Browsing by Author "Awasthi, Amit"

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Collection efficiency and interstage loss of nanoparticles in micro-orifice-based cascade impactors
(2013-04-01)
Liu, Chun-Nan
;
Awasthi, Amit
;
Hung, Yi-Hung
;
Tsai, Chuen-Jinn
;
環境工程研究所
In this study, two micro-orifice-based cascade impactors, including the micro-orifice uniform deposit impactor (MOUDI, MSP Model 110) and the NCTU micro-orifice cascade impactor (NMCI), were tested for the collection efficiency and interstage loss of nanoparticles. In the NMCI, new nozzle plates with smooth nozzle shape made by the LIGA (Lithography, Electroplating, and Molding) process were used to replace the 7th-10th stages in one of the MOUDI. Test results show that after adjusting proper S/W ratios (S: jet to plate distance, W: nozzle diameter) to 2.52, 3.01, 13.44, and 24.75 for the 7th, 8th, 9th and 10th stage of the NMCI, respectively, and 5.56, 11.18, 9.3, and 10.9 for the 7th, 8th, 9th and 10th stage of the MOUDI, respectively, the cutoff aerodynamic diameters (d(pa50)) are close to the nominal values given in Marple et al. (1991). Different S/W ratios are needed due to differences in the nozzle shape and nozzle diameter between two cascade impactors. Total interstage loss of nanoparticles from the inlet to the 6th-10th stage of the MOUDI exists due to the convection-diffusion mechanism, which increases with decreasing d(pa). For the MOUDI, total loss is 2.9-15.3 % (d(pa): 105.8 to 15.4 nm) for the inlet to the 6th stage and it increases to 20.1-26.1 % (d(pa): 23 to 15.4 nm) for the inlet to the 10th stage, respectively. Similar but slightly lower loss also exists in the NMCI. Field comparison tests in the ambient air show that mass size distributions measured by the MOUDI agree well with those of the NMCI. Finally, nozzle clogging tests using high concentration incense smokes indicate that the NMCI has a much less tendency for particles to clog in the nozzles than the MODUI. (C) 2012 Elsevier Ltd. All rights reserved.
Differences in 24-h average PM2.5 concentrations between the beta attenuation monitor (BAM) and the dichotomous sampler (Dichot)
(2013-08-01)
Liu, Chun-Nan
;
Awasthi, Amit
;
Hung, Yi-Hung
;
Gugamsetty, Balakrishnaiah
;
Tsai, Chuen-Jinn
In this study, PM2.5 concentrations were measured simultaneously by a Dichotomous sampler (Dichot, Model SA241, Andersen Inc., Georgia, USA) (PM2.5,D) and a beta attenuation monitor (BAM) (PM2.5,B) at each of three air monitoring stations in Taiwan. Results show that PM2.5,B concentrations measured by the VEREWA-F701 BAM (without federal equivalent method (FEM) designation) are consistently higher than PM2.5,D concentrations by 58.4 37.4% at Jhongshan station, while less overestimation exists at Sinjhuang and judong stations, which is 29.8 +/- 20.2 and 28.4 +/- 19.0%, respectively, where the earlier version of the Met-One BAM-1020s (without FEM designation) are used. Different factors influencing the overestimation, which include aerosol water content, volatilization of inorganic species and positive artifacts due to acid gas adsorption by the glass fiber filter tapes were studied for the BAM-1020. Results show that the overestimation is mainly caused by the positive artifacts due to acid gas adsorption by the glass fiber filter tapes used in the BAM-1020. Aerosol water content and volatilization loss of inorganic semi-volatile species are found to be less important to the overestimation. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.
Sampling and conditioning artifacts of PM2.5 in filter-based samplers
(2014-03-01)
Liu, Chun-Nan
;
Lin, Sih-Fan
;
Awasthi, Amit
;
Tsai, Chuen-Jinn
;
Wu, Yueh-Chuen
Field studies were conducted at Taiwan National Chiao-Tung University (NCTU) campus to evaluate the evaporation loss of fine particles (PM2.5) collected by the multi-filter PM10-PM2.5 sampler (MFPPS), which was collocated with a dichotomous sampler (Dichot, Andersen, Model SA-241), a WINS PM2.5 sampler (Thermo, Model 2000-FRM), and a tapered element oscillating microbalance with the filter dynamic measurement system (TEOM-FDMS, Thermo, Model 1405-DF). Porous-metal denuder samplers (PDSs) were installed in sampling channels of the MFPPS to measure the concentration of evaporated ion species. Results showed that the evaporation loss in PM2.5 was severe during sampling, accounting for 5.8-36.0% of the corrected PM2.5 concentration and the percentage increased with decreasing loaded particle mass and increasing filtration velocity. During 24-h sampling, the evaporated NH4+, NO3- and Cl- concentrations accounted for 9.5 +/- 6.2, 5.4 +/- 3.7, and 2.0 +/- 1.3% in corrected PM(2.)5 concentration, respectively, or 46.4 +/- 19.2, 66.9 +/- 18.5, and 74.4 +/- 14.0% in the concentration of each species, respectively. Due to the evaporation loss, PM2.5 concentrations measured by the WINS, Dichot, and MFPPS were lower than those the TEOM-FDMS by 16.6 +/- 9.0, 15.2 +/- 10.6 and 12.5 +/- 8.8%, respectively. When the MFPPS PM(2.)5 concentrations were corrected for the evaporated loss determined by the PDS, good agreement with those by the TEOM-FDMS was achieved. (C) 2013 Elsevier Ltd. All rights reserved.
Source Characterization and Apportionment of PM10, PM2.5 and PM0.1 by Using Positive Matrix Factorization
(2012-08-01)
Gugamsetty, Balakrishnaiah
;
Wei, Han
;
Liu, Chun-Nan
;
Awasthi, Amit
;
Hsu, Shih-Chieh
Ambient Particulate Matters (PM10, PM2.5 and PM0.1) 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 PM10, PM2.5 and PM0.1 were found to be 39.45 +/- 11.58, 21.82 +/- 7.50 and 1.42 +/- 0.56 mu g/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.
"Source Characterization and Apportionment of PM10, PM2.5 and PM0.1 by Using Positive Matrix Factorization"
(2012-08-01)
Gugamsetty, Balakrishnaiah
;
Wei, Han
;
Liu, Chun-Nan
;
Awasthi, Amit
;
Hsu, Shih-Chieh
"Ambient Particulate Matters (PM10, PM2.5 and PM0.1) 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 PM10, PM2.5 and PM0.1 were found to be 39.45 +/- 11.58, 21.82 +/- 7.50 and 1.42 +/- 0.56 mu g/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."