Journal of Aerosol Science

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1 Journal of Aerosol Science 57 (2013) Contents lists available at SciVerse ScienceDirect Journal of Aerosol Science journal homepage: Comparison of PM emissions from a gasoline direct injected (GDI) vehicle and a port fuel injected (PFI) vehicle measured by electrical low pressure impactor (ELPI) with two fuels: Gasoline and M15 methanol gasoline Bin Liang a,b, Yunshan Ge a,*, Jianwei Tan a, Xiukun Han a, Liping Gao a, Lijun Hao a, Wentao Ye a, Peipei Dai a a National Lab of Auto Performance and Emission Test, Beijing Institute of Technology, Beijing , China b Beijing Automotive Research Institute Co., Ltd., Beijing , China article info Article history: Received 23 July 2012 Received in revised form 9 November 2012 Accepted 13 November 2012 Available online 30 November 2012 Keywords: Particulate matter (PM) M15 methanol gasoline Gasoline direct injection (GDI) Mass estimation Number distribution Electrical low pressure impactor (ELPI) abstract Two Euro 4 gasoline passenger vehicles (one gasoline direct injected vehicle and one port fuel injected vehicle) were tested over the cold start New European Driving Cycle (NEDC). Each vehicle was respectively fueled with gasoline and M15 methanol gasoline. Particle number concentrations were measured by the electrical low pressure impactor (ELPI). Particle masses were measured by gravimetric method and estimated from the number distributions using two density distributions (one is constant with the particle size and one is power law related with the size). The first 7 stages of ELPI were used for estimation. The results show that for each vehicle, PM masses measured by gravimetric method, the total PM numbers measured by ELPI and estimated PM masses for M15 are lower than those for gasoline. For each kind of fuel, PM masses by two methods and total PM numbers from the GDI vehicle are higher than those from the PFI one. PM number distribution curves of the four vehicle/fuel combinations are similar. All decline gradually and the maximum number of each curve occurs in the first stage. More than 99.9% numbers locate in the first 8 stages of which diameters are less than 1 mm. PM number emissions correlate well with the acceleration of the two vehicles. The estimated particle masses were much lower than the gravimetric measurements. & 2012 Elsevier Ltd. All rights reserved. 1. Introduction Research on alternative fuels around the world has been widely carried out for reasons like continually rising demands for present energy along with population growing and science and technology development, increasing fuel prices, worries about the exhausting of petroleum and requirements to guarantee energy security (Abu-Zaid et al., 2004; Bilgin & Sezer, 2008). Methanol, also named as methyl alcohol, has received great attention for its lower price and easier production from a lot of resources such as natural gas, coal, combustible trash, city waste and wood (Bilgin & Sezer, 2008; Wei et al., 2008). It is very important to produce methanol from coal which is abundant in the world for a relatively long time, especially for China. In China, taking methanol as an alternative fuel has two realistic reasons. Firstly, the structure of Chinese energy resources is short * Corresponding author. Tel.: þ ; fax: þ addresses: binliang1@yahoo.com.cn (B. Liang), geyunshan@bit.edu.cn (Y. Ge) /$ - see front matter & 2012 Elsevier Ltd. All rights reserved.

2 B. Liang et al. / Journal of Aerosol Science 57 (2013) of fuel and gas but rich of coal. Secondly, grains are not sufficient to produce ethanol for automobile use (Bilgin & Sezer, 2008; Wei et al., 2008; Zhang et al., 2010). Methanol also has some technical advantages as an alternative or supplementary fuel since it can be burned purely or in a mixture with gasoline at different ratios (Wei et al., 2008). Due to higher octane number, lower boiling point, lower carbon/hydrogen ratio and higher oxygen content over gasoline, engines with methanol can work on higher compression ratio and emit less carbon monoxide (CO) and hydrocarbon (HC) (Bilgin & Sezer, 2008; Wei et al., 2008; Zhao et al., 2010). Additionally, methanol has a higher latent heat of evaporation which can cooling the intake air and thus help on increasing the volumetric efficiency and power output of engines (Bilgin & Sezer, 2008; Zhao et al., 2010). For the above reasons, methanol has aroused great focus as a promising alternative fuel (Bilgin & Sezer, 2008; Liaoet al., 2006; Zhao et al., 2010). In 2009, China issued two standards which are GB/T methanol gasoline (M85) for motor vehicles and GB/T fuel methanol for motor vehicles. This accelerates the research on methanol gasoline in China. However, there are two disadvantages need to be mentioned for taking methanol as a vehicle fuel. Firstly, emissions of formaldehyde will increase along with the increase of methanol content in gasoline. Formaldehyde is carcinogenic and has great adverse effects on human health (Zhao et al., 2010). Secondly, burning methanol derived from coal contribute to more carbon dioxide (CO 2 ) emission than gasoline. The lifecycle CO 2 emission for methanol derived from coal is 5.3 t CO 2 per ton of methanol burned. For gasoline, the value is 4.03 t (Yang & Jackson, 2012). In order to increase fuel economy, reduce CO 2 and meet more stringent emission regulations, automobile manufacturers are increasingly employing gasoline direct injected (GDI) engine technology (Maricq et al., 2012; Myung et al., 2012). Due to the fuel is directly sprayed into the cylinder with higher injection pressures than port fuel injected (PFI) engine, the atomization and vaporization rate of the fuel are increased. Also, the volume of fuel and process of combustion can be more accurately controlled at different working conditions. Along with stratified combustion and charge air cooling technology, GDI engine can improve fuel efficiency, reduce cold start unburned hydrocarbons emissions and reduce CO 2 emissions (Zhao et al., 1999). However, since the time for preparing even combustible mixture is short and fuel impingement on surfaces of piston and cylinder happens unexpectedly, GDI engine may emit more particulate matter (PM) (Maricq et al., 2012; Myung et al., 2012; Zhao et al., 1999). Facing the popularization of GDI technique and increase of concerns on environmental protection, more stringent particulate matter emission standards applied to GDI engines are introducing around the world. In the European Union (EU), according to commission regulation (EC) no. 692/2008, also called Euro 5 and Euro 6, the particle limit values are 4.5 mg/km ( In the USA, both California Air Resources Board (ARB) and EPA are considering to tighten next tailpipe PM emissions standards. Particle limit values may require decreasing from 10 mg/mi to 6 mg/mi, and then 3 mg/mi (Maricq et al., 2012). In China, Beijing Municipal Environmental Protection Bureau is receiving suggestions from the public on the implementation of the BEIJING regulation, which equals to requirements of Euro 5 on PM emissions ( Table189/info8584.htm). Studies on regulated and unregulated emissions from engines tested on engine test benches or passenger vehicles tested on chassis dynamometers fueled with methanol/gasoline blends have been reported (Abu-Zaid et al., 2004; Bilgin & Sezer, 2008; Wei et al., 2008; Zhang et al., 2010; Zhao et al., 2010). But few investigated the effects of adding methanol to gasoline on PM emissions from GDI engines and GDI vehicles. In this study, two passenger vehicles, respectively equipped with GDI engine and PFI engine, fueled with gasoline and M15 methanol gasoline were examined. Tests were conducted on the chassis dynamometer over New European Driving Cycle (NEDC) at cold start mode. PM emissions were analyzed with two metrics: numbers measured by ELPI; masses measured by gravimetric method and estimated from measured number distributions. 2. Material and methods 2.1. Test vehicles and fuels Two light-duty passenger vehicles were tested in the comparative experiments. Both were manufactured by Shanghai Volkswagen Automotive Co., Ltd. and met the Euro 4 emission standard. Table 1 shows detailed technical data of the two vehicles. One equipped with gasoline direct injected engine which is the main stream GDI engine type in China. The other is port fuel injected. Both are turbocharged and fitted with three-way catalyst. Two types of fuel were used: commercial 93 research octane number gasoline and M15 methanol gasoline. The commercial 93 gasoline complies with China fourthstage fuel standard which equal to Euro 4. M15 methanol gasoline was made by mixing the commercial 93 gasoline with industrial grade methanol in fraction of 15% by volume. Table 2 shows properties of the two fuels. In the following context, Combo 1, Combo 2, Combo 3 and Combo 4 are used to represent the GDI vehicle fueled by gasoline, the GDI vehicle fueled by M15, the PFI vehicle fueled by gasoline and the PFI vehicle fueled by M15 respectively Test cycle All tests were carried out on a 40-in. single roll, DC electric chassis dynamometer (PECD 9400, Ono Sokki Ltd., Japan) over cold start NEDC. Before each test, the vehicle must be conditioned at a temperature of (2572) 1C over 16 h. The NEDC

3 24 B. Liang et al. / Journal of Aerosol Science 57 (2013) Table 1 Vehicle specifications. GDI PFI Type Passat 1.8TSI Passat 1.8T Displacement (L) Number of cylinders 4 4 Bore stroke (mm 2 ) Compression ratio Maximum power at engine speed (kw/rpm) 118/ /5700 Maximum torque at engine speed (N m/rpm) 250/ / Odometer (km) 12,076 75,680 Table 2 Fuel properties. Characteristic Gasoline M15 T10 (1C) T50 (1C) T90 (1C) Sulfur (ppm) Aromatics (vol%) Reid vapor pressure (kpa) Fig. 1. PM gravimetric measurement system. includes two parts. The first part is urban cycle which consists of four nonstop repeated ECE-15 cycles. The second part is extra urban driving cycle (EUDC). Urban cycle lasts for 780 s and travels km while EUDC, 400 s and km. The maximum speed in the urban cycle and EUDC is 50 km/h and 120 km/h respectively Gravimetric measurement of PM Fig. 1 shows the schematic diagram of the gravimetric measurement system. According to the emission regulations, through the full flow constant volume sampling system (CVS-7400T, Horiba Ltd., Japan), tailpipe gas was diluted by air and PM was collected on the filter. Dilution air was filtered to extract particulate matters by a dilution tunnel (DLT-1230, Horiba Ltd., Japan) % of particles with size diameter of 0.3 mm were filtered. The temperature of the dilution air was conditioned to C. The relative humidity was conditioned to 4572% relative humidity. The tunnel flow rate and flow rate through the filter were 9 m 3 /min and 90 L/min respectively. The filters were weighted on microbalance (CPA2P-F, Sartorius AG, Germany) in a Euro 5 standard compliant static controlled weighing chamber. The standard deviation of the microbalance is less than or equal to 1 mg. In the chamber, temperature and dew point of the environment were conditioned to C and C respectively. Filter weights were corrected for filter buoyancy in air Number measurement of PM Electrical low pressure impactor (ELPI) (Dekati Ltd., Finland) was used to monitor the size distribution of aerosol particles. ELPI includes 12 channels and each channel is connected to an electrometer current amplifier. Particles were first charged and then collected into different stages according to inertia. During each stage, corresponding electrometer current amplifier detects the current (Marjamaki et al., 2000). The current value and the size distribution in each stage are proportional based on particle size dependent relations between the properties of the charger and the impactor stages (Liu et al., 2011). SEMTECH emission flow meter (Sensors, Inc., the USA) and SEMTECH-DS analyzer were used to directly measure real-time exhaust flow rates. The flow meter was integrated with a stainless steel pipe of which outside diameter is four inches.

4 B. Liang et al. / Journal of Aerosol Science 57 (2013) Fig. 2. PM number measurement system. Fig. 3. PM masses of the four combinations tested through gravimetric measurement method. Fig. 2 shows the schematic diagram of the number measurement system. The stainless steel pipe of the flow meter was connected on the tailpipe. Gases from the pipe were partial flow sampled. Sampled gas passed through two dilutors and was measured by ELPI. Both dilutors used compressed air which was dried, high efficiency particulate air filtered to dilute the inlet gas. In order to prevent the high concentrated and high temperature exhaust from condensing and form an even dilution of gases and particles, the compressed air to the first dilutor and the mixture out of the first dilutor were all preheated to 195 1C Test procedures Each vehicle was firstly fueled with gasoline. Vehicles with gasoline were measured by gravimetric method on the first day and were tested by ELPI on the second day. After the tests on gasoline were finished, the fuel tanks were drained. Each vehicle was then filled with 10 l M15 methanol gasoline and was driven at a constant velocity of 60 km/h on the chassis dynamometer until it had no fuel. The fuel tanks were drained again and each vehicle was filled with 10 L M15 again. Same driving process was done until the fuel was not enough. Then vehicles were drained for the third time and filled up with M15. After the change of fuel was done, measurements on M15 were conducted accordingly. 3. Results and discussions 3.1. PM mass and number emissions Fig. 3 presents particle masses measured by gravimetric method for the four vehicle/fuel combinations over cold start NEDC. Fig. 4 exhibits total particle numbers tested by ELPI. Units are milligram per kilometer (mg/km) and number per

5 26 B. Liang et al. / Journal of Aerosol Science 57 (2013) Fig. 4. Total particle numbers of the four tests measured by ELPI. kilometer (#/km) respectively. There are three points need to be mentioned for the two figures. (1) Compared with gasoline, the GDI vehicle fueled with M15 gets 78% and 56% reductions for PM mass and total particle number respectively. For the PFI vehicle, the percentage reductions are 74% and 25%. Two possible reasons may explain these reductions. Firstly, M15 contains more oxygen than gasoline. The pre-mixed oxygen effect results in a more complete combustion (Wei et al., 2008; Zhao et al., 2010). Secondly, adding methanol in the gasoline can reduce the soot precursor concentrations. Compared with gasoline, methanol does not have aromatic components that are prone to soot production (Westbrook et al., 2006). (2) For gasoline, the PFI vehicle s PM mass and total particle number decline about 76% and 77% from those from the GDI vehicle. For M15, the values are 72% and 60%. (3) The PM mass limit value in Euro 5 for GDI vehicles is same with that for compression ignition (CI) vehicles. But the PM number limit value for GDI vehicles is not regulated. Comparisons between tested numbers and the PM number limit value for CI vehicles were conducted. But the main difference between the particle measurement method of ELPI and that legislated in the Euro 5 need to be mentioned. According to the European method, non-volatile particles are counted by a particle number counter with lower cut point at 23 nm. The volatiles and semi-volatiles are removed by using a hot dilution stage at C (the wall temperature set point should not exceed the wall temperature of the evaporation tube) and an evaporation tube at C. Since ELPI does not have the evaporation tube, total particles were measured. Also the lower cut point of ELPI is about 8 nm. Ratios of PM masses for Combo 1, Combo 2, Combo 3 and Combo 4 to the Euro 5 limit value are 3.1, 0.69, 0.74 and 0.19 respectively. For the total particle number, ratios are 7.8, 3.4, 1.8 and 1.4 accordingly. Ratios of 3.1 and 7.8 suggest that GDI vehicles face similar challenges from Euro 5 standard as diesel passenger vehicles on PM emissions. When GDI vehicles are fueled with M15, PM masses can meet the requirement. Although PFI vehicles have less mass emissions, their particle numbers are also need attention. Attributed to the development of emission control techniques for diesel vehicles, PM emissions from Euro 5 or Euro 6 diesel vehicles are decreasing greatly. Contribution of gasoline vehicles to the PM inventory will gradually increase and cannot be ignored. Fig. 6 illustrates transient particle number emission rates from the GDI vehicle fueled with gasoline over cold start NEDC. Particle number emission rates are derived by multiply PM number concentrations measured by ELPI with timealigned tailpipe emission flow rates measured by SEMTECH-DS. As can be seen in the figure, particle number emissions correlate with the vehicle acceleration. Transient particle number emission rates of the other three vehicle/fuel combinations show similar correlation Particle number distribution Fig. 5 shows PM number distributions of the four vehicle/fuel combinations. The four curves perform similar trend and all decrease gradually. The maximum values for Combo 1, Combo 2, Combo 3 and Combo 4 are km 1, km 1, km 1 and km 1 respectively. All these peaks occur in the first stage with an average diameter of 21 nm. At each stage, the PM number from each vehicle with M15 is lower than that with gasoline; the PM value from the GDI vehicle is higher than that from the PFI vehicle for the same fuel. Nanometer size particles are facing more stringent emission standards for its strong relation with mortality (Liu et al., 2011). EPA proposes to revise the annual PM2.5 (particles less than or equal to 2.5 mm in diameter) standard by lowering the level to within a range from 12.0 to 13.0 micrograms per cubic meter (mg/m 3 )( China issued GB on Feb. 29, 2012 in which PM2.5 limit values were first introduced. The 24-h average values are 35 mg/m 3 and 75 mg/m 3 for the first and second class districts respectively ( During these four tests, PM numbers of the stages 1 10 of which diameters are less than 2.5 mm amount for %, %, % and % of the total numbers respectively for Combo 1, Combo 2, Combo 3 and Combo 4. The percentages of stages 1 8 of which diameters are less than 1 mm are %, %, % and %.

6 B. Liang et al. / Journal of Aerosol Science 57 (2013) Fig. 5. Particle number distributions for the four tests measured by ELPI. Fig. 6. Transient PM number emissions for the GDI vehicle fueled with gasoline over cold start NEDC PM mass estimations ELPI is mostly used for measurement of particle number distributions. Some researches on conversion of the ELPI particle number distributions to particle mass were also reported. Liu et al. (2011) used size distributions of the first 7 ELPI stages to estimate particle masses from four diesel buses (two Euro 3 level buses and two Euro 4 level buses). But they did not compare the estimations with gravimetric measurements. Zervas et al. (2006) used ELPI to estimate emissions from three Euro 3 cars (a PFI gasoline car, a diesel car and a diesel car equipped with diesel particulate filter) over NEDC and compared the estimations with filtered masses. Also they compared the difference of the estimated results between the first 7 stages and all stages. They concluded that the use of all stages overestimated the particle masses. When the first 7 ELPI stages were used, results are better, but the dispersion is also high. Maricq et al. (2006) used the lowest 7 ELPI stages to estimate emissions from five cars (a diesel vehicle with an oxidation catalyst, a diesel vehicle equipped with a diesel particulate filter and an oxidation catalyst, a GDI vehicle and two PFI vehicles) and concluded that particle masses derived from number concentrations agree well with masses measured through gravimetric method on high level PM emission vehicles. They also stated that on the upper stages, non-idealities like electrical noise, electrometer drift, and small errors in the diffusion and electrostatic loss will be amplified by mass weighting. Based on these studies, the first 7 ELPI stages were used in this study for mass calculation. In order to calculate PM masses from number concentrations measured by ELPI, the effective density of particles is need to be given. Two kinds of density distributions were reported. One is constant with the particle size. The values used included 1.0 g/cm 3 (Shi et al., 1999; Zervas et al., 2006), 0.5 g/cm 3 (Witze et al., 2004)and1.7g/cm 3 (Ulfvarson et al., 1997). The other is a function of the size. Particles emitted from vehicle engines are agglomerates of small carbonaceous primary particles (Maricq et al., 2006). Since particles are highly agglomerated as size increases, the effective density decreases as the particle size increases (Park et al., 2003). Reported values include values of g/cm 3 (Zervas et al., 2006), 1.0 g/cm 3 at 50 nm and 0.3 g/cm 3 at 300 nm (Witze et al., 2004), 1.2 g/cm 3 at 30 nm to o0.3 g/cm 3 at 300 nm (Maricq & Xu, 2004), g/cm 3

7 28 B. Liang et al. / Journal of Aerosol Science 57 (2013) (Andrews et al., 2001) and g/cm 3 (Ahlvik et al., 1998). Among the second kind of density distributions, the power law relationship shown in Eq. (1) between the effective density and mobility diameter were reported (Maricq & Xu, 2004; Park et al., 2003; Virtanen et al., 2004). d r e p d f 3 m ð1þ where r e is the particle s effective density, d m the particle s mobility diameter and d f the fractal dimension which is commonly used to characterize the structure of agglomerated particles. This relationship is based on the fractal like morphology of particles and thus it is a reasonable approximation. In this study, two density distributions were used. One is constant with particle sizes and the density value is 1.0 g/cm 3. The other is a detailed power law density shown in Eq. (2) used by Maricq et al. (2006). r e ¼ r df 3 0 d m =d 0 ð2þ where r 0 is the primary particle density, d 0 the primary particle diameter. r 0, d 0 and d f are given the value of 2.0 g/cm 3, 20 nm and 2.3 nm respectively. Density distributions used for estimation were showed in Fig. 7. For the constant effective density distribution, the estimated particle mass is the sum of the particle mass of each stage. The particle mass of each stage is calculated by multiply effective density, volume and particle numbers of each stage. For the power law effective density distribution, the estimated particle mass is calculated via the fitting Eq. (3) used by Maricq et al. (2006). p M ¼ N 0 6 r 0 d ð 0 3 d f Þ d m f g e d f 2 ðlnsgþ 2 =2 ð3þ where N 0 is the total particle number and m g the geometric mean diameter. Values of r 0, d f and d 0 are same with those in Eq. (2). Fig. 8 shows particle masses estimated from the two density distributions and ratios of the estimated masses to gravimetric measurements for the four vehicle/fuel combinations. The upper part of this figure shows the estimated results and the lower part gives the ratios. Particle masses for the four vehicle/fuel combinations show a decreasing trend and follow the order Combo 14Combo 24Combo 34Combo 4 when each kind of density distribution is used. For each combination, the particle mass derived from constant density distributions is higher than that from power law ones. The exceeding percentage for Combo 1, Combo 2, Combo 3 and Combo 4 is 127%, 181%, 195% and 276% respectively. For each combination, estimated masses are much lower than the measured one. Masses calculated from constant density distribution are 7%, 17%, 5% and 13% of measured ones for Combo 1, Combo 2, Combo 3 and Combo 4 respectively. When power law density distributions are used, percentages are 3%, 6%, 2% and 4%. Several factors can help to explain why these big discrepancies exist. (1) For the low PM emitting vehicles, such as PFI gasoline vehicles and diesel particulate filter (DPF) equipped diesel vehicles, ELPI derived PM masses are much lower than gravimetric PM masses. From the data by Zervas et al. (2005, 2006), PM masses estimated from the first seven ELPI stages are averagely less than 20% and 10% of measured ones for the PFI gasoline vehicle and the DPF equipped diesel vehicle respectively over cold start NEDC (a constant density value of 1.0 g/cm 3 for each stage and the geometric mean diameter of each stage are used). Data by Maricq et al. (2006) show that estimated PM masses are less than half of filter collected ones for the DPF equipped diesel vehicle over each phase of the FTP cycle (power law density distribution and fitting equation mentioned above are used). Mostly the percentages are less than 40%. For PFI gasoline vehicles, except for the cold start phase, ratios of estimated masses to Fig. 7. Two density distributions used for estimating PM masses from PM number concentrations measured by ELPI.

8 B. Liang et al. / Journal of Aerosol Science 57 (2013) measured ones are less than 20% over the city portion and hot start phase of FTP cycle. Mostly the percentages are less than 10%. (2) In the previous studies (Maricq et al., 2006; Zervas et al., 2006), particles used for weighing and estimating were all sampled from the full flow CVS dilution tunnel in the same test. The same tunnel flow rate was used in both methods to calculate the final emission rates. In this paper, particles used for weighing were sampled from the CVS dilution tunnel in the first test. But particles and the total flow rates used for estimating were directly sampled from the tailpipe in the second test. For the comparison of the two test results, repeatability and measuring differences of flow rate seem to be two important influence factors. Zervas et al. (2006) reported that the repeatability of total particle Fig. 8. Particle masses estimated and ratios between estimated masses and measured masses. Fig. 9. Flow rates direct measured from the tailpipe for the two vehicles fueled with gasoline over NEDC.

9 30 B. Liang et al. / Journal of Aerosol Science 57 (2013) number measured by ELPI is 45%, 14%, and 96% for gasoline, diesel, and DPF-equipped diesel vehicles respectively. For filter collected PM, values are 60%, 12.7%, and 191%. These results show that comparative results of PM masses between the two methods are much scattering. Fig. 9 gives flow rates direct measured from the tailpipe for the two vehicles fueled with gasoline over NEDC (for each vehicle, flow rates recorded for M15 are similar with those for gasoline. So the two curves for M15 are not shown). The relationships between flow rates and vehicle speeds are reasonable. But the values are low, especially for the GDI vehicle. Sonntag et al. (2010) also reported that low exhaust flow readings were recorded in direct sampling by a Horiba OBS-1000 which uses the same measurement principle as that used in this paper. Eq. (4) was used by them to approximately estimate the minimum exhaust flow rate. This equation is based on the assumption that the exhaust gas is at constant pressure and temperature between the cylinder and sampling point. The fuel rate is also ignored for minor contribution to the exhaust flow at low fuel rate (Sonntag et al., 2010). exhaust flow ¼ engine displacement engine speed volumetric efficiency 1=2 ð4þ Engine speed is given the value of 750 rpm and volumetric efficiency is assumed to be 0.7. The calculated theoretical minimum exhaust flow rate is 7.8 L/s. This value is close to the flow rates of the first 11 s of idle stage. The average measured flow rate of this stage is 6.4 and 7.4 L/s for the GDI and PFI vehicle respectively. From this comparison, the calculated minimum flow rate seems to be reasonable. And thus the total measured flow rates are lower. 76% And 66% of the measured flow rates are lower than the calculated minimum one for the GDI and PFI vehicle respectively. Ratios of the minimum measured flow rate to the calculated one are 21% and 45% for the GDI and PFI vehicle respectively. For the GDI vehicle, 28% of the measured flow rates are less than 40% of the calculated one. These results may partially explain why the ratios of estimated masses to measured ones are low, especially for the GDI vehicle. (3) Organic vapor adsorption of filters used for weighing cannot be neglected for low PM emitting vehicles. Chase et al. (2004) reported that the vapor artifact accounts for 10 20% and 30 50% of the 2007 regulatory standard of 10 mg/mi for light duty vehicles for Teflo and TX40 filters respectively. Our data may also reflect this conclusion. Since methanol does not have aromatic components, when the vehicles were fueled with M15, filters may collect less organic materials than those with gasoline. Thus ratios of estimated/measured masses for vehicles fueled with M15 are higher than those with gasoline. (4) Systematic differences that come from the uncertainties in the soot effective density and the geometric standard deviation of the soot mobility distribution may result in an estimated 20% uncertainty in ELPI derived PM masses (Maricq et al., 2006). 4. Conclusions Particle masses and particle number concentrations from a GDI vehicle and a PFI vehicle over NEDC were measured. Each vehicle was respectively fueled with gasoline and M15 methanol gasoline. PM mass estimations from measured number concentrations using two different density distributions were conducted. For each vehicle, PM masses measured by gravimetric method, the total PM numbers measured by ELPI and estimated PM masses for M15 are lower than those for gasoline. Studies by Maricq et al. (2012) indicated that when the ethanol content increases to 430%, reduction in PM mass and number emissions are 30 45%. Storey et al. (2012) reported that PM masses from the stoichiometric GDI vehicle showed obvious reduction with E10 and E20. The percentage reduction for E10 and E20 are about 25% and 60% respectively. Take these three studies together, similar effects were found on PM mass and number emissions between the adding of methanol to gasoline and adding of ethanol to gasoline. For each kind of fuel, PM masses by two methods and the total PM numbers from the GDI vehicle are higher than those from the PFI one. Similar results were reported by Maricq et al. (2006). Their studies indicated that PM masses from a GDI vehicle fueled with gasoline over NEDC are in the range of mg/km; for phases 1 3 of the FTP cycle, PM masses fall in the range of 15 20, and 5 10 mg/km respectively. For the PFI vehicle, PM masses of the three stages of the FTP cycle are all lower than 1 mg/km. Zhao et al. (1999) also mentioned that PM masses of a GDI vehicle are on the order of 10 mg/mile and those from a PFI vehicle are in the range of 1 3 mg/mile. PM number distribution curves of the four vehicle/fuel combinations are similar. All decline gradually and the maximum number of each curve occurs in the first stage. More than 99.9% numbers locate in the first 8 stages of which diameters are less than 1 mm. PM number emissions correlate well with the acceleration of the two vehicles. Two density distributions and numbers of the first seven ELPI stages are used for particle mass estimation. But the estimated results were much lower than the gravimetric measurements. Acknowledgments The authors gratefully acknowledge financial support from Energy Foundation (G ).

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