UAV-based method for measuring CO ₂ emissions in forest ecosystems

This study addresses the difficulty of accurately quantifying CO ₂ emissions in forest ecosystems due to spatial heterogeneity, complex terrain, and the combined effects of horizontal and vertical transport. A methodology for quantifying 3-D CO ₂ emissions using an unmanned aerial vehicle was developed, evaluated, and applied to a forest ecosystem. The measurement platform was integrated with a high-precision closed-path CO ₂ analyzer to measure CO ₂ mole fractions and a calibrated ultrasonic anemometer to measure wind vectors, together with profile measurements of temperature and pressure. Within a mass-balance framework, the instrumented platform was flown along horizontal loops at multiple heights together with vertical ascent flight tracks, acquiring data along the flight tracks that were used to quantify horizontal advective and vertical turbulent carbon dioxide emission components, respectively. The method was applied at a subtropical plantation forest and evaluated against fluxes derived using a nearby eddy covariance flux tower. Validation against long-term CO ₂ flux measurements from the permanently installed eddy covariance system shows that vertical CO ₂ fluxes derived from the airborne observations agree well with the tower observations across seasons, with a correlation coefficient of 0.9 based on 168 paired flux estimates collected between May 2023 and December 2024. Measurements collected along the horizontal box-pattern flight paths further reveal diurnal variations in local canopy-air CO ₂ mass transport: lateral advection dominates in the early morning, whereas vertical uptake prevails under well-mixed midday conditions. Sensitivity analysis of emission intensities across control volumes with different horizontal dimensions (50 × 50, 100 × 100, and 150 × 150 m ² ) and a constant vertical extent of 50 m revealed stronger scale dependence during autumn mornings, indicating significant spatial heterogeneity in CO ₂ emissions. Uncertainty assessment suggests that the total relative uncertainty of the emission estimates derived using this approach is typically approximately 30 %, with wind-field measurement as the main error source. Overall, the proposed approach provides a flexible and reliable method for analyzing near-surface 3-D CO ₂ transport over structurally heterogeneous forests and complex terrain, helping to overcome the limited spatial coverage of traditional flux towers and remote sensing.