Application of a statistical emulator to fire emission modeling. (November 2015)

• Record Type: Journal Article
• Authors: Katurji, Marwan; Nikolic, Jovanka; Zhong, Shiyuan; Pratt, Scott; Yu, Lejiang; Heilman, Warren E.
• Is Part Of: Environmental modelling & software. Volume 73(2015:Nov.)
• Page Start: 254
• Page End: 259
• Publication Date: 2015-11
• Subjects: Fire emission -- Statistical emulator -- Simulator -- FEPS -- Emission prediction -- Gaussian processes; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.08.016
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: We have demonstrated the use of an advanced Gaussian-Process (GP) emulator to estimate wildland fire emissions over a wide range of fuel and atmospheric conditions. The Fire Emission Production Simulator, or FEPS, is used to produce an initial set of emissions data that correspond to some selected values in the domain of the input fuel and atmospheric parameters for the purpose of training the emulator. The emulated emissions are found to be within ±5% of the FEPS simulated emissions, providing confidence in the potential use of the GP-emulator for this and other similar applications. Cluster analysis for 1000 emulator-produced posterior samples spanning a wide-range of fuel and environmental conditions suggest that the emulator not only produces valid results but also preserves the physical relationships between the fire emission and the fuel and environmental conditions. Results show that the GP-emulator could be used as an alternative to the simulations from the FEPS modeling system when four or more input parameters related to fuel type, fuel moisture, and weather condition are allowed to vary. This work also provides a conceptual basis for constructing a nation-wide emissions inventory based on a trained GP-emulator representing the complex geographic distribution of fuel types and environmental conditions. Highlights: We emulate a fire emission model (FEPS) with a Gaussian process emulator. Results are within ±5% of the simulated values. GP-emulator could be used as a surrogate to the fire emission model. A conceptual framework for producing nation-wide emission inventory is presented.