Chao Peng , Chongzhi Zhai , Yang Chen , Mi Tian , Ying Xiang , Tianyu Zhai , Weikai Fang , Xin Long , Xiaocheng Wang , Mulan Chen , Yunqing Cao , Min Du , Zhenliang Li
{"title":"DRI-2001和DRI-2015对PM2.5中碳质气溶胶分析的模式间比较:方法开发与在重庆的应用","authors":"Chao Peng , Chongzhi Zhai , Yang Chen , Mi Tian , Ying Xiang , Tianyu Zhai , Weikai Fang , Xin Long , Xiaocheng Wang , Mulan Chen , Yunqing Cao , Min Du , Zhenliang Li","doi":"10.1016/j.apr.2025.102555","DOIUrl":null,"url":null,"abstract":"<div><div>Thermal-optical method is widely used to determine organic carbon (OC) and elemental carbon (EC) in PM<sub>2.5</sub> collected on filters. DRI-2001 and DRI-2015 analyzers have both been extensively employed with the IMPROVE_A protocol in the recent decades. However, differences in detectors and lasers between the two models can affect the measurement results. In this study, a novel using multiple linear regression was developed to equalize carbon fraction results between DRI-2001 and DRI-2015. After adjustment, high inter-model consistency was observed, with a mean bias within 5 % for total carbon (TC) and OC, and ∼10 % for EC. Larger inter-model differences (5.2 %–121.5 %) were found in OC1-OC4 and EC1-EC3. Fractions with high mass loading, particularly those linked to biomass burning (BB) and coal combustion (CC) (e.g., OC1, OC2 and OC4), exhibited better agreement after adjustment, with smaller mean bias within ∼15 % and higher R<sup>2</sup> values above 0.93 (<em>p</em> < 0.001). During winter in Wanzhou, the adjusted carbon fractions exhibited significantly improved inter-model agreement (<em>p</em> < 0.001). BB and CC were identified as the primary sources of carbonaceous aerosol, while secondary organic carbon (SOC) also contributed to elevated TC concentrations during pollution periods. Similar to DRI-2001 results, DRI-2015 measurements during winter indicated that CC and BB contributed 47.5 %, diesel exhaust 18.0 %, gasoline exhaust 21.6 %, and secondary formation 12.9 % to TC. These findings enhance our understanding of uncertainties and differences between models, leading to more accurate characterization of carbonaceous aerosol.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 8","pages":"Article 102555"},"PeriodicalIF":3.9000,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Inter-model comparison of the DRI-2001 and DRI-2015 for carbonaceous aerosol analysis in PM2.5: Method development and application in Chongqing\",\"authors\":\"Chao Peng , Chongzhi Zhai , Yang Chen , Mi Tian , Ying Xiang , Tianyu Zhai , Weikai Fang , Xin Long , Xiaocheng Wang , Mulan Chen , Yunqing Cao , Min Du , Zhenliang Li\",\"doi\":\"10.1016/j.apr.2025.102555\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Thermal-optical method is widely used to determine organic carbon (OC) and elemental carbon (EC) in PM<sub>2.5</sub> collected on filters. DRI-2001 and DRI-2015 analyzers have both been extensively employed with the IMPROVE_A protocol in the recent decades. However, differences in detectors and lasers between the two models can affect the measurement results. In this study, a novel using multiple linear regression was developed to equalize carbon fraction results between DRI-2001 and DRI-2015. After adjustment, high inter-model consistency was observed, with a mean bias within 5 % for total carbon (TC) and OC, and ∼10 % for EC. Larger inter-model differences (5.2 %–121.5 %) were found in OC1-OC4 and EC1-EC3. Fractions with high mass loading, particularly those linked to biomass burning (BB) and coal combustion (CC) (e.g., OC1, OC2 and OC4), exhibited better agreement after adjustment, with smaller mean bias within ∼15 % and higher R<sup>2</sup> values above 0.93 (<em>p</em> < 0.001). During winter in Wanzhou, the adjusted carbon fractions exhibited significantly improved inter-model agreement (<em>p</em> < 0.001). BB and CC were identified as the primary sources of carbonaceous aerosol, while secondary organic carbon (SOC) also contributed to elevated TC concentrations during pollution periods. Similar to DRI-2001 results, DRI-2015 measurements during winter indicated that CC and BB contributed 47.5 %, diesel exhaust 18.0 %, gasoline exhaust 21.6 %, and secondary formation 12.9 % to TC. These findings enhance our understanding of uncertainties and differences between models, leading to more accurate characterization of carbonaceous aerosol.</div></div>\",\"PeriodicalId\":8604,\"journal\":{\"name\":\"Atmospheric Pollution Research\",\"volume\":\"16 8\",\"pages\":\"Article 102555\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Pollution Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1309104225001576\",\"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/S1309104225001576","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}
Inter-model comparison of the DRI-2001 and DRI-2015 for carbonaceous aerosol analysis in PM2.5: Method development and application in Chongqing
Thermal-optical method is widely used to determine organic carbon (OC) and elemental carbon (EC) in PM2.5 collected on filters. DRI-2001 and DRI-2015 analyzers have both been extensively employed with the IMPROVE_A protocol in the recent decades. However, differences in detectors and lasers between the two models can affect the measurement results. In this study, a novel using multiple linear regression was developed to equalize carbon fraction results between DRI-2001 and DRI-2015. After adjustment, high inter-model consistency was observed, with a mean bias within 5 % for total carbon (TC) and OC, and ∼10 % for EC. Larger inter-model differences (5.2 %–121.5 %) were found in OC1-OC4 and EC1-EC3. Fractions with high mass loading, particularly those linked to biomass burning (BB) and coal combustion (CC) (e.g., OC1, OC2 and OC4), exhibited better agreement after adjustment, with smaller mean bias within ∼15 % and higher R2 values above 0.93 (p < 0.001). During winter in Wanzhou, the adjusted carbon fractions exhibited significantly improved inter-model agreement (p < 0.001). BB and CC were identified as the primary sources of carbonaceous aerosol, while secondary organic carbon (SOC) also contributed to elevated TC concentrations during pollution periods. Similar to DRI-2001 results, DRI-2015 measurements during winter indicated that CC and BB contributed 47.5 %, diesel exhaust 18.0 %, gasoline exhaust 21.6 %, and secondary formation 12.9 % to TC. These findings enhance our understanding of uncertainties and differences between models, leading to more accurate characterization of carbonaceous aerosol.
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.