Abstract
Haze is hazardous to human health. Although horizontal scanning LIDARs have been used to monitor air pollution sources, they have not been used for haze detection. In this work, we present a numerical model for haze detection using horizontal scanning LIDAR by incorporating multiple scattering theory. This model could evaluate whether multiple scattering theory is suitable for analyzing horizontal scanning LIDAR readings to detect haze without assembling LIDARs. We demonstrate this using a hypothetical LIDAR that has maximum horizontal range of 1 km as case study example. In our assessment, Python™ was used to develop simulation algorithm based on single and multiple scattering LIDAR equations. Relative humidity was below 80% which corresponded to potential haze. Visibility data at different haze levels were incorporated for analysis. We then evaluated errors in hypothetical LIDAR readings associated with multiple scattering. Lastly, we calculated ratios of multiple scattering returns in haze relative to clear weather as haze level indicators. Numerical assessment showed that multiple scattering effects were negligible for both wavelength channels (532 nm and 808 nm) at receiver field-of-view (RFOV) of 1.5 mrad, but introduced significant errors when RFOV is 10 mrad. Average ratio of multiple scattering returns evaluated against threshold of 1 could directly reflect the severity of haze. Although this approach was not suitable for heavy and severe haze, it sufficed for practical applications. Overall, the case study demonstrated the feasibility of incorporating multiple scattering theory when analyzing horizontal scanning LIDAR readings to detect haze without experimental verification.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.