Temporal variations of VOC concentrations in Bursa atmosphere

Yurdakul, Sema; Civan, Mihriban; Kuntasal, Öznur Oğuz; Doğan, Güray; Pekey, Hakan; Tuncel, Gürdal

doi:10.1016/j.apr.2017.09.004

Cited by 70 publications

(25 citation statements)

References 66 publications

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“…When the ratio of T/B is greater than 2, this indicates that volatile organic solvents, such as paint, are also an important source of NMHCs emissions (Xu et al, ), in addition to the traffic source. When the T/B value is less than 2, this shows that nontransportation sources (Yurdakul et al, ), such as industrial and fossil fuel combustion (Barletta et al, ), contribute significantly to the atmospheric NMHC composition. The seasonal variations in the T/B ratio are shown in Figure a.…”

Section: Resultsmentioning

confidence: 99%

“…The specific ratios of NMHCs are often used to make preliminary determinations regarding the sources of atmospheric NMHCs and the aging of air masses (An, Zhu, Wang, Li, et al, 2014;C. Liu et al, 2017;Yurdakul et al, 2017). Benzene is an important component of NMHCs, and the ratio of toluene-to-benzene (T/B) is often used to identify sources of pollution.…”

Section: Specific Ratios Of Nmhcsmentioning

confidence: 99%

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Source Apportionment and Secondary Transformation of Atmospheric Nonmethane Hydrocarbons in Chengdu, Southwest China

et al. 2018

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Nonmethane hydrocarbons (NMHCs) have an important influence on the formation of photochemical smog and secondary organic aerosols in the atmosphere. We investigated 55 NMHCs in Chengdu from 27 October 2016 to 30 September 2017 to identify their sources, pollution levels, and secondary transformation potential. The average concentration of NMHCs in Chengdu was 41.8 ± 20.8 ppbv. Meteorological conditions play a vital role in the formation and dispersion of NMHCs, PM2.5, and O3. The photochemical conversion of NMHCs was inhibited by lower solar radiation, leading to low O3 concentrations and high NMHC concentrations. Aromatics and alkenes played a leading role in the secondary transformation, accounting for 60 ± 16% and 29 ± 11% of the total secondary formation potential, respectively. The southwest air mass trajectory was the most significant transportation path affecting the NMHC concentration in Chengdu. The results of the positive matrix factorization model indicated that there were seasonal differences in the sources of NMHCs in Chengdu. Four major emission sources were identified, namely, vehicle exhaust, industrial, paint solvents, and biogenic sources. Vehicle exhaust emissions were the greatest contributor to NMHCs in Chengdu, accounting for approximately 45% of the NMHCs. Overall, toluene, m/p‐xylene and ethylbenzene constitute a large fraction of the calculated ozone and secondary aerosol formation potential. Future studies should consider targeting these compounds when evaluating ozone and aerosol reduction strategies. However, in terms of total control of NMHC pollution, Chengdu should focus on effective control measures for traffic emissions.

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Section: Resultsmentioning

confidence: 99%

Section: Specific Ratios Of Nmhcsmentioning

confidence: 99%

Source Apportionment and Secondary Transformation of Atmospheric Nonmethane Hydrocarbons in Chengdu, Southwest China

et al. 2018

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“…Absence of combustion products such as acethylene and isopentane promotes this result. Presence of propane and isobutane also suggests that LPG fuel exhaust emissions is merged into Factor 1 as they are also the good markers of LPG emissions (Kuntasal, 2005;Yurdakul, 2014). Factor 1 accounts for approximately 35% of the system variance, which makes this factor by far the most important source of VOCs measured in Ankara atmosphere.…”

Section: Factor Analysismentioning

confidence: 99%

“…Samples are collected for 25 minutes with 20 ml/min flow rate to obtain 500 ml sample volume. Trap temperature starts at -15 °C for the quantification of ethane and acetylene, (Yurdakul, 2014) rises to 300 °C and is held for 3 minutes. After cold trap, sample is injected to the system.…”

Section: Sampling Campaignmentioning

confidence: 99%

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Source Identification of VOCs In METU Campus Through Factor Analysis

Uzunpınar¹,

Sert²,

Kilavuz³

et al. 2018

Issue 1

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In this study, 51 ozone precursor VOCs, which are routinely measured in PAMS (Photochemical Assessment Monitoring Station) were measured in a suburban station located at Middle East Technical University, Environmental Engineering Department in, Ankara. Daily air samples were collected in evacuated canisters between JanuaryDecember, 2014. Collected samples were analyzed with GC-FID system and concentrations of 51 VOCs were determined. Mean VOC concentrations ranged between 0.048±0.061 µg m -3 (cis-2-penten) and 10±13 µg m-3 (toluene). Average benzene concentration was 1.49 ± 1.74 μg m -3. Factor Analysis (FA) was applied to determine the major sources of VOCs that contribute to the measured concentrations in the university campus. FA application revealed nine factors that can be grouped under four major components, including (1) transportation: gasoline vehicle exhaust emissions, evaporative losses from gasoline vehicles, gasoline evaporation in gas stations and diesel emissions, (2) industrial emissions: industrial evaporation and industrial application, (3) solvent emissions: surface coatings and solvent use and (4) asphalt application.

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Temporal dynamics, meteorological effects, secondary organic aerosol estimation, and source identification of size‐segregated carbonaceous aerosols

Tarhan,

Koçak

2024

CLEAN Soil Air Water

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During the period 2019–2020, size‐segregated aerosol samples containing elemental and organic carbon (EC and OC) were investigated. These samples were collected weekly using an eight‐stage cascade impactor from an urban site located at Aksaray University, Aksaray. The quantification of EC and OC was carried out through a thermal‐optical transmission device. The results revealed consistent size distribution attributes of EC and OC between winter and summer. Although EC accounted for an insignificant percentage (4.4%) of particulate matter (PM) in the PM9.0–10.0 fraction during winter, a more substantial portion of OC in the same fraction (13.4%) comprised EC. Seasonal variations were distinct for EC but not significant for OC. Strong correlations between OC and EC were observed in coarse particle fractions, indicating a common source, with weaker correlations in fine particles. The highest OC/EC ratio was in the PM0.43–0.65 fraction, followed by PM2.1–3.3. The ratio of OC to EC in fine PM exceeded the threshold of 15 consistently. The observation indicates that as particle size increases, there is a noticeable decline in the OC to EC ratios. Secondary organic aerosols (SOA) accounted for 60.8% (winter) and 89.8% (summer) of OC values, emphasizing the substantial impact of SOA on Aksaray's atmosphere. Both seasons exhibited a multimodal distribution of ambient OC. In winter, the EC distribution was dominated by fine particles, with a bimodal pattern (PM1.1–2.1 and PM0.43–0.65 peaks). Common pollutant sources, including traffic emissions, road dust, biogenic emissions, and coal combustion, were identified for both seasons in coarse and fine particle fractions. These findings underscore the importance of emission control strategies targeting fine PM in Aksaray.

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Temporal variations of VOC concentrations in Bursa atmosphere

Cited by 70 publications

References 66 publications

Source Apportionment and Secondary Transformation of Atmospheric Nonmethane Hydrocarbons in Chengdu, Southwest China

Source Apportionment and Secondary Transformation of Atmospheric Nonmethane Hydrocarbons in Chengdu, Southwest China

Source Identification of VOCs In METU Campus Through Factor Analysis

Temporal dynamics, meteorological effects, secondary organic aerosol estimation, and source identification of size‐segregated carbonaceous aerosols

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