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Quantifying the influence of local meteorology on air quality using generalized additive models
Recent acknowledgement of the sensitivity of air quality to changes in climate has initiated a closer examination of the relationships between meteorology and air quality. This paper presents the estimated response of daily air pollutant concentrations in Melbourne, Australia to local-scale meteorol...
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Published in: | Atmospheric environment (1994) 2011-02, Vol.45 (6), p.1328-1336 |
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creator | Pearce, John L. Beringer, Jason Nicholls, Neville Hyndman, Rob J. Tapper, Nigel J. |
description | Recent acknowledgement of the sensitivity of air quality to changes in climate has initiated a closer examination of the relationships between meteorology and air quality. This paper presents the estimated response of daily air pollutant concentrations in Melbourne, Australia to local-scale meteorology. The meteorological-pollutant relationships have been assessed after controlling for long-term trends, seasonality, weekly emissions, spatial variation, and temporal persistence using the framework of generalized additive models (GAMs). Overall, results found that the aggregate impact of meteorological variables in the models explained 26.3% of the variance in O
3, 21.1% in PM
10, and 26.7% in NO
2. This indicates that meteorology – at the local-scale, is a relatively strong driver of air quality in Melbourne. Analysis of partial residuals plots found that changes in temperature, particularly when above 35 °C, resulted in the strongest positive response for O
3 (150%), PM
10 (150%) and NO
2 (120%). Other variables (boundary layer height, winds, water vapor pressure, radiation, precipitation, and mean sea-level pressure) displayed some importance for one or more of the pollutants, but their impact in the models was less pronounced. In sum, we provide results that form a solid foundation for understanding the importance of local-scale meteorology as a driver of regional air pollution. Additionally, these results can be used to provide a window into how changes in climate may affect air quality.
►PM
10, and NO
2 all show significant responses to local-scale meteorology. ►Temperature changes are the strongest meteorological driver of air pollution. ►Boundary layer height, winds, and water vapor pressure are also important. ►Results suggest that climate change may worsen air quality. |
doi_str_mv | 10.1016/j.atmosenv.2010.11.051 |
format | article |
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3, 21.1% in PM
10, and 26.7% in NO
2. This indicates that meteorology – at the local-scale, is a relatively strong driver of air quality in Melbourne. Analysis of partial residuals plots found that changes in temperature, particularly when above 35 °C, resulted in the strongest positive response for O
3 (150%), PM
10 (150%) and NO
2 (120%). Other variables (boundary layer height, winds, water vapor pressure, radiation, precipitation, and mean sea-level pressure) displayed some importance for one or more of the pollutants, but their impact in the models was less pronounced. In sum, we provide results that form a solid foundation for understanding the importance of local-scale meteorology as a driver of regional air pollution. Additionally, these results can be used to provide a window into how changes in climate may affect air quality.
►PM
10, and NO
2 all show significant responses to local-scale meteorology. ►Temperature changes are the strongest meteorological driver of air pollution. ►Boundary layer height, winds, and water vapor pressure are also important. ►Results suggest that climate change may worsen air quality.</description><identifier>ISSN: 1352-2310</identifier><identifier>EISSN: 1873-2844</identifier><identifier>DOI: 10.1016/j.atmosenv.2010.11.051</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Additives ; air ; Air pollution ; Air quality ; Applied sciences ; atmospheric chemistry ; Atmospheric pollution ; Climate change ; Drivers ; emissions ; Exact sciences and technology ; Generalized additive models ; Marine ; Mathematical models ; Meteorology ; Nitrogen dioxide ; ozone ; pollutants ; Pollution ; sea level ; temperature ; vapor pressure ; variance ; Water vapor ; wind</subject><ispartof>Atmospheric environment (1994), 2011-02, Vol.45 (6), p.1328-1336</ispartof><rights>2010 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c431t-36b8512d2f20b2b3496d199b81acd3ab1cd3cb642e5b0473ce70666bbe1cfb9f3</citedby><cites>FETCH-LOGICAL-c431t-36b8512d2f20b2b3496d199b81acd3ab1cd3cb642e5b0473ce70666bbe1cfb9f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23932500$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Pearce, John L.</creatorcontrib><creatorcontrib>Beringer, Jason</creatorcontrib><creatorcontrib>Nicholls, Neville</creatorcontrib><creatorcontrib>Hyndman, Rob J.</creatorcontrib><creatorcontrib>Tapper, Nigel J.</creatorcontrib><title>Quantifying the influence of local meteorology on air quality using generalized additive models</title><title>Atmospheric environment (1994)</title><description>Recent acknowledgement of the sensitivity of air quality to changes in climate has initiated a closer examination of the relationships between meteorology and air quality. This paper presents the estimated response of daily air pollutant concentrations in Melbourne, Australia to local-scale meteorology. The meteorological-pollutant relationships have been assessed after controlling for long-term trends, seasonality, weekly emissions, spatial variation, and temporal persistence using the framework of generalized additive models (GAMs). Overall, results found that the aggregate impact of meteorological variables in the models explained 26.3% of the variance in O
3, 21.1% in PM
10, and 26.7% in NO
2. This indicates that meteorology – at the local-scale, is a relatively strong driver of air quality in Melbourne. Analysis of partial residuals plots found that changes in temperature, particularly when above 35 °C, resulted in the strongest positive response for O
3 (150%), PM
10 (150%) and NO
2 (120%). Other variables (boundary layer height, winds, water vapor pressure, radiation, precipitation, and mean sea-level pressure) displayed some importance for one or more of the pollutants, but their impact in the models was less pronounced. In sum, we provide results that form a solid foundation for understanding the importance of local-scale meteorology as a driver of regional air pollution. Additionally, these results can be used to provide a window into how changes in climate may affect air quality.
►PM
10, and NO
2 all show significant responses to local-scale meteorology. ►Temperature changes are the strongest meteorological driver of air pollution. ►Boundary layer height, winds, and water vapor pressure are also important. ►Results suggest that climate change may worsen air quality.</description><subject>Additives</subject><subject>air</subject><subject>Air pollution</subject><subject>Air quality</subject><subject>Applied sciences</subject><subject>atmospheric chemistry</subject><subject>Atmospheric pollution</subject><subject>Climate change</subject><subject>Drivers</subject><subject>emissions</subject><subject>Exact sciences and technology</subject><subject>Generalized additive models</subject><subject>Marine</subject><subject>Mathematical models</subject><subject>Meteorology</subject><subject>Nitrogen dioxide</subject><subject>ozone</subject><subject>pollutants</subject><subject>Pollution</subject><subject>sea level</subject><subject>temperature</subject><subject>vapor pressure</subject><subject>variance</subject><subject>Water vapor</subject><subject>wind</subject><issn>1352-2310</issn><issn>1873-2844</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNqFkctu1DAUQKMKpJaWXwBvEGwy-JE4yQ5UFahUCaG2a8uP68Ejx25tZ6Tp1-NoCku6sa3rcx8-bpp3BG8IJvzzbiPLHDOE_YbiNUg2uCcnzRkZB9bSsete1TPraUsZwafNm5x3GGM2TMNZI34tMhRnDy5sUfkNyAXrFwgaULTIRy09mqFATNHH7QHFgKRL6HGR3pUDWvKat4UAqQaewCBpjCtuD2iOBny-aF5b6TO8fd7Pm_tvV3eXP9qbn9-vL7_etLpjpLSMq7En1FBLsaKKdRM3ZJrUSKQ2TCpSV614R6FXuBuYhgFzzpUCoq2aLDtvPh7rPqT4uEAuYnZZg_cyQFyyGPn64H7Alfz0X5IMVSLtMe0qyo-oTjHnBFY8JDfLdBAEi9W92Im_7sXqXhAiqvua-OG5h8zVoE0yaJf_ZVM2sdphneX9kbMyCrlNlbm_rYXqHcV06GklvhyJ6hL2DpLI2q3fY1wCXYSJ7qVh_gAbV6hV</recordid><startdate>20110201</startdate><enddate>20110201</enddate><creator>Pearce, John L.</creator><creator>Beringer, Jason</creator><creator>Nicholls, Neville</creator><creator>Hyndman, Rob J.</creator><creator>Tapper, Nigel J.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SU</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope><scope>7ST</scope><scope>7TG</scope><scope>7TV</scope><scope>7U6</scope><scope>F1W</scope><scope>H96</scope><scope>H97</scope><scope>KL.</scope><scope>L.G</scope><scope>SOI</scope></search><sort><creationdate>20110201</creationdate><title>Quantifying the influence of local meteorology on air quality using generalized additive models</title><author>Pearce, John L. ; Beringer, Jason ; Nicholls, Neville ; Hyndman, Rob J. ; Tapper, Nigel J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-36b8512d2f20b2b3496d199b81acd3ab1cd3cb642e5b0473ce70666bbe1cfb9f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Additives</topic><topic>air</topic><topic>Air pollution</topic><topic>Air quality</topic><topic>Applied sciences</topic><topic>atmospheric chemistry</topic><topic>Atmospheric pollution</topic><topic>Climate change</topic><topic>Drivers</topic><topic>emissions</topic><topic>Exact sciences and technology</topic><topic>Generalized additive models</topic><topic>Marine</topic><topic>Mathematical models</topic><topic>Meteorology</topic><topic>Nitrogen dioxide</topic><topic>ozone</topic><topic>pollutants</topic><topic>Pollution</topic><topic>sea level</topic><topic>temperature</topic><topic>vapor pressure</topic><topic>variance</topic><topic>Water vapor</topic><topic>wind</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pearce, John L.</creatorcontrib><creatorcontrib>Beringer, Jason</creatorcontrib><creatorcontrib>Nicholls, Neville</creatorcontrib><creatorcontrib>Hyndman, Rob J.</creatorcontrib><creatorcontrib>Tapper, Nigel J.</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Environmental Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Pollution Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><jtitle>Atmospheric environment (1994)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pearce, John L.</au><au>Beringer, Jason</au><au>Nicholls, Neville</au><au>Hyndman, Rob J.</au><au>Tapper, Nigel J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantifying the influence of local meteorology on air quality using generalized additive models</atitle><jtitle>Atmospheric environment (1994)</jtitle><date>2011-02-01</date><risdate>2011</risdate><volume>45</volume><issue>6</issue><spage>1328</spage><epage>1336</epage><pages>1328-1336</pages><issn>1352-2310</issn><eissn>1873-2844</eissn><abstract>Recent acknowledgement of the sensitivity of air quality to changes in climate has initiated a closer examination of the relationships between meteorology and air quality. This paper presents the estimated response of daily air pollutant concentrations in Melbourne, Australia to local-scale meteorology. The meteorological-pollutant relationships have been assessed after controlling for long-term trends, seasonality, weekly emissions, spatial variation, and temporal persistence using the framework of generalized additive models (GAMs). Overall, results found that the aggregate impact of meteorological variables in the models explained 26.3% of the variance in O
3, 21.1% in PM
10, and 26.7% in NO
2. This indicates that meteorology – at the local-scale, is a relatively strong driver of air quality in Melbourne. Analysis of partial residuals plots found that changes in temperature, particularly when above 35 °C, resulted in the strongest positive response for O
3 (150%), PM
10 (150%) and NO
2 (120%). Other variables (boundary layer height, winds, water vapor pressure, radiation, precipitation, and mean sea-level pressure) displayed some importance for one or more of the pollutants, but their impact in the models was less pronounced. In sum, we provide results that form a solid foundation for understanding the importance of local-scale meteorology as a driver of regional air pollution. Additionally, these results can be used to provide a window into how changes in climate may affect air quality.
►PM
10, and NO
2 all show significant responses to local-scale meteorology. ►Temperature changes are the strongest meteorological driver of air pollution. ►Boundary layer height, winds, and water vapor pressure are also important. ►Results suggest that climate change may worsen air quality.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.atmosenv.2010.11.051</doi><tpages>9</tpages></addata></record> |
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subjects | Additives air Air pollution Air quality Applied sciences atmospheric chemistry Atmospheric pollution Climate change Drivers emissions Exact sciences and technology Generalized additive models Marine Mathematical models Meteorology Nitrogen dioxide ozone pollutants Pollution sea level temperature vapor pressure variance Water vapor wind |
title | Quantifying the influence of local meteorology on air quality using generalized additive models |
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