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The objective of this study was to investigate the effects of natural fermentation and inoculated fermentations with Pichia pastoris and active dry wine yeast BV818 (Saccharomyces cerevisiae) on the flavor of yellow peach wine. Simultaneous inoculation, sequential inoculation of P. pastoris and BV818 with a time interval of one and three days, and inoculation of BV818 alone were used. Gas chromatography-mass spectrometry (GC-MS), gas chromatography-ion mobility spectrometry (GC-IMS) and quantitative descriptive sensory analysis were used to study the effects of different fermentation methods on volatile flavor substances in yellow peach wine. The results showed that for all groups, ethanol fermentation was completed within 15 days, and 31 and 22 compounds were detected by GC-MS and GC-IMS, respectively. In the sequential fermentation groups, the content of alcohols increased, the contents of acids and esters decreased, and the numbers of terpenes, alcohols and acids increased. In the sensory evaluation, the sequential fermentation groups had higher aroma richness and aroma balance than the other groups. The simultaneous fermentation group scored higher in sensory score for nutty and sweet aroma. The naturally fermented wine had the strongest sour aroma. In summary, mixed fermentation with P. pastoris and S. cerevisiae can improve the aroma of yellow peach wine, and the sensory score of the wine produced by sequential inoculation with a three-day interval was highest.

The fuel consumption and greenhouse gas (GHG) emission patterns of taxis are in accordance with the urban structure and daily travel footprints of residents. With taxi trajectory data from the intelligent transportation system in Xi'an, China, this study excludes trajectories from electric taxis to accurately estimate GHG emissions of taxis. A gradient boosting decision tree (GBDT) model is employed to examine the nonlinear influence of the built environment (BE) on the GHG emissions of taxis on weekdays and weekends in various urban areas. The research findings indicate that the GHG emissions of taxis within the research area exhibit peak levels during the time intervals of 7:00–9:00, 12:00–14:00, and 23:00–0:00, with notably higher emission factors on weekends than on weekdays. Moreover, a clear nonlinear association exists between BE elements and GHG emissions, with a distinct impact threshold. In the different urban areas, the factors that influence emissions exhibit spatial and temporal heterogeneity. Metro/bus/taxi stops density, residential density, and road network density are the most influential BE elements impacting GHG emissions. Road network density has both positive and negative influences on the GHG emissions in various urban areas. Increasing the road network density in subcentral urban areas and increasing the mixed degree of urban functions in newly developed urban centers to 1.85 or higher can help reduce GHG emissions. These findings provide valuable insights for reducing emissions in urban transportation and promoting sustainable urban development by adjusting urban functional areas. [ABSTRACT FROM AUTHOR]

Existing studies have limited evidence about the complex nonlinear impact mechanism of road network topology and built environment on bike-sharing systems' greenhouse gas (GHG) emission reduction benefits. To fill this gap, we examine the nonlinear effects of road network topological attributes and built environment elements on the potential GHG emission reduction of dockless bike-sharing (DBS) trips in Shenzhen, China. Various methods are employed in the research framework of this study, including a GHG emission reduction estimation model, spatial design network analysis (sDNA), gradient boosting decision tree (GBDT), and partial dependence plots (PDPs). Results show that road network topological variables have the leading role in determining the potential GHG emission reduction of DBS trips, followed by land use variables and transit-related variables. Moreover, the nonlinear impacts of road network topological variables and built environment variables show certain threshold intervals for the potential GHG emission reduction of DBS trips. Furthermore, the impact of built environment on the potential GHG emission reduction of DBS trips is moderated by road network topological indicators (closeness and betweenness). Compared with betweenness, closeness has a greater moderating effect on built environment variables. These findings provide empirical evidence for guiding bike-sharing system planning, bike-sharing rebalancing strategy optimization, and low-carbon travel policy formulation. [ABSTRACT FROM AUTHOR]