Assessing a low-cost methane sensor quantification system for use in complex rural and urban environments.

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Sensor Technology

Background:

• Low-cost sensors enable novel temporal and spatial air quality assessments.
• Methane is a potent greenhouse gas, necessitating effective monitoring strategies.
• Oil and gas operations are significant sources of methane emissions.

Purpose of the Study:

• To evaluate a low-cost sensor quantification system for methane.
• To assess linear calibration models for converting raw sensor signals to methane concentrations (ppm).
• To examine calibration choices, data processing, and cross-sensitivities affecting sensor performance.

Main Methods:

• Deployment of a low-cost methane sensor system in two distinct locations: Colorado Front Range (near oil/gas) and urban Los Angeles.
• Assessment of various linear calibration models for raw sensor signal conversion.
• Analysis of calibration procedures, data processing techniques, and sensor cross-sensitivities.

Main Results:

• The Figaro TGS 2600 sensor demonstrated accuracy in quantifying methane from raw signals using the described techniques.
• The study confirmed the utility of low-cost sensors for analyzing air quality trends and events at fine spatial and temporal scales.
• The sensors proved effective in characterizing air quality in complex urban environments.

Conclusions:

• Low-cost methane sensors, when properly calibrated, provide accurate measurements.
• These sensors are valuable tools for preliminary air quality assessments and can inform targeted monitoring efforts.
• The technology supports enhanced understanding of methane distribution and its impact on environmental and human health.