Nitrogen Emission/Deposition Ratios for Air Pollution Sources That
Contribute to the Nitrogen Loading of Tampa Bay
Environmental Protection Commission of Hillsborough County
Pollution Recovery Fund Agreement Number 06-02A
Mid-Term Progress Report
September 21, 2008
Prepared by Noreen D. Poor, Principal Investigator
1. Project Abstract
Local agencies, institutions, universities, corporations, and governments that are
involved in bay monitoring and management, e.g., as stakeholders in the Tampa Bay
Estuary Program or as members of the Tampa Bay Regional Planning Council, have
estimated that to prevent further impairment of bay waters, nitrogen flowing into Tampa
Bay must be reduced by 17 tons per year (TBNEP, 1996). Assessing the reductions or
gains in nitrogen deposition for changes in power plant configurations or for levels of
vehicular traffic, e.g., are difficult to assess without atmospheric transport modeling.
Conversion factors for major sources and source categories in Hillsborough County
that relate tons of nitrogen emitted to tons of nitrogen deposited to Tampa Bay will be
developed from atmospheric deposition modeling with the CALMET/CALPUFF
modeling system. This will not only aid bay managers in assessing atmospheric
nitrogen emission reductions made in recent years, but will reveal which sources/source
categories, if controlled, would influence most the bay water quality.
2. Emissions Inventory
In the third six months of the project, the CALPUFF model was run with the USEPA
2002 emissions inventory prepared for air pollutants SO2, NOx, and NH3 as described in
the previous progress report, with two exceptions: Hillsborough County off-road NOx
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emissions were reduced from 14,454 tons/year to 1,900 tons/year, consistent with a local
estimate of ship traffic through Port of Tampa in 2002; and Pinellas County non-point SO2
emissions were reduced by 24,974 tons/year to omit the combustion emission anomaly.
3. CALPUFF Model File Management
The “rule of thumb” applied to solving problems that occurred in running the CALPUFF
model was that at the end of the project the files created for the project could be easily
transferred to and run by interested parties, e.g., without the need to recompile model or
to deal with “bugs” in the model. Attempts were made to run all of the sources (point,
area, and hourly emissions from power plants) for one year of meteorological data in one
file. This approach was not successful because at some point during a modeling run the
number of puffs tracked by the model exceeded the default limit and the run terminated.
To solve this problem, the input file was then split into three files: power plant hourly
emissions, point source emissions, and area source emissions. The point source
emissions included industrial and municipal stationary sources and smaller power plants
plus ammonia emissions for all power plants. Area source emissions included on-road,
off-road, and non-point source emissions. Initial runs were made using a small number of
discrete receptors to represent monitoring sites in Hillsborough and Pinellas Counties and
also with a gridded network of 1200 receptors across the Tampa Bay watershed.
Concentrations of SO2 and NOx predicted by the CALPUFF model at these receptors
were compared with measurements made at area monitors.
The earliest model simulations revealed that the line source representations of on-road
emissions resulted in unusual spatial gradients, for example, high pollutant concentrations
at the ends of the line rather than along the length of the line.
The line source
representation of on-road emissions was abandoned, and on-road emissions were added
to the volume source representation of county-wide emissions. Recall from the second
progress report that for each county in the CALPUFF modeling domain, the on-road, offroad, and non-point emissions were summed and input as a volume source centered at
the county seat with an effective emission height of zero (0.0) m, an initial lateral
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dispersion (σy) of 40 km and an initial vertical dispersion (σy) of 100 m. County-level
emissions were input as time invariant.
4. Deposition Parameters
The CALPUFF model dry deposition parameters were reviewed and updated, where
appropriate, for a standard temperature of 25 o C (298 K) and a standard pressure of 1
atm.
For nitrogen oxides (NOx=NO+NO2), dry deposition parameters for NO2 were
selected rather, e.g., than a weighted average of NO and NO2, an approach which was
consistent with the CALPUFF default NOx molecular weight of 46—the molecular
weight of NO2. Although NOx is conserved, the fraction of NOx that is NO2 changes
rapidly as a pollutant is released from the tailpipe of a car (Kenty et al., 2007) and the
2002 ambient ratio observed at a monitoring site in urban Tampa was 80% (v/v).
Gas diffusivities reported by Massman (1998) for SO2, NO2, NH3, and from Durham
and Stockberger (1985) for HNO3 were used (Table 1). Henry’s Law coefficients were
obtained from Seinfeld and Pandis (1998) and converted to a dimensionless form (v/v)
as shown in Equation 1, where
is the dimensionless Henry’s Law coefficient (Table
1), H is the Henry’s Law coefficient (M/atm), R is the gas constant (0.08205
atm⋅L/mol⋅K), and T is temperature (298 K).
Equation 1:
= (H⋅R⋅T)-1
The enhanced gas solubility coefficient α* was calculated from the ratio of H to H*,
where H* is the effective Henry’s Law coefficient for reactive gases, e.g., SO2, HNO3,
and NH3 absorbing into seawater (pH 7.9). Equilibrium constants for aqueous phase
reactions for these gases were taken from Seinfeld and Pandis (1998).
3
Reactivity for NH3 (ANH3) was estimated by first calculating a cuticle resistance (RcuticleNH3) as
given by Sutton et al. (1998) (Equation 2), where RH is the relative humidity, and
next estimating the relative reactivity according to Equation 3 (Scire et al., 2000). The
average relative humidity measured at Tampa International Airport in 2002 was 76%
(NCDC, 2008). CALPUFF default values for SO2 reactivity (ASO2) and cuticle resistance
(Rcuticle-SO2) were 8 and 30 s/cm, respectively. CALPUFF default reactivities for SO2,
NO2, and HNO3 were kept (Table 1).
Equation 2: Rcuticle-NH3 = 2⋅exp[(100-RH)/12]
Equation 3: ANH3 = ASO2⋅ Rcuticle-SO2/Rcuticle-NH3
Mesophyllic resistances (Rm) were calculated according to Equation 4 (Wesely, 1989),
where f0 is defined as the normalized activity. Effective Henry’s Law coefficients were
determined at pH 6.5 (e.g., near neutral). Values for f0 were zero for SO2, HNO3, and
NH3, and 0.1 for NO2 (Wesely, 1989). The CALPUFF default mesophyllic resistance for
NO2 is 5.
Equation 4: Rm = (H*/3000+100* f0)-1
Particle diameter controls particle dry deposition rates. Atmospheric particles typically
have a log-normal distribution that can be described by a geometric mean diameter and
a geometric standard deviation. The CALPUFF default distributions are based on the
MESOPUFF II chemistry, where SO2 and NO2 undergo atmospheric reactions with NH3
to form fine particle SO4 and NO3. In a coastal atmospheric, HNO3 reacts with coarse
particles of suspended sea salt to form NaNO3 instead of NH4NO3 and thus the NO3
distribution has a coarse particle mode (Table 2) (Dasgupta et al., 2007; Poor et al.,
2006).
4
The MESOPUFF II chemistry does not include a pathway for coarse particle nitrate
formation, however, to the extent that the model predicts NH4NO3 formation, its
deposition velocity will be calculated as that for NaNO3.
Preliminary equilibrium modeling suggests that in a warm, humid, coastal environment
such as Tampa, for conditions under which CALPUFF will predict NH4NO3 formation—
another words, when NH3 is in excess of the amount needed to fully neutralize
atmospheric H2SO4—the excess NH3 remains in the gas-phase. Thus, the CALPUFFmodeled fraction of NOx that becomes NH4NO3 is expected to be small.
CALPUFF limits the values and formats that can be entered for each of the deposition
parameters. For SO2 and HNO3, deposition rates were calculated from CALPUFF
simulations with large values for the enhanced gas solubility coefficient α*, e.g. 106, and
again with a value of 1,000, with no change observed in the numerical results.
Table 1.
CALPUFF Model Dry Deposition Parameters for Gases
a
b
Pollutant
SO2
NOx/NO2
HNO3
NH3
Diffusivity,
cm2/s
0.128
0.159
0.118
0.232
Input into CALPUFF as 1000
Input into CALPUFF as 0.001
α*
6.45E+06a
1.00E+00
1.22E+09a
2.24E+01
Reactivity
8
8
18
16
Mesophyllic
Resistance,
s/cm
0b
0b
0b
0b
Henry'
s Law
3.33E-02
4.09E+00
1.95E-07
6.60E-04
Table 2.
CALPUFF Model Dry Deposition Parameters for Aerosols
Pollutant
SO4
NO3
Geometric Mean Diameter, µm
0.48
3.50
Geometric Standard
Deviation, µm/µm
2.00
1.90
5
The CALPUFF default values for rainfall scavenging of HNO3, NO3, and NH3 were not
changed based on the results of recent research by Calderón et al. (2007, 2008).
5. Receptor Grid
With a gridded network of 1200 receptors (2-km grid scale), the power plant, area, and
point sources input files took about 1 day, 1 week, and 2 weeks, respectively, to run. The
longer runs of 1-2 weeks were on occasion prematurely terminated due to power
interruptions, for example, from a local lightning strike. A replacement gridded network
with 198 receptors was prepared to provide complete coverage of the Tampa Bay
watershed but with more distance between each receptor (Figure 1). This shortened the
run times to about 0.5 days, 1 day, and 2 days for the power plant, area, and point source
emissions files, respectively.
6
Figure 1. CALPUFF receptor grid across the Tampa Bay watershed used to estimate
nitrogen deposition to Tampa Bay. The scale for the terrain map of central Florida has
units of meters.
6. Observed versus Modeled Concentrations and Atmospheric Deposition Rates
With the above changes to the CALMET model input files, comparisons between
predicted and measured concentrations of SO2 and NOx improved, especially for longerterm averages such as an annual average. Emissions of SO2 are predominantly from
coal- and oil-fired power plants for which hourly emission data were available; moreover,
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13 local monitoring sites reported hourly observations for SO2 for all or part of 2002.
Figure 2 shows the average annual SO2 concentration gradients from combined
CALPUFF modeling of all sources (e.g., power plant, point, and area sources) along with
the average annual SO2 concentration measured at local monitoring sites. The
disagreement between modeled and measured concentrations tends to be the greatest
where such a steep concentration gradient exists and is a likely result of the underlying
differences in modeled versus actual meteorology coupled with limitations in the model’s
ability to simulate atmospheric turbulence.
Figure 2. Modeled and measured average annual SO2 concentrations in the Tampa Bay
watershed. Colored contour lines are CALPUFF-modeled and posted numbers are
measured SO2 concentrations. Concentration units are µg/m3.
8
Figure 3 shows modeled and measured average annual NOx concentrations for the
Tampa Bay watershed. Roughly 50% of the NOx emissions are from power plants for
which hourly emission data were available. In Hillsborough and Pinellas Counties fewer
monitoring sites reported hourly NOx concentrations as compared with sites reporting
SO2 concentrations. As was seen for SO2, steep concentration gradients exist near power
plants and other major sources, and the modeled NOx concentrations are in reasonable
agreement with observations seen in Hillsborough County, but are lower than
observations reported at a monitoring site in Pinellas County.
Figure 3. Modeled and measured average annual NOx concentrations in the Tampa Bay
watershed. Colored contour lines are CALPUFF-modeled and posted numbers are
measured NOx concentrations. Concentration units are µg/m3.
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A preliminary estimate of the 2002 average ambient air concentrations and atmospheric
nitrogen deposition rates are summarized in Tables 3 and 4. Also shown is an estimate of
the fraction of the concentrations and nitrogen deposition rates that comes from
Hillsborough County emission sources.
Table 3.
Summary of ambient air pollutant concentrations in the Tampa Bay watershed. Units are
µg/m3.
a
Urban
Rurala
CALPUFFb
a
SO2
11
3.0
9.1
SO4
3.5
2.5
0.65
NOx
25
17
12
HNO3
1.3
0.62
1.2
NO3
1.7
1.5
0.46
NH3
1.8
1.6
1.2
NH4
0.72
0.56
0.32
Poor et al., 2006. Data averaged from June 2002 to April 2003 for all but NO3, which was averaged for May
2002.
b
Averaged for 2002.
c
Calculated from modeled SO4 and NO3 concentrations.
The CALPUFF modeling simulations do not produce as much sulfur and nitrogen as
has been locally measured (Table 3). Long-distant transport of particle sulfur and
nitrogen, e.g., SO4, NO3, and NH4 to the Tampa Bay watershed is expected and could
explain the reason why modeled under-predict measured concentrations. Another
explanation is that choices made for CALPUFF modeling parameters cause the underprediction. To evaluate the latter explanation, the CALPUFF model simulations will be
done with a change in the volume source dimensions, e.g., from a lateral dispersion of 40
km to 20 km and for a change in the nighttime NOx to HNO3 transformation rate. Kenty et
al. (2007) gave evidence that nighttime transformation of NO to NO2, which precedes the
oxidation of NOx to HNO3, occurred at rates similar to those seen during daytime when
the process is thought to driven by photolytic reactions.
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Table 4.
Summary of nitrogen deposition rates to land surface of the Tampa Bay watershed. Units
are kg-S/ha/year or kg-N/ha/year.
Inferred
Drya
Weta
CALPUFF
Dry
Wet
SO2-S
SO4-S
NOx-N
HNO3-N
NO3-N
NH3-N
NH4-N
2.04
--
0.52
6.70
5.09
--
0.53
--
0.89
2.72
4.55
--
0.03
2.33
3.75
5.56
0.01
0.46
1.99b
0.00
0.35
0.45
0.06
0.16
1.23
0.76
0.07
0.46
a
Poor et al., 2006. Estimated using CALPUFF deposition velocities but observed concentrations.
Calculated as NO2-N.
b
CALPUFF-modeled dry and wet nitrogen deposition rates are much less than was
estimated by Poor et al. (2006); however, Strayer et al. (2007) estimated that 25% or ~1
kg-N/ha/year of wet-deposited inorganic nitrogen to Tampa Bay was from sources near to
Tampa Bay.
7. Summary of CALPUFF-Modeled Nitrogen Deposition Estimates
In Table 5 are presented the estimates of direct and indirect wet and dry deposition to
Tampa Bay. For an estimate of direct nitrogen deposition, annual average wet and dry
deposition rates were calculated for receptors located over Tampa Bay, and these
average rates were summed, units on these rates were converted from µg/m2/s to kgN/ha/year, and the resulting flux was multiplied by the 101,000-ha surface area of Tampa
Bay. Likewise, for an estimate of indirect nitrogen deposition, annual average wet and dry
deposition rates were calculated for receptors located over the Tampa Bay watershed,
and these average rates were summed, units on these rates were converted from µg/m2/s
to kg-N/ha/year, and the resulting flux was multiplied by the 570,000-ha surface area of
the watershed and by a transfer coefficient of 18%, based on previous estimates by
Pollman and Poor (2003).
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Ammonium-N (NH4) deposition was computed by assuming 1.5 moles of NH4 for every
mole of depositing SO4 (i.e., that SO4 is partially neutralized by NH4) plus 1.0 moles of
NH4 for every mole of depositing NO3.
Table 5.
Summary of CALPUFF-Modeled Nitrogen Deposition Rates to Tampa Bay. Units are
metric tons-N/year.
Dry-Direct
Dry-Indirect
Wet-Direct
Wet-Indirect
Total
NOx-N
112
209
0
0
321
HNO3-N
27
37
37
47
147
NO3-N
5
7
15
17
44
NH3-N
NH4-N
84
129
58
80
352
6
7
43
49
105
Total N
234
390
153
192
969
From Table 5, direct nitrogen deposition is ~390 metric tons/year, or about 50% of the
estimate by Poor et al. (2001), and indirect nitrogen deposition is ~580 metric tons/year,
using the 2002 USEPA emissions inventory for central Florida.
8. Hillsborough County’s Contribution to Nitrogen Deposition to Tampa Bay
CALPUFF modeling results indicate that, in 2002, sources within Hillsborough County
contributed ~26% of the inorganic nitrogen deposited to Tampa Bay (Figure 4). Of this
fraction, 52% was from area sources (on-road, off-road, and non-point), 41% came from
two power plants, and 7% from point sources.
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Figure 4. Contribution of Hillsborough County to total nitrogen deposition to Tampa Bay
based on a 2002 emissions inventory. Units are metric tons-N/year.
7. Project Progress Report
Estimates of air pollutant concentrations and deposition rates reported in this progress
report are still preliminary, pending additional model testing and data checking.
The project website (http://health.usf.edu/publichealth/eoh/calpuff.htm) was updated with the May
2008 midterm progress report and associated files. Likewise, following EPCHC receipt
and review of this progress report, this report will be uploaded to the project website.
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Calderón, S. M., Poor, N. D., Campbell, S. W., 2007. Estimation of the particle and gas
scavenging contributions to wet deposition of organic nitrogen. Atmospheric
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Calderón, S. M., Poor, N. D., Campbell, S. W., Tate, P., Hartsell, B. 2008. Rainfall
scavenging coefficients for atmospheric nitric acid and nitrate in a subtropical coastal
environment. Atmospheric Environment, doi: 10:1016/j.atmosenv.2008.05.040.
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Dasgupta, P., Campbell, S., Al-Horr, R., Ullah, S., Li, J., Amalfitano, C., Poor, N., 2007.
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