Horizontal lidar environmental monitoring: preliminary results on tropospheric backscattering evaluation and atmospheric dispersed particulate characterisation

Lidar technology, used in remote sensing, is capable of identifying deviations in local density by triggering an alert when there is a significant change in local density levels. Such variations in the tropospheric density can be attributed to both human activities (like industrial emissions and traffic in cities) and natural events (including wildfires, the ripening of climacteric fruits, and the dispersion of volcanic ash during eruptions). Considering the limitations of many backscattering coefficient inversion algorithms in providing absolute measurements, a key issue in horizontal lidar use is establishing a baseline backscattering coefficient. This baseline is crucial not just for applying various inversion algorithms to determine backscattering and extinction values, but also for calibrating lidar systems. This study introduces a numerically validated method, supported by field experiments, for determining a baseline backscattering coefficient, which aids in relative backscattering measurements. It also establishes a link between the backscattering coefficient and meteorological factors like temperature, humidity, and visibility as part of the proposed model. The preliminary field research was conducted in an urban setting known for heavy traffic, at a height of 15 m above street level, which is the expected height for emissions dispersion.