Simon Rosanka, Madison M. Flesch, Yin Ting T. Chiu and Annmarie G. Carlton
{"title":"Chemically specific sampling bias: the ratio of PM2.5 to surface AOD on average and peak days in the U.S.†","authors":"Simon Rosanka, Madison M. Flesch, Yin Ting T. Chiu and Annmarie G. Carlton","doi":"10.1039/D3EA00163F","DOIUrl":null,"url":null,"abstract":"<p >Accurate quantitative description of the atmospheric fine particulate matter (PM<small><sub>2.5</sub></small>) burden requires an understanding of aerosol amounts and properties that transcends measurement platforms. For example, air quality studies often seek to describe ambient PM<small><sub>2.5</sub></small> with columnar aerosol optical depth (AOD), point measurements of mass, or some combination. PM<small><sub>2.5</sub></small> chemical constituents affect such measurements differently. We investigate the ratio of PM<small><sub>2.5</sub></small>-to-AOD (<em>η</em>) from 2005 to 2016 at multiple surface locations across the contiguous U.S. using observations and models, and quantitatively account for PM<small><sub>2.5</sub></small> sampling bias of nitrate and aerosol liquid water (ALW). We find <em>η</em> peaks during winter and is lowest in summer at all locations, despite contrasting seasonality in PM<small><sub>2.5</sub></small> mass and AOD. Accounting for loss of nitrate and ALW from PM<small><sub>2.5</sub></small> monitors improves consistency among <em>η</em> calculations in space and time. Co-occurrence of extreme PM<small><sub>2.5</sub></small> mass concentrations and AOD events declined in the eastern U.S. but not in the west. On peak days, in all locations, ALW mass concentrations are higher and fractional contributions are larger relative to PM<small><sub>2.5</sub></small> chemical composition during average conditions. This suggests an increased fraction of ambient PM<small><sub>2.5</sub></small> is detectable <em>via</em> optical methods but not well described by surface mass networks on peak days. The Community Multiscale Air Quality (CMAQ) model reproduces similar spatial and temporal variability in <em>η</em> to surface observations in winter and summer simulations at the beginning and end of the analysis period. Accounting for sampling artifacts in surface monitors may improve agreement with model predictions and remote sensing of PM<small><sub>2.5</sub></small> mass concentrations. The poor understanding of organic compounds and their PM<small><sub>2.5</sub></small> sampling artifacts remains a critical open question.</p>","PeriodicalId":72942,"journal":{"name":"Environmental science: atmospheres","volume":" 5","pages":" 547-556"},"PeriodicalIF":2.8000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2024/ea/d3ea00163f?page=search","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental science: atmospheres","FirstCategoryId":"1085","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2024/ea/d3ea00163f","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Accurate quantitative description of the atmospheric fine particulate matter (PM2.5) burden requires an understanding of aerosol amounts and properties that transcends measurement platforms. For example, air quality studies often seek to describe ambient PM2.5 with columnar aerosol optical depth (AOD), point measurements of mass, or some combination. PM2.5 chemical constituents affect such measurements differently. We investigate the ratio of PM2.5-to-AOD (η) from 2005 to 2016 at multiple surface locations across the contiguous U.S. using observations and models, and quantitatively account for PM2.5 sampling bias of nitrate and aerosol liquid water (ALW). We find η peaks during winter and is lowest in summer at all locations, despite contrasting seasonality in PM2.5 mass and AOD. Accounting for loss of nitrate and ALW from PM2.5 monitors improves consistency among η calculations in space and time. Co-occurrence of extreme PM2.5 mass concentrations and AOD events declined in the eastern U.S. but not in the west. On peak days, in all locations, ALW mass concentrations are higher and fractional contributions are larger relative to PM2.5 chemical composition during average conditions. This suggests an increased fraction of ambient PM2.5 is detectable via optical methods but not well described by surface mass networks on peak days. The Community Multiscale Air Quality (CMAQ) model reproduces similar spatial and temporal variability in η to surface observations in winter and summer simulations at the beginning and end of the analysis period. Accounting for sampling artifacts in surface monitors may improve agreement with model predictions and remote sensing of PM2.5 mass concentrations. The poor understanding of organic compounds and their PM2.5 sampling artifacts remains a critical open question.