Satellite-Based Seasonal Fingerprinting of Methane Emissions from Canadian Dairy Farms Using Sentinel-5P

Abstract

Methane (CH4) emissions from dairy farming are a significant but under-quantified component of agricultural greenhouse gases. This study provides a satellite-based assessment of dairy-specific methane emissions across Canada using high-resolution Sentinel-5P TROPOMI data. By integrating spatial clustering of 1,701 dairy farms and processors, a quasi-experimental design with paired non-dairy reference regions, and seasonal pattern decomposition, we analyzed national and regional spatiotemporal emission trends. Results show persistently higher methane levels in dairy regions (mean difference: 16.99 ppb), with consistent fall-winter peaks. Notably, the dairy-specific methane anomaly, defined as the concentration difference between dairy and non-dairy regions declined by 62.25% from 2019 to 2024, with a sharp drop during 2022-2023 (-41.11%). Meanwhile, national methane levels rose by 3.83%, with increasing spatial heterogeneity across provinces. An inverse relationship between baseline methane levels and growth rates suggests a convergence effect. Seasonal analysis revealed universal spring minima and fall-winter maxima, offering distinct temporal signatures for source attribution. This study demonstrates the value of satellite-based monitoring for policy-relevant methane assessments and introduces a scalable framework applicable to other regions. The observed narrowing of dairy methane anomaly indicates evolving emission dynamics, potentially reflecting rising baseline methane rather than a definitive reduction in dairy source emissions. This highlights the need for integrated satellite and ground-based approaches to enhance understanding and guide mitigation efforts.