Shahzad, MI; Nichol, JE; Wang, J; Campbell, JR; Chan, PW (2013). Estimating surface visibility at Hong Kong from ground-based LIDAR, sun photometer and operational MODIS products. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION, 63(9), 1098-1110.
Hong Kong's surface visibility has decreased in recent years due to air pollution from rapid social and economic development in the region. In addition to deteriorating health standards, reduced visibility disrupts routine civil and public operations, most notably transportation and aviation. Regional estimates of visibility solved operationally using available ground and satellite-based estimates of aerosol optical properties and vertical distribution may prove more effective than standard reliance on a few existing surface visibility monitoring stations. Previous studies have demonstrated that such satellite measurements correlate well with near-surface optical properties, despite these sensors do not consider range-resolved information and indirect parameterizations necessary to solve relevant parameters. By expanding such analysis to include vertically resolved aerosol profile information from an autonomous ground-based lidar instrument, this work develops six models for automated assessment of surface visibility. Regional visibility is estimated using co-incident ground-based lidar, sun photometer, visibility meter, and MODerate-resolution maging Spectroradiometer (MODIS) aerosol optical depth data sets. Using a 355 nm extinction coefficient profile solved from the lidar, MODIS AOD (aerosol optical depth) is scaled down to the surface to generate a regional composite depiction of surface visibility. These results demonstrate the potential for applying passive satellite depictions of broad-scale aerosol optical properties together with a ground-based surface lidar and zenith-viewing sun photometer for improving quantitative assessments of visibility in a city such as Hong Kong. Implications: The study presents methods to estimate surface level visibility using remote sensing techniques, thus reducing the cost and effort required to estimate visibility at regional level. This helps to address environmental and health effects of ambient air pollution related to visibility for areas with no existing air quality monitoring stations. Policy regulation and hazard assessments impacting transportation and navigation can be improved by integrating the remotely estimated surface visibility with a real-time environmental data network.