globalchange  > 全球变化的国际研究计划
DOI: 10.5194/gmd-12-3283-2019
WOS记录号: WOS:000477627500001
论文题名:
The FireWork v2.0 air quality forecast system with biomass burning emissions from the Canadian Forest Fire Emissions Prediction System v2.03
作者: Chen, Jack1; Anderson, Kerry2; Pavlovic, Radenko3; Moran, Michael D.1; Englefield, Peter2; Thompson, Dan K.2; Munoz-Alpizar, Rodrigo3; Landry, Hugo3
通讯作者: Chen, Jack
刊名: GEOSCIENTIFIC MODEL DEVELOPMENT
ISSN: 1991-959X
EISSN: 1991-9603
出版年: 2019
卷: 12, 期:7, 页码:3283-3310
语种: 英语
WOS关键词: HORSE RIVER WILDFIRE ; OIL SANDS REGION ; CARBON EMISSIONS ; HEALTH IMPACTS ; UNITED-STATES ; PLUME-RISE ; FUEL CONSUMPTION ; INJECTION HEIGHT ; CROP RESIDUE ; SMOKE
WOS学科分类: Geosciences, Multidisciplinary
WOS研究方向: Geology
英文摘要:

Biomass burning activities can produce large quantities of smoke and result in adverse air quality conditions in regional environments. In Canada, the Environment and Climate Change Canada (ECCC) operational FireWork (v1.0) air quality forecast system incorporates near-real-time biomass burning emissions to forecast smoke plumes from fire events. The system is based on the ECCC operational Regional Air Quality Deterministic Prediction System (RAQDPS) augmented with near-real-time wildfire emissions using inputs from the Canadian Forest Service (CFS) Canadian Wildland Fire Information System (CWFIS). Recent improvements to the representation of fire behaviour and fire emissions have been incorporated into the CFS Canadian Forest Fire Emissions Prediction System (CFFEPS) v2.03. This is a bottom-up system linked to CWFIS in which hourly changes in biomass fuel consumption are parameterized with hourly forecasted meteorology at fire locations. CFFEPS has now also been connected to FireWork. In addition, a plumerise parameterization based on fire-energy thermodynamics is used to define the smoke injection height and the distribution of emissions within a model vertical column. The new system, FireWork v2.0 (FireWork-CFFEPS), has been evaluated over North America for July-September 2017 and June-August 2018, which are both periods when western Canada experienced historical levels of fire activity with poor air quality conditions in several cities as well as other fires affecting northern Canada and Ontario. Forecast results were evaluated against hourly surface measurements for the three pollutant species used to calculate the Canadian Air Quality Health Index (AQHI), namely PM2.5, O-3, and NO2, and benchmarked against the operational FireWork v1.0 system (FireWork-Ops). This comparison shows improved forecast performance and predictive skills for the FireWork-CFFEPS system. Modelled fire-plume injection heights from CFFEPS based on fire-energy thermodynamics show higher plume injection heights and larger variability. The changes in predicted fire emissions and injection height reduced the consistent over-predictions of PM2.5 and O-3 seen in FireWork-Ops. On the other hand, there were minimal fire emission contributions to surface NO2, and results from FireWork-CFFEPS do not degrade NO2 forecast skill compared to the RAQDPS. Model performance statistics are slightly better for Canada than for the US, with lower errors and biases. The new system is still unable to capture the hourly variability of the observed values for PM2.5, but it captured the observed hourly variability for O-3 concentration adequately. FireWork-CFFEPS also improves upon FireWork-Ops categorical scores for forecasting the occurrence of elevated air pollutant concentrations in terms of false alarm ratio (FAR) and critical success index (CSI).


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/143780
Appears in Collections:全球变化的国际研究计划

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作者单位: 1.Environm & Climate Change Canada, Air Qual Res Div, Ottawa, ON, Canada
2.Nat Resources Canada, Canadian Forest Serv, Ottawa, ON, Canada
3.Environm & Climate Change Canada, Air Qual Modelling Applicat Sect, Gatineau, PQ, Canada

Recommended Citation:
Chen, Jack,Anderson, Kerry,Pavlovic, Radenko,et al. The FireWork v2.0 air quality forecast system with biomass burning emissions from the Canadian Forest Fire Emissions Prediction System v2.03[J]. GEOSCIENTIFIC MODEL DEVELOPMENT,2019-01-01,12(7):3283-3310
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