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Article

Forecasting the Impacts of Prescribed Fires for Dynamic Air Quality Management

1
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
2
Brook Byers Institute for Sustainable Systems, Georgia Institute of Technology, Atlanta, GA 30332, USA
*
Author to whom correspondence should be addressed.
Atmosphere 2018, 9(6), 220; https://doi.org/10.3390/atmos9060220
Received: 21 April 2018 / Revised: 30 May 2018 / Accepted: 31 May 2018 / Published: 8 June 2018
(This article belongs to the Special Issue Fire and the Atmosphere)
Prescribed burning (PB) is practiced throughout the USA, most extensively in the southeast, for the purpose of maintaining and improving the ecosystem and reducing wildfire risk. However, PB emissions contribute significantly to trace gas and particulate matter loads in the atmosphere. In places where air quality is already stressed by other anthropogenic emissions, PB can lead to major health and environmental problems. We developed a PB impact forecasting system to facilitate the dynamic management of air quality by modulating PB activity. In our system, a new decision tree model predicts burn activity based on the weather forecast and historic burning patterns. Emission estimates for the forecast burn activity are input into an air quality model, and simulations are performed to forecast the air quality impacts of the burns on trace gas and particulate matter concentrations. An evaluation of the forecasts for two consecutive burn seasons (2015 and 2016) showed that the modeling system has promising forecasting skills that can be further improved with refinements in burn area and plume rise estimates. Since 2017, air quality and burn impact forecasts are being produced daily with the ultimate goal of incorporating them into the management of PB operations. View Full-Text
Keywords: burn activity forecasting; burn area; fire emissions; classification and regression tree (CART); community multiscale air quality (CMAQ) model; decoupled direct method (DDM); forecast evaluation; PM2.5; prescribed burning; satellite detection burn activity forecasting; burn area; fire emissions; classification and regression tree (CART); community multiscale air quality (CMAQ) model; decoupled direct method (DDM); forecast evaluation; PM2.5; prescribed burning; satellite detection
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MDPI and ACS Style

Odman, M.T.; Huang, R.; Pophale, A.A.; Sakhpara, R.D.; Hu, Y.; Russell, A.G.; Chang, M.E. Forecasting the Impacts of Prescribed Fires for Dynamic Air Quality Management. Atmosphere 2018, 9, 220. https://doi.org/10.3390/atmos9060220

AMA Style

Odman MT, Huang R, Pophale AA, Sakhpara RD, Hu Y, Russell AG, Chang ME. Forecasting the Impacts of Prescribed Fires for Dynamic Air Quality Management. Atmosphere. 2018; 9(6):220. https://doi.org/10.3390/atmos9060220

Chicago/Turabian Style

Odman, M. T., Ran Huang, Aditya A. Pophale, Rushabh D. Sakhpara, Yongtao Hu, Armistead G. Russell, and Michael E. Chang. 2018. "Forecasting the Impacts of Prescribed Fires for Dynamic Air Quality Management" Atmosphere 9, no. 6: 220. https://doi.org/10.3390/atmos9060220

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