Low-Cost Greenhouse Gas Measurement Modules

Stanford Terrestrial Carbon Cycle Group | Stanford EXtreme Environment Microsystems Lab (XLab)

In collaboration with Prof. Alison Hoyt, Prof. Debbie Senesky, Jack Lamb, Zhou Li, Sergio Cordero, Alyk Moomaw, Anthony Macias

Improving accuracy and expanding accessibility of climate science.

We have a limited understanding of greenhouse gas emissions from natural sources due to limited measurement capabilities. Current gas analyzers cost upwards of thousands of dollars and can only take one measurement at a time. However, emissions from trees in the Amazon floodplain alone are estimated to comprise 3% of global emissions (Pangala et al. 2017). By adapting commercial gas sensors and pairing them with Arduino loggers, we can mass-produce units for under $100, enabling longitudinal measurements and contributing to a stronger understanding of our planet.

CARBON CYCLE GROUP
SUSTAINABILITY ACCELERATOR
XLAB

Current Industry Products

Flux Tower

Expensive, stationary, requires solid foundation to be built

Flux Chambers

Expensive, stationary, allows for multiple measurements, utilizes expensive gas analyzer

Our Sensors

Sensirion SCD30

CO2 Sensor, $40

Figaro TGS2611

CH4 Sensor, $10

Tree Prototype (CO2 & CH4)

  • First deployment in Amazon Floodplain (May 2022)

  • Current iteration of data logger. Contains sensors, SD card reader, runs on D batteries

  • Door opening mechanism (DC motor & gear system) and magnets

  • Prototype Testing (Spring 2022)

  • Various chamber prototypes

  • Foam insulation to improve seal of chamber

  • Separate parts for heat staking

Agriculture Prototype (CO2)

  • Chamber venting system (DC motor & gears, magnets)

  • Lid mounted on PVC pipe, complete with logger and D batteries

  • Logger v2

  • Various lid prototypes

    Sell it.

Calibration

  • Research poster presentation at Stanford Syposium of Undergraduate Research (SESUR)

  • Discussing poster results with fellow group member

  • CH4 data from first Brazil deployment. Linear trend indicates correct calibration.

  • Emissions/day calculations based on flux data

  • Calibration results utilizing dynamic baseline concentrations

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