Abstract
A new point source pollutant dispersion model is developed, allowing fast evaluation of the critical one-hour-average ground concentrations, along with the corresponding receptor distance and meteorological conditions (wind speed and stability class) for urban or rural areas, under gradual or final plume rise and with or without buoyancy induced dispersion assumptions. Relatively unstable pollutants can be dealt-with, while site-specific meteorological data are not required, as the computed concentrations are maximized against all credible combinations of wind speed, stability class and mixing height, as well as against all receptor distances. The model combines, under a constrained numerical extremization algorithm, the minimum mixing height model of Benkley and Schulman, with the dispersion relations of Pasquill-Gifford and Briggs for rural and urban settings respectively, the buoyancy induced dispersion correlation of Pasquill, the power-law wind profile exponent values of Irwin and the buoyant plume rise relations of Briggs. The model is well suited for air pollution management studies, as it allows fast and accurate screening of selected point sources in study areas and evaluation of the ways to have thier impact reduced, as well as, for regulatory purposes, as it allows the setting of minimum stack size requirements as function of the exit gas volume and temperature, the pollutant emission rates, and the hourly pollutant concentration standards.
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Abbreviations
- ACMS:
-
Stack gas volume (Actual m3 s−1)
- C j :
-
One-hour average normalized ground-level concentration of pollutant j equal to Ψ j Q j (μg m−3 t−1 hr)
- C cr :
-
Critical one-hour average normalized ground-level pollutant concentration (μg m−3 t−1 hr)
- D :
-
Internal stack diameter at gas exit level (m)
- f :
-
Coriolis parameter
- F t :
-
Thermal plume rise parameter defined by Equation (8) (Actual m3 s−1)
- H :
-
Stack height (m)
- H eff :
-
Effective plume height, at the receptor (m)
- H f :
-
Effective final plume height (m)
- k :
-
Von Karman constant
- K :
-
Pasquill stability class, 1 to 6, or A to F
- k cr :
-
Critical Pasquill stability class corresponding to C cr, 1 to 6, or A to F
- L :
-
Depth of mixing layer (m)
- L m :
-
Depth of mixing layer due to mechanical turbulence (m)
- Q j :
-
Rate of emission of pollutant j from a single, or from multiple identical neighboring stacks (t hr−1)
- t :
-
Time required for a released pollutant to reach the receptor (s)
- t 1/2 :
-
Half-life of a reactive pollutant (s)
- T a :
-
Ambient air temperature (K)
- T s :
-
Stack gas exit temperature (K)
- U :
-
Wind speed at anemometer height (10 m) (m s−1)
- U cr :
-
Critical wind speed at anemometer height (10 m) corresponding to C cr (m s−1)
- U s :
-
Wind speed at the physical stack height level (m s−1)
- u * :
-
Surface friction velocity (m s−1)
- V s :
-
Exit gas velocity (m s−1)
- x :
-
Distance of a receptor from stack (m)
- x cr :
-
Critical receptor distance corresponding to C cr (m)
- x f :
-
Distance to final plume rise (m)
- z :
-
Height of a receptor (m)
- z 0 :
-
Surface roughness length (m)
- z r :
-
Measurement height for the near-surface reference wind speed (m)
- ΔH d :
-
Stack downwash (m)
- ΔH b :
-
Thermal plume rise (m)
- σ y :
-
Standard deviation of concentration distribution in the horizontal plane, adjusted, if required, for buoyancy-induced dispersion, Equation (3) (m)
- σ′ y :
-
Standard deviation of plume concentration distribution in the horizontal plane (m)
- σ z :
-
Standard deviation of the concentration distribution in the vertical plane, adjusted, if required, for buoyancy-induced dispersion, Equation (4) (m)
- σ′ z :
-
Standard deviation of plume concentration distribution in the vertical plane (m)
- Ψ j :
-
One-hour average concentration of pollutant j (μg m−3)
- (Ψ std) j :
-
Maximum allowed one-hour concentration of pollutant j (μg m−3)
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Economopoulos, A.P. A model for the critical hourly concentration, receptor distance and meteorological conditions from point sources with thermal plume rise. Water Air Soil Pollut 61, 339–363 (1992). https://doi.org/10.1007/BF00482615
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DOI: https://doi.org/10.1007/BF00482615