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Measurement, characterization, and s...
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Grover, Brett D.
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Measurement, characterization, and source apportionment of the major chemical components of fine particulate material, including semi-volatile species.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Measurement, characterization, and source apportionment of the major chemical components of fine particulate material, including semi-volatile species./
作者:
Grover, Brett D.
面頁冊數:
289 p.
附註:
Source: Dissertation Abstracts International, Volume: 67-03, Section: B, page: 1415.
Contained By:
Dissertation Abstracts International67-03B.
標題:
Chemistry, Analytical. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3209267
ISBN:
9780542579752
Measurement, characterization, and source apportionment of the major chemical components of fine particulate material, including semi-volatile species.
Grover, Brett D.
Measurement, characterization, and source apportionment of the major chemical components of fine particulate material, including semi-volatile species.
- 289 p.
Source: Dissertation Abstracts International, Volume: 67-03, Section: B, page: 1415.
Thesis (Ph.D.)--Brigham Young University, 2006.
The promulgation of revised standards for atmospheric fine particles (PM2.5) by the US EPA has sparked renewed interest in the ability to accurately measure and characterize suspended atmospheric particulate matter. Semi-volatile material (SVM), consisting of ammonium nitrate and semi-volatile organic material, is not accurately measured by EPA accepted methods such as the Federal reference method (FRM) or Tapered Element Oscillating Microbalance (TEOM). However, SVM is often a major fraction of urban aerosols.
ISBN: 9780542579752Subjects--Topical Terms:
586156
Chemistry, Analytical.
Measurement, characterization, and source apportionment of the major chemical components of fine particulate material, including semi-volatile species.
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The promulgation of revised standards for atmospheric fine particles (PM2.5) by the US EPA has sparked renewed interest in the ability to accurately measure and characterize suspended atmospheric particulate matter. Semi-volatile material (SVM), consisting of ammonium nitrate and semi-volatile organic material, is not accurately measured by EPA accepted methods such as the Federal reference method (FRM) or Tapered Element Oscillating Microbalance (TEOM). However, SVM is often a major fraction of urban aerosols.
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Recent advances in atmospheric sampling instrumentation allowed for the semi-continuous characterization of urban PM2.5, including SVM. The Filter Dynamic Measurement System (FDMS) was shown to measure total PM 2.5 mass including SVM. Validation of the FDMS was performed by comparison with the particle concentrator-Brigham Young University organic sampling system (PC-BOSS) and the real-time total ambient mass sampler (RAMS). Semi-continuous ambient particulate concentrations of sulfate, nitrate and ammonium ion were measured by a newly developed Dionex instrument which was field tested and validated for the first time in Fresno, CA. Either a modified Sunset Laboratory carbon monitor, collocated with a conventional Sunset carbon monitor employing a common inlet, or the newly developed dual-oven Sunset monitor allowed for the semi-continuous determination of both nonvolatile and semi-volatile organic material.
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This was the first attempt to characterize both nonvolatile and semi-volatile fractions of an urban aerosol in using all semi-continuous instruments. A suite of instruments for semi-continuous PM2.5 monitoring was recommended including, an R&P FDMS for the measurement of PM2.5 mass, a dual-oven Sunset monitor for the measurement of nonvolatile and semi-volatile carbonaceous species, and a Dionex GP-IC for the measurement of inorganic species. A TEOM monitor is also recommended to measure nonvolatile PM 2.5 mass. Using these instruments, semi-continuous mass closure was obtained for the first time during a study conducted in Riverside, CA.
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The advantage of using semi-continuous sampler data in the application of source apportionment was elucidated. One-h averaged data applied to source apportionment models was shown to increase the power of the model to predict sources, both primary and secondary, that exhibit diurnal short-term episodes.
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