Next Article in Journal
Evaluation of the IASI/Metop Dust Flag Product Using AERONET Data
Previous Article in Journal
Development and Evaluation of Dimensionless Design Storm Hyetographs for Southwestern Saudi Arabia in a Hyper-Arid Climate
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Atmosphere
Volume 16
Issue 11
10.3390/atmos16111238
atmosphere-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Vehicle Indoor Air Quality Due to External Pollutant Ingress While Driving

by
Ho-Hyeong Yang
1,
In-Ji Park
2,
Cha-Ryung Kim
2,
Hyun-Woo Lee
2 and
Ho-Hyun Kim
1,*
1
Department of Chemical and Environmental Engineering, Seokyeong University, Seoul 02713, Republic of Korea
2
Korea Transportation Safety Authority, Korea Automobile Testing and Research Institute, Hwaseong-si 18247, Republic of Korea
*
Author to whom correspondence should be addressed.
Atmosphere 2025, 16(11), 1238; https://doi.org/10.3390/atmos16111238
Submission received: 23 September 2025 / Revised: 19 October 2025 / Accepted: 25 October 2025 / Published: 27 October 2025
(This article belongs to the Section Air Quality)
Browse Figures
Versions Notes

Abstract

Vehicle indoor air quality (VIAQ) remains poorly standardized despite its growing health relevance. This study developed and applied a real-road test protocol to quantify in-cabin exposure to particulate and gaseous pollutants under different heating, ventilation, and air-conditioning (HVAC) modes: outside air (OA), recirculation (RC), and automatic (Auto). Concentrations of PM2.5, particle number (PN), NO, and NO2 were simultaneously measured inside and outside passenger vehicles using validated instruments. In-cabin PM2.5 levels were lowest in RC, intermediate in Auto, and highest in OA, showing strong HVAC dependence. Particle number distributions were dominated by submicron particles (<1.0 μm). Under RC, NO gradually increased while NO2 decreased, likely due to NO–NO2 interconversion and activated-carbon filtration. Short-duration, reproducible on-road tests were conducted under standardized vehicle, occupant, and HVAC settings to minimize variability. Although external conditions could not be fully controlled, consistent routes and configurations ensured comparability. The findings highlight HVAC operation as the dominant factor governing short-term VIAQ and provide practical insight toward harmonized test procedures and design improvements for cabin air management.

1. Introduction

Individuals are primarily exposed to air pollutants in indoor environments, where people spend most of their time. According to a time use survey in 2019 by KOSTAT [1], South Koreans spend more than 90% of the day indoors and approximately 1.2 h/day in vehicles, with approximately 57% (41 min) of that time spent specifically in passenger vehicles. Although the value differs from country to country, people around the world spend approximately 5% of their day in vehicles [2]. The global fleet of light-duty vehicles (LDVs), including passenger cars, was estimated at approximately 1.31 billion in 2020 and is projected to increase to 2.21 billion by 2050 [3]. This substantial rise in vehicle numbers directly contributes to increased traffic congestion and elevated exhaust emissions, thereby compelling people to spend more time in their vehicles daily and consequently increasing their potential exposure to pollutants.
Vehicles emit exhaust gases containing a mixture of particulate and gaseous pollutants generated from incomplete combustion, volatilization of unburned fuel, and the release of engine lubricants, including particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), and hydrocarbons (HC). In 2012, the International Agency for Research on Cancer (IARC) reclassified diesel exhaust as a Group 1 carcinogen (carcinogenic to humans) and gasoline exhaust as a Group 2B carcinogen. In addition to exhaust fumes, other non-exhaust emissions are related to transportation, such as those associated with the wear of motor vehicle brake pads, tires, and roads, as well as road re-suspended dust. Air pollutants emitted from vehicles can be inhaled by humans and have been related to numerous adverse health effects, such as lower respiratory function, cardiovascular disease, asthma, and premature death [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19]. In particular, passenger vehicles are vulnerable to exposure to exhaust fumes emitted by other types of vehicles due to their low body and low ventilation system intake points, and they have been associated with the highest exposure levels among commuter vehicles [19,20,21]. Furthermore, reports have shown that the pollutant concentrations within vehicles are very high compared to those outside of vehicles or in other indoor environments [22,23,24,25]. This implies that despite the relatively short time spent in a vehicle compared to other spaces, exposure to pollutants in vehicles can account for most of the total daily exposure because of the high ambient concentrations [22,26,27,28,29].
Vehicles represent a frequent transportation mode in modern life, and as vehicle use increases, consumers have shown more interest in ensuring air quality inside vehicles. Molden et al. [30] noted that even in transport modes generally considered to offer cleaner environments, cumulative exposure could be significant depending on journey conditions. According to Matthaios et al. [31], Pöhler et al. [32], and Moldanova et al. [33], new activated carbon filters can reduce in-cabin NO2 concentrations by up to 90%, whereas aged filters provide significantly reduced protection. In a related study, Matthaios et al. [34] reported that on-road air pollution was the largest single contributor to in-cabin exposure, explaining 22.3% of NO2 and 30% of PM2.5 levels. Vehicle-based factors—including model year, cabin volume, odometer reading, air filter type, window settings, and ventilation configuration—accounted for 48.7% and 61.3% of the variance in NO2 and PM2.5, respectively. Driving-related factors, such as vehicle speed, traffic conditions, signalized intersections, roundabouts, and nearby high-emitting vehicles, explained an additional 22% of NO2 and 7.4% of PM2.5 exposure. Similarly, Campagnolo et al. [35] emphasized the critical role of ventilation settings—particularly recirculation versus fresh-air modes—and the proximity of vehicles to high-emission sources as key determinants of in-cabin pollutant exposure. Their systematic review revealed that over 40% of existing studies focused on ventilation control, yet significant heterogeneity in ventilation setups across studies limited comparability, underscoring the need for standardized ventilation protocols in future VIAQ evaluations. Alongside prior work, studies such as Russi et al. [36] conducted experimental comparisons of heating, ventilation, and air conditioning (HVAC) modes and found that the recirculation mode reduced PM2.5 concentrations substantially inside electric vehicle cabins compared to the fresh-air mode. However, they also observed accumulation of volatile organic compounds (VOCs) under recirculation, likely due to interior sources such as plasticizers or human activity, indicating a trade-off between particulate and gaseous pollutant control.
Such diverse findings across studies have highlighted the complexity of in-cabin pollutant dynamics and the influence of ventilation strategies, thereby reinforcing the need for unified testing procedures. The findings have informed regulatory interest in developing standardized evaluation protocols. In response to the concerns above, the UN European Economic Commission for Europe Vehicles Interior Air Quality Informal Working Group (UNECE VIAQ IWG) [37] has studied vehicle indoor air quality (VIAQ) in relation to the ingress of external pollutants and methods of evaluating VIAQ under various test conditions.
Indoor air pollutant concentrations in vehicles can differ depending on numerous variables, such as the air quality outside vehicles, vehicle volume, fan speed, number of passengers, filter efficiency, and vehicle travel speed [38]. A higher vehicle driving speed can cause pressure differences inside and outside vehicles, resulting in a higher ingress of external pollutants [39]. As such, VIAQ can vary depending on the driving conditions and may change from vehicle to vehicle [40]. However, standardized test methods have not been established to assess VIAQ relative to external air quality under diverse conditions. Therefore, to ensure the quality of the environment inside vehicles, objective and reliable evaluation methods and standards are required to define and measure pollution inside vehicles.
In this study, we performed an on-road driving test and assessed changes in VIAQ due to the ingress of external pollutants during driving to develop an evaluation method accepted by both automobile manufacturers and consumers. We prepared the targets to be measured, driving route, test methods, and procedures, conducted an on-road driving test, and applied the test results as a basis for developing a standardized VIAQ evaluation method.

2. Test Method Design

2.1. Review of Factors Influencing Vehicle Indoor Air Quality

The level of pollution inside a vehicle may be higher than the levels in the ambient environment [23,25]. Furthermore, exposure to high levels of pollutants inside vehicles is mainly caused by high air exchange rates (AERs), outdoor air infiltration, and low filter efficiency [41,42,43,44]. The AER can exert a significant impact on the I/O ratio of pollutants inside vehicles [39,45].
Distance between vehicles is also an important factor influencing indoor pollutant levels. The proximity of other vehicles to the experimental vehicle can also increase the ingress of pollutants emitted by neighboring vehicles. Moving vehicles form vortices in the slipstream flow that interact with pollutants emitted by the vehicle itself. These flows have been shown to increase turbulence and Brownian diffusion and lead to ultrafine particle (UFP) accumulation at the periphery or center [46]. Reports have also indicated that the air quality may be extremely polluted in traffic jams, stop-and-go traffic situations, or behind a diesel-powered truck on a highway [47].
As such, air pollutant concentrations in vehicles can differ depending on numerous factors, such as the air quality outside vehicles, vehicle volume, fan speed, number of passengers, filter efficiency, and vehicle driving speed [38]. Based on factors influencing VIAQ and findings of previous studies and the UNECE VIAQ IWG, this study derived experimental methods for evaluating VIAQ during driving, including the test route, driving method, and HVAC mode settings.

2.2. Selection of Targets to Be Measured and Measurement Equipment

Two types of pollutants enter a vehicle and affect indoor air quality: exhaust fumes from the vehicle and non-exhaust emissions related to transportation. Vehicle exhaust fumes contain carbon monoxide (CO), nitrogen oxides (NOx), hydrocarbons (HC), and particulate matter (PM). Air pollutants include CO, NOx, sulfur oxides (SOx), total suspended particulates (TSPs), PM with a diameter of 10 µm or less (PM10), PM2.5, VOCs, ammonia (NH3), and black carbon (BC). In particular, high emissions of NOx, CO, and BC are associated with road mobile pollution sources. Scattering dust accounts for the highest proportion of PM emissions. More than 90% of traffic-related non-exhaust PM emissions are generated from traffic-related sources, such as the wear of motor vehicle brake pads, tires, and roads [48].
This study reviewed pollutants that affect VIAQ based on Korean and international studies on VIAQ and air quality management standards (Table 1). To evaluate indoor air quality in a vehicle during driving, this study selected PM2.5, PN (particle number concentration), NO, and NO2 as the target pollutants to be measured according to their measurability and exposure to human bodies.
In both the exploratory and definitive tests, we utilized Dusttrak (TSI Inc., Shoreview, MN, USA) to measure PM2.5 and Model 3330 (TSI Inc., Shoreview, MN, USA) to measure PN. The concentrations of NO and NO2 were measured using Testo’s Model 350K (Testo, Titisee-Neustadt, Germany) in the exploratory test and Serinus40 (Ecotech, Knoxfield, VIC, Australia) in the definitive test.
In both the exploratory and definitive tests, the air quality inside the vehicle was measured between the driver’s and passenger’s headrests. In the definitive test, the outside air quality measurement probe was installed through the second-row window on the driver’s side, and an isokinetic sampling inlet was utilized to ensure data reliability, considering that the vehicle was moving. An additional exhaust line was secured so that it could be discharged to the outside (Figure S1) to ensure that the outside air concentration measured by the equipment installed inside the vehicle would not be mixed with the air inside the vehicle.

2.3. On-Road Driving Test Method

2.3.1. On-Road Driving Route

The on-road test route consisted of roads in the city center of Ansan, South Korea, and a highway, with the route shifting to the highway after driving in the city center. The city center route was subject to a speed limit of 50 km/h in accordance with the Korean Road Traffic Act, and the highway route was subject to a speed limit of 50–100 km/h. The minimum mileage of each route was set to 16 km, and the driving test was conducted on real roads.
The mixed urban–highway route was designed to represent combined driving conditions that involve both stop-and-go traffic and steady-speed cruising, allowing short-term assessment of HVAC performance under varied ventilation and airflow dynamics. The focus of this study was not long-term exposure monitoring but the evaluation of in-cabin pollutant behavior during reproducible short-duration driving conditions.

2.3.2. HVAC Mode Setting

The HVAC mode, which is an important factor that influences VIAQ, was divided into outside air ventilation (OA), in-vehicle recirculation (RC), and automatic mode (Auto) with air-cleaning. The temperature in each HVAC mode was set to 22 °C, the air conditioner was set to be on, the fan speed was set to medium (50%), and the air-cleaning function was set to automatic mode (Figure S2).

2.3.3. Test Procedures and Conditions

In this study, we performed exploratory and definitive tests. In the exploratory test, we only measured the air quality inside the vehicle, while in the definitive test, we measured and compared both the air quality inside and outside the vehicle. The test vehicle was occupied by two passengers, i.e., a driver and a passenger. After arriving at the starting point of the on-road driving, the engine was turned off, the windows were opened, and the vehicle was ventilated to equalize the pollution levels inside and outside the vehicle. After the equipment was warmed up, measurements were started. In addition, the vehicle engine was turned on, the windows were closed, and the on-road driving test was performed.
During all driving tests, the doors and windows remained closed, and HVAC settings were unified as described in Section 2.3.2. The cabin load was fixed to two occupants, with no personal belongings placed inside the vehicle. Both participants wore long-sleeved polyester clothing to minimize potential emissions or interference from fabrics and skin exposure.
We used four vehicles (two gasoline [GSL] and two diesel [DSL]) in the test, and the specifications of each vehicle can be found in Table 2. As for the air-conditioning filters, which can affect VIAQ, we used manufacturer-certified activated carbon filters and replaced them with new ones prior to testing to ensure consistent HVAC performance and minimize variability related to filter condition.

2.4. Calculation of Cleaning Efficiency

The cleaning efficiency was calculated based on the PM2.5 concentration inside and outside the vehicle according to the following equation:
n p m = ( 1 − C p m   in C p m   o u t ) · 100 %
where Cpmin represents the indoor PM2.5 concentration (µg/m3) and Cpmout represents the outdoor PM2.5 concentration (µg/m3).

3. Results and Discussion

3.1. Exploratory Test

Table 3 presents the average concentrations of PM2.5, NO, and NO2 measured inside the vehicle under different HVAC settings in the exploratory test. Figure 1 presents the PM2.5 concentrations measured inside the vehicle during driving through the exploratory test. The change in concentration over time for each HVAC mode test showed the following patterns: the concentration was saturated to the same level as the outside air concentration through ventilation before driving, and started to gradually decrease after driving. In the OA and Auto modes, the concentration decreased to a certain level and did not decrease further, while in RC mode, the concentration decreased to a lower level than that in the other HVAC modes. This finding is consistent with those of previous studies showing that the concentration gradually decreased over time in RC mode and that the internal concentration was highest in OA mode, followed by Auto and RC modes [36,49,50].
Under Auto mode, the automatic blocking of outside air before entering the tunnel was activated automatically, and the effect of the HVAC mode was confirmed by the decrease and increase in PM concentration in RC and OA modes, respectively [51]. Under the OA mode, a transient rise in in-cabin pollutant levels was detected during uphill driving, presumably resulting from increased exhaust emissions of preceding vehicles under higher engine load conditions [52].
The PM2.5 concentration in the air outside vehicle A on the test day was somewhat low (daily average of approximately 11 µg/m3), and it was also low inside the vehicle (average of 0.06 to 0.68 µg/m3); thus, it was difficult to clearly confirm the difference in concentration per HVAC mode. The concentration in the air outside vehicle B on the test day was approximately 30 µg/m3, and compared to the indoor concentration in RC mode (0.69 ± 2.64 µg/m3), the indoor concentrations in OA (7.68 ± 1.45 µg/m3) and Auto modes (5.82 ± 1.46 µg/m3) were higher, thus confirming that VIAQ was affected by outdoor air quality. The results of the exploratory test showed that the concentration of pollutants inside the vehicle was most influenced by the outdoor air quality and HVAC mode; therefore, we found that simultaneous measurements of outdoor air quality concentrations were essential in the definitive test.
Figure 2 indicates the particle number concentration (#/cm3) of matter with a diameter between 0.3 μm and 10.0 μm within the vehicle. Particles with a diameter less than 1.0 μm had a high concentration. Compared with the results on the test day for vehicle B, which showed a higher PM2.5 mass concentration inside the vehicle due to the high outdoor air quality concentrations, a higher concentration was observed for vehicle A, which had low outdoor air quality concentrations on the test day. This difference was likely due to the different vehicle models and different routes for external pollutants to infiltrate or enter the vehicle.
Figure 3 shows the NO and NO2 concentrations measured inside the vehicle while driving during the exploratory test. The NO concentration inside the vehicle, which was saturated with the same concentration as outside air, gradually decreased after driving in the RC mode for both GSL and DSL vehicles (Figure 3(a1,a2)).
The average concentrations of NO and NO2 in GSL vehicle A ranged from 339.62 to 1493.33 ppb and from 220.00 to 292.45 ppb, respectively, depending on the HVAC mode, and the concentrations in diesel vehicle B ranged from 269.81 to 530.77 ppb and from 192.31 to 222.41 ppb, respectively. Whether the fluctuations in NO and NO2 concentrations were affected by HVAC changes or external concentrations could not be clarified. However, the average concentration in vehicle B was found to be lower than that in vehicle A, which was assumed to be influenced by the body type of the corresponding vehicle. A low-bodied vehicle has a lower ventilation system intake point, which increases the exposure to exhaust fumes from other vehicles [21,53]. Vehicle A was a midsize sedan, and vehicle B was an SUV. Compared to sedans, SUVs have a higher body and a higher outdoor air intake point. This distance from pollution sources, such as exhaust outlets of the preceding and neighboring vehicles, may have affected the results.
As measurements were performed within one minute in the exploratory test, air quality changes inside the vehicle during driving at high speed may not have been reflected in the data in real time. Furthermore, since changes in the outside air quality of the test vehicle could not be determined, the factors that influenced the data measured inside the vehicle could not be determined.

3.2. Definitive Test

The definitive test evaluation method was updated based on the results of the exploratory test. To clearly confirm the changes in pollutant concentrations within the vehicle in the definitive test, we simultaneously measured the air quality inside and outside the vehicle on a day when the outside air quality was not too poor and attempted to confirm changes in VIAQ due to the ingress of external pollutants into the vehicle. Furthermore, the data were measured every second, and a program was utilized to store and merge the data measured by all the equipment in real time to ensure the reliability of the comparison between the data.
Figure 4 shows the PM2.5 concentration and cleaning efficiency results, which were measured inside and outside the vehicle during driving through the definitive test.
Table 4 presents the average concentrations of PM2.5, NO, and NO2 measured inside and outside the vehicle under different HVAC settings in the definitive test. Vehicles C and D had the lowest average PM2.5 concentrations in RC mode, followed by the Auto and OA modes. In RC mode, the concentrations were reduced to a lower concentration relative to those of the other HVAC modes, which is consistent with the results of the exploratory test. The cleaning efficiency of vehicle D was mostly 100%, whereas that of vehicle C, which experienced higher PM2.5 concentrations outside the vehicle, was slightly lower (approximately 90% or higher). Nevertheless, in the RC mode, most PM2.5 was still effectively removed even though the air-cleaning function was not activated. In OA mode, vehicles C and D maintained a constant concentration level without significant variations during driving. For vehicle C, which had higher pollution levels outside the vehicle, the concentration inside the vehicle fluctuated as the concentration outside the vehicle decreased and increased. In Auto mode, since the air purification function of the vehicle was activated, the vehicle automatically detected the concentration of PM inside the vehicle and repeatedly let in and blocked outside air, which led to fluctuations inside the vehicle. The change was more remarkable in vehicle C, where the concentration outside the vehicle was high.
During driving, the PM concentration outside the vehicle temporarily increased while waiting for traffic signals and during traffic congestion. Consequently, the vehicle indoor concentration also increased in OA mode. This increase was particularly pronounced when the test vehicle was positioned immediately behind heavy-duty vehicles (e.g., trucks or buses) or other high-emitting sources, a frequent occurrence during stop-and-go traffic. Consequently, the vehicle indoor concentration also increased in OA mode. These episodes, highlighted by the yellow arrows in Figure 4(b1,b2), directly demonstrate the vulnerability of the OA mode to localized high-emission plumes entering the cabin. Alm et al. reported that PM levels inside a vehicle were slightly influenced by the number of traffic light stops along a driving route [54]. Exposure to high concentrations in low-speed driving conditions with repeated stop-and-go traffic patterns is associated with higher pollutant emissions from frequent acceleration of densely packed vehicles on the road and a lack of ventilation by external aerodynamics due to low vehicle travel speeds [55].
Furthermore, even when the preceding and neighboring vehicles on the road were buses or trucks, the external concentrations temporarily increased and affected the internal concentrations, which implies that pollutant emissions from the preceding vehicles exerted an impact on the indoor PM concentrations inside the test vehicle [35].
Figure 5 presents the concentrations of PM with a diameter between 0.3 μm and 10.0 μm within the vehicle. PM with a diameter of 1.0 μm or less accounted for the majority of the number concentrations. For PM with a diameter between 0.3 and 1.0 μm, the concentration in vehicle C ranged from 50 to 3239 particles/cm3 (average of 2285 particles/cm3), while that in vehicle D ranged from 0 to 3132 particles/cm3 (average of 1124 particles/cm3). In a study that measured the concentrations of PM with a size ranging from 0.02 to 1.0 µm within a vehicle during driving through equipment (TSI Model 8525, TSI Inc., USA), which is similar to the equipment used in this study, the concentration ranged from 5933 to 29,921 particles/cm3 (an average of 16,392 particles/cm3) [56]. The reason for the somewhat lower concentration in the previous study may have been related to differences in the test conditions, which were conducted on unpaved country roads/lanes in the previous study and on roads in the city center and highways in this study. Moreover, a higher PM concentration may have been found due to the inclusion of particles with a size ranging from 0.02 to 0.3 µm.
As the light scattering method employed in this study was an indirect method, the measured mass concentration value was not an absolute amount and varied greatly depending on the density of the particles, which depended on their chemical properties and conditions. Therefore, correction factors must be applied during the experimental process when comparing the light scattering method with the gravimetric method [57,58,59]. However, when the light scattering method equipment calibrated with standard particles in the laboratory is used under different environmental conditions, such as different emission sources and urban and suburban areas, the density of the particles differs, leading to an inevitable error in the measured mass concentration of particles [60]. As the constant for correcting PM concentrations measured by the light scattering method can vary significantly depending on the measurement point, season, and environmental conditions, it is necessary to derive correction factors for test conditions within the vehicle through future long-term and repetitive tests.
Figure 6 indicates the changes in NO and NO2 concentrations inside and outside the vehicle during driving. Unlike the results of the exploratory test, which showed decreases in concentration in RC mode, both vehicles C and D showed that the NO concentration inside the vehicle gradually increased after a certain time and maintained a constant concentration level, while the NO2 concentration decreased over time in RC mode. Additionally, the average NO concentration inside the vehicle was lowest in OA mode, while the NO2 concentration was highest in OA mode.
A previous study conducted a static test and found that the NO concentration increased and the NO2 concentration decreased inside the vehicle in RC mode, which was assumed to be due to the exhalation of the driver and conversion of NO2 to NO. However, in the dynamic test, the accumulation of indoor NO concentrations could not be clearly determined due to significant changes in outdoor NO concentrations [61], which is consistent with the results reported here.
The filter with activated carbon utilized in this study has been confirmed to be efficient in removing less volatile substances such as NO2 [33]. The gradual decrease in NO2 concentration while driving in RC mode is assumed to be due to the filter effect because it contained activated carbon.

4. Conclusions

In this study, we designed a test to measure the indoor air quality of a vehicle during driving to provide a basis for developing a standardized VIAQ evaluation method. In addition, we investigated the characteristic behavior of PM2.5, particle number concentration, and NO and NO2 levels by performing exploratory and definitive tests to measure the indoor and outdoor air quality of a vehicle driving on a real road.
In both the exploratory and definitive tests, we confirmed that the PM2.5 concentration inside the vehicle during driving was affected by the pollution level of outside air that entered the vehicle based on the HVAC mode. The PM2.5 concentration inside the vehicle differed depending on the HVAC mode, with the highest in OA mode, followed by Auto and RC modes.
The concentration of PM with a diameter between 0.3 and 10.0 μm was dominated by particles with a diameter of less than 1.0 μm, indicating the increased need for regulations on small PM, such as PM2.5 or nanoparticles, rather than larger particles, such as PM10.
The results obtained from the light scattering method equipment used to measure PM should be compared to those obtained by the gravimetric method. However, when light scattering equipment calibrated with standard particles in the laboratory is used to test real conditions, the density of the particles varies, causing errors in the measured values. To compensate for this limitation, research should focus on deriving correction factors for gravimetric and light scattering method equipment through long-term and repeated tests of on-road driving conditions.
In the definitive test, the NO concentration gradually increased in RC mode and then stabilized, while the NO2 concentration gradually decreased. The NO concentration may be influenced by exhalation by the driver and passengers or the conversion of NO2 to NO, whereas the NO2 concentration may be reduced by the use of filters with activated carbon. Thus, it is necessary to further investigate the factors that influence NO and NO2 concentrations in vehicles.
This study presented certain limitations. For example, the conditions on each test day differed due to the nature of on-road driving tests. Moreover, the test vehicles differed in model type and powertrain (two gasoline and two diesel), which limits the representativeness of the findings. Expanding the sample to include hybrid and battery-electric vehicles in future studies would help verify the robustness of this methodology across diverse powertrains and cabin designs. VIAQ is assumed to be affected by external factors (e.g., external air quality, road environment, test country, city, and meteorological conditions) as well as intrinsic factors (e.g., vehicle size, body type, and type of fuel). Thus, test data should be obtained through repeated and simultaneous tests in future research.
Nevertheless, this study confirmed that the concentration of each pollutant varied depending on the type of vehicle, HVAC mode, and driving conditions. These data are important for establishing standards on how to evaluate VIAQ during driving and may provide guidance for developing pollutant-specific criteria for VIAQ. Moreover, the findings will provide consumers with a better understanding of the health effects of their vehicles and may help automobile manufacturers develop technologies to reduce pollutants inside vehicles that affect consumers.
The findings have significant implications for the development of VIAQ standards and regulatory protocols. The observed differences in pollutant concentrations across HVAC modes underscore the importance of defining minimum performance thresholds for in-cabin filtration systems and encouraging the use of recirculation settings, particularly in high-exposure environments. Such evidence supports ongoing international efforts—such as those by the UNECE VIAQ Informal Working Group—to refine standardized testing procedures such as the M.R.3 protocol.
Moreover, the methodology of the present study, based on real-road synchronized measurements and isokinetic sampling, demonstrates the feasibility of developing reproducible and scientifically grounded VIAQ evaluation protocols. Incorporating vehicle-level performance metrics, such as cabin-to-ambient concentration ratios, could enhance the regulatory clarity and comparability of cabin air quality assessments across different vehicle classes.
From a policy perspective, integrating VIAQ metrics into eco-labeling systems or mandatory air quality disclosures may further empower consumers and incentivize manufacturers to invest in cleaner cabin environments. The steps are essential for translating scientific evidence into actionable standards that safeguard commuter health in a rapidly urbanizing and motorized world.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/atmos16111238/s1. Figure S1. Vehicle outside air quality measurement probe and outlet; Figure S2. Automatic mode with air-cleaning mode settings.

Author Contributions

H.-H.Y.: Writing—original draft, Validation, Visualization, Investigation, Methodology, Data curation, Formal Analysis; I.-J.P.: Methodology, Conceptualization; C.-R.K.: Funding acquisition, Conceptualization; H.-W.L.: Supervision, Funding acquisition; H.-H.K.: Writing—review and editing, Supervision, Project administration. All authors have read and agreed to the published version of the manuscript.

Funding

This work is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant No. RS-2023-00243220).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets generated and/or analyzed during the current study are not publicly available due to the ongoing nature of the research and the need for consultation with the funding agency, but are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare the following financial interests/personal relationships, which may be considered as potential competing interests: Ho-Hyun Kim reports that financial support was provided by the Korea Agency for Infrastructure Technology Advancement. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Abbreviations

The following abbreviations are used in this manuscript:
VIAQ Vehicle indoor air quality
HVAC Heating, ventilation, and air conditioning
IARC International Agency for Research on Cancer
UNECE VIAQ IWG UNEuropean Economic Commission for Europe Vehicles Interior Air Quality Informal Working Group
VOC Volatile organic compound
PNParticulate number concentration
AER Air exchange rate
OA Outside air ventilation
RC In-vehicle recirculation
AutoAutomatic mode
GSL Gasoline
DSL Diesel

References

  1. KOSTAT (Statistics Korea). Report on the Time Use Survey Volume 1–2 Time Spent on Activities (6~17); KOSTAT: Daejeon, Republic of Korea, 2020; Available online: https://books.google.com/books?id=9B8OzgEACAAJ (accessed on 19 October 2023)ISBN 978-89-5801-454-6.
  2. Klepeis, N.; Nelson, W.; Ott, W.; Robinson, J.; Tsang, A.; Switzer, P.; Behar, J.; Hern, S.; Engelmann, W. The National Human Activity Pattern Survey (NHAPS): A resource for assessing exposure to environmental pollutants. J. Expo. Anal. Environ. Epidemiol. 2001, 11, 231–252. [Google Scholar] [CrossRef] [PubMed]
  3. U.S. Energy Information Administration (EIA). EIA Projects Global Conventional Vehicle Fleet will Peak in 2038. Today in Energy 2021. Available online: https://www.eia.gov/todayinenergy/detail.php?id=50096 (accessed on 12 October 2025).
  4. Weisel, C.P.; Lawryk, N.J.; Lioy, P.J. Exposure to emissions from gasoline within automobile cabins. J. Expo. Anal. Environ. Epidemiol. 1992, 2, 79–96. [Google Scholar] [PubMed]
  5. Dor, F.; Moullec, Y.L.; Festy, B. Exposure of city residents to carbon monoxide and monocyclic aromatic hydrocarbons during commuting trips in the Paris metropolitan area. J. Air Waste Manage. Assoc. 1995, 45, 103–110. [Google Scholar] [CrossRef]
  6. Seaton, A.; Godden, D.; MacNee, W.; Donaldson, K. Particulate air pollution and acute health effects. Lancet 1995, 345, 176–178. [Google Scholar] [CrossRef]
  7. Flachsbart, P.G. Human exposure to carbon monoxide from mobile sources. Chemosphere Glob. Chang. Sci. 1999, 1, 301–329. [Google Scholar] [CrossRef]
  8. Brauer, M.; Hoek, G.; Van Vliet, P.; Meliefste, K.; Fischer, P.H.; Wijga, A.; Koopman, L.P.; Neijens, H.J.; Gerritsen, J.; Kerkhof, M.; et al. Air pollution from traffic and the development of respiratory infections and asthmatic and allergic symptoms in children. Am. J. Respir. Crit. Care Med. 2002, 166, 1092–1098. [Google Scholar] [CrossRef]
  9. Peters, A.; Von Klot, S.; Heier, M.; Trentinaglia, I.; Hörmann, A.; Wichmann, H.E.; Löwel, H. Cooperative Health Research in the Region of Augsburg Study Group. Exposure to traffic and the onset of myocardial infarction. N. Engl. J. Med. 2004, 351, 1721–1730. [Google Scholar] [CrossRef]
  10. Pope III, C.A.; Burnett, R.T.; Thurston, G.D.; Thun, M.J.; Calle, E.E.; Krewski, D.; Godleski, J.J. Cardiovascular mortality and long-term exposure to particulate air pollution: Epidemiological evidence of general pathophysiological pathways of disease. Circulation 2004, 109, 71–77. [Google Scholar] [CrossRef]
  11. Donaldson, K.; Tran, L.; Jimenez, L.A.; Duffin, R.; Newby, D.E.; Mills, N.; MacNee, W.; Stone, V. Combustion-derived nanoparticles: A review of their toxicology following inhalation exposure. Part. Fibre Toxicol. 2005, 2, 10. [Google Scholar] [CrossRef]
  12. Mills, N.L.; Törnqvist, H.; Robinson, S.D.; Gonzalez, M.; Darnley, K.; MacNee, W.; Boon, N.A.; Donaldson, K.; Blomberg, A.; Sandstrom, T.; et al. Diesel exhaust inhalation causes vascular dysfunction and impaired endogenous fibrinolysis. Circulation 2005, 112, 3930–3936. [Google Scholar] [CrossRef]
  13. Boldo, E.; Medina, S.; LeTertre, A.; Hurley, F.; Mücke, H.G.; Ballester, F.; Aguilera, I.; Eilstein, D.; Apheis Group. Apheis: Health impact assessment of long-term exposure to PM2.5 in 23 European cities. Eur. J. Epidemiol. 2006, 21, 449–458. [Google Scholar] [CrossRef] [PubMed]
  14. Pope, C.A.; Dockery, D.W. Health Effects of Fine Particulate Air Pollution: Lines that Connect. J. Air Waste Manag. Assoc. 2006, 56, 709–742. [Google Scholar] [CrossRef] [PubMed]
  15. Bai, N.; Khazaei, M.; van Eeden, S.F.; Laher, I. The pharmacology of particulate matter air pollution-induced cardiovascular dysfunction. Pharmacol. Ther. 2007, 113, 16–29. [Google Scholar] [CrossRef] [PubMed]
  16. Törnqvist, H.; Mills, N.L.; Gonzalez, M.; Miller, M.R.; Robinson, S.D.; Megson, I.L.; MacNee, W.; Donaldson, K.; Söderberg, S.; Newby, D.E.; et al. Persistent endothelial dysfunction in humans after diesel exhaust inhalation. Am. J. Respir. Crit. Care Med. 2007, 176, 395–400. [Google Scholar] [CrossRef]
  17. Hsu, D.J.; Huang, H.L. Concentrations of volatile organic compounds, carbon monoxide, carbon dioxide and particulate matter in buses on highways in Taiwan. Atmos. Environ. 2009, 43, 5723–5730. [Google Scholar] [CrossRef]
  18. Panel on the Health Effects of Traffic-Related Air Pollution. Traffic-Related Air Pollution: A Critical Review of the Literature on Emissions, Exposure, and Health Effects; Health Effects Institute (HEI): Boston, MA, USA, 2010. [Google Scholar]
  19. Knibbs, L.D.; Cole-Hunter, T.; Morawska, L.A. review of commuter exposure to ultrafine particles and its health effects. Atmos. Environ. 2011, 45, 2611–2622. [Google Scholar] [CrossRef]
  20. Kaur, S.; Nieuwenhuijsen, M.J.; Colvile, R.N. Fine particulate matter and carbon monoxide exposure concentrations in urban street transport microenvironments. Atmos. Environ. 2007, 41, 4781–4810. [Google Scholar] [CrossRef]
  21. El-Fadel, M.; Abi-Esber, L. In-vehicle exposure to carbon monoxide emissions from vehicular exhaust: A critical review. Crit. Rev. Environ. Sci. Technol. 2009, 39, 585–621. [Google Scholar] [CrossRef]
  22. Zhu, Y.; Eiguren-Fernandez, A.; Hinds, W.C.; Miguel, A.H. In-Cabin Commuter Exposure to Ultrafine Particles on Los Angeles Freeways. Environ. Sci. Technol. 2007, 41, 2138–2145. [Google Scholar] [CrossRef]
  23. Zhu, Y.; Hinds, W.C.; Krudysz, M.; Kuhn, T.; Froines, J.; Sioutas, C. Penetration of freeway ultrafine particles into indoor environments. J. Aerosol Sci. 2005, 36, 303–322. [Google Scholar] [CrossRef]
  24. Geiss, O.; Tirendi, S.; Barrero-Moreno, J.; Kotzias, D. Investigation of volatile organic compounds and phthalates present in the cabin air of used private cars. Environ. Int. 2009, 35, 1188–1195. [Google Scholar] [CrossRef]
  25. Jung, H. Modeling CO2 Concentrations in Vehicle Cabin; SAE Technical Paper; SAE: Warrendale, PA, USA, 2013. [Google Scholar] [CrossRef]
  26. Dons, E.; Int Panis, L.; Van Poppel, M.; Theunis, J.; Willems, H.; Torfs, R.; Wets, G. Impact of time–activity patterns on personal exposure to black carbon. Atmos. Environ. 2011, 45, 3594–3602. [Google Scholar] [CrossRef]
  27. Fruin, S.; Westerdahl, D.; Sax, T.; Sioutas, C.; Fine, P.M. Measurements and predictors of on-road ultrafine particle concentrations and associated pollutants in Los Angeles. Atmos. Environ. 2008, 42, 207–219. [Google Scholar] [CrossRef]
  28. Adams, H.S.; Nieuwenhuijsen, M.J.; Colvile, R.N.; McMullen, M.; Khandelwal, P. Fine particle (PM2.5) personal exposure levels in transport microenvironments, London, UK. Sci. Total Environ. 2001, 279, 29–44. [Google Scholar] [CrossRef] [PubMed]
  29. Brown, K.W.; Sarnat, J.A.; Koutrakis, P. Concentrations of PM2.5 mass and components in residential and non-residential indoor microenvironments: The Sources and Composition of Particulate Exposures study. J. Expo. Sci. Environ. Epidemiol. 2012, 22, 161–172. [Google Scholar] [CrossRef] [PubMed]
  30. Molden, N.; Hemming, C.; Leach, F.; Levine, J.G.; Ropkins, K.; Bloss, W. Exposures to Particles and Volatile Organic Compounds across Multiple Transportation Modes. Sustainability 2023, 15, 4005. [Google Scholar] [CrossRef]
  31. Matthaios, V.N.; Di Marco, M.; Buonanno, G.; Kumar, P. Quantifying the performance of vehicle cabin air filters for exposure mitigation in real driving conditions. Sci. Total Environ. 2023, 858, 160395. [Google Scholar] [CrossRef]
  32. Pöhler, D.; Riedner, S.; Brenner, R.; Gröschel, L.; Bigge, K.; Horbanski, M.; Platt, U. Personal exposure of NO2 for cyclist, car drivers and in indoor environments. In Proceedings of the EGU General Assembly Conference Abstracts, Vienna, Austria, 8–13 April 2018; Volume 14529. [Google Scholar]
  33. Moldanova, J.; Parsmo, R.; Langer, S.; Salberg, H.; Jutterström, S.; Rydström, A. Improving Cabin Air Quality in Road Vehicles; IVL Swedish Environmental Research Institute: Stockholm, Sweden, 2019. [Google Scholar]
  34. Matthaios, V.N.; Di Marco, M.; Järv, O.; Gulliver, J. In-vehicle exposure to traffic air pollution: Contribution of environmental, vehicle and driving factors. Sci. Total Environ. 2023, 899, 165537. [Google Scholar] [CrossRef]
  35. Campagnolo, D.; Cattaneo, A.; Corbella, L.; Borghi, F.; Del Buono, L.; Rovelli, S.; Spinazzé, A.; Cavallo, D.M. In-vehicle airborne fine and ultra-fine particulate matter exposure: The impact of leading vehicle emissions. Environ. Int. 2019, 123, 407–416. [Google Scholar] [CrossRef]
  36. Russi, L.; Guidorzi, P.; Pulvirenti, B.; Aguiari, D.; Pau, G.; Semprini, G. Air Quality and Comfort Characterisation within an Electric Vehicle Cabin in Heating and Cooling Operations. Sensors 2022, 22, 543. [Google Scholar] [CrossRef]
  37. UN European Economic Commission for Europe Vehicles Interior Air Quality Informal Working Group. Available online: https://wiki.unece.org/pages/viewpage.action?pageId=25266269 (accessed on 7 March 2024).
  38. Grady, M.L.; Jung, H.; Kim, Y.C.; Park, J.K.; Lee, B.C. Vehicle Cabin Air Quality with Fractional Air Recirculation; SAE Technical Paper; SAE: Warrendale, PA, USA, 2013. [Google Scholar] [CrossRef]
  39. Hudda, N.; Kostenidou, E.; Sioutas, C.; Delfino, R.J.; Fruin, S.A. Vehicle and Driving Characteristics That Influence In-Cabin Particle Number Concentrations. Environ. Sci. Technol. 2011, 45, 8691–8697. [Google Scholar] [CrossRef] [PubMed]
  40. Fruin, S.A.; Hudda, N.; Sioutas, C.; Delfino, R.J. Predictive Model for Vehicle Air Exchange Rates Based on a Large, Representative Sample. Environ. Sci. Technol. 2011, 45, 3569–3575. [Google Scholar] [CrossRef] [PubMed]
  41. Chan, L.Y.; Lau, W.L.; Zou, S.C.; Cao, Z.X.; Lai, S.C. Exposure level of carbon monoxide and respirable suspended particulate in public transportation modes while commuting in urban area of Guangzhou, China. Atmos. Environ. 2002, 36, 5831–5840. [Google Scholar] [CrossRef]
  42. Abi Esber, L.; El-Fadel, M.; Nuwayhid, I.; Saliba, N. The effect of different ventilation modes on in-vehicle carbon monoxide exposure. Atmos. Environ. 2007, 41, 3644–3657. [Google Scholar] [CrossRef]
  43. Qi, C.; Stanley, N.; Pui, D.Y.H.; Kuehn, T.H. Laboratory and On-Road Evaluations of Cabin Air Filters Using Number and Surface Area Concentration Monitors. Environ. Sci. Technol. 2008, 42, 4128–4132. [Google Scholar] [CrossRef]
  44. Xu, B.; Liu, S.; Liu, J.; Zhu, Y. Effects of Vehicle Cabin Filter Efficiency on Ultrafine Particle Concentration Ratios Measured In-Cabin and On-Roadway. Aerosol Sci. Technol. 2011, 45, 234–243. [Google Scholar] [CrossRef]
  45. Knibbs, L.D.; de Dear, R.J.; Morawska, L. Effect of cabin ventilation rate on ultrafine particle exposure inside automobiles. Environ. Sci. Technol. 2010, 44, 3546–3551. [Google Scholar] [CrossRef]
  46. Keita, N.S.; Mehel, A.; Murzyn, F.; Taniere, A.; Arcen, B.; Diourte, B. Numerical study of ultrafine particles dispersion in the wake of a cylinder. Atmos. Pollut. Res. 2019, 10, 294–302. [Google Scholar] [CrossRef]
  47. Mathur, G. Experimental Investigation to Monitor Indoor Air Quality (IAQ) in Detroit Metropolitan Area; SAE Technical Paper; SAE: Warrendale, PA, USA, 2006. [Google Scholar]
  48. Sommer, F.; Dietze, V.; Baum, A.; Sauer, J.; Gilge, S.; Maschowski, C.; Gieré, R. Tire Abrasion as a Major Source of Microplastics in the Environment. Aerosol Air Qual. Res. 2018, 18, 2014–2028. [Google Scholar] [CrossRef]
  49. Abi-Esber, L.; El-Fadel, M. Indoor to outdoor air quality associations with self-pollution implications inside passenger car cabins. Atmos. Environ. 2013, 81, 450–463. [Google Scholar] [CrossRef]
  50. Qiu, Z.; Liu, W.; Gao, H.O.; Li, J. Variations in exposure to in-vehicle particle mass and number concentrations in different road environments. J. Air Waste Manag. Assoc. 2019, 69, 988–1002. [Google Scholar] [CrossRef] [PubMed]
  51. Kwon, O.Y.; An, Y.S. In-vehicle Pollution under Various Driving Conditions. In Proceeding of the 43rd Meeting of KOSAE, Mokpo, Republic of Korea, 26 October 2006; pp. 564–565. [Google Scholar]
  52. Frey, H.C.; Zhai, H.; Rouphail, N.M.; Colyar, J.D. Fuel Use and Emissions Comparisons for Alternative Routes, Time of Day, Road Grade, and Vehicles Based on In-Use Measurements. Environ. Sci. Technol. 2008, 42, 2483–2489. [Google Scholar] [CrossRef] [PubMed]
  53. Ning, Z.; Cheung, C.S.; Lu, Y.; Liu, M.A.; Hung, W.T. Experimental and numerical study of the dispersion of motor vehicle pollutants under idle condition. Atmos. Environ. 2005, 39, 7880–7893. [Google Scholar] [CrossRef]
  54. Alm, S.; Jantunen, M. Urban commuter exposure to particle matter and carbon monoxide inside an automobile. Atmos. Environ. 1999, 33, 923–929. [Google Scholar] [CrossRef]
  55. Pham, L.; Molden, N.; Boyle, S.; Johnson, K.; Jung, H. Development of a standard testing method for vehicle cabin air quality index. SAE Int. J. Commer. Veh. 2019, 12, 151–161. [Google Scholar] [CrossRef]
  56. Geiss, O.; Barrero-Moreno, J.; Tirendi, S.; Kotzias, D. Exposure to Particulate Matter in Vehicle Cabins of Private Cars. Aerosol Air Qual. Res. 2010, 10, 581–588. [Google Scholar] [CrossRef]
  57. Wallace, L.A.; Wheeler, A.J.; Kearney, J.; Van Ryswyk, K.; You, H.; Kulka, R.H.; Rasmussen, P.E.; Brook, J.R.; Xu, X. Validation of continuous particle monitors for personal, indoor, and outdoor exposures. J. Expo. Sci. Environ. Epidemiol. 2011, 21, 49–64. [Google Scholar] [CrossRef]
  58. Kim, J.; Oh, J.; Choi, J.; Ahn, J.; Yoon, G.; Park, J. A study on the correction factor of optic scattering PM2.5 by gravimetric method. J. Kor. Soc. Urban Environ. 2014, 14, 41–47. [Google Scholar]
  59. Park, D.J.; Lee, K.Y.; Park, K.; Bae, M.S. Diurnal Size Distributions of Black Carbon by Comparison of Optical Particulate Measurements—Part I. J. Korean Soc. Atmos. Environ. 2016, 32, 1–8. [Google Scholar] [CrossRef]
  60. Lee, B.J.; Park, S.S. Evaluation of PM10 and PM2.5 Concentrations from Online Light Scattering Dust Monitors Using Gravimetric and Beta-ray Absorption Methods. J. Korean Soc. Atmos. Environ. 2019, 35, 357–369. [Google Scholar] [CrossRef]
  61. Mendez-Jimenez, D.; Lakey, P.S.; Shiraiwa, M.; Jung, H. Behavior of carbon monoxide, nitrogen oxides, and ozone in a vehicle cabin with a passenger. Environ. Sci. Processes Impacts 2021, 23, 302–310. [Google Scholar] [CrossRef]
Atmosphere 16 01238 g001
Figure 1. Time series of PM2.5 concentrations by heating, ventilation, and air conditioning (HVAC) mode in the exploratory test. (A) Vehicle A; (B) Vehicle B.
Figure 1. Time series of PM2.5 concentrations by heating, ventilation, and air conditioning (HVAC) mode in the exploratory test. (A) Vehicle A; (B) Vehicle B.
Atmosphere 16 01238 g001
Atmosphere 16 01238 g002
Figure 2. Evolution of indoor particle size distributions and concentrations by HVAC mode in the exploratory test. The figure displays the measured indoor particulate number (PN) concentrations based on three HVAC modes: (a1,a2) Recirculation (RC) mode, (b1,b2) Outside air (OA) mode, and (c1,c2) Auto mode. Within each mode, subplots indexed with ‘1’ (A) represent the indoor concentrations for Vehicle A, and subplots indexed with ‘2’ (B) represent the indoor concentrations for Vehicle B.
Figure 2. Evolution of indoor particle size distributions and concentrations by HVAC mode in the exploratory test. The figure displays the measured indoor particulate number (PN) concentrations based on three HVAC modes: (a1,a2) Recirculation (RC) mode, (b1,b2) Outside air (OA) mode, and (c1,c2) Auto mode. Within each mode, subplots indexed with ‘1’ (A) represent the indoor concentrations for Vehicle A, and subplots indexed with ‘2’ (B) represent the indoor concentrations for Vehicle B.
Atmosphere 16 01238 g002
Atmosphere 16 01238 g003
Figure 3. Time series of NO and NO2 concentrations by HVAC mode in the exploratory test. The figure shows the measured indoor concentrations under three HVAC modes: (a1,a2) RC, (b1,b2) OA, and (c1,c2) Auto. Within each mode, subplots indexed with ‘1’ (A) represent the indoor concentrations for Vehicle A, and subplots indexed with ‘2’ (B) represent the indoor concentrations for Vehicle B.
Figure 3. Time series of NO and NO2 concentrations by HVAC mode in the exploratory test. The figure shows the measured indoor concentrations under three HVAC modes: (a1,a2) RC, (b1,b2) OA, and (c1,c2) Auto. Within each mode, subplots indexed with ‘1’ (A) represent the indoor concentrations for Vehicle A, and subplots indexed with ‘2’ (B) represent the indoor concentrations for Vehicle B.
Atmosphere 16 01238 g003
Atmosphere 16 01238 g004
Figure 4. Time series of indoor/outdoor PM2.5 concentrations by HVAC mode in the definitive test. The figure shows the measured indoor concentrations under three HVAC modes: (a1,a2) RC, (b1,b2) OA, and (c1,c2) Auto. Within each mode, subplots indexed with ‘1’ (C) represent the indoor concentrations for Vehicle C, and subplots indexed with ‘2’ (D) represent the indoor concentrations for Vehicle D.
Figure 4. Time series of indoor/outdoor PM2.5 concentrations by HVAC mode in the definitive test. The figure shows the measured indoor concentrations under three HVAC modes: (a1,a2) RC, (b1,b2) OA, and (c1,c2) Auto. Within each mode, subplots indexed with ‘1’ (C) represent the indoor concentrations for Vehicle C, and subplots indexed with ‘2’ (D) represent the indoor concentrations for Vehicle D.
Atmosphere 16 01238 g004
Atmosphere 16 01238 g005
Figure 5. Evolution of indoor/outdoor particle size distributions and number concentrations by HVAC mode in the definitive test. The figure shows the measured indoor concentrations under three HVAC modes: (a1,a2) RC, (b1,b2) OA, and (c1,c2) Auto. Within each mode, subplots indexed with ‘1’ (C) represent the indoor concentrations for Vehicle C, and subplots indexed with ‘2’ (D) represent the indoor concentrations for Vehicle D.
Figure 5. Evolution of indoor/outdoor particle size distributions and number concentrations by HVAC mode in the definitive test. The figure shows the measured indoor concentrations under three HVAC modes: (a1,a2) RC, (b1,b2) OA, and (c1,c2) Auto. Within each mode, subplots indexed with ‘1’ (C) represent the indoor concentrations for Vehicle C, and subplots indexed with ‘2’ (D) represent the indoor concentrations for Vehicle D.
Atmosphere 16 01238 g005
Atmosphere 16 01238 g006
Figure 6. Time series of indoor/outdoor NO and NO2 concentrations by HVAC mode in the definitive test. The figure shows the measured indoor concentrations under three HVAC modes: (a1,a2) RC, (b1,b2) OA, and (c2,c3) Auto. Within each mode, subplots indexed with ‘1’ (C) represent the indoor concentrations for Vehicle C, and subplots indexed with ‘2’ (D) represent the indoor concentrations for Vehicle D.
Figure 6. Time series of indoor/outdoor NO and NO2 concentrations by HVAC mode in the definitive test. The figure shows the measured indoor concentrations under three HVAC modes: (a1,a2) RC, (b1,b2) OA, and (c2,c3) Auto. Within each mode, subplots indexed with ‘1’ (C) represent the indoor concentrations for Vehicle C, and subplots indexed with ‘2’ (D) represent the indoor concentrations for Vehicle D.
Atmosphere 16 01238 g006
Table 1. Standards for pollutants that affect air quality.
Table 1. Standards for pollutants that affect air quality.
StandardsPollutants
Comprehensive air-quality index (CAI)PM10, PM2.5, O3, NO2, CO, SO2
National ambient air quality standardPM10, PM2.5, O3, NO2, CO, SO2, Pb, Benzene
Public buses’ indoor air quality standardPM2.5, CO2
Indoor parking lot air quality standardPM10, CO, HCHO, NO2, Rn, TVOC
Standards in the tunnelCO, NOx
Green NCAP Clean Air IndexHC, NO2, NO, NH3, CO, PM, PN
NCAP: New Car Assessment Program.
Table 2. Specifications of the test vehicles.
Table 2. Specifications of the test vehicles.
TestExploratory TestDefinitive Test
VehicleABCD
Body typeSedanSUVSUVSUV
PowertrainGSLDSLGSLDSL
Model year2022202220222022
Displacement (cc)1999215124972151
Curb Weight (kg)1415175517501820
Odometer Reading (km)104613,75513,03833,961
GSL, gasoline; DSL, diesel.
Table 3. Average indoor air concentrations by HVAC mode in the exploratory test.
Table 3. Average indoor air concentrations by HVAC mode in the exploratory test.
HVACVehicle AVehicle B
PM2.5 (µg/m3)RC0.06 ± 0.300.69 ± 2.64
OA0.63 ± 0.497.68 ± 1.45
Auto0.68 ± 1.305.82 ± 1.46
NO (ppb)RC339.62 ± 277.59472.41 ± 133.50
OA675.00 ± 254.28269.81 ± 156.38
Auto1493.33 ± 193.86530.77 ± 93.41
NO2 (ppb)RC292.45 ± 33.10222.41 ± 46.05
OA275.00 ± 51.92220.75 ± 45.40
Auto220.00 ± 48.01192.31 ± 36.69
Table 4. Average indoor and outdoor air concentrations by HVAC mode in the definitive test.
Table 4. Average indoor and outdoor air concentrations by HVAC mode in the definitive test.
HVACVehicle CVehicle D
IndoorOutdoorIndoorOutdoor
PM2.5 (µg/m3)RC3.49 ± 2.6854.83 ± 7.251.04 ± 5.0438.97 ± 3.50
OA23.42 ± 1.9452.96 ± 5.5612.76 ± 0.8345.25 ± 3.33
Auto13.83 ± 5.0358.28 ± 10.308.16 ± 5.1236.58 ± 4.60
NO (ppb)RC97.96 ± 27.41141.23 ± 158.2493.15 ± 49.0776.04 ± 190.23
OA85.12 ± 91.62101.32 ± 170.8427.34 ± 61.6443.02 ± 111.33
Auto101.63 ± 64.22155.2 ± 256.3151.62 ± 71.0169.84 ± 167.89
NO2 (ppb)RC6.10 ± 5.7459.04 ± 42.4511.40 ± 5.9017.42 ± 29.94
OA46.71 ± 22.3763.26 ± 45.2011.91 ± 9.7113.41 ± 28.12
Auto21.25 ± 9.6158.07 ± 29.056.45 ± 6.7017.70 ± 34.37
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Yang, H.-H.; Park, I.-J.; Kim, C.-R.; Lee, H.-W.; Kim, H.-H. Vehicle Indoor Air Quality Due to External Pollutant Ingress While Driving. Atmosphere 2025, 16, 1238. https://doi.org/10.3390/atmos16111238

AMA Style

Yang H-H, Park I-J, Kim C-R, Lee H-W, Kim H-H. Vehicle Indoor Air Quality Due to External Pollutant Ingress While Driving. Atmosphere. 2025; 16(11):1238. https://doi.org/10.3390/atmos16111238

Chicago/Turabian Style

Yang, Ho-Hyeong, In-Ji Park, Cha-Ryung Kim, Hyun-Woo Lee, and Ho-Hyun Kim. 2025. "Vehicle Indoor Air Quality Due to External Pollutant Ingress While Driving" Atmosphere 16, no. 11: 1238. https://doi.org/10.3390/atmos16111238

APA Style

Yang, H.-H., Park, I.-J., Kim, C.-R., Lee, H.-W., & Kim, H.-H. (2025). Vehicle Indoor Air Quality Due to External Pollutant Ingress While Driving. Atmosphere, 16(11), 1238. https://doi.org/10.3390/atmos16111238

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop