
Fe (dis)
Fe (par)
Fe(TR)
Pb (dis)
Pb (par)
Pb (TR)
Li (TR)
Mn (dis)
Mn (par)
Mn (TR)
Hg(dis)
Hg(par)
Hg(TR)
Ni (dis)
Ni (par)
Ni(TR)
Se (TR)
Ag(TR)
Sr(dis)
Sr(TR)
Zn (dis)
Zn (par)
Zn (TR)
1992
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
1993
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
1994
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
1995
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
1996
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
X, constituent monitored; ns, not sampled; na, data not available.
6-5
-------
Fall Line Loadings
METHODOLOGY
Sampling was conducted along the fall lines of the Bay's three major tributaries (Figure
6.1) using ultra-clean sampling and analysis techniques for trace metal and organic contaminants
in the river fall line samples. Thorough descriptions of sampling and analysis procedures may be
found in other reports (CBP, 1994c; Foster and Lippa, 1996; Foster et al., in press).
Contaminant concentrations were used to estimate fall-line loadings in conjunction with
stream flow data. All contaminant loads were estimated above the fall lines. Fluvial loadings
above the fall lines were estimated for metals using a log-linear regression model (AMLE model)
described by Cohen et al. (1991) or an Interpolation-Integration (I-I) method over a twelve month
periods (Foster and Lippa, 1996). The AMLE model was preferred and used when data
requirements were met, which happened only with metals data for select years. All organic
contaminant data and some of the trace metal data were too sparse to meet the AMLE model
requirements (Cohen et al., 1991), in which case the I-I model was used. The I-I method, which
estimated baseflow (LBF) and stormflow (LSF) separately, is described by the equations below:
M n,
^L Z
1=1 k=l
F = conversion factor
^y = mean daily discharge (m3/s) on ith day of jth period (base flow)
^u = mean daily discharge (m3/s) on kth day of 1th storm
Cj = concentration (dissolved + particulate) of constituent (kg/m3) in jth period
ckl = concentration (dissolved + particulate) of constituent (kg/m3) on kth day of 1th storm
ty- = hours of base flow on ith day of jth period
tkl = hours of storm flow on kth day of 1th storm
rij = 0.5 number of days in jth period
n, = number of days per storm
N = number of periods
M = number of storms
Each daily load estimated using the I-I method was considered to be derived from
baseflow, stormflow, or a combination of the two in which case daily L,,f and Lsf values were
added together as partial daily loads for the beginning and ending days of the storm event.
6-6
-------
Fall Line Loadings
Estimated daily loads were summed throughout the study period to obtain annual (i.e., 12 month)
loads. Data censoring was employed in the I-I method whenever a contaminant was below the
quantitation limit in the surface water samples. In these cases, separate maximum and minimum
daily loads were estimated by adjusting the sample concentrations to the detection limits
(maximum) in one scenario and to 0 (minimum) in the other. Loadings were estimated as load
intervals when the differences between maximum and minimum estimates exceeded 10%. Mean
daily stream discharges were obtained from the output of USGS gaging stations.
EXPLANATION
45'
26 SO bn£S
T-S '
0 2660 KILOMETERS
45*
Figure 6.1. Map of Chesapeake Bay region showing nine watersheds monitored in 1994 synoptic study.
(Map provided courtesy of the USGS in Baltimore, MD.)
UNCERTAINTY
Estimates of contaminant loadings above the river fall lines are extremely dependent on
river flows, which vary widely throughout the year. The FLTMP was designed to collect river
water samples during baseflow and stormflow hydrologic conditions to obtain contaminant
6-7
-------
Fall Line Loadings
concentrations under wide ranges in flow. With the complexities of analyzing sub-parts-per-
trillion concentrations of contaminants in water, sampling was limited to 25-40 collections per
year. Therefore, the contaminant concentration data used to estimate annual loads was sparse,
especially for organic contaminants, and the spatial and temporal variability of river fall line
concentrations has not been systematically evaluated. The estimated fall line loads represent a
first-order determination of contaminant fluxes in the monitored tributaries. The most accurate
loadings exist for the Susquehanna River because the most intensive sampling effort has been
carried out for this tributary.
Uncertainties in river fall line loading estimates have not been rigorously evaluated. The
AMLE loading estimator provides model prediction errors for each constituent and has been the
preferred method used in this study. However, the AMLE has a minimum threshold for
concentration values (~60 measured concentrations for each constituent over a two year period)
for loading estimates and has been highly dependent on the detection frequency of each
monitored contaminant. Most organic contaminants and several metals have been measured at
less frequency than the model threshold values. (The AMLE model is rarely used with organic
contaminants because the organics data is very sparse and rarely has the FLTMP monitored
organic contaminants in consecutive years, whereas metals are routinely monitored annually
providing a larger basis set for the AMLE model.) Uncertainties determined for the I-I model are
obtained through the analytical procedures. For example, for organic contaminant data the
assigned uncertainties (first evaluated in the 1994 FLTMP) from propagated errors accumulated
through the analytical method; it is assumed in this case that hydrologic uncertainties are
insignificant and remain unknown. Uncertainties are also determined through the I-I model in
the form of loading intervals. When a particular contaminant in a river fall line sample is below
the analytical detection limit, the I-I model estimates two loads. The first is determined using the
analytical detection limit of the contaminant (maximum value) and another using a concentration
of zero. When the annual loads are compiled in the I-I model, an interval may exist for the
maximum to the minimum values. Uncertainty estimates have not been standardized in the
FLTMP and remain an important variable to be addressed in future studies.
DISCUSSION
River fall line loading estimates are a function of many hydrologic, geochemical, and
watershed variables, many of which have not been quantified or evaluated in the Chesapeake
basin. For example, the seasonal application rates of agrochemicals in the Bay's drainage basins
have been only crudely estimated from anecdotal information and for the most part are not
known with any reasonable certainty. Fall line loadings of agrochemicals will be a function of
seasonal application rates which must be better determined in the future. The temporal
variability in river fall line contaminant concentrations at the fall line has not been well
quantified, leaving sampling variability a virtually unknown uncertainty. In addition, the impact
of large storms, annual precipitation, soil moisture, and urban influences are only understood in a
general nature because little scientific data exists which describes or models fluvial transport
dynamics. And finally, the influence of the airshed and atmospheric deposition on fall line
6-8
-------
Fall Line Loadings
loadings is unknown. Therefore, the fall line loading estimates provided to date by the FLTMP
can only be viewed as preliminary, first-order flux values which provide very little in the way of
understanding the underlying mechanisms of transport. Other sources of information such as
land use and point source delineations also need good documentation as sources of the various
contaminants.
Loadings above the river fall lines represent an integration and interaction of all point and
non-point source inputs upstream from the point of sampling. Major upstream contributors to the
fall line loads cannot be determined without further systematic investigation; however,
correlations have been developed between contaminants and sources. For example, the
organonitrogen and organophosphorus pesticide inputs arise primarily from agricultural (e.g.,
atrazine and metolachlor) and urban (e.g., diazinon) sources, and the PAHs are derived primarily
from urban sources where large amounts of pyrolysis by-products are formed through gas phase
combustion. PCBs and organochlorine inputs have been less well characterized and are thought
to come from contaminated industrial sites, long-term sequestration into agricultural and urban
soils, and atmospheric deposition from global transport and cycling.
The most important variable influencing fall line loadings is river discharge because (a)
river discharge was such a large loadings driver relative to the fall line contaminant
concentrations in the loading estimation methods (given that the baseline river fall line
contaminant concentrations were generally in the low parts per billion to low parts per trillion
range), (b) and seasonal variability in river discharge in the major tributaries changed over a
greater scale than river fall line contaminant concentrations. Annual loadings for the organic
contaminants are listed in Tables 6.6 - 6.14 for the fall lines of the three major tributaries of the
Bay (Susquehanna, Potomac, and James Rivers) for the various chemical classes (organonitrogen
and organophosphorus pesticides, polycyclic aromatic hydrocarbons, and organochlorines). The
largest loadings were observed for the current use agrochemicals (e.g., atrazine, metolachlor, and
cyanazine) followed sequentially by the PAHs, PCBs, and organochlorine pesticides. The fall
line loadings estimated for the three major tributaries for most of the contaminants were
proportional to the land areas of each of the drainage basins. Thus, the Susquehanna River
fallline showed the largest loadings followed by the Potomac and James Rivers.
Trace metal loads above the three major tributaries are listed in Tables 6.15-6.17.
Aluminum had the greatest total annual load, followed by iron, then manganese. These results
reflected the crustal abundances of these metals. The lowest total load occurred for cadmium
although the loads for this element still appeared to be significantly higher than expected from
crustal abundance.
Instantaneous loads for the organic contaminants and trace metals in the nine tributary
synoptic study in 1994 are shown in Tables 6.18 - 6.25. Results of the spring tributary synoptic
study showed that for all trace metals, with the exception of iron, the largest instantaneous loads
were above the Susquehanna River fall line. However, the loads at the Potomac and James
6-9
-------
Fall Line Loadings
Rivers were greater than those for all of the other seven tributaries. These loads are, in part, the
result of higher river flows measured at these three river sites than those at the other six
tributaries. Organic contaminants followed the same trend, with the largest instantaneous loads
occurring above the Susquehanna, Potomac, and James River fall lines.
CORRELATION WITH 1994 TOXICS LOADING AND RELEASE INVENTORY
Organic contaminant loads reported in the 1994 TLRI included only atrazine
(Susquehanna and James Rivers), metolachlor, and alachlor (Susquehanna River only).
Analytical detection limits were insufficient to determine accurate loads for any other organic
constituents in the 1990 and 1991 fall line toxics monitoring program. Average annual atrazine
loads above the fall line of the Susquehanna River for 1990 and 1991 were found to be 4,000 kg,
where as in 1992 and 1994, atrazine loads above the Susquehanna River fall line were estimated
to be 1,700 kg and 2,970 kg, respectively. These loading estimates are all within a factor of 3,
which is quite good considering the change in analytical methods and load estimation techniques
during 1990-1994.
Variation in annual loads for all contaminants is most directly related to discharge above
the fall line. The average annual river discharges measured at the Susquehanna River fall line (at
Conowingo, MD) were 1,000 m3/s, 1,494 m3/s, 1,464 m3/s for 1992, 1993, and 1994,
respectively. The generally higher loadings estimated for organic and metal contaminants in
1994 in comparison to 1992, for example, can be attributed primarily to higher discharge in 1994
recorded at the Susquehanna River fall line.
There are other factors which account for the annual variability seen in the fall line load
estimates. Changes in analytical methodology, hydrographic and sampling variability, and
changes in watershed characteristics all affect fall line loadings. None of these factors has been
previously evaluated.
RECOMMENDATIONS
Contaminant loadings above the fall lines of the major northern and western shore
tributaries have been estimated for organics and metals between 1990-1994. We now have a
picture of the magnitudes of contaminant loadings to Chesapeake Bay from the major tributaries.
The fall line monitoring program has fulfilled the objectives of the pilot phase, which has been to
provide preliminary loading estimates for contaminants to the Bay from the rivers. Future work
should be devoted to refining the loading estimates for contaminants in the next phase of the
program: to be able to compare loadings estimated among the various sources. To accomplish
an accurate mass budget and preliminary model development for quantifying input of
contaminants to Chesapeake Bay, refined estimates of the uncertainties of loadings via the
tributaries are needed. To address this issue the following recommendations are put forward:
6-10
-------
Fall Line Loadings
Better define contaminant behavior above the fall lines in the watersheds. There needs to
be more mechanistic orientation of how contaminants enter and are transported in rivers.
Include the influence of the air shed in fall line loadings. We need to better understand
source dynamics in the watershed. Where do the contaminants ultimately come from?
Do they originate from contaminated soils, urban runoff, or atmospheric deposition?
These questions need to be addressed to move into the modeling phase of contaminant
transport in the Bay watershed.
Better define the uncertainties in the magnitudes of the fall line load estimates. The
Susquehanna and/or Potomac Rivers should be used as model basins to more precisely
define the factors which affect the loading estimates and to systematically quantify the
uncertainties in loadings estimates.
Better link the contaminant release information with fall line loadings. For example,
contaminant release data should support the fall line loading estimates by determining
pesticide application rates within river basins rather than within the states or counties.
To more fully understand the effects of extremely high flow events in the major
tributaries. Many contaminants are stored in sediments up in the watersheds, and
extremely high flow events may promote the transport of these contaminants to the Bay
in very large quantities over short time frames. These low frequency events may have
profound implications to the biological effects of contaminants in the Bay.
Establish one or more long-term contaminant-loading stations. We have established that
the majority of the loadings occur through the rivers if we look at the nutrient model.
Long-term data is essential for resolving management issues. We recommend that each
state in the watershed select one site, such as:
PA - Conowingo Dam (Susquehanna River)
Washington, D.C. - Chain Bridge (Potomac River)
VA - Cartersville (James River)
MD - Choptank or Nanticoke Rivers (Eastern Shore)
We recommend combining funds from EPA, USGS, and the states to start long-term
monitoring using our low-level techniques.
6-11
-------
Fall Line Loadings
Table 6.6. Annual loads (kg/yr) of organonitrogen and organophosphorus pesticides above the fall line
(AFL) of the Susquehanna River.
Organonitrogen &
Organophosphorus Pesticides
Simazine
Prometon
Atrazine
Diazinon
Alachlor
Metolachlor
Malathion
Cyanazine
Hexazinone
Estimation
Method
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
3/92-2/93
AFL
580-610
110-160
1700
8-98
97-106
920
8-86
430-480
170-180
2/93-1/94
AFL
.
.
-
.
.
_
.
-
-
2/94-1/95
AFL
2010-2020
1030
2970
220-260
710
2450
20-180
3010
130-250
Table 6.7. Annual loads (kg/yr) of organonitrogen and organophosphorus pesticides above the fall line
(AFL) of the Potomac River.
Organonitrogen &
Organophosphorus Pesticides
Simazine
Prometon
Atrazine
Diazinon
Alachlor
Metolachlor
Malathion
Cyanazine
Hexazinone
cis- and trans-Fenvalerate
cis- and trans-Permethrin
Estimation
Method
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
3/92-2/93
AFL
340
56-66
780
3-27
25-44
390
3-25
220-230
6-14
_
-
2/93-1/94
AFL
_
_
_
.
_
-
-
_
-
.
-
2/94-1/9S
AFL
.
.
_
_
_
-
-
_
-
_
-
6-12
-------
Fall Line Loadings
Table 6.8. Annual loads (kg/yr) of organonitrogen and organophosphorus pesticides above the fall line
(AFL) of the James River.
Organonitrogen &
Organophosphorus Pesticides
Simazine
Prometon
Atrazine
Diazinon
Alachlor
Metolachlor
Malathion
Cyanazine
Hexazinone
Estimation
Method
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
3/92-2/93
AFL
130-140
18-26
220
20-30
15-28
89-92
3-18
32-43
18-26
2/93-1/94
AFL
-
-
-
-
.
-
.
-
-
2/94-1/95
AFL
-
-
-
-
-
-
-
_
-
Table 6.9. Annual loads (kg/yr) of polycyclic aromatic hydrocarbons above the fall line (AFL) of the
Susquehanna River.
Polycyclic Aromatic Hydrocarbon
Naphthalene
2-Methylnaphthalene
2,6-Dimethylnaphthalene
Acenaphthylene
Acenaphthene
Fluorene
Phenanthrene
Fluoranthene
Pyrene
Benz[a]anthracene
Chrysene
Benzo[a]pyrene
Perylene
Estimation
Method
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
i_ u
I-I
3/92-2/93
AFL
300
_
_
_
-
_
98-120
.
_
55-120
-
14-120
-
2/93-1/94
AFL
.
.
-
-
-
_
-
_
_
-
-
-
-
2/94-1/95
AFL
_
220
140
50
57
120
450
1130
1030
380
330
440
480
6-13
-------
Fall Line Loadings
Table 6.10. Annual loads (kg/yr) of polycyclic aromatic hydrocarbons above the fall line (AFL) of the
Potomac River.
Polycyclic Aromatic Hydrocarbon
Naphthalene
2-Methylnaphthalene
2,6-Dimethylnaphthalene
Acenaphthylene
Acenaphthene
Fluorene
Phenanthrene
Fluoranthene
Pyrene
Benz[a]anthracene
Chrysene
Benzo[a]pyrene
Perylene
Estimation
Method
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
3/92-2/93
AFL
60-75
_
_
-
-
.
19-23
-
-
29-48
-
11-49
-
2/93-1/94
AFL
.
_
_
_
-
.
-
.
-
_
-
-
-
2/94-1/95
AFL
_
_
.
_
.
-
-
-
-
_
-
-
-
Table 6.11. Annual loads (kg/yr) of polycyclic aromatic hydrocarbons above the fall line (AFL) of the
James River.
Polycyclic Aromatic Hydrocarbon
Naphthalene
2-Methylnaphthalene
2,6-Dimethylnaphthalene
Acenaphthylene
Acenaphthene
Fluorene
Phenanthrene
Fluoranthene
Pyrene
Benz[a]anthracene
Chrysene
Benzo[a]pyrene
Perylene
Estimation
Method
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
3/92-2/93
AFL
43-67
_
_
_
_
-
140
-
-
26-35
-
61-82
-
2/93-1/94
AFL
-
.
_
.
-
-
-
_
_
.
-
-
-
2/94-1/95
AFL
-
-
-
-
-
-
-
-
-
-
-
-
-
6-14
-------
Fall Line Loadings
Table 6.12. Annual loads (kg/yr) of organochlorines above the fall line (AFL) of the Susquehanna River.
Organochlorines
alpha-HCH
beta-HCH
gamma-HCH
Oxychlordane
trans-Chlordane
cis-Chlordane
trans-Nonachlor
Dieldrin
p,p'-DDE
o,p'-DDD
Endrin
p,p'-DDD
p,p'-DDT
Methoxychlor
PCBs
Hexachlorobenzene
cis- and trans-Fenvalerate
cis- and trans-Permethrin
Estimation
Method
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
3/92-2/93
AFL
-
.
_
26-32
11-17
21-28
-
7-14
-
-
.
-
6-29
-
170-198
-
14-44
4-95
2/93-1/94
AFL
-
.
-
-
-
-
-
-
-
-
.
-
-
-
-
-
-
-
2/94-1/95
AFL
11
6
18
10
12
6
13
12
16
20
4-11
13
12
1-8
160-190
4
-
-
6-15
-------
Fall Line Loadings
Table 6.13. Annual loads (kg/yr) of organochlorines above the fall line (AFL) of the Potomac River.
Organochlorines
alpha-HCH
beta-HCH
gamma-HCH
Oxychlordane
trans-Chlordane
cis-Chlordane
trans-Nonachlor
Dieldrin
p,p'-DDE
o,p'-DDD
Endrin
p,p'-DDD
p,p'-DDT
Methoxychlor
PCBs
Hexachlorobenzene
cis- and trans-Fenvalerate
cis- and trans-Permethrin
Estimation
Method
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
3/92-2/93
AFL
-
-
-
14-15
4-6
13-15
_
13-15
.
_
_
-
3-10
-
22-48
.
-
-
2/93-1/94
AFL
-
-
-
-
.
.
-
-
_
.
.
.
-
-
.
-
-
-
2/94-1/95
AFL
_
-
.
-
-
-
_
_
-
.
-
-
-
-
-
-
-
-
6-16
-------
Fall Line Loadings
Table 6.14. Annual loads (kg/yr) of organochlorines above the fall line (AFL) of the James River.
Organochlorines
alpha-HCH
beta-HCH
gamma-HCH
Oxychlordane
trans-Chlordane
cis-Chlordane
trans-Nonachlor
Dieldrin
p,p'-DDE
o,p'-DDD
Endrin
p,p'-DDD
p,p'-DDT
Methoxychlor
PCBs
Hexachlorobenzene
cis- and trans-Fenvalerate
cis- and trans-Permethrin
Estimation
Method
I-I
I-I
I-I
I-I
I-I
I-I
I-i
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
I-I
3/92-2/93
AFL
-
-
-
6-10
11-12
16-19
-
3-4
-
-
-
-
0.1-6
-
18-32
-
.
-
2/93-1/94
AFL
-
-
-
-
-
.
-
-
-
-
-
.
-
-
-
-
.
-
2/94-1/95
AFL
-
_
_
_
_
_
-
-
.
-
_
_
_
_
.
_
_
-
6-17
-------
Fall Line Loadings
Table 6.15. Annual loads (metric tons per year) of trace metals above the fall line (AFL) of the
Susquehanna River.
Trace Metals
Al
As
Cd
Cr
Cu
Fe
Pb
Mn
Hg
Ni
Zn
Estim.
Method
1992
AMLE
II
II
II
AMLE
AMLE
AMLE
II
AMLE
AMLE
Loads
3/92-2/93
AFL'
828-994
0-32
0-32
64-74
60-71
17-29
42-53
.
0.3-3
147-190
349-453
Estim.
Method
1993
AMLE
II
II
II
AMLE
AMLE
AMLE
AMLE
- ••• • —
Loads
2/93-1/94
AFL"
1,111-1,388
12-49
0-46
80-94
111-135
76,448-
119-163
.
-
-
992-1,314
Estim.
Method
1994
II
II
II
II
II
II
II
II
II
Loads
2/94-1/95
AFL"
67,400
_
29
115-116
199
44,100
45
4,830
.
186
438
"Loads determined from total recoverable concentrations except for Al loads for 1992 and 1993 in which they were determined
from dissolved (only) concentrations.
bLoads determined from the sum of dissolved and paniculate concentrations.
Table 6.16. Annual loads (kg/yr X 10'3) of trace metals above the fall line (AFL) of the Potomac River.
Trace Metals
Al
As
Cd
Cr
Cu
Fe (dissolved only)
Pb
Mn
Hg
Se
Ni
Zn
Estim.
Method
1992
II
II
II
II
II
II
n
ii
ii
Loads
3/92-2/93
AFL'
-
0-58
0-19
31-50
44-60
_
41-77
.
„
0-76
60-167
241-327
Estim.
Method
1993
Loads
2/93-1/94
AFL
.
_
_
.
_
_
_
_
„
.
.
Estim.
Method
1994
Loads
2/94-1/95
AFL
_
_
_
_
_
_
_
_
_
_
-
"Loads determined from total recoverable concentrations.
6-18
-------
Fall Line Loadings
Table 6.17. Annual loads (metric tons per year) of trace metals above the fall line (AFL) of the James
River.
Trace Metals
Al
As
Cd
Cr
Cu
Fe (dissolved only)
Pb
Mn
Hg
Ni
Zn
Estim.
Method
1992
AMLE
II
II
AMLE
AMLE
AMLE
AMLE
II
AMLE
AMLE
Loads
3/92-2/93
AFL"
729-949
0-4
0-6
31-44
22-28
1,490-1,940
24-34
-
0.02-0.6
25-38
93-118
Estim.
Method
1993
Loads
2/93-1/94
AFL
-
-
-
-
.
.
.
-
-
-
-
Estim.
Method
1994
Loads
2/94-1/95
AFL
-
-
-
_
.
_
_
_
_
_
-
"Loads determined from total recoverable concentrations except for Al which was determined from dissolved (only)
concentrations.
Table 6.18. Instantaneous loads (mg/s) of organonitrogen and organophosphorus pesticides above the
fall lines or head of tide of the nine major tributaries of Chesapeake Bay from March 26 through May 5,
1994.
Simazine
Prometon
Atrazine
Alachlor
Metolachlor
Cyanazine
Hexazinone
Pam
0.50
0.17
0.51
0.009
0.056
0.020
0.38
Mat
0.010
0.083
0.12
0.051
0.005
0.016
0.29
Jam
2.40
0.52
1.02
0.064
0.045
0.14
0.52
Rap
0.58
0.27
0.61
0.016
0.011
0.036
0.66
Pot
18.2
4.31
17.8
0.90
5.40
1.93
28.8
Chop
0.81
0.18
2.98
0.15
0.84
0.11
2.14
Nant
0.82
0.085
0.24
0.13
0.041
0.017
0.37
Pat
0.005
0.005
0.004
0.003
0.002
0.007
0.002
Sus
154
13.8
172
8.46
39.9
1.43
174
6-19
-------
Fall Line Loadings
Table 6.19. Instantaneous loads (mg/s) of organonitrogen and organophosphorus pesticides above the
fall lines or head of tide for the nine major tributaries of Chesapeake Bay from November 8 through
November 18, 1994.
Simazine
Prometon
Atrazine
Alachlor
Metolachlor
Cyanazine
Hexazinone
Pam
0.209
0.049
0.085
0.007
0.002
0.054
0.028
Mat
0.30
0.031
0.055
0.002
0.001
0.005
0.017
Jam
0.59
0.32
0.15
0.034
0.013
0.040
0.061
Rap
0.51
0.088
0.25
0.007
0.003
0.011
0.22
Pot
3.67
1.38
3.20
0.047
0.107
0.057
1.35
Chop
0.031
0.008
0.013
0.000
0.005
0.001
0.026
Nant
0.019
0.009
0.011
0.001
0.045
0.001
0.047
Pat
0.27
0.076
0.26
0.095
0.015
0.003
0.19
Sus
0.077
1.37
4.51
0.27
0.65
0.81
2.83
Table 6.20. Instantaneous loads (mg/s) of polycyclic aromatic hydrocarbons above the fall line or head
of tide of the nine major tributaries of Chesapeake Bay from March 26 through May 5,1994.
MNa
DMN
ACE
CAN
FLU
PHEN
FLR
PYR
CHR
BAA
BAP
PER
Pam
0.12
0.31
0.037
0.020
0.003
0.005
0.011
0.028
0.025
0.014
0.001
0.001
Mat
0.076
0.015
0.012
0.002
0.003
0.006
0.008
0.032
0.019
0.009
0.001
0.001
Jam
18.9
0.67
0.23
0.46
0.080
0.25
0.32
0.68
0.76
L0.49
0.26
0.18
Rap
0.011
0.028
0.023
0.056
0.003
0.003
0.018
0.051
0.030
0.015
0.003
0.001
Pot
24.3
0.74
1.18
6.09
0.74
0.56
1.39
3.70
13.2
9.46
4.49
3.15
Chop
1.13
0.014
0.008
0.004
0.002
0.011
0.010
0.023
0.013
0.008
0.000
0.000
Nant
0.15
0.011
0.004
0.007
0.002
0.004
0.005
0.010
0.018
0.017
0.001
0.001
Pat
0.002
0.007
0.000
0.007
0.001
0.001
0.003
0.027
0.11
0.091
0.032
0.032
Sus
85.2
1.43
5.84
9.93
1.30
1.52
3.66
10.2
56.1
42.9
6.95
7.31
' Refer to Table 3 for PAH abbreviations.
6-20
-------
Fall Line Loadings
Table 6.21. Instantaneous loads (mg/s) of polycyclic aromatic hydrocarbons above
the nine major tributaries of Chesapeake Bay from November 8 through November
the fall line or head of tide of
18, 1994.
MN
DMN
ACE
ACN
FLU
PHEN
FLR
PYR
CHR
BAA
BAP
PER
Pam
0.002
0.12
0.018
0.001
0.008
0.002
0.001
0.019
0.016
O.001
O.001
O.001
Mat
0.001
0.053
0.013
O.001
0.003
0.001
O.001
0.006
0.007
O.001
0.003
O.001
Jam
5.69
0.33
0.26
0.005
0.028
0.001
O.001
0.088
0.093
0.021
0.052
0.009
Rap
0.003
0.009
0.034
0.001
0.004
0.001
O.001
0.005
0.005
O.001
0.001
O.001
Pot
6.12
0.14
0.20
0.11
0.079
0.043
0.010
0.27
0.45
0.24
0.29
0.11
Chop
O.001
0.003
0.006
0.007
0.001
O.001
0.001
0.001
0.001
O.001
0.001
O.001
Nant
O.001
0.003
0.003
O.001
0.001
O.001
O.001
O.001
0.001
O.001
0.001
O.001
Pat
0.001
0.041
0.020
0.001
0.009
O.001
0.001
0.017
0.033
0.020
0.019
0.007
Sus
7.005
0.120
0.598
0.312
0.136
0.078
0.292
0.807
1.548
1.384
0.679
0.820
Table 6.22. Instantaneous loads (mg/s) of organochlorines above the fall line or head of tide of the nine major
tributaries of Chesapeake Bay from March 26 through May 5, 1994.
PCBs
HCB
p,p'-DDE
p,p'-DDT
cc-BHC
P-BHC
Y-BHC
Oxychlor
Y-Chlordane
cc-Chlordane
t-Nonachlor
Dieldrin
o,p'-DDD
Endrin
p,p'-DDD
Pam
0.0002
0.0870
0.0399
0.0024
0.0002
-------
Fall Line Loadings
Table 6.23. Instantaneous loads (mg/s) of organochlorines above the fall line or head of tide of the nine
major tributaries of Chesapeake Bay from November 8 through November 18, 1994.
PCBs
HCB
p,p'-DDE
p,p'-DDT
cc-BHC
P-BHC
Y-BHC
Oxychlor
y-Chlordane
cc-Chlordane
t-Nonachlor
Dieldrin
o,p'-DDD
Endrin
p,p'-DDD
Pam
-------
Fall Line Loadings
Table 6.25. Instantaneous loads (mg/s) of total trace metals above the fall line or head of tide of the nine
major tributaries of Chesapeake Bay from November 8 through November 18, 1994.
Al
Cd
Cr
Cu
Fe
Mn
Ni
Pb
Zn
Pam
3860
naa
2.95
12.8
6350
550
9.19
2.71-
2.92
67.6
Mat
548
0.74
3.22
3.88
5980
175
5.85
2.45
10.6
Jam
966
4.19
L21.4
22.6
6100
313
37.5
3.05-
4.51
24.2-
25.1
Rap
390
0.51
2.84
8.29
1130
40.4
7.55
1.28
7.92
Pot
17800
5.57
68.9
72.2
12400
648
64.4
10.7
115
Chop
14.6
0.11
0.26
0.15
L548
11.9
0.93
0.02-
0.05
0.94
Nant
46.6
0.22
1.00
0.24
161
13.4
2.12
0.00-
0.04
18.7
Pat
186
0.56
1.97
2.75
1420
381
5.85
0.45
20.6
Sus
126000
929
4550
2180
651000
94300
3230
1270
5670
"not available
6-23
-------
CHAPTER 7 - Pesticide Usage and Occurrence in Surface
and Ground Water
Eric Maurer
Chesapeake Bay Program Office
Environmental Protection Agency
410 Severn Avenue, Suite 109
Annapolis, MD 21403
INTRODUCTION
The use of pesticides for agricultural and non-agricultural purposes and the potential for
these chemicals to adversely affect both surface and ground water as well as the Bay's living
resources is a concern of the Chesapeake Bay Program. Although the use of pesticides is a
necessary aspect of pest control, Integrated Pest Management (IPM) techniques can be utilized to
potentially reduce the use of pesticides and possible risks associated with these chemicals.
Additionally, the utilization of IPM practices improves the overall management of farm inputs.
Some examples of IPM techniques include scouting, planting resistant varieties, crop rotation,
and utilizing biological controls.
Current data show that more than 30 percent of the cropland acreage within the watershed
is under some level of IPM. These data, however, are inconsistent between the states and may
not capture the total number of acres under IPM. The Pesticide Workgroup (workgroup) of the
Toxics Subcommittee is currently initiating efforts to capture data on the adoption of IPM
techniques within the Chesapeake Bay watershed to determine the level of education and
outreach efforts necessary to increase IPM.
To determine the potential impacts to the Bay, a current pesticide usage analysis must be
completed to determine what pesticides are actually being used. This will allow IPM managers
to focus efforts on those pesticides with the highest risk as well as determine a baseline from
which to measure any decrease in pesticide use.
PESTICIDE USAGE ANALYSIS
Pesticide use in the Chesapeake Bay watershed in terms of pounds of active ingredient
(AT) applied is targeted mainly toward weed control on agronomic crops. The control of
competitive weed populations in corn, soybeans, alfalfa, and small grains through pesticide
inputs allows farmers to minimize labor, equipment, and time constraints associated with specific
farm economics.
7-1
-------
Pesticide Use
This chapter summarizes usage estimates from 1990 -1996 for those pesticides that are
used most frequently on the four major crops within the Chesapeake Bay watershed: corn,
alfalfa, soybeans, and small grams (wheat, oats/rye, and barley). These crops represent
approximately 80-90 percent of all cropland within the watershed, excluding other hay and land
used for pasture. The data for the remaining crops that represent 10-20 percent of the cropland
will not likely be as reliable at the state level. Thus, these data were not presented. Data
gathering techniques utilized for this usage analysis are explained later in this chapter.
Although this analysis quantifies only the most frequently used pesticides on each of the
four crops, there are also several others which were listed that show relatively minor usage across
all three states. For example, although only 10,000 pounds AI of aldicarb were applied to
soybeans in 1996, it was the only insecticide that displayed any quantifiable usage. Thus, it was
included hi the table to provide the reader with an idea of which insecticide was typically chosen.
If these pesticides were not unique in some fashion, they were not included in the table.
Figures 7.3 and 7.4 provide a trend analysis of pesticide usage from 1990-1996 in terms
of pounds AI applied to agricultural lands and multiple acres treated within the Bay watershed.
These tables provide context to the chemical specific analysis provided hi Tables 7.1-7.5. The
differences between the aggregated 1996 estimates presented in Table 7.1 and those presented hi
Figures 7.3 and 7.4 can be explained by the number of chemicals accounted for in each of the
analyses. The number of chemicals accounted for hi Tables 7.1-7.5 is a subset of the total range
of pesticides presented in Figures 7.3 and 7.4.
Additionally, Figures 7.3 and 7.4 show that pesticide usage is variable from year to year
due to several factors including weather, pest pressure, product availability, price, and regulatory
concerns. Other limitations of these data will be discussed later in this chapter as well as steps
necessary to better quantify usage within this region.
Table 7.1 provides aggregated totals and Tables 7.2-7.5 provide a summary of the major
pesticides usage for the aforementioned crops. Usage on Tables 7.2-7.5 is shown for each crop,
by chemical and state. Pesticides that showed relatively minor usage are listed at the bottom hi
the "Notes" section. It is important to note that all of these tables present the data as total pounds
AI on multiple acres treated. Multiple acre treatments occur when a given pesticide is applied
more than once to the same acre in a particular year. This allows us to present the total pounds
AI applied annually of a given pesticide.
The herbicides that were used most frequently (atrazine and metolachlor) in the Bay
watershed constitute the bulk of overall pesticide usage and are applied at relatively stable rates
of application from year to year. Atrazine and metolachlor represent two families of herbicides
which account for the majority of groundwater concerns in this country. IPM approaches could
potentially reduce these risks.
7-2
-------
Pesticide Use
Corn
Table 7.2 shows that in 1996, about 6.5 million pounds AI were applied to about 5.5
million acre treatments. Atrazine is the largest contributor to this total with about 35 percent of
the total pounds AI and multiple acres treated. Atrazine (35 percent), metolachlor (26 percent),
pendimethalin (8 percent), and alachlor (7 percent) represent more than 75 percent of the total
pounds AI applied. Herbicides account for nearly 95 percent of the total pounds AI applied to
com.
Alfalfa
Based on historical estimates, pesticide usage was relative low for alfalfa in 1996.
Previous year estimates show that it would not be uncommon for usage to exceed 1996 estimates
fourfold. Table 7.3 shows that approximately 112,000 acre treatments were treated with 70,000
pounds AI in 1996. Dimethoate (33 percent) and chlorpyrifos (14 percent) represent the largest
pesticides used in terms of pounds AI. Dimethoate (32 percent), carbofuran (13 percent), and
chlorpyrifos (12 percent) represent the largest usage in terms of multiple acre treatments. All of
these chemicals are considered insecticides and accounted for two thirds of all pesticides applied
to alfalfa.
Soybeans
Pesticide usage was relatively low for soybeans in 1996 compared to other years.
However, it was still hi the range of other years which was not the case for alfalfa. Table 7.4
shows that approximately 1.4 million pounds AI were applied to more than 1.7 million acre
treatments. Metolachlor (42 percent), alachlor (14 percent), and glyphosate (13 percent)
accounted for nearly 70 percent of the total pounds AI applied. Aldicarb, which accounted for
less than 1 percent of total usage, was the sole insecticide that made the list.
Small Grains
Table 7.5 presents usage on small grains (wheat, oats/rye, and barley) and shows that
more than one million acre treatments received a pesticide application in 1996. 2,4-D accounted
for 31 percent of the 183,000 pounds AI applied to these sites. In addition to 2,4-D, glyphosate
(17 percent) and disulfoton (15 percent) represented more than 60 percent of pesticides applied.
Small grains received the lowest typical rates of any of the crops with an average rate of less than
0.2 pounds Al/acre/year for all of the pesticides combined. Small grains were the only crops in
which a fungicide (mancozeb, propiconazole, and tridimefon) made the list of major chemicals
used.
Com accounted for 79 percent of the total pounds AI applied to the four crops within the
7-3
-------
Pesticide Use
Bay watershed in 1996. Soybeans accounted for 18 percent of total pesticide usage, small grains
accounted for 2 percent, and alfalfa received less than one percent of all pesticides applied.
1,985,000 acres of corn (42 percent), 1,140,000 acres of soybeans (23 percent), 990,000 acres of
small grains (20 percent), and 740,000 acres of alfalfa (15 percent) were planted in the Bay
watershed in 1996. Atrazine (28 percent) and metolachlor (28 percent) accounted for over half of
all pesticides applied to these four sites.
Additionally, Pennsylvania, Maryland and Virginia accounted for 49%, 28%, and 23%,
respectively, of the total pounds AI applied and multiple acres treated. Herbicides accounted for
approximately 95 percent of the total pounds AI applied to these four crops.
DISCUSSION OF DATA GATHERING TECHNIQUES AND LIMITATIONS
It is vitally important to note that pesticide usage is variable and may or may not
represent an average year for any specific site analyzed. Several factors can influence pesticide
usage in any given year. Some of these factors include pest pressure, economics, weather,
regulatory concerns, etc. Thus, this analysis provides only a snapshot of chemical specific
pesticide usage in 1996. The trend analysis attempts to provide a more general overview of
pesticide usage.
The pesticide usage estimates are based on proprietary and non-proprietary data sources.
Some of the non-proprietary sources include U.S. Department of Agriculture's 1992 National
Agricultural Statistics Service, National Agricultural Chemical Association's 1992 Industry
Profile, 1992 pesticide usage analysis for the National Center for Food and Agricultural Policy,
state surveys, and state pesticide experts. These data were compared to those in the proprietary
data sources to derive more reliable estimates.
To establish usage estimates for the watershed, a multiplier was applied to the state usage
estimates. This multiplier was derived by dividing the crop specific acreage within the
watershed portion of the state by the total acreage of that crop within the entire state. This
allowed for the use of state pesticide usage estimates which are more reliable than county
estimates because the data is derived from a much larger sample size. Reliable data showing
crop acreage within counties that lie within the Bay watershed are available from the states'
agricultural statistics service.
Since all data sources have unique limitations, it is preferable to derive pesticide usage
estimates from as many sources as possible. Although this analysis did utilize several sources,
additional data sets would improve the quality of these data.
Due to agreements with companies that provide proprietary data, point estimates from
these sources can not be disclosed. This is another reason several sources are utilized.
7-4
-------
Pesticide Use
Proprietary sources provide more validity to those estimates that are publicly available because
these sources tend to be more statistically valid. Thus, they are an integral component of this
analysis.
PESTICIDES IN SURFACE AND GROUND WATER
As stated earlier in the introduction, the use of pesticides for agricultural and non-
agricultural purposes and the potential for these chemicals to adversely affect both surface and
ground water as well as the Bay's living resources is a concern of the Chesapeake Bay Program.
Many pesticides are soluble in water and may enter the Bay or its tributaries in a dissolved state
through storm water and ground water flows.
Ground water delivers more than half of the fresh water that enters the Bay. This water is
transported to the Bay as base flow to non-tidal tributaries or upwelled directly to the mainstem
and tidal tributaries. Although the Bay is not utilized for drinking water, excessive pesticide
exposure could have negative impacts on the overall ecosystem.
Pesticides and/or their metabolites are typically persistent in the environment. This
characteristic can result in undesirable loads to surrounding ground and surface water. Estimates
of these loads for select pesticides are reported in the fall line and atmospheric deposition chapter
of this inventory.
Additionally, this section provides a summary of ambient levels of high use pesticides
found in surface and ground water. The United States Geological Survey (USGS) recently
released two reports entitled "Pesticides in Surface Water of the Mid-Atlantic Region" and
"Nitrate and Selected Pesticides in Ground Water of the Mid-Atlantic Region." Along with the
pesticide usage data, these reports provide a comprehensive view of where these chemicals are
being detected in ground water and surface water samples.
Table 7.6 and Figure 7.1 summarize data for the high use pesticides detected in surface
water. Four pesticides (atrazine, metolachlor, simazine, and 2,4-D) were detected in over 50
percent of the sites sampled. The remaining six pesticides were only detected at 7-30 percent of
the sites sampled. Chlorpyrifos concentrations in surface water exceeded the federal acute
ambient water quality criterion once (0.14 percent of analyses) and the chronic criterion twice
(0.28 percent of analyses). There are no chronic or acute criteria for the other high use
pesticides. Atrazine was detected in over 90 percent of the sites sampled and 86 percent of
analyses. Concentrations ranged from 0.002-25 ug/1, well below the level judged to be
ecologically significant (50 ug/1; Solomon et al., 1996).
Table 7.7 and Figure 7.2 provide a summary of data related to pesticides detected in
ground water. The number of detections in ground water was significantly less than what was
7-5
-------
Pesticide Use
found in surface water. Atrazine was the only pesticide detected in greater than 50 percent of the
sites sampled. It should be noted that both Tables 7.6 and 7.7 present data for only those high
use pesticides listed in Table 7.1 and for which USGS screened for.
RECOMMENDATIONS
*• The link between pesticide usage, ambient levels in the Bay and the potential for negative
impacts to the ecosystem is unclear. This area should be the primary focus for additional
research efforts. Additionally, these efforts should not focus solely on pesticides but
include heavy metals and nutrients as well.
*• In order to ensure that ambient concentrations of the high use pesticides in the
Chesapeake Bay are below levels that cause adverse impacts on aquatic life, ambient
water quality criteria must be developed.
7-6
-------
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Pesticide Use
High Use Pfestiddes in Ground Water
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Note: These data are from USGSs Md-Aflantic Assessment (MAI A) project nitrogen and pestia'de concentrations for
937 p/ouTd water sites. Only data from 1993-1996 within the Chesapeake Bay Watershed were used for this analysis.
Figure 7.1. Surface water pesticide detection sites.
7-14
-------
Pesticide Use
High Use Pesticides in Ground Wrter
Sanpled in the Chesapeake Bay Watershed
(1993-1996)
2AO
ALACHLOR
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CYANAZINE
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Qxxnd Water Stes - Detections
Q-oind Water Stes - No Detections
Note: These data are from USGSs Md-AllanticAsssssnnent (MA1A) project nitrogen and pesfidde conoentrations for
937 groind water sites. Onlydatafrom1993-1996withintreChesapeake Bay Watershed were used for ttis analysis.
Figure 7.2. Ground water pesticide detection sites.
7-75
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Pesticide Use
S
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Figure 1.3. Multiple Acres Treated With Pesticides Within the Watershed.
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Figure 1.4. Pounds of Pesticide Active Ingredients Applied to Agricultural
Lands Within the Watershed.
7-16
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CHAPTER 8 - Relative Importance of Point and Non-Point
Sources of Chemical Contaminants to Chesapeake Bay
David Velinsky Joel Baker
Patrick Center for Environmental Research Chesapeake Biological Laboratory
The Academy of Natural Sciences University of Maryland
1900 Benjamin Franklin Parkway P. O. Box 38
Philadelphia, PA 19103-1195 Solomons, MD 20688
INTRODUCTION
This chapter compares the loadings of selected contaminants from point and nonpoint
sources to assess the relative importance of each source in contributing loads to the tidal Bay and
its major tidal rivers. This comparison of loadings from each source category will enable
managers to determine where to focus limited resources for source reductions in specific areas of
the Chesapeake Bay watershed. Specific objectives of this chapter are to: 1) combine loading
estimates from individual sources (as described in the previous chapters) to yield annual loadings
of selected contaminants to the mainstem Chesapeake Bay and tributaries; 2) compare the
magnitudes of individual loadings to assess the relative importance of each source type; 3)
examine the errors and uncertainties in the current estimated loadings; and 4) recommend further
actions to reduce the uncertainty in loadings to the Bay. Sources such as atmospheric deposition,
urban runoff, point sources, and fall line inputs to the tidal Bay are examined and augmented
with shoreline erosion rates, where possible. Loads for selected contaminants are presented for
the mainstem tidal area as well as major sub-tributaries of Chesapeake Bay such as the Potomac,
James, and Patuxent rivers. In addition, estimates are made for the Anacostia watershed which
was designated by the Chesapeake Executive Council as one of three Regions of Concern. The
Anacostia had the most complete data set of the three areas.
METHODOLOGY
Specific chemicals that were investigated for this comparative analysis include selected
trace elements arsenic (As), cadmium (Cd), copper (Cu), lead (Pb), mercury (Hg), and zinc (Zn).
Loading information was also compiled for organic contaminants including total polychlorinated
biphenyls (PCBs) and specific polycyclic aromatic hydrocarbons (PAHs) such as chrysene,
phenanthrene, pyrene, and benzo(a)pyrene. These chemicals were chosen due to their inclusion
in the Chesapeake Bay Toxics of Concern List (CBP, 1998) and availability of data for the
various sources.
The data for this analysis and the limitations of each data set are presented in previous
chapters of this report. In general, the sources chosen for these estimates include point sources
8-1
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Comparative Loadings in the Bay
(municipal, industrial, and federal), non-point sources (shoreline erosion and urban runoff),
riverine runoff from upstream sources (loads from the non-tidal portion of the watershed entering
tidal waters at the fall line), and atmospheric deposition (Figure 8.1). For this comparative
loadings analysis, loadings to the tidal portion of the Chesapeake Bay rivers are fall line
loadings, representing the total loadings from upstream sources, and below fall line loadings
from point sources, atmospheric deposition, urban runoff and shoreline erosion. The fall line is
the zone between tidal and non-tidal waters of each tributary. For this report, fall line inputs are
the integrated sum of the various sources within the watershed. They include point source and
non-point sources upstream of the fall line. Below are brief descriptions of the methods used for
each source category for this chapter.
Point Source
Loadings from the Point Source chapter (Chapter 1) for the chemicals indicated above
were used for this analysis, and unless otherwise noted, the high and low estimates were
averaged. For the trace metals, dissolved, total recoverable, or total loads are reported in Chapter
1. This was due to the reporting method and type of chemical analysis by each facility. In this
chapter, the highest load from these three categories was used for comparison. Lastly, loads for
total PCBs were estimated from Arochlor 1260 only. All loads are reported in pounds per year
(Ib/yr).
Urban Stormwater Runoff
Data were obtained from Chapter 2 of this document. In brief, runoff volumes were
calculated from relationships between rainfall, land use, and impervious area. Chemical loads
were determined from the runoff volume and literature-derived event-mean concentrations of
specific chemical contaminants. All loads are reported in pounds per year (Ib/yr).
Shoreline Erosion
To provide a rough estimate of loads of chemical eroding from shoreline sediments, data
presented in Helz et al. (1985) and Bryne and Anderson (1973) were used. From these studies,
the average mass erosion rates (kg sediment/yr) were obtained directly or calculated from volume
erosion rates (m3 sediment /yr) and estimates of bulk sediment density. Metal fluxes were
calculated using the average concentrations for shoreline material derived from Helz et al. (1985)
and are reported as Ib/yr. Errors inherent in these calculations include the use of average rates
and concentrations throughout the Bay given the geochemical variability of shoreline material.
In addition, shoreline material is generally more coarse and would only be transported during
storm events. However, these estimates do provide an order of magnitude estimate from
shoreline sources. All loads are reported in pounds per year (Ib/yr).
8-2
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Comparative Loadings in the Bay
Atmospheric Deposition
Atmospheric deposition samples were collected from three stations located around the
edge of the Bay starting in late 1990 or early 1991 to 1993 from the Chesapeake Bay
Atmospheric Deposition Program. Wet deposition samples were collected weekly or bi-weekly,
while dry deposition was estimated from measured aerosol concentrations and particle deposition
rates (See Chapter 3 for details). Estimates are to the tidal waters of the Bay and tributaries only.
The loading rates in Chapter 3 were modified to include an urban source effect using data
from Baltimore Harbor and the amount of urban area in the Bay region. Additionally, loads are
direct to the surface waters (i.e., gross absorptive fluxes) and are not corrected for gas or aerosol
exchange back into the overlying air mass unless noted. This is especially important for organic
contaminants such as PCBs and aromatic hydrocarbons, and for mercury for which gas exchange
from the water to the atmosphere can be substantial. All loads are reported in pounds per year
(Ib/yr).
Fall Line (i.e., Upstream Sources)
Fall line inputs are those directly delivered to the tidal waters of the specific tributary and
Bay. The fall line, for this report, is the boundary between tidal and non-tidal waters. Fall line
estimates provide a measure of the amount of material discharged or released from all sources in
a watershed above the fall line and delivered to the upper reaches of the Bay's tidal tributaries
(i.e., James River) or the upper mainstem Bay (i.e., Susquehanna River). Estimates are derived
from the data presented in Chapter 6 for the mainstem Bay and various tributaries and from
Gruessner et al. (1997) for the Anacostia River. All loads are reported in pounds per year (Ib/yr).
Chemicals in fall line transport are derived from many upstream sources, both natural and
anthropogenic. As such, above fall line (AFL) inputs include point sources, urban runoff, stream
bank erosion, agricultural sources, acid mine drainage, and atmospheric deposition, among
others. It is not possible at this time to subdivide the total fall line loads by specific contributing
sources. While most sources discharge or are calculated to discharge to the free-flowing river,
atmospheric inputs are deposited to all surface areas (land and water) within the watershed and
need to be transported to the river. There are many attenuating processes that can sequester a
portion of the atmospherically-derived metals or organic compounds before they reach the
adjacent creek, stream or river, and many of these processes are chemical specific due to
different geochemical reactions. Also, once a chemical is introduced into the free-flowing river,
similar geochemical processes can act on the contaminant and can alter the amount of material
eventually transported over the fall line into tidal waters. Therefore, it is difficult to allocate the
above fall line sources noted in the previous chapters into what is actually measured at the fall
line.
8-3
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Comparative Loadings in the Bay
Other Sources
This updated inventory, although more complete than the 1994 inventory, is not a
comprehensive accounting of all loads of all chemical contaminants to the Bay and its tidal
rivers. The load for only a subset of all chemical contaminants entering the Bay were measured
or estimated, and some sources of chemical contaminants loads are not quantified or separated
from the total load. For example, the load to the Bay that is measured at the fall line is the sum
of all sources in the non-tidal watershed including atmospheric deposition to the watershed,
natural weathering of rock and soils, agricultural sources from chemical applications, point
sources, and stormwater runoff. However, due to the lack of adequate data, it is not possible to
allocate the total load into its components. Other sources of loads that have not been fully
accounted for or separated from the various loads are the following:
• Point source loads from over 3,700 minor facilities that discharge with a flow of less than
0.5 million gallons per day,
• The fraction of the atmospheric deposition load that is carried off the watershed (i.e., the
land) into the Bay by stream or river runoff,
• The fraction of the agricultural load that is carried off agricultural land by atmospheric
deposition and subsequent stream runoff,
• Groundwater loads both direct to the tidal Bay and the fraction of the fall line load to the
tidal waters and,
• Natural background loads of chemicals (i.e., trace metals) entering the Bay from natural
process such as mechanical or chemical weathering of rock.
Some of these loads are captured through fall line load estimates and possibly urban
runoff estimates, while others (e.g., direct agricultural loads) were not estimated due to a lack of
accurate data. Therefore, in the figures in this chapter, another category has been added called
"other sources" to remind the reader that this is not a comprehensive inventory and there are
some sources that are not completely accounted for or separated from other source categories.
Uncertainty Analysis of Loads
The determination and quantification of the important input fluxes to Chesapeake Bay are
complex tasks. Many problems are inherent in these types of calculations including: 1) a general
lack of quality data; 2) incomparability of chemical measurements and forms from each source
category; and 3) incomplete reporting of the various sources as discussed in the previous loading
chapters. There is some level of uncertainty in all loads estimates that are due to a number of
factors (i.e., both systematic and random) ranging from uncertainty in measurements, spatial
extrapolation, temporal variation in rainfall or streamflow, and the method used to estimate
loads. While it would be best to have a consistent method to estimate the uncertainty in each
source category, this may not be possible given the available data. In many cases the level of
8-4
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Comparative Loadings in the Bay
uncertainty can be fairly accurately calculated while in some cases the level of uncertainty can
only be estimated. The major cause of error and temporal variation was provided in each chapter
and was incorporated into the comparative loadings analysis. Below is a summary of the
uncertainty analysis that was provided within each source category:
Atmospheric loads
Baker (Chapter 3) estimated that sources of random error in wet deposition loading
estimates include the measurement errors associated with quantifying chemical concentrations in
precipitation and the rainfall amount. For atmospheric wet deposition, the propagated
uncertainties to the metals and organics fluxes were estimated at ±10% and ±20%, respectively.
It was estimated that dry aerosol deposition loadings are likely precise to within a factor of 2-3.
In addition, the overall random error of a typical instantaneous gas exchange flux was calculated
as ± 40%. Lastly, a potentially larger source of uncertainty in deposition loadings results from
the spatial extrapolation from the few regional and single urban deposition sites to the Bay.
Point Source loads
A formal uncertainty analysis for point source loads has not been calculated due to the
nature of the data set (Chapter 1). While there are random errors in the calculation of the load,
systematic errors in reporting may also be large. Current methods for estimating organic loads
from point sources are highly uncertain and of limited use, particularly for the organic
contaminants. Reporting programs in which data were collected were not set up with the
objective of calculating loads, but rather for determining compliance with regulated parameters
in discharge permits. For certain chemicals — all PCBs, pesticides, and most PAHs — most or all
values were reported at below the detection limits. In addition the detection limit used or
provided may be unduly high relative to the regulatory-based method used for analysis.
Therefore loading estimates for these contaminants may be as low as zero or as high as the
detection limit multiplied by the flow. However, this uncertainty is not the case for most of the
trace metal data since many measurements were above the detection limit. The range of
estimates based upon the detection limit and flow were used to estimate the likely bounds for the
loads and can be very large dependent on the number of samples that are below the detection
limit.
As eluded to above, one of the largest uncertainties in this inventory is the point source
load estimate for organic contaminants. In most cases no organic contaminants were detected
and the detection limit was high. For measurements of organic contaminants and some trace
metals that are below the detection limit, using typical pollutant concentrations (TPC) from the
literature (instead of the detection limit) may be a better approach for estimating loads from point
sources. Below is an illustration of the use of a typical pollutant concentration (TPC) to help
constrain the load estimates, using PCBs as an example. For this example, a TPC is used as a
default for point sources that do not have accurate measurements and where detection limits are
high. TPCs are simply "typical" concentrations of a chemical for similar industrial activities or
8-5
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Comparative Loadings in the Bay
processes. The TPC provides a planning level estimate that helps understand the possible
relative importance of point sources, and this illustration will help to interpret the point source
organics data presented in this chapter.
Total average PCB loads (i.e., Arochlor 1260) were estimated for the tidal Potomac River
to illustrate the uncertainty of the point source estimates. Atmospheric deposition loads are the
sums of wet and dry deposition, while removal from the surface water via volatilization was not
considered. Fall line loads from the non-tidal watershed were measured over multiple years as
part of the Chesapeake Bay Program Fall Line monitoring program (see Chapter 6). As can be
seen from Figure 8.2, point source load estimates for PCBs are highly uncertain relative to the
other sources. In this regard, virtually all measurements of PCBs are below the detection limit.
Therefore concentrations could range between zero and the detection limit (e.g., high u.g/L),
resulting in loads ranging from 0-210,000 Ib/yr.
To get an idea of what the actual PCB loads are within this large range, one method
would be to assume a typical concentration for total PCBs in point source effluent (based on
values in the literature) for those facilities where PCBs would be expected to be present. Loads
would be calculated by multiplying the concentration by the point source flows in the tidal
portion of the watershed. Recent studies by Durell and Lizotte (1998) and DRBC (1998) showed
wastewater treatment plants (WWTP) effluent concentrations of total PCBs much lower
compared to the detection limits used for Chesapeake Bay point sources. In 26 WWTP effluents
in the NY/NJ Harbor Estuary (Durell and Lizotte, 1998), total PCBs ranged from 0.010 to 0.055
u.g/L (sum of 71 target congeners) with an overall average of 0.025 ng/L. Concentrations of total
PCBs from 7 WWTP in the tidal freshwater Delaware River (DRBC, 1998), ranged from
approximately 0.0014 to 0.045 u.g/L with an overall average of 0.013 ng/L.
Assuming a low and high concentration of 0.0014 ^ig/L and 0.05 ng/L, respectively,
approximately 170 Ib/yr of PCBs, on average, are entering the tidal Potomac waters from point
sources (Figure 8.3). This estimate is three orders of magnitude lower than the estimate made
using the given detection limit to calculate loads (200,000 Ib/yr). Using literature derived typical
pollutant concentrations, the estimated point source loads of PCBs to the tidal Potomac indicate
that approximately 60% of the total load is derived from point sources and the fall line loads are
comparable to the point source loads, with a very small load originating from atmospheric
deposition. Overall, the use of a TPC for point sources in which most or all of the measured
concentrations are at the detection limit and the limit appears to be unduly high, may be
warranted so that planning level estimates can be derived.
Fall line loading estimates
Uncertainties have not been rigorously evaluated for fall line loading estimates (see
Chapter 6). The level of uncertainty is related to the variability in the measured concentration
and discharge. In addition, estimates of contaminant loadings above the river fall lines are
8-6
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Comparative Loadings in the Bay
extremely dependent on river flows, which vary widely throughout the year. While loads for the
Susquehanna, Potomac and James rivers were averaged over multiple years, loads for many
tributaries were obtained for only a single year from only two sampling events. Estimates of
contaminant loadings are dependent on river flow, which can vary substantially from year to
year. Also, due to the extreme cost and time for fall line monitoring and chemical analysis, the
contaminant concentration data used to estimate loads were sparse. The most accurate loadings
exist for the Susquehanna River for which multiple years of data have been collected. For this
analysis, four years of loadings data from the Potomac, James and Susquehanna Rivers were
used to estimate the overall level of uncertainty. The trace metals, copper, cadmium, and lead,
were used as it appears that they had the most complete data set. On average the relative standard
deviation was approximately ± 20%, and this value was applied to all fall line loadings.
Shoreline erosion loads
Variations in the shoreline erosion estimate was based on the range of estimates between
the 1994 estimate from the 1994 Reevaluation Report (CBP, 1994b) and the estimate from the
1982 Technical Synthesis Report (CBP, 1982). These were independently determined and
provide some idea as to the range of loads from shoreline sediments.
Urban runoff loads
The uncertainty in the urban runoff load estimates were not rigorously determined, but a
rough estimate of the quantifiable uncertainty was presented (see Chapter 2). Three main sources
of quantifiable error have been identified: modeling error in the average annual runoff estimates,
interannual variability in the estimates (i.e., runoff), and variability in the measured chemical
contaminant concentrations. A comparison of the basinwide urban land use data that was used in
the Chesapeake Bay Watershed Model suggested an estimate of about ± 10% error in the amount
of urban land and the percentage of impervious surface associated with those urban areas
(Mandel et al., 1997), both of which affect the average annual runoff estimates. There was some
additional uncertainty or variation associated with the average annual runoff estimates due to
interannual variability in rainfall amounts. To develop an estimate of this uncertainty, 95%
confidence intervals were calculated around the mean annual runoff estimates from 1986-1993.
The magnitudes of the confidence intervals in either direction, expressed as the percent of the
mean, ranged from 9 to 26% and the average was 16%. Combining the ±10% estimate of
modeling error due to land use with the ±16% error from the interannual runoff variability, the
uncertainty in the calculated runoff values is likely to be about ±25%. A similar approach was
taken to determine order of magnitude estimates in the uncertainty of the EMC values.
Gruessner et al. estimated a conservative error of ±54% as an estimate of the uncertainty in the
EMC values and since the load estimates are calculated from the product of the runoff and EMC
values, the combined quantifiable uncertainties suggest that the average annual loads are
approximately ± 60%. This level of uncertainty was applied to all urban runoff estimates.
8-7
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Comparative Loadings in the Bay
INPUTS TO THE TIDAL CHESAPEAKE BAY
The loads of selected chemical contaminants to the tidal Chesapeake Bay were calculated
by taking the sum of all estimates of loadings entering the tidal rivers of the Bay for atmospheric
deposition, fall line loads, urban runoff, shoreline erosion, and point sources that are described in
previous chapters of this inventory.
Trace Elements
Summary: The highest estimated metals load comes from upstream sources (fall line) to
the tidal waters of the Bay.
Point source loads are important for copper and mercury.
Loads from shoreline erosion and urban runoff account for up to 13% of the
total metals loads to the tidal Bay.
In Figures 8.4-8.9, the various inputs of cadmium, copper, lead, mercury, zinc, and
arsenic are summarized along with the total load (in Ib/yr) to the tidal waters of Chesapeake Bay.
The trace metals copper and zinc had the greatest average total load to the tidal Bay of 710,000
Ib/yr and 3,300,000 Ib/yr, respectively, while mercury had the least, 9,500 Ib/yr.
Fall Line
All metal loads are dominated by upstream inputs (fall line loads). These loads are likely
underestimated because not all Bay tributaries were sampled and quantified; however, this
would be a small load since the total flow is dominated by the tributaries that were monitored.
Point Sources
Point source inputs are important for mercury and copper. The level of uncertainty in the
copper loads estimates is very low because the majority of measurements were above the
detection limit. However, there was more uncertainty in the mercury loads estimates because
many of the values were below detection limit (see previous discussion of uncertainty for point
sources)
Shoreline Erosion
Erosion of shoreline material accounts for less than approximately 13% of the total load,
with the greatest loads to the tidal Bay for zinc and lead.
Urban Runoff
Urban runoff accounts for between 6 and 13% of the total load for these trace elements,
the greatest being for lead and zinc.
8-8
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Comparative Loadings in the Bay
Atmospheric Deposition
Atmospheric inputs of metals directly to tidal waters are a small percentage of the total
load and range from approximately 3% for copper and cadmium to 7% for lead. Atmospheric
inputs of lead are approximately twice as high as point source inputs. The importance of this is
not just that the load is higher but also that it is spread out over the entire tidal water area, while
point source inputs are usually in small bays or tributaries.
Organic Contaminants
Summary: Urban stormwater runoff is a substantial source ofPAHs to the tidal
Chesapeake Bay.
Point sources of organic contaminants (PAHs, andPCBs) are highly uncertain
and therefore loads are largely unknown.
Total PCBs loads are approximately equally divided between atmospheric and
fall line loads to the tidal waters of the Bay.
Estimates for organic contaminant loads to the mainstem tidal Bay are presented in
Figures 8.10-8.13 for four polycyclic aromatic hydrocarbons (PAHs, benzo[a]pyrene, chrysene,
phenanthrene, and pyrene) and total PCBs (no figure provided). No data for PAH loads from
shoreline erosion were available.
For specific aromatic hydrocarbons, average loads range from 130,000 Ib/yr for
phenanthrene to 64,000 Ib/yr for benzo[a]pyrene and chrysene (Figures 8.10-8.13). Total PCB
loads to the tidal waters of the Bay, without point source estimates are nearly equally divided
between fall line inputs (650 Ib/yr) and atmospheric deposition (wet and dry) to the tidal waters
(540 Ib/yr).
Point Sources
Point source loads estimates of PAHs are highly uncertain as indicated by the large
uncertainty bars in Figures 8.10-8.13. Virtually all of the measurements of PAHs were below the
detection limit. Therefore the loads could range anywhere between zero to the product of the
detection limit and flow. Therefore, the point source loads of PAHs are unknown and the data
presented in the figures are of limited use.
Urban Runoff
Given that point source loads estimates are highly uncertain, the urban stormwater runoff
is the most substantial known source of PAH loads to the tidal Bay. Urban runoff accounts for
approximately 12% of the total input of PAHs to the tidal Bay. Since the point source loads
estimates are so uncertain, the relative contribution of urban runoff is probably much greater than
8-9
-------
Comparative Loadings in the Bay
initially estimated. Urban stormwater runoff would include power plant combustion, automobile
emissions, both gas/oil combustion and oil drippings, and tire wear.
Fall Line/Atmospheric Deposition
Inputs from the non-tidal watershed (as measured at the fall line) account for less than 3%
of the total load while total atmospheric deposition (i.e., wet, dry, and gas exchange into the
water) ranges from < 0.5% for benzo[a]pyrene (77 Ib/yr) to 5% for phenanthrene (6,400 Ib/yr).
INPUTS TO TRIBUTARIES OF CHESAPEAKE BAY
A comparison of the point and nonpoint source loads was conducted for some of the
major tributaries of the Bay: the James, Potomac and Patuxent rivers below the fall line. The
organic contaminant data used to make these comparisons for many of the tributaries have a large
amount of uncertainty (i.e., point source data), therefore only trace elements (copper, cadmium,
and lead) and a subset of the organic data (i.e., PAHs only) will be discussed below for all areas.
Total PCB loadings data are not presented due to the uncertainties in the point source data. An
illustration of this uncertainty was presented above. In addition, loadings estimates were
compiled for one of the three Regions of Concern with the most complete loadings data set
(Anacostia River) and compared to the three larger rivers.
Inputs of Chemical Contaminants to the James, Potomac, and Patuxent Rivers
Summary: Sources of metals to the major tidal rivers are variable.
Urban runoff is the dominant source of metals loads to the Patuxent River.
Upstream sources of metals loads are dominant in the Potomac and James
Rivers.
Urban runoff is a substantial source of PAHs to the tidal James, Patuxent, and
Potomac Rivers.
Point sources of organic contaminants (PAHs, andPCBs) are highly uncertain
and therefore loads to the James, Patuxent, and Potomac Rivers are largely
unknown.
8-10
-------
Comparative Loadings in the Bay
James River
Metals
Trace element loads to the tidal James River range from 9,400 Ib/yr for cadmium to
110,000 Ib/yr for copper (Figures 8.14-8.16). Fall line loads are the dominant source of metals to
the tidal James River. Point sources loads for copper and cadmium account for 11,000 Ib/yr
(11% of the total load) and 1,600 Ib/yr (17% of the total load), respectively. Urban runoff
sources for all metals account for approximately 11 to 16% of the total load to the tidal river.
Polycyclic Aromatic Hydrocarbons (PAHs^
For the PAHs, benzo[a]pyrene and phenanthrene, urban runoff and to a lesser degree,
either atmospheric deposition or fall line inputs, are major sources of PAHs to the river (Figures
8.17-8.18). Point source loads estimates of PAHs are highly uncertain as indicated by the large
uncertainty bars in the figures. Virtually all of the measurements of PAHs were below the
detection limit. Therefore the point source loads could range anywhere between zero to the
product of the detection limit and flow. Therefore, the point source loads of PAHs are unknown
and the data presented in the figures are of limited use. Urban runoff accounts for approximately
4 to 6% of the total input of PAHs to the tidal Bay. Given that point source loads estimates are
highly uncertain, the relative contribution of urban runoff is substantially greater than initially
estimated.
Potomac River
Metals
Loads of trace metals to the tidal Potomac River range from 2,300 Ib/yr for cadmium to
approximately 160,000 Ib/yr for lead (Figures 8.19-8.21). Fall line loads are the dominant source
to the tidal river, comprising greater than 75% of the total load. Average point source loads for
copper, 17,000 Ib/yr, account for 11 % of the total load with lesser amounts for cadmium and
lead. Urban runoff from the tidal watershed to the river accounts for between 7% for cadmium
and 14% of the total load for lead. Atmospheric inputs, direct to the tidal water, are small and
generally less than 3% for all metals with the largest load of 3,400 Ib/yr for lead (2% of the total
load).
Polvcvclic Aromatic Hydrocarbons (PAHS')
As with the James River, the PAH (benzo[a]pyrene and phenanthrene) loads are
dominated by point sources although the data is very uncertain (Figures 8.22-8.23). Urban
runoff and to a lesser degree, either atmospheric deposition or fall line inputs, are major sources
8-11
-------
Comparative Loadings in the Bay
of PAHs to the river.
Patuxent River
Metals
In contrast to the James and Potomac rivers, loads to the tidal Patuxent River for all
metals are dominated by urban runoff. Inputs of metals ranged from 390 Ib/yr for cadmium to
4,200 Ib/yr for copper (Figure 8.24-8.26). Urban runoff accounts for between 44 to 51% of the
total tidal input for copper and cadmium, respectively to 66% for lead. Inputs from the non-tidal
portion of the watershed (i.e., fall line) are substantial for copper (37% of the total) and smaller 9
to 23% of the total load for cadmium and lead, respectively (Figures 8.24-8.26). Deposition to
the tidal waters of the river accounts for between 10% for Cu and Zn to approximately 20% for
lead. Point source inputs account for a small percentage of the total load (5 to 10% of the total
load for all metals).
Polycyclic Aromatic Hydrocarbons (PAHs)
For the PAHs, benzo[a]pyrene and phenanthrene, the loads are dominated by urban
runoff with average loads of 320 and 720 Ibs/yr respectively, although there is a large degree of
uncertainty as indicated by the range of the estimates (Figure 8.27-8.28). Total and atmospheric
deposition and point source loads are a small but important component of the total load to the
Patuxent River. Atmospheric deposition loads range from < 1 to 22% of the total load for
benzo[a]pyrene and phenanthrene, respectively, and from 4 to 8% of the total load for point
source loads of benzo[a]pyrene and phenanthrene.
Inputs of Trace Elements to the Anacostia River
Summary: Upstream sources of metals are dominant in the Anacostia River, with the
second highest load coming from urban runoff and combined sewer overflows.
The load of contaminants to the Anacostia River, a Region of Concern, was complied
from various sources including the data from the previous chapters, MW COG (1997), Velinsky
et al. (1996) and Gruessner et al., (1997). These documents describe loadings to the Anacostia
River and are part of the Regional Action Plan assessment. It should be noted that upstream
sources (i.e., fall line loads) were measured directly over a 1-yr period while the other source
categories were estimated from various land use/hydrologic models. Due to the limited data set,
as compared to the other, larger tributaries, uncertainties in the loads were not estimated for the
Anacostia.
Loads to the tidal Anacostia River were estimated for cadmium, copper, lead, zinc
8-12
-------
Comparative Loadings in the Bay
(Figures 8.29-8.32). Since there were insufficient data for other contaminants from all sources,
only trace metal loads are presented. Total loads to the tidal waters range from 340 Ib/yr for
copper to more than 23,000 Ib/yr for zinc. Upstream sources dominate the input of these metals,
with more than 77% of the total input derived from the non-tidal watershed. Urban runoff or
combined sewer overflows (CSO) inputs to the tidal Anacostia River can also be a major source
of trace elements. For zinc and lead, combined sewer loads account for between 18% and 23%
of the total load to the tidal waters. Urban stormwater runoff loads are variable for these metals
(Figures 8.29-8.32). While previous calculations by Velinsky et al. (1996) suggest that urban
runoff was a major source of aromatic hydrocarbons to the tidal river, the recent data by
Gruessner et al. (1997) indicates that upstream sources could be more substantial. Uncertainties,
or ranges, were not reported for Anacostia River loads due to a lack of data from the different
data sources. For example, reports for point source and urban runoff loads did not include ranges
and therefore they could not be calculated hi this inventory.
Watershed Yields
Summary: The Anacostia River watershed, a highly urbanized area, produces 3 and 12
times more copper and lead, respectively, per watershed area than any of the
major rivers in the Bay watershed.
Landuse characteristics in a watershed influences the chemical loadings from a
watershed.
Loadings are not proportional to the size of the watershed.
The total watershed yield for specific trace metals was calculated by dividing the total
load (Ib/yr) for a watershed by its total drainage area (above and below the fall line) for four trace
metals (units: Ib/km2-yr; Table 8.1). This calculation can be used to evaluate if specific
watershed characteristics are more important in determining the overall load to the tidal Bay.
Land use (i.e., amount of urban area) and point sources could be two important characteristic
affecting the yield of a chemical from a watershed area.
Table 8.1. Trace metal total watershed yields for selected tributaries of the Bay.
Cu
Cd
Pb
Hg
Susquehanna
4.05
0.61
2.44
0.052
Potomac
3.90
0.61
4.17
0.084
James
3.95
0.35
3.15
0.055
Patuxent
1.75
0.16
1.54
0.018
Anacostia
13.1
0.46
42.9
0.026
Units: Ib/km2-yr.
8-13
-------
Comparative Loadings in the Bay
The watershed yield information suggests that there is no trend between watershed size
and area and the load of specific trace metals. For example, the Susquehanna River watershed,
the largest in the Bay watershed, did not show the greatest areal yields indicating that watershed
area was not directly related to the loads. The copper yield for the Anacostia watershed was
higher than other watersheds by a factor ranging between 3 and 6. The Anacostia's lead yield
was approximately 12 times higher than the other watersheds. This indicates a higher
concentration of copper and lead sources in the Anacostia watershed which most likely originate
from urban runoff, illustrating the higher per unit area loads in urban environments. Landuse
characteristics are probably more important in determining the load of a contaminant to the Bay.
The higher yields for the Anacostia, may be the result of higher urban stormwater sources for
many contaminants.
Copper yields were very similar between the Susquehanna, Potomac, and James Rivers,
the three largest watersheds in the Bay, while the copper yield for the Patuxent watershed was
slightly lower (Table 8.1). Cadmium yields for most watersheds were in good agreement except
for the Patuxent watershed in which the total cadmium yield was lower by a factor of 4.
Similarly, lead yields for the Susquehanna, Potomac and James watersheds agreed, while the
yield for the Patuxent watershed was slightly lower. Mercury yields were similar for the
Susquehanna and Potomac watersheds, while slightly lower for the both the Patuxent and
Anacostia watersheds. The good agreement for watershed yields for many metals between
watersheds suggests a fairly accurate accounting of sources and loads, however, systematic error
in data gathering can not be discounted at this time.
DISCUSSION AND RECOMMENDATIONS
Sources of contaminants to the tidal Bay and specific tributaries varied substantially. Fall
line loadings are a substantial source of metals to the tidal Bay and individual rivers such as the
Potomac, James, and Anacostia rivers. Point sources are substantial sources for select metals in
the tidal Bay. Urban runoff is a substantial source of organic contaminants to the tidal Bay and
many of its rivers and a substantial source of metals to the Patuxent river. Point source loads of
organic contaminants are largely unknown due to limitations of the data. In the Anacostia, a
highly urbanized Region of Concern, watershed yields of metals were much higher than in the
Susquehanna, Potomac, James, and Patuxent rivers.
To better define the load from point sources specific monitoring efforts are needed
throughout the Bay area and specific targeted areas, such as the Regions of Concern. This is due
to the fact that point sources may be under or overestimated (i.e., detection limits, lack of data).
While it would be prohibitively expensive to accurately determine the concentration of specific
metals and organic contaminants in every outfall of the Bay, representative discharges could be
sampled to provide a Baywide database of typical pollutant concentrations (i.e., TPCs) for
8-14
-------
Comparative Loadings in the Bay
specific industrial/municipal facilities. This database could then be used to help augment the
statewide monitoring efforts and provide a better information to make loadings summaries.
Additionally, more accurate chemical analysis and reporting within the National Pollutant
Discharge Elimination System (NPDES) and Permit Compliance System (PCS) programs need
to be initiated. Information within the NPDES database is difficult to obtain, not accurately
reported (i.e., missing units, decimal points, etc.), and are not accurately analyzed (i.e., laboratory
analysis). Historically, the NPDES data was used mainly to determine water quality violations at
a facility, not loads. However, with the advent of TMDLs, the NPDES data is now being used to
determine loads to specific waterbodies. Unless the laboratory analysis of the NPDES programs
and reporting aspects of the PCS improved, loads obtained from this data will be questionable.
Overall, better basic monitoring information is needed for almost all sources identified in
this inventory and in each chapter specific recommendations are provided to better quantify each
source. To improve upon the loading analysis for future loadings studies, additional information
is needed. The purpose of many of these recommendations is to help provide site specific data
that can be applied to other areas of the tidal and non-tidal Bay. As such, studies should focus on
representative areas in which the data can be applied to other areas. Recommendations include:
* For all sources determine a consistent chemical fraction (e.g., total, total recoverable,
dissolved).
> Explore alternate methods such as the typical pollutant concentration method for
subsequent updates to the point source inventory for organic contaminants.
> Use lower detection limit methods for dissolved, particulate or total analyses for point
sources and other sources as needed.
* Improved analysis for organic contaminants for many source functions.
+ Include urban agricultural stations in the atmospheric deposition network as well as
stations within specific watersheds.
»• Conduct comprehensive sampling of representative major point source dischargers for
specific contaminants using clean methods.
> Conduct site specific studies (i.e., sampling, analysis, and modeling) to better estimate the
urban flux of chemical contaminants.
* Characterize and determine the source of chemical contaminants within the measured fall
line loads (i.e., source allocation, watershed retention).
8-15
-------
Comparative Loadings in the Bay
Develop confidence levels and measures of uncertainty for each source category and
incorporate into the final loadings analysis.
8-16
-------
C5
PQ
CS
03
5/J
I
1
t/2
ffl
-------
Comparative Loadings in the Bay
60000
40000
CO 20000
U
0
PCBs
Total Input: 27,000 Ib/yr
AD FL UR SE PS Other
Sources
Figure 8.2. Total loads of PCBs to the tidal Potomac River from atmospheric deposition (AD);
fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS). Examples of
"Other Sources" not fully quantified may include loads from smaller point sources, agricultural
runoff, atmospheric deposition, groundwater, and natural sources. The variability in the
atmospheric deposition and fall line estimates is smaller than the symbol representing the
average.
160
140
120
s~\
^ 100
.e
? 80
5 60
40
20
0 -t
TPC Estimate
Total Input: 170 Ib/yr
I
AD FL UR SE PS Other
Sources
Figure 8.3. Total estimated loads of PCBs to the tidal Potomac River based on typical pollutant
concentrations (TPC) from the literature from atmospheric deposition (AD); fall line (FL); urban
runoff (UR); shoreline erosions (SE); and point sources (PS). Examples of "Other Sources" not
fully quantified may include loads from smaller point sources, agricultural runoff, atmospheric
deposition, groundwater, and natural sources.
8-18
-------
Comparative Loadings in the Bay
g
s
a
13
S
U
100
S 75 H
SO/
20/i
10
Cadmium
Total Input: 94,000 Ib/yr
/
I
AD FL
UR
SE
PS Other
Sources
Figure 8.4. Total loads of cadmium to the tidal waters of the Chesapeake Bay from atmospheric
deposition (AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources
(PS). Examples of "Other Sources" not fully quantified may include loads from smaller point
sources, agricultural runoff, atmospheric deposition, groundwater, and natural sources.
600
500
400
300
£ 100
o
o
X
s-
Copper
Total Input: 710,000 Ib/yr
Q,
§• 50
U
I
AD FL UR SE PS Other
Sources
Figure 8.5. Total loads of copper to the tidal water of the Chesapeake Bay from atmospheric
deposition (AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources
(PS). Examples of "Other Sources" not fully quantified may include loads from smaller point
sources, agricultural runoff, atmospheric deposition, groundwater, and natural sources. The
variability in the shoreline erosions estimate is smaller than the symbol representing the average.
8-19
-------
Comparative Loadings in the Bay
o
0
o
^H
X
i.
£
•B'
41
3UU 1
400
300
200
100
n
-p Lead
Total Input: 560,000 Ib/yr
4 *
5 I * M ?
AD FL UR SE PS Other
Sources
Figure 8.6. Total loads of lead to the tidal water of the Chesapeake Bay from atmospheric
deposition (AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources
(PS). Examples of "Other Sources" not fully quantified may include loads from smaller point
sources, agricultural runoff, atmospheric deposition, groundwater, and natural sources. The
variability in the shoreline erosions estimate is smaller than the symbol representing the average.
8
6
4
I *
I"
1
-------
Comparative Loadings in the Bay
3000
^ 2500
o
o
5 2000
X
>> 1500
w 1000
fl
•P*
SI
500
0
Zinc
Total Input: 3,300,000 Ib/yr
I
AD FL UR SE
PS Other
Sources
Figure 8.8. Total loads of zinc to the tidal water of the Chesapeake Bay from atmospheric
deposition (AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources
(PS). Examples of "Other Sources" not fully quantified may include loads from smaller point
sources, agricultural runoff, atmospheric deposition, groundwater, and natural sources. The
variability in the point source estimate is smaller than the symbol representing the average.
o
o
o
X
o
4>
160
120
80 V
1&A
10
Arsenic
Total Input: 140,000 Ib/yr
I
AD FL UR SE
PS Other
Sources
Figure 8.9. Total loads of arsenic to the tidal water of the Chesapeake Bay from atmospheric
deposition (AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources
(PS). Examples of "Other Sources" not fully quantified may include loads from smaller point
sources, agricultural runoff, atmospheric deposition, groundwater, and natural sources.
8-21
-------
Comparative Loadings in the Bay
o
o
o
150
X 100
? so/
g 20 x
^ 1S
3 10
N _ j
a 5 -
Benzo[a]pyrene
Total Input: 64,000 Ib/yr
AD FL UR SE
PS Other
Sources
Figure 8.10. Total loads of benzo[a]pyrene to the tidal water of the Chesapeake Bay from
atmospheric deposition (AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point
sources (PS). Examples of "Other Sources" not fully quantified may include loads from smaller
point sources, agricultural runoff, atmospheric deposition, groundwater, and natural sources. The
variability in the atmospheric deposition and fall line estimates is smaller than the symbol
representing the average.
o
o
o
T-H
X
&
0
a
»5
k.
s
13U •
100
SO/
20 /
10
0
Chrysene
^^
Total Input: 64,000 Ib/yr
/
/
<
«. *
i
i
»
7
AD FL UR SE PS Other
Sources
Figure 8.11. Total loads of chrysene to the tidal water of the Chesapeake Bay from atmospheric
deposition (AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS).
Examples of "Other Sources" not fully quantified may include loads from smaller point sources,
agricultural runoff, atmospheric deposition, groundwater, and natural sources. The variability in the
atmospheric deposition and fall line estimates is smaller than the symbol representing the average.
8-22
-------
Comparative Loadings in the Bay
O
O
200
Phenanthrene
Total Input: 130,000 Ib/yr
C
v
~ 25
c
0
AD FL UR SE
PS
Other
Sources
Figure 8.12. Total loads of phenanthrene to the tidal water of the Chesapeake Bay from
atmospheric deposition (AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and
point sources (PS). Examples of "Other Sources" not fully quantified may include loads from
smaller point sources, agricultural runoff, atmospheric deposition, groundwater, and natural
sources. The variability in the fall line estimate is smaller than the symbol representing the
average.
X
V
Id
zuu -
160
120
80
20 x
10
0
Pyrene
Total Input: 88,000 Ib/yr
<
(
. . I
\
x
9
AD FL UR SE PS Other
Sources
Figure 8.13. Total loads of pyrene to the tidal water of the Chesapeake Bay from atmospheric
deposition (AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources
(PS). Examples of "Other Sources" not fully quantified may include loads from smaller point
sources, agricultural runoff, atmospheric deposition, groundwater, and natural sources.
8-23
-------
Comparative Loadings in the Bay
o
o
o
1—I
X
|
1
•s
os
U
8
6,
2 -
Cadmium
Total Input: 9,400 Ib/yr
AD FL UR
SE
PS Other
Sources
Figure 8.14. Total loads of cadmium to the tidal James River from atmospheric deposition (AD);
fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS). Examples of
"Other Sources" not fully quantified may include loads from smaller point sources, agricultural
runoff, atmospheric deposition, groundwater, and natural sources.
o
o
o
ce
•d
c
e
eu
0>
C.
D.
O
U
100
75 -
50
25
0 4
Copper
Total Input: 110,000 Ib/yr
AD FL UR SE
PS Other
Sources
Figure 8.15. Total loads of copper to the tidal James River from atmospheric deposition (AD);
fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS). Examples of
"Other Sources" not fully quantified may include loads from smaller point sources, agricultural
runoff, atmospheric deposition, groundwater, and natural sources. The variability in the point
source estimate is smaller than the symbol representing the average.
8-24
-------
Comparative Loadings in the Bay
80
o
o
o
60
40
« 20 ^
M
Lead
Total Input: 84,000 Ib/yr
AD FL UR SE PS Other
Sources
Figure 8.16. Total loads of lead to the tidal James River from atmospheric deposition (AD); fall line
(FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS). Examples of "Other
Sources" not fully quantified may include loads from smaller point sources, agricultural runoff,
atmospheric deposition, groundwater, and natural sources. The variability in the point source
estimate is smaller than the symbol representing the average.
O
O
X
in
g
-2;
3
o
N
4»
PQ
75.C
50.0
25.0 /
5.0
2-5 "
0.0
Benzo[a]pyrene
Total Input: 30,000 Ib/yr
I
J- 9
AD FL UR SE
PS Other
Sources
Figure 8.17. Total loads of benzo[a]pyrene to the tidal James River from atmospheric deposition
(AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS). Examples
of "Other Sources" not fully quantified may include loads from smaller point sources, agricultural
runoff, atmospheric deposition, groundwater, and natural sources. The variability in the atmospheric
deposition and fall line estimates is smaller than the symbol representing the average.
8-25
-------
Comparative Loadings in the Bay
/— V,
0
o
0
^^
^^
£j
^•^
B
b.
A
"£
S3
C
ja
150.0 -
100.0
50.0 /
5.0 /
2.5 -
0.0
Phenanthrene _
Total Input: 63,000 Ib/yr
/
/
i
"*• •••
<
i
i
X
/
" <)
*
/
AD FL UR SE PS Other
Sources
Figure 8.18. Total loads of phenanthrene to the tidal James River from atmospheric deposition
(AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS).
Examples of "Other Sources" not fully quantified may include loads from smaller point sources,
agricultural runoff, atmospheric deposition, groundwater, and natural sources. The variability in
the fall line estimate is smaller than the symbol representing the average.
•I
30.0
20.0
5.0 xi
2.5 ]
Cadmium
Total Input: 23,000 Ib/yr
0.0
AD FL UR
SE
PS Other
Sources
Figure 8.19. Total loads of cadmium to the tidal Potomac River from atmospheric deposition
(AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS).
Examples of "Other Sources" not fully quantified may include loads from smaller point sources,
agricultural runoff, atmospheric deposition, groundwater, and natural sources.
8-26
-------
Comparative Loadings in the Bay
o
0
o
I— 1
X
^
£
i.
a
a
0
U
JL3U 1
120
90
60 /
30 /
20
10
A
Copper
) i
Total Input: 150,000 Ib/yr
-L
' /
/ /
1 1 4s
9
•
» , ...
AD FL UR SE PS Other
Sources
Figure 8.20. Total loads of copper to the tidal Potomac River from atmospheric deposition (AD);
fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS). Examples of
"Other Sources" not fully quantified may include loads from smaller point sources, agricultural
runoff, atmospheric deposition, groundwater, and natural sources.
180
150
o"
o
S 120
^ 90
-^ 40.
Lead
Total Input: 160,000 Ib/yr
T3
A
V
20
AD FL UR SE PS Other
Sources
Figure 8.21. Total loads of lead to the tidal Potomac River from atmospheric deposition (AD);
fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS). Examples of
"Other Sources" not fully quantified may include loads from smaller point sources, agricultural
runoff, atmospheric deposition, groundwater, and natural sources.
8-27
-------
Comparative Loadings in the Bay
^^
o
o
o
X
L.
C,
-------
Comparative Loadings in the Bay
u
0.4
o
S 0.3 ]
X
§ 0.2 -I
|
o.i
0.0
Cadmium
T Total Input: 390 Ib/yr
AD FL UR
SE
PS Other
Sources
Figure 8.24. Total loads of cadmium to the tidal Patuxent River from atmospheric deposition
(AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS).
Examples of "Other Sources" not fully quantified may include loads from smaller point sources,
agricultural runoff, atmospheric deposition, groundwater, and natural sources.
o
o
o
TH
*
^>
09
•e
c
9
O
a.
a
o
2 -
Copper
Total Input: 4,200 Ib/yr
AD FL UR SE PS Other
Sources
Figure 8.25. Total loads of copper to the tidal Patuxent River from atmospheric deposition (AD);
fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS). Examples of
"Other Sources" not fully quantified may include loads from smaller point sources, agricultural
runoff, atmospheric deposition, groundwater, and natural sources.
8-29
-------
Comparative Loadings in the Bay
^* A
o 4
o
3 -
2 -
t»
es
«
Lead
Total Input: 3,700 Ib/yr
AD FL UR SE
PS Other
Sources
Figure 8.26. Total loads of lead to the tidal Patuxent River from atmospheric deposition (AD);
fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS). Examples of
"Other Sources" not fully quantified may include loads from smaller point sources, agricultural
runoff, atmospheric deposition, groundwater, and natural sources.
i^s U..J
O
o
X 0.4
i.
S 0.3
0.2
— 0.1
N
n o.o
Benzo[a]pyrene
Total Input: 320 Ib/yr
AD FL UR SE
PS Other
Sources
Figure 8.27. Total loads of benzo[a]pyrene to the tidal Patuxent River from atmospheric
deposition (AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources
(PS). Examples of "Other Sources" not fully quantified may include loads from smaller point
sources, agricultural runoff, atmospheric deposition, groundwater, and natural sources. The
variability in the atmospheric deposition and fall line estimates is smaller than the symbol
representing the average.
8-30
-------
Comparative Loadings in the Bay
1.0
o
o
2 0.8
X!
s«
•£» 0.6 ^
•*~s
a 0.4 ^
IM
c 0.2
c
£ o.o i
I
Phenanthrene
Total Input: 720 Ib/yr
AD FL UR
SE
PS Other
Sources
Figure 8.28. Total loads of phenanthrene to the tidal Patuxent River from atmospheric
deposition (AD); fall line (FL); urban runoff (UR); shoreline erosions (SE); and point sources
(PS). Examples of "Other Sources" not fully quantified may include loads from smaller point
sources, agricultural runoff, atmospheric deposition, groundwater, and natural sources. The
variability in the fall line estimates is smaller than the symbol representing the average.
0.30
Cadmium
Total Input: 340 Ib/yr
0.00
AD FL UR CSO PS Other
Sources
Figure 8.29. Total loads of cadmium to the tidal Anacostia River from atmospheric deposition
(AD); fall line (FL); urban runoff (UR); combined sewer overflow (CSO); and point sources
(PS). Point source loadings were not reported. Examples of "Other Sources" not fully quantified
may include loads from smaller point sources, agricultural runoff, atmospheric deposition,
groundwater, and natural sources. The variability was not calculated due to the lack of data and
reported ranges.
8-31
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Comparative Loadings in the Bay
>»
6.0
5.0
4.0 /
£ i.o
a
§- 0.5 1
U
0.0
Copper
Total Input: 6,000 Ib/yr
AD
UR CSO
PS Other
Sources
Figure 8.30. Total loads of copper to the tidal Anacostia River from atmospheric deposition (AD); fall
line (FL); urban runoff (UR); combined sewer overflow (CSO); and point sources (PS). Examples of
"Other Sources" not fully quantified may include loads from smaller point sources, agricultural runoff,
atmospheric deposition, groundwater, and natural sources. The variability was not calculated due to the
lack of data and reported ranges.
o
o
o
Lead
Total Input: 19,000 Ib/yr
AD FL UR CSO PS Other
Sources
Figure 8.31. Total loads of lead to the tidal Anacostia River from atmospheric deposition (AD); fall line
(FL); urban runoff (UR); combined sewer overflow (CSO); and point sources (PS). Point source
loadings were not reported. Examples of "Other Sources" not fully quantified may include loads from
smaller point sources, agricultural runoff, atmospheric deposition, groundwater, and natural sources.
The variability was not calculated due to the lack of data and reported ranges.
8-32
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Comparative Loadings in the Bay
20
o
o
X
s.
Zinc
Total Input: 23,000 Ib/yr
AD FL UR CSO
PS Other
Sources
Figure 8.32. Total loads of zinc to the tidal Anacostia River from atmospheric deposition (AD);
fall line (FL); urban runoff (UR); combined sewer overflow (CSO); and point sources (PS).
Examples of "Other Sources" not fully quantified may include loads from smaller point sources,
agricultural runoff, atmospheric deposition, groundwater, and natural sources. The variability
was not calculated due to the lack of data and reported ranges.
8-33
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CHAPTER 9 - Mass Balance of Chemical Contaminants
within Chesapeake Bay
David Velinsky Joel Baker
Patrick Center for Environmental Research Chesapeake Biological Laboratory
The Academy of Natural Sciences University of Maryland
1900 Benjamin Franklin Parkway P. O. Box 38
Philadelphia, PA 19103-1195 Solomons, MD 20688
INTRODUCTION
The Chesapeake Bay Basinwide Toxics Reduction Strategy Reevaluation Report
(Chesapeake Bay Program, 1994b) described the results of a multi-year effort to evaluate the
nature, extent, and magnitude of the Bay's chemical contaminant problems. Continuing these
efforts, the data within the preceding chapters present recent information regarding the various
measured and potential inputs to the Bay. While these studies continue the Bay Program's effort
to account for the sources of chemical contaminants, a more exacting examination of both the
sources (inputs) and sinks (outputs) is needed. The identification and quantification of the
different sources and sinks of anthropogenic chemicals in Chesapeake Bay is an important step
towards understanding their cycling and potential effects, and can help target strategies for
contaminant reductions.
One way to place this information into a coherent framework, or accounting system, is to
develop chemical contaminant mass balances (Velinsky, 1997). A mass balance requires that the
quantities of chemical contaminants entering the Bay, less the amount stored, transformed, or
degraded within the system, equal the amount leaving the Bay system. With a working mass
balance budget, various control strategies can be simulated to evaluate long-term changes for
each contaminant or for contaminant groups. Such simulations and predictions can be valuable
in the assessment of the effect of chemical contaminants on ecosystem health, and can help make
expensive monitoring programs within the Bay more cost-effective. Once a mass balance is
accurately verified, it could be used to answer "what if questions such as; if specific sources are
reduced, how much reduction is needed and how long will it take to lower the concentration of a
specific contaminant in the water column or an organism to a given level?
A mass balance framework is a useful system in understanding the inputs, outputs and
flow of chemical contaminants in the Bay and tributaries. Specifically, a mass balance provides:
1) a gross check and balance on whether or not loadings estimates are consistent and realistic, 2)
an idea of the fate of contaminants in the Bay and its tributaries, 3) a management tool for
predicting results from load reductions, and 4) a consistent way to identify key data gaps and
uncertainties that need to be addressed for management/scientific purposes.
9-1
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Mass Balance
This chapter presents an initial test of a simple chemical contaminant mass balance for
Chesapeake Bay. This mass balance utilizes data obtain from the preceding chapters and
information obtained from the Solomons Island Mass Balance Workshop (May 7&8, 1998). The
overall objective of this exercise is to help verify the loads estimated for the Bay. An inherent
problem with the current load estimates is that are of varying accuracy and precision, and are
integrated over different spatial and temporal scales. A second problem is that an independent
reality check for the loading estimates is lacking. This initial mass balance is used to help
compare and evaluate the loadings estimates in the Toxics Loadings and Release Inventory
(TLRI). However, major differences (i.e., > 10X) between inputs and outputs of a given
contaminant likely indicate problems with one or the other estimates, or both.
Model Framework
The mass balance model used in this study is designed to be as simple as possible while
maintaining the extreme spatial variability (i.e., salinity, chemical concentrations, etc.) of the
mainstem of the Chesapeake Bay. This is a very simple model, and is not meant to represent the
state-of-the-art in water quality modeling. Rather, it is an initial attempt to organize the chemical
contaminant loading data within the context of measured ambient levels and estimated
contaminant loss processes. This effort describes the spatial variability on scales of tens of
kilometers and on an annual time scale.
This model allows us to compare the
loadings described in the preceding chapters
to net loss processes, and also to estimate
the transport of chemicals from the
tributaries to the mainstem of the
Chesapeake Bay. The model takes the input
of contaminants from the mouth of each
tributary (i.e., the boundary between the
mainstem bay and a tributary), along with
other loadings direct to the mainstem (i.e.,
atmospheric deposition, point sources, etc.),
transports them through the Bay, allowing
for burial, degradation, volatilization
between the air/sea interface, and sediment
burial.
- — Surface Water Adva
- Bottom Water Advec
^]X Dispersion
JAR
Figure 9.1. Schematic
Contaminant Mass Bai
j
BH <-
•%.
ction
:tion
Px
-•- —
Pt -
-»-
Rp .,
Yk -
Jm _
""" \'~
•ii— H — i
Susquehanna
i
•
! 1
-:. 8
' i
\ t
6
; i
_ * 5
! 1 ""
- ' 4
; l
3
i t
2
• i
t
1
1 CP
|ER/| t
Ocean
of Chesapeake Bay Chemical
ance Model (after Hagy, 1998).
The model is based on a salt-balance
model developed by Hagy (1998). The
mainstem is divided horizontally into nine
boxes (numbered 1-9 from south to north),
with all but the northern-most box further
subdivided by depth into a surface and
9-2
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Mass Balance
bottom layers (Figure 9.1). Water exchanges between these 17 model cells were calculated by
Hagy by balancing water flows to match the salinity profiles determined by the Chesapeake Bay
monitoring program. Similarly, transport of solids among the boxes depends upon the water
flows and the observed suspended solids concentrations in the mainstem. Tributary flows
entering the mainstem model boxes were determined by the long-term flow and suspended solids
records at the respective tributary gauging stations.
Tributaries are not explicitly modeled here, but rather are treated as single boxes which
process loadings and export chemicals to the mainstem at the boundary between the tributary and
mainstem boxes. It is important to remember that this model does not properly describe the
dynamics of contaminant movements within each tributary. This constraint results from the lack
of spatially-explicit concentration data within the tributaries and because the salt-balance
approach breaks down in the fresher reaches of the tributaries. There is no explicit linkage
between contaminant loadings to the tributaries (which are simply totaled and reported by the
model) and the net exports from the tributary (which are calculated as the product of the net
water outflow and the estimated ambient chemical concentrations at the mouth of each river).
Chemical contaminants enter and leave each model cell by a variety of processes (Figure
9.2). Chemical inputs to each model segment or cell include those sources cataloged in the
previous chapters of this report as well as flows of chemicals from adjacent model cells and
exchange with the sediments (resuspension and burial). Gross advective transport between
adjacent cells is calculated as the product
of the estimated concentration of the
chemical in the cell (g/m3) and the water
transport flux (mVday) estimated from the
salt balance and the tributary flows. The
sinking flux which transports chemicals
from surface to bottom model cells is
calculated in two steps. First, the
concentration of particle-associated
chemical contaminant in the surface cell
is calculated as a fraction of the total
(dissolved plus particulate) concentration
using an estimated distribution coefficient
and the measured suspended solids
concentration. This particle-associated
chemical contaminant concentration
(g/m3) is then multiplied by a 'settling
velocity' term (equal to 1 m/day in this
model) and the interfacial area (m2) to
estimate the settling flux (g/day). Long-
wet
Aerosol
Gas
Exchange
Upstream
Point
Stormwater
Runoff
Shoreline
Upstream .
Groundwater
Surface
Sinking
Up/down-welling
Bottom
. Downstream
Degradation
Downstream
Diffusion Resuspension Burial
Figure 9.2. Flows of chemical contaminants into and from
model cells.
9-3
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Mass Balance
term net rates of chemical burial in sediments is calculated as the product of the measured (or
interpolated) chemical concentration in surficial sediments and the long-term net sediment
accumulation rate estimated from measured sediment accretion rates. The bottom of each model
cell is the boundary between bottom waters and sediments. Diffusion of chemicals from the
sediments are estimated from field and laboratory flux chamber experiments for metals;
diffusional fluxes for organic chemicals are assumed to be zero. Resuspension is considered to
be a chemical recycling process within the water column (which, therefore, does not affect the
mass balance on each model cell), and is calculated as the difference between calculated settling
and long term burial rates.
The model calculates chemical flows into and from each model cell on a monthly basis,
assuming constant daily flows within each month. All observations were either aggregated (in
the case of more frequent measurements such as tributary flows) or disaggregated (in the case,
for example, of loadings that were reported on an annual basis) to provide the average daily value
for each month. Results from the monthly budgets for each cell were aggregated to produce
annual summaries of loadings and losses to the mainstem Chesapeake Bay.
It is very important to remember that this 'mass balance' does not require that the
loadings and losses of each chemical 'balance'. That is, the model does not 'force' a balance,
and no loading or loss term is calculated by difference in order to create a balance. In fact, there
is no reason to suspect that the Chesapeake Bay is at steady state with respect to chemical
loadings, and it is entirely reasonable to expect that loads do not equal losses. The model simply
converts all of the loading terms to the same units and temporal scale and sums them. This is
compared to our best estimate of total contaminant losses in the mainstem. Major (i.e., order of
magnitude) discrepancies between loadings and losses of a given contaminant, however, likely
indicate problems with one or the other estimates, or both.
RESULTS AND DISCUSSION
Trace Elements
Below are two examples of the model for copper (Cu) and mercury (Hg).
Copper
Point source, fall line, urban stormwater, atmospheric deposition, and shoreline erosion
inputs to the Bay and its tributaries were derived from the information within the preceding
chapters. Sediment diffusion of copper out of the sediments was obtained from studies and
unpublished data by Riedel et al. (1995a,b;1997; 1999a,b; unpublished data), Cornwall et al.
(unpublished data), and others. For copper as well as other metals there is a lack of sediment
diffusion data for most areas of Chesapeake Bay and its tributaries. Studies were conducted with
Baltimore Harbor, Mid-Chesapeake Bay (Site M), and Patuxent River sediments; either in the
9-4
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Mass Balance
laboratory or in-situ. The limited data were used along with best professional judgement to
derive rates for the mainstem Bay and tributaries. It should be noted that the sediment diffusion
flux of copper to the bottom waters of the Bay is an internal source, and does not affect the
assessment of the overall input/output budget within the current model framework.
Accurate concentrations of dissolved copper in the water column throughout the Bay
were limited, and there was no information for particulate copper for the mainstem or many
tributaries of the Bay. Dissolved data were obtained from the studies of Culberson and Church
(1988), Donat et al. (1994; unpublished data), Henry and Donat (1996), Donat and Henry (1997),
and for the Patuxent and Anacostia Rivers from Riedel et al. (1995a,b;1997; 1999a,b;
unpublished data), Velinsky et al. (1999), and Coffin et al. (1998). The dissolved copper
concentrations in the mainstem Bay covered a 10 year period from the work by Culberson and
Church (1988) to Donat (1994; unpublished data), Henry and Donat (1996), and Donat and
Henry (1997), however, for the current model framework total concentrations of copper are
needed. Since there was no particulate (or total) copper concentrations, an average copper
partition coefficient (i.e., K^ [L/kg = cone, in dissolved phase/cone, in particulate phase]) was
derived using the Patuxent River copper data set (Riedel and Gilmour, unpublished data) with
varying salinities. The Patuxent River copper K^ values were used for each segment of the
model.
Concentrations of copper in the surface sediments of Chesapeake Bay and its tributaries
were obtained from the comprehensive report by Eskin et al. (1996). The data within the report
represents surface sediment concentrations from samples collected over various years. Each
segment was assigned a median or average concentration for the entire area of the segment.
While median or average concentrations were used to calculate the burial of trace metals, there is
substantial spatial variability in the concentration of metals throughout all areas. Additionally, as
stated above, deposition rates were assumed to cover the entire area of each segment (see Officer
et al, 1984). This would tend to overestimate the total deposition to the sediment due to the
spatial variations in deposition within each box or area of the mainstem bay.
The total copper load to the mainstem Bay is approximately 118,000 kg/yr (Table 9.1)
and indicates that approximately 60% of the total input to the tidal Bay (322,000 kg/yr) is
retained within the tributaries. In other words, a substantial portion of the total load to the entire
Chesapeake Bay is retained within the tributaries with approximately 40% of the total input
transferred to the mainstem Bay. Tributary inputs and shoreline erosion account for major input
to the mainstem Bay; approximately 90% of the total input, while direct atmospheric (wet+dry)
and point sources are small and total approximately <1% of the total mainstem load. Due to a
lack of data, the flux of sediment and associated copper from shoreline erosion was assumed to
be to the mainstem Bay, and this is probably an overestimation given the extensive shoreline in
the tributaries and potential erosion.
9-5
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Mass Balance
The main mechanism for the loss of copper from the mainstem Bay is sediment burial
with only a small fraction exchanging out the Bay mouth to the coastal waters (Table 9.2). The
total output from the mainstem was calculated to be 110,000 kg/yr which is in excellent
agreement with the total input to the mainstem Bay. Given the uncertainty in the modeling
framework and assumptions for various input/output rates (i.e., flows, sedimentation rates, etc), it
is remarkable that a good balance was obtained and suggests that the inputs to the Bay are fairly
well constrained. The loss of copper via burial (105,000 kg/yr) is a net rate with sediment
diffusion re-releasing approximately 20,000 kg Cu/yr back into the mainstem Bay.
In summary, the present mass balance estimate within Chesapeake Bay for copper
appears to be fairly well constrained. While there is a good agreement between the sources of
copper and removal of copper, better quantification of the tributary inputs (i.e., the boundary
between the tributaries and the mainstem) and sediment burial are needed. These along with the
Susquehanna River inputs are the major fluxes identified by the model. The majority of the
copper loads to the mainstem Bay is from Susquehanna River with lesser amounts from the
tributaries. As stated earlier, shoreline erosion was assumed to be direct to the mainstem Bay.
However, given the extensive shoreline and potential erosion in the tributaries the total flux
needs to be separated between tributary and mainstem Bay inputs. These areas would help
support the agreement between inputs and outputs in the Chesapeake Bay.
Mercury
Loadings of total mercury to the Chesapeake Bay below the fall-lines are summarized in
Table 9.3. Estimates of atmospheric deposition (wet deposition, dry aerosol deposition, and net
volatilization) and fall-line loadings are taken from the studies of Mason and co-workers (Mason
et al., 1997a,b; Lawson and Mason, 1998; Benoit et al., 1998; Mason et al., 1999; Mason and
Lawrence, 1999). Mercury loadings from point sources and urban runoff are taken from
estimates in the preceding chapters. Erosion of shoreline material is assumed to be an
insignificant source of mercury, though whether erosion is an important source of mercury to the
Bay is largely unknown. The role of groundwater as a source of mercury to the Bay is also
unknown and is assumed to be zero for this exercise. As is the case with the other chemicals
analyzed here, point source loadings of mercury were estimated as the average of the 'high' and
'low' estimates taken from Chapter 1.
According to this analysis, tributary and point source inputs contribute the majority of the
total mercury loading to the Bay below the fall-lines. The point source loads are likely an
overestimation due to analytical methods and detection limit issues with point source effluent
analysis. Diffusion from sediments, urban runoff, and inputs from the rivers contribute about
75% of the total mercury load to the mainstem Bay if the point source loads are correct. The
majority of the mercury enters the bay in its tributaries below the fall-lines. Virtually all of the
urban runoff and point sources of mercury are discharged to the tributaries rather than the
mainstem. As was seen with other particle-reactive chemicals, the vast majority of the mercury
9-6
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Mass Balance
discharged into the tributaries is retained and not transmitted to the mainstem. Less than 10% of
the mercury that enters the tributaries is transmitted into the mainstem of the Chesapeake Bay.
Although we do not have sufficient data from the tributaries to verify these estimates of mercury
retention, this calculation suggests that localized tributary sediments should be enriched hi
mercury and other particle-reactive contaminants.
Losses of mercury from the mainstem Chesapeake Bay include export to the ocean, burial
in sediments, and volatilization (Table 9.4). In this analysis, burial accounts for three quarters of
the mercury loss, with export and volatilization resulting in 20% and 3% of the annual mercury
loss, respectively. The estimated total annual losses of mercury from the mainstem Chesapeake
are four times the estimated loadings to the mainstem. Whether this discrepancy reflects a real
imbalance between loads and losses or indicates over- and/or underestimations of sources and
sinks cannot be determined from these data.
Organic Contaminants
Below are two examples of the mass balance calculations for organic contaminants
presented using total PCBs (sum of all measured congeners or, in the case of point source
loadings, Aroclor 1260) and the polycyclic aromatic hydrocarbon (PAH) phenanthrene.
Total PCBs
Total PCB loadings were calculated for each source type as described in the preceding
chapters (Table 9.5). As no estimate of PCB loadings from urban runoff were made, we assumed
here that the PCB load was equal to one half of the total mercury load from urban runoff, based
on our recent observations that the concentrations of total PCBs in the water column and
sediments of an urban-runoff dominated system (i.e., Baltimore Harbor) are approximately one
half those of mercury (Ashley et al., 1999; Mason and Lawrence, 1999). Transport of total PCBs
from the tributaries to the mainstem was estimated for each tributary assuming a total PCB
concentration at the river mouths of 0.95 to 1.2 ng/L (Nelson et al., 1998).
The comparison of loadings of total PCBs to the Chesapeake Bay below the fall lines
shows that estimated point sources are three orders of magnitude greater than all other sources
(Table 9.1) and this is certainly not correct. In fact, the estimated point source loadings of PCBs
far exceed our best estimate of the amount of PCBs in the mainstem Chesapeake Bay (perhaps on
the order of 1,000 kg total in the water column and sediments). Even if the point source estimate
is 100 fold too high, however, we still conclude that point source emissions of PCBs is an
important contribution to the total loading. This was illustrated by the Potomac River point
source data described in the previous chapter. In this example, point source concentrations of
total PCBs were derived from recent studies in the Delaware and Hudson Rivers and used with
the flow from point sources to the tidal Potomac River. The resultant load indicates that
approximately 60% of the total PCB load is derived from point sources and PCB loads are
9-7
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Mass Balance
comparable to fall line estimates to the tidal Potomac. In the current analysis, virtually all of the
PCBs entering the Chesapeake Bay are loaded into the tributaries. The estimate for the total
PCB loading to the mainstem of the Chesapeake Bay is 183 kg/year, one third of which is
supplied by loading from the Susquehanna River. Urban runoff and atmospheric deposition
supply approximately equal loads of PCBs to the mainstem Chesapeake Bay.
It is crucial to note that a vanishingly small fraction of the PCB loading to the tributaries
is transported to the mainstem Chesapeake Bay (< 0.5% of 410,000 kg/year,). Even excluding
the admittedly flawed point source estimate from the comparison, only 5% of the non-point
source loads to the tributaries are transported to the mainstem. This implies that tributaries are
extremely efficient traps for these particle-reactive chemicals and that dilution by downstream
transport is not an effective cleansing mechanism for the tributaries. Stated another way, these
simple calculations support the observation of higher concentrations in the Chesapeake Bay
tributaries, where local chemical loadings remain concentrated near discharge points (i.e., point
and non-point sources).
Interestingly, the estimates of PCB loadings to the mainstem are six times less than our
estimates of PCB losses from the mainstem. Losses of PCBs are distributed among ocean export
(50%), volatilization (30%) and burial (20%; Table 9.6). Some fraction of this difference may be
real, as the inventories of PCBs in the bay are likely decreasing with time (i.e., losses exceed
loadings) in response to the production and use ban on PCBs in the late 1970's. Also, these
calculations do not include any net release of PCBs from sediments. A net release on the order
of 180 jig/m2-year from the sediments would be required to balance loads and losses; this is
about 3.5 times the long-term PCB burial rate.
Phenanthrene
Loadings of phenanthrene to the Chesapeake Bay are summarized in Table 9.7. Unlike
PCBs, where volatilization exceeds wet and dry aerosol deposition, absorption of gaseous
phenanthrene from the atmosphere is a significant source to the Bay (Nelson et al., 1998;
Bamford et al., 1999). Point sources, as estimated in this report, comprise three quarters of the
total phenanthrene loading to the Bay below the fall lines, while gas absorption and urban runoff
contribute most of the phenanthrene entering the mainstem of the Bay. Approximately 90% of
phenanthrene entering the Chesapeake Bay is loaded into the tributaries. As was the case of
PCBs, only a small fraction of the phenanthrene entering the tributaries (53,000 kg/year) is
transported to the mainstem (1250 kg/year, or 0.2%). This inefficient transmission of
phenanthrene likely reflects both burial in tributary sediments and degradation near the emission
sources. Degradation of phenanthrene in surface waters, primarily via photolytic reactions,
accounts for two thirds of the loss of phenanthrene from the mainstem, and burial and export to
the ocean are approximately equal in magnitude (Table 9.8).
The reader will note that the independent estimates of phenanthrene loading to the
9-8
-------
Mass Balance
mainstem (4,360 kg/year) and losses (4,310 kg/year) agree to within 2%. As with the copper
balance, whether this reflects the skill or the luck of the author remains to be determined.
9-9
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Mass Balance
Table 9.1. Loadings of total copper to Chesapeake Bay.
Wet Deposition
Dry Aerosol Deposition
Urban Runoff
Point Sources
Shoreline Erosion
Groundwater
Tributaries to Bay
TOTAL
Total Load
Below Fall-
Lines
4,700
4,300
24,500
36,600
27,700
0
224,000
322,000
Total Load to
Mainstem
330
430
7,200
330
27,700
0
81,700
118,000
Total Load to
Tributaries
(by difference)
4,400
3,900
17,300
36,300
0
0
142,300
204,200
Units: kg/yr
Table 9.2. Losses of total copper from the mainstem
Chesapeake Bay.
Export to the Ocean 2,000
Burial in Sediments 105,000
TOTAL MAINSTEM LOSSES 107,000
Units: kg/yr
9-10
-------
Mass Balance
Table 9.3. Loadings of Mercury to Chesapeake Bay.
Total Load Total Load to Total Load to
Below Fall- Mainstem Tributaries
Lines (by difference)
Wet Deposition
Dry Aerosol Deposition
Diffusion from Sediments
Urban Runoff
Point Sources
Shoreline Erosion
Groundwater
Tributaries to Bay
TOTAL
105
21
240
370
1,200
0
0
2,600
4,540
92
17
130
0
3
0
0
180
420
13
4
110
370
1,200
0
0
2,400
4,120
Units: kg/yr
Table 9.4. Losses of Mercury from the Mainstem
Chesapeake Bay.
Export to the Ocean 350
Volatilization 57
Burial in Sediments 1,350
TOTAL MAINSTEM LOSSES 1,760
Units: kg/yr
9-11
-------
Mass Balance
Table 9.5. Loadings of total PCBs to Chesapeake Bay.
Total Load Total Load to
Below Fall- Mainstem
Lines
Wet Deposition
Dry Aerosol Deposition
Urban Runoff
Point Sources
Tributaries to Bay
TOTAL
65
65
180
410,000
130
410,400
27
27
55
0
74
183
Total Load to
Tributaries
(by difference)
38
38
129
410,000
72
410,300
Units: kg/yr
Table 9.6. Losses of total PCBs from the mainstem
Chesapeake Bay.
Export to the Ocean 560
Volatilization 340
Burial in Sediments 280
TOTAL MAINSTEM LOSSES 1,180
Units: kg/yr
9-12
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Mass Balance
Table 9.7. Loadings of Phenanthrene to Chesapeake Bay.
Total Load Total Load to
Below Fall- Mainstem
Lines
Wet Deposition
Dry Aerosol Deposition
Gas Absorption from the Atmosphere
Urban Runoff
Point Sources
Tributaries to Bay
TOTAL
65
150
3,040
7,130
47,000
120
57,510
46
110
1,950
2,100
4
150
4,360
Total Load to
Tributaries
(by difference)
19
44
1,090
5,030
47,000
95
53,300
Units: kg/yr.
Table 9.8. Losses of Phenanthrene from the Mainstem
Chesapeake Bay.
Export to the Ocean 750
Degradation (k=0.045 day1) 2,860
Burial in Sediments 700
TOTAL MAINSTEM LOSSES 4,310
Units: kg/yr
9-13
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Mass Balance
SUMMARY AND CONCLUSIONS
The mass balance analysis for total PCBs, phenanthrene, copper and mercury reveal
different levels of agreement between the inputs to the mainstem Bay and the outputs. While
copper and phenanthrene show good agreement between the inputs and outputs, total PCBs and
mercury do not. Both total PCBs and mercury outputs from the mainstem water column are
higher than the loads to the mainstem by about a factor of 5. Unfortunately, due to the lack of
sufficient data it is impossible to quantify the uncertainty for these estimates and this is where
future monitoring efforts should be focused. Greatest uncertainty for the sources is most likely
tributary inputs to the mainstem segment of the model, while for the output of chemicals, the
greatest amount of uncertainty is probably with the export to the ocean and burial in the
sediments.
The comparison between the total load below the fall line and inputs to the mainstem Bay
reveal a common and important feature for all chemicals. In this analysis, most of the loads are
to the tributaries (i.e., Potomac, James, York Rivers) with the majority (i.e., > 90%) of these
inputs for total PCBs, phenanthrene, mercury, retained in the tributaries. Copper shows the
greatest export to the mainstem from the tributaries with approximately 60% of the total load
exported to the mainstem. However, due to the method used for this analysis and the available
data, this estimate is tentative at best.
This study suggests focusing monitoring efforts on specific sources and geographic areas
that would greatly improve and expand a mass balance and provide better check and balances
between inputs and outputs. This would enable better confidence in the loading estimates from
the previous chapters. For example, in many tributaries point sources or urban runoff are
dominant sources. The method used to calculate these sources should be updated. This is
especially true for the point source data in which there is a large range in the estimates. The best
method would be to determine, by flow, the dominant point sources and analyze their effluent
using state of the art methods with lower detection limits. Given that this would be very costly,
select point sources that represent specific industrial types (i.e., SIC) should be monitored to
provide baywide typical pollutant concentrations (TPCs) for unmonitored point sources. This
data could be used in conjunction with NOAA's extensive TPC database and would greatly
improve the overall point source estimate to the Bay. Additionally, the water column
concentrations of many chemicals are lacking throughout the Bay with respect to the data needs
of this or future models. Transport of dissolved and particulate metals and organic contaminants
at the tributary and ocean boundaries is largely unknown and are a major source/sink in the
model for all contaminants.
In general, basic monitoring information is needed for almost all sources and sinks
identified in this report. While these monitoring data will not provide information as to the
effects of chemical contaminants, they do provide the needed information as to where and how
9-14
-------
Mass Balance
much a reduction in a particular source load is needed. Until both sources and sinks are better
quantified, future input-output balances will remain uncertain and of limited quantitative use.
Once accurately verified, a mass balance model could be used to answer "what if questions such
as; if specific sources are reduced, how much reduction is needed and how long will it take to
lower the concentration of a specific contaminant in the water column or an organism to a given
level?
For a more complete mass balance model to be useful, its development must be driven by
the objectives upon which both managers and scientists decide. Also, there are many questions
concerning the feasibility of using a mass balance approach to manage or evaluate chemical
contaminants in Chesapeake Bay. For example, if a concerted effort is applied to determine the
absolute inputs and outputs from significant sources and sinks, will enough specific information
exist to help managers of the various sources of contaminants (i.e., point source regulators or
urban planners) determine the need for potential additional regulation of these sources? Also, if
additional regulatory actions are taken, will living resources that are affected by contaminants
respond and show some improvement (i.e., fewer fish advisories)?
As can be seen from the simple input-output model for the mainstem Bay, the data needs
for any of these tasks are enormous and would therefore be very expensive. However, it would
be useful and less expensive to focus on one tributary. This would allow a testing of specific
questions as to how contaminants are transported through a system and would help guide the data
needs for a much larger and complex system as the Chesapeake Bay. In addition, the preliminary
mass balance indicates that a majority of the contaminants, due to their particle-reactive
behavior, are trapped within the tributaries of the Bay. Therefore, it is more relevant to look at
the balances within specific tributaries to determine how much material is transported to the
mainstem Bay.
The development of a simple mass balance would provide useful information to Bay
managers. For example, current load estimations to the Bay could be evaluated and judged for
accuracy by also estimating the outputs. This would help managers and scientists determine any
unrecognized source(s) to the Bay. When an accurate assessment of the relative loading exists,
the importance of each source can be determined, and a determination can be made of the
possible measures in controlling these sources in an overall context. This information is needed
to help focus clean-up efforts and the limited dollars to areas and sources that will make the
biggest difference in the overall health of Chesapeake Bay.
Summary Recommendations for Implementing the Mass Balance
> Determine the spatial/temporal distribution of dissolved, particulate and volatile chemical
contaminants throughout the Bay and within the tributaries.
9-15
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Mass Balance
*• Obtain accurate point source loading estimates.
*• Obtain recent surface and subsurface sediment concentrations of chemical contaminants.
* Determine the depositional areas and rates within the mainstem and tributaries of the Bay.
> Derive relationships between sediment variables (e.g., sediment concentrations of metal
or organic, grain size, organic carbon, etc) and the diffusion to the overlying bottom
waters.
>• Water and chemical exchange rates at the ocean-bay interface.
> Focus research/monitoring efforts on a specific tributary to test specific hypothesis on
inputs and outputs fluxes.
9-16
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Mass Balance
ACKNOWLEDGMENT
We would like to thank the participants of the Solomons Island Mass Balance Workshop
(May, 1998) for their assistance in gathering the data for the mass balance model. Special thanks
to Rob Mason, Fritz Riedel, and Laura McConnell for editorial help. Jim Hagy helped derive a
working salt balance for the modeling framework.
9-17
-------
References
Achman, D.R., K.C. Hornbuckle, and SJ. Eisenreich. 1993. Volatilization of PCBs from
Green Bay, Lake Michigan, Environ. Sci. Technol., 27:75-87.
Ashley, J.T.F. and I.E. Baker. 1998. Hydrophobic organic contaminants in surficial sediments
of Baltimore Harbor: inventories and sources. Environ. Toxicol. Chem. (In press).
Athayde, D.E., P.E. Shelly, E.D. Driscoll, D. Gaboury and G.B. Boyd. 1983. Results of the
Nationwide Urban Runoff Program: Volume I - Final Report. US EPA, Washington, DC.
Baker, I.E., D.L. Poster, C.A. Clark, T.M. Church, J.R. Scudlark, J.M. Ondov, R.M. Dickhut,
and G. Gutter. 1997. Loadings of atmospheric trace elements and organic contaminants to
the Chesapeake Bay. In Atmospheric Deposition of Contaminants to the Great Lakes and
Coastal Waters, I.E. Baker, Ed., SETAC Press, PensacolaFL, 171-194.
Bamford, H.A., D.L. Poster, and J.E. Baker. 1999a. Temperature dependence of the Henry's
Law constants of thirteen polycyclic aromatic hydrocarbons between 4 C and 31 C. Environ.
Toxicol. Chem., in press.
Bamford, H.A., J.H. Offenberg, R. Larsen, F.C. Ko, and J.E. Baker. 1999b. Diffusive exchange
of polycyclic aromatic hydrocarbons across the air-water interface of the Patapsco River, an
urbanized subestuary of the Chesapeake Bay. Environ. Sci. Technol., in press.
Benoit, J.M., Gilmour, C.C., Mason, R.P., Reidel, G.S., and Reidel, G.F. 1998. Behavior of
mercury in the Patuxent River estuary. Biogeochemistry, 40,249-265.
Bidleman, T.F. and McConnell, L.L. 1995. A review of field measurements to determine air-
water gas exchange of persistent organic pollutants. Sci. Total Environ., 159:101-117.
Byrne, RJ. and J.L. Anderson. 1973. Virginia Journal of Science 24(3): 158.
Chesapeake Bay Program. 1982. Chesapeake Bay Program Technical Studies: A Synthesis.
U.S. EPA Chesapeake Bay Program, Washington, D.C., September, 1982, 634 pp.
Chesapeake Bay Program. 1994a. Chesapeake Bay Basin Toxics Loading and Release
Inventory: Basinwide Toxics Reduction Strategy Commitment Report. CBP/TRS 102/94.
U.S. EPA Chesapeake Bay Program, Annapolis, MD.
Chesapeake Bay Program. 1994b. Chesapeake Bay Basinwide Toxics Reduction Strategy
r-1
-------
References
Revaluation Report. CBP/TRS 117/94, U.S. EPA Chesapeake Bay Program Office,
Annapolis, MD, September, 1994,192 pp.
Chesapeake Bay Program. 1994c. Chesapeake Bay fall line toxics monitoring program 1992
Final Report, CBP/TRS 121/94. U.S. EPA Chesapeake Bay Program Office, Annapolis,
MD.
Chesapeake Bay Program. 1998. Chesapeake Bay Toxics of Concern List. U.S. EPA
Chesapeake Bay Program Office, Annapolis.(currently under review).
Church, T.M., J.R. Scudlark, K.M. Conko, O.P. Bricker, and K.C. Rice. 1998. Transmission of
atmospherically deposited trace elements through an undeveloped, forested Maryland
watershed. Final Report to the Maryland Department of Natural Resources, Chesapeake Bay
Research and Monitoring Division, Contract CB93-005-002.
Clark, LJ. 1969. Mine Drainage in the North Branch Potomac River Basin. Chesapeake
Technical Support Laboratory, Middle Atlantic Region. Federal Water Pollution Control
Administration, U.S. Department of the Interior. Technical Report No. 13.
Coffin, R.B., M. Orr, E. Carey, L. Cifuentes, and J. Pohlman. 1998. Contaminant distribution
and fate in Anacostia River sediments: Particulate Transport Survey. NRL/MR 6115-
98-8139. Naval Research Laboratory, Washington, DC.
Cohen, T.A., Caulder, D.L., Gilroy, E.J., Zynjuk, L.D., and R.M. Summers. 1991. The validity
of a simple log-linear model for estimating fluvial constituent loads: an empirical study
involving nutrient loads entering Chesapeake Bay. Water Resour. Res. 28,2353-2363.
Cole, R.H., R.E.Frederick, R.P. Healy, R.G. Rolan. 1983. NURP Priority Pollutant Monitoring
Project: Summary of Findings. US EPA, Washington, DC.
Culberson, C.H. and T.M. Church. 1988. Oceanographic Data Report Number 6: data from the
CDR Cruises: July 1985 to July 1987. Delaware Sea Grant College Program, University of
Delaware, Newark, DE.
Delaware River Basin Commission (DRBC). 1998. Study of the Loadings of PCBs from
Tributaries and Point Sources Discharging to the tidal Delaware River. Estuary Toxics
Management Program, DRBC, West Trenton, NJ. June 1998, 52pp with appendixes.
Donat, J.R. 1994. The speciation of dissolved copper and cadmium in Chesapeake Bay. EOS,
Transactions, American Geophysical Union, 75(44): 330. Abstracts for the American
Geophysical Union Fall Meeting, December 1994. San Francisco, CA.
r-2
-------
References
Donat, J.R. and C.W. Henry III. 1997. Concentrations, complexation, and speciation of
dissolved zinc in Chesapeake Bay. Abstracts for the 213th National Meeting of the
American Chemical Society, April 13-17,1997. San Francisco, CA. Part 1, GEOC 165.
Durell, G.S. and R.D. Lizotte Jr. 1998. PCB levels at 26 New York City and New Jersey
WPCPs that discharge to the New York/New Jersey Harbor Estuary. Environmental Science
and Technology 32(8): 1022-1031
Eisenreich, S.J., K.C. Hornbuckle, and D.R. Achman. 1997. Air-water exchange of semivolatile
organic chemicals in the Great Lakes. In Atmospheric Deposition of Contaminants to the
Great Lakes and Coastal Waters, J.E. Baker, Ed., SETAC Press, Pensacola FL, 109-136.
Eskin, R.A., K.H. Rowland and D.Y. Alegre. 1996. Contaminants in Chesapeake Bay
Sediments: 1984-1991. CBP/TRS 145/96. Chesapeake Bay Program, U.S. EPA, Annapolis,
MD, May, 1996.
Foster, G.D. and K.A. Lippa. 1996. Fluvial loadings of selected organonitrogen and
organophosphorus pesticides to Chesapeake Bay. J. Agric. Food Chem., 44,2447-2454.
Foster, G.D., K.A. Lippa, and C.V. Miller. (In press) Seasonal concentrations of organic
contaminants at the fall line of the Susquehanna River basin and estimated fluxes to
Chesapeake Bay. Env. Toxicol. Chem.
Gruessner, B., D.J. Velinsky, G.Foster, J. Scudlark, T.M. Church and R. Mason. 1997.
Dissolved and particulate transport of chemical contaminants in the Northeast and Northwest
Branches of the Anacostia River. ICPRB Report #97-2. Prepared for the DCRA, District of
Columbia. Interstate Commission on the Potomac River Basin, Rockville, MD.
Gruessner, B., R. Mandel, D. Caraco, M. Pierce, and S.S. Schwartz. 1998. Chemical
Contaminant Loads in Urban Stormwater Runoff from the Chesapeake Bay Basin, Interstate
Commission on the Potomac River Basin Report # 98-2, Rockville, MD.
Gustafson, K.E. and R.M. Dickhut. 1997. Gaseous exchange of polycyclic aromatic
hydrocarbons across the air-water interface of southern Chesapeake Bay. Environ. Sci.
Technol., 31:1623-1629.
Gutierrez-Magness, A.L., J.E. Hannawald, L.C. Linker and K.J. Hopkins. 1997. Chesapeake
Bay Watershed Model Application and Calculation of Nutrient and Sediment Loadings:
Appendix E - Phase IV Watershed Land Use and Model Links to the Airshed and Estuarine
Models. EPA 903-r-97-019, CBP/TRS 180/9. Chesapeake Bay Program, Annapolis, MD.
r-3
-------
References
Harman, J.A. 1996. Fate and Transport of Agricultural Pesticides in the Patuxent River, a Sub-
estuary of the Chesapeake Bay, M.S. Thesis, University of Maryland, College Park, 139 pp.
Harman-Fetcho, J.A., L..L. McConnell, and J.E. Baker. 1999. Agricultural pesticides in the
Patuxent River, a tributary of the Chesapeake Bay. J. Environ. Qual., in press.
Helz, G.R., S.A. Sinex, K.L. Fermi, and M. Nichols. 1985. Processes controlling Fe, Mn, and
Zn in sediments of northern Chesapeake Bay. Estuarine Coastal Shelf Science 21: 1-16.
Henry IH, C.W. and J.R. Donat. 1996. Zinc complexation and speciation in the Chesapeake
Bay. EOS, Transactions, American Geophysical Union, 76(3): OS72. Abstracts for the
American Geophysical Union/American Society of Limnology and Oceanography Ocean
Sciences Meeting, February 1996. San Diego, CA.
Hoff, R.M., W.MJ. Strachan, C.W. Sweet, C.H. Chan, M. Shackleton, T.F. Bidleman, K.A.
Brice, D.A. Bumiston, S. Cussion, D.F. Gatz, K. Harlin, and W.H. Schroeder. 1996.
Atmospheric deposition of toxic chemicals to the Great Lakes: a review of data through
1994. Atmos. Environ., 30:3505-3527.
Holsen, T.M., X. Zhu, N.R. Khalili, J.J. Lin, P. Lestari, C.S. Lu, and K.E. Noll. 1997.
Atmospheric particle size distributions and dry deposition measured around Lake Michigan.
In "Atmospheric Deposition of Contaminants to the Great Lakes and Coastal Waters" J.E.
Baker, Ed, SETAC Press, Pensacola, 35-50.
Hombuckle, K.C., C. Sweet, R. Pearson, D.L. Swackhamer, and SJ. Eisenreich. 1995.
Assessment of annual air-water fluxes of PCBs in Lake Michigan. Environ. Sci. Technol.,
29:869-877.
Horner, R.R., J.J. Skupien, E.H. Livingston, and H.E. Shaver. 1994. Fundamentals of Urban
Runoff Management: Technical and Institutional Issues. Terrene Institute, Washington, DC.
Lawson, N.M. and Mason, R.P. 1998. Accumulation of mercury in estuarine food chains.
Biogeochemistry, 40,235-247. [CES Contribution No. 2847]
Leister, D.L. and J.E. Baker. 1994. Atmospheric deposition of organic contaminants to
Chesapeake Bay. Atmos. Environ., 28:1499-1520.
Makepeace, D.K., D.W. Smith, and SJ. Stanley. 1995. Urban Stormwater Quality: Summary of
Contaminant Data. Critical Reviews hi Environmental Science and Technology, 25(2):93-
139.
r-4
-------
References
Mandel, R., D. Caraco, and S. S. Schwartz. 1997. An Evaluation of the Use of Runoff Models
to Predict Average Annual Runoff From Urban Areas. Interstate Commission on the
Potomac River Basin Report # 97-7, Rockville, MD.
Maryland Department of the Environment and Toxics RAP Stakeholders Workgroup. 1996.
Toxics Regional Action Plan for Baltimore Harbor.
Mason, R.P., N.M. Lawson, and K.A. Sullivan. 1997a. Atmospheric deposition to the
Chesapeake Bay watershed—regional and local sources. Atmos. Environ., 31:3531-3540.
Mason, R.P., N.M. Lawson, and K.A. Sullivan. 1997b. The concentration, speciation and
sources of mercury in Chesapeake Bay precipitation. Atmos. Environ., 31:3541-3550.
Mason, R.P., Lawson, N.M., Lawrence, A.L., Leaner, J.J., Lee, J.G., and Sheu, G.-R. 1998.
Mercury in the Chesapeake Bay. Accepted for publication hi Marine Chemistry.
McConnell, L.L., E. Nelson, C.P. Rice, J.E. Baker, W.E. Johnson, J.A. Haraian, and K. Bialek.
1997. Chlorpyrifos in the air and surface water of Chesapeake Bay: predictions of
atmospheric deposition fluxes. Environ. Sci. Technol., 31:1390-1398.
Metropolitan Washington Council of Governments (MW COG). 1997. An Existing Source
Assessment of Pollutants to The Anacostia Watershed. Dept. of Environmental Programs,
MW COG, Final Report, June 1997.
Nelson, E.D., L.L. McConnell, and J.E. Baker. 1998. Diffusive exchange of gaseous polycyclic
aromatic hydrocarbons and polychlorinated biphenyls across the air-water interface of the
Chesapeake Bay. Environ. Sci. Technol., 32:912-919.
Offenberg, J.H. and J.E. Baker. 1997. Polychlorinated biphenyls in Chicago precipitation:
enhanced wet deposition to near-shore Lake Michigan. Environ. Sci. Technol., 31:1534-
1538.
Offenberg, J.H. and J.E. Baker. 1999. Influence of Baltimore's atmosphere on organic
contaminants over the northern Chesapeake Bay. J. Air Waste Manag., in press.
Officer, C.B., D.R. Lynch, G.H. Setlock, and G.H. Helz. 1984. Recent sedimentation rates in
Chesapeake Bay. In: The Estuary as a Filter, (ed.: V.S. Kennedy), Academic Press, New
York, 131-157 pp.
Olsenholler, S.M. 1991. Annual Loading Estimates of Urban Toxic Pollutants in the
Chesapeake Bay Basin. Metropolitan Washington Council of Governments, Washington,
r-5
-------
References
DC.
Ondov, J.M., T.L. Quinn, and G.F. Battel. 1997. Influence of temporal changes in relative
humidity on size and dry depositional fluxes of aerosol particles bearing trace elements. In
Atmospheric Deposition of Contaminants to the Great Lakes and Coastal Waters, J.E. Baker,
Ed., SETAC Press, PensacolaFL, 17-34.
Poster, D.L., R. M. Hoff, and I.E. Baker. 1995. Measurement of the particle size distributions of
semivolatile organic contaminants in the atmosphere. Environ. Sci. Technol., 29:1990-1997.
Poster, D.L. and I.E. Baker. 1996a. The influence of submicron particles on hydrophobic
organic contaminants in precipitation. 1. Concentrations and distributions of polycyclic
aromatic hydrocarbons and polychlorinated biphenyls in rainwater. Environ. Sci. Technol.,
30:341-348.
Poster, D.L. and J.E. Baker. 1996b. The influence of submicron particles on hydrophobic
organic contaminants in precipitation. 2. Scavenging of polycyclic aromatic hydrocarbons by
rain. Environ. Sci. Technol., 30:349-354.
Poster, D.L. and J.E. Baker. 1997. Mechanisms of atmospheric wet deposition of chemical
contaminants. In Atmospheric Deposition of Contaminants to the Great Lakes and Coastal
Waters, J.E. Baker, Ed., SETAC Press, PensacolaFL, 51-72.
Riedel, G. F., J. G. Sanders, and C. C. Gilmour. 1995a. Contaminant flux from sediments:
Impact on Chesapeake Bay food webs. Final Report to NOAA/ Maryland Sea Grant.
Riedel, G. F., J. G. Sanders and R. W. Osman. 1995b. The role of benthic infauna and
fluctuating oxygen concentrations in the flux of toxic trace element from Chesapeake Bay
sediments, pp. 54-57 In (EJ. Olmi, Hill, P. and Sanders, J.G.) Chesapeake Bay
Environmental Effects Studies Toxics Reaearch Program, 1994 Workshop report. Virginia
Sea Grant College Program VSG-95-10.
Riedel, G. F., J. G. Sanders and R. W. Osman. 1997. Biogeochemical control on the flux of
trace elements from estuarine sediments: Water column oxygen and benthic infauna.
Estuarine Coastal and Shelf Science 44:23-38.
Riedel, G .F., R. W. Osman and J. G. Sanders. 1999a. Biogeochemical Control on the Flux of
Trace Elements from Estuarine Sediments: Effects of Seasonal and Short-term Anoxia. In
Press, Marine Environmental Research.
Riedel, G.F., D.L. Breitburg, C.C. Gilmour and J.G. Sanders. 1999b. Impact of sediment-
r-6
-------
References
associated contaminants on benthic species in Chesapeake Bay: Implications for carbon and
contaminant transfer in food webs. Final Report to Maryland Sea Grant/Chesapeake Bay
Environmental Effects Committee on CBEEC project R/CBT-31.
Schueler, T.R. 1994. Hydrocarbon Hotspots in the Urban Landscape: Can They Be Controlled?
Watershed Protection Techniques, 1(1): 3-5.
Scudlark, J.R., K.M. Conko, and T.M. Church. 1994. Atmospheric wet deposition of trace
elements to Chesapeake Bay: CBAD study Year 1 results. Atmos. Environ., 28:1487-1494.
Shepp, D.L. 1996. Petroleum Hydrocarbon Concentrations Observed in Runoff from Discrete,
Urbanized Automotive-Intensive Land Uses. Presented at Water Environment Federation's
Watershed '96 Conference, Baltimore, MD. Metropolitan Washington Council of
Governments, Washington, DC.
Solomon, K. R., D. B. Baker, R. P. Richards, K. R. Dickson, S. J. Klainey, T. W. LaPoint, R. J.
Kendall, J. M. Giddings, J. P. Giesy, L. W. Hall, Jr., and W. M. Williams. 1996. Ecological
risk assessment of atrazine in northern American surface waters. Environ. Toxicol. Chem.,
15:31-76.
Staudinger, J. and P.V.Roberts. 1996. A critical review of Henry'slaw constants for environmental
applications. Crit. Rev. Environ. Sci. Tech., 26:205-297.
Tataya, S., S. Tanabe, R. Tatsukawa. 1988. In Toxic Contamination in Large Lakes, Schmidtke,
N., Ed.; Lewis Publishers, Chelsea, MI, USA, 1988, pp. 237-281.
US Environmental Protection Agency. 1993. NPDES Storm Water Sampling Manual. US EPA,
Office of Water. Washington, DC.
Velinsky, DJ. 1996. A Chemical Mass Balance Framework for Chesapeake Bay. Interstate
Commission on the Potomac River Basin Report # 96-2, Rockville, MD.
Velinsky, D.J. 1997. A Chemical Contaminant Mass Balance Framework for Chesapeake Bay.
EPA 903-R-97-016, CBP/TRS 176/97. Chesapeake Bay Program Office, U.S. Environmental
Protection Agency, Annapolis, MD.
Velinsky, D.J., T.L. Wade, B. Gammisch, and J. Cornwell. 1996. Sediment deposition and
inventory of chemical contaminants in the tidal Anacostia River, Washington, D.C.. Society of
Environmental Toxicology Chemistry, 17th Annual Meeting, November 1996.
Velinsky, D.J., G. Riedel, and G. Foster. 1999. Effects of stormwater runoff on the water quality
r-7
-------
References
of the tidal Anacostia River. PCER Report 98-6. Patrick Center for Environmental Research,
Academy of Natural Sciences, Philadelphia, PA.
Virginia Department of Environmental Quality (VA DEQ). 1996. Technical Assessments in
Support of the Elizabeth River Regional Action Plan Development. Prepared by URS
Consultants, Inc. Contract No. 9705001-42. April 1996.
Wanninkhof, R., J. Ledwell, and J. Crusius. 1990. Gas transfer velocities on lakes measured with
sulfur hexafluoride. In Air-Water Mass Transfer, S. Wilhelms and J. Gulliver, Eds., American
Society of Civil Engineer, New York, pp. 441-458.
Wood, C.R. 1996. Water quality of large discharges from mines in the anthracite region of eastern
Pennsylvania. U.S. Geological Survey. Water Resources Investigations Report 95-4243.
Wu, Z.Y., J.M. Ondov, J.Z. Holland, and Z.C. Lin. 1992. Dry deposition fluxes of elements in
Chesapeake Bay aerosol. J. Aerosol Sci., 23:S969-S972.
Wu, Z.Y., M. Han, Z.C. Lin, and J.M. Ondov. 1994. Chesapeake Bay atmospheric deposition
study, Year 1: sources and dry deposition of selected elements in aerosol particles. Atmos.
Environ., 28:1471-1486.
Zufall, M. J. and C.I. Davidson. 1997. Dry deposition of particles to water surfaces. In Atmospheric
Deposition of Contaminants to the Great Lakes and Coastal Waters, J.E. Baker, Ed., SETAC
Press, Pensacola FL, 1-16.
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Appendices
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Appendix A: Chemicals and default detection limits
CHEMICAL SUBSTANCES
DEFAULT LIMITS(mg/l)
1,1,1 -TRICHLOROETHANE
1,1,2,2-TETRACHLOROETHANE
1,1,2-TRICHLOROETHANE
1,1-DICHLOROETHANE
1,1-DICHLOROETHYLENE
1,2,4-TRICHLOROBENZENE
1,2-CIS-DICHLOROETHYLENE
1,2-DICHLOROBENZENE
1,2-DICHLOROETHANE
1,2-DICHLOROPROPANE
1,2-DIPHENYLHYDRAZINE
1,2-TRANS-DICHLOROETHYLENE
1,3DICHLOROPROPENE
1,3-DICHLOROBENZENE
1,3-DICHLOROPROPENE
1,4-DICHLOROBENZENE
2,3,7,8-TETRACHLORODIBENZOFURAN
2,4,6-TRICHLOROPHENOL
2,4-DICHLOROPHENOL
2,4-DIMETHYLPHENOL
2,4-DINITROPHENOL
2,4-DINITROTOLUENE
2,6-DINITROTOLUENE
2-CHLOROETHYLVINYLETHER
2-CHLORONAPHTHALENE
2-CHLOROPHENOL
2-METHYL-4-CHLOROPHENOL
2-METHYLNAPTHTHALENE
2-NITROPHENOL
3,3'-DICHLOROBENZIDINE
3,4-BENZOFLUORANTHENE
4,6-DINITRO-O-CRESOL
4-BROMOPHENYLPHENYLETHER
4-CHLOROPHENYLPHENYLETHER
4-NITROPHENOL
ACENAPHTHENE
ACENAPHTHYLENE
ACETONE
ACROLEIN
ACRYLONITRILE
ALDRIN
ALUMINUM, ACID SOLUABLE
ALUMINUM, DISSOLVED
ALUMINUM, TOTAL
ALUMINUM, TOTAL RECOVERABLE
AMMONIA + UNIONIZED AMMONIA
ANTHRACENE
ANTIMONY, TOTAL
ARSENIC, DISSOLVED
ARSENIC, TOTAL
ARSENIC, TOTAL RECOVERABLE
ASBESTOS
BARIUM, DISSOLVED
BARIUM, TOTAL
BENZENE
BENZIDINE
BENZO[A]ANTHRACENE
BENZO[A]PYRENE
BENZO[GHI]PERYLENE
0.0038
0.0069
0.005
0.0047
0.0028
0.0019
0.001
0.0019
0.0028
0.006
0.000001
0.0016
0.000002
0.0019
0.000002
0.0044
0.01
0.0027
0.0027
0.0027
0.042
0.0057
0.0019
0.00013
0.0019
0.0033
0.003
0.01
0.0036
0.017
0.0048
0.024
0.0019
0.0042
0.0024
0.0019
0.0035
1
0.0007
0.0005
0.0019
0.02
0.02
0.02
0.02
0.01
0.0019
0.008
0.0009
0.0009
0.0009
0.001
0.001
0.0044
0.044
0.0078
0.0025
0.0041
A-l
-------
Appendix A: Chemicals and default detection limits
CHEMICAL SUBSTANCES
DEFAULT LIMITS(mg/l)
BENZ01KJFLUORANTHENE
BERYLLIUM, TOTAL
BHC-ALPHA
BHC-BETA
BHC-DELTA
BHC-GAMMA
BIS (2-CHLOROETHYL) ETHER
BIS (2-CHLOROISOPROPYL) ETHER
BIS (2-ETHYLHEXYL) PHTHALATE
BISI2-CHLOROETHOXY) METHANE
BORON, TOTAL
BROMODICHLOROMETHANE
BROMOFORM
BUTYL BENZYL PHTHALATE
CADMIUM, DISSOLVED
CADMIUM, TOTAL
CADMIUM, TOTAL RECOVERABLE
CARBON DISULFIDE
CARBON TETRACHLORIDE
CHLORDANE
CHLORIDE
CHLORINE, FREE AVAILABLE
CHLORINE, FREE RESIDUAL
CHLORINE, TOTAL RESIDUAL
CHLOROBENZENE
CHLORODIBROMOMETHANE
CHLOROETHANE
CHLOROFORM
CHLORPYRIFOS
CHROMIUM, DISSOLVED
CHROMIUM, HEXAVALENT
CHROMIUM, HEXAVALENT DISSOLVED
CHROMIUM, HEXAVALENT TOTAL RECOVERABLE
CHROMIUM, TOTAL
CHROMIUM, TOTAL RECOVERABLE
CHROMIUM, TRIVALENT
CHRYSENE
CLAMTROL CT-1
COBALT, TOTAL
COPPER, DISSOLVED
COPPER, TOTAL
COPPER, TOTAL RECOVERABLE
CYANIDE
CYANIDE, FREE AMENABLE TO CHLORINATION
CYANIDE, FREE NOT AMENABLE TO CHLORINATION
CYANIDE, TOTAL
CYANIDE, TOTAL RECOVERABLE
CYANIDE, WEAK ACID DISSOCIABLE
ODD
DDE
DDT
DI-N-BUTYL PHTHALATE
DI-N-OCTYLPHTHALATE
DIBENZO(A,H)ANTHRACENE
DICHLOROBROMOMETHANE
DICHLOROETHENE
DIELDRIN
DIETHYL PHTHALATE
DIMETHYL PHTHALATE
0.0025
0.00002
0.000003
0.0042
0.0031
0.000004
0.0057
0.0057
0.0025
0.0053
0.003
0.0022
0.0047
0.0025
0.005
0.005
0.001
0.01
0.0028
0.000014
1
0.0002
0.0002
0.0002
0.006
0.0031
0.00052
0.0016
0.004
0.0003
0.0003
0.0003
0.004
0.004
0.0001
0.0025
0.002
0.003
0.003
0.003
0.02
0.02
0.02
0.02
0.02
0.02
0.0028
0.0056
0.0047
0.0025
0.0025
0.0025
0.0022
0.0028
0.0025
0.0019
0.0016
A-2
-------
Appendix A: Chemicals and default detection limits
CHEMICAL SUBSTANCES
DEFAULT LIMITS(mg/l)
DIOXIN
ENDOSULFAN - ALPHA
ENDOSULFAN - BETA
ENDOSULFAN SULFATE
ENDRIN
ENDRIN ALDEHYDE
ETHION
ETHYL BENZENE
ETHYLBENZENE
FLUORANTHENE
FLUORENE
FLUORIDE
FLUORIDE, TOTAL
HALOGENATED HYDROCARBONS
HEPTACHLOR
HEPTACHLOR EPOXIDE
HEXACHLOROBENZENE
HEXACHLOROBUTAD1ENE
HEXACHLOROCYCLOPENTADIENE
HEXACHLOROETHANE
HEXAMETHYLPHOSPHORAMINE
HYDRAZINE
INDENOf 1,2,3-CD)PYRENE
IRON, DISSOLVED
IRON, TOTAL
IRON, TOTAL RECOVERABLE
ISOPHORONE
LEAD, DISSOLVED
LEAD, TOTAL
LEAD, TOTAL RECOVERABLE
MAGNESIUM, TOTAL
MANGANESE, DISSOLVED
MANGANESE, TOTAL
MERCURY, DISSOLVED
MERCURY, TOTAL
MERCURY, TOTAL RECOVERABLE
METALS, TOTAL
METHYL BROMIDE
METHYL CHLORIDE
METHYL ISOBUTYL KETONE
METHYLENE CHLORIDE
MOLYBDENUM, TOTAL
N-NITROSODI-N-PROPYLAMINE
N-NITROSODIMETHYLAMINE
N-NITROSODIPHENYLAMINE
NAPHTHALENE
NICKEL, DISSOLVED
NICKEL, TOTAL
NICKEL, TOTAL RECOVERABLE
NITRITE PLUS NITRATE
NITROBENZENE
NITROGEN, AMMONIA TOTAL
NITROGEN, KJELDAHL TOTAL
NITROGEN, NITRATE DISSOLVED
NITROGEN, NITRATE TOTAL
NITROGEN, NITRITE TOTAL
NITROGEN, ORGANIC TOTAL
NITROGEN, TOTAL
NITROGLYCERIN
0.000002
0.0056
0.000006
0.000023
0.0001
0.0072
0.0072
0.0022
0.0019
0.1
0.0019
0.0022
0.0019
0.0009
0.0004
0.0016
0.02
0.005
0.0037
0.03
0.03
0.03
0.0022
0.01
0.01
0.01
0.02
0.001
0.001
0.007
0.007
0.007
0.0012
0.00008
1
0.0028
0.02
0.00046
0.00015
0.0019
0.0016
0.005
0.005
0.005
0.01
0.0019
0.01
0.03
0.002
0.002
0.01
0.03
0.03
0.03
A-3
-------
Appendix A: Chemicals and default detection limits
CHEMICAL SUBSTANCES
DEFAULT LIMITSImg/l)
PCB 1221
PCB 1232
PCB 1242
PCB 1254
PCB-1016
PCB-1248
PCB-1260
PENTACHLOROBIPHENYL
PENTACHLOROPHENOL
PETROLEUM HYDROCARBONS
PETROLEUM OIL, TOTAL RECOVERABLE
PHENANTHRENE
PHENOL
PHENOLICS
PHENOLS
PHOSPHATE, ORTHO
PHOSPHOROUS
PHOSPHORUS, DISSOLVED
PHOSPHORUS, TOTAL
PHTHALATE ESTERS
POLYCHLORINATED BIPHENYLS (PCBS)
PYRENE
SELENIUM, DISSOLVED
SELENIUM, TOTAL
SELENIUM, TOTAL RECOVERABLE
SILVER
SILVER, DISSOLVED
SILVER, TOTAL
SILVER, TOTAL RECOVERABLE
SULFATE
SULFATE, TOTAL
SULFIDE, TOTAL
SULFITE
TANTALUM, TOTAL
TETRACHLOROETHYLENE
THALLIUM, TOTAL
TIN, DISSOLVED
TIN, TOTAL
TITANIUM, TOTAL
TOLUENE
TOTAL TOXIC ORGANICS
TOXAPHENE
TRANS-1,2-DICHLOROETHYLENE
TRICHLOROETHENE
TRICHLOROETHYLENE
TRICHLOROFLUOROMETHANE
TUNGSTEN, TOTAL
VANADIUM, TOTAL
VINYL CHLORIDE
VOLATILE ORGANICS
XYLENE
ZINC, DISSOLVED
ZINC, TOTAL
ZINC, TOTAL RECOVERABLE
Note: No data available for empty spaces under "Default Limits.
0.001
0.001
0.001
0.0001
0.0001
0.0036
1
0.0054
0.0015
0.002
0.01
0.06
0.01
0.01
0.00001
0.0019
0.0006
0.0006
0.0006
0.002
0.002
0.002
0.002
1
1
1
1
0.0041
0.02
0.007
0.007
0.05
0.006
1
0.00024
0.0016
0.0019
0.0019
0.01
0.003
0.00018
1
0.005
0.002
0.002
0.002
A-4
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EPA Report Collection
Regional Center for Environmental Information
U.S. EPA Region III
Philadelphia, PA 19103
-------
-------
Chesapeake Bay Basin
Toxics Loading and Release Inventory
May 1999
Chesapeake Bay Program
410 Severn Avenue, Suite 109
Annapolis, Maryland 21403 U.S EPA Region III
o,,,n~v<«l f'cml-pT for Environmental
1-800 YOUR BAY i.e#oi.«i U-iaer
r.'vr
j (; '60 A-:di Street (3PM52)
http://www.chesapeakebay.net ridiaclelphia, PA 19103
Printed by the U.S. Environmental Protection Agency for the Chesapeake Bay Program
-------
Executive Summary
I. WHAT IS THE PURPOSE OF THIS
INVENTORY?
This Toxics Loading and Release Inventory
is one of many tools the Chesapeake Bay
Program is using to set more targeted
source reduction and pollution prevention
goals to reduce and eliminate toxic impacts
in the Bay. The overall goal of the 1994
Chesapeake Bay Basinwide Toxics
Reduction and Prevention Strategy is "a
Chesapeake Bay free of toxics by reducing
or eliminating the input of chemical
contaminants from all controllable sources
to levels that result in no toxic or
bioaccumulative impact on the living
resources that inhabit the Bay or on human
health."
To address that goal, the Bay Program has
been following these steps (Figure 1):
1. Identifying areas of the Bay impacted
by toxics.
2. Determining chemicals causing the
toxic impacts.
3. Determining the origin of those
chemicals.
4. Implementing management actions to
reduce inputs of those chemicals to
levels that will result in no toxic or
bioaccumulative impacts on the Bay's
living resources or on human health,
based on available data and current
state of science.
3. Identify the chemical sources.
Point source loads
(industries; federal facilities;
wastewater treatment
plants); urban runoff loads;
atmospheric deposition
loads, etc.
4. Reduce chemical inputs.
Identify the toxics impacts
\on living resources.
2. Identify the chemicals
causing the impacts./
WATER
Benthic community
SEDIMENT
Figure 1. Chesapeake Bay Program process for managing chemical contaminant-related problems in the Bay
and its rivers. This figure illustrates that the loading data reported in this inventory are only one piece of the
overall toxics management picture. The inventory must be used in conjunction with data on toxics impacts
and impairing chemicals in order to identify sources to control.
-------
Executive Summary
Since the signing of the 1994 strategy, the
Bay Program has made significant progress
in identifying toxic impacts in the Bay and
chemicals causing the impacts. In early
1999, the Bay Program completed its
characterization of toxic impacts in all tidal
rivers of the Bay. This toxics
characterization will supplement existing
characterizations carried out by Bay
Program partners and will provide a
scientifically-based description of the
distribution and extent of chemical
contaminant impacts in the Bay. This
characterization and other state efforts have
identified chemicals which cause problems
in localized areas of the Bay's rivers. In
addition, the Bay Program has developed a
Chesapeake Bay Toxics of Concern List of
chemicals which cause, or have the potential
to cause, adverse impacts on the Bay system.
The information on impacts and
chemicals causing impacts, coupled with
this updated 1999 Chesapeake Bay
Basinwide Toxics Loading and Release
Inventory, will enable managers,
scientists, and stakeholders to target their
toxics reduction and prevention activities
toward specific sources and chemicals in
impacted areas of the Bay.
This inventory can be used by managers,
scientists, and the public in the following
ways:
* Scientists, managers, and stakeholders
can use this inventory, coupled with the
toxics characterization, to set reduction
targets for sources of chemicals causing
toxic impacts in the Bay's tidal rivers.
*• Managers can use the assessment of the
relative importance of point and
nonpoint sources of chemical
contaminants to better target their
management programs to the most
important sources.
> Scientists can use this inventory to
identify the greatest data needs to
improve future loads estimates.
* The public can use this inventory to
learn about their waterbodies of interest
- the types of chemicals entering these
waters, the magnitude of the loads, and
chemical sources. This information,
coupled with the toxics characterization
of these waters, will help the public
identify how and when to act to reduce
chemical loads to these waters.
This inventory reports chemical contaminant
loads to the Bay and its rivers but does not
report what the loads mean to the Bay's
living resources or which specific sources
and chemicals are causing impacts. A big
load of a chemical contaminant does not
necessarily mean a big impact, nor does a
small load always indicate a small impact.
A big load of chemical contaminants from a
particular source also does not mean that the
source is uncontrolled. For example, point
source dischargers may be in compliance
with their permits, but may still produce a
substantial load to the Bay and tidal rivers.
This is often the case with large flow
facilities (i.e., wastewater treatment plants)
that emit a very low concentration of a
chemical into the Bay and tidal rivers, but
their flow is so large that it results in a large
load. As stated previously, this inventory can
be used in conjunction with the toxics
characterization to help managers target
management actions toward specific
geographic areas, chemicals, and sources.
Toxicity of a chemical depends on many factors
such as the concentration, chemical/physical
form, and persistence of the chemical; the
chemical/physical properties of the waterbody
it is entering (i.e., pH, sediment type, etc.); and
the type and life stage of the living resources
exposed to the chemical.
i-2
-------
Executive Summary
II. WHAT IS THE FOCUS FOR THIS
INVENTORY?
Loads and Releases
This inventory reports both loadings and
releases to the Bay watershed. Loadings are
estimates of the quantity of chemical
contaminants that reach the Bay and tidal
rivers, from sources such as point sources
discharging into the Bay or its rivers, urban
runoff, atmospheric deposition on the Bay or
its rivers, shipping and boating, and acid
mine drainage. Releases are the estimates of
the quantity of chemical contaminants
emitted to the Bay's watershed that have the
potential to reach the Bay. The only release
information in this inventory is for pesticide
usage.
Loads to Tidal Rivers and Bay
The Chesapeake Bay has a direct connection
with the Atlantic Ocean. Because of the
ocean tides, saltwater from the Atlantic is
mixed in the Bay with freshwater derived
from land runoff. The part of the Bay and
its rivers that is influenced by the tide is
referred to as the "tidal Bay" and "tidal
rivers." Moving upstream, there comes a
point at which the rivers are no longer
influenced by the ocean tide. The portions
of the rivers that are not under the influence
of the tide is referred to as "non-tidal." The
boundary between the non-tidal and tidal
portions of a river is called the "fall line."
The fall line is the physiographic boundary
representing the natural geographic break
between the non-tidal and tidal regions of
the Bay watershed. For example, in the
Potomac River, the fall line is at Great Falls.
The tidal portions of rivers appear to be
efficient traps for chemical contaminants,
which may be a reason why only low levels
of chemical contaminants are detected in the
Bay. This inventory mainly reports chemical
contaminant loads to the Bay and its tidal
rivers, as opposed to non-tidal waters,
because tidal waters are the focus of the Bay
Program's toxics efforts. The sites of many
of the known toxics problems are in tidal
waters and most of the urban areas and
toxics-related land use activities are adjacent
to tidal waters. However, it is important to
note that non-tidal waters — above the fall
line — are also sources of chemical
contamination. Chemical contaminant loads
can enter the Bay and its rivers above the fall
line (non-tidal waters) or below the fall line
(tidal waters). Measurements taken at the fall
line are used to represent the fraction of
upstream loads (whether from point or
nonpoint sources) that make it to the tidal
waters. Upstream sources can originate from
point sources such as industries, federal
facilities (e.g., military bases), and
wastewater treatment plants or nonpoint
sources such as agricultural or urban runoff.
In this inventory, chemical contaminant loads
entering the rivers above the fall line are
reported for point sources, urban runoff, and
acid mine drainage only. Loads to the tidal
rivers, below the fall line, are reported for
point sources, urban runoff, atmospheric
deposition, and shipping and boating spills.
(Figure 2)
i-3
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Executive Summary
Watershed (land)
Point Source Loads
Urban Stormwater Runoff Loads
Acid Mine Drainage Loads
Above Fall Line
NON-TIDAL
Point Source Loads
Urban Stormwater Runoff Loads
Atmospheric Deposition
"Loads
Shipping and Boating
Loads
Figure 2. The sources of chemical contaminant loads to the Bay, above the fall line and below the fall line,
reported in this inventory.
Chemicals Reported
Loadings are reported for chemicals on the
Chesapeake Bay Toxics of Concern List
(TOC) and the Chemicals of Potential
Concern List. These chemicals cause or
have the potential to cause adverse effects on
the Bay's living resources. Other chemicals
that are not on these lists, but having very
high loads, are also reported. The TOC list
represents inorganic contaminants such as
metals (copper, lead, mercury) and organic
contaminants such as polynuclear aromatic
hydrocarbons (PAHs) and polychlorinated
biphenyls (PCBs). Metals come from both
point and nonpoint sources from a variety of
activities. PAHs come from the combustion
of fossil fuels and from oil and grease used
in cars. PCBs were used as fire retardants
and can be found in older electric
transformers and other machinery. Although
PCBs are banned, they are still found in the
environment and we still report them where
found.
i-4
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Executive Summary
Controlling Toxic Inputs: Concentrations
Versus Cumulative Loads
Historically, the regulatory focus for
controlling toxic inputs to waterbodies has
been on controlling concentrations at the end
of a pipe, or point sources, with very little
focus on nonpoint sources. Discharges of
chemicals to the Bay and its rivers are
allowed if they fall below the levels thought
to cause impacts on the Bay's living
resources. Managing concentrations of
contaminants in this way may be appropriate
for those chemicals that do not linger in the
water or sediment, either because they break
down or they are in well-flushed systems. In
this case, living resources may not be
exposed to these chemicals for a sufficient
amount of time to cause an impact.
However, for persistent chemicals in poorly-
flushed systems (i.e., harbors), managing the
cumulative load of those chemicals may be
more appropriate. In this case, persistent
chemicals may accumulate in the water or
sediment in a poorly-flushed system and
result in ambient concentrations that pose a
greater threat to the living resources exposed
to them.
Nationally, we are starting to see a shift from
managing end-of-pipe concentrations to
controlling cumulative loads from both point
and nonpoint sources through state
implementation of the Clean Water Act's
Total Maximum Daily Loads program. This
approach complements and enhances
traditional approaches of controlling
chemical concentrations exiting pipes by
addressing the ambient concentration of
contaminants (resulting from all sources) to
which living resources may be exposed.
From the perspective of the Bay's living
resources, what matters is the concentration
of a chemical to which they are exposed,
what form it is in, and how long it persists.
Some of these chemicals persist and
accumulate in the environment, while some
degrade or are flushed out of the Bay and
tidal rivers. Some may interact with each
other to become more or less toxic. The
physical and chemical properties of the
living resource's habitat may impact the
toxicity of the chemicals as well. By
managing the loads, we can take into account
impacts that may result from cumulative
loads coming from many different sources,
synergistic effects of multiple contaminants
and other factors that may affect toxicity.
This approach recognizes that all sources
(not just the largest sources) may play a part
in causing an impact and, therefore, may
play a part in reducing or eliminating the
impact.
As the Bay Program and states evolve
toward a more loads-based system for toxics
management, inventories such as this one
will become more important in helping
managers to target their source reduction
efforts in impacted areas. Data collection
efforts will need to evolve to reflect this
evolution by improving measurements that
allow for easier and more certain loads
estimates.
-------
Executive Summary
III. WHAT IMPROVEMENTS HAVE
BEEN MADE SINCE THE 1994
INVENTORY?
Point Source Loads in this inventory are
reported for industries, federal facilities, and
municipalities discharging a flow of 0.5
million gallons per day or larger into the Bay
and are based on measured data from sources
such as the Permit Compliance System. In
the 1994 inventory, point source loads relied
more heavily on the national Toxics Release
Inventory (TRI). The TRI database is of
limited value in estimating point source
loads (or releases) to the surface waters of
the Bay and tidal rivers because data are
based on estimates rather than measured
values; the database represents only a small
fraction (approximately 5%) of all point
sources; and releases to surface waters
appear to be overestimated. Estimates of
point source loads have been improved by
including nearly twice as many facilities as
the 1994 inventory. Estimates for facilities
above and below the fall line are based on
more monitored data sources collected over a
consistent period of time for more chemicals.
Urban Runoff Loads are from chemical
contaminants on urban land (both impervious
and pervious surfaces) that are transported to
the Bay and its rivers by stormwater runoff.
These estimates are much improved because
they are based on recent stormwater
monitoring data collected by each
jurisdiction in the watershed in support of the
National Pollutant Discharge and
Elimination System stormwater permitting
program. Previous estimates were based on
nationwide data, mostly from the early
1980s. Estimates are reported from above
the fall line and below the fall line.
Atmospheric Deposition Loads are loads
from chemical contaminants in the air that
are deposited onto the Bay and its tidal
rivers. These estimates are updated and
expanded using recent field measurements
and improved theoretical understanding of
deposition processes. Volatilization of
organic contaminants from the surface
waters to the air is considered for the first
time in calculating a "net" atmospheric
loading to the Bay and tidal rivers. Initial
estimates of the contribution of urban areas
to atmospheric deposition loads to the Bay
and tidal rivers also are reported. Only loads
below the fall line are reported. The TRI
database for industrial air releases was not
included in this inventory, as it was in 1994,
since the improved and expanded
atmospheric loadings data (below the fall
line) are based on measured data and are a
much better representation of loads than the
TRI data estimates of releases.
Shipping and Boating Loads are chemical
contaminants entering the Bay and tidal
rivers from boating-related spills. These
estimates are improved because they are
based on additional data sources; recovery
data were used to calculate net spill
quantities; and spills were more accurately
located based on better geographic data.
Only loads to the Bay and tidal rivers, below
the fall line, are reported.
Acid Mine Drainage Loads are chemical
contaminants, typically metals, from active
and abandoned coal mines. These loads are
reported for the first time, based on a
comprehensive literature synthesis of
contaminant levels found in acid mine
drainage entering streams in the upper
portion of the watershed. These loads are
above the fall line, where the mines are
located.
Fall Line Loads represent the aggregate of
point and nonpoint sources above the fall
i-6
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Executive Summary
line that make it to the tidal waters. These
loads are much improved due to upgrades in
analytical methods and load estimation
techniques. Loads from the Susquehanna
and James rivers are updated and new loads
are reported for the Potomac, Patuxent,
Choptank, Nanticoke, Pamunkey, Mattaponi,
and Rappahannock rivers.
Pesticide Releases to the watershed were
based on much improved pesticide usage
data from a variety of national databases and
data from state surveys and pesticide experts
collected over a consistent period of time.
However, pesticide usage was not translated
into loads.
Relative Importance of Sources to the Bay
and its tidal rivers is reported in this
inventory for the first time to provide
managers, scientists, and the public with
information on the most important sources of
estimated chemical contaminant loads.
Loadings from sources with the most
widespread and available data were reported
from point sources, urban runoff, and
atmospheric deposition. Shoreline erosion
loads of several metals were estimated for
this "relative importance of sources" chapter,
but were not included as a separate chapter
because data are so sparse. Upstream
contaminant loads to the tidal waters from all
sources are represented by the fall line
loadings data.
Mass Balance of Chemical Contaminants is
a new section of the inventory which
provides (1) a gross check and balance on
whether or not loadings estimates are
consistent and realistic, (2) an idea of the fate
of contaminants in the Bay and its
tributaries, (3) a management tool for
predicting results from load reductions, and
(4) a consistent way to identify key data gaps
and uncertainties that need to be addressed
for management/scientific purposes.
IV. WHAT ARE THE LIMITATIONS
OF THE 1999 INVENTORY?
These loading and release data represent the
best data available to date. However, there
are still many uncertainties and limitations of
the data which are highlighted at the end of
each chapter. Where feasible, confidence
levels in the data have been quantified. It is
important to note that most of the data that
were used to calculate loads were not
collected with that purpose in mind. Many
problems are inherent in these types of
calculations including a general lack of
quality data, incomparability of chemical
measurements and forms from each source
category, and incomplete reporting of the
various sources as discussed in the individual
loading chapters. Although this inventory is
much improved over the 1994 inventory, it is
still a work in progress with some limitations
listed below.
The inventory is not comprehensive:
This updated inventory, although more
complete than the 1994 inventory, is not a
comprehensive accounting of all loads of all
chemical contaminants to the Bay and its
tidal rivers. Loads are reported for only a
subset of all chemicals released in the
watershed. Additionally, some sources of
chemical contaminant loads are not
quantified or completely accounted for as
described below.
*• Point source loads are only estimated
for major facilities (facilities with a flow
of 0.5 million gallons per day or greater)
and have not been estimated for the
approximately 3,700 minor facilities in
the watershed because data from the
Permit Compliance System are often
i-7
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Executive Summary
incomplete for these smaller facilities.
*• Atmospheric deposition loads are only
those deposited directly to the water.
The loads that are carried off the
watershed (i.e., the land) into the Bay
and tidal rivers by stormwater runoff are
not accounted for in the atmospheric
deposition loads category. However,
these loads from the upper portion of the
watershed, above the fall line, are
partially accounted for in the fall line
loads estimates for those chemicals that
were measured at the fall line. Loads
from the lower part of the watershed are
partially accounted for by the below fall
line urban runoff estimates.
> Agricultural loads (i.e., pesticides from
cropfields, metals from poultry
production), as in the 1994 inventory,
are not reported as a separate source
category in this inventory because very
little data on pesticide loads are
available and it is difficult to translate
pesticide usage data into loads.
However, loads from agricultural lands
upstream are accounted for in the fall
line loadings estimates for those
chemicals that were measured at the fall
line. Below the fall line, loadings for
select pesticides are accounted for in the
atmospheric deposition loadings data.
*• Groundwater loads are not reported as a
separate source category and are only
accounted for in the fall line loadings
data for those chemicals measured at the
fall line. There are no available data to
estimate groundwater loads below the
fall line.
> Natural background loads have not
been quantified as a separate source
category because data were not available
to determine the portion of loads
originating from natural processes such
as mechanical or chemical weathering of
rock, which results in metal loads. The
shoreline erosion loads estimates for
select metals in the "relative importance
of sources" chapter provides a partial
accounting of natural background loads.
Point source loads estimates are uncertain:
Point source loads are important, but
uncertainty in loading estimates is large in
some cases. Loads may not have been
adjusted to account for pollutants that are
present in a facility's intake water.
Additionally, reporting programs in which
data were collected were not set up with the
objective of calculating loads, but rather for
determining compliance with regulated
parameters in discharge permits. For certain
organic contaminants — all PCBs, pesticides,
and most PAHs — values were reported as
below the detection limits. With the data
available for these organic contaminants, the
load may be as low as zero or as high as the
detection limit multiplied by the flow. Using
zero for organic contaminants could grossly
underestimate the load, but using the high
value for organic contaminants could grossly
overestimate the load. This uncertainty is
not the case for the metals data, since most
metals are above the detection limit.
To get an idea of the magnitude of loads of
organic contaminants from point sources in
the Potomac river watershed, PCB
concentrations in wastewater treatment plant
effluent in the New York/New Jersey Harbor
estuary were used to estimate loads. These
PCB concentrations were measured at much
lower detection limits than used in this
inventory. Based on this analysis, if lower
detection limits were used to measure end-
of-pipe concentrations of organic
i-8
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Executive Summary
contaminants, the estimated point source
loads may be substantial (up to 60% of the
total PCB load entering the tidal Potomac
river) but still less than the high load in the
range described above.
The contribution of specific upstream
sources to tidal loads are unknown:
More information is needed regarding the
fate, transport, and attenuation processes of
chemical contaminants above the fall line, in
order to determine the important contributors
of upstream sources of chemical
contaminants to the Bay and its tidal rivers.
Updated loadings cannot be compared to the
1994 inventory to assess trends:
The 1999 inventory is an important step
forward in the Bay Program's efforts to
compile a comprehensive, high quality
inventory of point and nonpoint source loads
to the Bay. The Bay Program has made
significant improvements to the previous
1994 inventory by increasing the sources
quantified and improving analytical and
loadings estimate techniques. Since the
loadings estimates in this inventory include
many more sources and new and improved
analytical and loadings estimation
techniques, they cannot be compared to those
from the 1994 inventory to assess trends.
Also annual fluctuations in meteorology
affect our ability to compare fall line
loadings and nonpoint source loads from
year to year. Therefore, this inventory does
not report on loadings trends since the 1994
inventory.
i-9
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Executive Summary
V. MAJOR FINDINGS
Sources of contaminants to the Bay and its tidal rivers vary by chemical and by land use and
activities on the watershed. Through analysis of loadings data estimated using data collected
between 1990 and 1997, some clear patterns are observed:
*• Upstream sources, from either point or nonpoint sources to non-tidal waters above the
fall line, provide substantial loads of metals to the Bay and tidal rivers. Fall line loads
account for between 60% for mercury to 87% for arsenic of total loads to the Bay and its tidal
rivers.
> Point sources below the fall line account for a substantial load of metals, such as copper
and mercury, to the entire Bay and its tidal rivers. Point source loads of copper and
mercury account for 11% and 28% of total loads respectively.
2 6
2
Mercury
Total Input: 9,500 Ib/yr
I
AD FL UR SE PS Other
Sources
160
g 120
^H
X
-b 80/
5 20 /
10
Arsenic
Total Input: 140,000 Ib/yr
/
i
AD FL UR SE PS Other
Sources
Total loads of mercury and arsenic to the tidal waters of the Bay from atmospheric deposition (AD); fall line
(FL); urban runoff (UR); shoreline erosion (SE); and point sources (PS). Examples of "Other Sources" not
fully quantified may include loads from smaller point sources, agricultural runoff, atmospheric deposition,
groundwater, and natural sources.
i-10
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Executive Summary
600
500
X 400
o
o
^ 300
C- lOOx,
Copper
Total Input: 710,000 Ib/yr
v
Q.
Q.
O
U
50
AD FL UR SE PS Other
Sources
100
o
o
*H
X
5
3
'i
•o
C!
U
75 -
SO/
20
10
Cadmium
Total Input: 94,000 Ib/yr
AD FL
UR
SE
PS Other
Sources
Total loads of copper and cadmium to the tidal waters of the Bay from atmospheric deposition (AD); fall line
(FL); urban runoff (UR); shoreline erosion (SE); and point sources (PS). Examples of "Other Sources" not
fully quantified may include loads from smaller point sources, agricultural runoff, atmospheric deposition,
groundwater, and natural sources. For copper, the variability in the shoreline erosion estimate is smaller than
the symbol representing the average.
-------
Executive Summary
500
o 400
o
X 300
200
100
0
Lead
Total Input: 560,000 Ib/yr
\
AD
FL UR
SE
PS Other
Sources
o
o
SI
JUUU •
2500
2000
1500
1000
500
0 -
( >
, 5
AD FL UR
Zinc
Total Input: 3,300,000 Ib/yr
* ?
SE PS Other
Sources
Total loads of lead and zinc to the tidal waters of the Bay from atmospheric deposition (AD); fall line
(FL); urban runoff (UR); shoreline erosions (SE); and point sources (PS). Examples of "Other Sources"
not fully quantified may include loads from smaller point sources, agricultural runoff, atmospheric
deposition, groundwater, and natural sources. For lead, the variability in the shoreline erosion estimate is
smaller than the symbol representing the average, and for zinc, the variability in the point source
estimate is smaller than the symbol representing the average.
i-12
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Executive Summary
Point sources below the fall line are important loads to the different tidal rivers and can
account for up to approximately 10% of the total quantified load for some metals. Organic
contaminant loads are very uncertain at this time, but data suggest that point source loads of
PCBs can be substantial and should be the target of additional monitoring and analysis.
Urban runoff below the fall line is a substantial source of select organic contaminants
(PAHs) to the Bay and tidal rivers. Given that point source loads estimates are highly
uncertain (as indicated by the large uncertainty bar in the figures), urban stormwater runoff is
the most substantial known source of PAH loads to the Bay and tidal rivers. Urban runoff
loads of PAHs to individual rivers are also substantial as illustrated in the Patuxent River
figure.
13U
0*
0
o
X 100
£>
^ 50j
g 20/
1 15
.2, 10
9
N _
g 5
ffl .
Benzo[a]pyrene
Total Input: 64,000 Ib/yr ]
/
i
* *
i
'
?
AD FL UR SE PS Other
Sources
Total loads of the PAH benzo[a]pyrene to the tidal waters of the Bay from atmospheric deposition (AD); fall
line (FL); urban runoff (UR); shoreline erosion (SE); and point sources (PS). Examples of "Other Sources" not
fully quantified may include loads from smaller point sources, agricultural runoff, atmospheric deposition,
groundwater, and natural sources. The variability in the atmospheric deposition and fall line estimates is
smaller than the symbol representing the average.
i-13
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Executive Summary
§
o
1-1
X
f,
150
100
SO/
20 /.
10
Chrysene
Total Input: 64,000 Ib/yr
AD FL UR SE PS Other
Sources
** 200
X
J5* 100
w
I
Phenanthrene
Total Input: 130,000 Ib/yr
i
>:
AD FL UR SE
PS Other
Sources
Total loads of the PAHs chrysene and phenanthrene to the tidal waters of the Bay from atmospheric deposition
(AD); fall line (FL); urban runoff (UR); shoreline erosion (SE); and point sources (PS). Examples of "Other
Sources" not fully quantified may include loads from smaller point sources, agricultural runoff, atmospheric
deposition, groundwater, and natural sources. For chrysene, the variability in the atmospheric deposition and
fall line estimates is smaller than the symbol representing the average.
i-14
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Executive Summary
o
0
1-H
*
j
OJ
a
«
e.
iUU •
160
120
80
Pyrene
Total Input: 88,000 Ib/yr
<
/
20 ;/
10
0
. I
»
/
9
TtL •
AD FL UR SE PS Other
Sources
Total loads of pyrene to the tidal waters of the Bay from atmospheric deposition (AD); fall line (FL); urban
runoff (UR); shoreline erosion (SE); and point sources (PS). Examples of "Other Sources" not fully quantified
may include loads from smaller point sources, agricultural runoff, atmospheric deposition, groundwater, and
natural sources.
0.2
•o 0.1
N
a
CJ
« 0.0
Benzo [a] pyrene
Total Input: 320 Ib/yr
I
AD FL
UR
SE
PS Other
Sources
Total loads of benzo[a]pyrene to the tidal Patuxent River from atmospheric deposition (AD); fall line (FL);
urban runoff (UR); shoreline erosion (SE); and point sources (PS). Examples of "Other Sources" not fully
quantified may include loads from smaller point sources, agricultural runoff, atmospheric deposition,
groundwater, and natural sources. The variability in the atmospheric deposition and fall line estimates is
smaller than the symbol representing the average.
i-15
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Executive Summary
> Urban runoff below the fall line is a substantial source of metals to the Patuxent and
Anacostia Rivers as illustrated in the figures summarizing cadmium loads. Ranges were not
calculated for the Anacostia River loads due to a lack of data (and lack of uncertainty
reporting) from the different data sources.
0.4
S 0.3
X
*«
8, 0.2
I.,
0.0
Cadmium
T Total Input: 390 Ib/yr
I *
AD FL UR SE
PS Other
Sources
Total loads of cadmium to the tidal Patuxent River from atmospheric deposition (AD); fall line (FL); urban
runoff (UR); shoreline erosion (SE); and point sources (PS). Examples of "Other Sources" not fully quantified
may include loads from smaller point sources, agricultural runoff, atmospheric deposition, groundwater, and
natural sources.
0.30
g 0.25
T-l
* 0.20
-, 0.15
-2 0.10
TJ
r9? 0.05
0.00
Cadmium
Total Input: 340 Ib/yr
AD FL UR CSO PS Other
Sources
Total loads of cadmium to the tidal Anacostia River from atmospheric deposition (AD); fall line (FL); urban
runoff (UR); combined sewer overflow (CSO); and point sources (PS). Point source loadings were not
reported. Examples of "Other Sources" not fully quantified may include loads from smaller point sources,
agricultural runoff, atmospheric deposition, groundwater, and natural sources. Uncertainties were not
calculated due to a lack of data and reported ranges.
i-16
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Executive Summary
Point sources of organic contaminants (PAHs and PCBs) are highly uncertain because
of measurement methods currently used for permit compliance monitoring; therefore, loads
are largely unknown.
Loadings are dependent on land use characteristics on the watershed and not the size of
the watershed. For example, the Anacostia River watershed, a relatively small urban
watershed, produces 12 times the loads of the metal, lead, than any of the other major river
watersheds.
Trace metal total watershed yields for selected tributaries of the Bay.
Copper
Cadmium
Lead
Mercury
Susquehanna
4.05
0.61
2.44
0.052
Potomac
3.90
0.61
4.17
0.084
James
3.95
0.35
3.15
0.055
Patuxent
1.75
0.16
1.54
0.018
Anacostia
13.1
0.46
42.9
0.026
Units: Ib/km2-yr.
* Below the fall line, atmospheric deposition loads increase in areas of the Bay and tidal
rivers adjacent to urban areas.
*• Shipping and boating-related spills from 1990 -1996 resulted in 154 substances such as
jet fuel, gasoline, diesel oil, asphalt, and PCBs being loaded into Bay and tidal rivers in
4,736 recorded incidents. Most of the materials were spilled in the mainstem Bay or in
areas such as the West Chesapeake Basin and the tidal James River where large port,
industrial, or military installations are located.
» Acid mine drainage has impacted 1100 miles in 158 streams in the Chesapeake
watershed according to the 1996 state 303(d) reports. The causes cited for water quality
degradation from acid mine drainage are related to low pH and/or metals contamination (iron,
manganese, and aluminum).
»• Pesticide loads to the Bay and tidal rivers are largely unknown. 7,749,000 pounds of
pesticide active ingredient were applied to the four major crops in the watershed in
1996: corn, soybeans, small grains, and alfalfa. Some of these pesticides have been detected
in surface and groundwater. Studies are needed to quantify the fraction of pesticides that end
up in the Bay and its tidal rivers.
i-17
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Executive Summary
VI. WHAT ACTIONS CAN BE TAKEN TO IMPROVE THE INVENTORY?
This inventory represents the most comprehensive loadings analysis for chemical contaminants
compiled to date for the Bay and tidal rivers. This inventory can serve as a useful planning tool
for directing future management and monitoring activities in the watershed. Specific
recommendations for improving loads estimates for each source are detailed in the individual
chapters of this inventory. Some overall recommendations for improving the inventory are:
*• Continue to increase the number of accountable sources and improve analytical and loads
estimation techniques.
> Improve the point source loadings estimates, particularly for the organic contaminants, by
obtaining more information on wastewater characteristics and by considering better methods
for detecting organic contaminants.
> Determine the important upstream sources of chemical contaminants to the Bay and tidal
rivers by increasing our understanding of contaminant transport and attenuation processes.
> Quantify other potentially significant sources of loads from agricultural lands and
groundwater. Specific studies to quantify the fraction of pesticides used that are loaded into
the Bay and its tidal rivers would be particularly useful.
i-18
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Acknowledgments
Special recognition goes to the Toxics Subcommittee's Directed Toxics Assessment Workgroup
and the Toxics Subcommittee Fellows for their input into the development and review of this
report. This inventory can be found on the Chesapeake Bay Program web page at
http://www.chesapeakebay.net or contact the Bay Program Office at 1-800 YOUR BAY.
Directed Toxics Assessment Workgroup Members
Kelly Eisenman, Toxics Coordinator
USEPA Chesapeake Bay Program
Joel Baker
University of Maryland
David Burdige
Old Dominion University
Jeffrey Cornwell
University of Maryland
Anita Key
DC Department of Health
Joe Macknis
USEPA Chesapeake Bay Program
Heather Daniel, Toxics Fellow
Chesapeake Research Consortium
Alan Messing
Old Dominion University
Cherie Miller
U.S. Geological Survey
Percy Pacheco
NOAA
Mark Richards
VA Dept. of Environmental Quality
Joseph Scudlark
University of Delaware
Carrie McDaniel, Toxics Fellow
Chesapeake Research Consortium
Mike Unger
VA Institute of Marine Sciences
Nathalie Valette-Silver
NOAA
David Velinsky
Academy of Natural Sciences
Allison Wiedeman
USEPA Chesapeake Bay Program
-------
Table of Contents
I. Executive Summary i-1
II. Acknowledgments ii-1
III. Table of Contents iii-1
List of Tables/Figures iii-4
IV. Description of Inventory Chapters iv-1
V. Loadings
Chapter 1
Point Source Loadings 1-1
Introduction 1-1
Temporal and Spatial Coverage 1-1
Chemicals Reported 1-5
Mapping of Point Source Facilities 1-5
Methodology 1-6
Uncertainty and Data Handling 1-8
Discussion 1-11
Correlation with 1994 TLRI 1-17
Recommendations 1-17
Chapter 2
Urban StormwaterLoadings 2-1
Introduction 2-1
Temporal and Spatial Coverage 2-1
Methodology 2-4
Uncertainty 2-6
Discussion and Comparison with 1994 Toxics Loading and Release Inventory 2-8
Recommendations 2-19
Chapter 3
Atmospheric Deposition Loadings 3-1
Introduction 3-1
Temporal and Spatial Coverage 3-2
Methodology 3-3
Uncertainty 3-6
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Table of Contents
Loading Estimates 3-8
Comparison with 1994 Toxics Loading and Release Inventory 3-8
Recommendations 3-9
Chapter 4
Shipping and Boating Loadings 4-1
Introduction 4-1
Temporal and Spatial Coverage 4-1
Methodology 4-1
Uncertainty 4-3
Discussion 4-4
Correlation with 1994 Toxics Loading and Release Inventory 4-5
Recommendations 4-5
Chapter 5
Acid Mine Drainage Loadings 5-1
Introduction 5-1
Temporal and Spatial Coverage 5-2
Methodology 5-2
Uncertainty 5-3
Discussion 5-3
Recommendations 5-9
VL The Fall Line
Chapter 6
Fall Line Loadings 6-1
Introduction 6-1
Temporal and Spatial Coverage 6-1
Methodology 6-6
Uncertainty 6-7
Discussion 6-8
Correlation with 1994 Toxics Loading and Release Inventory 6-10
Recommendations 6-10
VII. Releases
Chapter 7
Pesticide Use « 7-1
Introduction 7-1
Pesticide Usage Analysis 7-1
iii-2
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Table of Contents
Discussion of Data Gathering Techniques and Limitations 7-4
Pesticides in Surface and Ground Water 7-5
Recommendations 7-6
VIII. Relative Importance of Point and Non-point Sources to the Bay 8-1
Chapter 8
Introduction 8-1
Methodology 8-1
Inputs to the Tidal Chesapeake Bay 8-8
Inputs to the Tributaries of Chesapeake Bay 8-10
Discussion and Recommendations 8-14
IX. Mass Balance of Chemical Contaminants within Chesapeake Bay 9-1
Chapter 9
Introduction 9-1
Model Framework 9-2
Results and Discussion 9-4
Summary and Conclusions 9-14
X. References r-1
XI. Appendices A-l
iii-3
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Table of Contents
LIST OF TABLES/FIGURES
Chapter 1 - Point Source Loadings
Table 1.1. Toxicpoint source data sources 1-3
Table 1.2. Total Chesapeake Bay watershed load estimates by chemical 1-20
Table 1.3. Point source load estimates and percentage by major basin 1-22
Table 1.4. Point source load estimates by state 1-70
Figure 1.1. Chesapeake Bay basinmajor point source discharges 1-4
Figure 1.2. Relative low Chesapeake Bay basin point source loads by chemical category 1-13
Figure 1.3. Relative high Chesapeake Bay basin point source loads by chemical category 1-14
Figure 1.4. Loading estimates of metals by major basin 1-15
Figure 1.5. Loading estimates of PCB'sby major basin 1-15
Figure 1.6. Loading estimates of pesticides by major basin 1-15
Figure 1.7. Loading estimates ofPAH'sby major basin 1-15
Figure 1.8. Loading estimates of inorganics by major basin 1-16
Figure 1.9. Loading estimates of organics by major basin 1-16
Chapter 2 - Urban Stormwater Loadings
Table2.1. Potential Sources for Common Pollutants in Urban Stormwater 2-3
Table 2.2. Average Annual Precipitation Runoff from All Urban Lands in the Chesapeake Bay
Basin, 1984-1991 2-10
Table 2.3. Jurisdictions in the Chesapeake Bay Basin with available NPDES Stormwater data and
land uses sampled 2-11
Table 2.4. Chemicals Above Detection Level (ADL) in Chesapeake Bay Basin NPDES
Stormwater Sampling Data 2-12
Table 2.5. Descriptive Statistics and EMCs for selected chemicals detected in Chesapeake Bay
Basin NPDES Stormwater Sampling Data (ug/L) 2-13
Table 2.6. Comparison of EMC values with those from a previous estimate contaminant loads in
the Chesapeake Bay Basin (ug/L) 2-15
Table 2.7a. Average annual chemical contaminant loads in Stormwater runoff. 2-16
Table 2.7b. Average annual chemical contaminant loads in Stormwater runoff. 2-17
Table 2.8. Comparison of Baywide loads with those from a previous estimate of contaminant loads
in the Chesapeake Bay Basin 2-18
Figure 2.1. Chesapeake Bay Watershed Model segments 2-5
Chapter 3 - Atmospheric Deposition Loadings
Table3.1. Data sources for 1998 atmospheric deposition estimates 3-11
Table 3.2. Surface water segments below the fall lines used to calculate atmospheric deposition
loads 3-12
Table 3.3. Average annual atmospheric deposition fluxes to the Chesapeake Bay 3-13
Table 3.4a. Wet deposition loads to the Chesapeake Bay below the fall lines 3-15
in-4
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Table of Contents
Table 3.4b. Dry aerosol deposition loads to the Chesapeake Bay below the fall lines 3-16
Table 3.4c. Net gas exchange deposition loads to the Chesapeake Bay below the fall lines 3-17
Table 3 Ad. Total atmospheric deposition loads to the Chesapeake Bay below the fall lines 3-18
Table 3.5. Influence of urban areas on atmospheric deposition loadings to the Bay 3-19
Table3.6. Comparison of 1994 and 1998 TLRI atmospheric deposition loadings 3-20
Chapter 4 - Shipping and Boating Loadings
Table 4.1. Chemicals selected for the 1996 Chesapeake Bay Toxics of Concern List, the Chemicals
of Potential Concern List, and Delisted Chemicals 4-7
Table 4.2a. Spills of toxic materials containing chemicals on the Chesapeake Bay Toxics of
Concern and Chemicals of Potential Concern Lists [Ranked alphabetically] 4-8
Table 4.2b. Spills of toxic materials containing chemicals on the Chesapeake Bay Toxics of
Concern and Chemicals of Potential Concern Lists [Ranked by total loading] 4-9
Table 4.2c. Spills of toxic materials containing chemicals on the Chesapeake Bay Toxics of
Concern and Chemicals of Potential Concern Lists [Ranked alphabetically] 4-10
Table 4.2d. Spills of toxic materials containing chemicals on the Chesapeake Bay Toxics of
Concern and Chemicals of Potential Concern Lists [Ranked by total loading] 4-11
Table 4.3a. Spills of toxic materials from ships and land facilities to the Chesapeake Bay and its
tidal tributaries [Ranked by total loading] 4-12
Table 4.3b. Spills of toxic materials from ships and land facilities to the Chesapeake Bay and its
tidal tributaries [Ranked alphabetically] 4-18
Chapter 5 - Acid Mine Drainage Loadings
Table 5.1. Streams in the Chesapeake drainage affected by acid mine drainage and miles
impacted 5-4
Table 5.2. Summary of cumulative acid mine drainage chemical constituent loads in the
Susquehanna River tributaries draining the anthracite coal fields in Pennsylvania 5-10
Table 5.3. Summary of cumulative acid mine drainage chemical constituent loads in the West
Branch Susquehanna River tributaries draining the bituminous coal fields in
Pennsylvania 5-12
Table 5.4. Summary of cumulative acid mine drainage chemical constituent loads in the North
Branch Potomac River tributaries draining the bituminous coal fields in Maryland and
West Virginia 5-14
Chapter 6 - Fall Line Loadings
Table 6.1. Summary of Chesapeake Bay Fall Line Toxics Monitoring Program sampling between
1992 and 1997 6-2
Table 6.2. List of organonitrogen and organophosphorus pesticides monitored at the fall line by
year 6-3
Table 6.3. List of polycyclic aromatic hydrocarbons monitored at the fall line by year 6-3
Table6.4. List of organochlorine contaminants monitored at the fall line by year 6-4
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Table of Contents
Table6.5. List of trace metals monitored at the fall line by year 6-5
Table 6.6. Annual loads of organonitrogen and organophosphorus pesticides above the fall line of
the Susquehanna River 6-12
Table 6.7. Annual loads of organonitrogen and organophosphorus pesticides above the fall line of
the Potomac River 6-12
Table 6.8. Annual loads of organonitrogen and organophosphorus pesticides above the fall line of
the James River 6-13
Table 6.9. Annual loads of polycyclic aromatic hydrocarbons above the fall line of the
Susquehanna River 6-13
Table 6.10. Annual loads of polycyclic aromatic hydrocarbons above the fall line of the Potomac
River 6-14
Table 6.11. Annual loads of polycyclic aromatic hydrocarbons above the fall line of the James
River 6-14
Table 6.12 Annual loads of organochlorines above the fall line of the Susquehanna River 6-15
Table 6.13. Annual loads of organochlorines above the fall line of the Potomac River 6-16
Table 6.14. Annual loads of organochlorines above the fall line of the James River 6-17
Table 6.15. Annual loads of trace metals above the fall line of the Susquehanna River 6-18
Table 6.16. Annual loads of trace metals above the fall line of the Potomac River 6-18
Table 6.17. Annual loads of trace metals above the fall line of the James River 6-19
Table 6.18. Instantaneous loads of organonitrogen and organophosphorus pesticides above the fall
lines or head of tide of the nine major tributaries of Chesapeake Bay from March 26
through May 5,1994 6-19
Table 6.19. Instantaneous loads of organonitrogen and organophosphorus pesticides above the fall
lines or head of tide of the nine major tributaries of Chesapeake Bay from November
8 through November 18,1994 6-20
Table 6.20. Instantaneous loads of polycyclic aromatic hydrocarbons above the fall lines or head of
tide of the nine major tributaries of Chesapeake Bay from March 26 through May 5,
1994 6-20
Table 6.21. Instantaneous loads of polycyclic aromatic hydrocarbons above the fall lines or head of
tide of the nine major tributaries of Chesapeake Bay from November 8 through
November 18,1994 6-21
Table 6.22. Instantaneous loads of organochlorines above the fall lines or head of tide of the nine
major tributaries of Chesapeake Bay from March 26 through May 5,1994 6-21
Table 6.23. Instantaneous loads of organochlorines above the fall lines or head of tide of the nine
major tributaries of Chesapeake Bay from November 8 through November 18,
1994 6-22
Table 6.24. Instantaneous loads of total trace metals above the fall lines or head of tide of the nine
major tributaries of Chesapeake Bay fromMarch.26 through May 5,1994 6-22
Table 6.25. Instantaneous loads of total trace metals above the fall lines or head of tide of the nine
major tributaries of Chesapeake Bay from November 8 through November 18,
1994 6-23
• •• x
m-6
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Table of Contents
Figure 6.1. Map of Chesapeake Bay region showing nine watersheds monitored in 1994 synoptic
study 6-7
Chapter 7 - Pesticide Use
Table 7.1. Pesticide usage on the four major crops grown within the Chesapeake Bay Watershed
by chemical name, 1996 7-7
Table 7.2. Pesticide usage on corn in the Chesapeake Bay Watershed by chemical name, 1996. ..7-8
Table 7.3. Pesticide usage on alfalfa in the Chesapeake Bay Watershed by chemical name,
1996 7-9
Table 7.4. Pesticide usage on soybeans in the Chesapeake Bay Watershed by chemical name,
1996 7-10
Table 7.5. Pesticide usage on small grains in the Chesapeake Bay Watershed by chemical name,
1996 7-11
Table 7.6. High use pesticides in surface water sampled in the Chesapeake Bay Watershed (1993-
1996) 7-12
Table 7.7. High use pesticides in ground water sampled in the Chesapeake Bay Watershed (1993-
1996) 7-13
Figure 7.1. Surface water pesticide detection sites 7-14
Figure 7.2. Ground water pesticide detection sites 7-15
Figure 7.3. Multiple acres treated with pesticides within the watershed 7-16
Figure 7.4. Pounds of pesticide Active Ingredients applied to agricultural lands within the
watershed 7-16
Chapter 8 - Relative Importance of Point and Non-point Sources to the Bay
Table 8.1. Trace metal total watershed yields for selected tributaries of the Bay 8-13
Figure 8.1. Conceptual framework used in developing contaminant budgets for the tidal Chesapeake
Bay 8-17
Figure 8.2. Total loads ofPCBs to the tidal Potomac River 8-18
Figure 8.3. Total estimated loads ofPCBs to the tidal Potomac River based on TPC 8-18
Figure 8.4. Total loads of cadmium to the tidal water of Chesapeake Bay 8-19
Figure 8.5. Total loads of copper to the tidal water of Chesapeake Bay 8-19
Figure 8.6. Total loads of lead to the tidal water of Chesapeake Bay 8-20
Figure 8.7. Total loads of mercury to the tidal water of Chesapeake Bay 8-20
Figure 8.8. Total loads of zinc to the tidal water of Chesapeake Bay 8-21
Figure 8.9. Total loads of arsenic to the tidal water of Chesapeake Bay 8-21
Figure 8. lO.Total loads of benzo[a]pyrene to the tidal water of Chesapeake Bay 8-22
Figure 8.11.Total loads of chrysene to the tidal water of Chesapeake Bay 8-22
Figure 8.12.Total loads ofphenanthrene to the tidal water of Chesapeake Bay 8-23
Figure 8.13.Total loads of pyrene to the tidal water of Chesapeake Bay 8-23
Figure 8.14.Total loads of cadmium to the tidal James River 8-24
Figure 8.15.Total loads of copper to the tidal James River 8-24
iii-7
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Table of Contents
Figure 8.16.Total loads of lead to the tidal James River 8-25
Figure 8. IT.Total loads ofbenzo[a]pyrene to the tidal James River 8-25
Figure 8.18.Total loads of phenanthrene to the tidal James River 8-26
Figure 8.19.Total loads of cadmium to the tidal Potomac River 8-26
Figure 8.20.Total loads of copper to the tidal Potomac River 8-27
Figure 8.21.Total loads of lead to the tidal Potomac River 8-27
Figure 8.22.Total loads ofbenzo[a]pyrene to the tidal Potomac River 8-28
Figure 8.23 .Total loads of phenanthrene to the tidal Potomac River 8-28
Figure 8.24.Total loads of cadmium to the tidal Patuxent River 8-29
Figure 8.25.Total loads of copper to the tidal Patuxent River 8-29
Figure 8.26.Total loads of lead to the tidalPatuxent River 8-30
Figure 8.27.Total loads ofbenzo[a]pyrene to the tidalPatuxentRiver 8-30
Figure 8.28.Total loads ofphenanthrene to the tidal Patuxent River 8-31
Figure 8.29.Total loads of cadmium to the tidal Anacostia River 8-31
Figure 8.30.Total loads of copper to the tidal Anacostia River 8-32
Figure 8.31. Total loadsof lead to the tidal Anacostia River 8-32
Figure 8.32.Total loads of zinc to the tidal Anacostia River 8-33
Chapter 9 - Mass Balance of Chemical Contaminants within Chesapeake Bay
Table 9.1. Loadings of total copper to Chesapeake Bay 9-10
Table9.2. Losses of total copper from the mainstem Chesapeake Bay 9-10
Table 9.3. Loadings of mercury to Chesapeake Bay 9-11
Table 9.4. Losses of mercury from the mainstem Chesapeake Bay 9-11
Table9.5. Loadings of total PCBs to Chesapeake Bay 9-12
Table 9.6. Losses of total PCBs from the mainstem Chesapeake Bay 9-12
Table 9.7. Loadings of phenanthrene to Chesapeake Bay 9-13
Table 9.8. Losses of phenanthrene from the mainstem Chesapeake Bay 9-13
Figure 9.1. Schematic of Chesapeake Bay Chemical Contaminant Mass Balance Model 9-2
Figure 9.2. Flows of chemical contaminants into and from model cells 9-3
iii-8
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DESCRIPTION OF INVENTORY CHAPTERS
The inventory is divided into the following six sections:
Executive Summary summarizes the purpose of this inventory, improvements since the
1994 inventory, limitations of loading and release estimates, and major findings, with an
emphasis on comparing the relative contributions of point and nonpoint sources of metals
and organic contaminants entering the Bay and its major tidal tributaries.
Loadings are estimates of the quantity of chemical contaminants that reach the Bay
waters. These loadings can enter the Bay above the fall line or below the fall line. The
fall line is the physiographic boundary between the Piedmont and the Atlantic Coastal
Plain provinces, representing the natural geographic break between the tidal and non-tidal
regions of the Bay watershed.
• Loads to the non-tidal portions of the Bay's and its rivers (above the fall line) are
reported from acid mine drainage.
• Loads to the tidal portion of the Bay and its rivers (below the fall line) are
reported from atmospheric deposition and shipping and boating.
• Both above the fall line (non-tidal) loadings and below the fall line (tidal)
loadings are reported for point sources and urban runoff.
Fall Line Loadings estimates represent the aggregate of chemical contaminant loads
from upstream point and nonpoint sources that make their way to the tidal portion of the
Bay and its rivers. These estimates are based on measurements taken at the fall line.
Releases are estimates of the quantity of chemical contaminants emitted to the Bay's
watershed that have the potential to reach the Bay. Only pesticide usage data are
summarized in this section. While not a direct measure of loads, the pesticide usage data
can provide inference about the quantity of pesticides released onto the watershed, a
fraction of which may end up in the groundwater or surface waters of the Bay.
Relative Importance of Point and Non-Point Sources of Chemical Contaminants to
Chesapeake Bay and its rivers is reported in this inventory for the first time to provide
managers, scientists, and the public with information on the most important sources of
chemical contaminant loads. Loadings from sources with the most widespread and
available data were reported from point sources, urban runoff, atmospheric deposition,
and shoreline erosion (where available). Upstream contaminant loads to the tidal waters
from all sources are represented by the fall line loadings data.
Mass Balance of Chemical Contaminants is a new section of the inventory which
provides (1) a gross check and balance on whether or not loadings estimates are
consistent and realistic, (2) an idea of the fate of contaminants in the Bay and its
tributaries, (3) a management tool for predicting results from load reductions, and (4) a
consistent way to identify key data gaps and uncertainties that need to be addressed for
management/scientific purposes.
iv-1
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CHAPTER 1 - Point Source Loadings
Allison Wiedeman Cory Dippel NingZhou
Chesapeake Bay Program Chesapeake Bay Program Chesapeake Bay Program
Environmental Protection Agency Chesapeake Research Consortium Virginia Tech
410 Severn Avenue, Suite 109 410 Severn Avenue, Suite 109 410 Severn Avenue, Suitel09
Annapolis, MD 21403 Annapolis, MD 21403 Annapolis, MD 21403
INTRODUCTION
The purpose of this chapter is to present data on chemical contaminants discharged to
surface waters by point sources located within the Chesapeake Bay watershed. Point sources are
end-of-pipe discharges from industrial, municipal, or federal facilities. The information
presented herein is an assimilation of data obtained from EPA's National Pollution Discharge
Elimination System (NPDES) Permit Compliance System (PCS) and other effluent reporting or
sampling programs performed by the Bay jurisdictions. Data was obtained in terms of chemical
effluent concentration and discharge flows, and analyses were performed by the Chesapeake Bay
Program Office to calculate total estimated discharged load. The loads are presented as pounds
of chemical discharged per year. Analyses were performed after consultation with the
Chesapeake Bay Program's Toxic Subcommittee's Directed Toxic Assessment (DTA)
Workgroup. The data sources, methodologies, and assumptions used to calculate discharged
loads as well as the total estimated loads are presented in detail in the following sections of this
chapter.
Three appendicies accompany this chapter of the Toxics Loading and Release Inventory
document. These appendicies include Appendix A: List of chemicals and default detection
limits, Appendix B: Loads of chemical categories by Standard Industrial Classification (SIC)
codes, and Appendix C: Inventory of Point Source Loads by Facility. Appendix C is published
separately from this document and is available from the Chesapeake Bay Program Office.
TEMPORAL AND SPATIAL COVERAGE
There are approximately 4000 industrial, municipal, and federal point source dischargers
within the Chesapeake Bay watershed. Of these, 316 are classified as currently operating
"major" dischargers in the PCS database, discharging greater than 0.5 million gallons per day
(MOD). This inventory includes 276 of these major point sources discharging to the Chesapeake
Bay watershed for which data was available to evaluate loadings. Figure 1.1 shows the location
of all 316 major point source dischargers in the Chesapeake Bay basin. However, only 228
facilities had data for the specified list of chemicals analyzed in this inventory (see "Chemicals
Reported" section).
1-1
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Point Source Loadings
The loadings in this section include data from Pennsylvania, Maryland, Virginia, and the
D.C. Blue Plains waste water treatment plant collected between 1992 -1996. This range was
chosen because it spans 5 years, the same as the (NPDES) monitoring program permit cycle.
Every facility will have had their permit reissued at some point during this time frame.
The data sources for each state are summarized in Table 1.1. The complete inventory of
point source loadings by facility, including all chemicals for which loads were calculated can be
found in Appendix C.
Data from the Toxic Release Inventory (TRI) database are not included in this chapter.
The data summarized in this report are estimated using actual measured concentrations, flows,
and loadings whereas TRI data are estimated releases. Combining these very different data
sources would introduce a large margin of error.
1-2
-------
Point Source Loadings
Table 1.1. Toxic Point Source data sources.
DATA
CATEGORY
1.
NPDES
FORM2C
& FORM A
2.
NPDES
DMR
3.
VATMP
DATA
SOURCES
Hard copy*
NPDES
Application
forms (2c &
A)1
A.
NPDES
DMR Reports
from PCS2
B.
NPDES
DMR Reports
in hard copy
TMP (Toxics
Management
Program) 3
VIRGINIA
Collected when
available and
within the time
frame (1992-
1996)
COLLECTED
Data from 5
regions were
collected.
MARYLAND
Collected for 63
facilities which had a
current (1992-1996)
application form in their
file.
COLLECTED
NOT APPLICABLE
DISTRICT OF
COLUMBIA
(BLUE PLAINS)
NONE COLLECTED,
Monthly operating reports
collected instead
COLLECTED
Monthly operating reports
for Blue Plains WWTP were
collected from the District
of Columbia Dept. of
Health.
NOT APPLICABLE
PENN-
SYLVANIA
NONE
COLLECTED,
data is entered
into PCS
COLLECTED
NOT
APPLICABLE
' Where data is listed as a hardcopy source, the CBPO loaded the data into an electronic database.
1 Application form descriptions
Form 2c is required for any facility which discharges to waters of the U.S. This form includes information such as outfall descriptions, flows,
latitude/longitude, and sources of pollutants within the facility. In addition, the form contains a list of 165 pollutants (the 126 priority
pollutants as designated by US EPA, and standard water chemistry parameters). Which of those chemicals facilities are required to report is
dependent on the type of facility. For every pollutant the facility has reason to believe is present in their discharge in concentrations of 10 ppb
or greater, they must submit quantitative data. Form A is used for municipal WWTP. This form contains much of the same information as
Form 2c with only 55 chemicals listed for which the facility may describe their wastewater.
Limitations: The main limitation of this data source is that for many parameters, only one sampling event occurred to obtain the data. Data are
not originally in electronic format.
2 Permit Compliance System (PCS) data
Discharge Monitoring Reports (DMR's) from the NPDES program are entered for the major dischargers and sometimes minor dischargers into
this national database. This database contains data for all the states. PCS is the principal source of toxics data which was supplemented, where
appropriate, by various data sources as described in the data source table.
Limitations: Database is lacking consistent temporal coverage, spatial data is inconsistently present, all fields in the database are text, missing
data and errors are not uncommon, units are often not reported, or are inconsistently reported (ie., some chemicals are reported in both mg/1 and
ug/1), detection limits are not always present for a non-detect chemical, and data on minor facilities (discharging less than 0.5 MGD) may be
lacking or insufficient.
3 Virginia TMP data
The VA TMP is part of the NPDES program in Virginia. TMP data is generated from quarterly or semiannual sampling efforts depending upon
the facility. The TMP is a separate program from NPDES which monitors compliance of 405 facilities in VA with biomonitoring and chemical
analyses. The TMP monitors the same chemicals as those found on Form 2c. The TMP computerized database does not hold the chemical data
which the facilities must report on their effluent. It only holds information on facility permit compliance. The chemical data remains in hard
copy and is stored in the NPDES permit files at the regional offices in Virginia. This is the data which the CBPO has obtained for this loadings
analysis.
Limitations: For some parameters only one sampling event occurred to obtain the data. Data are not originally in electronic format.
1-3
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Point Source Loadings
CHESAPEAKE BAY BASIN MAJOR POINT SOURCE DISCHARGERS
IN
A
50 0 50 Miles
Figure 1.1. Chesapeake Bay Basin major point source dischargers.
1-4
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Point Source Loadings
CHEMICALS REPORTED
Between all the above data sources, there are over 800 chemicals reported, the majority of
which are reported through the VA IMP. To calculate loadings for 800 chemicals would have
been too immense of an undertaking in the time allowed for this report. Therefore, it was
decided to include only a subset of these chemicals in this report. The 231 chemicals chosen
include all of the potentially toxic chemical parameters in PCS, the priority pollutants, the Toxics
of Concern list chemicals, and the Chemicals of Potential Concern. Appendix C includes a
complete list of loadings for all facilities and all 231 chemicals. Appendix A lists the 231
parameters for which data were available to calculate loadings. Due to the large amount of data,
Tables 1.2 -1.4 provide a summary for only a subset of the 231 parameters. This chemical
subset of 79 parameters includes the 1990 list of Toxics of Concern (as well as the draft revised
1996 list of the Toxics of Concern), the 1990 list of Chemicals of Potential Concern, and
individual PCB's and PAH's. Because some facilities did not report any of the chemical subset,
only 228 facilities were used for the loading analysis.
This report also summarizes data in terms of the chemical categories of metals, PCBs,
pesticides, PAHs, organics, and inorganics. Metals are substances or mixtures such as lead,
copper, or mercury. PCBs (Polychlorinated biphenyls), although banned, are used as fire
retardants and can be found in electric transformers and other machinery. Pesticides are
compounds, either organic or inorganic which are used to control the growth of plants
(herbicides), insects (insecticides), or fungus (fungicides). PAHs (Polycyclic Aromatic
Hydrocarbons) are compounds such as naphthalene, or phenanthrene, which come from the
combustion of fossil fuels and from oil and grease. Organic chemicals include compounds
containing hydrocarbons and their derivatives (hydrocarbon combined with other elements,
principally nitrogen and oxygen). Organics discussed in this report include all organic chemicals
except PCBs, PAHs and pesticides. Inorganic chemicals include compounds other than organic
chemicals and metals.
MAPPING OF POINT SOURCE FACILITIES
In coordination with the calculation of loads for facilities, an effort was made to
accurately map all of the major point sources. Location information (latitude/longitude, address,
county, zip codes) from PCS was compiled for all major facilities. The information was used to
map each facility in Arc View in the following ways: If a facility had an accurate
latitude/longitude it was used first. If a correct lat/long was unattainable, the facility was mapped
using address matching. If neither an accurate lat/long or address was available, the facility was
mapped using zip code centroid matching. Figure 1.1 shows the accurate location of all major
point source dischargers in the Chesapeake Bay watershed.
1-5
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Point Source Loadings
METHODOLOGY
There are over 4000 point source dischargers in the Chesapeake Bay Watershed. The
majority of these facilities are minor facilities, and depending upon the state, data for them are
generally not reported in PCS unless they are minors deemed "significant". Calculating loads for
all the watershed facilities was too large of an undertaking for this report. In order to maintain
consistency between all the jurisdictions, only major facilities are included in the loadings
analysis.
Monthly flows were matched with monthly concentration values and the load calculated
according to the formula below. Monthly loads for each individual year were averaged to obtain
an annual load.
The following formula was used to estimate the annual average load of chemical
contaminants for all states:
Annual Load (Ibs/yr) = Concentration x Flow x 8.344 x # of days in the year for which data was
available
where:
Load = pounds /year (Ibs/yr)
Concentration = milligrams/liter (mg/L)
Flow = million gallons/day (MOD)
8.344 = a factor for converting MOD and mg/L into Ibs/day
Outfalls within each facility were identified, when possible, as effluent, influent, internal,
etc. All outfalls identified as effluent were summed, by year, to obtain an annual load for the
facility. The annual loads for each year for each facility were averaged to obtain the load
estimates as reported in this chapter.
In cases where a concentration was present but the corresponding flow was not and vise
versa, a zero was assumed and put in place of the missing value. Due to this method, some of the
loading estimates may be recorded as a zero. A zero may also indicate the chemical was non-
detect, or that the concentration value was not recorded in the PCS database.
For each year at any given facility, the average concentration for any given chemical was
used in the loads calculation regardless of how many data points were present for each year. If
there were no data points for a given year, the average did not include that year. For example, if
a copper load was only obtainable for a given facility for the years of 1992, 1994, 1995, and
1996, the average would be the sum of the loads for those years, divided by the four years for
which there was data available.
1-6
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Point Source Loadings
District of Columbia
Blue Plains WWTP was the only facility in DC for which data was obtainable. There are
3 additional active major facilities in D.C. for which data was unavailable in PCS.
Data collected from PCS was supplemented by data from Monthly Operation Reports
where there were missing parameters or monthly values from PCS. Using monthly average
concentration and flow values, annual average concentrations and flows were calculated. For
some pollutants only a single data value was available to estimate the average concentration.
Maryland
Data collected from PCS was supplemented by data from permit applications where there
were missing parameters or monthly values from PCS. If DMR (PCS) data existed for a
particular chemical, these data alone were used to calculate loads. If only permit application data
existed for a particular chemical, these data along with PCS flows were used to calculate loads.
For some pollutants at some facilities, however, only a single data value was available to
estimate the average concentration. Using monthly average concentration and monthly average
flow values, annual average concentrations and flows were calculated.
Virginia
Data collected from PCS was supplemented by data from permit applications and data
from the VA TMP program where there were missing parameters or monthly values from PCS.
If DMR (PCS) data existed for a particular chemical, these data alone were used to calculate
loads. If only TMP data exist for a particular chemical, these data along with PCS flows were
used to calculate loads. If only permit application data exist for a particular chemical, these data
along with PCS flows were used to calculate loads. For some pollutants at some facilities,
however, only a single data value was available to estimate the average concentration. Using
monthly average concentration and monthly average flow values, annual average concentrations
and flows were calculated.
Pennsylvania
Data collected from PCS was the only data source used in the calculation of annual loads.
Annual loads were calculated using monthly average concentration and monthly average flow
data from the PCS database. For some pollutants at some facilities, however, only a single data
value was available to estimate the average concentration.
1-7
-------
Point Source Loadings
UNCERTAINTY AND DATA HANDLING
Coverage
The non-electronic data for this chapter was collected over a period of 14 months
beginning in July of 1996 through September of 1997. Data collected in the beginning may not
have the same temporal coverage as the data collected towards the end of the data collection
process. For instance, data collected in July of 1996 will not have a complete year of data for
1996. PCS data was retrieved from 1992 through September of 1996.
The point source loading estimates to the Chesapeake Bay are underestimated due to the
inclusion of only major dischargers within the signatory states/Districts (Maryland, Virginia,
Pennsylvania, and the District of Columbia). The loadings of minor dischargers collectively may
be significant. It was decided to maintain consistency between all states in choosing only major
dischargers, and as time allows in future efforts, to assimilate data for minor facilities as well.
Non-detects of various chemicals
The definition of the Detection Limit (DL) is the lowest value to which a compound can
be reliably measured as being present. A Quantitation Limit (QL) is the level at which the
quantity or concentration of a pollutant can be reliably determined. Detection Limits and
Quantitation Limits for any given chemical vary depending upon the analytical method and/or
the laboratory conducting the analysis. It is often uncertain as to whether a detection limit, or a
quantitation limit was reported. Approximately 80% of the data collected for this chapter was
non-detect. The method in which non-detect (ND) concentrations are treated can result in very
different loading estimates. Non-detect concentrations can be set equal to zero, to the detection
limit, or some value in between (such as half the detection limit), with each option resulting in a
different loading estimate.
For these loading estimates, the loadings are presented in a range, setting all ND to both
zero and the DL. In cases where a chemical was reported as ND, but was missing a DL, a default
detection limit value was used. Default values were obtained from EPA's Environmental
Monitoring Methods Index (EMMI). The EMMI database contains an inventory of information
on environmentally significant analyses monitored by the US EPA and methods for their
analyses. The detection limit with the most appropriate method was chosen for each chemical
missing a detection limit. The list of EMMI default detection limits can be found in Appendix B,
along with the complete chemical list.
All tables in this chapter present the loading estimates by a range. The low estimate of
loadings represents the average of both non-detects (set to zero) and detected values. The high
estimate of loadings represents the average of non-detects (set to the detection limit) and detected
1-8
-------
Point Source Loadings
values. It is important to note that for certain chemicals (all PCB's, pesticides, and most PAH's),
virtually all values were non-detect, therefore, the detection limits are driving the high range of
the loads.
The estimated load may vary significantly depending upon whether the non-detects used
to calculate the loadings are set to zero or the detection limit. As an example, Figure 1.2
represents the relative loadings of point source chemical categories with the non-detects of point
sources set equal to zero. With this treatment of the non-detects, metals are the predominant
chemical load with PCBs, PAHs and pesticides virtually zero. Figure 1.3 represents the relative
loadings of all chemical categories with the non-detects set equal to the detection limit. Using
this treatment of non-detects, the relative loads of PCBs and pesticides dominate all other
chemical categories.
The chapter entitled "Relative Importance of Point and Non-Point Sources of Chemical
Contaminants to the Chesapeake Bay" uses the average of the low and high loading estimates for
point sources. This chapter further discusses the uncertainty in dealing with data containing
many non-detects.
PCS Reporting
Data in PCS is entered into the database in many different ways. There are many fields
for which chemical and flow data can be entered: average load, maximum load, concentration
minimum, concentration average, and concentration maximum. Concentration average was the
preferred value, however, in cases where this was missing, concentration maximum or minimum
was assumed to represent the average. Records for which concentration maximum or minimum
were used were documented in the comments field in the database. In cases where average load
or maximum load existed, and a concentration value was lacking, the flow and the load were
used to back calculate to the concentration. The back calculated concentrations were then used
in the loading calculations as were all other concentrations. Records for which a back calculated
concentration was generated were documented in the comments field in the database.
Data was also inconsistently reported between each jurisdiction. Each state has different
methods and requisites of entering data into PCS. These differences proved challenging when
the data for all states was compiled into a database. Consistency between all states had to be
restored before the data could be used to produce loadings.
Metals Reporting in a Variety of Forms
Several metals were reported in a variety of forms (such as copper appearing as total
copper, dissolved copper and total recoverable copper). For presentation and summary purposes,
wherever multiple forms of a particular chemical were reported, they were consolidated into one
1-9
-------
Point Source Loadings
parameter to produce Table 1.2. A hierarchy was implemented when consolidating such
chemical parameter which was to use the highest value whenever more than one form per facility
was reported.
Nitrogen Reporting
A similar situation exists regarding reporting of nitrogen and nitrogen species as for
metals discussed above. Nitrogen and nitrogen species are reported in various ways in the point
source database including ammonia plus unionized ammonia, ammonia nitrogen, nitrate
nitrogen, nitrate dissolved nitrogen, and nitrite plus nitrate. The inventory has combined these
data where appropriate in an effort to determine one representative load of a certain species. For
example, ammonia plus unionized ammonia and nitrogen ammonia total are combined to present
one load for ammonia nitrogen. In cases where a facility supplied data for both parameters, the
highest value only was used. Nitrogen nitrate dissolved and nitrogen nitrate total are combined
into nitrate nitrogen. Nitrite plus nitrate is listed as nitrite and nitrate nitrogen.
Outfalls
Outfalls are often not identified clearly in PCS. It was difficult to distinguish effluent,
influent, stormwater, and internal outfalls within the PCS database. Best efforts were made to
verify effluent outfalls with each state before including them in the loadings calculations,
however, some outfalls may have been double counted or missed.
Influent concentrations/Cooling -water discharges
Influent concentration values are often present for larger facilities such as power plants,
which use stream water for cooling purposes. Due to the complexity of the data, influent data
were not used unless specifically available to calculate the "net effluent" chemical
concentrations. Loads for those facilities may be overestimated due to the fact that influent
loadings were not taken into account.
Stormwater Outfalls
There are many facilities which have stormwater related outfalls. The discharge of these
outfalls is dependent upon rainfall, hence they do not discharge 365 days/year. Every attempt
was made to accurately identify and discount these outfalls, however, some may have missed. In
these cases, the loadings may be overestimated.
Unit inconsistencies
Units are not consistently reported in PCS. In addition, units for any given parameter
1-10
-------
Point Source Loadings
may be inconsistently and inaccurately reported in the PCS database. For instance, flow values
may have been reported in MOD, gallons per day, or thousand gallons per day, depending upon
the facility, outfall, and/or who entered the data into PCS. It was often difficult to ascertain the
correct units in questionable cases. Questionable flows and concentrations were sent to each
state and the District of Columbia for review and correction.
Data Review
The Chesapeake Bay Program requested review of data for 25 facilities where questions
arose in the database. Responses from 22 facilities were received which allowed corrections to
be made in the inventory regarding flow quantities, unit errors or typos, and concentrations.
Off-Line Facilities
Some facilities in the inventory stopped discharging during the years of 1992-1996. Only
the years of actual discharge were used for load calculations for facilities which ceased
discharging during the period of data collection.
DISCUSSION
Table 1.2 presents the total Chesapeake Bay basin point source load estimates for a subset
of the 79 chemical parameters analyzed for the purposes of this chapter. Note that only 51
chemicals are included in Table 1.2. This is because, as explained earlier in this report, where
related chemicals were reported in a variety of parameters, they were consolidated to one
parameter for summary purposes in Table 1.2.
The top 18 chemicals with the highest loads are presented below in descending order.
These are the chemicals whose low load estimates are greater than 1000 Ibs/yr.
1-11
-------
Point Source Loadings
Top 18 Chemicals with the highest loads
CHEMICAL
AMMONIA NITROGEN
NITRATE NITROGEN
NITRITE + NITRATE NITROGEN
IRON
ALUMINUM
ZINC
MANGANESE
PETROLEUM HYDROCARBONS
COPPER
NICKEL
CHROMIUM
LEAD
CADMIUM
NAPHTHALENE
ARSENIC
CHLORPYRIFOS
MERCURY
2,4-DINITROPHENOL
Loads* (Ibs/year)
212,027,519.36
17,150,864.30
5,706,187.43
1,932,958.60
662,631.32
563,786.40
531,045.18
367,803.65
114,224.75
42,435.87
20,972.61
19,221.61
9,997.50
8,543.91
3,165.52
2,878.05
1,390.99
1,254.00
This list includes chemicals with low load estimates higher than 1000 Ibs/year.
* Based on low estimates.
Tables 1.3a-p present the point source load estimates and percent total by major basin.
Tables 1.3 and 1.4 include all 79 chemical parameters in their unconsolidated forms.
Table 1.4 presents point source load estimates by individual states. Note that for the 80
facilities in Pennsylvania, data are unavailable for many parameters. This is due to the sources of
data (see Table 1.1), which for Pennsylvania, is much less voluminous than for the other
jurisdictions. Thus, it's not necessarily true that loads are less in Pennsylvania, but that less data
is available.
Appendix B presents the loadings for chemical categories by industry type or standard
industrial code (SIC code) for 227 out the 228 facilities for which loads were calculated for the
79 chemical parameters subset. There is one facility for which the SIC code was unavailable.
Out of the 227 facilities, the majority (134) are classified as sewerage, and 20 provide electrical
services. The chemical categories summarized in Appendix B are Inorganics, Metals, Organics,
PAHs, PCBs, and Pesticides. Based on the low load estimates, the loads of pesticides are only
1-12
-------
Point Source Loadings
coming from sewerage. PCBs were only recorded for a General Medical/Surgical Hospital
facility. The highest loads of PAHs are from sewerage, plastic materials/synthesized resins, and
paper mills. The highest loads of organics are from electrical services, sewerage, and
ammunition. Industrial classes of sewerage, inorganic pigments, and medical chemicals
represent the highest loads of metals, and classes of nitrogen fertilizers, sewerage and paper mills
represent the highest loads of inorganics. Based on the high load estimates, the highest loads of
pesticides, PCBs, PAHs, and organics are coming from electrical services, plastic materials, and
synthesized resins. The highest loads of metals are coming from the same industrial class for
metals' low load estimates, which are sewerage, inorganic pigments, and medical chemicals.
The same situation applied to inorganics, its high load and low load estimates have the same
source for highest loading, which are nitrogen fertilizers, sewerage and paper mills.
Figures 1.2 and 1.3 show the relative total low and high Chesapeake Bay Basin point
source loads by chemical category. Note that the inorganic category is not included in these
figures. This is because approximately 98% of the point source load is from inorganics,
primarily nitrogen compounds. And as mentioned previously the amount of pesticides and
organics are driven by their detection limits, as seen in Figure 1.3 as compared to Figure 1.2.
RELATIVE LOW LOADS BY CHEMICAL CATEGORIES
PAHs PCBs
0% A r o%
ORGANICS \ / PESTICIDES
9% ^\ \ / ^~ 0%
METALS
91%
Figure 1.2. Relative Low Chesapeake Bay Basin point source loads by chemical category.
1-13
-------
Point Source Loadings
RELATIVE HIGH LOADS BY CHEMICAL CATEGORIES
PESTICIDES
31%
METALS
13%
ORGAMCS
12%
Figure 1.3. Relative High Chesapeake Bay Basin point source loads by chemical category.
Figures 1.4-1.9 show the low and high loading estimates of each individual chemical
category by the major basins (Note that Figure 1.8, loading estimates for Inorganics, is primarily
driven by the nitrogen compounds). Data from Table 1.2, using consolidated methods and
nitrogen species parameters, were used to produce these graphs. Graphs not showing a low
estimate indicate that the majority of the values were non-detect. As shown in Figures 1.5 -1.7,
the high loadings for PCB's, pesticides, and PAH's are driven primarily by the detection limit.
The low estimates for these chemical categories are mostly zero, indicating that nearly all the
concentrations were non-detect. Graphs which show a large low estimate and a small high
estimate indicate that most of the concentrations were detected. The highest loadings of metals
are in the Potomac, and are due primarily to iron, aluminum, manganese, zinc, and copper.
Highest loadings of Inorganics are in the James which is primarily due to nitrogen species.
1-14
-------
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Point Source Loadings
CORRELATION WITH 1994 TOXICS LOADING AND RELEASE INVENTORY
The results in this chapter cannot be directly compared to the results in the Point Source
chapter of the 1994 TLRI. The time period of data collected for the last report varied depending
upon state. Facilities included hi the 1994 TLRI comprised about one third of the majors.
Additionally, the sources of data are more comprehensive in this analysis than in the previous
TLRI. For these reasons, the loadings in this new chapter may appear greater when compared to
the last report.
This version of the Point Source chapter of the TLRI provides more comprehensive and
up-to-date loading estimates when compared to the 1994 report. This inventory includes nearly
twice as many facilities, additional and different data sources collected over a consistent time
period, and reports loadings on more chemicals. Careful consideration needs to be taken with
regards to the limitations, assumptions, and caveats of the data presented in this chapter when
comparing any of the results from this inventory with the results of the 1994 inventory.
RECOMMENDATIONS
> Further efforts should be made to include additional D.C. facilities, especially majors.
Insufficient data exists for the 3 remaining D.C. majors: Washington Aquaduct-Delecarlia
Plant, Pepco-Potomac Electric Company, and Potomac Electric Power Company.
*• EPA's PCS system should be improved and be made useful for the purpose of calculating
loadings for point source dischargers.
*• Special training and discussion seminars should be held for all personnel from the Bay
jurisdictions who are responsible for PCS entry. A standard approach for entering data
should be firmly established.
+ Incorporate a new application requirement that a pre-existing facility must report average
annual loadings for all pollutants identified in their application and also for those listed
on their previous permit. This submission should be maintained in an appropriate
database.
* Incorporate a standard permit requirement that facilities submit an annual summary of
total loads during that year using a combination of actual DMR data and estimates based
on their previous permit application data. Maintain these annual loadings in an
appropriate database.
*• The following inaccuracies and inconsistencies within PCS need to be amended:
• Units for all parameters need to be consistently and accurately reported in the PCS
1-17
-------
Point Source Loadings
database.
• Duplicate parameter codes in PCS need to be eliminated. The use of CAS
numbers as a unique chemical identifier should be implemented.
• Records of missing data without an explanation code should either be filled in
with data, or explained with a code in the database.
• Data for metals should be properly recorded as total, total recoverable, or
dissolved in PCS.
• Numeric data should be stored in fields with numeric formatting. Any qualifying
text should be placed in a separate field from numeric data.
»• A consistent criteria for including priority minor dischargers in future inventory updates
should be developed.
> States should clearly identify outfalls for facilities with intake pipes, and/or non-contact
cooling water from the same water body. The net effluent load should be determined
using the influent loads.
»• To better estimate the loads of chemicals with non-detects, such as PCB's, further
anaylses must be conducted to assess typical pollutant concentrations in point source
discharges. The recent published report entitled the "Study of the Loading of PCB's from
Tributaries and Point Sources Discharging to the Tidal Delaware River," put out by the
Delaware River Basin Commission, contains data that may provide better estimates of
PCB loads for those facilities with non-detects.
> The mapping effort verified the location of all major dischargers in the Chesapeake Bay
watershed. This list of facilities, along with any related location information should be
updated in the PCS database.
> Involve dischargers in the review of the data for future loading inventories.
> A discharger outreach program should be established focusing on new uses of DMR data
as well as education on completing DMR's properly. In addition, the importance of
correct flow values and units should be emphasized.
*• A zero present in the loading estimates can have several meanings. It may indicate the
chemical was non-detect, or that flow was reported as zero for a given record, or that the
concentration was reported as zero for a given record, or that the concentration was not
recorded in the PCS database. A procedure for distinguishing between each of the above
cases should be established for future inventory and database updates.
> Any point source data not reported in PCS should be submitted to the Chesapeake Bay
1-18
-------
Point Source Loadings
Program in accordance to the data submirtal requirements of the Information
Management System.
Data for point sources within the Chesapeake Bay Watershed in non-signatory states
(West Virginia, Delaware, and New York) should be included in future inventory
updates.
Additional analyses of intake cooling waters should be performed to determine net
discharge loads where not done previously.
Loads for the approximate 3700 minors should be investigated.
Indirect discharges to the POTW's should be investigated.
Consider including other chemicals than the list of 79 that were included in this chapter's
analysis.
1-19
-------
Point Source Loadings
Table 1.2. Total Chesapeake Bay Watershed Load Estimates by Chemical.
CHEMICAL
2,4,6-TRICHLOROPHENOL
2,4-DICHLOROPHENOL
2,4-DIMETHYLPHENOL
2,4-DINITROPHENOL
2-METHYL-4-CHLOROPHENOL
2-METHYLNAPTHTHALENE
ACENAPHTHENE
ALDRIN
ALUMINUM
AMMONIA NITROGEN
ARSENIC
BENZO[A]ANTHRACENE
BENZO[A]PYRENE
BENZO[GHI]PERYLENE
CADMIUM
CHLORDANE
CHLORPYRIFOS
CHROMIUM
CHRYSENE
COPPER
DIBENZO(A,H)ANTHRACENE
DIELDRIN
DIOXIN
ENDOSULFAN - ALPHA
ENDOSULFAN - BETA
ENDRIN ALDEHYDE
FLUORANTHENE
FLUORENE
INDENO(1 ,2,3-CD)PYRENE
IRON
LEAD
MANGANESE
MERCURY
NAPHTHALENE
NICKEL
NITRATE NITROGEN
NITRITE + NITRATE NITROGEN
PCB 1221
PCB 1232
PCB 1242
PCB 1254
PCB-1016
PCB-1248
TOTAL CHESAPEAKE BAY WATERSHED
LOAD ESTIMATE (Ibs/year)
LOW
231.87
32.24
221.71
1,254.00
0.00
0.00
1.92
540.41
662,631.32
212,027,519.36
3,165.52
54.92
54.73
3.84
9,997.50
0.00
2,878.05
20,972.61
185.62
114,224.75
3.84
0.10
0.07
0.00
0.00
0.00
55.88
42.86
3.84
1,932,958.60
19,221.61
531,045.18
1,390.99
8,543.91
42,435.87
17,150,864.30
5,706,187.43
0.00
0.00
0.00
0.00
0.00
0.00
HIGH
200,451.21
223,189.26
209,598.20
2,375,251.21
316,221.58
928.84
74,103.75
92,405.67
672,864.16
212,115,969.45
12,061.04
626,162.00
115,160.68
167,453.58
14,220.73
392,854.86
3,024.96
126,599.92
115,212.50
122,642.80
121,761.66
178,967.89
4,203.26
2,274,682.66
2,803,653.33
2,410,241.49
103,693.64
103,566.19
165,240.85
1,933,405.83
61,741.28
532,168.84
7,103.98
170,764.04
77,609.57
17,168,223.99
5,718,090.97
1,173,074.17
1,904,299.62
1,904,268.49
1,393,319.56
1,904,225.58
1,904,030.00
1-20
-------
Point Source Loadings
CHEMICAL
PCB-1260
PENTACHLOROBIPHENYL
PETROLEUM HYDROCARBONS
PHENANTHRENE
POLYCHLORINATED BIPHENYLS (PCBS)
PYRENE
TOXAPHENE
ZINC
LOW
0.15
0.00
367,803.65
76.94
0.00
84.51
0.00
563,786.40
HIGH
1,904,119.68
97.73
395,822.06
216,302.01
15,481.95
162,085.78
2,008,422.57
568,580.05
1-21
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