Share Email Print

Proceedings Paper

Validation of smoke plume rise models using ground-based Lidar
Author(s): V. Kovalev; S. Urbanski; A. Petkov; A. Scalise; C. Wold; W. M. Hao
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Biomass fires can significantly degrade regional air quality through the emission of primary aerosols and the photochemical production of ozone and secondary aerosols. The injection height of smoke from biomass burning into the atmosphere (‘plume rise height’) is one of the critical factors in determining the impact of fire emissions on air quality. Plume rise models are used to simulate plume rise height and prescribe the vertical distribution of fire emissions for input to smoke dispersion and air quality models. While several plume rise models exist, their uncertainties, biases, and application limits when applied to biomass fires are not well characterized. The poor state of model evaluation is due in large part to a lack of appropriate observational datasets. We have initiated a research project to address this critical observation gap. In August of 2013 we performed a multi-agency field experiment designed to obtain the data necessary to improve the air quality models used by agricultural smoke managers in the northwestern United States. In the experiment, the ground-based mobile lidar, developed at the US Forest Service Missoula Fire Science Laboratory, was used to monitor plume rise heights for nine agricultural fires in the northwestern United States. The lidar measurements were compared with plume rise heights calculated with the Briggs equations, which are used in several smoke management tools. Here we present the preliminary evaluation results and provide recommendations regarding the application of the models to agricultural burning based on lidar measurements made in the vicinity of Walla Walla, Washington, on August 24, 2013.

Paper Details

Date Published: 21 October 2014
PDF: 9 pages
Proc. SPIE 9239, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI, 92391S (21 October 2014); doi: 10.1117/12.2066895
Show Author Affiliations
V. Kovalev, U.S. Forest Service (United States)
S. Urbanski, U.S. Forest Service (United States)
A. Petkov, U.S. Forest Service (United States)
A. Scalise, U.S. Forest Service (United States)
C. Wold, U.S. Forest Service (United States)
W. M. Hao, U.S. Forest Service (United States)

Published in SPIE Proceedings Vol. 9239:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI
Christopher M. U. Neale; Antonino Maltese, Editor(s)

© SPIE. Terms of Use
Back to Top