Fine Particle Emissions from On-Road Vehicles in the Zhujiang Tunnel

May 14, 2008 - road dust churned up by cars (3, 5, 6). Health studies have demonstrated that exposure to roadway PM can increase the risk of respirato...
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Environ. Sci. Technol. 2008, 42, 4461–4466

Fine Particle Emissions from On-Road Vehicles in the Zhujiang Tunnel, China L I N G - Y A N H E , † M I N H U , * ,‡ YUAN-HANG ZHANG,‡ XIAO-FENG HUANG,† AND TING-TING YAO† Laboratory for Environmental and Urban Sciences, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China, and State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China

Received September 13, 2007. Revised manuscript received March 17, 2008. Accepted April 3, 2008.

Little is known about the characteristics of particulate matter emissions from vehicles in China, although such information is critical in source apportionment modeling, emission inventories, and health effect studies. In this paper, we report a comprehensive characterization of PM2.5 emissions in the Zhujiang Tunnel in the Pearl River Delta region of China. The chemical speciation included elemental carbon, organic carbon, inorganic ions, trace elements, and organic compounds. The emission factors of individual species and their relative distributions were obtained for a mixed fleet of heavy-duty vehicles (19.8%) and light-duty vehicles (80.2%). In addition, separate emission factors of PM2.5 mass, elemental carbon, and organic matter for heavy-duty vehicles and light-duty vehicles also were derived. As compared to the results of other tunnel studies previously conducted, we found that the abundances and distributions of the trace elements in PM2.5 emissions were more varied. In contrast, the characteristics of the trace organic compounds in the PM2.5 emissions in our study were consistent with characteristics found in other tunnel studies and dynamometer tests. Our results suggested that vehicular PM2.5 emissions of organic compounds are less influenced by the geographic area and fleet composition and thereby are more suitable for use in aerosol source apportionment modeling implemented across extensive regions.

1. Introduction Motor vehicles are a major source of the particulate matter (PM) pollution found in the atmosphere of urban areas. PM emissions from vehicles result from tailpipe exhaust (1, 2), from wear from tires and brakes (3, 4), and from resuspended road dust churned up by cars (3, 5, 6). Health studies have demonstrated that exposure to roadway PM can increase the risk of respiratory illnesses and be detrimental to human health (7–9). Numerous studies have been conducted to characterize vehicular PM emissions in the U.S. and other developed countries, with respect to emission factors, chemical composition, and size distribution. Consequently, * Corresponding author tel./fax: +86-10-62759880; e-mail: [email protected]. † Shenzhen Graduate School. ‡ College of Environmental Sciences and Engineering. 10.1021/es7022658 CCC: $40.75

Published on Web 05/14/2008

 2008 American Chemical Society

a good understanding of the nature and environmental impacts has been established in those geographic areas (e.g., refs 10–13). In comparison, little information on the status of vehicular PM emissions in China is currently available. Pollutant emissions from the huge population of vehicles in China might have an important impact on both the regional and the global climate. To our knowledge, only two peerreviewed papers have reported the direct characterization of PM emissions from vehicles in China, one concerning organic chemical composition (14) and the other concerning elemental carbon (EC) size distribution (15). Because of different fuel quality, engine conditions, and operation practices, the PM emission characteristics from vehicles in China may not be fully the same in different regions. The objectives of this paper are to report a comprehensive chemical characterization of PM2.5 emissions from vehicles in China obtained from a tunnel study and to compare our results with results reported in other tunnel studies and with results from dynamometer tests previously conducted. Roadway tunnels have been demonstrated to be a suitable environment to measure PM emissions from on-road mixed fleets (16). In comparison to driving cycle-controlled dynamometer tests, tunnel studies capture very different driving cycles and potentially offer a more realistic characterization of vehicular emissions (17). This study was carried out in a roadway tunnel located in the Pearl River Delta (PRD) region on the southeastern coast of China. The PRD region is noted for its rapid economic development and thriving export industry, which comes with the consequence of a fast deterioration of its environment (18). We report here the emission factors for PM2.5 mass, EC, organic carbon (OC), inorganic ions, and various metallic elements and organic compounds. Results from this study will provide necessary data needed on source apportionment modeling, health effects, and inventory studies in China.

2. Experimental Procedures 2.1. Tunnel Sampling. This aerosol sampling campaign was conducted in the Zhujiang Tunnel in the western urban area of Guangzhou (113.25°E, 23.13°N). The Zhujiang Tunnel, an underwater tunnel crossing the Pearl River, has a total length of 1238 m. The tunnel consists of a 721 m flat underwater section and two 517 m open slope sections outside both ends. It has two bores, each of which has three lanes with traffic in the same direction. The vehicle speed limits in the Zhujiang Tunnel are 15 to ∼50 km/h, and the most typical vehicle speed is 40 to ∼50 km/h. The sampling work took place in September 2004. Two four-channel PM2.5 samplers (Tianhong Corp.) were placed 50 m from the entrance and from the exit, respectively, inside bore 1 with a cross-sectional area of 52.8 m2 and were operated simultaneously, as shown in the Supporting Information Figure S1. The operating flow rates of the four channels were all 16.7 L min-1. Two channels were loaded with 47 mm quartz fiber filters (Whatman), and the other two channels were loaded with 47 mm Teflon filters (Pall). All quartz filters were baked at 550 °C for 5 h before sampling to eliminate organic impurities. A total of 13 sampling events were conducted in three types of periods within a week (i.e., morning, afternoon, and evening tests), and each event lasted for ∼4 to ∼6 h. Field blank samples also were collected by loading filters into the samplers but without pulling air through. All samples were stored in a refrigerator (-18 °C) before chemical analysis. The meteorological parameters at both the entrance and the exit sampling locations were synchronously recorded. A video camera was placed at the entrance to record the passing VOL. 42, NO. 12, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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vehicles during the sampling periods. The videotapes were then used to determine the vehicle counts and to classify the vehicles into two categories, namely, heavy-duty (HD) diesel vehicles (large buses and heavy-duty trucks) and light-duty (LD) vehicles (small cars, light-duty trucks, and motorcycles). The traffic densities of the 13 tests varied between 784 and 2776 per hour, and the HDV fractions varied between 18.4 and 35.1%. More details of the sampling events are summarized in Table S1 in the Supporting Information material. 2.2. Chemical Analysis. The mass concentrations were determined gravimetrically by weighting the Teflon filters before and after sampling in a temperature-controlled (21 ( 1 °C) and relative humidity-controlled (40 ( 5%) clean room. A 1.45 cm × 1 cm cut of each quartz filter was used to determine the OC and EC contents using a thermal/optical transmittance aerosol carbon analyzer (Sunset Laboratory) with the NIOSH method for diesel soot (18). The OC mass was multiplied by a factor of 1.4 to estimate the mass of organic matter (OM). One Teflon filter in each sample set was extracted using ultrapure water in an ultrasonic bath. The resulting solution was analyzed for ionic species (Cl-, NO3-, SO42-, oxalate, malonate, succinate, glutarate, and NH4+) using ion chromatography (IC) (DX500, Dionex) with the method described by Huang et al. (19). The second Teflon filter in each sample set was used for measurement of trace elements using an Agilent 7500c ICP-MS instrument. The experimental details of the ICP-MS analysis are available in the Supporting Information. The elemental concentration levels of field blank samples were undetectable or 2) associated with gasoline engine exhaust and lower values (0.3 to ∼0.9) associated with diesel exhaust (2, 17). Therefore, the low OC/EC ratios in the Zhujiang Tunnel indicated that diesel vehicles played a dominant role in the PM2.5 emissions in the fleet. Given that the HD diesel vehicles constituted as much as 20% of the fleet in the Zhujiang Tunnel, it is reasonable to obtain lower OC/EC ratios in the Zhujiang Tunnel than those (0.7 to ∼1.7) reported in the Sepulveda Tunnel (21), the Kilborn Tunnel, the Howell Tunnel (22), and the Van Nuys Tunnel (23) in the U.S. Regression analysis according to eq 2 was used to estimate the separate HDV and LDV emission factors for PM2.5 mass, EC, and OM, and the dependence of the emission factors from the HDV fraction is shown in Supporting Information Figure S2. The correlation coefficients (r2) of the linear regressions for PM2.5 mass, EC, and OM were 0.59, 0.78, and

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0.62, respectively, which were all statistically significant according to a Student’s t test with a 99% confidence interval. The good correlations indicate that the variations in the emission factors of PM2.5 mass, EC, and OM among different tests were mainly controlled by variation of the fleet composition. As a result, the derived emission factors of HD vehicles for PM2.5 mass, EC, and OM were 267 ( 56, 141 ( 21, and 76 ( 14 mg vehicle-1 km-1, respectively, and the derived emission factors of LD vehicles for PM2.5 mass, EC, and OM were 52 ( 15, 16 ( 5.4, and 19 ( 3.7 mg vehicle-1 km-1, respectively. As compared to the LDV emissions, HD vehicles had a 5.1 times larger PM2.5 mass emission factor, an 8.7 times larger EC emission factor, and a 4.0 times larger OM emission factor, indicating that HD vehicles emitted many more particulate pollutants than LD vehicles did in the Zhujiang Tunnel. The very low OC/EC ratio (0.38) of HD vehicles implies the poor combustion efficiencies of diesel engines in HD vehicles in the Zhujiang Tunnel. The OC/EC ratio of the LD vehicles was also low (0.83), indicating important contributions from diesel LD vehicles to the LDV emissions. This might be a reasonable result because it was estimated that ∼10 to ∼20% of LD vehicles in Guangzhou were powered by diesel engines (43). Table 2 compares the HDV and LDV emission factors derived in the Zhujiang Tunnel with results from other tunnel studies in the literature. The HDV emission factors in the Zhujiang Tunnel are roughly comparable to those in other tunnels, while the LDV emission factors in the Zhujiang Tunnel are usually much higher. 3.2. Emission Factors of Inorganic Ions. The sum of major inorganic ions (i.e., sulfate, nitrate, chloride, and ammonium) comprised 6.4% of the PM2.5 emissions, with the emission factors of 3.87 ( 0.61, 1.37 ( 0.59, 0.98 ( 0.16, and 0.80 ( 0.25 mg vehicle-1 km-1, respectively. As diesel exhaust usually contains more sulfate due to the higher sulfur content in diesel fuel (24), the emission levels of sulfate were much higher in the Zhujiang Tunnel than in the Sepulveda Tunnel (Table 1). The emission level of chloride was also a little higher in the Zhujiang Tunnel. The good correlation between Cl- and Na (r2 ) 0.67) indicates that the resuspension of sea salt particles deposited on the road might be a major source of both of them. However, the higher Cl-/Na mass ratio (2.7) than that typically found in seawater (1.8) suggests that Cl- also had other significant sources. In contrast, the emission levels of nitrate and ammonium were about half of those observed in the Sepulveda Tunnel, possibly because the ∼10 °C higher ambient temperature in the Zhujiang Tunnel during the sampling periods (av 31.8 °C) led to more volatilization of particfle-phase ammonium nitrate. 3.3. Emission Factors of Elements. The sum of the 19 measured trace elements contributed 2.8% to the PM2.5 emissions. Fe was the most abundant element, with an emission factor of 1.12 ( 0.09 mg vehicle-1 km-1, followed by Ca (0.64 ( 0.09 mg vehicle-1 km-1), Na (0.37 ( 0.07 mg vehicle-1 km-1), Mg (0.22 ( 0.02 mg vehicle-1 km-1), and K (0.14 ( 0.04 mg vehicle-1 km-1), which together accounted for 93% of the total mass of the 19 elements. The five elements correlated well with each other (r2 ) 0.55 to ∼0.81), suggesting a similar origin. Their poor correlations with EC (r2 < 0.1) VOL. 42, NO. 12, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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suggest that direct tailpipe emissions were not a major source. As they are major components of crustal material, a significant source could be the resuspension of road dust caused by traffic. In addition, the higher ratio of Fe/Ca (1.74) than that found in crustal material (1.38) suggests other significant sources of Fe. Particles liberated from mechanical processes, such as the wear of engines, brakes, and tires, have been found to be important sources of Fe in aerosols (4), (25). Vehicles were also implicated as an important source of Fe by a positive matrix factorization analysis of aerosol composition from data from the PRD (26). Combustion of motor oil additives is another potentially important source of Ca and Mg (25). It should be noted that these crustal elements may have much higher emission factors in PM10 than in PM2.5 because road dust mostly exists in the coarse mode. The remaining 14 measured elements contributed 0.2% in total to the PM2.5 emissions. Despite the small amounts, some of these elements, such as Cr, Ni, Cd, Cu, and Pb, are critical in the health effects related to PM, including asthma (9). Zn and Cu had the highest emission factors of 0.078 ( 0.010 and 0.034 ( 0.002 mg vehicle-1 km-1, respectively, and correlated well with each other (r2 ) 0.78). Relatively higher PM2.5 emissions of Cu and Zn also were observed in the tunnel studies in the U.S., as seen in Table 1. Cu and Zn showed little correlation with EC or with Ca (r2 < 0.4), while they showed some significant correlation with Fe (r2 ) 0.63 to ∼0.86), indicating some similar origins to Fe, such as brake wear. Potential origins of Cu and Zn also include motor oil and its additives (4, 25, 27). The low emission factor (0.014 ( 0.003 mg vehicle-1 km-1) of Pb, the traditional tracer element for emissions from leaded gasoline-powered vehicles used in receptor model studies (27, 28), indicates that nowadays vehicles in China are not a significant source of airborne Pb as a result of the phaseout of leaded gasoline across China in the late 1990s. When comparing the results obtained from the Zhujiang Tunnel with those from the Sepulveda Tunnel, the Kilborn Tunnel, and the Howell Tunnel in the U.S. (Table 1), we observed that both emission factors and relative distributions of the elements showed large variations among the different tunnel studies, frequently by more than 1 order of magnitude. Possible reasons for the large differences include different roadway conditions, vehicle conditions, fleet compositions, and fuels and motor oils. The comparison suggests the necessity of obtaining local emission source profiles and emission factors in studying the health effects of elemental species and for aerosol source apportionment modeling. 3.4. Emission Factors of Organic Compounds. The average emission factors and abbreviated names of 40 individual organic compounds identified in the Zhujiang Tunnel, including n-alkanes, PAHs, hopanes, n-alkanoic acids, and dicarboxylic acids, are listed in Supporting Information Table S3. The sum of them accounted for 2.56% of the OM emissions and 0.79% of the PM2.5 mass emissions. Despite the small mass fractions, the molecular distributions of organic compounds in aerosols are known to be source indicative (29, 30). Organic tracers have been successfully used in chemical mass balance (CMB) receptor models to conduct aerosol source apportionment in the U.S. (30–32). Below, we compare the molecular distributions of the different classes of organic compounds in the Zhujiang Tunnel with measurements from two other tunnel studies with detailed PM2.5 organic speciation (i.e., the Van Nuys Tunnel study in California (23) and the Wutong Tunnel study in Shenzhen, China (14)). Figure 1 shows bar charts comparing the organic compound compositions, expressed as the relative abundances in PM2.5 mass, in the three tunnel studies. n-Alkanes, an abundant class of compounds in gasoline, diesel fuel, and lubricating oil, were identified as a major class of particle-phase organic compounds in vehicular 4464

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FIGURE 1. Comparison of distributions of n-alkanes (a), PAHs (b), and hopanes (c) in PM2.5 emissions in the Zhujiang Tunnel, the Van Nuys Tunnel, and the Wutong Tunnel. exhaust (1, 33, 34). n-Alkanes from C16 to C32 were determined in the PM2.5 emissions in the Zhujiang Tunnel, with a total emission factor of 359 µg vehicle-1 km-1. The n-alkane homologues exhibited a smooth hump-like distribution with the highest abundance at C23, as shown in Figure 1a. Such a distribution pattern was similar to patterns observed in both the Van Nuys Tunnel and the Wutong Tunnel. The abundance level of n-alkanes in PM2.5 in the Zhujiang Tunnel was similar to that in the Van Nuys Tunnel and about half of that in the Wutong Tunnel. Two minor differences were observed in the n-alkane distributions in the Zhujiang Tunnel and Van Nuys Tunnel: (i) there were slightly more C29-C32 homologues with an odd carbon number predominance over the smooth n-alkane distribution curve in the Van Nuys Tunnel. These higher molecular weight homologues are typical components of plant wax and thus were attributed to the vegetative detritus created as tires passed over plant material on the road bed in the Van Nuys Tunnel (23). (ii) The homologue of the highest abundance was C23 in the Zhujiang Tunnel, one carbon number lower than C24 in the Van Nuys Tunnel. The n-alkane in highest abundance was found to be C20 for HD and medium-duty diesel vehicles and C25 or C26 for gasoline-powered vehicles in dynamometer tests (1, 33, 34). As the emissions collected in tunnel studies present a composite result of emissions from a mixed vehicle fleet, the higher fraction of HD vehicles in the Zhujiang Tunnel might be the cause for the shift of the n-alkane distribution toward the lower carbon number homologue as compared to that in the Van Nuys Tunnel.

The measurements of PAH distributions in vehicular exhaust reported in the literature showed wide variations. Sixteen major PAHs, with molecular weights from 178 (PHE and ANT) to 300 (COR), were identified in this study. The sum of their emission factors was 51.2 µg vehicle-1 km-1. BghiP had the highest abundance among the measured PAHs, while ANT had the lowest abundance. The relative abundances of the common PAHs in the PM2.5 mass were generally at a comparable level in the Zhujiang Tunnel, the Van Nuys Tunnel, and the Wutong Tunnel, as shown in Figure 1b. It was found that gasoline engine exhaust contains more high molecular weight PAHs, while more low molecular weight PAHs exist in diesel exhaust (35, 36). The relative abundances of BghiP and IcdP were higher in the Van Nuys Tunnel, while the relative abundances of FLU and PYR were higher in the Zhujiang Tunnel and the Wutong Tunnel, consistent with the higher fractions (ca. 20%) of HD vehicles in the fleets passing through the two tunnels in China. Hopanes are known molecular markers of aerosol emissions from fossil fuel utilization (37). Eight major hopane homologues, with carbon numbers from C27 to C34 (except C28), were identified in the Zhujiang Tunnel, and the sum of their emission factors was 74.2 µg vehicle-1 km-1. The most abundant homologue was 17(H),21(H)-hopane (HPC30), followed by HPC29. As compared to results from the Van Nuys Tunnel and the Wutong Tunnel, both the relative abundances in PM2.5 mass and the homologue distributions were very similar among the three tunnels (Figure 1c). This seems to suggest that the hopane emissions might be independent of the fleet composition. This is a reasonable result given that hopanes originate from the lubricating oil used in both gasoline-powered and diesel vehicles rather than from the fuel. Dynamometer tests also revealed a similar hopane distribution pattern in gasoline engine exhaust and diesel exhaust (1, 33, 34). Although the hopane distributions derived from various types of vehicles are very similar, they are substantially different from that associated with coal combustion (38). Our measurements indeed confirmed that hopanes can also be used as reliable tracers for particles emitted from vehicles in China in source apportionment modeling. n-Alkanoic acids from F11 to F23 also were identified, and the sum of their emission factors was 24.4 µg vehicle-1 km-1. An even-to-odd carbon number predominance was observed for the n-alkanoic acid homologues. F16 and F18 were much more abundant than others, consistent with measurements made in the Van Nuys Tunnel and the Wutong Tunnel. The origins of n-alkanoic acids may include tailpipe exhaust, tire debris, and brake debris. The prominent abundances of F16 and F18 in the homologues were in accordance with tire wear debris (3), implying that tire wear could be the dominant release pathway of n-alkanoic acids from vehicles. Low molecular weight dicarboxylic acids (C2-C4) were found to be emitted in higher amounts than other classes of organic compounds identified. The average emission factors of oxalic, malonic, and succinic acids were 142 ( 29, 134 ( 20, and 110 ( 27 µg vehicle-1 km-1, respectively. Nevertheless, vehicular emissions are not a significant source of oxalic acid in ambient aerosols because the strong in-cloud secondary formation of oxalic acid overwhelms other minor sources (39, 40). In summary, as compared to large variations in the abundances and distributions of trace elements in vehicular PM2.5 emissions in different tunnels, the characteristics of trace organic compounds were consistent in different tunnel studies and dynamometer tests. Our results suggest that vehicular PM2.5 emissions of organic compounds are less influenced by geographic area and fleet composition.

Acknowledgments This work was supported by the “863” project (2006AA06A308 and 20060106A3015) and the National Basic Research Program (2002CB211605 and 2005CB422204) from the Ministry of Science and Technology, China and the Scientific and Technical Research Foundation of Shenzhen Municipality. We thank Profs. Boguang Wang, Jianzhen Yu, and Sihua Lu and Dr. Yuanxun Zhang for their kind help with this work.

Supporting Information Available The supporting information material includes the experimental methods of the ICP-MS analysis and more detailed data of the tunnel experiments. This information is available free of charge via the Internet at http://pubs.acs.org.

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