A Physics-Based Framework for Accurate On-Farm Enteric Methane Sensing

The accuracy of on-farm sensors remains a limiting factor in their use to verify efforts to reduce enteric methane emissions. These “sniffers”, although scalable, measure gas concentration (ppm), which is poorly correlated with mass flux (g/day), because the dilution of enteric methane by turbulence is unmeasured. We develop a multiphysics framework that provides the first mechanistic connection from the biological source to the sensor reading. Our model combines a physiological mass balance of rumen gas production and mixing with a transient, buoyant puff model that captures the fluid dynamics of the emission event as it disperses into the near-field environment. Validated against field measurements of mass flux from emission events (a 9% error in mass prediction and a root-mean-square error of 0.4 mg/s), the model replicates the magnitude, fluctuations, and overall dispersion of mass flux using basic physiological variables and quantifies the “captured fraction” of mass by the device. This framework is a foundational tool for transforming low-cost sensor data into accurate measures of mass emission fluxes.