Earth and Atmospheric Sciences, Department of


First Advisor

Jun Wang

Second Advisor

Qi Hu

Date of this Version

Summer 11-2016


Yue, Y., 2017: Spatial Continuous Biomass Burning Emission Inventory: Application to WRF-Chem Model over the Northern Sub-Saharan African Region. University of Nebraska-Lincoln.


A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Earth and Atmospheric Sciences, Under the Supervision of Professor Jun Wang and Professor Qi (Steve) Hu. Lincoln, Nebraska: November, 2016

Copyright © 2016 Yun Yue


Fire, as a significant global source of trace gases and aerosol particles, plays an important role in perturbations of the chemical and physical properties of the atmosphere. Fire products from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on polar-orbiting satellites Terra and Aqua are largely used in several emission inventories. However, the MODIS fire products have inherent limitations due to the following reasons: (a) they cannot detect fires underneath clouds; (b) the fire detection sensitivity decreases at the edge of MODIS scan where viewing angles and MODIS pixel sizes are bigger than at nadir; and (c) there are gaps between MODIS swaths at the ground in low latitude regions. This study develops an empirical method to remedy these limitations and applied this method to improve pixel level emission, (hereafter the new emission). Another comparison emission, “scale old” emission, was also built after multiplying the daily domain emission ratio of new and original with original emission. In order to evaluate the bias correction method, three Weather Research and Forecasting model with Chemistry (WRF-Chem) simulations were conducted using original (hereafter, old), new, and “scale old” emissions in January 2010 over the northern sub-Saharan African region. A two-day case study and assessment of the WRF-Chem simulation for one month show the new emission implementation improved the model performance especially at satellite gap and large viewing angle regions. The comparison between model simulated aerosol vertical profile and Cloud-Aerosol Lidar data with Orthogonal Polarization data also demonstrated the new emission increased the model performance.

Advisors: Jun Wang, Qi (Steve) Hu