Dandan Zhang, Randall V Martin, Aaron van Donkelaar, Chi Li, Haihui Zhu, Alexei Lyapustin
{"title":"模型空间分辨率对全球地球物理卫星得出的细颗粒物的影响。","authors":"Dandan Zhang, Randall V Martin, Aaron van Donkelaar, Chi Li, Haihui Zhu, Alexei Lyapustin","doi":"10.1021/acsestair.4c00084","DOIUrl":null,"url":null,"abstract":"<p><p>Global geophysical satellite-derived ambient fine particulate matter (PM<sub>2.5</sub>) inference relies upon a geophysical relationship (η) from a chemical transport model to relate satellite retrievals of aerosol optical depth (AOD) to surface PM<sub>2.5</sub>. The resolution dependence of simulated η warrants further investigation. In this study, we calculate geophysical PM<sub>2.5</sub> with simulated η from the GEOS-Chem model in its high-performance configuration (GCHP) at cubed-sphere resolutions of C360 (∼25 km) and C48 (∼200 km) and satellite AOD at 0.01° (∼1 km). Annual geophysical PM<sub>2.5</sub> concentrations inferred from satellite AOD and GCHP simulations at ∼25 km and ∼200 km resolutions exhibit remarkable similarity (<i>R</i> <sup>2</sup> = 0.96, slope = 1.03). This similarity in part reflects opposite resolution responses across components with population-weighted normalized mean difference (PW-NMD) increasing by 5% to 11% for primary species while decreasing by -30% to -5% for secondary species at finer resolution. Despite global similarity, our results also identify larger resolution sensitivities of η over isolated pollution sources and mountainous regions, where spatial contrast of aerosol concentration and composition is better represented at fine resolution. Our results highlight the resolution dependence of representing near-surface concentrations and the vertical distribution of chemically different species with implications for inferring ground-level PM<sub>2.5</sub> from columnar AOD.</p>","PeriodicalId":100014,"journal":{"name":"ACS ES&T Air","volume":"1 9","pages":"1112-1123"},"PeriodicalIF":0.0000,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11407304/pdf/","citationCount":"0","resultStr":"{\"title\":\"Impact of Model Spatial Resolution on Global Geophysical Satellite-Derived Fine Particulate Matter.\",\"authors\":\"Dandan Zhang, Randall V Martin, Aaron van Donkelaar, Chi Li, Haihui Zhu, Alexei Lyapustin\",\"doi\":\"10.1021/acsestair.4c00084\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Global geophysical satellite-derived ambient fine particulate matter (PM<sub>2.5</sub>) inference relies upon a geophysical relationship (η) from a chemical transport model to relate satellite retrievals of aerosol optical depth (AOD) to surface PM<sub>2.5</sub>. The resolution dependence of simulated η warrants further investigation. In this study, we calculate geophysical PM<sub>2.5</sub> with simulated η from the GEOS-Chem model in its high-performance configuration (GCHP) at cubed-sphere resolutions of C360 (∼25 km) and C48 (∼200 km) and satellite AOD at 0.01° (∼1 km). Annual geophysical PM<sub>2.5</sub> concentrations inferred from satellite AOD and GCHP simulations at ∼25 km and ∼200 km resolutions exhibit remarkable similarity (<i>R</i> <sup>2</sup> = 0.96, slope = 1.03). This similarity in part reflects opposite resolution responses across components with population-weighted normalized mean difference (PW-NMD) increasing by 5% to 11% for primary species while decreasing by -30% to -5% for secondary species at finer resolution. Despite global similarity, our results also identify larger resolution sensitivities of η over isolated pollution sources and mountainous regions, where spatial contrast of aerosol concentration and composition is better represented at fine resolution. Our results highlight the resolution dependence of representing near-surface concentrations and the vertical distribution of chemically different species with implications for inferring ground-level PM<sub>2.5</sub> from columnar AOD.</p>\",\"PeriodicalId\":100014,\"journal\":{\"name\":\"ACS ES&T Air\",\"volume\":\"1 9\",\"pages\":\"1112-1123\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11407304/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS ES&T Air\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1021/acsestair.4c00084\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/9/13 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS ES&T Air","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1021/acsestair.4c00084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/13 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
Impact of Model Spatial Resolution on Global Geophysical Satellite-Derived Fine Particulate Matter.
Global geophysical satellite-derived ambient fine particulate matter (PM2.5) inference relies upon a geophysical relationship (η) from a chemical transport model to relate satellite retrievals of aerosol optical depth (AOD) to surface PM2.5. The resolution dependence of simulated η warrants further investigation. In this study, we calculate geophysical PM2.5 with simulated η from the GEOS-Chem model in its high-performance configuration (GCHP) at cubed-sphere resolutions of C360 (∼25 km) and C48 (∼200 km) and satellite AOD at 0.01° (∼1 km). Annual geophysical PM2.5 concentrations inferred from satellite AOD and GCHP simulations at ∼25 km and ∼200 km resolutions exhibit remarkable similarity (R2 = 0.96, slope = 1.03). This similarity in part reflects opposite resolution responses across components with population-weighted normalized mean difference (PW-NMD) increasing by 5% to 11% for primary species while decreasing by -30% to -5% for secondary species at finer resolution. Despite global similarity, our results also identify larger resolution sensitivities of η over isolated pollution sources and mountainous regions, where spatial contrast of aerosol concentration and composition is better represented at fine resolution. Our results highlight the resolution dependence of representing near-surface concentrations and the vertical distribution of chemically different species with implications for inferring ground-level PM2.5 from columnar AOD.