Regionalized PM2.5 Community Multiscale Air Quality Model Performance Evaluation Across a Continuous Spatiotemporal Domain
Peer Reviewed
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2017/01/01
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Personal Author:
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Description:The regulatory Community Multiscale Air Quality (CMAQ) model is a means to understanding the sources, concentrations and regulatory attainment of air pollutants within a model's domain. Substantial resources are allocated to the evaluation of model performance. The Regionalized Air quality Model Performance (RAMP) method introduced here explores novel ways of visualizing and evaluating CMAQ model performance and errors for daily Particulate Matter = 2.5 micrometers (PM2.5) concentrations across the continental United States. The RAMP method performs a non-homogenous, non-linear, non-homoscedastic model performance evaluation at each CMAQ grid. This work demonstrates that CMAQ model performance, for a well-documented 2001 regulatory episode, is non-homogeneous across space/time. The RAMP correction of systematic errors outperforms other model evaluation methods as demonstrated by a 22.1% reduction in Mean Square Error compared to a constant domain wide correction. The RAMP method is able to accurately reproduce simulated performance with a correlation of r = 76.1%. Most of the error coming from CMAQ is random error with only a minority of error being systematic. Areas of high systematic error are collocated with areas of high random error, implying both error types originate from similar sources. Therefore, addressing underlying causes of systematic error will have the added benefit of also addressing underlying causes of random error. Description provided by NIOSH
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Subjects:
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Keywords:
- Atmosphere
- Particulates
- Air quality
- Analytical models
- Air pollutants
- Emission sources
- Models
- Performance capability
- Regulatory activities
- Air pollution
- Air pollution sampling
- Air monitoring
- Air quality measurement
- Air quality monitoring
- Air quality control
- Simulation methods
- Environmental monitoring
- Environmental pollution
- Environmental technology
- Data processing
- Author Keywords: Model performance evaluation
- Regulatory modeling
- PM2.5
- CMAQ
- Modeled data
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ISSN:1352-2310
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Pages in Document:258-265
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Volume:148
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NIOSHTIC Number:nn:20050606
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Citation:Atmos Environ 2017 Jan; 148:258-265
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Contact Point Address:Marc L. Serre, Department of Environmental Sciences and Engineering, UNC, 135 Dauer Drive, Chapel Hill, NC 27599-7431, United States
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Email:marc_serre@unc.edu
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Federal Fiscal Year:2017
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Performing Organization:University of North Carolina, Chapel Hill
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Peer Reviewed:True
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Start Date:20050701
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Source Full Name:Atmospheric Environment
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End Date:20270630
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Main Document Checksum:urn:sha-512:2d51e12f3fdd6fe3cf90bb2f7de82c87c9d820b3badff1df7f4a4d9cd5293bf3134a40943ff05776dbe3992fcd3dcc03d07033b6729372885b98bc8b4c76a624
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