The Heath Press

Gaussian Plume (Reflected, No Deposition)

This page demonstrates a simplified Gaussian plume approach for estimating atmospheric NH₃ concentrations downwind of a point source (e.g., a livestock building). The model uses Pasquill–Gifford stability classes to approximate atmospheric dispersion, and it shows how concentrations typically decrease with distance, while also depending strongly on wind speed, source height, crosswind offset, and atmospheric stability. The “reflected” option includes a standard ground-reflection term that mimics the effect of an impermeable surface, often used as a first-order approximation in classic plume formulations.

Important: this tool is intentionally not a regulatory-grade calculator. It is meant for scenario exploration and intuition—e.g., comparing stability classes, testing the influence of wind speed, or seeing how concentration profiles change at different heights. The dispersion parameterisations are simplified, and local effects such as building aerodynamics, plume rise, complex terrain, chemical conversion, and removal processes are not represented in full detail.

Gaussian Plume: Concentration vs Distance (NH₃)

Browser-based Gaussian plume calculator (standard or reflected) using Pasquill–Gifford stability classes. Output: x–y plot of concentration (µg/m³) vs distance (m).

Default ≈ your Python value (incl. multipliers).
Comma-separated, e.g. 0,1,3
to
Units: Q = N × E × fraction (g/s). Concentration computed in g/m³, displayed as µg/m³ (×1e6).
Total emission Q (horizontal)
At X = 100 m (z = first curve)
Concentration vs distance

A more complete modelling chain can also include deposition , allowing concentration fields to be translated into deposition fluxes over land types. In addition, it is possible to model situations with a background concentration (baseline NH₃ in air) to explore how local emissions interact with regional conditions—especially relevant in livestock-dense areas. Finally, ir. Wouter de Heij also has the capability to run Monte Carlo simulations, propagating uncertainty in key inputs (emission rate, wind speed, stability, etc.) to generate confidence ranges rather than single curves. Contact him for more information.

Disclaimer: This is a demonstration tool for education and transparent discussion. It should not be used as a substitute for site-specific measurements, validated dispersion–deposition modelling, or permit-related assessments.