{"title":"计算气溶胶质量平衡中有机碳与有机物的换算系数","authors":"","doi":"10.1016/j.apr.2024.102301","DOIUrl":null,"url":null,"abstract":"<div><p>Aerosol mass balance studies based on filter samples require a conversion factor to derive organic matter (OM) concentrations from organic carbon (OC) measurements from thermo-optical methods. This factor provides indirect insights on the molecular structure of OM needed in chemical transport models. Site- and season-specific ratios of OC to OM (<em>f</em><sub>OM:OC</sub>) were calculated using data from five rural background sites in France between 2012 and 2021 by relating the unidentified chemical fraction in PM<sub>2.5</sub> samples to thermo-optical OC concentrations. Further, multiple linear formulations were used to evaluate the impact of possible artefacts on the determination of <em>f</em><sub>OM:OC</sub>. The resulting <em>f</em><sub>OM:OC</sub> was then compared to other estimates derived from online aerosol mass spectrometry data, showing good agreement. The spatial and temporal variability in <em>f</em><sub>OM:OC</sub> is discussed considering factors such as seasonality, meteorological conditions and the atmospheric oxidative potential. Linear-mixed effect models were formulated to quantitatively determine the drivers which influence the <em>f</em><sub>OM:OC</sub> at the French rural background sites. Both ozone and relative humidity were variables with statistically significant effects on <em>f</em><sub>OM:OC</sub>, indicating that differences in the contributions from both photooxidation and water content, explain the variability in <em>f</em><sub>OM:OC</sub> observed at the French rural background sites. Site-specific <em>f</em><sub>OM:OC</sub> yielded more accurate PM<sub>2.5</sub> mass closure and are therefore recommended in mass-balance exercises. Accurate <em>f</em><sub>OM:OC</sub> are critical to maintain consistency in OM time series, especially in cases where filter-based time series may be replaced by state-of-the-art online instrumentation.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":null,"pages":null},"PeriodicalIF":3.9000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1309104224002666/pdfft?md5=63a95e5239088b5d1876c438b600c9a2&pid=1-s2.0-S1309104224002666-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Calculations of the conversion factor from organic carbon to organic matter for aerosol mass balance\",\"authors\":\"\",\"doi\":\"10.1016/j.apr.2024.102301\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Aerosol mass balance studies based on filter samples require a conversion factor to derive organic matter (OM) concentrations from organic carbon (OC) measurements from thermo-optical methods. This factor provides indirect insights on the molecular structure of OM needed in chemical transport models. Site- and season-specific ratios of OC to OM (<em>f</em><sub>OM:OC</sub>) were calculated using data from five rural background sites in France between 2012 and 2021 by relating the unidentified chemical fraction in PM<sub>2.5</sub> samples to thermo-optical OC concentrations. Further, multiple linear formulations were used to evaluate the impact of possible artefacts on the determination of <em>f</em><sub>OM:OC</sub>. The resulting <em>f</em><sub>OM:OC</sub> was then compared to other estimates derived from online aerosol mass spectrometry data, showing good agreement. The spatial and temporal variability in <em>f</em><sub>OM:OC</sub> is discussed considering factors such as seasonality, meteorological conditions and the atmospheric oxidative potential. Linear-mixed effect models were formulated to quantitatively determine the drivers which influence the <em>f</em><sub>OM:OC</sub> at the French rural background sites. Both ozone and relative humidity were variables with statistically significant effects on <em>f</em><sub>OM:OC</sub>, indicating that differences in the contributions from both photooxidation and water content, explain the variability in <em>f</em><sub>OM:OC</sub> observed at the French rural background sites. Site-specific <em>f</em><sub>OM:OC</sub> yielded more accurate PM<sub>2.5</sub> mass closure and are therefore recommended in mass-balance exercises. Accurate <em>f</em><sub>OM:OC</sub> are critical to maintain consistency in OM time series, especially in cases where filter-based time series may be replaced by state-of-the-art online instrumentation.</p></div>\",\"PeriodicalId\":8604,\"journal\":{\"name\":\"Atmospheric Pollution Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1309104224002666/pdfft?md5=63a95e5239088b5d1876c438b600c9a2&pid=1-s2.0-S1309104224002666-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Pollution Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1309104224002666\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Pollution Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1309104224002666","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Calculations of the conversion factor from organic carbon to organic matter for aerosol mass balance
Aerosol mass balance studies based on filter samples require a conversion factor to derive organic matter (OM) concentrations from organic carbon (OC) measurements from thermo-optical methods. This factor provides indirect insights on the molecular structure of OM needed in chemical transport models. Site- and season-specific ratios of OC to OM (fOM:OC) were calculated using data from five rural background sites in France between 2012 and 2021 by relating the unidentified chemical fraction in PM2.5 samples to thermo-optical OC concentrations. Further, multiple linear formulations were used to evaluate the impact of possible artefacts on the determination of fOM:OC. The resulting fOM:OC was then compared to other estimates derived from online aerosol mass spectrometry data, showing good agreement. The spatial and temporal variability in fOM:OC is discussed considering factors such as seasonality, meteorological conditions and the atmospheric oxidative potential. Linear-mixed effect models were formulated to quantitatively determine the drivers which influence the fOM:OC at the French rural background sites. Both ozone and relative humidity were variables with statistically significant effects on fOM:OC, indicating that differences in the contributions from both photooxidation and water content, explain the variability in fOM:OC observed at the French rural background sites. Site-specific fOM:OC yielded more accurate PM2.5 mass closure and are therefore recommended in mass-balance exercises. Accurate fOM:OC are critical to maintain consistency in OM time series, especially in cases where filter-based time series may be replaced by state-of-the-art online instrumentation.
期刊介绍:
Atmospheric Pollution Research (APR) is an international journal designed for the publication of articles on air pollution. Papers should present novel experimental results, theory and modeling of air pollution on local, regional, or global scales. Areas covered are research on inorganic, organic, and persistent organic air pollutants, air quality monitoring, air quality management, atmospheric dispersion and transport, air-surface (soil, water, and vegetation) exchange of pollutants, dry and wet deposition, indoor air quality, exposure assessment, health effects, satellite measurements, natural emissions, atmospheric chemistry, greenhouse gases, and effects on climate change.