Wildland Fire Emission Sampling at Fishlake National Forest, Utah Using an Unmanned Aircraft System

Emissions from a stand replacement prescribed burn were sampled using an unmanned aircraft system (UAS, or “drone”) in Fishlake National Forest, Utah, U.S.A. Sixteen flights over three days in June 2019 provided emission factors for a broad range of compounds including carbon monoxide (CO), carbon dioxide (CO2), nitric oxide (NO), nitrogen oxide (NO2), particulate matter < 2.5 microns in diameter (PM2.5), volatile organic compounds (VOCs) including carbonyls, black carbon, and elemental/organic carbon. To our knowledge, this is the first UAS-based emission sampling for a fire of this magnitude, including both slash pile and crown fires resulting in wildfire-like conditions. The burns consisted of drip torch ignitions as well as ground-mobile and aerial helicopter ignitions of large stands comprising over 1,000 ha, allowing for comparison of same-species emission factors burned under different conditions. The use of a UAS for emission sampling minimizes risk to personnel and equipment, allowing flexibility in sampling location and ensuring capture of representative, fresh smoke constituents. PM2.5 emission factors varied 5-fold and, like most pollutants, varied inversely with combustion efficiency resulting in lower emission factors from the slash piles than the crown fires.本数据集采集自美国犹他州费什莱克国家森林的一场林分更替型计划火烧，采用无人驾驶航空器系统（Unmanned Aircraft System, UAS，简称无人机）对其排放物进行采样。2019年6月为期3天的16架次飞行作业，获取了涵盖一氧化碳（CO）、二氧化碳（CO₂）、一氧化氮（NO）、二氧化氮（NO₂）、直径小于2.5微米的颗粒物（PM2.5）、包括羰基化合物在内的挥发性有机物（VOCs）、黑碳以及元素碳/有机碳在内的多类化合物的排放因子。据我们所知，本次研究是首次针对该规模火烧开展的基于无人机的排放采样，其覆盖枝桠堆火与树冠火两种燃烧场景，可模拟野火发生的环境条件。本次火烧采用滴火把点火、地面移动点火以及空中直升机点火三种方式，针对面积超过1000公顷的大片林分实施，可对比不同燃烧条件下同一树种林分的排放因子差异。采用无人机开展排放采样，可最大程度降低人员与设备面临的作业风险，同时提升采样点位的灵活性，确保采集到具有代表性的新鲜烟气组分。PM2.5排放因子的变化幅度达5倍，且与多数污染物一样，随燃烧效率升高呈反比关系——枝桠堆火的排放因子低于树冠火。