DOI: 10.1016/j.atmosenv.2019.117181
论文题名: Evaluation of WRF-CMAQ simulated climatological mean and extremes of fine particulate matter of the United States and its correlation with climate extremes
作者: Li X. ; Seth A. ; Zhang C. ; Feng R. ; Long X. ; Li W. ; Liu K.
刊名: Atmospheric Environment
ISSN: 1352-2310
出版年: 2020
卷: 222 语种: 英语
英文关键词: Air pollution control
; Air quality
; Climate change
; Climate models
; Particles (particulate matter)
; Petroleum reservoir evaluation
; Quality assurance
; Aerodynamic diameters
; Air quality modeling
; Evaluation framework
; Extreme quantiles
; Fine particulate matter
; Meteorological extremes
; Model performance
; WRF-CMAQ
; Quality control
; air quality
; atmospheric chemistry
; atmospheric pollution
; climate change
; correlation
; extreme event
; forest management
; performance assessment
; policy making
; prediction
; public health
; spatiotemporal analysis
; air pollution
; air quality
; air temperature
; bootstrapping
; carbon footprint
; climate change
; controlled study
; correlational study
; forecasting
; forest management
; human
; particulate matter
; priority journal
; seasonal variation
; secondary organic aerosol
; spatiotemporal analysis
; United States
; wind speed
; United States
学科: Extreme quantile analysis
; Fine particulate matter
; Model performance
; WRF-CMAQ
中文摘要: Fine particulate matter (PM2.5, with aerodynamic diameters < 2.5 μm) pollution is one of the most pervasive air quality problems facing the world. Reliable air quality modeling of PM2.5 is essential to future air quality projection, which serves as a critical source of information for policy-making. Although various evaluation methods have been suggested to assess the capability of air quality models in reproducing PM2.5, most of studies were focused on the mean behaviors of air quality models, with little emphasis on extreme conditions, which may be more crucial for human health and climate change. To address this need, we proposed an evaluation framework in this study to characterize both mean and extreme conditions of PM2.5 and applied it to the WRF-CMAQ simulations over contiguous United States for the period of 2001–2010. Results from statistical, spatiotemporal, and extreme quantile evaluation methods show consistent good performance of the model in the Eastern U.S. However, PM2.5 mean variations and extreme trends in the western U.S. are not well represented by the model attributable to the existence of complex terrains and active fire activities. In addition, the magnitude of decreasing trends for extreme events is smaller than that for the mean PM2.5. Strong correspondence is found between PM2.5 extremes and meteorological extremes that are associated with a stagnant condition. More extreme PM2.5 pollution episodes are expected in a warming climate, with rural regions and the western U.S. suffering the most. Our results highlight the urgency for proper forest management and joint-control of air quality and carbon emissions in order to combat extreme air pollution events in the future. © 2019 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/161077
Appears in Collections: 气候变化与战略
There are no files associated with this item.
作者单位: Department of Geography, University of Connecticut, Storrs, CT 06269, United States; Department of Geosciences, University of Connecticut, Storrs, CT 06269, United States; School of Environment Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China; Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources, Chinese Academy of Sciences, Beijing, 100101, China
Recommended Citation:
Li X.,Seth A.,Zhang C.,et al. Evaluation of WRF-CMAQ simulated climatological mean and extremes of fine particulate matter of the United States and its correlation with climate extremes[J]. Atmospheric Environment,2020-01-01,222