Literature DB >> 22168097

Uncertainties in PM2.5 gravimetric and speciation measurements and what we can learn from them.

William C Malm1, Bret A Schichtel, Marc L Pitchford.   

Abstract

The U.S. Environmental Protection Agency (EPA) and the federal land management community (National Park Service, United States Fish and Wildlife Service, United States Forest Service, and Bureau of Land Management) operate extensive particle speciation monitoring networks that are similar in design but are operated for different objectives. Compliance (mass only) monitoring is also carried out using federal reference method (FRM) criteria at approximately 1000 sites. The Chemical Speciation Network (CSN) consists of approximately 50 long-term-trend sites, with about another 250 sites that have been or are currently operated by state and local agencies. The sites are located in urban or suburban settings. The Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network consists of about 181 sites, approximately 170 of which are in nonurban areas. Each monitoring approach has its own inherent monitoring limitations and biases. Determination of gravimetric mass has both negative and positive artifacts. Ammonium nitrate and other semivolatiles are lost during sampling, whereas, on the other hand, measured mass includes particle-bound water. Furthermore, some species may react with atmospheric gases, further increasing the positive mass artifact. Estimating aerosol species concentrations requires assumptions concerning the chemical form of various molecular compounds, such as nitrates and sulfates, and organic material and soil composition. Comparing data collected in the various monitoring networks allows for assessing uncertainties and biases associated with both negative and positive artifacts of gravimetric mass determinations, assumptions of chemical composition, and biases between different sampler technologies. All these biases are shown to have systematic seasonal characteristics. Unaccounted-for particle-bound water tends to be higher in the summer, as does nitrate volatilization. The ratio of particle organic mass divided by organic carbon mass (Roc) is higher during summer and lower during the winter seasons in both CSN and IMPROVE networks, and Roc is lower in urban than non-urban environments.

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Year:  2011        PMID: 22168097     DOI: 10.1080/10473289.2011.603998

Source DB:  PubMed          Journal:  J Air Waste Manag Assoc        ISSN: 1096-2247            Impact factor:   2.235


  8 in total

1.  Simulation of airborne trace metals in fine particulate matter over North America.

Authors:  Jun-Wei Xu; Randall V Martin; Barron H Henderson; Jun Meng; Burak Oztaner; Jenny L Hand; Amir Hakami; Madeleine Strum; Sharon B Phillips
Journal:  Atmos Environ (1994)       Date:  2019-10-01       Impact factor: 4.798

2.  The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part II: Evaluation and Case Studies.

Authors:  V Buchard; C A Randles; A M da Silva; A Darmenov; P R Colarco; R Govindaraju; R Ferrare; J Hair; A J Beyersdorf; L D Ziemba; H Yu
Journal:  J Clim       Date:  2017-07-27       Impact factor: 5.148

3.  Source identification and apportionment of PM2.5 and PM2.5-10 in iron and steel scrap smelting factory environment using PMF, PCFA and UNMIX receptor models.

Authors:  Lasun T Ogundele; Oyediran K Owoade; Felix S Olise; Philip K Hopke
Journal:  Environ Monit Assess       Date:  2016-09-19       Impact factor: 2.513

4.  Mass reconstruction methods for PM2.5: a review.

Authors:  Judith C Chow; Douglas H Lowenthal; L-W Antony Chen; Xiaoliang Wang; John G Watson
Journal:  Air Qual Atmos Health       Date:  2015-05-07       Impact factor: 3.763

5.  Combining PM2.5 Component Data from Multiple Sources: Data Consistency and Characteristics Relevant to Epidemiological Analyses of Predicted Long-Term Exposures.

Authors:  Sun-Young Kim; Lianne Sheppard; Timothy V Larson; Joel D Kaufman; Sverre Vedal
Journal:  Environ Health Perspect       Date:  2015-02-27       Impact factor: 9.031

6.  The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition.

Authors:  Jessica H Belle; Howard H Chang; Yujie Wang; Xuefei Hu; Alexei Lyapustin; Yang Liu
Journal:  Int J Environ Res Public Health       Date:  2017-10-18       Impact factor: 3.390

7.  Estimating PM2.5 speciation concentrations using prototype 4.4 km-resolution MISR aerosol properties over Southern California.

Authors:  Xia Meng; Michael J Garay; David J Diner; Olga V Kalashnikova; Jin Xu; Yang Liu
Journal:  Atmos Environ (1994)       Date:  2018-03-10       Impact factor: 4.798

8.  Constraining chemical transport PM2.5 modeling outputs using surface monitor measurements and satellite retrievals: application over the San Joaquin Valley.

Authors:  Mariel D Friberg; Ralph A Kahn; James A Limbacher; K Wyat Appel; James A Mulholland
Journal:  Atmos Chem Phys       Date:  2018-07-09       Impact factor: 6.133

  8 in total

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