An interactive tool for source-apportionment of trace/heavy metals in soils — distinguishing geogenic (natural/crustal) from anthropogenic (human-caused) contamination — using the Enrichment Factor method and the Birch (2003) classification scheme.
Built as a companion tool for anyone doing contaminated-soil geochemistry work (e.g. abandoned mine sites, industrial legacy soils), where calculating and classifying EF values by hand across many samples/elements is tedious and error-prone.
- Enter raw elemental concentrations (µg/g) per sample
- Enter your own crustal/background reference concentrations
- Choose a reference (normalizing) element — typically Fe or Al
- Get EF per element per sample, automatically classified using Birch (2003) thresholds (no enrichment → extremely severe)
- Import samples from a CSV (comma-, semicolon- or tab-separated; a
Backgroundrow fills the reference values), or download a template - Compare samples/sites side by side on a bar chart, with an optional log scale for the wide range EF values cover
- Export all results to CSV
- Click any result to see the underlying calculation
- Try it instantly with Load example (illustrative placeholder numbers, not real data or a published baseline)
- Your inputs are saved in your browser, so a refresh doesn't lose them (nothing is uploaded anywhere)
Sample,Fe,Cu,Pb,Zn
Background,,,,
Site A,,,,First column is the sample name; other columns are element symbols
(Cu, Cu (µg/g) and Cu_ppm all work), with concentrations in µg/g.
Non-numeric cells such as <LOD are left blank.
To try it, download
example-soil-data.csv — an illustrative
dataset (background row plus control, tailings, floodplain, roadside and
garden samples). The numbers are made up for demonstration; they are not
real field data or a published baseline.
This tool does not ship with built-in crustal reference values. EF is a ratio to a baseline, and that baseline is a scientific choice, not a constant — it depends on your region, rock type, and which compilation you trust. Plugging in numbers you haven't verified yourself defeats the purpose of a "source apportionment" calculation.
Commonly cited sources for generic upper continental crust composition:
- Wedepohl, K.H. (1995). The composition of the continental crust. Geochimica et Cosmochimica Acta, 59(7), 1217–1232.
- Taylor, S.R. & McLennan, S.M. (1995). The geochemical evolution of the continental crust. Reviews of Geophysics, 33(2), 241–265.
- Rudnick, R.L. & Gao, S. (2003). Composition of the Continental Crust. Treatise on Geochemistry, 3, 1–64.
For a real study, a local/regional background dataset (uncontaminated soils from a comparable geological setting near your study area) is generally more defensible than a generic global crustal average — check what your field/journal expects.
EF = (Cx / Cref)_sample ÷ (Cx / Cref)_crust
Where Cx is the concentration of the element of interest, and Cref is
the concentration of the reference element (e.g. Fe), in both the sample
and the crustal/background baseline.
| EF range | Interpretation |
|---|---|
| ≤ 1 | No enrichment |
| 1 – 3 | Minor enrichment |
| 3 – 5 | Moderate enrichment |
| 5 – 10 | Moderate–severe |
| 10 – 25 | Severe enrichment |
| 25 – 50 | Very severe |
| > 50 | Extremely severe |
Reference: Birch, G.F. (2003). A scheme for assessing human impacts on coastal aquatic environments using sediments. In Coastal GIS: An Integrated Approach to Australian Coastal Issues, Wollongong University Papers in Center for Maritime Policy, 14.
npm install
npm run devThen open the local URL Vite prints (usually http://localhost:5173).
npm run buildOutputs a static site in dist/ you can deploy anywhere (GitHub Pages,
Netlify, Vercel, S3, etc.).
MIT — see LICENSE.