Characteristics of volatile organic compounds from motorcycle
exhaust emission during real-world driving
by
Jiun-Horng Tsai, Pei-Hsiu Huang, Hung-Lung Chiang*
*To whom correspondence should be addressed;
E-mail:[email protected]; Tel: 22079685; Fax: 886-4-22079687 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
Characteristics of volatile organic compounds from motorcycle
exhaust emission during real-world driving
Jiun-Horng Tsaia, Pei-Hsiu Huangb, Hung-Lung Chiangb
aDepartment of Environmental Engineering, Sustainable Environmental Research Center, National Cheng-Kung University, Tainan, Taiwan.
b Department of Health Risk Management, China Medical University, Taichung, Taiwan
Abstract
The number of motorcycles has increased significantly in Asia, Africa, Latin American and Europe in recent years due to their reasonable price, high mobility and low fuel consumption. However, motorcycles can emit significant amounts of air pollutants; therefore, the emission characteristics of motorcycles are an important consideration for the implementation of control measures for motorcycles in urban areas. Results of this study indicate that most volatile organic compound (VOC) emission factors were in the range of several decades mg/km during on-road driving. Toluene, isopentane, 1,2,4-trimethylbenzene, m,p-xylene, and o-xylene were the most abundant VOCs in motorcycle exhaust, with emission factors of hundreds mg/km. Motorcycle exhaust was 15.4 mg/km for 15 carbonyl species. Acetaldehyde, acetone, formaldehyde and benzaldehyde were the major carbonyl species, and their emission factors ranged from 1.4-3.5 mg/km. 1,2,4-trimethylbenzene, m,p-xylene, 1-butene, toluene, o-m,p-xylene, 1,2,3-trimethylbenzene, propene, 1,3,5-trimethylbenzene, isoprene, m-diethylbenzene, and m-ethyltoluene were the main ozone formation potential (OFP) species, and their OFP was 200 mg-O3/km or higher.
Keywords: Emission factor; real world driving mode; on-board emission measurements; carbonyls; ozone formation potential (OFP)
1. Introduction
The number of motorcycles in many developing urban areas in Asia, Latin America and Africa has grown much faster than that of four-wheel vehicles (ACEM, 2013). There are currently 350 million motorcycles in the world, and the number is expected to increase to 500 million by 2015. The sales volume 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58
of motorcycles is forecast to grow 7.2% annually to 134.5 million units in 2016 (The Freedonia Group, 2013). In Asia, especially in China, India and Indonesia, where motorcycles are an important means of transportation, the predominant models are small, inexpensive motorcycles (The Freedonia Group, 2013). In Europe, the use of motorcycles has increased significantly in Italy (Rome, Milan), France (Paris), the United Kingdom (London), and Spain (Barcelona) (Dall’Osto and Querol, 2013). In EU-27 in 2007/2008, powered two-wheelers accounted for 1.6 to 21.3% of the total passenger vehicle fleet in various European countries, with a mean of about 10% (EC, 2010). In metropolitan areas, where traffic congestion and parking difficulties influence the choice of transportation mode, motorcycles play an increasing and important role. However, motorcycles not only present traffic problems but also emit a lot of air pollutants and contribute a large fraction of air pollution in urban areas.
Motorcycles accounted for about 54% of the total vehicle population in Jakarta ten years ago (Asian Development Bank, 2002a). With an incredible annual motorcycle increase in southern Asia (e.g., Hanoi, Vietnam), motorcycles contributed to more than 50% of air pollutants (Asian Development Bank, 2002b; Tung et al., 2011). In 2011, it was reported that motorcycles contributed 94% CO, 68% NMVOC, 61% SO2 and 99% CH4 of traffic emissions in Ho Chi Minh City, Vietnam (Ho and Clappier, 2011). In Taiwan, most of the CO, HC, and NOx emissions in urban areas are from motor vehicles. However, over 90% SO2 was emitted from stationary sources such as power plants, iron and steel industries, and refinery plants, with just 7% coming from motor vehicles (TEPA, 2007). The gastrointestinal fermentation of animals, rice farming, solid waste landfill, and wastewater treatment were the major sources of methane. Therefore, the source profiles of SO2 and CH4 in Taiwan were significantly different from those in Ho Chi Minh City, Vietnam. In Taiwan, the source profiles from mobile emissions indicated that 30% of NMHC (82,000 metric tons) were emitted from motorcycles (TEPA, 2013). The same problems of motorcycle traffic and resultant pollution are plaguing many Asian cities, and these problems will undoubtedly occur in Latin America, Africa and even Europe as the use of motorcycles increases.
In Taiwan, the EPA has employed a variety of control programs such as stringent emission standards and emission fees to control stationary sources and reduce some pollutants to improve air quality. Control of mobile sources 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94
could be the next issue in improving air quality in urban areas. Some stringent emission standards associated with engine design, fuel efficiency improvement, and catalysis development have been implemented by manufacturers and government cooperation. In addition, the government has implemented measures to enhance and extend public transport infrastructures, optimize traffic management and enforcement, accelerate the adoption and deployment of improved technology, and create effective inspection and maintenance programs. Unfortunately, a large portion of air pollution is still contributed by motorcycle emissions in metropolitan areas. Real-world driving emissions data serve as a baseline for the establishment of effective control measures.
Generally dynamometer tests and real-world road traffic studies are used to measure motorcycle emissions. The dynamometer can determine the emission factors of specific engines but cannot depict a fleet of motorcycles with different cumulative mileage, ages, engine displacement, or the mixing of exhausts to reflect actual traffic conditions. In addition, dynamometer chassis testing is conducted under carefully controlled laboratory conditions. Road traffic emission data have been obtained from roadsides and road tunnels (De Vlieger, 1996; Pierson et al., 1996; Laschober et al., 2004; He et al., 2008), but it is not easy to generalize these data to other driving conditions. In addition, most real-world emission factors do not directly determine the tailpipe exhaust of motor vehicles, which could be a limitation in terms of comparison with dynamometer test results.
The selected vehicle class, engine size, city size, local road infrastructure, and driving behavior can affect the pollutant emission factors of vehicles (Chen et al., 2003; Wang et al., 2008; Kumar et al., 2011; Zamboni et al., 2011). Some studies have pointed out that currently used driving cycles and dynamometer testing are unable to accurately assess vehicle emissions because they are not representative of the exhaust emission of real-world driving conditions (Chen et al., 2003; Tsai et al., 2005; Wang et al., 2008; Tong et al., 2011; Chiang et al., 2014). Therefore, the development of an on-board motorcycle emission analysis and sampling system is important to reflect actual emissions.
This work involved the design of a sampling system to take exhaust from the tailpipe during on-road driving of motorcycles to more accurately reflect the real-world emission characteristics of motorcycles than dynamometer testing (Tsai et al., 2003) or other roadside studies such as tunnel studies (Chiang et al., 2007) or remote sensing (Kawashima et al., 2006).
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This study is focused on VOC emissions of motorcycle exhaust during real-world driving in the Taichung metropolitan area in central Taiwan. Many VOCs are regarded as hazardous air pollutants by the U.S. Environmental Protection Agency (USEPA, 2002). Their effects include atmospheric photochemical reactions that form ozone and secondary organic aerosols and reduce visibility. VOCs have been a concern due to their various acute and chronic adverse health effects such as inflammatory reactions in airways, respiratory symptoms, and reduced pulmonary function (USEPA, 1990). Many VOCs have been proved to be carcinogenic, teratogenic, and mutagenic with chronic hazards to the skin, immune system, central nervous system (brain), liver, and kidney, further raising concerns about exposure to these volatile chemicals (WHO, 2000).Some studies have suggested associations between ambient VOCs and adverse health outcomes, such as asthma (Delfino et al., 2003; Wichmannet al., 2009). Moreover, several VOCs, such as benzene, are classified as human carcinogens (Group 1) (IARC, 2014). Unfortunately, motor vehicles could be the main sources of VOCs, especially in urban areas; therefore, it is important to determine the VOC emission of motorcycle exhaust during real-world driving.
The test motorcycle was equipped with a global positioning system (GPS) and data logger to obtain speed-time data, an on-board exhaust gas analyzer to determine the concentration of regulated air pollutants, and an exhaust gas sampling system to take VOC samples during the entire test run. Three representative roads were selected to investigate the motorcycle emission characteristics between morning and evening rush hour and non-rush hour conditions for workdays and weekends.
2. Experimental
2.1 The selected area, routes and motorcycles
Taichung is the third largest city in Taiwan, with an area of about 2,214 km2 and a metropolitan population of 2.69 million in 2013. The downtown population density is more than 20,000 people/km2. In Taichung, there are more than 1.76 million motorcycles, which was about 64.6% of the total vehicles in 2013 (Ministry of Transportation and Communication, 2014) and 0.65 motorcycle per capita. The motorcycle is the most important transportation means for daily activity. In downtown Taichung, mobile sources account for approximately 32% of HCs, 89% of NOx and 98% of CO and are also important sources of air pollution in other cities of Taiwan (TEPA, 2013). 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168
Consequently, it is important to determine the exhaust pollutant emissions from mobile sources.
Test motorcycles were selected on the basis of mileage and engine type (engine volume was 125-150 cc and carburetor fuel system) for in-use motorcycles in Taiwan. Eight in-use four-stroke motorcycles were tested in this study. All of them were equipped with a two-way catalyst, ages ranged from brand new to 12 years, and their mileage ranged from 2.1 to 39.9103 Km. In this work, the motorcycles were maintained and inspected for safety and compliance with TEPA emission standards (Phase VII motorcycle emission standards for engine capacity ≤150 cc were conducted in July 1, 2007; CO: 3.5%, HC: 1600 ppm, particulate matter-opacity: 15%) was determined before testing.
Although older and high-mileage motorcycles and vehicles emit highly polluted exhaust (Lin et al., 2006), in some of the work, the results were statistically insignificant (Tsai et al., 2000; Chiang et al., 2008). However, inspection and maintenance programs are an important factor affecting motor vehicle emissions (Chang and Yeh et al., 2006; Chiang et al., 2008). In this work, the motorcycles were maintained and inspected to ensure their safety before the real-world road tests were carried out. The motorcycle mileage and age effect on exhaust emission was found to be statistically insignificant in this study. Three main routes were selected to investigate motorcycle driving cycles. Route A (Zhong-Gang road, green road) and route C (Da-Ya road, red road) are the main connections from Taichung downtown to the rural area, and route B (Wen-Xin road, blue road) is the circle connection for downtown Taichung city. Figure 1 presents the testing routes.
Motorcycle testing durations were 07:00-09:00 (rush hour in the morning, RHM), 17:00-19:00 (rush hour in the evening, RHE) and 14:00-15:00 (non-rush hour, NRH). The distances of the test routes ranged from 4.3 to 5.4 km, which closely matches the common travel distance, 4-5 km/trip, in Taiwan. The width of the motorcycle-driving lane ranges from 3.5 to 5.0 m; route A has a dedicated motorcycle lane; the other two routes (B and C) do not. Each motorcycle was run for three periods for each route during workdays and weekends. At least 18 runs (3 routes, 3 periods, and workdays and weekend) were conducted for every motorcycle in the driving cycle tests. Three motorcycles were used to conduct duplicate test runs. In total, 198 test runs (including duplicate test runs) were conducted.
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2.2 Data collection system
The test motorcycle was equipped with a GPS in a personal digital assistant (PDA), and the accepted signals were logged in the data logger system. Details are included in previous work (Chiang et al., 2014). The preliminary work assured the stability of time-speed data recording, the stability of the refitted equipment on the motorcycle, and the accuracy and precision of the motorcycle driving speed. The present study employed the approach of fixed-route vehicle chasing. There are nine parameters to present the characteristics of different routes, periods and days. The selected parameters are average speed of the entire driving cycle including the idle periods, v1 (km h-1); average acceleration of all acceleration phases, a (m s-2); average deceleration of all deceleration phases, d (m s-2); time proportion of the driving cycle, i.e., idle (pi); acceleration (pa); cruising (pc); and deceleration (pd) (%); average number of acceleration-deceleration changes within one driving period, M; and root mean square acceleration, RMS (m s-2).
2.3 Real world gas sampling system
An on-board automated instrument (HORIBA MEXA-584L) was employed to analyze the motorcycle exhaust constituents including CO, THC, NOx and CO2. A computer monitor showed the recorded real-time variation of exhaust concentration. The sampling tube of the monitor was connected directly to the tailpipe of the motorcycle. The packing of the stability system was conducted for the exhaust gas analyzer to reduce the vibration effect on the sensitivity of the analyzer on the chase motorcycle. The sampling equipment schematic diagram is shown in Figure 2.
2.4 Paraffins, olefins and aromatics analysis
Air samples for the analysis of C3-C11 hydrocarbons (the analyzed species were presented in Table 3) were collected using a vacuum box containing three-liter Tedlar bags during the entire run. Exhaust gas was taken in via a sampling pump with a controlled flow rate. A rigid air-tight chamber (SKC-Vac-U-Chamber) contained a Tedlar bag (SKC Tedlar 232 Series). Three consecutive samples were collected at each exhaust pipe at 0.1 L /min (Gilian Personal Air Sampler) for the entire cycle to yield average concentrations. After sampling, the sample bags were placed into a black container and taken to the laboratory for hydrocarbon species analysis. The 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239
sampling equipment schematic diagram was similar to previous work and is shown in Figure 2.
Paraffin, olefin and aromatic species were pre-concentrated in a purge-and-trap system (Entech 7100 instrument) and subsequently analyzed in a GC/MS (HP-6890 Gas Chromatograph and HP 5973N Mass Spectrometer). The GC was equipped with a fused silica capillary column (non-polar RTx-1, 105 m × 0.25 mm ID × 1.0 μm film thickness). Calibration standards were prepared by diluting the certified standard gas (56 Enviro-Mat Ozone Precursor, Matheson, USA) with ultra-high-purity nitrogen (99.995%) in dilution bottles. The performance of the GC/MS was evaluated with perfluorotributylamine for quality control. The relative standard deviation for all paraffins, olefins and aromatics was < 15%, the accuracy ranged from 87±7% (propane) to 104±12% (p-ethyltoluene), and the method detection limit varied from 0.02 (n-decane) to 0.14 (n-butane) ppb.
2.5 Carbonyl analysis
Aldehydes were determined by the derivation technique. A substance impregnated with 2, 4-dinitrophenyhydrazine (DNPH) was used to trap aldehydes. The trapped materials were extracted to get the derivatized compounds (the carbonyl species are shown in Table 4). High-performance liquid chromatography (HPLC) was employed to separate and measure the DNPH derivatives of aldehydes. The HPLC system was a Dionex system (Dionex TCC-100 HPLC column compartment and P680 HPLC pump) with an ultraviolet detector (Thermo Finngan UV 6000LP), a computerized pump, and an eluent delivery system. The separation column was a Supelcosil LC18 column (25 cm × 4.6 mm I.D., 5 m particles), the gradient program was conducted in this study, the eluent was 60:40 acetonitrile-water, the flow rate was 1.2 ml min-1, the injection volume was 20 l, and the detection wave length was 360 nm.
The analyzed carbonyl-dinitrophenylhydrazine (DNPH) derivatives were supplied by Supelco (TO-11 Mix, Supelco Inc., Bellefonte, PA, USA) and used to determine the aldehyde and ketone concentration, and several neat aldehydes (Sigma-Aldrich Inc., USA) were used for recovery tests. Recovery, reproducibility (in terms of coefficient of variation), and linearity (in terms of R-square of the regression line) were in the range of 82-112%, 5.6–12.4%, 0.995–0.999, respectively. 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275
After VOC sample collection of the entire run, the exhaust was immediately drawn from the Tedlar bag into the pre-coated DNPH (dinitrophenylhydrazine) cartridge (LpDNPH S10 Cartridge, Supelco Inc., Bellefonte, PA) at a sampling rate of 0.15 l min-1 for 2 min. The cartridges were then capped and stored until analysis. Specifications of this cartridge included capacity of 75 g formaldehyde, low background (< 0.35 g aldehydes), and sampling temperature in the range of 10-100oC (USEPA, 1999). Ten sets of a series of two cartridges were used to measuring the breakthrough of carbonyls; the concentration of the second cartridge was undetectable for all measured carbonyl species in the pretesting study. Therefore, one cartridge was used to measure carbonyls for one run in this study. The method detection limit varied from 0.14 (m-tolualdehyde) to 0.77 (formaldehyde) ppb. Three duplicated analyses were done for each extracted carbonyl sample from the cartridge.
2.6 Data Analysis
The emission factors of various pollutants were assessed with the exhaust concentrations, the volume of the exhaust, and the total running mileage in one test cycle. Because the actual exhaust volumes in various driving patterns were not available, the mean rotating speed of the engine, the volume of the cylinder, and the running time in that driving period were applied to derive the emission factors. The method follows that used by Tsai and coworkers (2003), and the equations are as follows:
(1)
(2) (3)
where Vm is the exhaust gas volume of a specific driving mode (m3), R is the rotating speed of the engine (rpm), t is the total time in that driving mode (minute), Ev is the volume of the engine cylinder (cc), and F is the correction factor of the engine type, which is 0.5 for a 4-stroke engine. The parameter Mi is the exhaust amount of the pollutant i (g) in a specific driving mode, Ci is the
F 10 t R V 6 v m E 3 STP i i C V 10 M /L EFi Mi 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306
concentration of the pollutant i (mg Nm-3), VSTP is the normalized value of V by temperature and pressure correction (1 atm and 0oC, Nm3), L is the running mileage during the test procedure (km), and EFi is the emission factor of that pollutant i (g km-1).
A dynamometer and instrument system was used to measure the exhaust volume of the test motorcycles, and a theoretical calculation was conducted in a different driving mode for comparison. The volume correction factor (F) of 4-stroke engines was 0.46 to 0.53 (0.49±0.05) for the eight test motorcycles, revealing a difference of 8-15% in exhaust volume between the dynamometer results and the theoretical calculation (Chiang et al., 2014). Although the theoretical calculation does not present the true exhaust volume, it can be employed to estimate motorcycle emissions.
3. Results and Discussion
3.1 Criteria pollutants and fuel consumption
For different routes, high CO2 and HC emissions were determined on the A and B routes, associated with high fuel consumption (shown as Table 1). The motorcycle lane exclusion on route A to limit the driving speed (the lowest driving speed was determined for route A) could cause high fuel consumption (shown as Table 2). High motorcycle volume loading per meter width on the route could be the reason for the high fuel consumption in route B. The lowest CO2 and HC emissions but highest CO emission were determined for route C, which could be due to the driving characteristics (such as high speed, low idle fraction, high M value [average number of acceleration-deceleration changes within a typical driving cycle]), which could reduce the engine combustion efficiency.
Based on the statistical analysis, there were insignificant differences (p>0.05) among the averages of CO, HC, NOx, CO2 and fuel consumption for workdays and weekends. Almost the same CO2 emissions were determined on workdays and weekends. However CO was 4% lower and HC was 15% higher on workdays than on weekends. On weekend mornings, low traffic volume loading could reduce motorcycle pollution emissions. Higher traffic loading was determined at the NRH on weekends than on workdays, which could affect driving patterns and increase HC emissions. This phenomenon 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340
could also reflect human activities, as people often leave home late on the weekend.
Fuel consumption was 3% higher, CO2 emission was 7% higher, CO emission was up to 13% higher and HC emission was 15% lower during the RHM than the NRH. In the RHE, fuel consumption was 2.4% lower than during the NRH. In addition, HC and NOx were more than 10% lower in the RHE than during the NRH. Low fuel consumption was determined at night and reflected low exhaust emission. NOx, CO and CO2 emission were lower in the RHE than during the RHM.
HC was 21% lower and NOx was 8% lower, but CO emission was 23% higher in the RHM than the NRH. In the evening, HC and NOx were also reduced, and CO emission increased 13% in the RHE over the NRH. A different traffic flow pattern was observed among different sampling periods; high motorcycle traffic loading reflected high pollution emission in the RHM. But low traffic loading was determined in the NRH, presenting high hydrocarbon emission. Driving characteristics such as acceleration and deceleration (high a and d values in the NRH) and low cruising period could cause incomplete fuel combustion in the engine. In addition, low NOx emission factor was determined during real-world driving compared to the ECE cycle. Generally, NOx is formed in combustion engines by a thermal process, and lower NOx emission reflects the lower combustion temperature in the same engine. Therefore, low NOx also presents poor combustion efficiency and can increase the emission of CO and HC during real-world driving.
Based on our previous study, the idle and deceleration stages have higher VOC emissions than the acceleration and cruising driving modes (Tsai et al., 2003). However, other studies have shown the deceleration stage corresponding to low emission rates (Bokare and Maurya, 2013; Zhang et al., 2013). According to the literature, more experimental data are necessary to judge the effect of acceleration/deceleration on the exhaust emission of motorcycles.
In this study, the tested motorcycles met emission standard criteria. Therefore, engine parameters such as air-fuel ratio were adjusted to the optimal condition and high fuel combustion efficiency. Because the maintenance and inspection were conducted before the real-world driving teats, the effect of air-fuel ratio on pollution emission was not addressed in this study. Based on the literature, the air-fuel ratio influences the exhaust concentration of alcohols and carbonyls in a complex way for different fuels, 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377
but the total HC increases with the air-fuel ratio for commercial fuel (Zervas et al., 2002).
3.2 VOCs emission factor
3.2.1 Paraffins, olefins, and aromatics
The paraffin, olefin and aromatic emission factors of motorcycles are shown in Table 3. Results indicated that the emission factors of toluene, isopentane, 1,2,4-trimethylbenzene, m,p-xylene, and o-xylene were abundant in motorcycle exhaust on three selected routes, and their emission factor was as high as hundreds mg/km. Most paraffin, olefin and aromatic emission factors were in the range of several decades mg/km during real-world driving. n-Undecane and n-decane were high in paraffin species, and hexene and 1-butene were dominant in olefin species. Benzene emission factors were 34 mg/km for Zhong-Gang, 59 mg/km for Wen-Xin, and 22 mg/km for Da-Ya.
Figure 3a presents the dominant paraffin, olefin and aromatic species
for different routes, days and periods. Emission factors of 52 paraffins, olefins and aromatics were 1.45±0.63 g/km for Zhong-Gang, 2.43±0.86 g/km for Wen-Xin and 1.34±0.47 g/km for Da-Ya. For 52 VOC groups, there were 37-43% paraffins, 7.5-13% olefins and 45-55% aromatics in motorcycle exhaust for the various tested routes. High VOC emission was determined in Wen-Xin with similar VOC emissions in Zhong-Gang and Da-Ya. According to the driving parameters in Table 2, the Wen-Xin routes revealed high “a” and “d” (acceleration and deceleration), which could reduce combustion efficiency and increase pollution emissions during on-road driving (Tsai et al., 2005; Tsang et al., 2009).
The chromatographic peaks of ethylene and acetylene could not be completely separated; therefore, their data is not presented in this work, which could be a limitation in the study. Based on the tunnel studies, the fraction of ethylene was about 3.5-8.9% of non-methane hydrocarbon (Sagebiel et al., 1996; Zielinska et al., 1996; Haw et al., 2002; Na et al., 2002; Rubin et al., 2006). Therefore, the uncertainty caused by ethylene and acetylene for non-methane hydrocarbon concentration was less than 10-15% in this work.
Figure 3b presents the major paraffin, olefin and aromatic emissions of
motorcycle exhaust on workdays and weekends. On workdays, the emission factors of 52 VOCs in motorcycle exhaust were as high as 1.92 g/km and as much as 1.2 times higher than on the weekend. The emission factor ratio of workdays and weekends was 1.5 for benzene, 1.6 for toluene, 1.2 for 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414
ethylbenzene and 1.0 for xylene. In addition, n-undecane, 1-hexene, dimethylbutane, isoprene, 2,4-dimethylpentane, isobutane, 2,3-dimethylpentane, methylcyclopentane, cyclopentane, 2,2-dimethylbutane, and 1-pentene were significantly higher on workdays than on weekends.
For different driving periods, the emission factors for the 52 VOCs were 1.54 g/km for RHM, 1.97 g/km for RHM, and 1.71 g/km for RHE (seen Figure 3c). High VOC emission was determined in the NRH; driving conditions—high
acceleration and deceleration values and low cruising—could reduce the
engine combustion efficiency. In addition, high motorcycle flow loading was observed in the weekend NRH, which could be another cause of emissions and reflect human activity patterns in metropolitan areas. High VOC emission, up to 2.50 g/km, was determined during RHE on workdays, which could be attributed to low visibility in the evening and reduce the driving speed. At the RHE, weekend VOC emission of weekend was reduced to 40% on workdays, which could be due to the reduced motorcycle flow rate.
3.2.2 Carbonyls
The emission factor of 15 carbonyl species from motorcycle exhaust was 15.4 mg/km. Acetaldehyde, acetone, formaldehyde and benzaldehyde were the major carbonyl species in motorcycle exhaust, with emission factors ranging from 1.4-3.5 mg/km. For different tested routes, the carbonyl emission factors were Wen-Xin (21.1±4.6 mg/km) > Zhong-Gang (13.6±4.2 mg/km) > Da-Ya (11.6±2.7 mg/km). Figure 4 shows the emission factors of analyzed carbonyl species in motorcycle exhaust for different routes, periods and days.
The average emission factor of carbonyls was 1.2 times higher on workdays than on the weekend. The ratio of workdays to weekends for acetaldehyde, formaldehyde, acetone and benzaldehyde emission factors ranged from 1.17-1.30.
For different periods, the emission factor of carbonyls was 14.0±4.4 mg/km for RHM, 12.9±2.9 mg/km for NRH and 15.9±6.1 mg/km for RHE. According to the raw data, the sequence was as follows: workday RHE (19.9 mg/km) > weekend NRH (17.7 mg/km) > workday RHM (16.1 mg/km) > workday NRH (14.0 mg/km) > weekend RHE (13.0 mg/km) > weekend RHM (11.8 mg/km) (data not shown). Differences were insignificant for different days and periods, although the ratio of high and low average concentrations was as high as 1.69. In addition, the kinematic characteristics of carbonyl concentration were also insignificant for different days and periods in this study.
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Figure 5 shows the VOC groups fraction. Paraffins ranged from 481-975
mg/km, olefins from 100-309 mg/g, aromatics from 734-1151 mg/km, and carbonyls from 12-21 mg/km for different routes. The fraction of different groups was 36-40% for paraffins, 7.4-12.6% for olefins, and 47-56% for aromatics and less than 1% for carbonyls. For the groups fraction, there were much higher variations for different routes than for different days and periods. Based on our previous work, the HC emissions were higher under real driving conditions than the ECE cycle of dynamometer testing (Chiang et al., 2014). Most motorcycles are not warmed up before use in Taiwan due to the subtropical weather. Therefore, cold-start testing was conducted for the real-world driving tests in this study. The same trends were observed for high VOC species emission during real-world driving compared with the ECE cycle testing, which was done by Yao and coworkers (Yao et al., 2013) (shown as
Table 3). For 52 VOC species, the real-world driving exhaust was 5-8 times
that of the ECE dynamometer test. High standard deviation and co-variation were determined in the VOC emission of real-world driving in this study. Many factors affect the VOC emissions in motorcycles, including maintenance and inspection, driving behavior, mileage and age of motorcycle, and environmental conditions such as ambient temperature, humidity, road slope, road surface, and traffic volume. Pentane group compounds such as isopentane, 2,2,4-trimethylpentane, and 2,3,4-trimethylpentane were 2-29 times higher than the ECE cycle on the dynamometer test. In addition, the benzene ring compounds (such as toluene, xylene, styrene, 1,2,4-trimethylbenzene etc.) were also significantly increased during real-world driving. Long-chain paraffins including decane, and n-undecane were abundant in motorcycle exhaust. High molecular weight compounds were formed in the exhaust at a rate ten times higher than in the ECE cycle, which could be due to incomplete combustion occurring during real-world driving and causing high VOC emission. High molecular weight paraffins (such as n-alkanes, iso-alkanes and cyclo-alkanes) (Botero et al., 2014) and aromatic species (such as benzene, toluene, trimethylbenzene, etc.) could be the precursor of PAHs and soot particles (Wang and Frenklach, 1997; Richter and Howard; 2000). In addition, carbonyl species emission was 10-35% higher during real-world driving than in the ECE dynamometer test (shown as Table
4). Therefore, real-world driving showed a significant increase in paraffins and
aromatics in motorcycle exhaust. Dynamometer testing could underestimate VOC emissions. 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489
3.3 Ozone formation potentials 3.3.1 Paraffins, olefins, and aromatics
Maximum incremental reactivity (Carter, 2009) and hydrocarbon emission factors of motorcycle exhaust were applied to determine the ozone formation potential. The ozone formation potentials of 52 VOCs species were 6447 mg-O3/km for Zhong-Gang, 10659 mg-mg-O3/km for Wen-Xin and 6280 mg-mg-O3/km for Da-Ya (shown as Figure 6).
1,2,4-trimethylbenzene, m,p-xylene, 1-butene, toluene, o-xylene, 1,2,3-trimethylbenzene, propene, 1,3,5-1,2,3-trimethylbenzene, isoprene, m-diethylbenzene, and m-ethyltoluene were the main ozone formation potential species, and their ozone formation potential was as high as 200 mg-O3/km for the three tested routes. For workdays, the ozone formation potential of VOCs from motorcycle exhaust was 1.19 times that on weekends, with an ozone formation potential up to 8462 mg-O3/km. For different periods, the ozone formation potential of VOCs was 6653±1105 mg/km for RHM, 9234±2958 mg/km for NRH and 7500±4778 mg/km for RHE.
3.3.2 Carbonyls
The ozone formation potentials of carbonyls were 61.5 mg-O3/km for Zhong-Gang, 95.0 mg-O3/km for Wen-Xin and 49.5 mg-O3/km for Da-Ya (shown as
Figure 7). Acetylaldehyde and formaldehyde were abundant (two species
contributed 62-69% of the ozone formation potential of 15 carbonyl species). Their ozone formation potentials were 15-32 mg-O3/km for the various routes. The ozone formation potential of carbonyl species of RHM and RHE was 1.09 and 1.22 times that of NRH, respectively. In addition, the workday OFP of carbonyls species was 1.16 times of the weekend. Figure 8 displays the OFP for different VOC groups. The ozone formation potential was 60-70% from aromatics, 17-26% from olefins, 8-12% from paraffins and less than 1% from carbonyls.
4. Conclusions
High motorcycle volume loading per meter width per hour on the route could be the reason for the high fuel consumption and hydrocarbon emission in route B. On weekend mornings, low traffic volume loading could reduce the pollution emission from motorcycle. There were no differences among the averages of CO, HC, NOx, CO2 and fuel consumption for workdays and weekends. Toluene, isopentane, 1,2,4-trimethylbenzene, m,p-xylene, and o-491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527
xylene were the most abundant VOCs in motorcycle exhaust. Most of the analyzed VOC emission factors were in the range of several decades mg/km during real-world driving. Acetaldehyde, acetone, formaldehyde and benzaldehyde were the major carbonyl species in motorcycle exhaust, and their emission factors were 1.4-3.5 mg/km. 1,2,4-trimethylbenzene, m,p-xylene, 1-butene, toluene, o-m,p-xylene, 1,2,3-trimethylbenzene, propene, 1,3,5-trimethylbenzene, isoprene, m-diethylbenzene, and m-ethyltoluene were the main ozone formation potential species. Based on the results, the dynamometer test does not seem to reflect real-world motorcycle exhaust emissions and could underestimate VOC emissions for real-world driving. Therefore, the development of an on-board exhaust analyzer and sampling system is important for the estimation of motorcycle pollution and other assessment of mobile source pollution control programs.
Acknowledgments:
The authors express their sincere thanks to the National Science Council, Taiwan and Taiwan Environmental Protection Agency (NSC-96-2221-E-039-012) for their support.
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Table and Figure captions Tables
Table 1 Motorcycle driving parameter characteristics of the various testing
routes, periods and days
Table 2 Airborne pollution emission factors of motorcycle exhaust and fuel
consumption
Table 3 Emission factors of paraffin, olefin and aromatic species from
real-world motorcycle exhaust
Table 4 Emission factor of carbonyl species from real-world motorcycle
exhaust Figures
Figure 1 Selected roads for real-world driving in downtown Taichung Figure 2 Motorcycle exhaust gas monitoring and sampling system
Figure 3 Primary VOC emission factors of motorcycle exhaust for different
routes, days and periods.
Figure 4 Carbonyl emission factors of motorcycle exhaust for different routes,
days and periods.
Figure 5 VOC group emission factors of motorcycle exhaust for different
routes, days and periods.
Figure 6 OFP of major VOCs of motorcycle exhaust for different routes, days
and periods.
Figure 7 OFP of carbonyls of motorcycle exhaust for different routes, days
and periods.
Figure 8 OFG of VOC groups of motorcycle exhaust for different routes, days
and periods. 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741
