Chemical Mass Closure and Chemical Characteristics of Ambient Ultrafine Particles and other PM Fractions

Chen, Sheng Chieh; Tsai, Chuen Jinn; Huang, Cheng; Chen, Hong Dar; Chen, Shui Jen; Lin, Chih Chung; Tsai, Jen Hsiung; Chou, Charles C.‐K.; Lung, Shih-Chun Candice; Huang, Wei; Roam, Gwo Dong; Wu, Wan Yi; Smolik, J.; Džumbová, Lucie

doi:10.1080/02786826.2010.486385

Cited by 54 publications

(32 citation statements)

References 40 publications

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“…The PM samples collected by the silicon grease-coated foils in stages 1-9 of MOUDI (18-0.1 mm) were analyzed gravimetrically but not chemically, because of interference from the grease-coating. The Teflon filters were conditioned for at least 24-h in a temperature and relative humidity controlled room (22 ± 1°C, 40 ± 5% RH) before sampling (Chen et al, 2010). The average mass concentrations of PM 10 and PM 2.5 determined by the MOUDI were in agreement with those obtained from the Dichot, with a relative deviation of < 20% (Chen et al, 2010).…”

Section: Sampling Methods and Analysissupporting

confidence: 69%

“…PM 10 , PM 2.5 and PM 0.1 samples were collected by using a MOUDI (Model 110, MSP Corp., MN, USA) and a dichotomous samplers (Model SA-241, Andersen Inc., Georgia, USA) operated at flow rates of 30 and 16.7 L/min (Chen et al, 2010), respectively. The MOUDI sampler has 10 size stages, with the nominal cutoff diameters of 18 (inlet), 10, 5.6, 3.2, 1.8, 1.0, 0.56, 0.32, 0.18, 0.1 and 0.056 mm (Marple et al, 1991).…”

Section: Sampling Methods and Analysismentioning

confidence: 99%

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Source Characterization and Apportionment of PM10, PM2.5 and PM0.1 by Using Positive Matrix Factorization

Gugamsetty

Han

Liu

et al. 2012

Aerosol Air Qual. Res.

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203

117

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Ambient Particulate Matters (PM 10 , PM 2.5 and PM 0.1 ) were investigated at Shinjung station in New Taipei City, Taiwan. Samples were collected simultaneously using a dichotomous sampler (Andersen Model SA-241) and a MOUDI (MSP Model 110) over a 24-h period from May 2011 to November 2011 at Shinjung station. Samples were analyzed for metallic trace elements using ion coupled plasma mass spectroscopy (ICP-MS) and ionic compounds by ion chromatography (IC). The average concentrations of PM 10 , PM 2.5 and PM 0.1 were found to be 39.45 ± 11.58, 21.82 ± 7.50 and 1.42 ± 0.56 μg/m 3 , respectively. Based on the chemical information, positive matrix factorization (PMF) was used to identify PM sources. A total of five source types were identified, including soil dust, vehicle emissions, sea salt, industrial emissions and secondary aerosols, and their contributions were estimated using PMF. The crustal enrichment factors (EF) were calculated using Al as a reference for the trace metal species to identify the sources. Conditional probability functions (CPF) were computed using wind profiles and factor contributions. The results of CPF analysis were used to identify local point sources. The results suggest a competitive relationship between anthropogenic and natural source processes over the monitoring station.

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Section: Sampling Methods and Analysissupporting

confidence: 69%

Section: Sampling Methods and Analysismentioning

confidence: 99%

Source Characterization and Apportionment of PM10, PM2.5 and PM0.1 by Using Positive Matrix Factorization

Gugamsetty

Han

Liu

et al. 2012

Aerosol Air Qual. Res.

Self Cite

203

117

View full text Add to dashboard Cite

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“…Ultrafine particles (UFPs) are recently attracting increasing attention due to their potential effects on human and environmental health (Chen et al, 2010). Their large surface-to-volume ratio and ability to deposit deep in the respiratory tract make UFPs potentially more toxic than their larger counterpart (Nel et al, 2006;Braniš and Větvička, 2010).…”

Section: Introductionmentioning

confidence: 99%

Deep Investigation of Ultrafine Particles in Urban Air

Avino

Casciardi

Fanizza

et al. 2011

Aerosol Air Qual. Res.

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This work describes the results of a study which started in 2007 to investigate the ultrafine particle (UFP) pollution in the urban area of Rome. The sampling site was located in a street with high density of autovehicular traffic, where measurements have shown that carbonaceous particulate matter represented an important fraction of aerosol pollution. UFPs have been classified by means of an electrostatic classifier. Monodisperse aerosol was either counted by ultrafine water-based condensation particle counter or sampled by means of a nanometer aerosol sampler. Samples collected were investigated using energy filtered transmission electron microscope in combination with energy dispersive X-ray spectroscopy and electron energy loss spectroscopy. Electron transmission microscope observations revealed that carbonaceous UFPs were present also as nanotube related forms.The rapid evolution of aerosol from autovehicular exhaust plumes was observed by highly time-resolved aerosol size distribution measurements.

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“…Therefore, another issue associated with PC involves the choice of the charring correction method-transmittance or reflectance. Substantial charring takes place within the filter and so the drop of filter transmittance in the inert mode is larger than the drop of reflectance, which is dominated by charring only of the near-surface organics (Chow et al 2004;Chen et al 2010). Consequently, the PC concentration determined by the TOT (thermal/optical transmittance) method is »15% higher than PC determined by the TOR method.…”

Section: ¡3mentioning

confidence: 88%

“…However, the backup QBQ filter may adsorb less gaseous organic matter than the front quartz filter, especially at low exposure, if the front quartz filter is not in equilibrium with the sample air stream. The front filter would thus deplete the air stream of organic vapors (Kirchstetter et al 2001;Mader and Pankow 2001;Chen et al 2010). As a result, the QBQ OC level is usually lower than a comparable QBT filter for low exposure.…”

Section: ¡2mentioning

confidence: 99%

Estimating ambient particulate organic carbon concentrations and partitioning using thermal optical measurements and the volatility basis set

et al. 2016

Aerosol Science and Technology

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We introduce a new method to estimate the mass concentration of particulate organic carbon (POC) collected on quartz filters, demonstrating it using quartz-filter samples collected in greater Pittsburgh. This method combines thermal-optical organic carbon and elemental carbon (OC/EC) analysis and the volatility basis set (VBS) to quantify the mass concentration of semi-volatile POC on the filters. The dataset includes ambient samples collected at a number of sites in both summer and winter as well as samples from a highway tunnel. As a reference we use the two-filter bare-Quartz minus Quartz-Behind-Teflon (Q-QBT) approach to estimate the adsorbed gaseous fraction of organic carbon (OC), finding a substantial fraction in both the gas and particle phases under all conditions. In the new method we use OC fractions measured during different temperature stages of the OC/EC analysis for the single bare-quartz (BQ) filter in combination with partitioning theory to predict the volatility distributions of the measured OC, which we describe with the VBS. The effective volatility bins are consistent for data from both ambient samples and primary organic aerosol (POA)-enriched tunnel samples. Consequently, with the VBS model and total OC fractions measured over different heating stages, particulate OC can be determined by using the BQ filter alone. This method can thus be applied to all quartz filter-based OC/EC analyses to estimate the POC concentration without using backup filters.

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Chemical Mass Closure and Chemical Characteristics of Ambient Ultrafine Particles and other PM Fractions

Cited by 54 publications

References 40 publications

Source Characterization and Apportionment of PM10, PM2.5 and PM0.1 by Using Positive Matrix Factorization

Source Characterization and Apportionment of PM10, PM2.5 and PM0.1 by Using Positive Matrix Factorization

Deep Investigation of Ultrafine Particles in Urban Air

Estimating ambient particulate organic carbon concentrations and partitioning using thermal optical measurements and the volatility basis set

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