Toward UAV-based methane emission mapping of Arctic terrestrial ecosystems

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Arctic Ecology

Background:

• Methane is a potent greenhouse gas with rising emissions expected in Arctic wetlands due to climate change.
• Current methane emission estimates have high uncertainties due to spatial variability and limitations of existing measurement methods (e.g., restricted access, high cost, power needs, maintenance).
• Traditional methods like flux chambers and eddy covariance towers have spatial limitations.

Purpose of the Study:

• To explore the use of an unmanned aerial vehicle (UAV) combined with a high-precision trace gas analyzer to map methane emission variability at the landscape scale.
• To assess the potential of this novel setup to complement established methods for greenhouse gas monitoring in Arctic ecosystems.
• To identify optimal conditions for UAV-based methane mapping.

Main Methods:

• A high-precision trace gas analyzer (0.6 ppb precision) was connected via a long tube to a consumer-grade quadcopter.
• The UAV-analyzer system was deployed in a high-Arctic tundra fen ecosystem in Zackenberg Valley, Northeast Greenland.
• Concentration measurements were mapped, and correlated with emission data from previous studies and concurrent stationary chamber measurements.

Main Results:

• The UAV-analyzer setup successfully differentiated near-surface methane concentrations (<5 ppb) within meters under favorable weather conditions.
• Five of ten mapping campaigns showed significant correlations between methane concentration hot/cold spots and high/low emission areas (1.40–7.4 mg m⁻² h⁻¹).
• Concurrent stationary chamber measurements indicated lower emissions (0.1–3.9 mg m⁻² h⁻¹) compared to previous years.

Conclusions:

• UAV-based trace gas analysis offers a promising method to map spatial methane variability in Arctic wetlands, complementing traditional techniques.
• The system's effectiveness is dependent on favorable weather conditions (calm, some air mixing); windy and wet conditions are unsuitable.
• Further improvements to the UAV-analyzer setup could enhance its ability to detect differences in ecosystems with generally higher methane emissions.