Abstract
Abstract. Monitoring PM2.5 (particulate matter with aerodynamic diameter d ≤ 2.5 µm) mass concentration has become of more importance recently because of the negative impacts of fine particles on human health. However, monitoring PM2.5 during cloudy and nighttime periods is difficult since nearly all the passive instruments used for aerosol remote sensing are not able to measure aerosol optical depth (AOD) under either cloudy or nighttime conditions. In this study, an empirical model based on the regression between PM2.5 and the near-surface backscatter measured by ceilometers was developed and tested using 6 years of data (2006 to 2011) from the Howard University Beltsville Campus (HUBC) site. The empirical model can explain ∼ 56, ∼ 34 and ∼ 42 % of the variability in the hourly average PM2.5 during daytime clear, daytime cloudy and nighttime periods, respectively. Meteorological conditions and seasons were found to influence the relationship between PM2.5 mass concentration and the surface backscatter. Overall the model can explain ∼ 48 % of the variability in the hourly average PM2.5 at the HUBC site when considering the seasonal variation. The model also was tested using 4 years of data (2012 to 2015) from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, which was geographically and climatologically different from the HUBC site. The results show that the empirical model can explain ∼ 66 and ∼ 82 % of the variability in the daily average PM2.5 at the ARM SGP site and HUBC site, respectively. The findings of this study illustrate the strong need for ceilometer data in air quality monitoring under cloudy and nighttime conditions. Since ceilometers are used broadly over the world, they may provide an important supplemental source of information of aerosols to determine surface PM2.5 concentrations.
Highlights
The adverse impacts of high PM2.5 mass concentration on human health have been found from epidemiological studies around the world (Samet et al, 2000; Pope et al, 2009; Krewski et al, 2009)
Under daytime clear-sky conditions when Aerosol optical depth (AOD) measurements from the Multifilter Rotating Shadowband Radiometer (MFRSR) are available, www.atmos-meas-tech.net/10/2093/2017/
Remote sensing of PM2.5 is generally based on AOD measurements due to its strong relationship with PM2.5
Summary
The adverse impacts of high PM2.5 (particulate matter with aerodynamic diameter d ≤ 2.5 μm) mass concentration on human health have been found from epidemiological studies around the world (Samet et al, 2000; Pope et al, 2009; Krewski et al, 2009). There are extensive studies investigating the PM2.5–AOD relationship by the use of either an empirical statistical method (Engel-Cox et al, 2004; Liu et al, 2005, 2009; Gupta et al, 2006; Koelemeijer et al, 2006; Gupta and Christopher, 2008; Paciorek et al, 2008; Di Nicolantonio et al, 2009; Schaap et al, 2009; Lee et al, 2012; Sorek-Hamer et al, 2013; Strawa et al, 2013; Chudnovsky et al, 2014; Hu et al, 2013, 2014; Ma et al, 2014) or a chemical transportation model (Liu et al, 2004; Van Donkelaar et al, 2006, 2010; Kessner et al, 2013; Xu et al, 2015) In these studies, aerosol vertical distributions are estimated based on model simulation or under an assumption that aerosols are well mixed within the boundary layer and decrease exponentially with height.
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