Pollution Investigation

$14.95 – $100.95

Investigate the cause of water pollution in Big Lake.

What is causing the water pollution in Big Lake? Is it the dairy farm, the landfill or the factory?

  • Conduct simulated water tests for nitrates, PCBs, E. coli bacteria, and lead.
  • Analyze the test results to determine the source of pollution that is affecting the town’s water supply.
  • Learn about the potential health effects of pollution.
Download Teacher Guide
 $14.95
Assembled kits
 $100.95
Materials to assemble 10 kits - includes all supplies, printed labels, and student instructions copy master
 $53.95
Materials to refill 10 kits
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Kit Includes

  • Student instructions
  • 4 tubes of simulated “Water” samples
  • 4 strips of simulated “Nitrate Indicator Paper”
  • 1 simulated “PCB Test Strip”
  • 2 plastic well strips
  • 1 tube of simulated “E. coli Stain”
  • 1 tube of simulated “Lead Indicator Solution”
  • 6 labeled droppers
  • Pollutant Testing Procedures sheet

Also Required

  • Safety goggles

Quantity Discounts

Kits:

  • 1 – 9 kits: $14.95 each
  • 10 – 24 kits: $14.20 each
  • 25+ kits: $13.46 each

Unassembled:

  • 1 – 9 packs: $100.95 each
  • 10+ packs: $95.90 each

Refills:

  • 1 – 9 packs: $53.95 each
  • 10+ packs: $51.25 each

Correlation to Next Generation Science Standards (NGSS) Shop by NGSS »

Performance Expectations:

MS-ESS3-3. Apply scientific principles to design a method for monitoring and minimizing a human impact on the environment.

  • Science & Engineering Practices

    Analyzing and Interpreting Data - Analyze and interpret data to provide evidence for phenomena

  • Disciplinary Core Ideas

    ESS3.C: Human Impacts on Earth Systems - Human activities have significantly altered the biosphere, sometimes damaging or destroying natural habitats and causing the extinction of other species. But changes to Earth’s environments can have different impacts (negative and positive) for different living things.

  • Crosscutting Concepts

    Cause and Effect - Cause and effect relationships can explain and predict behaviors in complex natural and designed systems.

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