Polarization Lidar Detection of Agricultural Aerosol Emissions

Abstract

Agricultural aerosol emissions can significantly impact human and animal health as well as the environment. Therefore, it is essential to adopt new sensing techniques for real-time monitoring these emissions in high temporal and spatial resolution. In recent years, light detection and ranging (lidar) technology has been used for measuring the particulate matter emitted from agricultural operations. However, conventional nonpolarized lidar systems cannot discriminate between different types of aerosols, which can lead to misinterpretation of the results. To overcome this limitation, this study applies the polarization lidar technique to monitor agricultural aerosols. A 355 nm polarization lidar system was used to measure the emissions generated during pesticide spraying operations. The results showed that depolarization ratios due to field dust (0.220-0.268) and to road dust (0.385) are clearly higher than those caused by pesticide spray drift (0.028-0.043) or by diesel exhaust (0.099), which can be used to differentiate each type of aerosol. These results support the development of new polarization lidar systems specifically designed to study the impact of agricultural activities on air quality.

Assessment of spray drift potential reduction for hollow-cone nozzles: Part 2. LiDAR technique

“…The difficulties associated with dust in field measurements can be solved by wetting the soil prior to the start of a spray drift study. Another way to minimize this disturbance, is to use a polarization LiDAR system capable of discriminating between dust and spray drift as proposed by Gregorio et al (2018).…”

“…The minimum separation between the LiDAR system and the sprayer was 60 m (at the end of the sprayer displacement), thus ensuring full overlap. One of the main difficulties for the LiDAR measurement of spray drift is the presence of dust suspended in the air as a consequence of fan action and sprayer displacement, which can distort the resulting signal (Gregorio et al, 2018). To assess this effect, on July 12 dust raised by the tractor and the sprayer was measured under dry soil conditions (T1) and, after watering the soil, under wet soil conditions (T2).…”

PM emissions from open field crop management: Emission factors, assessment methods and mitigation measures – A review

“…This kind of information could be useful to answer some methodological questions, like if the PM concentration measurements are better done near or far from the emitting source (Holmén et al, 2008). A further advantage of the more recent LiDAR application is that it is possible to differentiate aerosols of different origins (Gregorio et al, 2018;Holmén et al, 2008), such as the engine exhaust plume and the soil dust plume coming from a single area source. Willis et al (2017), by coupling LiDAR measurements with PSD quantification through stationary sampler and micrometeorological measurements, were further able to calculate ER, at a whole facility scale, from LiDAR measurements.…”