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Comparison of fine particles emissions of light-duty gasoline vehicles from chassis dynamometer tests and on-road measurements
Atmospheric Environment 68 (2013) 82e91
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Comparison of fine particles emissions of light-duty gasoline vehicles from chassis dynamometer tests and on-road measurements Tiezhu Li*, Xudong Chen, Zhenxing Yan School of Transportation, Southeast University, P.O. Box 210096, Nanjing, China
h i g h l i g h t s < A new on-board system for measuring the instantaneous emission of fine particles was set up. < More fine particles in nucleic mode during the NEDC were emitted than those during the on-road measurements. < The number concentration of particle obeys a bimodal distribution on the urban streets. < The number concentration of particle obeys a unimodal distribution on the chassis dynamometer test. < Hard acceleration with higher speed produced more fine particles.
a r t i c l e i n f o
a b s t r a c t
Article history: Received 3 June 2012 Received in revised form 14 November 2012 Accepted 16 November 2012
Fine particles are highly related to human health, especially ultrafine particles and nanoparticles. The mass of emissions from a gasoline vehicle is relatively lower than that of a diesel vehicle, but the number of gasoline vehicles in China is so huge that the number of fine particles can’t be ignored. An on-board measurement system was established to measure the instantaneous number and mass size distributions of fine particles emitted from a light-duty gasoline vehicle under a real-world driving condition. The exhaust gas was sampled from the inside of the tailpipe. Measurements were carried out using a lightduty gasoline vehicle for goods on a chassis dynamometer and on urban streets in a downtown area of Nanjing. Size and time resolved data were obtained from an Engine Exhaust Particle Sizer (EEPS). The system was operated under the New European Driving Cycle (NEDC) and steady-state speed tests. The comparisons of size distribution and number concentration (NC) in different driving cycles in the realworld with the results from the chassis dynamometer are shown. The time proportion of operating modes in NEDC is different from that on real urban roads. The particle sizes for the NCs obey a bimodal distribution from the on-road data with mode sizes of 10.8 nm and 39.2 nm, while those from the chassis dynamometer tests obey a unimodal distribution with a mode size of 10.8 nm. The maximum NCs of particles were increased as the vehicle operating modes changed from idling, cursing to deceleration and acceleration from the on-board measurements, while compared to that from the on-board measurements, the maximum concentrations at the mode size were however in different order and the cruising mode became the second highest peak instead of the deceleration mode. The ratios of the NCs from the chassis dynamometers to that from on-road data in the speed of 15 km h1, 32 km h1, and 50 km h1 are 2.78, 2.19, and 0.48, respectively. Similarly for the mass concentration the ratios are 0.19, 0.17, and 0.009, respectively. The acceleration in the interval of 0.6e0.9 m s2 has the greatest influence on the NC in onroad measurements, while the acceleration of 0.52 m s2 has the most significant impact on the NC in the chassis dynamometer tests. The vehicle load increases the total number and mass concentration in a small range, showing no significant impact on particles size distribution especially the nanoparticles. The comparison shows that the fine particle emissions are indeed different between the NEDC and the on-road measurements in Nanjing. The differences show that the fine particles emission on the real road can’t be represented well by the results in the NEDC, and the corresponding errors should be in consideration when the vehicle emissions from the NEDC are applied. The study makes us clear that the fine particles emission characteristics of the light-duty vehicle on the urban roads are really different with that in the NEDC. Ó 2012 Elsevier Ltd. All rights reserved.
Keywords: Fine particle emission Size distribution On-road measurement Chassis dynamometer test Light-duty gasoline vehicle
* Corresponding author. Tel.: þ86 13813850110. E-mail address: [email protected] (T. Li). 1352-2310/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.atmosenv.2012.11.031
T. Li et al. / Atmospheric Environment 68 (2013) 82e91
1. Introduction The particulate matter (PM) with aerodynamic diameters lower than 2.5 mm (PM2.5) is added to the latest revised ambient air quality standards (GB 3095-2012, China). PM in the atmosphere is usually distinguished in three different classes: the ultrafine particles (UFPs) (Dp < 0.1 mm), the fine particles (Dp < 2.5 mm), and the coarse particles (2.5 mm < Dp < 10 mm) (Kittelson, 1998). Two somewhat different sizes are more relevant to vehicle exhaust aerosols: the nuclei size range (Dp < 0.05 mm), consisting mainly of volatile particles, and the accumulation range (0.05 mm < Dp < 1.0 mm), consisting mainly of agglomerated soot particles with adsorbed volatile material (Vouitsis et al., 2003). Current particulate emission standards are mass-based and ineffective for controlling ultrafine particles. Mass tends to be conserved during the dilution and sampling process. But the particle number is not conserved and may be changed significantly by homogeneous nuclei and coagulation. The particle emissions in a gasoline vehicle are low, but the number of the gasoline vehicles has already reached up to around 55 million in China (NBSC, 2011). Thus, the emission emitted from light-duty gasoline vehicles must be considered. According to the particle size distribution spectrum for the number concentration (NC) of motor vehicle emissions, the vast majority of exhaust PM is in the PM2.5 range, more precisely, in the PM0.1 range (Morawska et al., 1998). In cities, a major fraction of UFPs is related to road traffic in terms of cars, buses, and trucks. Epidemiological and toxicological studies have shown that the elemental compositions of fine particles pose a harmful threat to human health, and UFP causes adverse health effects in sensitive human beings more than larger particles due to their increased lung deposition efficiency (Wilson and Suh, 1997). Even under a low mass concentration, ultrafine particles with high NC still would elicit more serious inflammatory reaction in the lungs of animals compared to larger-sized particles (Oberdörster et al., 1994). The environmental monitoring results in Shanghai show that the fine particles (FPs) in the traffic environment were influenced by the regional weather and road vehicle emissions (Shen et al., 2011). Curbside measurements showed that besides soot mode particles in the range of 30e200 nm, nuclei mode particles were also produced by traffic (Wehner et al., 2009). Atmospheric UFP needs to be controlled for several reasons: (1) the toxic nature of fresh emissions, (2) the ability of ultrafine fraction particles to penetrate the epithelial cells and accumulate in lymph nodes, (3) the possible association with pediatric asthma and the potential for oxidative damage to DNA (Sioutas et al., 2005). In general, there are two common methods used to measure the particle emissions of individual vehicles. They are the chassis dynamometer tests (CDTs) and the on-road measurements (ORMs). The advantage of CDT is that a vehicle can be studied without any influence from other vehicles. The whole test conditions can be controlled, especially the vehicle operating modes. The PM is
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emitted mainly by diesel vehicles, and the implementation of diesel particulate filters is effective in reducing the emissions. But for the light-duty gasoline vehicles, the study on fine particle emissions is limited. Some studies have found that the measurement of PM size distributions is sensitive to the sampling conditions applied in the CDTs (Bergmann et al., 2009). Basically, this method is suitable for measuring the emitted particles directly. The second method used to measure the particle emission under real-world condition is the chasing experiments (Kittelson et al., 2006). During the chasing experiments, a mobile laboratory equipped with measurement instruments follows the vehicle to be surveyed and measures the particle emissions (Giechaskiel et al., 2005). Morawska et al. (2007) used a plume capture trailer to collect a sample of the naturally diluted air within 1e3 m behind the tailpipe with the biggest disadvantage of distorting the flow field of test vehicle. Wehner et al. (2009) presented an on-board method to study the exhaust emissions with the time resolution of the instrument 90 s, which is not suitable for measuring the instantaneous fine particles emission. In this study, an on-board system of exhaust particle measurement is developed to measure the instantaneous fine particle emissions on the urban roads. A database of vehicle operating modes and particle emissions in urban streets of Nanjing was built. The time alignment of different instruments is discussed. And the results of data from the CDTs and the ORMs are compared. The particle size distributions in different operating modes in the CDTs and the ORMs are discussed. Finally, the impacts of vehicle speed and acceleration on the particle size and NC distributions are analyzed. The following abbreviations are listed here. Ultrafine particlesUFPs; fine particles-FPs; number concentration-NC; mass concentration-MC; on-road measurements-ORMs; chassis dynamometer tests-CDTs; Engine Exhaust Particle Sizer SpectrometerEEPS; On-Board Diagnostic System Ⅱ-OBDⅡ; New European Driving Cycle-NEDC; extra-urban driving cycle-EUDC; Diameter of Particle-Dp.
2. Measurements 2.1. Instruments The measurement equipment (Table 1) was installed in a lightduty vehicle (Wuling 6376A3, a gasoline multi-point EFI; engine displacement 1.149L; VKT 49866KM; emission standard EU-Ⅲ; weight 1030 kg; Manual Transmission 5). The sampling tube was connected to the interior side of the tailpipe. Instruments of EEPS, the air compressor and the converter for the power supply were placed inside the car. The electrical power was provided by a gasoline generator (6.5 kw). The car OBDⅡ was used to monitor the car speed, the engine speed and the air mass flow.
Table 1 Instruments used in the test. Instruments
Range
Resolution
Measurement parameter/symbol
Weight
Engine Exhaust Particle Sizer Spectrometer (EEPS) The Dekati Diluter DI-1000
5.6e560 nm
0.1 s
Particle number size distribution
32 kg
Continuous working 1 C
For diluting aerosol and gaseous samples from the tailpipe
2.8 kg
Dekati DH-1723 Pressurised air heater and DR-1823 Temperature controller PUMA 1525 Air compressor Joytom GPSMap 60csx HWADANGE7500 gasoline generator
The dilution ratio 1:8 0e500 C
To eliminate the unwanted condensation and nuclei
1.5 kg
1.12 kw, 4.6 CFM Dependent on the SD card 0e6.5 kw
To supply compressed air To record the speed and the travel distance of the vehicle The electrical supplier for the instruments
30 kg 0.2 kg 60 w 65 kg
Automotive Diagnostic Software ScanMaster
0e200 km h1
1450 RPM 1s 8.2/3600 (kw rpm1) 1s
To record the engine speed and vehicle speed
0.06 kg
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Firstly, the gasoline power generator was set at the right door of the vehicle to prevent CO from the generator, and a mini tailpipe was connected to the generator. During the ORM, the right door of the test vehicle was open to obtain more fresh air and CO dissipation. Secondly, the air compressor was set at the rear of the car, connected to the pressure gauge by a rubber tube. The other end of the pressure gauge was connected to the Dekati DH-1723 Pressurised air heater, while the air heater was linked to the Dekati Diluter DI-1000 using a pitot tube that resists high temperature. The outlet of the diluter was connected to the EEPS using a rubber hose with an inside diameter of 8 mm. The diluter was fixed to the handle of the air compressor, and the package of the air heater was put beside the left door of the vehicle and fixed to the floor. The EEPS was placed on the left rear of the vehicle tied up to an elastic steel plate. The special sampling head was inserted into the tailpipe, while it was connected to the diluter using a pitot tube about 4 m long. The outside part of the sampling tube was stacked on the car body. A chair was put beside the left door to place the portable computer connected to the EEPS using RS232 converter. The vehicle OBDⅡ was connected to the portable computer to record the engine speed and vehicle speed. The setup of the measurement platform is shown in Fig.1.
ranges from 10 km h1 to 80 km h1 at intervals of 10 km h1, enduring 5 min for each one. Almost all of the instruments were put outside the test vehicle resulting to that the carrying weight in the CDTs is about 265 kg lower than that in the ORMs. 2.3. On-road measurements The aims of the measurements are to obtain the instantaneous particle emission data on Nanjing urban roads and to study the particle size distributions in the real-world urban driving cycle. Measurements were performed on different classes of urban streets located in downtown in Nanjing city from March 12 to 20, 2012. The routes include 7 major arterials, 7 minor arterials, 2 branches, and 1 freeway, with a total distance of 31.2 km. The maximum speed during the measurements is 60 km h1, and the measured average speed is around 23 km h1. The vehicle speed is recorded second by second by the ELM327 and the GPS. The tests were carried out at 11:00e15:00, with ambient temperature about 10 C. The mean wind speed ranges between 3.4 m s1 and 7.9 m s1 with southeast wind, and the relative humidity is 49%. The measurement system for the ORMs is shown in Fig. 2. 3. Results and discussions
2.2. Chassis dynamometer tests 3.1. The data validation and time alignment The CDTs were carried out on a 48 00 single roll chassis dynamometer with a full flow constant volume exhaust tunnel. The sampling tube was plugged into the tailpipe with an insulation head, and the exhaust was diluted at a fixed dilution ratio about 1:8. Primary dilution was performed immediately in the tailpipe at the tip of the sampling tube, and then diluted by dry and clean compressed air. Nuclei particles occur in tailpipe measurements. It has been reported that their formation is highly dependent on the dilution process (Abdul-Khalek et al., 1999). The heater temperature was set at 180 C. The sample was then carried to the real time particle size spectrometer (EEPS3090, TSI Inc.) for the determination of particle number and size distribution. The EEPS was operated at a 10 L min1 sample air and a 40 L min1 sheath air yielded a size range between 5.6 and 560 nm. The method recommended by limits and measurement methods for emissions from light-duty vehicles (Ⅲ, Ⅳ) (GB 18352.3-2005, China) is used for the certification of light-duty vehicles based on the NEDC. The cycle consists of four repeated ECE-15 driving cycles and a EUDC. What is more, a steady-state speed test was carried out and repeated 4 times. The speed
The vehicle speed was recorded by the OBDⅡ system, with the speed from the dynamometer operation system during the CDTs. The ELM327 was connected to OBDⅡ system for measuring the engine speed and vehicle speed, used to diagnose the operation of the vehicle. The comparison of the OBDⅡ vehicle speed to the speed from the operation system is shown in Fig. 3. The speed from the OBDⅡ system is 7% higher than the dynamometer speed. The statistical results show that the difference of the population means is significantly different from the test difference (0) for the raw speed and the standard speed (a, b) at the 0.05 level; while the difference of the population means is not significantly different with the test difference (0) between the modified speed and the standard speed (c, d). During the ORMs, the data of the vehicle speed comes from both the OBDⅡ and the GPS. Some signals may be lost and some abnormal speeds may appear in the GPS during the measurements. To obtain a more precise description of speed and acceleration distribution, and a more accurate relationship between the speed, acceleration and the fine/ultrafine particle emissions, the speed
Fig. 1. Schematic of on-board measurement system, (1) dilutor package, (2) air compressor, (3) EEPS, (4) computer connected to the EEPS and the OBDⅡ.
T. Li et al. / Atmospheric Environment 68 (2013) 82e91
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Fig. 2. Layout of sampling system for the ORM.
validation is necessary. Just ahead of the comparison of the two different speeds, some lost speeds or abnormal speeds need to be corrected. The distribution of speeds is shown in Fig. 4. According to the t-test, the difference is not significant. The two speeds show good correlation.
3.2. Fine particle size distribution under different driving cycles Prior to the ORMs, the fine particle emission characteristics of the test vehicle are evaluated during the NEDC. The data obtained from the CDTs are used to validate and be compared the results from the on-road measurements. Fig. 5a shows the speed distribution and the total NC in the CDTs. Fig. 5b shows the results of the
ORMs. During the ORMs, some concentration data are lost, noted by the two circles. To obtain a specific description of vehicle operating modes on urban streets of Nanjing, the parameters of the ORMs and the CDTs are listed in Table 2. The average speed on real world urban roads is lower than the average speed of 19 km h1 in ECE-15, much lower than that in the EUDC with the average speed of 62.6 km h1. The time proportion of acceleration and deceleration in the urban streets has reached up to 24.3% and 25.2%. Apparently, the total proportion of acceleration and deceleration in ORMs is 1.4 times more than that in the ECE-15 and the EUDC. Meanwhile, the time proportions of cruising in ECE-15 and EUDC are 29.2% and 52.3%, which are higher than those in the two ORM routes. The stop and start is more frequent during the ORMs. The driving cycle is more
Fig. 3. (a) Raw OBDⅡ speed and the standard (STD) speed from the dynamometer operation system in ECE, (b) raw OBDⅡ speed and the standard in EUDC, (c) the modified OBDⅡ speed and the standard speed in ECE, (d) the modified OBDⅡ speed and the standard speed in EUDC.
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Fig. 4. Distributions of the vehicle speed from OBDⅡ(star) and the speed from GPS.
complex in the ORMs, which can’t be represented well by that in the CDTs. The particle size distributions for the NC as a function of driving mode in both the ORMs and the CDTs are shown in Fig.6. Fig. 6a shows that the distributions were in general unimodal and mode sizes were at around 40 nm except the idle condition where a clear bimodal distribution pattern could be seen with mode sizes of w11 nm and 40 nm respectively. The maximum NCs of particles were increased as the vehicle operating modes changed from idling, cursing (21.3 km h1) to deceleration and acceleration. In the Fig.6b, the particles showed unimodal distributions for all the operating conditions with a mode size of w11 nm. The maximum concentrations at the mode size were however in different order with Fig. 6a. The cruising (34 km h1) mode became the second highest peak instead of the deceleration mode, compared to Fig. 6a. The maximum NC in acceleration in the ORMs is 3.65E6 # cm3 with the particle size of 39.2 nm, which is 0.33 times the maximum of 1.11E7 # cm3 with a particle size of 10.8 nm in the CDT. Under the idling condition, the NC in the ORM is 7.85E5 # cm3, just 0.10 times that in the CDT about 7.61E6 # cm3, where the particle size
is 10.8 nm. For the particles (Dp < 25 nm), the NC takes a proportion of 28.7% in the whole measurement range in the ORM, while for the UFP, which is 96.5%. As a comparison, the proportion of particles (Dp < 25 nm) is 92.2%, while for the UFP, the proportion is 99.9% in the CDT. Apparently, the NC is in the vicinity of zero with the particle size larger than 100 nm in the CDTs, where more particles with higher diameter exist in the ORMs. The driving cycles are more complex in the ORMs and the frequent stop and start makes the engine load change all the time. Compared to the situations in the CDTs, the mixture fuel is burned completely and less soot particles are emitted. Similarly, the NC during acceleration is at the maximum for both the CDTs and the ORMs. The acceleration increases the throttle opening, making the cylinder temperature rise, resulting to smaller airefuel ratio. And the mixture will be richer, which constitutes a strong condition of a high-temperature hypoxia fuel pyrolysis dehydrogenation, generating more soot core. A large number of particles are formed from the core undergoing the process of surface growth and condensation. The NC of UFP really takes up the major proportion of particles in the measurement range. Some agreement can be found in the size distribution
Fig. 5. (a) Time resolved total particle number and speed observed during the NEDC, (b) The NC with corresponding speed from the ORM.
T. Li et al. / Atmospheric Environment 68 (2013) 82e91 Table 2 The proportions of vehicle operating modes. Modes
ORM
ECE
EUDC
Acceleration Deceleration Idling Cruising Average speed Max. speed
649 s 24.3% 671 s 25.2% 771 s 28.9% 576 s 21.6% 17 km h1 62 km h1
160 s 20.5% 116 s 14.9% 276 s 35.4% 228 s 29.2% 19 km h1 50 km h1
106 s 26.5% 35 s 8.8% 50 s 12.5% 209 s 52.3% 62.6 km h1 120 km h1
for the total NC in the operating modes in Tianjian discussed by Du et al. (2002). Also, the maximum NC of size distribution happens when the particle medians are 10.8 nm and 39.2 nm, which is a little different from that discussed by Kittelson et al. (2006) and Bukowiecki et al. (2002). 3.3. Influences of vehicle speed on fine particles emissions To study the influence of speed on particle size distribution, the data from the steady-state speed of the CDTs were analyzed. The results are shown in Fig. 7. The same speeds are chosen from the ORMs and the CDTs, and then the size distributions for the NCs and MCs are discussed as follows. In Fig. 7a, the size distributions for particle NC at different speeds showed basically a unimodal distribution with a mode size of 10.8 nm (Dp ¼ 10.8 nm). The maximum NC for each speed is reduced as the speed increased from the speed of 10 km h1 to 80 km h1 (the highest is 9.47E6 # cm3 at speed 10 km h1; the lowest is 8.11E5 # cm3 at a speed of 80 km h1). This is a little different from that obtained by Li, (2007) with the maximum at the highest speed 70 km h1. The mass size distributions in Fig. 7b showed multimodal patterns for all speed conditions with three mode sizes at w20 nm, 80 nm and 200e300 nm. The two circles show that the concentration at the particle median size in the range of 107.5 nme191.1 nm and 294.3 nme560 nm are close to zero. In order to make sure that this phenomenon is not caused by the background particles, some tests are carried out on the same dynamometer using the vehicle (SEAT Ibiza Mk4 (6J)) meeting the EU-V emission standard. The results shown in Fig. 8 show that the particles (Dp > 294.3 nm) are also very close to zero. Although the sampling vehicle meets a stricter emission standard, the size distributions for NCs towards larger particle sizes are similar to those for the test vehicle. The size distributions for NC at speeds of 60 km h1 and 70 km h1 obey bimodal distributions with the particle medians of 10.8 nm and 52.3 nm,
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with the maxima NCs of 7.3E5 # cm3 and 7.1E5 # cm3, respectively. At the other speeds, the NCs are so lower that the size distributions are not significantly, with the maximum NC of 1.37E5 # cm3. At higher speeds, the engine load increases. The combustible gas mixture within the engine is richer, and the mixture in combustion chamber is uneven. The poor combustion condition leads to the rise of certain volatile organic and smoke particle emissions. Fig. 8a shows that the NCs are very close to zero with the particle medians in the range of 124.1 nme165.5 nm and 339.8 nme523.3 nm. And Fig.8b shows that all the MCs at these speeds obey a unimodal distribution, with particles median of 93.1 nm. The MCs at the speeds of 60 km h1 and 70 km h1 are much higher than those at other speeds, with maxima 162.6 mg m3 and 148.1 mg m3, respectively. Just as discussed about the NCs in Fig. 8a, the corresponding MCs are very close to zero. During the two steady-state speed tests, the size distributions for NCs with Dp larger than 124.1 nm are very close to zero. The comparison shows that this phenomenon does exist in the CDTs. One thing is certain that the particles in nuclei mode with a median of 10.8 nm take a major proportion of the NCs. At the speeds of 10 km h1, 20 km h1, 30 km h1, the proportions of nuclei mode particles to the corresponding size range are 91.3%, 92.5%, 88.6% in the sampling test, while in the target tests, the proportions are 97.5%, 97.2%, 97.8%. That means the particles of nuclei mode indeed takes up the majority, in agreement with that from Wehner et al. (2009). It can also be seen from that more nuclei mode particles are produced in the low speed and low load of a gasoline vehicle (Li, 2007; Graskow et al., 1998). The comparison data are chosen from the ECE-15 tests and the ORMs under cruising condition, 15 km h1, 32 km h1, and 50 km h1. The size distributions for NCs and MCs are shown in Fig.9. Apparently, for all the speeds in the CDTs, the size distributions for NCs obey a unimodal distribution with a particle median of 10.8 nm. And Fig.9a shows that the NCs with a Dp larger than 339.8 nm are very close to zero. At the three speeds in the ORMs, the maximum NCs are concentrated in the range of 56.23 nme 64.94 nm. The average NCs at the three speeds (15, 32, and 50 km h1) in the CDTs are 2.78, 2.19, and 0.48 times higher than those in the ORMs, respectively. While, the MCs in the CDTs are separately 0.19, 0.17, 0.009 times higher than those in the ORMs. The reason is probably that the vehicle operated more smoothly in the CDTs than that in the ORMs without hard acceleration and deceleration. The mixture was burned completely resulting to less particles with larger sizes. The total
Fig. 6. (a) Particle number distribution in different driving cycles from ORM and (b) that from CDT. NC is the concentration of the number of particles in # cm3 (presented in dN/ dlogDp).
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Fig. 7. (a) Size distributions for NC, and MC (b) size distributions for in different speeds from the CDT. MC is the mass of particles measured in mg cm3 (presented dM/dlogDp).
Fig. 8. (a) Size distribution for NCs, and (b) size distribution for MCs from the sampling tests.
carrying weight of the vehicle in the ORMs was about 265 kg, higher than that in the CDTs which was not carrying the instruments and operators. To obtain the same speed in the CDTs and the ORMs more power from the vehicle was needed. More mixture was burned, and then more soot was formed in the condition of hypoxia (Wang et al., 2009). In addition, the dilution air in the ORMs was from the surrounding real-world, while the CDTs were carried out in the relatively closed room. The mixture in the engine cylinder was composed of gasoline fuel and the air from the environment. The background particles maybe have some impacts on the size distributions, which can’t be treated separately.
3.4. Influences of vehicle acceleration on fine particles The accelerations described at Fig.10a are mostly distributed uniformly between 1.5 m s2 and 1.5 m s2, and the other accelerations are scattered above 1.5 m s2 and below 1.5 m s2. The accelerationespeed profile in the CDTs is shown in Fig.10b, with some fixed accelerations. The driving conditions are complex and frequent accelerations and decelerations happen in real-world traffic. The accelerationespeed profile in the ECE-15 can’t be treated as a good representation of the real-world driving cycle. Just as discussed above, the acceleration does have the biggest influence on the particle emissions.
Fig. 9. (a) Size distribution for the NC and (b) the average MC at different speeds from the CDT and the ORM.
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Fig. 10. (a) Acceleration levels as a function of speed in the ORM and (b) in the NEDC.
Fig. 11. (a) The particle NC distribution in the ORM, (b) and the particle NC distribution in the CDT.
A typical result of a representative ORMs is chosen to show the particle size distributions shown in Fig.11a, while Fig.11b shows the particle size distributions for the NC in the CDTs. The accelerations and decelerations are divided into eight bins according to the frequency of accelerations, shown in Table 3. Fig. 11a shows that the NCs in all the acceleration bins reach up to the maxima where the median of particle size is 39.2 nm, with a maximum NC of 4.90E6 # cm3 in the bin [0.6 m s2, 0.9 m s2) and a minimum NC of 2.54E6 # cm3 in the bin (0.6 m s2, 0.3 m s2]. The NCs for other bins are very close to each other. Fig.11b shows that the NCs in all the acceleration bins obey a unimodal distribution, with a particle median of 10.8 nm. The maximum concentration of 1.09E7 # cm3 happens in the interval of [0.3 m s2, 0.6 m s2), with the acceleration of 0.52 m s2. However, the NCs are very close in these intervals [0.6 m s2, 0.9 m s2), (>0.9 m s2], and (<0.9 m s2]. The on-road data in Fig. 12a shows a shift of 93.1e107.5 nm in the maxima of the size distributions toward larger particle sizes in accordance with the acceleration bins [0.6, 0.9), (>0.9], [0.3, 0.6), (<0.9), [0.3, 0.3), [0.9, 0.6), and [0.6, 0.3). The ratios of Table 3 The definition of operating modes. Acceleration
Cruising
0.9 m s2 [0.6,0.9） m s [0.3,0.6) m s [0.1,0.3) m s (0.1,0.1) m s
Deceleration
Idling
0.9 m s2 (0.9,0.6] m s (0.6,0.3] m s (0.3,0.1] m s Speed <0.5 km h1
average MC in the above acceleration bins in the ORMs to those in the CDTs are 59.0, 20.9, 31.1, 48.6, 34.5, 44.2, and 35.5, respectively. The maximum of the MC in the CDT is 19.7 mg m3 (Fig. 12b), and that in the ORMs is 650.3 mg m3 (Fig. 12a). Just as discussed above, the maximum MC happened in the interval of [0.6 m s2, 0.9 m s2). The average speeds corresponding to the acceleration bins are shown in Table 4. The biggest average speed is 28.0 km h1, just corresponding to the acceleration interval [0.6 m s2, 0.9 m s2). The NC distributions in different acceleration bins basically correspond to the average speed, which can be treated as a reason that at higher average speeds, the NC is higher. Indeed, more particles are emitted under the condition of hard acceleration at higher speeds. 3.5. Influences of vehicle load on number and mass concentration The vehicle load during the ORMs is 265 kg heavier than that in the CDTs, which needed to be discussed. Some studies were carried out to study the impact of weight on the emission (Zhai et al., 2006). Frey et al. (2007) found that modal diesel fuel consumption rates were found to increase by 33% on average when the number of on-board passengers increased from less than 20 to more than 40. To make a more precise description of impact of vehicle load on fine particles emission, an extra test was added under the NEDC. The same instruments were used with basically the same ambient temperature and humidity. It shows an identical number concentration distribution, which comes to the maximum at the particle size of w10.8 nm. But the total number concentration
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Fig. 12. (a) The particle MC distribution in the ORM, (b) the particle MC distribution in the CDT.
Table 4 Average speed in acceleration bins from the ORM and the CDT. Bins(m s2)
[0.3 w 0.6)
[0.6 w 0.9)
(>0.9]
[0.6 w 0.3)
[0.9 w 0.6)
(<0.9)
[0.3 w 0.3)
Avg. ORM (km h1) Avg. CDT (km h1)
24.5 23.6
28.0 26.8
25.3 13.6
23.3 24.9
21.0 21.1
21.7 10.9
22.9 26.7
with the higher load is about 23% higher than that without extra load. The two concentrations show a unimodal lognormal distribution with the particle size of 254 nm. But the total mass concentration with higher load is 12% greater than that under the condition of normal load. The extra test tells that the vehicle load has a certain impact especially on the total number and mass concentration but no significant impact on the size distribution, especially the nanoparticles emission. All in all, the results are still acceptable. From this, the difference between the number and mass concentration from the ORMs and CDTs are mainly caused by the different speedeacceleration profile. However, the impact of load on particle emission is just studied from the weight of the instruments and stuff member in the tests. More systematical tests are needed to examine thoroughly the vehicle load impact on emission characteristics. 3.6. Influences of environmental temperature and relative humidity In general, both temperature and relative humidity play a role in UFs number concentration (Jamriska et al., 2008). Basically, the FP emission is different in winter and summer which has proved by many researches (Rönkkö et al., 2006). Casati et al. (2007) reported that when the temperature ranged from 9 to 25 Cand relative humidity was between 55% and 69%, there was no significant of the number concentration distribution. But, in winter, the number of small particles (Dp < 15 nm) is increased. When the study was carried out, and the temperature under the condition of real-world and chassis dynamometer test were so close that it can’t be the main impact factor. Morawska et al. (2008) showed that nucleation mode particles were largely influenced by relative humidity with high concentrations during high humidity periods. Charron and Harrison (2003) proved that the lack of a dependence on the relative humidity during the daytime was considered indicative that the nucleation was not a major factor in particle production. The weather was fine when the tests were carried out, and the relative humidity was just about 49%, which was identical with that in CDTs. Thus, it is not possible for the relative humidity to cause the difference. The FPs emission is influenced by many factors, making it not easy to be included all impacts from the outside environment. Thus, the result of the study is limited in a certain condition. In further
research, some factors such as the dilution air temperature and background particles concentration will be discussed in detail. 4. Summary and conclusions The sizes distributions for the NC in the CDTs are different from that in the ORMs with different driving cycle. The size distributions for the NC obey a unimodal distribution with the median of particle 10.8 nm in CDTs, where the maxima of the NC increased when the engine load increased from idling, deceleration and cruising to acceleration. In ORM, the size distributions obey a bimodal distribution with two modal sizes of 10.8 nm and 39.2 nm. More particles in nuclei mode were produced in the CDTs with the maximum 1.1E7 # cm3, and the ratio of the NC to that in the ORMs is 3.0, but the MC in the CDTs was just 0.13 times the MC in the ORMs. In the CDTs, more particles in nuclei mode were produced at the lower speeds. At the speeds of 10 km h1e80 km h1, the size distributions for the NC show a unimodal distribution with a particles median of 10.8 nm, while the size distributions at the speeds in the ORMs shift in the particles median of 39.2 nm. The average NCs at the three speeds of 15 km h1, 32 km h1, and 50 km h1 in the CDTs are 2.78, 2.19, and 0.48 times those in the ORMs, respectively. Meanwhile, the MCs in the CDTs are 0.19, 0.17, and 0.009 times those in the ORMs, respectively. Frequent hard acceleration has an adverse effect on the gasoline fine particles emission. The size distributions for the NC came up to the maxima in the acceleration interval of [0.6 m s2, 0.9 m s2) during the ORMs; while in the CDTs, the acceleration is 0.52 m s2. The maximum ratio of the MC in the ORMs to that in the CDTs are 50. The dilution ratio was fixed at 1:8, and the compressed air in dilution came from the surrounding. The background NC of fine particles can’t be excluded in the study. The measurements were just carried out on a gasoline vehicle. More types of gasoline vehicles are needed for the future studies. Acknowledgements The authors would like to thank all the colleagues involved in the measurements. This work is supported partially by the National Natural Science Foundation of China (No. 50778041, 51008155,
T. Li et al. / Atmospheric Environment 68 (2013) 82e91
51178111, 50910105065) and the 2011 Jiangsu research and innovation projects for college graduates (CXLX_0138). References Abdul-Khalek, I., Kittelson, D., Brear, F., 1999. The Influence of Dilution Conditions on Diesel Exhaust Particle Size Distribution Measurements. SAE Paper 01-1142. Bergmann, M., Kirchner, U., Vogt, R., Benter, T., 2009. On-road and laboratory investigation of low-level PM emissions of a modern diesel particulate filter equipped diesel passenger car. Atmospheric Environment 43, 1908e1916. Bukowiecki, N., Dommen, J., Prevot, A.S.H., Richter, R., Weingartner, E., Baltensperger, U., 2002. A mobile pollutant measurement laboratorydmeasuring gas phase and aerosol ambient concentrations with high spatial and temporal resolution. Atmospheric Environment 36, 5569e5579. Casati, R., Scheer, V., Vogt, R., Benter, T., 2007. Measurement of nuclei and soot mode particle emission from a diesel passenger car in real world and laboratory in situ dilution. Atmospheric Environment 41, 2125e2135. Charron, A., Harrison, M., 2003. Primary particle formation from vehicle emission during exhaust dilution in the roadside atmosphere. Atmospheric Environment 37, 4109e4119. Du, Q., Yang, Y.X., Zhu, D., Cai, X.L., 2002. Investigation of automobile driving pattern on real-road condition in Tianjin. Transactions of Tianjin University (English Edition) 8 (4), 1e5. Frey, H.C., Rouphail, N.M., Zhai, H.B., Farias, T.L., Goncalves, G.A., 2007. Comparing real-world fuel consumption for diesel- and hydrogen-fueled transit buses and implication for emissions. Transportation Research Part D 12, 281e291. Giechaskiel, B., Ntziachristos, L., Samaras, Z., Scheer, V., Casati, R., Vogt, R., 2005. Formation potential of vehicle exhaust nuclei mode particles on-road and in the laboratory. Atmospheric Environment 39 (18), 3191e3198. Graskow, B.R., Kittelson, D.B., Ahmadi, M.R., Morris, J., 1998. Exhaust Particulate Emissions from a Direct Injection Spark Ignition Engine. SAE Paper 01-1145. Jamriska, M., Morawska, L., Mengersen, K., 2008. The effect of temperature and relative humidity on size generated traffic exhaust particle emissions. Atmospheric Environment 42 (10), 2369e2382. Kittelson, D.B., 1998. Engines and nanoparticles, a review. Journal of Aerosol Science 29, 575e588. Kittelson, D.B., Watts, W.F., Johnson, J.P., 2006. On-road and laboratory evaluation of combustion aerosols e part 1: summary of diesel engine results. Journal of Aerosol Science 37, 913e930. Li, X.L., 2007. Study of Emission Characteristics of Ultrafine Particles Emitted from Engines and Variation of Ultrafine Particles During Exhaust Dilution. Shanghai Jiaotong University, Shanghai, pp. 57e78, (in Chinese).
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Morawska, L., Bofinger, N.D., Kocis, L., Nwankwoala, A., 1998. Submicrometer and supermicrometer particles from diesel vehicle emissions. Environmental Science & Technology 14, 2033e2042. Morawska, L., Ristovski, Z.D., Johnson, G.R., 2007. Novel method for on-road emission factor measurements using a plume capture trailer. Environmental Science & Technology 41, 574e579. Morawska, L., Ristovski, Z., Jayaratne, E.R., Keogh, D.U., Ling, X., 2008. Ambient nano and ultrafine particles from motor vehicle emissions: characteristics, ambient processing and implications. Atmospheric Environment 42, 8113e 8138. National Bureau of Statistics of China, 2011. http://www.stats.gov.cn/tjsj/ndsj/2011/ indexch.htm. Oberdörster, G., Ferin, J., Lehnert, B.E., 1994. Correlation between particle size, in vivo particle persistence, and lung injury. Environmental Health Perspectives 102 (5), 173e179. Rönkkö, T., Virtanen, A., Vaaraslahti, K., Keskinen, J., Pirjola, L., Lappi, M., 2006. Effect of dilution conditions and driving parameters on nucleation mode particles in diesel exhaust: laboratory and on-road study. Atmospheric Environment 40, 2893e2901. Shen, J.X., Xiao, S., Yu, Q., Ma, W.C., Chen, L.M., 2011. PM1, PM2.5 and PM10 pollution levels in Shanghai road environment. Environmental Chemistry 30 (6), 1e2 (in Chinese). Sioutas, C., Delfino, R.J., Singh, M., 2005. Exposure assessment for atmospheric ultrafine particles (UFPs) and implications in epidemiologic research. Environmental Health Perspectives 113 (8), 947e955. Vouitsis, E., Ntziachristos, L., Samaras, Z., 2003. Particulate matter mass measurements for low emitting diesel powered vehicles: what’s next? Progress in Energy and Combustion Science 29 (6), 635e672. Wang, F.B., Bao, J.J., Qiao, W.G., Gao, J.H., 2009. An experiment study on the particulate emission from gasoline vehicles under cycle test conditions. Automotive Engineering 31 (8), 737e740 (in Chinese). Wilson, W.E., Suh, H.H., 1997. Fine particles and coarse particles: concentration relationships relevant to epidemiologic studies. Journal of the Air & Waste Management Association 47 (1), 37e48. Wehner, B., Uhrner, U., Von Löwis, S., Zallinger, M., Wiedensohler, A., 2009. Aerosol number size distributions within the exhaust plume of a diesel and a gasoline passenger car under on-road conditions and determination of emission factors. Atmospheric Environment 43, 1235e1245. Zhai, H.B., Frey, H.C., Rouphail, N.M., 2006. Speed and facility-specific emissions estimates for transit buses based on measured speed profiles. In: Proceedings of the Annual Meeting of the Air & Waste Management Association, New Orleans, Paper No. 195.
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Atmospheric Environment journal homepage: www.elsevier.com/locate/atmosenv
Comparison of fine particles emissions of light-duty gasoline vehicles from chassis dynamometer tests and on-road measurements Tiezhu Li*, Xudong Chen, Zhenxing Yan School of Transportation, Southeast University, P.O. Box 210096, Nanjing, China
h i g h l i g h t s < A new on-board system for measuring the instantaneous emission of fine particles was set up. < More fine particles in nucleic mode during the NEDC were emitted than those during the on-road measurements. < The number concentration of particle obeys a bimodal distribution on the urban streets. < The number concentration of particle obeys a unimodal distribution on the chassis dynamometer test. < Hard acceleration with higher speed produced more fine particles.
a r t i c l e i n f o
a b s t r a c t
Article history: Received 3 June 2012 Received in revised form 14 November 2012 Accepted 16 November 2012
Fine particles are highly related to human health, especially ultrafine particles and nanoparticles. The mass of emissions from a gasoline vehicle is relatively lower than that of a diesel vehicle, but the number of gasoline vehicles in China is so huge that the number of fine particles can’t be ignored. An on-board measurement system was established to measure the instantaneous number and mass size distributions of fine particles emitted from a light-duty gasoline vehicle under a real-world driving condition. The exhaust gas was sampled from the inside of the tailpipe. Measurements were carried out using a lightduty gasoline vehicle for goods on a chassis dynamometer and on urban streets in a downtown area of Nanjing. Size and time resolved data were obtained from an Engine Exhaust Particle Sizer (EEPS). The system was operated under the New European Driving Cycle (NEDC) and steady-state speed tests. The comparisons of size distribution and number concentration (NC) in different driving cycles in the realworld with the results from the chassis dynamometer are shown. The time proportion of operating modes in NEDC is different from that on real urban roads. The particle sizes for the NCs obey a bimodal distribution from the on-road data with mode sizes of 10.8 nm and 39.2 nm, while those from the chassis dynamometer tests obey a unimodal distribution with a mode size of 10.8 nm. The maximum NCs of particles were increased as the vehicle operating modes changed from idling, cursing to deceleration and acceleration from the on-board measurements, while compared to that from the on-board measurements, the maximum concentrations at the mode size were however in different order and the cruising mode became the second highest peak instead of the deceleration mode. The ratios of the NCs from the chassis dynamometers to that from on-road data in the speed of 15 km h1, 32 km h1, and 50 km h1 are 2.78, 2.19, and 0.48, respectively. Similarly for the mass concentration the ratios are 0.19, 0.17, and 0.009, respectively. The acceleration in the interval of 0.6e0.9 m s2 has the greatest influence on the NC in onroad measurements, while the acceleration of 0.52 m s2 has the most significant impact on the NC in the chassis dynamometer tests. The vehicle load increases the total number and mass concentration in a small range, showing no significant impact on particles size distribution especially the nanoparticles. The comparison shows that the fine particle emissions are indeed different between the NEDC and the on-road measurements in Nanjing. The differences show that the fine particles emission on the real road can’t be represented well by the results in the NEDC, and the corresponding errors should be in consideration when the vehicle emissions from the NEDC are applied. The study makes us clear that the fine particles emission characteristics of the light-duty vehicle on the urban roads are really different with that in the NEDC. Ó 2012 Elsevier Ltd. All rights reserved.
Keywords: Fine particle emission Size distribution On-road measurement Chassis dynamometer test Light-duty gasoline vehicle
* Corresponding author. Tel.: þ86 13813850110. E-mail address: [email protected] (T. Li). 1352-2310/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.atmosenv.2012.11.031
T. Li et al. / Atmospheric Environment 68 (2013) 82e91
1. Introduction The particulate matter (PM) with aerodynamic diameters lower than 2.5 mm (PM2.5) is added to the latest revised ambient air quality standards (GB 3095-2012, China). PM in the atmosphere is usually distinguished in three different classes: the ultrafine particles (UFPs) (Dp < 0.1 mm), the fine particles (Dp < 2.5 mm), and the coarse particles (2.5 mm < Dp < 10 mm) (Kittelson, 1998). Two somewhat different sizes are more relevant to vehicle exhaust aerosols: the nuclei size range (Dp < 0.05 mm), consisting mainly of volatile particles, and the accumulation range (0.05 mm < Dp < 1.0 mm), consisting mainly of agglomerated soot particles with adsorbed volatile material (Vouitsis et al., 2003). Current particulate emission standards are mass-based and ineffective for controlling ultrafine particles. Mass tends to be conserved during the dilution and sampling process. But the particle number is not conserved and may be changed significantly by homogeneous nuclei and coagulation. The particle emissions in a gasoline vehicle are low, but the number of the gasoline vehicles has already reached up to around 55 million in China (NBSC, 2011). Thus, the emission emitted from light-duty gasoline vehicles must be considered. According to the particle size distribution spectrum for the number concentration (NC) of motor vehicle emissions, the vast majority of exhaust PM is in the PM2.5 range, more precisely, in the PM0.1 range (Morawska et al., 1998). In cities, a major fraction of UFPs is related to road traffic in terms of cars, buses, and trucks. Epidemiological and toxicological studies have shown that the elemental compositions of fine particles pose a harmful threat to human health, and UFP causes adverse health effects in sensitive human beings more than larger particles due to their increased lung deposition efficiency (Wilson and Suh, 1997). Even under a low mass concentration, ultrafine particles with high NC still would elicit more serious inflammatory reaction in the lungs of animals compared to larger-sized particles (Oberdörster et al., 1994). The environmental monitoring results in Shanghai show that the fine particles (FPs) in the traffic environment were influenced by the regional weather and road vehicle emissions (Shen et al., 2011). Curbside measurements showed that besides soot mode particles in the range of 30e200 nm, nuclei mode particles were also produced by traffic (Wehner et al., 2009). Atmospheric UFP needs to be controlled for several reasons: (1) the toxic nature of fresh emissions, (2) the ability of ultrafine fraction particles to penetrate the epithelial cells and accumulate in lymph nodes, (3) the possible association with pediatric asthma and the potential for oxidative damage to DNA (Sioutas et al., 2005). In general, there are two common methods used to measure the particle emissions of individual vehicles. They are the chassis dynamometer tests (CDTs) and the on-road measurements (ORMs). The advantage of CDT is that a vehicle can be studied without any influence from other vehicles. The whole test conditions can be controlled, especially the vehicle operating modes. The PM is
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emitted mainly by diesel vehicles, and the implementation of diesel particulate filters is effective in reducing the emissions. But for the light-duty gasoline vehicles, the study on fine particle emissions is limited. Some studies have found that the measurement of PM size distributions is sensitive to the sampling conditions applied in the CDTs (Bergmann et al., 2009). Basically, this method is suitable for measuring the emitted particles directly. The second method used to measure the particle emission under real-world condition is the chasing experiments (Kittelson et al., 2006). During the chasing experiments, a mobile laboratory equipped with measurement instruments follows the vehicle to be surveyed and measures the particle emissions (Giechaskiel et al., 2005). Morawska et al. (2007) used a plume capture trailer to collect a sample of the naturally diluted air within 1e3 m behind the tailpipe with the biggest disadvantage of distorting the flow field of test vehicle. Wehner et al. (2009) presented an on-board method to study the exhaust emissions with the time resolution of the instrument 90 s, which is not suitable for measuring the instantaneous fine particles emission. In this study, an on-board system of exhaust particle measurement is developed to measure the instantaneous fine particle emissions on the urban roads. A database of vehicle operating modes and particle emissions in urban streets of Nanjing was built. The time alignment of different instruments is discussed. And the results of data from the CDTs and the ORMs are compared. The particle size distributions in different operating modes in the CDTs and the ORMs are discussed. Finally, the impacts of vehicle speed and acceleration on the particle size and NC distributions are analyzed. The following abbreviations are listed here. Ultrafine particlesUFPs; fine particles-FPs; number concentration-NC; mass concentration-MC; on-road measurements-ORMs; chassis dynamometer tests-CDTs; Engine Exhaust Particle Sizer SpectrometerEEPS; On-Board Diagnostic System Ⅱ-OBDⅡ; New European Driving Cycle-NEDC; extra-urban driving cycle-EUDC; Diameter of Particle-Dp.
2. Measurements 2.1. Instruments The measurement equipment (Table 1) was installed in a lightduty vehicle (Wuling 6376A3, a gasoline multi-point EFI; engine displacement 1.149L; VKT 49866KM; emission standard EU-Ⅲ; weight 1030 kg; Manual Transmission 5). The sampling tube was connected to the interior side of the tailpipe. Instruments of EEPS, the air compressor and the converter for the power supply were placed inside the car. The electrical power was provided by a gasoline generator (6.5 kw). The car OBDⅡ was used to monitor the car speed, the engine speed and the air mass flow.
Table 1 Instruments used in the test. Instruments
Range
Resolution
Measurement parameter/symbol
Weight
Engine Exhaust Particle Sizer Spectrometer (EEPS) The Dekati Diluter DI-1000
5.6e560 nm
0.1 s
Particle number size distribution
32 kg
Continuous working 1 C
For diluting aerosol and gaseous samples from the tailpipe
2.8 kg
Dekati DH-1723 Pressurised air heater and DR-1823 Temperature controller PUMA 1525 Air compressor Joytom GPSMap 60csx HWADANGE7500 gasoline generator
The dilution ratio 1:8 0e500 C
To eliminate the unwanted condensation and nuclei
1.5 kg
1.12 kw, 4.6 CFM Dependent on the SD card 0e6.5 kw
To supply compressed air To record the speed and the travel distance of the vehicle The electrical supplier for the instruments
30 kg 0.2 kg 60 w 65 kg
Automotive Diagnostic Software ScanMaster
0e200 km h1
1450 RPM 1s 8.2/3600 (kw rpm1) 1s
To record the engine speed and vehicle speed
0.06 kg
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Firstly, the gasoline power generator was set at the right door of the vehicle to prevent CO from the generator, and a mini tailpipe was connected to the generator. During the ORM, the right door of the test vehicle was open to obtain more fresh air and CO dissipation. Secondly, the air compressor was set at the rear of the car, connected to the pressure gauge by a rubber tube. The other end of the pressure gauge was connected to the Dekati DH-1723 Pressurised air heater, while the air heater was linked to the Dekati Diluter DI-1000 using a pitot tube that resists high temperature. The outlet of the diluter was connected to the EEPS using a rubber hose with an inside diameter of 8 mm. The diluter was fixed to the handle of the air compressor, and the package of the air heater was put beside the left door of the vehicle and fixed to the floor. The EEPS was placed on the left rear of the vehicle tied up to an elastic steel plate. The special sampling head was inserted into the tailpipe, while it was connected to the diluter using a pitot tube about 4 m long. The outside part of the sampling tube was stacked on the car body. A chair was put beside the left door to place the portable computer connected to the EEPS using RS232 converter. The vehicle OBDⅡ was connected to the portable computer to record the engine speed and vehicle speed. The setup of the measurement platform is shown in Fig.1.
ranges from 10 km h1 to 80 km h1 at intervals of 10 km h1, enduring 5 min for each one. Almost all of the instruments were put outside the test vehicle resulting to that the carrying weight in the CDTs is about 265 kg lower than that in the ORMs. 2.3. On-road measurements The aims of the measurements are to obtain the instantaneous particle emission data on Nanjing urban roads and to study the particle size distributions in the real-world urban driving cycle. Measurements were performed on different classes of urban streets located in downtown in Nanjing city from March 12 to 20, 2012. The routes include 7 major arterials, 7 minor arterials, 2 branches, and 1 freeway, with a total distance of 31.2 km. The maximum speed during the measurements is 60 km h1, and the measured average speed is around 23 km h1. The vehicle speed is recorded second by second by the ELM327 and the GPS. The tests were carried out at 11:00e15:00, with ambient temperature about 10 C. The mean wind speed ranges between 3.4 m s1 and 7.9 m s1 with southeast wind, and the relative humidity is 49%. The measurement system for the ORMs is shown in Fig. 2. 3. Results and discussions
2.2. Chassis dynamometer tests 3.1. The data validation and time alignment The CDTs were carried out on a 48 00 single roll chassis dynamometer with a full flow constant volume exhaust tunnel. The sampling tube was plugged into the tailpipe with an insulation head, and the exhaust was diluted at a fixed dilution ratio about 1:8. Primary dilution was performed immediately in the tailpipe at the tip of the sampling tube, and then diluted by dry and clean compressed air. Nuclei particles occur in tailpipe measurements. It has been reported that their formation is highly dependent on the dilution process (Abdul-Khalek et al., 1999). The heater temperature was set at 180 C. The sample was then carried to the real time particle size spectrometer (EEPS3090, TSI Inc.) for the determination of particle number and size distribution. The EEPS was operated at a 10 L min1 sample air and a 40 L min1 sheath air yielded a size range between 5.6 and 560 nm. The method recommended by limits and measurement methods for emissions from light-duty vehicles (Ⅲ, Ⅳ) (GB 18352.3-2005, China) is used for the certification of light-duty vehicles based on the NEDC. The cycle consists of four repeated ECE-15 driving cycles and a EUDC. What is more, a steady-state speed test was carried out and repeated 4 times. The speed
The vehicle speed was recorded by the OBDⅡ system, with the speed from the dynamometer operation system during the CDTs. The ELM327 was connected to OBDⅡ system for measuring the engine speed and vehicle speed, used to diagnose the operation of the vehicle. The comparison of the OBDⅡ vehicle speed to the speed from the operation system is shown in Fig. 3. The speed from the OBDⅡ system is 7% higher than the dynamometer speed. The statistical results show that the difference of the population means is significantly different from the test difference (0) for the raw speed and the standard speed (a, b) at the 0.05 level; while the difference of the population means is not significantly different with the test difference (0) between the modified speed and the standard speed (c, d). During the ORMs, the data of the vehicle speed comes from both the OBDⅡ and the GPS. Some signals may be lost and some abnormal speeds may appear in the GPS during the measurements. To obtain a more precise description of speed and acceleration distribution, and a more accurate relationship between the speed, acceleration and the fine/ultrafine particle emissions, the speed
Fig. 1. Schematic of on-board measurement system, (1) dilutor package, (2) air compressor, (3) EEPS, (4) computer connected to the EEPS and the OBDⅡ.
T. Li et al. / Atmospheric Environment 68 (2013) 82e91
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Fig. 2. Layout of sampling system for the ORM.
validation is necessary. Just ahead of the comparison of the two different speeds, some lost speeds or abnormal speeds need to be corrected. The distribution of speeds is shown in Fig. 4. According to the t-test, the difference is not significant. The two speeds show good correlation.
3.2. Fine particle size distribution under different driving cycles Prior to the ORMs, the fine particle emission characteristics of the test vehicle are evaluated during the NEDC. The data obtained from the CDTs are used to validate and be compared the results from the on-road measurements. Fig. 5a shows the speed distribution and the total NC in the CDTs. Fig. 5b shows the results of the
ORMs. During the ORMs, some concentration data are lost, noted by the two circles. To obtain a specific description of vehicle operating modes on urban streets of Nanjing, the parameters of the ORMs and the CDTs are listed in Table 2. The average speed on real world urban roads is lower than the average speed of 19 km h1 in ECE-15, much lower than that in the EUDC with the average speed of 62.6 km h1. The time proportion of acceleration and deceleration in the urban streets has reached up to 24.3% and 25.2%. Apparently, the total proportion of acceleration and deceleration in ORMs is 1.4 times more than that in the ECE-15 and the EUDC. Meanwhile, the time proportions of cruising in ECE-15 and EUDC are 29.2% and 52.3%, which are higher than those in the two ORM routes. The stop and start is more frequent during the ORMs. The driving cycle is more
Fig. 3. (a) Raw OBDⅡ speed and the standard (STD) speed from the dynamometer operation system in ECE, (b) raw OBDⅡ speed and the standard in EUDC, (c) the modified OBDⅡ speed and the standard speed in ECE, (d) the modified OBDⅡ speed and the standard speed in EUDC.
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T. Li et al. / Atmospheric Environment 68 (2013) 82e91
Fig. 4. Distributions of the vehicle speed from OBDⅡ(star) and the speed from GPS.
complex in the ORMs, which can’t be represented well by that in the CDTs. The particle size distributions for the NC as a function of driving mode in both the ORMs and the CDTs are shown in Fig.6. Fig. 6a shows that the distributions were in general unimodal and mode sizes were at around 40 nm except the idle condition where a clear bimodal distribution pattern could be seen with mode sizes of w11 nm and 40 nm respectively. The maximum NCs of particles were increased as the vehicle operating modes changed from idling, cursing (21.3 km h1) to deceleration and acceleration. In the Fig.6b, the particles showed unimodal distributions for all the operating conditions with a mode size of w11 nm. The maximum concentrations at the mode size were however in different order with Fig. 6a. The cruising (34 km h1) mode became the second highest peak instead of the deceleration mode, compared to Fig. 6a. The maximum NC in acceleration in the ORMs is 3.65E6 # cm3 with the particle size of 39.2 nm, which is 0.33 times the maximum of 1.11E7 # cm3 with a particle size of 10.8 nm in the CDT. Under the idling condition, the NC in the ORM is 7.85E5 # cm3, just 0.10 times that in the CDT about 7.61E6 # cm3, where the particle size
is 10.8 nm. For the particles (Dp < 25 nm), the NC takes a proportion of 28.7% in the whole measurement range in the ORM, while for the UFP, which is 96.5%. As a comparison, the proportion of particles (Dp < 25 nm) is 92.2%, while for the UFP, the proportion is 99.9% in the CDT. Apparently, the NC is in the vicinity of zero with the particle size larger than 100 nm in the CDTs, where more particles with higher diameter exist in the ORMs. The driving cycles are more complex in the ORMs and the frequent stop and start makes the engine load change all the time. Compared to the situations in the CDTs, the mixture fuel is burned completely and less soot particles are emitted. Similarly, the NC during acceleration is at the maximum for both the CDTs and the ORMs. The acceleration increases the throttle opening, making the cylinder temperature rise, resulting to smaller airefuel ratio. And the mixture will be richer, which constitutes a strong condition of a high-temperature hypoxia fuel pyrolysis dehydrogenation, generating more soot core. A large number of particles are formed from the core undergoing the process of surface growth and condensation. The NC of UFP really takes up the major proportion of particles in the measurement range. Some agreement can be found in the size distribution
Fig. 5. (a) Time resolved total particle number and speed observed during the NEDC, (b) The NC with corresponding speed from the ORM.
T. Li et al. / Atmospheric Environment 68 (2013) 82e91 Table 2 The proportions of vehicle operating modes. Modes
ORM
ECE
EUDC
Acceleration Deceleration Idling Cruising Average speed Max. speed
649 s 24.3% 671 s 25.2% 771 s 28.9% 576 s 21.6% 17 km h1 62 km h1
160 s 20.5% 116 s 14.9% 276 s 35.4% 228 s 29.2% 19 km h1 50 km h1
106 s 26.5% 35 s 8.8% 50 s 12.5% 209 s 52.3% 62.6 km h1 120 km h1
for the total NC in the operating modes in Tianjian discussed by Du et al. (2002). Also, the maximum NC of size distribution happens when the particle medians are 10.8 nm and 39.2 nm, which is a little different from that discussed by Kittelson et al. (2006) and Bukowiecki et al. (2002). 3.3. Influences of vehicle speed on fine particles emissions To study the influence of speed on particle size distribution, the data from the steady-state speed of the CDTs were analyzed. The results are shown in Fig. 7. The same speeds are chosen from the ORMs and the CDTs, and then the size distributions for the NCs and MCs are discussed as follows. In Fig. 7a, the size distributions for particle NC at different speeds showed basically a unimodal distribution with a mode size of 10.8 nm (Dp ¼ 10.8 nm). The maximum NC for each speed is reduced as the speed increased from the speed of 10 km h1 to 80 km h1 (the highest is 9.47E6 # cm3 at speed 10 km h1; the lowest is 8.11E5 # cm3 at a speed of 80 km h1). This is a little different from that obtained by Li, (2007) with the maximum at the highest speed 70 km h1. The mass size distributions in Fig. 7b showed multimodal patterns for all speed conditions with three mode sizes at w20 nm, 80 nm and 200e300 nm. The two circles show that the concentration at the particle median size in the range of 107.5 nme191.1 nm and 294.3 nme560 nm are close to zero. In order to make sure that this phenomenon is not caused by the background particles, some tests are carried out on the same dynamometer using the vehicle (SEAT Ibiza Mk4 (6J)) meeting the EU-V emission standard. The results shown in Fig. 8 show that the particles (Dp > 294.3 nm) are also very close to zero. Although the sampling vehicle meets a stricter emission standard, the size distributions for NCs towards larger particle sizes are similar to those for the test vehicle. The size distributions for NC at speeds of 60 km h1 and 70 km h1 obey bimodal distributions with the particle medians of 10.8 nm and 52.3 nm,
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with the maxima NCs of 7.3E5 # cm3 and 7.1E5 # cm3, respectively. At the other speeds, the NCs are so lower that the size distributions are not significantly, with the maximum NC of 1.37E5 # cm3. At higher speeds, the engine load increases. The combustible gas mixture within the engine is richer, and the mixture in combustion chamber is uneven. The poor combustion condition leads to the rise of certain volatile organic and smoke particle emissions. Fig. 8a shows that the NCs are very close to zero with the particle medians in the range of 124.1 nme165.5 nm and 339.8 nme523.3 nm. And Fig.8b shows that all the MCs at these speeds obey a unimodal distribution, with particles median of 93.1 nm. The MCs at the speeds of 60 km h1 and 70 km h1 are much higher than those at other speeds, with maxima 162.6 mg m3 and 148.1 mg m3, respectively. Just as discussed about the NCs in Fig. 8a, the corresponding MCs are very close to zero. During the two steady-state speed tests, the size distributions for NCs with Dp larger than 124.1 nm are very close to zero. The comparison shows that this phenomenon does exist in the CDTs. One thing is certain that the particles in nuclei mode with a median of 10.8 nm take a major proportion of the NCs. At the speeds of 10 km h1, 20 km h1, 30 km h1, the proportions of nuclei mode particles to the corresponding size range are 91.3%, 92.5%, 88.6% in the sampling test, while in the target tests, the proportions are 97.5%, 97.2%, 97.8%. That means the particles of nuclei mode indeed takes up the majority, in agreement with that from Wehner et al. (2009). It can also be seen from that more nuclei mode particles are produced in the low speed and low load of a gasoline vehicle (Li, 2007; Graskow et al., 1998). The comparison data are chosen from the ECE-15 tests and the ORMs under cruising condition, 15 km h1, 32 km h1, and 50 km h1. The size distributions for NCs and MCs are shown in Fig.9. Apparently, for all the speeds in the CDTs, the size distributions for NCs obey a unimodal distribution with a particle median of 10.8 nm. And Fig.9a shows that the NCs with a Dp larger than 339.8 nm are very close to zero. At the three speeds in the ORMs, the maximum NCs are concentrated in the range of 56.23 nme 64.94 nm. The average NCs at the three speeds (15, 32, and 50 km h1) in the CDTs are 2.78, 2.19, and 0.48 times higher than those in the ORMs, respectively. While, the MCs in the CDTs are separately 0.19, 0.17, 0.009 times higher than those in the ORMs. The reason is probably that the vehicle operated more smoothly in the CDTs than that in the ORMs without hard acceleration and deceleration. The mixture was burned completely resulting to less particles with larger sizes. The total
Fig. 6. (a) Particle number distribution in different driving cycles from ORM and (b) that from CDT. NC is the concentration of the number of particles in # cm3 (presented in dN/ dlogDp).
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Fig. 7. (a) Size distributions for NC, and MC (b) size distributions for in different speeds from the CDT. MC is the mass of particles measured in mg cm3 (presented dM/dlogDp).
Fig. 8. (a) Size distribution for NCs, and (b) size distribution for MCs from the sampling tests.
carrying weight of the vehicle in the ORMs was about 265 kg, higher than that in the CDTs which was not carrying the instruments and operators. To obtain the same speed in the CDTs and the ORMs more power from the vehicle was needed. More mixture was burned, and then more soot was formed in the condition of hypoxia (Wang et al., 2009). In addition, the dilution air in the ORMs was from the surrounding real-world, while the CDTs were carried out in the relatively closed room. The mixture in the engine cylinder was composed of gasoline fuel and the air from the environment. The background particles maybe have some impacts on the size distributions, which can’t be treated separately.
3.4. Influences of vehicle acceleration on fine particles The accelerations described at Fig.10a are mostly distributed uniformly between 1.5 m s2 and 1.5 m s2, and the other accelerations are scattered above 1.5 m s2 and below 1.5 m s2. The accelerationespeed profile in the CDTs is shown in Fig.10b, with some fixed accelerations. The driving conditions are complex and frequent accelerations and decelerations happen in real-world traffic. The accelerationespeed profile in the ECE-15 can’t be treated as a good representation of the real-world driving cycle. Just as discussed above, the acceleration does have the biggest influence on the particle emissions.
Fig. 9. (a) Size distribution for the NC and (b) the average MC at different speeds from the CDT and the ORM.
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Fig. 10. (a) Acceleration levels as a function of speed in the ORM and (b) in the NEDC.
Fig. 11. (a) The particle NC distribution in the ORM, (b) and the particle NC distribution in the CDT.
A typical result of a representative ORMs is chosen to show the particle size distributions shown in Fig.11a, while Fig.11b shows the particle size distributions for the NC in the CDTs. The accelerations and decelerations are divided into eight bins according to the frequency of accelerations, shown in Table 3. Fig. 11a shows that the NCs in all the acceleration bins reach up to the maxima where the median of particle size is 39.2 nm, with a maximum NC of 4.90E6 # cm3 in the bin [0.6 m s2, 0.9 m s2) and a minimum NC of 2.54E6 # cm3 in the bin (0.6 m s2, 0.3 m s2]. The NCs for other bins are very close to each other. Fig.11b shows that the NCs in all the acceleration bins obey a unimodal distribution, with a particle median of 10.8 nm. The maximum concentration of 1.09E7 # cm3 happens in the interval of [0.3 m s2, 0.6 m s2), with the acceleration of 0.52 m s2. However, the NCs are very close in these intervals [0.6 m s2, 0.9 m s2), (>0.9 m s2], and (<0.9 m s2]. The on-road data in Fig. 12a shows a shift of 93.1e107.5 nm in the maxima of the size distributions toward larger particle sizes in accordance with the acceleration bins [0.6, 0.9), (>0.9], [0.3, 0.6), (<0.9), [0.3, 0.3), [0.9, 0.6), and [0.6, 0.3). The ratios of Table 3 The definition of operating modes. Acceleration
Cruising
0.9 m s2 [0.6,0.9） m s [0.3,0.6) m s [0.1,0.3) m s (0.1,0.1) m s
Deceleration
Idling
0.9 m s2 (0.9,0.6] m s (0.6,0.3] m s (0.3,0.1] m s Speed <0.5 km h1
average MC in the above acceleration bins in the ORMs to those in the CDTs are 59.0, 20.9, 31.1, 48.6, 34.5, 44.2, and 35.5, respectively. The maximum of the MC in the CDT is 19.7 mg m3 (Fig. 12b), and that in the ORMs is 650.3 mg m3 (Fig. 12a). Just as discussed above, the maximum MC happened in the interval of [0.6 m s2, 0.9 m s2). The average speeds corresponding to the acceleration bins are shown in Table 4. The biggest average speed is 28.0 km h1, just corresponding to the acceleration interval [0.6 m s2, 0.9 m s2). The NC distributions in different acceleration bins basically correspond to the average speed, which can be treated as a reason that at higher average speeds, the NC is higher. Indeed, more particles are emitted under the condition of hard acceleration at higher speeds. 3.5. Influences of vehicle load on number and mass concentration The vehicle load during the ORMs is 265 kg heavier than that in the CDTs, which needed to be discussed. Some studies were carried out to study the impact of weight on the emission (Zhai et al., 2006). Frey et al. (2007) found that modal diesel fuel consumption rates were found to increase by 33% on average when the number of on-board passengers increased from less than 20 to more than 40. To make a more precise description of impact of vehicle load on fine particles emission, an extra test was added under the NEDC. The same instruments were used with basically the same ambient temperature and humidity. It shows an identical number concentration distribution, which comes to the maximum at the particle size of w10.8 nm. But the total number concentration
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Fig. 12. (a) The particle MC distribution in the ORM, (b) the particle MC distribution in the CDT.
Table 4 Average speed in acceleration bins from the ORM and the CDT. Bins(m s2)
[0.3 w 0.6)
[0.6 w 0.9)
(>0.9]
[0.6 w 0.3)
[0.9 w 0.6)
(<0.9)
[0.3 w 0.3)
Avg. ORM (km h1) Avg. CDT (km h1)
24.5 23.6
28.0 26.8
25.3 13.6
23.3 24.9
21.0 21.1
21.7 10.9
22.9 26.7
with the higher load is about 23% higher than that without extra load. The two concentrations show a unimodal lognormal distribution with the particle size of 254 nm. But the total mass concentration with higher load is 12% greater than that under the condition of normal load. The extra test tells that the vehicle load has a certain impact especially on the total number and mass concentration but no significant impact on the size distribution, especially the nanoparticles emission. All in all, the results are still acceptable. From this, the difference between the number and mass concentration from the ORMs and CDTs are mainly caused by the different speedeacceleration profile. However, the impact of load on particle emission is just studied from the weight of the instruments and stuff member in the tests. More systematical tests are needed to examine thoroughly the vehicle load impact on emission characteristics. 3.6. Influences of environmental temperature and relative humidity In general, both temperature and relative humidity play a role in UFs number concentration (Jamriska et al., 2008). Basically, the FP emission is different in winter and summer which has proved by many researches (Rönkkö et al., 2006). Casati et al. (2007) reported that when the temperature ranged from 9 to 25 Cand relative humidity was between 55% and 69%, there was no significant of the number concentration distribution. But, in winter, the number of small particles (Dp < 15 nm) is increased. When the study was carried out, and the temperature under the condition of real-world and chassis dynamometer test were so close that it can’t be the main impact factor. Morawska et al. (2008) showed that nucleation mode particles were largely influenced by relative humidity with high concentrations during high humidity periods. Charron and Harrison (2003) proved that the lack of a dependence on the relative humidity during the daytime was considered indicative that the nucleation was not a major factor in particle production. The weather was fine when the tests were carried out, and the relative humidity was just about 49%, which was identical with that in CDTs. Thus, it is not possible for the relative humidity to cause the difference. The FPs emission is influenced by many factors, making it not easy to be included all impacts from the outside environment. Thus, the result of the study is limited in a certain condition. In further
research, some factors such as the dilution air temperature and background particles concentration will be discussed in detail. 4. Summary and conclusions The sizes distributions for the NC in the CDTs are different from that in the ORMs with different driving cycle. The size distributions for the NC obey a unimodal distribution with the median of particle 10.8 nm in CDTs, where the maxima of the NC increased when the engine load increased from idling, deceleration and cruising to acceleration. In ORM, the size distributions obey a bimodal distribution with two modal sizes of 10.8 nm and 39.2 nm. More particles in nuclei mode were produced in the CDTs with the maximum 1.1E7 # cm3, and the ratio of the NC to that in the ORMs is 3.0, but the MC in the CDTs was just 0.13 times the MC in the ORMs. In the CDTs, more particles in nuclei mode were produced at the lower speeds. At the speeds of 10 km h1e80 km h1, the size distributions for the NC show a unimodal distribution with a particles median of 10.8 nm, while the size distributions at the speeds in the ORMs shift in the particles median of 39.2 nm. The average NCs at the three speeds of 15 km h1, 32 km h1, and 50 km h1 in the CDTs are 2.78, 2.19, and 0.48 times those in the ORMs, respectively. Meanwhile, the MCs in the CDTs are 0.19, 0.17, and 0.009 times those in the ORMs, respectively. Frequent hard acceleration has an adverse effect on the gasoline fine particles emission. The size distributions for the NC came up to the maxima in the acceleration interval of [0.6 m s2, 0.9 m s2) during the ORMs; while in the CDTs, the acceleration is 0.52 m s2. The maximum ratio of the MC in the ORMs to that in the CDTs are 50. The dilution ratio was fixed at 1:8, and the compressed air in dilution came from the surrounding. The background NC of fine particles can’t be excluded in the study. The measurements were just carried out on a gasoline vehicle. More types of gasoline vehicles are needed for the future studies. Acknowledgements The authors would like to thank all the colleagues involved in the measurements. This work is supported partially by the National Natural Science Foundation of China (No. 50778041, 51008155,
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