Emission Factors for Gas-Powered Vehicles Traveling Through Road

Environ. Sci. Technol. 2006, 40, 6722-6729

Emission Factors for Gas-Powered Vehicles Traveling Through Road Tunnels in Saõ Paulo, Brazil L E I L A D . M A R T I N S , * ,† MARIA F. ANDRADE,† EDMILSON D. FREITAS,† A N G EÄ L I C A P R E T T O , ‡ L U C I A N A V . G A T T I , ‡ EÄ D L E R L . A L B U Q U E R Q U E , § EDSON TOMAZ,§ MARIA L. GUARDANI,⊥ MARIA H. R. B. MARTINS,⊥ AND OLIMPIO M. A. JUNIOR⊥ Department of Atmospheric Sciences, Institute of Astronomy, Geophysics and Atmospheric Sciences, University of Saõ Paulo, Saõ Paulo, 05508-900, Brazil, Atmospheric Chemistry Laboratory, Institute for Energy and Nuclear Research, Department of Chemical Process Development, School of Chemical Engineering, State University of Campinas, and Saõ Paulo State Environmental Regulation Agency

The objective of this study was to improve the vehicular emissions inventory for the light- and heavy-duty fleet in the metropolitan area of Saõ Paulo (MASP), Brazil. To that end, we measured vehicle emissions in road tunnels located in the MASP. On March 22-26, 2004 and May 04-07, 2004, respectively, CO, CO2, NOx, SO2, and volatile organic compounds (VOCs) emissions were measured in two tunnels: the Janio Quadros, which carries light-duty vehicles; and the Maria Maluf, which carries light-duty vehicles and heavy-duty diesel trucks. Pollutant concentrations were measured inside the tunnels, and background pollutant concentrations were measured outside of the tunnels. The mean CO and NOx emission factors (in g km-1) were, respectively, 14.6 ( 2.3 and 1.6 ( 0.3 for light-duty vehicles, compared with 20.6 ( 4.7 and 22.3 ( 9.8 for heavy-duty vehicles. The total VOCs emission factor for the Maria Maluf tunnel was 1.4 ( 1.3 g km-1. The main VOCs classes identified were aromatic, alkane, and aldehyde compounds. For the heavy-duty fleet, NOx emission factors were approximately 14 times higher than those found for the lightduty fleet. This was attributed to the high levels of NOx emissions from diesel vehicles.

Introduction It is well-known that vehicular emissions make a significant contribution to air contamination in urban areas. In the metropolitan area of Saõ Paulo (MASP), a megacity located in southern Brazil, vehicular emissions are responsible for approximately 98, 97, and 96%, respectively, of all emissions of carbon monoxide (CO), hydrocarbons (HCs) and nitrogen oxides (NOx) (1). There are three different methods of estimating such emissions: dynamometer tests of individual * Corresponding author phone: +55-11-3091-2836; fax: +55-113091-4714; e-mail: [email protected]. † University of Sa ˜ o Paulo. ‡ Institute for Energy and Nuclear Research. § State University of Campinas. ⊥ Sa ˜ o Paulo State Environmental Regulation Agency. 6722

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vehicles; measurements taken in tunnels; and on-board monitoring (2). Emission factors obtained from in-tunnel measurements represent the bulk of emissions from a large number of vehicles of various types used in urban areas. In addition, these emission factors can be useful as reference points in discussions regarding emissions inventories and vehicular emission control strategies. Estimating emission factors from in-tunnel measurements has been proposed by various authors (2-7). In-tunnel measurements allow the actual emissions for a variety of vehicles to be obtained under certain driving conditions (hot start) and provide information that complements dynamometer test results. The MASP has a vehicle fleet of approximately 7.8 million vehicles, of which 84.9% are light-duty vehicles, 5.8% are heavy-duty vehicles, and 9.3% are motorcycles. This fleet is unique in that most of the vehicles are fueled by ethanol or by a gasoline-ethanol mixture: 14.5% of the fleet burns hydrated ethanol (95% v/v); and 69.5% burns a mixture containing 75-78% gasoline (by volume) and 22-25% ethanol (a blend referred to as gasohol). Therefore, approximately 34% of the fuel burned by the fleet is ethanol (1). Recently, flex-fuel vehicles (capable of burning either gasohol or ethanol) and converted vehicles (which burn compressed natural gas) were introduced into this vehicular fleet. At the time of this study, the concentration of sulfur in diesel fuel sold in large metropolitan areas of Brazil, such as the MASP (1100 ppm), was lower than that in diesel fuel sold in other areas of the country (3500 ppm). In summary, the MASP presents an unconventional mixture of vehicle types and fuels, and the profile of its vehicle fleet has changed substantially in the last several years. Due to their toxicity, vehicle-emitted volatile organic compounds (VOCs), especially those such as benzene, directly or indirectly influence human health, as do aldehydes, aromatics, and most alkenes, which are precursors of secondary pollutants such as ozone and secondary organic aerosol. This study is the first attempt to estimate the VOCs emission factors from vehicles in road tunnels in Brazil. The significance of this study is also related to the previously mentioned characteristics of the MASP vehicle fleet. The most widely consumed fuel is a blend of gasoline (22-25% ethanol) and there are more than 1 million vehicles running on pure ethanol. The number of diesel-powered vehicles is also significant, mainly due to high the levels of NOx and particulate matter they emit. This study reports the results of field measurements of air pollutants released in road tunnels. The main goals of this study were as follows: to identify the characteristics of gaseous pollutants in a road tunnel; to measure in-tunnel emission factors for the MASP fleet in terms of gaseous NOx, CO, and VOCs; and to characterize the VOCs emitted by the MASP fleet.

Experimental Section Sampling Location. Field measurements were carried out in two road tunnels within the MASP. From March 22 to 26, 2004, measurements were taken in the Janio Quadros (JQ) tunnel, and from May 04 to 07, 2004, measurements were taken in the Maria Maluf (MM) tunnel. The JQ tunnel is located in the southwest portion of Saõ Paulo. It is a twolane tunnel that is 1900 m in length, and the traffic in both lanes flows in the same direction. The in-tunnel emissions are mainly from gasohol- and ethanol-powered vehicles. The speed limit inside the tunnel is 70 km h-1, and the ventilation system operates continuously. In addition, there is a slight 10.1021/es052441u CCC: $33.50

 2006 American Chemical Society Published on Web 10/04/2006

TABLE 1. Species Measured in the Janio Quadros and Maria Maluf Tunnels, Together with Data Regarding Methods and Sampling Sites species measured NOx CO

SO2a CO2 HCs HCs carbonyls

method and analyzer

measurement site

chemiluminescences thermo electron (42B), 0.5 ppbv detection limit nondispersive infrared techniquesthermo electron (48B), 0.1 ppm detection limit pulse fluorescences thermo electron (43B), 1 ppbv detection limit combined infrared gas analysissLI-COR 6262 system GC/FID and GC/MS analysissstainless steel canisters GC/FID detections tubes HPLC analysiss DNPH-cartridge

in-tunnel and fresh air in-tunnel and fresh air

in-tunnel in-tunnel and fresh air in-tunnel and fresh air in-tunnel and fresh air in-tunnel and fresh air

a No measurements of SO in background ambient air were taken 2 in either tunnel.

downhill grade. The MM tunnel is located in the southeast portion of the city. It carries light-duty and heavy-duty vehicles burning gasohol, ethanol, or diesel. It is 1020 m in length, has four 5.15-m wide lanes (two traveling in each direction), and the terrain is level. A concrete wall approximately 16 m in width separates the west-bound traffic from the east-bound traffic. At the tunnel midpoint, there is an open corridor connecting the two sides, which is where the measurements were taken. Ventilation fans on the roof of the tunnel operate continuously to provide fresh air. For both tunnels, in-tunnel pollutant concentrations were measured at the midpoint, and the background air was measured outside the tunnels. The sites outside the tunnels were located far from the tunnels in order to avoid their influence. In addition, in the region surrounding each tunnel, there are no other potential sources of pollutant emissions. Sampling and Analysis. On workdays, air samples for analysis of CO, NOx, and SO2 were collected continuously by the Saõ Paulo State Companhia de Tecnologia de Saneamento Ambiental (CETESB, Environmental Regulation Agency) [The official annual report of air quality in the MASP provided by CETESB is available at http://www.cetesp.sp.gov.br.], and air samples for analysis of CO2 were collected from 8:00 to 18:00. In-tunnel measurement and sampling methods are summarized in Table 1. In addition, VOCs were sampled and analyzed using three different methods. In the first method, HCs were sampled by drawing air through a stainless steel, vacuum canister at 50 mL min-1. In the second method, the HCs were sampled in a tube containing Tenax TA adsorbent (Supelco, Bellefonte, PA), at 35 mL min-1, using an automated sequential tube sampler (STS-25; Perkin-Elmer, Norwalk, CT). For measurements of carbonyl compounds (third method), the air was drawn into a cartridge containing 2,4-dinitrophenylhydrazine (Sep-Pak DNPH-Silica; Waters, Milford, MA) at 2 L min-1. All samplings were conducted over 2-h periods between the hours of 8:00 and 18:00. Measurements taken outside of the tunnels were also conducted within the same time frames. Ozone scrubber filters (Waters) were used to avoid artifact formation on ambient samples. The canisters were analyzed in the Laboratory of Atmospheric Chemistry of the Instituto de Pesquisas Energe´ticas e Nucleares (IPEN, Institute for Energy and Nuclear Research). Gas chromatography-mass spectrometry (CG-MS, Varian 3800, Saturn 2000) was used to identify HCs, and simulta-

neously in the same chromatography a flame ionization detection was used to quantify HCs as described in detail by Pretto (8). The HCs were separated on a DB-1 column (J & W Scientific, Folsom, CA) with a length of 60 m, an inside diameter (i.d.) of 0.32 mm and a film thickness of 1 µm. After separation, the samples were divided between the two detectors. The quantification of HCs was performed using four certified gas mixtures (Scott Specialty Gases, Plumsteadville, PA). The analysis conditions were as follows: 200 °C injector; Helium, as the carrier gas, at a constant flow rate of 2.2 mL min-1; oven initial temperature of -50 °C, increased by 6 °C min-1 until reaching 200 °C, then allowed to return to -50 °C; 1.3-kV detector tension. Possible artifacts due to interactions of HCs with components of ambient air, such as ozone, water vapor, or free radicals are sources of errors in determination of HCs concentrations (9). The uncertainty of analysis is dependent upon compound. For this analysis, detection limits ranged from 0.03 to 0.07 ppbv for the GCMS used, and the relative standard deviation (RSD) for 40 VOCs were between 2.4 and 8.1% (8). The tubes were analyzed at the State University of Campinas (Saõ Paulo, Brazil) using a thermal desorber (ATD400; Perkin-Elmer) coupled to the GC-FID system (AutoSystem XL; Perkin-Elmer). The HCs were separated on a CIOLA-1 column (100% dimethylpolysiloxane; 60-m length; 0.25-mm i.d.; 0.2-µm film thickness). The analysis conditions used were as follows: carrier gas: helium 5.0; desorption temperature: 300 °C; desorption flow: 60 mL min-1; split: 25 mL min-1; temperature program: 35 °C for 10 min, 35100 °C at 5 °C min-1, 100 °C for 2 min; detector temperature: 250 °C. In addition, experimental error ranged from 4 to 20% for compounds and intervals of concentrations obtained by the method in ref 10. The analysis of carbonyls was performed at the University of Saõ Paulo Institute of Chemistry using a high-performance liquid chromatography (HPLC) system (SCL-10A; Shimadzu, Tokyo, Japan). The analytical apparatus includes a Rheodyne injection valve with a 20-µL sample loop, two pumps (LC10AD; Shimadzu) and an UV/visible detector (SPD-10AV UVvis; Shimadzu) at 365 nm. Hydrazones were separated using a Shimadzu Shim-pack CLC-ODS column (15 cm × 6 mm × 5 µm) connected to a Shim-pack G-ODS precolumn operated at ambient temperature (25 °C). Concentrations of carbonyls in air samples were calculated using the calibration data of the external carbonyl DNPH standards (11-13). The RSD was estimated at 6.3% for formaldehyde and 4.4% for acetaldehyde, with detection limits of 0.196 ppbv and 0.137 ppbv, respectively. For the other carbonyls analyzed, the degree of uncertainty of analysis varied on the same order, with detection limits ranging from 1 pptv to 0.4 ppbv. Traffic Volume. Traffic volume through the tunnel was counted manually at 15-minute intervals throughout the sampling day (8:00-18:00), using a supplemental video system. The data represents every other interval. Vehicles using the JQ tunnel were classified as motorcycles, light passenger vehicles, or light-duty trucks/vans, whereas those using the MM tunnel were classified as motorcycles, light passenger vehicles, or heavy-duty vehicles. Classifications were made in function of fuel burned and vehicle class.

Results and Discussion Diurnal Profiles. During a typical working day, approximately 30 000 vehicles pass through the JQ tunnel. Most are light passenger vehicles, approximately 95% of which burn gasohol or pure ethanol. Including all four lanes, approximately 70 000 light and heavy vehicles pass through the MM tunnel on a daily basis. Data describing the traffic profile for both tunnels is presented in Table 2. Gasohol is the principal fuel burned by vehicles using either tunnel. VOL. 40, NO. 21, 2006 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 2. Average Composition of the Vehicle Fleets Using the Janio Quadros or Maria Maluf Tunnels in 2004 date March 23 March 24 March 25 March 26b May 5 May 6

vehicle type

fuel

light passenger vehiclea motorcycle light-duty truck or van light passenger vehicle motorcycle light-duty truck or van light passenger vehicle motorcycle light-duty truck or van light passenger vehicle motorcycle light-duty truck or van light passenger vehicle motorcycle heavy-duty vehicle light passenger vehicle motorcycle heavy-duty vehicle

gasohol/ethanol gasohol diesel gasohol/ethanol gasohol diesel gasohol/ethanol gasohol diesel gasohol gasohol diesel gasohol/ethanol gasohol diesel gasohol/ethanol gasohol diesel

vehicle count 26 150 2054 1058 27 576 2358 1348 27 024 2370 950 14 548 1322 934 54 928 7886 9472 49 646 7746 9230

traffic volume (veh. h-1) 2615 ( 537 205 ( 66 106 ( 72 2757 ( 586 236 ( 72 135 ( 93 2702 ( 544 237 ( 62 95 ( 30 2425 ( 466 220 ( 32 156 ( 53 5774 ( 860 833 ( 186 990 ( 172 4965 ( 1004 775 ( 135 923 ( 251

% of the fleet 89.4 7.0 3.6 88.2 7.5 4.3 89.0 7.8 3.1 86.6 7.9 5.6 76.2 10.6 13.1 74.5 13.8 12.0

a Taxis were counted as light passenger vehicles, although most burn natural gas. Taxis were estimated to account 0.7% of the fleet (14). measured from 8:00 until 14:00.

b

Only

FIGURE 1. Mean workday in-tunnel diurnal profiles of CO, NOx, and SO2 in the Janio Quadros tunnel (JQT) and Maria Maluf tunnel (MMT). On average, 13% of the vehicles using the MM tunnel were diesel-powered. In Figure 1, the CO, NOx, and SO2 concentrations observed in both tunnels are presented. Total NOx concentrations were converted to µg m-3 using a molecular weight of 46 g mol-1 and are reported as NO2 mass equivalents even though most of the NOx was emitted in the form of NO. The marked difference between the two tunnels in terms of the concentrations of NOx and SO2 indicates the significant emissions of such gases by the heavy-duty fleet. Pollutant concentrations were at their lowest during the night (at approximately 3:00), and peaked during the morning (at approximately 9:00). For the JQ tunnel, the mean in-tunnel concentrations were higher than those obtained outside the tunnel: 5.4 ( 2.2 times higher for CO; 5.4 ( 2.6 times higher for NOx; and 3.5 ( 1.4 times higher for the sum of all VOCs analyzed. For the MM tunnel, in-tunnel concentrations were 7.3 ( 4.6 times higher than concentrations outside the tunnel for CO, 4.4 ( 3.9 times higher for all VOCs analyzed, and 25.9 ( 21.1 times higher for NOx. The large standard deviations in the MM tunnel concentrations are related to differences in flow intensity and traffic driving patterns during the study period. 6724

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On May 6, heavy traffic congestion was observed in the MM tunnel. That was mainly due to the poor weather conditions in the MASP on that day, as well as to day-to-day variations in traffic volumes. In addition, the differences between the two tunnels in terms of the ratio of in-tunnel concentrations to outdoor (background) concentrations were much more pronounced for NOx than for other gases, a finding that is primarily attributed to the contribution made by the heavyduty diesel-powered fleet. As can be seen in Figure 2, the CO profile in the JQ tunnel (which carries almost exclusively light passenger vehicles) is related to the light traffic flow, with the exception of the morning rush-hour peak. This morning peak is due to frequent traffic congestion at this time. In both tunnels, the traffic flow velocity was extremely low during the first hours of the morning, resulting in fewer numbers of vehicles than those counted in mid-afternoon, when the velocity was higher. Midday concentrations of NOx were higher than those of CO during the same period. This is related to the fact that NOx emission is dependent on speed, but less than is that of CO, as has been stated by Keen et al. (15)

∆[P]D ) ∆[P] - ∆[CO] (1 - fD)

FIGURE 2. Workday diurnal profile of the correlation between CO and the number of vehicles in the Janio Quadros tunnel. Emission Factors for Regulated Gaseous Pollutants. Emission factors for light-duty vehicles traveling through the JQ tunnel were computed directly from the light-duty fleet measurements of CO, CO2, and NOx concentrations using the following eq (6, 7, 16):

Ep )

(

)

∆[P] ‚ w c, ∆[CO2] + ∆[CO]

(1)

where Ep is the emission factor of the pollutant (kg of pollutant emitted per kg of fuel burned), ∆[P] is the backgroundsubtracted in-tunnel pollutant concentration (µg m-3), ∆[CO2] and ∆[CO] are the background-subtracted concentrations of CO2 and CO, respectively, given in µg of carbon m-3 (i.e., when converting concentrations of CO2 and CO from mol fractions to mass units, a molecular weight of 12 g mol-1, rather than 44 g mol-1 and 28 g mol-1 for CO2 and CO, respectively, was used), and wc is the carbon weight fraction of the fuel (0.87 for diesel and 0.85 for gasohol). Organic compounds were ignored in the eq 1 denominator because their contribution to total carbon concentrations in the tunnels is negligible in comparison to those made by CO2 and CO. Emissions from heavy-duty diesel-powered vehicles traveling through the MM tunnel could not be computed directly since the traffic in that tunnel consisted of both light-duty vehicles and heavy-duty vehicles (diesel-powered busses and trucks). Therefore, it was necessary to apportion pollutant emissions in the MM tunnel into the two vehicle classes in function of fuel burned: light-duty (burning gasohol or pure ethanol) and heavy-duty (burning diesel). Previous road tunnel studies have shown that heavy-duty diesel-powered trucks and light-duty gasoline-powered vehicles emit comparable amounts of CO per unit of distance traveled (6, 7). The CO2 emissions in the MM tunnel were apportioned using traffic counts and fuel economies (of light-duty gasolinepowered vehicles and heavy-duty diesel-powered trucks) using the following equation:

∆[CO2]D ∆[CO2]

)

fDUDFDwD

,

(fDUDFDwD) + ((1 - fD) ‚UGFGwG)

(2)

where ∆[CO2]D is the component of ∆[CO2] attributable to emissions from heavy-duty diesel-powered vehicles, fD is the proportion of traffic identified as heavy-duty diesel-powered trucks, U is the fuel consumption rate, F is fuel density (740 g L-1 for gasohol and 840 g L-1 for diesel), and w is the carbon weight fraction in fuel. The subscripts D and G denote diesel and gasohol, respectively. The contributions made by other pollutants in the MM tunnel were expressed using the equation:

(

∆[P]2

∆[CO]2

)

,

(3)

where ∆[P]D is the component of ∆[P] attributable to heavyduty vehicle emissions, and ∆[CO]‚(1 - fD) is the fraction of ∆[CO] attributed to light-duty vehicle emissions. For the JQ tunnel, the light-duty vehicle pollutant emission ratio (∆[P]2/ ∆[CO]2) was measured. These fuel-based emission factors, expressed as mass emitted per unit volume of fuel burned, are representative of a typical situation with different types of vehicles and under different vehicle operating conditions (speed, mass, acceleration, engine size, etc.). Emission factors can be expressed per kilometers driven. Average fuel consumption was assumed to be 12 L per 100 km for the light-duty fleet and 47 L per 100 km for the heavyduty fleet (7). There are uncertainties associated with the fuel economy values used in apportioning the MM tunnel emissions (see eq 3) as well as with the fuel densities and carbon fractions used to calculate the emission factors (6, 7). The SO2 emission factors were not calculated due to problems that occurred in the SO2 measurements taken outside the tunnels. The mean emission factors obtained for light-duty vehicles were 14.6 ( 2.3 g km-1 for CO and 1.6 ( 0.3 g km-1 for NOx. For heavy-duty vehicles, the mean emission factors were 20.6 ( 4.7 g km-1 and 22.3 ( 9.8 g km-1 for CO and NOx, respectively. The large standard deviations for the heavyduty vehicle emission factors can be attributed to differences in the traffic patterns on May 5 and May 6 and, as previously mentioned, to the day-to-day variations in traffic volume. In the analysis of the JQ tunnel data, the highest CO emission factors were found to be correlated with traffic congestion and lower traffic flow rates. However, the highest NOx emission factors were observed between 11:00 and 13: 00, which was not found to be true for CO, indicating that NOx emission is less dependent on velocity than is that of CO. The NOx emission factors for the heavy-duty fleet were approximately 14 times higher than those calculated for the light-duty fleet. Kristensson et al. found that the contribution of the heavy-duty fleet to NOx levels is on the order of 2050% (2). The mean ratio of NOx concentrations to CO concentrations was 0.12 ( 0.03 in the JQ tunnel and 0.26 ( 0.10 in the MM tunnel, indicating that heavy-duty diesel-powered vehicles emitted approximately 54% of the total NOx. In addition, such vehicles were responsible for an estimated 25% of all SO2 emissions recorded. Table 3 shows the comparisons between emission factors obtained in the present study and those reported by the authors of other tunnel studies. The CO and NOx emission factors for the JQ and MM tunnels were much higher than those found in studies performed in other tunnels. These discrepancies can be attributed to the emission controls put on vehicles. The current emission limits for new cars in Brazil, as established by the national Programa de Controle da Poluiç aõ do Ar por Veıćulos Automotores (PROCONVE, Program for the Control of Air Pollution Emission by Motor Vehicles), are 2.0 g km-1 and 0.25 g km-1 for CO and NOx ,respectively. For diesel-powered vehicles, the limits are based on dynamometer measurements and are given in grams emitted per kilowatt-hour of engine power: 2.1 g kWh-1 and 5.0 g kWh-1 for CO and NOx, respectively (1). In addition, the motorcycle fleet in the MASP has increased considerably over the past few years, and motorcycle emission controls (which have only been in force since 2003) apply exclusively to new sales. In Brazil, there is as yet no program of emission inspection for current vehicles. The age of the fleet associated with the lack of vehicle maintenance and common alteration VOL. 40, NO. 21, 2006 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 3. Emission Factors (in g km-1) in Comparison with Other Tunnel Studiesa tunnel Washburn tunnel (Houston, TX, USA)b So¨ derleds tunnel (Stockholm, Sweden)c Tuscarora tunnel (Tuscarora, PA, U.S,)d Fort McHenry tunnel (Baltimore, MD, USA)c Janio Quadros and Maria Maluf tunnels (current study) a

vehicle type LD

CO

NOx

6.6

0.80 1.07 ( 0.03

LD HD all vehicles LD

5.27 ( 0.10 3.04 ( 0.30

8.0 ( 0.8 1.36 ( 0.03 0.24 ( 0.16

HD LD

3.75 ( 1.00 3.95 ( 0.34

12.09 ( 0.53 0.50 ( 0.06

HD LD

6.11 ( 1.75 14.6 ( 2.3

8.97 ( 0.28 1.6 ( 0.3

HD

20.6 ( 4.7

22.3 ( 9.8

LD ) light-duty fleet; HD ) heavy-duty fleet.

b

Ref 7. c Ref 2.

d

Ref

17.

of the catalysts may also be the cause of large differences on CO emission factors when compared with that obtained in other studies. The dissimilarities between our results and those of other authors might also be related to differences in the proportion of heavy-duty to light-duty vehicles and in driving patterns, as well as in the type and quality of fuel burned. In comparison with other tunnels studied, the CO

emission factors obtained for the JQ and MM tunnels are reasonably similar (with some discrepancies) to those reported for the Washburn and Fort McHenry tunnels, although the NOx-related differences are greater (7, 17). Previous studies of emission factors in Brazil were based on dynamometer tests. Since the implementation of new technology based on PROCONVE directives, there has been a significant decrease in emission factors for gasohol-powered vehicles. In addition, the mandatory addition of ethanol to gasoline in Brazil brought a reduction (of approximately 50%) in CO emissions when it was implemented (18). Emission Factors for Organic Compounds. The emission factors of individual VOCs were not calculated for light-duty or heavy-duty vehicles due to the difficulties involved in the speciation and in the differentiation between those emitted by gasohol-powered vehicles and those emitted by dieselpowered vehicles. These difficulties arose due to the small size of the VOC fraction in relation to the total pollutants observed in the MM tunnel as well as to our limited data. However, a bulk estimate of the emission factors of the VOCs analyzed in the MM tunnel was performed, taking into consideration all vehicle and engine types. The mean VOC emission factors for all vehicles using the MM tunnel are presented in Table 4. The means were calculated for samples collected during the morning period (8:00-12:00) and during the afternoon period (12:00-18:00) on May 5 and May 6. In addition, the mean emission fraction

TABLE 4. Average Emission Factors, by Day and by Period, for the Volatile Organic Compounds Analyzed in the Maria Maluf Tunnel pollutant toluene 1-butene n-pentane cyclohexanea benzene n-butane m+p-xylene n-hexane 1,2,4-trimethylbenzene formaldehyde acetaldehyde o-xylene n-heptane 1-ethyl-4-methylbenzene ethylbenzene n-octane methyl pentane aldehydes >C2 n-nonane isobutane 1,3,5-trimethylbenzene 1-pentene 3-methylhexane 1-ethyl-3-methylbenzene cumene 1-ethyl-2-methylbenzene decane n-propylbenzene methylcyclopentanea n-undecane acetone methylcyclohexanea 1-methylethylbenzene 2,3-dimethylpentane isoprene 2-butanone 1-hexene n-dodecane styrenea 2,2-dimethylbutane 2,4-dimethylpentane 2,3- dimethylhexane selected VOCs a

May 5 (mg kg-1) 8:00-12:00 486.2 598.5 246.4 210.8 277.4 321.6 168.3 158.6 184.1 265.9 255.8 172.5 174.2 196.2 72.1 113.1 95.4 143.4 76.8 51.0 87.2 89.4 75.7 171.3 413.9 51.1 50.7 154.9 115.2 31.6 70.6 96.0 123.3 30.2 5.8 19.8 28.3 10.2 16.4 17.6 5898

May 5 (mg kg-1) 12:00-18:00 822.8 1109.7 547.0 456.7 452.1 368.0 347.9 240.4 302.5 327.9 246.7 224.2 237.4 187.6 163.0 169.5 130.5 139.2 128.1 73.7 119.0 109.2 170.7 187.3 23.9 67.9 125.6 118.1 42.3 66.1 64.8 98.3 44.0 66.1 30.7 36.3 31.0 16.4 22.2 17.2 8054

Results from second method

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May 6 (mg kg-1) 8:00-12:00 3843.7 2511.2 2453.1 3062.1 2103.1 2043.4 1772.4 1751.0 1411.3 1116.1 985.3 1172.5 1151.9 755.5 918.3. 628.8 794.5 576.3 641.9 622.5 515.2 548.8 543.8. 389.2 90.2. 391.0 421.5 191.7 157.3 289.7 161.2 222.3 106.9 215.2 162.9 202.5 162.0 149.8 122.9 93.0 83.1 33 956

May 6 (mg kg-1) 12:00-18:00 752.4 595.6 567.7 455.7 551.3 455.4 393.3 371.3 436.3 380.5 361.1 328.2 254.6 190.7 184.5 189.8 188.1 168.4 132.6 115.1 213.0 106.7 124.3 95.7 44.8 94.4 82.0 46.8 36.4 63.5 87.7 70.6 23.0 55.2 40.4 72.4 45.6 41.0 20.5 26.2 28.9 26.0 8470

Period mean for the entire fleet (mg km-1) 134.5 ( 135.4 113.9 ( 82.2 87.9 ( 86.1 81.3 ( 112.7 78.3 ( 72.0 74.9 ( 70.3 62.0 ( 62.8 60.1 ( 62.7 52.5 ( 49.6 48.4 ( 35.1 45.7 ( 29.1 44.4 ( 39.8 41.1 ( 39.9 32.0 ( 23.8 31.1 ( 33.0 29.3 ( 28.1 28.7 ( 27.7 24.9 ( 21.2 22.6 ( 22.5 20.9 ( 22.6 20.8 ( 17.7 19.6 ( 19.2 19.5 ( 18.9 19.3 ( 11.5 17.9 ( 24.4 16.4 ( 16.0 14.0 ( 15.1 12.2 ( 6.0 11.2 ( 4.6 9.6 ( 10.4 9.3 ( 4.4 9.2 ( 5.3 8.3 ( 4.5 7.9 ( 7.4 7.6 ( 7.0 6.9 ( 0.5 6.8 ( 7.3 6.2 ( 5.6 5.7 ( 6.0 4.0 ( 4.6 3.7 ( 3.1 3.3 ( 2.7 1353.8 ( 1259.0

FIGURE 3. Mean contributions of the 12 most abundant VOCs emitted in the Maria Maluf tunnel in 2004. (by period) of each VOC analyzed is presented in relation to the mean CO emission factor (for the light-duty fleet). The values are presented in mass units of VOCs emitted per mass of fuel burned (mg kg-1) and in mass units of VOCs emitted per kilometer driven (mg km-1), taking into consideration the proportions of light-duty vehicles and heavy-duty vehicles traveling through the MM tunnel. The significant differences between the mean VOC values recorded on the morning of May 5, and those recorded on the morning of May 6 are attributable a considerable variation in traffic patterns, which were also responsible for the differences observed in the mean values for regulated gaseous compounds recorded on those 2 days. May 5 was considered a day with good traffic conditions, whereas record congestion occurred in the city and in the MM tunnel on May 6. Emission factors, which are strongly dependent on driving conditions such as acceleration and speed, were influenced by the wide variations in traffic congestion over the course of a given day, as well as by day-to-day variations in traffic congestion. The mean emission factor for the sum of all VOCs analyzed in the MM tunnel was approximately 1.4 ( 1.3 g km-1. Figure 3 shows the individual contributions of the twelve VOCs that, among the VOCs analyzed, were found to be the most abundant in the MM tunnel. Those twelve compounds accounted for 65.3% of the VOCs emissions recorded in the MM tunnel. Such VOC emission characteristics can reflect

the specific composition of fuel (mainly gasohol, pure ethanol, and diesel) burned in the tunnel sampled. However, significant fractions of light HCs (C2-C3), olefins and ethanol were not analyzed. Co´lon et al. (19) measured the concentrations of ethanol in the city of Saõ Paulo and found high concentrations of ethanol and methanol. Among the VOCs analyzed in the MM tunnel, alkanes, aromatic compounds, alkenes and aldehyde compounds were identified as the main classes emitted (without considering the number of species analyzed in each class). Xylene compounds, as well as toluene and benzene, made significant contributions, findings that are in agreement with those of Hsieh et al. (3) The aldehyde compounds: acetaldehyde and formaldehyde, which are important species for ozone formation, accounted for 3.4 and 3.6%, respectively, of all the VOCs emitted (by the fleet as a whole) in the MM tunnel. There is evidence that aldehyde concentrations in Brazil have decreased as reported by Grosjean et al. (for instance, in relation to 1990s for acetaldehyde and formaldehyde) (20). This decrease has occurred in parallel with technological advances in automobile manufacturing and changes in the proportion of cars in the MASP fleet that burn pure ethanol. Table 5 presents a comparison with other tunnel experiments in terms of the percentages of organic compounds most emitted in relation to the CO emission factor. With the exception of the So¨derleds tunnel in Sweden, the percentages recorded in the MM tunnel were typically higher than those recorded in other tunnels located in the United States, Taiwan, and Europe. The reasons for those differences are probably similar to those previously cited for the differences in CO and NOx values. Comparisons with studies conducted in other parts of the world are problematic due to the great number of factors that can influence the results (traffic conditions, driving patterns, vehicle maintenance, etc.) Differences related to the type of fuel used make the task of evaluating and comparing data even more complex. Analysis performed of liquid fuel sold by the leading fuel distributors in the MASP during 1999 and reported by Andrade et al. showed that gasohol contains 24.9% ethanol, 22.4% olefins, 12.2% aromatics, and 0.37% benzene (23). Annual Vehicular Emissions. The calculation of total annual vehicular emissions, spatial distribution, and temporal variations in concentrations plays a very important role in air quality models. In Figure 4 is presented an estimate of the 2004 vehicular emissions in the MASP, based on emission factors obtained from tunnel measurements. To estimate the annual vehicular emissions, various factors were taken

TABLE 5. Percentages of VOCs Emitted in Relation to CO Emission Factor: Comparisons Among Tunnel Studiesa percentage of organic pollutant emitted in relation to CO (%) pollutant CO toluene 1-butene n-pentane cyclohexane benzene n-butane m+p-xylene n-hexane 1,2,4-trimethylbenzene formaldehyde acetaldehyde o-xylene

Tuscarora tunnel (U.S.)b LD and HD

So1 derleds tunnel (Sweden)c all vehicles

Gubrist tunnel (Switzerland)d LD

Taipei tunnel (Taiwan)e all vehicles

100 and 100 0.47 and 0.37

100 1.28

100 0.49 0.04 0.10

100 0.80 0.23 0.26

0.30 and 0.23

0.33

0.35 and 0.29

0.92

0.19 0.15 0.24 0.04

0.34 0.18 0.25 0.11 0.39

0.13 and 0.72

0.25 0.06 0.37

0.11

0.22

0.13 and 0.12

JQ and MM tunnels (Brazil)f all vehicles 100 0.90 0.76 0.59 0.54 0.52 0.50 0.41 0.40 0.35 0.32 0.31 0.30

JQ ) Janio Quadros; MM ) Maria Maluf; LD ) light-duty fleet; HD ) heavy-duty fleet. b Refs 2 and 17 (data from September of 1992). c Ref 2 (data from the winter of 1998/1999). d Refs 21 and 22 (data from 2002). e Ref 5. f Current study (CO and NOx emission factors are for all vehicles using the MM tunnel). a

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FIGURE 4. Percentage contributions of CO, NOx, and HCs made by the light-duty and heavy-duty fleets in 2004: Comparison between annual vehicular emissions data provided by CETESB and data obtained in the present study. into consideration. First, we assumed that the emission factors are representative of average emissions from the MASP fleet. Second, the daily traffic flow distribution for 2004 was calculated on the basis of 252 working days at 100% of maximum flow, 50 Saturdays at 80% of maximum flow and 63 Sundays and holidays at 50% of maximum flow. Finally, we took as a premise, the estimate that light-duty vehicles travel an average of 36.7 km day-1 and that heavy-duty vehicles travel an average of 167 km day-1. These values were adapted from a technical report published by Murgel et al. (24), which was sponsored by the Instituto de Pesquisas Tecnolo´gicas (IPT, Institute for Technological Research) (25). The authors derived their data from the percentages of each vehicle type, as reported in December of 2004 by the Departamento Estadual de Traˆnsito/Processamento de Dados do Estado de Saõ Paulo (DETRAN/PRODESP, State Department of Motor Vehicle Transit/State of Saõ Paulo Data Processing Center) (14). Figure 4 shows the comparison between the data collected in the present study and those available from CETESB for 2004, which is the official inventory for the MASP. The CETESB inventory was obtained using a different methodology, based on the number of vehicles, consumption of fuel per kilometer, and the average number of kilometers per day that the vehicles travel, as well as on international emission factors adapted for the PROCONVE. The results were converted from tons of pollutants per day into kilotons of pollutants per year, and annual emissions were calculated for the MASP. The values obtained in the present study are generally higher than those presented by CETESB in terms of the emission factors, except for HC emission factors (due to the fraction measured). For CO, the annual emissions for 2004 were 4.0% higher in this study than in the CETESB data. For HCs (here the term HCs indicates all organic compounds analyzed), not including evaporative emissions, the value recorded in the present study was 25% lower than the corresponding CETESB finding, and annual vehicle emissions for NOx were found to be 96% higher than those reported by CETESB. The differences between our data and the CETESB data are mainly attributable to the alternative approach used in the calculation of the emission factors. In addition, the difference for HCs is associated with the specific fraction measured, as well as with the fact that species such as ethane, ethene, propane, propene, and ethanol not were measured. In addition, the emission factors estimated from tunnel measurements most likely do not account for cold-start emissions. 6728

9


The comparison between the light-duty and heavy-duty fleets in terms of their 2004 emissions of CO, NOx, and HCs, as well as the comparison between our data and the CETESB data, can also be seen in Figure 4. Although different methodologies were used, the estimated contributions made by all compounds were relatively similar in both data sets, although the differences among emission factors for motorcycles, taxis, and cars were not accounted for. In addition, the emission factors used to estimate of the contribution of HCs were the same for the light-duty fleet as for the heavyduty fleet. The results indicate that the diesel-powered fleet, albeit representing only 5.8% of the total fleet, makes a significant contribution to NOx emissions in the MASP. Therefore, it is recommended that efforts be made to reduce emissions from diesel-powered vehicles.

Acknowledgments This study received financial support in the form of a grant from the Fundaç aõ de Amparo a` Pesquisa do Estado de Saõ Paulo (FAPESP, Foundation for the Support of Research in the State of Saõ Paulo; grant no. 02/09060-1 to L.D.M.). We thank Helber Freitas for assisting us with the CO2 measurements, as well as Rosana Astolfo and all of the other participants for their experimental work. We are also grateful to Lilian R. F. de Carvalho and Pe´rola de Castro Vasconcellos for providing the aldehydes analysis laboratory, as well as to the Companhia de Engenharia Tra´fego (CET, Transit Engineering Agency) and the Consladel Company for providing the necessary infrastructure for the tunnel measurements. Finally, we thank Lynna J. Scranton for reviewing this paper.

Literature Cited (1) CETESB. Relato´rio Anual de Qualidade do Ar no Estado de Saõ Paulo 2004 [in portuguese]; CETESB-Companhia de Tecnologia de Saneamento Ambiental: Saõ Paulo, Brazil, 2005. (2) Kristensson, A.; Johansson, C.; Westerholm, R.; Swietlicki, E.; Gidhagen, L.; Wideqvist, U.; Vesely, V. Real-world traffic emission factors of gases and particles measured in a road tunnel in Stockholm, Sweden. Atmos. Environ. 2004, 38, 657-673. (3) Hsieh, C.; Chang, K.; Kao, Y. Estimating the ozone formation potential of volatile aromatic compounds in vehicle tunnels. Chemosphere 1999, 39, 1433-1444. (4) Hsu, Y.; Tsai, J.; Chen, H.; Lin, W. Tunnel study of on-road vehicle emissions and the photochemical potential in Taiwan. Chemosphere 2001, 42, 227-234. (5) Hwa, M.; Hsieh, C.; Wu, T.; Chang, L. W. Real-world vehicle emissions and VOCs profile in the Taipei tunnel located at Taiwan Taipei area. Atmos. Environ. 2002, 36, 1993-2002.

(6) Kirchstetter, T. W.; Harley, R. A.; Kreisberg, N. M.; Stolzenburg, M. R.; Hering, S. V. On-road measurement of fine particle and nitrogen oxide emissions from light- and heavy-duty motor vehicles. Atmos. Environ. 1999, 33, 2955-2968. (7) McGaughey, G. R.; Desai, N. R.; Allen, D. T.; Seila, R. L.; Lonneman, W. A.; Fraser, M. P.; Harley, R. A.; Pollack, A. K.; Ivy, J. M.; Price, J. H. Analysis of motor vehicle emissions in as Houston tunnel during the Texas Air Quality Study 2000. Atmos. Environ. 2004, 38, 3363-3372. (8) Pretto, A. O. Estudo do Comportamento dos gases-traç o O3, NOx, CO, SO2 e de COVs na atmosfera da cidade de Saõ Paulo [in portuguese]. Ph.D. Thesis of Institute of Nuclear Energy and ResearchsIPEN, 2005, Saõ Paulo, Brazil, http://www.ipen.br/ biblioteca/information.htm. (9) Plass-Du ¨ lmer, C.; Michl, K.; Ruf, R.; Berresheim, H. C2-C8 Hydrocarbon measurement and quality control procedures at the Global Atmosphere Watch Observatory Hohenpeissenberg. J. Chromatogr. A 2002, 953, 175-197. (10) Albuquerque, E.L. de; Andrietta, L. C. G.; Souza, K.R.P. de; Tomaz, E.; Concentration of Selected VOC in Metropolitan Region of Saõ Paulo. In Air Pollution XII; Brebbia, C. A., Ed.; WIT Press: UK, 2004; ISBN: 1-85312-722-1. (11) Montero, L.; Vasconcellos, P. C.; Souza, S. R.; Pires, M. A. F.; Sanchez-Ccoyllo, O. R.; Andrade, M. F.; Carvalho, L. R. F. Measurements of atmospheric carboxylic acids and carbonyl compounds in Saõ Paulo city, Brasil. Environ. Sci. Technol. 2001, 35, 3071-3081. (12) Souza, S. R.; Vasconcellos, P. C.; Mantovani, W.; Carvalho, L. R. F. Emissaõ por folhas de Ficus benjamina L. (Moraceae) de compostos orgaˆnicos vola´teis oxigenados. Rev. Bras. Bot. 2002, 25(4), 413-418. (13) Pisani, S. O.; Bruns, R. E.; Vasconcellos, P. C.; Carvalho, L. R. F. Artifact evidence in carbonyl compound sampling using the enclosure technique with cuvette system. J. Environ. Monitor. 2003, 5, 795-801. (14) DETRAN/PRODESP (Depto. de Ana´lises) Arquivo: Frota Circulante-2004, Saõ Paulo, 2005. [http://www.prodesp.sp.gov.br./ ]. (15) Kean, A. J.; Harley, R. A.; Kendall, G. R. Effects of vehicle speed and engine load on motor vehicle emissions. Environ. Sci. Technol. 2003, 37, 3739-3746. (16) Marr, L. C.; Kirchstetter, T. W.; Harley, R. A.; Miguel, A. H.; Hering, S. V.; Hammond, S. K. Characterization of polycyclic aromatic

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hydrocarbons in motor vehicle fuels and exhaust emissions. Environ. Sci. Technol. 1999, 33, 3091-3099. Pierson, W. R.; Gertler, A. W.; Robinson, N. F.; Sagebiel, J. C.; Zielinska, B.; Bishop, G. A.; Stedman, D. H.; Zweidinger, R. B.; Ray, W. D. Real-world automotive emissionssSummary of studies in the fort McHenry and Tuscarora Mountain tunnels. Atmos. Environ. 1996, 30, 2233-2256. Moreira, J. R.; Goldemberg, J. The alcohol program. Energy Policy 1999, 27, 229-245. Coloń, M.; Pleil, J. D.; Hartlage, T. A.; Guardani, M. L.; Martins, M. H. Survey of volatile organic compounds associated with automotive emissions in the urban airshed of Saõ Paulo, Brazil. Atmos. Environ. 2001, 35, 4017-4031. Grosjean, D.; Grosjean, E.; Moreira, L. F. R. Speciated Ambient Carbonyls in Rio de Janeiro, Brazil. Environ. Sci. Technol. 2002, 36, 1389-1395. Stemmler, K.; Bugmann, S.; Buchmann, B.; Reimann, S.; Staehelin, J. Large decrease of VOC emissions of Switzerland’s car fleet during the past decade: results from a highway tunnel study. Atmos. Environ. 2005, 39, 1009-1018. Colberg, C. A.; Tona, B.; Catone, G.; Sangiorgio, C.; Stahel, W. A.; Sturm, P.; Staehelin, J. Statistical analysis of the vehicle pollutant emissions derived from several European road tunnel studies. Atmos. Environ. 2005, 39, 2499-2511. Andrade, M. F.; Ynoue, R. Y.; Harley, R.; Miguel, A. H. Air quality model simulating photochemical formation of pollutants: the Saõ Paulo Metropolitan Area, Brazil. Int. J. Environ. Pollut. 2004, 22, 460-475. Murgel, E. M.; Szwarc, A.; Santos. M.D.S.R.; Branco, G.M.; Carvalho, H. Inventa´rio de emissaõ veicular metodologia de Ca´lculo. Congresso Brasileiro de Engenharia Sanita´ria e Ambiental. Saõ Paulo, Brazil [in portuguese]. Rev. Eng. Sanita´ria 1987, 25-14°. IPT, Avaliaç aõ Tećnico-Econoˆmica de Modelos de Implantaç aõ da Inspeç aõ Tećnica de Veıćulos. [in portuguese]; Technical report no. 45, 745; IPT: Saõ Paulo, Brazil, 2001.

Received for review December 5, 2005. Revised manuscript received April 4, 2006. Accepted August 22, 2006. ES052441U

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Emission Factors for Gas-Powered Vehicles Traveling Through Road

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