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Pesticides, Organic Contaminants, and Pathogens in Air
affected residences in New Orleans, (2) mapping evacuation routes and collection sites for hazmat containers displaced by the storm, (3) defning exclusion zones around dangerous hazmat containers, and (4) selecting safety gear
for workers handling hazardous debris. The United Nations Environment
Programme (UNEP) selected the CAMEO suite as a tool to help developing
nations prepare for—and respond to—chemical accidents. Under UNEP’s
Awareness and Preparedness for Emergencies at the Local Level (APELL)
program, CAMEO has been demonstrated or taught in 50 countries.
Another popular air dispersion model is U.S. EPA’s AERMOD (Table 5.5).
The AMS/EPA Regulatory Model (AERMOD) is an air dispersion model
based on planetary boundary layer theory. It is a steady-state dispersion
model designed for short-range (up to 50 km) dispersion of air pollutant
emissions from stationary industrial sources. AERMOD utilizes a similar
input and output structure to ISCST3 and shares many of the same features,
as well as offering additional features. It is used extensively to assess pollution concentration from a wide variety of sources. A few examples of the
many uses of the dispersion model include an assessment of exposure to air
pollutants (NO 2 and SO 2 ) in an industrial complex setting in Thailand (Jittra
et al., 2015) and assessment of mass loss of sulfuryl fuoride from two structure fumigation operations in California (Tao, 2019). In the Thailand study,
emission data were obtained from 292 point sources in an industrial area.
Modeled concentration data were compared to measured data from 10 receptor sites. Overall results revealed that AERMOD provided accurate predictions compared to the measured concentrations for both NO 2 and SO 2 . In the
California study, total mass loss of the fumigant from the tarped structures
was determined, based on measured air concentrations, and estimated using
AERMOD with a back calculated fux value (Johnson et al., 2010; Ross et al.,
1996). The estimated total mass loss compared well with the measured values
(see also Chapter 8, Fumigants).
CALPUFF is an advanced, integrated Lagrangian puff modeling system
for the simulation of atmospheric pollution dispersion (Table 5.5). Unlike
steady-state Gaussian models such as AERMOD, CALPUFF allows variable/
curve plume trajectories, variable meteorological conditions, accurate
treatment of calm hours and low wind speed conditions, while retaining
information of previous hours’ emissions. Since CALPUFF is the preferred
model for >50 km long-range transport, one case study used the model to
predict the plume shape and concentrations of tracers (e.g., perfuorocarbons
and SF 6 ) 100 and 600 km downwind of a release point (Irwin, 1998). Overall,
CALPUFF-generated plume shapes compared well with what were measured using arcs of samplers. However, the centerline of the modeled plumes
was offset from the measured plumes by as much as 17°. Modeled centerline
concentrations at 100 km were 1.5–2.0 times greater than the measured concentrations (e.g., 1.05 ppt [actual] vs. 1.80 ppt [model]). At 600 km, the modeled centerline concentrations were less than the measured values, but both
were the same order of magnitude (e.g., 0.38 ppt [actual] vs. 0.13 ppt [model]).
Pesticides, Organic Contaminants, and Pathogens in Air
affected residences in New Orleans, (2) mapping evacuation routes and collection sites for hazmat containers displaced by the storm, (3) defning exclusion zones around dangerous hazmat containers, and (4) selecting safety gear
for workers handling hazardous debris. The United Nations Environment
Programme (UNEP) selected the CAMEO suite as a tool to help developing
nations prepare for—and respond to—chemical accidents. Under UNEP’s
Awareness and Preparedness for Emergencies at the Local Level (APELL)
program, CAMEO has been demonstrated or taught in 50 countries.
Another popular air dispersion model is U.S. EPA’s AERMOD (Table 5.5).
The AMS/EPA Regulatory Model (AERMOD) is an air dispersion model
based on planetary boundary layer theory. It is a steady-state dispersion
model designed for short-range (up to 50 km) dispersion of air pollutant
emissions from stationary industrial sources. AERMOD utilizes a similar
input and output structure to ISCST3 and shares many of the same features,
as well as offering additional features. It is used extensively to assess pollution concentration from a wide variety of sources. A few examples of the
many uses of the dispersion model include an assessment of exposure to air
pollutants (NO 2 and SO 2 ) in an industrial complex setting in Thailand (Jittra
et al., 2015) and assessment of mass loss of sulfuryl fuoride from two structure fumigation operations in California (Tao, 2019). In the Thailand study,
emission data were obtained from 292 point sources in an industrial area.
Modeled concentration data were compared to measured data from 10 receptor sites. Overall results revealed that AERMOD provided accurate predictions compared to the measured concentrations for both NO 2 and SO 2 . In the
California study, total mass loss of the fumigant from the tarped structures
was determined, based on measured air concentrations, and estimated using
AERMOD with a back calculated fux value (Johnson et al., 2010; Ross et al.,
1996). The estimated total mass loss compared well with the measured values
(see also Chapter 8, Fumigants).
CALPUFF is an advanced, integrated Lagrangian puff modeling system
for the simulation of atmospheric pollution dispersion (Table 5.5). Unlike
steady-state Gaussian models such as AERMOD, CALPUFF allows variable/
curve plume trajectories, variable meteorological conditions, accurate
treatment of calm hours and low wind speed conditions, while retaining
information of previous hours’ emissions. Since CALPUFF is the preferred
model for >50 km long-range transport, one case study used the model to
predict the plume shape and concentrations of tracers (e.g., perfuorocarbons
and SF 6 ) 100 and 600 km downwind of a release point (Irwin, 1998). Overall,
CALPUFF-generated plume shapes compared well with what were measured using arcs of samplers. However, the centerline of the modeled plumes
was offset from the measured plumes by as much as 17°. Modeled centerline
concentrations at 100 km were 1.5–2.0 times greater than the measured concentrations (e.g., 1.05 ppt [actual] vs. 1.80 ppt [model]). At 600 km, the modeled centerline concentrations were less than the measured values, but both
were the same order of magnitude (e.g., 0.38 ppt [actual] vs. 0.13 ppt [model]).