Three-Dimensional atmospheric chemical transport models are utilized to investigate impacts of fire emissions on ground-level PM2.5 total mass concentrations. Currently, climatologically-based fire emissions, including wild, prescribed, and agricultural fires, obtained from the NEI (National Emission Inventory) have been generally used to simulate impacts on air quality from these emission sources. Climatologically-based fire emissions make a significant contribution to PM components (especially in carbonaceous species); however, they have a critical limitation due to high irregularity of fire events, unrealistic distribution in location of sources and their temporal and spatial variability without consideration of land types and weather conditions. In addition, county-level fire emission inventories in NEI are treated as area sources but should be modeled as point sources with certain locations to achieve more accurate forecasts from air quality models. NOAA's (National Oceanic and Atmospheric Administration) NAQFC (National Air Quality Forecasting Capability) developmental version, which utilizes the CMAQ 4.7.1 (Community Multiscale Air Quality) model, was used to simulate the period from April to June, 2010 in this study. Simulations were performed with 4 fire emission scenarios: 1) no fire emissions, 2) NEI fire emissions with the traditional climatologically-based method, 3) NEI fire emissions with weighting method on land types and weather condition to produce better temporal and spatial distribution of fire estimates, and 4) emissions with satellite-detected real fire events. The goal of this study is to see the impacts of the improved fire emissions on PM2.5 and its species predictions over the conterminous U.S. (CONUS) domain. Observed PM2.5 mass and speciation data for the periods of April to June 2010 from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network will be compared with results from the model. This study will assess the influence of more realistic fire emissions on forecasting PM2.5 concentrations.