Articles | Volume 9, issue 3
Atmos. Meas. Tech., 9, 1369–1376, 2016
https://doi.org/10.5194/amt-9-1369-2016
Atmos. Meas. Tech., 9, 1369–1376, 2016
https://doi.org/10.5194/amt-9-1369-2016

Research article 01 Apr 2016

Research article | 01 Apr 2016

Profiling the PM2.5 mass concentration vertical distribution in the boundary layer

Zongming Tao et al.

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Cited articles

An, J., Zhang, R., and Han, Z.: Seasonal changes of total suspended particles in the air of 15 big cities in northern parts of China, Climatic and Environmental Research, 5, 25–29, 2000.
Bernes, J. E., Bronner, S., and Becket, R.: Boundary layer scattering measurements with a charge-coupled device camera lidar , Appl. Optics, 42, 2647–2652, 2003.
Bo, G., Liu, D., and Wu, D.: Two-wavelength lidar for observation of aerosol optical and hygroscopic properties in fog and haze days, Chinese Journal of Lasers, 41, 0113001, https://doi.org/10.3788/cjl201441.0113001, 2014.
Che, H., Xia, X., Zhu, J., Wang, H. Wang, Y., Sun, J., Zhang, X., and Shi, G.: Aerosol optical properties under the condition of heavy haze over an urban site of Beijing, China, Environ. Sci. Pollut. R., 22, 1043–1053, https://doi.org/10.1007/s11356-014-3415-5, 2015.
Cordero, L., Wu, Y., Gross, B. M., and Moshary, F.: Use of passive and active ground and satellite remote sensing to monitor fine particulate pollutants on regional scales, Advance environmental, chemical, and Biological sensing technologies IX, Proc. Of SPIE, 8366, 83660M, 2012.
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Short summary
A new measurement technology of PM2.5 mass concentration profile near ground is addressed using a CCD side-scatter lidar and a PM2.5 detector. The PM2.5 mass concentration profile can be built upon the vertical distribution of the extinction coefficient for aerosol. The PM2.5 is always loading in the planet boundary layer with a complex muti-layer structure. The new method for PM2.5 mass concentration profile is useful for improving our understanding of air quality and atmospheric environment.