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Methane Sensing

Using AI Tools for Measuring Atmospheric Methane

Leave a Comment / Emissions Technology, Greenhouse Gas Emissions, Methane Sensing, Neural Networks TDLAS, TDLAS AI Tools / By

TLDR: A dataset of simulated absorbance scans and a 1D convolutional neural net were used to train a model to predict methane mole fraction to within 0.25% of actual mole fraction. This provides the potential to rapidly improve data processing of TDLAS-based sensors. 1. Initial Absorbance Simulation We start with simulating methane absorbance. By using …

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Satellite Based Methane Emissions Monitoring

Leave a Comment / Methane Sensing / By

Quantitative monitoring of methane greenhouse gas emissions is becoming increasingly important as the effects of climate change are becoming harder to ignore.[1] In this series of posts, we will dig deeper into the challenges associated with accurately monitoring methane gas emissions. This being a worthwhile endeavor since methane gas emissions account for up to 10% of …

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