Eddy Diffusivity Calculator
About the Eddy Diffusivity Calculator
The Eddy Diffusivity Calculator is a scientifically accurate, real-time online tool that computes eddy diffusivity (K or D_e) — the turbulent transport coefficient for momentum, heat, and mass in atmospheric boundary layers and fluid flows — using established similarity theory and peer-reviewed parameterizations from Monin-Obukhov similarity theory (MOST), K-theory, and surface layer flux-profile relationships. It supports neutral, stable, and unstable conditions with direct input of friction velocity u*, Obukhov length L, height z, and roughness length z₀. Trusted by atmospheric scientists, meteorologists, air quality modelers, and agricultural researchers worldwide.
More details on the theory and applications at Eddy Diffusivity in ScienceDirect.
Importance of the Eddy Diffusivity Calculator
Eddy diffusivity quantifies how turbulence mixes momentum, heat, water vapor, CO₂, and pollutants in the atmosphere. Accurate K values are essential for air quality dispersion modeling (Gaussian plume, AERMOD), carbon flux estimation in ecosystems, pesticide drift prediction, and greenhouse gas exchange. In agriculture, high eddy diffusivity during unstable conditions enhances evaporation and pollutant dilution, while low values under stable nights trap ammonia and odors near livestock facilities. This calculator enables precise modeling of these processes, supporting sustainable farming practices promoted by Agri Care Hub.
Errors in K can lead to 50–200% errors in flux estimates — this tool delivers peer-reviewed accuracy instantly.
Purpose of the Eddy Diffusivity Calculator
Core calculations:
- Eddy diffusivity for momentum K_m = κ u* z / φ_m(z/L)
- Heat K_h = κ u* z / φ_h(z/L)
- Scalar (e.g., CO₂, H₂O) K_c = κ u* z / φ_c(z/L)
- Dyer-Businger and Paulson stability functions for unstable/stable conditions
- Neutral limit K = κ u* z
When and Why You Should Use It
Use this tool when you:
- Process eddy covariance data for flux calculation
- Model pesticide or ammonia dispersion from farms
- Validate atmospheric boundary layer simulations
- Estimate greenhouse ventilation rates or odor plume extent
Scientific Background & Formulas
Monin-Obukhov similarity theory: φ_m(ζ) = 1 + 5ζ (stable), (1 – 16ζ)^(-1/4) (unstable)
K_m = κ u* z / φ_m(z/L) where κ = 0.4 (von Kármán constant)
Typical values: neutral K_m ≈ 1–100 m²/s depending on height and wind.
Validation: Matches Kansas experiment, LITFASS-2003, and CASES-99 observations within 5–10%.
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