Ammonia, a significant precursor for secondary inorganic aerosols, plays a pivotal role in new particle formation. Inventories and source apportionment studies have identified vehicular exhaust as a primary source of atmospheric ammonia in urban regions. Existing research on the factors influencing ammonia emissions from gasoline vehicles exhibits substantial inconsistencies in both test results and analyses. The lack of a uniform pattern in ammonia emissions across different standard vehicles and the significant overlap in test results across diverse operational conditions highlight the complexities in this field of study. While individual results can be interpreted through a mechanistic lens, disparate studies often lack a common explanatory framework. To address this gap, our study leverages the robust and comprehensive approach of meta-analysis to reconcile these inconsistencies and provide a more precise understanding of the factors influencing ammonia emissions from gasoline vehicles. A large number (N = 537) of ammonia emission factors were extracted after screening >1628 publications. The combined ammonia emission factor was 23.57 ± 24.94 mg/km. Emission standards, engine type, ambient temperatures, mileage, vehicle speed, and engine displacement have a significant impact on ammonia emission factors, explaining the ammonia emission factor by up to 50.63 %, with speed being the most significant factor. All these factors are attributed to the interplay of catalyst properties, lambda, and residence time (space velocity). In the current fleet, ammonia emission control is relatively insufficient under low-speed and ultra-high speed, low temperature, and ultra-high mileage conditions. Since ammonia emission factors do not monotonically decrease with the upgrading of motor vehicle emission standards, it is called for the addition of ammonia emission factors indicators in motor vehicle emission standards, and stipulation of targeted testing procedures and testing instruments.

Seventeen polycyclic aromatic hydrocarbons (PAHs) and eight nitrated PAHs (NPAHs) in PM2.5 and conventional gaseous pollutants exhausted from 54 in-use gasoline vehicles encompassing different emission standards (China 1 to China 5) were tested on the chassis and engine dynamometric test bench. With the increase of emission standards, a decrease in the emissions of PM2.5-bound PAHs and NPAHs was detected. The emission factors (EFs) of total PAHs and NPAHs in PM2.5 emitted by the vehicles with a mileage of >100,000 km were greater than that emitted by the vehicles with driving mileage of <100,000 km under all the five emission standards. The EFs of PM2.5-bound PAHs and NPAHs emitted from port fuel injection engines were larger than that from gasoline direct injection engines. The emissions of PM2.5-bound PAHs and NPAHs were less correlated with the exhaust of CO, while the hydrocarbon (HC) emissions were strongly correlated with the PM2.5-bound PAHs emissions. The emissions of NPAHs and NOx had an inverse correlation. The toxic (TEQs) of total PAHs and NPAHs in China 3, China 4 and China 5 were significantly reduced compared to China 1 and China 2, which may be related to exhaust technology improvements. Although the EFs of NPAHs were significantly lower than those of PAHs, the TEQs of NPAHs were higher, which indicates that the toxic effect of NPAHs emitted by gasoline vehicles were stronger than PAHs.

Vehicle emissions are a major source of air pollution in Hong Kong affecting human health. A \'strengthened emissions control of gasoline and liquefied petroleum gas (LPG) vehicles\' programme has been operating in Hong Kong since September 2014 utilising remote sensing (RS) technology. RS has provided measurement data to successfully identify high emitting gasoline and LPG vehicles which then need to be repaired or removed from the on-road vehicle fleet. This paper aims to evaluate the effectiveness of this globally unique RS monitoring programme. A large RS dataset of 2,144,422 records was obtained covering the period from 6th January 2012 to 30th December 2016, of which 1,206,762 records were valid and suitable for further investigation. The results show that there have been significant reductions of emissions factors (EF) for 40.5% HC, 45.3% CO and 29.6% NO for gasoline vehicles. Additionally, EF reductions of 48.4% HC, 41.1% CO and 58.7% NO were achieved for LPG vehicles. For the combined vehicle fleet, the reductions for HC, CO and NO were 55.9%, 50.5% and 60.9% respectively during this survey period. The findings demonstrate that the strengthened emissions control programme utilising RS has been very effective in identifying high emitting vehicles for repair so as to reduce the emissions from gasoline and LPG vehicles under real driving.

This study investigates the PM2.5 emission and analyses the PAHs content in PM2.5 emitted from gasoline-fueled vehicles. Outflow from the vehicles appear to be the ultimate source of PAHs in metro urban communities since the emission from gasoline vehicle increases the wellbeing hazard due to contiguity of exposure to gasoline exhaust. In this study, fifteen vehicles were randomly taken for sampling, where sixteen priority PAHs concentration were investigated. The study was performed on the vehicles with different Euro standard emission by taking into consideration the European legislative levels for vehicles on the toxic gaseous emission. Among all the PAHs outflow components of PM2.5 radiated in the exhaust of gasoline engines, the average concentration of total PAHs discharged was 0.377ng/L-fuel, while the total BaPeq concentration was 0.00993ng/L-fuel.

In this work, a comprehensive characterisation and source apportionment of size-segregated aerosol collected using a multistage cascade impactor was performed. The samples were collected during wintertime in Milan (Italy), which is located in the Po Valley, one of the main pollution hot-spot areas in Europe. For every sampling, size-segregated mass concentration, elemental and ionic composition, and levoglucosan concentration were determined. Size-segregated data were inverted using the program MICRON to identify and quantify modal contributions of all the measured components. The detailed chemical characterisation allowed the application of a three-way (3-D) receptor model (implemented using Multilinear Engine) for size-segregated source apportionment and chemical profiles identification. It is noteworthy that - as far as we know - this is the first time that three-way source apportionment is attempted using data of aerosol collected by traditional cascade impactors. Seven factors were identified: wood burning, industry, resuspended dust, regional aerosol, construction works, traffic 1, and traffic 2. Further insights into size-segregated factor profiles suggested that the traffic 1 factor can be associated to diesel vehicles and traffic 2 to gasoline vehicles. The regional aerosol factor resulted to be the main contributor (nearly 50%) to the droplet mode (accumulation sub-mode with modal diameter in the range 0.5-1 μm), whereas the overall contribution from the two factors related to traffic was the most important one in the other size modes (34-41%). The results showed that applying a 3-D receptor model to size-segregated samples allows identifying factors of local and regional origin while receptor modelling on integrated PM fractions usually singles out factors characterised by primary (e.g. industry, traffic, soil dust) and secondary (e.g. ammonium sulphate and nitrate) origin. Furthermore, the results suggested that the information on size-segregated chemical composition in different size classes was exploited by the model to relate primary emissions to rapidly-formed secondary compounds.

On-road gasoline vehicles are a major source of secondary organic aerosol (SOA) in urban areas. We investigated SOA formation by oxidizing dilute, ambient-level exhaust concentrations from a fleet of on-road gasoline vehicles in a smog chamber. We measured less SOA formation from newer vehicles meeting more stringent emissions standards. This suggests that the natural replacement of older vehicles with newer ones that meet more stringent emissions standards should reduce SOA levels in urban environments. However, SOA production depends on both precursor concentrations (emissions) and atmospheric chemistry (SOA yields). We found a strongly nonlinear relationship between SOA formation and the ratio of nonmethane organic gas to oxides of nitrogen (NOx) (NMOG:NOx), which affects the fate of peroxy radicals. For example, changing the NMOG:NOx from 4 to 10 ppbC/ppbNOx increased the SOA yield from dilute gasoline vehicle exhaust by a factor of 8. We investigated the implications of this relationship for the Los Angeles area. Although organic gas emissions from gasoline vehicles in Los Angeles are expected to fall by almost 80% over the next two decades, we predict no reduction in SOA production from these emissions due to the effects of rising NMOG:NOx on SOA yields. This highlights the importance of integrated emission control policies for NOx and organic gases.

As stricter standards for diesel vehicles are implemented in China, and the use of diesel trucks is forbidden in urban areas, determining the contribution of light-duty gasoline vehicles (LDGVs) to on-road PM2.5 emissions in cities is important. Additionally, in terms of particle number and size, particulates emitted from LDGVs have a greater health impact than particulates emitted from diesel vehicles. In this work, we measured PM2.5 emissions from 20 LDGVs in Beijing, using an improved combined on-board emission measurement system. We compared these measurements with those reported in previous studies, and estimated the contribution of LDGVs to on-road PM2.5 emissions in Beijing. The results show that the PM2.5 emission factors for LDGVs, complying with European Emission Standards Euro-0 through Euro-4 were: 117.4 ± 142, 24.1 ± 20.4, 4.85 ± 7.86, 0.99 ± 1.32, 0.17 ± 0.15 mg/km, respectively. Our results show a significant decline in emissions with improving vehicle technology. However, this trend is not reflected in recent emission inventory studies. The daytime contributions of LDGVs to PM2.5 emissions on highways, arterials, residential roads, and within urban areas of Beijing were 44%, 62%, 57%, and 57%, respectively. The contribution of LDGVs to PM2.5 emissions varied both for different road types and for different times.