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This study aims to evaluate and quantify the environmental, health, and economic benefits due to the penetration of electric vehicles in the fleet composition by replacing conventional vehicles in an urban area. This study has been performed for the city of Turin, where road transport represents one of the main primary emission sources. Air pollution data were evaluated by ADMS-Roads, the flow traffic data used for simulation come from a real-time monitoring. Instead, statistics on mortality and hospitalizations due to cardiovascular and respiratory diseases were collected from the regional health information system and the National Health Institute and implemented in the BenMap software to evaluate the health and economic impacts. In both cases, two scenarios to evaluate the annual benefits of reducing PM, PM and NO were used: reduction to the levels gained by the assumptions of 2025 and 2030 Scenario and the PM, PM and NO concentrations were considered for evaluating short-term and long-term effects. The analysis performed doesn't include background pollution levels, i.e. the concentrations percentage reductions are only related to the local contribution, therefore derived from the contribution only of traffic source. The results show that fleet electrification has a potential benefit for concentrations reduction in comparison to the base Scenario, especially related to NO, less for PM and PM. Regarding 2025 Scenario (4 % (passenger car) and 5 % (light-duty vehicles) electric vehicles), reductions of 52 % of NO2, 35 % of PM10 and 49 % of PM2.5 are observed. Meanwhile, as regards 2030 Scenario reductions of 87 % of NO2, 36 % of PM10 and 50 % of PM2.5 are reached. Also, in terms of social costs a decrease of 47 % for the 2025 Scenario and 66 % for the 2030 Scenario in comparison to the base Scenario is arise.
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http://dx.doi.org/10.1016/j.jenvman.2021.113416 | DOI Listing |
Adv Sci (Weinh)
September 2025
School of Control Science and Engineering, Shandong University, Jinan, 250061, China.
Real-time and accurate temperature monitoring has been widely recognized in both academia and industry to ensure battery operation safety. Traditional techniques are generally limited to incomplete information caused by discrete sampling points. Hence, the spiral-serpentine distributed optical fiber sensor (DOFS) layout is presented to realize in-situ full-range temperature measurement.
View Article and Find Full Text PDFAdv Mater
September 2025
Center for High Pressure Science (CHiPS), State Key Laboratory of Metastable Materials Science and Technology, Yanshan University, Qinhuangdao, 066004, China.
Neuromorphic computing presents a promising solution for the von Neumann bottleneck, enabling energy-efficient and intelligent sensing platforms. Although 2D materials are ideal for bioinspired neuromorphic devices, achieving multifunctional synaptic operations with simple configurations and linear weight updates remains challenging. Inspired by biological axons, the in-plane anisotropy of 2D NbGeTe is exploited to develop dual electronic-optical synaptic devices.
View Article and Find Full Text PDFChem Soc Rev
September 2025
TUMint. Energy Research GmbH, Lichtenbergstr. 4, Garching 85747, Germany.
The current most mature, competitive, and dominant battery technology for electric vehicles (EVs) is the Li-ion battery (LIB). As future EVs will rely on battery technology, further innovation is essential for the success of mobility electrification towards improving the driving range and reducing the charging time and price competitiveness. The commonly cited next generation technologies are hybrid and solid-state batteries (SSBs) enabling high energy densities using lithium.
View Article and Find Full Text PDFSci Adv
September 2025
Beijing Key Laboratory of Micro-Nano Energy and Sensor, Center for High-Entropy Energy and Systems, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China.
Turbulence-induced vibrations pose substantial risks to aircraft structural integrity and flight stability, particularly in unmanned aerial vehicles (UAVs), where real-time impact monitoring and lightweight protection are critical. Here, we present a bioinspired twist-hyperbolic metamaterial (THM) integrated with a triboelectric nanogenerator (TENG) for simultaneously impact buffering and self-powered sensing. The THM-TENG protector exhibits tunable stiffness (40 to 4300 newtons per millimeter), ~70% impact energy absorption, and achieves a specific energy absorption of ~0.
View Article and Find Full Text PDFJ Acoust Soc Am
September 2025
The Marcus Wallenberg Laboratory for Sound and Vibration Research, Department of Engineering Mechanics, KTH Royal Institute of Technology, Teknikringen 8, 10044 Stockholm, Sweden.
This work presents a data-driven approach to estimating the sound absorption coefficient of an infinite porous slab using a neural network and a two-microphone measurement on a finite porous sample. A one-dimensional-convolutional network predicts the sound absorption coefficient from the complex-valued transfer function between the sound pressure measured at the two microphone positions. The network is trained and validated with numerical data generated by a boundary element model using the Delany-Bazley-Miki model, demonstrating accurate predictions for various numerical samples.
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