3-1

3.0 CALPUFF FORMULATION AND IMPLEMENTATION 

The RHR relates visibility attenuation to extinction coefficient (bext) which is a measure of light 

scattering and absorption due to atmospheric constituents. Values for bext are estimated using an 

empirically derived equation which relates the extinction coefficient to relative humidity and the 

following components of particulate matter mass: (a) sulfates (SO4); (b) nitrates (NO3); (c) organic 

carbon (OC); (d) elemental carbon (EC); (f) particulate matter (IP) (“crustal material”); and (g) coarse 

mass (CM) (i.e., PM10 – PM2.5). The BART guidance requires the use of modeled concentrations of 

these components, together with a “humidity correction factor”, to estimate values for bext on all days 

within a three year period. These estimates, when compared with naturally occurring background 

extinction, are used to determine whether a source is causing or contributing to visibility impairment 

and also to measure the effectiveness of emissions controls on the source aimed at mitigating such 

effects. EPA notes that secondary particulate matter constitutes an important fraction of PM2.5 and that 

the modeling requirements for secondary and primary particulate matter differ in their need to consider 

atmospheric chemistry and in the degree of spatial resolution needed for the modeling (EPA, 2001, pg 

22). 

This chapter introduces the formulation of the CALPUFF modeling system. We summarize the 

model capabilities as described in the user’s manuals (Scire et al., 2000a,b) and discuss the capabilities 

and limitations of the model. Equipped with this information, states and source operators can identify 

those situations for which screening and/or source-specific applications of CALPUFF are appropriate. 

In most cases, we expect that application of the CALPUFF system will be sufficient to meet the 

BART Rule requirements. For that subset of conditions requiring advanced methods, Chapter 5 

provides details on full-science alternative models and available data bases for BART modeling. Such 

conditions might include a situation where the default modeling shows that a source just barely causes 

or contributes to visibility degradation or in negotiations over the final BART determination that 

weighs technical and economic feasibility against expected air quality benefits. In both situations, a 

more accurate estimate of a source’s impacts may be very important to source operators. 

3.1 Original Model Development 

 

The CALPUFF modeling system was originally developed as a component of a three-part 

modeling system sponsored by the California Air Resources Board (ARB) in the mid-1980s. The ARB 

sought to develop a new puff-based model, a new grid-based model and an improved meteorological 

processor that would support application of the two. CALGRID was the urban-scale photochemical 

grid model resulting from the project (Yamartino et al., 1992) comparable in science and capabilities to 

the Urban Airshed Model (UAM-IV) (Scheffe and Morris, 1993). The model formulation was aimed 

at overcoming the deficiencies in EPA’s steady-state Gaussian plume models that were routinely used 

in California for inert and linearly reactive materials (principally SO2) from elevated point sources. 

Thus, the CALGRID model was designed to treat the complexities of urban-scale photochemical 

processes while CALPUFF was formulated to treat the non-steady state transport, diffusion, linear 

reaction, and deposition of primary pollutants from point sources. CALPUFF was not designed to 

address photochemical oxidants or and secondary aerosol formation production processes in a 

scientifically rigorous manner. 

 

In recent years, CALPUFF and its meteorological pre-processor (CALMET) have been used in 

a range of regulatory modeling studies to address point source issues that include complexities posed 

by complex terrain, large source-receptor distances, parameterized chemical transformation and 
 

3-2

deposition, and issues related to Class I visibility impacts. These applications are more complex than 

the California ARB’s non-steady-state, linear chemistry formulation of the mid-1980s. 

The CALPUFF modeling system has been adopted by the EPA as a guideline model for sourcereceptor distances greater than 50 km, and for use on a case-by-case basis in complex flow situations 

for shorter distances. It was recommended for Class I impact assessments by the FLM Workgroup 

(FLAG, 2000) and the Interagency Workgroup on Air Quality Modeling (IWAQM) (EPA, 1998). As 

directed in the BART guidance, CALPUFF is the primary modeling system for screening and sourcespecific BART applications in the CENRAP region. Thus, examination of the model’s formulation 

provides the context for assessing the extent to which it suitable for simulating the various physical 

processes and gas-phase, aerosol, and aqueous-phase chemical processes that influences visibility. 

3.2 CALPUFF Model Formulation 

The CALPUFF user’s guide (Scire et al., 2000a) depicts the modeling system as shown in 

Figure 3-1. CALMET is a diagnostic/interpolation model that provides meteorological inputs to 

CALPUFF. These fields include hourly-averaged three-dimensional wind and temperature fields and 

two-dimensional fields of mixing heights and other meteorological parameters. CALMET uses routine 

surface and aloft meteorological observations and/or three-dimensional output from prognostic 

numerical models such as MM5 (Grell et al., 1995) or RUC (Benjamin et al., 2004) to construct the 

meteorological inputs. Other inputs to the air quality program include emissions information, receptor 

locations, ancillary geophysical information, and estimated concentrations of ambient pollutants that 

are entrained by the modeled puffs as each is carried downwind. Tables 3-1 and 3-2 summarize the 

key features of the CALMET/CALPUFF models as described in the user’s guides. 

Two post-processor routines are included to facilitate cumulative source impacts (POSTUTIL) 

and estimates of light extinction and visibility attenuation at Class I receptors of interest (CALPOST). 

In particular, CALPOST contains several options for computing change in extinction and deciviews for 

visibility assessments while the POSTUTIL postprocessor includes options for summing contributions 

of individual sources or groups of sources to assess cumulative impacts. POSTUTIL also contains an 

empirical nitric acid-nitrate chemical equilibrium module to estimate the cumulative effects of 

ammonia consumption by background sources once the simulation is completed. 

 3.2.1 Model Concept and Governing Equations 

The starting point for the CALPUFF development was the choice of the fundamental reference 

system of which there are two: Eulerian and Lagrangian. Consistent with the original ARB design 

criteria, the Lagrangian (moving puff) reference system was chosen for CALPUFF. In the Eulerian 

approach, the behavior of pollutants is described relative to a fixed coordinate system. The Lagrangian 

reference frame, in contrast, relates the behavior of pollutants relative to a coordinate system that 

moves with the average wind. These two approaches yield different mathematical relationships for 

pollutant concentrations that are equally valid. The choice of which approach to adopt depends upon 

the specific design goals of the modeling system. 

 The advantages and drawbacks of each approach are thoroughly discussed in the literature 

(Tesche, 1983; Seinfeld and Pandis, 1998; Jacobson, 1999; Russell and Dennis, 2000). One of the 

criticisms of early Eulerian grid models was their ‘over-dilution’ of point source emissions into the 

fixed grid cells; but for the past twenty years, this limitation has been overcome through with the 

development of sub-grid-scale, plume-in-grid algorithms (Seigneur, et al., 1981; Godowitch, 2004; 
 

3-3

Karamchandani et al., 2005; Emery and Yarwood, 2005) and the use of multi-scale nested grids 

(Russell and Dennis, 2000). While the Lagrangian approach is conceptually simple, flexible, and 

computationally inexpensive, the governing equations are not directly applicable to situations 

involving non-linear chemical reactions (Seinfeld and Pandis, (1998) and it is awkward to handle a 

large number of sources realistically. 

 3.2.2 Transport and Dispersion 

Adopting the Lagrangian concept, CALPUFF simulates the transport, dispersion, linear 

chemical transformation, and deposition of individual puffs carried downwind by the threedimensional fields generated by CALMET. The model’s implementation follows puffs from the near 

source region (a few tens of meters) to hundreds of kilometers downwind. Its puff-based formulation, 

in conjunction with three-dimensional hourly meteorological data, allow CALPUFF to simulate the 

effects of time- and space-varying meteorological conditions on pollutants emitted from a variety of 

source types. The major features and options of the CALPUFF model are summarized below: 

Building Downwash: The Huber-Snyder and Schulman-Scire downwash models are both incorporated 

into CALPUFF. An option is provided to use either model for all stacks, or make the choice on a stackby-stack and wind sector-by-wind sector basis. Both algorithms have been implemented in such a way 

as to allow the use of wind direction specific building dimensions. The PRIME building downwash 

model (Schulman et al., 2000) is also included in CALPUFF as an option. 

Dispersion Coefficients: Turbulent dispersion in CALPUFF is treated with the K-theory (fluxgradient) closure scheme, defined for a Lagrangian frame of reference. Several options are provided in 

CALPUFF for the computation of dispersion coefficients, including the use of turbulence 

measurements (σv and σw), the use of similarity theory to estimate σv and σw from modeled surface 

heat and momentum fluxes, or the use of Pasquill-Gifford (PG) or McElroy-Pooler (MP) dispersion 

coefficients, or dispersion equations based on the CTDM. Options are provided to apply an averaging 

time correction or surface roughness length adjustments to the PG coefficients. Recently, the EPA 

AERMOD dispersion parameters have been included in CALPUFF and are used regularly. 

Puff Sampling Functions: Puff sampling routines are included in CALPUFF to address computational 

difficulties encountered when applying a puff model to near-field releases. For near-field applications 

during rapidly-varying meteorological conditions, an elongated puff (slug) sampling function may be 

used. An integrated puff approach may be used during less demanding conditions. Both techniques 

reproduce continuous plume results under the appropriate steady state conditions. 

Wind Shear Effects: A key underpinning of the Lagrangian concept is that the modeled puffs retain 

their identity over the time- and spatial-scale associated with the effects the model is attempting to 

predict (i.e., visibility impairment at 200 km or beyond) While discrete puffs emitted from a source 

retain their physical integrity for a period of time, at some point the action of horizontal and vertical 

variations in wind speed and direction (i.e. ‘wind shear’) shred the puff into multiple elements. These 

new puff parcels, composed of remnants of the old puff, continue to be diffused and dispersed by the 

wind. The point where significant puff shredding occurs is difficult to define since it depends 

substantially upon the complexity of the meteorological conditions and the underlying terrain. But 

when shredding occurs, the Lagrangian concept in CALPUFF breaks down. By ignoring puff 

shredding (i.e., by keeping puffs intact), the model will systematically over-predict pollutant 

concentrations. 
 

3-4

To deal with this conceptual limitation, CALPUFF contains an optional puff splitting algorithm 

to simulate vertical wind shear effects across individual puffs. Differential rates of dispersion and 

transport among the “new” puffs generated from the original, well-mixed puff act to increase the 

effective rate of horizontal spread of the material as would be expected in the real atmosphere. Puffs 

may also be split in the horizontal when the puff size becomes large relative to the grid size to account 

for wind shear across the puffs. Detailed guidance on when and how the puff-splitting algorithm 

should be used and actual verification studies demonstrating that the technique operates as intended are 

not discussed in the model documentation or presented in the science literature.

Complex Terrain: Effects of complex terrain on puff transport are derived from the CALMET winds. 

In addition, puff-terrain interactions at gridded and discrete receptor locations are simulated using one 

of two algorithms that modify the puff-height (either that of ISCST3 or a general “plume path 

coefficient” adjustment), or an algorithm that simulates enhanced vertical dispersion derived from the 

weakly-stratified flow and dispersion module of the Complex Terrain Dispersion Model 

(CTDMPLUS) (Perry et al., 1989). The puff-height adjustment algorithms rely on the receptor 

elevation (relative to the elevation at the source) and the height of the puff above the surface. The 

enhanced dispersion adjustment relies on the slope of the gridded terrain in the direction of transport 

during the time step. 

Subgrid Scale Complex Terrain (CTSG): An optional module, CTSG treats terrain features that are not 

resolved by the gridded terrain field, and is based on the CTDMPLUS (Perry et al., 1989). Plume 

impingement on subgrid-scale hills is evaluated at the CTSG subgroup of receptors using a dividing 

streamline height (Hd) to determine which pollutant material is deflected around the sides of a hill 

(below Hd) and which material is advected over the hill (above Hd). The local flow (near the feature) 

used to define Hd is taken from the gridded CALMET fields. As in CTDMPLUS, each feature is 

modeled in isolation with its own set of receptors. 

Overwater and Coastal Interaction Effects: The CALMET processor contains overwater and overland 

boundary layer parameterizations allowing certain of the effects of water bodies on plume transport, 

dispersion, and deposition to be estimated. In a sense, CALPUFF operates as a hybrid model, by 

utilizing gridded fields of meteorology and dispersion conditions as well as grid-based descriptions of 

underlying land use. This includes the abrupt changes that occur at the coastline of a major body of 

water. 

Dry Deposition: A resistance model is used for the computation of dry deposition rates of gases and 

particulate matter as a function of geophysical parameters, meteorological conditions, and pollutant 

species. For particles, source-specific mass distributions may be provided for use in the resistance 

model. Of particular interest for BART analyses is the ability to separately model the deposition of fine 

particulate matter (< 2.5 μm diameter) from coarse particulate matter (2.5-10 μm diameter). 

Wet Deposition: An empirical scavenging coefficient approach is used to compute the depletion and 

wet deposition fluxes due to precipitation scavenging. The scavenging coefficients are specified as a 

function of the pollutant and precipitation type (i.e., frozen vs. liquid precipitation). 

 

 3.2.3 Primary Particulates 

CALPUFF is designed to simulate PM10 or PM2.5 or other user defined size distributions of 

particles. The smaller the particles, the more they disperse like an inert gas. In most cases, the 

dispersion of inert PM2.5 particles will differ only slightly from that of an inert gas. A key primary 
 

3-5

PM2.5 emission from coal-fired electric generating units (EGUs) of relevance to visibility calculations 

is particulate sulfate. Although primary sulfate emissions account for only a small fraction of the total 

sulfur emissions from such sources, it is appropriate to include their effect if reasonable estimates of 

primary sulfate emissions from the source are available. Treating primary sulfate emissions is likely to 

be most important at short distances from the stack before significant SO2 to secondary sulfate 

conversion has taken place. 

 3.2.4 Gas-Phase Chemistry 

Chemical reactions in the gas-phase play an important role in secondary aerosol formation by 

generating radical concentrations (e.g., the hydroxyl radical). These radical species oxidize SO2 and 

NOx, providing the precursors to aqueous–phase chemistry (i.e., chemistry in liquid water droplets) 

that convert SO2 to sulfate (e.g., H2O2 and O3), and form condensable gases from some volatile organic 

compounds (VOCs) that can then condense into particulate secondary organic aerosols (SOA). The 

levels of NOx, VOC, and O3 concentrations along with the reactivity of the VOCs, sunlight, 

temperature, and water vapor are all key variables that influence the radical cycle and consequent 

sulfate and nitrate formation rates. 

CALPUFF neglects realistic gas-phase processes entirely. The chemistry in CALPUFF 

parameterizes chemical transformation effects using five species (SO2, SO4

=

, NOx, HNO3, and NO3

-

) 

via a set of user-specified, diurnally-varying transformation rates. The model estimates secondary fine 

particulate matter (sulfate and nitrate) from emissions of gas-phase SO2 and NOx. Rather than 

simulating important non-linear gas phase oxidant chemistry, the model employs a user-supplied 

hourly ozone concentration as a surrogate for the hydroxyl radical and other oxidizing radical species. 

Ambient ammonia concentrations are also a user input along with temperature and relative humidity. 

Although simplifications of photochemistry have been attempted in the past, correct 

representation of the gas-phase photochemistry and the radical cycles are critically important in order 

to properly characterize sulfate and nitrate formation in the real atmosphere. Seigneur et al., (2000) 

demonstrated this fact in their evaluation of full-science representations of photochemistry against 

simplified representations (but more advanced than CALPUFF). They concluded that simplified 

linearized transformation schemes are inadequate for describing sulfate and nitrate formation 

processes: 

“These results indicate that the accurate prediction of source-receptor relationships for PM2.5

requires a comprehensive treatment of PM2.5 formation from gaseous precursors for the 

secondary components of PM2.5 and a spatially resolved treatment of transport processes for 

primary PM2.5. Simplified treatments of either atmospheric chemistry or transport are 

appropriate only when the secondary or primary components of PM2.5, respectively, are not 

significant. Therefore, the development of source-receptor relationships for PM2.5 should be 

based on air quality models that provide comprehensive descriptions of atmospheric chemistry 

and transport.” 

Morris et al., (1998) also compared the sulfate and nitrate particulate estimates from a comprehensive 

full-science regional model with those from a model incorporating a simplified empirical chemical 

mechanism developed in a manner similar to the mechanism in CALPUFF. Evaluating the full-science 

and empirical chemistry models against observed concentrations, Morris and co-workers concluded: 
 

3-6

“Given the importance of the radical cycle for determining secondary PM formation rates, it 

appears that empirical gas-phase algorithms are inadequate for determining secondary PM 

formation.” 

The uncertainty and potential biases introduced into the CALPUFF visibility estimates due to neglect 

of gas phase oxidant chemistry remain unknown. 

3.2.5 Aerosol Chemistry 

 

Formation of secondary fine particulate matter (e. g., nitrates, sulfates, organic aerosols) in 

point source plumes is strongly dependent on the rate of mixing with ambient (background) air and the 

chemical composition of this background. The rates of oxidation of sulfur dioxide (SO2) and nitrogen 

dioxide (NO2) to sulfate and nitric acid can be very different within a power plant or industrial plume 

compared to that in the background air (Gillani and Godowitch, 1999; Karamchandani et al., 2000). 

Similarly, the formation of secondary organic aerosols from emitted VOCs and those from other 

anthropogenic and biogenic sources, adds yet another pathway in the formation of visibility-impairing 

aerosols. The presence of atmospheric ammonia introduces further nonlinearities into the gas phase 

and aerosol reactions. Accordingly, for a model to realistically simulate the production of secondary 

particulate sulfate, nitrate, and organic aerosols from a potential BART source, the mixing processes 

and chemical reactions within and outside of the plume must be treated realistically. If the chemical 

interactions between these two fundamentally different and interactive chemical environments are 

overly-simplified or neglected altogether, the ability of the model to correctly calculate plume 

concentrations, deposition, or visibility impacts is lost. 

Sulfate and Nitrate Formation. Two SO2 and NOx chemical transformation schemes are available in 

CALPUFF: the MESOPUFF-II algorithm (Scire et al., 1983; Atkinson et al., 1982) and the RIVAD 

algorithm (Latimer et al., 1986). These algorithms calculate sulfate and nitrate formation rates based 

on the puff concentrations, background environmental parameters provided by CALMET, and 

background ozone and ammonia concentrations provided as input by the user. SOA particulates are not 

treated by either mechanism. The parameters used are as follows (note that each method does not use 

all of these parameters). 

Puff Average Concentrations (from CALPUFF)

• NOx concentration 

• SO2 concentration 

Environmental Parameters (from CALMET)

• Temperature 

• Surface Relative Humidity (RH) 

• Atmospheric Stability 

• Solar Radiation 

Background Concentrations (User Input)

• Ozone (O3) 

• Ammonia (NH3) 
 

3-7

The MESOPUFF-II chemical transformation scheme is EPA’s recommended approach for Class I area 

impact assessment (IWAQM, 1998). It entails pathways for five active pollutants (SO2, SO4, NOx, 

HNO3, and NO3) as follows: 

k1

SO2 Æ SO4

k2

NOx Æ HNO3 (+RNO3) 

k3

NOx Æ HNO3

NH3

HNO3 (g) ÅÆ NO3 (PM) 

where, 

SO2 is the puff average sulfur dioxide concentration; 

NOx is the puff average oxides of nitrogen concentrations; 

SO4 is sulfate concentrations formed from the SO2; 

HNO3 is the nitric acid formed from the NOx; 

NO3 is the particulate nitrate that is in equilibrium with the nitric acid; and 

NH3 is the background ammonia concentration. 

Daytime Rates

k1 = 36 x R0.55 x [O3]

0.71 x S-1.29 + k1(aq) 

k1(aq) = 3 x 10-8 x RH4 (added to k1 above during the day) 

k2 = 1206 x [O3]

1.5 x S-1.41 x [NOx]-0.33

k3 = 1261 x [O3]

1.45 x S-1.34 x [NOx]-0.12 

Nighttime Rates

k1 = 0.20 (%/hr) 

k2 = 0.00 (%/hr) 

k3 = 2.00 (%/hr) 

with, 

k1 is the SO2 to SO4 gas-phase transformation rate (%/hr)

k1(aq) is the SO2 to SO4 aqueous-phase transformation rate (%/hr) 

k2 is the NOx to HNO3+RNO3 transformation rate (%/hr) 

k3 is the NOx to HNO3 (only) transformation rate (%/hr) 

S is the stability index ranging from 2 to 6 

(PGT class A&B=2, C=3, D=4, E=5, F=6) 

R is the total solar radiation intensity (kw/m2) 

RH is the relative humidity (%) 

[O3] is the user provided background ozone concentrations (ppm) 

[NOx] is the plume average NOx concentration (ppm) 

NH3 is the user provided background ammonia concentrations 
 

3-8

Daytime chemical transformations are based on statistically analyzed hourly transformation 

rates (Scire et al., 1983) obtained from box model simulations using the Atkinson et al., (1982) 

photochemical mechanism. In this scheme, gas-phase oxidation of SO2 and NOx depends on the 

hydroxyl (OH) radical concentrations for which background ozone, solar intensity (R), and stability 

index are used as surrogates. At night, OH concentrations are much lower and default SO2 and NOx 

oxidation rates of 0.2 %/hr and 2.0 %/hr are assumed. The k1(aq) sulfate formation rate is added to the 

k1 rate during the day as a surrogate for aqueous-phase sulfate formation which begins to assume 

importance above approximately 50% RH (~0.2 %/hr sulfate formation rate) and peaks at 100% RH 

(3%/hr sulfate formation rate). 

The sulfate and nitrate formation rate equations used in the MESOPUFF II scheme were 

originally generated by developing regression equations for a few key variables on the results of 144 

box model simulations that used the 1982 photochemical mechanism of Atkinson et al. These box 

model simulations varied ambient temperature, ozone concentration, sunlight intensity, VOC 

concentrations, atmospheric stability, and plume NOx concentrations as shown in Table 3-1. The 

actual environmental conditions used to generate the sulfate and nitrate transformation equations were 

extremely limited. For example, the transformation rates did not cover temperatures below 10 deg C 

(50 deg F) or cleaner rural atmospheric conditions with VOC concentrations less than 50 ppbC. 

The CALPUFF MESOPUFF-II chemistry clearly neglects several environmental parameters 

and chemical processes that are important in simulating sulfate and nitrate formation in NOX/SO2

emissions source plumes. In many cases these deficiencies lead to an overestimation bias of the 

source’s sulfate and nitrate impacts. Factors that lead such a bias include: 

Lack of Temperature Effects: Photochemistry is known to be highly temperature sensitive, as 

evidenced by the fact that elevated ozone concentrations tend to occur on hot summer days. 

Lower temperatures produce lower OH and other radical concentrations and consequently 

lower sulfate and nitrate formation rates. The CALPUFF sulfate and nitrate formation rates, 

however, do not adequately incorporate temperature effects. The MESOPUFF-II chemical 

transformation algorithm was developed under conditions with a minimum temperature of only 

10° C (50° F). Thus, under conditions colder than 10° C, CALPUFF will overpredict sulfate 

and nitrate formation rates and impacts. CALPUFF typically estimates maximum sulfate and 

visibility impacts during the late fall/early spring and winter months; these are the same months 

when the CALPUFF overestimation bias from not considering temperature effects will be 

greatest. In addition, under colder temperatures, NOx will be converted to peroxyacetyl nitrate 

(PAN) so that the NOx is no longer available to be converted to nitrate. Since the CALPUFF 

chemistry ignores the PAN sink for NOx, it will systematically overpredict nitrate impacts. 

Effects of NOx Emissions on Sulfate Chemistry: Downwind of a point source with significant 

NOx/SO2 emissions, high NOx and SO2 concentrations co-exist. Under high NOx 

concentrations, radical concentrations are greatly reduced, resulting in very low ozone, sulfate, 

and nitrate formation rates. This is due to the NOx inhibition effect on photochemistry 

whereby: (1) the titration of NO with ozone eliminates ozone and its source as a radical 

generator; and (2) the high NO2 concentrations eliminate the OH radical via the NO2 + OH 

reaction thereby effectively shutting down photochemistry. Thus, in a NOx/SO2 point source 

plume near the source, there will be very low OH radical and ozone concentrations and 

consequently very low sulfate and nitrate formation. Since the simple MESOPUFF-II 

transformation equations cannot account for the NOx effect on the sulfate formation, 

CALPUFF will tend to over-predict sulfate formation rate in a NOx/SO2 point source plume 
 

3-9

near the source, which in turn leads to overstating the sulfate formation rate. Because 

NOx/SO2 point sources are typically buoyant, they are frequently be emitted aloft in a stable 

layer where the high NOx concentrations and inhibited sulfate and nitrate formation rates could 

persist 100 km or more downwind. 

Aqueous-Phase Sulfate Formation Algorithm. CALPUFF’s MESOPUFF-II chemistry treats aqueousphase sulfate formation solely as a function of relative humidity (RH), which actually has no direct 

affect on aqueous-phase sulfate formation chemistry. The CALPUFF MESOPUFF-II aqueous-phase 

sulfate formation rate ranges from values of approximately 0.2 %/hr at 50% RH to 3.0 %/hr at 100% 

RH. Relative humidity (RH) is a measure of the content of water vapor in the atmosphere. However, 

in reality aqueous-phase sulfate formation will depend on the amount of atmospheric liquid water 

content (LWC) in cloud or fog droplets, the pH of the water droplets, and the level of H2O2, ozone, and 

SO2 concentrations. Accordingly, in the atmosphere, aqueous-phase sulfate formation chemistry is not 

affected by RH. Thus, the CALPUFF aqueous-phase chemistry parameterization is incorrect. 

Although under conditions of clouds and fog there will be high RH, the occurrence of high RH with 

very little or no clouds or fog can be quite frequent. 

In a liquid water droplet, the reaction of SO2 with H2O2 to form sulfate is essentially 

instantaneous and is usually limited by the amount of H2O2 present (i.e., oxidant limited) for a 

NOx/SO2 point source. Once the H2O2 is reacted away within the water droplet, sulfate formation via 

this pathway slows to the rate of H2O2 formation, which would be extremely slow to nonexistent in a 

large point source plume due to the scavenging of radicals by the high NOx concentrations. This 

introduces an inaccurate representation of sulfate formation in CALPUFF that creates uncertainties and 

bias in modeled visibility impacts. Whether this uncertainty results in an under- or overestimate of 

sulfate formation is difficult to determine since the approach is scientifically invalid. Under conditions 

of high RH and little clouds or little plume interaction with clouds, it will clearly overstate sulfate 

formation. However, under conditions of cloudy conditions with available photochemical oxidants 

(i.e., H2O2 and O3) and a dilute NOx/Sox point source plume, it may understate sulfate formation. 

Near large NOx/SO2 point source where the elevated NOx concentrations scavenge and limit 

photochemical oxidants, the MESOPUFF-II algorithm will likely overstates sulfate formation. 

Thus, the CALPUFF aerosol chemistry fails to account for many environmental parameters that 

are necessary to simulate sulfate and nitrate formation rates, including VOCs and their reactivity, 

temperature, liquid water content, and NOx concentrations. In their evaluations against full-science 

PM models and observations, Seigneur et al., (2000) and Morris et al., (1998) both independently 

found that the empirical chemistry modules, such as employed by CALPUFF, are inadequate for 

estimating sulfate and nitrate formation. These findings are supported by EPA’s PM2.5 and Regional 

Haze SIP modeling guidance (EPA, 2001) that recommends against using Lagrangian models such as 

CALPUFF for simulating secondary PM. 

 From the foregoing, it is clear that the CALPUFF chemical transformation algorithms neglect 

important chemical processes necessary to accurately estimate the sulfate and nitrate impacts due to 

SO2 and NOX emissions. Given that EPA recommends the model for BART determinations, a key 

question is “What is the influence of the simplified chemistry on modeled estimates of visibility 

impacts from BART sources? In some cases, the inadequacies in the CALPUFF chemistry algorithms 

may simply introduce broader uncertainties into the calculation of estimated sulfate and nitrate 

impacts. In many cases, however, the simplifications made in the CALPUFF description of chemical 

processes result in a systematic bias in the estimated concentrations and visibility impacts due to SO2

and NOX emissions sources. For large point sources that emit SO2 and NOx emissions, such as EGUs, 
 

3-10

petrochemical process heaters, cement plant kilns, etc., many of the limitations in the CALPUFF 

MESOPUFF-II SO2 and NOx transformation algorithms would result in an overestimation bias. While 

models that are systematically biased high (i.e., over-predict impacts) may be appealing to regulatory 

decision-makers because they are ‘conservative’, the overprediction tendency may well lead to 

unwarranted and excessive control of emissions from some sources. Thus, the tradeoff between 

simplicity and conservativism on the one hand and technical credibility and unbiased answers on the 

other is a key element in the negotiation of modeling protocols developed by the states or source 

operators. 

 3.2.6 Surface Removal 

An especially important contributor to particulate concentrations is the rate of deposition to the 

surface. PM2.5 particles, which have a mass median diameter around 0.5 μm, have an average net 

deposition velocity of about 1 cm/min (or about 14 m/day) and thus the deposition of fine particles is 

not usually significant except for ground-level emissions. On the other hand, coarse particles (those 

PM10 particles larger than PM2.5) have an average deposition velocity of more than 1 m/min (or 1440 

m/day), which is significant, even for emissions from elevated stacks. 

CALPUFF includes parametric representations of particle and gas deposition in terms of 

atmospheric, deposition layer, and vegetation layer “resistances” and, for particles, the gravitational 

settling speed. Gravitational settling, which is of particular importance for the coarse fraction of PM10, 

is accounted for in the calculation of the deposition velocity. Effects of inertial impaction (important 

for the upper part of the PM10 distribution) and Brownian motion (important for small, sub-micron 

particles) and wet scavenging are also addressed. The BART guidance recommends that fine 

particulate matter (less than 2.5 μm diameter), which has higher light extinction efficiency than coarse 

particulate matter (2.5-10 μm diameters), should be treated separately in the model. CALPUFF allows 

for user-specified size categories to be treated as separate species, which includes calculating sizespecific dry deposition velocities for each size category. 

3.3 CALMET Meteorological Preprocessor 

The CALMET meteorological model consists of a diagnostic wind field module and 

micrometeorological modules for over-water and overland boundary layers. When modeling a large 

geographical area such as the CENRAP domain, the user has the option to use a Lambert Conformal 

Projection coordinate system to account for Earth’s curvature. The major features and options of the 

meteorological model are summarized in Table 3-1. The techniques used in the CALMET model are 

briefly described below. 

3.3.1 Boundary Layer Modules 

The CALMET processor contains two boundary layer modules for application to overland and 

overwater grid cells. 

Overland Boundary Layer Module: Over land surfaces, the energy balance method of Holtslag and van 

Ulden (1983) is used to compute hourly gridded fields of the sensible heat flux, surface friction 

velocity, Monin-Obukhov length, and convective velocity scale. Mixing heights are determined from 

the computed hourly surface heat fluxes and observed temperature soundings using a modified Carson 

(1973) method based on Maul (1980). The module also determines gridded fields of PGT stability 

class and hourly precipitation rates. 
 

3-11

Overwater Boundary Layer Module: The aerodynamic and thermal properties of water surfaces 

suggest that a different method is needed for estimating boundary layer parameters in the marine 

environment. A profile technique, using air-sea temperature differences, is used in CALMET to 

compute the micro-meteorological parameters in the marine boundary layer. An upwind-looking 

spatial averaging scheme is optionally applied to the mixing heights and three-dimensional temperature 

fields in order to account for important advective effects. 

3.3.2 CALMET Diagnostic Wind Field Module 

The CALMET wind model was constructed from two other meteorological models used in 

California in the late 1970s. One was the California Institute of Technology (CIT) mass consistent 

interpolation model described by Goodin et al., (1980). The other was the Complex Terrain Wind 

Model (CTWM) developed at Systems Applications, Inc. (Tesche and Yocke, 1978; Yocke and Liu, 

1978). The CTWM terrain adjustments used to modify the flow fields were assembled in the 1970s as 

part of research into fire spread and avalanche forecasting in mountainous regions of California. 

Various heuristic algorithms were developed to approximate down slope drainage flows, terrain 

blocking and channeling (Geiger, 1965), thermal heat islands (Stern and Malkus, 1953), surface 

friction retardation, capping by an elevated inversion and so on. These algorithms were based on 

empirical studies in wind tunnels, numerical modeling experiments, and field studies in the Alps, some 

dating back to the 1930s (Defant, 1933). Later work by Tesche et al., (1986), Kessler et al., (1987) and 

Douglas and Kessler (1988) integrated the CIT and CTWM modeling system into a single 

meteorological model that included algorithms to blend observational data with prognostic 

meteorological model output. The combined model was used extensively for urban-scale ozone 

studies throughout the U.S. prior to the switch to MM5 as the preferred meteorological model for SIP 

studies in the mid-1990s. 

The CALMET model development incorporated the main features of the CTWM and CIT wind 

model and significantly updated the physical parameterizations and improved model input/output (I/O) 

schemes (Scire et al., 2000a). Today, CALMET uses the CTWM two-step approach to the 

computation of the wind fields. In the first step, an ‘initial-guess’ wind field is constructed and then 

adjusted to approximate the kinematic effects of terrain, slope flows, and terrain blocking. Currently, 

the gridded MM5 field is used as the initial guess prior to terrain-perturbation. The second step 

consists of an objective analysis procedure to blend the MM5 field with observational data to produce 

a final wind field. This introduction of observational data in the second step of the CALMET wind 

field development is optional. It is also possible to run the model in “no observations” (No-Obs) 

mode, which involves the use only of MM5 gridded data for the initial guess field followed by finescale terrain adjustments on the scale of the CALMET domain. 

Normally, the CALMET computational domain is specified to be at smaller grid spacing than 

the MM5 dataset used to initialize the initial guess field. For example, 36/12 km MM5 data sets 

available for 2000-2003 over the CENRAP domain have been used to develop the 6 km CALMET 

grids shown in Figures 5-1 through 5-4. 

The current thermal, kinematic, and dynamic effects parameterized in CALMET, used in the 

first step of the windfield development, are as follows: 
 

3-12

Kinematic Effects of Terrain: The CTWM algorithms for kinematic effects (Liu and Yocke, 1980) is 

used to evaluate the influence of the terrain on the wind field. The initial guess field winds are used to 

compute a terrain-forced vertical velocity, subject to an exponential, stability-dependent decay 

function. The effects of terrain on the horizontal wind components are evaluated by applying a 

divergence-minimization scheme to the initial guess wind field. The divergence minimization scheme 

is applied iteratively until the three-dimensional divergence is less than a threshold value. 

Slope Flows: The original slope flow algorithm (Defant, 1933) has been upgraded (Scire and Robe, 

1997) based on the shooting flow algorithm of Mahrt (1982). This scheme includes both advectivegravity and equilibrium flow regimes. At night, the slope flow model parameterizes the flow down the 

sides of the valley walls into the floor of the valley, and during the day, upslope flows are 

parameterized. The magnitude of the slope flow depends on the local surface sensible heat flux and 

local terrain gradients. The slope flow wind components are added to the wind field adjusted for 

kinematic effects. 

Blocking Effects: The thermodynamic blocking effects of terrain on the wind flow are parameterized 

in terms of the local Froude number (Allwine and Whiteman, 1985). If the Froude number at a 

particular grid point is less than a critical value and the wind has an uphill component, the wind 

direction is adjusted to be tangent to the terrain. 

3.4 Estimation of Regional Haze Contributions 

The default procedure for quantifying visibility impacts is described in several documents 

(IWAQM, 1998; FLAG, 2000). Implementation of these procedures in CALPUFF is described in the 

user’s documentation (Scire et al., 2000b). Generally, ‘visibility’ may be quantified either by visual 

range (the greatest distance that a large object can be seen) or by the light extinction coefficient, which 

is a measure of the light attenuation per unit distance due to scattering and absorption by gases and 

particles. Visibility is impaired when light is scattered in and out of the line of sight and by light 

absorbed along the line of sight. The light extinction coefficient (bext) considers light extinction by 

scattering (bscat) and absorption (babs): 

 

b

ext

 = b

scat

 + b

abs

 

The scattering components of extinction (bscat) are represented by light scattering due to air molecules 

(i.e., Rayleigh scattering, brayleigh) and light scattering due to particles, bsp. The absorption components 

of extinction (babs) include light absorption due to gases (bag) and particles (bap). Furthermore, particle 

scattering, bsp, can be expressed by its components: 

 

b

sp

 = b

SO4

 + b

NO3

 + b

OC

 + b

SOIL

+ b

Coarse

 

where the chemical species and soot scattering coefficients are given as: 

 

b

SO4 = 3 [(NH4

)

2

SO

4

] f(RH) 

b

NO3 = 3 [NH4

NO

3

]f(RH) 
 

3-13

b

OC = 4 [OC] 

b

SOIL= [Soil] 

b

Coarse= 0.6 [Coarse Mass] 

 

b

ap

 = 10 [EC] 

 

The numeric coefficient at the beginning of each equation is the dry scattering or absorption efficiency 

in meters-squared per gram. The f(RH) term is a monthly-average relative humidity adjustment factor. 

The terms in the brackets are the estimated concentrations fro CALPUFF (or other model) in 

micrograms per cubic meter (μg/m3

). 

 

Finally, the total atmospheric extinction is estimated as: 

 

b

ext

 = b

SO4

 + b

NO3

 + b

OC

 + b

SOIL

+ b

Coarse

+ b

ap

+ b

rayleigh 

or, substituting in the above terms, 

 bext = 3 f(RH) [(NH4)2SO4] + 3 f(RH) [NH4NO3] + 4[OC] + 1[Soil] + (3-1) 

 + 0.6[Coarse Mass] + 10[EC] + bRay

This is the so-called IMPROVE extinction equation currently recommended by EPA (2003). Note that 

the sulfate (SO4) and nitrate (NO3) components are hygroscopic because their extinction coefficients 

depend upon relative humidity. The concentrations, in square brackets, are in μg/m3

 and bext is in units 

of Mm-1. The Rayleigh scattering term (bRay) has a default value of 10 Mm-1, as recommended in EPA 

guidance for tracking reasonable progress (EPA, 2003a). The effect of relative humidity variability on 

the extinction coefficients for SO4 and NO3 can be estimated in several ways, but following the EPA 

BART guidelines, the Class I area-specific monthly f(RH) values shown in Table 6-1 should be used. 

 

Modeled ground level concentrations of each of the above visibility impairing pollutants are 

used with the IMPROVE equation to deduce the extinction coefficient. The change in visibility 

(measured in terms of ‘deciviews’) is compared against background conditions. The delta-deciview, 

Δdv, value is calculated from the source’s contribution to extinction, bsource, and background extinction, 

bbackground, as follows:

 

Δdv = 10 ln((bbackground

+ bsource)/ bbackground) 

 

The impact of a source is determined by comparing the Δdv, or haze index (HI), for estimated natural 

background conditions with the impact of the source and without the impact of the source. If the Δdv 

value is greater than the 0.5 dv threshold the source is said to contribute to visibility impairment and is 

thus subject to BART controls. 

CALPOST uses a previous IMPROVE f(RH) curve (FLAG, 2000) which differs slightly from 

the f(RH) now used by IMPROVE and EPA (2003), mainly at high relative humidity. Also, 

CALPOST sets the maximum RH at 98% by default (although the user can change it), while the EPA’s 

guidance now caps it at 95% (easily modified in the CALPUFF input file). 
 

3-14

For regional haze light extinction calculations, use of a plume-simulating model such as 

CALPUFF is appropriate only when the plume is sufficiently diffuse that it is not visually discernible 

as a plume per se, but nevertheless its presence could alter the visibility through the background haze. 

The IWAQM Phase 2 report states that such conditions occur starting 30 to 50 km from a source. This 

is consistent with the BART guidance recommendation for using CALPUFF for source-receptor 

distances greater than 50 km. But, CALPUFF is also recommended by EPA as an option that can be 

considered for shorter transport distances when the plume may in fact be discernible from the 

background haze. 

Apart from the chemistry issues discussed previously, there do not appear to be any major 

reasons why CALPUFF cannot be used for even shorter transport distances than 30 km, as long as the 

scale of the plume is larger than the scale of the output grid so that the maximum concentrations and 

the width of the plume are adequately represented and so that the sub-grid details of plume structure 

can be ignored when estimating effects on light extinction. The standard 1-km output grid that has 

been established for Class I area analyses should serve down to source-receptor distances somewhat 

under 30 km; how much closer than 30 km will depend on the topography and meteorology of the area 

and should be evaluated on a case-by-case basis with individual CENRAP State modelers. (For 

reference, the width of a Gaussian plume, 2σy, is roughly 1 km after 10 km of travel distance, 

assuming Pasquill-Gifford dispersion rates under neutral conditions.) 

3.4.1 CALPOST Methods 

Calculation of the impact of the simulated plume particulate matter component concentrations 

on light extinction is carried out in the CALPOST postprocessor. For BART applications, this 

processor is of considerable importance. 

CALPOST is used to process the CALPUFF outputs, producing tabulations that summarize the 

results of the simulations, identifying for example, the highest and second-highest hourly-average 

concentrations at each receptor. When performing visibility-related modeling, CALPOST uses 

concentrations from CALPUFF to compute light extinction and related measures of visibility 

(deciviews), reporting these for a 24-hour averaging time. The CALPOST processor contains several 

options for evaluating visibility impacts, including the method described in the BART guidance, which 

uses monthly average relative humidity values. CALPOST contains implementations of the IWAQMrecommended and FLAG-recommended visibility techniques and additional options to evaluate the 

impact of natural weather events (fog, rain and snow) on background visibility and visibility impacts 

from modeled sources. CALPOST uses Equation 3-1 to calculate the extinction increment due to the 

source of interest and provides various methods for estimating the background extinction against 

which the increment is compared in terms of percent or deciviews. 

For background extinction, the CALPOST processor contains seven techniques for computing 

the change in light extinction due to a source or group of sources (i.e., Methods 1 through 7). These 

are usually reported as 24-hour average values, consistent with EPA and FLM guidance. In addition, 

there are two techniques for computing the 24-hour average change in extinction (i.e., as the ratio of 

24-hour average extinctions, or as the average of 24-hour ratios). Method 2 is the current default, 

recommended by both IWAQM (EPA, 1998) and FLAG (2000) for source-specific. Method 6 is 

recommended by EPA’s BART guidance (70 FR 39162). 
 

3-15

In Method 2, user-specified, speciated monthly concentration values are used to describe the 

background. When applied to natural conditions, for which EPA’s default natural conditions 

concentrations are annual averages, the same component concentrations would have to be used 

throughout the year (unless potential refinements to those default values resulted in concentrations that 

vary during the year). Hourly background extinction is then calculated using these concentrations and 

hourly, site-specific f(RH) from a 1993 IWAQM curve or, optionally, the EPA regional haze f(RH) 

curve.1

 Again the RH is capped at either 98% (default) or a user-selected value (most commonly at 

95%). 

Method 6 is similar to Method 2, except monthly f(RH) values (e.g., EPA’s monthly 

climatologically representative values) are used in place of hourly values for calculating both the 

extinction impact of the source emissions and the background conditions extinction. Hourly source 

impacts, with the effect on extinction due to sulfates and nitrates calculated using the monthly-average 

relative humidity in f(RH), are compared against the monthly default natural background 

concentrations. Thus the monthly-averaged relative humidity is applied to the hygroscopic components 

(i.e., sulfate and nitrate) of both the source impact and the background extinction with Method 6. 

3.4.2 POSTUTIL 

The POSTUTIL processor allows the cumulative impacts of multiple sources from different 

simulations to be summed, including computing the difference between two sets of predicted impacts 

(useful for evaluating the benefits of BART controls). It also contains a chemistry module to evaluate 

the equilibrium relationship between nitric acid and nitrate aerosols. This capability allows the 

potential non-linear effects of ammonia scavenging by background sulfate and nitrate sources to be 

approximated in the formation of nitrate from an individual source. The processor can compute the 

impacts of individual sources or groups of sources on sulfur and nitrogen deposition into aquatic, forest 

and coastal ecosystems, thereby allowing changes in deposition fluxes resulting from changes in 

emissions to be quantified. 

The POSTUTIL processor attempts to overcome the bias introduced when CALPUFF assumes 

that the full background ammonia concentration is entrained into each discrete puff. For a single puff, 

this may be satisfactory, but the model overestimates the production of ammonium nitrate when 

multiple puffs co-exist and overlap. The POSTUTIL processor re-partitions the ammonia and nitric 

acid concentrations to conform to the ammonia-limiting processes influencing nitrate formation. 

Though based on recognized science, this approximate post-processing method is fundamentally 

dependent on reliable estimates of ambient NH3 at the Class I receptor of interest. 

3.4.3 Refined Extinction and Background Visibility Estimates 

EPA, the IMPROVE Steering Committee, and the RPOs are evaluating whether refinements 

are warranted to the methods recommended for calculating extinction and the default estimate of 

natural background visibility. Whether EPA will approve of any changes to the IMPROVE equation is 

uncertain at this time. Also, the responsibility for incorporating any changes to the algorithms in 

CALPUFF (e.g., new f(RH) curves) is unclear. If changes to these methods are recommended by 

EPA, CENRAP is encouraged to adopt them. However, details of the process for incorporation of any 

 

1

 Note that the hourly-varying natural background extinction here is not consistent with that prescribed by the EPA’s 

natural conditions guidance (EPA, 2003b), for which a “climatologically-representative” f(RH) that only varies monthly is 

to be used. Method 6 uses these monthly average humidity values. 
 

3-16

refinements to the IMPROVE equations in the CALPUFF system should be addressed in the State’s or 

source operators modeling protocol. 

3.5 Model Availability 

The EPA-approved version of the CALPUFF modeling system is available from Earth Tech, 

Inc., (http://www.src.com/calpuff/calpuff1.htm). The main models (CALMET, CALPUFF, and 

CALPOST), their GUIs, and many of the processors are available to download. One may also register 

to receive notices of model updates. The most recent update to the system (25 May 2005) is a new 

version of CALMM5 (MM5 V3) that has been added to the Download BETA-Test page. This version 

of CALMM5 processes MM5 Version 3 output data directly. 

Earth Tech offers CALPUFF training courses that include a description of the technical 

formulation of the models, overviews of each of the processor programs, and hands-on application of 

the models to several case study data sets. Attendees of the course receive a training notebook, a 

workbook of case study problems, exercises, and data sets, updates on recent and future model 

enhancements, and the latest (proprietary) versions of the models and Graphical User Interfaces 

(GUIs). Other third-party training courses and materials are also available. 

3.6 CALPUFF Evaluation Studies 

Tesche (2002, 2003) reviewed results of various CALPUFF evaluation studies and reached the 

following conclusions: 

> There is a paucity of model evaluation information for CALPUFF at scales of 50 to 200 

km and beyond; 

> Based on the limited information available, CALPUFF may be able to give unbiased 

estimates of short-term (i.e., 3-10 hr) concentrations of non-reactive contaminants to 

within a factor of two (e.g. 200%) out to distances of about 200 km from a source. This 

level or uncertainty in a 200 km radius around a source is increased if one examines 

CALPUFF’s predictions in a particular modeling cell (e.g., one containing a population 

center) at a specific hour as opposed to considering the question of bias generally over 

the entire 200 km region irrespective of location and time of occurrence; 

> For time periods of a day or less, CALPUFF is unable to produce reliable predictions of 

non-reactive concentrations at a specific location and time; 

> What limited experimental data do exist suggest that the accuracy and reliability of the 

model’s predictions degrade as the distance scale increases; 

> While the IWAQM recommendations on the range of applicability of the CALPUFF 

model (50 to 200 km) rests on very sparse model evaluation information, EPA’s 

suggestion that the model can be used for scales beyond 200 km, even with case-bycase approval, is not based on model evaluation data; and 

> For chemically reactive pollutants such as SO2, NOx, sulfate, nitrate, nitric acid, and 

other secondary reaction products, the testing of CALPUFF model over extended spatial 

scales (50 km and beyond) has not been attempted in a rigorous manner. 
 

3-17

Scire et al., (2001) report an evaluation of CALPUFF sulfate, nitrate, light extinction, and 

sulfur and nitrogen deposition at a Class I areas over a range of source-receptor distances. In this 

study, in which a large number of sources were modeled simultaneously, sulfate and nitrate predictions 

at the CASTNet monitoring site in Pinedale, Wyoming were evaluated against observations, and light 

extinction predictions were evaluated using transmissometer measurements. Wet sulfur and nitrogen 

predictions were compared to observations at several acid deposition monitoring sites. This study is 

especially relevant because it evaluates the performance of the model to predict variables of direct 

interest in Class I visibility analyses, such as sulfate and nitrate concentrations and light extinction 

coefficients 

More recently, Chang et al., (2003) reported an intercomparison of CALPUFF with two other 

transport and dispersion models with high resolution field data. CALPUFF predictions for inert SF6

were compared using two recent mesoscale field datasets: the Dipole Pride 26 (DP26) and the 

Overland Along-wind Dispersion (OLAD). Both field experiments involved instantaneous releases of 

sulfur hexafluoride tracer gas in a mesoscale region with desert basins and mountains. Tracer 

concentrations were observed along lines of samplers at distances up to 20 km. CALPUFF predictions 

were evaluated using the maximum 3-h dosage (concentration integrated over time) along a sampling 

line. At the DP26 sampler array, CALPUFF had mean biases within 35% and random scatters of about 

a factor of 3–4. About 50%–60% of the CALPUFF predictions were within a factor of 2 of the 

observations. At the OLAD site, the model underpredicted by a factor of 2–3, on average, with 

random scatters of a factor of 3–7. Only about 25%–30% of the CALPUFF predictions of inert SF6

were within a factor of 2 of observations. 

The tracer studies with which CALPUFF transport and diffusion capabilities were evaluated in 

the IWAQM Phase 2 report were generally over distances greater than 50 km. More recently, model 

performance has been performed at shorter distances including a power plant in Illinois in simple 

terrain at source-receptor distances in arcs ranging from 0.5 km to 50 km from the stack (Strimaitis et 

al., 1998). Another CALPUFF evaluation study over short-distances is reported by Morrison et al. 

(2003). These studies address model performance over source-receptor distances from a few hundred 

meters to 50 km. 
 

3-18

Figure 3-1. CALPUFF Modeling System Components. (Scire et al., 2000a) 
 

3-19

Table 3-1. Major Features of the CALMET Meteorological Model. (Scire et al., 2000b)

 • Boundary Layer Modules of CALMET 

 - Overland Boundary Layer - Energy Balance Method 

 - Overwater Boundary Layer - Profile Method 

 - Produces Gridded Fields of: 

 -- Surface Friction Velocity 

 -- Convective Velocity Scale 

 -- Monin-Obukhov Length 

 -- Mixing Height 

 -- PGT Stability Class 

 -- Air Temperature (3-D) 

 -- Precipitation Rate 

 • Diagnostic Wind Field Module of CALMET

 - Slope Flows 

 - Kinematic Terrain Effects 

 - Terrain Blocking Effects 

 - Divergence Minimization 

 - Produces Gridded Fields of U, V, W Wind Components 

 - Inputs Include Domain-Scale Winds, Observations, and 

 (optionally) Coarse-Grid Prognostic Model Winds 

 - Lambert Conformal Projection Capability 
 

3-20

Table 3-2. Major Features of the CALPUFF Dispersion Model (Scire et al., 2000a) 

 • Source types

 - Point sources (constant or variable emissions) 

 - Line sources (constant or variable emissions) 

 - Volume sources (constant or variable emissions) 

 - Area sources (constant or variable emissions) 

 • Non-steady-state emissions and meteorological conditions

 - Gridded 3-D fields of meteorological variables (winds, temperature) 

- Spatially-variable fields of mixing height, friction velocity, convective velocity 

scale, 

 Monin-Obukhov length, precipitation rate 

 - Vertically and horizontally-varying turbulence and dispersion rates 

 - Time-dependent source and emissions data for point, area, and volume sources 

 - Temporal or wind-dependent scaling factors for emission rates, for all source types 

 • Interface to the Emissions Production Model (EPM)

 - Time-varying heat flux and emissions from controlled burns and wildfires 

 • Efficient sampling functions

 - Integrated puff formulation 

 - Elongated puff (slug) formulation 

 • Dispersion coefficient (σy, σz) options

 - Direct measurements of σv and σw

 - Estimated values of σv and σw based on similarity theory 

 - Pasquill-Gifford (PG) dispersion coefficients (rural areas) 

 - McElroy-Pooler (MP) dispersion coefficients (urban areas) 

 - CTDM dispersion coefficients (neutral/stable) 

 • Vertical wind shear

 - Puff splitting 

 - Differential advection and dispersion 

 • Plume rise

 - Buoyant and momentum rise 

 - Stack tip effects 

 - Building downwash effects 

 - Partial penetration 

 - Vertical wind shear 

 • Building downwash

 - Huber-Snyder method 

 - Schulman-Scire method 

 - PRIME method 

 
 

3-21

Table 3-2. Major Features of the CALPUFF Dispersion Model (Concluded). 

 • Complex terrain

 - Steering effects in CALMET wind field 

 - Optional puff height adjustment: ISC3 or "plume path coefficient" 

 - Optional enhanced vertical dispersion (neutral/weakly stable flow in CTDMPLUS) 

 • Subgrid scale complex terrain (CTSG option)

 - Dividing streamline, Hd, as in CTDMPLUS: 

 - Above Hd, material flows over the hill and experiences altered diffusion rates 

 - Below Hd, material deflects around the hill, splits, and wraps around the hill 

 • Dry Deposition 

 - Gases and particulate matter 

 - Three options: 

- Full treatment of space and time variations of deposition with a resistance 

model 

 - User-specified diurnal cycles for each pollutant 

 - No dry deposition 

 • Overwater and coastal interaction effects

 - Overwater boundary layer parameters 

 - Abrupt change in meteorological conditions, plume dispersion at coastal boundary 

 - Plume fumigation 

 • Chemical transformation options

- Pseudo-first-order chemical mechanism for SO2, SO=

4, NOx, HNO3, and NO3 

(MESOPUFF II method) 

 - Pseudo-first-order chemical mechanism for SO2, SO=

4, NO, NO2 HNO3, and NO3 

(RIVAD/ARM3 method) 

 - User-specified diurnal cycles of transformation rates 

 - No chemical conversion 

 • Wet Removal

 - Scavenging coefficient approach 

 - Removal rate a function of precipitation intensity and precipitation type 
 

3-22

Table 3-3. Parameter Variations in Box Model Simulations Used to Develop the 

CALPUFF Sulfate and Nitrate Formation Algorithms. (Morris et al., 2003).

Surrogate 

Parameter 

Number of 

Variations 

Model Input Parameters And Variations 

Season 3 Temperatures of 30, 20 and 10 °C were used for the, 

respectively, summer, fall and winter seasons. 

Diurnally varying clear skies solar radiation was 

assumed for each season corresponding to a latitude of 

40°. 

Background Air 

Reactivity 

4 For the summer season the following four levels of 

background ozone and VOCs were used: 

Ozone 

(ppb) 

VOC 

(ppbC) 

20 50 

50 250 

80 500 

200 2,000 

For fall and winter the ozone concentrations were 

assumed to be 75% and 50% of the summer levels. 

Dispersion 2 Two different rates of plume dispersion were used: (1) 

a stable case with a wind speed of 1.5 m/s and; (2) a 

slightly unstable case with a wind speed of 5.0 m/s. 

Release Time 2 Photochemical box model simulations were performed 

with release times of sunrise and noon. 

Plume NOx 

Concentration 

3 Initial plume NOx concentrations of 7, 350 and 1400 

ppb were used.