In the industry, different approaches are put in place to minimize as much as possible the emissions of dust. These include scrubbers, enclosures or application of dust suppressants. However some dust generating processes do not allow efficient dust suppression. Dust generated during processes like ship loading and unloading or blasts during mining operations can hardly be controlled and suppressed. In these cases, modulating the operations based on weather conditions can be the best approach to minimize the impact of dust generation to neighboring sites. In this scenario, reliable data for predicting dust propagation are required and a limited number of point sensors is not sufficient. To address the need of reliable and distributed data, a medium range (＜500 m) dust mapping sensor based on a digital LiDAR (Light Detection And Ranging) system was developed. The compact eye-safe system is mounted on a robust tripod allowing for 2D/3D mapping of the environment. The digitized backscattered laser signals are processed to obtain a 2D/3D maps of relative concentration. When combined with calibrated point sensor measurements, the 2D/3D maps are converted to absolute concentration maps. The recent system improvements will be presented, which includes real-time LiDAR signal calibration for absolute concentration reporting, autonomous dust events detection within user specified region of interest and alarm broadcasting from these events. Several application-specific tests have been performed. The latest of these was real-time monitoring of fugitive dust emissions from cargo raw material unloading. The LiDAR was installed at a port where raw material unloading was generating clouds of dust and where wind transportation is an issue for nearby residents. Real-time dust monitoring capabilities were shown to provide valuable information and dust control management efforts (before/after dust management countermeasures) were quantified for improving industrial processes towards better air quality.
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