Gaussian plume concentration calculator

Estimate concentration from a continuously emitting point source using a steady Gaussian plume model.

The calculator returns C at your selected downwind distance x, crosswind position y, and height z.

Important notes (learning use only)
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Example preset

Choose a preset to fill the form and refresh results instantly.

Inputs

Advanced options (line heatmap)

Calculation result

Concentration C (selected unit)
status

σy (m)
σz (m)
model
Details (exponential term/intermediate value)

Center line (y=0, z=0) concentration profile

distance x Concentration C (µg/m³) log10(C+ε)

Isodensity heatmap (x-y, z=0)

low high

Formulas and assumptions

FAQ

What should I do first on this page?

Start with the minimum required inputs or the first action shown near the primary button. Keep optional settings at defaults for a baseline run, then change one setting at a time so you can explain what caused each output change.

Why does this page differ from another tool?

Different pages often use different defaults, units, rounding rules, or assumptions. Align those settings before comparing outputs. If differences remain, compare each intermediate step rather than only the final number.

How reliable are the displayed values?

Values are computed in the browser and rounded for display. They are good for planning and educational checks, but for regulated or high-stakes decisions you should validate assumptions with official guidance or professional review.

Can I share and reproduce this result?

Yes. Use the share or URL controls when available. Keep a baseline case and one changed case so others can reproduce your reasoning and verify that the direction and scale of change are consistent.

Is my input uploaded somewhere?

Core calculations run locally in your browser. Some pages encode parameters in a shareable URL, but no automatic upload is performed unless you explicitly share that link.

How to use Gaussian plume concentration calculator effectively

What this calculator does

This page is for estimating outcomes by changing inputs in one controlled workflow. The model keeps your focus on variables, not output shape. Start with stable assumptions, then test sensitivity by changing one key input at a time to observe directional impact.

Input meaning and unit policy

Each input has an expected unit and a typical range. For reliable interpretation, check whether you are using the same unit system, period, and base assumptions across all runs. Unit mismatch is the most common source of unexpected drift in numeric results.

Use-case sequence

A practical sequence is: first run with defaults, then create a baseline log, then run one alternative scenario, and finally compare only the changed output metric. This sequence reduces cognitive load and prevents false pattern recognition in early experiments.

Common mistakes to avoid

Avoid changing too many variables at once, mixing incompatible data sources, and interpreting a one-time output without checking robustness. A single contradictory input can flip conclusions, so keep each experiment minimal and document assumptions as part of your note.

Interpretation guidance

Review both magnitude and direction. Direction tells you whether a strategy moves outcomes in the desired direction, while magnitude helps you judge practicality. If both agree, you can proceed; if not, rebuild the baseline and verify constraints before deciding.