Gaseous nitrous acid (HONO), playing a crucial role in the generation of hydroxyl (OH) radicals and thus secondary pollution, lacks a source. Vehicular emission is a significant HONO source and is usually estimated by a traditional estimation indicator (RHONO/NOx = 0.8 %). Nevertheless, with more direct measurements for vehicular HONO emissions, RHONO/NOx values have been reported to vary over a wide range. In this study, we conducted the driving tests with a chassis dynamometer for ten light-duty gasoline vehicles. HONO emission factors have realized a significant reduction with the updating of emission standards, with emission factors of 0.40 mg/km, 0.13 mg/km, and 0.06 mg/km for China IV, China V, and China VI vehicles, respectively. Besides precursors, water content and exhaust temperature were found to be possible decisive factors for initiating HONO generation. Furthermore, by coupling NOx emissions and combustion efficiency, we modified the estimation indicator for vehicular HONO emissions and a better estimation effect has been verified. Additionally, we established a dynamic inventory of vehicular HONO emissions in Jinniu District in Chengdu and further found the traditional estimation indicator would overestimate HONO emissions by around 17 %. Our findings would help to advance a deeper understanding of vehicular HONO emissions and the modified estimation indicator would be beneficial in minimizing the uncertainties of the HONO budget in the troposphere.

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.

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.