Measurement and source characteristics of carbonyl compounds in the atmosphere in Kaohsiung city, Taiwan

The concentrations of 18 atmospheric carbonyls species were measured at Nan-Chie and Hsiung-Kong sites in Kaohsiung City, Taiwan, during the summer and winter of 2006. Formaldehyde and acetaldehyde were the most abundant carbonyls with respective annual mean concentrations of 17.99 μg/m 3 and 13.69 μg/m 3 at Nan-Chie, and 21.47 μg/m 3 and 16.68 μg/m 3 at Hsiung-Kong; altogether the two species accounted for approximately 56-57% of total carbonyls. In summer, the total concentrations of carbonyls were 74.06 μg/m 3 and 89.99 μg/m 3 at Nan-Chie and Hsiung-Kong, respectively. In winter, the concentrations were 37.14 μg/m 3 and 46.50 μg/m 3 at Nan-Chie and Hsiung-Kong, respectively. Measured results indicated the predominance of photolysis and photooxidation reactions of aldehydes in summer. In this study, receptor models using principal component analysis (PCA) and absolute principal component scores (APCS) suggest that the primary pollution sources at Nan-Chie in the summer were secondary emissions/vehicle exhausts (gasoline engines)/stationary emissions (food industry), stationary emissions (petrochemical)/waste treatment and restaurant emissions; the primary pollution sources at Nan-Chie in winter were vehicle exhausts (gasoline engines)/stationary emissions (petrochemical) and restaurant emissions. At Hsiung-Kong, the primary pollution sources in summer were secondary emissions/vehicle exhausts (gasoline engines and diesel engines)/stationary emissions (metal assembly), restaurant emissions and others; the primary pollution sources in winter were vehicle exhausts (gasoline engines)/restaurant emissions and vehicle exhausts (diesel engines)/stationary emissions (metal assembly).

Section: Pca/apcs Receptor Modelsmentioning

confidence: 99%

Seasonal Variation and Source Apportionment of Atmospheric Carbonyl Compounds in Urban Kaohsiung, Taiwan

Wang

Huang

Chen

et al. 2010

“…Anthropogenic activities like vehicular emission and biomass burning have been reported as the significant sources of CCs in various studies all over the world (Possanzini et al, 1996;Kean et al, 2001;Ho et al, 2002a, b;Wang et al, 2010;Chen et al, 2014). In addition to that significant emission flux of many CCs has been observed from the waste dumping sites .…”

Section: Seasonal Variation Of the Carbonyl Compoundsmentioning

confidence: 99%

How the Atmosphere over Eastern Himalaya, India is Polluted with Carbonyl Compounds? Temporal Variability and Identification of Sources

Sarkar

Chatterjee

Majumdar

et al. 2017

A study was conducted on atmospheric carbonyl compounds for the first time over a Himalayan atmosphere in India. Samples were collected from a high altitude hill station, Darjeeling (27.01°N, 88.15°E, 2200 masl) during June 2012 to May 2013. Temporal variation, meteorological influence, source apportionment and ozone formation potential etc were studied for acetaldehyde, formaldehyde, acetone, butanaldehyde, propanaldehyde, benzaldehyde, crotonaldehyde, valeraldehyde, isovaleraldehyde, hexanaldehyde, p-tolualdehyde and o-tolualdehyde. High concentration of Acetone (81.6 ± 63.5 µg m -3 ) was observed which could be due to the higher photochemical production from its precursor volatile organic compounds emitted from tea plants and tea processing units. The concentration of acetaldehyde (20.7 ± 47.6 µg m ). Meteorological parameters like temperature and surface reaching solar radiative flux played the major roles for the seasonal variation of the carbonyl concentration over the hill station. The average ratio of formaldehyde to acetaldehyde over Darjeeling was found to be 1.64 ± 1.43 well representing a typical urban atmosphere at this part of Himalaya. Positive matrix factorization model showed that the biogenic emissions from tea plants and vehicular emissions were the major sources of carbonyl compounds over the hill station.

“…It was performed by utilizing the orthogonal transformation method with varimax rotation to determine the eigenvalues of variance matrix of original variables; usually, factors with eigenvalues > 1 were chosen. (Amaya et al, 2009;Wang et al, 2010). Once a factor is determined by PCA, it consists of patterns of variation of the factor loadings of input parameters.…”

Section: The Pca/apcs Receptor Modelsmentioning

confidence: 99%

“…The factor loadings indicate the correlation of each species with each component and a species was said to load on a given component if the factor loading was 0.5 or greater for that component. The characteristics of a factor can then be inferred from the dominant pollutants, such as VOCs, PAHs and carbonyl compounds (Ho et al, 2002;Chang et al, 2009;Guo et al, 2009;Wang et al, 2010).…”

Section: The Pca/apcs Receptor Modelsmentioning

confidence: 99%

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Measurements and PCA/APCS Analyses of Volatile Organic Compounds in Kaohsiung Municipal Sewer Systems, Southern Taiwan

Huang

Chen

Wang

2012

This study measured 71 volatile organic compounds (VOCs) collected using stainless steel canisters at 15 monitoring sites in two main Kaohsiung municipal sewers, A-Sewer and B-Sewer, during winter and summer periods in 2008 and 2009. The results indicate that the overall average of total VOCs, TVOC, in A-Sewer was 1173.51 ± 187.69 μg/m 3 , which was about 40% higher than that in B-Sewer (689.22 ± 151.64 μg/m 3 ). However, TVOC in the winter/dry season was about three (or five) times that in the summer/wet season for A-Sewer (or B-Sewer). For the A-Sewer, chlorinated organics, aromatics, and alkanes were predominant, and altogether contributed to about 90.0% of the TVOC in winter and about 70.6% in summer, with alkenes, ethers, ketones, and sulfur compounds as minor components. For B-sewer, aromatics, alkanes, and chlorinated organics were predominant, and altogether contributed to about 94.1% of the TVOC in winter and about 74.3% in summer, while others were minor ones. The principal component analysis (PCA) and absolute component scores (APCS) models indicate that the percentage source contributions for A-Sewer were solvent usage (31.65 ± 11.27%), oil refineries and storage leaks (28.71 ± 11.52%), auto paintings (19.14 ± 9.74%), asphalt plants (17.05 ± 8.73%), and others (3.45 ± 3.95%). The percentage source contributions for B-Sewer were printing factories (45.35 ± 9.19%), oil refineries and storage leaks (31.78 ± 8.59%), solvent usage (18.64 ± 8.50%), and dry cleaning (4.23 ± 4.70%).