NAQFC Developmental Forecast Guidance for Fine Particulate Matter (PM2.5)
The National Air Quality Forecasting Capability (NAQFC) upgraded its modeling system that provides developmental numerical predictions of particulate matter smaller than 2.5 μm in diameter (PM2.5) in January 2015. The issuance of PM2.5 forecast guidance has become more punctual and reliable because...
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creator | Lee, Pius McQueen, Jeffery Stajner, Ivanka Huang, Jianping Pan, Li Tong, Daniel Kim, Hyuncheol Tang, Youhua Kondragunta, Shobha Ruminski, Mark Lu, Sarah Rogers, Eric Saylor, Rick Shafran, Perry Huang, Ho-Chun Gorline, Jerry Upadhayay, Sikchya Artz, Richard |
description | The National Air Quality Forecasting Capability (NAQFC) upgraded its modeling system that provides developmental numerical predictions of particulate matter smaller than 2.5 μm in diameter (PM2.5) in January 2015. The issuance of PM2.5 forecast guidance has become more punctual and reliable because developmental PM2.5 predictions are provided from the same system that produces operational ozone predictions on the National Centers for Environmental Prediction (NCEP) supercomputers.
There were three major upgrades in January 2015: 1) incorporation of real-time intermittent sources for particles emitted from wildfires and windblown dust originating within the NAQFC domain, 2) suppression of fugitive dust emissions from snow- and/or ice-covered terrain, and 3) a shorter life cycle for organic nitrate in the gaseous-phase chemical mechanism. In May 2015 a further upgrade for emission sources was included using the U.S. Environmental Protection Agency’s (EPA) 2011 National Emission Inventory (NEI). Emissions for ocean-going ships and on-road mobile sources will continue to rely on NEI 2005.
Incremental tests and evaluations of these upgrades were performed over multiple seasons. They were verified against the EPA’s AIRNow surface monitoring network for air pollutants. Impacts of the three upgrades on the prediction of surface PM2.5 concentrations show large regional variability: the inclusion of windblown dust emissions in May 2014 improved PM2.5 predictions over the western states and the suppression of fugitive dust in January 2015 reduced PM2.5 bias by 52%, from 6.5 to 3.1 μg m−3 against a monthly average of 9.4 μg m−3 for the north-central United States. |
doi_str_mv | 10.1175/WAF-D-15-0163.1 |
format | Article |
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There were three major upgrades in January 2015: 1) incorporation of real-time intermittent sources for particles emitted from wildfires and windblown dust originating within the NAQFC domain, 2) suppression of fugitive dust emissions from snow- and/or ice-covered terrain, and 3) a shorter life cycle for organic nitrate in the gaseous-phase chemical mechanism. In May 2015 a further upgrade for emission sources was included using the U.S. Environmental Protection Agency’s (EPA) 2011 National Emission Inventory (NEI). Emissions for ocean-going ships and on-road mobile sources will continue to rely on NEI 2005.
Incremental tests and evaluations of these upgrades were performed over multiple seasons. They were verified against the EPA’s AIRNow surface monitoring network for air pollutants. Impacts of the three upgrades on the prediction of surface PM2.5 concentrations show large regional variability: the inclusion of windblown dust emissions in May 2014 improved PM2.5 predictions over the western states and the suppression of fugitive dust in January 2015 reduced PM2.5 bias by 52%, from 6.5 to 3.1 μg m−3 against a monthly average of 9.4 μg m−3 for the north-central United States.</description><identifier>ISSN: 0882-8156</identifier><identifier>EISSN: 1520-0434</identifier><identifier>DOI: 10.1175/WAF-D-15-0163.1</identifier><language>eng</language><publisher>Boston: American Meteorological Society</publisher><subject>Accuracy ; Air monitoring ; Air pollution ; Air quality ; Air quality forecasting ; Airborne particulates ; Atmospheric particulates ; Atmospheric sciences ; Deforestation ; Dust ; Dust storms ; Emission ; Emission inventories ; Environmental monitoring ; Environmental protection ; Ice ; Ice cover ; Information science ; Laboratories ; Life cycle ; Life cycle engineering ; Life cycles ; Mathematical models ; Modelling ; Nitrates ; Outdoor air quality ; Ozone ; Particulate emissions ; Particulate matter ; Pollutants ; Pollution monitoring ; Pollution sources ; Protection ; Seasons ; Ships ; Snow ; Spatial variations ; Supercomputers ; Suspended particulate matter ; Terrain ; Tests ; Upgrading ; Variability ; Weather forecasting ; Wildfires</subject><ispartof>Weather and forecasting, 2017-02, Vol.32 (1), p.343-360</ispartof><rights>Copyright American Meteorological Society Feb 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c269t-5b9e051328cf6302a66f40c1a3f3f48159c553126ea4dbe0298b794083c79e753</citedby><cites>FETCH-LOGICAL-c269t-5b9e051328cf6302a66f40c1a3f3f48159c553126ea4dbe0298b794083c79e753</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,3667,27903,27904</link.rule.ids></links><search><creatorcontrib>Lee, Pius</creatorcontrib><creatorcontrib>McQueen, Jeffery</creatorcontrib><creatorcontrib>Stajner, Ivanka</creatorcontrib><creatorcontrib>Huang, Jianping</creatorcontrib><creatorcontrib>Pan, Li</creatorcontrib><creatorcontrib>Tong, Daniel</creatorcontrib><creatorcontrib>Kim, Hyuncheol</creatorcontrib><creatorcontrib>Tang, Youhua</creatorcontrib><creatorcontrib>Kondragunta, Shobha</creatorcontrib><creatorcontrib>Ruminski, Mark</creatorcontrib><creatorcontrib>Lu, Sarah</creatorcontrib><creatorcontrib>Rogers, Eric</creatorcontrib><creatorcontrib>Saylor, Rick</creatorcontrib><creatorcontrib>Shafran, Perry</creatorcontrib><creatorcontrib>Huang, Ho-Chun</creatorcontrib><creatorcontrib>Gorline, Jerry</creatorcontrib><creatorcontrib>Upadhayay, Sikchya</creatorcontrib><creatorcontrib>Artz, Richard</creatorcontrib><title>NAQFC Developmental Forecast Guidance for Fine Particulate Matter (PM2.5)</title><title>Weather and forecasting</title><description>The National Air Quality Forecasting Capability (NAQFC) upgraded its modeling system that provides developmental numerical predictions of particulate matter smaller than 2.5 μm in diameter (PM2.5) in January 2015. The issuance of PM2.5 forecast guidance has become more punctual and reliable because developmental PM2.5 predictions are provided from the same system that produces operational ozone predictions on the National Centers for Environmental Prediction (NCEP) supercomputers.
There were three major upgrades in January 2015: 1) incorporation of real-time intermittent sources for particles emitted from wildfires and windblown dust originating within the NAQFC domain, 2) suppression of fugitive dust emissions from snow- and/or ice-covered terrain, and 3) a shorter life cycle for organic nitrate in the gaseous-phase chemical mechanism. In May 2015 a further upgrade for emission sources was included using the U.S. Environmental Protection Agency’s (EPA) 2011 National Emission Inventory (NEI). Emissions for ocean-going ships and on-road mobile sources will continue to rely on NEI 2005.
Incremental tests and evaluations of these upgrades were performed over multiple seasons. They were verified against the EPA’s AIRNow surface monitoring network for air pollutants. Impacts of the three upgrades on the prediction of surface PM2.5 concentrations show large regional variability: the inclusion of windblown dust emissions in May 2014 improved PM2.5 predictions over the western states and the suppression of fugitive dust in January 2015 reduced PM2.5 bias by 52%, from 6.5 to 3.1 μg m−3 against a monthly average of 9.4 μg m−3 for the north-central United States.</description><subject>Accuracy</subject><subject>Air monitoring</subject><subject>Air pollution</subject><subject>Air quality</subject><subject>Air quality forecasting</subject><subject>Airborne particulates</subject><subject>Atmospheric particulates</subject><subject>Atmospheric sciences</subject><subject>Deforestation</subject><subject>Dust</subject><subject>Dust storms</subject><subject>Emission</subject><subject>Emission inventories</subject><subject>Environmental monitoring</subject><subject>Environmental protection</subject><subject>Ice</subject><subject>Ice cover</subject><subject>Information science</subject><subject>Laboratories</subject><subject>Life cycle</subject><subject>Life cycle engineering</subject><subject>Life cycles</subject><subject>Mathematical models</subject><subject>Modelling</subject><subject>Nitrates</subject><subject>Outdoor air quality</subject><subject>Ozone</subject><subject>Particulate emissions</subject><subject>Particulate matter</subject><subject>Pollutants</subject><subject>Pollution monitoring</subject><subject>Pollution sources</subject><subject>Protection</subject><subject>Seasons</subject><subject>Ships</subject><subject>Snow</subject><subject>Spatial variations</subject><subject>Supercomputers</subject><subject>Suspended particulate matter</subject><subject>Terrain</subject><subject>Tests</subject><subject>Upgrading</subject><subject>Variability</subject><subject>Weather 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Developmental Forecast Guidance for Fine Particulate Matter (PM2.5)</title><author>Lee, Pius ; McQueen, Jeffery ; Stajner, Ivanka ; Huang, Jianping ; Pan, Li ; Tong, Daniel ; Kim, Hyuncheol ; Tang, Youhua ; Kondragunta, Shobha ; Ruminski, Mark ; Lu, Sarah ; Rogers, Eric ; Saylor, Rick ; Shafran, Perry ; Huang, Ho-Chun ; Gorline, Jerry ; Upadhayay, Sikchya ; Artz, Richard</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c269t-5b9e051328cf6302a66f40c1a3f3f48159c553126ea4dbe0298b794083c79e753</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Accuracy</topic><topic>Air monitoring</topic><topic>Air pollution</topic><topic>Air quality</topic><topic>Air quality forecasting</topic><topic>Airborne particulates</topic><topic>Atmospheric particulates</topic><topic>Atmospheric sciences</topic><topic>Deforestation</topic><topic>Dust</topic><topic>Dust 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Ivanka</au><au>Huang, Jianping</au><au>Pan, Li</au><au>Tong, Daniel</au><au>Kim, Hyuncheol</au><au>Tang, Youhua</au><au>Kondragunta, Shobha</au><au>Ruminski, Mark</au><au>Lu, Sarah</au><au>Rogers, Eric</au><au>Saylor, Rick</au><au>Shafran, Perry</au><au>Huang, Ho-Chun</au><au>Gorline, Jerry</au><au>Upadhayay, Sikchya</au><au>Artz, Richard</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>NAQFC Developmental Forecast Guidance for Fine Particulate Matter (PM2.5)</atitle><jtitle>Weather and forecasting</jtitle><date>2017-02-01</date><risdate>2017</risdate><volume>32</volume><issue>1</issue><spage>343</spage><epage>360</epage><pages>343-360</pages><issn>0882-8156</issn><eissn>1520-0434</eissn><abstract>The National Air Quality Forecasting Capability (NAQFC) upgraded its modeling system that provides developmental numerical predictions of particulate matter smaller than 2.5 μm in diameter (PM2.5) in January 2015. The issuance of PM2.5 forecast guidance has become more punctual and reliable because developmental PM2.5 predictions are provided from the same system that produces operational ozone predictions on the National Centers for Environmental Prediction (NCEP) supercomputers.
There were three major upgrades in January 2015: 1) incorporation of real-time intermittent sources for particles emitted from wildfires and windblown dust originating within the NAQFC domain, 2) suppression of fugitive dust emissions from snow- and/or ice-covered terrain, and 3) a shorter life cycle for organic nitrate in the gaseous-phase chemical mechanism. In May 2015 a further upgrade for emission sources was included using the U.S. Environmental Protection Agency’s (EPA) 2011 National Emission Inventory (NEI). Emissions for ocean-going ships and on-road mobile sources will continue to rely on NEI 2005.
Incremental tests and evaluations of these upgrades were performed over multiple seasons. They were verified against the EPA’s AIRNow surface monitoring network for air pollutants. Impacts of the three upgrades on the prediction of surface PM2.5 concentrations show large regional variability: the inclusion of windblown dust emissions in May 2014 improved PM2.5 predictions over the western states and the suppression of fugitive dust in January 2015 reduced PM2.5 bias by 52%, from 6.5 to 3.1 μg m−3 against a monthly average of 9.4 μg m−3 for the north-central United States.</abstract><cop>Boston</cop><pub>American Meteorological Society</pub><doi>10.1175/WAF-D-15-0163.1</doi><tpages>18</tpages></addata></record> |
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subjects | Accuracy Air monitoring Air pollution Air quality Air quality forecasting Airborne particulates Atmospheric particulates Atmospheric sciences Deforestation Dust Dust storms Emission Emission inventories Environmental monitoring Environmental protection Ice Ice cover Information science Laboratories Life cycle Life cycle engineering Life cycles Mathematical models Modelling Nitrates Outdoor air quality Ozone Particulate emissions Particulate matter Pollutants Pollution monitoring Pollution sources Protection Seasons Ships Snow Spatial variations Supercomputers Suspended particulate matter Terrain Tests Upgrading Variability Weather forecasting Wildfires |
title | NAQFC Developmental Forecast Guidance for Fine Particulate Matter (PM2.5) |
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