Emission factors and characteristics of criteria pollutants and volatile organic compounds (VOCs) in a freeway tunnel study

Chiang, Hung‐Lung; Ching-Shyung, Hwu; Shih-Yu, Chen; Wu, Ming-Ching; Sen-Yi, Ma; Huang, Yao-Sheng

doi:10.1016/j.scitotenv.2007.03.039

Cited by 56 publications

(4 citation statements)

References 28 publications

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“…These findings encourage our assignment of butanone as 'respirator peak'. 2-Methylpentane, a branched-chain alkane and a structural isomer of hexane, is associated with major emission by vehicle pollutants [38]. Yoshida et al were able to demonstrate an observable absorption amount of 2-methylpentane by inhalation in a rat model based on the knowledge of well-known diffusion from, e.g.…”

Section: Discussionmentioning

confidence: 99%

Influence of the respirator on volatile organic compounds: an animal study in rats over 24 hours

et al. 2015

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Long-term animal studies are needed to accomplish measurements of volatile organic compounds (VOCs) for medical diagnostics. In order to analyze the time course of VOCs, it is necessary to ventilate these animals. Therefore, a total of 10 male Sprague-Dawley rats were anaesthetized and ventilated with synthetic air via tracheotomy for 24 h. An ion mobility spectrometry coupled to multi-capillary columns (MCC-IMS) was used to analyze the expired air. To identify background contaminations produced by the respirator itself, six comparative measurements were conducted with ventilators only. Overall, a number of 37 peaks could be detected within the positive mode. According to the ratio peak intensity rat/ peak intensity ventilator blank, 22 peaks with a ratio >1.5 were defined as expired VOCs, 12 peaks with a ratio between 0.5 and 1.5 as unaffected VOCs, and three peaks with a ratio <0.5 as resorbed VOCs. The peak intensity of 12 expired VOCs changed significantly during the 24 h measurement. These results represent the basis for future intervention studies. Notably, online VOC analysis with MCC-IMS is possible over 24 h in ventilated rats and allows different experimental approaches.

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Section: Discussionmentioning

confidence: 99%

Influence of the respirator on volatile organic compounds: an animal study in rats over 24 hours

et al. 2015

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“…According to our tunnel tests in Tianjin, the EFs (mg km −1 veh −1 ) were 1.97±0.52 for benzene, 0.66±0.26 for ethylbenzene, 3.29±1.10 for toluene, 0.48±0.19 for o-xylene, and 1.42±0.42 for m/p-xylene. The emission level of BTEX in this study was compared to that of reported tunnel studies in Taiwan in 2000 (Hwa et al, 2002), Hong Kong in 2003(Ho et al, 2009, Guangzhou in 2004(Zhang et al, 2018c, Taiwan in 2005(Hung-Lung et al, 2007, Guangzhou in 2014 (Zhang et al, 2018c), Nanjing in 2015 (Zhang et al, 2018b), and Hong Kong in 2015 (Cui et al, 2018). As shown in Fig.9, the BTEX levels tested in recent four years (Guangzhou in 2014, Nanjing in 2015, Hong Kong in 2015, and Tianjin in 2017 decreased when compared to those tested during the last decades (Taiwan in 2000, Hong Kong in 2003, Guangzhou in 2004, and Taiwan in 2005.…”

Section: Btex and Diagnostic Ratiosmentioning

confidence: 99%

“…Figure 9. The BTEX levels observed in different tunnel studies (Taiwan in 2000(Hwa et al, 2002l; Hong Kong in 2003(Ho et al, 2009; Guangzhou in 2004(Zhang et al, 2018c; Taiwan in 2005(Hung-Lung et al, 2007; Guangzhou in 2014 (Zhang et al, 2018c); Nanjing in 2015 (Zhang et al, 2018b); Hong Kong in 2015 (Cui et al, 2018)), and the linear regressions (dash-dot lines filled with 95% regression confidence intervals) between the emission factors of BTEX and the test years.…”

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confidence: 99%

Vehicular volatile organic compounds (VOCs)-NOx-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment

Song

Liu

Sun

et al. 2018

Preprint

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Abstract. Vehicular emission is a key contributor to ambient volatile organic compounds (VOCs) and NOx in Chinese megacities. However, the information of real-world emission factors (EFs) for a typical urban fleet is still limited, hindering the development of a more reliable emission inventory in China. Based on a more-than-two-week (August 8&ndash;24, 2017) tunnel test in urban Tianjin in northern China, and on the use of a statistical regression model, the Positive Matrix Factorization (PMF) receptor model, and the Calculate Emissions from Road Transport (COPERT) IV model, characteristics of vehicular VOCs-NOx-CO emissions were analyzed systematically. The fleet-average EFs (pollutant: downslope, upslope, and overall in mgkm&minus;1veh&minus;1) were estimated respectively as follows: (NO: 61.92±72.46, 158.58±73.48, 97.52±69.84), (NO2: 16.52±11.49, 23.98±20.14, 15.86±9.38), (NOx: 79.45±78.43, 181.22±88.29, 116.56±77.61), and (CO: 269.96±342.38, 577.76±382.22, 344.67±250.01). The EFs of NO-NO2-NOx and CO from heavy-duty vehicles (or diesel vehicles) were differentiated from light-duty vehicles (or gasoline vehicles). The ratios (v/v) of NO2 to NOx in the primary vehicular exhaust were approximately 0.18±0.09, 0.10±0.22 and 0.10±0.05 for downslope, upslope, and the entire tunnel, respectively. The fleet-average EF of the 99-target non-methane VOCs (NMVOCs) was 40.56±12.18mgkm&minus;1veh&minus;1, lower than the previous studies in China. The BTEX (benzene, toluene, ethylbenzene, p-xylene, m-xylene and o-xylene) levels decreased by approximately 79% when emission standards increased from China I to China V. The source profiles of NMVOCs from the tailpipe and evaporative emissions were resolved by the PMF model. The evaporative emissions accounted for nearly one-half of the total vehicular VOC emissions, indicating that evaporative and tailpipe emissions contributed equally to VOC emissions. The relative contributions of evaporative NMVOC emissions to total vehicular NMVOC emissions are temperature-dependent with the average increasing ratio of 7.55%&deg;C&minus;1. The primary emission ratio (ER, m/m) of VOCs/NOx was approximately 2.04, suggesting that vehicular NOx and VOCs can be co-emitted with a proper ER. According to the vehicular ERs of VOCs/NOx in Tianjin (2000&ndash;2016) and China (2010&ndash;2030), as even more stringent emission standards are implemented in the future, the O3 chemical regimes were likely to be VOCs-limited (i.e., 8:1 threshold) for cities or regions where VOCs and NOx emissions are dominated by vehicular exhaust. Our study enriched the database on the fleet-average emission factors of on-road vehicles for emission inventory, air quality modeling, and health effects studies, provided implications for following O3 control in China from the view of primary emission, and highlighted the importance of further control of evaporative emissions.

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“…There are a series of studies analyzing on-road emissions [17][18][19][20][21][22]; some of them focus on different vehicle emission equipment, and others concern characteristics of regional vehicle emission. Others concern regional vehicle emission characteristics which were conducted in China, especially Beijing-Tianjin-Hebei, Yangtze River Delta and Pearl River Delta regions [23][24][25], yet little attention is paid to the southwest.…”

Section: Introductionmentioning

confidence: 99%

Real-World Vehicle Volatile Organic Compound Emissions and Their Source Profile in Chengdu Based on a Roadside and Tunnel Study

Feng

Hu²,

Zhou

et al. 2021

Atmosphere

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With the continuous progress of air pollution prevention and control in China, the study of the emission characteristics of vehicles has become increasingly important. An in situ experiment was performed in the Tianfu tunnel in Chengdu to determine the vehicle emissions of volatile organic compounds (VOCs). A total of 50 species of VOCs were quantified in the tunnel, with total concentrations in the range of 32.25–162.18 ppbv in the entrance and 52.90–233.92 ppbv in the exit, respectively. Alkanes were the most abundant group, followed by alkenes, aromatic hydrocarbons, oxygenated VOCs, alkynes and chlorocarbons. The general emission factors of the measured VOCs ranged from 141.71 mg veh−1 km−1 to 236.12 mg veh−1 km−1, and the average ± std was 177.31 ± 24.59 mg veh−1 km−1. The emission factors of diesel-fuelled vehicles, gasoline-fuelled vehicles and natural gas-fuelled vehicles were estimated based on linear regression analysis, with values of 272.39 ± 191.17 mg veh−1 km−1, 185.08 ± 12.85 mg veh−1 km−1 and 158.72 ± 3.21 mg veh−1 km−1, respectively. The results of roadside experiments indicate that the roadside ambience atmosphere contains many species characterized with vehicle emission features. Especially, there were fuel evaporation emission related substances, which were higher in content than tunnel samples.

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Emission factors and characteristics of criteria pollutants and volatile organic compounds (VOCs) in a freeway tunnel study

Cited by 56 publications

References 28 publications

Influence of the respirator on volatile organic compounds: an animal study in rats over 24 hours

Influence of the respirator on volatile organic compounds: an animal study in rats over 24 hours

Vehicular volatile organic compounds (VOCs)-NO<sub><i>x</i></sub>-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment

Real-World Vehicle Volatile Organic Compound Emissions and Their Source Profile in Chengdu Based on a Roadside and Tunnel Study

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Emission factors and characteristics of criteria pollutants and volatile organic compounds (VOCs) in a freeway tunnel study

Cited by 56 publications

References 28 publications

Influence of the respirator on volatile organic compounds: an animal study in rats over 24 hours

Influence of the respirator on volatile organic compounds: an animal study in rats over 24 hours

Vehicular volatile organic compounds (VOCs)-NO&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt;-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment

Real-World Vehicle Volatile Organic Compound Emissions and Their Source Profile in Chengdu Based on a Roadside and Tunnel Study

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Vehicular volatile organic compounds (VOCs)-NO<sub><i>x</i></sub>-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment