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Deriving Optical Properties of Urban Aerosols in North Carolina

Graduate #68
Discipline: Ecology Environmental and Earth Sciences
Subcategory: Geosciences and Earth Sciences

Andre Jones - North Carolina Central University


Study has presented a high potential of utilizing MODIS Satellite Imagery to monitor PM2.5 at regional scale. However, this approach is often challenged by the lack of strong correlation between ground PM2.5 measurements and AOD values from MODIS imagery because of the usage of universal optical properties in the collection of AOD. The objective of this research is to derive optical properties of local urban aerosols and develop a new AOD retrieval approach at a 1-km resolution from MODIS satellite imagery in order to help improve poor AOD-PM2.5 correlation in North Carolina. MICROTOPS II Sun-photometer was used for ground AOD collection and AEROCET 831 was used for ground PM2.5 collection. Data collection was cycled through 5 specific locations chosen by environment and social attributes (Commercial, Suburban, Industrial, and Traffic Area) on ‘clear-sky’ days due to distortion of data that can occur from cloud cover or precipitation. Measured AOD data was used an input to OPAC with other data including humidity and mass concentration of PM2.5. Then OPAC was used to retrieve microphysical parameters including the Angstrom exponent, the single scattering albedo, the asymmetry parameter and the phase function. The next step involves generating a new AOD dataset (at 1-km resolution) from MODIS L 1B data using the modified C005-L algorithm and then deriving missing values of pixels using Kriging interpolation method. Variation in spatial and seasonal distribution of the measured AOD and optical parameters were found in the data study. A new correlation coefficient was also developed of AOD-PM2.5 correlation in NC after utilizing local optical parameters and incorporating meteorological parameters. It is expected that our findings will help develop a new approach to significantly improve AOD-PM2.5 correlation in NC.

Funder Acknowledgement(s): My Research Project is funded by NSF.

Faculty Advisor: Zhiming Yang, zyang@nccu.edu

Role: All of the submitted research is my work.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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