Methodology

Peer-reviewed staining. Same protocol, every sample.

You take about 100 mL of tap water, stain it with Nile Red, filter it through a 1.0 μm membrane, and photograph the membrane under blue light. Microplastic particles fluoresce bright pink. Everything else stays dark.

Nile Red staining is well-established in the peer-reviewed literature — we didn't invent it, we adapted it. The papers are linked below, and there's a prompt at the bottom of this page you can paste into ChatGPT, Claude, or Gemini to verify any of this independently.

1

Collect ~100 mL in glass

Run the tap for 30 seconds, then fill any clean glass container with about 100 mL of water. Glass — not plastic — so the container itself can't contaminate the sample.

2

Digest organics

Add the pre-measured hydrogen peroxide dropper. It breaks down algae, biofilm, and other biological material that would otherwise stain alongside plastics. Wait 30 minutes.

3

Stain with Nile Red

Add the pre-measured Nile Red dropper. The dye binds specifically to hydrophobic particles — which is essentially all common plastics. It cannot bind to minerals, salts, or dissolved solids. Wait 30 minutes.

4

Filter and photograph

Push the stained water through the 1.0 μm syringe filter. Tape the orange filter clip over your phone camera, shine the blue LED on the membrane, and take a photo. The pink dots are microplastics.

5

Upload to the map

Upload the photo. Our computer-vision pipeline counts the particles and your sample joins the public map. Your raw photo stays attached to the count, so anyone — including you — can re-check the result.

Why the numbers are comparable

We've run the protocol on 100+ samples. Same reagents, same filter pore size, same imaging setup, same counting pipeline. That consistency is the whole point: when every sample goes through an identical process, the resulting counts can be honestly compared against each other.

We don't claim our particle counts are interchangeable with FTIR or Raman lab results. Different methods produce different numbers. What we do claim is that a Silver Lake sample and an Echo Park sample on this map ran through the same pipeline, so comparing them is meaningful. That's how the map works.

Every photo and every count is public. If a result looks wrong, the raw image is right there and anyone can scrutinize it.

The research

The strongest argument for Nile Red staining isn't anything we say. It's the body of peer-reviewed work that established it. Read it yourself.

Don't take our word for it — ask an AI

We'd rather you verify this independently than trust us. Copy the prompt below and paste it into ChatGPT, Claude, Gemini, or whichever LLM you trust. It'll walk through the chemistry, the literature, and the limitations — and tell you whether the method holds up.

I'm evaluating an at-home microplastics test that uses Nile Red fluorescence staining on ~100 mL of tap water, followed by filtration through a 1.0 μm membrane and imaging under blue light. The protocol is adapted from Leonard et al. 2022 (Journal of Hazardous Materials Letters), and the technique builds on Maes et al. 2017 and Erni-Cassola et al. 2017. Please walk me through: 1. What Nile Red is and why it specifically binds to hydrophobic microplastic particles. 2. The peer-reviewed evidence that Nile Red fluorescence is a valid method for detecting microplastics in water. 3. The known strengths and limitations of this approach (size cutoff, polymer coverage, false positives). 4. Whether running the same locked protocol across many samples produces internally comparable particle counts — even if absolute counts can't be cross-compared with FTIR/Raman labs. 5. Your honest assessment: is this a legitimate way for a curious person to see microplastics in their own tap water? Give me citations where possible.

What we detect

  • · Particles ≥ 10 μm
  • · All common polymers (PE, PP, PET, PS, nylon)
  • · Fibers, fragments, and films

What we don't

  • · Nanoplastics under 10 μm
  • · Polymer ID (count, not type)
  • · Black rubber particles (color blocks fluorescence)

Add your sample to the map

Run the same protocol on your own water. Your sample joins the public dataset.

Results are for informational purposes and shouldn't be read as a regulatory or health determination. Each result reflects an individual household sample, not a municipal-system measurement.