Spatial and seasonal variation and source apportionment of volatile organic compounds (VOCs) in a heavily industrialized region

Dumanoğlu, Yetkin; Kara, Melik; Altıok, Hasan; Odabaşı, Mustafa; Elbir, Tolga; Bayram, Abdurrahman

doi:10.1016/j.atmosenv.2014.08.048

Cited by 240 publications

(77 citation statements)

References 64 publications

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“…High fractions of C 5 -C 9 alkanes including hexane (32 ± 6.2 %), cyclohexane (40 ± 7.9 %), methylcyclohexane (47 ± 6.9 %), n-octane (56 ± 4.2 %), n-nonane (58 ± 2.9 %) and aromatics (i.e., 22 ± 3.0 % for benzene, 39 ± 5.4 for toluene and 45 ± 7.3 % for xylenes) were present (Fig. 10a), which was similar to the chemical compositions measured from the oil refineries (Liu et al, 2008;Dumanoglu et al, 2014). The calculated daily source contributions from the PMF model were well correlated with the high loading species in its source profiles.…”

Section: Oil Refiningsupporting

confidence: 71%

Monitoring of volatile organic compounds (VOCs) from an oil and gas station in northwest China for 1 year

et al. 2018

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Abstract. Oil and natural gas are important for energy supply around the world. The exploring, drilling, transportation and processing in oil and gas regions can release a lot of volatile organic compounds (VOCs). To understand the VOC levels, compositions and sources in such regions, an oil and gas station in northwest China was chosen as the research site and 57 VOCs designated as the photochemical precursors were continuously measured for an entire year (September 2014-August 2015) using an online monitoring system. The average concentration of total VOCs was 297 ± 372 ppbv and the main contributor was alkanes, accounting for 87.5 % of the total VOCs. According to the propylene-equivalent concentration and maximum incremental reactivity methods, alkanes were identified as the most important VOC groups for the ozone formation potential. Positive matrix factorization (PMF) analysis showed that the annual average contributions from natural gas, fuel evaporation, combustion sources, oil refining processes and asphalt (anthropogenic and natural sources) to the total VOCs were 62.6 ± 3.04, 21.5 ± .99, 10.9 ± 1.57, 3.8 ± 0.50 and 1.3 ± 0.69 %, respectively. The five identified VOC sources exhibited various diurnal patterns due to their different emission patterns and the impact of meteorological parameters. Potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models based on backward trajectory analysis indicated that the five identified sources had similar geographic origins. Raster analysis based on CWT analysis indicated that the local emissions contributed 48.4-74.6 % to the total VOCs. Based on the high-resolution observation data, this study clearly described and analyzed the temporal variation in VOC emission characteristics at a typical oil and gas field, which exhibited different VOC levels, compositions and origins compared with those in urban and industrial areas.

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Section: Oil Refiningsupporting

confidence: 71%

Monitoring of volatile organic compounds (VOCs) from an oil and gas station in northwest China for 1 year

et al. 2018

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“…This source, identified as vehicular emissions, explains 14.1% of ethylene, 53.7% of propane, and 35.4% of acetylene. These VOCs, indicated as tracers of emissions from vehicles, are consistent with other PMF-based studies for Los Angeles [53], Shanghai [57], Tianjin [58], Houston [59], and other receptor models, such as in Turkey reported by Dumanoglu et al [25].…”

Section: Source Identification By Pmfsupporting

confidence: 91%

“…However, large and inherent uncertainties exist in current emission inventories owing to inaccurate and incomplete information of emission sources, including source profiles, emission factors, and source activities [22]. The lack of complete emission profiles makes PMF the most used method to identify VOCs source [8,[23][24][25][26][27]]. The PMF model uses a statistical approach for quantifying the contribution of sources to samples; PMF only uses time serials of ambient VOC concentration as input [28] without any source profiles used in the chemical mass balance (CMB) model [29].…”

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confidence: 99%

An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan

et al. 2018

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The positive matrix factorization (PMF) model is widely used for source apportionment of volatile organic compounds (VOCs). The question about how to select the proper number of factors, however, is rarely studied. In this study, an integrated method to determine the most appropriate number of sources was developed and its application was demonstrated by case study in Wuhan. The concentrations of 103 ambient volatile organic compounds (VOCs) were measured intensively using online gas chromatography/mass spectrometry (GC/MS) during spring 2014 in an urban residential area of Wuhan, China. During the measurement period, the average temperature was approximately 25 • C with very little domestic heating and cooling. The concentrations of the most abundant VOCs (ethane, ethylene, propane, acetylene, n-butane, benzene, and toluene) in Wuhan were comparable to other studies in urban areas in China and other countries. The newly developed integrated method to determine the most appropriate number of sources is in combination of a fixed minimum threshold value for the correlation coefficient, the average weighted correlation coefficient of each species, and the normalized minimum error. Seven sources were identified by using the integrated method, and they were vehicular emissions (45.4%), industrial emissions (22.5%), combustion of coal (14.7%), liquefied petroleum gas (LPG) (9.7%), industrial solvents (4.4%), and pesticides (3.3%) and refrigerants. The orientations of emission sources have been characterized taking into account the frequency of wind directions and contributions of sources in each wind direction for the measurement period. It has been concluded that the vehicle exhaust contribution is greater than 40% distributed in all directions, whereas industrial emissions are mainly attributed to the west southwest and south southwest.Atmosphere 2018, 9, 390 2 of 18 and urbanization, megacities and city clusters in China are suffering from severe photochemical pollution [7]. Concern about VOC concentrations in China caused the central government to start controlling VOCs, during the 12th five-year period (2011)(2012)(2013)(2014)(2015), in key regions as well as the launch of VOCs monitoring programs and pilot projects [8]. There are extensive offline and online observations performed to investigate the current ambient status of VOCs in main populated cluster areas of China like the North China Plain [9-11], Yangtze Delta [12], and Pearl River Delta [13,14]. Reliable source identification is the premise of effective VOCs control measures. Bottom-up emission inventory summarizing the products of activity data and emission factors for all known individual sources and the up-bottom receptor model (RM) are widely used for source identification [15][16][17]. Studies have been conducted to obtain more accurate and reliable VOCs source profiles for on-road vehicle emissions [18,19] and industries [20,21]. However, large and inherent uncertainties exist in current emission inventories owing to inaccurate and incomplete infor...

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“…The geographical location of Istanbul (Black Sea in the north and the Marmara Sea in the south) produces surface heating differences leading to different meteorological conditions that play an important role in the transport of pollutants, especially of ozone (İm et al, 2008). Over the last 2 decades the only VOC measurements have been reported for other cities in Turkey by use of off-line sampling and GC-FID or GC-MS (gas chromatography mass spectrometry) analysis (Bozkurt et al, 2018;Yurdakul et al, 2013aYurdakul et al, , 2018Civan et al, 2015;Kuntasal et al, 2013;Demir et al, 2011;Pekey and Hande, 2011;Elbir et al, 2007;Muezzinoglu et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

Composition and variability of gaseous organic pollution in the port megacity of Istanbul: source attribution, emission ratios, and inventory evaluation

et al. 2019

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In the framework of the TRANSport Emissions and Mitigation in the East Mediterranean (TRANSEMED/ChArMEx) program, volatile organic compound (VOC) measurements were performed for the first time in Istanbul (Turkey) at an urban site in September 2014. One commercial gas chromatograph coupled to a flame ionization detector (GC-FID) and one proton transfer mass spectrometer (PTR-MS) were deployed. In addition, sorbent tubes and canisters were implemented within the megacity close to major emission sources. More than 70 species including non-methane hydrocarbons (NMHCs), oxygenated VOCs (OVOCs), and organic compounds of intermediate volatility (IVOCs) have been quantified. Among these compounds, 23 anthropogenic and biogenic species were continuously collected at the urban site.VOC concentrations show a great variability with maxima exceeding 10 ppb (i.e., n-butane, toluene, methanol, and acetaldehyde) and mean values between 0.1 (methacrolein + methyl vinyl ketone) and 4.9 ppb (methanol). OVOCs represent 43.9 % of the total VOC concentrations followed by alkanes (26.3 %), aromatic compounds (20.7 %), alkenes (4.8 %), terpenes (3.4 %), and acetonitrile (0.8 %).Five factors have been extracted from the Positive Matrix Factorization model (EPA PMF 5.0) and have been compared to source profiles established by near-field measurements and other external variables (meteorological parameters, NO x , CO, SO 2 , etc.). Surprisingly, road transport is not the dominant source, only explaining 15.8 % of measured VOC concentrations contrary to the local emission inventory. Other factors are toluene from solvent use (14.2 %), biogenic terpenes (7.8 %), natural gas evaporation (25.9 %) composed of butanes, and a last factor characterized by mixed regional emissions and composed of most of the species (36.3 %). The PMF model results point out the influence of industrial emissions while there is no clear evidence of the impact of ship emissions on the measured VOC distribution. For the latter additional measurements of organic compounds of Published by Copernicus Publications on behalf of the European Geosciences Union.

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Spatial and seasonal variation and source apportionment of volatile organic compounds (VOCs) in a heavily industrialized region

Cited by 240 publications

References 64 publications

Monitoring of volatile organic compounds (VOCs) from an oil and gas station in northwest China for 1 year

Monitoring of volatile organic compounds (VOCs) from an oil and gas station in northwest China for 1 year

An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan

Composition and variability of gaseous organic pollution in the port megacity of Istanbul: source attribution, emission ratios, and inventory evaluation

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