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Source apportionment
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The traffic factor increases during the day possibly due to the higher number of vehicles. Bivariate polar plots suggest the Houston Ship Channel area as the primary emission source for LPG, natural gas/crude oil, FCC/high temperature operations, and petrochemical industries.
16p
thebadguys
15-01-2022
10
0
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The present study sought to clarify the contributions to PM mass of ultrafine, fine (PM2.5), and coarse particles (PM10 – PM2.5) in an urban–industrial area with multiple emission sources. We performed both online measurements of PM at a high temporal resolution and size-resolved offline measurements.
11p
thebadguys
15-01-2022
9
0
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Weather Research and Forecast model (WRF) was coupled with Comprehensive Air Quality Model with Extensions (CAMx), and found that regional transport contributed significantly to PM2.5 pollution in Zhangjiakou (74.6%). The results of this study indicate that joint prevention and control of regional air pollution would meaningfully improve air quality in the BTH region.
12p
thebadguys
15-01-2022
9
2
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In this research we applied chemical mass balance (CMB) receptor modelling to determine VOCs source apportionment. One week VOCs observation data at Hanoi University of Science and Technology in June 2017 was applied for investigation. Fourteen VOC species among 55 of which were applied for CMB modelling. Transportation and biomass burning source profiles were developed by monitoring in this study.
8p
abcxyz123_02
03-03-2020
16
0
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The complexity of the volatile organic compound (VOC) mixture in the Houston area makes studies of the air quality in that area very challenging. In this paper, a novel factor analysis model, where the normal chemical mass balance model was augmented by a parallel equation that accounted for wind speed and direction, temperature, and weekend/weekday effects, was fitted with a multilinear engine (ME) to provide identification and apportionment of the VOC sources at the La Porte Municipal Airport site in Houston during the Texas Air Quality Study (TexAQS) 2000.
10p
cao_can
02-01-2013
54
2
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Hopke and co-workers (6), Heidam (7), Henry (8), and Barrie and Barrie (9) applied principal component analysis (PCA) to source identification, but Paatero and Tapper (10, 11) showed that PCA cannot provide a trueminimal variance solution since they are based on an incorrect weighting. In view of the limitations of PCA, a new technique, positive matrix factorization (PMF), was developed for sources identification and apportionment (12).
8p
cao_can
02-01-2013
56
2
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