Development of a continuous UAV-mounted air sampler and application to the quantification of CO₂ and CH₄ emissions from a major coking plant

<p>The development in uncrewed aerial vehicle (UAV) technologies over the past decade has led to a plethora of platforms that can potentially enable greenhouse gas emission quantification. Here, we report the development of a new air sampler, consisting of a pumped stainless coiled tube of 150 m in length with controlled time stamping, and its deployment from an industrial UAV to quantify CO<span class="inline-formula">₂</span> and CH<span class="inline-formula">₄</span> emissions from the main coking plant stacks of a major steel maker in eastern China. Laboratory tests show that the time series of CO<span class="inline-formula">₂</span> and CH<span class="inline-formula">₄</span> measured using the sampling system is smoothed when compared to online measurement by the cavity ring-down spectrometer (CRDS) analyzer. Further analyses show that the smoothing is akin to a convolution of the true time series signals with a heavy-tailed digital filter. For field testing, the air sampler was mounted on the UAV and flown in virtual boxes around two stacks in the coking plant of the Shagang Group (steel producer). Mixing ratios of CO<span class="inline-formula">₂</span> and CH<span class="inline-formula">₄</span> in air and meteorological parameters were measured from the UAV during the test flight. A mass-balance computational algorithm was used on the data to estimate the CO<span class="inline-formula">₂</span> and CH<span class="inline-formula">₄</span> emission rates from the stacks. Using this algorithm, the emission rates for the two stacks from the coking plant were calculated to be <span class="inline-formula">0.12±0.014</span> t h<span class="inline-formula">⁻¹</span> for CH<span class="inline-formula">₄</span> and <span class="inline-formula">110±18</span> t h<span class="inline-formula">⁻¹</span> for CO<span class="inline-formula">₂</span>, the latter being in excellent agreement with material-balance-based estimates. A Gaussian plume inversion approach was also used to derive the emission rates, and the results were compared with those derived using the mass-balance algorithm, showing a good agreement between the two methods.</p>