Remote sensing of PM2.5 from ground-based optical measurements

Remote sensing of particulate matter concentration with aerodynamic diameter r≤2.5μm (PM2.5) by using ground-based optical measurements of aerosols is investigated based on 6 years of hourly average measurements of aerosol optical properties, PM2.5, ceilometer backscatter coefficients and meteorological factors from Howard University Beltsville Campus facility (HUBC). The accuracy of retrievals of PM2.5 is limited by using only column-integrated aerosol optical depth (AOD). In this study, ceilometer backscatter coefficients are used to provide vertical information of aerosol. It is found that the PM2.5-AOD ratio can vary largely for different aerosol vertical distributions. The ratio is also sensitive to mode parameters of bimodal lognormal aerosol size distribution when the geometric mean radius for the fine mode is small. Using two Angstrom exponents calculated at three wavelengths of 415, 500, 860nm are found better representing aerosol size distributions than only using one Angstrom exponent. A regression model is proposed to assess the impacts of different factors on the fitting of PM2.5. Compared to using AOD only in regression model, using combination of AOD and ceilometer backscatter can prominently improve the fitting of PM2.5 especially in large AOD cases. The contribution of further introducing Angstrom coefficients is apparent in small AOD cases. Using combined measurements of AOD, ceilometer backscatter, Angstrom coefficients and surface temperature in the regression model can improve the R-squared to 0.62 from 0.44 for which only AOD is used.