3-1 3.0 CALPUFF FORMULATION AND IMPLEMENTATION

The RHR relates visibility attenuation to extinction coefficient (b ext ) which is a measure of light scattering and absorption due to atmospheric constituents. Values for b ext are estimated using an empirically derived equation which relates the extin ction coefficient to relative humidity and the following components of particulate matter mass: (a) sulfates (SO 4 ); (b) nitrates (NO 3 ); (c) organic carbon (OC); (d) elemental carbon (EC); (f) particulat e matter (IP) (“crustal material”); and (g) coarse mass (CM) (i.e., PM 10 – PM 2.5 ). The BART guidance requires the use of modeled concentrations of these components, together with a “humidity correction factor”, to estimate values for b ext on all days within a three year period. These estimates, wh en 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 particulat e matter constitutes an important fraction of PM 2.5 and that
the modeling requirements for secondary and primary pa rticulate matter differ in their need to consider atmospheric chemistry and in the degree of spatia l resolution needed for the modeling (EPA, 2001, pg 22).

This chapter introduces the formulation of th e CALPUFF modeling syst em. 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 screeni ng and/or source-specific applicati ons of CALPUFF are appropriate.

In most cases, we expect that application of th e CALPUFF system will be sufficient to meet the BART Rule requirements. For that subset of conditions requiring adva nced methods, Chapter 5 provides details on full-science alte rnative models and available data bases for BART modeling. Such conditions might include a situation where the default modeling shows th at a source just barely causes or contributes to visibility degr adation or in negotiations over the final BART determination that weighs technical and economic feasibility against exp ected 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 Re sources 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 app lication of the two. CALGRID was the urban- scale photochemical grid model resulting from the project (Yamartino et al., 1992) comparable in sc ience and capabilities to the Urban Airshed Model (UAM-IV) (Scheffe and Mo rris, 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 SO 2 ) from elevated point sources. Thus, the CALGRID model was designed to treat the complexities of ur ban-scale photochemical processes while CALPUFF was formulated to treat the non-steady state tran sport, diffusion, linear reaction, and deposition of primar y pollutants from point sources. CALPUFF was not designed to address photochemical oxidants or and secondary aerosol forma tion 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 studie s to address point source issues that include complexities posed by complex terrain, large source -receptor distances, parameterized chemical transformation and3-2 deposition, and issues related to Class I visibility im pacts. 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 assessmen ts 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 regi on. Thus, examination of the model’s formulation provides the context for assessing th e extent to which it suitable for simulating the various physical processes and gas-phase, aerosol, an d aqueous-phase chemical processe s 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/interpolati on model that provides meteorological inputs to

CALPUFF. These fields include hourly-averaged three-dimensional wind and temperat ure 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 (G rell 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 esti mated concentrations of ambient pollu tants 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 f acilitate cumulative source impacts (POSTUTIL) and estimates of light extinction and visibility attenuation at Class I re ceptors of intere st (CALPOST). In particular, CALPOST contains several options fo r computing change in extinction and deciviews for visibility assessments while the POSTUTIL postpr ocessor includes options fo r summing contributions of individual sources or groups of sources to assess cumulative impact s. POSTUTIL also contains an empirical nitric acid-nitr ate chemical equilibrium module to es timate 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 Lagr angian. Consistent with the original ARB design criteria, the Lagrangian (moving puf f) reference system was chosen for CALPUFF. In the Eulerian approach, the behavior of pollutants is described rela tive 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 mathema tical relationships for pollutant concentrations that are equally valid . The choice of which appr oach to adopt depends upon the specific design goals of the modeling system.

The advantages and drawbacks of each approa ch are thoroughly discussed in the literature (Tesche, 1983; Seinfeld and Pandis, 1998; Jaco bson, 1999; Russell and Dennis, 2000). One of the criticisms of early Eulerian grid models was their ‘over-dilution’ of point so urce 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 conc eptually simple, flexible, and computationally inexpensive, the governing equations are not directly applicable to situations involving non-linear chemical reactions (Seinfeld a nd 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 indi vidual puffs carried downwind by the threedimensional fields generated by CA LMET. The model’s implementati on 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-dimens ional hourly meteorological data, allow CALPUFF to simulate the effects of time- and space-varyi ng 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 di rection specific building dimensi ons. 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 co efficients, including the use of turbulence measurements ( σ v and σ w ), the use of similarity theory to estimate σ v and σ w from modeled surface heat and momentum fluxes, or the use of Pasquill-G ifford (PG) or McElroy- Pooler (MP) dispersion coefficients, or dispersion equati ons 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 in cluded 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-fie ld 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 condi tions. Both techniques reproduce continuous plume results under th e appropriate steady state conditions.

Wind Shear Effects : A key underpinning of the Lagrangian c oncept is that the mo deled puffs retain their identity over the time- and spatial-scale associ ated 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 di ffused and dispersed by the wind. The point where significant puff shredding occu rs is difficult to define since it depends substantially upon the complexity of the meteorol ogical 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 m odel will systematically over-predict pollutant

concentrations.3-4 To deal with this conceptual limitation, CALP UFF contains an optional puff splitting algorithm

to simulate vertical wind shear effects across individual puffs. Diff erential 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 si ze becomes large relative to the grid size to account for wind shear across the puffs. Detailed guida nce on when and how the puff-splitting algorithm

should be used and actual verification studies demons trating 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 trans port 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 th e puff-height (either that of IS CST3 or a general “plume path coefficient” adjustment), or an algorithm that simu lates enhanced vertical dispersion derived from the weakly-stratified flow and di spersion module of the Comp lex Terrain Dispersion Model (CTDMPLUS) (Perry et al., 1989). The puff-height adjustment algorithms rely on the receptor elevation (relative to the elevati on 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 th e 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 ba sed on the CTDMPLUS (Pe rry et al., 1989). Plume impingement on subgrid-scale hills is evaluated at the CTSG subgroup of receptors using a dividing streamline height (H d ) to determine which pollutant material is deflected around the sides of a hill (below H d ) and which material is a dvected over the hill (above H d ). The local flow (near the feature)

used to define H d is taken from the gridded CALMET fiel ds. As in CTDMPLUS, each feature is modeled in isolation with its own set of receptors.

Overwater and Coastal Interaction Effects : The CALMET processor cont ains 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 meteor ology 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 com putation of dry depositi on rates of gases and particulate matter as a function of geophysical para meters, meteorological c onditions, and pollutant species. For particles, source-spec ific mass distributions may be prov ided for use in the resistance model. Of particular intere st for BART analyses is th e ability to separately m odel the deposition of fine particulate matter (< 2.5 μ m diameter) from coarse particulate matter (2.5-10 μ m diameter).

Wet Deposition : An empirical scavenging coefficient appro ach 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., fro zen vs. liquid precipitation).

3.2.3 Primary Particulates

CALPUFF is designed to simulate PM 10 or PM 2.5 or other user define d size distributions of particles. The smaller the particles, the more they disperse like an inert gas. In most cases, the dispersion of inert PM 2.5 particles will differ only slightly from that of an inert gas. A key primary3-5 PM 2.5 emission from coal-fired electric generating units (EGUs) of releva nce to visibility calculations is particulate sulfate. Although primary sulfate emi ssions 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 availabl e. Treating primary sulfate emissions is likely to be most important at short distances from the stack before significant SO 2 to secondary sulfate conversion has taken place.

3.2.4 Gas-Phase Chemistry

Chemical reactions in the gas-phase play an im portant role in secondary aerosol formation by generating radical concentrations (e.g., the hydroxyl radical). These radical species oxidize SO 2 and NOx, providing the precursors to aqueous–phase chem istry (i.e., chemistry in liquid water droplets)

that convert SO 2 to sulfate (e.g., H 2 O 2 and O 3 ), and form condensable gases from some volatile organic compounds (VOCs) that can then condense into par ticulate secondary organi c aerosols (SOA). The levels of NOx, VOC, and O 3 concentrations along with the re activity 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 proces ses entirely. The chemistry in CALPUFF parameterizes chemical transformati on effects using five species (SO 2 , SO 4 = , NO

x , HNO 3 , and NO 3 - ) via a set of user-specified, diurna lly-varying transformation rates. The model estimates secondary fine particulate matter (sulfate and nitrat e) from emissions of gas-phase SO 2 and NO

x . Rather than simulating important non-linear gas phase oxidant chemistry, the model employs a user-supplied hourly ozone concentration as a su rrogate 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 ha ve been attempted in the past, correct representation of the gas-pha se photochemistry and the radical cycles are critically important in order to properly characterize sulfate and nitrate formati on in the real atmosphere. Seigneur et al., (2000)

demonstrated this fact in their evaluation of fu ll-science representations of photochemistry against simplified representations (but more advanced th an CALPUFF). They concluded that simplified linearized transformation schemes are inadequate for describing sulfate and nitrate formation

processes:

“These results indicate that the accurate pr ediction of source-recepto r relationships for PM 2.5 requires a comprehensive treatment of PM 2.5 formation from gaseous precursors for the secondary components of PM 2.5 and a spatially resolved treatment of transport processes for primary PM 2.5 . Simplified treatments of either atmospheric chemistry or transport are appropriate only when the seconda ry or primary components of PM 2.5 , respectively, are not significant. Therefore, the developmen t of source-receptor relationships for PM 2.5 should be based on air quality models that provide compre hensive 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 mode l incorporating a simplified empirical chemical mechanism developed in a manner similar to the mech anism in CALPUFF. Eval uating the full-science and empirical chemistry models against observed con centrations, 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 ar e 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 de pendent on the rate of mixing with ambient (backgr ound) air and the chemical composition of this background. The rates of oxidation of sulfur dioxide (SO 2 ) and nitrogen dioxide (NO 2 ) to sulfate and nitric acid can be very diffe rent within a power plant or industrial plume compared to that in the bac kground 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 in troduces 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 out side of the plume must be treate d realistically. If the chemical

interactions between thes e two fundamentally different and inte ractive chemical environments are overly-simplified or neglected alto gether, the ability of the mode l to correctly calculate plume concentrations, deposition, or vi sibility impacts is lost.

Sulfate and Nitrate Formation. Two SO 2 and NOx chemical transforma tion schemes are available in CALPUFF: the MESOPUFF-II algor ithm (Scire et al., 1983; Atkinson et al., 1982) and the RIVAD algorithm (Latimer et al., 1986). Th ese algorithms calculate sulfate and nitrate formation rates based on the puff concentrations, background environm ental parameters provided by CALMET, and background ozone and ammonia concentr ations 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

• SO 2 concentration

Environmental Parameters (from CALMET)

• Temperature

• Surface Relative Humidity (RH)

• Atmospheric Stability

• Solar Radiation

Background Concentrations (User Input)

• Ozone (O 3 )

• Ammonia (NH 3 )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 fi ve active pollutants (SO 2 , SO 4 , NOx,

HNO 3 , and NO 3 ) as follows:

k 1 SO 2 Æ SO 4 k 2 NOx Æ HNO 3 (+RNO 3 )

k 3 NOx Æ HNO 3 NH 3 HNO 3 (g) ÅÆ NO 3 (PM)

where,

SO 2 is the puff average sulfur dioxide concentration; NOx is the puff average oxides of nitrogen concentrations;

SO 4 is sulfate concentrations formed from the SO 2 ; HNO 3 is the nitric acid formed from the NOx;

NO 3 is the particulate nitrate that is in equilibrium with the nitric acid; and

NH 3 is the background ammonia concentration.

Daytime Rates

k 1 = 36 x R 0.55 x [O 3 ] 0.71 x S -1.29 + k 1(aq)

k 1(aq) = 3 x 10 -8 x RH 4 (added to k 1 above during the day)

k 2 = 1206 x [O 3 ] 1.5 x S -1.41 x [NOx] -0.33

k 3 = 1261 x [O 3 ] 1.45 x S -1.34 x [NOx] -0.12

Nighttime Rates

k 1 = 0.20 (%/hr)

k 2 = 0.00 (%/hr)

k 3 = 2.00 (%/hr)

with,

k 1 is the SO 2 to SO 4 gas-phase transformation rate (%/hr)

k 1(aq) is the SO 2 to SO 4 aqueous-phase transformation rate (%/hr)

k 2 is the NOx to HNO 3 +RNO 3 transformation rate (%/hr)

k 3 is the NOx to HNO 3 (only) transforma tion 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/m 2 ) RH is the relative humidity (%) [O 3 ] is the user provided backgr ound ozone concentrations (ppm) [NOx] is the plume average NOx concentration (ppm)

NH 3 is the user provided bac kground ammonia concentrations3-8 Daytime chemical transformations are based on statistically analyzed hourly transformation rates (Scire et al., 1983) obtai ned from box model simulations us ing the Atkinson et al., (1982) photochemical mechanism. In this scheme, gas-phase oxidation of SO 2 and NOx depends on the hydroxyl (OH) radical concentrations for which bac kground ozone, solar intens ity (R), and stability index are used as surrogates. At night, OH concentrations are much lower and default SO 2 and NOx

oxidation rates of 0.2 %/hr and 2.0 %/hr are assumed. The k 1(aq) sulfate formation rate is added to the

k 1 rate during the day as a surroga te for aqueous-phase sulfate form ation 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 forma tion rate equations used in the MESOPUFF II scheme were originally generated by developing regression equati ons for a few key variables on the results of 144 box model simulations that used the 1982 photochemi cal 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 nitr ate transformation equations were extremely limited. For example, the transformati on rates did not cover temperatures below 10 deg C (50 deg F) or cleaner rural atmospheric condit ions with VOC concentr ations 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 NO X /SO 2 emissions source plumes. In many cases these defici encies lead to an overestimation bias of the source’s sulfate and nitrate impacts. F actors 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 con centrations tend to occur on hot summer days. Lower temperatures produce lower OH and othe r radical concentrations and consequently

lower sulfate and nitrate formation rates. Th e CALPUFF sulfate and n itrate formation rates, however, do not adequately incorporate temper ature effects. The MESOPUFF-II chemical transformation algorithm was deve loped under conditions with a minimum temperature of only

10 ° C (50 ° F). Thus, under cond itions 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 spri ng and winter months; th ese 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 syst ematically overpredict nitrate impacts.

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

NOx/SO 2 emissions, high NOx and SO 2 concentrations co-exist. Under high NOx concentrations, radical concentra tions are greatly reduced, resulting in very low ozone, sulfate,

and nitrate formation rates. This is due to the NOx inhibition ef fect on photochemistry whereby: (1) the titration of NO with ozone eliminates ozone and its source as a radical generator; and (2) the high NO 2 concentrations eliminate the OH radical via the NO 2 + OH reaction thereby effectivel y shutting down photochemistry. Thus, in a NOx/SO 2 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/SO 2 point source plume3-9 near the source, which in turn leads to overstating the sulfate formation rate. Because

NOx/SO 2 point sources are typically buoyant, they ar e frequently be emitted aloft in a stable layer where the high NOx concentrations and inhi bited sulfate and nitrate formation rates could persist 100 km or more downwind.

Aqueous-Phase Sulfate Formation Algorithm. CALPUFF’s MESOPUFF-II chem istry treats aqueousphase sulfate formation solely as a function of re lative humidity (RH), which actually has no direct affect on aqueous-phase sulfate formation chem istry. 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 cont ent of water vapor in the atmosphere. However, in reality aqueous-phase sulfate formation will depend on the am ount of atmospheric liquid water content (LWC) in cloud or fog droplets, the pH of the water droplets, and the level of H 2 O 2 , ozone, and

SO 2 concentrations. Accordingly, in the atmosphere, aqueous-phase su lfate 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 f og can be quite frequent.

In a liquid water droplet, the reaction of SO 2 with H 2 O 2 to form sulfate is essentially instantaneous and is usually limited by the amount of H 2 O 2 present (i.e., oxidant limited) for a

NOx/SO 2 point source. Once the H 2 O 2 is reacted away within the water droplet, sulfate formation via this pathway slows to the rate of H 2 O 2 formation, which would be extremely slow to nonexistent in a large point source plume due to th e scavenging of radicals by the high NOx concentrations. This introduces an inaccurate representa tion of sulfate formation in CALP UFF 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 a pproach is scientifically invalid. Under conditions of high RH and little clouds or little plume interac tion with clouds, it will cl early overstate sulfate formation. However, under conditions of cloudy c onditions with available photochemical oxidants (i.e., H 2 O 2 and O 3 ) and a dilute NOx/Sox point source plume, it may understate sulfate formation. Near large NOx/SO 2 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 a ccount for many environmental parameters that are necessary to simulate sulfate and nitrate fo rmation rates, including VOCs and their reactivity, temperature, liquid water content, and NOx concentra tions. 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 PM 2.5 and Regional Haze SIP modeling guidance (EPA, 2001) that recomme nds against using Lagrangian models such as CALPUFF for simulating secondary PM.

From the foregoing, it is clea r that the CALPUFF chemical tr ansformation algorithms neglect important chemical processes necessary to accurate ly estimate the sulfate and nitrate impacts due to

SO 2 and NO X emissions. Given that EPA recommends the model for BART determinations, a key question is “What is the influence of the simplif ied chemistry on modeled estimates of visibility impacts from BART sources? In some cases, the in adequacies in the CALPUFF chemistry algorithms may simply introduce broader uncerta inties 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 estimat ed concentrations and visi bility impacts due to SO 2 and NO X emissions sources. For larg e point sources that emit SO 2 and NOx emissions, such as EGUs,3-10 petrochemical process heaters, cement plant kiln s, etc., many of the limitations in the CALPUFF

MESOPUFF-II SO 2 and NOx transformation algorithms would re sult in an overestimation bias. While models that are systematically bi ased 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 contro l of emissions from some sour ces. Thus, the tradeoff between simplicity and conservativism on the one hand and t echnical credibility and unbiased answers on the other is a key element in the ne gotiation of modeling protocols de veloped 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. PM 2.5 particles, which have a mass median di ameter around 0.5 μm, ha ve an average net deposition velocity of about 1 cm/m in (or about 14 m/day) and thus th e deposition of fine particles is not usually significant except for ground-level emissions. On the othe r hand, coarse particles (those

PM 10 particles larger than PM 2.5 ) have an average deposition veloc ity of more than 1 m/min (or 1440 m/day), which is significant, even fo r emissions from elevated stacks.

CALPUFF includes parametric re presentations of particle and gas deposition in terms of atmospheric, deposition layer, and vegetation layer “r esistances” and, for particles, the gravitational settling speed. Gravitational settli ng, which is of particular importa nce for the coarse fraction of PM 10 , is accounted for in the calculation of the deposition ve locity. Effects of inertial impaction (important for the upper part of the PM 10 distribution) and Brownian motion (important for small, sub-micron particles) and wet scavenging are also addre ssed. 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 diameter s), 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 velo cities for each size category.

3.3 CALMET Meteorological Preprocessor

The CALMET meteorological m odel consists of a diagnos tic wind field module and micrometeorological modules for over-water an d 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 feat ures 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 laye r modules for applicat ion to overland and overwater grid cells.

Overland Boundary Layer Module : Over land surfaces, the energy ba lance 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 c onvective velocity scale. Mixing heights are determined from the computed hourly surface heat fluxes and observe d temperature soundings using a modified Carson (1973) method based on Maul (1980) . The module also determines gr idded fields of PGT stability class and hourly pr ecipitation rates.3-11 Overwater Boundary Layer Module: The aerodynamic and thermal pr operties of water surfaces suggest that a different method is needed for es timating 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 fo r important advective effects.

3.3.2 CALMET Diagnostic Wind Field Module

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

California in the late 1970s. On e 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 Syst ems 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 spr ead and avalanche forecasting in m ountainous regions of California. Various heuristic algorithms were developed to approximate down slope drainage flows, terrain blocking and channeling (Geiger, 1965), thermal heat islands (S tern and Malkus, 1953), surface friction retardation, capping by an elevated invers ion 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 (Def ant, 1933). Later work by Tesche et al., (1986), Kessler et al., (1987) and Douglas and Kessler (1988) inte grated the CIT and CTWM mo deling system into a single meteorological model that included algorithms to blend observational data with prognostic meteorological model output. The combined mode l was used extensively for urban-scale ozone studies throughout the U.S. prior to the switch to MM5 as the pr eferred meteorological model for SIP

studies in the mid-1990s.

The CALMET model development incorporated the main features of th e CTWM and CIT wind model and significantly updated the physical parameterizations and im proved 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’ wi nd field is constructed and then adjusted to approximate the kinematic effects of te rrain, slope flows, and terrain blocking. Currently, the gridded MM5 field is used as the initial gue ss prior to terrain-pertur bation. The second step consists of an objective analysis procedure to blend the MM5 field w ith observational data to produce

a final wind field. This introduct ion of observational data in the second step of the CALMET wind field development is optional. It is also possi ble 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 th e scale of the CALMET domain.

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

the MM5 dataset used to initiali ze the initial guess field. For ex ample, 36/12 km MM5 data sets

available for 2000-2003 over the CENRAP domain ha ve 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 de velopment, 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 initi al guess field winds are used to compute a terrain-forced vertical velocity, subj ect to an exponential, st ability-dependent decay

function. The effects of terrain on the horizontal wind compone nts are evaluated by applying a divergence-minimization scheme to the initial gue ss 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 al gorithm (Defant, 1933) has been upgraded (Scire and Robe, 1997) based on the shooting flow al gorithm of Mahrt (1982). This scheme includes both advectivegravity and equilibrium flow regime s. At night, the slope flow mode l parameterizes the flow down the sides of the valley walls into the floor of th e valley, and during the day, upslope flows are parameterized. The magnitude of the slope flow de pends on the local surface sensible heat flux and local terrain gradients. The slope flow wind components are ad ded to the wind field adjusted for

kinematic effects.

Blocking Effects : The thermodynamic blocking effects of te rrain 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 Region al 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). Generall y, ‘visibility’ may be quan tified 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 dist ance due to scattering a nd absorption by gases and particles. Visibility is impaired when light is s cattered in and out of the line of sight and by light absorbed along the line of sight. Th e light extinction coefficient (b ext ) considers light extinction by scattering (b scat ) and absorption (b abs ):

b

ext = b

scat + b

abs

The scattering components of extinction (b scat ) are represented by light scattering due to air molecules (i.e., Rayleigh scattering, b rayleigh ) and light scattering due to particles, b sp . The absorption components of extinction (b abs ) include light absorp tion due to gases (b ag ) and particles (b ap ). Furthermore, particle scattering, b sp , 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 [(NH

4 )

2 SO

4 ] f(RH)

b

NO3 = 3 [NH

4 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 equa tion is the dry scattering or absorption efficiency in meters-squared per gram. The f(RH) term is a monthly-average relative hum idity adjustment factor.

The terms in the brackets are the estimated c oncentrations fro CALPUFF (or other model) in micrograms per cubic meter (μg/m 3 ).

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,

b ext = 3 f(RH) [(NH 4 ) 2 SO 4 ] + 3 f(RH) [NH 4 NO 3 ] + 4[OC] + 1[Soil] + (3-1) + 0.6[Coarse Mass] + 10[EC] + b Ray

This is the so-called IMPROVE extinction equation currently recommended by EPA (2003). Note that the sulfate (SO 4 ) and nitrate (NO 3 ) components are hygroscopic becaus e their extinction coefficients depend upon relative humidity. The concentrations, in square brackets, are in μg/m 3 and b ext is in units

of Mm -1 . The Rayleigh scattering term (b Ray ) 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 SO 4 and NO 3 can be estimated in severa l 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 exti nction coefficient. Th e change in visibility (measured in terms of ‘deciviews’) is compared against background conditions. The delta-deciview,

Δ dv, value is calculated from the s ource’s contribution to extinction, b

source , and background extinction,

b background , as follows:

Δ dv = 10 ln ((b background + b

source )/ b background )

The impact of a source is determined by comparing the Δ dv, or haze index (HI), for estimated natural background conditions with the impact of the source and without the impact of the source . If the Δ dv 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), main ly at high relativ e 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 modi fied in the CALPUFF input file).3-14 For regional haze light extinc tion calculations, use of a plume-simulating model such as CALPUFF is appropriate only when the plume is suffici ently diffuse that it is not visually discernible as a plume per se , but nevertheless its presence could alte r 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 recomme ndation for using CALPUF F 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 prev iously, there do not appear to be any major reasons why CALPUFF cannot be used for even shorte r 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 a nd so that the sub-grid de tails of plume structure can be ignored when estimating effects on light extin ction. 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 topograp hy and meteorology of the area

and should be evaluated on a case- by-case basis with individual CE NRAP State modelers. (For reference, the width of a Gaussian plume, 2 σ y , 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 pl ume 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 out puts, producing tabulations that summarize the results of the simulations, identifying for exampl e, the highest and second-highest hourly-average concentrations at each receptor. When perfor ming visibility-related modeling, CALPOST uses concentrations from CALPUFF to compute light extinction and related m easures of visibility (deciviews), reporting these for a 24-hour averaging time. The CALPOST processor contains several options for evaluating visibility impacts, including th e method described in th e 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 backgrou nd 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 th e background extinction against which the increment is compared in terms of percent or deciviews.

For background extinction, the CALPOST processo r 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, consis tent with EPA and FLM guidance. In addition, there are two techniques for computing the 24-hour av erage change in extincti on (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 c oncentration values are used to describe the background. When applied to natu ral conditions, for which EPA’ s default natural conditions concentrations are annual averages, the same co mponent concentrations would have to be used throughout the year (unless potential re finements 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, optiona lly, 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 m onthly 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 extincti on 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-av eraged 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 ch emistry 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 depositi on 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 overcom e the bias introduced when CALPUFF assumes that the full background ammonia concen tration is entrained into each disc rete puff. For a single puff, this may be satisfactory, but the model overest imates 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 approxi mate post-processing method is fundamentally dependent on reliable estimates of ambient NH 3 at the Class I receptor of interest.

3.4.3 Refined Extinction and Back ground Visibility Estimates

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

are warranted to the methods recommended for cal culating extinction and th e default estimate of natural background visibility. Whether EPA will appr ove 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 th ese methods are recommended by EPA, CENRAP is encouraged to adopt them. Howeve r, 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 CALPUF F system should be addressed in the State’s or source operators modeling protocol.

3.5 Model Availability

The EPA-approved version of th e 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 adde d to the Download BETA-Test page. This version of CALMM5 processes MM5 Vers ion 3 output data directly.

Earth Tech offers CALPUFF training courses th at include a description of the technical formulation of the models, overviews of each of th e processor programs, and hands-on application of the models to several case study data sets. Attendees of the cour se receive a training notebook, a workbook of case study problems, exercises, and data sets, updates on rece nt and future model enhancements, and the latest (proprietary) versi ons of the models and Graphical User Interfaces (GUIs). Other third-party training cour ses 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 mode l evaluation information for CALP UFF 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 dist ances of about 200 km from a source. This level or uncertainty in a 200 km radius ar ound a source is increased if one examines CALPUFF’s predictions in a particular m odeling cell (e.g., one containing a population center) at a specific hour as opposed to consid ering 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 sugge st that the accuracy a nd 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 spar se model evaluation information, EPA’s suggestion that the model can be used fo r scales beyond 200 km, even with case-bycase approval, is not based on model evaluation data; and

> For chemically reactive pollutants such as SO 2 , NO

x , sulfate, nitrate, nitric acid, and other secondary reaction produc ts, 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 simultaneousl y, sulfate and nitrate predictions at the CASTNet monitoring site in Pinedale, Wyom ing were evaluated agains t observations, and light extinction predictions were evaluated using transmissometer measurements. Wet sulfur and nitrogen predictions were compared to observations at seve ral acid deposition monitori ng sites. This study is especially relevant because it eval uates the performance of the model to predict variables of direct interest in Class I visibility analyses, such as su lfate and nitrate concentra tions and light extinction

coefficients

More recently, Chang et al., (2003) reported an intercomparison of CALPUFF with two other transport and dispersion m odels with high resolution fi eld data. CALPUFF predictions for inert SF 6 were compared using two recent mesoscale fi eld datasets: the Dipole Pride 26 (DP26) and the Overland Along-wind Dispersion (OLAD). Both fi eld experiments involved in stantaneous releases of

sulfur hexa fl uoride tracer gas in a mesoscale region w ith desert basins and mountains. Tracer concentrations were observed along lines of samplers at distances up to 20 km. CALPUFF predictions were evaluated using the maximu m 3-h dosage (concentration integr ated over time) along a sampling line. At the DP26 sample r 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 w ithin a factor of 2 of the observations. At the OLAD site, the model underp redicted 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 SF 6 were within a factor of 2 of observations.

The tracer studies with which CALPUFF transport and diffusion cap abilities were evaluated in the IWAQM Phase 2 report were generally over dist ances 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 fr om 0.5 km to 50 km from the stack (Strimaitis et al., 1998). Another CALPUFF evaluation study over s hort-distances is repor ted by Morrison et al. (2003). These studies address model performance over source-receptor distan ces from a few hundred

meters to 50 km.3-18 Figure 3-1. CALPUFF Modeling Syst em 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 Fiel d 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 Capability3-20 Table 3-2. Major Features of the CALPU FF Dispersion Model (Scire et al., 2000a)

• Source types - Point sources (constant or variable emissions) - Line sources (consta nt 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 meteorol ogical variables (winds, temperature) - Spatially-variable fields of mixing hei ght, friction velocity, convective velocity scale,

Monin-Obukhov le ngth, precipitation rate - Vertically and horizontally-var ying turbulence and dispersion rates - Time-dependent source and emissions data for point, area, and volume sources - Temporal or wind-dependent scaling fact ors for emission rates, for all source types

• Interface to the Emission s Production Model (EPM) - Time-varying heat flux and emissi ons from controlled burns and wildfires

• Efficient sampling functions - Integrated puff formulation - Elongated puff (slug) formulation

• Dispersion coefficient ( σ y , σ z ) options

- Direct measurements of σ v and σ w - Estimated values of σ v and σ w based on similarity theory - Pasquill-Gifford (PG) disp ersion coefficients (rural areas) - McElroy-Pooler (MP) dispersion coefficients (urban areas) - CTDM dispersion coe fficients (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 method3-21 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, H d , as in CTDMPLUS:

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

- Below H d , 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 vari ations of depositi on with a resistance

model - User-specified diur nal cycles for each pollutant - No dry deposition

• Overwater and coastal interaction effects - Overwater boundary layer parameters - Abrupt change in meteorological c onditions, plume dispersion at coastal boundary - Plume fumigation

• Chemical transformation options

- Pseudo-first-order chemical mechanism for SO 2 , SO = 4 , NO

x , HNO 3 , and NO 3 (MESOPUFF II method)

- Pseudo-first-order chemical mechanism for SO 2 , SO = 4 , NO, NO 2 HNO 3 , and NO 3 (RIVAD/ARM3 method) - User-specified diurnal cycles of transformation rates

- No chemical conversion

• Wet Removal - Scavenging coefficient approach - Removal rate a function of preci pitation intensity and precipitation type3-22 Table 3-3. Parameter Variations in Box Mo del Simulations Used to Develop the

CALPUFF Sulfate and Nitrate Formatio n 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 concentr ations of 7, 350 and 1400 ppb were used.