Marked impacts of transient conditions on potential secondary organic aerosol production during rapid oxidation of gasoline exhausts

Jun 08, 2023

npj Climate and Atmospheric Science volume 6, Article number: 59 (2023) Cite this article

207 Accesses

1 Altmetric

Metrics details

Vehicle emission is a major source of atmospheric secondary organic aerosols (SOA). Driving condition is a critical influencing factor for vehicular SOA production, but few studies have revealed the dependence on rapid-changing real-world driving conditions. Here, a fast-response oxidation flow reactor system is developed and deployed to quantify the SOA formation potential under transient driving conditions. Results show that the SOA production factor varies by orders of magnitude, e.g., 20–1500 mg kg-fuel−1 and 12–155 mg kg-fuel−1 for China V and China VI vehicles, respectively. High speed, acceleration, and deceleration are found to considerably promote SOA production due to higher organic gaseous emissions caused by unburned fuel emission or incomplete combustion. In addition, China VI vehicles significantly reduce SOA formation potential, yield, and acceleration and deceleration peaks. Our study provides experimental insight and parameterization into vehicular SOA formation under transient driving conditions, which would benefit high time-resolved SOA simulations in the urban atmosphere.

Vehicle emission contributes a significant share of atmospheric particulate matter (PM), affecting air visibility, human health, and global climate1,2,3. Vehicles emit both primary aerosols containing black carbon and primary organic aerosol (POA), and organic gaseous compounds, such as volatile organic compounds (VOCs) and semi/intermediate VOCs (S/IVOCs), which can be converted into secondary organic aerosols (SOA) through atmospheric oxidation4,5,6. Recent measurements have shown that the SOA formation from gasoline vehicle exhaust in urban areas has been a dominant contributor to organic aerosol mass, greatly outweighing the contribution of POA7,8.

Estimating vehicle exhaust contribution to the atmospheric SOA typically involves identified precursors such as single-ring aromatics, isoprene, and n-alkanes9. However, these VOCs species only explain a relatively small fraction of the measured SOA mass in previous laboratory studies10,11. A large SOA formation is contributed by the unresolved complex mixture of organic vapors in the vehicle exhaust12,13,14. In addition, the parameterization or modeling studies of vehicular SOA production lack reports15. The contribution of vehicle emissions to the atmospheric SOA burden remains uncertain16,17.

Several factors influence the SOA formation from vehicle exhaust, such as fuel types, engine technology, emission standards, and operating conditions. Among all the influencing factors, operating conditions have been reported to play a crucial role in vehicular SOA production since the organic gaseous emission varies dramatically with vehicle driving changes18. For example, an in-situ photochemical simulation revealed that the SOA production of gasoline vehicle exhaust under the idling condition was about 20 times higher than that of cruising driving19. Also, a recent online measurement of non-methane VOCs in exhaust emissions showed that the composition of organic vapors changed rapidly with the transient driving condition20. Thus, rapidly changing driving conditions of vehicles may lead to a wide variation in SOA production during short timescales. However, most previous studies focused on the influences of different cruising conditions or driving cycles, instead of transient conditions, on SOA production from vehicle exhaust19,21,22,23. Few previous research has successfully quantified the impacts of the transient conditions, partially because the experimental simulation of the rapid oxidation of vehicle exhaust is challenging.

Oxidation flow reactor (OFR) simulation, which can obtain the SOA potential within several minutes under a high level of oxidants (specifically the hydroxyl radical, OH), provides an opportunity to study the rapidly reacting SOA precursors24,25. For example, a widely adopted flow reactor, the potential aerosol mass chamber (PAM), has been developed and used in photo-oxidation measurements. However, it is difficult for PAM to characterize the rapid gaseous precursor changes because of the broad residence time distribution of more than 100 s26,27. Although some recent studies have improved the time resolution of organic precursor oxidation by shortening the length of the OFR, the targeted and parametric evaluation of SOA production under transient driving conditions has not yet been quantified28,29.

Another influencing factor, emission standards, also dramatically regulate vehicular exhaust emission, consequently affecting the production of SOA. Recent reports revealed that the continuous tightening of emission standards facilitates the reduction of organic gas emissions from gasoline vehicles and the changing of chemical composition, which may lead to varying extents/rates of SOA production9,30,31. Nonetheless, the reports on the SOA level for different standard vehicles are insufficient, especially for the latest standard, e.g., China VI, limiting assessing the emission reduction of vehicle fleet effects on atmosphere improvement through the updates of vehicle emission standards.

In this study, we designed a fast-response laminar flow OFR reactor to simulate the transient SOA formation with driving conditions from vehicle exhaust. Then we quantify the impacts of transient driving conditions on SOA formation via chassis dynamometer tests under transient driving cycles. Vehicles with different emission standards, i.e., China IV, China V, and China VI (the newest emission standard in China, equal to Euro VI), are also investigated to evaluate the SOA production from different vehicle types. At last, a parameterization is established for predicting vehicular SOA production under real-world driving conditions.

The time series of driving speed, primary emissions, and SOA production during two typical Worldwide Harmonized Light Vehicles Test Cycle (WLTC) tests for China V and China VI vehicles, respectively, are shown in Fig. 1.

a, b Speed profile and CO2 emission, (c, d) primary emissions of THC and CO, (e, f) size distribution of seed particles with SA, (g, h) SOA concentration and its ratio to CO, and (i, j) SOA production factor (PF). The left and right panels denote the results of China V and China VI vehicles, respectively.

During cycle tests, CO2 concentration changes widely and sharply with the speed variation, indicating the transient temporal variations of fuel consumption rates (Fig. 1a, b). Even though it is a hot-start cycle, a high hydrocarbon emission peak is observed at the starting state of the China V vehicle (Fig. 1c). In contrast, as an indicator for incomplete combustion extent and conversion efficiency on the catalyst, CO emission presents a small sharp peak during the start process, showing a different temporal variation from THC emission. This difference in CO and THC in the starting stage suggests that incomplete combustion is a partial driver of the THC peak, while a large share of THC emission likely attributes to unburned fuel exhaust32,33. During high-speed region, CO exhibits a marked elevation for both China V and China VI vehicles and is strongly related to THC emission (Fig. 1c, d), indicating that incomplete combustion dominates the organic gaseous emissions during high-speed driving.

After exposure to the high-level OH radicals inside the reactor, gaseous precursors of the vehicle exhaust are rapidly oxidized into secondary aerosol (SA, including SOA and inorganic composition, Supplementary Fig. 1). As shown in Fig. 1e, f, with the transient changes of driving conditions, a series of peaks in number concentration and diameter variation are generated, indicating the rapid nucleation and condensation inside the reactor. Significant SOA formation pulses are observed during the cycle test, with a wide range of two orders of magnitude for the China V vehicle. Similar temporal variations in SOA formation are also observed for the China VI vehicle, even though they show much lower concentrations than those of China V vehicle (Fig. 1g, h). Notably, the SOA production factors (PFs) exhibit a wide range, from 20–1500 mg kg-fuel−1 to 12–155 mg kg-fuel−1 for China V and China VI vehicles, respectively (Fig. 1i, j). Besides, both tests present two sets of peaks in the start-up and final high-speed stages during the cycles, accounting for nearly 70% of the total emissions throughout the entire cycle tests.

According to previous studies, the significant variation in the SOA formation from vehicle exhaust may be attributed to several factors, e.g., OH exposure, condensation sink (CS), and emission of precursors8,14,17. In this study, to reveal the effect of transient emission on SOA formation, we specially controlled the factors of OH exposure and CS factors.

During each test, the changes in primary emissions lead to a variation of OH oxidant reactants (generally defined as external OH reactivity, OHRext) and further affect the extent of oxidation. In the tests of China V and China VI vehicles, the OH exposure ranges are 2.5–10 × 1011 and 4.9–10.1 × 1011 molecule s cm−3 (Supplementary Fig. 2), respectively, equal to ~1.9–7.5 and 3.7–7.6 days of aging in ambient (assuming the OHambient = 1.5 × 106 molecule cm−3)34. Such levels of OH exposure are significantly higher than the reported values in the previous OFR aging experiments of vehicle exhaust, in which the SOA peak occurred within ~1.5 days10,23. Also, our OH gradient experiments under steady idling conditions show that SOA formation exhibits a "plateau" in the range of 1.2–8 OH-equivalent days (Supplementary Fig. 3). As a result, the OH radical concentration inside the Veh-OFR is sufficient, and its fluctuation unlikely results in the large variation in the SOA formation.

In the OFR system, low residence time inhibits complete condensation of SOA, especially when CS is small and partitioning to the particle phase is limited. As recently pointed out by Jathar et al. and Zhao et al., the effective SOA yield in vehicle exhaust varied by orders of magnitude with the variation of aerosol concentration inside the reactor during vehicle tests, because the losses of aged low-volatile species are negatively correlated with aerosol concentration inside the reactor26,31. In this study, a constant seed aerosol has been introduced into the reactor to provide a stable and sufficient CS, significantly reducing the sensitivity of SOA formation to CS, which has been verified by the modeling and gradient experiments (Supplementary Figs. 4–6).

Organic gases emission is concluded to be the dominant factor driving the SOA transient fluctuation when we exclude OH exposure and CS. Organic gases in vehicle exhausts consist of both fuel components (e.g., single-aromatics) and incomplete combustion products (e.g., short-chain alkanes and oxidized VOCs)35,36. Considering that CO only comes from incomplete combustion, comparisons between the temporal trends of SOA and SOA/CO can be used to indicate the sources of organic gases.

Upon the start of the China V vehicle test, the organic vapors, represented as THC, exhibit a large peak lasting for ~200 s, correspondingly resulting in marked peaks of SOA formation. A similar SOA peak is found in the China VI vehicle test. The observed SOA peaks are likely dominated by the unburned fuel emissions generated by the fuel-rich running during the test start regime, since the ratio of SOA/CO exhibits a significantly different trend with SOA variation (Fig. 1g, h)37.

During the high-speed stages, SOA and SOA PF for the China V vehicle significantly elevate to a higher level, while SOA/CO only undergoes a moderate increase. This could be ascribed to significantly increasing both incomplete combustion and unburned fuel exhaust during the high-load driving condition for the China V vehicle. In contrast, for the China VI vehicle, SOA/CO ratio and SOA have roughly the same temporal profile, implying that incomplete combustion dominates the contributor to the SOA formation. This indicates that the sources of organic gases varied both by transient driving conditions and control level (represented by emission standards).

Figure 2 presents the average SOA production and related ratios by emission standards. The average SOA production factors across WLTC cycle tests are 276 ± 131, 145 ± 79, and 41 ± 27 mg kg-fuel−1 (Fig. 2a), or 18 ± 11, 8 ± 4, and 2 ± 1 mg km-veh−1 for China IV, China V, and China VI vehicles, respectively. A significant reduction trend is observed in emission standard updating, indicating that replacing older vehicles with newer ones significantly reduces the SOA level in urban environments. However, the ratio of SOA/POA shows an unexpected upward trend, especially in the update from China V to China VI (Fig. 2b). This suggests that the POA reduction far exceeds that of SOA due to the upgrading of engine technology and after-treatments (e.g., installation of gasoline particulate filters), highlighting the importance of organic precursor gases control for future vehicles.

The results, which are classified by vehicle emission standards, obtained from all Veh-OFR experiments of (a) SOA production, (b) the ratios of SOA to POA, (c) the ratios of SOA to THC, and (d) the ratios of SOA to CO. The green shading (c) indicates the SOA yield range of m-xylene under different particle loading reported by Peng et al. 38. d The red dotted line represents the SOA/CO ratio of the Pittsburgh in-situ tunnel study reported by Tkacik et al. 45. d The blue shading indicates the SOA/CO ratios of the roadside measurements in Carolina (Saha et al. 46) and Hong Kong (Liu et al. 47). d The red shading indicates the SOA/CO ratios of the in-situ ambient OFR measurements in the urban areas of Beijing (Liu et al. 25), Los Angeles (Ortega et al. 43), and Guangzhou (Hu et al. 44). The boxes represent the 25th and 75th percentiles with a centerline and a blue dot being the median and mean values, respectively. The whiskers represent the 5th and 95th percentiles.

The comparison of the vehicle-related SOA potential measurements between this study with other studies are shown in Supplementary Fig. 7. It shows that the SOA production factors measured in our experiments are comparable with other dynamometer studies. Notably, the comparison further reveals that driving conditions and emission standards are important drivers to the variations.

The effective SOA yield of organic precursors in the vehicle exhaust, represented as the ratio of SOA/THC, ranging from 0.2 to 0.4. The SOA yield of China V vehicle exhaust is the highest among the emission standards, while the China VI vehicle is the lowest. This trend is different from that reported by Zhao et al., which showed that the SOA yield varied less across the different emission standards31. Such discrepancy may be caused by the experimental conditions, e.g., seed aerosol control. Meanwhile, the measured VOCs profiles (Supplementary Fig. 8) show that the proportion of aromatics in the China V vehicle exhaust is the highest, followed by China IV and China VI vehicles, partly explaining the SOA yield distribution. Unexpectedly, the effective SOA yield of the bulk exhaust is roughly equivalent to the SOA yield range of m-xylene, suggesting relatively high SOA yield in our experimental system with seed particles38.

The estimated SOA is calculated based on VOC emission profiles and reference yields39,40. The result shows that the estimated SOA using identified VOCs species accounts for 21%, 27%, and 34% of the measured SOA for China IV, China V, and China VI vehicles, respectively (Supplementary Fig. 9). This suggests that S/IVOCs and other organic vapors likely contribute a large proportion of SOA, similar to the conclusions in previous studies10,41,42. Meanwhile, we find that the proportion of SOA caused by S/IVOCs seems to decline with the updates in emission standards. Additionally, the concentration ratio of VOCs to THC is found to be on an upward trend with emission standards (Supplementary Fig. 10). This is different from the study of Qi et al., which reported that the proportion of VOCs in THC tended to decrease with the updates in vehicular emission standards9.

Many ambient measurements use SOA/CO as an indicator of the evolution of primary organic gaseous emission25,43,44. The measured variations in SOA/CO ratio in this study (nearly 270 μg m−3 ppm−1) show no statistically significant difference in the emission standards (Fig. 2d). This may be due to the synergistic emission reduction effect of organic vapors and CO in vehicle exhaust control. In addition, SOA/CO ratios obtained from dynamometer tests of this study are ~3 times higher than that in tunnel measurement ( ~ 90 μg m−3 ppm−1) reported by the previous research45. Also, the values are several times higher than those values in roadside measurements (30–60 μg m−3 ppm−1)46,47 and urban ambient (15–30 μg m−3 ppm−1)25,43,44. Overall, a marked declining trend of SOA/CO ratios is found among the dynamometer tests, tunnel, roadside, and urban ambient environments. Several reasons may cause this gradient variation from emission source to ambient, one of which is that the losses of organic vapors (or aged vapors) during the atmospheric dispersion may be more significant than CO.

The transient SOA formation measurements in this study provide us an excellent opportunity to explore the linkage between SOA potential and driving conditions, e.g., speed and acceleration, which have never been well-constrained.

Figure 3 presents the concentration, PF, and some ratios involving SOA in different speed and acceleration bins. The SOA concentration increases nonlinearly with speed and presents a marked peak after reaching a critical speed bin (Fig. 3a–c). For the China IV vehicle, the higher SOA formation generally occurs at the speed bins above 60 km h−1, and both acceleration and deceleration behaviors produce high SOA values. By comparison, the SOA peaks of the China V vehicle generally occur during driving conditions above 80 km h−1, while the China VI vehicle only produces significant SOA peaks at the highest speed bins above 100 km h−1. The difference in SOA production and shift in the critical speed reflects the improvement of the emission control in updating emission standards.

a–c The SOA concentrations in the reactor, (d–f) SOA productions, (g–i) SOA-to-THC ratios, and (j–l) SOA-to-CO ratios measured from vehicle exhaust with China IV, China V, and China VI emission standards under different driving conditions. The speed (km h−1) is divided into [0, 10), [10, 20), [20, 30), [30, 40), [40, 50), [60, 70), [70, 80), [80, 90), [90, 100), [100, 110), and [110, 120) bins. The acceleration (m s−2) is divided into [<−1.5), [−1.5, −1), [−1, −0.5), [−0.5, 0), [0, 0.5), [0.5, 1), [1, 1.5), and [>1.5) bins.

In addition to speed bins, acceleration driving conditions are also found to impact the SOA formation significantly. Elevated SOA concentrations are constantly found in the acceleration processes, especially in high-speed bins (Fig. 3a, b). Through online VOCs measurement, Marques et al. found that incomplete combustion product species, e.g., alkane and cycloalkane fragments, were abundant during the acceleration process20. Therefore, the SOA spikes in the acceleration processes are likely generated by incomplete combustion products.

The SOA PF (Fig. 3d–f), presented as the SOA-to-CO2 ratio, shows an increasing trend with speed. Besides, different from the SOA concentrations, the SOA PF peaks frequently occur during the deceleration conditions, indicating a delayed emission in the exhaust of organic precursors relative to CO2 emissions. During deceleration driving, the engine combustion immediately stops, leaving unburned fuel components in the tailpipe exhaust48. In addition, due to the inertia of the engine rotation, negative pressure is formed inside the cylinder and fuel circuit, enhancing the evaporation of residual fuel49. Both mechanisms emit large amounts of THC and generate SOA production peaks. Therefore, the acceleration and deceleration processes have different mechanisms for generating organic gaseous precursors and SOA formation. For China VI vehicles, the SOA PF peaks rarely occur during acceleration and deceleration driving conditions, indicating improved engine technology and after-treatment. Overall, the impacts of driving conditions on SOA production tend to weaken with the update of emission standards.

Figure 3g–i shows the distributions of SOA to THC ratio upon the driving conditions, which reflect the SOA yield of vehicle exhaust. For the China IV and China V vehicles, the SOA/THC ratios vary from 0.1 to 0.6 with the driving condition. In particular, the SOA/THC ratio peaks appear randomly in the speed and acceleration bins, indicating that the organic precursor compositions varied with transient driving conditions. For the China VI vehicle, a strong correlation (R2 = 0.79) is found between THC and SOA (Supplementary Fig. 11), suggesting that the SOA production tends to be driven by the variation of THC concentration rather than composition for the latest emission standard vehicles.

A wide range of SOA/CO ratios under the transient driving conditions is observed among the tests (Fig. 3j–l). Notably, the SOA/CO ratios in low-speed regimes are significantly higher than that in high-speed bins for all vehicle tests. This further proves that the unburned fuel emission in the low-speed stage is an important diver for SOA potential, while incomplete combustion dominates the SOA formation during the high-speed stages50,51.

To further identify the impacts of transient driving conditions on SOA production, the cruise driving tests are conducted to compare with the WLTC tests at the same speed bins. It was expected that the SOA formation potential under transient driving conditions was higher than that of cruising driving, which represents a steady-state operation. However, our results show that SOA PF under some cruising driving conditions, e.g., idling and 120 km h−1 cruising, is not lower than those obtained from transient cycle tests and exhibits a large variation in speed (Fig. 4a–c). This implies that the evaluation of SOA potential under cruising driving has a limited representation for real-world driving exhaust.

Comparison of (a–c) SOA productions and (d–f) the SOA/CO ratios under cruising driving conditions with those under WLTC conditions. The cruising driving test lasts 10–15 min for each speed. The stepped blue line represents the mean value of WLTC cycle at the same speed bins.

Interestingly, the variation of SOA/CO ratios in cruising tests has a similar trend with transient test (Fig. 4d–f), showing a decreased trend with driving speed. This indicates that the contribution of incomplete combustion to SOA potential tends to increase with speed. Cross et al. reported that the emissions of incomplete combustion products, e.g., oxygenated IVOCs, highly increased due to the higher temperatures and pressures under high-load engine operation50. Such conclusion may explain the experimental result of Wang et al., which shows that the SOA PF under the idling of vehicles is much higher than that of 50 km h−1 cruising19. It is probably because the unburned fuel components dominate the exhaust at idle state.

The current work established a fast SOA formation system and successfully deployed it to quantify the SOA formation potential under transient driving conditions. The results reveal the marked impacts of transient driving conditions on SOA production with orders of magnitude variation. Factors, i.e., high speed, acceleration, and deceleration, are identified as driving the high values. Particularly, we found that the SOA peaks in different periods are mainly because of unburned fuel emission and incomplete combustion. For example, unburned fuel emission dominates SOA production during low-speed driving. Moreover, with emission standards updating, such impacts caused by driving conditions tend to weaken.

The considerable differences in SOA production by driving conditions and emission standards should be accounted for when assessing the SOA contribution of vehicle exhausts in the real world. To better evaluate SOA production under real-world conditions, we introduce a parameter of vehicle-specific power (VSP) to quantify the relationship between SOA production and driving conditions. As shown in Fig. 5, the SOA production rate shows a nonlinearly monotonic increase with VSP, with the sensitivity varying with emission standards. Such parameterization could be easily adopted by typical vehicular emission models, e.g., MOVES and IVE models, providing useful information for the "bottom-up" high-time emission inventories.

The production rate (g s−1) presents a function of vehicle-specific power (VSP, kW ton−1). The results are classified into different vehicle emission standards, i.e., (a) China IV, (b) China V, and (c) China VI. The boxes represent the 25th and 75th percentiles with a centerline and a blue dot being the median and mean values, respectively. The whiskers represent the 5th and 95th percentiles.

The OFR experiments generally present the maximum SOA formation from vehicle exhaust. It's worth mentioning that several extreme conditions were set to achieve the high time resolution of SOA formation, such as high OH exposure and CS. In addition, this study focuses on the OH pathway of gas-phase reaction. Other pathways, e.g., NO3 radical and heterogeneous reaction, are not included. In the real-world atmosphere, the chemical processes of SOA formation are much more complex. Nevertheless, this work provides a new insight into vehicular SOA formation under transient driving conditions, which would benefit high time-resolved SOA simulations in the urban atmosphere52.

To study the high time-resolved SOA forming, we designed a new reactor (hereafter referred to as Veh-OFR) to expose the sampled diluted vehicle exhaust to high levels of oxidants. Veh-OFR was a 6.8 L vertical quartz glass cylindrical tube (98 cm long and 9.4 cm internal diameter). The airflow inside Veh-OFR included sheath flow and sample flow (Supplementary Fig. 12). The sample flow consisted of the seed aerosol and diluted exhaust, while the sheath flow mixed the ozone and humid air. Veh-OFR was a 254-type oxidation flow reactor53, which means that OH radicals were produced from the photolysis of the ozone at 254 nm UV radiation. The total flow rate through the reactor was 15.0 L min–1 with a median residence time of 37 s (Supplementary Fig. 13).

During the photochemical experiments, isokinetic injection of sample flow and sheath flow was achieved to ensure the laminar state of the airflow inside the reactor. Such a design may favor shortening the timescale of physical dispersion inside the reactor. Compared to the reported reactors, Veh-OFR enhanced the productivity of OH radicals, which benefited shortening the timescale of the gas-phase oxidation process54. In addition, a constant airflow with seed aerosols was continuously introduced into the reactor during the photo-oxidation experiments. This significantly affected the gas-particle partitioning and shortened the timescale of gas-particle equilibration time55,56. Through the above-mentioned optimized processes, the time resolution of SOA formation inside the Veh-OFR achieved 15 s, verified by the transient pulse experiments (Supplementary Figs. 14 and 15).

Detailed information on the fast response flow reactor for photochemical oxidation is shown in Supplementary Note 1.

During the vehicle exhaust tests, the sample air consisted of considerable OHRext, e.g., VOCs and NO. The real OH exposure was likely to be less than the initial productivity of the reactor57. Here, the real-time OH exposure during vehicle tests was quantified using the method reported by Li et al.:58

where R represents the ratio of input and output ozone concentration; Res denotes the residence time of the OFR reactor; \({{In}}_{{O}_{3}}\) denotes the input ozone concentration; OHRext denotes the sum of external OH activities, which are calculated as follows:

where OHRi denotes the external OH activity of species i; Ci denotes the concentration of species i; ki-OH denotes the reaction rate constant of species i with OH radical.

Ideally, if the composition of SA at the outlet of the reactor was detected instantaneously, the real-time SOA would be obtained. However, current instruments for aerosol chemical composition measurement (e.g., AMS) could not achieve a high time resolution of several seconds59.

During the photochemical aging of vehicle exhaust, SA mainly consisted of ammonium nitrate and OA. Therefore, the SOA concentration could be obtained through the difference between the measured SA and calculated ammonium nitrate. The parameters for the calculation of ammonium nitrate formation were obtained by sensitive experiments (Supplementary Figs. 17 and 18). It should be mentioned that ammonium aerosols could be formed through the oxidation of NOx and NH3 in the exhaust as a function of OH exposure. The concentration of SOA is calculated as follows:

where CSA denotes the measured SA concentration (μg m−3), CNOx and CNH3 denote the gaseous concentrations (μg m−3) of NOx and NH3 in the reactor, respectively; y1 and y2 denote the conversion yields of NOx and NH3 to secondary aerosols, respectively, relating to the NH3 level and the OH exposure inside the reactor:

This SOA calculation method was verified by the ratio of OA/NaCl (seed composition) in the offline filter samples and the concentration ratio of calculated SOA to seed aerosol (Supplementary Fig. 19).

The schematic system of the vehicle dynamometer test combined with in-situ OFR photochemical simulation is shown in Supplementary Fig. 11.

Six light-duty in-use vehicles with different emission standards (Supplementary Table 1), i.e., China IV, China V, and China VI, were selected for the chassis dynamometer tests (48 inch four-wheel, AVL, Austria). The test fuel was E10 fuel (ethanol volume ratio of 10%, v/v). Multiple test cycles, i.e., WLTC and cruising driving, were used to simulate different driving conditions. WLTC cycle was an aggressive cycle with rapid accelerations, start-stop, and high-speed operations. The cruising driving conditions, i.e., 0, 30, 60, 90, and 120 km h−1 speeds, were selected for testing, with each speed test lasting for 15 min. These tests were all hot-started operations, aiming to ensure consistency.

A partial flow dilution sampling system (DI-1000, Dekati) with a dilution ratio of 8 was used to sample the tailpipe exhaust into the Veh-OFR. The dilution air was supplied by a zero air generator (TH-2007A, Tianhong), removing the hydrocarbons through activated carbon and a heated oven.

The input ozone (O3) concentration of Veh-OFR was changed incrementally by the voltage adjustment of an ozone generator. During photochemical experiments, relative humidity was controlled within the range of 35–40%. The temperature of the reactor environment was kept at 25 ± 2 °C through a large load cooling fan. The reactor would be flushed with a 40 L min−1 zero air flow for 10 min before each test cycle.

A significant characteristic of this study was the addition of seed aerosol into the OFR system. The sampled exhaust air was mixed with a constant seed aerosol flow to provide enough condensation sink.

The primary emissions, including CO, CO2, NO, NO2, and total hydrocarbons (THC), and the exhaust volume flow were monitored continuously throughout a system of portable emission measurement system with a resolution of 1 s (model 493, AVL). O3 was determined by a UV photometric analyzer (model 49i, Thermo). NH3 was measured by an infrared analyzer with cavity ring-down spectroscopy technology (model G2103, Picarro).

The seed aerosol flow was generated by an aerosol atomizer (model 3076, TSI) with NaCl solution. The primary and secondary aerosols were measured by a high-resolution engine exhaust particle sizer (EEPS, model 3090, TSI), which was a device for measuring electrical mobility diameter (6–530 nm) with a resolution of 1 s. Meanwhile, the outlet particle of the reactor was measured by a scanning mobility particle sizer with a resolution of 2 min (SMPS, model 3938, TSI). The EEPS data was calibrated in real-time with SMPS data (Supplementary Fig. 20).

Offline VOCs were sampled using a stainless steel tank (3.2 L, Enteck) followed by an ozone scrubber before and after photochemical aging, then 117 species were detected by a Gas Chromatography-Mass Selective detector.

The fuel-based production factor (PF) of SOA was calculated as follows:

where [SOA], [CO2], and [CO] are the concentrations of SOA, CO2, and CO in μg m−3, respectively. MWCO2, MWCO, and MWC are the molecular weights of CO2, CO, and carbon, respectively. Cf denotes the carbon mass fraction of fuel, adopted to be 0.8610,60.

VSP denotes the driving power per unit weight (kW ton−1), which accounts for speed, acceleration, rolling resistance, and aerodynamic drag61,62. For a typical light-duty vehicle, VSP is

where v is vehicle speed (km h−1); a is vehicle acceleration (km h−1 s−1); r denotes road grade (%). In this study, VSP is used to quantify the relationship between the SOA potential with driving conditions.

The datasets associated with the current study are available from the corresponding author ([email protected]) on reasonable request.

Peng, J. et al. Markedly enhanced absorption and direct radiative forcing of black carbon under polluted urban environments. Proc. Natl Acad. Sci. USA 113, 4266–4271 (2016).

Article Google Scholar

Long, X. et al. The nature and oxidative reactivity of urban magnetic nanoparticle dust provide new insights into potential neurotoxicity studies. Environ. Sci. Technol. 54, 10599–11060 (2020).

Article Google Scholar

Myhre, G. et al. Radiative forcing of the direct aerosol effect from AeroCom Phase II simulations. Atmos. Chem. Phys. 13, 1853–1877 (2013).

Article Google Scholar

Peng, J. et al. Ageing and hygroscopicity variation of black carbon particles in Beijing measured by a quasi-atmospheric aerosol evolution study (QUALITY) chamber. Atmos. Chem. Phys. 17, 10333–10348 (2017).

Article Google Scholar

Srivastava, D., Vu, T. V., Tong, S., Shi, Z. & Harrison, R. Formation of secondary organic aerosols from anthropogenic precursors in laboratory studies. npj Clim. Atmos. Sci. 5, 22 (2022).

Article Google Scholar

Sun, K. et al. Vehicle emissions as an important urban ammonia source in the United States and China. Environ. Sci. Technol. 51, 2472–2481 (2017).

Article Google Scholar

Shah, R. U. et al. Urban oxidation flow reactor measurements reveal significant secondary organic aerosol contributions from volatile emissions of emerging importance. Environ. Sci. Technol. 54, 714–725 (2020).

Article Google Scholar

Liao, K. et al. Secondary organic aerosol formation of fleet vehicle emissions in China: Potential seasonality of spatial distributions. Environ. Sci. Technol. 55, 7276–7286 (2021).

Article Google Scholar

Qi, L. J. et al. Primary organic gas emissions from gasoline vehicles in China: Factors, composition and trends. Environ. Pollut. 290, 117984 (2021).

Article Google Scholar

Du, Z. et al. Comparison of primary aerosol emission and secondary aerosol formation from gasoline direct injection and port fuel injection vehicles. Atmos. Chem. Phys. 18, 9011–9023 (2018).

Article Google Scholar

Zhao, Y. et al. Intermediate volatility organic compound emissions from on-road gasoline vehicles and small off-road gasoline engines. Environ. Sci. Technol. 50, 4554–4563 (2016).

Article Google Scholar

Tkacik, D. S., Presto, A. A., Donahue, N. M. & Robinson, A. L. Secondary organic aerosol formation from intermediate-volatility organic compounds: Cyclic, Linear, and Branched Alkanes. Environ. Sci. Technol. 46, 8773–8781 (2012).

Article Google Scholar

Gordon, T. D. et al. Secondary organic aerosol formation exceeds primary particulate matter emissions for light-duty gasoline vehicles. Atmos. Chem. Phys. 14, 4661–4678 (2014).

Article Google Scholar

Jathar, S. H. et al. Unspeciated organic emissions from combustion sources and their influence on the secondary organic aerosol budget in the United States. Proc. Natl Acad. Sci. USA 111, 10473–10478 (2014).

Article Google Scholar

Gentner, D. R. et al. Review of urban secondary organic aerosol formation from gasoline and diesel motor vehicle emissions. Environ. Sci. Technol. 51, 1074–1093 (2017).

Article Google Scholar

Hallquist, M. et al. The formation, properties and impact of secondary organic aerosol: current and emerging issues. Atmos. Chem. Phys. 9, 5155–5236 (2009).

Article Google Scholar

Zhao, Y. L., Tkacik, D. S., May, A. A., Donahue, N. M. & Robinson, A. L. Mobile sources are still an important source of secondary organic aerosol and fine particulate matter in the Los Angeles Region. Environ. Sci. Technol. 56, 15328–15336 (2022).

Article Google Scholar

Pieber, S. M. et al. Gas-phase composition and secondary organic aerosol formation from standard and particle filter-retrofitted gasoline direct injection vehicles investigated in a batch and flow reactor. Atmos. Chem. Phys. 18, 9929–9954 (2018).

Article Google Scholar

Wang, H. et al. Secondary aerosol formation from a Chinese gasoline vehicle: Impacts of fuel (E10, gasoline) and driving conditions (idling, cruising). Sci. Total Environ. 795, 148809 (2021).

Article Google Scholar

Marques, B. et al. Detailed speciation of non-methane volatile organic compounds in exhaust emissions from diesel and gasoline Euro 5 vehicles using online and offline measurements. Toxics 10, 184 (2022).

Article Google Scholar

Simonen, P. et al. Characterization of laboratory and real driving emissions of individual Euro 6 lightduty vehicles−fresh particles and secondary aerosol formation. Environ. Pollut. 255, 113175 (2019).

Article Google Scholar

Deng, W. et al. Primary particulate emissions and secondary organic aerosol (SOA) formation from idling diesel vehicle exhaust in China. Sci. Total Environ. 593, 462–469 (2017).

Article Google Scholar

Zhang, Y. et al. Comparison between idling and cruising gasoline vehicles in primary emissions and secondary organic aerosol formation during photochemical ageing. Sci. Total Environ. 722, 137934 (2020).

Article Google Scholar

Kang, E., Root, M. J., Toohey, D. W. & Brune, W. H. Introducing the concept of Potential Aerosol Mass (PAM). Atmos. Chem. Phys. 7, 5727–5744 (2007).

Article Google Scholar

Liu, J. et al. Secondary organic aerosol formation from ambient air at an urban site in Beijing: Effects of OH exposure and precursor concentrations. Environ. Sci. Technol. 52, 6834–6841 (2018).

Article Google Scholar

Jathar, S. H. et al. Linking load, fuel, and emission controls to photochemical production of secondary organic aerosol from a diesel engine. Environ. Sci. Technol. 51, 1377–1386 (2017).

Article Google Scholar

Palm, B. B. et al. In situ secondary organic aerosol formation from ambient pine forest air using an oxidation flow reactor. Atmos. Chem. Phys. 16, 2943–2970 (2016).

Article Google Scholar

Karjalainen, P. et al. Time-resolved characterization of primary particle emissions and secondary aerosol formation from a modern gasoline passenger car. Atmos. Chem. Phys. 16, 8559–8570 (2016).

Article Google Scholar

Simonen, P. et al. A new oxidation flow reactor for measuring secondary aerosol formation of rapidly changing emission sources. Atmos. Meas. Tech. 10, 1519–1537 (2017).

Article Google Scholar

Park, G. et al. Primary and secondary aerosols in small passenger vehicle emissions: Evaluation of engine technology, driving conditions, and regulatory standards. Environ. Pollut. 286, 117195 (2021).

Article Google Scholar

Zhao, Y. L., Lambe, A. T., Saleh, R., Saliba, G. & Robinson, A. L. Secondary organic aerosol production from gasoline vehicle exhaust: Effects of engine technology, cold start, and emission certification standard. Environ. Sci. Technol. 52, 1253–1261 (2018).

Article Google Scholar

Martinet, S. et al. Euro 6 unregulated pollutant characterization and statistical analysis of after-treatment device and driving-condition impact on recent passenger-car emissions. Environ. Sci. Technol. 51, 5847–5855 (2017).

Article Google Scholar

Saliba, G. et al. Comparison of Gasoline Direct-Injection (GDI) and Port Fuel Injection (PFI) Vehicle Emissions: Emission Certification Standards Cold-Start, Secondary Organic Aerosol Formation Potential, and Potential Climate Impacts. Environ. Sci. Technol. 51, 6542–6552 (2017).

Article Google Scholar

Peng, J. et al. Evolution of secondary inorganic and organic aerosols during transport: A case study at a regional receptor site. Environ. Pollut. 218, 794–803 (2016).

Article Google Scholar

Jathar, S. H. et al. Secondary organic aerosol formation from photo-oxidation of unburned fuel: Experimental results and implications for aerosol formation from combustion emissions. Environ. Sci. Technol. 47, 12886–12893 (2013).

Article Google Scholar

Drozd, G. T. et al. Time resolved measurements of speciated tailpipe emissions from motor vehicles: trends with emission control technology, cold start effects, and speciation. Environ. Sci. Technol. 50, 13592–13599 (2016).

Article Google Scholar

Zhang, Z. et al. Primary organic gas emissions in vehicle cold start events: Rates, compositions and temperature effects. J. Hazard. Mater. 435, 128979 (2022).

Article Google Scholar

Peng, W. H., Le, C., Porter, C. W. & Cocker, R. D. Variability in aromatic aerosol yields under very low NOx conditions at different HO2/RO2 regimes. Environ. Sci. Technol. 56, 750–760 (2022).

Article Google Scholar

Ma, P. K. et al. Evaluating the impact of new observational constraints on P-S/IVOC emissions, multi-generation oxidation, and chamber wall losses on SOA modeling for Los Angeles, CA. Atmos. Chem. Phys. 17, 9237–9259 (2017).

Article Google Scholar

Tsigaridis, K. et al. The AeroCom evaluation and intercomparison of organic aerosol in global models. Atmos. Chem. Phys. 14, 10845–10895 (2014).

Article Google Scholar

Peng, J. et al. Gasoline aromatics: a critical determinant of urban secondary organic aerosol formation. Atmos. Chem. Phys. 17, 10743–10752 (2017).

Article Google Scholar

Tang, R. et al. Measurement report: Distinct emissions and volatility distribution of intermediate-volatility organic compounds from on-road Chinese gasoline vehicles: implication of high secondary organic aerosol formation potential. Atmos. Chem. Phys. 21, 2569–2583 (2021).

Article Google Scholar

Ortega, A. M. et al. Real-time measurements of secondary organic aerosol formation and aging from ambient air in an oxidation flow reactor in the Los Angeles area. Atmos. Chem. Phys. 16, 7411–7433 (2016).

Article Google Scholar

Hu, W. W. et al. Oxidation flow reactor results in a Chinese megacity emphasize the important contribution of S/IVOCs to ambient SOA formation. Environ. Sci. Technol. 56, 6880–6893 (2022).

Article Google Scholar

Tkacik, D. S. et al. Secondary Organic Aerosol formation from in-use motor vehicle emissions using a potential aerosol mass reactor. Environ. Sci. Technol. 48, 11235–11242 (2014).

Article Google Scholar

Saha, P. K., Reece, S. M. & Grieshop, A. P. Seasonally varying secondary organic aerosol formation from in-situ oxidation of near-highway air. Environ. Sci. Technol. 52, 7192–7202 (2018).

Article Google Scholar

Liu, T. Y. et al. Secondary organic aerosol formation from urban roadside air in Hong Kong. Environ. Sci. Technol. 53, 3001–3009 (2019).

Article Google Scholar

Zhu, G. et al. Experimental study on combustion and emission characteristics of turbocharged gasoline direct injection (GDI) engine under cold start new European driving cycle (NEDC). Fuel 215, 272–284 (2018).

Article Google Scholar

Kouremenos, D., Rakopoulos, C., Yfantis, E. & Hountalas, D. An experimental investigation of fuel-injection-pressure and engine-speed effects on the performance and emission characteristics of a divided-chamber diesel engine. Int. J. Energy Res. 17, 315–326 (1993).

Article Google Scholar

Cross, S. E., Sappok, G. A., Wong, W. V. & Kroll, H. J. Load-dependent emission factors and chemical characteristics of IVOCs from a medium-duty diesel engine. Environ. Sci. Technol. 49, 13483–13491 (2015).

Article Google Scholar

Gentner, D. R. et al. Elucidating secondary organic aerosol from diesel and gasoline vehicles through detailed characterization of organic carbon emissions. Proc. Natl Acad. Sci. USA 109, 18318–18323 (2012).

Article Google Scholar

Shah, R. U. et al. Urban oxidation flow reactor measurements reveal significant secondary organic aerosol contributions from volatile emissions of emerging importance. Environ. Sci. Technol. 54, 714–725 (2020).

Article Google Scholar

Peng, Z. et al. HOx radical chemistry in oxidation flow reactors with low-pressure mercury lamps systematically examined by modeling. Atmos. Meas. Tech. 8, 4863–4890 (2015).

Article Google Scholar

Watne, Å. K. et al. Fresh and oxidized emissions from in-use transit buses running on diesel, biodiesel, and CNG. Environ. Sci. Technol. 52, 7720–7728 (2018).

Article Google Scholar

Zhang, X. et al. Influence of Vapor Wall Loss in Laboratory Chambers on Yields of Secondary Organic Aerosol. Proc. Natl Acad. Sci. USA 111, 5802–5807 (2014).

Article Google Scholar

Lambe, A. et al. Effect of oxidant concentration, exposure time, and seed particles on secondary organic aerosol chemical composition and yield. Atmos. Chem. Phys. 15, 3063–3075 (2015).

Article Google Scholar

Peng, Z. et al. Non-OH chemistry in oxidation flow reactors for the study of atmospheric chemistry systematically examined by modeling. Atmos. Chem. Phys. 16, 4283–4305 (2016).

Article Google Scholar

Li, R. et al. Modeling the radical chemistry in an oxidation flow reactor: Radical formation and recycling, sensitivities, and the OH Exposure estimation equation. J. Phys. Chem. A. 119, 4418–4432 (2015).

Article Google Scholar

Pieber, S. M. et al. Inorganic salt interference on CO2+ in Aerodyne AMS and ACSM organic aerosol composition studies. Environ. Sci. Technol. 50, 10494–10503 (2016).

Article Google Scholar

Wang, J. M. et al. Near-road air pollutant measurements: accounting for inter-site variability using emission factors. Environ. Sci. Technol. 52, 9495–9504 (2018).

Article Google Scholar

Huai, T. et al. Vehicle specific power approach to estimating on-road NH3 emissions from light-duty vehicles. Environ. Sci. Technol. 39, 9595–9600 (2005).

Article Google Scholar

Cheng, H. et al. Ammonia emission measurements for light-duty gasoline vehicles in China and implications for emission modeling. Environ. Sci. Technol. 52, 11223–11231 (2018).

Article Google Scholar

Download references

This work was financially supported by the National Key Research and Development Program of China (2022YEF0135000), the Natural Science Foundation of Tianjin (20JCYBJC01270), the National Natural Science Foundation of China (42175123, 42107125), and Tianjin Research Innovation Project for Postgraduate Students (No. 2021YJSS013).

Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, 300071, Tianjin, China

Jinsheng Zhang, Jianfei Peng, Ainan Song, Zongyan Lv, Hui Tong, Zhuofei Du, Jiliang Guo, Lin Wu, Ting Wang & Hongjun Mao

Department of Chemistry and Molecular Biology, University of Gothenburg, 41296, Gothenburg, Sweden

Mattias Hallquist

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

J.P. and J.Z. conceived the study. J.Z., A.S., Z.L., and H.T. performed the experiments and conducted the data analyses. Z.D., J.G., L.W., T.W., and H.M. interpreted and discussed the data results. J.Z. wrote the paper. J.P. and H.M. revised the paper. All authors contributed to the final paper.

Correspondence to Jianfei Peng.

The authors declare no competing interests.

Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

Zhang, J., Peng, J., Song, A. et al. Marked impacts of transient conditions on potential secondary organic aerosol production during rapid oxidation of gasoline exhausts. npj Clim Atmos Sci 6, 59 (2023). https://doi.org/10.1038/s41612-023-00385-4

Download citation

Received: 15 December 2022

Accepted: 16 May 2023

Published: 05 June 2023

DOI: https://doi.org/10.1038/s41612-023-00385-4

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative