Gasoline Direct Injection Engine Emissions of OC and EC: Laboratory Comparisons with Port Fuel Injection Engine

Received: January 20, 2022
Revised: April 5, 2022
Accepted: April 28, 2022

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Cite this article:

Zhang, J., Liggio, J., Chan, T.W., Huang, L., Brook, J.R. (2022). Gasoline Direct Injection Engine Emissions of OC and EC: Laboratory Comparisons with Port Fuel Injection Engine. Aerosol Air Qual. Res. 22, 220032. https://doi.org/10.4209/aaqr.220032

HIGHLIGHTS

• OC obtained from different protocols is consistent with peak release temperature.
• GDI vehicle had higher emissions under cold-start but not aggressive cycles.
• The emissions from GDI vehicle were less volatile than PFI vehicle.

Keywords: Gasoline direct injection, Port fuel injection, OC, EC, Gasoline particle filter

1 INTRODUCTION

Gasoline vehicle engines are generally known to emit less black carbon (BC) and total particle mass than those in diesel vehicles (Gordon et al., 2014). However, equipping diesel vehicles with diesel particle filters (DPF) has significantly reduced particle emissions, which has been shown in the laboratory test (Valverde and Giechaskiel, 2020) and on-road measurements (Preble et al., 2015; Chao et al., 2020). To further improve air quality, it is thus increasing important to focus on reducing emissions from gasoline vehicles. Gasoline direct injection (GDI) vehicles have many advantages over traditional port fuel injection (PFI) vehicles (Munoz et al., 2018) including improved fuel economy, more precise fuel injection control, less fuel pumping loss, higher compression, and charge air cooling (Chan et al., 2014). However, GDI vehicles have also been found to have higher particulate matter (PM) and BC emissions compared to traditional port fuel injection (PFI) vehicles (Saliba et al., 2017; Chan et al., 2014, 2012). The increased PM and BC emissions are due to incomplete gasoline vaporization and combustion, caused by the difference in fuel injection method and mixture preparation (Maricq et al., 2012; Zimmerman et al., 2016b; Chan et al., 2014, 2012). To reduce particle emissions from GDI vehicles, gasoline particle filters (GPF) have been developed and their use is becoming increasingly common (Munoz et al., 2018; Chan et al., 2014, 2012).

The particles emitted by vehicles are primarily composed of carbonaceous chemical species, broadly consisting of organic carbon (OC) and elemental carbon (EC) (Zhang et al., 2009; Lin et al., 2020). The characteristics of carbonaceous aerosols emitted by diesel vehicles have been studied extensively, whereas research on gasoline vehicle particle composition remains limited, with a relatively small number of studies reporting OC and EC emissions (Cai et al., 2017; May et al., 2013; Chan et al., 2016; Lim et al., 2021). OC emissions are complex, given that they are a mixed state of both particle and gas phase organic compounds, with semivolatile organic compounds (SVOC) dynamically partitioning between phases (Miersch et al., 2019). Such partitioning depends upon exhaust and ambient air conditions such as temperature and molecular structure, including the influence of rapid atmospheric oxidation (Zhang et al., 2013, 2016). This significantly complicates the sampling and measurement of OC emissions and assessment of their overall impact on ambient PM levels. The amount of gaseous SVOC and intermediate volatility species (IVOC), which are, at least partially adsorbed on a quartz filter when sampling, can be estimated by measuring OC on a quartz filter behind a Teflon filter (QBT) (May et al., 2013; Zhang et al., 2013, 2016; Chow et al., 2001; Cheng et al., 2010).

In order to help understand filter-based OC measurements, the different laboratory methods, which do affect the OC and EC emissions reported, are important to consider. Measurement consistency, or at least an understanding of the causes of differences between emissions data that may have relied on different laboratory methods, is necessary improve emission inventories, potentially leading to more confidence in model predictions, source apportionment studies and radiative forcing calculations (Huang et al., 2006; Andreae et al., 2005). Multiple thermal-optical protocols for OC and EC analysis exist. The National Institute for Occupational Safety and Health (NIOSH) (Birch and Cary, 1996) protocol has been evaluated by the U.S. EPA for measuring quartz filter samples for the national monitoring network and is also commonly used to measure OC and EC from source samples (Chow et al., 2001). The Interagency Monitoring of Protected Visual Environment (IMPROVE) protocol (Chow et al., 2001) is also widely applied for ambient and emission source carbonaceous aerosols measurement. Other thermal optical protocols include the European Supersites for Atmospheric Aerosol Research (EUSAAR) (Chiappini et al., 2014), Gwangju Institute of Science and Technology (GIST) (Jung et al., 2011) and EnCan Total-900 protocol (ECT9) (Huang et al., 2006).

In studies comparing OC and EC quantification under different measurement protocols, differences of up to a factor of two have been found for the relative OC and EC amounts (‘OC/EC split’), which arises from use of different heating temperatures and dwell times at each temperature step (Chiappini et al., 2014; Chow et al., 2005; Cheng et al., 2014; Giannoni et al., 2016). The magnitude of the differences in the OC/EC split among different protocols also depends upon the composition of the particles being tested (Chiappini et al., 2014).

The current study was designed to characterize carbonaceous aerosols emitted from GDI and PFI vehicles and the effects of a GPF on GDI emissions. The effects of engine type and vehicle operating conditions or cycles (e.g., cold or hot start, acceleration and speed) on OC and EC measurements are reported with a focus on the relative importance of gas phase OC (i.e., SVOC) adsorption on the quartz filters. This study also quantified the effects of three different thermal-optical measurement protocols (Chow et al., 2001; Huang et al., 2006; Chow et al., 2005) on the results, allowing other researchers to compare their results with various protocols.

2 METHODS

 
2.1 Vehicles and Driving Cycle Setting

The experiment was carried out on two light-duty passenger cars: a 2011 2.4 L Hyundai Sonata with a GDI engine and a 2010 2.4 L Volvo S40 with a PFI engine. During the experiment, the GDI vehicle was tested with and without a gasoline particle filter (GPF), which are referred as GDI+GPF and GDI, respectively. Descriptions and specifications of the two vehicles and the GPF are summarized in Chan et al. (2012, 2014). The emission experiments were conducted in a chassis dynamometer emissions measurement facility using three test cycles: (1) U.S. Federal Test Procedure (FTP-75), (2) FTP-72, and (3) US06 Supplemental Federal Test Procedure (US06). Information relating to these cycles are described in the Table S1, Figs. S1–S3 and elsewhere (Chan et al., 2014). Briefly, The FTP-75 represents city driving conditions, consisting of a cold-start, urban, and hot-start phases, where the cold- and hot-start phases are identical. The FTP-72 is a hot-start cycle, consisting only of the last two phases of the FTP-75. The US06 drive cycle simulates the aggressive driving condition (Maricq et al., 2013).

 
2.2 Particle Emissions Sampling

The exhaust from vehicles was diluted continuously using charcoal and high efficiency particulate air (HEPA)-filtered room air and then introduced into a full-flow constant-volume sampling (CVS) dilution tunnel. Two filter packs were utilized in parallel to sample diluted exhaust from the dilution tunnel using an isokinetic sampling technique at 16.7 L min^–1 onto a 47 mm diameter pre-fired quartz filters over the entire drive cycle for OC and EC analysis. One of the filterpacks contained a single 47 mm bare quartz filter (Q) and the other contained a 47 mm Teflon filter followed by QBT. Q and QBT integrated samples were collected for each vehicle and test cycle. The OC determined from the QBT is assumed here to estimate the volatility of the particle emissions, since it represented the gas phase OC not trapped by Teflon filter (Cheng et al., 2010). While previous studies have used OC on QBT as a positive artifact correction (Cheng et al., 2010), this study found negative OC of Q-QBT, since a negative artifact (i.e., particle phase SVOC evaporated from the front filter) is also captured on QBT (Zhang et al., 2013, 2016). Therefore, in this paper we use OC on QBT independently and also consider subtracting OC on QBT from Q.

Emissions of other gaseous phase pollutants (CO, CO₂, NO_x and THC) were also measured as given in Table S2. Repeat tests for these gaseous pollutants were performed for most of the cycles to assess variability among tests with the average values and standard deviations shown in Table S2. The differences for the gaseous pollutants between tests for CO, CO₂, NO_x and THC were 15%, 2%, 21% and 8%, respectively. We assume that a similar variability was likely to be present in the OC and EC emissions, and thus obtained Q and QBT samples once for each cycle and engine configuration.

 
2.3 Carbonaceous Aerosol Measurement Methods

The quartz filters (Q and QBT) were analyzed using three thermal optical protocols. The details are provided in organic carbon. Briefly, these included: (1) IMPROVE where the reflectance signal was used to determine the OC/EC split (i.e., thermal optical reflectance, TOR) (Chow et al., 2001); (2) NIOSH 5040 protocol for thermal optical transmission (TOT) (Giannoni et al., 2016); and (3) ECT9 (Huang et al., 2006). In the ECT9 protocol, the quartz filter was heated stepwise to temperatures of 550°C and 870°C in a pure helium environment to determine OC, including low molecular weight non-refractory organic carbon and pyrolyzed organic carbon (POC) detected at each temperature (Huang et al., 2006). Then the environment was shifted to 10% O₂/90% He, and the filter was heated to 900°C to determine EC. By using the high inert mode temperature, the remained POC could be detected as EC are negligible (Huang et al., 2006). Each protocol also follows different temperature-ramping sequences (Table S3). The IMPROVE protocol was conducted with a DRI 2001 thermal-optical carbon analyzer, and the NIOSH 5040 and ECT9 protocols were carried out with a Sunset Laboratory thermal-optical-transmittance analyzer. The OC and EC results for each protocol are compared in the Table S4.

 
3 RESULTS AND DISCUSSION

 
3.1 Comparison of the OC/EC Protocols

Fig. 1 summarizes the relative OC, EC, and total carbon (TC) for the NIOSH and ECT9 with respect to IMPROVE. In comparison, the IMPROVE and NIOSH protocols generally gives similar TC amount, while the ECT9 protocol results in higher TC than the IMPROVE protocol, but by less than 10%. This overall agreement is in accordance with other studies, which demonstrated that the variance in TC among different protocols was generally less than 10% (Chow et al., 2005; Khan et al., 2012). OC obtained by the IMPROVE protocol was generally the lowest among the three protocols, followed by NIOSH and then ECT9, which is consistent with a lower peak temperature for OC release using in IMPROVE (550°C vs. 850°C or 870°C). Accordingly, EC determined by IMPROVE was the highest, followed by ECT9 and NIOSH. Since the ECT9 method yielded the highest TC, its EC result was greater than NIOSH.

Fig. 1. Comparison of the relative (a) OC, (b) EC and (c) TC concentrations measured by the NIOSH and ECT9 protocol with respect to IMPROVE. The edges of boxes indicate the 25^th and 75^th percentile, the whiskers extend to the 10^th and 90^th percentile, and the central (red) lines on the boxplots are averaged data.

The difference of the protocols is mainly due to a portion of organic compounds evolve at relatively high temperatures (Subramanian et al., 2006). It could also be slightly affected by the difference of detection methods, since only transmittance method could detect the charred POC inside quartz filter. Nonetheless, this reason still has low impact, as the emissions directly from engine exhaust have not been oxidized in the atmosphere and the POC formation was low (< 5% of TC) for all three protocols used. Given the expected analytical uncertainties in any single OC/EC analysis, we use the average values of three protocols for each sample (Table S4) in the remainder of the results below. More confidence may also be gained by averaging the results given their differences imply some analytical uncertainty in the OC and EC measurements.

 
3.2 OC and EC Emission Factors (EF)

OC and EC EFs in µg C km^–1 for each vehicle and test cycle are given in Table 1. The OC EFs for the three engine conditions during the FTP-75 and FTP-72 drive cycles were comparable and lower than the US06 drive cycle. The EFs between the GDI, GDI+GPF and PFI during the FTP-75 drive cycle were found to differ by less than 36%. Similar quantities and variations were found during the FTP-72 cycle. In contrast, under the US06 drive cycle the OC EFs were larger, especially from the PFI engine, and there was considerable variability among the vehicles. Specifically, the OC EFs for the GDI and PFI vehicles were 1455 ± 234 and 3581 ± 82 µg C km^–1, respectively, which were 3.7 and 15.8 times higher than that of FTP-72 test cycle. As both US06 and FTP-72 are hot-start cycles, this higher emission rate for OC is likely due to the aggressive driving pattern. This is consistent with previous measurements on the same vehicles which also showed significantly higher emissions from the PFI vehicle during very aggressive driving conditions compared to the GDI counterpart (Chan et al., 2014, 2012, 2013). This is likely related to the different fuel injection methods of the two types of vehicles. During very demanding conditions (e.g., US06 cycle), the continued increase in fuel injection for the PFI vehicle significantly leads to incomplete vaporization of the fuel, thus worsening the emissions. In contrast, the switch from stratified-charge mode to the homogeneous-charge mode in the GDI engine during very demanding conditions allows the GDI vehicle to provide the needed power without significantly worsening the emissions (Chan et al., 2014, 2013). The OC EF from the PFI engine was more-sensitive to the cycles, similar to what has been observed elsewhere (He et al., 2018). Comparing GDI + GPF to GDI, OC decreased significantly with the addition of the GPF in the US06 cycle because some of the OC was likely in the particle phase and thereby captured by the GPF. For the FTP-72 drive cycles, there was a increase in OC emissions when using a GPF. A previous study has suggested that this could be a result of small and limited soot regeneration in the GPF (Chan et al., 2016). Such an increase in emissions is likely to be compensated partly by the decrease in emissions during cold-start mode, and therefore is not that evident during the FTP-75 drive cycle (Chan et al., 2013).

The EC EFs of the GDI vehicle during the FTP-75, FTP-72 and US06 cycles were 14.1, 65.9 and 6.2 times higher than that of PFI vehicle, respectively. The effect of the GPF on the GDI emissions was significant, decreasing EC by at least 98% in each test cycle, consistent with all previous measurements (Chan et al., 2014, 2013). Similar results of up to a 99% decrease in soot emissions was observed for other GDI vehicles installed with a GPF (McCaffery et al., 2020). Consistent with this, Jang et al. (2018) reported that particle numbers also decreased, but the extent varied by test cycle.

Unlike OC, for which there are relatively few publications comparing GDI and PFI engines, more has been reported for EC or BC. Zimmerman et al. (2016b) reviewed the literature and found that the mean BC emission level from GDI vehicles (around 1.5 mg mile^–1) was four times more than that of PFI vehicles (around 0.3 mg mile^–1). Chan et al. (2014) previously tested (FTP-75) the same two vehicles studied in this paper with a focus on in situ black carbon (BC) measurements and observed that the ratios of BC from GDI versus PFI vehicles were in the range of 7.8–18 at 22°C. Saliba et al. (2017) found that the EC ratio of the GDI versus PFI engine was 4.8 and 3.1 for ultra-low-emission vehicles and super ultra-low-emission vehicles, respectively.

Different injection and combustion conditions for GDI and PFI engines are known to lead to changes in OC and EC emissions. In GDI engines, liquid fuel accumulation on the piston and cylinder after injection (Maricq et al., 2013) causes a less uniform mixture of air and fuel compared to PFI vehicles during cold start (e.g., FTP-75 cycle) (Chan et al., 2014) causing more emissions for both EC and OC. Different injection and combustion situations also occur for aggressive driving cycles (e.g., US06). Specifically, for GDI vehicles extra load is needed during acceleration in the test cycles and therefore the engine operation mode changes from homogeneous-charge to stratified-charge, causing a heterogeneous air-fuel mixture (Zhao et al., 1999; Barone et al., 2012). For PFI vehicles, enrichment of the fuel mixture under high load leads to incomplete vaporization of fuel (Chan et al., 2014, 2013).

 
3.3 Characteristics of Vehicle Semivolatile and Particle Phase OC

While the differences in EC emissions among engine configurations were as expected, the OC emission differences were more complex. A more-detailed comparison of the OC emissions detected on the QBT and on the Q filters after subtracting the OC on the QBT (Q-QBT) are presented in Figs. 2(a–c). OC on the QBT from the GDI engine, which likely represents gas phase SVOC emissions and particle evaporation, was 70-80% lower than that of the PFI engine for all three driving cycles. In contrast, OC derived from Q-QBT, which likely corresponds to particle phase, was a factor of 5–6 higher for GDI vs. PFI during the FTP-75 and FTP-72 cycles, but much lower, by 85%, during US06 conditions.

Fig. 2. OC emission factors from backup and bare quartz filters, and their ratio comparison with other types of samples. The figure (a), (b) and (c) shows OC emission factors obtained by Q and Q- QBT from three vehicle test settings (note the different y-axis scales). The (d) is comparison of OC QBT/Q in this study with references of different ambient sampling locations. The references reported measure OC using a TOR method with maximum inert mode temperature of 550°C (Cheng et al., 2010; Chen et al., 2010; Zhu et al., 2012; Cheng et al., 2009) and 580°C (Watson et al., 2009).

There are two main sources of organic compounds from gasoline vehicle emissions. One is incomplete volatilized fuel droplets, which forms at the combustion temperature boundary layer, and has a greater proportion in the gas phase (Jiang et al., 2018), implying it will predominantly be seen on QBT. The other is incomplete combustion of fuel, which occurs when an inhomogeneous mixture of fuel and air is pyrolyzed during combustion (Chan et al., 2014), which is more likely to form particle phase compounds (e.g., PAHs) (Miersch et al., 2019) and thus be detected on Q. The results in Fig. 2(d) suggest that the OC emissions from the PFI engine were more volatile than those from the GDI engine. This was clearly seen in the results of the most volatile OC fraction on QBT (OC1 by the IMPROVE method, which has the lowest heating temperature for OC1 among the protocols) (Table S5). The OC1 on QBT was 30.4 and 47.8 µg km^–1 for PFI vehicles during the FTP-75 and FTP-72 cycles, which was 31 and 34 times higher than that of GDI vehicles, respectively (Table S5). The THC measurements (Table S2) show that the greater amounts of volatile/gas phase OC from PFI engines, captured in the quartz filter measurements (Fig. 2), extended into the VOC emissions. Specifically, THC emissions were 40% and 50% higher from the PFI engine during the FTP-75 and FTP-72 cycles, respectively. A similar trend of higher THC concentrations from PFI engines was also observed in tests conducted for LEV1 and LEV2 strategies (Saliba et al., 2017). This behavior for PFI indicates that the OC was more-likely to be due to volatilized fuel, thus distributing more in the gas phase (collected on QBT).

The higher Q-QBT associated with the cold-start FTP-75 cycle of the GDI engine could be due to formation of pyrolyzed particles caused by the ‘wall-effect’ of liquid fuel accumulating on the wall of the cylinder (Chan et al., 2014; Maricq et al., 2013). During the aggressive test cycle (US06) the OC1 measured by the IMPROVE method on QBT from the PFI engine was 65% higher than the GDI vehicle, which could be a result of excessive fuel being injected in the PFI engine than in the GDI engine (Jiang et al., 2018). This explanation is also consistent with the larger EC EFs for GDI vs. PFI discussed above.

Comparing GDI and GDI+GPF, more OC on the QBT was observed when the GPF was added during FTP-75 and FTP-72 cycles (Fig. 2). Most of the increase on the QBT came from the more-volatile OC1 fraction; ~67 times higher after GPF installation (Table S5). A possible explanation is reactions on the surface of the GPF which converted some of the most volatile gas phase OC, including VOCs (i.e., THC), to less volatile organics that can then be adsorbed on the QBT. Given the relatively large amount of hydrocarbon emissions, conversion of a small fraction could have large impacts on the OC available to adsorb on the QBT. This GPF-induced production of SVOC and possibly particle phase OC is consistent with several other studies (Zhang et al., 2016; Robinson et al., 2007). Munoz et al. (2018) also reported higher PAH emissions in GDI exhaust following a GPF. Clearly, the influence of the GPF on vehicle OC emissions is complex and needs to be better understood, although it was highly effective for reducing EC and non-volatile OC. Continuous GPF regeneration adds further complexity, although the majority of the EC and OC collected is converted to CO₂ or CO given the availability of oxygen (Munoz et al., 2018).

Fig. 2(d) also shows the proportion of OC on QBT versus Q in this study compared to similar measurements from heavily impacted locations, such as near-road and tunnel studies, to regional ambient air. The QBT/Q values in our emission measurements are significantly higher than studies in a tunnel, at roadside and ambient environments (Cheng et al., 2010; Chen et al., 2010; Zhu et al., 2012; Cheng et al., 2009), implying a greater proportion of the more volatile OC compounds in the fresh exhaust. Under the field study conditions shown, the reduction in the proportion of gas phase OC relative to the more non-volatile particle OC could be due to cooling and condensation on particles and other surfaces and/or rapid reaction forming less volatile particle OC (i.e., SOA) (Zhang et al., 2016). Zimmerman et al. (2016a) observed a rapid growth of nano particles from a GDI vehicle as its exhaust plume transported away from the road suggesting condensation of low volatility gas phase organic compounds.

Large amounts of gas phase OC emitted by vehicles have been reported by others. Zhao et al. (2016) measured the total intermediate volatility organic compounds (IVOC) and SVOC from gasoline vehicles and found that IVOC and SVOC collected on absorbent tubes contributed 47% and 53% of the total organics collected on the quartz filter, respectively. Li et al. (2016) found that in traffic tunnel and dynamometer tests the OC collected on a bare quartz filter consisted of only 12% low volatility OC, while 60–80% was SVOC. Lu et al. (2018) suggested that the distribution of particle phase OC, SVOC and IVOC is ultimately determined by the combination of the volatility distribution in the emissions and the ambient temperature environment. Our measurements clearly show that, for the conditions created in the CVS (T = 22°C), a large fraction of the overall OC consists of the more volatile compounds remaining in the gas phase.

In addition to complicating the measurement of actual particle OC emissions, the gas phase OC is potentially important to subsequent particle OC formation after emission through atmospheric transformations. Lu et al. (2018) measured IVOC in gasoline and diesel vehicle exhaust with an in situ gas chromatograph after the emitted particles were removed by a front filter, finding that the IVOC contributed about one third of total SOA yields in non-methane organic gases emissions. This suggested that IVOC was an important source of SOA formation in the atmosphere. Indeed, IVOC has been found to readily form SOA in smog chamber studies (Jathar et al., 2014). Ultimately this implies that after emission from the tailpipe the volatility of the gas phase OC decreases and particle OC increases, including SOA formed through oxidation of IVOC (Jathar et al., 2014; Zhang et al., 2016), consistent with the ratios shown in the Fig. 2(d).

 
4 CONCLUSIONS AND IMPLICATIONS

Carbonaceous particle samples from three vehicle settings (GDI, GDI + GPF, and PFI) were collected under different cycles (FTP-75, FTP-72 and US06) and measured with three protocols (IMPROVE, NIOSH and ECT9). Comparing the protocols, the IMPROVE and NIOSH gave similar TC, while the ECT9 resulted in higher TC. The IMPROVE protocol determined OC to be the lowest and EC to be the highest among the protocols, probably due to incomplete OC evaporation at relatively low inert mode peak temperature.

The OC EFs for the three engine conditions during the FTP-75 and FTP-72 drive cycles were comparable and lower than that of US06 drive cycle. The OC EF for PFI vehicle during US06 cycle increased to 3581 µg C km^–1, which was 11 times higher than that of FTP-72 cycle with the same vehicle and 1.5 times higher than GDI vehicle at the same cycle. The EC EFs of the GDI vehicle were 6.2 to 14.1 times higher than PFI vehicle, and the EC emissions could be reduced by at least 98% in each test cycle by applying GPF.

OC on the QBT from GDI vehicle emissions was 70-80% lower than that of the PFI vehicle, and this value for the most volatile fraction OC1 could even reach 97% during FTP-72 cycle, indicating higher volatility of PFI vehicle emissions. Generally, the QBT/Q value in our vehicle emissions measurements were much higher than other roadside or ambient air studies, suggesting more volatile OC compounds in the fresh vehicle exhaust. More OC on the QBT was observed after the GPF applied on the GDI vehicle during FTP-75 and FTP-72 cycles, and the OC1 also increased around 67 times, implying reactions on the surface of GPF could probably produce new SVOC.

The particle and gas phase organic compounds from both GDI and PFI engines under various driving cycles requires further study in order to quantify their impact on environmental pollution. GDI vehicles are believed to have more PM emissions than PFI vehicles, however, this behavior cannot be generalized. Our results indicate that the PFI vehicle can cause larger OC emissions under aggressive cycles with excessive fuel injection. The effect of GPFs on particle removal also needs to be more-comprehensively evaluated, since it increased the SVOC emissions though particle emissions were decreased. Our study suggests oxidation and condensation of gas phase organic compounds occurs as the exhaust passes through the GPF. This enhanced effect of GPF on SVOC could also induce more SOA formation. With wider GPF application in coming years, further studies on GPF performance and their effects on SOA are needed.

 
ACKNOWLEDGEMENTS

The authors would like to acknowledge the contribution of the Emission Research and Measurement Section (ERMS) staff for their assistance in conducting this vehicle emissions research project. This work was sponsored by the Science and Technology Planning Project of Jiangsu Provincial Environmental Protection Group (JSEP-TZ-2021-2003-RE and JSEP-TZ-2021-2002-RE) and Program of Energy Research and Development from Natural Resources Canada (PERD ECOII program).