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The benefit of real‐world applicable indicators in resolving robust traffic‐related source contributions was investigated using tunnel measurement. PM2.5/CO was introduced as a metric to present evidence in non‐exhaust identification indirectly in terms of PM2.5 accumulation and dilution scenarios, and the rates (hourly variation of the difference between PM2.5 and PM2.5/CO) were 0.59−1.88 and −0.79 to −0.65, corresponding to peak and off‐peak hours, respectively. Real‐world PAHs indicators were examined, among which the exhaust indicators showed stable applicability from BghiP, and the non‐exhaust indication noted by BkF and DahA in peak hours were largely weakened in off‐peak hours, showing noticeable profile mixing between exhaust, brake and tyre wear. Source contributions were resolved by principal component analysis (PCA) with support of linear discriminant analysis (LDA) on inter‐group centroid diagnosis. The rate of vehicular non‐exhaust (brake and tyre wear) contribution lifted 10.3 times in peak hours compared with off‐peak hours, and its emission factor was noticeably enhanced 16 times, from 0.03 mg/(km·veh) to 0.48 mg/(km·veh). Guided by global vehicle electrification, the contribution of non‐exhaust in vehicular emissions were estimated to increase with larger ratio of emission factor between non‐exhaust and exhaust, and the growing market share of electric vehicles, under each mode of regenerative braking. The monetary impact of non‐exhaust caused by electric vehicles was calculated reaching the exhaust when electric vehicles increase to 50% in busy commuting megacities. The results provide applicable indicators for accurate source apportionment and support data for the refined control of non‐exhaust emission under rapid vehicle electrification. Plain Language Summary: Vehicle emitted non‐exhaust has garnered considerable global attention as source of heavy metals, microplastics and emerging pollutants. Real‐world applicable indicators were gained to characterize the benefits of robust and dynamic apportionment between exhaust and non‐exhaust emissions. This study estimated the contributions of non‐exhaust to total vehicle emissions for varying levels of emission factor ratios between non‐exhaust and exhaust and market share of electric vehicle. Key Points: PM2.5/CO can be used as a metric to present evidence of non‐exhaust identification indirectly in typical traffic environmentAccurate indicators were determined and applicability for recognizing exhaust and non‐exhaust was examined under heavy and low trafficFuture contribution of non‐exhaust to total vehicle emissions was predicted by emission factor ratios and electric vehicle percentages [ABSTRACT FROM AUTHOR]

With the implementation of strict emission regulations and the use of cleaner fuels, there has been a considerable reduction in exhaust emissions. However, the relative contribution of tire wear particles (TWPs) to particulate matters is expected to gradually increase. This study conducted laboratory wear experiments on tires equipped on domestically popular vehicle models, testing the factors and particle size distribution of TWPs. The results showed that the content of tire wear particle emission was mainly ultrafine particles, accounting for 94.80% of particles ranging from 6 nm to 10 μm. There were at least two concentration peaks for each test condition and sample, at 10~13 nm and 23~41 nm, respectively. The mass of TWP emission was mainly composed of fine particles and coarse particles, with concentration peaks at 0.5 μm and 1.3–2.5 μm, respectively. Both the number and mass of TWPs exhibited a bimodal distribution, with significant differences in emission intensity among different tire samples. However, there was a good exponential relationship between PM10 mass emissions from tire wear and tire camber angle. The orthogonal experimental results showed that the slip angle showed the greatest impact on TWP emission, followed by speed and load, with the smallest impact from inclination angle. [ABSTRACT FROM AUTHOR]

On-line chemical characterization of atmospheric particulate matter (PM) with soft ionization technique and ultrahigh-resolution Mass Spectrometry (UHRMS) provides molecular information of organic constituents in real time. Here we describe the development and application of an automatic measurement system that incorporates PM 2.5 sampling, thermal desorption, atmospheric pressure photoionization, and UHRMS analysis. Molecular formulas of detected organic compounds were deducted from the accurate (±10 ppm) molecular weights obtained at a mass resolution of 100,000, allowing the identification of small organic compounds in PM 2.5. Detection efficiencies of 28 standard compounds were determined and we found a high sensitivity and selectivity towards organic amines with limits of detection below 10 pg. As a proof of principle, PM 2.5 samples collected off-line in winter in the urban area of Beijing were analyzed using the Ionization Module and HRMS of the system. The automatic system was then applied to conduct on-line measurements during the summer time at a time resolution of 2 hr. The detected organic compounds comprised mainly CHON and CHN compounds below 350 m/z. Pronounced seasonal variations in elemental composition were observed with shorter carbon backbones and higher O/C ratios in summer than that in winter. This result is consistent with stronger photochemical reactions and thus a higher oxidation state of organics in summer. Diurnal variation in signal intensity of each formula provides crucial information to reveal its source and formation pathway. In summary, the automatic measurement system serves as an important tool for the on-line characterization and identification of organic species in PM 2.5. [ABSTRACT FROM AUTHOR]