×

People

Mohamed Layachi

Mohamed Layachi

Alumni Students, Cohort III, Undergraduate

B.E, Earth Systems Science and Environmental Engineering, Undergraduate, 06/01/2021

Cohort Level: Cohort - III

Career Goal: My plan is to pursue a masters after completing my bachelors. I would like to explore my options in the next year before I graduate as to what masters program I would pursue but I would hope that its in a related field to environmental engineering and data science/ machine learning.

Expected Graduation Date: May 22, 2021

Degree: B.E Earth Systems Science and Environmental Engineering

Research Title: Diurnal Assessment of Aerosol Optical Depth Products from GOES_ABI with AERONET for PM25 estimation

Research Synopsis: Surface fine particulate matter (PM2.5) is a significant health concern. Unfortunately, conventional monitoring of PM25 is hampered by cost which limits spatial coverage but satellites can potentially fill this spatial gap. With the recent launch of GOES16 Advanced Baseline Imager (ABI), we can extract AODs at 5 minute resolution allowing better temporal coverage over the day but questions about relating AOD to PM25 at different times of the day are critical and the main purpose of our research is to compare the diurnal error budgets of the AOD product with the error budgets we observe in comparison to the diurnal variability in PM25 estimators based on AOD retrievals.

Surface fine particulate matter (PM2.5) is a significant health concern. Unfortunately, conventional monitoring of PM25 is hampered by cost which limits spatial coverage but satellites can potentially fill this spatial gap. With the recent launch of GOES16 Advanced Baseline Imager (ABI), we can extract AODs at 5 minute resolution allowing better temporal coverage over the day but questions about relating AOD to PM25 at different times of the day are critical and the main purpose of our research is to compare the diurnal error budgets of the AOD product with the error budgets we observe in comparison to the diurnal variability in PM25 estimators based on AOD retrievals.

CESSRST Consortium

CESSRST is led by The City University of New York and brings together Hampton University, VA; University of Puerto Rico at Mayaguez, PR; San Diego State University, CA; University of Maryland Baltimore County, MD; University of Texas at El Paso, TX.