DOI: 10.1016/j.atmosenv.2016.09.010
Scopus记录号: 2-s2.0-84996536597
论文题名: Evaluation of fire weather forecasts using PM2.5 sensitivity analysis
作者: Balachandran S ; , Baumann K ; , Pachon J ; E ; , Mulholland J ; A ; , Russell A ; G
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2017
卷: 148 起始页码: 128
结束页码: 138
语种: 英语
英文关键词: Fine particulate matter
; Forest ecosystem management
; PM2.5
; Prescribed fires
; Sensitivity
; Source apportionment
Scopus关键词: Atmospheric movements
; Ecology
; Ecosystems
; Fires
; Forecasting
; Managers
; Particles (particulate matter)
; Precipitation (meteorology)
; Principal component analysis
; Rain
; Sensitivity analysis
; Fine particulate matter
; Forest ecosystem management
; PM2.5
; Prescribed fires
; Sensitivity
; Source apportionment
; Weather forecasting
; aerosol
; data set
; ecosystem management
; fire
; forest ecosystem
; humidity
; particle size
; particulate matter
; precipitation (climatology)
; prescribed burning
; sensitivity analysis
; temperature
; weather forecasting
; aerosol
; air quality
; Article
; forecasting
; humidity
; meteorology
; particulate matter
; precipitation
; prescribed burning
; principal component analysis
; priority journal
; sensitivity analysis
; temperature
; weather
; Florida [United States]
; Jacksonville
; United States
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: Fire weather forecasts are used by land and wildlife managers to determine when meteorological and fuel conditions are suitable to conduct prescribed burning. In this work, we investigate the sensitivity of ambient PM2.5 to various fire and meteorological variables in a spatial setting that is typical for the southeastern US, where prescribed fires are the single largest source of fine particulate matter. We use the method of principle components regression to estimate sensitivity of PM2.5, measured at a monitoring site in Jacksonville, NC (JVL), to fire data and observed and forecast meteorological variables. Fire data were gathered from prescribed fire activity used for ecological management at Marine Corps Base Camp Lejeune, extending 10–50 km south from the PM2.5 monitor. Principal components analysis (PCA) was run on 10 data sets that included acres of prescribed burning activity (PB) along with meteorological forecast data alone or in combination with observations. For each data set, observed PM2.5 (unitless) was regressed against PCA scores from the first seven principal components (explaining at least 80% of total variance). PM2.5 showed significant sensitivity to PB: 3.6 ± 2.2 μg m−3 per 1000 acres burned at the investigated distance scale of ∼10–50 km. Applying this sensitivity to the available activity data revealed a prescribed burning source contribution to measured PM2.5 of up to 25% on a given day. PM2.5 showed a positive sensitivity to relative humidity and temperature, and was also sensitive to wind direction, indicating the capture of more regional aerosol processing and transport effects. As expected, PM2.5 had a negative sensitivity to dispersive variables but only showed a statistically significant negative sensitivity to ventilation rate, highlighting the importance of this parameter to fire managers. A positive sensitivity to forecast precipitation was found, consistent with the practice of conducting prescribed burning on days when rain can naturally extinguish fires. Perhaps most importantly for land managers, our analysis suggests that instead of relying on the forecasts from a day before, prescribed burning decisions should be based on the forecasts released the morning of the burn when possible, since these data were more stable and yielded more statistically robust results. © 2016 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/82702
Appears in Collections: 气候变化事实与影响
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作者单位: Georgia Institute of Technology, School of Civil and Environmental Engineering, Atlanta, GA, United States; Atmospheric Research and Analysis, Inc., Morrisville, NC, United States; Universidad de La Salle, Programa de Ingenieria Ambiental, Bogota, Colombia; University of Cincinnati, Department of Biomedical, Chemical and Environmental Engineering, Cincinnati, OH, United States
Recommended Citation:
Balachandran S,, Baumann K,, Pachon J,et al. Evaluation of fire weather forecasts using PM2.5 sensitivity analysis[J]. Atmospheric Environment,2017-01-01,148