Vehicle exhaust emissions are a dominant feature of urban environments and are widely believed to have detrimental effects on plants. The effects of diesel exhaust emissions on 12 herbaceous species were studied with respect to growth, flower development, leaf senescence and leaf surface wax characteristics. A diesel generator was used to produce concentrations of nitrogen oxides (NO(x)) representative of urban conditions, in solardome chambers. Annual mean NO(x) concentrations ranged from 77 nl l(-l) to 98 nl l(-1), with NO:NO(2) ratios of 1.4-2.2, providing a good experimental simulation of polluted roadside environments. Pollutant exposure resulted in species-specific changes in growth and phenology, with a consistent trend for accelerated senescence and delayed flowering. Leaf surface characteristics were also affected; contact angle measurements indicated changes in surface wax structure following pollutant exposure. The study demonstrated clearly the potential for realistic levels of vehicle exhaust pollution to have direct adverse effects on urban vegetation.
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http://dx.doi.org/10.1016/j.envpol.2008.11.049 | DOI Listing |
Sci Rep
January 2025
Department of Biochemistry, College of Science, King Saud University, P.O.Box 2455, Riyadh, 11451, Saudi Arabia.
Nano-biochar considers a versatile and valuable sorbent to enhance plant productivity by improving soil environment and emerged as a novel solution for environmental remediation and sustainable agriculture in modern era. In this study, roles of foliar applied nanobiochar colloidal solution (NBS) on salt stressed tomato plants were investigated. For this purpose, NBS was applied (0%, 1% 3% and 5%) on two groups of plants (control 0 mM and salt stress 60 mM).
View Article and Find Full Text PDFJ Chromatogr A
January 2025
College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, PR China. Electronic address:
α-Terpineol and 1,8-cineole are two important compounds in essential oils. This study developed an efficient method to recover α-terpineol from model oil (MO) based on association extraction by in situ formations of deep eutectic solvent (DES) between α-terpineol and some quaternary ammonium salts (QASs) by hydrogen-bond (HB) interaction. Such interaction could be broken almost completely by the introduction of water, due to the stronger HB interaction between water and QASs, which could release α-terpineol by liquid-liquid separation and save the organic solvents consumption.
View Article and Find Full Text PDFPlants (Basel)
January 2025
Key Laboratory of Mountain Hazards and Earth Surface Processes, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China.
Climate change has led to an increasing frequency of droughts, potentially undermining soil stability. In such a changing environment, the shallow reinforcement effect of plant roots often fails to meet expectations. This study aims to explore whether this is associated with the alteration of plant traits as a response to environmental change.
View Article and Find Full Text PDFPolymers (Basel)
January 2025
Department of Cosmetic and Biomaterials Chemistry, Faculty of Chemistry, Nicolaus Copernicus University in Toruń, Gagarina 7, 87-100 Toruń, Poland.
As the demand for sustainable and innovative solutions in food packaging continues to grow, this study endeavors to introduce a comprehensive exploration of novel active materials. Specifically, we focus on characterizing polylactide-poly(ethylene glycol) (PLA/PEG) films filled with olive leaf extract (OLE; ) obtained via solvent evaporation. Examined properties include surface structure, thermal degradation and mechanical attributes, as well as antibacterial activity.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Environmental Remote Sensing and Geoinformatics, Trier University, Universitätsring 15, 54296 Trier, Germany.
Assessing vines' vigour is essential for vineyard management and automatization of viticulture machines, including shaking adjustments of berry harvesters during grape harvest or leaf pruning applications. To address these problems, based on a standardized growth class assessment, labeled ground truth data of precisely located grapevines were predicted with specifically selected Machine Learning (ML) classifiers (Random Forest Classifier (RFC), Support Vector Machines (SVM)), utilizing multispectral UAV (Unmanned Aerial Vehicle) sensor data. The input features for ML model training comprise spectral, structural, and texture feature types generated from multispectral orthomosaics (spectral features), Digital Terrain and Surface Models (DTM/DSM- structural features), and Gray-Level Co-occurrence Matrix (GLCM) calculations (texture features).
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