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Mobile sources are the primary contributor of volatile organic compounds (VOCs) emissions from anthropogenic sources in the Beijing-Tianjin-Hebei Region. Establishing a detailed VOCs emission inventory and clarifying the ozone generation potential (OFP) and their active species is conducive to scientific control of mobile source pollution. Based on the activity level data of mobile sources in the Beijing-Tianjin-Hebei Region, combined with the emission factor method and related research on source profiles, an emission inventory of VOCs from mobile sources was established to identify the emission contribution of key sources and components. Additionally, the ozone generation potential of VOCs was estimated using the maximum incremental reactivity (MIR). The results indicated that total VOCs emissions from mobile sources in the Beijing-Tianjin-Hebei Region in 2021 was 214.6 kt, with 28.5 kt from Beijing, 28.1 kt from Tianjin, and 158.0 kt from Hebei Province. The VOCs emissions from mobile sources in the Beijing-Tianjin-Hebei Region were dominated by on-road mobile sources, with a proportion of 93.15%, of which gasoline motor vehicles contributed 72.70% to the emissions. Among non-road mobile sources, construction machinery and agricultural machinery had notable annual VOCs emissions, accounting for 2.01% and 1.99%, respectively. Aromatics, alkanes, and alkenes were the components with the highest VOCs emissions from mobile sources in the region, while alkenes, aromatics, and OVOCs had the highest contributions to OFP, accounting for 91.96%. Ethylene, propylene, toluene, formaldehyde, 1,2,3-trimethylbenzene, 1-butene, acetaldehyde, 1,3-butadiene, isopentane, and propionaldehyde were the major reactive species of OFP in the Beijing-Tianjin-Hebei Region, contributing 69.49% to the total OFP. The top contributing sources of VOCs emissions and OFP in Beijing, Tianjin, and Hebei provinces were all gasoline motor vehicles, in addition to motorcycles, diesel motor vehicles, and civil aviation aircraft in Beijing; construction machinery and ships in Tianjin; and diesel motor vehicles and agricultural machinery in Hebei Province, which also contributed relatively high local VOCs emissions and OFP.
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http://dx.doi.org/10.13227/j.hjkx.202406242 | DOI Listing |
Light Sci Appl
September 2025
State Key Laboratory of Flexible Electronics, Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications (NUPT), Nanjing, 210023, China.
As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components.
View Article and Find Full Text PDFJ Med Internet Res
September 2025
Department of Community Medicine, Faculty of Health, UiT The Arctic University of Norway, Tromsø, Norway.
Background: The ability to access and evaluate online health information is essential for young adults to manage their physical and mental well-being. With the growing integration of the internet, mobile technology, and social media, young adults (aged 18-30 years) are increasingly turning to digital platforms for health-related content. Despite this trend, there remains a lack of systematic insights into their specific behaviors, preferences, and needs when seeking health information online.
View Article and Find Full Text PDFBackground: The growing approval and use of digital therapeutics (DTx) for managing chronic diseases, such as diabetes, has prompted questions about their effectiveness.
Objective: This systematic review and meta-analysis aimed to report the effectiveness of DTx interventions in the management of patients with type 1 diabetes, type 2 diabetes, and prediabetes.
Methods: Data sources, including Web of Science, MEDLINE, Embase, and the Cochrane Library, were searched from inception to July 30, 2023.
JMIR Res Protoc
September 2025
Center for Alcohol & Addiction Studies, School of Public Health, Brown University, Providence, RI, United States.
Background: Digital media frequently contains positive portrayals of alcohol content, which has been shown to be associated with alcohol-related cognitions and behaviors. Because youth are heavy media consumers and have access to unsupervised, repeat viewing of media content on their personal mobile devices, it is critical to understand the frequency of encountering alcohol content in adolescents' daily lives and how adolescents engage with the content.
Objective: This paper outlines the study protocol for examining adolescents' exposure to alcohol-related content in digital media within their natural environments.
Nutr Health
September 2025
Independent researcher, Rome, Italy.
Artificial intelligence (AI) is increasingly applied in nutrition science to support clinical decision-making, prevent diet-related diseases such as obesity and type 2 diabetes, and improve nutrition care in both preventive and therapeutic settings. By analyzing diverse datasets, AI systems can support highly individualized nutritional guidance. We focus on machine learning applications and image recognition tools for dietary assessment and meal planning, highlighting their potential to enhance patient engagement and adherence through mobile apps and real-time feedback.
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