Abstract
Methane (CH4) is one of the main greenhouse gas for which sources and sinks are poorly constrained and better capacity of mapping landscape emissions are broadly requested. A key challenge has been comprehensive, accurate, and sensitive emission measurements covering large areas at a resolution that allows separation of different types of local sources. We present a sensitive drone-based system for mapping CH4 hotspots, finding leaks from gas systems, and calculating total CH4 fluxes from anthropogenic environments such as wastewater treatment plants, landfills, energy production, biogas plants, and agriculture. All measurements are made on-board the drone, with no requirements for additional ground-based instruments. Horizontal flight patterns are used to map and find emission sources over large areas and vertical flight patterns for total CH4 fluxes using mass balance calculations. The small drone system (6.7 kg including batteries, sensors, loggers, and weather proofing) maps CH4 concentrations and wind speeds at 1 Hz with a precision of 0.84 ppb/s and 0.1 m/s, respectively. As a demonstration of the system and the mass balance method for a CH4 source that is difficult to assess with traditional methods, we have quantified fluxes from a sludge deposit at a wastewater treatment plant. Combining data from three 10 min flights, emission hotspots could be mapped and a total flux of 178.4 ± 8.1 kg CH4 d–1 was determined.
Highlights
Our ability to predict and mitigate climate change is highly dependent on the quantitative understanding of greenhouse gas (GHG) emissions and their regulation
The method cannot currently be used for direct emission estimates with a unmanned aerial vehicle (UAV) using measured vertical wind speeds, especially with the uncertainty introduced by turbulence from the propellers of a rotary UAV
We used a transmitter on the UAV and a receiver connected to a laptop for real-time visualization of CH4 concentrations and other parameters to find the altitude limits of the plume, above where only background levels were sampled
Summary
Our ability to predict and mitigate climate change is highly dependent on the quantitative understanding of greenhouse gas (GHG) emissions and their regulation. The global decision to adopt climate goals of temperature change (rather than actual GHG emissions; COP21, Paris 2015) substantially increases our knowledge requirements because all GHG sources and sinks affect temperature. GHG emissions and their feedbacks have to be properly quantified to guide decisions toward the climate goals. Methane (CH4) has 86 times higher global warming efficiency than carbon dioxide (CO2) per kg of gas on a 20 year time scale, is increasing at a high but irregular rate for partly unknown reasons, and is at its highest level during the last 800 000 years.[1] This implies that efforts to find and reduce CH4 emissions will be efficient for reducing global warming, but for this, we currently lack methods that are accurate, easy to use, and commonly available
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