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In the present work, volatile organic compounds (VOCs) from vehicle exhaust and cooking fumes were investigated via simulation experiments, which covered engine emissions produced during gasoline direct injection (GDI) using two kinds of fuels and cooking emissions produced by preparing three domestic dishes. The distinct characteristics of VOCs emitted during the two processes were identified. Alkanes (73% mass fraction on average) and aromatics (15% on average) dominated the vehicle VOCs, while oxygenated VOCs (49%) and alkanes (29%) dominated the cooking VOCs. Isopentane (22%) was the most abundant species among the vehicle VOCs. N-hexanal (20%) dominated the cooking VOCs. The n-hexanal-to-n-pentanal ratio (3.68 ± 0.64) was utilized to identify cooking VOCs in ambient air. The ozone formation potential produced by cooking VOCs was from 1.39 to 1.93 times higher than that produced by vehicle VOCs, which indicates the significant potential contribution of cooking VOCs to atmospheric ozone. With the equivalent photochemical age increasing from 0 h to 72 h, the secondary organic aerosol formation by vehicle VOCs was from 3% to 38% higher than that of cooking VOCs. Controlling cooking emissions can reduce SOA pollution in a short time due to its higher SOA formation rate than that of vehicle VOCs within the first 30 h. However, after 30 h of oxidation, the amount of SOAs formed by vehicle exhaust emissions exceeded the amount of SOAs produced by cooking activities, implying that reducing vehicle emissions will benefit particle pollution for a longer time. Our results highlight the importance of VOCs produced by cooking fumes, which has not been given much attention before. Further, our study suggested that more research on semi-volatile organic compounds produced by cooking emissions should be conducted in the future.

Scenario identification plays an important role in assisting unmanned aerial vehicle (UAV) cognitive communications. Based on the scenario-dependent channel characteristics, a support vector machine (SVM)-based air-to-ground (A2G) scenario identification model is proposed. In the proposed model, the height of the UAV is also used as a feature to improve the identification accuracy. On the basis, an improved scenario identification method is developed including dataset acquisition, identification model training, and height-integrated model feedback. The shooting and bouncing ray/image (SBR/IM) method is used to obtain the datasets of channel characteristics, i.e., root-mean-square delay spread (RMS-DS), K factor, and angle spread (AS) under five typical scenarios: over-sea, suburban, urban, dense urban and high-rise urban. SBR/IM is a symmetry-based ray tracing (RT) simulation method. After the identification model is trained, a height-integrated feedback scheme is used to increase the identification performance. The simulation results show that the identification accuracy of improved method is about 14% higher than the method without height feature, which reaches nearly 100% under the over-sea and suburban and over 80% in urban, dense urban, and high-rise urban.

Rational design LDHs (layered double hydroxides) with 3D hierarchical hollow structures have generated widespread interest for catalytic oxidation due to the high complexity in shell architecture and composition. Herein, we reported a handy two-step method to construct a 3D hierarchical NiCo2O4/NiO nanocage. This synthetic strategy contains a partial in situ transformation of ZIF-67 (zeolitic imidazolate framework-67) into Co-NiLDH yolk-shelled structures following ethanol etching, and a structure-preserved transformation from Co-NiLDH@ZIF-67 to a biphase nanocage following calcination. CoNi-yh-T (varied reaction time and calcination temperature) nanocages were investigated systematically by Brunauer–Emmett–Teller (BET), X-ray photoelectron spectroscopy (XPS), H2- temperature-programmed reduction (TPR), NH3-temperature-programmed desorption (TPD) and studied for toluene oxidation. The CoNi-6h-350 sample showed much higher activity with 90% toluene conversion (T90) at 229 °C at a high space velocity (SV = 60,000 mL g−1 h−1) than other catalysts (T90 >240 °C). Abundant surface high valence Co ions caused by the novel hierarchical nanostructures, together with adsorbed oxygen species and abundant medium-strength surface acid sites, played a key role for catalytic activities.

CuO-CeO2 nanocatalysts with varying CuO contents (1, 5, 9, 14 and 17 wt %) were prepared by one-step flame spray pyrolysis (FSP) and applied to CO oxidation. The influences of CuO content on the as-prepared catalysts were systematically characterized by X-ray diffraction (XRD), N2 adsorption-desorption at −196 °C, field emission scanning electron microscopy (FESEM), high-resolution transmission electron microscopy (HRTEM), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and hydrogen-temperature programmed reduction (H2-TPR). A superior CO oxidation activity was observed for the 14 wt % CuO-CeO2 catalyst, with 90% CO conversion at 98 °C at space velocity (60,000 mL × g−1 × h−1), which was attributed to abundant surface defects (lattice distortion, Ce3+, and oxygen vacancies) and high reducibility supported by strong synergistic interaction. In addition, the catalyst also displayed excellent stability and resistance to water vapor. Significantly, in situ diffuse reflectance infrared Fourier transform spectroscopy (in situ DRIFTS) showed that in the CO catalytic oxidation process, the strong synergistic interaction led readily to dehydroxylation and CO adsorption on Cu+ at low temperature. Furthermore, in the feed of water vapor, although there was an adverse effect on the access of CO adsorption, there was also a positive effect on the formation of fewer carbon intermediates. All these results showed the potential of highly active and water vapor-resistive CuO-CeO2 catalysts prepared by FSP.