Evaluation of vapor recovery systems efficiency and personal exposure in service stations in Mexico City

Cruz-Núñez, Xóchitl; Hernández-Solı́s, José M; Ruíz-Suárez, L. G.

doi:10.1016/s0048-9697(03)00048-2

Cited by 25 publications

(19 citation statements)

References 8 publications

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“…Note that the new units are not equipped with vapor recovery systems. Cruz-Núñez et al (2003) reported that installation of vapor recovery systems can reduce exposure levels of benzene by 99 % and toluene by 68 % in petrol stations in Mexico.…”

Section: Implementation Of Source Control Measuresmentioning

confidence: 99%

Investigation of gasoline distributions within petrol stations: spatial and seasonal concentrations, sources, mitigation measures, and occupationally exposed symptoms

Sairat

Homwuttiwong

Homwutthiwong

et al. 2015

Environ Sci Pollut Res

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We measured levels of VOCs and determined the distributions of benzene concentrations over the area of two petrol stations in all three seasons. Using the concentrations and sampling positions, we created isoconcentration contour maps. The average concentrations ranged 18-1288 μg m(-3) for benzene and 12-81 μg m(-3) for toluene. The contour maps indicate that high-level contours of benzene were found not only at the fuel dispenser areas but also at the storage tank refilling points, open drainage areas where gasoline-polluted wastewater was flowing, and the auto service center located within the station area. An assessment of the benzene to toluene ratio contour plots implicates that airborne benzene and toluene near the fuel dispenser area were attributed to gasoline evaporation although one of the studied stations may be influenced by other VOC sources besides gasoline evaporation. Additionally, during the routine refilling of the underground fuel storage tanks by a tank truck, the ambient levels of benzene and toluene increased tremendously. The implementation of source control by replacing old dispensers with new fuel dispensers that have an efficient cutoff feature and increased delivery speed can reduce spatial benzene concentrations by 77%. Furthermore, a questionnaire survey among 63 service attendants in ten stations revealed that headache was the most reported health complaint with a response rate of 32%, followed by fatigue with 20%. These prominent symptoms could be related to an exposure to high benzene concentrations.

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Section: Implementation Of Source Control Measuresmentioning

confidence: 99%

Investigation of gasoline distributions within petrol stations: spatial and seasonal concentrations, sources, mitigation measures, and occupationally exposed symptoms

Sairat

Homwuttiwong

Homwutthiwong

et al. 2015

Environ Sci Pollut Res

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“…These two VOC groups have been identified as the main species responsible for the ozone and secondary organic aerosol (SOA) formation in Mexico City (Gasca et al, 2004;Mugica et al, 2002a). High levels of aromatic hydrocarbons, particularly of toluene, benzene and xylenes, have been detected in different microenvironments and associated with diverse public transport systems in Mexico City (Shiohara et al, 2005;Gomez-Perales et al, 2004;Cruz-Nuñez et al, 2003;Bravo et al, 2002;Ortiz et al, 2002;Meneses et al, 1999).…”

Section: E Velasco Et Al: Measurements Of Volatile Organic Compoundmentioning

confidence: 99%

“…Traffic counts performed during the MCMA-2003 campaign on avenues close to the two sites indicated that at La Merced traffic stays high from 6:00 h until late evening, whereas at Pedregal there is the typical morning and afternoon rush hour peaks. Meteorological analysis by de Foy et al (2005) showed that in the basin, which includes La Merced, winds are very calm at sunrise leading to minimal horizontal dispersion. By sunset, wind speeds have reached a maximum leading to substantial dilution.…”

Section: Diurnal Patterns Of Various Vocs At Selected Sitesmentioning

confidence: 99%

Distribution, magnitudes, reactivities, ratios and diurnal patterns of volatile organic compounds in the Valley of Mexico during the MCMA 2002 & 2003 field campaigns

et al. 2007

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Abstract.A wide array of volatile organic compound (VOC) measurements was conducted in the Valley of Mexico during the MCMA-2002 and 2003 field campaigns. Study sites included locations in the urban core, in a heavily industrial area and at boundary sites in rural landscapes. In addition, a novel mobile-laboratory-based conditional sampling method was used to collect samples dominated by fresh on-road vehicle exhaust to identify those VOCs whose ambient concentrations were primarily due to vehicle emissions. Four distinct analytical techniques were used: whole air canister samples with Gas Chromatography/Flame Ionization Detection (GC-FID), on-line chemical ionization using a Proton Transfer Reaction Mass Spectrometer (PTR-MS), continuous real-time detection of olefins using a Fast Olefin Sensor (FOS), and long path measurements using UV Differential Optical Absorption Spectrometers (DOAS). The simultaneous use of these techniques provided a wide range of individual VOC measurements with different spatial and temporal scales. The VOC data were analyzed to understand concentration and spatial distributions, diurnal patterns, origin and reactivity in the atmosphere of Mexico City. The VOC Correspondence to: E. Velasco (evelasco@mce2.org) burden (in ppbC) was dominated by alkanes (60%), followed by aromatics (15%) and olefins (5%). The remaining 20% was a mix of alkynes, halogenated hydrocarbons, oxygenated species (esters, ethers, etc.) and other unidentified VOCs. However, in terms of ozone production, olefins were the most relevant hydrocarbons. Elevated levels of toxic hydrocarbons, such as 1,3-butadiene, benzene, toluene and xylenes, were also observed. Results from these various analytical techniques showed that vehicle exhaust is the main source of VOCs in Mexico City and that diurnal patterns depend on vehicular traffic in addition to meteorological processes. Finally, examination of the VOC data in terms of lumped modeling VOC classes and its comparison to the VOC lumped emissions reported in other photochemical air quality modeling studies suggests that some alkanes are underestimated in the emissions inventory, while some olefins and aromatics are overestimated.

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“…Exposure to benzene with a concentration of 20,000 parts per million (ppm) for a period of between 5 to 10 minutes can be fatal (International Agency for Research on Cancer, 1988) and it causes cancer diseases (Cruz-Núñez et al, 2003;Jo and Song, 2001). The results of the studies describe how exposure to benzene causes acutenonlymphocytic leukemia and preleukemia (Cruz-Núñez et al 2003;WHO, 1989).…”

Section: Introductionmentioning

confidence: 99%

“…The results of the studies describe how exposure to benzene causes acutenonlymphocytic leukemia and preleukemia (Cruz-Núñez et al 2003;WHO, 1989). The exposure limit of benzene in the workplace is 0.5 ppm, according to suggestions from the Occupational Safety and Health Ministry (USA) (Maltoni et al, 1990).…”

Section: Introductionmentioning

confidence: 99%

Predicting Atmospheric Concentrations of Benzene in the Southeast of Tehran using Artificial Neural Network

Asadollahfardi¹,

Mehdinejad²,

Mirmohammadi³

et al. 2015

Asian J. Atmos. Environ

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Air pollution is a challenging issue in some of the large cities in developing countries. In this regard, data interpretation is one of the most important parts of air quality management. Several methods exist to analyze air quality; among these, we applied the Multilayer Perceptron (MLP) and Radial Basis Function (RBF) methods to predict the hourly air concentration of benzene in 14 districts in the municipality of Tehran. Input data were hourly temperature, wind speed and relative humidity. Both methods determined reliable results. However, the RBF neural network performance was much closer to observed benzene data than the MLP neural network. The correlation determination resulted in 0.868 for MLP and 0.907 for RBF, while the Index of Agreement (IA) was 0.889 for MLP and 0.937 for RBF. The sensitivity analysis related to the MLP neural network indicated that the temperature had the greatest effect on prediction of benzene in comparison with the wind speed and humidity in the study area. The temperature was the most significant factor in benzene production because benzene is a volatile liquid.

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Evaluation of vapor recovery systems efficiency and personal exposure in service stations in Mexico City

Cited by 25 publications

References 8 publications

Investigation of gasoline distributions within petrol stations: spatial and seasonal concentrations, sources, mitigation measures, and occupationally exposed symptoms

Investigation of gasoline distributions within petrol stations: spatial and seasonal concentrations, sources, mitigation measures, and occupationally exposed symptoms

Distribution, magnitudes, reactivities, ratios and diurnal patterns of volatile organic compounds in the Valley of Mexico during the MCMA 2002 & 2003 field campaigns

Predicting Atmospheric Concentrations of Benzene in the Southeast of Tehran using Artificial Neural Network

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Evaluation of vapor recovery systems efficiency and personal exposure in service stations in Mexico City

Cited by 25 publications

References 8 publications

Investigation of gasoline distributions within petrol stations: spatial and seasonal concentrations, sources, mitigation measures, and occupationally exposed symptoms

Investigation of gasoline distributions within petrol stations: spatial and seasonal concentrations, sources, mitigation measures, and occupationally exposed symptoms

Distribution, magnitudes, reactivities, ratios and diurnal patterns of volatile organic compounds in the Valley of Mexico during the MCMA 2002 &amp; 2003 field campaigns

Predicting Atmospheric Concentrations of Benzene in the Southeast of Tehran using Artificial Neural Network

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Distribution, magnitudes, reactivities, ratios and diurnal patterns of volatile organic compounds in the Valley of Mexico during the MCMA 2002 & 2003 field campaigns