Paper
9 May 2012 Use of passive and active ground and satellite remote sensing to monitor fine particulate pollutants on regional scales
Author Affiliations +
Abstract
This paper explores the performance of current remote sensing methods for estimation of fine particulate matter (PM2.5, diameter < 2.5μm) in the New York City area (40.821°N, 73.949°W) during 2010. We analyze the relationship between surface PM2.5 mass concentration and column aerosol optical depth (AOD) at 500-nm by using the synergy measurements of surface in-situ, AERONET-sunphotometer, lidar and NOAA-GOES satellite. The regression slopes and correlation coefficients between PM2.5 and AOD show the good performance in summer and indicate dramatic monthly variation which are associated with the seasonal differences of PBL-heights, fine-mode contribution to the total AOD and aerosol volume-to-extinction ratio. Additionally, the relationship of PM2.5 and fine-mode AOD shows higher correlations than the PM2.5 and total AOD (R2 total = 0.5011, R2 fine = 0.6132, R2 coarse = -0.0235). Also, when considering the lidar-derived PBL-heights in the different months and removing aloft layer and cloudy cases, the PM2.5 estimations using AOD show improvements during the cold months; furthermore, the correction on aerosol volume-to-extinction ratio results in better estimations of fine particulate matter concentrations and therefore confirms the importance of including these parameters into air quality models. Moreover, the AOD data from NOAA-Geostationary Operational Environmental Satellites (GOES) are initially evaluated by comparing with AERONET-AOD, and further illustrate the good correlation with PM2.5 concentration.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lina Cordero, Yonghua Wu, Barry M. Gross, and Fred Moshary "Use of passive and active ground and satellite remote sensing to monitor fine particulate pollutants on regional scales", Proc. SPIE 8366, Advanced Environmental, Chemical, and Biological Sensing Technologies IX, 83660M (9 May 2012); https://doi.org/10.1117/12.918765
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Aerosols

Satellites

LIDAR

Particles

Remote sensing

Phase modulation

Atmospheric modeling

Back to Top