Application: UAV
Inferring methane emissions from African livestock by fusing drone, tower, and satellite data. - Van Hove et al. 2024
Significant uncertainties persist in mapping methane sources across Africa's extensive agricultural regions. We developed an observing system that estimates methane emission rates by assimilating drone and flux tower observations — including CH₄ measurements from Aeris Technologies — into an atmospheric dispersion model using Bayesian inference. Applied to verify methane sources identified via hyperspectral satellite radiance anomalies, the approach quantifies emissions from diverse ruminant livestock (cattle, goats, sheep, and camels) in sub-Saharan Africa. Our Bayesian estimates align with IPCC Tier 2 values, capture the expected post-feeding emission increase, and prove more robust than mass balance methods under variable wind conditions. The method reliably quantifies weak sources (down to ~100 g h⁻¹) with ±50% uncertainty (reducing to ±12% for strong cattle sources of 1,000–1,500 g h⁻¹). These results highlight the potential of drone-based Bayesian inference for estimating complex methane sources across Africa and beyond, including wetlands, landfills, and wastewater sites, thereby supporting improved emission inventories and climate models.
In Situ Observations Reveal Underestimated Greenhouse Gas Emissions from Wastewater Treatment with Anaerobic Digestion − Sludge Was a Major Source for Both CH4 and N2O - Galfalk & Bastviken 2025
This study used drone-based measurements with Aeris Technologies analyzers (including Strato N₂O/CO₂ and Strato CH₄/C₂H₆ sensors mounted on DJI Matrice 300 and Airolit Explorian XLT drones) to quantify greenhouse gas emissions of CH₄ and N₂O from wastewater treatment plants (WWTPs) employing anaerobic digestion (AD) and sludge storage. Results revealed that combined CO₂-equivalent emissions were 2.4-fold higher than IPCC-recommended emission-factor-based estimates, with N₂O emissions from sludge—previously assumed to be zero—accounting for 9% of CH₄ emissions by weight and contributing half of the total CO₂-equivalent sludge emissions. These findings underscore the need for emission mitigation strategies as AD use increases for energy recovery, while emphasizing the importance of direct flux observation tools for WWTP managers to prioritize effective interventions.
UAV Based In situ Measurements of CO2 and CH4 Fluxes over Complex Natural Ecosystems - Bolek et al. 2024
This study presents an unoccupied aerial vehicle (UAV) platform designed to resolve horizontal and vertical patterns of CO₂ and CH₄ mole fractions in the lower atmospheric boundary layer, providing valuable data for upscaling fluxes from heterogeneous natural ecosystems and identifying greenhouse gas emission hotspots. The platform integrates an Aeris Strato analyzer (from Aeris Technologies) for CH₄, connected sequentially, alongside a 2D anemometer for wind speed, temperature, humidity, and pressure measurements. Laboratory and field validations confirmed reliable accuracy, with strong agreement against tower-based CO₂, H₂O, and wind data. Using interpolated GHG mole fraction maps, the system assessed spatial variability in poorly observed near-surface layers—particularly relevant for remote regions like the Arctic—and demonstrated flux calculations from local sources via the profile method, showing acceptable qualitative agreement with eddy covariance estimates despite uncertainties. This UAV tool thus complements stationary networks such as eddy covariance towers and manual chambers by enhancing observations of the atmospheric boundary layer's lowest part.
Sensitive Drone Mapping of Methane Emissions without the Need for Supplementary Ground-Based Measurements - Galfalk et al. 2021
This study introduces a lightweight drone-based system (6.7 kg total) for sensitive mapping of methane (CH₄) hotspots, leak detection in gas systems, and quantification of total CH₄ fluxes from anthropogenic sources such as wastewater treatment plants, landfills, energy production, biogas facilities, and agriculture, with all measurements conducted onboard without supplementary ground-based instruments. Horizontal flight patterns enable large-area hotspot identification, while vertical profiles support mass balance flux calculations. The platform logs CH₄ concentrations and wind speeds at 1 Hz with precisions of 0.84 ppb/s and 0.1 m/s, respectively, using a customized Aeris MIRA Pico mid-infrared laser analyzer (1.9 kg). As a demonstration for a challenging source, three 10-minute flights over a sludge deposit at a wastewater treatment plant mapped emission hotspots and determined a total flux of 178.4 ± 8.1 kg CH₄ per day, highlighting the system's potential for accurate, comprehensive monitoring of difficult-to-access methane sources where traditional methods fall short.